Stress Ecology

Stress Ecology

Christian E.W. Steinberg

Stress Ecology Environmental Stress as Ecological Driving Force and Key Player in Evolution

Christian E.W. Steinberg Department of Biology Laboratory of Freshwater and Stress Ecology Humboldt-Universität zu Berlin Späthstraße 80/81 12437 Berlin Germany [email protected]

ISBN 978-94-007-2071-8 e-ISBN 978-94-007-2072-5 DOI 10.1007/978-94-007-2072-5 Springer Dordrecht Heidelberg London New York Library of Congress Control Number: 2011936021 © Springer Science+Business Media B.V. 2012 No part of this work may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, microfilming, recording or otherwise, without written permission from the Publisher, with the exception of any material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)

Preface

I dedicate this book to our “crazy” animals who voluntarily migrate into chemically stressful environments and spend energy to overcome this situation. Yet, they even benefit from this stress and thereby teach us that several stress paradigms are outdated and must be re-considered. In my classes on “Stress Ecology” in Berlin (Germany), Wuhan and Kunming (China), and Rio de Janeiro (Brazil), I probably stressed many young scientists and, nevertheless, hope that this stress was as positive to them as the stress to our “crazy” animals was. Finally, I gratefully acknowledge the help, stimulation, discussion, and inspiration of so many friends, colleagues, and students: Ralph and Steffi Menzel, Nadine Saul, Kerstin Pietsch, Yvonne Pörs, Hanno Bährs, Rihab Bouchnak, Ramona Rauch, Ramona Henkel, Sylva Hofmann, Nadia Ouerghemmi, Steffen Hermann, Laura Vinćentić, Shumon Chakrabarti, Antonia Engert, Sandra Euent, Maxim Timofeyev, Darya Bedulina, Marina Protopopova, Elena Sapozhnikova, Zhanna Shatilina, Vassily Pavlichenko, Albert Suhett, and, last but not least, Stephen Stürzenbaum. Furthermore, I particularly thank Dawn M. Allenbach, University of New Orleans, for carefully checking the manuscript and commenting on many parts of it. Her work and thoughts have substantially improved the quality of several chapters of the book. Even to a book, space limitation applies. Due to this circumstance, I would like to apologize in advance to all individuals whose research was not cited or whose papers have not been discussed in full but whose work has certainly advanced the understanding of this complex field of research and education. Many thanks are due to the staff of Springer, Dordrecht, The Netherlands, particularly Paul Roos, Suzanne Mekking, and Martine van Bezooijen, for their understanding and their continuous help in preparing my book.

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Contents

  1 Why a Small Worm Is Not Crazy...........................................................

1

  2 Activation of Oxygen: Multipurpose Tool............................................. 2.1 Oxygen Activation in Ecosystems..................................................... 2.1.1 Effects on Organisms............................................................. 2.2 Activation of Oxygen in Organisms.................................................. 2.2.1 Using “Stolen” Structures...................................................... 2.2.2 Using Own Structures............................................................ 2.3 Oxidative Stress................................................................................. 2.3.1 Key Studies of Oxidative Stress............................................

7 7 9 10 10 12 31 32

  3 Defense Means Against Pathogens and Parasites: Reactive Oxygen Species......................................................................... 3.1 Defense in Plants............................................................................... 3.1.1 Spermatophytes..................................................................... 3.1.2 Macroalgae............................................................................ 3.1.3 Pathogens Modulate Community Structure........................... 3.2 Defense Response in Animals........................................................... 3.2.1 Phagocytes............................................................................. 3.2.2 Prophenoloxidase in Invertebrates.........................................

47 47 47 49 51 52 52 53

  4 Arms Race Between Plants and Animals: Biotransformation System....................................................................... 4.1 Major Arms of the Plants.................................................................. 4.1.1 Furanocoumarins................................................................... 4.1.2 Terpenoids............................................................................. 4.1.3 Flavonoids – Protectants Against Abiotic or Biotic Stress?..................................................................... 4.2 The Biotransformation System.......................................................... 4.2.1 Plants Outcompete Archaea, Bacteria, Fungi, and Animals in Terms of CYP Gene Numbers...................... 4.3 Phase I: Functionalization................................................................. 4.3.1 Cytochrome P450 (CYP) Enzymes.......................................

61 62 62 62 64 67 71 73 73 vii

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4.4 Phase II: Conjugation........................................................................ 4.4.1 Glutathione Transferases....................................................... 4.4.2 Glycosyltransferases.............................................................. 4.4.3 Sulfotransferases.................................................................... 4.4.4 Esterase and Hydrolase.......................................................... 4.5 Armament of Animals I: Biotransformation Phases I and II............. 4.5.1 Insects.................................................................................... 4.6 Armament of Animals II: Exporters (Phase 0 and III)...................... 4.6.1 Chemosensitization................................................................ 4.6.2 Multixenobiotic Transporters as Defense Against Dietary Allelochemicals........................................... 4.7 Body-Maintenance vs. Xenobiotic Biotransformation...................... 4.8 Ecological Significance of Individual Biotransformation Components......................................................... 4.8.1 Natural and Synthetic Xenobiotics........................................ 4.8.2 Herbivores Use Plants’ Armaments in Defense Against Their Own Enemies............................... 4.8.3 How to Survive the Contamination of Superfund Sites?......... 4.8.4 Self-intoxification by CYP Activity in Caenorhabditis elegans...................................................... 4.9 Biotransformation and the Evolution of Pesticide Resistances......... 4.9.1 CYPs and Herbicide Resistance............................................ 4.9.2 GSTs and Herbicide Resistance............................................ 4.9.3 CYPs and Insecticide Resistance........................................... 4.9.4 Esterases and Hydrolases and Insecticide Resistance........... 4.9.5 GSTs and Insecticide Resistance...........................................

101 102 102 103 103 104 105

  5 Heat Shock Proteins: The Minimal, but Universal, Stress Proteome ....................................................................................... 5.1 Bacteria.............................................................................................. 5.1.1 Escherichia coli...................................................................... 5.2 Plants................................................................................................. 5.2.1 Salinity and Elevated CO2 Concentrations............................ 5.2.2 Induced Thermotolerance in Tomato..................................... 5.3 Animals.............................................................................................. 5.3.1 Abiotic Stressors.................................................................... 5.3.2 Biotic Stressors...................................................................... 5.4 Costs of HSP Expression................................................................... 5.5 Some Need It Cold............................................................................

107 111 111 111 111 113 114 114 120 125 127

  6 Heavy Metals: Defense and Ecological Utilization............................... 6.1 General Strategies.............................................................................. 6.2 The Metallothionein System.............................................................. 6.3 How Do Worms Cope with High Metal Burdens?............................ 6.4 Heavy-Metal Tolerance and Genetic Adaptation in Animals............ 6.4.1 Springtail Orchesella cincta: Model of Cadmium Tolerance in Animals............................

75 75 77 78 79 79 80 89 90 92 92 94 94 96 99

131 132 132 134 137 139

Contents

6.5 Hyperaccumulating Plants: Surviving in Adverse Environments.................................................................. 6.5.1 Why Do Closely Related Plant Species Posses Contrasting Tolerance to Heavy Metals?................... 6.5.2 Ecological Mode of Action of Metal Defenses..................... 6.5.3 Cross Talk Between Metal and Biotic Stress Signaling......... 6.5.4 Long-Term Strategy of Hyperaccumulators.......................... 6.5.5 Costs of Metal Resistance and Adaptation............................

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140 148 151 152 154 155

  7 The Potential of Stress Response: Ecological Transcriptomics .......... 7.1 Archaea.............................................................................................. 7.2 Bacteria.............................................................................................. 7.2.1 Escherichia coli...................................................................... 7.2.2 Shewanella oneidensis........................................................... 7.3 Plants................................................................................................. 7.3.1 General and Specific Responses to Abiotic Stress................ 7.3.2 Climate Change..................................................................... 7.3.3 Towards a Regulon................................................................ 7.3.4 Plant-Pathogen Interactions................................................... 7.3.5 Plant-Herbivore Interactions.................................................. 7.3.6 Response to Selected Anthropogenic Stressors..................... 7.4 Stress-Related Gene Expression Profiles in Animals........................ 7.4.1 Response Patterns.................................................................. 7.4.2 Establishing the Defensome.................................................. 7.4.3 Natural Abiotic Stressors....................................................... 7.4.4 Natural Biotic Stressors......................................................... 7.4.5 Selected Anthropogenic Stressors......................................... 7.5 Stress-Related Gene Expression Profiles in Fish............................... 7.5.1 Abiotic Stressors.................................................................... 7.5.2 Biotic Stressors...................................................................... 7.6 Linkages Between Gene Expression and Higher Biological Levels............................................................ 7.7 Population Genetics........................................................................... 7.7.1 Metapopulation of the Butterfly Melitaea cinxia................... 7.7.2 The Estuarine Killifish Fundulus heteroclitus.......................

161 164 165 166 166 167 167 170 171 174 174 180 181 181 183 185 186 187 196 196 203

  8 Not All Is in the Genes............................................................................. 8.1 No Junk: MicroRNAs........................................................................ 8.1.1 miRNAs Regulate Plant Responses to Environmental Stresses...................................................... 8.1.2 miRNAs Regulate Animal Responses to Environmental Stresses...................................................... 8.2 Environmental Stress, Transgenerational Inheritance, and Epigenetics.............................................................. 8.2.1 Transgenerational Effects...................................................... 8.2.2 Epigenetic Effects.................................................................. 8.2.3 Environment and Epigenetic Mechanisms............................

213 213

206 208 208 210

214 218 219 219 224 230

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  9 The Actual Response: Ecological Proteomics and Metabolomics ...................................................................................   9.1 Basics of Proteomics and Metabolomics........................................   9.2 Minimal Stress Response................................................................   9.3 Key Studies of Ecological Proteomics and Metabolomics..............   9.3.1 Archaea and Oxidative Stress............................................   9.3.2 Bacteria and Salt................................................................   9.3.3 Fungi..................................................................................   9.3.4 Plants..................................................................................   9.3.5 Animals: Fish.....................................................................   9.3.6 Animals: Arthropods.........................................................   9.3.7 Animals: Worms................................................................   9.4 Metaproteomics: Microbial Communities......................................

241 241 242 248 249 249 250 250 261 269 275 276

10 Whatever Doesn’t Kill You Might Make You Stronger: Hormesis ......................................................................... 10.1 History............................................................................................. 10.2 Examples......................................................................................... 10.3 How Variable Are Stress Responses?.............................................. 10.4 Sustainability of Hormetic Responses............................................. 10.5 Hormesis in Mixtures...................................................................... 10.6 Underlying Mechanisms.................................................................

279 279 280 283 285 287 287

11 Multiple Stressors as Environmental Realism: Synergism or Antagonism....................................................................... 11.1 Additive/Synergistic Effects............................................................ 11.1.1 Seegrass: Heat Stress and Drift Algae............................... 11.1.2 Amphibians: Environmental Stress and Predators............. 11.1.3 Amphibians: Environmental Stress and Intraspecific Competition............................................ 11.1.4 Combinations with Toxicants Introduced by Man............. 11.2 Mixed Effects.................................................................................. 11.3 Antagonistic Effects........................................................................ 11.3.1 Food Stress and Natural Xenobiotics................................ 11.3.2 Predation Threat and Parasites........................................... 11.3.3 Non-pathogenic Bacteria and Systemic Resistance in Plants...........................................................

308

12 One Stressor Prepares for the Next One to Come: Cross-Tolerance ...................................................................... 12.1 Cross-Tolerance in Microorganisms................................................ 12.1.1 Escherichia coli.................................................................. 12.1.2 The Marine Vibrio Parahaemolyticus................................ 12.2 Free-Living Yeasts...........................................................................

311 313 313 314 315

295 301 301 302 302 303 306 307 307 308

Contents

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12.3 Examples of Cross-Tolerance in Plants........................................... 12.3.1 UV-Stress and Resistance Against Pathogens................... 12.3.2 Heavy Metal Stress and Resistance Against Pathogens and Parasites........................................ 12.4 Examples of Cross-Tolerance in Animals....................................... 12.4.1 Anhydrobiosis.................................................................... 12.4.2 Swordtails, Xiphophorus Helleri....................................... 12.4.3 Aquatic Invertebrates.........................................................

315 315 318 319 319 322 323

13 Longevity: Risky Shift in Population Structure? . ............................... 13.1 Plants............................................................................................... 13.2 Animals........................................................................................... 13.2.1 Regulation of Lifespan Extension in Animals................... 13.2.2 Which Genders and Life Traits Are Affected?.................. 13.2.3 Which Life Phase Is Expanded?........................................

327 327 329 331 335 337

14 Footprints of Stress in Communities . ................................................... 14.1 Fluctuating Asymmetry................................................................... 14.2 Quality Indices with Emphasis on Freshwaters.............................. 14.2.1 Indices for Saproby, Eutrophication, and Further Impacts........................................................... 14.2.2 Feeding Types.................................................................... 14.3 Maintenance Strategies with Emphasis on Free-Living Nematodes.............................................................. 14.4 Species at Risk Indices, SPEAR..................................................... 14.5 Biomass Spectra.............................................................................. 14.5.1 Food Web Structure........................................................... 14.5.2 Invasive Species................................................................. 14.5.3 Chemical Constraints.........................................................

345 345 350

353 354 356 359 359 360

15 Environmental Stresses: Ecological Driving Force and Key Player in Evolution ......................................... 15.1 Ecological Driving Force................................................................ 15.2 Trigger of Microevolution and Evolution........................................ 15.2.1 Microevolution................................................................... 15.2.2 Evolution............................................................................ 15.2.3 Role of Epigenetics............................................................ 15.2.4 The TATA Box and Evolution........................................... 15.2.5 Sex as Stress Response......................................................

369 369 373 373 376 381 383 385

Appendices........................................................................................................ Appendix 1: Cytochrome P450 Enzyme Families..................................... Appendix 2: Classification of Glutathione Transferases............................ Cytosolic GSTs................................................................................

387 387 387 387

350 351

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Appendix 3: Transporters........................................................................... The P-gp (ABCB) Family............................................................... The MRP (ABCC) Family.............................................................. The MXR (ABCG) Family, Also Called White-Brown Complex Homologs (WBCs).................................... Transporter Proteins in Plants.........................................................

393 393 394 394 395

Abbreviations and Glossary............................................................................ 401 References......................................................................................................... 407 Index.................................................................................................................. 461

Chapter 1

Why a Small Worm Is Not Crazy

Usually, stress is considered adverse: too much work load, or, conversely, ­unemployment; lack of success; unsolved family problems, etc. More scientifically, Selye (1936) discovered in his fundamental study by challenging rats that “if the organism is severely damaged by acute non-specific nocuous agents such as exposure to cold, surgical injury, production of spinal shock (transcision of the cord), excessive muscular exercise, or intoxications with sublethal doses of diverse drugs (adrenaline, atropine, morphine, formaldehyde, etc.), a typical syndrome appears, the symptoms of which are independent of the nature of the damaging agent or the pharmacological type of the drug employed, and represent rather a response to damage as such”. In ecological terms, stress may therefore be defined as any internal state in an organism resulting from placing it outside its fundamental ecological niche, whereby the niche may be defined in terms of gene expression profiles under normal or ideal operating conditions (van Straalen 2003). Selye (1936) showed that a stress response includes three different phases: the bipartite alarm phase, the resistance phase, and the exhaustion phase (Fig. 1.1). The alarm phase corresponds to modifications of biochemical and genetic parameters in the absence of reduced vital activities and growth. These physiological reactions terminate a primary disturbance and enable restitution. An exposure that is too strong or fast will result in acute damage and cell death. The resistance phase is characterized by the activation of defense mechanisms (e.g., antioxidant defense, protein repair, biotransformation) that are concomitant with first signs of reduced vital activity and growth. The exhaustion phase becomes apparent by a collapse of vital cellular functions (e.g. photosynthesis, membrane integrity, reproduction), leading to chronic damage and ultimately to death. This model implies that stress is something that happens to organisms, something that is fate and cannot be avoided (if the organisms cannot escape the situation), something that must be tolerated instead. But what about organisms that actively look for stressful environments, migrate into them, and suffer from symptoms of stress such as loss of energy, activation of oxygen, induction of stress genes, etc.? Organisms C.E.W. Steinberg, Stress Ecology: Environmental Stress as Ecological Driving Force and Key Player in Evolution, DOI 10.1007/978-94-007-2072-5_1, © Springer Science+Business Media B.V. 2012

1

2

1  Why a Small Worm Is Not Crazy Permanent stress

Di

Exhaustion phase Maximum resistance

Adjustment

Normal range

Adaptation

ba e

au

nc

h Ex

r stu

Re sti tu tio n

Eustress

Distress

Resistance phase Ha rd en ing

Alarm phase

sti on

Acute damage, death

Stress phase genes

Minimum resistance

Chronic damage Induction Repression

Fig. 1.1  The classical stress phase model based on Selye (1936) and amended by several authors. Shades of grey of arrows represent different genes specifically expressed during the individual stress phases (From Steinberg et al. 2008a, with permission from Elsevier)

d­ emonstrating this seemingly crazy behavior do exist. For countless generations, the ­nematode Caenorhabditis elegans has been cultured in solutions or on agar plates completely free of humic substances, a biogeochemical matrix of soils and aquatic systems. These substances recently have been demonstrated to cause many stress defense reactions, such as oxygen activation and eventually lipid peroxidation, expression of stress proteins, and modulation of biotransformation enzymes. Many of these responses are transcriptionally controlled and require a great deal of energy (Steinberg et al. 2008b). In a simple laboratory test, C. elegans was offered the choice to stay in humic-free environments or to migrate to humic-rich environments (Fig.  1.2). The individuals were allowed to feed on bacteria either with or without concomitant humic substances. The majority of the animals decided to feed on bacteria with humic substances present – despite the aforementioned far-reaching consequences. The nematodes were able to sense the presence of humic substances, because several olfactory and chemosensory genes were induced (Menzel et al. 2005a). The nematode C. elegans may appear to be a rather peculiar organism that is an “exception to the rule” that species prefer a stress-free environment. Yet, a look into recent literature shows that it is by no means an isolated case. For instance, the bacterium Herminiimonas arsenicoxydans behaves as strangely as the worm. It is a species of ultramicrobacteria and was first been reported in 2006 as an isolate of industrial sludge. Aside from multiple biochemical processes such as arsenic oxidation, reduction, and efflux, H. arsenicoxydans – most astonishingly – also exhibits positive chemotaxis and motility towards arsenic (Muller et al. 2007), a metalloid, which is commonly classified as “toxic” and “dangerous for the environment”. Yet, Fig.  1.3 shows increased swimming rings with increasing arsenic and ferric iron concentration. No such effect occurred with other toxic elements tested, such as cobalt.

1  Why a Small Worm Is Not Crazy

3

Fig. 1.2  Caenorhabditis elegans attraction test with humic substances (Modified and redrawn from Menzel et al. 2005a)

Fig. 1.3  Effect of metal and metalloid concentration on swimming properties in Herminiimonas arsenicoxydans. Motility assays were performed in the presence of an increasing concentration of As[III], Co[II], or Fe[III]. The level of motility of wild-type strain (ULPAs) and of its aoxAB knockout derivative was evaluated as the diameter of the swimming ring expressed in millimeters (From Muller et al. 2007; courtesy of Public Library of Science). The knockout mutants do not significantly respond to As[III] exposure

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1  Why a Small Worm Is Not Crazy

The hypothesis that arsenic contributes to the metabolism of H. ­arsenicoxydans was further supported by its positive chemotactic response toward arsenic, ­demonstrating that the bacterium is able to sense and respond to the presence of arsenic in the medium. Muller et  al. (2007) concluded that the genome of H. arsenicoxydans contains 12 methyl-accepting chemotaxis protein–encoding genes. As most of these genes have no predicted function, it is tempting to speculate that at least one of them plays a role in this mechanism. Why do both the worm and bacteria behave so strangely? Surely, according to current (eco)-toxicological paradigms, they must be crazy or masochistic. However, the worm and bacteria do not know these paradigms and demonstrate that our knowledge must be incomplete. In fact, several consecutive and detailed studies with C. elegans revealed that the worm is by no means crazy, but rather smart, because they increase their number of offspring under the stressful conditions (Höss et al. 2001) and prolong their individual lifespans (Steinberg et al. 2007) – provided that the exposed humic material had certain qualities and the overall chemical stress remained in the mild range. The presence of natural endogenous and exogenous chemical stressors have been instrumental for, and in fact have driven, the development of various stress defense systems. In addition, anthropogenic chemical stressors, though sometimes severe or even lethal, also can impact organismal stress defense systems. The example of H. arsenicoxydans demonstrates the existence of a strategy to efficiently colonize seemingly hostile environments and may have played a crucial role in the occupation of ancient ecological niches on Earth (Muller et al. 2007). The purpose of this book is to elucidate the background, basic mechanisms, and benefits of various stress defense mechanisms. In the beginning, its structure follows the signaling pathway of stresses in organisms, then covers the potential and actual stress responses, shows beneficial effects on the individual level which include modulation of life traits and development of stress resistances, discusses shifts in population structures, and tries to find footprints of stress in communities. In particular, the book is comprised of several topics: Activation of oxygen: multipurpose tool: To most biomolecules, elemental oxygen is inert. Under energy consumption, it has to be activated. If it is activated, it is multipurpose tool. Some organisms steel structures to activate oxygen from others by feeding them; others have to accomplish this task with external help. Defense means against pathogens and parasites: reactive oxygen species: Activated oxygen is also a universal tool against and particulate invaders. Arms race between plants and animals: biotransformation system: The biotransformation system started as an arm race between plants and animals. Plants produce secondary plant metabolites to defend against herbivory, and animals try to cope with this chemical challenge by enzyme systems of low specificity. Due to this low specificity, organisms can even handle many, but not all, synthetic chemicals without being intoxicated.

1  Why a Small Worm Is Not Crazy

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Heat shock proteins: the minimal, but universal stress response: The coined term “heat shock protein” is misleading, since these protein families have a fundamental function, not only after various external or internal stresses. Their energy consuming stress response is as universal as the activation of oxygen. Organisms in stable environments have lost this stress response pathway. Heavy metals: defense and ecological utilization: Most organisms developed after heavy metals were buried beneath the biosphere. Yet, where both co-occur organisms are forced to handle the stress, to develop strategies to survive and to pass the adverse challenge to competitors or predators. The basis of stress response: ecological transcriptomics. Transcription is the initial step in gene expression and gives the first indication of cellular response potentials. Yet, such molecular biological data should be combined with further “omics” techniques. Not all lies in the genes: microRNAs and epigenetics. The translation of transcription products into proteins can be strongly modulated as the readability of the genetic information itself. The post-genetic era has overcome the genetic bias and opens new fields of investigations. The actual response: ecological proteomics and metabolomics. The stress response is formed by proteins and their metabolites. We are beginning to understand that each environmental stress appears to have a proteomic and metabolomic fingerprint. Whatever doesn’t kill you might make you stronger: hormesis. It seems that the hormesis concept is more than a fashionable concern. To avoid a zero-sum game, from an ecological viewpoint this concept has to be considered more comprehensively than many current laboratory studies do. Multiple stressors as environmental realism: synergism or antagonism. A central belief is that organisms living under conditions close to their environmental tolerance limits appear to be most vulnerable to additional stress. Yet, there is increasing body of evidence that multiple stressors do not necessarily act additively or synergistically, but antagonistically. The mechanisms behind remain obscure in many instances. One stressor prepares for the next one to come: cross-tolerance. Subsequent or even simultaneous stressors induce cross-tolerances and prepare for the next stressor. This phenomenon is essential for organisms and populations to survive under suboptimal or fluctuating environmental conditions. Longevity: risky shift in population structures. The modulation of lifespan and reproduction under stresses shifts the population structure and bears the intrinsic risk of extinction. Footprints of stress in communities. The stress defenses translate into changes in community structures, which can be assessed by various phenotypic approaches and one theory-based approach. The gap between molecular and cellular responses and these approaches remains open. Environmental stresses – ecological driving force and trigger of evolution.

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1  Why a Small Worm Is Not Crazy

We will see that not all stress is stressful – in contrast, it appears that mild chemical stress in the environment, below the mutation threshold, is essential for many subtle manifestations of population structures and biodiversity and may indeed have played a key role in the evolution of life in extreme environments. Even without any anthropogenic chemical discharge into the environment, ecosystems are loaded with natural chemicals which may have served as triggers for the evolution of some defense systems. Due to the long period of co-existence between stressors and organisms, the latter have not merely adapted, but have instead developed biochemical and molecular biological strategies to convert an adverse stress into a benefit for their individual integrity, for individual health and longevity, for the potential extension of the realized ecological niche, and for biodiversity and evolution. We are only just beginning to understand the subtle impacts on and the underlying mechanisms of stress in organisms; however, it does not seem fallacious to state that several ecological phenomena which are attributed to other factors, such as climate, nutrients and food, or competition, are at least influenced by factors that triggered the evolution of defense systems. This book is not a textbook on ecotoxicology, environmental genetics, environmental physiology, ecological parasitology, or chemical ecology. Rather, it is simply an attempt to examine how stress in general affects organisms in beneficial ways. We hope that it will find its way into the scientific community and, finally, that the readers will not suffer from stress.

Chapter 2

Activation of Oxygen: Multipurpose Tool

To most biomolecules, elemental oxygen is inert since it usually does not oxidize them without prior activation either inside or outside of organisms. Atmospheric oxygen in its ground state is distinctive among the gaseous elements because it is a bi-radical. This means it possesses two unpaired electrons with parallel spins which make it paramagnetic. In this constitution, it is very unlikely to participate in reactions with organic molecules unless activated. Activation of oxygen can be facilitated by two different mechanisms: • absorption of sufficient physical energy to reverse the spin on one of the unpaired electrons and to form the diamagnetic form of molecular oxygen, the so-called singlet oxygen 1O2, or • stepwise monovalent reduction. Both pathways of oxygen activation are energy dependent (Fig. 2.1). In the environment, photoactivation of oxygen may take place whenever light is absorbed by chromophores (pigments, humic substances). This process is termed photodynamic or photosensitized reaction. Inside phototrophs, this process is central in the photosynthesis. Externally, this process is of major ecological significance. Other pathways, such as superoxide dismutation or electron donation by • O2 − to an oxidized election acceptor, are not likely to occur in nature (Elster 1982).

2.1  Oxygen Activation in Ecosystems In natural systems, the majority of chromophoric substances are comprised of humic substances. These are brownish materials which mainly derive from plant debris that leach into freshwater systems and ultimately into the oceans. Whenever they interact with light, a series of chemical reactions occur. They absorb both ultraviolet (UV) and visible light (VIS) in the wavelength range (290) 300–600  nm. These chromophores are activated many times a day. One calculation says that on a sunny C.E.W. Steinberg, Stress Ecology: Environmental Stress as Ecological Driving Force and Key Player in Evolution, DOI 10.1007/978-94-007-2072-5_2, © Springer Science+Business Media B.V. 2012

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2  Activation of Oxygen: Multipurpose Tool Singlet oxygen

O-O:

Superoxide radical

. O-O:

. O-O . Triplet oxygen ground state

+31.8

. O-O:H

-90.8

H:O-O:H Hydrogen peroxide

-36.8

H:O . + H:O:H Hydroxyl radical

Water

-224.7

Free energy, kJoule M-1

+92.0

Perhydroxyl radical

H:O:H Water

Fig. 2.1  Nomenclature of the various forms and activation pathways of oxygen. Left: absorption of energy (92 kJ M−1) to activate the triplet state into the singlet state. Right: After the endergonic • − (31.8 kJ M−1) reduction of O2 to O 2 , the subsequent reduction steps are exergonic and occur spontaneously, either catalyzed or uncatalyzed. Red figures denote endergonic reactions, blue ­figures indicate exergonic reactions

day in Lake Greifensee (Switzerland), each chromophore in the lake’s epilimnion is activated 270 times, that is, ten times or more per hour (Schwarzenbach et al. 1993). The light-absorption capacity is, in most cases, linked to the presence of p-electron systems that are available from heteroatoms, aromatic rings, or conjugated double bonds. These are the so-called ‘chromophores’. With energy absorption, the outermost electron orbitals gain energy, and electrons are elevated from their lowest energy state to a higher energy state. Molecules in excited states are more reactive than in their ground states. Direct photochemical reactions are immediate chemical changes to the chromophore such as isomerization, bond cleavage, or degradation of larger molecules into smaller molecules because of electron transfer reactions. In the presence of oxygen, photochemical decarboxylation and formation of CO2 are observed in HSs, which are usually enhanced by the presence of iron in HS complexes. The different reaction products are called reactive oxygen species (ROS). The individual ROS have very different half-lives, from only a few microseconds for 1O2 to well over 1 h for H2O2. Depending on production rates and half-lives, average steady-state concentrations for ROS from 10−18 to 10−2 M are found in natural waters (Steinberg and Paul 2008). Production and gross ecological effects of ROS are summarized in Fig. 2.2. The light-induced formation of ROS is called sensitization, and the photo-excited ­molecule itself is the sensitizer. Although the sensitizer molecule returns without

2.1  Oxygen Activation in Ecosystems

9

Fig. 2.2  Schematic presentation of photolytic production of reactive oxygen species (ROS) in an aquatic ecosystem. The major process is their release from illuminated dissolved chromophoric organic carbon. The ROS may interact with a great variety of water constituents, including organisms and dissolved organic compounds (From Steinberg and Paul 2008, with permission from Elsevier)

modification to the ground state, the photogenerated reactive species can attack any suitable target in its neighborhood, including the sensitizer itself. In fact, ROS account for the majority of photodegradation reactions observed with HSs. Any photosensitized reaction involves the transfer of energy, hydrogen atoms, protons, or electrons. The importance of oxygen in the photooxidation of natural organic matter is evident from oxygen consumption studies dating back to the early days of limnology. Oxygen plays a pivotal role as the initial scavenger of radicals that are produced during irradiation of water. This leads to the generation of alkoxy and peroxy radicals that decay to stable oxygenated species.

2.1.1 Effects on Organisms Photolysis of various chromophoric dissolved compounds results in the production of ROS, of which H2O2 is long-lived and • O2 − as well as 1O2 have the highest ­reactivity. All ROS may attack organisms. H2O2 easily penetrates membranes and contributes to internal oxidative stress which may be detrimental to the organism. For instance, leachates from aquatic macrophytes, which release the highest ­concentrations

10

2  Activation of Oxygen: Multipurpose Tool

of H2O2, support microbial growth least. In addition, the ­predominantly adverse effect of internal oxidative stresses, for instance from UV irradiation or processing of xenobiotic chemicals, is well documented and comprises induction and modulation of stress response proteins and enzymes, reduction of photosynthetic activity, and increased membrane (lipid) peroxidation. However, oxidative stress as a potential ecological driving force has not yet gained the attention it deserves (Steinberg and Paul 2008). Only very recently, Glaeser et al. (2010) studied the short-term as well as long-term effects of 1O2 on bacterioplankton composition in a humic lake. The authors artificially increased the natural rate of 1O2 formation in short-term (~4 h) in situ and long-term (72 h) laboratory incubations of surface water samples from a humic acid-rich lake. The analysis of abundant bacterioplankton phylotypes upon 1O2 exposure showed that a moderate increase in 1O2 exposure led to similar changes in different years, indicating the establishment of bacterial communities adapted to 1O2 exposure. Bacterioplankton phylotypes favored under these conditions belonged to Betaproteobacteria of the beta II cluster (e.g. Polynucleobacter necessarius) and the beta I cluster related to Limnohabitans (R-BT subcluster) as well as Alphaproteobacteria affiliated to Novosphingobium acidiphilum. In contrast, Actinobacteria of the freshwater acI-B cluster were sensitive to even moderate 1 O2 exposure. Overall, the authors demonstrated that 1O2 exposure due to photolysis of dissolved organic matter represents an important ­natural selective factor affecting bacterial species dynamics in aquatic ecosystems.

2.2  Activation of Oxygen in Organisms 2.2.1 Using “Stolen” Structures In organisms, the activation of oxygen in principle does not differ from the abiotic processes in the environment. Oxygen has to be activated for any aerobic ­heterotrophic process to occur. Oxidative burst and a subsequent potential oxidative stress is a universal phenomenon experienced by both aerobic and anaerobic organisms from all domains of life (Imlay 2003). Solar irradiation has the potential to activate oxygen by forming singlet oxygen. For organisms, the necessary energy is provided free of charge. Heterotrophic reduction of oxygen, however, is energy demanding, and the energy has to be deducted from other processes, such as body maintenance (growth, repair, and longevity) or reproduction. Consequently, smart animals should be able to save energy for heterotrophic and reproductive processes. And they do, probably much more frequently than is addressed in the literature. “Stolen chloroplasts” (= kleptochloroplasts) convert a heterotroph into a mixtotroph organism. This occurrence is typical of dinoflagellates, such as Gymnodinium sp. and Cryptoperidiniopsis sp. who take the kleptochloroplasts generally from cryptophytes, their preferred phytoplankton prey (Jakobsen et al. 2000). After ­ingestion, chloroplasts may remain photosynthetically active for some time (Schnepf and Elbrächter 1999;

2.2  Activation of Oxygen in Organisms

11

Fig. 2.3  Ingestion rates as a function of irradiance (mmol photons m−2  s−1) for the ciliates Strombidinopsis acuminatum fed the pigmented Prorocentrum minimum and Coxliella sp. fed the non-pigmented Gymnodinium simplex (From Strom 2001, courtesy of Inter-Research Science Center). The increased ingestion efficiency of pigmented prey is obvious. For sake of clarity, straight lines are drawn by CS

Eriksen et al. 2002). In this respect, Skovgaard (1998) showed that their photosynthetic activity is lost within a few days. In his detailed study, he showed that light had a positive effect on growth kinetics of Gymnodinium cf. ­gracilentum in that growth and ingestion rates are higher at a high light intensity than at a low light intensity. He concluded that this effect was due to factors other than photosynthetic activity of kleptochloroplasts, since a control experiment with a supposed strictly heterotrophic dinoflagellate also showed a dependence of growth kinetics on light intensity. More recent work (Strom 2001, 2002) also showed that some strictly ­heterotrophic protists digest phytoplankton at a higher rate in the light than in the dark and provided some mechanistic explanations. The light-dependent digestion differences translated into substantially higher rates of protist feeding and population growth, so that grazing potential may be linked to light intensity. In fact, chloroplast-sequestering dinoflagellates grow well in the light, but only when food is available (Jakobsen et al. 2000), which means that the gain of photosynthetic capability is not significant. Light-aided digestion in protists has been seen only for phytoplankton prey, and was not observed when prey was heterotrophic. The phenomenon is mediated by visible light, which includes photosynthetically active wavelengths. These observations suggest that the digestive mechanism involves the photosynthetic apparatus of ingested prey cells. The hypothesis on the mechanism is that active oxygen compounds, whose formation should be promoted by photosensitization reactions involving chlorophyll, directly decomposed lipids and proteins of the ingested phytoplankton cell once the cell was enclosed in the degradative environment of the protist food vacuole. The light-aided digestion is not restricted to dinoflagellates, but has been shown also with ciliated protozoans (Fig. 2.3) and applies most likely to all transparent heterotrophs in a euphotic zone.

12

2  Activation of Oxygen: Multipurpose Tool

2.2.2 Using Own Structures 2.2.2.1 Balancing ROS and RNS – The Redox Homeostasis Traditionally, ROS and reactive nitrogen species (RNS) were considered to be toxic by-products of aerobic metabolism, which were disposed of using antioxidants. However, in recent years, it has become apparent that plants actively produce ROS and RNS as signaling molecules to control processes such as programmed cell death, abiotic stress responses, pathogen defense, and systemic signaling (Mittler 2002).

Oxygen Activation In the presence of photosynthetic pigments, which become excited by light ­absorption, the inert triplet state is transformed into the reactive singlet oxygen by absorbing energy from the excited pigment. This happens in the light-harvesting complex of both photosystems. In the case of photosynthetic electron transport, O2 uptake associated with photoreduction of O2 to • O2 − is called the Mehler reaction. Although photoreduction of oxygen is an important alternative sink for the consumption of excess energy, it is always associated with the generation of toxic ROS. The major process of oxygen activation in all organisms is the stepwise reduction of triplet oxygen. The first univalent reduction step is energy demanding; the subsequent one-electron reduction steps are not energy dependent and can occur spontaneously or require an appropriate e−/H+ donor. In biological systems, heavy metal ions (Fe2+, Cu+) and semiquinones can act as e− donors. Four-electron reduction of oxygen in the respiratory electron transport chain is always accompanied with a partial one- to three-electron reduction, yielding the formation of ROS: superoxide • − radical ( O2 ), hydroxyl radical ( • OH ), hydrogen peroxide (H2O2), and singlet 1 oxygen ( O2). Although H2O2 is less reactive than • O2 − , in the presence of reduced heavy metals such as Fe2+ in a chelated form (which is the case in biological systems), the formation of • OH can occur in the Fenton reaction (Blokhina et al. 2003). Ferrous iron is oxidized by hydrogen peroxide to ferric iron, a hydroxyl radical, and a hydroxyl anion. Ferric iron then is reduced back to ferrous iron, peroxide radical, and a proton by the same hydrogen peroxide (dismutation):

Fe 2 + + H 2 O2 → Fe 3+ + • OH + OH −

(2.1)



Fe 3+ + H 2 O2 → Fe 2 + + • OOH + H + .

(2.2)

The recycling of iron from ferric to ferrous form by reducing agents facilitates the permanent generation of • OH and maintains the Fenton reaction; hence, it is a self-catalyzing chain reaction with damage of cellular structures and biomolecules far in excess of the initial ROS concentration. In biological systems, the availability

2.2  Activation of Oxygen in Organisms

13

of ferrous ions (and other redox-sensitive metals, such as Cu, Zn, Mn, and recently discovered: Ni) limits the rate of the Fenton reaction. Consequently, it is one major strategy of cells and organisms to reduce the availability of redox-sensitive metals in case of an oxidative stress, with phenols central in this termination of the Fenton reaction (see below). Mechanisms for the generation of ROS in biological systems are represented by both non-enzymatic and enzymatic reactions. Non-enzymatic one-electron O2 reduction can occur at low oxygen concentrations. Among enzymatic sources of ROS, xanthine oxidase (XO), an enzyme responsible for the initial activation of dioxygen, should be mentioned. As electron donors, XO can use xanthine, hypoxanthine or acetaldehyde. The next enzymatic step is the dismutation of the superoxide radical by superoxide dismutase to yield H2O2. Due to its relative stability, the level of H2O2 is regulated enzymatically by an array of catalases (CAT) and peroxidases localized in almost all compartments of the cell. Peroxidases, besides their main function in H2O2 elimination, can also catalyze • O2 − and H2O2 formation by a complex reaction in which NADH is oxidized using trace amounts of H2O2 first produced by the non-enzymatic breakdown of NADH. Next, the NAD· radical reduces O2 to • O2 − , some of which dismutates to H2O2 and O2. Thus, peroxidases and catalases play an important role in the fine regulation of ROS concentration and signaling in the cell through activation and deactivation of H2O2. Lipoxygenase (LOX, linoleate:oxygen oxidoreductase) reaction is another possible source of ROS and other radicals. It catalyzes the hydroperoxidation of polyunsaturated fatty acids (PUFA). The hydroperoxyderivatives of PUFA can undergo autocatalytic degradation, producing radicals and thus initiating the chain reaction of lipid peroxidation (LPO). In addition, LOX-mediated formation of singlet oxygen or superoxide radicals is feasible (Blokhina et al. 2003). Most cellular compartments have the potential to become a source of ROS. Most ROS are formed in the chloroplasts via reduction to • O2 − or via excitation. Another potential source of ROS, namely H2O2, is the oxidation of glycolate or fatty acids in the peroxisomes (Fig. 2.4, Table 2.1). In the apoplast, several enzymes may also lead to ROS production under normal and stress conditions by oxidation of amines and oxalate. The mitochondrial electron transport system is also a source of ROS (Fig. 2.4, Table 2.1), including • O2 − , H2O2, and • OH . In general, ROS are generated in mitochondria, an undesirable side product of oxidative energy metabolism (Dröge 2002). Direct reduction of O2 to • O2 − takes place in the flavoprotein region of NADH dehydrogenase segment of the respiratory chain. Several observations reveal ubiquinone as a major H2O2 generating location of the mitochondrial electron transport chain in vitro with • O2 − as a major precursor (Fig. 2.4). It is calculated that in animals, approximately 1.5% of electrons flowing through the electron transport chain can be diverted to form • O2 − (Novo and Parola 2008). Superoxide radicals are known to be produced during NADPH-dependent microsomal electron transport. Two possible loci of • O2 − production in microsomes are auto-oxidation of oxycytochrome-P450 complex that forms during microsomal mixed function oxidase (MFO) reactions and/or auto-oxidation of cytochrome P450 reductase, a flavoprotein that contains both flavin adenine

14

2  Activation of Oxygen: Multipurpose Tool

Fig. 2.4  Simplified scheme situating redox reactions in plant metabolism and their relationship to signaling. ROS are produced by many reactions, notably photosynthetic and respiratory metabolism, including photorespiration (not shown), and by homologs of mammalian respiratory burst oxidases (Rboh). ROS are processed by dismutases (superoxide dismutase, catalases) and reductive systems in which NAD(P)H, ascorbate and glutathione play a key part. Interactions between ROS, ascorbate and glutathione are important in acclimatory signaling mechanisms by which the plant perceives and responds to environmental change. These mechanisms involve interplay with many other cell signaling components, some of which are indicated in the outer green frame. Redox signals other than ROS are also produced by photosynthetic and mitochondrial electron transport chains. ASC ascorbate; GSH glutathione; MET mitochondrial electron transport; PET photosynthetic electron transport (From Noctor 2006, courtesy of Blackwell)

dinucleotide (FAD) and flavin mononucleotide (FMN, or riboflavin-5¢-phosphate) (Bhattacharjee 2005). Cell wall peroxidase is able to oxidize NADH and in the process catalyze the formation of • O2 − . This enzyme utilizes H2O2 to catalyze the oxidation of NADH to NAD+, which in turn reduces O2 to • O2 − . Superoxide radicals subsequently dismutate to H2O2 and O2. Other important sources of ROS in plants that have received little attention are detoxification reactions catalyzed by cytochrome-P450 in cytoplasm and endoplasmic reticulum (ER). In plants, ROS are also generated at the plasma membrane or extracellularly in the apoplast. Plasma membrane NADPHdependent oxidase (NADPH oxidase) has recently received a lot of attention as a

2.2  Activation of Oxygen in Organisms

15

Table 2.1  Producing, scavenging, and avoiding reactive oxygen species ­animals; PS = photosystem Localization Mechanism In plants In animals Production Photosynthesis Chloroplast (water-splitting site in PSII, reduction by ferredoxin in PSI) Excited chlorophyll Chloroplast (light harvesting complexes) Respiration Mitochondria (reduction Mitochondria by bioquinones) (reduction by bioquinones) Lipoxygenase Membranes Membranes Glycolate oxidase Mitochondria, peroxisomes Mitochondria, peroxisomes Fatty acid b-oxidation Further oxidases Xanthine oxidase Peroxisomes Peroxisomes Nitric oxide synthase Cyclooxygenase Other NAD(P)H dependent oxido-reductases NADPH oxidases Plasma membrane Plasma membrane of phagocytic and non­phagocytic cells Oxalate oxidase Apoplast Amine oxidase Apoplast Peroxidases, Mn2+ and Cell wall NADH Detoxification Endoplasmic reticulum, Endoplasmic cytoplasm reticulum, cytoplasm Scavenging Superoxide dismutase

Chloroplast, cytosol, mitochondria, peroxisomes, apoplast Ascorbate peroxidase Chloroplast, cytosol, mitochondria, peroxisome, apoplast Catalase Peroxisomes Glutathione peroxidase Cytosol, membranes Peroxidases Thioredoxin peroxidase

Cell wall, cytosol, vacuole Chloroplast, cytosol, mitochondria

Mitochondria, peroxisomes

(ROS) in plants and

Primary ROS •

O2 −

O2

1

•

O2 − ,H 2 O2 ,• OH

ROO• H2O2 •

O2 −

•

O2 −

H2O2 H2O2 H 2 O2 ,• O2 − •

O2 −

•

O2 −

Mitochondria, peroxisomes

H2O2

Peroxisomes Cytosol, membranes Cytosol Cytosol, mitochondria

H2O2 H 2 O2 , ROO• H2O2 H2O2 (continued)

16

2  Activation of Oxygen: Multipurpose Tool

Table 2.1  (continued) Mechanism Ascorbic acid

Glutathione a-Tocopherol Carotenoids Proline Mycosporine-like amino acids, phlorotannins Alternative oxidases Avoidance Anatomical adaptations C4 or CAM metabolism Chloroplast movement Suppression of photosynthesis Photosystem and antenna modulations

Localization In plants Chloroplast, cytosol, mitochondria, peroxisomes, apoplast Chloroplast, cytosol, mitochondria, peroxisomes, apoplast Membranes Chloroplast Chloroplast, cytosol, mitochondria

In animals

Primary ROS

Cytosol, mitochondria, peroxisomes Cytosol, mitochondria, peroxisomes Membranes

H 2 O2 ,• O2 − H2O2 ROO• ,1 O2 O2 1 O2 1

Cytosol, mitochondria

1

O2 ,ROO•

•

O2 −

Leaf structure, epidermis

•

O2 − ,H 2 O2 ,1 O2

Chloroplast, cytosol, vacuole Cytosol Chloroplast

•

O2 − ,H 2 O2

•

O2 − ,H 2 O2 ,1 O2 O2 − ,H 2 O2

Chloroplast

•

Chloroplast, mitochondria

Mitochondria

•

O2 − ,1 O2

source of ROS for oxidative burst, which is typical of incompatible plant–pathogen interaction. In phagocytes, plasma membrane localized NADPH oxidase was identified as a major contributor to their bacteriocidal capacity. In addition to NADPH oxidase, pH-dependent cell wall-peroxidases, germin-like oxalate oxidases and amine oxidases have been proposed as a source of H2O2 in apoplast of plant cells. pH-dependent cell-wall peroxidases are activated by alkaline pH, which in the ­presence of a reductant produces H2O2. Alkalization of apoplast upon elicitor recognition preceding the oxidative burst and production of H2O2 by a pH-dependent cell wall peroxidase has been proposed as an alternative pathway of ROS production during biotic stress (Bhattacharjee 2005). Reactive Nitrogen Species Reactive nitrogen species (RNS) are a family of reactive molecules derived from nitric oxide ( • NO ) and • O2 − produced via the enzymatic activity of inducible nitric oxide synthase 2, NOS2, and NADPH oxidase respectively. RNS act together with

2.2  Activation of Oxygen in Organisms

17

ROS to damage cells, causing nitrosative stress (Pauly et al. 2006). Therefore, these two species are often collectively referred to as ROS/RNS. Reactive nitrogen species also are continuously produced as by-products of aerobic metabolism or in response to stress. Nitric oxide exerts physiological effects by controlling vascular tone, cell adhesion, vascular permeability, and platelet adhesion. Furthermore, • NO is able to react rapidly with • O2 − to form the much more powerful oxidant peroxynitrite (ONOO−). • NO is not particularly toxic in vivo because • NO is removed because of its rapid diffusion through tissues. ONOO− is a strong oxidant and produces nitrite and a hydroxide ion rather than isomerizing to nitrate. Like the other oxidants, it can react with proteins, lipids, and nucleic acids. ONOO− can also interact with mitochondria, reaching them from extra-mitochondrial compartments or being locally produced through the interaction of • NO (generated by the mitochondrial NOS) and • O2 − . Mitochondrial toxicity of ONOO− results from direct oxidative reactions of principal components of the respiratory chain or from free radicalmediated damage. Persistent generation of significant levels of ONOO− can lead to the induction of cell death, either by apoptosis or necrosis (Novo and Parola 2008). Scavenging of ROS Major ROS-scavenging mechanisms include superoxide dismutase (SOD), ascorbate peroxidases (APX), and catalase (CAT) (Table 2.1). The balance between SOD and APX or CAT activities in cells is crucial for determining the steady-state level of superoxide radicals and hydrogen peroxide. Together with sequestering of metal ions, this balance is important to prevent the formation of the highly toxic hydroxyl radical via the Fenton reaction. The different affinities of APX (mM range) and CAT (mM range) for H2O2 suggests that they belong to two different classes of H2O2scavenging enzymes: APX might be responsible for the fine modulation of ROS for signaling, whereas CAT might be responsible for the removal of excess ROS during stress, which most likely enables plants particularly to distinguish between different challenges (for details, see below). The major ROS-scavenging pathways that are well summarized by Mittler (2002) (Fig. 2.5) are: • The water–water cycle in chloroplasts (Fig. 2.5a), • The ascorbate–glutathione cycle in chloroplasts, cytosol, mitochondria, apoplast and peroxisomes (Fig. 2.5b), • Glutathione peroxidase (GPX; Fig. 2.5c), and • CAT in peroxisomes (Fig. 2.5d). The water–water cycle (Fig. 2.5a) draws its reducing energy directly from the photosynthetic apparatus. Thus, this cycle appears to be autonomous with respect to its energy supply. However, the source of reducing energy for ROS scavenging by the ascorbate–glutathione cycle (Fig. 2.5b) during normal metabolism and particularly during stress, when the photosynthetic apparatus might be suppressed or

18

2  Activation of Oxygen: Multipurpose Tool

Fig. 2.5  Pathways for reactive oxygen species (ROS) scavenging in plants. (a) The water–water cycle. (b) The ascorbate–glutathione cycle. (c) The glutathione peroxidase (GPX) cycle. (d) • − Catalase (CAT). SOD acts as the first line of defense converting O 2 into H2O2. APX, GPX, and CAT then detoxify H2O2. In contrast to CAT (d), APX and GPX require an ascorbate (AsA) and/or a glutathione (GSH) regenerating cycle (a–c). This cycle uses electrons directly from the photosynthetic apparatus (a) or NAD(P)H (b, c) as reducing power. ROS are indicated in red, antioxidants in blue and ROS-scavenging enzymes in green. Abbreviations: DHA dehydroascorbate; DHAR, DHA reductase; Fd ferredoxin; GR glutathione reductase; GSSG oxidized glutathione; MDA monodehydroascorbate; MDAR, MDA reductase; PSI photosystem I; tAPX thylakoid-bound APX (From Mittler 2002, with permission from Elsevier)

2.2  Activation of Oxygen in Organisms

19

d­ amaged, is not entirely clear. In animals and yeasts, the pentose-phosphate ­pathway is the main source of NADPH for ROS removal. Because CAT does not require a supply of reducing equivalents for its function, it might be insensitive to the redox status of cells and its function might not be affected during stress, unlike the other mechanisms (Fig. 2.5). Antioxidants such as ascorbic acid and glutathione, which are found at high concentrations in chloroplasts and other cellular compartments (5–20  mM ascorbic acid, 1–5  mM glutathione), are crucial for defense against oxidative stress. Maintaining a high reduced per oxidized ratio of ascorbic acid and glutathione is essential for the proper scavenging of ROS in cells. This ratio is maintained by glutathione reductase (GR), monodehydroascorbate reductase (MDAR), and ­dehydroascorbate reductase (DHAR) using NADPH as reducing power (Fig. 2.5). It has also been suggested that the oxidized per reduced ratio of the different antioxidants can serve as a signal for the modulation of ROS-scavenging mechanisms. The overall balance between different antioxidants must be tightly controlled. Antioxidant Systems To control the level of ROS and RNS and to protect cells under stress conditions, plant tissues contain several enzymes that scavenge ROS: SOD, CAT, peroxidases (POD), glutathione peroxidase (GPX), detoxifying LPO products (GST, phospholipid-hydroperoxide glutathione peroxidases, and APX), and a network of low molecular-weight mass antioxidants (ascorbate, glutathione, phenolic compounds, tocopherols). In addition, a array of enzymes is needed for the regeneration of the active forms of the antioxidants (MDAR, DHAR, GR) (Blokhina et al. 2003). Major Antioxidant Enzymes Superoxide Dismutase The scavenging of • O2 − is achieved through SOD, which catalyses the dismutation of superoxide radicals to H2O2. This reaction has a 10,000-fold faster rate than spontaneous dismutation. The enzyme is present in all aerobic organisms and in all subcellular compartments susceptible to oxidative stress. Recently, a new type of SOD with Ni in the active centre has been described in Streptomyces. The other three types of this enzyme, classified by their metal cofactor, can be found in living organisms. They are the structurally similar Fe-SOD (prokaryotic organisms, chloroplast stroma) and Mn-SOD (prokaryotic organisms and the mitochondrion of eukaryotes) and the structurally unrelated Cu/Zn-SOD (cytosolic and chloroplast enzyme, gramnegative bacteria). These isoenzymes differ in their sensitivity to H2O2; all three enzymes are nuclear encoded (Blokhina et al. 2003; Gill and Tuteja 2010). The reaction catalyzed by superoxide dismutase can be summarized as:

•

O2 − + • O2 − + 2H + → H 2 O2 + O2 .

(2.3)

20

2  Activation of Oxygen: Multipurpose Tool

Catalase and Peroxidases The intracellular level of H2O2 is regulated by a wide range of enzymes, the most important being CAT and POD. CAT is a common enzyme found in nearly all living organisms that are exposed to oxygen where it functions to catalyze the dismutation of H2O2 to H2O and O2. CAT has one of the highest turnover numbers of all enzymes: one CAT molecule can convert millions of H2O2 molecules to H2O and O2 per sec• ond. As an intermediate, OH is produced, which is a very strong oxidant and can initiate radical chain reactions with organic molecules, particularly with PUFA in membrane lipids. The dismutation by CAT can be summarized as: 2H 2 O2 → 2H 2 O + O2 .



(2.4)

Peroxidases are a large family of enzymes that reduce H2O2:

2H 2 O2 → 2H 2 O + oxidized donor.

(2.5)

Ascorbate Peroxidases Ascorbate peroxidases (APX) are enzymes that detoxify peroxides such as H2O2 using ascorbate as a substrate and are an integral component of the glutathioneascorbate cycle. The reaction they catalyze is the transfer of electrons from ascorbate to a peroxide, producing dehydroascorbate and water as products:

C6 H8 O6 + H 2 O2 → C6 H 6 O6 + 2H 2 O.

(2.6)

Glutathione Peroxidase Glutathione peroxidases (GPX) comprise an enzyme family having peroxidase activity. The biochemical function is to reduce lipid hydroperoxides to their corresponding alcohols and to reduce free hydrogen peroxide to water. The reactions catalyzed by GPX can be summarized as:

2 GSH + H 2 O2 → GSSG + 2H 2 O,

(2.7)

where GSH represents reduced monomeric glutathione, and GSSG is the oxidized glutathione disulfide. Glutathione reductase then reduces the oxidized glutathione to complete the cycle:

GSSG + NADPH + H + → 2 GSH + NADP + .

(2.8)

2.2  Activation of Oxygen in Organisms

21

Phospholipid Hydroperoxide Glutathione Peroxidase Phospholipid hydroperoxide glutathione peroxidase is a key enzyme in the ­protection of the membranes exposed to oxidative stress, and it is inducible under various stress conditions. The enzyme catalyzes the regeneration of phospholipid hydroperoxides at the expense of GSH and is localized in the cytosol and the inner membrane of mitochondria of animal cells. Until recently, most investigations of this enzyme have been performed on animal tissues (Gill and Tuteja 2010). Alternative Oxidase Plants and some other organisms possess a complex branched respiratory network in their mitochondria (and in the case of plants also chloroplasts). Some pathways of this network are not energy-conserving and allow sites of energy conservation to be bypassed, leading to a decrease of energy yield in the cells. Consequently, ROS production can be balanced also by this alternative channeling by a group of enzymes called alternative oxidases, AOXs. AOXs can divert electrons flowing through electron-transport chains and use them to reduce O2 to water (Fig.  2.6). Thus, they decrease ROS production by two mechanisms: they prevent electrons from reducing O2 into • O2 − ; and they reduce the overall level of O2, the substrate for ROS production, in the organelle. Decreasing the amount of mitochondrial AOX increases the sensitivity of plants to oxidative stress. In addition, chloroplast AOX is induced in transgenic plants that lack APX and/or CAT, and in normal plants in response to high light (Sluse and Jarmuszkiewicz 1998; Mittler 2002). Other groups besides plants which may possess AOX systems include non-­ photosynthesizing unicellular eukaryotes including amoeboid (e.g., Acathamoeba castellanii) and parasite protists (e.g., Trypanosoma sp., Plasmodium sp., Phytomonas sp., Cryptosporidium sp.), non-fermentative yeast (Candida sp., Yarrowia sp.) and ­filamentous fungi (Aspergillus fumigatus, A. niger, Ajellomyces capsulatus, Blumeria graminis, Cryptococcus neoformans), and probably animals (phyla Mollusca, Nematoda, Chordata) (McDonald and Vanlerberghe 2004; Jarmuszkiewicz et al. 2010). Sequences similar to the plant oxidase also have been identified in bacterial genomes like Novosphigobium aromaticivorans or Anabaena variabilis (McDonald et al. 2003). Antioxidant Substrates There are several antioxidant substrates that control redox homeostasis without the involvement of enzymes. The major substrates as well as a few “exotic” or recently discovered ones will be introduced briefly to indicate that additional antioxidant compounds can be expected. Glutathione The tripeptide glutathione (GSH, g-glutamylcysteinylglycine) (Fig.  2.7) is an ­abundant compound in tissues. It is in virtually all cell compartments (cytosol,

22

2  Activation of Oxygen: Multipurpose Tool

Fig. 2.6  Involvement of alternative oxidase (AOX) in reactive oxygen species (ROS) avoidance. In both the mitochondrial electron-transport chain (a) and the chloroplast electron-transport chain • − (b), AOX diverts electrons that can be used to reduce O2 into O 2 and uses these electrons to reduce O2 to H2O. In addition, AOX reduces the overall level of O2, the substrate for ROS production, in the organelle. AOX is indicated in yellow and the different components of the electrontransport chain are indicated in red, green or gray. Abbreviations: Cyt-b6f cytochrome b6f; Cyt-c cytochrome c; Fd ferredoxin; PC plastocyanin; PSI, PSII photosystems I and II (From Mittler 2002, with permission from Elsevier) Fig. 2.7  Structure of glutathione

O

O

HS H N

HO H2N

N H

O OH

O

endoplasmic reticulum, vacuole, and mitochondria) where it executes multiple functions. GSH is the main storage form of sulfur, and it acts as a potent detoxifier of ­xenobiotics through GSH-conjugation (see Chap. 4) and can serve as a precursor of ­phytochelatins (see Chap. 6). Together with its oxidized form, GSSG, GSH maintains a redox balance in the cellular compartments. A central nucleophilic cysteine residue is responsible for the high reductive potential of GSH. It scavenges cytotoxic H2O2 (Eq. 2.7 in the absence of GST) and reacts non-enzymatically with other

2.2  Activation of Oxygen in Organisms Fig. 2.8  Structure of ascorbic acid

23 OH HO

H

HO

O

O

OH

ROS: 1O2, • O2 − , and • OH . The central role of GSH in antioxidative defense is due to its ability to regenerate another powerful water-soluble antioxidant, ascorbic acid, via the ascorbate-glutathione cycle (Fig. 2.5). Ascorbic Acid Ascorbic acid (AA) (Fig. 2.8) is a sugar acid with antioxidant properties and one of the most studied antioxidants. It is in the majority of plant cell types, organelles, and the apoplast. Under physiological conditions, AA exists in the reduced form in leaves and chloroplasts, and its intracellular concentration can build up to mM range. The ability to donate electrons in a wide range of enzymatic and non-­ enzymatic reactions makes AA the main ROS-detoxifying compound in the aqueous phase. AA can directly scavenge 1O2, • O2 − (Eq. 2.9), and • OH , and reduce H2O2 to water via APX reaction. In chloroplasts, AA acts as a cofactor of violaxantin de-epoxidase, thus sustaining dissipation of excess excitation energy. AA regenerates tocopherol from tocopheroxyl radical, providing membrane protection (Eq. 2.10; and below) (Blokhina et al. 2003).

2• O2 − + 2H + + AA → 2H 2 O2 + dehydroascorbate.

(2.9)



tocopheroxyl radical + AA → tocopherol + monodehydroascorbate.

(2.10)

Tocopherols Tocopherols and tocotrienols [vitamin E = four tocopherols (a-, b-, g-, d-) and four tocotrienols (a-, b-, g-, d-), see Fig.  2.9] are essential components of biological membranes where they have both antioxidant and non-antioxidant functions. The four tocopherol and tocotrienol isomers consist of a chroman head group and a phytyl side chain, giving vitamin E compounds amphipathic character. Relative antioxidant activity of the tocopherol isomers in vivo is a > b > g > d which is due to the methylation pattern and the amount of methyl groups attached to the phenolic ring of the polar head structure. Hence, a-tocopherol with its three methyl substituents has the highest antioxidant activity of tocopherols. Though antioxidant activity of tocotrienols vs. tocopherols is not frequently studied, a-tocotrienol is proven to be a better antioxidant than a-tocopherol in a membrane environment. Tocopherols,

24

2  Activation of Oxygen: Multipurpose Tool CH3 HO CH3 H3C

CH3

CH3

CH3 CH3

O CH3 R

HO

1

CH3

R 2

CH3

CH3

O R 3

CH3

CH3

Fig. 2.9  Structures of a-tocopherol (above) and of tocotrienols (below)

synthesized only by plants and algae, are found in all part of plants. Chloroplast membranes of higher plants contain a-tocopherol as the predominant tocopherol isomer and are hence well protected against photooxidative damage. Vitamin E is a chain-breaking antioxidant, i.e. it is able to repair oxidizing ­radicals directly, preventing the chain propagation step during lipid autoxidation. It reacts with alkoxy radicals (LO•), lipid peroxyl radicals (LOO•), and with alkyl ­radicals (L•), derived from PUFA oxidation. The reaction between vitamin E and lipid radical occurs in the membrane-water interphase where vitamin E donates a ­hydrogen ion to lipid radical with consequent tocopheroxyl radical (TOH•) formation. Regeneration of the TOH• back to its reduced form can be achieved by ascorbate, reduced glutathione, or coenzyme Q (Blokhina et al. 2003; Gill and Tuteja 2010). More details are presented below when LPO and repair mechanisms are presented. Phenolic Compounds Phenolics are diverse plant secondary metabolites (flavonoids, tannins, hydroxycinnamate esters, and lignin) abundant in plant tissues. Polyphenols possess ideal ­structural chemistry for free radical scavenging activity, and they are more effective antioxidants in  vitro than tocopherols or ascorbate. Antioxidative properties of ­polyphenols arise from their high reactivity as hydrogen or electron donors, from the ability of the polyphenol-derived radical to stabilize and delocalize the unpaired electron (chain-breaking function), and from their ability to chelate heavy metal ions (termination of the Fenton reaction). Moreover, phenolic compounds can be involved in the hydrogen peroxide scavenging cascade in plant cells (Blokhina et al. 2003). Proline Proline (Fig. 2.10) is a non-essential a-amino acid, one of the twenty DNA-encoded amino acids. It is unique among the 20 protein-forming amino acids in that the a-amino

2.2  Activation of Oxygen in Organisms

25

Fig. 2.10  Structure of proline

O OH N H

HN

N O

HO HO

OH CH3 HO

NH

HO

O

CH3

NH

OH OH

OH OH

Fig. 2.11  Structures of palythine (left) and porhyra (right), two of 20 mycosporine-like amino acids

group is secondary. Only recently, its general antioxidant property in plants (Reddy et al. 2004; Sharma and Dietz 2006), fungi (Chen and Dickman 2005), and animals has been recognized (Krishnan et al. 2008). Krishnan et al. (2008) conclude that proline metabolism is more pivotal in maintaining redox homeostasis than previously thought. Polysaccharides Inspecting the highly diverse groups of freshwater and marine algae in terms of antioxidant substrates, several unexpected compounds can be identified. For instance, the cells of the red microalga Porphyridium are encapsulated within a sulfated polysaccharide whose external part (i.e., the soluble fraction) dissolves into the medium. Tannin-Spitz et al. (2005) showed that the main function of the polysaccharide is to protect the algal cells from oxidative stress. Mycosporine-Like Amino Acids and Phlorotannins Mycosporine-like amino acids (Fig.  2.11) and phlorotannins (Fig.  2.12) and have attracted scientific interest particularly as so-called sun-screens (UV-absorbing compounds) in benthic micro- and macro-algae as well as in copepod zooplankton (Tartarotti et al. 2004; Karsten et al. 2009). Mycosporine-like amino acids are characterized by a cyclohexenone or cyclohexenimine chromophore conjugated with one or two amino acids (Fig. 2.12) that absorb UV irradiation in the wavelength range 310– 365 nm. As early as in 1995, Dunlap and Yamamoto identified the antioxidative property of mycosporine-glycine. Evidence is now accumulating that mycosporine-like amino acids, in general, may serve as antioxidant molecules scavenging ROS ­following salt stress, desiccation, or thermal stress (Oren and Gunde-Cimerman 2007).

26

2  Activation of Oxygen: Multipurpose Tool

Fig. 2.12  Structure of one phlorotannin

OH

OH OH

O O

HO

O

OH

HO

In brown algae, phlorotannins (polymers of phloroglucinol and 1,3,5-trihydroxy­ benzen) play a series of roles as plant secondary metabolites that are mainly associated with anti-herbivory defense, antifouling activity, and antioxidant activity. In a recent paper, Huovinen et al. (2010) studied the impact of UV irradiation on the physiological photosynthetic activity, content, and antioxidant activity of phlorotannins in three large kelps Macrocystis pyrifera, Lessonia nigrescens, and Durvillaea antarctica. In general, the antioxidant activity was related to the concentration of soluble phlorotannins, particularly in Lessonia. Lipid Peroxidation Lipid peroxidation (LPO), primarily of the phospholipids of cell membranes, is one of the few examples of carbon-centered radical production. The idea of LPO as a solely destructive process has recently changed, since lipid hydroperoxides and oxygenated products of lipid degradation as well as LPO initiators (i.e. ROS) can participate in the signal transduction cascade (Blokhina et  al. 2003). LPO can be divided into three stages: initiation, propagation, and termination. The initiation phase includes activation of O2 and is mainly mediated by • OH . PUFAs, the main components of membrane lipids, are susceptible to peroxidation. LPO in cells can also be initiated by the enzymes of the lipoxygenase family which catalyze the dioxygenation of PUFAs in lipids. A scheme of lipid peroxidation and repair is displayed in Fig. 2.13. Protein Carbonylation Carbonylation of proteins, that is the appearance of carbonyl groups, such as aldehyde or ketone groups, is an irreversible oxidative damage, often leading to a loss of protein function, which is a widespread indicator of severe oxidative damage. Whereas moderately carbonylated proteins are degraded by the proteasome system, heavily carbonylated proteins tend to form high-molecular-weight aggregates that are resistant to degradation and accumulate as damaged or unfolded proteins. Such aggregates of carbonylated proteins can inhibit proteasome activity (Dalle-Donne et al. 2006). As a biomarker of oxidative stress, protein carbonylation is often, but

2.2  Activation of Oxygen in Organisms

27

Fig. 2.13  Membrane lipid peroxidation. (a) Initiation of the peroxidation process by an oxidizing radical X•, by abstraction of a hydrogen atom, thereby forming a pentadienyl radical. (b) Oxygenation to form a peroxyl radical and a conjugated diene. (c) Peroxyl radical moiety partitions to the water-membrane interface where it is posed for repair by tocopherol. (d) Peroxyl radical is converted to a lipid hydroperoxide, and the resulting tocopherol radical can be repaired by ascorbate. (e) Tocopherol has been recycled by ascorbate; the resulting ascorbate radical can be recycled by enzyme systems. The enzymes phospholipase A2 (PLA2), phospholipid hydroperoxide glutathione peroxidase (PH-GPx), glutathione peroxidase (GPx) and fatty acylcoenzyme A (FA-CoA) cooperate to detoxify and repair the oxidized fatty acid chain of the phospholipid (From Buettner 1993, with permission from Elsevier)

not always, more sensitive than LPO as shown with eelpout, Zoarces viviparous, exposed to bunker oil (Fig. 2.14) (Almroth et al. 2005): At least plants distinguish between different sources of activated oxygen ROS play a central role in the defense of plants against pathogen attack. During this response, ROS are produced by plant cells via the enhanced enzymatic activity of plasma-membrane-bound NADPH oxidases, cell-wall-bound peroxidases, and amine

28

2  Activation of Oxygen: Multipurpose Tool

Fig. 2.14  Exposure of eelpout to bunker oil. (a) Thiobarbituric acid reactive substances (TBARS) (indicative of lipid peroxidation) and (b) protein carbonyls in livers. Letters (a–c) indicate statistical difference between treatment groups, p < 0.05. Columns with identical letters do not significantly differ from each other (From Almroth et  al. 2005, with permission from Elsevier). The dosages refer to bunker oil

oxidases in the apoplast. H2O2 produced during this response (up to 15 mM; directly or as a result of superoxide dismutation) is thought to diffuse into cells and, together with salicylic acid (SA) and NO, to activate many of the plant defenses, including programmed cell death. The activity of APX and CAT is suppressed ­during this response by the phytohormones SA and NO, the production of APX is post-­transcriptionally suppressed, and the production of CAT is down-regulated at the level of steady-state mRNA. Thus, the plant simultaneously produces more ROS and at the same time diminishes its own capacity to scavenge H2O2, resulting in the over-­accumulation of ROS and the activation of programmed cell death. The suppression of ROS-scavenging mechanisms together with the synthesis of NO appears to be crucial for the activation of programmed cell death because, in their absence, increased ROS production at the apoplast does not result in the induction of p­ rogrammed cell death.

2.2  Activation of Oxygen in Organisms

29

Fig. 2.15  Differences in the steady-state levels of reactive oxygen intermediates (ROS) during biotic stress and abiotic stress. Biotic stress (a) results in the activation of NADPH oxidase and the suppression of ascorbate peroxidase (APX) and catalase (CAT). This leads to the over-accumulation of ROS and the activation of defense mechanisms. Abiotic stress (b) enhances ROS ­production by chloroplasts and mitochondria. However, by inducing ROS-scavenging enzymes such as APX and CAT, it reduces ROS levels. The question mark indicates that little is known about the regulation of ROS metabolism during a combination of biotic and abiotic stresses. Chloroplasts are indicated in green, mitochondria in gray and the steady-state levels of ROS in yellow (From Mittler 2002, with permission from Elsevier)

The role ROS play during programmed cell death appears, therefore, to be o­ pposite to the role they play during abiotic stresses, during which ROS induce ROS-scavenging mechanisms such as APX and CAT that decrease the steady-state level of ROS in cells (Fig. 2.15) (Mittler 2002). The differences in the function of ROS between biotic and abiotic stresses might result from the action of hormones such as SA and NO, from cross-talk between different signaling pathways, or from differences in the steady-state level of ROS produced during the different stresses. The differentiation of plants between abiotic and biotic challenges results in different defense reactions (Fig. 2.16) (Kotchoni and Gachomo 2006): abiotic stressors induce a specific set of abiotic stress-resistance genes, activate specific ionic pumps, induce the production of osmolytic compounds, sequesters toxic molecules into compartmental vesicles, adjusts osmosis, and activates protein phosphorylation and dephosphorylation pathways. The consequences are modulations of root development and gravitropism, stomatal closure and eventually a comprehensive abiotic stress tolerance, including cross-tolerance (see Chap. 12). In contrast, biotic stressors induce a specific set of defense genes against pathogen infections, production of antimicrobial compounds, activation of transcription factors and specific protein phosphorylation and dephosphorylation, and re-enforcement of the cell wall. The results are cell protection in the form of resistance of host cells to pathogen infection, including programmed cell death (PCD). The apparent conflict in ROS metabolism between biotic and abiotic stresses (Fig. 2.15) raises the question of how the plant manipulates its rate of ROS production and ROS scavenging when it comes under biotic attack during an abiotic stress.

30

2  Activation of Oxygen: Multipurpose Tool

Wounding

Heavy metals

Viruses Bacteria

Salt

Fungi

Heat

Pathogen elicitors

Cold

Nematodes

Ozone

UV irradiation Light

II

I

I‘

II‘ II‘

Cellmembrane Cell membrane

ROS

Drought

Insects

Plant cell

I

Induction of specific set of abiotic stress resistance genes, activation of specific ionic pumps, production of osmolytic compounds, sequestration of toxic molecules into compartmental vesicles, osmotic adjustments, activation of protein phosphorylation and dephosphorylation pathways

II

Root development, gravitropism, stomatal closure, abiotic stress tolerance

I‘

Induction of specific set of defense genes against pathogen infections, production of antimicrobial compounds, activation of transcription factors and specific protein phosphorylation and dephosphorylation, re-enforcement of cell wall

II‘ II‘

Defense/Cell protection, resistance of host cells to pathogen infection, programmed cell death (PCD)

Fig. 2.16  Involvement of ROS (including NO) in cellular metabolic processes of plant response to various abiotic and biotic environmental stresses. I and II indicate the subsequent downstream events mediated by ROS in plant cells exposed to abiotic stresses, while I’ and II’ indicate the subsequent downstream events mediated by ROS in plants cells exposed to pathogens and pathogen-elicitors. The resistance of the plant cells to the stress condition is dependent on the intensity and the speed of these downstream events (From Kotchoni and Gachomo 2006, courtesy of the Indian Academy of Sciences)

In support of the possible existence of such a conflict, tobacco plants that were subjected to oxidative stress (and consequently had a higher level of antioxidative enzymes) had a reduced rate of programmed cell death compared with unstressed control plants (Mittler et al. 1999). In addition, plants that overproduce CAT have a decreased resistance to pathogenic infection (Polidoros et al. 2001). The ecological significance of the plant’s fight against pathogens and parasites is covered in the Chap. 3.

2.3  Oxidative Stress

31

2.3  Oxidative Stress Table 2.2 lists selected papers, which show an oxidative stress after the impact of different environmental stressors on various organisms. The term “oxidative stress” is used for states where the balance between generation and elimination of ROS is Table 2.2  Selected studies of oxidative stress induced by different environmental stressors Environmental stressor References Comprehensive review Lushchak (2011) Heat Lesser (1996); Butow et al. (1998); Nedelcu et al. (2004); Mahan and Mauget (2005); Bagnyukova et al. (2007); Locato et al. (2008); Mahan et al. (2009); Gür et al. (2010) Cold Mahan and Mauget (2005); Vogel et al. (2005); Streb et al. (2008); Mahan et al. (2009); Ibarz et al. (2010) Irradiation, incl. UV Dunlap and Yamamoto (1995); Lesser (1996); Alexieva et al. (2001); Lascano et al. (2003); Tartarotti et al. (2004); Streb et al. (2008); Janknegt et al. (2009); Huovinen et al. (2010); Zhang et al. (2010a) Radiofrequency irradiation Tkalec et al. (2007) Ozone Sharma and Davis (1994); Sharma et al. (1996); Fares et al. (2010) Ammonia Ching et al. (2009) Metals, metalloids van Bogelen et al. (1987); Brennan and Schiestl (1996); Babai and Ron (1998); Ferianc et al. (1998); Rijstenbil and Gerringa (2002); Tamás et al. (2006); Streb et al. (2008); Tamás et al. (2008); Ahsan et al. (2009); review by Franco et al. (2009); Lushchak et al. (2009); Małecka et al. (2009); Piotrowska et al. (2009); Radić et al. (2009); Ríos et al. (2009); Szivák et al. (2009); Wang and Song (2009); Vasylkiv et al. (2010); Khan et al. (2011) Menzel et al. (2005b); Timofeyev et al. (2006a, b); Kamara and Natural xenobiotics: plant Pflugmacher (2007); summarized in Saul et al. (2009); polyphenols, humic Anastasiadi et al. (2010); Bedulina et al. (2010a) substances Natural xenobiotics: Vardi et al. (2002); Bláha et al. (2004); Gehringer et al. (2004); cyanotoxins Pflugmacher (2004); Politycka and Bednarski (2004); Hu et al. (2005); Ou et al. (2005); Li et al. (2007b); Oracz et al. (2007); Pflugmacher et al. (2007); Yang et al. (2007); Bai et al. (2009); Hong et al. (2009); Persson et al. (2009); Bártová et al. (2010) Synthetic xenobiotics, incl. Lascano et al. (2003); Dorval et al. (2005); Zabalza et al. (2007); pesticides Chagas et al. (2008); Bebianno and Barreira (2009); review by Franco et al. (2009); Lee and Choi (2009); Fernández et al. (2010); Hannam et al. (2010); Nesto et al. (2010) Almroth et al. (2005); Bocchetti et al. (2008); Ramos-Gómez et al. Complex exposures, (2008); Wang et al. (2008) contaminated sediments Flooding, hypoxia and Blokhina et al. (2001, 2003); Jackson and Colmer (2005); re-oxygenation Voesenek et al. (2006); Lushchak and Bagnyukova (2007); Colmer and Voesenek (2009); Hashiguchi et al. (2009); Sairam et al. (2009); Skutnik and Rychter (2009) Hyperoxia Lushchak et al. (2005) (continued)

32 Table 2.2  (continued) Environmental stressor Salinity Desiccation, drought

Physical activity/sedentary lifestyle Nutrients, food Nutrient-limited growth Demographic factors, population density Pathogens, parasites

Symbiosis Predation

2  Activation of Oxygen: Multipurpose Tool

References Jebara et al. (2005); Amako and Ushimaru (2009); Hashemi et al. (2010) Alexieva et al. (2001); Kranner et al. (2002); Esfandiari et al. (2008); Denekamp et al. (2009); Malik and Storey (2009); Smitha et al. (2009); Damanik et al. (2010); Iqbal and Bano (2010) Clarkson and Thompson (2000); Carmeli et al. (2007) Jensen and Hessen (2007); Guo and Xie (2010); Steinberg et al. (2010a) Lu et al. (2009); Zhang et al. (2010a, b) Hlaváčk et al. (2009) Weinberger and Freidlander (2000); Newton et al. (2004); Evans et al. (2006); Ferreira et al. (2006); Luhová et al. (2006); Tománková et al. (2006); Cosse et al. (2007); Albrecht and Bowman (2008); Cerenius et al. (2008); Wang et al. (2008); Green et al. (2009) Glyan’ko and Vasil’eva (2010); Nanda et al. (2010) Slos and Stoks (2008)

disturbed in favor of the former (Sies 1991; Blokhina et al. 2003). Clear indications of oxidative stress are accumulation of LPO products, protein carbonyls, or histological malformations.

2.3.1 Key Studies of Oxidative Stress To any environmental challenge, be it abiotic or biotic, exposed aerobic organisms respond by activation of oxygen. This will be exemplified with selected examples of contrasting environmental triggers. 2.3.1.1 Heat Stress Terrestrial Plants Heat stress is particularly common and dangerous for plants as they lack metabolic mechanisms for thermic homeostasis and need light energy, which is accompanied by temperature increases in the exposed tissues. Plant survival under heat stress requires the activation of proper defense mechanisms in order to avoid the damage of metabolic machineries. For instance, Locato et al. (2008) studied the alteration of several redox parameters and the changes in the activity or expression of the enzymes

2.3  Oxidative Stress

33

involved in ROS scavenging after cell exposure to two different heat stress ­conditions: a heat shock inducing programmed cell death, and a more moderate heat shock, determining a redox impairment without affecting cell viability. Under moderate heat shock, redox homeostasis was mainly guaranteed by an increase in GSH content and in APX and CAT activities. On the other hand, the heat shock-induced programmed cell death caused an increase in the activity of the enzymes recycling the ascorbate- and GSH-oxidized forms and a reduction of APX, whereas CAT decreased only after a transient rise of its activity, which occurs in spite of a decrease of its gene expression. Overall, enzyme-dependent ROS scavenging is enhanced under moderate heat shock and suppressed under heat shock-induced programmed cell death. Moreover, the APX suppression occurring very early during programmed cell death could represent a hallmark of cells that have activated a suicide program. Phytoplankton With lake phytoplankton, Butow et  al. (1998) proved that the above mentioned symptoms of oxidative stress are not restricted to individuals or populations, but also apply to communities. Higher temperatures caused increased LPO in phytoplankton communities, but this appeared to be greatly augmented by carbon limitation. It is interesting to note that, although carbon limitation induced increased CAT activity, increased temperature reduced it, allowing for the substantial rise in LPO. Fishes In ectothermic animals, an increase of environmental temperature which leads to metabolic activation and increased oxygen consumption initiates so-called oxidative stress. Little is known about oxidative stress in fish exposed to heat shock. Studies in this area mainly examine HSP induction and characterization in fish cell culture or whole organisms under different stressful conditions or physiological adaptations and gene expression during thermal acclimation to lower or higher temperatures. Adaptations of temperature-tolerant species are of a particular interest (Lushchak and Bagnyukova 2006). These authors studied heat shock and recovery in the goldfish, Carassius auratus auratus, including changes in levels of oxidatively damaged proteins and lipids, thiol content, and activities of antioxidant enzymes. Particularly, SOD was affected strongly by heat shock and recovery. LPO products in brain and liver did not occur during short-term exposures but did occur during long-term exposures. Unexpectedly, levels of LPO products in the liver rose again during recovery. Gammarids Physically and chemically stable environments, such as deep-water layers of oceans or lakes, do obviously not provide environmental triggers for their inhabitants to

34

Lipophilic antioxidant capacity nmol/mg fresh weight

2  Activation of Oxygen: Multipurpose Tool

0.4 0.3

*

0.2

*

*

*

0.1

*

0.0 Control

0.5h

1h

3h

6h

12h

Fig. 2.17  Decreasing antioxidant capacity of the lipophilic fraction in the oligostenothermic Baikalian gammarid, Ommatogammarus flavus, exposed to 20°C (Sapozhnikova, Timofeyev, and Steinberg unpublished; photograph credit VV Pavlichenko). * indicates statistically significant differences from controls

develop easily inducible defense responses. Consequently, any change in the ­environment of such organisms should result in severe stress symptom. To test this hypothesis, the Baikalian deep-water gammarid, Ommatogammarus flavus, was exposed to 20°C – a clear thermal stress to this animal. O. flavus inhabits depths up to 1,300 m with its population maximum in depths >100 m (Bazikalova 1945). Figure 2.17 shows that the increased temperature immediately leads to decreases in the antioxidant capacity as exemplified with the membrane-bound fraction. In a previous study, Timofeyev and Steinberg (2006) showed that the antioxidant enzymes did not respond properly in this oligostenothermic species so that the oxidative stress obviously attacks immediately the membranes and decreases its stress resistance. 2.3.1.2 Ozone Ozone in the lower atmosphere is an air pollutant with harmful effects on the respiratory systems of animals, and it will burn sensitive plants. As a mechanism for ozone-elicited damages, the generation of ROS by ozone degradation in the apoplast has been proposed. The primary site of ozone interaction with plant cells is the extracellular matrix where ozone challenges the antioxidant protection of the cells. Accordingly, ozone sensitivity generally correlates with the ascorbate status of the apoplast. In addition, ozone-sensing takes place by covalent modification of redox-sensitive components of the plasma membrane, for example in ion channels like the plasma membrane Ca2+-channels. Subsequent intracellular signal transduction is an intriguing network of hormone, Ca2+, and MAPK signaling pathways. Comparison of recent transcriptome analysis revealed that in addition to genes

2.3  Oxidative Stress

35

generally induced by all kinds of oxidative stress, approximately one-third of the responsive ­transcripts are ozone-specific, indicating jasmonic acid (JA), SA, and ethylene-independent redox signaling triggered by extracellular redox sensing (Baier et al. 2005). In a recent study, Fares et al. (2010) showed that a metabolic shift towards phenolics with higher antioxidant capacity was observed in ozoneexposed poplar leaves. 2.3.1.3 Anoxia and Re-oxygenation of Plant Roots Oxygen status of cells and tissues depends on environmental conditions of oxygen supply. Under flooding, which occurs during storm events, the root system is the plant organ most susceptible to oxygen deprivation. Membrane lipids undergo changes under anoxia, which may be considered adaptive, and which may result in the acceleration of lipid peroxidation after restoration of the oxygen supply. Particularly, this aspect has been the focus of the study by Blokhina (2000). She documents that re-oxygenation caused injury to membrane lipids, indicated by the presence of LPO products. Interestingly, wheat was anoxia-intolerant and contained higher amounts of LPO products than did more tolerant rice which adapted to flood events. 2.3.1.4 CO2 Limitation in Phytoplankton and High pH-Values During heavy blooms of phytoplankton, dissolved CO2 may temporarily limit primary production and exert an environmental stress on the phototrophs. The primary proof of an internal oxidative stress has been provided by Butow et al. (1998) who checked the activity of antioxidant enzymes and LPO products in field populations and laboratory studies of the dinoflagellate, Peridinium gatunense. The studies demonstrated that the increase in CAT activity was not directly due to increasing environmental pH. Vardi et al. (1999) confirmed the findings showing that depletion of dissolved CO2 stimulated formation of ROS and induced cell death in both natural and cultured P. gatunense populations (Fig. 2.18). Conversely, addition of CO2 prevented ROS formation. Since CAT inhibited cell death in culture, the authors concluded that H2O2 was the active ROS. Intracellular ROS accumulation induced protoplast shrinkage and DNA fragmentation prior to cell death. It is plausible that CO2 limitation resulted in the generation of ROS to a level that induced programmed cell death, which resembles apoptosis in animal and plant cells. Interestingly, Vardi et al. (1999) showed that P. gatunense cells”have the choice” to die or to form cysts. Cell death could be blocked by a cysteine protease inhibitor, which stimulated cyst formation. This finding can be interpreted in terms of evolution, since it is reasonable to assume that by allowing only the best-adapted individuals to establish cysts, less healthy members of the community will be eliminated. Hence, programmed cell death confers a selective advantage to a population during subsequent seasons.

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Fig. 2.18  Cell death and accumulation of ROS in Peridinium gatunense. (a) The percentage of ROS-positive cells during the winter–spring bloom in Lake Kinneret. Cells were collected from a depth of 3 m, between 8:00 a.m. and 10:00 a.m. during the 1998 season, and analyzed by epifluorescent microscopy of representative fields (450–600 cells per data point). The inset shows a ­representative image of P. gatunense stained with dihydrorhodamine 123. The red color is due to the autofluorescence of the chlorophyll, whereas yellow or green indicates ROS-containing cells. Video monitoring showed that cells emitting green fluorescence were swimming, albeit slower than the unstressed ones. As the ratio of orange and green colored cells was fairly constant their values were combined. The absolute values varied between experiments, depending on light intensity and the starting inoculum, but similar relative values were obtained in three independent experiments. (b) The percentage of ROS-positive (grey bars) and dead (white bars) cells in batch cultures. Cell death was assayed with Syntox (the inset shows a stained nucleus in the right-hand cell). The graphs show typical progressions in the numbers of ROS-positive and Syntox-positive cells during growth. The exact timing of change in these parameters varied between experiments and depended on light intensity. The line in (b) shows the dissolved CO2 concentration in the growth medium (From Vardi et al. 1999, with permission from Elsevier)

2.3.1.5 Natural Xenobiotics: Humic Substances Humic substances (HSs) are ubiquitous biogeochemicals with diverse chemical ­functionality that dominate the dissolved organic matter pool in most aquatic ecosystems. Nevertheless, they historically have been considered inert to aquatic organisms. However, as shown in the last decade, HSs are taken up by organisms and induce ­typical (mild) stress responses. In a pioneering study, Timofeyev et al. (2006b) showed that Baikalian gammarids respond very sensitively to HSs from distant locations

nM dienic conjugates/mg protein

2.3  Oxidative Stress

37

1400 1200 1000

0.6 mmol L-1 DOC

E. cyaneus

1.2 mmol L-1 DOC

800 600 400 200 0 control

0.5 h

2h

6h

24 h

3d

6d

Exposure time

Fig. 2.19  Lipid peroxidation products in the cytosol of Eulimnogammarus cyaneus on exposure to natural organic matter (NOM) of Lake Schwarzer See, Brandenburg State, Germany (From Timofeyev et al. 2006b, with permission from Elsevier; photograph credit VV Pavlichenko)

Fig. 2.20  Development of internal H2O2 and lipid peroxidation, measured as diene conjugates, in Gammarus lacustris exposed to 1.2  mM NOM of Lake Schwarzer See, Brandenburg State, Germany (From Steinberg et  al. 2008b, with permission from Springer; photograph credit VV Pavlichenko). * indicates statistically significant differences from controls. Note: Lipid peroxidation starts before free H2O2 accumulates in the tissues

(Fig.  2.19). A higher exposure concentration induced an earlier and longer lasting LPO. However, the animals seem to have means to overcome the oxidative stress, since the amount of LPO product decreased with time; the LPO product decreased earlier and more clearly in lower HS exposure concentration than in the higher one. In addition, the Palearctic species, Gammarus lacustris, responded with oxidative stress upon exposure to the same humic substances as the Baikalian species did. Figure 2.20 shows furthermore that, at least in this specific case, LPO started clearly

38

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before free H2O2 accumulated, implying that G. lacustris may utilize LPO as an antioxidative defense. 2.3.1.6 Metals, Such as Cu Copper toxicity is caused by uptake of its bioavailable fraction in cells. Cupric ions block and reduce thiol sites on proteins and catalyze the production of ROS that initiate LPO chain reaction. In a continuous culture experiment, Rijstenbil and Gerringa (2002) showed that the toxic effects of Cu in the marine diatom Ditylum brightwellii can be traced by measuring the decreasing contents of glutathione and the increasing contents of LPO products. 2.3.1.7 PAR and UV Irradiation Marine Microalgae Marine microalgae typically experience fluctuating irradiance conditions due to cooccurring changes in intensity of incoming irradiance (daily and seasonally), cloud coverage and their changing position in the water column. Janknegt et al. (2009) investigated the photoacclimation properties in two marine microalgae, Thalassiosira weissflogii and Dunaliella tertiolecta. Both species showed immediate antioxidant responses (indicated by a reduced glutathione redox status, Fig. 2.21) due to their transfer to the outdoor conditions. Furthermore, upon outdoor exposure, carbon assimilation and growth rates were reduced in both species compared with initial conditions; however, these effects were most pronounced in D. tertiolecta. Outdoor UV exposure did not alter antioxidant levels when compared with PAR-only controls in both species. In contrast, growth was significantly affected in the static UVR cultures, concurrent with significantly enhanced UVR resistance. This study confirmed that antioxidants play a minor role in the reinforcement of natural UVR resistance in T. weissflogii and D. tertiolecta. Marine Ectotherms Very recently, Dahms and Lee (2010) reviewed major effects of UV on selected marine ectotherms. For instance, Antarctic fish, possess an elevated content of polyunsaturated fatty acids (PUFA) in the plasma membrane that ensure membrane fluidity at low temperatures as one adaptation to permanently cold conditions. Yet, a higher PUFA content may place Antarctic fish at an elevated risk of UV-induced oxidative stress, because PUFAs are primary targets for ROS. Furthermore, oxidative stress plays a role in apoptosis or programmed cell death by activation of p53, a cell cycle checkpoint that allows a multicellular organism to

2.3  Oxidative Stress

39

Fig. 2.21  Antioxidant responses of Dunaliella tertiolecta and Thalassiosira weissflogii. (a, b) Glutathione reductase (GR) activity. (c, d) Cellular amount of glutathione and (e, f) glutathione redox status (GRS). Immediate: cultures exposed for 1 day (from sunrise till 5:00 P.M.) to outdoor irradiance conditions. Short term: cultures exposed for 3 days to outdoor irradiance conditions. Long term: cultures exposed to outdoor irradiance during the 4 subsequent days. Bars show mean values of three (Immediate and Short term) or four (Initial and Long term) replicates, error bars represent SDs. *Differs significantly from the initial value (p < 0.05); adiffers ­significantly from the previous exposure period (p < 0.05); bdiffers significantly from the other irradiance conditions within the same exposure period (p < 0.05) (From Janknegt et  al. 2009, with permission from Wiley)

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repair or destroy cells exposed to agents that cause DNA damage. The UV-mediated production of ROS damages DNA and activates the p53 pathway. The latter allows affected cells to undergo DNA editing and repair. In Atlantic cod larvae, for instance, the expression of p53 increased significantly after exposure to UV and oxidative stress, resulting in apoptosis and potentially the death of the developing embryo. The enhanced expression of p53 not only delayed cell division and the total number of cells a larva may have, but it also decreased the amount of time that repaired cells have to grow in the context of a temporally-fixed developmental program. Activation of the p53 pathway, if it does not lead to apoptosis and larval mortality, may therefore result in smaller size at hatching as observed for cod larvae exposed to UV. For those larvae that survive the effects of UV at the biochemical and molecular levels, there is an energetic cost at the organismal level. The sublethal energetic costs of repairing DNA damage or responding to oxidative stress may result in poor growth performance (see also Chap. 13). The small, but significant, decrease in size at hatching observed may result in a longer planktonic persistence of these fish and increase the probability of death due to predation. 2.3.1.8 Synthetic Xenobiotic Chemicals From the many available studies of xenobiotic-induced oxidative stress, those with polycyclic aromatic hydrocarbons (PAHs) are of particular interest due to the extreme oil spill in the Gulf of Mexico in 2010. PAHs are a ubiquitous class of organic contaminants found throughout the marine environment, with the majority of inputs arising from anthropogenic sources. Natural constituents of crude oil at around 19,000  mg  kg−1, PAHs are both toxic and biologically persistent. PAH ­concentrations in excess of 1.5 mg l−1 have been reported in seawater following an accidental blowout of an offshore oil platform and from oil spills (Hannam et al. 2010). Phenanthrene, a major component of crude oil, is one of the most abundant PAHs in aquatic ecosystems and is readily bioavailable and toxic to a range of marine invertebrates, such as bivalves. Hannam et al. (2010) determined the sublethal effects of phenanthrene on several oxidative stress parameters in the hemolymph of the commercially-important scallop Pecten maximus. Phenanthrene exposure resulted in oxidative stress with a significant decrease in total GSH and significantly increased levels of LPO in the hemolymph. 2.3.1.9 Manufactured Nanoparticles The fullerenes, one type of manufactured nanoparticles, are lipophilic and localize into lipid-rich regions such as cell membranes in vitro, and they are redox active. Other nano-sized particles and soluble metals have been shown to selectively ­translocate into the brain via the olfactory bulb in mammals and fish. The question arose of whether a redox-active, lipophilic molecule could cause oxidative damage in an aquatic species. The goal of the pioneering study by Oberdörster (2004) was to

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Fig. 2.22  Lipid peroxidation of brain, gill, and liver of largemouth bass (Micropterus salmoides) after 48 h of exposure to 0.5 or 1 ppm nC60. Lipid peroxidation was indirectly measured by monitoring the production of MDTA from the oxidation of malondialdehyde: (a) Aquarium averages. Heavy black bands represent the means; thinner lines indicate medians; boxes represent 25th and 75th percentiles; error bars indicate minimum and maximum **p < 0.01 (From Oberdörster 2004; courtesy of the National Institute of Environmental Health Sciences)

investigate oxyradical-induced lipid and protein damage, as well as impacts on total GSH levels, in ­largemouth bass (Micropterus salmoides) exposed to fullerenes. Significant lipid peroxidation was found in brains of bass after a 48 h exposure to 0.5 parts per million (ppm) (Fig. 2.22). GSH was also marginally depleted in gills of fish. This was the first study to show that uncoated fullerenes can cause oxidative damage and depletion of GSH in vivo in an aquatic species and that these particles can pass the blood-brain barrier – usually characteristic of low-molecular weight dissolved chemicals. In C. elegans exposed to silver nanoparticles, Roh et al. (2009) found a clear induction of the SOD3 (mitochondrial Mn-SOD) and DAF-12 genes, indicating that oxidative stress was the major mode of action combined with a dramatically decreased reproduction potential. DAF-12 encodes a nuclear receptor regulating dauer ­formation. Being metallic nanoparticles, a specific response could be expected. In fact, the upregulation of MTL-2 (metallothionein gene), but not of MTL-1 was observed. A closer look at the potential regulatory pathway showed that the adverse mechanisms appeared to be even more fundamental. Steinberg et al. (2011) determined that ­protein formation and conformation in the endoplasmic reticulum (ER) were affected. The ER is a eukaryotic organelle that forms an interconnected network of tubules, vesicles, and cisternae within cells. Besides the interference in the ER, ion ­homeostasis also was disturbed because the corresponding genes are down-regulated.

2.3.1.10 Mechanical Stress – Injury Wound repair represents a vital process that is essential for the survival of sessile coenocytic macroalgae, such as the giant unicellular chlorophyte Dasycladus ­vermicularis. Because no other cells assist or mediate in the organism’s response to injury, survival clearly is based on the individual cell’s ability to repair itself in an expeditious manner. Injury in a shallow water marine environment may arise from

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Fig. 2.23  Development of H2O2 in the giant unicellular chlorophyte Dasycladus vermicularis generated after injury. The concentration of H2O2 emitted into solution was calculated as mM H2O2 g FW−1 as shown in the ordinate (From Ross et al. 2005b, with permission from Wiley)

numerous causes, including strong surf action, sand abrasion, and grazing by a ­variety of predators, parasites, or epiphytes. Although multicellular organisms have the capability of producing regenerative tissue adjacent to a wound, unicellular algae must rely on an instantaneous sealing mechanism to avoid the loss of ­irreplaceable cytoplasmic contents. Ross et al. (2005a) described the initial events involved in the wound-healing process in D. vermicularis. The initial wound repair mechanism is based on a rapid gelling process. Ross et al. (2005b) also provided evidence for the onset of an oxidative burst that occurs at the site of injury initiated approximately 35–45 min post injury with increasing intracellular H2O2 levels (Fig. 2.23). This burst was coincident with the onset of peroxidase activity and subsequent browning and hardening of the wound plug – the scheme of stress response by Selye (1936) revisited. 2.3.1.11 Food Quantity and Quality In nature, food quality and quantity change temporally. Recently, Dissanayake et al. (2008) showed that nutritional status influences antioxidative status of adult shore crabs, Carcinus maenas. In the laboratory, crabs were either starved, given a restricted diet (fed on alternate days), or fully fed (fed each day). Adult shore crabs were relatively resistant to short-term (7 days) nutritional changes; after 14 days, however, starved crabs had significantly lower antioxidant status compared to crabs under both types of feeding regime. Food quality also affects the antioxidant status of organisms. Certain food quality is a stress and can increase respiration; this applies particularly to carbon-rich diets (Jensen and Hessen 2007). Although yeast is widely accepted as a suitable food, culturing Daphnia with yeast alone results in animals of clearly inferior condition (Goulden et al. 1982). This is mainly due to the resistance of the yeast cell wall to digestion, so the manno-protein layer that surrounds the yeast cell can obviously not be digested by Daphnia. To study gene transcriptional response to different food qualities, Steinberg et al. (2010a) supplied Daphnia magna with two diets

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(chlorococcal alga Pseudokirchneriella subcapitata and baker’s yeast) fed ad ­libitum and exposed it to an environmentally realistic concentration of humic substances. Exposure to humic substances caused a transcriptionally controlled stress response with CAT and HSP60. Furthermore, the exposure to humic substances reduced the antioxidant capacity. Yet, a much stronger oxidative stress is caused by feeding yeast, which reduced the antioxidative capacity to values of approximately 50% of the green algal diet. This reduction is most likely due Daphnia’s inability to digest the yeast cell wall. The authors assumed that the biochemical machinery in the gut continuously activated oxygen to cleave the yeast’s cell wall and thus reduced the antioxidative capacity of the animals. 2.3.1.12 Oxidative Stress Against Competitors In nature, the application of allelochemicals is widespread in order to manipulate the performance of competitors and predators or to combat parasites and pathogens in plants rather than in animals. This is simply because most plants are sessile and lack flight as an instantaneous avoidance tactic. Without doubt, the direct uptake of allelochemicals via consumption can impair the conditions of the consumers. This  aspect will be covered in Chap. 4. However, what about the effect of ­allelochemicals released into the environment? Are they effective at least against competitors? This question is intensely debated. Duke (2010), in reviewing the literature on released polyphenols as a means against competitors in terrestrial as well as aquatic systems, questions that there is any real proof of this assumption. Many papers are based on laboratory findings and do not adequately consider that upscaling is more than blowing up the dimensions. Allelochemicals, once released into the environment, are subject to environmental processes, which strongly alter their persistence: direct and indirect photodegradation in irradiated systems, hydrolysis, or adsorption onto solid surfaces reduce concentrations or availability of allelochemicals. Consequently, many laboratory studies applied allelochemicals at too high of an exposure concentration and therefore do not prove the general applicability of the allelochemistry hypothesis. Having this in mind, there is obviously only one convincing example of released allelochemicals being effective on competitors. Algal Toxins: Suitable Role Model of Allelopathy? From an ecological viewpoint, Lewis (1986) raised early fundamental concerns against allelopathy in the plankton system by pointing out some problems with the evolution of allelopathy as a competitive mechanism among plankton. In the dynamic water-column, nonproducers can also share the benefit from the production of a costly allelopathic compound. Accordingly, it is difficult to envisage the evolution of allelopathic traits among plankton that are continuously being mixed through turbulent motion and random swimming. With certain deduction, similar concerns also exist against potential allelopathic interaction between macrophytes

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and phytoplankton, a hypothesis that is discussed in terms of stabilizing the ­plankton dominated turbid states of shallow lakes (Scheffer 2004). In lakes and oceans, algal blooms cause a rise in pH-value, which alone may lead to oxidative stress and programmed cell death. If these blooms are comprised of harmful algae, which produce allelochemicals, it becomes challenging to separate both stressors from each other. An ecologically meaningful study published by Vardi et al. (2002) elucidated the reasons for annual variability in the composition of phytoplankton assemblages. The researchers showed that domination by the patch-forming dinoflagellate, P. gatunense, or alternatively a bloom of a toxic cyanobacterium, Microcystis sp., in Lake Kinneret was based on mutual densitydependent allelopathic interactions. Laboratory experiments confirmed the reciprocal, density-dependent inhibition of growth. Application of spent P. gatunense medium induced sedimentation and subsequently massive lysis of Microcystis cells within a short period of time, and sedimentation and lysis were concomitant with a large rise in the level of McyB, which is involved in toxin biosynthesis by Microcystis (Dittmann et al. 1997). P. gatunense responded to the presence of Microcystis by a biphasic oxidative burst and activation of certain protein kinases (Fig.  2.24). Blocking this recognition by MAP-kinase inhibitors abolished the biphasic oxidative burst and affected the fate (death or cell division) of the P. gatunense cells. Vardi et  al. (2002) proposed that patchy growth habits might confer enhanced defense capabilities, providing ecological advantages that compensate for the aggravated limitation of resources in the patch. Hence, cross-talk via allelochemicals may explain the phytoplankton assemblage in Lake Kinneret. The allelochemical effects were mutual. Hence, to examine the possibility that Microcystis recognized the presence of P. gatunense, Vardi et  al. (2002) applied spent P. gatunense medium on Microcystis cultures. This treatment resulted in loss of buoyancy of the Microcystis cells, followed by a rapid and massive lysis of the cells. Despite the substantial Microcystis cell death observed here, the level of McyB, detected in the remaining cells increased dramatically. The observation that spent P. gatunense medium caused lysis of the Microcystis cells and enhanced the cultures’ potential for toxin production may help to elucidate the biological role and regulation of microcystin production: in this case, there are doubtless allelochemicals to fight competitors. Less clear is the presumable allelochemical interaction of cyanobacteria in the northern Baltic Sea (Møgelhøj et  al. 2006; Suikkanen et  al. 2006). The original hypothesis that the reduction of certain eukaryotic phytoplankton species (mainly cryptophytes) in the presence of Nodularia spumigena or its toxin, nodularin, was based on allelochemical interactions could not be confirmed in subsequent papers. Instead, the presence of the cryptophyte, Rhodomonas salina, did not affect the production and excretion of nodularin by N. spumigena as described for the warfare in Lake Kinneret. Furthermore, addition of pure nodularin did not affect the growth of R. salina. Instead of allelopathic inhibition, the growth of the test algae was controlled by the pH level of the culture media and by the pH tolerance of each species involved (Møgelhøj et al. 2006). Because N. spumigena can elevate pH up to levels >10.0, it out-competes many phytoplankton species.

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Fig. 2.24  Induction of reactive oxygen species (ROS) formation in Peridinium gatunense by Microcystis. Green fluorescence indicates ROS-positive cells; the red images show chlorophyll autofluorescence. (a) Control cells. (b) Cells exposed to Microcystis (MG) for 0.5 h. (From Vardi et al. 2002, with permission from Elsevier)

Overall, except for the allelopathic warfare in Lake Kinneret plankton, no c­ onvincing example of allelochemical-mediated oxidative stress in plankton has been published. Babica et al. (2006) questioned even the often-claimed concept of microcystins as general allelochemicals, since only a limited number of studies described harmful effects of microcystins at concentrations that are typical for the environment. Even more general, Jonsson et al. (2009) showed in a meta-analysis of recent experimental marine work that, with few exceptions (direct cell-cell encounters, particularly of dinoflagellates), allelopathic effects were only significant at very high cell densities typical of blooms. Hence, there is no experimental support for allelopathy at pre-bloom densities, throwing doubts on allelopathy as a mechanism in bloom formation and succession. Actually, the allelopathy hypothesis appears to be a zero-hypothesis.

sdfsdf

Chapter 3

Defense Means Against Pathogens and Parasites: Reactive Oxygen Species

The rapid reductive activation of oxygen, the oxidative burst, is central when plants and animals defend themselves against invading bacteria, viruses, or fungi. This energy-demanding process and subsequent processes, such as sex reversal particularly in gammarids, have wide-reaching consequences for the host populations which shall be displayed by key examples especially from aquatic systems.

3.1 Defense in Plants 3.1.1 Spermatophytes Recognition of invading pathogens results in a coordinated activation of plant defense mechanisms. The oxidative burst, during which large amounts of H2O2 are generated at the cell surface, is one of the earliest responses of plant cells to attempted invasion of pathogenic microorganisms or in response to challenges by various elicitor molecules, including O3 . H2O2 generated during oxidative bursts under biotic stress has several effects (Bhattacharjee 2005): –– it may be directly microbiocidal –– it can mediate excess linking of cell wall polymers –– it induces the expression of protein-encoding genes involved in defensive and antioxidant processes –– it can induce programmed cell death, characteristic of hypersensitive reactions H2O2 plays two distinct roles in pathogenesis. One involves the restriction of pathogen growth, and the other involves the induction of phytoalexins and pathogenesis-related proteins, so-called PR proteins. H2O2 is a putative, selective signal for the induction of a subset of defense genes as shown by direct injection of H2O2 C.E.W. Steinberg, Stress Ecology: Environmental Stress as Ecological Driving Force and Key Player in Evolution, DOI 10.1007/978-94-007-2072-5_3, © Springer Science+Business Media B.V. 2012

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Fig. 3.1  A pictorial comparison of the two best characterized forms of induced resistance in plants, both of which lead to similar phenotypic responses (From Vallad and Goodman 2004. With permission from the Crop Science Society of America)

which enhances expression of PR genes, antioxidant enzymes, phytoalexins, and enhanced accumulation of the signaling SA. As yet, there are few data regarding intracellular signaling processes mediating H2O2 responses and oxidative stress that result in increased cytosolic Ca2+ . H2O2induced programmed cell death in soybean cultures depends on Ca2+ influx and protein phosphorylation. Mitogen activated protein (MAP) kinase is activated in response to a number of infectious conditions. However, it still remains unclear whether the activities of protein kinases are essential for H2O2-mediated programmed cell death and gene expression. Upon infection, plants develop first a local hypersensitive response (HR) and then subsequent systemic acquired resistance (SAR) and induced systemic resistance (ISR). ISR is distinct from SAR, because it does not involve the accumulation of pathogenesis-related proteins or SA but instead relies on pathways regulated by jasmonate and ethylene (Vallad and Goodman 2004). Both kinds of resistance are sketched in Fig. 3.1. Systemic acquired resistance, induced by the exposure of root or foliar tissues to abiotic or biotic elicitors, is dependent on the phytohormone salicylate (SA) and associated with the accumulation of pathogenesis-related (PR) proteins. Induced systemic resistance, induced by the exposure of roots to specific strains of plant growth-promoting rhizobacteria, is dependent on the phytohormones

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ethylene and jasmonate (JA), independent of salicylate, and is not associated with the accumulation of PR proteins or transcripts. However, both responses are intertwined molecularly, as demonstrated by their reliance on a functional version of the gene NPR1 in Arabidopsis thaliana. The early host responses following pathogen detection include changes in ion fluxes, activation of signaling pathways (especially kinase cascades), gross alteration of transcriptional profiles, generation of reactive oxygen species (ROS), and production of nitric oxide (NO). These immediate changes are subsequently followed by altered cellular activities with the recruitment of several hormones that then participate in defense. The typical outcome of these responses is programmed cell death of infected cells. This suite of defense responses is termed the HR. ROS are important signaling molecules that regulate the onset of HR cell death which is preceded by differential regulation of NADPH oxidase, PODs, SODs, and CYP-like and other similar proteins. There is a transient Ca2+ signature change upon infection with avirulent pathogens that is required for effective defense. Changes in ion fluxes are thought to activate several kinase cascades; for example, Ca2+ binding by calcium-dependent protein kinases triggers phosphorylation relays. These cascades are important for signal transduction during defense. ROS generated during the HR also induce expression of defense-related genes in addition to initiating the programmed cell death that is associated with the HR. ROS also probably increase cross-linking of the cell wall. The mitochondrial alternative oxidase, AOX, functions to limit ROS production and has also been implicated in hormone-induced resistance. However, the role of AOX in defense has not yet been clarified (Soosaar et al. 2005). In conjunction with ROS, the small molecule NO is required for pathogeninduced programmed cell death in the HR. NO also induces the expression of defense-related genes, although the virus-resistance function of some of these gene products is unclear. Following the HR, a secondary defense response, SAR, is activated. SA is produced during the HR and then appears later in uninfected tissues that are developing SAR. However, salicylic acid is not the systemic signal for SAR. Recent evidence indicates that the systemic signal might be lipid-derived. Salicylic acid is thought to play a fundamental role in SAR by inducing resistance to many pathogens, and it accumulates locally in pathogen-infected tissues of different species such as Arabidopsis, tobacco, and cucumber. SA bleeds out of the petioles of pathogen-infected leaves, and labeling studies have confirmed systemic transport of SA from pathogen-infected leaves. However, SAR can develop before SA levels rise in petioles of infected leaves. Recently, evidence was provided that methyl-SA, rather than SA, functions as the critical mobile signal (Heil and Ton 2008).

3.1.2 Macroalgae The hypersensitive response is not restricted to spermatophytes; in fact, similar responses are reported also from macroalgae, for instance the rhodophyte Gracilaria

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Fig. 3.2  Impact of various saccharides on the elimination of Flavoacterium-Cytophaga (top) from Gracilaria conferta and on the release of H2O2 by G. conferta (bottom) (From Weinberger and Freidlander 2000. With permission from Wiley)

sp., after exposure to specific oligosaccharides, a class of elicitor molecules. Certain oligosaccharides play a role as signaling agents in spermatophytes and rhodophytes. Weinberger and Freidlander (2000) tested the elicitation of G. conferta with oligoagars and showed a triggered release of H2O2 which was strong enough to eliminate up to 60% of the resident bacterial flora (Fig. 3.2). In fact, this physiological response of G. conferta as a defense response is comparable to the hypersensitive response of spermatophytes. Viruses are active components of the plankton community and potentially ­significant mediators of algal mortality. In particular, viruses can decimate microalgal blooms. Evans et al. (2006) conducted the first study to determine the effect of viral infection on the production of ROS in phytoplankton cells. Following pathogen recognition, some cells exhibit defense related oxidative bursts within hours and sometimes minutes of infection. Oxidative bursts serve a number of protective

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Fig. 3.3  Production of reactive oxygen species (H2O2) (left) and reduction in cell photochemical capacity (arbitrary units) (right) during viral infection of Emiliania huxleyi (Fom Evans et al. 2006. With permission from Wiley)

­functions including direct damage to the pathogen (De Gara et  al. 2003) and u­ ltimately the induction of programmed cell death, which limits the spread of the invading organism. In their pioneering study, Evans et al. (2006) showed that virally infected algae exhibited elevated levels of ROS production and photosynthetic processes were adversely affected. During viral infection, virally-induced cell lysis caused Emiliania huxleyi cell numbers to decline steadily in the infected cultures concomitant with the accumulation of viral particles, whereas control cultures grew normally. Furthermore, H2O2 concentrations in the infected cells increased strongly. Cell photosynthetic capacity levels fell to zero, indicating that photosynthesis was disrupted in infected cells (Fig. 3.3). Several aspects of this study deserve mentioning. First, the concentration of intracellular ROS and excretion of H2O2 after viral challenge was generally comparable with those observed in response to other stressors including elevated temperature and UV levels. This indicates that production of ROS is a general and primary defense against various stressors. Second, infection leads to a reduction of photosynthesis (Evans et al. 2006). This can best be explained as an avoidance reaction as discussed by Mittler (2002). Finally, in a subsequent study, Evans and Wilson (2008) showed that the ecological consequences of viral infection can be dramatic. The heterotrophic dinoflagellate Oxyrrhis marina, a major predator of E. huxleyi, preferentially fed on virus-infected individuals over their healthy counterparts.

3.1.3 Pathogens Modulate Community Structure In general, the presence of plants infested by parasites and pathogens can have ­profound adverse influences upon their individual hosts but positive influences upon the ecosystem. Following successful parasite attachment, hosts may exhibit

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reductions in both biomass accumulation and reproductive output. Some host ­species are significantly damaged by the presence of the parasite, while others possessing resistance or tolerance mechanisms are not affected. Consequently some species can be indirectly enhanced by parasite presence within a community. This means that in multi-species assemblages, parasitic plants can shift the relative species composition in favor of certain species or groups of species. The annual facultative root hemi-parasite Rhinanthus minor plays an important role in regulating grassland ecosystem structure and function by suppressing dominant grasses and allowing forbs (non-leguminous, perennial dicots) to proliferate, potentially increasing plant diversity (Cameron et al. 2005). Furthermore, R. minor can exert indirect effects on plant communities through increasing nitrogen availability in the soil and increasing soil nitrogen cycling. On the individual level, however, the impact even of an hemi-parasite can be detrimental. The parasite can influence the host both indirectly and directly. In terms of indirect effects, the parasite can influence its host by shifting the competitive balance between neighbors and by facilitation of resource cycling. Directly, the parasite can steal and compete for a host’s resources and/or adversely influence its host’s metabolic processes such as photosynthesis. This applies even to the aforementioned hemi-parasite, which has the potential to undertake some independent photosynthesis but is still reliant on its host for a significant proportion of its carbon and mineral nutrition.

3.2 Defense Response in Animals 3.2.1 Phagocytes Phagocytes are white blood cells that protect the body by ingesting (phagocytosing) harmful foreign particles, bacteria, and dead or dying cells. They are among the most important components of the innate immune response and are essential for fighting infections and for subsequent immunity. Phagocytes are important throughout the animal kingdom and are highly developed within vertebrates. Phagocytes occur in many species; some amoebae behave like macrophage phagocytes, which suggests that phagocytes appeared early in the evolution of life. Two of the most important antimicrobial systems of phagocytic cells are the NADPH phagocyte oxidase and inducible nitric oxide synthase (iNOS) pathways, which are responsible for the generation of •O2– and NO• radicals (Fang 2004). The importance of NO• in host defense has been appreciated only recently. One important biological role of NO• is as an antimicrobial effector molecule that is produced by phagocytic cells. In contrast to the NADPH phagocyte oxidase, iNOS activity is mainly regulated at the transcriptional level. Although phagocytes are typically induced to produce ROS immediately after a microbial stimulus, RNS production requires de  novo

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p­ rotein synthesis. Stimulation of microbial pattern-recognition receptors triggers signaling cascades that lead to iNOS transcription (Fang 2004).

3.2.2 Prophenoloxidase in Invertebrates Comparable to the HR in plants which encapsulates invading pathogens, invertebrate animals, especially arthropods, possess the so called melanization reaction which is a common response to parasite entry. Invertebrate animals lack true antibodies and hence an adaptive immune response. One innate defense is the production of antimicrobial peptides as a response to parasite entry. The production of these peptides is slightly delayed and will usually occur within a few hours after entry of a bacterium or fungus. Evidently, some sort of recognition of the foreign particle has to take place in order to transfer the message to the cells that will synthesize the appropriate immune factors, such as antimicrobial peptides. Recognition of foreign material is believed to occur through recognition molecules in the blood (hemolymph) of invertebrates. These induce activation of the prophenoloxidase-activating system (proPO-AS) and may also induce activation of other defense processes (Söderhäll and Cerenius 1998). The proPO-AS is an efficient, non-self recognition system in invertebrates that can recognize and respond to picograms per litre of lipopolysaccharides or peptidoglycans from bacteria and b-l,3-glucans from fungi. As a result of activation of the proPO-AS, the parasite is blackened in the host hemolymph by the deposition of melanin due to the action of phenoloxidase, an oxidoreductase. This reaction is called the melanization reaction and is easily observed around parasites in the hemolymph or the cuticle. The proPO-AS consists of several different proteins among which are proteinases, proteinase inhibitors, and recognition molecules that recognize structural features of the bacterial and fungal components. Upon activation of the system, the associated proteins gain biological activity and participate in the cellular defense reactions of the host animal. The enzyme involved in melanin formation is phenoloxidase (monophenyl L-dopa:oxygen oxidoreductase). Phenoloxidase activity has been detected in the hemolymph or coelom of many invertebrate groups. This enzyme catalyses the oxidation of phenols to quinones, which then will polymerize non-enzymatically to melanin. The intermediary compounds formed as well as melanin itself are toxic to micro-organisms due to the formation of H2O2 (Söderhäll and Cerenius 1998). One interesting study of phenoloxidase activity was published by Wilson et al. (2001) who studied larvae of the African armyworm, Spodoptera exempta, and their resistance to the pathogenic fungus Beauveria bassiana. Insects in high-density populations invest relatively more in pathogen resistance than those in low-density populations (i.e. density-dependent prophylaxis). Such increases in resistance are often accompanied by cuticular melanism (Fig. 3.4), which is characteristic of the highdensity form of many phase-polyphenic insects. High levels of cuticular PO are associated with increased resistance to an ectoparasitic wasp and an entomopathogenic

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Fig. 3.4  Densitydependent cuticular melanization in Spodoptera exempta. Live larvae, showing the pale, low-density phenotype on the left and the dark, high-density phenotype on the right (From Wilson et al. 2001. With permission from Wiley)

fungus; high levels of midgut PO are correlated with increased resistance to a baculovirus. Furthermore, fungus-induced mortality in Spodoptera littoralis was significantly affected by dose: at both doses, fungus-induced mortality in S. littoralis was greater in solitary-reared caterpillars and in caterpillars with pale cuticles than in crowdreared caterpillars and those with dark cuticles, and these effects were additive. Furthermore, fungus-induced mortality was much greater for S. exempta than S. littoralis (Fig.  3.5). These results strengthen the link between melanism and disease resistance and implicate the involvement of phenoloxidase. Melanization is an important immune mechanism in arthropods and possibly among many other invertebrate taxa, although the latter have been investigated less frequently. However, except for some effectors as proPO, the innate immune response is less well understood outside model insect species, and its role in natural host–pathogen systems is generally not well documented. Two recent studies demonstrate both the progress in fundamental arthropod immunology and application of proPO in species protection. In animals with a complex life cycle, larval stressors may carry over even to the adult stage. Carry-over effects not mediated through age and size at metamorphosis may have adverse effects in the adult stage, as de Block and Stoks (2008) impressively showed with damselflies. Their study focused on the poorly documented immune costs of short-term food stress both in the larval stage and after metamorphosis in the adult stage by quantifying immune function in an experiment where larvae of the damselfly Lestes viridis were challenged by a transient starvation period. The authors showed that directly after starvation, immune variables were reduced in starved larvae. Levels of proPO and phenoloxidase, PO, remained low after starvation, even after metamorphosis, making these adults more susceptible to pathogen attack. A rapid up-regulation of proPO transcription upon exposure to a pathogen is a common response and has been reported in a variety of arthropods, namely the

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Fig. 3.5  Resistance to the entomopathogenic fungus Beauveria bassiana in relation to (a) rearing density and (b) cuticular melanization. In (a) the comparison is between larvae reared solitarily and those in crowds (three or four larvae per pot); in (b) the comparison is between larvae with pale cuticles and those with dark cuticles. Low dose refers to 1 × 108 conidia ml−1, and 1 × 109 conidia ml−1to high does. Symbols above the bars refer to the statistical significance of the difference between treatments: ns p > 0.05, *p < 0.05, **p < 0.01, ***p < 0.001 (From Wilson et al. 2001. With permission from Wiley)

noble crayfish, Astacus astacus, and the signal crayfish, Pacifastacus leniusculus (Cerenius et al. 2003; Liu et al. 2007), the giant river prawn, Macrobrachium rosenbergii (Lu et  al. 2006), the mangrove crab, Scylla serrata (Ko et  al. 2007), the Chinese mitten crab, Eriocheir sinensis (Gai et al. 2008), Daphnia magna (Labbé and Little 2009; Pauwels et al. 2010b), and the Oriental leafworm moth, Spodoptera litura (Rajagopal et al. 2005). Up-regulation of proPO transcription is often coupled with increased PO activity (Lu et al. 2006; Gai et al. 2008). It is interesting to note that the resistant signal crayfish, P. leniusculus, continuously produces high levels of proPO transcripts (Cerenius et al. 2003).

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3  Defense Means Against Pathogens and Parasites: Reactive Oxygen Species

Table 3.1  Relationship between presence of a parasite and increased host phototaxis (From Lefèvre et al. 2009. With permission from Elsevier) Effect of parasite Gammarid (Host) Parasite on phototaxis Gammarus insensibilis Microphallus papillorobustus (within the Increase central nervous system) Gammarus lacustris Polymorphus paradoxus (within hemocoel) Increase Gammarus pulex Pomphorhynchus laevis (within hemocoel) Increase Pomphorhynchus minutus (within hemocoel) None Gammarus roeseli Pomphorhynchus laevis (within hemocoel) None

3.2.2.1 Parasitized Crustaceans: Highly Complex Response Doubtless, parasitized animals change their behavior, reproductive success, ­population dynamics, and evolutionary potential. There are many informative studies, particularly with crustaceans, which highlight these aspects singly, yet none bridges the whole range from molecular biology or biochemistry to population dynamics. Following the recent review of Cerenius et al. (2008), we assume that the general first line of defense against parasites is the transcriptionally controlled oxygen activation prior to potential melanization and encapsulation of the pathogens. This energy consumption reduces body growth, competition strength, and mating behavior, and eventually puts the population at risk. An additional risk for populations exists for those taxa, such as gammarids, which have the potential for sex reversal if parasitized. Furthermore, parasites promote host gene flow in metapopulations (Altermatt et  al. 2007) and trigger (micro)-evolution (Capaul and Ebert 2003). Behavior Parasite-induced alteration of host behavior is a widespread transmission strategy among pathogens. An excellent review of the manipulative strategies in host-parasite interactions has been published by Lefèvre et  al. (2009). The following will present key examples to briefly demonstrate parasite-mediated behavior of hosts. Seminal studies have been carried out with gammarids. Amphipods are attacked by parasites that often have complex life cycles in which the parasite requires transmission to a vertebrate host to complete its development. In some of these systems, once the parasite reaches the infective stage, the parasitized host shows changes in escape behavior resulting in an increased likelihood that the infected gammarid will be consumed by the parasite’s appropriate vertebrate host (Table 3.1). It is likely that the behavioral changes are mediated by the happiness hormone, serotonin, produced by the parasite or the host itself (Lefèvre et al. 2009). In a river survey and subsequent laboratory simulation, MacNeil et  al. (2003) observed Gammarus pulex amphipods both unparasitized and parasitized with the acanthocephalan Echinorhynchus truttae. They found that there were higher

3.2  Defense Response in Animals

57

p­ roportions of unparasitized amphipods in/under stone substrates and within weeds. In contrast, there were higher proportions of parasitized amphipods in the water column and at the water surface. Parasitized amphipods also were more active and had a greater preference for illumination (see also Table 3.1). Overall, these subtle differences in micro-habitat usage and behavior translated to greatly increased vulnerability to fish predation and an improved transmission of the parasite. Similar results were obtained when parasitized and unparasitized amphipods were exposed to fish kairomones: the non-infected amphipods reduced their activity after the addition of fish odor, but the infected amphipods failed to show a significant decrease. This failure shows a parasite strategy to increase its chances of transmission by making its amphipod host more vulnerable to predation of fish (Dezfuli et al. 2003). Some of the underlying molecular pathways of host-parasite interaction will be presented in the Chap. 9. Sex Determination and Population Risk Environmental sex determination, where an individual’s sex is determined in response to an environmental cue experienced after birth, has been reported in diverse groups of vertebrates and invertebrates (Barske and Capel 2008). One of several environmental cues is parasitism which is well documented to cause intersex in freshwater and marine amphipods due to feminizing microsporidian parasites (Ford and Fernandes 2005; Ford et  al. 2006). How does intersex of amphipods translate to population dynamics? One of the rare studies to answer this question has been carried out by Ford et al. (2007). They modeled the population effects of different levels of intersexuality in the amphipod, Echinogammarus marinus. One result was that the population density increased exponentially if intersex females occur at the expense of males. However, if the number of intersex females reached approximately ½ the number of normal females, even if the percent of males in the population is as low as 27% (e.g., 27% males, 45% normal females, 28% intersex females), the population would be extinguished within 10 years. These results suggest a selective advantage in female-biased sex ratios in populations with significant levels of intersexuality, up to a certain threshold, where the increase in the total number of females seemed to compensate for the lower recruitment rates of intersex individuals (namely, intersex females). Furthermore, even in this scenario, if the recruitment rate of normal females was negatively affected, the population survivorship would be compromised. Population Dynamics Few studies have investigated the distribution and abundance of endoparasites within natural zooplankton populations and the subsequent ecological consequences of parasitism in Daphnia. Using laboratory experiments, Bittner et al. (2002) studied the epidemiological interactions between the parasite Caullerya mesnili and its

58

3  Defense Means Against Pathogens and Parasites: Reactive Oxygen Species

host D. galeata at the individual and population level. This parasite was found to be transmitted directly and horizontally through waterborne infection stages. In a life table experiment at low and high food levels, the life expectancy and fecundity of infected D. galeata were dramatically reduced at both food levels as compared to the uninfected controls. Additionally, the authors found a significant interaction between infection and food level, indicating a stronger parasitic effect in well-fed hosts. To test the effects of the parasite at the population level, Bittner et al. (2002) compared the size of D. galeata populations infected with C. mesnili with the size of parasite-free microcosm populations. In all infected populations, the parasite drove the host population to extinction. Competition and Microevolution A prevailing view of host-parasite co-evolution is that of an arms race between two antagonists. The dynamic nature of such arms races is characterized by reciprocal selection, which favors host genotypes with low fitness costs due to parasitic infections and parasite genotypes with increased rates of spread within the host population. In such cases, selection may be negative frequency dependent, that is, parasites adapt to common host genotypes, and hosts evolve defenses against common parasite genotypes. The dynamic nature of arms races can produce very complex patterns. In particular, the reciprocity of selection makes it difficult to disentangle the impact of parasite selection on the host population from the impact of host selection on the parasite population (Capaul and Ebert 2003). Capaul and Ebert tested the extent to which parasite-mediated selection by different parasite species influenced competition among clones of D. magna. They monitored clone frequency changes in laboratory microcosm populations consisting of 21 D. magna clones (Fig. 3.6). Parasite treatments and a parasite-free control treatment were followed over a 9-month period. Capaul and Ebert found significant differences in clonal success among the treatments: the two parasite treatments differed from the control treatment and from each other, with one clone winning the competition. The clone differed in the challenged common garden experiments. The study showed that parasite-mediated selection can strongly alter the outcome of clonal competition. The results indicate that parasites influenced microevolution in Daphnia populations during periods of asexual reproduction. Gene Flow in Metapopulations Migration is a fundamental process for metapopulation dynamics and the persistence of local populations. It has been shown that an increased immigration rate can reduce the probability of local extinction by reinforcing local population sizes in natural and experimental systems. Migration also introduces new genetic material, which can prevent the negative demographic consequences of inbreeding. These processes depend on the effective immigration rate, which is not only a function of

3.2  Defense Response in Animals

59

Fig. 3.6  Changes in Daphnia magna clone frequencies in the control, Glugoides intestinalis, Ordospora colligata, and Pasteuria ramosa treatment over 9 months. Mean clone frequencies (6 standard errors) across the six replicates in each treatment are shown. Solid thin lines indicate clones that did not increase to high levels in any of the treatments. In each graph, clones with the most distinct dynamics are indicated with different line types and with small numbers to indicate the clone identities. Line types are the same across the four graphs (From Capaul and Ebert 2003. With permission from Wiley)

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3  Defense Means Against Pathogens and Parasites: Reactive Oxygen Species

the rate with which migrants travel among sites but also of the fitness differences between the immigrants and the resident individuals. If immigrants experience an advantage relative to local population members, the effective migration rate is higher than the basic migration rate. Natural populations are often expected to be adapted to local conditions, suggesting that conspecific immigrants should be on average competitively inferior. Thus, local adaptation counteracts the beneficial effects of migration, such as the introduction of new genetic material and the spread of favorable alleles across metapopulations (Altermatt et al. 2007). Altermatt et al. (2007) reported two experiments testing whether parasite abundance and genetic background influences the success of host migration among pools in a D. magna metapopulation. In natural populations of D. magna, immigrant hosts were found to be on average more successful when the resident populations experienced high prevalences of a local microsporidian parasite. The researchers then determined whether this success is due to parasitism per se or to the genetic background of the parasites. In a common garden competition experiment, the authors found that parasites reduced the fitness of their local hosts relatively more than the fitness of allopatric host genotypes. Their experiments were consistent with theoretical predictions based on co-evolutionary host-parasite models in metapopulations. A direct consequence of the observed mechanism is an elevated effective migration rate for the host in the metapopulation.

Chapter 4

Arms Race Between Plants and Animals: Biotransformation System

Interactions between plants and herbivores are of major importance in natural ecosystems. The phytochemical co-evolution theory suggests that plant secondary metabolites are likely the most important mediators of plant-herbivore interactions, although their primary cause for production is the shielding effect against adverse environmental triggers. According to this theory, both plants and insect herbivores generate selective forces that lead to the evolution of plant defense (i.e., plant secondary metabolites, PSM) and herbivore offense (i.e., detoxification ability) in a so-called co-evolutionary arms race. These chemicals, although not required for primary plant metabolic processes such as respiration or growth, have been extensively recognized for their role in plant defense against herbivore and pathogen attack (Bidart-Bouzat and Imeh-Nathaniel 2008). There is still some concern, though, as to whether or not the primary reason for the production of PSM is protection from photodamage rather than from herbivory. Nevertheless, there is no doubt that these metabolites also function as food allelochemicals, that is plant defense. For animals, food is only one challenge; hence the question arises how they maintain homeostasis in the face of an adverse environment. The need to deal with biological, chemical, and physical challenges has driven the evolution of an array of gene families and pathways affording protection from and repair of damage. Genes and proteins affording such protection for an organism collectively may be consi­ dered a “defensome”. A central part of this system is the “chemical defensome”, an integrated network of genes and pathways that allow an organism to mount an orchestrated defense against toxic natural and anthropogenic xenobiotic chemicals (Goldstone et al. 2006). Furthermore, many pathways of the defense systems which evolved in animals to protect them from plant allelochemicals do not have a high substrate specificity and may therefore also be used to defend against synthetic xenobiotics. Before we consider the pros and cons of this low specificity, we have to learn about the evolution of the biotransformation system by roughly following the phytochemical co-evolution theory.

C.E.W. Steinberg, Stress Ecology: Environmental Stress as Ecological Driving Force and Key Player in Evolution, DOI 10.1007/978-94-007-2072-5_4, © Springer Science+Business Media B.V. 2012

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4  Arms Race Between Plants and Animals: Biotransformation System

4.1 Major Arms of the Plants At this point, we should state that both parties of the “plant-animal warfare” make use of the same (but not entirely identical) enzyme systems: cytochrome P450 enzymes (CYP),1 glutathione transferases, glycosyltransferases, or sulfotransferases are central in generating the plants’ weapons as well as to render them as harmless as possible by their predators. The production of weapons will be exemplified by (1) the furanocoumarin synthesis, the most toxic (Fig. 4.1) (Schuler 2011) and (2) the terpenoid synthesis, one of the most wide-spread plant defense compounds, particularly in coniferous trees. Each of these are discussed with respect to (3) flavonoids.

4.1.1 Furanocoumarins Furanocoumarins are derived by attachment of a furan ring to coumarin in either a linear or angular orientation in order to strongly increase the appetite-suppressing properties of coumarin. It is obvious that members of the CYP71 family are involved in the synthesis of these highly toxic compounds. In the detoxification of furanocoumarins, members of the CYP6 family are central (Fig.  4.1). We shall revisit the latter CYP family when discussing food generalists vs. specialists and the evolution of insecticide resistance. In general, the CYP superfamily is a large and diverse group of enzymes, whose major function is to catalyze the oxidation of organic substances. This oxidation may be both a rather specific step in the formation of defense chemicals, such as the furanocoumarins, and a non-specific oxidation of a xenobiotic compound. The various families are not differentiated by their function, but by their amino acid identity. The occurrence of CYP families in different organisms and known functions are listed in Appendix 1.

4.1.2 Terpenoids Terpenoids comprise a large and diverse class of naturally-occurring organic defense chemicals, derived from the five-carbon isoprene. Furthermore, steroids and sterols in animals are biologically produced from terpenoid precursors. Keeling and Bohlmann (2006) review the production of these chemicals in conifer trees, since terpenoids are their most prominent defense chemicals. Again, CYPs are important in the diversification of terpenoids through oxidative functionalization.

Reduced cytochrome P450 enzymes (CYPs) possess an absorption maximum at 450 nm in the reduced state.

1 

4.1  Major Arms of the Plants

63 O CYP6B1 CYP6B4

O

O

OH HO

O

O

O

O

O

O O

OH HO

O

CH3

O

O

O

H3C

CYP6AB3 CYP6AB11

O O imperatorin

O

OH O

CH3

H3C

coumarin

O

CH3

O

O

CH3 xanthotoxin O

O O

O

CH3

CH3

O

O

O

Fig. 4.1  Degradation of selected furanocoumarins. CYP detoxification of the linear furanocoumarin xanthotoxin occurs in some lepidopteran insects (e.g., Papilio polyxenes, P. glaucus, Helicoverpa zea) and takes place via epoxidation on the furan ring and subsequent hydroxylation. CYP detoxification of the linear furanocoumarin imperatorin occurs in some lepidopteran insects (Depressaria pastinacella, Amyelois transitella) and takes place via epoxidation of the extended isoprenyl side chain. In these detoxification reactions, 4 enzymes of the CYP6 family are involved (From Schuler 2011. With permission from Elsevier)

Diterpene resin acids such as abietic acid are important components of conifer oleoresin biosynthesized through the action of CYPs. Studies with lodgepole pine (Pinus contorta) tissue extracts showed that stepwise oxidation of the diterpene abietadiene to abietic acid can be achieved by membrane-bound CYP and soluble aldehyde dehydrogenase enzyme activities. The general pathway scheme of oxidation of abietadiene to abietic acid (Fig. 4.2) in conifer secondary metabolism parallels that of oxidation of ent-kaurene to ent-kaurenoic acid in the biosynthesis of gibberellin phytohormones. A multifunctional CYP, CYP701A3, responsible for the three-step oxidation of ent-kaurene to kaurenoic acid has been identified in A. thaliana. It is interesting to note that a multifunctional CYP, CYP88A, also catalyses the subsequent three-step oxidation from kaurenoic acid to the phytohormone, gibberellinA12, in A. thaliana. Terpenoid defenses exist constitutively in many conifers, as Keeling and Bohlmann (2006) noticed, but they are also inducible upon insect herbivory or oviposition or fungal inoculation. Conifer terpenoid defenses are not without costs to the tree. An evaluation of the metabolic costs of terpenoids shows that, by weight, they are some of the most expensive metabolites to produce. Both constitutive and induced defensive responses in plants require substantial re-allocation of resources away from growth and reproduction. Induced responses are thought to be less costly as the resources are only used in response to a clear attack detected by the plant. However, induced responses may not act fast enough in some situations to be effective, such as when responding to a rapid, pheromone-mediated, mass attack by bark beetles carrying symbiotic pathogenic fungi. Less severe local wounding may

64

4  Arms Race Between Plants and Animals: Biotransformation System CH3

CH3

CH3

CH3

CH3

CH3

H

H3C

H CH3

H CYP701 familiy

H3C

H O OH

Abietadiene

Abietic acid

Fig. 4.2  Involvement of enzymes of the CYP701 family in synthesis of abietic acid

stimulate systemic effects that prepare the whole tree for subsequent herbivory. Inter-tree signaling may also induce a defensive response in adjacent trees.

4.1.3 Flavonoids – Protectants Against Abiotic or Biotic Stress? Flavonoids occur widely in terrestrial vascular plants and are a biologically important and chemically diverse group of secondary metabolites that can be divided into subgroups including anthocyanidins, flavonols, flavones, flavanols, flavanones, chalcones, dihydrochalcones, dihydroflavonols, isoflavonoids, and pterocarpanes. The corresponding biosynthetic enzymes belong to various enzyme families, such as dioxygenases, monooxygenases (CYPs), and glycolsyltransferases (UGTs) (Tanaka et al. 2008). Since the products of these enzymes, which also play a central role in the biotransformation system, are also strongly stress-responsive, this excursus will briefly sketch flavonoids as protectants against abiotic and biotic environmental stress. All these compounds are no longer considered to be waste products or evolutionary remnants without current function, nor merely metabolic end products that are toxic to the plant and are therefore stored away in vacuoles. There has been some debate about the reasons why flavonoids have been developed during evolution. One convincing model is the oxidative pressure hypothesis by Close and McArthur (2002) which explains factors affecting phenolic levels in leaves via their effects on oxidative pressure. The authors suggested that the level of many, if not most, phenolics varies in plants under different light and nutrient conditions, for the same reason that levels of other well established antioxidants vary. That is, plants may increase phenolic production directly in response to oxidative pressure produced from excess light energy (Fig. 4.3) and as a physiological response to quench reactive oxygen species and to avoid oxidative stress. The authors suggested further that the observed ecological pattern in levels of most phenolics is more consistent with the concept that photodamage is the main elicitor. At the evolutionary level, patterns of phenolic levels

4.1  Major Arms of the Plants

65

Abiotic factors • excess light energy •increasing CO2 level •UV irradiation, ozone •low nutrients •cold and drought

+

Biotic factors • herbivores

+ Oxidative pressure

•fungi •pathogens

-

+

-

Quenching of reactive oxygen and nitrogen species

Constitutive/induced phenolics

Fig. 4.3  The oxidative pressure hypothesis by Close and McArthur (2002) as an evolutionary concept for flavonoid distribution and abundance (Amended from Treutter 2005, with permission from Wiley). Abiotic factors, which decrease the efficiency of photosynthesis, are the strongest selective agents or elicitors of phenolics. Note that, in this concept, herbivory affects oxidative pressure less than the abiotic factors and mainly when severe enough to cause nutrient stress at the whole plant level. Symbols indicate positive (+) or negative (−) effects

between species may reflect different selective pressure from potential risk of photodamage. Herbivores may be only weak selective targets for phenolics in general, or strong selective targets for only some phenolics (Treutter 2005). The authors also suggested that between species differences in phenolic levels, previously explained in terms of resource availability, allocation trade-off, and herbivory risk, may in fact reflect differences in risk of photodamage. They hypothesized that leaves from slow-growing trees adapted to nutrient-poor, boreal forest environments are subjected to large amounts of oxidative pressure during periods of low temperature coupled with high light. Furthermore, because they are long-lived, they are subject to a high potential accumulation of ROS damage relative to shorterlived leaves. As a result of selective pressure from both the daily and cumulative potential costs of photodamage, these slow-growing plants have evolved higher constitutive phenolic levels for their antioxidant, not anti-herbivore, capacity. Despite the ongoing debate about their major evolutionary cause, there is no doubt that PSM in general also function as food allelochemicals and that they respond to climatic factors such as increasing UV irradiation or ozone concentrations. Therefore, the evaluation of global climate change effects on PSM becomes essential to predict future reciprocal evolutionary changes between plants and herbivores. Plant defense responses to herbivory depend on the plants’ evolutionary

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4  Arms Race Between Plants and Animals: Biotransformation System

history (e.g., past exposure to herbivory) as well as the physical environment affecting plant-insect associations. Human-induced changes in abiotic environmental factors such as atmospheric carbon dioxide (CO2) and ozone (O3) levels, ultraviolet (UV) light, precipitation patterns, or temperature may directly affect the concentration of secondary chemicals in plants (Bidart-Bouzat and Imeh-Nathaniel 2008). 4.1.3.1 Elevated Carbon Dioxide Elevated CO2 clearly influences inducibility of plant chemical defenses. In a growth chamber study, Bidart-Bouzat et al. (2005) found that herbivory by the diamondback moth (Plutella xylostella) induced a significant increase in the levels of total as well as some individual glucosinolates in Arabidopsis thaliana only under elevated CO2 conditions. In addition, elevated CO2 modified plant-insect relationships, that is, the type and degree of association between insect performance (i.e., adult insect weight) and glucosinolate levels. Even the plant tolerance to herbivory is reduced at elevated CO2 concentrations (Lau and Tiffin 2009). Only plants under ambient, but not at elevated CO2 concentrations, were able to compensate for biomass loss by herbivory. 4.1.3.2 Elevated Ozone Unlike CO2, which overall enhances plant growth, tropospheric O3 causes oxidative stress in plant cells resulting in decreased plant photosynthesis, respiration, and plant growth as well as inducing changes in nutrient allocation and senescence. Several studies have shown that changes in O3 concentrations can alter the production of secondary chemicals in plants. Plant physiological stress imposed by augmented O3 levels may stimulate the induction of metabolic pathways (e.g., SA and JA pathways) involved in the production of PSM (Bidart-Bouzat and Imeh-Nathaniel 2008). 4.1.3.3 Elevated UV Irradiation Due to the reduction of the stratospheric O3 layer, UV-B irradiation has increased considerably. UV increases the production of PSM with photoprotective qualities, which include many phenolic compounds such as flavonoids, coumarins, and stilbenes and, in turn, influences plant-insect interactions (e.g., decreased herbivory under higher UV-B light levels). Decreases in insect herbivory under enhanced UV-B lead to decreased insect oviposition rates, insect abundance, insect consumption, and insect performance as well as decreased plant damage. 4.1.3.4 Elevated Temperature Although little information exists regarding potential elevated temperature-induced changes in PSM and their potential effects on insect performance, it can be

4.2  The Biotransformation System

67

hypothesized that increased production of PSM under these conditions may adversely affect insect performance such as larval development and female fecundity, but also result in shorter developmental times and increased survival (BidartBouzat and Imeh-Nathaniel 2008). However, this is only one side of the coin – the other is the so-called “xenohormesis hypothesis” which particularly considers certain polyphenols as information molecules produced by plants and used by heterotrophs to induce self-protection. This hypothesis will be discussed below, yet it is not understood whether it applies also to molecules other than polyphenols, for instance, to the aforementioned glucosinolates. In sum, plants may win one round in the plant-animal warfare since the relationship between chemical weapons of the plants and the defense mechanisms in their enemies may come out off balance and will have to be re-adjusted once more.

4.2 The Biotransformation System Central in the chemical defensome is the biotransformation system. Biotransformation is the chemical modification made by an organism on a chemical compound and is known to metabolize a wide variety of chemical compounds, which is facilitated by the rather low specificity of many enzymes involved; one major primary function is to maintain biochemical homeostasis. As far as animals in general, and herbivores in particular, are concerned, homeostasis is challenged by biochemical compounds taken up via food, the PSM. Complete avoidance is typically not possible due to the ubiquity and diversity of PSM. Yet, there are physiological mechanisms that animals can use to detect the consequences of ingested PSM. Central is the biotransformation system which comprises four distinct phases (Fig. 4.4): • Phase 0: Excretion of parent compounds by transporter proteins, with permeability glycoproteins (P-gps) being major and well-studied representatives. • Phase I: Oxidative, reductive, or hydrolytic transformation of a chemical compound by enzymes. Hydrophilicity of the xenobiotic compound increases, mainly through the activity of cytochrome P450 (CYP) enzymes. • Phase II: Conjugative transformation of a chemical compound by a variety of transferase enzymes; hydrophilicity of the xenobiotic compound increases further. • Phase III: Absorption, distribution, and excretion of metabolites by transporter proteins, such as P-gps. Provided phase 0 exporters have the capability to efficiently excrete exogenous and endogenous potentially toxic compounds, the question arises why there is still a need for phase I and II biotransformation. If the exporters work properly, they could completely prevent cells and organisms from becoming intoxicated, and there would be no need for energy consuming enzyme synthesis and functioning. This view, however, is shortsighted for at least three reasons: 1. The enzyme families of the biotransformation system are not only in charge of metabolizing exogenous and endogenous “wastes”, but also of steroid and fatty acid metabolism (Arnold et al. 2010; Konkel and Schunck 2010).

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4  Arms Race Between Plants and Animals: Biotransformation System

Various exporters Defense by excretion (animals, plants)

Phase 0

Excretion of conjugates (animals, plants)

animals only?

Hormones, natural and man-made xenobiotics, humic substances

Phase III

Phase I • oxidation • reduction • hydrolysis (plants & animals)

Phase II conjugation (plants & animals)

Phase III bound residues in plants

Fig. 4.4  Sketch of the different phases of the biotransformation system in animals and plants. This sketch presents aquatic organisms, particularly Dreissena polymorpha, because the environmental significance of exporter proteins was first discovered in this species (Photographs: credit VV Pavlichenko)

2. The “waste” substrates contain valuable material which can be re-used (see discussion of generalist vs. specialist bush rats below). 3. Not all chemical compounds can be excreted by the exporters; some have the ability to block the exporters by the so-called chemosensitization (see Sect. 4.6.1). This blockage can significantly increase the internal concentrations of xenobiotics that otherwise would be excreted. An illustrative toxicological sketch of how the model synthetic xenobiotic benzo[a]pyrene (B[a]P) is processed in phases 0 to III is presented in Fig. 4.5. A possible metabolic fate of B[a]P is illustrated, although many other metabolites are also formed. The xenobiotic diffuses freely across the plasma membrane, where it becomes a substrate for the CYP system, resulting in the formation of an epoxide. This in turn becomes a substrate for epoxide hydrolase. The diol product of this reaction can again be acted upon by CYP to form a carcinogenic and mutagenic diol-epoxide derivative of the xenobiotic. The metabolite rather than the educt is carcinogenic (Pelkonen and Nebert 1982). Due to the short-term coexistence of synthetic xenobiotics and the biotransformation system, it often happens that the metabolites have a higher toxic potential than the educts have; in contrast to synthetic xenobiotics, the processing of natural xenobiotics usually leads to less toxic and often even beneficial metabolites.

4.2  The Biotransformation System

69

OH GS

CYP

O2

Phase III detoxification

Phase 0 detoxification

H OH

O O

Epoxide hydrolase

H2O GS GS

OH OH

HO HO HO HO

OH OH

CYP

O2

O O

OH OH

GSH T GS

Phase II detoxification

HO HO OH OH

Phase I detoxification

CELL

Fig. 4.5  Overview of enzymic detoxification, exemplified with the synthetic xenobiotic, benzo[a] pyrene

Both aforementioned enzymes are microsomal, and form phase I of enzymic detoxification. To emphasize once more: in the case of B[a]P, cellular damage occurs only after metabolic activation by CYPs producing highly reactive electrophiles. The activity of CYP enzymes depends on the availability of energy and activated oxygen (Fig. 4.6). GSTs are mainly cytosolic phase II enzymes which catalyze conjugation products to GSH. The GSH-xenobiotic conjugate is too hydrophilic to diffuse freely from the cell and must be pumped out actively by a transmembrane ATPase (phase III). This results in the unidirectional excretion of the xenobiotic from the cell, since the hydrophilic GSH moiety prevents re-diffusion across the plasma membrane. Ultimately, this conjugate is excreted from mammals as mercapturic acids. Many xenobiotic chemicals, including B[a]P, are exported immediately after they have diffused into the cell. This export is mediated by membrane-bound proteins as phase 0 of the biotransformation. Most of the responses are receptor mediated as sketched in Fig. 4.7. An inducer (agonist) enters the cell via passive diffusion or active uptake. It can be exported immediately after entry via permeability glycoproteins (phase 0). The nuclear receptor, aryl hydrocarbon receptor (AHR), is located in the cytoplasm. Once the compound binds to AHR, they are activated by transport factors and translocated to the nucleus. The activated receptors eventually bind to response elements leading to the

70

4  Arms Race Between Plants and Animals: Biotransformation System

H

NADPH

oxidized

reduced

O2

Cytochrome P450 reductase (Fe-S)

Cytochrome P450

reduced

oxidized

NADP+

ROS

H2O OH

Fig. 4.6  The activity of cytochrome P450 enzymes depends on availability of energy and activated oxygen. Particularly in the presence of redox-sensitive metals (iron, manganese), the activation of oxygen (see Chap. 2) releases more reactive oxygen than is used for the oxidation of substrate and CYP. Because the CYP enzymes place only one oxygen atom from the oxygen molecule on the substrate, they are called monooxygenases

Natural and synthetic xenobiotic compounds Transport factors

Binding site (XRE)

Activated complex

Nucleus

Transcription

AH Receptor

DNA mRNA Translation CYP1A GST, UGT, P-gps Cell membrane

Fig. 4.7  Scheme of the major receptor-mediated mechanism of enzyme and protein induction in the biotransformation phases

4.2  The Biotransformation System

71

transcription of the respective CYP, GST, UGT, or P-gp isoforms. mRNA translocates to the cytoplasm where the translation into CYP and other active proteins occurs. One hypothesis poses that PSM are the likely primordial trigger for protein induction in animals. Supplementing this hypothesis, Steinberg (2003) has posed the hypothesis that primordial humic substances may have been the trigger instead. Since organisms exposed to chemicals have several stress response reactions in common, which are almost identical from bacteria to vertebrates, these reactions must have developed very early during the evolution of life on Earth. One chemical trigger of this development may have been primordial humic substance-like compounds, which are likely to have developed very early during biological and chemical evolution (Miller 1955; Ziechmann 1996). Besides these chemical cues, a variety of other triggers can activate the biotransformation system. Some of these and their respective references are listed in Table 4.1.

4.2.1 Plants Outcompete Archaea, Bacteria, Fungi, and Animals in Terms of CYP Gene Numbers Comparing plants, Archaea, bacteria, fungi, and animals with respect to biotransformation (here CYP) gene numbers, it soon becomes obvious that plants have the highest number – one of the surprising disclosures of the complete Arabidopsis sequence. For instance, A. thaliana possesses more than 279 and O. sativa 356 CYP genes (Table 4.2). By January 2004, a total of 1,098 named plant CYP genes were described by Nelson et al. (2004a). Among animals, the mouse, Mus musculus, and the mosquito, Anopheles gambiae, possess numbers as high as 80, 102, and 105 CYP genes, respectively (Table 4.2), clearly exceeding the number of Homo sapiens genes (57). Even the nematode, Caenorhabditis elegans (67); the sea urchin, Strongylocentrotus purpuratus (120); the silkmoth, Bombyx mori (81); the waterflea, Daphnia pulex (75); or the fruitfly, Drosophila melanogaster (85), possess more CYP genes than humans. In this respect, humans are comparable to the pufferfish, Fugu rubripes (54). Why do such large differences exist? It is assumed that the numbers of biotransformation genes in the various organisms roughly reflect their ecological niches in terms of chemical self-protection against abiotic stressors and defense against pathogens, parasites, and predators on the one hand and are means to overcome these chemical defense systems in predators (herbivores) on the other hand. It is a clear arms race, which is won by plants – at least in terms of gene numbers. As one major strategy of self-defense, plants synthesize a wide variety of plant secondary metabolites. In their biosynthesis, each compound requires a pathway with a set of specific enzymes of high substrate specificity; many of them are CYP enzymes (see Figs.  4.1 and 4.2). The reverse process, namely the biodegradation of such compounds in herbivores or omnivores, is less specific and therefore requires fewer enzymes. In other words, the ecological niches determine the numbers of biotransformation genes.

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Table 4.1  Selected studies of biotransformation, including MXR activity, induced by different environmental stressors. Priority is given to those papers which describe and emphasize ecological processes rather than xenobiotic monitoring Environmental stressor Selected references Heat Lee et al. (2008); Kim et al. (2009b) Cold Perepechaeva et al. (2006) (UV)-irradiation Fritsche et al. (2007); Behrendt et al. (2010); Sasaki et al. (2010) Osmotic stress Kagawa and Cao (2001) Acidification Zhou et al. (2009) Desiccation, drought Kiyosue et al. (1993); Iuchi et al. (2000); Bianchi et al. (2002); Ji et al. (2010) Heavy metals and metalloids Ivanina and Sokolova (2008); Lee et al. (2008); Cao et al. (2010); Kim et al. (2009b, 2010b); Zhang et al. (2010b) Xenobiotics, sediments Cummins et al. (1999); Akkanen and Kukkonen (2003); van der Oost et al. (2003); Li et al. (2007a, b); Saez et al. (2008) Natural xenobiotics I: humic Pflugmacher et al. (2001); Meems et al. (2004); Matsuo et al. substances, plant leachates (2006); Timofeyev et al. (2007); Andersson et al. (2010) Dugravot et al. (2004); review by Dittmann and Wiegand Natural xenobiotics II: plant (2006); Li et al. (2007a, b); Liang et al. (2007); secondary metabolites, Contardo-Jara et al. (2008); DeBusk et al. (2008); Amé cyanotoxins et al. (2009); Sotka et al. (2009); DeGabriel et al. (2010); Whalen et al. (2010a, b) Salinity Ji et al. (2010) Pathogens, parasites Taylor et al. (1990); Albrecht and Bowman (2008); Wang et al. (2008) Symbiosis Zhang et al. (2010b)

This phenomenon can be seen even in closely related organisms. For instance, Dieterich et al. (2008) compared the bacteriovorous nematode, Caenorhabditis elegans, with another nematode, Pristionchus pacificus. The authors observed that the P. pacificus proteome has many more CYPs, UDP-glycosyltransferases (UGTs), and carboxylesterases, which have key roles in the metabolism of natural and synthetic xenobiotics. Only the GST numbers are similar. In the P. pacificus genome, Dieterich and co-authors observed elevated copy numbers of almost all gene types involved in the metabolism of xenobiotics. Most pronounced were the increases in CYP enzymes in phase I and sulfotransferase (SULT) and UGT enzymes in phase II. P. pacificus resembles C. elegans in many traits, including a short generation time and hermaphroditic propagation. However, the ecological niche occupied by P. pacificus is completely different from that of C. elegans. P. pacificus is associated with beetles. At the beginning of this association, known as necromeny, non-feeding dauer larvae actively invade the beetle. The larvae remain arrested in the dauer stage until the death of the insect and resume development by feeding on bacteria, fungi and nematodes that grow on the insect’s carcass. Necromenic species are thus permanently exposed to a diversity of microbes and the natural xenobiotic compounds produced by these organisms, which require specific defense mechanisms. In contrast to P. pacificus, C. elegans inhabits nutrient- and microorganism-rich organic material, such as

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Table 4.2  CYP genes in selected Archaea, bacteria, plants, fungi, and animals Gene number CYP genes % a Sulfolobus solfataricus 2,960 1 0.03 Mycobacterium tuberculosisb 4,294 22 0.52 Bacillus subtilisc 4,245 8 0.19 Oryza sativa wild typed ~33,600 356 1.06 Arabidopsis thalianae 25,000 ³279 1.12 Saccharomyces cerevisiaef ~6,300 3 0.05 Caenorhabditis elegansg 20,060 67 0.33 Pristionchus pacificusg 23,500 198 0.84 Daphnia pulexh ~17,000 75 0.44 Drosophila melanogasteri ~14,000 86 0.61 Homo sapiensj ~25,000 57 0.23 a  http://cmr.jcvi.org/cgi-bin/CMR/GenomePage.cgi?org=ntss02 b  http://cmr.jcvi.org/tigr-scripts/CMR/GenomePage.cgi?database=gmt c  http://cmr.jcvi.org/tigr-scripts/CMR/GenomePage.cgi?database=ntbs01 d  Sakai and Itoh (2010) e  The Arabidopsis Genome Initiative (2000) f  Goffeau et al. (1996) g  Dieterich et al. (2008) h  Baldwin et al. (2009); http://wfleabase.org/ i  Yendell et al. (2005); Chung et al. (2009) j  International Human Genome Sequencing Consortium (2004); Nelson et al. (2004b)

compost and rotten fruits (Kiontke and Sudhaus 2006), with much less natural xenobiotic compounds. Overall, the relatively higher number of detoxification and degradation enzymes in P. pacificus is consistent with its necromenic lifestyle.

4.3 Phase I: Functionalization 4.3.1 Cytochrome P450 (CYP) Enzymes The CYP enzymes comprise one of the largest and most versatile protein families. They are known for phase I metabolism of most (lipophilic) xenobiotic compounds, be they natural (food allelochemicals, hormones) or synthetic (synthetic organic chemicals, such as drugs, pesticides, polycyclic aromatic hydrocarbons, chlorinated organics, etc.). The reactions they catalyze are extremely diverse, but usually are based on activation of molecular oxygen with insertion of one of its atoms into the substrate and reduction of the other to form water (see Fig. 4.8). Many CYPs have, however, endogenous functions, being specialized in the metabolism of lipids or of signal molecules, such as steroid hormones, eicosanoids and pheromones. The great diversity of this gene family is a result of consecutive gene duplications as sketched in Fig. 4.9 and the subsequent divergence of genes. Ancient CYPs first evolved for important physiological functions, e.g. sterol synthesis, and existed before the time of prokaryote/eukaryote divergence.

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Phase I CYP naphthalene

1-hydroxy-naphthalene

Fig. 4.8  Representation of the functionalization of a anthropogenic xenobiotic chemical (naphthalene) by a CYP-catalyzed reaction as facilitated in the liver of flounders. The generated 1-hydroxynaphthalene is entrained into phase II and are the subject of a conjugation reaction, such as glucuronidation (see Fig. 4.13) or sulfation (see Fig. 4.15)

Fig. 4.9  Sketched duplication of a part of a chromosome (Created by and courtesy of K Aainsqatsi) OH OH O

HO

OH O

HO

R OH

O

R=H Naringenin R = OH Dihydrokaempferol

R OH

O

R=H Eriodictyol R = OH Dihydroquercetin

Fig. 4.10  CYP75B1 is a flavonoid 3¢-hydroxylase. CYP75B1 catalyzes the 3¢-hydroxylation of ring B of naringenin and dihydrokaempferol to form eriodictyol and dihydroquercetin, respectively (From Werck-Reichhart et al. 2002. Courtesy of The Arabidopsis Book)

Changing environments and life strategies probably drove the functional diversification leading to the broad activity towards exogenous compounds. As plants developed protective phytoalexins, new CYPs were recruited for the detoxification of these compounds (Nelson et al. 1996; Rewitz et al. 2006). An overview is presented in Appendix 1. Figures  4.10 and 4.11 display two of several plant CYP-catalyzed reactions which lead to secondary metabolites with the potential to act as strong food allelochemicals.

4.4  Phase II: Conjugation O

N

75 H

H

O

R-SH

N H Indole-3-acetaldoxime

N

H

SR

N H S-alkyl-thiohydroximate

Fig. 4.11  CYP83B1 catalyzes the first committed step of indole glucosinolate biosynthesis. In the presence of thiol compounds (R-SH), CYP83B1 forms S-alkylthiohydroximate adducts. Formation of the adducts proceeds non-enzymatically outside the active site. In the absence of a thiol compound, the highly electrophilic product of CYP83B1 catalysis inactivates the enzyme (From Werck-Reichhart et al. 2002. Courtesy of The Arabidopsis Book)

4.4 Phase II: Conjugation This phase comprises a variety of conjugating enzymes; many of them produce conjugates which serve as food allelochemicals with the potential to structure the predator community. Therefore, this phase will be considered more deeply than phase I.

4.4.1 Glutathione Transferases The glutathione transferases have historically also been called glutathione S-transferases, and it is this latter name that gives rise to the widely used abbreviation GST. These enzymes catalyze nucleophilic attack by reduced glutathione (GSH) on nonpolar compounds that contain an electrophilic carbon, nitrogen, or sulfur atom (for more details, see Appendix 2). Their substrates include halogenonitrobenzenes, arene oxides, quinones, and a,b-unsaturated carbonyls (Hayes et al. 2005). Three major families of proteins that are widely distributed in nature exhibit glutathione transferase activity. Two of these, the cytosolic and mitochondrial GST, comprise soluble enzymes that are only distantly related. The third family comprises microsomal GST and is now referred to as membrane-associated proteins in eicosanoid and glutathione (MAPEG) metabolism. A further distinct family of transferases exists, represented by the bacterial fosfomycin resistance proteins FosA and FosB (Hayes et al. 2005; Allocati et al. 2009). Cytosolic and mitochondrial GST share some similarities in their threedimensional fold but bear no structural resemblance to the MAPEG enzymes. However, all three families contain members that catalyze the conjugation of GSH

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a

Cl

SG

O

O N O

N O GSH +

+ HCl

N O

N

O

O

O

HO

O

CDNB

b

HO H3C

CH3

2 GSH +

H3C

CH3 + GSSG + H2O

CuOOH

Fig. 4.12  Examples of conjugation and reduction reactions catalyzed by GST. (a) Conjugation of 1-chloro-2,4-dinitrobenzene (CDNB), (b) reduction of cumene hydroperoxide (CuOOH)

with 1-chloro-2,4-dinitrobenzene and exhibit glutathione peroxidase activity toward cumene hydroperoxide; these reactions are shown in Fig. 4.12. The cytosolic GST and MAPEG enzymes catalyze isomerization of various unsaturated compounds and are intimately involved in the synthesis of prostaglandins. Cytosolic GSTs represent the largest family of such transferases and have activities that are unique to this group of enzymes. They catalyze thiolysis of 4-nitrophenyl acetate; display thiol transferase activity; reduce trinitroglycerin, dehydroascorbic acid, and monomethylarsonic acid; and catalyze the isomerization of maleylacetoacetate and D5-3-ketosteroids (Hayes et al. 2005). GSTs metabolize insecticides, herbicides, carcinogens, and by-products of oxidative stress. Elevated levels of GST are associated with tolerance of insecticides and with herbicide selectivity (see below Sect. 4.9). In microbes, plants, flies, fish, and mammals, expression of GSTs is up-regulated by exposure to prooxidants, chemicals that induce oxidative stress either through creating ROS or inhibiting antioxidant systems. Increase in transferase activity is also observed in animals that undergo prolonged torpor or hibernation when comparisons are made between their estivated state and their wakeful condition. It is similarly observed during transition of the common toad, Bufo bufo, from an aquatic environment to a terrestrial one. Collectively, these findings indicate that induction of GST is an evolutionarily conserved response of cells to oxidative stress (Hayes et  al. 2005). A detailed classification of GSTs can be found in Appendix 2.

4.4  Phase II: Conjugation COOH

OH

+

UDP

O HO

Phenol

77

UGT

O OH

-UDP OH

UDP glucuronic acid

COOH HO

O

HO

O OH

Phenyl glucuronide

Fig. 4.13  Glucuronidation of phenol by UDP-glycosyltransferase (UGT). Uridine 5¢-diphosphate (UDP) glucuronic acid is formed from glucose and UDP glucose dehydrogenase

4.4.2 Glycosyltransferases Uridine 5¢-diphospho-glucuronosyltransferase (UDP-glucuronosyltransferase, UGT) is a glycosyltransferase that catalyzes the glucuronidation reaction. Alternative names are glucuronyltransferase, UDP-glucuronyl transferase, or UDP-GT. In vertebrates, UGTs represent major phase II drug metabolizing enzymes, conjugating a wide ­variety of drugs, dietary phytoalexins, and endobiotics such as bilirubin and steroid hormones. They often work in concert with other drug metabolizing enzymes to convert lipid-soluble compounds into water-soluble and excretable forms. Lipophilic endo- and xenobiotics enter cells by passive diffusion or uptake transporters. Phase I enzymes, mainly CYPs, convert them into nucleophilic phenols and polyphenols or electrophiles, such as quinones and epoxides, which are then conjugated by phase II enzymes, such as UGTs and SULTs or GSTs, respectively. One typical glucuronation reaction is presented in Fig. 4.13. The resulting organic anions are removed from the cell by export transporters (phase III). A number of drug metabolizing enzymes ­rapidly interconvert nucleophiles and electrophiles (Bock 2003). Arguably the most important of the phase II (conjugative) enzymes in vertebrates, UGTs have been the subject of increasing scientific inquiry since the mid- to late-1990s. The reaction catalyzed by the UGT enzyme involves the addition of a glucuronic acid moiety to natural and synthetic xenobiotics. UGT is present in humans, other animals, plants, and bacteria. UGTs most probably evolved in vertebrates as a result of the struggle against PSM (Bock 2003). The story gets more obscure because recent advances in molecular biology show that with 107 UGT genes, Arabidopsis possess three- to four-times the numbers of UGT genes that vertebrates have (Yonekura-Sakakibara 2009). In comparison, the silkworm, Bombyx mori, for instance, possess only 42 putative UGT genes which is considered a high number in animals (Huang et  al. 2008). The UGT superfamily in higher plants is thought to encode enzymes that glycosylate a broad array of acceptor molecules, including phytohormones, all major classes of PSM, and xenobiotics such as herbicides. Plant UGTs are more substrate specific than the animal UGTs (Ross et  al. 2001), yet, the function of the majority of UGTs currently remains obscure (Yonekura-Sakakibara 2009). The function of several glucosinolates is well understood (Van Poecke 2007). Glucosinolates (Fig. 4.14) are amino acid-derived metabolites containing a sulfate

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Fig. 4.14  Chemical structure of glucosinolates, R = Allyl-, indolyl-, or benzyl-

Fig. 4.15  Phase II biotransformation of a polycyclic hydrocarbon, naphthalene, as facilitated in the liver of flounders. This step is the SULT catalyzed sulfation

O OH

O

S

OH O

Phase II SULT 1-hydroxy-naphthalene

1-naphthyl sulfate

and a thioglucose moiety. Depending on the amino acid from which they are derived, glucosinolates can be divided into three classes: aliphatic glucosinolates, aromatic glucosinolates, and indole glucosinolates. Glucosinolate-containing plants suffer less from insect herbivory than plants without glucosinolates. However, many herbivorous insect species have overcome glucosinolate-defenses and use them as oviposition and feeding stimulants, thus specializing on glucosinolate-containing plants. Glucosinolate-degradation products are also known to attract natural enemies of glucosinolate-adapted herbivores.

4.4.3 Sulfotransferases Membrane-bound sulfotransferases (SULTs) mainly catalyze endogenic substrates, whereas cytosolic sulfotransferases traditionally are known as the phase II drugmetabolizing or detoxifying enzymes that serve to detoxify drugs and other synthetic and natural xenobiotics (Fig. 4.15), particularly food allelochemicals. These enzymes in general catalyze the transfer of a sulfonate group from the active sulfate to low-molecular weight substrate compounds containing hydroxyl or amino group(s). Sulfation is not restricted to vertebrates, but appears to be an important step in the elimination of synthetic xenobiotics also in invertebrates such as Daphnia magna (Ikenaka et al. 2006). In zebrafish, Danio rerio, 15 SULTs have been characterized to date (Liu et al. 2010). These SULTs, which fall into four major SULT gene families, exhibit differential substrate specificities. Except for one family, none are known to metabolize xenobiotics. In plants, several sulfate conjugates have been shown to contribute to stress resistance or vice versa to induce stress symptoms in pests, pathogens, or herbivores. For instance, glucosinolates are thought to be central in the plant’s defense against microorganisms and predators; these compounds are thioglucosides derived from

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amino acids and are found in cruciferous plants (Brassicaceae). After tissue damage of food processing, the glucosinolates are hydrolyzed by a thioglucosidase enzyme to yield glucose and a variety of reactive products such as isothiocyanates, organic nitriles, and thiocyanates. Although glucosinolates are present in healthy plants, their concentration increases in response to fungal infection and mechanical wounding caused either by insect attack or mammalian herbivory (Varin et al. 1997). The recently characterized AtST1 is inducible in response to pathogen infection and to some herbicides (Marsolais et al. 2007). Choline sulfate accumulates in statice, Limonium sp., and all species of the salt stress-tolerant Plumbaginaceae family that have been investigated. It has been hypothesized that choline sulfate acts as an osmoprotectant in response to salinity or drought stress (Varin et al. 1997). More recently, it has been shown that the overexpression of a specific UGT gene increased salt stress-tolerance in A. thaliana (Tognetti et al. 2010).

4.4.4 Esterase and Hydrolase Two more enzyme families, esterases and hydrolases, are essential in the metabolism of natural and synthetic xenobiotics and are best understood with the metabolism of and resistance to pesticides. Esterases comprise a multi-functional and heterogeneous group of enzymes that have as a shared characteristic participation in ester hydrolysis. In insects, they are related to several metabolic processes such as food digestion, insecticide metabolism, pheromone production, and juvenile hormone hydrolysis. This family includes a number of enzymes with different substrate specificities, such as acetylcholinesterases. Carboxylesterase and organophosphorus hydrolase biochemically are closely related enzymes (Newcomb et al. 1997). Organophosphorus hydrolase is a naturally occurring enzyme which has the ability to hydrolyze organophosphates. Organophosphate is the general name for esters of phosphoric acid and is one of the organophosphorus compounds. They can be found as part of insecticides, herbicides, and nerve gases, amongst others. Organophosphorus pesticides inhibit acetylcholinesterase; hence, acetylcholine accumulates at nerve synapses and neuromuscular junctions. There exists evidence that acetylcholinesterase (AChE) activity, for instance in Daphnia, may serve as a biomarker for organophosphorus exposure (Printes et al. 2008). The authors showed that AChE activity was significantly associated with concentration and length of exposure to the selected organophosphorus pesticide.

4.5 Armament of Animals I: Biotransformation Phases I and II Due to enormous economic implications, most information on metabolism of natural and synthetic xenobiotics as well as resistance to pesticides derives from numerous studies in insects. With a delay of one or even more decades, less

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economically important organisms such as desert rodents, marine invertebrates, or c­ yanotoxin-resistant freshwater fish are subject of similar studies.

4.5.1 Insects Whereas insecticides tend to be applied as pure compounds, occasionally with synergists, allelochemicals almost invariably occur as complex mixtures of structurally related compounds (see the review by Li et al. 2007b). In addition, insecticides are designed to effect rapid mortality; many of the most successful and widely used are fast-acting neurotoxins. In contrast, allelochemicals can function effectively to protect plants from herbivory through non-preference or growth reduction. Owing to the idiosyncratic distribution of allelochemical biosynthesis among plant families, polyphagous insects likely encounter a broad diversity of chemical structures; in contrast, insecticides are often applied in a broadcast fashion and are more likely to be encountered irrespective of host plant identity. As a result, whereas the acquisition of metabolic resistance to insecticides within a species can be associated with an increase in tolerance of 10,000-fold or greater, intraspecific variation in metabolic resistance to allelochemicals tends to be of much smaller magnitude, but with significant effects on life traits as the “xenohormesis”-hypothesis explains. 4.5.1.1 Xenohormesis Pioneering studies with the yeast Saccharomyces cerevisiae and Drosophila (Howitz et al. 2003) have shown that a variety of PSM increase the lifespan of several organisms. Lamming et al. (2004) explored whether any of these effects are caused by the so-called sirtuin activation, a pathway highly favored as one major regulation in promoting lifespan and stress resistance. Sirtuin genes are found in all eukaryotes examined so far, including plants, fungi, and animals. Sirtuins are a class of proteins that possess either histone deacetylase or mono-ribosyltransferase activity. Because plants possess multiple sirtuins, it is reasonable to imagine that the sirtuin-activating polyphenols are actually stress-signaling molecules that coordinate sirtuin-mediated defenses in plants (Howitz et al. 2003). In fact, many of the polyphenols that activate the sirtuins, such as resveratrol and quercetin, are synthesized by plants during times of stress (e.g., infection, starvation, and dehydration). These findings raise the question: Why do plant stress molecules activate sirtuins from their predators? One explanation is that animals and fungi have since lost their ability to synthesize polyphenols but have retained the ability to be activated by these plant molecules because they provide a highly useful advance warning of a deteriorating environment and/or food supply, allowing organisms to begin conserving resources and increasing cell defenses (Fig. 4.16). This interspecies communication of stress signals has been termed “xenohormesis” (Howitz et al. 2003). This means that heterotrophs (animals and fungi) have evolved the ability to sense

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Fig. 4.16  The xenohormesis hypothesis (Howitz and Sinclair 2008, with permission from Elsevier) proposes that the common ancestor of plants and animals synthesized polyphenols. Since the divergence of phyla, there has been selection such that heterotrophs (animals and fungi) detect chemical cues about their environment from plants. These chemical cues would give the heterotroph advance warning about the deterioration of the environment, allowing them to prepare while conditions are still relatively favorable

signaling and stress-induced molecules from other species (plants), and that they are under selective pressure to do so. In essence, xenohormesis refers to interspecies hormesis, such that an animal or fungal species uses chemical cues from other species about the status of its environment or food supply to mount a preemptive defense response that increases its chances of survival. But why is this phenomenon called xenohormesis instead of hormesis (see Chap. 10)? The reason is that the stress occurs in one organism and the beneficiaries include other organisms that evolved to sense those chemical cues (Howitz and Sinclair 2008). When it comes to consumption of natural xenobiotics, it is important to distinguish xenohormetic effects from straightforward hormetic effects (Howitz and Sinclair 2008). The latter may result from low doses of toxins that cause a moderate biological stress, presumably cellular damage, thereby inducing a beneficial stress response. For the herbivores and omnivores and their responses to the more common

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dietary phytochemicals, hormesis is unlikely the primary mode of action. The authors further suggested that the majority of life trait benefits from phytochemical consumption result not from responses to mild cellular damage or from the antioxidant properties of polyphenols (for instance, see Saul et al. 2010) but rather from the evolutionarily adaptive modulation of the enzymes and receptors of stress-response pathways. Concurrent with the evolution of highly efficient detoxifying mechanisms, Howitz and Sinclair (2008) proposed that there has been selective pressure on animals and fungi to use the “information” content of plant secondary compounds of the environment. Mechanisms that minimize the dangers of toxins could thus have evolved concurrently without loss of the advantageous ability to use phytochemicals as molecular signals. In other words, the xenohormetic and hormetic modes of action are not mutually exclusive, even for the same compound, and may well function synergistically in response to the complex mixtures of phytochemicals in food. 4.5.1.2 CYP and Allelochemical Tolerance Insect CYPs play a paramount role in allelochemical metabolism and tolerance. CYPs metabolize all classes of plant allelochemicals (including furanocoumarins, terpenoids, indoles, glucosinolates, flavonoids, cardenolides, phenylpropenes, ketohydrocarbons, alkaloids, lignans, pyrethrins, and the isoflavonoid rotenone) because of their catalytic versatility and broad substrate specificity. Moreover, many intact host plants (including corn, parsnip, parsley, cowpeas, cotton, peanuts, soybean, and hairy indigo) and isolated allelochemicals (including monoterpenes, indoles, furanocoumarins, and flavones) induce expression of particular CYPs (Li et al. 2007a, b). Perhaps best characterized are the CYPs involved in furanocoumarin metabolism within the genus Papilio (Li et al. 2007b; Schuler 2011). The first two CYP cDNAs, CYP6B1v1 and CYP6B3v1, were isolated from the black swallowtail butterfly, P. polyxenes, a specialist restricted to feeding on furanocoumarin-containing plants in the families Apiaceae and Rutaceae. Subsequently, cDNAs representing 16 CYP6B genes were isolated from P. glaucus and P. canadensis, two more polyphagous papilionids. Transcripts of all these CYPs are inducible by furanocoumarins at ecologically relevant concentrations. Meanwhile, additional strong evidence for CYP participation in plant allelochemical metabolism exists for several other insects. Specialist/Generalist Counter Defense Strategies: CYP6Bs as a Paradigm Specialization and generalization represent ends of the spectrum for the utilization of host plants by herbivorous insects. Whereas specialists typically encounter high levels of a narrow and predictable range of dietary allelochemicals, generalists have to cope with a tremendous diversity of allelochemicals idiosyncratically distributed among potential host plants. To overcome their unique toxicological challenges, in

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theory specialists should have a highly efficient and specialized detoxification system, whereas generalists require an all-purpose detoxification system capable of degrading a broad range of plant toxins present in their host plants as well as complex regulatory machinery capable of inducing a subset of enzymes when encountering a particular allelochemical (Li et al. 2007a, b). Li et al. (2007a, b)) refer to the well-documented comparison of butterfly and worm species. Long-term studies focusing on CYP-mediated allelochemical metabolism in two specialists (the butterfly, P. polyxenes, and the parsnip webworm, Depressaria pastinacella) and three generalists (the butterflies, P. glaucus and P. canadensis, and the corn earworm, Helicoverpa zea) provide a paradigm for dissecting the evolutionary and molecular mechanisms that facilitate polyphagy and specialization. These five lepidopteran species are able to feed on furanocoumarin-containing plants, but their host ranges and the rate at which they encounter furanocoumarins differ significantly. The two specialists feed exclusively on furanocoumarin-containing plants. Among the generalists, P. glaucus feeds occasionally on furanocoumarin-containing host plants, H. zea feeds rarely on furanocoumarin-containing host plants, and P. canadensis normally does not encounter furanocoumarins in any of its host plants. From these five species, two CYP6B genes have been characterized from each of the two specialists, nine have been characterized from each of the Papilio generalists, and four have been characterized from H. zea. The differential recovery rates of CYP6B sequences favor the hypothesis that generalists may have more allelochemical-metabolizing genes to cope with the diversity of allelochemicals they encounter. Metabolic data showed that CYP6B8 of the generalists efficiently metabolized six diverse plant allelochemicals (xanthotoxin, quercetin, flavone, chlorogenic acid, indole-3-carbinol, and rutin) and CYP6B1 of the specialists efficiently metabolized linear and angular furanocoumarins (xanthotoxin and angelicin) and less efficiently metabolized flavone and a-napthoflavone. Furthermore, CYP-mediated constitutive metabolism of furanocoumarins is significantly higher in the two specialists than in the three generalists. The inducibility of CYP-mediated furanocoumarin metabolism, however, is generally higher in the three generalists than in the two specialists. Consistent with these larval metabolism assays, transcripts of the specialist P. polyxenes CYP6B1 are constitutively detectable but barely inducible by xanthotoxin, whereas transcripts of the generalist P. glaucus CYP6B4 are barely detectable but highly inducible by xanthotoxin (Li et al. 2007a, b). For almost four decades, it has been hypothesized that the ability to cope with a toxin-rich diet serves as a pre-adaptation for the acquisition of insecticide resistance (Gordon 1961). Because many synthetic insecticides resemble plant allelochemicals or are, in the case of the pyrethroids, derived from them, the possibility exists that the CYPs responsible for insecticide detoxification have evolved from the CYPs responsible for allelochemical detoxification. Studies on H. zea support this notion. In this species, exposure to xanthotoxin enhanced resistance to the insecticide cypermethrin, with at least two CYPs capable of metabolizing both substrates (Li et al. 2007a, b). A study with the Colorado potato beetle, Leptinotarsa decemlineata, demonstrates how the concert of genes of the various biotransformation phases are modulated

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by different food plants of one family. Zhang et al. (2008) tested this beetle that mainly feeds on potatoes but also on other solanaceous host plants, such as tomatoes, peppers, or eggplants. The authors checked 38 CYP, three GST, and three esterase genes and showed that major modulation occurred with the CYP rather than GST or EST genes. In particular, CYP4BN13v1 was up-regulated after the beetles were transferred from potato to tomato, pepper, or eggplant. 4.5.1.3 Glutathione Transferases, Esterases and Hydrolase Biochemical assays have demonstrated the inducibility of GSTs by allelochemicals and host plant foliage. Among the most potent inducers are host plants in the Apiaceae (including parsley, Petroselinum crispum, and parsnip, Pastinaca sativa) and Brassicaceae (crucifers) families; among the active allelochemical inducers are furanocoumarins, indoles, flavonoids, isothiocyanates, a,b-unsaturated carbonyls, and glucosinolates. Some allelochemicals, however, act as potent GST inhibitors (quercetin, ellagic acid, juglone, apigenin, and tannic acid) or transcription repressors (quercetin). Despite the potato beetle study above, esterase involvement in allelochemical metabolism and tolerance in insects was documented only at the biochemical level with butterflies. For instance, two closely related tiger swallowtails, P. glaucus and P. canadensis, are differentially tolerant of phenolic glycosides, mediated through esterases. In the tobacco cutworm, Spodoptera litura, sublethal doses of the widely occurring plant glycoside rutin resulted in a significant increase in midgut carboxylesterase activity, even though it is not metabolized. A third case involves the gypsy moth, Lymantria dispar, in which the survival of first instars feeding on diets containing phenolic glycosides was positively correlated with esterase activity (Li et al. 2007a, b). GSTs as Protector Against Oxidative Stress GSTs play a vital role in the inactivation of toxic products of oxygen metabolism. Blood-feeding insects such as mosquitoes face a particular challenge from oxidative stress, because the digestion of hemoglobin results in a massive production of ROS. These ROS trigger a cascade of reactions that can be highly damaging to the cells. They can cause the inactivation of enzymes through conformational change, degrade DNA, and damage cellular membranes by the conversion of polyunsaturated fatty acids to lipid hydroperoxides. These in turn can give rise to highly reactive a,b-unsaturated aldehydes that, although essential components of signaling pathways, are toxic at high concentrations. Delta and sigma insect GSTs can detoxify these aldehydes by conjugation with glutathione (Ranson and Hemingway 2005). Microcystin Tolerance in Freshwater Fishes With considerable delay, studies of the effect of food allelochemicals were conducted in animals other than insects. These studies focused on contrasting tolerances of

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O

HO

H 3C H3C

N O O

H3C

O

N NH CH2

CH3

OH

O NH CH3

CH3

O

CH3

H N

NH H N

O NH2 HN

O O

OH

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CH3

NH

Fig. 4.17  Structure of microcystin-LR, the most studied microcystins of over 80 known variants

freshwater fishes consuming cyanotoxin-containing food, on different food specialists among desert rodents, and marine snails feeding on chemically defended prey. Microcystins are a family of potent hepatotoxins produced by cyanobacteria. Since cyanobacterial blooms increase significantly in eutrophic water bodies worldwide, cyanotoxins have become a health threat to humans as well as to terrestrial and aquatic wildlife. Microcystin-LR (MC-LR) (Fig.  4.17), the most commonly encountered toxic type, specifically inhibits the serine/threonine protein phosphatases (PP1 and PP2A), resulting in the disruption of many cellular processes and alteration of cytoskeletal structures. As heptapeptides, microcystins possess many functional groups and hence do not require functionalization in phase I and are subject to glutathione transferase activity instead. Previous studies indicated that the detoxification of MC-LR in the liver indeed begins with a conjugation reaction to glutathione catalyzed by GSTs (Pflugmacher et al. 1998). Compared to mammals, fish, especially phytoplanktivorous species such as silver carp (Hypophthalmichthys molitrix), bighead carp (H. nobilis), and Nile tilapia (Oreochromis niloticus niloticus), are rather resistant to MC-LR (Xie et al. 2004) and can even use the nutrient and energy content of toxic cyanobacteria. The question arises whether or not the tolerance of these fishes is based on the inducibility of specific GST classes (for details of the classification, see Appendix 2). Subsequently, Liang et  al. (2007) elucidated the underlying mechanism of the contrasting sensitivity by comparing the MC-tolerant fish species, silver carp and Nile tilapia, with the sensitive grass carp (Ctenopharyngodon idella). They studied the semi-quantitative mRNA expression of alpha- and rho-class GST and found a close relationship between inducibility and tolerance: highly resistant silver carp and Nile tilapia had inducible liver expression of either alpha- or rho-class GST, whereas the sensitive grass carp had no inducible expression of either one (Fig. 4.18). This shows that inducible rather than constitutive expression of the liver GST gene is the

Fig. 4.18  Relative alphaand rho-class GST mRNA concentration in three fish species of contrasting sensitivity exposed to microcystin-LR: Silver carp Hypophthalmichthys molitrix (MC-resistant), Nile tilapia Oreochromis niloticus (MC-resistant), and grass carp Ctenopharyngodon idella (MC-sensitive) (From Liang et al. 2007. With permission from Wiley). PBS = phosphate buffered saline = physiological blank. Different letters indicate significant differences

Ratio GST/beta-actin m RNA (%)

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major means of fish tolerance to microcystins. Recent studies imply that exporter proteins also may be involved in MC-tolerance: Amé et al. (2009) showed that P-gp expression responded to MC-exposure in one fish species. However, the comparison of this resistant species with a related sensitive fish species is currently lacking.

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Table 4.3  Number of phase I and phase II genes up-regulated in two Neotoma species fed diets of different juniper content (From Skopec et al. 2007. With permission from Elsevier) Generalist N. albigula Specialist N. stephensi Terpene-free vs 25% Terpene-free vs 25% juniper 25% juniper vs 70% juniper juniper Phase I Phase II

0 0

4 0

5 2

Bush Rats: Generalists vs. Specialists In mammalian herbivores, dietary specialization is uncommon. Freeland and Janzen (1974) proposed an interesting hypothesis: the lack of dietary specialization in mammalian herbivores is due to a limitation of the detoxification system in processing large quantities of a single type of PSM. Consequently, most mammalian herbivores are thought to eat a variety of plants to avoid consuming high levels of a single PSM that would overwhelm their detoxification system. The progress in biotransformation research resulted in an update of this hypothesis such that specialists are predicted to rely more on phase I enzymes that are less energetically costly than phase II enzymes which utilize more energy during detoxification because the conjugate is lost when the metabolite is excreted (Skopec et al. 2007). Hence, specialist mammalian herbivores should rely less on phase II enzymes to minimize the loss of conjugates than generalists. Because specialists theoretically consume fewer types of PSM, they can rely more on the substrate specific pathways of the phase I system. Supporting evidence for this hypothesis is that dietary generalists excrete higher levels of phase II metabolites in urine than dietary specialists (Sørensen et al. 2005). Based on this background, Skopec et  al. (2007) studied dietary specialization within Neotoma woodrats feeding on plants with very disparate PSM. The authors focused on the specialist N. stephensi and its sympatric generalist, N. albigula. N. stephensi is a specialist on one-seeded juniper Juniperus monosperma which comprises 70% or more of its diet. N. albigula, in contrast, consumes only 25% juniper in its diet. Juniper is an evergreen containing high levels of monoterpenes, with toxic alpha-pinene being the most abundant terpene. In fact, N. stephensi has a superior ability to detoxify alpha-pinene by phase I enzymes (Haley et al. 2007a). Skopec et  al. (2007) expanded this study by simultaneously measuring the expression of genes in the liver. They examined whether the specialist’s greater capacity for juniper consumption is due to unique hepatic gene regulation in response to juniper or to innate differences between the species in hepatic gene expression. As predicted, there were significant transcriptional differences in 11 detoxification genes (Table 4.3). Specialist N. stephensi on juniper diets up-regulated more genes encoding for phase I enzymes than phase II enzymes. In contrast, N. albigula did not up-regulate any genes encoding for phase I or phase II enzymes. These results confirm the above findings in specialist insects in which a high number of biotransformation enzymes is inducible after ingesting the allelochemical-rich diet. This confirms that the woodrat specialist’s ability to feed on juniper is not due to constitutive levels of gene expression, instead it can respond to high levels of juniper with large

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changes in hepatic gene regulation. Furthermore, in corroboration of the updated hypothesis of Freeland and Janzen (1974), the inducible enzymes belong to phase I rather than phase II because of energetic reasons. In a second pair of Neotoma specialist/generalists (N. macrotis/lepida), however, this hypothesis could not be confirmed (Haley et al. 2007b). The phase I genes that were up-regulated in N. stephensi fed the 70% juniper diet were five CYPs (CYPolf1, CYP1A2, CYP2A, CYP3A, and CYP2B) as well as glutathione peroxidase. All these up-regulated CYPs have exogenous compounds as substrates. In addition, two phase II genes were up-regulated: heparan sulfate 6-sulfotransferase 1 (HS6ST1) and catecholamine-O-methyltransferase (COMT). Heparan sulfate-6-sulfotransferase is involved in the metabolism of heparan sulfate that plays an integral role in blood coagulation. COMT conjugates a methyl group to its substrate. The loss of a methyl group as a conjugate may be less energetically costly than glucose or amino acid conjugates used by other phase II enzymes. What happens if herbivores have to change their diet? As we have seen, the diet breadth of herbivores as well as the ability to adapt to new dietary components is thought to be governed by biotransformation enzymes in the liver. Magnanou et al. (2009) studied the gene expression in the generalist woodrat (Neotoma lepida). They compared a population from the Great Basin that fed on the ancestral diet of juniper to one population from the Mojave Desert that putatively switched from juniper to creosote (Larrea tridentate). Juniper and creosote have notable differences in PSM and thus should require different biotransformation enzymes for detoxification. Indeed, dietary shifts between plants with disparate chemistry such as juniper and creosote necessitates more extensive changes in biotransformation mechanisms than plants with similar chemistries such as juniper and cedar (both terpene-rich). This study confirms the hypothesis that biotransformation enzymes limit diet switching.

Marine Snails: Generalists vs. Specialists Similar to their terrestrial counterparts, marine consumers that regularly feed on allelochemically-rich prey have evolved a parallel suite of biochemical resistance mechanisms. The induction or high constitutive activity of GSTs seen in several marine molluscs after allelochemical exposure has been suggested as a protective mechanism against dietary intoxification. For instance, high cytosolic GST activity was observed from the digestive gland of the generalist marine gastropod Cyphoma gibbosum. This gastropod predator utilizes three families of gorgonian corals as hosts and in doing so encounters a range of lipophilic allelochemicals that includes diterpenes, sesquiterpenes, acetogens, highly-functionalized steroids and eicosanoids (Whalen et al. 2010a). The authors found that Cyphoma GST subunit composition was invariant and activity was constitutively high regardless of gorgonian diet. This confirms that, as

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seen already in insects, generalist GSTs operate as all-purpose detoxification enzymes thereby allowing this predator to exploit a range of chemically-defended prey, resulting in a competitive dietary advantage for this species (Whalen et  al. 2010a). In addition to phase II enzymes, exporters also play a central role in the allelochemical tolerance of generalists (see below). 4.5.1.4 Ecological Significance of UGT Since UGT is a major enzyme in vertebrates, less attention is paid to its ecological and ecophysiological significance in invertebrates. In a transcriptional study with the nematode C. elegans exposed to two different humic substance sources, Menzel et al. (2005b) showed that one gene in particular that encodes a UGT was most responsive to one of the humic preparations. This gene was much more responsive than CYP genes, indicating that humic materials, which are rich in functional groups and relatively hydrophilic, can immediately enter phase II of the biotransformation system. More recently, Daimon et al. (2010) have published one surprising example with silkworms. In the silkworm, Bombyx mori, dietary flavonoids are metabolized and accumulate in cocoons, thereby causing green coloration. The green color is a product of the UDP-glucosyltransferase. When the silkworms were exposed to UV irradiation, it became obvious that flavonoids increase the UV resistance of cocoons and thus could confer an increased survival advantage to insects contained in these cocoons.

4.6 Armament of Animals II: Exporters (Phase 0 and III) Besides the well studied phase I and II enzyme systems, a new principle for handling natural and synthetic xenobiotics has arisen from an appreciation of the role of multidrug transporters which prevent putative toxins from entering the cells in the first place. This mechanism is not detoxification sensu strictu but is more akin to a ‘first line of defense’ against xenobiotics (Epel 1998). This mechanism depends on the relatively low substrate specificity of the multidrug transporters which use ATP to pump a variety of potentially toxic compounds out of the organism so that damage to cell constituents is minimized. These multi-drug transporters have been well characterized in bacteria and mammals (Krishnamurthy and Schuetz 2006) and particularly studied in relation to cancer therapy where the amplification of this transporter correlates with acquired resistance of the tumor to a wide variety of chemotherapeutic drugs. This phenomenon is referred to as multidrug resistance, and these transporters are referred to as “transporters, multidrug resistance”. Another name for this transport protein is the P-glycoprotein, the ‘P’ referring to its permeability-altering properties and the ‘glycoprotein’ referring to the high degree of glycosylation of these proteins (Epel 1998). These transporters belong to a related family of proteins referred to as the ABC family. Three ABC subfamilies have toxicologically relevant efflux

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activity: P-glycoproteins, multidrug resistance proteins, and the ABCG family (formerly breast cancer resistance protein, BCRP) transporters (Epel et al. 2008). A much higher number of transporters are found in plants than in animals (for detailed information, see Appendix 3). Many transporters are remarkably nonspecific with respect to their substrates. This lack of specificity is adaptive and part of the arms race, since it provides predators with a mechanism to keep pace with the evolution of the new natural-defense molecules of their prey and fortunately protects against many novel anthropogenic products (Epel et al. 2008). A number of environmental researchers have directed their attention to the role of this transporter in protecting aquatic organisms against natural and synthetic xenobiotics. The pioneering work on the environmental role of this transporter came from Kurelec and Pivcevic (1989) who showed that membrane vesicles from the zebramussel, Dreissena polymorpha, possessed properties indicative of the multidrug transporters. Several studies have proved that the P-glycoproteins can be induced by a variety of chemical compounds. Recently, sequences and functional data for MDR/MXR transporters have been published for zebrafish, Danio rerio, and rainbow trout, Oncorhynchus mykiss (Annilo et  al. 2006; Zaja et  al. 2008; Fischer et al. 2010; Lončar et al. 2010). Interestingly, Zucchi et al. (2010) were able to induce genes for ABC proteins in an Antarctic notothenioid fish species (the rock cod, Trematomus bernacchii) which is a bioindicator species of Cd in the Southern Ocean. The corresponding protein products also were found. Although Cd is not a substrate of ABC transporters, the MXR system was involved in mitigating toxic effects even of this heavy metal.

4.6.1 Chemosensitization There is growing concern that the activity of ABC transporters can be affected by environmental chemicals (Fig. 4.19). A consequence of this inhibition of transporter action could be increased sensitivity of cells and tissues to toxic transporter substrates, referred to as chemosensitization. A variety of environmentally relevant chemicals have been identified that can cause chemosensitization, including pesticides, fragrance compounds and others (Smital et al. 2004). So far, many xenobiotics and also some natural products, particularly biomolecules from marine algae, have been found to act as chemosensors. The question arises whether or not humic substances (HSs) also lead to chemosensitization. Indeed they do, as exemplified with the amphipod Eulimnogammarus cyaneus (Fig. 4.20). The presence of HS increased the residual concentration of rhodamine B in this amphipod (rhodamine B is an easily detectable model xenobiotic compound used in MXR studies). The results indicate that the presence of HS modified the MXR activity. This chemosensitization depends on both exposure concentration and exposure time.

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Fig. 4.19  Efflux transporters prevent fluorescent dyes from entering the cytoplasm and provide a simple means of assaying activity. The sequence on the left shows effective exclusion of a fluorescing dye from cells and tissues of three different aquatic organisms. The sequence on the right depicts the consequences of inhibiting transport activity in the same material. As shown, only a small amount of the dye enters unless the transporter is inhibited (From Epel et al. 2008. With permission from the American Chemical Society)

The results above also answer another question. In their review, Haitzer et  al. (1998) found that seven out of 27 studies reported an increase in bioconcentration of synthetic xenobiotics when the animals were co-exposed to HSs at relatively low concentrations. Although several hypotheses were discussed by Haitzer et al. (1998) and Steinberg (2003), none appeared to be convincing and a subsequent experimental verification failed (Haitzer et al. 2001). The chemosensitization of exporters by dissolved HSs has not been discussed; however, this mechanism appears best to explain the increased internal xenobiotic concentrations.

0

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3 Exposure time, h

6

Fig. 4.20  Modulation of the exporter activity by natural organic matter (NOM) from Lake Schwarzer See in the amphipod Eulimnogammarus cyaneus as shown by the rhodamine B efflux method. The animals were exposed to two DOC concentrations (7.5 and 15 mg l−1); data represent the residual concentrations in the animals (Modified from Timofeyev et al. 2007. With permission from Elsevier)

4.6.2 Multixenobiotic Transporters as Defense Against Dietary Allelochemicals It has been suggested that ABC transporters also are responsible for regulating the absorption of allelochemicals in the guts of consumers and may therefore influence the foraging patterns and ultimately diet choice of these organisms (Sorensen and Dearing 2006). If inducers of MXR activity are present in sufficient concentration in the diet, ingestion of compounds could result in the enhanced efflux of co-ingested allelochemicals and possibly promote feeding. In this respect, Whalen et al. (2010b) characterized the MXR proteins involved in resistance to dietary allelochemicals in two species of tropical gastropods that feed exclusively on allelochemically defended gorgonian corals: Tritonia hamnerorum, a specialist, and Cyphoma gibbosum, a generalist. The authors showed that proteins with homology to P-gps were highly expressed in T. hamnerorum and demonstrated the activity of P-gp and MRP families of ABC transporters. In C. gibbosum, MRP-1 (a homolog of vertebrate glutathione-conjugate transporters) were constitutively expressed regardless of gorgonian diet. Overall, constitutive expression of selected promiscuous exporters is advantageous to the generalist predator that maintains a chemically diverse diet. The involvement of exporters complete the mosaic of all-purpose allelochemical detoxification in generalists.

4.7 Body-Maintenance vs. Xenobiotic Biotransformation Animals spend much energy in overcoming adverse effects of food allelochemicals by metabolizing them and by exporting educts or metabolites. Yet, what happens if animals are challenged by energy limitation? How do they allocate needed energy

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Fig. 4.21  Activity of cytochrome P450 enzymes in rainbow trout, measured as EROD activity, exposed to three diet regimes [(■) full-rations, (○) half-rations, (D)] fasted for 9 weeks followed by re-feeding of all treatment groups on full-rations. * denotes significant differences from initial EROD activity within a treatment group (p < 0.05) (From Gourley and Kennedy 2009. With permission from Elsevier)

under conditions of energy deprivation? This fundamental issue is especially pertinent with teleost fish, which are often exposed to natural conditions of fluctuating food availability and intake. Fasting and starvation require organisms to successively catabolize glycogen, lipid, and protein stores in the body for survival. In addition to natural periods of limited energy, exposure to chemical stressors can increase energy demand, causing decreases in available energy for other purposes resulting in reductions in voluntary activity, mobilization of available energy reserves, and delayed reproductive activities. Limited energy intake may result in the down-regulation of cellular defense mechanisms, or if maintained, result in trade-offs with other physiological systems. In other words, such trade-offs may impinge on the success of the individual organism’s foraging, migration, and escape behaviors, and on the reproductive capacity of the population (De Coen and Janssen 2003). To examine the outcome of such trade-offs, Gourley and Kennedy (2009) tested juvenile rainbow trout, Oncorhynchus mykiss, and found that P-gp (ABCB1) and CYP activities were maintained in trout fasted for 9 weeks and appear to be prioritized physiological mechanisms even under conditions of long-term fasting (Fig. 4.21). Conversely, GST enzyme activity does not appear to be recalcitrant under fasting conditions and was significantly attenuated within 6 weeks of treatment. However, down-regulated GST activity was recoverable after 1 week of re-feeding, demonstrating response plasticity in an organism adapted to tolerate changes in food

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availability. Calorie-restricted and fasted trout also exhibited dynamic changes in whole body measures over this period, suggesting that body stores were catabolized to mobilize energy resources to support these systems, amongst others. New research suggests that scarcity-sensing proteins may regulate these biochemical and physiological changes (Bordone and Guarente 2005). Signaling molecules of interest include sirtuin proteins, which in starved mammals provide the organism with a greater capacity to metabolize fat and take up glucose as well as increase insulin sensitivity and reduce lipid accumulation in the liver (Bordone and Guarente 2005). Bile acids have also been suggested as signaling molecules in mammals capable of modulating transcription of proteins involved in phase I, II, and III defense systems and metabolic pathways via membrane and nuclear receptors, both of which have been identified in fish (Gems 2007; Gourley and Kennedy 2009). Overall, the described strategy of energy allocation in juvenile rainbow trout implies that animals, in general, take the arms race between prey and predator very seriously and, more particularly, even the fasted fish is well prepared to feed on prey rich in natural xenobiotics if available again.

4.8 Ecological Significance of Individual Biotransformation Components Biotransformation enzymes are involved in the formation of PSM as well as lipid and hormone metabolism and homeostasis. As seen, PSM are natural xenobiotic compounds for animals; consequently, one main task of the biotransformation system in animals is the metabolism of xenobiotics. Due to their low substrate specificity, this system does not only attack natural but also anthropogenic xenobiotic compounds. The low substrate specificity of the biotransformation system will be demonstrated with a few key examples before we learn that herbivores may use the armaments of the plants to attack their enemies. Furthermore, we shall learn about the risk of self-intoxification, about fish who survive the contamination of Superfund sites, and about the relationship between pesticide resistance and plants and animals – an important economic issue in agriculture. In all cases, biotransformation enzymes are central.

4.8.1 Natural and Synthetic Xenobiotics 4.8.1.1 Cytochrome P450 Cytochrome P450 1A (CYP1A) induction is used widely as a biomarker of exposure to pollutants such as petroleum hydrocarbons. Matsuo et al. (2006) evaluated CYP1A induction in an Amazonian fish, Colossoma macropomum, acclimated to humic substances and acutely exposed to crude oil. Humic substances are ubiquitous in Amazonian waters, and they are known to affect the bioavailability of pollutants.

nmol pyrene equv g-1 w.w.

4.8  Ecological Significance of Individual Biotransformation Components

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PBO concentration, µg l-1

Fig. 4.22  Effect of piperonyl butoxide (PBO, a general inhibitor of CYP activity) on tissue concentration of pyrene and its metabolites in Daphnia magna after 24 h exposure in organic carbon-free artificial freshwater. The black bars represent the proportion of parent pyrene and the white bars represent the proportion of metabolites (From Akkanen and Kukkonen 2003. With permission from Elsevier)

Crude oil induced CYP1A expression in C. macropomum, as expected. Exposure to both humic substances and crude oil resulted in greater levels of CYP1A expression relative to that in fish exposed to petroleum alone. Interestingly, CYP1A induction was also observed in fish exposed to HSs alone. The corresponding CYP proteins also were detected. Induction by HSs was concentration dependent, and activity was higher in fish exposed to humic substances from a commercial source than in fish exposed to the HSs from a natural source. The results show that there are as yet unknown CYP1A inducing components (aryl hydrocarbon receptor agonists) in HSs (see also Menzel et al. 2005b). In a study with the crustacean, Daphnia magna, Akkanen and Kukkonen (2003) showed that this invertebrate species also possesses the capability to efficiently metabolize polycyclic aromatic hydrocarbons, as exemplified with pyrene (Fig. 4.22). The authors analyzed 14C-labelled educts and products after 24 h and found almost 90% of the internalized pyrene was metabolized. After adding piperonyl butoxide, a general CYP inhibitor, the share of non-metabolized pyrene increased, indicating the involvement of CYP monooxygenases in biotransformation. 4.8.1.2 Glutathione Transferase An approach comparable to the Amazonian fish exposed to natural and synthetic xenobiotics was chosen by Meems et al. (2004) in studying Daphnia magna and its GST activity when exposed to the insecticide cypermethrin alone and in combination with synthetic humic preparation, HS 1500 (for information, see Meinelt et al. 2007). HS 1500 alone caused an increase in cytosolic (soluble) GST activity in a concentration-dependent fashion (Fig. 4.23). In contrast to the fish study, however, combined exposure decreased the sGST activities below both single exposures

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200

150

5 100

50

CM 0.1 µg l -1-1CM

Fig. 4.24  Soluble GST activities in Daphnia magna after 24-h treatment with 5.0 or 50 mg l−1 of the artificial humic substance, HS 1500, plus 0.1 mg l−1 cypermethrin in combination, expressed as relative changes compared to the blank control. CM cypermethrin (From Meems et al. 2004. With permission from Elsevier)

sGST activity, % of control

Fig. 4.23  Concentrationdependent increase of soluble GST activity in Daphnia magna after 24-h exposure to HS1500, a synthetic humic substance (From Meems et al. 2004. With permission from Elsevier)

HS1500, mg l-1

5

50

HS1500, mg l-1 + 0.1 µg l-1 CM

(Fig. 4.24) which was probably due to complex formation and subsequent reduced bioavailability of both xenobiotics.

4.8.2 Herbivores Use Plants’ Armaments in Defense Against Their Own Enemies As we have seen above, insect herbivores by necessity have to deal with a large arsenal of plant defense metabolites. The idea of plant secondary compounds functioning as defense agents in plants implies their deleteriousness to non-adapted

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herbivores. Adapted herbivores metabolize, but do not mineralize or only sequester these compounds. Do these animals benefit from their tolerance against these chemicals? Several studies indicate that they do. For instance, Narberhaus et al. (2005) proved that leaf beetles, Longitarsus anchusae, are adapted to pyrrolizidine alkaloids, PSM commonly found in the families Asteraceae, Boraginaceae, and Fabaceae, and accumulate these compounds as N-oxides. Through a series of prey choice experiments with three carabid predator species, chemically non-protected bark beetle, Pityogenes chalcographus, pupae were chosen almost uniformly over L. anchusae pupae. This finding is supported by a meta-analysis of 85 species of Lepidoptera feeding on 40 hosts (Coley et  al. 2006) which revealed that species feeding on mature leaves with high contents of PSM were the most defended. Those species feeding on fast-expanding young leaves with low contents of PSM were the least defended and most preferred as prey by ants. Female insects make use of PSM to protect their eggs against oophages. Several species are known which load their eggs with dietary sequestered components and turn these plant effronteries against potential adversaries, thus appropriating the plant’s chemical defenses. Insect eggs clearly benefit from the ability of their mothers and sometimes their fathers to ingest and sequester plant toxins that can be channeled to their eggs. Various glycosides (e.g., catalpol), glucosinolates and their hydrolysis products (mustard oil), steroids (e.g., cucurbitacins), and other terpenes, phenolypropanoids, aristolochic acids, cyanogenic compounds, and alkaloids can be sequestered in hemolymph, most often in un-metabolized form (Nishida and Fukami 1990; Hilker and Meiners 2002; Opitz et al. 2010) The aforementioned interactions structure even biocenoses. Marine and terrestrial studies show convincingly that small, sedentary herbivores that utilize plants as both food and habitat can gain enemy-free space by living on hosts that are chemically defended from larger, generalist consumers. Although large herbivores are increasingly recognized as important consumers of macrophytes in freshwater communities, the potential indirect effects of herbivory on plant-associated macroinvertebrates were studied only recently by Parker et al. (2007). The authors showed that the large, generalist consumers in a riverine system, Canada geese, Branta canadensis, and crayfish, Procambarus spiculifer, both selectively consumed riverweed, Podostemum ceratophyllum, over an aquatic moss, Fontinalis novae-angliae (Fig. 4.25), even though moss comprised nearly 90% of the total plant biomass on riverine rocky shoals. Moss supported twice as many plant-associated macroinvertebrates as riverweed, suggesting that it might provide a spatial refuge from consumption by these larger consumers. In contrast to results with Canada geese and crayfish, both the amphipod, Crangonyx gracilis, and the isopod, Asellus aquaticus, consumed significant amounts of moss but rejected riverweed in laboratory feeding assays. Moreover, neither amphipod nor isopod feeding was deterred by the crude organic extract of Fontinalis, suggesting that these mesograzers tolerate or circumvent the chemical defenses that deterred larger consumers. Thus, herbivory by large, generalist herbivores may drive freshwater plant community structure towards chemically defended plants and favor the ecological specialization of smaller, less mobile herbivores on unpalatable hosts that represent enemy-free space (Fig. 4.26).

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Fig. 4.25  Percentage of (a) Canada geese, Branta canadensis, and (b) crayfish, Procambarus spiculifer, feeding on fresh tissues from six aquatic macrophyte species collected from the Chattahoochee River (Georgia, USA). Statistics are from Fisher’s exact tests assessing feeding on each plant relative to a palatable control food that was always consumed (bread for geese, Ludwigia palustris for crayfish) for each consumer species (From Parker et al. 2007. With permission from Wiley)

Fig. 4.26  Abundance of plant-associated macroinvertebrates per gram of wet Podostemum ceratophyllum (riverweed) and Fontinalis novae-angliae (aquatic moss) collected from the Chattahoochee River (Georgia, USA). Statistics are from t-tests (From Parker et al. 2007. With permission from Wiley)

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The benefit of prey animals by using PSM as weapons is not only restricted to prey-predator interactions but applies also to the host-parasite relationship. For example, although the quality of the food plant Lolium perenne (perennial ryegrass) as a host plant for the Argentine stem weevil, Listronotus bonariensis, is reduced by the presence of several alkaloids produced by the wild type of the fungal endophyte Neotyphodium lolii, these alkaloids also affect the parasitoid, Microctonus hyperodae, when its host feeds on L. perenne infected by the fungus. In laboratory cages, parasitism of L. bonariensis was reduced when M. hyperodae adults were presented with hosts provided with ryegrass infected with N. lolii. In other experiments, M. hyperodae larval development times were extended when L. bonariensis was fed infected ryegrass (Urrutia et al. 2007). This bottom-up effect applies even to an more complex trophic relationship. This was shown for the solitary hyperparasitoid Lysibia nana (Hymenoptera: Ichneumonidae) which parasitizes the gregarious endoparatoid Cotesia glomerata (Hymenoptera: Braconidae), which in turn uses caterpillars of cabbage white butterflies (Pieris). Harvey et al. (2004) showed that plant and herbivore quality were important factors affecting the development of L. nana as mediated through plant glucosinolates via the primary parasitoid host (Pieris sp.).

4.8.3 How to Survive the Contamination of Superfund Sites? Due to the low substrate specificity of many biotransformation enzymes, most synthetic xenobiotics are attacked with the result that often metabolites with increased toxicity are produced. As a consequence, exposed animals intoxicate themselves when trying to get rid of the xenobiotics. However, it has been recognized that toxic and persistent anthropogenic contaminants may also act as selective agents. There is evidence for rapid adaptation/acclimation to environmental metal exposures by aquatic invertebrates and vertebrates indigenous to an industrial cove (Nacci et al. 1999). For instance, populations of killifish, Fundulus heteroclitus, collected from estuaries contaminated with complex mixtures of organic and inorganic compounds were characterized as tolerant to selected local contaminants. For example, killifish collected from dioxin-contaminated Newark Bay (New Jersey, USA), a so-called Superfund site, were shown to be less sensitive than fish from reference sites when challenged with dioxin or toxicologically similar compounds in the laboratory (Nacci et al. 1999). To test the hypothesis that wild populations of killifish persisting under intense and constant exposure to highly toxic contaminants display evidence of resistance which may be genetic adaptation or controlled by epigenetic mechanisms, Nacci et al. (1999) examined contaminant responsiveness first in embryos from killifish adults collected from reference sites and from contaminated New Bedford Harbor (NBH) sites (Massachusetts, USA). They measured the responsiveness of the embryos towards the model contaminant 3-methyl cholanthrene. The reference population was much more sensitive than the embryos from the Superfund site

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Fig. 4.27  Fundulus heteroclitus. Left: Ethoxyresorufin-o-deethylase (EROD, model substrate for CYP1A enzymes) response to 3-methyl cholanthrene (3-MC) in embryos from two reference sites (REF) and New Bedford Harbor, MA (NBH). Effective concentrations (EC) are also shown (REF: EC20 = 47 ng l−1, ○; NBH: EC20 = 2,884 ng l−1, ◊). Right: EROD responses to 2.2 mg l 3-methyl cholanthrene of first (F1)- or second (F2)-filial generation embryos of parents collected from the reference site West Island (WI), New Bedford upper harbor (UH), and New Bedford mid-harbor (MH) (From Nacci et al. 1999. With permission from Springer)

(Fig. 4.27, left) with an EC20 of 47 ng l−1 at the reference site and ca. 2.9 mg l−1 at the Superfund site. F1 and F2 fish from NBH demonstrated poor and similar responsiveness (Fig. 4.27, right). At this stage of evaluation, we can summarize that fishes from the contaminated site do not metabolize contaminants as strongly as fishes from non-contaminated sites do; they avoid the risk of being intoxicated by metabolites with higher toxicity. From another Superfund site, a highly contaminated site on the Elizabeth River (Virginia, USA) Meyer and Di Giulio (2002) showed that offspring of this killifish population were resistant to the teratogenicity and CYP1A-inducing activity of PCB congener 126, a prototypical coplanar halogenated aromatic hydrocarbon. Obviously, the adaptation observed at the Elizabeth River site involves the suppression of normal AHR-inducible gene expression for several CYP-genes (Wills et  al. 2010). However, the resistance is lost after the second filial generation (F2) (Fig. 4.28). Furthermore, the pattern of greater resistance to acute toxicity and CYP1Ainducing activity in the first generation levels off, and third generation fishes are not distinguishable from reference sites in terms of responsiveness. In a subsequent study, Meyer et al. (2003) presented evidence not only of the down-regulation of biotransformation enzymes but also an up-regulation of antioxidant defenses that play a role in both short-term and multigenerational tolerance of the toxicity of the Superfund site-inhabiting fishes. In a comprehensive comparison, Nacci et al. (2010) found remarkable intraspecific variation in sensitivity to broadly distributed PCBs among wild populations of F. heteroclitus. The authors showed that killifish populations vary over four orders of magnitude in their sensitivity to PCB126 and that this variation was adaptive to the magnitude

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Fig. 4.28  In ovo EROD activities in PCB126-exposed killifish embryos. Note that the Elizabeth River F3 generation demonstrate basal and induced EROD activities that are only marginally less than those of the reference King’s Creek F2 embryos (From Meyer and Di Giulio 2002. With permission from Elsevier)

of contamination at the residence site. The four least-sensitive killifish populations reside in US Atlantic coast urban harbors >100  km apart from one another: New Bedford, MA; Bridgeport, CT; Newark, NJ; and Norfolk, VA, USA. These killifish are relatively insensitive to local contaminants, with mixed evidence concerning the heritability of this trait. Furthermore, the authors showed that tolerance to PCB126 was extreme, with some mechanistic similarities among these four killifish populations. However, these populations do not respond identically to each other, and in at least one population tolerance appeared to degrade over the F1 and F2 generations tested. Based on these studies, the mechanism of resistance and inheritance of this trait is growing in mechanistic understanding. Complementary ongoing studies using molecular approaches provide an opportunity to identify unique and shared mechanisms of tolerance in these independently evolving populations and explore the adaptive benefits and costs of contemporary evolutionary responses in the wild. These aspects shall be revisited in Chaps. 7 and 8.

4.8.4 Self-intoxification by CYP Activity in Caenorhabditis elegans As learned above, F. heteroclitus inhabiting Superfund sites avoid the risk of selfintoxification by reducing CYP expression and CYP activity. However, this smart behavior does not apply generally. Menzel et al. (2005a) showed this elegantly with C. elegans by depleting the CYP isoforms (CYP35) in charge of the metabolism of synthetic xenobiotics. The CYP35A/C depleted worms resembled wild type in terms of morphology and reproductive rate under control conditions. However, in the

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Fig. 4.29  CYP35A/C gene knockdown mutant of Caenorhabditis elegans diminishes xenobioticmediated reproductive decline. L1 larvae of N2 wild type, XA6700 alone and combined with CYP35A/C RNAi by feeding, respectively, were cultivated on agar plates in the absence or presence of four different xenobiotics. The amount of complete F1 offspring is presented in box plots showing each outlier. *p < 0.05; **p < 0.01 (From Menzel et  al. 2005b. With permission from Elsevier)

presence of any of four xenobiotics (fluoranthene, PCB52, lansoprazole, atrazine), reproduction increased in comparison to N2 wild type (Fig.  4.29). By knocking down CYP35A/C gene expression, the generation of more toxic metabolites was prevented, which resulted in an increase in reproductive capacity.

4.9 Biotransformation and the Evolution of Pesticide Resistances Generally, the same or similar enzymes which metabolize natural xenobiotics also metabolize pesticides and lead to resistance. One major mechanism of adaptive evolution of stress tolerance is the over-expression of target stress response genes.

4.9.1 CYPs and Herbicide Resistance One major mechanism of xenobiotic resistance is the potential to over-express detoxifying enzymes. The involvement of CYPs in plant resistance to herbicides has been excellently reviewed by Powles and Yu (2010). Plant CYPs are bound to the endoplasmic reticulum (in a few cases to plastid membranes) and are involved in the synthesis of hormones, sterols, fatty acid derivatives, and in many aspects are

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involved in plant secondary metabolism. The role of CYPs in herbicide conversion is usually hydroxylation or dealkylation of the compound. In most cases, these reactions can be summarized as activation and insertion of an atom from molecular oxygen to form a more reactive product using electrons. In weeds, CYP-based herbicide resistance is a very threatening mechanism because CYP enzymes can simultaneously metabolize herbicides of different modes of action, potentially including never-used herbicides. Such resistance evolution was identified in the 1980s, with landmark reports that resistant black-grass, Alopecurus myosuroides, and ryegrass, Lolium rigidum, biotypes displayed nontarget-site cross-resistance across several herbicide modes of action, including herbicide groups never used. Importantly, there was concomitant evolution of cross-resistance to other CYP-metabolizable herbicides of different modes of action. One puzzling aspect is that, to date, CYP-based evolved herbicide resistance has been reported mostly in grass weed species, with few reports in dicots.

4.9.2 GSTs and Herbicide Resistance Herbicide-metabolizing GSTs have been purified and characterized from several crops. For instance, maize is very tolerant of triazine herbicides because of high activity of GSTs able to catalyze the conjugation of triazines to glutathione. It follows that widespread use of triazine herbicides could select for weeds with GSTs able to detoxify triazine herbicides. Indeed, evolved GST-mediated triazine herbicide resistance has been reported in Abutilon theophrasti. Further studies revealed that increased GST (triazine) activity is due to higher catalytic capacity rather than to enzyme overexpression or the presence of a novel GST. This indicates a possible mutation in the GST gene that can improve herbicide binding and therefore GST catalytic efficiency. In a resistant Echinochloa phyllopogon biotype, it was demonstrated that fenoxapropp-methyl resistance can be due to glutathione-herbicide conjugation. GST enzymes can play both a direct role (herbicide conjugation) and an indirect role (stress response) in evolved herbicide resistance (Powles and Yu 2010).

4.9.3 CYPs and Insecticide Resistance CYP-mediated insecticide resistance is due to increased detoxification. This resistance could result from a change in the catalytic activity of the CYP involved and/or a change in the level of expression of the protein. A classical example is the resistance to pyrethroid insecticides of a strain of the house fly, Musca domestica, which has extremely high levels of cypermethrin resistance (Scott et  al. 1998). In this example, the enzyme CYP6D1 (Fig. 4.30) had a central function and belongs to the same family as those (CYP6Bs) responsible for the resistance of specialist herbivores.

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Cl

O Cl H3C

CH3

O

N

O

Cl

O Cl CYP6D1 P450 reductase NADPH O2 Cytochrome b5

O OH

H3C

CH3

Fig. 4.30  Metabolism of the synthetic pyrethroid, cypermethrin by CYP6D1 (After Scott et al. 1998. With permission from Elsevier)

Later, more enzymes of the CYP6 family, from other families and the involvement of jumping genes (transposons) have been identified. For instance, Catania et al. (2004) proved that DDT resistance in Drosophila melanogaster is well correlated with the insertion of an Accord-like element into the 5¢region of the CYP gene, CYP6G1. This suggests that CYP6G1 lost its plastic response due to insecticide selection pressure. Remarkably, this molecular phenotype spread globally within decades, reaching almost fixation in non-African Drosophila populations (Roelofs et al. 2010). Furthermore, the over-transcription of CYP6G1 confers not only resistance to DDT but also to a number of existing and novel insecticides (Daborn et al. 2002). Convincing evidence that CYP over-expression is the cause of resistance has been provided in more cases. For instance, DDT resistance can result from the constitutive overexpression of CYP6G in the fruitfly D. melanogaster. Likewise, CYP12A4 overexpression confers lufenuron resistance in this species. In other studies, multiple CYP genes are over-expressed in resistant strains: In the housefly, the over-expressed CYP6A1 and CYP6D1 genes are involved in diazinon resistance in one strain and in pyrethroid resistance in another strain, but in each case other genes are over-expressed as well (CYP12A1, GST-1, CYP6D3). Similarly, CYP6P3 is involved in permethrin resistance in Anopheles gambiae, and CYP6CM1vQ is involved in imidacloprid resistance in the whitefly, Bemisia tabaci. Multiple CYP genes have been reported to be over-expressed in pyrethroid-resistant strains in the cotton bollworm, Helicoverpa armigera (Brun-Barale et al. 2010).

4.9.4 Esterases and Hydrolases and Insecticide Resistance In a pioneering paper, Newcomb et al. (1997) studied the evolution of resistance to diazinon in the sheep blowfly Lucilia cuprina. Diazinon is an organophosphate insecticide that is commonly used in Australasia. Diazinon binds to and inactivates esterases, including acetylcholinesterase, an enzyme that is crucial to neurotransmission (Dean and Thornton 2007). Resistance to diazinon had been statistically associated with an allele at another esterase locus, E3. To assess whether this allele confers the ability to detoxify the insecticide and to determine the mechanism for this shift, Newcomb et  al. (1997) compared E3 sequences from several natural

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populations and found that alleles from resistant and susceptible flies differed by five amino acids. More examples shall elucidate metabolic resistance based on esterase activity. Van Leeuwen and Tirry (2007) showed that bifenthrin (a synthetic pyrethroid) resistance in the two-spotted spider mite, Tetranychus urticae, was based on several-fold higher esterase activity. GST did not seem to play any role in the observed resistance. Furthermore, the resistance of this mite to organophosphate and carbamate acaricides is based on several mutations in one of two genes encoding acetylcholinesterase (Khajehali et al. 2010). Selective insecticides with modes of action different from those of broadspectrum neurotoxic insecticides, such as the pyrethroids, are highly desirable in integrated pest managements. Among these insecticides are ecdysteroid agonists, a new group of insect growth regulators with low mammalian toxicity that induce precocious and incomplete molting leading to larval mortality. Even against this new insecticide, resistances have begun to develop, for instance, in the cotton leafworm, Spodoptera littoralis. Mosallanejad and Smagghe (2009) demonstrated that CYP enzymes, rather than GSTs or esterases, were responsible for this resistance.

4.9.5 GSTs and Insecticide Resistance Participation of insect GSTs in allelochemical tolerance differs between food generalists and specialists. GST isoenzymes isolated from the polyphagous fall armyworm, Spodoptera frugiperda, metabolize many organothiocyanates. In contrast, GSTs isolated from the less polyphagous Trichoplusia ni can metabolize only two organothiocyanates, and the more specialized Anticarsia gemmatalis can metabolize only one, consistent with their host range difference (Li et al. 2007a, b). With respect to the involvement of GSTs in insecticide resistance, most research has focused on DDT resistance in mosquitoes, Anopheles sp. Indoor residual house spraying with this insecticide was a central part of the malaria eradication program in many countries in the 1950s and 1960s. The campaign failed, in part, because of insecticide resistance and the inability of the public health infrastructure in many disease-endemic countries to deliver such a demanding program. Despite selection of resistance in many Anopheles populations, DDT continued to be the insecticide of choice for malaria control in many countries until the 1990s, with countries such as India arguing that resistance did not affect the repellent properties of DDT, which may be as important in reducing malaria transmission as the direct killing effects on the insects. Several different approaches have been taken to identify the particular GSTs involved in DDT resistance in Anopheles gambiae. From partial purification of mosquito GSTs and characterization of the different fractions’ ability to dehydrochlorinate DDT, it is apparent that DDTase activity is not an inherent property of all GST enzymes. By a combination of different approaches, including genetic mapping, expression analysis, and in vitro expression of recombinant GST enzymes, the

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epsilon-GST, GSTE2, was identified as the enzyme responsible for DDT resistance in a strain of A. gambiae from east Africa. Homodimers of GSTE2 are extremely efficient at metabolizing DDT, and expression of this enzyme is elevated in DDTresistant individuals. Recent work has also implicated elevated activities of an epsilon-GST in conferring resistance to DDT in the yellow fever mosquito, Aedes aegypti. This protein has high levels of DDTase activity and is over-expressed in DDT-resistant mosquitoes. In contrast to its putative A. gambiae ortholog, the A. aegypti enzyme also has peroxidase activity, which may contribute to the high levels of pyrethroid resistance seen in this strain (Ranson and Hemingway 2005).

Chapter 5

Heat Shock Proteins: The Minimal, but Universal, Stress Proteome

The initial observation that led to the discovery of the heat shock proteins (HSPs) was that heat shock generated focal swellings or “puffs” on chromosomes of Drosophila salivary glands (Roberts et al. 2010). Such swellings were recognized as indicating that genes were being activated in those areas of the genome to give rise to their encoded proteins. These therefore became known as the “heat shock loci” and were initially considered a phenomenon unique to fruitflies. It was not until 1974 that these loci were proven the sites of transcriptional induction of genes encoding for a particular group of proteins, which were designated HSPs. It was even longer before it was recognized that they occurred in mammals and indeed at all evolutionary levels (Lindquist and Craig 1988). Furthermore, it is now recognized that the response is universal to all cells and that other stressors such as toxins, protein degradation, hypoxia, acidosis, microbial damage, predation, or population density will also lead to their up-regulation (Table 5.1). Intra-cellular counterparts of HSPs, referred to as “constitutive chaperones”, are also found within the cytoplasm of normal unstressed cells, representing up to 10% of the total protein in healthy growing cells (Pockley 2003). Constitutive chaperones primarily reside in the cytosol, nucleus, and mitochondria. They are universal to all cells and essential for various homoeostatic functions, including maintenance of protein structure and folding; supporting and repairing damaged cytoskeleton elements; assisting in the production and folding of intra-cellular proteins, enzymes, and hormone receptors; and maintenance of mitochondria and nuclear and cell wall lipoprotein membranes (Fig. 5.1) (Roberts et al. 2010). When such cells are stressed, however, there is up-regulation of the constitutive chaperones to produce newly formed HSPs which can be detected in the cells and in tissue fluids at concentrations several times those of the constitutive chaperones. Thus, the term “stress proteins”, a more embracing term, is also used to describe them (Lindquist 1986). This universal stress defense indicates a low stressor specificity of the heat shock systems. In fact, the heat shock proteins, or more generally the stress proteins, represent the minimal stress proteome in all organisms.

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Table 5.1  Selected references for ecologically relevant triggers of HSP synthesis Environmental stressor Selected references Abiotic stresses on Reviewed by Timperio et al. (2008) plants Geissler et al. (2010) Elevated CO2 Heat Tissières et al. (1974), Jenkins et al. (1997), Otsuka et al. (1997), Li et al. (1999), Tomanek and Somero (1999), Hofmann et al. (2002), Sonna et al. (2002), Tomanek and Sanford (2003), Dahlhoff (2004), Duncan (2005), Sures and Radszuweit (2007), Swindell et al. (2007), Anestis et al. (2008), Mikulski et al. (2009), Timofeyev et al. (2009), Bedulina et al. (2010b), Currie et al. (2010), Lesser et al. (2010), and Tomanek (2010) Cold Jenkins et al. (1997), Goto et al. (1998), Li et al. (1999), Martinez et al. (2001), Sonna et al. (2002), Sejerkilde et al. (2003), Takle et al. (2005), Swindell et al. (2007), Donaldson et al. (2008), and Colinet et al. (2010) Irradiation, incl. UV Trautinger et al. (1996), Jenkins et al. (1997), Kiriyama et al. (2001), Swindell et al. (2007), and Tartarotti and Torres (2009) Steinert and Pickwell (1993), Eckwert and Köhler (1997), Köhler Heavy metals, and Eckwert (1997), Werner and Nagel (1997), Tedengren metalloids, metallic et al. (1999), Arts et al. (2004), La Porte (2005), Brulle et al. nanoparticles (2006), Sures and Radszuweit (2007), Haap and Köhler (2009), Ahamed et al. (2010), and Scheil et al. (2010) Wiegand et al. (2004), Timofeyev et al. (2004), Steinberg et al. Natural xenobiotics: (2007), and Bedulina et al. (2010a) plant polyphenols, humic substances Werner and Nagel (1997), Schröder et al. (1999), Ait-Aissa et al. Synthetic xenobiotics, incl. pesticides (2000), Weber and Janz (2001), Lee et al. (2006), Song et al. (2006), Eder et al. (2007), and Scheil et al. (2010) Hypoxia Ma and Haddad (1997), Baird et al. (2006), and Currie et al. (2010) Salinity and osmotic Diamant et al. (2001), Drew et al. (2001), Hamilton et al. (2001), stress Spees et al. (2002), and Swindell et al. (2007) Demographic factors Sørensen and Loeschcke (2001), Martínez-Padilla et al. (2004), and Merino et al. (2006) Food and starvation Bourgeon et al. (2006), Hansen et al. (2006), Hao et al. (2007), and Steinberg et al. (2010a) Pathogens Collins and Hightower (1982), Kaufmann and Schoel (1994), Deitch et al. (1995), Soosaar et al. (2005), Song et al. (2006), Eder et al. (2007), and Swindell et al. (2007) Parasites Merino et al. (1998, 2002), Rinehart et al. (2002), MartínezPadilla et al. (2004), Tomás et al. (2005), Pauwels et al. (2007), and Ittiprasert et al. (2009) Predation Kagawa et al. (1999), Kagawa and Mugiya (2002), Fleshner et al. (2004), Pijanowska and Kloc (2004), Pauwels et al. (2005, 2010a), Slos and Stoks (2008), and Thomson et al. (2010) Physical activity Skidmore et al. (1995), Fehrenbach and Niess (1999), Nickerson et al. (2005), and Brown et al. (2007) Wounding Pinsino et al. (2007) and Swindell et al. (2007) Desiccation, drought, Alamillo et al. (1995), Tammariello et al. (1999), Sales et al. anhydrobiosis (2000), Hayward et al. (2004), Sinclair et al. (2007), Swindell et al. (2007), Denekamp et al. (2009), Mizrahi et al. (2009), and Schokraie et al. (2011) Oxidative stress Ropp et al. (1983), Gophna and Ron (2003), Swindell et al. (2007), Heidler et al. (2010), Sharma et al. (2010), and Wang et al. (2010c, d)

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Fig. 5.1  Cellular function of heat shock proteins. The fate of proteins with non-functional conformations after stress exposure may be either to re-obtain the functional conformation, form aggregations with other misfolded proteins, or to be degraded. HSPs play a helper role in shifting the equilibrium in the direction of more functional proteins or degradation of damaged proteins (From Sørensen et al. 2003. With permission from Wiley)

These tasks are important under normal cellular conditions; however, the need for molecular chaperones is accelerated under stressful conditions that could potentially damage cellular and molecular structures in the cells (Sørensen et al. 2003). Regulation of HSP gene transcription is mediated by the interaction of heat shock factors (HSFs) with heat shock elements in gene promoter regions (Pockley 2003). All HSFs have remarkable structural similarity, but there are significant differences in the complement and activity of HSF family members in different groups of organisms (Feder and Hofmann 1999). For example, many insect groups such as fruitflies have only one HSF while finfish and other vertebrates have three or four and plants have 20 (Baniwal et al. 2004). HSF1, HSF2, and HSF4 are ubiquitously expressed among taxonomic groups, whereas HSF3 appears to be avian specific. HSF1 is the main transcription factor regulating response to physiological and environmental stress. New synthesis of HSPs is assumed to replenish the pool of free chaperones. There is good evidence that in a kind of autorepression, some of the chaperones (e.g., HSP17-CII, HSP70, HSP90) are involved in the second part of the HSF cycle leading to the restoration of the inactive state of HSFs in plants and animals. In eukaryotes, HSPs are categorized into several families and named according to their function, sequence homology, and molecular mass in kilo-Daltons (kDa).

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Table 5.2  The main HSP (heat shock protein) chaperone families (Modified after Rutherford 2003) Chaperone Action HSP100 Disaggregates HSP90 Supports nearly mature conformations; signal transducer; capacitor HSP70 Binds linear polypeptide for folding; translocation assembly of multiprotein complexes HSP60 (GroEL, Folds “molten globule” proteins or domains TriC) Small HSPs Prevents aggregation, particularly during heat shock; involved in longevity

These families primarily include HSP100, HSP90, HSP70, HSP60, HSP40, and several smaller HSP groups. The main HSP families recognize different structural features that are specific to immature, unstable, and damaged proteins (Table 5.2). The HSPs that are constitutively involved in protein folding and maturation (HSP60, HSP70, and HSP90) also buffer phenotypic variation, whereas the small HSPs (sHSPs) and HSP100 are primarily involved in recovery after stress. Small HSPs have been reported only recently to buffer variation (Takahashi et al. 2010). Different chaperone families recognize structural features that are specific to immature and unstable proteins at different stages of folding and unfolding. The HSP70 chaperones, ring-shaped chaperonins (CPNS), and HSP90 are involved in successively more advanced stages of protein folding and function, whereas the small HSPs and HSP100 act predominantly during stress. Why does such a low specificity in the stress response exist? Kültz (2005) assigned this responsiveness to the most striking and common impact of stress: the deformation and damage of macromolecules, mainly membrane lipids, proteins, and/or DNA. Some specificity may arise because the types of lesions and damage to proteins, DNA, and membranes vary somewhat depending on the type of stress. Another common feature of diverse stresses is the generation of oxidative stress and change in cellular redox potential, referred to as oxidative burst (see Chap. 2). ROS and cellular redox potential have long been regarded as key regulators of cellular stress response signaling, with ubiquitous roles as second messengers in cells exposed to stress. The molecular basis of stressor-specificity has been a subject of much debate. One way of achieving stressor-specificity with the same set of components (induced/activated stress proteins) is via stressor-specific interactions, post-translational modifications, and compartmentation of stress proteins resulting from different relative levels of induction within a common set of stress proteins. Recent reviews of the heat shock proteins as the classical, most prominent stress response are available for different groups of organisms: –– Prokaryotes (Arsène et al. 2000; Lim and Gross 2011) –– Plants (Baniwal et al. 2004) –– Animals (Hofmann 2005). Selected examples will elucidate the universality of HSF/HSP-mediated stress responses.

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5.1 Bacteria 5.1.1 Escherichia coli In E. coli, the heat shock response to temperature upshift from 30°C to 42°C consists of the rapid, up to 15-fold, induction of synthesis of more than 20 heat shock proteins (HSPs), followed by an acclimation period where the rate of HSP synthesis decreases to reach a new steady-state level. Major HSPs are molecular chaperones, including the DnaK (equivalent to HSP70 in eukaryotes) and GroE (HPS60 family equivalent) chaperone systems, the two major chaperone systems of E. coli with 15–20% of total protein at 46°C (Arsène et al. 2000). The E. coli heat shock response is positively controlled at the transcriptional level by the product of the rpoH gene, the heat shock promoter-specific s32 subunit of RNA polymerase, part of the sS system (see Chap. 12). Because of its rapid turnover, the cellular concentration of s32 is very low under steady-state conditions and is limiting for heat shock gene transcription. The heat shock response is induced as a consequence of a rapid increase in s32 levels and stimulation of s32 activity. The shut down of the response occurs as a consequence of declining s32 levels and inhibition of s32 activity. Stressdependent changes in heat shock gene expression are mediated by the antagonistic action of s32 and negative modulators which act upon s32. These modulators are the DnaK chaperone system which inactivates s32 by direct association and mediates its degradation by proteases. Degradation of s32 is mediated mainly by an ATP-dependent metallo-protease associated with the inner membrane (Arsène et al. 2000).

5.2 Plants 5.2.1 Salinity and Elevated CO2 Concentrations Soil salinity is an abiotic stress which poses a serious threat to agriculture because it limits the growth and cultivation of traditional crop plants, especially in arid and semiarid climate zones. The four major constraints of salinity on plant growth are osmotic effects, restriction of CO2 gas exchange, ion toxicity, and nutritional imbalance. Global climate change exacerbates this problem by causing a rise in atmospheric CO2 concentration. Compared to salinity, elevated CO2 concentration alone has contrary effects on plants: it often improves the photosynthesis of C3 plants while increasing their stomatal resistance, hence decreasing photorespiration and oxidative stress but increasing energy supply (Ainsworth and Rogers 2007). Therefore, higher investments in energy-dependent salt tolerance mechanisms may be enabled, such as the over-expression of proteins related to salinity tolerance. Geissler et al. (2010) investigated the influence of elevated atmospheric CO2 concentration on the salinity tolerance of the cash crop halophyte Aster tripolium. Under ambient CO2 concentration, enhanced expressions and activities of the antioxidant enzymes SOD, APX (APO), and GST in the salt-treatments were recorded, indicating an oxidative

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Fig. 5.2  Relative volume percentages of selected spots of total protein in control and salt treatments in the proteomic analysis of Aster tripolium. (a) Ambient CO2. (b) Elevated CO2. Significant differences (p £ 0.05) between the salinity treatments (within one CO2 treatment) are indicated by different letters, significant differences between the CO2 treatments (within one salt treatment) are indicated by an asterisk. sws seawater salinity. APO = ascorbate peroxidase (APX); GST = glutathione transferase; SOD = superoxide dismutase; HSP20 = heat shock protein 20 (From Geissler et al. 2010. With permission from Springer)

stress. Elevated CO2 led to significantly higher enzyme expressions and activities in the salt-treatments so that ROS could be detoxified more effectively. Furthermore, the expression of a protective HSP20 increased under salinity and was enhanced further under elevated CO2 concentration (Fig. 5.2). Additional energy was required for the mechanisms mentioned above, which was indicated by the increased expression of an ATPase subunit and ATPase activities under salinity. The higher ATPase expression and activities also enable a more efficient ion transport and compartmentation for the maintenance of ion homeostasis. The authors concluded that elevated CO2 concentration is able to improve the

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survival of A. tripolium under salinity because more energy is provided for the synthesis and enhanced activity of enzymes and proteins, which enable a more efficient ROS detoxification and ion compartmentation/transport.

5.2.2 Induced Thermotolerance in Tomato A peculiarity of plants is the unique complexity of the HSF family; detailed analyses are mainly restricted to tomato and Arabidopsis and to three important representatives of the family (HSFs A1, A2, and B1). The three HSFs represent examples of striking functional diversification specialized for the three phases of the heat stress response: triggering, maintenance, and recovery. This is best illustrated for the tomato HSF system: 1. HSFA1a is the master regulator responsible for heat stress-induced gene expression, including synthesis of HSFA2 and HSFB1. It is indispensable for the development of thermotolerance. 2. Although functionally equivalent to HSFA1a, HSFA2 is exclusively found after heat stress induction and represents the dominant HSF, the “work horse” of the heat stress response in plants subjected to repeated cycles of heat stress and recovery in a hot summer period. HSFA1a is the master regulator for heat stress response and in this function cannot be replaced by any other HSFs. The evidence for this stems from two different transgenic tomato lines with altered expression of HSFA1a generated by incorporation of HSFA1 transgene cassettes: (i) an over-expression (OE) line, and (ii) a co-suppression (CS) line. The latter leads to the synthesis of double stranded small interfering RNA (siRNA) and post-transcriptional gene silencing of HSFA1a. Consequently, no HSFA1a is detectable in leaves of CS lines. What are the biological consequences of the marked changes in HSFA1a expression levels between wild type and transgenic lines? Under normal growth conditions, all three lines showed no obvious phenotype. However, exposure to a mild heat stress treatment documented that the CS plants are unable to acquire thermotolerance. They died soon after the stress treatment, whereas wild type (WT) and OE plants were not affected. However, exposure to a severe heat stress was also lethal to the WT plants, but OE plants survived, documenting their higher level of adaptive capacity. In correspondence with the phenotypic effects, the expression levels of heat stress-inducible chaperones were markedly increased in correlation with the level of HSFA1a in the three genetic lines. From phylogenetic analysis, the HSF families of tomato and Arabidopsis seem to be similar in complexity and basic composition, but so far, no similar master regulator HSF has been identified in Arabidopsis. From the point of view of evolutionary adaptation to survive under stressful conditions, the situation with a single master regulator in tomato appears very risky, whereas Arabidopsis seems to

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p­ rovide more flexibility. However, more comparative analyses of HSF function in both plants are required to justify such a conclusion (Baniwal et al. 2004). In a metabolomic context, the synopsis of HSP involved in various stress responses is presented in Chap. 9.

5.3 Animals 5.3.1 Abiotic Stressors Selected examples of abiotic stressors shall elucidate the universal nature of the heat shock response, including heat, cold, combination of altitude and temperature, humic substances, heavy metals, and pesticides. 5.3.1.1 Heat Temperature controls and limits all physiological and behavioral parameters of ectotherms. For fish, water temperature has been described as the “abiotic master factor”. Optimal temperature ranges, as well as upper and lower lethal temperatures, vary widely between and among species and are dependent on genetics, developmental stage, and thermal histories. The threshold induction temperature of HSPs in two species of goby fish Gillichthys mirabilis and G. seta, showed a seasonal acclimatization, increasing by several degrees Centigrade in the summer compared with winter HSP induction temperatures (Dietz and Somero 1992) (Fig. 5.3). Summeracclimatized fishes had higher levels of HSP90 in brain tissue than winter-acclimatized specimens did. For winter-acclimatized fishes, increased synthesis of HSP90 was observed when the temperature was raised from 18°C to 28°C. For summeracclimatized fish, no significantly increased synthesis of HSP90 occurred until the experimental temperature was raised to 32°C. The data showed that the threshold temperature at which enhanced expression of HSP-encoding genes occurs is not hard-wired genetically but is subject to acclimatization. Littoral aquatic animals, such as gammarids, inhabit environments with significant fluctuation of physical and chemical conditions (temperature, light, oxygen content, pH-value). Many of these fluctuations provoke stress, particularly the temporal fluctuations. In a comparative study, Timofeyev et al. (2009) evaluated sHSPs, related to a-crystalline, as an anti-thermal stress response in two contrasting freshwater amphipods, the stenoecious Baikal endemic Eulimnogammarus cyaneus and the Palearctic Gammarus lacustris. Small HSP synthesis clearly responded differently in the two gammarids (Fig. 5.4). In G. lacustris, sHSP concentrations peaked after 12 h with a subsequent decline, while concentrations increased steadily in E. cyaneus until the end of exposure. Since this protein has both chaperone and membrane stabilizing functions, the

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Fig. 5.4  Western blot of sHSP levels in Gammarus lacustris (left) and Eulimnogammarus cyaneus (right) on exposure to 25°C (From Timofeyev et al. 2009. With permission from Elsevier; photographs courtesy of VV Pavlichenko)

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observed increase of concentrations prevents damages to or provides a repair mechanism for cellular proteins and membranes. The sHSP synthesis is highly energy consuming, and one may assume that upon a stress, organisms from strongly fluctuating environments (comparably shallow Palearctic lakes) express sHSPs only on a short-term basis, while organisms from a more stable environment (Lake Baikal) with a huge thermal buffer do not modulate the sHSPs expression in this manner. The different ability to respond to thermal stresses is obviously also one mechanistic basis for the different habitat occupation of common Palearctic and endemic Baikal amphipods; or, in turn, the pattern of the sHSP modulation may distinguish between stenoecious/endemic and euryoecious/Palearctic species. An elegant body of work from the laboratory of Martin Feder on the role of Drosophila HSP70 in the ecology and evolutionary physiology of stress tolerance provides an important natural context to our predominantly laboratory-based understanding of the heat-shock response. D. melanogaster in the wild typically feeds on damaged and fermenting fruit. In direct sunlight, fruit-eating Drosophila larvae can be exposed to ambient temperatures as high as 44°C – although 30°C is the highest sustained temperature that is compatible with the growth and reproduction of flies in the wild. If the temperature reaches ~36°C, the rate at which HSP70 is transcribed increases greatly, increasing the previously negligible levels of the product to 1–2% of the cellular protein in a matter of minutes (Feder and Hofmann 1999). Field studies indicate that there is a direct relationship between HSP70 activation, survival, and fitness in flies in the wild. To investigate the functional correlation between HSP70 induction and stress tolerance in Drosophila, experimental lines of flies were engineered to contain 12 extra transgenic copies of the HSP70 gene (extra-copy lines). When placed under natural thermal stress, comparison with perfectly matched excision controls (excision lines) – containing only the disrupted transgene insertion site – showed markedly increased stress tolerance in the extra-copy lines (Feder et al. 1996). Importantly, both extra-copy lines and excision lines had the same uniform genetic background, so any differences in the physiology of heat tolerance could be attributed solely to the HSP70 gene and not to variation in the myriad other HSPs or physiological factors or to mutational effects of the transgene insertion site. Therefore, thermotolerance in Drosophila is primarily attributed to HSP70 and is correlated with its ability to restore the function of heat-damaged proteins (Sørensen et al. 2003). 5.3.1.2 Cold In fish, HSP70 is temperature inducible at different embryonic stages (Takle et al. 2005). Takle et al. (2005) subjected Atlantic salmon, Salmo salar, to hot and cold treatments during four embryonic stages from gastrulation to the completion of somiogensesis and found a 14% incidence of vertebral deformities. Following the cold treatment, HSP70 expression was highest at the 45th somite stage with a fourfold increase (compared with a 12-fold increase after heat shock) (Fig. 5.5). The findings of this study indicate that HSP70 confers protection in S. salar embryos.

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Fig. 5.5  Relative HSP70 mRNA levels in ~45th somite stage of Atlantic salmon embryos following heat shock at 16°C (black bars) and cold shock at 1°C (white bars) for 1 h. * significance at p < 0.05; hpt = hours post-treatment (From Takle et al. 2005. With permission from Elsevier)

Werner et  al. (2005) conducted field and laboratory studies to examine the expression of HSP72 and HSP78 in the white muscle of rainbow trout, Oncorhynchus mykiss, parr. A sigmoid relationship and a linear relationship with temperature change were found for HSP72 and HSP78, respectively. These authors also found that the highest HSP72 levels in juvenile O. mykiss were measured at warm water sites with diurnal temperature fluctuations ³6.5°C. This indicates that HSPs were expressed in response to both stressful water temperatures and daily temperature fluctuations (Donaldson et al. 2008). 5.3.1.3 Combination of Altitude and Temperature HSP70 expression consumes a great deal of cellular energy and competes with basic metabolism. Consequently, HSP induction may increase vulnerability to other stresses (Feder and Hofmann 1999; Karl et al. 2009). Continuous or frequent exposure to stress may therefore reduce the expression of HSP70 through evolution, as the associated costs may outweigh its benefits (Sørensen et al. 2001). Such variation in the expression of HSPs may limit the distribution and abundance of organisms along steep ecological (e.g., thermal) gradients in nature. Recently, Karl et al. (2009) tested if Copper butterflies, Lycaena tityrus, originating from different altitudes and/or being exposed to different rearing and induction temperatures showed differences in HSP70 response. HSP70 expression generally increased with colder and warmer induction temperatures. Furthermore, HSP70 expression increased substantially at the higher rearing temperature in low-altitude butterflies, which might represent an adaptation to occasionally occurring heat spells. On the other hand, high-altitude butterflies showed much less plasticity in response to rearing temperatures and overall seemed to rely more on genetically fixed thermal stress resistance.

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5.3.1.4 Natural Xenobiotics: Humic Substances Humic substances are complex mixtures of organic molecules that make up the majority of the dissolved natural organic matter (NOM) in freshwater ecosystems. Abiotic as well as biotic ecological reactivity of different NOMs strongly vary with site and season (Paul et al. 2004; Vogt et al. 2004). Bedulina et al. (2010a) designed a study to comparatively evaluate the impact of NOMs from different sources on major anti-stress mechanisms – including sHSPs and HSP70 – in the amphipod Gammarus pulex. NOMs were isolated from three different sources. Despite different origin and composition of the humic substances, the HSP development in the exposed animals was rather uniform (Fig. 5.6): –– HSP70 responded much more strongly than sHSPs –– After only 30  min, HSP70 showed maximum concentration (induction?) and responded in biphasic (Lake Fuchskuhle, Brazilian sediment) and triphasic (Lake Schwarzer See) patterns –– Except for sHSPs in the treatment with NOM from the Brazilian sediment, sHSPs also showed increased levels after 30 min. This multiphase response indicates that the HSP induction is cost-intensive and the individuals try to return to basic conditions; yet, the permanent exposure to the unusual biochemical trigger necessitates repeated response.

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Fig. 5.7  HSP70 levels in Danio rerio larvae after exposure to control conditions and five concentrations of NiCl2. Different letters indicate significance at p £ 0.05 (From Scheil et al. 2010. With permission from Wiley)

Humic substances are documented to be as old as biomolecules themselves (Ziechmann 1996), which indicates that humic substances may have been a primordial exogenous trigger by which organisms were forced to develop antistress systems, including stress proteins. This assumption can serve as one explanation of the rather uniform stress response in G. pulex upon exposure to contrasting NOMs. 5.3.1.5 Heavy Metals From the many studies of heavy metal toxicity, one illustrative example with nickel (Ni) and zebrafish, Danio rerio, larvae will be presented. The heavy metal Ni is an essential nutrient and plays important roles in the biology of microorganisms and plants because many enzymes contain Ni, for instance a class of superoxiddismutases. Recently, Scheil et al. (2010) tested the impact of increasing concentrations of NiCl2 on zebrafish larvae (Fig. 5.7) and found a slight increase of HSP70 in larvae exposed to 1 mg l−1 Ni. HSP70 levels decreased at higher concentrations of Ni, leading to lower HSP70 levels in larvae exposed to 10 and 15  mg  l−1 Ni. Obviously, the stress response followed an optimum curve: the reduction of the HSP70-level at higher concentrations indicates rather an exhaustion of the stress protein response than a recovery of the exposed larvae. 5.3.1.6 Synthetic Xenobiotics: Pesticides For pesticides, there exist numerous studies with a variety of model organisms and a high diversity of chemical compounds. Again, we focus on the recent illustrative study with zebrafish larvae conducted by Scheil et al. (2010), who selected chlorpyrifos, an organophosphate insecticide, acaricide, and miticide used to control foliage and soil-borne insect pests on a variety of food and feed crops. Chlorpyrifos acts as

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5  Heat Shock Proteins: The Minimal, but Universal, Stress Proteome 6

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an acetylcholinesterase inhibitor, is primarily a contact poison, and is one of the most widely used organophosphate insecticides. The results are depicted in Fig. 5.8. Concentrations of 100 and 600  mg  l−1 chlorpyrifos led to significantly increased HSP70 levels. In contrast to NiCl2, the response to chlorpyrifos showed only the increasing part of the HSP optimum curve.

5.3.2 Biotic Stressors Several biotic interactions, both intra- and interspecific, are stressful and have proven to be HSP inducers: demographic factors, unsuitable food, predation, parasitism, and diseases. 5.3.2.1 Demographic Factors The inducible HSPs and the response to extreme environmental triggers consist not just of the states on and off. Sørensen and Loeschcke (2001) showed in Drosophila that a moderately high-rearing density during larval stages led to a low but detectable up-regulation of HSP70. The authors suggested that either waste product accumulation or food limitation was responsible for the HSP induction. Adult flies raised under high larval density had increased longevity and heat stress resistance in spite of the stressful developmental conditions. As part of the protein quality control system, HSPs obviously play a major role in the struggle for maintaining functional cellular machinery upon exposure to intrinsic stress (Sørensen et al. 2003). For Eurasian kestrels, Falco tinnunculus, Martínez-Padilla et al. (2004) showed that brood hierarchies established through hatching asynchrony were costly for small chicks because of impaired growth and survival as indicated by the level of HSP60

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Fig. 5.9  Effects of the interaction between sex and size difference with respect to the largest sibling on the levels of HSP60 from peripheral blood of Eurasian kestrel nestlings (From Martínez-Padilla et al. 2004. With permission from Wiley)

and HSP70 in peripheral blood in nestlings. Nestlings showing a large size difference with respect to their largest sibling had higher levels of both stress proteins, and this effect was stronger for female chicks (Fig. 5.9). This means a low position in the brood hierarchy increases stress, and this effect is more marked for female chicks in species where females are larger and require more food in the nest. 5.3.2.2 Unsuitable Food Unsuitable food can serve as stress. In this context, Steinberg et al. (2010a) supplied Daphnia magna with two different diets (chlorococcal alga Pseudokirchneriella subcapitata and baker’s yeast) fed ad libitum and exposed it to an environmentally realistic concentration of humic substances. Exposure to humic substances caused a transcriptionally controlled stress response with the studied genes catalase (CAT) and HSP60 (Fig.  5.10). Furthermore, exposure to humic substances reduced the antioxidant capacity. A much stronger oxidative stress is caused by feeding yeast, which reduced the anti-oxidative capacity to values of approximately 50% of the green algal diet. This reduction was most likely due to the yeast cell wall’s resistance to digestion. Obviously, the biochemical machinery in the gut of Daphnia continuously activated oxygen to cleave the yeast’s cell wall and reduced the antioxidative capacity of the animals. This oxidative stress caused an induction of HSP60 to maintain protein homeostasis. 5.3.2.3 Predation Although predation is a strong selection pressure, little is known about the molecular mechanisms to cope with predator stress. This is crucial to understanding the

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Fig. 5.10  Pairwise comparisons of relative mRNA contents of CAT (white) and HSP60 (black) in Daphnia magna when fed algae or yeast and exposed to 0.04 mM DOC of humic substances. (a): Gene profiles in green algae fed animals, when exposed to humic substances. The pure algal diet was set 1.0. (b): Gene profiles in yeast fed animals, when exposed to humic substances. The pure yeast diet was set 1.0 (From Steinberg et al. 2010a. With permission from Springer)

mechanisms and constraints involved in the evolution of antipredator traits. Kagawa et al. (1999) conducted a pioneering study with goldfish, Carassius auratus, reared with bluegills, Lepomis macrochirus, and it was found that the expression of HSP70 was significantly enhanced in the brains of goldfish reared with bluegills for 6 and 12 h in a single tank. The hepatopancreas and the kidney were not affected by the treatment (Fig. 5.11). In the presence of fish predators or their infochemicals (kairomones), invertebrate prey such as the waterflea, D. magna, responds similarly to goldfish except that the major responsive HSP in the prey is HSP60. Pauwels et  al. (2005) quantified the expression of HSP60 in four clones of the waterflea when exposed to fish kairomones. Expression of HSP60 induction increased after 6 h and returned to base levels after 24 h of predator stress, suggesting that increased protein production is a costly transient mechanism to cope temporarily with novel predator stress before other defenses are induced. Furthermore, Pauwels et al. (2005) found genetic variation in the fixed levels and in the fish-induced levels of HSP60, which seemed to be linked to each clone’s history of fish predation. Overall, HSP60 is a part of a multiple-trait antipredator defense strategy of Daphnia clones to cope with predator stress. Slos and Stoks (2008) have recently addressed the cost of predator stress. Predator stress often takes the form of reduced growth (Lima 1998), and stress physiology suggests several mechanisms which may underlie this growth reduction. Under predator stress, prey organisms typically show a series of physiological effects including an

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Fig. 5.11  HSP70 (optical density) in brain and hepatopancreas of goldfish, Carassius auratus, exposed to the bluegill predator, Lepomis macrochirus (From Kagawa et al. 1999. With permission from Springer)

increase in respiration which enable them to react to the predator (“fight-or-flight” response). These effects increase short-term survival through the mobilization and shunting of energy to muscles for the actual fight or flight. This may have a direct energetic cost in the sense that less energy is allocated to growth, thereby causing growth reduction under predation risk. Additionally, indirect energetic costs may result from the up-regulation of cellular metabolism such as proteins (Sørensen et al. 2003). Figure 5.12 clearly shows that, under predation risk, there was a growth reduction and an increase in oxygen consumption in Enallagma cyathigerum larvae, indicative of the “fight-or-flight” response. Predation risk did not affect HSP60 levels but did induce an increase in energetically costly HSP70 levels. Furthermore, the induction of stress proteins most likely contributes to the growth reduction under predation risk. Stress protein production is a likely response to the accelerated cellular metabolism under predation risk and the associated increased challenge to maintain homeostasis and/or could be part of the generalized stress response that serves to protect the cell from cytotoxic stress response substances (Slos and Stoks 2008). Alternatively, the release of HSP70 under predation risk exposure could serve as a danger signal to the immune system, facilitating a faster and more directed response if injury would be followed (Pockley 2003). A recent study by Thomson et  al. (2010) showed with the songbird, Ficedula hypoleuca (pied flycatcher) that the stress response forms an integral part of the non-lethal effects of predators on prey. They found that individuals breeding in closer proximity to a predator (Accipiter nisus, sparrowhawk) showed significantly lower body mass and higher HSP70 levels. 5.3.2.4 Parasites Populations often face changes in environmental conditions in a relatively short timescale, which may lead to microevolution of traits to cope with these changing

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Fig. 5.12  Mean growth rate (a), oxygen consumption (b), and levels of HSP60 (c) and HSP70 (d) of Enallagma cyathigerum larvae in the presence and absence of predation risk. To simulate predation, kairomones of the stickleback Gasterosteus aculeatus were added. Numbers above bars represent sample sizes (*p < 0.05; ns = not significant) (From Slos and Stoks 2008. With permission from Wiley)

selective pressures. Pauwels et al. (2007) demonstrated microevolution of a physiological trait in a natural population of the waterflea, D. magna. Levels of the stress protein HSP60 showed genetic variation, indicating in situ evolutionary potential, and the levels increased between the years 1970 and 1990. The observed microevolutionary increase did not fit the historically documented changes in fish predation pressure in this pond, but it paralleled an increase in the load of infective stages of epibionts through time. In line with this, the locally most abundant epibionts caused an induction of HSP60. Because stress proteins show evolutionary potential and protect organisms against a wide array of environmental factors, microevolution of stress proteins in natural populations is likely to be common. Ittiprasert et al. (2009) who studied the transmission of schistosome parasites in water snails recently presented another elucidating example. It is well understood that schistosomes develop successfully in susceptible snails but are encapsulated and killed in resistant ones. Mechanisms shaping these outcomes involve the parasite’s ability to evade the snail’s defenses. RNA analysis from resistant, non-susceptible, and susceptible juvenile snails, Biomphalaria glabrata, to Schistosoma mansoni revealed that stress-related genes HSP70 and reverse transcriptase (RT) were co-induced early in susceptible snails but not in resistant or non-susceptible

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ones: susceptible snails responded to infestation with their minimal but universal stress proteome machinery. 5.3.2.5 Pathogens Plants Central in the plant immune response to pathogens are disease resistance proteins (R-proteins). The conserved HSP90 is required for resistance; however, the function of the HSP90–R-protein complex is not yet clear. HSP90 could be involved in the conformational regulation of these complexes. It might also be required for the stability of R-proteins, perhaps preventing their degradation. Another possibility is that HSP90 and other chaperones regulate the conformation of R proteins within complexes, perhaps facilitating intramolecular rearrangements (Soosaar et al. 2005). Animals HSPs are involved in any insult including pathogen challenging, as exemplified in invertebrates such as scallops. Song et al. (2006) observed a clearly time-dependent expression pattern of AIHSP70 after bay scallops, Argopecten irradians, were infected by Vibrio anguillarum. mRNA expression reached a maximum level after short-term exposure and then dropped progressively. Increased levels of HSP70 in various tissues were also observed in coho salmon, Oncorhynchus kisutch, exposed to the pathogen Renibacterium salmoninarum, sea bream, Sparus sarba, exposed to Vibrio alginolyticus and rainbow trout, Oncorhynchus mykiss, infected with the bacterial pathogen V. anguillarum. The increased HSP expression and tissue-specific HSP response in the western painted turtle, Chrysemys picta bellii, during bacterial infection also suggested a role for HSPs in immunopathological events in reptiles. An early study showed that the expression of HSP70 increased in eastern oyster, Crassostrea virginica, hemocytes with increasing intensity of Perkinsus infection (Song et al. 2006 with further references). Overall, HSP70 is involved in the response to bacteria in vertebrates as well as invertebrates.

5.4 Costs of HSP Expression From the presented examples, it is obvious that HSP induction is a universal response of organisms to any kind of stressor. Now, the questions arise: What are the costs of the HSP response? Does it lead to reduced fitness of individuals? Are there even benefits of HSP expression? This issue has been comprehensively addressed by many researchers. For instance, Hercus et al. (2003) showed that in D. melanogaster females,

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Hsp70 level stress resistance

5  Heat Shock Proteins: The Minimal, but Universal, Stress Proteome

Hsp70 level

Stress resistance

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Fig. 5.13  Schematic description of HSP70 expression level and survival rate under stress in relative units to stress after hardening generalized from heat-stressed Drosophila melanogaster. The hardening benefits and HSP70 level were measured at various times after hardening. Hardening increased survival and the HSP70 level. However, the curves characterizing the two processes do not coincide as HSP70 level decreases much faster with time than survival. The HSP70 expression levels therefore only explain a part of the increased thermotolerance obtained by the hardening treatment (From Hoffmann et al. 2003. With permission from Elsevier)

repeated mild stress had a slightly detrimental effect on fertility and fecundity only when young flies were exposed to the stress but not later in life. The time dependency of benefits and potential costs (the expression of high levels of HSP70) therefore does not necessarily coincide. Along the same lines, it has been shown that when levels of inducible HSP70 expression after heat hardening return to normal, the beneficial effect of hardening on survival of a heat stress can still be substantial (Fig. 5.13). It is important to understand costs, as the ecological importance of inducible HSPs depends on the balance between benefits and costs. Costs of HSP expression have been shown with regard to fertility/fecundity, energy, development, and survival. Costs are thought to arise through the shutdown of normal cell functions during the stress response, the extensive use of energy, and the toxic effects of high HSP concentrations due to interference with normal cell function (Feder and Hofmann 1999). Direct costs of hardening (expression of HSP70) were investigated by Krebs and Feder (1998), who hardened D. melanogaster larvae at different stages and found that multiple heat exposures reduced survival but did not affect development time. Furthermore, the hardening costs were not correlated with survival, suggesting that the differences in expression cannot explain the survival effects. The superimposition of costs upon those normal for acclimation had no effect on mortality or developmental time, even when resources were especially limiting; in other words, the direct expense of HSP expression was therefore minor. Nevertheless, other effects are involved in expressing high levels of HSP70, as Sørensen et al. (2003) summarized. High HSP levels decrease or even retard growth and cell division (Krebs and Feder 1997) and reduce reproduction (Krebs and Loeschcke 1994; Silbermann and Tatar 2000). Silbermann and Tatar (2000) showed that heatinduced HSP70 expression in D. melanogaster was associated with a reduction in egg

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hatching among progeny of exposed mothers. Krebs and Loeschcke (1994) found that fecundity of D. melanogaster was reduced. However, these fecundity costs are minor under mild temperature stress. The deleterious effects may explain why cells eliminate HSP70 in the absence of stress and why the fastest removal occurs in early development when cell division is most active (Parsell and Lindquist 1993). The tight regulation suggests that a strong trade-off applies to expression of HSPs between the benefits of increased stress resistance on the one hand and costs to development, fertility, or fecundity on the other (Krebs and Loeschcke 1994). What are the costs and benefits of acclimation? Animals can counter extreme thermal conditions by becoming physiologically acclimated, allowing them to survive and even reproduce under conditions that would otherwise be highly stressful. Conspecific populations from different environments may vary substantially in stress resistance because they have become acclimated to local conditions. Acclimation is likely to be beneficial only when the acclimation regime correctly predicts the future regime. The overall balance between benefits and costs depends on the length and severity of the treatment, the environmental conditions that follow, and the time it takes to produce a fitter phenotype in response to an acclimation treatment. If temperatures fluctuate, organisms acclimated to cold or hot conditions could potentially suffer from a decrease in fitness as temperatures move to the opposite extreme (Kristensen et al. 2008). Kristensen et al. (2008) used field releases of D. melanogaster on two continents across a range of temperatures to test for costs and benefits of developmental cold acclimation (reared at 15°C throughout development) or adult cold acclimation (newly hatched flies developed at 25°C exposed to 11°C for 5 days). Both types of cold acclimation had enormous benefits at low temperatures in the field; in the coldest releases, only cold-acclimated flies were able to find a food resource. However, this advantage came at a huge cost; flies that had not been cold acclimated were up to 36 times more likely to find food than the coldacclimated flies when temperatures were warm. Such costs and strong benefits were not evident in laboratory tests where Kristensen et al. (2008) found no reduction in heat survival of the cold-acclimated flies. Field release studies, therefore, reveal costs of cold acclimation that standard laboratory assays do not detect. Thus, although physiological acclimation may dramatically improve fitness over a narrow set of thermal conditions, it may have the opposite effect once conditions extend outside this range, an increasingly likely scenario as temperature variability increases under global climate change (Kristensen et al. 2008). In Chaps. 12 and 13, we shall learn about the benefits of HSP expression, namely that the activation and induction of a common set of stress proteins can be the molecular basis of cross-tolerance, stress-hardening, and increased lifespan.

5.5 Some Need It Cold Environmental stress dramatically affects gene expression and production of heatshock proteins – the heat-shock response. Conversely, one can predict that organisms in almost stress-free environments would have reduced or even lost the ability to

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Fig. 5.14  Acquisition of thermotolerance in Hydra. At t = 0 groups of 10 polyps were transferred from 18°C to either 25°C (▲) or 30°C (● and ■) and incubated for 2 h. Such pretreated polyps were then subjected to a temperature of either 33°C (H. oligactis) or 34°C (H. vulgaris). Controls consisted of groups of 10 polyps transferred directly from 18°C to 33°C or 34°C (�,○, or □). (a) Hydra vulgaris. (b) Hydra oligactis. At the indicated time the number of viable polyps was determined (different symbols represent different experiments). Note the difference in time scales (From Bosch et al. 1988. Courtesy of the National Academy of Sciences of the United States of America)

express heat-shock proteins. Given the validity of the universality of the heat-shock response with environmental stress, organisms in such environments must have developed strategies to deactivate the production of HSPs above the constitutive level. If so, these organisms should not be able to withstand any change in their environment. In fact, several oligostenothermic organisms from cold-stable environments were identified which prove this prediction – for instance, the polyp Hydra oligactis (known as the brown Hydra) which is widely dispersed in the northern temperate zone. It is a common organism found in still waters from early spring to late autumn. Its occurrence reflects that it avoids the warmer climates and the warmer seasons. In contrast to this species, H. vulgaris and H. magnipapillata are cosmopolitan and inhabit warmer habitats. Experiments by Bosch et al. (1988) revealed that thermotolerance can be acquired by H. vulgaris but not by H. oligactis. To determine if this acquired thermotolerance could be observed in Hydra, polyps were either directly incubated at a high, lethal temperature or pre-incubated for 2 h at an elevated but non-lethal temperature and subsequently exposed to high temperature. The ability of the polyps to withstand the high temperature treatment was then tested. The results of this experiment are shown in Fig. 5.14. After pretreatment at 30°C, H. vulgaris showed 100% survival at the high temperature for at least 4 days (Fig. 5.14a). In H. oligactis, however, pre-incubation did not lead to any protection (Fig.  5.14b). The reason for the failure to

129

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H. oligactis

hsp70 mRNA abundance, arbitrary units H. magnipapillata

5.5  Some Need It Cold

90

Fig. 5.15  Accumulation of HSP70 mRNA following heat shock in Hydra oligactis and H. magnipapillata (From Brennecke et al. 1998. With permission from Wiley)

induce thermotolerance is that the latter species is not able to produce HSPs. In a subsequent paper, Gellner et  al. (1992) demonstrated that the transcriptional induction of HSP70.1 expression in response to stress was similar in H. oligactis and other Hydra species which are adapted to habitats of wide temperature range and variable water quality. However, the released HSP70 mRNA did not accumulate (Fig. 5.15); it was obviously not stable. Thus, the difference in HSP70 mRNA stability is responsible for the habitat-correlated differences in the stress response in Hydra species. The cold-adapted species does not produce HSP70 above the constitutive level and saves energy in doing so. The hypothesis that organisms from stable environments save energy by suppressing expensive defense mechanisms gained recent support from comparative studies with gammarids from contrasting habitats. For instance, Bedulina et  al. (2010b) determined the thermotolerance of two closely related amphipod species from sub-littoral (Orchestia gammarellus) and supra-littoral zones (Gammarus oceanicus) of the sea and found that the environmental temperature regime modifies key cellular defense mechanisms: higher levels of constitutive HSP synthesis and higher levels of antioxidant enzymes in the supra-littoral species likely reflected adaptation to this highly thermally variable environment. Another well understood example of even more extremely cold-adapted organisms than the Hydra species is that of Antarctic fishes which are compared to phylogenetically related species from New Zealand. Particularly, Antarctic fish of the teleost suborder Notothenioidei are extreme stenotherms that live in the cold, thermally stable waters of coastal Antarctica where temperatures range from +0.3°C to −1.86°C. It is certain that these highly endemic fish have been isolated in extremely cold water for many millions of years (Hofmann et  al. 2000 and references therein). Hence, Antarctic notothenioids provide a unique opportunity to study evolutionary adaptation to stable, subzero temperatures. As a consequence of having undergone several million years of evolution in extreme cold, notothenioids are distinguished by a number of physiological adaptations to low

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temperatures and by a loss of specific traits that are obviously no longer needed (for details, see Cheng and Detrich 2007). Evolution in such environments might also permit the loss of traits whose function is to increase heat tolerance or to facilitate acclimatization to short-term changes in temperature. To check whether or not highly cold-adapted stenothermal fishes have lost this trait, Hofmann et al. (2000) first examined the occurrence of heat-shock response in the Emerald rockcod, Trematomus bernacchii. A constitutively expressed HSP70 was present in this species. Yet, fishes subjected to a mild heat stress yielded no evidence for synthesis of any size class of HSP. Whether the loss of the heat-shock response is due to dysfunctional genes for inducible HSPs, unstable mRNAs (as in H. oligactis), or the absence of a functional heat-shock factor or some other lesion remained obscure in this first fish study. To identify how widespread the loss of the HSPs is within the Antarctic and coldtemperate non-Antarctic notothenioids, Hofmann et al. (2005) studied the thornfish, Bovichtus variegatus, and the black cod, Notothenia angustata. Interestingly, one of the two New Zealand notothenioids possessed a heat-shock response: B. variegates expressed HSPs in response to heat stress, whereas N. angustata did not display robust stress-inducible HSP synthesis at the protein-level. However, mRNA for a common HSP gene, HSP70, was present in cells of both New Zealand species following exposure to elevated temperatures. Consequently, the question arises, then the HSP70 mRNA was unstable and, hence responsible for the lack of the heat-shock response in N. angustata – comparable to the oligostenothermic Hydra species. The answer to this question is no. The Antarctic fishes have developed a different strategy. In a subsequent study, Place and Hofmann (2005) studied the expression of two genes, the constitutive HSC71 gene and the inducible HSP70 gene, in tissues from T. bernacchii to expression in tissues of Pagothenia borchgrevinki, a second Antarctic notothenioid, and the Antarctic eelpout, Lycodichthys dearborni, a phylogenetically distant Antarctic species. It became obvious that the expression of HSC71 was similar in all species; however, the constitutive expression of the inducible HSP70 gene was also manifested in these species and on a relatively high level. This suggests that the cold and thermally stable Antarctic environments seem to be perturbing to the formation and maintenance of native protein structures and that molecular chaperones facilitate the proper folding of proteins at low temperature. In sum, these fishes are indeed unable to mount a typical heat-shock response, but they do not lack the ability to synthesize HSPs. Consequently, the stability of the stressinduced gene product, the heat-shock protein, remains doubtful. One major pathway of protein degradation is by proteases, primarily by the ubiquitin (Ub)-proteasome pathway; and levels of Ub-conjugated proteins in the cell are good indicators of the integrity of the cellular protein pool, with high levels representing a high degree of protein damage (Todgham et al. 2007). In fact, this mechanism applies to Antarctic fishes lacking a proper heat-shock response, since levels of Ub-conjugated proteins in cold-adapted Antarctic fishes were significantly higher than in New Zealand fishes, suggesting that life at sub-zero temperatures impacts protein homeostasis that is the maintenance of a functional cellular protein pool. Living in the cold bears some pronounced disadvantages.

Chapter 6

Heavy Metals: Defense and Ecological Utilization

In its present form with its high diversity of aerobic pro- and eukaryotic organisms, life on earth only developed after the majority of heavy metals had been buried below the surface and after the majority of reduced iron had been oxidized to banded iron formations and, in turn, molecular oxygen could escape into the atmosphere (Schlesinger 1997; Krämer 2010). This separation of organisms from heavy metal deposits implies that the concurrence of both organisms and metals bears potential conflicts, forces organisms to handle such chemically stressful situations, and requires organisms to develop strategies to survive and evolve further and eventually to pass on the adverse challenge to competitors or predators. Organisms cope with fluctuating and mostly adverse environmental conditions by inducing general as well as stress-specific, and in some cases even adaptive, responses. Hereby, even an individual stressor, such as the exposure to one individual heavy metal, provokes not only stress-specific responses, but actuates more or less the whole stress-response machinery. This chapter considers the major defense mechanisms against metals, mostly exemplified with cadmium, Cd, as a model heavy metal, to which selected benthic and terrestrial animals and metal-tolerant plants are exposed. First, we shall learn about the stress-specific defense and then about the costs of this defense since, as with any stress-response, the specific defense is energy demanding. This means that the energy allocation of an organism has to be readjusted and this happens usually at the expense of basic physiological functions. One enthralling aspect of heavy metal challenge to organisms is the phenomenon of the hyperaccumulators in plants: Why are these plants that metal-tolerant? In which features do they differ from their less tolerant relatives, e.g. from the same genus? Are there differences in the stress response in animals and plants? This chapter reverses the common order of other chapters and brings the animal issue first and plants second, because, due the well understood phenomenon of hyperaccumulators, much more information is available about heavy-metal tolerance in plants than in animals. The following chapter presents an evolutionary outlook which tries to answer two questions: What regulates the phenotypic plasticity of metal-exposed organisms? Moreover: do the genes of the exposed organisms regulate all responses? C.E.W. Steinberg, Stress Ecology: Environmental Stress as Ecological Driving Force and Key Player in Evolution, DOI 10.1007/978-94-007-2072-5_6, © Springer Science+Business Media B.V. 2012

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6.1 General Strategies There are two generic functional strategies for reducing metal toxicity [review by Morgan et al. (2007) and Brulle et al. (2010)]. The first reduces net tissue metal accumulation, and the other increases the proportion of the body burden accumulated in non-bioreactive states. Limiting the accumulated-metal burden in metalladen environments can be genetically determined by down-regulating cation influx pumps. The principle is exemplified by the repression of high-affinity phosphate pumps in arsenate-resistant plants (Meharg and Hartley-Whitaker 2002), but similar tolerance strategies appear not to have been described in invertebrates. The alternative strategy of reducing body metal burdens through up-regulating excretory or periodic-shedding mechanisms is well-known in invertebrates (Posthuma et al. 1992; Postma et al. 1996), with Cd tolerance in a number of different taxa aided by efflux pumps similar to multidrug resistance p-glycoproteins (Callaghan and Denny 2002) (also see Appendix 3). However, increased bio-immobilization capacity may be the most common strategy. This is exemplified by the enhanced ability of the tubificid worm Limnodrilus hoffmeisteri from a long-term polluted site to sequester Cd in insoluble intracellular, metal-rich granules (Klerks and Bartholomew 1991); in contrast, worms from a clean reference site appeared to rely mainly on metallothionein induction to protect against short term Cd exposure.

6.2 The Metallothionein System1 The best-studied defense mechanism against heavy metals is the metallothionein (MT) system; however, it is not the only one in plants and animals. Genes encoding MTs are found in all eukaryotes – often in multiple copies – as well as in some prokaryotes. Multiplication of genes, in general, increases tolerance against the metal challenge as exemplified with metal-tolerant epigeic animals as wells hyperaccumulators below. Metallothioneins are small (3.5–14  kDa), ubiquitous proteins remarkably rich in cysteine (20–30% of amino acids) and devoid of aromatic amino acids and histidine (Palmiter 1998). In addition to metal binding, they contribute to control of the cellular redox status by multiple cysteine residues which can be oxidized (Viarengo et al. 2000). The functions of MTs are metal homeostasis and detoxification. Often several isoforms of MTs exist in a species that are involved in the one or the other function. This means that environmental monitoring with bulk MT contents, as often applied, may fail in many instances. Furthermore, MT isoforms are often metal specific as shown

In the “omics” age, the analysis of metal-binding proteins is often termed “metallomics”. Metallomics is a recently described metal-based variation of proteomics (see Chap. 9) that focuses on metalloproteins as markers of metal exposure and the physiological defense status of the organism. The analysis of metalloproteins profits from the very high sensitivity of inductively coupled plasma mass spectrometry, capable of analyzing metal-binding biomolecules at very low levels in complex biological matrices. Further methodological progress will clearly contribute to the improved understanding of metallomics in general and ecological metallomics in particular.

1 

6.2  The Metallothionein System

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Fig. 6.1  Cadmium effects on gene expression: literature reports. Gene expression data from control and Cd-treated Daphnia pulex. Gene expression log ratios (M = log2 treated/control) were plotted against log mean intensity values (A = 1/2log2 (treated * control). Cd-responsive elements are highlighted: cuticle protein, pink; hemoglobin, green; metallothionein, blue; ferritin, orange; chitinase, yellow; opsin (light-sensitive receptors), grey (Shaw et al. 2007, courtesy of BioMed Central)

with the blue mussel, Mytilus edulis (Ciocan and Rotchell 2004) challenged by Cd. In contrast to many proteins, MT quantity does not decrease with metal exposure; instead, the metal induces MT synthesis, providing a protective mechanism against metal toxicity. MTs from M. edulis comprise two groups of isoforms having apparent molecular masses of 10 and 20  kDa (MT10 and MT20, both groups with various subtypes). Exposure to Cd results in a marked increase in MT20, a primarily inducible isoform that is expressed only at a low level in the absence of heavy metals. Conversely, MT10 isoforms are expressed at basal levels and not induced by Cd-exposure. This means that the inducible MT20s are responsible for metal detoxification, whereas MT10s are basally expressed and therefore assure metal homeostasis. In general, the diversity of MT systems in invertebrates is considerable, as is their metal-specificity. In C. elegans, for instance, one Cd inducible MT was discovered which was not responsive to copper (Cu) or zinc (Zn) (Swain et al. 2004). In the waterflea, Daphnia pulex, three MT genes were found (Shaw et al. 2007) while in Daphnia magna, two MTs were identified, both inducible by Cd and Cu but not by Zn (Poynton et al. 2007). Shaw et  al. (2007) identified biologically sensible patterns of gene regulation upon metal challenge in D. pulex. Many of the Cd-responsive genes were part of common physiological pathways (i.e., ecdysis, metal detoxification) and few were indicative of general stress response (e.g., heat shock proteins, heme-oxidase) or overt cellular toxicity. Ecdysteroid-responsive genes and other molt related genes comprised the majority of genes regulated in response to Cd exposure (Fig. 6.1): Ecdysis and molt related regulatory pathways are generally influenced by Cd. In addition to ecdysis, Cd-binding genes were identified as well as a gene responsible for oxygen transport and iron metabolism in Daphnia. Expression of hemoglobin is known to be induced by anoxia, limiting iron supplies and Cd. At the

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cellular-level, Cd is known to induce oxidative stress. Glutathione transferase (GST) is an ­important antioxidant defense enzyme that works to detoxify the products of oxidative stress and was up-regulated in Cd-challenged Daphnia.

6.3 How Do Worms Cope with High Metal Burdens? In abandoned mine soils contaminated with various heavy metals, earthworms still reside with concentrations exceeding even 600 mg g−1 of Cd per dry weight. In addition to surviving this toxicological challenge, they bioaccumulate this metal ion to a body burden in excess of one per milligram dry weight. This accumulation of Cd is in strong contrast to the exclusion observed with other metal ions – for example, copper (Stürzenbaum et al. 2001). However, even where ions with closely related chemistry, such as Cd and Zn, are elevated within the same environment, the compartmentalization, and therefore the metabolic pathway, remains distinct. Therefore, the earthworm must have a highly developed and specific trafficking pathway for toxic metal ions. Indeed, in Lumbricus rubellus, Stürzenbaum et al. (2001) identified two MT isoforms, wMT-1 and wMT-2. Only the latter is responsive to Cd. More recently, a gene for a third Cd-binding MT isoform has been found in this earthworm: wMT-3 is enriched in embryonic tissue with still unknown function (Stürzenbaum et al. 2004). Recently, Hughes et al. (2009) turned the current knowledge almost upside down by showing that the metabolomic responses of the nematode C. elegans to Cd are largely independent of the MT status but dominated by changes in cystathionine and phytochelatins. They obtained metabolic profiles from C. elegans exposed to sublethal concentrations of Cd. Neither in the presence nor in the absence of Cd did the metallothionein status (single or double mtl knockouts) markedly modulate the metabolic profile. However, Cd exposure resulted in a decrease in cystathionine concentrations and an increase in the non-ribosomally synthesized peptides phytochelatin-2 and phytochelatin-3. This suggested that a primary response to low levels of Cd is the differential regulation of the C. elegans trans-sulfuration pathway which channels the flux from methionine through cysteine into phytochelatin synthesis. These results were substantiated by the finding that phytochelatin synthase mutants (pcs-1) were at least an order of magnitude more sensitive to Cd than single or double metallothionein mutants were. This study confirms the pioneering papers by Vatamaniuk et al. 2001. The phytochelatin-mediated pathway may also apply to other metals and metalloids (e.g., copper, zinc, arsenic) known to induce phytochelatin production in plants and microbes (Hughes et al. 2009). Phytochelatins are low-molecular weight peptides (Fig.  6.2) synthesized from glutathione by the enzyme PC synthase. They were considered to be plant-specific until the recent isolation of a phytochelatin synthase and a phytochelatin transporter gene from C. elegans (Vatamaniuk et al. 2001). PCs have also been found in earthworms and chironomids (Cobbett and Goldsbrough 2002) as well as the tunicate, Ciona intestinalis, but the gene is lacking in vertebrates (Dehal et al. 2002). PCs may be more important in invertebrates than hitherto thought.

6.3  How Do Worms Cope with High Metal Burdens? Fig. 6.2  Chemical structure of phytochelatin (n = 2–11)

135 SH O

H H

N H

OH

+

NH

NH O OH

O O

n

Fig. 6.3  Scheme showing how heavy metal exposure, directly as well as indirectly through signal transduction, triggers a transcriptional response, including induction of metallothionein (MT) and phytochelatin (PC) which may mitigate damage by decreasing the free metal pool (Modified from Janssens et al. 2009, with permission from Wiley). The prevalence of the PC pathway in detoxification of Cd in Caenorhabditis elegans is highlighted (see Hughes et al. 2009). It is open to further studies whether or not these findings can be generalized; yet, Bernard et al. (2010) doubt that the PC pathway has the same significance in Eisenia fetida as in C. elegans

The Cd-induced transcriptional profile includes genes related to metal trafficking (metallothionein, phytochelatin synthase, ion pumps), antioxidant defense (superoxide dismutase, catalase, peroxidases), sulfur salvage (sulfate uptake proteins; synthesis of methionine, cysteine and glutathione), iron metabolism (ferrotransferrin, iron transporters, ferritine), and the innate immune response (serine proteases and antimicrobial peptides) (van Straalen and Roelofs 2005, 2006). An overview of the proposed regulatory pathways is sketched in Fig. 6.3. Brulle et al. (2007) were particularly interested in the energy allocation in Cdchallenged earthworms, Eisenia fetida. The authors suggested a preferential energy allowance for MT synthesis to facilitate a faster and more effective detoxification process but also for exposed animals to acquire a metal resistance. Diverted energy

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Fig. 6.4  Percentage of differentially expressed genes in different gene categories in Eisenia fetida cells after exposure of the worms to a complex mixture of metallic trace elements representative of a highly polluted smelter soil (From Brulle et al. 2008. With permission from Elsevier)

would be redistributed to the cellular machinery responsible for the synthesis of MT in order to protect the organism from the toxic effects of Cd. MT synthesis is temporarily performed to the detriment of the synthesis of other proteins which are not of major importance when exposure to metal trace elements occurs. Moreover, the number of transcripts coding antioxidant system proteins like CAT and SOD strongly drops. These declines can be consecutive to massive synthesis of MT with antioxidant properties against the ROS formed following an exposure to Cd. This trade-off constitutes a global response to a highly stressful situation. Usually, environmental contaminations do not occur as mono-toxicant pollution but as a complex mixture of inorganic and organic chemical compounds. To increase the environmental realm of their studies, Brulle et al. (2008), in a more recent paper, exposed E. fetida to a mixture of heavy metals representative of a highly polluted smelter soil. To better understand the physiological changes, the mechanisms of acclimation and the mechanisms of detoxification caused by metals the expressed sequence tags, ESTs, were associated to six major cellular physiological functions: (i) immunity; (ii) metabolism; (iii) signal transduction; (iv) replication, repair, transcription, and translation; (v) cytoskeleton production and maintenance; and (vi) transport (Fig. 6.4). It becomes obvious that, besides the share of unknowns and non-classifiables, metabolism as well as processes related to transcription, repair,

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and signaling transduction are mostly affected. Yet, interestingly a relatively high share of immunity genes also are hit, sensitizing the exposed animals by an immunotoxic impact and hence increasing the risk of microbial infections by altering the defense processes. In a subsequent study, the involvement of immunogenes were approved (Bernard et al. 2010).

6.4 Heavy-Metal Tolerance and Genetic Adaptation in Animals Physiological acclimatization is a form of phenotypic plasticity by which an organism can adjust its metabolism in an acute response in order to cope with altered environmental conditions such as heavy metal challenge. Genetic adaptation is an evolutionary mechanism that acts over several generations in which genotypes with better constitutive or plastic responses toward adverse environmental conditions have a higher fitness and hence increase their abundance in the population. Both mechanisms are genetically determined; Posthuma and van Straalen (1993) have provided reviews of terrestrial and aquatic studies of tolerance to heavy metals in invertebrate species. A potential epigenetic mechanism is being considered as an alternative pathway for heavy metal resistance in invertebrates (Vandegehuchte et al. 2010). It is obvious from many populations subject to sufficiently strong selection by heavy metal contamination such as mine ores or industrial emissions that genetically determined heavy-metal tolerance can evolve. However, metal tolerance in animals involves physiological and genetic mechanisms and have not (yet) produced morphologically recognizable ecotypes or species as in the case of some plants. Many animals may evolve an enhanced and intermittent or even persistent heavymetal tolerance. This can be achieved by altering the structure of proteins (through mutations in the coding regions of genes) or by altering the amount of protein (through changes in transcriptional regulation). MT expression, as one prominent metal detoxification pathway, is assumed to be regulated by metal regulatory transcription factor 1 (MTF-1); however, up to now, the involvement of MTF-1 has only been proven for some vertebrates and Drosophila. Data on invertebrates such as nematodes and earthworms suggest that other mechanisms of metallothionein induction may be present. A detailed study of Cd tolerance was done for a species of soil-living springtail, Orchesella cincta. The MT gene of this species is overexpressed in metal-exposed field populations. Analysis of the MT promoter has demonstrated extensive polymorphisms that have functional significance. In a study comparing 20 different populations, the frequency of a high-expresser promoter allele was positively correlated with the concentration of metals in soil, especially Cd (Janssens et al. 2009). Mutations responsible for variation in transcriptional regulation of a certain gene can be located in different sites of a genome. Cis-regulatory variants are located in the functional non-coding DNA, such as promoters, silencers, and enhancers, representing polymorphisms in the structure and arrangement of ­binding

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Fig. 6.5  The transcription of a single gene involves a great variety of regulatory proteins binding to DNA sequences upstream of the gene and to each other. Details in text (From Janssens et al. 2009. With permission from Wiley)

sites for ­transcription factors, chromatin-remodeling factors, and factors that determine mRNA stability. In contrast, trans-regulatory variants determine the amount and properties of one or several of these factors, mostly regulatory proteins but also microRNAs which determine the expression of the particular gene (Janssens et al. 2009) (Fig. 6.5). Adaptive mutations (black dots) may occur in the coding region of the gene (structural mutations), and these mutations may change the structure of the protein if they are non-silent. In addition, many different mutations may change the amount of protein produced by modulating expression of the gene. These mutations may reside in cis (directly upstream of the gene, often involving rearrangements of transcription factor binding sites) and in trans (elsewhere in the genome, influencing the expression or structure of transcriptional regulators). In the case of the collembolan O. cincta, adaptive changes in the cis-regulatory region of metallothionein are shown to be involved in field-selected heavy-metal tolerance. The over-expression of target genes as a major mechanism of adaptive evolution of stress tolerance also has been identified for metal tolerance in invertebrates. For example, metal tolerant populations of O. cincta are linked to the constitutive over expression of the MT gene (Roelofs et al. 2007). In a microarray study, Cd-induced

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gene expression of a tolerant population was compared to a metal-sensitive ­reference population (Roelofs et al. 2010). Clear differences between the two strains/ecotypes at the transcriptional level were observed. The reference population showed an unequivocal signature of stress-induced perturbation of gene expression in response to the metal challenge that was significantly different to the tolerant population which lost part of its plastic response.

6.4.1 Springtail Orchesella cincta: Model of Cadmium Tolerance in Animals Orchesella cincta is a common species of Collembola inhabiting the litter layer of forests and woodlands, with a preference for disturbed habitats. Tolerance in populations from historically contaminated sites as compared to animals from reference sites is achieved by smaller reduction in growth upon Cd exposure, increased survival of populations upon dietary Cd exposure, and elevated excretion efficiency for lead (Pb) and Cd. In between molts, about 90% of the Cd body burden can be retrieved in the gut tissue (Janssens et al. 2009). A 7.1 kDa Cd-binding protein was isolated from O. cincta which was characterized as an MT. This MT is inducible by Cd, binds 7–8 Cd atoms per molecule, and is almost exclusively expressed in the midgut tissues (Hensbergen et al. 2000). O. cincta MT was shown to be encoded by a single copy gene. An increased Cd inducibility was revealed in a tolerant population (Sterenborg and Roelofs 2003). A field survey of 15 European populations revealed eight alleles in the coding region of the O. cincta MT and an increase in genetic diversity at this locus in heavy metalstressed populations in comparison to reference populations (Timmermans et  al. 2009). The authors suggest that selection may be directed to linked regulatory loci, such as the promoter. Differential transcriptional regulation of genes other than MT was reported to play a role in heavy-metal tolerance in O. cincta. These genes, involved in cell signaling, cellular trafficking, and apoptosis, exhibited a population-specific response to Cd exposure (Roelofs et al. 2007). Janssens et al. (2007) described polymorphisms in the O. cincta MT promoter locus. Later, Janssens et al. (2008) compared 23 O. cincta field populations from a wide variety of contaminated soils in Belgium, France, Germany, and The Netherlands, including sites near smelters, mines, and landfills. In each population, allele and genotype frequencies for the MT promoter locus were estimated. When grouped according to the degree of heavy metal contamination, the sites were best discriminated on the basis of the frequency of one MT promoter. A significant correlation was observed between the promoter frequency and the exchangeable Cd concentration of the soil. Overall, the O. cincta study indicates that altered transcriptional regulation of MT is involved in the evolution of metal tolerance in the mine populations.

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6.5 Hyperaccumulating Plants: Surviving in Adverse Environments In addition to sites contaminated by human activity, natural mineral deposits containing particularly large quantities of heavy metals are present in many regions of the globe. These areas often support characteristic plant species that thrive in these metal-enriched environments. Whereas many species avoid the uptake of heavy metals from these soils, some of these species can accumulate significantly high concentrations of toxic metals to levels that by far exceed the soil levels (Memon and Schröder 2009). It is known that the essential metals Fe, Mn, Zn, Cu, Mo, and Ni are taken up and accumulated by plants (Williams et al. 2000). Certain plants are also able to accumulate heavy metals which have no known biological function. These include Cd, Cr, Pb, Co, Ag, and Hg (Baker and Brooks 1989). However, excessive accumulation of heavy metals can be toxic to most plants. The ability to acquire a tolerance both against heavy metals and an accumulation to very high concentrations have evolved both independently and together in a number of different plant species so that the question arises why some plants have developed a metal-resistance while others did not. This answer is another paragraph in the plantherbivore warfare, the “Metal Defense Hypothesis”. The Metal Defense Hypothesis explains with high plausibility why hyperaccumulating plants bioconcentrate metals far above their physiological requirement. Metals defense against biotic stress by herbivores, pathogens, and parasites is the answer. This hypothesis was initially formulated based on an observation that fewer insects feed on Ni hyperaccumulators. Further investigations have also reported some cases where high levels of Ni, Zn, Cd, or Se have provided effective protection against fungi or even snails and viruses (Poschenrieder et  al. 2006). Plants are usually referred to as hyperaccumulators if they concentrate metals in their aboveground tissues to levels far exceeding those present in the soil or in nonaccumulating species growing nearby. It has been proposed that a plant containing more than 0.1% of Ni, Co, Cu, Cr, and Pb or 1% of Zn on a dry weight basis is called a hyperaccumulator, irrespective of the metal concentration in the soil (Baker and Walker 1990). Metal hyperaccumulators have the rare ability to colonize heavy-metal-loaded soils and to hyperaccumulate heavy metals. Over 450 plant species identified as hyperaccumulators account for less than 0.2% of all angiosperms (Baker et  al. 2000). Already in 1865, the first reference to heavy metal hyperaccumulation in plants was made when Noccaea caerulescens (formerly Thlaspi caerulescens) growing on Zn-rich soils near the German-Belgium border was reported to contain 17% of Zn in its ash. Brooks et al. (1977) coined the term “hyperaccumulator”. The majority are Ni hyperaccumulators (>317 species; Baker et al. 2000). Hyperaccumulators occur in over 34 different families. The Brassicaceae family is relatively rich in them, in particular the genera Alyssum and Noccaea. Since Ni hyperaccumulation occurs in a broad range of unrelated families, it is certainly of polyphyletic origin (Macnair 2003). Specific heavy metal accumulator plants have

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been reported, for example, Mn (Acanthopanax sciadophylloides, Maytenus ­founieri); Ni (Sasa borealis, Alyssum sps.); Co (Clethra barbinervis); Cd, Zn (Clethra barbinervis, Ilex crenata, Noccaea caerulescens, Arabidopsis halleri); Pb (Thlaspi rotundifolium ssp. cepaeifolium, N. caerulescens, Sesbania drummondii); and Se (Brassica juncea). Furthermore, several endemic metal accumulators can be expected as a survey of the flora of Cu mining areas of Southeastern Anatolia by Memon and his group showed who identified a Brassica nigra ecotype as Cuaccumulating (Memon and Schröder 2009). How did hyperaccumulation evolve? The selective factors causing the evolution of hyperaccumulation are unknown and difficult to identify retrospectively. The different non-mutually exclusive current hypotheses are increased metal tolerance, protection against herbivores or pathogens, inadvertent uptake, drought tolerance, and allelopathy. The hypothesis of protection against herbivores and pathogens is certainly the most popular one (Verbruggen et al. 2009a). What makes the hyperaccumulators so peculiar? Which mechanisms and regulatory pathways increase their tolerance to the heavy metals? Moreover, why do closely related species, such as Arabidopsis thaliana and A. halleri, behave so contrastingly with respect to metal tolerance? All plants apparently possess a basal tolerance of toxic non-essential metals such as Cd2+ and metalloids such as As and Se (Clemens 2006). In a multicellular organism, the situation is complicated by tissue- and cell-specific differences and by intercellular transport. Figure 6.6 illustrates the processes that influence metal accumulation rates in plants: mobilization and uptake from the soil, compartmentation and sequestration within the root, efficiency of xylem loading and transport, distribution between metal sinks in the aerial parts, and sequestration and storage in leaf cells. At every level, concentration and affinities of chelating molecules, as well as the presence and selectivity of transport activities, affect metal accumulation rates (Clemens et al. 2002). In their pioneering paper, Herbette et al. (2006) identified the early response of A. thaliana to Cd exposure. The response profiles demonstrated the existence of a regulatory network that differentially modulates gene expression in a tissue- and kinetic-specific manner. One of the main responses observed in roots was the induction of genes involved in sulfur assimilation–reduction and GSH metabolism. In addition, GSH and PC content showed a transient decrease of GSH after 2 and 6 h of metal treatment in roots correlated with an increase of PC contents. Altogether, the results showed that to cope with Cd, plants activate the sulfur assimilation pathway by increasing transcription of related genes to provide an enhanced supply of GSH for PC biosynthesis. Interestingly, in leaves an early induction of several genes encoding enzymes involved in the biosynthesis of phenylpropanoids was observed. Accumulation of these metabolites is crucial as far as their biological activities could be linked to the antioxidant or metal chelating properties.

To date, only for a very few plants, for instance the marine diatom Thalassiosira weissflogii, Cd has been identified as an essential nutrient (Lee et al. 1995).

2 

Fig. 6.6  The plant metal homeostasis network. Molecular mechanisms proposed to be involved in heavy metal accumulation by plants. (a) Metal ions are mobilized by secretion of chelators and by acidification of the rhizosphere. (b) Uptake of hydrated metal ions or metal-chelate complexes is mediated by various uptake systems residing in the plasma membrane. Inside the cell, metals are chelated and excess metal is sequestered by transport into the vacuole. (c) From the roots, heavy metals are transported to the shoot via the xylem. Presumably, the larger portion reaches the xylem via the root symplast. Apoplastic passage might occur at the root tip. Inside the xylem, metals are present as hydrated ions or as metal-chelate complexes. (d) After reaching the apoplast of the leaf, metals are differentially captured by different leaf cell types and move cell-to-cell through plasmodesmata. Storage appears to occur preferentially in trichomes. (e) Uptake into the leaf cells again is catalyzed by various transporters [not depicted in (e)]. Intracellular distribution of essential heavy metals (= trafficking) is mediated by specific metallochaperones and transporters localized in endomembranes (please note that these processes function in every cell). Abbreviations and symbols: CW cell wall; M metal; filled circles chelators; filled ovals transporters; bean-shaped structures metallochaperones (From Clemens et al. 2002. With permission from Elsevier)

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Following mobilization, a metal has to be captured by root cells. Metals are first bound by the cell wall, an ion exchanger of comparatively low affinity and low selectivity. Transport systems and intracellular high-affinity binding sites then mediate and drive uptake across the plasma membrane. Uptake of metal ions is likely to take place through secondary transporters such as channel proteins and/or H+coupled carrier proteins. The major groups are: –– –– –– –– ––

zinc-regulated transporter (ZRT) iron-regulated transporter proteins (IRT) (ZRT, IRT- like proteins = ZIP) cation diffusion facilitators (CDF) heavy metal ATPases (HMA) natural resistance associated macrophage protein (NRAMP) transporter families –– FRD3, a ligand transporter (Krämer et al. 2007). With the model green algal species Chlamydomonas reinhardtii, there is a discussion about the transporters involved in Cd-tolerance. Hanikenne et  al. (2005) identified the transporter as a member of the ATP-binding cassette (ABC transporter of mitochondria (ATM)/heavy-metal tolerance (HMT) subfamily of the half-size ABC transporters. This subfamily includes vacuolar HMT-type proteins transporting PC–Cd complexes to the vacuole. On the other hand, Wang and Wu (2006) assigned the Cd-tolerance to CrMRP2, a member of the multidrug resistance-associated protein (MRP)/cystic fibrosis transmembrane conductance regulator (CFTR) subfamily of ABC transporters. The concerned gene, CrMRP2, was expressed upon Cd-exposure and was implicated in the formation/accumulation of a stable high molecular weight PC-Cd complex. A synopsis of the main metal transporters is presented in Table 6.1. How do plant cells cope with heavy metal excess? This process has recently been depicted for Cd by Verbruggen et al. (2009b) (Fig. 6.7). Cd2+ ions are taken up by Fe2+ and Zn2+ ZIP transporters and possibly by Ca2+ transporters/channels. In nonhyperaccumulators like Arabidopsis, the ZIP transporter IRT1 seems to be a main entry for Cd. The main detoxification pathway of Cd2+ in roots of non-hyperaccumulators relies on PC complexation and vacuolar transport of Cd–PC complexes of low molecular weight. In the vacuole, high-molecular weight complexes may be formed that contain sulfides (S2−). The stability of those complexes and the fate of PCs are not well understood. Cd can also be transported to the vacuole by the activity of different transporters (cation exchangers, HMA3) or as Cd-GS2 complexes by an unidentified ABC transporter. Part of the vacuolar Cd pool can be effluxed back into the cytosol by NRAMP activity. MTs are also potential Cd ligands in the cytosol. A considerable fraction of Cd loaded into the xylem seems to be in the ionic form. HMA4 and to a lesser extent HMA2 are involved in Cd xylem loading. Cd may also be loaded as bound to an unidentified (X) ligand. In Cd hyperaccumulators, a higher influx of Cd into the roots is thought to be mediated by ZIP transporters. In Noccaea caerulescens, there is no conclusive evidence that IRT1 homologs have a Cd transport activity. Vacuolar storage of Cd in roots is limited, either as Cd(II) or Cd(II)–GS/Cd(II)–PC complexes. There is no evidence that HMA3 has

AtNRAMP1-6 LeNRAMP1-3 AhNRAMP3 AtZIP1-12 OsZIP4 AtIRT1 OsIRT1-2 LeIRT1-2 NcIRT1-2 NtIRT1 AtMTP1 NgMTP1 AhMTP1 PtdMTP1 NtMTP1 CrMRP2 CrCds1

NRAMP (metal remobilization from the vacuole)

ZIP (metal uptake into cells)

IRT (metal uptake into cells)

CDF (cation diffusion facilitator)

MRP HMT

A. thaliana, A. halleri, Noccaea caerulescens, Glycine max, Oryza sativa

A. thaliana, O. sativa

A. thaliana, N. caerulescens, L. lycopersicum, O. sativa, Nicotiana tabacum

A. thaliana, A. halleri,Noccaea goesingense,N. tabacum, Populus trichocarpa, P. deltoids

Chlamydomonas reinhardtii

Cd

Zn

Cd, Zn

Zn

Fe, Cd

Cell

Roots

Shoots and roots

Shoots and roots

Shoots and roots

Table 6.1  Overview of some of the identified metal transporters and their tissue-specific expression in plants (Memon and Schröder 2009; Verbruggen et al. 2009a, amended) Plant name Protein families Gene name Metals Tissue expression Arabidopsis thaliana , A. halleri, HMA (xylem loading/unloading AtHMA1-8 Cu, Zn, Cd, Co, Pb Shoots and roots Lycopersicon lycopersicum metal (complexes)) AhHMA3-4 NcHMA4 GmHMA8 OsHMA9

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cd(II)-x cd(II)

cd(II)

145

?

+x cd(II)

2 GSH

cd(II)-GS2 HMW

MT cd(II)-GS2

ZIP transporters (e.g. IRT1*)

S2−

cd(II)-PCs LMW

Ca

2+

channels

Heavy metal ATPases (HMA3* at the vacuolar membrane, primary role in xylem loading of HMA4 and to a lesser extent of HMA2)

cd(II)-PCs LMW

Unidentified Cd(II)-GS2 and Cd(II)-PC ABC transporter(s)

cd(II)-X

?

+X ?

2 GSH

MT cd(II)-GS2

cd(II)-GS2

NRAMP (NRAMP3, NRAMP4) Unidentified Cd(II)-X transporter

cd(II)

cd(II)

cd(II)

Cation exchangers (CAX2, CAX4, MHX)

Possible Cd ligand *No evidence for Cd transport activity in hyperaccumulators

HMW S2−

cd(II)-PCs LMW

cd(II)-PCs LMW

Fig. 6.7  Mechanisms to cope with As or Cd excess in roots. A schematic representation of main processes involved in Cd2+ uptake, possible metabolism, vacuolar sequestration, and translocation in roots of non-hyperaccumulators (upper graph) and hyperaccumulators (lower graph). Inside the cell, only the vacuole is shown. Line thickness relates to flux rate. Question marks refer to poorly characterized processes. For simplicity, neither root tissue specificity, efficiency of radial symplastic route, nor long-distance transport through phloem is represented (From Verbruggen et al. 2009b. With permission from Elsevier). HMW = high molecular weight; LMW = low molecular weight

Cd transport activity in hyperaccumulators. In addition, NRAMP3 and NRAMP4 genes are highly expressed, suggesting a higher vacuolar efflux. The majority of Cd(II) is loaded into the xylem by the activity of HMA4. To contribute to answers to the question of why hyperaccumulators are that peculiar, Weber et al. (2006) analyzed transcriptome changes upon Cd2+ and Cu2+ exposure in roots of A. thaliana and the Cd2+-hyperaccumulator A. halleri. Particularly, three categories of genes were identified: (1) common responses which might indicate stable and functionally relevant changes conserved across plant species; (2) hyperaccumulator-specific responses as well as transcripts differentially regulated between the two species, representing candidate genes for

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Fig. 6.8  Venn diagrams displaying the overlaps between Cu2+ and Cd2+ responses in Arabidopsis thaliana and Arabidopsis halleri (a) as well as the overlaps in responses to Cu and Cd exposure between the two species (b). The diagrams in (a) reveal the existence of Cd2+-specific responses. There are 4 and 140 genes that constitute the “Arabidopsis Cd2+” and the “Arabidopsis Cu2+” core responses, respectively (b) (From Weber et al. 2006. With permission from Wiley)

Cd2+ hypertolerance; and (3) those specifically responsive to Cd2+ and therefore indicative of toxicity mechanisms or potentially involved in signaling cascades. The data of Weber et al. (2006) defined, for instance, Arabidopsis core responses to Cd2+ and Cu2+. In particular, the number of Cd2+-responsive genes detected in A. halleri in relation to the total number of transcripts present was lower for A. halleri by about a factor of 10. Of the five Cd2+-responsive genes in A. halleri, four are up-regulated also in A. thaliana (Fig. 6.8). They constitute the “Arabidopsis Cd2+ core response”. With Cd2+, 23 transcripts were identified as being specifically up-regulated in A. thaliana; seven of these are not up-regulated by any other biotic or abiotic-stress condition tested so far. The majority of these specifically Cd2+-responsive genes in A. thaliana roots encode putative signal-transduction components. The detection of apparently highly Cd2+-specific transcriptional responses suggests either the existence of a specific Cd2+-sensing system or the perception of rather specific Cd2+ effects (Weber et  al. 2006). Meanwhile the numbers of candidate genes that are expressed at higher levels in A. halleri have increased to more than 30 (Hanikenne et al. 2008). The involvement of heavy-metal transporters in A. halleri in comparison with A. thaliana is shown in Fig. 6.9.

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Fig. 6.9  Heavy metal-related transporters exhibit distinct expression patterns among various tissues in Arabidopsis halleri: transcript levels of WBC11, HMA4, NRAMP5, IRT3, ZIP3, and ZIP12 in A. halleri (roots, stems, and leaves) and in A. thaliana (roots, floral stems, and leaves). The transcript levels of all genes were normalized against the ACT8 transcript level in the roots of A. thaliana (From Chiang et al. 2006. With permission from the American Chemical Society)

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6.5.1 Why Do Closely Related Plant Species Posses Contrasting Tolerance to Heavy Metals? Hyperaccumulating plants survive in environments contaminated by heavy metals, therefore they must have developed an adaptive evolution of stress tolerance. It can easily be assumed that this stress tolerance is associated with constitutive over-expression of stress genes. More generally, the phenomenon of constitutive overexpression of a large array of genes seems to be a common process in the adaptation of plants to extreme environments. For example, the salt cress, Eutrema salsuginea (formerly Thellungiella halophila), is a close relative of A. thaliana but can grow in 0.5 M NaCl medium without special morphological alterations. It appeared that a large number of genes that are stress-inducible in A. thaliana were constitutively over-expressed in Eu. salsuginea. The possible importance of epigenetics in plant adaptation to extreme environments has not yet been investigated (Verbruggen et al. 2009a). In fact, the overexpression of genes has been shown in the metal hyper-accumulating plant N. caerulescens (van de Mortel et  al. 2006). Besides stress response genes (metallothioneins), genes involved in metal homeostasis (Zn transporters) and lignin biosynthesis were constitutively over-expressed. Finally, up regulation of errorprone DNA polymerase, resulting in increased mutagenesis and evolvability, has been associated with stress-adapted evolution in bacteria (Foster 2005). Arabidopsis halleri and A. thaliana are excellent candidates for comparison of their response to Cd or Zn exposure on the molecular level and to get insight in evolutionary mechanisms. This comparison has recently been published by Hanikenne et al. (2008). It is well understood that HMA4 is among a large number of genes more highly expressed in A. halleri than in A. thaliana and encodes a plasma membrane protein of the 1B family of heavy metal pumps in the P-type ATPase superfamily. To find out whether A. halleri HMA4 (AhHMA4) functions in metal hyperaccumulation or hypertolerance of A. halleri, the authors reduced the expression of AhHMA4 by RNA interference. The obtained results demonstrated that in fact high HMA4 transcript levels are required for highly efficient root-to-shoot Zn flux and for Zn hyperaccumulation in the shoots of A. halleri. This is distinct from the function of A. thaliana HMA4 (AtHMA4) in root-toshoot translocation of Zn for the maintenance of Zn-dependent processes in the shoot. In A. halleri, the silencing of AhHMA4 impairs the release of Zn from the root symplasm into the apoplastic xylem vessels which provide the primary pathway for the movement of solutes from the root to the shoot with the transpiration stream. The next step was to address the molecular basis for elevated HMA4 expression in A. halleri compared to the non-accumulator A. thaliana. There is evidence that there is a triplication of HMA4 in the genome of A. halleri. Increased expression of HMA4 in A. halleri supports the enhanced Zn flux from the root symplasm into the xylem vessels necessary for shoot Zn hyperaccumulation and acts as a physiological master switch to up-regulate Zn deficiency response gene expression in roots.

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This means that the high HMA4-dependent Zn flux into the xylem depletes ­symplastic Zn pools, thereby triggering the up-regulation of Zn deficiency response genes in the roots. Is the high level of HMA4 transcripts sufficient to protect the plant cells from damage? To answer this intriguing question, Hanikenne et al. (2008) produced A. thaliana AhHMA4 transformants and grew them in media supplemented with toxic concentrations of Zn or Cd. 150 mM Zn or 40 mM Cd led to enhanced leaf chlorosis and smaller rosettes which are signs of Zn and Cd hypersensitivity of the shoots. When cultivated in 5 mM Zn, AhHMA4 transformants were healthy and accumulated slightly higher Zn concentrations than non-transgenic plants. These results suggest a more efficient transfer of metals from roots to leaves in AhHMA4 transformants compared to non-transgenic A. thaliana. The metal sensitivity of shoots of A. thaliana expressing AhHMA4 indicates that additional genes are required for metal detoxification in order to accommodate the high HMA4dependent metal flux into the shoots of A. halleri that were not studied by Hanikenne et al. (2008). Verbruggen et al. (2009a) evaluated the gene duplication issue more skeptically because in a previous study, van de Mortel et al. (2006) indeed found a total of 131 genes encoding putative transcription factors up-regulated in N. caerulescens compared with A. thaliana, but no clear candidates have popped up (van de Mortel et al. 2008). Hence, gene duplication may contribute to the ability of hyperaccumulators to express genes at a very high level. The tolerance of hyperaccumulators includes also the detoxification of metals, and two categories of genes are promising candidates for this job: genes encoding metal binding proteins and peptides and genes encoding spontaneous and enzymatic antioxidants, besides general stress genes, such as HSPS (Weber 2005). In fact, these genes and enzymes are up-regulated or have significantly increased in activity, as recently has been documented by Chiang et al. (2006). To better understand the hyperaccumulating mechanism, the authors used an Arabidopsis cDNA microarray to compare the gene expression of A. halleri and A. thaliana. By analyzing the expression of metal-chelators and antioxidation-related genes, Chiang et al. (2006) found that MT 2b and MT 3, APX, and MDAR4 in the ascorbate-glutathione pathway were expressed at higher levels in A. halleri than in A. thaliana. The authors further validated that the enzymatic activity of APX and class III peroxidases (POX) were highly elevated in A. halleri. Therefore, the authors monitored H2O2 accumulation in the two species exposed to Cd and paraquat in vivo. Both treatments caused significant H2O2 accumulation in A. thaliana but not in A. halleri (Fig.  6.10). The endogenous H2O2 accumulation in A. halleri was much lower than that in A. thaliana, even in the control experiment. These data suggest that antioxidation activity contributed in part by the high activity of APX and POX can function efficiently in H2O2 removal. As yet, there are some indications that GSH is involved in defense from oxidative stress. The cytosolic antioxidant capacity appears to be sufficient to maintain cell viability even in the absence of catalase, and that under such conditions, a strong increase in the level of reduced GSH can be measured. Also, exposure of maize

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Fig. 6.10  Differential antioxidant capacities in Arabidopsis halleri and A. thaliana. Three-week-old A. thaliana (At) and 8-week-old A. halleri (Ah) plants treated with water (ddH2O; control) or oxidative-stress inducers (50 mM Cd for 3 h, 100 mM Cd for 24 h or 1 mM paraquat for 24 h) were stained with a specific H2O2 staining agent. The oxidative stress is indicated by a brown color of the leaves (From Chiang et al. 2006. With permission from the American Chemical Society)

seedlings, tomato, parsley, and tobacco cell cultures to heavy metals accelerated GSH synthesis, clearly indicating the importance of GSH in protecting plants against various forms of stress (Memon and Schröder 2009). This assumption gets support by the study of Semane et al. (2007) who investigated the effect of Cd on leaves of 3-week-old A. thaliana with a particular interest on GSH production and consumption and on antioxidative defense. Cd induced a significant increase in the mRNA level of genes involved in GSH synthesis (GSH1 and GSH2) and phytochelatin synthase (PCS1). In the Cd-treated plants, a significant decrease of reduced GSH occurred combined with an increase of PC. Cd treatment increased the accumulation of glutathione disulfide (GSSG), the oxidized form of GSH. The accumulation of GSSG was accompanied by a decrease of the glutathione reductase (GR) transcript level, while the activities of GR and nicotinamide nucleotide phosphatereducing enzymes were significantly enhanced. A general increase of ROS scavenging enzymes such as APX, CAT, or SOD was observed, indicating that the ascorbate–GSH cycle had been switched on (see Chap. 2). Obviously, the plants respond to Cd stress particularly by the ascorbate–GSH defense network at both the transcriptional and enzymatic levels. Taken together, Arabidopsis plants exposed to low Cd concentrations (1 mM Cd) were able to adopt a new metabolic equilibrium, allowing them to cope with this metal. However, when exposed to elevated concentrations (10 mM Cd), loss of cellular redox homeostasis resulted in oxidative stress and toxicity. In sum, hyperaccumulators show an increased expression in key genes involved in production of ligands for metals, including sulfur compounds and general antistress enzymes and proteins. Yet, Verbruggen et al. (2009a) conclude their review on the mechanisms of hyperaccumulation with a rather critical outlook: The complexity

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of hyperaccumulation is far from being understood not only at the tissue level but also at the subcellular level. Metal transport has been studied mainly at the plasma membrane or at the tonoplast. It is expected, however, that general metal homeostasis, including processes at all other endomembranes, will be modified in hyperaccumulators. Furthermore, transport mechanisms are still poorly understood for most of the metal transporters. The form of the metal that is handled by transporters is also a matter of debate, and the possible role of metal-chaperones so far has only been demonstrated for Cu. In general, there is a lack of studies at the protein level (in particular of membrane proteins) in hyperaccumulators. In the absence of protein data or functional studies, the biological significance of changes at the transcript level remains to be established (see Chap. 9). The aforementioned mechanisms and how completely they may be discovered to date look likely to be the short-term response, similar in concept to a stress response with the purpose of limiting the immediate toxic effects of metals (Maestri et al. 2010). Yet, what about the long-term response of metal sequestering? What are the eco-physiological consequences? Do all hyperaccumulating plants have the same strategy? Only very few papers cover these aspects.

6.5.2 Ecological Mode of Action of Metal Defenses Plant protection by metals requires one or several of the following conditions: • the metal is more toxic to the pathogen or herbivore than to the plant • the metal hampers the virulence of the pathogen or herbivore • the metal increases the resistance of the plant to the biotic stress factor As Poschenrieder et al. (2006) summarized, five different modes of action have been proposed. 6.5.2.1 Phytosanitary Effects A high level of metal ion activity in the soil or on the plant surface kills or inhibits the growth and development of the pathogen or herbivore. A well-known example is the fungistatic effect of copper sulfate. 6.5.2.2 Elemental Defense Hypothesis Metal accumulation within plant tissues can contribute to self-defense against biotic stress. The hypothesis was initially formulated based on an observation that fewer insects feed on Ni hyperaccumulators. Herbivores consuming plant tissues with high concentrations of metal are affected either by the toxicity (i.e. the metal acts like a plant systemic pesticide) or by the evocation of an aversion response.

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6.5.2.3 Trade-Off Hypothesis This hypothesis postulates that increasing tissue concentrations of potentially toxic heavy metals in hyperaccumulator plants allows resources dedicated to organic defenses to be reduced. However, to date, no conclusive quantitative results are available. 6.5.2.4 Metal Therapy Metals might act as a remedy for metabolic defects in the hyperaccumulator plant. This hypothesis about the therapeutic effects of metals is based on the frequent observation that hyperaccumulators, when grown on a substrate with low levels of metal are highly sensitive to biotic stress. The constitutively high concentrations of salicylate found in the hyperaccumulator species of Thlaspi might render these plants insensitive to pathogen-induced signals that are required for defense induction. 6.5.2.5 Metal-Induced Fortification Metal ions can elicit defense reactions and can sometimes confer a rarely complete pathogen resistance in non-hyperaccumulator plants. There are several ways to elicit defense reactions. Non-growth-reducing Cd concentrations can inhibit a systemic virus spread in tobacco. Cadmium-induced resistance against Fusarium infection has been related to metal-induced proteins in wheat. Metal-induced ROS can trigger defense signals and the synthesis of defense-related secondary metabolites.

6.5.3 Cross Talk Between Metal and Biotic Stress Signaling Signal transduction pathways of biotic stress offer multiple points of interaction with metal ion stress signaling. Stress-activated increases in cytoplasmic Ca2+, ROS production, NO, salicylate, thioredoxin, and mitogen-activated protein kinases (MAPKs) are central cross points of interactions between pathogen-elicited responses and more-or-less-specific toxic effects of different metal ions. Jasmonate and ethylene are typically involved in signal induction as a result of cell damage by herbivores and necrotrophic pathogens, but Cd has also been found to induce JA and ethylene (Poschenrieder et al. 2006). Metal ion stress and biotic stress share common signaling molecules, and the ability to maintain high levels of reduced glutathione seems to be a key factor for both metal tolerance and pathogen resistance. However, the modes of signal transduction seem to be highly stress-specific. Receptor specificity, subcellular sites of production of different ROS, specificity and regulation of MAPK activities, and differences in activated genes and their products are responsible for the specificity of responses (i.e., activation of the signaling pathway will not provide broad co-resistance among and between multiple biotic and ion toxicity stresses).

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Fig. 6.11  Metabolic cross-talk. Biotic stress and metal ion toxicity can interact at the metabolic level (From Poschenrieder et al. 2006. With permission from Elsevier)

Moreover, a fundamental difference in the relevance of stress signaling between biotic and ion toxicity stress relies on the effectiveness of the inducible defense responses. In biotic stress resistance, pathogen elicitor-induced ion fluxes and the oxidative burst are essential for triggering the activation of genes responsible for the synthesis of compounds such as phytoalexins that efficiently stop the pathogen which is the origin of the signal. Metal ion-induced ROS activate antioxidant production. This helps to limit ROS-derived injury but does not eliminate the stress factor. Induction of phytochelatin or other potential metal binding substances can lower the metal ion activity. However, in the long-term, this will only be effective if this is accompanied by efficient compartmentation and/or efflux mechanisms (i.e., by more efficient transport systems) (Poschenrieder et al. 2006). The requirement to maintain high levels of reduced glutathione under both biotic and abiotic stress conditions, the implication of sulfur-containing secondary products in biotic stress resistance, and the importance of phytochelatins in metal homeostasis highlights the interactions of metal ion and biotic stress in sulfur metabolism (Fig. 6.11). The shikimate pathway, which links the metabolism of carbohydrates to the biosynthesis of aromatic compounds, is another key route for interactions between both stress types (Fig.  6.11). The shikimate pathway and sulfur metabolism produce compounds with a role in either or both biotic stress defense and metal binding. A high level of reduced glutathione is required for stress resistance in general. Auxin, a shikimate pathway-derived growth regulator, provides a link between stress metabolism and adaptive growth. Auxin-induced enhanced lateral root formation

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allowing root growth into less toxic soil regions and shoot or tiller re-growth after herbivore attack are examples of the importance of adaptive growth under stress conditions. The following chemical compounds provide clues to the response of plants to microorganisms and metal ions: • Essential amino acids, • Phenolics such as SA directly involved in stress signaling, • Catechol, a strong antioxidant relevant in Ni tolerance in the hyperaccumulator Thlaspi goeingense, • Catechin, a high-affinity ligand for metal ions under neutral pH conditions, • Flavonoids exudated into the rhizosphere and acting as plant signals to N2-fixing symbiotic microorganisms or Al resistance, and phytoalexins. Poschenrieder et al. (2006) conclude that the result of the metal–plant–parasite interaction depends on the ability of the interacting organisms to maintain adequate metal homeostasis. Metal protection is only possible if the metal is less toxic to the plant than to the parasite, i.e., the plant is more resistant to the metal than the pathogen or the herbivore.

6.5.4 Long-Term Strategy of Hyperaccumulators Obviously intrigued by the fascinating perspectives of molecular biology and modern biochemistry, many papers consider only the short-term response. However, in hyperaccumulators, it is likely that long-term responses can be more sustainable and effective: sequestration in plant cell walls should fulfill this role. This strategy is also much more cost-effective than the permanent synthesis of peptides and proteins. Maestri et al. (2010) reviewed the mechanisms for metal sequestration and chelation and state that plant cell walls constitute a vast extension of material which can bind and effectively sequester metal ions. Several genes involved in root lignin biosynthesis, few others implicated in suberin biosynthesis, and some involved in wax synthesis were identified as overexpressed in N. caerulescens compared to A. thaliana when exposed to Zn (van de Mortel et al. 2006, 2008). This finding correlated with the increased lignification of the endodermal cell layer and the observation of two endodermal cell layers in roots of N. caerulescens. A more strongly developed endoderm in the hyperaccumulator could function to minimize the remobilization of metals accumulated in the stele during the trans-root processes resulting in metal loading into the xylem. The genes found differently expressed in A. thaliana in respect to N. caerulescens under Zn or Zn/Cd treatments have been at times related to lignification processes even if in some cases they are either involved in wax synthesis or in general phenylpropanoids metabolism: flavonoid, flavones, anthocyans, and other pigments. The genes, univocally responsible for lignification which have been found active during metal response in N. caerulescens, can be summarized as genes coding for members of the • 4-coumarate-CoA ligase family, 4CLL (At1g20490, At1g20500, At5g38120) • caffeoyl-CoA 3-O-methyltransferase family, CCOMTL (only At1g67980) • cinnamyl-alcohol dehydrogenase family, CAD (only At1g72680).

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Maestri et al. (2010) concluded that higher focus on genes and enzymes involved in plant cell wall synthesis and maintenance should be necessary. In particular, cellulose and other polysaccharides have received comparatively less attention than lignin, but it is to be expected that their role could be as important, at least due to their ability to form stable bonds with metals because of their highly ordered structure.

6.5.5 Costs of Metal Resistance and Adaptation Organisms exposed to chemical stressors must mobilize defensive and repair ­processes if they want to survive. These processes are energy demanding and can be considered in terms of energy and resource allocation; this means, it is likely to have negative fitness consequences. This can increase survival in stressful condition, such as excessive metals in the soil, but at the same time leaves less energy for reproduction, growth, defense against pathogens, parasites or predators, and other processes. For instance, in the least killifish, Heterandria formosa, Xie and Klerks (2004) reported the fitness costs and trade-offs associated with the evolution of Cd-resistance: smaller-sized offspring, decreased fecundity, smaller brood size, longer time to first reproduction (primipara), and shorter female life expectance than in the control populations. In field populations of stressed wolf spiders, Pirata piraticus, the clutch masses were reduced (Hendrickx et al. 2003). In a meta-analysis, Audet and Charest (2007) showed that plant growth was negatively correlated with heavy metal concentrations. These relationships were found for the majority of heavy metals tested (e.g., Zn, Cd, Pb, Cu, Cr, and Fe) with a few exceptions (e.g., Ni, Co, and Mn). Plants adjust their relative biomass allocation and distribution to roots or shoots when subjected to environmental stress conditions, particularly nutrient deficiency, a phenomenon referred as allocation plasticity. In this regard, plants can be categorized in their stress-tolerance strategy as either “slow-growers” or “fast-growers” relating to growth rate and heavy metal uptake (Grime 1979). Audet and Charest (2008) investigated the current model of allocation plasticity in the context of heavy metal phytoremediation with four families of interest (Brassicaceae, Fabaceae, Poaceae, and Solanaceae) implying soil metal conditions ranging from low (trace) to high (toxic) levels. The “fast-growers” show a shift of biomass partitioning whereby their relative biomass allocation to roots is high under low, then decreasing at intermediate, and again increasing at high heavy metal levels according to a parabolic pattern (Fig. 6.12). Likewise, the “slow-growers” follow a similar tendency although much less dramatically. As for plant-metal partitioning, both grower types show increasingly greater plant-metal partitioning to roots relative to shoots as plant-metal or soil-metal levels increase. Overall, the “fast-growers” show a high degree of allocation plasticity in regards to biomass plasticity, whereas the “slow-growers” show a high degree of metabolic plasticity in regards to metal partitioning. Plants expressing a high level of allocation plasticity may shift their biomass allocation from shoots to roots to circumvent the challenges of increasing soil-metal conditions, notably metal toxicity and edaphic changes

Metal level

Metal partition, root/shoot

Fig. 6.12  Conceptual model of allocation plasticity and plant-metal partitioning for “fastgrower” (solid line) and “slow-grower” (dotted line) plant types. Designated are three growth zones representing low, intermediate, and high plant-metal or soil-metal levels (From Audet and Charest 2008. With permission from Elsevier)

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resulting in soil-nutrient imbalances. This relative shift in biomass is likely due to increasing requirements for nutrients or other limiting resources. As soil-metal levels reach potentially toxic levels, the rhizosphere may buffer the proximal soil-environment through the exudation of mucilage consisting of organic acids (e.g., polyuronic acids) involved in the regulation of soil-pH, soil-metal redox potential, and the mobilization of limiting mineral nutrients. While root exudation has a general function of protecting the root apical zones from desiccation, facilitating ion uptake, and improving soil-root contact and aggregation, it also contributes in developing microbial community profiles (review by Audet and Charest 2008). In this regard, the rhizospheric microbial community significantly affects soilnutrient composition by immobilizing heavy metals via bacterial and fungal “metalbinding” then decreasing soil-metal bioavailability and plant-metal uptake (Audet and Charest 2007). This rhizospheric effect is thought to buffer the soil-environment and reduce heavy metal phytotoxicity in a stress-avoidance strategy. Although the overall trend of shifting biomass could represent a broad stress-tolerance strategy, the patterns of allocation plasticity Audet and Charest (2008) observed among the four families tested were not all the same. Between Fabaceae and Poaceae, their

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findings show a significant and pronounced shift in root to shoot biomass partitioning as either the plant-metal or soil-metal levels increased, then displaying a high level of allocation plasticity. By contrast, the Brassicaceae show no specific pattern of biomass partitioning nor any significant level of allocation plasticity. Hence, the authors attribute these different patterns of biomass allocation among these families to their specific growth strategies relating to their status as “slow-grower” or “fastgrower” types. Moreover, the relationships tested among the Solanaceae show, in general, a low data resolution as a result of the small sample size and narrow plantmetal or soil-metal distribution. Consequently, the findings pertaining to the Solanaceae cannot be considered representative of any biological trend until more data are available. Audet and Charest (2008) determined that the Brassicaceae mostly express “slowgrower” characteristics thus enabling them to tolerate potentially toxic HM conditions and then partly contributing to their status as hyperaccumulators (e.g., Noccaea and Brassica spp.). The authors have determined that the Fabaceae and Poaceae mostly express “fast-grower” characteristics thus enabling their rapid growth and adaptation in contaminated environments (e.g., Trifolium and Lolium spp.). Another aspect of “slow” or “fast” growth strategy in relation to metal stress concerns the investment in symbiotic associations. One such example relates to the arbuscular mycorrhizal fungi and their dynamic roles in enhancing the stress tolerance of numerous herbaceous plant species (Audet and Charest 2007), in which they: 1. Increase heavy metal uptake via the extensive mycorrhizospheric network at low soil-metal concentrations; and 2. Reduce heavy metal bioavailability by metal-binding processes at high soil-metal levels, then increasing plant biomass and tolerance through a metal stressavoidance. Notably, this dynamic mycorrhizal effect at high soil-metal levels has been shown to decrease plant-heavy metal uptake and subsequently reduce cellular oxidative stress (Schützendübel and Polle 2002). The typically mycotrophic plant families (Fabaceae, Poaceae, and Solanaceae) evaluated in this study may invest more in mycorrhizal stress-avoidance as an extrinsic tolerance strategy (Audet and Charest 2006). On the other hand, the typically non-mycotrophic families, such as the Brassicaceae, must rely more on intrinsic plant stress tolerance mechanisms, for example phytochelatin production or heavy metal sequestration (Cobbett and Goldsbrough 2002). Consequently, it is most likely that a dynamic compromise between biomass allocation and metal partitioning influences overall plant growth strategy and investment toward “intrinsic” or “extrinsic” stress tolerance mechanisms. This meta-analysis raised some interesting hypotheses, yet there are still several questions open: Do the relationships hold true for other plant families (e.g., Cannabaceae, Lamiaceae, Pteridaceae, etc.)? For instance, do similar relationships exist among aquatic or wetland families having different physiological adaptations to their ecosystems? Considering the particular physical characteristics of these environments, do the families respond differently to pollution exposure? How do their respective growth strategies enable them to circumvent such challenges? By integrating these

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aspects, Audet and Charest (2008) assume that the development of a more complete picture of plant and ecosystem function and plant adaptations to environmental stress conditions should be feasible. Maestri et  al. (2010) continue their stimulating stress-ecological review by assuming that the emergence of specialized allocation patterns associated with resistance/tolerance behavior leads necessarily to the development of a trade-off between maintenance and reproduction, and subsequently to a trade-off between resistance/tolerance and fitness. Cellular mechanisms devoted to sequestration of metals in organelles or organs and to protection of cell structures through ligands concur with this trade-off (Pierce et al. 2005). In productive habitats, these tolerant/ resistant organisms, which exhibit adaptive morphological changes (stress-tolerators or ruderals, sensu Grime 1979), are overgrown by competitors. In the presence of high soil concentrations of metals, a more conservative use of resources permits survival and a competitive advantage notwithstanding the constant stress (Kazakou et  al. 2008). However, the foregoing speculations do not completely explain the hyperaccumulator phenotype, which is associated with a trait of resistance/tolerance, even though genetically independent, but at the same time does not fit with the idea of trade-off based only on resources allocation. In fact, the general natural mechanism underlying the hyperaccumulator phenotype fits more with the idea of resource conservation rather than allocation. Many hyperaccumulator species have a decreased growth rate, limited energy expenditure, and decreased metabolic rate. These plants could be at a disadvantage when resources are abundant but find themselves at ease in disturbed habitats because, for example, the high concentration of metals in their organs deters animals from grazing on them (Pollard and Baker 1997; Jiang et al. 2005). A recent meta-analysis of the literature showed that herbivores vary in their preference for or aversion to high metal concentration in plant tissues; therefore, the advantage conferred by hyperaccumulation would depend on the type of herbivores feeding on the particular plant species (Vesk and Reichman 2009). On the other hand, some insects feed on hyperaccumulating plants and accumulate metal in their tissues; in turn, they may exploit this as a defense against predators (Boyd 2007, 2009). This contradiction helps to explain why many hyperaccumulators grow in complex assemblages of plant species that include both hyperaccumulators and nonhyperaccumulating competitors. Spatial environmental variability may explain the apparent juxtaposition of both strategies alongside each other. Metal allelopathy may be an additional aspect of hyperaccumulation behavior; hyperaccumulators cause a local increase in metal soil concentration (phyto-enrichment, through leaf fall), thereby decreasing the fitness of neighboring non-tolerant species (Freeman et al. 2006; Morris et al. 2009). Ruderal species tend to be representative of disturbed environments. They are short-lived, fast-growing, and rapidly go to seed when confronted with environmental stress. Stress-tolerators grow slowly and delay reproduction in unfavorable conditions. Neither strategy appears to explain or typify all metal hyperaccumulator plants. In fact, it has been shown that for some hyperaccumulators the presence of the metal at high concentration in the soil is essential for a normal growth

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(Küpper et al. 2001). When analyzing the existence of trade-offs between traits and ­environments, it has to be considered that physiological performance needs to be associated with fitness but under a range of natural conditions. Resistance/ tolerance represents the physiological performance in a small range: the presence of the metal. The hyperaccumulator phenotypes could represent the physiological response on a broader range. The extension of the trade-off to animals feeding or to other environmental cues can be an example of this “extended” fitness. Are hyperaccumulator plants more or less “specialized” than the tolerant/resistant plants? It appears that the hyperaccumulators share common mechanisms with tolerant plants but show peculiar mechanisms as well which make them more generalist examples of trade-off between trait and environment. This could result in phenotypic plasticity half way between the specialized tolerant and the generalist non-tolerant species (Maestri et al. 2010).

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Chapter 7

The Potential of Stress Response: Ecological Transcriptomics

How do organisms cope with complex environmental stressors? How do they respond to environmental challenges? Transcription is the initial step in gene expression, thus a transcriptional response gives the first indication of cellular mechanisms that are affected by a stressor. As a consequence, it can provide a sensitive starting point to assess ecological stress responses assuming all ecologically relevant effects are indeed accompanied by alterations in gene expression profiles. Ecological transcriptomics is a powerful tool that unravels mechanistic processes, reveals novel modes of action and regulation pathways, and provides the opportunity to get a dynamic picture of biological systems and the ability to comprehensively dissect different states of biological activities in cells, tissues, or whole organisms. Yet, molecular-biological data should be construed with great accurateness, since they may easily be over- or even misinterpreted which is well understood (Menzel et al. 2009a) and should be combined with further “omics” techniques such as proteomics or metabolomics. Having this alert in mind, this chapter pinpoints the merits of the merging molecular biological techniques with ecology (Table 7.1), such as identification of potential new biomarkers or even pathways of acute and chronic stress (Prunet et al. 2008). A receptor (or sensor) detects the presence of the effector (e.g., a hormone, a metal, or a damaged protein) and becomes activated (Fig. 7.1). This activation often results in binding the receptor to specific DNA sequences in the cell nucleus and promotes transcription of target genes placed in the proximity of these control sequences. The product of this process, called messenger RNA (mRNA), becomes edited and exported to the cell cytoplasm where its information is translated to synthesize the corresponding protein molecules which constitute the molecular basis of the biological response to the presence of the effector. There are multiple modulations and variations of this theme, but as a general rule, the amount of protein reflects the relative concentration of the corresponding mRNA, whose transcription rate ultimately depends on the activation of the receptor, determined by the presence and the effective concentration of the effector (Piña et al. 2007). Subsequent chapters will show that the entire regulatory power of stress response does not lie in genes; instead, it becomes increasingly clear that the C.E.W. Steinberg, Stress Ecology: Environmental Stress as Ecological Driving Force and Key Player in Evolution, DOI 10.1007/978-94-007-2072-5_7, © Springer Science+Business Media B.V. 2012

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Table 7.1  Ecologically relevant transcriptome studies Environmental stressor Key references Abiotic stressors on Review by Timperio et al. (2008) plants Review by Prunet et al. (2008) Diverse abiotic and biotic stressors on fishes Climate change Reviewed by Ahuja et al. (2010) Heat Gasch et al. (2000), Petersohn et al. (2001), Sørensen et al. (2005, 2007), Weber et al. (2005), Kassahn et al. (2007), Reusch et al. (2008), Bahrndorff et al. (2009b), Farcy et al. (2009), Lu et al. (2009), De Boer et al. (2010), and Vergauwen et al. (2010) Cold Vogel et al. (2005), Weber et al. (2005), Beck et al. (2007), Kassahn et al. (2007), Kilian et al. (2007), Sinclair et al. (2007), Sørensen et al. (2007), Bahrndorff et al. (2009a), Mathiason et al. (2009), and Vergauwen et al. (2010) Drought McKay et al. (2003), Beck et al. (2007), Kilian et al. (2007), André et al. (2009), and Caramelo and Iusem (2009) Desiccation Sinclair et al. (2007), Sørensen et al. (2007), Denekamp et al. (2009); review by Moore et al. (2009), Timmermans et al. (2009), Mali et al. (2010), and Reuner et al. (2010) Acidification Weber et al. (2005) and De Boer et al. (2010) Irradiation, incl. UV Qiu et al. (2005), Kilian et al. (2007), and Behrendt et al. (2010) Ozone Olbrich et al. (2009) Heavy metals Bundy et al. (2008), Nota et al. (2008); reviewed by Steinberg et al. (2008a), Svendsen et al. (2008), and Andre et al. (2010) Menzel et al. (2005a), Fu and Xie (2006), Skopec et al. (2007), Wei Natural xenobiotics, et al. (2008a, b), Magnanou et al. (2009), Schwarzenberger et al. incl. food (2009), and Trevisan et al. (2010) allelochemicals Synthetic xenobiotics, Pedra et al. (2004), Menzel et al. (2005b), Gong et al. (2007), Voelker incl. pesticides et al. (2007), Owen et al. (2008); reviewed by Steinberg et al. (2008a), Svendsen et al. (2008), Garcia-Reyero et al. (2009), Nota et al. (2009), Olsvik et al. (2009), Pereira et al. (2010), Viñuela et al. (2010), and Weisman et al. (2010) Complex exposure, Wang et al. (2008), Menzel et al. (2009b), and Vandenbrouck et al. mixtures (2010) Hypoxia Branco-Price et al. (2005), Gonzali et al. (2005); review by Nikinmaa and Rees (2005), Kassahn et al. (2007), Marques et al. (2008), Boswell et al. (2009); review by Zhang et al. (2009), and Blokhina and Fagerstedt (2010) Salinity Petersohn et al. (2001), Weber et al. (2005), Kassahn et al. (2007), Paul et al. (2008), and Yang et al. (2010) Starvation Petersohn et al. (2001), Weber et al. (2005), and Sinclair et al. (2007) Nutrients, food Gasch et al. (2000), Zinke et al. (2002), Castelein et al. (2008); review by Panserat and Kaushik (2010), and Steinberg et al. (2010a) Nutrient-limited growth Buckhout et al. (2009) and Lu et al. (2009) Pathogens, parasites Marathe et al. (2004), Miranda et al. (2007), Albrecht and Bowman (2008), Ascencio-Ibáñez et al. (2008), Wang et al. (2008), Green et al. (2009), and Seidl et al. (2009) Predation Schwarzenberger et al. (2009) and Miyakawa et al. (2010) Osmotic stress Gasch et al. (2000) Behavior, social stress Toma et al. (2002), Sneddon et al. (2005), Aubin-Hort et al. (2007), Cummings et al. (2008), Adhikari et al. (2009), and St-Cyr and Aubin-Hort (2009) Oxidative stress Gasch et al. (2000), Girardot et al. (2004), Landis et al. (2004), and Maaty et al. (2009)

Fig. 7.1  Scheme of primary response to effectors (endogenous or exogenous). The information regarding the interaction between the receptor and a specific pollutant is transferred through the whole mechanism. This interaction can be monitored at the mRNA level or at the protein level (Piña et al. 2007. With permission from Elsevier)

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Box 7.1  The TATA Box The TATA box is a DNA sequence (cis-regulatory element) found in the promoter region of genes in archaea and eukaryotes with a core sequence 5¢-TATAAA-3¢, which is usually followed by three or more adenine bases. TATA-containing genes are enriched in stress-related genes, and they are extensively regulated compared to TATA-less genes. It is suggested that TATA boxes are associated with promoters of genes that require rapid and variable regulation. Conversely, TATA-less genes are enriched among “housekeeping” or growth related genes (López-Maury et al. 2008). Moreover, the intrinsic variability TATA-containing genes enables rapid individual cell responses which results in a “burst” of gene expression that confers a clear benefit when organisms are facing acute environmental stress. In other words, the TATA box increases the plasticity of gene regulation (Roelofs et al. 2010). Since stress response genes are enriched in TATA containing genes, it might be expected that TATA boxes show rapid regulatory evolution specifically when abiotic stress is the selective force. This hypothesis was tested by Tirosh et al. (2006) in a systems biology context. The study provided clear evidence that long-term adaptive evolution of stress tolerance among yeast species is correlated with short term regulatory changes to environmental stress. The study also showed that stress response genes with TATA box show exceptional rapid regulatory evolution in yeast, C. elegans, fruit fly, plants, and mammals (Tirosh et al. 2006). Furthermore, experimental mutation accumulation studies show a significant correlation between transcriptional plasticity and mutation variance in TATA box containing stress response genes (Landry et al. 2007). Taken together, these data highlight the importance of the TATA box containing stress response genes in both short- and long-term regulatory adaptation (Roelofs et al. 2010).

regulation of the gene activity as well as post-transcriptional and post-translational modifications appear almost as significant as the transcriptional pathway itself. Overall, key studies of challenged organisms of all kingdoms will demonstrate the power of transcriptomics.

7.1 Archaea Archaea have adapted to some of the most extreme environments known to support life, including highly oxidizing conditions. In a transcriptome and proteome study, Maaty et al. (2009) induced an oxidative stress in Sulfolobus solfataricus. Microarray analysis of mRNA expression showed that 102 transcripts were significantly regulated 30 min after exposure to H2O2. A recently characterized ferritin-like antioxidant

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protein, DPSL1, was the most highly regulated species of mRNA and protein in addition to being post-translationally modified. As expected, a number of antioxidant related mRNAs and proteins were differentially regulated. Three of these (DPSL, SOD, and peroxiredoxin) were shown to interact and likely form a novel supramolecular complex for mitigating oxidative damage. Despite the central role played by DPSL, cells maintained a lower level of protection after disruption of the DPSL gene, indicating a level of redundancy in the oxidative stress pathways of S. solfataricus. Maaty et al. (2009) showed that a portion of the cellular DPSL protein pool is present in a complex likely to include SOD and peroxiredoxin. Furthermore, the comparison of the oxidative stress response of an archeal organism with bacteria and eukaryotes reveals evolutionarily conserved pathways where complex and overlapping defense mechanisms protect against oxygen toxicity.

7.2 Bacteria Stressors such as heat, salt, ethanol, or acid stress, as well as glucose, oxygen, or phosphate starvation induce a large group of stress proteins which is mediated by the general stores sigma factor (sB) of gram-positive bacteria but is missing in strictly anaerobic or in some facultatively anaerobic gram-positive bacteria. For example, one of the strongest and most noticeable responses of Bacillus subtilis cells to a range of stress and starvation stimuli is the dramatic induction of about 150 sB-dependent general stress genes (Hecker et al. 2007). The activity of sB itself is tightly regulated by a complex signal transduction cascade with at least three main signaling pathways that respond to environmental stress, energy depletion, or low temperature. In Escherichia coli, the stress response is mediated through the general stress sigma factor sS. While nearly absent in rapidly growing cells, sS is strongly induced during entry into stationary phase and/or many other stress conditions and is essential for the expression of multiple-stress resistances. Genome-wide expression profiling data indicate that up to 10% of E. coli genes are under direct or indirect control of sS (Hengge-Aronis 2002). Weber et  al. (2005) identified a total of 481 sS-dependent genes, of which only 140 were found under all three growth and stress conditions (Fig. 7.2). The other 341 genes revealed their sS dependence under only one or two of the growth and stress conditions used (with genes in all possible combinatorial groups). The functional annotations showed that besides genes with known functions in stress management, nearly all sS-controlled core genes with known or probable functions fall into three groups: metabolic enzymes, transport proteins and/or intrinsic membrane proteins of unclear function (likely transporters), or regulatory proteins. Upon closer inspection of the metabolic genes, an interesting pattern became apparent. A number of genes involved in central energy metabolism (glycolysis,

DPS-Like proteins (DPSL) are a distinct subclass of di-iron carboxylate proteins widely distributed in phylogenetically diverse prokaryotes. 1 

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Fig. 7.2  Numbers of sS-controlled genes identified under different growth and stress conditions in Escherichia coli as shown in a Venn diagram (From Weber et al. 2005. Courtesy of the American Society for Microbiology)

fermentation, anaerobic respiration, and the pentose phosphate shunt) exhibited positive sS control at least under one condition tested (Weber et  al. 2005). This paper indicates that induction of sS in starving or otherwise stressed cells contribute to decreasing aerobic respiration in favor of a more fermentative and/or anaerobic respiration-based energy metabolism. Two illustrative examples are considered in depth which also supports the general stress response: Escherichia coli exposed to seawater, and Shewanella oneidensis exposed to different irradiation qualities.

7.2.1 Escherichia coli Any enteric bacterium is challenged by a combination of hostile conditions threatening their viability, such as pH, salinity, irradiation, or oxidative stress. They can survive even in seawater for extended periods (Rozen et  al. 2002). Microarray experiments conducted on E. coli exposed to seawater demonstrated that the expression of the majority of genes remained unchanged, with less than 10% of the genes down-regulated and 25% up-regulated. Gene ontology analysis identified that (1) cell division and the synthesis of nucleic acid components had stopped; (2) carbon and energy metabolism was modulated; (3) systems needed for energy supply were induced, including both aerobic and anaerobic respiration; and (4) cells were geared towards rapid movement (whether in a chemotactic search for nutrition or in flight from the inhospitable conditions imposed upon them).

7.2.2 Shewanella oneidensis This gram-negative anaerobic bacterium inhabits deep-sea, anaerobic soil, or sedentary habitats. Hence, it appears to be sensitive to natural solar irradiation (NSR) as shown by Qiu et al. (2005), who also evaluated UV-A and UV-B alone. The modulated genes were classified as “energy metabolism”, “protein synthesis”,

7.3  Plants Fig. 7.3  Venn diagram of up-regulated genes (a) and down-regulated genes (b) in the tested Shewanella oneidensis strain in response to natural solar irradiation (NSR), UV-A, and UV-B (From Qiu et al. 2005. Courtesy of the American Society for Photobiology)

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“cellular process”, “biosynthesis”, and “transport and binding proteins”. The results are summarized in the Venn diagram in Fig. 7.3 and show some common cellular responses to NSR, UV-B, and UV-A. NSR up-regulated 390 genes, of which only 108 genes were also induced by UV-A. Even fewer genes were common in NSR and UV-B treatments. However, the functional distribution of differentially expressed genes in response to NSR was more similar to that of UV-A than UV-B, because the majority of solar UV is in the UV-A wavelength range.

7.3 Plants 7.3.1 General and Specific Responses to Abiotic Stress Several attempts have been conducted to differentiate between general and specific response patterns in plants. Recently, a highly resolved transcriptome study with the model plant Arabidopsis thaliana has shed light on this issue, particularly the milestone paper by Kilian et al. (2007). The features of the early transcript phases of A. thaliana can very likely serve as a template for a great variety of organisms and their stress responses: an initial, general transcriptional stress reaction comprised of a set of core environmental stress response genes which, by adjustment of the energy balance, has a crucial function in various stress responses. Later, a much more specific response counteracts the stress. For example, in a survey of 8,100 genes of A. thaliana, around 2,400 genes were observed as having a common expression in response to salt, osmotic, and cold stress treatments. Obviously, a small common set of signal transduction components was triggered during many stress responses. This comprehensive study revealed further that a very fast transcriptional reaction occurred shortly after the onset of stress treatment which appeared not to be stressspecific and which was induced by the activity of a core of plant environmental stress response genes (Fig. 7.4). The split into stress-specific responses became visible at later

Fig. 7.4  Venn diagrams of up- and down-regulated genes in response to cold, drought, and UV-B light stress in shoots and roots of Arabidopsis thaliana within 24 h (From Kilian et al. 2007. With permission from Wiley). Thirty minutes after the onset of stress, cold and drought stress share 13 up-regulated genes in common, whereas drought and UV-B share 70. All three stressors have only 9 genes in common. Maximum gene expression is reached after 1 h, with 59 genes common to all stressors. Later, the stress response seems to become more stressor-specific with fewer genes commonly up-regulated

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time points. Abiotic stress-modulated alterations in gene expression occurred quickly. The first changes were observed within 30 min. of the application of stress. Immediate changes were detected in roots and shoots independent of whether the whole plant or only the shoot or the roots were exposed, showing an immediate production of a systemic signal by the shoot or root which is transferred to the other organ. The total number of differentially expressed genes and the pattern of how these genes were up- or down-regulated over time differed distinctly between the different stimuli. A very striking example is the different gene expression pattern induced by the continuous application of salt or osmotic stress to Arabidopsis (addition of mannitol). As indicated by a transient expression pattern, the plant was able to cope with the high salt conditions. In contrast, high osmolarity induced a continuous response which dramatically increased with time. This observation implies that the plant clearly differentiates between the ionic and the osmotic contribution of stresses at a global gene expression level. In spite of these differences, there is a set of common genes that are rapidly induced independently of the applied abiotic stress. Around 50% of these common immediately responsive genes represent transcriptional regulators which might encode basic, but non-specific, master regulators generally required for the plant core environmental stress response (Kilian et al. 2007). These early-induced, common genes are not related to those responsible for the core environmental stress response of yeast and fission yeast, suggesting that plants have evolved a distinct early stress response. The very early response of the plant to abiotic stress is rather non-specific. This might point to common initial signaling events. For drought, cold, UV light, and other abiotic stresses, the production of ROS is well understood. Besides Ca2+ changes, the generation of ROS is one crucial event known so far to be common among such divergent stresses and may function in integrating the responses of plants to abiotic and biotic stresses (see Chap. 2). ROS serve as an important initial signal for the immediate abiotic stress reaction which includes the regulation of early master genes common to all stresses. Kilian et al. (2007) found that particularly C2H2-type zinc finger transcriptional regulators were identified in the group of rapidly, strongly, and generally stress-induced genes. One of these zinc fingers has been shown to play a central role in ROS signaling in Arabidopsis (Davletova et al. 2005). These zinc finger proteins most likely act as transcriptional repressors on carbohydrate metabolism and photosynthesis under conditions of abiotic stress. This immediate onset of a metabolic reprogramming may enable the adjustment of energy homeostasis to the stress conditions which is necessary for a successful stress defense (Sakamoto et al. 2004). Overall, these findings suggest that a large proportion of the gene expression response to a specific stress is not adaptive for this stress. This apparent lack of specificity could simply be an indication that a large proportion of the regulated genes are not specific for any given stress but form part of a core stress response. A general, unspecific stress response has the advantage that it can cross protect against multiple environmental conditions, which might frequently occur together and in combination with stresses that the cell cannot sense. It is also possible, however,

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that a portion of the stress response program reflects neutral evolutionary drift or large-scale connectivity and dynamic compensatory adjustment of the transcriptional regulatory network (López-Maury et al. 2008).

7.3.2 Climate Change Ahuja et al. (2010) reviewed the most publicly recognized aspect of climate change: elevated carbon dioxide concentration, e[CO2]. In response to e[CO2], Arabidopsis showed down-regulation of transcripts related to photosynthesis, the Calvin cycle, photorespiration, photosystem (PS) I and II subunits, light harvesting, and electron transport. Conversely, up-regulated transcripts included genes linked to carbon metabolism and utilization, cellulose synthesis enzymes, cell wall proteins, glycolysis, trehalose metabolism, callose biosynthesis, and fructokinase involved in starch/ sucrose degradation. In contrast to Arabidopsis, aspen (Populus tremuloides) long-term exposure to e[CO2] caused up-regulation of photosynthesis genes encoding chloroplast proteins and auxin-binding proteins, while aquaporin plasma membrane intrinsic protein PIPa2 showed down-regulation. In another transcriptomic study in aspen, a CO2-responsive genotype partitioned carbon into pathways associated with active defense and/or response to stress as well as carbohydrate and/or starch biosynthesis and subsequent growth, while a CO2-unresponsive genotype partitions carbon into pathways associated with passive defense (e.g., lignin) and cell wall thickening. However, a proteomic response of rice to e[CO2] showed differential expression of proteins belonging to photosynthesis, carbon metabolism, and energy pathways. Several molecular chaperones and ascorbate peroxidase also responded to e[CO2]. Furthermore, the combination of e[CO2] and iron (Fe) limitation induced morphological, physiological, and molecular responses, enhancing the plant’s capacity to access and utilize Fe from Fe(III)-oxide. All these studies showed regulation of novel genes, proteins, and metabolites emphasizing changes in photosynthesis, carbon metabolism, growth, amino acids, sugars, starch, and other metabolic processes. The current molecular data of plant adaptations to e[CO2] still are rudimentary. 7.3.2.1 UV Irradiation The response of plants to UV-B seems to be more complicated and more specific than that of animals (see below) (Jenkins 2009). Instead of regulation via the general AHR-pathway, plants appear to have a specific receptor and regulation. For instance, A. thaliana possesses the UV RESISTANCE LOCUS8 (UVR8) which is most likely the photoreceptor regulating HY5 expression, a key effector of UV-B responses. Very recently however, Sasaki et al. (2010) found a gene for rice CYP, OsCYP84A, which was classified into CYP84A in the CYP71 clan. Reverse transcription-polymerase chain reaction (RT-PCR) analysis indicated that this gene was

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ubiquitously expressed without any temporal or spatial specificity under normal growth condition, but its expression was inducible and significantly increased by UV-B and UV-C irradiation. Rice transformants in which OsCYP84A expression was suppressed by the antisense gene showed apparent growth retardation with obvious symptoms of damage on the plant bodies under UV-B irradiation, although no phenotypic alteration occurred under normal growth conditions (white light). These results suggest the existence of a novel UV-tolerance system involving OsCYP84A. 7.3.2.2 Multiple Stressors of Climate Change Ahuja et al. (2010) also reviewed the studies investigating plant responses to environmental stresses applied in combination, since, for instance, heat stress is often accompanied by water deficiency and drought by salinity. The outcome of their comprehensive investigations on multiple stresses highlights the functional roles of GRP7 (encoding glycine-rich protein 7) in environmental stress responses and the involvement of HOS3 (which encodes an elongase-like protein) in abiotic stress signaling through the very long chain fatty acids pathway and confers multiple-stress tolerance via TaSnRK2.4 (Triticum aestivum serine/threonine protein kinase). Furthermore, it becomes obvious that WRKY-type transcription factors in abiotic stresses are of particular relevance. Moreover, barley HvCBF4 (Hordeum vulgare C-repeat binding factor 4), a gene which is induced and over-expressed by lowtemperature stress in rice, also resulted in tolerance to other abiotic stresses. Furthermore, the characterization of transcription factors (OsABF1 from rice and WLIP19) from wheat emphasizes their significance in general abiotic stress responses. A synoptic presentation of the multiple-stress responsive genes is given in Fig. 7.5.

7.3.3 Towards a Regulon The products of stress-inducible genes identified in vast microarray experiments can be classified into two groups: (1) proteins functioning in direct abiotic tolerance [e.g. late embryogenesis abundant (LEA) proteins], and (2) regulators for intracellular signaling and stress-inducible gene expression (e.g., protein kinases such as MAP kinases, phosphatases, phospholipid metabolic enzymes, and various types of transcription factors). The identification of stress-inducible signal transducers gave rise to the idea that plants have developed flexible cellular response mechanisms to efficiently respond to various abiotic stresses (Hirayama and Shinozaki 2010). Outcomes indicate that further levels of regulation based on post-transcriptional and post-translational mechanisms are involved in the abiotic stress response. Posttranscriptional and post-translational processes are key mechanisms to finely modulate the amount and activity of pre-existing transcripts and proteins with an ultimate effect on proteome and metabolome complexity (Mazzucotelli et al. 2008).

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Fig. 7.5  Recent research continues to identify gene responses induced by more than one environmental stress. Such genes or gene networks provide potentially valuable starting points to develop broader crop protection strategies (From Ahuja et al. 2010. With permission from Elsevier). Abbreviations of multiple-stress responsive gene: AP37, 59 = APETELA 37, 59: transcription factors; CcHyPRP Cajanus cajan hybrid-proline-rich protein; DREB2A Dehydration-responsive element binding protein 2; DSM1 Mitogen-activated protein kinase kinase kinase; GmWRKY13, GmWRKY21, GmWRKY54 WRKY-type transcription factor genes; GRP7 Glycine-rich protein 7; HOS3 Hyper-osmotically sensitive gene; HvCBF4 Hordeum vulgare C-repeat binding factor 4; LEW1 Leaf Wilting 1; OsABF1 O. sativa ABA responsive element binding factor 1; P. furiosus SOR Pyrococcus furiosus superoxide reductase; PUB22, 23 Plant U-Boxes 22 and 23 containing E3 ubiquitin ligases; TaSnRK2.4 Triticum aestivum serine/threonine protein kinase; TsVP Thellungiella halophila V-H+-PPase; WLIP19 wheat low-temperature induced protein 19

Recent findings have suggested new layers of regulation and complexity. Posttranscriptional mechanisms based on alternative splicing and RNA processing as well as RNA silencing define the actual transcriptome supporting the stress response. Various steps of RNA processing affect quantitatively and qualitatively the mRNA population. Alternative splicing, which concerns up to two thirds of the genes, has important consequences on the availability of different kinds of transcripts and ultimately of proteins. RNA-mediated silencing is also emerging as an alternative mechanism to control the amount of specific transcripts by their degradation (Mazzucotelli et  al. 2008). Furthermore, the recently discovered microRNAs (miRNAs) and endogenous small interfering RNAs (siRNAs) are emerging as important players in the regulatory network of the plant stress responses (Sunkar 2010).

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Abiotic stress Sensors Signal ROS, Ca2+, etc transducers Plant hormones Feedback (positive, negative)

postranslational modifications • phosphorylation • ubiquitination • SUMOylation

TFs

Genes epigenetic regulation • histone modification • DNA methylation Signal transducers

Transcription cascades postranscriptional modifications • small RNA • alternative splicing • mRNA turnover TFs

Genes TFs Functional proteins (molecular chaperons, LEA proteins, metabolic enzymes, etc)

Stress Response & Tolerance Fig. 7.6  Overall model of an abiotic stress response in plants (Redrawn from Hirayama and Shinozaki 2010. With permission from Wiley)

These small non-coding RNAs post-transcriptionally silence target genes either by guiding degradation or by repressing translation of target mRNAs. Cold, dehydration, salt stress, and nutrient starvation up-regulate and down-regulate the expression of different plant miRNAs whose targets are supposed to be negative and positive regulators of stress tolerance, respectively (see Chap. 8). Figure  7.6 sketches the current understanding of abiotic stress responses in conjunction with the contribution of Arabidopsis genome information. Cells receive stress signals through various sensors (not yet known), and the signals are transduced by various signaling pathways in which many second messengers, phytohormones, signal transducers, and transcriptional regulators function. Stress-inducible genes are regulated by multiple stress signals, and some of them are regulated by transcription factors (TFs) that are induced by stress stimuli, e.g., a transcriptional cascade. Some stress-inducible genes encode functional proteins that are directly involved in stress tolerance. Other stress-inducible genes encode regulatory proteins, such as signal transducers, that presumably form positive and negative feedback loops to regulate stress responses. The availability of Arabidopsis genome information has made countless contributions in clarifying this system, not only in terms of transcriptional regulation but also in terms of post-transcriptional and post-translational modifications and epigenetic regulation (Hirayama and Shinozaki 2010).

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A methodological solution to the high diversity of stress responses in plants is the creation of a meta-analysis, the establishment of the regulon organization of stress defense. Genes that share a similar expression profile across multiple spatial, temporal, environmental, and genetic conditions are likely to be under common transcriptional regulations. Such sets of co-expressed genes are considered eukaryotic regulons. With Arabidopsis, Mentzen and Wurtele (2008) showed that most regulons correspond to identifiable biological processes and include a combination of genes encoding related developmental, metabolic, and regulatory functions. The procedure shall be exemplified by the regulon with organelle-specific functions: six regulons with over 20 genes represent plastidic functions that are encoded predominantly by nuclear genes (regulons: photosynthesis/chloroplast biogenesis; plastid stress and circadian rhythm; plastid organization and biogenesis; plastid-encoded genes; fatty acid biosynthesis; glucosinolate biosynthesis). The advantage of this meta-analysis is that many genes of unknown molecular function or process can be assigned to a regulon which may facilitate a more detailed future functional assessment.

7.3.4 Plant-Pathogen Interactions The plant innate immune response is mediated by resistance ® genes and involves HR cell death. During resistance responses, the host undergoes net changes in the transcriptome. To understand these changes, Marathe et  al. (2004) generated a whole genome transcript profile for an R-gene-mediated resistance to a cucumber mosaic virus strain in Arabidopsis. The authors identified 444 putative factors belonging to nine different functional classes that show significant transcript regulation during Arabidopsis-virus interaction. Identified functional classes represented in the resistome include kinases and phosphatases, protein degradation machinery/ proteases, transcriptional regulators, and others. The analysis also revealed 80 defense-responsive genes that might participate in R gene-mediated defense against both viral and bacterial pathogens. In addition, chromosome distribution of genes that respond to bacterial and viral pathogens showed that they were located in small gene clusters and transcriptionally co-regulated.

7.3.5 Plant-Herbivore Interactions The plant-herbivore interaction is the most universal of all ecological interactions. The genetics and genomics revolution, preferably in tandem with protein and metabolite profile analysis, allows candidate genes to be pinpointed, and targeted genetics allows their contribution to a quantitative trait to be assessed. Plants make use of a wide variety of constitutive barriers to slow down or avoid being eaten.

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Plant eaters capable of handling this first line of defense often encounter a second barrier, the so-called induced defenses which are only expressed after herbivory. Research has largely focused on the molecular signaling pathways that underlie them and that enable plants to tune their response to different attackers. Two central signaling pathways have been identified: One depends on the phytohormone SA, the other on the hormone JA (Kessler and Baldwin 2002). An attack by biotic agents can lead to drastic rearrangements of gene expression. Attack results in up-regulation of defense-related genes and down-regulation of genes involved in photosynthesis, which provides a mechanistic explanation for the well-known growth–defense trade-off (Snoeren et al. 2007).

7.3.5.1 Plants’ Responses to Herbivory Differ Greatly There is no common template for how plants respond to particular herbivores, yet several commonalities can be identified (Kant and Baldwin 2007). One of the clearest is the herbivore-induced JA-mediated responses that give rise to the accumulation of defense-associated products, such as proteinase inhibitors, alkaloids, terpenes, and glucosinolates. Similarities between the different herbivore-induced responses exist only at the level of early transcriptional changes, since most of the herbivore-induced defense responses diversify downstream of induction and over time. Furthermore, responses of the same plant species to different attacker species can be very different, and induced signal-transduction pathways can influence each other. Therefore, the effects of combinations of species that attack the same plant can have quite surprising effects on the expressed plant phenotype (Snoeren et al. 2007). Generalist vs. Specialist Herbivore Caterpillars feeding on Arabidopsis induced several functional classes of genes, including defense proteins such as a few putative lectins and a cysteine proteinase; phenylpropanoid pathway genes that may be involved in phytoalexins production, radical scavengers or cell wall fortification; oxidative and abiotic stress related genes; and genes involved in relocation of resources. For none of these is it clear how and whether they function in plant defense against insects. Genes with known functions in Arabidopsis defenses, such as those involved in glucosinolate biosynthesis and degradation and genes involved in signaling, were also up-regulated by caterpillars. Only very few genes were down-regulated by caterpillar feeding, and the function of those were unclear (Reymond et al. 2004). The authors compared expression profiles in Arabidopsis plants infested with the generalist herbivore Spodoptera littoralis and the specialist herbivore Pieris rapae; specialists may have found ways to attenuate inducible plant defenses. Interestingly, the authors found hardly any differences in induced gene-expression (Fig. 7.7), indicating the specialist found ways to deal with plant defenses rather than to attenuate plant defenses. Indeed, P. rapae can divert glucosinolate degradation from harmful isothiocyanates

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Fig. 7.7  Comparison of transcript profiles in Arabidopsis induced by a specialist (Spodoptera littoralis) and a generalist herbivore (Pieris rapae). Relative changes in gene expression were measured after 3–5 h challenge. Black dots represent genes that showed no changes in gene expression. Blue dots represent genes that were induced by both insects. Magenta dots represent genes only induced by S. littoralis, and green dots represent genes only induced by P. rapae (from Reymond et  al. 2004. Courtesy of the American Society of Plant Biologists). Only genes homologs to ASPARAGINE SYNTHETASE (At3g47340) and the protein phosphatase gene ABSCISSIC ACID INSENSITIVE1 (At4g26080) were specifically induced by Pieris

to less harmful nitriles, something that S. littoralis likely cannot (Van Poecke 2007). Reymond et al. (2004) identified a list of inducible genes that responded to a specialist and a generalist chewing herbivore and showed the importance of the JA pathway in this response. Directly and indirectly, the JA pathway controls or influences the expression of the majority of genes identified as being insect-activated. In a similar approach, Moran et al. (2002) studied the response of Arabidopsis to aphid feeding. Aphids also induced some of the genes found to be induced by caterpillars. These included oxidative stress related genes, a pathogenesis related protein gene (BGL2/PR2), and signaling related genes. Others, such as the pathogenesis related protein PR1, were induced by aphids but not by caterpillars (Moran et al. 2002; Reymond et al. 2004). Aphid feeding also reduced the expression of some genes, including oxidative stress related genes, phenylpropanoid pathway genes, and signaling genes (Moran et al. 2002). In contrast to these findings, Zheng and Dicke (2008) showed in their review that there are considerable differences in the transcriptomic response of a plant to different attackers as well as responses of different plant cultivars in response to the same herbivore. To understand how plants integrate pathogen- and insect-induced signals into specific defense responses, de Vos et al. (2005) monitored the dynamics of SA, JA, and ethylene (ET) signaling in Arabidopsis after attack by a set of microbial pathogens and herbivorous insects with different modes of attack. Analysis of global gene

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expression profiles demonstrated that the signal signature characteristic of each Arabidopsis-attacker combination was orchestrated into a surprisingly complex set of transcriptional alterations in which, in all cases, stress-related genes were overrepresented. Comparison of the transcript profiles revealed that consistent changes induced by pathogens and insects with very different modes of attack showed considerable overlap. All together, SA, JA, and ET played a primary role in the orchestration of the plant’s defense response, but other regulatory mechanisms, such as pathway crosstalk or additional attacker-induced signals, eventually shaped the highly complex attacker-specific defense response. Zheng and Dicke (2008) continued this line of argument in that even in response to insects with a similar feeding mode, such as aphids (Myzus persicae) and whiteflies (B. tabaci), the transcriptomic changes can be quite different. Plant genotypes can also differ in transcriptional responses to the same herbivore. Two white cabbage (Brassica oleracea var. capitata) cultivars differ considerably in the global gene expression patterns induced by an attack of P. rapae caterpillars. Linking studies at the level of transcriptomic changes with studies on metabolite production and expression of different levels of resistance are underway and will provide new insight into the mechanisms underlying variation in ecological interactions. Volatiles Snoeren et al. (2007) have reviewed a specific plant-herbivore interaction, namely the role of herbivore-induced plant volatiles in community ecology, in terms of gene expression. Insect–plant communities are characterized also by indirect interactions, many of which are mediated by infochemicals. Plants respond to insect herbivory with the production of volatiles that attract the enemies of the herbivores, such as insect predators and parasitoids. Several genes encoding enzymes involved in the biosynthesis of herbivoreinduced plant volatiles that mediate carnivore attraction have been identified – for example, genes in A. thaliana, lima bean, maize, Medicago truncatula, and strawberry. Manipulating the functional expression of these genes affects the interaction of the plants with carnivorous arthropods. For instance, the TPS10 terpene synthase gene of maize encodes an enzyme that mediates the herbivory-induced production of (E)-b-farnesene and (E)-b-bergamotene. Heterologous expression of TPS10 in A. thaliana under the control of a constitutive promoter resulted in the constitutive attraction of the parasitic wasp Cotesia marginiventris (Dicke et al. 2009) indicating the general kairomone property of this volatile chemical. Exposure of a plant to the attack of two species that induce the same signaling pathway can enhance the attraction of carnivores. For instance, double infestation of lima bean and cucumber plants by a spider mite and a leaf-chewing caterpillar, both inducing the JA signal transduction pathway, resulted in a stronger attraction of the specialized predatory mite Phytoseiulus persimilis than single prey–infested plants in both plant species (Dicke et al. 2009).

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Fig. 7.8  Summary of differentially expressed genes from microarray analysis during infection of poplar leaves with the fungus Melampsora medusae: Venn diagram showing the overlap of up- or down-regulated elements between the various time points (DPI = days post inoculation) (From Miranda et  al. 2007. Courtesy of the International Society for Molecular Plant-Microbe Interactions)

7.3.5.2 Pathogens and Parasites To gain detailed insight into the infection process, Miranda et al. (2007) analyzed the temporal patterns of up- and down-regulated transcript abundance in poplar leaves challenged by the fungus Melampsora medusae. A small number of pathogen-defense genes encoding PR-1, chitinases, and other pathogenesis-related proteins were consistently up-regulated throughout the experimental period, but most genes were affected only at individual time points. The largest number of changes in gene expression were observed late in the infection at 6–9 days post-inoculation (dpi) (Fig. 7.8). At these time points, genes encoding enzymes required for proanthocyanidin (condensed tannin) synthesis were up-regulated dramatically. Strongly M. medusae–repressed genes at 9 dpi included previously characterized wound- and herbivore-induced defense genes which showed antagonism between the tree responses to insect feeding and M. medusae infection. 7.3.5.3 Comparison of Biotic and Xenobiotic Challenges in Arabidopsis Reveals New Regulatory Pathways Very recently, Weisman et al. (2010) published an interesting comparison of transcriptional inducers. Plants, following treatment with PAHs, exhibit a variety of stresses, such as accumulation of H2O2, oxidative stress, cell death, up-regulation of antioxidant systems, and reduced plant growth. These symptoms broadly resemble the pathogenic HR. While there is substantial evidence of oxidative stress, the signaling and biochemical changes leading to the complex PAH symptoms are

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Fig. 7.9  Comparison of transcriptional responses to phenanthrene and Botrytis cinerea. Scatter plot of 1,031 differentially-expressed transcripts from microarray data of 21-day old phenanthrenetreated Arabidopsis plants, compared to B. cinerea treatment. Counts represent the number of transcripts up (+) or down (−) regulated in each condition. Roman numerals identify the quadrants described in the text below (From Weisman et al. 2010. Courtesy of BioMed Central)

unknown. Furthermore, the phytohormone ethylene (ET) has long been known to play a central role in oxidative stress responses and cell death, in plant growth inhibition, and in abiotic as well as pathogen responses. These broad parallels suggest that ET signaling may play a role in the PAH stress response. Consequently, Weisman et al. (2010) performed DNA microarray experiments to measure global transcriptional changes in Arabidopsis when treated with the three-ringed PAH phenanthrene. In addition, possible roles of ET signaling were investigated using ET-responsive reporter plants, ET-production mutants, ET-signaling mutants, and exogenous application of an ET-precursor. The transcriptional profile indicated that the PAH response shares commonality with biotic stress responses. Illustrating this relationship, Fig.  7.9 compares the phenanthrene dataset to the treatment with the pathogenic fungus Botrytis cinerea and indicates a strong correlation between the two treatments. In this figure, Quadrants I and III contain the transcripts that were jointly up- or down-regulated on both treatments. The vast majority of the phenanthrene responsive transcripts fall

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into these categories. For instance, the cell wall expansins AtEXP1, AtEXP8, and AtEXP11 were down-regulated in both treatments (Quadrant III). Quadrant II contains transcripts that were down-regulated by phenanthrene but up-regulated by the B. cinerea fungal attack and includes the ethylene biosynthesis gene ACS6. Inversely, Quadrant IV contains transcripts that are highly expressed on phenanthrene and diminished by the pathogen, including the cell wall expansin AtEXP4 and AtNAP2 (POP1) which encodes a NAP-type ABC transporter. Overall, a battery of altered transcripts revealed perturbations of the ROS, the pathogenic hypersensitive response, and the systemic acquired resistance. The study supported the hypothesis that the hormones SA, ethylene, and JA are involved in PAH response. 7.3.5.4 Natural Xenobiotics: Humic Substances Humic substances (HSs) have positive effects on plant growth and physiology (Steinberg 2003; see also Chap. 13), but the molecular mechanisms underlying these events are only partially understood. HSs exert auxin-like activity, but data supporting this hypothesis are under debate. To investigate the auxin-like activity of HS, Trevisan et al. (2010) studied its biological effect on lateral root initiation in Arabidopsis thaliana and utilized a combination of genetic and molecular approaches to unravel HS auxin activity in the initiation of lateral roots. The data obtained using specific inhibitors of auxin transport or action showed that HSs induce lateral root formation mostly through their “auxin activity”. These findings were further supported by the fact that HSs used in this study activated the auxin synthetic reporter DR5::GUS and enhanced transcription of the early auxin responsive gene IAA19.

7.3.6 Response to Selected Anthropogenic Stressors Several studies deal with the transcriptomic response of plants to anthropogenic stressors and underline the aforementioned response scheme with the induction of general and specific defense genes. This means that the defensome of plants is responds so generally that even new chemical stressors can be handled – if the stress is below lethality. These studies, of which many are reviewed by Steinberg et al. (2008a), identified that several up-regulated genes coincided well with the classical stress phases “alarm”, “hardening/resistance”, and “exhaustion” phase (Selye 1936; Larcher 1987). For instance, Luis et al. (2006) showed that in the green algal species, Chlamydomonas reinhardtii, the gene encoding ribulose 1,5-bisphosphate carboxylase/oxygenase represents the alarm phase, the genes encoding Fe-SOD and an enzyme responsible for a-tocopherol synthesis represent the hardening phase, whereas the gene encoding the cyclin-dependent protein kinase stands for the exhaustion phase.

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7.4 Stress-Related Gene Expression Profiles in Animals 7.4.1 Response Patterns 7.4.1.1 Invertebrates Several invertebrates are well-established models or even pioneer organisms in ecological functional genomics: the fruitfly Drosophila melanogaster, the nematode Caenorhabditis elegans, the crustacean genus Daphnia, and earthworms. Comparable to the Arabidopsis study by Kilian et al. (2007), there is a highly timeresolved study with D. melanogaster in terms of transcriptional heat stress response (Sørensen et al. 2005). The authors found known stress responding genes as well as new candidate genes and processes to be involved in the stress response. They identified three main groups of stress responsive genes that were early-up-regulated, early-down-regulated, and late-up-regulated, respectively (Fig. 7.10). The majority of stress-responsive genes were down-regulated. As an expected exception, heatshock genes were generally found to be up-regulated by stress in general. In detail: Heat early up-regulated genes were (number of genes in parentheses): chaperones (15), response to stress (17), glutathione transferase (8), protein kinase cascade (6), and gluconeogenesis (3). Many of the early up-regulated genes are also among those found in other studies of stress-induced gene expression. Although metabolism in general was down-regulated after stress, the process of gluconeogenesis, which produces glucose from pyruvate, seemed up-regulated. Glucose is needed as an energy source for nerve tissues, and possibly gluconeogenesis was up-regulated by stress while the remaining metabolism was down-regulated to secure an energy source for important and sensitive nerve tissue (Sørensen et al. 2005). Heat early down-regulated genes were primarily related to metabolism, with many genes in catalytic activity (188), hydrolase activity (129), and peptidase activity (57). The effects of stress in general were more uniform among stress types in terms of what was suppressed, whereas the response in terms of increased expression included more specific groups of genes (Sørensen et al. 2005). The genes found to be late up-regulated were also related to metabolism to a large degree. These genes share characteristics with early down-regulated genes, with many genes involved in metabolism. The stressed animals compensate for the initial stress response in terms of down-regulation of metabolism and return back to normal. 7.4.1.2 Vertebrates Recently, Vergauwen et al. (2010) published a study which differentiated short-term and long-term responses of the zebrafish D. rerio to warm or cold challenges at temperatures outside of their preferred range.. The authors found that warm acclimation depleted energy stores and decreased the condition factor, while cold acclimation

Normalised expression

a

3 2 1 0 −1 −2 −3

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Fig. 7.10  Normalized expression profile in Drosophila over time in three main groups of heat stress–responsive genes; (a) early-up-regulated genes (265); (b) early-downregulated genes (508); (c) late-up-regulated genes (226) (number of genes in parentheses) (From Sørensen et al. 2005. Courtesy of the Cell Stress Society International)

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−1h 0.25h 1h

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increased both. The energy store parameters as well as the transcriptional responses indicated that warm acclimation was particularly stressful. However, after 28 days of warm acclimation, energy stores had recovered from the initial depletion. This could have been facilitated by the observed down-regulation of transcripts involved in catabolic processes. Transcriptional regulation is an important means of coordinating the temperature compensation process. The authors distinguished an early response which was independent of the direction of the temperature change and a direction specific long-term response. The early response was characterized by the up-regulation of defense mechanisms, tissue regeneration and formation of blood cells. In the long-term response, there was a strong emphasis on compensating for the altered metabolic rate as well as cell structure and replacement.

7.4.2 Establishing the Defensome Many biochemical studies show a surprising degree of uniformity in the stress responses of different species at the cellular level, even to widely different environmental stress factors (Kültz 2005; Roelofs et  al. 2008). Genes and proteins affording protection for an organism collectively may be considered a “defensome”. A central part of this system is the “chemical defensome”, an integrated network of genes and pathways that allow an organism to mount an orchestrated defense against toxic chemicals. This defensome concept appears to be almost universally applicable as Goldstone et al. (2006) and Goldstone (2008) showed with the marine animals Nematosella vectensis (Cnidaria) and Strongylocentrotus purpuratus (Echinodermata). Behrendt et  al. (2010) confirmed that even that genes involved with handling UV irradiation are up-regulated via CYP1 not only in mammals but also in zebrafish embryos, whereby a tryptophan photoproduct is the AHR agonist (Jönsson et al. 2009). This means that one single regulatory pathway is activated by several environmental stressors and triggers. Consequently, the defensome concept shall be considered in detail. As indicated in Fig. 7.11, the chemical defensome principally includes soluble receptors and other ligand-activated transcription factors that act as cellular sensors of toxicants or damage. The first line of cellular defense, against amphipathic or slightly lipophilic compounds in particular, is the active expulsion of these compounds by efflux proteins known as ATP binding cassette (ABC) or multidrug efflux transporters (see Appendix 3). Generally, once toxicants enter the cytoplasm, biotransformation is required to enhance elimination or inactivation (see Chap. 4). Antioxidant defenses are critical components of defense systems in organisms living in aerobic environments (see Chap. 2). Metal homeostasis and detoxification is facilitated via metal binding proteins and peptides; the best understood proteins are metallothioneins (MT) (see Chap. 6). A second class of metal-binding compounds is phytochelatins, metal-binding peptides composed primarily of GSH groups. It was believed that phytochelatins were present only in plants and fungi until phytochelatin synthase (PCS) was discovered in the nematode C. elegans (Clemens et al. 2001),

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Fig. 7.11  Conceptual organization of the chemical defensome. Organic and inorganic toxicants are actively exported and subjected to a variety of biotransformative reactions including oxidation, reduction, conjugation, and hydrolysis. Solid lines indicate possible pathways for exogenous toxicants, dotted lines represent possible gene induction in response to stress-activated receptors, and dot-dashed lines indicate possible sources of toxicant-stimulated endogenous production of reactive oxygen. Gene families responsible for the some of the activities are indicated in appropriate boxes and are abbreviated as found in the text (From Goldstone et al. 2006. With permission from Elsevier)

and now it is clear that many other lineages contain PCS homologs (Goldstone et al. 2006). Important stress receptors include the aryl hydrocarbon receptor (AHR), hypoxiainducible factor 1, the aryl hydrocarbon nuclear translocator (ARNT), and metal transcription factor 1. Ligand-activated nuclear receptors (NRs) function as chemically activated transcription factors, primarily with endogenous functions but also importantly in xenobiotic sensing (Goldstone 2008). The major components of the defensive gene network are conserved in the sea anemone genome, indicating that they must have primordial origins. Despite the fact that the individual genes within the defensome network may vary across organisms, this network may be comprised in evolutionarily conserved modules which are retained across evolution.

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7.4.3 Natural Abiotic Stressors 7.4.3.1 Cold and Desiccation Desiccation tolerance or anhydrobiosis is the ability of an organism to survive almost complete drying without sustaining damage. Anhydrobiosis is observed in certain micro-organisms, plants, and animals such as rotifers, brine shrimp cysts, tardigrades, and insect larvae. In the dry state, the metabolism is suspended and the duration that anhydrobiotic organisms can survive ranges from years to centuries. Tardigrades are able to survive long periods of desiccation. Anhydrobiosis probably depends on a series of complex morphological, physiological, and genetic adaptations that involve the stabilization of macromolecular complexes. Consequently, a number of components have been identified and appear to be important for protecting these organisms from desiccation damage. Mali et al. (2010) studied gene expression profiles of anhydrobiosis in the tardigrade Milnesium tardigradum. Studying functional differences gave insight into global mechanisms that were at work in the desiccating animals. Twenty-four Gene Ontology (GO) terms were significantly underrepresented in the inactive stage. The underrepresented GO-terms, which were mapped to “nucleosome”, “nucleosome assembly”, “chromatin assembly or disassembly”, and “chromatin assembly”, consist exclusively of transcripts coding for histones. The cellular component subset of differential terms was also associated solely with structural components of the genome, such as “nucleosome”, “chromatin”, “chromosome”, and “chromosomal part”. Finding only underrepresented terms is consistent with the global metabolic arrest of animals undergoing cryptobiosis. Metabolic suppression in terms of replication and translation during desiccation indicates a general strategy which has also been outlined with the Antarctic nematode, Plectus murrayi (Adhikari et al. 2009). Sinclair et  al. (2007) conducted a comparable study with Drosophila. They exposed adult male D. melanogaster to cold, desiccation, or starvation and examined expression of five genes during exposure and recovery: FROST, SMP-30, HSP23, HSP70AA (a transcript of an inducible form of HSP70), and DESATURASE2. FROST and SMP-30 are directly implicated in cold exposure in Drosophila, and FROST expression increases during desiccation. FROST is expressed during recovery from cold and is up-regulated during desiccation. Desiccation and starvation (but not cold) elicit increased expression of the senescence-related gene SMP-30. DESAT2 decreases during recovery from desiccation but not in response to starvation or cold. HSP70 expression increases immediately during recovery from cold exposure but is unchanged in response to desiccation or starvation stress, and HSP23 levels do not respond to any of the stressors. The responses to (and recovery from) cold and desiccation are qualitatively different. Many soil-dwelling springtail species (Collembola) are extremely vulnerable to drought and desiccation. However, several species have evolved methods either to survive or to prevent dehydration under desiccating conditions. Several species of Collembola survive stressful desiccating conditions by absorbing water vapor from

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the environment. To obtain insight into the transcriptomic responses underlying this ‘water vapor absorption’ mechanism, Timmermans et al. (2009) subjected Folsomia candida to transcriptome profiling. The authors showed that ecologically relevant desiccation stress leads to strong time-dependent transcriptomic changes. Exposure of F. candida to desiccation (98.2% relative humidity) results in a high number of gene transcripts being differentially expressed. GO analyses suggest that carbohydrate transport, sugar catabolism, and cuticle maintenance are biological processes involved in combating desiccation (Timmermans et al. 2009).

7.4.3.2 pH and Temperature De Boer et al. (2010) exposed F. candida to a range of two abiotic stress treatments (pH and temperature) for 3 days and measured expression of a panel of nine stress response genes. The exposure to different pH values had a minimal effect on the expression of the nine selected genes: only V-ATPase expression was significantly increased due to decreasing pH. This up-regulation possibly was due to increased proton trafficking across the cell membrane at a lower pH. HSP70 was up-regulated in collembolans exposed to 30°C along with HSP40 at 0°C. The authors speculate that the minor pH effect on gene expression, compared to the temperature treatment, can be explained by the spatially restricted exposure to external pH in the gut. The data showed that only one or two stress response genes were transcriptionally affected by pH and temperature thus exerting minimal effects. The up-regulation of HSP70 at lower temperatures has not been observed before. HSP70 up-regulation was previously only associated with recovery from cold. However, up-regulation under cold might indicate a novel cold defense mechanism which remains to be elucidated in future studies (Nota et al. 2010).

7.4.4 Natural Biotic Stressors 7.4.4.1 Food Allelochemicals Daphnia magna Responds to Cyanobacteria-Containing Food Cyanobacterial blooms have increased worldwide, and these blooms have been claimed to be a major factor leading to the decline of most important freshwater herbivores, i.e., representatives of the genus Daphnia. Schwarzenberger et  al. (2009) fed a microcystin-containing diet to D. magna and studied a short list of candidate genes. They found two up-regulated genes involved in basic metabolism encoding glyceraldehyde-phosphate dehydrogenase and ubiquitin conjugating enzyme. This up-regulation indicates that microcystins have more general effects on the metabolism of D. magna than previously thought.

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187

Daphnia pulex Responds to Predation It is well understood that D. pulex produces structures referred to as neckteeth (see Fig. 8.6) on its head, primarily in the earlier instars (first to third instar), in the presence of predatory phantom midges (Chaoborus larvae) or their kairomones. Timing of the sensitivity to kairomones in D. pulex generally can be divided into the embryonic and post-embryonic developmental periods. Miyakawa et  al. (2010) examined which of the genes in the embryonic and first-instar juvenile stages exhibit different expression levels in the presence or absence of predator kairomones. The morphogenetic factors HOX3, EXTRADENTICLE, and ESCARGOT were up-regulated by kairomones in the post-embryonic stage. Most of the differences in gene expression induced by the kairomone exposure were observed in post-embryonic juveniles, while a single novel gene, DD1, was up-regulated in the embryonic stage. Taken together, a putative physiological and developmental cascade is suggested for the defense morph formation consisting of the following steps: (1) kairomone reception by embryos, (2) physiological changes through endocrine mechanisms including JH and insulin pathways, (3) morphogenesis triggered by pattern formation genes.

7.4.5 Selected Anthropogenic Stressors Several studies with invertebrates challenged by natural and synthetic xenobiotics and metals have been reviewed by Steinberg et al. (2008a). Here, we pinpoint to subsequent progresses and innovations. 7.4.5.1 Heavy Metals Nota et  al. (2008) exposed the springtail Folsomia candida to soil containing an ecologically relevant Cd concentration and found a cumulative total of 1,586 differentially expressed transcripts across three exposure durations (Fig. 7.12), including transcripts involved in stress response, detoxification, and hypoxia. At day 2, 964 transcripts were differentially expressed; at day 4 only 596 were expressed, and by day 7 the highest number during the study was expressed at 1047. A total of 305 transcripts were differentially expressed at all times; 307 at days 2 and 4, and 411 at days 4 and 7. The analysis of GO terms revealed that Cd altered many biological processes that cost extra energy. This is likely the most important cause of the observed decrease in reproduction in long-term studies. The authors reported many responses in F. candida to Cd-intoxication which were consistent with reported responses in other organisms (e.g., heat-shock response, detoxification), even though they used different concentrations, exposure times, and probably exposure routes. In addition, the authors also described Cd-induced responses not known from literature

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Fig. 7.12  Kinetics of the cadmium transcriptomics of Folsomia candida represented by Venn diagrams showing the differentially expressed transcripts. The number in the right-bottom is the amount of non-significantly expressed transcripts (From Nota et al. 2008. With permission from the American Chemical Society)

Day 2

359

Day 4

65

120

305 235

106

401

Day 7

3540

(e.g., hypoxia, penicillin production) which are likely to be organism-specific and could be dependent on the soil environment, namely genes involved in the “penicillin and cephalosporin biosynthesis pathway” which have never been identified in animals before but are expressed in F. candida’s tissue. The antibiotic biosynthesis was important at all time points examined and could possibly be a response to increased Cd-induced susceptibility to invading pathogens which might be caused by repression of genes involved in the immune-system (C-type lectins and Toll receptor). This study presents a global view on the environmental stress response of an arthropod species exposed to contaminated soil and discovered interesting novel regulatory pathways. 7.4.5.2 Single Organic Compounds Polycyclic aromatic hydrocarbons are common pollutants in soil, have negative effects on soil ecosystems, and are potentially carcinogenic. Nota et  al. (2009) reported an interesting toxicogenomic study with F. candida that translates the ecological effects of the PAH phenanthrene in soil to early transcriptomic responses. Nota et al. (2009) examined two different exposure concentrations of phenanthrene, namely the EC10 (24.95  mg  kg−1 soil) and EC50 (45.80  mg  kg−1 soil), on reproduction of this springtail which evoked 405 and 251 differentially expressed transcripts, respectively. This means that the number of significantly affected genes decreased with increasing effect concentration. Fifty transcripts were differential in response to either concentration. The low effect concentration showed more upthan down-regulated genes relative to the high effect concentration. Many transcripts encoding xenobiotic detoxification and biotransformation enzymes (phases I, II, and III) were up-regulated in response to either concentration. This demonstrates that F. candida has comparative responses to other organisms. Furthermore, indications of general and oxidative stress were found in response to phenanthrene. Chitin metabolism appeared to be disrupted particularly at the low

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189

Fig. 7.13  Transcriptional response to chlorpyrifos (CPF), diazinon (DZN) and combination of both. Venn diagram showing significantly regulated genes by CPF (cyan circle), DZN (orange circle), a combination of both (CPF + DZN, blue circle), and their overlap (From Viñuela et al. 2010. Courtesy of Public Library of Science)

concentration, and protein translation appeared suppressed at the high concentration of phenanthrene, most likely in order to reallocate energy budgets for the detoxification process. Finally, an immune response was evoked especially in response to the high effect concentration which was also described in the above described transcriptomic study using the same effect concentration (EC50) of Cd. When exposing the redworm, Eisenia fetida, to an explosive (TNT), Gong et al. (2007) discovered that the expression of genes involved in multiple biological processes was altered, including muscle contraction, neuronal signaling and growth, ubiquitination, fibrinolysis and coagulation, iron and calcium homeostasis, oxygen transport, and immunity. Sublethal doses of TNT affected the nervous system, causing blood disorders similar to methemoglobinemia, and weakened immunity in E. fetida. The findings provide new insights into the toxicological mechanisms of TNT at the global gene expression level. This information furthers our understanding of how TNT causes toxic effects in a soil organism and allows comparison with higher organisms. 7.4.5.3 Organophosphorus Pesticides Organophosphorus pesticides were originally designed to affect the nervous system by inhibiting the enzyme acetylcholinesterase, an important regulator of the neurotransmitter acetylcholine. Over the past years, evidence has mounted that these compounds affect many other processes. To address the question of side-effects, Viñuela et al. (2010) performed a microarray study in C. elegans which was exposed to two widely used organophosphorus pesticides, chlorpyrifos and diazinon, and a low dose mixture of these two compounds. Their analysis revealed transcriptional responses related to detoxification, stress, innate immunity, and transport and metabolism of lipids in all treatments. The authors found that for both compounds as well as in the mixture, these processes were regulated by different gene transcripts. Synoptically, this difference becomes obvious even in a Venn diagram (Fig.  7.13). Compared to control worms, 551 and 245 genes were significantly regulated in CPF and DZN treated worms, respectively. Both compounds regulated

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126 genes in common. To gain insight into the biological processes associated with the regulated genes, the authors determined which GO terms were over-represented. In both treatments, significantly enriched GO terms were related with detoxification (monooxygenase activity), metabolic process, and transport of lipids. Enzymes and functional domains associated with detoxification in C. elegans were mainly CYP and short-chain dehydrogenase (SDR) in phase I of the xenobiotic metabolism and UGT and GST in phase II.

7.4.5.4 Insecticide and Herbicide In a recent paper, Pereira et  al. (2010) compared equitoxic concentrations of an insecticide (methomyl) and an herbicide (propanil) on the non-target species Daphnia magna and monitored mRNA expression level. Both pesticides promoted transcriptional changes in energy metabolism (e.g., mitochondrial proteins, ATP synthesis-related proteins), molting (e.g., chitin-binding proteins, cuticular proteins), and protein biosynthesis (e.g., ribosomal proteins, transcription factors). Methomyl induced the transcription of genes involved in specific processes such as ion homeostasis and xenobiotic metabolism. Propanil highly promoted hemoglobin synthesis and up-regulated genes specifically related to defense mechanisms (e.g., innate immunity response systems) and neuronal pathways. What is emerging from these data and datasets from aforementioned microarray studies is that where growth is impaired or animals immobilized, genes associated with energy production and (in the case of ecdysozoans) molting are nearly always affected. These genes are therefore likely to represent general stress responses directly linked to phenotypic responses. There is little evidence for expression responses purely restricted to genes associated with the pesticide target site. The toxic response is therefore more subtle and more complicated than first thought.

7.4.5.5 Organic Mixtures Vandenbrouck et al. (2010) applied an integrated systems approach in which transcriptomic, metabolomic (see Chap. 9), and energetic responses of juvenile (4 days old) daphnids were evaluated in response to exposure to two polyaromatic hydrocarbons (pyrene, fluorantheneH) and binary mixtures thereof. In addition, these responses were linked to responses measured during chronic experiments (21 days) assessing survival, growth, and reproductive traits. Hierarchical cluster analysis did not result in a clear distinction between the single compounds, suggesting similar molecular modes of action. Cluster analysis with both the single compounds and the binary mixture treatments resulted in a separation of treatments based on differences in toxic ratios rather than component differences. This means that these two substances with presumed similar modes of action based on chemical characteristics also display similar biological modes of action.

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191

7.4.5.6 Does a General Xenobiotic Response Exist in Invertebrates? The question of a general xenobiotic response was studied with the earthworm Lumbricus rubellus. Owen et al. (2008) and Svendsen et al. (2008) generated an 8,000-element transcriptome microarray for L. rubellus. The microarray identified transcription profiles following exposure to three xenobiotics from different chemical classes: inorganic (Cd), organic (fluoranthene), and agrochemical (the herbicide atrazine). Analysis of these profiles revealed compound-specific fingerprints that identify the molecular responses of the annelid to each contaminant. The majority of genes that showed significant relationships between xenobiotic dose and transcript levels do not have informative similarity to known proteins and were thus annotated as genes “regulated by xenobiotic exposure”. Cu allowed a more detailed insight. Being an essential element that is also highly toxic to earthworms in high concentration, it can be expected that not only general toxic-response pathways are induced/perturbed but also specific biological mechanisms that are essential for Cu handling and homeostasis. Bundy et  al. (2008) exposed worms to sub-lethal levels of Cu. The data provided evidence that the Cu exposure led to a disruption of energy metabolism: transcripts of enzymes from oxidative phosphorylation were significantly over-represented, and increases in transcripts of carbohydrate metabolizing enzymes (maltase-glucoamylase, mannosidase) had corresponding decreases in small-molecule metabolites (glucose, mannose). Treating both enzymes and metabolites as functional cohorts led to clear inferences about changes in energetic metabolism (carbohydrate use and oxidative phosphorylation) which would not have been possible by taking a “biomarker” approach to data analysis. 7.4.5.7 Complex Exposures: Sediments Traditionally, toxicity of river sediments is assessed using whole sediment tests with benthic organisms. The challenge, however, is the differentiation between multiple effects caused by complex contaminant mixtures and the unspecific toxicity endpoints such as survival, growth, or reproduction. The use of gene expression profiling facilitates the identification of transcriptional changes at the molecular level that are specific to the bio-available fraction of pollutants and likely potentially contrasting effects in complex mixtures of river sediments. Furthermore, it bears the potential to identify not yet found toxicity risks. In a pilot study, Menzel et al. (2009b) exposed the nematode C. elegans to three sediments of German rivers with increasing (low, medium, and high) levels of transition metal and organic contamination. Besides chemical analysis, three standard bioassays were performed: reproduction of C. elegans, genotoxicity (Comet Assay), and endocrine disruption (Yeast Estrogen Screen Test). Gene expression was profiled using a whole genome DNA-microarray approach to identify overrepresented functional gene categories and derived cellular processes. Gene expression showed that disaccharide and glycogen metabolism were affected, whereas further functional

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pathways, such as oxidative phosphorylation, ribosome biogenesis, metabolism of xenobiotics, aging, and several developmental processes were differentially regulated only in response to the most contaminated sediment. Numerous differentially regulated parent GO terms and related derived daughter terms were analyzed in detail with a sub-selection of overrepresented biological processes illustrated in Fig. 7.14a–c. The diagrams depict that the majority of derived GO categories are only overrepresented in the Elbe sediment. This indicates that in particular the biological processes of “reproduction”, “determination of adult life span”, and several developmental processes (such as organ, larval, and genitalia development) are differentially modulated by the Elbe sediment. One may speculate that several developmental processes affect C. elegans upon exposure to the Elbe sediment – only the process of aging provides more detailed cues, where most of the significantly regulated genes were found upregulated. Finally, it is reassuring to observe that GO terms associated with reproduction are overrepresented in Rhine and Elbe sediment exposures, a finding that correlates well only with the observed reduction in brood size in nematodes exposed to Rhine sediments. The highly contaminated Elbe sediment, however, did not show an offspring reduction in the phenotypic test. The gene list of differentially regulated transcripts was compared to past toxicogenomic data where C. elegans were exposed to single xenobiotic compounds: PCB52 (Menzel et al. 2007), Cd (Cui et al. 2007), or two humic substances (Menzel et al. 2005a). Although the current data showed only limited overlap to the differential gene-lists obtained from humic substances and Cd exposures, several genes matched those identified upon treatment to PCB52. In detail, 36 up- and 9 down-regulated genes were common to the Elbe and PCB52 gene list and 28 up- and 14 down-regulated genes to the Rhine list. Noteworthy is that both sediments induced the NADHcytochrome b5 reductase encoding gene. Moreover, the Elbe sediment significantly induced WRN1 and RPA1, both coding for proteins involved in DNA damage checkpoint functions. Furthermore, the PCB52 inducible CYP35A5 was found to be upregulated in the Rhine sediment derived sample. C-type lectin (CLEC47) was down-regulated when exposed to either sediment sample, PCB52, or Cd. Nematodes exposed to contaminated environments will modulate their metabolic resources and available energy to combat the environmental insult (Calow 1991). In line with this, Menzel et al. (2009b) found that C. elegans exposed to Elbe or Rhine sediments down-regulated higher-ranking GO categories which include catalytic activities and binding and metabolic processes. An analogous strategy of C. elegans was observed by DNA microarray studies following single compound exposures to PCB52 (Menzel et al. 2005b) and Cd (Cui et al. 2007). Interestingly, exposure to both sediments resulted in a down-regulation of several members of the starch and sucrose metabolism pathway, including the trehalose encoding genes TRE2 and TRE3. The disaccharide trehalose is an invertebrate sugar transport and storage material (Behm 1997) that is present in C. elegans at all life stages. The highest concentrations of trehalose (up to 2.3% of dry weight) are found in eggs and dauer larvae, two diapausing stages that are highly resistant to environmental stressors (McElwee et al. 2006); it is proposed to function as an energy reserve and stress protectant (Pellerone et al. 2003). In contrast, the gene expression of a-amylase,

6

3.3E-03

2.5E-05

6.4E-06

3.0E-03

Significant in both sediments

p-value*

Neg. regulation of developmental process25

Neg. regulation of cellular process26

2.0E-03

Positive regulation of biological process17

2.0E-03 1.0E-03 2.5E-08 Regulation of cellular process16

p-value*

Organ 24 development

5.0E-06

System 15 development

Rhine sediment

p-value*

Anatomical structure mor14 phogenesis

Regulation of biological process8

4.5E-07 4.3E-12

Embryonic 19 development

Nematode larval 31 development

6.9E-08

Larval development27

Embryonic development ending in birth28

7.2E-08 1.1E-08 4.1E-20

Postembryonic development18

5.3E-09 4.0E-09 4.9E-21

2.5E-12 6.0E-29 Multicellular organismal development9

Multicellular organismal 3 process

3.2E-12 5.1E-28

3.8E-08

4

Positive regulation of growth rate29

9.8E-09

Regulation of growth rate20

4.0E-03

1.2E-08

Positive regulation of growth21

8.7E-06

Hermaphrodite genitalia development33

1.2E-04

Genitalia development32

1.4E-04

Sex differentiation30

6.3E-05

Reproductive developmental process22

1.4E-04

Reproductive process12

5

Reproduction

2.4E-04 3.8E-09

Sexual reproduction11

1.8E-08 4.3E-04

Regulation of growth10

3.6E-04

Growth

3.2E-04 1.9E-10

Fig. 7.14  (a) Partial Gene Ontology (GO) tree presenting relevant biological processes which were found to be overrepresented in Caenorhabditis elegans exposed to Elbe and/or Rhine sediment (From Menzel et al. 2009b. Courtesy of BioMed Central). Note: The high potential of sexual interference of Elbe sediments (red) could not be inferred from classical tests; conversely, the potential of the Rhine sediments was shown by classical tests. Overall, micro­array data are more consistent with the degrees of contamination than single toxicity tests are

Elbe sediment

1.6E-08

Anatomical structure development7

Biological 2 regulation

Developmental 1 process

p-value*

Determination of adult life span23

3.0E-03

Multicellular organismal 13 aging

3.0E-03

Aging

2.7E-07 4.7E-12

3.1E-13 4.5E-29

Biological processes (partial GO tree)

7.4  Stress-Related Gene Expression Profiles in Animals 193

2.7E-05

p-value*

2.0E-03

Protein 6 complex

Nuclear 14 lumen

4.0E-03

Organelle 7 lumen

2.0E-03

Membraneenclosed 2 lumen

2.0E-03

3.0E-12

Integral to membrane29

1.2E-11

Intrinsic to membrane26

6.2E-08 4.4E-09

Cytoplasmic part28

7.9E-04

25

4.5E-14 5.1E-09

Cytoplasm

2.9E-06

Membrane part21

1.9E-12

16

1.8E-25

Membrane

2.8E-33 1.9E-09

Intracellular part20

7.5E-21

15

1.6E-38 7.7E-26

Intracellular

3.3E-27

8

7.4E-93

3

1.3E-92

Cell part

2.1E-79

Cell

3.5E-79

Mitochondrial inner membrane30

8.0E-03

Chromosomal part27

1.0E-03

Chromosome23

4.3E-11 1.2E-04

Nucleus22

5.7E-12

2.4E-09

Intracellular n.-membrane18 bound org.

3.7E-15 1.8E-05

Intracellular membrane17 bound org

8.6E-16

6.7E-08

6.7E-08

Nuclear part24

4.0E-03

Intracellular organelle part19

1.8E-06

Organelle 12 part

4.3E-15 1.8E-06

Membranebound 11 organelle

2.4E-09 1.0E-15

4

1.0E-23

Organelle

3.2E-19

N-membranebound 10 organelle

8.0E-24 1.8E-05

Intracellular 9 organelle

2.6E-19

Cellular components (partial GO tree)

Fig. 7.14  (continued) (b) Partial Gene Ontology (GO) tree presenting relevant cellular components which were found to be overrepresented in Caenorhabditis elegans exposed to Elbe and/or Rhine sediment (From Menzel et al. 2009b. Courtesy of BioMed Central). Note: The high genotoxicity of Elbe sediments, indicated by the comet assay, is well reflected by gene expression (red); however, also the Rhine sediments posses a genotoxicity risk (green) which was not indicated by the comet assay

Significant in both sediments

p-value*

Rhine sediment

p-value*

Elbe sediment

p-value*

Ribosome

13

2.0E-04

Ribonucleoprotein complex5

6.0E-03

3.8E-09

Macromole1 cular complex

2.1E-04

194 7  The Potential of Stress Response: Ecological Transcriptomics

2.3E-04

Adenyl ribonucleotide 22 binding

8.0E-03

Purin ribonucleotide 19 binding

6.0E-03

Ribonucleotide 15 binding

5.0E-03

Adenyl nucleotide binding20

5.0E-03

Purin nucleotide 16 binding

Nucleotide 8 binding

6.0E-03

2.9E-04

Nucleic acid 7 binding

Receptor 17 activity

7.2E-04

Signal transducer 9 activity

1.0E-03

Molecular transducer 3 activity

1.0E-03

Elbe sediment

p-value*

Transferase 10 activity

1.6E-02

1.0E-14

Rhine sediment

p-value*

Oxidoreductase 11 activity

9.0E-03

Catalytic 4 activity

6.0E-12

3.6E-04

p-value* Significant in both sediments

p-value*

Hydrolase 12 activity

Fig. 7.14  (continued) (c) Partial Gene Ontology (GO) tree presenting relevant molecular functions which were found to be overrepresented in Caenorhabditis elegans exposed to Elbe and/or Rhine sediment (From Menzel et al. 2009b. Courtesy of BioMed Central). Note: Both sediments affect chromosomes, however, each with a different mechanism: Elbe sediments (red) interfere with the binding of nuclear bases; Rhine sediments (green) specifically modulate the zinc binding. Such a resolution is not achievable with standard ecotoxicological tests

Zinc ion binding21

1.1E-04

Transition metal ion binding18

1.0E-05

9.8E-04

Cation 14 binding

8.0E-03 1.6E-09

Metal ion 13 binding

1.2E-07

Ion binding

Protein 6 binding

1.0E-13 7.0E-04

5

1.3E-03 3.7E-04

2

1.1E-49

2.3E-09

2.3E-34 Binding

7.7E-07

Structural molecule 1 activity

8.0E-03

Molecular functions (partial GO tree)

7.4  Stress-Related Gene Expression Profiles in Animals 195

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7  The Potential of Stress Response: Ecological Transcriptomics

whose yeast and human orthologs help to facilitate the breakdown of glycogen (Teste et al. 2000), was found to have strongly increased. Although the Cd level of the Elbe sediment was found to be 5-fold higher than the Rhine sample, the sediment data presented here is remarkably divergent from the global gene expression pattern observed in laboratory exposures to Cd (Cui et al. 2007). This underlines how single compound exposures, though valuable in their own right, cannot model conditions of true environmental complexity.

7.5 Stress-Related Gene Expression Profiles in Fish Fish have attracted the most attention regarding gene expression profiling under stress by low or high oxygen content as well as synthetic chemicals, and most studies are highly advanced. Furthermore, gene expression profiling seems to be the tool of choice in particular with chemicals/pharmaceuticals which do not show clear or even any effects in classical ecotoxicological tests. Only recently, several studies on transcriptional stress responses to abiotic and biotic as well as handling stresses have been published.

7.5.1 Abiotic Stressors 7.5.1.1 Hypoxia and Hyperoxia Aquatic systems exhibit large, natural fluctuations in dissolved oxygen. During blooms of phototrophs, hyperoxic conditions and, during strong heterotrophic consumption, hypoxic conditions may occur and produce stressful conditions to aquatic organisms.

Hypoxia The role of oxygen in regulating patterns of gene expression in mammalian development, physiology, and pathology has received increasing attention, especially after the discovery of the hypoxia-inducible factor (HIF), a transcription factor that has been linked to a “master switch” in the transcriptional response of mammalian cells and tissues to low oxygen. At present, considerably less is known about the molecular responses of non-mammalian vertebrates to hypoxic exposure. Nikinmaa and Rees (2005) discussed hypoxia-induced gene expression in fishes from an evolutionary and ecological context. Recent studies have described homologs of HIF in fish and have begun to evaluate their function. A number of physiological processes are altered by hypoxic exposure of fish, although the evidence linking them to HIF is less well developed. It now appears that fish possess homologs of two HIFs which

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may play similar roles as those in mammals in hypoxic gene expression. Furthermore, hundreds of hypoxia-responsive genes have been identified in the meantime (reviewed by Zhang et al. 2009). In order to understand mechanisms of the long-term adaptive response to hypoxia in fish, van der Meer et  al. (2005) identified several novel hypoxia-dependent changes in gene expression that were related to physiological adaptation to low environmental oxygen. Examples include genes coding for proteins such as monocarboxylate transporter (MCT4), responsible for transport of metabolites like pyruvate and lactate; myoglobin, which increases the oxygen diffusion rate through tissues; and two genes previously associated with human metabolic disorders that affect cholesterol trafficking and degradation (Zhang et al. 2009). Zhang et al. (2009) categorized the Japanese medaka, Oryzias latipes, hypoxia differentially expressed genes into known GO groups. As may have been expected, metabolism was the largest GO group of down-regulated genes in brain and liver and comprise metabolism, catabolism, RNA (RNA metabolism, processing, and/or splicing), and protein (protein catabolism, metabolism, and/or transport), indicating an overall slow-down in general metabolic processing in these tissues. Two biological pathways were found significantly dysregulated in medaka upon hypoxic exposure: the ubiquitin–proteasome pathway was down-regulated, while the phosphatidylinositol signaling pathway was up-regulated. Down-regulation of the ubiquitin–proteasome pathway indicates the suppression of major energy-consuming processes. The up-regulated phosphatidylinositol signaling pathway (indicated by a key gene, phospholipase C1) promotes inositol production, resulting in increased detoxification rates for liver tissues (Zhang et al. 2009). To test the reliability of findings from one species and their generalizability to another species, Boswell et al. (2009) carried out an interesting cross-genus hybridization experiment with the Japanese medaka and the live-bearing aquarium fish, Xiphophorus maculatus, which is less well characterized in terms of molecular biology. Boswell et al. co-exposed X. maculatus and medaka to hypoxic conditions and utilized the developed medaka oligonucleotide microarray to assess any molecular genetic responses in both fishes. The findings showed that hypoxia induced modulation of gene expression patterns in related molecular genetic pathways in three different X. maculatus tissues. Thus, these changes represent basal roles of acclimatization to the hypoxic environment. Furthermore, comparison of these data with previous medaka hypoxia studies revealed common genetic responses between both fish genera. In particular, 12, 436, and 63 features were up-regulated, while, 12, 395, and 56 features were down-regulated in liver, gill, and brain tissues, respectively, of X. maculatus challenged by hypoxia (Fig. 7.15). The most responsive tissue was the gill. Expectedly, the ubiquitin–proteasome pathway was significantly downregulated in X. maculatus. Chronic Hypoxia In contrast to most mammals (with the exception of some marine mammals), some teleosts have developed the ability to withstand extreme chronic hypoxia. These

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Fig. 7.15  Venn diagram analysis of hypoxiaresponsive genes in Xiphophorus maculatus that are significant in either direction (From Boswell et al. 2009. With permission from Elsevier)

vertebrate species possess unique adaptations in order to survive short- and longterm oxygen deprivation. However, Marques et al. (2008) have only recently investigated the molecular basis of these adaptations in fish. The authors profiled the gene expression changes in the hearts of adult zebrafish, D. rerio, and found 376 differentially regulated genes, of which 260 genes showed increased and 116 genes decreased expression levels. Two notch receptors (NOTCH-2 and NOTCH-3) as well as regulatory genes linked to cell proliferation were transcriptionally up-regulated in hypoxic hearts. Notch receptors are present in all metazoans with essential roles in development, including heart development. Marques et al. (2008) observed an up-regulation of several genes important for the protection against ROS. Furthermore, chronic hypoxia simultaneously induced up-regulation of the insulinlike growth factor II (IGF-2) and the insulin-like growth factor binding protein 1 (IGFbp1). The up-regulation of IGFbp1 seems to be a general response to hypoxia in zebrafish embryos, where it mediates hypoxia-induced embryonic growth retardation and developmental delay. IGFbp1 is a secreted protein which binds to IGFs in the extracellular environment and prevents receptor activation. Here, IGFbp1 by binding IGF-2 may have prevented both cardio-protective as well as apoptotic effects of enhanced IGF-2 expression. Hyperoxia Transcriptional regulation of antioxidant defenses in fish under hyperoxia is almost completely unknown. Only recently, an aquaculture study fills this gap (Olsvik et al. 2006). In intensive aquaculture of many species, it is now common to oxygenate the rearing water to increase biomass and production. In fish, exposure to hyperoxia can induce a reduction in gill ventilation and elevate the partial pressure of CO2 in the blood, resulting in a respiratory acidosis and chloremia. The respiratory acidosis may be compensated for within days, but short-term exposure to hyperoxia may cause gill oxidative cell damage. Long-term effects of exposure to hyperoxia are less known. Olsvik et  al. (2006) exposed Atlantic cod, Gadus morhua, to three oxygen regimes and analyzed genes encoding for antioxidant enzymes as well as general stress defense such as MT and CYP1A in the fish livers. The exposure revealed significant differences in transcript levels of the antioxidant genes of SOD and GSH-Px (Fig. 7.16). The transcript level of GSH-Px was significantly up-regulated

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Fig. 7.16  Atlantic cod, Gadus morhua: relative mean normalized expression (MNE) of superoxide dismutase (SOD), catalase, CAT, phospholipid hydroperoxide glutathione peroxidase (GSH-Px), metallothionein (MT) and cytochrome P450 1A (CYP1A) in liver of Atlantic cod exposed to 46%, 76%, and 145% O2 levels. The box plots show median, 25th and 75th percentiles (box) and error bars of the range (highest to lowest values); 1 significant difference between the hypoxia and normoxia groups; 2 significant difference between the hypoxia and hyperoxia groups (From Olsvik et al. 2006. Courtesy of The Company of Biologists)

in fish exposed to hyperoxia and significantly down-regulated in fish exposed to hypoxia. Significant down-regulation was also found for SOD and CYP1A under hypoxia. CAT and MT did not change in liver of cod exposed to suboptimal oxygen levels. Prolonged exposure to unfavorable oxygen saturation levels did not alter the oxidative state index, indicating that the antioxidant glutathione system is maintained at an unchanged level in liver of the examined cod. It is interesting to note, but not surprising, that hyperoxic stress conditions are defended with the same regulatory pathway as internal oxidative stress created by a surplus production of ROS or a surplus consumption of antioxidants.

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7.5.1.2 UV Irradiation UV-B-irradiation (280–320  nm) is readily absorbed by and can cause severe damage to proteins and DNA. Effects of UV irradiation result from generation of ROS and subsequent organic radical formation, as well as direct damage to cellular macromolecules. UV irradiation induces expression of CYP1 in human and animal cells. This involves tryptophan, which forms endogenous AHR agonists, via enzyme action or direct oxidation. Oxidation of tryptophan by UV irradiation or sunlight produces multiple products that can induce CYP1A expression (Fritsche et al. 2007). With developing zebrafish, Behrendt et al. (2010) showed that UV-B can induce expression of CYP1 as well as stress response genes such as SOD and PCNA. PCNA is the proliferating cellular nuclear antigen involved in the re-synthesis of DNA. The pathway for CYP1 induction in zebrafish is probably dependent on the generation of an AHR ligand, whereas SOD1 and PCNA are induced by ROS and DNA damage, respectively. 7.5.1.3 Metals and Metalloids Gene profiling studies that investigate the effect of metals have only recently been forthcoming. For instance, Klaper et al. (2006) studied the pathways of methylmercury (MeHg) toxicity in fish. Hg in its methylated form is neurotoxic, particularly to the developing nervous system. However, the mechanistic effects of MeHg on other physiological processes such as reproduction are at large unknown, and there are comparatively few studies that examine risks of MeHg exposure. Klaper et al. (2006) found that the expression of genes commonly associated with endocrine disruption was altered due to the exposure to Hg. Vitellogenin gene expression, for example, significantly declined in female fish exposed to increasing concentrations of Hg. Other genes included those associated with egg fertilization and development, sugar metabolism, apoptosis, and electron transport. The authors also observed differences in expression profiles in male and female fish (including genes not specifically associated with reproduction), suggesting that the differences in physiology and MeHg toxicity are potentially interlinked. Cu is an essential micronutrient, and fish assimilate it either through the gills from the surrounding water or through the digestive tract via the diet. Though essential, elevated levels of Cu can cause a range of negative effects, including reduced growth, interference with ion-regulation, and endocrine disruption. Many of these responses are in part due to the reactivity of Cu with H2O2 and its potential to undergo (Fenton-like) redox reactions to form ROS. The resulting cellular damage can be membrane peroxidation, DNA damage, and protein carbonyl production. Like other organisms, fish combat elevated levels of ROS with protective ROSscavenging enzymes such as SOD and CAT. However, once these enzymes are saturated, irreversible cellular damage and death can occur (Craig et al. 2007). In two experiments, Craig et al. (2007) examined the impacts of Cu on gene expression,

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oxidative damage, and cell oxidative capacity in the liver and gills of zebrafish. Soft water-acclimated zebrafish exposed to environmentally relevant Cu concentrations resulted in significant increases of cytochrome c oxidase subunit 17 and catalase, associated with both increased Cu load and protein carbonyl concentrations in the gill and liver. Furthermore, there were indications that Cu alters normal mitochondrial biogenic processes, possibly though cytochrome c oxidase subunit 17. However, unlike MeHg, Cu did not modulate endocrine disruption. Arsenic (As) is a prominent environmental toxicant and carcinogen; nevertheless, its molecular mechanism of toxicity and carcinogenicity remains poorly understood. Lam et al. (1996) performed microarray-based expression tests profiling the liver of zebrafish exposed to As(V). The authors found that there was an increase in transcriptional activity associated with metabolism, especially for biosynthesis, membrane transporter activities, the cytoplasm, and the endoplasmic reticulum. Many differentially expressed genes encoding heat-shock proteins and genes involved in DNA damage/repair, antioxidant activity, hypoxia induction, iron homeostasis, and ubiquitin-dependent protein degradation were identified, strongly suggesting that DNA and protein damage cause major cellular injury as a result of As metabolism and oxidative stress. 7.5.1.4 Nanoparticles Metal and metal oxide nanomaterials comprise a large segment of the growing nanotechnology market. Nanoparticles have been made from many metals, including Au, Ag, Cu, Ni, Co, Zn, and Ti. Nanoparticles have unique physicochemical properties such as tiny size, large surface area, surface reactivity, and charge, shape, and media interactions. As a result, the properties of nanoparticles differ substantially from their respective bulk materials of the same composition. However, certain novel properties of nanoparticles could lead to as yet unidentified adverse biological effects with the potential to create toxicity. Recent papers indicate that nanoparticles are more toxic than bulk materials (Wang et al. 2009a; Roh et al. 2010). Furthermore, microscopic techniques showed that fluorescently labeled nanoparticles were efficiently ingested by C. elegans and translocated to primary organs including the epithelial cells of the intestine as well as to secondary organs belonging to the reproductive tract (Pluskota et al. 2009). Cu and Ag nanoparticles are acutely toxic to a wide spectrum of aquatic species including zebrafish. This toxicity is largely manifest at the gills. Griffitt et al. (2009) exposed adult female zebrafish to toxic (nano-Cu and nano-Ag) and presumably nontoxic (nano-TiO2) nanoparticles, as well as soluble forms of the toxic nanometals. The gene expression profiles in the gills demonstrated that the exposure to each nanometal produced a distinct gene expression profile at both tested times (Fig. 7.17). There was little commonality between gene sets affected by the different exposures. At 24 h, there were only 37 genes that were significantly affected by both nano-Cu and nano-Ag (Fig. 7.17a). At 48 h, when the nano-TiO2 exposed fish were included, there were 53 genes affected by all three nanometals (Fig. 7.17b). Similarly,

202 Fig. 7.17  Venn diagram analysis of Danio rerio genes identified by microarray analysis as significantly differentially expressed following exposure to nano-Ag, nano-Cu, or nano-TiO2. (a) 24 h; (b) 48 h (From Griffitt et al. 2009. Courtesy of the Society of Toxicology)

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Nanosilver (148)

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95 genes were affected by both nano-Cu and nano-Ag, 20 genes overlapped between nano-Ag and nano-TiO2, and 32 were commonly affected by nano-Cu and nano-TiO2. These results indicate that each nanometal is producing biological responses by different mechanisms. The detailed analysis of the genes affected by nano-Cu indicated that many of the genes were involved in apoptosis, mitogenesis, and proliferation as well as in cancer progression. Since apoptosis on the one hand and proliferation and cancer progression on the other are mutually exclusive, it is not likely that these regulatory pathways run simultaneously. Of interest, nano-TiO2 exposure altered expression of a number of genes involved in ribosomal function that were not affected by other nanometals, indicating that, although not overtly toxic within the time frame studied, exposure to nano-TiO2 may have adverse effects on zebrafish gills.

7.5.1.5 Endocrine Disrupting Compounds Endocrine disrupters are a real threat of fish populations. In a 7-year whole-lake experiment, Kidd et al. (2007) showed convincingly that chronic exposure of fathead

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minnow, Pimephales promelas, to low concentrations (5–6  ng  l−1) of the potent ­synthetic estrogen 17 a-ethinylestradiol led to feminization of males (indicated by the production of vitellogenin mRNA and protein) and altered oogenesis in females; ultimately, a near extinction of this species from the lake occurred. Hence, the regulatory pathways are interesting to examine. Van der Ven et al. (2006) showed this pathway with zebrafish exposed to the tetracyclic antidepressant Mianserin. Analysis of brain and gonad tissue clearly demonstrated the estrogenic activity of Mianserin (“Bolvidon”, “Depnon”, “Norval”, or “Tolvon”) and its potency to disrupt endocrine signaling, based on induction of molecular biomarkers of estrogenicity (e.g., vitellogenin). The possible mechanism underlying the estrogenic activity of Mianserin may be caused by the disturbance of the hypothalamo-pituitary-gonadal axis via serotonergic and adrenergic systems in the brain of zebrafish. The European flounder, Platichthys flesus, is another favorite candidate for assessing the effects of endocrine disruptors, particularly in European estuaries. Williams et al. (2007) identified 175 genes showing significant induction or repression; those associated with the GO terms mitochondria, amino acid synthesis, ubiquitination, and apoptosis were over-represented while those associated with immune function, electron transport, cell signaling, and protein phosphorylation were underrepresented. Several other studies highlight the counter-intuitive effects on apoptotic as well as proliferative pathways and demonstrate the impact of estrogen on mitochondria and steroid transporters. Overall, even the early studies provide valuable insights into the mode of action of 17-b-estradiol in liver and show that its gene expression profile differs from chemicals that are estrogen analogs, such as DDE or nonylphenol (Fig. 7.18) (Larkin et al. 2003).

7.5.2 Biotic Stressors 7.5.2.1 Food Allelochemicals: Cyanotoxins Microcystins (MCs), a family of cyclic peptides, are the most widespread hepatotoxic toxins in eutrophicated, cyanobacteria-dominated water bodies which inhibit serine/threonine protein phosphatases 1 (PP1) and 2A (PP2A) in human hepatic cells. Fish are intimately exposed to MCs and are often forced to consume MC-contaminated food. However, the question of how fish respond to these natural xenobiotics has only recently been addressed in terms of transcription (Wei et al. 2008a). The authors found 243 genes up-regulated (Fig. 7.19), and 30 genes downregulated in livers of exposed zebrafish. The predominantly overrepresented pathways were those pertaining to cell cycle and mitogen-activated protein kinases (MAPK) signaling pathway. Ten genes were grouped in cell cycle pathway, and six genes in MAPK signaling pathway. Cell cycle is regulated through a delicate balance between phosphorylation and dephosphorylation of some proteins. Since MCs act as phosphatase inhibitors, the

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Fig. 7.18  Gene expression profiles of largemouth bass livers exposed to 17-b-estradiol and two chemicals that behave as estrogens. Red indicates up-regulated genes and green indicates downregulated genes (From Larkin et al. 2002. With permission from Elsevier). Despite the common expression of various vitellogenin genes by all exposures, the differences between 17-b-estradiol and the two endocrine disruptors, 4-NP and p,p¢-DDE, are evident

induction of cell cycle may be due to MC-LR-induced inhibition of PP1A and PP2A which are involved in the regulation of cell cycle progression. Importantly, Wei et al. (2008a, b) showed that the expressions of CYCLIN B1 and GADD45A (growth arrest and DNA-damage-inducible, alpha) in cell cycle pathway were significantly increased. CYCLIN B1 is a protein required for mitotic initiation; GADD45 is a P53-regulated stress protein and plays an important role in the cell cycle G2-M checkpoint. According to these results, MC-LR exposure can result in cell proliferation and promote tumorigenesis in the liver of zebrafish. The activation of the MAPK signaling pathway further confirms the carcinogenic potential of MC-LR.

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Fig. 7.19  Distribution of MC-LR-up-regulated genes in zebrafish livers over different functional GO categories. The percentage of genes in each functional category is listed (From Wei et  al. 2008a, b. With permission from Elsevier)

7.5.2.2 Social Stress and Behavior The formation of dominance hierarchies due to competition for limited resources, such as food and foraging sites, is evident in several teleost species. Socially subordinate fish experience unreliable access to food, a general lack of control and predictability, and a constant threat of aggression from dominants. In the wild, social status is a major determinant of life history traits, reproductive success, and survival in many species (reviewed in Prunet et al. 2008). Aubin-Hort et al. (2007) studied brain gene expression profiles in dominant male and female breeders and subordinate male and female helpers of an African cichlid, Neolamprologus pulcher. Four genes were found to vary between dominant and subordinate fish independent of sex. One of these genes was arginine vasotocin which has been linked to aggressive and reproductive behaviors in fish and birds and to social affiliation and partner preference in mammals. This means that dominant breeder females were masculinized at the molecular level while at the same time becoming reproductively competent. In females, a tremendously important behavior for fitness is mate choice. Cummings et al. (2008) studied female swordtails, Xiphophorus nigrensis, in a mate choice experiment and exposed females to a large male, a small male, another

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female, or an empty tank. They found that females exposed to a large attractive male had brain gene expression profiles that were different from that of females in presence of other social stimuli, such as non attractive small males, females, and controls with no social interactions. The authors uncovered significant correlations between a preference behavior score for a male and expression levels of candidate genes (neuroserpin, neuroligin 3, importin, and the immediate early gene EGR-1, a marker of neural activity) in the female brains, such that the more choosy they were, the more these genes were expressed in their brain (St-Cyr and Aubin-Hort 2009).

7.6 Linkages Between Gene Expression and Higher Biological Levels Knowledge of the phenotypic consequences of stress as well as the genomic components that are induced or suppressed enables us to identify not only the mode of action of the stressor but also which genomic components affect organismal growth, reproduction, and survival, and thus populations. So, increased knowledge of the fundamental interactions between genome and phenotype should enable us to better predict population stress responses (Heckmann et al. 2008). Only a few studies combine gene expression profiles with parameters on higher biological levels. Connon et al. (2008) noted gene expression in D. magna under Cd exposure and linked this expression to somatic growth, development, and population growth rate. The latter was approximately linearly negative with increasing Cd concentration (Fig. 7.20). Gene expression profiles revealed that 30% of the modulated genes were involved with metabolism including carbohydrate, fat, and peptide metabolism, and energy production. Another 30% were involved with transcription/ translation, while 40% of responding genes were associated with cellular processes like growth and molting, ion transport, and general stress responses including oxidative stress. In their study, Heckmann et al. (2008) exposed D. magna to the non-steroidal anti-inflammatory drug ibuprofen. In mammals, ibuprofen operates as a reversible inhibitor of the enzyme cycloxygenase which is responsible for metabolism of arachidonic acid to produce eicosanoids. Ibuprofen has been identified as having a targeted impact on reproduction in D. magna following chronic exposure. Heckmann et al. (2008) conducted a microarray study in concert with assessment of life history traits and population dynamics. Intriguingly similarly to vertebrates, D. magna genes related to eicosanoid metabolism showed early response to ibuprofen. The consequence was a disruption of signal transduction affecting juvenile hormone metabolism and oogenesis with a clear consequence on the population level: the D. magna population was soon extinguished. In another study, C. elegans gene expression was integrated with organism and population level parameters exposed to nano-Ag (Roh et  al. 2009). This study showed a dramatically decreased reproduction potential due to an overall oxidative

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Fig. 7.20  Mean population growth rate (PGR) per day of Daphnia magna after 9 days exposure to CdCl2. Bars indicate standard errors; *** p < 0.001, **p < 0.01, *p < 0.05 (From Connon et al. 2008. With permission from the American Chemical Society)

stress (increased expression of SOD3) and due to abnormal dauer formation protein (DAF12) genes. In a closer look at the gene list and the application of Babelomics, Steinberg et al. (2010c) identified even on the biological level that more structures and processes were adversely affected, namely very basic functions such as protein formation and conformation in the endoplasmic reticulum. In another study, Connon et al. (2009) were able to link mechanistic and behavioral responses to sublethal exposure to the pyrethroid insecticide esfenvalerate in the endangered delta smelt Hypomesus transpacificus. They found that exposure to the insecticide affected swimming behavior of larval delta smelt at concentrations on the ng l−1 level, and significant differences in expression were measured in genes involved in neuromuscular activity. Alterations in the expression of genes associated with immune responses along with apoptosis, redox, osmotic stress, detoxification, and growth and development appear to have been invoked by the insecticide exposure. Swimming impairment correlated significantly with expression of aspartoacylase (ASPA), an enzyme involved in brain cell function. This study demonstrated that exposure to sublethal concentrations of esfenvalerate results in neurological damage and a series of compensatory molecular responses that attempt to repair nerve damage. The authors hypothesized that induction of transcription of the genes encoding ASPA, hemopexin, parvalbumin, and creatine kinase are part of a pathway of damage-triggered repair mechanisms responding to esfenvalerate insult. Reduction in expression of ASPA indicates that myelin sheaths may be degraded, resulting in a number of detrimental effects on the lesion sites; similarly, muscular structure and function is being compromised as measured by alterations in titin and myozenin expression. The expression of b-microglobulins could be a compensatory reaction to toxic damage, protecting cells from infections in a susceptible immune system caused by exposure to esfenvalerate. As can be expected from the aforementioned response of fish to hypoxia, this frequent environmental stress has clear adverse impacts on fish reproductive functions. In a recent study, Martinovic et al. (2009) characterized modes of action in mature zebrafish. Short-term exposure to hypoxia affected expression of genes associated with initial adaptive responses such as metabolism of carbohydrates and

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proteins, nucleotide metabolism, hemoglobin synthesis, ROS metabolism, and locomotion. Prolonged hypoxia affected a suite of genes belonging to different GO categories: lipid metabolism, reproduction (e.g., steroid hormone synthesis), and immune responses. Yet, reproduction likely is affected by hypoxia via not only one but multiple modes of action. These include previously hypothesized mechanisms such as modulation of expression of steroidogenic genes and down-regulation of the serotonergic pathway. In addition, Martinovic et al. (2009) proposed that there were multiple other points of disruption of reproductive system function linked, for example, to reorganization of lipid transport and other mechanisms involved in responding to hypoxia (e.g., hydroxylsteroid dehydrogenase alterations, downregulation of contractile elements).

7.7 Population Genetics Another giant step towards realistic environmental situations is taken when gene profiling utilizes a whole population or even different populations of one species. Genomic studies of wild populations have the potential to reveal the genetic basis of traits affecting fitness and may ultimately lead to a synthesis of population biology and genomics (Wheat et  al. 2011). Two striking studies shall be presented in detail.

7.7.1 Metapopulation of the Butterfly Melitaea cinxia Temporally varying selection due to changing environmental conditions may maintain genetic variation with large fitness effects. Furthermore, selection may vary from one habitat type to another in a heterogeneous environment, thereby maintaining genetic variation at the landscape level. Less well understood is what happens in fragmented landscapes (Fig. 7.21) in the absence of habitat differences but with a high rate of population turnover (Wheat et al. 2011 and references therein). Wheat et al. (2011) examined the consequences of repeated local extinctions and re-establishment of new populations for the pattern of genetic variation with large fitness effects across a heterogeneous landscape. They used data and material from the long-term ecological study of the Glanville fritillary butterfly, Melitaea cinxia (inset in Fig. 7.21), in the Åland Islands in Finland. This large metapopulation persists in a balance between stochastic local extinctions and establishment of new populations in a network of several thousand small meadows (Hanski 1999). Wheat et al. (2011) found that the gene expression profiles and the physiology of individuals from new populations represent a nonrandom draw from the set of individuals present in source (old) populations, both in terms of reproductive physiology and in terms of flight metabolism. Females from new populations exhibited overall higher expression of abdominal genes involved in egg provisioning and fecundity including

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Fig. 7.21  Habitat patch appropriate for Glanville fritillary butterflies in the Åland islands, Finland. Host plants (Plantago lanceolata, Veronica spicata) for this butterfly grow in the thin soil bordering granite outcrops but are absent in longer grass, pastures, and forest. Inset: Glanville fritillary butterfly Melitaea cinxia. Photo credit: Jim Marden (From Klepsatel and Flatt 2011. With permission from Wiley)

up-regulation of amino acid transporters and storage molecules known as larval serum proteins and important for egg provisioning; the egg yolk precursor vitellogenin; and the fecundity regulator angiotensin-converting enzyme (Fig. 7.22). New-population females also had a higher titer of juvenile hormone, a major gonadotropin in insects, and a larger number of mature, chorionated eggs than oldpopulation females. New-population females therefore reach reproductive maturity faster and seem to fuel egg production by accelerating the release of proteins from fat body tissue. In terms of flight physiology, new-population females had a higher peak metabolic rate during flight and increased expression of proteasome and chaperone genes in the thorax, with the expression levels of these genes being positively associated with metabolic rate, reflecting the high energetic demands of increased flight activity required for dispersal and colonization (Klepsatel and Flatt 2011). A very noteworthy aspect of this study relates to life history trade-offs. Because new-population females have enhanced reproductive and flight performance, they must turn a substantial fraction of their larval-derived protein resources into both eggs and flight muscle – and what about the trade-off? A previous study might provide an answer. When measured in large outdoor field cages that permit mobility, the more dispersive new population females had reduced maximal lifespan indicating that increased flight metabolism and reproductive performance trades-off with longevity (Hanski et al. 2006) – strong evidence of the Disposable Soma Theory (see Chap. 13).

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Fig. 7.22  Differential gene expression in the abdomens of butterflies representing the new vs. old population matrilines and related reproductive physiology. (a) Volcano plot of microarray data highlighting probes for egg-provisioning genes (larval serum proteins) and angiotensin converting enzyme. (b) Transcript abundance of vitellogenin (VG; black bars) and angiotensin converting enzyme (ACE; open bars) mRNA in the abdomen (From Wheat et al. 2011. With permission from Wiley)

7.7.2 The Estuarine Killifish Fundulus heteroclitus Nacci et al. (1999), for example, described that aquatic species such as the estuarine fish Fundulus heteroclitus (mummichog) can adapt to local environmental pollution conditions, even to pollution by persistent organic chemicals, such as dioxin-like compounds, that are particularly toxic to developing fish. Fish from contaminated Massachusetts sites were profoundly less sensitive to the toxicants than reference fish. Specifically, concentrations of dioxin-like compounds similar to those measured in mummichog eggs from the contaminated site were lethal to reference embryos. Furthermore, responsiveness to dioxin-like compounds was inherited at least to the F2 generation and independent of maternal contaminant contributions. In contrast to the Massachusetts mummichogs, it was found that resistance is not highly heritable in a Virginia population originating from contaminated sites of the Elizabeth River (Meyer and Di Giulio 2002). However, the authors show that offspring of this population of Elizabeth River killifish also are resistant to the teratogenicity and CYP1A-inducing activity of PCB126, a prototypical coplanar polyhalogenated aromatic hydrocarbon. The genetic evaluation at the population level solved this contradiction. Fisher and Oleksiak (2007) used Fundulus cDNA

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Fig. 7.23  Venn diagram showing numbers of significant genes for each polluted versus reference sites comparison. Two genes are significantly different in all three polluted populations compared to their respective reference populations. NBH New Bedford Harbor comparison; Newark Newark Bay comparison; ER Elizabeth River comparison (From Fisher and Oleksiak 2007. Courtesy of BioMed Central)

arrays to compare metabolic gene expression profiles of the brains from individuals of nine populations including the aforementioned populations. The authors found that up to 17% of metabolic genes had evolved adaptive changes in gene expression in the polluted populations. Two genes in particular showed a conserved response among three polluted populations, suggesting common, independently evolved mechanisms for adaptation to environmental pollution in these natural populations (Fig. 7.23). What happens to the regulatory pathway of the metabolism of the fish inhabiting these Superfund sites? To identify both shared and unique responses to chronic pollutant exposure, Oleksiak (2008) compared metabolic gene expression in F. heteroclitus populations from each of three Superfund sites to two flanking reference site populations. In comparisons to their two clean reference sites, the three Superfund sites had 8–32% of genes with altered expression patterns. Between any two Superfund populations, up to nine genes (4%) show a conserved response, yet among all three populations, there was no gene which had a conserved, altered pattern of expression. Across all three Superfund site populations, the most significant gene was fatty acid synthase. Fatty acid synthase is involved in the storage of excess energy as fat, and its lesser expression in the polluted populations suggests that the polluted populations may have limited energy stores. Body weight was a significant covariate for many of the genes which could reflect accumulation and different body burdens of pollutants. Overall, the altered gene expression in these populations likely represents both induced and adaptive changes in gene expression (Oleksiak 2008). Finally, Williams and Oleksiak (2008) provided evidence that the populations of F. heteroclitus which flourish in the heavily polluted and geographically separated Superfund sites have even independently evolved adaptative resistance to chemical pollutants. In these polluted populations, natural selection has altered allele frequencies of loci that affect fitness or that are linked to these loci. The few shared loci among polluted sites indicate that selection may be acting on multiple loci involved in adaptation, and loci shared between polluted sites potentially are involved in a generalized adaptive response – the start of a radiation?

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Chapter 8

Not All Is in the Genes

Phenotypic plasticity describes the ability of a genotype to form different phenotypes in distinct environmental conditions and occurs in many traits ranging from morphology through developmental biology to physiology and behavior (Tollrian 2002). This means that the genotype is the basis or the potential of an organism to translate into a phenotype, but there are many more mechanisms which determine the specific phenotype. Two mechanisms which bear clear environmental relations are the action of microRNAs (also see Fig. 7.6) and transgenerational or even epigenetic modes of action.

8.1 No Junk: MicroRNAs Small RNAs are an abundant class of newly identified endogenous non-protein-coding small RNAs with a length of 20–25 nucleotides and have been considered as “junk RNA” for a long time. Only recently the paradigm shifted completely, and these RNAs are considered major regulatory tools. Small RNAs are classified into microRNAs (miRNAs), small interfering RNAs (siRNAs1), trans-acting siRNAs (ta-siRNAs), natural antisense siRNAs (nat-siRNAs), and repeat-associated siRNAs (ra-siRNAs). The largest class of small RNAs expressed in animal cells are longer-than-average (26–31 nucleotides) Piwi-interacting RNAs (piRNA), a class of germ-line-specific small RNAs. A new category of small RNAs ranging from 30 to 40 nucleotides in size, referred to as long-siRNAs (l-siRNASs) has been added recently to the list (Sunkar 2010). Of these, miRNAs are the most abundantly expressed and well-studied class of small RNAs in plants. miRNAs display near-perfect complementarity with their target mRNAs and interfere with target gene expression by causing degradation or

1

Also known as short interfering RNA or silencing RNA.

C.E.W. Steinberg, Stress Ecology: Environmental Stress as Ecological Driving Force and Key Player in Evolution, DOI 10.1007/978-94-007-2072-5_8, © Springer Science+Business Media B.V. 2012

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inhibition of the translation of the mRNA targets in plants. Modes of action will be exemplified with miRNA and piRNA (Sect. 8.2). Ever since miRNAs were recognized in 2001, the broad significance of these newly identified small RNAs is becoming clear and is being fully appreciated because more and more evidence suggests that miRNAs play an essential role in multiple biological processes. A majority of identified miRNAs are highly evolutionarily conserved among many distantly related species, suggesting that miRNAs play a very important role in essential biological processes including developmental timing, stem cell differentiation signaling transduction, disease, and cancer (Zhang et al. 2007). Currently, miRNAs have been considered one of the most important regulatory molecules which regulate gene expression at the post-transcriptional level by targeting mRNAs for either direct cleavage or repression of translation. In other words, transcriptome analyses show mRNA accumulation, but this does not necessarily mean that mRNAs of expressed genes are actively translated. In addition to the transcriptome profile, it is important to examine which mRNAs are translated, degraded, or temporarily stored during stress treatments.

8.1.1 miRNAs Regulate Plant Responses to Environmental Stresses Abiotic and biotic stresses are a big issue for plant growth and development. Although several genes have been identified and isolated from plants, the principle mechanism of plant resistance to stress still remains unknown. Recent evidence suggests that miRNAs play an important role in plant response to biotic and abiotic stresses and that 26% of expressed sequence tags containing miRNAs were identified in stress-induced plant tissues (Zhang et al. 2005, 2006), including pathogen-, salt-, drought-, or transition metal stresses (Ding and Zhu 2009). 8.1.1.1 miRNAs and Abiotic Stress Whereas in mammals several examples of miRNA-mediated inhibition or enhancement of viral infection have been reported, in plants neither miRNAs nor endogenous siRNAs have yet been implicated directly in the response to biotic stress (Mallory and Vaucheret 2006). Consequently, the following focuses on the role of miRNAs in abiotic stress defense. The first indication for a role of miRNAs in adaptive response to abiotic stresses came from bioinformatics on miRNA and target gene predictions and miRNA cloning from stressed A. thaliana plants which revealed new miRNAs that had not been cloned previously from plants grown in normal conditions. For example, miR395 is not detectable in plants grown under standard conditions but is induced during lowsulfate stress. miR395 targets ATP sulfurylases that catalyze the first step of inorganic sulfate assimilation; hence, this enzyme is down-regulated under low-sulfate stress.

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Similarly, miR399 is not detectable in plants grown under standard conditions but is induced during low-phosphate stress. miR399 targets a ubiquitin-conjugating enzyme (UBC), and UBC mRNA accumulation is decreased during low-phosphate stress which is important to induce the phosphate transporter gene AtPT1 and attenuate primary-root elongation. Over-expression of miR399 leads to down-regulation of UBC, even under high-phosphate conditions, and induces accumulation of phosphate in these plants. Other miRNAs are likely to have roles during stress based on the function of their targets or their pattern of expression. For example, miR398 targets two Cu-SODs that protect cells against harmful oxidative radicals produced during stress (Table 8.1). Furthermore, in poplar trees, Populus tremula, miR408 expression is induced by tension and compression stresses in xylem tissues, suggesting that this miRNA has a critical role in the structural and mechanical fitness of woody plants. The functional understanding of miRNAs is currently progressing. In a comprehensive study, Li et al. (2009) classified 72 putative miRNA sequences in Euphrates Poplar, Populus euphratica, into 21 families, 12 of which were novel, increasing the number of known poplar miRNA families from 42 to 54. Expression analysis indicated that five P. euphratica miRNAs were induced by dehydration stress; bioinformatics prediction showed that the 130 target genes are involved in development, resistance to stress, and other cellular processes. With rice, Oryza sativa, Lv et al. (2010) showed that miRNAs are not only ubiquitous regulators but also involved in cold resistance. The miRNAs were mainly down-regulated and thus their targets, mainly transcription factors, were turned on in response to cold. Also Arabidopsis signaling pathways, such as auxin pathways, were affected by cold-inducible miRNAs (Zhou et al. 2008); there were several common responsive miRNAs in rice and Arabidopsis, but also several miRNAs which were speciesspecific. Furthermore, the common miRNAs were regulated in opposite directions in both species, indicating different regulatory pathways (Table 8.1). From the table, it also becomes obvious that the two best studied plant species have several miRNA families in common which regulate salt responses. The response to low-oxygen conditions also is regulated under involvement of miRNAs. Hypoxia stress associated with natural phenomena such as water logging results in widespread transcriptome changes and a metabolic switch from aerobic respiration to anaerobic fermentation. In root tissue of Arabidopsis thaliana, miRNAs and ta-siRNA play a role in gene regulation and possibly developmental responses to hypoxia, and a major signal for these responses is likely to be dependent on mitochondrial function (Moldovan et al. 2009, 2010). An update of miRNAs affecting plant stress responses is presented in Table 8.1 covering major abiotic stresses such as drought, salt, cold, oxidative stress, hypoxia, and UV-B irradiation as well as nutrient deprivation (sulfate, phosphate, and copper). Do abiotic and biotic stressors activate common miRNAs? Is there so-called cross-talk between these two of challenges? Answers to these questions will provide insight into the evolution of a general stress abatement. Interestingly, SananMishra et al. (2009) discovered that 23 sequences of miRNAs were derived from rice exposed to salt stress while 18 were derived from rice infected with a virus.

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Table 8.1  miRNA families affecting stress response in selected plant species (From Ding et al. 2009; Jia et al. 2009; Moldovan et al. 2009; Sunkar 2010). miRNAs in bold indicate miRNA families with similar or even identical functions in different plant species Arabidopsis Oryza Populus Populus Phaseolus Stressor thaliana sativa trichocarpa tremula vulgaris Zea mays up miR157 miR393 miR393 Drought/ dehydramiR167 miR2118 tion miR168 miR171 miR319 miR393 miR396 miR397 miR408 down miR169 miR1446 miR144 miR1447 miR1450 Salt

up

down

Cold

up

miR156 miR158 miR159 miR165 miR167 miR168 miR169 miR171 miR319 miR393 miR394 miR396 miR398

miR165 miR166 miR169 miR172 miR393 miR396 miR397 miR408

miR169

miR482 miR1450

miR530 miR1445 miR1446 miR1447 miR171l

miR398

miR2118

miR156 miR159 miR160 miR162 miR164 miR166 miR167 miR171 miR319 miR395 miR399 miR156 miR159 miR162 miR166 miR168 miR171 miR319 miR396

miR168 miR477 miR535 miR1435

(continued)

8.1  No Junk: MicroRNAs Table 8.1  (continued) Arabidopsis Oryza Stressor thaliana sativa down

Oxidative stress

up down

Hypoxia

up

217

Populus trichocarpa

Populus tremula

up

miR398 miR156 miR157 miR158 miR159 miR172 miR391 miR775

miR167 miR166 miR171 miR396

miR159 miR395 miR474 miR528 miR156 miR160 miR165 miR166 miR167 miR398a

down

Sulfur

up down

Phosphorus up

Zea mays

miR156 miR475 miR476 miR166 miR167 miR168 miR169 miR319

down

UV-B

Phaseolus vulgaris

miR156 miR160 miR164 miR165 miR166 miR167 miR168 miR398 miR408 miR159 miR169 miR390 miR393 miR395 miR399 miR472

miR395b miR399c miR2111 miR156 miR778 miR827 (continued)

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Table 8.1  (continued) Arabidopsis Oryza Stressor thaliana sativa

Copper

down

miR169 miR395 miR398

up

miR397 miR398 miR408 miR857

miR397 miR398 miR408 miR857

Populus trichocarpa

Populus tremula

Phaseolus vulgaris

Zea mays

miR397 miR398 miR408 miR857d

down Computationally predicted by Zhou et al. (2007) Also central in Medicago truncatula and Panicum virgatum (switchgrass) c  Also central in P-deficient tomatoes d  miR397, miR398, miR408, and miR857 collectively called “the Cu-miRNAs” (Burkhead et al. 2009) a 

b 

A few of these putative miRNAs were common to both. At least two of these miRNAs were up-regulated in response to both abiotic and biotic stresses which suggests a converging functional role of miRNAs in managing various stresses. In maize, a total of 98 miRNAs, from 27 plant miRNA families, had significantly altered expression after salt treatment (Ding et al. 2009). Interestingly, 18 miRNAs were found which were only expressed in the salt-tolerant maize line and 25 miRNAs that showed a delayed regulation pattern in the salt-sensitive line. Overall, saltresponsive miRNAs are involved in the regulation of metabolic, morphological, and physiological adaptations of maize seedlings at the post-transcriptional level.

8.1.2 miRNAs Regulate Animal Responses to Environmental Stresses Increasing evidence suggests that miRNAs have versatile multiple biological functions in animals, although only a few targets of animal miRNAs have been identified and the function of very few miRNAs have been worked out in detail (Zhang et al. 2007). Two members of miRNAs, lin-4 and let-7, regulate developmental timing in C. elegans (Reinhart et al. 2000; Hammell et al. 2009). Loss of function of lin-4 or let-7 resulted in retarded development. Besides animal metabolism, development, and aging (see Chaps. 12 and 13), most studies of miRNAs in animals are devoted to embryonic development, diseases, and cancer (Stefani and Slack 2008). One study identified the role of miRNAs in the freezing tolerance of wood frogs, Rana sylvatica, (Biggar et al. 2009). This species is freeze-tolerant, able to endure the conversion of 65–70% of total body water into extracellular ice as well as the multiple consequences of freezing including large decreases in cell volume and the imposition of anoxia (Storey and Storey 2004). Biggar et  al. (2009) showed that levels of miR-21 increased significantly during freezing in liver and skeletal muscle; miR-16 transcripts also rose significantly in liver of frozen frogs but fell in skeletal

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muscle. This study demonstrated a differential regulation of miRNA species in a freeze-tolerant vertebrate and displayed a mechanism for rapid, yet reversible, gene silencing during animals’ transition into the frozen state. In particular, the freeze responsive changes in miR-21 and miR-16 indicate that these small RNAs have roles in anti-apoptotic and cell cycle regulation in the frozen animal. Regulation of these pathways have profound implications for energy homeostasis in the frozen state by helping to inhibit ATP usage by nonessential energy-expensive cell functions such as cell growth, division, and replacement (Biggar et al. 2009).

8.2 Environmental Stress, Transgenerational Inheritance, and Epigenetics The transfer to offspring of phenotypic traits acquired by the adult parent is an old notion in biology, espoused most famously by Lamarck (1809) and infamously by Lysenko (1948), as Ho and Burggren (2010) phrased. In particular, half a century before Charles Darwin published On the Origin of Species, the French naturalist Jean-Baptiste Lamarck outlined his own theory of evolution. A cornerstone of this was the idea that characteristics acquired during an individual’s lifetime can be passed on to its offspring. In its day, Lamarck’s theory was generally ignored. Now all that is changing. No one is arguing that Lamarck got everything right, but over the past decade it has become increasingly clear that environmental factors, such as diet or stress, can have biological consequences (Young 2008). This means that maternal effects – the environment that mothers provide to their offspring, their provision of nutrients, and the environment that offspring of the same clutch share – have come to be recognized as an important influence on offspring fitness (Carter et al. 2004). The impact on offspring can last for only one to several generations; this means that simple effects, where eggs or embryos get direct stress-response information (proteins, mRNAs) from their mothers or are directly challenged by an environmental stress during their development, clearly differ from true increases in phenotypic diversity by epigenetic mechanisms. However, even a one-generation effect can be epigenetically regulated; this should be proven in each single case separately.

8.2.1 Transgenerational Effects Transgenerational effects have occasionally been reported; the principle shall be exemplified with key examples. 8.2.1.1 Poor Elemental Food Quality as Challenge A mother’s environment can strongly affect her offspring’s viability and fitness. Frost et al. (2010) examined whether phosphorus (P) limitation of the aquatic invertebrate,

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Daphnia magna, altered the responses of its offspring to inadequate P nutrition. Mother Daphnia consuming P-poor algal food produced smaller neonates which had lower body P content compared to control (P-rich) mothers. These offspring from P-stressed mothers, when fed P-rich food, grew faster and reproduced on the same schedule as those from P-sufficient mothers. In contrast, offspring from P-stressed mothers, when fed P-poor food, grew more slowly and had delayed reproduction compared to their sisters born to control mothers and fed P-poor diets. The authors also presented some evidence that daughters from P-stressed mothers were more susceptible to infection by a virulent bacterium. This study showed that P-stress was not only transferred across generations, but also that its effect on offspring varies depending upon the quality of their own environment, such as presence of pathogens. 8.2.1.2 Calorie Restriction as Challenge Life-history alteration in response to food availability, as is commonly observed during periods of famine, is an essential strategy for enabling many organisms to persist in nature. Extension of lifespan by mild food shortage, often mimicked by calorie restriction (CR) in the laboratory, is one of the most common life-history alterations among evolutionarily distinct eukaryotes from single to multicellular organisms. The CR-induced longevity is usually associated with reproductive suppression (yet, see also Chap. 13) and is considered to be a means for postponing reproduction until environmental conditions improve for offspring (Stearns 1992). Although the life-history of offspring often changes in response to the parental environment, it has remained ambiguous whether or not CR-induced longevity is transmitted to the next generation. Recently, Kaneko et al. (2011) investigated the effects of CR on life span, oxidative stress resistance and the expression levels of two antioxidant enzymes (CAT and Mn-SOD) in the parthenogenetic rotifer Brachionus plicatilis during two consecutive generations. Rotifers under CR lived 50% longer than those fed ad libitum (AL) (Fig. 8.1) in association with enhancement of oxidative stress resistance (see Chap. 12) and increased mRNA levels of CAT and Mn-SOD. The daughters of the CR-treated mothers lived 20% longer than those from the mothers fed AL regardless of food-rich and CR conditions for the daughter (Fig. 8.2). Furthermore, the daughters from the CR-treated mothers were endowed at birth with a higher ability to resist oxidative stress and increased mRNA levels for CAT but not for Mn-SOD. In agreement with the mRNA expression patterns, CR increased the protein levels of CAT and Mn-SOD in eggs and the whole body of mothers, respectively. 8.2.1.3 Natural Xenobiotics as Challenge Being chased or even eaten is the ultimate threat for an organism, and it can easily be understood that the resulting information induced by the defense stimulus is passed to the filial generations as just seen with Daphnia. Yet, transgenerational

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Fig. 8.1  Rotifer Brachionus plicatilis: life span, fecundity, and oxidative-stress resistance of mothers cultured under different feeding regimes. (a) Rotifers fed ad libitum (AL) or under calorie restriction (CR), providing food on every other day. Boxes indicate 24 h. (b) The life span (solid line) of the CR group was about 50% longer than that of the AL counterpart. The number of daughters (broken line) of the CR group was significantly lower than that of the AL counterpart (From Kaneko et al. 2011. With permission from Wiley)

effects occur even upon exposure to much more subtle natural environmental stressors, enabling the organism to sustain their population even in strongly fluctuating environment. This has been shown with the cladoceran Moina macrocopa from a puddle in Rio de Janeiro, Brazil. Females were pre-exposed to humic substances (HSs) from dark brown-water coastal lagoons in Rio de Janeiro State for ten generations. Offspring of these humic-treated waterfleas apparently were less sensitive to salt stress in terms of growth responses, because they were significantly larger at primipara than the non-exposed animals (Suhett et al. 2011) (Fig. 8.3). The applied scenario bears clear environmental significance since salt water of the Atlantic Ocean occasionally intrudes into the coastal lagoons. The humic-stress induces a cross-tolerance and, in turn, enables the inhabitants of the coastal lagoons to withstand the occasional osmotic stress (see Chap. 12). Exposure of D. magna females to HSs was an unequivocal stress to which they responded in two ways: they reduced the production of asexual neonates, and they started to asexually produce ephippia which contained nonviable eggs (Bouchnak and Steinberg 2010). Yet the animals had a significantly expanded lifespan (not shown). The production of ephippia followed a concentrationdependent relationship (Fig. 8.4). Exposed P0 females, however, obviously developed

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1.30

1.25 1.20

1.15 1.10

maternal HS exposure

1.35

no maternal HS exposure

Fig. 8.3  Transgenerational increased salt tolerance of females of a Moina macrocopa clone pre-exposed to indigenous humic material (Modified after Suhett et al. 2011; micrograph: credit JM Santangelo, Universidade Federal Rural do Rio de Janeiro)

mm body length at primipara of F1

Fig. 8.2  Brachionus plicatilis: life span and oxidative stress resistance in daughters from ad libitum (AL) and calorie restriction (CR) mothers. The mothers were transferred daily to freshly prepared media, with AL feeding or CR feeding, and their daughters were subjected to the experiment. The different superscripts indicate significant differences. (a) The neonates produced by the AL and CR mothers at the age of 5  days were cultured under AL or CR feeding conditions. (b) Neonates produced by the AL and CR mothers at the age of 5 and 7 days, and cultured each in the medium containing 50 mM paraquat under AL feeding (From Kaneko et al. 2011. With permission from Wiley)

Moina macrocopa

Cumulative mean ephippia number per female

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1

40

0.5

20 10

0

0

7

14

21

28

0

Days

35 5

Cumulative mean ephippia number per female

Fig. 8.4  Exposure of Daphnia magna to humic substances is an environmental stress to mothers (P0 generation), indicated by asexual production of ephippia (humic substance concentrations in mg l−1 HuminFeed® as DOC). The increase of ephippia is concentration dependent (Bouchnak and Steinberg, unpublished)

0.30

20 mg l-1 DOC, HuminFeed ®

P0 F2

0.15

F1 0 0

7

14

21

28

Days Fig. 8.5  Daphnia magna mothers (P0) pass stress resistance to filial generations. Exposure for all generations was identical to 20 mg l−1 HuminFeed®. The exposed daughters from exposed mothers (F1) do not produce ephippia at all, whereas exposed granddaughters from exposed daughters (F2) start to produce ephippia again which are significantly lower in number than their grandmothers. *p < 0.05 (Bouchnak and Steinberg, unpublished)

a stress resistance which was passed to the F1 and F2 females (Fig.  8.5). In F1 females, no ephippia were observed when exposed in the same manner as P0 individuals. Interestingly, this stress resistance was less strong in F2 individuals; they produced an intermediate number of ephippia (Bouchnak and Steinberg, unpublished). Since very recently, the capability of HSs to initiate spontaneous DNA methylation (S Menze and Steinberg unpublished), the underlying mechanism may be an epigenetic one. The acquired stress resistance was also reflected in the production of neonates of the humic-exposed generations. This production increased from P0 to F1 and decreased from F1 to F2; yet the numbers of F2 neonates still exceeded that of P0. In sum, this indicates the stress resistance was not permanent and disappeared

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Mean cumulative offspring per female

500

P0 only exposure*

F1

No exposure

250 Permanent exposure**

0 500

F2

No exposure/P0 only exposure

250 Permanent exposure**

0 0

30

60

90

120

150

Days

Fig. 8.6  Comparison of Daphnia magna neonate numbers of subsequent generations, F1 and F2, if only the mothers/grandmothers (P0) have been exposed to 20 mg l−1 HuminFeed®: succeeding generations benefit from their exposed mother and grandmothers, respectively. The graphs also contain the offspring numbers of females of the three generations, permanently exposed to 20 mg l−1 HuminFeed®; * p <0.05; ** p <0.01(Bouchnak and Steinberg, unpublished)

after a few generations. However, the stress resistance lasted longer than only one generation; hence, a to be detected epigenetic mechanism may also apply; if so, this may be based on the capability of humic substances to spontaneously methylate substrates, as documented by the abiotic formation of methyl mercury (Weber 1993). What happens if only mothers were stressed? In another trial, the neonate production of P0 to F2 of only P0 individuals exposed to humic substances were compared to those of permanently exposed P0 to F2. If only P0 individuals were exposed, the succeeding generations benefited from the stress to the mothers and grandmothers, respectively, because the neonate number of the F1 generation exceeded not only that of the permanently exposed F2 individuals, but also that of the non-exposed ones (Fig. 8.6). Even in the F2 generation, the offspring number was as high as in the non-exposed individuals while still exceeding the numbers of the permanently exposed individuals. Whether or not the described effects are based on epigenetic mechanisms is open to future studies.

8.2.2 Epigenetic Effects The fate of a gene and its product is not defined by the DNA sequence per se, but also by the manner by which the gene is marked and programmed by chromatin

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modification, DNA methylation, and non-coding RNA. Epigenetic programming2 of gene expression is stable and long-term yet reversible and responsive. A change in gene programming by chromatin could have the same impact as a genetic polymorphism leading to either enhancing or silencing of expression of a gene. Thus, interindividual differences in epigenetic marking would result in interindividual phenotypic differences (Szyf et al. 2008). This means that not all lies in stronger activation of the various defense responses that are elicited following attack by either pathogens, predators, or parasites, or in response to abiotic stress. The advantage to the organism in being pre-stressed for particular stress responses is in facilitating a more rapid response if the stress recurs. It provides the benefit of enhanced protection without the costs associated with constitutive expression of stress related genes (van Hulten et al. 2006; Bruce et al. 2007). 8.2.2.1 Epigenetics as Exemplified with Plants Expression of the genome is influenced by chromatin structure which is governed by processes often associated with epigenetic regulation, namely histone variants, histone post-translational modifications, and DNA methylation. Developmental and environmental signals can induce epigenetic modifications in the genome, such as cold in the well understood vernalization phenomenon in plants. Reprogramming of cell differentiation in response to environmental stress leads to phenotypic and developmental plasticity which are important mechanisms of stress resistance. Phenotypic plasticity helps adjust the durations of various phenotypic phases in plants and thus allows plants to avoid exposure of critical growth phases, especially reproductive development, to stress. Retention of stress memory for short durations is well known in plants, as evident from acclimation responses (Thomashow 1999). Recently, Molinier et al. (2006) showed that environmental influences, specifically UV irradiation and a bacterial elicitor, changed the flexibility of the plant genome in somatic tissue of treated plants and in somatic tissue of their progeny. As these influences persist in the entire population of plants, the basis for the change is epigenetic rather than genetic. Indeed, the stress memory can be retained for only short durations if the memory depends on the half-life of stress-induced proteins, RNAs, and metabolites, while the memory can last longer if it involves reprogramming in phenology and morphology of plants. Epigenetic processes, that is stable or heritable DNA

2 Developmental biologist Conrad Waddington coined “epigenetics” in the 1940s as “…the interactions of genes with their environment which bring the phenotype into being.” Holliday and Pugh (1975) proposed that covalent chemical DNA modifications, including methylation of cytosineguanine (CpG) dinucleotides, were the molecular mechanisms behind Waddington’s hypothesis. Further revelations that X inactivation in mammals and genomic imprinting are regulated by epigenetic mechanisms highlighted the heritable nature of epigenetic gene-regulation mechanisms. Therefore, in the 1990s, epigenetics was described as the study of changes in gene expression that occur not by changing the DNA sequence, but by modifying DNA methylation and remodeling chromatin (Jirtle and Skinner 2007).

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methylation and histone modifications, can also be a choice of retaining stress memory for longer times (Chinnusamy and Zhu 2009). Overall, environmental factors can lead to epigenetically-mediated increased genomic flexibility even in successive, untreated generations, and thereby increase the potential for adaptation (Molinier et al. 2006). DNA Methylation Stresses can induce changes in gene expression through hypomethylation or hypermethylation of DNA. In maize, Zea mays, roots, for instance, cold stress-induced expression of a specific transposon-like sequence was correlated with a reduction in methylation in the DNA of the nucleosome core. Even after 7 days of recovery, cold-induced hypomethylation was not restored to the basal level. In tobacco, Nicotiana tabacum, as another example, aluminum, paraquat, salt, and cold stresses induced DNA demethylation in the coding sequence of a glycerophosphodiesteraselike protein (reviewed in Chinnusamy and Zhu 2009). Osmotic stresses induce transient DNA hypermethylation in two heterochromatic loci in tobacco cell-suspension culture. DNA hypermethylation is also induced by drought stress in pea, Pisum sativum. In the common ice plant Mesembryanthemum crystallinum, a facultative halophyte, drought and salt stresses induced a switch in photosynthesis mode from C3 to CAM. This metabolic change was associated with stress-induced-specific hypermethylation of satellite DNA. In addition to the aforementioned mechanisms, transposons also are involved in an epigenetic-mediated stress response. Transposons constitute a significant portion of plant genomes and are maintained in a repressed state by DNA methylation. Environmental factors may activate transposons through DNA demethylation. In the common snapdragon, Antirrhinum majus, cold stress induced hypomethylation and transposition of a specific transposon, Tam-3 (Chinnusamy and Zhu 2009). Stress-induced histone modifications can also influence DNA methylation. For instance, specific histone modification-dependent pathways appear to mediate methylation of about two-thirds of the methylated loci in the Arabidopsis genome (Zhu 2008). Thus, dynamic histone modification marks could be converted into DNA methylation marks which are often more stable. Temperature and other abiotic stresses can regulate gene silencing via RNAi. For instance, low temperature promoted virus-induced gene silencing while high temperature delayed it. Endogenous small interfering RNAs (siRNA)s that are regulated by abiotic stress have been identified in Arabidopsis (Sunkar et al. 2007). In Arabidopsis, a gene silencing via RNA interference has been identified leading to decreased proline degradation and enhanced proline accumulation, both of which confer salt-stress tolerance (Borsani et al. 2005). Stress-induced changes in histone variants, histone N-tail modifications, and DNA methylation have been shown to regulate stress-responsive gene expression and plant development. Transient chromatin modifications mediate acclimation response. Heritable, epigenetic modifications may provide within generation and transgenerational stress memory (Fig. 8.7).

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Primary stress signals: drought, salt, cold, heat, etc. Secondary stress signals: hormones, metabolites (ROS, etc.) Changes in expression and/or activity of epigenetic regulators: small RNAs, RdDM components, histone variants, histone modification enzymes, chromatin remodeling factors Changes in histone variants, histone modifications and DNA methylation Heritable (i.e. epigenetic) changes

Non-heritable changes

Mitotically and meiotically heritable

Mitotically heritable

Reversible stress-responsive gene regulation

Very stable stressindiced gene regulation

Stable stressresponsive gene regulation

Short-term stress resistance, i.e. acclimation

Trangenerational stress memory

Long-term resistance within-generation stress memory Current Opinion in Plant Biology

Fig. 8.7  Epigenetic regulation of stress tolerance in plants. Primary and secondary stress signals induce changes in the expression and/or activity of epigenetic regulators, namely small RNAs, RdDM components, histone variants, histone modification enzymes, and chromatin remodeling factors. These epigenetic regulators modify histone variants, histone modifications, and DNA methylation. Some of these are heritable epigenetic modifications while others are transient changes. Transient chromatin modifications mediate acclimation response. Heritable epigenetic modifications provide within-generation and transgenerational stress memory (From Chinnusamy and Zhu 2009. With permission from Elsevier)

There are commonalities in responses to biotic and abiotic stresses but different terminology is used in the literature. Enhanced responses to biotic stresses come under the category of induced defense, while altered responses to abiotic stresses are referred to as acclimation or hardening (Bruce et al. 2007). In plants, a considerable proportion of DNA methylation marks can be stably transmitted from parents to offspring. Recently, Verhoeven et al. (2010) explored stress-induced methylation variation in apomictic dandelion, Taraxacum officinale, plants. Apomictic dandelions reproduce through unfertilized seeds, and offspring are genetic copies of the mother plant. The dandelion system thus has the advantage

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that epigenetic alterations can be studied in the absence of genetic variation. The following stressors were applied: low nutrients, salt stress, JA application, and SA application. JA and SA are phytohormones involved in herbivore and pathogen defenses, and their application is often used to experimentally mimic biotic attack and to elicit defense pathways. Comparing individual samples with the consensus epigenotype reveals that more methylation changes occurred in each of the nutrient, salt, JA, and SA groups than in the control group in offspring generation 1. Most methylation changes observed in generation 1 were faithfully transmitted to offspring. Only a small proportion reverted to the consensus epigenotype. In generation 2, an additional one to eight methylation changes per group were observed at loci that had not changed in generation 1. It is obvious that ecological stresses promote autonomous, heritable epigenetic variation and, depending on phenotypic effects, this variation is available for natural selection to act upon. Stress effects on methylation patterns were statistically detectable, but it was not typically observed that individual loci showed a consistent methylation change as a result of stress (shared among the majority of replicates), whereas control plants remained unchanged. Rather, there was a subset of inherently unstable loci that were often also polymorphic within the control group, and the effect of stresses was to increase the likelihood that methylation changes occurred at these loci. The functional interpretation of this pattern is unclear. Nevertheless, the study highlighted the potential of epigenetic inheritance to play an independent role in evolutionary processes which is superimposed on the system of genetic inheritance.

8.2.2.2 Predation Defense in Animals and Plants Animals A classical example of phenotypic inheritance is that of induced morphological defenses which have been best studied in animals. Helmet formation in Daphnia cucullata (Fig. 8.8) is a textbook example of cyclomorphosis which is a seasonal variation in morphology, although the mechanisms that maintain this polyphenism have not been adequately demonstrated. Morphological defenses in cladocerans can by induced by chemicals known as kairomones that are released by predators, such as the predaceous cladoceran Leptodora ti, the dipteran phantom midge Chaoborus flavicans, or planktivorous fishes. Agrawal et  al. (1999) exposed D. cucullata females to the kairomone of a predator and measured the relative helmet length in the F1 and F2 offspring. F1 offspring from mothers in the kairomone environment always had larger helmets than offspring from mothers in the control environment (Fig.  8.8b). The same applies to the next generation (F2).

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Fig. 8.8  (a) Scanning electron micrograph showing typical (right) and predator-induced morphs (left) of Daphnia cucullata of the same clone. (b) Relative helmet length of F1 and F2 generation of D. cucullata (Modified from Agrawal et  al. 1999. With permission from Nature). Kairomoneexposed females pass the property of long helmet formation to their F1 as well as F2 brood. In these individuals, the relative helmet length grows when they mature. In contrast to this, the offspring of non-exposed females possess only relatively short helmets whose relative lengths decrease when the individuals mature

Plants Remember Predation Threat Phenotypicly imprinted transgenerational defense mechanisms against predation as shown above with Daphnia are by no means restricted to animals. For one plant species, Agrawal et  al. (1999) showed that non-lethal exposure of wild radish, Raphanus raphanistrum, to a herbivore not only induced a defense but caused the attacked radish to produce offspring that are better defended against herbivores than offspring from unthreatened parents. Caterpillars feeding on the F1 generation of seedlings from maternal plants which were subject to herbivory by Pieris rapae gained 20% less weight than those feeding on seedlings whose parents were not damaged. This effect is most probably due to specific defensive chemicals, particularly glucosinolates. Yet, even induced morphological defenses seem to appear in phototrophs. It is well known that phytoplankton algae are able to withstand grazing pressure of zooplankton by various responses in morphology, life-history, and behavior (Lass and Spaak 2003). The most obvious mechanism is through changes in morphological features such as size and cell wall shape. For instance, inducible colony formation is a common adaptive response of many coccal green algae to the threat of herbivory (Lürling 2003; Verschoor et al. 2004).

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Recently, Verschoor et al. (2009) discovered that colony formation in Scenedesmus obliquus lasts for several generations even after the predator stress had been terminated. In mesocosms as well as in laboratory bioassays, the authors found that the relaxation of the defense mechanism (disintegration of colonies) took 8–15 days with the longer period in the mesocosms. This difference can most likely be explained by slowly-degrading herbivore-excreted infochemicals still present after extinction of the rotifers. Yet, this did not apply to the bioassays; they were free of infochemicals. Hence, kairomone-stressed S. obliquus passed its phenotype to several filial generations – a transgenerational effect. This effect was light-dependent, hence, active photosynthesis seemed to be a prerequisite for colonies to retain their forms. Also the development of defense structures in/on the cell wall appears to have a memory effect. Overall, kairomones of Daphnia can induce spine development and colony formation in Scenedesmus and colony formation in Desmodesmus (Lürling 2003).

8.2.3 Environment and Epigenetic Mechanisms Even with biologists, environment is not defined in the same way. If ecologists and ecotoxicologists use this term, they refer to terrestrial and aquatic ecosystems. If developmental biologists use the word, the often mean the maternal environment of a fertilized egg and embryo or food taken up from the environment. If molecular biologists use the term, they may think of the intracellular environment of the DNA. There is not only a gap but a huge canyon between the different biological disciplines. Consequently, the concepts of environmental cues vary greatly. Many laboratory studies which prove epigenetic mechanisms use high concentrations, for instance, of methyl donors or chemicals that compromise HSP90. On the other hand, ecologists and ecotoxicologists stop when they have identified a transgenerational effect of a chemical exposure and do not go into mechanistic details. Due to different methodologies and scales, epigenetics currently starts to step into the real environments, particularly the aquatic ones. One classical example of epigenetic control of ecological processes is the vernalization reaction of terrestrial plants (Burn et al. 1993). Flowering and seed development are crucial for plant reproduction. Hence, plants have evolved mechanisms to flower when environmental conditions are appropriate. Vernalization is a quantitative response to low-temperature exposure that causes progressively earlier flowering. It represents a physiological response to environmental stimuli that establishes an appropriate gene expression by altering the epigenetic state of the genome via DNA methylation (Jaenisch and Bird 2003). In particular, Burn et al. (1993) showed that late-flowering ecotypes of Arabidopsis thaliana flower early after cold treatment. Treatment with a DNA demethylating agent induced non-vernalized plants to flower earlier than untreated controls. That is to say that vernalization is combined with a reduction of DNA methylation. Because the low temperature that induces vernalization also provoke cold acclimation, some of the gene expression programs could be under common epigenetic control (Chinnusamy and Zhu 2009).

8.2  Environmental Stress, Transgenerational Inheritance, and Epigenetics Fig. 8.9  Reaction schemes of cytosine methylation

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Methyl donor NH2

NH2 H 3C

N NH

O

DNA methytransferase

N NH

O

8.2.3.1 Mechanisms The epigenome consists of chromatin and its modifications as well as a covalent modification by methylation of cytosine rings found at the dinucleotide sequence CpG. The epigenome determines the accessibility of the transcription machinery which transcribes the genes into messenger RNA. Inaccessible genes are therefore silent, whereas accessible genes are transcribed (Szyf et al. 2008). Research over the past decade has focused on two molecular mechanisms that mediate epigenetic phenomena: DNA methylation and histon modification. Histon proteins are the basic building blocks of chromatin. DNA Methylation, Histone Methylation and Acetylation DNA methylation involves the addition of a methyl group to the 5 position of cytosine (one of the four bases of DNA) which occurs in animals in the context of CpG (cytosine followed by guanine) dinucleotides, whereas in plants the position is somewhat more flexible. This modification can be inherited through cell division. DNA methylation is typically removed during zygote formation and reestablished through successive cell divisions during development. DNA methylation is a crucial part of normal organismal development and cellular differentiation in higher organisms. DNA methylation stably alters the gene expression pattern in cells. Common wisdom was that once DNA methylation patterns were formed during development, they remained stable thereafter (Razin and Riggs 1980). This classical model predicted that any epigenetic variations would form exclusively during gestation but not later in life. Recent data imply that environmental exposures might alter the epigenome after birth, supporting the hypothesis that DNA methylation and chromatin modification machineries (Fig. 8.9) remain active and dynamic throughout life, even in post-mitotic cells (Szyf et al. 2008). DNA methylation, histone acetylation and deacetylation, and histone methylation all work together to build up chromatin structures which coordinately may shift from a transcriptional permissive state to a transcriptional inactive state and vice versa (Fig. 8.10). Genes are inactivated when the chromatin is condensed, and they can be transcribed when the chromatin is opened (relaxed). In addition to these mechanisms, siRNAs target several molecules, for instance DNA methyltransferase itself, and prevents cytosine methylation and maintains the accessibility of the gene for transcription factors.

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Fig. 8.10  Close interactions between DNA methylation and histone modifications. (a) Relaxed chromatin is accessible for transcription factors (TFs). Chemical modifications (green) on the core histones (yellow) result in a relaxed chromatin structure. (b) DNA methyltransferases (DNMTs) add methyl groups (grey triangle) to CpG dinucleotides, resulting in gene silencing that can affect the former modification of the histones. (c) The chemical modification (red) to the core histone results in a condensed and inactive chromatin structure. TFs are sterically hindered and cannot bind to their recognition sequence on the DNA (From Strietholt et al. 2008. Courtesy of BioMed Central)

Further Chromatin Modification Besides DNA methylation and chromatin acetylation, another mechanism of chromatin modification is the role of heat-shock proteins as “capacitors” of morphological change. In general, this epigenetic regulatory pathway has garnered less attention than other chromatin modifications. Yet, it is well understood that the heat-shock protein HSP90 is not always required for protein folding, but it is linked to proteins that control cell growth during development. Rutherford and Lindquist (1998) surveyed the properties of the fruitfly Drosophila with impaired HSP90 function and showed that almost any resultant body structure can be altered. The idea is that HSP90 normally buffers the organism against a variety of developmental disruption sources. This may yield as a side effect the accumulation of genetic variation that can be expressed once the “capacitor” is inactivated. While most of the novel phenotypes will likely be maladaptive, their frequency and variety may boost the chances of natural selection to find a new route through the current adaptive landscape (Pigliucci 2003).

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Further Mechanisms Besides epigenetic mechanisms, stress resistance may also involve accumulation of signaling proteins and/or transcription factors. Signaling proteins may accumulate in an inactive configuration that is activated upon exposure to stress, perhaps by a protein kinase being triggered by changes in calcium levels. Activation of heatshock proteins might also occur in a similar way. It has also been suggested that there could be accumulation of transcription factors in primed plants that enhance defense gene transcription after stress recognition (Bruce et al. 2007). The global stress expression data set provided by Kilian et al. (2007) suggests that the observed accumulation of the transcriptional regulators is the result, and not the cause, of the initial transcriptional reaction. 8.2.3.2 HSP90 as Capacitor of Phenotypic Traits Among the major heat-shock proteins, HSP90 is unique in its functions. It is not required for the in  vivo maturation or maintenance of most proteins. Most of its many identified cellular targets are signal transducers, that is cell-cycle and developmental regulators whose conformational instability is relevant to their roles as molecular switches (Rutherford and Lindquist 1998). Studies of yeast illustrate the specificity of HSP90: at normal temperatures, reductions in HSP90 levels that have no apparent effects on cell growth or metabolism can completely abolish signaling through HSP90-dependent pathways. Conditions that cause general protein damage can divert HSP90 from its normal targets to other partially denatured proteins. Because of its dual involvement with inherently unstable signal transducers on the one hand and with the cellular response to stress on the other, HSP90 may link developmental programs to environmental contingency. In their seminal laboratory study, Rutherford and Lindquist (1998) reported that when Drosophila HSP90 was mutant or pharmacologically impaired, phenotypic variation affecting nearly any adult structure was produced, with specific variants depending on the genetic background and occurring both in laboratory strains and in wild populations. Multiple, previously silent, genetic determinants produced these variants and, when enriched by selection, they rapidly became independent of the HSP90 mutation. Therefore, widespread variation affecting morphogenic pathways exists in nature but is usually silent. HSP90 buffers this variation, allowing it to accumulate under neutral conditions. When HSP90 buffering is compromised, for example by temperature, cryptic variants are expressed and selection can lead to the continued expression of these traits, even when HSP90 function is restored (Fig. 8.11). This provides a plausible mechanism for promoting evolutionary change in otherwise entrenched developmental processes. In her commentary, McLaren (1999) asked how widespread is the effect described above and refers to some convincing examples. For instance, the HSP90mediated canalization could probably be the explanation of the heritable changes

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Fig. 8.11  Exposing cryptic genetic variation (a) When heat-shock protein HSP90 is expressed at the normal level, wild-type Drosophila with a normal phenotype develop (indicated by only the wild-type fly being in the white area). Numerous cryptic variations are suppressed by the buffering action of HSP90 (grey area). (b) When the level of HSP90 is reduced by gene targeting, by drug treatment, or by heat treatment, cryptic variations are no longer suppressed, and mutant flies develop (white area). These mutants can be subject to selection. (c) After several generations of selection (in this case, for flies with deformed legs), mutant flies develop even when HSP90 is restored to its normal level (white area). Many cryptic variations are again suppressed. Development has been shifted to a new pathway, that is, a change of canalization (From McLaren 1999. With permission from Elsevier)

in a classical experiment in which chemical fertilizer changed the phenotype (Fig. 8.12). When the size was doubled or halved, the plants bred true, but those that were less affected retained their plasticity. Perhaps the plants that reacted more drastically to the fertilizer treatments were expressing cryptic genetic variation that shifted development into a new channel, with a new target for the homeostatic buffering effect of signal-transduction chaperones. Similar results have been obtained more recently with tobacco as well as with flax, involving specific DNA alterations as well as phenotypic changes. Another key example: 18 generations of selection for tameness in foxes resulted not only in heritable variations in the normal reproductive pattern but also in the appearance of new morphological characters (tail curling, spotting, pigmentation changes). These were postulated to be due to the activation of “dormant” alleles, activated by the stress of destabilizing selection. In flour beetles, it was shown that the destabilizing effect of distant hybridization (deformed appendages, changes in sex ratio and size) was uncovering genetic variation that preexisted within species but was concealed by homeostasis. “The lens of hybridization”, they concluded, “magnifies segregating genetic differences within species” (Wade et al. 1997). McLaren (1999) concludes that these examples attest to the generality of the phenomenon that plant and animal breeders have exploited for centuries and that Rutherford and Lindquist (1998) have explained for the first time in molecular terms – namely that genetic or environmental stress can produce heritable developmental changes. If this canalization occurs even in populations under environmental realistic stresses, it is still a matter of intense discussion since several authors mention that they are unaware of any concrete examples of this potentially important phenomenon (Morgan et al. 2007; Sgrò et al. 2010), but the possibility of its

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Fig. 8.12  Heritable changes caused by environmental stress. Fourth generation plants of two extreme types of flax induced by different fertilizer treatments in the parental generation (From McLaren 1999. With permission from Elsevier)

existence should be recognized. Furthermore, Milton et al. (2003) and Debat et al. (2006) found that a reduction of HSP90 activity did not affect phenotypic variation. Very recently, Takahashi et al. (2010) discovered that several small HSP genes showed involvement in the process of morphogenesis and developmental stability of Drosophila. The genes studied were knocked down rather than the concerning proteins compromised by environmentally realistic stresses. Due to possible different functions in terms of developmental buffering of these small HSPs, phenotypic stability of an organism is probably maintained by multiple mechanisms instead of by HSP90 alone, triggered by different environment stresses. Manitašević et al. (2007) published an intriguing paper on wild dwarf sword lily Iris pumila and showed that even natural stressors can compromise HSP90. The authors studied the seasonal variation in HSP90 expression in the leaves of two naturally growing I. pumila populations, one inhabiting an open dune site, and the other the understory of a Pinus sylvestris stand (also see Chap. 14). The level of the HSP90 was found to vary significantly both across seasons and between habitats. Two HSP90 isoforms, referred to as HSP90a (86 kDa) and HSP90b (84 kDa), were detected. At both habitats, the level of HSP90a was highest in autumn, that of HSP90b in spring, whereas both of them reached a nadir in summer. Throughout the growing season, the relative abundance of HSP90b was higher in plants growing

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Fig. 8.13  Relationship between Hsp90b level and specific leaf area variation in the dwarf sword lily Iris pumila. The mean relative HSP90b level (line) and the mean coefficient of variation (CV %) in specific leaf area (SLA) (bars) through seasons in Iris pumila plants naturally growing at an exposed (a) and a shaded (b) habitat are presented. (From Manitašević et al. 2007. With permission from Wiley)

under vegetation canopy in comparison to those inhabiting the open dune site (Fig. 8.13). An inverse relationship between the phenotypic variation in specific leaf area and the level of HSP90b over seasons at both habitats was observed, indicating the role of this protein in buffering phenotypic variation in the wild. Furthermore, also the floral organ plasticity in response to micro-environmental variation was greater with decrease in HSP90b isoform expression (Tucić et al. 2008). It is open to future cross-transplantation studies to identify whether or not this effect is even transgenerational. By applying the classical HSP90-inhibitor geldanamycin, Sollars et al. (2003) have convincingly shown that compromising HSP90 opens the path for morphological evolution. Using a sensitized isogenic D. melanogaster strain, the authors presented evidence supporting an epigenetic mechanism for HSP90’s capacitor function, whereby reduced activity of HSP90 induced a heritably altered chromatin state. The altered chromatin state was evidenced by ectopic expression of abnormal eye phenotype which was epigenetically heritable in subsequent generations, even when function of HSP90 was restored. Mutations in nine different genes that encode

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chromatin-remodeling proteins also induce the abnormal phenotype. One mutation, verthandi3 (vtd3), caused the highest frequency of ectopic outgrowth and was evident in several filial generations. Overall, these findings suggested that HSP90 acts as a capacitor for morphological evolution through epigenetic and genetic mechanisms. In evolutionary terms, this means that a potentially adaptive phenotype could be fixed very rapidly via epigenetic mechanisms without having to wait for the proper genetic variation to arise. The resulting evolutionary change is both more rapid and less stable, which means that it can easily be reversed should the environmental conditions call for it (Pigliucci 2003). 8.2.3.3 HSP90 and Piwi-Interacting RNA We have learned that the HSP90 chaperone machinery may be an evolutionary conserved buffering mechanism of phenotypic variance which provides the genetic material for natural selection. Recently, Specchia et al. (2010) showed that, in Drosophila, geldanamycin-medicated functional alterations of HSP90 affect the piRNA silencing mechanism leading to transposon activation. In other words, Piwi suppresses genetic variation or, vice versa, loss of Piwi3 causes transposon mobilization. This in turn induces de novo gene mutations that affect the development pathways and that can be expressed and fixed across subsequent generations. More recently, Gangaraju et al. (2011) show that Piwi also suppresses epigenetic variation and forms a protein complex with HSP90. They provide evidence for a model in which Piwi functions as an adaptively inducible canalizer to both suppress transposon-mediated mutagenesis and suppress epigenetic variation. These findings make clear that epigenetic and mutagenic processes are not an alternative to genetic adaptation. Rather, they are mechanisms induced in response to some stimulus, and the changes can potentially be transmitted across generations. Thus, there is a need for a synthesis that incorporates the range of responses an organism makes to environmental change. The theory should take into account genetic and epigenetic adaptation, the timescales of these processes, the potential for reversibility and the interplay between individual and population processes (Ruden 2011). 8.2.3.4 Stress by Environmental Chemicals Induces Epigenetic Changes Heavy metals and synthetic xenobiotics also may induce epigenetic and transgenerational effects – with ambiguous results. Well understood is the impact of Ni as a potent human carcinogen that has been shown to alter DNA methylation patterns and affect histone acetylation status. Both of these changes are associated with the proximity of the affected regions to heterochromatin. The two processes probably

Piwi genes encode regulatory proteins responsible for maintaining incomplete differentiation in stem cells and maintaining the stability of cell division in germ line. 3

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occur in concert in mammalian cells. However, in yeast cells, DNA methylation is absent, and Ni is capable of regulating gene expression through changes in acetylation of the lysine residues in the N terminal tail of histone H4. Arsenic, As, is another important environmental carcinogen, and it is methylated during its metabolism. Hence, it has been proposed that As metabolism may deplete intracellular methyl group stores and thereby lead to changes in DNA methylation that may be involved in carcinogenesis. However, the data concerning DNA methylation changes following arsenic exposure are equivocal, leading researchers to propose that DNA hypo- and hypermethylation are both important in the development of As-induced cancers in humans (Sutherland and Costa 2003; Salnikow and Zhitkovich 2008). Comparable studies on ecological subjects are in their infancy but open promising outlooks in ecology. In a few cases, the sensitivity of the exposed animals decreases in subsequent generations as shown, for instance, in Daphnia magna with pharmaceuticals (b-adrenergic blockers) (Dzialowski et  al. 2006). Very recently, DNA methylation has been detected in D. magna (Vandegehuchte et  al. 2009a). This indicates the possible presence of epigenetic mechanisms regulating gene expression in this species. As such, effects of transient chemical exposure could be transferred through epigenetic inheritance to non-exposed generations. Vandegehuchte et al. (2009b) report a decrease in DNA methylation in the first nonexposed generation of offspring which was not detected in the next generation. In a most recent study, in Zn-exposed daphnids, a large number of genes were found to be differentially transcribed, including transcription and translation related genes (down-regulated), genes associated with oxidative stress (up-regulated), and different types of metabolism-related genes (mostly up-regulated). In the two subsequent generations of non-exposed daphnids, a considerable number of differentially regulated genes were observed, indicating an effect of Zn-exposure in the non-exposed progeny. However, none of the differentially transcribed genes observed in the Zn-exposed generation were regulated in the same direction in both non-exposed subsequent generations. The exposure of D. magna to a sublethal Zn concentration for one generation did not result in a stable transgenerational epigenetic effect with consequences for reproductive output nor was a stably epigenetically inheritable effect observed on the transcription of any of the studied genes (Vandegehuchte et al. 2010). Two examples will elucidate the adverse as well as the beneficial results of animals exposed the synthetic xenobiotics. The example with an adverse result is the action of endocrine disrupting chemicals in fishes; that one with a beneficial overall result is the smart behavior of the euryhaline killifish Fundulus heteroclitus. Obviously, different mechanisms of chromatin modification seem to apply for endocrine disruptors and the Superfund sites with contaminations of persistent organic chemicals. Evidence that epigenetic variation plays a fundamental role in adaptation to rapidly changing environmental conditions comes from Ruden et al. (2005). These authors characterize one HSP90-mediated mechanism in mammals: this protein maintains several nuclear hormone receptors, such as the estrogen receptor, as agonist-receptive monomers in the cytoplasm. In the presence of an agonist, HSP90 dissociates and the receptors dimerize, enter the nucleus and ultimately activate

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transcription of the target genes. In addition to this function, HSP90 also has a role in modifying the chromatin conformation of many genes. For example, HSP90 has been shown to increase the activity of a specific methyltransferase which activates the chromatin of target genes. Further evidence for chromatin-remodeling functions is that HSP90 acts as a capacitor for morphological evolution by masking epigenetic variation. Release of the capacitor function of HSP90, such as by environmental stress or by drugs that inhibit the ATP-binding activity of HSP90, exposes previously hidden morphological phenotypes in the next generation and for several generations thereafter. In this review, the authors discuss that the transgenerational effects of diethylstilbestrol (DES), a synthetic estrogen which caused uterine abnormalities and cancer in human females, is mediated via HSP90 (Ruden et al. 2005). The synthetic estrogen DES also affected lower vertebrates, as shown with the Chinese rare minnow, Gobiocypris rarus, by Zhong et al. (2005). Interestingly, a transgenerational effect was observed in that the sex steroid homeostasis has been disturbed in both male and female progeny: parental DES exposure significantly decreased testosterone level in male progeny and slightly elevated estradiol in female offspring. It seems very plausible that this disturbance of hormone homeostasis also has been facilitated via the HSP90 mechanisms. Nonylphenol also caused a transgenerational disturbance of sexual hormone homeostasis in fish, with decreased testosterone levels in males and increased ones in females (Schwaiger et  al. 2002); yet, whether or not this hypothesized epigenetic pathway generally applies for endocrine disruptors, the idea is an exciting area of future research. Also with endocrine disrupting chemicals, Aniagu et  al. (2008) showed that another epigenetic mechanism may apply, namely DNA methylation. The authors studied the response of the three-spine stickleback, Gasterosteus aculeatus, to exposure to 17-b-estradiol and 5-aza 2¢deoxycytidin (5AdC), a well known methylation inhibitor as a positive control. 5AdC significantly lowered hepatic global methylation levels in these fish. The natural estrogen and potential carcinogen, 17-b-estradiol, also decreased global DNA methylation levels in female liver, but this effect was not statistically significant. In contrast, both estradiol and 5AdC caused statistically significant global genomic hypermethylation in the gonads of male sticklebacks while the increase seen in the female gonads was not statistically significant. Since this paper focused on the tumor-promoting potential of estradiol, the authors unfortunately did not study the heritability of this methylation pattern to successive generations. In Chap. 4, we came across the smart behavior of the euryhaline mummichog, F. heteroclitus (Atlantic killifish). In particular, natural populations of this teleost fish tolerate a broad range of environmental conditions, including temperature, salinity, hypoxia, and chemical pollutants (Meyer and Di Giulio 2003; Fisher and Oleksiak 2007). Strikingly, populations of F. heteroclitus inhabit and have adapted to highly polluted Superfund sites that are contaminated with persistent toxic chemicals. These natural populations provide a foundation to discover critical gene pathways that have evolved in a complex natural environment in response to anthropogenic environmental stressors.

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The mummichog population which inhabits a creosote-contaminated Superfund site on the Elizabeth River (Virginia, USA) exhibited a lack of induction of cytochrome P4501A (CYP1A) mRNA, immunodetectable protein, and catalytic activity after exposure to typical inducers. This “refractory CYP1A phenotype” could not be explained by alterations in mRNA expression of known CYP1A transcription factors. Furthermore, the refractory phenotype has been lost progressively during development in laboratory-reared F1 generation fish. Thus, while heritable, the refractory CYP1A phenotype did not appear to be genetically based but epigenetically mediated. To test the hypothesis that cytosine methylation at CpG sites in the promoter region of CYP1A underlies the refractory CYP1A phenotype, TimmeLaragy et al. (2005) compared the methylation status of CpG sites in the CYP1A promoter region of DNA from killifish from the Elizabeth River and a reference site. The authors examined genomic DNA both from livers of wild-caught adult killifish and from pools of F1 generation embryos raised in the laboratory. In fish from both the contaminated and the reference site, cytosine methylation was not detectable at any of the 34 CpG sites examined. This means that the potential epigenetic regulatory pathways does not obviously take place via DNA methylation of the specific gene. If CpG methylation is not responsible for the persistent but impermanent lack of CYP1A inducibility in Elizabeth River killifish, it is possible that some other epigenetic mechanism must be responsible, such as histone modification, endogenous RNA interference, or RNA degradation. Fisher and Oleksiak (2007) discovered one potential alternative mechanism. They used Fundulus cDNA arrays to compare metabolic gene expression patterns in the brains of individuals among nine populations: three independent, polluted Superfund populations and two genetically similar reference populations for each Superfund population. The most striking result has been that one of the most strongly induced genes is that which codes for a betaine-homocysteine methyltransferase. This is a zinc metallo-enzyme that catalyzes the transfer of a methyl group from betaine to homocysteine to produce dimethylglycine and methionine respectively. Likely that methionine, in turn, can donate the methyl group to methylate DNA, proteins, lipids, and other intracellular metabolites. Although the specific regulatory pathway for the lack of induction of CYP1A remains obscure, it is likely to be a more indirect rather than a direct methylation of DNA. In another study, Williams and Oleksiak (2008) provided evidence that the populations of F. heteroclitus which flourish in the heavily polluted and geographically separated Superfund sites have independently evolved adaptative resistance to chemical pollutants. In these polluted populations, natural selection has altered allele frequencies of loci that affect fitness or that are linked to these loci. The few shared loci among polluted sites indicate that selection may be acting on multiple loci involved in adaptation, and loci shared between polluted sites potentially are involved in a generalized adaptive response. Due to the bias on genetics in the past decades, epigenetics has not been considered properly. However, epigenetically controlled transgenerational effects, in order to cope with a problematic or fluctuating environments, are not only a scientifically challenging issue but probably occur much more often in the environment than anticipated so far and open the door to a new field of functional ecology.

Chapter 9

The Actual Response: Ecological Proteomics and Metabolomics

9.1 Basics of Proteomics and Metabolomics Whereas transcriptomics mirrors the potential of an organism to respond to an ­environmental challenge, proteomics combined with metabolomics indicate the prevailing defense pathways. Proteomics is the large-scale study of proteins, particularly their expression levels and functions. Environmental metabolomics is the application of metabolomics to characterize the interactions of organisms with their environment. These interactions can be studied from individuals to populations which can be related to the traditional fields of ecophysiology and ecology and from instantaneous effects to those over evolutionary time scales, the latter enabling studies of genetic adaptation (Bundy et al. 2009). Usually, metabolomics comprises the study of profiles of small-molecule metabolites which are the end products of cellular processes. Thus, while mRNA gene expression data and proteomic analyses do not tell the whole story of what might be happening in a cell, metabolic profiling can give an instantaneous snapshot of the physiology of that cell. In the following chapters, proteomics and metabolomics will be jointly dealt with. One principle result of proteomics is shown in Fig. 9.1. As challenge to the blue mussel, Mytilus edulis, the authors lowered the ambient salinity from 6 to 3 parts per 1,000 (ppt) and found that this treatment caused a protein expression signature of 26 protein spots: 17 were specifically induced, whereas 9 were repressed. By comparing the protein expression signatures of different stressors, Shepard et al. (2000) identified that different signatures were found for each stressor and different sets of repressed proteins. In many but not all cases, both types of biomarkers mutually correlate. In the example shown in Fig. 9.2, biochemical biomarkers were compared with their gene expression counterparts in liver samples from the Ebro barbel, Barbus graellsii. Whereas EROD enzymatic activity correlated with expression of the CYP1A gene which encompasses the cytochrome P450 responsible for this enzymatic activity (top panel), no significant correlation was found in the same samples between ­metallothionein levels and the expression of the corresponding gene (bottom panel) (Piña et al. 2007). C.E.W. Steinberg, Stress Ecology: Environmental Stress as Ecological Driving Force and Key Player in Evolution, DOI 10.1007/978-94-007-2072-5_9, © Springer Science+Business Media B.V. 2012

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Fig. 9.1  Two-dimensional gel separation of whole-body homogenate proteins from Mytilus edulis exposed to lowered salinity (6–3 ppt). Composite gels were produced using spots found on 75% of eight gels from four individuals per treatment. Key proteins repressed (absent on treatment gel) are denoted with circles and induced (absent on control gel) are denoted by squares. (a) control composite with proteins repressed only by lowered salinity and (b) salinity composite with proteins induced by lowered salinity (From Shepard et al. 2000. With permission from Elsevier)

For the detection of metabolites, highly resolving gas chromatographic (GC c­ oupled with mass spectrometry) as well as nuclear-magnetic resonance (NMR) techniques are methods of choice. One example of a 1H-NMR fingerprint analysis is presented in Fig. 9.3. Salt cress, Thellungiella halophila, a Brassicaceae species closely related to Arabidopsis thaliana, is tolerant to high salinity. The two species were compared under conditions of osmotic stress (Lugan et al. 2010). Overall, the same metabolic pathways were regulated by salt stress in both species. The main difference was quantitative: Thellungiella had much higher levels of most metabolites than Arabidopsis in all treatments.

9.2 Minimal Stress Response Kültz (2005) defines the cellular stress response as a defined set of cellular ­functions, including cell cycle control, protein chaperoning and repair, DNA and chromatin stabilization and repair, removal of damaged proteins, and certain

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Fig. 9.2  Correlation between mRNA expression and protein content or enzymatic activity in the freshwater fish Barbus graellsii: EROD activity and CYP1A expression levels (top) and MT protein and mRNA expression (bottom) (Piña et al. 2007. With permission from Elsevier)

aspects of ­metabolism. Proteins involved in key aspects of the cellular stress response are ­conserved in all organisms. Major proteins ubiquitously conserved in all three domains are listed in Table 9.1. Cells with chronic stress exposure constitutively express several stress proteins at very high levels, including HSP60, HSP70, peroxiredoxin, and superoxide dismutase in mammalian renal inner ­medullary cells and RecA/Rad51 in the extremophile archaeon Pyrococcus furiosus. Functionally, the 44 stress proteins cluster into distinct categories that reflect different aspects of the cellular stress response. They include redox-sensitive proteins as well as proteins involved in sensing, repairing, and minimizing macromolecular damage, such as molecular chaperones and DNA repair enzymes. In addition, numerous enzymes (notably oxidoreductases) that are involved in energy metabolism and cellular redox regulation are part of the minimal stress proteome. Some conserved stress proteins also function in cell cycle control (HSP60, FtsH, and ribosomal RNA methyltransferase). Notably, not all aspects of the cellular stress response, in particular signaling-related mechanisms, are based on ubiquitously conserved pathways and proteins.

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Fig. 9.3  Arabidopsis and Thellungiella challenged by salt. 1 H-NMR fingerprints of shoot extracts show that Arabidopsis and Thellungiella mainly differ in the abundance of metabolites (1 fumarate; 2 sucrose; 3 & 4 glucose; 5 malate; 6 proline; 7 choline; 8 malate and citrate; 9 proline; 10 glutamine; 11 glutamate and quinate; 12 GABA; 13 alanine; 14 threonine; 15 fatty acids, valine, leucine and isoleucine; is, internal standard) (From Lugan et al. 2010. With permission from Wiley)

Eukaryotes and prokaryotes differ in the nature of phosphorylation-based signal transduction. Two-component systems based on His/Asp phosphorylation predominate in prokaryotes, whereas more complex eukaryotic signaling cascades are mainly based on Ser/Thr/Tyr phosphorylation. Second, DNA in eukaryotes is packaged into a nucleus which is absent in prokaryotes, and the degree of packaging is higher because eukaryotic genomes are generally larger. Thus, chromatin organization is more complex, and histones and other chromatin proteins have unique roles in eukaryotes. Consequently, eukaryotic mechanisms of transcriptional regulation and cell cycle control are more complex and depend on proteins that differ from those utilized for equivalent functions in bacteria (Kültz 2005). The proper stress response of an exposed organism not only depends on the modulation of transcriptional activity of stress-related genes but also on the stability of the produced proteins. Beyond protein phosphorylation, other posttranslational modifications like ubiquitination and SUMOylation regulate the activation of preexisting molecules to ensure a prompt response to stress (Mazzucotelli et al. 2008). Ubiquitination refers to the post-translational modification of a protein by the covalent attachment of one or more ubiquitin monomers. Ubiquitin is a small, highlyconserved regulatory protein that is ubiquitously (that is, universally) expressed in eukaryotes. The most prominent function of ubiquitination is the labeling of proteins for degradation. Inactive proteins (i.e., incorrect folding) and proteins which are no longer required for cell function are tagged by ubiquitin for proteolysis.

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Table 9.1  The minimal stress proteome of cellular organisms (From Kültz 2005. Courtesy of Annual Reviews Inc.) DNA damage sensing/ Fatty acid/lipid Redox regulation repair metabolism Aldehyde reductase MutS/MSH Long-chain fatty acid ABC transporter Glutathione reductase MutL/MLH Multifunctional beta oxidation protein Thioredoxin Topoisomerase I/III Long-chain fatty acid CoA ligase Peroxiredoxin RecA/Rad51 Superoxide dismutase MsrA/PMSR SelB

Molecular chaperones Petidyl-prolyl isomerase

Proline oxidase a

DnaJ/HSP40

Quinone oxidoreductase c

GrpE (HSP70 cofactor)

NADP-dependent oxidoreductase YMN1 c Putative oxidoreductase YIM4 c

HSP60 chaperonin d

Energy metabolism Citrate synthase (Krebs cycle) Ca2+/Mg2+-transporting ATPase b Ribosomal RNA methyltransferase d Enolase (glycolysis)

DnaK/HSP70

Phosphoglucomutase

Protein degradation FtsH/proteasomeregulatory subunit d Lon protease/protease La

Other functions Inositol monophosphatase b

Aldehyde dehydrogenase c Isocitrate dehydrogenase c Succinate semialdehyde dehydrogenase c 6 phosphogluconate dehydrogenase c Glycerol-3-phosphate dehydrogenasec

Serine protease

Nucleoside diphosphate kinase e Hypothetical protein YKP1

2-hydroxyacid dehydrogenasec

Protease H/prolyl endopeptidase Hydroxyacylglutathione Aromatic amino acid hydrolase aminotransferase Aminobutyrate aminotransferase a Proline oxidase degrades proline to pyrroline 5-carboxylate, hence it is also involved in amino acid degradation b Signaling functions (Ca2+- and phosphoionitide-mediated) c Many oxidoreductases are also important for energy metabolism d These proteins are also involved in cell cycle control e Involved in nucleotide synthesis (possible role in DNA repair)

Transcriptome and proteome analyses carried out in, for instance, different plant species following exposure to abiotic stresses indicated that hundreds of ubiquitination-related transcripts/proteins were modified during stress responses, suggesting a role for ubiquitination in determining stress tolerance. The network of post-transcriptional and post-translational modifications ensures temporally and spatially appropriate patterns of downstream stress-related

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Fig. 9.4  Model describing the cross-talk among post-transcriptional (mRNA level) and posttranslational (protein level) regulations involved in the control of plant response to abiotic stress. Cross-hatched arrows indicate connections not yet reported in plants but suspected by evidence from animal studies (Mazzucotelli et al. 2008. With permission from Elsevier)

gene expression. The emerging picture is of an increasing variety of interacting ­mechanisms shaping the transcriptome and proteome and contributing to the fine tuning of cell metabolism (Mazzucotelli et al. 2008) (Fig. 9.4). The expression of genes encoding components of post-translational control is often controlled at the transcriptional level, subjected to gene silencing by action of miRNA or to alternative splicing events. Multiple signaling pathways may converge on the same target protein by multisite modifications, resulting in complex combinatorial regulatory patterns that dynamically and reversibly affect the activity of a target protein. Different post-translational mechanisms may act together or have antagonistic effects. In animals, phosphorylation of a protein target is often essential to its ubiquitination. SUMOylation and phosphorylation reciprocally interact on the target proteins, with SUMOylation only targeting phosphorylated proteins or preventing phosphorylation. In addition, ubiquitination and SUMOylation often have antagonistic effects by acting on the same amino acid residues (Mazzucotelli et al. 2008). Table 9.2 lists selected ecological studies on proteomics and metabolomics.

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Table 9.2  Selected proteomics and metabolomics studies related to environmental stressors Environmental stressor Reference Abiotic stresses on Reviewed by Timperio et al. (2008) plants Ahuja et al. (2010), Geissler et al. (2010); reviewed by Hashiguchi Elevated CO2, climate change et al. (2010) Temperature Schwerin et al. (2009) Heat Ferreira et al. (2006), Malmendal et al. (2006), Garbuz et al. (2008), Ulrich and Marsh (2008), Nguyen et al. (2009), and Silvestre et al. (2010) Cold Beck et al. (2007), Hua (2009), Xiaoqin et al. (2009), and Ibarz et al. (2010) Irradiation, incl. UV Ehling-Schulz and Scherer (1999), Bhargava et al. (2008), Taupp et al. (2008), Xu et al. (2008), Kim et al. (2009a), Kaspar et al. (2010), Nguyen et al. (2009), and Meng et al. (2010) Drought, desiccation, reviewed by Chaves et al. (2003), Chen et al. (2006), Beck et al. anhydrobiosis (2007), Yoshimura et al. (2008), Carmo-Silva et al. (2009), Moore et al. (2009), Ashraf (2010), Lovisolo et al. (2010), Narsai et al. (2011), and Schokraie et al. (2010, 2011) Dubey et al. (2003), Bosworth et al. (2005), Jackson and Colmer Flooding, hypoxia, anoxia (2005), Wulff et al. (2008), Hashiguchi et al. (2009), Jiang et al. (2009), Zeis et al. (2009), Bailey-Serres and Voesenek (2010), Komatsu et al. (2010), and Li et al. (2010) Salt Aghaei et al. (2008, 2009), Paul et al. (2008), Srivastava et al. (2008), Wang et al. (2009a, b), Witzel et al. (2009), Yang et al. (2009), Zörb et al. (2009, 2010) Dowd et al. (2010), Fränzel et al. (2010), Geissler et al. (2010), Jacoby et al. (2010), Komatsu et al. (2010), Li et al. (2010), Lu et al. (2010), Lugan et al. (2010), Pang et al. (2010), Sobhanian et al. (2010a, b) Ozone Agrawal et al. (2002), Cho et al. (2008), Renaut et al. (2009); reviewed by Agrawal et al. (2009), Ahsan et al. (2010), and Sarkar et al. (2010) Heavy metals and Knigge et al. (2004), Sarry et al. (2006), Bona et al. (2007), Bhargava metalloids et al. (2008), Keyvanshokooh et al. (2009), Sanchez et al. (2009), Taylor et al. (2009, 2010), Bagwell et al. (2010), Dorts et al. (2010) Silvestre et al. (2010), Wang et al. (2010a) Acid mine drainage Mueller et al. (2010) Carletti et al. (2008), Mezhoud et al. (2008a, b), Malécot et al. (2009), Natural xenobiotics:, Pollack et al. (2009), and Wang et al. (2010a, b, c, d) cyanotoxins, humic substances Synthetic xenobiotics Knigge et al. (2004), Olsson et al. (2004), De Wit et al. (2008), Kling et al. (2008), Kluender et al. (2009), Wei et al. (2008b), Sanchez et al. (2009), Chora et al. (2010), Jin et al. (2010b), de Wit et al. (2010); reviewed by Lemos et al. (2010), and Taylor et al. (2010) Complex Wang et al. (2008) and Danchenko et al. (2009) contaminations Oxidative stress Hu et al. (2010) Food, nutrients Martin et al. (2003), Vilhelmson et al. (2004), Nguyen et al. (2007), Dowd et al. (2008), Jury et al. (2008), Hamza et al. (2010), and Sveinsdóttir and Gudmundsdóttir (2010) (continued)

248 Table 9.2  (continued) Environmental stressor P-deficiency, plants Parental care Pathogens, parasites

Symbiosis Herbivory, predation

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Reference Torabi et al. (2009) Chong et al. (2005) Booth and Bilodeau-Bourgeois (2009), Erb et al. (2009); reviewed by Lefèvre et al. (2009), Xiong et al. (2010); reviewed by Allwood et al. (2008, 2010), Peluffo et al. (2010), reviewed by Quirino et al. (2010), and Wang et al. (2010b) Batista et al. (2010) and Pineda et al. (2010) Erb et al. (2009), Jansen et al. (2009), Maserti et al. (2011), Pineda et al. (2010), and Zhang et al. (2010b)

9.3 Key Studies of Ecological Proteomics and Metabolomics Only a few proteomic studies exist which examine different compartments of ­natural ecosystems in terms of proteomics and/or metabolomics. One example is the comprehensive proteomic study carried out in the Doñana National Park, southwest Spain, by combining pollutant analysis, biomarker assessment, and environmental proteomic studies. Doñana National Park is an important wildlife reserve that may be threatened by the pesticides widely used in citrus fruit, strawberry, and rice crops grown in nearby areas and also by the metals released in 1998 by the collapse of a pyrite mine tailings dam 60 km north of Doñana (López-Barea and Gómez-Ariza 2006). In this study, three sentinel species were used in each different ecosystem: the red crab, Procambarus clarkia, to follow the status of streams and marshes, the wild mouse, Mus spretus,) in terrestrial ecosystems, and a clam species, Scrobicularia plana,) at the right bank of the Guadalquivir Estuary. In M. spretus, 40 protein spots were significantly different between contaminated and reference areas. In P. clarkii, proteomes were analyzed in the cytosolic fractions of nerve tissue and gills. Twenty-five protein forms in the gills showed differences in intensity between both areas. The proteomic analysis in the S. plana revealed that in samples with higher metal loads the following proteins were over-expressed: hypoxanthine phosphoribosyl-transferase (HPRT) and glyceraldehyde-3-phosphate dehydrogenase (G3PDH). HPRT pertains to the purine-salvage pathway which recovers free hypoxanthine and guanine by their reaction with 5-phosphoribosyl-1-pyrophosphate. While the relationship of this enzyme and oxidative stress has not yet been described, there are indications that purine nucleotide metabolism can be a target for reactive oxygen species. G3PDH is a glycolytic/gluconeogenic enzyme involved in glucose degradation and energy yield and de  novo synthesis from precursors, but it has nonglycolytic functions. Thus, G3PDH and other glycolytic enzymes are involved in transcriptional regulation, stimulation of cell motility, and the regulation of apoptosis (López-Barea and Gómez-Ariza 2006). Most studies are less comprehensive than the Doñana National Park approach and focus on single species and single stressors yet present interesting insights into the stress regulation of various organisms.

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9.3.1 Archaea and Oxidative Stress Archaea1 have adapted to some of the most extreme environments known to support life, including highly oxidizing conditions. However, in comparison to bacteria and eukaryotes, relatively little is known about the biology and biochemistry of Archaea in response to changing conditions and repair of oxidative damage. Maaty et al. (2009) conducted transcriptome, proteome, and chemical reactivity analyses of H2O2-induced oxidative stress in Sulfolobus solfataricus. Microarray analysis of mRNA expression showed that 102 transcripts were regulated within 30 min of exposure to H2O2. Parallel proteomic analyses found that 18 had significant changes in abundance. A recently characterized ferritin-like antioxidant protein, DPSL, was the most highly regulated species of mRNA and protein. As expected, a number of antioxidant related mRNAs and proteins were differentially regulated. Three of these – DPSL, SOD, and peroxiredoxin – were shown to interact and likely form a novel supramolecular complex for mitigating oxidative damage. Despite the central role played by DPSL, cells maintained a lower level of protection after disruption of the DPSL gene, indicating that loss of DPSL is not catastrophic to S. solfataricus cells, suggesting cross-talk and redundancy in the response to oxidative stress. Cross-talk and redundancy are common in the bacterial and eukaryotic organisms used in the composite network analysis.

9.3.2 Bacteria and Salt In their natural habitat as well as in fermentative production processes micro­ organisms have to cope with various stresses. At the transcript and protein levels, Fränzel et  al. (2010) investigated the quantitative dynamics of Corynebacterium glutamicum during adaptation to hyperosmotic stress. C. glutamicum is a Grampositive, aerobic, non-pathogenic bacterium that is one of the most important microorganisms for the production of fine chemicals. The osmolyte carrier proline/ ectoine carrier, playing a pivotal role in hyperosmotic stress defense, exhibited the strongest up-regulation of all proteins. A conspicuously regulated group comprised proteins involved in lipid biosynthesis of the cell envelope. This was in accordance with the phenotypic observation of a more viscous and stickier cell envelope and the finding of altered lipid composition. Together with the fact that several transporters were down-regulated, this membrane adaptation appeared to be one of C. glutamicum’s major protection strategies against hyperosmotic stress. In addition, the authors demonstrated that, contrary to former postulations, no oxidative stress

Single-celled non-spore forming microorganisms with transcription and translation that are more closely related to those of eukaryotes. Archaea use sources of energy ranging from familiar organic compounds, to ammonia, metal ions, hydrogen gas, or sunlight.

1 

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occurred during salt stress. Ultimately, it is remarkable that various proteins with divergent mRNA-protein dynamics and regulation have been observed. This lead to the assumption that there are still unknown mechanisms in between bacterial transcription, translation, and post-translation and that these are waiting to be discovered.

9.3.3 Fungi In fungi, light was shown to influence the rate and direction of growth, sexual and asexual reproduction, and the formation of pigments. The impact of UV on the basidiomycete Nidula niveo-tomentosa was only recently studied by Taupp et al. (2008). Exposure to UV-A light stimulated the growth of this fungus. The spectrum of UV-A-induced proteins comprised several stress-related proteins including a CAT, HSPs, GST, and proteasomes. In addition, growth-related enzymes of the citric cycle were found to be up-regulated as a response to irradiation with UV-A, corresponding well with the stimulated growth.

9.3.4 Plants Many genomic-scale datasets in plants have been generated over the last few years. A set of studies has examined the transcriptome of different organs and developmental stages of Arabidopsis in response to about 40 conditions. These studies constitute a major step toward the identification of gene regulatory networks in plants; however, intrinsic complexity of some of the networks have been addressed only very recently, such as cell-type-specific transcriptomic profiling (­Moreno-Risueno et al. 2010). With this in mind, the following paragraphs present key examples of the proteomics and metabolomic response of plants challenged by major ecological triggers.

9.3.4.1 Dehydration and Temperature Shock Dehydration Molecular studies on the dehydration-stress response have revealed both abscisic acid (ABA)-dependent and ABA-independent pathways, as reviewed by Urano et  al. (2010). The endogenous ABA level significantly increases response to water-deficit stress to regulate physiological stress responses and gene expression. Metabolite profiling revealed that the ABA accumulated during dehydration regulates the accumulation of various amino acids and sugars such as glucose and ­fructose.

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In particular, the dehydration-inducible accumulations of branch-chain amino acids (saccharopine, proline, and agmatine) are correlated with the dehydration-inducible expression of their key biosynthetic genes which are regulated by endogenous ABA. In contrast, the levels of raffinose and galactinol are not regulated by ABA during dehydration stress. Dehydration-treated plants have a great need to adjust osmotically, detoxify ROS, and ameliorate photo-inhibition. Metabolic profiling revealed that sucrose replaces proline in plants as the major osmoprotectant during the more severe combined dehydration and heat-stress treatment.

Temperature Plants’ responses and acclimation to temperature stress have been precisely characterized by metabolite profiling. A recent metabolome analysis showed common metabolites in response to cold and other stresses and demonstrated a prominent role for the dehydration responsive element-binding factor/C-repeat (DREB1/CBF) transcriptional network in the cold-response pathway. In Arabidopsis and rice, the DREB1/CBF cold-response pathway is one of the most well-characterized genetic systems in cold-responsive gene expression and acclimation. Metabolome analysis of transgenic Arabidopsis over-expressing DREB1A/CBF3 revealed that there is a striking similarity between the low-temperature regulated metabolome (monosaccharides, disaccharides, oligosaccharides, and sugar alcohols) and that regulated by the DREB1A/CBF3 transcription factor. In particular, the low-temperature-inducible accumulation of galactinol and raffinose is correlated with the expression of the GolS3 gene which is a direct target of DREB1A/CBF3 Comparative metabolite analysis between Arabidopsis Columbia (Col-0) plants responding to heat shock and cold shock showed an overlap with those produced in response to cold shock. Moreover, these results suggested that a metabolic network of compatible solutes including proline, monosaccharides (glucose and fructose), galactinol, and raffinose have an important role in tolerance to temperature stress. Natural variations in freezing tolerance were analyzed in nine Arabidopsis accessions. Plants acclimating to cold conditions were analyzed using a combination of genome-wide transcript profiling and metabolite profiling. The global climate changes in metabolite profiles were not correlated with plants’ responses to cold stress, whereas global changes in transcriptome profiles were correlated with plants’ abilities to acclimate to cold conditions (Urano et al. 2010).

9.3.4.2 Irradiation, Including UV Irradiation, including UV, is another climatic challenge to which plants are exposed. Kaspar et al. (2010) monitored the proteome of barley (Hordeum vulgare) seedlings exposed to UV-B irradiation and identified the responsive proteins in mesophyll of the epidermis. Interestingly, the early-induced UV-B-mediated changes in protein

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expression were largely confined to the epidermis. The proteomic analyses revealed the main reaction in epidermis tissue. They are primarily initial stress responses, such as the accumulation of antioxidants, HSPs, and proteins for supply of precursors for PSM, for example, flavonoids. This recent study confirms earlier ones; for instance, Förster et al. (2006) compared the wild-type and two very highly light-resistant mutants of the green alga Chlamydomonas reinhardtii after high light or very high light treatment to identify proteins with a potential role in photo-protection and survival in excess light. This study revealed deep modifications in proteomes; in particular, chaperonins and HSP were differentially expressed among mutants and wildtype exposed to different kinds of light for different periods. Among chaperonins, CPN60, CPN23, and CPN20 showed the most relevant changes in expression, whereas HSP70, out of all heat-shock proteins, appeared to be up-regulated in very high light-resistant mutants exposed to excess light compared to wild type. It is interesting to note that HSP70 expression changes are consistent with transcriptional profiles of the same protein in other studies on high-light-induced gene expression in Arabidopsis (Timperio et al. 2008). 9.3.4.3 Salt Some aspects of salt stress responses are intimately related to drought and cold stress responses due to the fact that sub-lethal salt-stress condition is ultimately an osmotic effect which is apparently similar to that brought on by water deficit and to some extent by cold and heat stresses. Salinity acts like drought on plants, preventing roots from performing their osmotic activity where water and nutrients move from an area of low concentration to an area of high concentration. Many research groups have used a proteomic approach for the identification of salt-responsive proteins in several plants (Timperio et al. 2008). For instance, Salekdeh et al. (2002) identified several salt-responsive proteins in root proteome of salt-tolerant and ­salt-sensitive rice varieties, including ABA- and stress-responsive proteins, ascorbate peroxidase, and many others. Several proteins were found to be modulated in expression by salt concentration in a coordinated manner. These proteins were involved in photosynthesis, photorespiration, signal transduction, metabolism regulation, oxidative stress defense, control of ion channels, and protein folding. Regarding HSPs, many authors confirmed that protein STI1 appeared to be ­up-regulated in response to salt stress; this protein contains two heat-shock chaperonin-binding motif (STI1), three tetratricopeptide repeat (TPR), and two Sti1 domains. The up-regulation of this regulatory protein may decrease the sterility of pollen ­during another development. HSP90 obviously interacts with TPR-containing proteins to modulate diverse cellular processes through protein–protein interaction (Timperio et al. 2008). Salicornia europaea is a succulent annual euhalophyte and one of the most salt tolerant plant species. Wang et al. (2009a, b) studied the salt tolerance mechanism by analyzing the proteomic responses of this plant to high salinity. The results

9.3  Key Studies of Ecological Proteomics and Metabolomics 7%

11%

5%

2% 3%

9%

13%

8%

5%

5%

10%

9% 8%

5%

253

Amino acid transport and metabolism Carbohydrate transport and metabolism Coenzyme metabolism Defense mechanisms associated proteins Detoxifying and antioxidant DNA replication, recombination and repair Energy production and conversion Inorganic ion transport and metabolism Nucleotide transport and metabolism Photosynthesis related proteins Posttranslational modification, chaperones Signal transduction mechanisms Transcription, translation, and trafficking Function unknown and hypothetical proteins

Fig. 9.5  An outline of functional classification for the identified proteins in Salicornia europaea exposed to high salinity. The proportion of identities in each functional category was the sum of the proportion of all identities (From Wang et  al. 2009b. With permission from the American Chemical Society)

d­ emonstrated that the majority of found proteins were energy production and ­conversion related proteins, followed by photosynthesis and carbohydrate metabolism associated enzymes (Fig. 9.5). Analysis of protein expression patterns revealed that energy production and ion homeostasis-associated proteins played important roles for this plant’s salt tolerance ability. Pang et al. (2010) compared leaf proteomics of Arabidopsis, a glycophyte, and its close relative salt cress, Thellungiella halophila, under different salt stress conditions. There were more proteins changed in abundance in Arabidopsis than in Thellungiella. Distinct patterns of protein changes in the two species were observed (Fig.  9.6): the identified proteins cover a wide range of molecular functions, ­including photosynthesis, energy (respiration), metabolism, protein synthesis, ­protein destination, stress and defense, signaling, transcription, cell organization, development, and transport. In Arabidopsis, the salt-responsive proteins were classified into 13 categories, while in Thellungiella the proteins were grouped into 11 categories. In terms of quantitative protein changes in response to salt stress, proteins involved in photosynthesis, energy, metabolism, and protein destination account for the major proportion in both Arabidopsis and Thellungiella. Different from halophytes, salt stress caused significant stress symptoms in Arabidopsis, including chlorosis, low tissue water content, and high electrolyte leakage. In Arabidopsis, the majority of the up-regulated proteins were involved in metabolism, photosynthesis, energy, and protein destination. In Thellungiella, more proteins involved in protein synthesis, photosynthesis, metabolism, and energy exhibited significant expression changes. In addition, proteins implicated in energy metabolism; ROS scavenging and detoxification; protein translation, processing, and degradation; signal transduction; hormone and amino acid metabolism; and cell

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Fig. 9.6  Functional classification of the identified proteins. The pie chart shows the distribution of salt-responsive proteins into their functional classes in percentage. (a) Salt-responsive proteins in Arabidopsis. (b) Salt-responsive proteins in Thellungiella (From Pang et al. 2010. With permission from the American Chemical Society)

wall modifications were identified, indicating that many processes work ­cooperatively to reestablish cellular homeostasis under salt stress. Furthermore, the results of the comparative analysis indicated that gene ­expression at the transcriptional level did not correlate well with that at the protein level, highlighting the importance of employing proteomics to reveal biochemical mechanisms of salt tolerance. An even more detailed proteome picture was drawn by Sobhanian et al. (2010a) studying the halophyte C4 plant Aeluropus lagopoides (Poaceae). A total of 1,805 protein spots were detected, of which 39 were up-regulated and 44 were down-regulated by treatment with NaCl (Fig.  9.7). Metabolism-related proteins were ­up-regulated, whereas some photosynthesis-related proteins were down-regulated, particularly those of the RuBisCo complex. In contrast, the activity of glyoxalase I increased with increasing NaCl concentration. Metabolome studies indicated up-regulation of amino acids and down-regulation of tricarboxylic acid cycle-related metabolites. These studies suggest that up-regulation of energy formation, amino acid biosynthesis, C4 photosynthesis, and detoxification are the main strategies for salt tolerance in A. lagopoides. Metabolomic analyses of Arabidopsis and Thellungiella revealed drastically different profiles between the two species. Compared with Arabidopsis, Thellungiella maintained higher levels of metabolite levels in both the absence and presence of salt stress (for details, see above, particularly Fig. 9.3). 9.3.4.4 Flooding Soil water logging and submergence (collectively termed flooding) are abiotic stresses that influence species composition and productivity in numerous plant

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255

Signal transduction 3% Replication 2% Cellular processes 3% Metabolism 43% Unknown 7% Membrane transport 7% Up-regulated

Protein biosynthesis 10%

Defence 15% Photosynthesis 10% Unknown 13%

Metabolism 26%

Membrane transport 2% Protein biosynthesis 11% Down-regulated Protein desination and storage 6% Defence 2%

Photosynthesis 40%

Fig. 9.7  Ontological classification of identified proteins from the shoots of Aeluropus lagopoides after NaCl treatment (From Sobhanian et al. 2010a. With permission from the American Chemical Society)

c­ ommunities. A major constraint resulting from excess water is an inadequate ­supply of oxygen to submerged tissues, since diffusion of oxygen through water is 104-fold slower than in air. In an early paper on the anoxia-tolerant rice, Oryza sativa, coleoptile, Huang et al. (2005) identified a newly synthesized pyruvate orthophosphate dikinase that generates pyrophosphate (inorganic diphosphate, P2O74–) from ATP. Pyrophosphate is capable of substituting for scarce ATP in sucrose breakdown in a key ATP-requiring step in glycolysis. The induction of the glycolysis and fermentation pathways has been confirmed several times not only in rice but also in various other plants such as soybeans (Hashiguchi et al. 2009). Functional distribution of 35 up-regulated protein spots and 16 down-regulated proteins are shown in Fig. 9.8. Besides this change in energy generation, a general stress response was also shown to occur as various ROS

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Fig. 9.8  Functional distribution of proteins in soybeans affected by flooding stress for 24  h. (a) Thirty-five up-regulated protein spots were determined; the chart shows the distribution of these proteins after functional classification. (b) Sixteen down-regulated protein spots were determined; the chart shows the distribution of these proteins after functional classification (From Hashiguchi et al. 2009. With permission from the American Chemical Society)

scavengers were up-regulated. Other identified proteins with diverse functional ­categories suggest that flooding stress includes not only hypoxic stress but also other stresses such as weak light, disease, and water stresses. 9.3.4.5 Ozone Tropospheric ozone (O3) is a destructive gaseous pollutant causing extensive damage to both natural and cultivated plant populations. O3 enters the plant through leaf stomata and reacts with cell wall and membrane components, leading to the production of ROS either by contact with water, plasma lemma, or other cellular components,

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with damaging consequences for cells. The proteomic effects of O3 were recently reviewed by Timperio et al. (2008). Ozone causes drastic reductions in major leaf photosynthetic proteins, including the abundantly present ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO), and induction of various defense- and stressrelated proteins. The latter were identified as pathogenesis related (PR) class 5 protein, PR 10 class protein, APX, SOD, calcium-binding protein, calreticulin, and a protease similar to an HSP100-class protein of E. coli. This protease is involved in disaggregation of protein with increasing temperature. Controlling intracellular proteolysis is, in fact, essential for cellular function, providing removal of damaged and misfolded polypeptides and of short-lived regulatory proteins. This is a fundamental mechanism in normal cells, and it is of particular relevance in many disease states. In bean and maize, SOD decreased in response to ozone stress while APX and sHSPs increased. Their functions were correlated with important cellular pathways such as glycolysis, photosynthesis, and antioxidant- and pathogen-related defense. Recently, it was found that several enzymes from the carbon metabolism were down-regulated in young poplar trees while two isoforms of HSP70 increased, confirming their main role in protein folding during ozone stress. 9.3.4.6 Natural Xenobiotics: Humic Substances Humic substances are known to affect plant metabolism at different levels. HSs enhance plant growth, as measured in terms of an increase in length or in the fresh and dry weights of shoots and roots. HSs also result in the production of higher leaf chlorophyll concentrations, more lateral root initials, an improved micro- and macronutrient uptake (Carletti et al. 2008). These authors extracted HSs from earthworm feces and used them to treat corn, Zea mays, seedlings to identify changes in patterns of root protein expression. Forty-two out of 60 differentially expressed proteins were identified (Fig. 9.9). The majority of them were down-regulated by the HS-treatment. The proteins identified included malate dehydrogenase, ATPases, cytoskeleton proteins, and different enzymes belonging to the glycolytic/­ gluconeogenic pathways and sucrose metabolism. Beside HSP70, the up-regulated proteins belonged to the plasma membrane proteome and facilitated cellular transport. Several of them belong to the cytoskeleton which coordinates all aspects of growth in plant cells. 9.3.4.7 Synopsis Abiotic Stressors Most abiotic stresses have shown that plants respond in similar manners to various stresses and there is similarity in the plants’ adaptive mechanisms (reviewed by Timperio et  al. 2008) (Table  9.3). They are expressed in different parts of the cell (Fig. 9.10). A direct result of stress-induced cellular changes is the enhanced accumulation of toxic compounds in cells that include ROS which provide a crucial link in the cross-talk to different responses. It has been suggested that plant cells sense ROS via

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Fig. 9.9  Relative intensities, spot ID, and p values for the 60 differentially expressed protein spots in roots of exposed Zea mays seedlings (From Carletti et  al. 2008. With permission from Springer)

redox-sensitive transcription factors such as heat-shock transcription ­factors (HSFs) which in turn activate HSP expression. Therefore, most HSPs are intimately associated with ROS. Table 9.3 indicates proteins both specific and non-specific to a stressor. The role of HSPs in directing defense mechanisms has been found in challenges by low and high temperatures, drought, salinity, or flooding as well as by osmotic, cold, and salt stresses (Table 9.3). Most HSPs have strong cytoprotective effects, maintaining proteins in their functional conformations, preventing aggregation of non-native proteins, refolding denatured proteins so they regain their functional conformation, and removing non-functional but potentially harmful polypeptides (arising from misfolding, denaturation, or aggregation). Consequently, HSPs ensure maintenance of homeostasis, protect cells, and help to resume equilibrium during recovery. In response to several stresses, plants synthesize different classes of HSPs/chaperones which act in concert in cellular protection and play complementary and sometimes overlapping roles in the protection of proteins from stress. This supports the hypothesis that the plant multiple stress tolerance mechanism is a complex network by which several pathways overlap and interact with each other (Timperio et al. 2008).

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Table 9.3  List of the major specific and non-specific proteins expressed during plant stress (From Timperio et al. 2008. With permission from Elsevier). The first column refers to specific proteins typical of each stress, while the second and third refer to common response pathways involving both antioxidant enzymes and HSPs Aspecific response ROS  Stress Specific response ROS scavenger HSP Heat

Cold

Freezing

Galactinol synthase, choline kinase, peptidyl prolyl isomerase, glutaredoxina, thaumatinb Osmotinf, dehydrinsg, glycine-rich protein

Light

Glycine-rich protein, anti-freezing protein Osmotin, dehydrins, aquaporinsk, LEA proteinssl NAB1n, RB38o

Heavy metals

MT, phytochelatins

Drought

APX, GST, CAT, SOD

HSP110, HSP100, HSP90, HSP70, HSP60, sHSPs, CPN60c, BIPd

APX, CAh, Met synthase, GST, Thioredoxini

sHSPs, HSP70, CPN20, CPN60, GRP78J (HSP70) sHSPs, GRP78(HSP70) sHSPs, HSP70, HSC70m

APX, CA Aldose/aldehyde reductase, Met synthase APX

GSH-derived peptides, such as phytochelatins COX6b-1r, triosephosphate isomerase, enolase, UGPase, GST, GPX, methyltransferase GST, APX, Fe-SOD

HSP70B, CPN60, CPN23, CPN20, sHSPs HSP70

HSP70, STI1s, Osmotin, dehydrins, remorin1, HIR HSP90, sHSPs proteins, GF14a, GF14bp, ABPq Ozone Cysteine synthase, sHSPs, HSP70, isoflavone reductase, HSP60 Ca-binding protein1, calreticulint a  Small redox enzymes with glutathione as a cofactor b  Pathogen-responsive protein, first found in the katemfe fruit (Thaumatococcus daniellii) c  Chaperonin, see Glossary d  Molecular chaperone of the HSP70 family e  Small osmotic-shock responsive protein f  Cold- and drought-responsive proteins g  Carbonic anhydrase h  Small redox proteins present in all organisms i  Glucose-related protein, chaperone of the subfamily of HSP70 j  Proteins embedded in the cell membrane that regulate the flow of water k Late embryogenesis abundant proteins, see Glossary l  Human heat-shock protein 70 m  Light-responsive stress protein in the cytoplasm n  Light-responsive stress protein in the chloroplasts o  Nuclear proteins p  Proteins central plant primary metabolism, ion homeostasis, and ABA regulation q  Actin binding protein r  Cytochrome c oxidase subunit 6B1, known from humans s  Protein containing, among others, two heat-shock chaperonin binding motif t  Calcium-binding protein Salt

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Fig. 9.10  Localization of major stress-related proteins in the plant cell. Protein belonging to a specific class and those belonging to the common response pathway are listed together (From Timperio et  al. 2008. With permission from Elsevier). Remorin is a protein involved in biotic interactions such as control of infection and release of rhizobia. Abbreviations and protein names are in Table 9.3

9.3.4.8 Herbivory Proteomics Herbivorous insects have major ecological and economic impacts on plants, such as conifers. Understanding the molecular and biochemical mechanisms by which ­conifers defend themselves from insect pests is a major goal of ongoing research in forest health genomics. Lippert et  al. (2007) studied changes to the proteome of Sitka spruce, Picea sitchensis, bark tissue were examined subsequent to herbivory by white pine weevils, Pissodes strobe, or mechanical wounding. Significant changes were observed as early as 2 h following the onset of insect feeding. Among the insect-induced proteins were a series of related small HSPs, other stress response proteins, proteins involved in secondary metabolism, oxidoreductases, and a novel spruce protein. In total, there were 43 proteins specific to mechanic and herbivorous challenge and 10 to herbivorous challenge alone (Fig. 9.11).

Metabolomics Jansen et al. (2009) presented the first study in which both participating organisms in a plant–insect herbivore interaction are chemically analyzed using a global metabolomic approach. As discussed in detail in Chap. 4, insect herbivores by

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Fig. 9.11  Distribution of differentially expressed proteins in control, mechanically wounded, and weevil-induced bark tissue in Picea sitchensis. This Venn diagram shows the breakdown of differentially expressed proteins with respect to the treatment group in which they were up-regulated (From Lippert et al. 2007. With permission from Wiley-VCH)

necessity have to deal with a large arsenal of plant defense metabolites. The levels of defense compounds increase with insect damage. These induced plant responses also affect the metabolism and performance of successive insect herbivores. As the chemical nature of induced responses is largely unknown, global metabolomic analyses are a valuable tool to gain more insight into the metabolites possibly involved in such interactions. The researchers analyzed the interaction between feral cabbage, Brassica oleracea, and small cabbage white caterpillars, Pieris rapae, focusing on how previous attacks to the plant affect caterpillar metabolism as well as comparing shoot and root induction by treating the plants on either plant part with JA. The study revealed that the levels of three structurally related coumaroylquinic acids were elevated in plants treated on the shoot. The levels of these compounds in plants and caterpillars were highly correlated: these compounds were defined as the “metabolic interface”.

9.3.5 Animals: Fish 9.3.5.1 Changing Salinity Sharks Partially euryhaline sharks and rays tolerate physiologically challenging variable ­salinity conditions in estuaries as a trade-off to reduce predation risk or to gain access to abundant food resources. To understand these trade-offs and to evaluate the underlying mechanisms, Dowd et al. (2010) examined the responses of juvenile leopard sharks to salinity changes and showed that leopard sharks employed a strategy of maintaining plasma urea, ion concentrations, and Na+/K+-ATPase activities in the short-term, possibly because they rarely spend extended periods in low salinity conditions in the wild. Furthermore, the authors found no evidence of apoptosis at the time points tested, while gill and rectal gland exhibited proteomic changes related to the cytoskeleton, suggesting that leopard sharks remodel existing

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o­ smoregulatory epithelial cells and activate physiological acclimatory responses to solve the problems posed by low salinity exposure.

Teleosts A similar regulation applies to teleosts transferred from fresh to brackish water as Lu et al. (2010) recently showed with gills of the ayu (or sweetfish), Plecoglossus altivelis. The modulated and identified proteins were involved in osmoregulation, cytoskeleton, energy metabolism, and stress response. In particular, the authors showed that seven proteins were down- and one protein was up-regulated was upregulated when ayu were transferred from fresh to brackish water. Interestingly and in accordance with the shark results, the gene encoding a Na+/K+-ATPase subunit underwent no significant change. High salinity led to a down-regulation and reduced concentration of betaine–homocysteine methyltransferase in ayu gills. This is the only known enzyme that utilizes betaine as a substrate for methylation. Betaine is an important methyl donor used for the synthesis of several products which play a key role in protein and energy metabolism. Furthermore, it is also involved in the osmoregulation of fishes. Decreased expression of betaine–homocysteine methyltransferase leads to the accumulation of intracellular betaine which is beneficial to maintaining gill cell volume of ayu in brackish water. Overall, the proteins found modulated in ayu were mostly involved in protecting cells against dramatic changes in osmotic pressure.

9.3.5.2 Cold All physiological processes in ectotherms, such as fish, are affected by water temperature, and thus they are vulnerable to seasonal variations. Farmed species cannot escape from adverse environment conditions, specifically low winter temperatures. In addition, farmed fish are susceptible to other stress factors such as confinement, handling and other management procedures, and crowding. Animal performance and stress responses seem to be generalized and independent of the type of stressor; in other words, there is a common response to stress. Thus, during a cold challenge in fish, changes occur in cell metabolism, tissue mitochondrial density and properties, and cell membrane composition. Ibarz et al. (2010) studied the proteomic response of gilthead sea bream, Sparus aurata challenged by a cold shock. This fish is extensively farmed in the Mediterranean Sea. It is exposed to wide fluctuations in environmental temperature, but it has only a narrow range of thermotolerance. Growth is compromised when the water temperature falls below 13°C which provokes fasting, growth arrest, and general metabolic depression. The metabolic rate, liver composition, and enzyme activities of gilthead sea bream demonstrate that this species, unlike other temperate fish, has little capacity (if any) to acclimate to low temperatures. Exposure to stress such as low temperatures increases ROS, including nitrogen oxides, and leads to lipid

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Fig. 9.12  Physiological grouping of hepatic responses by cold stress to gilthead sea bream Sparus aurata. Following identification, spots were grouped according to main cellular function. The data are presented as the mean ± SEM. All of the spots that are plotted showed significant differences between warm and cold groups (p < 0.05) (From Ibarz et al. 2010. With permission from Wiley-VCH)

p­ eroxidation. Liver proteomics showed that many proteins were down-regulated after cold exposure (Fig. 9.12), including actin (the most abundant protein in the proteome) followed by enzymes of amino acid metabolism and enzymes with ­antioxidant capacity, such as betaine-homocysteine-methyl transferase, GST, and CAT. Some protective proteins, however, were up-regulated at low temperatures, including peroxiredoxin, thioredoxin, and lysozyme as well as enzymes such as aldehyde dehydrogenase and adenosin-methionine synthetase. Yet, the up-regulation of proteases, proteasome activator protein, and trypsinogen-like protein indicated an increase in proteolysis. Furthermore, increases in elongation factor-1a, the GAPDH oxidative form, tubulin, and Raf-kinase inhibitor protein indicated oxidative stress and the induction of apoptosis. 9.3.5.3 Hypoxia/Anoxia In fish, adaptation to anoxia is important due to the ever changing levels of dissolved oxygen occurring in water because of normal daily fluctuations or to human influence like pollution or global warming. To understand the response of rainbow trout to long-term anoxia, Wulff et  al. (2008) exposed the fish for 24 h to N2-induced anoxia. This challenge induced global perturbations on protein expression in ­rainbow

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trout hypodermal fibroblast cell lines. The anoxic insult changed the level of 33 ­proteins: 22 of these were up-regulated and 11 were down-regulated. The identified proteins included two proteins involved in energy metabolism (phosphoglycerate mutase, isocitrate dehydrogenase). In addition to the metabolism proteins, the authors observed the up-regulation of a cluster of proteins that contribute to cytoskeleton function. Furthermore, an up-regulation of peroxiredoxin six was observed. This increase indicates a need for protection against ROS in the cells; the applied anoxia obviously resulted in an unbalanced redox homeostasis in an oxidative stress. 9.3.5.4 Parental Care Fish mucus is responsible for several vital biological functions such as mechanical and disease protection, respiration, communication, nest building, and particle trapping. More intriguingly, newborns of several cichlid species also ingest parental epidermal mucosal secretion as an early food source. The discus fish, Symphysodon aequifasciata, is a cichlid species demonstrating advanced parentalcare behavior which involves active feeding of larva with mucus secretions and specialized epidermal cells. Chong et al. (2005) compared the protein profile from parental and non-parental fish. The analysis of the up-regulated spots identified proteins such as fructose biphosphate aldolase, nucleoside diphosphate kinase, and HSPs which are essential to support energy provision, cell repair and proliferation, stress mediation, and defense mechanisms in parental fish during the parental-care period. Concurrently, the detection of several antioxidant-related proteins such as thioredoxin peroxidase and hemopexin suggests a need to overcome oxidative stress during hypermucosal production in parental-care behavior. A C-type lectin was also found to be uniquely expressed in parental mucus and could have an important role in providing antimicrobial, immune-related protection to both parental fish and fry. 9.3.5.5 Nutrition Most teleost fish species are adapted to use amino acids as the preferred energy source over carbohydrates and thus require high levels of dietary amino acids. In commercial aquaculture, this requirement is met with fishmeal-based feed. The sustainability of this practice has been questioned, and progress has been made on the replacement of fishmeal with a number of different ingredients, including soybean, lupin, peas, and sunflower. Vilhelmson et al. (2004) investigated growth and metabolism in rainbow trout, Oncorhynchus mykiss, fed a diet composed of a mixture of plant proteins compared with those fed a fishmeal-based diet. The authors showed that liver protein profile changed in response to the alteration in the diet. A number of metabolic pathways were identified as sensitive to the protein source substitution. These included pathways are involved in primary energy generation, maintenance of reducing potential, bile acid synthesis, and cellular transport and protein

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d­ egradation. Interestingly, the pathways shown to be affected in the study were somewhat different from those identified in a previous work by Martin et al. (2003) with soybean-based protein replacement of fishmeal, with the effects on the abundance of several stress response proteins notably absent. The latter authors found altered levels of several stress proteins, e.g., HSP70, HSP108, and aryl sulfotransferase, indicating a stress response that was not observed in the study by Vilhelmson et al. (2004). Overall, there were surprisingly few similarities between the two studies; obviously, the metabolic effects of plant protein replacement in aquaculture feed varies with plant protein source. 9.3.5.6 Caloric Restriction Calorie availability pivotally affects metabolic rate, reproductive fitness, growth, and survival in fish on the one hand. On the other hand, caloric restriction is the most efficient and reliable method to increase longevity; caloric restriction refers to giving organisms only 60% or 70% of the amount of calories normally ingested by control organisms fed ad libitum but supplying them with adequate amounts of minerals and vitamins to avoid deficiencies. This has proven effective in rotifers, Caenorhabditis elegans, Drosophila melanogaster, spiders, fishes, and rodents (Minois 2000). Calories in the form of fatty acids are the most significant source of ATP for many fish species. Accordingly, fish manipulate storage and mobilization of fatty acids as part of their natural metabolism. Characterizing the molecular signaling behind lipid metabolism has traditionally been approached by looking at candidate proteins, e.g., fatty acid binding proteins, organelle function, and enzymatic indicators of fatty acid flux. In a recent study, Jury et al. (2008) gained detailed insight into how fish respond to changes in calorie availability. The authors compared high and low calorie diets in zebrafish, D. rerio, and found 29 proteins were differentially expressed between treatments. Differentially expressed proteins were mapped to GO terms, and these terms were compared to the entire zebrafish GO annotation. The most significant GO terms associated with high-calorie diet were the decrease in oxygen-binding activity in the high-calorie treatment, namely transporter activity and binding, tetrapyrole binding, heme binding, and iron ion binding. Life traits, however, were not recorded in the fish so that the fitness of the low-calorie diet group cannot be judged. 9.3.5.7 Food Allelochemicals: Cyanotoxins Cyanotoxins are well-known food allelochemicals produced by many cyanobacterial species. The transcriptional analysis in the zebrafish, D. rerio, by Wei et al. (2008a, b) revealed that the predominantly overrepresented pathways were those pertaining to cell cycle and mitogen-activated protein kinase (MAPK) signaling. Furthermore, the comparative evaluation of microcystin-sensitive and -resistant fish showed that

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the inducible, instead of constitutive, expression of liver GST genes of the ­alpha- and rho-classes play a key role in the tolerance to microcystin. In one of the proteomic studies with the medaka, Oryzias latipes, and microcystins (MCs), Mezhoud et al. (2008a) confirmed major transcriptional findings by Wei et  al. (2008a, b) by identifying proteins involved in cytoskeleton assembly, cell signaling, oxidative stress, and apoptosis. Also in D. rerio, proteins involved in cytoskeleton assembly, macromolecule metabolism, oxidative stress, and signal transduction were modulated (Wang et al. 2010b). In a subsequent paper, Malécot et al. (2009) refined their results in O. latipes by focusing on membrane and organelle proteins. Seventeen proteins were modulated in response to MC-LR treatment. Eight of them were newly reported: prohibitin, fumarylacetoacetase, protein disulfide isomerase A4 and A6, glucose regulated ­protein 78 kDa, 40 S ribosomal protein SA, cytochrome b5, and ATP synthase mitochondrial d subunit. These proteins are involved in protein maturation or in the response to oxidative stress. Based on their proteomic results, the authors ­constructed a sketch of the main MC-LR effects in hepatocytes (Fig.  9.13). In particular, Microcystin-LR enters hepatocytes by an organic anion transporting polypeptide (OATP) that usually transports biliary acid. In the cell, the toxin will inhibit protein phosphatase 1 and 2A and aldehyde dehydrogenase 2. These inhibitions lead to several deregulations such as the MAPK signaling pathway deregulation but also to the production of reactive oxygen species and disorganization of the cytoskeleton. The oxidative stress may alter DNA and protein thus inducing proteins involved in DNA repair or protein maturation and degradation. These multiple effects can either lead to cell proliferation (tumorigenesis) or cell death by apoptosis or necrosis. 9.3.5.8 Synthetic Xenobiotics and Heavy Metals Due to the relatively low correlation between observed amounts of mRNA and ­protein (i.e., the amount of mRNA does not always equal the amount of protein), gene expression analysis is inadequate to predict effects on the proteome level, and ­proteomics is finding its way into the comprehensive effect assessment of synthetic xenobiotics. Some interesting studies shall emphasize its increasing significance. De Wit et  al. (2008) exposed zebrafish to tetrabromobisphenol-A, one of the most frequently used brominated flame retardants. The analysis of the differentially expressed liver proteins elucidated a stress response indicated by HSP70 and chaperone protein GP96. In addition, stimulation of phosphoglycerate mutase 1 was observed, implying an interference with the glycolysis pathway. Concerning the suppressive effects of tetrabromobisphenol-A, two down-regulated proteins could be identified: one cytoskeleton protein corresponding to b-actin, and betaine homocysteine methyltransferase (already known to be involved in osmoregulation). The latter protein plays an important role in the homeostasis of homocysteine metabolism. Interestingly, the proteome response of zebrafish to brominated flame retardants appeared to be gender-specific. For instance, while betaine homocysteine

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Fig. 9.13  Microcystin-LR (MC-LR) main effects in hepatocytes of medaka Oryzias latipes (From Malécot et al. 2009. With permission from Elsevier)

­ ethyltransferase was induced in both genders, a female-specific down-regulation m of iron-homeostatic proteins were observed (Kling et al. 2008). A gender-specific response to synthetic xenobiotics appears to more common than anticipated, since Wei et  al. (2008a, b) observed this phenomenon also in Chinese rare minnow, Gobiocypris rarus exposed to perfluoroocatnoic acid. Later, De Wit et al. (2010) devoted another paper to the estrogenic and metabolic effects of 17 a-ethinylestradiol, a synthetic estrogen and active component of oral contraceptives. Numerous studies have demonstrated that exposure to this estrogen provokes interference with embryonic development, increased vitellogenin synthesis, and hampered reproduction in zebrafish. However, estrogens have the potential to disturb physiological functions other than through reproductive pathways alone. Other studies have shown that estrogens can affect somatic growth, immune function, and stress response (De Wit et al. 2010 with references). However, the wide varieties of mechanisms at the cellular level which underlie the different types of

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Fig. 9.14  Categorization of all differentially expressed transcripts and proteins according to their corresponding GO-term (biological process) in zebrafish, Danio rerio, exposed to 17 a-ethinylestradiol (From De Wit et al. 2010. With permission from Elsevier)

toxicity often are not fully understood. Therefore, the researchers applied a combined transcriptomic and proteomic approach to study the underlying molecular mechanisms of 17 a-ethinylestradiol in adult zebrafish. Assessment of the major biological functions of the differentially expressed transcripts and proteins illustrated that both individual platforms could profile a clear estrogenic interference next to numerous metabolism-related effects and stress responses. Figure 9.14 provides an overview of the major biological processes that were affected. Based on this primary categorization, differential transcripts and proteins were further subdivided according to more specific functional annotations. As illustrated, microarray analysis defined a clear impact on the GO category “nucleobase, nucleoside, nucleotide and nucleic acid metabolism” which embodies differentially expressed mRNAs involved in RNA and DNA metabolism and transcription. Especially genes involved in DNA repair were affected. In exposed males, the authors observed strong stimulations of the transcript which regulates ­pre-mRNA alternative splicing, mRNA editing, and translation. The category of transcriptionrelated genes depicted a stimulation of estrogen receptor gamma (ERg) and ­hepatocyte nuclear factor 4a (HNF-4a) in male fish exposed to 17 a-ethinylestradiol for 4 days. In addition, an interference with steroid metabolism was clearly reflected by the differentially expressed genes that were involved in “lipid metabolic processes”. As expected, the mRNAs corresponding to vitellogenin displayed strong stimulations in the male fish exposed to 17 a-ethinylestradiol and indicate the risk of feminization. From a more commercial point, Keyvanshokooh et  al. (2009) analyzed the proteomic effects of methylmercury (MeHg) on juvenile beluga, Huso huso. MeHg

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is the most toxic form of mercury which is bioaccumulated in the aquatic food chain. It has been shown that one of the main targets of MeHg toxicity is the brain, but there was little knowledge of the molecular mechanisms of its toxic effects. In their study, Keyvanshokooh et  al. (2009) found eight proteins with significantly altered expression level in beluga brain exposed to MeHg. These proteins were involved in cell metabolism, protein folding, cell division, and signal transduction. Overall, this paper supported the hypothesis that MeHg exerts its toxicity through oxidative stress induction and apoptotic effects.

9.3.6 Animals: Arthropods 9.3.6.1 Shrimps and Hypoxia The Chinese shrimp, Fenneropenaeus chinensis, is one of the most commercially important cultured species in aquaculture of China. Hypoxia, as one suboptimal environmental condition, affects the physiological state of shrimp during pond aquaculture. To better understand the response mechanism, Jiang et al. (2009) analyzed differentially expressed proteins of hepatopancreas in adult Chinese shrimp. Thirty-three proteins were identified and functionally classified: energy production down-regulated; metabolism-related mainly down-regulated; immune-related unexpectedly up-regulated; antioxidant proteins and chaperones down-regulated, obviously due to reduced ROS production; and cytoskeleton proteins down-regulated. This study provides some insight into the hypoxic stress response of shrimp at the protein level but also leaves several questions unanswered. Why do the shrimps up-regulate the immune-related proteins? What is the temporal development of this response? Does the stress response change with the duration of the stress? What is the mechanistic background of the difference in the modulation of the cytoskeletons in this shrimp with the proteins down-regulated and the rainbow trout with the proteins up-regulated (see above)?

9.3.6.2  Daphnia and Food Allelochemicals The frequency of cyanobacterial blooms has increased worldwide, and these blooms have been claimed to be a major factor leading to the decline of the most important freshwater invertebrate herbivores, i.e., representatives of the genus Daphnia. This suppression of Daphnia was attributed to the presence of biologically active secondary metabolites in cyanobacteria (Rohrlack et al. 2001). Among these metabolites, protease inhibitors are found in almost every natural cyanobacterial bloom and have been shown to specifically inhibit Daphnia’s digestive proteases in vitro, but to date no physiological responses have been reported in situ at the protein and genetic levels.

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Schwarzenberger et  al. (2010) detected nine digestive proteases in D. magna which were up-regulated at the RNA-level. D. magna also responded to dietary protease inhibitors by the induction of new and less sensitive protease isoforms at the protein level. These physiological responses proved to be independent from microcystin effects as there were only negligible differences between protease expression of D. magna fed with toxic M. aeruginosa and its microcystin-free mutant. Furthermore, the authors showed that a D. magna clone responded physiologically to dietary cyanobacterial protease inhibitors by phenotypic plasticity of the targets of these specific inhibitors, i.e., D. magna gut proteases. These regulatory responses are adaptive for D. magna as they increase the capacity for protein digestion in the presence of dietary protease inhibitors. The type and extent of these responses in protease expression might determine the degree of growth reduction in D. magna in the presence of cyanobacterial protease inhibitors. The rapid response of D. magna to cyanobacterial protease inhibitors supports the assumption that dietary cyanobacterial protease inhibitors, rather than the cyanotoxins, exert a strong selection ­pressure on D. magna proteases themselves. 9.3.6.3  Daphnia and Synthetic Xenobiotics In addition to the classical ecotoxicity test, there is widespread interest in exploiting “omics” approaches to screen the toxicity of chemicals, potentially enabling their rapid categorization into classes of defined mode of action. In their comparative study, Taylor et al. (2010) focused on four model toxicants: Cd (inducer of oxidative stress), fenvalerate (sodium channel activator), 2,4-dinitrophenol (DNP; uncoupler of oxidative phosphorylation), and propranolol (nonselective b-blocker). The authors discovered toxicant-specific perturbations to putatively identified metabolic pathways, including propranolol-induced disruption of fatty acid metabolism and eicosanoid biosynthesis and fenvalerate-induced disruption of amino sugar metabolism. The findings highlight the capability of metabolomics to discover early-event metabolic responses that can discriminate between the acute toxicities of chemicals and indicate the underlying mode of action. In this respect, proteomics is superior to transcriptomics, since it reflects the concrete protein side rather than the potential of transcribed genes. 9.3.6.4 Insects and Heat One important physical factor affecting the distribution of ectothermic organisms is the temperature of their environment. Waagner et al. (2010) studied low amounts of free amino acids in the springtail, Folsomia candida, challenged by a short-term, fluctuating heat shock. Particularly, five free amino acids (arginine, leucine, lysine, phenylalanine, and tyrosine) were significantly reduced. This finding contrasts with earlier findings with Drosophila melanogaster. Temperature increase is often related to increased metabolic activity and protein breakdown, resulting in

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decreased concentration of metabolites and increased concentration of free amino acids. In D. melanogaster, the relative concentration of some free amino acids increased significantly following heat hardening and/or non-fluctuating heat shock (Malmendal et al. 2006). Probably, the study on F. candida was more environmentally realistic and indicates that the individuals were more in the state of allostasis than homeostasis due to daily thermal disturbance. 9.3.6.5  Drosophila and Cold A short exposure to a mild cold stress is sufficient to increase cold tolerance in many insects. This phenomenon, termed rapid cold hardening, expands the thermal interval that can be exploited by the insect. To investigate the possible role of altered metabolite levels during rapid cold hardening, Overgaard et  al. (2007) showed that cold shock treatment was a persistent disturbance of the metabolite profile in D. melanogaster that correlated well with a delayed onset of cold shock mortality. The most pronounced changes following the rapid cold hardening treatment were elevated levels of glucose and trehalose. The authors observed that the onset and magnitude of the increased sugar levels correlated tightly with the improved chill tolerance following rapid cold hardening. These findings suggest a putative role of cryoprotectants during rapid cold hardening. This mechanism does not conflict with the well-known membrane modifications as key adaptations occurring during rapid cold hardening. It is possible that increased levels of cryoprotectants enhance the membrane effect. 9.3.6.6 Moths and UV-Light The cotton bollworm, Helicoverpa armigera (Lepidoptera: Noctuidae), is one of the most serious insect pests worldwide and has developed resistance to several ­insecticides (see Chap. 4). The caterpillars cause substantial damage to cotton, corn, tobacco, soybean, and other vegetable crops; hence, environmentally friendly management strategies are required, for instance application of blacklight which emits electromagnetic irradiation near the UV region at 320–400 nm, to trap insect pests, including H. armigera. The moths of this nocturnal insect display a conspicuous positive phototactic behavior to light stimuli and are especially sensitive to UV light. Recent studies confirmed that UV light exposure can increase the levels of oxidative stress, disturb the functional activity of proteins, and intensify the activity of protein oxidation processes. Meng et al. (2010) provided important new insights into the adaptation mechanisms of H. armigera to UV light irradiation. Altered proteins were associated closely with signal transduction, RNA processing, protein processing, stress response, metabolism, and cytoskeleton structure (Fig.  9.15). A significant challenge will be to assess the specific role of each of these proteins. An even more comprehensive study on another insect pest was carried out by Nguyen et al. (2009) who challenged wingless and winged Macrosiphum euphorbiae, a potato aphid. The researchers examined the direct effects of fluctuating heat

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10%

21%

7% 10%

10%

3% 14%

25%

signal transduction

RNA processing

protein processing

stress response

metabolism

structural proteins

others

unknown

Fig. 9.15  Functional categorization of differentially abundant proteins identified in Helicoverpa armigera adults in response to UV light irradiation (From Meng et al. 2010. With permission from Elsevier)

and UV stress regimes, alone and in combination, on performance of this aphid as measured by movement, growth, development, and reproductive rates. Furthermore, they also correlated these effects with physiological changes in stressed aphids using the proteomic approach. Aphid proteomes revealed ~470 protein spots, with the fluctuating heat stress leading to many more changes than exposure to UV-B. The reduced performance of aphids under heat stress correlated with lower abundance of several enzymes in central pathways of energy metabolism, including the tricarboxylic acid cycle and the respiratory chain. Several exoskeletal proteins were induced or their abundance was increased under high temperature stress, indicating that cuticle barrier enhancement at molting in response to heat stress is an aphid adaptation to stressful thermal conditions. The proteome of winged aphids was more broadly modulated under stress than that of wingless aphids (Fig. 9.16). Greater homeostatic capabilities as revealed at the proteomic level could explain the higher tolerance of the winged aphid morph to environmental stress and its more stable performance and fitness.

9.3.6.7 Parasites Proteomics has revolutionized many fields in biology, including host-parasite interactions (Lefèvre et al. 2009). Pioneer proteomic studies have been carried out on six arthropod host–parasite systems: two orthoptera–hairworm systems, two insect vector–pathogen systems, and two gammarid–parasite systems (Fig. 9.17). Initially, proteomics was used to explore the mechanisms in the host central nervous system underlying the suicidal behavior of crickets and grasshoppers when manipulated by their hairworms. Two orthoptera-hairworm systems have been investigated: (i) the cricket, Nemobius sylvestris, parasitized by the hairworm, Paragordius tricuspidatus; and (ii) the long-horned grasshopper, Meconema thalassinum, parasitized by the hairworm, Spinochordodes tellinii. Proteomic studies showed that adult hairworms produced host mimetic proteins and manipulated

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Fig. 9.16  Venn diagram representing the number of spots significantly modulated in wingless and winged potato aphids Macrosiphum euphorbiae exposed to three experimental stress regimes: Heat- UV+, Heat + UV-, and Heat + UV+. Induction refers to de  novo synthesis of proteins and up-regulation to increased production. In the area of triple-overlap for winged aphids, coupled symbols stand for differential modulation among treatments, with the left and right symbols representing the effect of UV irradiation and heat stress, respectively (From Nguyen et al. 2009. With permission from Elsevier)

behavior with them. These proteins suggested a direct action of the hairworms on the host’s central nervous system that can lead directly to an alteration of the host behavior or indirectly via a host genome response. The analysis of the head proteomes revealed that the percentage of proteins potentially linked to the hairworm manipulative process was higher for M. thalassinum compared to N. sylvestris. For the hairworms, some of the proteins potentially linked to the manipulative process were the same. The altered functions were similar for both orthopteran species except for some families of proteins only differentially expressed in M. thalassinum that were involved in geotactic behavior, in protein biosynthesis, and in recovery following an infection. In the brain of manipulated orthoptera, differential expression of proteins specifically linked to neurogenesis, the visual process, the geotactic process, and ­neurotransmitter activities were observed (Fig. 9.17, N. ­sylvestris and M. thalassinum bars) (Lefèvre et al. 2009). These studies also provide evidence that pathogens can alter the head proteome of their insect vectors (Fig. 9.17, Anopheles gambiae and G. palpalis gambiensis bars). Some of the altered protein families are similar between dipterans (i.e., sugar metabolism, signal transduction, and heat-shock response). An alteration in energy metabolism was observed in the central nervous system of both parasitized hosts (Lefèvre et al. 2009). Finally, these parasito-proteomics studies indicate that parasites can alter host apoptosis pathways and sugar metabolisms.

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Fig. 9.17  Proportion of identified proteins linked to a biological process and differentially expressed during the manipulative process in head proteomes of the arthropod hosts for six host– parasite systems. (i) The cricket, Nemobius sylvestris, parasitized by the hairworm, Paragordius tricuspidatus; (ii) the long-horned grasshopper, Meconema thalassinum parasitized by the hairworm, Spinochordodes tellinii; (iii) Anopheles gambiae-Plasmodium berghei; (iv) Glossina papalis gambiensis-Trypanosoma brucei brucei; (v) Gammarus insensibilis parasitized by the trematode, Microphallus papillorobustus; (vi) Gammarus pulex parasitized by the ancantocephalan, Polymorphus minutes (From Lefèvre et al. 2009. With permission from Elsevier)

For the two gammarid species (Fig. 9.17, Gammarus insensibilis and G. pulex bars), the proteome of G. insensibilis displayed a slightly stronger response to the manipulative process caused by its trematode compared to G. pulex manipulated by its acanthocephalan. The altered functions were similar for both gammarid species except for some families of proteins only expressed in G. insensibilis: those involved in the visual process, DNA binding, cell proliferation, and metabolism (Lefèvre et al. 2009). The proteomics results obtained for G. insensibilis–M. papillorobustus corroborated previous studies suggesting a major role of serotonin in the expression of the aberrant evasive behavior (see Chap. 3). The proteomics results have shown that arginine kinase was differentially expressed in the brain of infected G. insensibilis and G. pulex compared to uninfected individuals. This phosphotransferase is known to be one of the regulating

9.3  Key Studies of Ecological Proteomics and Metabolomics

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Fig. 9.18  Functional classification of the proteins found to be regulated in the earthworm Eisenia fetida after Cd exposure (From Wang et al. 2010a. With permission from the American Chemical Society)

factors in nitric oxide (NO) synthesis. NO is liberated during immunological reactions, but it also acts as a neuromodulator. Thus, these proteomics results provided supportive evidence for the hypothesis that parasites exploit host defense reactions in order to manipulate host behavior (Lefèvre et al. 2009).

9.3.7 Animals: Worms 9.3.7.1 Earthworms The majority of earthworm (Eisenia fetida, Lumbricus rubellus) studies focus on ­ecotoxicologic issues since these animals are able to tolerate high body burdens of xenobiotic chemicals, particularly heavy metals such as Cd (Stürzenbaum et al. 2001, 2004). In a recent proteomics study, Wang et al. (2010a) identified a functional profile of the Cd-responsive proteins in the earthworm E. fetida. The identified proteins were involved in several processes, including transcription, translation, the tricarboxylic acid cycle, the cellular amino acid metabolic process, protein amino acid phosphorylation, glycolysis, the glucose metabolic process, and antioxidant response (Fig. 9.18); and these proteins work cooperatively to establish a new homeostasis under Cd exposure. In contrast to previous studies, Wang and coworkers (2010a) did not find that metallothioneins were Cd-responsive proteins – the reason remains obscure. The same laboratory also provided a functional profile of Escherichia coli O157:H7-responsive proteins in this earthworm species (X Wang et al. 2010b). This bacterium is a food-borne pathogen and is lethal even to earthworms. The molecular responses to E. coli O157:H7 stress revealed a similar profile as the Cd challenge. In addition, several proteins were found only in response to the pathogen challenge, such as HSP90 or an the antimicrobial peptide lumbricin I. The proteome response of E. fetida to synthetic xenobiotics, namely DDT, endosulfan, and phenanthrene, was the subject of a study conducted by Myrna Simpson’s laboratory (McKelvie et al. 2009, 2010; Brown et al. 2010). Beside methodological

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Fig. 9.19  Gene Ontology functional classification of all 109 differentially expressed proteins identified in the cadmium shock experiment in a bacterial community (From Lacerda et al. 2007. With permission from the American Chemical Society)

aspects, the authors focused on the low-molecular weight organic compounds and confirmed the aforementioned Folsomia-study by noticing that exposure to xenobiotics disrupts amino acid homeostasis. Particularly, alanine consistently increased for DDT and endosulfan exposed E. fetida. The authors concluded that deviations from the normal homeostatic ratio of 1.5 for alanine to glycine is a biomarker of DDT and endosulfan exposure.

9.4 Metaproteomics: Microbial Communities Several recent studies and reviews show that characterizations of microbial ­populations in natural environments at both a functional biomolecular level and a whole-community level have become feasible by metaproteomics (Lacerda et  al. 2007; Lacerda and Reardon 2009; Mueller et  al. 2010). Metaproteomics refers to the proteomics study of communities as metaorganisms, whereby a metaorganism is defined as a collection of organisms evolving as a whole, sharing genes and metabolic capacities (Lacerda and Reardon 2009). The potential of metaproteomics will be exemplified by the study of Lacerda et al. (2007). The authors exposed a bacterial community to an inhibitory level of Cd and identified proteins differentially expressed over time following exposure. The authors observed significant community proteome responses, with more than 100 protein changes. The most common expression pattern was immediate up- or down-regulation within 15 min of shock followed by maintenance of that level. Proteins of importance included ATPases, oxidoreductases, and transport proteins. The functional categories and the distribution of the unique differentially expressed proteins are shown in Fig. 9.19.

Fig. 9.20  Community structure of biofilm samples. (a) Percent composition of each community proteome based on the organismal assignments for each ­protein identified. X-axis labels represent biofilm community names. (b) Clustering of biofilm communities (column labels) using community structure data collected by FISH. Color scale is based on the percent composition of each community (From Mueller et al. 2010. Courtesy of the Public Library of Science)

9.4  Metaproteomics: Microbial Communities 277

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Lacerda and Reardon (2009) reviewed ecological studies focusing on naturally occurring bacterial adaptation to their environments. Proteomics were used in several studies to provide insights into the mechanisms of adaptation, especially to extremes of temperature. Proteins of hyperthermophilic organisms such as Sulfurispharea sp. were of particular importance since they have an enhanced conformational stability, allowing them to be active at high temperatures. Other ­ecological studies focused on cold adaptation of bacteria such Exiguobacterium sibiricum, a strain isolated from Siberian permafrost sediment with 39 cold acclimation proteins, including chaperones and three cold shock proteins. These results indicated that the adaptive nature of E. sibiricum at near-freezing temperatures could be regulated by cellular physiological processes through the regulation of specific cellular proteins. Very recently, Mueller et al. (2010) applied the metaproteomics approach to biofilms from an acid mine drainage environment. The authors integrated extensive proteomic, geochemical, and biological information from 28 microbial communities representing a range of biofilm development stages and geochemical conditions to evaluate how the physiologies of the dominant and less abundant organisms change along environmental gradients. The initial colonist dominates across all environments, but its proteome changes between two stable states as communities diversify, implying that interspecies interactions affect this organism’s metabolism. Its overall physiology is robust to abiotic environmental factors, but strong correlations exist between these factors and certain subsets of proteins, possibly accounting for its wide environmental distribution. Lower abundance populations are patchier in their distribution, and proteomics data indicate that their environmental niches may be constrained by specific sets of abiotic environmental factors. This research establishes an effective strategy to investigate ecological relationships between microbial physiology and the environment for whole communities in situ (Mueller et al. 2010). Proteins from iron-oxidizing Leptospirillum Group II bacteria dominated all proteomics data sets (Fig. 9.20a). Mature biofilms with proportionally lower representation of Leptospirillum Group II had higher abundances of proteins from later biofilm colonizers. The subdominant groups included another iron-oxidizing species, Leptospirillum Group III, and two potentially mixotrophic archaea, G-plasma, and A-plasma (Fig.  9.20b). A small number of proteins also were derived from Actinobacterium 1, Actinobacterium 2, and Firmicutes sp. and other archaea (E-plasma, I-plasma, Ferroplasma Types I and II, and ARMAN-2). Overall, environmental stress response proteomics approaches have provided insights into the physiological responses of microorganisms to temperature, chemicals, and other stresses (Lacerda and Reardon 2009). While the up-regulation of known stress-response proteins was frequently observed, there were also discoveries of proteins involved in other detoxification or adaptation strategies, including novel transporter proteins, lipid biosynthesis pathways, and osmoprotectants. It is clear from this set of studies that proteomics analysis not only reveals system-wide stress responses but also has the ability to identify specific mechanisms of defense that characterize each stress condition.

Chapter 10

Whatever Doesn’t Kill You Might Make You Stronger: Hormesis

10.1 History Hormesis is well established in everyone’s thinking: “Whatever doesn’t kill you makes you stronger”. Yet for a long time, science has had difficulty accepting this as a matter of fact. For instance, if one was searching for the keyword “hormesis” in easily accessible sources some 15 or 20 years ago, one was overwhelmed with comments such as “charlatanry” or “unscholarly issue of homeopathy”. German pharmacologist Hugo Schulz was thought to be the first to describe hormesis in 1888 following his observations that the growth of yeast could be stimulated by small doses of poisons. This was coupled with the work of German physician Rudolph Arndt who studied animals given low doses of drugs, eventually giving rise to the Arndt-Schulz rule. This rule concerning the effects of pharmaca or poisons in low, respectively strong concentrations. According to this, highly diluted pharmaca or poisons enhance life processes, while strong concentrations may inhibit these processes and even terminate them. This rule has been applied intensively by homeopaths, to support their theories. Arndt’s advocacy of homeopathy contributed to the rule’s diminished credibility in the 1920s and 1930s and may be seen as one of the reasons for the marginalization of hormesis in pharmacology and toxicology. However, German Rudolf Virchow was the first but largely overlooked scientific descriptor of hormesis, his hypothesis being put forward three and a half decades before that of Schulz (Henschler 2006). Virchow observed an increase of the beating activity of tracheal epithelia ciliae by exposure to sodium and potassium hydroxide at low concentrations as well as a concentration-dependent decrease to arrest of beating activity at higher concentrations. Although reports on this phenomenon have continuously been published, little attention has been paid to it by biomedical researchers. This situation changed dramatically nearly a decade ago when Calabrese and Baldwin (2003a, b) published two papers with programmatic tiles: “Toxicology rethinks its central belief” and “Hormesis: the dose-response revolution”.

C.E.W. Steinberg, Stress Ecology: Environmental Stress as Ecological Driving Force and Key Player in Evolution, DOI 10.1007/978-94-007-2072-5_10, © Springer Science+Business Media B.V. 2012

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In fact, the dose–response relationship of exposed organisms does not obey a linear, but biphasic, relationship in many instances. Hormesis describes this biphasic relationship, where a low-dose stimulation and beneficial effect precedes a high-dose inhibitory and toxic effect. Kendig et  al. (2010) proposed a single, unambiguous, streamlined definition of hormesis as, “Hormesis is a dose-response relationship for a single endpoint that is characterized by reversal of response between low and high doses of chemicals, biological molecules, physical stressors, or any other initiator of a response.” We shall discuss whether or not this definition suffices from an ecological perspective. However, the older but similar definitions were questioned by Thayer et  al. (2005) who argue that many examples used to support the widespread frequency of hormesis are better described by the more general term “non-monotonic” dose responses. Non-monotonic is used to describe dose–response relationships in which the direction of a response changes with increasing or decreasing dose. Use of the term hormesis, with the associated descriptors of low-dose stimulation and highdose inhibition, can only be justified if there is an understanding of the biological processes underpinning that specific dose–response. Furthermore, in an ecological context, it is meaningful only if the Darwinian fitness of the organisms increases in the hormetic exposure range.

10.2 Examples Countless case studies display biphasic (non-monotonous) responses of cells or organisms to various challenges, and numerous meta-analyses have been published (e.g., Calabrese 2005; Calabrese and Baldwin 2001) describing hormetic dose–response curves. Calabrese scrutinized the vast number of experimental studies in different fields of biomedical research, covering several classes of chemicals (e.g., drugs such as anti-tumor agents, pesticides, heavy metals, plant growth accelerators, microbicides, occupational toxicants) and different types of ionizing irradiation, ending up in a series of reviews. A few examples are depicted in Figs. 10.1 and 10.2. Hormesis is well known from medicine, where under-dosage of antibiotics (Fig. 10.1 #57) or anti-tumor agents (Fig. 10.2) stimulate both pathogens and cancer cells. A general conclusion may be drawn from this tremendous amount of accumulated information: hormetic phenomena in individual life traits occur much more frequently than previously recognized. Hormesis manifests as a highly non-specific phenomenon with regard to the biological systems under study and with regard to the stressing agents used; it is reproducible and quantifiable. Does this generalization hold true if one analyzes the data sets in depth? For instance, exposing Daphnia magna to 4-nonylphenol increased its fecundity in a concentration-dependent fashion (Fig. 10.3, left). If only this life trait parameter is considered, this stimulation could be considered hormetic comparable to the increase in fecundity in Fig. 10.1 (3). However, if further parameters such as malformation of the neonates’ shell or first antenna are checked, it becomes obvious that stunted antennae occur even at the lowest exposure concentration, impairing the swimming capability

10.2  Examples

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Fig. 10.1  Selected published examples of hormetic effects: (1) pyrifenox on reproductive performance of codling moth Cydia pomonella; (3) 4-nonylphenol on the number of live offspring per Daphnia female; (5) cadmium chloride on the number of offspring per Daphnia female; (57) penicillin on the growth of Staphylococcus Oxford H (From Calabrese 2005 with references to the original papers in the supplementary materials. With permission from Elsevier)

of the neonates. 4-nonylphenol is embryotoxic, and the increased numbers of ­neonates are counterbalanced by the reduced viability of the offspring. In terms of sustaining the population, these results cannot be considered hormetic; they are toxic. The Daphnia case is not isolated. Weltje et al. (2005) presented more examples with synthetic xenoestrogens. They carried out a 96-h life-cycle test with the nematode Caenorhabditis elegans and 4-n-octylphenol (0.1–1,000 nM). C. elegans was chosen for this assessment because it possesses an estrogen receptor. A significant increase in the number of juveniles per adult was observed for concentrations up to 100 nM. Growth of the exposed nematodes, however, was significantly inhibited at all concentrations. For the concentrations 0.1–100 nM, the reduced body length may have been the result of allocating energy to reproduction rather than to growth. At 1,000 nM, 4-n-octylphenol had probably reached a toxic level as it no longer stimulated reproduction but still inhibited growth. In females of the gonochoristic prosobranch snail species Marisa cornuarietis, bisphenol-A (BPA) and 4-tert-octylphenol induced a complex syndrome of alterations referred to as “superfemales”, even at concentrations as low as 1  mg  l−1. Affected specimens are characterized by the formation of additional female organs, an enlargement of the accessory pallial sex glands, and a massive stimulation of egg and clutch production. This stimulation of egg production during the sexual repose

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10  Whatever Doesn’t Kill You Might Make You Stronger: Hormesis 35)

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Fig. 10.2  Selected published examples continued: (22) tannin on fertilization success of two urchin species; (35) g-rays on the life span of female house crickets; (98) waste on growth of the diatom Skeletoneman costatum; and an anti-tumor agent on yeast cell proliferation (From Calabrese 2005 with references to the original papers in the supplementary materials. With permission from Elsevier)

Fig. 10.3  Left: Total offspring produced by daphnids during exposure to concentrations of 4-nonylphenol. Right: Composition of developmental abnormalities resulting from exposure of daphnids to concentrations of 4-nonylphenol. Developmental arrest of embryos did not occur at any exposure concentration. No significant difference existed in the relative distribution of the three developmental abnormalities over the concentration–response curve (From LeBlanc et al. 2000. Courtesy of the National Institute of Environmental Health Sciences)

10.3  How Variable Are Stress Responses?

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phase of the snails is detrimental to the affected females because it causes a ­congestion of clutches in the pallial oviduct, leading to a rupture of the oviduct and ultimately to the female’s death. The paper on endocrine disrupters by Weltje et  al. (2005) was one of the first ­environmental studies with synthetic xenobiotics to question the generalizability of hormesis. Another cautionary tale is seen with Cd as Kaiser (2003) pointed to a striking example: animal studies suggested that low doses of this element could help prevent some cancers. However, Safe (2003) reported that at these low effective doses – even below those recommended as safe in the diet – Cd acts as an endocrine disrupter in female rats, causing growth in uterine and breast tissues that could lead to cancer. From an ecological perspective, true hormetic response stimulations elicited by biological, chemical, or physical stressors must lead to an increase in population fitness. In nature, however, one hormetic life trait response often takes place at the expense of another life trait variable. This cost could either be a decrease in another trait, as was shown for insects and daphnids, where an increase in number of eggs and neonates produced was counterbalanced by lower offspring survival. Several of the studies presented by Calabrese (2005) likewise showed varying degrees of hormesis and compensations in other traits if several life history parameters were measured. Alternatively, the cost could be paid over time with the hormetic response increase being followed by a subsequent decrease, where the organism “recovers” after the stress (Cedergreen 2008). What is the individual and population benefit if the benefit in one life trait is counterbalanced by another one? From an ecological point of view, biphasic effects only count if the overall effect is still beneficial; ­otherwise it is a pure zero-sum game only. Mixed effects occur even with dietary phytochemicals (natural xenobiotics), such as tannic acid, which are considered only beneficial. For instance, Saul et al. (2010) administered tannic acid to the nematode C. elegans and found a stronger lifespan-expanding effect with the lower concentration than with the higher concentration. Oxidative and thermal stress resistances also increased (Fig. 10.4), and the mean offspring numbers per worm remained unchanged as compared to the control. However, body length was reduced. This effect may be considered hormetic because the smaller body size most likely will not pose a risk to the worms in terms of ­persistence in the environment; conversely, smaller worms will have a reduced risk of being predated. This tannic acid example will be discussed below in more detail in terms of transcription.

10.3 How Variable Are Stress Responses? In nature, organisms are seldom challenged by only one stressor. What happens with exposure to multiple stressors? Is the response maintained if a second stressor is applied simultaneously? To address this issue, Engert and Steinberg (unpublished) carried out a simple experiment in order to figure out whether or not life traits which may be indicative of (hormetic) responses are constant over an gradient of another

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Fig. 10.4  Variations of lifespan and stress resistances in Caenorhabditis elegans administered increasing concentrations of tannic acid (From Saul et al. 2011. Modified)

environmental factor. The authors looked at energy allocation into major life history traits (lifespan, growth, reproduction) in a poikilothermic model animal, Moina macrocopa, exposed to humic substances at different temperatures. Elevated temperatures cause an oxidative stress in these cladocerans. The results of mean lifespan are presented in Fig. 10.5. At 15°C, the humic gradient decreased the life expectancy of this small, short-lived waterflea as did the exposure to 20°C but to a significantly smaller extent. Even a reversal can be seen: despite the reduced lifespan in the control at 25°C, humic-stress induced longevity in a dose-dependent fashion. Increasing the temperature further leads to a leveling off: at 30°C there is no lifespan modulation. This means that, at least in poikilothermic animals, a potential nonmonotonous response may depend on the ambient temperature and is by no means a constant response norm. Furthermore, it is very likely that similar non-constant stress responses occur along other environmental gradients. Since dose-response

10.4  Sustainability of Hormetic Responses

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relationships are usually evaluated under standard laboratory conditions, this issue clearly questions the generalizability of the hormetic phenomenon as an intrinsic response trait of the exposed organism. Applying even more ecological realism, Ferreira et  al. (2010) showed for the feeding rates of D. magna that antagonism was observed for the combination of Ni and extreme temperatures, whereas a synergism occurred in the combined exposure of Ni and low dissolved oxygen levels. This study clearly supports the notion that the modulation of life history trait variables upon exposures to chemical stressors are highly variable, rather than fixed responses. This aspect should find its way also into hormesis studies. Overall, most studies of hormesis are merely phenotypic and consider only one parameter. Do they neglect those parameters which are adverse and contradict the expectations?

10.4 Sustainability of Hormetic Responses Low dose growth stimulations in plants by herbicides which are toxic at higher doses have been recorded for some time. The herbicide most frequently used in the world, glyphosate, seems to be one of the herbicides which consistently elicits this growth response. When herbicide hormesis in plants has been reported, it is almost always at single time points and in individual plant traits, such as plant height, leaf area, shoot weight, etc. In a recent study, Cedergreen (2008) investigated growth of shoot parameters of barley, Hordeum vulgare, over time to detect whether the glyphosate-induced growth increase was sustained. The results showed that an actual biomass growth rate increase took place within the first week after spraying glyphosate (Fig. 10.6).

Fig. 10.6  The dry weight of barley, Hordeum vulgare, plants harvested once a week after the time of spraying for 8 weeks as a function of glyphosate dose. Data for the second experiment harvested 1 week after spraying are given with open symbols. Data are given as mean ± SE and are fitted to a biphasic dose–response model in the cases where this model gave the best fit based on residual sums of squares. Individual treatments which were significantly higher than controls are denoted with * (From Cedergreen 2008. With permission from Elsevier)

286 10  Whatever Doesn’t Kill You Might Make You Stronger: Hormesis

10.6  Underlying Mechanisms

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This initial growth boost kept treated plants larger than untreated plants for up to 6 weeks, but at harvest there was no significant difference between control plants and treated plants. Even though growth rates only increased during the first week after spraying, the first week growth rates were so fast that the biomass increases of the plants were maintained for approximately 6 weeks after spraying. Such a boost in growth could give plants receiving growth stimulating doses a competitive advantage over sensitive or adversely-affected species.

10.5 Hormesis in Mixtures The majority of mixture studies are conducted to investigate the effect of one compound on the inhibitory action of another. However, since stimulatory responses to low concentrations of chemicals are gaining increased attention and improved statistical models are available to describe this phenomenon of hormesis, scientists are challenged by the question of what will happen in the low concentration range when all or some of the chemicals in a mixture induce hormesis? Can the mixture effects still be predicted, and can the size and concentration range of hormesis be predicted? A study of Belz et al. (2008) focused on binary mixtures of tetraneurin-A, parthenin, or caffeic acid with one or two compounds inducing hormesis and evaluated six data sets of root length of Lactuca sativa, where substantial and reproducible hormetic responses to allelochemicals and herbicides have been found. Results showed that both the concentration range and amplitude of hormesis can be determined in the case of mixtures of chemicals showing large and reproducible hormesis and which appear to follow the model of concentration addition (Fig. 10.7).

10.6 Underlying Mechanisms Calabrese and Baldwin (2001) offer a mechanistic definition of hormesis as being a biphasic adaptive response to stimuli, the positive response being due to either a direct interaction with a vital substrate or an overcompensation reaction. The term “adaptive response” implies that low- and high-dose exposures activate more or less identical defense pathways and that the low-dose exposure trains the defense systems for future adverse, high-dose exposures. To date, this explanation remains a phenotypic description and does not adequately consider the underlying mechanisms of action. Thayer et al. (2005) raised some fundamental concerns: Hormesis (defined operationally as low-dose stimulation, high-dose inhibition) is often used to promote the notion that while high-level exposures to toxic chemicals could be detrimental, low-level exposures would be beneficial. Some proponents claim hormesis is an adaptive, generalizable phenomenon and argue that the default assumption for risk assessments should be that toxic chemicals elicit stimulatory (i.e., “beneficial”) effects at low exposures. In many cases, non-monotonic dose–response curves are called hormetic responses even in the absence of any mechanistic characterization of that response. Use of

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Fig. 10.7  Selected concentration–response relationships for the inhibition of root length of lettuce, Lactuca sativa. (a) Effect of parthenin, tetraneurin-A, and their 50:50% mixture and (b) effect of parthenin, caffeic acid, and their 50:50% mixture (From Belz et al. 2008. With permission from Elsevier) the term “hormesis,” with its associated descriptors, distracts from the broader and more important questions regarding the frequency and interpretation of non-monotonic dose responses in biological systems. A better understanding of the biological basis and consequences of non-monotonic dose–response curves is warranted for evaluating…risks. The assumption that hormesis is generally adaptive is an oversimplification of complex biological processes. Even if certain low-dose effects were sometimes considered beneficial, this should not influence regulatory decisions to allow increased environmental exposures to toxic and carcinogenic agents, given factors such as interindividual differences in susceptibility and multiplicity in exposures. (Thayer et al. 2005, courtesy of the National Institute of Environmental Health Sciences)

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Fig. 10.8  Venn diagrams representing of the number of transcripts identified as differentially expressed following high dose-rate, HDR, g-irradiation, low dose rate, LDR, g-irradiation and 125 I-IUdR exposures. The intersections indicate genes modulated in common for these exposures. (a) Induced genes, (b) repressed genes (From Sokolov et  al. 2006a. With permission from Elsevier)

It is interesting to note that many more papers have been published referring mainly to the phenotypic non-monotonous dose-response curve, although methods for mechanistic in-depth analyses are available. For instance, differential analyses of gene expression or protein synthesis appear to be promising methods to substantiate this notion. Indeed, there is an increasing body of evidence that the gene expression profiles of low-dose exposures differ from higher doses. Evidence comes from studies on irradiation (Ding et al. 2005; Sokolov et al. 2006a, Fig. 10.8), gravity (Allen et al. 2007), and drugs and toxic chemicals (Toyoshiba et al. 2006; Gong et al. 2007). Sokolov et al. (2006a) identified 2,303 differentially expressed genes after 2 h of cell growth following high dose-rate (HDR) g-irradiation of fibroblasts. Of these 2,303 genes, 1,164 genes were induced (Fig.  10.8a) and 1,139 were repressed (Fig. 10.8b). Following low dose-rat (LDR) g-irradiation of the cells in culture, the authors found 2,167 differentially expressed genes. Of these, 1,180 genes were upregulated (Fig. 10.8a) and 987 genes were down-regulated (Fig. 10.8b). Subsequently, Sokolov et al. (2006b) carried out Gene Ontology (GO) studies to characterize the regulative pathways. Oxidative phosphorylation, metabolism of nucleotides, protein kinase cascade, and cell cycle were among the up-regulated biological processes affected by g-irradiation. The translational elongation, negative regulation of cell growth, antigen processing, and protein targeting were among the down-regulated genes. Remarkably, only about two thirds of the differentially expressed genes were the same following both HDR and LDR g-irradiation exposures, indicating the involvement of distinct transcriptional programs in cellular response to irradiation delivered with the different dose rates. Administering paracetamol to rats, Toyoshiba et  al. (2006) analyzed low- and high-dose effects and identified two gene interaction networks clearly segregated by  the two doses: at lower doses, oxidative stress signaling pathways did not ­interact  with the apoptosis-related genes, but they did in the higher doses. In a more

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Fig. 10.9  Venn diagrams of modulated Gene Ontology terms in Caenorhabditis elegans exposed to 100, 200, and 300 mM tannic acid (increasing darkness of the circles) (From Pietsch personal communication)

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e­ nvironmentally relevant example, Gong et al. (2007) showed a hormetic increase in reproduction when the earthworm Eisenia fetida was exposed to trinitrotoluene. This effect was mirrored by transcriptional responses specific to the low-dose exposure. If one considers the lifespan extension in C. elegans by tannic acid (Fig. 10.4), this biphasic response appears to be real proof of hormesis: the lowest concentration had the strongest longevity effect while the highest concentration was toxic. The Gene Ontology (GO) analysis of a whole genome DNA microarray of C. elegans exposed to 100, 200, and 300 mM tannic acid showed that only a few processes were induced by all three concentrations (Fig. 10.9). For instance, there are no biological processes shared by all exposure concentrations and even none between the longevitypromoting lower concentrations. One biological process was common between the lowest (promoting) and the highest (retarding) concentration. Interestingly, the median concentration shared as much as 15 biological processes with the toxic concentration. With molecular functions, only three were shared by all exposure concentrations but only one by the longevity promoting lower concentrations. Together, these differences point at distinct transcriptional programs not only between the longevity-promoting and the toxic exposures but also between the two longevity-promoting concentrations themselves. A detailed list of the up-regulated regulatory pathways is presented in Table 10.1. In order to evaluate if a lifespan extension in C. elegans not only occurs with plant polyphenols but also with geopolymers like humic substances, the nematode

Table 10.1  GO analysis of the tannic acid regulated genes (From Pietsch personal ­communication). The cut-off for the genes being subject to this analysis was 1.25 as compared to the standard ACT-1. The analysis was carried out using DAVID software (david.abcc.ncifcrf.gov) >10−3 10−3 to 10−5 10−5 to 10−7 100 mM Biological processes Muscle contraction Cellular components Myosin complex Cytoskeleton Molecular function Serine hydrolase activity Phosphoprotein phosphatase activity Neurotransmitter transporter activity 200 mM Biological processes

Cellular components

Molecular function

300 mM Biological processes

Cellular lipid metabolic process Muscle contraction Organic acid metabolic process Protein metabolic process Actin cytoskeleton Cytoskeleton Extracellular matrix part Membrane part Cytoskeletal part Mitochondrial outer membrane Serine-type peptidase activity Phosphoprotein phosphatase activity Vitamin B6 binding Neurotransmitter transporter activity Active transmembrane transporter activity

Protein metabolic process Amine metabolic process Sulfur metabolic process Regulation of pharyngeal pumping Multi-organism process Neuropeptide signaling pathway Heterocycle metabolic process Cellular components Myosin complex Proteinaceous extracellular matrix Membrane part Cytoskeleton Mitochondrial outer membrane Molecular functions Phosphoprotein phosphatase activity Vitamin B6 binding Peptidase activity, acting on L-amino acid peptides Kinase activity Cysteine-type endopeptidase activity Active transmembrane transporter activity Carboxylesterase activity Neurotransmitter transporter activity Active transmembrane transporter activity One representative of each pathway is presented with p < 0.05. Individual significance levels are indicated by different gray levels as shown in the uppermost panel

292

10  Whatever Doesn’t Kill You Might Make You Stronger: Hormesis

Fig. 10.10  Survival rates and lifespans of Caenorhabditis elegans exposed HuminFeed® at increasing concentrations, mg l−1 DOC. With HuminFeed®, the differences between control and 2.5, 5, and 20 mg l−1 exposures were significant at the p <0.005 level. There were no significant differences between the control and the 25 mg l−1 exposure, indicating that the dose-response relationship was non-monotonous (likely hormetic) (From Steinberg et  al. 2007. Courtesy of Northeastern University, Boston)

Fig. 10.11  Venn diagram of modulated genes in Caenorhabditis elegans exposed to 2.5 and 25 mg l−1 HuminFeed® (red, above: up-regulated; green, below: down-regulated genes) (From Menzel 2010)

was exposed to HSs which has been proven effective in growth retardation in the water mold Saprolegnia parasitica (Meinelt et  al. 2007). Processed leonardite HuminFeed® significantly prolonged the life of the nematode in the low to medium concentration range (2.5, 5, and 10 mg l−1 DOC), whereas the 25 mg/L exposure was in or even below the range of the control animals (Fig. 10.10). It appears that the modulation of lifespan by exposure to HuminFeed® followed the hormesis

10.6  Underlying Mechanisms

293

Table 10.2  GO analysis of HuminFeed® up-regulated genes (From Menzel 2010). The cut-off for the genes being subject to this analysis was 1.7 as compared to the standard ACT-1. The analysis was carried out using DAVID software (david.abcc.ncifcrf.gov) >10−3 10−3 to 10−5 10−5 to 10−7 −1 2.5 mg l DOC Biological processes Carboxylic acid biosynthetic process Lipid biosynthetic process Cellular components Cytoskeleton Lysosome Molecular functions Ceramidase activity Lipase activity 25 mg l−1 DOC Biological processes

Determination of adult life span Lipid biosynthetic process Biogenic amine metabolic process Cellular component assembly involved in morphogenesis Coenzyme metabolic process Acetyl-CoA catabolic process Neuropeptide signaling pathway Cellular components Lysosome Intermediate filament cytoskeleton Mitochondrion Molecular functions Serine-type peptidase activity Cysteine-type endopeptidase activity Ceramidase activity Vitamin B6 binding Cofactor binding Cation binding Electron carrier activity One representative of each pathway is presented with p < 0.05. Individual significance levels are indicated by different gray levels as shown in the uppermost panel

­principle. The low to medium exposures expand the lifespan50 (lifespan at the 50% survival rate) by as much approximately 3 days, a lot for an animal that usually only lives about 20 days. To check whether the mechanism was an adaptive response in terms of differentially regulated genes at low-dose exposure being an increment – at least a huge one – of those differentially regulated at high-dose exposure, whole genome DNA microarrays were carried out with worms exposed to 2.5 and 25 mg l−1 HuminFeed®. The results are presented in Fig. 10.11 and make clear that the this assumption is not true. The exposure to 2.5 mg l−1 HuminFeed® up-regulated 524 genes, of which only 166 genes are also up-regulated in the 25 mg l−1 exposure – less than one third. The situation is even more confusing, because 86 of the genes up-regulated by the 2.5 mg l−1 exposure are down-regulated at the high concentration. This finding does not support the assumption of hormesis being an adaptive response. The regulatory pathways are significantly different, a conclusion that becomes more obvious when a GO analysis is carried out (Table 10.2).

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10  Whatever Doesn’t Kill You Might Make You Stronger: Hormesis

Overall, in an ecological sense, real hormesis rather than only non-monotonous dose-responses of single parameters occur, but it is less frequent than thought. In most published instances, only one life trait parameter is considered in terms of hormesis. Yet, only those non-monotonous dose-responses should be termed ­“hormetic” which increase the Darwinian fitness of organisms and hence may change population and even community structures, if only life trait is elicited. However, if there are contrasting responses in different life traits, the overall result should at least not risk the persistence of the population. The underlying signaling pathways are still obscure, but some mechanisms can be hypothesized: –– Various receptor isoforms possess different inducibility and induce different transcript quantities. This has been found with AHR2 isoforms in Atlantic salmon challenged by chlorinated dioxins (TCDD) (Hansson and Hahn 2008). The inability of invertebrate AHR homologs to bind dioxins and related chemicals (Hahn 2002) suggests that other pathways apply, because C. elegans is able to metabolize chemical compounds well known as AHR agonists (Menzel et  al. 2005a, 2007; Schäfer et al. 2009). –– Threshold effects of various reactions [e.g., cytochrome c oxidase inhibition (Letellier et  al. 1994) or phosphorylation and dephosphorylation reactions (Thomas et al. 2004)] are common. –– The same applies to threshold effects of intracellular signaling [e.g., by NO, where different concentration thresholds of NO elicit a discrete set of signal transduction pathways (Gunawardena 2005)] In sum, the few displayed mechanistic examples indicate that hormesis is not limited to a simple adaptive response but accompanied by a transcriptional activation of different regulatory pathways. Future studies should aim to: –– Decipher the precise profiles and networks that drive hormesis rather than extend the existing catalog of the hormetic phenomena; and –– Model hormetic effects in single life traits in terms of competiveness in protected as well as non-protected environments.

Chapter 11

Multiple Stressors as Environmental Realism: Synergism or Antagonism

Under field conditions, organisms seldom live in fulfillment of all their biotic and abiotic requirements. Rather, they have to face a wide range of different discomforts such as non-optimal temperatures, unpleasant light qualities and quantities, drought, flood, unbalanced nutrient compositions, hypoxia or hyperoxia, highly acidic or highly alkaline conditions, saline environments, and natural xenobiotic chemicals among the abiotic factors. Biotic factors include intra- and interspecific competitors as well as various enemies including predators, parasites, and pathogens. Yet, this natural situation becomes even more complex with exposure to synthetic xenobiotics. According current paradigms, organisms living under conditions close to their environmental tolerance limits appear to be more vulnerable to additional stresses; furthermore, increasing temperature and decreasing food or nutrient level appear to raise the toxicities of introduced chemicals (Heugens et  al. 2001). Actually, three recent reviews are devoted to examining the impacts of multiple stressors on the effect of synthetic chemicals (Holmstrup et al. 2010, Laskowski et al. 2010) as well as determining toxicity modulation mediated by global climate change (Noyes et al. 2009). After evaluating 150 animal-focused studies, Holmstrup et al. (2010) concluded that synergistic interactions between the effects of various natural stressors and toxicants are common; such interactions were reported in more than 50% of the studies, supporting the statement of Heugens et al. (2001) that organisms living close to their tolerance limits appear to be more vulnerable. Interesting antagonistic interactions were also detected, but in fewer cases (Table  11.1). The cases included in the following list cover the interactions of chemical and physical stressors with other abiotic stressors as well as multiple biotic stressors on the individual level and on higher aggregated biological levels. Plant studies are also considered.

C.E.W. Steinberg, Stress Ecology: Environmental Stress as Ecological Driving Force and Key Player in Evolution, DOI 10.1007/978-94-007-2072-5_11, © Springer Science+Business Media B.V. 2012

295

296

11  Multiple Stressors as Environmental Realism: Synergism or Antagonism

Table 11.1  Key effect studies of multiple stressors, at least one of which being an ecological stressor Environmental stressors Effect Observation Reference Stressor I Stressor II Individual level Birds Athene cunicularia (burrowing owl) Food quantity Insecticide

SYN

Reduced population growth

Gervais et al. (2006)

ANT

Reduced toxicity

Holmstrup et al. (2010)

Ambystoma tigrinum (tiger salamander) Pesticides Viral disease

SYN

Increased lethality

Kerby and Storfer (2009)

Rana sphenocephala (leopard frog) Insecticide UV

–

Reptiles Anolis carolinensis (Carolina anole) Insecticide Elevated temperature Amphibians

Rana clamitans (green frog) Insecticide Eutrophication (nitrogen compounds) Population Herbicide density Rana catesbeiana (bullfrog) Population Herbicide density Insecticide Eutrophication (nitrogen compounds) Insecticide Pathogenic fungus

SYN

Bridges and Boone (2003) Increased lethality

–

SYN

Boone et al. (2005) Jones et al. (2011)

Increased lethality

–

Jones et al. (2011) Puglis and Boone (2007)

–

Rana pipiens (northern leopard frog) Herbicide Slightly alkaline pH

SYN

Increased lethality

Chen et al. (2004)

Hyla chrsoscelis (Cope’s gray treefrog) Insecticide Competitor

SYN

Increased lethality

Mackey and Boone (2009)

Hyla versicolor (gray treefrog) Population Herbicide density Bufo americanus (American toad) Insecticide Population density

–

Jones et al. (2011)

–

Distel and Boone (2009) (continued)

11  Multiple Stressors as Environmental Realism: Synergism or Antagonism Table 11.1  (continued) Environmental stressors

297

Effect

Observation

SYN

Size at metamorphosis Teplitsky et al. (2007)

SYN

Age at metamorphosis

SYN

Delayed metamorphosis Change from behavioral to morphological defense

Teplitsky et al. (2005) Teplitsky and Laurila (2007)

Reduced transcription of stress genes

Olsvik et al. (2010)

Coregonus lavaretus (European whitefish) Cyanotoxins Ectoparasites SYN

Reduced fitness

Ernst et al. (2007)

Gasterosteus aculeatus (three-spined stickleback) Eutrophication Global warming SYN

Biomass increase

Moss (2010)

Danio rerio (zebrafish) Hypoxia PAHs

SYN

Development

ANT

Activity

Matson et al. (2008) Holmstrup et al. (2010)

ANT

Survival

Holmstrup et al. (2010)

SYN

Survival

Cardoso et al. (2005)

SYN ANT

Female growth Male growth

Stueckle et al. (2009)

Ephoron virgo (mayfly) Hypoxia Copper Hypoxia Insecticide

SYN –

Survival

van der Geest et al. (2002)

Coenagrion puella (damselfly) Pesticide Predation

SYN

Survival

Campero et al. (2007)

Rana arvalis (moor frog) Predation acid origin/ neutral exposure Predation neutral origin/ neutral exposure Rana temporaria (Europ. common frog) Fungicide Predation Population density

Predation

SYN

Reference

Fishes Salmo salar (Atlantic salmon) g-irradiation Metals: Al, Cd

Nickel Ictalurus puntatus (Channel catfish) Copper temperature

ANT

Planktonic and benthic invertebrates Hydrobia ulva (mud snail) Eutrophication Flood Uca pugnax (mud fiddler crab) Salt Insecticide

(continued)

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11  Multiple Stressors as Environmental Realism: Synergism or Antagonism

Table 11.1  (continued) Environmental stressors

Effect

Observation

Reference

Monoporeia affinis (amphipod) Parasite Surfactant

SYN

Parasite infection

Jacobson et al. (2010)

Sericostoma vittatum, Chironomus riparius (benthic insect larvae) Predation Insecticide SYN Survival Caenorhabditis elegans (benthic nematode) Electro­ Heat SYN magnetism Daphnia magna (great waterflea) Poor elemental Antidepressant drug food Low food Humic substances quality Food Fish predation deprivation Food Endocrine disruptor deprivation Predation Parasite (Caullerya)

Stress gene expression Junkersdorf et al. (2000)

ANT

Reduced toxicity

SYN ANT SYN

Offspring number Female lifespan Survival, life history variables

–

Heavy metals

SYN

Parasite Predation

Insecticide Parasite (Pasteuria)

Predation Insecticide Predation

Insecticide Parasite Parasite

SYN SYN ANT SYN SYN ANT

Insecticide Food deprivation Benign food Predation

Predation Predation

– SYN

Predation Insecticide

ANT SYN

Offspring

Predation

Insecticide

SYN

Reduced phenotypic plasticity

Predation

Insecticide

–

Macrophyte allelochemicals Parasite, different strains Suspended solids

Insecticide

Hansen et al. (2008) Steinberg et al. (2010a) Beklioglu et al. (2010)

SYN

Predation

Predation

Pestana et al. (2009)

Reduced defense structures Survival Age at maturity Offspring number Age Sterilization Reduced parasite fitness Life history traits

Lass and Bittner (2002) Hunter and Pyle (2004) Coors and De Meester (2008)

Coors and De Meester (2010)

Pauwels et al. (2010a) Pestana et al. (2010) Barry (2000)

SYN

Growth

Jansen et al. (2010) Burks et al. (2000)

SYN ANT SYN

Lifespan Offspring Food shortage, increased toxicity

Ben-Ami et al. (2008) Herbrandson et al. (2003) (continued)

11  Multiple Stressors as Environmental Realism: Synergism or Antagonism Table 11.1  (continued) Environmental stressors Oxygen depletion Heat Temperature extremes Low dissolved oxygen Daphnia spec. Cyanotoxin

299

Effect

Observation

Reference

Pesticide Cadmium Nickel Nickel Nickel

ANT ANT ANT ANT ANT

Feeding rate Feeding rate Feeding rate Feeding rate Survival

Holmstrup et al. (2010) Laskowski et al. (2010) Ferreira et al. (2010)

Nickel

SYN

Feeding rate

Food deprivation

SYN

Survival

SYN SYN

Survival, reproduction Chen et al. (2004) Survival, reproduction

Simocephalus vetulus (waterflea) Food quantity Acid pH Herbicide Slightly alkaline pH

Brachionus plicatilis (rotifer) Food restriction Oxidative stress ANT Lifespan of P0 Food restriction Oxidative stress ANT Lifespan of F1 Terrestrial invertebrates – insects, woodlice, earthworms Drosophila melanogaster (fruitfly) Parasite Drought, starvation Hypoxia Heat

SYN SYN

Pterostichus oblongopunctatus (ground beetle) Food deprivation SYN Heavy metal mixture: Zn, Insecticide SYN Pb, Cd Temperature Nickel SYN Pesticide SYN Nickel + pesticide SYN

Folt et al. (1999)

Kaneko et al. (2011)

Fitness Fitness

Hoang (2001) Lighton (2007)

Time to death Time to death

Stone et al. (2001)

Toxicity

Bednarska and Laskowski (2009)

Porcellio scaber (woodlouse) Heavy metal Elevated temperature

ANT

Toxicity

Holmstrup et al. (2010)

Protaphorura armata (springtail) Pyrene Cold

ANT

Toxicity

Holmstrup et al. (2010)

Dendrobaena octaedra (earthworm) Phenanthrene Cold

ANT

Toxicity

Holmstrup et al. (2010)

ANT

Stress resistance

Reviewed by Dimkpa et al. (2009)

Herbs, trees Various terrestrial plant species Non-pathogenic Salt, drought, osmotic soil bacteria stress, flooding, heat, nutrient deficiency, iron toxicity

(continued)

300

11  Multiple Stressors as Environmental Realism: Synergism or Antagonism

Table 11.1  (continued) Environmental stressors

Effect

Observation

Reference

ANT

Stress resistance

Reviewed by Poschenrieder et al. (2006)

Betula pubescens (mountain birch) Heavy metals Herbivory Heavy metals Drought

ANT SYN

Growth Growth

Eränen et al. (2009)

Vigna unguiculata (cowpea) UV-B Increased temperature

SYN

Growth, reproduction

Singh et al. (2010)

SYN

Growth, survival

Holmer et al. (2011)

SYN

Growth, survival

de los Santos et al. (2010)

North Japan rivers Deforestation Canalization

SYN

Biodiversity

Fausch et al. (2010)

Litter decomposition Eutrophication Zinc

SYN

Decomposition

Fernandes et al. (2009)

SYN

Shift to a new ecosystem

Hecky et al. (2010)

SYN

Survival

Wei and ChowFraser (2005, 2006)

SYN

Survival

Slocum and Mendelssohn (2008)

SYN

Survival

SYN

Survival

Goldman Martone and Wasson (2008)

Heavy metals, metalloids

Herbivores, parasitic fungi, viruses

Halophila ovalis (ephemeral seagrass) Eutrophication, Heat incl. pore water S2− accumulation Zostera noltii (dwarf eelgrass) Water Low light movement Ecosystem level Rivers

Lake Victoria Low wind stress Warming climate, Eutrophication Macrophytes Typha latifolia (common cattail) Water level Urbanization, invasive fluctuation competitor (Glyceria) Oligohaline marsh Disturbance herbivory

Salt marshes Anthropogenic disturbance Reduced tide amplitudes

Invasion of non-native plants Invasion of non-native plants

(continued)

11.1  Additive/Synergistic Effects

301

Table 11.1  (continued) Environmental stressors

Effect

Observation

Reference

Multiple stressors

SYN

Survival

SYN

Survival

Orth et al. (2006); Alber et al. (2008) Deegan et al. (2007)

Forests epidemiology: Mediterranean forest Drought, UV Ozone ANT

Survival

Eutrophication

Predator-removal

Paoletti (2006)

Pure mixture ecotoxicological studies are not listed below. Instead, the reader is referred to Noyes et al. (2009), Holmstrup et al. (2010), and Laskowski et al. (2010) SYN additive/synergistic, ANT less-than additive/antagonistic, – no obvious effect

11.1 Additive/Synergistic Effects There is evidence that organisms living under conditions close to their ecological tolerance limits are more vulnerable to additional stressors. Some detailed examples elucidate such adverse situations.

11.1.1 Seegrass: Heat Stress and Drift Algae Seagrasses are important benthic marine plants that create physical structure for sessile epibionts, reduce wave energy, stabilize sediments, act as nursery and feeding grounds for herbivores and predators, and contribute significantly to primary production. However, seagrass habitats are increasingly threatened by anthropogenic activity, for example, from stress associated with eutrophication (nutrient pollution and increases of drift algae) and climate change (Orth et al. 2006). Recently, Holmer et al. (2011) conducted a laboratory experiment to test whether abundance of the rhodophyte Gracilaria comosa (a drift alga) is resistant to wide environmental fluctuations, had negative effects on the small ephemeral seagrass Halophila ovalis, and whether the effects were exacerbated by high temperature. The authors found an additive negative effect of the two stressors when tested simultaneously on seagrass performance, with most data variability explained by the drift algae as exemplified with the growth of leaves, rhizomes, and roots. The authors showed: (a) that stress-resistant drift algae can have strong negative effects on a small ephemeral seagrass, (b) this negative effect can increase both additively and synergistically with increasing temperature depending on performance measure, and (c) the negative effects may be mediated by a build-up of dissolved porewater sulfides.

302

11  Multiple Stressors as Environmental Realism: Synergism or Antagonism

11.1.2 Amphibians: Environmental Stress and Predators Phenotypic plasticity is a widespread and important adaptation to spatially and temporally varying environments. Understanding the environmental dependence of adaptive responses in phenotypic plasticity is particularly important for contemporary populations, because these are exposed to an increasing number and amount of novel environmental stressors. However, the effects of additional stressors on the expression of adaptive plasticity have remained under-explored (Teplitsky et al. 2007). Teplitsky et  al. (2007) investigated the effects of acidity on the expression of inducible defenses in two moor frog (Rana arvalis) populations originating from either acidic or circumneutral waters. Coping with acid stress is energetically demanding, yet at least during the embryonic stage, acid-origin populations have higher acid-stress tolerance than do neutral-origin populations. This suggests that (i) acid stress could compromise the ability of tadpoles to invest in inducible defenses, but that (ii) this effect might differ among populations. In R. arvalis, inducible defenses consist of modifications of morphology, such as deeper tail fin and tail muscle and shorter body, that incur some costs, e.g., competitive ability or reduced growth and development rates, thereby setting the stage for potential tradeoffs between responses to acid stress and responses to predators. In both populations, predator presence resulted in later metamorphosis at a larger size. However, pH affected the metamorphic traits differently in the two populations: Exposure to the acid treatment did not affect metamorphic size in the neutralorigin population, whereas it resulted in increased size in the acid-origin population. Moreover, metamorphosis was delayed in the acid treatment of the neutral population but not in the acid population. In the neutral population, this resulted in an additive effect of acidity and predation stress on age at metamorphosis: in the acid/predatorpresent treatment, tadpoles metamorphosed significantly later than in the neutral/ predator-absent treatment. Overall, pH-related costs differed between populations. While tadpoles from the neutral population suffered from acid stress in terms of reduced developmental rate, those from the acid population seemed to suffer from neutral stress in terms of reduced size at metamorphosis.

11.1.3 Amphibians: Environmental Stress and Intraspecific Competition Competition affects the expression of inducible defenses, but because costs of behavioral and morphological antipredator defenses differ along resource gradients, its effects on defenses may depend on the traits considered. Teplitsky and Laurila (2007) exposed tadpoles of the common frog Rana temporaria to non-lethal predators (Aeshna dragonfly larvae) and to a gradient of intraspecific competition. The defense strategy of the tadpoles revealed a shift from morphological and behavioral

11.1  Additive/Synergistic Effects

303

defenses at low tadpole density to morphological defense at high density. Morphological responses mainly involve an increase in tail fin depth, which acts as a lure and distracts the attacks towards the tail from the body containing the vital organs. The tail is less vulnerable and can tear off easily, allowing the tadpole to escape the grasp of the predator. Tadpoles expressed strong antipredator behavior in the presence of predator. The tadpoles were hiding and thereby less visible in the presence of predators, but the level of investment in this response depended on the density of intraspecific competitors. At low densities, hiding behavior was strong, but hiding decreased as density increased so that predator presence had no effect on hiding in the highest density treatments. The two measures of activity level gave contrasting results. The first estimate (activity level as the proportion of active tadpoles over the total number of tadpoles) revealed a significant predator-density interaction: tadpoles were less active in the presence of predators when competition was low, but activity was not sensitive to predator presence when competition was high. In contrast, when activity was estimated as the proportion of tadpoles active over the number of visible tadpoles, the analysis revealed that the tadpoles had lower activity level in the presence of predators, but the predator-density interaction was not significant. Tail fin depth was significantly affected by predator presence but not by density alone. However, there was a significant predator-density interaction on tail fin depth. At the lowest density, tadpoles had relatively deep tail fins irrespective of the predator treatment. As density increased tadpoles had shallower tails in the absence of predators, but tail depth remained unaffected by density in the absence of predators. The results indicate that competition can strongly affect reaction norms of inducible defenses.

11.1.4 Combinations with Toxicants Introduced by Man 11.1.4.1 Amphibians: Pesticide and Predation Agricultural intensification, combined with pesticide application, has led to declines in many animal populations and resulted in the decrease of species richness in aquatic and terrestrial farmland communities. Pesticide application can decrease the fitness of individuals and lead to population declines, even of non-target populations. Harmful consequences of pesticides may only become apparent when combined with other stressors, notably natural ones such as predation. Teplitsky et al. (2005) investigated how exposure to a common fungicide (fenpropimorph) affected predation responses in the common frog Rana temporaria (Fig. 11.1). The concentrations of fungicide used were comparable to those found in nature. The higher concentration of fungicide reduced tadpole activity late in the experiment, and few of the tadpoles reached metamorphosis. In the lower concentration, the ability to respond adaptively to predator presence was not affected, but the costs in terms of delayed metamorphosis and smaller relative body size of this response were increased.

304

11  Multiple Stressors as Environmental Realism: Synergism or Antagonism

Fig. 11.1  Rana temporaria tadpole activity in the pesticide and predator treatments during the three observation periods (early, middle, and late in development). Circles: no pesticide; squares: 2 mg l−1; triangles: 11 mg l−1. Open symbols stand for the absence of predator, filled symbols for the presence of predator (From Teplitsky et al. (2005). With permission of the American Chemical Society)

11.1.4.2 Damselfly Larvae: Pesticide and Predation Campero et al. (2007) studied interactive effects of pesticide and predation cues with larvae of the damselfly Coenagrion puella. Larvae were reared at three different predation risk levels and a range of environmentally realistic concentrations of three pesticides used worldwide (atrazine, carbaryl, and endosulfan). The authors compared key developmental responses (growth rate, developmental time, and final size) against food ingestion, assimilation, and conversion efficiency and acetylcholinesterase (AChE) activity. Predation risk impaired all parameters, including AChE activity, while the effects of pesticide stress were smaller for atrazine and endosulfan and absent for carbaryl. The effects of both stressors and their interaction on life history were mostly indirect through resource acquisition and energy allocation. Compensatory physiological mechanisms to pesticide stress (atrazine and endosulfan) were present in larvae reared in the absence of predation stress but were offset under predation stress. As a result, smaller size (atrazine and endosulfan) and lower growth rate (endosulfan) from pesticide stress were only found in the highest predation risk treatment. Overall, damselfly populations at high density and living in fishponds are more affected by pesticides than populations at low densities in fishless ponds.

11.1  Additive/Synergistic Effects

305

50%

100%

100

80

) survival (%

120

100

80

ur)

ho

e(

20 40

72 60 80 coppe 100 96 120 r (mg/L )

tim

0

re

su

po

ex

0 24 48

20

su

ho

e(

20 40 72 60 coppe 80 100 96 r (mg/L 120 )

re

0

40

po

0 24 48

20

60

ex

40

ur)

60

tim

) survival (%

120

Fig. 11.2  Survival of newly hatched Ephoron virgo larvae after 0–96 h of exposure to different concentrations of copper at 100% and 50% air saturation (van der Geest et al. (2002). With permission from Wiley)

11.1.4.3 Mayflies: Hypoxia and Copper In many rivers, the number of typical riverine insect species, such as mayflies, stoneflies, and caddisflies, is greatly reduced compared to historic records. This can no longer be explained by high concentrations of a relatively small number of dominant toxicants since many rivers have changed from heavily contaminated systems with a few selected key toxicants to systems with complex contamination. This contamination consists of many substances in low concentrations coinciding with other unfavorable conditions, such as low oxygen concentrations. It has been hypothesized that the joint adverse effects of such multiple stressors may be a steering factor in the distribution of riverine insect species. Van der Geest et al. (2002) therefore determined the combined effects of toxicants and oxygen depletion. Larvae of the mayfly Ephoron virgo were exposed to copper under normoxic and hypoxic conditions. The median effective concentrations for copper-induced mortality were significantly lower in the hypoxia treatments than in the normoxia treatments (Fig.  11.2). Overall, the combination of stressors (copper and lowered oxygen) has a stronger impact than can be expected of the individual factors alone. 11.1.4.4 Potworms: Temperature and Phenanthrene Enchytraeus doerjesi is a recently discovered terrestrial enchytraeid species that is easy to culture and fast growing. The animals were exposed to increasing ­phenanthrene concentrations at increasing temperatures. Both temperature and phenanthrene significantly affected population dynamics of E. doerjesi (Laskowski et al. 2010).

306

11  Multiple Stressors as Environmental Realism: Synergism or Antagonism

Fig. 11.3  The three-dimensional plot showing how the population growth rate (l per week) of potworms, Enchytraeus doerjesi, depends on phenanthrene (PHE) and temperature. Arrows indicate the evolutions of the response with increasing temperature and PHE concentration. Note that the relationship with phenanthrene concentration gets steeper with increasing temperature and that at the highest phenanthrene concentration the temperature effect reverses (R2 = 79%, p < 0.0001) (From Laskowski et al. (2010). With permission from Elsevier)

Growth rate increased with temperature, and the animals reproduced at extremely low levels in the 10°C treatment (Fig. 11.3). Phenanthrene did not increase mortality at this temperature. However, at higher temperatures, phenanthrene caused a significant decrease in population growth rate. The authors found that the relationship between population growth rate and combined effect of phenanthrene and temperature was non-linear and impossible to predict without experimental data.

11.2 Mixed Effects Stress adaptations often include a trade-off of weakened performance in non-local conditions, resulting in divergent selection and potentially in genetic differentiation and evolutionary adaptation. A study by Eränen et al. (2009) demonstrated an adaptation of mountain birch (Betula pubescens czerepanovii) populations from industrially polluted areas of the Kola Peninsula, north-western Russia, to heavy metals, whereas no adaptations to wind or drought stress were detected in populations from windexposed sites. Heavy metal-adapted seedlings were maladapted to drought; rather, a trade-off was visible in the drought treatment, where control-origin seedlings outperformed heavy metal-adapted seedlings. This indicates that heavy metal adaptation in mountain birch was stressor-specific and did not result in co-tolerance but rather in maladaptation to drought and possibly other forms of abiotic stress. This is in accordance with the theory that adaptation to stress carries a cost, and spending resources on defense or resistance leads to weakened performance in conditions where these traits are not needed (Bijlsma and Loeschcke 2005).

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Contrary to drought stress, field data showed that Betula seedlings from polluted habitat origin suffer less leaf damage from insect herbivores than control origin seedlings, indicating co-resistance to at least one form of biotic stress in the heavy metal-adapted seedlings. Increased herbivory resistance of heavy metal-adapted plant populations has been detected in several taxa (see Chap. 6). This co-tolerance is mainly attributed to defense mechanisms derived from heavy metals intoxicating the herbivores. Yet, this mechanism did not apply in the study conducted by Eränen et al. (2009), since the detected variation in herbivore damage was not due to leaf physical characteristics but rather to physiological or chemical characteristics. The underlying mode of action of this interesting finding, however, remained obscure.

11.3 Antagonistic Effects Less-than additive or even antagonistic effects appear seldomly in combined ­exposures but provide interesting surprises.

11.3.1 Food Stress and Natural Xenobiotics In freshwater systems, many abiotic and biotic factors determine the natural fluctuation of Daphnia sp. populations: climatic and water quality parameters, quantitative and qualitative food quality and quantity, predation, and humic substances. Many factors/stressors act in concert. In a recent paper, Steinberg et al. (2010a) supplied Daphnia magna with two different diets (chlorococcal alga Pseudokirchneriella subcapitata and baker’s yeast) fed ad libitum and exposed it to an environmentally realistic concentration of humic substances (HSs). Exposure to HSs caused a transcriptionally controlled stress response in CAT and HSP60 genes. Furthermore, exposure to HSs reduced antioxidant capacity. A much stronger oxidative stress was caused by feeding yeast, reducing anti-oxidative capacity by approximately 50% compared to the algae diet. This reduction is most likely due to the yeast cell wall’s ability to resist digestion; the authors assumed that the biochemical machinery in the gut continuously activated oxygen to cleave the yeast cell wall and thus reduced the antioxidative capacity of the animals. In addition to the stress, HS exposure extended the mean lifespan of both the algae- and yeast-fed D. magna, at the expense of offspring numbers. Yeast-fed animals exposed to HSs changed their energy allocation by reducing life span but increasing offspring numbers on a comparatively low level, whereas algae-fed animals increased lifespan but reduced offspring number on a comparatively high level. These data demonstrate that ecologically relevant parameters are differently affected by the simultaneous action of two environmentally relevant stressors, such as suboptimal diet and natural xenobiotics. This probably applies to many other zooplankton as well. It is interesting to note that simultaneous exposure to two

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stressors in the presented scenario did not have a synergistic but an antagonistic gross effect. This should provide feedback to population structure, intra- as well as interspecies competition, and succession. One may assume that, for instance, several succession phenomena have been attributed to more classical environmental factors, such as light or temperature, that are in reality due to changing food qualities and simultaneous stress by a second challenge.

11.3.2 Predation Threat and Parasites Host-parasite interactions are shaped by the co-evolutionary arms race of parasite virulence, transmission success, and host resistance and recovery. The virulence and fitness of parasites depend on host condition and is mediated by host energy constraints. Recently, Coors and De Meester (2010) investigated to what extent stress imposed by predation risk influenced host-parasite interactions. They challenged the crustacean host Daphnia magna with the sterilizing bacterial endoparasite Pasteuria ramosa and simultaneously exposed the host to fish kairomones. Parasite virulence was not influenced by predation threat; however parasite fitness decreased in the presence of fish kairomones. This effect was attributable to reduced somatic growth of the host, presumably resulting in fewer resources for parasite development. The smaller size of kairomone-exposed hosts resulted in an exhibited antipredator strategy consisting of a re-allocation of resources to early reproduction instead of somatic growth. This response is advantageous for the prey under sizeselective fish predation pressure and results at the same time in a fitness disadvantage for the parasite P. ramosa.

11.3.3 Non-pathogenic Bacteria and Systemic Resistance in Plants Dense populations of microorganisms colonize the root zone of plants. Rootcolonizing, non-pathogenic bacteria can increase plant resistance to biotic and abiotic stress factors. Dimkpa et al. (2009) reviewed the possible regulatory mechanisms of and benefits to plant hosts. One mechanism appears to start with a kind of infection stress to the plant. Inoculation with non-pathogenic root zone bacteria can trigger signaling pathways that lead to higher pathogen resistance of the host – the so-called induced systemic resistance (ISR). This is possible because a plant’s immune system consists of two branches: one responding to pathogen virulence factors, and the other recognizing and responding to elicitor molecules that are also typical for many non-pathogenic bacteria. Some bacteria, such as Bacillus sp., have been shown to induce ISR, and the primed physiological state of an inoculated plant could therefore be one explanation for increased tolerance against abiotic stresses. Indeed, the phenomenon of priming, although not yet fully understood at the molecular

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level, is thought to be associated with an accumulation of inactive signaling proteins which become activated and transduced upon subsequent exposure of the plant to similar stresses. In addition, observed changes in gene expression in Arabidopsis thaliana, first inoculated with Paenibacillus polymyxa and then exposed to drought or infected with the pathogenic bacterium Erwinia carotovora, support the conclusion that genes involved in plant response to biotic and abiotic stresses may be coregulated. Consistent with this, constitutive expression of the rice OSMYB4 gene encoding a transcription factor involved in cold acclimation resulted in elevated tolerance of transgenic A. thaliana to both abiotic (salt, UV, ozone, drought) and biotic (viruses, bacteria, fungi) stresses (Dimkpa et al. 2009). The authors conclude their review with an outlook that the cross-protection of root-colonizing, non-pathogenic bacteria may be applied in agricultural production systems affected by a changing climate, in phytoremediation, and in biofertilization. In summary, the displayed examples make clear that multiple stressors act in concert, but only a few experimental studies have investigated how multiple stressors affect organisms. Recent evidence suggests that stressors not only occur simultaneously but also can act interactively in ways that cannot currently be predicted based on results from single stress experiments. Empirical evaluation using multiple stressors is necessary.

sdfsdf

Chapter 12

One Stressor Prepares for the Next One to Come: Cross-Tolerance

Being stressed by, for instance, a chemical trigger can result in an organism increasing resistance to other chemicals or even to physical and biological triggers. This phenomenon is called cross-tolerance or multiple-stress resistance. Due to a rapidly changing environment, in prokaryotic microorganisms cross-tolerance to environmental stressors seems to be the common case rather than an exception and is based on one key regulatory pathway, the sS regulation (see also Chap. 7), whereas crosstolerance is somewhat less common in eukaryotic organisms and based on several regulatory mechanisms. In eukaryotes, several mechanisms are discussed: elevated concentrations of stress proteins (HSPs) (e.g., Vierling 1991; Todgham et al. 2005; Sung et al. 2008; Lu et  al. 2009; Sørensen et  al. 2009; Roberts et  al. 2010; Ryckaert et  al. 2010); increased concentrations of osmolytes in plants, yeasts, and animals such as trehalose, mannitol, and other sugars (Lapinski and Tunnacliffe 2003; Alvarez et al. 2004; Banti et al. 2008; Benoit et al. 2009; Lu et al. 2009); increased contents of spontaneous antioxidants in plants such as ascorbate and glutathione (Streb et al. 2008; Chao and Kao 2010); or high body fat content (Harshman et al. 1999). Very recently, Cao et al. (2010) reported that ABC exporters also have the potential to facilitate cross-protection in plants if heavy metals are involved. Based on studies with D. melanogaster, there are some concerns about the universality of cross-tolerance. For instance, in cold-treated flies, Sinclair et al. (2007) and MacMillan et al. (2009) did not find correlations to any of the other stressors applied, suggesting different mechanisms of tolerance. This supports arguments that correlations between stress tolerances may be coincidental rather than based on one common defense regulation, at least in D. melanogaster. Selected studies on cross-tolerances are listed in Table 12.1; to show similarities in plants and animals, studies are listed based on the primary stressor and the subsequent resistance rather than the organismal kingdoms.

C.E.W. Steinberg, Stress Ecology: Environmental Stress as Ecological Driving Force and Key Player in Evolution, DOI 10.1007/978-94-007-2072-5_12, © Springer Science+Business Media B.V. 2012

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Table 12.1  Selected studies of cross-tolerance induced by different environmental stressors, excluding immunology Environmental stressors Primary stressor Resistance against References Free-living microorganisms (food compromising organisms and pathogens excluded) Alkaline pH Heat Vibrio parahaemolyticus – Koga et al. (2002) H2O2 Starvation Heat V. parahaemolyticus – Koga and Takumi (1995b) Mild osmolyte stress H2O2 Heat Cd V. parahaemolyticus – Koga and Takumi (1995a) Mild osmolyte stress Cd Heat Mild osmolyte stress Acid pH Heat V. parahaemolyticus – Koga et al. (1999) Membrane-irritants (crystal violet) Natural detergents Starvation Salt Pseudomonas aeruginosa – Siddiqui and Shaukat (2003) H2O2 Heat Acid pH Substrate deprivation Oxidative stress Nitrosomonas europaea – Chandran and Love (2008) Desiccation Short-term osmotic Rhodococcus opacus – Alvarez et al. (2004) stress Heat Ethanol Vibrio – Gresikova et al. (1997) Free-living yeasts Phosphorus-limited growth

Heat

Plants and animals Heat Anoxia/hypoxia Cold

Cold

Desiccation Heat Bacterial infection Osmotic stress Heavy metals (Cd) Heavy metals High light intensities Heat Pathogens Desiccation

Saccharomyces cerevisiae – Lu et al. (2009)

Arabidopsis Banti et al. (2008, 2010); tidepool sculpin Oligocottus maculosus – Todgham et al. (2005) Oryza sativa – Saltveit (2002); Drosophila – Bubliy and Loeschcke (2005); pea Pisum sativum – Georgieva and Lichtenthaler (2006); codling moth Cydia pomonella – Chidawanyika and Terblanche (2011) Drosophila – Bubliy and Loeschcke (2005) Drosophila – Bubliy and Loeschcke (2005) Artemia franciscana – Sung et al. (2008) O. maculosus – Todgham et al. (2005) Oryza sativa – Chao and Kao (2010) P. sativum – Streb et al. (2008); Arabidopsis – Cao et al. (2010) P. sativum – Streb et al. (2008) Drosophila – Bubliy and Loeschcke (2005); Alpine plants – Larcher et al. (2010) Three crops – Plazek and Zur (2003); Płazek et al. (2004); × Triticosecale – Gołȩbiowska and Wȩdzony (2009) Drosophila – Bubliy and Loeschcke (2005) (continued)

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Table 12.1  (continued) Environmental stressors Primary stressor Resistance against Starvation

Heat Desiccation

Cold Aceton fume Oxidative stress Drought/dehydration Cold Heat UV irradiation UV irradiation

Ozone Salinity H2S Urea Ammonia Humic substances Heavy metals Cu Pesticides

Drought Heat Pathogens Pathogens Irradiation Multiple stresses Heat Ammonia Urea Physical stress (netting) Osmotic stress Pathogens, parasites, herbivores Zn Cold Drought Sulfite Air pollution (SO2)

References Drosophila – Bubliy and Loeschcke (2005) Drosophila – Harshman et al. (1999); Bubliy and Loeschcke (2005) Drosophila – Bubliy and Loeschcke (2005) Drosophila – Harshman et al. (1999) Brachionus plicatilis – Kaneko et al. (2011) Folsomia candida – Bayley et al. (2001); Belgica antarctica – Benoit et al. (2009) B. antarctica – Benoit et al. (2009) P. sativum, wheat Triticum aestivum – Alexieva et al. (2001) P. sativum, T. aestivum – Alexieva et al. (2001) Cucumber Cucumis sativus – Teklemariam and Blake (2003) Tobacco Nicotiana tabacum – Yalpani et al. (1994) Arabidopsis – Sharma et al. (1996) Europian olive Olea europaea – Remorini et al. (2009) Various plants – reviewed by Tuteja (2007) C. elegans – Miller and Roth (2007) Drosophila – Borash et al. (2000) Swordtail Xiphophorus – Meinelt et al. (2004) Waterflea Moina – Suhett et al. (2011) Various plants, reviewed by Poschenrieder et al. (2006); birch Betula pubescens – Eränen et al. (2009) D. magna – Lopes et al. (2005) Green alga Chlorella ellipsoidea – Clare et al. (1984) Corn Zea mays – - Malan et al. (1990) C. ellipsoidea – Rabinowitch and Fridovich (1985) Z. mays – Malan et al. (1990)

12.1 Cross-Tolerance in Microorganisms 12.1.1 Escherichia coli Most studies consider pathogenic or food-quality compromising microorganisms, but only a few papers deal with free living microbes in their native habitats which, due to environmental changes, pose fluctuating challenges for the microorganisms. The ability to adapt rapidly to changing environmental conditions is crucial for growth and survival of bacteria in their natural environments and is best studied with enteric bacteria such as E. coli.

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At the molecular level, the general stress response is dependent on a subunit of RNA polymerase, sS (encoded by rpoS). s-factors are bacterial proteins that help control how genes are used. Regulation of sS occurs at nearly every theoretically possible level. rpoS transcription is stimulated by controlled downshifts in growth rate as well as by continuous reduction in growth rate; the latter results in an inversely correlated increase in rpoS transcription. By contrast, abrupt cessation of growth, as for example in response to sudden glucose starvation, only weakly increases rpoS transcription. rpoS translation, i.e., the rate of translation of already existing rpoS mRNA, is stimulated (i) by high osmolarity (a hyperosmotic shift rapidly activates translation more than 5-fold, but continuous growth at high osmolarity also has clear effects), (ii) during growth at moderately low temperatures, (iii) on reaching a certain cell density during growth in minimal glucose medium, and (iv) in response to a pH downshift in rich medium (HenggeAronis 2002). Besides this multifaceted regulation of sS synthesis, there is also control of sS degradation. In response to stresses such as starvation, a shift to hyperosmolarity, classical heat shock, or a pH downshift to pH 5, sS proteolysis is considerably reduced or even completely inhibited. As a consequence, sS rapidly accumulates in the cell and activates response genes. The kinetics of this stabilization can be very rapid (on hyperosmotic shift) or can take somewhat more time (after heat shock). This indicates that even in cases where the same level of sS regulation is affected by different stress conditions, the regulatory mechanisms involved are likely to be different (Hengge-Aronis 2002). Weber et al. (2005) later identified a total of 481 sS-dependent genes and stated that this sS-regulon comprises up to 10% of all E. coli genes; hence, it is not surprising that any stressful challenge to the bacterial cell results in the activation of several response genes and produces cross-tolerance.

12.1.2 The Marine Vibrio Parahaemolyticus In several papers, Koga et al. (1995a, b, 1999, 2002) investigated cross-tolerance in the halophilic bacterium Vibrio parahaemolyticus, commonly residing in marine environments. For instance, alkali-adapted cells were found to have increased resistance against various stresses, including heat and hydrogen peroxide. In similar experimental set-ups, Koga and co-workers showed that starved V. parahaemolyticus cells were resistant to thermal exposure, mild osmolyte stress, and oxidative stress. In addition, heat-adapted cells resisted Cd and mild osmolyte stresses and, vice versa, Cd-treated cells possessed an increased tolerance to heat and mild osmolyte stress. In another study, the researchers demonstrated that acid-adapted cells tolerated stresses by increased temperature and membrane-irritating chemicals. The authors assume that these cross-tolerances were facilitated by HSPs.

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12.2 Free-Living Yeasts Yeast, Saccharomyces cerevisiae, responds to a variety of environmental stresses, including heat shock and growth limitation. There is considerable overlap in these responses both from the point of view of gene expression patterns and cross-protection for survival. Lu et al. (2009) performed experiments in which cells growing at different steady-state growth rates were subjected to a short heat pulse. Slow growth rates were maintained by phosphorus deficiency. The authors found that cells growing slowly were cross-protected for heat shock.

12.3 Examples of Cross-Tolerance in Plants Plants are continuously challenged by abiotic and biotic stress factors. Because they do not have the choice of flight as mobile animals have, they have developed a variety of strategies against these attacks which will be exemplified by recent studies.

12.3.1 UV-Stress and Resistance Against Pathogens The existence of common defense systems to combat stress was first inferred from simple observations that plants resistant to one stress are often more resistant to others. In some cases, the resistance phenotypes could even transcend the biotic– abiotic stress boundary. For example, ozone exposure can induce resistance to virulent phytopathogenic Pseudomonas syringae strains in Arabidopsis and to tobacco mosaic virus in tobacco (Fig. 12.1). The cross-tolerance is only possible if the whole plant is exposed to the primary signal or if systemic signals are also stimulated to ensure robust systemic resistance phenotypes (Bowler and Fluhr 2000). Formation of ROS leads to alterations in intracellular redox homeostasis, a consequence of which is the activation of specific signaling pathways mediated by H2O2. The addition of H2O2 or its experimental generation in catalase-antisense transgenic plants by exposure to high light irradiation can cause the induction of several defense-related genes (Fig.  12.2). The use of plants with reduced H2O2detoxifying capabilities exemplifies the potential role of this molecule as a signal. Indeed, enzymes that scavenge H2O2 are down regulated during pathogenesis. Conversely, H2O2 is a potent activator of certain MAP kinase cascades which are components of pathogen defense signaling (Bowler and Fluhr 2000). The role of H2O2 as an intracellular signal in animal cells is well known. For example, it activates the NF-kB transcription factor which mediates inflammatory, immune, and acute phase responses to diverse stress stimuli. Several plant disease resistance genes share some homology with molecules involved in NF-kB-mediated responses, indicating that similarities exist between animal and plant stress signaling systems.

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Fig. 12.1  Pre-treatment of plants with a sub-lethal dose of ozone or ultraviolet (UV) irradiation can confer tolerance to a virulent pathogen or other abiotic stressors such as drought, heat, or cold. A plant not given this pre-treatment will die (From Bowler and Fluhr (2000). With permission from Elsevier)

Pathogen defense in plants also involves the production of nitric oxide (NO) which, when combined with • O2 - , can generate highly toxic molecules such as peroxynitrite radicals. Although peroxynitrite is an important intermediate in the phagocytic oxidative burst in animals, this does not appear to be the case in plants. Instead, NO appears to act in conjunction with H2O2 rather than • O2 - . A further complication is that, as with other reactive oxygen species, NO can have opposite effects depending on the applied exogenous doses and the degree of insult that the plant is suffering (Bowler and Fluhr 2000). In many instances, single cells are primarily attacked and the responses of cells must be integrated with the response at the whole plant level. Systemic signaling

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Fig. 12.2  Systemic expression of the pathogenesis-related protein PR-1 in local and distal leaves of catalase-antisense plants after light treatment (see text for explanation) (From Bowler and Fluhr (2000). With permission from Elsevier)

has been intensively studied in response to localized pathogen attack and wounding, and systemic signals are also generated in response to abiotic stresses. During pathogen infection, long-range signaling can lead to systemic acquired resistance (SAR) in which localized treatment with an avirulent pathogen gives robust wholeplant resistance to unrelated virulent pathogens; this resistance can last up to several months. Conversely, systemic signaling in response to wounding can enhance defense against insects. In both cases, the signaling systems involve SA, JA, and ethylene. Cross-talk has been observed in several instances, and although in some cases the pathways can be mutually antagonistic, in other situations they can be coregulated and synergistic. Conversely, it has been reported that the controlled generation of H2O2 in plants that have decreased ROS scavenging capacity because of compromised catalase expression results in both local and systemic induction of a pathogenesis-related protein (PR-1) (Fig. 12.2) and subsequently in inducible local resistance to bacterial pathogens. In transgenic tobacco plants expressing an antisense catalase construct (Cat1AS), H2O2 can be generated experimentally by shifting the plants to photoinhibitory light conditions. This system has been used to investigate the role of H2O2 in (a) local and (b) systemic signaling. (a) Half a leaf

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was covered with foil during treatment with high light irradiation, whereas in (b) a top leaf was entirely covered to shield it from the high light irradiation. Following exposure to photoinhibitory light for 2  days the foil was removed and the plants were returned to low light intensity levels for 2 weeks before harvest. (a) Samples were collected from the exposed and unexposed areas of the same leaf, and in (b) from different exposed and unexposed leaves. The western blot analysis of PR-1 abundance (right) demonstrates that PR-1 levels increase only in antisense and not control plants and that both exposed (E) and covered (C) areas contain increased levels, even though the covered areas did not have any visible damage (indicated by a minus symbol, damage is indicated by a plus symbol, damaged areas at the time of harvest are indicated in light-green on the plants). (a) H2O2 can stimulate local responses, whereas in (b) a role for H2O2 is implicated in systemic signaling.

12.3.2 Heavy Metal Stress and Resistance Against Pathogens and Parasites Although fungi, viruses, and herbivores continuously attack plants, disease is the exception rather than the rule because of host resistance. To succeed, an attack must overcome the diverse defense strategies that plants deploy against the invader. This requires the interaction of a susceptible host and a virulent pathogen. A third indispensable factor to complete the so-called disease triangle (Fig. 12.3) is a conducive environment. Poschenrieder et al. (2006) summarize that climate, soil properties, competition, and human activity are among the most relevant environmental factors determining disease intensity in plants. Attention is focusing on metal hyperaccumulator plants, not only because of their potential use in phytoremediation (Kramer 2005; see also Chap. 6) but also as an object of fundamental research in the field of stress signaling and transduction pathways. Adequate intracellular concentrations of essential metal ions are not only required for optimal growth and development of plants and their enemies but also for pathogen virulence and plant defenses. Poschenrieder et al. (2006 with references therein) provide several interesting examples: • High levels of zinc or manganese are required in the mandibles of seed-penetrating larvae of moths and beetles. Larvae of other coleopterans which have little if any ability to chew into seeds do not have metal in their mandibles. • High levels of Fe are needed in bacterial infection processes as exemplified with Erwinia chrysanthemi. Full virulence of this pectinolytic enterobacterium depends on the production in planta of specific siderophores to facilitate the iron demand. • Metal-translocating ATPases or metallothionein-like proteins are required in plant fungal infections. If the phytopathogenic fungus Colletotrichum lindemuthianum lacks the gene CLAP1 encoding a Cu-transporting ATPase it forms only few appressoria and is unable to induce disease symptoms in beans. A high

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Fig. 12.3  The disease triangle shows that disease intensity (area of the triangle) depends on three interacting factors: the plant, the pathogen, and the environment. The metal ion concentration in the environment can have positive or negative influences on pathogen virulence and plant susceptibility. Deficient concentrations of essential metal ions threaten the fitness of both interacting organisms. Nutrient deficiency will then largely determine competitiveness and infection type. Under conditions of metal ion toxicity, the degree of metal avoidance and/or tolerance of the interacting organisms will determine the host parasite–interaction (From Poschenrieder et al. (2006). With permission from Elsevier)

Zn-affinity metallothionein-like protein is required for appressorium-mediated cuticle penetration of the rice blast fungus Magnaporthe grisea. These examples indicate that there is tough competition among microorganism and between pathogens and host for available iron, copper, or other heavy metals.

12.4 Examples of Cross-Tolerance in Animals Pioneering studies of cross-tolerance were carried out with fruitflies in laboratory experiments (Table  12.1). The following section discusses the anhydrobiosis in invertebrates, particularly in tardigrades, and a few characteristic examples from aquatic habitats.

12.4.1 Anhydrobiosis Desiccation tolerance of dormant stages of various invertebrates enables a very effective passive dispersal, decreasing the probability of extinction, and increasing the genetic diversity (Hengherr and Schill 2011). Furthermore, it belongs to the most obvious manifestations of cross-tolerance. Eukaryotes able to withstand desiccation

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Fig. 12.4  Scanning electron micrographs of the tardigrade Echiniscus granulatus. Dorsal view of (a) active and (b) anhydrobiotic state. Tardigrades anhydrobiotic tun state are able to tolerate exposure to various chemical and physical extremes (From Wełnicz et al. (2011). With permission from Elsevier)

enter a state of suspended animation known as anhydrobiosis which is thought to require accumulation of the non-reducing disaccharides trehalose (animals, fungi) and sucrose (plants). Non-reducing saccharides are major bioprotectants for stabilizing proteins, nucleic acids, and membranes during anhydrobiosis. The water replacement hypothesis states that saccharides form hydrogen bonds with cellular membranes to replace the lost water and thus preserving native structures that would normally denaturate during dehydration. The alternative hypothesis proposes hydrophilic molecules enter a glassy state during desiccation which prevents their denaturation, aggregation, and disintegration due to immobilization (Lapinski and Tunnacliffe 2003; Wełnicz et al. 2011). Water replacement and glass formation are not mutually exclusive, and both are involved in desiccation tolerance (Hengherr et al. 2011b). Intriguing studies were carried in the bdelloid rotifers Philodina roseola and Adineta vaga; and Lapinski and Tunnacliffe (2003) showed that desiccation tolerance does not necessarily depend on the presence of carbohydrates. Furthermore, trehalose synthase genes (TPS) were not found in rotifer genomes.

12.4.1.1 Tardigrades In a series of papers, Schill and co-workers studied the desiccation tolerance of dormant stages particularly of tardigrades (Fig. 12.4). The absolute trehalose levels (max. 2.9% d.w.) detected in tardigrades are much lower than those reported for other anhydrobiotic organisms (10–20% d.w.). Hence, trehalose is not essential for cell stabilization and tardigrades have additional mechanisms. Therefore, the attention has turned to the role of stress proteins, HSPs and LEA proteins. LEA proteins were identified in the active state of Milnesium tardigradum (Schokraie et al. 2010) and the anhydrobiotic state of Macrobiotus hufelandi (McGee et al. 2004). Because there is no

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further experimental evidence on the involvement of LEA proteins in the anhydrobiotic process in tardigrades the precise function of LEA proteins remains obscure. Up to now, several studies on HSP response were published. In M. tardigradum three HSP70 isoforms have been identified. However, two of them do not seem to have a specific function for anhydrobiosis and only one isoform was up-regulated during transition from hydrated to anhydrobiotic state (Schill et al. 2004). Reuner et al. (2010) reported that in the same species the transcript of one Mt-HSP70 isoform during the dehydration and Mt-HSP90 in the dehydrated state were significantly up-regulated. Overall, it is suggested that the HSPs might be involved in the biochemical system connected to a repair process after desiccation rather than to a system connected to molecular stabilization in the anhydrobiotic state itself and that the HSP expression is species-specific (Wełnicz et al. 2011). In comparison to several studies on HSP70, the small, a-crystalline (sHSP) proteins have received attention in the study by Reuner et  al. (2010) showing that Mt-sHSP17.2 is strongly expressed after a heat shock but is not regulated during anhydrobiosis, while Mt-sHSP19.5 is not inducible by heat but is down-regulated during transition from the anhydrobiotic to the active state. The observed low expression changes suggest a minor role of these proteins during desiccation (Wełnicz et al. 2011). As another protecting mechanism, Rizzo et al. (2010) assume the possession of an effective antioxidant metabolism. This assumption is based on the observation that desiccated specimens of Paramacrobiotus richtersi possess higher contents of antioxidant enzymes, particularly SOD and POD. The fact that desiccated specimens showed a reduced CAT activity indicates that the higher content of antioxidant enzyme is not a pure concentration effect, but most likely a strategy of tardigrades to avoid damages caused by desiccation. Wełnicz et al. (2011) conclude there review that transcriptomics (see Chap. 7) and metabolomics (Schokraie et al. 2010) significantly contributed to the understanding but did not solve the secret of the tardigrade anhydrobiosis.

12.4.1.2 Bryozoans and Crustaceans Dormant stages (statoblasts) of the freshwater bryozoan Cristatella mucedo are very well adapted to cope with various hostile conditions like desiccation or low temperatures. Hengherr and Schill (2011) studied the desiccation mechanism and showed that the statoblasts contain low levels of trehalose without any alterations during desiccation stress. Hence, it is unlikely that trehalose plays a major role in desiccation tolerance of bryozoan statoblasts. Instead, biological glasses are present during the desiccation state. Intracellular glasses consist of complex mixtures of proteins and saccharides that potentially interact with other cytoplasmatic components like salts and amino acids. A similar mechanism is thought to apply to encysted embryos of the brine shrimp Artemia franciscana (Hengherr et al. 2011b) and for the water

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60

Control

Mass development of the exposed groups (g)

5mg/L-group 45

30mg/L-group 180mg/L-group

30

15 Two weeks handling stress 0

1

2

3

4

5

6

7

8

9

10 11 12 13 14 15 16 17 18 19 20 21 Week

Fig. 12.5  Mean individual mass of 50 juvenile individuals of Xiphophorus helleri exposed to increasing concentrations of a synthetic humic substance (From Meinelt et al. (2004). With permission from Springer). Note that the fish in the control group did not recover from the handling stress, yet the individuals exposed to humic substances did

fleas Daphnia magna, D. pulex, and the tadpole shrimps Triops longicaudatus, T. cancriformis, and T. australiensis (Hengherr et al. 2011a).

12.4.2 Swordtails, Xiphophorus Helleri In several aquaristic and aquacultural reports, the ability of humic substances (HSs) to improve the physiological conditions of fishes was proposed but not documented in scientific papers. To check this HS-property, Meinelt et al. (2004) exposed newborn swordtails, Xiphophorus helleri, to increasing concentrations of an synthetic humic substance. The mean body mass of X. helleri in the different groups is shown in Fig. 12.5. Within the three exposed groups, no dose-dependent effect of humic substances on growth was detectable. In all groups, the initially continuous increase in body mass stagnated between week 9 and 11 when fish were severely stressed by daily netting. Following this stressful period, fish in all exposed groups continued their steady growth, even demonstrating an increased growth rate during the first 2 weeks after the netting stress. In contrast, the growth of control fish did not recover well from the netting stress and the body mass of control fish remained at the prestress levels until the end of the experiment. It can be assumed that even the lowest exposure concentration of humic substances induced a cross-tolerance in the fish, most likely via heat-shock proteins. Although these proteins were not analyzed in X. helleri, their involvement can be concluded by analogy because small HSPs, HSP60, and HSP70 have consistently been found to be up-regulated in the nematode

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C. elegans, the waterflea D. magna, and several amphipod species exposed to HSs (Timofeyev et al. 2004; Steinberg et al. 2007, 2010a; Bedulina et al. 2010a).

12.4.3 Aquatic Invertebrates Sung et al. (2008) presented an intriguing example of cross-tolerance against biological challenges in invertebrates. This laboratory studied larvae of the brine shrimp Artemia franciscana which serve as an economically important food for fish and shellfish larviculture. Artemia are predominantly found in extreme habitats where few animals exist, and the ability to tolerate environmental perturbations makes this aquatic crustacean an interesting model organism for stress response studies. For example, numerous studies address the effects of temperature and salinity, important physical factors in the life of this organism, on the survival of Artemia cysts, larvae, and adults. Several Artemia HSPs were identified, for instance HSP70 and HSP90. In larviculture, Artemia are also subject to bacterial diseases that devastate entire populations and consequently hinder their use as food. Exposure to abiotic stress (e.g., non-lethal heat shock) was shown to shield Artemia larvae against infection by pathogenic Vibrio. This cross-protection was mediated by increases in HSP70. With larvae of the Antarctic midge, Belgica antarctica (Diptera, Chironomidae), Benoit et  al. (2009) presented evidence for a trehalose-mediated cross-tolerance mechanism. Larvae of B. antarctica are frequently exposed to dehydrating conditions on the Antarctic peninsula. In their study, the researchers examined how rates and levels of dehydration alter heat and cold tolerance and how these relate to levels of trehalose within the insect. When dehydrated, larvae tolerated cold and heat stress more effectively. Levels of trehalose increased during dehydration and are likely a major factor increasing subsequent cold and heat resistance. This hypothesis was also supported by experimental results showing that injection of trehalose enhanced resistance to temperature stress and dehydration. The researchers concluded that changes in temperature tolerance in B. antarctica are linked to the rate and severity of dehydration and that trehalose elevation is a probable mechanism enhancing this form of cross-tolerance. In Chap. 8, we learned that the rotifer Brachionus plicatilis responded to calorie restriction (CR) stress by extending its lifespan. As longevity is often associated with the enhancement of oxidative stress resistance, the survival rate under oxidative stress with the model chemical paraquat was compared between ad libitum fed (AL) and CR (fed every other day) rotifers (Fig. 12.6c). Survival time after exposure to 10 mM paraquat of AL and CR rotifers was significantly extended after 4 days (Fig. 12.6d). The acquisition of cross-tolerances is particularly crucial in strongly fluctuating environments such as coastal freshwater lagoons with occasional intrusion of salt water (Fig. 12.7, left). Suhett et al. (2011) studied the stress resistance of the smallbodied cladoceran, Moina macrocopa, which was recently identified from ephemeral water bodies in Rio de Janeiro (Elmoor-Loureiro et al. 2010). Closely related

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Fig. 12.6  Oxidative-stress resistance of rotifers cultured under different feeding regimes: ad libitum (AL) or calorie restriction (CR). (c) AL and CR rotifers at the age of 4 days were subjected to 10 mM paraquat under AL feeding, boxes indicate 24 h. Boxes indicate 24 h. (d) Survival time after the exposure to 10 mM paraquat. Each group contained 24 individuals (From Kaneko et al. (2011). With permission from Wiley)

Fig. 12.7  Left: Aerial image of one polyhumic coastal lagoon (Lagoa Comprida) in the Restinga de Jurubatiba National Park (Rio de Janeiro State, Brazil). The lagoon is separated from the Atlantic Ocean (foreground) only by a small sandbar (=Restinga) (Photograph credit: Romulo Campos, Rio de Janeiro). Right: Lifespan modulation in Moina macrocopa by intermittent exposure to salt (5.5 g l−1) alone and salt + humic substances (HSs, 10 mg l−1 DOC) from a coastal lagoon in the Restinga de Jurubatiba National Park (Suhett pers. comm.)

species inhabit coastal lagoons of the Restinga de Jurubatiba National Park, Rio de Janeiro State, and suffer from salt water intrusion from the Atlantic Ocean during storm events (Santangelo et al. 2008). A relatively mild, pulsed osmotic challenge (5.5 mg l−1 salt) reduced the mean lifespan of M. macrocopa (fed Pseudokirchneriella subcapitata) by approximately 3  days (Fig.  12.7 right). Since these lagoons are polyhumic containing up to 200 mg l−1 DOC (Suhett et al. 2011), co-exposure to

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humic substances and salt obviously induces a cross-tolerance, because the mean lifespan of this challenge is only slightly reduced as compared to the blank control (Fig. 12.7 right). These findings propose a novel ecological aspect of life-history alteration. Organisms have been evolutionarily shaped to adjust their energy allocation between somatic cells for self-maintenance and the germline for reproduction (Stearns 1992). Longevity and reproductive suppression induced by CR and chemical stresses are considered to be an increased investment for self-maintenance to allow survival in fluctuating environments. For organisms with relatively short generation times and low locomotive ability like rotifers, an immediate investment in self-maintenance in a starved condition is critical to their survival. Furthermore, if mothers have the ability to reproduce offspring adapted to their environmental conditions, the survival of the offspring (an important component of fitness) is increased (Kaneko et al. 2011). Such cross-tolerances and transgenerational plasticity is crucial for the maintenance of a population, yet it also may modulate population structures. This idea will be discussed in detail in the next chapter.

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Chapter 13

Longevity: Risky Shift in Population Structure?

The idea that multiple-stress resistance may serve as a means to expand the individual lifespan has been coined by Parsons (1995) and since then often has been put forward and supported by experimental data (i.e., Cypser and Johnson 2002; SharabiSchwager et al. 2009), which led to the development of the “stress resistance” theory of aging. Indeed, long-lived individuals often have increased resistance against a variety of stresses throughout life (Kirkwood et  al. 2000; Kirkwood and Austad 2000). Genes underlying the stress response may therefore have the ability to affect lifespan. The progress in modern genetic techniques has allowed researchers to test this idea. The general stress response involves the expression of stress proteins such as chaperones and antioxidative proteins, downregulation of genes involved in energy metabolism, and the release of protective substances (Murphy et al. 2003). Do these same changes in expression patterns have the ability to mitigate aging and prolong lifespan? It appears that parts of this response indeed are also associated with extended longevity, whereas some elements are not due to their high cost or long-term deleterious consequences.

13.1 Plants Little is known of the stress resistance theory of aging in plants. As Sharabi-Schwager et al. (2009) summarized, aging in higher plants is most obviously manifested in the senescence of leaves – an indispensable process developed to maximize the reutilization of nutrients that have been accumulated in senescing leaves that can no longer contribute to the plant. Furthermore, it has been suggested that leaf senescence can be reconciled with other evolutionary theories of the origin of aging in animals. Senescence in plants is an age-dependent deterioration process that occurs at the cell, tissue, organ, or organism level and leads to death or the end of the lifespan. Leaf senescence is particularly associated with efficient recycling of nutrients that are translocated from senescencing cells to developing parts of the plant; it is a C.E.W. Steinberg, Stress Ecology: Environmental Stress as Ecological Driving Force and Key Player in Evolution, DOI 10.1007/978-94-007-2072-5_13, © Springer Science+Business Media B.V. 2012

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highly regulated and ordered process that involves cessation of photosynthesis, disintegration of chloroplasts, breakdown of leaf proteins, loss of chlorophyll, and removal of amino acids and thereby enables the rest of the plant (i.e., the younger leaves, fruits or flowers) to benefit from the nutrients accumulated during the lifespan of the leaf (Sharabi-Schwager et al. 2009). While leaf senescence relates to a particular organ, whole plant longevity is determined by the complete loss of function and viability of all tissues and organs within the entire plant. Leaf and whole plant senescence occur in an age-dependent manner but are also governed by complex interactions between various internal and external signals. The internal factors that induce senescence are the age of the leaves and the developmental stage of the plant, including changes in endogenous levels of the phytohormones that affect senescence such as ethylene and cytokinin. The external factors that affect leaf and plant senescence include exposure to environmental stresses, pathogen infection, and shading. In addition, various studies have indicated that oxidative stress and generation of ROS play a major role in triggering the senescence syndrome. Certain lines of evidence reveal the correlation between plant stress tolerance and regulation of senescence and lifespan. Arabidopsis plants over-expressing the CBF2 transcriptional activator gene are more tolerant to drought and freeze stresses and also show delayed leaf senescence phenotypes and enhanced lifespans (SharabiSchwager et  al. 2010) (Fig. 13.1). Furthermore, Arabidopsis mutants deficient in ascorbic acid or tocopherols are sensitive to oxidative stress and exhibit premature senescence and reduced seed longevity, respectively. Together, these findings suggest a tight link between stress resistance and longevity in plants, similar to what has been hypothesized in animals. Humic substances have been shown to retard aging in some animals, either in the post-reproductive or in the reproductive phase (Steinberg et al. 2007, 2010a; Euent et al. 2008). Plants, however, have not been studied in this respect, because they were thought not to age as an entire organism but as individual organs. Nevertheless, there are means to assess anti-aging properties of humic substances in plants. In a recent contribution, Pörs and Steinberg (unpublished) presented evidence that HS-exposed freshwater macroalgae, Chara hispida, benefited from HSs by delayed aging of the photosynthetic apparatus, indicated by its fluorescence properties (Fig.  13.2). The variable fluorescence/maximal fluorescence (Fv/Fm) ratio indicates the photosynthetic yield. Values of approximately 0.7 are representative of healthy photosynthetic apparatuses, whereas decreasing values show increasing aging of this apparatus. The aging process can easily be seen in the old whirl of the control plant. Shading with foil or euqally strong light filtering through a HS-containing cuvette reduced this aging. However, the strongest age-retarding effect was achieved by HS exposure. The effect of delayed aging was not due to light quenching alone, since an aliquot reduction of the underwater light quantity led to medium aging of the photosynthetic apparatus. Recently, Urbaniak et al. (2011) showed that C. hispida is HS-tolerant - and, we may add, benefits from HS-exposure. Similar anti-aging effects apply to several microalgae but not to the cyanobacterium Microcystis aeruginosa, dominant in eutrophicated freshwater bodies (Bährs and Steinberg 2011). Overall, this indicates that the different resistance of phototrophs to environmental stressors clearly shapes the primary producer guilds, yet we are at the very beginning of understanding this issue.

13.2  Animals

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Fig. 13.1  Biochemical and physiological changes occurring during developmental senescence of wild-type (WS-2 ecotype) and CBF2-overexpressing Arabidopsis plants. (a) Chlorophyll content. (b) Protein content. (c) Ion leakage. (d) Survival curve: the percentage of plants in which the lower leaf was still green (From SharabiSchwager et al. (2010). With permission from Oxford University Press)

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13.2 Animals One key regulatory mechanism of cross-tolerance is the action of various stress proteins in their function as chaperones. An involvement of the molecular chaperones in the determination of cellular longevity can be assumed from the relatively high constitutive level of chaperones in the long-lived cells of an organism (Krøll 2005). One strong indication of the importance of molecular chaperones for cellular longevity can be taken from the observation that the level of expression of HSP70 and a HSP90 form is relatively high in inherently immortal embryonic stem cells.

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Fig. 13.2  Delayed aging of the photosynthetic apparatus in the freshwater macroalgae Chara hispida due to exposure to humic substances. Upper panel: experimental set-up. To exclude light quenching effects by humic substance, this exposure was compared to the performance of foilshaded whirls. Lower panel: Photosynthetic yield (variable over maximal chlorophyll fluorescence, Fv/Fm) in the three treatments (Pörs and Steinberg unpublished)

The likely importance of molecular chaperones for cellular immortalization appears also from the frequent hyper-expression of various chaperones in immortal cancer cell lines from catfish (Krøll 2002, 2004). Conversely, low levels of chaperone expression contribute to the phenotype of aging and can be assumed from the observed low levels of HSP90 in senescent cells.

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Several authors attribute HSPs and particularly small mitochondrial HSPs to cross-tolerance and lifespan extension (Morrow et  al. 2004a; Vermeulen and Loeschcke 2007). HSP22 is a key player in cell-protection mechanisms against oxidative injuries and aging. The respiratory chain localized across the mitochondrial membrane is responsible for the transformation of NADH and FADH2 in ATP. This reaction also produces oxygen radicals that are detoxified by scavenging enzymes, except for a small concentration of • OH - which is also produced by the Fenton reaction and leads to increasing ROS in the mitochondrial matrix. Mitochondrial DNA is particularly sensitive to ROS, and damages result in production of mutated proteins that are less active and prone to form aggregates. Post-transcriptional modifications of proteins by ROS also increase the pool of aggregated and/or inactive proteins. All these modified proteins can inhibit the protein degradation system and contribute to increased ROS concentration in mitochondria. This results in a feedback loop in which increasing amounts of ROS are produced without means to degrade them, leading to mitochondrial function impairment which may be responsible for aging. HSP22 could act by preventing aggregation of non-native proteins through its chaperone properties. To assess the key role of HSP22 in the aging process, Morrow et  al. (2004b) conducted longevity experiments on homozygous EP(3)3583-18 (no HSP22 expression) and EP(3)3583-11 (HSP22 expression) flies; the lifespan extending impact of HSP22 is clearly seen: overexpressing the mitochondrial HSP22 increases D. melanogaster lifespan by 32% and resistance to oxidative stress, whereas flies that are not expressing this small HSP have a 40% decrease in lifespan. Observations in C. elegans also suggest that the level of expression of the small heat-shock proteins (a-crystallines) as well as the heat-shock factor HSF-1 participate in lifespan regulation (McElwee et al. 2004). A beneficial effect of HSP16 on longevity has also been suggested from studies in C. elegans (e.g., Steinberg et al. 2007). Thus, disruption of the heat-shock factor (HSF) by RNAi shortens lifespan and results in the accelerated appearance of aging markers. Moreover, extra copies of HSP16 have been shown to confer thermotolerance and extend longevity. Overall, there is a link between longevity and (i) expression of a mitochondrial chaperone and (ii) resistance to oxidative stress.

13.2.1 Regulation of Lifespan Extension in Animals Many plant secondary metabolites (PSM), particularly polyphenols, have been shown to prolong the lifespan of animals. For animals, PSM are natural xenobiotics, and one main task of the biotransformation system is the metabolism of xenobiotics. Due to the long-term co-evolution of plants and herbivores, herbivores have not merely adapted to the natural xenobiotics but have developed biochemical and molecular strategies to convert an adverse stress into a benefit for their individual integrity, for individual health and longevity, and for biodiversity and evolution. Some regulatory pathways are currently known.

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13.2.1.1 Genetic Control: DAF-16/FoxO Pathway Without doubt, HSPs play a central role in lifespan extension yet are not the only molecules involved in this process. Using DNA microarray technique, Murphy et al. (2003) identified a large set of genes whose activity is linked to lifespan, and they provide evidence that many of these genes act in concert to control longevity and aging. A prime example of an interesting gerontogene is DAF-16. This gene encodes a transcription factor (a protein that modifies the activity of other genes), DAF-16,1 which is a powerful regulator of C. elegans lifespan. DAF-16 is switched off by a hormonal signaling pathway akin to that activated by the mammalian insulin and insulin-like growth factor 1 (IGF-1) proteins. Reduced activity of this pathway can greatly increase adult lifespan not only in C. elegans but also in fruitflies and mice (Gems and McElwee 2003; Kenyon 2010). Murphy et al. (2003) identified two classes of genes that are influenced by DAF-16. Class 1 genes are switched on by DAF-16 and are associated with increased lifespan, whereas class 2 genes are repressed by DAF-16 and are associated with reduced lifespan. Do any of these genes actually have a role in determining lifespan? To test this, Murphy et al. (2003) analyzed the genes’ functions using an elegant methodology called RNA interference. If C. elegans are fed bacteria that produce pieces of dsRNA matching a given worm gene, the activity of that gene is reduced or silenced. The expectation was that in some cases, silencing the genes in class 1 would reduce lifespan, whereas silencing class 2 genes would increase lifespan. As it turned out, a surprisingly high proportion of genes behaved as predicted. So, does the identity of DAF-16-regulated genes explain the biochemistry of aging or is it just another big list of gerontogenes? The list certainly gives a few inklings. One influential theory of the biochemistry of aging is the oxidativedamage theory: over time, oxidative by-products of metabolism cause molecular damage which accumulates and eventually causes aging and death. Murphy et al. (2003) found that some of the genes that are up-regulated by DAF-16 do encode enzymes that protect against or repair oxidative damage (Fig.  13.3). Consistent with earlier studies, the pro-longevity genes include some that encode antioxidant enzymes and others encoding heat-shock proteins, which can restore misfolded proteins to their active conformations. Genes that promote aging include some that encode yolk proteins, consistent with a link between aging and reproduction. Another pro-aging protein is the insulin-like INS-7, which, by binding to the insulin/IGF-1 receptor (DAF-2), may repress DAF-16 on the same and other cells. This suggests the presence of a positive feedback loop that regulates DAF-2 activity. There are also many other proteins whose mechanistic links to aging are as unclear as they are intriguing.

1

In vertebrates, the DAF-16 equivalents are FoxO (Forkhead box) transcription factors.

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Fig. 13.3  Aging versus long life: the molecules involved. Murphy et al. (2003) have found that the transcription factor DAF-16 controls the expression of a battery of genes, many of which have small effects on lifespan – promoting either aging or longevity – in Caenorhabditis elegans. Arrows indicate activation; T-bars indicate inhibition (From Gems and McElwee (2003). With permission from Nature)

13.2.1.2 Genetic Control: DAF-16/FoxO-Independent Pathway Almost simultaneously to the emerging hypothesis of DAF-16/FoxO being central in lifespan extension, reports showed that this is only one of several regulatory pathways and seems to depend on the secondary plant compounds involved. For instance, by using a daf-16(mgDf50) mutant strain, Saul et al. (2008) showed that exposure to the polyphenol quercetin led to significantly increased mean lifespan. Furthermore, quercetin-treated daf-16(mgDf50) worms also acquired an enhanced resistance to thermal and oxidative stress; the latter finding supports the correlation of multiplestress resistance and lifespan extension. Dietary restriction, which has the remarkable ability to extend lifespan, is both DAF-16/FoxO-dependent and DAF-16/FoxO-independent. In a comprehensive study, Greer and Brunet (2009) showed that the involvement of the DAF-16/FoxO pathway depends on the specific dietary restriction regime. Particularly, the trial where bacteria are serially diluted on agarose plates extended the lifespan of C. elegans without major genes of the DAF-16 pathway involved. The authors show that the low-energy sensing AMP-activated protein kinase AMPK/aak-2 and the Forkhead transcription factor DAF-16/FoxO were necessary for longevity induced by a dietary restriction regimen where bacteria were serially diluted on plates. They also demonstrate that AMPK and DAF-16 were dispensable for the

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lifespan extension induced by dietary restriction via dilution of bacteria in liquid cultures. Overall, different dietary restriction methods extend lifespan by mostly independent genetic mechanisms. Very recently, Kenyon (2010) reported that the eat-2 mutation which inhibit feeding throughout life, are likely to increase lifespan by means of TOR (target of rapamycin) inhibition, as TOR inhibition does not further increase the eat-2 mutant lifespan. TOR is a specific protein kinase that regulates cell growth, cell development, and transcription. 13.2.1.3 Action of miRNAs As shown, aging is under genetic control in C. elegans, but the regulatory pathways of lifespan regulation are not yet completely understood. Particularly, miRNAs regulate gene expression at the post-transcriptional level by targeting mRNAs for either direct cleavage or repression of translation. Evidence shows that one miRNA, lin-4, is implicated in lifespan (Boehm and Slack 2005). The authors show that lin-4 and its target, the putative transcription factor LIN-14 regulate lifespan in an antagonistic manner. Reducing the activity of lin-4 shortened lifespan and accelerated tissue aging, whereas over-expressing lin-4 or reducing the activity of LIN-14 extended lifespan. Lifespan extension conferred by a reduction in LIN-14 was dependent on the DAF-16 and HSF-1 transcription factors, suggesting that the lin-4–LIN-14 pair affects lifespan through the insulin/insulin-like growth factor–1 pathway. de Lencastre et al. (2010) identified several novel miRNAs by deep sequencing of aged C. elegans and showed that four of the most highly up-regulated miRNAs exhibit aberrant lifespan phenotypes as well as abnormal stress responses. Some miRNAs act to promote normal lifespan and stress resistance, whereas others inhibit theses phenomena. These miRNAs genetically interact with genes in the DNA damage checkpoint response pathway and in the insulin signaling pathway. These recent findings reveal that miRNAs both positively and negatively influence lifespan (Fig. 13.4). In detail, de Lencastre et al. (2010) found that miR-239 function depends on DAF-16; hence, the authors searched for potential targets of miR-239 in the insulin/IGF signaling pathway. Interestingly, however, none of the core genes in this pathway are targeted by miR-239. When they examined the expression of genes in the insulin/IGF signaling pathway by qRT-PCR, they found a decrease in the mRNA levels of AGE-1 and PDK-1 in day 10 animals of a long-lived mutant, suggesting that miR-239 may act upstream of AGE-1/PDK-1 (Fig. 13.4) and induce longevity. In contrast to miR-239, miR-71 not only interacts with the insulin/IGF signaling pathway but also with the DNA damage response pathway. Specifically, it blocks two checkpoint proteins, CDC-25.1 and CHK-1, which in turn block longevity. Consequently, miR-71 indirectly extends lifespan. It is noteworthy that the long-lived mutant mir-239(nDf62) also possessed multiple-stress resistance as tested by heat and oxidative stresses. In this case, longevity correlates well with multiple-stress resistance. Because several miRNAs up-regulated during aging regulate genes in conserved pathways of aging and thereby influence

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Fig. 13.4  Model for molecular and genetic interactions of age-related miRNAs with known aging pathways. Pointed arrows denote positive interaction; blunt arrows denote negative interactions (From de Lencastre et al. (2010). With permission from Elsevier)

lifespan in C. elegans, de Lencastre et al. (2010) proposed that miRNAs may play important roles in stress response and aging of more complex organisms. Knowledge of miRNAs is growing exponentially, as Grillari and Grillari-Voglauer (2010) showed in their recent review of miRNAs and the role in aging and age-related diseases.

13.2.2 Which Genders and Life Traits Are Affected? The evolutionary life history principle considers aging to manifest mainly during the period of extended survival beyond essential lifespan, the time required to fulfill the Darwinian purpose of life in terms of successful reproduction for the continuation of generations (Rattan 2006). This applies to many, but not all, short-lived animals studied so far. In protected environments, mild stress may extend individual lifespans or increase lifetime reproductive output. In a few cases, both life traits simultaneously increase. Furthermore, genders may be differently affected. There exist only a few studies which show that lifespan extension in ecological species can be gender-specific. One example is Daphnia magna. Usually, D. magna is a cyclically parthenogenetic cladoceran. This means that it can combine sexual and asexual reproduction and hence benefits from the advantages of both systems. Currently, it is well understood that the production of parthenogenetic male offspring occurs through environmental cues such as temperature, photoperiod, and crowding. Applying a relatively high population density, exposure to HSs is such a strong additional stress that a few days after the onset of the experiment the females produced parthenogenetic males. As soon as males could be identified in the Daphnia garden, they were isolated and exposed separately in an identical exposure

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Fig. 13.5  Exposure of high-density Daphnia magna garden to increasing concentrations of HuminFeed® as DOC at 21°C. (a) Females, lifespan reduction at all concentrations. (b) Males: lifespan extension at all concentrations. In both graphs, the differences between control and the exposures were significant at the p < 0.01 level. Note: Time scales (x-axis) in the figures differ (From Euent et al. (2008). Courtesy of Northeastern University, Boston)

pattern as the females. The results are presented in Fig.  13.5. Exposed females respond with reduced lifespan at any concentration (Fig.  13.5a) while males increased lifespan (Fig. 13.5b). Since even aged D. magna females can still reproduce well, this gender-specific modulation of longevity synchronizes the lifespans of both females and males and allows a prolonged period of sexual reproduction.

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Fig. 13.6  Lifespan modulation (a) and cumulative as well as single day reproductive output (b) of Caenorhabditis elegans exposed to caffeic acid; white: control; grey: 300 mM CA, error bars represent standard deviation, * p < 0.05, ** p < 0.01 (From Pietsch et al. (2010a, b) With permission from Parlar Scientific Publications)

13.2.3 Which Life Phase Is Expanded? In a recent contribution, Pietsch et al. (2010a, b) comparatively evaluated life traits of the nematode C. elegans, a dweller of rotten fruit, and the cladoceran Moina macrocopa, a puddle inhabitant. The organisms were exposed to caffeic acid (CA), a constituent of the water-soluble fraction of phenolic substances in soils. The applied life table data is common in aging research. The authors tried to answer the question whether or not CA was toxic to the exposed model organisms and if their strategic respond to CA exposure was similar. In particular, how did CA exposure modulate the lifespans and/or offspring numbers in both model organisms? Both life traits are alternatives in the lifetime resource allocation and may help to optimize the niche exploitation of C. elegans and M. macrocopa. Exposure to CA at all concentrations extended the lifespan of C. elegans significantly (Fig. 13.6a), with the strongest extension at 300 mM. At this concentration, the impact on reproduction was checked: C. elegans only reproduced during 4 days (Fig.  13.6b), and exposure to 300  mM CA led to delayed but not significantly

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Fig. 13.7  Lifespan modulation (a) and lifetime reproductive output (b) of female Moina macrocopa fed Pseudokirchneriella subcapitata and exposed to caffeic acid, CA in mM, *p < 0.05, **p < 0.01 (From Pietsch et al. (2010a, b). With permission from Parlar Scientific Publications)

reduced overall reproduction. However, during the first 2 days, reproduction was significantly reduced. This means that the non-productive phase of the nematode was extended. A delay of the onset of reproduction is not uncommon, since a tendency towards delayed reproduction in C. elegans has also been observed upon exposure to tannic acid, ellagic acid, gallic acid, resveratrol, and vitamin E (Saul et al. 2011, and references therein). The authors excluded antimicrobial effects of CA since lifespan extension were also achieved with heat-killed bacteria mixed with the polyphenols. In contrast to C. elegans, M. macrocopa reproduced during its entire lifetime, and a delayed start of reproduction was not observed with CA treatment (Fig. 13.7b). Exposure concentrations up to 200 mM did not significantly modulate the lifespan, but 300  mM and 500  mM clearly reduced it (Fig.  13.7a); this reduction as such may be taken as an indication of a slight intoxication. Yet in contrast to lifespan, the lifetime reproductive output significantly increased with rising CA concentrations. This means that CA exposure is not toxic but impacts the energy allocation of M. macrocopa. It is interesting to note that both model organisms are short-lived and usually reproduce asexually with high numbers of offspring. Hence, both may be categorized as r-strategists which colonize unstable or unpredictable environments; here, the ability to reproduce quickly is crucial. Furthermore, both model organisms possess the capability of producing diapausing stages to overcome adverse

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Fig. 13.8  Changes in life trait variables in Moina macrocopa exposed to increasing concentrations of a humic substance preparation (HuminFeed®, mM DOC) at 21°C and fed the coccal green alga Pseudokirchneriella subcapitata (From Steinberg et  al. (2010b). With permission from Taylor and Francis)

situations: C. elegans develops dauer stages (resting larvae), and M. macrocopa produces ephippia (fertilized resting eggs). This means that there is no clear difference in their main strategy to exploit their habitats, which could explain the difference in responses to CA exposure. In other words, there is no noticeable extrinsic factor that could best be met with the specific resource allocation demonstrated by these two model organisms under CA exposure. It appears, rather, that C. elegans and M. macrocopa simply mirror the intrinsic variability of allocation of metabolic resources during chemical exposure and aging. Furthermore, the applied CA concentrations are by no means toxic; they only modulate resource allocation in the two model animals. A variable energy allocation in M. macrocopa was observed if the animals were fed the coccal green algae Pseudokirchneriella subcapitata (Fig.  13.8), Monoraphidium minutum (Fig.  13.9), or Desmodesmus armatus (Fig.  13.10). In terms of longevity and reproductive output, P. subcapitata diet achieved best results of all green algae diets. This algal species is rich in polyunsaturated fatty acids and phosphorus and the amino acids histidine, arginine, and taurine (derivative of cysteine) but lacking ornithine (amino acid in the urea cycle). Furthermore, P. subcapitata is the only food alga with phosphoethanolamine but has the lowest protein content per dry weight of the three tested food algae. M. minutum and D. armatus are less rich in polyunsaturated fatty acids and phosphorus than P. subcapitata but

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Survival rate, %

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Fig. 13.9  Changes in life trait variables in Moina macrocopa exposed to increasing concentrations of a humic substance preparation (HuminFeed®, mM DOC) at 21°C and fed the coccal green alga Monoraphidium minutum. ***p < 0.001 (Bouchnak and Steinberg unpublished)

have a higher protein content. Obviously, the amino acid composition rather than the protein content impacts the energy allocation in M. macrocopa. The controling role of the rare amino acids is subject to future studies. The pictures changes completely, if an HS-stress is added: then, M. minutum diet increased M. macrocopa’s lifespan and led to increased offspring numbers with rising HS-concentrations. Both life trait parameters follow a concentration-response relationship (Fig. 13.9); the levels of these life trait variables, however, do not reach those of the P. subcapitata diet (Fig. 13.8). A third version of food quality-controlled energy allocation is induced by D. armatus diet with no lifespan change but increased offspring numbers, yet on a rather low level compared to M. minutum and P. subcapitata fed animals. The latter follows roughly a concentration-response relationship. Mean lifespans of D. armatus fed individuals were longer than in M. minutum fed ones (Fig.  13.10). This means that D. armatus diet supports longevity rather than offspring. A comparable observation was published by Nandini et al. (2004) who fed M. macrocopa coenobium-forming Scenedesmus quadricauda (currently D. armatus or D. communis) or single-celled Chlorella vulgaris and found that the S. quadricauda supported longevity whereas C. vulgaris supported offspring better. These authors attributed the extended life-span in Scenedesmus-fed individuals to the better cell volume to cell

13.2  Animals

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Lifetime reproductive output, N

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Fig. 13.10  Changes in life trait variables in Moina macrocopa exposed to increasing concentrations of a humic substance preparation (HuminFeed®, mM DOC) at 21°C and fed the coccal green alga, Desmodesmus armatus. *p < 0.05, ***p < 0.001 (Bouchnak and Steinberg unpublished)

wall ratio in the coenobia of S. quadricauda, but do not offer an explanation for the increased offspring number in Chlorella-fed individuals. The additional stress by HSs tends to reduce lifespan, at least at the lowest concentration. Overall, food quality is a strong bottom-up control of energy allocation in cladocerans with PUFAs, major nutrients, and amino acid composition as factors. Further studies are needed, especially studies examining the effects of mixed algaebacteria diets. In another Daphnia magna series, Bouchnak and Steinberg (unpublished) studied its reactions to increasing concentrations of a humic substance preparation with a low individual density. Daphnia responded by increasing lifespan but significantly reduced lifetime reproductive output. This reduction was clearly concentrationdependent (Fig. 13.11). One widely accepted theory of aging concerning energy allocation is the socalled “Disposable Soma Theory” (Kirkwood and Austad 2000). The theory implies that the finite amount of energy available to an organism is distributed to three sectors, namely maintenance, growth, and reproduction. The optimal allocation of metabolic resources between somatic maintenance and reproduction in organisms is the core assumption of this aging theory. Additional energy consumption that is necessary to facilitate an increased lifespan or to combat stress should, therefore,

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mean cumulative offspring per female

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Fig. 13.11  Changes in life trait variables in a low-density Daphnia magna garden exposed to increasing concentrations of a humic substance preparation (HuminFeed®, mM DOC) at 21°C and fed the coccal green alga Desmodesmus armatus. ***p < 0.001 (Bouchnak and Steinberg unpublished)

cause an energy imbalance resulting, for example, in negative effects in body size or offspring quantity. With optimal resource allocation, animals optimize the exploitation of their ecological niches and cope with stressors in a fluctuating environment. Daphnia’s response to HS-stress is consistent with this theory. Yet, the other cladoceran model organisms responds differently to the. Whereas in C. elegans and D. magna the energy tends to be redistributed from reproduction to maintenance (longevity), in M. macrocopa energy is redistributed from maintenance to reproduction if fed P. subcapitata. However, if fed M. minutum and stressed by HSs, M. macrocopa seems to totally contradict the Disposable Soma Theory. In obvious disagreement with the Disposable Soma Theory, Moina macrocopa responded several times with increased lifespan, larger body sizes, and significantly elevated lifetime reproductive output (Fig. 13.12) when exposed to HSs at optimal temperatures (25°C). Even at the highest exposure concentration, no adverse effects were observed. At sub- and super-optimal temperatures, growth always increased in a temperature/concentration-dependent fashion and reproduction did not show a clear relationship to temperature or exposure concentrations. Lifespan decreased at sub-optimal temperatures with increasing HS concentrations yet was unchanged at super-optimal temperatures (not shown). This indicates that there is a strong thermal dependence of the energy allocation in Moina, and it can be reversed under both sub- and super-optimal thermal conditions.

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Body length, mm 0.8

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Fig. 13.12  Life trait variables of Moina macrocopa fed the coccal green alga Pseudokirchneriella subcapitata and exposed to increasing concentrations of a humic substance preparation (HuminFeed®, mg l−1) at 25°C (Engert and Steinberg unpublished)

These few examples demonstrate several options for an organism to alter life history traits in response to mild stress. All experiments were conducted in protected environments and with optimal food supply. Even under such optimal conditions, there are risks for populations as modeling with Leslie matrices makes clear. The modeling considered the different larval stages that are pooled and displayed versus adults in the graphs. The model ran for 35 generations and shows a balanced distribution between juveniles and adults in a normal population. The population can be maintained for some time. In three different scenarios, lifespan and offspring were modulated. A slight decrease in lifespan and a moderate increase in fertility results in a moderate increase of individuals in the whole population while appearing only slightly unbalanced. A stronger increase in fertility leads to an explosion of the population that is not counteracted by a modeled 40% lifespan reduction. On the contrary, an increase of adult lifespan by 40%, which is not unusual as experienced with several model animals, combined with a 20% reduction of lifetime offspring numbers ends with the extinction of the population. Remember, in these scenarios, there is no carrying capacity of the system. One can easily see that increases in population density must, in the long-term, lead to extinction if there is any resource limitation, such as available food or space for the individuals. In nature, however, populations are also top-down controlled by predators, parasites, or pathogens. An intrinsic risk of extinction of the population exists in the scenario with reduced offspring and increased adult lifespan. This realistic scenario (see the examples of Brachionus plicatilis in Fig. 8.1 and Daphnia magna in Fig. 13.11) shows that the population can go extinct without any external stressor. In the model, the population goes extinct after 35 generations. The reproductive rate was too low, and the extended lifespan of the adults could not compensate for the reduced birth rate. This realistic example shows that only small shifts in life traits can increase the intrinsic risk for extinction of populations.

sdfsdf

Chapter 14

Footprints of Stress in Communities

Environmental stress and degradation can affect individuals, populations, and communities directly and indirectly in obvious ways such as mass mortality, reduced fecundity, or both, ultimately leading to extinction of populations and even entire species. More subtle effects include reduced growth, increased disease susceptibility, and increased rates of morphological anomalies (Allenbach 2011), as well as changes in food-web structures. Overall, there is great interest in understanding and monitoring sub-lethal biological responses that are faithful indicators of environmental stresses. Consequently, this chapter will introduce several phenotypic approaches (fluctuating asymmetry, quality indices, maturity index, species at risk indices) and one theory-based approach (biomass spectra) to assess the integrity of populations, communities, or even ecosystems. Overall, there is a gap between molecular, biological, and biochemical stress identification on the one hand and stress evaluation on higher aggregated levels on the other hand, and this gap does not seem to be easily bridged. Both parts of stress ecology appear to be different disciplines.

14.1 Fluctuating Asymmetry The ability to maintain a predetermined morphological phenotype under diverse conditions is a fundamental property in organisms. This morphological homeostasis can be disrupted under stress, and deviations from an optimal phenotype result. An optimal morphology is anticipated in certain cases, e.g., as perfect symmetry of bilateral characters. Development of left and right sides in bilaterally symmetrical individuals is presumably under the control of the same genome and influenced by identical environmental conditions. It is axiomatic that the optimum, perfect symmetry, is evidenced by small random individual differences between left and right, normally distributed around zero. The variance of the normal distribution may

C.E.W. Steinberg, Stress Ecology: Environmental Stress as Ecological Driving Force and Key Player in Evolution, DOI 10.1007/978-94-007-2072-5_14, © Springer Science+Business Media B.V. 2012

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therefore express the degree of developmental instability, so-called fluctuating asymmetry (FA). Researchers consider FA an epigenetic measure of stress. FA tends to increase as habitats become ecologically marginal; this includes exposure to environmental toxicants. Furthermore, increased FA is a reflection of poorer developmental homeostasis at the molecular, chromosomal, and epigenetic levels (Parsons 1990). Bilateral asymmetry is estimated simply from length of characters on the left and right side of the body or from the number of a certain repetitive character on each side. This simplicity leads to a general applicability, meaning that easily accessible and abundant species may be chosen for studies. Developmental instability results from disturbance of a fundamental homeostasis and may therefore be speculated to be inversely proportional to fitness or to performance in important life history traits such as reproductive capacity, longevity, etc. A number of recent studies have indicated such relations. Individuals with decreased FA may have increased longevity (e.g., moth Malacosoma disstria, ladybird Harmonia axyridis), mate more frequently (e.g., scorpionfly Panorpa vulgaris, damselfly Coenagrion puella, yellow dungfly Scatophaga stercoraria, earwig Forficula auricularia), or be preferred by mating females (e.g., barn swallow Hirundo rustica, chicken Gallus gallus domesticus). Other studies have shown that differences in FA between populations correlate with fitness components such as size, fecundity, viability, and percentage of viable eggs (Sommer 1996 with references therein; Campo et al. 2009). These studies suggest that fitness components may be assessed by measuring developmental instability. An assumption in the interpretation of FA is that an environmental stressor activates compensatory responses in developing organisms. These responses result in a comparatively greater mean FA in a population relative to populations from non-contaminated sites. Furthermore, they increase variability in FA among individuals from the perturbed population, resulting from individual differences in developmental homeostasis. The survival potential of organisms with greater FA may be reduced because the ability to tolerate new environmental challenges has been compromised (Allenbach et al. 1999). This shall be exemplified with one illustrative study. Allenbach et al. (1999) used two fish species common to the Great Plains of North America (the western mosquitofish, Gambusia affinis, and the sand shiner, Notropis ludibundis) to examine the relationship between individual 96-h time-to-death toxicity tests and average FA. The fishes were exposed to parathion, an organophosphate. Figure  14.1 shows that individuals with high estimates of asymmetry died earlier than those with low estimates, with some individuals living even after 132  h. This means fish with higher FA are more susceptible to future stressors in their environment, in this case pesticide exposure. This notice applies to individuals as well as species, since G. affinis exhibits higher FA and dies earlier than N. ludibundis. Recently, Tucić and Miljković (2010) examined the level of floral FA in six natural populations of dwarf sword lily Iris pumila experiencing sun-exposed (more stressful) and shaded (less stressful) environmental conditions. The authors applied the multi-trait index (FA17) to assess the FA levels in three floral traits: fall width, standard width and style branch width and detected a significant FA–stress association (Fig. 14.2). Light stress in the exposed habitats increased FA significantly.

14.1  Fluctuating Asymmetry

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Average FA

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Hours Fig. 14.1  Observed mean fluctuating asymmetry (FA) of mosquitofish Gambusia affinis (black columns) and sand shiners Notropis ludibundis (white columns) exposed to parathion that died at successive 12-h intervals (From Allenbach et al. (1999). With permission from Wiley) 0.04

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Fig. 14.2  Iris pumila. Left: Image of Iris pumila, courtesy Nova. Right: Mean values (± standard error) of the composite index (FA17) for floral traits in six natural populations from exposed (DuneA, DuneB and DuneC; open bars) and shaded (WoodRP, WoodPS and WoodPN; filled bars) habitats. The differences between exposed and shaded plants are significant (From Tucić and Miljković (2010). With permission from Wiley)

From experimental and theoretical studies, there is, however, evidence that fluctuating asymmetry is not necessarily a consistent index of stress. For instance, Leung et al. (2000) noticed that FA stress relationships are real but are typically weak, difficult to detect, and depend on the index chosen. In addition to their computational simulation, Bjorksten et al. (2000) argued that experimental studies showed that the relationship between FA and stress may be inconsistent, and there is little evidence that sexual traits are especially responsive to stress. They continue that one of the problems with using FA to measure stress or quality is that the developmental and genetic basis of FA was only poorly understood at that

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time. Although FA has been proposed to show relationships with stress, fitness, sexual selection, heterozygosity, and inbreeding, a solid theoretical basis for these predictions is emerging only recently. For instance, Manitašević et al. (2007) convincingly showed that FA in I. pumila correlated well inversely with the HSP90 content. This chaperone functions as capacitor of phenotypic variability and appeared at higher levels in shaded than in exposed plants (see Chap. 8). Bjorksten et al. (2000) also argued that FA is difficult to measure accurately. FA has a large sampling error and provides a rough estimate of underlying developmental stability, because it uses a sample of two data points to estimate the variance in individual development. Large samples are needed to detect stress effects on FA, and measurements need to be made at least twice with appropriate control for session bias. Consequently, studies of FA, far from being easy and cheap, present many difficulties. Furthermore, the results of recent studies continue to be inconsistent, in spite of improvements in techniques and in analysis. This statement provoked several replies. For instance, Van Dongen and Lens (2000) claimed that it was too early to abandon asymmetry as a potentially accurate estimator of stress. First, detailed controlled experiments should focus on factors that might influence the asymmetry– stress association, the genetic architecture of developmental stability, and the ontogeny of asymmetry. Second, meta-analyses can model the observed heterogeneity and attempt to find influential factors. Finally, given the observed heterogeneity in FA–stress associations, Van Dongen and Lens suggested combining both trait asymmetry and size to detect stress, which might increase sensitivity considerably. Since the critique of Bjorksten et al. (2000), the acceptance of FA as an indicator of stress seems to have only gradually increased, mainly because major problems addressed above appear to be unsolved. Still, mostly phenotypic descriptors are applied which often find some stress-FA relationship. In a recent paper, Vangestel and Lens (2011) tested if and to what extent FA increases with nutritional stress, estimated from independent feather growth measurements, in free-ranging house sparrows Passer domesticus. Feather marks showed significant heterogeneity among study plots, indicating that house sparrow populations were exposed to variable levels of nutritional stress during development. However, individuals from more stressed populations did not show increased levels of FA in tarsus or rectrix length, nor was there evidence for significant between-trait concordance in FA at the individual or the population level. Lack of support for FA in tarsus and rectrix length as an estimator of nutritional stress in house sparrows indicated that developmental instability is insensitive to nutritional stress in this species, poorly reflected in patterns of FA due to ecological or statistical reasons, or highly context-specific. Such uncertainty continues to hamper the use of FA as a biomarker tool in environmental monitoring and conservation planning. In the same line, Van Dongen et al. (2009) showed in a study with three-spined sticklebacks Gasterosteus aculeatus that the developmental instability (measured as FA) was more dependent on populationlevel genetic variation than on external stresses. Ottaviano and Scapini (2010) noticed the absence of a significant level of FA in the amphipod Talitrus saltator populations exposed to oil and pesticide pollution of water and sediments and addressed this lack simply the (unlikely) potential of high

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levels of tolerance of this species to pollution. Nevertheless, this implies that FA does not reflect the chemical pollutions. Even more drastically, Hopton et al. (2009) found differences in developmental instability in small rodents after a tornado event; but these differences could not be related to the disastrous event itself. Contrastingly, Uetz et al. (2009) did find that FA in a secondary sexual character (male leg tufts) in a wolf spider, Schizocosa ocreata, was a sensitive indicator of putative environmental stress in form of a tornado; the exact cause of higher levels of developmental instability in spiders from the disturbed area, however, remained unknown. The pros and cons of descriptive FA may be further continued. However, we shall draw our attention to a recent review on FA as indicator of exogenous stress in fishes (Allenbach 2011) and shall find some issues of the aforementioned discussion revisited. Fishes are an excellent group for such a review. They are the most speciose group (25,000–30,000 species) of vertebrates with representatives occurring in virtually every aquatic habitat. A tractable number of studies examine naturally occurring FA and FA induced by exogenous stress in fish which is large enough to elucidate gaps and patterns in the research. If the use of FA as an indicator of environmental stress is to be accepted in mainstream evolutionary and population biology, certain standardizations need to be applied across the entire FA research field: 1. Character choice: Careful consideration must be given to character choice in FA studies. If no data are available for a species’ natural FA variation, then preliminary work must be done in order to choose the most appropriate characters for study. 2. Measurement error: Because FA itself is such a small proportion of withinindividual character variation, great care must be taken to account for measurement error. Even a small amount of measurement error can mask the FA signal. 3. Baseline data: It is important to know what natural level of FA occurs in order to better understand an individual’s or a population’s response to exogenous stress. Without baseline FA data for a given species, it is unclear if the observed levels in the field are merely a reflection of natural variation or response to a stressor. In laboratory studies, control treatments can serve as baseline FA estimates. 4. Laboratory tests: More laboratory experiments are needed not only to corroborate field observations but also to better elucidate exactly which stressor may be causing FA since natural environments often experience a mix of anthropogenic influences. 5. Replication of studies: If a particular study is only conducted once, its result could have been obtained purely by chance. More studies that are true replications should be conducted in order to get at an average result that can be presented to other researchers within and outside the FA field of interest. If a consensus of its usefulness as an indicator of developmental stress can be reached, FA truly can become a powerful tool for helping biologists assess environmental degradation (Allenbach 2011). Future studies should therefore aim to combine phenotypic and molecularbiological approaches as Manitašević et al. (2007) successfully did. Their study can serve as template, particularly because the chosen molecularbiological variables are relatively easy to evaluate.

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14.2 Quality Indices with Emphasis on Freshwaters Even undergraduate textbooks on freshwater ecology truthfully state: Freshwater bodies are mirrors of their surrounding landscape (Likens 1985). They are the result of chemical loading from atmospheric deposition, surface runoff, seepage water, and landscape management. Various water bodies house characteristic food webs which, in turn, are indicative of the specific features of their habitat, be they natural or artificial. Several anthropogenic impacts are well understood and documented for eutrophication of lakes (Ohle 1953; Schindler 1974); acidification of lakes and rivers and their recovery (Monteith et al. 2007); and saprobization, eutrophication, and other impacts of rivers and streams (Hering et al. 2006). Many attempts have been undertaken to develop indices of such stress-related footprints. Although these indices vary in complexity and level of aggregation, all have in common that they persist on the phenotypic level. Yet, this does not belittle the merits of indices for the solution of practical management problems. We shall learn three well established or recently developed representative indices. Streams and rivers are among the most threatened habitat types, and quality measures were developed rather early. Therefore, we will focus on indices developed for and applied to river systems, specifically the index to identify saproby and eutrophication, the maturity index based on free-living nematodes, and the Species at Risk indices.

14.2.1 Indices for Saproby, Eutrophication, and Further Impacts Although the type and severity of human-generated pressures affecting the integrity of streams varies strongly, the major drivers can be summarized as (Hering et al. 2006): • • • • •

multiple use: fisheries, navigation, and drinking water extraction nutrient enrichment (eutrophication) organic pollution acidification alterations of hydrology and morphology

Awareness of the deleterious effects of human impacts on streams has resulted in a long history of monitoring using biological indicators. For example, the use of invertebrates in bioassessment began as early as the first decade of the twentieth century in order to examine the pollution of Berlin, Germany, waterways (Kolkwitz and Marsson 1902). These authors grouped macroinvertebrates of the River Spree, its tributaries, and connecting channels according to their tolerance to decreasing oxygen contents of the water bodies and coined this system term “saproby”. The dissolved oxygen content in the water decreased in this river system due to mineralization of putrescible organic matter from discharged waste and wastewater.

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In a comprehensive study of Central and Northern European rivers, Hering et al. (2006) compared and contrasted the response of diatoms, macrophytes, macroinvertebrates, and fishes to different stressors, such as eutrophication/organic pollution, catchment land use, and hydromorphological degradation: 1. Periphytic diatoms, macrophytes, benthic macroinvertebrates and fish showed significant response to eutrophication/organic pollution gradients. Generally, diatom metrics most strongly correlated to eutrophication gradients in mountain and lowland streams, followed by invertebrate metrics, which correlated well to organic pollution in mountain streams and less well in lowland streams. 2. Responses of the four organism groups to other gradients were less strong; all organism groups responded in varying degrees to land use changes, hydromorphological degradation on the microhabitat scale, and general degradation gradients, while the response to hydromorphological gradients on the reach scale was mainly limited to benthic macroinvertebrates and fish. 3. Fish and macrophyte metrics generally showed a poor response to degradation gradients in mountain streams and a strong response in lowland streams. In designing biomonitoring programs, the authors recommend that consideration should be given to the stream type being addressed, the types of stressors potentially affecting the integrity of the stream ecosystem, and the period of the study. In small Central European mountain streams, benthic diatoms and macroinvertebrates are the most diverse organism groups and best reflect the main stress gradients. Fish assemblages are usually species-poor, so assemblage-based metrics may have a limited capacity to detect stress. Further, macrophytes are often patchily distributed and thus less suitable for monitoring purposes. In medium-sized lowland streams in Central and Northern Europe, all four of the organism groups are suitable for monitoring. For the effects of land use and eutrophication, all organism groups are also well suited. In particular, for nutrient impact, benthic diatoms often show the highest sensitivity and are best suited to indicate eutrophication. If the focus of the study is on organic pollution, benthic macroinvertebrates and/or fish should be considered as these groups are more directly affected by oxygen condition which inversely reflect the load with putrescible organic substances. Land-use affects stream communities by altering nutrients (eutrophication), habitat quality (sedimentation), and toxicity (e.g., pesticides), and these effects are most strongly reflected by fish, benthic invertebrates, and benthic diatoms.

14.2.2 Feeding Types The analyses of functional feeding types are the most frequently investigated ecological measures, since they do not aggregate the diverse information of field surveys into numerical indices and are therefore easy to understand. Practical knowledge concerning trophic-relationships, food web structures, food quotient, and essential nutrients is widely available. The distribution of functional feeding guilds within an

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Fig. 14.3  Different feeding types (% individuals) of aquatic invertebrates and their responses to environmental stress expressed in ecological quality classes; (a) feeding type gatherer/collector, (b) feeding type grazer/scraper (From Schmidt-Kloiber et  al. (2006). With permission from Springer)

assemblage permits a relatively dynamic view of the nutrient status of a particular river site and is based on the ideas of the River Continuum Concept (RCC) (Vannote et al. 1980). The RCC is an attempt to generalize and explain longitudinal changes in stream ecosystems and explains how biological communities develop and change from the headwaters to the mouth. The RCC hypothesizes that riparian forest canopy shades many headwater streams. This shading, in turn, limits the growth of algae, periphyton, and other aquatic plants. The heterotrophic communities in these regions depend on the import of biochemical energy in the form of coarse particulate matter (detritus from leaves and litter on the forest floors). Predictable changes occur as one

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proceeds downstream to streams with wider channels. When the channel widens, the amount of incident sunlight and average temperatures increases. Levels of primary production increase in response to increases in light, which shifts the dominant production pathways in many streams from allochthonous (from outside the aquatic system) to autochthonous (indigenous) ones. Consequently, among the feeding types, the share of grazers and collectors increases. How the feeding types can be utilized to assess the integrity of rivers was presented by Schmidt-Kloiber et  al. (2006). Changes in the structure of the feeding guild indicated a disturbance. Clear trends between the composition of feeding types in the community and an investigated stressor are graphed in Fig. 14.3a; the left corner of the figure indicates the reference site (“best ecological”1 conditions); the ecological quality of the river sites under investigation decreased to the right ending with the most compromised sites. The increase of the gatherer/collector feeding type was proportional to the decrease in river quality. Conversely, the grazer/ scraper feeding type increased with the stressor decrease (Fig. 14.3b). The impoundment of rivers reduces flow velocity, supports phytoplankton growth, and consequently impoverishes the underwater light climate; phytoplankton nourish gatherers and collectors, whereas grazers and scrapers find less food in the water-sediment interface under impounded conditions.

14.3 Maintenance Strategies with Emphasis on Free-Living Nematodes Presence as well as absence of stressors causes specific shifts in biocenoses; if the action of a stressor stopped, the system tends to return to the former state. The different states of succession are clearly noticeable, for instance, in the ratio of colonizers to persisters as maintenance strategists. After an impact, that reduces the given biocenoses to a few individuals and/or taxa, the colonizers will re-appear first with remediation. Later, they will be replaced by persisters until a characteristic equilibrium is reached. Shifts in maintenance strategists can be found in any group of organisms. In many cases, the strategists can be recognized by their morphometric properties (e.g., the number of eggs per female, size of females) which also allows for the use of groups of organisms which may be difficult to define taxonomically. Successful approaches can be found with nematodes (Bongers 1990). Nematode assemblages offer several advantages for assessing the quality of freshwater, marine, and terrestrial ecosystems: their diversity is high; they occur in high numbers, they are easily sampled, and they represent a trophically heterogeneous group. Nematodes that rapidly increase in number under favorable conditions can be considered to be “colonizers”, comparable to r-strategists sensu lato. Other characteristics 1

Ecology is an analzing, rather than a moralizing science.

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3

1

, es iat ed

niz ers ,%

erm Int 4

0 100

2 Persisters, %

%

Co lo

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Fig. 14.4  Schematic presentation of the nematode maturity index according to Bongers (1990). Disturbances (1, 2) and recoveries (3, 4) in nematode faunas after different loads. 1 = impact of easily degradable organic material, which first supports bacterial growth and subsequently the bacteria feeders among the nematodes (the colonizers); 2 = toxic impact which reduces persisters much more strongly than the colonizers. The recoveries lead to relatively mature biocenoses with high shares of persisters

of colonizers are a short life cycle, high colonization ability, and their tolerance to disturbance, eutrophication, and anoxybiosis. Colonizers live in ephemeral habitats. On the other hand “persisters”, K-strategists sensu lato, have a low reproduction rate, long life cycle, low colonization ability, and are sensitive to disturbance. Persisters live in habitats with a long durational stability (Bongers 1990). A schematic example from sediment toxicology may help to explain the sense of this approach (Fig.  14.4). In the first case, easily degradable organic matter was deposited and used by bacteria, stimulating tremendous bacterial production. This upsurge caused a subsequent increase in the number of colonizers, mainly bacteriafeeders. This increase in colonizers was accompanied by a reduction in the (relative) number of persisters. Once most organic matter was used and the bacteria density had fallen to the initial value, the numbers of colonizers also dropped down to their initial level. If the sediment was, however, treated with a toxic substance (second case), both strategists are numerically reduced. The nematode fauna recover slowly and only when the intoxication has stopped. This pragmatic approach of ecosystem integrity assessment was verified by, among many others, Beier and Traunspurger (2001) in a study of the sediment nematodes of two small German streams with contrasting pollution. A clear change of the nematode community structure towards a high percentage of colonizers at the impacted site indicated the predominance of bacteria as available food. The changes of the nematode community were related to eutrophication (case one in Fig. 14.4).

14.4 Species at Risk Indices, SPEAR The aforementioned system indicates organic pollution of rivers only as putrescible matter and does not discriminate between different classes of chemical substances or reflect the persistence of organic chemicals. With several papers, Liess and his

14.4  Species at Risk Indices, SPEAR

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Fig. 14.5  Sketch of a trait-based indicator system for pesticides (From Liess et al. (2008). With permission from Elsevier)

laboratory started to fill this gap (e.g., Liess et al. 2008). A promising approach to find a community metric independent of natural environmental factors and therefore stable gradients of natural factors is to employ biological traits (e.g., generation time, body size, migration) rather than taxonomic indices since it has been shown that many of these traits are stable at a large spatial scale (Bonada et al. 2006). In contrast to natural factors, exposure to pesticides or persistent organic pollutants influence trait modalities, for instance by extending the aquatic developmental period and shifting emergence to later seasons, and hence allow interpretation and/ or prediction of community change. In their pioneering paper Liess and Schulz (1996) showed that larvae of the caddisfly Limnephilus lunatus exposed to 0.01 mg l−1 of the synthetic pyrethroid fenvalerate exhibited only a relatively slightly elevated chronical lethality, yet emergence was strongly delayed. Consequently in the field, particularly under competition or risk of desiccation of the small streams, such reactions can endanger survival of the population. Generalizing such findings, Liess and Von der Ohe (2005) developed the SPEcies At Risk (SPEAR) system (Fig. 14.5). The following traits are central in SPEAR: physiological sensitivity to organic pollutants including pesticides, generation time including time to recover from the chemical stress, migration ability, and emergence time. Currently, two SPEAR-indices exist, SPEARpesticides and SPEARorganic, designed to detect and quantify effects of pesticides (particularly insecticides) and general organic toxicants, respectively. Liess and von der Ohe (2005) showed that the pesticide-specific SPEAR system is relatively independent of abiotic environmental factors other than pesticides and applicable across different biogeographical regions. The authors hypothesized that in macroinvertebrate communities the distribution of species sensitivity to organic toxicants in general is independent of natural longitudinal factors, but depends on contamination with organic toxicants. To confirm this hypothesis, Beketov and

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Fig. 14.6  Ordination plot for principle components analysis of the biological indices in a data set, including both uncontaminated and contaminated streams. Environmental variables are passively projected onto the ordination model (From Beketov and Liess (2008). With permission from Elsevier)

Liess (2008) analyzed the relationship between community sensitivity SPEARorganic and natural and anthropogenic environmental factors in a large-scale river system, from alpine streams to a lowland river. The results showed that SPEARorganic is indeed largely independent of natural longitudinal factors but depends strongly on contamination with organic toxicants such as petrochemicals and synthetic surfactants (Fig. 14.6).

14.5 Biomass Spectra Biomass spectra, that are the frequency distribution of different biomass size classes, are deducible from the recently established metabolic theory of ecology (Brown et al. 2004) and are still a matter of strong debate; nevertheless, they are theorybased – in contrast to the aforementioned empirical measures of integrity. Ecosystems are highly aggregated biological systems and may be considered to be super-organisms since they possess specific features (patterns and processes) which are lacking in lower aggregated systems such as populations and biocenoses. These features are, for instance, closed nutrient cycles or systemic homeostasis and, as a result, specific food web structures (discrete, discontinuous structures) or energy flow patterns (continuous structures). These characteristics may be applied

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as indicators of system integrity or disturbance. This meets the paramount important requirement for suitable biotic indicators of ecosystem change. For several decades, biomass spectra have successfully been developed for aquatic systems (see below). Allometric relationships between size classes of organisms and their abundance can demonstrate an energy flow pattern (Brown et al. 2004). Since the early twentieth century, it has been known that almost all characteristics of organisms vary predictably with body size. Huxley (1932) is credited with pointing out that most size-related variations can be described by so-called allometric equations which are power functions of the form

Y = Y0 M b .

(14.1)

The equation relates some dependent variable, Y (e.g., metabolic rate, development time, population growth rate, rate of molecular evolution), to body mass, M, through two coefficients: a normalization constant, Y0, and an allometric exponent, b. Most of these biological scaling exponents have the unusual property of being multiples of ¼, rather than the multiples of 1/3 that would be expected from Euclidean geometric scaling. For example, Kleiber (1932) showed that the wholeorganism metabolic rate, I, scales as

I = I 0 M3/ 4 ,

(14.2)

where I0 is a normalization constant independent of body size. The same relation, with different values for the normalization constant, describes: (1) basal metabolic rate, the minimal rate of energy expenditure necessary for survival under ideal conditions; and (2) field metabolic rate, the actual rate of energy expenditure by a free-living organism in nature, which ideally would include allocation to growth and reproduction sufficient to maintain a stable population. West et  al. (1997, 1999a, b) showed that the distinctively biological quarter-power allometric scaling could be explained by models in which whole-organism metabolic rate is limited by rates of uptake of resources across surfaces and rates of distribution of materials through branching networks. The fractal-like designs of these surfaces and networks cause their properties to scale as ¼ powers of body mass or volume rather than the 1/3 powers that would be expected based on Euclidean geometric scaling (Brown et al. 2004). Metabolic theory predicts how metabolic rate, by setting the rates of resource uptake from the environment and resource allocation to survival, growth, and reproduction, controls ecological processes at all levels of organization from individuals to the biosphere. Examples include: (1) life history attributes, including development rate, mortality rate, age at maturity, lifespan, and population growth rate; (2) population interactions, including carrying capacity, rates of competition and predation, and patterns of species diversity; and (3) ecosystem processes, including rates of biomass production and respiration and patterns of trophic dynamics.

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Sheldon et al. (1972) were the first to empirically show that marine plankton and nekton can be divided into discrete size classes. At that time, they unexpectedly found almost identical biomasses in the various size classes when these were put into logarithmic scales. Later, Sprules et al. (1983) applied this approach to freshwater lakes, and Peters (1983) used physiological examinations of respiration, growth, or generation time of various aquatic organisms to work out that these features depend mainly on the body size (allometric relation). By comparing biomass size spectra from Lakes Ontario and Malawi, Sprules (2008) recently affirmed that physiological and ecological similarities of like-sized organisms at various hierarchical levels of organization lead to regular and repeatedly observed emergent properties of aquatic ecosystems that are independent of specific species. The allometric relations are valid across 20 magnitude classes of body size, from single-celled organisms to large mammals. According to this assumption, energy flow does not necessarily follow discrete trophic levels (Peters 1983). Simply, the larger organisms feed on the smaller ones – except for pathogens and parasites. This assumption has gained considerable environmental realism, since the prevalence of omnivory in real food webs has been shown for terrestrial, marine, as well as freshwater systems: the smaller organism is the prey of the larger one and who feeds whom is a matter of the specific growth conditions of the different species (Sprules and Bowerman 1988; Thompson et al. 2007). The basic argument of this “ataxonomically” continuous distribution of plankton biomass across all size classes is as follows (Peters 1983): respiration and growth rate (RW) drop with increasing individual body weight (W):

R W ~ W -0.25

(14.3)

The respective time-related parameters such as generation length (T) increase with body weight at a comparable rate:

T ~ W 0.25

(14.4)

This results in a cumulative energy requirement per life span (ET) of:

E T » (T * R W ) » W 0

(14.5)

The efficiency of the energy transfer from food to the consumer is also found to depend on body size, similar to other features such as food use efficiency, growth, and efficiency of production. In sum, the complex, spatially and temporally varying structures and dynamics of ecological systems are largely consequences of biological metabolism (Brown et al. 2004). From the aforementioned findings it can be hypothesized that

abundance * weight class » constant

(14.6)

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With A the abundance, WC the weight class, and C a constant, two diagnostic theses can be derived: I. Energy equation:

logA = C - logWC

(14.7)

This equation must be fulfilled; on average, experimental data should not deviate significantly from the slope = −1. II. Continuity: The energy equation should be fulfilled by experimental data without any remarkable gap within the data distribution. If both requirements are not satisfied, then the integrity of the community under consideration is most likely hurt (Steinberg and Brüggemann 1997). Various examinations have shown that these allometric relations are valid in nondisturbed systems and may serve to predict the effect of toxic substances and other disturbances on pelagic ecosystems. Key examples will explain the feasibility of the biomass spectra approach to assess the integrity, abnormalities, or interesting irregularities of pelagic systems: food web structure, invasive species, chemical constraints, and fish stock exploitation.

14.5.1 Food Web Structure Hypersaline coastal lagoons are highly fluctuating systems and not often in the focus of ecological research, but they are excellent examples to demonstrate the power of biomass spectra. Gilabert (2001) analyzed the seasonality of such spectra in a Mediterranean hypersaline lagoon and showed that this fluctuating system does not always follow the aforementioned continuity requirement. Gilabert found two antagonistic examples of food web structure: the first with higher biovolume levels of autotrophic organisms, and the second with higher biovolume of heterotrophic ones (Fig. 14.7). The latter indicates the seasonal predominance of the heterotrophic pathway fueled by allochthonous detritus.

14.5.2 Invasive Species The transfer of ballast water between ports has served as an important vector for facilitating the invasion of many aquatic species to new habitats. Such is thought to be the case for Cercopagis pengoi, a Ponto-Caspian predatory cladoceran. It was first detected at relatively low abundances in Lake Ontario in 1998. Abundances in parts of the lake in the following year reached high values, and it had increased its range. The rapid increase in both lakewide abundance and range raised great concerns for the degree and impact of C. pengoi’s invasion into North America (Benoît

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Fig. 14.7  (a) Biomass spectra; (b) taxonomic spectra for the dominance of autotrophs (left) and for the dominance of heterotrophs (right) (From Gilabert (2001). With permission from Oxford University Press)

et  al. 2002). To overcome the general lack of information on the ecology of C. pengoi, normalized biomass spectra were appropriate tools. The spectra supported an impact of C. pengoi on organisms <0.1 mg dry weight, which was represented mainly by juvenile copepods. Among the cladocerans, only Bosmina longirostris abundance declined in the presence of C. pengoi. These organisms provide a vital link in the microbial loop and represent an important fraction of secondary production in pelagic areas of the lower Great Lakes, hence C. pengoi has the potential to affect pelagic secondary production in the invaded systems (Benoît et al. 2002). Another example of an invasive species, which interrupts existing food webs, is the spread of the exotic gizzard shad, Dorosoma cepedianum, into Oneida Lake, New York. This fish belongs to the herring family Clupeidae and is native to fresh and salt waters of eastern North America. Gizzard shads contribute to eutrophication, both by fertilizing algae with their copious feces and by preying on “grazing” zooplankton that normally feed on algae. Gamble et  al. (2006) showed that gizzard shads had the most significant impact selectively on the size class that is dominated by Daphnia – indicating that shads successfully compete with the indigenous fish population without an obvious risk of disrupting the energy transfer from primary producers to top predators.

14.5.3 Chemical Constraints Chemical constraints considered are (1) low oxygen regimes in the sediment water interface as well as (2) eutrophication and toxic substances.

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Fig. 14.8  Normalized biomass-size spectra of the benthic macrofauna inside (a) and outside (b) of marine oxygen minimum zones (From Quiroga et al. (2005). With permission from Elsevier)

14.5.3.1 Oceanic Oxygen Minimum Zones Oxygen minimum zones are ubiquitous and persistent features on the continental margins of ocean basins where dissolved oxygen concentrations decrease to low levels (<0.5 ml l−1). These oxygen minimum zones develop beneath highly productive surface waters due to high biological and biochemical oxygen demand. Benthic populations and community structures are greatly influenced by the presence of oxygen minimum zones. Oxygen minimum zones are generally dominated by nematodes, oligochaetes, and small-bodied polychaetes, probably associated with the high availability of food and the reduction in predation pressure (Quiroga et al. 2005). The slope of the normalized biomass-size spectra for organisms living in the oxygen minimum zone was significantly different from that of organisms living beneath that zone (Fig. 14.8). This indicates that benthic communities inhabiting the oxygen minimum zone consisted of smaller macrofauna in comparison to the size-structures observed at stations located beneath that zone. This pattern can be explained by physiological constraints: small organisms are better able to satisfy their metabolic demands (including respiration), because they have a higher surface area to body volume ratio. This also means that the biomass-size diversity decreases with decreasing oxygen concentration, presenting fewer size classes than those found in communities living under normal oxygen conditions (Quiroga et al. 2005).

14.5.3.2 Eutrophication and Toxic Substances As a basis of comparison, a convincing example of an integer pelagic system has been published by Sprules and Stockwell (1995) (Fig. 14.9, left) for Lake Ontario. The allometric graph shows clearly that total biomass decreases with increasing body size and that the product from individual biomass and abundance is almost constant over all size classes. The small variation of points around the line suggests that this plankton community is close to steady state conditions. As an example for a biomass spectrum characteristic of a non-steady state system, the reader is referred

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10

Lake Ontario mesotrophic

Lake St. Clair eutrophicated, highly flushed

8 6

zoo

lg (abundance)

Normalized biomass (log m−2)

15

5 fish

0

4

Jul Aug Sep

2 0 -2

-5

-4 -10 -15

-10

-5 log mass (g)

0

5

-6

-6

-4

-2

0 2 4 6 lg (body weight)

8

Fig. 14.9  Normalized biomass spectra and linear regressions of the plankton association in Lake Ontario, as a mean over the entire water column and one growth season (left) and in the contaminated Lake St. Clair (right) in three subsequent months in 1984 (After Sprules and Stockwell (1995). With permission of the Oxford University Press; Sprules and Munawar (1991). With permission from Springer)

to the plankton in the eutrophicated and highly flushed Lake St. Clair (Sprules and Munawar 1991) (Fig.  14.9, right): the variation around the linear trend is much higher than that from Lake Ontario. Although the axes in both graphs are not identical, the stress on the plankton system in Lake St. Clair is obvious by the strong scatter around the regression line. This plankton system is not at steady state. Tittel et al. (1998) confirmed that differences in the biomass of the various size classes were a consequence of eutrophic conditions as exemplified by Lake Arendsee, Germany, not of littoral or benthic influences as discussed by, e.g., Sprules and Munawar (1986). In this context, it appears of no significance that the use of nonlinear functions (Sprules and Goyke 1994) may achieve better statistics; the indications remain identical. In empirical studies, it appears increasingly feasible that the presented ataxonomic approach can serve as a measure of the integrity of the ecosystem considered or parts of it. Two parameter classes would result, which could be used to detect and evaluate the disturbance (harm or even damage) in the examined section of the ecosystem: • Energy equation: statistical parameters for the fitted (linear or parabolic) function (variances, bias) • Continuity: statistical parameters describing the scatter of measured values along the energy equation • Stability parameters such as time required by the system to recover from the disturbance after eliminating the disturbance. Illustrating the latter topic, Sellanes et al. (2007) showed that, in marine macroinvertebrate communities under oxygen deprivation, it took more than 5 years to return

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Fig. 14.10  Two allometric scalings and soil nutrient ratios. Arranged according to a decreasing coefficient of variation in the study sites. Top: faunal biomass spectrum slope (A = Animalia). Bottom: mass – abundance slope of the complete community food web (A + E + F = Animalia, Eubacteria, and Fungi). The logarithm of the C:P ratio equals the sum of the log C:N and log N: P ratios and is the best sole predictor for allometric scaling after pH. Diamonds: abandoned; squares: managed by liming (From Mulder and Elser (2009). With permission from Wiley)

to “normal” structures. Supporting the second requirement, Steinberg and Brüggemann (1997) and Steinberg et al. (1998a, b) discovered by means of flow cytometry that particularly picoplanktic cyanobacteria (Synechococcus/Synechocystis-like particles) were lacking in both eutrophicated and acidified waters and therefore may serve as an indicator of plankton integrity. In a recent series of papers on soil invertebrates, Mulder (2006, 2010; Mulder and Elser 2009) showed that the allometric food web topology allows for the recognition of altered magnitude of interaction strengths in the propagation of stress and environmental disturbance across trophic levels. Particularly, soil acidity and soil fertility control the slopes of the allometric relationship between biomass and abundance of invertebrates as exemplified in Fig. 14.10. Plotting biomass spectrum slopes and mass–abundance slopes against the logarithms of the soil nutrient ratios revealed strong relationships between nutrient ratios and faunal biomass size spectra (Fig. 14.10). The interpretation of the biomass spectrum slope is intuitive: negative trends indicate that faunal biomass under nutrient deficiency declined with increased body size. Biomass spectrum slopes were most significantly correlated with the logarithm of the soil C:P ratio but less with the logarithms of the N:P and C:N ratios. In all cases of allometric scaling, the logarithm of the C:P ratio was the best sole predictor (Fig.  14.10, right column). All the negative trends along the environmental correlates of Fig.  14.10 indicate that (i) faunal biomass declined with increased body size within log(M) bins, and (ii) faunal population density decreased with increased body size. Hence, differences in soil P availability are

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reflected within the studied grasslands (and possibly in other biomes as well) in the body-size distribution of the biomass and density of the soil microfauna and mesofauna, since stoichiometric theory predicts that soil fauna with higher P demands would suffer a competitive disadvantage in lower P soils due to poorer stoichiometric food quality. 14.5.3.3 Fish Stock Exploitation Fish stock exploitation is the best-established example of the application of allometric relationships. In their pioneering paper, Sheldon et al. (1972) showed that the form of the size spectra varied predictably both geographically and with depth. They presented a hypothesis that roughly equal concentrations of material occur at all particle sizes within the range from 1 mm to about 106 mm, i.e., from bacteria to whales (see Eq. 14.6). They stated that the biomass of higher trophic levels could be predicted based on plankton data. Sprules and Stockwell (1995) transferred this allometric approach to the pelagic system of the Laurentian Great Lakes. Their basic assumption was that models of predator-prey interactions predict the size distribution of biomass in aquatic communities to be a series of repeated quadratic curves corresponding to component trophic groupings. Sprules and Goyke (1994) exemplified this assertion for Lakes Michigan and Ontario. The achieved parabolas all have the same curvature, and the vertex of each could be shifted a fixed horizontal and vertical distance from the others. The trophic parabolas, or biomass “domes”, stand in fixed relation to one another, making it possible to predict the location of other domes if data are only available for one of them (Dickie et al. 1987; Boudreau and Dickie 1992; Sprules and Goyke 1994). The latter authors showed that such estimates of zooplankton production in Lake Ontario agree well with direct sampling. Size-based production techniques can reduce the huge investments of time and energy normally required for assessing production of fish stocks. Vice versa, any deviation from this regularity is an alarm signal for ecological peculiarities or anthropogenic disturbances in the pelagic food web. More generally, spectra from different environments exhibit a uniform low slope but with different intercepts that appear to reflect ecosystem differences in nutrient circulation and availability. Detail on the secondary structuring at various positions in the trophic system appears to provide information useful for distinguishing between long-term changes in productivity and short-term perturbations in biomass or abundance (Boudreau and Dickie 1992). This implies again that biomass spectra provide a means to assess the integrity of pelagic systems with particular respect to fisheries and to derive indicators for sustainable fisheries. Several studies prove the practical feasibility of this approach, particularly for marine fisheries (Pope and Knights 1982; Pope et al. 1988; Rice and Gislason 1996; Bianchi et al. 2000). For instance, Blanchard et al. (2005) used the size-based community metrics for Celtic Sea fish using data from the English groundfish survey of the area (1987–2003). The results revealed that the size structure of the community

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Fig. 14.11  Abundance (biomass)–body mass relationships for northern North Sea fishes 2002– 2004. Open circles indicate biomass by body mass class and body mass class midpoint when individuals were pooled by body mass class independent of species identity. Filled circles indicate mean biomass and mean body mass of individual species. Continuous lines are the fitted relationships between biomass by body mass class and body mass (From Jennings et  al. (2007). With permission from Wiley)

had changed over time and that a decrease in the relative abundance of larger fish was accompanied by an increase in smaller fish. Temporal analyses of the effects of fishing and climate variation suggested that fishing generally has had a stronger effect on size structure than changes in temperature. Similar to the aforementioned example of soil organisms provided by Mulder and Elser (2009), the slopes of abundance–mean body mass relationships in fish communities indicate the energy availability in a given year and in a given region (Fig. 14.11). The steeper the slope, the less energy is passed to the larger fishes.

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Fig. 14.12  Predicted slopes of an unexploited size spectrum (dotted line) and of size spectra for the exploited North Sea in 1982 (dashed line) and 2001 (solid line). Circles indicate biomass at body mass for the entire food web (fish and invertebrates) in the central North Sea in 2001 (From Jennings and Blanchard (2004). With permission from Wiley)

When this allometric relationship is plotted for all North Sea fish species (open circles) from 2002 to 2004, it becomes obvious that in 2002, more energy was available than in the following years. Shin et al. (2005) presented an excellent overview on conceptual models which apply the allometric approach to marine fisheries and fishing effects. There are several reasons why size-based indicators theoretically allow tracking of direct fishing effects on fish communities: (i) high-value, generally larger species are targeted through spatio-temporal fishing strategies; (ii) fishing gears are size-selective and often designed to remove larger fish and allow smaller ones to escape; (iii) older (and larger) fish in a population become fewer because cohorts accumulate the effects of fishing mortality through time; and (iv) large-sized species are more vulnerable because they have lower potential rates of increase and will be less able to withstand a given rate of mortality. Several size-structured models have been explored in order to quantify the effects of fishing on emergent size spectra. The theoretical simulations of Gislason and Rice (1998) and Benoît and Rochet (2004) suggested a linear relationship between fishing mortality and both slope and intercept of the size spectrum. Expanding the model of Silvert and Platt (1978), which formalized the flux of matter in a plankton community as a function of time and individual weight, and assuming that respiration and growth are allometric processes, mortality (fishing and predation) is a function of size. This suggests that fishing effects may be better captured by the curvature of the size spectrum or the scatter around the regression line than by its slope (also see discussion of diagnostic theses above). Based on simulations with an individual-based model in which predation is a size-based

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opportunistic process and key processes of the life cycle (growth, reproduction, mortality) depend on food intake, Shin and Cury (2004) showed that slope and curvature of the size spectrum decrease quasi-linearly as a function of fishing mortality (Fig. 14.12). Based on such models, figures of sustainable fishing can be derived by consensus and successfully monitored, particularly for the larger size classes.

sdfsdf

Chapter 15

Environmental Stresses: Ecological Driving Force and Key Player in Evolution

Natural environments have always been hostile for organisms. Exposure to climatic stress is the norm in nature, and hydrological changes, especially drought and flood, are of major importance. Human interference can exacerbate these effects (Parsons 1995). Consequently, environmental stress is notoriously associated with population decline and extinction; hence, its potentially positive roles in shaping communities and triggering evolution are often overlooked (Lexer and Fay 2005), and if considered, they are often still gene-centered. However, clearly below the mutation threshold and even below the epigenetically triggered inheritance of acquired properties, environmental stresses are essential driving forces in ecosystems which enable life particularly in fluctuating environments. At an even more fundamental level, it is clear that environmental stressors have been and still are key players in shaping organismal evolution. In other words, moderate stress plays an important role in facilitating local adaptation by enabling better adjustments, synchronization, and functioning of many organismal systems. On the other hand, response to an acute and unfamiliar stressor precludes normal organismal functions, and the high cost of stress tolerance or lack of evolved stress response strategies leads to evolutionary stasis (Parsons 1994).

15.1 Ecological Driving Force Ecological stressors are everywhere and unavoidable for prokaryotes as well as eukaryotes, for animals, and particularly for plants. Any abiotic or biotic variable can be a stressor. Too hot or too cold conditions are stressful; too much or too little water as well as too much or too little light can become significant stressors; the same applies to the absence of nutrients or food as well as too many nutrients or high food levels. In addition, nutrient patterns and food quality can induce stress symptoms. Herbivory and predation are stressful or eventually lethal to prey. Even the establishment of symbiosis starts as an infection, and parasites and pathogens C.E.W. Steinberg, Stress Ecology: Environmental Stress as Ecological Driving Force and Key Player in Evolution, DOI 10.1007/978-94-007-2072-5_15, © Springer Science+Business Media B.V. 2012

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are obvious stressors. In contrast to the public association of environmental stress with adverse symptoms, organisms are well prepared to encounter mild to medium stresses; in fact, they have adapted to them. Moreover, due to the long-term co-evolution of organisms and stresses, organisms are able to convert a seemingly adverse stress into benefits for their individual integrity, for individual health and longevity, and multi-species biodiversity and evolution. Even more pronounced, natural stresses are crucial for the maintenance of life on earth. Many stress responses are so unspecific that organisms are able to successfully counter even anthropogenic stressors, to which they have not (yet) adapted, with the same tools. All organisms respond rather similar to any type of stress; they activate oxygen by its stepwise reduction, actuate the biotransformation machinery, and simultaneously protect proteins from deformation by increasing the number of chaperones and chaperonins. Since these steps are uniform in prokaryotes and eukaryotes, one may hypothesize that a primordial environmental trigger common to all organisms led to the evolution of the defense system. This trigger might have been humic substance-like compounds, which Miller (1955) and observed in his classical experiment demonstrating co-evolution between these substances and biomolecules such as amino acids. Ziechmann (1996) confirmed this work later. These compounds are natural xenobiotics (Steinberg et al. 2003) which induce similar defense responses as current synthetic chemicals, or vice versa, synthetic chemicals can be dealt with using the same defense systems as those dealing with natural xenobiotic chemicals, however, often less successfully. After the establishment of a common primordial stress defense system, its specification developed simultaneously with the evolution of organismal biodiversity, providing, for instance, plants with a higher number of biotransformation and transporter units than animals and adjusting the organisms to the specific requirements of their ecological niche. Plants, in turn, utilize the diversity of synthetic pathways to produce a variety of secondary metabolites which protect them as sessile organisms against many abiotic stressors as well as against attacks from herbivores, pathogens, and parasites. The latter use the unspecific biotransformation system to cope with the plants’ chemical armament; the arms race between plants on the one hand and animals, pathogens, and parasites on the other is established. Since environmental stressors may change with climate change, plants primarily are affected by and forced to re-adjust their defense system and thereby stress their enemies, who then have to adapt to the new challenge by the plants. Usually, the early defense steps of all organisms take place in disfavor of regular cell functions such as synthesis of nucleic acid compounds for subsequent cell division, and carbon and energy metabolism, such as catalytic activity, hydrolase activity, or peptidase activity. Where applicable, this down-regulation of regular pathways happens in favor of flight reactions. After the early and very fast nonspecific stress response, stress-specific responses help the organisms adjust to the new environmental challenge and prepare for the re-establishment of regular metabolism as the last step. Central in the response to any challenge is the minimal stress proteome with its various HSPs. HSPs are involved in the defense of any possible stress and prepare

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the organism for the next stressor to come. For example, this means that the challenge by a chemical trigger can result in increasing resistance to other chemical or even physical or biological triggers. This phenomenon is known as crosstolerance or multiple-stress resistance. In prokaryotic microorganisms, cross-tolerance to environmental stressors seems to be the common case rather than an exception, whereas cross-tolerance is less common in eukaryotic organisms and is based on more than one regulatory mechanism. The acquisition of cross-tolerances is particularly crucial in strongly fluctuating environments and may apply more strongly to plants than to animals since most of the latter have the choice of flight in order to escape adverse environmental conditions. Nevertheless, unpredictable and unavoidable multiple challenges apply to all organisms, and cross-tolerance is a major tool to survive in fluctuating environments. Furthermore, non-lethal stresses separate sensitive species with a low potential of cross-tolerance from the more robust species, which may easily gain crosstolerances. Hence, these stressors are triggers of microevolution and macroevolution. Stress-resistances can be permanently inherited via genetic mechanisms (mutants). There is increasing evidence that stress resistance can be maintained for several to many generations by epigenetic mechanisms. Hence, stresses as factors shaping communities on a short-term as well as on an evolutionary basis deserve future attention. Environmental stressors are of a physical nature (excess of light, UV irradiation, heat, cold, drought, flood) or of a chemical nature (salt, acids, bases, metals, natural and synthetic xenobiotics). In many cases, it is almost irrelevant whether the initial trigger for the cross-tolerance is a physical or a chemical one provided it remains on the mild level and does not provoke acute lethality. The initial stressor prepares the organism for a second chemical or physical stressor. However, biological stressors such as pathogen infection may be attenuated if the organism has been physically or chemically challenged before. This was clearly demonstrated with Arabidopsis thaliana infected by Pseudomonas syringae (Bowler and Fluhr 2000) and with Artemia franciscana larvae infected by Vibrio campbelli (Sung et  al. 2008). The stressed organisms increased their HSP levels after the primary physical challenge. The converse pathway of cross-tolerance acquisition, namely by a primary pathogenic challenge, however, has not yet been documented although this kind of biotic stress also increases the concentrations of stress proteins (see Table 5.1). However, a non-pathogenic biological challenge may increase the tolerance to another biological challenge. For instance, inoculation with non-pathogenic root zone bacteria leads to higher pathogen resistance of the host plant (Dimkpa et al. 2009). It remains to be elucidated whether or not this priming also increases resistance to abiotic stressors. Currently, there are no reports on this issue. Furthermore, there are indications that predation risk as another major biotic challenge to organisms may reduce the fitness of parasites, probably not via HSPs but via reduced somatic growth of the host, presumably resulting in fewer resources for parasite development (Coors and De Meester 2010). These examples make clear that even mild biotic stressors have the potential to increase the fitness of the affected organisms and deserve to be studied in detail.

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Interestingly, there seems to be a general relationship between stress resistance traits and longevity or aging traits (Sørensen et al. 2003). Several recent papers tie stress exposure, stress resistance, and the expression of HSPs to life span (longevity), although the mechanisms and ecological implications are not yet fully understood. A prevalent theory states that the activation of defense/cleaning systems (HSPs, antioxidases, and DNA repair) by stress postpones the deleterious effects that otherwise would occur with age (Minois 2000). Particularly, the expression of small HSPs seems to prolong the individual life span (Morrow et al. 2004a, b; Steinberg et al. 2007). One important question is whether a longer life leads to increased fitness. Data on this topic indicate that increased longevity also increases the lifetime reproductive success in several, but not all, tested animals, thereby increasing their fitness. This phenomenon was clearly shown with the fruitfly Drosophila (Norry and Loeschcke 2002, 2003), and it tends to apply to the cladoceran Moina macrocopa exposed to specific humic substances (HSs) and fed the coccal green alga Pseudokirchneriella subcapitata (Steinberg et  al. 2010a). If M. macrocopa was fed another coccal green alga, namely Monoraphidium minutum, and stressed by HSs, it increased, both its lifespan and its lifetime reproductive output (Chap. 13). Increased numbers of individuals resulting from the increased reproductive output can lead to greater competition with the longer-lived parental generation for limited resources – with uncertain outcome. These results were obtained in a protected laboratory environment, and the ecological relevance needs to be investigated further. The more common case, however, is that either longevity or reproduction, but not both, is increased after a mild challenge. Either modulation can cause a shift in the demographic structure, whereby lifespan extension combined with reduced offspring numbers result in a population decline after several generations – even in a protected environment. Consequently, it is a future scientific challenge to identify whether or not this intrinsic risk of population extinction applies even in nature. Another challenge is to expand the knowledge gained from zoological studies to botanical organisms. A current paradigm states that most plants do not age in the strict gerontological sense, namely as an entire organism (Thomas 2002), so that it can be expected that mild stresses do not necessarily lead to lifespan extension of the entire plants but of certain organs, which means that only these organs have developed a stress resistance. However, recent lines of evidence reveal a correlation between plant stress tolerance and regulation of senescence and life span of entire plants. It is open to future studies whether or not this evidence is generalizable and to figure out the conditions under which it does not apply. Another open issue is the question of what this means in an ecological context. Does potential delayed aging of a species or of stressed individuals shape the plant community by shifting intraand inter-specific competition? What does it mean in the context of global climate change? Are these species better prepared to meet predicted increases in drought, heat, and salinity of soils? Finally, the question arises whether environmental stresses, which strengthen individual life traits, also translate into long-term advantages of adaptation or even speciation.

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15.2 Trigger of Microevolution and Evolution There is growing evidence that the genetic mechanism is a major, but not the only form of adaptations. Adaptation can here be defined as the process of change in a clone/strain or population of a species to cope with new environmental conditions whereby the organisms acquire characteristic features. These features include changes in morphology, physiology, or behavior that improve survival as well as reproductive success in the particular environment. If such changes occur only phenotypical acclimation is the result. Hence, acclimation is the capability of a genotype to change its phenotype according to prevailing environmental conditions. On the other hand, adaptation in an evolutionary sense occurs through changes in allele frequencies because of selection pressure exerted by the environment. In particular, populations at the margins of their ecological range are likely to be disproportionately more exposed to ongoing changes compared to populations from areas central to a species’ range. Adaptation is a common and widespread microevolutionary phenomenon that is essential in the long-term as a response to environmental change (Salamin et al. 2010). Phenotypic diversity also depends on the epigenetic programming of gene expression profiles (see Chap. 8). The genome is programmed by the epigenome. Two of the fundamental components of the epigenome are chromatin structure and covalent modification of the DNA molecule itself by methylation. DNA methylation patterns are sculpted during development and it has been a long held belief that they remain stable after birth in somatic tissues (Szyf et al. 2008). These authors suggest, however, that epigenetic equilibrium remains responsive throughout life and that environmental triggers could play a role in generating interindividual or interclonal differences in exposed organisms. If this epigenetic programming is stable over many generations, as documented for Drosophila melanogaster challenged by the HSP90-inhibitor geldanamycin (Sollars et al. 2003), phenotypic changes cannot be distinguished from genetically controlled adaptations – they are adaptation-like acclimations and equivalent to them.

15.2.1 Microevolution Microevolution – the change in gene frequency within a population over time – is often found under stress conditions and is based on four different processes: mutation, selection (natural and artificial), gene flow, and genetic drift. Stress conditions may be, e.g., parasite infection, predation threat, low food quality, temperature changes, drought, flooding, xenobiotic exposure, or metal challenge. 15.2.1.1 Parasites and Crowding As shown in Chap. 3, Capaul and Ebert (2003) found significant differences in the success of various D. magna clones under stress from different parasites,

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Fig. 15.1  Relative ephippia production of five Daphnia galeata clones in a 56-day experiment (Modified from Koch et al. (2009). With permission from Springer)

with one clone winning the competition during periods of asexual reproduction. Yet, microevolution applies also to the sexual reproduction of Daphnia. The production of resting stages in aquatic environments is an important fitness factor. Resting stages are often the only possibility for dispersal or for coping with unfavorable conditions such as dryness, strong seasonal temperature fluctuations, predation, and decreasing food supply. Koch (2009) compared five clones of Daphnia galeata subject to density stress. Clones of equal densities produced significantly different numbers of ephippia (Fig. 15.1). After the termination of the stressor, the clone-diversity may be reduced.

15.2.1.2 Temperature Seemingly more subtle environmental challenges such as slight temperature increases trigger microevolution as evidenced in the context of global climate warming. Climate warming changes the environment of most organisms and is expected to lead to a change in selection pressures with microevolutionary consequences that allow the acclimation and final evolutionary adaptation of organisms to this new environment and thereby long-term population persistence (see Box 15.1). Microevolution in response to climate change is usually demonstrated by linking particular genotypes to climate. This will be exemplified with one invertebrate and one vertebrate study. The community of the Daphnia galeata-hyalina hybrid complex in the Saidenbach Reservoir (Saxony, Germany) was studied for three consecutive years (2005–2007), including one (2007) following an unusually warm winter that prevented the formation of ice cover (Zeis et al. 2010). Genetic composition during the 2007 season differed substantially from the two preceding years that experienced the usual ice periods. The 2007 population was dominated by hybrids of

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Daphnia galeata x hyalina whereas in the 2005 and 2006 seasons, Daphnia hyalina genotypes dominated. The genetic composition of the pool of diapausing eggs produced in autumn and the rate of change of genotype abundance during the following spring indicate recruitment of the D. hyalina subpopulation from ex-ephippial animals during the spring population increase. The study indicates a profound role of recruitment strategy in the observed shift in genetic composition. Increasing winter temperatures favor overwintering animals, leading to an increase in the contribution of these genotypes to the population. In tawny owls Strix aluco the yellow to red-brown coloration is a highly heritable trait consistent with a simple Mendelian pattern of brown dominance over grey (Karell et al. 2011). Strong viability selection against the brown morph occurred only under snow-rich winters. As winter conditions have become milder in the last decades, selection against the brown morph diminished. Concurrent with this reduced selection, the frequency of brown morphs have increased rapidly. This is the first evidence that recent climate change alters natural selection in a wild population leading to a microevolutionary response. 15.2.1.3 Synthetic Xenobiotics and Metals Many experimental studies show the potential of heavy metal and xenobiotic contaminations to induce microevolution in animals and plants. The striking example of the Atlantic killifish Fundulus heteroclitus inhabiting Superfund sites at the Atlantic coast of North America was extensively discussed in previous chapters. Another example was presented by Lopes et  al. (2009) who investigated the effects of metal toxicity on the genetic diversity of populations of Daphnia longispina. Five clones differing in their sensitivity to lethal concentrations of a metalrich mine drainage effluent were subjected to three levels (absent, weak, strong) of mine drainage. The most sensitive genotypes disappeared under both weak and strong stress levels. Because the surviving resistant clones were the most sensitive ones to other chemicals, it was suggested that successive inputs of partially lethal concentrations of different chemicals could lead to the disappearance of the population, even if the time between inputs is large enough to allow density recovery. Overall, the study presents evidence for the occurrence of chemical-mediated genetic erosion – another word for microevolution. In polluted environments, intra- and interpopulation changes at the molecular level proceed rapidly and lead to the formation of new ecotypes in a relatively short time. Słomka et al. (2011) analyzed the genetic diversity and genetic structure of seven populations of heartsease Viola tricolor growing on soil contaminated with heavy metals (Zn, Pb, Cd; waste heaps) and on control soil. A structure analysis showed a clear difference between the non-metallicolous and metallicolous populations with the greatest interpopulation differentiation among the populations on metal-containing soils which showed also higher genetic polymorphism and gene diversity than the control populations.

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15.2.2 Evolution Natural selection acts on phenotypic variations between individuals in a population. The function of genes is to ensure that traits favored by selection are inherited by the offspring of individuals possessing what Darwin referred to as useful variation (Mayr 2001). A population may evolve through a combination of individual elimination and differential survival into a local adapted population with the capacity to tolerate environmental stresses. An adaptation to climatic factors is the evolution of to the C4 photosynthetic pathway (Box 15.1). Populations are not genetically homogeneous across their distribution ranges and can be subject locally to evolutionary processes. A central tenet of evolutionary ecology is: Phenotype = Genotype × Environment (Morgan et  al. 2007). Interpopulation variations in stress-susceptibility are reflected in measured life trait variables and stress. In stress-tolerant population, the heritability of tolerance traits is a prerequisite to distinguish constitutive adaptation from the physiological adjustment (“acclimation” or “phenotypic plasticity”, Table 15.1) that occurs during an individual’s exposure history to stressors (Morgan et al. 2007). How does the genotype translate into the corresponding genotype? In fact, genotype-to-phenotype mapping was one of the major focuses of the molecular biology revolution. Many studies have defined the stability, which is generally measured as the rate of change of the phenotype per cellular generation, of various phenotypes. Box 15.1  Evolution of C4 Photosynthesis A classical example of the impact of global climatic changes on adaptation can be found in the grass family which was triggered by an adaptive response to decreasing atmospheric CO2 concentration. The C4 photosynthetic pathway is a suite of biochemical and anatomical adaptations that enhances photosynthetic performance in plants under high-temperature and low-CO2 environments when compared to the standard C3 pathway. This suite of adaptations has appeared independently over 18 times in the diversification of the grass family. This evolutionary independence stands in contrast to the observed phenotypic convergence found in all C4 plants. By incorporating the change in CO2 concentration through time into a model of character evolution, Christin et al. (2008) showed that the appearance of the C4 pathway in grasses is associated with an abrupt decrease in atmospheric CO2 levels in the Oligocene. The accumulation of numerous biochemical and morphological modifications required for a functioning C4 metabolism suggests that some lineages are predisposed to acquire these changes in response to changing environmental conditions. This raises the question of whether such biochemical flexibility is generally associated with the potential for plants to adapt to changing environments (from Salamin et al. 2010 and references therein) (Fig. 15.2). (continued)

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Box 15.1  (continued)

Fig. 15.2  Paleogene CO2 levels and C4 photosynthesis evolution. (a) CO2 concentrations (ppmv) during the Paleogene. The surface of the curve represents maximal and minimal estimates. (b) Ages of the different C4 grass lineages. Thick bars represent the interval between stem and crown group nodes of each C4 lineage and thin bars give the standard deviations (From Christin et al. (2008). With permission from Elsevier)

Notably, this massive research effort has identified phenotypes whose stability differs significantly from typical phenotypic stabilities (Fig. 15.3). For example, certain phenotypes are inherently less sensitive to mutation, and this insensitivity of a phenotype to genetic mutation is often referred to as “robustness” or “canalization” (Waddington 1942). By contrast, other phenotypes exhibit unusually rapid variation due to underlying hypervariable sequences in the genome. Still other phenotypes exhibit rapid variation despite no underlying genotypic change; these

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Table 15.1  Generic mechanisms whereby organisms cope with excessive stresses (From Morgan et al. (2007). With permission from the American Chemical Society) Acclimation Adaptation tolerance resistance stress response during an individual’s lifetime stress responses evolve during multigenerational exposure histories responses are induced rather than being “fixed” responses are often constitutive or constitutive phenotypic plasticity – morphology, biochemistry, heritable, genetically-determined, behavior adaptations resulting from directional selection phenotypic plasticity is genetically determined genetically differentiated populations are “ecotypes” adapted organisms may have lower fitness offspring raised in clean environments may than non-adapted organisms in “clean” be acclimated if stressor (e.g., metal) is environment – the cost of tolerance transferred from mother to embryo traits may be lost if stressor is withdrawn removal of stress may result in population reverting to the non-adapted state if the adaptation has a fitness cost

Fig. 15.3  The timescales of inheritance. The figure shows rough timescales, in units of cellular generation, for the stability of phenotypes regulated by the indicated mechanisms (From Rando and Verstrepen (2007). With permission from Elsevier)

phenotypes belong to the class of “epigenetically” heritable phenotypes. These and many other examples demonstrate that phenotypic stability spans many orders of magnitude beyond the range expected from classic genetic mutation studies, with some phenotypes varying rapidly while others are unusually stable (Fig.  15.3) (Rando and Verstrepen 2007 and references therein). Both inheritance and selection can act on a wide array of different timescales, ranging from fewer than one cellular (or organismal) generation to more than one billion generations. A number of different mechanisms exist that regulate the stability of biological phenotypes. Phenotypes inherited epigenetically often exhibit rapid variation, whereas genetically robust phenotypes are stabilized against random mutation – arguably the most common mechanism for phenotypic change.

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Fig. 15.4  Predicted gene diversity (top; light grey) and genetic differentiation (bottom; dark grey) trends along a spatial gradient from a theoretical point-pollution/contamination source. Explanations in the text (From Guinand et al. (2011). With permission from Elsevier)

15.2.2.1 Metals as Evolutionary Trigger Morgan et al. (2007) presented a model involving a decrease in gene diversity and an increase in genetic differentiation at target loci as responses to stress and contamination gradients resulting from a point-source of metal-pollution. A number of conditions should normally be satisfied before metal pollution results in the sitespecific evolution of resistance: (i) a stress intensity exceeding the capacity of the local species to prevail by plastic responses alone; (ii) a sufficiently long population exposure history relative to the generation period; (iii) the availability of resistant genotypes, albeit at low frequency, in the non-polluted region contiguous with the polluted site; and (iv) limited mobility and gene flow (Fig. 15.4). It is interesting to determine whether the proposed schedule can be verified by field studies other than those of Morgan and co-workers (2007). Actually, Guinand et al. (2011) carried out one of these studies with young-of-the-year common sole, Solea solea in Charentais Straits, Bay of Biscay, France. The genetic data for null alleles and corrected estimation of their frequencies fit Morgan et al.’s (2007) model particularly well (Fig. 15.4). Gene diversity is expected to decrease in the vicinity of the source, according to increasing gradients in stress intensity, contamination, and/or bioavailability (in black; from – → +++). Genetic differentiation among populations is expected to increase and gene diversity to decrease with the associated gradient of putative selective pressures. Generally, strength of gene flow will conflict with selective pressures to homogenize allele frequencies among populations, contributing to lower levels of population differentiation and a higher level of gene diversity. Depending on the status of the loci investigated (selected vs neutral), observed patterns of gene diversity and genetic differentiation are expected to be distinct. Selected loci are expected to follow the expected trends for gene diversity

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and genetic differentiation as long as gene flow is low, while neutral loci are expected to be independent of trend as no selective pressure is directly acting on them, making them less sensitive to stress intensity and level of contamination (i.e., no environmentally driven gene differentiation, no loss in gene diversity). Neutral loci are possibly sensitive to selective pressure due to environmental stress only if they are linked to a locus being the real target of selection (“hitch-hiking selection”). Contrary to results presented above, studies dealing with metal-induced genetic change often found overall depletion of genetic diversity at all investigated biomarkers according to the “genetic erosion” hypothesis (van Straalen and Timmermans 2002). This suggests that genetic drift, selection for individuals with distinct genetic profiles such as those who display inbreding is probably responsible for overall loss of gene diversity. When reconsidering Guinand et al.’s (2011) study, genetic differentiation results at locus MT for the sole may support a selective hypothesis in young-of-the-year sole as selection is locus-specific. This selective hypothesis agrees with the numerous published cases dissecting how selection may operate at MT loci. This includes cases of aquatic organisms in which some MT alleles have been shown to respond to selection (oligochaete, Limnodrilus hoffmeisteri; Pacific oyster, Crassostrea gigas). In Drosophila populations, metal resistance seems to be associated with a duplication of the MT gene. It has also been shown that elements located in intron one regulated expression of a MT gene and the efficiency of the detoxification process in sea urchin, Strongylocentrotus purpuratus (Guinand et al. 2011 with references therein). Populations of Orchesella cincta springtails differ in heavy-metal resistance, and this has been linked to the expression of MTs. Differences in expression seem to be due, at least in part, to variation in the promoter region of the MT gene (Hoffmann and Willi 2008). Morgan et al. (2007) refer to another molecular-genetic mechanism that may also lead to fast adaptation to stress-induced environmental changes in prokaryotes and eukaryotes involving satellite repeat sequences and microsatellites or simple sequence repeats. There is accumulating evidence that repeated sequences in invertebrates as well as vertebrates are transcribed under physiological and pathological stress. The following quotations from Herbert (2004) give a flavor of the fundamental importance of the field and serve as a prompt to evolutionary geneticists and ecotoxicologists: “We find that non-protein coding RNAs are central to the translation of coding RNAs and to the co-regulation of other cellular events. Through combinatorial processes that lead to new coRNAs, these events can vary over time. New RNA spaces can be explored in search of those that create selective advantage for their host.” 15.2.2.2 Heat as Evolutionary Trigger The evolution of thermal responses associated with HSP genes is also likely to involve changes in expression, with structural changes involving HSP alleles and potentially gene duplication. Expression patterns in HSP genes have been linked with adaptation to thermal environments across a range of organisms, including

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insects, fish and bacteria. Variation in the expression of HSP genes might be related to the presence of transposons in promoter regions of the genome, at least in Drosophila species. Alleles of HSP genes in Drosophila melanogaster might vary geographically in frequency and also change in frequency in response to laboratory selection. Duplications in HSP70 vary in copy number within and among species of the Drosophila virilis group, and copy number relates to thermotolerance (Hoffmann and Willi 2008 and references therein).

15.2.3 Role of Epigenetics The mobilization of HSPs is an important component of a universal and tightly orchestrated stress response that has probably allowed organisms to survive otherwise lethal temperatures and other harmful stressors throughout evolution (Rutherford 2003). Recent reports document further roles of some of the constitutively important chaperone families that are expressed at the population level. Genetic or pharmacological manipulation of these chaperones alters the expression of genetic variation in several systems. Therefore, as well as having a vital role in stress physiology, chaperones also provide a plausible molecular mechanism for regulating the capacity of populations and lineages for evolutionary adaptation to changing environments – evolvability that is the ability to produce evolutionary “improvement” or adaptation through the process of random mutation, recombination, and selection. During periods of environmental stress, competition for chaperones by stressdamaged proteins presumably compromises the ability of the chaperones to protect or fold their usual targets, thereby reducing the activities of most target proteins. According to recent studies, the modulation of chaperone and target functions in response to stress would alternately mask and expose phenotypic variation, depending on the degree of stress and the availability of free chaperones. This indicates that chaperones control a reserve of neutral genetic variation which builds up in populations under normal conditions and could be expressed as heritable phenotypic variation during periods of environmental change. Historically, the discussion of regulated evolvability has centered on the regulation of mutation and recombination. The conditions under which the increased generation of variation by mutation is adaptive to populations and lineages under selection were considered in depth with respect to the evolution of “inducible mutators” which increase the mutation rate in response to stress. Many of the same issues apply to the evolution of chaperone-regulated evolvability, although – in contrast to the inducible mutators – chaperones do not alter genotype but rather the expression of genetic variation as phenotypic variation (Queitsch et al. 2002; Rutherford 2003). Morgan et al. (2007) presented an educational cartoon of these processes (Fig. 15.5). Under unstressed “normal” environmental conditions, the misfolded products (U1, Ñ) of basal genetic mutations may be refolded by heat-shock protein 90 (HSP90; U2) so that the proteins have normal activities (U3) and, thus, the mutations have no

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Fig. 15.5  Highly schematized attempt to illustrate the principles of the release of latent or cryptic mutations by stressful conditions experienced during an organism’s early development. ○, normally folded proteins; ●, repaired proteins (From Morgan et al. (2007). With permission from the American Chemical Society)

apparent phenotypic consequences. Under stressful conditions, there is an additional mutation burden above the basal level, yielding new cohorts of misfolded proteins (S1, gray triangle); a finite quantity of HSP90 can only repair a limited proportion of the damaged proteins (S2), such that some of the previously silent basal mutations are revealed in the phenotype through their unbuffered products (S3,∇). The “new” phenotypes are subject to natural selection and may perchance be adaptive under prevailing stressful conditions. Because of buffering, populations may be more genetically variable than trait variation indicates under neutral or favorable environmental conditions. The corollary is that should conditions deteriorate, some individuals may possess previously unsuspected heritable traits that are by chance adaptive, thus promoting rapid microevolutionary response to spatially or temporally abrupt environmental challenges (Rutherford and Lindquist 1998). Morgan et  al. (2007) noticed that they were unaware of any concrete

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examples of this potentially important epigenetic pathway in any population, but the possibility of its existence should be recognized. The report of Manitašević et al. (2007), however, shows that environmental stressors other than geldanamycin have the potential to compromise HSP90 and that compromised HSP90, in turn, increases the phenotypic variation (see Chap. 8). As shown with the Atlantic killifish surviving at the Superfund sites, epigenetic mechanisms play an essential role in general, indicating that this pathway of stress response is essential and deserves high attention. The second major epigenetic pathway, namely the DNA cytosine methylation, has been proposed for several transgenerational phenomena but not ruled out. For instance, a recent study in rats found that treating gestating mothers with the endocrine disrupter vinclozolin resulted in decreased male fertility in the progeny and that this phenotype was heritable for at least four generations (Anway et al. 2005). It is important to note that the study used a synthetic hormone as the environmental agent, and Rando and Verstrepen (2007) wonder what adaptive advantage would be served by inheritance of decreased fertility. This “inducible” transgenerational phenotype is unlikely to have been selected for. As a much more environmentally and evolutionarily realistic example, we have learned that the Atlantic killifish surviving at the Superfund sites “apply” genetic as well as not yet fully discovered epigenetic mechanisms indicating that these pathway of stress-response are essential. Particularly, the epigenetic pathway deserves high attention and one may expect that many more examples remain to be discovered. An overview of empirically detectable stress-induced phenotypic and genetic variations is presented in Table 15.2 that includes releases of hidden variations.

15.2.4 The TATA Box and Evolution The presence of the TATA box (see Box 7.1) is crucial for a rapid and variable response of stress genes in challenged organisms. Changes in external conditions trigger adaptive variation in intracellular regulation, but an excess of unpredictable regulatory variation can interfere with the robustness of cellular functions. The interplay between variability and robustness – that is, between promoting and buffering intracellular changes – is fundamental for evolution. Stress-related genes tend to have more noisy expression characteristics than growth-related genes, and noisy expression is associated with TATA boxes. Noise levels are tuned by evolution to balance fidelity and variation of gene expression. Although too much noise with respect to the regulation of processes such as cell proliferation or development could be detrimental for fitness, variable regulation of environmental responses could actually increase the chance of survival during stress (López-Maury et  al. 2008). Stress-related genes are also more subject to gene duplications and losses than growth-related genes, and duplicated stress-related genes show higher expression divergence than developmental genes as discussed with, for example, pesticide tolerances (Chap. 4).

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Table 15.2  Empirical patterns of the stress-induced phenotypic and genetic variation (Amended from Badyaev (2005). With permission from The Royal Society, London) General phenomenon Specific pattern (organisms) Stress-induced generation Exposure to stress induces directional and locally adaptive of novel genetic variation mutations (e.g., green algae, bacteria, yeast, Daphnia) Increase in evolutionary rate of a gene (cyanobacteria) Increase in frequency of sexual recombination (e.g., Volvox; Saccharomyces; Brachionus; Caenorhabditis elegans; Daphnia; Ostracoda, such as Eucypris virens) Increase in mutation and/or recombination rates (many species, see pesticide resistances) Increase in stress-induced transposition (e.g., plants, Drosophila) Appearance of primitive, ancestor-like forms Stress challenge of general homeostasis releases hidden variation

Phenotypic responses to stress mimic the expression of mutation Phenotypically neutral genetic variance in ancestral forms of domesticated organisms becomes adaptive in the hybrid backgrounds, including domesticated form (e.g., soybeans, maize, sunflowers) and other organisms Environmental dependency and context dependency in expression of genetic variation Complex and redundant developmental systems enable accumulation of mutational variance

Stress challenge of specific buffering mechanisms releases hidden variation

Stress-induced changes in regulation of chaperone proteins releases normally unexpressed genetic variation Release of cryptic genetic variation by artificial selection (Drosophila) Epigenetic regulation of genes uncovers normally unexpressed phenotypic variation (e.g., Arabidopsis, Drosophila, Fundulus heteroclitus)

Between-cell variation in the expression of stress-related genes might be beneficial by enabling populations to sample multiple phenotypes, thus increasing the chance that some cells survive adverse conditions. Variable gene expression that is triggered as an adaptation to stress in turn increases the evolvability of gene expression. Long-term evolution of gene expression changes between species is correlated with short-term regulatory changes to environmental stress: genes that show high environmental responsiveness within one species also tend to show high expression divergence between species. Accordingly, stress-related genes that are associated with TATA boxes show exceptionally rapid regulatory evolution, as shown with worms, flies, plants, and mammals. These findings indicate the possibility that the regulatory characteristics of TATA-box promoters encourage the evolvability of gene expression. In sum, changing environments and stressful conditions keep organisms “on their toes”, and stress not only promotes short-term adaptations but also seems to be a major driving force for evolutionary innovation. In other words, “adversity has the effect of eliciting talents which in prosperous circumstances would have lain dormant” (Horace) (in López-Maury et al. 2008).

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Mean fitness, arbitrary units

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15.2.5 Sex as Stress Response Although in many lineages sex is an obligatory part of the life cycle, in prokaryotes and many lower eukaryotes, sex is facultative. Under non-stressful conditions, these organisms reproduce vegetatively or parthenogenetically and avoid the “twofold cost of sex” (two mature bodies are needed to produce only one new body). More than 100 years ago, Weismann (1904) proposed the idea that sex functions to provide variation for natural selection to precede more effectively. This hypothesis means that high recombination rates increase the mean fitness of individuals and populations and enable them to survive better in fluctuating environments than populations with low recombination rates (Fig. 15.6). The Weismann Effect is expected whenever fitness correlations between loci are negative. Under these circumstances, the net effect of sex is to bring together favorable mutations and separate favorable mutations from harmful mutations, all of which can increase the efficacy of selection. However, this plausible hypothesis long lacked robust empirical support. Recently, Goddard et al. (2005) tested Weismann’s hypothesis on Saccharomyces cerevisiae yeast populations. The authors produced by genetic manipulation strains that differed only in their capacity for sexual reproduction. As predicted sex increases the rate of adaptation to a new harsh environment (such as low glucose content, elevated temperature, elevated osmolarity) but has no measurable effect on fitness in a new benign environment where there is little selection. This indicates that sexual reproduction strongly enhances the probability of a population to survive hostile environments. Yet, the question of how stressors translate into the occurrence of two genders remains unanswered.

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The shift from vegetative or parthenogenetic to sexual reproduction applies also to Cladocera such as Daphnia sp. (Eads et al. 2008), Ostracoda such Eucypris virens (Martins et  al. 2008), Rotatoria such as Brachionus plicatilis (Denekamp et  al. 2009), and even to plants like the ciliated green alga Volvox carteri (Nedelcu and Michod 2003). For instance, female Daphnia typically reproduce asexually, but unfavorable environments induce parthenogenetic production of males (genetically identical to their mothers) and haploid gametes that are fertilized and enter a state of extended metabolic dormancy called diapause. These unfavorable conditions are predation, parasitism, food availability and quality, and temperature. To these stressors, Daphnia responds immediately by common stress reactions such as activation of oxygen and increased production of stress proteins (see Chaps. 2 and 5). Furthermore, it starts to be understood that juvenile hormone pathways are central in male production but the regulatory pathway from environmental stress signals to the production of hormones or their analogs remains obscure (Eads et al. 2008). The monogonont rotifer Brachionus plicatilis can be found in water bodies where environmental factors restrict population growth to short periods. The adverse conditions for growth include evaporation of water in temporary habitats leading to high salinity and desiccation, unfavorable temperatures, lack of food, or appearance of predators. In this hostile environment, the survival of the population is ensured via the production of resting eggs. Resting eggs are produced after mictic (sexually reproducing) females are fertilized by males thus switching from an asexual type of reproduction to sexual reproduction. In the resting eggs, LEA proteins, small HSPs, and some antioxidant genes are up-regulated (Denekamp et al. 2009). In this case, too, the signaling pathway from the environmental trigger over male occurrence and resting egg production suffers from several gaps in evidence. This gap is filled by studies on the ciliated multicellular alga V. carteri. From Chap. 2, we understand that (almost) all forms of stress elevate the cellular ROS level with the potential of DNA damage. In a series of papers, Nedelcu and Michod (2003), Nedelcu et al. (2004), and Nedelcu (2005) addressed the hypothesis that the mechanistic connection between stress and sex in facultatively sexual lineages involves ROS and reflects the ancestral role of sex as an adaptive response to the DNA-damaging effects of stress-induced ROS. Furthermore, they assume that sex is the preferred way to create a stress-resistant spore – as opposed to an asexual haploid spore. Nedelcu and Michod (2003) used antioxidants such as catalase (which dismutates H2O2 into H2O and O2, see Chap. 2) and heat-shocked V. carteri cultures in the absence or presence of catalase. If sexual induction in V. carteri is mediated by ROS, agents that remove ROS should diminish the sexual response. Consistent with this prediction, catalase reduced (by up to 100%) the sexual progeny. Furthermore, the sex-inducing heat shock in V. carteri increased the production of H2O2 in somatic cells (Nedelcu et al. 2004). Genes involved in sexual induction are evolutionarily related to genes associated with various stress responses (Nedelcu 2005). Overall, the results of the V. carteri studies show that sex, cell-cycle arrest, and apoptosis are alternative responses at least in this algal species to increased levels of stress with the alternative being death or sex. What an option!

Appendices

Appendix 1: Cytochrome P450 Enzyme Families The various families are not differentiated by their function, but by their amino acid identity; e.g. members of CYP families share >40% amino acid identity, while members of subfamilies must share >55% amino acid identity. An overview of the families and their function is given in Table A.1 below.

Appendix 2: Classification of Glutathione Transferases Glutathione transferases are divided into at least four major families of proteins, namely cytosolic GSTs, mitochondrial GSTs, microsomal GSTs, and bacterial fosfomycin-resistance proteins. The cytosolic GSTs have been sub-grouped into numerous divergent classes on the basis of their chemical, physical and structural properties. The mitochondrial GSTs, also known as kappa-class GSTs, are soluble enzymes that have been characterized in eukaryotes. The third GST family comprises membrane-bound transferases called membrane-associated proteins involved in ecosanoid and glutathione metabolism (MAPEG), but these bear no similarity to soluble GSTs. Representatives of all three families are also present in prokaryotes. The fourth family is found exclusively in bacteria (Allocati et al. 2009). The classification follows Sheehan et al. (2001), Hayes et al. (2005), Ranson and Hemingway (2005).

Cytosolic GSTs Members of the GST superfamily are classified on the basis of sequence similarities. Seven classes of cytosolic GSTs are recognized in mammalian species, designated alpha, mu, pi, sigma, theta, omega, and zeta. Many of these classes are in C.E.W. Steinberg, Stress Ecology: Environmental Stress as Ecological Driving Force and Key Player in Evolution, DOI 10.1007/978-94-007-2072-5, © Springer Science+Business Media B.V. 2012

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Table A.1  General overview of CYP families/subfamilies and enzyme functions in various species (Nelson et al. 1996; Werck-Reichhart et al. 2002; Hewitt et al. 2007) CYP1 CYP2 CYP3 CYP4 CYP5 CYP6 CYP7A CYP7B CYP8 CYP9 CYP10 CYP11 CYP12 CYP13 CYP14 CYP15 CYP16 CYP17 CYP18 CYP19 CYP21 CYP23 CYP24 CYP25 CYP26 CYP27 CYP28 CYP29, 31-37 CYP38 CYP39 CYP42-44 CYP45 CYP46 CYP47-49 CYP51 CYP52 CYP53-69

Vertebrates; dioxin-inducible; metabolism of polycyclic hydrocarbons, halogenated and heterocyclic hydrocarbons, and aromatic amines Vertebrates and invertebrates; metabolism of drugs and environmental chemicals Vertebrates and invertebrates; metabolism of drugs and environmental chemicals Vertebrates, fatty acid hydroxylases; invertebrates (lobster, sea urchin, polychaetes), xenobiotica metabolism, unknown function(s) Vertebrates; thromboxane synthase Insects; metabolism of plant secondary products and pesticides Vertebrates; cholesterol 7a-hydroxylase Vertebrates; unknown function(s) Vertebrates; prostacyclin synthase Insects pesticide metabolism Mollusks (mitochondrial enzyme) Vertebrates; cholesterol side-chain cleavage, steroid 11 b-hydroxylase, and aldosterone synthase (mitochondrial enzyme) Insects (mitochondrial enzyme) Nematodes Nematodes Insects Nematodes Vertebrates; steroid 17 a-hydroxylase Insects Vertebrates; aromatization of androgens Vertebrates; steroid 21-hydroxylase Nematodes Vertebrates; steroid 24-hydroxylase (mitochondrial enzyme) Nematodes Vertebrates Vertebrates; steroid 27-hydroxylase (mitochondrial enzyme) Insects, xenobiotica metabolims Nematodes, (clams, polychaetes, insects); fatty acid metabolism; xenobiotica metabolims Sponge Vertebrates Nematodes, polychaetes Lobster Vertebrates Insects Animals, filamentous fungi, yeast and plants, parasitic protozoa and bacteria; sterol biosynthesis Yeast; alkane hydroxylases Fungi; biosynthesis (continued)

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Table. A.1  (continued) CYP71 CYP72-94 CYP72 CYP73 CYP74 CYP75 CYP79 CYP81 CYP83 CYP84 CYP85 CYP86 CYP88 CYP90 CYP93 CYP97 CYP98 CYP101-133 CYP501-507 CYP701 CYP702-726

Plants, largest family, function mainly obscure; flavonoid and other secondary compound metabolism, such as furanocoumarins Plants, function often unknown; flavonoid and glycosinolate biosynthesis Plants, herbicide metabolism Plants, cinnamic acid hydroxylase Plants, fatty acid metabolism Plants, flavonoid biosynthesis Plants, linamarin and lotaustralin biosynthesis Plants, isoflavone metabolism Plants, glycosinolate biosynthesis Plants, lignin biosynthesis Plants, biosynthesis of phytohormones, brassinosteroids Plants, fatty acid metabolism Plants, gibberellin hormone biosynthesis Plants, fungi, mammals; sterol biosynthesis Plants, isoflavone metabolism Plants, diverse algae Plants, chlorogenic acid biosynthesis Archaea, bacteria, cyanobacteria Lower eukaryotes, (pathogenic) fungi, yeast Plants, gibberellin hormone biosynthesis Plants, function unknown

non-mammalian species as well. Other classes of cytosolic GSTs, namely beta, chi, delta, epsilon, lambda, phi, rho, tau, and the “u” class, have been identified in non-mammalian species. MAPEG Enzymes These members of the GST superfamily constitute a unique branch where most of the proteins are mainly involved in the production of eicosanoids. Throughout nature, a total of four MAPEG subgroups have been described. The founding member of the MAPEG family, MGST1, appears to function solely as a detoxication enzyme. Microsomal GSTs The microsomal GST class is evolutionarily and structurally distinct from the cytosolic class but catalyzes a similar range of reactions.

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Non-mammalian GSTs In non-mammalian species, several new classes have been discovered in addition to the above mentioned mammalian GSTs. Orthologs of these new classes of genes and proteins were later often found to be present also in mammals, in some cases carrying out functions not ascribed previously to GSTs. Beta Class These GSTs have been described in a wide variety of bacteria, including Escherichia, Proteus, Pseudomonas, Klebsiella, Enterobacter, Serratia, Burkholderia, and Rhodococcus species (Sheehan et  al. 2001). They play a role in antibiotic resistance. Delta Class Major class of insect GSTs, especially in larval stages. The independent expansion of the delta class in different families of insects suggests that they are involved in adapting insects to their particular ecological niches and are perhaps particularly important in the detoxification of environmental xenobiotics; elevated levels of delta-class GSTs have been implicated in resistance to all the major classes of insecticides. Epsilon Class The Epsilon class is also a large, insect-specific class. Members of this class are implicated in the detoxification of and resistance to insecticides. Omega Class The omega GST class was first identified in humans, but members of this class also occur in nematodes, helminthes, and insects. The physiological function of omega GSTs is unclear; they may play a housekeeping role in protecting against oxidative stress. Rho Class Described only from teleost fish GST with, so far, no homologs in mammals (Konishi et al. 2005). This class plays an important role in reducing the harmful effects of exposure to natural xenobiotics (see cyanotoxin resistance in certain fish species).

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Sigma Class In helminthes, sigma-class enzymes are related to prostaglandin synthesis. Prostaglandins are C20-compound which mediate a variety of strong physiological effects. Sigma-class enzymes were first found in squid digestive glands. In insects, these proteins are found predominantly in the indirect flight muscles, which might indicate defense against oxidative stress.

Theta Class This class is found in a diverse range of organisms and were originally postulated to be the progenitor of all GST classes.

Zeta Class This class is present in a spectrum of species ranging from plants to humans. zetaclass GST is identical with maleylacetate isomerase, an enzyme of the catabolic pathway for tyrosine. Their sequence is highly conserved, suggesting an essential housekeeping role.

Fungal GSTs By comparison with other major groups, such as mammals, plants and insects, relatively little is known about GSTs from fungi. It is clear that these enzymes are expressed widely in a large number of fungal species, although not in Saccharomyces cerevisiae. As with mammals, plants and insects, the enzymes are expressed in multiple forms which appear to be inducible by xenobiotics.

Plant GSTs – Phi and Tau Classes Two GST classes are plant-specific: phi (previously Type I) and tau (previously Type III) classes. GSTs play many roles in plants, having been implicated in herbicide resistance, being inducible by pathogens and/or dehydration, showing direct binding of auxins and catalyzing the formation of anthocyanins. Moreover, they appear to be important in both higher and lower plant species. Unlike animals, plants appear to have made the transition from water to land only once and to have evolved the entire multicellular diploid phase of their life cycle on land. GSTs from several classes are expressed in most plant species by multiple genes for GSTs.

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SG NO2

NO2 + H+ + Cl-

NO2

GSH

NO2

Fig. A.1  Conjugation of the substrate 1-chloro-2,4-dinitrobenzene by many cytosolic GSTs of both bacteria and eukaryotes. This reaction also serves as classic analysis for the activity of GSTs

Insect GSTs – Classes I and II The classification system for insect GSTs recognized two immunologically distinct classes designated I and II, whereby former classes I GSTs are similar to the delta and class II GSTs to the omega/zeta/sigma/theta classes. Helminth GSTs Helminth organisms are prominent parasites affecting human and animal health. These organisms are unusual in that they have generally low levels of phase I and other detoxification enzyme activities, but express GSTs, especially in response to drug treatment. Helminth GSTs belong to the sigma and other classes. Bacterial GSTs GSTs have been found to be broadly distributed in aerobic prokaryotes, but to date not in anaerobic bacteria or in Archaea. Four different classes of cytosolic GSTs have been identified: beta, chi, theta, and zeta. beta GSTs are able to conjugate the model substrate 1-chloro-2,4-dinitrobenzene (CDNB) (Fig. A.1). Theta class enzymes in bacteria are represented by two dichloromethane dehalogenases produced by facultative methylotrophic bacteria. The zeta-class GST comprises also dehalogenases. Recently a novel class of cytosolic GSTs, called chi class, was proposed: Two cyanobacterial GSTs have been purified and characterized from Thermosynechococcus elongatus and Synechococcus elongatus. Also MAPEG members were identified in several bacteria; however, to date no information about their physiological role is available (Allocati et al. 2009). Bacterial GSTs have an active role in protecting against oxidative stress and are involved in the detoxification of antimicrobial agents. This stress defense is facilitated particularly by the beta-class GSTs. Some GSTs are implicated in the basal metabolism and supply bacterial cells with carbon sources. Bacterial GSTs are also involved in the metabolism of several monocyclic aromatic compounds such as toluene, xylenes, phenols, and atrazine. They also take part in the metabolism of polycyclic aromatic hydrocarbons. Microbial dehalogenases play a key role in

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OH

OH

Cl

Cl

Cl

Cl OH

HCl

2 GSH

GSSG

OH

Cl

Cl

Cl

H OH

HCl

2 GSH

GSSG

Cl

Cl

H

H OH

Fig. A.2  Reductive dehalogenation of tetrachlorohydroquinone to trichlorohydroquinone and from trichlorohydroquinone to 2,6-dichlorohydroquinone (After Allocati et al. 2009)

the biometabolism of several chlorinated xenobiotics, both aliphatic and aromatic. Bacterial GSTs catalyze different reactions using GSH as a cofactor, i.e. DCM dehalogenases catalyze the hydrolytic dechlorination of dichloromethane, whereas TCHQ dehalogenase catalyzes a reductive dehalogenation (Fig. A.2) (Allocati et al. 2009). Of outstanding ecological significance is the capability of a bacterial lignin degrading GST enzyme (Masai et al. 1993). This fundamental step for the earth’s carbon cycle, has been described for, e.g., Sphingomonas paucimobilis. It is most likely that enzymes of the bacterial GST family are also involved in the metabolism of humic substances, another huge organic global carbon pool, as proposed by Steinberg (2003).

Appendix 3: Transporters Despite a not yet unified nomenclature, we summarize: ABC transporters utilize the energy of ATP hydrolysis to transport various substrates across cellular membranes. They are divided into three main functional categories. In prokaryotes, importers mediate the uptake of inorganic and organic nutrients into the cell. The membranespanning region of the ABC transporter protects hydrophilic substrates from the lipids of the membrane bilayer thus providing a pathway across the cell membrane. It is assumed that eukaryotes do not possess any importers. Exporters or effluxers, which are both present in prokaryotes and eukaryotes, function as pumps that extrude toxins and drugs out of the cell. In gram-negative bacteria, exporters transport lipids and some polysaccharides from the cytoplasm to the periplasm. The third subgroup of ABC proteins does not function as transporters, but is involved in translation and DNA repair processes instead.

The P-gp (ABCB) Family Pgp, also called MDR1 or ABCB1, is the prototype of ABC transporters. Pgp is known to transport organic cationic or neutral compounds. Much research has focused on understanding the seeming promiscuity of these transporters, indicating common characteristics among substrates, such as moderate hydrophobicity, small

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size, and positively charged domains. A downside to this multispecificity, which Pgp shares with some of the other efflux transporter families, is that the proper function of the system is vulnerable to the presence of multiple substrates that compete for substrate binding sites. They can be blocked by so-called chemosensitizers (see main text, Chapter 4.6.1). A surprising outcome of the Arabidopsis genome project was the annotation of a large number of sequences encoding member of the ABC transporter superfamily, including 22 genes encoding ABCB subfamily. As mammalian ABCB orthologs are associated with multiple drug resistance, plant ABCBs were initially presumed to function in detoxification, but were soon seen to have a clear developmental role; they mediate the cellular and long-distance transport of phytohormone auxin (Geisler and Murphy 2006). Some of these transporters are of particular interest because they appear to function as importers, a property that has yet to be demonstrated for any other eukaryotic plasma membrane ABC transporter (Verrier et al. 2008).

The MRP (ABCC) Family Some members of this family also contribute to multidrug efflux by acting like P-gp to efflux unmodified xenobiotics. However, members of this family also act on endogenous substrates that are normal products of metabolism, or – and this is an important difference – they work on toxicants that have entered the cell and are modified as a part of the abovementioned phase I and phase II detoxification. The resulting conjugated and negatively charged molecules are recognized by various ABCC transporters and then exported from the cell. In plants, MRPs seem to be the major exporters of xenobiotic conjugates or endogenous and exogenous toxins. Recently, in Arabidopsis and in the mycorrhizal fungus Glomus intraradices, MRPs were found to facilitate also heavy metal detoxification.

The MXR (ABCG) Family, Also Called White-Brown Complex Homologs (WBCs) The most-studied member in this family is ABCG2 commonly referred to as BCRP, also causes significant resistance to a limited group of chemotherapeutic treatments (substrate specificity is less broad than for ABCB and ABCC) as well as effluxing dietary toxicants. A difference from the aforementioned transporter types, which are so-called full transporters (the gene product constitutes one structural unit), is that ABCG2 is a half transporter, in which two protein molecules are assembled to form a structural unit active as a homodimer (Epel et al. 2008). This family is markedly expanded in plants, with more than 40 members in both Arabidopsis and rice and found to be required for cuticular lipid export (Verrier et al. 2008). Overexpression of members of this family improves drought and salt stress resistance in Arabidopsis (Kim et al. 2010a).

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Transporter Proteins in Plants The very numerous plant ABC proteins can be assigned to 13 subfamilies particularly on the basis of protein size (full, half, or quarter molecule). Compared to the less numerous animal ABC proteins, still only little is known about the function of ABC proteins in plants and several surprising future outcomes may be encountered. Nevertheless, many plant transporters are involved in handling environmental challenges. According to current knowledge, mainly multidrug resistance-associated protein homologs (MRPs) take part in response to chemical stress situations; they transport glutathione-conjugates or endogenous and exogenous toxins, or sterol glucuronids. Recently, in Arabidopsis (Bovet et al. 2005; Gaillard et al. 2008) and in the mycorrhizal fungus Glomus intraradices, MRPs facilitate also heavy-metal detoxification (González-Guerrero et al. 2010). Another group with even more members are the multidrug resistance homologs (MDRs) mainly involved in transport natural and synthetic auxins and alkaloids. In metal detoxification, ATP-binding cassette transporter of the mitochondrion homologs (ATMs) play a central role, whereas pleiotropic drug resistance homologs (PDRs) appear to be central in defense against pathogens. Emerging evidence assigns PDRs also a role in metal detoxification (Kim et al. 2007). Recently, also the role of white-brown complex homologs (WBCs) in xenobiotic metabolism and detoxification and formation of arbuscular mycorrhizal symbiosis was identified (Rea 2007; Q Zhang et al. 2010). Also only recently, members of this family were found to increase drought and salt stress resistance (Kim et al. 2010a). For heavy-metal resistance in hyperaccumulators, several specific transporters are involved and described in Chap. 6: The major groups are zinc-regulated transporter (ZRT), iron-regulated transporter proteins (IRT) (ZRT, IRT- like proteins = ZIP), cation diffusion facilitators (CDF), heavy-metal ATPases (HMA), and natural resistance associated macrophage protein (NRAMP) transporter families as well as FRD3, a ligand transporter. The following paragraphs present some examples of stress response and basic ecophysiology in which ABC transporters are involved and the reader will find that the functional overlap of the different ABC transporter classes is greater than the classification may indicate, and it is highly likely that more functions for members of this family await discovery. Multidrug Resistance Homologs (MDRs): Central in Auxin Transport The MDRs (alias P-glycoprotein homologs, PGPs), with a membership of 22 in Arabidopsis and 24 in rice, represent the second largest ABC protein subfamily and the largest full-molecule ABC transporter subfamily in plants. They were first identified in mammalian cells because their over-expression confers a multidrug resistance phenotype. The two most studied plant MDRs are the founding member of the Arabidopsis subfamily, AtPGP1 (alias AtMDR1), and AtMDR1 (alias AtMDR11 or AtPGP19).

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Both AtPGP1 and AtMDR1 are clearly implicated in auxin transport. When MDRs were first identified in plants it was thought that they would prove to participate in processes analogous to those in which their mammalian counterparts participate. One example of the importance of the ABC transporter in auxin transport has recently been published by Mathiason et al. (2009) who studied the gene expression profiles in grapevine buds which had fulfilled chilling requirement. Endodormant buds require a period of chilling before they break and begin to grow. Four genes encoding an ABC transporter family protein were found to be down-regulated during the chilling requirement fulfillment period in grape buds; the decrease in ABC transporter gene expression corresponds to the fact that plant tissues and organs are at rest (not growing) during the chilling requirement fulfillment period. The knock-out of the transporter genes leads to dwarfism as shown with Arabidopsis mutants (Geisler et al. 2005). Multidrug Resistance-Associated Protein Homologs (MRPs): Xenobiotic-Conjugate Transporters The second most highly represented subfamily of full-molecule ABC transporters is the MRPs with 16 genes in Arabidopsis and 17 in rice. Many early studies of MRPtype transport processes in plants focused on the uptake of model GSH conjugates of, for instance, pesticides. It is very likely that many plant MRPs are crucial for the vacuolar sequestration (“excretion storage”) of both endogenous compounds and xenobiotics that are susceptible to conjugation with GSH and/or other adducts (Rea 2007). It appears that transporters of the MRP family are also involved in detoxification of certain, but not all metals (González-Guerrero et al. 2010). One illustrative example of the action of MRPs has recently been published by Schröder et al. (2007). Numerous herbicides and xenobiotic organic pollutants are detoxified in plants to glutathione conjugates. Following this enzyme catalyzed reaction, xenobiotic GS-conjugates are thought to be compartmentalized in the vacuole of plant cells. In their study, Schröder et  al. (2007) presented evidence from experiments with roots of barley that part of these conjugates underwent long range transport in plants to the tips of the roots, rather than be stored in the vacuole. This means that plants possess an excretion system for unwanted compounds giving them similar advantages as animals. MRPs are Even More Protective: Arabidopsis Beside the glutathione conjugate transport activity, a member of this class, AtMRP6, has been found essentially expressed during early seedling development and, furthermore, inducible by Cd and oxidative stress. The position of AtMRP6, namely between two other MRP genes (all of which being induced by Cd) suggest that AtMRP6 is part of a cluster involved in metal tolerance (Gaillard et al. 2008).

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MRPs Are Even More Protective: Fungi Since recently, it is understood that upon exposure of the arbuscular mycorrhizal fungus Glomus intraradices to high concentrations of either Cu, Zn, or Cd, the cytoplasmic concentrations of heavy metals were kept low, whereas vacuoles had the highest intracellular concentrations of heavy metals. Accumulation of heavy metals in the arbuscular mycorrhizal fungal vacuoles implies the presence of a number of heavy-metal transporters involved in loading these organelles. GonzálezGuerrero et  al. (2010) reported on the expression of GintABC1, the first ABC transporter gene described in arbuscular mycorrhizal fungi. GintABC1 presents an expression pattern consistent with a role in Cu, Cd, and oxidative stress protection. GintABC1 was up-regulated by Cd and Cu, but not by Zn, suggesting that this transporter might be involved in Cu and Cd detoxification. Paraquat, an oxidative agent, also induced the transcription of GintABC1. Obviously, redox changes are involved in the transcriptional regulation of GintABC1 by Cd and Cu. Pleiotropic Drug Resistance Homologs (PDRs) The third subfamily of full-molecule ABC transporters, the PDRs, is encoded by over 15 open reading frames in Arabidopsis and 23 in rice. Yeast PDR5 is the prototype of this family. Considered to be a functional equivalent of the mammalian MDRs, yeast PDR5 is a plasma membrane-localized protein competent in the extrusion of a broad range of anticancer drugs, cyclic peptides, and steroids. The participation of PDR-type ABC transporters in plant-pathogen interactions has been a subtext in most considerations of these proteins. Several are induced by some of the elicitors produced by pathogens and a few contribute to the transport of antifungal compounds. PDRs may also contribute to the transport of signaling molecules or secretion of volatile fragrances. For example, the existence of compounds like WAF-1, a sclareol-like labdane diterpene that accumulates in the intercellular space of wounded tobacco leaves and functions as a signal for activation of the expression of wound- and pathogen-elicited defense-related genes, is at least consistent with a scheme of this type (Rea 2007). Recently, Hlaváček et al. (2009) showed that PDR exporters not only play essential roles in cell resistance to various toxic compound, but also influence the developmental phases and physiology of yeast populations growing in liquids. Hence, PDRs appear to be involved in population quorum sensing, which consequently influences one specific transcription factor level via feedback regulation. Obviously, the potency of PDRs is not yet exhausted by the above sketched functions, because Kim et al. (2007) reported on the involvement of the AtPDR8 transporter in heavy metal (Cd) extrusion. So far, only AtMRP3 and AtATM3 have been suggested to transport Cd2+ among plant ABC transporters and facilitate heavy-metal resistance. In their study, Kim et al. showed that also AtPDR8 acted as an efflux pump of Cd2+ or Cd conjugates at the plasma membrane of Arabidopsis cells. AtPDR8, but not AtPDR7, exhibited a clear dose response. As AtPDR8 has

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been suggested to be involved in the pathogen response and in the transport of chemicals that mediate pathogen resistance, this ABC protein is likely to transport a broad range of substrates. Even more recently, Cao et  al. (2010) reported that the AtPDR12 exporter is required for a cross-tolerance. They showed that cold pretreatment enhanced Pb(II) resistance in Arabidopsis, as indicated by lower reduction of root length, fresh weight, and chlorophyll content in the cold-treated plants than the control ones. This was associated with the activation of the expression of AtPDR12 gene, a pump excluding Pb(II) and/or Pb(II)-containing toxic compounds from the cytoplasm to the exterior of the cell. This finding was further supported by genetic evidence showing that cold treatment was unable to enhance resistance of atpdr12 mutant to Pb(II) stress but could enhance Pb(II) resistance of the wild type. White-Brown Complex Homologs (WBCs): Versatile Defense Function Against Pathogens, Xenobiotics, and More With 29 half-molecule transporters in Arabidopsis and 30 in rice, the plant WBC subfamily is many times larger than its equivalents in nonplant eukaryotes with the exception of Drosophila, whose genome contains 15 WBC (alias ABCG) genes. Two half-molecule transporters are assembled to form an active structural unit. WBCs are versatile with respect to their function. A basic function has been shown by Zhang et al. (2010). The majority of the vascular flowering plants, including most crop species of agronomic significance, are able to develop symbiotic associations with arbuscular mycorrhizal fungi. The symbiosis develops in the roots where the arbuscular mycorrhizal fungi deliver phosphate and nitrogen to the root cortex and in return obtain carbon from the plant. To form arbuscular mycorrhizal symbiosis, the two symbionts undergo a series of coordinated, developmental transitions that enable the fungus to enter the root cortex and establish highly branched hyphae called arbuscules in the root cells. Development of the symbiosis is regulated at least in part by the plant, and the initial stages of the symbiosis are controlled by a symbiosis signaling pathway. To identify genes involved in arbuscule formation, Zhang et  al. (2010) undertook a genetic screen for mutant impaired in arbuscule development. This screen led to the identification of a mutant, stunted arbuscule (str), in which arbuscule development is initiated but subsequently arrests and arbuscular mycorrhizal symbiosis fails. Furthermore, ancient and highly conserved pair of ABC transporters of the WBC subfamily were essential for arbuscular mycorrhizal symbiosis. A major task of the WBCs is defense against pathogens. For instance, Albrecht and Bowman (2008) studied gene expression in Citrus sinensis following infection with a fastidious, phloem-inhabiting bacterium of the genus Candidatus Liberibacter. Gene expression changes involved a variety of different processes including cell defense, transport, cellular organization, photosynthesis, and carbohydrate metabolism. Notable was the high up-regulation after 13–17 weeks after inoculation of genes encoding ABC transporter family proteins, which are involved in the membrane

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transport of endogenous secondary metabolites. The ABC transporter belonged not only to WBCs, but also to MRPs. WBCs are involved even in handling of xenobiotica. For instance, in their quest for plant genes that might contribute to detoxification of the explosive TNT, Mentewab et al. (2005) identified some genes encoding WBCs that were up-regulated when Arabidopsis seedlings were grown on media containing this compound. In addition, exposure to the two other explosives up-regulated this gene, yet, to a lesser degree. Very recently, Kim et al. (2010a) twice showed that the over-expression of one member of this family (AtABCG36) improves drought and salt stress resistance in Arabidopsis. When grown on soil in green house longer than 5 weeks, transgenic Arabidopsis plants that over-express an ATP-binding cassette (ABC) transporter, AtABCG36/AtPDR8, produced higher shoot biomass and less chlorotic leaves than the wild-type. Kim et al. (2010) found that AtABCG36-over-expressing plants were more resistant to drought and salt stress and grew to higher shoot fresh weight than the wild-type by a mechanism that includes reduction of sodium content in plants. ATP-Binding Cassette Transporter of the Mitochondrion Homologs (ATMs): Heavy Metal Transporter ATMs belong to the half-molecule ABC transporter. The Arabidopsis ATM subfamily comprise AtATM1, AtATM2, and AtATM3. A facet of plant ATMs is their activation by heavy metals. Although AtATM1 appears to be expressed constitutively, AtATM3 expression is induced by exposure to heavy metals such as Cd. AtATM3 is not unique among the ATMs in this regard because another member of this subfamily from the unicellular green alga Chlamydomonas reinhardtii also contributes to Cd tolerance: mutation of this gene, designated CrCDS1, leads to Cd-hypersensitivity (Hanikenne et al. 2005).

sdfsdf

Abbreviations and Glossary

ABA  abscisic acid, signaling intermediate that controls the expression of many, but not all, genes responding to environmental stress and plant pathogens ABC transporters  ATP-binding cassette transporters; transmembrane proteins that function in the transport of a wide variety of substrates and conjugates across extra- and intracellular membranes allelopathy  chemical inhibition of one (plant) species by another allelochemicals  low molecular weight phyto-inhibitory compounds produced by plants alternative splicing  or differential splicing, process by which the exons of the RNA produced by transcription of a gene (a primary gene transcript or pre-mRNA) are reconnected in multiple ways during RNA splicing. The resulting different mRNAs may be translated into different protein isoforms; thus, a single gene may code for multiple proteins apoplast  free diffusional space outside the plasma membrane in a plant apoptosis  main type of programmed cell death in multicellular organisms aquaporins  proteins embedded in the cell membrane that regulate the flow of water arachidonic acid  polyunsaturated omega-6 fatty acid 20:4(w-6) arbuscular mycorrhizal symbiosis  type of mycorrhiza in which the fungus penetrates the cortical cells of the roots of a vascular plant calreticulin  calcium-binding protein canalization  ability of a genotype to produce the same phenotype regardless of variability of its environment capacitor  phenotypic capacitors are biological switches that hide and reveal heritable phenotypic variation. Evolutionary capacitors are the subset of phenotypic capacitors that can promote adaptation cDNA  a single-stranded DNA complementary to an RNA, synthesized from it by in vitro reverse transcription chaperones  class of proteins that assist in the correct folding or assembly of other proteins in vivo C.E.W. Steinberg, Stress Ecology: Environmental Stress as Ecological Driving Force and Key Player in Evolution, DOI 10.1007/978-94-007-2072-5, © Springer Science+Business Media B.V. 2012

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Abbreviations and Glossary

chaperonins  CPNs, class of molecular chaperones, restricted to bacteria, mitochondria, and chloroplasts cross-talk  signal components in signal transduction can be shared between different signal pathways and responses to a signal inducing condition (e.g., stress) can activate multiple responses in the cell/the organism cross-tolerance  increased tolerance of one stress after preconditioning by another cuticle or cuticula  a multi-layered structure outside the epidermis of many invertebrates, notably roundworms and arthropods, in which it forms an exoskeleton cytokinins  phytohormones promoting cell division dehydrins  lant proteins produced in response to cold and drought stress DNA array  collection of DNA spots, commonly representing single genes, arrayed on a solid surface by covalent attachment to a chemical matrix, qualitative or quantitative measurements utilize the selective nature of nucleic acid hybridization under high-stringency conditions and fluorophore-based detection. Ecdysis  molting of the cuticula in arthropods and related groups ectopic outgrow  expression of a gene in an abnormal place in an organism eicosanoids  signaling molecules made by oxidation of 20-carbon essential fatty acids, (EFAs). They exert complex control over many bodily systems elongase  enzyme involved in elongating fatty acids endoplasmic reticulum  ER, eukaryotic organelle that forms an interconnected network of tubules, vesicles, and cisternae within cells. Rough endoplasmic reticula synthesize proteins, while smooth endoplasmic reticula synthesize lipids and steroids, metabolize carbohydrates and steroids, and regulate calcium concentration, drug detoxification, and attachment of receptors on cell membrane proteins epigenome  the overall epigenetic state of a cell eukaryotes  organisms whose cells are organized into complex structures by internal membranes: animals, plants, fungi, and protists GO  Gene Ontology, major bioinformatics initiative to unify the representation of gene and gene product attributes across all species GSH  reduced glutathione GSSG  glutathione disulfide = oxidized glutathione heterologous expression  of a protein: a protein is experimentally put into a cell. Heterologous expression is a tool to find out whether a particular gene produces mRNA and/or protein and whether the protein produced is functional histone  strongly alkaline proteins found in eukaryotic cell nuclei, which package and order the DNA into structural units called nucleosomes homeostasis  property of a living organism, that regulates its internal environment so as to maintain a stable, constant condition HSP  heat-shock protein: a group of conserved proteins which are upregulated during stress responses IGF I and II  insulin-like growth factors I and II IGFbp  insulin-like growth factor-binding protein which binds both IGFs and circulates in the plasma; binding of this protein prolongs the half-life of the IGFs

Abbreviations and Glossary

403

iNOS  inducible nitric oxide synthase pathway; one of two major antimicrobial systems in phagocytic cells JA  jasmonic acid, a phytohormone regulating plant growth including growth inhibition, senescence, and leaf abscission. JA has an important role in response to wounding of plants and systemic acquired resistance. When insects attack plants, they respond by releasing JA, which inhibits the insects’ ability to digest protein LEA proteins  late embryogenesis abundant proteins; proteins in animals and plants that protect other proteins from aggregation from desiccation or osmotic stresses MAPK  mitogen-activated protein kinase that responds to extracellular stimuli (mitogens, osmotic stress, heat shock, and proinflammatory cytokines) and regulates various cellular activities, such as gene expression, mitosis, differentiation, proliferation, and cell survival/apoptosis methemoglobinemia  higher than normal level of methemoglobin in the blood. Methemoglobin is a form of hemoglobin that does not bind oxygen microRNAs  miRNAs, abundant class of newly identified endogenous non-protein coding small RNAs with 20–25 nucleotide length mitogen  chemical substance that encourages a cell to commence cell division, triggering mitosis multiple stress tolerance  see cross-tolerance necrosis  accidental death of cells and living tissue; in contrast to apoptosis, does not send cell signals which tell nearby phagocytes to engulf the dying cell necrotrophic  form of nutrition in which a parasitic symbionts damages or kills the organism where it resides PAHs  polycyclic aromatic hydrocarbons p53  gene encoding protein 53, TP53, is a transcription factor that regulates cell cycle and functions as tumor suppressor PAR  photosynthetically active radiation, usually from 400 to 700 nm PCBs  polychlorinated biphenyls phenoloxidase  enzymes that oxidize phenolic compounds to quinines posttranslational modification  modification of a protein after its translation. It is one of the later steps in protein biosynthesis for many proteins protein carbonylation  appearance of carbonyl groups (aldehyde or ketone) in proteins as the result of oxidative modification reactions; standard marker for oxidative stress prokaryotes  group of organisms that lack a cell nucleus (=karyon), or any other membrane-bound organelles prophenoloxidase  melanin-synthesizing enzyme, important arthropod immune protein proteasome  large protein complexes inside all eukaryotes, archaea, and some bacteria with the main function to degrade unneeded or damaged proteins by proteolysis protein kinase  kinase enzyme that modifies other proteins by chemically adding phosphate groups to them (phosphorylation).

404

Abbreviations and Glossary

regulon  genes that share a similar expression profile across multiple spatial, temporal, environmental and genetic conditions are likely to be under common transcriptional regulations RNAi  RNA interference: system within living cells that helps to control which genes are active and how active they are R-proteins  plant disease resistance ® proteins recognize matching pathogen avirulence proteins ruderal species  plant species that is first to colonize disturbed lands. The disturbance may be natural (e.g., wildfires or avalanches), or due to human influence – constructional (e.g., road construction, building construction or mining), or agricultural (e.g., abandoned farming fields or abandoned irrigation ditches) SA  salicylic acid, a phytohormone with roles in plant growth and development, photosynthesis, transpiration, ion uptake and transport. SA also induces specific changes in leaf anatomy and chloroplast structure. SA is involved in endogenous signaling, mediating in plant defense against pathogens SAR  systemic acquired resistance, a whole-plant resistance response that occurs following an earlier localized exposure to a pathogen sigma factors  bacterial proteins that help control gene expression stress hardening  increased tolerance of a stress after preconditioning at low doses of that stress SUMO proteins  Small Ubiquitin-like Modifier or SUMO proteins are a family of small proteins that are covalently attached to and detached from other proteins in cells to modify their function. SUMOylation  post-translational modification involved in various cellular processes, such as nuclear-cytosolic transport, transcriptional regulation, apoptosis, protein stability, response to stress, and progression through the cell cycle. SUMOylation is directed by an enzymatic cascade analogous to that involved in ubiquitination. In contrast to ubiquitin, SUMO is not used to tag proteins for degradation symplast  inner side of the plasma membrane of plant cell in which water (and lowmolecular solutes) can freely diffuse between cells TOR  target of rapamycin, a protein kinase transcriptional regulation  process by which the amount of mRNA from a gene is determined transcription factor  protein that binds to specific DNA sequences and thereby controls the transfer (or transcription) of genetic information from DNA to mRNA transposons  sequences of DNA that can move around to different positions within the genome of a single cell, a process called transposition. In the process, they can cause mutations and change the amount of DNA in the genome. Transposons make up a large fraction of genome sizes ubiquitin  small, highly-conserved regulatory protein that is ubiquitously expressed in eukaryotes ubiquitination  or ubiquitylation refers to the post-translational modification of a protein by the covalent attachment of one or more ubiquitin monomers. The

Abbreviations and Glossary

405

most prominent function of ubiquitination is labeling proteins for degradation. Besides this function, ubiquitination also controls the stability, function, and intracellular localization of a wide variety of proteins vitellogenin  egg yolk precursor protein expressed predominantly in female organisms, classified as a glyco-lipoprotein, having properties of a sugar, fat, and protein

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Ziechmann W (1996) Huminstoffe und ihre Wirkungen. Spektrum, Heidelberg Zinke I, Schutz CS, Katzenberger JD, Bauer M, Pankratz MJ (2002) Nutrient control of gene expression in Drosophila: microarray analysis of starvation and sugar-dependent response. EMBO J 21:6162–6173 Zörb C, Herbst R, Forreiter C, Schubert S (2009) Short-term effects of salt exposure on the maize chloroplast protein pattern. Proteomics 9:4209–4220 Zörb C, Schmitt S, Mühling KH (2010) Proteomic changes in maize roots after short-term adjustment to saline growth conditions. Proteomics 10:4441–4449 Zucchi S, Corsi I, Luckenbach T, Bard SM, Regoli F, Focardi S (2010) Identification of five partial ABC genes in the liver of the Antarctic fish Trematomus bernacchii and sensitivity of ABCB1 and ABCC2 to Cd exposure. Environ Pollut 158:2746–2756

Index

A ABC exporters, 311 ABCG transporters, 90 Abietic acid, 63 Abiotic requirement, 295 Abiotic stress, 108 Abutilon theophrasti, 103 Acanthopanax sciadophylloides, 141 Acathamoeba castellanii, 21 Accipiter nisus, 123 Acetylcholinesterase (AChE), 79, 104, 105, 189, 304 inhibitor, 120 AChE. See Acetylcholinesterase (AChE) Acidification, 72, 162, 350 Acidity, 302 Acid mine drainage, 247 Acid pH, 312 Acids, 371 a-crystalline. See Small heat-shock proteins ACT8, 147 Actinobacteria, 10, 278 Adaptation, 372, 373 Adineta vaga, 320 Aeluropus lagopoides, 254, 255 17 a-ethinylestradiol, 203, 267, 268 Ag. See Silver (Ag) Age at maturity, 357 Agonist, 69 AhHMA4, 148 AHR. See Aryl hydrocarbon receptor (AHR) AH receptor. See Aryl hydrocarbon receptor (AHR) Ajellomyces capsulatus, 21 Al. See Aluminum (Al) Alarm phase, 1 Alkaline pH, 312

Alkaloids, 97 Alkyl radical, 24 Allelochemical, 43, 61, 82, 83, 92, 298 Allelopathic traits, evolution of, 43 Allelopathy, 43, 141 Allometry equations, 357 relationship, 357–359, 363, 364, 366 scaling, 363 All-purpose detoxification, 83, 89 Alopecurus myosuroides, 103 Alphaproteobacteria, 10 Alternative oxidase (AOX), 21, 49 Alternative splicing, 246, 268 Aluminum (Al), 297 resistance, 154 Alyssum, 140 Amazon, 94 Ambystoma tigrinum, 296 Amine oxidase, 15 Amino acid identity, 62, 387 Amino acids, 339 Ammonia, 313 Anabaena variabilis, 21 Anhydrobiosis, 185, 320 Anolis carolinensis, 296 Anopheles gambiae, 71, 105, 273, 274 Anoxia, 247, 312 Antarctica, 129 Antarctic fish, 38, 129, 130 Antarctic midge, 323 Anticarsia gemmatalis, 105 Antioxidant, 24, 34, 164, 321 defense, 100 Antioxidase, 372 Antirrhinum majus, 226 Antisense, 318

C.E.W. Steinberg, Stress Ecology: Environmental Stress as Ecological Driving Force and Key Player in Evolution, DOI 10.1007/978-94-007-2072-5, © Springer Science+Business Media B.V. 2012

461

462 Anti-tumor agent, 280 AOX. See Alternative oxidase (AOX) APO. See Ascorbate peroxidase (APX, APO) Apoplast, 14–17, 23, 28, 34, 142, 148 Apoptosis, 17, 35, 38, 40, 139, 200, 202, 203, 207, 248, 261, 263, 266, 273, 289, 386 APX. See Ascorbate peroxidase (APX, APO) Arabidopsis, 113, 150, 169, 170, 173–176, 178, 179, 181, 215, 226, 250–254, 312, 328, 329, 384, 394–399 A. halleri, 141, 144, 146–148, 150 A. thaliana, 49, 63, 66, 71, 141, 144, 146, 147, 150, 167, 168, 180, 214–216, 226, 230, 242, 309, 312, 313, 315, 371 Arginine, 339 Argopecten irradians, 125 Arsenic (As), 3, 141, 145, 201, 238 Artemia franciscana, 312, 313, 321, 323, 371 Aryl hydrocarbon receptor (AHR), 69, 100, 184, 200, 294 agonist, 95, 200 pathway, 170 As. See Arsenic (As) Ascorbate, 18, 20, 24, 27, 33, 34 Ascorbate-glutathione cycle, 17, 18, 23, 150 Ascorbate-glutathione pathway, 149 Ascorbate peroxidase (APX, APO), 15, 17–21, 23, 28, 29, 33, 111, 112, 149, 150, 170, 252, 257, 259 Ascorbic acid, 16, 19, 23, 328 Asellus aquaticus, 97 Aspergillus fumigatus, 21 Aspergillus niger, 21 Astacus astacus, 55 Asteraceae, 97 Aster tripolium, 111, 112 Ataxonomic approach, 358, 362 Athene cunicularia, 296 Atlantic killifish, 99, 101, 239, 375, 383 Atmospheric CO2, 111 Atrazine, 102, 191, 304, 392 B Bacillus, 308 Bacillus subtilis, 73, 165 Bacterial disease, 323 Bacterial infection, 125, 312, 318 Bacterioplankton, 10 Baikalian gammarid, 34, 36 Banded iron formations, 131 Barbus graellsii, 241, 243

Index Bark beetles, 63 Bases, 371 Beauveria bassiana, 53, 55 Behavior, 2, 57, 58, 93, 101, 114, 158, 162, 205, 207, 213, 229, 238, 239, 264, 271–274, 297, 302, 303, 373, 378 Behavioral defense, 302–303 Belgica antarctica, 323 Bemisia tabaci, 104 Benthic, 25, 131, 191, 301, 362 communities, 361 diatoms, 351 insect larva, 298 macrofauna, 361 macroinvertebrates, 351 Benzo[a]pyrene, 68, 69 17-b-estradiol, 203, 204, 239 Betaine-homocysteine-methyltransferase, 240, 262, 263, 266 Betaproteobacteria, 10 Betula pubescens, 300, 306, 313 Bilateral asymmetry, 346 Bioconcentration, 91 Biodiversity, 6, 300, 331, 370 Biogeographical regions, 355 Biomass, 52, 66, 97, 155–157, 198, 285, 297, 358, 361–364, 399 allocation, 155, 157 production, 357 spectra, 345, 356, 359–361, 363, 364 Biomphalaria glabrata, 124 Biotransformation, 1, 67, 69–72, 78, 83, 87, 88, 95, 183, 370 enzymes, 2, 87, 88, 94, 99, 100, 188 system, 4, 64, 67, 68, 71, 89, 94 evolution of, 61 Biphasic response, 280, 290 Blumeria graminis, 21 Body mass, 123, 322, 357, 365, 366 Bombyx mori, 71, 77, 89 Boraginaceae, 97 Bosmina longirostris, 360 Bovichtus variegatus, 130 Brachionus, 384 Brachionus plicatilis, 220–222, 299, 313, 343, 386 Branta canadensis, 97, 98 Brassica, 157 B. juncea, 141 B. nigra, 141 B. oleracea, 177, 261 Brassicaceae, 79, 84, 140, 155, 157, 242 Brine shrimp, 185, 323 Bryozoa, 321

Index Bufo americanus, 296 Bufo bufo, 76 Burkholderia, 390 Bush rats, 68 C C4, 16, 376, 377 Cadmium (Cd), 90, 131–141, 143, 144, 146, 148–150, 152, 155, 187, 189, 191, 192, 196, 206, 270, 275, 276, 281, 283, 297, 299, 312, 314, 375, 396, 397, 399 Caenorhabditis elegans, 2, 4, 41, 71, 72, 89, 101, 102, 133–135, 164, 181, 183, 189–195, 201, 206, 218, 265, 281, 284, 290, 292, 294, 298, 313, 323, 331–335, 337–339, 342, 384 Caffeic acid, 287, 288, 337–339 Calorie restriction, 323, 324 CAM, 226 metabolism, 16 Canalization, 300 Candida, 21 Carassius auratus, 33, 122, 123 Carboxylesterase, 79, 84, 291 Carcinogenicity, 201 Carcinogens, 76 Carcinus maenas, 42 Carotenoids, 16 Carrying capacity, 343, 357 CAT. See Catalase (CAT) Catalase (CAT), 13–15, 17–21, 28, 29, 33, 35, 43, 121, 122, 135, 136, 149, 150, 199–201, 220, 250, 259, 315, 317, 321, 386 Cation diffusion facilitator (CDF), 143, 144 Caullerya mesnili, 58 Cd. See Cadmium (Cd) CDF. See Cation diffusion facilitator (CDF) Cd2+-hyperaccumulator, 145 Cd-responsive gene, 133 Cellular transport, 257, 264 Cercopagis pengoi, 359 Chain reaction, 12, 20, 38, 170 Chaoborus, 187 Chaoborus flavicans, 228 Chaperone, 107, 109–111, 113, 114, 125, 130, 151, 170, 181, 209, 234, 237, 243, 245, 258, 259, 266, 269, 278, 327, 329, 331, 348, 370, 381, 384 Chaperonin, 110, 252, 259, 370 Chara hispida, 330 Chemical defense, 66, 71, 97

463 Chemical defensome, 61, 67, 183, 184 Chemicals, synthetic, 4, 196, 295, 370 Chemical trigger, 71, 311 Chemosensitization, 68, 90, 91 Chemosensory genes, 2 Chemotaxis, 2, 4 Chironomus riparius, 298 Chlamydomonas reinhardtii, 143, 144, 180, 252, 399 Chlorella vulgaris, 340 1-Chloro–2,4-dinitrobenzene, 76 Chlorophyll, 11, 15, 36, 257, 328, 329, 398 autofluorescence, 45 fluorescence, 330 Chloroplast, 10, 13, 15, 16, 19, 21, 23, 24, 29, 170, 174, 259, 328 Choice of flight, 315, 371 Choline sulfate, 79 Chromatin, 138, 185, 225, 231, 232, 236, 239, 242, 244, 373 acetylation, 232 modification, 224–226, 231, 232, 238 Chromium (Cr), 140, 155 Chromophore, 7, 8, 25 Ciona intestinalis, 134 Citrus sinensis, 398 Clethra barbinervis, 141 Climate, 6, 128, 309, 318, 365, 374 change, 1, 11, 162, 170, 247, 301, 370, 372, 375 zones, 111 Clonal competition, 59 Clonal success, 59 Co. See Cobalt (Co) Coastal lagoon, 221, 323, 324, 359 Cobalt (Co), 3, 140, 141, 144, 155, 201 Coenagrion puella, 297, 304 Co-evolution, 59–61, 331, 370 Co-existence, 6, 68 Cold, 1, 31, 38, 65, 72, 108, 114, 116, 117, 127, 129, 130, 162, 165, 167–169, 173, 181, 185, 186, 215, 216, 225, 226, 230, 247, 251, 258, 259, 262, 263, 271, 278, 299, 309, 311–314, 316, 321, 323, 369, 371, 398 CO2 limitation, 35 Colletotrichum lindemuthianum, 318 Colonizer, 278, 353, 354 Colossoma macropomum, 95 Competition, 6, 57, 59, 60, 205, 302, 303, 318, 319, 355, 357, 372, 374, 381 Competitors, 43 Complex contaminations, 247 Compounds, UV-absorbing, 25

464 Conjugated diene, 27 Copper (Cu), 12, 13, 38, 49, 133, 134, 140, 141, 144, 146, 151, 155, 191, 200–202, 215, 218, 297, 305, 313, 319, 397 Coregonus lavaretus, 297 Cotesia glomerata, 99 Co-tolerance, 306 Coumarin, 62, 66 Coxliella, 11 CpG. See Cytosin guanine (CpG) C4 photosynthesis, 254, 376, 377 evolution of, 376 C4 plants, 254, 376 CPN, 110 CPN20, 252 CPN23, 252 CPN60, 252, 259 Crangonyx gracilis, 97 Crassostrea gigas, 380 Crassostrea virginica, 125 Cristatella mucedo, 321 CrMRP2, 143 Cross-talk, 29, 44, 153, 215, 246, 249, 257, 317 Cross-tolerance, 5, 29, 103, 127, 221, 311, 312, 314, 315, 319, 322, 323, 325, 329, 371, 398 evolution of, 103 trehalose-mediated, 323 Cryptococcus neoformans, 21 Cryptoperidiniopsis, 10 Cryptosporidium, 21 Ctenopharyngodon idella, 85, 86 Cu. See Copper (Cu) Cu-miRNAs, 218 Cu-SOD, 215 Cu/Zn-SOD, 19 Cyanotoxin, 31, 72, 203, 247, 265, 270, 299 resistance, 80 Cyclooxygenase, 15 Cydia pomonella, 281, 312 CYP, 62, 63, 67–75, 77, 82–84, 88, 89, 93–95, 100–105, 170, 190, 388. See also Cytochrome P450 enzymes gene number, 71 genes, 73 CYP1, 200 CYP1A. See Cytochrome P450 1A (CYP1A) CYP6B genes, 83 Cypermethrin, 83, 95, 96, 103, 104 CYP6 family, 62 Cyphoma, 88

Index Cyphoma gibbosum, 88, 92 CYP inhibitor, 95 Cysteine, 133–135, 175, 259, 291, 293, 339 Cytochrome P450 1A (CYP1A), 95, 100, 198–200, 210, 240, 241 Cytochrome P450 (CYP) enzymes, 49, 62, 70, 71, 73, 93 Cytokinin, 328 Cytoplasm, 14, 15, 69, 91, 107, 161, 183, 201, 238, 259, 393, 398 Cytosin guanine (CpG), 231, 232, 240 Cytosol, 15–17, 21, 37, 107, 143 D DAF–2, 332 DAF–12, 41 DAF–16, 332–334 DAF–16/FOXO, 333 Danio rerio, 78, 90, 119, 120, 181, 198, 202, 265, 266, 268, 297 Daphnia, 79, 181, 229, 230, 281, 299, 360, 384, 386 D. cucullata, 228 D. galeata, 59, 374 D. galeata x hyalina, 375 D. longispina, 375 D. magna, 42, 55, 56, 78, 95, 96, 121, 122, 124, 133, 186, 190, 206, 207, 220, 223, 224, 238, 269, 270, 280, 285, 298, 307, 308, 313, 322, 323, 335, 336, 341–343, 374 D. pulex, 71, 133, 322 Darwinian fitness, 294 Dasycladus vermicularis, 41, 42 DDE, 203 DDT, 105, 275 DDT resistance, 104–106 Defense chemicals, 62 Defense system, evolution of, 6, 370 Defense morphological, 228, 229, 297, 303 transgenerational, 229 Deforestation, 300 Dehydration, 80, 173, 185, 215, 216, 250, 251, 313, 320, 321, 323, 391 Dehydroascorbate (DHA), 18, 20, 23, 76 Dehydroascorbate reductase (DHAR), 18, 19 Delayed metamorphosis, 297, 303 Demography consequence, 59 factors, 108, 120 structure, 372 Dendrobaena octaedra, 299

Index Density-dependent prophylaxis, 53 Deoxyribonucleic acid (DNA), 24, 35, 40, 84, 110, 137, 138, 161, 200, 201, 230, 234, 240, 242–244, 266, 268, 274, 331, 373 damage, 40, 192, 200, 201, 204, 334, 386 demethylation, 226, 230 hypermethylation, 226 methylation, 225–227, 230–232, 237–240, 373, 383 methyltransferase, 231, 232 microarray, 179, 191, 192, 290, 293, 332 modification, 225 polymerase, 148 repair, 201, 266, 268, 372, 393 sequence, 164, 224 Depressaria pastinacella, 63, 83 Desiccation, 25, 32, 72, 108, 156, 162, 185, 247, 312, 313, 319–321, 355, 386 Desmodesmus, 230 Desmodesmus armatus, 339, 342 Detoxification, 15, 253, 278, 380, 390, 392, 394–397, 399 Development time, 99, 126, 357 DHA. See Dehydroascorbate (DHA) DHAR. See Dehydroascorbate reductase (DHAR) Diatoms, benthic, 351 Dietary restriction, 333, 334 Dietary shift, 88 Digestion, 11, 79, 84, 121, 270, 307 Dioxin, 99, 210, 294, 388 Disease, 105, 120, 214, 218, 256, 257, 264, 318, 335, 345 resistance, 54, 125 triangle, 318, 319 viral, 296 Disposable Soma Theory, 209, 341, 342 Disturbance, 363 Ditylum brightwellii, 38 DNA. See Deoxyribonucleic acid (DNA) DnaK, 111, 245 Dorosoma cepedianum, 360 DPSL, 165, 249 Dreissena polymorpha, 68, 90 Driving force, 5, 10, 369, 384 Drosophila, 80, 116, 120, 182, 232–235, 237, 312, 313, 372, 380, 384, 398 D. melanogaster, 71, 73, 104, 116, 126, 127, 181, 185, 236, 265, 270, 271, 299, 311–313, 373, 381 Drought, 32, 72, 79, 108, 162, 168, 169, 171, 185, 214–216, 226, 247, 252, 258,

465 259, 295, 299, 300, 306, 309, 313, 316, 328, 369, 371, 372 Drought-responsive protein, 259 Dunaliella tertiolecta, 38, 39 Durvillaea antarctica, 26 E Echiniscus granulatus, 321 Echinochloa phyllopogon, 103 Echinogammarus marinus, 58 Echinorhynchus truttae, 57 Ecological niche, 6, 71, 72, 342, 370, 390 Eggplants, 84 Eisenia fetida, 135, 136, 189, 275, 290 Electromagnetism, 298 Elicitor, 16, 30, 47, 48, 50, 64, 65, 153, 225, 308, 397 Ellagic acid, 338 Emiliania huxleyi, 51 Enallagma cyathigerum, 123, 124 Encapsulation, 57 Enchytraeus doerjesi, 306 Endocrine disruptor, 203, 204, 238, 239, 283, 298 Endoparasite, 58, 308 Endoplasmic reticulum (ER), 14, 15, 22, 41, 102, 201, 207 Energy allocation, 94, 131, 135, 304, 307, 325, 338–342 Energy transfer, 358, 360 Enterobacter, 390 Environmental stress, 5, 30, 31, 35, 64, 72, 108, 109, 127, 155, 158, 161, 164, 165, 167, 171, 172, 183, 188, 192, 207, 219, 221, 223, 225, 234, 235, 239, 247, 272, 278, 296, 302, 312, 315, 328, 345, 346, 349, 352, 369–372, 376, 380, 381, 383, 384, 386 Ephoron virgo, 297 Epibiont, 124, 301 Epidermis, 16, 251 Epigenetics, 5, 99, 137, 148, 173, 213, 219, 224–227, 230, 232, 236–240, 346, 369, 371, 373, 378, 383, 384 Epigenome, 231, 373 ER. See Endoplasmic reticulum (ER) Eriocheir sinensis, 55 Erwinia chrysanthemi, 318 Escherichia coli, 111, 165, 166, 257, 275, 313, 314, 390 Esfenvalerate, 207

466 Esterase, 79, 84, 104, 105 Estrogen, 203, 239, 267 Estrogen receptor, 238, 268, 281 Ethanol, 165, 312 Ethylene, 22, 35, 48, 49, 152, 176, 178, 180, 317, 328 Eucypris virens, 386 Eulimnogammarus cyaneus, 37, 90, 92, 114, 115 Eutrema salsuginea, 148 Eutrophication, 296, 297, 300, 301, 350, 351, 354, 360 Evolution, 5, 6, 35, 43, 52, 61, 62, 64, 71, 82, 90, 102–104, 117, 122, 138, 148, 155, 164, 184, 215, 219, 236, 237, 331, 357, 369, 370, 376, 379–381, 383, 384 Exhaustion phase, 1, 180 Exiguobacterium sibiricum, 278 Exporters, PDR, 397 Extinction, 5, 59, 203, 208, 230, 319, 343, 345, 369, 372 F FA. See Fluctuating asymmetry (FA) Fabaceae, 97, 155–157 Falco tinnunculus, 120 Fasting, 93 Fatty acid, 27, 171, 244, 245, 265, 389 biosynthesis, 174 derivatives, 102 flux, 265 hydroxylase, 388 metabolism, 67, 270, 388 Fatty acid synthase, 211 Fe. See Iron (Fe) Feeding rate, 285 type, 351–353 Feminization, 203, 268 Fenneropenaeus chinensis, 269 Fenton reaction, 12, 24, 331 Fenvalerate, 270, 355 Ferredoxin, 15, 18, 22 Ferroplasma, 278 Fe-SOD, 19, 180, 259 Ficedula hypoleuca, 123 Fight-or-flight response, 123 Firmicutes, 278 Fish community, 365 Fishing, 365–367 Fishing, sustainable, 367 Fish stock exploitation, 359, 364

Index Fitness, 59, 60, 116, 125, 127, 137, 155, 158, 205, 208, 211, 215, 219, 240, 265, 272, 280, 283, 297–299, 303, 308, 319, 325, 346, 348, 371, 374, 378, 383, 385 Flavonoids, 24, 62, 64, 66, 82, 84, 89, 154, 252 Flavoprotein, 13 Flooding, 31, 35, 247, 254, 256, 258, 299 Flow cytometry, 363 Fluctuating asymmetry (FA), 345–349 Fluctuating environment, 5, 116, 221, 240, 323, 325, 342, 369, 371, 385 Fluctuating irradiance, 38 Fluoranthene, 102, 190, 191 Folsomia candida, 186–188, 270, 313 Fontinalis novae-angliae, 97 Food, 6, 11, 32, 54, 59, 61, 67, 82, 84, 93, 105, 108, 119–121, 127, 162, 205, 220, 221, 230, 247, 261, 264, 275, 295, 298, 323, 343, 353, 354, 358 algae, 339 allelochemicals, 61, 65, 73–75, 78, 84, 92, 162, 203, 269 availability, 93, 220 deprivation, 298, 299 ingestion, 304 quality, 42, 219, 298, 307, 308, 340, 373 quantity, 42, 296 restriction, 299 supply, 81, 343 webs, 350 structure, 345, 351, 356, 359 Freezing, 218, 259, 328 Fugu rubripes, 71 Fullerenes, 40, 41 Fundamental ecological niche, 1 Fundulus heteroclitus, 99–101, 210, 211, 239, 240, 375, 384 Fungicide, 297, 303 Furanocoumarin, 62, 63, 82–84, 389 Furan ring, 62, 63 G Gadus morhua, 198 Gallic acid, 338 Gallus gallus domesticus, 346 Gambusia affinis, 346, 347 Gammarid, 33, 47 Gammarus G. insensibilis, 57, 274 G. lacustris, 37, 57 G.lacustris, 114, 115

Index G. oceanicus, 129 G. pulex, 57, 118, 274 G. roeseli, 57 Gasterosteus aculeatus, 124, 239, 297, 348 Geldanamycin, 236, 237, 373, 383 Gene expression, 1, 5, 33, 48, 87, 88, 100, 102, 111, 113, 127, 133, 139, 141, 148, 149, 161, 164, 168, 169, 171, 175–177, 181, 185–187, 189, 191, 192, 194, 196–198, 200, 201, 203, 205, 206, 208, 210, 211, 213, 214, 225, 226, 230, 231, 238, 240, 241, 246, 250–252, 254, 266, 289, 309, 315, 334, 373, 383, 396, 398 Gene flow, 57, 59, 373, 379, 380 Generation time, 72, 325, 355, 358 Gene silencing, 113 Genetic erosion, 375, 380 Genotoxicity, 191, 194 Gillichthys G. mirabilis, 114, 115 G. seta, 114 Glass formation hypothesis, 320 Global climate change, 65, 251, 295 Global warming, 263, 297 Glossina papalis gambiensis, 274 Glucosinolate, 66, 67, 75, 77, 78, 82, 84, 97, 99, 175, 229 biosynthesis, 174 Glucuronidation, 74, 77 Glugoides intestinalis, 56 Glutathione (GSH), 14, 16, 18–21, 24, 33, 38, 41, 69, 75, 76, 84, 103, 134, 135, 141, 149, 150, 152, 153, 183, 199, 245, 259, 311, 387, 393, 395, 396 synthesis, 150 Glutathione ascorbate cycle, 20 Glutathione disulfide (GSSG), 20, 150 Glutathione peroxidase (GPX), 15, 17–21, 27, 76, 88, 259 Glutathione peroxidase cycle, 19 Glutathione reductase (GR), 18–20, 39, 150, 245 Glutathione transferase (GST), 22, 62, 69, 71, 72, 75–77, 84, 85, 88, 93, 95, 96, 103, 105, 106, 111, 112, 134, 181, 190, 250, 259, 263, 266, 387 activity, 96 alpha-class, 85, 86 beta-class, 392 classes, 85 class I, 392 class II, 392 cytosolic, 75, 76, 88, 387, 392

467 delta-class, 84, 390epsilon-class, 106 fungal, 391 helminth, 392 insect, 390 kappa-class, 387 microsomal, 75, 387, 389 mitochondrial, 75, 387 phi-class, 391 rho-class, 85, 86, 390 sigma-class, 84, 391 tau-class, 391 theta-class, 391 zeta-class, 391 Glycine max, 144 Glycolate oxidase, 15 Glycolsyltransferase, 64 Glycosides, 84, 97 Glycosyltransferase, 62, 77 Glyphosate, 285, 286 Gobiocypris rarus, 239, 267 Gold (Au), 201 Goldfish, 33, 123 GolS3, 251 GPX. See Glutathione peroxidase (GPX) GR. See Glutathione reductase (GR) Gracilaria comosa, 301 Gracilaria conferta, 49, 50 Growth, 301, 308, 312, 313, 318, 322, 334, 341, 342, 345, 348, 352–354, 357, 358, 366, 367, 371, 383, 386 female, 297 limitation, 315 male, 297 rate, 304 GSH. See Glutathione (GSH)GSH-Px, 198, 199 GSSG, 18, 20, 22 GST. See Glutathione transferase (GST) Gymnodinium, 10 G. gracilentum, 11 G. simplex, 11 H Halophila ovalis, 300 Hardening, 42, 126, 180, 227 cold, 271 heat, 126, 271 Harmonia axyridis, 346 Heat, 31–33, 72, 108, 113, 114, 117, 126, 127, 162, 165, 171, 234, 247, 258, 259, 272, 278, 298–301, 312–314, 316, 323, 334, 371, 372, 385

468 Heat shock, 33, 107, 116, 117, 129, 133, 251, 252, 270, 271, 273, 314, 315, 321, 323, 386 Heat shock factors (HSF), 109, 110, 113, 258, 334 Heat-shock proteins (HSPs), 107, 109–112, 128, 130, 201, 232, 235, 250, 252, 258, 259, 264, 311, 314, 322, 332, 370, 372, 381HSP40, 110, 245 HSP60, 110, 120–124, 243, 245, 259–322 Hsp60, 43 HSP70, 109–111, 116–126, 129, 130, 185, 186, 245, 252, 257, 259, 265, 266, 321–323, 329 expression, 116, 117 mRNA, 129 HSP72, 117 HSP78, 117 HSP90, 109, 110, 114, 125, 230, 232–239, 252, 259, 275, 321, 323, 329, 348, 381–383 induction profiles, 115 inhibitor, 236, 373 mutation, 233 senescence, 330HSP100, 110, 257, 259 HSP108, 265HSP110, 259 induction, 33, 114, 117, 118, 120, 125 synthesis, 129 Heat-shock response, 111, 114, 116, 130, 187 Heat stress, 251, 252, 271, 273 Heavy metal ATPases (HMA), 143, 144, 395 Heavy metals, 5, 12, 24, 72, 90, 108, 114, 119, 131–137, 139, 140, 142, 143, 148, 150, 152, 155–157, 162, 237, 247, 259, 266, 280, 298–300, 306, 307, 311–313, 319, 375, 395, 397, 399 Heavy-metal tolerance (HMT), 137 Helicoverpa H. armigera, 104, 271, 272 H. zea, 63, 83 Hemoglobin synthesis, 190, 208 Hemolymph, 40, 53, 97 Herbicide, 76, 77, 79, 102, 103, 190, 285, 287, 296, 299, 389, 396 resistance, 102, 103 Herbivore, 61, 65, 67, 71, 78, 81, 87, 88, 94, 96, 97, 99, 103, 140, 141, 151, 152, 154, 158, 174–178, 186, 228, 229, 260, 269, 300, 301, 307, 313, 318, 331, 370 Herbivory, 4, 26, 61, 63, 65, 66, 78–80, 97, 175, 177, 229, 248, 260, 300 Herminiimonas arsenicoxydans, 2, 3

Index Heterandria formosa, 155 Heterotrophic reduction of oxygen, 10 Hg. See Mercury (Hg) Hirundo rustica, 346 Histidine, 339 Histone, 185, 225, 227, 238, 244 acetylation, 231, 237 deacetylation, 231 modifications, 226, 227, 232, 240 Histone deacetylase, 80 HMA. See Heavy metal ATPases HMA4, 144, 145, 147–149 HMT. See Heavy-metal tolerance (HMT) Homeostasis, 61, 67, 94, 123, 130, 234, 258, 266, 271, 275, 346, 384 biochemical, 67 calcium, 189 cellular, 254, 276 Cu, 191 developmental, 346 energy, 169, 219 hormone, 239 ion, 41, 112, 190, 253, 259 iron, 201 metal, 133, 142, 148, 151, 153, 154, 183 morphological, 345 protein, 121 redox, 12, 21, 25, 150, 264, 315 steroid, 239 systemic, 356 thermic, 32 Homo sapiens, 71, 73 Hordeum vulgare, 171, 172, 251, 285, 286 Hormesis, 5, 80–82, 279, 280, 285, 287, 290, 292, 294 Hormone, 29, 34, 49, 57, 73, 77, 94, 102, 107, 161, 180, 208, 253, 389 Host behavior, 275 HR. See Hypersensitive response (HR) H2S, 313 Humic substances (HSs), 2, 7, 31, 36, 43, 71, 72, 90, 91, 95, 96, 108, 114, 180, 192, 221, 223, 224, 247, 257, 285, 298, 307, 313, 322–324, 328, 330 Huso huso, 268 Hydra, 130 H. magnipapillata, 128, 129 H. oligactis, 128, 129 H. vulgaris, 128 Hydrogen peroxide (H2O2), 8, 9, 12–20, 22–24, 28, 35, 37, 38, 42, 312, 314, 315, 317, 318 Hydrolases, 79, 104 Hydrolysis, 43, 79, 97, 184, 393

Index Hydroxyl radical, 12, 17 Hyla chrsoscelis, 296 Hyla versicolor, 296 Hyperaccumulation, evolution of, 141 Hyperaccumulator, 131, 132, 140, 145, 152, 154, 157, 158, 318, 395 Hyperoxia, 31, 198, 199, 295 Hyperparasitoid, 99 Hypersaline lagoon, 359 Hypersensitive response (HR), 48, 49, 53, 174, 178, 180 Hypertolerance, 148 Hypomesus transpacificus, 207 Hypophthalmichthys molitrix, 85, 86 Hypophthalmichthys nobilis, 85 Hypoxia, 31, 107, 108, 162, 187, 188, 197–199, 201, 207, 215, 217, 247, 269, 295, 297, 299, 305, 312 Hypoxia-inducible factor, 184, 196 I Ictalurus puntatus, 297 Ilex crenata, 141 Indole, 75, 78, 82 Induced systemic resistance (ISR), 48, 308 Inducer, 69, 84, 92, 120, 150, 240, 270 Inducible defense, 34, 153, 302 Infection, 29, 51, 52, 59, 80, 152, 178, 207, 220, 260, 273, 308, 319, 369, 373 fungal, 79, 318 microbial, 137 viral, 51, 214 Innate immunity, 52, 189, 190 iNOS. See Nitric oxide synthase (iNOS) Insecticide, 76, 79, 80, 95, 104, 105, 119, 190, 207, 296–299, 355 resistance, 62, 80, 83, 103–105 Insulin, 332 Insulin-like growth factor (IGF–1), 198, 332, 334 Insulin pathway, 187 Intercellular transport, 141 Intersex, 58 Intracellular signal, 34, 48, 171, 294, 315 Invasive species, 300, 359, 360 Invertebrates, 53, 58, 78, 89, 132–134, 137, 138, 181, 187, 319, 323, 350, 366, 380, 388 aquatic, 99, 352 benthic, 297, 351 marine, 40, 80, 125 soil, 363 terrestrial, 299

469 Iris pumila, 235, 236, 346, 347 Iron (Fe), 2, 3, 8, 12, 131, 133, 135, 140, 144, 155, 170, 189, 265, 267, 278, 299, 318 Iron-regulated transporter proteins (IRT), 144, 395 Irradiation, 9, 31, 171, 247, 250, 251, 271, 289, 297, 313, 315, 318, 371 IRT. See Iron-regulated transporter proteins (IRT) IRT3, 147 Isoprene, 62 ISR. See Induced systemic resistance (ISR) J JA. See Jasmonate; Jasmonic acid Jasmonic acid (JA), 35, 49, 66, 152, 175–177, 180, 228, 261, 317 Juniperus monosperma, 87 Juvenile hormone, 79, 206, 209, 386 K Kairomone, 58, 122, 124, 177, 187, 228, 308 Klebsiella, 390 Kleptochloroplast, 10 Kola Peninsula, 306 L Lactuca sativa, 287, 288 Lake Arendsee, 362 Lake Baikal, 116 Lake Fuchskuhle, 118 Lake Greifensee, 8 Lake Kinneret, 36, 44 Lake Malawi, 358 Lake Ontario, 358, 359, 361–364 Lake Schwarzer See, 37, 92, 118 Lakes Michigan, 364 Lake St. Clair, 362, 363 Lake Victoria, 300 Larrea tridentate, 88 Laurentian Great Lakes, 364 Lead (Pb), 139–141, 144, 155, 299, 375, 398 Leaf area, 236, 285 LEA proteins, 171, 259, 320, 386 Lepidoptera, 63, 83, 97, 271 Lepomis macrochirus, 122, 123 Leptinotarsa decemlineata, 83 Leptodora ti, 228 Leptospirillum, 278

470 Lessonia, 26 Lessonia nigrescens, 26 Lestes viridis, 54 Lethality, 180, 296, 355, 371 Lifespan, 4, 5, 80, 127, 209, 220, 221, 283, 284, 292, 298, 299, 307, 323, 324, 328, 331–338, 340–343, 357, 372 extension, 290, 331–335, 338, 372 female, 298 Light, 114, 169–171, 250, 252, 256, 259, 271, 295, 300, 308, 312, 315, 328, 330, 346, 353, 369 Lignin, 24, 148, 154, 170, 389, 393 Limnephilus lunatus, 355 Limnodrilus hoffmeisteri, 132, 380 Limonium, 79 Linoleate, oxygen oxidoreductase, 13 Lipid, 17, 20, 33, 35, 40, 73, 77, 93, 94, 110, 189, 208, 240, 249, 278, 291, 293, 393, 394 autoxidation, 24 hydroperoxide, 20, 26, 27, 84 metabolism, 208, 265 Lipid peroxidation (LPO), 2, 10, 13, 19, 26–28, 31, 33, 35, 37, 38, 40, 41 Lipid peroxyl radicals, 24 Lipoxygenase, 13, 15, 26 Listronotus bonariensis, 99 Litter decomposition, 300 Lolium, 157 L. perenne, 99 L. rigidum, 103 Longevity, 5, 6, 10, 110, 120, 209, 220, 265, 284, 290, 323, 325, 327–329, 331, 333, 334, 336, 340, 342, 346, 370, 372 cellular, 329 plants, 328 seed, 328 Longitarsus anchusae, 97 LPO. See Lipid peroxidation (LPO) Lucilia cuprina, 104 Ludwigia palustris, 98 Lumbricus rubellus, 134, 191, 275 Lycaena tityrus, 117 Lycodichthys dearborni, 130 Lycopersicon lycopersicum, 144 Lymantria dispar, 84 Lysibia nana, 99 M Macrobiotus hufelandi, 320 Macrobrachium rosenbergii, 55

Index Macrocystis pyrifera, 26 Macroevolution, 371 Macroinvertebrates, 97, 98, 350, 351, 355, 362 Macrophyte, 9, 43, 97, 98, 351 Macrosiphum euphorbiae, 271, 273 Magnaporthe grisea, 319 Maintenance, 10, 107, 112, 113, 130, 136, 148, 155, 158, 186, 233, 258, 264, 276, 325, 341, 353, 370 Malacosoma disstria, 346 Manganese (Mn), 13, 70, 140, 141, 155, 318MAPEG. See Membraneassociated proteins ecosanoid and glutathione MAP kinase. See Mitogen activated protein kinase (MAPK) MAPK signaling pathway, 34, 203, 204, 266 Marine fisheries, 364, 366 Marine microalgae, 38 Marisa cornuarietis, 281 Maturity index, 345, 350, 354 Maytenus founieri, 141 MDAR. See Monodehydroascorbate reductase (MDAR) MDAR4, 149 Meconema thalassinum, 272, 274 Medicago truncatula, 218 MeHg. See Methylmercury (MeHg) Mehler reaction, 12 Melanization, 53, 54, 57 Melitaea cinxia, 208, 209 Membrane, 9, 15, 16, 20, 21, 23, 26, 34, 40, 63, 78, 84, 90, 94, 102, 107, 110, 111, 114, 151, 165, 186, 249, 256, 262, 266, 271, 291, 314, 320, 331, 388, 393, 398 integrity, 1 proteome, 257 Membrane-associated proteins ecosanoid and glutathione (MAPEG), 75, 387, 389, 392 enzymes, 76 Membrane-irritant, 312 Mercury (Hg), 140, 200 Mesembryanthemum crystallinum, 226 Mesofauna, soil, 364 Messenger RNA (mRNA), 28, 71, 85, 86, 117, 122, 125, 138, 150, 161, 163–165, 172, 190, 203, 210, 213, 214, 219, 220, 240, 241, 243, 246, 249, 250, 266, 268, 314, 334 unstable, 130

Index MET. See Mitochondrial electron transport (MET) Metabolic rate, 158, 183, 209, 262, 265, 357 Metabolic switch, 215 Metabolic theory of ecology, 356 Metabolomics, 5, 161, 241, 247, 248, 260, 270, 321 Metal, 3, 13, 17, 19, 31, 38, 40, 70, 99, 143, 144, 149, 151, 152, 154, 155, 161, 200, 371 resistance, 135, 137 sequestration, 154 tolerance, evolution of, 139 Metal Defense Hypothesis, 140 Metallochaperone, 142 Metalloids, 2, 3, 13, 17, 19, 31, 72, 108, 200, 247, 300 Metallothionein (MT), 41, 132–135, 137–139, 148, 183, 199, 241, 243, 259, 275, 318 gene, 138, 380 isoforms, 134 MT 3, 149 MT10, 133 MT20, 133 MT 2b, 149 promoter, 139 Metal regulatory trascription factor 1 (MTF–1), 137 Metamorphosis, 54, 297, 302, 303 Metaorganism, 276 Metapopulation, 57, 59, 60, 208 Metaproteomics, 276, 278 Methylation inhibitor, 239 Methylmercury (MeHg), 200, 201, 268, 269 Microbicide, 280 Microctonus hyperodae, 99 Microcystin, 44, 45, 85, 86, 186, 203, 266, 270 Microcystis, 44, 45 Microcystis aeruginosa, 270, 328 Microevolution, 57, 59, 123, 124, 371, 373–375, 382 Microfauna, soil, 364 Microphallus papillorobustus, 57, 274 Micropterus salmoides, 41 MicroRNA (miRNA), 5, 172, 213–216, 218, 219, 246, 334, 335 family, 218 Mictic female, 386 Migration, 59, 60, 93, 355 Milnesium tardigradum, 185 Mineralization, 350 miRNA. See MicroRNA (miRNA)

471 Mitochondria, 13, 15–17, 21, 22, 29, 107, 143, 203, 291, 331, 387 Mitochondrial electron transport (MET), 13, 14 Mitochondrial HSP, 331 Mitogen activated protein kinase (MAPK), 48, 152, 171, 265, 315 Mixotroph, 10, 278 Mn. See Manganese (Mn) Mn-SOD, 19, 41, 220 Modifications post-transcriptional, 164, 245, 331 post-translational, 110, 164, 173, 225, 244 Moina macrocopa, 221, 222, 284, 285, 313, 323, 324, 337–341, 343, 372 Molybdenum (Mo), 140 Monodehydroascorbate, 23 Monodehydroascorbate reductase (MDAR), 18, 19 Monomethylarsonic acid, 76 Monooxygenase, 64, 70, 95 Monoporeia affinis, 298 Monoraphidium minutum, 372 Monovalent reduction, 7 Mortality, 126, 357, 367 algal, 50 cold shock, 271 copper-induced, 305 fishing, 366, 367 fungus-induced, 54 larval, 40, 105 mass, 345 rapid, 80 mRNA. See Messenger RNA (mRNA) MRP. See Multidrug resistance-associated protein MRP families, 92 MT. See Metallothionein (MT) MTL–2, 41 Multidrug resistance, 89, 90, 143 Multidrug resistance-associated protein (MRP), 143, 144, 394, 395, 399 Multiple-stress resistance, 165, 314, 327, 333, 334, 371. See also Cross-tolerance Multiple-stress tolerance, 171, 258, 311 Mummichog, 239 Musca domestica, 103 Mus musculus, 71 Mus spretus, 248 Mutants, 3, 134, 179, 234, 252, 328, 371, 396 Mutation threshold, 6, 369 Mycosporine-like amino acids, 16, 25 Mytilus edulis, 133, 241, 242

472 N NADPH, 13, 14, 19, 20 NADPH oxidases, 14, 15, 27, 29, 49, 52 Nano-Ag, 201, 202, 206 Nano-Cu, 201, 202 Nanoparticles, 41, 108, 201 Nano-TiO2, 201, 202 Naphthalene, 74, 78 Natural organic matter (NOM), 9, 37, 92, 118 Natural resistance associated macrophage protein (NRAMP), 143, 144, 395 NRAMP3, 145 NRAMP4, 145 NRAMP5, 147 Necromeny, 72 Nekton, marine, 358 Nematode assemblages, 353 Nemobius sylvestris, 272, 274 Neolamprologus pulcher, 205 Neotoma N. albigula, 87 N. lepida, 88 N. stephensi, 87 Neurotoxins, 80 NF-kB transcription factor, 315 Ni. See Nickel (Ni) Nickel (Ni), 13, 19, 119, 140, 151, 155, 201, 237, 285, 299 Nicotiana tabacum, 144, 226, 313 Nidula niveo-tomentosa, 250 Ni hyperaccumulator, 140 Nitric oxide (NO), 8, 9, 12–17, 30, 49, 275, 316 Nitric oxide synthase (iNOS), 15, 52, 53 inducible, 16 Nitrosomonas europaea, 312 NO. See Nitric oxide (NO) Noccaea, 157 N. caerulescens, 140, 141, 143, 144, 154 N. goesingense, 144 Nodularia spumigena, 44 Nodularin, 44 NOM. See Natural organic matter (NOM) Nonylphenol, 203, 239, 280–282 North Sea, 365, 366 Notothenia angustata, 130 Notropis ludibundis, 346, 347 Novosphigobium aromaticivorans, 21 NRAMP. See Natural resistance associated macrophage protein (NRAMP) Nutrient, 6, 156, 162, 219, 228, 247, 252, 327, 341, 351, 369, 393 deficiency, 155, 299, 363 deprivation, 215 soil, 363

Index O 1 O2, 7–10, 12, 16, 23 O2, 7, 15, 316 • O2-, 12–16, 18, 19, 23 4-n-octylphenol, 281 Offspring numbers, 224, 283, 307, 337, 340, 343, 372 • OH, 12, 13, 15, 19, 20, 23, 26 Olea europaea, 313 Olfactory genes, 2 Oligoagars, 50 Oligocottus maculosus, 312 Oligostenothermic, 34, 128, 130 Ommatogammarus flavus, 34 Oncorhynchus O. kisutch, 125 O. mykiss, 90, 93, 117, 125, 264 Oneida Lake, 360 Oophages, 97 Orchesella cincta, 137, 139, 380 Orchestia gammarellus, 129 Ordospora colligata, 56 Oreochromis niloticus, 85, 86 Organic pollution, 350, 351, 354 Organophosphorus hydrolase, 79 Organophosphorus pesticides, 189 Organothiocyanates, 105 Ornithine, 339 Oryza sativa, 71, 73, 144, 215, 216, 255, 312, 313 Oryzias latipes, 197, 266, 267 Osmolyte, 29, 249, 311 stress, 312, 314 Osmoprotectant, 79, 251, 278 Osmotic stress, 72, 108, 162, 167, 169, 207, 221, 226, 242, 249, 252, 258, 262, 299, 312, 324 Oxalate oxidase, 15, 16 Oxidative burst, 10, 16, 42, 44, 47, 50, 110, 153, 316 Oxidative functionalization, 62 Oxidative pressure hypothesis, 64, 65 Oxidative stress, 9, 10, 13, 19, 21, 25, 26, 31, 33–35, 37, 38, 40, 41, 43–45, 48, 64, 66, 76, 84, 108, 110, 111, 121, 134, 149, 150, 157, 162, 164–166, 176, 178, 188, 199, 201, 206, 215, 220, 238, 247–249, 252, 263, 264, 266, 269–271, 284, 289, 299, 307, 313, 314, 323, 328, 334, 390, 391, 392, 396 Oxygen, 114 activation, 2, 7, 10, 12, 57, 370 depletion, 299, 305, 361

Index Oxygen minimum zone, 361 Oxyrrhis marina, 51 Ozone, 31, 35, 65, 162, 247, 256, 257, 259, 301, 309, 313, 315, 316 P P53, 38, 204 Pacifastacus leniusculus, 55 Pagothenia borchgrevinki, 130 PAHs. See Polycyclic aromatic hydrocarbons (PAHs) Panicum virgatum, 218 Papilio, 82, 83 P. canadensis, 82, 84 P. glaucus, 82, 84 P. polyxenes, 63, 82, 83 Paragordius tricuspidatus, 272, 274 Paraquat, 149, 150, 222, 226, 323, 324, 397 Parasite, 4, 32, 42, 43, 51, 53, 57, 71, 72, 108, 154, 155, 162, 225, 248, 272–274, 295, 297–299, 308, 313, 319, 343, 358, 369–371, 373, 392 infection, 298 Parasitized animals, 57, 58, 272–274 Parasitized host, 57 Parathion, 346, 347 Parental care, 248 Parthenogenetic males, 335 Passer domesticus, 348 Pasteuria, 298 Pasteuria ramosa, 56, 308 Pastinaca sativa, 84 Pastocyanin (PC), 22 Pathogen, 71, 72, 78, 108, 162, 248, 312, 313 attack, 54, 61 defense, 12, 315 infection, 317, 328, 371 recognition, 50 resistance, 53 Pathogenesis-related protein, 47–49, 178, 317 Pathogenic fungus, 63, 296 Pathogenic Vibrio, 323 Pb. See Lead (Pb) PC. See Pastocyanin; Phytochelatin PCB, 100, 102 PCNA, 200 PCSI. See Phytochelatin synthase PC synthase, 134 Pecten maximus, 40 p-electron system, 8 Penicillin, 188, 281 Pentadienyl radical, 27

473 Pepper, 84 Peridinium gatunense, 35, 36, 44 Permeability, 17, 89 Permeability glycoproteins (P-gps), 67, 69, 71, 86, 90, 92, 93, 393 Peroxidase (POD), 13–15, 19–21, 27, 42, 49, 106, 135, 199, 321 Peroxisomes, 13, 15–17 Peroxyl radical, 27 Peroxynitrite, 17, 316 Persister, 353, 354 Pesticide, 31, 73, 79, 90, 102, 108, 114, 119, 151, 162, 189, 190, 248, 280, 296, 299, 303, 304, 313, 346, 348, 351, 355, 388, 396 resistance, 79 PET. See Photosynthetic electron transport (PET) Petrochemicals, 356 Petroselinum crispum, 84 P-gps. See Permeability glycoproteins (P-gps) pH, 114 Phagocytes, 16, 52 Phaseolus vulgaris, 216 Phenanthrene, 40, 179, 188, 275, 305, 306 Phenol, 13, 35, 53, 64, 65, 77, 392 Phenoloxidase (POX), 53, 54 Phenotypic variability, 348 Pheromone, 63, 73, 79 Philodina roseola, 320 Phlorotannins, 16, 26 Phosphorus, 217, 312 availability, 364 deficiency, 248, 315 Photoactivation, 7 Photodamage, 61, 64, 65 Photodynamic, 7 Photoreduction, 12 Photorespiration, 14, 111, 170, 252 Photosensitization, 7, 11 Photosynthesis, 1, 7, 15, 16, 51, 52, 65, 66, 111, 169, 170, 174, 175, 226, 230, 252, 253, 257, 328, 398 Photosynthetic activity, 10, 11, 26 Photosynthetic electron transport (PET), 12, 14 Phototaxis, 57 Phototrophs, 7, 35, 196, 229, 328 Physical activity, 32, 108 Physical stress, 280, 283, 295, 313, 371 Physical trigger, 311 Phytochelatin (PC), 22, 134, 135, 141, 143, 150, 153, 157, 183, 259 Phytochelatin synthase (PCSI), 134, 150, 183

474 Phytohormone, 28, 48, 63, 77, 173, 175, 179, 228, 328, 389, 394 Phytomonas, 21 Phytoplankton, 10, 11, 33, 35, 44, 50, 229, 353 Phytoremediation, 155, 309, 318 Phytotoxicity, 156 Picea sitchensis, 260, 261 Pieris, 99 Pieris rapae, 175, 176, 229, 261 Pigmented prey, 11 Pigments, 7, 12, 154, 250 Pimephales promelas, 203 Pinus P. contorta, 63 P. sylvestris, 235 Pirata piraticus, 155 Pissodes strobe, 260 Pisum sativum, 226, 312, 313 Pityogenes chalcographus, 97 Plankton, 43, 45, 50, 358, 361, 363, 364, 366 integrity, 363 Plantago lanceolata, 209 Plant-insect interaction, 66 Plant-metal partitioning, 155, 156 Plant secondary metabolites (PSM), 24, 26, 61, 65–67, 71, 72, 74, 77, 80, 87, 88, 94, 97, 99, 152, 252, 269, 331, 370, 399 Plasma membrane, 14, 15, 27, 34, 38, 68, 142, 148, 151, 170, 257, 394, 397 Plasticity, transgenerational, 325 Platichthys flesus, 203 Plecoglossus altivelis, 262 Plumbaginaceae, 79 Plutella xylostella, 66 Poaceae, 155–157, 254 POD. See Peroxidase (POD) Podostemum ceratophyllum, 98 Polychaetes, 361, 388 Polycyclic aromatic hydrocarbons (PAHs), 40, 73, 95, 178, 188, 297, 392 Polymorphus minutes, 274 Polymorphus paradoxus, 57 Polynucleobacter necessarius, 10 Polyphenol, 24, 31, 43, 67, 77, 80–82, 108, 290, 331, 333, 338 Polysaccharide, 155, 393 sulfated, 25 Polyunsaturated fatty acid (PUFA), 13, 20, 24, 26, 38, 84, 339, 341 Pomphorhynchus laevis, 57 Pomphorhynchus minutus, 57

Index Population, 33–35, 47, 53, 57–59, 88, 93, 99, 100, 104, 105, 124, 127, 137–139, 155, 172, 202, 206, 208–211, 221, 225, 233, 234, 237, 239–241, 256, 276, 278, 281, 283, 294, 302–304, 306–308, 323, 345, 346, 348, 356, 360, 366, 369, 372–376, 378–381, 384, 386 density, 32, 107, 296, 297, 335, 363, 397 dynamics, 58, 206, 305 growth, 11, 296 growth rate, 206, 207, 306, 357 structure, 4, 5, 308, 325 Populus P. euphratica, 215 P. tremula, 215, 216 P. tremuloides, 170 P. trichocarpa, 144 P. trichocarpa, 216 Porcellio scaber, 299 Porphyridium, 25 POX. See Phenol oxidase (POX) Predation, 32, 40, 107, 108, 120–122, 162, 229, 248, 297, 298, 302–304, 307, 357, 366, 369, 374, 386 pressure, 124, 308, 361 risk, 123, 124, 261, 304, 308, 371 size-selective, 308 Predator, 5, 42, 43, 71, 75, 78, 80, 90 Pristionchus pacificus, 72, 73 Procambarus clarkii, 248 Procambarus spiculifer, 97, 98 Programmed cell death, 12, 28, 29, 33, 35, 38, 44, 47–49, 51 Proline, 16, 24, 25, 226, 245, 251 Pro-longevity genes, 332 Properties, 358, 369 allometric, 357 anti-aging, 328 fluorescence, 328 morphometric, 353 soil, 318 structural, 387 Prophenoloxidase, 53 Prorocentrum minimum, 11 Protein carbonylation, 26 Protein carbonyls, 28, 31 Protein damage, 41, 130, 201, 233 Protein kinase, 171 Protein level, 151, 163, 220, 246, 249, 254, 269, 270 Protein phosphatase, 85, 176, 203, 266, 291

Index Proteomics, 5, 161, 241, 246, 248, 250, 253, 254, 260, 263, 266, 270, 272–276, 278 Proteus, 390 Pseudokirchneriella subcapitata, 43, 307, 324, 340, 343, 372 Pseudomonas, 390 Pseudomonas aeruginosa, 312 Pseudomonas syringae, 315, 371 PSM. See Plant secondary metabolites (PSM) Pterostichus oblongopunctatus, 299 PUFA. See Polyunsaturated fatty acid (PUFA) Pyrene, 95, 190, 299 Pyrethroid, 83, 103–105, 207, 355 resistance, 104, 106 Pyrococcus furiosus, 243 Q Quality index, 345, 350 Quercetin, 80, 83, 84, 333 R Radiation, 211 Rana R. arvalis, 297, 302 R. catesbeiana, 296 R. clamitans, 296 R. pipiens, 296 R. sphenocephala, 296 R. sylvatica, 218 R. temporaria, 297, 302–304 Raphanus raphanistrum, 229 Rat, 283 Reactive nitrogen species (RNS), 12, 16, 19, 52 Reactive oxygen species (ROS), 4, 8, 9, 12–16, 18, 19, 21, 22, 25, 26, 29, 30, 34, 35, 45, 49–52, 64, 65, 76, 84, 169, 180, 198–200, 248, 251, 253, 256, 257, 259, 262, 264, 266, 315, 316, 328, 331, 386 metabolism, 29, 208 production, 21, 22, 28, 29, 49, 152, 269 scavenging, 17, 19, 28, 29, 33, 200, 256, 259, 317 Receptor, 41, 53, 69, 70, 82, 94, 95, 133, 152, 161, 170, 183, 184, 188, 198, 238, 294, 332 Recombination, 381, 384, 385 sexual, 384 Reduction of oxygen, 12 Renibacterium salmoninarum, 125

475 Re-oxygenation, 31, 35 Reproduction, 1, 10, 41, 52, 59, 63, 102, 116, 126, 155, 158, 187, 188, 191, 192, 200, 206, 208, 220, 230, 238, 250, 267, 281, 284, 289, 299, 300, 308, 325, 332, 335, 338, 339, 341, 342, 354, 357, 367, 372, 374, 385, 386 Resistance, 29, 48, 49, 52, 88, 89, 99–101, 103, 121, 143, 152, 158, 174, 177, 210, 306, 311, 315, 328, 333, 371, 378, 379 adaptative, 211, 240 antibiotic, 390 chemotherapeutic drugs, 394 cyanotoxin, 390 cold, 215, 323 DDT, 104–106 digestion, 42 disease, 315 drought, 394, 395, 399 drug, 394 genes, 174 heat, 323 herbicide, 391 herbivory, 307 host, 308, 318 insecticide, 271, 390 metal, 380, 395, 397 multidrug, 395 oxidative stress, 331 pathogen, 53, 55, 152, 308, 315, 317, 371, 398 Pb, 398 pesticide, 94, 102, 104, 384 phase, 1, 180 plants, 30, 49, 111, 151, 214, 308, 317 proteins, 75, 387 salt, 394, 399 toxins, 397 UV, 38, 89 xenobiotica, 311 Respiration, 15, 42, 61, 66, 166, 215, 253, 264, 357, 358, 361, 366 aerobic, 166 anaerobic, 166 Resveratrol, 80, 338 Rhinanthus minor, 52 Rhodamine B, 90, 92 Rhodococcus, 390 Rhodococcus opacus, 312 Rhodomonas salina, 44 River Continuum Concept (RCC), 352 RNA interference, 148, 226, 240, 332 RNA polymerase, 111, 314

476 RNS. See Reactive nitrogen species (RNS) ROS. See Reactive oxygen species (ROS) rpoH gene, 111 rpoS, 314 R-proteins, 125 S SA. See Salicylate; Salicylic acid Saccharomyces, 384 Saccharomyces cerevisiae, 80, 312, 315, 385, 391 Salicornia europaea, 252, 253 Salicylate (SA), 48, 49 Salicylic acid (SA), 28, 29, 35, 66, 154, 175–177, 180, 228, 266, 317 Salinity, 32, 72, 79, 108, 111, 112, 162, 166, 171, 239, 241, 242, 252, 258, 261, 323, 372, 386 Salmo salar, 116, 297 Salt, 79, 111, 112, 165, 167, 169, 214–216, 221, 228, 247, 252, 259, 297, 299, 309, 312, 313, 321, 323, 324, 360, 371 stress, 25, 169, 173, 215, 221, 228, 242, 250, 252–254, 258, 394, 395, 399 Saprobization, 350 Saprolegnia parasitica, 292 SAR. See Systemic acquired resistance (SAR) Sasa borealis, 141 Scallops, 125 Scenedesmus obliquus, 230 Schistosoma mansoni, 124 Schizocosa ocreata, 349 Scrobicularia plana, 248 Scylla serrata, 55 Seagrass, 300, 301 Seawater, 40, 112, 166 Sediments, 72, 301, 348, 353, 354 contaminated, 31, 354 Elbe, 192, 194–196 Rhine, 192, 193, 195 river, 191 Selection, 59, 81, 105, 137, 139, 192, 208, 233, 234, 306, 373, 375, 376, 378, 380, 381, 384, 385 natural, 211, 228, 232, 237, 240, 376, 385 pressure, 104, 121, 270, 373, 374 sexual, 348 Selenium (Se), 140, 141 Self-defense, 71, 151 Self-intoxification, 94 Self-protection, 67, 71

Index Semiquinones, 12 Senescence, 66, 185, 328 leaves, 327, 328 plants, 328, 372 premature, 328 Sensitization, 8 Sensitizer, 8 Sensor, 161, 173, 183 Sericostoma vittatum, 298 Serratia, 390 Sesbania drummondii, 141 Sex determination, 58 Shewanella oneidensis, 166, 167 sHSP. See Small heat-shock protein (sHSP) Silver (Ag), 140, 201 Simocephalus vetulus, 299 Singlet oxygen, 7, 10, 12, 13 siRNA. See Small interfering RNA (siRNA) Sirtuin, 80, 94 Size, 302, 304, 308 Size body, 283, 303, 342, 355, 357, 358, 361, 363 Size class, 357, 358, 360, 361, 367 biomass, 356 Size spectra, biomass, 358, 361, 363, 364, 366 Skeletoneman costatum, 282 Small heat-shock protein, 110, 114–116, 118, 257, 259, 260, 321, 322, 331, 386 Small interfering RNA (siRNA), 113, 172, 213, 226, 231 SO2, 313 SOD. See Superoxide dismutase (SOD) SOD3, 41, 207 Solanaceae, 155, 157 Solar irradiation, 166 Solea solea, 379 Sparus aurata, 262, 263 Sparus sarba, 125 SPEAR. See SPEcies At Risk (SPEAR) Speciation, 372 SPEcies At Risk (SPEAR), 345, 350, 355 SPEARorganic, 355, 356 SPEARpesticides, 355 Spinochordodes tellinii, 272, 274 Spodoptera S. exempta, 53, 54 S. frugiperda, 105 S. littoralis, 54, 105, 175, 176 S. litura, 55, 84 ss dependent genes, 165, 314 sS proteolysis, 314 sS regulation, 311, 314

Index sS synthesis, 314 sS system, 111 Staphylococcus, 281 Starvation, 54, 80, 93, 108, 162, 165, 173, 185, 312–314 Stilbene, 66 Streptomyces, 19 Stress cold, 171 defense, 4, 370 gene, 1, 148, 149, 165, 297, 298, 383 oxidative, 333 phase model, 1 proteins, 327, 329 response, 327, 334, 335 social, 162, 205 thermal, 25, 34, 116, 117, 333 UV, 272 Stress-hardening, 127 Stress proteins, 2, 107, 110, 119, 121, 123, 124, 127, 165, 243, 265, 311, 320, 371, 386 Stress resistance, 4, 34, 78, 80, 117, 120, 127, 153, 215, 223, 225, 233, 284, 323, 327, 328, 334, 371, 372 genes, 29 oxidative, 220–222, 324 thermal, 283 Stress response, 1, 5, 10, 36, 42, 43, 71, 81, 103, 110, 114, 119, 121, 123, 126, 129, 131, 133, 148, 151, 161, 164–169, 171, 172, 174, 183, 187, 190, 206, 216, 225, 244, 245, 250, 255, 260, 262, 265–267, 269, 271, 278, 323, 369, 370, 378, 381, 386, 395 abiotic, 12, 171, 173, 196 actual, 4 biotic, 179, 196 cellular, 110, 242, 243 cold, 252 core, 169 dehydration, 250 early, 169 epigenetic, 226 genes, 102, 186, 200 heat, 113, 114, 181 hypoxic, 269 initial, 181, 252 non-constant, 284 non-specific, 370 oxidative, 165, 179 pathways, 82 plant, 172, 215

477 population, 206 universal, 5 Stress-specific response, 167, 370 Stress tolerance, 102, 116, 138, 148, 157, 173, 227 abiotic, 29 evolution of, 164 mechanisms, 157 plant, 328, 372 salt, 79 yeast, 164 Strix aluco, 375 Strombidinopsis acuminatum, 11 Strongylocentrotus purpuratus, 71, 183, 380 Substances, 284 Substrate deprivation, 312 Succession, 45, 308, 353 Sulfation, 74, 78 Sulfolobus solfataricus, 73, 164, 249 Sulfotransferase, 62, 72, 78, 88 aryl, 265 Sulfur, 22, 75, 135, 141, 150, 153, 217 metabolism, 153, 291 Sulfuration, 134 Sulfurispharea, 278 Sulfurylases, 214 SULT, 72, 77, 78 SUMOylation, 244 Superfund, 94, 99–101, 211, 238–240, 375, 383 Superoxide dismutase (SOD), 13–15, 17–19, 33, 49, 111, 112, 135, 136, 150, 165, 198–200, 243, 245, 249, 257, 259, 321 Superoxide radical, 12–14, 17, 19 Surfactant, 298 synthetic, 356 Survival, 32, 41, 67, 81, 84, 89, 93, 113, 116, 120, 123, 126–128, 139, 155, 158, 190, 191, 205, 206, 252, 265, 283, 293, 297–300, 305, 313, 315, 323, 325, 329, 335, 346, 355, 357, 373, 376, 383, 386 Symbiosis, 32, 72, 248, 369, 395, 398 Symphysodon aequifasciata, 264 Synechococcus/Synechocystis, 363 Synechococcus elongatus, 392 Synthetic hormone, 383 Synthetic xenobiotics, 283, 375 Systemic acquired resistance (SAR), 48, 49, 180, 317 Systemic resistance, 315 Systemic signaling, 12, 317, 318 System integrity, 354, 357

478 T Tail fin, 302, 303 Talitrus saltator, 348 Tannic acid, 84, 283, 284, 290–292, 338 Tannins, 24 Taraxacum officinal, 227 TATA box, 164, 383, 384 Taurine, 339 Temperature, 32–34, 51, 66, 111, 114–117, 127–129, 181, 183, 186, 233, 239, 247, 262, 270, 278, 284, 296, 297, 299, 305, 323, 335, 353, 365, 374, 376, 386 changes, 373 elevated, 299 extremes, 299 fluctuations, 374 lethal, 381 optimal, 114, 295, 342, 343 stress, 251 sub-optimal, 342 sub-zero, 130 super-optimal, 342 unfavorable, 386 water, 114 winter, 262, 375 Terpenoid defense, 63 Terpenoids, 62, 63, 82 Testosterone, 239 Tetranychus urticae, 105 Thalassiosira weissflogii, 38, 39, 141 Thaumatococcus daniellii, 259 Thellungiella, 254 Thellungiella halophila, 148, 242, 253 Theory of aging, 327 Thermosynechococcus elongatus, 392 Thermotolerance, 113, 116, 126, 128–130, 262, 331, 381 Thioglucosides, 78 Thioredoxin peroxidase, 15, 264 Thlaspi T. caerulescens, 140 T. goeingense, 154 T. rotundifolium, 141 Time to death, 299 Titanium (Ti), 201 Tobacco, 49, 84, 150, 152, 226, 234, 271, 313, 315, 397 Tobacco mosaic virus, 315 Tocopherol, 16, 19, 23, 24, 27, 328 Tocopheroxyl radical, 23, 24 Tocotrienol, 23

Index Tolerance, 5, 80, 97, 158, 171, 378 abiotic, 171 abiotic stress, 308 acid, 302 allelochemicals, 82, 89, 105 Cd, 137, 143, 399 cold, 251, 271 desiccation, 185, 319, 320 drought, 141 freezing, 218, 251 heat, 116, 314 heavy metal, 131, 137–141, 143 herbivory, 66 insecticides, 76 limits, 295, 301 low oxygen, 350 mechanisms, 52 metals, 132, 141, 152, 396 microcystin, 84, 86, 266 multigenerational, 100 Ni, 154 pathogen, 316 pesticide, 383 pH, 44 population, 101 salt, 111, 222, 226, 252, 254 strategy, 132, 157 temperature, 323 UV, 171 Tomatoes, 84, 218 Toxicity, 100, 150, 268, 296, 299 cellular, 133 ions, 152 mammalian, 105 mechanism, 146 mercury, 200, 269 metal, 38, 119, 132, 133, 151, 155, 375 metal ions, 319 mitochondrial, 17 oxygen, 165 Transcription, 2, 5, 42, 49, 52–54, 71, 87, 89, 94, 107, 109, 111, 113, 121, 129, 136, 137, 141, 150, 161, 164, 169, 171, 173–175, 177, 180, 181, 190, 196, 198, 203, 206, 207, 214, 231, 239, 244, 246, 250, 253, 268, 275, 283, 289, 294, 297, 307, 397 activator, 328 changes, 191 factor, 29, 171, 172, 183, 184, 190, 215, 251, 258, 309, 333 metal, 184 factors, 138, 149, 231–233, 240, 397 inducer, 178

Index level, 254 plasticity, 164 profile, 135, 179, 191, 252 regulation, 137, 139, 244, 248 regulator, 169 repressor, 84, 169 response, 135, 146, 179, 183, 189, 196 Transformation, 67, 331 conjugative, 67 hydrolytic, 67 oxidative, 67 reductive, 67 Transgenerational effect, 219–221, 226, 230, 237, 239, 240 Translation, 206, 250, 275 Transmission, 57, 58, 105, 124, 308 Transparent heterotroph, 11 Transporters, 90, 249, 265, 370 ABC, 90, 92, 143, 180, 245, 393, 394, 395, 396, 397, 398 ABCC, 394 amino acid, 209 ATM, 399 efflux, 91, 394 export, 77 half-molecule, 398 heavy-metal, 146, 147, 397 iron, 135 iron-regulated (IRT), 143, 395 ligand, 143 MDR/MXR, 90 membrane-, 201 metal, 151 monocarboxylate, 197 MRP, 396 multidrug, 89, 90 multidrug efflux, 183 neurotransmitter, 291 phosphate, 215 proteins, 67, 278 steroid, 203 transmembrane, 291 uptake, 77 zinc-regulated (ZRT), 143, 395 ZIP, 143 Zn, 148 Transposon, 104, 226, 237, 381 Trematomus bernacchii, 90, 130 Triazine, 103 Trichoplusia ni, 105 Trifolium, 157 Trigger, 5, 6, 32, 33, 49, 53, 61, 71, 84, 118, 120, 183, 250, 370, 371, 373, 374, 379, 383, 386

479 Trinitrotoluene, 290 Triops australiensis, 322 Triops cancriformis, 322 Triplet oxygen, 12 Triticosecale, 312, 313 Triticum aestivum, 171, 172 Tritonia hamnerorum, 92 Trophic dynamics, 357 Trophic parabola, 364 Trypanosoma, 21 Trypanosoma brucei brucei, 274 U Ubiquinone, 13 Ubiquitin, 130, 172, 186, 197, 201, 215, 244 Ubiquitination, 189, 203, 244, 245 UDP-glucosyltransferase, 77, 89 UGT, 64, 71, 72, 77, 79, 89, 190 Urea, 261, 313, 339 Uridine 5’-diphosphate (UDP), 77 UV-B irradiation, 66, 171, 215, 217, 251 UV irradiation, 10, 25, 26, 65, 66, 72, 89, 108, 162, 170, 183, 200, 225, 273, 313, 316 V Vacuole, 16, 22, 64, 142–145, 396, 397 food, 11 Veronica spicata, 209 Vibrio, 312 V. alginolyticus, 125 V. anguillarum, 125 V. campbelli, 371 V. parahaemolyticus, 312, 314 Vigna unguiculata, 300 Vinclozolin, 383 Viola tricolor, 375 Vitamin E, 23, 24, 338 Vitellogenin, 200, 203, 204, 209, 210, 267, 268 Volvox, 384 Volvox carteri, 386 Vulnerability, 58, 117 W Water replacement hypothesis, 320 Water-water cycle, 17, 18 WBC11, 147 wMT–1, 134 wMT–2, 134 wMT–3, 134

480 Wounding, 63, 108, 317 mechanical, 41, 79, 260, 261 X Xanthine oxidase (XO), 13, 15 Xenobiotics, 22, 68, 72, 77, 99, 102, 391, 394, 396 chlorinated, 393 natural, 31, 68, 72, 78, 81, 94, 102, 108, 118, 162, 180, 203, 220, 247, 257, 283, 295, 307, 331, 370, 371, 390 synthetic, 31, 61, 68, 72, 73, 77–79, 89–91, 94, 95, 99, 101, 108, 119, 162, 187, 191, 237, 238, 247, 266, 267, 270, 275, 295, 371, 390 Xenohormesis, 67, 80, 81 Xiphophorushelleri, 313 Xiphophorus helleri, 322, 324 Xiphophorus nigrensis, 205 XO. See Xanthine oxidase (XO)

Index Y Yarrowia, 21 Yeast, 19, 21, 42, 43, 80, 121, 122, 164, 169, 196, 233, 238, 279, 282, 307, 311, 384, 385, 388, 397 Z Zea mays, 216, 226, 257, 258, 313 Zebrafish, 78, 90, 119, 181, 183, 198, 200–205, 207, 265, 266, 268, 297 Zinc (Zn), 13, 133, 134, 140, 144, 148, 149, 154, 155, 201, 238, 299, 313, 319, 375, 397 Zinc finger, 169 ZIP, 143, 144, 395, 397 ZIP3, 147 ZIP12, 147 Zn. See Zinc (Zn) Zoarces viviparous, 27 Zooplankton, 25, 58, 229, 308, 360, 364 Zostera noltii, 300