Advances in Microbial Physiology Volume 41

Advances in

MICROBIAL PHYSIOLOGY VOLUME 41

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Advances in

MICROBIAL PHYSIOLOGY Edited by

R. K. POOLE Department of Molecular Biology and Biotechnology The Krebs Institute f o r Biomolecular Research The University of Shefield Firth Court, Western Bank Shefield SIO 2TN, UK

Volume 41

ACADEMIC PRESS A Harcaurt Science and Technology Company

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Contents

CONTRIBUTORS TO VOLUME 41 .................................

ix

Factors Affecting the Production of L-Phenylacetylcarbinol by Yeast: A Case Study Alison L. Oliver. Bruce N . Anderson and Felicity A. Roddick Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2 . Biochemical production of L-phenylacetylcarbinol . . . . . . . . . . . . . . 4 3. Development and optimization of the fermentation process . . . . . . 11 4 . An industrial process for the production of L-phenylacetylcarbinol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 5. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

Fungal Production of Citric and Oxalic Acid: Importance in Metal Speciation. Physiology and Biogeochemical Processes Geoffrey M . Gadd 1. 2. 3. 4.

5. 6. 7. 8.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 Metal chemistry of oxalic and citric acids . . . . . . . . . . . . . . . . . . . . 50 Fungal biosynthesis of oxalic acid and calcium oxalate formation . 53 Role of metals and oxalate in lignocellulose degradation and plant pathogenesis ...................................... 61 Catabolism of oxalic acid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 Fungal biosynthesis of citric acid . . . . . . . . . . . . . . . . . . . . . . . . . . 65 Fungal organic acid production and metal biogeochemistry . . . . . . 68 Fungal organic acid production and metal biotechnology . . . . . . . . 76

vi

CONTENTS

Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

78 79

Bacterial Viability and Culturability Michael R. Barer and Colin R. Harwood 1. 2. 3. 4. 5. 6. 7.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 Definitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 The ‘viable but non-culturable’ (VBNC) hypothesis . . . . . . . . . . . . 96 ‘As yet uncultured’ (AYU) bacteria . . . . . . . . . . . . . . . . . . . . . . . . . 99 ‘New’methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102 Factors influencing the outcome of culturability tests . . . . . . . . . . 1 1 1 Should bacterial viability be assessed at the individual or community level? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122 8. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124 Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126

The Histidine Protein Kinase Superfamily Thorsten W. Grebe and Jeffry B . Stock 1. 2. 3. 4.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Histidine protein kinase subfamilies . . . . . . . . . . . . . . . . . . . . . . . Cognate receiver domains . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Domain shuffling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

139 197 206 211 214 214

Bacterial Tactic Responses Judith P. Armitage Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 231 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 231 2 . What is meant by ‘bacterial taxis’? ........................ 232 3 . History . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233 4 . How Bacteria swim and glide . . . . . . . . . . . . . . . . . . . . . . . . . . . . 235 5. The chemosensory pathway of E . coli ...................... 238 6. Responses to electron acceptors and light . . . . . . . . . . . . . . . . . . .263 7 . What is the role of tactic responses in natural environments? . . . .269 8 . Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 277 Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 277 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 278

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CONTENTS

The Bacterial Flagellar Motor

Richard M . Berry and Judith P. Armitage Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2. The flagellar structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3. Flagellar motor function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4. Models of the flagellar motor . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

292 292 296 310 322 328 329 329

Authorindex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Subject index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

339 363

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Contributors to Volume 41

Bruce N. ANDERSON, Department of Chemical and Metallurgical Engineering, Royal Melbourne Institute of Technology University, GPO Box 2476V, Melbourne, Victoria 3001, Australia ([email protected]) Judith P. ARMITAGE, Microbiology Unit, Department of Biochemistry, University of Oxford, South Parks Road, Oxford OX1 3QU, UK ([email protected]) Michael R. BARER, Department of Microbiology and Immunology, The Medical School, University of Newcastle-upon-Tyne, Framlington Place, Newcastle-upon-Tyne NE2 4HH, UK ([email protected]) Richard M. BERRY, The Randall Institute, King’s College London, 26-29 Drury Lane, London WC2B 5RL, UK Geoffrey M. GADD,Department of Biological Sciences, University of Dundee, Dundee DD 1 4HN, UK ([email protected]) Thorsten W. GREBE, Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA ([email protected]) Colin HARWOOD, Department of Microbiology and Immunology, The Medical School, University of Newcastle-upon-Tyne, Framlington Place, Newcastle-upon-Tyne NE2 4HH, UK CSL Limited, 45 Popular Road, Parkville 3052, Alison L. OLIVER, Australia

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CONTRIBUTORS TO VOLUME 41

Felicity A. RODDICK, Department of Chemical and Metallurgical Engineering, Royal Melbourne Institute of Technology University, GPO Box 2476V, Melbourne, Victoria 300 1, Australia ([email protected]) Department of Molecular Biology, Princeton University, Jeffry B. STOCK, Princeton, NJ 08544,USA ([email protected])

Factors Affecting the Production of L-Phenylacetylcarbinol by Yeast: A Case Study Alison L. Oliver, Bruce N. Anderson and Felicity A. Roddick Department of Chemical and Metallurgical Engineering, RMIT University. GPO Box 2476V Melbourne, victoria 3000, Australia

ABSTRACT

L-Phenylacetylcarbinol (L-PAC)is the precursor for L-ephedrine and Dpseudoephedrine, alkaloids possessing a-and 0-adrenergic activity. The most commonly used method for production of L-PAC is a biological method whereby the enzyme pyruvate decarboxylase (PDC) decarboxylates pyruvate and then condenses the product with added benzaldehyde. The process may be undertaken by either whole cells or purified PDC. If whole cells are used, the biomass may be grown and allowed to synthesize endogenous pyruvate, or the cells may be used as a catalyst only, with both pyruvate and benzaldehyde being added. Several yeast species have been investigated with regard to L-PACproducing potential; the most commonly used organisms are strains of Sacchuromyces cerevisiue and Cundidu utilis. It was found that initial high production rates did not necessarily result in the highest final yields. Researchers then examined ways of improving the productivity of the process. The substrate, benzaldehyde, and the product, L-PAC,as well as the by-products, were found to be toxic to the biomass. Methods examined to reduce toxicity include modification of benzaldehyde dosing regimes, immobilization of biomass or purified enzymes, modification of benzaldehyde solubility and the use of twophase reaction systems. Various means of modifying metabolism to enhance enzyme activity, relevant metabolic pathways and yield have been examined. Methods investigated include the use of respiratory quotient to influence pyruvate production and induce fermentative activity, reduced aeration to increase PDC activity, and carbohydrate feeding to modify glycolytic enzyme activity. The effect of temperature on L-PACyield has been examined to identify conditions ADVANCES IN MICROBIAL PHYSIOLOGY VOL 41

ISBN 0-12-027741-7

Copyright 0 1999 Academic Press All rights of reproduction in any form reserved

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ALISON L. OLIVER, BRUCE N. ANDERSON AND FELICITY A. RODDICK

which provide the optimal balance between L-PAC and benzyl alcohol production, and L-PAC inactivation. However, relatively little work has been undertaken on the effect of medium composition on L-PACyield. Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2. Biochemical production of L-phenylacetyl carbinol ....................... 2.1. Mechanism of L-PACproduction ...................... 2.2. Pyruvate decarboxylase and provision of substrates . . . . . . . . . . . . . . . . . . 2.3. Alcohol dehydrogenase and reaction by-products .................... 3. Development and optimization of the fermentation process . . . . . . . . . . . . . . . 3.1. Selection of a high-yielding producer organism ...................... 3.2. Physicochemical conditions and their effect on L-PACproduction . . . . . . . 3.3. Physiological condition of cells for optimum L-PAC production . . . . . . . . . 3.4. Nutrient effects in L-PAC production ............................... 3.5. Production of L-PACby batch, fed-batch or continuous fermentation . . . . 3.6. The use of additives to modify metabolic activity .................... 3.7. Reduction of the toxic effects of substrate, product and by-product . . . . . 3.8. Other methods for influencing L-PACproduction ..................... 4. An industrial process for the production of L-phenylacetylcarbinol . . . . . . . . . . 5. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2 3 4 4 6 9 11 12 13 16 18 20 21 23 33 34 39 40

ABBREVIATIONS

ADH BCD CSL 2,4-D DMF Ki kl'a

Km L-PAC NAA PCO, PDC PEG PO, RQ TPP YADH

Alcohol dehydrogenase P-Cy clodextrin Corn steep liquor 2,4-Dichlorophenoxy acetic acid N,N-Dimethylformamide Inhibition constant - the concentration of a compound at which a reaction is inhibited by 50% Volumetric liquid mass transfer coefficient for oxygen Michaelis constant - the substrate concentration at which the reaction velocity is 50% of its maximum L-Phenylacetylcarbinol a-Naphthoxy acetic acid Partial pressure of carbon dioxide (millibar) Pyruvate decarboxylase Polyethylene glycol Partial pressure of oxygen (% saturation) Respiratory quotient Thiamine pyrophosphate Yeast alcohol dehydrogenase

THE PRODUCTION OF L-PHENYLACETYLCARBINOLBY YEAST

3

1. INTRODUCTION

L-Phenylacetylcarbinol (L-PAC)is used as a substrate in the manufacture of Lephedrine and D-pseudoephedrine, alkaloids possessing a-and P-adrenergic activity (Long and Ward, 1989b). Ephedrine is used in the treatment of conditions including hypotension and asthma, while pseudoephedrine, an optical isomer of ephedrine, is used mainly as a nasal decongestant in cold and influenza medications. These alkaloids can be produced by one of two methods: direct extraction from plant material (Ephedra spp.) or synthesis using L-PAC as a precursor. Until early this century, plant material was the sole source of both ephedrine and pseudoephedrine; however, the total alkaloid content in Ephedra spp. is generally low, the highest concentration being approximately 2.5% by weight, and occurs as a mixture of ephedrine and pseudoephedrine. The alkaloid content is also subject to seasonal variation, requiring the collection of large amounts of plant material followed by time- and labour-intensive processing (Morton, 1977). In contrast, the synthesis of ephedrine or pseudoephedrine via L-PACis less labour intensive and independent of climatic conditions, enabling a continuous supply of product of guaranteed quality. While there are several chemical methods for L-PAC synthesis (Culik et al., 1984; Nikolova et al., 1991), the usual method of production is via yeast fermentation. Production via fermentation is preferable to chemical synthesis because of the mild conditions used, and because the pharmacologically active laevorotatory form (L-PAC) is produced whereas chemically synthesized PAC is a racemic mixture (D-PACand L-PAC).D-PACcannot be used to prepare L-ephedrine or D-pseudoephedrine. In addition, the waste products of other processes, e.g. molasses, can be used as raw materials in the L-PAC fermentation medium, after which the spent broth is amenable to biological waste treatment. The final ephedrine and pseudoephedrine concentrations produced by synthetic routes are similar to those present in plant extracts. This review is divided into three sections: first in the specific processes involved in the conversion of benzaldehyde to L-PAC are examined and the background on the enzymes involved in the process is provided; in the second the effects of manipulating fermentation parameters on yeast behaviour are examined; and in the third an industrial process used for the production of LPAC is outlined (Oliver et al., 1997).

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ALISON L. OLIVER, BRUCE N. ANDERSON AND FELICITY A. RODDICK

2. BIOCHEMICAL PRODUCTION OF LPHENYLACETYLCARBINOL 2.1. Mechanism of L-PACProduction

The biochemical production of L-PAC was first demonstrated in the early 1920s by Neuberg and co-workers who described its formation after the addition of benzaldehyde to a culture of actively fermenting top yeast (McKenzie, 1936). They proposed two possible mechanisms: the first, thought to be the most likely of the two scenarios, was the conversion of pyruvate by carboxylase to an activated acetaldehyde followed by the enzymic combination of benzaldehyde and the activated acetaldehyde by carboligase; the second proposal was the joining of benzaldehyde and pyruvate via a carboligase, followed by decarboxylation of the complex using carboxylase (McKenzie, 1936). Pyruvate decarboxylase (PDC) is now known to be responsible for both nonoxidative decarboxylation and a carboligase reaction, which results in the production of a-hydroxy ketones (Pohl, 1997). The production of L-PACby yeast was considered to be analogous to the production of acetoin (methylacetylcarbinol)which was demonstrated by Green el al. in 1942 using a crude yeast enzyme extract. Weight was added to the hypothesis that acetaldehyde was an intermediate in the production of acetoin when Gross and Werkman ( 1947) demonstrated the incorporation of isotopically labelled acetaldehydeinto acetoin by a dried yeast ‘juice’.Acetoin was not considered to be a normal fermentation product by Happold and Spencer (1952), although it is a known product of wine yeast fermentation (Romano and Suzzi, 1996).Happold and Spencer’s proposal is supported by Hohmann (1997), who suggested that the production of acetoin is ‘probably not important under physiological conditions,’owing to the low concentrations of acetaldehyde present in yeast cytosol. Happold and Spencer found that the presence of additional acetaldehyde resulted in the formation of acetoin. Green et al. (1942) found that the production of significant quantities of acetoin required the presence of both acetaldehyde and pyruvate rather than either in isolation. The role of a single enzyme for the production of acetoin was advanced by Juni (1952) who was unable to separate his brewer’s yeast extract into separate fractions for pyruvate decarboxylation and for acetoin formation. He later introduced the concept of a two-site mechanism for the formation of acetoin (Juni, 1961). Although it was previously assumed that PDC catalysed the condensation of benzaldehyde and pyruvate to L-PAC,confirmation did not occur until BringerMeyer and Sahm (1988) demonstrated the production of L-PACby purified PDC from both Zymomonas mobilis and Saccharomyces carlsbergensis. Their results were confirmed by Cardillo et al. (199 I ) who showed that benzaldehyde was condensed more readily than other substituted aldehydes by

5

THE PRODUCTION OF L-PHENYLACETYLCARBINOLBY YEAST

Saccharomyces spp. Although Fuganti et al. (1988) questioned whether the enzyme responsible for L-PAC production was known, they reconfirmed the ability of baker's yeast to produce L-PAC and considered the mechanism of LPAC production to be analogous to the production of acetoin, thereby implying that PDC was essentially responsible for L-PACproduction. Crout et al. (199 1) provided definitive proof of the ability of purified yeast PDC to convert a range of aldehydes to ketols, including L-PAC, by following the reactions using 'H-nuclear magnetic resonance (NMR) spectroscopy. Kren et al. (1993) also demonstrated the production of various ketols by purified yeast PDC. PDC, located in the cytosol, catalyses the irreversible conversion of pyruvate to acetaldehyde with the resultant loss of a molecule of CO,. The reaction requires the cofactors thiamine pyrophosphate (TPP) and a magnesium ion, which is thought to act as a link between the apoenzyme and the thiamine pyrophosphate (Pohl, 1997).

CH,CHO + CO, Acetaldehyde

CH,COCOOH PYruvate decarboxY1ase, Pyruvate TTP, Mg2+

(1)

PDC then catalyses the condensation of acetaldehyde and pyruvate, forming acetoin:

,

CH,COCOOH + CH,CHO PDC CH,CHOHCOCH, Pyruvate Acetaldehyde p p , Mg2+ Acetoin

+ CO,

(2)

After the formation of acetaldehyde according to Equation 1, L-PAC is formed (analogous with Equation 2) by the condensation of acetaldehyde with added benzaldehyde:

,

CH,COCOOH + C,H,CHO PDC C6H,CHOHCOCH, Pyruvate Benzaldehyde p p , Mg2+ PAC

+ C02

(3)

L-PACis considered to be a product of the stationary phase of growth (Liew et al.,1995). In the process employed by Oliver et al. (1997), the pyruvate consumed in the reaction is generated by the yeast via glycolysis and is allowed to accumulate exogenously during the exponential phase of growth. Commercial processes are generally divided into two stages: a first stage where the yeast is grown and pyruvate is accumulated, followed by a bioconversion stage where benzaldehyde is added and L-PAC produced. For fermentations where pregrown yeast is used as a catalyst only, direct pyruvate supplementation is required in the bioconversion phase.

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ALISON L. OLIVER, BRUCE N. ANDERSON AND FELICITY A. RODDICK

2.2. Pyruvate Decarboxylase and Provision of Substrates

As described above, PDC is the enzyme responsible for the production of LPAC. PDC is usually found to exist as either dimers or tetramers whereby the active PDC holoenzyme generally exists as a tetramer, while the apoenzyme exists as a dimer (Pohl, 1997). The existence of the dimer and tetramer forms is pH dependent. In yeast, PDC has been reported to exist only as a tetramer in the pH range 5.5-6.5, as both tetramers and dimers at pH values up to 9.5, and dimers only at pH > 9.5 (Pohl, 1997). However, Hohmann (1997) has reported the existence of PDC only in the form of dimers at a pH of 8.4. PDC from 2. mobifis has been found to exist only in the form of tetramers (Pohl, 1997). While PDC subunits were thought previously to have different compositions, they are now known to be identical (Hohmann, 1997). A total of six PDC genes has been identified in Saccharomyces cerevisiae, of which three are structural genes (PDC 1, PDC5 and PDC6) and the remaining three are considered to be genes related to expression of PDC (PDC2, PDC3, PDC4) (Flikweert etal., 1996; Hohmann, 1997; Pohl, 1997; ter Schure et al., 1998).A single structural gene coding for PDC has been identified in 2. mobilis (Pohl, 1997). While the majority of work in this area appears to have been performed on S. cerevisiae, genes for PDC have been identified in a number of yeast species, not including Candida utilis. Flikweert and co-workers undertook studies to assess the role of each of the isoenzymes in overall PDC activity, and found that the expression of each of the isoenzymes in S. cerevisiae differed. Using batch culture with either ethanol or glucose as carbon substrate, PDC 1 was expressed constitutively while PDC5 was induced in the presence of glucose. PDC6 was present at insignificant levels. These findings were echoed in a review on pyruvate decarboxylases by Hohmann ( 1 997), who indicated that only PDC 1 and PDC5 played an apparent role in sugar catabolism, with 80-90% and 10-20% of total PDC activity being attributed to these two genes, respectively, for glucose-grown biomass. In addition to the production of acetoin, S. cerevisiae PDC has been found to be involved in the production of fuse1 oils, which are flavour compounds present in alcoholic beverages and bread. Fuse1 oils are produced by the decarboxylation of branched chain 2-0x0 acids, derived from aromatic amino acids. The products are then dehydrogenated by alcohol dehydrogenase (ADH). The activity of PDC with the 2-0x0 acids is significantly lower than for pyruvate (ter Schure et al., 1998). Production of novel aldehyde analogues is discussed later in this chapter. PDC activity can be induced and manipulated both by the degree of aeration supplied to the culture and by the choice of carbohydrate substrate in the medium. PDC activity is required to enable glycolytic flux only under anaerobic conditions; therefore, a reduction in aeration should result in the induction of PDC. Both Sims and co-workers (1991) and Rogers et al. (1997) have

THE PRODUCTION OF L-PHENYLACETYLCARBINOL BY YEAST

7

demonstrated that an increase in C. utilis PDC activity occurs when oxygen concentration is reduced. Such a response is highly beneficial for the production of L-PAC.However, both groups of researchers found that the activity of ADH, responsible for generation of unwanted by-products, exceeds that of PDC under anaerobic or partially anaerobic conditions. The effect of aeration conditions on yeast physiology is discussed later in this chapter. Induction of PDC activity by carbohydrate source is dependent on the yeast species involved and the carbohydrate source supplied. Glucose is one substrate capable of inducing glycolytic enzymes, especially PDC. A number of workers have demonstrated that the addition of glucose to cultures results in an increase in the level of PDC activity. Maitra and Lob0 (1971) found that the addition of glucose as a pulse to Saccharomyces spp. cultures resulted in an increase in the production of glycolytic enzymes, including PDC, following a short lag period. The medium used for growth was carbohydrate-free and acetate was used as the carbon source. Similarly, Schmitt and Zimmerman (1982) demonstrated an 18-fold increase in the PDC activity of S. cerevisiae after glucose was added to a shake flask culture grown on ethanol as the sole carbohydrate source. These results are in agreement with those of Harrison (1972) and Sims et al. (1991). Sims and co-workers also demonstrated the reversible nature of PDC activation. They showed that, under anaerobic conditions, when deprived of glucose (by centrifuging and resuspending biomass in glucose-free medium) the PDC activity of C. utilis was reduced by 50%. PDC activity was restored by the addition of glucose to the medium under anaerobic conditions; however, if the culture was aerated in addition to glucose supplementation, there was no change in PDC activity. Such enzyme activation does not occur for all carbohydrate types. When yeast species are grown anaerobically on glycosides which give the Kluyver effect, PDC activity is reduced compared with glycosides, such as glucose, which can be metabolized anaerobically (Sims and Barnett, 1991). As a result of their research, they found that PDC activity may be rate limiting in anaerobic conditions. This finding is in agreement with that of van Urk et al. (1989). PDC is a substrate-pyruvate-activated enzyme (Hubner et al., 1978; Hohmann, 1997), which is also allosterically inhibited by inorganic phosphate (Boiteux and Hess, 1970). Boiteux and Hess reported an increase in the Michaelis constant (K,) of purified PDC from S. carlsbergensis from 1.3 mM in the absence of inorganic phosphate to approximately 11 m~ in the presence of 100 nm phosphate. The inhibitory effect was determined to be competitive in nature, the variation in K , having no effect on the maximum activity of the enzyme. The sensitivity of PDC to inhibition by phosphate was determined to be of the same order of magnitude as its sensitivity to activation by pyruvate. Saccharomyces spp. and C. utilis are commonly used for the production of L-PAC;however, in early work, little was done to compare enzyme activities directly. The PDCs of S. cerevisiae and C. utilis were compared by van Dijken

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ALISON L. OLIVER, BRUCE N. ANDERSON AND FELICITY A. RODDICK

and Scheffers (1986), and van Urk et al. (1989). They determined that the activity of PDC from S. cerevisiae was approximately eight times that of PDC from C. urilis, although the PDC from the former was determined to be more sensitive to inhibition by phosphate. With respect to phosphate, the PDC from C. utilis displayed similar K , values to that from S. carlsbergensis, namely 3.6 mM in the absence of phosphate, and 11 mM in the presence of 100 mM phosphate. In contrast, PDC from S. cerevisiae exhibited K , values of 3.0 mM in the absence of phosphate and 48 mM in the presence of 100 mM phosphate. Consequently, the availability of phosphate plays an important role in the activity of PDC and thus PDC productivity. A combination of reduction in the cytosolic concentration of phosphate and increased pyruvate concentrations was proposed by van Urk et al. (1989) as contributing factors to increased PDC activity after pulsing the culture with glucose. The process used by Oliver et al. (1 997) involved pulsing with molasses midway through the fermentation, hence a similar increase in PDC activity would most probably have resulted. Significant work has been undertaken by Rogers and co-workers (Chow et al., 1995; Shin and Rogers, 1996a; Rogers et al., 1997) to evaluate the kinetics of PDC from C. utilis in both purified form and in whole cells. They recorded PDC activities of 0.85-0.9 U/mg protein for whole, stationary-phase biomass after growth in batch culture. After partial purification, Chow et al. (1995) recorded an increase in PDC activity to 4.8 U/mg protein, which was comparable with commercially obtained PDC. Pohl (1997) suggests that a specific activity in the range of 45-60 U/mg can be achieved for PDC purified from yeast and plants. Rogers et al. (1997) reported a number of kinetic parameters for purified PDC from C. utilis. The K , values for benzaldehyde and pyruvate were 42 m M (4°C pH 7.0) and 2.2 mM (25°C pH 6.0) respectively, with concentrations in excess of 10 m~ pyruvate required to give saturating conditions. The inhibition constant (Ki) for acetaldehyde was approximately 20 m ~while , substrate inhibition was evident at benzaldehyde concentrations in excess of 180 mM ( 19.1 gm Chow et al. (1995) undertook studies to determine the kinetics of deactivation of PDC by benzaldehyde. They determined that the deactivation followed first-order kinetics for benzaldehyde; however, the response was not linearly related to time for benzaldehyde concentrations between 100 and 300 mM. In much of the work undertaken on production of L-PAC, PDC has been found not to be the factor limiting L-PAC production (Vojtisek and Netrval, 1982; Shin and Rogers, 1996a; Tripathi et al., 1997) since some PDC activity remained at the end of the fermentations. Rather, both Tripathi and co-workers ( I 997) and Vojtisek and Netrval(1982) found that low pyruvate concentration in the medium limited yields. Glycolytic enzymes were implicated as potentially rate limiting by both Tripathi and co-workers, and Nikolova and Ward (1991).

THE PRODUCTION OF L-PHENYLACETYLCARBINOLBY YEAST

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Based on the information above, the conditions used by Oliver et al. (1997) (see Section 4) appear to be highly conducive to the production of L-PAC. Pyruvate is present in significant quantities and, according to Hohmann ( 1 997), the capacity of pyruvate dehydrogenase is limited compared with that of PDC, thereby restricting metabolism of pyruvate via the only alternative route. Further, the biomass is supplemented with carbohydrate in combination with reduced aeration. The work of Sims and Barnett (199 1) and Sims et al. (199 1) indicates that the combination of these two conditions is conducive to the induction of PDC.

2.3. Alcohol Dehydrogenase and Reaction By-products

The complete conversion of added benzaldehyde to L-PACis not achieved in whole cell systems because of the formation of by-products, namely benzyl alcohol and benzoic acid (Smith and Hendlin, 1953; Ose and Hironaka, 1957; Agarwal et al., 1987; Long and Ward, 1989b; Mahmoud et al., 1990a,b,c; Tripathi et al., 1991). Minor by-products include acetoin, butane-2,3-dione, 1phenylpropan-2,3-dione, 1-phenyl-1,2-propandioland 2-hydroxypropiophenone (Pohl, 1997). Benzaldehyde volatilizes readily, which may lead to some losses, even in fermenters equipped with exhaust air condensers. The main by-product of the L-PACprocess, however, is benzyl alcohol with reports of up to 50% of added benzaldehyde being converted to benzyl alcohol (Ose and Hironaka, 1957). For each gram of added benzaldehyde converted to benzyl alcohol rather than to L-PAC,the potential L-PACyield is reduced by approximately 1.4 g. The benzyl alcohol yields obtained in the study by Oliver et al. (Oliver, 1996; Oliver et al., 1997) were up to 4 g/l, equivalent to lost L-PACproduction of nearly 6 g/l. It is clear that minimizing the formation of benzyl alcohol production during L-PAC fermentations has the potential to increase the final L-PACyield significantly.This is further demonstrated by the work of Shin and Rogers (1996a,b) and Rogers et al. (1997), who performed a mass balance on the process for production of L-PAC using purified PDC. They were able to account for 98% of benzaldehyde consumption, the remaining 2%being attributed to evaporative losses and experimental error. All of the pyruvate added was accounted for as PAC, acetoin, free acetaldehyde or residual pyruvate. It appeared that further yields of L-PAC may have been achieved had additional benzaldehyde been added, as there was residual PDC activity after 6 h. Benzyl alcohol production from benzaldehyde is facilitated by the enzyme alcohol dehydrogenase, as shown in Equation 4. C,H,CHO NADH+H+ Benzaldehyde

ADH

C,H5CH,0H +NAD+ (4) Benzyl alcohol

10

ALISON L. OLIVER, BRUCE N. ANDERSON AND FELICITY A. RODDICK

The production of benzyl alcohol, in addition to a range of other aromatic alcohols, by pure ADH has been demonstrated by Long et al. (1989), although Bowen et al. (1 986) had previously investigated the inhibition of yeast ADH by aldehydes and found that their enzyme preparation displayed no reactivity with benzaldehyde. The reaction is reversible, although equilibrium constants ( K , ) of lo4 at pH 7.0 (Conn et al., 1987) and 7 x 10-9-1.8 x lo-'' (Jones, 198d) have been reported. In view of the reported equilibrium constants, the formation of ethanol, or benzyl alcohol, would be highly favoured under the fermentation conditions used for L-PACproduction if the equilibrium constants were similar for all ADH isoenzymes. The inhibition of both fermentation and growth by ethanol have been demonstrated to be completely independent and non-competitive (Aiba et al., 1968; Brown et al., 1981; Pascual et al., 1988). There are differences in ADH activities between Crabtree-positive and Crabtree-negative yeasts, with the ADH activity of Crabtree-negative yeasts, e.g. C. utilis, being significantly lower than that of Crabtree-positive yeasts, e.g. S. cerevisiae. van Urk et al. (1990) measured activities of 1.61-2.91 U/mg protein for C. utilis and 5.7-7.0 U/mg protein for S. cerevisiae. Accordingly, with respect to reported ADH activities, it would appear that Crabtree-negative yeasts such as C. utilis would be better suited to L-PAC production than Crabtree-positive yeasts. However, the activity of PDC from C. utilis ( 0 . 0 8 4 1 1 Wing protein) was much lower than that of S. cerevisiue (0.58-1.12 U/mg protein). Further, in contrast to S. cerevisiae, the PDC activity of C. urilis did not increase when the culture was pulsed with glucose. The latter finding is in contrast to that of Sims et al. (1991) who found that PDC was synthesized de novo in response to glucose pulsing. Verduyn et al. (1988) compared the substrate specificities of ADH purified from freshly grown Hansenula polymorpha and C. utilis with commercially obtained ADH purified from S. cerevisiae. They found that the ADHs from both H. polymorpha and C. utilis were capable of reducing methylglyoxal and displayed greater activity than the ADH from S. cerevisiae when butanol was the substrate. The activity of the enzyme from C. utilis was actually higher for butanol than for ethanol under optimal pH conditions, unlike the enzyme from Succharornyces. A further dissimilarity to the S. cerevisiae enzyme was the maintenance of the degree of activity with increasing chain length of substrate: ADH from C. utilis was found to be reactive with 2-propanol and 2-butanol. While the ADH from C. utilis appears to have several distinct advantages over the enzyme from S. cerevisiae, the affinity of the former for ethanol is considerably lower than that of the latter, although this is counterbalanced by its greater stability. Verduyn and co-workers noted that three isoenzymes existed in S. cerevisiae, two being cytoplasmic and one mitochondrial. However, work undertaken by Nikolova and Ward (1991) using mutants lacking all three of these isoenzymes showed that some ADH activity remained. ADH-IV activity

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has since been demonstrated in S. cerevisiue and is thought to have potential for the production of benzyl alcohol (Rogers et ul., 1997). Other aldehydes for which whole baker’s yeast has been found to be reactive include a,a,a-trifluorotolualdehyde, nitrobenzaldehyde, anisaldehyde, fluorobenzaldehyde, tolualdehyde and chlorobenzaldehyde. All of these aldehydes were used as substrates and converted to the corresponding alcohols when substituted in either the ortho-, metu- or puru-positions (Nikolova and Ward, 1994b), although increasing substrate hydrophobicity reduced yeast catalytic activity. These substrates were tested in a two-phase medium of hexane containing 2% (v/v) water. While activity was demonstrated for all of these substrates, the conversion of benzaldehyde to benzyl alcohol proceeded at almost the highest rate. Only the rate of conversion of p-nitrobenzaldehyde was higher, while the lowest rate was for a,a,a-trifluoro-o-tolualdehyde. Other studies by Leskovac et ul. (1997) found that aliphatic aldehydes were the most efficiently reduced by yeast ADH (YADH), followed by branchedchain aldehydes and lastly by aromatic aldehydes. Leskovac and co-workers used 4-dimethylamino-truns-cinnamaldehydeand chloroacetaldehyde as substrates; the YADH was of unspecified origin. The conversion of chloroacetaldehyde was essentially irreversible, the first known instance of a near-irreversible reaction involving YADH. The reduction of acetaldehyde to ethanol by ADH is an important metabolic mechanism in yeasts because of its role in the regeneration of NAD+, an electron acceptor in the phosphorylation of glyceraldehyde-3-phosphate, an intermediate in the glycolytic pathway. The regeneration of NAD+ assumes particular importance when in situ accumulation of pyruvate is desired. To date, there has been no success in completely preventing the production of benzyl alcohol in whole cell cultures, despite many reported attempts. There has, however, been some success in reducing the amount of benzaldehyde converted to benzyl alcohol. Methods which have been used include the random induction of mutant strains, the use of isoenzyme mutants, benzaldehyde dosing protocols and the use of additives to variously enhance PDC activity and reduce ADH activity. As briefly mentioned above, work is also taking place on developing purified enzyme systems. Studies which were undertaken specifically with the aim of reducing the benzyl alcohol yield, rather than increasing PDC activity, are discussed in greater detail later in this review.

3. DEVELOPMENT AND OPTIMIZATION OF THE FERMENTATION PROCESS

The development and optimization of a fermentation process is dependent on an array of factors, including the type of organism used, its physiological

12

ALISON L. OLIVER, BRUCE N. ANDERSON AND FELICITY A. RODDICK

condition, the physical conditions for growth/production and the medium composition, all of which when correctly combined create conditions conducive to high product yields. Studies into the optimization of L-PAC production by these various processes are reviewed below. 3.1. Selection of a High-yielding Producer Organism

L-PAC yields can be significantly affected by the choice of the production strain. Desirable qualities include the presence of a high level of PDC activity, low ADH activity, and high tolerance levels for benzaldehyde, benzyl alcohol and PAC. High affinity for benzaldehyde by PDC is beneficial but rarely measured. The importance of some of these criteria was demonstrated by Bringer-Meyer and Sahm (1988) when they compared purified enzymes from whole cell cultures of S. carlsbergensis and 2. mobilis. Although the PDC activity of 2. mobilis was five times that of the enzyme from S. carlsbergensis, a lower affinity for benzaldehyde resulted in a L-PACyield in 2. rnobilis, which was four to five times lower. Most early studies compared strains on an holistic basis, measuring their ability to produce PAC, and productivity over a set period, rather than identifying the biochemical basis for their performance. No single species of organism has been accepted universally as the strain most suited to L-PAC production, although Saccharomyces spp. have been identified as the best L-PACproducers in comparative studies by a number of groups (Becvarova and Hanc, 1963; Gupta et al., 1979; Netrval and Vojtisek, 1982; Mahmoud et al., 1990a), and are known to be producers of acetoin (Romano and Suzzi, 1996). Importantly, Netrval and Vojtisek demonstrated that the yeast with the highest initial productivity was not necessarily the most productive over an extended period (24 h), in contrast to Becvarova and Hanc’s suggestion (based on 6-h transformations) that the highest yields were produced by the yeast with the highest decarboxylase activity. Netrval and Vojtisek’s findings have been supported by those of Shin and Rogers (1996a,b) and Rogers et al. (1997) who found that, while initial rates of L-PAC production were higher at higher PDC activities, this did not necessarily result in higher final yields. These findings have also been supported by the work of Tripathi et al. (1997) and Bringer-Meyer and Sahm (1988). Prior to Becvarova and Hanc’s (1963) comparison of six brewing and food yeasts, screening of organisms was limited. Both brewer’s (Smith and Hendlin, 1953, 1954; Netrval and Vojtisek, 1982) and baker’s (Becvarova et al., 1963; Voets et al., 1973; Long et al., 1989; Long and Ward, 1989a; Nikolova and Ward, 1992a) yeasts were, and have continued to be, common choices owing to their ready availability and low cost. Both possess good PDC activity, although brewer’s yeast also has high ADH activity. Although some ADH activity is desirable for the regeneration of NAD+, particularly if pyruvate is

THE PRODUCTION OF L-PHENYLACETYLCARBINOLBY YEAST

13

being generated in situ, high ADH activity can result in high levels of benzyl alcohol, which potentially reduces the L-PACyield by reducing the amount of available benzaldehyde for conversion to L-PAC. Baker’s yeast may be preferable because of its generally lower ADH activity. Other strains used include locally isolated strains of S. cerevisiae (Agarwal et al., 1987;Tripathi et al., 1988; Agarwal and Basu, 1989) and various yeast strains from culture collections (Becvarova and Hanc, 1963). The L-PAC yields from local isolates were comparable to yields from yeasts obtained from culture collections. One way of seeking further increases in L-PACyield is via the use of genotypically and/or phenotypically modified biomass, although success is not guaranteed. For example, Nikolova and Ward ( 1 99 1) tested eight S. cerevisiae ADH I, II and I11 isoenzyme mutants, and achieved similar benzyl alcohol concentrations for all the strains tested regardless of their isoenzyme configurations. Also, a benzaldehyde-tolerant strain of C. utilis with increased productivity and benzaldehyde consumption rate isolated by Dissara and Rogers (1995) had a lower final L-PACyield than the parent strain because of a lower specific growth rate. The use of chemical (ethylmethane sulphonate, N-methyl-N’-nitro-Nnitrosoguanidine, nitrous acid) and physical (ultraviolet and gamma rays) agents to generate mutant strains has met with some success, with increases in L-PACyield ranging from 10% using S. cerevisiae (Sambamurthy et al., 1984; Ellaiah and Krishna, 1987) to 100%using S. cerevisiae and C.Jlareri (Seely et al., 1989b). The types of changes induced have included acetaldehyde and ephedrine resistance (Seely et al., 1989b), increased productivity, benzaldehyde tolerance and benzaldehyde consumption rate (Sambamurthyeta!., 1984; Ellaiah and Krishna, 1987; Dissara and Rogers, 1995). Benzaldehyde, L-PAC and sodium cyanide resistance has been induced by exposure of Saccharomyces spp. cultures to each of the three chemical agents (Gupta et al., 1979; Ellaiah and Krishna, 1987), although only benzaldehyde-tolerant strains had improved rates of conversion of benzaldehyde to L-PAC. Another approach has been the use of site-directed mutagenesis to increase the carboligase activity of PDC. When applied to PDC extracted from Z. mobilis, the resultant mutant enzyme gave a three-to four-fold increase in LPAC production when coupled with an enzymatic system to remove acetaldehyde [Bruhn et al. 1995, 1996 (as cited by Pohl, 1997)l. 3.2. Physicochemical Conditions and their Effect on L-PAC Production

The physical environment of a fermentation affects cell metabolism and structure, and product stability. Product stability is increasingly likely to be directly

14

ALISON L. OLIVER, BRUCE N. ANDERSON AND FELICITY A. RODDICK

affected if the product is excreted into the fermentation medium, as is L-PAC. The three variables over which process control is most precise are dissolved oxygen, pH and temperature. 3.2.1. Effect of Dissolved Oxygen Concentration on Metabolism Both Voets et al. (1973) and Ellaiah and Krishna (1988) demonstrated the benefit of limited aeration on L-PAC production by S. cerevisiae. Aeration of medium at a rate of 0.3 Vl.min enhanced L-PAC production compared with non-aerated cultures, although at 0.5 Vl.min, L-PAC production was reduced (Voets et al., 1973). Ellaiah and Krishna (1988) demonstrated that L-PACyield varied with the mass transfer coefficient (kLa), the maximum L-PAC yield being obtained when the kLa was 2.35 mm/l.h. Culik et al. (1984) deliberately reduce3 aeration to induce fermentative activity in S. coreanus and hence to stimulate L-PACproduction. They found that increasing the rate of aeration when L-PAC production began to slow increased the final L-PACyield, although the specific reasons for enhanced LPAC production were not detailed. Rogers and co-workers (1997) also employed a strategy of reduced aeration to stimulate the activity of PDC in their fed-batch and three-stage continuous culture systems with resulting LPAC yields of 22 g/l (in defined medium) and 10.6 g/l, respectively. Mahmoud et al. (1990a,b,c)induced anaerobiosis in S. cerevisiae by sparging the culture with nitrogen gas, which may have improved the L-PAC yield by ensuring the regeneration of NAD+, essential for the production of pyruvate from sucrose. However, the benzyl alcohol yields may have also been increased in the nitrogen-sparged cultures, compared with the aerated cultures, owing to the absence of molecular oxygen, which is known to exert a repressive effect on ADH activity (Nagodawithana et al., 1974; Jones et al., 1981; Ward and Young, 1990). In their study of the role of PDC on the Kluyver effect on C. utilis, Sims et al. (1991) found that PDC was synthesized de novo under anaerobic conditions in the presence of D-glucose. Under aerobic conditions the PDC was partially deactivated. Anaerobic conditions in these experiments were achieved by sparging with nitrogen gas; however, Sims and co-workers also demonstrated that depletion of oxygen by actively growing biomass was also sufficient to enable synthesis of PDC. Concomitant with the increase in PDC activity under anaerobic conditions was an increase in ADH activity, which in the case of the process used for L-PAC production could lead to higher concentrations of benzyl alcohol, i.e. reduced L-PAC yields. It is likely that reduction in aeration (Culik et al., 1984). and even sparging of cultures with nitrogen as practised by Mahmoud et al. (1990a,b,c), was intended to increase PDC activity. It is also possible that the reductions in L-PAC yields observed by Voets et al. (1973) and

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Ellaiah and Krishna (1988) under conditions of increased aeration were due to deactivation of PDC as a result of the cultures becoming aerobic. The findings of van Dijken and Scheffers (1986) suggest that increased glycolytic flux results from glucose pulsing under anaerobic conditions for C. utilis, thus increasing the levels of pyruvate. This is important in that the L-PAC yield is potentially enhanced owing to increased pyruvate availability. In contrast to the findings of Rogers and co-workers, Tripathi et al. (1997) found that L-PACyields were higher if the biomass was grown anaerobically, with the biotransformation taking place under aerobic conditions. The greater yields were attributed to the induction of PDC under the anaerobic growth conditions accompanied by increased pyruvate concentrations. However, with aerobic growth, it is likely that pyruvate would be diverted from the production of L-PAC by consumption through aerobic metabolic pathways. Variation in the levels of enzymes owing to differences in aeration is not peculiar to PDC. In a paper published in 1972, Harrison noted that growth of microorganisms or cultured cells under either aerobic or anaerobic conditions affected the levels of enzymes present. Anaerobic conditions were likely to enhance the levels of enzymes related to fermentation pathways, and low dissolved oxygen concentrations resulted in increases in glycolytic enzyme concentrations. Aerobic conditions enhanced the levels of Krebs cycle enzymes. Oliver et al. (1997) (see Section 4)used a system where, after the growth of biomass, the level of aeration was reduced in conjunction with pulsing of molasses. Based on the discussion in preceding paragraphs, an increase in PDC activity would have occurred. Pyruvate production continued for some time into the bioconversion phase of the fermentation process of Oliver and coworkers even under conditions of increasing benzaldehyde concentration. 3.2.2. Eflect of pH on Cellular Metabolism

When using S. cerevisiae for L-PAC fermentations, a pH range of 4-6 has generally been employed (Smith and Hendlin, 1953; Voets et al., 1973; Gupta et al., 1979; Long and Ward, 1989a,b), while Rogers and co-workers (1997) employed a pH of 6.2 for the bioconversion stage of their three-stage process using C. utilis. Rogers et al. (1997) also found that L-PACproduction was more sensitive to pH than was benzyl alcohol production. 3.2.3. Effect of Temperature on Metabolism

According to Rogers (1990), the rate of L-PAC production by C. utilis was approximately 1.5 times higher at 30 "C than at 20 "C; however, benzyl alcohol

16

ALISON L. OLIVER, BRUCE N. ANDERSON AND FELICITY A. RODDICK

yield was also increased at the higher temperature. The use of a lower temperature improved L-PAC yield with respect to benzyl alcohol yield and increased L-PAC stability, although the growth rate declined at temperatures below 25 "C. The use of a lower temperature may have also helped to reduce alcohol toxicity. Temperatures as high as 35 "C were found to have little effect on L-PACproduction by S. cerevisiae (Ellaiah and Krishna, 1988), although temperatures ranging from 25 "C (Vojtisek and Netrval, 1982; Nikolova and Ward, 1991) to 28-30 "C are used more routinely (Smith and Hendlin, 1953, 1954; Voets et al., 1973; Netrval and Vojtisek, 1982; Nikolova and Ward, 1991, 1994a). The manipulation of fermentation temperatures to improve yields has generally not been a key component of laboratory studies. 3.3. Physiological Condition of Cells for Optimum L-PAC Production

The biotransformation of a chemical is largely dependent on the physiological condition of the biomass, which, in turn, is influenced by the medium composition and physicochemical conditions used throughout the process. This applies to both the growth phase and the bioconversion phase of the L-PACfermentation. While a popular choice for laboratory studies, the use of purchased commercial baker's (Long and Ward, 1989a,b;Voets e f al., 1973; Nikolova and Ward, 1992a,c, 1994a) and brewer's yeast (Smith and Hendlin, 1953;Vojtisek and Netrval, 1982) as added biocatalyst reduces the ability for control and/or optimization of biomass preparation. The absence of control over biomass preparation may be of particular concern where purchased biocatalysts are used after very short acclimatization periods. Although baker's yeast is considered to have good PDC activity, as described above, the reduction in aeration results in enhanced production of PDC, provided that the acclimatization period is sufficient to allow for further induction of PDC production. Insufficient time for induction of PDC may result in reduced L-PACyields. No studies were undertaken to determine enzyme activities or the effect of the acclimatization period on those activities. The effect of cell age has been considered for S. cerevisiae (Agarwal et al., 1987), with the greatest L-PAC production observed with biomass that was 15-24 h old. The L-PACyield was considered to be dependent on a combination of enzyme activity and benzaldehyde tolerance, with reduced yields from older or younger biomass owing to lower activity or tolerance. Freshly cultivated inoculum ranged from 16 h (Ellaiah and Krishna, 1987) to 24 h (Netrval and Vojtisek, 1982; Mahmoud et al., 1990a,b,c; Nikolova and Ward, 1991, 1992b) and even to 28 h old (Becvarova and Hanc, 1963). The age of commercially obtained brewer's and baker's yeast was never stated, and as little as

THE PRODUCTION OF L-PHENYLACETYLCARBINOL BY YEAST

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1 h was allowed for adaptation to transformation conditions prior to commencement of the benzaldehyde feed (Smith and Hendlin, 1954; Voets et al., 1973; Long and Ward, 1989b).Yeast freshness was considered to be important by Becvarova et al. (1963) and Voets et al. (1973). The cessation of L-PAC production has been directly linked with reduced viability by Long and Ward (1989b); however, the loss of viability coincided with exposure to high benzaldehyde concentrations.Although PDC activity is resistant to benzaldehyde concentrations as high as 7 g/l, sucrose metabolism, cell growth and viability, which may in turn reduce the L-PAC production capacity, are affected by concentrations as low as 2-3 g/l. Indeed, recent reports (Rogers et al., 1997) placed the minimum concentration required for inhibition of growth of C. utilis at 1 gA, with a growth inhibition constant of just 0.30 g/l. They found that the specific rate of L-PAC production was strongly affected at benzaldehyde concentrations of 3 g/l. Biomass rendered non-viable by other means can still catalyse the transformation of benzaldehyde to L-PAC provided that pyruvate is supplied, as demonstrated with non-viable immobilized S. cerevisiae biomass (Seely et al., 1989a). Other authors have noted differences in metabolic activity whilst using acetone powders of yeast. Increased residual benzaldehyde and acetyl benzoyl concentrations were detected, but benzyl alcohol was not detected when acetone-dried powders were used by Voets et al. (1973). transcinnamaldehyde, a compound not normally detected in fermentations using freshly grown biomass, was detected in S. cerevisiae acetone powder fermentations (Voets et al., 1973). In contrast, Ose and Hironaka (1957) found that benzyl alcohol was produced by acetone dried yeast powders. When both benzaldehyde and pyruvate are present in sufficient concentration, PDC activity is reportedly the rate-limiting factor in L-PAC production by S. carlsbergensis (Vojtisek and Netrval, 1982), and low PDC concentrations were identified as a cause of low L-PACproduction capacity by S. cerevisiae (Mahmoud et af.,1990a). Continuous culture, particularly at high dilution rates, has been shown to be an effective method for increasing S. cerevisiae PDC activity, with four- and seven-fold increases in specific productivity for 23- and five-fold increases in flow rate during the growth and transformation phases of the fermentation, respectively (Tripathi et al., 1988, 1991). Culik et aE. (1984) adapted biomass for L-PAC production by preventing diauxic growth during the growth phase. This was achieved by ensuring sufficient oxygen supply. Fermentative metabolism was then induced in the Saccharomyces sp. by reducing aeration and regulating the feeding of sucrose. Using such methods, L-PAC yields of 10 g/l or more could be achieved. Alternatively, Seely et al. (1989b) allowed the cultures of S. cerevisiae to become oxygen-limited or anaerobic for up to 16 h prior to commencement of biotransformation. By following these guidelines, cells from any stage of

18

ALISON

L. OLjVER, BRUCE N. ANDERSON AND FELICITY A. RODDICK

growth up to late log phase could be successfully used for L-PACproduction with little variation in yield. 3.4. Nutrient Effects in L-PACProduction

The role of nutrition in the production of L-PAChas received limited attention to date. Manipulation of fermentation media, in particular, complex industrial media, to enhance the production of L-PAC requires an understanding of the metabolic roles of macronutrients and micronutrients.The work undertaken on yeast nutrient requirements in general and their effects on metabolism is extensive, and it is neither practical nor possible to review all aspects of the work here. Some aspects of yeast nutrition relevant to L-PAC production will therefore be discussed briefly. Vojtisek and Netrval(l982) investigated the use of corn steep liquor (CSL) and yeast hydrolysate, and found them both to be beneficial for the production of L-PAC by S. carlsbergensis when added to an otherwise simple medium. Noronha and Moreira (1993) developed a L-PAC production medium (details not published) with a glucose concentration of approximately 100 g/l (S. Noronha, 1996, personal communication) to stimulate the fermentative activity of S. cerevisiae. Others, all employing S. cerevisiae, have used media ranging from fully defined media (Agarwal ef al., 1987; Tripathi et al., 1991) to very simple media containing nothing more than molasses and urea and/or phosphate (Ellaiah and Krishna, 1987, 1988). Glucose, sucrose and pyruvate are frequently used substrates for the L-PAC production process with the sucrose supplied either as pure sucrose or as molasses. Glucose or sucrose is generally used when biomass is grown in situ prior to the initiation of the bioconversion phase (Netrval and Vojtisek, 1982; Ellaiah and Krishna, 1988; Nikolova and Ward, 1991). Sucrose has also been used as a substrate for the generation of pyruvate during a short acclimatization period prior to benzaldehyde dosing when commercially obtained biomass was used (Long and Ward, 1989a,b;Nikolova and Ward, 1991).When the biomass is used essentially as a catalyst, pyruvate is generally used and has been found to produce higher and more reproducible L-PAC yields because the regeneration of NADH is limited, and hence the production of benzyl alcohol is also limited (Nikolova and Ward, 1991). It is not uncommon for industrial fermentation media to contain one or more complex materials. Generally inexpensive and readily available complex carbon and nitrogen sources may also be used as a source of vitamins, trace elements and growth factors (Zabriskie et al., 1980), in some cases fulfilling all of the vitamin requirements of the organism (Stanbury and Whitaker, 1984). However, various compounds may be present in inhibitory concentrations (Oura, 1983; Jones and Greenfield, 1984; Cejka, 1985), may be

THE PRODUCTION OF L-PHENYLACETYLCARBINOL BY YEAST

19

non-metabolizable (Reed and Peppler, 1973; Meyrath and Bayer, 1979), or may be complex ionic nutrients (Jones and Greenfield, 1984; Berry and Brown, 1987), functions which may be considered as either beneficial or detrimental. Optimization of individual nutrients is difficult because a change in the concentration of the complex material alters the concentrations of all individual components. Increased yields may be obtained by using defined medium, although the use of a defined medium on an industrial scale may limit the commercial viability of the process (Zabriskie et ul., 1980, Stanbury and Whitaker, 1984). Among the benefits of using defined medium are constant composition, and the exclusion of toxic or inhibitory compounds; however, the cost of the medium may be disproportionate to the value of the product and the overall yields may be no better. Defined media are frequently used on a laboratory scale to determine nutrient requirements. Dissara and Rogers (1995) achieved L-PACyields of up to 22 g/l using a defined medium, on a 5-1 scale, compared with 13 g/l in undefined medium. On the other hand, Vojtisek and Netrval (1982) achieved higher L-PAC yields (4.7-5.6 g/l) when yeast hydrolysate and/or CSL was included in the medium compared with yeast hydrolysate alone (2.5 gA). However, the basal medium used by Vojtisek and Netrval was much simpler than the defined medium used by Dissara and Rogers. The work undertaken on production of L-PACto date has been quite limited in the extent to which the effects of nutrients on metabolism have been closely examined. An investigation undertaken by Derrick and Large (1993) on the growth of C. utilis in continuous culture using valine and ammonium as nitrogen sources found that, under nitrogen limitation, increases in pyruvate yield of up to 100-foldwere achieved. Thus growth under nitrogen limitation may in turn lead to enhanced L-PACyields. One of the drawbacks from the use of complex industrial fermentation media is the presence of an array of different forms of the same macronutrients leading to diauxic growth patterns. Diauxic growth is more frequently seen in batch cultures; in continuous culture the biomass can adapt and eventually use all of the nutrients simultaneously. Culik et al. (1984) experienced scale-up problems owing to diauxic growth; ammonium and sucrose were used preferentially, followed by the utilization of carbon and organic nitrogen from corn extract, and finally ethanol produced initially from sucrose was used. Diauxic growth is not exhibited by all organisms; C. utilis, for example, is capable of the simultaneous use of metabolically produced ethanol in conjunction with added glucose (Ghoul et al., 1991), whereas the addition of glucose to S. cerevisiue cells will cause an immediate return to net ethanol generation rather than consumption (van Urk et al., 1988, 1990). Oliver (1996) et al. and Oliver (1 997) undertook a study aimed at simplifying a complex medium used industrially for the production of L-PAC by C. utilis. Medium components included molasses, CSL and whey in addition to

20

ALISON L. OLIVER, BRUCE N. ANDERSON AND FELICITY A. RODDICK

pure sources of glucose, phosphate, nitrogen, magnesium and thiamine. Although C. utilis is known to be prototrophic for vitamins, the thiamine was provided to ensure that the cofactor demand exerted by PDC was met. They found that up to 60% of the original molasses content of the medium could be substituted by the equivalent amount of sucrose in the form of raw sugar, with no loss in either pyruvate or L-PACyield. Furthermore, both CSL and whey could be omitted from the medium leading to slight increases in pyruvate yield but no change in L-PACyield. These results are consistent with the findings of Derrick and Large (1993) discussed above. Other benefits arising from these modifications to the medium included reduced inorganic content and chemical oxygen demand of the spent medium, the latter largely due to lower residual reducing sugar levels. The protocol used by Oliver (1996) and Oliver et al. ( 1997) included pulse feeding of carbohydrates (either molasses or sucrose). Rogers et al. (1997) also employed pulsed carbohydrate feeding in some of their studies. The benefits of using pulse feeding of carbohydrate in relation to the induction of PDC activity are outlined in Section 2.2. 3.5. Production of L-PAC by Batch, Fed-batch or Continuous Fermentation

The majority of studies on the production of L-PAChave been undertaken on a batch basis for comparison of yeast strains and to optimize production; the development of fed-batch or continuous production of L-PAC is relatively recent. The advantages of fed-batch or continuous production lie in the use of the same culture of organisms for production over an extended period, so reducing downtime, reducing of substrate and product toxicity by continuous dilution of medium, leading to higher final yields. Agarwal and Basu (1989) compared batch and fed-batch fermentationsusing free cells of S. cerevisiue and found that fed-batch fermentationscould be run for up to 14 times longer than batch fermentations. ‘Semi-continuous’may be a more appropriate term than ‘fed-batch’because aliquots of medium were periodically replaced rather than additional medium being added to the total volume. The fed-batch protocol was most beneficial up to the third cycle when the total LPAC yield was up to 120% higher than the total yield for an equivalent number of batch fermentations,i.e. based on an equivalent medium volume. Thereafter,the productivity decreased but was relatively constant, with approximately 50% more L-PACat any given time than for an equivalent number of batch fermentations. Mahmoud et al. (1990b) compared batch and ‘semi-continuous’fermentation protocols using S. cerevisiue immobilized in alginate. Unlike Agarwal and Basu (1989) who also used a strain of S. cerevisiue, Mahmoud et ul. (1990b) replaced the entire volume of medium at the end of each 24-h cycle rather than

THE PRODUCTION OF L-PHENYLACETYLCARBINOLBY YEAST

21

a proportion thereof but similarly recorded a decrease (approximately 50%)in L-PACproduction after the first two cycles, which could not be restored by the regeneration or re-immobilization of the biomass. L-PACproduction remained relatively constant for the remaining cycles. Over seven cycles a fivefold increase in total L-PACyield was measured relative to a single batch fermentation, although it was unclear whether this referred to batch fermentations conducted in shake flasks (Mahmoud et al., 1990a) or a single cycle in a column reactor (Mahmoud et ul., 1990b). When transformations were run continuously, flow rate was determined to influence productivity (Tripathi et al., 1991) with a sevenfold increase in productivity, through a fivefold increase in flow rate for S. cerevisiue. The continuous system developed by Rogers and co-workers is fundamentally different from the systems developed by Agarwal and Basu (1989) and Mahmoud et al. (1990b).While the systems established by the last two groups embodied the concept of periodical replacement of part or all of the medium, the fermentation conditions were kept constant. In the case of Rogers et al. (1997), conditions were modified to exploit particular aspects of yeast physiology and metabolism. They found that a single-stage continuous system was unsuitable for use because of the toxicity of the benzaldehyde. Continuous culture may also affect enzyme activities, since the PDC and ADH activities of C. utilis were lower than those of S. cerevisiue when grown under the same continuous culture conditions (Derrick and Large, 1993). A well-controlled fed-batch system was considered by Rogers et al. (1997) to be preferable to a continuous system. Two- and three-stage systems were developed of which the three-stage system was the best. The separate stages were designed to: (1) optimize biomass yield; (2) induce semi-fermentativeactivity and enhance PDC activity; and (3) provide a biotransformation phase where benzaldehyde was added and converted to L-PAC.Respiratory quotient (RQ) was the major control variable for each stage. Using a continuous process, LPAC yields of up to 10.6 g/l were achieved, while yields of up to 22 g/l have been achieved for a three-stage fed-batch system. Significant reductions in PDC activity occurred. Similar to Sims et al. (1991), Rogers and co-workers reported an approximate fivefold increase in PDC activity, induced by controlling the RQ at 4-5 to induce partially fermentative conditions. Shin and Rogers (1995b) found that an RQ of 5-7 was most favourable for L-PACproduction with minimum benzyl alcohol formation. While pyruvate yields were enhanced at higher RQ levels, higher benzyl alcohol yields resulted.

3.6. The Use of Additives to Modify Metabolic Activity As previously mentioned, the complete conversion of benzaldehyde to L-PAC has not been achieved with any yeast strains as some benzyl alcohol has always

22

ALISON L. OLIVER, BRUCE N. ANDERSON AND FELICITY A. RODDICK

been produced. Even the use of ADH isoenzyme mutants (Nikolova and Ward, 1991) failed to prevent benzyl alcohol production. In the absence of an ADHfree yeast, reduced benzyl alcohol production and increased L-PAC yields have been sought by the use of additives, e.g. inhibitors or alternative hydrogen acceptors, which are not required for normal metabolic activity. The use of additives to reduce benzyl alcohol yield by dried brewer’s yeast was originally investigated by Smith and Hendlin (1954) who proposed three different methods: the use of alternative H+ acceptors, the addition of sulphydryl inhibitors (to inhibit ADH), and the use of nicotinic acid analogues to compete with NADH for enzyme active sites. Colloidal sulphur was the only H+ acceptor which successfully reduced the benzyl alcohol yield; however, owing to its toxicity, the L-PAC yield was also reduced. The use of sulphydryl inhibitors was similarly unsuccessful owing to the inhibition of other sulphide-containing glycolytic enzymes. Of the nicotinic acid analogues, only the amides were successful in reducing benzyl alcohol yields. Using concentrations of analogues up to 50 mM, reductions in benzyl alcohol of up to 20% were achieved with an equivalent concomitant increase in the yield of L-PAC. Ose and Hironaka (1957), also using dried brewer’s yeast, confirmed the findings of Smith and Hendlin and tested an additional hydrogen acceptor, acetaldehyde. They found that 70% conversion of benzaldehyde to L-PAC was achieved when a mixture of acetaldehyde and benzaldehyde was added to the medium compared with 40% conversion without added acetaldehyde. The increase in L-PAC yield matched the decrease in benzyl alcohol. By using radiolabelled acetaldehyde, Ose and Hironaka were able to exclude the use of acetaldehyde as a substrate in the production of L-PAC and it was believed to be an alternative hydrogen acceptor to benzaldehyde, thus preventing the production of benzyl alcohol. Acetaldehyde dosing has since been used successfully by Becvarova et al. (1963) and Becvarova and Hanc (1963), who used a mixture of equal parts of benzaldehyde and a 50% aqueous solution of acetaldehyde, or equal parts of benzaldehyde and acetaldehyde, respectively, to achieve increased L-PACyields compared with controls where no acetaldehyde was added. Netrval and Vojtisek (1982), and Vojtisek and Netrval(1982), routinely added a mixture of acetaldehyde and benzaldehyde to fermentations, although no comparison was given for a fermentation without added acetaldehyde. Increases of up to 30% in L-PACproduction by C. utilis were obtained by Oliver (1996) when acetaldehyde was supplied at two different concentrations and under varying dosing regimes. Acetaldehyde was supplied at levels equimolar and twice equimolar to the anticipated maximum benzyl alcohol yield, and, in contrast to the findings of Ose and Hironaka (1 957), led to a marginal (less than 10%) increase in benzyl alcohol production,. While the use of acetaldehyde may result in reduced benzyl alcohol yields, it is important to balance the benefits with the known disadvantages.

THE PRODUCTION OF L-PHENYLACETYLCARBINOLBY YEAST

23

Acetaldehyde is known to be more toxic than ethanol on a weight basis (Stanley, 1993). Inhibition of growth by concentrations as low as 0.3 g/l have been observed (Stanley et al., 1993), although the acetaldehyde concentration calculated by Stanley to inhibit growth of S. cerevisiae by 50% was 0.5 g/l. This concentration is similar to that reported by Carlsen et al. (1991) as inhibitory to the respiration of S. cerevisiae (0.55 gA) grown on glucose. Some individual enzymes are even more sensitive to the effects of acetaldehyde: PDC has a Ki of 4-7 m~ (0.2 - 0.3 g/l) while ADH has a Ki of 120-160 p~ (5-7 mg/l) (Jones, 1989). Rogers et al. (1997) determined an inhibition constant for acetaldehyde for C. utilis-derived PDC of 20 m~ (equivalent to 0.882 gA). These quantities are much lower than the amounts added to the fermentation medium by Oliver (1996) (up to 1.5 gA), suggesting that some inhibition of PDC and hence reduced L-PAC yields may have occurred. The physiological role of acetaldehyde is believed to be as a competitor with benzaldehyde for active sites on ADH. The miscibility of acetaldehyde with aqueous solutions is greater than for benzaldehyde and so it should be more readily available to ADH than benzaldehyde. Dosing with acetaldehyde allows the reaction to proceed in the direction favoured under fermentation conditions, in addition to enabling the regeneration of NAD+ for use in glycolysis. The addition of acetaldehyde to medium has been reported by Stanley (1993) to stimulate glycolytic flux in anaerobic fermentations through increased generation of NAD+. Ellaiah and Krishna (1987) tested the additives a-naphthoxy acetic acid (NAA), 2,4-dichlorophenoxy acetic acid (2,4-D), ethylenediaminetetraacetic acid (EDTA) and niacinamide on a strain of S. cerevisiae. None were successful in enhancing L-PAC yield; reductions of up' to 25% were observed. On addition of 20 p g / d niacinamide, there was a negligible decrease in L-PAC yield ( 6 5 % ) in contrast to the findings of Smith and Hendlin (1954). Other respiratory inhibitors which have been tested for their ability to improve L-PAC yield by C. utilis include sodium azide, sodium cyanide and salicyl hydroxamic acid (Rogers, 1990). Of these, only the addition of sodium azide resulted in an increase (10%)in L-PAC yield and was accompanied by a similar decrease in benzyl alcohol yield. 3.7. Reduction of the Toxic Effects of Substrate, Product and By-product

Production of L-PAC is self-limitingowing to the toxic nature of benzaldehyde, benzyl alcohol and L-PAC. The potential effects of benzaldehyde on biomass and fermentation outcome include retardation or inhibition of growth, reduction of viability and alteration of cell permeability to substrate and product (Long and Ward, 1989b). Liew et al. (1995), who studied the use of a

24

ALISON L. OLIVER, BRUCE N. ANDERSON AND FELICITY A. RODDICK

continuous membrane bioreactor, attributed reduced flux across the membrane to lysis of biomass on addition of benzaldehyde. Benzyl alcohol is substantially more toxic than ethanol, with benzyl alcohol concentrations as low as 5 g/l causing up to 80% inhibition of both L-PAC and benzyl alcohol production rates for C. utilis (Rogers et al., 1997) in addition to inhibition of growth. Ethanol concentrations of up to 21 g/l caused only minor inhibition of initial benzyl alcohol production, and the Kifor growth of C. utilis was 39 g/l ethanol (Rogers et al., 1997). The same group has reported a Ki for growth of 4.1 gA L-PAC,which is therefore also much more toxic than ethanol. In terms of the sensitivity of individual enzymes, purified yeast ADH is more sensitive to benzaldehyde (with inactivation at concentrations as low as 0.2 g/l) and PAC than purified yeast PDC which is most sensitive to benzyl alcohol (Long and Ward, 1989b). Owing to the highly toxic nature of benzaldehyde, the ability of yeast to adapt is limited. Pelleting of free cells in fermentations when exposed to benzaldehyde was noted by Mahmoud et d.(1990a) and was thought to be a mechanism for reduction of the toxic effect of benzaldehyde. Because of the limited tolerance of yeast to benzaldehyde, benzyl alcohol and L-PAC,various physical methods have been developed to reduce the exposure of the yeast. The techniques used include benzaldehyde dosing regimes, immobilizationof biomass, biphasic fermentations and the use of additives. The role of nutrientshffering agents in reducing the toxic effects of benzaldehyde also merits consideration, although the number of studies in the area is extremely limited. The addition of 20% yeast extract to enzyme suspensions was found by Long and Ward (1989b) to be helpful in slowing the inactivation of ADH with 61% residual activity after 6 h in the presence of 7 g/l benzaldehyde. 3.7.1. Substrate Dosing

One of the simplest and least costly methods of reducing the biomass exposure to inhibitory concentrations of benzaldehyde is to alter the benzaldehyde dosing regime and thus limit the maximum benzaldehyde concentration in the medium at any time. Much of the early experimental work undertaken on the production of L-PACwas conducted on a small scale in shake flasks, leaving little scope for variation in the benzaldehyde dosing regime. Long and Ward (1989b) compared the L-PAC yields obtained from S. cerevisiae using shake flasks, where a total of 12 gA of benzaldehyde was added to each flask, being added as either two aliquots each of 6 g/l.h or six aliquots each of 2 g/l.h. Markedly different behaviour was demonstrated by the yeast for the two conditions. When six small aliquots of benzaldehyde were added to the broth, the yeast viability was maintained at close to the initial level for the

THE PRODUCTION OF L-PHENYLACETYLCARBINOL BY YEAST

25

first 4 h of the biotransformation,while the cell viability in the culture dosed with 6 g/l.h benzaldehyde dropped to approximately 30% of the initial value within the same period. Sucrose consumption continued in the medium with the small benzaldehyde doses and the residual benzaldehyde concentration was lower than in the medium receiving the two large doses. Higher L-PACtitres were also recorded in the medium with the six benzaldehyde doses - approximately 4 4 . 5 g/l compared with 3.3 g/1 for the medium with two doses although the maximum L-PACconcentration occurred earlier in the fermentation for the condition with two doses. The benefits of protecting biomass from large initial concentrations of benzaldehyde were clearly demonstrated. During their development of a semi-continuous process for L-PACproduction using S. cerevisiae, Mahmoud et al. (1990b) compared intermittent and continuous benzaldehyde dosing protocols. They found that, by adding benzaldehyde continuously over 6 h, up to double the amount (12 g/l) could be added compared with the amount previously added intermittently (6 g/l) without inhibition of L-PACproduction, resulting in 2.5 times the L-PAC yield (10 g/l rather than 4 g/l). The advantages offered by continuous benzaldehyde dosing over intermittent feeding were also demonstrated when a wild-type strain and a strain of S. cerevisiae adapted to benzaldehyde were exposed to intermittent and continuous dosing of benzaldehyde to the same final benzaldehyde concentration (8 g/l). For the adapted cells, 70% of the added benzaldehyde was converted to L-PAC under continuous dosing, while only 26% was converted in the intermittently dosed medium. For the wild-type cells, the conversion efficiencies were 57% and 41%, respectively. The use of a continuous feeding protocol appeared to reduce the inhibitory effect of benzaldehyde and led to more efficient conversion of benzaldehyde to L-PAC. Studies by Agarwal et al. (1987) found that, by maintaining medium benzaldehyde concentrations greater than 4 m, PDC activity remained higher than ADH activity in S. cerevisiae. The reduced rate of benzyl alcohol production at higher concentrations was likely to be the result of inactivation of ADH by benzaldehyde. Long and Ward (1989b) found that residual activity of purified ADH exposed to 0.2 g/l benzaldehyde had dropped to 82% after 6 h compared with a residual activity of 90.6%for ADH incubated in the absence of benzaldehyde, and had dropped to 33% for ADH incubated in the presence of 3 g/l benzaldehyde. In contrast, the PDC activity remained constant at 89% and 87% in the presence of 0.2 g/l and 7 g/l benzaldehyde, respectively. Thus, benzaldehyde concentration and dosing regime may be used to help control the formation of by-products. While the potential use of high benzaldehyde concentrations to lower benzyl alcohol yields was recognized by Long and Ward (1989b), they also noted that the inhibition or inactivation of ADH by benzaldehyde could restrict the regeneration of NAD+.This may be beneficial in whole cell systems where the biomass is used as a catalyst and exogenous pyruvate is added to the

26

ALISON L. OLIVER, BRUCE N. ANDERSON AND FELICITY A. RODDICK

medium. However, when endogenous production of pyruvate is required, as in the system used by Oliver et al. (1997), the addition of benzaldehyde resulting in inhibition of ADH may also result in reduced glycolytic flux and hence reduced L-PACyields. Work undertaken by Rogers et al. (1997) expanded on that of Agarwal et al. (1987) by demonstrating that higher yields of by-products were formed at benzaldehyde concentrations of less than 150 m and greater than 200 m, and when the molar ratio of benzaldehyde to pyruvate was between 0.5 and 1.O. Shin and Rogers (1995b) found that benzyl alcohol was preferentially produced by both free and immobilized biomass at concentrations of less than 30 m benzaldehyde, while L-PAC was the main product when benzaldehyde concentrations were in excess of 40 m. A two-phase protocol was utilized by Oliver et al. (1997) comprising batch generation of the C. utilis biomass followed by fed-batch L-PACproduction. In the production phase, conversion of the accumulated pyruvate to L-PAC was maximized by the addition of a large initial aliquot of benzaldehyde, this was accompanied by the addition of nutrients and carbohydrate to promote further pyruvate production prior to the commencement of continuous benzaldehyde dosing and a second addition of carbohydrate. 3.7.2. Immobilization of Enzymes or Biomass

Benzaldehyde concentrations as low as 1-2 g/l are capable of inhibiting the growth of C. utilis (Dissara and Rogers, 1995) and S. cerevisiue (Long and Ward, 1989b) and, although higher initial concentrations of benzaldehyde (6 g/l) can result in higher L-PACproduction, there is an almost immediate effect on cell viability (Long and Ward, 1989b). Some protection from the toxic effects of substrates and/or products can be conferred by immobilizing the biomass, a process also used successfully for enzymes. The potential benefits of immobilization include modification of metabolism, stabilizing and extending the life of the catalyst, broadening the range of reaction conditions, simplifying product recovery and the separation of biomass from spent broth, and simplifying biomass recycling (Navarro and Durand, 1977; Ward and Young, 1990; Shacar-Nishri and Freeman, 1993). One of the negative aspects of immobilization of biomass, as observed by Rogers et al. (1997), is the more limited control over metabolism manifested as reduced L-PAC yields, although enhanced resistance to benzaldehyde was noted. The reduced L-PAC yields were attributed to lower levels of accumulated pyruvate (by a factor of 2-3 times). A further effect of immobilization is limitation of mass transfer owing to reduced diffusion. Both Shin and Rogers (1996b) and Rogers et al. (1997) reported an increased K,,, for pyruvate with immobilized purified PDC.

THE PRODUCTION OF L-PHENYLACETYLCARBINOL BY YEAST

27

Immobilization may be by entrapment within a matrix, adsorption to a support or cross-linking to either a support or to adjacent cells. In studies on L-PACproduction, entrapment in alginate has been the most common method of immobilization, although Seely et al. (1989a) investigated the use of polyazetidine for the immobilization of whole cells, Nikolova and Ward (1994a) tested a variety of polymers using lyophilized yeast, and Shin and Rogers (1995a,b) used polyacrylamide and calcium alginate for the immobilization of PDC. Rogers et al. (1995, 1997) compared the performance of free and immobilized biomass and PDC from various biotransformation processes on the basis of productivity and molar conversion yield (Table 1). Both are important criteria for comparing industrial-scaleprocesses, although the use of productivity, rather than specific productivity as a performance indicator limits the ability to compare different strains or conditions directly. The L-PACyields of the immobilized and free cell processes were similar; however, owing to the reduced productivity of the immobilized biomass additional reaction time was required. Increased L-PACyields and productivities were recorded for the purified and immobilized PDC transformations compared with the whole cell methods. Modified enzyme activity was observed by Shin and Rogers (1995a) when they compared the performance of PDC from C. utilis, both free and immobilized in polyacrylamide beads. The immobilized PDC was reported to have displayed higher activity ( K , = 72 m)and greater tolerance to benzaldehyde (Ki = 161 m) than free PDC, although figures were not given for the free PDC. A Ki for L-PACof 240 r m was reported for immobilized PDC. The modifications in activity and tolerance were attributed to the presence of a benzaldehyde concentration gradient in the beads. The optimum pH differed for free and immobilized PDC, while the reaction with immobilized PDC was more sensitive to temperature. Among the disadvantages of immobilization noted were the lower conversion efficiency and longer time required for biotransformation. Immobilized PDC used on a continuous basis generated an average L-PACconcentration of 4.5 g/l and exhibited a half-life of 29 days, its stability apparently affected by both denaturation of the enzyme and its leakage from the matrix. The average L-PAC concentration contrasted with the maximum of 17.1 g/l achieved using immobilized PDC in a 16-h batch biotransformation. Tripathi et al. (1997) reported free cells to be more efticient at biotransforming benzaldehyde than immobilized cells; they noted that this contradicted the findings of other groups. However, it appears that the benzaldehyde concentration used in their work was within the range where ADH activity exceeded PDC activity. Nikolova and Ward (1994a) investigated the effect of the physicochemical properties of a selection of polymers on the production of L-PACand benzyl alcohol by baker’s yeast. Freshly lyophilized biomass was used as a catalyst for

Table I Comparison of kinetic evaluations for various methods of L-phenylacetylcarbinol (L-PAC)production. Reproduced with permission from Rogers er al. (1997) Process

L-PAC(gll)

Batch and fed-batch proeesse~ Free cells 12.4 22.4 Free cells 12 (cyclodextrins) 9.9 Immobilized cells 10 15 Free PDC 28.6 27.1 Immobilized P d c

continoous pl-omses Immobilized cells Immobilized cells (semicontinuous) Three-stage system (free cells) PDC = pyruvate karboxylase.

Reaction time (h) productivity (g/l.h)

Molar conversion yield (96)

Reference

17 14

57 65

Culik et al. (1984) Wang et al. (1994)

0.73 1.6

3 24 22 8 12

3.3 0.42 0.7 3.6 2.3

59 58 95 93

Mahmoud er ul. (1990~) Seely er al. (1989a) Mahmoud et ul. (199Ob) Shin and Rogers (199%) Shin and Rogers (196a) Shin and Rogers (1996b)

4

-

0.6

45

Shin and Rogers (1995b)

4.5

-

0.4-0.8

57

Mahmoud et al. (199Ob)

10.6

-

0.44

56

Wang (1993)

60

rn W

c

8 z

?

THE PRODUCTION OF L-PHENYLACETYLCARBINOL BY YEAST

29

the transformation of benzaldehyde to L-PAC. The highest L-PAC yield (0.98 g/l) was produced by the free cell suspension followed by the hydrophilic, polyethylene glycol-containing polymers (ENT-4000 and PU-6), the polypropylene glycol-containing gels (PU-3 and ENTP-2000), and lastly the alginate and silicone gels. The hydrophobic gels, PU-3 and ENTP-2000, produced the highest and lowest L-PAC:benzyl alcohol ratios, respectively (1:0.08 and 1:1.80); the free cell suspension was second only to the PU-3 gel in the ratio of product to by-product obtained. The results of the biotransformation were attributed to the physicochemical properties of the gels including hydrophilicity,hydrophobicity and porosity, although little detail as to the relative properties of the polymers was given. The high porosity of alginate beads enables easy and relatively unrestricted diffusion of substrates and products, an important factor in preventing toxicity (Smidsrod and Skjak-Braek, 1990).Mahmoud et al. (1990a,b) investigated the use of S. cerevisiae ATCC 834 immobilized in calcium alginate for both batch and semi-continuous fermentations. The immobilized cells could withstand benzaldehyde concentrations up to 0.6% w/v, while the growth of free cells was inhibited in 0.4% benzaldehyde - 2 . 5 4 times higher than reported by Gupta et al. (1979), who found that 0.15% benzaldehyde was sufficient to inhibit the growth of S. cerevisiae CBS 1171. Increased benzaldehyde tolerance, attributed to the presence of a benzaldehyde concentration gradient, as for Shin and Rogers (1995b), enabled the production of up to 7.5 times more L-PACthan for free cells. The benzaldehyde uptake rate by immobilized cells remained constant at varying initial benzaldehyde concentrations up to 0.6% w/v benzaldehyde. At higher initial benzaldehyde concentrations, the benzaldehyde uptake rate decreased. In contrast, the benzaldehyde uptake rate decreased beyond an initial benzaldehyde concentrationof only 0.4% with free cells. Variation in the L-PAC yield with variation in the bead cell mass was attributed to the development of concentration gradients within the beads and therefore a lower concentration of benzaldehyde being available to the internal biomass. In semi-continuous fermentations undertaken by Mahmoud et al. (1990b), the same batch of biomass beads was used for up to seven cycles with some bead damage and biomass loss observed after three cycles. The observed bead damage coincided with an approximate 50% drop in L-PACproduction, which was possibly due to the increased exposure of the yeast to the benzaldehyde and transformation products, and hence increased toxic effects. Reactivation of the beads after the third cycle made no difference to the L-PACyield per cycle, with similar yields per cycle (2.5-3 g/l) for the third through to the seventh biotransformationcycle. The total amount of L-PACproduced in seven cycles was five times the amount produced in just one cycle. Bead cell mass is an important parameter, with 5 g of beads per 50 ml of medium determined to be the optimal concentration by Tripathi et al. (1991)

30

ALISON L. OLIVER, BRUCE N. ANDERSON AND FELICITY A. RODDICK

for their strain of S. cerevisiae. Higher concentrations of beads resulted in a rapid decline in productivity which was attributed to oxygen limitation. The beads were resuspended in fresh medium that did not contain any pyruvate prior to the biotransformation. Supplementationof the medium with pyruvate may have enabled the use of higher bead concentrations without a loss of productivity. The creation of cross-links between cells using polyazetidine was patented by Seely et al. (1989a) as an alternative method of immobilization. Although the cross-linking of cells to solid substrates including glass beads, sand and ion- exchange resins was described, the cross-linking of cells directly to other cells was preferred, owing to the cost advantages compared with the additional cost of using a physical support. Freshly grown biomass was rendered nonviable, and the cell-wall structure modified to enhance permeability to substrates and products during the preparation process. An added advantage of this method is the ability to store the immobilized biomass for extended periods after preparation. The advantages of immobilizing yeast using polyazetidine on the basis of L-PAC yield could not be determined because the immobilized system was not compared with a free cell system; yields of up to 12 g/l were achieved. While the immobilization matrix appears to have a definite effect, the preparation of the biomass prior to immobilization also has a significant effect on L-PACproduction. Shin and Rogers (1995b) enhanced PDC activity prior to harvesting and immobilization of the biomass by reducing the aeration and stirring rate. They noted that enzyme activity decreased initially after immobilization but was restored to near pre-immobilizationlevels once a glucose feed had been introduced. Liew et al. (1995) used a method dissimilar to the other continuous methods described above, namely a continuous membrane bioreactor where biomass was recovered by membrane filtration. There appeared to be a number of distinct disadvantages with this method; the flux was affected by high biomass concentrations and, as mentioned previously, by lysis of biomass after the addition of benzaldehyde. 3.7.3. Modi$cation of Benzaldehyde Solubility

The effect of benzaldehyde solubility on L-PAC yields has been tested by incorporating co-solvents to increase the concentration of dissolved benzaldehyde in the medium beyond the solubility limit of benzaldehyde in water (0.03 g/lOO ml). Ideally, neither L-PACyield nor L-PACformation should be directly nor adversely affected by the co-solvent used. The effect of increasing benzaldehyde solubility on L-PAC production by S. cerevisiae was tested by Mahmoud et al. (1990a), who dissolved 0.6 ml of benzaldehyde in 6 ml of

THE PROOUCTION OF L-PHENYLACETYLCARBINOL BY YEAST

31

N,N-dimethylformamide (DMF) prior to adding the benzaldehyde to the medium. They found that increasing the solubility of the benzaldehyde in this manner had no significant effect on L-PAC yield, and therefore the benzaldehyde was neither more toxic nor more readily converted to L-PACwhen it was more soluble. The results presented by Mahmoud et al. (1990a), however, did not preclude the possibility of DMF toxicity as a counterbalance to potentially higher L-PACyields in the presence of higher benzaldehyde concentrations. The lack of improvement in yield using DMF as a co-solvent contrasts with the results of Seely et al. (1989a) who, using a strain of S. cerevisiae, described increased conversion rates and final yields when co-solvents were incorporated in the medium to increase the concentration of dissolved benzaldehyde. The co-solvents used included methanol, ethanol, propanol and butanol as well as ethylene glycol, glycerol and polyethylene glycol (PEG) of varying molecular weights. The inclusion of 20% by weight of ethanol as a cosolvent for benzaldehyde in the reaction medium was reported to have increased both the rate of reaction and the final yield of L-PAC (from 0.6 g/l in the absence of ethanol with 25 m~ benzaldehyde, to up to five times in the presence of 25 m~ benzaldehyde and to up to 10 times (5.5 g/l) in the presence of 100 m~ benzaldehyde). L-PAC yields of 10.5 g/l were reported in the presence of glycerol compared with 6 g/l in the absence of the co-solvent. The use of PEG as a co-solvent was considered particularly advantageous because,unlike short-chain alcohols it has no adverse effect on the PDC, . Growth has been found to be more sensitive than fermentation to ethanol inhibition, with concentrations as low as 4 8 % (w/v) being sufficient to reduce the growth rate of a laboratory strain of S. cerevisiae (Brown et al., 1981).An ethanol concentration of 12% (w/v) was required to inhibit growth completely, similar to the ethanol concentration found to inhibit the growth of a commercial S. cerevisiue strain (Brown et al., 1981); 9-10% (w/v) ethanol is commonly reported as being required for complete inhibition of growth (Casey and Ingledew, 1986). The growth rate inhibition constant (Ki) reported for the S. cerevisiae strain used by Brown and co-workers was 2.01% (w/v); the Ki for fermentation was 4.46% (w/v) with a slightly higher fermentation Ki (6.1% (w/v) for the commercial yeast strain. A fermentation Ki of 3.7% was reported by Pascual et al. (1988) for S. cerevisiae. These ethanol concentrations are all significantly lower than the 20% (w/v) ethanol added to the reaction medium by Seely et al. (1989a). However, fermentativeactivity has been reported in the presence of ethanol concentrations as high as 20% (Aiba et al., 1968) and 30% (Casey and Ingledew, 1986), and a lesser degree of toxicity has been reported for ethanol that has been added to yeast cultures compared with endogenously produced ethanol (Nagodawithana and Steinkraus, 1976; Novak et al., 1981; Casey and Ingledew, 1986). However, Pamment and coworkers (Dasari et al., 1990) indicated that the apparent inhibition due to endogenously produced ethanol also included that due to the by-products of the fermentation. On the

32

ALISON L. OLIVER, BRUCE N. ANDERSON AND FELICITY A. RODDICK

other hand, studies by Rogers et al. (1997) indicated a potential positive contribution from added ethanol in that up to 2-3 M ethanol produced an initial rate increase of 3040% in PDC activity. When benzaldehyde was supplied to C. utilis either neat or diluted with ethanol (1:2, v/v) at two dosage rates by Oliver et al. (1997), there was little effect on L-PACproduction, with only slight increases recorded at the higher benzaldehyde dose rate in the presence of ethanol. Carbohydrate metabolism was enhanced and benzaldehyde conversion was reduced with the addition of ethanol and with increased benzaldehyde flow rate, although the benzyl alcohol concentration was 50% less under the latter condition. The reduction in benzyl alcohol yield was probably due to more rapid inactivation of the ADH, as suggested by Agarwal et al. (1987) following their studies with S. cerevisiae. The creation of benzaldehyde inclusion compounds using P-cyclodextrin to both increase the (BCD) was used effectively by Mahmoud et al. (1990~) availability of benzaldehyde and to reduce the exposure of biomass to the benzaldehyde. In the presence of BCD, a total cumulative amount of 12-14 g/l benzaldehyde could be added to the medium, a significantly higher amount than previously reported (5-6 g/l), without causing serious damage to cells. Using such high concentrations of benzaldehyde, L-PAC yields of up to 12 g/l were achieved in the presence of 1.5% BCD compared to a yield of approximately 5.5 g/l L-PAC for the control experiment. Mahmoud and co-workers proposed that improved L-PACyields in the presence of BCD were the result of lower concentrations of free benzaldehyde, owing to its incorporation into BCD inclusion complexes, which in turn reduced the toxic effects of benzaldehyde but possibly also reduced its rate of conversion. A reduction in the rate of benzaldehyde conversion in the presence of BCD was discounted by the observation that maximum L-PACtitres occurred earlier in the presence of the BCD than in the control fermentations and benzaldehyde consumption was more rapid in the former. The role of cyclodextrins as a metabolic stimulant was confirmed by increased rates of glucose consumption with increasing BCD concentration and a trend, although inconclusive, towards increased cell growth rates. 3.7.4. livo-phase Fermentation Medium

Biphasic systems are particularly useful when either the substrate or product is poorly water soluble, as is the case with the L-PAC production process. The biomass or enzymes are suspended in a partially hydrated, water-immiscible solvent and the substrate or products partition into the solvent, As for immobilized cell systems, the advantages of biphasic systems include easy separation of substrate and product from the catalyst and, in some instances

THE PRODUCTION OF L-PHENYLACETYLCARBINOLBY YEAST

33

greater stability of either the enzymes or whole cells (Antonini et al., 1981), although substrate and product inhibition may still occur. Nikolova and Ward have investigated the use of whole cells, cell-free extracts and pure enzymes in biphasic systems for the production of L-PACand benzyl alcohol (Nikolova and Ward, 1992a,b,c). Furthermore, the effect of these solvents on the activity of whole biomass immobilized in silicon-alginate was investigated (Nikolova and Ward, 1993). Hexane, hexadecane, toluene, decane, ethylacetate, butylacetate, toluene and chloroform were evaluated for their ability to support and/or improve the bioconversion potential of yeast in the systems mentioned above. The best yields of both L-PACand benzyl alcohol, with the least cell damage, were achieved with the non-polar solvents hexane and hexadecane using moisture levels of 2% for enzyme systems and 10% for whole cell systems (Nikolova and Ward, 1992a,b,c). When immobilized biomass was used in a non-aqueous system (2% moisture), the solvents for which the highest yields for benzyl alcohol were produced were hexane and decane (Nikolova and Ward, 1993). Below 2% moisture, PDC and ADH activity decreased. The use of whole cell systems obviated the need for cofactors and catalyst extraction, offering instead ease of biomass recycling and improved enzyme stability (Nikolova and Ward, 1992b,c). The activity of yeast ADH and ADH isoenzyme mutants of S.cerevisiae in hexane with 2% moisture was one-half to one-third the activity of the same systems in aqueous medium for benzyl alcohol production; PDC activity was not directly compared (Nikolova and Ward, 1992a,b,c). Yields were generally lower in the biphasic medium, with the exception of the ADH isoenzyme mutant containing ADH I, II and LII which had a similar reaction rate in both media (Nikolova and Ward, 1992a,b,c). Non-polar solvents are perceived to be effective in twophase systems because they are believed to prevent the complete removal of water which is present in the enzyme microenvironment. This rationale is likely to apply also in whole cell systems. 3.8. Other Methods for Influencing L-PACProduction

Other methods used to influence the L-PACfermentation process include the application of low-voltage alternating current to the medium during growth and biotransformation (Ellaiah and Krishna, 1988) and the control of the respiratory quotient (Rogers et al., 1997). The application of an alternating current had no effect on the final L-PACyield and, apart from stating that growth was stimulated, no rationale was put forward for its use by Ellaiah and Krishna. The use of respiratory quotient (the ratio of the rate of CO, production to 0, consumption) to control fermentations is based on the manipulation of fermentative activity. Fully respiratory growth (RQ = 1) resulted in increased benzyl alcohol production and correspondingly poor L-PAC yields. The

34

ALISON L. OLIVER, BRUCE N. ANDERSON AND FELICITY A. RODDICK

optimal RQ for the production of L-PACby C. utilis was determined to be approximately 4-5 (Rogers ef al., 1997). Neither of these methods are currently used for the production of L-PAC.

4. AN INDUSTRIAL PROCESS FOR THE PRODUCTION OF

L-PHENYLACENLCARBINOL

Work conducted by the authors on the effect of nutrients on L-PACproduction was based on a process used on a commercial scale. As described previously, a two-phase fed-batch fermentation procedure was used. The first phase comprised the growth phase where the conditions were conducive to the growth of biomass and accumulation of an exogenous store of pyruvate, while in the second, the bioconversion phase, PDC catalysed the conversion of the accumulated pyruvate and added benzaldehyde to form L-PAC.The growth-phase medium used originally comprised (in g/l): molasses 104, CSL 5.32, glucose syrup 10.6, urea 3.76 and KH,PO, 0.52. A typical 'standard' fermentation is described below; a time line illustrates the variations (Fig. 1). The physical variables of the fermentation were set at pH 5.2, 24.8 "C and 1.2 volumes per volume per minute (vvm) air. The medium was saturated with oxygen prior to inoculation. For an initial period of 2.5-3 h post-inoculation the PO, was stable after which oxygen consumption increased rapidly. Consumption of oxygen exceeded the rate of replenishment and resulted in a PO, of zero within 10 h of inoculation (Fig. 2). Measurement of the partial pressure of dissolved CO, showed that pC0, increased concomitantly with the decrease in PO,, a further indication of increased metabolic activity. During the growth phase, biomass grew actively and the available carbohydrate supply was metabolized until it was exhausted (approximately 16 h after inoculation). A minimum viable cell count of lo9 cells/ml (dry weight of approximately 19 gA) was achieved at the end of the growth phase. Acidification of the medium, as a result of pyruvate production, occurred continuously during the growth phase, requiring the addition of alkali to maintain the pH at the set point of 5.2. Typical exogenous pyruvate concentrations of 4-5 g/l were achieved by the end of the growth phase using the original medium formulation. The bioconversion phase was initiated by the alteration of the independent variables (pH 6.2, 18.8 "C, 0.6 vvm air), the addition of extra medium components [molasses 54 g/l and 16 mV1 nutrient solution containing (in gA): urea 0.89, whey 0.98, KH,PO, 0.59, MgSO, 0.28, and thiamine HC10.0012] plus a dose of benzaldehyde (0.8 mv1). These changes resulted in a sudden increase in p C 0 , followed by a decrease, suggesting that the cells became stressed. Tivo

35

THE PRODUCTION OF L-PHENYLACETYLCARBINOL BY YEAST

Start fermentation 10 L Growth Medium

0.4% (v/v) aliquot

(GP)

16 h. 24.8"C, 1.2 vvm. p H 5.2

Addition of carbohydrate (54 g/L GP medium) Bioconversion mixture (16 mUL GP medium) Benzaldehyde aliquot (0.8 mUL GP medium)

Initiate Bioconversion Phase (BPI

2 h, 18.8" C,0.6 vvm. pH 6.2

Addition of carbohydrate (74 GP medium) Continuous benzaldehyde flow commenced ( I .5 mUL GP medium.h)

I

.

I

Initiate Pump Start (PSI I

22 h, 18.8" C, 0.6 wm,p H 6.2

Acidification of medium ceases, continuous addition of acid commences (AR) (approx. 5 h after BP initiated)

A

PdinpCQ (approx. 12 h after BP initiated)

1 0 1 1 Fermentation terminated after

Figure I Schematic diagram of the procedure followed for a standard fermentation by Oliver et nl. (1997).

36

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I

8 7

I

7

I

l-

s

I

8

I 9

0

I

3

I

I

I 0 rn

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8

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:

I

2I

2 7

8

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z I z

I

ALISON L. OLIVER, BRUCE N. ANDERSON AND FELICITY A. RODDICK

z :

THE PRODUCTION OF L-PHENYLACETYLCARBINOL BY YEAST

37

hours later, further molasses was added (74 gA) and a pump started to add benzaldehyde continuously (total 15 m u ) at 1.5 ml/l.h. Acidification of the medium due to the production of pyruvate continued for approximately 5 h after the initiation of the bioconversion phase, albeit at a reduced rate. After this time, the rate of alkali dosing slowed and the pH gradually rose above the bioconversion phase set point of 6.2 (Fig. 2) and acid addition commenced. The increase in pH and the resulting acid dosing to maintain the pH suggested that pyruvate was being metabolized (resulting in L-PACor other less acidic metabolites). The period between the cessation of alkali dosing and the commencement of acid dosing was designated as the acid rollover. The acid rollover coincided with the commencement of an increase in the PO, and a decrease in the p C 0 , The biomass concentration contmued to increase for a few hours after the initiation of the bioconversion phase and then began to decline. Cell viability remained higher than 90%, after which a decline in both biomass concentration and viability commenced. Viability was less than 5% at the end of the fermentation. Approximately 12 h after the initiation of the bioconversion phase, there was a surge in the pCO,, which then subsided over a period of approximately 4 h. The peak was indicative of an increase in PDC activity, CO, being a product of the PDC-catalysed reaction. A small dip in the PO, occurred concomitantly with the increase in CO, concentration. The fermentation was continued for a total of 40 h before it was terminated, based on the protocol for full-scale commercial L-PAC production. The protocol followed was intended to maximize the L-PAC yields achieved, based on the physiological behaviour of yeast as described earlier in this review. Biomass was allowed to grow under good aeration conditions, producing an endogenous supply of pyruvate, until, by the end of the growth phase, the conditions had become fermentative because of the high rate of oxygen consumption. The reduction of aeration at the start of the bioconversion phase helped to ensure that the conditions remained partially fermentative, and the medium was pulsed with carbohydrate to induce PDC activity. A pulse of benzaldehyde was also added to stimulate the PDC activity without causing excessive benzyl alcohol production. The slow benzaldehyde feed started later was intended to maintain PDC activity at higher rates than ADH activity. The main aim of the authors’ study was the simplification of the fermentation medium without detriment to the L-PAC yield. The potential benefits included reduced production costs, and reduced nutrient load and chemical oxygen demand (COD) in the spent broth. They successfully demonstrated that up to 60% of the molasses added to the medium could be replaced by sucrose (as raw sugar), to give an increase in L-PAC (to 14 g/l) and pyruvate (6 g/l) yields. No effect was observed on the benzyl alcohol yield (1.1 g/l). The effect

38

ALISON L. OLIVER, BRUCE N. ANDERSON AND FELICITY A. RODDICK

of such a change is an anticipated savings in storage costs owing to the proportionately higher sucrose concentration in raw sugar compared with molasses. Later studies by the authors also demonstrated that the total concentration of carbohydrate in the growth-phase medium could be reduced by up to 20% without significant losses in L-PACyield. A guaranteed minimum of 10 g/l of L-PACcould not be achieved if the bioconversion phase carbohydrate content was reduced by more than 25%. Both CSL and whey powder were added in relatively small quantities and the exact role of either component was unknown. CSL is high in nitrogenous compounds and this, combined with the fact that a considerable quantity was added to the fermentation medium with respect to the amount of urea added, was thought to be the reason for its inclusion in the medium. Results show, however, that omission of CSL from the medium had no detrimental effects on the overall outcome of the fermentation. Marginally increased pyruvate yields, attributed to increased glycolytic flux, were recorded (6.7 g/l), as was a reduction in ADH activity (benzyl alcohol yields of 0.5 g/l). These changes did not, however, translate to increased L-PAC yields, which remained essentially unchanged (12.8 g/l). The addition of whey to the medium was originally undertaken to provide a source of lactose. However, because C. utilis is unable to utilize this carbohydrate (the medium was not originally developed for the growth of C. utilis), the inclusion of whey in the medium was considered superfluous. Whey also contributes lactic acid (which C. utilis can utilize) and thiamine, but at the concentrations present combined with the amount of whey added to the medium, the contribution of both was considered to be insignificant. The omission of whey from the medium proved to be apparently beneficial, resulting in a 15% increase in the acid rollover pyruvate concentration. However, there was no effect observed on L-PAC yield, or on any of the other measured variables, including benzyl alcohol concentration. Preliminary experiments were undertaken by Oliver et al. ( 1997) to determine the effect of lowering urea and potassium dihydrogen phosphate concentrations. The results indicated that both of these materials could be reduced by up to 15% without any detrimental effect on either the L-PAC or the benzyl alcohol yields. As an extension to the work on the fermentation medium composition, the effect of benzaldehyde feed rate and acetaldehyde or ethanol addition were examined. While work by both Long and Ward (1989b) and Mahmoud et al. (1990b) demonstrated the benefits of benzaldehyde dosing over extended periods, Agarwal and co-workers (1987) showed that ADH activity remained higher than that of PDC when benzaldehyde concentrations were less than 4 m~ (Section 3.7.1). The rationale behind increasing the benzaldehyde flow rate was thus to raise the benzaldehyde concentration to a level such that ADH activity, and subsequently benzyl alcohol yield, would be significantly reduced.

THE PRODUCTION OF L-PHENYLACETYLCARBINOL BY YEAST

39

Increasing the benzaldehyde flow rate from 1.2 ml/l.h to 2.5 mVl.h successfully brought about a reduction in benzyl alcohol concentration of 50%, although the resulting increase in L-PACyield was less than 10% (to approximately 13 gA). Increasing benzaldehyde flow rates also resulted in marginally reduced (slightly more than 10%)pyruvate concentrations. The lower benzyl alcohol concentrations were thought to be due to premature inactivation of ADH, as proposed by Agarwal et al. (1987). As noted in Section 3.6, it has been proposed that acetaldehyde can compete with benzaldehyde for sites on ADH. In studies by Oliver (1996), significant gains were made in the yield and efficiency of L-PACproduction in the presence of added acetaldehyde, although reductions in the benzyl alcohol yield were minimal. The addition of ethanol (up to a total of 9.8 g/l) was also tested as a method for increasing benzaldehyde solubility. The result was a very slight reduction in benzyl alcohol production at low benzaldehyde flow rates but minimal effect at the maximum benzaldehyde flow rate (2.5 ml/l.h) tested. The effect of added ethanol on L-PAC yield was negligible. The limited effects of ethanol dosing observed were considered to result from the addition of ethanol at inappropriately low levels in the study since the amount of ethanol added (0.22 M) was substantially less than the 2-3 M concentration shown by Rogers et al. (1997) to be required before an effect is observed on PDC activity in C. utilis. Acetaldehyde dosing was also undertaken. However, there was no effect on L-PACor benzyl alcohol yields when concentrations of 2 g/l or less were added.

5. CONCLUSION

In theory, the L-PACproduction process appears to be a straightforward condensation of added benzaldehyde with acetaldehyde generated metabolically through the decarboxylation of pyruvate. In practice, the process is far from simple because of toxicity effects from the substrate (benzaldehyde),the principal by-product (benzyl alcohol) and the product itself (L-PAC).A number of strategies have been employed to ameliorate the toxic effects, and to maximize the L-PACyield, whilst minimizing the generation of by-products. Such strategies rely heavily on increased understanding of the predominant enzyme systems involved (PDC and ADH), together with a more detailed understanding of the biochemical and physiological basis for variations in L-PAC yield between the yeast species examined and the different fermentation systems employed. The effects of nutrients on L-PAC production are less well understood and appear to be worthy of further investigation. An overall increase in the understanding of the biochemistry and physiology of yeast systems capable

40

ALISON L. OLIVER, BRUCE N. ANDERSON AND FELICITY A. RODDICK

of L-PACsynthesis will aid in the optimization of full-scale L-PACproduction through productivity increases and reduced medium-related expenses.

Agarwal, S.C. and Basu, S.K. (1989) Biotransformation of benzaldehyde to L-acetyl phenyl carbinol by fed batch culture system. J. Microb. Eiorechnol. 4, 84-86. Agarwal, S.C., Basu, S.K., Vora, V.C., Mason, J.R. and Pirt, S.J. (1 987) Studies on the production of L-acetyl phenyl carbinol by yeast employing benzaldehyde as precursor. Biotech. Eioeng. 29,783-785. Aiba, S., Shoda, M. and Nagatani, M. (1968) Kinetics of product inhibition in alcohol fermentation. Biotech. Eioeng. 10, 845-864. Antonini, E., Carrea, G. and Cremonesi, P. (1981) Enzyme catalysed reactions in water organic solvent two-phase systems. Enzyme Microb. Technol. 3,291-296. Becvarova, H. and Hanc, 0. (1963) Production of phenylacetylcarbinol by various yeast species. Folia Microbiol. 8, 4 2 4 7 . Becvarova, H., Hanc, 0. and Macek, K. (1963) Course of transformation of benzaldehyde by Saccharomyces cerevisiae. Folia Microbiol. 8, 165-169. Berry, D.R. and Brown, C. (1987) Physiology of yeast growth. In: Yeast Eiotechnology (D. R. Berry, I. Russell, and G. G Stewart, eds), pp. 159-199. Allen and Unwin, London. Boiteux, A. and Hess, B. (1970) Allosteric properties of yeast pyruvate decarboxylase. FEES Lett. 9,293-296. Bowen, W.R., Pugh, S.Y.R. and Schomburgk, N.J.D. (1986) Inhibition of horse liver and yeast alcohol dehydrogenase by aromatic and aliphatic aldehydes. J. Chem. Technol. Eiotechnol. 36, 191-196. Bringer-Meyer, S. and Sahm, H. (1988) Acetoin and phenylacetylcarbinol formation by the pyruvate decarboxylases of Zymomonas mobilis and Saccharomyces carlsbergensis. Eiocatalysis 1,321-33 1. Brown, S.W., Oliver, S.G., Harrison, D.E.F. and Righelato, R.C. (1981) Ethanol inhibition of yeast growth and fermentation: differences in the magnitude and complexity of the effect. Eul: J. Appl. Microbiol. Eiotechnol. 11, 151-155. Cardillo, R., Servi, S. and Tinti, C. (1991) Biotransformation of unsaturated aldehydes by microorganisms with pyruvate decarboxylase activity. Appl. Microbiol. Eiotechnol. 36, 300-303. Carlsen, H.N.. Degn, H and Lloyd, D. (1991) Effects of alcohols on the respiration and fermentation of aerated suspensions of baker’s yeast. J. Gen. Micmbiol. 137,2879-2883. Casey, G . P. and Ingledew, W.M. (1986) Ethanol tolerance in yeasts. CRC Crit. Rev. Microbiol. 13, 219-280. Cejka, A. (1985) Preparation of media. In: Eiotechnology: A Comprehensive Treatise, Vol. 2 (H.-J. Rehm and G. Reed, eds), pp. 630-698. Verlag-Chemie, Weinheim. Chow, Y.S., Shin, H.S., Adesina, A.A. and Rogers, P.L. (1995) A kinetic model for the deactivation of pyruvate decarboxylase (PDC) by benzaldehyde. EiotechnoL Letr. 17, 1201-1 206. Conn, E.E., Stumpf, P.K., Bruening, G. and Doi, R.H. (1987) Outlines ofEiochemistry, 5th edn. John Wiley and Sons, Singapore. Crout, D.H.G.. Dalton, H., Hutchinson, D.W. and Miyagoshi, M. (1991) Studies on pyruvate decarboxylase: acyloin formation from aliphatic, aromatic and heterocyclic aldehydes. J. Chem. Soc. Perkin Trans. 1329-1334.

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Culik, K., Netrval, J., Souhrada, J., Ulbrecht, S., Vojtisek, V. and Vodnansky, M. (1984) Czech patent no. 222941. Dasari, G., Worth, M.A., Connor, M.A. and Pamment, N.B. (1990) Reasons for the apparent differences in the effects of produced and added ethanol on culture viability during rapid fermentations by Saccharornyces cerevisiae. Biotechnol. Bioeng. 35, 109- 122. Demck, S. and Large, P. J. (1993) Activities of the enzymes of the Ehrlich pathway and formation of branched-chain alcohols in Saccharomyces cerevisiae and Candida utilis grown in continuous culture on valine or ammonium as sole nitrogen source. J. Gen. Microbiol. 139, 2783-2792. Dijken, J.P. van and Scheffers, W.A. (1986) Redox balances in the metabolism of sugars by yeasts. FEMS Micmbiol. Rev. 32, 199-224. Dissara, Y.and Rogers, P.L. (1995) Evaluation of mutants of Candida utilis for L-PAC production from benzaldehyde. Proceedings of the 4th Pacific Rim Biotechnology Conference, pp. 248-249. Ellaiah, P. and Krishna, K.T. (1987) Studies on the production of phenyl acetyl carbinol from benzaldehyde by Saccharomyces cerevisiae. Indian Drugs 24, 192-1 95. Ellaiah, P. and Krishna, K.T. (1988) Effect of aeration and alternating current on the production of phenyl acetyl carbinol by Saccharomyces cerevisiae. Indian J. Technol. 26, 509-5 10. Flikweert, M.T., Zanden, L. van der, Janssen, W.M. T.M., Steensma, H.Y., Dijken, J.P. van and Pronk, J. T. ( I 996) Pyruvate decarboxylase: an indispensable enzyme for growth of Saccharomyces cerevisiae on glucose. Yeast 12, 247-257. Fuganti, C., Grasselli, P., Poli, G., Servi, S. and Zorzella, A. (1988) Decarboxylative incorporation of a-oxobutyrate and a-oxovalerate into (R)-a-hydroxyethyl- and n-propyl ketones on reaction with aromatic and a$-unsaturated aldehydes in baker’s yeast. J. Chem. SOC. Chem. Commun. 16 19- 1621. Ghoul, M., Boudrant, J. and Engasser, J.M. (1991)A comparison of different techniques for the control of the growth of Candida utilis CBS 621. Process Biochem. 26, 135-142. Green, D.E., Westerfeld, W.V., Vennesland, B. and Knox, W.E. (1942) Carboxylases of animal tissues. J. Biol. Chem. 145, 69-84. Gross, N.H. and Werkman, C. H. (1947) Isotopic composition of acetyl methyl carbinol formed by yeast juice. Arch. Biochern. 15, 125-131. Gupta, K.G., Singh, J., Sahni, G. and Dhawan, S. (1979) Production of phenyl acetyl carbinol by yeasts. Biotechnol. Bioeng. 21, 1085-1089. Happold, F.C. and Spencer, C. P. (1952) The enzymic formation of acetylmethylcarbinol and related compounds. Biochim. Biophys. Acta. 8,543-556. Harrison, D.E.F. (1972) Physiological effects of dissolved oxygen tension and redox potential on growing populations of micro-organisms. J. Appl. Chem. Biotechnol. 22, 417-440. Hohmann, S. (1997) Pyruvate decarboxylases. In: Yeast Sugar Metabolism (F.K. Zimmerman and K.-D. Entian, eds), pp. 187-21 1. Technomic, Lancaster, PA. Hubner, G., Weidhase, R. and Schellenberger, A. (1978) The mechanism of substrate activation of pyruvate decarboxylase: a first approach. Eul: J. Biochem. 92,175-1 81. Jones, R. P. (1989) Biological principles for the effects of ethanol. Enzyme Microb. Technol. 11,130-153. Jones, R.P. and Greenfield, P.F. (1984) A review of yeast ionic nutrition. Part I: growth and fermentation requirements. Process Biochem. 19,4840. Jones, R.P., Pamment, N. and Greenfield, P. F. (1981) Alcohol fermentation by yeasts -the effect of environmental and other variables. Process Biochem. 16,4249. Juni, E. (1952) Mechanisms of the formation of acetoin by yeast and mammalian tissue. J. Biol. Chem. 195,727-734.

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Juni, E. (1961) Evidence for a two-site mechanism for decarboxylation of a-keto acids by a-carboxylase. J. Biol. Chem. 236,2302-2308. k e n , V., Crout, D.H.G., Dalton, H., Hutchinson, D.W., Konig, W., Turner, M.M., Dean, G. and Thomson, N. (1993) Pyruvate decarboxylase: a new enzyme for the production of acyloins by biotransformation. J. Chem. SOC. Chem. Commun. 341-343. Leskovac, V., Trivic, S., Zeremski, J., Stancic, B. and Anderson, B.M. (1997) Novel substrates of yeast alcohol dehydrogenase - 3,4-dimethylamino-cinnamaldehyde and chloroacetaldehyde. Biochem. Mol. Biol. Int. 43, 365-373. Liew, M.K.H., Fane, A.G. and Rogers, P.L. (1995) Applicability of continuous membrane bioreactor in production of phenylacetylcarbinol. J. Chem. Tech. Biotechnol. 64, 200-206. Long, A. and Ward, O.P. (1989a) Biotransformation of aromatic aldehydes by Sacchatumyces cerevisiae: investigation of reaction rates. . I . Industrial Microbiol. 4, 49-53. Long, A. and Ward, O.P. (1989b). Biotransformation of benzaldehyde by Saccharrmyces cerevisiae: characterization of the fermentation and toxicity effects of substrates and products. Biotechnol. Bioeng. 34,933-94 I . Long, A., James, P. and Ward, O.P. (1989) Aromatic aldehydes as substrates for yeast and yeast alcohol dehydrogenase. Biotechnol. Bioeng. 33,657-660. Mahmoud, W.M., El-Sayed, A.H. and Coughlin, R.W. (1990a) Production of L-phenylacetyl carbinol by immobilised yeast cells: I. Batch fermentation. Biotechnol. Bioeng. 36,47-54. Mahmoud, W.M., El-Sayed, A.H. and Coughlin, R.W. (1990b) Production of‘ L-phenylacetyl carbinol by immobilised yeast cells: 11. Semicontinuous fermentation. Biotechnol. Bioeng. 36, 55-63. Mahmoud, W. M., El-Sayed, A.H. and Coughlin, R.W. (1990~)Effect of P-cyclodextrin on production of L-phenylacetyl carbinol by immobilised cells of Saccharomyces cerevisiae. Biotechnol. Bioeng. 36, 256-262. Maitra, P.K. and Lobo, Z. (1971) A kinetic study of glycolytic enzyme synthesis in yeast. J. Biol. Chem. 246,475488, McKenzie, A. (1936) Asymmetric synthesis. Ergebnisse Enzymforsch. 5,49-78. Meyrath, J. and Bayer, K. (1979) Biomass from whey. In: Economic Microbiology, Vol. 4 (A. H. Rose, ed.), pp. 207-269. Academic Press, London. Morton, J.F. (1977) Major Medicinal Plants: Botany, Culture and Uses, pp. 33-36. Charles C. Thomas, Springfield. Nagodawithana, T.W. and Steinkraus, K.H. (1976) Influence of the rate of ethanol production and accumulation on the viability of Saccharomyces cerevisiae in ‘rapid fermentation’. Appl. Environ. Microbiol. 31, 158-162. Nagodawithana, T.W., Castellano, C. and Steinkraus, K.H. (1974) Effect of dissolved oxygen, temperature, initial cell count and sugar concentration on the viability of Saccharomyces cerevisiae in rapid fermentations. Appl. Microhiol. 28, 383-39 I . Navarro, J.M. and Durand, G. (1977) Modification of yeast metabolism by immobilization onto porous glass. Eur: J. Appl. Microbiol. 4,243-254. Netrval, J . and Vojtisek, V. (1982) Production of phenylacetylcarbinol in various yeast species. Eur: J. Appl. Microbiol. Biotechnol. 16, 35-38. Nikolova, P. and Ward, O.P. (1 99 1) Production of L-phenylacetyl carbinol by biotransformation: product and by-product formation and activities of the key enzymes in wild-type and ADH isoenzyme mutants of Sacchatumyces cerevisiae. Biotechnol. Bioeng. 20,493498. Nikolova, P. and Ward, O.P. (1992a) Production of phenylacetyl carbinol by biotransformation using baker’s yeast in two-phase systems. In: Biocatalysis in Non-conventional Media (J. Tramper et al., eds), pp. 675-680. Elsevier Science Publishers, Amsterdam.

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Nikolova, P. and Ward, O.P. (1992b) Reductive biotransformation by wild type and mutant strains of Saccharomyces cerevisiae in aqueous-organic solvent biphasic systems. Biotechnol. Bioeng. 39, 870-876. Nikolova, P. and Ward, O.P. ( 1 992c) Whole cell yeast biotransformations in two-phase systems: effect of solvent on product formation and cell structure. J. Industrial Micmbiol. 10, 169-177. Nikolova, P. and Ward, O.P. (1993) Effect of organic solvent on biotransformation of benzaldehyde to benzyl alcohol by free and silicone-alginate entrapped cells. Biotechnol. Technol. 7 , 897-902. Nikolova, P. and Ward, O.P. (1994a) Effect of support matrix on ratio of product to by-product formation in L-phenylacetyl carbinol synthesis. Biotechnol. Lett. 16,7-10. Nikolova, P. and Ward, O.P. (1994b) Reductive biotransformation of benzaldehyde derivatives by baker’s yeast in non-conventional media: effect of substrate hydrophobicity on the biocatalytic reaction. Biocutulysis 9,329-341. Nikolova, P., Long, A. and Ward, O.P. (1991) Colorimetric determination of L-phenylacetyl carbinol produced by biotransformation of benzaldehyde and pyruvate using Saccharomyces cerevisiae. Biotechnol. Technol. 5 , 3 1-34. Noronha, S . and Moreira, A.R., (1993). Bioconversion of benzaldehyde by yeast. Ahstr: Pup. Am. Chem. SOC.205, Biot, 173. Novak, M., Strehaiano, P., Moreno, M. and Goma, G. (1981) Alcoholic fermentation: on the inhibitory effect of ethanol. Biotechnol. Bioeng. 23, 201-21 1. Oliver, A. L. (1996) Influence of medium components on the production of phenylacetylcarbinol (PAC) by yeast. M. App. Sci. Thesis. Royal Melbourne Institute of Technology, Melbourne, Australia. Oliver, A.L., Roddick, F.A. and Anderson, B.N. (1997). Cleaner production of phenylacetylcarbinol through productivity improvements and waste minimization. Pure Appl. Chem. 69,2371-2385. Ose, S . and Hironaka, J. (1957) Studies on production of phenyl acetyl carbinol by fermentation. Proceedings of the International Symposium on Enzyme Chemistry 2, 457460. Oura, E. (1983) Biomass. In: Biotechnology: A Comprehensive Treatise, Vol. 3 (H.-J. Rehm and G. Reed, eds), pp. 18-19. Verlag-Chemie, Weinheim. Pascual, C., Alonso, A., Garcia, I., Romay, C. and Kotyk, A. (1988) Effect of ethanol on glucose transport, key glycolytic enzymes, and proton extrusion in Saccharomyces cerevisiae. Biotechnol. Bioeng. 32, 374-378. Pohl, M. (1997) Protein design on pyruvate decarboxylase (PDC) by site-directed mutagenesis Adv. Biochem. Eng. Biotechnol. 58, 15-43. Reed, G. and Peppler, H.J. (1973) Yeast Technology. AVI, Connecticut. Rogers, P.L. (1990) ICI Internal Report. Orica Ltd, Ascot Vale, Victoria, Australia. Rogers, P.L., Shin, H.S. and Wang, B. (1995) Review of biotransformation of benzaldehyde to L-phenylacetylcarbinol (L-PAC), an intermediate in L-ephedrine production. Proceedings of the 4th Pac$c Rim Biotechnology Conference, pp. 2 10-2 11. Rogers, P.L. Shin, H.S. and Wang, B (1997) Biotransformation for ephedrine production. Adv. Biochem. Eng. Biotechnol. 56,33-59. Romano, P. and Suzzi, G. (1996) Origin and production of acetoin during wine yeast fermentation. Appl. Environ. Microhiol. 62, 309-3 15. Sambamurthy, K., Ellaiah, P. and Krishna, K.T. (1984) Studies on the production of phenyl acetyl carbinol from benzaldehyde by Saccharomyces cerevisiae. Indian J. Pharm. Sci. Jan-Feb, 62. Schmitt, H.D. and Zimmermann, F.K. (1982) Genetic analysis of the pyruvate decarboxylase reaction in yeast glycolysis. J. Bacteriol. 151, 1146-1 152.

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Schure, E.G. ter, Flikweert, M.T., Dijken, J.P. van, Pronk, J.T. and Venips, C.T. (1998) Pyruvate decarboxylase catalyses decarboxylation of branched-chain 2-oxoacids but is not essential for fuse1 alcohol production by Saccharomyces cerevisiae. Appl. Environ. Microbiol. 64, 1303-1 307. Seely, R.J., Heefner, D.L., Hageman, R.V., Yarus, M.J. and Sullivan, S.A. (1989a) US patent 89/04421. Seely, R.J., Hageman, R.V., Yarus, M.J. and Sullivan, S.A. (1989b) US patent 89/04423. Shacar-Nishri, Y. and Freeman, A. (1993) Continuous production of acetaldehyde by immobilked yeast with in situ product trapping. Appl. Biochem. Biotechnol. 39140,387-399. Shin, H.S. and Rogers, P.L. (1995a) Kinetics of biotransformation of benzaldebyde to Lphenylacetylcarbinol (L-PAC) by immobilised pyruvate decarboxylase from Candidu utilis. Proceedings ofthe 4th Pacgc Rim Biotechnology Conference, pp. 328-329. Shin, H.S. and Rogers, P.L. ( I 995b) Biotransformation of benzaldehyde to L-phenylacetylcarbinol, in intermediate in L-ephedrine production, by immobilised Candidu utilis. Appl. Microbiol. Biotechnol. 4 7 - 1 4 . Shin, H.S. and Rogers, P.L. (1996a) Production of L-phenylacetylcarbinol (L-PAC) from benzaldehyde using partially purified pyruvate decarboxylase (PDC). BiotechnoL Bioeng. 49, 52-62. Shin, H.S. and Rogers, P.L. (1996b) Kinetic evaluation of biotransformation of benzaldehyde to L-phenylacetylcarbinol by immobilised pyruvate decarboxylase from Candidu utilis. Biotechnol. Bioeng. 49,429-436. Sims, A.P. and Barnett. J.A. (1991) Levels of activity of enzymes involved in anaerobic utilization of sugars by six yeast species: observations towards understanding the Kluyver effect. FEMS Microbiol. Lett. 77, 295-298. Sims, A.P., Stalbrand, H. and Bamett. J.A. (1991) The role of pyruvate decarboxylase in the Kluyver effect in the food yeast, Candidu utilis. Yeast 7,479-487. Smidsrod, 0 . and Skjak-Braek, G. (1990) Alginate as immobilization matrix for cells. Trends Biotechnol. 8, 71-78. Smith, P.F. and Hendlin, D. (1953) Mechanism of phenylacetylcarbinol synthesis by yeast. J. Bacteriol. 65,440-445. Smith, P.F. and Hendlin, D. (1954) Further studies on phenylacetylcarbinol synthesis by yeast. Appl. Microbiof. 2, 294. Stanbury, P.F. and Whitaker, A. ( 1 984) Principles of Fermentation Technology, pp. 74-90. Pergamon Press, Oxford. Stanley, G.A. (1993) Acetaldehyde effects in Saccharomyces cerevisiae. Ph.D. thesis, University of Melbourne, Australia. Stanley, G.A., Douglas, N.G., Every, E. J., Tzanatos, T. and Pamment, N. B. (1993) Inhibition and stimulation of yeast growth by acetaldehyde. Biotechnol. Lett. 15, 1199-1204. Tripathi, C.K.M., Basu, S.K., Vora, V.C., Mason, J.R. and Pirt, S.J. (1988) Continuous cultivation of a yeast strain from biotransformation of L-acetyl phenyl carbinol (L-PAC) from benzaldehyde. Biotechnol. Lett. 10,635-636. Tripathi, C.K.M., Basu, S.K., Vora, V.C., Mason, J.R. and Pirt, S.J. (1991) Biotransformation of benzaldehyde to L-acetyl phenyl carbinol (L-PAC)by immobilised yeast cells. Res. Industry 36, 159-160. Tripathi, C.K.M., Agarwal, S.C., Bihari, V., Joshi, A.H. and Basu, S.K. (1997) Production of L-phenylacetylcarbinol by free and immobilised yeast cells. Indian J. Exp. Biol. 35, 886-889. Urk, H. van, Mak, P.R., Scheffers, W.A. and Dijken, J.P. van ( I 988) Metabolic responses of Saccharomyces cerevisiae CBS 8066 and Candida utilis CBS 621 upon transition from glucose limitation to glucose excess. Yeast 4, 283-291.

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Urk, H. van, Schipper, D., Breedveld, G.J., Mak, P.R., Scheffers, W.A. and Dijken, J.P. van ( 1989) Localization and kinetics of pyruvate-metabolising enzymes in relation to aerobic alcoholic fermentation in Saccharomyces cerevisiae CBS 8066 and Candida utilis CBS 621. Biochim. Biophys. Acta 992.78-86. Urk, H. van, Voll, W.S.L., Scheffers, W.A. and Dijken, J.P. van (1990) Transient-state analysis of metabolic fluxes in Crabtree-positive and Crabtree-negative yeasts. Appl. Environ. Microbiol. 56, 281-287. Verduyn, C., Breedveld, G.J., Scheffers, W.A. and Dijken, J.P. van (1988) Substrate specificity of alcohol dehydrogenase from the yeasts Hansenula polymorpha CBS 4732 and Candida utilis CBS 621. Yeast 4, 143-148. Voets, J.P., Vandamme, E.J. and Vlerick, C. (1973) Some aspects of the phenylacetyl carbinol biosynthesis by Saccharomyces cerevisiae. Z. Allg. Mikrobiol. 13,355. Vojtisek, V. and Netrval, J. (1982) Effect of pyruvate decarboxylase activity and of pyruvate concentration on the production of 1 -hydroxy- 1-phenylpropanone in Saccharornyces carlshergensis. Folia Microbiol. 27, 173-177. Wang, B. (1993) Kinetic study of fed-batch and continuous bioconversion processes for Lphenylacetylcarbinol (L-PAC) production by the yeast Candida utilis. Ph.D. thesis, University of New South Wales, Sydney, Australia. Wang, B., Shin, H.S. and Rogers, P.L. (1994) Microbial and enzymatic biotransformation of benzaldehyde to L-phenylacetylcarbinol (L-PAC),an intermediate in L-ephedrine production. In: Better Living Through Innovative Biochemical Engineering (W.K. Teo, M. G.S. Yap and S.W.K. Oh, eds), p. 249. Continental Press, Singapore. Ward, O.P. and Young, C. S. (1990) Reductive biotransforrnations of organic compounds by cells or enzymes of yeast. Enzyme Microb. Technol. 12,482-493. Zabriskie, D.W., Arrniger, W.B., Phillips, D.G. and Albano, P.A. (1980) Traders’ Guide to Fermentation Media Formulation.Traders’ Protein Division, Traders’ Oil Mill Company, Memphis, TN.

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Fungal Production of Citric and Oxalic Acid: Importance in Metal Speciation, Physiology and Biogeochemical Processes Geoffrey M. Gadd Department of Biological Sciences, University of Dundee, Dundee, DDI 4HN9 UK

ABSTRACT

The production of organic acids by fungi has profound implications for metal speciation, physiology and biogeochemical cycles. Biosynthesis of oxalic acid from glucose occurs by hydrolysis of oxaloacetate to oxalate and acetate catalysed by cytosolic oxaloacetase, whereas on citric acid, oxalate production occurs by means of glyoxylate oxidation. Citric acid is an intermediate in the tricarboxylic acid cycle, with metals greatly influencing biosynthesis: growth limiting concentrations of Mn, Fe and Zn are important for high yields. The metal-complexing properties of these organic acids assist both essential metal and anionic (e.g. phosphate) nutrition of fungi, other microbes and plants, and determine metal speciation and mobility in the environment, including transfer between terrestrial and aquatic habitats, biocorrosion and weathering. Metal solubilization processes are also of potential for metal recovery and reclamation from contaminated solid wastes, soils and low-grade ores. Such ‘heterotrophicleaching’can occur by several mechanisms but organic acids occupy a central position in the overall process, supplying both protons and a metal-complexing organic acid anion. Most simple metal oxalates [except those of alkali metals, Fe(II1) and All are sparingly soluble and precipitate as crystalline or amorphous solids. Calcium oxalate is the most important manifestation of this in the environment and, in a variety of crystalline structures, is ubiquitously associated with free-living, plant symbiotic and pathogenic fungi. The main forms are the monohydrate (whewellite) and the dihydrate (weddelite) and their formation is of significance in biomineralization, since they affect nutritional heterogeneity in soil, especially Ca, P, K and A1 cycling. The formation of insoluble toxic metal oxalates, e.g. of Cu, may confer ADVANCES IN MICROBIAL PHYSIOLOGY VOL 41 ISBN 0-12-027741-7

Copyright 0 1999 Academic Press All rights of reproduction in any form reserved

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GEOFFREY M. GADD

tolerance and ensure survival in contaminated environments. In semiarid environments, calcium oxalate formation is important in the formation and alteration of terrestrial subsurface limestones. Oxalate also plays an important role in lignocellulose degradation and plant pathogenesis, affecting activities of key enzymes and metal oxidoreduction reactions, therefore underpinning one of the most fundamental roles of fungi in carbon cycling in the natural environment. This review discusses the physiology and chemistry of citric and oxalic acid production in fungi, the intimate association of these acids and processes with metal speciation, physiology and mobility, and their importance and involvement in key fungal-mediated processes, including lignocellulose degradation, plant pathogenesis and metal biogeochemistry. 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2. Metal chemistry of oxalic and citric acids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3. Fungal biosynthesis of oxalic acid and calcium oxalate formation . . . . . . . . . . . 3.1. Oxalic acid biosynthesis ......................................... 3.2. Calcium oxalate ................................................ 4. Role of metals and oxalate in lignocellulose degradation and plant pathogenesis ...................................................... 4.1. Lignocellulose degradation ...................................... 4.2. Plant pathogenesis ............................................. 5. Catabolism of oxalic acid ............................................ 6. Fungal biosynthesis of citric acid ...................................... 6.1. Role of metals in citric acid production ............................. 7. Fungal organic acid production and metal biogeochemistry . . . . . . . . . . . . . . . 7.1. Metal solubilization and anion mobility ............................. 7.2. Role of organic acids in corrosion of stone and building materials . . . . . . 7.3. Role of fungal oxalate in limestone biomineralization . . . . . . . . . . . . . . . . . 8. Fungal organic acid production and metal biotechnology ................. 8.1. Metal solubilization for recovery and bioremediation . . . . . . . . . . . . . . . . . Acknowledgements ................................................. References ........................................................

48 50 53 53 55 61 61 64 65 65 67 68 68 72 74 76 76 78 79

1. INTRODUCTION

In the terrestrial environment,fungi are of fundamental importance as decomposers, plant pathogens and symbionts (mycorrhizas),playing important roles in carbon, nitrogen and other biogeochemical cycles (Wainwright, 1988).They are often dominant in acidic conditions and, in soil, can comprise the largest pool of biomass (including other microorganisms and invertebrates)(Metting, 1992). This, combined with their branching filamentous explorative growth habit and high surface area to mass ratio ensures that fungal-metal interactions

FUNGAL PRODUCTION OF CITRIC AND OXALIC ACID

49

are an integral component of major environmental cycling processes. Metals, both essential and inessential, and their derivatives can interact with fungi in various ways depending on the metal species, organism and environment, while fungal metabolic activities can also influence speciation and mobility (Gadd, 1993;Wainwright and Gadd, 1997). Certain mechanisms may mobilize metals into forms available for cellular uptake and leaching from the system, e.g. complexation with organic acids, other metabolites and siderophores (Francis, 1994), while immobilization may result from sorption on to cell components and exopolymers, transport and intracellular and extracellular sequestration or precipitation (Morley and Gadd, 1995; Gadd, 1996; Sayer and Gadd, 1997; White et al., 1997). Such apparently opposing processes of solubilization and immobilization are important for biogeochemical cycles for indigenous or introduced metals, and fundamental determinants of fungal growth, morphogenesis and physiology (Morley et al., 1996; Ramsay et al., 1999). Furthermore, several processes are relevant to environmental bioremediation (White et al., 1997; Sayer et al., 1998). Organic acids have important roles in fungal nutrition and physiology, apart from their possible utilization as carbon and energy sources, which include contributions to intracellular osmotic potential, charge balance and pH homeostasis (see Jennings, 1995). In addition, the production of metal-complexing organic acids assists both essential metal and anionic nutrition of fungi and plants via the solubilization of phosphate and sulphate, from insoluble metalcontaining substances, including salts and minerals. Production of such acids is also important in biodeterioration and weathering. Although much information on fungal organic acid production has been obtained as a result of the commercial importance of citric acid (Mattey, 1992; Kubicek, 1998),the wider significanceof citric and oxalic acids in affecting metal speciation and mobility should not be overlooked. As well as the relevance to metal nutrition and toxicity, metal solubilization by the formation of organic acid complexes is important in environmental metal mobility and transfer between terrestrial and aquatic habitats, in plant nutrition and productivity, metal recovery from wastes and low-grade ores (‘heterotrophic leaching’) (Burgstaller and Schinner, 1993), and bioremediation (Francis et al., 1992; Dodge and Francis, 1994; Francis and Dodge, 1994). Metal immobilization by insoluble metal oxalate formation is again a process of marked environmental significance regarding fungal survival, biodeterioration, pathogenesis, soil weathering, mineral formation and metal detoxification. Oxalate-containing or oxalate-derived minerals, including humboldtine (ferrous oxalate dihydrate), whewellite (calcium oxalate monohydrate) and weddelite (calcium oxalate dihydrate), occur in the geosphere, with significant microbiological involvement in their production. Many plants contain calcium oxalate, which can render them poisonous to herbivores and humans, and this can also constitute a significant fraction of the dry weight of lichen thalli (Purvis and Halls, 1996). In a fungal

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GEOFFREY M. GADD

context, oxalic acidkalcium oxalate has long been known to be of ubiquitous occurrence and associated with fungi from different groups (Hamlet and Plowright, 1877; De Bary, 1887). The scope of this review is the physiology and chemistry of citric and oxalic acid production in fungi, the intimate association of these acids and processes with metal physiology and mobility, and their importance and involvement in key fungal-mediated processes, including lignocellulose degradation and plant pathogenesis, and metal biogeochemistry.

2. METAL CHEMISTRY OF OXALIC AND CITRIC ACIDS

Organic acids can form coordination compounds or complexes with metals. These may be non-ionic, anionic or cationic depending on the sum of the charges of the central metal atom or ion and surrounding ions and molecules (Basolo and Johnson, 1964; Munier-Lamy and Berthelin, 1983). If the organic acid, e.g. citric or oxalic acid, contains two or more electron donor groups so that one or more rings are formed, then the organic acid can be termed a chelating agent and the resulting complexes termed metal chelates (Martell and Calvin, 1952). Such complexation is dependent on the relative concentrations of the anions and metals in solution, the pH and the stability constants of the various complexes (DenCvre et al., 1996). Oxalic acid is a relatively strong acid and crystallizes from water as monoclinic prisms of oxalic acid dihydrate. In the biosphere, oxalic acid occurs in rocks, microorganisms, including fungi, plants and animals as the free acid but more commonly as the K or Ca salt (Hodgkinson, 1977). Indeed, in a microbiological context, raphides of calcium oxalate were, with microbes, among the first objects to be observed under the optical microscope (Leeuwenhoek, 1675). Like monocarboxylic acids, oxalic acid can be converted into salts and, as with other dicarboxylic acids, it is possible to obtain compounds where only one of the carboxyl groups has been derivatized, or where both carboxyl groups have been converted into the same or different derivatives (Hodgkinson, 1977). The oxalate ion, C 0 2-, is a bidentate 2. 4 ligand, forming a five-membered chelate ring when it binds to a metal (Fig. 1). A metal (M) which normally forms octahedral six-coordinate complexes (e.g. A13+,Cr3+,Fe3+)can bind three oxalates to form an anionic complex (Fig. 1):

This can be crystallized as a potassium salt K3[M(C204),].3H20.Metals which form square planar four-coordinate complexes (e.g. Cu2+,Zn2+) can complex two oxalates (Fig. l),

51

FUNGAL PRODUCTION OF CITRIC AND OXALIC ACID

1

L

B

A

C

3-

D

E

Figure I Metal complex formation by oxalic acid. (A) oxalic acid; (B) oxalate; (C) bidentate metal (M) complex formation; (D) complex anion formation with metals which form square planar four-coordinatecomplexes, e.g. Cu2+,(Cu oxal)2-; (E) complex anion formation with metals which form octahedral six-coordinate complexes, e.g. A13+, Fe3+, C?+, (A1 ~ x a l ) ~(Fe - , oxal)j-, (Cr ~ x a l ) ~ - .

M2++ 2C20,2- + M(C20,)22-

(2)

with the crystallized potassium salt being K2[M(C20,),].2H20. Some metals, e.g. Al, Cr, Zn and Fe, form acid complexes, e.g. H,[Cr(C,O,)]. Most simple oxalates are sparingly soluble in water except those of the alkali metals (Li, Na, K), ammonium and Fe(III), the last probably because of the formation of the Fe[Fe(C,O,),] complex. Divalent metal oxalates are of similar solubilities with the most soluble being magnesium oxalate and the least soluble being calcium and lead oxalates (Table l). Precipitation occurs according to the following equation: M,qn+

+ n/2C20,2- + M(C2O,),,.xH20

(3)

Because of the coordinating properties of the bidentate oxalate ion, most metals of particular interest to biologists form both simple and complex oxalates; these metals include Mg, Ca, Sr, Ba, Cr, Mn, Fe, Co, Ni, Cu, Zn, Ga, Ag, Cd, Sn, Hg, Pb, and a range of actinides and lanthanides. Many simple oxalates are crystalline or amorphous solids with solubility constants ranging from lo4 to The values for divalent metal oxalates generally lie between

52

GEOFFREY M. GADD

Table I

Solubility products of some metal oxalates (Adapted from Chang, 1993)

Metal oxalate

Temperature (“C)

Solubility product

Barium (dihydrate) Cadmium (trihydrate)

18 18 25 18 25

I .20 x 1.53 x 1.42 x 1.78x 2.57 X 2.87 x 2.10 x 2.74 x 8.51 x 8.57 x 4.83 X 1.70 x I .75 x 5.40 x 5.61 x 1.35x 1.37 x

Calcium (monohydrate)

25 25

Copper (11) Ferrous Lead

18

Magnesium (dihydrate) Manganese (11) (dihydrate) Mercury (I) Silver (I) Strontium (monohydrate) Zinc (dihydrate)

25 25 25 25 25 25 18 18

25

10-7 10-9

lW9 10-7

lo-” 1O-Io 10-5 10“ 10-7

I 0-13 lo-’, 10-9 10-9

CH2COOH

I

HO-C-COOH

I

CH2COOH A

B

Figure 2 Metal complex formation by citric acid. (A) citric acid; (B) bidentate complex, e.g. (Ca cit)-, (Ni cit)-, (Fe(OH), cit)2-; (C) tridentate complex, e.g. (Cd tit)-, (Fe tit)-, (FeOH tit)*-, (Pb cit)-, (Cu tit)% (D) binuclear complex - (UO,), tit:-. Adapted from Francis et al. (1992).

53

FUNGAL PRODUCTION OF CITRIC AND OXALlC ACID

(Table 1). It is generally believed that only simple oxalates can and occur in biological systems because the excess oxalate ion required for complex stability would be toxic. Citric acid can form mononuclear, binuclear or polynuclear complexes depending on the metal (Fig. 2). Ca2+,Fe3+and Ni2+form bidentate, mononuclear complexes with two carboxylic acid groups while Cu2+,Fe2+,Cd2+and Pb2+form tridentate mononuclear complexes with two carboxylic acid groups and the hydroxyl group. Uranium forms a binuclear complex involving four carboxylic acid groups and two hydroxyl groups from two citric acid molecules (Francis et al., 1992) (Fig. 2). Such complex formation affects metal mobility, toxicity and biodegradation: the recalcitrance of metal citrate complexes may play a role in the migration of hazardous metals from metal and nuclear disposal sites (Francis et al., 1992).

3. FUNGAL BIOSYNTHESIS OF OXALlC ACID AND CALCIUM OXALATE FORMATION 3.1. Oxalic Acid Biosynthesis

Oxalic acid may be considered as a toxic by-product of citric acid production, and its synthesis appears to depend on whether glucose or citric acid is used as the carbon source (Wolschek and Kubicek, 1999). Biosynthesis on glucose occurs by hydrolysis of oxaloacetate to oxalate and acetate catalysed by cytosolic oxaloacetase [oxaloacetate (acety1)hydrolasel (Fig. 3); this can be considered to be a valve whereby carbon overflow is channelled into an energetically neutral pathway and so competes with citrate production (Kubicek, 1988;Wolschek and Kubicek, 1999).Where citric acid is used, oxalic acid production occurs by means of the glyoxylate cycle (Fig. 4)(Hodgkinson, 1977; Dutton and Evans, 1996; Wolschek and Kubicek, 1999).

2 ADP

Glucoseu

2 ATP

2 ADP

2 b m v a t e y 2 woacetate

co2

<

OXALATE Acetate

-

?

Figure 3 Oxalate biosynthesis by Aspergillus niger. Further steps in acetate metabolism are uncertain (Wolschek and Kubicek, 1999).

54

GEOFFREY M. GADD

Succinate C I ~ T -------E Isocitrate

Glyoxylate

-

OXALATE

Figure 4 Oxalate biosynthesis by glyoxylate oxidation (see Dutton and Evans, 1993; Shimada et al., 1997).

Cytoplasmic oxaloacetase is inducible in A. niger and dependent on neutralization of acidic growth medium, the presence of carbonate and Mn2+as a cofactor (Havir and Anagnostakis, 1985; Dutton and Evans, 1996). The enzyme has also been identified in several species of brown- and white-rot fungi, including Tyromyces palustris, Coriolus versicolor and Phanerochaete chrysosporium (Akamatsu et al., 1991, 1992, 1993a,b,c).In addition to mitochondrial production of oxaloacetate in the tricarboxylic acid (TCA) cycle, Aspergillus niger also possesses a cytosolic pyruvate carboxylase which produces oxaloacetate, a reaction important in citric acid production by this species (Kubicek, 1998; Wolschek and Kubicek, 1999). In Sclerotium rolfsii, glyoxylate is oxidized to oxalate by glyoxylate dehydrogenase (glyoxylate NADP- oxidoreductase)(Maxwell and Bateman, 1968a),the glyoxylate arising from the action of isocitrate lyase on isocitrate, which is cleaved to succinate and glyoxylate (see Gadd, 1988). Production of glyoxylate dehydrogenase is induced by pH values >3.5, with optimal activity at pH 9 (Balmforth and Thomson, 1984). Glyoxylate oxidation to oxalate by glyoxylate dehydrogenase has also been observed in other fungi including Fomes annosus and Tyromycespalustris (Hutterman et al., 1980;Akamatsu, 1993).In S. rolfsii, glyoxylate dehydrogenase and isocitrate lyase appeared to be located in microbodies (Maxwell et al., 1972; Armentrout et al., 1978), which could be analogous to plant glyoxysomes (Dutton and Evans, 1996). The ectomycorrhiza Puxillus involutus was able to use bicarbonate for oxalate biosynthesis in a nitrate-nitrogen medium, the oxalate being synthesized either directly from oxaloacetate, or via citrate, isocitrate and glyoxylate (Lapeyrie, 1988).As well as these mechanisms of oxalate production, ascorbic acid analogues may also act as precursors of oxalic acid synthesis in certain fungi, e.g. Sclerotinia sclerotiorum, although further work is needed to confirm the steps involved (Franceschi and Loewus 1995; Loewus et al., 1995). Oxalic acidoxalate production is widespread in fungi with factors affecting biosynthesis including carbon and nitrogen source, and medium or environment pH (Punja and Jenkins, 1984a; Lapeyrie etal., 1987; Bennett and Hindal, 1989; Pierson and Rhodes, 1992; Akamatsu et al., 1993c, 1994; Dutton et al., 1993; Micales, 1994, 1995a; Wang and McNeil, 1995; Dutton and Evans, 1996; Shimada et al., 1997; Gharieb and Gadd, 1999). For example, nitrate as a nitrogen source and maintenance of the culture pH above 3.0 enhanced

55

FUNGAL PRODUCTION OF CITRIC AND OXALIC ACID

oxalate production by S. rolfsii (Maxwell and Bateman, 1968a,b). Effects of C, N and the pH have also been noted on a wide variety of wood-rotting basidiomycetes, including both white-rot and brown-rot species, especially when carbon sources are depleted in medium (Dutton et al., 1993; Gharieb and Gadd, 1999). While it is dificult to generalize, it appears that brown-rot fungi tend to produce most oxalate in low-nitrogen culture media, whereas white rots prefer high-nitrogen media (Akamatsu et al., 1994; Henriksson et al., 1995; Shimada et al., 1997). However, differences in yield may reflect differences in production through the growth phase. For example, the white-rot basidiomycetes, Coriolus versicolor, Heterobasidium annosum, Pleurotus jlorida and Phanerochaete chrysosporium, produced millimolar concentrations of oxalate in the stationary phase, but little was produced during earlier active growth and no lowering of medium pH was observed. In contrast, some brown-rot fungi, Amyloporia xantha, Coniophora marmorata, Coniophora puteana and Poria vaporaria produced oxalate throughout growth and concentrations up to 20 mM reduced the medium pH (Dutton et al., 1993). Differences in oxalate yield may also reflect differential expression of the oxalate-degrading enzyme, oxalate decarboxylase, in the different species (Micales, 1995b, 1997). Under nutrient-rich conditions, oxalate was not produced by l? chrysosporium (Kuan and Tien, 1993), while Poria placenta increased oxalate production under nitrogen limitation (Micales, 1994) or during growth on amorphous cellulose (Ritschkoff et al., 1995). Carbon and nitrogen sources influence oxalate production by plant pathogenic and mycorrhizal fungi (see Dutton and Evans, 1996), with nitrate being the preferred nitrogen source for Paxillus involutus (Lapeyrie et al., 1987). Oxalate production by P. involutus was enhanced by the presence of carbonatehicarbonate (Lapeyrie et al., 1987; Lapeyrie, 1988).

3.2.Calcium Oxalate In the environment, the main forms of calcium oxalate are the monohydrate (whewellite) and the dihydrate (weddelite), which extensively occur in fossil rocks, microorganisms, plants and human urinary calculi. The monohydrate is monoclinic while the dihydrate is tetragonal in crystallization, although both can crystallize in a variety of forms. The solubility and instability of hydrated calcium oxalate increases with increasing water of crystallization, and this is reflected in the pattern of crystallization of calcium oxalate from aqueous solution. The initial precipitation phase is the trihydrate which loses water of crystallization to form either the monohydrate or the dihydrate, depending on conditions: CaC20,.3H20,

+ CaC,0,.2H20, + H,O

(4)

56

GEOFFREY M. GADD

CaC20,.2H,O,

+ CaC,O,H,O, + H,O

(5)

CaC20,.3H,0,

+ CaC,O,.H,O, + 2H,O

(6)

or

The solubility of calcium oxalate increases with decreasing pH because of the formation of dioxalate ions and oxalic acid: Ca2++ C,O,2-

CaC,O, C,OZ-

t)

(7)

+ H+ t)H.C,O,

H.C,04-

+ H+t)H,C,O,

(9)

Solubility increases markedly below pH 5 and may also be increased by the presence of substances which will form soluble complexes with either calcium or oxalate ions, such as citric acid and magnesium. Conversely, solubility may be decreased by the presence of a common ion, e.g. by the addition of calcium chloride or ammonium oxalate. The ubiquitous association of oxalic acidcalcium oxalate with many and diverse kinds of fungi from all major classes has long been evident in natural, laboratory and industrial environments (De Bary, 1887; Foster, 1949; Arnott, 1982a,b, 1995; Malajczuk and Cromack, 1982; Dutton et al., 1993; Dutton and Evans, 1996).In fact, the absence of calcium oxalate may be a more significant systematic character in some species (Krisai and Mrazek, 1986).Calcium oxalate crystals can be associated with the hyphae of oxalic acid-producing strains, as well as fruiting bodies, with the main forms being the monohydrate (whewellite) and the dihydrate (weddelite), the latter being the most ubiquitous (Fig. 5 ) . Sometimesthe two hydration states can be distinguished by their morphology as the monohydrate belongs to the monoclinic system, while the dihydrate belongs to the hexagonal system (Arnott, 1995). It is thought that monohydrate crystals may arise from previously produced dihydrate in a recrystallization process (Verrecchia et ~ l . 1993), , the monohydrate being the more stable form. However, Horner et al. (1995) found that the youngest portions of fungal rhizomorphs (from an oak wood) possessed monohydrate crystals, whereas older parts of the hyphae were associated with the dihydrate, while only monohydrate was found in mantle hyphae of larch ectomycorrhiza (Jones et al., 1992).This could reflect changes that occur over development and maturation of the calcium oxalate, although contrasts with the proposed sequence of events for biomineralizationin Quaternary calcretes (Verrecchiaet al., 1993).The relative contribution of fungal metabolism or diagenesis in effecting changes in crystal morphology and hydration state is therefore unclear at present.

FUNGAL PRODUCTION OF CITRIC AND OXALIC ACID

57

Figure 5 Scanning electron micrographs of calcium oxalate crystals produced in solid malt extract agar medium supplemented with 0.5% (w/v) gypsum by (a) Serpulu himantioides, (b) Aspergillus niger and (c,d) in leaf litter microcosms. In (c), note the small needle-like crystals characteristic of calcium oxalate monohydrate, as well as prismatic crystals of calcium oxalate dihydrate, and, in (d), the prism-like crystal of calcium oxalate dihydrate within the hyphal network. Scale bar markers: 10 pm (Gharieb, Sayer, Tait and Gadd, unpublished; see Gharieb et al., 1998).

In the environment, calcium oxalate formation by free-living and symbiotic mycorrhizal fungi is frequently observed both in soil, decomposing wood and in leaf litter (Graustein et al., 1977; Cromack e f al., 1979; Lapeyrie et al., 1984; Snetselaar and Whitney, 1990; Cairney and Clipson, 1991; Homer et al., 1995; Shinners and Tewari, 1997; Tewari et al., 1997), and also associated with certain plant pathogenic fungi (Punja and Jenkins, 1984b; Punja et al., 1985; Yang et al., 1993; Arnott, 1995). A variety of calcium oxalate crystal formations have been described with many fitting into the four groups: tetragonal bipyramids, prisms, tablets and needles (Keller, 1985; Amott, 1995; Whitney

58

GEOFFREY M. GADD

and Amott, 1986a,b, 1988; Shinners and Tewari, 1997). However, morphology is extremely variable and crystals can be separate or arranged in arrays, and may also arise from twinning (Arnott, 1995). The most common types in plants are large single needles (styloids),bundles of needles (raphides), stellate conglomerates (druses), rhombohedra1 (prismatic) and packets of angular microcrystals (crystal sand); analogous morphologies also arise in fungi (Franceschi and Loewus, 1995). Some crystal shapes appear to be transient, although in some cases their shape and location appears to be species specific (Horner et al., 1995). While most reports demonstrate calcium oxalate forrnation external to the biomass, an obvious consequence of oxalic acid excretion (Sayer and Gadd, 1997; Gharieb et al., 1998), other reports have described intracellular formation of calcium oxalate, with some crystals apparently covered by a wall or membrane (De Bary, 1887; Arnott, 1982a,b, 1995; Powell and Arnott, 1985; Whitney and Arnott, 1987) or deduced to arise in specific wall chambers (Amott, 1995), or in vacuolar vesicles (Lapeyrie et al., 1990). For fungi growing in the soil, the regularity of calcium oxalate deposits over the surface of hyphae has suggested a more complex mode of formation than precipitation of oxalate with exogenous calcium, hence the proposal that deposition of calcium oxalate arises within the hyphae and is not a simple surface precipitation (Arnott, 1982a,b, 1995;Arnott and Webb, 1983;Arnott and Fryar, 1984). However, it seems doubtful whether truly intracellular calcium oxalate deposition occurs in fungi (Franceschi and Loewus, 1995). In several fungi, semi-mature crystals are encased in an organic sheath covering the hyphae. Such sheaths are carbohydrate/proteinbased (Nicole et al., 1993) but are subject to distortions and shrinkage when treated with conventional electron microscopy reagents (Daniel, 1994; Connolly et al., 1995). It is likely that shrinkage during dehydration could make the extracellular matrix of fungi appear like the cell wall and lead to possible misinterpretation of electron micrographs (Connolly and Jellison, 1995; Connolly et al., 1995). In the white rot Resinium bicolor, the hydrated hyphal sheath is considerably thicker than the dehydrated sheath and contains numerous calcium oxalate crystals. Calcium oxalate druses nucleated and grew only in the more mature hyphal sections, suggesting that only the hyphal sheath possessed the extensibility necessary to accommodate them (Connolly and Jellison, 1995). The pattern of crystal formation along hyphae may reflect the nature and location of oxalate andor Ca2+secretion, although exogenous calcium is generally abundant (Connolly and Jellison, 1995). It is pertinent that, in plants, oxalates may accumulate in vacuoles, but there is no significant information relating to the role of the fungal vacuole in oxalate storage or deposition (Franceschi and Loewus, 1995). In basidiomycete rhizomorphs, some of the interwoven hyphae are encrusted with crystals and ‘vessel hyphae’ within may also possess crystalline deposits (Cairney et al., 1989; Cairney, 1990; Cairney and Clipson, 1991). Because of this, it is thought that the ability of litter degraders to

FUNGAL PRODUCTION OF CITRIC AND OXALIC ACID

59

translocate and precipitate calcium as calcium oxalate could contribute to nutritional heterogeneity in soil, with concomitant influences on P, A1 and K (see later) (Connolly and Jellison, 1995, 1997).While the abundance of oxalate and importance in P and Ca cycling is clear for forest ecosystems, in arid ecosystems, oxalate production by mycorrhizal fungi appears limited to matforming fungi, such as Hysterangium separabile, and arbuscular hyphae do not have associated crystal structures (Allen et al., 1996). In addition to calcium oxalate, fungi are also able to precipitate other metal oxalates (Figs 6 and 7). The production of oxalic acid by fungi provides a means of immobilizing soluble metal ions, or complexes, as insoluble oxalates, decreasing bioavailability and conferring tolerance (Sayer and Gadd, 1997).As mentioned earlier, most metal oxalates are insoluble, some exceptions being Na, K, Li and Fe (Strasser et al., 1994). Copper oxalate (moolooite) has been observed around hyphae growing on wood treated with copper as a preservative (Murphy and Levy, 1983; Sutter et al., 1983, 1984).The copper appeared on the surface of the wood and around hyphae as copper oxalate, which was reported to be non-toxic because of its insolubility. A. niger can form metal oxalate crystals after 1-2 days when grown on medium amended with a wide range of metal compounds, including insoluble metal phosphates (Fig. 6)

Figure 6 Solubilization of insoluble Co,(PO,), by organic acid production and subsequent reprecipitationas insoluble cobalt oxalate. Aspergillus niger was grown at 25 "C for 6 days on malt extract agar containing 0.5% (wlv) Co,(PO,),. The photograph shows the clear zone of solubilization around the colony and the precipitation of cobalt oxalate crystals within this zone (see Gadd, 1996; Sayer and Gadd, 1997).

60

GEOFFREY M. GADD

Figure 7 Scanning electron micrographs of purified insoluble metal oxalate crystals produced by Aspergillus niger. (a) Cobalt oxalate, (b) copper oxalate, (c) zinc oxalate, (d) manganese oxalate, (e) strontium oxalate dihydrate and (f) strontium oxalate dihydrate with needle-like crystals of strontium oxalate monohydrate; (a-d) were obtained after growth on solid malt extract agar (MJZA) supplemented with 0.5% (w/v) of the corresponding metal phosphates; (e) and (9 were obtained after growth on MEA containing 15 m~ %(NO,),. Scale bar markers: (a,d) 100 pm; (b,c,e,f) 10 pm (Sayer, Whatley and Gadd, unpublished; see Sayer and Gadd. 1997).

61

FUNGAL PRODUCTION OF CITRIC AND OXALIC ACID

(Sayer and Gadd, 1997) and powdered metal-bearing minerals (Fig. 5) (Sayer et al., 1997; Gharieb et al., 1998). A. niger has been shown to produce metal oxalates with many different metals, e.g. Ca, Cd, Co, Cu, Mn, Sr and Zn (Fig. 7) (Sayer and Gadd, 1997). Morphological examination of fungal-produced metal oxalate crystals and comparison, where possible, with chemically synthesized oxalates, has often shown some clear differences in crystallographic form (Vivier et al., 1994; Sayer and Gadd, 1997). Thus, the formation of oxalates containing potentially toxic metals may provide a mechanism whereby oxalate-producing fungi can tolerate environments containing high concentrations of toxic metals. Copper oxalate has also been observed in lichens growing on copper-rich rocks where it is also thought that the precipitation of copper oxalate could be a detoxification mechanism (see later) (Purvis, 1984, Purvis and Halls, 1996).

4. ROLE OF METALS AND OXALATE IN LIGNOCELLULOSE DEGRADATION AND PLANT PATHOGENESIS 4.1. Lignocellulose Degradation

Brown-rot and white-rot fungi are the main wood-rotting basidiomycetes, with brown rots, e.g. Coniophoraputeana and Serpula lacrymans, unable to metabolize lignin (leaving an amorphous brown residue) and white rots, e.g. Phanerochaete chrysosporium and Coriolus versicolor, able to degrade all plant cell wall components (Dutton and Evans, 1996). Oxalate plays an important role in affecting the activity of key enzymes and processes in both these groups of fungi (Goodwin et al., 1994; Khindaria et al., 1994; Shimada et al., 1994; Tanaka et al., 1994). In brown rots, oxalic acid production lowers the external pH, which aids cellulose degradation but also gives rise to oxygen radicals. The pH of wood can fall to around 2.5 after the growth of brown rots (Green et al., 1991; Espejo and Agosin, 1991; Dutton et al., 1993; Micales, 1994); such low pH values arise because of the strength of oxalic acid as an organic acid (pK, = 1.1) (Hyde and Wood, 1997). The oxalic acid is believed to act as an electron donor in the reduction of Fe(II1) to Fe(II), with the resultant Fe(I1) being oxidized in the Fenton reaction, yielding hydroxyl radicals for the oxidative degradation of cellulose and hemicellulose (Hirano et al., 1995; Dutton and Evans, 1996; Hyde and Wood, 1997): Fe2++ H,02

+ Fe3++ HO'+ HO-

(10)

However, direct reduction of Fe(II1) by oxalate has been dismissed because of the slow speed of reaction and requirement for light (Horne, 1960; Wood,

62

GEOFFREY M. GADD

2.5 3.5 4.5 pH 3.0 4.0

Figure 8 Model for hydroxyl radical production by brown-rot fungi without damage to the hyphae (adapted from Hyde and Wood, 1997). Secretion of cellobiose dehydrogenase (CDH) provides a mechanism for Fe(II1) reduction in the presence of oxalate: diffusion of Fe(I1) away from the hyphae promotes autooxidation. Generation of Fe(II)/H,O, away from the hyphae means resultant hydroxyl radicals will not be deleterious to the fungus.

1994; Zuo and Hoigne, 1994; Hyde and Wood, 1997). Another hypothesis has been proposed where Fe(II1) is reduced to Fe(I1) by extracellular cellobiose dehydrogenase, meaning that cellobiose or cellulose act as an electron source for both reduction of Fe(II1) and 0, to generate H,O, for the Fenton reaction (Fig. 8) (Hyde and Wood, 1997). It should be noted that oxalate may promote the Fenton reaction in a bifunctional manner, since increasing concentrationsof oxalate (< 5 mM or an oxalate : Fe ratio of 50) can inhibit oxidative breakdown of cellulose catalysed by Fenton oxidation, and also H,O, and Fe(1II) (Shimada et al., 1997).Thus, while both Fe(II1) and H,O, are important for Fenton-type oxidation, if oxalate exceeds 5 mM in wood, then non-enzymatic cellulose hydrolysis may be more important in brown-rot wood decay (Akamatsu et al., 1991; Shimada et al., 1997). It is possible that lignin scavenges the hydroxyl radicals first, and then phenoxy and other indirectly formed lignin-derived radicals may attack cellulose and hemicellulose because there is no selectivity for hydroxyl radicals to oxidize cellulose (Magara et al., 1994; Shimada et al., 1997). In brown-rot fungi, polygalacturonase and oxalic acid formation are also induced by pectin. The enzyme and oxalic acid may act synergistically to hydrolyse pectin in pit membranes and middle lamellae (Green et al., 1995). Here, a possible involvement of calcium oxalate should be alluded to since calcium is mainly located as calcium pectate in middle lamellae. Thus, in pectin degradation, the calcium is removed by calcium oxalate formation, which may perturb cell wall structure, perhaps favouring entry of lignocellulosic enzymes

63

FUNGAL PRODUCTION OF CITRIC AND OXALIC ACID

(Dutton ef al., 1993).However, there are relatively few reports on pectinase production by wood-rotting fungi (Dutton and Evans, 1996). In white-rot fungi, the low production of oxalic acid observed has been explained as a result of the presence of oxalate decarboxylase, which degrades oxalate to formate and CO, (Micales, 1995b; Green and Highley, 1997). However, decomposition of oxalate is also a result of interactions with whiterot lignin and manganese peroxidases. In the absence of oxalate, veratryl alcohol and Mn(I1) are oxidized by lignin peroxidase (Lip) and manganese peroxidase (MnP), respectively, producing veratrylaldehyde (VA) and Mn(II1). Such a system is metal regulated because high [Mn] induces the MnP system, while repressing the Lip system. At low [Mn], MnP is repressed and Lip is induced (Perez and Jeffries, 1993). However, if oxalate is present, VA cation radicals and Mn(II1) are reduced back to the substrate level by oxalate which, at the same time, yields CO, and formate radicals; these are further oxidized to superoxide anion radicals under aerobic conditions (Fig. 9) (Shimada et al., CH20H

LiP or MnP

[Mn3+] or

c02 O * - x +

02

co2:

700-

coo-

[VAtl

6

or

[Mn3+]

OCH3 OCH3

Figure 9 Reaction mechanisms for oxidative decomposition of oxalate by lignindegrading systems with lignin peroxidase (Lip) and manganese-dependent peroxidase (MnP) (adapted from Shimada ef a[., 1997). In the absence of oxalate, veratryl alcohol (VA) and Mn(I1) are oxidized by LIP or MnP, respectively, to veratraldehyde via VA cation radicals and Mn(II1). In the presence of oxalate, VA cation radicals and Mn(II1) are reduced back to the substrate level with production of CO, and formate radical, which further results in superoxide anion radicals. Thus, lignin degradation can be inhibited by the presence of oxalate.

64

GEOFFREY M. GADD

1997).The oxalate is important in Lip repression at high [Mn] because, as long as Mn(I1) and Mn(II1) are kept in solution by chelation, repression continues. However, Mn(IV)02 is eventually precipitated, which relieves repression and allows lignin degradation to proceed (Perez and Jeffries, 1993). Thus, in the presence of oxalate, lignin degradation is inhibited and this has been shown to be non-competitive in nature, both for VA and Mn(I1) oxidation (Akamatsu et al., 1990; Popp et al., 1990; Ma et al., 1992; Shah et al., 1992; Shimada et al., 1997). Despite this, the formation of superoxide anion radicals will lead to H202production (see above). Oxidation of phenolic moieties of lignin is not inhibited by oxalate and if these accumulate, lignin degradation may be inhibited (Akamatsu et al., 1990). The presence of oxalate decarboxylase and phenol oxidase (laccase) in white-rot fungi may provide a mechanism for removal of oxalate and phenolics, so that the Lip system may function adequately (Shimada et al., 1997).Apart from the roles described, oxalate also acts as a Mn chelator and stabilizes Mn(II1) in the MnP system (Perez and Jeffries, 1993; Kishi et al., 1994). This interaction facilitates Mn(II1) dissolution from the Mn(III)-enzyme complex to be followed by Mn(I1I) catalysed oxidation of phenolic components (Popp et al., 1990; Dutton and Evans, 1996; Shimada et al., 1997). 4.2. Plant Pathogenesis

Oxalic acid has been implicated in the phytopathogenesis of several fungi with its effects being due to several mechanisms which may act singly or in concert (Rowe, 1993). The decrease in pH of infected tissues on oxalic acid production may enhance the activity of extracellular lytic enzymes, many of which have pH optima below 5 , as well as being of general detriment to plant tissues (Dutton and Evans, 1996). As mentioned above, some fungi secrete oxalic acid with cell wall degrading enzymes, and this may assist the solubilization of pectin in membranes in the middle lamellae (Green et al., 1995). The occurrence of calcium oxalate in necrotic plant tissue infected by numerous fungal plant pathogens (Punja and Jenkins, 1984a) provides further evidence for the important role of oxalic acid in calcium removal, which in turn allows polygalacturonase to hydrolyse pectates more easily (Green et al., 1995; Dutton and Evans, 1996). Interestingly, mutants of Sclerotinia sclerotiorum that are unable to synthesize oxalic acid were, in contrast to wild-type strains, non-pathogenic in bioassays (Godoy et al., 1990),while plant cultivars resistant to S. sclerotiorum were more oxalic acid-tolerant than sensitive cultivars (Noyes and Hancock, 198l). Several other similar examples occur in the literature (Kritzman et al., 1977; Havir and Anagnostakis, 1983; Marciano et al., 1983; Wang and Tewari, 1990; Callahan and Rowe, 1991). Numerous other debilitating or toxic effects of oxalic acid have also been

65

FUNGAL PRODUCTION OF CITRIC AND OXALlC ACID

documented. These include calcium removal from plasma membranes, copper removal causing inhibition of enzymes, such as polyphenol oxidase, and magnesium oxalate formation arising from Mg removal from ribosomal subunits, enzymes, ATP and chlorophyll (Rao and Tewari, 1989; Ferrar and Walker, 1993).

5. CATABOLISM OF OXALlC ACID

Oxalic acid is decarboxylated by oxalate decarboxylase to CO, and formate: (COOH),

+ CO, + HCOOH

(1 1)

The formate may subsequently be dehydrogenated by formate dehydrogenase, yielding NADH and CO, (Shimada et al., 1997). Oxygen-requiring oxalate decarboxylase is found in a variety of fungi. In some wood-rotting basidiomycetes, oxalate decarboxylase is induced by the presence of oxalic acid (Magro et al., 1988; Mehta and Datta, 1991; Dutton et al., 1994; Micales, 1997), although in Aspergillus niger, the enzyme was non-inducible and only synthesized when the culture pH fell below 2.5 (Emiliani and Bekes, 1964). The optimum pH for oxalate decarboxylase is in the range pH 1.75-2.20 (Micales, 1995b). In Coriolus versicolor, oxalate decarboxylase was found intracellularly and extracellularly: secretion occurred at the end of exponential growth, which accounts for the lack of detectable oxalate in the medium at this growth stage. However, oxalate levels rose after this because the pH of the medium became too high for oxalate decarboxylase activity (Dutton et al., 1994). Addition of calcium carbonate to medium, which raises the pH, also inhibits oxalate decarboxylase activity (Takao, 1965). In Postia placenta, oxalate decarboxylase was induced by growth inhibitory concentrations of oxalic acid in low- and highdecay isolates, and was associated with the hyphal surface and hyphal sheath (Micales, 1997). The oxalate decarboxylase-mediated prevention of oxalate overproduction may maintain a non-toxic, low pH microenvironment which facilitates decay (Micales, 1997). Such a process may be enhanced by the formate produced during oxalic acid breakdown combining with the remaining oxalic acid to form a low pH buffer (Agosin et al., 1989).

0. FUNGAL BIOSYNTHESIS OF CITRIC ACID

Citric acid is an intermediate in the TCA cycle and therefore is ubiquitous in living organisms. It is extensively used in the food and beverage industry and

GEOFFREY M.GADD

66 Acetyl-CoA ,

Figure 10 Citrate formation from gluocose via anaplerotic CO, fixation (see Wolschek and Kubicek, 1999).

is produced predominantly by A. niger. World annual production is estimated around 40 000 tons (Roehr et al., 1992). It forms complexes with metals (Fe, Cu) and is therefore used for stabilization of oils and fats, and to prevent metal-ion catalysed oxidation of ascorbic acid (Kubicek, 1998).A. niger forms citric acid by the conversion of pyruvate, which arises from glycolytic catabolism of glucose to the precursor of citrate, oxaloacetate (Roehr et al., 1996; Kubicek, 1998).A key step in this process is the use of 1 mol pyruvate (of the 2 mol arising from glycolytic conversion of 1 mol glucose) and the CO, released during acetyl CoA formation to form oxaloacetate (Fig. 10). If oxaloacetate was only formed by one turn of the TCA cycle, 2 mol CO, would be lost and only two-thirds of the glucose carbon would give rise to citric acid. Such anaplerotic CO, fixation is catalysed by pyruvate carboxylase, itself induced by high carbohydrate concentrations, and this explains high commercial yields of citric acid (Kubicek, 1998). In A. niger, pyruvate carboxylase is cytosolic in location (Bercovitz et al., 1990) and pyruvate is directly converted to oxaloacetate and then to malate by malate dehydrogenase (Ma et al., 1981). It is thought that cytosolic malate is the co-substrate of the mitochondrial tricarboxylic acid carrier and enhanced intracellular malate may therefore stimulate citrate export from mitochondria (Kubicek, 1988, 1998). A. niger possesses a further glucose catabolism pathway catalysed by glucose oxidase, which converts glucose to gluconic acid, and this enzyme is induced by high glucose concentrations and aeration (Dronawat et al., 1995; Wolschek and Kubicek, 1999). Therefore, gluconic acid may also be present at least at the initial phase of a citric acid fermentation, although glucose oxidase (extracellular) is eventually inactivated once the pH falls below 3.5 (Mischak er al., 1985).A. niger may also produce oxalic acid as a by-product of citric acid fermentation, depending on whether glucose or citric acid is used as the carbon source (see elsewhere) (Kubicek, 1988; Kubicek et al., 1988; Wolschek and Kubicek, 1999). The concentration and kind of carbon source are important parameters for citric acid production, and only easily assimilated sugars allow both high yields and rates of citric acid production (Kubicek and Roehr, 1986). Other important factors include dissolved oxygen tension and aeration (Kubicek et

FUNGAL PRODUCTION OF CITRIC AND OXALIC ACID

67

al., 1998), pH (Kubicek and Roehr, 1986), nitrogen source (Dawson et al., 1989; Choe and Yoo, 1991; Yigitoglu and McNeil, 1992), phosphate and the presence of certain metals (see below) (Kubicek, 1998). Citric acid is reported to appear in large amounts when the pH falls below 2.5. Such a low pH may influence the growth phase and pH <3.5 may inactivate glucose oxidase, which would otherwise convert some of the glucose into gluconic acid (Mischak et al., 1985; Roukas and Harvey, 1988). Other pH effects may include effects on citrate transport and activity of the plasma membrane H+-ATPase (Mattey et al., 1988; Mattey, 1992). 6.1. Role of Metals in Citric Acid Production

The influence of metals can be so important that this can be regarded as the key to a successful submerged fermentation in an industrial context (Kubicek, 1998). Growth-limiting concentrations of Mn, Fe and Zn are essential to achieve high yields of citric acid; for example, Mn concentrations as low as 2 pg 1-’ can reduce acid production by 20% (Clark et al., 1966). Because of such effects, industrial carbon sources may need to be rendered ‘metal-free’ before use or apparently antagonistic substances, such as copper, lower alcohols or lipids, are added (Kubicek, 1998). Since the available Mn2+is too low to activate divalent cation dependent enzymes, such as isocitrate dehydrogenase, it seems that a metabolic step is affected that requires bound rather than free Mn2+(the converse appears to be the case for Zn2+and Fe2+)(Kubicek, 1998). Although it has been suggested that Mn deficiency impairs DNA and protein synthesis (Ma et al., 1985; Hockertz et al., 1987), this is not the only metabolic effect: inhibition of triglyceride and phospholipid synthesis has also been observed (Orthofer et al., 1979; Kubicek and Roehr, 1986; Jernecjc et al., 1989; Meixner et al., 1985). The latter may have consequences for membrane permeability and relevant transport processes: increased citrate efflux has been observed under Mn2+limitation, while citrate uptake from the medium was detected only in A. niger precultivated in Mn-replete medium (Netik et al., 1997). In addition, measurement of citrate uptake required the presence of Mn2+in the assay and was also inhibited by ethylenediamine tetra-acetic acid (EDTA). The Mn2+requirement could partially be replaced by Mg2+,Fe2+or Zn2+, although it was inhibited by Cu2+ (Netik et al., 1997). The effect of Cu2+may be due to inhibition of Mn2+uptake, which can occur via a specific system in A . niger (Hockertz et al., 1988; Seehaus et al., 1990). It is hypothesized that the citrate uptake system depends on Mn2+symport or, more likely, requires metal ion-complexed citrate. For export, since Mn2+deficiency can lead to changes in membrane lipid composition (Meixner et al., 1985), it has been speculated that this leads to ‘carrier inversion’, where an uptake system pumps citrate out of the cells (Netik et al., 1997). This carrier-inversion

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hypothesis may also explain the antagonistic effect of lower alcohols and fatty acids on the presence of Mn2+in fermentation substrates (Kubicek and Roehr, 1986). Such a reciprocal regulation of citrate uptake or export by Mn2+has obvious nutritional consequences for the organism (Netik et al., 1997). Mn deficiency also causes gross morphological alterations in A. niger with the production of bulbous, highly branched, vacuolate mycelia with thickened cell walls (Kisser et al., 1980). Such a morphology fortuitously provides better rheology and enables higher oxygen transfer in citric acid fermentations (Olsvik et al., 1993; Fujita et al., 1994; Iwahori et al., 1995). Interestingly, the addition of calcium (0.5 gl-I CaC1,) to the medium of citric acid-producing A. niger reduced biomass yield but increased citric acid production, with the induction of a pelleted growth form, and increased branching and bulbous cells. It was thought that a cytotoxic effect of citric acid may be involved in these morphological changes (Pera and Callieri, 1997). The effect of Fe is less clear and it is possible that any observed effects are due to contaminating Mn (Kubicek and Roehr, 1986). The mechanism of the Zn2+effect on citric acid production, which is not as pronounced as that of Mn, is similarly uncertain.

7. FUNGAL ORGANIC ACID PRODUCTION AND METAL BIOGEOCHEMISTRY 7.1. Metal Solubilization and Anion Mobility

Solubilization of insoluble metal compounds is an important but unappreciated, aspect of fungal physiology for the release of anions, such as phosphate, and essential metal cations into forms available for intracellular uptake and also into biogeochemical cycles. Fungal solubilization of insoluble metal compounds, including certain oxides, phosphates, sulphides and mineral ores, and leaching of metals from soil and other solids, can occur by several mechanisms, with organic acids occupying a central position in the overall process. Solubilization can occur by protonation of the anion of the metal compound, decreasing its availability to the cation, with nutrient-proton antiport the plasma membrane proton-translocatingATPase and the production of organic acids acting as sources of protons for ‘acidolysis’(Burgstaller and Schinner, 1993; Gadd, 1993; Sayer et al., 1995; Karamushka et al., 1996; Morley et al., 1996; Dixon-Hardy et al., 1998). In addition, organic acid anions are frequently capable of soluble complex formation (‘complexolysis’) with metal cations thereby increasing mobility (Burgstaller and Schinner, 1993; White et al., 1997). Such complexation is dependent on the relative concentrations of the anions and metals in solution, pH and the stability constants of the various complexes (Densvre et al., 1996). Another example of organic acid-mediated

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69

solubilization is ‘redoxolysis’, where oxalic acid can effect the reduction of Fe(II1) to Fe(I1) thus increasing iron solubility (Ghiorse, 1988). A further mechanism of metal solubilization is the production of low molecular weight iron-chelating siderophores that specifically solubilize Fe(II1). Siderophores are the most common means of acquisition of iron by fungi, the most common fungal siderophore being femchrome (Crichton, 1991).Using a simple screening method based on observing clear zones of solubilization around colonies growing on solid medium amended with the desired insoluble metal compound (Jones et al., 1991; Lapeyrie et al., 1991; Burgstaller and Schinner, 1993; Sayer et al., 1995), the incidence of metal-solubilizing ability among natural soil fungal communities appears to be high; in one study approximately one-third of the isolates tested were able to solubilize at least one of Co3(P04),, ZnO or Zn,(PO,), and approximately one-tenth were able to solubilize all three compounds (Sayer et al., 1995). Using this method, A. niger was found to be capable of solubilizing a wide range of insoluble metal compounds, including CdS, Cu,(PO,),, nickel phosphate, manganese sulphide and metal-bearing mineral ores, including cuprite (CuS), rhodochrosite [Mn(CO,),] (Sayer et al., 1997) and gypsum (CaS0,.2H20) (Gharieb et al., 1998). A range of low molecular weight organic acids, including oxalic, formic, citric, malic and acetic acids, are found in soil and derive from a number of sources which include organic matter decomposition, plant root exudates, and fungal and bacterial metabolite production (Song and Huang, 1988; Berthelin etal., 1991; Drever, 1994).As described earlier, such acids can have profound effects on the speciation and mobility of metals, with resultant consequences for biogeochemical cycles, microbial and plant nutrition, and nutrient cycling. As well as influences on metal solubility, organic acids can also increase the availability of phosphate and sulphate (Evans and Anderson, 1990; Drever and Vance, 1994; Cajuste et al., 1996; Gharieb et al., 1998). Most phosphate fertilizers are applied in a solid form (e.g. calcium phosphate) and need to be solubilized before becoming available to plants and other organisms (Asea et al., 1988; Kucey, 1988; Leyval et al., 1993; Bojinova et al., 1997). Increased phosphate uptake by mycorrhizal plants is believed to be due to the high phosphate-solubilizing ability of the mycorrhizal symbionts (Lapeyrie et al., 1991) and, in Canada, a formulation containing spores of Penicillium bilaii has been registered for application to crops because it is believed that the phosphate-solubilizing ability of the fungus (Asea et al., 1988) will improve crop productivity (Cunningham and Kuiack, 1992). This organism produces both citric and oxalic acid, with citric acid being produced under nitrogen limitation and oxalic acid under carbon limitation (Cunningham and Kuiack, 1992). As mentioned earlier, protons which arise from other mechanisms also contribute to metal (and phosphate) solubilization in addition to the action of the organic acids: in the absence of organic acid production, proton excretion which

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accompanied NH,+assimilation was important in AlPO, and calcium phosphate solubilization (Lapeyrie et al., 1991; Illmer and Schinner, 1992, 1995; Illmer et al., 1995). Soil fungi, including mycorrhizas, may increase inorganic nutrient availability to plants and other microorganisms by increasing the mobility of essential metal cations and other anions, e.g. sulphate (Gharieb et al., 1998). It is significant that root infection is favoured in nutrient-deficient soils, and this promotes increased growth of the host plant. It is believed that mycorrhizas provide host plants with growth-limiting resources at the stages in their growth when they are most required (Read, 1991). Solubilization may therefore be important for the release of essential metal ions to plants. Oxalate is a common low molecular weight organic anion in many soils; it is sometimes dominant (Graustein et al., 1977), and this increases the solubility of both P and Al, thus influencing nutrient availability and soil weathering (Fox and Comerford, 1990, 1992). Oxalate concentrations in the soil solution can range from 25 to 1000 p~ in forest soils, and oxalate may be the only low molecular weight organic acid found in non-rhizosphere soil (Fox and Comerford, 1990). Ligand-exchange reactions at oxide surfaces directly release P, while surface complexation also enhances dissolution of Al-oxide surfaces, increasing both A1 and P solubility. Such solubilization increases as the organic acid anion concentration increases (Fox et al., 1990a,b). Oxalic acid may also solubilize P bound by Ca2+and Fe3+(Cannon et al., 1995; Cajuste et al., 1996) with the process approximating to the model of Jurinak et al. (1986) for oxalate-mediated increase in P solubility from apatite: Ca,(PO,),OH

+ 5H,C,O, + 5CaC,O, + 3H3P0, + H,O

(12)

Similar reactions occur with A1 and Fe phosphate minerals. The occurrence and position of carboxylic and phenolic functional groups on organic acids determines complexing ability, which is thus related to the stability constant of the ligand. P release is generally greater with acids that form stable metal complexes (Fox et al., 1990a,b; Bolan et al., 1994). For Al, log K,, was a good indicator of this and, of several organic acids examined, A1 and P release increased exponentially with increasing values of stability constants (Fox et al., 1990b). Oxalate concentrations are generally higher in the rhizosphere (Fox and Comerford, 1990),which has obvious implications for P availability to the plant (Fox and Comerford, 1992).It has been found that the amounts of A1 and P released are controlled by the cumulative oxalate loading rate, suggesting that continuous release of even small amounts of organic anions could solubilize large amounts of P and A1 on an annual basis (Fox and Comerford, 1992). Oxalic acid is produced by ectomycorrhizalfungi (Graustein et al., 1977) and this may be significant in increasing P availability to host plants (Cannon et al., 1995). Oxalate is a major organic acid produced by Paillus involutus and Pisolinthus tinctorius, with both fungi able to weather a phlogopite mica,

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71

displacing interlayer K+,Al'+ and/or Mg2+from within the mineral (Paris et al., 1995a). The role of H+ in K+ replacement was invoked with the formation of metal oxalates acting on the multivalent cations (Paris et al., 1996). It was found that I? involutus was a very active oxalate producer under K+ and Mg2+ deficiency, which could explain mineralogical changes that are effected by the fungi and further underline the key role of oxalic acid in weathering in response to nutrient limitation (Comerford et al., 1990; Paris et al., 1996). Oxalic acid from I? involutus is also involved in vermiculite weathering (Paris et al., 1995b).Within mats of Hysterangium crassum, soil oxalate concentrations were higher than in surrounding soil, while the pH was considerably lower (Cromack et al., 1979). Bulk weathering of the clay minerals was more pronounced in these mats than in uncolonized soil, a result again of Fe and A1 solubilization. Similar observations have been made for Hysterangium setchellii and Gauteria monticola in relation to P solubility (Griffiths et al., 1994). Citric acid is also able to increase soluble P - as are other organic acids not discussed in this article, e.g. acetic, formic, lactic, malic and tartaric acids (Bolan et al., 1994; Kpomblekou-A and Tabatabai, 1994); tricarboxylic acids (e.g. citric acid) were more effective than dicarboxylic acids (e.g. oxalic acid) (Bolan et al., 1994). In one study, 1 m~ citric and oxalic acids were more effective than 1 m~ H2S0, in phosphate release from phosphate-containingrocks (Kpomblekou-A and Tabatabai, 1994). The complexing ability of oxalate and its effect on A1 mobility is also a factor in secondary-porositydevelopment in sandstones during diagenesis by increasing feldspar solubility and dissolution rate (Huang and Longo, 1992; Franklin et al., 1994). Similar observations on increases in mineral solubility and dissolution kinetics have also been made at lower 'room' temperatures for feldspar (Manley and Evans, 1986; Mast and Drever, 1987; Amrhein and Suarez, 1988; Drever and Stillings, 1997). In some of these studies, the higher dissolution rates in the presence of organic acids were concluded to be a result of H+ activity rather than complexation (Manley and Evans, 1986), while dissolution rates were proportional to the A1 content (Amrhein and Suarez, 1988; Stillings et al., 1996). Dissolution kinetics of kaolinite were also increased by oxalate (Chin and Mills, 1991). Although organic acids may accelerate dissolution by lowering pH, this may be significant only below approximately pH 5 (Drever and Stillings, 1997). Quartz dissolution and iron crystallite formation are also associated with fungal-derived oxalic acid (Feldmann, 1997; Feldmann et al., 1997).Although gross concentrations of organic anions in the soil solution may appear insufficient to cause significant increases in dissolution rates of silicate minerals, higher concentrations are likely to be present in microenvironments surrounding fungal hyphae (Drever and Stillings, 1997); it should also be noted that individual organic acids in the soil solution can exceed millimolar concentrations (Stevenson, 1967), with extremely high concentrations in the vicinity of certain plants and fungal hyphae (Cromack et al.,

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1979; Gardner et al., 1983). It is now known that weatherable minerals under many European coniferous forests contain a network of pores, believed to be formed by fungal excretion of organic acids. Symbiotic mycorrhizal hyphae could translocate dissolved minerals from these pores directly to the plants, and thus avoid nutrient competition with other microbes (Jongmans et al., 1997). The pores are about 3-10 pm, sometimes containing hyphae, and widespread in feldspars and horneblendes from a variety of locations. Organic acid concentrations in the soil ranged from micromolar to millimolar and included citrate and oxalate: it was calculated that calcium-rich feldspars could be dissolved to form pores at the rate of 0.3-30 pm year' (Jongmans et al., 1997). Solubilization of insoluble toxic metal compounds in the environment can have adverse effects if potentially toxic metal ions are released into the soil and/or water systems from metal-contaminatedlocations (Francis et al., 1992). It has been suggested that certain microbiological solubilization processes, including proton efflux, are included in the safety assessment of waste repositories (Arter et al., 1991). Metal-citrate complexes are highly mobile and are not readily degraded (Francis et al., 1992). Brynhildsen and Rosswall(l996) have found that citrate degradation by mixed microbial cultures from soil extracts was completely inhibited when the acid was bound to Zn, Cu or Co, and partly inhibited when bound to Al, although degradation of Cu and Zn citrate complexes was unaffected in soil. Some rock phosphate fertilizers contain Cd, and solubilization of these to release the phosphate could also release Cd, increasing its availability to the soil biota (Leyval et al., 1993). Metal-contaminated mining areas are often revegetated to help stabilize soils and reduce runoff and wind erosion. The production of organic acids and other metabolites by rhizosphere microorganisms in such locations can also influence metal mobility, especially when the soil microflora have not been completely restored (Banks et al., 1994a,b). 7.2. Role of Organic Acids in Corrosion of Stone and Building Materials

Microbial organic acid production can lead to corrosion of building materials (Little etal., 1994; Douglas and Singh, 1995) and stone monuments (Hirsch et al., 1995; Garcia-Valles et al., 1996). A wide range of organisms can cause changes in the surface layers of rocks, with organic acid production an important component of the overall process (Berthelin, 1983).Acidogenic fungi can cause extensive deterioration of clays, micas and feldspars due to production of oxalic, citric and gluconic acids (De la Torre et al., 1993). Different groups of organisms appear to act synergistically in stone deterioration with algal/cyanobacterial lysis providing nutrients for heterotrophs, and

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73

development of more complex microbial communities.Fungal strains isolated from weathered sandstone included oxalic, fumaric and succinic acidproducing strains of Penicillium and Fusarium, with Penicillium corylophilum producing oxalic acid only when cultured in the presence of the alga Monoraphidium braunii (Gomez-Alarconet al., 1994). In other studies, fungi isolated from sandstone produced citric, glutamic, pyruvic, malic, succinic, lactic, formic, fumaric and oxalic acids in laboratory culture; many of these acids could also be extracted from rock samples (Hirsch et al., 1995). Fungalproduced organic acids are also capable of cement degradation, a phenomenon of relevance to deterioration of building materials and also nuclear waste repositories. Minerals in cement, e.g. hydrated calcium silicate and Ca(OH),, were readily degraded by alkalophilic strains of A. niger and Mycelia sterilia producing oxalic, gluconic and malic acids (Perfettini et al., 1991). Oxalic acid production is also involved in the corrosion of stonework by lichens. Physical and chemical changes to stonework of ancient monuments, such as fracturing and encrustation can lead to biodeterioration, with calcium oxalate (whewellite and weddelite) being a significant chemical component in surface patinas, particularly on limestone (Edwards et al., 1992, 1994; Russ et al., 1996).Weddelite has been proposed to serve as a water-absorbing substrate which transforms to whewellite when the humidity falls (Lamprecht et al., 1997).At the thallus-substrate interface, oxalic and polyphenolic lichen acids are produced by the fungal symbiont, which act to remove metals from the mineral substrate while carbonic acid arises from CO, produced in respiration. Calcium oxalate can be a major constituent of lichen thallus encrustation, as well as calcium carbonate in some cases (Edwards et al., 1992, 1994, 1995, 1997; Prieto et al., 1997). The nature of the metal oxalate may depend on the chemical composition of the rock (Edwards and Lewis, 1994). For example, Pertusaria corallina produces calcium oxalate on a basalt substrate but magnesium oxalate forms during growth of Lecanora a m on serpentine (Edwards and Lewis, 1994). Hydrated copper oxalate, moolooite CuC,O,.nH,O (n-0.4-0.7), is found as vivid blue inclusions in whewellite or weddelite occurring within the medulla of four lichen species growing on copper-bearing rocks (Chisholm et al., 1987). In some copper-tolerant lichen species, the copper oxalate content can reach 5% of the thallus dry weight (Purvis, 1984). Calcium oxalate is also located on the surface of many lichens, as well as within the thallus and at the thallus-rock interface, and these may persist even after death. Within such lichen encrustations, which can be up to 2 mm thick, further deterioration can result in changes in the hydration state of the calcium oxalate (Edwards and Lewis, 1994). On granite, a monolayered or multilayered patina can arise from surface biofilm activity, mineral deposition and dust trapping, which can be regarded as a microstromatolitic structure, containing calcite, calcium oxalate, gypsum and calcium phosphate as main minerals, and deduced to be produced by the stromatolite-forming microorganisms

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(Blazquez et al., 1997). Oxalate has been shown to be the only organic acid detectable in cryptoendolithic (‘hidden-in-rock’), lichen-dominated, microbial communities in Antarctica with a proposed significant role in affecting dissolution of Si, Fe, Al, P and K (Johnston and Vestal, 1993). 7.3. Role of Fungal Oxalato in Limestone Biomineralization

Fungi can play a significant role in limestone diagenesis in semi-arid regions where large areas of limestones and carbonate soils are cemented by calcite (Verrecchia et al., 1990). Weathered profiles that develop on chalky parent rocks in arid regions usually include a layer called a ‘platy calichekalcrete’ or ‘platy zone’ (Verrecchia and Dumont, 1996). While physical and chemical phenomena contribute to this process, the most abundant organic feature is mineralized fungal hyphae and it is now realized that fungal activity is of fundamental importance to the mineral dynamics of the porekarbonate system. Fungal hyphae are present in the pores, which range in diameter from several micrometres to several hundred micrometres (Verrecchia et al., 1990,1993). The hyphae that develop in the pores of the limestone are encrusted with sharp crystalline spikes exterior to the hyphae. Up to around 80% of the limestone micropores are inhabited by fungi and, in some places, pores are partly infilled with needle-fibre calcite (Verrecchia et al., 1990) with the matrix around the pore being enriched in CaCO,; this is sometimes recrystallized and separated from the pore by a mat of calcite crystals (Verrecchia and Dumont, 1996). The crystals, often needle-like but showing a variety of morphologies, are calcium oxalate monohydrate (whewellite) and arise from oxalic acid production by the fungi, itself promoted by alkaline conditions, and subsequent precipitation of calcium oxalate:

In the absence of fungal hyphae, the calcite needles have different forms, and the fungi are clearly altering the mineral dynamics of the porekarbonate microsystem (Verrecchia and Dumont, 1996). It is likely that polyhydrate oxalates form first and, after dehydration, evolve into the monohydrate (Verrecchia et al., 1993). A biogeochemical model of this system proposes that organic acid excretion, and calcium oxalate formation, leads to dissolution of the internal pore walls so that the solution becomes enriched in dissolved carbonates. During passage of this solution through the pore walls, CaCO, recrystallizes owing to a decrease in pCO,, which contributes to hardening of the material. Subsequent biodegradation of the oxalate as a result of microbial activity leads to

FUNGAL PRODUCTION OF CITRIC AND OXALIC ACID

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Figure I I Mechanisms involved in the pore-fungus-carbonate-oxalate system (adapted from Verrecchia and Dumont, 1996). H = fungal hypha and associated crystals of calcium oxalate; MH = mineralized fungal hypha containing crystals of needle-fibre calcite (NFC). After decomposition, NFC is freed within the pore system. CaCO, (sec.) (shaded area) = a secondary CaCO, cement arising from either precipitation in the soil solution or transformation of oxalate. The stippled area denotes clay and quasi-coatings. The processes shown lead to the eventual closing of the system, and cementation of chalky material and calcretes in surficial and semi-arid environments.

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transformation into carbonate, which results in precipitation of calcite in the pore interior or periphery, the latter ultimately leading to closure of the pore system and hardening of the chalky parent material (Fig. 1 1) (Verrecchia et al., 1990;Verrecchia and Dumont, 1996). The final stage is conversion of calcium oxalate into calcium carbonate by diagenesis:

Many soil microorganisms can convert calcium oxalate to calcium carbonate (Graustein et al., 1977) and this process increases secondary calcium carbonate cementation. Ultimately, the pores become completely filled and a hard limestone (‘desert crust’) results (Verrecchia, 1990; Verrecchia and Dumont, 1996). During decomposition of hyphae, associated calcite crystals are released and these can act as sites of further secondary calcite precipitation (Verrecchia et al., 1993;Verrecchia and Verrecchia, 1994). Thus, fungal activity, in influencing cation mobility and acidification, is an important factor in early lithification, alteration and diagenesis of terrestrial subsurface limestones (Verrecchia and Dumont, 1996).

8. FUNGAL ORGANIC ACID PRODUCTION AND METAL

BIOTECHNOLOGY 8.1. Metal Solubilization for Recovery and Bioremediation

The fungal removal or leaching of metals (‘heterotrophic leaching’) from industrial wastes and by-products, low-grade ores (Dave and Natarajan, 1981 ; Burgstaller and Schinner, 1993) and metal-bearing minerals (Tzeferis et al., 1994; Drever and Stillings, 1997), is a process relevant to metal recovery and recycling and/or bioremediation of contaminated solid wastes (Groudev, 1987; Burgstaller and Schinner, 1993; Hahn et al., 1993; Krebs et al., 1997; White et al., 1997). It should also be noted that heterotrophic leaching may also have application to biotechnological recovery of phosphate (or indeed other solubilized anions) from rock phosphate or other sources (Parks er al., 1990; Vassilev et al., 1995, 1997; Bojinova et al., 1997). Most biological leaching processes utilize chemoautotrophic bacteria, particularly Thiobacillus spp. (Ewart and Hughes, 1991). However, the pH of culture media may be increased by many industrial metal-containing wastes, such as filter dusdoxides from metal processing, and most thiobacilli cannot solubilize metals effectively above pH 5.5, the optimum being pH 2.4 (Burgstaller and Schinner, 1993). Although fungi need aeration and a carbon source, they can function at higher pH values and so could have potential where leaching with bacteria is not possible. However,

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fungi may not readily be used in situ, and their use in specific bioreactors is generally envisaged. Leaching of metals with fungi can be very effective, although a high level of organic acid production may need to be maintained. For example, laboratory-scale leaching of Ni, Co and Mn from low-grade laterite ores has been carried out using strains of Aspergillus and Penicillium (Tzeferis et al., 1994; Sukla e f al., 1995). Leaching of 55-6096 Ni was achieved when the fungi were grown in the presence of the ore, and 70% was leached at high temperature (95 "C)by the application of metabolites produced on cultivation of the fungi at 3OoC in a glucose and sucrose medium (Tzeferis, 1994). Heterotrophic leaching by fungi can occur as a result of several processes, including the production of protons, and siderophores (in the case of iron). In most fungal strains, however, leaching occurs mainly by the production of organic acids which provide a source of protons and complexing organic acid anions (Burgstaller and Schinner, 1993; Muller et al., 1995; Sayer and Gadd, 1997). The pH of non-regulated A. niger cultures can fall to values between 1.5 and 2.0 owing to high citric acid production, the optimal pH for citric acid production being below 3.5 (Schrickx et d., 1995). As discussed previously, organic acid production can be manipulated by changes in culture conditions (Xu et al., 1989; Schrickx et al., 1995; Dixon-Hardy et al., 1998). For examM) leads to the production of large amounts ple, manganese deficiency of citric acid by A. niger (Meixner et al., 1985), and industrial concentrations of citric acid produced by A. niger can reach 600 m~ (Mattey, 1992). Oxalic acid production can also be manipulated for solubilization of metals such as A1 and Fe: up to -430 m~ oxalic acid was excreted in a stirred-tank reactor controlled at pH 6. While both gluconic and oxalic acid were produced on sucrose, only oxalic acid was produced on lactose permeate, a low-cost carbon substrate (Strasser et al., 1994). Fly ash from municipal waste incineration contains a variety of metals (Cd, Zn, Ni, Pb and Cu), with A1 and Zn in particular being present in amounts considered economical for recovery (Singer et al., 1982;Torma and Singh, 1993; Bosshard et at., 1996).A. niger produced gluconate in the presence of fly ash but citric acid in its absence; variation in fly ash concentration resulted in varying amounts of solubilized metals. A two-step process, where citric acid produced by controlled growth of A. niger was used as the leaching agent, provided a leaching system only marginally less efficient than leaching with commercial citric acid of equal molarity (Bosshard et al., 1996). A strain of Penicillium simplicissimum isolated from a metal-contaminated site developed the ability to produce citric acid (> 1 0 0 m ~in ) the presence of metal contaminants, and has been used successfully to leach Zn from insoluble ZnO contained in industrial filter dust (Schinner and Burgstaller, 1989; Franz et al., 1993; Burgstaller and Schinner, 1993). Acidolysis was found to be the main ZnO solubilization mechanism.

GEOFFREY M.GADD

78

ZnO + 2H+ + Zn2++ H,O

(15)

with the protons from the citric acid produced being responsible for nearly all the solubilization,prior to possible formation of a zinc citrate complex, which may prevent Zn2+toxicity (Burgstaller et al., 1992). Citric acid efflux is enhanced in t? simplicissirnum by the presence of filter dust andor zinc oxide, an effect of the high buffering capacity of zinc oxide (Franz et al., 1991; Burgstaller et al., 1994). Biological leaching of red mud, a chemical waste produced by alkaline extraction of alumina from bauxite, has been examined with t? simplicissimum, the most efficient fungus for solubilization of A1 (1880 mg I-’ at 3% (v/v) red mud) (Vachon et al., 1994). However, 75% of A1 present (10585 mg I-’) was leached from 10%(v/v) red mud, an amount greater than that achieved using pure commercial citric acid. The authors concluded that biologically produced organic acids did provide a feasible possibility for industrial-scale extraction (Vachon et al., 1994). Culture filtrates from A. niger have also been used to leach Cu, Ni and Co from copper converter slag (Sukla et al., 1992). If necessary, metal-citrate complexes could eventually be degraded for ultimate metal recovery (Francis, 1994). Another possible application or effect of fungal metal solubilization could be the removal of unwanted contaminants, such as phosphates (Burgstaller and Schinner, 1993), while interaction of leaching technologies with biosorption is also a possibility (Gadd, 1993; Tobin et al., 1994). Another related bioremediation scheme uses commercial citric acid to remove metals and radionuclides from contaminated wastes by forming watersoluble metal citrate complexes. The resulting metal citrate complexes are then microbially and photochemically degraded and the metals recovered in concentrated form with the degrading bacterial biomass (Francis et al., 1992; Francis and Dodge, 1994; Dodge and Francis, 1994).

ACKNOWLEDGEMENTS

The author gratefully acknowledges research support from the Biotechnology and Biological Sciences Research Council (SPC 028 12), the Royal Society (London), the Royal Society of Edinburgh, NATO (Envir. LG 950387) and the Nuffield Foundation. Thanks are also due to Dr Jacqueline Sayer, Dr Mohammed Gharieb, Dr Victor Karamushka, and Amanda Whatley and Karen Tait for their sterling contributions on various aspects of metal-fungal-organic acid interactions. Martins Kierans and Margaret Gruber are also acknowledged for assistance with scanning electron microscopy and photography.

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Vassilev, N., Baca, M.T., Vassileva, M., Franco, I. and Azcon, R. (1995)Rock phosphate solubilization by Aspergillus niger grown on sugar-beet waste medium. Appl. Microbiol. Biotechnol. 44,546-549. Vassilev, N., Vassileva, M. and Azcon, R. ( 1 997) Solubilization of rock phosphate by immobilized Aspergillus niger. Biores. Technol. 59, 1 4 . Verrecchia, E.P. ( 1990) Lithodiagenetic implications of the calcium oxalatexarbonate biogeochemical cycle in semi-arid calcretes, Nazareth, Israel. Geomicrobiol. J. 8, 89-101. Verrecchia, E.P. and Dumont, J.-L. (1996) A biogeochemical model for chalk alteration by fungi in semiarid environments. Biogeochemistry 35,447470. Verrecchia, E.P. and Verrecchia, K.E. (1994) Needle-fiber calcite: a critical review and a proposed classification. J. Sedim. Res. A64 650-664. Verrecchia, E.P., Dumont, J.L. and Rolko, K.E. (1990) Do fungi building limestones exist in semi-arid regions? Naturwissenschaften 77, 584-586. Verrecchia, E.P., Dumont, J.L. and Verrecchia, K.E. (1993) Role of calcium oxalate biomineralization by fungi in the formation of calcretes: a case study from Nazareth, Israel. J. Sedim. Petrol. 63, 1000-1006. Vivier, H., Marcant, B. and Pons, M.-N. (1994) Morphological shape characterization: application to oxalate crystals. Particle Particle Sys. Cha,: 11, 150-155. Wainwright, M. (1988) Metabolic diversity of fungi in relation to growth and mineral cycling in soil - a review. Trans. B,: Mycol. SOC.90, 159-170. Wainwright, M. and Gadd, G.M. (1997) Fungi and industrial pollutants. In: The Mycota IV Environmental and Microbial Relationships (D. T. Wicklow and B. E. Soderstrom, eds), pp. 85-97. Springer-Verlag, Berlin. Wang, A. and Tewari, J.P. (1990) Role of oxalic acid in pathogenesis by Mycena citricolor (Agan'cales, Hymenomycetes), causal agent of the American leaf spot of coffee. Crypt. Bot. 1,396-398. Wang, Y.C. and McNeil, B. (1995) pH effects on exopolysaccharide and oxalic acid production in cultures of Sclerotium glucanicum. Enzyme Microbiol. Technol. 17, 124-1 30. White, C., Sayer, J.A. and Gadd, G.M.(1997) Microbial solubilization and immobilization of toxic metals: key biogeochemical processes for treatment of contamination. FEMS Microbiol. Rev. 20,503-5 16. Whitney, K.D. and Amott, H.J. (1986a) Morphology and development of calcium oxalate deposits in Gilbertella persicaria (Mucorales) Mycologia 78,42-5 1. Whitney, K.D. and Amott, H.J. (1986b) Calcium oxalate crystals and basidiocarp dehiscence in Geastrum saccutum (Gasteromycetes) Mycologia 78,649-656. Whitney, K.D. and Amott, H.J. (1987) Calcium oxalate crystal morphology and development in Agaricus bisporus. Mycologia 79, 180-1 87. Whitney, K.D. and Amott, H.J. (1988) The effect of calcium on mycelial growth and calcium oxalate crystal formation in Gilbertella persicaria (Mucorales) Mycologia 80, 707-7 15 . Wolschek, M.F. and Kubicek, C.P. (1999) Biochemistry of citric acid accumulation by Aspergillus niger. In: Citric Acid Biotechnology (B. Kristiansen, M. Mattey and J. Linden, eds), pp. 1 1-3 1. Taylor and Francis, London. Wood, P.M. (1994) Pathways for production of Fenton's reagent by wood-rotting fungi. FEMS Microbiol. Rev. 13, 313-320. Xu, D.-B., Madrid, C.P., Roehr, M. and Kubicek, C.P. (1989)The influence of type and concentration of the carbon source on the production of citric acid by Aspergillus niger. Appl. Microbiol. Biotechnol. 30, 553-559. Yang, J., Tewari, T.P. and Verma, P.R. (1993) Calcium oxalate crystal formation in Rhizoctonia solani AG 2-1 culture and infected crucifer tissue: relationship between host calcium and resistance. Mycol. Res. 97, 1516-1522.

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Yigitoglu, M. and McNeil, B. (1992) Ammonium and citric acid supplementation in batch cultures of Aspergillus niger. FEMS Microbiol. Lett. 8 , 7 1-74. Zuo, Y. and Hoigne, J. (1994) Photochemical decomposition of oxalic, glyoxalic and pyruvic acids catalyzed by iron in atmospheric waters. Atmos. Environ. 28, 123 1-1239.

Bacterial Viability and Culturability Michael R. Barer and Colin R. Harwood Depanment of Microbiology and Immunology, The Medical School, Framlington Place, Newcastle upon Tyne, NE2 4HH

ABSTRACT

Renewed interest in the relationships between viability and culturability in bacteria stems from three sources: (1) the recognition that there are many bacteria in the biosphere that have never been propagated or characterized in laboratory culture; (2) the proposal that some readily culturable bacteria may respond to certain stimuli by entering a temporarily non-culturable state termed 'viable but non-culturable' (VBNC) by some authors; and (3) the development of new techniques that facilitate demonstration of activity, integrity and composition of non-culturable bacterial cells. We review the background to these areas of interest emphasizing the view that, in an operational context, the term VBNC is self-contradictory (Kell et al., 1998) and the likely distinctions between temporarily non-culturable bacteria and those that have never been cultured. We consider developments in our knowledge of physiological processes in bacteria that may influence the outcome of a culturability test (injury and recovery, ageing, adaptation and differentiation, substrateaccelerated death and other forms of metabolic self-destruction, prophages, toxin-antitoxin systems and cell-to-cell communication). Finally, we discuss whether it is appropriate to consider the viability of individual bacteria or whether, in some circumstances, it may be more appropriate to consider viability as a property of a community of bacteria. 1. Introduction ....................................................... 2. Definitions ........................................................ 3. The 'viable but non-culturable' (VBNC) hypothesis ....................... 4. 'As yet uncultured' (AYU) bacteria ..................................... 5. 'New'methods ..................................................... 5.1. Fluorescence methods ..........................................

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5.2. The Kogure ‘tentative direct microscopic method of counting live 103 bacteria’ ...................................................... 106 5.3. Molecular approaches ........................................... 108 5.4. Developments in instrumentation ................................. 110 5.5. What do the ‘new’ methods tell us? ................................ 111 6. Factors influencing the outcome of culturability tests ..................... 112 6.1. Injury and recovery ............................................. 113 6.2. Ageing ....................................................... 115 6.3. Adaptation and differentiation .................................... 6.4. Substrate-accelerated death and other forms of metabolic 117 self-destruction ................................................ 6.5. Lysogenic bacteriophages and toxin-antitoxin systems . . . . . . . . . . . . . . . 119 120 6.6. Cell-to-cell communication (quorum sensing) ....................... 7. Should bacterial viability be assessed at the individual or community level? , . 122 8. Conclusions ....................................................... 124 126 Acknowledgements ................................................. 126 References ........................................................

1. INTRODUCTION

The terms ‘viable’ and ‘viability’ are used extensively both in microbiology and in common parlance. Here we argue that the microbiological usage is in danger of losing its meaning unless a new consensus can be developed. We revisit the arguments set out by Postgate (1967) in the first paper of the first volume of this series, review technical and conceptual developments since that time and draw conclusions in the light of those developments. While discussions concerning the appropriate use of terms may appear to be academic, it should not be forgotten that many practical decisions in the real world are based on detecting specific bacteria by culture and on enumerating them by ‘viable counts’. Judgements on the classification of food or drink as microbiologically safe for human consumption, of beaches being sufficiently clean for recreational bathing, of antibiotics having bactericidal activity, and of pharmaceutical preparations being sterile and suitable for parenteral administration are all currently based on culture tests where viability is equated with culturability. The introduction of new molecular and cytological techniques that facilitate detection of bacteria independently of culture has raised the prospect of developing new criteria that attach the decision-making process to these determinations rather than culture and subsequent incorporation of these into legislation. In consequence, the need for precision and consensus in our use of the term viability as applied to bacteria and its practical implications is, if anything, increasing. It is our belief that progress towards a new consensus can be achieved by making a clear distinction between use of these terms in operational (practical)

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and conceptual (theoretical) domains (Kell et al., 1998). Precedent leads us to recognize that measurement of the number of bacteria in a sample that can be propagated in laboratory cultures (culturability*) provides the most widely accepted practical measure of viability (Postgate, 1976; Madigan et al., 1997). However, two prominent strands of research have undermined the sanctity of the operational canon which equates viability and culturability.The first strand concerns the proposal that certain bacteria may become temporarily nonculturable - termed by some ‘viable but non-culturable’ (VNC or VBNC) - in response to specific stimuli, while the second stems from the recognition by molecular and cytological means that there are many bacteria in the biosphere that have never been cultured. The difficulties raised by investigations in these areas are, to some extent, compounded by the new methods alluded to above. Thus, where such methods have been applied together with culture, substantial discrepancies have been recognized in both the distribution and activity of specific organisms determined by the two approaches. One obvious potential solution to these problems is to adopt an operational definition of viability other than culturability. Clearly, such a general change would require extensive validation of the methodology employed and the question of whether this can be justified by currently available evidence is considered below. A more difficult aspect of the current debate is the lack of consensus in what microbiologists mean by ‘viability’. We do not propose to amplify on these semantic arguments here as we have considered them at length elsewhere (Barer, 1997; Kell et al., 1998). However, while the debate persists, we consider it essential that workers define their own usage of these terms.

2. DEFINITIONS

In general, bacterial species can be divided into those that have and those that have not been propagated by laboratory culture. It follows, therefore, that culturability can only be used as an operational definition of viability in the former group. A universal definition of bacterial viability therefore requires discussion of some conceptual issues. In common parlance, use of the terms ‘viable’ and ‘viability’ reflects our expectation that entities, which may be animate, inanimate or abstract, will survive over a generally accepted (but rarely stated) period of time. In macrobiology, the time frame for the viability of an individual is the normal life span for that species in a particular environment. In microbiology, the life *While accepting that the terms ‘cultivable’and ‘capacity for cultivation’are linguistically accurate, established usage and the need to cross-refer to other texts leads us to use ‘culturable’and ‘culturability’ in the present context.

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span of individual cells is rarely considered and the time frame under consideration often extends for several generations. It follows that reproductive capacity becomes as inherent to our view of the viability of bacteria as it would be to our understanding of the long-term survival of any species. Since life span itself is an important and necessary variable in microbial physiology, it is hardly surprising that application of terms commonly applied to entities that have relatively constant life expectancies (unless they are prematurely terminated) gives rise to confusion. As a point of reference for subsequent discussions we have provided brief conceptual and operational definitions of commonly used (and misused) terms relating to bacterial culturability and viability (Table 1). A number of general points emerge. Firstly, the operational definitions are, by their very nature, retrospective, i.e. they can only be applied after completion of a defined and sometimes lengthy test. Even though the results of some rapid tests correlate well with culturability in some defined settings, we are not aware of any generally applicable test that allows the viability of bacteria to be determined in real time (see below). Secondly, the definitions have been coined such that they may be applied at the single-cell or population level, another point to which we shall return. Finally, we emphasize that these definitions are primarily intended to serve the objectives of this review; we are not advocating a microbiological form of ‘politicalcorrectness’.We recognize modifications that we have made from an earlier review and accept that others may wish to use alternative definitions. Nonetheless, we appeal to authors to either state or refer to the definitions to which they adhere. It will be noted that we have avoided defining the terms ‘live’, ‘alive’, ‘vital’, ‘senescent’, ‘moribund’and ‘dead’. In general, we prefer to limit the use of these terms since they are powerfully evocative in an anthropomorphic context. However, they may be useful and can be defined by reference to terms in Table 1. Of course, it is also recognized that there are difficulties in applying these terms in a human context, particularly in a medico-legal sense.

3. THE ’VIABLE BUT NON-CULTURABLE’ (VBNC) HYPOTHESIS

The issues relating to putative VBNC states have been recently reviewed (Kell et al., 1998) and consequently will only be covered briefly in this review. Our initial comments refer only to those bacteria that can readily be cultured in the laboratory. A combination of laboratory experiments and epidemiological issues led Colwell and her associates to develop the VBNC hypothesis (Xu et al., 1982; Brayton et al., 1987; Hussong et al., 1987a,b; Roszak and Colwell, 1987a,b;

Table I

Definitions

Term

:

Conceptual definition

Operational definition

0

1. Viable

Retaining the capacity for replication over a stated or generally accepted time frame

Explicit demonstration of replication in a validated laboratory system

Ft

2. Replication

Genomic replication and segregation into a new selfpropagating unit (propagule)

Observed cell fission or increase in number of propagules

G

3. Culturabie

Capable of detectable replication in a realizable laboratory system

Detected replication in a validated laboratory system

4. Growth

Accumulation of biomass

Demonstrated accumulation of biomass

5. Dormancy

A reversible state of low metabolic activity in a unit that maintains viability

A demonstratedreversible low state of metabolic activity demonstrated by a specific technique or set of techniques in an

? C

operationally viable unit A demonstrated transition from a temporary state of nonculturability in a defined system to culturability in that system. The procedure must exclude regrowth as a possible explanation

5

;;I I

2

%0 0

C

6. Resuscitation Transition from a state in which the specified unit had temporarily lost the capacity for self-replication to regaining that capacity 7. Regrowth Growth and/or replication of a very small subpopulation of the study population that causes changes in cell numbers that are below the limit of detection for the study methods applied 8. Cryptic Growth andor replication of a subpopulation within the study growth population that cannot be detected by the methods applied 9. Suicide An irreversible process by which a viable unit determines the loss of its own viability by a specific mechanism

a

5

Growth andor replication demonstrated by one method that led to detection of the organism by another, less sensitive, method. If the latter were applied alone, resuscitation would appear to have occurred Growth andor replication demonstrated by one method that was not detected by another, less sensitive method A non-reversible response in which a population of propagules can be shown to have lost demonstrableviability as a result of a process intrinsic to that response

10. Activity

A metabolic or behavioural process occurring within the unit under consideration.The unit may be viable or non-viable

A demonstrated behavioural, biochemical or physiological process occurring within the unit under consideration

1 1. Survival

Maintenance of viability

Maintenance of operational viability

(D

4

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Pearson et al., 1993). Coherent arguments have been advanced to support the view that a number of pathogenic bacteria, notably Vibrio cholerae (Huq and Colwell, 1996) and Campylobacterjejuni (Rollins and Colwell, 1986; Pearson et al., 1993) adopt specific physiological states during residence outside human or animal hosts, and that these states are critical to the maintenance of environmental sources and reservoirs of infection. In the proposed VBNC state, it is contended that cells may become temporarily non-culturable until they are exposed to an environment that stimulates their resuscitation and that the cells that retain capacity for resuscitation can be identified by application of a cytological test of activity (Oliver, 1993). These proposals have led to a flurry of purported demonstrations of bacteria that have the capacity for transition to and from the proposed VBNC state (Oliver, 1993; Kell et al., 1998). However, there are two critical practical issues in assessing the evidence relating to the VBNC hypothesis. The first, to which we return below, is the degree to which activity assays can be accepted as measures of viability. The second concerns whether the cell populations that were studied truly resuscitated or whether the observed phenomena can be attributed to ‘regrowth’.We emphasize the need for careful statistical analysis in such experiments, particularly where infectivity is studied in animals (Jones et al., 1991; Oliver and Bockian, 1995) or humans (Colwell et al., 1996), so that effects can be unambiguously attributed to temporarily non-culturable cells as distinct from a small fraction of culturable cells (Barer et al., 1998; Kell et al., 1998). Failure to make this distinction in published infection studies does not detract from the interest of the work; however, it does undermine the degree to which the observed effects can be attributed to temporarily nonculturable cells. Despite a number of studies where transition to and from a temporarily nonculturable state offers the simplest explanation for the observed phenomena ( e g Votyakova et al., 1994; Wai et al., 1996; Steinert et al., 1997; Whitesides and Oliver, 1997),we do not consider that these enable us to define a VBNC state or states in physiological terms. Reports of resuscitation are still relatively rare. Given other potential explanations, we believe it is necessary for the reported resuscitation phenomena to be repeated in several laboratories. Moreover, as there is much concern over the potential hazards posed by temporarily non-culturable bacteria (Byrd et al., 1991;Barer et al., 1993), a high priority should be given to the development of methods capable of distinguishing between such bacteria and those that are permanently non-culturable (non-viable).Such methods could then be applied to determine how extensive infective and other hazards posed by temporarily non-culturable bacteria might be. It should be apparent from Table 1 that we consider culturability to be the only validated operational definition of viability. In consequence, we consider the term ‘VBNC’ to be an oxymoron (Barer, 1997) and prefer the terms ‘temporarily non-culturable’ (Ekweozor et al., 1998) or ‘not immediately

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culturable’ (NIC) (Kell et al., 1998) to describe non-culturable cells that are capable of being resuscitated. Whether temporal non-culturability can result from a specific programmed differentiation or adaptive processes remains an open question. As far as we are aware, no clear evidence for either type of process has been presented. We also consider the view that all categories of currently identified temporarily non-culturable cells are most appropriately referred to as ‘injured’ (see below) is both pertinent and in need of further attention. Finally, some authors have used the term ‘VBNC’to encompass all bacterial cells that can be detected (e.g. by microscopy) but which defy our attempts to culture them (Bloomfield et al., 1998). Clearly, this usage potentially includes temporarily non-culturable cells and cells of bacteria that have never been cultured in the laboratory. Indeed, some authors have even suggested that our failure to culture cells in both categories may be attributable to a single biochemical phenomenon (Dodd et al., 1997; Bloomfield et al., 1998).We cannot accept this latter view since many different processes have been demonstrated to underlie both temporary non-culturable states and our failure to isolate specific organisms in culture (Barer et d., 1998). Moreover, we consider that application of VBNC to ‘as yet uncultured’ bacteria adds further to the terminological confusion.

4. ‘AS YET UNCULTURED’ (AYU) BACTERIA

The sequence of discoveries and developments that led to a recognition of the extent to which we have so far failed to recover many bacterial species in culture is one of the most exciting developments in modern bacteriology (Pace, 1997). For many years the discrepancy between number of bacterial cells that could be detected by microscopy and the number of colony-forming units recoverable in samples from a given environment has been recognized by the phrase ‘the great plate count anomaly’ (Staley and Konopka, 1985).The emergence and acceptance of Woese’s 16s ribosomal RNA sequence data as the basis for the universal phylogenetic tree (‘tree of life’) (Woese, 1987)paved the way for an unusual development; a field of biological science that could measure the scale of its own ignorance. Over a period of 5 years or so, the practical foundations for the investigation of AYU bacteria were established. Two key developments, the design and use of universal primers for bacterial 16s rRNA genes that facilitated the recovery and sequencing of these genes from environmental samples (Giovannoni et al., 1990) and the synthesis of labelled rRNA-directed oligonucleotide probes whose specific binding in situ can be determined by microscopy or cytometry, underpinned this achievement (Giovannoni et ai.,1988; Delong et al., 1989).

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These methods have enabled explicit identification of AYU bacteria at both molecular and cellular levels (Amann et al., 1995). Although in practice it is difficult to differentiate between the relative contributionsof biomass and biodiversity (many AYU organisms with restricted diversity versus few organisms comprising many diverse AYU taxa), there now seems little doubt that the AYU fraction of bacterial biodiversity exceeds the cultured fraction by between one and two orders of magnitude (Wayne, et al. 1987; Pace, 1997). More recently, the capacity to determine metabolic activity and gene expression by cytological assay in cells identified by rRNA oligonucleotide probes has further extended our potential to investigate AYU bacteria (Whiteley et al., 1996; Poulsen et al., 1997; Moller et al., 1998). In the present context, consideration must be given to how the viability of AYU bacteria may be assessed and the factors that may underlie our failure to recover these organisms in culture. The general issue of viability is relatively straightforward since cells attributable to AYU bacteria must have been the progeny of cells that were viable. However, unless their potential to replicate can be explicitly demonstrated, no specific individual cell can be identified as being viable. Cytological assessments of metabolic activity, DNA content and rRNA content show that a cell may retain certain resources that are compatible with viability but, as discussed below, their correlation with replicative potential is uncertain. It should be appreciated that many of the organisms assigned AYU status may, in fact, be culturable, hence our use of the term ‘uncultured’rather than ‘unculturable’(Wayne ef al., 1987). It is well recognized that almost every attempt to recover bacteria from environmental samples leads to the isolation of novel species. It is also widely appreciated that, where isolation of bacteria that comprise a small minority of those in a particular sample is desired, powerful selective culture methods may be required. Hence isolation of some potentially readily culturable bacteria may be delayed until suitable selective methods have been developed. Finally, there are many cultured organisms in collections such as those of pharmaceutical companies that have yet to be identified. Until all the organisms in culture have had their 16s rRNA genes sequenced, we cannot be certain that organisms identified by molecular methods are even difficult to culture. Despite these cautionary points, the evidence for the existence of AYU bacteria is substantial and we must therefore consider why their isolation and culture may be difficult or even ultimately unachievable. rlllJo broad categories are considered, firstly slow or cell density-limited growth and, secondly, highly specific nutritional and/or environmental requirements. Button and his colleagues achieved a most revealing demonstration of the former category (Button et al., 1993; Schut et al., 1993). Working on marine samples from Alaska these workers used dilution cultures to obtain growth vessels that contained only one replicating bacterial unit. They hypothesized that

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marine oligotrophs might be adapted to grow at low cell densities and that their replication might not be detected by visible turbidity. They therefore elected to monitor growth by flow cytometry. Not only did they recover several isolates with mean generation times in the range 12-72 h by this approach but they also observed that the proportion of bacteria that could be considered unculturable by this method was only 40% of the total population detected. This contrasts with the 0.01-1 % range of unculturable (strictly ‘unplatable’) cells often quoted in relation to marine samples (Amann et al., 1995). It is clear that it would be very difficult to isolate cells replicating at these rates from non-oligotrophicenvironments unless suitable selective reagents can be identified. Moreover, the monitoring of growth by flow cytometry is only likely to be applied in a limited number of research laboratories. Interestingly, repeated passage of one of the isolates in this study led to its developing the capacity to form colonies on agar media. Whether this capacity was a pre-existing property of the organism, or the result of a mutation or mutations selected for in vitro remains to be established (Schut et al., 1997). The spectacular successes achieved in isolating what appear to be most of the major pathogenic bacteria affecting humans in the period from 1880 to 1920 arguably produced a sense of complacency about what could be achieved by conventional agar culture. The inclusion of blood and animal tissue extracts in media clearly provides a complex nutritional environment appropriate to many if not most medically significant bacteria. Nonetheless, there were warnings amongst the observations made during the ‘golden era of bacteriology’ that crude replication of the nutritional components present in the environment inhabited by the bacteria in question would not necessarily lead to their isolation and culture. Foremost amongst these observations is the recognition of Hansen’s bacillus, Mycobacterium leprae, which, since it was reported (Hansen, 1880), has defied all attempts at propagation in axenic culture. Interestingly, other species of the genus Mycobacteriurn provide examples of organisms whose nutritional requirements are highly exacting. These include M. paratuberculosis, which requires the mycobacterial iron-chelating agent mycobactin (Barclay and Ratledge, 1983), M. haemophilum, which requires blood, an unusual requirement for mycobacteria (Wayne and Sramek, 1992), and M. genovense (Bottger et al., 1992). The last of these examples falls into the novel category of organisms that were identified first by molecular methods and subsequently recovered in culture (Bottger et al., 1992; Coyle et al., 1992). Perhaps the most exciting case of an organism in this category is Tropheryma whippelii, the agent of the chronic human intestinal condition Whipple’s disease. Relman and associates ( 1992) identified this organism by molecular methods and, subsequently, Schoedon et al. (1997) recovered it by intracellulargrowth in macrophage cultures by addition of the cytokine interleukin 4.The organism’s requirements are evidently so specific that macrophages require a specific pattern of

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stimulation before they provide an environment capable of supporting replication of i? whippelii. These observations have stimulated renewed interest in attempts to culture M . leprae by selective macrophage stimulation (Fredricks and Relman, 1997). However, there are alternative possibilities suggested by recent work that may offer an answer to the riddle posed by this defiant bacterium (Mukamolova et al., 1998) (see below). These examples serve to illustrate growth patterns and environmental issues that may be responsible for the extent of AYU bacteria. We consider the evidence that these phenomena account for the majority of failed attempts at isolatiodculture to be substantial. Nonetheless, although we reject use of the term VBNC in this context (Barer et al., 1998; Bloomfield et al., 1998), we recognize the possibility that exposure to certain media may cause some bacterial cells to injure themselves as a result of their own metabolic processes and look forward to publication of evidence relating to this possibility in specific instances.

5. ‘NEW‘ METHODS

Postgate (Postgate, 1967, 1969, 1976) divided procedures for estimating viability into direct (culture-based) and indirect (non-culture-based) methods. While we agree with this classification, our discussion will predominantly concern indirect methods, since most recent activity has been in this field. We review four major areas of development and discuss their impact on the issues of viability and culturability. 5.1. Fluorescence Methods

While some fluorescence methods were available at the time of Postgate’s review, many new procedures have since been developed. One important factor is the development of improved instrumentation, facilitating detection and measurement of fluorescence (see below), and another is the remarkable success of the company ‘MolecularProbes’, which has popularized the use of fluorescent reagents first in eukaryotic cell biology and latterly in bacteriology. Whatever the detection system, fluorescence-based assays provide signals that can be related to known properties of the organisms tested. Just as importantly, the results can be monitored at the cellular rather than the population level. Apart from the mild cachet associated with fluorescence detection technology, the central attraction of fluorescence methods stems from their sensitivity (low, i.e. micromolar, reagent concentrations can often be used) and the fact

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that they are applicable to samples even when they or the background on which they are mounted is opaque. What do fluorescence methods measure? Essentially they should be considered as equivalent to other cytochemical or histochemical methods. All the same considerations regarding reagent access, mechanism of labelling and localization apply. Histochemical control reactions are often highly demanding but they are rarely performed in microbiological investigations. It is also important to recognize that a labelling property that is associated with replicating cells but that is absent from formaldehyde or heat-fixed cells does not enable us to conclude that the method is capable of detecting viability. We agree with McFeters et al. (1995) that the methods should be viewed as indicators of the specific aspects of cellular physiology and/or metabolism upon which the outcome of labelling is dependent. We do not propose to review systematically the fluorescence methods that have been reported to provide indirect measures of viability. We recognize that some methods have been validated as indirect measures of viability in some circumstances, for example, where cells have been exposed to defined stresses leading to loss of culturability by a limited range of mechanisms. Nonetheless, we retain the view of Postgate that indirect (including fluorescence) methods do not provide 'short cuts' (Postgate, 1976) by which viability may be determined. This does not mean that we consider fluorescence methods to be without value or that there are no situations in which they may be used as an indirect measure of viability or of likely viability. The recognition of particular activities within cells may be of significance whether or not those cells retain the capacity for further self-replication. Furthermore, where the relationship between labelling property and growth potential has been extensively validated against specific processes causing cells to lose viability (e.g. loss of membrane integrity), indirect methods may be useful. A non-exhaustive list of fluorescence methods is outlined in Table 2. 5.2. The Kogure 'Tentative Direct Microscopic Method of Counting Live Bacteria'

Somewhere en route, this admirable method (Kogure et al., 1979), which was developed to assess possible viability of uncultured bacteria in marine samples, has been redirected to the assessment of cultures rendered non-culturable in vitro (Xu et al., 1982; Roszak etal., 1984; Roszak and Colwell, 1987b; Linder and Oliver, 1989).The procedure involves amendment of samples from aquatic environments containing bacteria with low amounts of nutrient (classically, yeast extract) and the DNA gyrase inhibitor, nalidixic acid. Incubation, usually at 20 "C, leads to cell elongation without fission in a variable proportion of the

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Table 2 An overview of fluorescence and luminescence methods that have been used to assay activity or cellular integrity in bacteria Method

Example

Comment

Enzyme substrates

Fluorescein diacetate,' fluorescein digalactoside.2 ChemChrome B3

Enzyme not necessarily expressed under all physiological conditions

Redox indicators

CTC? Alamar Blue5

Results depend on endogenous and exogenous substrate and may be independent of the electron transport system

Membrane energizatiodpotential probes

Rhodamine 123: Oxano17

Controls necessary to confirm labelling or exclusion due to physiological property

Permeability probes

Propidium iodide! ethidium homodimerg

No clear cut-off, some live cells are permeant

Nucleic acid stains

Hoechst 33258/33342,1° DAP1,I'SYTO series,'*

Quantification of the target nucleic acid is dependent on its physical state

~ 0 ~ 0 1 3

FISH probes

16s rRNA-directed probes,I4 Elegant means of identifying target cells and assessing chromosomal painting15 ribosomal content

Specific ion probes

Quin 2, Fura 2, Indo I , SBFI, SPQ16

Calcium, sodium and chloride probes. Little used in bacterial studies

pH probes

BCECF,17 Calcein,l* SNARF- 1

Mainly used in physiological studies and on large cell populations

Proprietary viability

SYTOX green,19BacLight LIVEDEAD kit2'

Essentially nucleic acid stains with differential permeability for intact cells

Sources: 1 = Mor er ol. (1988), Diaper and Edwards (1994); 2 = Ikenaka ef al. (1990). Plovins er al(1994). Nwoguh er al. (1995); 3 = Diaper and Edwards (19941, Clarke and Pinder (1998); 4 = Rodriguez eta/. (1992), Bovill er al. (1994); 5 = Collins and Franzblau (1997); 6 = Bercovier er al. (1987). Kaprelyants and Kell(1992): 7 = Jepras er al. (1995). Lopezamoros et al. (1995); 8 = Gant eral. (1993); 9 = Kaneshiro era/. (1993); 10 = Davey and Kell(1996); 1 I = Hoff (1988). Kepner and Pratt (1994); 12 = Ibrahim el nl. (1997); Lebaron el al (1998); 13 = Mane eral. (1996); 14 =Amann eral. (1995). Poulsen er a / . (1995); 15 = Lanoil and Giovannoni (1997); 16 = Davey and Kell(1996), Slavik (1998); 17 = Molenaaref al. (1991); 18 =Diaper and Edwards (1994); 18 =Diaper and Edwards (1994); 19 = Roth eral. (1997): 20 = Braux er al. (1997). Decamp er nl. (1997). Jacobsen er nl. (1997), Joux er al. (1997). Rigsbee er nl. (1997). Duffy and Sheridan (1998). Vim et al. (1998).

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cells. The initial explanation for the cell elongation was that nalidixic acid prevented cell division but not cell growth. The method is particularly attractive because, apart from the added nutrient, it appears to demonstrate growth potential in a medium that retains characteristics of the natural environment of the bacteria present. Also, by inhibiting cell division, it seems to place both culturable and non-culturable bacteria on an even playing field because the former are prevented from overwhelming the latter, as would be the case with a culture-based test. Application in the types of study for which the method was originally designed and with the cautious interpretation implied by Kogure and colleagues, original title and subsequent modifications seems justified (Brayton et al., 1987; Barcina et al., 1995). However, extension of the method to characterize non-culturable cells of culturable bacteria raises some important questions. Inclusion of nalidixic acid in the incubation mixture was originally intended to prevent cells from dividing. This poses a paradox that is particularly apparent where the non-culturable cells have been produced from culturable cells in laboratory microcosms. Such cells (whether temporarily or permanently non-culturable) are supposedly not capable of division, so why is the nalidixic acid required? We suggest that, rather than simply preventing division of cells stimulated to grow by nutrient amendment, the nalidixic acid itself provides a stimulus to which some cells respond. This response is likely to be an SOS response, a well recognized effect of quinolone antimicrobial agents (Drlica and Zhao, 1997). The SOS response includes expression of SulA, a protein that interacts with the tubulin-like protein FtsZ preventing septation and resulting in filamentous growth of cells (Bi and Lutkenhaus, 1993; Walker, 1996). These observations do not resolve the paradox posed by the responses observed when the Kogure method is applied to laboratory microcosms. Central to the paradox is the question of whether the growth implied by the elongation process is a response to the quinolone, the nutrient amendment or both. In our experience, both appear essential (A. T. Newton, R. Smith and M. R. Barer, unpublished observations), although we have not been able to exclude the possibility that limited replication occurs in the absence of the quinolone. Further, if nutrient amendment is capable of producing growth in a fraction of the population, why is this not reflected by the culturability test applied at the same time? Two recognized phenomena might be invoked as alternative answers to this latter question. The first is the phenomenon of limited replication (Binnerup et al., 1993); perhaps the elongating cells are not capable of completing more than a limited number of generations, specifically, below the number that could be recognized by the simultaneously applied test of culturability or by changes in the total cell count. The limitation might be imposed by available resources, injury to cell components, such as DNA, or processes akin to those controlling maximum cell density during primary

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isolation of the marine oligotroph Sphingomonas sp. strain RB2256 (Schut et al., 1997). Alternatively, it is well recognized that most probable number (MPN; or limiting dilution broth) counts and agar plate counts may give divergent results (Kaprelyants and Kell, 1993; Kaprelyants et al., 1994; Votyakova et al., 1994).The effort required to conduct MPN counts has limited their use and we simply do not know whether such counts, performed in the same medium as the Kogure test (without the quinolone), would give figures comparable to the Kogure result. All of these possibilities are amenable to experimental assessment, as are our speculations concerning the SOS response. In recommending that these issues be addressed, we also urge attention to statistical issues. Few publications clearly state their criteria for assigning cells observed in the Kogure test to positive or negative categories. It is not adequate to make such assignments on subjective criteria unless control and stimulated preparations are counted in a blinded fashion. Moreover, if a criterion such as doubling in cell length is used, this is only meaningful by reference to a control population. For example if, in a population where the distribution of cell lengths is normal, the standard deviation of the cell length in the control population is half the mean cell length, at least 1.25% of the control population will meet the doubling criterion. This issue becomes particularly important when the elongating population comprises a small proportion of the total cell count. Kogure-positive cells are often reported at less than 1% of the total cell count. To achieve counts with statistical validity, the positive cells would have to be longer than the control population mean by at least three control population standard deviations (and more as the fraction of responding cells becomes smaller). Finally, these considerations raise the question of what the appropriate control should be for the Kogure test when it is applied to laboratory microcosms. Should we use unamended samples or samples treated with either nutrient or nalidixic acid alone? 5.3. Molecular Approaches

The development of our understanding of bacteria at the molecular level and of techniques for genetic manipulation has provided some remarkable and powerful techniques for the interrogation of cell functions. In studies that essentially extend those which underpinned recognition of AYU bacteria, many workers have addressed the two questions, can we detect molecular processes in non-culturablebacteria and are they related to viability? Two types of assay have been used: detection of specific messenger RNA (mRNA) by combined reverse transcription and the polymerase chain reaction (RT-PCR) (Engstrand et al., 1992; Khan et al., 1996; Yamazaki et al., 1996; Felske et al., 1997; Rayner et al., 1998; Sheridan et al., 1998), and detection of cellular rRNA by in situ hybridization (ISH) (Delong et al., 1989; Lee et al.,

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1993; Amann et al., 1995). The generally short half-life of mRNA in bacteria makes this a desirable target and the argument that cells containing such short-lived molecules must be actively making them seems coherent. However, it is well known that the half-lives of certain mRNA species are substantially extended in certain physiological states, notably during starvation (Albertson and Nystrom, 1994; Marouga and Kjelleberg, 1996). Furthermore, most studies that have used RT-PCR to assess ‘viability’have applied the reaction at the population level, and this means that stringent precautions must be taken to exclude possible contributions from a sub-population of culturable cells that were present at or below the detection limit of the culture method applied. The demanding nature of the RT-PCR reaction and the culturability assays means that these two procedures are rarely combined in a statistically adequate fashion. The continuing improvement of in situ RT-PCR reactions applied to bacterial systems is a promising development that should allow the presence of specific transcripts to be assigned at the cellular level, thereby facilitating specific recognition of transcripts in non-culturable cells (Tolker-Nielsen et ul., 1998). As noted above, oligonucleotide ISH reactions directed at 16s or 23s rRNA molecules can be used to study non-culturable cells of both culturable and AYU bacteria. Although rRNA content is related to growth rate (Delong et ul., 1989; Lee et al., 1993; Poulsen et al., 1995) and has been observed to decline in non-growing cells and indeed in non-culturable cells, the minimum concentration of rRNA compatible with viability is not known. Clearly, the detection of rRNA indicates some potential for protein synthesis; however, rRNA is relatively stable and the relationship to recent translation is even less clear than in the case of mRNA. The recent demonstration that the pre-rRNA molecules (partially processed transcripts of the rDNA operon) can be detected by fluorescence in situ hybridization (FISH) (Licht et al., 1998) provides another exciting avenue through which dynamic molecular processes can be interrogated at the cellular level in bacteria. An alternative approach for detecting transcriptional and translational activity in non-culturable cells is to use reporter genes. Here, a gene whose expression can readily be detected is introduced into, and maintained in, a culturable cell population. The reporter gene is either used to monitor expression of a particular gene or operon as a transcriptional or a translational fusion. The cells from the cultured population are then rendered non-culturable and expression of the reporter molecule monitored biochemically or at the cytological level. Where the objective is to monitor expression of a specific gene in nonculturable cells, careful controls are necessary to distinguish expression before and after transition to non-culturability. Induced expression relating to a specific promoter offers clear advantages in this respect because application of the inducing signal can be delayed until the target cells are non-culturable. Selected examples of reporter gene-based studies relevant to these issues are given in Table 3.

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Table 3 Examples of the use of reporter gene systems to assess bacterial activity and integrity Reporter

Use

lac2

Activity in non-culturablecells Nwoguh et al. (1995)

Green fluorescent protein (Gfp)

Marking of cells and evidence of protein synthesis

Dhandayuthapani et al. ( 1 995), Kremer et al. ( 1 995)

Red-shifted variants of Gfp

High throughout screening assays in M.tuberculosis

Collins et al. ( 1 998)

Unstable variants of Gfp

To differentiate recent translation from persisting protein

Andersen et al. (1998)

Vibrio harveyi

Marking of cells Activity assays

Aminhanjani et al. (l993), Ferguson et al. (1995). Loessner et al. (1996). Aldsworth et al. (1998)

Reporter bacteriphages for detection and activity assay

Jacobs et al. (1993), Sarkis et al. ( 1995)

L d B Firefly luciferase

References

TWO further approaches that may be considered within the molecular genetic category should be mentioned here. These are detection of gene transfer involving non-culturable cells and the use of bacteriophages. One interesting report indicates that plasmids may be transferable from culturable to non-culturable cells (Arana et al., 1997) and the development of plaqueforming bacteriophages as a rapid means of detecting specific bacteria (Wilson et al., 1997; Stewart et a/.,1998) raises the possibility that these viruses might be able to multiply in non-culturable cells of the target organism. Further investigation of these approaches is necessary before their value can be assessed. 5.4. Developments in Instrumentation

In the present context, developments in instrumentation have either extended the range of direct and/or indirect methods used to assess activity at cellular or population levels. In this section, we assess the impact that the availability of these instruments has had on studies concerned with bacterial viability and culturability. Flow cytometry (FCM), which was developed in the 1970s, has been used in both direct and indirect assays (Davey and Kell, 1996).The method depends

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on passing a stream of single cells past a light source (often a laser) and detecting both light-scattering and fluorescence with strategically placed photomultiplier tubes. It allows for the rapid assessment of the light scattering properties and fluorescence (up to three excitation and emission wavelengths simultaneously) of cell suspensions at flow rates around 103 cells per second. This clearly facilitates the analysis of very large cell populations and the simultaneous recording of up to four distinct cellular properties. The use of FCM to detect growth at times well before change in biomass would have been detected by macrocolony formation or increase in broth turbidity has been used to considerable effect (Button et af.,1993). Moreover, the availability of these instruments has undoubtedly assisted development of new fluorescent or fluorogenic reagents by increasing the market for such products. FCM functions optimally with relatively high cell density suspensions that are free from particles that may either block the flow or generate confusing signals. A particularly valuable addition to flow cytometry is fluorescence-activated cell sorting (FACS), which can be used to separate populations of cells with specific signal patterns (Davey and Kell, 1996). An interesting recent development, related to FCM, is solid-phase cytometry (Mignon-Godefroy et al., 1997). Here the test material is accumulated on a sample filter, fluorescently labelled then scanned with a narrow laser beam; emissions are again detected by a photomultiplier.The potential advantages of this approach include easier processing of larger sample volumes than FCM, the ability to tolerate more particulate material, the capacity to cross-check specific signals by microscopy and, in some cases, the capacity to place the sample filters on agar plates and obtain colonial growth that can be specifically related to individual signals. The technology is particularly valuable for the detection and confirmation of rare events. It clearly has much to offer in the present context and we await its further evaluation with interest. Three lines of development in fluorescence microscopy have augmented the range of available instrumentation: charged coupled device (CCD) cameras (particularly where the detector is cooled) have enhanced the sensitivity of cytological assays (Shotton, 1993); digital image analysis systems have enabled objective and quantitative assessments of the results (Whiteley et af., 1998); and the development of convolutional deblurring systems (Shaw, 1994) and confocal microscopes (Pawley, 1995) have allowed analysis of thick samples (10-300 pm) in three dimensions. The last of these developments is particularly important because it enables bacteria to be analysed under circumstances where their spatial interrelationships with other features in their natural environments, including other microorganisms, have not been unduly disrupted (James et al., 1995;Manz et al., 1995; Neef et al., 1996; Christensen et af., 1998). These situations include biofilms and flocks or other consortia of organisms (Amann et al., 1996; Neef et al., 1996). Microscopy has predominantly been used in indirect assessments of

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viability and the microcolony assays used by Postgate and Quesnel and their colleagues (Postgate, 1967;Al-Qudah et al., 1983) have not, with some notable exceptions (Rodrigues and Kroll, 1988; Hojberg et al., 1997), been used extensively in recent years. Many instruments have been developed with the objective of detecting growth earlier than is possible by conventional colony or turbidity methods and the reader is referred to recent reviews for a discussion of their relative merits (Swaminathan and Feng, 1994; Hobson et al., 1996). The discussion above concerning limited cell replication raises an interesting point in this context (and in relation to microcolony assays). What is the minimum number of generations that can be considered indicative of viability? 5.5. What Do the 'New' Methods Tell Us?

A theme we have pursued throughout this section has been our ability to classify all new methods into direct and indirect assessments of viability. We see no reason to deviate from the framework established by Postgate and hold that, irrespective of their sophistication, the newly developed indirect methods are not reliable means of determining viability in all circumstances.We recognize that to some this view may seem harsh and offer further discussion in two areas to support our view. The first area concerns the significance of negative reactions obtained in indirect assays. Where these assays depend on reagent delivery into or extraction of indicator molecules from non-culturable cells, there are no reliable means by which we can be sure that these key aspects of the assay have performed successfully. Such permeability issues can be addressed in growing cells. However, it is self-evident that the structure of the cell envelope changes during sporulation, and several workers have noted changes in cell structure and lipid composition during studies in non-culturable forms of culturable bacteria (Rollins and Colwell, 1986; Linder and Oliver, 1989; Colwell and Huq, 1994; Hazeleger et al., 1995). These observations make it difficult to be sure that reagent access is adequate or that extraction of the molecule to be analysed has been effective. Moreover, why should temporarily non-culturable cells be active rather than dormant (cf. Table 1 and Kell et al., 1998)? Dormant cells of M. luteus and bacterial spores, respectively, show reduced activity (Kaprelyants and Kell, 1993) or no activity (Coney, R. P. and Barer, M. R., unpublished observations) in rhodamine-123 accumulation assays. Why should demonstrable aspects of cellular activity continue in temporarily nonculturable bacteria? In sporulating bacteria, performing the assay after a germinant has been added to the sample can, to some extent, circumvent this problem. However, in the case of non-culturable bacteria that are putatively temporarily so, we have no idea what the appropriate germinant might be.

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These issues undermine our confidence in activity assays and assays aimed at determining the content (e.g. DNA and RNA) of non-culturable cells. We also wish to expand briefly on the potential significance of assays which demonstrate that recent transcription and/or translation must have taken place in non-culturable cells (see Section 5.3). Although such demonstrations may seem a plausible basis on which to consider a cell viable and the processes involved are undoubtedly a necessary aspect of viability, they are not in themselves sufficient for cell replication. The same argument may be applied to a positive result in the Kogure test, although the processes involved there are not clearly established. This distinction between aspects of cellular composition and activity that are necessary for and those that are sufficient for viability provide a clear view of the problems faced by indirect assays. If a cell can be shown to contain the same amount of DNA as a cell of the same strain that was subsequently cultured, we still do not know whether it has the DNA it needs for replication. It has what appears to be sufficient DNA but it may not have the necessary DNA. Even the quantitative issues cannot readily be resolved. We simply do not know what the minimum set of intact processes required for viability may be, let alone have the capacity to demonstrate them all in one assay. Moreover, it seems likely that lesions or deficiencies affecting any one of these processes might lead to non-culturability and potential reasons for nonculturability are, therefore, legion. We may learn more about these issues from minimum genome programmes (Itaya, 1995). These arguments may also be inverted to pose the question, ‘what features may we expect in a cell that has lost viability as a result of one particular lesion or deficiency?’. There seems no obvious reason why such a cell should go to the trouble of dismantling its physiological functions simply to assist microbiologists in differentiating between viable and non-viable cells. Of course, cellular autolysis may provide essential nutrients to other bacteria in the same community. Conversely, maintenance of cell integrity in non-viable cells may also provide certain advantages to a bacterial community because such cells may continue to participate in nutrient cycling reactions or production of secondary metabolites that inhibit other organisms. Loss of the capacity to replicate does not mean that an organism ceases to have a useful function in its community (consider the historical role of eunuchs).

6. FACTORS INFLUENCING THE OUTCOME OF

CULTURABILITY TESTS

Culturability tests are integral to virtually all aspects of bacteriology. From the determination of inhibitory action in identification and susceptibility tests to monitoring the microbial content of industrial systems, environmental samples

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and medical specimens, what can be grown and the number of independent colony- or turbidity-forming units present constitute the benchmarks against which practical decisions are taken. The value of culture as a basis for such decisions has been undermined by the developmentsoutlined above. Moreover, the desirability of replacing culture by molecular methods for diagnostic work presents additional challenges. Just as we have learned to temper our reactions to the detection of microbes by microscopy by comparing such results with those obtained by culture, it seems likely that we shall need more sophisticated molecular detection systems (e.g. detection of specific mRNA molecules) that are more explicitly and practically instructive than detection of genomic DNA. Where the influence of an organism on its environment is dependent on its potential for replication (viability) any new indicator will have to be calibrated against culturability. Thus, for the foreseeable future, it will be necessary to understand the factors that can cause a viable cell to be temporarily nonculturable. 6.1. Injury and Recovery

Injury can be caused by chemical or physical agents and may be lethal (render cells non-viable) or sublethal; the latter may affect subsequent growth characteristics. Where the processes have been studied, some information concerning the molecular species that have been damaged is available. Thus, for example, injury to the cell envelope (Ray et al., 1976), proteins (Elkest and Marth, 1992; Nystrom, 1998) and DNA (Walker, 1996) are all recognized, and recovery is seen as the processes by which those damaged molecules are repaired or replaced. The SOS response discussed above, was first recognized as a response to DNA damage (Defais et al., 1971) and arrests cell division (hence culturability) until SulA-mediated inhibition of FtsZ (septation) ceases. A large section of the information on injury and repair processes in bacteria relates to DNA damage and is concerned with the potential of the repair processes to introduce genetic change (Quillardet and Hofnung, 1993). Relatively few investigations have studied the interactions between sublethal DNA damage and culturability. Perhaps the most relevant recent work here is that of Mackey and Seymour (1987) who investigated the recovery of DNA repair mutants of Escherichiu coli after heat-induced damage. They found sensitivity to heating at 52 "C was increased in recA, recB and pol A mutants, but not in uvrA, uvrB or recF mutants. Interestingly, they observed specific immediate post-exposure conditions that could either increase or decrease the colony counts obtained in their polA mutant. The authors suggested that their treatment rendered the target cells sensitive to hydrogen peroxide in the culture medium by inactivating inducible catalase/peroxidase. Classically,injury has been recognized by failure of an organism to grow on

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a selective medium that normally supports its growth whilst maintaining its ability to grow on a non-selective medium (Allen et al., 1952; Mossel and Ratto, 1970; Ray et al., 1972; Speck et al., 1975; Hackney et al., 1979). However, damage can also produce cells that cannot grow at all until the recovery (repair) process has taken place (Walker, 1996; Dukan et al., 1997). Thus, while the selectivehon-selective medium test provides a useful generic approach to detect injured cells for experimental studies (LeChevallier et al., 1985; Singh et al., 1986), it cannot be considered universal. Another approach to identifying injured cells has been to compare colony counts on media with and without additions that reduce oxidative stress. In the 1970s, it was recognized that, in some cases, addition of reagents such as pyruvate or catalase to the recovery medium could give higher colony counts relating to certain stressed bacterial populations than unsupplemented media (Martin et al., 1976; Brewer et al., 1977; Flowers et al., 1977; Mossel et al., 1980a). Like the selectivehon-selective medium approach, this method can be used to categorize cells as injured (Arana et al., 1992) but does not provide a means of detecting all injured cells (Mossel et al., 1980a). In some cases, peroxide in the enumeration medium may be acting as a selective reagent (Mackey and Seymour, 1987) whereas in others peroxide toxicity may occur prior to plating (Arana et al., 1992). Injury can also be recognized by demonstrating the necessity for a recovery phase before cells will grow on under conditions used for selective isolation. This type of phenomenon has been demonstrated with respect to the ability of organisms to grow at relatively high temperatures (Mossel et al., 1980b; Humphrey, 1986) and on selective media (Speck et al., 1975). The noxious agent in injury is normally thought to be exogenous. However, the possibility has been recognized that damaging molecular species such as oxygen radicals may be produced endogenously by bacteria that have not adapted to a specific medium or that are not capable of doing so (see Section 6.4). 6.2. Ageing

Ageing in bacteria may be defined as the process that occurs when growth ceases. At some point, this presumably leads to loss of replication potential. The effects of this process may be mitigated by turnover, but it seems reasonable to assume that accumulation of damage and decline in the resources available to repair that damage are constant pressures on the viability of nongrowing bacteria. Nystriim (1998) has recently proposed a scheme that identifies several molecular processes at the centre of the ageing process in bacteria. The scheme concentrates on proteins as the key molecules that determine whether a cell

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retains the capacity for replication and identifies oxidative stress as the principal detrimental influence. Hence those activities that can reverse or oppose the effects of oxidation, particularly on sulfur groups, appear to maintain culturability, essentially by retarding the ageing process. The molecules responsible for reversal of damage include heat-shock proteins, L-isoaspartyl protein methyl transferase, peptide methionine sulphoxide reductase and glutathione reductase, while catalase and superoxide dismutase actively oppose damage. The ArcNArcB response regulator/sensorpair appears to control many of the elements of this system. ArcA represses genes encoding dehydrogenases of the flavoprotein class, several enzymes of the tricarboxylic acid (TCA) cycle and the cytochrome o-type oxidase complex while other regulators, including OxyR, SoxRS, RpoS and RpoH, up-regulate the expression of elements that reverse or oppose the effects of oxidant stress. The net effect is to reduce the production of oxygen radicals and to protect cells from their deleterious effects. The scheme proposed by Nystrom (1998) provides an excellent platform from which many hypotheses concerning the survival of growth-arrestedcells may be tested. For example, the bulk rate of protein synthesis and turnover in growth-arrested cells should have discernible effects on survival. However, in the present context, we are concerned with damage to polypeptides that are required for the cell or population of cells to return to a growingheplicating state, and we are faced with the question of how many distinct targets in the proteome can be involved. A priori it seems likely that there could be many critical targets (e.g. RNA polymerase, adenylate kinase, FtsZ) or combinations thereof, whose damage might limit (see Section 6.1) or abolish a cell’s replication potential. Ultimately, it would be desirable to identify all of these putative targets, although the technical difficultiesinvolved would be substantial. A starting point might be to ask whether the evidence points to a restricted range of dominant targets or to a more diverse set. It seems unlikely that polypeptides are the only molecular targets underpinning the ageing process. In a given environment, cellular nucleic acids, lipids and carbohydrates all, presumably, accumulate damage that has the potential to affect culturability. Clearly, the impact of these lesions depends on whether the cell concerned has retained repair andor turnover functions, which would, of course, be determined by its functional protein complement. Moreover, these non-protein organic molecules appear to be less sensitive to oxidative modification and their damage has been studied extensively in relation to specific noxious influences (e.g. antibiotics, disinfectants, radiation, heat). Another way to look at ageing in bacteria is to consider the age of individual cellular components. Even in replicating cells, all components are not of equal age. For example, semi-conservative replication of DNA means that one strand of the genomic DNA was acquired from the parental cell and there is a

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one in four chance that the strand concerned came from the grandparent. Cell wall material also passes on from generation to generation. While the septa1 material is newly synthesized, the poles contain material that was synthesized in previous generations (Clarke-Sturman et al., 1989). It is therefore possible that a given cell may have certain components, such as single nucleic acid strands, ribosomes and peptidogylcan, that are several generations old. The critical and largely unanswerable question here is the degree to which partition of such aged components into a particular cell may compromize its culturability. However, although these processes have the potential to produce some degree of replicative senescence, the effect is not uniform on the population of a replicating culture. At one extreme it may be imagined that a given strand of genomic DNA has a finite ‘life span’ of say 12 h when its environment is that of a steadily replicating cell. If the host organism replicates 20 times in this period, then one cell in lo6 will contain this aged molecule after 12 h. The frequency at which cells are affected by receipt of old components can therefore be seen as a function of the life span of the component, its rate of turnover and the rate of cell replication. In this context, replication itself can be seen as a way of avoiding the ageing process and confining its effects to a minority of cells. 6.3. Adaptation and Differentiation

It is clear that a simple growinghon-growing two-state description of bacteria, which dominated many aspects of practical bacteriology in the past, is not adequate to describe the different ways in which these organisms behave. All the environmental signals that a bacterial culture is capable of sensing alter the profile of genes transcribed and messages translated by that culture (VanBogelen et al., 1997). In some cases, particular signals elicit a programme of successive changes in gene expression (Kjelleberg et al., 1993). By convention, when such a programme leads to morphological changes that can be recognized by light microscopy, the process is called differentiation.* It is quite clear that differentiation into forms such as spores can alter culturability. This can be quantitative by changing the lag phase (effectively by adding the time taken for germination and outgrowth) or qualitative by restricting the range of media that support growth of the organism to those that contain the required germinants. The critical question for this discussion is whether some non-differentiating organisms are capable of adaptive responses that affect either or both aspects of culturability. These issues have been highlighted in a recent review in which the authors consider whether the

* The distinction is somewhat arbitrary and we would prefer to use the terms morphological and physiologicallmetabolic differentiation. Nonetheless, we retain the conventional usage here.

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responses of bacterial cells, which were demonstrated to be temporarily nonculturable (or NIC), are best classified as adaptation or injury (Kell et af., 1998). Two well-studied systems provide a focus for these considerations: the effect of cold storage on Vibrio vulnificus and dormancy in extended stationary phase in Micrococcus futeus. The I! vulni$cus studies published predominantly by Oliver and his associates seem to provide a particularly promising avenue through which a genetic basis for temporal non-culturability might be determined. Exposure of this organism to temperatures around 4 "C is associated with a decline in culturability without cell lysis. Hence, large numbers of non-culturable cells are produced over periods ranging from days to several weeks depending on the state of the inoculum at the time of temperature downshift and the maintenance environment (Oliver, 1995). On several occasions, resuscitation of these non-culturable cells has been reported following temperature upshift (Nilsson et al., 1991; Oliver and Bockian, 1995; Oliver et af., 1995; Whitesides and Oliver, 1997; Warner and Oliver, 1998). The association of these temperature shifts with changes in culturabilty indicates that environmental signals known to elicit adaptive responses, the coldand heat-shock responses, may, respectively, cause cells to become NIC and subsequently to resuscitate. Although it is attractive to speculate that cells may 'elect' to become NIC as part of the cold-shock response (McGovern and Oliver, 1995; Panoff et a f . , 1998), we are not aware of any evidence that expression of genes within the cold-shock regulon of I! vulnificus cause cells to become either temporarily or permanently non-culturable. The I! vulnificus story is complicated by data indicating that cold-induced injury plays a significant role in loss of culturability and that a fraction of the injured population may retain the potential to resuscitate presumably through their capacity for repair (Weichart and Kjelleberg, 1996;Weichart et al., 1997). Moreover, some concerns have been expressed about the capacity of the culture methods applied in the earlier studies to distinguish between resuscitation and regrowth (Weichart et af., 1992) and a few of these concerns remain (Kell et af., 1998). Nonetheless, work on I! vulnificus holds out the clearest possibilities for linking the established field of adaptive responses in bacteria with the VBNC hypothesis. The extended stationary phase phenomena studied in M. futeus by Kaprelyants, Kell and their colleagues provides an example of a well-studied system in which temporary non-culturability is associated with dormancy as defined operationally in Table 1. Maintenance of stationary-phase M. futeus cultures at room temperature for several months leads to production of large numbers of non-culturable cells. These showed substantially reduced capacity to take up the membrane energization-sensitivedye rhodamine-123 (the test of dormancy in these experiments) compared with early stationary- or exponential-phase cells (Kaprelyants and Kell, 1993). Further studies demonstrated that

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temporarily non-culturable cells could be resuscitated in the presence of supernatants from growing M. luteus cultures (Kaprelyants et al., 1994, 1996). Critically, the use of most probable number cultures and penicillin lysis in these experiments excluded regrowth as a likely explanation for the claimed resuscitation events. The influence of culturable cells on NIC cells was further elucidated (Votyakova et al., 1994) and the approach has recently led to the identification of a 17 kDa protein exported by M. luteus that is responsible for resuscitation (Mukamolova et al., 1998). As the production of non-culturable cells in the M.luteus studies is a slow process compared with the phenomena observed in K vuln@cus, it seems less likely that an adaptive response is involved in the sense of a programme of gene expression which leads to the development of NIC cells. However, the changes in gene expression that occur in stationary phase have been studied extensively (Kolter et al., 1993; Hengge-Aronis, 1996; Nystrom, 1998) and it remains possible that the development of M. luteus cells that are both NIC and dormant could represent one aspect of this adaptive response. Interestingly, there is also evidence that NIC M. luteus cells are injured and that a repair process takes place. Prior to resuscitation, many dormant cells are permeant to the fluorescent DNA stain PO-PRO-3 and resuscitation is associated with restoration of the membrane barrier to this reagent (Votyakova et al., 1994; Kaprelyants et al., 1996). Since these observations favour damage rather than a specific adaptive response as the cause for declining culturability in the M . luteus studies, there seems little incentive to search for genes that might actively promote transition to the NIC state. In contrast, the recent description of the 17 kDa resuscitation promoting factor (Rpf) holds out strong prospects for identifying genes whose expression is regulated by this ‘bacterial cytokine’ (Mukamolova et al., 1998). 6.4. Substrate-accelerated Death and Other Forms of Metabolic Self-destruction

In this and the next section we consider processes intrinsic to the cell population under investigation that may, when stimulated, lead to a reduction in culturable cell numbers. These processes are very difficult to take into account when performing culturability tests because their importance has only been demonstrated in a limited range of systems. Postgate and colleagues described the phenomenon of substrate-accelerated death (Dawes, 1976). They observed that, when cultures of Klebsiella aerogenes were grown to stationary phase by specific substrate limitation then maintained in non-nutrient media containing that substrate, widely divergent values were obtained for culturability on recovery media supplemented with or without the ‘traumatic’ (sic) substrate (Postgate and Hunter, 1963, 1964;

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Calcott and Postgate, 1972). Their culturability (viability) test was a slideculture-based microcolony assay and they found that the specific substrate exhausted cultures yielded a significantly higher percentage of colony-forming cells on medium without the traumatic substrate compared with medium with this substrate. Thus, in the case of lactose exhaustion, counts on lactose-containing medium could be brought up to the same levels obtained on lactose-free medium by inclusion of cyclic AMP (CAMP)in the lactose-containing recovery medium (Calcott and Postgate, 1972). Moreover, cells treated with the traumatic substrate had low levels of cAMP (Calcott et al., 1972) and these may have been attributable to phosphodiesterase activity (Calcott and Calvert, 1981). Although it was clear that CAMP-dependent processes such as genes regulated by the cognate CRP (CAMPreceptor protein) protein and catabolite repression were involved, neither the mechanism of ‘death’nor the protective effect of CAMPhave been explained. Although phenomena associated with substrate-accelerated death have been demonstrated in Klebsiella, Escherichia, Streptococcus, Azotobacter, Arthrobacter and Mycobacteriu (Calcott and Calvert, 198 l), the overall importance of these phenomena has not been established. Substrate-accelerated death could account for underestimates of viability in any system in which cells are exposed to the original limiting nutrient in the recovery medium. This issue can be readily addressed in laboratory experiments but clearly presents a problem for environmental studies where the limiting nutrient is unlikely to be known. As pointed out by Dawes (1976), there are adjustments that could be made to recovery media that might reduce this problem but, as far as we are aware, neither these nor the overall impact of substrate-accelerated death on recovery of bacteria from environmental samples have been investigated systematically. The advances in our understanding of cAMP in prokaryotes (Botsford and Harman, 1992) and in metabolic control at the molecular level combined with the resurgence of interest in bacterial viability indicate that the time is ripe for a re-investigation of substrate-accelerated death. Recently, it has been suggested that VBNC phenomena might be explained on the basis of a metabolic imbalance that leads to overproduction of oxygen radicals in relation to the source cell’s capacity to deal with these potentially lethal molecular species (Dodd et al., 1997; Bloomfield et al., 1998). Although there are many attractive aspects to this proposal as an explanation for discrepancies between active cell numbers and those that can produce colonies, we and others have been critical of the formulation of the hypothesis (Barer et al., 1998). The principal reasons for this are the authors’ implication that VBNC phenomena can be considered unitary in their origin and their use of the term ‘suicide’.As we note above, and quite apart from the contradictions of the term VBNC, so many different processes that lead to the production of nonculturable cells have been brought under its umbrella that we do not believe the

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term can have any useful meaning in relation to the specific processes discussed by these authors. Moreover, we do not favour the use of the term ‘suicide’ in this context because there are mechanisms that have been defined at the molecular level that can be legitimately described by this term (see Section 6.5). These points aside, there is circumstantial evidence for the self-destructive mechanism proposed (Aldsworth et al., 1998), although the degree to which it can be distinguished from the catalase protection phenomena described in Section 6.1 and specifically assigned to oxidative damage remains to be established. 6.5. Lysogenic Bacteriophages and Toxin-Antitoxin Systems

These two elements -the hoWsoc programmed cell death system is an example of the latter (Gerdes et al., 1997) - both have the potential to influence the outcome of a culturability test. They are considered together here because they represent fairly well characterized molecular processes that can lead to a sudden fall in culturability in response to specific stimuli. Moreover, the balance of selective pressures that leads to their maintenance within a bacterial population indicates that they may confer some survival advantage on the host cell. In the case of bacteriophages, this may be in the form of genes such as ‘virulence’ determinants whose expression may be advantageous in the life cycle of the host bacterium. Although it seems self-evident that populations of bacteria carrying lysogenic bacteriophages have the potential for rapid loss of culturability when phage production is induced, there is little information on the influence this potential has in practice. Given the potential for oxidative stress at the time of plating bacteria onto agar and the capacity for such stress to induce DNA damage, we speculate that, in some cases, low colony counts might result from SOS response-related induction of bacteriophage. The frequent recognition of prophages by the genome-sequencing projects (Blamer et al., 1997; Kunst et al., 1997; Cole et al., 1998) makes the potential for phagemediated lysis at the time of plating extensive. In contrast, the toxin-antitoxin systems have generally been identified as plasmid maintenance determinants and have been employed to this end in biotechnological applications (Pecota et al., 1997). While it is straightforward to understand why a host bacterium maintains a plasmid-encoded toxin-antitoxin system, the presence of chromosomal homologues of these systems indicates that there may be other selective pressures involved in their maintenance. For example, the capacity for cells to self-destruct may confer a survival advantage on the organism at the population level, particularly when the population is large and confronted with starvation (Aizenman et al., 1996;

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Nystrom, 1998). In this context it does seem legitimate to use the term ‘suicide’ because the process is encoded by host genes and seems to represent an evolved response to environmental circumstances. We contend that this contrasts with the metabolic self-destruction processes (i.e. substrate-accelerated death, see Section 6.4) that result from failure to adapt to a new environment. Bacterial toxin-antitoxin systems are characterized by the production of a stable toxin and an unstable antitoxin. They fall into two groups, the proteic systems (Jensen and Gerdes, 1995), in which toxin-antitoxin interactions occur at the protein level, and those in which translation of the toxin mRNA is regulated by antisense RNA (Gerdes et al., 1997). In the latter case the relative instability of the antisense (antitoxin) messenger provides the incentive for its continued transcription rather than direct neutralization of the active toxin by an unstable polypeptide. From the perspective of this discussion, three very interesting proteic ‘suicide’ systems have been identified in E. coli. Firstly, the chromosomal chpA locus (also designated rnazEF) is located just downstream of the relA gene. Its transcription is repressed by ppGpp and amino-acid starvation (Aizenman et al., 1996) and can therefore be expected to result in an excess of toxin (Nystrom, 1998). Secondly, the delayed relaxed phenotype, which includes poor recovery after starvation, associated with relB mutants has recently been shown to involve a newly identified toxin-antitoxin system encoded by the chromosomal relBEF operon. Thirdly, the ccd system of the F plasmid encodes the CcdB toxin which binds to the GyrA subunit of DNA gyrase by a mechanism that is similar to quinolones. The CcdB toxin is also a powerful inducer of the SOS response (Couturier et al., 1998)’and its expression and neutralization presumably influence the processes affecting activity and culturability assays discussed above (see Sections 5.2 and 6.1). The molecular target of toxin action has only been identified in the case of CcdB and two other systems, and the phenotype of the cells at the time when culturability is lost is essentially unknown. Moreover, the recognition that toxin action may sometimes be reversible (Jensen and Gerdes, 1995)raises the possibility that cells may be rendered temporarily non-culturable by the action of some toxins belonging to these toxin-antitoxin gene families. The systems discussed in this section are primarily of concern in the present context inasmuch as they may affect culturability and activity assays at the time of sampling. It is clear that they can have a substantialeffect on cell integrity and replication, although very little is known about their influence in practice. 6.6. Cell-to-cell Communication (Quorum Sensing)

This topical subject has been addressed in several recent reviews (Fuqua et al., 1996; Swift etal., 1996a,b; Gray, 1997; Kleerebezem et al., 1997) and will not

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be covered in detail here. However, the proposal that bacteria may need to communicate with each other for growth (Kaprelyants and Kell, 1996) is clearly relevant to this review. It is now clear that many aspects of bacterial physiology are profoundly influenced by potent autocrine molecular signals. In Gram-positive bacteria, post-translationally processed peptides have been the dominant molecular family identified (Kleerebezem et al., 1997), while the N-acyl homoserine lactones appear to be the key extracellularcompounds in many Gram-negative bacteria (Swift et al., 1996a,b). Signalling has been shown to be involved in processes as diverse as competence induction (Kleerebezem et al., 1997), luminescence (Williams et al., 1992) and virulence (Pearson et al., 1997). Here we are concerned with the effect that the concentration of a particular signal (or signal antagonist) may have on culturability assays. The central dogma of those that perform colony and MPN counts has been that a viable individual cell has the independent capacity to replicate to discernible levels when placed in an appropriate nutritious medium. Kaprelyants and Kell challenge this view by presenting evidence that counts of culturable bacteria maintained in extended stationary-phasecultures can be enhanced by several orders of magnitude in the presence of conditioned media containing putative communication molecules (pheromones). Subsequently, this group has characterized one of the molecules in the conditioned medium as a bacterial cytokine, Rpf (see Section 6.3), and it should now be possible to determine the basis for its biological activity. A search for rpfhomologues in other bacteria revealed that related genes appear to be present in mycobacteria (notably the pathogenic species M . tuberculosis and M. leprae) and in several other high G+C ratio Gram-positive bacteria but not in other bacteria for which the cornplete genome sequence was available (Mukamolova et al., 1998). While these findings have exciting implications for the cultivation of mycobacteria and for the extended latent phase of clinical tuberculosis, the general question of whether rpfis just one example of an essential gene contributing to the growth and replication of all bacteria must be addressed. At present there is little evidence to support the view that Gram-negative and low G+C Gram-positive bacteria have Rpf-like systems. However, there are several experimental systems in which communication clearly influences the length of the lag phase or the rate of growth (Kaprelyants and Kell, 1996). Conversely, the presence of autocrine inhibitory or killer molecules has also been inferred in a number of studies (Weichart et al., 1992; Zambrano and Kolter, 1993; Barrow et al., 1996; Zhang-Barber et al., 1997). These factors make it difficult to decide on conditions under which to perform culture tests. Signalling molecules may be present at the time of sampling and subsequently they may be disrupted by or diluted out by the test procedure. Moreover, conditions of the test procedure may influence production of signalling molecules. However limited or influential cell signalling phenomena are on the

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outcome of culturability assays, this particular Pandora’s box is now open and signalling as a potential source of bias must now be taken into account. Clearly ,all standard dilution assays such as colony and MPN counts do not provide cells with the same concentration of signalling molecules at each dilution level. The challenge is to devise culturability tests that control the constellation of signalling molecules available to the test population and to do so in a manner that enables consistent determinations. In one interesting study, Bogosian and colleagues (1998) attempted to account for these difficulties by providing equal access to the putative growth-supporting pheromones of immediately culturable cells in a mixed-culture assay system. In fact, they were unable to detect any influence attributable to signalling molecules and, in particular, found no evidence for transition from NIC to culturable states in the Enterobacteriaceaetested. It is worth noting that most signalling phenomena have been recognized between cells belonging to a single species or strain. There is no theoretical bar to cross-talk between species in microbial consortia. Indeed it would be surprising, given the relatively restricted range of molecules so far identified in this role, if more examples of cross-talk did not emerge in the future (Bassler et al., 1997; Dunphy et al., 1997). Finally, direct interference with signalling processes has recently been shown to affect the survival capacity of carbon-starved bacteria (Srinivasan et al., 1998). The antagonistic molecules were isolated from marine plants and appear to prevent establishment of biofilm growth on leaf surfaces. Clearly, we have some way to go before we have identified, let alone controlled, the influence of signalling molecules on culturability tests.

7. SHOULD BACTERIAL VIABILITY BE ASSESSED AT THE INDIVIDUAL OR COMMUNITY LEVEL?

In this review we have predominantly considered viability as a testable property of individual cells. However, in the preceding section we recognized that contributions from other cells in a community of bacteria may influence the capacity of a particular cell to yield a positive result in a culturability test. Furthermore, we have also noted the possibility that some cells in a community may deliberately sacrifice themselves in order to provide resources, enabling the remaining cells to maintain themselves against adverse conditions. To these instances we should add the recognition that community size clearly influences many bacteriological phenomena. The duration of the lag phase has been shown to be inversely related to the number of cells present at the time of inoculation in several instances (note this is distinct from the effects on time before growth can be detected; see Kaprelyants and Kell, 1996);

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establishment of infections requires that the infectious dose is exceeded and both the outcome and reproducibility of antibiotic susceptibility tests depend on careful inoculum control. It also seems clear that, apart from the extracellular products that have been characterized as pheromones, the activity of certain enzymes at the community level as opposed to the individual level in ‘detoxifying the environment’, e.g. by antibiotic (Brook and Gober, 1995) or hydrogen peroxide degradation (Ma and Eaton, 1992),can protect cells that do not produce the required activity within that community. These considerations provoke us to ask whether it is appropriate to assess the viability of individual bacteria. On the one hand, the capacity of an individual cell to replicate to discernible levels seems closely linked to a panoply of signals received from its colleagues and the environment. On the other, survival during replication appears to depend on a variety of protective activities, many of which are provided by the community rather than the individual. An alternative view is that viability is a property of a community of bacteria. In different settings, the community may comprise a single strain or diverse species. From this perspective, viability might be recognized as the capacity of the test community to increase its biomass andor numbers in a specific environment. One consequence of this approach is that the absolute number of propagules in a community is just one component of that community’s fitness for a particular environment. Thus, while it may be possible to revive injured cells within in a community, as observed by McFeters’ group (LeChevallier et al., 1985; Singh et ul., 1986), their capacity to contribute to a stressful colonization event such as an infection may be limited. Conversely, there might be community-levelresponses that confer greater fitness for certain environments such that a smaller number of individuals drawn from that population could successfully colonize. Outside the laboratory, bacterial communities are nearly always consortia composed of different species. There are many instances where interactions between heterologous species may alter the outcome in culturability or activity assays. These may involve well-recognized molecules presumably involved in natural competition, such as antibiotics and colicins. Alternatively, metabolic cross-protection (Aldsworth et al., 1998) or cross-talk between signalling molecules (Kaprelyants and Kell, 1996) could be involved.Again, it is appropriate to consider the relevance of these factors to the outcome of a culturability test. Coordinated behaviour of bacteria in natural communities is most strikingly observed in biofilms. The importance of signalling in the establishment, development and structure of these complex consortia is now clear, and evaluation of the health and survival potential of a particular biofilm by assessing the number of culturable cells within it seems wholly inappropriate (Davies et al., 1998; Kolter and Losick, 1998). Conversely, there clearly are some settings in which the survival of a single propagule is of biological and practical significance. The general need for

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sterility (absence of any viable cells) in the provision of surgical instruments, parenteral pharmaceutical preparations and many industrial processes seems beyond doubt. There is also considerable evidence to suggest that some undesirable processes such as hazardous levels of contamination, spoilage during food production or other manufacturing processes and infective diseases can be initiated by a single organism. In view of these considerations, we suggest that viability tests might be adjusted to determine the potential of bacteria within the sample material to initiate a specific process. Clearly, this is already the case in many instances where experience and legislation have established upper limits to acceptable levels of culturability of specific bacteria in foods, potable water and bathing areas. However, there is considerable unease relating both to the utility and the validity of these (semi-)quantitative tests. One purpose of this section has been to raise the issue of whether quantitative tests of culturability actually provide the best test of an organism’s ability to colonize or influence a new environment.

8. CONCLUSIONS (Figs 1 and 2)

1. Culturability remains the only secure operational definition of viability. 2. We prefer the terms temporarily non-culturable and not immediately culturable (NIC) to ‘viable but non-culturable’ (VNCNBNC). 3. As yet uncultured (AYU) bacteria should be considered separately from non-culturable forms of culturable bacteria. 4. New indirect methods, such as fluorescence and reporter gene-based assays provide information about the physiological properties of cells but can only be considered reliable indicators of culturability under highly defined conditions. 5. The outcome of a culturability test can be influenced by multiple factors. Some of these have been summarized in Fig. 1. These make it very difficult to design, sample and test regimens that reveal all potentially culturable cells of a particular bacterial strain within environments that present different stimuli to the test organism. Our experience indicates that these factors become more significant in bacterial populations that are not replicating or have been stressed or both. 6. There are some situations where it is more appropriate to consider the viability of a bacterial population or community rather than its component individuals.

Input

Environm mts relevant to the test Natural or Test sample and II Culture conditions Experimental

Properties of the organism(s) to be tested (Genetically determined):

state@) (PS) of

Range of stimulons and the responses they may initiate

sample processing

New Physiological state@) (PS):

the test organisms: Replicating/ Non-replicating’

Nutritional requirements Physical requirements

l

General responses to environmental

R/NR GRTES ?+ Activation of: Suicide systems Prophages Metabolic selfdestr~ction~

I Replication I GRTES ?+ Activation of Suicide systems Prophages Metabolic self-destruction

t

Properties of the

PO + PS Environmental Stimuli: Chemical Physical

OutDut

4

f

Environmental Stimuli: Chemical Physical Biological

Environmental Stimuli: Chemical Physical Biological

Number of cells5 at end of test in a) colonies or b) broth a) Colony or microcolony size b) Cell number in broth. May be detected by: turbidity, absorbance, conductivity. flow cytometry Coulter counter, indicator change and many other means

Figure 1 Scheme indicating some of the potential influences on the outcome of a culturability test. Notes: 1 = Non-replicating may include dormant forms such as spores; 2 = the patterns of response indicated by this phase are outlined in Fig. 2; 3 = these include, in particular, signalling molecules (pheromones, cytokines, etc.); 4 = although these processes may occur in the environment from which the sample was drawn, they are only relevant after sampling inasmuch as their stimulation by the test may lead to an unrepresentative result; 5 = number of cells is used for simplicity here. Increase in biomass sufficient for detection would also be acceptable.

A

lu

m

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Exposure to rpeclfic rtimuli

A Severe

Death Recovery

Mild

7 Differentiation

Figure 2 Scheme outlining the main patterns of response to environmental stimuli. Responses are determined by the strength of the stimulus and the genes comprising the stimulons activated by specific stimuli in the particular organisms tested.

ACKNOWLEDGEMENTS

The financial support of the Biotechnology and Biological Research Council, the Natural Environmental Research Council and the Wellcome Trust for work on non-culturable cells in the authors' laboratories is gratefully acknowledged.

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Zhang-Barber, L., Turner, A.K., Martin, G., Frankel, G., Dougan, G. and Barrow, P.A. (1997) Influence of genes encoding proton-translocatingenzymes on suppression of Salmonella typhimurium growth and colonization. J. Bacteriol. 179.7 186-7 190.

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The Histidine Protein Kinase Superfamily Thorsten W. Grebe and Jeffry B. Stock Department of Molecular Biology, Princeton University, NJ 08544, USA

ABSTRACT

Signal transduction in microorganisms and plants is often mediated by His-Asp phosphorelay systems. Two conserved families of proteins are centrally involved: histidine protein kinases and phospho-aspartyl response regulators. The kinases generally function in association with sensory elements that regulate their activities in response to environmental signals. A sequence analysis with 348 histidine kinase domains reveals that this family consists of distinct subgroups. A comparative sequence analysis with 298 available receiver domain sequences of cognate response regulators demonstrates a significant correlation between kinase and regulator subfamilies. These findings suggest that different subclasses of His-Asp phosphorelay systems have evolved independently of one another. 1. Introduction ....................................................... 1.1. Protein phosphorylation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2. Histidine protein kinases ......................................... 1.3. Systemdesign . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.4. Homologyboxes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2. Histidine protein kinase subfamilies ................................... 2.1. Subfamilies of histidine kinases ................................... 3. Cognate receiver domains . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4. Domain shuffling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

139 139 140 182 195 197 199 206 211 214 214

1. INTRODUCTION 1.1. Protein Phosphorylation in Bacteria

The discovery of protein phosphorylation dates back to the middle of the last century, when milk and egg proteins were found to contain covalently linked ADVANCES IN MICROBIAL PHYSIOLOGY VOL 41

ISBN 0-12-027741-7

Copyright 0 1999 Academic Press All rights of reproduction in any form reserved

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THORSTEN W. GREBE AND JEFFRY 6.STOCK

inorganic phosphate. Phosphoserine was detected in egg yolk protein in 1932 (Lipmann and Levene, 1932) and phosphothreonine was identified in casein over two decades later, while phosphotyrosine as a mode of protein modification was unknown until 1979 (Eckhart er al., 1979). The first phosphorylation on histidine was reported by Boyer et al. (1962) who discovered this type of modification in mitochondria1 succinyl-CoA synthase (succinyl-thiokinase). Krebs and Fischer were the first to recognize the importance of protein phosphorylation in the regulation of enzymatic activities (Krebs and Fischer, 1956). Many additional examples of regulation through phosphorylation were subsequently discovered in eukaryotes, but a striking lack of protein phosphorylation in prokaryotes led to the view that this type of modification was exclusively eukaryotic. A first indication to the contrary was reported by Kuo and Greengard (1969) who claimed to have isolated a cyclic AMP-dependent kinase from Escherichiu coli that could transfer phosphate from ATP to histones. However, this observation has never been reproduced. The issue of whether there are ATP-dependent kinases in bacteria was settled only when Wang and Koshland reported the isolation of the first regulatory serine- and threonine-phosphoryl groups from an acidic hydrolysate of bacterial proteins in 1978. At this time, most routine purification procedures for proteins called for acidic conditions at one point or another, e.g. acidic media or trichloroacetic acid TCA precipitations. Serine-, threonine- and tyrosine phosphates survive this kind of treatment. The phosphoramidate bond of phosphohistidines, however, is very prone to acid hydrolysis. Phosphohistidinesare stable to alkali and survive 13h at 100°C in 1 . 5 potassium ~ hydroxide (Buss & Stull, 1983), but a standard TCA precipitation can cause significant hydrolysis. In addition, phosphohistidines have a higher free energy than ATP and tend to function substoichiometricallyas phosphotransfer intermediates rather than as regulatory modifications per se. For these reasons, the discovery of histidine protein kinases in bacteria was delayed until these important regulatory components were purified and studied in vitro (Hess et al., 1988; Ninfa et al., 1988a,b). Even the very rare event of bacterial kinase phosphorylation on tyrosines was discovered before the far more common modification on histidines (Vallejos et al., 1985). 1.2. Histidine Protein Kinases

The first histidine protein kinases to be sequenced were EnvZ (Mizuno et ul., 1982), PhoR (Tommassen et al., 1982), CpxA (Albin et al., 1986), NtrB (Nixon et al., 1986), DctB (Ronson et al., 1987a), VirA (Leroux et al., 1987) and CheA (Stock et al., 1988). The role of these proteins in signal transduction

THE HISTIDINE PROTEIN KINASE SUPERFAMILY

141

was deduced from an analysis of the evolutionary relationship between the genes involved in chemotaxis and osmosensing in E. coli and Salmonella (Stock et al., 1985). The first indication that a protein kinase activity was involved came from studies of nitrogen regulation in E. coli (Ninfa and Magasanik, 1986). Ninfa et al. proposed the first model for two-component signal transduction: NtrB functions as a kinase/phosphatase to control the amount of cellular NtrC-phosphate in response to cytoplasmic signals of nitrogen availability. NtrC acts in turn to regulate transcription at nitrogen-regulated promoters. The chemotaxis system of E. coli was second to provide support for the kinase signal transduction mechanism. In this system it was demonstrated that the kinase CheA autophosphorylates and then passes its phosphoryl group to a cognate response regulator protein, CheY (Hess et al., 1988a,b;Wylie et al., 1988). Several-hundred homologous systems have been found since and many have been shown to employ essentially the same biochemical mechanism as that originally elucidated in the Ntr and Che systems. The initial conviction that histidine protein kinases are restricted to prokaryotic organisms has had to be revised (Chang et al., 1993; Ota and Varshavsky, 1993; Chang and Meyerowitz, 1994; Swanson and Simon, 1994). To date, 5% of all histidine protein kinase sequences are found in fungi, amoebae and plants. In addition, mitochondria1 branched-chain alpha-ketoacid dehydrogenase kinases which phosphorylate at serine residues show an intriguing sequence homology with histidine kinases. The H-, N-, D- and G-boxes are conserved, but the phosphorylated target protein does not appear to contain a receiver domain (Popov et al., 1992, 1997; Chang and Meyerowitz, 1994; Harris et al., 1995, 1997). Mitochondria1pyruvate dehydrogenase kinase also shares homologous N-, Dand G-boxes with canonical histidine protein kinases, but the target phosphorylation site is a serine (Popov et al., 1993; Thelen et al., 1998).The existence of both these proteins, which are encoded as nuclear genes, raises the possibility that histidine protein kinases were passed from bacteria through mitochondria to vertebrate species. A similar situation may pertain to chloroplasts and plant evolution. A particular case are the phytochromes. Phytochromes are photosensory molecules that show significant homology to histidine protein kinases (Schneider-Poetsch et al., 1991). Only a few members of the phytochrome superfamily have canonical H-boxes, e.g. PhyA-osa (Kay et al., 1989) and PhyC-ath (Cowl et al., 1994). (For a list of three-letter species identifiers, see Table 1.) Phytochromes channel photosensory information into signallingpathways that use G-proteins rather than response regulators (Neuhaus et al., 1993). The cyanobacterial phytochrome Cphl-ssp is an exception, however. It donates phosphoryl groups to a response regulator, Rphl (Yeh et al., 1997), and may therefore be considered a missing link in the evolution of histidine protein kinases to phytochromes (Quail, 1997). There are five phytochromes in

Toble 1

A

Alphabetical list of three-letter species identifiers used in this chapter

P h)

aae Aquija aeolicus abr Azospirillum brasilense aca Azorhizobium caulinodans aeu Alcaligenes eutrophus a h Archaeoglobusfulgidus arh Agrobacterium rhizogenes aSp Anabaenasp. ath Arabidopsis thaliann atu Agrobacteriumtumefaciens avi Azotobacter vinelandii bav Bordetella avium bbr Bacillus brevis bbu Borrelia burgdorferi bfr Bactemidesfragilis bja Bradyrhizobiumjaponicum bme Bacillus megaterium bpa Bradyrhizobiwnparasponia bpe Bordetella pertussis bps Burkholderiapseudomallei bpt Bordetellaparapertussis bsu Bacillus subtilis bte Bacteroides thetaiotaomicron bth Bacillus thuringiensis cac Closhidium acetobutylicum cal Candida albicans cbu Coxiella bumetii ccr Caulobactercrescentus cpe Clostridiumperfringens cpi Carnobacteriumpiscicola ctr Chlamydia trachomatis cvi Calothrix viguien

ddi eae eae eag eca ed eM)

efa efe fdi fsP ge hha hi0 hPY bsa hse hsp kox kPn Ila ImO

IPl Isa mb mex mle mor mth mtu mxa

Diciyostelium discoidewn Eubacteriwn acidaminophilum Enterobacteroemgenes Enterobacteragglomerm Erwinia carotovora Enterobacter cloacae Escherichia coli Enterococcusfaecalis Enterococcusfoecium Fremyella diplosiphon Fischerella sp. Glomerella cingulata Halobacterium halobium Haemophilus injluenzae Helicobacterpylon Halobacterium salinarum Herbaspirillumseropedicae Halobacterium sp. Klebsiella oxytoca Klebsiellapneumoniae Loctococcus h t i s Listeria monocyiogenes Lactobacillusplantarum Lactobacillus sake Mycobacterium bovis Methylobacteriumatorquens Mycobacterium kprae Methylobacteriumorganophilum Methanobacterium t h e m . Mycobacterium tuberculosis Myxococcusxanthus

ucr Neurospora crassa osa Oyza sariva (Rice) pae Pseudomoms aeruginosa pde Paracoccus denitrificans pho Pyrococcus horikoshii pmi Proteus mirabilis por Chloroplast of Porphyra purpurea . . . . ipu Pseuimoms put& pso Pseudomonas solanacearum psp Pseudomoms sp. pst Provia'encia stuartii psy Pseudomoms syringae pto Pseudomoms tolaasii pvi Pseudomonas viridijlava pvu Proteus vulgaris rca Rhodobacter capsulatus rce Rhodospirillum centenum reu Ralstonia eutrvpha rte Rhizobium Ieguminosarum m e Rhizobiwn meliloti rpa Riftia pachyptila enhsymbiont rph Rhizobiumphaseoli rra Rathayibacter rathayi rru Rhodospirillum rubrum rsh Rhodobactersphaeroides m Ralstonia solanacearum rsp Rhodococcus sp. san Streptococcusanginosus sau Staphylococcusaweus sce Saccharomyces cerevisiae sco Streptomycescoelicolor

set sdu sdy sep sgo shy sin sli slu sly smi sml SQU

spo

ssp sti sty

syn

tde lfe bna tpa

ttl val

vco vha xca m e xor yen

Streptococcusconstellatus Salmonella dublin Shigella dysenteriae Staphylococcus epidennidis Streptococcusgordonii Streptomyceshygroscopicus Streptococcusintermedius Streptomyceslividans Staphylococcus lugdunensis Solanum lycopersicum Streptococcusmitis Streptococcusmilkri Streptococcuspneumoniae Schizosaccharomycespombe synechococcus sp. Salmonellatyphi Salmonella typhimrium Synechocystis sp. Treponema denticola Thiobacillusferrooxidans Themtogamantima Treponemapallidum Thauera TI Wbrioalginolyticus Wbtio cholerae Wbrioharveyi Xanthomoms campestris Xenorhabdus nematophilus Xanthomonas oryzae Yersinia enterocolitica

THE HISTIDINE PROTEIN KINASE SUPERFAMILY

143

Arabidopsis (Clack et al., 1994), only one of which has a histidine at the position that a sequence comparison predicts would be the phosphorylation site. In this context, it should be noted that there are several histidine kinase homologues in bacteria that either are not kinases or that phosphorylate at residues other than histidine. These include E l 169520_bme, ERS2_ath, G2648505_afu, G264893 1-afu, G2649096_afu, G2649555_afu, G2650176_afu,G2650366_afu, G2650669_afu, J04195_syn, MTH786_mth, NifL-eag, NifL-kox, NifL-kpn, S111687_syn, TP0980_tpa, TP098 I -tpa, YegE-eco, YhcK-eco and YtrP-bsu (for species identifiers, see Table 1). There are numerous proteins in both prokaryotes and eukaryotes that are unrelated to the histidine protein kinase superfamily but are nevertheless phosphorylated on histidines. Examples are succinyl-CoA synthetase (Boyer et al., 1962; Mitchell et al., 1964), enzymes I, IIA, and IIB and HPr of the phosphoeno1pyruvate:sugarphosphotransferase system (PTS) (Kundig et al., 1964; Weigel et al., 1982; Reizer et al., 1993), nucleoside diphosphate kinase (NDPK) (Zetterqvist, 1967;Walinder, 1968; Walinder et al., 1968), isocitrate lyase (Robertson et al., 1988), phosphoglycerate mutase (Rose, 1970; Rose et al., 1973, adrenocortical cyclic nucleotide-independent protein kinase (Kuroda and Sharma, 1982, 1983), histones HI and H2a from Physarumpolycephalum (Pesis et al., 1988), as well as rat and bovine histones H4 (Fujitaki et al., 1981; Huebner and Matthews, 1985), and human P-selectin (Crovello et al., 1995). Physiological processes that involve sensing through histidine kinases include cell differentiation and cell-cycle regulation, chemotaxis and gliding motility, nitrogen and phosphate homeostasis, production of and resistance to antibiotics, quorum sensing and genetic competence, setting of circadian rhythms and fruit ripening, regulation of turgor and sugar transport, virulence and pathogenicity (Table 2) (for reviews, see Stock et al., 1989; Parkinson and Kofoid, 1992;Alex and Simon, 1994; Hoch and Silhavy, 1995;Appleby et al., 1996; Stock and Surette, 1996; Ohta and Newton, 1996; Wurgler-Murphy and Saito, 1997. Table 3 shows a list of the histidine kinases that have been included in the present sequence analysis, together with accession numbers and potential cognate response regulators. Histidine protein kinases can be found in all major branches of the bacteria and archaea as well as in eukaryotes. The only major group lacking these systems is the animal kingdom. Aside from mitochondria1 homologues, no histidine kinases have been identified in these organisms and their is apparently no histidine protein kinase homologue in the Caenorhabditis elegans genome. In prokaryotes, there seem to be no general rules governing which divisions use histidine kinases and which do not (Fig. 1). It rather seems that the distribution of reported kinases mirrors society’s major research foci, namely

Table 2 Twocomponent phosphorelay systems and their functions. The extension ‘-RR’indicates the receiver domain of a hybrid kinase.

Process

Kinase

Regulator

Organism (reference for kinase)

Antibiotic resistance/synthesis Antibiotic synthesis Antifungal antibiotics Vancomycin resistance

AbsA 1 APdA vans

AbsA2 A@-RR VanR

Streptomyces (Brian et al., 1996) Pseudomom (Corbell and Loper, 1995) Enternbacteria (Arthur et al., 1992)

Catabolism

DegS

DegU

Bacillus (Louw et al.. 1994)

Chemotaxis

CheA

CheY, CheB

Archoeoglobus (Klenk et al., 1997), Bacillus (Fuhrer and Ordal, 1991), Borrelia (Fraser et al., 1997; Trueba et al., 1997), Enterobacter (Dahl et al., 1989), Escherichia (Kofoid and Parkinson, 1991), Halobacterium (Rudolph and Oesterhelt, 1995), Helicobacter (Tomb et al., 1997), Listeria (Dons et al., 1994), Pseudomom (Ditty et al., 1998), Pyrncoccus (Kawarabayasiet al., 1998), Rhizobium (Greck et al., 1995), Rhodobacter (Ward et al., 1995; HambLin et al., 1997), Rhodospirillum (Jiang and Bauer, 1997), Salmonella (Stock et al., 1988). Synecbcystis (Kaneko et al., 1996), Thenotoga Swanson et al., 1996) and Treponema (Fraser et al., 1998)

Autoinduction Competence Competence Quorum Sensing

COmD Cod LuxN, LuxQ

COmE

COmA Lux0

Streptococcus (Cheng et al., 1997; Pestova et al., 1996) Bacillus (Weinrauch et al., 1990) Vibrio (Bassler etal., 1993, 1994)

-.. P

P

L

rn n n

9

m

Differentiation/ development Cell cycle control Motility Nodulation Capsule synthesis Ethylene response Light response, bacteria Light response, plants Cytokinin binding Osmosensing/development Osmosensing Germination Hyphal growth Sporulation

-I

Difl FrzE NodV RcsC ETR (ERS) Cph 1 PhyC CKIl DokA Slnl DhkB Nikl KinA,B,C

DifK FrzE-RR NodW RcsB ETR-RR Rcp 1 ?

cKI1-RR DokA-RR Sln 1-RR DhkB-RR Nikl-RR SPOOF

Caulobacter (Ohta et al., 1992) Myxococcus (McCleary and Zusman, 1990) Brudyrhizobium (Gottfert et al., 1990) Enterobacteria (Stout and Gottesman, 1990) Arabidopsis (Hua et al., 1995), Lycopersicon (Payton et al., unpublished) Synechocystis (Yeh et al., 1997) Arabidopsis (Cowl et al., 1994) Arabidopsis (Kakimoto, 1996) Dictyostelium (Schuster et al., 1996) Saccharomyces (Ota and Varshavsky, 1993) Dictyostelium (Zinda and Singleton, 1998) Neurospora (Alex et al., 1996) Bacillus (Perego et al., 1989; Trach and Hoch, 1993; LeDeaux and Grossman, 1995)

I rn

z

0)

-4 -

P

rn z D W

0

;;I -

z E z

% rn v)

C

-u

rn W

Nitrogen metabolism N,-fixation Nitrate reduction Nitrogen assimilation

Phosphate metabolism

P FixL

FixJ

NarX NtrB

NarL NtrC

CreC

CreB

PhoR

PhoB

Azorhizobium (Kaminski and Elmerich, 1991), Bradyrhizobium (Anthamatten and Hennecke, 1991), Rhizobium (Patschkowski et al., 1996; D'hooghe et al., 1998) Enterobacteria (Stewart et al., 1989) Azospirillum (Machado et al., 1995), Brudyrhizobium (Nixon et al., 1986), Escherichia coli (Miranda-Rios et al., 1987), Herbaspirillum (Steffens et al., unpublished), Klebsiellu (MacFarlane and Merrick, 1985), Proteus (Steglitz-Morsdorfet al., 1993), Rhizobium (Patriarca et al., 1993), Rhodobacter (Foster-Hartnettet al., 1993), Rhodospirillum (Zhang et al., 1995), Salmonella (McFarland et al., 1981), 7'hiobacillus (Kilkenny et al., 1994), Vibrio (Maharaj et al., 1989) Enterobacteria (Wanner and Latterell, 1980 Amemura et al., 1986; Wanner, 1995) Enterobacteria (Makino et al., 1986; Lee et al., 1989)

CitA, DpiA

CitB, DpiB

Enterobacteria (Bott, 1997; Ingmer et al., 1998)

s

7

a

Citrate fermentation

P VI

-.

Table 2 cont.

m P

--

Process

Kinase

Regulator

Organism (reference for kinase)

Adaptation Anaerobic repression Chromatic adaptation Osmosensing

ArcB RcaE EnvZ

ArcB-RR

KdpE

E. coli (Iuchi et al., 1990) Fremyella (Kehoe and Grossman, 1996) E. coli (Mizuno et al., 1982),Salmonella (Liljestrom et al., 1988), Xenorhabdus (Tabatabai and Forst, 1995) E. coli (Wdderhaug et al., 1992)

CiaR PmrA

Streptococcus (Guenzi et al., 1994) Streptococcus (Soncini and Groisman, 1996)

Turgor sensing (K+-transport) KdpD Cell wall integrity

CiaH

PmrB Transport Dicarboxylic acid Hexose-phosphate Phosphoglycerate Vilence/pathogenicity Alginate Alginate Pectate lyase Phytotoxin Vilence Vilence Extracellular &toxin Extracellular toxins Plant cell transformation Root colonization

?

OmpR

DctB UhPB PgtB

Algz Kid PelY CorS BvgS PhOQ AgrC

Rhizobium (Ronson et al., 1987a) E. coli (Island et al., 1992) Salmonella (Yang et al., 1988)

vis

NgR AlgB PelY-RR CorR BvgA PhoP AgrA ViR

VuA COlS

ColR

v i

Pseudomonas (Yu et al., 1997) Pseudomonas (Ma et al., 1997) Pseudomoms (Liao et al., 1994) Pseudomonas (Ullrich et al., 1995) Bordetella (Arico et al., 1989) Salmonella (Miller et al., 1989) Staphylococcus (Novick et al., 1995) Clostridium (Lyristis et al., 1994) Agmbacterium (Leroux et al., 1987; Morel et al., 1989) Pseudomonas (Dekkers et al., 1998)

rc, R rn

#

c rn n n R

<

m cn

4

8 7i

Table 3 List of histidine protein kinases. Species names are in alphabetical order. The group affiliation of histidine kinase domains and receiver domains is given in italics below the name of the protein. The classification of response regulators is based on the receiver domains. The numbers rn indicate the amino acid range of kinase and receiver domains, respectively, that have been used in the sequence analysis. ‘RR’ indicates the receiver Z rn domain of a hybrid kinase 2

2 G

5

Kinase

Regulator(s)

Species (Accessic a)

(Subfamilv)

(Subfamily)

(aa range of kinase domain)

(aa range of receiver domain)

Agrobacterium tumefaciens

ChvG atu

ChvI atu

LI 8860

HPK 3 b 333-570 of total 690

RAl

Agrobacterium tumefaciens

V i A atu

VuA RR atu

VirG atu

XI6905

HPK 4. hybrid 459-695 of total 833

Llnclassi$ed (VirA) 691-832

R A2 2 6 1 45

Agrobacterium tumefaciens

VirAL atu

VirAL RR atu

X05241

HPK 4, hvbrid m 9 5 of total 835

Unclassified (WrA) 691-834

Alcaligenes hydrogenophilus

H o d ahy

HoxA ahy

U82565

HPK 3g 200453 of total 456

-Q

33

0

iz E

1-1 I8

RF 9-127

Anabaena sp. PCC 7120

CvaC asD

CvaC RRI asp

CyaC RR2 asp

D89625

HPK l a 505-734 of total 1155

R A2 9-123

RF 796916

Anabaena sp. PCC 7120

HeDK asD

U68034

HPK l b 329-570 of total 575

Aquifex aeolicus

HksPl aae

NtrCl aae

a 0 0 0 7 2 4 AE000657

HPK 4 423-636 of total 646

R A4 1-124

Aquifex aeolicus

HksP2 aae

PhoB aae

AEWJ683 AEooo657

HPK 4 87-310oftotal310

RAI 5-125

Species (Accession)

Aquifex aeolicus Auxx)679 AEOoO657

Arabidopsis thaliana U21952

Kinase

Regulator(s)

(Subfmily)

(Subfami@) (aa range of receiver domain)

(aa range of b a s e domain)

HksP4 aae

NhC3 aae

122-339 of total 339

1-123

HPK 4

R A4

ERS ath

HPK I b

333-585 of total 613

Arabidopsis thaliana L24119

Arabidopsis thalianu Am3952

Arabidopsis thaliana Columbia 2435516 AFO24504

Arabidopsis thaliana Wassilewskzjia D87545

ETRl atb

ETRl RR ath

334572 of t d 738

RBI 609-73 1

62708752 atb HPK Ic, hybrid

R 82

472-747oftotal1190

1026-1 180

HPK Ib, hybrid

G2708752 RR ath

62435516 atb

G24355 16 RR ath

1-251 oftotal648

R B2 461439

HPK Ic, hybrid (noH-Box)

CKIl atb

CKIl RR ath

HPK Ic, hybrid

R 82

391469 of total 1122

985-1 122

Archaeoglobus fulgidus

CheY afu

CheB afu

1-121

1-123

R C2

AFXIO1031Awwx)782

R C5

A rchaeoglobusfulgidus AE000958 AM00782

398-600 of total 608

Archaeoglobusfulgidus AE000984 AM00782

62648833 afu

HPK 6

325-528 of total 528

m

Archaeoglobus fulgidus

62648910&

AM00989 AM00782

HPK 6 1 15-3 17 of total 323

Archaeoglobus fulgidus

62649045 afu

AEooo997 AEooo782

HPK 6 121-323 of total 338

Archaeoglobus fulgidus AEOOlOOO AEOOO782

62649082afu

Archaeoglobus fulgidus

62649099 afu

Archaeoglobus fulgidus

62649399 afu

AEOOloOl AUWX)782

HPK 6 256-450 of total 456

Archaeoglobus fulgidus

62649708 afu

Archaeoglobus fulgidus AM01051 AEooo782

Archaeoglobus fulgidus AM01073 AEooo782

Archaeoglobus fulgidus

z

HPK 6 127-330oftotal334

62249834 afu HPK 6 325-531 of total 531

62650174afu HPK 6 113-324 of total 329

G2650175 afu

R C2

10-125

62650436 afu

AEOO1092AMoo782

HPK 6 261472 of total 481

Azorhizobium caulinodans

Icizhca

X56658

z

HPK 6 m 2 1 6 of total 222

AEOO1022AEooo782

AEOO1042AE000782

-0

0

HPK 3h 679-908 of total 908

HPK 4 266494 of total 504

FixJ aca RA4

5-122

Species (Accession)

Azorhizobium caulinodans X63841 S71362

Azospirillum brasilense 237984

Bacillus brevis L15444

Bacillus sp. B21-2 Dl0690

Kinase

Regulator(s)

(Subfmily) (aa ranee of kinase domain)

(Subfamily)

(aa range of receiver domain)

NtrY aca

NtrX aca

495-725 of total 771

2-122

HPK 4

NtrB abr

R A4

NtrC abr

HPK 4

R A4

147-378 of total 400

3-121

DegS bbr

DegU bbr

HPK 7

R Cl

175-381 of total 386

9-129

Ibc&L!m HPK 4

155-367 of total 373

Bacillus subtilis

M57894M51894299112ALi339126

Bacillus subtilis X54010 293932

CheA bsu

CheY bsu

CheB bsu R CS

347-537 of total 671

R C2 2- 120

C o d bsu

C o d bsu

HPK 9

HPK 7

557-769 of total 769

Bacillus subtilis U56901

DePS bsu HPK 7

17&385 of total 385

Bacillus subtilis M31067

Bacillus subtilis U63302 U33938 S61781 299120

1-122

RE

1-127

DegU bsu

R CI 3-123

KinA bsu

SpoOF bsu

SpoOA bsu R CI

386604 of total 606

R C2 2-120

HPK 4

KinB bsu

r

3-125

HPK 4

R C2

SpoOF bsu

SDoOA bsu

202-423 of total 428

2-120

R CI 3-125

m

KinC bsu

S - d F bsu

SpOA bsu

L34803 U51911 AFO12285AFO12284

HPK 4 205-423 of total 428

R C2

R CI

Bacillus subtilis

bs!m HPK 8

l=Ycma!

Bacillus subtilis

371-583oftoId 593

R C3 1-128

Bacillus subtilis

PhoR bsu

PhoP bsu

ha3549

HPK l a 341-572 of total 579

RAl 2-120

Bacillus subtilis

ResE bsu

ResD bsu

355-589 of total 589

RA1 6123

Z99 1 I8 AUX)9126

LO9228 Z991 I6 A m 1 2 6

HPK la

Bacillus subtilis

SDaK bsu

SpaR bsu

U09819 LO7785

HPK 3c 228456 of total 459

RAI

Bacillus subtilis

1-1 17

YcbA bsu

Y cbB bsu

299105AL009126

HPK 3 (only I12 aa) 277-380 of total 387

1-121

Bacillus subtilis

YclK bsu

D50453

HPK l a 238468 of total 473

Bacillus subtilis BOO1488

YdbF bsu HPK 5 3 12-525 of total 535

R Cl

YclJ bsu RAl 1-122

YdbG bsu R C4 5-127

YdfH bsu

Ydfl bsu

A8001488

HPK 7 191-399 of total 407

R CI 1-126

Bacillus subtilis

YesM bsu

YesN bsu

HPK 8 373-577 of total 577

1-126

Bacillus subtilis

299107AL009126

R CI

Species (Accession)

Bacillus subtilis D78508

Kinase

Regulator(s)

(SUbfnmilY) (aarange of kinase domain)

(Subfmily) (aamge of reCejver domain)

Y6.l bsu HPK 7

YfiK bsu R CI

182-384 of total 400

1-121

Bacillus subtilis 2443240

32CL52.5of total 542

Bacillus subtilis

Z99110Aux)9126

YkoH bsu

HPK la

222-449 of total 454

Bacillus subtilis Z99111AuK)9126

Bacillus subtilis Z99111ALo09126

2619013

Bacillus subtilis Z99119 Aux)9126

3-121

3BrQI.w HPK 4

507-726 of total 738

YkvDbSU

HPK 4

282-502

Bacillus subtilis

YkoG bsu R A1

No R. MaR

0;total 506

YAEmm

YocG bsu

HPK 7

169-370 of total 370

R C1 1-125

HPK 3i

R A1

105-323 of total 334

1-126

3 19-524 of total 533

R C4 1-122

YtsA bsu

Bacillus subtilis 293931 299120

Bacillus subtilis 294043

Yvco bsu

HPK 3i

117-346 of total 356

YvcP bsu RAI

1-125

R

Bacillus subtilis 299121 A m 1 2 6

Bacillus subtilis 299120 Aux)9126

Bacillus subtilis 299120299121 Au)o9126

Yvfr bsu

YvfU bsu

-I

HPK 7

R Cl

12C323 of total 328

1-127

rn

YvaE bsu

R CI

140-343 of total 360

1-123

YaGbSU

Y vrH bsu

340-573 of total 573

Bacillus subtilis 299122 Aux)9126

Bacillus subtilis

Bacillus subtilis D83026 D45911

Bacillus subtilis D78193

Bacillus thuringiensis U03552

RAI

136-256

YwpD bsu

E z D cn rn cn

HPK 8 -267

D14399

Y vaC bsu

HPK 7

HPK la

I

of total 278

YxdK bsu

YxdJ bsu

HPK 3i

RAI

102-323 of total 325

1-118

s

YxiM bsu

YxiL bsu

D

HPK 7

rn

3xI n

s

R C1

192-393 of total 406

5-131

YvcG bsu

YvcF bsu

HPK la

RAI

367-601 of total 61 I

2-1 18

I-

<

HkoAbth

HPK 4

153-372 of total 312

Bacteroides fragilis s59000

RDrX bfr HPK lo

RprY bfr RAI

280-514oftotal519

7-125

Bacteroides thetaiotaomicron

RteA bte

RteA RR bte

RteB bte

M81439 M81881

HPK 3 d hybrid, H2-dOmain 28S515 of total 772

Unclassified

Unclass$ed (R A, C ) 3-122

539-658

A

ul w

Table 3 (continued)

Species (Accession)

Kinase

Regulator@)

(Subfamily) (aa range of kinase domain)

(Subfamily) (aa range of receiver domain)

Riss bav

RisA bav

AJ224802

HPK 2b 239-460of total 474

RA1

Bordetella pertussis

BvgS bDe

BveS RR bpe

BveA bDe

HPK lb. hybrid, H2-domain 71CL945of total 1238

RBI 972-1097

R Cl

CbeAl bbu

CheY2 bbu

CheB2 bbu

R C2

25-146

Unchsified 1-86

CheY3 bbu

CheB 1 bbu

Bordetella avium

M24101

Borrelia burgdorferi L39965 U61498 X91907 AEmI 158 AwKx)783

Borrelia burgdorferi

AM01 168 Awxx)783 U28%2

Borrelia burgdorferi AM01 146 AwwK)783

HPK 9 385-576 of total 716

CheA2 bbu

HPK 9 534-722 of total 864

9-129

R C2

25146

G2688313 RR bbu

G2688314 bbu

HPK lb, hybrid 754-994 of total 1494

R B1

R A2

1155-1280

GMss706 bbu

(32688707 bbu

HPK 4 143-358 of total 382

R A4

Bradyrhizobiumjaponicum

BdfA bia

2801651 AH42096

3-120

rn 0

Fixl bja

HPK 4 272-500 of total 505

R A4

4122

Bradyrhizobiumjaponicum

NodV bia

NodW bja

HPK 4 653-882of total 889

W

z

FixL bia

M31765

2!rn D

HPK l a [Yf o r HI 631-865 of total 873

X56808

Bradyrhizobiumjaponicum

Unclassified 1-98

62688313 bbu

Awx)1176

Borrelia burgdorferi

2-121

R A4

20-131

c rn n

n

s

m cn

--I

0 0 21

Bradyrhizobiumjaponicum

NwsA bia

NwsB bia

222637

HPK 4 572-804 of total 81 1

Bradyrhizobiumjaponicum

Ra@ bia

RayA bja

HPK 2a 225-455 of total 474

RA1 1-120

Yo9666

R A4 14-132

Re@ bja

A1006100

ReeR bja

HPK 3e 200420 of total 440

R A4 12-135

Brudyrhizobiumparusponia

NtrB bpa

NtrC bpa

MI4227

HPK 4 130-363 of total 377

R A4 3-121

Brudyrhizobiumjaponicum

Burkholderia pseudomallei

I r s bDS

IrlR bps

MOO5358

HPK 2a 23-60 of total 464

RAI 1-1 19

Calothrix viguieri

E307792 evi

2765035 YO9899

HPK l a 505744 of total 744

Candida albicans

CaHKl cal

CaHKl RR cal

AFO13273

HPK Ib, hybrid 1988-2222oftotal2471

R Bl 233&2471

Candida albicans

CaSLNl cal

CaSLNl RR cal

-006362

HPK l b , hybrid (insert) 500-644 and 968-1044 of total 1377

R Bl 1247-1 373

Candida albicans

Chiklcal

Chikl RR cal

A8006363 U69886

HPK l b , hybrid 491-730 of total 1081

R Bl 873996

Camobacterium piscicola

CbnK cDi

CbnR cpi

LA7121

HPK 10 220-429 of total 442

RD 2-130

-I

5

Table 3 (continued)

Species

(Accession)

Caulobacter crescentus M98873

Caulobacter crescentus

a

Kinase

Regulator(s)

(WfmW

(

(aa range of kinase domain)

(aa range of receiver domain)

DivK ccr

318-549 of total 5%

RBI 2-122

DivL ccr

CtrA ccr

531-757 of total 769

RAI 1-124

WuJetaL(1999)

HPK l o [Yfor HI

Caulobacter crescentus

PleC ccr

DivK ccr

592-827 of total 841

RBI 2-122

M91449

Chloroplast of Porphyra purpureu Avon U38804

HPK Ib

Q,

wfmw

DivJ ccr

HPK Ib

ul

Ycfza mr

HPK l a

408456 of total 656

Clostridium acetobutylicurn U3%73

Coxiella burnetii U07186 2126373

KdDD cac

KdpE cac

667-900 of total 900

RAI 4-121

HPK la

r

OrsA cbu HPK 2b

208421 of total 425

Dictyosteliurn discoideum U42597

Dictyosteliurn discoideurn AFD24654

Dictyosteliurn discoideurn -29726

DhkA ddi

DhkA RR ddi

RegA ddi RAI

1377-1621 of total 2150

R B1 2024-2148

HPK Ib, hybrid

DhkB ddi

DhkB RRddi

951-1 185 of total 1%9

RBI 1838-1969

HPK Ib. hybrid

DhkC ddi

DhkC RR ddi

410-1550 of total 1225

R BI 1076-1 200

HPK Ib, hybrid

?J

Y

Dictyostelium discoideum

DhkD ddi

DhkDRRddi

AF029704

HPK la, hybrid 202440 of total 709

R A2 568-69 1

Dictyostelium discoideum

DokA ddi

DokA RR ddi

X96869

HPK Ib, hybrid 1033-1265 of total 1670

R BI 1516-1635

Enterococcus faecium

VanS efe

VanR efe

M68910

HPK l a 145-372 of total 384

RAI 2-119

Erwinia carotovora

RDfA eca

RpfA RR eca

U62023

HPK Ib. hybrid, H2&main 182-5 18 of total 929

R BI 674-796

Escherichia coli

ARB eco

ArcB RR eco

ArcA eco

X53315 U18997 U00096

HPK Ib. hybrid, H2-domnin 273-508 of total 778

RBI 52345

RAI 1-120

A M eco

At& eco

HPK 4 379-599 of total 608

RA4 4-122

Escherichia coli L13078 D90851

Escherichia coli

BaeS eco

BaeR eco

Dl4054 D90846 D90847

HPK la 231457 of total 466

RAI 9-127

Escherichia coli

BarA eco

BarA RR eco

HPK Ib, hybrid, H2-domain 283-517 of total 918

R BI 667-786

Dl0888 DO1163 D90894 Auw)o362 UOOO96

Escherichia coli

BasS eco

BasR eco

U14003 AEooo483 U00096

HPK 2a 133-353 of total 363

RA1 1-1 18

Escherichia coli

CheA eco

CheY eco

CheB eco

M34669

HPK 9 319-507

RA3 S126

R C5 3-124

Of total 654

Table 3 (continued)

Species

(Accession)

Escherichia coli D90835

A

Kinase

Regulator(s)

(SI&fm.ly) (aa range of kinase domain)

(SUbfami[y) (aa range of receiver domain)

!Ar!&BQ

HPK 2a 226452 of total 452

CopR e c ~ 37-161

CDXA eco

CDXR eco

X13307

HPK 26 230-453 of total 458

RAI 1-1 17

Escherichia coli

crec eco

CreB eco

U14003 Uooo96

HPK 3c 246470 of total 474

RAI

BxSsm

I2sa&zQ

U14003

Escherichia coli

HPK 5 330-535 of total 543

DDiB eco

m

RAI

Escherichia coli

Escherichia coli

Ln

>121 4

R C4 1-123

DpiA eco

rri

U82598 W7510 U46667

HPK 5 328-538 of total 552

R C4 4-123

Escherichia coli

EnvZ eco

OmDR eco

J01656AMoo416 U00096

HPK 26 224-437 of total 450

RAI

EI&cQ

Eves RR e c ~

EvgA eco

R BI

R CI 1-124

Escherichia coli

D14008 AEooo325 U00096

HPK Ib. hybrid, H2-domnin 702-935 of total 1197

Escherichia coli

61033145eco

AEooo342 uooo%

HPK 3c

u36841

25-91

2

r

'G122

958-1076

D

z

0

c rn n n

a

< !JJ

of total 496

Escherichia coli

HvdH eco

HydG eco

M28369

HPK 4 235-455 of total 465

R A4

5-123

v)

I

x

Escherichia coli M36066

Escherichia coli X65714 D90875 M94724 AM00333 U00096

Escherichia coli X69189 X13360 X15996 X65715 D90757

Escherichia coli X05173 L19201 AM00462 U00096

Escherichia coli X83541

Escherichia coli D90393 AJ300213 Uooo%

KduD eco

KdDE eco

654-882 of total 894

RAl 1-1 18

kbEQXx3

NarP eco

NarL eco

351-556 of total 566

R Cl 6-126

R Cl 6-126

NarX eco

NarL eco

NarP eco

38CL585 of total 598

R Cl 6-126

R CI 6-126

NtrB eco

NtrC eco

12CL346 of total349

RA4 3-121

Pcos eco

PcoR eco

238-4155 of total 466

RAl 1-1 19

Phd)eco

PhoP eco

HPK l a

HPK 7

HPK 7

HPK 4

HPK 2a

HPK 3a

258-479 of total 486

Escherichia coli

U73857 X04704 AM00146 UOOO96

Escherichia coli M28242 L11272

Escherichia coli

U41101 AM00256 Uooo%D90804 D90803

Eschenchia coli X94231 X78195AEOOO201 Uoo096

I rn

1-118

PhoB eco

194422 of total 43 1

RAl 2-122

RcsC eco

HPK lb.. hvbrid ,

RcsC RR eco

RcsB eco

444-673 of total 933

RBI 808-926

RE 3-126

RstB eco

RstA eco

202425 of total 433

RA2 4-121

Tors eco

Tors RR eco

TorR eco

R 83 67 1-790

RAl 2-119

HPK 26

HPK l b , hybrid H2-domain 424-65 1 of total 904

W 5J

0

!i z xz

E;rn

RAI

WoR eco HPK l a

-I

Table 3 (continued)

Species (Accession)

Escherichia coli M17102L10328AE000444U00096

Escherichia coli uoooo7

Escherichia coli 1799791 D90868

Escherichia coli U28377

Fischerella sp. PCC 7605 U97518

Kinase

Regulator(s)

( S ~ f ~ ~ Y ) (aa range of kinase domain)

(SUbfamibJ (aa range of receiver domain)

UhDB eco

R CI

2944% of total 500

1-124

YehU eco

YehT eco

363-561 of total 561

R C3 6130

YehUl eco

0

UhDA eco

HPK 7

HPK 8

Q)

MrkE eco

HPK 8

R C3

346-550 of total 559

1-120

YgiY eco HPK 20

RAI

227449 of total 449

1-118

G882555 eco

62160761fbu

HPK lai

58-295 of total 308

Fremyella diplosiphon U59741

Glomerella cingulata u77605 w7606

Haemophilus injluenzae U32707 LA2023

c)

HPK lai 41 1-646 of total 655

RcaCn fdi

RA2

RAl 1-125

W

Chkl pci

Chkl RR gci

101-34Ooftotal745

RBI 64%745

HPK Ib, hybrid

3124

U32713 LA2023

rn rn

D

z

0 L

rn n

?

HPK Ib

m

NarOhin

NarP hin

354-563 of total 567

R CI 4-124

HPK 7

D

n

ArcBhin 112-325 of total 325

Haernophilus infuenzae

r

RcaF fdi

RcaE fdi

cn -I

0

0

x

Haemophilus influenzae

PhoR hin

PhoB hin

U32818 LA2023

HPK IA I8W14 of total 425

RAI 2-121

Haemophilus influenzae

YpiX hin

U32843 LA2023 225-45 1 of total 45 1

RA1 1-118

Halobactenurn salinarum

CheA hss

CheY hsa

X82645

HPK 9 348-539 of total 668

R C2 2-120

-I

I rn

CheB hsa

R CS

1-121

Halobacterium sp. NRC-I

H0337 hSD

H0337 RR h w

2822308

HPK 6, RR-HK 707-913 oftotal 917

RF 92-2 14

Helicobacter pylon

CheA hDy

CheA RR hpv

CheY hpy

AE000555 AMOO5l 1

HPK 9, hybrid 324514 of total 803

RA2 676-803

R A3 1-124

Helicobacter pylon'

62314530 h y

G231453 1 hvv

A m 3 6 AEOOO511

HPK 3a 181-392 of total 397

R A4 3-123

Herbaspirillum seropedicae

NtrB hse

NhC hse

AFO82873

HPK 4 128-363 of total 363

R A4 1-128

Klebsiella pneumoniae

CitB kun

U31464 331-539 of total 547

R C4 3-123

Klebsiella pneumoniae

PhoR kvn

PhoB kpn

M31794

HPK l a 194-422 of total 431

RAI 2-122

Lactobacillus plantarurn CI I

PlnB ID1

PlnC lpl

PlnD lpl

X94434 X75323

HPK 10 235-442 of total 442

RD 1-129

RD 1-129

Species (Accession)

Lactobacillusplantanun LPCOlO Y15127

Kinase

(Subfamily) (aa range of kinase domain)

PlsK ID1 HPK 10 2 1 9 2 6 of total 426

Lactobacillus sake Lb706 221855

Regulator@) (Subfamily) (aa range of receiver domain)

PlsR ID1 RD 4-129

SakBISa

HPK 10

1 9 9 3 0 of total 430

Lactobacillus sake LTH 673 248542 AFOO2276

SDDKIsa

HPK 10

223-448 of total 448

Lactococcus lactis 6F3 x76884

Lactococcus lactis subsp. cremoris

NisK Ila

NisR lla

219-447 of total 447

RAI 1-126

HPK 3c

LIkiIlAUa

us1166

HPK la

Lactococcus lactis subsp. cremoris

LlkinB Ila

U81485 2182990

SpDR Isa RD 1-121

257-490 of total 4W

HPK la

294-517 of total 517

Lactococcus lactis subsp. cremoris US1486

LlkinC Ila

HPK

In

21-58

Lactococcus lactis subsp. cremoris U81487

of total 475

LlkiIlDIla HPK 7

121-326 of total 332

Lactococcus lactis subsp. cremoris US1488

Llkineorfl Ila

HPK la

220441 of total441

m

Listeria monocytogenes X76170

CheA lmo HPK 9

~~~

~~

295486 of total 618

Methanobacterium thermoautotrophicum AE000882 AE000666

CheY Imo

-I

RC 2 1-1 19

rn

I

MTH1124 mth HPK I 1

171-348 of total 348

Methanobacterium thermoautotrophicum AE000801 AE000666

-0

n

MTH123 mth

0

HPK I 1

dz

146356 of total 356

Methanobacterium thermoautotrophicum AE000892 AE000666

MTH1260 mth HPK 11, IR for HI

146354 iftotal 354

Methanobacterium thermoautotrophicum AE000805 AE000666

MTH174 mth HPK I 1

577-785 of total 785

Methanobacterium thermoautotrophicum AE000814 AE000666

MTH292 mth HPK I 1

357-564 of total 564

Methanobacterium thermoautotrophicum AE000821 AE000666

MTH356 mth HPK 11

362-567 of total 567

Methanobacterium thermoautotrophicum AE00082 1 AE000666

MTH360 mth HPK I 1

486700 of total 700

Methanobacterium thermoautotrophicum AE000828 AE000666

Methanobacterium therrnoautotrophicum AE000829 AE000666

MTH444 mth

MTH445 mth

142-369 of total 373

RH 4-134

MTH446 mth

MTH447 mth

371-583 of total 583

Unclassified (Mth447D01) 1-121

HPK 3h

HPK I 1

Species (Accession)

Methambacterium thermoautotrophicum AEooo830 AM00666

Methanobacterium themautotmphicum AEooo831 AEooo666

Kinase

Regulator@)

(Subfamily) (aa range of kinase domain)

fSUbfom2yJ

(aarange of receiver domain)

MTH459 rnth HPK 11

288-495 of total 495

MTH468 mth HPK 11 350-554 of total 554

Methambacterium thermoautotrophicum AEooo843 AM00666

Methobacterium themautotmphicum AEooo859 AEooo666

MTH619 rnth HPK I 1

539-749 of total 749

MTH823 rnth HPK I1

494-677 of total 677

AEooo865 AEooo666

MTH901 rnth

MTHW1 RR mth

HPK 11,RR-HK 139-352of total 352

3-124

Methanobacterium thermoautotmphicurn

MTHW2 rnth

MTH901 rnth

HPK 11 2.54-462 of total 462

5125

Methanobacterium themautotmphicum

AEooo865 AEooo666

Methanobacterium themautotmphicum AEOOO872 AM00666

Methylobacterium organophilum U18290 1586734

Mycobacterium tuberculosis 273101 24401 13 299494

Unclassified (Mth4471901)

Unclassifid (Mth447hW)

MTH985 rnth HPK I1

150-365 of total 365

MxcO mor HPK 7

26 1467 of total 495

3Oc mtu

31c mtu

HPK 2a

RAI

221-146 of total 446

1&134

...

z

r

Mycobacterium tuberculosis m22121

Mycobacterium tuberculosis 2072665 295120AL123456

El264624 rntu

HPK la

237465 of total475

El264625 mtu

2m

RAI

z fn

8-127

=! 0

G2072665 mtu HPK I 1

Z

283-501 of total 501

Mycobacterium tuberculosis U14909295121 a1234 5 6

Mycobacterium tuberculosis 280226 a123456

Mycobacterium tuberculosis Y13628 277162 a 1 2 3 4 5 6

Mycobacterium tuberculosis U88959 292539 P96368 a 1 2 3 4 5 6

Myxococcus xanthus M35192

Myxococcus xanthus L39904

MtrB rntu HPK la

RAI

286-520 of total 567

5-127

PhoR mtu

PhoP mtu

HPK la

19-146

SenX3 rntu

ReeX3 mtu

HPK l u

RAl

148-376 of total 410

1-120

TrcS mtu

TrcR mtu

HPK la

51-175

FnE m a

FrzE RR m a

AF029787

R A3

316507 of total 777

658-777

Pils mxa

PilR m a

HPK 4

R A4

4-122

Sass mxa HPK 4

2 6 H 8 2 of total 497

Myxococcus xanthus DK.5090 U20214

LkfzbEa HPK 3g,RI-HK 139-385 of total 385

z

41 Ei Z

xZ

$ rn

R A1

26a-499 of total 509

HPK 9. hybrid

-0

RAl

2 M 9 of total 485

306-525 of total 525

Myxococcus xanthus DKlOl

rn

MtrA mtu

AseA RR m a RF

7- 120

Frzzi m a Wnchsified 1-126

Table 3 (continued)

Species (Accession)

a

Kinase (Subfamily) (aa range of kinase domain)

(SGWlY)

(aa range of m i v e r domain)

Neurospora crassa

Nikl ncr

Nikl RR n a

u50264

HPK l b , hybrid 699-935 of total 1281

RBI 10851210

Paracoccus denitnjkans

E& !&

ms RRpde

MoxY pde

MoxX pde

AJ223460 PDAJ3460

Paracoccus denitriJicans M92421

HPK 3d 75303 of total 441 HPK 7 225439 of total 446

m m

Rermlatods) ._

RG 324441 RE

IS134

Proteus rnirabilis

RcsC Dmi

RcsC RR pmi

RcsB pmi

AFO71215

HPK l b , hybrid 3 1-247 of total 507

RBI 396-507

RE %I24

Proteus vulgaris

NtrB DVU

NtrC pvu

X68129

HPK 4 120-348 of total 348

R A4 3-121

Providencia stwm'i

AarGpst

AarR Dst

AFO41833

HPK 3a 256-485 of total 485

R A1 1-82

Pseudomom aeruginosa

LUz€?@ HPK 8

1542971 U50713

156358 of total 358

AlgR pae R C3 1-123

Pseudomom aeruginosa

CheAY m e

ChpA RR

CheB pae

U79580

HPK 9 1151-1339 of total 1638

R A3 1515-1636

6-122

Pseudomonas aeruginosa

LemA -me

L e d RR pae

AFO303.52

HPK Ib, hybrid, H2-domain 274-510 of total 925

RBI 664-78 1

Unclarsified

m

PilR Dae

Pseudomonas aeruginosa 212154 L22436

Pseudomonas aeruginosa

300-526 of total 530

R A4 3-130

Pi15pae

PirR pae

AF05 1692

HPK 2 b 224442 of total 458

Pseudomom aeruginosa FRDI

KinB Dae

RAl 9-132

AleB pae

u97063

HPK l a 3 6 5 9 5 of total 595

R A4 8-136

Pseudomonas aeruginosa PAK

FleS w e

HeR Dae

LA1213

HPK 4 172-365 of total 402

R A4 2-120

Pseudomonas aeruginosa PA0

PfeS oae

PfeR pae

Lo7739

HPK 26 225-446 of total 446

R A1 77-201

Pseudomonas fluorescens

COlS Dfl HPK 20 202425 of total 425

ColR pfl

YO9798

Pseudomonas fluorescens

L2-2

L29642

Dfl HPK la, hybrid 191-575 of total 575

Pseudomonas fluorescens

StvS Dfl

R A1 1-124

L29642 RR Dfl R A3 449-568

StyR pfl

AF024619

HPK 4 280-51 1 of total 522

R A4

Pseudomonas fluorescens v-5

4-121

Alxkw!

ApdARRpfl

U30858

HPK lb. hybrid, H 2 - d o m i n 275-510 of total 917

RBI -790

Pseudomonas putida

CheA DPU HPK 9 415-605 of total 747

CheY ppu

CheB Dpu

RA3 1-124

R C5 2-125

AFo31898

Table 3 (continued)

Species

(Accession)

Pseudomonas putida U72354

-. Kinase

Regulator(s)

(Subfmily)

(S~familyl (aa range of receiver domain)

(aa range of kioase domain)

Tods pDU HPK 4

741-971oftotal978

Pseudomonas solanacearum u02041

VsrA DSO

AH31161

Pseudomonas sp. Y2 AJKKJ330

VsrD DSO

264473 of total 502

1-127

VsrB RR Dso

253-483 of total638

Pseudomonas sp. VLBl20

R A4 25-146

R CI

L21173

swkEsk!

RF

510-631

R A4

from partid sequence

4-128

HPK la hybrid 175405 of total982

vsrc DSO

Unclassified 5-130

StdR psp

HPK 4

€tYum!

a0

TodT DVU

HPK 7

Pseudomom solanacearum

Q,

stys RR psg RA2 451-570

stx€LIm HPK 4

741-971 of total 982

Pseudomonas syringoe P". glycinea U33326

Cors Dsv HPK 3d 19-27

Pseudomonas syringae pv. syringae AFoo1355

Pseudomorns syringae pv. syringae M80477

of total 434

HpkY -DSV

CorR Dsv RG 1-120

G2078566 Dsv

4 ~~.

HPK

RF

103-342 of total 342

1-1 19

LemA Dsv

L e d RR psy

265-500 of total 907

RBI 656784

~~

HPK Ib.. hvbrii H2-domain ,

D z

0

Pseudomoms syringae pv. tomato LO5176

coDsDsv HPK 20 226456 of total 487

CopR psy RAI 1-1 19

-I

I rn

Pseudomnas tolaasii

WeN Dto

PheN RR pto

u95300

HPK Ib. hvbrid, H2-domain 7 1-305 of;otal706

RBI 46-585

Pseudomoms viridiflava

PelY ~ v i

PelY RR pvi

-0

L30101

HPK Ib, hybrid, H2-domain 2.54489 of total 896

R Bl 644-772

i

Pyrococcus horikoshii

CheA pho

CheY pho

AP000002 MOO9481

HPK 9 438-628 of total 766

R C2 1-120

Ralstonia eutropha X98451 M26073 S51060 X67305

Ralstonia eutropha

c z c s reu

CzcR reu

HPK 2a 22-52 of total 475

R A1 1-117

H o d reu

HoxA reu

U82564

HPK 3g 201-457 of total 622

Rhizobium leguminosarum

DctB rle

DctD rle

X06253

HPK 4 396-622 of total 622

RA4 5-126

Rhizobium leguminosarum

F d rle

FixL RR rle

270305

HPK 4 , hybrid 2614% of total641

Rhizobium leguminosarum

RF 5-126

RF 521-641

PODOrle

PopP rle

X89983

HPK 3a 236-379 and 392467 of total 467

RAI 1-1 19

Rhizobium meliloti

ActS m e

L39938

HPK 3e 200-419 of total 433

L l G 3 u m R A4 21-138

W

0

v,

Table 3 (continued) Species (Accession)

4

Kinase

Regulator(s)

(Subfamily) (aa range of kinase domain)

(Subfamily) (aa range of receiver domain)

4

0

Rhizobium meliloti

CheA rme

CheYI m e

U13166

HPK 9 416-4335 of total 758

RA3

RC

2-121

4-128

Rhizobium meliloti

JktB m e

!2ah?s

J03683

HPK 4 41 1 4 3 6 of total 636

R A4 4-125

Rhizobium meliloti

ExoS m e

ChvI m e

AF027298

HPK 36 331-568 of total 577

R A1 1-123

Rhizobiurn meliloti

ExsG m e

ExsF m e

2808506 AJ225561

HPK 11 700-912 of total 912

7-124

Rhizobium meliloti

FigL m

FixJ rmg

J03 174 221854

HPK 4 266-494 of total 505

e

Rhizobium phaseoli

NtrB roh

X7 1436

HPK 4 131-363 oftotal 383

Rhodobacter capsulatus

w2ba

X64733 446774

HPK 4 420-649 of total 657

CheB m e

UncrosSified

R A4

3-124

DctR rca R A4

2-125

Rhodobacter capsulatus BIO

HuDT rca

Lo2348

HPK 3g 1 9 H 5 6 of total 456

Rhodobacter capsulatus SB1003

NtrB rca

NtrC rca

X72382 L11718 X12359

HPK 4 12 1-350 of total 356

R A4 2-123

c rn

n n ID

<

m

+

v)

8 iT

Rhodobacter capsulatus SB1003 L35179

IbmGa HPK 3e

Rhodobacter sphaeroides

RegA rca

-I

R A4 11-135

rn

I

CheY rsh

X80027 349-475 of total686

R A3 2-122

Rhodobacter sphaeroides

CheAII rsh

CheY rsh

CheB rsD

No00977

HPK 9 32C-509 of total 654

R A3 2-121

R C5 9- 134

Rhodobacter sphaeroides

DorS rsh

DorS RR rsh

DorR rsh

AFO16236

HPK I b , hybrid H2-domain 305-539 of total 815

R Bl 558-684

RAI 4-130

Rhodobacter sphaeroides

HuDT rsh

L37 195

HPK 3g 1 8 7 4 3 of total 443

Rhodobacter sphaeroides

PrrB rsh

PrrA rsh

U22347

HPK 3e 202430 of total 462

R A4 12-135

Rhodococcus sp. M5

BpdS rsp

BpdT rsp

U85412

HPK 7 137C-1576 of total 1576

R CI 1-122

Rhodospirillum centenurn SW

CheAY rce

CheA RR rce

U64519

CheY rce

HPK 9, hybrid 277468 of total 901

R A3 77&901

R A3 1-121

Rifia pachyptila endosymbiont

RssA ma

RssA RR rpa

U91704

RssB 'pa

HPK Ib, hybrid 377412 of total 773

R BI 64s773

6-127

R A2

Saccharomyces cerevisiae

SLnl sce

Slnl RR sce

U01835

Sskl sce

HPK Ib, hybrid (insen) 557-701 and 849-925 of total 1220

R BI 1087-1213

R B1 503449

-.

Table 3 (continued)

Kinase Species (Accession)

(Subfamily) (Aa range of kinase domain)

AF060858

2 2 1 4 9 of total 454 M21279

Salmonella typhimurium L13395 L13394

(Aa range of receiver domain)

&!m!x

HPK 4 438-660 of total 668

I?mEbQ

HPK 20 13S356 of total 356

RAI 22-139

&!a?! Unclassified F128

PmrA sty RAI 1-123

SViR sty

U51927

HPK Ib. hybrid 38641 1 of total 823

RBI

ll.!wb&

IBubz?!

Schizosaccharomycespombe

E339934 SDO

E339934 RR spo

298918

HPK lb, hybrid 1744-1983 of total 2310

R Bl 2178-2310

Solanum lycopersicum

ERS slv

U38666

HPK l b 33S584 of total 635

Solanum lycopersicum

ETRl slv

U41103

HPK 16. hybrid 348402 of total 754

Staphylococcus aureus

Lyts sau

LytR sau

LA2945

HPK 8 ~.~ .~ .

R C3 1-124

M89480

ru

(Subfamil)

Salmonella typhimurium

Salmonella typhimurium

21

CoDR sdu

Salmonella dublin

Salmonella typhimurium

Regulator(s)

HPKT 2 9 4 4 % of total 500

370-584 of total 584

684-805

RCl 1-124

P0 c rn

ETRl RR sly RB1 627-748

-n n

2

m

Staphylococcus aureus KS154 U85096

Staphylococcus aureus RN4282 X52543

Staphylococcus epidemidis AFO12132

A g C sau HPK

10

NO00867

RD

220-430 of total 430

1-1 14

AgrCl sau

A g A 1 sau

221423 of total 423

RD 1-129

&dhl!

AerA sep

HPK 10

HPK 10

217.429 of total 429

Streptococcus constellam NCTC I1325

AmA sau

RD 1-127

ComD sct

HPK

10

228440 of total 440

Streptococcus gordonii U80077

c o d SQO

HPK 10

C O m E sgo RD

239-453 of total 453

Streptococcus gordonii Challis NCTC 7 X98109

Streptococcus gordonii NCTC 3165 No00870

C o d 1 seo

COmEl seo

240-453 of total 453

RD 1-123

HPK 10

c o d 3 SPO

HPK 10

240453 of total 453

Streptococcus gordonii NCTC 7865 X98110

COmD2 SEO HPK 10 239-452 of total 452

Streptococcus intemedius NCDO 2227 NO00869

COmE2 seo RD 1-1 17

ComD sin

HPK I0

229441 of total 441

Streptococcus pneumoniae R6 X77249

c i a SDn

CiaR spn

207-436 of total 444

1-120

HPK la

Species (AcceSSiOn)

Streptococcuspneumoniae R6 U33315 U76218

Kinase (ShfAyJ

(aa range of kinase domain)

caam!l HPK 10 215437oftotal441

Streptomyces coelicolor U51332

Streptomyces coelicolor DIM54

Streptomyces coelicolor -20958

Streptomyces coelicolor -22374

Streptomyces coelicolor -22374

AbsAl sco

AL031031

(aa range of receiver domain)

ComE spn RD 1-126

AbsA2 sco

HPK 7

R CI

183-389 of total 571

1-127

Afsoz sco

AfSOl sco

225-507 of total 535

RAl 1-1 19

HPK la

E1215U)l sco HPK 20

El215200 sco RAI

242467 of total 481

1-127

El286180 sco

El286181 sco

184-384 of total 384

9-134

El286185 sco

El286184 sco

HPK 7

HPK 5

334-541 of total 566

Streptomyces coelicolor

Regulator(s) (WfmW

R CI

R C4

1-122

El310290 sco

El310290 RR sco

El310292 sco

1356-1610 of total 1829

RBI 1707-1829

4-128

HPK I b, hybrid

Streptomyces coelicolor

El311959 sco

-31

R C1

107 183-395 of total 405

Streptomyces coelicolor -31

155

El313519 sco

HPK 7

208-421 of total 429

2-127

El313520 sco R CI

1-127

RA2

Streptomyces hygroscopicus NRRL 5491 X86780

am!E HPK 2a

175-399 of total 399

Streptornyces lividans 66 X58793

Synechococcus PCC7942 U70379

Synechococcus sp. PCC7942 D14056

sMm!Y

cuts sli

CUtR sli

18s.414 of total 414

RAI 1-125

HPK 20

y70379 SSD

G1575690 SSE

210-438 of total 438

R A1 1-120

HPK la

-I m

I

RAI 1-125

xz

€ixsl& HPK lai

D

142-379 of total 387

Synechococcus sp. PCC7942 D13172

Synechocystis sp. PCC6803 X72856

SDhS SSD

SphR ssp

160-396 of total 415

RAl 22-152

HPK l a

%

D ~ D svn A HPK la

413-657 of total 663

Synechocystis sp. PCC6803 D64006

Synechocystis sp. PCC6803 D90904AB001339

CheAY 1 svn

CheAY 1 RR syn

CheY syn

903-1093 of total 1402

R A3 1274-1397

R A2 1-1 19

HPK 9,hybrid

C h e A Y 2 svn HPK 9, hybrid 454644 of total 924

Synechocystis sp. PCC6803 D64001

C D h l ssp HPK 3h, phytochmme 5 19-745 of total 748

Synechocystis sp. PCC6803 D63999

Sll0337 svn

HPK la

188421of total 430

CheAY2 RR ssp RA3 199-924

Rcpl ssp RH 8-141

Species (Accession)

Kinase

Regulatorjs)

(Subfamily) (aa range of kinase domain)

(SqmiW (aa range of receiver domain)

Synechocystis sp. PCC6803

sn0474S

D&u)(L1AB001339

HPK l b 4-50

Synechocystis sp. PCC6803 D64ooo

V ~

of total 806

€NO750svn h!PK l a i 147-383 of total 383

Synechocystis sp. PCC6803

wo7mSvn

S110789 svn

D64005

HPK l a 2-3 of total 458

RA1

Synechocystis sp. PCC6803

SII0798 svn

Sll0797 svn

D64005

HPK la

RAI

2 1 U 5 of total 454

1-122

1-122

Synechocystis sp. PCC6803

Slll003 spn

D90902

HPK l a 428661 of total 661

Synechocystis sp. PCC6803 D90905 U67397

sn1124 m

Synechocystis sp. PCC6803

sll1228m

S111228 RR svn

1653170D90911

HPK lb, hybrid 153-392 of total 663

RBI 417-540

HPK l a 1157-1367 oftotal 1371

Synechocystis sp. PCC6803 m

7 590-829 of total 998

Synechocystis sp. PCC6803

Sll1475 svn

D90916

HPK l a 59-287 of total 297

m

Synechocystis sp. PCC6803 m 1 0

SL11590 syn

HPK 3f 112-350 of total 350

S111592 svn

-I

R CI 7-127

rn

Synechocystis sp. PCC6803

SU1672 syn

S111672 RR svn

D909oO

HPK Ib. hybrid 365-602 of total 834

RBI 629-750

Synechocystis sp. PCC6803

SU1871 SM

Slr1982 syn

m 1 2

HPK l b 428-663 of total 671

4123

Synechocystis sp. PCC6803

su1888 SYll

m 1 2

HPK Ib 185432 of total 432

Synechocystis sp. PCC6803 m 1 0

su1905 m

Sll1905 RR2 svn

S111905 RRl svn

RBI

R A2

739-855

17-139

slro210 SM

D64002

HPK l b 190-407of total 417

Synechocystis sp. PCC6803

slro222 m

Synechocystis sp. PCC6803 D64005

Synechocystis sp. PCC6803 D63999

S111673 svn

R A2 8-13]

HPK l b , hybrid 311-542oftotal1014

Synechocystis sp. PCC6803

D64ooo

I

HPK la,hybrid 930-1162oftotal1178

SlrO311 sp

HPK 7 550-759 of total 759

Slro322 syn

HPK 9,hybrid 432-622 of total 1095

Synechocystis sp. PCC6803

slro484 syn

D64001

HPK Iai 404-641 of total 675

SM222 RRn syn Unclassified 5-126

SM312 svn R C1 6-132

SM322 RR svn

R A3 799-925

A

Table 3 (continued)

Species (Accession)

Synechocystis sp. PCC6803 D64006

Kinase

Regulator(s)

(Subfamily) (aa range of kinase domain)

(Subfrn.lYl (aa range of receiver domain)

slro533 svn HPK l a 168-405 of total 405

Synechocystis sp. PCC6803

sLr0640 S

D64CKJ2

HPK 3b 18-35 of total 441

Synechocystis sp. PCC6803

Slr1324 svn

LBO911

HPK l a 178407 of total 420

Synechocystis sp. PCC6803

Slr1393 svn

D90904

HPK Ib (insert) 717-751and768-962oftotal974

Synechocystis sp. PCC6803

Slr1414 svn

D909oO

M

HPK 3f [Rfor HI 195-422 of total 437

Synechocystis sp. PCC6803

Slr1759 svn

D90903

HPK Ib, hybrid 768-1014 of total 1462

Synechocystis sp. PCC6803

Slr1805 svn

Slr1759 RR2 syn

Slr1759RRI syn

RBI 1139-1305

R 83 1033-1 I50

S111708 svn

HPK 3f 517-749 of total 749

R CI

Synechocystis sp. PCC6803

Slr1969 svn

Slr1969 RR svn

D90912

HPK l a hybrid 369-656 of total 750

631-750

D90908

11 OD

13-142 Unclawified

Synechocystis sp. PCC6803

Slr2098 svn

Slr2098 RR svn

Slr2099 svn

LBO910

HPK Ib, hybrid 517-751oftotal1261

R 83 7704%

RA2 1&134

Synechocystis sp. PCC6803

Slr2099 spn

Slr2100 svn

m 1 0

HPK l a i 134-366 of total 366

R A2 10-127

Synechocystis sp. PCC6803

Slr2104 svn

Slr2104 RR svn

m 1 0

HPK Ib, hvbrid 448-682 of total 950

RA2 717-836

Thauera TI

n t c 1 ttl

TutC RR ttl

TUBttl

u57m

HPK l a . hybrid 171404 of total 979

R A2 449-567

RA4 7-127

Thauera TI

n t c 2 ttl

(seeTutcl-ttl)

HPK 4 738-967 of tOmI 979

Thermotoga maritima

CheA tma

CheY mta

U30501

HPK 9 348-539ofIotal671

RC 2 2-120

Thermotoga maritima

HD~A tma

DrrA tma

U67196

HPK l a 17W12 of total 412

RAl f129

Thiobacillusferrooxidans ATCC 33020

NtrB tfe

NtrC tfe

L18975

HPK 4 127-352 of total 361

R A4 1-123

Treponema denticola

CheA Me

CheY tde

.GO74950

HPK 9 500-4547 of total 801

R C2 24- 145

Treponemapallidurn

CheA tDa

CheY tpa

U61851 AEoo1215 AM00520

HPK 9 4 7 M 5 9 of total 812

R C2 24-144

vibrio alginolyticus NCIB 1I038

NtrB val

NtrC val

m8499

HPK 4 120-348 of total 348

R A4

Table 3 (continued)

Species (Accession)

2

Kinase

Regulator(s)

(Subfmily) (Aam g e of kinase domain)

(Subfamily) (Aarange of receiver domain)

Kbrio cholerae

FlrB vch

FlrC vch

AFO14113

HPK 4 116-337oftotal351

R A4 3-125

vibrio cholerae

WoR vco

PhoB vco

AFo43352

HPK l a 196-426 of total 433

RAI 2-1 25

vibrio harveyi

Lux0 vha

L u x O RR vha

urn069

HPK Ib. hybrid 473-710 of tntal859

R RI

Xanthomom campestris pv. campestris

RDfC xca

RpfC RR xca

SwissPmt: P49246

HPK Ib, hybrid, H2-domain 130-364 of total 677

R B1 412-536

Xanthomom oryzae pv. oryzae

RaK xor

RDfC RR xor

X97865

HPK l b , hybrid H2-domain 130-363 of total 676

410-536

OD

0

L u x O vha R A4 1-124

20

RBI

Xenorhubdus nematophilus

EnvZ m e

om& me

urn746

HPK 26 116-342 of total 342

RAI 4128

GI rn

W

m rn

THE HISTIDINE PROTEIN KINASE SUPERFAMILY

181

Table 4 Major prokaryotic divisions. Names underlined indicate divisions with reported histidine kinases. The classification is based on the taxonomy homepage at the American National Center for Biotechnology Information

Archaea Crenarchaeota Pyrodictiales Sulfolobales Thermoproteales Unclassified Crenarchaeota Euryarchaeota Archaeoelobales Halobacter ides Methanococcales (Methanococcusjannaschii) Methanomicrobiales Methanopyrales Thermococcales Thennoplasmales Unclassified Euryarchaeota Korarchaeota Environmental samples Unclassified Archaea Halophilic archaea Environmental samples

Eubacteria Aauificales

ChlamydialesNermcomicrobia group Coprothermobacter group Cyanobacteria (blue-green alcael C y t o p h a J m w Fibrobacter/acidobacteriumgroup es (Gram-oositive bacterid Flexistipes group Fusobacteria Green non-sulfur bacteria Holophaga group Nitrospira group Planctomycetales Proteobacteria Synergistes group Thermodesulfobacterium group Thermotogales Thermus/deinococcus group Unclassified Eubacteria

182

THORSTEN W. GREBE AND JEFFRY B. STOCK

human and plant pathogens as well as biotechnologicallypromising organisms such as extremophiles.The number of histidine kinases within different organisms can vary substantially - from 0 in Mycoplasma genitalium (Fraser et al., 1995) and Methanococcus jannaschii (Bult et al., 1996) to more than 30 in Bacillus subtilis (Kunst et al., 1997) and Synechocystis (Kaneko et al., 1996; Mizuno et al., 1996). Organisms that can live in a wide range of different environmental conditions appear to be equipped with larger sets of histidine kinases, which often function as sensors for changing environmental parameters. Being able to survive in sewers, intestines, blood plasma and almost any type of nutrient broth, E. coli sports some 30 sensor protein kinases (Blattner et al., 1997; Mizuno, 1997). Haemophilus injluenzae, a human pathogen, which specializes on warm-blooded hosts, has a restricted set of four identified histidine kinases, while Mycoplasma genitalium, an obligate parasite that lives in a practically constant environment, has a genome that appears totally to lack histidine kinase homologues. 1.3. System Design

In recognition of the two conserved protein superfamilies of His-Asp phosphorelay systems, they have been termed two-component regulatory systems (Ronson et al., 1987b), despite the fact that other, relatively diverse elements of protein structure, are invariably involved. Nevertheless, in their simplest form, these systems comprise only two proteins, a histidine protein kinase and a response regulator. The histidine kinases typically contain two functionally and structurally distinct parts, a variable N-terminal sensor region and a conserved C-terminal kinase core domain that features the phosphoaccepting histidine as well as the so called homology boxes. The latter are highly conserved sequence fingerprints that serve to define the family (Stock et al. 1988; Parkinson and Kofoid, 1992). Some kinases lack the sensing domain, e.g. the chemotaxis kinase CheA where sensing has been outsourced to a distinct class of chemoreceptors, termed MCPs (Adler, 1969; Kondoh et al., 1979; Grebe and Stock, 1998); and NtrB, where an auxiliary protein, PI,, relays information on the status of cellular nitrogen metabolism (Brown et al., 1971;Adler et al., 1975; Ninfa et al., 1995; Jiang et al., 1998a,b).A few additional examples of kinases that appear not to have sensing domains have been found through sequencing projects over the last few years, including G2313251-hpy (Tomb et al., 1997), G2649099-afu (Klenk et al., 1997), and probably G953193-pae (Hachler et al., 1996). Despite the fact that the first two histidine kinases identified, NtrB and CheA, exhibited this characteristic, kinases without sensing domains are extremely rare. Because they lack transmembrane sensors, NtrB and CheA are soluble proteins and, therefore, they are relatively easy to purify and characterize.

THE HISTIDINE PROTEIN KINASE SUPERFAMILY

183

Response regulators generally contain at least two functional domains: a phospho-aspartyl receiver domain that interacts with the kinase domain of a cognate histidine protein kinase, and one or more output domains, . Response regulators most commonly transcription factors with output domains that bind DNA. About 25% of all response regulators have no output domain, however, and a few output domains have been identified with enzymatic activities, e.g. CheB of the chemotaxis system is a protein methylesterase (Stock and Koshland, 1978) and RegA from Dictyostelium is a CAMPphosphodiesterase (Shaulsky et al., 1998). The sensing domains of the histidine protein kinases regulate the rate of autophosphorylation. The phosphorylated kinase in turn interacts with the receiver domain of its cognate response regulator, donating its phosphorylgroup to an invariant aspartate in the receiver domain. A phosphorylationinduced conformational change in the receiver is thought to modify the activities of associated response regulator output domains. Phosphorylation of response regulators with no output domains are thought to cause changes in affinity for target effector proteins, e.g. phosphorylation of CheY causes this isolated receiver domain to bind to the flagellar motor switch to cause a change in swimming direction that leads to chemotaxis (Welch et al., 1993; Alon et al., 1998; Scharf et al., 1998). There are other examples, however, where isolated receiver domains appear to function solely to pass phosphoryl groups between histidines in more complicated phosphorelay systems. For example, SpoOF in the Bacillus subtilis sporulation system passes phosphoryl groups from a histidine in the kinase KinA to a histidine in SpoOB (Hoch, 1995; Tzeng and Hoch, 1997). Phosphatase activities also play critical roles in regulating response regulator phosphorylation. They can be either located within the receiver domain, e.g. CheY (Sourjik and Schmitt, 1998) CheB (Stock and Surette, 1996), in the kinase domain, e.g. EnvZ (Igo et al., 1989; Kanamaru et al., 1989; Yang and Inouye, 1993; Dutta and Inouye, 1996) or require additional proteins, e.g. CheZ in chemotaxis (Hess et al., 1988b), and RapA, B in sporulation (Hoch, 1995; Reizer et al., 1997). Apart from the conserved kinase domain, histidine kinases vary substantially in design. They can be membrane bound or soluble, e.g. EnvZ is an integral membrane protein with two transmembrane helices framing a periplasmic sensing domain (Forst et al., 1987 and KinC of B. subtilis (Kobayashi et al., 1995; LeDeaux and Grossman, 1995) has two transmembrane helices but lacks an extended periplasmic domain. Kinases with four predicted transmembrane helices include KdpD (Zimmann et al., 1995) and FixL (Lois et al., 1993). Based on its hydrophobicity profile, there are at least eight transmembrane helices in UhpB (Friedrich and Kadner, 1987; Kadner, 1995), whereas CheA (Ridgway et al., 1977), DegS (Henner et al., 1988; Kunst et al., 1988; Tanaka and Kawata, 1988; Msadek et al., 1990, 1995), KinA (Perego et

Figure I Sequence alignments for the individual histidine protein k i n a (HPK) subfamilies. Flanking sequences between H-, X-, N-, D-, F- and G-boxes have been removed. Light shading marks hydrophobic residues: A, C, F, I, L, M and V. Generally, dark shading indicates conserved residues. In the X-box,dark shading indicates conserved charged residues. Above the alignments of the individual groups: ‘.’ variable residue, ‘-’ represents D or E, ‘+’ K or R, and ‘h’ a conserved hydrophobic amino acid. ‘y’ indicates any of the structurally similar residues H, F or Y; ‘B’ is D or N. The X-box is only shown for those HPK subfamilies, HPK,,,for which it could ambiguously be defined through sequence comparisons. It is therefore not shown for H P q , , .

8

E

i

M

EJ!

iT

u 0

s

s'

8

i

Figure 1 cont.

192

THORSTEN W. GREBE AND JEFFRY B. STOCK

Table 5 Classification of kinases. Left = kinase group; right = name of protein; for three-letter sequence identifiers, see Table 1 HPK l a HPK l a HPK l a HPK la HPK la HPK l a HPK l a HPK l a HPK la HPK la HPK la HPK l a HPK l a HPK l a HPK l a HPK la HPK l a HPK l a HPK l a HPK l a HPK la HPK l a HPK l a HPK l a HPK la HPK l a HPK la HPK l a HPK la HPK la HPK l a HPK l a HPK l a HPK la HPK l a HPK l a HPK la HPK la HPK la HPK la HPK la HPK la HPK la, [Y for HI HPK la, [Y for HI HPK I& hybrid HPK la, hybrid HPK la, hybrid HPK la, hybrid HPK la, hybrid HPK la. hybrid HPK lai HPK lai HPK Iai

AfsQZ-sco BaeS-eco Cia-spn CyaC-w DspA-syn E1264624-mtu E307792Lcvi HpkAtma KdpD-cac KdpD-eco KinB-pi% LlkinA-lla LlkinB-lla LlkinC-lla Llkineorfl-lla MtrB-mtu

PhoR-bsu PhoR-eco PhoR-hin PhoR-kpn PhoR-mtu PhoR-vco ResE-bsu RprXbfr SenX3-mtu s110337-syn S110790-syn S110798-syn SII 1003-syn Slll124-syn S111475-syn Slr0533-syn Slrl324Lsyn SphS-ssp TrcS-mtu u70379-ssp Vans-efe Ycf26-por YclK-bsu YkoH-bsu YvrG-bsu YycG-hsu BdfA-bja DivL-ccr DhkD-ddi L29642-pfl Slr0222-syn Slr 1969-syn StyS I -psp TU~C 1-ttl G216076l-fsp RcaE-fdi

sars-ssp

s110750-syn HPK lai Slr0484-syn HPK lai Slr2099-syn HPK lai ArcB-hin HPK Ib HPK Ib Divl-ccr ERS-ath HPK Ib ERS-sly HPK Ih HPK Ib HepK-asp PleC-ccr HPK Ib S110474-syn HPK Ib s111353-syn HPK Ib SII 187I-syn HPK Ib SIII888-syn HPK Ib HPK Ib Slr0210-syn Slr1393Xsyn HPK Ih (Insert) HPK Ib, hybrid CaHKl-cal Chikl-cal HPK I b. hybrid HPK Ib, hybrid Chkljci HPK Ib, hybrid DhkA-ddi HPK Ib, hybrid DhkB-ddi HPK Ib, hybrid DhkC-ddi HPK Ib, hybrid DokA-ddi HPK Ib. hybrid El3 10290-sco HPK Ib, hybrid E339934-spa HPK Ib, hybrid ETR I -ath ETRI -sly HPK Ib. hybrid 132688313-bhu HPK 1b, hybrid HPK Ib, hybrid LuxQ-vha HPK Ih, hybrid Nikl-ncr HPK Ih, hybrid RcsC-eco HPK Ib, hybrid RcsCgmi HPK Ib. hybrid RssA-rpa HPK Ib, hybrid S111228-syn HPK I b, hyhrid S111672-syn HPK Ib. hybrid S111905-syn HPK Ib, hybrid slr1759-syn HPK Ih, hybrid Slr2098-syn HPK 1b. hybrid Slr2 I04-syn HPK Ih, hyhrid SpiR-sty HPK Ib, hybrid (insert) CaSLNl-cal HPK Ib. hybrid (insed) Slnl-sce HPK Ib, hybrid, H2 A@-pfl HPK Ib, hybrid, H2 ArcB-eco HPK Ib, hybrid, H2 BarA-eco BvgS-bpe HPK 1 b, hybrid, H2 HPK Ih, hyhrid. H2 DorS-rsh HPK Ih, hybrid, H2 EvgS-eco HPK Ih. hybrid, H2 LemA-pae HPK Ib. hybrid, H2 Led-psy HPK Ib, hybrid, H2 PelY-pvi HPK Ib, hybrid, H2 PheN-pto HPK Ih. hybrid, H2 RpfA-eca HPK Ib. hybrid, H2 RpfC-xca

HPK Ib, hybrid, H2 HPK I b, hybrid, H2 HPK Ic. hybrid HPK Ic. hybrid HPK Ic. hvbrid . .(noH-box) HPK 2a HPK 2a HPK 2a HPK 2a HPK 2a HPK 2a HPK 2a HPK 2a HPK 2a HPK 2a HPK 2a HPK 20 HPK 2a HPK 2a HPK 2a HPK 2a HPK 2b HPK 2b HPK 2h HPK 2b HPK 2b HPK 2h HPK 2h HPK 2b HPK 3a HPK 3a HPK 3a HPK 3a HPK 3b HPK 3b HPK 3h HPK 3c HPK 3c HPK 3c HPK 3c HPK 3c HPK 3d HPK 3d HPK 3d HPK 3d, hybrid, H2 HPK 3e HPK 3e HPK 3e HPK 3e HPK 3f HPK 31 HPK 3f, [R for HI HPK 3g

RpfC-xor Tors-eco CKI 1-ath G2708752-alh 2435516-ath 30c-mtu Bass-eco COB-pfl Cops-eco COPSJSY Cops-sdu Cuts-sli czcs-reu E1215201-sco IrlS-bps OrfS-shy PcoS-eco PmrB-sty KagB-hja YgiY-eco YgiY-hin CpxA-eco EnvZ-eco EnvZxne PfeS-pae PirS-pae QrsA-chu RisS-bav RstB-eco AarG-pst G2314.530-hpy PhoQ-eco PopQ-rIe ChvG-atu ExoS-mie Slm640-syn CreC-eco G1033145-eco NisK-lla SpaK-bsu YchA-bsu CorS-ps y FlhS-pde VsrB-pso RteA-hte Acts-rme PrrB-rsh Re@-rca Regs-hja SII ISYO-syn Slr1805-syn Slr1414-syn Hod-ahy

193

THE HISTIDINE PROTEIN KINASE SUPERFAMILY

Table 5 cont. HPK 3g HPK 3g HPK 3g HPK 3g. RKHK HPK 3h HPK 3h HPK 3h, phytwhrome HPK 3i HPK 3i HPK 3i HPK 4 HPK 4 HPK 4 HPK 4 HPK 4 HPK 4 HPK 4 HPK 4 HPK 4 HPK 4 HPK 4 HPK 4 HPK 4 HPK 4 HPK 4 HPK 4 HPK 4 HPK 4 HPK 4 HPK 4 HPK 4 HPK 4 HPK 4 HPK 4 HPK 4 HPK 4 HPK 4 HPK 4 HPK 4 HPK 4 HPK 4 HPK 4 HPK 4 HPK 4 HPK 4 HPK 4 HPK 4 HPK 4 HPK 4 HPK 4 HPK 4 HPK 4 HPK 4 HPK 4

Hod-reu HupT-rca HupT-rsh AsgA-mxa G2649082-ah MTH444-mth Cph I-ssp YtsB-bsu YvcQ-hsu YxdK-hsu AtoS-eco DctB-rle DctB-rme DctS-rca DegM-bsp FixL-aca FixL-bja FixL-me FleS-pae FlrB-vch G2688706-hbu HknA-bth HksPl-aae HksP2-aae HksP4-aae HpkY-psy HydH-eco HydH-sty KinA-bsu King-bsu KinC-hsu NodV-bja NuB-ahr NtrB-bpa NtrB-eco NtrB-hse NtrB-pvu NtrB-rca NuB-rph NUB-tfe NuB-Val NtrY-aca NwsA-bja PgtB-sty PilS-mxa PilS-pae Sass-mxa StdSc-psp StyS-pfl StyS2-psp TodS-ppu TU~C~-~I YkrQ-bsu YkvD-bsu

HPK 4, hyhrid HPK 4, hybrid HPK 4, hyhrid HPK 5 HPK 5 HPK 5 HPK 5 HPK 5 HPK 5 HPK 5 HPK 6 HPK 6 HPK 6 HPK 6 HPK 6 HPK 6 HPK 6 HPK 6 HPK 6 HPK 6 HPK 6, RR-HK HPK 7 HPK 7 HPK 7 HPK I HPK 7 HPK 7 HPK 7 HPK 7 HPK 7 HPK 7 HPK 7 HPK 7 HPK 7 HPK 7 HPK 7 HPK 7 HPK 7 HPK 7 HPK 7 HPK 7 HPK 7 HPK 7 HPK 7 HPK 7 HPK 8 HPK 8 HPK 8 HPK 8 HPK 8 HPK 8 HPK 8 HPK 9 HPK 9

FixL-rle VirA-atu VirAL-atu CitA-kpn DcuS-eco DpiB-eco E1286185-sco YdhF-bsu YflR-hsu YufL-bsu G2648416-afu G2648833-afu G26489 10-afu G2649045-afu G2649099-afu G2649399-afu G2649708Kafu (32649834-afu G2650174-afu G2650436-afu H0337-hsp AhsA I -sco BpdS-rsp ComP-hsu DegS-hhr DegS-hsu El 286180-sco El31 196O-sco E1313519-sco LlkinD-lla MoxY-pde MxcQ-mor NarQ-eco NarQhin NarX-eco SId31 I-syn UhpB-eco UhpB-sty VsrA-pso YdM-bsu YW-bsu YocF-bsu Yvfl-bsu YvqC-bsu YxjM-hsu AlgZ-pae LytS-bsu LytS-sau YehU-eco YehU 1-eco YesM-hsu YwpD-bsu CheA-ah CheA-hsu

HPK 9 HPK 9 HPK 9 HPK 9 HPK 9 HPK 9 HPK 9 HPK 9 HPK 9 HPK 9 HPK 9 HPK 9 HPK 9 HPK 9 HPK 9 HPK 9, hyhrid HPK 9, hybrid HPK 9, hybrid HPK 9, hybrid HPK 9, hybrid HPK 9, hybrid HPK 10 HPK 10 HPK 10 HPK 10 HPK 10 HPK 10 HPK 10 HPK 10 HPK 10 HPK 10 HPK 10 HPK 10 HPK 10 HPK 10 HPK 10 HPK I I HPK I I HF'K I I HPK I 1 HPK 11 HPK I I HPK I I HPK I I HPK I I HPK 11 HPK 11 HPK 11 HPK 11 HPK I I HPKII HPKII,[RforH] HPK I I , RR-HK

CheA-eae CheA-eco CheA-hsa CheA-lmo CheA-pho CheA-ppu CheA-rme CheA-rsh CheA-tde CheA-tma CheA-tpa CheA I-bhu CheA2-bhu CheAlI-rsh CheAY-pae CheA-hpy CheAYrce CheAYI-syn CheAY2-syn FrzE-mxa Slr0322-syn AgrC-sau AgrCdep AgrCl-sau CbnK-cpi ComD-sct ComD-sgo ComD-sin ComD-spn ComDl-sgo ComD2-sgo ComD3-sgo PlnB-lpl PlsK-lpl SakB-lsa SppK-lsa ExsG-me (32072665-mtu MTH 1 1 2 4 ~ 1 t h MTH 123-mth MTH174-mth MTH292-mth MTH356-rnth MTH360-mth MTH446-mth MTH459-mth MTH468-mth MTH6 19-mth MTH823-mth MTH902-mth MTH985-mth MTH I26O-mth MTH90l-mth

194

THORSTEN W. GREBE AND JEFFRY 6 . STOCK

al., 1989; Hoch, 1995)and NtrB (Chen et al., 1982;Ninfa et al., 1995) are soluble cytoplasmic proteins lacking transmembrane helices. An indication as to the origins of this remarkable diversity has been detected in DokA whose 1670 residues show no sign of transmembrane helices. Nevertheless, there are indications for former transmembrane stretches that might have been lost during evolution (Schuster et al., 1996). DhkA (Wang et al., 1996), which is believed to share a common ancestor with DokA still possesses prominent transmembrane domains. The basic two-component His-Asp phosphorelay mechanism is often embedded in more extensive phosphotransfer networks wherein the phosphoryl group is passed on to a second histidine and thence to a second aspartate. The first system with a four-member relay was discovered in B. subtilis, where it governs the events leading to sporulation (Burbulys et al., 1991). Other histidine protein kinases that feed into such multi-component phospho-relays are L e d (Hrabak and Willis, 1992) and its homologues PelY (Liao et al., 1994) and ApdA (Corbel1 and Loper, 1995), ArcB (Iuchi et al., 1990; Kato et al., 1997), BarA (Nagasawa et al., 1992), BvgS (Arico et al., 1989), DorS (Mouncey et al., 1997), KinA,B,C (Perego et al., 1989; Trach and Hoch, 1993; Hoch, 1995; LeDeaux and Grossman, 1995; LeDeaux et al., 1995), RpfA (Frederick et al., 1997),RteA (Stevens et al., 1992), Slnl (Ota and Varshavsky, 1993), StyS (Beltrametti et al., 1997; Velasco et al., 1998),Tors (Jourlin et al., 1996), and TutC (Coschigano and Young, 1997). These relays typically involve a domain of some 100 residues, termed an HPt- or H2-domain, that transfers phosphate via an active-site histidine from one receiver domain to a second receiver domain (Appleby et al., 1996; Kato et al., 1997). In some cases, the first receiver domain and sometimes the HPt-domain are encoded together in a single large polypeptide, termed a hybrid histidine kinase. Some 20% of all known histidine protein kinases belong to this class, termed here HPK,, (Fig. 1, Table 5 ) . All known eukaryotic histidine kinases belong to the HPK,, subfamily. Intriguing examples, from an evolutionary standpoint, are the osmosensing phosphorelays of the Slnl/Sskl (Maeda et al., 1994) and the EtrllCtrl (Clark et al., 1998) kinase pathways of yeast and Arabidopsis, respectively, in which modules of predominantly prokaryotic two-component signalling have been mixed with the exclusively eukaryotic mitogen-activated protein (MAP) kinase pathway (Posas et al., 1996;Wurgler-Murphy and Saito, 1997). The advantage of multicomponent phosphorelays is understood to lie in the opportunity to integrate incoming signals from different sources and prevent premature and potentially disadvantageous triggering of complex physiological processes.

THE HISTIDINE PROTEIN KINASE SUPERFAMILY

195

1.4. Homology Boxes

Members of the histidine protein kinase superfamily exhibit clusters of highly conserved residues that are presumed to play crucial roles in substrate binding, catalysis and/or structure. These characteristic sequence fingerprints have been termed homology boxes: the H-, N-, D-, F- and G-boxes (Stock et al., 1988, 1995; Parkinson and Kofoid, 1992). These sequences are generally most conserved in the largest of the histidine kinase subfamilies, HPK,, and HPKIb (Fig. 1, Table 5 ) . In other subfamilies these so-called boxes tend to be less conserved, and in some cases may be so distorted that they can only be identified through detailed sequence alignments (Fig. 2). The H-box contains the site of histidine phosphorylation. This histidine is generally located at the face of an a-helix within an up-down-up-down helix bundle (Kato et al., 1997; Zhou et al., 1997). A highly conserved proline at position 5 after the phospho-accepting histidine is almost invariable in HPK subfamilies 1 4 . In subfamilies 5-1 1, this proline tends to be missing (Fig. 2). The distribution of charged and hydrophobic residues around the phosphoaccepting histidine tends to be different for different subfamilies. In many cases these sequence features can serve as subfamily identifiers. In general, it is the homology boxes that define subfamilies, whereas flanking sequences tend to be highly variable even within subfamilies. There are individual kinases where the conserved H-box histidine has been replaced by aspartate (S110094-syn; see Fig. 2), tyrosine (DivL-ccr and BdfA-bja; see Fig. 2; and HPK,, in Fig. 1) or arginine (Mth1260_mth, see HPK,, in Fig. 1; and Slr1414-syn; see HPK,,in Figure 2). It has been experimentally shown that the substituted tyrosine in DivL of Caulobacter crescentus is phosphorylated (Wu et al., 1999). Other examples of histidine replacements at this position have only been identified through sequencing projects. It is interesting to note that S110094 of Synechocystis, which contains an aspartate instead of a histidine, also lacks the D-box (Fig. 1). Recent structural studies of the histidine protein kinase core have shed considerable light on the function of the other conserved regions (Tanaka et al., 1998; Bilwes et al., 1999). The D-box is part of the nucleotide binding domain and probably interacts with the amino group of the adenine ring. The G-box lies over the adenine nucleotide phosphates where it plays a critical role in phosphotransfer (Yang and Inouye, 1993; Stewart et al., 1998). A statistical analysis of the variability of amino acid residues at every position in histidine kinase multi-sequence alignments using Shannon’s entropy (Litwin and Jores, 1992) revealed a previously unrecognized stretch of conserved residues beginning approximately 30 residues downstream from the phospho-accepting histidine (Figs 1 and 3). The importance of this region was suggested by the observation that it was a mutational hot spot in EnvZ, termed the X-region (Hsing et al., 1998). Prior to this, the only mutation in this

Figure 2 Histidine protein kinase homologues with substitutedhistidmes.

THE HISTIDINE PROTEIN KINASE SUPERFAMILY

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location that had been reported in the literature was a change, P188Q, in NtrB that was picked as a suppressor of an N t r phenotype (Atkinson and Ninfa, 1993).From the effect of mutations in this region on the migration of EnvZ in SDS-PAGE, Hsing et al. concluded that this sequence plays an important structural role. Secondary structure predictions suggest that the X-box is largely a-helical. This region corresponds to the second a-helix of the dimerization domain recently described in EnvZ and CheA (Park et al., 1998; Bilwes et al., 1999).

2. HISTIDINE PROTEIN KINASE SUBFAMILIES

A multisequence alignment of 348 kinase domains reveals several distinct subfamilies. The PILEUP, DISTANCES and GROWTREE programs of the Wisconsin Genetics Computer Group (GCG) package were used for the alignment. PILEUP did not align all sequences in a single stack, rather it distributed them into different subgroups according to their degree of similarity. Figure 4 shows a simplified schematic of a PILEUP result. Categorization of the histidine protein kinases was based on the outcome of multisequence alignments with the parameters of the PILEUP program set at their default values (12 for gap creation, 4 for gap extension). Three types of kinase sequences could not be assigned: those with ambiguous subfamily affiliations, those with no apparent subfamily affiliation, and those that aligned only with one other sequence. According to these criteria, over 90%of all histidine protein kinases fell into one of 11 different subfamilies: HPK1-HPK,, (Tables 3 and 5 , Fig. 5). Some of these kinase groups, such as chemotaxis kinases ( H P K J , the competence kinases (HPK,,) or the methanobacterial kinases (HPK, ,) show very distinct sequence characteristics (Figure 2) that clearly distinguish them from all other histidine kinases. In other cases, e.g. HPK subfamilies 1-4, the boundaries are much more problematic. Genomic sequencing has shown that in some bacterial strains most of the histidine protein kinases belong to a single subfamily, e.g. in the archaea Archaeoglobusfulgidus (Klenk et al., 1997) 10 of 12 kinases belong to HPK, and in the archaea Methanobacterium thermoautotrophicum (Smith et al., 1997) 15 of 16 kinases belong to HPK,,. These findings suggest single independent lateral gene transfer events followed by radiation. Eukaryotes probably provide an even more extreme example of this, since essentially all known nonplastid eukaryotic histidine kinases belong to a single group, HPK,,. The situation is very different for B. subtilis (Kunst et al., 1997) and E.coli (Blattner et al., 1997; Mizuno, 1997). In these two organisms, the kinases are almost evenly distributed over 8-10 different subgroups (Fig. 1, Table 3).

Figure 3 Statistical evaluation of the variability of amino acid residues using Shannon’s entropy (Litwin and Jones, 1992). For every amino acid position in the multisequence alignment of 108 sequences of the major group of histidine kinases, HPK,,a variability value has been determined. No variability corresponds to 0, total variability to 4.3 (= all of the 20 amino acids are found with the same likelihood). Homology Boxes are indicated as H, X, N, D, F and G. For the other b a s e groups, (HPK,, ,), the profiles look similar but are not statistically as significant owing to the smaller number of available sequences.

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Figure 4 Typical outcome of a multi-sequence alignment.For both protein classes, histidine protein kinases and response regulators, the PILEUP program will not align all sequences in a single stack. Rather, it will split all sequences into different piles in accordance with their relatedness. For the kinase and response regulator classifications a stack of sequences with at least three members was considered a group. Sequencesthat would not align with any other sequence or those that aligned only with one other sequence were ignored.

2.1. Subfamilies of Histidine Kinases 2.1.1. HPK,

This is the most common type of histidine protein kinase. PhoR and most hybrid kinases, including all known eukaryotic histidine kinases, are members of this subfamily (Table 5 , Fig. 1). They exhibit all the characteristic HPK sequence fingerprints, i.e. the H-, X-, N-, D-, F-, and G-boxes: H-box: Fhxxh(S/T/A)H(D/E)h(R/K)TPLxxh X-box: conserved hydrophobicity pattern N-box: (D/N)xxxhxxhhxNLhxNAhx(F/H/Y)( S / T ) D-box, F-box: hxhxhxDxGxGhxxxxxxxhFxxF G-box: GGxGLGLxhhxxhhxxxxGxhxhxxxxxxGxxFxhxh where x is variable and h is any hydrophobic residue. There are no significant sequence features that could be used to distinguish between groups 1a and 1b. Subfamily I b is distinct, however, in that it contains almost all eukaryotic and hybrid kinases. The 1b sequences are very closely related to each other and, in multisequence alignments, they tend to cluster (Figs 1 and 5 ) . Another feature of the l b subgroup is a relatively conserved X-box and a virtually invariant motif, KFT, behind the second N of the N-box (Fig. 1). The residue that precedes the phospho-accepting H-box histidine, usually serine, threonine or alanine, in this kinase class tends to be a serine. The acidic residue distal to the histidine is generally a glutamate. The l b kinases also have a highly conserved glutamine at position 4 in front of the first asparagine of the N-box. This residue is not as prevalent in HPK,, proteins. The second residue after the F-box is a glutamine in HPK,, kinases, but an arginine in most HPK,, kinases. In HPK,, kinases, the 1lth residue following the third glycine of the G-box (GX-GLGL) is methionine. HPK,, proteins have a histidine at this position (Fig. 1).

Figure 5 Juxtaposition of kinase and receiver dendrographs. The left dendrograph graphically depicts HPK group affiliations as they can be derived from a multisequence alignments using PILEUP. DISTANCES and GROWTREE (GCG-package). The right dendrograph represents the result for an equivalent analysis of the receiver domains ot presumably cognate response regulators. In all cases where the association of a kinase with a response regulator was not known from the literature, it was based on their genetic linkage. Kinase-regulator pairs are usually encoded by adjacent genes. Lines connect each cognate two-component pair. CheA and orphan kinases have been removed from these dendrographs. The branch lengths do not represent phylogenetic distances.

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The kinase domains of the hybrid kinases Ckil-ath and G2708752-ath are about 280 residues long and thus some 50 amino acids longer than the average kinase domain. They did not align with other sequences but share strong sequence similarities in their boxes with other hybrid kinases of HPK,,. We have therefore classified these within a separate grouping, HPK,, (Fig. 1). 2.1.2. HPK,

The HPK, subfamily (Table 5 , Fig. 1) contains EnvZ, one of the most thoroughly investigated histidine kinases (Pratt & Silhavy, 1995; Egger et al., 1997;Tanaka et al., 1998).The H P q , subgroup is distinct from HPK,, in that these proteins have a phenylalanine six residues proximal to the phosphoaccepting histidine. Members of H P b , have a leucine or methionine at this position. The 2b group has an arginine at position 3 after the conserved proline of the H-box. This arginine seems to be diagnostic for group 2b since only one sequence of group 2a and no kinase from any other group has a positively charged residue at this position (Fig. 1). 2.1.3. HPK,

These kinases are very closely related to the HPK, and HPK, subfamilies, but do not clearly fall into either category(Tab1e 5, Fig. 1). In three of the four proteins of the HPK,, group, the H-box histidine is followed by a serine instead of the acidic residue that is most commonly found at this position (Fig. 1). The only other kinases with this general characteristic are the CheAs, i.e. H P b . Another noteworthy feature of the HPK,, class is the lack of a second phenylalanine in the F-box. The three kinases in the HPK,, class have an asparagine rather than a threonine preceding the conserved H-box proline (Fig. 1). Located three residues downstream from the conserved histidine, this residue would be predicted to lie adjacent to the phosphorylation site on one face of an a-helix. This characteristic feature is also found in two other subfamilies with an H-box proline, HPK,, and HPK,; and in five of the subfamilies that lack the conserved H-box proline, HPK,, HPK,, HPK,, HPK,, and HPK,, (Fig. 1). Members of the HPK,, subfamily have rather typical H-, N-, D-, F- and Gboxes. This class includes CreC (Wanner and Latterell, 1980;Amemura et al., 1986; Wanner, 1995), which like PhoR and Vans can phosphorylate the response regulator PhoB (Wanner, 1992; Fisher et al., 1995). Both PhoR (Makino et al., 1986; Wanner, 1993) and Vans (Arthur et al., 1992; Evers et al., 1996), are in a different kinase subfamily, HPK,,, but the cognate response regulators of all three kinases, CreB, PhoB and VanR, fall into the same

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THORSTEN W. GREBE AND JEFFRY 6. STOCK

Table 6 Classification of response regulators based on their receiver domains. Left = receiver group; right = name of protein; for three-letter sequence identifiers, see Table 1 RAI RAl R Al RA1 RAI RAI RAI RAI RAI RAI RAl RAI RAI RAI RAI RAl RAI RAI RAI RAl RAI RA1 R A1 R Al RAI RAl RAI RAl RA1 RAl RAI RAl RAl RAI RAI RAl RAI RAI RAI RAI RAI RA1 RAI RAl RAI

3lc-mtu AarR-pst AfsQ I -sco ArcA-eco BaeR-eco BasR-eco ChvI-atu ChvI-rme CiaR-spn ColR-pfl CopR-eco CopR-psy CopR-sdu CpxR-eco CreB-eco CtrA-ccr CutR-sli CzcR-reu DorR-rsh DrrA-tma E1215200-sco E1264625-mtu G 1575690-ssp (2882555-eco IrlR-bps KdpE-cac KdpE-eco MtrA-mtu NisR-lla OrnpR-eco OmpR-xne OrfR-shy PcoR-eco PfeR-pae PhoB-aae PhoBeco PhoB-hin PhoB-kpn PhoB-vco PhoP-bsu PhoP-eco PhoP-rntu PirR-pae PrnrA-sty PopP-rle

RA1 R Al R Al R Al R Al R A1 R Al R Al RAI R A1 RAI R Al RAI RAl RAI R A1 R Al R Al RAI RAI R Al R A2 R A2 R A2 R A2 R A2 R A2 R A2 R A2 R A2 R A2 R A2 R A2 R A2 R A2 R A2 R A2 R A3 R A3 R A3 R A3 R A3 R A3 R A3 R A3

RagA-bja RcaCn-fdi RegX3-mtu ResD-bsu RisA-bav RprY-bfr S110789-syn S110797-syn SpaR-bsu SphR-ssp TorR-eco TrcR-mtu VanR-efe YclJ-bsu YgiX-hin YkoG-bsu YtsA-bsu YvcP-bsu YvrH-bsu YxdJ-bsu YycF-bsu CheA-RR-hpy CheY-syn CyaC-RRl-asp DhkD-RR-ddi E l 3 10292-sco (32688314-bbu RcaF-fdi RssB-rpa RstA-eco S111673-syn S111905-RR 1-syn Slr2099-syn Slr2 100-syn StyS-RR-psp TutC-RR-tt I VirG-atu CheA-RR-rce CheAY 1-RR-syn CheAY2-RR-ssp CheY-eco CheY-hpy CheY-ppu CheY-rce CheY-rsh

R A3 R A3 R A3 R A3 R A3 R A3 R A3 R A3 R A3 R A4 R A4 R A4 R A4 R A4 R A4 R A4 R A4 R A4 R A4 R A4 R A4 R A4 R A4 R A4 R A4 R A4 R A4 R A4 R A4 R A4 R A4 R A4 R A4 R A4 R A4 R A4 R A4 R A4 R A4 R A4 R A4 R A4 R A4 R A4 R A4

CheY-rsh CheY I-rme C hey 2-me ChpA-RR-pae FrzE-RR-rnxa L29642-RR-pfl RcaCc-fdi S110038-syn Slr0322-RR-syn ActR-rme AlgB-pae AtoC-eco DctD-.de Dc tD-rme DctR-rca FixJ-aca FixJ-bja FixJ-rme FleR-pae FlC-vch (3231453 I-hpy (32688707-bbu HydG-eco LuxO-vha NodW-bja NtrC-abr NtrC-bpa NtrC-eco NtrC-hse NtrCgvu NtrC-rca NtrC-tfe NtrC-val NtrC 1-aae NtrC3-aae NtrX-aca NwsB-bja PilR-mxa PilR-pae PrrA-rsh RegA-rca RegR-bja StdR-psp StyR-pfl StyR-psp

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THE HISTIDINE PROTEIN KINASE SUPERFAMILY

Table 6 cont.

R A4 R A4 RBI RBI R B1 R B1 R B1 RBI R B1 RBI RBI RBI R B1 R B1 RBI RBI R B1 RBI RBI RBI R B1 RBI R B1 RBI RBI RBI R Bl RBI R B1 RBI RBI RBI R B1 RBI RBI RBI RBI R B1 R B1 R B1 R B1 RBI R B2 R B2 R B2

TodT-ppu TutB-ttl ApdA-RR-pfl ArcB-RR-eco BarA-RR-eco BvgS-RR-bpe CaHK I-RR-cal CaSLNI-RR-cal Chik 1-RR-cal Chkl-RR-gci DhkA-RR-ddi DhkB-RR-ddi DhkC-RR-ddi DivK-ccr DokA-RR-ddi DorS-RR-rsh E1310290-RR-sco E339934-RR-spo ETR 1J U - a t h ETRI-RR-sly EvgS-RR-eco G2688313-RR-bbu LemA-RR-pae LemA-RR-PSY LuxQRR-vha Nik I-RR-ncr PelY-RR-pvi PheN-RR-pto RcsC-RR-eco RcsC-RR-pmi RpfA-RR-eca RpfC-RR-xca RpfC-RR-xor RssA-RR-rpa S111228-RR-syn SII 1672-RR-syn S111905-RR2-syn Sln 1-RR-sce Slr 1759-RR2-syn Slr1982-syn Slr2104-RR-syn SpiR-RR-sty CKI I-RR-ath (324355 I6-RR-ath G2708752-RR-ath

R B3 R B3 R B3 R CI R CI R C1 R CI R CI R CI R CI R C1 R C1 R CI R CI R CI R C1 R CI R C1 R CI R C1 R C1 R C1 R CI R CI R C1 R C1 R CI R C1 R C1 R CI R C2 R C2 R C2 R C2 R C2 R C2 R C2 R C2 R C2 R C2 R C2 R C2 R C3 R C3 R C3

Slrl759-RRl-syn Slr2098-RR-syn Tors-RR-eco AbsA2-sco BpdT-rsp BvgA-bpe DegU-bbr DegU-bsu El2861 81-sco El31 1959-sco El 3 13520-sco EvgA-eco NarL-eco NarP-eco NarP-hin S111592-syn S111708-syn SlrO312-syn SpoOA-bsu UhpA-eco UhpA-sty VsrD-pso YcbB-bsu Ydff-bsu YesN-bsu YfiK-bsu YocG-bsu YvfU-bsu YvqE-bsu Y xjL-bsu CheY-afu CheY-bsu CheY-hsa CheY-lmo CheY-pho CheY-tde CheY-tma CheYtpa CheY2-bbu CheY3-bbu G2650175-afu SPOOF-bsu AlgR-pae LytR-sau LytT-bsu

R C3 R C3 R C4 R C4 R C4 R C4 R C4 R C4 R C5 R C5 R C5 R C5 R C5 R (2.5 R C5 R C5 RD RD RD RD RD RD RD RD RD RD RD RD RE RE RE RE RF RF RF RF RF RF RF RF RG RG RH RH

MrkE-eco YehT-eco CitB-kpn DcuR-eco DpiA-eco El2861 8 4 3 . ~ 0 YdbG-bsu YufM-bsu C heB-afu CheB-bsu CheB-eco CheB-hsa CheB-ppu CheB-rce CbeB-rme CheBrsp AgrA-sau AgrA-sep AgrAl-sau CbnR-cpi COmE-sgo ComE-spn ComE I-sgo comE2-sgo PlnC-lpl PlnD-lpl PlsR-lpl SppR-lsa ComA-bsu MoxX-pde RcsB-eco RcsB-pmi AsgA-RR-mxa CyaC-RR2-asp FixL-RR-rle G2078566-psy H0337-RR-hsp Hox A-ahy HoxA-reu VsrB-RR-pso CorR-ps y FlhS-RR-pde MTH445-mth Rcp 1s s p

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THORSTEN W. GREBE AND JEFFRY 6. STOCK

receiver subfamily, R,, (Table 6). So, in terms of their ‘homology boxes’ and their receiver domain specificity, the HPK,, subgroups seem closely related to members of the HPK, subfamily. The four sequences of HPK3, have an unusual H-box with a stretch of four alanines proximal to the conserved histidine, as well as an unusual glycine two residues upstream from the conserved proline at a position that is generally occupied by an arginine or lysine (Fig. 1). In HPK, the phospho-accepting histidine is followed by glutamate, whereas in dPK,, it is followed by aspartate. Both 3g and 3h kinases seem to lack the typical threonine adjacent to the H-box proline. The F-box motif in HPK,, (‘FDPFFTTKP’)resembles that of the HPK, kinases. The HPK,, subfamily is distinguished by a tryptophan two residues proximal to the H-box histidine, glutamine substituting the first asparagine in the N-box, and a G-box with only two glycines (Fig. 1). 2.1.4. HPK,

This family contains the NtrBs (Ninfa et al., 1995) and the FixLs (Agron and Helinski, 1995), kinases that function in the regulation of nitrogen metabolism. Members of this subfamily (Table 5 ) generally have an alanine preceding the H-box histidine and a glutamine or asparagine preceding the H-box proline (see description of subfamily 3b). The KFT-motif that tends to follow the Nbox in most kinases is generally missing in this group. Besides the characteristic H-box, the HPK, subfamily has a signature sequence at the site of the second phenylalanine of the F-box: PFX-TTK (see also HPK,,, Fig. 1). 2.1.5. HPK5

CitA (Bott, 1997;Bott etal., 1995) and DpiB (Ingmer et al., 1998) are members of the HPKs subfamily of kinases (Table 5 ) . These sequences lack both the conserved phenylalanine and proline of the H-box. A conserved arginine takes the place of a conserved hydrophobic residue at position 4 upstream from the H-box histidine. An asparagine at position 4 distal to the histidine is also characteristic (see description of subfamily 3b). The first asparagine of the N-box is preceded by a glycine instead of the bulky hydrophobic residue found in kinase subfamilies 1-3. The F-box contains only one phenylalanine (Fig. 1). 2.1.6.HPK6

The HPK, kinases are confined to Archaeoglobus (Klenk et al., 1997), except

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205

for one sequence from another archaea, H0337 of Halobacterium. The archaeoglobal kinases have an arginine preceding the H-box histidine (like DpiB-eco of HPK,) and the downstream proline is missing (Fig. 1).

2.1.7. HPK, This subclass contains DegS (Msadek et al., 1990, 1995; Louw et al., 1994)and NarQ (Chiang et al., 1992, 1997; Rabin and Stewart, 1992, 1993; Walker and DeMoss, 1993) (Table 5). The H-box is distinguished by the presence of a negatively charged group two residues upstream from the conserved histidine and a positively charged residue, usually an arginine, eight residues upstream (Fig. 1). This places these residues adjacent to one another on one face of the presumed H-box a-helix. In addition, in all cases the phospho-accepting histidine is followed by an aspartate residue. The proline and phenylalanine that tend to be conserved in most kinase H-boxes are generally missing in HPK, kinases. The N-box is also distinct: the second asparagine is conserved, but in place of the first asparagine there is a glutamate. In addition, the F-box seems to be missing and the distance between the D- and the G-boxes is reduced (Fig. 1). 2.1.8. HPKs This group contains LytS (Brunskill and Bayles, 1996; Table 5). Several unusual features typify this kinase subclass: in the H-box, a proline precedes the conserved histidine, while the proline found in most kinases five residues downstream from the histidine is missing. Moreover, the H-box histidine is followed by a phenylalanine instead of the usual acidic residue. This subclass also has an unusual N-box signature sequence: ‘hPxhxhQxhhENAh’. The F-box is not conserved, and the distance between the H- and X-box is reduced (Fig. 1).

2.1.9. HPK, This subfamily contains the CheAs (Stock et al., 1988; Kofoid and Parkinson, 1991; Bilwes et ai. 1999; Table 5 ) . These proteins are specialized for chemotaxis responses and invariably function in complexes with auxiliary sensory components (Borkovich and Simon, 1991; Gegner et al., 1992; Liu et al., 1997). Their overall domain organization is quite distinct. The site of histidine phosphorylation appears to be localized to a domain that is similar to the HPt domains of complex phosphorelay systems (Swanson et al., 1993; Zhou et ai., 1995; Levit et al., 1996; Kato et al., 1997). The sequence around the phosphoaccepting histidine is quite distinct in the CheA subclass. The histidine is

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THORSTEN W. GREBE AND JEFFRV 8. STOCK

followed by a serine or threonine rather than by the typical acidic residue. The only other kinase subfamily in which a serine is located at this position is HPK,,. There is no proline in the vicinity of the conserved histidine. Nineteen residues downstream from the phospho-accepting histidine there is a second conserved histidine. Moreover, in the N-box the first conserved asparagine has been replaced by a histidine, the motif ‘KFT’ found in the major HPK class is replaced by the motif ‘DHG’, and the two phenylalanines of the F-box are separated by three rather than by two residues (Fig. 1).

2.1 .lo.HPK,, This group includes the kinases that regulate competence for genetic transformation in Streptococcus spp. (Havarstein et al., 1995, 1996; Pestova et al., 1996; Cheng et al., 1997; Table 5). The group has a characteristic tyrosine two residues downstream from the conserved histidine and there is no H-box proline. In addition, there is only one asparagine in the N-box and there is apparently no D-box (Fig. 1). 2.1.11. HPK,,

The methanobacterial group of kinases (Smith et al., 1997;Table 5) have putative H-boxes with very low similarity to H-boxes in any other class of histidine kinases. The conserved histidine in this subfamily is followed by an arginine. Four residues downstream from the conserved histidine there is an asparagine (Fig. 1). The N-box has only one asparagine, with a glutamate replacing the first asparagine. Besides the methanobacterial kinases, this group includes one sequence from Rhizobium and one from Mycobacterium. ExsG of Rhizobium (Sinorhizobium) meliloti shares 25% sequence identity with G2072665-mtu (Cole et al., 1998) over a region of 124 residues spanning the region from the H-box to the N-box. The relation to other members of the HPK, subfamily is rather tenuous, however. After G2072665, it most resembles Mthl260. However, in this case, the similarity only includes the N-box, which for this group is very characteristic (27% identity in 33 amino acids). ExsG does not have a conserved D-box (Fig. 1).

3. COGNATE RECEIVER DOMAINS

A similar multisequence analysis was performed with all receiver domains that have been associated biochemically and/or genetically with one or more

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Table 7 Classification of response regulators based on their output domains. Left = output group; right = name of protein; for three-letter sequence identifiers, see Table 1. ActR ActR ActR ActR CheB CheB CheB CheB CheB CheB CheB CheB CheB CheB CheB CheB Tandem Tandem CitB CitB CitB CitB CitB CitB ComE COmE COmE COmE COmE COmE ComE ComE COmE COmE COmE COmE C o d FixJ FixJ FixJ FixJ FixJ FixJ FixJ FixJ FixJ FixJ FixJ FixJ FixJ FixJ

ActR-rme PirA-rsh RegA-rca RegR-bja CheB-afu CheB-bsu CheB-eco CheB-hsa CheB-pae CheB-ppu CheB-rce CheB-rme CheB-rsp CheB-sty CheBl-bbu CheB2-bbu Slr0322-RR-syn Sb209 8-RR-s yn CitB-kpn DcuR-eco Dpi A-eco E1286184-sco YdbG-bsu YufM-bsu AgrA-sau AgrA-sep AgrAl-sau CbnR-cpi ComE-san COmE-sgo ComE-spn ComE-sgo ComE-smi PlnC-lpl PlnD-lpl PlsR-lpl SppR-lsa AbsA2-sco BpdT-rsp BvgA-bpe CornA-bsu CorR-ps y DctR-rca DegU-bbr DegU-bsu El2861 8 I-sco El31 1959-sco E 13 13520-sco E290952-mtu Evg A-eco FixJ-aca

FixJ FixJ FixJ FixJ FixJ FixJ FixJ FixJ FixJ FixJ FixJ FixJ FixJ FixJ FixJ FixJ FixJ FixJ FixJ FixJ FixJ FixJ FixJ FixJ FixJ FixJ FixJ FixJ FixJ H2-Domain H2-Domain (ArcB) H2-Domain (ArcB) H2-Domain (ArcB) H2-Domain (ArcB) H2-Domain (ArcB) H2-Domain (ArcB) H2-Domain (LemA) H2-Domain (LemA) H2-Domain (LemA) H2-Domain (LemA) H2-Domain (LernA) H2-Domain ( L e d ) H2-Domain (LemA) HZ-Domain (LemA) H2-Domain (LemA) H2-Domain (LemA) HZ-Domain (LemA) LytR LytR LYfl LYfl

FixJ-bja FixJ-rme MoxX-pde NarL-eco NarP-eco NarP-hin NodW-bja NwsB-bja RcsB-eco RcsB-pmi RcsB-sti S111592-syn SII 1708-syn Slr03 12-syn StdR-psp StYR-Pfl StyR-PsP TodT-ppu Turn-tt 1 UhpA-eco UhpA-sty vsrc-pso VsrD-pso Ydfl-bsu YfiK-bsu YocG-bsu YvW-bsu YvqE-bsu YxjL-bsu RteA-RR-bte ArcB-RR-eco DorS-RR-rsh S111905-RR2-syn Slr 1759-RR2-syn Slr2104-RR-syn Tors-RR-eco ApdA-RR-pfl Bar A-RR-KO BvgS-RR-bpe CyaC-RU2-asp EvgS-RR-eco LemA-UR-pae LemA-RR-ps y PelY-RR-pvi PheN-RR-pto RpfA-RR-eca U25692-RR-pto LytR-sau LytT-bsu MrkE-eco VirR-cpe

208

THORSTEN W. GREBE AND JEFFRY 6 . STOCK

Table 7 cont. LytR LytR NtIC NtrC NtrC NtrC NtrC NtrC NtrC NtrC NtrC NtrC NtIC NtIC NtrC NtrC NtrC NtIC NtrC NtrC NtrC NtrC NtrC NtrC NtrC NtrC NtrC NtrC

NtrC NtrC NtrC NWC NtrC NtrC NtrC NtrC NtrC Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null

YccH-bsu YehT-eco AlgB-pae AtoC-eco CT468-ctr DctDrle Dc tD-me FleR-pae FlrC-vch (32688707-bbu HoxA-ah y HoxAreu HydG-eco HydG-sty LuxO-vha NifA-avi NtrC-abr NtrC-atu NtrC-bpa NtrC-eco NvC-hse NtrC-kpn NtrC-pvu NtrC-rca NtrC-rme NtrC-nu NtrC-rsh Ntri-sty NtrC-tfe NtrC-val NtrC 1-aae NtrCLaae NtrX-aca OrfR-eac PilR-mxa PilR-pae RteB-bte AsgA-RR-mxa CaHK1-RR-cal CaSLN I-RR-cal CheA-RR-hpy CheA-RR-rce CheAY 1-RR-syn C he AY2-RR-ssp CheY-afu CheY-hsu CheY-eco CheY-hpy CheY-hsa CheY-lmo CheY-pho CheYgpu

Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null

CheY-rce CheY-rsh CheY-rsh CheY-sty CheY-syn CheY-tde CheY-tma CheY-tpa CheY I-me CheY2-hbu CheY2rme CheY3Xbhu Chk 1-RRAci ChpA-RR-pae CHI-RR-ath CyaC-RR 1-asp DhkA-RR-ddi DhkB-RR-ddi DhkC-RF-ddi DhkD-RR-ddi DivK-ccr DokA-RR-ddi E l 3 10290-RF-sco E 1319771-RR-spo E334753-RR-mle E339934-RR-spo ETR 1-RR-ath ETR I-RR-sly Fi xL-RR-rle FlhS-RR-pde FrzE-RR-mxa FrzZii-mxa G2072666-mth (32078566-psy G24355 16-RR-ath G2649095-afu G2650 175-afu G2650 175-afu (32650670-afu G2708752-RR-ath H0337-RR-hsp L29642-RR-pfl LuxN-RR-v ha LuxQ-RR-v ha MTH440-RR-mth MTH445-mth MTH457-RR-mth RcaCc-fdi Rcal-fdi Rcp 1-ssp RcsC-RR-eco RcsC-RF-pmi

209

THE HISTIDINE PROTEIN KINASE SUPERFAMILY

Table 7 cont. Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null Null OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR

RssA-RR-rpa S110038-syn SII 1905-RR I-syn Sln 1-RR-sce Slr0222JZRn-syn Slrl759-RRl-syn Slr 1969-RR-syn Slr1982-syn SpiR-RR-sty SpoOF-bsu StYS-M-psP TutC-RR-tt I VirA-RR-arh VirA-RR-atu VirAL-RR-atu VsrB-RR-pso YhcK-eco YkvE-bsu 3lc-mtu AarR-pst AfsQl-sco ArcA-eco BaeR-eco BasR-eco ChvI-atu ChvI-rme CiaR-s pn ColR-pfl CopR-eco CopR-psy CopR-sdu CpxR-eco CreB-eco CtrA-ccr CutR-sli CzcR-reu D 1033093-sgr DorR-rsh DrrAtma E 1215200-sco E1264625-mtu G 1575690-ssp (3882555-eco GtcR-bbr IrlR-bps KdpE-cac KdpE-eco MtrA-mtu MxbM-mex NisR-lla OmpR-ecl OmpR-eco

OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR OmpR

OmpR-sti OmpR-st y OmpR-xne OmpRjen OrfR-shy PcoR-eco PfeR-pae PhoB-aae PhoB-eco PhoB-hin PhoB-kpn PhoB-sdy PhoB-vco PhoP-bsu PhoP-eco PhoP-mtu PhoP-sty PirR-pae PmrA-sty PopP-rle RagA-bja RcaCn-fdi RegX3-mbo RegX3-mle RegX3-mtu ResD-bsu Ris A-bav RisA-bbs RisA-bpt RprY-bfr RstA-eco S110789-syn S110797-syn SpaR-bsu SphR-ssp TorR-eco TrcR-mtu VanR-efe VanRB-efa VirG-atu YbdJ-bsu YcbL-bsu YclJ-bsu YgiX-hin YkoG-bsu YrkP-bsu YtsA-bsu YvcP-bsu Y vqA-bsu YvrH-bsu YxdJ-bsu Yy c F b s u

I

HPK la(39) 4:

HPK l b (47)

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Recelver Classes

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Output Classes

Figure 6 Linkage between functional domains in two-component systems. The left panel of graphs shows kinase domain subfamilies versus receiver domain subfamilies. The right panel of graphs shows kinase domain subfamilies versus output domain subfamilies. The subfamily names for the kinase domains are shown along the ordinates. The numbers in parenthesis are the numbers of available cognate response regulators. The subfamily names of the receiver and output domains are shown along the abscissas. Example of how to read this figure: 28 cognate kinasehesponse regulator pairs were available for the HPK, subfamily in this sequence analysis. If the cognate response regulators were classified by their receiver domains, all 28 would fall into the subfamily RA. If they were classified by their output domains instead, all 28 would fall into the OmpR subfamily of response regulators. The archaeoglobal kinases, HPK,, and the methanobacterial kinases, HPK, have been omitted from the chart since, to date, almost no cognate response regulators are known, for these two types of kinases.

,,

THE HISTIDINE PROTEIN KINASE SUPERFAMILY

21 1

specific kinases. A total of 298 of these cognate receiver domains were identified (Tables 3,6, and 7). The multisequence alignment indicated that, like the histidine kinases, receiver domains fall into distinct subfamilies (Tables 6 and 7, Fig. 5 ) . Whereas there were 11 different kinase subfamilies, only eight receiver domain subfamilies could be clearly distinguished, R,-R,. Response regulator receiver domains have previously been classified in terms of their output domains, e.g. OmpR, FixJ, NtrC, etc. (Volz, 1993; Pao and Saier, 1995; Hakenbeck and Stock, 1996; Table 7). To a first approximation, our classification based solely on receiver domain sequence analyses coincides with the previous grouping (Fig. 6 , Tables 6 and 7). There are a few exceptions, however. For example, according to the output domain classification, NarP-eco and FixJ-rme belong to the FixJ class, but we find that their receiver domains clearly fall into different subfamilies: R, for NarP and R, for FixJ (Table 7). The corresponding lunase domains also fall into two different classes: NarL belongs to the HPK, subfamily, which almost exclusively interacts with R, receivers, and FixL is a member of HPK,, almost all of which interact with R, receivers (Tables 3 and 6). This apparent discrepancy in NarP and FixJ classification c,ould reflect domain shuffling during the evolution of these proteins. In at least two-thirds of all cases, there is a strong correlation between kinase and cognate regulator classifications. Figure 5 shows the juxtaposed dendrographs of 2 10 kinaseheceiver pairs. The strongest correlation in kinase and cognate receiver groupings is observed for the pairs HPK,,-R,, HPK,,-R,, HPK,-R,, HPK,-R,, and HPK,,-R, (Figs 5 and 6). The fact that practically all hybrid kinases and all eukaryotic kinases fall into a single class, HPK,,, and their receivers fall into a single class, R,, strongly argues in favour of the idea that the eukaryotic His-Asp phosphorelay systems arose from a single evolutionary gene transfer event.

4. DOMAIN SHUFFLING AND THE EVOLUTION OF HIS-ASP

PHOSPHORELAY NETWORKS

The His-Asp phospho-relay systems are composed of several structurally and functionally distinct domains that interact with one another to process information. One might imagine that during evolution these elements of protein structure would be shuffled to provide a spectrum of different sensory response configurations. We see surprisingly little indication, however, for this type of modular rearrangement. In general, the kinase catalytic domains, their Hdomain targets, the cognate receiver domains and the output effector elements seem to have evolved as integral units. It should be noted however, that in analysing the receiver domains, we have selected only those that are clearly associated with specific histidine kinases. In almost all cases this association

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THORSTEN W. GREBE AND JEFFRY B. STOCK

derives from a juxtaposition of the corresponding genes. Broader specificity receivers that have evolved independently of any particular kinase might be encoded as independent genes and have therefore been excluded. Moreover, even with the limited set we have examined, at least a quarter of the receiver domains fall outside any straightforwardkinase-receiver subfamily association. Clearly, the central two signal transduction components, the histidine kinases and their cognate receiver domains, have recruited other structural elements (Pa0 and Saier, 1995). Walker A motifs have been identified in the sensing domain of KdpD-eco (Jung and Altendorf, 1998), in the kinase domain of ChvG-atu (Charles and Nester, 1993), and in the linker region of BvgS-bpe (Beier et al., 1996). Leucine zippers are employed by AgrC-sau (Van Wamel et al., 1998) and TodS-ppu (Lau et al., 1997). Moreover, hybrid kinases seem to fuse two-component modules at will: receiver and HPtdomains can be fused to kinase domains. If a receiver domain is fused to a kinase domain it usually will be linked to the C-terminus, but it can also be found at the N-termini of hybrid kinases, as in AsgA-mxa (Plamann et al., 1995), H0337-hsp (GenBank: AFO16485), Mth90l-mth (Smith et al., 1997) or PhcR-rso (Clough et al., 1997). An example of a very recent event of gene duplication are the two copies of the pheN allele in Pseudomonas toluasii. One is missing most of the sensor while the other copy has a sensing domain almost identical to ApdA and LemA (Han et al., 1997). In the face of all this potential variability, it seems remarkable that the basic familial relationships outlined above appear to have been maintained in organisms that are thought to have diverged over a billion years ago. For example, one can still see that all the eukaryotic kinases and receiver domains are very closely related, and in some organisms, such as the methanobacteria, there seems to have been a recent gene transfer event followed by duplication. One gets the impression that the current state of these signalling systems may be quite recent, with considerable lateral gene transfer almost obscuring boundaries between species. This would explain both the extreme variability of the histidine kinase superfamily as well as the apparent conservation of recruited auxiliary elements, such as the various response regulator output domains. Consider, for example, YcbA and YcbM of B. subtilis. In YcbA, only the Cterminal 110 residues, starting after the N-box, are homologous to the C-termini of kinase domains, whereas the N-terminal275 amino acids appear to be completely unrelated. YcbM has only 158 amino acids, with significant HPK homology only extending from residue 80, starting with the D-box. Both genes, ycbA and ycbM, are adjacent to genes with clearly defined receiver domains, ycbB and ycbL, respectively, strongly suggesting that they are derived from standard phosphorelay systems. It seems likely that these structures are derived from relatively recent events because the origins of the component elements are still so clearly resolved. All of these phenomena would seem to reflect extensive evolutionary modifications at a very rapid rate.

THE HISTIDINE PROTEIN KINASE SUPERFAMILY

213

Another example of apparently recent genetic restructuring is provided by FixL from Rhizobium leguminosarum and HpkY from Pseudomonas syringae. FixL-rle is a hybrid kinase. Its sensor, 260 aa, is unrelated to the 102 aa sensor of HpkY-psy. The kinase domains, however, are 5 1% identical and the receiver domains share 38% identity, although one, the FixL receiver is part of a hybrid kinase, whereas the other, G2078566-psy is an isolated receiver domain. In the case of the mycobacterial pair, SenX3RegX3, and PhoRPhoP of B. subtilis the kinase, receiver, and output domains also share high degrees of identity: 41%, 48% and 42%, respectively. Their sensory domains appear to be entirely unrelated, however. In fact, as far as sensing is concerned, one gets the impression that almost anything goes. Highly variant sensing domains can be attached to very conserved signalling and receiving modules, providing a powerful tool for rapid evolutionary change. A dramatic example of this process as it pertains to sensory domain shuffling can be seen in the case of the ComD kinase receptors of Streptococcus spp. where one can see sensory domain mosaics that clearly reflect an ongoing process of sensory domain rearrangements (Havarstein et al., 1997). One characteristic of His-Asp phosphorelay signal transduction systems is that they tend not to be essential, their numbers vary widely between different species and there is often considerable functional redundancy. The examples that are beginning to emerge from genomic sequences strongly support the notion of very rapid evolution of these signal transduction systems. The archaeal histidine kinases are a striking example for rapid radiation, presumably beginning from a single gene transfer event. The methanobacteria contain several kinases that are very similar to one another in the kinase domain (up to 55% identity) but very distinct from all other kinase classes. Here, even the sensory domains, although substantially deviating from each other, still show significant similarity. The same scenario seems to pertain for Archaeoglobus. The situation in the Archaea and the eukaryotes contrasts with what is observed in bacteria such as E. coli or B. subtilis, where histidine kinases fall into 8-10 different subgroups. The cyanobacterium Synechocystis shows both patterns - a wide diversity like E. coli and B. subtilis and apparently unique subgroups of sequences analogous to those found in the Archaea. Thus, in the relatively limited number of genomes that have been sequenced, one sees a huge range in both the number of kinases and their diversity. Apparently, species can become specialized to constant environments where sensory adaptation is unnecessary and signalling systems are completely deleted. Conversely, they can apparently acquire new systems with novel signal transduction components to allow movement into new environments. These arguments may have important implications for the evolution of eukaryotes and metazoans in that lower eukaryotes such as Dictyostelium seem to have experienced a relatively recent and dramatic radiation of His-Asp phosphorelay relay systems

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THORSTEN W. GREBE AND JEFFRY B. STOCK

(Wurgler-Murphy and Saito, 1997; Brown and Firtel, 1998; Loomis et al., 1998).

ACKNOWLEDGEMENTS

The authors thank Bonnie Bassler, Regine Hakenbeck and Tom Silhavy for helpful discussions, Austin Newton and Jianguo Wu for sharing sequence information prior to publication, Jeffrey Stewart for calculating Shannon’s entropy values, and the participants of the course MOL548, Bob DeRose, Brendan Lilley, Jaffet Ghebretnsae, Mike Zinda, Sandra Da Re, Todd Hofmeister and Tracy Raivio. This work has been supported by grants from the Deutsche Forschungsgemeinschaft (Gr1651) and the National Institute of Health (GM57773).

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Bacterial Tactic Responses Judith P. Armitage Microbiology Unit, Department of Biochemistry, University of Oxford, South Parks Road, Oxford OX1 3QU, UK

ABSTRACT

Many, if not most, bacterial species swim. The synthesis and operation of the flagellum, the most complex organelle of a bacterium, takes a significant percentage of cellular energy, particularly in the nutrient limited environments in which many motile species are found. It is obvious that motility accords cells a survival advantage over non-motile mutants under normal, poorly mixed conditions and is an important determinant in the development of many associations between bacteria and other organisms, whether as pathogens or symbionts and in colonization of niches and the development of biofilms. This survival advantage is the result of sensory control of swimming behaviour. Although too small to sense a gradient along the length of the cell, and unable to swim great distances because of buffetting by Brownian motion and the curvature resulting from a rotating flagellum, bacteria can bias their random swimming direction towards a more favourable environment. The favourable environment will vary from species to species and there is now evidence that in many species this can change depending on the current physiological growth state of the cell. In general, bacteria sense changes in a range of nutrients and toxins, compounds altering electron transport, acceptors or donors into the electron transport chain, pH, temperature and even the magnetic field of the Earth. The sensory signals are balanced, and may be balanced with other sensory pathways such as quorum sensing, to identify the optimum current environment. The central sensory pathway in this process is common to most bacteria and most effectors. The environmental change is sensed by a sensory protein. In most species examined this is a transmembrane protein, sensing the external environment, but there is increasing evidence for additional cytoplasmic receptors in many ADVANCES IN MICROBIAL PHYSIOLOGY VOL 41

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species. All receptors. whether sensing sugars. amino acids or oxygen. share a cytoplasmic signalling domain that controls the activity of a histidine protein kinase. CheA. via a linker protein. Chew. A reduction in an attractant generally leads to the increased autophosphorylationof CheA. CheA passes its phosphate to a small. single domain response regulator. CheY. CheY-P can interact with the flagellar motor to cause it to change rotational direction or stop. Signal termination either via a protein. CheZ. which increases the dephosphorylationrate of CheY-P or via a second CheY which acts as a phosphate sink. allows the cell to swim off again. usually in a new direction. In addition to signal termination the receptor must be reset. and this occurs via methylation of the receptor to return it to a non-signalling conformation. The way in which bacteria use these systems to move to optimum environments and the interaction of the different sensory pathways to produce speciesspecific behavioural response will be the subject of this review. Abbreviations ........................................................ 231 1 Introduction ....................................................... 231 232 2 What is meant by 'bacterial taxis'? .................................... 233 3 . History ......... . . . . . . . . . . . . . . . . . . . . . . . . . . . . ....................... 235 4 How bacteria swim and glide ......................................... 235 4.1. Theflagellum ................................................. 4.2. Patterns of swimming .......................................... 237 238 5 . The chemosensory pathway of E . coli .................................. 240 5.1. Chemoreceptors ............................................... 5.2. Cytoplasmic signalling .......................................... 244 246 5.3. CheY ........................................................ 249 5.4. Adaptation .................................................... 5.5. Localization of MCPs ........................................... 251 5.6. Why are MCPs targeted to the poles? ............................. 252 5.7. Phosphotransferase sugars ...................................... 253 254 5.8. Thermotaxis .................................................. 254 5.9. Repellent sensing .............................................. 5.10. Variations on a theme .......................................... 255 262 5.1 1 Pattern formation .............................................. 262 5.12. Fumarate ..................................................... 263 6 . Responses to electron acceptors and light .............................. 6.1. Light ......................................................... 263 267 6.2. Electron acceptors ............................................. 7 . What is the role of tactic responses in natural environments? . . . . . . . . . . . . . . 268 269 7.1. Magnetotaxis ................................................. 269 7.2. Aquatic environments .......................................... 271 7.3. Biofilms ...................................................... 272 7.4. Role in pathogenicity/symbiosis .................................. 7.5. Pathogens .................................................... 273 276 8 . Conclusions ....................................................... Acknowledgements ................................................. 277 References ........................................................ 277

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ABBREVIATIONS

BR

Bacteriorhodopsin Counterclockwise Clockwise Dimethylsulfide DMS Dimethylsulfoxide DMSO Demethy lsulfoniopropionate DMSP HPK Histidine protein kinase N-acy1-HSL N-acyl-homoserinelactone ICM Inner cytoplasmic membrane MCP Methyl-accepting chemotaxis protein PBP Periplasmic binding protein Phosphotransferase system PTS Photoactive yellow protein PYP Sensory rhodopsin SR

ccw cw

1. INTRODUCTION

It now appears that the majority of bacterial species are motile. Some obligate pathogens are non-motile, e.g. mycobacteria, as are some symbionts, such as the bacteroides of the gut, but this may reflect a very specialized life-style. Species isolated from environments as diverse as the ‘black-smokers’at the bottom of the oceans, salt and soda lakes, the open oceans, fields, oligotrophic springs, as well as the animal gut or the forest floor, swim. Members of almost all kingdoms of the Bacteria and the Archaea domains swim. Other species glide on surfaces. The mechanism of free swimming appears to be the same across all species, and suggests a single early evolutionary event. Gliding, on the other hand, is still a mystery but, looking at the phylogenetic distribution of gliding, it may have evolved independently several times. However, in all cases, the synthesis of the means of moving takes a considerable percentage of the biosynthetic energy of a cell and it is certain that, if a bacterium moves, it provides the cell with a survival advantage. Swimming moves a bacterium towards its optimum environment for growth or maintains it in its current position. Obviously, the optimum environment for one species may be toxic to another species and, as would be expected for any system with an ancient evolutionary history, the sensory mechanism has been adapted for the niche of each species. Indeed, some species with very variable metabolic repertoires can change components of the sensory pathway to suit current conditions. In this review, I will try to give a general outline of the common features of sensory behaviour in bacteria, using the details of the well-characterized system of Escherichia coli as the basic central model system, as most data

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suggest that chemosensing in most bacteria follows the skeletal structure of the E. coli system, but with more complex pathways grafted on. I will also attempt, at a very basic level, to put some of what we know into the context of the normal growth environment of some species. This coverage will necessarily be selective as the chemosensory pathway is understood in any detail in only a very few species. For recent reviews of the detailed chemistry of E. coli chemotaxis, see Stock and Surette (1996); Falke et al. (1997), and Levit et al. (1998). Studies of the role of chemotaxis in other species and the role in their natural environment have been much more limited. Although a large variety of species has been looked at, many of these studies have been, of necessity in many cases, purely phenomenological. A few examples will therefore be used to illustrate the probable role of chemosensing in natural environments.

2. WHAT IS MEANT BY ‘BACTERIAL TAXIS’?

Most bacteria are only a few micrometres long, although some motile marine species can be as small as 0.1 pm and some spirochetes as large as 100 pm (a recently isolated fish gut symbiont was found to be several hundred micrometres long and tens of micrometres wide and motile, but this is almost certainly a rare occurrence). In general, bacteria are too small to sense a spatial gradient because there is not enough distance nose-to-tail for a gradient to exist; indeed, there is no ‘nose’ or ‘tail’ in bacterial cells for this reason. Bacteria therefore compare ‘now’ with ‘then’, temporally sensing a spatial gradient and biasing their usual random pattern of swimming towards a more favourable environment (Berg, 1983; Schnitzer et al., 1990). Taxis in bacteria, therefore, is not (usually) the directed movement seen in eukaryotic microbes, in which they sense the direction of a stimulus and head directly for it, rather it is a ‘klinokinesis with adaptation’. This is defined as a reaction by which the frequency of speed or direction changing per unit time is determined by the strength of the stimulus. Therefore, movement by E. coli towards L-serine would be correctly called positive klinokinesis with adaptation. A detailed discussion of the conceptual problems involved in kinesis and taxis can be found in a review by Dunn (1990). The very large body of literature on bacterial responses to gradients or transient changes in stimuli uses, with almost no exceptions, the word ‘chemotaxis’to describe E. coli moving towards L-serine. The same will be done in this chapter, but readers should be aware that eukaryotic and prokaryotic responses are different, although the end result may be similar. The nature of the environment surrounding bacteria is also very different from that around larger organisms. Bacteria are so small that they experience

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no inertia, only viscosity. When a bacterium stops swimming, it stops within the diameter of a proton. It displaces no liquid, but carries a shell of medium with it. The rate of diffusion of effectors to the cells’ receptors is therefore important. Because of the mechanism of swimming and the constant buffeting by Brownian motion it is difficult for cells to swim in straight lines, instead they swim in curves. The frequent direction-changing and environmental-sensing does, however, keep them on the right track. An E. coli population inoculated into the centre of a petri dish containing nutrient soft agar will have swarmed to the edge of the plate within 24 h, about 1000 body lengths an hour (ignoring growth), a rather slow walking pace for a human. Very little is known about the distances travelled in natural environments but, as should become clear, chemotaxis is certainly important within those environments.

3.HISTORY Bacteriology began because bacteria swim (reviewed by Annitage, 1997). Antonie van Leeuwenhoek would not have realized that the tiny particles he saw in the suspension of pepper water in the late 17th century were living organisms if they had not swum with purpose around their environment. He was fascinated by the tiny size of legs, and therefore bones and blood vessels, that would be required on such minute ‘animalcules’; see Ford (1991) for a readable account. Unfortunately, this aspect of microbiology went largely ignored until the middle of the nineteenth century, when scientific study was put on a rather more professional footing. Perhaps the last great amateur in the area was the traveller, Christian Gottfried Ehrenberg, who began observing bacterial behaviour in the 1840s and was the first person to describe the ‘waveshaped’ flagella on a swimming bacterium, probably Chromatium, as the organelles of movement. Another German, Thomas Engelmann, a professional university scientist, produced the first major description of bacterial swimming and behaviour. Bacteria had been recognized by now as a group of organisms in their own right, although there was controversy as to whether they were plants or animals. In 1881, Engelmann looked at ‘putrefactive’ bacteria under a cover slip and found that, with time, they accumulated at the edge of the cover slip or around air bubbles, and continued actively swimming. The few remaining away from the edge stopped swimming. If he added carbonic acid, he noted that the cells not only slowed down but showed great agitation. He thought the difference in response to oxygen and carbonic acid, which looked similar to the ‘breathing sensitivity’ of animals, together with their tendency to accumulate in regions of high nutrient concentration, suggesting a hunger response, proved the ‘unity of nature’ (Engelmann, 1881, 1883; Ehrenberg, 1838).

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Engelmann was also the first person to describe the photosensitive behaviour of photosynthetic bacteria. He isolated bacteria from the Rhine, close to his work. As with Ehrenberg, he was almost certainly watching the behaviour of a Chromatium species; the description of the pattern of swimming is so accurate that it cannot really be any other species. He described a bacterium swimming at 20-40 p d s , rotating about its long axis at about 3-6 r e d s and periodically reversing the direction of swimming. The bacteria did not swim in the dark, but started to swim if illuminated. When they swam over a dark-light boundary, they reversed, which caused them to accumulate in a spot of light. He shone an intense source of gas light through a prism on to a thin layer of bacteria and found that they accumulated in particular regions of the light spectrum, reversing if they moved out of those wavelengths and swimming normally when not in a favoured wavelength. The bacteria accumulated in regions corresponding to their photosynthetic absorption spectrum, but they also accumulated beyond the visible spectrum, in the infra-red. The blue and red/orange regions of the spectrum were empty, but the 570, 550-5 10 and 850 nm regions had tight bands of swimming bacteria. This led him to the suggestion that photosynthetic pigments may also absorb in the infra-red. Wilhelm Pfeffer, in Tubingen at the end of the nineteenth century, developed one of the techniques which is still a major tool for anyone working on bacterial chemotaxis (Pfeffer, 1884, 1904). He inserted a fine glass capillary, sealed at one end and filled with a chemical, into a bacterial suspension. If bacteria were attracted to the chemical, they accumulated around and within the capillary; if repelled, the area cleared. The capillary method is still in use as a rapid method for analysing the qualitative chemosensory behaviour of different bacterial species or the effect of a specific mutation. He also looked at chemotaxis in a quantitative way, using the capillary method to identify thresholds, documenting sensitivity and gain within bacterial chemotaxis and describing adaptation. In this way he linked bacterial behaviour to the general animal phenomenon of perception and, as did Engelmann, used behaviour to support the idea of the uniformity of life. Pfeffer had a particular interest in osmotactic responses and showed that a strong positive chemoattractant concentration could reduce a repellent response to osmolites, the first indication that different sensory pathways might interact. In the early 1950s, Roderick Clayton examined the behaviour of the photosynthetic bacterium Rhodospirillum rubrum (Clayton, 1953a,b,c). He produced the most exhaustive description of the step-down response of this bacterium to a reduction in light intensity under different growth conditions. He confirmed the similarity between the photosynthetic spectrum and the photoresponse spectrum and characterized the light intensity change required to produce a response, showing that whatever the starting intensity, cells would respond to a 1% drop in intensity, illustrating the sensitivity of the sensory system. He

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suggested that the cells were in some way responding to a change in intracellular ATP. This idea was dismissed when investigations into E. coli revealed dedicated transmembrane chemoreceptors. However, it has recently become apparent that some species do respond to their metabolic state, in addition to chemoeffectors binding to receptors, and Clayton was almost certainly at least partly right in his interpretation.

4. HOW BACTERIA SWIM AND GLIDE 4.1. The Flagellum

The structure and operation of the bacterial flagellum has been the subject of several recent reviews (see pages 29 1-337 for literature overview). This brief outline is therefore designed to illustrate the general structure and function as relevant to the behaviour of the cell. The bacterial flagellum is a semi-rigid helical filament made of a polymer of a (usually) single protein, flagellin. It spontaneously polymerizes into a helical form and, if dissociated by a reduction in pH, will reform when the pH is restored to normal. In some species there is more than one flagellin gene, e.g. Sinorhizobium meliloti and Caulobacter crescentus use four related flagellins to make a fully functional helix (Dingwall er al., 1990; Pleier and Schmitt, 1991). In other species, phase variation is used to change the flagellin, and therefore the major bacterial antigen, under different conditions (Iino and Kutsukake, 1983). This is a trait most studied in pathogenic Salmonella. The helix is rotated at its base by a membrane-embedded motor. The motor consists of a rotor and stator. The rotor comprises the central part of the motor. There is a protein ring known as the MS-ring, the product of the FliF gene, in the cytoplasmic membrane which appears to form the scaffolding for the proteins which, on the cytoplasmic face of the MS-ring, form the active part of the rotor. These three proteins, FliG, FliM and FliN, form a ring around the base of the MS-ring. FliG, present at about 25-50 copies, forms part of the rotor itself, while FliM and FliN appear to be involved in interaction with the chemosensory signalling pathway and control the switching of the motor (Khan et al., 1992; Blair, 1995; Macnab, 1996; Mathews et al., 1998). The three proteins together are called the switch complex or the C-ring (Francis et al., 1994). The C-ring forms the rotary part of the motor, rotating as ions, usually protons but they may be Na+ in alkalophiles or species in sodium environments, move through the stator and interact, possibly electrostatically, with conserved groups on the FliG proteins of the C-ring (Zhou et al., 1998). The stator is composed of a ring of about eight Mot complexes made of two

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membrane-spanning proteins: MotB, which has a single membrane-spanning domain and binds to the peptidoglycan of the cell wall, and MotA, which has four membrane-spanning helices and appears to form the major component of the ion channel (although MotB may also play a major part in the movement of ions) (Blair and Berg, 1988, 1990, 1991). The ions move down the electrochemical gradient created by respiration or photosynthesis, and rotate the motor at between about 300 Hz for proton driven motors and over 1000 Hz for Na+ motors (Lowe et al., 1987; Magariyama e f a f . ,1994). This rotation drives bacteria through their environment at speeds from about 15 y d s to in excess of 200 p d s . Depending on the species, the motor can either switch rotational direction or stop, although the ion gradient remains constant and inward. The control of switching depends on the cytoplasmic chemosensory system. It appears that flagella-driven motility evolved early in bacterial evolution as a similar pattern is seen for all flagellate species, both eubacteria and archaea. In some, such as spirochetes, the flagella have become internalized, arising from the poles of the cell and running along the length of the cell, between the flexible outer cell wall and the internal cell body. The cell itself is helical and, when the filaments rotate, driven by the proton gradient, the rotation of the filament drives the cell wall to rotate in the opposite direction to the cell body. The helical cell then screws its way through the environment,an optimum swimming mechanism for species that are often found in viscous environments, including mucous membranes (Goldstein and Charon, 1988; Charon et al., 1992). There has been a recent suggestion that the shape of a bacterial species has developed to allow efficient swimming and tactic signalling. Thus, a rodshaped cell is best suited to the life of a motile but very small organism, reducing the effects of Brownian motion when compared to coccoid cells, and increasing the efficiency of temporal gradient sensing (Dusenbery, 1998). Little is known about the mechanisms involved in gliding, and it is possible that there is more than one mechanism, particularly given the different gliding behaviours of different species and the contradictory data (Youderian, 1998). For example, Flavobacterium (Cytophaga)johnsoniae can glide at speeds comparable to some flagellate swimming rates (10 p d s ) , moving swiftly over a surface and then suddenly up-ending and flipping over, to glide off at speed in a new direction (Pate and De Jong, 1990; Beatson and Marshall, 1994). On the other hand, species such as Myxococcus xanthus may glide only at rates of 10 p d m i n , changing direction by reversing the gliding direction (Hartzell and Youderian, 1995; Ward and Zusman, 1997). Whether gliding depends on extracellular slime, rotation of structures similar to flagellar motors, anchor points, rotation of the cell along surfaces or some other mechanism is unknown. However, it may well be that different species use different mechanisms and gliding has evolved independently in different genera.

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4.2. Patterns of Swimming

All bacterial species swim in a similar pattern. Smooth swimming is punctuated periodically with a change in direction. This usually occurs every few seconds. In E. coli, smooth swimming is the result of the six or so flagella all rotating in a counterclockwise (CCW) direction and coming together as a rotating bundle. Periodically, the flagellar motors switch to clockwise (CW) rotation, forcing the bundle apart as the wavelength and handedness of the filament changes, causing the cell to tumble on the spot. Spirillum volutans, on the other hand, has tufts of polar flagella, while Pseudomonas aeruginosa has a single polar flagellum. In these cells, direction changing is brought about by simply switching the direction of motor rotation and reversing swimming direction. In spirochetes, changing the direction of rotation of the internalized flagella results in flexing of the cell body. Bacteria are buffeted by their environment and that means, together with the natural curving caused by a rotating filament, they rarely swim in straight lines (see Armitage and Packer, 1997; Berry and Armitage, this volume). There is some evidence that this is a more efficient way for bacteria to swim through environments that may have a high particulate composition, and certainly many soil species have polar flagella (Duffy and Ford, 1997). Yet other species, e.g. Rhodobacter sphaeroides and S. meliloti, change direction by stopping or slowing filament rotation (Armitage and Macnab, 1987; Armitage and Schmitt, 1997). In all cases, the result is a random pattern of swimming through an environment. This random, three-dimensional swimming pattern is biased by environmental gradients to move the bacteria towards their optimum environment for growth. In general, bacteria swim for longer when moving in a positive direction, towards an attractant or away from a repellent. They still change direction

Transmembrane

Figure I The different sensory stimuli sensed by motile bacteria and which lead to changes in swimming behaviour.

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periodically, but if this results in moving down a gradient they will change direction again at close to the unstimulated rate, whereas, if they are going in the positive direction, the period will be longer, biasing the overall direction (Frymier et al., 1995). Some species have the reverse pattern: R. sphaeroides changes direction more often when moving down a gradient, while swimming up the gradient has little effect (Packer et al., 1996). The overall result is, however, the same; a biased pattern of swimming, moving the population towards an improving environment for growth. Bacteria can respond to a wide range of stimuli, from pH changes to oxygen levels (Fig. 1). These all have to be balanced to produce an overall response. The best understood system is that of E. coli.

5. THE CHEMOSENSORY PATHWAY OF E. COLl

The best understood chemosensory system is that of the two enteric species, E. coli and Salmonella typhimurium. In the late 196Os, Julius Adler showed that transport and metabolism were not required for chemotaxis by E. coli, as transport mutants were still chemotactic, while specific chemotaxis mutants could still metabolize the chemoattractant. In addition, analogues that could not be metabolized were still attractants (Adler, 1976). He isolated mutants that had lost responses to one chemoattractant,but still responded to others and was able to identify three chemoreceptors,Tsr (serine receptor), Tar (aspartate and maltose), and Trg (ribose and galactose). A fourth receptor, Tap (dipeptides), was identified later. Tap is found in E. coli, but not Salmonella. Salmonella has a receptor, Tcp, for citrate, which is not a carbon source for E. coli (Stock and Surette, 1996). This illustrates that even the pathways of two very closely related species have adapted to the metabolic requirements of that species. Methionine auxotrophs were found to lose chemotaxis if starved of methionine. This led to the discovery that S-adenosyl methionine was required for chemotaxis and was involved in post-translational modification of a number of membrane proteins, the extent of post-translational labelling by methionine being dependent on whether an attractant had been added or removed (Kort et al., 1972; Hazelbauer and Engstrom, 1981). The overall view of chemotaxis in E. coli, and therefore every other bacterial species, was that one of a limited number of attractants bound to transmembrane receptors and, as a result, a signal was generated which resulted in post-translational modification of the receptors. Mutants that lost all chemosensory behaviour, but still swam, allowed identification of five genes responsible for general chemosensory signal transduction. These, eventually called che8, cheR, cheA, cheY and cheZ, were assumed to encode the intracellular signalling sequence to the flagellar motor (Fig. 2).

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Environmental signal

d

inner membrane f

peptidoglycan layer I

outer membrane

Figure 2 The chemosensory pathway of Escherichia coli. Signals coming through the receptors (MCPs, Aer or PTS) signal through the phospho-relay pathway of CheA, the histidine protein kinase, to the two responses regulators: CheY, which when phosphorylated binds to the motor to cause switching; and CheB, the methyl esterase involved in adaptation. MCP = methyl accepting chemotaxis protein; Aer=oxygen sensor; PTS=phosphotransferase transport system; W = Chew, A = CheA; Y = CheY; 2 = CheZ R = CheR; B = CheB; El = enzyme 1 of PTS transport system, common to all PTS transporters.

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5.1. Chemoreceptors

The chemoreceptorsof E. coli are all built on the same basic design (Fig. 3) and analysis of the chemoreceptors of a wide range of species has identified within that design a common domain necessary for sensory transduction - see Fake el al. (1997) for an overview. The four E. coli chemoreceptors are each between 533 and 553 amino acids in length, have two membrane-spanningdomains that result in a large periplasmic domain and a large cytoplasmic C-terminal domain. There is very little homology between the periplasmic domains on a sequence level, nor is there obvious similarity between the transmembrane domains. However, the cytoplasmic domain is very highly conserved between transducers. Indeed, it is this cytoplasmic highly conserved domain that is common to all chemosensory transducers across the bacterial and archaeal world. 5.I . I . Periplasmic Domain

The chemoreceptors, often called methyll-accepting chemotaxis proteins or MCPs, form stable dimers in the cell membrane (Milligan and Koshland, 1988). As would be expected, there is little sequence homology between the periplasmic domains of the different MCPs, as they ‘sense’ different molecules. What was very puzzling for a long time was the mechanism involved in sensing two completely different stimuli. Tar, for example, responds not only to changes in the concentration of the amino acid aspartate, but also to the change in concentration of a sugar, in this case maltose, bound to its periplasmic binding protein (PBP) (Gardina et al., 1997). The family of periplasmic binding proteins usually act to transport a wide range of specific ligands to their cytoplasmic membrane-spanning transport proteins but, in E. coli, the maltose, galactose, ribose and dipeptide PBPs have an additional role. When bound, they can interact with one of the MCPs. This has interesting implications for the sensing of the two chemoeffectors acting through Tar. Tar is expressed as part of the flagellum and chemosensory regulon and, as aspartate interacts directly with Tar, interaction will be directly related to the extracellular concentration of the amino acid. Expression of the maltose PBP, on the other hand, is under the control of the maltose transport system and the response will depend on the level of its expression. The relative response to aspartate and maltose therefore changes under different growth conditions. Other sugars cause chemotactic responses as a result of transport through the phosphotransferase sugar system (see below). Since Tar is able to respond to binding by both a small amino acid, aspartate, and a large protein, the maltose PBP, there has been a good deal of investigation into the mechanisms involved. If E. coli is subjected to an increase in both maltose and aspartate, the chemotactic response is additive,

Figure 3 Diagram of the Escherichia chemoreceptor dimer. Tar.A, dimer alone; B. dimer with associated proteins; MBP = maltose binding protein; asp = aspartate: A = aspartate binding site; TMI and TM2 = transmembrane domains 1 and 2; 0 , site of methylation. Adapted from Falke et al. (1997) with permission.

N

f

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almost equal to the sum of responses that would have occurred to the addition of each of the effectors alone. The homodimeric periplasmic domains of Tar from both E. coli and S.typhimurium have been crystallized with and without aspartate bound, and subjected to extensive mutational analysis (Biemann and Koshland, 1994; Danielson et al., 1994;Yeh et al., 1996).Purified periplasmic domains retain their wild-type binding kinetics for aspartate and are unaffected by solubilization in octylglucoside, suggesting that the behaviour of purified domains and the crystal structures provide an accurate picture of activity in vivo. Strong negative cooperativity is shown by aspartate binding to Tar of E. coli, suggesting that the binding of one molecule to one subunit substantially reduces the affinity of the second aspartate binding site for its ligand. Mutants can be constructed that lose the response to maltose, but not to aspartate, and vice versa. The crystal structure of the dimer shows two fourhelix bundles, with aspartate bound at the dimer interface to one of two non-overlapping antiparallel rotationally symmetrical binding sites. Mutational studies also suggest that the maltose-binding protein interacts with both subunits of the Tar dimer, binding at one of the two symmetrical non-overlapping sites which differ from the aspartate binding site (Gardina et al., 1997).The crystal structures and genetic analysis have led to a model in which the effector interaction occurs at the interface of the two monomers. Steric hindrance prevents the binding of two MBPs at once, and only one aspartate-binding site is accessible to solvent at any one time. Interestingly, when chimeras were constructed in which the periplasmic and cytoplasmic domains of the individual monomers were engineered so that the binding sites on the monomers were in either the same or the opposite orientation, it was found that aspartate and maltose could transmit signals independently if the sites were in the opposing orientation. However, signalling by one attractant was inhibited if a saturating concentration of the other was added and the subunits were in the same orientation, suggesting the two attractants were then competing for signalling through one subunit (Weerasuriya et al., 1998). In a wild-type dimer, the attractants can bind in either the same or opposing orientations, and this may well explain the partial additive responses seen when both attractants are added simultaneously. As Tar has been crystallized, its structure, combined with the genetic analysis of behaviour, has been used to model the binding and structural changes of the other MCPs of E. coli, particularly Tsr and Trg. Genetic studies had predicted binding sites for serine on Tsr, with one residue binding per dimer. The same negative cooperativity is seen for serine binding that is found for aspartate binding, suggesting a similar mechanism (Lin et al., 1994). Modelling the binding domain on to the Tar structure puts the important residues into a binding pocket similar to that identified in Tar. Comparisons with Tcp, the citrate receptor, suggest that the small molecule ligand-binding motif is shared amongst the chemoreceptors. The negative cooperativity and asymmetrical

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binding of the chemoattractants breaks the symmetry of the dimer (Yamamoto and Imae, 1993). It seems likely that this is an important mechanism in signalling.

5.1.2. Transmembrane Signalling Once the ligand has bound, this has to be signalled across the membrane to the cytoplasmic domain of the MCP. Many eukaryotic receptors signal by dimerization of monomers, but MCPs are known to form stable dimers; covalent dimers produced by disulfide inter-subunit linking can still signal. The dimer results in four transmembrane a-helices, two from each monomer. These tend to be called TMl and TM2 for one monomer and TMl’ and TM2’ for the second. Extensive studies have been carried out on the possible mechanisms involved in signalling across the membrane, involving large-scale cysteine substitution to cross-link different regions of the a-helices, and revertant and second site suppressor studies of signalling mutants to identify the interface of the transmembrane helices (Danielson et al., 1994; Chervitz and Falke, 1995). Combined with solution nuclear magnetic resonance (NMR), the results of these studies suggest that the a-helices form a loose four-helix bundle with the TMls associated along one face. Results indicate that one of the transmembrane helices, TM2, rotates as a result of the signal from attractant binding, which signals through one of the a-helices (a4)of the periplasmic domain (Luck and Falke, 1991; Falke etal., 1992; Lee et al., 1995). Crystal structures of the periplasmic domains that signal through to the TM a-helices suggest that there is a small vertical movement of the TM2 helix in the membrane and a slight tilt. Binding of an attractant is therefore thought to signal through to the cytoplasmic domain by the movement of one of the TM2 transmembrane helices with respect to the relatively fixed central axis of the TM 1s. However, these changes may be just one, major, component of signal transduction. It now seems possible that effector binding may also bring together numbers of receptor dimers in clusters, allowing the cytoplasmic domains to interact and control the strength of signal (Levit et al., 1998).

5.1.3. Cytoplasmic Domain Whether the major signal is the result of transmembrane signalling or the formation of receptor clusters, the change in receptor binding has to change the cytoplasmic domain in such a way that the cytoplasmic signalling sequence is set in train as well as eventual adaptation of the receptor to block the generation of the signal. The cytoplasmic domain of the MCPs is very highly conserved, particularly the central signalling region. Well in excess of 60

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MCPs from different bacterial species have been sequenced, from all the eubacterial subgroups and from archaea, and all show extensive conservation of the cytoplasmic signalling domain (Morgan et al., 1993; LeMoual and Koshland, 1996).The signalling domain is conserved not only between ‘classical’ sensory receptors with periplasmic domains and transmembrane signalling, but also in cytoplasmic receptors homologues which have been identified in species as diverse as R. sphaeroides and Halobacterium salinarium. Receptors with this conserved signalling domain have also been identified that sense oxygen via bound redox groups. The general conservation of this signalling domain between such diverse sensory proteins suggests that this domain is the early central component of the signalling pathway and the sensory domains have been added according to the niche of the species. The cytoplasmic domain is made up of ten a-helices (five from each monomer) which have been divided into domains on the strength of mutational studies. There is a region called the methylation domains which comprises the region just below the a-helical linker domain, which links the transmembrane helices to the cytoplasmic domain and the C-terminal end of the MCP. Together they appear to form a coiled-coil structure (LeMoual and Koshland, 1996). These contain the glutamate and glutamine residues which are methylated by the S-adenosyl methionine-dependent methyl transferase, CheR, during receptor adaptation (see below). Between these two regions is the highly conserved signalling domain. The signalling domain is the site of interaction with Chew and CheA, the proteins involved in initiating cytoplasmic signalling to the motor, and is the region highly conserved across species (LeMoual and Koshland, 1996). Genetic studies show that mutations within this domain can result in cells which are either predominantly smooth swimming or predominantly tumbly, suggesting that this region controls the activity of the histidine protein kinase, CheA (Ames and Parkinson, 1994). 5.2. Cytoplasmic Signalling

A small protein, the 18 kDa Chew, links the signalling domain of the MCP to the histidine protein kinase, CheA (Borkovich et al., 1989). Little is known about this protein, as the E. coli Chew tends to form aggregates and it has not been studied in detail by structural methods. Recent data, however, indicate that Chew, from R. sphaemides forms dimers (D.S.H. Shah, S.L.Lee and J.P. Armitage, unpublished). It has no known catalytic activity but, without it signalling stops. Although it is thought to be a simple scaffolding protein, transmitting the conformationalchanges in the signalling domain to the kinase, its structure is fairly well conserved between species. Some chew from an

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a subgroup species, such as R. sphaeroides, can suppress a Chew defect in E.coli (Hamblin er al., 1997a, D.S.H. Shah and J.P. Armitage, unpublished data). The signalling domain of the MCP, Chew and CheA form a quaternary complex in vitm (Bourret et al., 1991). The MCP binding region of Chew has been identified by mutagenesis, but the region binding to CheA has yet to be identified. Chew binds to the C-terminal domain of CheA, a soluble histidine protein kinase (HPK) homodimer (Surette et al., 1996). CheA belongs to the extensive family of HPKs identified in a wide range of bacterial species. All HPKs have a characteristic kinase domain, which in CheA is located towards the C-terminal end and characterized by four boxes (the N, D, F and G boxes) (Fig. 4). This region probably binds Mg-ATP. CheA functions as a dimer and ATP binding to the conserved domain allows the protein to phosphorylate a conserved histidine, His-48, on the other monomer of the dimer, located near the N-terminus of the protein (Hess et al., 1987, 1988). The catalytic domain can be isolated independently and is still capable of transferring phosphate to His48 (Swanson et al., 1993). Isolated CheA has a slow rate of autophosphorylation,about 10’ min (Surette et al., 1996). The rate is reduced if CheA is bound to attractant-bound MCPs and this increases 100-fold if the MCP is unbound (Borkovich and Simon, 1990). The region containing His-48, known as P1, also has a structure conserved in other HPKs. Purified P1 has no enzymatic activity, but can be phosphorylated by another kinase, after which it can function alone to transfer phosphate to its substrates CheY and CheB (Swanson et al., 1993; Morrison and Parkinson, 1994). The phosphoramidate bond of phospho-His is very unstable compared to, for example, phospho-Ser, as the standard free energy of phosphotransfer from ATP to His is positive. Phospho-CheA can phosphorylate ADP to ATP in vitro. It is assumed that in vivo the high intracellular concentration of ATP and the rapid transfer of the phosphate to the substrate proteins keeps a high rate of CheA autophosphorylation operating with little back reaction, but that may not be the case in species with two copies of CheY (see below). Between the conserved histidine and the domain involved in ATP binding is a domain, P2, which binds CheY and CheB, the eventual substrates of CheA. This domain can be released and remains folded as an antiparallel P-sheet with two antiparallel helices on one surface. This fragment has been crystallized 1

H48

H

Phorphotranrfer CheY,B (W (P1)

ND FG Hlstldlne klnare CheA dlmedsatlon

I

651

Chew MCP blndlng

Figure 4 Domain organization of CheA showing the regions involved in binding the different chemosensory proteins and conserved amino acids.

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with CheY bound, and the structure and mutagenesis studies show that the ligands, CheY and CheB, are competitive for binding and dock at a specific hydrophobic region near the end of one of the helices (Parkinson and Kofoid, 1992; Li et al., 1995; Welch et al., 1998). The ligands still bind when the P1 domain is removed. The CheY binding domain is flanked by two very flexible regions which appear to allow this domain to move rapidly and independently of the rest of the CheA molecule. The P2 domain is not present in many other HPK molecules, which suggests that the binding to this mobile domain has a specific function in CheA and its homologues. It has been suggested that the mobility allows fast inter-domain phosphotransfer, resulting in an amplified signal.

5.3. CheY The bacterial phospho-relay systems rely on a signal causing the autophosphorylation of an HPK which then transfers the phosphate to an aspartate kinase (response regulator), which can then carry out a cellular function, usually DNA binding to control transcriptional activity (Kofoid and Parkinson, 1988; Stock et al., 1995). In chemotaxis, this is somewhat different as the substrates for CheA phosphorylation are not transcriptional activators. CheA phosphorylates two competing response regulators, CheY and CheB. CheY has attracted a great deal of interest as not only is it the molecule that controls the direction of flagellar rotation, but it is the prototypical response regulator, having only the aspartate receiver domain of response regulators and no other domains. CheY was identified as the molecule involved in controlling chemotaxis by using tethered, flagellate sphaeroplasts of E. coli. It had earlier been shown that ionotophoresing an attractant at one end of a filamentous E. coli cell resulted in a signal being transmitted part of the way down the filament (measured by the increased smooth rotation of motors close to the site of stimulation).The time taken for the signal to move from motor to motor and the distance the signal travelled indicated a small diffusible molecule, rather than an electrical signal (Block et al., 1982). In addition, it was shown that flagellate, tethered sphaeroplasts of E. coli rotated primarily CCW but, when CheY-P was added to the lysis medium, they switched to CW rotation (Ravid et al., 1986; Barak and Eisenbach, 1992a). Mutants with cheY deleted or mutated are smooth swimming, i.e. they cannot switch, rotating their flagella exclusively CCW. The results, taken together with recent crystallography studies, suggest that CheY binds to the P2 domain of CheA and that phosphate is transferred from His-48 in a reversible reaction to generate phospho-CheY.This is released from P2 and diffuses through the cell to the motor, binding to FliM of the switch and increasing the probability of switching to CW, probably by reducing the energy barrier between CCW and CW rotation (Welch et al., 1993, 1994).

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CheY, being only 14 kDa, has been crystallized and studied by solution NMR under a range of conditions, including recently in a phosphorylated conformation (Stock et al., 1989, 1993; Moy et al., 1994). The structure of CheY is probably common to the phosphorylation domains of all response regulators. It has five a-helices surrounding a five-stranded parallel P-sheet structure, with the phosphorylation site on aspartate 57. Asp-57 mutants are not phosphorylated and this residue is conserved in all response regulators. In addition, there is another group of conserved acidic, usually aspartate, residues that are located close to the active site. Together they form an acidic pocket. Phosphorylation depends on Mg2+and involves CheY itself acting as a phosphotransferase. Indeed, it can take phosphate from several metabolic phosphodonors such as carbamoyl phosphate or acetyl phosphate, although whether this has a role under natural conditions is unknown (Lukat et al., 1991). Mg2+probably serves to stabilize the transition state, probably a pentavalent phosphate allowing Asp-57 to carry out a nucleophilic attack on the phospho-histidine. Proton donation, to allow phosphate transfer from the phosphohistidine of CheA, probably requires the conserved lysine found close to the acid pocket. NMR studies indicate that a phosphotransfer to Asp-57 results in a large conformational change and, when phosphorylated, the affinity of CheY for CheA decreases, but increases for the switch protein FliM (Lowry et al., 1994). Mutational and NMR data have identified three distinct regions on CheY that interact with its three protein effectors, P2 of CheA, FliM and CheZ, and all are distinct from the phosphorylation site. Dephosphorylation of CheY-P occurs autocatalyticallywith a half-time of under 10 s. This is in contrast to many other response regulators that remain phosphorylated for many tens of minutes, and reflects the need for a fast signal and signal termination, which is not required on this time scale for transcriptional control. However, this rate of autodephosphorylationis not fast enough for signal termination in chemotaxis and a second protein (CheZ) is brought in to increase the rate in enteric species (Eisenbach, 1996). CheZ is not well characterized. It has been isolated as a dimer, but also as a high-order oligomer with phospho-CheY but not CheY, and it appears to compete with FliM for CheY-P but not CheY (Blat and Eisenbach, 1994, 1996a,b).The oligomer is thought to increase the rate of hydrolysis. CheZ homologues have not been found in species outside the y-subgroup. Bacteria from other subgroups, however, often have two copies of CheY, one often fused to either a Chew or CheA homologue CheA. It seems probable that signal termination occurs through the activities of these two CheYs. In S. meliloti it has been shown that one CheY can interact with the motor, but the second apparently does not (Sourjik and Schmitt, 1998). Both are, however, phosphorylated and, as CheY-P can also act as a kinase, it is possible that the reversible phosphorylation of CheA by CheY-P and its transfer to the CheY,which is unable to bind the motor, could act as a phosphate sink and

A

i --t

+

tlpB

UpA

H H l l U + +--t

+

orf9 orflcheK

cheA

n u

I 3

---t

off10 cheYnl

cheAu

&

d

chew

cheR

+

+ ++ c h e Y ~orf20rf3

n +U

cheWn cheWm

+

+

cheRn

cheB

i

B

-II

U d

+

d

+

+

--+

+

mob4

mots

cheA

chew

tar

cheR

cheB

&&

cheY cheZ

Figure 5 Comparison between operon organization of Rhodobacter sphaeroides (A) and Escherichia coli (B). tlp, transducer-like protein, coding for MCP-like proteins without two transmembrane domains.movi and motB, motor proteins. For other abbreviations, see text.

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serve to terminate the signal. In these cases, the kinetics have not been fully characterized and the full mechanisms remain to be elucidated. R. sphaeroides has two operons coding for sets of chemosensory proteins (Fig. 5 ) (see later) including four CheY homologues. Each operon appears to have CheY genes associated with it. Only one of the homologues, CheY4, can bind to the motor switch. All 4CheYs, however, can suppress a CheZ mutation in E. Coli, supporting their role as putative phosphate sinks (D.S.H. Shah, D.C. Harris and J.P. Armitage, unpublished). Recently, genome sequencing has shown that C.crescentus has two chemosensory operons, which also include four cheY and no cheZ genes. 5.4. Adaptation

CheA not only transfers its phosphate to CheY but can also phosphorylate another response regulator, CheB. CheB is again an unusual response regulator as it has, in addition to the regulatory domain of a standard response regulator, a catalytic domain: a methyl esterase. The activity of the methyl esterase is controlled by whether or not the aspartate-containing domain is phosphorylated, phosphorylation increasing activity by an order of magnitude (Lupas and Stock, 1989). Adaptation is an essential part of chemotaxis. If the receptor did not in some way reset after encountering a change in receptor occupancy, the receptor would continue to generate a signal and the cell would be unable to respond to future changes. In fact, mutants in the adaptation mechanism are either smooth swimming, CheB mutants or constantly tumbly, CheR mutants. Therefore, although the signallingpathway is intact, a gradient cannot be sensed without the ability to reset the receptor. The cytoplasmic domains of most MCPs have two regions which have conserved glutamate residues that serve as substrates for the two enzymes involved in receptor adaptation, namely, CheR, the methyl transferase and CheB, the methyl esterase. In E. coli there are three methylation sites on one domain and one on the C-terminal domain. The glutamates may be transcribed as glutamines, but CheB can post-translationally deamidate the amino acid to form glutamate (Sherris and Parkinson, 1981). The combination of charged glutamates and uncharged glutamines results in a ‘neutral’signalling protein being inserted into the membrane after translation. Mutants deleted for CheR cannot methylate the receptors and constantly tumble, while CheB mutants have overmethylated receptors and smooth swim constantly. The methylation sites appear to lie on the same face of an a-helix. In a simplified model, the decrease in attractant bound to a receptor would change the conformation of the cytoplasmic domain of the receptor and increase the autophosphorylation rate of CheA. CheY and CheB compete for binding to P2 and phospho-CheB becomes an active methyl esterase. This can then remove methyls from the

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Figure 6 Clustering of MCPs in Rhodobacter sphaeroides grown under different conditions. (a) Aerobic cells with clusters of MCPs at the poles (large arrows) and in the cytoplasm (small arrow). (b) Photosynthetically grown cells with few polar MCPs (large arrows) but a cytoplasmic cluster (small arrow) (adapted from Harrison et al., 1997).

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conserved glutamates of the relevant MCP. This change in methylation (in which the methyls are released as methanol) alters the packing of the methylation helices and reduces the signal through the signalling domain to CheA (Fig. 4).As there are four methylation sites that can be methylated independently to alter the helical configuration, this allows adaptation over a range of stimulus strengths. However, experimental studies suggest that the difference in histidine kinase activity can vary 50-fold between fully demethylated and fully methylated MCP; this is much greater than this model would suggest, and adds strength to the idea that many cytoplasmic domains may be involved (see later). This process of post-translational reversible carboxymethylation of glutamates appears unique to bacterial chemotaxis. There is no phosphatase to increase the rate of CheB dephosphorylation and the protein therefore has evolved a more rapid rate of autocatalytic dephosphorylation than CheY-P. The methyl groups are added to the glutamates by a specific methyl transferase, CheR, which has been crystallized and the structure elucidated (Djordjevic and Stock, 1997). There is a specific CheR docking motif on the very C-terminal end of some, but not all, MCPs. In E. coli and S. typhimurium Tsr, Tar and Tcp have a CheR-binding domain but Trg and Tap do not, although they are still methylated in response to attractant binding. Trg is not, however, methylated if Tsr or Tar are not present in the membrane, suggesting that the CheR bound to Tsr or Tar can methylate the glutamate residues of Trg and indicating that they may be physically close in the membrane (Feng et al., 1997). It has been assumed that CheR may be free as a pool in the cytoplasm, along with CheB. However, R. sphaeroides, which has two sets of chemosensory proteins, has two copies of cheR but only one cheB (Hamblin et al., 1997b).This may suggest that CheR molecules are generally attached to ‘their’MCPs while CheB is free to diffuse between the receptors. 5.5. Localization of MCPs

Early studies of MCPs suggested that they were randomly located around the cell. However, antibodies raised to MCPs of C. crescentus were found to be clustered at the pole of the cell when examined by immunogold electron microscopy (Alley et al., 1992).It was possible that this was a characteristic of C. crescentus, as this species undergoes a differentiation cycle, with nonmotile stalked cells dividing to release non-growing but motile, chemotactic swarmer cells with single polar flagella. It was thought that the polar MCPs may simply be the result of targeting them to the swanner cell before cell division. However, this was shown not to be the case when similar studies found clusters of MCPs at the poles of E. coli cells (Maddock and Shapiro, 1993). Since then, MCPs have also been found to cluster at the poles of R.

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sphaeroides, but in addition they are also found in a cytoplasmic cluster in this species (Harrison et al., 1998) (see later and Fig. 6). Detailed measurement of the numbers found at the poles of E. coli suggest that the MCPs are targeted after cell division, as one pole always has significantly larger numbers than the other, but during cell growth the number appears to increase. If mutants lacking Chew or CheA were examined, the polar clusters disappeared and the MCPs were found dispersed over the surface of the cells. These two proteins are therefore essential for localization of MCPs. 5.6. Why are MCPs Targeted to the Poles?

5.6.I . Sensitivity and Gain

There are several reasons why MCPs might be located at the poles. One suggestion was that bacteria may in fact have a ‘nose’and that clustering receptors may help in gradient measurement. This cannot be the case (Berg and Turner, 1995).Almost all bacteria are too small to sense a gradient along their length, and there is no evidence at all that they swim with any pole forward. Indeed, R. sphaeroides has a flagellum which is subpolar, causing the cell to swim with the long side of the cell forward, but the MCPs are still at the two poles. A second possibility is that this is simply the default location. Many proteins appear to default to the previous septation site, and the several thousand MCPs not required for transport or energy-producing processes may localize there. Recent work has, however, suggested that localization may indeed have a purpose, and has suggested an alternative, or a more complex, signalling mechanism. As mentioned above, mutants with only Trg or Tap MCPs can no longer respond to their chemoeffectors and are not methylated, but if Tsr or Tar are expressed, although these MCPs cannot bind or sense the effectors for the other two MCPs, E. coli can now respond via these MCPs and they are now methylated. Trg and Tap lack the CheR-binding domains and it was therefore suggested that the CheR bound to the other, more numerous, MCPs was methylating the other two MCPs, thus allowing signalling (Feng et al., 1997). If this is the case, the MCPs must be in close proximity. The studies on receptor signalling described earlier all relied on a stable MCP dimer signalling through the transmembrane domains to the bound pair of Chew proteins, and thus through to the CheA dimer and the soluble CheY. This was to some extent supported by surface plasmon resonance studies (Simon et al., 1989). It has been suggested that this stable dimer signalling does not really explain the problems of the sensitivity of signalling nor the range. In more recent studies, the conserved cytoplasmic domains of Tar MCPs were linked together using leucine zippers, a technique which allowed the formation of soluble complexes with an apparent stoichiometry of seven MCP

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dimers to 2-4 molecules of Chew per CheA dimer (Liu et al., 1997). Electron microscopy suggested that the complexes were held together by interactions via Chew and CheA, and that the structure could duplicate by zipper interaction. This allows for the formation of large complexes. The incorporation of CheA into the complexes increased the rate of CheA autophosphorylation 100-fold, as did the incorporation of Chew and CheA into MCP complexes in intact membranes. This has led to an alternative signalling hypothesis in which the change in binding of the effector to the periplasmic domain may alter the packing of the MCPs, with this altering the packing of the cytoplasmic domains (Bray et al., 1998; Levit et al., 1998). Thus, a repellent would alter packing such that CheA would become active, while the addition of an attractant would hold CheA in an inhibited conformation. The glutamate residues involved in adaptation would therefore cause signalling because of electrostatic repulsion between cytoplasmic domains. When methylated, the charges would be masked and the conformation become active, while, when demethylated, the glutamate charges would result in repulsion and conformational change and signalling. Higher order interaction between receptor dimers would therefore be essential for signalling, hence the polar clusters (Fig. 5). The mechanism for signal transduction may turn out to be a combination of transmembrane signalling and receptor clustering. More experiments with transmembrane and cytoplasmic receptors are required to elucidate the complete mechanism. A model based on signalling through the formation of receptor clustering has been proposed in which the dynamic range of sensitivity seen in bacterial chemosensing depends on controlling the sizes of the receptor clusters, the extent of lateral packing controlling the signal (Bray et al., 1998).Thus, a bacterial cell would be able to respond to a change of a few molecules over background concentrations of orders of magnitude, which is what it does. Whether this level of gain is required at the receptor level does, however, remain controversial. 5.7. Phosphotransferase Sugars

E. coli responds not only to the binding of sugar-binding proteins to MCPs but also shows responses to certain sugars independently of these MCPs. These are sugars transported through the phosphoenolpyruvate-dependent phosphotransferase system (PTS). E. coli has at least 15 PTS systems. Membrane-bound substrate-specific transport proteins, Enzymes I1 or EII, accept phosphate from a non-specific donor enzyme, Enzyme I or EI, and phosphorylate the sugar as it is transported. EI, a PEP-dependent histidine kinase and a phosphohistidine carrier protein (HPr) are the phospho-relay to the Ens. Although metabolism of the sugar is not required for a chemotactic response, the sugar must be transported to cause a signal (Postma et al., 1993).

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JUDITH P. ARMITAGE

Methylation is not required for signalling to occur, but CheA and CheY are necessary. EI of the PTS'has been shown to interact directly with CheA, suggesting that EI, when actively involved in transporting sugars, suppresses CheA phosphorylation, resulting in smooth swimming (Lux et al., 1995; Lengeler and Jahreis, 1996). Interestingly, fructose is transported via a rather different PTS system where phosphorylation relies on Fpr,a fusion between an HPr-like protein and EL This protein does not cause a chemotaxis signal and E. coli transporting via this pathway is not chemotactic to fructose. R. sphaeroides has only an FPr PTS and its chemotactic response to fructose depends not on PTS transport, but metabolism of the sugar (Jeziore et al., 1998). 5.8. Thermotaxis

E. coli responds not only to changes in chemical concentration but also to changes in temperature by changing its swimming behaviour (Mizuno and Imae, 1984; Imae, 1985). Early studies found that cells did not swim towards their optimum growth temperature, but towards the temperature at which they had been grown, biasing their swimming pattern from either a lower or higher temperature. However, mutants in the serine receptor, Tsr, lost this response, as did cells incubated in a saturating concentration of serine. This led to the idea that temperature could alter the conformation of the cytoplasmic signalling domain of Tsr and cause a sensory signal, but this was inhibited if the receptor was fully occupied and a conformational change could not be induced. More recent studies have shown that it is not only Tsr that can signal a change in temperature but also the other sensory proteins (Nara et al., 1991; Nishiyama et al., 1997). 5.9. Repellent Sensing

In general, studies on chemotaxis in E. coli have been carried out using the removal of an attractant or addition of a repellent as the signal. Addition of a repellent results in a change in receptor methylation similar to the removal of the attractant, but the characteristics of the response have never been as clearcut. E. coli shows repellent responses to metal ions, such as Ni and Co, to changes in pH, amino acids (such as leucine), and organic acids (such as acetate). The last two are compounds that can act as growth substrates; indeed, E. coli grows very well on acetate. Why E. coli should be repelled by good metabolites is not understood, but may indicate a more non-specific mechanism involved in the responses than sensing of attractants. While Tsr appears to be the major receptor for repellents, the other receptors

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can be involved and changes in methylation may affect all receptors (Eisenbach et al., 1990; Yamamoto et al., 1990; Hanlon et al., 1992). The responses to organic acids and pH may all involve changes to the cytoplasmic signalling domain of the MCPs (Repaske and Adler, 1981; Slonczewski et al., 1982).The simultaneous release of ‘caged’ positive and negative chemoeffectors by a flash of ultraviolet light and the use of time-resolved motion analysis suggested that, while single receptors time-averaged different ligands, if effectors using two different receptors were used, a non-integrated response could result, with the cells initially tumbling and then swimming smoothly. This indicated that the processing time for the signals through different receptors may not be identical and the signals may not be of the same strength (Khan et al., 1995). (‘Caged’ compounds are chemoeffectors chemically bound to a large molecule which can be released by photolysis to produce a step-up in effector concentration within a very short and measurable time frame.) Responses to repellents are still not well understood, although they provide a useful tool for measuring response kinetics. Interestingly, no repellents have been identified for R. sphaeroides and it remains to be identified whether this is the result of structural differences in the MCPs. Osmotaxis was one of the early responses measured by Pfeffer, with bacterial cells being shown to respond to their osmotic environment. The relationship between osmotaxis and chemotaxis is not really understood. E. coli is attracted to its optimum concentration of an osmotic agent, such as sucrose or ribitol, and repelled by higher or lower concentrations. These responses appear to be independent of the MCP receptors (Martinac et al., 1987,1990; Adler et al., 1988; Buechner et al., 1990). There is some evidence that responses may be linked to pressure gated ion channels (Martinac et al; 1990). 5.10. Variations on a Theme

The chemosensory signalling pathway is fairly well understood in E. coli, although a great deal of work still needs to be carried out on the mechanisms involved in receptor clustering and their role in sensory signalling and, as yet, the mechanisms involved in CheY-P controlling motor switching and the mechanisms of signal termination are still not understood. However, it is still probably the best understood sensory system in biology. Does the E. coli model apply to other species? In general, the few species studied in detail seem to have the central signalling pathway of receptor, Chew, CheA and CheY, but on to this have been added a range of different inputs and combinations of sensory proteins. Table 1 lists a number of species where the chemosensory genes have in part or completely (because of genome sequencing) been identified, and illustrates the variety of combinations of chemosensory genes that are

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Table I Some of the combinations of chemosensory proteins identified by genome sequencing and behavioural studies. Asterisks indicate species with complete genome sequences; the genes are therefore mainly identified by homology. The other species have had the genes identified by phenotypic analysis and there may be more genes to be identified. All species in which chemosensory genes have been investigated have proteins with the conserved cytoplasmic signalling domain of the MCP, CheA, Chew and CheY although the copy numbers of each can vary greatly. CheZ has only been identified in enteric species. The motile archaebacterium Methanococcusjannaschii interestingly appears to have no che genes in its complete genome sequence Organism

MCP CheA Chew CheY CheZ CheB CheR A-Y W-Y Y-Y

E. coli* B. subtilis" H. pylori* B. burgdotferi I: pallidurn* C.crescentus R. sphueroides R. centenurn M.xanthus

5 10 3 5 4 13 12 ?

?6

1 1 1 2 1 2 2 1 2

1 1 1 4 2 4 3 1

3

1

1 1 4 I 4 4 1 2

1

1

1

2 1 2 1 I 1

1 1

1 3

2 1 2 2 1

2

1 1

1

emerging. In many cases, although the genes have been identified, little is known of their function. For example, why does Helicobacter pylori have three chew-cheY (cheV)fusions, but no cheB or cheR and are these involved in adaptation? The straightforward E. coli system obviously evolved for its lifestyle and other more complex systems have evolved for different niches. The numbers of MCPs and the chemicals sensed through them varies greatly from species to species. E. coli has only four MCPs, all transmernbrane, and one related receptor, Aer,which may be in the membrane and senses respiratory electron transport. Sequence analysis and detailed behavioural studies suggest that other species may have many more MCP receptors and these may be both transmembrane and soluble receptors. Although, as yet, little is known about the soluble receptors, it is probable that they sense the metabolic state of the cell. It has been recently shown that a cytoplasmic receptor in H. salinarium is involved in sensing the cytoplasmic concentration of the fermentation substrate, arginine (Storch etal, 1999).It was initially suggested that E. coli has only four MCPs because of its limited membrane space and, if one amino acid is changing concentration, others probably are also; this obviates the need for more receptors. It now seems more likely that the limited number of receptors reflects the metabolic lifestyle of the particular species. E. coli likes growing on sugars and the 15 or so FTS transport systems could be thought of as 'extra' receptors, particularly as the signal is fed through the

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CheA signalling complex. Similarily, Bacillus subtilis has only three MCPs, but is able to respond to almost all amino acids through these three, possibly via amino-acid binding proteins (Ordal et al., 1993). Other species obviously use more complex sensing systems. Species as diverse as Desulfovibrio vulgaris (a strict anaerobe), H . salinarium (a halophilic archeaon), and R. sphaeroides and C. crescentus, both a-subgroup species but which are found in very different environments,have large numbers of MCPs, i.e. between 12 and 15 (Fu et al., 1994; Brooun et al., 1997; G. Wadhams and J.P. Annitage, unpublished) C. crescentus unfinished sequence, The Institute for Genomic Research (TIGR), www.tigr.org). The chemosensory responses of R. sphaeroides are not identical under all growth conditions. This species will respond to some carbon and nitrogen sources only when they are limiting for growth, suggesting that the cytoplasmic receptors may sense metabolic state and respond only if limiting for that particular metabolite (Poole and Armitage, 1989). A large number of studies have shown that transport and metabolism are required for responses to compounds as diverse as ammonia, sugars and amino acids (Poole et al., 1993; Jacobs et al., 1995; Jeziore et al., 1998). The expression of the chemosensory systems and MCPs is also environmentally regulated. Immunogold electron microscopy and Western blot analysis using an antibody against the conserved region of MCPs showed a 17fold increase in MCP levels under aerobic conditions compared to anaerobic conditions. Under aerobic conditions, large clusters of MCPs were seen at both poles of the cell and there were also clusters within the cytoplasm but under anaerobic conditions, the polar clusters were dramatically reduced (Harrison et al., 1999). It was considered possible that this could be the result of the great increase in invaginated inner cytoplasmic membrane (ICM) under photosynthetic conditions required to house the photosynthetic apparatus, which might make signalling by a small diffusible protein from the poles to the lateral flagellum difficult. However, expression of MCPs and the components of the chemosensory pathway also increases under dark anaerobic conditions when dimethylsulfoxide (DMSO) rather than oxygen was used as electron acceptor. Under these conditions, photosynthetic ICM is still expressed. The role of the 12 or so MCPs has still not been elucidated as, unlike E. coli, deletion of individual mcp genes does not result in the loss of a single response, but a change in behaviour under a range of conditions. For example, mcpA deletion results in reduced chemotaxis under aerobic conditions and mcpS deletion results in increased swarming under all conditions (Ward et al., 1995; D.S. Shah, G.H Wadhams, J.C. Mantota and J.P. Armitage, unpublished observations). In addition, although cheB mutants in R. sphaeroides lose their chemotactic responses and show smooth swimming, methylation of MCPs has not been conclusively measured on the time scales obtained withe E. coli. Chemosensory signalling must be more complex in these species (Fig. 7). Pseudomonas putida grows on the aromatic acid, 4-hydroxybenzoate (4HB)

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Extracellular signals

~

inner membrane peptidoglycan layer outer membrane

Hook\

Filament

Figure 7 Possible chemosensory pathway of Rhodobacter sphaeroides. Under the conditions shown here, there are both cytoplasmic and membrane receptors. The dominant sensory pathway, both chemosensory and photosensory, appears to be through CheA,, and CheY, under laboratory conditions, although some sugars seem to signal through CheA,. CheY,, CheY,, and CheY,,, appear not to bind to the motor under normal conditions, but to serve as signal terminators for CheY," by acting as phosphate sinks. In this diagram it is assumed that the proteins encoded by the different operons are targeted to either the membrane or cytoplasmic MCPs, with CheB acting as a mobile protein between the two clusters. iMCP = cytoplasmic MCP; A = CheA; B = CheB; R = CheR; Y = CheY.

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and shows chemotaxis towards this compound (Hanvood et al., 1990; Grimm and Harwood, 1997). The permease for &hydroxybenzoate, PcaK, has been found to be not only a member of the major-facilitator-super family of transporters, but also required for the chemotactic response to 4HB and several other aromatic acids. PcaK does not resemble any MCPs, but is a classical transport protein with 12 membrane-spanning helices. Mutations in PcaK result in the loss of taxis to the aromatic acids, even at pHs where the aromatic acids are able to diffuse into the cell and allow normal growth, suggesting a real signalling role for the transport proteins in chemotaxis (Ditty et al., 1998). Naphthalene is also an attractant for Pputida and in this case an HCPlike receptor for naphthalene appears to be encoded on a catabolic plasmid limiting sensing of napthalene to its degradation (Grimm and Harwood, 1999). Few species have had the same attention lavished on them as E. coli and therefore the sensory pathway in other species is much less well understood. B. subtilis has, however, been studied in some detail, and its complete genome sequence is known. B. subtilis responds to a very wide range of amino acids and sugars and a large number of diverse repellents have been identified. As with many non-enteric species, B. subtilis has all the central components of the signalling pathway except CheZ (Ordal et al., 1993). It does not, however, have two free copies of CheY, but a fusion between Chew and CheY called CheV; whether this fusion is involved in signal termination as suggested for the CheA-CheY fusions is not known. The number of receptors is small, as in E. coli, but the large number of amino acids sensed suggests that the amino acids probably do not interact with the receptors directly, but may use binding proteins (Garrity and Ordal, 1995). These have not yet been identified. The responses to sugars may involve the PTS transport system and EI, as in E. coli, but in the case of B. subtilis, MCPs are also required for a normal response. It is possible, however, that the requirement for MCPs in PTS signalling is indirect rather than direct, with the MCPs providing the scaffold for the CheW/CheA proteins (Garrity et al., 1998). Another major difference is that an increase in CheY-P concentration appears to be the response to an increase rather than decrease in attractant. An increase in CheA activity results in smooth swimming in B. suhtilis rather than tumbling. Two proteins, CheD and CheC, seem to be involved in both CheB/CheR-dependent adaptation and signal termination (Rosario and Ordal, 1996). The MCPs of B. subtilis seem fairly similar to those of E. coli in that, when deleted, responses to amino acids are lost. However, in addition to the receptors appearing much less specific, the extent of their methylation shows little change after stimulation (Thoelke e?af., 1989). What does change is the rate of turnover of methyl groups on all three of the ‘classical’ MCPs, not just those binding the chemoeffector, with methyl groups apparently moving from one MCP to another. (There are two other MCP-like proteins called Tlps, as they have not been found to be methylated

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but have the highly conserved signalling domain.) CheC inhibits CheRdependent methylation of MCPs, with mutations in cheC, resulting in smooth swimming and increased methylation. Mutations in the other unusual gene, cheD, cause tumbly phenotypes and low levels of MCP methylation. This has led to the hypothesis that CheD binding to MCP is required for CheR to methylate the MCP, and the binding of CheD is negatively controlled by CheC. The addition of an attractant would thus produce high levels of CheY-P, which would allow CheD and CheC to interact. This would reduce their binding to the MCP, and thus reduce CheA activity and the subsequent level of CheY-P. In E, coli, methyl groups released from MCPs following demethylation are released as methanol. In both B. subtilis and the archaeon H. salinarium, methanol is released when both attractants and repellents are added, rather than on removal of an attractant or addition of a repellent (Nordmann et al., 1994; Muller et al., 1997).The methanol is not, however, released immediately, as in E. coli, but after several cycles of stimulation. There are data suggesting that methanol is not released from the MCPs directly, but from a protein to which the methyl groups are thought to be transferred, probably via CheB. CheB does not seem to cause the release of the methyl groups as methanol, as in E. coli, but to transfer the methyls to a carrier. Several mutations have been identified that may ultimately identify the proteins involved (Kirby et al., 1997). The pattern of methylation and methanol release is very similar to that seen in the archaea, suggesting an early origin for this mechanism. Sequence analysis of the chemotaxis operons of S. meliloti, R. sphaeroids and C.crescentus suggests that cheD homologues are also present in these Gram-negative bacteria. Mutations in this gene result in abnormal behaviour, but its role has not been fully characterized. It may be relevant that no short-term changes in methylation have been identified in either S. meliloti or its close relative R. sphaeroides (Annitage and Schmitt, 1997). Myxococcus xanthus is a social, gliding bacterium which moves very slowly in two dimensions over leaf litter, preying on other soil bacteria. Over 100 genes control its gliding behaviour; these have been divided into two subsets, one in which mutations result in alteration of ‘social’motility and the other which is concerned with ‘adventurous’ or single-celled motility (MacNeil et al., 1994a,b; Hartzell and Youderian, 1995). Chemotaxis is involved in aggregation into multicellular spore-forming bodies. There has been some controversy about whether or not slow-gliding species, moving at 1-5 ydmin, can show chemotaxis using temporal gradients. However, there are genes in M.xanthus that are very similar to those coding for the chemosensory proteins of E. coli and mutations within these genes result in altered patterns of gliding, causing either smooth or reversing phenotypes (Zusman et al., 1990).Thefrz genes code for proteins involved in controlling reversal frequency. The MCP-encoding gene isfrzCD but the putative protein sequence does not contain any transmembrane fragments (McBride et al., 1992). FrzA

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is a Chew homologue, while FrzG and FrzF are CheB and CheR homologues, respectively. FrzE encodes a CheA-CheY fusion, whilefrzZ encodes a CheY-CheY fusion. FrzB and FrzZ have no obvious homologues in E. coli (Ward and Zusman, 1997).What are the roles for these in the complex behavioural life of M . xanthus? M.xanthus has a complex life cycle with all stages dependent on motility and influenced by the frz genes. The bacterium forms vegetative ‘swarms’ when nutrients are plentiful, with the moving colonies of bacteria excreting complex mixtures of proteases, nucleases and lipases to digest macronutrients and bacteria in their surroundings. When nutrients become scarce, the cells form tighter aggregates and these become fruiting bodies with spores. ‘A’or adventurous motility allows individual cells to move away from a group, and ‘S’ or social motility requires cell-cell interaction and the bacteria move as a group. There are data implicating chemotaxis in at least two areas of these complex behaviours, but often in combination with a second independent sensory system which measures cell-cell contact or cell density. The MCP homologue, FrzCD, has been found to methylate in response to increased nutrient levels, conditions under which reversal was also reduced. FrzCD is cytoplasmic and this suggests that gliding cells can sense a change in an intracellular nutrient via FrzCD and that this signals, via FrzA (Chew equivalent) and FrzE (the CheA-Y fusion), to control reversal frequency (McBride et al., 1992). Interestingly, only groups of cells respond; individual cells isolated from a group that showed a response no longer respond to changes in nutrient level. This suggests that some form of cell-cell signalling is involved in controlling movement of well-fed cells; the swarm would therefore be sensing not only the nutrient gradient but also cell density (Shi and Zusman, 1993). Isolated single cells can, however, respond to repellents through this pathway and, while single cells do not respond to nutrient gradients (including extracts of E. coli), if a single cell comes into physical contact with a colony of E. coli (its prey), it enters the colony and stops gliding until the colony has been digested. Again, cell contact must be important in stopping the cell movement (McBride and Zusman, 1996). Frz mutants do not show this stop response, again suggesting a connection between gliding behaviour and cell-cell contact. While M. xanthus may not be attracted to E. coli, E. coli is attracted to M.xanthus. In growth limiting conditions, M. xanrhus excretes what is probably an amino acid and this ‘lures’, for example, E. coli, via its Tsr dependent chemosensory system, to its death. The Frz system, therefore, appears to be involved in the scavenging behaviour of M. xanthus swarms, but what about development? Experiments in which the movements of tetrazolium-stained single cells were followed during fruiting body formation showed that large rafts of cells formed and reversed very infrequently, and this behaviour required S-motility,frz genes and a celldensity-dependent signal (Shi et al., 1996). It is again possible that the

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cell-density signal, C-signal, is sensed through the Frz chemosensory pathway as a type of ‘autoattractant’.The reversal frequency, and thus the movement of cells within a developing fruiting body, would therefore be controlled by the aggregation signal being sensed by the chemosensory pathway. There are a great many areas in which the sensory behaviour of M . xunthus is still not well understood. For example, there are still a number of uncharacterized proteins and response regulator fusions that may be unique to these bacteria and the role of methylation in a slow moving bacterium is not understood. In addition a number of che gene homologues have recently been identified in sequence studies that are not part of the frz regular (Table 1, Ward, Law and Zugman, pers.comm.). The relationship between the sensory system which controls movement when the cells are well fed, and the sensory signalling involved in cell aggregation and differentiation and the control of the type of response remains a fascinating question (Sager and Kaiser, 1994). It seems probable that this is not the only case in which chemosensing and ‘quorum’sensing operate together to control bacterial behaviour, and it should be remembered that, for species in natural environments, the final response of a cell is probably the result not only of balancing several chemosensory inputs but also other sensory pathways. 5.1 1. Pattern Formation

An interesting phenomenon which depends on chemotactic behaviour has been seen in several motile species of bacteria, namely, the formation of patterns in semi-solid nutrient media (Budrene and Berg, 1995; Woodward et ul., 1995).These patterns are remarkably intricate and temporally stable. Wild-type E. coli cells, when inoculated into the middle of a semi-solid agar with a single nutrient chemoeffector, move out and form a travelling ring of cells moving down the nutrient gradient created by metabolism. However, if high levels of succinate are used as the nutrient, the cells secrete the attractant aspartate and, rather than a stable ring following the succinate concentration gradient, concentric patterns of spots of bacterial density form, the pattern being dependent on the succinate concentration. The long-range spatial order is the result of two activities, the swarm ring moving outwards and local aggregates responding to the secreted attractant. In the case of E. coli and S. typhimurium, pattern formation can be suppressed by a background of aspartate. The pattern apparently forms because of the changes in dominance of the two stimuli. Whether this type of pattern formation can be produced by other motile species and whether it has any role in natural environments is unknown, but most species will be faced with multiple stimuli under most growth conditions. Nevertheless, motile bacterial cells can produce striking macroscopic patterns and there have been suggestions that the interaction of signals to pro-

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duce multicellular complexes may have some relevance to cell migration during developmental processes. 5.12. Fumarate

Some bacterial species may be able to sense their metabolic state in an MCPindependent manner, and this may indicate a more primitive sensory pathway. Several years ago it was shown that fumarate was part of the chemosensory pathway of H. salinarium. A smooth-swimming mutant could be made to switch by the addition of fumarate (Marwan et al., 1990; Montrone et al., 1993). It was suggested that pools of fumarate might be released in response to changes in phototactic light stimuli and directly control motor switching. As H. salinarium has since been shown also to have a classical chemosensory system, fumarate must act in addition to the Che pathway or interact with that pathway (Rudolph and Oesterhelt, 1995). It was thought to be an archael signalling system until fumarate was shown also to cause increased CW rotation of the motors of E. coli sphaeroplasts (Barak and Eisenbach, 1992b; Montrone et al., 1998). It was also found that the E. coli repellents, indole and benzoate, inhibited fumarase activity (Montrone et al., 1996). Furnarate appears to act directly on the motor by altering the free-energy difference between the CW and CCW direction of rotation (Barak et al., 1996). Whether this has a role under normal biological conditions is unclear, but it may indicate an earlier Che-independent form of motor control, directly connecting metabolism to motor. This would be expected to be masked under many conditions by the Che pathway, but may be relevant under some growth-limiting conditions and in species of bacteria where Che proteins appear to be lacking, but the cells still respond. The genome sequence of the motile archaeon Methanococcus jannaschii has not revealed any che genes, nor has that of Aquipex aeolicus. The mechanisms controlling the behaviour of these species are therefore a mystery, but may involve metabolic sensing. Recently, it has been suggested that thermosensing may control flagella switching in these two thermophilic archaea as temperature is much more important to strictly autotrophic organisms than their chemical environment (Faquy and Jarrell, 1999).

6. RESPONSES TO ELECTRON ACCEPTORS AND LIGHT

6.1. Light

Most motile bacterial species respond to the electron acceptors required for generation of an electrochemical proton gradient and many that are capable

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of photosynthetic growth also respond to light. The mechanisms involved in responding to light by the archaeon H. salinarium is probably the best understood system and combines the mechanisms used for proton translocation of bacteriorhodopsin (BR) with the conserved signalling domain of an MCP. H . salinariurn grows in saturating salt concentrations and, when the oxygen levels are low, it induces BR, a retinal-based light-driven proton pump. In addition to BR, it has three other retinal-based light-absorbing pigments: one, halorhodopsin (HR), uses light to drive a chloride pump; but the other two are sensory rhodopsins. SRII is a constitutive retinal-containing sensory protein which absorbs blue light and undergoes a fast photocycle which generates a signal to control the flagella bundle. Increasing blue light causes the cells to reverse and keeps the cells out of damaging blue light. Under anaerobic conditions when BR is induced, an additional sensory rhodopsin (SRI) is also induced. SRI acts to produce both a positive signal in orange light and a negative repellent signal in blue light. The photopigment undergoes a fast transformation to a blue-absorbing form in orange light. If blue light is present, there is a fast transformation back to the orange-absorbing form but, if blue light is not present, the transformation is slow. Therefore in orange light, which is useful for BR activity, the SRI is in the blue form and sends a positive signal, but, when blue light is present, the orange form predominates and this sends a negative signal (for reviews, see Hoff et al., 1997; Spudich, 1998). Each SR protein has an accompanying sensory protein, HtrI and HtrII. These proteins have cytoplasmic domains homologous to those of the highly conserved domains of MCPs (Yao and Spudich, 1992; Ferrando et al., 1993). If the Htrs are deleted from H. halobium the SR proteins are able to pump protons, just like the Schiff’s base-driven BR, but the presence of Htr prevents any proton pumping (Bogomolni et al., 1994). It is therefore assumed that absorption by retinal of the appropriate wavelength of light leads to a conformational change in the retinal and probably a change in charge. This is transmitted to the Htr proteins through the membrane-spanning a-helices and the conformation of the signalling domain controls the activity of CheA and CheY (Fig. 8). Light sensing in most other species is linked to photosynthetic electron transfer. Non-photosynthetic bacteria will, however, respond to a flash of blue light by tumbling, and prolonged exposure can lead to a complete loss of motility. This is almost certainly the result of the photooxidation of porphyrins, which then act as repellents through the classical MCP system (Yang et al., 1996). Some photosynthetic eubacteria, Ectothiorhodospira halophila, Chromatium salexigens and some strains of R. sphaeroides, have been found to contain a 4-hydroxy cinnamic acid-dependent soluble protein, the photoactive yellow protein (PYP), which undergoes a photocycle similar to BR in blue light, and many of these species do respond to flashes of bright blue light by

A

Repellent

B

signal

system

signal

Figure 8 Photosensory transduction in Halobacterium salinarium. (A) shows the signalling pathway through SRI, the inducible photoreceptor, and SRII, the constitutive receptor. SRI signals both positive and negative wavelength changes. (B) shows the time scale and photochemical transformation that occurs to the retinal molecule of SRI and (C) shows the sensory transducer HtrI, which signals from SRI to the sensory pathway. The cytoplasmic domain of SRI is very closely related to that of Escherichia coli MCPs. Figure adapted from several Spudich reviews, with permission.

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stopping or reversing (Hoff et al., 1992; Sprenger et al., 1993; Hellingwerf et al., 1998). However, the role of this protein in these responses is uncertain as deletion of the protein in R.spaeroides does not cause the loss of the blue light responses (R. Kort and K.J. Hellingwerf, personal communication). Most photosynthetic bacteria respond to light by changing their behaviour when swimming over a light-dark boundary, although little response is seen when they swim over a dark-light boundary. They therefore sense and respond primarily to a reduction, rather than an increase, in light intensity (for reviews see Armitage, 1997, 1998). Whether or not bacteria can respond to a light gradient is arguable and may depend on their environment and the type of gradient possible. Free-swimming cells are unlikely to be able to move far enough in a given time to experience the 1% drop in light intensity required to cause a step-down response and experiments with free-swimming cells in light gradients suggests that this is indeed the case (Sackett et al., 1997). However, when in environments where intensities may fall rapidly, such as microbial mats or dense colonies, the response could be different. Indeed, R. centenum has been shown to respond as a moving colony to a light gradient, the colony moving across an agar plate towards infra-red light and away from white light (Ragatz et al., 1994, 1995). If presented with light from two directions, the colony will move along the averaged path. Individual cells from the colony could not respond to gradients when suspended in liquid medium and oxygen electrode measurements showed that there was a large oxygen gradient within the colony. It is therefore possible that the colony movement is a combination of oxygen and light-sensing as observations of the edge of the moving colony showed the cells not to be moving directly forward but to be moving in constant swirls of cells. In all cases of positive responses to light by photosynthetic eubacteria, photosynthetic electron transport has been shown to be essential. Inhibitors of photosynthetic electron transport inhibit photoresponses, as do mutations within the reaction centres which leave pigments intact (Armitage and Evans, 1981; Grishanin et al., 1997; Romagnoli and Armitage, 1999). Photosynthesis is therefore necessary for the sensory signal, unlike the retinal-dependent signalling of archaea. It seems probable that the signal generated is a change in electron transport rate rather than a change in electrochemical proton gradient (Ap), as low concentrations of uncouplers which cause a step-down in Ap do not alter responses, but electron transport inhibitors which alter the rate of electron flow but not the size of Ap do cause a response (Grishanin et al., 1997). The sensory protein has not been identified, but the signal is transmitted through the chemosensory pathway in both R. sphaeroides and R. centenum (Romagnoli and Armitage, 1999). Mutants in the che genes of R. centenum lost the ability to swarm towards red light (Jiang et al., 1997, 1998). In R. sphaeroides, the situation is more complex as there are two chemosensory operons. Deletion of operon 1 has no effect on photoresponses, but deletion of

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operon 2, with or without the presence of operon 1, leads to the loss of photoresponses. Interestingly, the results with different mutations suggest that the signal goes through CheA2 and CheW2, indicating the involvement of an MCP-like protein. This is supported by the inverted response to step-down in light in mutants which lack CheB and cannot demethylate their MCPs. Therefore, although methylation has not been measured in R. sphaeroides, the loss of a protein involved in adaptation in E. coli can alter responses to light, suggesting a role for a classical signalling pathway from a redox sensor to the motor.

6.2. Electron Acceptors

The light response could be sensed by a receptor related to the ‘oxygen’ sensor of E. coli. An FAD binding protein with a cytoplasmic domain homologous to the highly conserved domain of an MCP has been identified which signals changes in ‘oxygen’ levels to the flagellum through a Che pathway (Bibikov et al., 1997; Rebbapragada et al., 1997). This protein, Aer, is thought to sense the change in the rate of electron flow through the quinone region of the respiratory electron transport chain, rather than oxygen itself and this signal is transmitted to CheA and CheY . Mutants in Aer do not accumulate around air bubbles, while overexpression of Aer results in an increased sensitivity to oxygen. The mechanism involved in oxygen sensing by the FAD has not been identified and it seems that this is not the only receptor for respiratory activity. Mutants in Aer still show some responses to changes in oxygen level and there is some evidence that the MCP, Tsr, may be able to sense changes in A p directly, but again the mechanism is not understood. It has been suggested that a balancing between signals from electron transport and responses to changes in A p could account for both positive responses to optimum oxygen concentrations and the repellent responses shown to concentrations too high for normal metabolic activity (Rebbapragada et al., 1997; Zhulin ef al., 1997). This sensory mechanism may reflect a wide-spread mechanism for sensing energy state in a large number of organsims (Taylor and Zhulin, 1998). Several independent mechanisms seem to have evolved for sensing oxygen levels. One of the 12 MCPs identified in H. salinarium appears to be an oxygen sensor, but in this case it uses a cytochrome oxidase attached to the highly conserved domain of an MCP (Brooun er al., 1997). This suggests that H. salinarium can sense molecular oxygen directly. D. vulgaris, a strict anaerobe, on the other hand has a sensory protein, DcrA, with a c-type haem attached to a domain with homology to the highly conserved cytoplasmic signalling domain of an MCP (Fu et al., 1994). The ecology of a strict anaerobe is obviously different from the facultative bacteria in which aerotaxis has been

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studied. DcrA could sense either oxygen or redox potential, as the haem irons of D. vulgaris have been shown to be directly oxidized by oxygen. Under anaerobic conditions, DcrA would be reduced and oxygen would lead to either the direct oxidation of bound haem or allow haem to bind to the signalling domain; this would alter the conformation and signalling through the highly conserved domain. Unlike Aer, which does not apparently have glutamate residues that could be methylated, DcrA has been shown to methylate in response to changing oxygen concentrations. The different methods identified to sense changes in oxygen levels may add weight to the idea that the highly conserved signalling domain was the evolutionary early component of chemosensing and different sensory domains have been grafted on by different species to serve their specific niche. As electron transfer is involved in both light and oxygen sensing, do they compete? The answer appears to be ‘yes’. Most bacteria that grow using respiratory electron transfer can also use other electron acceptors when oxygen is absent, inducing expression of specific acceptors if an electron acceptor is in the environment. Thus E. coli will grow on nitrate in the absence of oxygen and under these conditions will show tactic responses to nitrate (Laszlo et al., 1984; Shioi and Taylor, 1984). R. sphaeroides will grow on DMSO in the absence of oxygen and again shows taxis towards it (Gauden and Armitage, 1995). In both cases, if the responding cells are now exposed to oxygen, the response to nitrate or DMSO is lost and the cells now respond to oxygen; this correlates with electron flow having been diverted from the alternative acceptor to oxygen. Similarly, with R. sphaeroides, light will inhibit responses to either DMSO or oxygen, although the addition of oxygen to photosynthetically growing cells will reduce the size of the photoresponse (Grishanin et al., 1997).All the data suggest that bacteria do not respond to a specific stimulus, i.e. to light, oxygen or nitrate, but to the change in electron flow through a common receptor, which then signals through the chemosensory pathway. As suggested with Aer and Tsr for oxygen sensing, however, there may be more than one receptor in R. sphaeroides as, although oxygen, DMSO and light have been shown to compete, mutants which have lost photoresponses will still show responses to oxygen and DMSO. No research has yet been carried out into competition between electron transport-dependent signals and the chemosensory signals. Recent sequence comparisons of a large number of proteins known to be involved in sensing changes in light, oxygen or redox potential, including Aer, has identified a domain common to their proteins. This PAS domain has been identified in proteins from Bacteria, Archaea, and Eurcarya and may suggest an energy sensing system in all living structure (Taylor and Zhulin, 1999).

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7. WHAT IS THE ROLE OF TACTIC RESPONSES IN NATURAL ENVIRONMENTS?

Only E. coli and Salmonella have had their chemosensory pathways analysed in any great detail, but there have been numerous individual studies of the possible role of motility and chemotaxis to the natural history of a wide range of species, from environmentally important species to pathogens. The extent of investigation varies enormously, but there is an increasing body of evidence that chemotaxis plays an essential part in the survival of a very wide range of species: it allows surfaces to be reached for colonization and thus has an essential role in pathogenicity and symbiotic interactions and may be important for the initial colonization of surfaces for biofilm formation. Many bacterial species isolated from the environment have been shown to be motile and chemotactic. Chemotactic responses were usually found to nutrients important for their survival and the responses to light and electron receptors usually reflected their natural niche. However, very little work has been undertaken to examine the role of taxis in situ. One of the behavioural responses which almost certainly plays an important role in the natural ecology of some bacteria is magnetotaxis. 7.1. Magnetotaxis

A large number of bacterial species appear to be magnetotactic, although few have been isolated in pure culture. There are coccoid, spiral and rodshaped species, but all possess intracellular membrane-bound magnetosomes, flagellate motility and negative aerotaxis (Frankel, 1984; Frankel and Blakemore, 1988; Spring and Schleifer, 1995). Magnetotactic species are usually found in estuarine or salt marsh mud, where they grow microaerophilically. The turbulent environment can result in the bacteria being displaced by tidal movement into the aerobic upper layers of the water. The chains of magnetosomes contain single-domain magnetite, which orient the cells along the local magnetic field lines. This orientation combined with a strong negative aerotactic response results in two-dimensional, rather than three-dimensional, swimming patterns, moving the cells back into the microaerophilic mud (Frankel et al., 1997). 7.2. Aquatic Environments

The behaviour of photosynthetic species in microbial mats and in stratified lakes has been investigated and, while gas vacuoles may be required to move

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bacteria over large distances, in mats, swimming motility may be important in local movements during the natural day-night cycle. There is some evidence that gliding motility is important in maintaining the vertical distribution of both the sulfur bacterium Thioploca, and cyanobacteria within sediments (Pentecost, 1984; Huettel et al., 1996). Recent studies on the behaviour of a mixed population of sulfate-reducingbacteria within a cyanobacterialmat showed extensive diurnal migration by the bacteria linked to diurnal oxygen stress, and a complex interplay of oxygen, carbon and sulfate chemotaxis helped maintain the different species, whether facultative, microaerophilic or anaerobic in their optimum environment (Teske ef d.,1998). In experiments where microcores of natural microbial mats were replaced with small glass beads, highly motile natural isolates of marine bacteria were also found to concentrate and position themselves within a very distinct band within 3 days of regrowth. The sensory signal for maintaining the bacteria within the band was not identified, as classical chemoattractants had no effect on positioning of the band but, as the species were not identified, the dominant effectors were unknown and oxygen could have played a major role (Barbara and Mitchell, 1996). Measurement of bacteriochlorophyll fluorescence of photosynthetic bacteria in a stratified lake in situ showed that they moved several centimetres during the day. The movement might be the result of a combination of photoresponses and responses to the changing sulfide and oxygen concentrations, as during the day the bacteria need to be in high light and sulfide, but low oxygen and balancing the signals may be the cause of the cyclic movement (Joss et aZ., 1994). Clouds of highly motile bacteria are found close to surfaces in marine environments. The bacteria, which are mainly unclassified, show strong aerotactic and chemotactic behaviour. These may serve to produce these high cell densities close to surfaces where nutrient levels are higher than in the open waters (Mitchell et al., 1995). In addition, marine algae secrete high levels of demethylsulfoniopropionate(DMSP) and there is evidence that marine species may be chemotactic to DMSP, using it as a metabolite, and responsible for its turnover in natural environments.The chemosensory response depends on the induction of the enzyme DMSP lyase; the optimum concentration found to attract Alcaligenes M3A was about lo4 M, comparable to the concentration measured close to phytoplankton. Dimethylsulfide (DMS) gas is the major source of biogenic sulfur emissions from the oceans and is involved in climate regulation. This is therefore a situation where chemotaxis could be directly involved in the rate of DMS production and sulfur-cycling between seawater and atmosphere (Zimmer-Faust et al., 1996). Several marine isolates move differently when free-living rather than on surfaces. Free-living Vibrio alginolyticus swims using a single Na+-driven flagellum, but on surfaces the increased viscosity is sensed through the flagellar motor and induces the synthesis of large numbers of proton-driven

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lateral flagella, which allow the cells to move over surfaces (Atsumi et al., 1992). This type of transformation, from single or few flagella on freeswimming cells to large numbers of lateral filaments when on surfaces is now being found in many species including Gram-positive bacilli, some gram-negative pathogens and marine species, suggesting that this is a common solution to the problem of small bacteria moving over surfaces. They tend to move as large rafts, and this multicellular movement probably helps to overcome the excessive viscous drag and tension of the surface (Moens and Vanderleyden, 1996). An interesting behavioural response is shown by stable consortia of bacteria. Several phototrophic consortia have been identified in eutrophic fresh water, ‘Chlorochromatiumaggregatum ’ and ‘Pelochromatiumroseum ’ are two whose behaviour has been investigated (Frost1 and Overmann, 1997; Overmann et al., 1997). They are both consortia formed between a large central, motile but pigmentless bacterium and pigmented non-motile cells which surround it (some have been described with several layers of cells around the motile central cell). These consortia can make up as much as two-thirds of the biomass of the chemocline of a lake and may therefore be important in the physiology of these ecosystems. Analysis of the vertical distribution of specific consortia shows that they are found at specific regions with maximum light intensity but very low oxygen levels. The behavioural response must balance the signals from oxygen, light, sulfide and iron to keep the consortia in these regions. The diurnal distribution was also found to change, with the consortia moving upwards at night. When the behaviour of these bacteria was analysed in the laboratory, it was found that, although the motile member of the group was not photosynthetic, the consortia responded to changes in light intensity and accumulated in wavelengths that corresponded to bacteriochlorophylls c and d, the pigments found in the non-motile members of the group. The nonmotile species therefore must signal to the motile bacterium when the light intensity changes. The mechanism is unknown, but many motile species respond to changes in pH and the change in extracellular pH that may accompany changes in photosynthetic activity could serve as a signal. In some cases, consortia only remain together when incubated photosynthetically and disperse in the dark. Given the predominance of these consortia in some freshwater lakes, it seems likely that this association, and the phototactic and chemotactic behaviour that goes with their formation, is important for the colonization of these lakes.

7.3.Biofilms In natural environments, many bacteria are not found free-living, as in the laboratory, but as biofilms, which may involve single or multiple species. These

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biofilms can be very stable and the bacteria within them are often metabolically very different from the same species growing individually in suspension (planktonic). This natural phenomenon has enormous economic and health implications, as biofilms cost oil and shipping industries large amounts of money, and the formation of biofilms on medical implants is a major problem in medicine. Biofilms on plant roots, on the other hand, are thought to protect plants from infection by pathogens and may be involved in non-symbiotic nitrogen fixation (Costerton et al., 1995). It is likely that the interplay of at least two environmental responses is essential for biofilm formation, motility and quorum sensing, before the process of extracellular matrix synthesis (Davies et al., 1998; Kolter and Losick, 1998). A biofilm is a mechanism for keeping a bacterial species in a particular location, limiting overcrowding, nutrient limitation and toxin production by packing them at low density in a polysaccharide matrix. Secreted N-acyl homoserine lactones (N-HSLs), the bacterial cells’ mechanism for sensing population density (Fuqua et al., 1994), are necessary for biofilm formation, but several studies have shown that motility is also essential for the very early stages of biofilm formation and perhaps for movement within the biofilm, which can project many tens of micrometres from the surface (Pratt and Kolter, 1998).Although the requirement for chemotaxis has not been shown, it seems probable that chemotaxis is used to direct the bacteria to surfaces where the local charge and nutrient concentration tends to be higher than in surrounding environments and, if it is a plant or animal tissue surface, there are probably local gradients of excreted compounds. Biofilms also slough off individual cells, and it is probable that this leads to population and biofilm spreading and this requires motility. R. sphaeroides produces an N-acyl HSL, but a mutant unable to produce it forms large amounts of extracellular matrix and large flocculant colonies (Puskas et al., 1997). In this case the interplay of motility, nutrient levels and quorum sensing may determine whether the cells are free-swimming, planktonic or form a protective biofilm-like matrix. The addition of the N-acyl HSL to a flocculent colony results in its dispersal and an increase in swimming speed. The link between quorum sensing and motility is more apparent in the relationship between the bioluminescent bacterium Vibrio jischeri and the squid (Ruby, 1996). Free-living K jischeri are highly motile and non-motile mutants are unable to develop symbiotic relationships with the squid (Graf et al., 1994). When a squid is colonized by the wild-type bacterium, flagella are lost within 24 h but, if the bacterium is returned to open sea waters, the flagella are resynthesized (Ruby and Asato, 1993). Colonization of the squid therefore results in suppression of flagellar synthesis, but whether this is cell densitydependent, as with bioluminescence,is unknown. Flexible-shaped bacteria, such as spiroplasma and spirochetes, apparently alter their cell body helicity when swimming into or out of an environment with increased viscosity. This results in faster swimming into viscous

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environments, which may be mucous membrane or the cellular matrix, and slower swimming when moving out. This physical phenomenon results in enhanced invasiveness and, although not a tactic response, in combination with taxis it may help pathogenic species, invade their host (Kaiser and Doetsch, 1975; Petrino and Doetsch, 1978). 7.4. Role in PathogenicitySymbiosis

The role of motility and taxis in the infection of higher organisms has been of interest for many years and two recent reviews cover some aspects of the area (Moens and Vanderleyden, 1996; Ottemann and Miller, 1997). 7.4.1.Nitrogen-fixing Bacteria There have been a number of studies on the role of chemotaxis in the colonization of legume roots because of the economic and ecological importance of nitrogen fixation by both free-living and symbiotic species. Again, there are no unequivocal data that a particular rhizobial species is attracted to its specific plant root hair as a result of any species-specific exudates, but rhizobia are highly motile and chemotactic, and are attracted by root exudates (Gulash et al., 1984; Munzo Aquilar et al., 1988; Malek, 1989,1992).This would almost certainly move the cells up the nutrient gradients around a plant root towards the root hairs, but the response may not be specific for the host. It seems probable that, as with most colonizations, the attachment to roots is a complex process with motility and chemotaxis taking bacteria to the surface. This is followed by adhesion and colonization, processes combining quorum sensing and complex intracellular signalling pathways. Plants secrete nod-inducing flavenoids into the rhizosphere and these can be degraded by rhizobial species; it has been suggested that the degradative products of flavenoids in the rhizosphere could act as chemoattractants (Rao and Cooper, 1995).While many rhizobial species have been shown to exhibit chemotaxis towards root exudates in general, the most convincing evidence that chemotaxis is involved in colonization comes from studies on the free-living nitrogen-fixing bacterium, Azospirillurn brasilense (Vande Broek et al., 1998).A number of mutants have been identified in this species that are non-motile or non-chemotactic, and are unable to colonize wheat roots in vivo. Flagella have been implicated in the initial process of adhesion, while polysaccharide production appears important in the later stages. Bacillus rnegateriurn is a root-colonizing bacterium which has been shown to protect roots against fungal attack. This species shows a highly sensitive chemotactic response to soybean root exudates, particularly amino acids, over

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a wide range of temperatures and pHs. This has led to the suggestion that chemotaxis not only leads to the successfulcolonizationby the bacterium of plant roots but also serves to protect the roots from potential pathogens (Zheng and Sinclair, 1996).

7.5. PATHOGENS 7.5.1 Plant Pathogens

The role of motility and chemotaxis in plant wound infection is unclear. There are reports that wound secretions act as attractants for the pathogen Agrobacteriurn turnefaciens, working at lower concentrations than required to induce the expression of pathogenic genes. This suggests that the bacterium can sense a wounded plant, swim towards it and then induce pathogenicity (Shaw, 1991; Kemner et al., 1997). Wounded plants secrete specific inducers of virulence genes, namely, acetosyringones and sugars. A periplasmic protein, ChvE, is involved both in chemotaxis towards monosaccharidesand virulence gene induction. Erwinia, Pseudornonas and Xanthornonas species are all motile, but whether or not that motility has a direct role in their pathogenicity has not been investigated. Mixed inocula of motile and non-motile transposon mutants of r! putida did show that only the motile wild-type could effectively colonize the rhizosphere around spinach roots, although, when directly inoculated, there was no significant difference in the ability to colonize the roots. This suggests that motility may be an essential trait in the colonization of roots (Sakai et al., 1996). 7.5.2. Animal Pathogens

A great deal more research has been carried out on the role of motility and taxis in pathogenic interaction by animal pathogens. As many virulence factors, for example quorum sensing, specific pili development and toxin secretion pathways are similar in plants and animals, it seems likely that motility will have a role in moving plant as well as animal pathogens to their site of adhesion andor invasion. In animal pathogens, flagellar synthesis and virulence factors are often co-regulated. Non-motile or non-chemotactic mutants usually remain pathogenic if they are inoculated directly on to an invasion site, but if they are incubated with the host rather than inoculated on to the site of potential infection, infection is lost. For example, a non-chemotactic Vibrio anguillarum will not infect trout when added to its water, although pathogenicity has not been lost. A mutation in the methyl transferase gene, cheR,

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resulted in a smooth-swimming phenotype and, although the mutants remained fully pathogenic when added to the fish directly, could not cause infections when added to fish tanks (O’Toole et al., 1996).This organism and a related fish pathogen, V alginolyticus, have been shown to exhibit strong chemotactic responses to mucus from sea bream. Mucus was isolated from a different part of the fish and tested for its chemotactic strength. Pathogens were found to respond and adhere to mucus from the skin and gills, the usual sites of infection, but showed little response to mucus from the intestine (Bordas et al., 1998). Recently, there have been many studies on the role of motility in human infection. Kbrio cholerae is highly motile, and there is research suggesting that motility and expression of virulence factors are intimately linked, the correct environmental signals for pathogenicity appear to switch off motility and switch on virulence genes. However, the initial role of motility in invasion has not been fully characterized (Richardson, 1991; Postnova et al., 1996; Bordas et al., 1998). More detailed studies have been carried out on wound infection, urinary tract infections and intestinal mucus invasion. Recent research has concentrated on infections by Campylobacterjejuni and H. pylori, given their involvement in serious outbreaks of gasteroenteritis, and in stomach ulcers and gastric cancer, respectively (Mobley, 1997). Early studies of C.jejuni showed, surprisingly, that in vivo this organism did not appear attached to the gut lining but freely swimming in mucus-filled pits of the large intestine (Szymanski et al., 1995). C.jejuni is highly motile in viscous media that inhibit most flagellate species, suggesting that motility has evolved to operate efficiently in its niche in the intestine. There is some evidence that chemotaxis is essential for colonization as non-chemotactic but motile mutants showed a limited ability to colonize intestines in animal model systems, while non-motile mutants were unable to colonize birds or rabbits (Nachamkin et al., 1993; Yao et al., 1997). CheY mutants also failed to colonize mice. Similarily, flagellar mutants of H . pylori were less able to colonize gnotobiotic piglets (Eaton et al., 1992). H. pylori has been found to respond chemotactically to urea and bicarbonate, and negatively to oxygen (Mizote et al., 1997). The gastric epithelial cells secrete urea and bicarbonate, and hydrolysis of urea by urease is essential for colonization of the gastric mucosa. It seems likely that the positive responses to these compounds indicate that chemotaxis plays an essential role in colonization of the stomach by H. pylori and helps to maintain it in that niche. Proteus mirabilis is a major cause of urinary tract infections. It is one of an increasing number of bacterial species that have been found to swim using a small number of flagella in liquid media but, when growing on surfaces, the increased viscosity apparently induces increased flagella synthesis, and the cells become hyperflagellate and often elongated, which allows them to move as large rafts of cells over surfaces. In the case of I! mirabilis, it has been suggested that the hyperflagellate, swarming cells may be better able to colonize

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the urethra, bladder and kidneys (Allison et al., 1992). Indeed, swarmer cells have been shown to have an increased level of expression of a large number of virulence factors. Mutations in genes resulting in the loss of motility and swarming also cause a reduction in the expression of virulence factors. In animal models, only swarmer cells were isolated from infected kidneys even though the initial inoculum had contained only free-swimming non-swarmer cells, suggesting that swarmer differentiation does occur in vivo. Experiments designed to investigate the role of flagella in infection have, however, been equivocal, with one study showing a reduction in infection by non-motile cells and the other showing no effect (Legnani-Fajardoet al., 1996; Mobley et al., 1996). These results suggest that the link between motility and virulence may be very complex, and more sophisticated studies may be needed before we can be sure whether or not F! mirabilis swarms up the human urethra to reach sites of infection. Clostridium septicum is another pathogenic species in which small free-swimming cells differentiate into swarmers on surfaces. Adhesion to, and invasion of, cultured human epithelial cells was greatest if the short motile form was used rather than swarmers, suggesting that differentiation may play different roles in different species (Wilson and Macfarlane, 1996). A connection between swarming motility and quorum sensing has been identified in the occasional human pathogen, Serratia liquifaciens, where the development of swarmers has been shown to require genes controlling not only flagella synthesis, but also the synthesis of N-acyl HSL, again indicating that motility is just one of several environmental sensing systems determining the fate of the cell (Givskov et al., 1998). It may be interesting that the so-called ‘Qpe III’ secretion system used by a range of important pathogens, such as Yersinia, Shigella, Salmonella and Bordetella, to secrete toxins is very similar to the flagellar motor in structure (Stephens and Shapiro, 1996). This system is required for the direct release of toxic proteins without a classical signal sequence. For example, the Yops from Yersinia ‘inject’toxins directly into the eukaryotic cytoplasm after cell-cell contact, and there are suggestions of a common evolutionary origin for the export apparatus for flagellar proteins and Type III toxins (Cornelis, 1997;Cornelis and Wolf, 1997).The majority of Qpe III-secreting pathogens are also motile. In several of these, including Bordetella, a link between motility and pathogenicity has been suggested. The cells are flagellate and motile when not in a suitable colonization site and one of the effects of the expression of virulence factors in response to extracellular signals is to switch off flagella synthesis. Mutants unable to switch off flagella synthesis showed a reduced ability to infect, even when the mutation was combined with one allowing expression of virulence factors. The antigenic ability of flagellin may be one reason, but it seems likely that, in the case of this species, control of motility and colonization is essentially negatively connected. In these species, it has been suggested that the motile phase may be important for transmission rather than colonization.

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Chemotaxis may also play a part in the survival of pathogens. E. coli is repelled by concentrations of hydrogen peroxide, hypochlorite and Nchlorotaurine lower than the toxic concentrations.As these compounds are part of the ‘respiratory burst’ produced by phagocytes in response to bacterial invasion, the ability of bacteria to use chemotaxis to evade the leucocytes could help in survival (Benov and Fridovich, 1996).

8. CONCLUSIONS

Motility is one of the common traits shown by bacteria. It is rapidly becoming obvious that this ancient activity has been adapted by different species for survival in their respective niches. While E. coli remains the useful paradigm for looking at bacterial motility, this system is very simple compared to that used by other species. Not only do other species respond to a wider range of compounds, they may also sense their own metabolic state and only respond to compounds currently required for growth. Their pattern of responses may also change with their environment, responding to compounds aerobically which are ignored anaerobically. The chemosensory system probably does not operate in isolation, but is integrated with sensory pathways controlling a wide range of physiological functions, from pathogenicity and biofilm formation to changes in osmoregulation and oxygen level. The short-term behavioural response and the longer-term transcriptional control are all part of a complex network of sensory signals controlling bacterial behaviour. Bacteria combine the signals coming through their chemosensory pathway with signals for surface contact and cell density, for example, and the final response may be modified accordingly. The role of chemosensing in pathogenicity, symbiosis and environmental localization is complex and we have only just started to understand chemotaxis in its wider context.

I would like to start by apologizing to the many people whose work has not been cited. This review only starts to scratch the surface of the rapidly increasing field, and I have had to make a very difficult and personal choice of the data to cite to illustrate the subject. I would also like to thank Dickon Alley and Igor Zhulin for genomic data, and John Jefferys for help with the figures. Chemotaxis data on R. sphaemides came from studies supported in my laboratory by the BBSRC and Wellcome Trust.

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Ward, M.J., Harrison, D.M., Ebner, M.J. and Armitage, J.P. (1995) Identification of a methyl-accepting chemotaxis protein in Rhodobacter sphaeroides. Mol. Microbiol. 18, 115-121. Weerasuriya, S., Schneider, B.M. and Manson, M.D. (1998) Chimeric chemoreceptors in Escherichia coli: signaling properties of Tar-Tap and Tap-Tar hybrids. J. Bacteriol. 180,914-920. Welch, M., Oosawa, K., Aizawa, S . 4 . and Eisenbach, M. (1993) Phosphorylation-dependent binding of a signal molecule to the flagellar switch of bacteria. Proc. Natl Acad. Sci. USA 90,8787-879 1. Welch, M., Oosawa, K., Aizawa, S.4. and Eisenbach, M. (1994) Effects of phosphorylation, Mg2+,and conformation of the chemotaxis protein CheY on its binding to the flagellar switch protein FIiM. Biochemistry 33, 10470-10476. Welch, M., Chinardet, N., Mourey, L., Birck, C. and Samama, J.P. (1998) Structure of the CheY-binding domain of histidine kinase CheA in complex with CheY. Nat. Struct. Biol. 5,25-29. Wilson, L.M. and Macfarlane, G.T. (1996) Cytotoxicity, adhesion and invasion of Clostridium sepricum in cultured human epithelial cells (CACO-2, HEp-2): pathological significance of swarm cell differentiation. Anaerobe 2,71-79. Woodward, D.E., Tyson, R., Myerscough, M.R., Murray, J.D., Budrene, E.O. and Berg, H.C. (1995) Spatio-temporal patterns generated by Salmonella typhirnurium. Biophysi. J. 68,2181-2189. Yamamoto, K. and Imae, Y. (1993) Cloning and characterization of the Salmonella typhimurium-specific chemoreceptor Tcp for taxis to citrate and from phenol. Proc. Natl Acad. Sci. USA 9 0 , 2 17-22 I . Yamamoto, K., Macnab, R.M. and Imae, Y. (1990) Repellent response functions of the Trg and Tap chemoreceptors of Eschrrichia coli. J. Bacteriol. 172,383-388. Yang, X.-H., Sasarman, A., Inokuchi, H. and Adler, J. (1996) Non-iron porphyrins cause tumbling to blue light by an Escherichia coli mutant defective in hemC. Proc. Narl Acad. Sci. USA 93,2459-2463. Yao, R., Burr, D.H. and Gueny, P. (1997) CheY-mediated modulation of Campylobacter jejuni virulence. Mol. Microbiol. 23, 1021-1031. Yao, V.J. and Spudich, J.L. (1992) Primary structure of an archaebacterial transducer, a methyl-accepting protein associated with sensory rhodopsin I. P roc. Natl Acud. Sci. USA 89, 11915-1 1919. Yeh, J.I., Biemann, H.-P., Prive, G.G., Pandit, J., Koshland, D.E. Jr and Kim, S.-H. (1996) High resolution structures of the ligand binding domain of the wild-type aspartate receptor. J. Mol. Bid. 262, 186-201. Youderian, P. (1998) Bacterial motility: secretory secrets of gliding bacteria. Curr. Bid. 8, 408-41 1. Zheng, X.Y. and Sinclair, J.B. (1996) Chemotactic response of Bacillus megaterium B 1532-2 to soybean root and seed exudates. Physiol. Mol. Plant Parhol. 48,21-35. Zhou, J., Lloyd, S.A. and Blair, D.F. (1998) Electrostatic interactions between rotor and stator in the bacterial flagellar motor. Proc. Natl Acad. Sci. USA. 95,6436-6441. Zhulin, I.B., Johnson, M.S. and Taylor, B.L. (1997) How do bacteria avoid high oxygen concentrations? Biosci. Rep. 17, 335-342. Zimmer-Faust, R.K., De-Souza, M.P. and Yoch, D.C. (1996) Bacterial chemotaxis and its potential role in marine dimethylsulfide production and biogeochemical sulfur cycling. Limnol. Oceanogr 41, 1330-1 334. Zusman, D.R., McBride, M.J., McCleary, W.R. and O’Connor, K.A. (1990) Control of directed motility in Myxococcus xanfhus. In: Biology offhe Chemotactic Response (J.P. Armitage and J.M. Lackie, eds), pp. 199-219. Cambridge University Press, Cambridge.

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The Bacterial Flagella Motor Richard M. Berry’ and Judith P. Armitage2 ‘The Randall Institute, King’s College London, 2 6 2 9 Drury Lane, London WC2B 5RL, UK 2Microhiology Unit, Department of’Biochemistry, University of Oxford, South Parks Road, Oxford OX1 3QU, UK

ABSTRACT

The bacterial flagellum is probably the most complex organelle found in bacteria. Although the ribosome may be made of slightly more subunits, the bacterial flagellum is a more organized and complex structure. The limited number of flagella must be targeted to the correct place on the cell membrane and a structure with cytoplasmic, cytoplasmic membrane, outer membrane and extracellular components must be assembled. The process of controlled transcription and assembly is still not fully understood. Once assembled, the motor complex in the cytoplasmic membrane rotates, driven by the transmembrane ion gradient, at speeds that can reach many 100 Hz, driving the bacterial cell at several body lengths a second. This coupling of an electrochemical gradient to mechanical rotational work is another fascinating feature of the bacterial motor. A significant percentage of a bacterium’s energy may be used in synthesizing the complex structure of the flagellum and driving its rotation. Although patterns of swimming may be random in uniform environments, in the natural environment, where cells are confronted with gradients of metabolites and toxins, motility is used to move bacteria towards their optimum environment for growth and survival. A sensory system therefore controls the switching frequency of the rotating flagellum. This review deals primarily with the structure and operation of the bacterial flagellum. There has been a great deal of research in this area over the past 20 years and only some of this has been included. We apologize in advance if certain areas are covered rather thinly, but hope that interested readers will look at the excellent detailed reviews on those areas cited at those points. ADVANCES IN MICROBIAL PHYSIOLOGY VOL 41 ISBN 0- 12-02774 1-7

Copyright 0 1999 Academic Press All rights of reproduction in any form reserved

RICHARD M . BERRY AND JUDITH P. ARMITAGE

292 Abbreviations

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1 . Introduction ....................................................... 2. The flagellar structure ............................................... 2.1. Thefilament ................................................... 2.2. Thehook ...................................................... 2.3. The basal body ................................................. 2.4. The Mot proteins ............................................... 2.5. Theswitchcomplex ............................................. 2.6. Theexport apparatus ........................................... 2.7. Genetics of flagellar synthesis .................................... 3. Flagellar motor function ............................................. 3.1. Methods of measuring flagellar rotation ............................ 3.2. The driving force for rotation ..................................... 3.3. Reversibility ................................................... 3.4. Torque versus rotation rate ....................................... 3.5. Smoothness of rotation .........................................

.

4 Models of the flagellar motor ......................................... 4.1. Classification of existing models .................................. 5. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References ........................................................

292 292 296 298 299 301 302 306 308 309 310 310 312 316 317 321 322 322 328 329 329

ABBREVIATIONS

CCW

cw

HAP

Counterclockwise Clockwise Hook-associated protein

.

1 INTRODUCTION

Many species of bacteria are able to sense their environment and to swim towards places where conditions are more favourable. Various styles of swimming are employed by different species (Fig. 1) but almost all are based on the rotation of rigid. extracellular. helical flagellar filaments. driven by a rotary motor embedded in the cell envelope (Fig. 2; see later). All free-swimming flagellate bacteria swim in three dimensions in characteristic patterns. punctuated by reversals. stops or changes of direction (Berg. 1983). Mechanisms exist both to generate the swimming pattern and to modulate it in response to sensory stimuli (‘taxis’). For example. swimming Escherichiu coli are propelled by a bundle of several flagella rotating counterclockwise (CCW) together (Macnab. 1977; Block et ul., 1991b) . Occasionally. the bundle flies apart and the cell stops swimming to ‘tumble’ on the spot.

+

D

C

9

-

.

I

c

Figure 1 Motility pattern of a range of different flagellate species. (A) Salmonella fyphimurium showing running-tumbling-running pattern with a bundle of flagella rotating together to push the cell forward, interspersedwith brief periods of tumbling when the flagella change the direction of rotation. (B)Pseudomona uerugirwsubeing either pushed or pulled by rotation of the flagellum in either a counterclockwise or clockwisedirection. (C) Rhodobacrer sphuemides showing swimming-stopswimming motility. The flagellum rotates CW,periodically stoppingand relaxing into a short wavelength helix. Slow rotation reorients the cell for the next period of swimming. (D) Spirochaeru aurentia is able to swim through viscous environment as a result of the rotation of the internal cytoplasmiccylinder,caused by the rotation of periplasmic flagellar filaments. Smooth swimming results from the filaments rotating in the same direction (motors opposed);flexing is the result of the rotation in opposite direction. Reproduced from Armitage (1992) with permission.

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When the bundle re-forms, the cell swims off in a new, random direction. The flagella on a tumbling cell rotate clockwise (CW) and the handedness and pitch of their filaments are different from those of a swimming cell. It is probable that the tumble is initiated by the switching of motors from CCW to CW rotation, a mechanism controlled by the cytoplasmic chemosensing system Other species show variations on this theme. In Halobacterium halobium, a bipolar archaebacterium, the cell reverses briefly by reversing the direction of rotation of the flagellar bundle; glycoproteins in the filament make it possible for the bundle to stay together during motor reversals (Kupper et al., 1994). Pseudomonas species with a single polar flagellum can be either pulled or pushed by the flagellum rotating either CW or CCW, and spend about 50% of the time in each mode (Kelly-Wintenberg et al., 1990). Some species, e.g. Rhodobacter sphaeroides and Rhizobium meliloti, rotate their flagella in only one direction, modulating their swimming direction by brief stops or speed changes (Armitage and Macnab, 1987; Gotz and Schmitt, 1987). In all species, the swimming pattern is modulated by changes in the environment in such a way as to bias the swimming of bacteria in a favourable direction for growth. In general, when a cell is swimming up a gradient of attractant concentration (or down a gradient of repellant), changes of direction are less likely andor, when a cell is swimming down a gradient of attractant, changes of direction are more likely. Taxis has been the subject of several recent reviews (Armitage, this volume; Macnab, 1996; Stock and Surette, 1996; Grebe and Stock, 1998) and the molecular mechanisms involved in chemotaxis or other behavioural responses will not be dealt with here. Some bacteria can move without flagella, notably gliding species, such as myxococcus and Cytophaga (Zusman et al., 1990; Beatson and Marshall, 1994) and certain species of marine synechococcus have no apparent means of propulsion (Waterbury et al., 1985; Pitta et al., 1997), but the mechanisms for these types of motility are poorly understood and will not be discussed here. The first indication that the prokaryotic flagellum might not operate by bending as eukaryotic flagella do, but might in fact rotate as a rigid helix, came over 25 years ago (DePamphilis and Adler, 197la; Berg and Anderson, 1973; Silverman and Simon, 1974), although it had been suggested and dismissed as implausible 30 years earlier (Weibull, 1960). It had been known for several years that the bacterial filament was made of a polymer of a single protein, flagellin. The filaments had been shown to dissociate at low pH into monomers and spontaneously reform into a helical filament when the pH was raised (Smith and Koffler, 197 1). This protein could also be used to raise antibodies specific for a particular species, or even strain, of bacterium. In the late 1940s, flagellar filaments had been seen by Pijper, using high light-intensity, dark-field microscopy. Bundles of filaments behind swimming cells appeared to be propagating waves away from the cell body, which could be explained either by coordinated bending or rigid rotation of the filaments.

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Pijper even saw bundle formation and wavelength transformations, but he did not recognize the flagella as the organelles of movement, only extracellular slime (Pijper, 1948)! The simplicity and small size of bacterial flagellar filaments (diameter 15-20 nm, about 10 times smaller than eukaryotic flagella) made it seem unlikely that the propulsion mechanism was contained within the filament itself. Evidence that bacterial filaments are in fact rigid rotating helices came from two experiments in the early 1970s. When polystyrene beads were coated with antiflagellar antibody and ‘stuck’ to the filaments of swimming cells, the beads moved from one side of the filament to the other as if rotating about an axis, rather than staying at one side as would have happened if the filament were propagating a wave (Berg and Anderson, 1973). When antiflagellar antibody was used to coat a glass slide and cells attached to the slide by their flagella, the cell bodies rotated about a fixed point when observed under a microscope (Silverman and Simon, 1974). The strongest supporting evidence came when filament-minus strains were isolated. These cells could not swim but, if tethered via an antibody raised to the hook (the structure linking the filament to the cell body), the cell bodies rotated. This proved that rotation is driven by an active mechanism at the base of the filament and ruled out the possibility that the filament-tethered cells were swimming around an inert point of attachment to the slide. Dark-field light microscopy was again used to look at filament activity in vivo, but this time the filament was assumed to be the organelle responsible for movement. This showed rotation of flagella bundles and that they came apart during tumbles and reformed for the next period of smooth swimming (Macnab, 1976). The assumption was still that the driving force for motility would be ATP hydrolysis, as it is in eukaryotic systems. However, it was found that if ATP synthesis were inhibited by arsenate, a phosphate analogue, E. coli carried on swimming. Using Rhodospirillum rubrum, it was found that if the two components of the electrochemical proton gradient, A 9 and ApH, were independently collapsed (using valinomycin and K+ or a permeant weak acid such as acetate, respectively), the cells continued swimming normally. However, if both valinomycin/K+and acetate were added together to discharge both the electrical and pH component of the electrochemical proton gradient simultaneously, or a proton ionophore such as carbonylcyanide mchlorophenylhydrazone (CCCP) was added, motility ceased (Manson et al., 1977; Glagolev and Skulachev, 1978). In addition, mutants of E. coli lacking the ATP synthase could still swim if given nitrate as a terminal electron acceptor (which allowed the formation of an electrochemical proton gradient) but not if growing by glycolysis (which allowed ATP synthesis but not the formation of a proton gradient) (Larsen et al., 1974). All these results pointed to the identification of a rotary motor driven by the flux of H+ ions down an electrochemical gradient across the cytoplasmic membrane.

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The above experiments relied on inhibitors and mutants, and were open to the criticism that metabolism was being grossly altered, However, confirmation came when it was shown that flagella in cell envelopes isolated from E. coli could rotate if an artificial membrane potential was generated by the addition of K+and valinomycin (Ravid and Eisenbach, 1984). In some species of alkalophilic or marine bacteria, such as Vibrio alginolyticus, sodium ions (Na+) replace protons (H+),but in all other ways Na+-driven motors appear to be the same as their H+-drivencounterparts (Hirota and Imae, 1983; Liu et al., 1990; Atsumi et al., 1992). Indeed, functional hybrid motors have now been made with the Mot proteins of a proton motor replacing the analogous proteins in a Na+ motor Y. Asia, R.E. Sockett and M. Homma, unpublished data. Streptococcus cells swim at up to 20 p d s driven by H+motors that rotate at a few hundred hertz. Na+motors are even more impressive. Vibrioalginolyticus rotates its sodium motors at over 1000 Hz, propelling these cells at up to 200 p d s (Magariyama et al., 1994). The bacterial flagellum was the first rotary electric motor identified in nature, but recent evidence indicates that the F, part of the F, F,-ATPase also rotates, again driven by the transmembrane flux of protons or sodium ions (Armitage,this volume; Abrahams et al., 1994; Boyer, 1997; Noji et al., 1997; Sabbert et al., 1997). The major questions arising from these discoveries are: how is the flux of ions across the cytoplasmic membrane used to generate the torque that makes bacterial flagella rotate; how can the flagellum switch direction when the ion flux is unidirectional; and how is the rotation and switching controlled by environmental stimuli to allow chemotaxis? The last question, now the best understood, is beyond the scope of this review and we refer the reader to a number of recent reviews on this subject (Jones and Aizawa, 1991b; Parkinson, 1993; Stock and Surette, 1996;Armitage and Schmitt, 1997). In this review we will concentrate on the rotary flagellar motor itself what it looks like, how it is made and how it works.

2. THE FLAGELLAR STRUCTURE

With some variation of the theme, the flagella from all species investigated seem to be built on the same basic pattern (Fig. 2a). The flagellum consists of a helical filament connected via the hook to the so-called ‘basal-body’,which is surrounded by a ring of torque-generatingparticles in the cytoplasmic membrane. These particles are anchored to the cell wall and are necessary for torque generation. In mechanical terms, the filament is the propeller, and the basal-body and torque-generating particles together are the motor. Within the motor, the basal-body is the ‘rotor’ and rotates (along with the hook and filament) relative to the anchored torque-generating particles or ‘stator’.

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Figure 2 A(i) A schematic diagram of the bacterial flagellum. The central part (drawn in white) rotates, whilst the torque-generating particles containing MotA and MotB (dark shading) are anchored to the peptidoglycan of the cell wall. Torque is generated by interactions between the C-ring, the torque-generating particles and ions flowing across the cytoplasmic membrane, through the motor. A(ii) The averaged image of electron micrographs of the isolated basal body in a plane directly related to A(i), but lacking the Mot proteins. B(i) A freeze fracture image of an E. coli cell fractured through the cytoplasmic membrane. One ring of Mot proteins is highlighted by the superimposed box (3 rings of Mots are visible in the image). B(ii) shows a ring of Mot proteins in higher magnification. (Photographs kindly provided by David De Rosier A(i) and Shahid Khan B(i)(ii)).

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2.1. The Filament

The filament is usually 5-10 pm long and is generally composed of over 10000 copies of a single protein, flagellin, with a molecular mass varying, depending on the species, from 25 to 60 kDa. Some species may have more than one flagellin but the proteins are usually closely related (Joys, 1988; Dingwall et al., 1990; Pleier and Schmitt, 1991). The C- and N-terminal regions of the different flagellins show homology and are important in polymerization, while the central regions are variable. These central regions are the most exposed and are the most antigenic parts of flagellin. Electron micrographs, high-intensity light microscopy and video-enhanced differential interference contrast microscopy show that flagellar filaments can be made to switch between several different helical conformations (Asakura, 1970; Calladine, 1982; Block et al., 1991b). This can be driven by motor switching (in vivo) or by changes in either the viscous forces on the filament or pH (in vitro) (Macnab, 1976, 1977; Kamiya et al., 1979, 1982; Kamiya and Asakura, 1982). How can a structure made of a single protein form helical structures that can undergo polymorphic transitions? Hotani and coworkers identified 12 different helical conformations by varying the viscous or ionic environment of isolated filaments (Kamiya et al., 1982) and his early structural analysis has since been confirmed by cryoelectron microscopy (Trachtenberg and DeRosier, 1987; Trachtenberg et al., 1987; Trachtenberg and Hammel, 1992). Negative staining has revealed that the flagellin monomers polymerize as 11 fibrils or protofilaments to form a hollow cylinder. A range of Salmonella typhimurium mutants has been isolated with straight flagellar filaments. Negative staining separated these into two groups, RH and LH, on the basis of their X-ray diffraction patterns, suggesting that the monomers in the two filament types had polymerized in different conformations. Using three-dimensional reconstructions of the filaments, the LH filaments have been shown to have all the flagellin subunits in one conformation while the subunits in the RH form showed a different conformation (Morgan and DeRosier, 1992). The two different conformations result in different spacing between subunits so that, for a given number of subunits, one conformation produces longer fibrils than the other. The change from RH to LH conformation was shown to be a rotation of 30° clockwise along the radial axis and 38O clockwise along the vertical axis of the subunit, causing a 50° bend in the outer domain of the subunit relative to the inner domain. The intersubunit spacing of the subunits went from 5 1.6 A, to 52.1 A, indicating a change in the contacts within the inner domains of the subunit proteins (Trachtenberg and DeRosier, 1991; Yamashita et al., 1995). In the 12 polymorphs that have been identified, including the two straight mutants, it appears that the shape of the filament is dictated by the number of fibrils or protofilaments in the RH form compared with the LH form. If some, but not all, of the

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fibrils are in the shorter conformation, the flagellar filament bends to forms a helix, reducing the tension caused by the mismatched lengths of adjacent fibrils. The pitch of the helix is determined by the degree of bending and the pitch of the 1 1-start helix. Circular-dichroism studies on the isolated and polymerized flagellin molecules suggest that flagellin is composed of three domains in solution and a fourth which becomes organized on polymerization. The terminal regions of flagellin are on the inside of the filament, while the antigenic central region is on the outside (Vonderviszt et al., 1991). On polymerization, the central and terminal regions form an interlocking structure with the neighbouring subunits. Changes in the overall filament shape come about when one or more protofilaments change from one state into the other (Vonderviszt et al., 1991; Trachtenberg and DeRosier, 1992). Under natural conditions, this may be caused by the change in the torque or direction of rotation of the motor. The torque generated by the motor is therefore responsible for the helical shape and handedness of the filament. This is seen, for example, in E. coli when a switch from CCW to CW rotation results in a change in both wavelength and handedness of the filament, and in R. sphaeroides, when a stop in rotation causes relaxation of the filament from a functional helix to a large amplitude, short wavelength coiled form (Fig. 1) (Macnab, 1977; Armitage and Macnab, 1987; Armitage et al, 1999). Interestingly, the filament has a central 30 8, channel (Trachtenberg and DeRosier, 1987; Homma et al., 1990). There is now good evidence that the flagellin subunits are synthesized in the bacterial cytoplasm and transported down the central channel as disordered subunits for ordered polymerization at the terminal end of the growing filamen, polymerization being under the control of the hook-associated proteins (HAPS)(see later) (Homma et al., 1984; Homma and Iino, 1985; Macnab, 1996).

2.2. The Hook

At the base of the filament, connecting it to the motor, is a structure called the hook. In most species examined, the hook is a short curved structure, slightly thicker than the filament (about 20 nm) and about 50 nm long (Homma et al., 1990). The structure of the hook is very similar to that of the flagellum, with the 120 or so elongated subunit monomers arranged in several fibrils that produce, in the case of s. typhimurium, a segment of right-handed helix (Sosinsky et al., 1992). Three-dimensional reconstruction of the hooks of S. typhimurium and Caulobacter crescentus show deep grooves in the hook in the six-start direction, possibly allowing the hook to bend (Wagenknecht et al., 1982). The compliance (torsional spring constant) of the hook and the filament has been measured by tethering E. coli cells to slides via either antifilament or anti-

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hook antibody. Flagellar motors were locked (either partially by de-energizing cells or fully by fixing with glutaraldehyde) and the cell bodies were rotated through angles up to 200’ using an optical laser trap (optical tweezers) before being released. The compliance of the tether was calculated via the time course of the return of the cell body to its resting position. Results showed that the compliance of the flagellum is almost all contributed by the hook. When cells were tethered using antifilament antibody, a two-phase response was measured, with the tether behaving as a linear torsional spring for about 180’ and then becoming much more rigid (Block et al., 1989). When cells were tethered by polyhooks they showed only one phase, similar to the soft phase of the complete filament tether (Block er al., 1991a). The torsional compliance of the hook is on the order of dyne cm per radian (lo-’’ N m per radian), and the filament is about 100 times stiffer. Why should the hook be flexible? It may reflect the suggested role of the hook as a universal joint in peritrichously flagellate species, allowing several flagella to come together as a bundle. Torsional compliance may play a role in allowing different flagella to match speeds as a bundle forms or it may merely be a by-product of the flexural compliance that is necessary for the hook to act as a universal joint. Hook-associatedproteins (HAPs) lie between the hook and the filament. Mutants in these HAPs tend to show an increase in polymorphic transformation of the filament (Fahrner et al., 1994; Armitage et al, 1999). It is possible that the hook transmits the change in motor torque to the filament to allow conformational switching. Normally, only major changes in torque are transmitted from the hook through the HAPs, but in their absence the frequent minor changes that occur in the compliant hook are transmitted and result in changes in flagellar waveform. If this is the case, it will be useful to examine the compliance of the hooks of species with a single flagellum, as compliance would not be required for bundle formation but would be required for conformational switching of the filament structure. R. sphaeroides, which has only a single flagellum, has a filament which undergoes regular and multiple conformationalchanges, perhaps supporting a role in torque transmission (Armitage et al., 1999). Three HAPs have been identified in E. coli. HAP1 and HAP3 are located between the hook and filament while HAP2 caps the filament (Homma and Iino, 1985; Homma et al., 1990). They are all present in only a small number of copies, about 10-20, which is equivalent to one or two turns of the helical structure of the hook or flagellum. HAP2 appears to stop extracellular flagellin monomers from spontaneously polymerizing to the distal end of the filament and is required to ensure that monomers exported through the filament are incorporated into the growing filament tip rather than excreted into the medium. The other HAPs may have a role in polymerization of the hook and filament subunits, and in controlling transfer of torque between the hook and filament.

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2.3. The Basal Body

All early pictures of the structure attaching the filament to the cell membrane show a stack of about four rings, two (the L and P rings) in a position equivalent to the outer membrane (absent in Gram-positive bacteria) and two more or less in the position of the cytoplasmic membrane (Cohen-Bazire and London, 1967; DePamphilis and Adler, 1971b). A central rod appears to link together the rings and the hook (Fig. 2) Figure 2B shows (i) the averaged image of electron micrographs of the isolated basal body in a plane directly related to Fig. 2A, but lacking the Mot proteins, and (ii) is a freeze fracture image of a section through the cytoplasmic membrane showing the ring of ‘studs’ around the basal body and thought to be the Mot complex. (Aizawa et al., 1985). These pictures of isolated ‘basal bodies’ led to early theories of torque generation in which the inner rings rotate against each other and thus rotate the filament. The basal body complex in E. coli is made up of eight different proteins, four in the rod (FlgB, C, F and G) and three forming the L, P and MS ring (FlgH, I and FliF). The location of the eighth protein (FliE) has not been established (Macnab, 1996). Gel autoradiography and scanning electron microscopy have indicated that there are 26 or 27 FliF proteins in the MS ring, which is probably also the number of copies of the distal rod protein, FlgG (Jones et al., 1990). There are probably about six copies each of FlgB, C and F. It is now known that the harsh treatment required for basal body isolation preserves only the central core of the total motor structure and leaves half of the motor apparatus in the membrane and cytoplasm. In vivo, rapid-freeze electron microscopy and molecular biological studies have shown that there is a set of proteins (the Mot complex) outside the central core of the motor (Khan et al., 1988, 1991; fig. 2(b)(ii)) and a complex structure on the cytoplasmic face of the motor (the switch and export complexes). These together are responsible for transducing the proton gradient into mechanical rotation. Detailed molecular biological studies, combined with image-processed electron microscopy, have also shown that the two rings in the inner membrane, the M and S rings, and the connecting rod, are the protein product of a single gene,fliF. The M and S rings cannot, therefore, rotate against each other (Ueno et al., 1992, 1994). Further evidence supporting this is that mutations in the M/S ring gene (fliF) do not lead to paralysed mutants and no mutations in this gene have been identified that compensate for any of the paralysed phenotypes.

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2.4. The Mot Proteins

The majority of non-motile mutants isolated in the early studies of bacterial motility were non-flagellate. This reflects the highly organized hierachy of

Figure 3 Regulation of flagellar gene expression and assembly in Salmonella and Escherichia coli. The flagellar operons are expressed as a hierachy. The operons are shown as stippled bars, translating to products, as indicated by white arrows. Positive regulatory control is shown by solid black arrows and negative regulatory control by dashed arrows. The promoters of the different classes of operons are indicated as p ( romoter of class 1 operon), etc., and sigma factors for transcriptional initiation as OCF'. Negative control by and inactivates it. FlgM in turn is inactivated by FlgM occurs because it binds to FliA (e3) its secretion from the cell via the flagellum-specific export pathway,flgM behaves partly like a class 2 gene as there is readthrough from the UpstreamflgA operon. c-AMP = cyclic AMP; CAP = catabolite activator protein. Modified from Macnab (1992).

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control of the 40-50 genes required for flagellar synthesis (Fig. 3) (reviewed in Macnab, 1992). If any gene necessary for an early step in assembly is disrupted, then genes needed later in assembly are not expressed and no filament is assembled. However, a small group of mutants were identified which assembled apparently normal flagella but were unable to swim. The genes involved were isolated and shown, in E. coli and S. typhimurium, to map on an operon including chemotaxis genes, rather than the structural genes for the flagellum. They were also found to be expressed independently of the hierarchy controlling the expression of the structural genes. These genes are motA and morB. Homologues have now been identified in many other, non-enteric species, including alkalophiles. The Mot proteins, MotA and MOB, are integral membrane proteins and are expressed after the rotor part of the motor is synthesized and assembled. They can be expressed independently of the flagellar regulon and will still target the flagellum. The evidence for the location of the Mot proteins is indirect, but electron microscopy suggests that they form a ring of proteins around the MS ring of the basal body. Freeze-fracture and rapid freeze studies on wild-type bacteria identified rings of studs in the membrane, usually numbering about 11 (Fig. 2 ) (Khan et al., 1988).The central core in these structures had the same diameter as the flagellar rod. When either motA or motB mutants were examined, no rings could be identified, indicating that both MotA and MotB are required to form the studs. The variable number of studs in the ring may be the result of freezefracture pulling some studs into the other face of the membrane or it may reflect real variability in the number of Mot complexes around the flagellum. Similar rings containing 14-16 studs have also been seen at the poles of Aquaspirillum serpens, an organism with polar tufts of flagella (Coulton and Murray, 1978). Overproduction of Mot proteins showed that they are targeted to the cytoplasmic membrane, and sequence studies suggest that MotA has four membrane-spanning helices but MotB only one, with most of the protein in the periplasm (Stader et al., 1986; Wilson and Macnab, 1988; Wilson and Macnab, 1990). MotA appears to have only two short regions in the periplasm while it has an extensive sequence in the cytoplasm. Using this topological information and some indirect mutant studies, it was suggested that MotA is the protonconducting protein of the motor, with MotB forming a connection to the peptidoglycan, thus providing the stator (Blair and Berg, 1990, 1991; Blair et al., 1991). Intergenic suppression studies indicate that MotA and MotB interact with each other via their periplasmic domains and MotB could be considered the anchor for MotA; therefore, both may be considered to form the complete stator (Garza et al., 1995). Although the Mot proteins show no homology to any previously identified proton translocating protein, e.g F,F,-ATPase or cytochrome oxidase, studies on a range of motA mutants have shown that MotA, possibly in association with MotB, is almost certainly the proton translocating protein (Sharp et al.,

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1995; Zhou and Blair, 1997). Slow-swimming MotA mutants showed a marked inhibition of swimming at high speeds in the presence of deuterium oxide (heavy water) compared with the wild type (Blair and Berg, 1991). Measurement of proton fluxes in artificially energized membrane vesicles from strains overexpressing either wild-type or mutant MotA proteins from paralysed strains showed that the proton fluxes were much higher in vesicles with the wild-type protein compared with the motA mutant. Overexpression of wild-type MotA also caused impaired growth of E. coli, whereas overexpression of MotA from a paralysed mutant had no effect on growth. Sequence studies on a range of different paralysed MotA mutants have shown the mutations clustered in the four hydrophobic regions of the protein, which is consistent with a proton-conducting role. Although indirect evidence suggests that MotA is the proton pore in the flagellar motor, both MotA and MotB proteins are required for torque generation. ‘Resurrection’experiments have been carried out where the appropriate wildtype gene has been fused behind the lac promoter and expressed in either motA or motB mutants tethered by antiflagellar antibody (Block and Berg, 1984; Blair and Berg, 1988). After transcription was initiated, the tethered cells started to rotate and then speeded up in a series of equal increments. The interpretation of these results is that speed increments occur when independent torque-generating units containing MotA or MotB are incorporated into the motor. Downward as well as upward steps were seen, so the incorporation of units is reversible. Also, the probability of CW rotation was almost zero at the lowest level - motors started reversing only when they had more than one torque generator. This last result is not understood. The maximum number of speed increments seen was eight. Furthermore, after eight increments, motor speeds remained steady for considerable periods and were slightly faster than the speeds of wild-type cells. Comparison between this result and the 8-12 particles typically seen by electron microscopy suggests that each force-generating unit may correspond to more than one intramembraneparticle, and also that exponentially growing bacteria may not possess a full complement of force-generating units. In experiments where flagellar motors resurrected after being disrupted either mechanically or electrically (Berry et al., 1995; Fung and Berg, 1995), equal speed increments were observed that were less than one-eighth of the maximum speed seen for the same cell. The question of the maximum number of torque-generating units per motor remains unresolved, but perhaps the most likely explanation for the data is that there are up to 16 units which come and go in pairs (in undamaged motors). No resurrection experiment has ever seen more than eight speed increments, which would be expected if the smaller speed increments seen with damaged motors corresponded to incorporation of pairs containing one damaged and one intact unit. Torque is generated by independent force-generating units in Na+- as well

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as in H+-driven motors. Muramoto and co-workers (1994) observed stepwise decreases in speed after ultraviolet irradiation of tethered cells of V alginolyticus in the presence of a photoreactive analogue of amiloride, a known inhibitor of Na+ channels and Na+ flagellar motors. These results are interpreted as the successive inactivation of independent units upon the irreversible binding of the amiloride analogue, and suggest that there are between five and nine units per motor. V alginolyticus and Vibrio haemolyticus have proton-driven lateral flagella when growing on surfaces and single, polar, sodium-driven flagella for rapid free swimming (Atsumi et al., 1992). Analysis of the Na+ motor identified two proteins apparently essential for motor rotation, MotY and MotX. Unlike the motor genes in other systems examined, the two genes were located independently of each other and not associated with any flagellar genes. MotY was thought to be the equivalent of MotB, with a single membrane-spanning domain and a possible peptidoglycan binding domain. MotX showed no homology to MotA but, if expressed in E. coli, caused Na+-dependenttoxicity. However, unlike all MotA proteins identified from other species, it has onlyone membrane-spanning domain (McCarter, 1994a,b, 1995).Additional genes have been identified that are required for Na+motor activity in V alginolyticus: p o d and pomB, found as a single operon. PomA and PomB do have sequence similarity to MotA and MotB, and it is thought that these may form the Na+conducting channel of the motor. P o d has a conserved Asp residue very similar to that of MotB. Controlled expression of PomA resulted in incremental increases in speed, again suggesting that this may be equivalent to MotA in proton-driven motors with incremental speed also occurring with MotY expression (Asai et al., 1997). Why V alginolyticus should have four gene products involved in motor rotation is not understood, but it has been suggested that, as the viscous drag on the polar filament produces the signal controlling expression of the lateral proton driven flagella, MotX and MotY could futlction as sensors of the rate of Na+ flux, with PomA and PomB providing the motor function. A number of mutational and intergenic suppressor studies have been carried out in order to identify the key residues involved in motor function. It was found that suppressors of motB mutations could be divided into three groups (Irikura et al., 1993; Garza et af.,1995). The majority of suppressors were in motA, but a significant number were in a gene coding for a component of the switch complex,fliG. Several mutations were found near to the binding domain, which suggested that these might result in a misalignment of the stator and rotor, and some suppressors compensated for this shift. MotA has a large sequence in the cytoplasm and, as this is thought to be the site of torque generation, a number of random and specific mutants were made. Four residues in the 22 kDa cytoplasmic loop were found to be particularly important: two proline residues at the cytoplasdmembrane interface, and two

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charged residues in the cytoplasmic domain. Structural analysis suggests that these might interact electrostatically with residues on the FliG component of the switch. The path of the proton is still not characterized but a study into the role of the conserved acidic residues in all of the proteins thought to be involved in torque generation (MotA, MotB, FliG, FliM and FliN) indicated a critical role for Asp32 of MotB (Blair et al., 1991; Sharp et al., 1995; Zhou et al., 1998b). None of the conserved acidic residues in the other proteins is essential for torque generation, which suggests that Asp32 on MotB has a role in binding the proton during torque generation in E. coli. The Mot complex structures of only a few non-enteric species have been studied in detail. Interestingly, the sequences of motB genes show very little homology across species, the best conservation being in the membranespanning regions. In particular, the region thought to link the membrane-spanning domain and the peptidoglycan binding domains appears very variable in length and sequence. This fits with deletion studies on this linking region in S. typhimurium that suggest that this region is simply an anchor and the role can be successfully carried out by many sequences. Sequence comparison of MotA proteins and their homologues from other species reveal regions of homology between species as diverse as E. coli, Bacillus subtilis and R. sphaemides. Several conserved amino acids have been identified in MotA sequences from all species investigated, suggesting an essential role for these in motor structure or function. For example, there are prolines at the membrane interface which could be involved in protein stabilization and there are several charged residues conserved within the cytoplasmic loop that may be involved in proton translocation (see below) (Shah and Sockett, 1995). 2.5. The Switch Complex

Three genes were identified in E. coli and S. typhimurium,fliG,JliM andfliN, that are expressed early in flagellar biosynthesis (Yamaguchi et al., 1984) and are necessary for flagellar assembly; deletion results in non-flagellate phenotypes. However, specific mutations can result in non-flagellate, non-motile or non-chemotactic phenotypes, depending on the allele (Kihara et al., 1989; Magariyama et al., 1990).The three phenotypes are associated with mutations in fairly distinct regions of the three genes. All three proteins, collectively called the switch complex, have a sequence suggesting a peripheral membrane location. Mutations in fliM cause paralysis, but regulated underexpression and overexpression of both fliM andJliN show that the proteins are located separately from the torque-generating proteins MotA and MotB, but interact with each other (Sockett et al., 1992; Tang and Blair, 1995; Tang et al., 1995). Using a fusion of FliG and the MS-ring gene product, the

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switch complex was found to be located on the cytoplasmic face of the MSring. Support for complex formation between the three proteins comes from pseudorevertant and suppressor studies. Some mutations in these three genes can be compensated for by mutations in genes coding for the Mot proteins and the chemotactic Che signalling proteins. The Che proteins are all cytoplasmic proteins, adding strength to the idea that the switch complex is located in the cytoplasm but is also connected to the motor proteins. Rapid-freeze electron microscopy and negative staining of several species of bacteria have revealed what appear to be intracellular structures attached to the cytoplasmic side of the flagellar motor, extending into the cytoplasm (Fig. 2) (Khan et al., 1992; Francis et al., 1994). Immunoelectron microscopy puts the Fli proteins in this so-called C-ring. Mutations infliG that result in assembled but paralysed flagella, all cluster in the C-terminal segment of the protein. Analysis of the phenotypes of a number of paralysed phenotypes with mutations infliG, fliM orfliN indicated that FliG has a direct role in torque generation, but FliM or FliN do not (Lloyd et al., 1996). Mutagenesis in this region indicates that three charged residues, Arg279, Asp286 and Asp287, are important for torque generation, with other charged residues playing lesser roles (Lloyd and Blair, 1997). This was taken further in double mutants in which the conserved charged residues on both MotA and FliG were replaced singly or in pairs by either neutral or oppositecharged residues. The mutants were then tested on swarm plates for strong synergism or suppression of movement. This identified a number of interacting residues on the two proteins important for torque generation. These were residues that are probably not important for structural integrity as like-charge substitutions still allowed motor rotation, as did reversal of the charge of a possibly interacting pair of residues on the two proteins. Substitution of a neutral amino acid had less effect than one of opposite charge. Although no single electrostatic interaction was critical for the motor activity, the data do indicate that Asp289 and Asp288 on FliG interact with Arg90 on MotA, and Arg28 1 on FliG interacts with Glu98 on MotA. The role of electrostatic interactions in torque generation is not understood. These interactions are weak but would become more effective if the groups came into close proximity during one of the steps of motor rotation. They would also be more effective if water was excluded from the interface. Whether the electrostatic interaction forms a proton-conducting path, or is involved in accelerating one of the steps involved in rotation remains to be identified (see later). The stoichiometry of the proteins in the switch complex suggests that there may be 26 copies of each Fli protein within the C-ring. It seems likely that the flagellum is rotated as a result of energy transfer from ions moving down their electrochemical gradient between the eight membrane-spanning Mot complexes and the 26 or so FliG proteins of the switch complex on the cytoplasmic face of the motor. The cytoplasmic chemotactic signalling proteins probably

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interact with the FliM and FliN components of the switch complex to change its conformation relative to the Mot proteins and cause rotation to stop or switch direction (Welch et al., 1993). 2.6. The Export Apparatus

The flagellar proteins found in the cytoplasmic membrane, and the L- and Pring proteins all have the classical Sec export signal sequence. All of the other flagellar proteins found external to the cell membrane are exported via a flagellar-specific pathway, which appears to be related to the Type I11 secretion system in the virulence systems of some pathogens (Dreyfus et ul., 1993; Van Gijsegem et al., 1995; Chilcott and Hughes, 1998). The proteins which make up the hook and filament, including the rod and the hook-associated proteins, have no recognizable export signal sequences and all appear to pass down the central channel in the rod, the growing hook, and the filament for polymerization at the distal end by a mechanism still poorly understood. The export apparatus is thought to be a protein complex located on the cytoplasmic face of the basal-body complex, perhaps close to the switch or C-ring complex. Several genes have been identified with a role specifically in assembly rather than the final flagellar structure. Only one has been characterized in detail, the jliZ gene product, althoughjlhA andjliH may be involved. FlhA is also related to proteins involved in expression of virulence factors, as are several other flagellar proteins; see Table 4 in Macnab (1996) for more detail of the relationship. FliI has homology to the P-subunit of the F,F,-ATPase and can bind ATP (Vogler et ul., 1991). FliI may be an ATP-hydrolysing component of a protein translocase responsible for activating transport of the extracellular components of the flagellum through the growing flagellum itself or a flagellaspecific chaperone protein. The flagellum is an extremely complex structure, which must be put together in a highly controlled sequence. The proteins tend to be assembled in the order of their expression (see below) but, for proteins that are expressed from the same operon, there must be some control within the structure itself and some mechanism for the state of the external structure to feedback to the cell (Fig. 3). The rod proteins are exported first, followed by the hook proteins. The hook is always the same length and there must be a signal controlling its length. Mutants inJliK produce very long hooks (polyhooks) and no filament, suggesting a breakdown in control of both hook length and filament expression (Suzuki and Iino, 1981). FliK mutations which result in loss of filaments can be suppressed by mutations in FlhB, a membrane protein. It has been suggested that FliK is involved in hook length and FlhB in inhibiting filament export, normally overcome by FliK. In the absence of both FliK and FlhB, the filament proteins can be exported. The mechanism used to determine hook

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length is unclear. Finally, other HAPS,the flagellin molecules themselves and the anti-o-factor FlgM are exported. The export of FlgM allows the expression of the late genes to take place, see below. The hook-associated protein, HAPl, displaces a protein at the end of the hook and the other two HAPs, HAP3 and HAP2, are then exported to provide the framework for filament polymerization. The flagellin monomers pass through the central channel to polymerize between HAP3 and HAP2. HAP2 is retained at the distal end of the filament as the structure grows, possibly to prevent flagellin proteins being lost into the surrounding medium. 2.7. Genetics of Flagellar Synthesis

It is not the remit of this review to discuss the genetics of flagellar synthesis, since there have been several excellent reviews recently (Jones and Aizawa, 1991a; Macnab, 1992, 1995, 1996). For the purposes of this article it is (hopefully) sufficient to know that, in enteric bacteria, there are over 40 genes involved in making and operating a flagellum, all of which have been identified and cloned in E. coli. Only about 17 different proteins have been identified in the mature organelle. Although some gene products may be present in low copy number, it still indicates that a large number of genes are involved in controlling transcription andor assembly (Kubori et al., 1992). This is not surprising, as the protein products are required in numbers ranging from under ten to several thousand in the completed flagellum. It would obviously be disastrous for the cell if the flagellin monomers were synthesized before the basal body was in place to allow external polymerization. There are also few flagella per cell, the numbers and location varying between species. In all cases, the timing of synthesis and the site of assembly of a new flagellum must be controlled. In E. coli there are 15 operons coding for flagellar proteins and a few single operons coding for components of the chemosensory pathway. The operons are expressed as a heirachy, a regulon, with a single master operon,flhDC, at the apex (Fig. 3). Both gene products are required for expression of the class 2 and class 3 operons. Genes in class 2 and class 3 operons have related, but distinct, promoter sequences; they share a -10 consensus but not the -35 site. FliA is a flagella-specifico-factor, o-flagella or oF.The master operon controls expression of class 2 operons, and these are required for expression of class 3 operons. Control of expression of class 3b operons is via the interaction of oFand the exported anti-factor FlgM. As long as FlgM remains in the cell, the operons requiring oFwill not be expressed. When FliM is exported from the cell, on completion of the hook, oFcan induce expression of the class 3b operons, which code for proteins required late in flagellum assembly, e.g. the flagellin proteins. The expenditure in cellular energy required to maintain,

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transcribe and translate flagellar genes and to operate a flagellum means that a bacterium is unlikely to be motile unless motility provides a survival advantage. Catabolite repression in E. coli in fact stops flagellar synthesis in a high-glucose medium, as it is in its optimal environment for growth. R. sphaeroides swims more slowly when given l o r n organic acids, their preferred electron donors and carbon sources, even though the Ap remains high and they still maintain their flagella. Experiments with chemostat-grown and well-mixed cultures show also that in well-mixed environments, non-motile mutants have a 2% growth rate advantage over motile wild-type cells, and nonmotile mutants dominate rapidly. However, in poorly mixed conditions, such as unmixed cultures or semi-solid media, motile cells proliferate and nonmotile cultures rapidly revert to motile (Pilgram and Williams, 1976). Macnab has calculated that it takes about 2% of the cell’s energy to synthesize flagella, while energy used to drive flagellar rotation is less than 0.5% of the energy generated from aerobic respiration. This is, of course, for E. coli in a rich medium and, while the rate of synthesis of flagella can be linked to the growth rate of the cell, operation of the flagella will take the same amount of energy in rich or growth-limitingmedia. The energy expenditure on swimming may be quite significant for a lithotrophically growing species

3. FLAGELLAR MOTOR FUNCTION 3.1. Methods of Measuring Flagellar Rotation

The majority of physiological and mechanical studies of the bacterial flagellar motor have used strains of E. coli, S. typhimurium and Streptococcus. A common and powerful technique which allows direct measurement of the rotation rate of individual flagellar motors is that of tethering cells (Silverman and Simon, 1974) (the small size of the flagellum makes direct observation of its rotation difficult) (Fig. 4). Flagellar filaments are attached to a microscope coverslip using antibodies and the flagellar motor causes the entire cell body to rotate. Tethered cells typically spin at about 10 Hz, at which point the torque generated by the motor is balanced by the viscous drag on the cell body. This compares with speeds in excess of 100 Hz for motors of free-swimming cells, in which the viscous drag coefficient of the rotating filament is considerably smaller than that of the tethered cell. Other techniques, where the motor rotates at low speeds, use beads (Eisenbach et al., 1990)or dead cells (Ishihara et al., 1983; Fung and Berg, 1995) attached to filaments as markers of rotation. In all cases, inertial forces are negligible. The Reynold’s number (which is an indicator of the ratio of inertial to viscous forces) for a swimming or tethered cell is of the order This means that, if the flagellar motor were to stop, the cell

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Tethered cell

’ \ Laser

dark-field

/

\

Bead attached to motor

Figure 4 Three methods which can be used to observe flagellar or motor rotation. Tethering involves fixing a cell via a single flagellum to a glass slide and observing cell body rotation. Because of the increased viscous drag the cell bodies rotate more slowly than flagella, at speeds of up to 20 Hz,and this can be followed using video recording or quadrant diode. Laser dark-field microscopy allows the fast rotation of the flagellum itself to be measured. The helical filament is imaged as a series of bright bands which move along the filament axis as the helix rotates. An alternative method uses as a marker for rotation a small bead attached to the flagellum or hook. The rotation of the bead can again be measured using laser light.

would come to a halt in a distance comparable to an atomic diameter. Thus the rotation rate is simply equal to the motor torque divided by the frictional drag coefficient of whatever is rotating. While tethered cells are easy to prepare and observe, they have traditionally allowed only slow flagellar rotation to be measured. In the first successful attempt to measure rapid flagellar rotation, the average rotation rate of flagellar bundles in a population of swimming cells was inferred from the frequency spectrum of cell body vibrations (Lowe et al., 1987). Parallel measurements of bundle rotation rates using this technique and linear swimming speeds indicated that the two were directly proportional, allowing swimming speed to be used as an indicator of rotation rate. However, while the proportionality between swimming speed and motor rotation holds at a population level, swimming speed is not a reliable indicator of the rotation rate of individual flagellar motors (Kudo et al., 1990; Magariyama et al., 1994).Three techniques have emerged in recent years which do allow the observation of rapid rotation of single motors. The first of these is laser dark-field microscopy, in which a laser bean1 aligned on the optical axis of a microscope is focused on to the filament of an immobilized cell and the light scattered by the filament is collected by the microscope objective. Using this technique, rotation rates of almost 200 Hz in E. coli and as fast as 1700 Hz in V alginolyticus have been measured (Kudo et al., 1990; Magariyama et al., 1994). In an extension of the tethered cell technique, ‘electrorotation’uses electric fields rotating at megahertz frequencies to apply controlled external torque to the flagellar motor (Berg and Turner, 1993; Washizu et al., 1993) (see later for details of method). Rotation

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rates as high as 900 Hz have been achieved in tethered E. coli cells covalently cross-linked to silica-coated sapphire windows. (Covalent cross-linking is necessary because traditional antibody tethers are not strong enough for these high speeds, while sapphire windows were needed to dissipate the heat generated by the strong electric fields used in electrorotation.) The third technique for observing rapid flagellar rotation uses a focused infra-red laser to measure the rotation rates of small (0.3-1.0 pm diameter) spherical beads attached to truncated flagellar filaments (W.S. Ryu, personal communication). Speeds up to 250 Hz have been measured using this technique. The actual measurement of the speed of flagellar rotation is achieved either by video microscopy or by a variety of photodetector-based techniques. In video methods, rotation rates are typically obtained by analysis of videotapes of rotating tethered cells, either manually or using customized computer software. More recently, advances in computer power have allowed on-line analysis. Video methods have the advantage that many cells can be observed simultaneously in a single experiment, but have limited time resolution owing to video frame rates of 60 Hz or less. In contrast, photodetector methods allow recordings of only one motor at a time (or of the average properties of a whole population) but have the advantage of much higher temporal resolution. Photodetector methods are necessary for the measurement of rotation rates above about 30 Hz. A number of different variations exist, depending on the rotation assay. Earlier methods record changes in the light intensity of an image or part of an image caused by moving filaments, cell bodies or beads. For example, the simplest method measures changes in transmitted light intensity when the image of a tethered cell passes over a pinhole placed in front of the photodetector (Berg, 1976). In a variation on this theme, the image is duplicated and the pinhole is replaced by two linearly graded transmission filters (Kobayasi et al., 1977; Berg et al., 1982), which record, in two dimensions, the rotation of the centre of the image. Similarly, the changing light intensity transmitted by a slit placed over the image of a rotating flagellar filament is used to measure rotation rates in the laser dark-field technique. For the measurement of rapidly rotating beads attached to flagella, a nonimaging technique is used, in which the deflection of a laser beam by the bead is detected using a quadrant photodiode.

3.2. The Driving Force for Rotation Aside from its rotary motion, the most striking difference between the flagellar motor and linear molecular motors of eukaryotes is that the flagellar motor is powered by transmembrane ion fluxes rather than ATP hydrolysis. Flagellar motors of many species are energized by a transmembrane electrochemical gradient of H+ ions (protons), and the majority of studies of flagellar

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energization have used bacteria whose motors run on this ‘protonmotive force’ (Ap). As mentioned above, in some marine or alkalophilic species, Na+ replaces H+as the ion that powers flagellar rotation. These Na+ motors are able to rotate faster than their proton counterparts but otherwise they seem to be the same; indeed, functioning hybrid motors have been constructed. Interestingly, some species can produce either type of motor, with each type adapted for a different type of motility and expressed under different conditions. As described above, ci alginolyricus can swim using a single Na+-drivenflagellum in open Oceans but, when attached to a surface, large numbers of proton-driven flagella are induced, allowing the cells to swarm over the surface. To measure the dependence of flagellar rotation on the electrochemical gradient and flux of the energizing ions, we need to be able to measure, or better still to control, Ap or the Na+-motive force, ANa. Ap may be written as KT Ap = A Y +-In

e

where AY is the transmembrane voltage (inside minus outside), Ci and Co are the activities of H+ inside and outside the cell, respectively, k is Boltzmann’s constant, T the absolute temperature and e the charge of the proton. The same expression holds for the Na+-motive force if Ci and Co represent the activities of Na+ rather than H+.There are two separate components of Ap; the electrical component (denoted by A Y in Equation 1) and the chemical component (represented by the second term on the right-hand side of Equation 1). The chemical component may be controlled by altering proton concentrations inside or outside the cell. Control of membrane voltage has been achieved by establishing a K+ diffusion potential in de-energized cells whose membranes have been made permeable to K+ by the ionophore valinomycin. Cells of E. coli are not de-energized by simple starvation, so strains of Streptococcus have traditionally been used for experiments using this method of artificial energization. R. sphaeroides is photosynthetic, allowing natural control of Ap by growing cells in bright light and then reducing light levels (Grishanin et al., 1997; Armitage and Evans, 1985; R.M. Berry and J.P. Armitage, unpublished observation). This species has the added advantage of possessing, in the photosynthetic membrane, carotenoid pigments, an intrinsic indicator of the membrane potential A Y (Clark and Jackson, 1981). Patch-clamp techniques, which in principle offer the most attractive prospect for controlling Ap and measuring proton fluxes through flagellar motors, are impractical for a number of reasons. Firstly, the small size of bacteria renders patch-clamping technically difficult. The presence of the outer membrane makes patch-clamping the cytoplasmic membrane very difficult and, while it is possible to create giant spheroplasts by lysis of the peptidoglycan, the outer membrane often remains attached (Buechner et al.,

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1990; Martinac et af., 1990). To add to these problems, spheroplasts are nonmotile, presumably because the peptidoglycan plays a crucial function in anchoring the stator of the flagellar motor. Direct control of the membrane voltage in E. coli using a voltage-clamp technique has been demonstrated (Fung and Berg, 1995), but the technique has the disadvantages of extreme technical difficulty and short life (a few minutes) of the preparation. E. coli cells were grown with cephalexin to produce cells tens of pm long with a single cytoplasmic compartment. Long cells were then sucked into a custom micropipette with a narrow constriction about 10 pm from the tip, where the cells became stuck. The portion of the cell membrane inside the pipette was made permeable by the presence of a proton ionophore in the pipette, and a transmembrane voltage could then be applied to motors on the external portion of the cell by voltage clamping the inside of the pipette. The preparation lasted until diffusion of the ionophore collapsed the membrane voltage. The literature to date contains only one direct measurement of proton flux through the flagellar motor. The rate of proton uptake by a population of swimming cells was measured when flagellar rotation was stopped (Meister et al., 1987). Flagella were stopped by adding anti-filament antibody to cross-link the filaments of different motors and proton uptake rates were monitored via changes in the pH of a weakly buffered medium in which the cells were swimming. It was deduced that the rotation-dependent proton flux is proportional to rotation rate, and corresponds to the transit of approximately 1000 protons per revolution of the motor. For a motor rotating at 100 Hz, this would give a current of lo5protons per second, or -0.01 PA, two orders of magnitude smaller than the single-channel currents typically recorded in patch-clamp experiments. Thus the possibility of directly measuring proton fluxes through single motors seems remote. There have been numerous measurements of the relationship between Ap and both swimming speed and tethered rotation rate of artificially energized cells. The consensus for tethered cells appears to be that torque varies linearly with Ap up to -150 mV (Fig. 5 ) , and that the chemical and electrical components of Ap are equivalent. For swimming cells, various authors report different threshold potentials for swimming, from -13 mV (Harrison et al., 1994) to -50 mV Khan et al., 1990) in H+motors, and as large as -100 mV in the Na+powered motors of an alkalophilic Bacillus strain (Hirota and Imae, 1983). Also saturation of swimming speed has been reported at potentials ranging from -50 mV to -200 mV in different species. However, this does not necessarily reflect a non-linearity between motor rotation rate and Ap in the low-load, high-speed conditions of swimming cells. Rather, the threshold and saturation effects may reside in the hydrodynamics of swimming propelled by rotating flagella. Tethered cells are a better test for the existence of a &I threshold for rotation, as rotation rates of single motors are measured directly. Rotation rates appear to

-

THE BACTERIAL FLAGELLAR MOTOR

315

4

0

50

100

150

Protonmotive Force (mV) Figure 5 The relationship between proton motive force (Ap) and torque in tethered cells. In the high-load, low-speed regime of tethered cells, the relationship between torque and Ap is linear up to at least -150 mV.The thick line is based on data from Fung and Berg (1995), while the thin line is based on data from Khan et al. (1985) (the two lines are displaced slightly so that they can be distinguished). The apparent threshold for rotation when the Ap is increased from zero (lower thin line) is absent when the Ap is reduced towards zero (upper thin line). This is probably due to inactivation of the torque-generating units when the motor is de-energized.

be directly proportional to Ap over the range -20 to -200 mV (Khan and Macnab, 1980; Khan and Berg, 1983; Fung and Berg, 1995). Early work suggested a threshold Ap for rotation (Berg et al., 1982), but subsequent results indicate that rotation rates are proportional to Ap all the way to zero Ap (Khan et al., 1985). In the latter study, there remained an apparent threshold for rotation when Ap was increased from zero, but when cells were subsequently de-energized the linear relationship between rotation rate and Ap extended all the way down to zero (see Fig. 5). In this work, as elsewhere, a time lag was observed between abrupt re-energizationof cells and the subsequent onset of flagellar rotation (Armitage and Evans, 1985; Kami-ike et al., 1991; Fung and Berg, 1995). This contrasts with the rapid changes in speed (as short as 15 ms) in response to sudden changes in Ap in motors that are already rotating (Shimada and Berg, 1987). These results can be understood if de-energization inactivates or ‘locksup’ motors, which take time to recover on re-energization. Strong evidence for this hypothesis is provided by the experimentsof Fung and Berg, who measured torque recovery in discrete steps of equal size when the membrane potential of de-energized cells was suddenly restored to normal (Fung and Berg, 1995).This indicates that de-energization inactivates the torque-generatingunits (MotA/B) in the motor, and that these units reactivate independently over a few minutes fol-

316

RICHARD M. BERRY AND JUDITH I? ARMITAGE

lowing re-energization.It is not known whether deactivatedunits remain attached to the flagellar motor, or whether they diffuse away and have to be replaced from a circulating pool in the membrane.

3.3.Reversibility Another remarkable feature of the flagellar motors of many species is their reversibility. Naturally energized cells, where Ap is negative inside and protons are driven into the cell down the electrochemical gradient, are able to switch between rotation at approximately the same speed in either direction (Berg, 1974). Switches are fast, occurring within 10 ms in tethered cells and within 1 ms in single filaments (Berg, 1976; Kudo et al., 1990). Switches occur at random intervals, and individual switches of different motors on the same cell are not at all correlated,indicating that the stochastic process controlling motor switching occurs at the level of the individual motor (Ishihara et al., 1983; Macnab and Han, 1983). Using long cells deficient in septation it was found that motors on the same cell had a similar bias between rotation directions, and that variations in the bias of separate motors were closely correlated if the motors were separated by a few pm or less. Thus it appears that a diffusible signal with a range similar to the size of normal cells controls directional bias, while local stochastic processes control the individual switching events of a single motor. The diffuse signal is believed to be the phosphorylated form (CheY-P) of the signal protein, CheY (Ravid et al., 1986).CheY is the response regulator of the chemosensory phosphorelay system. It is usually phosphorylated by a histidine protein kinase, CheA, whose activity is under the control of the chemosensory system (although in unstimulated conditions it may undergo phosphorylation at a low frequency by small phosphodonors, such as acetyl phosphate). The binding of CheY-P to FliM of the switch increases the probability of CW over CCW rotation. Presumably, CheY-P binds to the rotor (FliM) and in so doing reduces the free energy of the CW state relative to the CCW state. In the absence of CheY-P, at room temperature, motors rotate exclusively CCW. However, CW rotation can be observed in mutants lacking CheY if the temperature is reduced to close to O'C, indicating an entropic contribution to the free energy difference between CW and CCW states (Turner et al., 1996). In addition to CW and CCW rotation, there may be a third so-called 'pause' state in which the motor does not rotate. Kuo and Koshland (1989) saw short pauses lasting less than 0.25 s, whose frequency was correlated with the frequency of switching events. Pauses had been seen earlier but were attributed to cell bodies sticking to the tethering surface (Berg, 1976). In evidence against this explanation, pauses are also seen in single filaments and in beads stuck to the filaments of cells far from any surfaces (Eisenbach et al., 1990; Kudo et al., 1990). The possibility remains, however, that pauses are artefacts of the assays

THE BACTERIAL FLAGELLAR MOTOR

317

used to observe rotation or the computer programs used to analyse the resulting data, rather than a genuine feature of flagellar rotation. We might expect a flagellar motor in a mode that couples the influx of protons to CCW rotation to couple the efflux of protons to CW rotation upon reversal of the direction of Ap. Berg and coworkers (1982), however, found that motors of Streptococcus rotated CW when artificially energized by a small Ap in either direction. One possible explanation is that cells switch from one mode to the other, in response either to the change in Ap or to the accompanying change in pH. The confusion of wild-type motors naturally switching direction can be avoided by studying mutants that are unable to switch. One such mutant was found which was insensitive to changes in cytoplasmic pH and which rotated CCW only when Ap was in the ‘normal’direction (proton influx) and CW only with a reversed Ap (proton efflux), indicating that the basic torque-generating cycle of the motor is reversible with respect to the direction of proton flux. This is known to be the case in nature’s other rotary proton-driven machine, the F,, part of the F,F,-ATPase. As further evidence, Fung and Berg (1995) found that while reversing the direction of Ap in voltageclamped E. coli cells usually caused motors to stop rotating (as a result of de-energization),in five cases out of 17, motors reversed direction and rotated a few times before stopping. In summary, the bacterial flagellar motor appears to be reversible at two levels. First, it possesses two modes which couple proton influx in normally energized cells to rotation in either direction. Second, each mode can probably be driven in either direction depending on the direction of Ap. However, the effects of reversing Ap upon the basic mechanism of the flagellar motor are confused, in E. coli at least, by the apparent disassembly of motors in the absence of a normal Ap.

3.4. Torque versus Rotation Rate

A satisfactory understanding of the flagellar motor will require a detailed model that accurately predicts the behaviour of the motor under a wide range of conditions. As well as the response of the motor to changes in Ap, an important test of different models is the relationship that they predict between motor torque and the speed of rotation. At low Reynold’s number the torque is equal to the product of speed and frictional drag coefficient. When the speed of the motor in tethered cells is altered between 10 Hz and a few hertz by increasing the viscosity of the medium, this product remains constant, indicating that the torque is constant over this speed range. In swimming Streptococcus cells, the flagella rotate in a bundle at about 100 Hz, while the cell body counter-rotates at a few hertz (Lowe et al., 1987).The torque in this case is the sum of the individual torques of the flagellar motors that form the bundle. This immediately

318

RICHARD M. BERRY AND JUDITH P. ARMITAGE

infers two things. First, the viscous drag coefficient of the cell body is about ten times greater than that of the bundle, hence the greater rotational speed of the bundle. Second, the motor generates considerably less torque in a swimming cell than it does in a tethered cell. This follows because the frictional drag coefficient of a swimming cell body, rolling around its long axis, will be less than that of a tethered cell rotating like a propeller - yet a number of motors working together do not generate enough torque to roll the cell body as fast as a single motor can rotate a tethered cell. The rotation rate of the motors in a swimming cell is the sum of the cell body and bundle speeds, and the conclusion is therefore that motors generate considerably less torque at speeds over 100 Hz than they do at around 10 Hz. The rotation rate can be altered, by changing the viscosity of the medium. This makes it possible to measure motor torque, calculated from body-roll frequencies, as a function of motor speed. By measuring the rotation rates in different viscosities, an approximately linear decrease in torque between 50 Hz and 100 Hz was found, extrapolating to zero torque at around 110 Hz (Lowe et al., 1987). Comparing absolute values of torque, based on estimates of the drag coefficients of the rolling cell bodies of swimming cells and the rotating bodies of tethered cells, the authors suggested that the torque-speed relationship may be roughly linear all the way down to the speeds of tethered cells. However, they also noted the large uncertainty, up to 40%, in the comparison of torques calculated for swimming and tethered cells. The observation of constant torque in tethered cells indicates that internal processes in the torque-generating cycle of the motor are not rate limiting at speeds on the order of 10 Hz and below. In swimming cells, on the other hand, torque is much reduced, indicating that the speed of motor rotation is limited by internal processes.At the ‘zero torque speed’ (110 Hz at 22°C for Streptococcus in the above experiment) these internal processes dissipate all the energy available to the motor and the output power goes to zero. (As an analogy, imagine a person riding a bicycle with one gear and no freewheeling. The ‘internal processes’ are the motions of the rider’s legs on the pedals, the output torque is what the rider applies to the back wheel via the chain. At very low speeds, the rider can push the pedals with all his force, and will produce constant torque. However, if he is going very fast downhill, there comes a point where he can only just move his legs around fast enough to keep up with the pedals, and is not pushing at all. Here, all his efforts are being dissipated in the motion of his legs.) These findings are confirmed by experiments on the temperature dependence of motor speed. In tethered cells, speed is insensitive to temperature while the motor speed in swimming cells increases sixfold as the temperature is increased from 10°C to 40°C (Khan and Berg, 1983; Lowe et al., 1987). This is to be expected if increasing the temperature increases the rates of internal motor processes, and if these rates limit motor speed in swimming but not in tethered cells. Further evidence comes from motors powered by non-physiological ions.

THE BACTERIAL FLAGELLAR MOTOR

319

Substitutions of deuterium (2H+) for H+, or Li+ for Na+ in H+- and Na+powered motors, respectively, reduced swimming speeds but not tethered cell rotation rates (Liu et al., 1990). Both substitutions are expected to slow down reactions involving the motion of ions through the flagellar motor. By varying the viscosity experienced by tethered or swimming cells, speeds up to 10 Hz and between 50 Hz and 100 Hz can be studied separately. Intermediate speeds are not accessible and there remains considerable uncertainty as to how the absolute torques in the two cases relate to each other. The technique of electrorotation allows an external torque to be applied to the motor, via the body of a tethered cell, and allows the entire speed range to be examined in a single motor. In particular, the motor can be studied under conditions where it is made to rotate backwards, or forwards at speeds higher than the zero-torque speed, by the electrorotation torque. These regimes are not accessible in cells rotating under their own power and provide a valuable testbed for models of how the motor works. The phenomenon of electrorotation has been known for a long time but has only recently been applied to studies of the bacterial flagellar motor (Berg and Turner, 1993; Washizu et al., 1993). Essentially, a rapidly rotating electric field polarizes the cell body and the surrounding medium. Owing to the high frequency of rotation (several megahertz), the polarization lags behind the electric field, and thus a torque is exerted upon the cell. This torque is proportional to the square of the electric field amplitude. The speed of rotation of a tethered cell with electrorotation is equal to the sum of the motor and electrorotation torques, divided by the frictional drag coefficient.That is to say, 'motor +

'external

=fw

where Tdenotes torque,fis the frictional drag coefficient and w is the rotation speed. If the motor torque were zero we would have

and combining Equations 2 and 3 gives

That is, the difference between speeds obtained with a functional motor and with a motor that generates no torque, at a given value of external torque, is proportional to the torque generated by the functional motor. To obtain o ', motors were either broken mechanically, de-energized by ionophores or irradated with UV, killing the cells. Figure 6 summarizes the results obtained using electrorotation, with motor torque plotted as a function of speed for motors of a CCW-only strain of E. coli (Berg and Turner, 1993; Berry and

320

RICHARD M. BERRY AND JUDITH P. ARMITAGE

4 -

pc:

o

sk?

-4

-

-8

-

-fv

0-(

-0

\\=\$

\.

c

11.2 \ \ 6 2 * c

A-

0-

I

0i

b

Figure 6 The relationship between torque and rotational speed measured by electrorotation. The torque/speed relationship is linear for negative speeds (i.e. when the motor is pushed against its natural direction) and up to a positive speed that depends upon temperature. At higher speeds the torque falls more steeply, reaching a maximum level of resistance at the highest speeds. Torque is shown as approximately constant in the initial linear regime, although the possibility exists that the decline in torque with speed is steeper than shown here (Berry and Berg, 1999).The absolute values of torque are based on measurements using optical tweezers (Berry and Berg, 1997) rather than electrorotation.

Berg, 1999). The regime of constant torque extends to surprisingly high speeds, around 60 Hz at 11.2 "C and up to 200 Hz at 22.6"C. At higher speeds, torque falls approximately linearly to zero and beyond, finally saturating at a constant resistance at very high speed. Torque versus speed curves for different temperatures are the same except for a rescaling of the speed axis, as would be expected if temperature affects only the absolute rates of processes in the cycle of the motor. This is consistent with previous results on the temperature dependence of the speeds of swimming and tethered cells. When motors are driven backwards by external torque, they generate similar torque to that produced when they rotate forwards, that is to say, the torque-speed curve is almost flat at speeds up to 100 Hz in either direction. Initial results with electrorotation of E. coli, but not of Salmonella, contradicted this result, instead suggesting that a considerably larger torque was required to make cells rotate backwards than was sufficient to stop them rotating forwards (Berg and Turner, 1993; Washizu et al., 1993). However, this effect was shown to be an artefact of the technique (Berry et al., 1995; Berry and Berg, 1996), and the continuity of the torque speed relationship through zero speed was demonstrated by using 'optical tweezers' instead of electrorotation to apply external torque to the motor (Berry and Berg, 1997).

THE BACTERIAL FLAGELLAR MOTOR

321

3.5. Smoothness of Rotation

Recent reports observing steps in the motion of the eukaryotic motor proteins kinesin and myosin have opened the possibility of understanding these motors at the level of mechanochemical transitions in single molecules (Kojima et al., 1997; Schnitzer and Block, 1997).The search for fine structure in the rotation of the bacterial flagellar motor is an old one but, to date, there have been no successes. Flower-like patterns seen in time-exposure photographs of slowly rotating de-energized cells indicated a five- or six-fold symmetry, but this probably reflects the helical symmetry of the hook, filament and rod rather than anything in the flagellar motor itself (Khan er al., 1985). All other attempts to measure steps in the rotation of the flagellar motor have failed, and the possibility remains that the motor rotates far more smoothly than either kinesin or myosin. If there are steps, however, there are several reasons why they might be harder to observe in the bacterial flagellar motor than in kinesin and myosin assays in vitro. First, there is the high flexibility of the tether in tethered cells, which will tend to smooth out any steps made by the motor and prevent them from being seen in the rotation of the tethered cell body (Block et al., 1989, 1991a). Second, there is the complication of many parallel torque-generating units. In a wild-type motor, one is looking not at a single motor molecule but at as many as 8 or 16 working together. It may be possible to surmount these problems by using resurrection mutants or other techniques to study single motor molecules, and the new technology of optical tweezers to increase the angular and temporal resolution of measurements. However, for the time being, direct measurements of the molecular details of flagellar rotation remain elusive. Another approach to understanding the basic structure of flagellar motion, instead of looking directly for steps, is to measure fluctuations in speed and infer the stochastic behaviour of the motor. There are various possible sources of the fluctuations in motor speed that are observable on all time scales. Candidates that have received a mention include unresolved short pausing and switching events, fluctuations in Ap, addition and removal of torque-generating units and, of course, rotational Brownian motion. An analysis of variance performed on the times taken by tethered cells to cover one or more revolutions suggested that results were consistent with a mechanism where free rotational Brownian motion was superimposed upon a constant, smooth rotation (Khan er al., 1985). However, the data used and the analysis do not exclude the possibility that the variance reflects fluctuations intrinsic to the flagellar motor mechanism. Based on this latter hypothesis, Berg concluded that, if the motor takes steps at random times (a Poisson process), each revolution would include around 400 such steps (Berg et al., 1982). Contributions to the variance from processes other than motor stepping would make this number an underestimate of the number of motor steps, while any regularity in the intervals between steps would mean that 400 is an overestimate.

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RICHARD M. BERRY AND JUDITH P. ARMITAGE

In a more sophisticatedexperiment, using electrorotation to control cell rotation rates, the possibility of free rotational Brownian motion superimposed upon a constant, smooth rotation, was excluded (Samuel and Berg, 1995).As in the earlier work, these results were consistent with about 400 randomly occurring events per revolution of the motor. When the experiment was repeated in a resurrection strain in which motors contained between one and four torque generators, the predicted number of steps was proportional to the number of generators,with about 50 per generator per revolution (Samuel and Berg, 1996). If these stochastic events correspond to actual physical steps, then each unit would take steps of approximately 3 nm around the perimeter of the C-ring. This compares with observed steps of 8 nm in kinesin and up to 20 nm in myosin.

4. MODELS OF THE FLAGELLAR MOTOR

A wide variety of theoretical models of the bacterial flagellar motor have been published. A review by Caplan and Kara-Ivanov (1993) describes many of these models in detail, as well as providing a thorough discussion of flagellar motor energetics in terms of non-equilibrium thermodynamics. A shorter but comprehensive summary of flagellar motor models may be found in Berg and Turner (1993). Rather than covering the same ground, we will attempt a broad classification of existing models to give an overview of the field, to facilitate comparisons and to illustrate similarities and differences between models that may not be immediately obvious. Some of the properties of flagellar motors are outlined in Table 1. 4.1. Classification of Existing Models

There are two levels to any thorough theoretical model of the bacterial flagellar motor. First, there is a physical concept describing structural elements of the motor and the processes they undergo that generate torque. This concept is then cast in mathematical form, usually via a kinetic description of internal states of the model, which allows qualitative and possibly quantitative predictions to be made. If these predictions are at odds with experimental evidence, then the model must be either modified or rejected. Table 2 divides existing flagellar motor models according to two categories at the level of the basic physical process. The first category is the structural or geometric motif that underlies the model - the path of protons through the motor and which elements move in the torque-generating cycle. Here there are three recurrent themes.

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THE BACTERIAL FLAGELLAR MOTOR

Table I

Measured characteristics of the flagellar motor.

Driving force

Proton or sodium electrochemical gradient

Manson et al. (1977). Glagolev and Skulachev (1978), Hirota and Imae (1983)

Number of protons per revolution

Approx. 1000

Meister et al. ( 1987)

Number of independent torque generators

Up to 8 ('?)

Blair and Berg (1988), Muramoto et a/. ( I 994)

Number of steps per revolution

Approx. 50 per torque generator ( -400)

Samuel and Berg (1995)

Swimming speed

<s to >200 p d s

Many observations of many species

Maximum rotation rate

300 Hz (Ap) 1700 Hz (AN4

Berg and Turner ( I 993), Magariyama et al. (1994)

Torque at stall

Approx 4 X 1O-I8Nm

Meister and Berg (1987)

Maximum power output

Approx.

Calculated from Meister and Berg (1987), Berg and Turner ( 1993)

(L\p)

Efficiency at stall (Ap)

so- 100%

Efficiency in swimming cell (Ap)

Approx. 5%

W

I , Protons interact simultaneously with rows of components on both the rotor and the stator. These rows are tilted with respect to one another, and protons flow into the cell by travelling at their point of intersection. Proton influx makes the rotor and stator slide relative to each other so that the intersection of the tilted rows follows the proton as it passes through the motor. 2. Protons are channelled on to the rotor from outside the cell. The rotor then moves, either under the effect of some force on the charged protons or simply due to thermal fluctuations. The protons are allowed to pass into the cytoplasm, completing the motor cycle, only after the rotor has moved a certain distance in the right direction. 3. Crossbridges form that bind the rotor to the stator, conformational changes coupled to proton translocation pull the rotor around relative to the stator and the cycle is completed by unbinding of the crossbridges. The first two types of model explicitly involve the well-defined structure of the flagellar motor and its placement in the cell envelope in the torque-

RICHARD M. BERRY AND JUDITH P. ARMITAGE

324 Table 2

Classification of published models of the flagellar motor mechanism Nature of the force between rotor and stator

Geometric motif

Electrostatic

Lluger (1 977, 1988-1), Kleutsche and Liruger (1990), Oosawa ( I 983, 1986)

Protons follow the intersection of tilted lines

Protons deposited on to rotor from extracellular medium and released into cytoplasm only after rotor has turned Crossbiidges bind rotor and stator, and conformational changes generate torque Other

Elastic deformation of proteins

Glagolev and Skulachev (1978), Mitchell (1984), Kobayasi (1988), Murata (1989), Blair and Berg ( 1990)

Berg et al. ( I 982), Berg and Khan (1983). Meister et al. (1989)

Berg and Anderson ( 1 973), Lluger (1988-11), Wagenknecht (1986) Fuhr and Hagendorn (1987) Adam ( 1 977) Elston and Oster (1997)

References in italics indicate papers that include a mathematical treatment of the model. n o separate models are included in the paper by Lauger (1988).

generating process. The third is based on the linear motors of eukaryotes, where single-motor molecules appear to be able to move along their filament substrates,essentially in free solution. Type 2 requires that protons bind to the rotor during the torque-generating cycle and it is worth noting here that mutagenesis of switch complex proteins has failed to identify possible sites for this binding (Zhou et al., 1998a). Figure 7 shows an example of each of the three types of model. The second category defined in Table 2 is the nature of the force between the rotor and stator. In the majority of models this force is either electrostatic or results from elastic deformation of protein components of the motor. Elasticforce models rely upon the formation of tight bonds between the stator and rotor at some point in the torque-generating cycle, while the long-range Coulomb interactions in electrostatic models require charges to be buried in the membrane or protein interior, where the dielectric constant is low. Any model must be consistent with known facts about the structure of the motor. Therefore, for example, the models of Fuhr and Hagendorn (which invokes Quincke rotation by electric fields in the plane of the membrane) and

325

THE BACTERIAL FLAGELLAR MOTOR

a)

f 9

b)

U

C)

0

F7

f=l

Figure 7 Three different types of model that have been proposed for the mechanism of operation of the bacterial motor. (a) Tilted lines of charge (Berry, 1993). Positively charged ions flowing through the stator attract lines of negative charges and/or repel lines of positive charges on the rotor. This attraction keeps the negative charge near the ion as it crosses the motor, which leads to rotation if the lines of rotor charge are tilted relative to the ion channel in the stator. (b) ‘Turnstile’ (Meister et al., 1989). Ions are deposited on to the rotor by channels that extend to the periplasm (top), and are removed by separate channels that extend into the cytoplasm (bottom). For an ion to cross the entire motor, it must be carried from one channel to the other by the rotation of the rotor. (c) Crossbridges and conformational change (Lauger, 1988). The stator undergoes a sequence of conformational changes driven by the transit of protons, leading to the following cycle: (1) it binds the rotor in the conformation marked by dashed lines; (2) a powerstroke to the conformation marked by solid lines pulls the rotor around; (3) it unbinds the rotor, and (4) it returns to the conformation marked by the dashed lines.

326

RICHARD M. BERRY AND JUDITH I? ARMITAGE

Adam (where the rotor is driven by streaming of the cytoplasmic membrane) seem unlikely, since neither has any explicit role for proton flux nor MotAB torque-generating units (Adam, 1977; Fuhr and Hagedorn, 1989). Other models where the M- and S-rings are the rotor and stator, respectively, are excluded by the discovery that the MS-ring is composed of a single protein, but the essential features of the torque-generating process in these models can be retained while the assignment of structural components is brought up to date (Lauger, 1977; Glagolev and Skulachev, 1978;Wagenknecht, 1986). For example, the model of Glagolev and Skulachev (1978) becomes that of Mitchell 1984, and Lauger’s early 1977 model is adjusted in later (1988 and 1990) incarnations to account for advances in our understanding of the structure of the motor (Mitchell, 1984; Lauger, 1988; Kleutsch and Lauger, 1990). In the majority of flagellar motor models, bidirectionality is not described explicitly. Suggested switching mechanisms involve either a change in the geometry of the motor following conformational changes in motor proteins, or changes in the nature of interactions between protons and the motor. In the latter case it is assumed that charge, rather than protonation itself, is the significant property that determines constraints upon motions of the rotor and stator. For example, protonation might give neutral sites (e.g. lysine or arginine residues) a positive charge in one directional mode, while loss of a proton gives other neutral sites (e.g. glutamate or aspartate residues) a negative charge in the other mode. An explicit version of such a switching mechanism is described in the model of Berry (1993). A plausible model must also predict correctly the measured relationships between Ap, proton flux, torque and speed in the flagellar motor. In order to test models at this level, a detailed theoretical treatment is necessary. Unfortunately, this is available only for a limited number of existing models (those indicated by italic type in Table 2). Most theoretical treatments have been based upon translating the physical model into a kinetic one. In a kinetic model, the continuum of possible physical states of the motor is divided into a discrete number of kinetic states. Dynamic processes are modelled as a set of allowed transitions between these states, governed by transition rates according to the Eyring theory (Glasstone ef al., 1941). The allowed transitions follow from the physical constraints that define the model and translate them into a kinetic cycle that couples rotation to the dissipation of chemical energy by proton flux. Transition rates depend upon both the chemical reactions linked to proton flux that power the motor and the work the motor has to do against external forces. Kinetic models have traditionally been described as either loose- or tight-coupled. The defining assumption of tight coupling is that the transit of a proton is necessarily accompanied by rotation of the rotor through a fixed angle and vice versa. Thus a fixed number of protons flow through the motor per revolution and the total flux of protons is directly proportional to rotation rate. The tight-coupling condition is applied arbitrarily and, at best, is

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a close approximation to actual physical constraints in the motor. Since flux is strictly proportional to speed, a tight-coupled analysis needs only to predict the interdependence of torque, speed and Ap. The normal procedure is to specify torque and Ap, and to calculate the rate at which the kinetic cycle of the motor is performed. The speed of the motor is equal to this rate multiplied by the (fixed) distance moved per cycle, under the assumption of tight coupling. In a loose-coupled analysis, no assumption is made about the number of protons per revolution. The coupling between rotation and flux, the essential function of the motor, emerges as a consequence of the sensitivity of internal states of the motor to both Ap and torque, rather than being assumed a priori. Thus each state has an internal energy which depends on the position of the rotor relative to the stator in a way specified by the particular model. The torque generated by each state is the gradient of this energy with respect to rotor/stator angle, while transition rates between states depend upon both the internal energies and Ap. For a given rotation rate, one can determine as a function of angle the probability of occupancy of each state, and thus separately the proton flux and torque generated. These are usually integrated over angle to give averaged torque and flux, although numerical simulation is also possible. Detailed tight-coupled treatments of two different models, those of Lauger and Berg, may be found in the literature (Lauger, 1977, 1988; Berg and Khan, 1983; Meister et al., 1989; Kleutsch and Lauger, 1990). Although the models are physically quite different, the kinetic treatments become very similar and, indeed, it can be shown that with certain sets of parameters the kinetic models become identical (Caplan and Kara-Ivanov, 1993). Loose-coupled treatments may be found for a number of models, many of which involve electrostatic torque generation. As in the case of tight-coupled models, the kinetic versions and therefore the predictions of different loose-coupled models can become very similar. The models of Berry and Oosawa both predict a dependence of proton flux upon speed that is consistent with the measurements of Meister et al., which are often taken as evidence for a tight-coupled mechanism (Oosawa and Masai, 1982; Oosawa and Hayashi, 1983; Meister et al., 1987; Berry, 1993).This is because Meister et al. measured the proton flux that is dependent upon rotation, not the total proton flux through the motor. The flux predicted by loose-coupled models can be split into one component that is approximately proportional to rotation rate, and another that is constant and equal to the proton leakage through a stalled motor. This second component would not be detected by the experiment of Meister et al. Furthermore, the model of Berry shows that this leakage flux can be very small or, in other words, that relatively tight coupling can emerge from a model that is in principle loosely coupled. On the other hand, some tight-coupled treatments allow the tight-coupling condition to break down under certain conditions (Kleutsch and Lauger, 1990). Thus we see that the distinction between tight and loose coupling is really a quantitative rather than a qualitative one in terms of the

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actual predicted behaviour, and should be thought of as referring to the analytical description of a model rather than the fundamental mechanism of the model itself. With the exception of the model of Elston and Oster (1997), all the models in Table 1 were published before the electrorotation experiments of Berg and Turner (1993) (see Fig. 6 ) . As a consequence, their parameters were all adjusted to predict the linear torque versus speed relationship reported by Lowe et al. (1987). It remains to be seen whether these models can be adjusted to predict the torque-speed curve of Fig. 6 and, if so, what are the implications of the necessary changes for the mechanism of the motor. In a highly simplified and purely kinetic tight-coupled model, the torque plateau of Fig. 6 and the continuity of torque through zero speed require that a single step simultaneously dissipates the free energy of the energizing protons and incorporates relative motion of the rotor and stator (Berry and Berg, 1999). This is a socalled ‘powerstroke’mechanism, as opposed to ‘thermal ratchet’ mechanisms, where rotor/stator motion is driven thermally and the energy of protons is fed into the motor cycle at some other point. In the model of Elston and Oster (where the kinetic treatment is replaced by calculations of the stochastic equations of motion of protons, stator particles and rotor), the torque-speed curve of Fig. 6 could not be reproduced exactly, although some variations of the physical model came closer than others.

5. SUMMARY

A great deal has been learned about the structure and mechanism of the bacterial flagellar motor, and we may be on the verge of understanding it at a molecular level. However, there is still much to learn. It will be important to improve the resolution of our picture of the motor structure. It is difficult to obtain structures at atomic resolution using X-ray crystallography owing to the transmembrane nature of many of the components and the size of the complex, and techniques involving site-directed mutagenesis or cryo-electron microscopy with image averaging may prove to be more informative. For the motor mechanism, a measurement of the torque-speed relationship at different values of protonmotive force (Ap) would be useful, as would any new information on the flux of ions through the motor. In these respects, comparison of H+- and Na+-drivenmotors may be informative, especially as the ability to manipulate genes encoding components of the latter improve. Perhaps the most promising direction of all would be to use new techniques such as optical tweezers to study motors that run on a single torque-generating unit, allowing the mechanism of the flagellar motor to be investigated at the singlemolecule level. As the structural and functional data accumulate, it should

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eventually be possible to understand in detail the physical and biochemical principles that underlie the working of this remarkable biological, rotary, electric motor. With the recent demonstration of a rotary mechanism in the proton-translocating FIFO-ATPase,the flagellar motor is no longer alone. It will be interesting to see if the F, part of the FIFO-ATPaseand the flagellar motor both work in the same way.

ACKNOWLEDGEMENTS

We are extremely grateful to Robert Macnab and David DeRosier for providing us with diagrams and unpublished electron micrographs, and David DeRosier, Elizabeth Sockett, Michio Homma and Howard Berg for unpublished data. RB thanks the Wellcome Trust for funding and JPA the BBSRC and Wellcome Trust.

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Author Index

Note - Page numbers in iralics indicate where a reference is given in full. Abee, T. 104, 110, 130.132 Abraham, J.P. 296, 329 Abshire, K.Z. 115, 136 Adachi, M. 64.86 Adam, G. 324,326,32Y Adesina, A.A. 8.40 Adler, J. 182, 214, 220, 238, 254, 255, 264, 277.279.282,283.284,286,288,294, 295, 301.313,330,331,333,334 Aganval, S.C. 8, 9, 12, 13. 15, 16, 18, 20, 21, 25, 26.27, 32, 38, 39,40,44 Agatzini, S. 77, YO Agosin, E. 61, 65, 79,82 Agron, P.G. 204,214 Aguera y Arcas. B. 183,214 Aiba, H. 183, 194, 21Y, 222 Aiba, S. 10, 3 I , 40 Aizawa, S. 183,'227 Aizawa, S.-I. 247,288,296,299,300, 301, 306, 308,309.3 1 I , 3 16,3 19, 320,329,332. 333,334,336 Aizenman, E. 119, 120,126 Akamatsu, Y. 54.55, 61.62.63, 64,65, 79,X6, 90 Akkermans, A.D. 106,129 Alam, M. 257,260,267,279,285 Albano, P.A. 18. 19.45 Albertson, N. 115,131 Albertson, N.H. 107, 126 Albin, R. 140,214 Aldsworth, T.G. 108, 119, 123, 126 Alex, L.A. 143, 145, 195, 197,205,214,215 Alger, J.R. 254,287 Allen, A. 275,282 Allen, E.B. 59.70, 79.81 Allen, L.A. 113, 126 Allen, M.F. 59, 70, 79.81. 85 Alley, M.R.K. 25 I , 277 Allison, C. 275,277 Alon, U. 183,214 Aloni, H. 254,280,310, 316,331 Alonso, S. 194,226

Alonson,A. 10,31,43 AI-Qudah, A.A. 110, 126 al-Suwaidi, Z. 108,136 Altendorf, K. 146, 183,212,219,226,227 Altwegg, M. 101,135 Alvarez, A.M. 104, 134 Amako, K. 98, 136 Amann, R. 98, 109,126,132,133,135 Amann, R.I. 100, 101, 104, 107, 126 Amemura, M. 145,201,214,220,221 Ames, P. 244,273,277,281 Aminhanjani, S. 108, 126 Amrhein, C. 71, 79 Anagnostakis, S.L. 54.64.84 Ander, P. 55,84 Andersen, J.B. 100, 108, 109,127, 128, 133 Anderson, B.M. 1 1,42 Anderson, B.N. 3,5, 8,9, 15, 19, 20, 26, 32, 36,38,43 Anderson, R.A. 294,295,324,330 Anderson, T. 294,332 Anderson, T.J. 69,82 Andon, N.L. 116,133 Angles, M.L. 100,134 Anthamatten, D. 145, 214 Antonini, E. 33.40 Appleby, J.L. 143, 194,214 Arana, I. 105, 108, 113, 127 Archibald, A.R. 115, 128 Arico, B. 146, 194,214 Arlat, M. 308,336 Armentrout, V.N 54, 79 Armiger, W.B. 18, 19.45 Armitage, J.P. 144, 218,227, 237, 238, 244, 245,250.25 1,252,254,257,260,263, 264,266,268,277,281,282,285,286, 287,288,293,294, 296, 299, 300, 313, 314,315,329,330,331,332 Armstrong, G.D. 274,287 Amott, H.J. 56, 57, 58, 79.88, 91 h e r , H.E. 72, 79 Arthur, M. 144,201,215

340 Artz, S. 145,221 Asai, Y. 305,329 Asakura, S. 298,329,332 Asato, L.M. 272,286 Asdaso. C. 88 Asea, P.E.A. 69, 79 Ashby, A.M. 273,285 Asher, 0. 3 10.3 16,331 Astwood, P.M. 140, 146,224 Atkey, P.T. 54, 55, 56, 61. 63, 82 Atkinson, M.R. 182, 194. 197,204,215,222 Atsumi, T. 270, 277, 296, 305, 329 Attwell, R.W. 96, 103, 136 Auclair, J.C. 78, YO Auling. G. 67,84, 90 Aust, S.D. 61.64.84.85, YO Ausube1,F.M. 140, 145, 146. 182.222.224 Awad, M.M. 146.221 Azcon, R. 76,91 Baca, M.T. 76, 91 Bachofen, R. 72, 76,77, 79,80, 85, 270, 282 Backman. K. 194,216 Baham, J.E. 71,84 Bahassi, E.M. 120, 128 Bai, Y. 266, 282 Bailey, A.M. 146. 226 Bainton, N.J. 121, 136 Baldi. E 76. 88 Balebona, M.C. 274,278 Ball, C.B. 182,220 Balmforth, A.J. 54. 79 Banks, M.K. 72.80 Barak, R. 246,263,278 Barbara, G.M. 269,278 Barbato, A. 70.85 Barber, D.A. 72.83 Barber, L.Z. 121, 127 Barberis, P. 308,336 Barcina, I. 105, 108, 113, 127 Barclay, R. 101,127 Barer. M.R. 93,94,95.96,98,99, 100, 102, 104,108, 109, 110, 116, 118.127, 129, 130,131,133,136 Barletta, R.G. 108. 130 Barlow, S.B. 59, 79 Barnett, J.A. 6, 7, 9. 14, 21.44 Ban, D.B. 64, YO Barn, D.P. 61, 84 Barrow, P.A. 121,127,137 Baskaran, S. 70.7 I , 80 Basolo. F. 50, 80 Bass, R.B. 232,240,241,280 Bassler, B.L. 122, 127, 144,215 Basu, S.K. 8.9, 12, 13, 15, 16, 17, 18,20,21, 25,26,27, 30, 32, 38, 39,40,44 Bateman, D.F. 54.55.87

AUTHOR INDEX Battat, E. 66, 80 Bauer, C.E. 144,219,266,282.286 Baulard, A. 108,131 Baumgartner, J.B. 244,284 Baumgartner, J.W. 251,252,280 Bayer, K. 19,42 Bayles, K.W. 205,215 Bazylinski, D.A. 269,280 Beatson, P.J. 236,278,294, 329 Becvarova, H. 12, 13, 17.22.40 Beer,V. 101, 127 Beier, D. 212, 215 Bekes. P. 65.82 Belas, R. 275.284 Bell, A.W. 144,227 Beltrametti, F. 194, 215 Bender, C.L. 146,226 Bengrine,A. 194,219 Bennett, A.R. 54.80 Bennetzen, J.L. 194,217 Benov, L. 276,278 Bercovier, H. 104, 127, 133 Bercovitz, A. 66,80 Berg, H.C. 183,224,232,236,238,246,252, 262,278,279,280.283,286,288,292, 294.295,298,300,303,304,306,310, 31 I , 312,314. 315, 316,317, 318, 319, 320,321 322,323,324,325, 327,328, 330,331, 332,333, 334,335,336 Berger, D.K. 145,220 Bergeron, H. 212,220 Bergman, K. 273,281 Bernd, K.K. 195, 197,218 Berry D.R. 19.40 Berry, R.M. 304.3 13.3 19,320,325,326,327, 328,330 Berthelin. J. 50, 69, 72.80.86. 88 Bestetti, G. 194, 215 Bettenbrock, K. 254,283 Beumer, R.R. 110. 130 Bhem, C.A. 54,55,86 Bi, E. 105, 127 Bibikov, S.I. 267, 278 Biemann, H.-€? 242,243,278,279,288 Bihari, V. 8, 12, 15, 27.44 Billings. S. 306,307,333,335,337 Bilwes, A.M. 195, 197,205,215 Binnerup, S.J. 105, 110, 127, 130 Biran, R. 267,278 Birck, C. 246, 288 Bjorn, S.P. 108, 127 Blair, B.F. 235, 289 Blair, D.F. 235, 236, 247, 278,284, 300, 303, 304.306, 307,321, 323,324,330,333, 335, 336,337 Blakemore, R.P. 269,280 Blat, Y. 247, 278

AUTHOR INDEX Blattner, F.R. 119, 127, 182, 197,215 Blazquez, F. 72.74.80.83 B1eecker.A.B. 141,216 Bloch, C.A. 119,127, 182, 197,215 Block, S.M. 232,246,278,286,292,298, 300,304,310,316,321,330,331,332, 335 Bloemendaal, C.J. 146,216 Bloom, B.R. 108,130 Bloomfeld, S.F. 99, 102, 118, 127, 129 Bockian, R. 98, 116, 133 Boe, L. 107, I35 Bogomolni. R.A. 264,278 Bogosian. G. 122.127 Boiteux, A. 7,40 Bojinova, D. 69, 76, 80 Bolan, N.S. 70,71,80 Bonanzinga, A. 270,284 Bonnaud, P. 7 I , 88 Boos, W. 144,216 Booth, I.R. 99, 102, 118,127, I29 Bootle, W.C. 254,257,282 Bordas, M.A. 274,278 Borkovich, K.A. 145,205,214,215,244, 245, 252,278,279,287 Bormans, A.F. 240,242,280 Borrego, J.J. 274, 278 Bosshard, P.P. 76,77,80,85 Bost, S. 101, 127 Botsford. J.L. 1 18, I27 Bott, M. 145,204,215 Bottger. E.C. 101.127, 129 Botton, B. 50.68, 7 I , 81, 88 Boucher, C. 308,336 Boucher, J.C. 146,227 Boudrant, J. 19,41 Bourne, N.A. 245.25 1,281 Bourret, R.B. 143, 183, 194,214,218,245, 252,27Y, 287 Boutibonnes, P. 116, 133 Boutton, T.W. 73, 89 Bouwerhertzberger, S. 113, 133 Bovill, R.A. 104.127 Bowen, W.R. 10.40 Bowler, C. 141,222 B0yer.P.D. 140, 143,215,222,296,330 Brandl, H. 76,17,80,85 Brandts, J.F. 242, 283 Brantley, S.L. 71.90 Braun, B. 141,224 Braun, T.F. 306,337 Braux. A S . 104, 128 Bray, D. 253,279 Brayton, P. 98, 128 Brayton, P.R. 96, 105, 128 Breedveld, G.J. 7, 8, 10.45 Brenner, D.J. 100, 136

341 Brewer, D.G. 113,128,12Y Brian, P. 144,215 Bridge, T.A.M. 49.89 Briggs, K.G. 57,90 Brinckman, F.E. 76.88 Bringer-Meyer, S. 4, 12.40 Britschgi, T.B. 99, I30 Brombacher, C. 76,85 Brook, I. 123,128 Brooks, J.D. 67,81 Brooun, A. 257,267,279 Brosch, R. I19,128,206,216 Brousseau, R. 212,220 Brown, C. 19.40 Brown, J.M. 215 Brown, M.S. 182,215 Brown, S.W. 10,31, 40 Bruchet, G. 57,86 Bruening, G. 10.40 Brunskill, E.W. 205,215 Bryant, A.E. 146,221 Brynhildsen, L. 72.80 Buchert, J. 55.89 Budrene, E.O. 262,279,288 Buechner, M. 255,279,283,313,330 Bult, C.J. 182, 215 Burbulys, D. 145, 194, 215,223 Burge, W.D. 96,130 Burgstaller, W. 49, 59.68, 69, 76, 77, 78, 80, 83,88,89,90 Burr, D.H. 275,288 Burris, R.H. 145,227 Buss, J.E. 140,215 Busta, F.F. 113, 134 Butler, L.G. 143,222 Butler, S.L. 232,240, 241.280 Butor, C. 109, 132 Button, D.K. 100, 109,128,135 Bycroft, B.W. 121,136 Byrd, J.J. 98, 128 Cairney, J.W.G. 57,58,80 Cajuste, B. 69, 70, 80 Cajuste, L.J. 69.70, 80 Calara, F. 260,283 CdkOtt, P H. 118, 128 Caldwell, B.A. 71.84 Caldwell, D.E. 109,131, 271,279 Calladine. C.R. 298,330 Callahan, F.E. 64.80 Callieri, D.A. 68, 88 Calvert, T.J. 118,128 Calvin, M. 50, 87 Camarena, L. 183,214 Campbell, E.A. 144,206,216 Cannon, J.P. 70,81 Cantwell, B. 212,223

342 Caplan, S.R. 3 10,3 16, 322,324.325, 327,330, 331,334,336 Cardillo. R. 4.40 Carlsen, H.N. 23,40 Carlson, L.C. 101, 128 Carpenter, P.B. 254,281 Carrea, G. 33.40 Carter, J. 104, 131 Casey, G.P. 3 1.40 Casjens, S. 144,217 Castellano, C. 14,42 Castello, P. 308,336 CdStk, A. 254, 287 Catala, P. 104, 132 Cavicchioli, R. 205,216 Cejka, A. 18.40 Chamberland, H. 58.88 Chamberlin, M.J. 256, 259, 285 Champness, W.C. 144,215 Chan, J. 108, 130 Chance, B. 268,282 Chang, C. 141, 145, 194,216,218 Chang, H.R. 101,127 Chang, J.C. 52,81 Charles, T.C. 212, 216 Charlton, T. 122, 135 Charon, N.W. 236,279. 281 Chen, T. 141. 144, 182, 195,205,225 Chen,Y. 58.81, 106,134 Chen,Y.M. 194.216 Cheng, Q. 144,206,216 Chervitz, S.A. 232, 240,241,243,279, 280 Chet, I. 54, 64. 84. 85 Chhahra, S.R. 121,136 Chiang, R.C. 205,216 Chilcott. G.S. 308,330 Chilvers, G.A. 54, 55, 86 Chin, P.K.F. 71.81 Chinardet, N. 246,288 Chippaux, M. 194.219 Chippendale, G. 275,284 Chisholm, J.E. 73,81 Chiu, J. 194,217 Choe,J. 67.81 Choudhary, M. 194,222 Choudhury, S. 77,90 Chow, Y.S.8,40 Christensen, A.B. 275,281 Christensen, B. 275,281 Christensen, B.B. 100, 109, 128, 133 Chua, N.H. 141,219, 222 Cimerman, A. 67.85 Clack, T. 143,216 C1ark.A.J. 313,331 Clark, D.S. 67.81 Clark, K.L. 194,216 Clarke, R.G. 104,128

AUTHOR INDEX Clarke-Sturman, A.J. 115, I28 Clausen, C.A. 62,64,84 Clayton, R.A. 144, 182, 197,204,220 Clayton, R.K. 234,279 Clipson, N.J.W. 57,58, 80 Clough, S.J. 212,216 Cohen, S.N. 145,204,219 Cohen. Y. 269,288 Cohen-Bazire, G. 301,331 Cole, S.P. 145, 194,223 Cole, S.T. 119. 128, 206.216 Coleman, N. 275,277 Collins, L.A. 104, 108, 128 Colombo, C. 194,215 Colonna-Romano, S. 145,223 Colwell, R.R. 96.98, 100, 103, 105, 110, 128, 130,133,134,135,136 Comeau, D. 183.21 7 Comerford, N.B. 70,71,81,83 Con1ey.M.P. 312,315,317,321,324,330 Conn, E.E. 10,40 Connolly, J.H. 58,59,81 Connor, M.A. 31,41 Constantinou, C. 254,280 Coomaraswamy, G. 206,218 Cooper, J.E. 273,286 Corbell, N. 144, 194,216 Cormier, M. 104,128 Cornelis, G.R. 276,279 Coschigano, P.W. 194,216 Costerton, J.W. 109, 123,129,131,271,279 Coughlin, R.W. 9, 12, 14, 16, 17, 20, 21, 24, 25, 28,29,30, 31, 32,38,42 Coulton, J.W. 303,331 Courvalin, P. 144,201,215,217 Couturier, M. 120, 128 Covarruhias, A.A. 145,221 Cowl, J.S. 141, 145, 216 Coy, M.A. 73.89 Coyle, M.B. 101. 128 Crabb, D.W. 141,218,223 Cragoe, E.J. Jr. 305,323,334 Crane, B.R. 195, 197,205,215 Cremonesi, P. 33.40 Crichton, R.R. 69.81 Crielaard, W. 264,281 Cromack, K. 56.87 Cromack, K. Jr. 57.70.71, 75,76,81, 84 Crout. D.H.G. 5,40,42 Crovello, C.S. 143,216 Cuevas, B.G. 69,70,80 Culik, K. 3, 14, 17, 19.28.41 Cullen, P.J. 145, 21 7 Curnrnings, A.D. 145,227 Cummings, P.T. 238,280 Cunningham, J.E. 69,81 Curry, A. 98,131

AUTHOR INDEX Cushion, M.T. 104, I31 Dahl, M.K. 144,216 Dahlquist, F.W. 205, 217, 227, 247, 284 Dalton, H. 5,40,42 Dalton, H.M. 100,134 Dam, R. 64.83 Daniel, G. 58. 81 Daniel, J.M. 146, 226 Danielson, M.A. 232,240,241,242, 243,279, 280 Dapice, M. 296,30 I , 303.3 14.3 19,332,333 Dasari, G. 31.41 Datta, A. 65, 87 Dave, S.R. 76,81 Davey, H.M. 104, 108, 109, 117,129,131 Davies, D.G. 123,129,271,279 Dawes, E.A. 117, 1 18, 129 Dawson, M.W. 67,81 Dean, G. 5.42 Dean. G.E. 301,303,329,335 Debarbouille, M. 194,220 De Bary, A. 50,56,58,81 Decamp, 0. 104,129 Dedonder, R. 194,205,220,222 Defais, M. 112, 129 Defez, R. 145,223 de Geus, P. 140,225 De Giudici, P. 69,80 Degn, H. 23.40 De Jong, D.M. 236,285 Dekkers, L.C. 146,216 De la Torre, M.A. 72.81 Delcour,A.H. 255,279,283,313,330 Delong, E.F. 99, 106, 107, 129,130 Deloughery, C. 197,206,212,224 DeLuca, M. 140, 143,215 DeMoss, J.A. 205,226 Denevre, 0. 50,68,81 Denny, T.P. 212, 216 Denyer, S.P. 108. 135 de Nys, R. 122,135 DePamphilis, M.L. 294, 301,331 Deppisch, H. 212,215 Deretic, D. 108, 129 Deretic, V. 108,129, 146, 227 DeRosier, D. 298,334 DeRosier, D.J. 298,299,300,307,331, 332, 335,336 Derrick, S. 19,20,21,41 De-Souza, M.P. 270,289 Deutscher, J. 143, 224 deVos, W.M. 120, 121,131 Devries, E.J. 100, 135 de Weger, L.A. 146,216 Dewers, T.A. 71. 83 Dexheimer, J. 58, 86

343 Dhandayuthapani, S. 108,129 Dhawan, S. 12, 13, 15,29,41 Dhir, V.K. 108, 135 D’hooghe. I. 145,216 Diaper, J.P. 104, 129 Diaz, E. 194,226 Dickrnan, M.B. 64.83 Di Lenna, P. 64,65,87 Dillon, S . 270, 284 Dimroth, P. 204,215 Dingwall, A. 235,279,298,331 Dispensa, M. 257,281 Dissara, Y. 13, 19, 26,41 Ditta, G.S. 183, 221 Ditty, J.L. 144,217, 259, 279 Dixon-Hardy, J.E. 68,77,81 Djordjevic, S. 251,279 Dohrogosz, W.J. 112, 134 Dodd, C.E. 99, 102, 118,127 Dodd, C.E.R. 99, 108, 118, 119, 123,126,129 Dodge, C.J. 49, 52.53, 72,78, 81.83 Doetsch, R.N. 272,282,285 Doi, R.H. 10,40 Domaille, P.J. 247, 284 Donaldson, J. 96.98, 133 Dons, L. 144,217 Doucette-Stamm, L.A. 197,206,212,224 Dougan, G. 121,137 Douglas, J. 72, 82 Douglas, N.G. 23, 44 Drever, J.I. 69.71, 76.82, 90 Drever, J.L. 71.87 Dreyfus, G. 308,331 Driessen, A.J.M. 257,282 Drlica, K. 105, 129 Drobniewski, F. 108,136 Dronawat, S.N. 66,82 Dube, S. 143,224 Duhnau, D. 144,227 Duhnau, E. 144,227 Dudley, L.M. 70,81,85 Duffy, G. 104,129 Duffy, K.J. 237,279 Dukan, S. 113,129 Dumont, J.L. 56,74,75,76,91 Dunford, H.B. 64.85 Dunlap, P.V. 272,281 Dunn, G.A. 237,279 Dunphy, G. 122,129 Durand, G. 26,42 Dusenbery, D.B. 236,279 Dutly, F. 101, 135 Dutta, R. 183, 195, 201, 217,225 Dutton, M.V. 53,54,55,56,61,63,64, 65,82 Eaton, J.W. 123, 132 Eaton, K.A. 275,280

344 Eberl, L. 109.128.275,281 Ebner, K.E. 140, 143.215 Ebner, M.J. 257.288 Eckhardt, F.E.W. 72,73,84 Eckhart, W. 140,217 Edwards, C. 104,129 Edwards, H.G.M. 73.82 Edwards, K.A.E. 73,82 Eelderink, I. 113, 133 Egea, L. 105, 113,127 Egger, L.A. 201.217 Ehrenberg, G.S. 233,280 Ehrlich, G.D. 106, 134 Eisenbach, M. 183,227,246, 247,254,263, 278,280,284,286,288,296,308,310, 316,331,334,336 Ekweozor, C.C. 98,129 El-Kalak, H. 66.86 Elkest, S.E. 112,129 Ellaiah, P. 13, 14, 15, 16. 18, 23,33,41,43 Ellefson. D.D. 195,225 Elmerich, C. 145,219 El-Sayed,A.H. 9, 12, 14, 16, 17,20,21,24,25, 28,29,30,3 I , 32,38,42 Elston, T.C. 328,331 Ely, B. 235,279,298.331 el-Zaatari, F.A. 106,129 Emiliani, E. 65.82 Emody, L. 98, I35 Engasser, J.M. 19,41 Engelberg-Kulka, H. 119, 120, 126 Engelbrecht, S. 296,335 Engelmann, T.W. 233.280 Engstrand, L. 106, 129 Engstrom, L. 143,226 Engstrom, P. 238,281 En0ki.A. 61,84 Epstein, W. 146. 226 Errera, M. 112,129 Escalante, R. 194, 226 Espejo. E. 61.65. 79.82 Estaquier, J. 108, 131 Evans, A. 69.82 Evans, C.S. 53,54,55,56.61,63,64.65,82 Evans, L.J. 71.87 Evans, M.C.W. 266,277,313,315,329 Evers, S. 201,217 Every, E.J. 23.44 Ewart, D.K. 76.82 Eyring, H. 326,331

AUTHOR INDEX

Farwell. D.W. 73,82 Fauquet, P. 112.129 Feinberg, S.L. 260,282 Feldmann, M. 7 1.82 Felske, A. 106, 129 Feng, J. 182, 194,204.222 Feng, P. 110,135 Feng. X. 25 1,252,280 Ferguson, Y 108,129 Fernandez-Astorga,A. 108,127 Fernando, M.E. 264,280 Ferrar, P.H.65,82 Ferrari, E. 194,218 Fett, W.F. 146, 194,221 Field, K.G. 99, 130 Figueroa, C. 59, 79 Finlay, R.D. 72.85 Firtel, R.A. 215 Fisher, E.H. 140.220 Fisher, S.L. 201,217 Flardh, K. I15.131 Fleming, G.R. 72.80 Fletcher, H.M. 267,286 Flikweert, M.T. 6,41,44 Flores, M. 73,84 Flowers, R.S. 113, 129, 132 Fluit, A.C. 212,226 Ford, B.J. 233,280 Ford, R.M. 237,238,279,280,300,329 Forrer, R. 101,135 Forst, S. 146, 183.217, 225 Forster, S. 269,282 Fossing, H. 269.282 Foster, J.W. 56.82 Foster-Hartnett, D. 145.217 Fox, T.R. 70,83 Franceschi. V.R. 54.58.83 Franch, T. 119, 120, 130 Francis, A.J. 49,52.53,72.78,81,83 Francis, N.R. 235,280,299,307,331,335 Franco, I. 76.91 Frankel, G. 121, 137 Frankel, R.B.269,280 Franklin, S.P. 71,83 Franks, D.G. 294,336 Franz. A. 77.78.83 Franzblau, S.G. 104, 108,128 Fraser, C.M. 144, 182,217 Frederick, R.D. 194,217 Fredricks, D.N. 102.130 Freeman, A. 26.44 Fahmer. K.A. 183,224,292,298,300,330,331 Fridoich, I. 276, 278 Falke, J.J. 232,240.241.242, 243, 271, 279, Friedrich. M.J. 183,217 280,283 Frostl, J.M. 270,280,285 Falkow, S. 101,134, 146, 194,214 Fryar, A. 58. 79 Fandrich, B.L. 268,282 Frymier, P.D. 238,280 Fane, A.G. 5,23,30,42 Fu, R. 257,267.280

AUTHOR INDEX Fuganti. C. 5.41 Fuhr, G. 326,331 Fuhrer, D.K. 144,217 Fujino, I. 104, 130 Fujita, H. 299, 306, 332,336 Fujita, M. 68.83, 85 Fujitaki, J.M. 143, 217 Fujiwara, T. 146,194,219 Fukui, M. 269,288 Fuller, D. 183, 224 Funayama, S. 145,221 Fung, D.C. 304,310,314,315,317,331 Fung, G. 143,217 Fuqua, C. 120,130 Fuqua, W.C. 271,280 Furie. B. 143,216 Furie, B.C. 143, 216 Futamata, H. 273,286 Gabbert, K.K. 145,217 Gadd. G.M. 49.54, 55.57, 58.59, 60, 61, 68, 69,70,76,77.78,81,83,85, 87, 89, 90, 91 Gallacher, I.M. 65, 82 Galli, E. 194,215 Garbaye, J. 50.68.81 Garcia, I. 10, 31.43 Garcia, J.L. 194,226 Garcia, M.T. 72, 81 Garcia-Valles, M. 72, 74.80, 83 Gardina, P.J. 240, 242.280 Gardner, W.K. 72,83 Gargus, J.J. 295,333 Garrity, L.F. 259,280,281 Gana, A.G. 303,305,331 Gasc, A.M. 146,217 Gauden. D.E. 238,266,268,281,285,313, 331 Gaustad, P. 206,213,218 Gegner, J.A. 205,217 Geiger, 1.P: 58.88 Genin, S. 308,336 Gerard, J. 58.86 Gerdes, K. 119, 120,130,131, 134 Gerisch. G. 145, 194,224 German, S. 308.336 Gest, H. 266,282,286 Gharieb, M.M. 49,54,55,57,58,61,68,69, 70.83.87 Ghiorse, W.C. 69.83 Ghosh, S. 143,220 Ghoul, M. 19.41 Giebel, I. 263, 278 Giesler, R. 72, 85 Gillow, J.B. 49,52,53,72,78,83 Giovannoni. S.J. 99, 104, 130, 132 Girons, IS. 144,226

345 Givskov, M. 100, 108, 109,127,128, 133,275, 281 Glagolev, A.N. 295,323,326,331 Glaser, G. 119, 120,126 Glasstone, S. 326,331 Glover, L.A. 108, 126, 129 Gluch, M. 294,333 Gober, A.E. 123,128 Gocayne. J.D. 182,217 Godoy,G. 64,83 Gold, M.M. 64,85 Goldberg, I. 66,80 Goldenberger,D. 101,135 Goldrick, D. 146,227 Goldstein, S.F. 236,281 Goma, G. 31.43 Gomez-Alarcon, G. 72,73,81,84 Gomez-Duarte,O.G.274,286 Goodman, A.E. 100,134 Goodman, B.A. 69,85 Goodwin, D.C. 61.84 Gony, M.C. 106,134 Gottesman, S. 145,225 Gottfert, M. 145,217 Gottschal, J.C. 100, 101, 106, 135 Gotz, R. 294,331 Gough, C. 308,336 Goy, M.F. 238,282 Graf, F. 7 1.82 Graf, J. 212,281 Graham, D.R. 205.21 7 Graham, D.Y. 106,129 Grancharov, I. 69.76.80 Grant, V.A. 104,130 Grasselli, P. 5, 41 Graustein, W.C. 57,70,71,75, 76,81,84 Graves, L.B. Jr. 54, 79 Gray, K.M. 120,130 Grebe, T.W. 182,217,294,331 Greck, M. 144,217 Green, D.E. 4,41 Green, F. 61,62,63,64,84 Greenberg, E.P. 120, 122, 123,127, 129, 130, 236,271,272,279,280,286 Greenfield, P.F. 14, 18, 19.41 Greengard, P. 140,220 Greenwood, M. 96.98.133 Grewal 109,136 Gribbon. L.T. 98,127 Griffiths, R.P. 71, 84 Grimes, D.J. 96, 103,135,136 Grimm,A.C. 144,217,257,259,279.281 Grishanin, R.N. 144,218,251,266,268,281, 313,331 Grob, P. 145,217 Groisman, E.A. 146,224 Gross, N.H. 4,41

346 Gross, R. 146, 194,212,214,215 Grossinan, A.D. 145, 183, 194,220 Grossman, A.R. 146,219 Groudev, S.N.76,84 Grover, T.A. 61.64, 84.85, YO Grunberg, H. 263,284,294,333 Gruzina, T.G. 68, 77,81 Gueguen, M. 116,133 Guenzi, E. 146,217 Gueny, P. 275,288 Guillet, J.G. 109, 132 Gulash, M. 273,281 Gultyaev, A.P. 119, 120, 130 Gunsalus, R.P. 205,216 Gunz, A. 101,135’ Gupta, K.G. 12, 13, 15.29.41

AUTHOR INDEX Hart, K. 72.86 Hartley, N. 141, 145,216 Hartzell, P.L. 236,260,281,283 Harvey, L. 67,89 Harwood, C.R. 93,94,95,96,98,99, 102, 104, 108, 110, 115. 116, 118. 127, 128,131. 133 Harwood, C.S. 144,217,257,259,279,281 Hatfull, G.F. 108, 130, 135 Hattori, T. 54,55,61,62,63,64,65,86,90 Havarstein, L.S. 144,206,213, 218,223 Havir, E.A. 54,64,84 Hawes, J.W. 141,218,223 Hawkins, M.A. 240,242,280 Hayashi, S . 327,334 Hazelbauer, G.L. 238, 243,244,251,252,260, 280,281 282.284.285 Hazeleger, W.C. I10,130 Healing, T.D. 96, 98. 133 Heefner, D.L. 13, 17,27,28,30,31,44 Helinski, D.R. 183, 204,214,221 Hellingwerf, K.J. 264, 281, 287 Hendlin, D. 9, 12, 15, 16, 17,22,23,44 Hengge-Aronis, R. 117, 130 Henis, Y. 64, 85 Hennecke, H. 145,214,217 Henner, D. 194,205,222 Henner, D.J. 194,218 Henriksson, G. 55.84 Herrick, B.A. 72,80 Herrington, D. 98,128 Hess, B. 7,40 Hess, J.F. 140, 141, 183,218,244,245, 252, 278,281,287 Hesse, J.E. 146,226 Highley, T.L. 61, 62, 63.64, 84 Higuchi, H. 321,333 Higuchi, T. 64, 79 Hindal, D.F. 54, 80 Hirano, T. 6 I , 84 Hironaka, J. 9, 17, 22.43 Hirota, N. 296, 3 14, 323, 332 Hirsch, P. 72,73,84 Hirschel, B. 101, 127 Hite, F. 116, 133 Hobot, J.A. 115,128 Hobson, N.S. 110,130 Hoch, J.A. 143, 145, 183, 194, 195,218,218, 223.225.226227 Hochli, M. 101, 135 Hockertz. S. 67.84 Hodgkinson, A. 50,53,84 Hoff. K.A. 104,130 Hoff, W.D. 264,281,287 Hofnung, M. 1 12, 134 Hogg, R.W. 295,333 Hohmann, S. 4, 6, 7.9.41 ~

Haardt, M. 274,287 Habicht, K. 269,288 Hachler, H. 182.218 Hacker, J. 98, 135 Hackett, J. 140, 225 Hackney, C.R. 113,130 Hagedorn, R. 326.331 Hageman, R.V. 13, 17,27,28,30, 31.44 Hahn, M. 76,84 Hainfeld, J. 299, 335 Hajash, A. 7 I , 83 Hakenbeck, R. I46,211,2l3,217,218 Hakoshima, T. 194, 195,205,219 Halls, C. 49, 61, 89 Hamasaki. N. 143,224 Harnblin. P.A. 144,218, 227, 245, 251, 254, 257,281,282 Hamlet, W.M. SO, 84 Hammel, I. 298,336 Han, B. 212,218 Han, D.P. 316,333 Hanc, 0. 12, 13, 17,22,40 Hancock, I.C. 115,128 Hancock, J.G. 64.88 Handa,A.K. 194,217 Hanley, T.R. 66.82 Hanlon, D.W. 254,281 Hanselmann. K.W. 72, 79,270,282 Hansen, G.A. 101,130 Happold, F.C. 4.41 Harberd. N.P. 141, 145,216 Harder, W. 100,135 Harding, G.P. 267,286 Harman, J.G. 118, 127 Harold, EM. 295,323,334 Harris, R.A. 141,218,223 Harris, W.G. 71.81 Harris-Haller, L.W. 303. 305, 331 Harrison, D.E.F. 7. 10, 15,31,40,41 Harrison, D.M. 250,252,257,281,288,314,332

AUTHOR INDEX Hoigne, J. 62, 92 Hojberg, 0. 110,130 Holmstrorn, K. 107,132,135 Holuigue, L. 140,226 Homma, M. 254,285,299,300,305,306,308, 329,332,333,336 Hong, J.S. 146, 227 Horitsu, H. 67.81 Horkawa, H. 144.21Y Home, R.A. 61,84 Homer, H.T. 56.57.84 Horowitz, P.M. 108,129 Hosoya, S. 62.87 Hotani, H. 298, 3 I I , 3 15. 319, 320, 332, 336 Hoyt, J.C. 143,224 Hrabak, E.M. 194,218 Hsing, W. 195, 197,218 Hua, J. 145,218 Huang, J.-S. 57.89 Huang, P.M. 69,90 Huang, W.L.71.84 Huang, W.M. 144,217 Hubner, G. 7.41 Huehner, V.D. 143,218 Huettel, M. 269,282 Hughes, C. 275,277 Hughes, K.T. 308,330 Hughes, M.N. 76.82 Hultquist, D.E. 140, 143, 215 Humayun, I. 301,303,332 Humphrey, T.J. 113, 130 Hunt, A. 109,136 Hunter, J.R. 117, 134 Hunter, T. 140, 217 Huq,A. 96.98, 105, 110,128, 130 Hurley. T.D.141, 218 Hussong, D. 96,130 Hutchinson, D.W. 5,40,42 Hutchinson, M.A. 140,217 Hutterman. A. 54.84 Hutzler, P. 109, 132 Hyde, S.M. 61,62,85 Iaccarino, M. 145,223 Ihanez, M. 104,134 brahim, P. 104,130 Iglewski, B.H. 121, 123,129, 133,271,279 Igo, M.M. 183,219 Iino, T. 235,282,299,300,306,308,332, 335, 336 Ikeda, T. 62,87 Ikenaka, K. 104,130 Ikura, M. 195, 201,225 Illmer. P. 70, 85 Imae, Y. 236,243.254,270,277,282,283, 284,285,288,296,305, 3 1 1.3 12,314, 323,329,332,333,334

347 Ingledew, W.M. 3 1,40 Ingmer, H. 145,204,219 Inokucbi, H. 264,288 Inoue, N. 106, 137 Inouye, M. 140, 146, 183, 195, 197,201,217, 222,223,225,227 Iochi, H. 31 1, 319, 320,336 Iriberri, J. 105, 113, 127 Irikura, V.M. 305, 306,308,332,335,336 Ishiguro, K. 104, 134 Ishihara, A. 3 10,3 16,332 Ishima, R. 195,201,225 Island, M.D. 146,219 Itaya, M. 1 1 1, 130 Ito, K. 67, 81 Iuchi, S. 146. 194,219 Iwahori, K. 68,83,85 Iwasaki, Y. 104, 130 Jackson, J.B. 3 13,331 Jacobs, D. 116,136 Jacobs, M.H.J. 257,282 Jacobs, W.R.108,130,135 Jacobsen, C.N. 104, I31 Jacobson, G.R.253,285 Jahreis, K. 254,283 Jakobsen, M. 104, I31 James, D.M. 144,205,221 James, G.A. 109,131 James, P. 10, 12,42 Janse, J.D. 110, 130 Janssen, D.W. 113,134 Janssen, W.M.T.M. 6.41 Jarpa, S. 65, 79 Jaskiewicz, J. 141,218 Jassim, S.A.A. 108, 135 Jeffries, T.W. 63, 64,88 Jellison, J. 58,59,81 Jenkins, R. 73,82 Jenkins, S.F. 54,57,64,89 Jennings, D.H. 49, 58.80.85 Jensen. D.F. 105,127 Jensen, R.B. 120,131 Jepras, R.I. 104,131 Jernecjc, K. 67.85 Jeziore, S.Y. 254.257, 282 Ji, G. 146. 222 Jiang, P. 182,219 Jiang, W. 201,217 Jiang, Z.Y. 144,219,266,282,286 Johnson, D.E. 275,284 Johnson, M.S. 267,269,280,286,289 Johnson, R.C. 50,80, 144,226 Johnson, S. 144,206,216 Johnston, C.G. 74.85 Johnstone, K. 212,218 Jones, C.J. 296,301,309,329,332

348 Jones, D. 56,69,85 Jones, D.M. 98,131 Jones, G.C. 73.81 Jones, G.E.B. 59.90 Jones, P.L. 275,277 Jones, R.P. 10, 14, 18, 19.23.41 Jones, W.A. 145,221 Jongmans, A.G. 7 2 , M Jores, R. 195, 198,221 Jorgensen. B. 269,288 Joshi, A.H. 8, 12, 15,27,44 Joss, A. 270.282 Jourlin, C. 194, 219 Joux, F. 104.131 Joys, T.M. 298,332 Jung, K. 212,219 Jung. K.H. 264,281 Jung, W. 71,82 Junge, W. 296,335 Juni, E. 4.41.42 Jurinak. J.J. 70. 81, 85 Kadner, R.J. 146, 183,217,219 Kado, C.I. 146, 222 Kagawa, T. 104.130 Kainosho, M. 195,201,225 Kaiser, D. 262, 286 Kaiser, G.E. 272,282 Kakimoto, T. 145,219 Kalkut, G. 108, 130 Kaltwasser, H. 145,224 Kalyanaraman, B. 64,88 Kamberov, E.S. 182, 194, 204,222 Kami-ike, N. 315,332 Kaminski, P.A. 145,219 Kamiya. R. 298,332 Kanamaru, K. 183,219 Kaneko, T. 144. 182,219,222 Kanel. B. 270,282 Kaneshiro, E.S. 104, 131 Kankaanpaa, P. 104,136 Kaplan, N. 140, 141,218,244,278 Kaplan, S. 194,222,272. 286 Kaprelyants, A S . 93, 94, 95, 96.98, 99, 102, 104,106,110,116,117,ll8,121,122, 123,127.131,133,136 Kar, R.N. 77.78,90 Kara-Ivanov, M. 322,327,330 Karamata, D. 194.220 Karamushka, V.I. 68,77, 81.85 Karp,M. 104,136 Kathiara, N . 65.82 Kato, H. 305,329 Kato, M. 194, 195,205,219 Kawagishi, I. 236,254,283,285,296,305, 308,311,323,329,331,334 Kawarabayasi, Y. 144,219

AUTHOR INDEX Kawata. M. 194,225 Kay, S.A. 141,219 Kayser, F.H. 182,218 Kedishvili, N.Y. 141,218,223 Kehoe. D.M. 146,219 Keith, B. 141,219 Kell, D.B. 93,94,95.96,98.99, 102. 104, 106, 108,109, 110. 116,117, 118, 121, 122, 123,127.129,131,133.136 Keller. J. 57,85 Kelly-Wintenberg, K. 294,332 Kemner, J.M. 273,282 Kemp, P.F. 106. 107, 132 Kepner, R.L. 104,131 Kerlavage, A.R. 144, 182,225 Kern, R. 141,222 Khan, I.H. 235,282,301,307,332,333 Khan, M.A. 106,131 Khan, S. 235,255,282,296,301,303,307, 314,315,318,319,321,324,327,330, 332,333 Khindaria, A. 61, 85 Khouri, H. 270,284 Kierans, M. 61,69,89 Kieser, T. 108, 130 Kihara, M. 305,306,332,333,335 Kilburn, J.O. 101,128 Kilkenny. C.A. 145,220 Killham, K. 108, 126 Kim, C.S. 119,134 Kim, D.Y. 303,306,330 Kim, S.-H. 242,288 King, M. 274,287 Kinosita. K. 296,334 Kirby, J.R. 259,260,282,288 Kirk, T.K. 64.88 Kirschner, P. 101, 127 Kishi, K. 64.85 Kisser, M. 68.85 Kjelleberg. S. 107, 115, 116, 121, 122. 131, 132.133,135,136,275.281 Kleerebezem, M. 120, 121,131 Klenk,H.P. 144, 182, 197,204,220 Kleutsch, B. 324,326,327,333 Klier, A. 194,205,220,222 Kloeser, S. 269,282 Knaphus, G. 56,57,84 Knight, W.G.7 0 , M Knox, W.E. 4,41 Kobayashi, K. 183,220 Kobayashi,Y. 183,220 Kobayasi, S. 312,333 Kobel, A.M. 294.334 Koenraad, P. 110,130 Koffler, H. 294,335 Kofoid, E.C. 143, 144, 182, 195,205,220.223, 246,282,285

AUTHOR INDEX Kogure, K. 103,131 Kohler, T. 260.26 1,284 Kojima, H. 321, 333 Kojima. S. 305,329 Kollmannsberger,H. 260.285 Ko1ter.R. 117, 121, 123,131,137,271,282, 286 Kominak, J. 66.89 Kondo, K. 98,136 Kondoh, H. 182,220 Konig, W. 5,42 Konings, W.N. 104,132,257,282 K0nishi.Y. 212,220 Konopka, A. 99,135 Koopman, M.B.H. 236,279 Korber, D.R. 109,131 Kornblum, J. 146,222 Kornitzer, D. 104, 127 Kort, E.N. 238,282 Kort, R. 264,281 Koshland, D.E. Jr. 140, 141, 183,225, 226, 240,242,243,244,278,279,282,284. 288,316,333 Kotani. H. 144, 182,219 Kotyk, A. 10,31,43 Kpomblekou-A, K. 7 1.85 Krah, M. 264,280 Krakowka, S. 275,280 Kranz, R.G. 145,217 Krebs, E.G. 140,220 Krebs, W. 76,85 Kreiswirth. B. 146,222 Kremer, L. 108,131 Kren,V. 5.42 Krisai, I. 56, 85 Krishna, K.T. 13, 14, 15, 16, 18,23,33,4/, 43 Krishnaswamy, S. 300,331 Kristiansen, B. 68, 88 Kristich. C.J. 260, 282 Kritzman, G. 64.85 Krogfeldt, K.A. 107,132 Krogfelt, K.A. 104, 107,134 Kroll, R.G. 110, 134 Krumbein, W.E. 74.80 Krywko, J.E. 247,284 Kuan, I.C. 55,86 Kubicek, C.P. 49,53,54,66,67,68,77,85,86, 87, 88, 89, 91 Kubori. T. 309, 333 Kucey, R.M.N. 69, 79.86 Kudo, S. 236,283,296,311,315,316,319, 320,323,332,333,334,336 Kuhl, W.E. 54.84 Kuiack, C. 69,81 Kuipers, O.P. 120. 121. 131 Kukral,A.M. 146,221 Kukuruzinska, M.A. 143,227

349 Kundig, W. 143,220 Kung, C. 255,279,283,284,313,330,334 Kunst, F. 119, 132, 182, 194, 197,205,220, 222 Kuntz, M.J. 141, 223 Kuo, J.F. 140,220 Kuo, S.C. 316,333 Kupper, J. 294,333 Kurahashi, Y. 3 1 1.3 19,320,336 Kuroda, Y. 143,220 Kurosawa, 0. 31 1,319,320,336 Kuspa,A. 221 Kuster, T.A. 62, 64,84 Kustu, S. 145,221 Kutsukake, K. 235,282,306,333,336 Kuver, J. 269,288 Kwa, S.L.S. 264, 281 Kwok, S.F. 141,216 Laamanen, I. 146,221 Labbe, D. 212,220 Lagarias, J.C. 141, 145,227 Laheurte, F. 69.80 Laidler, K.J. 326,331 Laird, R.J. 69,70, 80 Lambrecht, M. 273,288 Lamprecht, 1. 73.86 Lane, T. 145,223 Langomazino, N. 73.88 Lanoil, B.D. 104,132 Lapeyrie, F. 54.55. 57.58.69, 70,71,86,88 Lapidus, I.R. 310,316.331 Large, P.J. 19, 20, 21.41 LaRosiliere, R.C. 273,281 Larsen, M.J. 61.84 Larsen, P.B. 194,216 Larsen, S.H. 238,282,295,333 Laszlo, D.J. 268, 282 Latterell, P. 145, 201,226 Lau, P.C. 212,220 Lauger, P. 324,325,326,327,333 Lebaron, P. 104,131,132 Lebert, M.R. 243,260,282,285 LeChevallier, M.W. 113, 123,132 kcours, N. 58.88 LeDeaux, J.R. 145, 183, 194,220 Lee. B.H. 247,283 Lee, G.F. 243,282 Lee, K.E. 212,216 Lee, L. 254, 285 Lee,% 244,287 Lee, S.H. 106, 107,132 Lee, T.Y. 145, 220 Leeuwenhoek, A. van 50,86 Legisa, M. 67.87 Legnani-Fajardo, C. 275,282 Leibler, S. 183,214

350 Lemmer. H. 109.133 LeMoual, H. 244,282 Lengeler, J.W. 253,254,283,285 Leonard, R.B. 101,128 Leroux, B. 140, 146,220 Leskovac, V. I I , 42 Levene, P.A. 140,221 Levi, Y. 113, 129 Levin, M.D. 253,279 Levine, M.M. 98, 128 Levit, M. 205.220,221.225,245,246,253, 283,287 Levit, M.N. 232,243,253,283 Levy, J.F. 59, 88 Levy, L. 104,127,133 Lewandowski, Z. 271,279 Lewis, LR. 73.82 Lewis, M. 143,223 Leyval, C. 69,72.80,86 Li, C.Y. 71,75,81 Li, J. 242,283 Li, J.Y. 246, 283 Li, Y. 2 12,223 Liang, X. 273,282 Liao, C.H. 146, 194,221 Licht, T.R. 104, 107,132,134 Liew, M.K.H. 5,23, 30,42 Lilius, E.M. 104, 136 Liljestrom, P. 146,221 Lilly, A.A. 243,282 Limberger, R.J. 236,279 Lin, E.C. 146, 194.219 Lin, L.-N. 242,283 Linder, K. 103, 110, 132 Lindum, P.W. 275,281 Lineri, S. 104, 136 Linley, K. 108, 135 Lipmann, F.A. 140,221 Little, B. 72, 86 Litwin, S. 195, 198,221 Liu, D. 195,201,225 Liu, J.Z. 296,319,333 Liu, Y. 183,205,214,220,221,245. 253,283. 287 Lloyd, D. 23,40, 104,132 Lloyd, D.H. 73,89 Lloyd, S.A. 235,289,306,307.324.333.337 Loake, G.J. 273,285 Lobo,Z. 7.42 Locht, C. 108, 131 Lockatell, V. 275.284 Loessner, M.J. 108, 132 Loewus, F.A. 54.58,83,86 Lois, A.F. 183,221 London, J. 301,331 L0ng.A. 3.9, 10, 12. 15, 16. 17, 18,23,24,25, 26,38,42,43

AUTHOR INDEX Longo, J.M. 71.84 Loomis, W.F. 183, 194,221,224,226 Loper, J.E. 144, 194,216 Lopezarnoros, R. 104,132 Losick, R. 123,131,271,282 Louw, M.E. 144,205,221 Lovell, M.A. 121,127 Lowe,G. 236,283,311,314,317,318,323, 327,328,333,334 Lowe, S. 67,87 Lowry, D.F. 205,227,247,283,284 Lucas, D. 7 I , 81 Lucero. H.A. 140,226 Luck, L.A. 243,280,283 Ludden, P.W. 145,227 Ludwig, W. 100, 101, 104, 107, 109,126 Lugtenberg, B. 140,225 Lugtenberg, B.J. 146,216 Lui, Y. 232,243,253,283 Lukat, G. 245,287 Lukat, G.S. 247,283 Lundstrom, U. 72.85 Lupas. A. 249,283 Lupas, A.N. 140.222 Lurz, R. 205,221,253,283 Lutkenhaus, J. 105, 127 Lutter, R. 296,329 Lux, R. 254.283 Lyristis, M. 146, 221 Ma.D.B. 61.64.79.86.90 Ma, H. 66,67,86 Ma, M. 123,132 Ma, S. 146,221 McBride, M.J. 260,261,284,289,294,337 McCallus, D.E. 146, 194,221 McCarter, L. 145,221,270,277,296,305,329 McCarter. L.L. 305,334 McCleary, W.R. 145,221,260,289,294,337 McCray, J.A. 255,282 MacDermott. R.P. 101, 134 McDougald, D. 116,133,136 Macek. K. 12, 17,22,40 McFarland, N. 145,221 Macfarlane, G.T. 275,288 MacFarlane, S.A. 145,221 McFee, W.W. 70.83 McFeters, G.A. 103, 113, 123,132, 135 McGillivray, D.M. 108,129 McGovern, V.P. 116, 132 Machado, H.B. 145,221 McHardy, W.J. 56.85 McKenzie, A. 4,42 Mackey,B.M. 104, 106, 112, 113,127,132, 135

Macnab, R.M. 235,237,254,277,283,287, 288,292,294,295,298,299,300,301,

AUTHOR INDEX 302,303,305,306,308,309,310, 315, 316,329,331,332,333,335,336 Macnaughton, S.J. 100,136 McNeil, B. 54,67,91,92 MacNeil, S.D. 260,283 McNerney, R. 108,136 Maddock, J.R. 250.25 I, 252,257,277,281, 283 Maddox, I.S. 67, 81 Madhusudan 195,227 Madigan, M.T. 95, 132 Madrid, C.P. 77, 91 Maeda, K. 3 12,333 Maeda, T. 194,221,223 Maekawa, Y. 236,283,296.31 I , 323,334 Magara, K. 62,87 Magariyama, Y. 236,283,296.306.31 1.316, 319,320,323,333,334,336 Magasanik, B. 140, 141, 194,216,222 Magro, P. 64,65,87 Maguire, B.A. 144,218,251,281 Maharaj, R. 145,221 Mahimairaja, S. 70.7 1.80 Mahmoud, W.M. 9, 12, 14, 16, 17,20,21,24, 25,28,29, 30,31,32,38,42 Maitra, P.K. 7.42 Mak, P.R. 7,8, 19.44.45 Makino, K. 145,201,214,220,221 Malajczuk, B.N. 56.87 Malek, W. 273, 283 Malone, C. 106, 107,132 Manley, E.P. 71,87 Manson, M.D. 144,216,240,242,280,288, 295,303,305,312,315, 317, 321, 323, 324,330,331,334 Manz. W. 109. 132 Marcant, B. 61,91 Marciano, P. 64.87 Marciono, P. 65.87 Marconi, A.M. 194,215 Marguez, L. 64,85 Marie, D. 104,132 Maring, E. 54, 86 Marouga, R. 107,132 Marquez-Magana, L. 256,259,285 Marshall, K.C. 100,134, 236,278,294,329 Martell, A.E. 50.87 Marth, E.H. 112,129 Martin, G. 121,137 Martin, R. 100, 109,128 Martin, S.E. 113,128, 129, 132 Martinac, B. 255,279,283.284.3 13,330,334 Martinez-Hackert, E. 247,287 Martinko, J.M. 95, 132 Marwan. W. 263,264,280,284,294,333 Marx, S. 141,224 Masai, J. 327,334

351 Maskell, D. 275,282 Mason, D.J. 104, 132 Mason, J.R. 9, 13, 16, 17, 18, 21, 25, 26, 30, 32, 38,39,40,44 Mast, M.A. 71.87 Masters, C.I. 106, 135 Masure, H.R. 144,206,216 Mathews, M.A.A. 235,284 Mathews, S. 143,216 Matsuda, 2. 146, 194,219 Matsuguchi, T. 273,286 Matsumura, P. 218,245,246,247,281,284, 286,303,316,334,335 Mattey, M. 49, 67, 77, 87 Matthews, H.R.143,218,223 Mauel, C. 194,220 Maxwell, D.P. 54, 55, 79.87 Maxwell, M.D. 54,87 Mayor, J. 212,223 Meeker, J.W. 240,242,280 Mehta, A. 65.87 Meier, H. 109. 133 Meighen, E. 122, 129 Meikle, A. 108, 126 Meister,M. 236,283, 311, 314, 315,317, 318. 321,323,324,325,327, 328,332,333, 334 Meixner, 0. 67.77.87 Mejean, V. 194,219 Mekalanos, J.J. 146,221 Melkerud, P.-A. 72, 85 Merad, T. 115,128 Merkel, S.M. 145,225 Merrick, M. 145,221 Merrill, R. 259,281 Metting, F.B. 48.87 Meyer, M. 204,215 Meyerowitz, E.M. 141, 145,216.218 Meyrath, J. 19.42 Mez, K. 270,282 Micales, J.A. 54, 55, 61,63, 65, 87 Michiels, J. 145,216 Miernyk, J.A. 141,225 Mignon-Godefroy, K. 109, 132 Mii, K. 54,5562.63.64. 65.90 Mikkelsen, N.D. 119, 120, 130 Mikoshiba, K. 104,130 Millard, P.J. 104, 135 Miller, C.A. 145,204,219 Miller, J.F. 146, 194, 214, 272, 285 Miller, S.I. 146, 221 Milligan, D.L. 240,284 Mills, G.L. 71, 81 Milton, D.L. 274,285 Mimori, Y. 299,336 Minet, J. 104,128 Miranda-Nos, J. 145,221

352 Mischak, H. 66.67.77.87 Mishra, R.K. 77, 90 Misumi, H. 98,136 Mitchell, J.G. 269, 270,278,284 Mitchell, P. 326,334 Mitchell. R.A. 143, 222 Miura, M. 104,130 Miyagoshi, M. 5.40 Miyamoto. C. 122, 129 Mizote, T. 254,284 Mizuno, T. 140, 146, 182, 183, 194, 195, 197, 205,219,222,254,284 Mizushima, S. 183,219 Mobley, H.L. 274.275,284 Moens, S. 270,272,284 Moghazeh, S. 146,222 Moldover, B. 115, 136 Molenaar. D. 104, 132 Molera, J. 72, 83 Molin, S. 100, 104, 107, 108, 109,127,128, 132,133,134, 135,275.281 Molina. M. 104, 134 Molinas, C. 144,201,215 Moiler, S. 100, 109, 128,133 Monack, D. 146, 194.214 Montague, W. 118, 128 Montie, T.C 294,332 Montrone, M. 263,284 Mor, N. 104,133 Moreira, A.R. 18, 43 Morel, P. 146,222 Moreno. M. 3 1,43 Morgan, D.G.244,284,298,334 Morgan, D.R. 275,280 Morinigo, M.A. 274,278 Morita, N. 104,130 Moriya, T. 98.136 Morley, G.F. 49.68, 87 Morris, P.J.L. 122, 127 Morrison, D.A. 144,206,218,223 Morrison, T.B. 245,284 Morsdorf, G. 145.224 Morton, F.C. 253,279 Morton, J.F. 3.42 Mossel, D.A. 113, 133 Mossel. D.A.A. 113, 133 Mostratos, A. 110,126 Moszer, I. 119, 132, 182, 197,220 Mottonen, J.M. 247, 283,287 Mouncey, N.J. 194,222 Mourey, L. 246.288 Moy, F.J. 247, 284 Moyer, C.L. 99, 130 Mrazek, E. 56.85 Msadek. T. 194.205.220.222 Mudd. M. 146.227 Mue1a.A. 108, 113, 127

AUTHOR INDEX Mukamo1ova.G.V. 102, 106, 117,121,131, 133 Miiller, B. 77,83,88 Muller, J. 260,284 Munier-Lamy, C . 50,88 Munoz, M.L. 73.84 Munzo Aquilar, J.M. 273.285 Muramoto, K. 236,283,296,305,311,323,334 Murata, T. 334 Murphy, G.P. 141, 145,216 Murphy, J.T. 141. 145,227 Murphy, R.J.59,88 Murray, J.D. 262,288 Murray, R.G.E. 303.331 Musseleck, S. 263,284 Muszynski, M.G. 141,225 Muto, E. 321,333 Myerscough, M.R. 262,288 Nachamkin, I. 275.285 Nagasawa, S. 194,222 Nagatani, M. 10.3 I , 40 Nagodawithana, T.W. 14.31.42 Naidu, R. 70.7 1, 80 Nair, G.B. 104,129 Nakahira. K. 104,130 Nakano, H. 104,129 Nakano, K. 183,220 Nakata, A. 145,201, 214,220.221 Nakazawa, A. 143,227 Nakazawa, T. 254,284 Namba, K. 298,299,309,332,333,336 Nara, T. 254,285 Natarajan, K.A. 76,81 Naughton, A.M. 144,206,216 Navarro, J.M. 26.42 Navrot, J. 77, 90 Neef, A. 109, 133 Neher, J. 7 I , 82 Neidhardt, F.C. 115,136 Nerantzis, E.T. 77, 90 Nes. I.F. 206, 218 Nester, E.W. 140, 146,212,216. 220,273,282 Netik, A. 67.68.88 Netrval, J. 3, 8, 12, 14, 16, 17, 18. 19.22.28, 41.42.45 Neuhaus, G. 141,222 Newby, P. 108,135 Newton, A. 143, 145. 195,223.227 Ngok, F.K.26 I , 287 Nguyen, A.M. 106,129 Nicole, M. 58,88 Nikolova, P. 3. 8. 10, 11, 12. 13, 16, 18.22, 27, 33.42.43 Nikovska, G.N. 68,77,81 Nilsson, L. 116, 133 Nina, E.G. 182. 194,204,222

AUTHOR INDEX

353

Ninfa, A. 245, 287 Ninfa,A.J. 140. 141, 143, 182, 183, 194, 197, 204,215,219,222,225 Ninfa, E.G. 140, 145,222,223,245,287 Niqueux, E. 308.336 Nisbet, I.T. 146, 221 Nishioka, N. 305,329 Nishiyama, S. 254,285 Nitz, S. 260,285 Nixon, B.T. 140, 145, 146, 182,222.224 Noegel, A.A. 145, 194,224 Noji, H. 296,334 Nombela, C. 104, 134 Nordmann, B. 260,285 Norioka, S. 183,217 Noronha, S. 18,43 Norris, S.J. 144, 217 Novak, M. 3 1.43 Novick, R.P. 146,222 Noyes. R.D. 64.88 Nuutila, J. 104, 136 Nwoguh, C.E. 98, 104, 108,127,129,133 Nystr-m, T. 112,113, 114, 117,120,133 Nystrom, T. 107,126 Obrien. M. 96, I30 O’Connor. K.A. 260,289,294,337 O’Donnell,A.G. 100,136 Oehrne, F. 145, 194,224 Oesterhelt, D. 144,224,260, 263.264.280, 284,285,286,294,333 Ogasawwa, N. 119,132, 182, 197,220 Oh, E.Y. 143,217 Ohman, D.E. 146,221 Ohta, A. 54, 62, 79 Ohm, N. 143, 145, 195,223,227 Okino, H. 301, 332 Old. I.G. 144,226 Oliver,A.L. 3,5,8,9, 15, 19,20,22,23,26, 32, 36.38, 39,43 Oliver, J.D. 98, 103, 104, 110, 116, 121, 132, 133, 134.136 Oliver, S.G. 10. 31,40 Olsen, G.J. 99, 130, 182,215 Olsen, J.E. 144,217 Olson, E.R. 115,136 Olson, G.J. 76, 88 Olson, K.D. 264,278 Olsson, M. 72. 85 Olsvik, E. 68.88 O’Neil, J.P. 122, 127 0no.A.M. 195,201,225 Oosawa, F.324 327,334 Oosawa, K. 140, 141, 183,218,227,245,247, 281,288,299, 301,308,336 Ordal. G.W. 144.217.254.256.259.260.280. 281,282,284,285,286,288 .

,

I

Ordal, Z.J. 113,128,129,132 Orthofer, R. 67.88 Ose, S. 9, 17,22,43 Oster, G. 328, 331 Ostling, J. 122, 135, 275,281 Ota, I.M. 141, 145, 194,223 O’Toole, J. 274, 285 Ottemann, K.M. 272,285 Ouellette, G.B. 58, 88 Oura, E. 18,43 Overmann, J. 270,280,285 Oxburgh, R. 7 1.90 Ozawa, H. 273,286 Pace,N.R. 99, 100, 106. 107,129,130,133 Packer, H.L. 144,227, 237, 238,277,285, 300, 3 14,329,332 Pain, A. 212,218 Palma, R.L. 73,89 Palmer, R.J. 72, 73, 84 Palva, E.T. 146,221 Pamment, N. 14,41 Pamment, N.B. 23,31,41,44 Panchanadikar, V.V. 77.78.90 Pandit, J. 242,288 Panoff, J.M.116,133 Pao, G.M. 21 1,212,223 Parales, J. Jr. 145,225 Parales, R.E. 257,281 Parbery, D.G. 72.83 Paris, F. 7 1, 88 Park, H. 195, 197,201,217,223,225 Park, P. 225,246,287 Parker, J. 95,132 Parkhill, R. 119,128,206,216 Parkinson, J.S. 143, 144, 182, 194, 195, 205, 214.220,223,244,245.246,249,254, 267, 277,278,282,283,284, 285,287, 296,300,331,334 Parks, E.J. 76, 88 Parsek, M.R. 123,129,271,279 Partensky, F. 104,132 Parthuisot, N. 104,132 Pascual, C. 10,31,43 Pasley, S.M. 113, 126 Pate, J.L. 236, 285 Patel, A. 212,220 Patriarca, E.J. 145, 223 Patschkowski, T. 145,223 Paul, F.E. 104,131 Pawley, J.B. 109,133 Paxinos, R. 270,284 Pearson, A.D. 96,98,130,133 Pearson, J.P. 121, 123,129,133,271,279 Pearson, L. 270,284 Pearson, S.C. 104,131 Pecota, D.C. 119,134

354 Pedersen. K. 119, 120, 130 Pedrosa, F.O. 145,221 Peleg, Y. 66.80 Peliska, J.A. 182, 219 Peltonen, K. 104, 136 Penaloza-Vazquez. A. 146.226 Penchev, R. 144,227 Pentecost,A. 269,285 Pepin, R. 57.86 Peppler, H.J. 19, 43 Pera, L.M. 68.88 Perego, M. 145, 183. 194,223,224 Perera, J. 194,226 Perez, I. 63, 64,88 Perfettini, J.V. 73,88 Perozo, E. 264,278 Perrin, M. 57.86 Pesci, E.C. 121, 133 Pesis, K.H. 143,223 Pestova, E.V. 144,206,223 Peter, J.B. 140, 143,215 Petrino, M.G. 272,285 Petsko, G.A. 247,287 Pettersson, I? 55, 84 Pfeffer, W. 234,285 Phillips, D.G. 18, 19,45 Phillips, I. 104, 130 Phipps, D. 104, 134 Picatto, C. 58, 86 Piccini, C. 275,282 Pierce, M.S.F. 113. 126 Pierson, P.E. 54, 88 Pijper, A. 295,334 Pilgram. W.K. 3 10,334 Pilz. F. 67, 90 Pinder, A.C. 104,128 Pirt, S.J. 9, 13, 16, 17, 18. 21, 25, 26, 30, 32. 38, 39.40, 44 Pitta, T.P. 263,286,294, 300,329.334 Plamann, L. 212,223 Platzer, J. 144, 217 Pleier, E. 235, 285, 298, 334 Plonzig, J. 67. 84 Plovins, A. 104, 134 Plowright, C.B. 50.84 Plunkett, G . 182, 197, 215 Plunkett, G.R. 119, 127 Pocino, M. 108, 127 Pohl. M. 4,5,6, 8,9, 13,43 Polarek, J.W. 146,226 Poli,G. 5,41 Pons, M.-N. 61, 91 Poole, P.S. 254, 257. 282, 285 Poot, M. 104,135 Popov, K.M. 141,218,223 Popp, J.L. 64.88 Porter, J. 108,136

AUTHOR INDEX Posas, F. 194,223 Post, J.C. 106,134 Postgate, J. 94, 102, 110, 134 Postgate, J.R. 95, 102, 103, 117. 118,128, 134 Postma, P.W. 253,285 Postnova, T. 274,286 Potter, C.W. 106,131 Poulaingodefroy, 0. 108, 131 Poulsen, L.K. 100. 104, 107, 108, 127, 134 Powell, B.S. 146.222 Powell, M.D. 58,88 Power, E.G. 99, 102. 118,127 Ratt, J.R. 104, 131 Pratt, L.A. 201, 223, 271,286 Priefer. U.B. 145,223 Prieto, B. 88 Prins, R.A. 100, 101, 106,135 Prive, G.G. 242,288 Projan, S.J. 146,222 Pronk, J.T. 6,41.44 Prosser, J.1. 108, 126,129 Pugh, S.Y.R. 10.40 Punja, Z.K. 54.57.64.89 Puppe, W. 183,227 Purcell, E.M. 232,286 Purich, D. 182.214 Purvis, O.W. 49, 61, 73, 81. 89 Puskas, A. 272,286 Pyle, B.H. 103, 132 Qin. L. 195,201,225 Quadri, L.E. 120, 121,131 Quail, P.H. 143,223 Quang, P. 100, 109,128 Quesnel, L.B. 110,126 Quillardet, P. 112, 134 Quintiliani, R. Jr. 201, 2 / 7 Rabin, R.S. 205,223,224 Radman, M. 112,129 Raedts, M.J.H. 77,89 Ragatz, L. 266, 286 Raggett, S.L. 68.69.89 Raisys, V.A. 101, 128 Rajendran, N. 104, 129 Ramos, J.L. 100,133 Ramsay, L.M. 49, 89 Ramsing, N.B. 269,288 Randall, D.D. 141,225 Rang, C. 104, 107,134 Ranger, J. 69,70, 7 1, 86, 88 Rao, D.V. 65.89 Rao, J.R. 213,286 Rapoport, G . 194,205,220,222 Rappuoli. R. 146, 194,214.215 Rasmussen. B.F. 247,287 Rasmussen, J. 104, 131

AUTHOR INDEX Rasmussen, O.F. 144, 217 Ratledge, C. 101, 127 Ratto. M. 5 5 , 89 Ratto, M.A. 113, 133 Ravid, S. 246,286. 296,316,334 Rawlings, D.E. 145.220 Rawlings, M. 212,220 Ray, B. 112, 113,130,134, 135 Ray.R. 72,86 Rayner, M.G. 106,134 Read, D.J. 70.89 Read, R.B. Jr. 113, 135 Rebbapragada. A. 267,286 Reed, G. 19.43 Rees, C.E.D. 108,132 Reese, T.S. 235,282, 301,303, 307,332,333 Reeves, H.C. 143,224 Reeves, P. 140,225 Reid, S.J. 144, 205, 221 Reizer, A. 183,224 Reizer. J. 143, 183,224, 259, 281 Reller, A. 73, 86 Relman, D.A. 101, 102,130, I34 Repaske, D.R. 254,286 Resnick, M. 104, 127,133 Revertegat, E. 73,88 Rheims, H. 106,129 Rhodes, L.H. 54.88 Riccio, A. 145, 223 Richards, A.J.M. 273,285 Richardson, K. 274,286 Ridgway, H.F. 104,134 Ridgway, H.G. 194,224 Riesen, R. 73,86 Riggle, P.J. 144, 215 Righelato, R.C. 10, 31, 40 Rigo, L.U. 145,221 Rigsbee, W. 104,134 Ringe, D. 247,287 Rio, B. 58.88 Riol, J.-M. 67, 68.88 Riou, G . 104,128 Rioux, D. 58.88 Ritschkoff, A.C. 55.89 Rivas, T. 88 Robb. F.T. 145,221 Robb, S.M. 145,221 Robert, M. 71.88 Roberts, G.P. 145,227 Roberts, N. 96, 103,136 Robertson, B.R. 100, 109, 128,135 Robertson, E.F. 143,224 Roddick, F.A. 3,5,8,9, 15, 19,20, 26, 32, 36, 38,43 Rodrigues, U.M. 110,134 Rodriguez, G.G. 104,134 Rodriguez, M.J. 274,278

355 Roehr, M. 66,67,68,77.85,86,87,88, 89.91 Rogers. P.L. 5.6, g, 9, 11, 12, 13, 14, 15, 17, 19,20.21,23,24,26,27,28,29,30,32, 33,34, 39,40,41.42,43.44,45 Rogowsky, P.M. 146,222 Rojas, E. 65, 79 Rokem, J.S. 66,80 Rolko, K.E. 74,76,9/ Rollings, D. 96, 98, 133 Rollins, D.M.98, 110, 134 Romagnoli, S. 266,286 Romano, A.H. 143,224 Romano, P. 4, 12,43 Romay, C. 10,31,43 Rornbouts, EM. 110, 130 Ronson, C.W. 140, 145, 146, 182,222,224 Rood, J.I. 146, 221 Rosario, M.M. 259,286 Rose, Z.B. 143,224 Roseman, S. 143,220,227 Ross, H.F. 146, 222 Rosswall, T. 72.80 Roszak, D.B. 96, 103. 134, 135 Roth, A.F. 205,217,247,283 Roth, B.L. 104, I35 Roukas, T. 67.89 Rowe, D.E. 64,80,89 Roy, C. 146, 194,214 Ruby, E.C. 272,281,286 Rudd, K.E. 267,278 Rudolph, J. 144,224,263,286 Rumbak, E. 145,221 Rupert, P.B. 247,283 Rushing, B.G. 266,282 Russ, J. 73, 89 Russell, N.C. 73.82 Russo, ED. 195, 197,218 Ruzzi, M. 194,215 Sabbert, D. 296,335 Sackett, M.J. 263, 286 Sager, B. 262,286 Saha, S.K. 195, 197,201,223,225 Sahm, H. 4,12,40 Sahni, G. 12, 13, 15.29.41 Saier, M.H. 259, 281 Saier,M.H. Jr. 183,211,212, 223,224 Saito, H. 143, 194, 221, 223, 227 Saito, K. 54,86 Sakai, M. 273,286 Salmond, G.P.C. 120, 121,135,136 Salyers, A.A. 194, 224 Samadpour, M. 101,129 Samama, J.P. 246, 288 Sambamurthy, K. 13,43 Samuel, A.D.T. 322,323,335 Sanchez-Pescador, R. 145.221

356 Sanders, J.M. 194,224 Sanna. M.G. 144,225 Santanam, P. 182,218 Santorum, P. 105.127 Santos, R.A. 144,215 Sarkis, G.J. 108, 130, 135 Sasarman,A. 264,288 Sass, H. 270,285 Sato, J. 141,218 Sato, S. 144, 182,219 Sato, T. 183,220 Savidge, G.F. 104, 130 Sawada, M. 144.219 Saxild, H.H. 260,284 Sayer, J.A. 49,57,58.59,60, 61,68,69, 70, 76, 77, 81,83. 85,87, 89, 91 Schaefer, A.L. 272, 286 Schafer, W. 263,284 Schaffner, A. 101.135 Scharf, B.E. 183,224 Schaumburg. A. 141,224 Scheffers,W.A. 7.8. 10, 15, 19,41,44,45 Schell, M.A. 212.216 Schellenberger, A. 7.41 Scherer. S. 108. 132 Scherrer. J. 243,280 Schiel, S. 260,284 Schiel, S.L. 259,281 Schiemann. D.A. 113, 123,132 Schinner, F. 49,59,68,69,70, 76,77,78, 80, 83, 85, 88, 89, 90 Schipper, D. 7,8,45 Schleifer, K.H. 100, 101. 104, 107. 109, 126, 132, 133,269,287 Schluter, A. 145,223 Schmid, J. 67.84 Schmidt, T.M. 101. 134 Schmitt. H.D. 7.43 Schmitt, R. 144. 183,217,224,235,237,247, 260,277,285, 287, 294, 296, 298, 329, 331,334 Schneider. B.M. 242.288 Schneider-Poetsch,H.A. 141,224 Schnitzer, M.J. 232,286,321,335 Schoedon, G. 101,135 Schomburgk,N.J.D. 10.40 Schreferl-Kunar. G. 86 Schrickx, J.M. 77.89 Schurr, M.J. 146,227 Schuster, S.C. 205, 225, 245,287 Schuster, S.S. 145, 194,224 Schut,F. 100, 101, 106. 109, 128,135 Schutt. C.E. 247,287 Schwabb,A.P. 72,80 Seaward, M.R.D. 73.82 Seehaus, C. 67,90 See1y.R.J. 13, 17.27, 28.30, 31.44

AUTHOR INDEX Segal, A. 182,215 Segall, J.E. 246.278,310,316,332 Servi, S. 4,5,40,41 Seymour, D.A. 112, 113,132 Shacar-Nishri,Y. 26,44 Shah, D. 244,287 Shah, D.S.H. 306,335 Shah, M.M. 64.90 Shahamat, M. 96,98,133 Shallcross, J.A. 104, 106, 127. I35 Shapira, R. 77, 90 Shapiro. L. 235,251,276.277,279,283,287, 298,331 Sharma, R.K. 143.220 Sharman, R.L. 99. 108, 118, 119. 123,126,129 Sharp, L. 306,335 Sharp, L.L. 303,306,335.337 Sharrard. R.M. 106, I31 Sharrock, R.A. 143,216 Shaulsky, G. 183, 194,221,224,226 Shaw, C.H. 273,285,287 Shaw, P. 109,135 Sheridan, G.E. 106. 135 Sheridan, J.J. 104. 129 Sherris, D. 249,287 Sherwood, E.E. 263,286,294,334 Shi, W. 261,287 Shimada, K. 315,335 Shimada, M. 54, 55, 61, 62, 63, 64,65, 79, 86, 90 Shimamoto, N. 309,333 Shimizu, H. 334 Shimizu, T. 183, 194, 195, 205,219, 220 Shim0murd.Y. 141, 218,223 Shin, H.S. 6, 8, 9, I I , 12, 14, 15, 17, 20, 21.23, 24,26,27.28,29, 30, 32, 33, 34. 39,40, 43,44,45 Shinagawa, H. 145,201.214,220,221 Shinano, H. 106.137 Shinitzky, M. 254,280 Shinners, T.C.57, 58, 90 Shinozaki, K. 141,219 Shioi, J.-I. 268,287 Shoda. M. 10,31,40 Shoemaker, N.B. 194,224 Shoji, K. 183, 220 Shotton. D. 109, 135 Showalter,R.E. 144,2/5 Sicard, M.A. 146,217 Siegele, D.A. 117,131 Silbaq, F. 104, 133 Silhavy, T.J. 143. 183, 195, 197,201,218,219, 223 Silva, B. 88 Silverman. M. 194,224,294,295, 310,335 Silverman, M.R. 144,215 Silverman, P.M. 140,214

AUTHOR INDEX Simidu, U. 103,131 Simon, M. 294,295,310,335 Simon. M.I. 140, 141, 143, 144, 145, 183, 194, 195, 197,205,214,215,218,224, 225, 227,244,245,246,252,278,279,281, 283,287 Simon, M.N. 299,335 Simpson, L.M. 104, 116,133,134 Sims,A.P. 6,7,9, 14.21.44 Sinclair,J.B. 274,288 Singer, A. 77.90 Singh, A. 113, 123,132, I35 Singh, A.K. 77,90 Singh, J. 12. 13, 15, 29.41, 72, 82 Singleton, C.K. 145,227 Singleton, EL. 96, 103,136 Sivaram, A. 268,282 Skidmore,J. 250,252,257,281 Skjak-Braek,C. 29.44 Skulachev, V.P. 295,323, 326,331 Slarke, D. 73.82 Slavik, J. 104, 135 Sloan, J. 146,221 Slonczewski, J.L. 254,287 Smidsrod, 0. 29,44 Smith, B.F.L. 69.85 Smith, D.R. 197,206,212,224 Smith, 1. 144, 227 Smith, P.F. 9, 12, 15, 16, 17.22.23.44 Smith, R.A. 143,217 Smith, R.W. 294,335 Snaidr, J. 109,126 Snetselaar, K.M. 57,90 Sockett, H. 305, 306,332,335 Sockett, R.E. 306,335 Sollins, P. 57, 70, 71, 75, 76, 81, 84 Sommer, J.M. 145,223 Soncini. F.C. 146,224 Song, S.K. 69,90 Sorensen, J. 110,130 Sorgensen,J. 105, 127 Sosinsky, G.E. 299,307,331,335 Sosne, G. 108,130 Souhrada, J. 3, 14, 17, 19,28,41 Soujik, V. 144, 183,217,224,247,287 Souza, E.M. 145,221 Spaink, H.P. 146,216 Speck, M.L. 112, 113,130,134, 135 Speidel, K. 71.75, 81 Spencer, C.P. 4.41 Sprenger,W.W. 264,287 Spring, S. 269,287 Spudich, J. 264,278 Spudich, J.A. 264,287 Spudich, J.L. 255,264,281,282,288 Spycher, G. 71.75.81 Sramek, H.A. 101,136

357 Srinivasan, M. 72, 85 Srinivasan, S. 122, 135 Stackebrandt,E. 106,129 Stader, J. 303,335 Stadtman, E.R. 182,214,215 Stalbrand, H. 6.7, 9, 14,21,44 Staley, J.T. 99, 135 Stanbury, P.F. 18, 19.44 Stancic, B. 11.42 Stanley, G.A. 23.44 Starostzik, C. 263, 284 Steadman, J.R. 64.83 Steensma, H.Y. 6,41 Steffens, M.B. 145,221 Steglitz-Morsdorf, U. 145,224 Steinert, M. 98,135 Steinkraus, K.H. 14.31.42 Stenstrom, T.A. 109,132 Stephens, C.M. 276,287 Sterflinger, K. 74, 80 Stem, N.J.275,285 Sternberg,C. 100, 108, 109, 127, 128,133 Stevens, A.M. 122,127, 194,224 Stevens, D.L. 146,221 Stevenson,F.J. 7 I, 90 Stewart,G. 99, 108, 118, 119, 120, 121, 123, 126,129,132,135,136 Stewart, G.S. 99, 102, 118, 127 Stewart, J.W.B. 69, 79 Stewart, P.S. 103, 132 Stewart, R.C. 195,225 Stewart,V. 145,224,225 Stibitz, S. 146, 194, 214 Stillings, L.L. 71, 76,82,90 St0ck.A. 140, 141, 144, 182, 195,205,222. 225,227 St0ck.A.M. 143,225,247,251,279,283,287 Stock, J. 140, 141, 144, 182, 195,205,217, 220,222,225,227,249,283.294.331 Stock, J.B. 143, 183,205,211,214,218,219, 221,225,232,238,243,245,246,247, 253,283,287,294,296,335 Stoebner, R.A. 303,305,331 Stoeckenius,W. 264,278 Stout, V. 145,225 Stouthamer,A.H. 77.89 Strasser, H. 59,77,78,80,88, 90 Straube, G. 76.84 Strehaiano, P. 3 1.43 Stull, J.T. 140,215 Stumpf, P.K. 10,40 Suarez, D.L. 71, 79 Sugiyama, S. 236,283,296,305,311. 323, 334 Sukla, L.B. 77,78,90 Sullivan, S.A. 13, 17,27, 28, 30, 31,44 Sun, Q. 145,218

358 Sun, Y.T. 7 I , 90 Surette, M. 143, 183,205,220,225 Surette, M.B. 294,296,335 Surette, M.G. 183,205,214, 221,225, 232. 238,245,246'253,283,287 Surtiningsih.T. 69.72.86 Sutcliffe, E.M. 98, 131 Suto, R.K. 54.86 Sutter, H.-P. 59, 90 Suzuki, H. 299,336 Suzuki, T. 308,335 Suzzi, G . 4, 12.43 Svihla, C.K. 66,82 Swaminathan,B. 110,135 Swanson, R.V. 141, 144,205,225,227,245, 246,283,287 Swift, S. 120, 121, 135,136 Swindells, M.B. 195,201,225 Szewzyk. R. 109, 132 Szewzyk, U. 109, 132 Szundi, I. 264,278 Szymanski, C.M. 274,287 Tabata, S. 182,222 Tabatabai, M.A. 7 I , 85 Tabatabai, N. 146. 225 Taga. N. 103,131 Taira, T. 306.336 Tait 57 Takahashi, M. 54, 55,62, 79 Takao, S. 65, 90 Takayarna, K. 122,135 Tall, B. 98, 128 TamanaiShacoori. Z. 104,128 Tamplin, M.L. 96, 105, 128 Tanaka, H. 61.84 Tanaka. N. 61,90 Tanaka, T. 194, 195,201,225 Tang, H. 306,307,333,335 Tang, H.L. 235,284.306.337 Tate, R. 145,223 Tatsuta, S. 68.83. 85 Taylor, B.L. 267.268, 269.280, 282,286,287, 289 Tedesco, i? 295,323,334 Teduka, H. 106,137 ter Schure, E.G. 6,44 Teske. A. 101,127,269,288 Tewari, J.P. 57,58, 64, 65,89,90,91 Tewari, T.P. 57, 92 Thai, T.C. 194, 223 Thammavongs. B. 116,133 Thelen, J.J. 141, 225 Thoelke, M.S. 259.288 Thomas, C.A. 108, 129 Thomas, C.R. 68.88 Thomas, D. 307,331

AUTHOR INDEX Thomson, A. 54.79 Thomson, N. 5.42 Thordal-Christensen,H. 105, 127 Throup, J.P. 120, 121, 135 Tieh,T.T. 71,83 Tien, M. 55.86 Tiffany, L.H. 56, 57, 84 Tinti, C. 4,40 Tobin, J.M. 78.90 T0dd.A.W. 71,75,81 Todd, R.L. 71,75,81 Tokimatsu, T. 54.55.62.63.64.65, 90 Tokishita, S. 194,222 Tolker-Nielsen, T. 107, 132, 135 Tomb, J.F. 144, 182, 197,204,220,225 Tomiura, Y. 62,87 Tommassen, J. 140,225 Tomomori, C. 195,201,225 Tong, K.I. 195,201,225 Torma, A.E. 77,90 Tormo, A. 117, 131 Torrero, M.N. 108, 128 Torres, N.V. 67,68.88 Torruella, M. 140,226 Tothill, 1. 110, 130 Touati, D. 113, 129 Trach, K. 145, 194, 223 Trach, K.A. 145, 194,215.225 Trachtenberg, S. 298,299,335,336 Trentham, D.R. 255,282 Trifillis, A.L. 275, 284 Tripathi,C.K.M. 8.9. 12, 13, 15, 17, 18.21.27, 30.44 Trivic, S. 11.42 Troussellier,M. 104, 131 Trueba, G.A. 144,226 Tucker, K.G. 68,88 Turner,A.K. 121,137 Turner, A.P.F. 110, 130 Turner, L. 183,224, 252,278, 304.31 1, 316, 319,320,322,323,328,330,336 Turner, M.M. 5.42 Tuschak, C. 270,285 Qagi, R.D. 78,90 'Qpke, D. 294,333 Qson, R. 262,288 Tzanatos. T. 23.44 Tzeferis, P.G. 76. 77. 90 Tzeng, Y.L. 183,226 Udani, R. 108,130 Ueno, T. 301.336 Ulbrecht. S . 3, 14, 17, 19,28,41 Ullrich, M. 146, 226 Unestam, T. 72,85 Urdea, M. 145,221 Uwer, U. 294,333

359

AUTHOR INDEX Vacante, D. 303,335 Vachon, P. 78, 90 Vairelles, D. 69, 70, 86 Vallejos, R.H. 140, 226 Valois, F.W. 294,336 VanBogelen, R.A. 115,136 Van Breeman, N. 72.85 VanBruggen, R. 195,225 Vance. G.F. 69,82 Vandamme, E.J. 12, 14, 15, 16, 17.45 Vande Broek, A. 273.288 Vandenbroucke-Grauls,C.M. 212,226 Vandenesch, F. 146,222 van der Drift, C. 295,323,334 Vanderleyden, J. 145,216, 270, 272, 273,284, 288 van der Zanden, L. 6.41 van Dijken, J.P. 6,7,8, 10, 15, 19,41,44,45 Van Gijsegem, F. 308,336 Van Grondelle, R. 264,281 Van Hees, R.A.W. 72.85 Van Melderen. L. 120,128 van Rossum, G. 212,226 van Urk, H. 7,8, 10, 19,44,45 van Verseveld, H.W. 77, 89 Van Wamel, W.J. 212, 226 Varshavsky, A. 141, 145, 194,223 Varughese, K.I. 195,227 Vassilev. N. 76, 91 Vassileva, M. 76, 91 Vaughan, D. 56.85 Vaulot, D. 104, 132 Velasco, A. 194,226 Veldman, A. 113,133 Veldtkamp, C.J. 58, 80 Velkova, R. 69, 76.80 Vendramin, M. 67,85 Vendrell-Saz, M. 72.74.80.83 Vennesland, B. 4.41 Verduyn, C. 10.45 Verhoef, J. 212,226 Verma, P.R. 57,92 Verrecchia, E.P. 56,74,75, 76.91 Verrecchia, K.E. 56,74,76,91 Venips, C.T. 6.44 Vestal, J.R. 74.85 Via, L.E. 108,129 Vigeant, M.A.-S. 300,329 Viikari, L. 55,89 V i a , M. 104,136 Vivier, H. 6 1.91 Vizcaino, C. 72.81 Vlerick, C. 12, 14, 15, 16, 17.45 Vodnansky, M. 3. 14, 17, 19,28,41 Voelkner, P. 146,226 Voets, J.P. 12, 14, 15, 16, 17,45 Vogler, A.P. 308,336

V0jtisek.V. 3, 8, 12, 14, 16, 17. 18, 19, 22, 28, 41 42.45 Voll, W.S.L. 10, 19,45 Volz, K. 2 1 1,226 Vonderviszt, F. 299,336 Voordouw, G. 257,267.280 V0ra.V.C. 9, 13, 16, 17, 18.21, 25, 26, 30, 32, 38, 39,40,44 Votyakova, T.V. 98, 106, 117, 136 I

Wagenknecht, T. 300,324,326,336 Wagner, M. 109,126 Wagner, P. 72.86 Wai, S.N. 98, 136 Wainwright, M. 48,49,91 Wakabayashi, K. 298,332 Walchi, 0. 59. 90 Walderhaug, M.O. 146,226 Walinder, 0. 143,226 Walker, G.C. 105, 112, 113, 136 Walker, J. 296,329 Walker, J.E. 296,329 Walker, J.R.L. 65, 82 Walker, M.S.205, 226 Wall, J.D. 257, 267,280 Wall, J.S. 299, 335 Wallis, C.K. 101, 128 Walsh, C.T. 201,217 Wang, A. 64,91 Wang, B. 6.8, 9, 11, 12, 14, 15, 17, 20, 21, 23, 24,27,28,32,33,34, 39,43,45 Wang, J.Y. 140,226 Wang, N. 194,226 Wang,X. 194,216,306,307,333,335 Wang. Y. 2 12.220 Wang, Y.C. 54.91 Wanner, B.L. 145,201,217,226 Ward, J.E. 140, 146,220 Ward, M.J. 144,227,236.257.260.288 Ward, O.P. 3, 8.9, 10. 11, 12, 13, 14, 15, 16, 17, 18,22,23,24,25,26,27, 33, 38.42, 43.45 Wariishi, H. 64,85 Warner, J.M. 116,136 Warnes, G. 104, 130 Warren, J.W. 275,284 Washizu, M. 31 I , 319,320,336 Waterbury, J.B. 294,336 Waters, C.Y. 72, 80 Watson, M.D. 273,285 Watson, S.W. 294,336 Watson, T.G. 144,205,221 Waygood, E.B. 143,227 Wayne, L.G. 100, 101,136 Webb, M.A. 58, 79 Weber, R. 140,214 Weerasuriya, S. 242,288

360

AUTHOR INDEX

Wei. B.Y. 146,219 Wei, Y. 143,223 Weibull, C. 294,336 Weichart, D. 93.94.95.96.98.99, 110, 116, 121,131,136

Weichart,D.H. 98,99, 102, 118,127 Weidhase, R. 7.41 Weigel, N. 143,227 Weinbaum. B.S. 59.79 Weiner. R.M. 96, 130 Weinrauch, Y. 144,227 Weinstock, G.M. 144,217 Weis, R.M. 242,246,283 Weiss, E. 96, 130 Welch, M. 183,227, 246, 247, 288, 308, 310, 316,331,336

Welsh, D. 141, 144. 182. 195,205,225 Werkman, C.H. 4.41 West, A.H. 247,287 Westerfeld. W.V. 4.41 Whatley 60 Whitaker, A. 18, 19,44 White, C. 49,68, 76, 78,8Y, 90. 91 White, 0. 144. 182,215,217,225 Whitelam. G.C. 141, 145,216 Whiteley, A.S. 100, 104, 109,130,136 Whiteley, J.M. 195, 227 Whitesides, M.D. 98, 116, 136 Whitney, K.D. 57, 58, YO, 91 Wickham, G.S. 99, 106, 107,129 Wiedemann. H.G.73,86 Wierzchos, J. 88 Wijers, B. 113, 133 Wijffelman, C.A. 146,216 Wilkinson, K.J. 78, YO Wilkinson. M.J. 104,131 Wilkinson, S.J. 49, 68,87 Willey, J.M. 294,336 Williams, A.W. 308, 331 Williams, ED. 310, 334 Williams, P. 120, 121. 135. 136 Williams, P.H. 54, 87 Willis, D.K. 194, 218 Willscher, S . 76.84 Wilson, L.M. 275,288 Wilson, M.J. 56, 69.85 Wilson, M.L. 303,336 Wilson, S.M. 108, 136 Winandy, J.E. 61.84 Winans, S.C. 120, 130, 140, 146,220,271,280 Winson, M.K. 121, 136 Witten, E.A. 194,223 Wobking, H. 78,80 Woese, C.R. 99, 136 Wohrer,W. 86 Wolf, A. 310, 316,331 Wolf, W.H. 276. 279

Wolf-Watz, H. 274,285 Wolfe, A.J. 195,225 Wolschek, M.F. 53,54,66,91 Wolterink. A. 106, 129 Wong, C.Y. 141,227 Wood, D.A. 54,55,56.61,63,82 Wood, P.M. 61,62,85.91 Wood, T.K. 119,134 Woods, D.R. 145,221 Woodward, D.E. 262,288 Worth, M.A. 31,41 Wozniak, D.J. 146,221 Wright, M. 144,215 Wu, J. 195,227 Wu, K. 119,134 Wu. S.H. 141, 145,227 Wu,Y.P. 104,131 Wurgler-Murphy. S.M. 143, 194,221,223,227 Wurtzel, E.T. 140, 146,222 Wyder, M.A. 104,131 Wylie. D. 141,227 Xie, D.X. 141. 145,216 XU,D.-B. 77.91 Xu, H.S. 96,98, 103, 128,136 Yamaguchi, S . 299, 301,305,306,309,329, 332,333,334,335,336

Yamakawa, K. 68,83.85 Yamamoto, K. 243,254,288 Yamashita, I. 299,336 Yamazaki, K. 106,137 Yamazaki, T. 195,201,225 Yanagida, T. 32 1,333 Yang, J. 57,92 Yang, M. 194,218 Ymg, X.-H. 264,275,285,288 Yang, Y. 146. 183, 195,227 Yano,M. 334 Yanofsky, M.F. 140, 146,220 Yao, R. 275,288 Yao, V.J. 264,288 Yarus, M.J. 13, 17, 27.28, 30, 31.44 Yasuda. R. 296,334 Yates, M.G. 145,221 Yeager, R. 113, 123,135 Yeh, J.I. 242,288 Yeh, K.C. 141, 145,227 Yigitoglu, M. 67, 92 Yoch, D.C. 270,289 Yoo, Y.J. 67, 81 Yoshida, M. 296,334 Yoshiyama, H. 254,284 Youderian, P. 236,260,281,288 Young, C.S. 14.26.45 Young,D.I. 102, 117, 121,133 Young, L.Y. 194,216

AUTHOR INDEX Young, M. 102, 117, 121,133,194,220 Yu, F.P.P. 103, 132 Yu,H. 146,227 Yu, N. 194,220 Yue, S.T. 104,135 Zabriskie, D.W. 18, 19.45 Zaglauer, A. 109,133 Zambrano, M.M. 12 1,137 Zanella, A. 71,78,80,88 Zehentgruber, 0. 66.86 Zennaro, E. 194,215 Zeremski, J. 11.42 Zetterqvist, 0. 143,226, 227 Zhang, W. 257,267,279 Zhang,Y. 106,134. 145,227 Zhang-Barber, L. 121,137 Zhao, J. 195,227 Zhao, X.L. 105, 129 Zha0.Y. 141,218,223

361 Zhelev, S. 69, 76. 80 Zheng, X.Y. 274,288 Zhou, H. 205,227 Zhou, J. 235,289,303.304.306,324,335,336, 337 Zhou, X.Z. 195,227 Zhulin, I.B. 267,286, 289 Ziegler, S.F. 140. 146,220 Zirnrnann, P. 183,227 Zimmer-Faust, R.K. 270,289 Zimmermann,F.K. 7.43 Zinda, M.J. 145,227 Zischek, C. 308,336 Zorzella, A. 5.41 Zuccarelli, A.J. 267, 286 Zunino, P. 275,282 Zuo, Y. 62, 92 Zusman, D.R. 145,221,236,260,261,284, 287,288,289,294,337

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Subject Index

Figure and table references are shown in italic. Acetaldehyde 5, 11, 22-3, 39 Acetoin 5 Agrobacterium tumefaciens 273 Alcaligenes 270 Alcohol dehydrogenase (ADH) 6,7, 10-13,21-3,25,26,32,39 and reaction by-products 9-1 1 Amino-acid residues, variability 198 Amyloporia xantha 55 Animal pathogens 274-6 Anion mobility 68-72 Aquatic environments 269-7 1 Aquijlex aeolicus 263 Arabidopsis 143, 194 Archaeoglobus 204.2 13 Arthroburter 118 As yet uncultured (AYU) bacteria 99-102 Aspergillus 77 Aspergillus niger 54,59,61,66-9,77,78 oxalate biosynthesis by 53 Azospirillum brasilense 273 Azotobacter 118 Bacillus 314 Bacillus megaterium 273 Bacillussubtilis 182, 183, 194, 197, 212, 213,256,259,306 Bacterial flagella synthesis genetics 309- 10 Bacterial flagellar filaments 295 Bacterial flagellar gene expression and assembly regulation 302 Bacterial flagellar motor 291-337 measured characteristics 323 models 322-8,324,325 Bacterial flagellar motor function 310-22 driving force for rotation 312-16 relationship between torque and rotational speed 320 reversibility 316-17 smoothness of rotation 321-2

torque versus rotation rate 317-20 Bacterial flagellar rotation, methods of measuring 310-12,311 Bacterial flagellar structure 296-310, 297 basal body 301 export apparatus 308-9 filament 298-9 hook 299-301 Bacterial flagellum 235-6 Bacterial swimming 233 patterns 237-8, 237,292,293,294,295 Bacterial tactic responses 229-89 in natural environment 269-76 Bacterial taxis, use of term 232-3 Bacterial viability 93-137 definition 95-6 Bacteriophages 108 Bacteriorhodopsin (BR) 263 Benzaldehyde 5, 8,9, 13, 17, 21-6, 29, 37,39 solubility modification 30-2 Benzyl alcohol 9, 10, 21, 22, 24, 27-9, 39 Biofilms 271-2 Bioremediation 76-8 Bordetella 276 Building materials, role of organic acids in corrosion 72-4 Caenorhabditis elegans 143 Calcium oxalate 55-61, 57, 73 Campylobacter jejuni 98, 274 Candida utilis 6-8, 10, 15, 19-24, 26, 32, 34, 38, 39 Capillary method 234 Carbonylcyanidetnchlorophenylhydrazone(CCCP) 295 Caulobacter crescentus 235,25 I , 256, 257,300 Cellobiose dehydrogenase (CDH) 62 Charged coupled device (CCD) cameras 109

364 CheA 238,239,244-7,249,253,255, 260.267 domain organization 245 CheA2 266 CheB 238,239,245,246,249,25 I, 266 CheC 259 CheD 259 Chemosensory protein combinations 256 CheR 238,239,25 1,259 Chew 239,244,245,253,255 CheW2 266 CheY 238,239,245-9,255,267,3 16 CheZ 238,239,247 Chlorochromatium aggregatum 270 Chromatiurn 233,234 Chmmatium salexigens 264 Citrate formation from glucose via anaplerotic CO, fixation 66 Citric acid fungal production 47-92 metal chemistry 50-3 role of metals in production 67-8 see also Organic acids Clostridium septicum 275 Cognate receiver domains 206-1 1 Coniophoru marwzorutu 55 Coniophora puteana 55,6 1 Coriolus versicolor 54, 55,61 Crabtree-negative yeasts 10 Crabtree-positiveyeasts 10 Culturability 93-1 37 as operational definition of viability 124, 125-6 conceptual and operational definitions 96.97 use of tkrm 95 Culturability tests adaptation and differentiation effects 115-17 ageing effect 113-15 cell-to-cell communication (quorum sensing) 120-2 environments affecting 124, 125-6 factors influencing outcome of 1 1 1-22 injury and recovery 1 12-1 3 lysogenic bacteriophages I 19-20 metabolic self-destruction 1 17-19 substrate-accelerateddeath 117-1 9 toxin-antitoxin systems 119-20 R-Cyclodextrin (BCD) 32 Cytochrome o-type oxidase complex 114 Cytophaga 294

Demethylsulfoniopropionate(DMSP) 270 Desuljovibrio vulgaris 256,267 2,4-Dichlorophenoxy acetic acid (2.4-D) 23

SUBJECT INDEX

Digital image analysis systems 109 N,N-Dimethylformamide(DMF) 3 1 DISTANCES program 197 DMSO 268 Domain shuffling 21 1-14 Ectothiorhodospira halophila 264 Electron acceptors 267-8 Ephedra spp. 3 Erwinia 273 Escherichia 1 18 Escherichia coli 112, 120, 141, 182, 197, 213, 232. 237, 292, 296,299, 303, 306,310,320 chemoreceptor dimer 241 chemoreceptors 240 chemosensory pathways 239,268 chemosensory signalling pathway 255 chemosensory system 238-63 homodimeric periplasmic domain of Tar 242 operon organisation 248,249 pattern formation 262 repellent sensing 254-5 themotaxis 254 Ethanol 11.23.24, 39 Fermentation process for L-PAC 11-34 Flagellum see Bacterial flagellum Flavobacterium (Cytophagaj johnsoniae 236 FlgM 309 FlhB 308 FliA 309 FliG 235,306,307 FliK 308 FliM 235, 246,247, 306, 307, 309, 316 FliN 235,306,307 Flow cytometry (FCM) 108-9 Fluorescence-activated cell sorting (FACS) 109 Fluorescence in situ hybridization (FISH) 107 Fluorescence methods for viability 102-3 overview 104 Fluorescence microscopy, developments in I09 Fomes annosus 54 Frz system 261 FrzA 261 FrzCD 261 Fungal oxalate in limestone biomineralization 74-6 Fungal production of organic acids 47-92 and metal biogeochemistry 68-76

SUBJECT INDEX

Gauteria monticola 7 1 Glyoxylate oxidation, oxalate biosynthesis by 54 Gram-positive bacteria 121 GROWTREE program 197

'H-nuclear magnetic resonance (NMR) spectroscopy 5 Haemophilus injluenzae 182 Halobacterium halobium 294 Halobacterium salinarium 244,256, 263, 267 photosensory transduction 265 Halorhodopsin (HR) 263 Hansenula polymorpha 10 Helicobacter pylori 255,274,275 Heterobasidium annosum 55 His-Asp phosphorelay systems 21 1-14 His-Asp phosphorelay systems 139 Histidine protein kinase (HPK) 140-82, 199 classification 192-3 domain subfamilies 210 homodimer 245 homologues 143 with substituted histidines 196 sensing domains 183 sequence analysis 143, 145-80 sequencing 140-1 subfamilies 197-206 sequence alignments1 84-91 superfamily 139-227 system design 182-94 see also specific HPK subfamilies HoWsoc programmed cell death system 1 I9 Homology boxes 141, 195-7,198, 199 Homoserine lactones (HSLs) 271-2 synthesis 275 Hook-associated proteins (HAPS) 299-301,309 HPK,, 197,206 HPK,, 197,206,210 HPK, 199-201 HPK;, 197 HPK,-HPK,, 197 HPK, 201 HPK; 201-4 HPK, 204 HPK, 204 HPK, 204-5,210,211 HPK, 205 HPK, 205.2 11 HPK, 197,205-6 Hysterangium crassum 7 1 Hysterangium separabile 59 Hysterangium setchellii 7 1

365

Kinase dendrographs 200 Klebsiella 1 18 Klebsiella aemgenes 117 Kogure tentative direct microscopic method of counting live bacteria 103-6 Lecanora atra 73 Light, responses to 263-6 Lignin peroxidase (UP) 63 Lignocellulose degradation 61-4 Limestone biomineralization, fungal oxalate in 74-6 L-PAC acidification of fermentation medium 37 biochemical production 4-1 1 bioconversion phase 34 choice of production strain 12 comparison of kinetic evaluations 28 effect of benzaldehyde solubility 30-2 effect of dissolved oxygen concentration on metabolism 14-15 effect of pH on cellular metabolism 15 effect of temperature on metabolism 15 fermentation process 11-34 immobilization of enzymes or biomass 26-30 industrial production process 34-9 methods for influencing production 33-4 nutrient effects in production 18-20 physical variables of fermentation 34 physiochemical production conditions 13-16 physiological condition of cells for optimum production 16-18 production by batch, fed-batch or continuous fermentation 20-1 production by yeast 1-45 production mechanism 4-5 reduction of toxic effects of substrate, product and by-product 23-33 role of nutrientslbuffering agents 24 substrate dosing 24-6 two-phase fermentation medium 32-3 use of additives to modify metabolic activity 21-3 Luminescence methods, overview 104 Lysogenic bacteriophages 1 19-20

Magnetotaxis 269 Manganese-dependent peroxidase (MnP) 63 MCPs 182,240 classical 259

366 clusters 257 cytoplasmic domains 2434, 249 cytoplasmic signalling 244-6 localization 25 1-2 receptors 256 structural differences 255 targeting to poles 252-3 transmembrane signalling 243 Metal biogeochemistry and fungal organic acid production 68-76 Metal biotechnology and organic acids 76-8 Metal chemistry, organic acids 50-3 Metal oxalates 60 solubility products 52 Metal recovery 76-8 Metal solubilization 68-72 for recovery and bioremediation 76-8 Methanococcus jannaschii 182,263 Methionine auxotrophs 238 Methyl-accepting chemotaxis proteins. See MCPs Micrococcus luteus 1 16, 117 Mitogen-activated protein (MAP) kinase pathway 194 Molecular approaches to viability 106-8 Monoraphidium braunii 73 Mot proteins 302-6 MotA 236 MotB 236 Multicomponent phospho-relays 194 Multi-sequence alignment I99 Mycobacteria 1 18 Mycobacterium genovense 101 Mycobacterium haemophilum 101 Mycobacterium leprae 101, 102, 121 Mycobacterium paratuberculosis 101 Mycobactenum tuberculosis 121 Mycoplasma genitalium 182 Myxococcus xanthus 236,260,261 NAD+ 23,25 a-Naphthoxy acetic acid (NAA) 23 Niacinamide 23 Nitrogen-fixingbacteria 272-3 Non-culturable cells 108, 111, 117 Not immediately culturable (NIC) CELLS 98-9, 116, 117, 122, 124 Nutrition in production of L-PAC 18-20 Organic acids and metal biotechnology 76-8 fungal production 47-92 and metal biogeochemistry 68-76 role in corrosion of stone and building materials 7 2 4 see also specific acids

SUBJECT INDEX

Osmotaxis 255 OxJate biosynthesis by A. niger 53 by glyoxylate oxidation 54 Oxalic acid biosynthesis 53-5 catabolism 65 fungal production 47-92 metal chemistry 50-3 metal complex formation 51 role in corrosion of stone and building materials 72 see also Organic acids Paxillus involutus 54,55,70,71 Pelochromatium roseum 270 Penicillium 77 Penicillium bilaii 69 Penicillium corylophilum 73 Penicillium simplicissimum 77-8 Periplasmic binding protein (PBP) 240 Pertusaria corallina 73 Phanerochaeie chrysosporium 54,55,61

L-Phenylacetylcarbino1.SeeL-PAC

Phosphorelay mechanism 194 Phosphorelay systems 144 Phosphorylated kinase I83 Phosphoserine 140 Phosphotransferasesugars 253-4 Photoactive yellow protein (PYP) 264 PILEUP program 197, 199 Pisolinthus tinctorius 70 Plant pathogenesis 64-5 Plant wound infection 273 Pleurotusflorida 55 Polyethylene glycol (PEG) 31 Pore fungus carbonate oxalate system

75

Poria placenta 55 Poria vaporaria 55 Prokaryotic divisions 181 Protein phosphorylation 139-40 Proteus mirabilis 275 Pseudomonas 273,294 Pseudomonas aeruginosa 237,293 Pseudomonas putida 257,273 Pseudomonas syringae 2 13 Pyruvate 5,25-6, 37 Pyruvate decarboxylase (PDC) 4-5, 14-17, 19,21,24-7, 32,37 and provision of substrates 6-9 Quorum sensing 120-2 Receiver dendrographs 200 Receiver domain subfamilies 210 Reporter gene-based studies 107, 108

SUBJECT INDEX

Resinium bicolor 58 Response regulators, classification 202-3.207-9 Reverse transcription and polymerase chain reaction (RT-PCR) 106 Reynold’s number 310,317 Rhizobium leguminosarum 2 13 Rhizobium meliloti 294 Rhodamine- 123 116 Rhodobacter sphaeroides 237,238, 244, 25 1-2,255-7,260,264,266,268, 272,293,294,299,300,306,310 chemosensory pathway 258 clustering of MCPs 250 operon organisation 248, 249 Rhodospin’llum centenum 266 Rhodospirillum rubrum 234, 295 Saccharomyces carlsbergensis 4 7 , 12, 17, 18 Saccharomyces cerevisiae 6-8, 10, 13-1 7, 20, 2 1,23-6,29-32 Saccharomyces spp. 5.7, 12 Salmonella 141,276,320 chemosensory pathways 268 Salmonella typhimurium 238,293, 298-300,303,306,3 I0 homodimeric periplasmic domain of Tar 242 pattern formation 262 Sclerotinia sclerotiorum 54, 64 Sclerotium rolfsii 54, 55 Serpula lacrymans 6 1 Serratia liquifaciens 275 Shigella 276 Sinorhizobium meliloti 235, 247,260 Solid-phase cytometry 109 Spirillum 237 Spirillum voluntans meliloti 237 Spirochaeta aurentia 293 Stone, role of organic acids in corrosion 72-4 Streptococcus 1 18,206,213, 3 I0,3 17 Switch complex (or C-ring) 235,306-8 Synechocystis 213

367

Temporarily non-culturable bacteria 98 Thioploca 269 Tlps 259 TMl 241,243 TM2 241,243 Toxin-antitoxin systems 1 19-20 Tricarboxylic acid (TCA) cycle 54,65, I14 Tropheryma whippelii 101-2 Tyromyces palustris 54 Valinomycin 296 VBNC hypothesis 9 6 9 , 118 Viability assessment at individual or community level 122-4 conceptual and operational definitions 96,97 developments in instrumentation 108-10 indirect assessments 110 microbiological usage 94 new methods of estimation 102-1 11 operational definition 97, 98 Viable but non-culturable hypothesis. See VBNC Vibrio alginolyticus 270, 296, 305, 3 13 Vibrio anguillarum 274 Vibrio cholera 274 Vibrio cholerae 98 Vibriopscheri 272 Vibrio haemolyticus 305 Vibrio vulni$cus 1 16, 117 Whipple’s disease 101 Xanthomonas 273

Yeast, L-phenylacetylcarbinol production 1-45

Yeast ADH (YADH) 11 Yersinia 276 Zymomonas mobilis 4,12

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