Advances in Immunology Volume 88

Contents

Contributors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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CD22: A Multifunctional Receptor That Regulates B Lymphocyte Survival and Signal Transduction Thomas F. Tedder, Jonathan C. Poe, and Karen M. Haas 1. 2. 3. 4. 5. 6. 7. 8. 9. 10.

Abstract. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . CD22 Expression . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . CD22 Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . CD22—A Receptor for Diverse Sialylated Ligands . . . . . . . . . . . . Effects of CD22 Engagement on B-Cell Activation and Function In Vitro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . CD22 Ligand Binding Regulates B-Cell Survival and Proliferation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The CD22 Cytoplasmic Domain Regulates B-Cell Signal Transduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . CD22-Directed Therapies and Clinical Trials in Oncology. . . . . . . CD22-Directed Therapies and Clinical Trials in Autoimmunity . . . Conclusions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1 2 3 4 5 7 8 15 28 30 36 37

Tetramer Analysis of Human Autoreactive CD4-Positive T Cells Gerald T. Nepom Abstract. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1. pMHC Tetramers Identify Human Autoreactive T Cells . . . . . . . . 2. Autoantigen pMHC Tetramers from Mouse to Man. . . . . . . . . . . . v

51 51 59

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3. Tetramer-Induced Autoreactivity . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Regulation of Phospholipase C-g2 Networks in B Lymphocytes Masaki Hikida and Tomohiro Kurosaki 1. 2. 3. 4. 5. 6. 7. 8. 9.

Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . From the BCR to PLC-g . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Roles for PLC-g . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Regulation of IP3 Receptors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Coupling Between Calcium Release and Calcium Influx . . . . . . . . Looking for Ca2þ Entry Channels . . . . . . . . . . . . . . . . . . . . . . . . . . NFAT and NF-kB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Modulation of Calcium Signaling . . . . . . . . . . . . . . . . . . . . . . . . . . . Concluding Remarks. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

73 73 74 78 79 81 83 86 88 89 90

Role of Human Mast Cells and Basophils in Bronchial Asthma Gianni Marone, Massimo Triggiani, Arturo Genovese, and Amato De Paulis 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12.

Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Human Mast Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Human Basophils . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Experimental Evidence for Mast Cells in Bronchial Asthma . . . . . Experimental Evidence for Basophils in Bronchial Asthma . . . . . . Mast Cell and Basophil Recruitment to Asthmatic Airways . . . . . . Anatomical and Functional Evidence for Mast Cells and Basophils in Asthma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Superallergens in Bronchial Asthma . . . . . . . . . . . . . . . . . . . . . . . . Angiogenesis in Bronchial Asthma . . . . . . . . . . . . . . . . . . . . . . . . . . Tissue Remodeling in Bronchial Asthma . . . . . . . . . . . . . . . . . . . . . Pharmacologic Modulation of Human Mast Cells and Basophils in the Treatment of Bronchial Asthma . . . . . . . . . . . . . . Conclusions and Implications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

97 97 101 109 116 117 118 119 121 127 128 130 136 138

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A Novel Recognition System for MHC Class I Molecules Constituted by PIR Toshiyuki Takai 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12.

Abstract. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . PIR and LILR in Ig-like Receptor Family . . . . . . . . . . . . . . . . . . . PIR Genes and Protein Structure . . . . . . . . . . . . . . . . . . . . . . . . . . Ligand for PIR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3D Structure of PIR and LILR and Their Interaction with MHC Class I . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Activation Signal via PIR-A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Inhibitory Signal via PIR-B . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Dominant Expression of PIR-B In Vivo . . . . . . . . . . . . . . . . . . . . . Pirb–/– B Cells, Neutrophils, and Macrophages are Hyperresponsive. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Modulated Cytokine Signaling in PIR-B Deficiency . . . . . . . . . . . . PIR in Transplantation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

161 161 163 166 169 171 174 176 177 178 180 182 186 187

Dendritic Cell Biology Francesca Granucci, Maria Foti, and Paola Ricciardi-Castagnoli 1. 2. 3. 4. 5. 6.

Abstract. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . DC Subtypes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Deciphering DC Biology with Genomic Approaches . . . . . . . . . . . DC Interactions with the Microbial World . . . . . . . . . . . . . . . . . . . DC Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

193 193 194 196 199 209 219 219

The Murine Diabetogenic Class II Histocompatibility Molecule I-Ag7: Structural and Functional Properties and Specificity of Peptide Selection Anish Suri and Emil R. Unanue Abstract. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 235 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 235

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2. Structural Features of I-Ag7 and DQ8 . . . . . . . . . . . . . . . . . . . . . . . 3. Biochemical Basis of Peptide Selection by I-Ag7 . . . . . . . . . . . . . . . 4. Why Is There a Difference in Results Between Binding and Peptide Selection? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. The Biological Role of I-Ag7 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

236 241 254 256 259

RNAi and RNA-Based Regulation of Immune System Function Dipanjan Chowdhury and Carl D. Novina 1. 2. 3. 4. 5. 6. 7. 8.

Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Short RNAs in the Mammalian Immune System . . . . . . . . . . . . . . miRNAs in Mammalian Virus Infection. . . . . . . . . . . . . . . . . . . . . . RNAi, NMD, and TCR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . NMD and TCR Expression . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . RNAi and NMD Are Genetically Linked . . . . . . . . . . . . . . . . . . . . RNAi, ADARs, and Viruses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

267 267 271 273 274 276 278 280 284 286

Index. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 293 Contents of Recent Volumes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 305 Color Plate Section

Contributors

Numbers in parenthesis indicated the pages on which the authors’ contributions begin.

Dipanjan Chowdhury (267), Center for Blood Research and Department of Pediatrics, Harvard Medical School, Boston, Massachusetts 02115 Maria Foti (193), Department of Biotechnology and Bioscience, University of Milano-Bicocca, Piazza della Scienza 2, 20126 Milan, Italy Arturo Genovese (97), Division of Clinical Immunology and Allergy, Center for Basic and Clinical Immunology Research (CISI), University of Naples Federico II, School of Medicine, I-80131 Naples, Italy Francesca Granucci (193), Department of Biotechnology and Bioscience, University of Milano-Bicocca, Piazza della Scienza 2, 20126 Milan, Italy Karen M. Haas (1), Department of Immunology, Duke University Medical Center, Durham, North Carolina 27710 Masaki Hikida (73), Laboratory for Lymphocyte Differentiation, RIKEN Research Center for Allegy and Immunology, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan Tomohiro Kurosaki (73), Laboratory for Lymphocyte Differentiation, RIKEN Research Center for Allergy and Immunology, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan Gianni Marone (97), Division of Clinical Immunology and Allergy, Center for Basic and Clinical Immunology Research (CISI), University of Naples Federico II, School of Medicine, I-80131 Naples, Italy Gerald T. Nepom (51), Benaroya Research Institute at Virginia Mason, Seattle, Washington 98101 Carl D. Novina (267), Cancer Immunology and AIDS, Dana-Farber Cancer Institute, Boston, Massachusetts 02115; Department of Pathology, Harvard Medical School, Boston, Massachusetts 02115 Amato De Paulis (97), Division of Clinical Immunology and Allergy, Center for Basic and Clinical Immunology Research (CISI), University of Naples Federico II, School of Medicine, I-80131 Naples, Italy ix

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Jonathan C. Poe (1), Department of Immunology, Duke University Medical Center, Durham, North Carolina 27710 Paola Ricciardi-Castagnoli (193), Department of Biotechnology and Bioscience, University of Milano-Bicocca, Piazza della Scienza 2, 20126 Milan, Italy Anish Suri (235), Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, Missouri 63110 Toshiyuki Takai (161), Department of Experimental Immunology and CREST Program of the Japan Science and Technology Agency, Institute of Development, Aging, and Cancer, Tohoku University, Sendai 980-8575, Japan Thomas F. Tedder (1), Department of Immunology, Duke University Medical Center, Durham, North Carolina 27710 Massimo Triggiani (97), Division of Clinical Immunology and Allergy, Center for Basic and Clinical Immunology Research (CISI), University of Naples Federico II, School of Medicine, I-80131 Naples, Italy Emil R. Unanue (235), Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, Missouri 63110

CD22: A Multifunctional Receptor That Regulates B Lymphocyte Survival and Signal Transduction Thomas F. Tedder, Jonathan C. Poe, and Karen M. Haas Department of Immunology, Duke University Medical Center, Durham, North Carolina 27710

1. 2. 3. 4. 5. 6. 7. 8. 9. 10.

Abstract ........................................................................................................... Introduction ..................................................................................................... CD22 Expression............................................................................................... CD22 Structure................................................................................................. CD22—A Receptor for Diverse Sialylated Ligands .................................................. Effects of CD22 Engagement on B‐Cell Activation and Function In Vitro .............................................................................................. CD22 Ligand Binding Regulates B‐Cell Survival and Proliferation.............................. The CD22 Cytoplasmic Domain Regulates B-Cell Signal Transduction ........................ CD22‐Directed Therapies and Clinical Trials in Oncology......................................... CD22-Directed Therapies and Clinical Trials in Autoimmunity .................................. Conclusions ...................................................................................................... References .......................................................................................................

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Abstract Recent advances in the study of CD22 indicate a complex role for this transmembrane glycoprotein member of the immunoglobulin superfamily in the regulation of B lymphocyte survival and proliferation. CD22 has been previously recognized as a potential lectin‐like adhesion molecule that binds a2,6‐linked sialic acid‐bearing ligands and as an important regulator of B‐cell antigen receptor (BCR) signaling. However, genetic studies in mice reveal that some CD22 functions are regulated by ligand binding, whereas other functions are ligand‐independent and may only require expression of an intact CD22 cytoplasmic domain at the B‐cell surface. Until recently, most of the functional activity of CD22 has been widely attributed to CD22’s ability to recruit potent intracellular phosphatases and limit the intensity of BCR‐generated signals. However, a more complex role for CD22 has recently emerged, including a central role in a novel regulatory loop controlling the CD19/CD21‐Src‐family protein tyrosine kinase (PTK) amplification pathway that regulates basal signaling thresholds and intensifies Src‐family kinase activation after BCR ligation. CD22 is also central to the regulation of peripheral B‐cell homeostasis and survival, the promotion of BCR‐induced cell cycle progression, and is a potent regulator of CD40 signaling. Herein we discuss our current understanding of how CD22 governs these complex and overlapping processes, how alterations in these tightly controlled regulatory activities may influence

1 advances in immunology, vol. 88 # 2005 Elsevier Inc. All rights reserved.

0065-2776/05 $35.00 DOI: 10.1016/50065-2776(05)88001-0

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autoimmune disease, and the current and future applications of CD22‐directed therapies in oncology and autoimmunity. 1. Introduction B lymphocytes are the central mediators of humoral immunity. They differentiate through highly regulated pathways before becoming mature plasma cells that secrete antigen (Ag)‐specific antibody. B cells depend on cues from their extracellular microenvironment for development, homeostasis, activation, proliferation, and effector function. These functions are regulated through cell surface molecules that generate transmembrane signals, regulate intercellular communication, and direct lymphocyte localization within tissues. These events are thought to primarily rely on signals generated by the B‐cell Ag receptor (BCR) composed of membrane immunoglobulin (Ig) noncovalently associated with disulfide‐linked CD79a/CD79b (Iga/Igb) heterodimers. Multiple other signaling molecules also provide important functional links between the cell surface and intracellular signaling (Tedder, 1998). CD22 and CD19 represent two specialized costimulatory or coreceptor cell surface molecules (Buhl and Cambier, 1997; Cyster and Goodnow, 1997; Nitschke and Tsubata, 2004; O’Rourke et al., 1997; Tedder et al., 1997a) that also function as ‘‘response regulators’’ (Tedder, 1998) to modulate the intensity, quality, and duration of homeostatic and BCR‐induced signals (Fujimoto et al., 1998; Sato et al., 1998). Response regulators carry out broader functions than costimulatory molecules because they establish intrinsic signaling thresholds that provide a context for other transmembrane and cytoplasmic signals. CD22 is also a lectin‐like member of the Ig superfamily expressed exclusively by all mature B‐lineage cells, which binds ligands in vivo to regulate BCR and CD19 signal transduction, and provide essential survival signals. In the current review, we describe a critical role for CD22 in regulating normal B‐cell function, CD19 and BCR signal transduction, BCR‐induced cell death, and the homeostatic survival of B cells in the periphery. These complex processes are differentially regulated by CD22 binding to its ligands or by intrinsic CD22 activity which functions independently of ligand engagement. Thus, CD22 is a multifunctional receptor that employs ligand‐dependent and -independent mechanisms to ultimately regulate the generation of physiologically relevant responses to foreign or self‐antigens (Ags) and govern events critical for B‐cell selection, activation, and differentiation. Because CD22 provides an important regulatory checkpoint for adjusting B‐cell function and survival, understanding CD22 function may provide mechanisms for modulating humoral immunity and treatments for malignancies or autoimmunity.

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2. CD22 Expression CD22 expression is B‐cell‐specific and developmentally regulated in mice and humans (Fig. 1). Mouse CD22 (mCD22) was first identified as the Lyb‐8.2 Ag immunoprecipitated from mouse splenocytes as 95 and 105 kDa glycoproteins (Symington et al., 1982). Mouse CD22 is absent or expressed at low levels on the surface of pre‐B cells and newly emerging IgMþ B cells, is present at low density on immature (B220lo IgMhi) B cells, and is fully expressed by mature recirculating (B220hi IgMint IgDþ) B cells (Erickson et al., 1996). Once in the periphery, mCD22 is expressed at high levels on all B‐cell subsets. mCD22 expression increases slightly on mitogen‐stimulated B cells, but is lost during plasma cell differentiation. Human CD22 (hCD22) expression is restricted to the cytoplasm of pro‐B and pre‐B cells, and its localization shifts to the cell surface simultaneously with IgD expression (Do¨ rken et al., 1986). The vast majority of human IgMþ IgDþ B cells express cell surface CD22. In lymphoid tissues, hCD22 is expressed by follicular mantle and marginal zone (MZ) B cells, but only weakly by germinal center B cells. Upon B‐cell activation,

Figure 1 CD22 gene and protein organization, chromosome location, and protein expression during B‐cell development and activation. Ig‐like domains 1 and 2 contain the ligand‐binding region of CD22. Various effector molecules are recruited to the CD22 cytoplasmic domain when phosphorylated on one or more of six conserved tyrosine residues, several of which lie within consensus ITIM motifs in humans and mice. CD22 is expressed on the surface of mature B cells (B) within lymphoid follicle marginal zones, mantle zones, and germinal centers, but not by T cells (T), monocytes (M), neutrophils (N), red blood cells (RBC), platelets (P), or dendritic cells (DC).

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hCD22 mRNA and protein expression increase during the first 2 days of culture with mitogens, followed by a marked loss of hCD22 by 3–4 days (Do¨ rken et al., 1986; Wilson et al., 1991). Interestingly, in contrast to human adult blood B cells, neonatal cord blood B cells downregulate CD22 protein expression following BCR activation, but upregulate CD22 expression following anti‐CD40 þ IL‐4 stimulation (Viemann et al., 2000). Thus, CD22 expression may be differentially regulated depending upon the activation stimuli as well as the responding B cell. As with mCD22, hCD22 expression ceases with B‐cell differentiation into plasma cells. 3. CD22 Structure The initial isolation of cDNAs encoding CD22 revealed it to be composed of five Ig domains (Stamenkovic and Seed, 1990). Subsequently, a CD22 cDNA encoding two additional Ig domains and a full‐length 141 amino acid cytoplasmic tail was isolated (Wilson et al., 1991). The five Ig domain form of CD22 was subsequently termed CD22a, while the seven Ig domain form was termed CD22b (Stamenkovic et al., 1991). Both cDNA isoforms result from differential splicing within a single gene, with the removal of domains three and four in the CD22a form (Wilson et al., 1993). However, the seven Ig domain form of CD22 is the dominant mRNA and protein species, although a variety of rare hCD22 mRNA transcripts lacking Ig domains 3 and/or 4 can be isolated from B‐cell lines (Engel et al., 1995a). mCD22 is also composed of seven Ig domains, and is 62% identical in overall amino acid sequence with hCD22 (Torres et al., 1992). The highest level of conservation (70%) is found between the seventh Ig domains, although the 140 amino acid cytoplasmic domain and the transmembrane domains are 68% identical in sequence. CD22 in humans and mice consists of a single amino‐terminal V‐set Ig domain and six C‐2‐set Ig domains (Engel et al., 1995a; Torres et al., 1992; Wilson et al., 1991). The hCD22 and mCd22 genes have at least 15 exons (Law et al., 1993; Wilson et al., 1993). Exons 4–10 encode single Ig domains; exons 11–15 encode transmembrane and cytoplasmic domains (Fig. 1). Immunoprecipitated cell surface hCD22 generally appears as a two chain glycoprotein of 140 and 130 kDa (Boue and LeBien, 1988a,b; Do¨ rken et al., 1986; Schwarting et al., 1985; Schwartz‐Albiez et al., 1991). Although initially proposed by some to be a heterodimer, the relative intensity of the lower Mr band of hCD22 is consistently less, and varies considerably depending on the cell source examined (Engel et al., 1995a). Immunoprecipitation studies with monoclonal antibodies (mAbs) reactive with different Ig domains revealed that the 140 kDa, seven Ig domain form of hCD22 is the predominant protein species expressed on the cell surface (Engel et al., 1995a). The lower

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Mr band variably observed in CD22 immunoprecipitations lacks domain 4, while a 120 kDa protein (<1%) that may represent CD22a is barely detectable in immunoprecipitations from some surface‐labeled B‐cell lines. Thus, the CD22 splice variants previously postulated to possess unique ligand binding activities are not present on the surface of B cells in significant amounts. Therefore, cell surface hCD22 and mCD22 are predominantly monomeric seven Ig domain molecules with identical ligand‐binding regions (Engel et al., 1995a; Law et al., 1995). CD22a and CD22b were originally proposed to bind different ligands via distinct domains within each splice variant. However, a large panel of function‐ blocking anti‐hCD22 mAbs were found to only bind epitopes localized to the first and/or second Ig‐like domains (Engel et al., 1995a). Using domain‐swap and domain‐deletion mutants of hCD22, these two amino‐terminal domains were the functional unit mediating CD22 adhesion with ligands on lymphocytes, neutrophils, monocytes, and erythrocytes. That adhesion‐blocking CD22 mAbs only bound Ig domains 1 and 2 contrasted markedly with domain mapping studies by others that reported broadly distributed CD22 ligand‐ binding sites for CD45RA and other ligands. This discrepancy led to the demonstration that soluble glycoconjugates in mouse ascites fluid are potent inhibitors of CD22 adhesion (Engel et al., 1993). Thus, the early studies of CD22 function and adhesion were misleading because soluble factors in ascites fluid were blocking CD22 function rather than the receptor‐specific mAb present in the ascites fluid. Nonetheless, it was clear that hCD22 represented a novel prototype member of the Ig superfamily that binds sialic acid– bearing ligands through its amino‐terminal Ig‐like domains. Mouse CD22 also uses its two amino‐terminal Ig domains for ligand binding, which are 55% identical in amino acid sequence with hCD22 (Law et al., 1995). 4. CD22—A Receptor for Diverse Sialylated Ligands In vitro studies have demonstrated a role for CD22 as a potent intercellular adhesion molecule in cell–cell interactions, recognizing N‐linked oligosaccharides possessing a2‐6‐linked sialic acid residues (Engel et al., 1993; Stamenkovic and Seed, 1990). Mouse CD22 is specific for ligands composed of a2,6‐linked N‐glycolylneuraminic acid (NeuGc), whereas humans only express CD22 ligands in the form of N‐acetylneuraminic acid (NeuAc) (Kelm et al., 1994; Powell and Varki, 1994; Powell et al., 1993; Sgroi et al., 1993). Thus, when expressed at high levels in ectopic cells, CD22 binds a variety of ligands that are broadly distributed on erythrocytes, T and B lymphocytes, neutrophils, and monocytes (Engel et al., 1993). Ligands have also been identified using CD22‐Ig fusion proteins, which bind to a diverse array of

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leukocytes and nonlymphoid cells. A unifying feature is that all CD22 ligands are sialic acid‐dependent, since CD22 ligand binding is eliminated by treating lymphoid and nonlymphoid target cells with neuraminidase (Engel et al., 1995a). In fact, b‐galactoside a2,6‐sialyltransferase has been identified as a golgi enzyme necessary for the generation of CD22 ligands as well as the HB‐6, CDw75, and CD76 leukocyte differentiation Ags (Bast et al., 1992; Munro et al., 1992). CD22 is now recognized as a member of the ‘‘sialoadhesin’’ or ‘‘SIgLec’’ subclass of the Ig superfamily whose members function as mammalian lectins (Engel et al., 1993; Kelm et al., 1994). The sialoadhesin family includes multiple other sialic acid‐binding receptors such as sialoadhesin, a differentiation Ag of monocytes (Crocker et al., 1994), and CD33, a differentiation Ag of myeloid progenitor cells (Simmons and Seed, 1988). CD22 ligands identified in vitro include structurally diverse sialic acid‐bearing molecules expressed by lymphocytes, neutrophils, monocytes, and erythrocytes as well as nonhematopoietic cells (Tedder et al., 1997b). Ligands identified using in vitro assays and CD22‐Ig fusion proteins, include glycoproteins, glycolipids, and gangliosides. Specific examples include CD22 itself, all isoforms of CD45, soluble IgM pentamers, haptoglobin, Ly‐6 proteins, and a variety of other diverse proteins present on leukocyte cell surfaces (Hanasaki et al., 1995; Pflugh et al., 2002; Stamenkovic et al., 1991). CD22 is also reported to bind cell surface Ig with 0.2–2% of surface Ig physically associated with immunoprecipitated cell surface CD22 (Leprince et al., 1993; Peaker and Neuberger, 1993). Whether this association is direct through the extracellular or intracellular CD22 domains or is through intermediate bridging molecules remains unknown. It is also unknown whether any of the ligands identified in vitro represent physiologic in vivo ligands, although important physiologic roles for CD22 ligand binding have been recently identified (Poe et al., 2004a). While CD22‐mediated adhesion is readily visualized during in vitro assays when CD22 is overexpressed in cell lines (Engel et al., 1993, 1995a; Stamenkovic and Seed, 1990), cis interactions between CD22 and other B‐cell surface sialoglycoproteins have been suggested to result in the occupancy or ‘‘masking’’ of CD22 on most primary mature B cells (Jin et al., 2002; Kelm et al., 2002; Razi and Varki, 1998). CD22 masking is proposed to downregulate positive signaling via cell surface receptors such as IgM and CD45, preventing B‐cell hyperactivation. However, CD22 masking is a reversible process, occurs independent of CD45 expression, and does not prevent the recruitment of CD22 to sites of cell–cell contact (Collins et al., 2004). Moreover, the presence of cell surface sialic acids does not affect the rate of CD22 internalization or interfere with CD22 interactions with CD45 or IgM (Zhang and Varki, 2004). ‘‘Unmasking’’ of some CD22 molecules also occurs following B‐cell sialidase

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treatment or costimulation via CD40, which may relieve CD22 negative regulation of BCR signaling within germinal centers or other microenvironments (Razi and Varki, 1998). CD22 unmasking has also been proposed to regulate the migration of mature recirculating B cells to the bone marrow by promoting trans interactions with ligands expressed on bone marrow endothelium (Floyd et al., 2000; Nitschke et al., 1999), although conclusions drawn from mice expressing CD22 receptors unable to bind ligands argue against this (Poe et al., 2004a). 5. Effects of CD22 Engagement on B‐Cell Activation and Function In Vitro Various roles for CD22 adhesion have been suggested, including tissue localization, serving as a sensing mechanism for neighboring leukocytes, and as a regulator of signaling. In vitro analyses have suggested that CD22 binding to sialic acid‐bearing ligands positively influences B‐cell function. For example, the simultaneous addition of CD22 mAbs and anti‐Ig antibodies to human B‐cell cultures results in more potent B‐cell proliferation than either antibody added alone (Pezzutto et al., 1987). Treatment of B cells with a solid‐phase CD22 mAb prior to anti‐Ig stimulation also enhances proliferation and reduces the concentration of anti‐Ig antibody needed for an equivalent response without anti‐CD22 mAb pretreatment (Doody et al., 1995). Anti‐CD22 mAb binding prior to BCR engagement also enhances the increase in [Ca2þ]i observed following surface IgM cross‐linking (Pezzutto et al., 1988). In contrast, extensive CD22 cross‐linking by mAbs induces B‐cell apoptosis and potentiates anti‐IgM antibody‐induced apoptosis in malignant B cells (Chaouchi et al., 1995). Therefore, CD22 ligation generates costimulatory signals in some assay systems and apoptotic signals in others. We have also used mAbs reactive with the ligand‐binding domains of hCD22 to assess the role of CD22 in B‐cell function. Several mAbs, such as HB22‐7 and HB22‐23, stimulate potent human B‐cell proliferation directly, even in the absence of BCR ligation (Tuscano et al., 1996a). When added to costimulation assays, the HB22‐7 mAb synergizes with anti‐IgM antibodies, interleukin‐2 (IL‐2), IL‐4, or CD40 mAb to significantly augment B‐cell proliferation. Even more striking levels of B‐cell proliferation occur under culture conditions that enhance B‐cell–B‐cell interactions. Binding of the HB22‐7 mAb also augments B‐cell differentiation and triggers predominantly IgG secretion when added with IL‐2 to B‐cell cultures. By contrast, a CD22 mAb that minimally inhibits ligand binding, HB22‐5, poorly costimulates B‐ cell function. Ligation of CD22 with either the HB22‐7 or HB22‐23 mAb results in rapid CD22 tyrosine phosphorylation and in increased association of

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CD22 with Lyn, the p85 subunit of PI 3‐kinase, and Syk (Tuscano et al., 1996b). The HB22‐5 mAb has modest effects on CD22 phosphorylation. It has also been postulated that CD22‐binding to ligands on T cells regulates T‐cell function (Aruffo et al., 1992; Stamenkovic et al., 1991; Tuscano et al., 1996a). For example, inhibition of B‐cell CD22 binding to its ligand on T cells by receptor blockade with the HB22‐7 mAb significantly impairs T‐cell proliferation in costimulatory assays (Tuscano et al., 1996a). Thus, ligand binding by CD22 may provide stimulatory signals for B cells and provide costimulatory signals for T‐cell proliferation. Several studies using in vitro analyses also suggest that CD22 binding to sialic acid‐bearing ligands negatively influences B‐cell function. In one recent and provocative study, B‐cell activation by Ag‐expressing target cells that coexpressed a2‐6‐sialoglycoconjugates was suppressed only when CD22 was expressed on the B‐cell surface, with the degree of B‐cell activation determined by the upregulation or downregulation of important cell surface molecules (Lanoue et al., 2002). The authors concluded that negative regulation through CD22 dampens B‐cell reactivity to self‐Ags, preventing the activation of autoreactive B cells. In two other recent articles, the effects of CD22 ligand binding on BCR‐induced [Ca2þ]i responses and SHP1 recruitment to tyrosine‐phosphorylated CD22 were evaluated. In the first study, cDNAs encoding mutant CD22 molecules lacking ligand‐binding activity were expressed in a CD22‐ deficient B‐cell line (Jin et al., 2002). Following BCR ligation, B‐cell lines expressing mutated CD22 molecules had larger BCR‐induced [Ca2þ]i responses compared to lines expressing wild‐type CD22. Enhanced [Ca2þ]i responses correlated with decreased CD22 phosphorylation and recruitment of SHP1. In the second study, a sialic acid‐based inhibitor that selectively prevented hCD22 from binding to sialic acid‐bearing ligands expressed on other B cells also resulted in augmented [Ca2þ]i responses and decreased CD22 phosphorylation/SHP1 recruitment following BCR ligation (Kelm et al., 2002). Although these in vitro studies are useful, they depend on altered cell lines and mimetics that may not recapitulate physiologic CD22 engagement. Therefore, understanding the physiologic significance and consequences of blocking CD22 ligand binding in vivo is critical for understanding CD22 function and its regulatory role in B‐cell development. 6. CD22 Ligand Binding Regulates B‐Cell Survival and Proliferation Newly generated B cells express CD22 as they mature to acquire positive BCR signaling responses (Fig. 2). This represents a critical transition in B‐cell maturation since interactions between CD22 and its ligands in vivo are now known to be crucial for mature B‐cell survival upon entry into the periphery,

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Figure 2 CD22 and CD40 provide essential overlapping signals for B‐cell survival and proliferation. The stages of expression of CD22 and CD40 are indicated, along with stages of expression at which signaling through these receptors regulates B‐cell homeostasis and/or activation.

in addition to regulating BCR‐induced proliferation (Poe et al., 2004a; Sato et al., 1998). 6.1. B‐Cell Survival in CD22

/

Mice

Four independent lines of CD22 / mice have been generated (Nitschke et al., 1997; O’Keefe et al., 1996; Otipoby et al., 1996; Sato et al., 1996a). Immature B‐cell numbers are normal in the bone marrow of CD22 / mice consistent with low‐level surface expression of CD22 at this stage of development (Fig. 1). However, one characteristic feature of CD22 / mice is 66% reduced numbers of circulating IgMþ B220þ B cells in blood and bone marrow (recirculating pool) relative to wild‐type littermates (Sato et al., 1996a). One of the most important feature of CD22 / B cells is their shorter lifespan, with enhanced apoptosis (Nitschke et al., 1997; Otipoby et al., 1996; Poe et al., 2004a). Despite this, B‐cell turnover is closely matched with B‐cell production in the bone marrow since only small changes in B‐cell subpopulations are observed in peripheral lymphoid tissues, with an increased frequency of peritoneal B‐1 B cells (O’Keefe et al., 1996; Sato et al., 1996a). Serum IgM levels are slightly (40%) increased in CD22 / mice, although other isotypes and humoral immune responses to T‐cell‐dependent Ags are normal (Sato et al., 1996a, 1998). Immune responses to T‐cell‐independent Ags are slightly decreased in CD22 / mice (Nitschke et al., 1997; Otipoby et al., 1996; Sato et al., 1996a). Thus, CD22 plays an important role in regulating mature B‐cell

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activation, effector function, and survival in vivo, but its loss does not have dramatic effects on early B‐cell development, maturation or differentiation. 6.2. CD22 Ligand Binding Regulates B‐Cell Survival and Proliferation Studies conducted with CD22 / mice have been unable to address the importance of CD22 ligand binding in regulating CD22 function. Therefore, to directly assess the relevance of CD22 ligand binding in B‐cell activation and survival, two lines of mice expressing mutant CD22 receptors incapable of ligand binding were generated, CD22D1‐2 and CD22AA (Poe et al., 2004a). CD22D1‐2 mice express a truncated form of CD22 lacking the two amino‐ terminal Ig domains required for ligand binding (Fig. 3). CD22AA mice express CD22 containing two point mutations (Arg130 to Ala130, Arg137 to Ala137) in the amino terminal Ig domain that results in the loss of CD22 ligand‐binding ability (van der Merwe et al., 1996). Mature naı¨ve peripheral B cells and mature recirculating bone marrow B cells in CD22 / , CD22D1‐2, and CD22AA mice have equally high in vivo turnover rates (Poe et al., 2004a). The effect of this high rate of B‐cell turnover on the peripheral B‐cell repertoire is currently unknown. CD22 ligand binding may also regulate B‐cell proliferation following Ag exposure as B cells from CD22 / , CD22D1‐2, and CD22AA mice exhibit a delayed proliferative response following in vitro stimulation with mitogenic F(ab0 )2 anti‐IgM antibodies (Poe et al., 2004a). Thus, CD22 interactions with its ligands are important for the regulation of B‐cell survival and proliferation. CD22 / B cells from mice with a C57BL/6 genetic background undergo dramatically higher rates of apoptosis than B cells from wild‐type littermates,

Figure 3 Ligand‐dependent and ligand‐independent functions of CD22 in vitro and in vivo. Protein structure of CD22 proteins produced in CD22AA and CD22D1–2 mice are illustrated.

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while CD22 / B cells from mice with a mixed B6x129 genetic background only undergo apoptosis at slightly higher rates than wild‐type littermates. Although the genetic factors that account for this difference are currently unknown, biochemical studies have shed some light on these dramatic distinctions in the effects of CD22‐deficiency. There is a dramatic absence of lymphoblast formation in splenic C57BL/6 CD22 / B‐cell cultures after anti‐IgM treatment for 48 hr, along with a parallel increase in the percentage of apoptotic cells (Poe et al., 2004b). That CD22 / B cells predominantly respond to BCR‐induced signals by undergoing apoptosis may relate to the finding that CD22 regulates c‐Myc expression following BCR stimulation. B cells from CD22 / mice with a C57BL/6 genetic background do not upregulate c‐Myc transcriptional activity following BCR engagement (Poe et al., 2004b). As a consequence, CD22 / B cells are unable to induce Cullin 1 (Cul1), a c‐Myc‐dependent ubiquitin ligase complex scaffolding protein whose expression is required for cell cycle progression from G1 to S‐phase of the cell cycle (Dealy et al., 1999; O’Hagan et al., 2000; Zheng et al., 2002). In the absence of Cul1 expression, the proper formation of SCF/ubiquitin ligase complexes is disrupted, resulting in defective ubiquitination and degradation of cyclin‐dependent kinase inhibitors such as p27Kip1 and p21Cip1, which are critical for progression past the G1 checkpoint (O’Hagan et al., 2000; Shirane et al., 1999; Yu, Gervais, and Zhang, 1998). Follicular B cells also have high rates of apoptosis in these mice, particularly among MZ B cells. Increased numbers of apoptotic B cells is a unique property of CD22 / splenocytes because hyporesponsive B cells from CD19 / mice and hyperresponsive B cells from mice that overexpress CD19 undergo apoptosis at the same rates as wild‐type B cells (Poe et al., 2001). These data thereby indicate that CD22 / B cells in the context of a C57BL/6 background predominantly respond to BCR‐induced signals by undergoing apoptosis. Thereby, newly generated B cells unable to express CD22 in vivo may be unable to respond positively to BCR signals and mature as they enter the periphery. 6.3. CD40 Rescues B‐Cell Survival in the Absence of CD22 Engagement Like CD22, other B‐cell surface receptors also generate survival signals, including CD40 (Gordon, 1995). CD40 costimulatory signals are dominant to the death signals initiated by BCR ligation in vitro and rescue B cells from apoptosis within germinal centers (Castigli et al., 1994; Kawabe et al., 1994; Tsubata et al., 1993). Importantly, CD40 engagement rescues CD22 / B cells from BCR‐induced cell death (Poe et al., 2004b), indicating that CD22 / B cells are not preprogrammed to undergo cell death. Also, CD40 ligation alone

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induces the dramatic expansion of both wild‐type and CD22 / B cells into lymphoblasts and enhances the proliferation of BCR‐stimulated CD22 / cells. Thus, CD22 expression positively regulates mature B‐cell survival, suggesting that CD22 expression promotes the survival of the peripheral pool of naı¨ve B cells before CD40 engagement (Fig. 2). Importantly, B cells from CD22D1‐2 and CD22AA mice are also hyperproliferative to stimulation with mitogenic antibodies against CD40 (Poe et al., 2004a,b). These results suggest that CD22 may negatively regulate B‐cell stimulation or aberrant B‐cell activation during T‐cell‐dependent immune responses in which CD40 signaling is crucial. However, in the absence of both CD22 ligand binding and CD40 ligation, mature B cells may not receive the appropriate survival signals and undergo apoptosis as a consequence of BCR engagement. 6.4. CD22 Ligand Binding Regulates Cell Surface CD22 Expression CD22 undergoes constitutive internalization followed by degradation in an acidic intracellular compartment without detectable recycling of the molecule back to the cell surface (Shan and Press, 1995). Ligation of the CD22 molecule with mAbs markedly accelerates internalization and downmodulates surface Ag expression, but does not accelerate CD22 degradation (Press et al., 1989; Shan and Press, 1995; Shih et al., 1994). The kinetics of CD22 internalization (t1/2 < 1 h) in B‐cell lines and degradation (t1/2 8 h) are similar to those reported for the epidermal growth factor receptor, another terminally internalized cell surface receptor (Shan and Press, 1995). BCR ligation and intracellular kinase activation does not appear to affect the constitutive endocytosis of CD22. Interestingly, CD22 mAb binding results in rapid internalization of 80% of bound CD22 mAbs, followed by a plateau phase with apparent retention of 20% of the mAb on the cell surface (Shan and Press, 1995). Constitutive internalization of CD22 also shows biphasic internalization kinetics. This suggests the presence of a recycling pool of CD22 or the existence of two distinct pools of cell surface CD22 with different internalization and degradation kinetics. It is possible that CD22 retained on the cell surface following mAb engagement represents molecules that have engaged appropriate ligands and are thereby retained. Support for this hypothesis comes from CD22AA and CD22D1‐2 B cells (Poe et al., 2004a). Mutant CD22 expression by mature spleen and bone marrow B cells is reduced in both CD22D1‐2 and CD22AA mice. It is possible that the absence of ligand binding increases CD22 turnover since cell surface CD22 is constitutively endocytosed. Similar incremental reductions in cell surface CD22 expression by CD22D1‐2 and CD22AA B cells are unlikely to result from structural alterations in these two independently

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targeted genes and the two mutant molecules are quite different. In addition, preliminary semi‐quantitative RT‐PCR analysis suggests that CD22 transcription is normal in CD22D1‐2 and CD22AA spleen B cells. Thus, CD22 ligand engagement may not only transduce important signals, but also retain this important regulator of signal transduction at the cell surface where it is functionally active. 6.5. CD22 Ligand Binding Regulates Cell Surface IgM Expression Peripheral B cells in CD22 / , CD22D1‐2, and CD22AA mice have decreased surface IgM expression, but increased MHC class II Ag and CD44 expression (Poe et al., 2004a; Sato et al., 1996a). Although less dramatic in these mice, this is similar to the phenotype of CD19‐overexpressing B cells (Engel et al., 1995b; Sato et al., 1997), and of SHP1‐defective B cells from moth‐eaten mice (Pani et al., 1995; Schultz et al., 1993; Sidman et al., 1978; Tsui et al., 1993). Rather than signifying different stages of differentiation, these results suggest that alterations in CD22 signaling influence the level of spontaneous BCR signaling which alters BCR turnover as in some transgenic mouse models (Bell and Goodnow, 1994). Downregulated surface IgM expression levels in mice overexpressing CD19 or in moth‐eaten mice is also thought to be a consequence of augmented transmembrane signaling through the BCR complex (Cyster and Goodnow, 1995; Engel et al., 1995b; Pani et al., 1995; Sato et al., 1997). By contrast, B cells from CD19‐deficient (CD19 / ) mice exhibit increased surface IgM expression, presumably due to hyporesponsive BCR signaling. Therefore, downregulated surface IgM levels in CD22 / mice suggests that CD22 regulates BCR signaling in the absence of Ag engagement since the majority of B cells are uniformly affected. Thus, the absence of CD22 expression may allow a higher level of spontaneous BCR signaling, which accelerates its turnover on the cell surface. CD22 interactions with its ligands may influence B‐cell signaling thresholds. Consistent with this hypothesis, the absence of CD22 ligand‐binding activity in CD22D1‐2 and CD22AA mice results in a phenotype similar to CD22 / B cells (Goodnow et al., 1988; Nitschke et al., 1997; O’Keefe et al., 1996; Otipoby et al., 1996; Poe et al., 2004a; Sato et al., 1996a). This is not simply due to decreased CD22 expression on mature B cells from CD22D1‐ 2 and CD22AA mice, because IgM and MHC class II expression are only modestly altered on B cells from CD22þ/ mice compared to the more severe defect on CD22D1‐2, CD22AA, and CD22 / B cells (Poe et al., 2004a; Sato et al., 1996a). This suggests that ligand binding by CD22 controls homeostatic BCR signaling directly, or more likely the downstream effects of homeostatic signaling that lead to B‐cell activation.

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6.6. CD22 Ligand Binding Regulates MZ B‐Cell Development MZ B cells represent a distinct nonrecirculating population localized within splenic follicles of both mouse and man. This B‐cell population demonstrates unique developmental characteristics, cell surface marker expression, and functional activity that differentiates them from mature recirculating follicular B cells (Martin and Kearney, 2002). MZ B cells may exist as a specialized B‐cell subpopulation poised to rapidly respond to blood‐borne T‐cell‐independent Ags and are thus deemed necessary for efficient humoral responses during infections (Guinamard et al., 2000; Martin and Kearney, 2000; Martin, Oliver, and Kearney, 2001). The MZ B‐cell compartment is significantly reduced in spleens of CD22 / mice (Samardzic et al., 2002; Sato et al., 1996a). The maintenance of MZ B cells also requires CD22 ligand‐binding activity, as MZ B cells are reduced equally in CD22D1‐2, CD22AA, and CD22 / mice (Poe et al., 2004a). Whether the reduction in MZ B cells results from a defect in their development, or whether CD22 ligand‐binding activity is required for MZ B‐cell localization and survival within the spleen remains to be determined. However, B cells within MZ regions of CD22 / mice appear to undergo apoptosis at higher rates than follicular B cells (Poe et al., 2004b). It is therefore possible that the overall high rate of B‐cell turnover in CD22 / , CD22D1‐2, and CD22AA mice does not permit the repopulation of MZ B cells, whereas follicular B cells are regenerated at faster rates by the bone marrow. Regardless, CD22 promotes MZ B‐cell development and/or survival through ligand‐dependent mechanisms. 6.7. CD22 Ligand Binding Does Not Regulate B‐Cell Tissue Localization It has been proposed that CD22 adhesive function regulates the migration of recirculating B cells to the bone marrow (Nitschke et al., 1999). This conclusion was based on a recombinant CD22‐Ig fusion protein binding to bone marrow sinusoidal endothelium, that treatment of mice with CD22‐Ig fusion protein or polyclonal rabbit anti‐CD22 antisera reduced the number of mature recirculating B cells in bone marrow by 50%, and that CD22 / mice have lower numbers of IgM‐secreting plasma cells in the bone marrow. Although provocative, these findings may also result from correlative changes in B‐cell function or CD22 signaling rather than CD22 serving as a specific adhesion receptor. For example, CD19 overexpressing mice also have lower numbers of circulating B cells and lower numbers of IgM‐secreting plasma cells in the bone marrow but it is unlikely that CD19 functions as an adhesion molecule (Tedder et al., 1997a). Moreover, CD22‐Ig fusion proteins bind an extremely diverse array of structurally distinct serum and cell surface sialoglycoconjugates, such

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that it is difficult to appreciate the specificity or physiological relevance of their binding to bone marrow sinusoidal endothelium. Importantly, adoptive transfer of fluorochrome‐labeled splenic B cells from CD22D1‐2 and CD22AA mice revealed no impairment in their migration to the bone marrow or lymphoid tissues of recipient mice (Poe et al., 2004a). The importance of CD22 in B‐cell migration in vivo warrants further assessment, although there is no current evidence to suggest that CD22 functions as a ‘‘classic’’ type of adhesion molecule in vivo or that it directly regulates lymphocyte migration through mechanisms other than regulating B‐cell survival and signal transduction. 7. The CD22 Cytoplasmic Domain Regulates B-Cell Signal Transduction B cells from CD22 / , CD22D1-2, and CD22AA mice are hyperresponsive to some transmembrane stimuli while hyporesponsive to others. For example, proliferative responses induced by anti‐IgM antibodies are decreased in CD22 / B cells (Otipoby et al., 1996; Sato et al., 1996a), while responses to LPS, CD40, and CD38 plus IL‐4 are either elevated or similar to those of wild‐ type B cells. These observations indicate that CD22 functions as a complex positive and negative regulator of B lymphocyte signal transduction dependent on the context of BCR signaling (Tedder, 1998). However, significant gaps remain in our understanding of how CD22 regulates transmembrane signals and how this receptor interprets signals generated through other cell‐surface receptors. Regardless, one feature is constant; B cells from CD22 / mice have greatly increased intracellular calcium ([Ca2þ]i) responses following BCR‐cross‐linking (Fig. 4A), while B cells from CD22D1-2 and CD22AA mice generate normal [Ca2þ]i responses (Poe et al., 2004a). Thus, at least some critical features of CD22 function do not require ligand binding, but may rather depend on the membrane localization of the CD22 cytoplasmic domain. Importantly, the augmented [Ca2þ]i responses observed in CD22 / B cells are similar to [Ca2þ]i responses generated by simultaneous BCR and CD19 ligation, or responses of Lyn / B cells (Fig. 4A), suggesting that these signaling molecules are functionally linked (Fujimoto et al., 2001). 7.1. BCR Signaling Pathways After Ag is recognized by membrane Ig, immunoreceptor tyrosine‐based activation motif (ITAM; D/EX2YX2L/IX6-8YX2L) sequences of CD79a and CD79b become phosphorylated and function as signal transducing elements for nonreceptor PTKs. BCR‐mediated signaling induces the activation of

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distinct families of PTKs including Syk; Btk of the Tec family; and Lyn, Fyn, Blk, and Lck of the Src family. Lyn is the predominant Src‐family PTK member expressed in B cells. The function of Lyn in B cells is complex and includes both the initiation and subsequent termination of BCR‐generated signals (DeFranco et al., 1998). This unique role for Lyn in governing not only positive signals, but also negative feedback signals, results from Lyn phosphorylation of tyrosines within immunoreceptor tyrosine‐based inhibition motif (ITIM; V/IXYX2L) sequences of presumably negative regulatory molecules. Src‐family PTKs associate with the BCR complex in resting B cells and become activated upon BCR ligation.

Figure 4 (Continued)

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Figure 4 CD22 regulation of [Ca2þ]i responses as described (Fujimoto et al., 2001). (A) [Ca2þ]i responses induced by simultaneous BCR (anti‐IgM F(ab0 )2 antibody fragments) and CD19 (MB19–1 mAb) ligation in B cells from wild‐type mice resembles that in B cells from CD22‐/‐ and Lyn‐/‐ mice. (B) Simultaneous BCR and CD19 engagement augments [Ca2þ]i responses and extinguishes CD22 phosphorylation and SHP1 recruitment, while extensive CD19 ligation inhibits BCR‐induced [Ca2þ]i responses. Left panel, [Ca2þ]i responses after BCR ligation with anti‐IgM or anti‐IgM plus CD19 antibody at high and low concentrations. Right panels demonstrate protein tyrosine phosphorylation (anti‐pTyr) in wild‐type B cells following BCR and/or CD19 ligation as indicated. Purified splenic B cells were incubated with medium alone, anti‐IgM F(ab0 )2 antibody fragments (40 mg/ml), CD19 antibody (40 mg/ml), or anti‐IgM (40 mg/ml) plus CD19 (10 mg/ml) antibodies for 3 min and detergent lysed. In some panels, CD19, CD22, or SHP1 were immunoprecipitated from B‐cell lysates, subjected to SDS‐PAGE analysis, and transferred onto membranes for antiphosphotyrosine (anti‐pTyr) immunoblotting. (C) Models for CD19/CD21 regulation of CD22 function. With BCR cross‐linking, CD19 augments BCR‐induced signals through its ability to amplify Src‐family PTK activation, which results in CD22 tyrosine phosphorylation. With CD19/CD21 cross‐linking, CD19 serves as a sensing mechanism for the generation of complement C3d‐Ag complexes and upregulates intrinsic levels of Lyn phosphorylation and activation, but it does not induce CD22 phosphorylation. With simultaneous BCR and CD19/ CD21 ligation, CD22 phosphorylation is inhibited, potentially due to the retention of Lyn by aggregated CD19 complexes. With simultaneous BCR and extensive CD19/CD21 ligation, CD22 and CD79 phosphorylation are both inhibited, potentially due to the sequestration of Lyn by aggregated CD19 complexes.

Following BCR ligation, activated Src‐family PTKs phosphorylate the ITAMs of CD79a and CD79b (Fig. 5A), resulting in the recruitment of Syk through its tandem Src homology 2 (SH2) domains (Saouaf et al., 1994). PTK function is additionally regulated by ‘‘cross‐talk’’ between PTKs, protein tyrosine phosphatases such as SHP1, and interactions with intracellular regulatory

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Figure 5 CD22 and CD19 regulation of [Ca2þ]i responses. (A) The CD19–CD22 regulatory loop interprets BCR‐induced signals. CD19 processive amplification of Lyn PTK activity leads to CD22 phosphorylation by Lyn. Phosphorylated CD22 binds SHP1 (in addition to the Grb2/Shc/SHIP complex), which in turn negatively regulates CD19 phosphorylation and amplification of Src family PTK activity. In addition, CD22 regulates cMyc expression through unknown pathways, which directly regulates Cul1 production and ubiquitin ligase (UL)‐dependent cell cycle progression.

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and adapter proteins (Thomas and Brown, 1999). The net positive effects of PTK activation include tyrosine phosphorylation of important transmembrane receptors, phosphoinositide generation and turnover, and increases in [Ca2þ]i through the activation of phospholipase C‐g2 (PLC‐g2). These events in turn lead to the activation of additional PTKs, as well as serine/threonine kinases, such as mitogen‐activated protein kinases (MAPKs). Collectively these activation pathways orchestrate events critical for the function of activated cells, including restructuring of the cytoskeleton and initiation of de novo gene transcription. 7.2. CD22 Regulation of BCR Signal Transduction The approximately 140 amino acid cytoplasmic domains of hCD22 and mCD22 are highly conserved, including six tyrosine residues that are potential targets for phosphorylation following surface BCR or CD22 ligation (Torres et al., 1992; Wilson et al., 1991). The cytoplasmic domains of mCD22 and hCD22 contain two potential ITAM‐like regions (Leprince et al., 1993). In addition, the mCD22 cytoplasmic domain encodes three potential ITIMs, whereas hCD22 contains four ITIM motifs. Through these motifs, hCD22 and mCD22 provide binding sites for SHP1, PLC‐g2, phosphatidylinositol (PI) 3‐kinase, Grb2, Syk, Shc, and SHIP (Blasioli et al., 1999; Poe et al., 2000; Yohannan et al., 1999). That CD22 contains both positive and negative signaling elements may explain why both positive and negative signaling roles for CD22 are observed during in vitro experiments. Although it has become popular to categorize signaling molecules as either positive or negative regulators, this is likely to be an oversimplification because each of these molecules may influence signaling in a manner dictated by the context of the cell microenvironment, the activation or differentiation state of the cell, or by the assay utilized (Tedder, 1998). A positive signaling role for CD22 in B‐cell function is suggested by the presence of ITAM‐like regions that, when phosphorylated, serve as docking platforms for the SH2 domains of Syk kinase and Src‐family tyrosine kinases

(B) Reciprocal regulatory activities of CD19 and CD22. CD19 signal transduction and amplification of Lyn PTK activity (Fig. 4C) leads to CD22 phosphorylation and recruitment of Grb2/Shc/ SHIP. The activation and recruitment of these molecules to the plasma membrane allows Lyn to phosphorylate Btk that is recruited through its pleckstrin homology domain (PH) to bind PI(3,4,5) P3 generated from PI(4,5)P2 by PI 3‐kinase. PLC‐g2 recruitment to the membrane allows it to cleave PI(4,5)P2 and augment [Ca2þ]i responses. By contrast, SHIP bound to CD22 dephosphorylates PI(3,4,5)P3, and thereby downregulates the duration and intensity of [Ca2þ]i responses.

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such as Lyn (Law et al., 1996; Tuscano et al., 1996b). Lyn may initiate tyrosine phosphorylation of cross‐linked CD22 since low amounts of purified Lyn bind to non‐tyrosine‐phosphorylated peptides that span the distal ITAM or tyrosines 807 and 822 (Tuscano et al., 1996b). Studies with Lyn‐deficient mice have also concluded that Lyn is predominantly responsible for CD22 tyrosine phosphorylation following BCR or CD22 cross‐linking (Chan, Lowell, and DeFranco, 1998; Fujimoto et al., 2000). Consistent with a costimulatory role for CD22, positive effector molecules of B‐cell activation, PI 3‐kinase and PLC‐g2, also bind tyrosine‐phosphorylated CD22 via their SH2 domains (Law et al., 1996; Leprince et al., 1993; Tuscano et al., 1996b). Syk, Lyn, and PI 3‐kinase associate with a tyrosine‐phosphorylated peptide that spans amino acid residues 822 and 842 of hCD22 (Tuscano et al., 1996b), implicating this site as an important region in mediating CD22 signal‐transduction. Thus, CD22 binding its physiologic ligands may augment B‐cell activation through the generation of positive signals. CD22 may actually contribute significantly to the earliest signaling cascades that occur during B‐cell activation since CD22 is rapidly tyrosine phosphorylated after B‐cell activation (Schulte et al., 1992). CD22 phosphorylation by Lyn may facilitate Syk and PLC‐g2 binding. This would allow for PLC‐g2 phosphorylation by Syk, and localization of activated PLC‐g2 to the plasma membrane where its phosphoinositide substrates are present (Law et al., 1996). Thus, under different experimental conditions or in vivo, interactions between CD22, IgM, Syk, Lyn, PI 3‐kinase, and PLC‐g2 may result in proliferative signals that surpass the downregulatory effects of CD22. Consistent with a costimulatory role for CD22, in vitro CD22 cross‐linking activates the c‐Jun NH2‐terminal kinase (JNK, also known as the stress‐activated protein kinase, or SAPK) signaling cascade. Significant SAPK activation is induced after cross‐linking CD22 on primary B cells and several B‐cell lines (Tuscano et al., 1999). CD22 has the ability to generate these BCR‐independent transmembrane signals since the HS Sultan plasmacytoma cell line used as part of these studies lacks surface Ig. Co‐cross‐linking surface Ig with CD22 fails to significantly alter this effect. This is consistent with CD22 cross‐linking leading to significant SAPK activation on splenic B cells (Tooze et al., 1997). In that study, the activity of extracellular signal–regulated kinase‐2 (ERK‐2), the MAPK isoform which is preferentially activated after Ig cross‐linking, was also modulated by CD22. A modest increase in ERK‐2 activity is observed after CD22 cross‐linking alone in our studies as well (Tuscano et al., 1999). However, a modest enhancement and significant prolongation of ERK‐2 activation after CD22/BCR coligation was observed in our studies. This is consistent with CD22 generating BCR‐independent signals, which could enhance and prolong BCR‐mediated ERK‐2 activation.

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The extensive CD22 cytoplasmic domain also serves as an interaction site for numerous negative regulatory molecules including SHP1 and SHIP, phosphatases that modify BCR‐mediated signaling, and BCR‐induced [Ca2þ]i release. All three mCD22 ITIMs provide docking sites for SH2 domains of the SHP1 protein tyrosine phosphatase (Doody et al., 1995). Following BCR cross‐linking, SHP1 associates with tyrosine‐phosphorylated CD22, inducing SHP1 phosphatase activity (Campbell and Klinman, 1995; Doody et al., 1995; Lankester et al., 1995; Law et al., 1996). In fact, CD22 and SHP1 associate in both resting and stimulated mouse splenic B cells and CD22 is the dominant phosphoprotein that associates with SHP1 (Sato et al., 1997). In addition, CD22 suppresses MAPK activation in mouse B cells when cross‐linked to membrane Ig (Tooze, et al., 1997). CD22 may also attenuate calcium signaling by potentiating plasma membrane calcium‐ATPase (PMCA) activity through a SHP1‐dependent pathway in a chicken B‐cell line (Chen et al., 2004). Interestingly, CD22 and SHP1 associate directly with PMCA4 through phosphorylation‐dependent interactions. Thus, PMCA‐mediated calcium efflux from cells may also act as a negative regulator of B‐cell signaling. These findings reinforce the predominant concept that CD22 associated with SHP1 plays a negative regulatory role in B‐cell signaling. CD22 also physically interacts with SHIP via Grb2/Shc interactions (Poe et al., 2000). SHIP independently forms complexes with the adapter proteins Grb2 and Shc (Chacko et al., 1996; Crowley et al., 1996; Harmer and DeFranco, 1998; Kavanaugh et al., 1996; Saxton et al., 1994), with Grb2 required for the efficient association of Shc and SHIP (Harmer and DeFranco, 1998). The SHIP/Grb2/Shc ternary complex has been proposed to modulate [Ca2þ]i responses and to be essential for preventing B‐cell hyperresponsiveness following BCR ligation (Harmer and DeFranco, 1998). Grb2 and Shc interact with distinct regions of CD22; Grb2 specifically interacts with a peptide containing CD22 phosphotyrosines 799/810, whereas Shc only interacts with peptides containing phosphotyrosines 755/765 and 810/825. By contrast, SHIP, Grb2, and Shc are only coprecipitated with a GST fusion protein consisting of the entire tyrosine‐phosphorylated CD22 cytoplasmic domain (GST‐CD22cyt [pTyr]), but not by any of the individual phosphopeptides. Therefore, it is likely that the interaction of SHIP and CD22 is indirect via Grb2 and Shc (Fig. 5B), and that both adapter proteins are required to form a stable Grb2/ Shc/SHIP complex (Harmer and DeFranco, 1998). That all three SHIP isoforms coprecipitate with GST‐CD22cyt further indicates that SHIP interactions with the CD22 cytoplasmic domain are indirect, and therefore likely to occur via Shc and/or Grb2 binding of SHIP phosphotyrosines. SHIP processes phosphatidylinositol 3,4,5‐trisphosphate (PI(3,4,5)P3) into the phosphatidylinositol 3,4‐bisphosphate (PI(3,4)P2) cleavage product (Fig. 5B). PI(3,4,5)P3 is

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a membrane phospholipid generated by PI 3‐kinase phosphorylation of phosphatidylinositol 4,5‐bisphosphate (PI(4,5)P2) that is involved in the membrane recruitment of pleckstrin homology (PH) domain‐containing proteins such as Btk, a PTK that activates PLC‐g2 (Fig. 5B). PI(3,4,5)P3 is generated by PI 3‐ kinase phosphorylation of phosphatidylinositol 4,5‐bisphosphate (PI(4,5)P2). PLC‐g2 activation results in PI(4,5)P2 hydrolysis, with the subsequent generation of inositol 1,4,5‐trisphosphate (InsP3) that mobilizes [Ca2þ]i from intracellular stores and diacylglycerol (DAG) that activates protein kinase C. By PI (3,4,5)P3 dephosphorylation, SHIP is able to reduce PI 3‐kinase‐initiated Akt phosphorylation and the membrane recruitment of Btk through its PH domain (Vanhaesebroeck et al., 2001). Thereby, the 50 ‐phosphatase activity of SHIP on PI(3,4,5)P3 negatively regulates PI 3‐kinase signaling in vivo. Thus, the CD22/SHIP/Grb2/Shc complex may facilitate SHIP recruitment to its plasma membrane substrates where it can modulate B‐cell [Ca2þ]i responses. Recently, CD22 was reported to regulate BCR signaling depending on the cell surface Ig isotype expressed (Wakabayashi et al., 2002). Cell lines expressing IgM were subject to CD22‐mediated regulation, which included inhibition of [Ca2þ]i mobilization and ERK activation following BCR cross‐linking, whereas cell lines that expressed a BCR with an IgG cytoplasmic tail were not subject to CD22‐mediated regulation. Interestingly, BCR ligation of cells expressing an IgG cytoplasmic tail did not induce CD22 tyrosine phosphorylation or subsequent SHP1 recruitment. This suggests that regulation of BCR signaling by CD22 may not be operative in class‐switched B‐cell blasts and memory B cells. Whether CD22 ligand binding alternatively continues to regulate the survival and additional effector functions of these differentiated populations remains to be determined. 7.3. Altered Signal Transduction Pathways in Primary CD22 /

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Biochemical studies of CD22 B cells have provided new insight into the effects of CD22 loss on BCR signaling (Sato et al., 1997). Although unexpected, overall tyrosine phosphorylation of cellular proteins in resting B cells from CD22 / mice is lower than in purified B cells from wild‐type littermates when assessed by Western blot analysis of total cell lysates or immunoprecipitated proteins with antiphosphotyrosine mAbs. Interestingly, CD19 and Vav are the only specific signaling molecules identified thus far that are more intensely tyrosine‐phosphorylated in CD22 / B cells (Sato et al., 1997). Vav, a hematopoietic cell‐specific cytoplasmic adapter protein and proto‐oncogene product, is rapidly phosphorylated following BCR ligation and is likely to be a central component of CD19 regulation of B‐cell signal transduction (Bustelo and Barbacid, 1992; Deckert et al., 1996; Fujimoto et al., 1998). Tyrosine

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phosphorylation of Vav directly and positively modulates its guanine‐nucleotide‐exchanging activity for Rac‐1 (Crespo et al., 1997). However, basal tyrosine phosphorylation of CD79a, CD79b, Lyn, Fyn, Blk, Syk, SHP1, SHIP, and PLC‐g2 are unchanged in CD22 / B cells compared to wild‐type B cells. However, BCR‐induced tyrosine phosphorylation of CD79a, CD79b, SHIP, and PLC‐g2 are particularly lower in CD22 / B cells. Decreased CD79a and CD79b tyrosine phosphorylation does not result from reduced activation of Syk or the Src‐family PTKs (Lyn, Fyn, Blk) because their patterns of tyrosine phosphorylation and activities during in vitro kinase assays are similar in CD22 / and wild‐type B cells. MAPK activation has also been assessed in CD22 / B cells (Poe et al., 2000), demonstrating a specific reduction in JNK activity, while ERK activation is normal. Thus, eliminating CD22 expression has significant but unexpected effects on multiple signaling pathways. Although the molecular explanation for the decrease in overall protein phosphorylation in CD22 / B cells is yet to be identified, this does not readily explain their augmented [Ca2þ]i responses following BCR engagement. 7.4. A CD19/CD22 Regulatory Loop Governs [Ca2þ]i Responses Rapid CD22 tyrosine phosphorylation following BCR ligation suggests that these two receptors are functionally linked (Leprince et al., 1993; Schulte et al., 1992; Tuscano et al., 1996b). However, more recent studies indicate that CD19 and CD22 form a regulatory loop and modulate each other’s functions directly, and thereby regulate BCR signal transduction indirectly (Fujimoto et al., 1999a). In support of this, the phenotypes of CD22 / , CD19 / , and CD19‐overexpressing mice indicate that CD19 and CD22 reciprocally regulate similar, if not overlapping, signaling pathways (Tedder et al., 1997a). CD22 / mice have increased numbers of B‐1 cells and functional properties remarkably similar to mice that overexpress CD19 (O’Keefe et al., 1996; Sato et al., 1996a). In addition, B cells from CD22 / ‐ and CD19‐overexpressing mice are hyperresponsive to BCR signaling. By contrast, CD19 / B cells are hyporesponsive to mitogens and BCR ligation, and CD19 / mice have a marked loss of peritoneal B‐1 cells (Engel et al., 1995b; Rickert et al., 1995; Sato et al., 1996b; Tarakhovsky et al., 1995; Zhang et al., 1995). Biochemical studies also indicate that CD19 and CD22 reciprocally regulate BCR signal transduction. For example, CD19 phosphorylation recruits Vav into the plasma membrane‐ bound CD19 signaling complex via SH2 interactions, which facilitates the subsequent phosphorylation of Vav by activated tyrosine kinases (Weng et al., 1994). Vav tyrosine phosphorylation is modest and transient after BCR ligation in CD19 / B cells, yet uniquely augmented after BCR cross‐linking in CD22 / B cells (Sato et al., 1997). Vav is most heavily tyrosine phosphorylated

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in response to CD19 ligation, with modest phosphorylation resulting from BCR and other signaling pathways (Bustelo and Barbacid, 1992; Collins et al., 1997; Sato et al., 1997). As another example, CD19 and CD22 have counterregulatory effects on MAPK activation (Tooze et al., 1997). Biochemical studies also demonstrate that CD19 and CD22 form a regulatory loop and modulate each other’s functions directly (Fig. 5A), and regulate BCR signal transduction indirectly (Fujimoto et al., 1999a). First, CD22 tyrosine phosphorylation is greatly diminished in CD19 / B cells following BCR cross‐linking. Central to this process is the recent demonstration that CD19 regulates intrinsic and BCR‐induced Lyn kinase activity through a unique mechanism of ‘‘processive amplification’’ (Fujimoto et al., 2000). Thereby, CD19 expression and amplification of Lyn kinase activity is required for optimal CD22 phosphorylation after BCR ligation (Fujimoto et al., 1999a; Sato et al., 1997). Decreased CD22 phosphorylation in CD19 / B cells reduces the amount of associated SHP1, thereby reducing the negative regulatory effects of CD22. Thus, CD19 expression has a crucial role for initiating the CD22/SHP1/SHIP negative regulatory pathway (Fig. 5A). Surprisingly, CD19 is a major target of CD22 inhibitory signals rather than BCR‐proximal signaling pathways. For example, Syk phosphorylation and function are normal in CD22 / B cells (Fujimoto et al., 1999b). By contrast, intrinsic CD19 tyrosine phosphorylation is constitutively higher in CD22 / B cells and is increased significantly in CD22 / B cells after BCR ligation relative to wild‐ type B cells (Fujimoto et al., 1999a). CD22 presumably regulates CD19 phosphorylation directly through recruited SHP1 (Somani et al., 2001). CD19 expression upregulates tyrosine phosphorylation of CD22 and Vav following BCR cross‐linking, while CD22 most likely regulates BCR signaling indirectly by regulating CD19 phosphorylation and CD19‐mediated Lyn amplification (Sato et al., 1997). CD22 regulation of CD19 function is critically important for normal B‐cell function because a 20% increase in CD19 expression (and presumably function) confers autoimmunity in mice and potentially in humans (Sato et al., 2000; Tedder et al., 2005). Functional CD19 and CD22 interactions have also been assessed genetically through the generation of CD19/CD22 double‐deficient (CD19/CD22 / ) mice (Fujimoto et al., 1999a). The characteristics of CD19/CD22 / mice clearly support the hypothesis that CD19 expression is necessary for CD22 function after BCR ligation (Fujimoto et al., 1999a). CD19‐deficiency is dominant in CD19/CD22 / mice, rather than CD19 and CD22 deficiencies having additive effects. Indeed, CD19/CD22 / mice show a remarkably similar phenotype to CD19 / mice. For example, tyrosine phosphorylation is decreased to similar levels in both CD19 / and CD19/CD22 / B cells. Serum Ig levels are identical in CD19 / and CD19/CD22 / mice, as are

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antibody responses to T‐dependent Ags, despite increased IgM levels and elevated IgM responses in CD22 / mice. Spleen B‐cell numbers are similarly reduced in CD19 / and CD19/CD22 / mice. As occurs in CD19 / mice, peritoneal B‐1 lineage cells are rare in CD19/CD22 / mice, despite increased B‐1 cells in CD22 / mice (O’Keefe et al., 1996; Sato et al., 1996a). BCR‐ induced tyrosine phosphorylation of total cellular proteins is equally impaired in CD19/CD22 / and CD19 / B cells. Lyn kinase activity is only modestly increased in CD19 / and CD19/CD22 / B cells after BCR ligation, while Vav tyrosine phosphorylation is decreased to a similar extent in CD19/CD22 / and CD19 / B cells. In addition, proliferative responses to mitogens are minimal in both CD19/CD22 / and CD19 / B cells. Thus, CD19 expression is necessary for optimal CD22 function. In some specific instances, CD19 and CD22 functions were additive rather than affecting identical signaling pathways in CD19/CD22 / mice (Fujimoto et al., 1999a). For example, CD22 expression influences circulating B‐cell numbers, regardless of CD19 expression. Although CD19 loss results in higher IgM expression by immature and mature B cells, CD22 loss results in lower IgM expression by more mature B cells. However, CD19/CD22 / B cells have high IgM expression early and low IgM expression later during maturation. We propose that the above events are regulated by CD22 ligand binding and may be independent of the CD19 signaling pathway, while many of the signaling events that proceed through CD19‐dependent pathways are regulated by CD22 expression independent of ligand engagement. Thus, CD19 and CD22 are likely to interact through independent pathways in addition to contributing to a common CD19/CD22 regulatory loop. 7.5. CD19/CD21 Extinction of CD22 Phosphorylation Augments [Ca2þ]i Responses A prominent feature of CD22 / mice is that their B cells exhibit dramatically increased [Ca2þ]i responses following BCR cross‐linking (Nitschke et al., 1997; O’Keefe et al., 1996; Otipoby et al., 1996; Sato et al., 1996a). Similar observations have been made in variants of the WEHI‐231 pre‐B‐cell line with diminished CD22 expression (Nadler et al., 1997). This feature appears specific to BCR signaling since significantly increased [Ca2þ]i responses are not observed following CD19 cross‐linking (Sato et al., 1996a). However, the mechanisms by which CD22 expression affects BCR‐induced [Ca2þ]i responses appear complex because multiple known and unknown signaling molecules regulate [Ca2þ]i mobilization including Syk, PI 3‐kinase, PLC‐g2, SHIP, BLNK, and Btk (Buhl et al., 1997; Hippen et al., 1997; Scharenberg and Kinet, 1996; Takata and Kurosaki, 1996).

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Because Syk is likely to regulate tyrosine phosphorylation of PLC‐g2 directly (Takata et al., 1994) and Syk phosphorylation and function are normal in CD22 / B cells (Fujimoto et al., 1999b), CD22 is unlikely to regulate [Ca2þ]i responses at the level of a BCR/Syk/PLC‐g2 pathway. Consistent with this, PLC‐g2 tyrosine phosphorylation is actually decreased in CD22 / B cells. Altered [Ca2þ]i responses could result from the failure of SHP1 to associate with CD22, given that exaggerated [Ca2þ]i responses are observed in SHP1‐defective B cells (Cyster and Goodnow, 1995). Decreased SHIP phosphorylation in CD22 / B cells may also explain augmented [Ca2þ]i responses, given that activated SHIP blocks BCR‐induced [Ca2þ]i responses (Scharenberg and Kinet, 1996). Like in CD22 / B cells, [Ca2þ]i responses are augmented in a SHIP‐deficient B‐cell line following BCR ligation (Okada et al., 1998), and B cells from SHIP / mice generate enhanced [Ca2þ]i responses following BCR‐FcgRIIB coligation (Liu et al., 1998). These findings support the notion that the normal function of the CD22/SHIP/Grb2/Shc complex is to downregulate BCR‐induced [Ca2þ]i responses (Fig. 5B) in conjunction with CD22 recruitment of SHP1 to its CD19 substrate on the plasma membrane (Fig. 5A). Studies with CD19/CD22 / B cells suggest that CD22 and CD19 actually influence [Ca2þ]i responses in an interdependent manner that can explain augmented [Ca2þ]i responses in CD22 / B cells (Fujimoto et al., 1999a). CD19 / B‐cell [Ca2þ]i responses are delayed and slightly diminished following IgM ligation compared with wild‐type B cells, while CD22 / B cells exhibit dramatically increased [Ca2þ]i responses. [Ca2þ]i responses are greatly increased in CD19/CD22 / B cells compared with wild‐type B cells, and appear to mimic the combined effects of CD19 and CD22 deficiencies. Consistent with this, simultaneous CD19 and IgM engagement generate [Ca2þ]i responses similar to those of CD22 / and Lyn / B cells (Fig. 4A). This suggests that simultaneous CD19 and IgM engagement circumvents the negative regulatory effects of CD22. Recent studies have verified this and revealed that the augmented [Ca2þ]i responses induced following simultaneous BCR and CD19 ligation result from CD19 extinction of CD22 phosphorylation (Fujimoto et al., 2001). Surprisingly, CD19 engagement with mAb at concentrations that induce optimal [Ca2þ]i responses with simultaneous BCR engagement does not augment BCR‐induced protein tyrosine phosphorylation in B cells, but actually reduces overall phosphorylation levels compared with IgM ligation alone (Fig. 4B). This treatment leads to increased CD19 phosphorylation and higher levels of Lyn bound to CD19, while CD22 phosphorylation and SHP1 binding to CD22 are significantly inhibited (Fig. 4B). This suggests a new model for CD19/CD22 regulation of [Ca2þ]i responses (Fig. 4C).

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CD19/CD22 regulation of [Ca2þ]i may occur through Lyn retention by CD19, which prevents Lyn from phosphorylating CD22 (Fujimoto et al., 2001). CD19/CD21 complex ligation via C3d‐Ag complexes or mAb engagement generates transmembrane signals that induce Lyn recruitment and amplification by CD19 (Fig. 4C). Phosphorylated CD19 binds PI 3‐kinase (Tuscano et al., 1996b; Yohannan et al., 1999), which may also contribute to efficient [Ca2þ]i mobilization by generating PIP3 to recruit Btk to the membrane (Bolland et al., 1998; Buhl and Cambier, 1999; Li et al., 1997a,b; Scharenberg et al., 1998). However, CD19 expression is not necessary for optimal PI 3‐kinase activation (Fujimoto et al., 2000). When CD19 and cell surface IgM are engaged simultaneously, Lyn activated by BCR engagement is further amplified through CD19 ‘‘processive amplification,’’ which results in enhanced [Ca2þ]i responses. We propose that Lyn recruitment to CD19 under these conditions extinguishes the ability of Lyn to phosphorylate CD22, which also enhances [Ca2þ]i responses. By contrast, CD19 hypercross‐linking with high levels of mAb (40 mg/ml) during simultaneous BCR ligation actually inhibits [Ca2þ]i responses to the levels seen with CD19 ligation alone (Fig. 4B). This suggests that CD19 hypercross‐linking not only sequesters Lyn away from CD22, but prevents Lyn phosphorylation of Syk downstream of BCR signaling (Fig. 4C). Thus, elevated [Ca2þ]I responses in CD22 / B cells may be explained, in part, by the absence of CD22 phosphorylation, which augments CD19 phosphorylation and inhibits the recruitment and phosphorylation of SHP1 and SHIP (Sato, Jansen, and Tedder, 1997). These results further confirm complex and overlapping interactions between CD19, CD22, Lyn, and SHP1 following BCR engagement (Fig. 5). 7.6. CD22 Regulates [Ca2þ]i Responses Independent of Ligand Binding Whether CD22 ligand binding regulates [Ca2þ]i responses has been a controversial matter. Results from experiments performed using cell lines have suggested that CD22 binding to sialic acid‐bearing ligands is required for CD22 to negatively influence BCR signal transduction and dampen self reactivity. In one study, CD22 expression suppressed B‐cell activation by Ag‐expressing target cells that coexpressed a2–6‐sialoglycoconjugates (Lanoue et al., 2002). In other studies, B‐cell lines with impaired CD22 ligand binding exhibited augmented Ca2þ responses following BCR engagement, which was proposed to result from decreased CD22 tyrosine phosphorylation and decreased SHP1 recruitment to CD22 (Jin et al., 2002; Kelm et al., 2002). By contrast, analysis of ST6Gal sialyltransferase gene‐deficient (ST6Gal I / ) mice, which fail to generate CD22 ligands, suggests that CD22 exerts stronger negative regulation of B‐cell signaling in the absence of ligand engagement

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(Collins et al., 2002; Hennet et al., 1998). However, primary CD22D1‐2 and CD22AA B cells have allowed us to directly assess the role ligand binding plays in CD22‐mediated regulation of BCR‐induced Ca2þ responses. Remarkably, CD22D1‐2 and CD22AA B cells flux Ca2þ at levels identical to B cells from their wild‐type littermates following treatment with both optimal and suboptimal BCR ligation (Poe et al., 2004a). Furthermore, CD22 tyrosine phosphorylation and its subsequent association with SHP1 are not impaired in CD22D1‐2 or CD22AA B cells following BCR ligation. Thus, CD22 expression at the B‐cell surface appears to be the only requirement for it to regulate BCR‐induced [Ca2þ]i responses, with no requirement for ligand binding. This is consistent with the model for CD22 extinction following BCR and CD19 ligation since the extracellular domain of CD22 does not need to be involved in this regulatory pathway (Fig. 4C). Nonetheless, although CD22 ligand engagement is not required for BCR‐induced [Ca2þ]i responses, this does not imply that ligand binding does not influence the ability of CD22 to regulate BCR signaling; however, this remains to be demonstrated. 8. CD22‐Directed Therapies and Clinical Trials in Oncology CD22 provides an important functional link between the cell surface, B‐cell survival, and regulation of intracellular signaling. Thus, it is not surprising that CD22‐directed therapies are being developed and tested clinically for both oncology and autoimmunity applications. Moreover, therapy for B‐cell malignancies and severe autoimmune disease has primarily relied upon broadly immunosuppressive agents such as cyclophosphamide, methotrexate, cyclosporin A, and corticosteroids. Although survival rates have improved dramatically, none of these therapies offers a cure and most have significant toxicities. With the advent of mAb‐based therapies, more specific and effective therapies with lower systemic toxicity are possible. Therapies directed at specifically reducing B‐cell numbers have recently acquired a great deal of attention and enthusiasm. For example, a chimerized CD20 mAb (Rituximab) effectively reduces normal and malignant B‐cell numbers without significant toxicity (Edwards and Cambridge, 2001; Leandro et al., 2002; Protheroe et al., 1999; Saleh et al., 2000; Stasi et al., 2001, 2002; Vita et al., 2002). It is therefore being used widely in human clinical trials for patients with lymphoma or autoimmune disease. Rituximab functions by binding the membrane‐embedded CD20 surface molecule on B cells, leading to B‐cell elimination through antibody‐dependent cellular cytotoxicity mediated by monocytes (Clynes et al., 2000; Hamaguchi et al., 2005; Uchida et al., 2004). Despite the effectiveness of Rituximab and its low toxicity, new therapies evoking different

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mechanisms of action with more selective effects on B‐cell subpopulations are needed. 8.1. CD22 Therapeutic Applications in Oncology CD22 is expressed by 60–80% of B‐cell lymphomas and leukemias, although expression density is more variable than for CD19 or CD20 (Press et al., 2001). In addition to chemotherapy, external‐beam radiation and naked mAb therapies, radioimmunotherapy is becoming a fourth mode of treatment for non‐Hodgkin’s lymphoma patients. Radiolabeled CD22 mAbs (Stein et al., 1993) have demonstrated high sensitivities in the diagnosis and the staging of B‐cell lymphomas, while therapeutic 131I‐ or 90Y‐labeled CD22 mAbs (LL2, Epratuzumab) that bind to the third extracellular Ig‐like domain of CD22 have generated partial to complete remissions (Coleman et al., 2003; Juweid et al., 1999; Siegel et al., 2003). Naked CD22 mAb (LL2) mediates antibody‐ and complement‐dependent cytotoxicity in vitro, with preclinical and early clinical studies providing a rationale for its use in immunotherapy (Carnahan et al., 2003; Leonard and Link, 2002). Because malignant B cells rapidly internalize CD22 and CD22 mAb binding leads to efficient intracellular routing of the CD22‐mAb complex to intracellular compartments (Press et al., 1994), the use of CD22 mAbs to deliver immunotoxins to non‐Hodgkin’s lymphoma and chronic lymphocytic leukemia cells has received considerable attention (Press et al., 1989; Sieber et al., 2003). This includes CD22 immunotoxins containing ricin A‐chain (Ghetie et al., 1988; 1992; 1994; Shen et al., 1988; Van Horssen et al., 1996), single‐chain ribosome‐inactivating proteins (Bolognesi et al., 1998; Bonardi et al., 1993; French et al., 1995b), Pseudomonas exotoxin‐A fragment (Decker et al., 2004; Kreitman et al., 1999; Mansfield et al., 1997a,b), and chemotherapeutic agents such as calicheamicin (DiJoseph et al., 2004, 2005). CD22 mAb‐immunotoxins containing ricin A‐chain (Amlot et al., 1993; Sausville et al., 1995; Vitetta et al., 1991) and ribosome‐inactivating proteins (Bonardi et al., 1992; French et al., 1995a, 1996) have been evaluated in phase I–II clinical trials, with partial or transient clinical remissions, potentially due to large tumor burdens in treated patients. Despite these clinical responses, severe and in certain cases fatal vascular leak syndrome was dose limiting. However, a more recent clinical trial using a recombinant CD22‐Pseudomonas exotoxin‐based immunotoxin induced complete remissions in 68% of chemorefractory hairy‐cell leukemia patients (Kreitman et al., 2001). Thus, multiple studies have validated CD22 as a rational target for treating B‐cell malignancies.

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8.2. Is Blocking CD22 Ligand Binding Therapeutic in Oncology? The importance of CD22 ligand binding for normal B‐cell survival suggests that blocking this interaction may influence malignant B‐cell survival. In addition, CD22 mAbs that block CD22‐ligand interactions have distinct functional properties during in vitro assays with B‐cell lymphoma cell lines. For example, binding of CD22 with these mAbs results in a 3‐ to 5‐fold induction of SAPK activity, and efficient and effective induction of apoptosis (Tuscano et al., 1999). That ligand‐blocking mAbs would have potent in vivo effects on lymphoma growth was validated using a Raji lymphoma xenograft model (Tuscano et al., 2003) and the HB22‐7 mAb (Engel et al., 1993). These Raji xenograft studies also assessed whether blocking CD22 ligand binding would be additive or synergistic when combined with radioimmunotherapy to enhance apoptosis induced by low dose–rate radiation. Surprisingly, mice treated with naked HB22‐7 mAb alone had impressive tumor volume reductions 14 days after treatment, with superior cure and survival rates when compared to other treatment groups. The combination of HB22‐7 mAb with radioimmunotherapy also significantly enhanced the magnitude of tumor volume responses if HB22‐7 mAb was given simultaneously or 24 hours after radioimmunotherapy, with superior response rates and survival. Based on these preclinical studies, the National Cancer Institute has humanized the HB22‐7 mAb, with lymphoma clinical trials scheduled to start in 2006. In addition, we have generated mouse anti‐mouse CD22 mAbs that block ligand binding (unpublished). In early preclinical studies, mAbs that block CD22 ligand binding also appear effective in inhibiting syngeneic tumor growth in mice. These findings complement the findings obtained with normal B cells and further suggest that both normal and malignant B cells require CD22 ligand binding for survival. 9. CD22-Directed Therapies and Clinical Trials in Autoimmunity Autoimmune diseases represent complex disorders characterized by adaptive immune responses that are inappropriately directed against self‐Ags. Despite this complexity, B cells are important contributors in the pathogenesis of autoimmunity, beyond their ability to produce autoantibodies (Chan et al., 1999; Chan et al., 1999; Madaio, 1998; Tuscano et al., 2003). This has provided new incentives to identify the multiple checkpoints that control both positive and negative selection of B cells, both centrally in the bone marrow and in peripheral lymphoid tissues. This complex series of checks and balances is necessary to allow the production of a large and diverse population of B cells capable of generating high affinity effector antibodies that have been purged of pathological autoreactivity. As a result, perturbations in select regulatory

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pathways that affect B‐cell function or selection may lead to autoimmune disease. Two broad categories of defects that lead to autoimmunity have been identified: those that alter signal transduction thresholds for cellular activation and those that alter B‐cell longevity. Given that CD22 regulates both signal transduction thresholds and B‐cell longevity, it is not surprising that CD22 has been implicated in the development of autoimmunity, at least in mouse models of disease. 9.1. Altered B‐Cell Activation and Survival Can Lead to Autoimmunity Because the generation and maintenance of self‐reactive B cells is regulated in part by signaling through the BCR complex, defective activation pathways that regulate BCR signaling can predispose to autoimmunity (Tedder, 1998). Consequently, peripheral tolerance is disrupted in mice that overexpress CD19 (Engel et al., 1995b), which results in hyperactive B cells and the spontaneous production of IgG subclass autoantibodies (Inaoki et al., 1997; Sato et al., 1996b). In fact, mice that have only a 15–30% increase in CD19 expression have a profoundly different phenotype from normal controls, developing autoimmune disease‐like manifestations in normally nonautoimmune strains of mice (Sato et al., 2000). Surprisingly, CD19 expression levels are also 20% higher on B cells from systemic sclerosis (SSc) patients compared with healthy individuals (Sato et al., 2000). Autoantibodies are detected in more than 90% of SSc patients and are considered to play a critical role in SSc pathogenesis (Okano, 1996). Like mice that overexpress CD19, the tight‐skin mouse, a genetic model for human SSc, also contains spontaneously activated B cells and autoantibodies against SSc‐specific auto‐Ags (Saito et al., 2002). CD19‐deficiency in tight‐skin mice results in quiescent B cells, with significantly reduced autoantibody production and skin fibrosis (Saito et al., 2002). Thus, modest alterations in CD19 or CD22 function could contribute to autoantibody development in humans. B cells from mice expressing a hypomorphic CD21 molecule or CD21 / mice express 30–50% increased densities of cell surface CD19 (Haas et al., 2002; Hasegawa et al., 2001). Multiple studies have suggested that altered CD21 function correlates with autoimmunity in mouse models (Boackle et al., 2001; Prodeus et al., 1998). Moreover, subtle alterations in the expression or function of other regulatory molecules involved in the CD19 signal transduction pathway may also predetermine autoimmunity susceptibility. Lyn‐deficient mice exhibit glomerulonephritis due to the presence of autoantibody immune complexes (Hibbs et al., 1995; Nishizumi et al., 1995). Moth‐eaten viable mice with catalytically compromised SHP1 (Kozlowski et al., 1993; Schultz et al., 1993) also demonstrate elevated levels of spontaneous autoantibodies,

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hypergammaglobulinemia, and tissue deposition of immune complexes (Tsui et al., 1993). Thus, mice with altered CD22, CD19, CD21, Lyn, or SHP1 expression are predisposed to produce autoantibodies and develop autoimmunity to varying degrees. Although speculative, it is possible that graded alterations in expression or function in these or other ‘‘response‐regulators’’ may result in the spectra of autoantibody specificities that characterize different autoimmune diseases. These findings suggest that antagonizing B‐cell signal transduction is a valid therapeutic strategy for patients with autoimmune disease. Altered expression of factors that regulate B‐cell survival can also lead to autoimmunity. One of the first examples of dysregulated apoptotic regulatory genes leading to autoimmunity was transgenic expression of dysregulated Bcl‐2 in mice, which allowed the inappropriate survival of autoreactive B‐cell clones that normally are lost through negative selection and apoptosis (Strasser et al., 1991). Bcl‐2 transgenic mice develop anti‐nuclear antibodies and have glomerulonephritis due to immune complex deposition. MRL mice provide a second example where homozygous mutations in the Fas gene (MRLlpr/lpr), encoding a death‐inducing receptor required for normal regulation of lymphocyte life spans, leads to a spectrum of autoreactivity resembling that found in human systemic lupus erythematosus (SLE) and other autoimmune diseases (Theofilopoulos, 1992). B‐cell depletion in autoimmune MRL mice blocks the manifestations of nephritis such as glomerulonephritis due to immune complex deposition, and also blocks cellular infiltrates into the kidney and vasculitis (Shlomchik et al., 1994). Intrinsic defects in external signals can also allow autoreactive B cells to escape deletion. One such signal comes from cytokines that are particularly important in B‐cell growth, differentiation, and survival. BAFF (B‐cell Activating Factor; also known as BlyS, TALL‐1, THANK, and zTNF4) is a member of the TNF family of cytokines that is produced by neutrophils, dendritic cells, and macrophages (Mackay et al., 2005). It induces immature B‐cell survival and growth of mature B cells within peripheral lymphoid tissues. BAFF binds three receptors; BCMA (B‐cell maturation Ag), TACI (transmembrane activator and calcium‐modulator and cyclophilin ligand interacter), and BAFF‐ receptor. Through these receptors, BAFF acts as a potent costimulator for B‐cell survival when coupled with BCR ligation. BAFF ligation correlates with increased Bcl‐2 expression and increased activation of NF‐kB, both of which increase B‐cell survival. Mice transgenic for either BCMA or BAFF have SLE‐ like disease, with anti‐DNA antibodies, elevated serum IgM, vasculitis, and glomerulonephritis (Mackay et al., 2005). Moreover, BAFF expression is elevated in MRLlpr/lpr mice and (NZB X NZW) F1 hybrid mice and correlates with disease progression in both models of autoimmunity (Gross et al., 2000).

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Elevated BAFF levels are also found in a significant number of SLE patients. These findings suggest that antagonizing B‐cell survival is a valid therapeutic strategy for patients with autoimmune disease. 9.2. Potential Role for CD22 in Autoimmunity In addition to regulating B‐cell apoptosis and normal BCR and CD19 signal transduction, defects in CD22 or its related signaling pathways contribute to the pathogenesis of abnormal B‐cell function. That the extracellular ligand‐ binding domains of CD22 are divergent in autoimmune strains of mice suggests that CD22 may directly influence autoantibody production or may contribute to the severity of autoimmune disorders (Mary et al., 2000). First, at least three alleles of the mCd22 gene have been identified that encode proteins that are 3% different in amino acid sequence (Law et al., 1993). One of these, the Cd22a allele, is uniquely found in some autoimmune‐prone strains of mice (DBA/1, DBA/2J, NZB, NZW, NZC, PL/J, and AKR/J) (Lajaunias et al., 1999; Nadler et al., 1997). The Lyb‐8.2 allele found in BALB/c and most other mouse strains is named Cd22b/Lyb‐8b and the DBA mouse allele is named Cd22a/Lyb‐8a (Law et al., 1993). Dramatic differences occur in the two amino‐terminal Ig domains encoded by these alleles; 16 amino acid substitutions are found as well as a 6 amino acid insertion in the first Ig domain of the Lyb‐8.2 allele. These changes explain the presence of the Lyb‐8.2 allele defined by the CY34 mAb that binds an epitope dependent on residues in both domains 1 and 2, while the NIM‐R6 mAb binds more membrane proximal Ig domains (Law et al., 1995; van der Merwe et al., 1996). One Thr‐to‐Met amino acid substitution occurs in the cytoplasmic domain, but none of the six Tyr residues conserved between hCD22 and mCD22 are affected. A third Cd22c/Lyb‐8c allele has been identified in BXSB mice which are lupus‐prone (Lajaunias et al., 1999). Furthermore, there are six gene sequence differences between BALB/c and C57BL/6 mice (Lajaunias et al., 1999; van der Merwe et al., 1996). CD22 in MRL mice is identical to CD22 of BALB/c mice with the exception of single amino acid changes in Ig domains 2 and 7, and the transmembrane domain, which are id entical to those found in C57BL/6 mice (Lajaunias et al., 1999). Nonetheless, the Cd22a allele present in multiple autoimmune‐prone strains of mice is likely to have been disseminated by a precursor strain that contributed to all of these lines. Although not proven, multiple investigators postulate that CD22 allelic differences contribute to autoimmunity. Consistent with this, the proximal region of chromosome 7 containing the Cd22 locus is implicated in the development of SLE‐like disease in NZM and NZW mice (Kono et al., 1994; Morel et al., 1994; Santiago et al., 1998). In addition, NZW

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mice synthesize aberrant CD22 mRNAs, some of which interfere with upregulated cell surface CD22 expression on NZW B cells following LPS exposure (Mary et al., 2000). Thus, CD22 genetic polymorphisms may contribute to autoimmunity. A second line of evidence that CD22 influences the development of autoimmunity is that one CD22 / mouse line has increased autoantibody production with age, including antibodies against double‐stranded (ds) DNA and dsDNA‐histone complexes (O’Keefe et al., 1996, 1999). Heterozygous CD22þ/ C57BL/6 mice carrying the autoimmune acceleration gene, Yaa, also have markedly increased production of IgG anti‐DNA autoantibodies (Mary et al., 2000). The hyperactivated status of CD22 / B cells is consistent with susceptibility to autoimmunity such that CD22 may augment autoimmune disease once induced or when combined with increasing age, other disease susceptibility loci, or pathogens. Alternatively, it has been proposed that CD22 ligand engagement prevents the development of autoimmunity (Lanoue et al., 2002). By contrast, our line of CD22 / mice develops hypergammaglobulinemia with age, with autoantibody levels merely paralleling increased serum Ig levels (unpublished observations). Thus, in this line of mice, CD22‐deficiency appears to result in overall B‐cell hyperactivity rather than preferentially supporting the expansion of autoreactive clones. Furthermore, estrogen administration, which accelerates and exacerbates autoimmunity in mice (Grimaldi et al., 2001) specifically upregulates CD22 and SHP1 levels in B cells (Grimaldi et al., 2002). The authors suggest that CD22 overexpression may reduce the occurrence of BCR‐induced apoptosis in autoreactive cells and promote their survival. Thus, there is evidence for CD22 deficiency as well as CD22 overexpression in influencing autoimmunity. A third line of evidence is that CD22 is the primary phosphoprotein associated with SHP1 in B cells (Sato et al., 1997). CD22 also regulates CD19 function. We have shown that augmented CD19 function induces autoimmunity in mice independent of its effects on the B‐1 population of B cells (Fujimoto et al., 1999a; Sato et al., 1996b). In fact, only a 20% increase in CD19 expression induces autoimmunity in mice with the onset and severity of autoimmunity linearly correlated with CD19 expression levels (Sato et al., 1996b, 2000) that correlates with a breakdown in B‐cell tolerance (Inaoki et al., 1997). Moreover, B cells from SHP1‐defective, CD22 / , and CD19‐ overexpressing mice are all hyperresponsive to activation signals (Pani et al., 1995) and have an IgMlo MHC class IIhi phenotype (Cyster and Goodnow, 1995). That autoimmunity and immune responses are regulated or ‘‘fine‐ tuned’’ by CD19‐dependent signal transduction pathways explains why subtle increases in CD19 expression or decreased CD22 function affects the onset

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or development of autoimmunity (Sato et al., 1996b, 2000; Tedder et al., 1997a, 2000). Whether these principles apply to humans remains unknown because combinations of subtle genetic alterations are likely to dysregulate normal B‐ cell function and thereby confer susceptibility to autoimmune disease. Regardless, these studies provide sufficient justification to assess this possibility and to determine whether alterations in CD22‐regulated signaling pathways and the resulting defects in B‐cell survival contribute to or inhibit autoimmunity. 9.3. Potential Role for MZ B Cells in Autoimmunity MZ B cells represent a B‐cell population that is highly susceptible to alterations in CD22 expression and function (Poe et al., 2004a; Samardzic et al., 2002; Sato et al., 1996a). This is important because MZ B cells display a diverse repertoire of BCR specificities that bind T‐cell‐independent and T‐cell‐dependent Ags, as well as self‐Ags (Martin and Kearney, 2002). Indeed, self‐reactive MZ B‐cell clones are found in both normal (Chen et al., 1997) and autoimmune strains of mice (Wellmann et al., 2001). The MZ B‐cell population is expanded in (NZB X NZW) F1 mice prior to disease development (Wither et al., 2000) and transgenic mice overexpressing BAFF exhibit MZ B‐cell expansion (Batten et al., 2000; Mackay et al., 1999). Similarly, pristane administration causes lupus‐like symptoms in mice and also leads to MZ B‐cell expansion (Yang et al., 2003). MZ B cells can produce autoreactive antibodies either spontaneously or under activating conditions. CD1dhi MZ B cells from (NZB X NZW) F1 mice spontaneously produce high amounts of IgM anti‐ DNA Abs (Zeng et al., 2000). Furthermore, estrogen treatment results in the expansion and activation of autoreactive MZ B‐cell clones in anti‐DNA heavy chain transgenic BALB/c mice (Grimaldi et al., 2001). The expansion and activation of autoreactive MZ B cells may be an important observation for certain disease pathologies as salivary glands become infiltrated with B cells expressing a MZ B‐cell phenotype in autoimmune mice overexpressing BAFF (Groom et al., 2002). B cells with a MZ B‐cell phenotype are also found to infiltrate the thyroid in patients suffering from Graves’ disease (Segundo et al., 2001). Thus, there is considerable evidence that MZ B cells participate in the development and exacerbation of autoimmunity. Because altered CD22 expression or blocking CD22 ligand binding can dramatically attenuate MZ B‐cell numbers, CD22 may be an important therapeutic target for eliminating MZ B cells. The development of BAFF antagonists encompasses a similar rationale. Thus, CD22‐directed therapeutics may allow for the manipulation of this unique population such that their involvement in autoimmunity can be controlled.

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9.4. CD22 Therapeutic Applications in Autoimmunity The importance of B‐cell survival in vivo is well appreciated, leading to the pursuit of therapies that influence this potent biological outcome. By interfering with B‐cell survival and enhancing B‐cell turnover, it is envisioned that B cells or B‐cell subsets can be specifically targeted without the risk of eliminating bulk B‐cell populations as with CD20‐directed therapies. Moreover, it may be possible to effect therapeutic benefit by attenuating B‐ cell responses to transmembrane signals without eliminating B cells that give rise to humoral immunity. Although CD40–CD40 ligand (CD40L) interactions are critical for normal B‐ and T‐cell interactions and mAbs against these therapeutic targets have demonstrated efficacy in mice, human clinical trials targeting this pathway have been disappointing. In fact, two trials assessing anti‐CD40L mAbs have been abandoned due to either lack of efficacy or unexpected toxicity (Davis et al., 2001; Huang et al., 2002). Other potential targets for treating B‐cell‐mediated human autoimmune diseases include BAFF antagonists and BMCA‐Ig and TACI‐Ig fusion proteins as decoy BAFF receptors (Gross et al., 2001). Administration of BMCA‐Ig or TACI‐Ig to (NZB X NZW) F1 mice leads to increased survival, decreased proteinuria, and slowed disease progression. Recent trials of CTLA‐4‐Ig fusion proteins that disrupt T‐cell–B‐cell interactions and T‐cell activation have been promising in the treatment of rheumatoid arthritis, showing moderate efficacy with no evidence of significant toxicity (Kremer et al., 2003). Accelerated B‐cell apoptosis and turnover by therapeutic mAbs that block CD22 ligand engagement may also have considerable benefit for the treatment of autoimmunity (Tuscano, Harris, and Tedder, 2003). Thus, interfering with B‐cell survival represents a valid and exciting approach for the treatment of autoimmunity. 10. Conclusions CD22 acts as a multifunctional receptor by participating in ligand‐dependent and ligand‐independent pathways, which may function independently or converge to ultimately regulate the generation of physiologically relevant responses to foreign or self‐Ags. Although a considerable amount of new information is available regarding CD22 function, further knowledge is essential for understanding how CD22 governs events critical for B‐cell selection, activation, and differentiation during immune responses. Better understanding of CD22 function and regulation may provide mechanisms by which humoral immunity can be modulated, leading to the development of new strategies to augment antimicrobial defense and acquired immune responses, and the development of novel approaches for modulation of chronic infections and

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Tetramer Analysis of Human Autoreactive CD4‐Positive T Cells Gerald T. Nepom Benaroya Research Institute at Virginia Mason, Seattle, Washington 98101 Abstract............................................................................................................. 1. pMHC Tetramers Identify Human Autoreactive T Cells ............................................. 2. Autoantigen pMHC Tetramers from Mouse to Man................................................... 3. Tetramer‐Induced Autoreactivity ............................................................................ References .........................................................................................................

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Abstract Self‐reactivity is an intrinsic property of the human immune system. Autoreactive T cells derive directly from the developmental requirement for TCR engagement by self‐antigens during lymphocyte maturation. The fundamental questions implicating these autoreactive cells in human autoimmunity then, are not ‘‘Where do they come from?’’, but rather ‘‘Why do they persist?’’, ‘‘How do they become activated?’’, and ‘‘How are they regulated or deleted?’’. New technologies, in which peptide‐MHC (pMHC) ligands used for T‐cell recognition are utilized as soluble fluorescent multimers, now permit the direct visualization of antigen‐specific autoreactive T‐lymphocytes. By using multimer technology to study self‐reactive cells present in autoimmune patients and control individuals, a very broad range of autoreactive potential has been identified. 1. pMHC Tetramers Identify Human Autoreactive T Cells Structural studies demonstrate that the variable chain segments of the T‐cell receptor bind to the pMHC complex through a combination of conserved structural determinants and unique contact interactions with highly variable residues. A single T‐cell receptor can bind and interact with a single pMHC complex; however, T‐cell activation requires at least a dimer or pseudo‐dimer interaction (Krogsgaard et al., 2005), and higher order multimers lead to more avid binding properties (Cochran, Cameron, and Stern, 2000). This property is exploited in the construction of soluble fluorescent pMHC ligands, which are generally used in the form of tetramers, in which four biotinylated pMHC monomers are joined via binding to streptavidin (Novak et al., 1999; Altman et al., 1996). These tetramers are surrogate ligands for recognition by the antigen‐specific T‐cell receptor, and bind to T cells based on the antigen specificity and MHC restriction properties of an individual T cell.

51 advances in immunology, vol. 88 # 2005 Elsevier Inc. All rights reserved.

0065-2776/05 $35.00 DOI: 10.1016/S0065-2776(05)88002-2

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Figure 1 illustrates the identification of antigen‐specific T cells from peripheral blood, in which HLA‐DR4 MHC molecules and peptides from viral proteins of herpes simplex virus 2 or influenza virus, or from the self‐antigen glutamic acid decarboxylase, were utilized to make different pMHC tetramers. In the example shown, a large number of influenza‐specific T cells were visualized by flow cytometry, but no HSV‐specific T cells were present. T cells specific for the autoantigen GAD65 were also readily observed. Indeed, detection of autoreactive T cells using tetramers is not rare, and has been reported in a number of interesting clinical situations. For example, autoantigen tetramer‐binding CD8þ T cells were detected in peripheral blood from patients who had received allogeneic heart transplants (Barber et al., 2004). In this study, six patients who had antivimentin antibodies after cardiac transplantation were tested, and two reacted with specific HLA A*0201 Class I tetramers containing vimentin peptides. There are many reports of similar pMHC tetramer reactivity for peptide‐ HLA A2 tetramers representing cancer‐associated antigens; for example, recognizing the P53 (264–272) peptide (Hoffmann et al., 2002) or a Her2/Neu E75 peptide in peripheral blood of breast and prostate cancer patients receiving Her2/Neu vaccine immunotherapy (Woll et al., 2004). In other examples, the pMHC epitopes recognized are not associated with known oncogenes, but are associated with self‐proteins expressed or overexpressed in growing tumors; for example, HLA‐A2 tetramers with an a‐actinin peptide interacting with CTL clones derived from PBL of a patient with lung cancer (Mami‐ Chouaib et al., 2002) and HLA‐A24 tetramers containing an Syt‐SSX peptide which identified CTL in the blood of patients with synovial carcinomas (Sato et al., 2002). The most detailed studies of self‐antigen tetramers for detecting CD8 T cells directed to tumors come from the study of malignant melanoma, in which tetramers to MELAN‐A/MART‐1, MAGE‐4, NY‐ESO‐1, and GP100 have all been used successfully to detect antigen‐specific CD8þ T cells in patients before or after immunotherapy (Cohen et al., 2003; Hu et al., 2004; Jager et al., 2002; Kobayashi et al., 2003; Reynolds et al., 1998; Speiser et al., 2002; Valmori et al., 2003; van Rhee et al., 2005). With respect to the CD4þ T‐cell response to autoantigens, identification of tetramer‐binding T cells may simply be a matter of looking in the right way. That is, it is possible that the peripheral T‐cell repertoire is capable of recognizing self‐specificities for most dominant peptide‐epitopes, likely reflecting the developmental history of T cells that encountered similar pMHC targets during selection. This concept was directly tested (Danke et al., 2004) by generating three diverse pMHC tetramers to self‐specificities, one associated with the melanocyte differentiation antigen tyrosinase, one for the cancer/testes tumor antigen NY‐ESO‐1, and one for the diabetes-associated

53 Figure 1 Flow cytometry of peripheral blood lymphocytes (PBL) utilizing pMHC tetramers. Two‐color fluorescence detection of cells that bind anti‐ CD4 mAb and pMHC tetramers are shown for HLA‐DR4 MHC molecules containing peptides from epitopes of influenza (HA), HSV‐2 (control), and the autoantigen glutamic acid decarboxylase (GAD65). PBL from an HLA DR4‐positive subject were cultured in vitro with the corresponding antigen for 10 days to expand the responding population prior to cytometry analysis. Large numbers of HA‐specific and GAD‐specific CD4þ T cells were present, illustrating the utility of this methodology for detection of T cells responding to foreign and self‐antigens, respectively.

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auto‐antigen glutamic acid decarboxylase. CD4þ T cells specific for each of these tetramers were readily identified in peripheral blood of normal, healthy human individuals; notably, however, detection was possible only after removal of regulatory T‐cell populations, using specific antibody depletion of CD4 þ CD25 þ T cells (Treg). The most straightforward interpretation of these results is that autoreactive cells to many self‐antigen pMHC targets may well be present in most or all individuals, with the caveat that detection using pMHC tetramers requires matching the MHC, choosing a reasonably dominant peptide epitope, and importantly, unmasking the autoreactive specificities by depletion of regulatory elements which suppress the antigen‐induced expansion of the autoreactive populations. 1.1. Stages of Autoimmune T‐Cell Expansion and Activation The concept that pMHC tetramer‐positive autoreactive cells circulate in the periphery of normal individuals is consistent with models of autoimmunity in which the MHC genetic predisposition to specific autoimmune diseases is reflected in the developmental T‐cell selection of potentially autoreactive T cells. Figure 2 illustrates such a model, previously developed to track progression of autoimmunity in people at risk for type‐1 diabetes (T1D) (Nepom and Kwok, 1998). In this model, the first key step is the selection of a repertoire of thymocyte specificities based on pMHC interactions during T‐cell maturation in the thymus. In this stage, the HLA allelic polymorphism of each individual determines the spectrum of dominant autoreactive epitopes used as a basis for T‐cell selection. These T cells mature into peripheral populations which are potentially autoreactive, restricted by the MHC used for selection, and can be directly observed by expansion from peripheral blood using either the original self‐antigen or a peptide mimetic. Data indicating that expansion of these cells is unmasked by depletion of regulatory T‐cell populations in normal individuals suggest that the potential for autoreactivity is actually a normal, unavoidable, and readily documented result of this first step of the autoimmunity pathway model (Danke et al., 2004). Tetramer analysis of CD4þ T cells in the murine model of diabetes in the NOD mouse also supports this paradigm. In one study (Stratmann et al., 2003), pMHC tetramers with the NOD MHC IAg7 were constructed using peptide mimetics for a specificity known to be represented in the T‐cell populations infiltrating islets in diabetic mice. Tetramer-positive T cells were identified in these studies in the pancreatic lymph nodes associated with diabetic and prediabetic animals. Notably, however, they were also identified in the nondiabetic strains of mice that shared the same IAg7 MHC. In other

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Figure 2 The ‘‘hopscotch’’ pathway toward autoimmune disease. Selection, expansion, and activation of autoreactive T cells occur in an ordered progression of steps punctuated by functional stages of disease. In the first stage, genetic traits, particularly MHC susceptibility genes, are permissive for selection of autoreactive specificities during thymocyte development. The specific pMHC interactions with TCR at this stage determine thresholds for T‐cell activation and survival, which create an avidity window for future events. Individuals with disease‐associated MHC genes jump to this first stage expressing potentially autoreactive peripheral T‐cell repertoires. In the second stage, these autoreactive cells encounter stimuli that lead to proliferation and expansion. These peripheral stimuli are likely to be very diverse and variable between different individuals, and include various viral exposures, transient tissue damage, and even nonspecific inflammatory events; The increase in the circulating number of autoreactive T cells at this step overcomes a stochastic barrier such that specific autoreactive cells may now encounter their cognate autoantigen, resulting in activation and triggering a complex cascade of immunologic effector functions. In the third stage, autoreactive lymphocytes must jump regulatory barriers, which include a set of protective mechanisms such as activation‐induced cell death and transacting suppressor cells. These regulatory barriers arrest progressive autoimmunity in most cases, but when overcome or bypassed, are manifest as the final stage of overt autoimmune diseases.

words, the primary determinant of the presence of tetramer-positive autoreactive cells was not the disease phenotype, but was the MHC of the host. This is consistent with the preceding model, namely that the first stage in the autoimmune pathway, the selection of potentially autoreactive T cells, appears to be a normal physiologic consequence of T‐cell selection, and can be directly observed both in humans and mice, using pMHC tetramers with dominant self‐epitopes. 1.2. Properties Associated with Self‐pMHC Recognition Although studies using tetramers of self‐pMHC complexes readily identify autoreactive T cells, there may nevertheless be key differences between pMHC tetramers containing self‐antigens, compared to similar tetramers with foreign nonself antigens. The frequency of specific pMHC tetramer-binding cells and the avidity of the TCR interaction with the pMHC tetramer both

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appear to be much lower for self‐pMHC recognition. Table 1 summarizes data from several studies in which pMHC tetramers specific for the hemagglutinin of influenza and pMHC tetramers specific for the GAD65 epitope associated with autoimmune diabetes were tested in the same individuals. In general, three properties distinguish the self and the nonself recognition profiles in these studies. First, the frequency of T cells autoreactive to GAD65 is lower than the frequency of cells reactive to influenza HA. While this undoubtedly reflects the fact that most people have either been infected or vaccinated with influenza, it also may indicate that there are biological constraints on the in vivo expansion of the autoreactive specificities. A second difference is the overall TCR‐pMHC avidity, as determined by tetramer binding. The vast majority of influenza HA reactive CD4þ T cells derived from peripheral blood will bind MHC tetramers containing the relevant specificity (Novak et al., 2001). In contrast, only one third to one half of the GAD65-reactive T cells derived from peripheral blood are highly avid binders to pMHC tetramers containing the relevant GAD epitopes (Reijonen et al., 2004). In the latter study, the GAD-responsive T cells represented a broad spectrum of receptor specificities and pMHC binding avidities, and measures of T‐cell activation, such as cytokine release and proliferation, were more sensitive for detection of the antigen‐specific populations than pMHC tetramer binding, which was limited to the high‐avidity cells. In these examples, the self‐ and non‐self‐peptides are both immunodominant in the context of the same HLA class II molecules, and both have similar binding affinities for the peptide‐MHC interaction, so that differences in pMHC tetramer binding to T cells largely reflects the receptor avidity properties of the T‐cell specificity. These differences not only reflect inherent differences between self and nonself recognition, but also provide important clues regarding the Table 1 Characteristics of pMHC Tetramer Interactions Property of CD4þ T cell 1. Frequency in peripheral blood 2. Proportion of antigen‐responsive T‐cell population which binds pMHC Tetramers 3. Avidity for pMHC 4. Lineage

HA (nonself) recognition

GAD (self‐antigen)

High (1/6,000–1/30,000)

Low (1/20,000–1/100,000)

High

Low

High TH1 > TH0

Low TH0 > TH1

Differences which have been observed between CD4þ T cells that bind self‐pMHC tetramers compared to non‐self‐antigens. For the most part, these properties are characteristic of the average response within a broad distribution, so that while high‐avidity cells do exist within the self‐pMHC binding population, this is much reduced compared to a foreign antigen response.

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amplification and the activation steps in the cascade of autoimmune progression presented in Fig. 2. Overall, the spectrum of avidity for dominant self‐antigens may be quite a bit lower than the spectrum for traditional foreign antigen responses, a result which was previously suggested by studies of HLA transgenic mice immunized with either HA or GAD65 (Gebe et al., 2003). Whether this difference is due to the lack of survival of high‐avidity autoreactive T cells through a process of thymic negative selection, or whether it is due to activation‐induced cell death and selective deletion of high‐avidity cells in the peripheral T‐cell population, is not known. In either case, however, it may reflect a fundamental fail‐safe mechanism that the immune system has utilized to attempt to prevent deleterious autoimmunity. In the pathway model described in Fig. 2, after initial selection of the autoreactive T cell, some peripheral expansion is necessary to raise the frequency of these cells in the periphery, to the point where they achieve a threshold poised for subsequent activation. Definitive precursor frequency calculations using self‐antigen pMHC tetramers have not yet been reported for human CD4þ autoreactive T cells. Using tetramer binding as a rough correlate of T‐cell frequency, however, suggests that there is at least a 5‐ to 10‐ fold expansion of autoreactive T cells distinguishing patients with clinical autoimmunity from at‐risk or normal HLA‐matched individuals (Reijonen et al., 2002). Extrapolation of these results to data derived from studies of influenza HA pMHC tetramers, in which tetramer binding correlated directly with measured precursor frequencies (Danke and Kwok, 2003), suggests that this amplification checkpoint may represent a transition from an autoreactive T‐cell frequency of less than 1 in 100,000 to a frequency as high as 1 in 20,000. Subsequent activation of these autoreactive T‐cells, termed ‘‘autoimmune triggering’’ in Fig. 2, very likely requires specific antigen presentation and local microenvironments associated with proinflammatory immune responses. Indeed, given the presence of autoreactive cells as a normal physiologic state, this step, which probably involves dendritic cell presentation of tissue‐specific antigens occurring in complex lymphoid environments, is the key triggering step in autoimmunity and plays a major role in directing the subsequent immune response toward specific outcomes. During this triggering event, establishing initial T‐cell phenotypes becomes one of the key elements that control the distinction between pathological expansion and a benign, subclinical persistence of autoreactive cells. In our studies of T‐cell phenotypes expressed by tetramer‐binding cells in human peripheral blood, the majority of pMHC‐positive cells derived to foreign antigens like influenza HA express a functional phenotype, which is partially polarized toward TH1 characteristics. Thus, these cells are commonly producers of g‐interferon, and are often low in the production of TH2‐like cytokines

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such as IL10 and IL4. In contrast, the pMHC tetramer‐positive cells specific for the GAD65 autoantigen have been less TH1 polarized. In most cases, they produce a multitude of heterogeneous cytokines, including IL13, IL5, and lower levels of g‐interferon, a phenotype sometimes referred to as TH0. This phenotypic generalization partially correlates with the avidity differences which correspond to self‐ and non‐self‐recognition profiles, but is not absolute, and numerous exceptions exist (Holzer et al., 2003). 1.3. Regulatory Control of pMHC Reactivity The last stage in Fig. 2 represents the regulatory immune response, which is the final arbiter of clinical autoimmunity in the face of activated autoreactive cells. Various mechanisms for immune regulation coexist in multiple compartments and involve many different cells. The studies discussed previously (Danke and Kwok, 2003; Danke et al, 2004), in which normal individuals show GAD65 pMHC tetramer‐positive cells after depletion of regulatory lymphocytes, contrast with the similar observation of GAD65 pMHC tetramer-positive cells in the blood of T1D subjects, which indicates that overt autoimmunity is detectable in these subjects without removal of regulatory cells (Reijonen et al., 2002). This observation suggests the hypothesis that autoimmunity has progressed to disease in T1D patients in part due to a spontaneous loss of regulatory competence. Either the autoreactive T cells have become refractory to regulation, or the regulatory components of the immune response failed to function properly. This regulatory step, the final stage in the proposed pathway model, has only recently been investigated using pMHC tetramers. Characteristics of human Treg were analyzed in terms of lineage and antigen specificity. In their initial report (Walker et al., 2003), a system was described for generating human CD4þ CD25þ T cells in vitro which function to suppress other T‐cell responses. This suppressor function was dependent upon activation via the T‐cell receptor. Once activated, these Treg were able to suppress bystander T‐cell responses, consistent with their activity in animal models of autoimmunity in which a broad therapeutic benefit was achieved with transfer of similar antigen‐specific Treg (Tang et al., 2004; Tarbell et al., 2004). These studies were then extended by utilizing pMHC tetramers to identify and generate antigen‐specific Treg (Walker et al., 2005). In this study, a population of Treg was generated through the antigen‐specific expansion of previously nonregulatory CD4þ CD25‐ responder T cells, followed by isolation of pMHC tetramer-binding CD4þ CD25þ cells utilizing flow cytometry. These tetramer‐positive cells were then secondarily expanded in the presence of antigen to yield a population of Treg that functions in an antigen‐specific manner. That

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is, triggering of regulatory function in these cells required contact with specific peptide MHC ligands. As with other Treg populations, the effector function of the antigen‐activated regulatory cells provided bystander suppression for other T‐cell responses as well. These findings suggest several opportunities for utilizing specific pMHC recognition to expand and elicit regulatory function in an antigen‐specific manner. In the context of human autoimmunity, identification of dominant pMHC epitopes is a necessary prerequisite for testing this novel therapeutic pathway, and is a logical, practical application for utilizing tetramers with autoreactive specificity. 2. Autoantigen pMHC Tetramers from Mouse to Man The essential requirements for using pMHC tetramers to study autoimmune disease are: knowledge of the relevant MHC, information regarding dominant T‐cell epitopes, and suitable access to lymphoid cells for analysis. All three of these requirements pose major challenges in human clinical applications, with useful insights coming from mouse models. Tetramers have been used to study autoreactive T cells in spontaneously occurring T1D models in the NOD mouse, and in the antigen‐elicited models of experimental autoimmune encephalomyelitis (EAE) and collagen‐induced arthritis (CIA). In the NOD diabetes model, both CD4 and CD8þ lymphocytes are known to be important for disease pathogenesis. However, in neither case are dominant pMHC targets known. To circumvent this problem, pMHC tetramers have been devised that utilize peptide‐mimetic sequences, selected by library screening approaches, which act as surrogates for the autoantigen pMHC recognition. In these studies (Jang, Seth, and Wucherpfennig, 2003; Stratmann et al., 2003), MHC class II molecules from the IAg7 haplotype were used for tetramers coupled to a peptide mimotope which acted as a surrogate ligand for islet‐specific T cells. This mimotope was originally isolated from a chemically synthesized random peptide library, based on its ability to stimulate a pathogenic T‐cell clone known as BDC‐2.5 (Yoshida et al., 2002). The BDC‐ 2.5 T cell had originally been cloned from diabetic NOD mice, and was shown to be able to transfer diabetes, therefore qualifying as a pathogenic T‐cell specificity, even though the native target is not known. It was demonstrated that tetramers containing IAg7 with the peptide mimotope reacted with T cells in the pancreatic and iliac lymph nodes, with frequencies from 0.05–0.15%, and were found as early as 2 weeks of age, well in advance of clinical disease (Stratmann et al., 2003). In histologic sections of pancreas, pMHC tetramerbinding T cells were also directly identified by immunocytochemistry. Tetramer‐ positive cells increased in number as the mice aged, and recovery of some

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of the tetramer‐positive cells yielded T‐cell clones with a wide range of TCR usage, antigen avidity, and cytokine production. A notable finding in this study was that congenic strains of mice that carry the same MHC haplotype as the NOD mouse but differed in other loci, were also studied. These strains are fully resistant to diabetes, yet the tetramer‐ positive cells were easily detectable in lymphoid organs, with distribution and numbers comparable to the NOD mouse. This is an important observation, which clarifies the concept that the autoreactive‐pMHC specificity is a necessary, but not a sufficient pathogenic element required for autoimmune disease. In the T‐cell progression model outlined in Fig. 2, this pMHC specificity drives the first stage, in which autoreactive T-cell potential is selected, but does not determine T‐cell or disease outcome. An additional notable feature of their work was the use of a high‐avidity peptide mimotope, in order to successfully design pMHC tetramers which detected autoreactive peripheral T cells (Stratmann et al., 2003). This strategy, which has the potential to bypass the constraints of low‐avidity self‐antigen reactivity, was also utilized in prior studies of class I restricted CD8þ T‐cell autoreactivity in NOD mice. In another study, class I pMHC tetramers were designed using H2‐Kd, containing a peptide known as NRP‐V7 (Trudeau et al., 2003). This peptide is a high‐avidity mimetic for a CD8þ T‐cell epitope associated with diabetes in the NOD mouse, and tetramers using this pMHC mimetic detected autoreactive T cells infiltrating the pancreatic islets of diabetic NOD mice. Indeed, up to 10% of CD8þ-infiltrating T cells in the islets were bound by the high‐avidity NRP‐V7 pMHC tetramer. Notably, a tetramer made with the lower‐avidity native sequence NRP peptide identified few or none of the cells. Also, relative to the islet infiltrates, the frequency of tetramer‐positive cells in peripheral blood was very low, in all cases less than 1% of CD8þ cells. On the other hand, in mice who progressed to diabetes, most showed tetramer‐positive cells in the blood on at least one prior occasion. This study, similar to that of Stratmann, illustrates the advantages of using high‐avidity pMHC tetramers to detect what appear to be low‐avidity responses to islet-associated self‐antigens. The other notable finding in this study was that detection in peripheral blood is challenged by the low frequency of circulating autoreactive cells, relative to a much higher frequency in target organs. Two studies (Chen et al., 2003; Liu et al., 2000) generated pMHC tetramers using IAg7 complexed with epitopes from GAD65, as previous studies have implicated autoimmunity in GAD65 in pathogenesis of diabetes in the NOD model (Jun et al., 2002; Sercarz, 2003). However, no NOD T cells were identified which bound these tetramers, unless the animals were deliberately immunized to GAD65. Interestingly, in the latter case, tetramer‐ binding T cells were subsequently identified which expressed regulatory

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cytokines and inhibited diabetes development. This finding is consistent with other observations in transgenic and knockout genetic models which suggest that immunity to GAD65 in the NOD mouse may be predominantly biased toward disease suppression (Jaeckel et al., 2003; Kim et al., 2004). Recently three pMHC class I tetramers were described for additional CD8þ T‐cell epitopes associated with spontaneous autoimmune diabetes in NOD mice (Lieberman et al., 2004). In this study, in which b‐cell-reactive T cells were cultured from the islets of individual NOD mice, each individual mouse exhibited a distinct profile of pMHC tetramer‐positive T cells. This high degree of variation, even within a single inbred strain of diabetic mouse, highlights the challenge for identifying immunodominant epitopes, which can be well represented in the outbred and highly diverse human population. Class II MHC tetramers have also been used in two other murine models of autoimmunity which, in contrast to the NOD, do not get spontaneous disease but which respond to self‐antigen immunization with progressive autoimmune symptoms resembling clinical pathology. In the case of murine experimental autoimmune encephalomyelitis (EAE), disease in H‐2u animals is elicited using an immunodominant epitope of myelin basic protein, MBP1–9. In H2S animals, disease is induced with proteolipid protein 139–151. In studies in these models, pMHC tetramers containing the immunizing peptide were used to detect CD4þ autoreactive cells following immunization (Bischof et al., 2004; Radu et al., 2000; Reddy et al., 2003). Self‐antigen‐specific CD4þ T cells accumulated in the lymph nodes draining the immunization site, similar to standard primary immune responses, and subsequently entered the central nervous system. Also, tetramer‐positive cells which entered the CNS displayed activation markers that distinguish them from the larger pool of tetramer‐ positive cells that remain in the periphery. Tetramer studies in human subjects with autoimmunity are confounded by the same issues observed in the animal models, namely low‐frequency, low‐ avidity, and the constraints of utilizing peripheral blood for analysis, rather than lymph nodes or target tissue. The most extensive studies in humans have been in subjects with T1D, utilizing MHC class II tetramers (Reijonen et al., 2003; 2004; Reijonen, Kwok, and Nepom, 2003). In these studies, pMHC tetramers using HLA DR4 molecules complexed with an immunodominant peptide from the islet autoantigen glutamic acid decarboxylase (GAD65) have been used to evaluate CD4þ antigen‐specific T‐cell frequencies in the blood of T1D subjects and controls. Because the majority of patients with T1D carry at least one HLA DR4 haplotype, patient populations can be surveyed using a reasonably small number of pMHC combinations. Due to the very low frequency of autoantigen‐specific CD4þ T cells in peripheral blood, detection of tetramer interactions with specific T cells in these studies requires the in vitro

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expansion of the antigen‐responsive population. In the studies, this is accomplished by incubation of peripheral lymphocytes with antigen for 7–14 days prior to flow cytometry analysis using fluorescent pMHC tetramers (Reijonen et al., 2003, 2004). The majority of HLA DR4 T1D subjects tested have pMHC‐staining T cells in this system. Single cell sorting experiments were used to confirm the antigen specificity of the tetramer population which in addition to being specific for GAD65, tended to make a heterogenous set of cytokines following antigen activation, with some cells expressing TH1 properties and the majority expressing TH0 phenotypes. Analysis of the tetramer‐ positive T‐cell clones revealed a broad range of pMHC avidity, with some very high‐avidity responses and some very low. Thus, within a single individual, both high‐ and low‐avidity T cells coexist to the same autoantigen. Nondiabetic individuals are classified as ‘‘at risk’’ or ‘‘prediabetic’’ if they carry T1D susceptibility genes and if autoantibodies to islet antigens are present in serum. Interestingly, some but not all of these at‐risk HLA DR4 subjects were found to have peripheral CD4þ T cells binding the same pMHC tetramers. Whether this type of analysis will be a useful prognostic tool for disease progression and individual assessment of disease risk will require more extensive longitudinal studies. Class II pMHC tetramers for two other human autoimmune diseases have also been described, an HLA DQ2 tetramer containing peptides derived from gliadin for the study of celiac disease, and HLA DR4 tetramers containing collagen peptides for the study of rheumatic disease. A study used the gliadin pMHC tetramers to stimulate and bind T‐cell clones and lines which were expanded in vitro after isolation from intestinal biopsy tissue (Quarsten et al., 2001). Specificities associated with at least three different peptides from gliadins were identified, and it remains to be seen whether there are any immunodominant epitopes suitable for direct detection studies in blood or in tissue. In the case of the collagen pMHC tetramers, two studies (Buckner et al., 2002; Kotzin et al., 2000) described the use of HLA DR4 complexed with type II collagen epitopes, but failed to directly detect CD4þ antigen‐specific T cells in patients with rheumatoid arthritis or relapsing polychondritis, respectively. In the latter study, however, peripheral blood‐ derived T cells from patients with relapsing polychondritis were expanded in vitro, and subsequently shown to bind the collagen pMHC tetramer, which was also capable of activating the specific T cells (Kwok et al., 2002). Similar tetramers were used in a humanized animal model of arthritis, in which HLA DR4 transgenic mice were immunized with collagen and developed acutely arthritic joints (Svendsen et al., 2004). In these studies, tetramer‐positive cells that were present in blood after immunization accumulated in the lymph nodes, while levels declined in synovial fluid and blood. The mechanism for this shift was not determined, but as in the NOD model studies described

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previously, suggest the importance of evaluating different tissue compartments to fully evaluate the distribution of tetramer‐positive responses. These studies of tetramer‐binding properties reinforce the general features previously discussed, in that autoreactive T cells are generally of low‐frequency, low‐avidity, and variable phenotype when studied in the periphery of the autoimmune patient. However, they also shed new light on the biology of the autoreactive CD4þ T cell, in several respects. For example, the frequency of pMHC tetramer‐positive T cells waxes and wanes, as documented in the murine NOD (Trudeau et al., 2003) and CIA (Svendsen et al., 2004) studies, and both find that the peripheral blood compartment is quite different from tissue and lymph node compartments proximal to the autoimmune target. This is not particularly surprising, but does highlight the fact that human studies of autoimmune patients, using peripheral blood as the source of autoreactive T cells, need to be interpreted with the recognition that the temporal and spatial picture is incomplete. Even more problematic is the issue of TCR avidity for the pMHC complex controlling T‐cell fate and, potentially, immunologic outcome. A class I pMHC tetramer analysis of patients with vitiligo suggests that both high‐frequency and high‐avidity responses correlate with clinical autoimmunity. In this study, T cells interacting with pMHC tetramers for MelanA/MART‐1, Tyrosinase, and GP100 were found in all vitiligo patients studied, and include some high‐ avidity populations (Palermo et al., 2001). This contrasts with observations in the studies of relapsing polychondritis and in T1D (Buckner et al., 2002; Reijonen et al., 2002), in which autoreactive cells were of low frequency and low avidity. Many more dominant epitopes need to be examined to understand the possible immunologic basis for such differences. There is an additional confounding issue with respect to class II pMHC tetramers: namely, that single epitopes may be displayed on antigen‐presenting cells in a variety of peptides of different length, and this may lead to heterogenous T‐cell recognition profiles. Peptide epitopes for CD4þ T‐cell recognition in the context of MHC class II restriction are known to involve peptides of variable length. For example, in our studies of the naturally processed autoantigen GAD65, peptides eluted from HLA‐DR4 molecules encompassed a set of sequences surrounding a single immunodominant epitope, with a peptide length of 13 amino acids in the core sequence of GAD65 from residues 555–567 (Nepom et al., 2001). This epitope occurs within a nested set of naturally processed peptides, including two longer variants, representing residues 552–572, and residues 554–570. Figure 3 presents a comparison of T‐cell activation derived from stimulation of a panel of T‐cell clones, using all three of these naturally processed peptides. The T‐cell clones were derived by cell sorting of pMHC tetramer-binding CD4þ cells from peripheral blood of

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Figure 3 Epitope length matters. An immunodominant epitope of the autoantigen GAD65 encompasses residues 555–567, which are contained within two larger naturally processed peptides 554–570 and 552–572 (Nepom et al., 2001). Four CD4þ T‐cell lines are shown which recognize this epitope, resulting in proliferation (SI ¼ stimulation index, the ratio of T‐cell response to specific antigen divided by response in the absence of antigen, determined by thymidine uptake) and in cytokine release (gIFN, measured in ng/ml in supernatants from antigen‐responsive cultured cells). Also shown for each T‐cell line responding to each peptide are the flow cytometry profiles with pMHC tetramer binding on the vertical axis. In each case, the specific tetramer contained HLA DR4 complexed with peptides of different length, as shown. Some T cells (e.g., #123) recognize and respond to the longer 552–572 peptide better than to the shorter variants, whereas other T cells (e.g., #307, #325) show the best binding to the short 555–567 epitope tetramer. T‐cell #228 is an example of an antigen‐responsive cell that nonetheless fails to show detectable levels of pMHC tetramer binding. These highly variable responses coexist within the heterogeneous population of peripheral autoreactive GAD65-specific T cells.

T1D subjects. Variable levels of response, and indeed differences in cytokine release profiles, were seen for different length variants. Also shown in Fig. 3 are the tetramer‐binding profiles of these T‐cell clones for pMHC tetramers containing the three different length variants. Again, differences are seen that reflect different avidity of each T‐cell receptor for the three length variants. The implication of this complex relationship between TCR, peptide, and MHC is that in the natural processed environment a multitude of signals of different strength are offered, and the specific T‐cell outcome may well depend upon complex variables, including processing by the APC which determines antigen

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length, which then guides the quality and quantity of the subsequent immune response. 3. Tetramer‐Induced Autoreactivity In addition to visualizing autoreactive T cells, pMHC tetramers can be used to probe T‐cell responses. Just as anti‐CD3 antibodies trigger TCR activation cascades, albeit in an antigen nonspecific manner, pMHC tetramers act as ligands for analyzing antigen‐specific receptor‐initiated events, similarly triggering activation initiated by the TCR. One of the key determinants of differential outcomes for T‐cell responses is the TCR avidity for the pMHC complex. Studies (Mallone et al., 2004) compared T‐cell responses following activation through the TCR utilizing autoreactive pMHC tetramers, containing the GAD65 epitope. T cells in these studies were derived from patients with T1D, and were selected for either high or low avidity for antigen based on tetramer‐binding properties. Both high‐ and low‐avidity T cells showed dose‐dependent activation profiles to pMHC stimulation, with the high‐avidity T cells responding to much lower concentrations of stimuli. One notable difference was the sensitivity to activation‐induced cell death (AICD). Tetramer binding triggered a Fas‐dependent apoptotic mechanism in the high‐avidity T cells, but not in the low‐avidity cells. This very likely represents only one of a set of differential signals that are avidity‐dependent, reflected in different duration of TCR signaling, or perhaps, differential recruitment of accessory molecules. The potential for activation through pMHC interactions has attractive therapeutic possibilities. In animal studies of autoimmunity, administration of various pMHC complexes can have dramatic outcomes, including immune deviation, TH2 cytokine release, and deletional tolerance through activation‐induced cell death (Casares et al., 1999; 2002; Masteller et al., 2003; Sharma et al., 1991; Spack et al., 1995). Further studies with human T‐cell clones responding to myelin basic protein or to GAD65 similarly indicate the potential for immune deviation or anergy induction (Appel et al., 2001; Mallone et al., in press). The wide spectrum of differential avidity to self‐pMHC complexes in subjects with autoimmunity, and the differential activation program of these T cells when stimulated through the antigen‐specific TCR, raises important questions about disease pathogenesis: Are autoreactive pathogenic T cells the high‐avidity population? And if so, how did they escape negative selection during thymic development? Alternatively, are the pathogenic cells low‐avidity autoreactive T cells that escaped negative selection but became aberrantly activated in the periphery due to exposure to high‐avidity mimetics, high‐ antigen density, or costimulation, which lowered the threshold for activation?

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Although these are fundamental questions in understanding autoimmunity, answers are not known, and tetramer studies to date are consistent with all possibilities. As noted above, high‐ and low‐avidity autoreactive cells coexist in the peripheral blood of patients with autoimmune disease, suggesting that there is no strong bias toward expansion and deletion in vivo of either population. While the high‐avidity cell population may be sensitive to activationinduced cell death in the presence of autoantigens, this stimuli may, under some circumstances, preferentially induce anergy and allow for the persistence of these cells (Mallone et al., in press). A study (Ober et al., 2000) directly compared the avidity of TCR binding determined by pMHC tetramers with the thymic selection thresholds observed in vivo. High‐affinity binding of the HY self‐antigen indeed correlated with negative selection, whereas low‐affinity binding correlated with positive selection of the CD8þ T cells in this class I pMHC system. Nevertheless, the presence of high‐avidity self‐reactive T cells in the periphery of subjects with autoimmunity, and in the blood of normal human subjects (Danke et al., 2004) suggests that this negative selection mechanism is often incomplete. Similar to the observations in T1D subjects, studies using class I pMHC tetramers to the melanoma‐associated MAGE antigens have also documented a wide spectrum of tetramer staining intensity by peripheral T cells, correlating with high‐ and low‐avidity recognition of antigen. In this CD8þ T‐cell system, similar to the CD4þ T cells in T1D subjects, a wide range of functional programs were represented in the diverse T‐cell population (Dutoit et al., 2001). The avidity of T‐cell recognition is dependent on three interactions: The T‐cell receptor binding to pMHC, the peptide–MHC affinity, and the clustering of these complexes in the cell membrane. The interplay between these factors was evaluated using pMHC tetramers with class I molecules complexed with cartilage-associated aggrecan peptides (Appel et al., 2004). In this study, the low‐avidity peptide–MHC interaction was manipulated by mutagenesis of a cystine in the binding pocket of the HLA B27 class I molecule. When this interaction was of low avidity, tetramer stability and binding to TCR was impaired; when this interaction was of higher avidity due to the presence of the native cystine, the pMHC stability was restored, and the tetramer binding increased correspondingly. This observation illustrates how disease‐associated MHC molecules interacting with self‐peptides may directly contribute to skewing of the T‐cell avidity profile in the autoreactive population. Coupled with the use of altered peptide ligands which function as high‐avidity mimetics, as described previously, this has the potential to be useful in defining the avidity maturation of an ongoing autoimmune response and also lead to the improved design of therapeutic mimetics designed to elicit AICD.

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3.1. Tetramer‐Assisted Perspectives on Autoimmunity Tetramers are valuable additions to the immunology toolkit. They provide a molecular tag for one of the most important elements of the adaptive immune response, namely the specificity of recognition by T cells. Their use in studies of autoimmunity has already provided several new insights, which have implications for both basic and clinical immunology: First, tetramer studies directly detect high‐avidity autoreactive cells present in the peripheral circulation of human subjects. This indicates that selection mechanisms that delete autoreactive high‐avidity cells are incomplete most of the time, and directs new attention to studies that are focused on discovering what these high‐ avidity cells are destined to become. Second, tetramer studies have demonstrated that normal individuals have autoreactive circulating cells that expand when regulatory controls are released. This fundamentally illustrates the underlying autoreactive potential which is inherent in the immune system and which presents both a major therapeutic challenge and an exciting opportunity through manipulation of the regulatory pathway. Third, soluble tetramers provide very specific ways to engage the TCR on antigen‐specific lymphocytes, which can be used to initiate activation pathways ranging from expansion to cell death. Subtle modifications in the tetramer structure reveal a spectrum of TCR avidity within a polyclonal T‐cell response, which can be manipulated to direct a variety of different T‐cell outcomes. And finally, the clinical use of tetramers to evaluate progressive autoimmunity and response to immunotherapy, although in its infancy, promises to expand the types of individualized patient management strategies that may become commonplace in the era of personalized molecular medicine. Acknowledgments These studies were supported by grants from the National Institutes of Health and the Juvenile Diabetes Research Foundation. The work of many colleagues and members of the Nepom laboratory contributed to the studies cited, and their contributions are gratefully acknowledged.

References Altman, J. D., Moss, P. A. H., Goulder, P. J. R., Barouch, D. H., McHeyzer‐Williams, M. G., Bell, J. I., McMichael, A. J., and Davis, M. M. (1996). Phenotypic analysis of antigen‐specific T lymphocytes. Science 274, 94–96. Appel, H., Kuon, W., Kuhne, M., Hulsmeyer, M., Kollnberger, S., Kuhlmann, S., Weiss, E., Zeitz, M., Wucherpfennig, K., Bowness, P., and Sieper, J. (2004). The solvent‐inaccessible Cys67 residue of HLA‐B27 contributes to T cell recognition of HLA‐B27/peptide complexes. J. Immunol. 173, 6564–6573.

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Regulation of Phospholipase C‐g2 Networks in B Lymphocytes Masaki Hikida and Tomohiro Kurosaki Laboratory for Lymphocyte Differentiation, RIKEN Research Center for Allergy and Immunology, Tsurumi‐ku, Yokohama, Kanagawa 230‐0045, Japan

1. 2. 3. 4. 5. 6. 7. 8. 9.

Abstract............................................................................................................. Introduction ....................................................................................................... From the BCR to PLC‐g ...................................................................................... Roles for PLC‐g .................................................................................................. Regulation of IP3 Receptors .................................................................................. Coupling Between Calcium Release and Calcium Influx ............................................. Looking for Ca2þ Entry Channels .......................................................................... NFAT and NF‐kB ............................................................................................... Modulation of Calcium Signaling............................................................................ Concluding Remarks............................................................................................ References .........................................................................................................

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Abstract The modulation of inositol‐1,4,5‐trisphosphate (IP3), a product of phospholipase C (PLC) activity, is one of a common signaling mechanism used in many biological systems. B lymphocytes also rely on IP3 and subsequent calcium signaling to ensure appropriate developmental outcomes, as well as antigen‐ specific responses. In establishing the optimal intensity and duration of the PLC‐g activity, an important role has emerged for adaptor molecules, which direct the appropriate subcellular localization of PLC‐g and induce its conformational changes. Generated IP3 binds to IP3 receptors located on the endoplasmic reticulum (ER), which in turn is essential for triggering calcium release from the ER and subsequent entry of extracellular calcium by so‐called Ca2þ entry channels. Recent data has begun to shed new light on the connection between the calcium release and the influx of extracellular calcium, and the molecular identity of the Ca2þ entry channels. 1. Introduction The tremendous diversity and plasticity of the immune responses are well exemplified by the B‐cell limb of the immune system. To accomplish this, B‐cell signaling through its antigen receptor (BCR) leads to a wide range of biological outputs, depending upon developmental stages and properties of the antigen. A simple ‘‘on‐and‐off’’ mode of signal transduction would not allow for such a diversity of responses. Rather, BCR signals must be precisely

73 advances in immunology, vol. 88 # 2005 Elsevier Inc. All rights reserved.

0065-2776/05 $35.00 DOI: 10.1016/S0065-2776(05)88003-4

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regulated in terms of their magnitude and duration. This is typically shown in the case of the PLC‐g‐calcium pathway. A large transient calcium rise activates NF‐kB, whereas NFAT is activated by a slow but sustained calcium plateau (Dolmetsch et al., 1997). Given the importance of the transcription factors (NF‐kB and NFAT) in B‐cell differentiation and survival (Choi et al., 1994; Henderson and Calame, 1998; Li and Verma, 2002; Peng et al., 2001; Venkataraman et al., 1994), these findings have spurred interest in uncovering when and how such differential Ca2þ signals are generated, and how these differential signals are translated into biological outcomes. Thus, the purpose of this review is to summarize the major advances in the PLC‐g‐calcium pathway in B cells, with specific emphasis on the significance of positive‐ or negative‐feedback loops in this pathway. In these regards, the first section addresses the roles of BCR‐proximal signaling molecules in the regulation of PLC‐g. Secondly, we address how IP3 and diacylglycerol (DAG), both of which are products of the PLC‐g action, trigger the Ca2þ release channels on the ER, and subsequently the Ca2þ entry channels in the plasma membrane. Finally, we discuss the role of PLC‐g‐calcium‐regulated effectors in B‐cell activation. 2. From the BCR to PLC‐g T cells mainly express the PLC‐g1 isoform, whereas PLC‐g2 is predominantly expressed in B cells (Hashimoto et al., 2000; Irvin et al., 2000; Park et al., 1991; Rhee and Bae, 1997; Secrist, et al.,1991; Wang et al., 2000). PLC‐g2 is activated by, at least, tyrosine phosphorylation by a complex of proteins connected to the BCR and the coordinated actions of recruitment to the inner face of the plasma membrane, where its substrate, PIP2, is located. Among three distinct families of nonreceptor tyrosine kinases (Lyn, Syk, and Btk), Syk and Btk are obligatory kinases in PLC‐g2 activation that follows BCR stimulation (Fig. 1) (Kurosaki, 1999). Indeed, the reduced levels of BCR‐induced IP3 production and calcium mobilization, which reflect PLC‐g activation, are seen in B cells from X‐linked agammaglobulinemia (XLA) patients and X‐linked immunodeficiency (Xid) mice (Fluckiger et al., 1998; Rigley et al., 1989), both of who have defective Btk genes. This defective PLC‐g2‐calcium signal in XLA patients and Xid mice is likely to cause the impaired maturation of B cells and compromised T‐cell‐independent immune responses (Rawlings and Witte, 1994; Smith et al., 1994). In the case of disruption of Syk, compared with that of Btk, a more severe phenotype in PLC‐g activation is seen, simply suggesting that Syk lies upstream of Btk in terms of BCR‐mediated PLC‐g2 activation (Takata et al., 1994; Takata and Kurosaki, 1996).

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Figure 1 Activation mechanisms of PLC‐g2. Upon BCR stimulation, Iga and Igb are doubly phosphorylated by Src‐PTKs, which leads Syk recruitment. BLNK, after being phosphorylated by activated Syk, binds Btk and PLC‐g2 in a SH2‐phosphotyrosine‐dependent manner. This association brings Btk and PLC‐g2 close to each other and also supports recruitment of these molecules to the plasma membrane. Thus, PLC‐g2 is phosphorylated by Btk and gains access to its substrate PIP2. After hydrolysis of PIP2 by PLC‐g2, generated IP3 binds to the IP3 receptor and stimulates the subsequent Ca2þ release from the intracellular pool.

For full activation of Syk, it requires not only an open conformation by binding of its two tandem SH2 domains to the phosphorylated Iga and Igb, but also the autophosphorylation of Syk at the regulatory loop of the kinase domain (Kurosaki et al., 1995; Rowley et al., 1995). In addition, Syk also undergoes phosphorylation on several other tyrosine residues that are located in the linker region connecting the two tandem SH2 domains (interdomain A), or the SH2 domains to the kinase domain (interdomain B) including Tyr317 (Keshvara et al., 1998). Although phosphorylation of these sites occurs as a consequence of Syk activation, this phosphorylation, in turn, could function as an initiator to attenuate the activation of Syk, thereby contributing to formation of a negative‐feedback regulation loop for Syk activation. For instance, Tyr317 in Syk is phosphorylated after BCR cross‐linking, thereby providing a binding site for Cbl and Cbl‐b (Deckert et al., 1998). Considering that the ring finger domains of the Cbl family act as E3 ubiquitin ligases that downregulate the activities of signaling molecules through protein ubiquitination/degradation (Joazeiro et al., 1999; Levkowitz et al., 1999; Yokouchi et al., 1999), a promising model has emerged that proposes that Cbl and/or Cbl‐b, after their

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Figure 2 Models of negative‐feedback regulatory loops for Syk and Btk, and positive‐forward regulatory loops for PLC‐g2. (A) Activated Syk autophosphorylates Tyr317, in addition to its substrates such as BLNK. This Tyr317 phosphorylation provides a binding site for Cbl, which acts as E3 ubiquitin ligase. Ubiquitin‐mediated degradation of Syk results in the attenuation of BCR signaling. (B) In this model, PLC‐g2 is activated by virtue of Btk action, leading to generation of DAG. Then, the generated DAG recruits PKCb to the plasma membrane, wherein PKCb is activated. Phosphorylation of Btk by PKCb downregulates Btk kinase activity and decreases its membrane localization, both of which in turn inhibit PLC‐g2 activity. (C) Calcium influx can be

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binding to the phosphorylated Tyr317 in Syk, dampen the Syk activity (Fig. 2A) (Thien and Langdon, 2001). In support of this model, B cells from Cbl‐b‐ deficient mice demonstrate reduced ubiquitination and subsequent prolonged phosphorylation of Syk during BCR stimulation (Sohn et al., 2003). The importance of kinase activity of Btk is clear; after being activated by its recruitment to the plasma membrane, Btk phosphorylates Tyr753 and Tyr759 on PLC‐g2, thereby augmenting the enzymatic activity of PLC‐g2 (Fig. 1) (Humphries et al., 2004; Kim et al., 2004; Rodriguez et al., 2001; Watanabe et al., 2001). But, new data suggest that Btk plays an additional role in a kinase‐ independent manner as well (Schwartzberg, 2003). The Btk PH/TH domain associates with phosphatidylinositol‐4‐phosphate 5 kinase (PIP5K) and participates in recruitment of PIP5K to the plasma membrane (Saito et al., 2003). Because PIP2, a substrate for both PI3K and PLC‐g2, is synthesized from PIP by PIP5K, this PIP5K recruitment results in generation of more PIP2. Thus, Btk plays two roles in PLC‐g2 activation. In addition to phosphorylating Tyr753 and Tyr759 on PLC‐g2, the recruitment of the Btk‐PIP5K complex to the membrane ensures that the activated PLC‐g2 does not run out of its substrate, thereby contributing to efficient production of IP3 and DAG. The existence of a negative‐feedback regulatory loop for Btk activation has been suggested by recent results (Kang et al., 2001; Yao et al., 1994). A first clue to this negative loop came from the observation that BCR‐mediated tyrosine phosphorylation of Btk is increased and prolonged in PKCb‐deficient B cells, which indicates PKCb functions as a potent inhibitor of Btk (Kang et al., 2001). As Btk has a positive role in the PLC‐g2‐calcium‐PKC pathway, a model is that PKCb, after being activated by a Btk‐dependent mechanism, phosphorylates Btk, which in turn, inactivates Btk kinase activity and subsequent PLC‐g2 activity (Fig. 2B). Indeed, Ser180 in the TH domain of Btk has been identified as a PKCb phosphorylation site, and the Ser180Ala Btk mutant is hyperactive, presumably owing to enhanced membrane localization as well as enhanced enzymatic activity. Furthermore, inhibition of PKCs leads to augmented PLC‐g2 activation (Kim et al., 2004). So, this negative‐feedback mechanism could contribute to controlling the duration of Btk residency in the plasma membrane and subsequent PLC‐g2 activation. Adaptor molecules serve as a substrate of BCR‐induced tyrosine kinases and phosphorylation of these molecules is essential for subsequent PLC‐g2 activation (Kurosaki, 2002). BLNK (also known as SLP‐65, BASH, and BCA), induced by PLC‐g2 and subsequent calcium release from ER. This calcium influx mediated by SOCs has been shown to recruit PLC‐g2 to the plasma membrane in the C2 domain‐dependent manner, thereby amplifying hydrolysis of PIP2 in the plasma membrane.

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after being phosphorylated by Syk, binds to Btk, Vav, and PLC‐g2 in a SH2‐phosphotyrosine‐dependent manner (Chiu et al., 2002; Fu et al., 1998; Hashimoto et al., 1999; Ishiai et al., 1999; Johmura et al., 2003). As BLNK is translocated to the plasma membrane after BCR stimulation, these binding causes two consequences; recruiting Btk, Vav, and PLC‐g2 to the plasma membrane, and bringing them into close proximity with each other. Thus, the former mechanism makes PLC‐g2 gain access to its substrate PIP2, located in the plasma membrane, while the latter one facilitates phosphorylation of Tyr753 and Tyr759 on PLC‐g2 by Btk (Humphries et al., 2004; Kim et al., 2004; Watanabe et al., 2001) (Fig. 1). In addition to Tyr753 and Tyr759, PLC‐g 2 undergoes phosphorylation at Tyr1217 in a Btk‐independent manner (Kim et al., 2004). Although the importance of this phosphorylation in the BCR signaling context is clear, this is probably not caused by direct activation of the PLC‐g2 lipase activity. Rather, phosphorylation on Tyr1217 seems to induce association with as‐yet unidentified SH2‐containing molecules, thereby stabilizing the PLC‐g2 residency in the plasma membrane and/or enhancing accessibility of PLC‐g2 to its substrate. PI3K activation is thought to contribute to PLC‐g2 activation through stabilizing the association of Btk and PLC‐g2 to the plasma membrane, given that both Btk and PLC‐g2 possess PH domains that bind selectively to the PI3K product PIP3 (Fig. 1). In fact, the importance of PIP3 in PLC‐g2 activation is further evidenced by deletion of SHIP (SH2 domain‐containing 5’ inositol phosphatase), a counteracting enzyme toward the action of PI3K (Brauweiler et al., 2000; Okada et al., 1998). A deficiency in this lipid phosphatase leads to increased PIP3, thereby enhancing PLC‐g2 phosphorylation and its subsequent activation (Brauweiler et al., 2000). 3. Roles for PLC‐g A central role for PLC‐g2 in calcium mobilization in B lymphocytes has been demonstrated using gene‐targeting experiments both in the cell line and in mice (Hashimoto et al., 2000; Takata et al., 1995; Wang et al., 2000). PLC‐g2‐ deficient mice exhibit a partial block at the developmental transition after pre‐BCR signaling and a more complete block at the transition from immature to mature B cells (Bell et al., 2004; Hashimoto et al., 2000; Hikida et al., 2003; Wang et al., 2000). As the defect in the pre‐BCR checking point is similar to, but less complete than, the block in Btk/Tec double knockout mice, low‐level expression of PLC‐g1 in pre‐B cells has been thought to compensate for PLC‐g2. Indeed, this idea is recently substantiated by the observation that PLC‐g1 haploid insufficiency in a PLC‐g2 null background resulted in a more complete block from pro‐ to pre‐B‐cell stage. More interestingly, allelic

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exclusion of the immunoglobulin heavy chain was perturbed in these mice (Wen et al., 2004). Hence, assuming that PLC‐g1 mediates a qualitatively identical signal with PLC‐g2, a certain level of PLC‐g activity is required for progression through the pre‐B‐cell stage as well as inducing allelic exclusion, and higher PLC‐g threshold appears to be set for further making up the mature B‐cell pools. 4. Regulation of IP3 Receptors After PLC‐g2 activation, the generated IP3 binds to IP3 receptors located in the ER, thereby stimulating the release of calcium from internal stores. It is thought that, once these calcium stores are emptied, the entry of external calcium is triggered through so‐called store‐operated calcium channels (SOCs) in the plasma membrane (Parekh and Penner, 1997). Three distinct IP3 receptor genes are identified with differential expression patterns, depending upon distinct cell types (Dent et al., 1996; Miyakawa et al., 1999; Newton et al., 1994; Wojcikiewicz et al., 1994). Triple knockout of all three IP3 receptor isoforms in DT40 B cells abolishes the BCR‐induced calcium mobilization both from internal stores and from extracellular stores, whereas this calcium mobilization still occurs by a single knockout of these three receptors. Thus, overall, three IP3 receptors are essential and functional redundant mediators for BCR‐mediated calcium mobilization (Miyakawa et al., 1999). And these data appear to support the store‐operated coupling model mentioned previously. Although expression of only one isoform does not abolish calcium mobilization, detailed calcium‐signaling patterns differ significantly among these three IP3 receptor isoforms. For instance, DT40 B cells expressing only the type 2 IP3 receptor showed regular and robust calcium oscillations upon BCR ligation, whereas monophasic calcium transient or rapidly dampened calcium oscillations were observed in mutant B cells expressing type 3 or type 1 alone, respectively (Miyakawa et al., 1999). Hence, differential and combinatorial expression of these three IP3 receptors is one of the critical determinants for creating transient or oscillatory calcium signals, which in turn could regulate the selectivity of transcriptional factors in B cells. For instance, NF‐kB is activated by a large transient calcium rise, whereas NFAT requires a slow, but sustained calcium plateau (Dolmetsch et al., 1997). Then, the question arises about the mechanisms underlying such differential calcium oscillation patterns. Although being not entirely clear, a clue came from mutational analysis of the type 1 IP3 receptor (Miyakawa et al., 2001). Binding of IP3 to the IP3 receptors is essential, but not sufficient to open the calcium‐release channel embedded in these receptors, and calcium by itself is

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Figure 3 Models of SOCs activation. (A) Left, the direct activation model by the diffusible messenger. In this model, it is postulated that depletion of calcium from intracellular store induces production of calcium influx factor (CIF). CIF diffuses to the plasma membrane and activates SOCs directly. Right, the indirect activation model by the diffusible messenger. CIF produced by depletion of the internal calcium pool diffuses and activates iPLA2 by displacement of inhibitory calmodulin (CaM). Once iPLA2 gets activated, it generates lysophospholipids, which in turn activate SOCs. (B) Left, the direct conformational‐coupling model. In this model, it is postulated

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thought to be required as a coagonist for the IP3 receptors. Asp2100 is responsible for such a calcium sensor, because its replacement with Glu causes a 10‐fold decrease in calcium sensitivity, but bears normal IP3 sensitivity. This Asp2100Glu mutant exhibits a dramatic decrease in calcium oscillation activity. Furthermore, consistent with the ability of the type 2 IP3 receptor to create robust calcium oscillations, this receptor, compared with type 1 and type 3, possesses higher calcium sensitivity (Miyakawa et al., 1999). Therefore, these data provide compelling evidence that calcium initially released by IP3 receptors feeds back to augment further calcium release in a positively cooperative fashion, thereby contributing to generation of calcium oscillations. 5. Coupling Between Calcium Release and Calcium Influx The mechanism by which SOCs are activated by intracellular calcium release still remains a mystery. SOCs are named functionally, particularly in terms of electrophysiological criteria, but not molecularly. Hence, for solving this important question, two interrelated issues should be addressed: the molecular identity of SOCs, and the nature of the signal that activates them. In the first issue, much recent interest has been directed toward the TRP‐family of ion channels and they have been considered likely to encode components of SOCs, as discussed in greater detail in the next section. Because of a limited amount of information about these two issues in lymphocytes, it is important to incorporate more from other cell types in this section. There are currently three models (Fig. 3), for activation of SOCs, but they are not mutually exclusive. Recent studies have suggested that these three models could coexist in the same cells and cooperate even in a single receptor system. The diffusible messenger model is the oldest one (Randriamampita and Tsien, 1993). According to this model, calcium influx factor (CIF) is produced by depleted internal stores and it triggers activation of SOCs (Fig. 3A, left panel). After initial excitement, the CIF model was strongly criticized because of a continuous uncertainty about the molecular nature, but a few

that conformational change of the IP3 receptor takes place by its opening and this change is transmitted to SOCs by direct interaction and activation of SOCs. Right, the indirect conformational‐coupling model. Instead of the IP3 receptor by itself, other ER‐resident molecules sense the conformational change of the IP3 receptor and directly interact to the SOC, thereby activating them. (C) The secretion model. This model suggests a mechanism by which depletion of calcium from intracellular store initiates the vesicular translocation and insertion of calcium channels to the plasma membrane. Then, delivery of these channels to the membrane might be a trigger for cation influx.

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groups have continued their struggle, attempting to identify native CIF and determine the CIF‐mediated pathway (Randriamampita and Tsien, 1995; Rzigalinski et al., 1999; Takemura and Ohshika, 1999; Thomas and Hanley, 1995; Trepakova et al., 2000). Although the original CIF model hypothesized that CIF directly binds and activates SOCs, an indirect activation model has been proposed recently (Smani et al., 2003; 2004). In this model, CIF‐induced displacement of inhibitory calmodulin from iPLA2 is a key event, leading to iPLA2 activation. Once iPLA2 is activated by CIF, lysophospholipids are generated, which in turn activate SOCs. Hence, according to this variant model, a more direct activator for SOCs is considered to be lysophospholipids rather than CIF (Fig. 3A, right panel). The conformational coupling model postulates that a direct interaction between the ER‐resident proteins such as IP3 receptors and SOCs is required for opening SOCs (Fig. 3B, left panel). This mechanism has been particularly appealing, because structural and functional coupling of transient receptor protein C3 (TRPC3) channel, possibly one of SOCs, and IP3 receptor was demonstrated in an in vitro system (Kiselyov et al., 2000). However, in contradiction with this model, triple knockout of all three IP3 receptor isoforms in DT40 B cells still exhibits proper calcium influx after pharmacological emptying of the ER calcium stores such as thapsigargin or ionomycin treatment (Sugawara et al., 1997). One interpretation that reconciles these data is that opening mechanisms for SOCs might differ between BCR signaling and pharmacological contexts, although some overlapping exists. In support of this explanation, in a triple knockout background, BCR‐mediated calcium influx can be restored by type 1 IP3 receptor mutants that have IP3 binding, but not channel activity (van Rossum et al., 2004). Conversely, the IP3 binding mutants cannot restore, simply suggesting that IP3‐mediated conformational change in the IP3 receptor is required for opening SOCs in the BCR signaling context. As an obvious extension of this model, this conformational change in the IP3 receptor can be transmitted to SOCs through other ER‐resident and/or intermediate molecules (Fig. 3B, right panel) (Yuan et al., 2003). In these regards, upon binding of IP3 to its receptors, conformationally coupled junctions might be newly formed between ER and plasma membrane, thereby contributing to activated SOCs. This idea appears to be consistent with studies that show the involvement of a GTP‐regulatory step in the activation of SOCs (Bird and Putney, 1993; Fasolato et al., 1993; Fernando et al., 1997; Yao et al., 1999), because these molecules are well‐known to participate in intracellular trafficking events. Assuming that SOCs comprise TRP‐family members, a series of recent studies suggest that recruitment of TRPs to the plasma membrane is the third mechanism by which SOCs are activated (Fig. 3C) (Clapham, 2003).

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Such a concept has considerable appeal as many TRP channels expressed in vitro are constitutively active. If this is also true in vivo, then BCR‐induced delivery of TRPs to the plasma membrane could be one trigger for SOCs‐ mediated cation influx. The first report corroborating an exocytic mechanism for a TRP channel was the demonstration that TRPV2 translocates to the plasma membrane after stimulation of the insulin growth factor using an overexpression system (Kanzaki et al., 1999). Since then, several TRP family members, TRPC3 (Xu and Sternberg, 2003), TRPC5 (Bezzerides et al., 2004), TRPV5, and TRPV6 (van de Graaf et al., 2003), have been shown to move to the plasma membrane after receptor stimulation (Montell, 2004). In the case of the TRPC5 in hippocampal neurons, incorporation of this channel into the plasma membrane is initiated by growth factors such as NGF that stimulate receptor tyrosine kinases (RTKs), and this incorporation appears to be dependent on PI3K, Rac, and PIP5K in the NGF signaling context (Bezzerides et al., 2004). Because these enzymes and GTP‐binding proteins are also activated in the BCR‐signaling context, the previous findings that PI3K is required for BCR‐mediated calcium influx (Clayton et al., 2002; Jou et al., 2002) might be accounted for by its involvement in translocation of SOCs to the plasma membrane. 6. Looking for Ca2þ Entry Channels Proteins of the TRP family are presently the best candidates for the pore‐ forming subunit of SOCs. The TRP family can be classified into six subfamilies (TRPC, TRPV, TRPM, TRPA, TRPP, and TRPML), and the total number of these genes has now turned out to be 28 in mice (see Fig. 4 for their structures) (Clapham, 2003). Among them, TRPV5 and TRPV6 seem to be stronger candidates, but their physiological properties, when overexpressed each alone in heterologous cells, such as HEK293 cells, do not fully resemble those of endogenous SOCs (Hoenderop et al., 2001; Vennekens et al., 2000; Voets et al., 2001). Thus, the best speculation at present is that SOCs in B lymphocytes are heteromultimeric complexes of TRP components, and additional regulatory or adaptor subunits are needed to promote channel assembly and subsequent coupling to store depletion previously mentioned. Functionally, the TRPV6 channel exhibited several key features of SOCs when expressed in CHO cells, including activation of TRPV6 through store depletion using either IP3 or thapsigargin, and a high degree of calcium selectivity in the presence of divalent cations (Yue et al., 2001). In contrast to these initial observations, a subsequent study reported that no activation of the TRPV6 channels was observed in HEK293 cells after ionomycin‐induced store release (Voets et al., 2001). One of the explanations for this disparity, among

84 Figure 4 Schematic structure of TRP‐family ion channels. All the members of the family consist of six transmembrane domain‐containing ion channels flanked with two cytoplasmic tails that are characteristic to each member. The TRP box is EWKFAR in TRPC, but is less conserved in TRPV and TRPM. CC indicates coiled‐coil domain. Ankyrin repeats (AnkR) range from 0 to 14 in number. CIRB stands for putative calmodulin‐ and IP3 receptor‐binding domain. EF hand, canonical helix‐loop‐helix Ca2þ‐binding domain; PDZ, amino acids‐binding PDZ domains; PLIK, phospholipase‐ C‐interacting kinase; Nudix, NUDT9 hydrolase protein homologue‐binding ADP ribose.

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many, is that both the function and pharmacological properties of TRPV6 are highly expression‐dependent. Thus, at low‐expression levels (in the case of CHO cells), the channel is store‐dependent, similar to native SOCs, whereas at higher expression levels (in the case of HEK293 cells), the TRPV6 is constitutively active. Similarly, expression‐dependent alterations of the channel properties were also observed in the case of TRPC3 (Vazquez et al., 2003). TRPC3, when expressed in HEK293 cell (corresponding to higher levels of expression), exhibited a constitutive activity that was substantially enhanced by agonist stimulation such as carbachol, but not by store depletion. However, in the relatively lower expression of TRPC3 in DT40 B cells, this channel behaved as a store‐operated channel. Then the question arises about the underlying mechanisms. At least two possible explanations seem to be possible. First, under low or endogenous levels of expression, store‐depletion may cause recruitment of TRPs in intracellular compartments to the plasma membrane. If so, overexpression of TRPs skews their expression from intracellular compartments to the plasma membrane even before stimulation, wherein TRPs exhibit no more store‐dependency. Second, under low‐expression conditions, heteromeric complexes are formed between the expressed TRP and regulatory factors, thereby leading to store‐dependency of these channels. On the other hand, overexpression of the individual TRP most likely generates predominantly homomultimers, losing the store‐dependency. Hence, to complement the overexpression experiments, knockout approach is undoubtedly required. Apart from the store‐operated mechanism, recent analyses of each TRP channel have made a novel paradigm emerge that many TRP channels respond to multiple inputs including lipid metabolites. For instance, opening of TRPM7 is positively controlled by PIP2; hence activation of PLC‐g‐coupled receptors such as BCR is able to cause channel inactivation in the case of TRPM7 (Runnels et al., 2002). Conversely, TRPC3, TRPC6, and TRPC7 are directly activated by DAG, a PLC‐g product (Hofmann et al., 1999; Okada et al., 1999; Venkatachalam et al., 2001). Thus, once PLC‐g is activated, not only IP3 but also DAG appears to be involved in modulation of TRP channels. After calcium influx occurs, it is proposed that PLC‐g2 is activated again, thereby forming a positive‐forward loop between PLC‐g2 and calcium, based upon the existence of the C2 calcium‐binding domain in PLC‐g2 (Nishida et al., 2003). Supporting this model, the PLC‐g2 mutant devoid of this C2 domain exhibited no more such amplification. Given the physical association between PLC‐g2 and TRP channels such as TRPC3 (Nishida et al., 2003), this model also suggests that the PLC‐g2 C2 domain could quickly sense the alteration of the calcium concentration just induced by TRPC3, possibly

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making a positive loop in a very‐restricted region inside B lymphocytes (Fig. 2C). In contrast to significant progress regarding how calcium signals are generated, how calcium signals are terminated is largely unknown. Several mechanisms, including inhibition of SOCs, SERCA‐mediated uptake of Ca2þ into intracellular Ca2þ stores, and the action of Ca2þ pumps (PMCAs) that pump Ca2þ out the cells, are proposed (Berridge et al., 2003). Indeed, the importance of PMCAs was recently shown in B lymphocytes as well as T lymphocytes (Bautista et al., 2002; Chen et al., 2004). 7. NFAT and NF‐kB Increased intracellular calcium promotes nuclear translocation of two important sets of transcription factors, namely the NFAT and the NF‐kB family (Fig. 5) (Dolmetsch et al., 1997). Activation of the NF‐kB transcription factors NF‐kB1, NF‐kB2, c‐Rel, RelA, and RelB is essential for B‐cell development as well as immune responses (Henderson and Calame, 1998; Li and Verma, 2002). Extraordinary progress has been made defining molecular events leading to NF‐kB activation (Ghosh and Karin, 2002). NF‐kB is released from inhibitors of the IkB family by phosphorylation and ubiquitination‐mediated proteolysis. And this IkB phosphorylation is triggered by a multimolecular complex comprising two serine threonine kinases, IKKa and IKKb, and a regulatory subunit IKKg. Thus, activation of the IKK complex is essential for subsequent NF‐kB activation. Deficiency in PKCb has a dramatic impact on the phosphorylation of IKKa and, to a lesser extent, IKKb, thereby reducing the activation status of the IKK complex (Saijo et al., 2002; Su et al., 2002). The proteins CARMA1, Bcl10, and MALT1 are involved in NF‐kB activation downstream of PKCb (Guo et al., 2004; Thome, 2004). Probably CARMA1, Bcl10, and MALT1 are physically associated with each other, and PKCb could mediate phosphorylation on Bcl10, which in turn facilitates and/or stabilizes these associations. Then, the question arises about connection between the CARMA1/Bcl10/MALT1 and the IKK complex. A new study shows the intriguing possibility that Bcl10 induces IKKg polyubiquitination in a MALT1‐, Ubc13‐, TRAF2‐, and TRAF6‐dependent manner, which in turn is important for activation of the IKK complex (Zhou et al., 2004). Because PKCb is more critically regulated by DAG, rather than calcium, the preceding mechanism suggests that NF‐kB activation in the BCR signaling context could be accounted for mainly by the DAG axis rather than calcium. However, although the experiments were not performed in lymphocytes, new data suggest that calcium pathway might be involved in NF‐kB activation, independently of PKCb activation. Mitochondrial inhibitors such as CCCP

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Figure 5 Regulation of NF‐kB and NFAT by PLC‐g2. BCR‐mediated PLC‐g2 activation causes elevation of cytoplasmic concentration of Ca2þ, which leads to the activation of calcineurin. NFAT is dephosphorylated by calcineurin and translocates to the nucleus. DAG, generated by PIP2 hydrolysis, activates PKCb, which then activates IKK complex presumably by promoting membrane recruitment and aggregation of the CARMA1/bcl10/MALT1 complex. This complex activates IKKs, resulting in the phosphorylation and ubiquitin‐mediated degradation of IkB. Released rel/p50 complex translocates to the nucleus. It has been reported that inhibition of calcineurin blocks the activation of NF‐kB suggesting that calcineurin is involved in NF‐kB activation pathway (Biswas et al., 2003).

increase intracellular calcium levels and activate NF‐kB in several cell types. More importantly, this NF‐kB activation is blocked by FK506 or cyclosporin A (Biswas et al., 2003; Venkatesha et al., 2004), suggesting involvement of calcineurin, a calcium‐sensitive serine threonine phosphatase (Fig. 5). CCCP appears to promote degradation of IkBb‐ (but not conventional Ikba‐) containing NF‐kB complexes (Biswas et al., 2003). Hence, if this mechanism takes place in B lymphocytes, calcineurin could participate in not only NFAT, as discussed in the following, but also NF‐kB activation. There are four calcium‐regulated members of the NFAT family (Feske et al., 2003; Rao et al., 1997). The activity of these proteins is determined by their phosphorylation status, which is tightly regulated by the interplay between calcineurin and opposing kinases. When calcineurin is activated through an increase in calcium levels, NFAT is dephosphorylated at a large number of phosphorylated serine residues and rapidly enters the nucleus (Okamura et al., 2000; Shibasaki et al., 1996). Conversely in stimulated cells in which NFAT is

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already localized to the nucleus, termination of calcium signaling results in rephosphorylation of NFAT, exposure of a nuclear export signal that is bound by the nuclear export receptor Crm1, and transport of NFAT back to the cytoplasm (Kehlenbach et al., 1998; Klemm et al., 1997). Hence, an implication of these findings is that in order to maintain NFAT in a dephosphorylated state for subsequent gene regulation, calcineurin should be present in the nucleus of stimulated cells. Furthermore, calcineurin‐mediated dephosphorylation must be capable of being reversed by NFAT kinases (Hogan et al., 2003; Kiani et al., 2000). More importantly, the property of reversible activation and deactivation by calcineurin and NFAT kinase, respectively, confers on NFAT a remarkable activity to sense dynamic changes in [Ca2þ]i in lymphocytes (Dolmetsch et al., 1997; Dolmetsch et al., 1998; Li et al., 1998; Tomida et al., 2003). Thus, the differential responsiveness of NFAT versus NF‐kB activation in calcium changes, as observed in activation of NF‐kB and NFAT by a large transient calcium rise and a slow, but sustained calcium plateau, respectively, appears to reflect the fact that NF‐kB activation requires irreversible degradation of IkB during activation processes, whereas NFAT is reversibly activated and deactivated through the calcium‐sensing enzyme calcineurin and opposing kinases. Although degradation of IkB is irreversible in a course of one hour range after stimulation, IkB is again transcribed and synthesized after a lag time, because IkB is well known to be a target gene of NF‐kB pathway (Li and Verma, 2002). Hence, in a longer time length such as 5 hours after stimulation, NF‐kB components are reversibly back into a calcium‐sensitive state again. 8. Modulation of Calcium Signaling Transgenic mice expressing a well‐defined HEL‐specific BCR on B cells in combination with mice harboring soluble HEL as a self‐antigen provide a well‐ controlled model to analyze anergic B cells. In this model, a distinct pattern of signaling by BCRs, activating NFAT or ERK, but not NF‐kB or JNK, characterizes anergic B cells (Glynne et al., 2000; Healy et al., 1997). These results indicate that chronic, suboptimal stimulation induces an inhibitory feedback to selectively uncouple the receptor from activation‐signaling pathways. In anergic B cells, basal calcium level is high and antigen‐mediated calcium oscillations are dampened (Healyet al., 1997). This differential calcium signaling, given the evidence that NF‐kB, but not NFAT, requires a large transient calcium rise, could explain why NF‐kB pathway is selectively uncoupled in anergic cells. Therefore, the preceding findings raise the question of how PLC‐g2‐calcium signaling properties are modulated by the inhibitory feedback operating in anergic B cells. Several data suggest ubiquitin E3 ligases (E3s) as an important

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possible mediator for this feedback (Davis and Ben‐Neriah, 2004; Liu, 2004). In the case of T cells, T cells are induced to the anergy state through anergy‐ inducing stimuli such as TCR stimulation without costimulation and treatment of the calcium ionophore ionomycin (Heissmeyer et al., 2004; Macian et al., 2002). Indeed, after ionomycin stimulation, at least three E3s: Itch, Cbl‐b, and GRAIL are upregulated at the mRNA and protein levels (Heissmeyer et al., 2004). When anergic T cells are restimulated, Itch and closely related HECT‐ domain E3 Nedd4 becomes localized to the membrane, whereby they target key signaling molecules, including PLC‐g1 and PKCy for degradation, thereby diminishing calcium mobilization. Hence, if a similar mechanism also operates in B cells, signaling molecules involved in PLC‐g‐calcium pathway, such as Syk, BLNK, PLC‐g2, IP3R, or TRPs, could be a target for ubiquitin‐mediated downregulation, thereby dampening calcium signaling observed in anergic B cells. As previously discussed, Syk was indeed shown to be a potential target for Cbl and/or Cbl‐b, thereby undergoing poly‐ubiquitination‐induced degradation (Sohn et al., 2003). In addition to poly‐ubiquitin‐mediated degradation, studies in yeast and in mammalian cells have shown that mono‐ubiquitin tags are necessary and sufficient to trigger endocytosis (Dupre et al., 2004). For instance, binding of epidermal growth factor (EGF) to its receptor (EGFR) stimulates receptor internalization, and EGF‐dependent mono‐ubiquitination of the EGFR by the E3 ligase Cbl triggers a sorting event on the early endosome (Levkowitz et al., 1998). Sorting involves recognition of the mono‐ubiquitinated receptors by proteins, such as Hrs and Tsg101, that contain ubiquitin‐binding domains (Chin et al., 2001; Lu et al., 2003). Hence, if Cbl and/or Cbl‐b are upregulated in anergic B cells, like ionomycin‐induced T‐cell anergy, enhanced cycles of endocytic sequestration and recycling would be expected. This enhanced endocytosis is likely to terminate BCR‐mediated calcium signaling prematurely by sequestering the early signaling complexes from the plasma membrane supply of PIP2 and PIP3 needed for Btk and PLC‐g2 activity. Supporting this possibility, endocytosis of BCRs to a large pool of recycling intracellular receptors is enhanced in anergic B cells compared with that of their naı¨ve counterparts (Heltemes‐Harris et al., 2004; Morris et al., 2000). Thus, E3s could modulate calcium signaling by at least two ways, degradation of signaling proteins and enhancing endocytosis. 9. Concluding Remarks Significant progress has been made defining the role of PLC‐g in B lymphocyte development and activation and deciphering the means by which BCR regulates PLC‐g. However, the molecular identification of calcium entry channels

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and elucidation of biochemical sequence of events leading to turn on and off these channels are still poorly understood. Given that many channels, pumps, and adaptors may functionally connect to each other, which in turn contributes to spatiotemporal regulation of effective calcium influx, an answer to this question will require deletion or activation of wild‐type and mutated genes under regulated conditions, as well as the use of multiple fluorescent proteins whose location and expression can be followed simultaneously inside living cells. References Bautista, D. M., Hoth, M., and Lewis, R. S. (2002). Enhancement of calcium signaling dynamics and stability by delayed modulation of the plasma‐membrane calcium‐ATPase in human T cells. J. Physiol. 541, 877–894. Bell, S. E., Vigorito, E., McAdam, S., Reynolds, H. M., Caraux, A., Colucci, F., and Turner, M. (2004). PLCg‐2 regulates Bcl‐2 levels and is required for survival rather than differentiation of marginal zone and follicular B cells. Eur. J. Immunol. 34, 2237–2247. Berridge, M. J., Bootman, M. D., and Roderick, H. L. (2003). Calcium signalling: dynamics, homeostasis and remodeling. Nat. Rev. Mol. Cell. Biol. 4, 517–529. Bezzerides, V. J., Ramsey, I. S., Kotecha, S., Greka, A., and Clapham, D. E. (2004). Rapid vesicular translocation and insertion of TRP channels. Nat. Cell. Biol. 6, 709–720. Bird, G. S., and Putney, J. W., Jr. (1993). Inhibition of thapsigargin‐induced calcium entry by microinjected guanine nucleotide analogues. Evidence for the involvement of a small G‐protein in capacitative calcium entry. J. Biol. Chem. 268, 21486–21488. Biswas, G., Anandatheerthavarada, H. K., Zaidi, M., and Avadhani, N. G. (2003). Mitochondria to nucleus stress signaling: a distinctive mechanism of NFkB/Rel activation through calcineurin‐ mediated inactivation of IkBb. J. Cell. Biol. 161, 507–519. Brauweiler, A., Tamir, I., Dal Porto, J., Benschop, R. J., Helgason, C. D., Humphries, R. K., Freed, J. H., and Cambier, J. C. (2000). Differential regulation of B cell development, activation, and death by the src homology 2 domain‐containing 5’ inositol phosphatase (SHIP). J. Exp. Med. 191, 1545–1554. Chen, J., McLean, P. A., Neel, B. G., Okunade, G., Shull, G. E., and Wortis, H. H. (2004). CD22 attenuates calcium signaling by potentiating plasma membrane calcium‐ATPase activity. Nat. Immunol. 5, 651–657. Chin, L. S., Raynor, M. C., Wei, X., Chen, H. Q., and Li, L. (2001). Hrs interacts with sorting nexin 1 and regulates degradation of epidermal growth factor receptor. J. Biol. Chem. 276, 7069–7078. Chiu, C. W., Dalton, M., Ishiai, M., Kurosaki, T., and Chan, A. C. (2002). BLNK: molecular scaffolding through ‘cis’‐mediated organization of signaling proteins. EMBO J. 21, 6461–6472. Choi, M. S., Brines, R. D., Holman, M. J., and Klaus, G. G. (1994). Induction of NF‐AT in normal B lymphocytes by anti‐immunoglobulin or CD40 ligand in conjunction with IL‐4. Immunity 1, 179–187. Clapham, D. E. (2003). TRP channels as cellular sensors. Nature 426, 517–524. Clayton, E., Bardi, G., Bell, S. E., Chantry, D., Downes, C. P., Gray, A., Humphries, L. A., Rawlings, D., Reynolds, H., Vigorito, E., and Turner, M. (2002). A crucial role for the p110d subunit of phosphatidylinositol 3‐kinase in B cell development and activation. J. Exp. Med. 196, 753–763.

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Role of Human Mast Cells and Basophils in Bronchial Asthma Gianni Marone, Massimo Triggiani, Arturo Genovese, and Amato De Paulis Division of Clinical Immunology and Allergy, Center for Basic and Clinical Immunology Research (CISI), University of Naples Federico II, School of Medicine, I‐80131 Naples, Italy Abstract ........................................................................................................... Introduction ..................................................................................................... Human Mast Cells ............................................................................................. Human Basophils .............................................................................................. Experimental Evidence for Mast Cells in Bronchial Asthma ...................................... Experimental Evidence for Basophils in Bronchial Asthma ........................................ Mast Cell and Basophil Recruitment to Asthmatic Airways ........................................ Anatomical and Functional Evidence for Mast Cells and Basophils in Asthma............... Superallergens in Bronchial Asthma ...................................................................... Angiogenesis in Bronchial Asthma ........................................................................ Tissue Remodeling in Bronchial Asthma ................................................................ Pharmacologic Modulation of Human Mast Cells and Basophils in the Treatment of Bronchial Asthma ................................................................... 12. Conclusions and Implications............................................................................... References .......................................................................................................

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Abstract Mast cells and basophils are the only cells expressing the tetrameric (abg2) structure of the high affinity receptor for IgE (FcERI) and synthesizing histamine in humans. Human FcERIþ cells are conventionally considered primary effector cells of bronchial asthma. There is now compelling evidence that these cells differ immunologically, biochemically, and pharmacologically, which suggests that they might play distinct roles in the appearance and fluctuation of the asthma phenotype. Recent data have revealed the complexity of the involvement of human mast cells and basophils in asthma and have shed light on the control of recruitment and activation of these cells in different lung compartments. Preliminary evidence suggests that these cells might not always be detrimental in asthma but, under some circumstances, they might exert a protective effect by modulating certain aspects of innate and acquired immunity and allergic inflammation. 1. Introduction Bronchial asthma is a genetically complex disease clinically recognized since ancient times. The term ‘‘asthma’’ was coined by Hippocrates (460–377 BC) in the Corpus Hippocraticum to describe the attacks of breathlessness and

97 advances in immunology, vol. 88 # 2005 Elsevier Inc. All rights reserved.

0065-2776/05 $35.00 DOI: 10.1016/S0065-2776(05)88004-6

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wheezing experienced by sufferers. Early contributors to our understanding of asthma include Galen and Moses Maimonides. In 1819, John Bostock first described ‘‘catarrus aestivus,’’ or hay fever, and in 1873 Charles Blackley recognized that pollen grains were the causative agents of hay fever (Cohen and Samter, 1992). In 1923, Coca and Cooke coined the term ‘‘atopy’’ to describe the ‘‘familiar occurrence of asthma, allergic rhinitis, and atopic dermatitis associated with positive skin tests to environmental antigens’’ (Coca and Cooke, 1923). In 1966, Kimishige and Teruko Ishizaka purified a new class of immunoglobulin, denominated ‘‘E’’ (¼ erythema), from the serum of a highly allergic patient (Ishizaka and Ishizaka, 1966). The identification of an IgE myeloma protein by Gunnar Johansson, Leif Wide, and Hans Bennich made reagents available for measurement of total and specific IgE (Wide et al., 1967). Bronchial asthma is a chronic inflammatory disease characterized by episodes of airflow obstruction, which reflects bronchial smooth muscle contraction, bronchial wall edema, and mucus plugging (Marone et al., 2004a). This syndrome is the most common cause of significant respiratory morbidity in adults and children in westernized countries. In the 1800s, ‘‘allergy’’ was described as a rare disorder restricted to the privileged