VOLUME ONE HUNDRED AND SEVENTEEN ADVANCES IN IMMUNOLOGY

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2 VOLUME ONE HUNDRED AND SEVENTEEN ADVANCES IN IMMUNOLOGY

3 ASSOCIATE EDITORS K. Frank Austen Harvard Medical School, Boston, Massachusetts, USA Tasuku Honjo Kyoto University, Kyoto, Japan Fritz Melchers University of Basel, Basel, Switzerland Jonathan W. Uhr University of Texas, Dallas, Texas, USA Emil R. Unanue Washington University, St. Louis, Missouri, USA

4 VOLUME ONE HUNDRED AND SEVENTEEN ADVANCES IN IMMUNOLOGY Edited by FREDERICK W. ALT Howard Hughes Medical Institute, Boston, Massachusetts, USA AMSTERDAM BOSTON HEIDELBERG LONDON NEW YORK OXFORD PARIS SAN DIEGO SAN FRANCISCO SINGAPORE SYDNEY TOKYO Academic Press is an imprint of Elsevier

5 Academic Press is an imprint of Elsevier 525 B Street, Suite 1800, San Diego, CA , USA 225 Wyman Street, Waltham, MA 02451, USA The Boulevard, Langford Lane, Kidlington, Oxford, OX5 1GB, UK 32 Jamestown Road, London, NW1 7BY, UK Radarweg 29, PO Box 211, 1000 AE Amsterdam, The Netherlands First edition 2013 Copyright 2013 Elsevier Inc. All rights reserved No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means electronic, mechanical, photocopying, recording or otherwise without the prior written permission of the publisher Permissions may be sought directly from Elsevier s Science & Technology Rights Department in Oxford, UK: phone (+44) (0) ; fax (+44) (0) ; permissions@elsevier.com. Alternatively you can submit your request online by visiting the Elsevier web site at and selecting Obtaining permission to use Elsevier material Notice No responsibility is assumed by the publisher for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions or ideas contained in the material herein. Because of rapid advances in the medical sciences, in particular, independent verification of diagnoses and drug dosages should be made ISBN: ISSN: For information on all Academic Press publications visit our website at store.elsevier.com Printed and bound in USA

6 CONTENTS Contributors vii 1. Mechanisms of Epigenetic Regulation of Leukemia Onset and Progression 1 Panagiotis Ntziachristos, Jasper Mullenders, Thomas Trimarchi, and Iannis Aifantis 1. Introduction 2 2. Aberrant DNA Methylation in Leukemia 6 3. Disruption of Histone-Modifying Complexes Polycomb and MLL in Leukemia Other Epigenetic Writers, Erasers, and Readers Novel Aspects and Technologies in Epigenetics: Implications for Leukemia 25 Acknowledgments 27 References Translocations in Normal B Cells and Cancers: Insights from New Technical Approaches 39 Roberto Chiarle 1. Mechanistic Elements that Generate Chromosomal Translocations Novel High-Throughput Methods to Study Chromosomal Translocations New Findings on Translocation Formation Obtained by HTGTS and TC-Seq Landscape of Translocations in Cancers Perspectives 63 Acknowledgments 64 References The Intestinal Microbiota in Chronic Liver Disease 73 Jorge Henao-Mejia, Eran Elinav, Christoph A. Thaiss, and Richard A. Flavell 1. Introduction Role of the Intestinal Microbiota on Chronic Liver Diseases Role of the Interactions Between the Innate Immune System and the Intestinal Microbiota on Chronic Liver Diseases Probiotics and their Potential Role in Liver Disease Therapy 89 v

7 vi Contents 5. Conclusions 90 References Intracellular Pathogen Detection by RIG-I-Like Receptors 99 Evelyn Dixit and Jonathan C. Kagan 1. General Principles of the Antiviral Innate Immune Response RLRs are RNA Sensors RIG-I Activation and Receptor Proximal Signal Propagation Regulatory Mechanisms of RIG-I Signaling Conclusions and Future Directions 117 Acknowledgments 118 References 118 Index 127 Contents of Recent Volumes 133

8 CONTRIBUTORS Iannis Aifantis Howard Hughes Medical Institute; Department of Pathology, New York University School of Medicine; NYU Cancer Institute, New York University School of Medicine, and Helen and Martin S. Kimmel Stem Cell Center, New York University School of Medicine, New York, USA Roberto Chiarle Department of Pathology, Children s Hospital Boston and Harvard Medical School, Boston, Massachusetts, USA, and Department of Molecular Biotechnology and Health Sciences, University of Torino, Italy Evelyn Dixit Harvard Medical School and Division of Gastroenterology, Boston Children s Hospital, Boston, Massachusetts, USA Eran Elinav Immunology Department, Weizmann Institute of Science, Rehovot, Israel Richard A. Flavell Department of Immunobiology, Yale University School of Medicine, New Haven, Connecticut, and Howard Hughes Medical Institute, Chevy Chase, Maryland, USA Jorge Henao-Mejia Department of Immunobiology, Yale University School of Medicine, New Haven, Connecticut, USA Jonathan C. Kagan Harvard Medical School and Division of Gastroenterology, Boston Children s Hospital, Boston, Massachusetts, USA Jasper Mullenders Howard Hughes Medical Institute; Department of Pathology, New York University School of Medicine; NYU Cancer Institute, New York University School of Medicine, and Helen and Martin S. Kimmel Stem Cell Center, New York University School of Medicine, New York, USA Panagiotis Ntziachristos Howard Hughes Medical Institute; Department of Pathology, New York University School of Medicine; NYU Cancer Institute, New York University School of Medicine, and Helen and Martin S. Kimmel Stem Cell Center, New York University School of Medicine, New York, USA Christoph A. Thaiss Immunology Department, Weizmann Institute of Science, Rehovot, Israel Thomas Trimarchi Howard Hughes Medical Institute; Department of Pathology, New York University School of Medicine; NYU Cancer Institute, New York University School of Medicine, and Helen and Martin S. Kimmel Stem Cell Center, New York University School of Medicine, New York, USA vii

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10 CHAPTER ONE Mechanisms of Epigenetic Regulation of Leukemia Onset and Progression Panagiotis Ntziachristos*,,,},1, Jasper Mullenders*,,,},1, Thomas Trimarchi*,,,}, Iannis Aifantis*,,,},2 *Howard Hughes Medical Institute, New York, USA Department of Pathology, New York University School of Medicine, New York, USA NYU Cancer Institute, New York University School of Medicine, New York, USA } Helen and Martin S. Kimmel Stem Cell Center, New York University School of Medicine, New York, USA 1 These authors contributed equally to this work 2 Corresponding author: address: iannis.aifantis@nyumc.org Contents 1. Introduction Leukemia as a heterogeneous and multifactorial disease Epigenetic factors and their possible roles in leukemia 4 2. Aberrant DNA Methylation in Leukemia The role of DNA methylation in hematopoietic malignancies The role of DNMT3A in leukemia The biology of TET proteins and their perturbations in leukemia IDH1 and IDH2 oncometabolic proteins Disruption of Histone-Modifying Complexes Polycomb and MLL in Leukemia PRC2 in hematological neoplasms Role of PRC1 in leukemia MLL function Other Epigenetic Writers, Erasers, and Readers Arginine methyltransferases Lysine demethylases (KDMs) Histone demethylases inhibitors (KDMi) Histone acetyl transferases Histone deacetylases Bromodomain-containing proteins Plant homeodomain-containing proteins Chromatin remodeling complexes Novel Aspects and Technologies in Epigenetics: Implications for Leukemia Combinatorial epigenetic marks Novel aspects of regulation and epigenetic factors in cancer 26 Acknowledgments 27 References 28 Advances in Immunology, Volume 117 ISSN # 2013 Elsevier Inc. All rights reserved. 1

11 2 Panagiotis Ntziachristos et al. Abstract Over the past decade, it has become clear that both genetics and epigenetics play pivotal roles in cancer onset and progression. The importance of epigenetic regulation in proper maintenance of cellular state is highlighted by the frequent mutation of chromatin modulating factors across cancer subtypes. Identification of these mutations has created an interest in designing drugs that target enzymes involved in DNA methylation and posttranslational modification of histones. In this review, we discuss recurrent genetic alterations to epigenetic modulators in both myeloid and lymphoid leukemias. Furthermore, we review how these perturbations contribute to leukemogenesis and impact disease outcome and treatment efficacy. Finally, we discuss how the recent advances in our understanding of chromatin biology may impact treatment of leukemia. 1. INTRODUCTION 1.1. Leukemia as a heterogeneous and multifactorial disease Hematopoietic malignancies are a broad category of diseases (Gilliland, 2001). Leukemia is one of the most aggressive among them and is characterized as the abnormal proliferation of immature cells of the hematopoietic system. Different types of leukemias can arise from lymphocytes (lymphocytic leukemia), myeloid cells (myeloid leukemia), erythrocytes (erythrocytic leukemia), and others in the bone marrow, lymph nodes, or spleen. Regardless of the cell type of origin, leukemia generally proceeds in either a chronic or an acute manner. Chronic disease consists of a long incubation period, whereas acute leukemia is associated with an abrupt accumulation of immature blood cells in the peripheral blood, bone marrow, and secondary lymphoid organs. Certain disorders are marked by both a chronic and acute phases, which are categorized based on several factors. Among the most common forms of leukemia are two chronic variants, chronic myeloid leukemia (CML) and chronic lymphoblastic leukemia (CLL), and two acute variants, acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML). We briefly review these disease types below Chronic myeloid leukemia CML is a unique case of leukemia that is characterized by the presence of the Philadelphia chromosome. This reciprocal translocation between chromosomes 9 and 22 leads to the formation of a chimeric protein consisting of the breakpoint cluster region (BCR) gene with the abelson kinase (ABL1) gene.

12 Mechanisms of Epigenetic Regulation of Leukemia Onset and Progression 3 The resulting Bcr-Abl oncogene is characterized by constitutive tyrosine kinase activity leading to activation of downstream targets (Bartram et al., 1983; Druker, 2008). The current standard of care for CML is the small-molecule kinase inhibitor Imatinib, a very specific inhibitor of the Bcr-Abl fusion protein. Treatment with Imatinib results in a 5-year progression free survival rate of approximately 89% (Druker et al., 2006). Resistance to Imatinib occurs in certain cases usually through mutations in the Imatinib binding site in Bcr-Abl (Deininger, Goldman, & Melo, 2000; Holtz, Forman, & Bhatia, 2005). It is also worth noting that Imatinib does not eradicate the disease, as it apparently does not target the CML leukemiainitiating cells (LICs) Acute myeloid leukemia AML is the most common acute leukemia and its incidence increases with age (Daver & Cortes, 2012). AML can either occur de novo or be preceded by a premalignant state. Several preleukemic conditions exist (Byrd et al., 2002) which have the potential to progress to AML. Myelodysplastic syndromes (MDS) or -myeloproliferative neoplasms (MPN) are characterized by a block in differentiation leading to accumulation of myeloid progenitor cells. Included in MDS and MPN are refractory anemia (RA), chronic myelomonocytic leukemia (CMML), polycythemia vera (PV), essential thrombocytosis (ET), and myelofibrosis (MF). Around one-third of the MDS cases progresses and gives rise to AML. AML is a heterogeneous disease that can be classified in as many as seven subtypes (de Jonge, Huls, & de Bont, 2011). These subtypes are characterized by a variety of cytogenetic and cell surface markers. Unlike CML, there is no unifying way of treating AML patients. In general, AML is treated with an array of chemotherapeutic drugs; in some cases, chemotherapy is followed by bone marrow transplantation. Overall, AML can be very hard to treat, resulting in a relatively high mortality, which is reported to account approximately to 10,000 deaths per year in the United States Acute lymphoblastic leukemia ALL is an acute disorder of either B-lymphocytes (B-ALL) or T-lymphocytes (T-ALL). ALL is the most common form of cancer in children (Pui & Evans, 2006). The genetics of ALL are quite complex and are comprised of a variety of chromosome fusions. Similar to AML, these chromosome fusions can be used to distinguish different subtypes of disease, which are associated with distinct clinical features and outcome.

13 4 Panagiotis Ntziachristos et al. In T-ALL, the most common genetic event is the activation of the Notch pathway. Mutations leading to enhanced Notch signaling are present in more than 50% of patients (Aifantis, Raetz, & Buonamici, 2008). This can be explained by the fact that in thymic development, signaling through the Notch receptor promotes cell cycle progression and proliferation and Notch1 therefore acts as a proto-oncogene in this setting. Treatment of ALL especially in children has become very effective, leading to cure rates as high as 80% (Chessells et al., 2003; Rivera et al., 2005). This is mainly achieved by the use of advanced chemotherapy regimen. Although this is an outstanding clinical achievement, novel less toxic treatments should still be pursued Chronic lymphocytic leukemia Chronic lymphocytic leukemia (CLL) is the most common type of adult leukemia (Cramer & Hallek, 2012). CLL is a disease of the B-cell lymphocytes that is characterized by a very slow progression. The incidence of CLL increases with aging. Progression of the disease can be at such a low rate that treatment is sometimes postponed till later stage. As in the leukemias described above, chromosomal aberrations and gene mutations (including mutations in the NOTCH pathway) are common in CLL. And, again, these genetic variants also determine disease outcome Epigenetic factors and their possible roles in leukemia The focus of this review is the regulation and deregulation of epigenetic processes in different types of leukemia. The term epigenetics was coined by C.H. Waddington in the 1940s and is a fusion of words genetics and epigenesis. The major meaning of epigenesis at that time was that the embryo gradually changes into the adult organism in contrast to the prevailing idea of that era that the adult is preformed at the embryo stage. A more modern definition of epigenetics has been proposed as a change in the state of expression of a gene that does not involve a mutation, but that is nevertheless inherited in the absence of the signal (or event) that initiated the change (Ptashne, 2007). The term is used for phenomena such as genomic imprinting, paramutation, polycomb complex-mediated gene silencing, and position effect variegation. Model organisms have proven to be incredible tools to obtain insight in epigenetic phenomena. For instance, Drosophila development allows the study of stem cells that are responsible for the formation of adult structures in the fly.

14 Mechanisms of Epigenetic Regulation of Leukemia Onset and Progression 5 Epigenetic phenomena must fit at least one of the following three criteria (Bonasio, Tu, & Reinberg, 2010): (i) a mechanism for propagation, the signal must be propagated through DNA replication/cell division; (ii) the signal must be transmitted to the progeny; and (iii) the signal should affect gene expression. Among, the modifications that fit these criteria are histone modifications, histone variants, DNA methylation, relative nucleosomal position, and occupancy and larger chromatin domains (Margueron & Reinberg, 2010). To date, DNA methylation is the only epigenetic mark that fulfills all three criteria. Many different mechanisms have been proposed that would explain the propagation and transmission of histone marks, or the histone variants; however, these processes are not completely understood currently and require further investigation (Bonasio et al., 2010). Recently, it has become clear that disruption of epigenetic processes contributes to leukemic transformation. Traditionally, mutations in leukemia were thought to involve two discreet classes of genes. One class contains genes whose mutation can give a proliferation or survival advantage to the cell and is not specific to the hematopoietic system. This would include components of RAS-MAPK signaling, PI3-kinase/AKT signaling, and others. A second class of genes mutated in leukemia consists of regulators of hematopoiesis which do not necessarily give a growth or survival advantage but result in differentiation defects (Gilliland, 2001; Shih, Abdel-Wahab, Patel, & Levine, 2012). Although epigenetic regulators often do not belong to either of these two classes of genes, they are nonetheless frequently mutated in leukemia. This is exemplified by the translocations that are commonly found in leukemia and affect mixed lineage leukemia (MLL), polycomb repressive complex 2 (PRC2), or the ten-eleven translocation (TET ) family. It has been proposed that deregulation of epigenetic factors can provide a tumor cell the plasticity needed to adapt to different situations. Similarly, it is thought that perturbation of epigenetic regulators prior to full transformation may be a priming event that allows a more permissive environment for leukemogenesis upon acquisition of additional mutations (Feinberg, 2007). Apart from the enzymes that catalyze the histone or DNA modifications (epigenetic writers), there are proteins that specifically bind modified histone residues (readers), as well as enzymes that remove covalent modifications (erasers). There are enzymes containing the appropriate domains for both reading and writing of the marks. Mutations that alter enzymatic function can be found in all these types of chromatin-interacting proteins. In this review, we will discuss the major perturbations to epigenetic processes found in leukemia. For purposes of clarity, we will divide this review

15 6 Panagiotis Ntziachristos et al. into three sections comprising the following: (1) DNA methylation; (2) polycomb and MLL complexes and their roles in physiology and disease; and (3) other epigenetic modulators, with an emphasis on the ones that are mutated in leukemia. Moreover, novel therapeutic options will be mentioned throughout the review, such as inhibitors of epigenetic modulators and their combinations with current therapies. Finally, emerging technologies and biological paradigms and how the potential for novel-targeted therapies will be discussed. Of course, the field is enormous and this review cannot cover every aspect of epigenetic regulation in leukemia; we thus apologize to our colleagues for any potential omissions. 2. ABERRANT DNA METHYLATION IN LEUKEMIA 2.1. The role of DNA methylation in hematopoietic malignancies DNA methylation is the most common epigenetic modification. Methylation of CpG islands in the promoters of genes is generally associated with reduced expression from that locus. CpG islands can be at least 200 bases in size with a GC content of at least 50%. CpG dinucleotides are quite rare in mammalian genomes (1%) (Esteller, 2008), despite which about 60% of human promoters contain CpG islands. Although the majority of CpG islands are unmethylated, a small percentage (6%) becomes methylated in a tissue-specific manner during early development or in differentiated tissues (Straussman et al., 2009). Besides CpG island methylation in the promoter, DNA methylation of the gene body is common. This is mainly seen in ubiquitously expressed genes and is positively correlated with gene expression (Hellman & Chess, 2007). It has been proposed that gene body DNA methylation might increase elongation efficiency and prevent spurious initiation of transcription (Zilberman, Gehring, Tran, Ballinger, & Henikoff, 2007). Aberrant methylation patterns are considered to be one of the characteristics of the cancer epigenome (Laird & Jaenisch, 1996). In general, global DNA hypomethylation is observed which can lead to chromosomal instability (Eden, Gaudet, Waghmare, & Jaenisch, 2003; Gaudet et al., 2003; Holm et al., 2005; Nishigaki et al., 2005). This general hypomethylation can lead to aberrant activation of oncogenes such as cyclin D2 and maspin (Oshimo et al., 2003). On the other hand, hypermethylation of the promoters of tumor-suppressor genes such as retinoblastoma 1, CDKN2A (also known as cyclin-dependent kinase inhibitor p16), the von Hippel Lindau

16 Mechanisms of Epigenetic Regulation of Leukemia Onset and Progression 7 tumor suppressor, and MutL protein homologue 1 can lead to aberrant silencing (Esteller, 2007; Herman & Baylin, 2003; Jones & Baylin, 2002). Therefore, it is not surprising that DNA methyltransferase (DNMT) enzymes, which catalyze the addition of a methyl group to CpG dinucleotides, play key roles in development and disease. DNMT1 is considered to be the maintenance methyltransferase and can act on unmethylated DNA. DNMT3A and DNMT3B are the de novo DNMTs, whereas DNMT3-like lacks catalytic activity but acts as cofactor for DNMT3A/B and interacts and colocalizes with them in the nucleus. Only recently, it became clear that mutations in DNMT3A are common in AML (Ley et al., 2010; Yan et al., 2011). Moreover, there has been an advent of specific DNMT inhibitors that are used against MDS with very encouraging results (Dawson & Kouzarides, 2012) The role of DNMT3A in leukemia DNMT3A mutations in hematopoietic malignancies Mutations in DNMT3A (Fig. 1.1) were reported in approximately 20% of cases of AML of various subtypes (Ley et al., 2010). Identical mutation percentages were found in the AML-M5 subtype that is classified as acute monocytic leukemia (Yan et al., 2011). In addition, it was reported that DNMT3A is mutated in other hematopoietic malignancies albeit at a lower frequency (Thol et al., 2011; Walter et al., 2011). DNMT3A mutations seem not to be restricted to leukemias from the myeloid lineage, as recently mutations have also been found in T-cell lymphoma and T-ALL (Couronne, Bastard, & Bernard, 2012; Simon et al., 2012). In pediatric AML, however, mutations in DNMT3A have not been found, despite the sequencing and analysis of a cohort consisting of 180 patients (Ho et al., 2011) Functional consequence of DNMT3A mutations So far, mutations identified in DNMT3A are found to be exclusively heterozygous. Specifically, a very clear hotspot can be identified for DNMT3A mutations, as around 50% of the mutations occur in residue R882 (Ley et al., 2010). In vitro experiments showed that AML-linked mutations in DNMT3A lead to a severe loss of enzymatic activity. However, as DNMT3A is one of two de novo DNMTs in the human genome, it is unclear what the molecular consequence of DNMT3A mutations is. One study compared the DNA methylation status of DNMT3A mutant versus wild-type AML samples. This revealed that, as expected, some

17 A O O HO O OH OH IDH1 or IDH2 O O OH O Mutant IDH1 or IDH2 OH Isocitrate OH Oxoglutarate O OH O OH OH 2-Hydroxyglutarate NH 2 N DNMTs CH 3 NH 2 N TETs OH NH 2 N N H O N O N O H H + + Oxoglutarate Succinate B (i) CpG CpG CpG RNAP2 (ii) DNMT DNMT DNMT CpG CpG CpG RNAP2 X CpG (iii) Unmodified CpG island TET2 TET2 TET2 CpG CpG CpG RNAP2? CpG Methylated CpG island CpG Hydroxy methylated CpG island Figure 1.1 The role of DNA methylation in leukemia. (A) Wild-type IDH converts isocitrate to oxoglutarate. Mutations in IDH1 and 2 as found in myeloid leukemias change the activity of the enzyme. Mutant IDH converts oxoglutarate to 2-hydroxyglutarate. Oxoglutarate is a cofactor to dioxygenases like the TET proteins. TET proteins convert 5-methylcytosine to 5-hydroxymethylcytosine. This potentially leads to a demethylation of the DNA, which will permit transcription from a previously silent locus. (B) Overview of the effect of the different enzymes that regulate DNA methylation. When CpG islands are unmethylated, transcription can occur from that locus. (i) DNMT enzymes methylate CpG islands in the promoter, this leads to repression of transcription from this locus. (ii) TET proteins can oxidize the methylcytosine to 5-hydroxymethylcytosine. (iii) The outcome of this reaction is not yet fully understood, but it is suggested that this leads to demethylation permits transcription.

18 Mechanisms of Epigenetic Regulation of Leukemia Onset and Progression 9 CpG islands in promoters indeed become hypomethylated. In AML samples with mutant DNMT3A, a lower level of methylation of CpG islands in the HoxA-gene cluster was detected. In addition, there was a clear correlation with increased expression of the HoxA genes, which leads to a less differentiated phenotype (Yan et al., 2011) Mouse models of DNMT3 function Initially, no apparent hematopoietic stem cell (HSC) differentiation defect was observed in mice mutant for either DNMT3A or DNMT3B (Tadokoro, Ema, Okano, Li, & Nakauchi, 2007). It was found that cells deficient for DNMT3A or DNMT3B could still give rise to a variety of progenitors. In addition, it was shown that HSCs depleted for both DNMT3A and DNMT3B could not reconstitute hematopoiesis of a recipient animal. After the identification of the DNMT3A mutations in AML, Challen et al. (2012) further examined the DNMT3A knockout phenotype. In this case, it was found that loss of DNMT3A led to decreased differentiation of mouse HSCs. This phenotype could be correlated with higher expression of genes that are involved in maintaining multipotency of HSCs. Strikingly, when comparing methylation patterns in wild type and DNMT3A mutant cells, no significant changes were found in overall DNA methylation. However, further analysis of specific loci revealed that some genes were hypo- while others were hypermethylated in DNMT3A knockout animals. Genes that were found to be hypomethylated and consequently higher expressed include the well-known HSC homeostasis genes RUNX1 and GATA Is mutant DNMT3A a prognostic marker in myeloid leukemia? The genetics of AML are very complex, but, nevertheless, it has been reported that the mutation status of DNMT3A by itself is a significant prognostic marker for disease outcome in AML (Ley et al., 2010; Marcucci et al., 2012; Ribeiro et al., 2012). Common genetic lesions co-occurring with mutant DNMT3A are mutations in NPM1 and FLT3. Especially, the combination of an FLT3- ITD mutation combined with mutant DNMT3A seems to be associated with unfavorable outcome in this disease (Patel et al., 2012). Moreover, one report showed that patients with DNMT3A mutations could benefit from higher than normal dose of chemotherapy (Daunorubicin) (Patel et al., 2012) DNMT inhibitors Currently, two DNMT inhibitors, vidaza (5-azacytidine) and decitabine (5-aza-2-deoxycytidine), are approved for the treatment of cancer patients. Both vidaza and decitabine are analogues of the nucleotide cytosine.

19 10 Panagiotis Ntziachristos et al. The relatively low side effects make these DNMT inhibitors the drug of choice for the treatment of MDS. However, in the more advanced AML, the use of decitabine is debated and is reported to have very little effect. Nevertheless, combination of inhibitors for histone deacetylases (HDACs) with DNMTi has given even more very promising outputs (Gore, 2011). Another preliminary study used a small cohort of patients in which it seems that DNMT3A mutant AMLs are more sensitive to the DNA methylation inhibitor Decitabine (Metzeler et al., 2012). The mechanism behind these responses is currently unknown The biology of TET proteins and their perturbations in leukemia TET proteins In a search for proteins that are homologous to the J-binding proteins from the parasite leishmania, the only homologous proteins identified in the human genome were the TET proteins (Tahiliani et al., 2009). J-binding proteins were known for their capacity to bind a modified DNA base, base J that is unique for the parasite. Base J is a glycosylated derivative of the base thymidine. This suggested a role for the TET proteins in modifying DNA directly. Indeed, further studies showed that in TET proteins resides the catalytic activity to modify 5-methylcytosine to 5-hydroxymethylcytosine (5-hmC) (Tahiliani et al., 2009). Soon after this finding, Delhommeau et al. (2009) reported frequent mutations of TET2 in AML again suggesting a key role for DNA methylation in leukemogenesis. Some of these mutations were later verified to be true loss-of-function variants (Ko et al., 2010); however, the role of 5-hmC in tumor development remains to be fully appraised. A variety of technical issues have hampered the study of TET2 and 5-hmC in leukemia. The lack of a TET2 antibody, for instance, has made it difficult to study its genomic occupancy. However, recent technical advances have made genome-wide 5-hmC profiling possible with base-pair resolution (Booth et al., 2012; Yu et al., 2012) Mutational status of TET proteins in leukemia First identified as a gene (TET1) in a chromosomal translocation in AML, it took some time to appreciate the importance of the TET proteins in leukemia. The initial report described a fusion between chromosomes

20 Mechanisms of Epigenetic Regulation of Leukemia Onset and Progression and 11 in AML that lead to a chimeric protein consisting of the MLL amino(n)-terminus and the carboxyl(c)-terminus of TET1 (Lorsbach et al., 2003). In addition, despite the fact that fusions and deletions in chromosome 4 were detected in a number of AML patients (Viguie et al., 2005), it was only later understood that a single gene was present in this locus. The gene product showed a high level of sequence conservation with the previously identified TET1 protein and was therefore named TET2. Further analysis of the human genome identified one more protein homologous to both TET1 and TET2, that is, TET3 (Delhommeau et al., 2009). Fusions of TET1 and deletions of the TET2 locus indicated an important role of the TET proteins in hematopoietic malignancies. And, indeed, sequencing efforts confirmed that TET2 (Fig. 1.1) is a commonly mutated gene in myeloid leukemia and premalignant stages of leukemia. So far, TET2 mutations have been found in AML, CMML, MDS, and other myeloid malignancies. The largest studies suggest that TET2 mutations can be identified in 2 10% of PV and ET patients, and in 10 20% of patients with primary MF or post-pv/et MF (Abdel-Wahab et al., 2010, 2009; Cimmino, Abdel-Wahab, Levine, & Aifantis, 2011; Tefferi et al., 2009). In addition, studies of paired MPN and AML samples from individual patients demonstrated that TET2 mutations are commonly acquired during transformation to AML from a chronic myeloid neoplasm (Abdel-Wahab et al., 2010). Surprisingly, mutational analysis of both TET1 and TET3 has not been as fruitful. Mutations in TET1 and TET3 have been reported in patients with CLL, but the overall incidence of these mutations is currently unknown (Quesada et al., 2012). One of the few studies that carefully investigated the status of all the three TET family members in myeloid malignancies found only TET2 and not TET1 nor TET3 mutated (Abdel-Wahab et al., 2009). Recently, TET2 has been found to be also mutated in lymphoid neoplasms (Couronne et al., 2012; Quivoron et al., 2011). Finally, recent studies point to a role for TET proteins in solid tumors, as sporadic mutations have been identified in brain (Parsons et al., 2011) and prostate cancers (Grasso et al., 2012) Consequence of TET2 mutations in AML The majority of our knowledge of the TET proteins comes from studies performed in nonhematopoietic cells. For instance, one study that sheds light on how TETs could be involved in active DNA methylation was performed in the brain (Guo, Su, Zhong, Ming, & Song, 2011). The proposed mechanism

21 12 Panagiotis Ntziachristos et al. involves activation-induced (cytidine) deaminase (AID) and APOBEC proteins, which promote the conversion of 5-hmC into an unmodified cytosine and thereby lead to active demethylation of the DNA. If this mechanism were proven to be universal, the consequence of loss of TET2 function would be increased DNA methylation. This does pose some sort of a conundrum as we have discussed earlier that loss-of-function mutations in DNMT3A are common in AML. So far, however, it is not clear what happens on the level of DNA methylation in TET2 mutant cells. There is conflicting evidence in the literature reporting that TET2 loss could lead to either increased or decreased DNA methylation (Figueroa et al., 2010; Ko et al., 2010) TET2 mouse models Several research groups, including ours, have modeled the loss of TET2 in the hematopoietic system (Li et al., 2011; Moran-Crusio et al., 2011; Quivoron et al., 2011). In all cases, the loss of TET2 leads to a decrease in 5-hmC levels as expected. Deletion of TET2 in the HSC compartment causes an increase in self-renewal capacity. During the maturation of the TET2 knockout animals, an increase in the frequency of both myeloid and lymphoid cells can be observed. This premalignant state develops into a myeloproliferative neoplasm as the mice become older; this results in splenomegaly and either an MDS or a CMML-like disease IDH1 and IDH2 oncometabolic proteins IDH1 and IDH2 mutations in leukemia The isocitrate dehydrogenase (IDH) enzymes are NADP-dependent molecules that normally function as homodimers to catalyze the oxidative decarboxylation of isocitrate to alpha-ketoglutarate (a-kg) with the concomitant production of NADPH. Mutations in IDH1 and IDH2 are important for our discussion for two reasons. First, the mutations occur in a hotspot resulting in the alteration of the enzymatic activity of the enzyme. Second, inhibition of TET2 seems to be part of the mechanism by which mutations in IDH1 and IDH2 cause leukemia (Figueroa et al., 2010). The first indication that the IDH enzymes were involved in carcinogenesis came from a study in gliomas (Yan et al., 2009). Strikingly, it was found that nearly all mutations occur in a couple of residues in either IDH1 (R132) or IDH2 (R140 or R172) (Fig. 1.1). Not much later mutations in IDH1 and IDH2 were detected in hematopoietic malignancies. Especially, myeloid malignancies are reported to have mutations in either IDH1 or

22 Mechanisms of Epigenetic Regulation of Leukemia Onset and Progression 13 IDH2 at a rate of around 9% (Green & Beer, 2010; Ward et al., 2010). In particular, mutations have been reported in MDS and MPN (Kosmider et al., 2010) Consequence of IDH mutations As mentioned above, mutations in the IDH1 and IDH2 proteins occur in the protein catalytic site. Wild-type IDH enzymes can convert isocitrate to a-kg. IDH1 is predominantly cytoplasmic, while IDH2 can be found in the cell mitochondria. So far, only heterozygous IDH mutations have been found, leaving one allele intact. One very exciting finding was the fact that mutations in IDH proteins do not abrogate its enzymatic function but change the outcome of its reaction toward isocitrate. Mutant IDH proteins have a much higher output of 2-hydroxyglutarate (2-HG) at the expense of a-kg (Ward et al., 2010). 2-HG is an oncometabolite that can be used as a marker to distinguish wild-type IDH from mutant IDH cancers. At the molecular level, this also somehow explains how mutations in an enzyme, so critical for cellular homeostasis, can be tolerated. Mutations in IDH1 and IDH2 seem to have similar effects on the enzyme function. It is therefore not surprising that mutations in IDH1 and IDH2 are mutually exclusive. Recent studies showed a role for oncometabolites, such as 2-HG, in the function of epigenetic modulators (Teperino, Schoonjans, & Auwerx, 2010). Under normal conditions, a-kg is produced in the trichloroacetic acid (TCA) cycle from isocitrate and is a cofactor for dioxygenases. Among these dioxygenases are the Jumonji-domain-containing histone demethylases, as well as the Tet family of hydroxymethylases. As we have discussed earlier, mutations in IDH1 and IDH2 lead to the increased production of 2-HG, leading to reduced catalytic activity of certain dioxygenase enzymes. In an elegant study, this hypothesis was proven (Figueroa et al., 2010). First, it was shown that DNA isolated from IDH mutant AMLs is more hypermethylated. Second, it was shown that mutations in IDH proteins inhibit the conversion of 5-mC into 5-hmC by TET proteins. This observation is supported by the fact that TET2 and IDH mutations are mutually exclusive in AML (Figueroa et al., 2010). Other enzymes that are affected by IDH mutations are the histone demethylases, especially the H3K9me3 demethylase KDM4C (Lu & Thompson, 2012; Lu et al., 2012; Turcan et al., 2012). Along these lines, it is possible that mutations of other enzymes in the TCA cycle can cause similar effects. Examples of these are loss-of-function mutations in the enzymes succinate dehydrogenase and fumarate hydratase (Kaelin, 2011).

23 14 Panagiotis Ntziachristos et al Animal models for IDH gene function Very recently, the IDH1 mutation commonly found in AML (R132H) was modeled in a mouse (Figueroa et al., 2010). This mutation was created in a conditional fashion in one of the endogenous IDH1 alleles. This murine model showed that mutant IDH1 is indeed sufficient to disrupt the hematopoietic system homeostasis. IDH1 mutant mice show extra medullary hematopoiesis and a loss of cells from the bone marrow. This phenotype is associated with an increase in methylation of both DNA and histones. 3. DISRUPTION OF HISTONE-MODIFYING COMPLEXES POLYCOMB AND MLL IN LEUKEMIA Posttranslational modification of N-terminal histone tails is a more recently appreciated mechanism of regulation of gene expression patterns in development and disease. Since Jenuwein and Allis (2001) first proposed the histone code hypothesis in 2001, there has been an explosion in research aimed at cataloging all posttranslational modifications added to the histones and their distribution across genomes as well as association with particular transcriptional states (Ernst et al., 2011; Tan, Luo, et al., 2011). Additionally, many groups have focused on understanding how enzymes that catalyze or remove these modifications and other proteins with the ability to read histone marks are involved in global regulation of chromatin states (Shih et al., 2012; Zhou, Goren, & Bernstein, 2011). The importance of such enzymes in disease development is highlighted by frequent mutation of many key histone modifiers in human cancer (Abdel-Wahab et al., 2012; Dawson, Kouzarides, & Huntly, 2012; Ntziachristos et al., 2012; Patel et al., 2012; Shih et al., 2012; van Haaften et al., 2009; Zhang, Ding, et al., 2012), including both solid tumors and hematological neoplasms. Deregulation of mechanisms regulating histone modification seems to have a particularly important role in leukemic transformation as genetic lesions targeting such proteins are often considered driver mutations, with potent oncogenic activity. Here, we will focus on two histone-modifying complexes, the PRC, including both PRC2 and PRC1, and MLL complexes, which are frequently perturbed in human leukemia of several different blood lineages PRC2 in hematological neoplasms PRC2 is a large multimeric enzymatic complex that includes the setdomain-containing methyltransferase EZH2. Other key components include chromodomain-containing protein EED, SUZ12, and histone

24 Mechanisms of Epigenetic Regulation of Leukemia Onset and Progression 15 A Polycomb repressive complex 2 B EZH2 JARID2 EED EZH2 Set SUZ12 RBBP4/7 CDKN2A/B HOXA NH 2 SANT SANT CXC SET Nonsense/InDels Missense Y641 T-ALL Myeloid disorders DLBCL C KDM6A ASH2L WDR5 KDM6B RBBP5 MLL Set COMPASS-like complex RNAP2 HOXA MEIS1 MLL-fusion methyltransferase complex MLL AF9 AF10 DOT1L ENL CBX8 TIP60 D MLL protein Breakpoint NH 2 CxxC AT Hooks PHD TA MLL-fusion proteins SET AT Hooks CxxC AF-9 H3K4me3 H3K79me2 H3K27me3 AT Hooks CxxC AF-4 Figure 1.2 Genetic perturbations impacting EZH2 and MLL proteins. (A) EZH2, the catalytic subunit of PRC2, represses gene activity by methylation of H3 on lysine 27. (B) Representative distribution of EZH2 mutations reported in T-ALL, myeloid disorders (MDS, MPN, CMML, AML), and DLBCL. (C) The wild-type MLL protein is the catalytic subunit of mammalian COMPASS-like complexes which enhances gene activity through methylation of H3 on lysine 4. MLL-fusion proteins frequently associate with members of DotCom to regulate methylation of H3 on lysine 79. (D) MLL-fusion proteins typically do not involve the Set methyltransferase domain but rather the N-terminal AT hooks and CxxC domain. Frequent MLL-fusion partners include AF-9, AF-4, and ENL. AT Hooks CxxC ENL chaperone RBBP4/7 (Margueron & Reinberg, 2011) (Fig. 1.2A). As its name suggests the main function of this complex is to silence gene expression at specific loci through catalysis of trimethylation of lysine 27 of histone 3 (H3K27me3). The presence of this mark not only enhances the activity of PRC2 itself but is also read by the polycomb repressive complex 1 (PRC1), leading to monoubiquitylation of histone 2A lysine 119 and subsequent chromatin compaction (Simon & Kingston, 2009). Gene silencing by PRC2 is critical for establishing proper lineage commitment during development by inactivating genes required for alternative cell fates. With a critical role in nearly every developmental system, it is not surprising that deregulation of PRC2 function contributes to tumorigenesis (Bracken & Helin, 2009; Margueron & Reinberg, 2011; Sauvageau & Sauvageau, 2010; Sawarkar & Paro, 2010). Although components of PRC2 are heavily mutated in many types of cancer, the consequences of such mutations in leukemia are especially intriguing with reports of both oncogenic and tumor-suppressor function

25 16 Panagiotis Ntziachristos et al. of the complex in neoplasms derived from different lineages (Ernst et al., 2010; Morin et al., 2010) (Fig. 1.2B). Originally suggested to be a loss-of-function mutation, recurrent mutations in EZH2 residue Y641 have now been shown to enhance PRC2 activity by cooperating with complexes containing the wild-type EZH2 protein leading to more efficient catalysis and hypertrimethylation of lysine 27 of histone 3 (H3K27me3) in follicular and diffuse large B-cell lymphoma (DLBCL) (McCabe et al., 2012; Sneeringer et al., 2010; Yap et al., 2011). Conversely, in T-cell acute lymphoblastic leukemia (T-ALL), loss-of-function mutations to several PRC2 subunits including EZH2, SUZ12, and EED have been reported to result in a more aggressive phenotype compared to wild-type tumors (Ntziachristos et al., 2012; Simon et al., 2012), suggesting a tumorsuppressor role for the complex in this context. Unlike DLBCL, T-ALL mutations targeting PRC2 components consist mainly of nonsense mutations upstream of the catalytic domain of EZH2 and larger deletions of the locus, suggesting a true loss-of-function outcome. Further highlighting the duality of PRC2 function in hematological tumors, it has been suggested that within different subtypes of myeloid disease both an oncogenic and a tumor-suppressor function for this complex exist. Ernst et al. (2010) have shown loss-of-function EZH2 mutations in MDS and MPN with poorer overall survival in patients with mutant alleles. However, in mouse models of MLL-AF9 positive AML, it seems that PRC2 is required for efficient transformation, suggesting a role for the complex in contributing to aberrant self-renewal of LICs (Neff et al., 2012; Shi et al., 2012). These results suggest that proper maintenance of the H3K27me3 modification is critical for normal cell homeostasis. Although the results discussed above are compelling, our understanding of the mechanism through which deregulated H3K27me3 might lead to leukemic transformation is very poorly understood. As a tumor suppressor, we might imagine an antagonistic relationship between PRC2 and oncogenic transcription factor networks. In diseases driven by transcriptional activators, we support a model where genes targeted for activation by the oncogenic factor might in turn be occupied for silencing by PRC2. Thus, loss of PRC2 function may create a more permissive environment for the activity of oncogenic transcription factors. As an oncogene, there is evidence that PRC2 can act to directly repress key tumor-suppressor genes such as the CDKN1A, CDKN1B (Velichutina et al., 2010), or CDKN2A/CDKN2B (Chen et al., 2009) loci providing a mechanism of epigenetic silencing in lieu of genetic inactivation.

26 Mechanisms of Epigenetic Regulation of Leukemia Onset and Progression 17 Recently, mutations of the protein ASXL1, that is part of the polycombrepressive deubiquitylase complex, were identified in human malignancies (Abdel-Wahab et al., 2012; Shih et al., 2012). This complex catalyzes the deubiquitination of H2AK119, the modification left by PRC1, suggesting a possible antagonistic relationship. Surprisingly, inactivation of ASXL1 has been shown to have a potent effect on PRC2 function leading to global decreases in H3K27me3 although the mechanism by which this occurs is unclear. However, loss of ASXL1 and PRC2 function at the HOXA cluster was shown to correlate with increased HOXA9 expression which is known to contribute to myeloid transformation (Abdel-Wahab et al., 2012) Role of PRC1 in leukemia Like PRC2, PRC1 has also been suggested to play a role both in maintenance of HSCs and transformation in vivo. However, unlike PRC2, there are very few reports of mutations in PRC1 complex members in cancer. Specifically, there are studies showing that PRC1 component BMI1 is required for normal HSC function and similarly for maintenance of leukemic stem cell function in MLL-rearranged leukemia (Oguro et al., 2012; Park et al., 2003). It has been proposed in both settings that BMI1 is essential for maintaining PRC1-mediated suppression of the CDKN2A/CDKN2B locus, thus allowing cells to evade cellular senescence. Nevertheless, mutations in BMI1 have not been described so far Histone methyltransferase inhibitors Chaetocin, deazaneplanocin (DZNep), and BIX are the best characterized histone methyltransferase inhibitors. All these inhibitors have so far only been tested in the preclinical environment. However, at this stage, results are promising; for example, chaetocin has anticancer properties against multiple myeloma (MM) cells (Greiner, Bonaldi, Eskeland, Roemer, & Imhof, 2005; Isham et al., 2007). Combination of the PRC2 (EZH2) inhibitor DZNep and a HDAC inhibitor (HDACi) (Panobinostat) has been shown to kill AML cells in vitro (Fiskus et al., 2009) MLL function The MLL gene is the human homologue of Drosophila melanogaster trithorax. Trithorax was initially described as a regulator of homeotic gene expression in flies. Now, it has become clear that MLL is a key component of mammalian COMPASS-like complexes, which play critical roles in both embryonic

27 18 Panagiotis Ntziachristos et al. development and hematopoiesis. COMPASS complexes contain hset1a and B, MLL1, MLL2, MLL3, or MLL4 as the catalytic subunit and have a critical role in activating transcription by catalyzing mono-, di-, and trimethylation on lysine 4 of histone 3 (H3K3me1, H3K4me2, H3K4me3). WDR5, RBBP5, and ASH2L are important core subunits that modulate the action of the methyltransferase (Dou et al., 2006). What determines the catalytic specificity of the complex regarding the component constitution is still unknown as deletion of any of the four catalytic subunits leads to minimal effects in the H3K4me3 levels possibly because of redundancy. However, deletion of the core subunits brings about global loss of H3K4me3 (Lubitz, Glaser, Schaft, Stewart, & Anastassiadis, 2007; Wang, Lin, et al., 2009). In this regard, loss of MLL2 in mouse embryonic stem cells (ESCs) leads to skewed differentiation, but evidence for a connection to H3K4 methylation is weak (Lubitz et al., 2007). MLLdeficient ESCs are defective in hematopoiesis (Ernst et al., 2004), but we do not know if this holds true for MLL3, MLL4, or SET1. Some studies support the role of the recently characterized DPY-30 protein as a critical regulator of MLL function (Jiang et al., 2011), although further investigation is required MLL fusions in leukemia Leukemias harboring 11q23 translocations involving MLL have characteristic clinical and biological outcomes (Bernt & Armstrong, 2011). MLLrearranged leukemias include lymphoid, myeloid, and mixed-phenotype acute leukemias phenotypes. They are found in >70% of infants with ALL and in 35 50% of infants with AML. Children with MLL-rearranged B-ALL exhibit an overall survival of 50% versus an overall survival of >80% for children that do not harbor the translocation. MLL rearrangements with more than 60 translocation partners have been documented. These translocation partners share no single unifying feature or functional association. The resulting MLL-fusion proteins contain the amino-terminal domain of MLL and the carboxy-terminal domain of the translocation partners. As the fusion proteins no longer contain the MLL SET domain, the oncogenic action of this chimeric protein is independent of the H3K4me3 mark. The majority of the MLL-fusion partners are part of nuclear proteins (Fig. 1.2C). Members of the so-called super elongation complex (SEC) (AF1, AF9, ENL, ELL, and AF4) are frequent fusion partners. MLL can also be fused to components of the Dot1-containing complex (DotCom) (Mohan, Lin, Guest, & Shilatifard, 2010; Smith, Lin, &

28 Mechanisms of Epigenetic Regulation of Leukemia Onset and Progression 19 Shilatifard, 2011) such as ENL (Tkachuk, Kohler, & Cleary, 1992) and AF-9 and AF-4 (Gu et al., 1992)(Fig. 1.2D). DOT1L is the catalytic component of DotCom, which facilitates di- and trimethylation of lysine 79 on histone 3 (H3K79me2, H3K79me3) (Fig. 1.2C). This histone mark is associated with actively transcribed genes and is essential for transformation by MLL-AF9 (Bernt et al., 2011; Daigle et al., 2011). Interestingly, cross talk between the MLL-AF9 fusion protein and polycomb protein CBX8 was recently revealed in leukemia. The essential role of CBX8 in MLL-AF9-driven leukemia shows that the relationship between trithorax and polycomb group proteins is not yet fully understood (Tan, Jones, et al., 2011). 4. OTHER EPIGENETIC WRITERS, ERASERS, AND READERS Apart from enzymes that directly add or remove epigenetic marks (writers/erasers), there are proteins that can read these marks. These readers can recruit other proteins that can propagate the signal and subsequent repress or activate target genes or bear themselves catalytic activity. Here, we discuss genetic and posttranslational perturbation of writers, erasers, and readers and drugs that are used against these proteins in preclinical and clinical settings in leukemia studies (Fig. 1.3A) Arginine methyltransferases The role of arginine methyltransferases and demethylases in tumorigenesis is poorly understood and is briefly discussed here. One methyltransferase, PRMT5, is of particular interest as this protein has been implicated in myeloproliferative neoplasms (Wysocka, Allis, & Coonrod, 2006; Zhang & Abdel-Wahab, 2012). It was shown that PRMT5 is aberrantly phosphorylated by mutant JAK2 (V617F, with increased activity) leading to decreased methylation of histones H2A and H4 and alterations in gene expression (Liu et al., 2011). Importantly, a specific inhibitor of the mutant JAK2 (Ruxolitinib) is used against MF. Inversely, the action of CCND1/CDK4 can lead to increased PRMT5 enzymatic activity in mouse lymphomas (Aggarwal et al., 2010). A putative role for PRMTs in cancers is further suggested by the fact that expression levels of both PRMT1 and 6 have been found to be elevated in different types of cancer (Yoshimatsu et al., 2011).

29 20 Panagiotis Ntziachristos et al. A KMTi PRC2 Set HATi HATs DNMT DNMTi vidaza decitabine CpG Sirtuins HDACs KDM KDMi SIRTi HDACi vorinostat romidepsin PRMT5 JAK2 (V617F) JAKi Ruxolitinib B Monoclonal antibodies EGFR Cell membrane Lysine methylation Lysine acetylation BCR-ABL Inhibitors of signal transduction Nuclear envelope Arginine methylation Epigenetic inhibitors Alkylating agents phosphorylation DNMT CpG CpG CpG Cisplatin Figure 1.3 Major epigenetic modifiers that are genetically affected in leukemia, their associated marks and the corresponding inhibitors. (A) Major epigenetic modifiers with the corresponding inhibitors (marked with the letter i). Inhibitors that are being used for the treatment of hematopoietic malignancies are shown in red. HDAC (vorinostat and romidepsin) and DNMT inhibitors vidaza (5-azacytidine) and decitabine (5-aza-2- deoxycytidine) are currently used against MDS and CTCL correspondingly. Ruxolitinib is a JAK2 inhibitor used against myelofibrosis. HAT inhibitors, such as curcumin, have

30 Mechanisms of Epigenetic Regulation of Leukemia Onset and Progression Lysine demethylases (KDMs) Lysine demethylases are very important for homeostasis and cancer. There are two major families of lysine demethylases. One consists of the amine oxidases and the second of the dioxygenases. Amine oxidation by the LSD family of flavin adenine dinucleotide-dependent demethylases (Shi et al., 2004) represents a type of active demethylation reaction. KDM1A (LSD1), the first reported histone demethylase (Shi et al., 2004), catalyzes demethylation of H3K4me1 and H3K4me2 and can also demethylate H3K9me1 and H3K9me2. KDM1A has also been shown to catalyze the demethylation of nonhistone targets, such as p53 (Huang et al., 2007) as well as DNMT1 and E2F1 (Wang, Hevi, et al., 2009; Xie et al., 2011). A second type of demethylation reaction is hydroxylation by JmjC-domain-containing proteins (Kooistra & Helin, 2012; Tsukada et al., 2006; Yamane et al., 2006). This broad family contains proteins, which catalyze demethylation of different histone and nonhistone substrates. Jumonji (Jarid2), the founding member of this family, lacks catalytic activity but plays important roles in pluripotency and development by modulating the PRC2 complex activity. JMJD3 or KDM6B, an H3K27me3 demethylase, has been reported to facilitate transcriptional initiation and elongation (Chen et al., 2012). UTX (KDM6A) and JMJD3 interact with the chromatin remodeling complex SWI/SNF (Miller, Mohn, & Weinmann, 2010), as well as MLL complexes, showing the diversity of interactions and actions of the group. The role of lysine demethylases in tumorigenesis has been exemplified by KDM1A and KDM2B (FBXL10) (Harris et al., 2012; He, Nguyen, & Zhang, 2011; Schenk et al., 2012). In addition, mutations in the lysine demethylase UTX, which can remove the H3K27me3 mark, have been found in human cancers (van Haaften et al., 2009). A recent study focusing specifically on ALL reported a low frequency of UTX mutations (Mar et al., 2012). Most of these mutations were found in clinically defined high-risk patients suggesting possible future therapeutic or prognostic relevance (Mar et al., 2012). been used in clinical trials against leukemia and other hematopoietic malignancies. Other inhibitors used in the lab include histone (lysine), methyltransferase (KMTi) and demethylase (KDMi) inhibitors, and sirtuins inhibitors (SIRTi). (B) Recently, different combinations of different epigenetic inhibitors, as well as combinations of epigenetic inhibitors with drugs inhibiting signaling transduction pathways, or chemotherapy (such as alkylating agents) are being used in clinical trials.

31 22 Panagiotis Ntziachristos et al Histone demethylases inhibitors (KDMi) The inhibition of histone demethylases as anticancer treatment has great potential. However, so far, the use of these inhibitors has been restricted to preclinical studies. For example, recently, it was shown that tranylcypromine (TCP, a LSD1 inhibitor) has activity against myeloid leukemia cell lines that are driven by the MLL-AF9 oncogene (Harris et al., 2012). So far, it has been reported that only acute promyelocytic leukemia (a subtype of AML) is sensitive to all-trans retinoic acid (ATRA) treatment. However more recently, in vitro combinatorial use of ATRA and TCP yielded promising results for other types of AML as well (Schenk et al., 2012). This further underlines the importance of combinatorial use of drugs in treatment of leukemia (Fig. 1.3B). Moreover, it is very encouraging that the advent of new technologies including high-throughput screens and advanced crystallographic techniques are paving the way to specific drugs, which target structurally similar molecules that fulfill different functions in the cell. A recent example is the generation of the first specific inhibitor for the H3K27me3 demethylases (Kruidenier et al., 2012), which can allow selective pharmacological intervention across the Jumonji family Histone acetyl transferases The family of histone acetyl transferases (HATs) consists of epigenetic modifiers that include CREB-binding protein (CBP), GCN5, and CLOCK. Mutations that inactivate the action of CBP were recently identified in ALL (Mullighan et al., 2011) and in B-cell lymphoma (Pasqualucci et al., 2011). The MOZ (monocytic leukemia zinc-finger protein) and MORF (MOZ-related factor) HATs are important for different developmental programs and have been implicated in leukemogenesis and other tumorigenic processes. In AML, the MOZ gene on chromosome 8p11 is fused to the CBP gene on 16p13, producing a transcript encoding the fusion protein MOZ-CBP (Borrow et al., 1996). Interestingly, the MORF gene has been identified (Champagne et al., 1999) fused to CBP in AML or MDS (Kojima et al., 2003; Yang & Ullah, 2007) HAT inhibitors Three HAT inhibitors (HATi) have been described to date. Curcumin (Shehzad, Wahid, & Lee, 2010) is broad acting inhibitor that also targets p300/cbp. Garcinol (Balasubramanyam et al., 2004) and anacardic acid

32 Mechanisms of Epigenetic Regulation of Leukemia Onset and Progression 23 (Sun, Jiang, Chen, & Price, 2006) are both p300 and KAT2B inhibitors. These three inhibitors are currently in preclinical development Histone deacetylases HDACis typically play a repressive role in transcription as they remove the activating acetylation marks from gene control elements. However, HDACs have also been detected at the promoters of transcribed genes (Wang, Zang, et al., 2009). There are four classes of HDACs and three of them depend on the substrate-zn chelation in their active site. Sirtuins (Type III HDACs) are the exception to this rule as they depend on NAD þ for their action. No genetic perturbations affecting HDACs have been described in leukemia to date. However, differential expression of the HDACs has been associated with other types of cancer. In the absence of retinoic acid, RARa plays a suppressive role in transcription through the recruitment of corepressors such as NcoR, SMRT, Sin3a, and HDACs. The PML-RARa fusion protein is a stronger repressor than endogenous RARa (Uribesalgo & Di Croce, 2011), thereby warranting the use of HDACis in this scenario HDAC inhibitors HDACis can be chemically classified as short-chain fatty acids, hydroxamic acids, cyclic peptides, and benzamide derivatives (Masetti, Serravalle, Biagi, & Pession, 2011). HDAC inhibition can lead to different outcomes, such as cell cycle arrest, differentiation, or apoptosis. The most widely used class of HDACis is the hydroxamic acids, which include trichostatin A and vorinostat (SAHA). SAHA has been approved for the treatment of several hematological malignancies, including cutaneous T-cell lymphoma (CTCL). Another hydroxamic acid, Panobinostat, is currently being subjected to trials in CML, refractory CTCL, and MMs (Wolf et al., 2012). Belinostat is another investigational HDACi and has demonstrated encouraging results in peripheral T-cell lymphoma (Copeland, Buglio, & Younes, 2010). In addition, romidepsin is a cyclic peptide (FK228) approved for CTCL. Benzamide derivatives (MGCD-0103) are a separate class of investigational drugs, in clinical development for the treatment of hematological malignancies and solid tumors. Sirtuin inhibitors have not been comprehensively studied to date. Cambinol, a sirtuin inhibitor that is structurally unrelated to other HDACi, has been shown to lead to apoptosis in BCL6-expressing Burkitt s lymphoma cells through inhibition of SIRT1 and SIRT2 (Heltweg et al., 2006). Overall, this is a very big family of inhibitors, having two members FDA approved for CTCL treatment.

33 24 Panagiotis Ntziachristos et al Bromodomain-containing proteins Another family of histone readers is the bromodomain (BRD)-containing protein family. The BRD recognizes acetylated residues and comprises a highly conserved, four-helix, left-twisted bundle with a characteristic hydrophobic cleft between two conserved loops. The BRD is present in the bromodomain and extra-terminal (BET) proteins as well as in members of the chromatin remodeling complexes (Snf2), the MLL complex and members of the SEC (Belkina & Denis, 2012). Recently, BET domain-containing proteins have been found to play a key role in the development of MM (Delmore et al., 2011) mainly through the induction of the c-myc gene. Another example is MLL-fusion proteins containing components of the SEC, including PAFc and ptefb that contain BET proteins (Dawson et al., 2011). These MLL-fusion proteins can activate transcription of potent oncogenes, such as BCL2, MYC, and CDK BRD inhibitors Recently, James Bradner and his group modified a thienodiazepine molecule so that it inhibited the binding of BRD4 to the acetylated residues of histone H4 (Filippakopoulos et al., 2010). This so-called JQ1 inhibitor abruptly inhibits MYC expression and the MYC-associated transcriptional signatures in MM. In MLL-fusion leukemias (Dawson et al., 2011; Delmore et al., 2011; Filippakopoulos et al., 2010), inhibition of the BET proteins with a specific inhibitor (GSK A (I-BET151)) lead to displacement of BRD3/4 and components of the SEC from chromatin improving the survival in mouse models of MLL-rearranged leukemia (Dawson et al., 2011). While BET proteins are involved in broad cellular processes, these two examples show that their inhibition may actually be feasible as a potential cancer therapy Plant homeodomain-containing proteins The plant homeodomain (PHD) recognizes the various methylation states of lysine 4 residue on histone 3 (H3K4). In addition, affinity of the PHD for H3K9me3 has also been documented in the case of JARID1C (Iwase et al., 2007). JARID1C is a histone demethylase for H3K4me3, which suggests cross talk between different histone marks. Translocation of PHD-containing proteins is highly prevalent in hematopoietic malignancies (Chi, Allis, & Wang, 2010). Specifically, the PHD of

34 Mechanisms of Epigenetic Regulation of Leukemia Onset and Progression 25 PHF23 and KDM5A that recognizes H3K4me3/2 has been found to be fused to the Nucleoporin 98 (NUP98) gene. NUP98 is a nuclear pore complex component. The NUP98 chimeric protein leads to aberrant transcriptional activation. The resulting fusion protein inhibits the removal of H3K4me3 and the repressive action of EZH2 complex (Wang, Song, et al., 2009) Chromatin remodeling complexes Intriguingly, no mutations in chromatin remodeling complexes, such as the BRG family, have been identified to date in hematopoietic malignancies (Wilson & Roberts, 2011). This probably suggests that this family has key roles in cellular physiology and mutations, even heterozygote ones, could affect key cellular processes. 5. NOVEL ASPECTS AND TECHNOLOGIES IN EPIGENETICS: IMPLICATIONS FOR LEUKEMIA 5.1. Combinatorial epigenetic marks Recent progress suggests that the histone marks do not act alone but in highly concerted combinations. The first example came from studies on ESCs, where the so-called bivalent domains (Bernstein et al., 2006) consist of the activating mark H3K4me3 and the repressive mark H3K27me3. Genes that display these marks are poised for activation or repression and their levels of transcription are fine-tuned by the relative levels of the two marks or by other stimuli. During differentiation, these genes are either up- or downregulated leading to the subsequent removal of the respective mark. Another example of combinatorial histone marks can be found on active genes. These genes can display the simultaneous presence of both H3K4me3 and the elongating mark H3K36me3 (Guenther, Levine, Boyer, Jaenisch, & Young, 2007). There are several other paradigms of cross talk between epigenetic marks (Zhou et al., 2011). In addition, these marks can occur both on histone tails and the DNA itself. For example, H3K4me3 is typically associated with low levels of DNA methylation (Meissner et al., 2008; Weber et al., 2007). It is not surprising that cancer cells have aberrations in their combinatorial histone marks. For example, Fraga et al. (2005) have reported that loss of acetylation at Lys16 and trimethylation at Lys20 of histone H4 is a common hallmark of human cancer. Strikingly, this loss of histone acetylation leads to

35 26 Panagiotis Ntziachristos et al. a following loss of DNA methylation. This implies that physiological and cancer histone marks must be interpreted in a combinatorial mode. One of the challenges has been to define how combinations of epigenetic marks reflect different chromatin states. One method to establish this is by studying the genome-wide localization of epigenetic marks. This has been done, for example, in human cancer cell lines (Ernst et al., 2011), D. melanogaster (Filion et al., 2010), and mammals (Ram et al., 2011). A recent study generated by Bernstein and colleagues described the binding of multiple chromatin modulators and transcription factors in a myeloid cell line and in ESCs. Analysis of the results revealed six classes of chromatin modules. These chromatin modules are characterized by different combinations of chromatin regulators. This study showed that although chromatin regulators might reside at different loci in the genome of different cell types, they do act on these loci in similar fashion (Ram et al., 2011). The findings described above provide us with the tools to understand how mutations of epigenetic regulators in cancer could affect combinatorial chromatin modules. For instance, there is the fact that a lot of these factors interact with each other (such as EZH2 and DNMT (Vire et al., 2006), UTX and MLL (Issaeva et al., 2007; Lee et al., 2007)). Different models have been used to describe the functional outcome of various epigenetic states (Ernst & Kellis, 2010; Hon, Hawkins, & Ren, 2009) Novel aspects of regulation and epigenetic factors in cancer Recently, a novel class of RNAs, termed long noncoding RNAs (lncrnas) was discovered. Strikingly, specific lncrnas, such as HOTAIR, have also been found to promote cancer metastasis. The effect of HOTAIR has been reported to be through interaction with the PRC2 complex (Gupta et al., 2010). Another study by the same group showed that HOTAIR could actually interact with both PRC2 and LSD1 complexes bridging by this way H3K27 methylation with H3K4me3 demethylation leading to gene repression (Tsai et al., 2010). Another lncrna, HOTTIP, has been found to mediate activation of the distal HOXA genes through recruitment of and MLL-containing methyltransferase complex (Wang et al., 2011). Moreover, a number of studies displayed the importance of chromosomal interactions and the integrity of the nuclear architecture in cancer. For example, Roix, McQueen, Munson, Parada, and Misteli (2003) demonstrated that there is a correlation between the spatial proximity of two loci in normal cell development and the likelihood of translocation during

36 Mechanisms of Epigenetic Regulation of Leukemia Onset and Progression 27 carcinogenesis. Specifically, in physiological circumstances, the MYC gene resides in close proximity to the IGH and IGL loci. These are the exact translocation partners for Myc as found in leukemia (Chiarle et al., 2011; Klein et al., 2011). Lieberman-Aiden et al. (2009) capitalized on techniques such as HiC to map the landscape of inter- and intrachromosomal associations in myeloid leukemia and lymphoblastoid cell lines. This paved the way for new studies that assayed the differences in interchromosomal associations, the translocation landscape, and the transcriptome between normal and cancer cells. A comprehensive study by Zhang, McCord, et al. (2012) evaluated the genome-wide correlation between translocations and chromosomal interactions. This study provided further evidence for the fact that spatial proximity is positively correlated with the potential to generate chromosomal translocations. In addition, a recent study by Hakim et al. (2012) correlated the action of AID, an enzyme that causes breaks to DNA, to the presence of translocations. This study showed that stimuli, such as DNA damage, can also affect the frequency of translocations. The importance of nuclear architecture in the process of tumorigenicity is further underscored by the fact that lamin, a protein important for the maintenance of nuclear architecture, is also strongly associated with epigenetic regulation. Moreover, DNA methylation studies in prostate cancer showed that lamin-associated areas exhibit local hypermethylation (Berman et al., 2012). A recent study showed the extent of associations resulting from RNA polymerase activity in cancer cell lines, and the association between the respective loci and various disease states (Li et al., 2012). Taken together, it has become clear that in order to understand cancer we will have to look at the full picture. This includes mutations, epigenetic changes, transcriptional changes, and possibly larger order chromatin interactions. Nowadays, there is no reliable epigenetic marker that can be used as a prognostic or diagnostic marker for leukemia. DNA methylation, particularly of CpG islands of DNA repair enzymes, has been shown a potential to be a useful prognostic marker in some types of cancer (Van Neste et al., 2012), but there is a long way to go before this becomes an established practice. Overview of the cancer s full properties will allow us to better estimate its potential. Ultimately, this leads to a better prognosis estimate and potentially it will allow for prediction of treatment outcome. ACKNOWLEDGMENTS We thank the members of the Aifantis laboratory for critical reading of the chapter and useful comments on the work. I. A. is a Howard Hughes Medical Institute (HHMI) Early Career

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48 CHAPTER TWO Translocations in Normal B Cells and Cancers: Insights from New Technical Approaches Roberto Chiarle*,,1 *Department of Pathology, Children s Hospital Boston and Harvard Medical School, Boston, Massachusetts, USA Department of Molecular Biotechnology and Health Sciences, University of Torino, Italy 1 Corresponding author: address: roberto.chiarle@childrens.harvard.edu Contents 1. Mechanistic Elements that Generate Chromosomal Translocations DNA DSB formation DNA-repair mechanisms involved in translocations Chromosome territories and gene proximity in translocations Spatial organization of the genome: Implications for translocations Novel High-Throughput Methods to Study Chromosomal Translocations High-throughput genomic translocation sequencing Translocation-capture sequencing New Findings on Translocation Formation Obtained by HTGTS and TC-Seq RAG1/2 translocation hotspots in pro-b lymphocytes AID hotspots in activated B lymphocytes Gene density, transcription, and translocations Role of nuclear positioning and chromosomal structure in translocations Landscape of Translocations in Cancers Distribution of chromosomal translocations in cancers Chromothripsis in cancer genomes Repetitive patterns and heterogeneity of translocations involving oncogenes Perspectives 63 Acknowledgments 64 References 64 Abstract Chromosomal translocations are recurrent genetic events that define many types of cancers. Since their first description several decades ago as defining elements in cancer cells, our understanding of the mechanisms that determine their formation as well as their implications for cancer progression and therapy has remarkably progressed. Chromosomal translocations originate from double-strand breaks (DSBs) that are brought into proximity in the nuclear space and joined inappropriately by DNA-repair pathways. Advances in Immunology, Volume 117 ISSN # 2013 Elsevier Inc. All rights reserved. 39

49 40 Roberto Chiarle The frequency and pattern of translocations are influenced by perturbations of any of these events. DSB formation is heavily determined by physiologic processes, such as the activity of RAG1/2 and AID enzymes during B-cell development or maturation, or by pathologic factors, such as ionizing radiations, ROS, or fragile sites. Cellular processes of mrna transcription, DNA replication, and repair can influence the chromosomal territories and modify the relative position and proximity of genes inside the nucleus. DNArepair factors contribute not only to the maintenance of genome integrity but also to translocations in normal and cancer cells. Next-generation sequencing techniques provide an unprecedented and powerful tool to approach the field of chromosomal translocations. Using specific examples, we will explain how genome-wide translocation mapping methods, such as high-throughput genomic translocation sequencing (HTGTS) and translocation-capture sequencing, combined with large-scale methods to determine nuclear proximity of genes or chromosome domains, such as 4C and Hi-C, have changed our view of the factors and the rules governing translocation formation in noncancer cells. Finally, we will review chromosomal rearrangements and newly described findings, such as chromothripsis, in cancer cells based on these novel rules on translocation formation. 1. MECHANISTIC ELEMENTS THAT GENERATE CHROMOSOMAL TRANSLOCATIONS Chromosomal translocations require a series of consecutive events for their formation (Fig. 2.1). The first event is the generation of at least a pair of DNA double-strand breaks (DSBs). Then, two DSBs need to find themselves within close enough proximity for the DNA-repair machinery to join them. When appropriate, the ligation of two DSBs restores DNA integrity, whereas illegitimate joining results in a chromosomal rearrangement. Various types of structural chromosomal rearrangements can be generated, including inversions, deletions, and intrachromosomal or interchromosomal translocations. Here, we will quickly review these types of events DNA DSB formation The generation of DSBs in a cell can result from physiologic or pathologic mechanisms. Physiologic mechanisms may be defined as those in which programmed DSBs are introduced within a restricted window during the development and maturation of B and T cells by specific enzymes, including recombination-activating genes (RAG) 1 and 2 and activation-induced cytidine deaminase (AID). In contrast, pathologic DSBs are generated by external agents, intracellular biochemical agents, or failure of the DNA replication machinery.

50 Translocation in Normal and Cancer Cells 41 Pathologic DNA double strand breaks (DSBs) ROS Ionizing radiations Stalled replication forks Common fragile sites and ERFSs Oncogene-induced replication breaks Topoisomerases DNA damage in micronuclei Off-target activity of RAG1/2 Off-target activity of AID Physiologic DNA double strand breaks (DSBs) RAG1/2 induced V(D)J recombination AID induced CSR and SHM DSB DSB Legitimate DNA repair C-NHEJ (all cell cycle) HR (S/G2 phases) FoSTeS (collapsed replication fork) MMBIR (collapsed replication fork) Illegitimate DNA repair C-NHEJ A-EJ FoSTeS MMBIR DNA integrity Translocations Duplications Chromothripsis Figure 2.1 Mechanisms of chromosomal translocation formation. Chromosomal translocations are initiated by double-strand breaks (DSBs) formation. DSBs can be programmed by physiologic events, or generated by pathologic processes. Once formed, two DSBs are in large majority correctly repaired to restore chromosome integrity. Less frequently, an erroneous joining of DSBs originates chromosomal translocations Physiologic breaks induced by RAG1/2 and AID enzymatic activity RAG-initiated DSBs and translocations The process of V(D)J recombination during B- and T-cell development is initiated by the activity of the RAG1 and RAG2 proteins (reviewed in Jung, Giallourakis, Mostoslavsky, & Alt, 2006). The IgH variable (V H ), diversity (D), and joining ( J H ) gene segments are assembled into the IgH variable region exons in a process that starts with RAG1 and RAG2 introducing DSBs at their borders. RAG1 and RAG2 form a complex that is absolutely required for V(D)J recombination. The RAG complex recognizes recombination signal sequences (RSSs) that flank V, D, and J segments and contain nonamers and heptamers flanked separately by 12- or 23-bp spacers (according to the so-called 12/23 rule). The RAG complex generates DSBs from a pair of RSS ends in the form of blunt 5 0 -phosphorylated DSBs and

51 42 Roberto Chiarle hairpin-sealed coding ends (Honjo, Alt, & Neuberger, 2004). The 12/23 rule and additional beyond 12/23 restrictions (Gostissa, Alt, & Chiarle, 2011) target RAG complex activity to defined segments in the IgH and TCR loci and limit its off-target activity in other sites in the genome. The mechanisms by which RAG activity is targeted to the correct loci have been partially elucidated. The binding of RAG1 and RAG2 proteins to target V(D)J sequences in the Ig and T-cell receptor (TCR) genes requires the precise orchestration of protein DNA complexes to narrow the possibility of off-target effects (Schatz & Swanson, 2011). RAG proteins bind DNA in a very focal pattern, in particular, within small regions of chromatin in the Igk and TCRa J-gene segments as well as the IgH and TCRb J-gene and J-proximal D-gene segments. These small regions, called recombination centers, involve multiple proteins in addition to RAG, such as the high-mobility-group proteins HMGB1 or HMGB2 (Swanson, 2004), and depend on canonical RSSs for access to RAG binding. RSSs accessibility depends on chromatin conformation that, in turn, is controlled by enhancers and active promoters in the region. These modifications depend on enzymes that modify and remodel chromatin structure and promote transcription by allowing for Pol II binding, thus revealing an essential role for chromatin in RAG activity and specificity (Krangel, 2007). In this context, RAG1 binds directly to RSSs via domains that directly interact with the nonamers and heptamers of the RSSs (Swanson, 2004). In contrast, RAG2 has limited capability for DNA binding and instead binds to histone H3 trimethylated at lysine 4 (H3K4me3), a marker of active and poised promoters (Liu, Subrahmanyam, Chakraborty, Sen, & Desiderio, 2007; Matthews et al., 2007). Accordingly, in vivo RAG1 binding sites were found preferentially in regions containing RSSs, whereas bound RAG2 was found within thousands of H3K4me3-enriched sites across the genome (Ji et al., 2010). The mechanisms that regulate RAG DNA binding and cleavage are exquisitely important for restricting the generation of RAG-mediated DSBs to their proper sites. Failure of this regulation, or off-target activity, results in the generation of DSBs that could be improperly repaired and could lead to the formation of chromosomal translocations. Indeed, off-target RAG activity is responsible for low-frequency DSBs that are observed throughout the genome, and the misrepair of DSBs at the Ig and TCR loci causes genomic instability and translocations in lymphoid cells (Lieber, Yu, & Raghavan, 2006; Mills, Ferguson, & Alt, 2003). Aberrant RAG activity has been implicated in the development of human malignancies (Tsai et al., 2008), whereas RAG2 integrity is essential to maintain genomic stability and prevent

52 Translocation in Normal and Cancer Cells 43 complex chromosomal translocations, amplifications, and deletions in the TCR and IgH loci (Deriano et al., 2011). Translocations found in B- or T-cell acute lymphoblastic leukemia (B-ALL or T-ALL, respectively), in mouse models of these diseases (Gladdy et al., 2003; Zha et al., 2010; Zhu et al., 2002) and in humans (Küppers, 2005), are thought to be initiated by RAG activity. Other examples of RAG-mediated translocations are the recurrent translocations observed in B-cell lymphomas, such as (1) the t(8;14) translocations that involve IgH and c-myc in endemic Burkitt s lymphoma (BL); (2) the t(11;14) translocations found in mantle cell lymphomas (MCL) involving IgH and the bcl-1 loci; (3) the t(14;18) translocation in follicular lymphoma (FL) that translocates IgH and bcl-2; and (4) the t(1;14) translocation in mucosa-associated lymphoid tissue (MALT) lymphomas that involves IgH and bcl-10 (Küppers & Dalla-Favera, 2001) AID-initiated DSBs and translocations AID is a B-cell-specific enzyme required for class switch recombination (CSR) as well as somatic hypermutation (SHM). It is mostly expressed by IgM-positive naïve B cells upon antigen stimulation, typically in the germinal center (GC) and to a lesser extent in the extrafollicular areas of secondary lymphoid organs, such as the spleen and lymph nodes. AID-mediated CSR generates DSBs in the IgH C H locus that are frequently involved in translocations, whereas SHM very rarely leads to DSB formation and translocation (Pasqualucci et al., 2001). AID is a single-strand (ss)-specific DNA cytidine deaminase that targets repetitive GC-rich sequences within CSR switch regions and catalyzes dc-to-du deamination. The presence of GC-rich sequences induces the formation of stable RNA:DNA complexes, resulting in displacement of the nontemplate strand as ssdna (R-loops). AID targets R-loops in the nontemplate strand, whereas its access to the template strand depends on the RNA exosome, a cellular RNA-processing/ degradation complex (Basu et al., 2011). Transcription of mrna is necessary for AID activity, as demonstrated by studies showing that AID is directed to DNA sites where RNA polymerase II (Pol II) activity is stalled (as a result of its association with Spt5; Pavri et al., 2010). This relationship between AID, mrna transcription, and Pol II stalling has likely implications for the mechanisms of AID-initiated translocations. AID expression, nuclear localization, and activity are finely regulated in B cells to limit its genotoxic effects. Indeed, AID expression is transient in B cells, owing to tight transcriptional control of the promoter as well as by

53 44 Roberto Chiarle mir-155 (Teng et al., 2008), as a mutation in the mir-155 binding site in the AID 3 0 -UTR has been shown to increase cellular AID levels and, consequently, the frequency of IgH-myc translocations (Dorsett et al., 2008). The protein levels of AID are also tightly regulated. After induction, AID is quickly degraded (Basu, Franklin, & Alt, 2009), with the majority of AID being retained in the cytoplasm and only a small amount entering the nucleus, and its enzymatic activity being controlled by protein kinase-a-mediated phosphorylation (Basu et al., 2005). AID off-target activity outside the IgH locus has been implicated in chromosomal translocations not only in B cells but also in nonlymphoid cells. Indeed, signs of AID off-target activity, in the form of SHM, have been found in up to 25% of the expressed genes analyzed in GC B cells (Liu et al., 2008), and AID is required for DSBs generated in the c-myc locus (Robbiani et al., 2008; Wang et al., 2009). In agreement with these findings, ectopic expression of AID in mice induces DSBs and tumor formation in B- and non-b cells (Okazaki, Kotani, & Honjo, 2007; Robbiani et al., 2009). In human tumors, AID is thought to initiate DSBs when translocations involve the IgH switch regions. Typical examples of such translocations are: (1) IgH and c-myc in sporadic BL, t(8;14); (2) IgH and Bcl-3 in chronic lymphocytic leukemia (CLL), t(14;19); (3) IgH and Bcl-6 in diffuse, large B-cell lymphoma (DLBCL), t(3;14); (4) IgH and Pax5 in lymphoplasmacytic (LP) lymphoma, t(9;14); and (5) the t(4;14), t(14;16), and t(6;14) translocations that recur in multiple myeloma (MM) (Küppers & Dalla-Favera, 2001; Mitelman, Johansson, & Mertens, 2007). In some translocations, such as the t(14;18) found in FL and the t(11;14) in MCL, it is thought that RAG and AID activity might collaborate in the generation of DSBs at the Bcl-2 and Bcl-1 loci (Tsai et al., 2008). In non-b cells, AID expression has been found in gastric (Matsumoto et al., 2007), liver, and colorectal tumors (Marusawa, 2008), and a role has also been suggested in germ cell tumors (Okazaki et al., 2007), breast cancer (Pauklin, Sernández, Bachmann, Ramiro, & Petersen-Mahrt, 2009), and prostate cancer (Lin et al., 2009) Pathologic induction of DSBs in normal and tumor cells Nonprogrammed pathologic DSBs can originate in G1-arrested or cycling cells by a variety of mechanisms resulting from (1) exposure to physical agents, such as ionizing radiations; or (2) the malfunctioning of cellular biochemical processes, such as the production of reactive oxygen species (ROS) or breaks in fragile sites during impaired replication. Ionizing (g ) radiation

54 Translocation in Normal and Cancer Cells 45 can directly induce DSBs in DNA in a dose-dependent manner (Lieber, 2010; Tsai & Lieber, 2010). Oxidative stress generates ROS that can react with DNA and induce DSB formation by triggering the induction of two neighboring SSBs (Kryston, Georgiev, Pissis, & Georgakilas, 2011). Fragile sites are regions of DNA that can generate DSBs when DNA synthesis is partially inhibited (Durkin & Glover, 2007). Some fragile sites are common to all cells. In cancer cells, they are implicated in DNA damage associated with replication stress and were shown to be involved in constitutional and cancer rearrangements in vivo (Arlt, Durkin, Ragland, & Glover, 2006). As examples, the FRA6E and FRA6F fragile sites are associated with break points in ALL and acute myelogenous leukemia (AML) (Sinclair, Harrison, Jarosová, & Foroni, 2005), and some BL show c-myc translocations close to the FRA8C and FRA8D fragile sites (Sinclair et al., 2005). Interestingly, oncogene-induced replication stress can induce the collapse of stalling replication forks and DSB formation at fragile sites (Halazonetis, Gorgoulis, & Bartek, 2008). Early replication fragile sites (ERFSs) have been recently described to form during cell cycle progression and DNA replication. ERFSs colocalize with highly expressed gene clusters in B lymphocytes subjected to replication stress (Barlow et al., 2013). DSBs in ERFSs are relevant, since greater than 50% of recurrent amplifications/deletions in human diffuse large B cell lymphoma map to ERFSs (Barlow et al., 2013). Finally, topoisomerases can induce DSBs. For example, in prostate cancer, topoisomerase IIb has been shown to induce DSB formation that results in the hallmark TMPRSS2-ERG translocation (Haffner et al., 2010). Notably, this DSB activity has been observed during topoisomerase inhibition by anticancer drugs (Felix et al., 2006) DNA-repair mechanisms involved in translocations In response to DSB generation, cells activate an intrinsic DNA-damageresponse (DDR) pathway to resolve DSBs and facilitate DNA repair. Notable molecular players within the DDR include ATM, the RAD50/MRE11/ NBS1 complex, H2AX, and 53BP1 (for a detailed review, see Lieber, 2010; Alt et al., 2013; Gostissa et al., 2011). The two major DDR pathways typically operate depending on the sequence homology of the DSB and division state of the cell. In dividing diploid cells, sequence homology is used by the homologous recombination (HR) pathway or by the single-strand annealing and breakage-induced replication pathways (San Filippo, Sung, & Klein, 2008). In nondividing cells, or when homology is not present, cells utilize a form of direct joining called nonhomologous DNA end joining (NHEJ).

55 46 Roberto Chiarle Classical NHEJ (C-NHEJ) relies on a series of factors that participate in a multistep DNA-repair process. First, Ku proteins (Ku70/86) bind to the DSB to generate a Ku DNA complex. The Ku DNA complex serves as a docking point for other DNA-repair complexes, such as the nuclease complex formed by Artemis and DNA-PKs, the DNA polymerases Pol l and m, and the ligase complex composed of XLF, XRCC4, and DNA Ligase IV (for a detailed description of these factors, see Lieber, 2010 and Gostissa et al., 2011). The recruitment and activity of these higher-order complexes result in the direct joining of DNA or minimal (2 3 base) microhomology (MH) of the ends. C-NHEJ is considered to be a highly efficient method to rapidly repair DSBs and restore chromosomal and genomic integrity. In particular, it is used to repair physiologic DSBs introduced by RAG1/2 during V(D)J recombination (see above) and most DSBs introduced by AID during CSR (Gostissa et al., 2011). Also, it shows a predisposition toward repairing DSBs on the same chromosome (Ferguson et al., 2000). When one essential core factor (e.g., Ku or Ligase IV) of the C-NHEJ pathway is missing, such as in knock-out mouse models or in human patients with specific genetic defects, cells can still join nonhomologous DNA ends by one or more mechanisms known collectively as the alternative end-joining (A-EJ) pathway. Many factors have been implicated in A-EJ, among them Nbs1, Mre11, CtlP, DNA Lig3, Parp1, and XRCC1, but their roles are still under investigation (Alt et al., 2013; Gostissa et al., 2011; Lieber, 2010). The signature function of A-EJ is to repair DSBs via short sequences of MH present at the ends of DSBs. However, MH is not absolutely required since A-EJ can also generate a substantial fraction of direct joins (Boboila et al., 2010b). A-EJ is considered to be a slower (Han & Yu, 2008)andmoretranslocation-prone pathway than C-NHEJ (Boboila et al., 2010a). The fact that translocations are also observed in normal cells indicates either that the C-NHEJ can sometimes mediate inappropriate DNA-repair responses that result in chromosomal translocation or that A-EJ might work in parallel with the C-NHEJ to repair some DSBs, possibly when the C-NHEJ is overwhelmed. In this context, I-SceI was shown to mediate translocation in WT mouse cells in which C-NHEJ and A-EJ were both intact (Gostissa et al., 2011; Klein et al., 2011; Weinstock, Elliott, & Jasin, 2006), showing a bias toward MH usage, possibly indicating a coexistence of C-NHEJ and A-EJ functions. A similar bias toward MH usage is observed in translocation junctions from cancer cells (Zhang & Rowley, 2006). The role of C-NHEJ in suppressing translocations and maintaining chromosomal integrity is exemplified by knock-out mouse models of C-NHEJ factors.

56 Translocation in Normal and Cancer Cells 47 Bcellsdeficientforvirtuallyanysingle C-NHEJ factor, such as Ku70, Ku86, XRCC4, Lig4, DNA-PKcs, Artemis, or XLF, show increases in DSB formation and translocation (Gostissa et al., 2011). When the p53-dependent G1/S checkpointwasmissing,asinap53 / background,mice deficient in Ku86, XRCC4, Lig IV or DNA-Pks, or Artemis expression as well as mice deficient in ATM developed pro-b-cell lymphomas that often carried IgH/c-myc translocations with c-myc amplifications. In Artemis-deficient mice, IgH/N-myc translocations were also observed. Medulloblastomas occurred in XLF-deficient mice and, together with lymphomas, were also found in other C-NHEJ-deficient mice (Gostissa et al., 2011). Overall, C-NHEJ maintains genome integrity and suppresses translocation formation, either by promptly repairing DSBs or by suppressing the translocation-prone repair activity of A-EJ Chromosome territories and gene proximity in translocations For a chromosomal translocation to be formed, two DSBs must be in close proximity to allow the DNA-repair pathways to join them. It is not clear, however, whether the two loci involved in a translocation should be close to each other before the DSBs are generated or whether DSBs have some mobility inside the nucleus. In classical cytogenetic studies using fluorescence in situ hybridization (FISH), the nuclear distance between c-myc and IgH, Igk, and Igl directly correlated with the respective frequency of translocations found in BL. Furthermore, in the interphase nucleus, the IgH locus was found to be proximal to some of its translocation partners found in lymphomas, such as the CCND1, Bcl-2, and Bcl-6 genes (Roix, McQueen, Munson, Parada, & Misteli, 2003). In a mouse model of lymphoma, the IgH locus was found to frequently colocalize with its translocation partners c-myc and Igl (Wang et al., 2009). This colocalization was tissue specific and limited to a relatively small portion of the chromosome, as it was lost with the chromosomal segment located at 15 Mb distance from Igl (Wang et al., 2009). Chromosomal proximity is similarly thought to influence translocation frequency in leukemias, including the ABL and BCR genes in chronic myelogenous leukemia (CML) and the promyelocytic leukemia (PML) and RARA genes in PML (Neves, Ramos, da Silva, Parreira, & Parreira, 1999), and in solid tumors such as prostate cancers, where androgen stimulation was shown to increase proximity in the frequently translocated TMPRSS2 and ERG genomic loci (Lin et al., 2009; Mani et al., 2009). However, the definition of proximity in such studies was probabilistic and quite arbitrary, as

57 48 Roberto Chiarle it was found only in a fraction of the cells examined and was established based on the limited resolution of confocal microscopes. A more precise determination of the physical contact between loci has been established by modern techniques, such as 4C and Hi-C (see Section 3.4) Spatial organization of the genome: Implications for translocations The nucleus is a highly dynamic structure where chromosomes as well as many fundamental cellular processes, including transcription, replication, and DNA repair, are organized and carried out within defined compartments (Fig. 2.2). Inside the interphase nucleus, chromosomes, smaller genomic regions, and even single genes are not randomly distributed but rather interact within highly ordered 3D structures known as chromosome territories. Chromosome territories can be directly visualized by in situ hybridization approaches, which highlight the localization of individual chromosomes in distinct patterns (Bolzer et al., 2005). The patterns of chromosome territories change with differentiation and development and are cell-type specific (Cremer et al., 2006; Misteli, 2007). The functions of chromosome territories are still unclear. Human lymphocytes show a strong correlation between the position of chromosomes and their gene density, with gene-rich chromosomes clustered toward the nuclear interior (Boyle et al., 2001). Gene-rich regions correlate with Chromosome territories Transcription factories Replication factories DNA repair centers Active A domain Inactive B domain mrna mrna RNA polymerases PCNA DNA polymerases C-NHEJ A-EJ mrna mrna Short chromosomes Long chromosomes Figure 2.2 Spatial organization of the genome. The nucleus is a highly dynamic structure. Chromosomes are organized in territories. Short chromosomes interact more frequently with each other than with long chromosomes. Within each chromosome, active A domains interact more frequently with other A domains, whereas inactive B domains are more frequently associated with B domains. Transcription factories are nuclear compartments (calculated in about 10,000 in HeLa cells) where transcription factors are recruited, assembled, and disassembled within few seconds to achieve efficient transcription of clustered genes. Replication factories and DNA repair centers are discrete compartments of the nucleus where DNA synthesis and DNA repair are achieved through the recruitment of specific factors (see text for details).

58 Translocation in Normal and Cancer Cells 49 decondensed chromatin status, whereas gene-poor regions are associated with condensed chromatin (Gilbert et al., 2004). Chromosomal territories can also be determined by the size of single chromosomes, with smaller chromosomes generally located toward the center of the nucleus (Bolzer et al., 2005). Indeed, very recent data collected with Hi-C mapping in G1-arrested pro-b cells showed that the longest chromosomes more frequently interact with each other than with smaller chromosomes (Zhang et al., 2012). The transcription of mrna by Pol II polymerases predominantly occurs in centralized structures called transcription factories (Cook, 1999). The concentration of transcription factors into these factories allows for efficient transcription, and cotranscribed genes are recruited together by modifications of chromosome structure and changes in chromatin conformation (Misteli, 2007). In this process of transcription-driven recruitment, single genes can change their positioning with respect to the nucleus. For example, in lymphocytes, activated IgH and CD4 relocalize from the periphery toward the center of the nucleus (Kosak et al., 2002; Kim et al., 2004). Similar principles of nuclear compartmentalization and dynamics also apply to replication and DNA repair. During the S phase, within the socalled replication factories, multiple factors involved in the replication machinery are rapidly assembled and disassembled within minutes to allow for efficient DNA synthesis. DNA repair occurs in repair centers where distinct foci of accumulating factors are recruited to ensure efficient repair of DSBs (Bekker-Jensen et al., 2006). Taken together, this evidence shows that the nucleus is a highly dynamic structure in which entire chromosomes, gene clusters, or even single genes can rapidly change their position inside the geometry of the nucleus or with respect to other chromosome or gene loci. Therefore, rather than assuming that the proximity between translocation-prone genes is fixed, their probability of contact appears to be somewhat fluid in a variable fraction of cells and influenced by factors such as cell-cycle phase (predominantly G1 or G1/S/G2 phases). Modern techniques for genome-wide contact analysis, such as 4C and Hi-C, have improved our understanding of chromosomal organization within the nucleus. These techniques capture the physical contact made between gene segments via the formalin-mediated cross-linking of histones that are in physical contact in the nucleus (Lieberman-Aiden et al., 2009; Simonis et al., 2006; Zhao et al., 2006). With 4C, it was found that actively transcribed loci, such as the b-globin locus, preferentially contacted other

59 50 Roberto Chiarle actively transcribed loci and that active and inactive genes are involved in long-range intra- and interchromosomal contacts (Simonis et al., 2006). Recent studies relied on Hi-C approaches to build spatial proximity maps of the human genome at 1 Mb resolution. These maps revealed that, in both cycling cells and G1-arrested cells, chromatin conformation is consistent with a fractal globule in which intrachromosomal interactions are much more frequent than interchromosomal interactions, and in each chromosome, the probability of contact was directly proportional to genomic distance (Lieberman-Aiden et al., 2009; Zhang et al., 2012). These physical data are entirely consistent with the concept of chromosome territories. Furthermore, genomic loci in A domains, characterized by their open chromatin conformation and tendency to correlate with gene-rich areas, showed higher probability of contact with other loci in A domains than with loci in the closed and transcriptionally inactive B domains, and vice versa (Lieberman-Aiden et al., 2009). These concepts that is, the clustering of genes during transcription, transcription factories, the higher probability of contact with regions of the same chromosome, and the segregation of open and closed chromatin to form two genome-wide compartments have profound implications for the interpretation of mechanistic factors that regulate translocation (Fig. 2.2). These implications will be analyzed below. 2. NOVEL HIGH-THROUGHPUT METHODS TO STUDY CHROMOSOMAL TRANSLOCATIONS To better study chromosomal translocation formation, the development of powerful detection methods in relatively simple assays in vivo is required. In the past decade, most translocation assays were performed by a direct PCR approach, a rather simple technique in which a series of primers were designed to detect translocations between two known genes, such as c-myc and the IgH locus (Ramiro et al., 2006, 2004; Wang et al., 2009), or multiple pairs of genes (Jankovic et al., 2010). Although direct PCR provides reliable quantitative measurements of translocation frequency between two loci, only defined translocations generated within a few kilobases from where primers are located can be detected, thus limiting its usefulness when translocation partners are unknown or larger regions of the genome are involved. The introduction of next-generation sequencing techniques has allowed for the development of broader, genome-wide methods to assay for chromosomal translocation formation.

60 Translocation in Normal and Cancer Cells High-throughput genomic translocation sequencing HTGTS was recently developed to clone translocation junctions from a baited DSB end (Chiarle et al., 2011). This bait was provided by DSBs generated via the homing endonuclease I-SceI that cuts a canonical recognition sequence of 18 bp (Liang, Romanienko, Weaver, Jeggo, & Jasin, 1996) targeted into the IgH or c-myc locus (Chiarle et al., 2011; Klein et al., 2011). Therefore, HTGTS isolates junctions between a chromosomal DSB introduced at a fixed site and other genic or intergenic regions in the whole genome. In this study, primary splenic B cells were isolated and activated in vitro for up to 4 days in conditions that allow for AID expression and CSR induction (Fig. 2.3). This relatively short time of activation AID-induced DSBs and translocations Mature B cells IgM + AID induction 4 days stimulation IL-4 + CD40 or LPS Translocations I-Scel-mediated DSBs DNA isolation Linker-mediated PCR Proliferation CSR to IgG1 + B cells Next-generation sequencing Translocation maps A-MuLV Pro-B cells G1 arrest RAG1/2 induction STI-571 Translocations DNA isolation Linker-mediated PCR I-Scel-mediated DSBs RAG1/2-induced DSBs and translocations Figure 2.3 Strategies to generate translocations maps from normal mature B cells and pro-b cells. Mature B cells are freshly isolated from spleens and activated to induce AID expression and class switch recombination. I-SceI-mediated DSBs are generated in the IgH and c-myc loci either by retrovirus-mediated I-SceI expression or by hormonemediated induction of I-SceI glucocorticoid receptor (GR) fusion. After 4 days, cells are collected and translocations junctions are cloned as described in the text. For pro-b cells, A-MuLV transformants are generated by Bcr-Abl transduction. In the presence of Bcl2 overexpression, the inhibition of Bcr-Abl tyrosine kinase activity by STI-571 induces G1 cell-cycle arrest and RAG1/2 induction. DSBs are generated by I-SceI GR fusion activation and translocations junctions are cloned as for mature B cells.

61 52 Roberto Chiarle minimized cellular selection and avoided biases related to the biological consequences of translocations on cell growth and survival. To clone translocation junctions, genomic DNA was digested into relatively small fragments by restriction enzymes and ligated to an adapter or, alternatively, to generate circular fragments. Up to three rounds of nested PCRs were performed with adapter- and locus-specific primers, and pooled PCR products were then sequenced by 454 sequencing and aligned to a reference genome after several steps of filtering to eliminate nonspecific products and artifacts. The method proved to be highly specific, with artificial nonspecific junctions being lower than 1% of detected sequences. By this method, almost 150,000 independent junctions from independent mice and libraries were generated. All sequences contained the translocation junction, thus allowing for MH studies (Chiarle et al., 2011) Translocation-capture sequencing Translocation-capture sequencing (TC-Seq) was developed in parallel with HTGTS based on similar principles (Klein et al., 2011; Oliveira et al., 2012). Fixed DSBs were generated in activated B cells in the c-myc locus targeted with the I-SceI recognition sequence. Translocations to I-SceI-c-myc were cloned with an adapter-based PCR approach. Genomic DNA was fragmented by sonication, blunted, ligated to double-stranded asymmetric linkers, and cut with I-SceI to eliminate native nontranslocated loci. Next, two rounds of seminested PCR were performed and the fragments assembled into a paired-end Illumina library. By this method, over 160,000 translocations were obtained from WT and AID-deficient B cells (Klein et al., 2011). 3. NEW FINDINGS ON TRANSLOCATION FORMATION OBTAINED BY HTGTS AND TC-Seq HTGTS and TC-Seq have greatly expanded our understanding and interpretation of translocation mechanisms. For example, using these methods, it was discovered that DSBs generated from fixed loci show a much wider genomic distribution than previously expected. Chromosomal translocations were mostly found within the same chromosome where the original DSB was located, in particular, within a relatively narrow (about 1 Mb) region around the DSB site. This intrachromosomal preference for DSB joining could be explained by the documented preference for C-NHEJ to repair DSBs within the same chromosome (Ferguson et al., 2000; Mahowald et al., 2009; Zarrin et al., 2007) and/or by recent data showing

62 Translocation in Normal and Cancer Cells 53 that regions within the same chromosome are much more likely to be in physical contact than regions between two different chromosomes (Lieberman-Aiden et al., 2009; Zhang et al., 2012; see Section 3.4). By HTGTS, the analysis of SNPs in translocation junctions showed that translocations are 6 10 times more likely to occur within the same allele where the DSBs are located (Zhang et al., 2012) RAG1/2 translocation hotspots in pro-b lymphocytes New translocation-mapping techniques, such as HTGTS, provide a viable tool to analyze RAG-mediated target and off-target DSB formation. In pro-b cell lines transformed with Abelson murine leukemia virus (A-MuLV), RAG expression is induced by cell-cycle arrest mediated by the inhibition of v-abl activity by the kinase STI571 (Bredemeyer et al., 2006). In ATM / pro-b cell lines, translocations were enriched in the expected RAG target sites (IgH, Igk, Igl) in TCR loci (TCRa/d, TCRg), which are considered to be inaccessible due to a closed chromatin conformation in pro-b cells. Thus, similar to AID in peripheral B cells, RAG is the major source of DSBs in pro-b cells, where it largely dictates the landscape of translocations (Zhang et al., 2012) AID hotspots in activated B lymphocytes HTGTS and TC-Seq translocation maps found a strong enrichment of expected AID targets. A prediction of AID targets for DSBs initiation was obtained by deep sequencing of genomic AID-binding sites. With this approach, AID was found to bind preferentially promoter-proximal regions where stalled polymerases and chromatin-activating marks were enriched (Yamane et al., 2011). In translocation maps, when B cells were stimulated with CD40 or LPS and IL-4, AID generated DSBs in the Sm,Sg1, Sg3, and Se regions, as expected. Chromosomal translocations to S regions were up to 20-fold higher than any other recurrent translocation in B cells, revealing the IgH S region as a major translocation hotspot in B cells and highlighting AID as the most important DSB-generating enzyme in a normal B cell (Chiarle et al., 2011; Klein et al., 2011). A series of known and unknown AID targets were also found to be involved in translocations or deletions. For example, (1) Pim1, Il21r, and Gas5 all translocate with Bcl6 in DLBCL (Nakamura et al., 2008; Ueda et al., 2002; Yoshida et al., 1999); (2) Pax5 and Ddx6 are translocated with IgH in DLBCL and in LP lymphoma (Iida, Rao, Ueda, Chaganti, & Dalla-Favera, 1999; Lu & Yunis, 1992; Yoshida et al., 1999);

63 54 Roberto Chiarle (3) c-myc and Pvt1 are repeatedly translocated in human BL and mouse plasmacytoma (Cory, Graham, Webb, Corcoran, & Adams, 1985; Einerson et al., 2006; Küppers, 2005); (4) Aff3 and Grhpr translocate with Bcl2 and Bcl6, respectively, in FL (Akasaka, Lossos, & Levy, 2003; Impera et al., 2008); (5) Ccnd2 and Bcl2l11 are translocated or deleted (respectively) in MCL (Bea et al., 2009; Gesk et al., 2006); and (6) Birc3 is translocated with Malt1 in MALT lymphoma (Murga Penas et al., 2006) and with mir142 in B-cell prolymphocytic leukemia (Gauwerky, Huebner, Isobe, Nowell, & Croce, 1989) Gene density, transcription, and translocations By HTGTS, about 10 20% of translocations were found to be interchromosomal and were widely distributed across all chromosomes (Chiarle et al., 2011; Klein et al., 2011). Strikingly, translocations strongly correlated with gene density and gene activity in each chromosome, clustering at a higher frequency in regions enriched in transcribed genes, and much less so in regions devoid of active genes (Chiarle et al., 2011). Furthermore, translocations were enriched in genes with Pol II and marks of active histones, such as H3K4 trimethylation, H3 acetylation, and H3K36 trimethylation (Klein et al., 2011). In actively transcribed genes, translocations accumulated in the promoter region, within a few kilobases of the transcription starting site, whereas in inactive genes, translocations were evenly dispersed throughout the gene. The clustering of translocations in the promoter region of WT B cells was found not only in AID target genes but also in genes not targeted by AID and in AID-deficient cells (Chiarle et al., 2011). The observed correlation between gene transcription and translocation is very intriguing. Transcription generates genetic instability by multiple mechanisms that are still poorly understood. Transcribed genes likely offer regions of genomic fragility, owing to the single-strand DNA conformation of transcribed gene segments, the collision of transcription machinery with replication forks, and the formation of DNA RNA hybrids (R-loops) (Aguilera, 2002; Ruiz, Gomez-Gonzalez, & Aguilera, 2011). In B cells, CSR (see Section ) is a recurrent source of DSBs and is heavily dependent on transcription. Transcription of the switch (S) regions determines the formation of stable DNA structures, in which the C-rich template strand forms R-loop intermediates, whereas the G-rich nontemplate strand generates secondary structures. AID deaminates DNA on the C-rich template strand of actively transcribing S regions, to allow for eventual DSB

64 Translocation in Normal and Cancer Cells 55 generation (Chaudhuri et al., 2003; Nambu et al., 2003). Binding of AID to transcribed regions is mediated by the transcription elongation complex (Besmer, Market, & Papavasiliou, 2006) and is enhanced by transcriptional pausing and stalling of Pol II (Canugovi, Samaranayake, & Bhagwat, 2009). The protein Spt5 is thought to mediate AID binding to stalled transcription sites (Pavri et al., 2010). Therefore, AID might be recruited not only to transcriptionally stalled sites in the immunoglobulin (Ig) loci to induce CSR and SHM but also to non-ig loci, thus favoring DSBs and translocations in genes such as c-myc, Bcl6, Pim1, and Pax5 that are repeatedly translocated in human lymphomas (Pavri & Nussenzweig, 2011). Indeed, TC-Seq studies showed strong overlap between translocations and AID- and Spt5-binding sites (Klein et al., 2011; Yamane et al., 2011). In the absence of AID, translocations were likely to result from DSB formation during physiological processes related to transcription and DNA replication (Branzei & Foiani, 2010). In this context, ERFSs could contribute to explain more than 50% of chromosomal aberrations in human diffuse large B cell lymphomas (Barlow et al., 2013) Role of nuclear positioning and chromosomal structure in translocations Physical proximity has always been considered a key determinant in chromosomal translocations in cancer. Early DNA FISH studies in the interphase nuclei of mouse and human B cells showed that loci frequently involved in lymphoma translocations, such as IgH and c-myc, or IgH and Bcl2, were often located in close proximity to each other (Parada, McQueen, & Misteli, 2004; Roix et al., 2003; see Section 1.3). Similarly, translocation partners in other hematologic malignancies, such as BCR ABL1 in chronic myeloid leukemia, RET CDC6 in thyroid malignancies, TMPRSS2 ERG/ ETV1 in prostate cancer, and PML RARA in acute PML, were frequently proximal in the cells considered to be tumor precursors (Mitelman et al., 2007). Proximity between loci seems to be dictated, at least in some instances (such as the IgH and c-myc loci), by the recruitment of a common transcription factory (see Section 1.4; Osborne et al., 2007). Pro-B cells undergo V(D)J rearrangements due to the expression of RAG enzymes that recognize specific sequences in the genome (see Section 1.1.1). Application of HTGTS translocation-mapping approaches to pro-b cells revealed high genomic stability in WT cells with a limited number of cloned translocations. In contrast, in ATM / cells,

65 56 Roberto Chiarle RAG-mediated breaks dominated the landscape of translocation (see Section 3.1). Thus, DSB frequency in RAG targets strictly determines the translocation pattern. In contrast, when DSBs were no longer a limiting factor, as in cells treated with ionizing radiation, most of the translocations (between 25% and 40%) were found in the same chromosome where the bait DSBs were located, supporting a strong influence of chromosomal territories on translocation formation (Zhang et al., 2012). Furthermore, translocations on the same chromosome were mostly in cis on the same allele. Strikingly, by combining HTGTS with Hi-C studies, it was found that translocations on the same chromosome, as well as translocations in trans with other chromosomes, strongly correlated with regions with a higher contact probability (Zhang et al., 2012). 4C-seq maps generated from genes that are actively transcribed in mature B cells, such as IgH and c-myc, showed that these genes shared similar genome-wide interactions, despite being on different chromosomes (chr. 12 for IgH and Chr. 15 for c-myc). The highest frequency of contacts was found in cis within the same chromosome 12 and 15, respectively, consistent with the data obtained in pro-b cells (see above; Zhang et al., 2012) and with the concept that chromosomes are organized in defined territories (Cremer & Cremer, 2010; Lieberman-Aiden et al., 2009). In contrast, trans interactions were likely to be driven by transcriptional activity and chromatin conformation, as IgH and c-myc interacted preferentially with loci associated with activating histone acetylation marks, Pol II binding, and active transcription (Hakim et al., 2012). These findings are consistent with the notion that chromosomes are organized into areas of compact and open chromatin, with open chromatin regions having a distinct nuclear organization and being enriched in genes (Gilbert et al., 2004). Genes within areas of active or inactive chromatin have a higher probability of contact than do genes between these areas (Lieberman-Aiden et al., 2009; Simonis et al., 2006). In mature B cells, in the absence of AID, DSBs are likely to be generated by common mechanisms associated with transcription and replication. In this setting, translocation pattern was shown to strictly correlate with the interaction frequencies between loci. In contrast, in the presence of AID, translocations correlated not with contact frequency but with DSB frequency, as determined by RPA binding in 53BP1 / cells (Hakim et al., 2012). Overall, these new genome-wide correlations between translocations, DSBs, and nuclear proximity indicate that in the presence of a dominant source of DSBs in B cells (i.e., RAG1/2 in pro-b cells and AID in mature

66 Translocation in Normal and Cancer Cells 57 B cells), the translocation landscape is mainly dictated by the frequency of DSBs in any given locus. In contrast, in the absence of such DSBs (such as in AID / B cells), the relative nuclear position mainly regulates translocation frequency. Future studies are needed to address these correlations in non-b cells, where a dominant mechanism for DSB formation is likely absent. 4. LANDSCAPE OF TRANSLOCATIONS IN CANCERS The landscape of chromosomal translocation in human cancers varies from tumors containing minimal structural variations to tumors with highly complex genomic rearrangements (CGRs). The recurrent presence of such structural abnormalities in cancers can be interpreted as driver events that are selected and enriched during tumor progression, or passenger events that originate during the life cycle of a tumor without particular selective forces that fix them in the cancer genome. Typical driver chromosomal translocations are those that define different categories of hematologic malignancies or specific subtypes of solid tumors, such as the BCR-ABL translocation in CML, various translocations in AML, most translocations in human lymphomas (see below), and recurrent translocations in solid cancers, such as EWSR1 fusions in Ewing sarcoma (Toomey, Schiffman, & Lessnick, 2010), ETS fusions in prostate cancer (Rubin, Maher, & Chinnaiyan, 2011), and anaplastic lymphoma kinase (ALK) fusions in lymphoma, lung carcinoma, and other cancers (Chiarle, Voena, Ambrogio, Piva, & Inghirami, 2008). In such tumors, the structural landscape of the tumor genome is dominated by the driver translocation events, with minimal additional structural variations in other chromosomes (Mitelman et al., 2007). Driver translocations were first discovered more than three decades ago with classical cytogenetic techniques because they are highly recurrent in cancers and, therefore, more easily identified. In contrast, our understanding of the more elusive nonrecurrent passenger chromosomal rearrangements has only recently become clearer, owing to the development of genome-wide analysis tools such as next-generation DNA sequencing, RNA sequencing, SNP-array analyses and, of course, adequate bioinformatics methods Distribution of chromosomal translocations in cancers Many human cancers show complex genomic structural rearrangements. These rearrangements can be divided into different types and can be intrachromosomal or interchromosomal. Intrachromosomal rearrangements are

67 58 Roberto Chiarle typically observed as deletions, tandem duplications, inversions, or other complex noninverted intrachromosomal rearrangements. Interchromosomal rearrangements are translocations between different chromosomes that account for less than 10% of all the structural variations in cancers with complex genomic structural rearrangements (Pleasance et al., 2010). Nextgeneration DNA sequencing allows for the improved characterization of such complex cancer genomes. Strikingly, in many cancer types, highly CGRs are confined to one or few chromosomes, where tens or hundreds of chromosomal rearrangements are clustered. Such events have been termed chromothripsis (Stephens et al., 2011) Chromothripsis in cancer genomes The first evidence of chromothripsis came from whole-genome sequencing of CLL patients. In this series, it was found that chromosomal rearrangements generally clustered within one entire chromosome and more frequently in smaller regions, such as an entire chromosomal arm or even in segments just a few tens of megabases or kilobases in length (Stephens et al., 2011). In these regions of chromothripsis, chromosomal rearrangements were both inverted and noninverted in orientation. Strikingly, there was an equal representation of the four major possible patterns of intrachromosomal rearrangements, that is, deletions, head-to-head and tail-to-tail inversions, and tandem duplications (Stephens et al., 2011). Chromothripsis has been found in a range (3 25%) of other cancer types, such as neuroblastoma (Molenaar et al., 2012); medulloblastoma (Northcott et al., 2012; Rausch et al., 2012); bone cancers (Stephens et al., 2011); MM (Magrangeas, Avet-Loiseau, Munshi, & Minvielle, 2011); and lung, renal, and thyroid cancers (Forment, Kaidi, & Jackson, 2012). Chromothripsis can also be characterized in terms of its limited copy-number state, where the rearranged regions vary between one or two copies, with segments exhibiting a loss of heterozygosity alternating with segments with retained heterozygosity (Kloosterman et al., 2011; Stephens et al., 2011). These extensive chromosomal rearrangements that occur during chromothripsis are thought to originate from a single catastrophic event rather than as a consequence of progressive sequential rearrangements. In the progressive rearrangement model, complex, localized clustering of rearrangements originates during many cell cycles, generating increasing complexity in genomic structure. This is the mechanism typically thought to cause genomic amplifications. As an example, amplifications of the c-myc

68 Translocation in Normal and Cancer Cells 59 locus are thought to derive from the so-called breakage fusion bridge cycle, where regional weakness of the DNA structure may lead to repeated cycles of DNA breakage and repair (Gostissa et al., 2011; Zhang et al., 2010). In contrast, during chromothripsis, the entire chromosome or chromosomal regions are shattered into several fragments in a narrow window of time and then joined. The minimal or absent sequence homology between the translocated pieces favors mechanisms of repair based on C-NHEJ or other end-joining pathways (Forment et al., 2012). The fact that tens to hundreds of pieces of chromosomal DNA can be rejoined within the same chromosome suggests that chromothripsis could occur when chromosomes are in a condensed state, such as during mitosis. Alternatively, it might be the result of the organization of chromosomes into territories where DNA repair, mostly C-NHEJ, favors joining within the same chromosome (Gostissa et al., 2011; Zhang et al., 2010). Indeed, mouse models of translocations indicate that, in the presence of a catastrophic event, such as ionizing radiations, rejoining of DSBs and translocations are preferentially clustered in cis within the same chromosomal allele (Zhang et al., 2012). Alternatively, other repair mechanisms could be involved, such as replication fork stalling and template switching (Branzei & Foiani, 2010) or microhomology-mediated break-induced replication (MMBIR) (Liu et al., 2011). The question on how such catastrophic events are generated is still open (Fig. 2.4). The fact that DNA shattering involves only a limited number of chromosomes, or limited segments within chromosomes, suggests that the DNA-damaging event should occur when chromosomes are at a condensed stage, such as mitosis. DSBs could be caused by an environmental stimulus, such as exposure to free radicals or ionizing radiation (Tsai & Lieber, 2010), or by DNA replication stress with premature termination of replication forks and DSB formation at potentially fragile sites (Halazonetis et al., 2008). Recently, it was shown that aberrant and persistent DNA replication within micronuclei can generate DNA damage and chromosome pulverization (Crasta et al., 2012). Additional catastrophic DNA-damaging events could occur during telomere attrition (Sahin & Depinho, 2010) or apoptotic events that would kill a normal but not a cancerous cell (Tubio & Estivill, 2011). Interestingly, germ line and somatic TP53 mutations were associated with chromothripsis both in medulloblastoma and AML (Rausch et al., 2012). This finding indicates that defects in checkpoint pathways designed to repair DNA damage predisposes to chromothripsis, likely by facilitating cell-survival mechanisms that operate during catastrophic

69 60 Roberto Chiarle Mitosis Chromosome shattering Micronucleus pulverization Radiation MMBIR Predisposition to cancer due to oncogenes and oncosuppressors alterations Postmitotic cell with chromothripsis NHEJ MMBIR DNA repair Chromosome territory P53 deficiency Mitosis exit Figure 2.4 Proposed mechanisms of chromothripsis in normal and cancer cells. During mitosis, chromosomes are condensed and focal DNA damage can be induced by radiation, microhomology-mediated break-induced replication (MMBIR), or chromosome lagging, micronuclei formation, and pulverization due to inappropriate chromosome segregation. After chromosome shattering, DNA fragments are joined by NHEJ within chromosomal territories. Repaired chromosomes contain chromosomal rearrangements such as deletions, head-to-head and tail-to-tail inversions, and tandem duplications. With mitosis exit, the chromothriptic chromosome can be reincorporated into the nucleus. Deficiency of DNA-damage checkpoints, such as P53 deficiency, facilitates the survival of cells during the chromothriptic process. As a result, chromothripsis can induce oncogene activations by translocations or duplications as well as loss of oncosuppressor genes by deletions or locus disruptions, thus facilitating cancer progression. events, such as the favoring of low-fidelity repair or bypassing of G2/M cellcycle checkpoints (Maher & Wilson, 2012). Chromothripsis could have important implications in the evolution of cancers. First, because regions of heterozygosity are conserved inside clusters of rearrangements, chromothripsis is thought to occur early in cancer cell development (Forment et al., 2012; Stephens et al., 2011), suggesting that such rearrangements might themselves influence the progression of cancer cells. Second, a particular cancer cell undergoing chromothripsis could derive some selective advantages. Chromosomal segments generated during massive chromosomal fragmentation might not be reincorporated into the derivative chromosome but instead might form double-minute chromosomes. In this

70 Translocation in Normal and Cancer Cells 61 context, one case of bone cancer chromothripsis was shown to generate one double-minute chromosome approximately 1.1 Mb in length that contained multiple amplified copies of c-myc (Stephens et al., 2011), likely giving a selective advantage to the cell. Alternatively, the catastrophic event could simultaneously disrupt multiple tumor-suppressor genes, as in the case of a chordoma sample in which the cyclin-dependent kinase inhibitor 2A (CDKN2A), the F-box and WD-40 domain containing protein 7 (FBXW7), and the Werner syndrome ATP-dependent helicase (WRN) genes were disrupted as a consequence of one single chromothriptic event (Forment et al., 2012). Interestingly, the pattern of intrachromosomal rearrangements resulting from chromothripsis in cancer cells has been faithfully reproduced in normal B cells in mouse models of induced translocations. In these models, a dominant source of DSBs is generated by the targeting of I-SceI substrate sequences in the IgH locus or in the c-myc locus. Those I-SceI-induced DSB loci are embedded in regions with a high density of spontaneous DSBs, generated in B cells by either AID in the IgH switch regions flanking the I-SceI site, or by AID-dependent and -independent mechanisms in the closely localized c-myc and Pvt1 genes. Indeed, the Pvt1 gene is frequently translocated not only in BL but also in nonlymphoid cancers such as lung cancer and medulloblastoma (Northcott et al., 2012; Pleasance et al., 2010). Therefore, these models show that a high density of synchronous DSBs generated in normal cells, within a chromosomal region of few kilobases, might simulate a chromothriptic event. Remarkably, normal cells react to these localized chromothriptic events by generating a pattern of chromosomal rearrangements highly similar to cancer cells, with deletions, head-to-head and tail-to-tail inversions represented in approximately equal frequency (Chiarle et al., 2011; Klein et al., 2011). Similarly, in human medulloblastoma, an approximately 200-kb region flanking the Pvt1 locus was found to be frequently involved in chromothriptic events, with frequent oncogenic rearrangements occurring with the c-myc locus upstream or the NDRG1 locus downstream of Pvt1 (Northcott et al., 2012). Additionally, events similar to chromothripsis can be observed in some genomic disorders where CGRs are identified (Zhang, Carvalho, & Lupski, 2009). These genomic disorders are thought to originate from germ line rearrangements during gametogenesis or early postzygotic development. In these conditions, multiple copy-number changes can be found, including deletions, duplications, and extensive translocations and inversions. To explain these events, a MMBIR model has been proposed for complex

71 62 Roberto Chiarle rearrangements, where copy gains or losses involve the generation and repair of DSBs in regions with domains of MH (Hastings, Lupski, Rosenberg, & Ira, 2009). It is speculated that MMBIR and subsequent replicationmediated repair by C-NHEJ could explain both CGRs in genomic disorders as well as chromothripsis in cancer cells (Kloosterman et al., 2012; Liu et al., 2011). Thus, the structural similarities between chromosomal rearrangements observed in normal B cells, CGR genomic disorders, and chromothripsis strongly argue in favor of similar mechanisms for DSB repair operating in normal and cancer cells Repetitive patterns and heterogeneity of translocations involving oncogenes In human patients, some translocations are recurrently found in specific subtypes of tumors. The IgH-c-myc translocations are typically found in BL and DLBCL, IgH-Bcl-2 translocations in B-cell lymphomas (mainly FL, CLL, and DLBCL), IgH-Bcl-1 translocations in MCL and MM, and Bcl-6 translocations in DLBCL. It is thought that these translocations are generated from the joining of one physiologic DSB in the IgH locus with one pathologic DSB in the oncogene as consequence of off-target activity of B-cellspecific genes such as RAG and AID (see Section 1.1). However, some oncogenes have much more heterogeneous patterns of translocations. For example, PAX5 is involved in the t(9:14) translocation with IgH in PL and other more aggressive lymphomas (Poppe et al., 2005), but 2.6% of pediatric B-ALL patients show multiple different translocation partners for PAX5. PAX5-ETV6 translocation was the first to be reported (Cazzaniga et al., 2001), but many others were subsequently discovered, including translocations of PAX5 with the transcription factors ETV6, FOXP1, ZNF521, PML, DACH1, DACH2, the chromatin regulators NCoR1, BRD1, the protein kinases JAK2, HIPK1, and others (Coyaud et al., 2010; Medvedovic, Ebert, Tagoh, & Busslinger, 2011). Similarly, the Bcl-6 oncogene is frequently involved in translocation events with many non-igh genes in lymphoma, including CIITA, Pim-1, eif4aii, TFRC, RHOH, Ikaros, and up to 20 different partners (Ohno, 2006). The explanation for how such non-igh translocations in lymphoid cells occur is not totally clear. Some are likely to be off-target AID translocation partners. Pax5, Pim-1, and RHOH frequently show SHM in B cells as a result of AID activity (Liu et al., 2008) and are found as hotspots in translocationmapping experiments (see Section 2). However, a clear role for AID or RAG has not yet been proved for many other genes, and other mechanisms

72 Translocation in Normal and Cancer Cells 63 for DSB formation could still be responsible for initiating such translocation. Even more compelling, specific cell-type mechanisms likely occur when the same oncogene translocates with specific partners in different tumor types. The ALK oncogene was first discovered as a partner of the Nucleophosmin 1(NPM1)-ALKtranslocationinanaplastic-large-celllymphoma(Morris et al., 1994). In the past 20 years, at least 20 different ALK translocation partners were discovered in lymphoma and recently also in solid tumors, such as myofibroblastic inflammatory tumors and lung, colorectal, and renal carcinoma (Chiarle et al., 2008; Kohno et al., 2012; Lipson et al., 2012; Soda et al., 2007; Takeuchi et al., 2012). For such translocations, the initiating events are very poorly understood. Strikingly, some translocations are highly tumor specific. For example, the NPM-ALK translocation, by far the most frequent translocation in lymphoma, is never encountered in solid tumors. In contrast, the EML4-ALK translocation that is predominant in lung carcinoma is never observed in lymphoma. Similarly, differential tissue-specific patterns are also found in other recurring oncogene translocations, such as RET, which is involved in translocations in thyroid and lung cancers (Lipson et al., 2012; Nikiforov & Nikiforova, 2011). Therefore, tissue-specific differences in translocation patterns do exist. Factors such as tissue-specific DSB formation, transcriptional activity of the implicated genes, or nuclear conformation and chromosome distribution must be investigated to explain the tissue specificity of translocation patterns. 5. PERSPECTIVES Recent breakthroughs in technology have critically advanced our ability to investigate the mechanisms that regulate translocation formation. We are now able to move on from studies focusing on a few specific genes to studies that can generate genome-wide maps of translocations and contacts in both normal and neoplastic cells. From these maps, we can rank the relative specific weight of the different factors required for translocation formation. DSB frequency seems to largely determine the pattern of translocations in normal cells and likely in cancer cells as well, but more studies are needed to prove this. In the absence of a dominant source of DSBs (i.e., in the absence of RAG or AID in B cells), translocations seem to follow the rules dictated by the proximity of chromosomal regions where the DSBs occur. The active transcription characteristics of genes influence their frequency of translocation, but it remains to be determined whether this effect depends on the increased probability of DSBs in transcribed genes or on increased

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82 CHAPTER THREE The Intestinal Microbiota in Chronic Liver Disease Jorge Henao-Mejia*,1, Eran Elinav,1, Christoph A. Thaiss,1, Richard A. Flavell*,,2 *Department of Immunobiology, Yale University School of Medicine, New Haven, Connecticut, USA Immunology Department, Weizmann Institute of Science, Rehovot, Israel Howard Hughes Medical Institute, Chevy Chase, Maryland, USA 1 Equal contributors 2 Corresponding author: address: richard.flavell@yale.edu Contents 1. Introduction Role of the Intestinal Microbiota on Chronic Liver Diseases Nonalcoholic fatty liver disease Cirrhosis and associated comorbidities Hepatocellular carcinoma Autoimmune liver disease Role of the Interactions Between the Innate Immune System and the Intestinal Microbiota on Chronic Liver Diseases Toll-like receptors Inflammasomes C-type lectins Dysbiosis associated with innate immune deficiency and its implications for liver disease Probiotics and their Potential Role in Liver Disease Therapy Conclusions 90 References 91 Abstract Recent evidence indicates that the intestinal microflora plays a critical role in physiological and pathological processes; in particular, it is now considered a key determinant of immune pathologies and metabolic syndrome. Receiving the majority of its blood supply from the portal vein, the liver represents the first line of defense against food antigens, toxins, microbial-derived products, and microorganisms. Moreover, the liver is critically positioned to integrate metabolic outcomes with nutrient intake. To accomplish this function, the liver is equipped with a broad array of immune networks. It is now evident that, during pathological processes associated with obesity, alcohol-intake, or autoimmunity, the interaction between these immune cell populations and the Advances in Immunology, Volume 117 ISSN # 2013 Elsevier Inc. All rights reserved. 73

83 74 Jorge Henao-Mejia et al. intestinal microbiota promotes chronic liver disease progression and therefore they represent a novel therapeutic target. Herein, we highlight recent studies that have shed new light on the relationship between the microbiome, the innate immune system, and chronic liver disease progression. 1. INTRODUCTION The human gastrointestinal tract contains trillion bacteria and approximately different bacterial species (Lozupone, Stombaugh, Gordon, Jansson, & Knight, 2012). These microorganisms have critical functions in multiple aspects of human physiology such as regulation of metabolic processes, education of the immune system, and promotion of epithelial cell responses that are essential to maintain mutualism (Maynard, Elson, Hatton, & Weaver, 2012; Tremaroli & Backhed, 2012). The intestinal microflora differs quantitatively and qualitatively among species and individuals. Life style, age, dietary habits, exposure to antibiotics, and host genotype play essential roles in the composition of the intestinal microflora (Claesson et al., 2012; Turnbaugh et al., 2009); moreover, disruption of the delicate balance that represents the ecosystem of bacterial communities of the gastrointestinal tract can lead to severe metabolic and inflammatory pathologies. The close functional relationship between the liver and the gastrointestinal tract (gut liver axis) is highlighted by multiple important physiological processes that intimately interconnect these organs. The liver, the largest organ in the body, has a dual blood supply. The hepatic artery, which arises from the celiac artery, supplies oxygenated blood to the liver, and the portal vein conducts venous blood from the intestines and the spleen. Approximately 75% of hepatic blood flow is derived from the hepatic portal vein ( ml/min), and therefore, the liver is constantly exposed to nutrients, toxins, food-derived antigens, microbial products, and microorganisms derived from the intestinal tract (Miyake & Yamamoto, 2013). This strategic location confers critical metabolic, immunologic, and detoxifying roles to the liver and stresses the crucial role of the intestinal microbiota on hepatic pathophysiology. In this review, we examine the impact of gut microbiota on hepatic diseases, focusing on how dysbiosis and immune responses triggered by microbiotaderived products shape the progression of chronic liver pathologies.

84 The Intestinal Microbiota in Chronic Liver Disease ROLE OF THE INTESTINAL MICROBIOTA ON CHRONIC LIVER DISEASES 2.1. Nonalcoholic fatty liver disease Nonalcoholic fatty liver disease (NAFLD) is the leading cause of chronic liver disease in Western societies, with a prevalence ranging from 20% to 40% in the general population and up to % in obese individuals (Ludwig, Viggiano, McGill, & Oh, 1980; Sheth, Gordon, & Chopra, 1997). NAFLD is considered the hepatic manifestation of metabolic syndrome (Marchesini et al., 2003), with many patients developing other comorbidities including insulin resistance, hyperlipidemia, cardiovascular disease, polycystic ovary syndrome, and obstructive sleep apnea (Cerda et al., 2007; Tolman, Fonseca, Dalpiaz, & Tan, 2007). While most patients with NAFLD remain asymptomatic, 20% progress to develop chronic hepatic inflammation (nonalcoholic steatohepatitis, NASH), which in turn can lead to cirrhosis, portal hypertension, hepatocellular carcinoma (HCC), and increased mortality (Caldwell et al., 1999; Propst, Propst, Judmaier, & Vogel, 1995; Shimada et al., 2002). NASH can be classified as primary NASH (associated with obesity, type 2 diabetes (T2DM), and hyperlipemia) and secondary NASH (occurring after pharmacological interventions, parenteral nutrition, jejunoileal bypass surgery, or Wilson s disease). Despite its high prevalence, factors leading to progression from NAFLD to NASH remain poorly understood and no treatment has proved effective (Charlton, 2008; Hjelkrem, Torres, & Harrison, 2008). A two-hit mechanism is proposed to drive NAFLD/NASH pathogenesis (Day & James, 1998). The first hit, hepatic steatosis, is closely associated with lipotoxicity-induced mitochondrial abnormalities that predispose the liver to additional proinflammatory insults (second hits) that promote disease progression. Second hits include increased generation of reactive oxygen species, increased lipid peroxidation, and gut-derived factors. Most likely, the parallel action of these hepatic tissue insults is required for the development of steatohepatitis (Sanyal et al., 2001). In the past decade, a growing body of research functionally links the intestinal microbiota with the development of steatosis (first hit) and with the progression to NASH (second hit). Obesity is considered the most common risk factor for NAFLD in humans (Younossi et al., 2011). Several lines of evidence unequivocally link the intestinal microflora with body weight and body fat composition

85 76 Jorge Henao-Mejia et al. Intestinal microbiota Type 2 diabetes Endotoxemia Insulitis Insulin resistance Steatosis Obesity Increased calorie extraction Cleavage of dietary polysaccharides Dyslipidemia Decreased choline metabolism Figure 3.1 Effects of the intestinal microbiota on the risk factors that promote NAFLD development. The microbiota can regulate the progression of multiple associated comorbidities that are associated with NAFLD pathogenesis such as choline metabolism, obesity, and diabetes mellitus. (Fig. 3.1). In animal studies, germ-free mice have a lower body fat content than conventionally raised mice; moreover, the inoculation of germ-free mice with microbiota from wild-type mice results in a significant increase in body fat accumulation (Turnbaugh et al., 2006). The phyla Bacteroidetes and Firmicutes represent a large proportion of the intestinal microbiota composition in mice and humans; however, their relative abundance profoundly affects the body composition of individuals (Ley et al., 2005; Ley, Turnbaugh, Klein, & Gordon, 2006). Genetically obese mice (ob/ob) have a significant increase in the Bacteroidetes to Firmicutes ratio when compared with lean littermate controls, but perhaps more importantly, germ-free mice colonized with microbiota from genetically obese mice gained weight faster and harvest calories more efficiently than mice colonized with intestinal microflora from lean mice (Turnbaugh et al., 2006). These findings indicate that the composition of the microbiota directly influences calorie extraction, body fat composition, and body weight. In humans, several lines of evidence now correlate the composition of the intestinal microbiota with multiple metabolic and inflammatory parameters as well as dietary habits (Claesson et al., 2012; Ley et al., 2006; Muegge et al., 2011). Similar to mice, obese individuals have increased levels of Bacteroidetes and the reduction of this phylum in the intestinal microflora is significantly associated with weight loss either by

86 The Intestinal Microbiota in Chronic Liver Disease 77 fat- or carbohydrate-restricted diets, suggesting that Bacteroidetes may be responsive to calorie intake (Ley et al., 2006). Metagenome-wide association studies have recently demonstrated that T2DM patients are characterized by gut microbial dysbiosis, a decrease in the abundance of butyrate-producing bacteria and an increase in various opportunistic bacterial pathogens. Moreover, these gut microbial markers can be useful for classifying T2DM, indicating that specific conformations of the intestinal microbiota play critical roles in the pathogenesis of T2DM and associated disorders (Qin et al., 2012). Calorie intake of Western society diets is a key determinant of metabolic syndrome. Long-term dietary habits have a profound effect on the human gut microbiota and therefore on potential deleterious metabolic outcomes. It has been proposed that the human gut microbiota should be divided into three compositions (enterotypes), yet this notion is still debated and merits further validation. Each suggested enterotype is dominated by a different genus Bacteroides, Prevotella, or Ruminococcus (Arumugam et al., 2011). Interestingly, enterotypes dominated by Bacteroides are associated with diet rich in protein and animal fat (Western diet), while Prevotelladominated enterotypes are associated with the consumption of a diet rich in carbohydrates/fiber (De Filippo et al., 2010; Wu et al., 2011), suggesting that the gut microbiota is shaped by the different diets to maximize energy extraction. Taken together, these studies show that the composition of the microbiota is a critical player in the metabolic status of the host and its disturbance is associated with metabolic abnormalities that are associated with the first hit (steatosis) during NAFLD pathogenesis. Although it is now clear that the intestinal microflora plays critical roles in body fat accumulation and weight gain, the role of gut-derived factors on NAFLD progression has just begun to be elucidated. Progression from steatosis to steatohepatitis is mainly an inflammatory process that likely reflects the concerted deleterious effects of multiple noxious stimuli. Several lines of evidence now suggest that intestinal bacterial communities might play an important part in this process. Jejunoileal bypass, small intestinal diverticulosis, total parenteral nutrition, and intestinal failure are associated with NASH progression (Carter & Karpen, 2007; Corrodi, 1984; Nazim, Stamp, & Hodgson, 1989; Quigley, Marsh, Shaffer, & Markin, 1993; Vanderhoof, Tuma, Antonson, & Sorrell, 1982); interestingly, small intestinal bacterial outgrowth (SIBO) as a consequence of low intestinal motility has been proposed as a key determinant factor for NAFLD progression in these conditions in humans (Carter & Karpen, 2007; Pappo et al., 1992; Quigley et al., 1993). In concordance with this, antibiotic treatment or

87 78 Jorge Henao-Mejia et al. surgical removal of the bypassed section of the intestine reverses SIBO and steatohepatitis. Similarly, rats fed under total parenteral nutrition are characterized by severe liver injury secondary to bowel hypomotility, which leads to the expansion of Gram-negative bacterial populations and increased hepatotoxic mediators such as endotoxin or tumor necrosis factor (Pappo et al., 1992). The role of the intestinal microbiota in the more highly prevalent primary NASH is less clear. The prevalence of SIBO is significantly increased in obese individuals as compared with healthy lean subjects (Sabate et al., 2008), but its role in NAFLD progression has largely been overlooked. Nevertheless, a recent study conducted by Miele et al. (2009) evaluated intestinal permeability, SIBO, and NAFLD disease stage. Interestingly, patients with NAFLD were reported to have significantly increased gut permeability and SIBO when compared with healthy individuals, suggesting that overgrowth of the intestinal bacterial flora gut could lead to bacterial translocation, portal endotoxemia, and ultimately hepatic injury (Miele et al., 2009). In concordance with this possibility, multiple studies have found high levels of SIBO prevalence in different cohorts of NASH patients (Sajjad et al., 2005; Wigg et al., 2001); moreover, we recently demonstrated that inflammasomemediated dysbiosis characterized by an expansion of the Prevotellaceae and Porphyromonadaceae families as well as the TM7 taxa promotes NAFLD progression in different mouse models (Henao-Mejia, Elinav, Jin, et al., 2012). Collectively, these studies indicate that different compositions of the bacterial communities of the intestines might regulate NAFLD progression in humans and therefore represent a novel therapeutic target. Characterization of the bacterial communities at different stages of NAFLD and the exact role of metabolites derived from the bacterial microflora in disease progression should shed some light on the precise role of the microbiome in liver disease in the context of metabolic syndrome Cirrhosis and associated comorbidities Cirrhosis is the final clinical histopathological stage of a wide array of liver diseases. The intestinal microbiota is a common denominator of the major complications of liver cirrhosis, including spontaneous bacterial peritonitis, hepatic encephalopathy (HE), and esophageal variceal bleeding (Basile & Jones, 1997; Campillo et al., 1999; Guarner & Soriano, 1997; Husova et al., 2005; Thalheimer, Triantos, Samonakis, Patch, & Burroughs, 2005). The process of liver fibrogenesis promotes dysbiosis and intestinal

88 The Intestinal Microbiota in Chronic Liver Disease 79 barrier dysfunction through multiple pathological processes. Cirrhotic patients have decreased blood flow through the portal vein and intestinal vascular congestion, which results in increased gut permeability (Bauer et al., 2001; Gunnarsdottir et al., 2003). Moreover, impaired liver function promotes changes in bacterial communities in the gut through decreased bile acid production and defective intestinal motility that leads to SIBO (Sung, Shaffer, & Costerton, 1993). Thus, it is now well recognized that impaired fluid/liver physiology and innate immunity in combination with dysbiosis are key pathological processes that promote bacterial translocation to the peritoneum. HE is a broad term that encompasses a constellation of neuropsychiatric abnormalities observed in patients with liver dysfunction (Bajaj, 2010). Overt HE is diagnosed in up to 45% of patients with cirrhosis, while minimal HE is observed in 60 80% of the patients (Bajaj, 2010). In healthy individuals, the liver protects the brain from ammonia by converting it to urea, which is then excreted by the kidneys. In the context of severe liver dysfunction, ammonia becomes the critical driver of HE pathogenesis and the intestinal microbiota is by far its predominant source (Williams, 2007). In particular, Urease-producing bacteria such as Klebsiella and Proteus species seem to play a critical role in increased ammonia production and HE development (Basile & Jones, 1997). In concordance with the concept of HE being a bacterial-driven disease, treatment with nonabsorbable antibiotics such as Neomycin and Rifaximinis is associated with a significant decrease in the risk of breakthrough episodes of HE, relapses, or hospitalization due to this neuropsychiatric complication (Bajaj et al., 2011; Bass et al., 2010; Sidhu et al., 2011). Recently, the role of specific bacterial families in cirrhosis has begun to be addressed. Two studies have performed nonculture-based methods to determine the composition of the microbiota in patients with cirrhosis and HE. Both studies found a higher concentration of Streptococcaceae and a negative correlation between cirrhosis and the abundance of Lachnospiraceae (Bajaj et al., 2012; Chen et al., 2011). Interestingly, Bajaj et al. (2012) found that in addition to changes in the intestinal microbiota between healthy and cirrhotic individuals, there was a significant increase in the abundance of different bacterial families (Enterobacteriaceae, Alcaligenaceae, and Streptococcaceae)in patients with confounded HE. Moreover, a positive correlation between cognitive dysfunction and the presence of Alcaligenaceae and Porphyromonadaceae was observed by standardized cognitive testing (Bajaj et al., 2012). The investigation of the gut microbiome in cirrhosis and its correlation to severe clinical

89 80 Jorge Henao-Mejia et al. complications is still in its early stages, but identification of bacterial species that specifically drives disease progression will greatly improve our understanding of the pathogenesis of these complex human diseases Hepatocellular carcinoma HCC is one of the most frequent human cancers worldwide. Approximately 80 90% of HCCs are preceded by chronic liver disease, hepatic fibrosis, and cirrhosis (Nordenstedt, White, & El-Serag, 2010). Therefore, it has been speculated that microbial-derived products are essential determinants of HCC progression. Indeed, recent studies performed using a mouse model of HCC showed that hepatocarcinogenesis in chronically injured livers depended on the intestinal microbiota and Toll-like receptor 4 (TLR4) activation in non-bone-marrow-derived resident liver cells. Importantly, TLR4 and the gut microbiota are not required for HCC initiation but for HCC progression as intestinal sterilization restricted late stages of hepatocarcinogenesis (Dapito et al., 2012). The role of the microbiome on human HCC is an unexplored area that warrants further investigation in the following years Autoimmune liver disease Primary sclerosing cholangitis (PSC) is a chronic liver disease characterized by inflammation and eventual obstruction of biliary ducts (Levy & Lindor, 2006). Although the pathogenesis of PSC remains undetermined, intestinal microbiota is considered to be a major factor in its etiology. The role of intestinal bacterial communities in ulcerative colitis (UC) pathogenesis is well characterized. Interestingly, approximately 75% of patients with PSC have UC and nearly 3% of patients with UC have PSC as a concomitant comorbidity (Bambha et al., 2003; Bergquist et al., 2008; Hashimoto et al., 1993; Joo et al., 2009; O Toole et al., 2012; Sano et al., 2011; Ye et al., 2011). Moreover, PSC is more frequent in UC patients with total colonic involvement suggesting a strong positive correlation between intestinal inflammation and PSC development (Joo et al., 2009; O Toole et al., 2012). Several lines of evidence point to the microbiota as a common denominator driving liver and intestinal inflammation in this condition. In the bile of PSC patients, Candida and enteric bacteria such as Escherichia coli are frequently detected (Rudolph et al., 2009). End-stage PSC liver shows

90 The Intestinal Microbiota in Chronic Liver Disease 81 significantly increased expression and activation of critical genes involved in innate immune pathways (Miyake & Yamamoto, 2013). Finally, serum atypical perinuclear antineutrophil cytoplasmic antibodies (panca) are frequently found in patients with PSC (Mulder et al., 1993; Terjung et al., 1998). Recently, the autoantigen of this atypical panca has been reported to be b-tubulin, but perhaps more importantly, panca crossreacts with FtsZ, a bacterial cytoskeletal protein present in all intestinal bacteria (Terjung et al., 2010). Thus, identifying the specific bacterial species that trigger PCS is a clinically relevant problem that deserves further investigation. Primary biliary cirrhosis (PBC) affects approximately 40 per 100,000 people in the United States. PBC is an autoimmune liver disorder characterized by immune cell activation and directed damage of cholangiocytes, which results in cholestasis that ultimately leads to hepatic fibrogenesis and liver failure in 26% of patients within 10 years of diagnosis (Washington, 2007). The presence in the serum of antimitochondrial antibodies (AMAs) is the hallmark of PBC. AMAs are detected in approximately 95% of PBC patients and their cross-reaction with bacterial components is proposed as a critical event for the early pathogenesis of PBC (Bogdanos et al., 2004; Hopf et al., 1989). AMAs have been reported to react with proteins of E. coli isolated from PBC patients (Bogdanos et al., 2004; Hopf et al., 1989). Moreover, IgG3 antibodies in approximately 50% of PBC patients cross-react with b-galactosidase of Lactobacillus delbrueckii, and in 25% of PBC patients, the serum reacts specifically with proteins of Novosphingobium aromaticivorans from stool specimens (Bogdanos et al., 2005; Selmi et al., 2003). Given this association, further study is warranted to determine if modulation of gut microbiota might aid in the treatment of this catastrophic disease. 3. ROLE OF THE INTERACTIONS BETWEEN THE INNATE IMMUNE SYSTEM AND THE INTESTINAL MICROBIOTA ON CHRONIC LIVER DISEASES The complex interplay between the host and its indigenous microflora is mediated by a large array of pattern-recognition receptors (PRRs) of the innate immune system (Carvalho, Aitken, Vijay-Kumar, & Gewirtz, 2012). Originally mainly appreciated for their role in recognizing invading pathogenic microbes and for the initiation of adaptive immune responses, these receptors and their downstream signaling cascades are increasingly regarded

91 82 Jorge Henao-Mejia et al. as pivotal for the recognition of the commensal microbiota. This microbial recognition plays an important role under homeostatic conditions, and dysfunction in innate signaling in the intestine has been associated with aberrant development of the intestinal immune system, failure in maintenance of intestinal epithelial homeostasis and barrier function, and exacerbated intestinal injury (Michelsen & Arditi, 2007). Importantly, this innate sensing function also serves to locally contain the microbiota and to exclude intestinal microorganisms from the systemic circulation (Slack et al., 2009). The innate receptors expressed in the gastrointestinal tract represent the first line of defense against invasion of microorganisms. However, in cases of increased microbial translocation through the gastrointestinal barrier, the liver as first line of defense requires the expression of innate PRRs in order to set in place a secondary surveillance system of microbial products potentially draining from the gastrointestinal tract. Indeed, intrahepatic expression of innate immune receptors has been described for Kupffer cells (Visvanathan et al., 2007), liver sinusoidal endothelial cells (Hosel et al., 2012), hepatic stellate cells (Wang et al., 2009), biliary epithelial cells (Yokoyama et al., 2006), and hepatocytes (Wang et al., 2005). Consequently, the liver has to master a delicate balance between its ability to induce systemic tolerance toward innocuous food particles and occasional translocation of commensal microbial products and its role in promoting inflammation when a persistent microbial stimulus caused by intestinal breech is indicative of systemic microbial spread. In the following sections, we will discuss how hepatic PRR signaling mediates host microbial interactions in this vital organ, and how aberrations in PRR expression and signaling contribute to the molecular etiology of liver disease Toll-like receptors TLRs were the first class of PRRs discovered. They recognize a wide range of microbial ligands, ranging from bacterial and fungal cell wall components to nucleic acid (Kawai & Akira, 2010). TLRs are expressed in a wide variety of liver cells and have long been recognized to be involved in the pathogenesis of liver diseases. In particular, Kupffer cells express high levels of TLR2, TLR3, and TLR4, and respond to LPS stimulation with the production of TNF-a, IL-6, and IFN-g. Moreover, the expression of TLRs has been found on hepatocytes, biliary epithelial cells, hepatic stellate cells, and liver sinusoidal endothelial cells (Miyake & Yamamoto, 2013)(Fig. 3.2). The TLR4 MyD88 NF-kB signaling axis has been found to play a critical role in various pathophysiological settings in the liver, including cirrhosis,

92 The Intestinal Microbiota in Chronic Liver Disease 83 Steatosis Hepatocyte: TLR2-4 Kupffer cell: TLR2-4 Stellate cell: TLR1-9 Inflammatory response in the liver TNF IL-6 LSEC: TLR2 Flux of PRR ligands Enterocytes: NLRP6 Intestinal dysbiosis Figure 3.2 Multiple layers of pattern-recognition receptor involvement in the pathogenesis of liver disease. Functional expression of the NLRP6 inflammasome in the intestine is necessary to avoid dysbiosis. Chronic intestinal inflammation is associated with increased translocation of microbes across the gastrointestinal tract and influx of microbial products into the liver. There, TLR expression on a variety of cell types mediates an aberrant respond to the increased microbial load, initiating an exaggerated inflammatory response that can lead to hepatitis. fibrosis, viral hepatitis, HCC, and fatty liver disease. For instance, in mice on a high-fat diet, TLR4 deficiency ameliorates hepatic steatosis (Li et al., 2011). In addition, signaling through TRIF downstream of TLR4 in Kupffer cells has been shown to promote alcoholic liver disease (Gao et al., 2011). Further, hepatic TLR4 expression is increased in animal models of NASH (Thuy et al., 2008), PSC (Mueller et al., 2011), and PBC (Wang et al., 2005). These animal studies have been supported by genetic data from humans. A polymorphism in the gene encoding TLR4, which attenuates the signaling downstream of the receptor in response to LPS stimulation, has been associated with a decreased risk to develop cirrhosis (Figueroa et al., 2012; Huang et al., 2007). Another TLR which has been repeatedly associated with enhanced severity of inflammatory liver disease is TLR9, which signals through IRF-7 to induce the expression of type I interferons (IFNs). Interestingly, type I IFNs

93 84 Jorge Henao-Mejia et al. were recently described to protect from TLR9-associated liver damage, and this effect was mediated by the endogenous IL-1 receptor antagonist (Petrasek, Dolganiuc, Csak, Kurt-Jones, & Szabo, 2011). The same authors also found a protective role for type I IFNs in a TLR4-driven model of alcoholic liver disease (Petrasek, Dolganiuc, Csak, Nath, et al., 2011). The involvement of TLRs in a multitude of liver pathologies clearly implied a role for increased microbial translocation across the gastrointestinal tract and hepatic recognition of microbial products (Fig. 3.2), but direct evidence for this notion has been lacking until recently. First insight came from a study by Seki et al. who showed an involvement of the microbiota in the development of hepatic fibrosis. Antibiotic treatment, as well as TLR4- or MyD88-deficiency, reduced fibrosis after bile duct ligation. TLR4 expression on hepatic stellate cells led to enhanced TGF-b signaling and recruitment of Kupffer cells to the fibrotic liver (Seki et al., 2007). As detailed below, we recently described that, under conditions of intestinal inflammation, the influx of microbial products into the liver promotes the development and progression of NAFLD in a TLR4- and TLR9-dependent manner (Henao-Mejia, Elinav, Jin, et al., 2012). In concordance with these results, Lin et al. recently used the concanavalin A (ConA) model of fulminant liver injury to demonstrate that the intestinal microbiota is critically involved in TLR4-mediated hepatitis. Treatment of mice with broad-spectrum antibiotics as well as TLR4 deficiency greatly ameliorated liver damage, as evidenced by reduced release of aminotransferases into the blood, dampened production of proinflammatory cytokines, and decreased hepatic cell death (Lin et al., 2012). In contrast, administration of purified LPS potentiated liver pathology in the ConA model. Adoptive transfer experiments using TLR4-deficient or sufficient splenocytes revealed that immune cells contribute to disease progression through TLR4 expression Inflammasomes Inflammasomes are a group of cytosolic multiprotein complexes, classically consisting of an upstream sensor protein of the NOD-like receptor (NLR) family, the adaptor protein ASC, and the downstream effector caspase-1 (Henao-Mejia, Elinav, Strowig, & Flavell, 2012). To date, the NLR proteins NLRP1, NLRP2, NLRP3, NLRP6, NLRP7, NLRC4, and the HIN-200 family member AIM2 have been reported to initiate the formation of an inflammasome. Upon stimulation with a diverse set of microbial

94 The Intestinal Microbiota in Chronic Liver Disease 85 or damage-associated molecular patterns, inflammasome assembly leads to the autocatalytic cleavage of caspase-1 and processing of pro-il-1b and pro-il-18 into their mature and bioactive forms (Strowig, Henao-Mejia, Elinav, & Flavell, 2012). Inflammasome activity is thought to require two sequential stimuli. The first stimulus drives transcription of the proforms of IL-1b and IL-18, while the second stimulus is required for the formation of the inflammasome complex (Latz, 2010). Inflammasomes fulfill a dual role, recognizing both endogenous damage-associated substances such as ATP or crystal particles and initiating immune responses in reaction to pathogen-associated molecular patterns during bacterial, viral, fungal, and parasitic infections (Elinav, Strowig, Henao-Mejia, & Flavell, 2011). In addition, the inflammasomes are critically involved in the complex interplay between the intestinal immune system and the gut microbiota, which will be covered in more detail below. Recently, inflammasomes were identified to play a role in the pathogenesis of liver disease. Inflammasome components are expressed by various cell types in the liver. Kupffer cells and sinusoidal endothelial cells express high level of NLRP1, NLRP3, and AIM2, and hepatocytes upregulate NLRP3 expression in an LPS-dependent manner (Boaru, Borkham-Kamphorst, Tihaa, Haas, & Weiskirchen, 2012). Imaeda et al. (2009) initially demonstrated an involvement of the NLRP3 inflammasome in the development of acetaminophen-induced hepatotoxicity and showed reduced mortality in acetaminophen-treated mice lacking any component of the NLRP3 inflammasome, although others could not find a role for NLRP3 in acetaminophen-mediated liver failure (Williams, Farhood, & Jaeschke, 2010). Watanabe et al. (2009) revealed expression of inflammasome components in hepatic stellate cells and demonstrated an involvement of the inflammasome in a mouse model of liver fibrosis using carbon tetrachloride or thioacetamide. Similarly, knockdown of NLRP3 ameliorated liver inflammation and protected ischemia reperfusion injury in mice by preventing excessive production of inflammatory cytokines and NF-kB activity (Zhu et al., 2011). These early studies mainly focused on the role of the inflammasome in the response against tissue damage in sterile injury-mediated models of liver disease. Subsequent reports, however, have also demonstrated an involvement of the inflammasome in liver pathology caused by microbial components or live microorganisms, such as in a model of Propionibacterium acnes-induced sensitization to LPS-induced liver injury (Tsutsui, Imamura, Fujimoto, & Nakanishi, 2010) and in Schistosoma mansoni infection (Ritter et al., 2010).

95 86 Jorge Henao-Mejia et al. In these studies, a cooperative behavior of TLR signaling and inflammasome activation was noticed to be a driving force in the development of overt liver inflammation, suggesting concerted recognition events of microbial- and damage-associated molecules. Interestingly, Csak et al. (2011) recently showed an involvement of the NLRP3 inflammasome in the development and progression of NASH. Upon induction of a mouse model of NASH, expression of inflammasome components was upregulated in the liver and inflammasome activation occurred in isolated hepatocytes. Mechanistically, palmitic acid, a saturated fatty acid, was found to activate the inflammasome and sensitized hepatocytes to IL-1b secretion in response to LPS. The results from this study indicated that both microbial and nonmicrobial PRR ligands act in concert to induce pathogenic inflammasome responses in the liver. A later study confirmed NLRP3 activation in the liver and showed that LPS stimulation alone is sufficient to drive hepatic production of inflammatory cytokines downstream of NLRP3 inflammasome activation (Ganz, Csak, Nath, & Szabo, 2011) C-type lectins C-type lectin (CTL) receptors and their downstream adaptor molecules are mediating recognition of glycosylated ligands on microorganisms (Sancho & Reis e Sousa, 2012). Dectin-1 and 2 are two CTLs involved in the immune response against fungal pathogens. The recognition of fungal-associated molecular patterns elicits a downstream cascade through the signaling molecules caspase recruitment domain-containing protein 9 (CARD9) and Syk (Kerrigan & Brown, 2011). A recent study found hepatic mrna expression in humans of many factors involved in CTL signaling, including Dectin-1, Syk, and CARD9 (Lech et al., 2012). Interestingly, CARD9, which is known as a susceptibility locus in inflammatory bowel disease (IBD), has recently been associated with PSC, along with Rel and IL-2, two other IBD risk loci (Janse et al., 2011). Rel is a member of the NF-kB family of transcription factors, CARD9 induces NF-kB signaling, and IL-2 is an NF-kB target gene, potentially combining all three susceptibility loci into one pathway. The involvement of three members of a fungal recognition pathway in PSC implies a functional role of innate immune recognition of fungal microorganisms in the pathogenesis of this disease. CARD9 is essential for the control of fungal infection, and CARD9-deficient mice show high rates of

96 The Intestinal Microbiota in Chronic Liver Disease 87 early mortality after infection with Candida albicans (Gross et al., 2006). As mentioned above, Candida is detected in the bile fluid of 1 in every 10 PSC patients. In most cases, the detection of fungi in the bile negatively influences the prognosis on disease severity (Rudolph et al., 2009). Functional studies are needed in the future to delineate the mechanisms and the importance of host fungal interactions in the pathophysiology of liver disease. Intriguingly, the recently suggested link between alterations in commensal fungal sensing and susceptibility to IBD may potentially provide a mechanistic explanation for the substantial susceptibility for PSC among chronic IBD patients (Iliev et al., 2012). Taken together, the involvement of PRRs of the innate immune system in the pathogenesis of inflammatory liver disease has so far been interpreted in the context of local responses to endogenous signal of damage. While PRR-mediated recognition of damage-associated molecular patterns certainly plays a critical role in disease development and progression, recent evidence indicates that one should also consider microbial ligands as drivers in hepatic inflammatory disorders Dysbiosis associated with innate immune deficiency and its implications for liver disease The cases described above are examples of a liver-intrinsic role of microbial recognition and its association with disease pathogenesis. Recent studies, however, point to a new role of extrahepatic innate immune-microbial cross talk in the initiation and progression of liver disease. First evidence came from a report demonstrating that mice lacking TLR5, the receptor recognizing bacterial flagellin, develop features of metabolic syndrome as a consequence of altered microbial composition in the gut (Vijay-Kumar et al., 2010). Although a recent study has argued that familial transmission, rather than genetic deficiency, might be the dominant driver of dysbiosis in mice (Ubeda et al., 2012), the intriguing notion that defective host microbiome interactions in the intestine might have consequences that are not limited to regulating inflammation in the gastrointestinal tract, but rather affect systemic metabolism and liver disease, has prompted further investigation. We recently found that the intestinal tracts of mice deficient in the inflammasome components NLRP3, NLRP6, ASC, and Caspase-1, as well as mice lacking the downstream effector cytokine IL-18, harbor an aberrant microbial community which is characterized by the overrepresentation of anaerobic bacterial species of the Prevotellaceae family and the candidate phylum TM7 (Elinav, Strowig, Kau, et al., 2011). This indicates that

97 88 Jorge Henao-Mejia et al. inflammasome activity in the intestine is required for the maintenance of a stable microflora composition, partially through the secretion of IL-18. The altered microbiota found in inflammasome-deficient mice was transferable to wildtype mice upon cohousing in the same cage, demonstrating a dominant population effect, and was reversible upon antibiotic treatment. The biogeographical niche enabling the outgrowth of Prevotellaceae seemed to be the area close to the colonic epithelial layer and the colonic crypts, an area which is normally less densely colonized with microbes due to mechanisms involving antimicrobial peptide production and mucus secretion. This altered intestinal flora leads to mild chronic inflammation and greatly predisposes to experimental colitis. Mechanistically, the colitogenic bacteria present in inflammasome-deficient mice leads to enhanced epithelial production of the chemokine CCL5, which in turn recruits proinflammatory immune cell populations to the intestinal lamina propria (Elinav, Strowig, Kau, et al., 2011). Most importantly, however, we found that the inflammatory processes regulated by the colitogenic flora were not limited to the regulation of local immune responses. When inflammasome-deficient mice were fed a methionine/choline-deficient diet, a model commonly used to induce NAFLD, they featured a dramatic outgrowth of bacterial species of the Porphyromonadaceae family and enhanced translocation of microbial products, in particular, TLR4 and TLR9 ligands, to the portal circulation (Henao- Mejia, Elinav, Jin, et al., 2012). Again, this increased microbial translocation across the gastrointestinal tract was dependent on dysbiosis-induced CCL5 production and intestinal inflammation. In the liver, the increased stimulation of TLR4 and TLR9 led to augmented production of TNF-a via MyD88/TRIF signaling, which initiated an inflammatory process leading to the development of NASH. The altered microbiota alone, when transferred from inflammasomedeficient or IL-18-deficient mice to wild-type recipients, was able to enhance susceptibility to NASH in a CCL5-, TLR4-, TLR9-, MyD88/TRIF-, and TNF-dependent manner, demonstrating that dysbiosis, rather than genetic deficiency, was responsible for increased disease susceptibility and that metabolic disease might feature infectious, that is, transmissible microbial, components. Correspondingly, antibiotic treatment of inflammasome-deficient mice fed an MCD diet not only ameliorated NASH severity but also inhibited transmission of the phenotype to wild-type recipients. Moreover, the abnormal microflora also influenced other manifestations of metabolic syndrome in other mouse models of disease. Genetically obese leptin receptor-deficient mice gained markedly more weight when cohoused with inflammasome-deficient mice and so did ASC-deficient

98 The Intestinal Microbiota in Chronic Liver Disease 89 mice and cohoused wild-type mice fed a high-fat diet. Antibiotic treatment reversed not only weight gain but also fasting plasma insulin amounts and glucose intolerance to normal levels, showing the strong influence of the microbial component on systemic metabolic parameters (Henao-Mejia, Elinav, Jin, et al., 2012). These results demonstrated that homeostatic extrahepatic expression of PRRs is necessary to prevent the development of dysbiosis in the gastrointestinal tract, which in turn predisposes to liver disease via the tight anatomical connection between both organ systems (Fig. 3.2). They also provide an example where multistage host microbial interactions via different kinds of PRRs and their downstream signaling are involved in disease progression, both at distal (in this case, inflammasomes) and proximal sites (in this case, TLRs). The changes induced by the colitogenic microflora affect inflammatory processes locally (induction of CCL5 and leukocyte recruitment to the intestine), at the most proximal sites draining the intestine (inflammatory cytokine production in the liver), and even beyond (multiorgan regulation of weight gain and insulin sensitivity). 4. PROBIOTICS AND THEIR POTENTIAL ROLE IN LIVER DISEASE THERAPY The recognition of the importance of dysbiosis in the development and progression of liver disease opens new avenues for the development of therapeutic approaches. Similar to diseases in which a contribution of dysbiosis has long been appreciated, such as IBD, therapeutic intervention with the aim of adjusting the composition of the intestinal microflora might prove a valuable tool in the treatment of liver diseases. Probiotics and prebiotics are actively exploited for their therapeutic effects in IBD (DuPont & DuPont, 2011). Probiotics are live microorganisms given as dietary supplements to modify their relative representation in the intestinal ecosystem, while prebiotics are nondigestible dietary substances which promote the growth of one or more types of microorganisms in the gut, with the aim of increasing their relative abundance in the intestinal microflora. The benefits of pro- and prebiotics include direct effects, such as the increased release of metabolic products, and indirect effects, in particular, through microbe microbe interactions and changes in population dynamics of intestinal microbial communities. Interestingly, the initial studies have demonstrated beneficial effects of probiotic interventions in liver disease. In a rat model of liver damage

99 90 Jorge Henao-Mejia et al. provoked by ischemia reperfusion, intestinal dysbiosis was observed, including the outgrowth of Enterobacteriaceae and a decrease in Bacteroides spp., Lactobacillus spp., and Bifidobacter spp. These changes could be reversed by dietary supplementation with Lactobacillus paracasei, which remarkably led to reduced liver inflammation, as evidenced by ameliorated production of the proinflammatory cytokines IL-1b, IL-6, and TNF-a (Nardone et al., 2010). Similarly, after chemical liver injury, probiotic therapy with Lactobacillus spp. reduced hepatic inflammation by supporting intestinal barrier function and reducing microbial translocation across the gastrointestinal tract (Osman, Adawi, Ahrne, Jeppsson, & Molin, 2007). Interestingly, in our inflammasome dysbiosis mouse model, representation of Lactobacillus was significantly reduced (Elinav, Strowig, Kau, et al., 2011), pointing toward potential involvement of this commensal family in prevention of local mucosal inflammation and the related tendency toward systemic metabolic complications. Indeed, probiotic interventions were shown to influence hepatic metabolism, as was demonstrated in a rat model of high-cholesterol diet, in which Lactobacillus spp. supplementation in the food reduced the levels of cholesterol and triglycerides in the liver (Xie et al., 2011). Further, HE in cirrhotic patients was ameliorated by probiotic therapy leading to decreased representation of E. coli and reduced blood ammonia levels (Liu et al., 2004). Future studies are clearly needed to understand the mechanisms by which dietary manipulation of the intestinal ecosystem exerts its effects on liver metabolism. Gnotobiotic mice represent an excellent tool to study the contribution of individual microorganisms and their metabolic pathways to liver function. 5. CONCLUSIONS The mesenteric lymph node is the first pass organ for nutrients and microbial substances entering the lymph fluid in the intestinal lamina propria. As such, it serves as a key site for tolerance induction to food particles but at the same time acts as a firewall to prevent systemic spread of microorganisms. Similarly, the liver is exposed to all substances leaving the gastrointestinal tract via the portal blood circulation and faces similar challenges balancing tolerance to innocuous particles draining from the intestine and barrier function to potentially harmful microbial substances. In contrast to the mesenteric lymph node, the liver is the body s prime metabolic organ, and any aberrations from the homeostatic state of host microbial interactions in the liver may affect its metabolic functions.

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108 CHAPTER FOUR Intracellular Pathogen Detection by RIG-I-Like Receptors Evelyn Dixit, Jonathan C. Kagan 1 Harvard Medical School and Division of Gastroenterology, Boston Children s Hospital, Boston, Massachusetts, USA 1 Corresponding author: address: jonathan.kagan@childrens.harvard.edu Contents 1. General Principles of the Antiviral Innate Immune Response RLRs are RNA Sensors Common and distinct features of RLRs and their signaling capabilities Structural characteristics of synthetic RLR ligands Viruses Bacteria RIG-I Activation and Receptor Proximal Signal Propagation Regulatory Mechanisms of RIG-I Signaling Regulators of RLR signaling Regulation of RLR signal transduction by subcellular compartmentalization Conclusions and Future Directions 117 Acknowledgments 118 References 118 Abstract The RIG-I-like receptors (RLRs) RIG-I, MDA5, and LGP2 trigger innate immune responses against viralinfections that serveto limitvirus replication and to stimulate adaptive immunity. RLRsare cytosolic sensors for virus-derivedrna and thusresponsible for intracellular immune surveillance against infection. RLR signaling requires the adapter protein MAVS to induce type I interferon, interferon-stimulated genes, and proinflammatory cytokines. This review focuses on the molecular and cell biological requirements for RLR signal transduction. 1. GENERAL PRINCIPLES OF THE ANTIVIRAL INNATE IMMUNE RESPONSE Viruses are obligate intracellular parasites and thus depend strictly on the biosynthetic machinery of the host in order to replicate and spread. As a result, the virus-driven exploitation of the host cell s metabolic pathways and Advances in Immunology, Volume 117 ISSN # 2013 Elsevier Inc. All rights reserved. 99

109 100 Evelyn Dixit and Jonathan C. Kagan reprogramming of cellular processes often lead to cell death. The struggle for survival between virus and host is ancient and as a consequence both have evolved multiple strategies to antagonize each other. While mammalian hosts developed sophisticated mechanisms of antiviral immunity, viruses acquired strategies to evade the immune response. Therefore, it is critical for the host to mount an effective innate and adaptive immune response immediately upon infection in order to successfully combat the pathogen. The innate immune response constitutes the earliest phase of the host s defense against pathogens and will stimulate and modulate the later onset adaptive response (Palm & Medzhitov, 2009). It operates through a set of germ line-encoded pattern recognition receptors (PRRs) that recognize pathogen-associated molecular patterns (PAMPs) of viruses, bacteria, fungi, and protozoa. PAMPs are conserved within broad classes of pathogens. They are typically products of biosynthetic pathways that are essential for the survival of the pathogen and thus lack the potential for immune evasion through genetic variability (Medzhitov, 2007). Owing to the panel of PAMPs that is recognized by PRRs, the innate immune system achieves an impressively complete coverage of pathogens despite the genetically limited number of available receptors. Engagement of antiviral PRRs by their cognate PAMPs activates signaling pathways that lead to the production of defense factors such as proinflammatory cytokines, type I interferons (IFN-a and IFN-b), or interferon-stimulated genes (ISGs). ISGs induced by IFN secretion or cell-autonomously upon viral infection collectively establish an antiviral state that limits viral replication and prevents further spread of the infection (Katze, He, & Gale, 2002). Detection of viruses poses a particular challenge to the host as they lack features in line with the postulated characteristics of PAMPs, that is, invariant structures required for survival. With few exceptions, viral proteins are highly variable without being functionally compromised by mutation. Moreover, viruses are obligate parasites relying on the host metabolism for their replication. The evolutionary solution to this problem is to recognize viral nucleic acids, either virus genomes or replication intermediates. Undoubtedly, nucleic acid is not a PAMP that is unique to viruses and thus virus detection comes at the cost of the potential for autoimmunity (Barton & Kagan, 2009). Nucleic acid detection is accomplished by a growing list of PRRs, namely, the cytosolic RIG-I-like receptors (RLRs) RIG-I and MDA5 (Yoneyama et al., 2005, 2004); the endosomal Toll-like receptors TLR3, TLR7/8, TLR9, and TLR13 (Kawai & Akira, 2010); the Ifi16/ cgas/sting axis (Ishikawa, Ma, & Barber, 2009; Sun, Wu, Du, Chen, &

110 RIG-I-Like Receptor Signaling 101 Chen, 2012; Unterholzner et al., 2010; Wu et al., 2012); and the AIM2 inflammasome (Burckstummer et al., 2009; Fernandes-Alnemri, Yu, Datta, Wu, & Alnemri, 2009; Hornung et al., 2009; Roberts et al., 2009). This review will focus on virus-induced signaling by RLRs; nucleic acid sensing by other receptor families is reviewed elsewhere (Barbalat, Ewald, Mouchess, & Barton, 2011). 2. RLRs ARE RNA SENSORS 2.1. Common and distinct features of RLRs and their signaling capabilities RLRs detect RNA derived from RNA viruses and in some instances DNA viruses. In terms of specificity and signaling output, RLRs are most similar to TLR3, as both detect viral RNA and induce ISGs, type I IFN, and proinflammatory cytokines (Alexopoulou, Holt, Medzhitov, & Flavell, 2001; Matsumoto et al., 2003; Schulz et al., 2005). However, there is a fundamental conceptual difference in nucleic acid detection between TLRs and RLRs. The nucleic acid-specific endosomal TLRs TLR3, TLR7/8, and TLR9 recognize extracellular nucleic acids having reached the endosomes through endocytosis (Takeda & Akira, 2005), whereas RLRs are cytosolic receptors required for detection of intracellular viral RNA from actively replicating viruses (Kawai & Akira, 2006). As such, RLRs represent an indispensable means for determining if a given cell is infected or not. In line with this key role in antiviral immunity, RLR signaling operates in most cell types. In contrast, TLR expression is restricted to specialized immune cells such as macrophages and dendritic cells. Even though RLRs are expressed in plasmacytoid dendritic cells, TLRs but not RLRs are required for IFN-a production in this cell type (Kato et al., 2005). Three highly related proteins constitute the family of RLRs: the founding member RIG-I, MDA5, and LGP2. They are characterized by a central ATPase containing DExD/H box helicase domain. RIG-I and MDA5 contain N-terminal tandem CARD domains that mediate downstream signaling, whereas LGP2 lacks a CARD (Yoneyama et al., 2005, 2004). RIG-I and LGP2 also harbor a repressor domain (RD) in their C-terminal regulatory domains (CTDs) (Fig. 4.1). Due to the presence of the RD in RIG-I, its overexpression in the absence of an activating ligand does not result in signaling, whereas MDA5 overexpression is sufficient to activate the pathway. In accordance with their domain architecture, RLRs lacking the CARDs have a dominant negative phenotype. RIG-I devoid of

111 102 Evelyn Dixit and Jonathan C. Kagan RIG-I CARD CARD ATPase/helicase RD/CTD MDA5 CARD CARD ATPase/helicase RD-like LGP2 11 ATPase/helicase RD/CTD MAVS CARD Pro TM Figure 4.1 Domain architecture of RLRs and MAVS. Domain boundaries are indicated for human RIG-I, MDA5, LGP2, and MAVS proteins according to Note that MDA5 harbors an RD-like domain in the C-terminus that does not participate in autoregulation. the CTD or the N-terminal fragment comprising solely the CARDs signal constitutively (Cui et al., 2008; Saito et al., 2007; Takahasi et al., 2008). All RLRs are present at low levels in resting cells, but their expression is strongly induced by type I IFN creating a feed forward loop for a robust antiviral response (Kang et al., 2004; Yoneyama et al., 2005, 2004). Despite different ligand specificities for viral RNA, both RIG-I and MDA5 rely on the same signaling cascade to trigger the expression of type I IFNs, ISGs, and proinflammatory cytokines (Yoneyama et al., 2005). The adapter protein MAVS (also known as IPS-1, VISA, and Cardif ) (Kawai et al., 2005; Meylan et al., 2005; Seth, Sun, Ea, & Chen, 2005; Xu et al., 2005) acts immediately downstream of the receptors and represents a node from which RLR signaling branches in several directions in order to promote the activation of NF-kB through the canonical IKKs, IKK-a, IKK-b, and IKK-g, of ATF2/c-jun through MAPK activation and most importantly of members of the interferon regulatory factor (IRF) family of transcription factors (Kawai et al., 2005; Meylan et al., 2005; Mikkelsen et al., 2009; Poeck et al., 2010; Seth et al., 2005; Xu et al., 2005). IRF3 and IRF7 are the essential transcription factors for IFN-b gene transcription, as activation of NF-kB and ATF-2/c-Jun alone is not sufficient for IFN-b induction. Interestingly, in dendritic cells, IRF5 can also function to promote IFN-b expression (Lazear et al., 2013). They reside in the cytosol in their latent forms until viral infection activates the noncanonical IKKs, TBK1 and IKK-i. Phosphorylation of IRF3 and IRF7 by these kinases causes hetero- or homodimerization and nuclear translocation. IRF3 and/or IRF7, NF-kB, and ATF-2/c-Jun together with

112 RIG-I-Like Receptor Signaling 103 the transcriptional coactivator CBP/p300 and the architectural protein HMG I(Y) assemble in an enhanceosome to direct IFN-b transcription (Hiscott, 2007; Honda, Takaoka, & Taniguchi, 2006) (Fig. 4.2). Once IFN-b is secreted, it binds to the IFN-a/b receptor (IFNAR) in an autocrine and paracrine manner resulting in JAK-STAT signaling and thus expression of several hundred ISGs by the ISGF3 transcription factor, which consists of STAT1, STAT2, and IRF9 (Platanias, 2005). However, despite their namesake, ISGs may also be induced independent of a preceding secretion of type I IFN (Collins, Noyce, & Mossman, 2004; Mossman et al., 2001). Influenza virus NDV SeV VSV HCV JEV TRIM25 Riplet RNF125 PKC-a/b P P P RIG-I NLRX1 WNV Dengue virus Reovirus MAVS MDA-5 EMCV Theiler s virus Cytoplasm IKK-i TBK1 IKK-a IKK-b IKK-g MAPKs? IRF3/7 NF-kB ATF2/c-Jun Type I IFN Cytokines ISGs Nucleus Figure 4.2 RLR signaling on a glance. The repertoire of viruses detected by RIG-I and MDA5, respectively, reflects their different ligand specificities. Both receptors use common signaling components to activate three sets of transcription factors required for expression of type I IFN, proinflammatory cytokines, and ISGs.

113 104 Evelyn Dixit and Jonathan C. Kagan Many ISGs function as direct antiviral effectors, acting to prevent viral genome replication, viral particle assembly, or virion release from infected cells. Others encode components of signaling pathways such as receptors for pathogen recognition or transcription factors resulting in a stronger IFN response and thereby creating a positive feedback loop. The role of LGP2 in antiviral immunity is less clear. LGP2 lacks a CARD domain (Fig. 4.1). Devoid of a signaling domain, LGP2 was proposed to be a negative regulator of RLR signaling. Overexpression of LGP2 does not activate IFN-b induction. On the contrary, reduced IRF3 activation was observed when LGP2 overexpressing cells were infected with Newcastle disease virus (NDV) (Rothenfusser et al., 2005; Yoneyama et al., 2005). In vivo experiments with different lines of LGP2-deficient mice strongly contradict the previous data generated by in vitro studies and implicate LGP2 as a positive regulator (Satoh et al., 2010; Venkataraman et al., 2007). In the absence of LGP2, both RIG-I and particularly MDA5-dependent responses to RNA virus infection are impaired, whereas responses to synthetic ligands of these RLRs are unaffected (Satoh et al., 2010). Presumably, LGP2 facilitates binding of viral RNA potentially in complex with protein to its cognate receptor, whereas the affinity of RIG-I and MDA5 is sufficiently strong to bind to naked synthetic agonists. Structural analysis of the binding interface of RNA with the CTD of RIG-I supports this model, as it predicts weaker affinity of MDA5 than RIG-I to its ligand (Takahasi et al., 2009). In addition to confirming the role of LGP2 as a positive, yet nonessential regulator of RLR signaling, a recent report implicates LGP2 as a cell-intrinsic regulator of virus-specific CD8 þ T cell survival and effector functions. CD8 þ T cells are crucial for controlling West Nile virus (WNV) pathology in the brain. LGP2-deficient mice displayed higher viral burden and significantly lower WNV-specific CD8 þ T cells in the brain leading to increased mortality as compared to wild-type animals (Suthar et al., 2012). Nonetheless, further clarification is required to determine the role of LGP2 in RLR signaling Structural characteristics of synthetic RLR ligands The two best characterized RLRs, RIG-I and MDA5, recognize structurally distinct RNA species that have reached the cytosol by infection or by means of transfection. Being cytosolic receptors, RIG-I and MDA5 do not respond to extracellular nucleic acid.

114 RIG-I-Like Receptor Signaling 105 The RIG-I ligand comprises an RNA molecule with two features: (i) a 5 0 -triphosphate (Hornung et al., 2006; Pichlmair et al., 2006) and (ii) base pairing at the 5 0 -end due to secondary RNA structures such as hairpin or panhandle conformations (Schlee et al., 2009; Schmidt et al., 2009). Studies aimed at the characterization of molecular features of the RIG-I ligand largely rely on in vitro transcripts. In vitro-transcribed RNA by all known RNA polymerases leavesatriphosphate at the 5 0 endofthe transcript(ppprna)(schlee& Hartmann, 2010). Transfection of ppprna into monocytes resulted in robust IFN-a secretion, whereas RNA lacking a triphosphate did not (Hornung et al., 2006). Similarly, highly immunogenic RNA extracted from influenza-infected cells was rendered nonstimulatory after phosphatase treatment (Pichlmair et al., 2006). However, a 5 0 -triphosphate alone is not sufficient to mark a singlestranded (ss) RNA molecule as nonself and to render it immunogenic. In support of this notion, synthetic 5 0 -triphosphate-ssrna did not activate RIG-I signaling. In contrast, when the same ssrna molecule was generated by in vitro transcription, it was stimulatory. Reverse cloning and sequencing of the latter RNA species revealed the presence of sequences generated by selfcoding intramolecular 3 0 -extension leading to blunt-ended RNA with complementary and 3 0 -ends. Thus, aberrant in vitro transcription products are responsible for the immunostimulatory properties of such preparations. The minimal length of the 5 0 -base paired region was found to be 19 bp. Furthermore, a 3 0 -overhang of 2 nt reduced the stimulatory activity by 70%, while no 5 0 -overhang was tolerated (Schlee et al., 2009). Alternative to 5 0 -base pairing, sequence composition may contribute to the stimulatory potential of ppprna. Hepatitis C virus (HCV) genomic ssrna is characterized by polyuridine motifs with interspersed C nucleotides (referred to as poly-u/ UC motifs) anda 5 0 -triphosphate.deletionof thepoly-u/uc motifabrogated the stimulatory activity of HCV genomic RNA (Saito, Owen, Jiang, Marcotrigiano, & Gale, 2008; Uzri & Gehrke, 2009). Thus, both panhandle structures and poly-u/uc may serve as a secondary PAMP for ppprna. However, short synthetic double-stranded (ds) RNA without a triphosphate was reported to activate RIG-I as well (Kato et al., 2008; Takahasi et al., 2008). Notably, the antiviral protein RNaseL can cleave ssrna of virus or host origin and thereby generate short (200 nt) ligands devoid of a 5 0 -triphosphate for RIG-I and MDA5 (Malathi, Dong, Gale, & Silverman, 2007). The structural features responsible for the immunogenicity of RNaseL-generated ligands have not been identified. The molecular nature of the MDA5 ligand remains poorly characterized. The stereotypic MDA5 agonist is polyi:c (Gitlin et al., 2006;

115 106 Evelyn Dixit and Jonathan C. Kagan Kato et al., 2006), a synthetic RNA molecule lacking 5 0 -triphosphates that is generated by the annealing of poly-inosine strands to poly-cytidine strands of various lengths. Thus, polyi:c contains an ill-defined mix of ramified ds and ssrna. Size fractionation of polyi:c revealed that MDA5 responds to high-molecular-weight (HMW) polyi:c, whereas polyi:c shorter than 1000 nucleotides acts as a RIG-I agonist (Kato et al., 2008). Size fractionation of total RNA isolated from encephalomyocarditis virus (EMCV)- infected cells yielded a prominent dsrna fraction of 11 kb and an even larger-molecular-weight RNA aggregate with variable ss and dsrna content. Of note only the RNA aggregate, but not the dsrna, stimulated MDA5 activity. Furthermore, this fraction required its intact secondary and tertiary structure to remain fully active (Pichlmair et al., 2009). Thus, MDA5 preferentially binds to HMW dsrna that presumably adopts a web-like conformation much like the synthetic RNA analog polyi:c Viruses The structural features of viral RNA that are displayed by a given virus depend on its replication cycle. As a consequence, the different ligand specificities of RIG-I and MDA5 are reflected by the largely nonoverlapping pattern of virus susceptibility of mice deficient in either of the two RLRs. RIG-I is required for innate responses to many ssrna viruses. The best-studied examples among these are the negative-stranded viruses of the orthomyxoviridae, for example, influenza A and B virus, paramyxoviridae, for example, NDV, Sendai virus (SeV), respiratory syncytial virus, and measles virus, and rhabdoviridae, for example, vesicular stomatitis virus (VSV) and rabies virus (Hornung et al., 2006; Kato et al., 2006; Loo et al., 2008; Plumet et al., 2007). Moreover, detection of positive-stranded flaviviruses including HCV and Japanese encephalitis virus is RIG-I dependent (Kato et al., 2006; Saito et al., 2007; Sumpter et al., 2005). In addition, recognition of cytoplasmic DNA can also feed into the RIG-I pathway. RIG-I does not detect DNA directly but can do so after RNA polymerase III-mediated transcription of AT-rich DNA. IFN induction in response to infection with DNA viruses such as adenovirus, herpes simplex virus-1, and Epstein Barr virus relies on this pathway (Ablasser et al., 2009; Chiu, Macmillan, & Chen, 2009; Samanta, Iwakiri, Kanda, Imaizumi, & Takada, 2006). MDA5 is required for protection against picornaviruses such as EMCV, Theiler s virus, mengovirus, murine norovirus, and murine hepatitis virus (Gitlin

116 RIG-I-Like Receptor Signaling 107 et al., 2006; Kato et al., 2006; McCartney et al., 2008; Roth-Cross, Bender, & Weiss, 2008). Similar to RIG-I, MDA5 has also been implicated in DNA virus detection. Vaccinia virus, a dsdna virus of the poxvirus family, activates MDA5 via a yet-to-be-characterized mechanism (Pichlmair et al., 2009). Some viruses such as WNV, Dengue virus, reovirus, and lymphocytic choriomeningitis virus (Fredericksen, Keller, Fornek, Katze, & Gale, 2008; Loo et al., 2008; Zhou et al., 2010) triggerboth RIG-I- and MDA5-dependent innate immune responses. RLR dependence of the aforementioned viruses was determined by infection of different RLR-deficient cell types or mice with purified virions and is summarized in Table 4.1. Table 4.1 RIG-I and MDA5 detect different sets of viruses Viruses detected by RIG-I Orthomyxoviridae ( ) ssrna, NS Paramyxoviridae ( ) ssrna, NS Rhabdoviridae ( ) ssrna, NS Flaviviridae (þ) ssrna NS Influenza A virus Kato et al. (2006) Influenza B virus Loo et al. (2008) Sendai virus Kato et al. (2006) Newcastle disease virus Kato et al. (2006) Respiratory syncytial virus Loo et al. (2008) Measles virus Plumet et al. (2007) Vesicular stomatitis virus Kato et al. (2006) Rabies virus Hornung et al. (2006) Hepatitis C virus Japanese encephalitis virus Saito et al. (2007) and Sumpter et al. (2005) Kato et al. (2006) dsdna-viruses Epstein Barr virus Ablasser et al. (2009), Chiu et al. (2009), and Samanta et al. (2006) Herpes simplex virus-1 Chiu et al. (2009) Adenovirus Chiu et al. (2009) Continued

117 108 Evelyn Dixit and Jonathan C. Kagan Table 4.1 RIG-I and MDA5 detect different sets of viruses cont'd Viruses detected by MDA5 Picornaviridae (þ) ssrna, NS Caliciviridae (þ) ssrna, NS Coronaviridae (þ) ssrna NS Encephalomyocarditis virus Gitlin et al. (2006) and Kato et al. (2006) Theiler s virus Kato et al. (2006) Mengovirus Kato et al. (2006) Murine norovirus-1 McCartney et al. (2008) Murine hepatitis virus Roth-Cross et al. (2008) Viruses detected by RIG-I and MDA5 Flaviviridae (þ) ssrna, NS Reoviridae dsrna S Arenaviridae ( ) ssrna, S Dengue virus Loo et al. (2008) West Nile virus Fredericksen et al. (2008) and Loo et al. (2008) Reovirus Loo et al. (2008) Lymphocytic choriomeningitis virus Zhou et al. (2010) RLR dependence to various viruses is listed according to virus families. The respective genome type is indicated as single-stranded (ss) or double-stranded (ds) RNA or DNA with negative ( ) or positive (þ) genome orientation featuring segmentation (S) or nonsegmentation (NS) Bacteria Various bacteria including Francisella tularensis, Mycobacteria tuberculosis, Brucella abortis, group B streptococcus (GBS), Listeria monocytogenes, and Legionella pneumophila have been shown to induce type I IFN in a TLR-independent manner (Charrel-Dennis et al., 2008; Henry, Brotcke, Weiss, Thompson, & Monack, 2007; O Riordan, Yi, Gonzales, Lee, & Portnoy, 2002; Opitz et al., 2006; Roux et al., 2007; Stanley, Johndrow, Manzanillo, & Cox, 2007; Stetson & Medzhitov, 2006). While it is well appreciated that viral replication is inhibited by type I IFN, the role of IFN in bacterial infections is less clear; for example, IFN has a protective effect during GBS infection (Mancuso et al., 2007), whereas it is disadvantageous during Listeria infection (Auerbuch, Brockstedt, Meyer-Morse, O Riordan, & Portnoy, 2004; Carrero, Calderon, & Unanue, 2004; O Connell et al., 2004). Even less clear is which bacterial ligands and host receptors trigger IFN secretion.

118 RIG-I-Like Receptor Signaling 109 The intracellular gram-negative bacterium L. pneumophila infects macrophages and causes Legionnaires disease. IFN-b induction in lung epithelial cells and macrophages depends on MAVS (Monroe, McWhirter, & Vance, 2009; Opitz et al., 2006). However, the signaling events upstream of MAVS activation are a matter of debate. Chiu et al. propose that AT-rich DNA reaches the host cytosol and is transcribed into an RNA ligand for RIG-I in an RNA polymerase III-dependent manner (Chiu et al., 2009). In contrast, Monroe et al. argue that the IFN response to Legionella genomic DNA does not require MAVS in mouse macrophages as MAVS-deficient and wild-type macrophages display comparable levels of IFN. Instead, their data support a model where Legionella RNA is directly detected by both RIG-I and MDA5 as macrophages deficient in either receptor display a partial phenotype (Monroe et al., 2009). Shigella flexneri, the causative agent of bacillary dysentery, infects macrophages of the colonic epithelium and rapidly induces cell death by pyroptosis. Escaping bacteria invade colonic epithelial cells where they replicate in the cytosol. Type II IFN-g is critical for inhibiting S. flexneri cytosolic growth. It is at this stage that IFN-g exerts its antimicrobial effect through RIG-I signaling in nonmyeloid cells. Both RIG-I- and MAVSdeficient mouse embryonic fibroblasts (MEFs) failed to restrict IFN-gdependent S. flexneri replication. Inhibition of RNA polymerase III also reduced the antimicrobial effect of IFN-g suggesting that RIG-I signaling is triggered by RNA polymerase III-generated RNA mediates. Interestingly, type I IFN induction is not required for this effect as IFNAR-deficient MEFs that are completely unresponsive to type I IFNs do not impair IFN-gmediated growth inhibition of S. flexneri. In contrast, in primary macrophages, RIG-I signaling is dispensable for IFN-g-mediated growth arrest ( Jehl, Nogueira, Zhang, & Starnbach, 2012). These findings underscore the importance of the interplay of distinct innate immunity pathways in order to successfully combat pathogens. 3. RIG-I ACTIVATION AND RECEPTOR PROXIMAL SIGNAL PROPAGATION RLR activation is a multistage process that requires a well-coordinated interplay of receptor, ligand, and several accessory proteins. In contrast to RIG-I, the specific requirements for efficient MDA5 activation are unclear, but it stands to reason that both proinflammatory RLRs follow a similar mechanism. As exemplified by RIG-I, our current understanding of this

119 110 Evelyn Dixit and Jonathan C. Kagan process involves the following sequence of events: (1) In resting cells, RIG-I adopts a closed conformation resulting in an autoinhibited (nonsignaling) state. (2) ppprna binding to RIG-I induces conformational changes that lead to dimerization and exposure of CARDs in the open conformation. (3) Dephosphorylation of RIG-I and TRIM25-dependent ubiquitination events fully activate the signaling capability of RIG-I. (4) RIG-I associates with MAVS in a CARD-dependent manner. (5). MAVS accumulates in signaling aggregates by a prion-like mechanism. In the absence of infection, RIG-I is kept in an autoinhibited state by intramolecular interactions between the CARDs and the helicase domain, which sterically hinders RNA binding to the helicase domain and prevents the CARDs from signaling (Kowalinski et al., 2011; Saito et al., 2007). Accordingly, the N-terminus of RIG-I comprising the two CARDs has a constitutively active phenotype when overexpressed (Yoneyama et al., 2004). Furthermore, phosphorylation of threonine 170 (and serine 8 in primate orthologs) by PKC-a and PKC-b suppresses RIG-I activity at steady state (Gack, Nistal-Villan, Inn, Garcia-Sastre, & Jung, 2010; Maharaj, Wies, Stoll, & Gack, 2012; Nistal-Villan et al., 2010). Only upon ligand binding does the closed conformation open up to facilitate downstream signaling by the CARDs. Biochemical studies have identified the CTD as the sensor for ppprna. Receptor ligand interactions were examined by measuring ATPase activity of purified deletion mutants of RIG-I lacking the CARDs (DCARD), the CTD (DCTD), or both (helicase) in response to treatment with a panel of RNA ligands derived from the rabies virus leader (RVL) sequence, that is, ppprna (ppprvl), nonphosphorylated ssrna (ssrvl), as well as dsrna (dsrvl). ssrvl did not activate ATPase activity in any of the RIG-I variants. ppprvl strongly stimulated ATPase activity of wild-type RIG-I. Deletion of the CARDs did not interfere with ppprvl-stimulated ATPase activity. Neither the helicase domain alone nor RIG-I lacking the CTD displayed ATPase activity in response to ppprvl. dsrna weakly stimulated wild-type RIG-I and the isolated helicase domain. Of note, dsrna activated DCARD more efficiently than ppprvl achieving ATPase activity levels comparable to wildtype RIG-I in complex with ppprvl. These findings suggest that the CARDs inhibit dsrna binding in an inactive conformation, while CTD promotes ppprvl binding in an active conformation. Further binding studies clearly demonstrated that the ppprna binding site resides within the CTD. X-ray crystallography of the CTD revealed two features that are required for ppprna binding: (1) A zinc coordination site comprising

120 RIG-I-Like Receptor Signaling 111 four highly conserved cytidine residues (C810, C813, C864, C869). These cytidines are conserved in a paralogous and orthologous manner within the family of RLRs. (2) A conserved groove with a positively charged patch at the center of which an RIG-I invariant lysine is located (K888) (Cui et al., 2008). Crystallographic structures of RIG-I give detailed insight into the conformational changes triggered by ligand binding and required for signal initiation. The structural data suggest a model where in the autorepressed state the CTD is devoid of intramolecular interactions and thus can freely engage in ppprna binding. This initial event increases the local RNA concentration and leads to cooperative binding of RNA and ATP to the helicase domain resulting in dramatic rearrangements within the helicase domain that are orchestrated by the pincher domain that connects the helicase domain with the CTD. The helicase domain and the CTD completely surround the RNA clasping onto the helix by numerous intermolecular interactions. This channel covers 9 10 bp along the RNA. Longer RNA molecules allow the binding of two RIG-I monomers simultaneously. However, this apparent dimerization is devoid of a protein protein interface but much rather reflects an RNA-guided oligomerization (Kowalinski et al., 2011; Luo et al., 2011). In line with the structural data of RNA-bound RIG-I, full-length RIG-I but not the DCTD mutant or MDA5 eluted as dimers after gel filtration when incubated with ppprna (Cui et al., 2008). Downstream signaling by ligand-activated RIG-I is achieved by the N-terminal tandem CARDs. Deletion of the CARDs results in a dominant negative phenotype of RIG-I (Yoneyama et al., 2004). Huh7.5 cells, a subpopulation of the hepatocyte cell line Huh7 that is characterized by a threonine to isoleucine mutation at position 55 (T55I) in the first CARD of RIG-I, fail to respond to HCV infection. As a consequence, the absence of a functional antiviral response creates conditions permissive for HCV replication in Huh7.5 (Sumpter et al., 2005). The T55I mutant interferes with the binding of the TRIM25 E3 ubiquitin ligase that is required for activation of RIG-I signaling. Gack et al. demonstrated that TRIM25 binds to the first CARD domain via its SPRY domain. Prerequisite for TRIM25 binding is dephosphorylation of RIG-I at T170 (and S8 in primates) by an unidentified phosphatase. The phosphomimetic mutation T170E abrogated binding of TRIM25 to RIG-I and interfered with downstream signaling events and antiviral activity of RIG-I (Gack et al., 2010). TRIM25 transfers K63-linked ubiquitin moieties to the lysine 172 residue (K172) within the second CARD using its RING domain. Oligomerization of RIG-I with the adapter

121 112 Evelyn Dixit and Jonathan C. Kagan protein MAVS critically depends on this modification. Accordingly, TRIM25-deficient MEFs do not secrete IFN-b after SeV infection. The absence of antiviral defenses is reflected by markedly higher viral titers upon VSV infection (Gack et al., 2007). Although TRIM25 does not attach ubiquitin moieties to MDA5, polyubiquitin binding by MDA5 is required for its signaling functions ( Jiang et al., 2012). The requirement for ubiquitination of RIG-I for initiation of downstream signaling was challenged by a study using a cell-free system to identify the minimal components for RIG-I signal transduction. The RIG-I pathway was reconstituted in a mixture containing affinity-purified RIG-I, crude mitochondria and peroxisomes (containing the adapter MAVS), cytosolic extracts (containing TBK1), in vitro-synthesized transcription factor IRF3, and ATP. RIG-I activation was quantified by measuring dimerization of IRF3, a readout for its activation. With this in vitro assay in place, the authors recapitulated key aspects of RIG-I signaling and revealed new regulatory mechanisms. IRF3 activation required MAVS and TRIM25 as depletion of these proteins by RNAi interfered with IRF3 dimerization. RIG-I needed to be isolated from virus-infected cells, be activated by RNA ligand in vitro, or be present as an N-terminal CARD fragment for IRF3 activation to occur. The ubiquitination machinery responsible for RIG-I activation was shown to be comprising E1, the E2 Ubc5 and Ubc13, and the E3 TRIM25, as the mitochondrial fraction of virus-infected cells depleted from Ubc5 (isoform b and c) and Ubc13 no longer elicited IRF3 dimerization. In line with the notion that Ubc13 is specific for synthesis of lysine 63 (K63)-linked ubiquitin and previous findings on the importance of K63-linked polyubiquitin for RIG-I activation, ubiquitin proteins with a sole lysine residue at position 63 were capable to activate the pathway in the cell-free in vitro system (Zeng et al., 2010). Thus, a requirement for both TRIM25 and K63-linked ubiquitin for IFN-b induction by RIG-I were confirmed in this experimental setup. The major discrepancy between the studies by Gack et al. and Zeng et al. is the attachment of polyubiquitin. While in the former study covalent linkage to the K172 residue of RIG-I was proposed, the latter study suggested that unanchored polyubiquitin chains serve as essential cofactors for RIG-I activation. Two major lines of evidence support this proposition: (1) RIG-I CARDs isolated from E. coli that lack an ubiquitination system-activated IRF3 when ubiquitin polymers were added to the cell-free system. (2) Endogenous polyubiquitin was coprecipitated with RIG-I CARDs from mammalian cells and subsequently recovered from the complex by selective heat denaturation. This preparation promoted IRF3 dimerization, but lost

122 RIG-I-Like Receptor Signaling 113 its activity when treated with the deubiquitination enzyme IsoT. Even though the K172 residue is not required as an acceptor for ubiquitination in this situation, its relevance for RIG-I signaling remains undisputed as it is critical for the binding affinity to polyubiquitin (Zeng et al., 2010). Both RIG-I and MDA5 signaling depends on the adapter protein MAVS to link receptor activity to the downstream kinases TBK1 and IKK-i (Fig. 4.2). MAVS is a 540 aa protein comprising an N-terminal CARD domain, a central proline-rich region (Pro), and a C-terminal transmembrane domain (Seth et al., 2005)(Fig. 4.1). While the transmembrane domain targets the adapter to its proper subcellular locations (mitochondria, peroxisomes, and mitochondria-associated membranes (MAM); see Section 4.2), the CARD domain is required for signaling (Dixit et al., 2010; Horner, Liu, Park, Briley, & Gale, 2011; Seth et al., 2005). When MAVS was initially characterized as an RLR signaling adapter, the authors noted that viral infection results in the formation of detergent-resistant aggregates (Seth et al., 2005). Recent studies by the same group defined these aggregates as highly organized, selfpropagating prion-like fibrils. Using the cell-free system for in vitro reconstitution of RLR signaling as described earlier, complexes of MAVS larger than the 26S proteasome were detected 9 h after SeV infection which coincided with IRF3 dimerization. These complexes displayed several features characteristic for prions: (1) The MAVS CARD is necessary and sufficient for formation of fiber-like structures as determined by electron microscopy. (2) These fibrils are resistant to protease K treatment and detergent solubilization. (3) Protease-resistant fibrils convert MAVS on mitochondria that were extracted from uninfected cells into functional aggregates leading to IRF3 activation. Interestingly, however, these MAVS aggregated did not stain with Congo Red, a dye that typically stains classic prion structures (chen prion paper). Conversely, mitochondria depleted of MAVS by RNAi prior to extraction did not result in IRF3 dimerization. Importantly, MAVS aggregates form within minutes upon activation of RLR signaling in the cell-fee reconstitution assay indicating that prion-like MAVS fibrils are a bona fide determinant of the MAVS activation status (Hou et al., 2011). 4. REGULATORY MECHANISMS OF RIG-I SIGNALING 4.1. Regulators of RLR signaling Several proteins regulate RLR signaling along the pathway in order to tailor the response. Various E3 ubiquitin ligases regulate RIG-I activity. TRIM25 as discussed in Section 3 and Riplet (also known as RNF135 or REUL)

123 114 Evelyn Dixit and Jonathan C. Kagan positively regulate RIG-I activity through K63-linked ubiquitination at its N- or C-terminus, respectively (Gack et al., 2007; Gao et al., 2009; Oshiumi, Matsumoto, Hatakeyama, & Seya, 2009; Oshiumi et al., 2010). In contrast, RNF125 mediates K48-linked ubiquitination that targets RIG-I for degradation and thus acts as a negative regulator (Arimoto et al., 2007). Recently, ZAPS was identified as a cofactor for RIG-I signaling. ZAPS is a member of the poly (ADP-ribose) polymerase (PARP) family but lacks the PARP-like domain present in ZAPS due to alternative splicing. ZAPS was shown to directly associate with RIG-I in a ligand-dependent manner and to amplify downstream signaling events such as activation of the transcription factors IRF3 and NF-kB and induction of type I IFN. As a result, ZAPS inhibited viral replication after infection with RIG-I-dependent viruses such as influenza virus or NDV (Hayakawa et al., 2011). While a continuously growing number of accessory proteins that modify RIG-I signaling activity emerges, the interplay between these proteins, the order in which they act upon RIG-I, and their relative significance for signaling output remain elusive until further systematic studies are done to address these questions. NLRX1 (also known as Nod9) was proposed to control RLR signal transduction at the level of MAVS; however, its role is a matter of debate. NLRX1 was reported to reside at the outer mitochondrial membrane from where it physically disrupts the virus-induced RLR MAVS interaction (Moore et al., 2008)(Fig. 4.2). Alternatively, NLRX1 was found to be localized within the mitochondrial matrix which deems impossible the proposed function as a direct interactor of MAVS to modulate its activity. Rather, it was shown that NLRX1 promotes the generation of reactive oxygen species (ROS) (Arnoult et al., 2009; Tattoli et al., 2008). Interestingly, several lines of evidence implicate ROS as modulators of RLR signaling. Cells deficient in autophagy accumulate dysfunctional mitochondria which entails increased ROS levels and display enhanced RLR signaling. Treatment with antioxidant reverses the effect (Tal et al., 2009). Conversely, mitochondrial uncoupling a process by which ROS generation is decreased reduced RLR signaling (Koshiba, Yasukawa, Yanagi, & Kawabata, 2011). Additional research is required to delineate the mechanism by which ROS regulate RLR-dependent antiviral responses. STING (also known as MITA, MPYS, or ERIS) (Ishikawa & Barber, 2008; Jin et al., 2011; Sun et al., 2009; Zhong et al., 2008) was originally identified as a regulator of RIG-I signaling owing to its ability to directly bind to RIG-I, MAVS, and TBK1 and to its knockout phenotype.

124 RIG-I-Like Receptor Signaling 115 Overexpression of the constitutively active fragment of RIG-I failed to induce IFN in STING-deficient MEFs. Moreover, VSV infection of STING-deficient mice resulted in significantly poorer survival rates and lower type I IFN serum levels relative to control littermates. It is of note that the response to transfected polyi:c remained unchanged in the absence of STING (Ishikawa et al., 2009). While STING was shown to play an undisputed role in the IFN response to cytosolic DNA from viruses or synthetic agonists, its implication in RLR signaling may not be essential Regulation of RLR signal transduction by subcellular compartmentalization All three receptors of the RLR family are cytosolic proteins, and they have not been found to be associated with any subcellular structure at steady state. However, several signaling components downstream of the receptors are membrane proteins whose functional domains project into the cytosol from the surface of the respective organelles. More importantly, proper localization of these proteins is a prerequisite for their biological activity. The best characterized example is the adapter protein MAVS. MAVS resides on the outer mitochondrial membrane (Seth et al., 2005), peroxisomes (Dixit et al., 2010) and MAMs (Horner et al., 2011), a specialized subdomain of the ER that connects mitochondria and peroxisomes (Hayashi, Rizzuto, Hajnoczky, & Su, 2009; Vance, 1990). Both peroxisomal and mitochondrial MAVS signal to induce ISG expression in MEFs. While mitochondrial MAVS induces type I IFN and as a consequence ISG expression in response to reovirus and influenza virus infection, peroxisomal MAVS directly induces ISG expression which creates a transient yet functional antiviral state. The lack of type I IFN induction by peroxisomal MAVS was also observed in macrophages. Unlike MEFs, macrophages upregulate not only expression of ISGs but also proinflammatory cytokines after reovirus infection (Dixit et al., 2010). A different study confirms the localization of MAVS on mitochondria and peroxisomes, and adds MAMs to the list of subcellular pools of MAVS. Moreover, the authors propose the MAM as an innate immune synapse for antiviral responses that coordinates MAVS-dependent signaling from mitochondria and peroxisomes (Horner et al., 2011). HCV-infected Huh7 hepatocytes are unable to induce IFN expression due to MAVS cleavage by the viral protease NS3/4A (Loo et al., 2006; Meylan et al., 2005). Others and we have shown that cytosolic MAVS is unable to signal (Dixit et al., 2010; Seth et al., 2005). Given that NS3/4A cleaves MAM-localized MAVS, but not mitochondrial MAVS, the authors conclude that at least for HCV

125 116 Evelyn Dixit and Jonathan C. Kagan infections mitochondrial MAVS is dispensable for RIG-I signaling. This notion is further supported by the finding that RIG-I is recruited specifically to MAM-resident MAVS upon HCV infection (Horner et al., 2011). In fact, a ternary complex consisting of active open-conformation RIG-I, TRIM25, and the chaperone e is redistributed to MAMs upon infection (Liu et al., 2012). MFN2 tethers the ER to mitochondria and thus maintains the MAM mitochondrial contacts (de Brito & Scorrano, 2008). Depletion of MFN2 by RNAi destabilizes the antiviral synapse, which shifts MAVS to peroxisomes and thereby increases RIG- I-mediated signaling in response to SeV, VSV, and HCV (at early time points before MAVS cleavage by NS3/4A) infection (Horner et al., 2011). It would be interesting to test the effect of MFN2 on the organelle-specific outcome of RLR signaling using cells with organelle-restricted MAVS expression. In addition to MFN2, MFN1 has been implicated in regulation of RIG-I signaling as well. Activation of RLRs by infection with SeV, NDV, influenza virus, VSV, Sindbis virus, or EMCV and by transfection with ppprna resulted in redistribution of mitochondrial MAVS. While some mitochondria accumulate MAVS, others become devoid of it during a process that depends on MFN1. RIG-I is evenly distributed throughout the cytosol in uninfected cells but is concentrated in foci upon infection. However, no colocalization between RIG-I and MAVS was observed. On the contrary, RIG-I colocalized with viral nucleocapsid. As a consequence, type I IFN induction after NDV infection was completely abolished in MFN1-deficient MEFs. These findings led the authors to propose a model where RIG-I is recruited to virus factories to maximize the chances of receptor ligand interaction. Mitochondria serve as vehicles that position MAVS. Some mitochondria enrich MAVS through repeated fission and fusion events and surround the foci of active viral replication in order to enable IFN induction (Onoguchi et al., 2010). While this model outlines how mitochondrial signaling is optimized to perpetuate IFN induction for the duration of infection and to establish a sustained antiviral immune response, it leaves two important questions unanswered. First, what are the kinetics of this process? The earliest time point presented in the study is 9 h postinfection. Second, what triggers mitochondrial remodeling and accumulation of MAVS? Regardless of whether activation of RLR signaling or a different stimulus initiates the rearrangement, this model does not explain RNA detection at the very first instance of virus encounter. Much rather it demands additional and disparate means of RLR signaling that

126 RIG-I-Like Receptor Signaling 117 ensure an immediate antiviral response until MAVS-enriched mitochondria are recruited to the periphery of virus factories. 5. CONCLUSIONS AND FUTURE DIRECTIONS RLR signaling is a crucial pathway for detection of intracellular viruses and mounting protective antiviral defenses. Since the identification of RIG-I and its related proteins MDA5 and LGP2, tremendous progress has been made in terms of the core components of this pathway and the regulatory mechanisms. Still, many open questions remain on the pathogen as well as the host side. What are the biological ligands that arise during a given viral infection? Viral genomes, viral transcripts, or replication intermediates are likely candidates. Do these naturally occurring ligands match the postulated structural features that were identified in vitro? Baum, Sachidanandam, and Garcia-Sastre (2010) sought to characterize such ligands by immunoprecipitation of endogenous RIG-I/RNA complexes from SeV and influenza virus-infected cells and subsequent deep sequencing. Copy-back defective interfering particles were identified as the natural ligand of both SeV and influenza virus. RIG-I also bound to (preferentially short segments of) genomic RNA of influenza virus. This study confirms the requirement for both a 5 0 triphosphate and a panhandle structure for RIG-I activation during SeV and influenza virus infection (Baum et al., 2010). How accessible are these ligands during infection? In the light of coevolution of virus and host, it stands to reason that viral PAMPs are spatially segregated from the respective PRRs. Is RLR-mediated virus detection merely possible by accidental escape of PAMPs or are mechanisms in place that actively sample sites of viral replication? Regarding the host factors required for an effective antiviral response, our understanding of the spatiotemporal control of this pathway is very limited. Despite the designation of RLRs as cytosolic receptors, the signal transduction cascade initiated upon ligand engagement is certainly not cytosolic, but strictly dependent on proper subcellular localization of many components of this pathway. The adaptor protein MAVS resides on and signals distinctively from peroxisomes, MAM, and mitochondria (Dixit et al., 2010; Horner et al., 2011; Seth et al., 2005). The negative regulator NLRX1 is also localized on mitochondria (Moore et al., 2008). In the course of infection, mitochondria are rearranged to surround sites of viral replication in an MFN1-dependent manner. Failure to do so severely abrogates an antiviral response (Onoguchi et al., 2010). What is the benefit for the host of

127 118 Evelyn Dixit and Jonathan C. Kagan such an elaborate subcellular arrangement of a signal transduction pathway? Perhaps, recruitment of molecules concentrated on an organelle might be faster and more energy efficient than recruiting every single molecule independently. Considering the different responses mediated by peroxisomal and mitochondrial MAVS, distribution of this pathway on two organelles might facilitate targeting of factors specifically required for each of the responses. A similar situation can be found with TLR4, the receptor for the prototypical PAMP lipopolysaccharide. Perhaps, a positive regulator of direct ISG induction is only targeted to peroxisomes or an inhibitor of such a signaling pathway is located on mitochondria. The TLR4 pathway exemplifies how the spatial distribution of signaling components governs the signaling output. While plasma membrane-bound TLR4 induces cytokine expression in an MyD88-dependent manner (Medzhitov, Preston-Hurlburt, & Janeway, 1997; Medzhitov et al., 1998), endocytosis of TLR4 induces type I IFN induction in a TRIF-dependent manner (Kagan et al., 2008; Yamamoto et al., 2002). For TLR4 signaling, TRAF3 was proposed to be limited in its mobility. The inability of TRAF3 to be recruited to TLR4 at the plasma membrane necessitates TLR4 to be endocytosed. It is at the endosome that the TRAM TRIF adaptor pair is recruited to engage TRAF 3 and to enable type I IFN signaling (Kagan et al., 2008). Similarly, an essential factor for direct ISG induction may be available exclusively at peroxisomes. Experimental evidence for the organelle-specific presence of regulators of RLR signaling comes from NLRX1. Overexpression of NLRX1 inhibits signaling mediated by mitochondrial MAVS, but not by peroxisomal MAVS (Dixit et al., 2010). The spatial regulation may also be indicative of RLR signaling being a multistage process, wherein in an initial wave a nascent infection is sensed, and in a later phase the process is optimized for a robust response during infection and finally is turned off. In order to address this possibility, kinetic studies rather than late end points after infection would be helpful. ACKNOWLEDGMENTS E. D. is supported by the Erwin Schrödinger Fellowship ( J3295-B22) of the Austrian Science Fund (FWF). The National Institutes of Health grants AI and P30 DK34854 support the work performed in the laboratory of J. K. Dr. J. K. holds an Investigators in the Pathogenesis of Infectious Disease Award from the Burroughs Wellcome Fund. REFERENCES Ablasser, A., Bauernfeind, F., Hartmann, G., Latz, E., Fitzgerald, K. A., & Hornung, V. (2009). RIG-I-dependent sensing of poly(da:dt) through the induction of an RNA polymerase III-transcribed RNA intermediate. Nature Immunology, 10, 1065.

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136 INDEX Note: Page numbers followed by f indicate figures, and t indicate tables. A Activation-induced cytidine deaminase (AID) binding, DSBs and translocations description, 43 expression, off-target activity, 44 transcription of mrna, 43 expression and CSR induction, HTGTS and TC-Seq translocation, in oncogene, physiologic mechanisms, 40 Acute lymphoblastic leukemia (ALL) and B-ALL, 3, 43 description, 3 and T-ALL, 4, 15 16, 43 treatment, 4 Acute myeloid leukemia (AML) chromosomal translocations, 57 description, 3 DNMT3A mutations, 7 MOZ gene, 22 myelodysplastic syndromes (MDS)/-neoplasms (MPN), 3 subtypes, 3 TET proteins, AID. See Activation-induced cytidine deaminase (AID) ALL. See Acute lymphoblastic leukemia (ALL) AML. See Acute myeloid leukemia (AML) Antiviral immunity host cell s metabolic pathways, innate immune response, 100 LGP2 role, 104 nucleic acid detection, PRRs and PAMPs, 100 Arginine methyltransferases, Autoimmune liver disease PBC, 81 PSC, B B lymphocytes AID targets for DSBs initiation, leukemia, 3, 43 RAG1/2 translocation, 53 Bromodomain (BRD)-containing protein family description, 24 development of MM, 24 inhibitors, 24 C Chromatin epigenetic marks, 26 in RAG activity, 42 remodeling complexes, 25 Chromosomal translocations DNA DSB formation (see DNA double-strand breaks (DNA DSBs)) DNA-repair mechanisms C-NHEJ, DDR pathway, 45 NHEJ, 45 high-throughput methods HTGTS, TC-Seq, 52 HTGTS and TC-Seq AID targets, B cells, gene density, transcription, and translocations, nuclear positioning and chromosomal structure, RAG1/2 translocation, pro-b cells, 53 mechanisms, 40 spatial organization of the genome chromosome territories, description, 48, 48f and DNA repair, 49 genome-wide contact analysis, transcription factories, 49 structural landscape chromothripsis,

137 128 Index Chromosomal translocations (Continued ) driver translocations, 57 intra/interchromosomal rearrangements, oncogenes, territories (see Chromosome territories) TET proteins, Chromosome territories functions of, and gene proximity, in situ hybridization approaches, 48 Chromothripsis cancer types, 58 chromosomal rearrangements, genomic disorders, implications, mechanisms, in normal and cancer cells, 59 60, 60f progressive rearrangement model, Chronic liver disease. See Intestinal microbiota, chronic liver disease Chronic lymphocytic leukemia (CLL), 4, 58 Chronic myeloid leukemia (CML) chromosomal proximity, description, 2 3 treatment with Imatinib, 2 3 Cirrhosis, intestinal microbiota description, and HE, liver fibrogenesis, Classical NHEJ (C-NHEJ) in knock-out mouse models/in human patients, 46 multistep DNA-repair process, 46 sequence homology, in translocations and chromosomal integrity, CLL. See Chronic lymphocytic leukemia (CLL) CML. See Chronic myeloid leukemia (CML) C-type lectin (CTL) receptors, D DNA-damage response (DDR) pathway, 45 DNA double-strand breaks (DNA DSBs) AID-initiated DSBs and translocations, fragile sites, nonprogrammed pathologic DSBs, physiologic/pathologic mechanisms, 40 RAG-initiated DSBs and translocations, topoisomerases, 45 DNA methylation aberrant methylation patterns, 6 7 CpG islands, 6 hypomethylation, 6 7 IDH1 and IDH2 proteins, mutations, DNMT3a, 7 PHD-containing proteins, TET proteins, DNA methyltransferase (DNMT) DNMT3A mutations in hematopoietic malignancies, 7, 8f molecular consequence, 7 9 mouse models, 9 prognostic marker, 9 inhibitors, 9 10 DNMT. See DNA methyltransferase (DNMT) Dysbiosis with innate immune deficiency, probiotic interventions, E Epigenetic modulators arginine methyltransferases, BRD-containing protein family, 24 chromatin remodeling complexes, 25 DNA methylation (see DNA methylation) HATs, HDACs, 23 histone demethylases inhibitors (KDMi), 22 histone-modifying complexes and MLL, lysine demethylases (KDMs), 21 H HATs. See Histone acetyl transferases (HATs) HCC. See Hepatocellular carcinoma (HCC) HDACs. See Histone deacetylases (HDACs) Hematopoietic malignancies. See also Leukemia

138 Index 129 DNA methylation, 6 7 DNMT3A mutations, 7 Hepatic encephalopathy (HE) intestinal microbiota, nonculture-based methods, pathogenesis, 79 Hepatocellular carcinoma (HCC), 80 High-throughput genomic translocation sequencing (HTGTS) AID targets, analysis of SNPs, application, clone translocation junctions, gene density, transcription, and translocations, normal mature B cells and pro-b cells, 51 52, 51f RAG1/2 translocation, 53 TC-Seq, 52 Histone acetyl transferases (HATs) family, 22 inhibitors (HATi), monocytic leukemia zinc-finger protein (MOZ), 22 MOZ-related factor (MORF), 22 Histone deacetylases (HDACs) classes, 23 inhibitors (HDACi), 23 transcription role, 23 Histone demethylases inhibitors (KDMi), 22 Histone-modifying complexes, leukemia description, MLL function, PRC1, 17 PRC2, 14 HTGTS. See High-throughput genomic translocation sequencing (HTGTS) I IDH. See Isocitrate dehydrogenase (IDH) IFN. See Interferon (IFN) Inflammasomes components, 85 intestinal tracts of mice deficient, NLRP3, 86 NLR proteins, response against tissue damage, sequential stimuli, Inhibitors BRD, 24 DNMT, 9 10 HAT (HATi), HDAC, 23 histone methyltransferase, 17 KDMi, 22 Innate immunity and intestinal microbiota CTL receptors, dysbiosis, inflammasomes, PRRs, receptors expression, 82 TLRs, PRRs and PAMPs, 100 Interferon (IFN) IFN-a, 101 IFN-b IRF3 and IRF7, LGP2 role, antiviral immunity, 104 IRF (see Interferon regulatory factor (IRF)) type I IFNs, TLR9-associated liver damage, Interferon regulatory factor (IRF) dimerization, IRF3 and IRF7, LGP2 role, antiviral immunity, 104 ubiquitination system-activated IRF3, Intestinal microbiota, chronic liver disease autoimmune liver disease, cirrhosis and associated comorbidities, gastrointestinal tract, 74 HCC, 80 hepatic artery, 74 and innate immune system (see Innate immunity) liver (see Liver) NAFLD (see Nonalcoholic fatty liver disease (NAFLD)) probiotics, IRF. See Interferon regulatory factor (IRF) Isocitrate dehydrogenase (IDH) animal models, 14 as homodimers, 12 13

139 130 Index Isocitrate dehydrogenase (IDH) (Continued ) 2-hydroxyglutarate (2-HG), 13 IDH1 and IDH2 mutations, oncometabolites, role, 13 wild-type, 13 L Leukemia ALL, 3 4 AML, 3 B-ALL/T-ALL, chromosomal translocations, 43 chromosomal proximity, chronic variants, 2 CLL, 4 CML, 2 3 DNA methylation, 6 14 epigenetic modifiers, 19, 20f epigenetics bivalent domains, 25 classes of genes, 5 combinatorial chromatin marks, 26 combinatorial histone marks, definition, 4 DNA methylation, 5 long noncoding RNAs (lncrnas), 26 modulators (see Epigenetic modulators) nuclear architecture, perturbations, 5 6 phenomena, 4, 5 histone-modifying complexes, IDH1 and IDH2 proteins, TET proteins, types, 2 Liver chronic disease (see Intestinal microbiota, chronic liver disease) and gastrointestinal tract, 74 Lysine demethylases (KDMs) amine oxidation and dioxygenases, 21 hydroxylation, 21 in tumorigenesis, 21 M Microbiota. See Intestinal microbiota, chronic liver disease Mitochondria IDH mutations, leukemia, 13 MAM, 113, , MAVS signal, NLRX1, 114 ubiquitination, RIG-I activation, 112 Mitochondria-associated membranes (MAM), 113, , Mixed-lineage leukemia (MLL) COMPASS complexes, description, fusion proteins, genetic perturbations, 14 15, 15f MLL-rearranged leukemias, 18 role of CBX8, 19 MLL. See Mixed-lineage leukemia (MLL) N NAFLD. See Nonalcoholic fatty liver disease (NAFLD) NHEJ. See Nonhomologous DNA end joining (NHEJ) NOD-like receptor (NLR) proteins development and progression, NASH, 86 Kupffer cells and sinusoidal endothelial cells, 85 types, Nonalcoholic fatty liver disease (NAFLD) calorie intake, Western society diets, obesity, prevalence, 75 prevalence of SIBO, 78 primary and secondary, 75 for progression, gut-derived factors, regulation, 75 76, 76f two-hit mechanism, 75 Nonhomologous DNA end joining (NHEJ) C-NHEJ (see Classical NHEJ (C-NHEJ)) description, 45 P PAMPs. See Pathogen-associated molecular patterns (PAMPs) Pathogen-associated molecular patterns (PAMPs) detection of viruses, innate immune system, 100 Pattern recognition receptors (PRRs) homeostatic extrahepatic expression, 89 host and indigenous microflora, innate immune response, 100

140 Index 131 innate receptors expression, 82 nucleic acid detection, TLRs, 82 PBC. See Primary biliary cirrhosis (PBC) Peroxisomes MAVS, 113, RIG-I pathway, 112 Plant homeodomain (PHD)-containing proteins JARID1C, 24 translocation, Polycomb repressive complex 1 (PRC1) histone methyltransferase inhibitors, 17 HSCs maintenance and transformation in vivo, 17 Polycomb repressive complex 2 (PRC2) components, EZH2, 14 15, 15f gene silencing, loss-of-function mutation, mutations, protein ASXL1, 17 and PRC1, 17 T-ALL mutations, as tumor suppressor, 16 PRC1. See Polycomb repressive complex 1 (PRC1) PRC2. See Polycomb repressive complex 2 (PRC2) Primary biliary cirrhosis (PBC) antimitochondrial antibodies (AMAs), 81 autoimmune liver disorder, 81 TLR4 expression, Primary sclerosing cholangitis (PSC) CARD9, microbiota, pathogenesis, 80 TLR4 expression, Probiotics description, 89 interventions, and prebiotics, 89 PRRs. See Pattern recognition receptors (PRRs) PSC. See Primary sclerosing cholangitis (PSC) R RAG. See Recombination-activating genes (RAG) Recombination-activating genes (RAG) DSBs and translocations aberrant RAG activity, mechanisms, 42 off-target RAG activity, recurrent translocations, B-cell lymphomas, 43 V(D)J recombination, in pro-b lymphocytes, 53, RIG-I-like receptors (RLRs) activation adapter protein MAVS, 113 ATPase activity, CARDs and helicase domain, 110 crystallographic structures, 111 description, downstream signaling, TRIM25 and K63-linked ubiquitin, ubiquitination, 112 adapter protein MAVS, domain architecture, , 102f IFN-b transcription, IFN role, bacterial infections, 108 IRF family, , 103f LGP2 role, 104 ligand specificities, MDA5, 104 nucleic acid detection, nucleic acid-specific endosomal TLRs, 101 regulators, RLR signaling adapter protein MAVS, MFN2 and MFN1, NLRX1, 114 STING, ZAPS, RIG-I, MDA5, and LGP2, structural characteristics, type II IFN-g, Shigella flexneri, 109 viruses detection, , 107t RLRs. See RIG-I-like receptors (RLRs) T T-cell acute lymphoblastic leukemia (T-ALL) mutations, Ten-eleven translocation (TET) proteins J-binding proteins, 10 mutations analysis, TET1, 10 TET2 mouse models, 12 TET2 mutations, 11 12

141 132 Index TLRs. See Toll-like receptors (TLRs) Toll-like receptors (TLRs) concanavalin A (ConA) model, 84 expression, 82 microbial translocation, 84 nucleic acid detection, PRRs, 82 and RLRs, 101 TLR9, TLR4 MyD88 NF-kB signaling, TLR4 pathway, Translocation-capture sequencing (TC-Seq) AID targets, description, 52

142 CONTENTS OF RECENT VOLUMES Volume 85 Cumulative Subject Index Volumes Volume 86 Adenosine Deaminase Deficiency: Metabolic Basis of Immune Deficiency and Pulmonary Inflammation Michael R. Blackburn and Rodney E. Kellems Mechanism and Control of V(D)J Recombination Versus Class Switch Recombination: Similarities and Differences Darryll D. Dudley, Jayanta Chaudhuri, Craig H. Bassing, and Frederick W. Alt Isoforms of Terminal Deoxynucleotidyltransferase: Developmental Aspects and Function To-Ha Thai and John F. Kearney Innate Autoimmunity Michael C. Carroll and V. Michael Holers Formation of Bradykinin: A Major Contributor to the Innate Inflammatory Response Kusumam Joseph and Allen P. Kaplan Interleukin-2, Interleukin-15, and Their Roles in Human Natural Killer Cells Brian Becknell and Michael A. Caligiuri Regulation of Antigen Presentation and Cross-Presentation in the Dendritic Cell Network: Facts, Hypothesis, and Immunological Implications Nicholas S. Wilson and Jose A. Villadangos Index Volume 87 Role of the LAT Adaptor in T-Cell Development and T h 2 Differentiation Bernard Malissen, Enrique Aguado, and Marie Malissen The Integration of Conventional and Unconventional T Cells that Characterizes Cell-Mediated Responses Daniel J. Pennington, David Vermijlen, Emma L. Wise, Sarah L. Clarke, Robert E. Tigelaar, and Adrian C. Hayday Negative Regulation of Cytokine and TLR Signalings by SOCS and Others Tetsuji Naka, Minoru Fujimoto, Hiroko Tsutsui, and Akihiko Yoshimura Pathogenic T-Cell Clones in Autoimmune Diabetes: More Lessons from the NOD Mouse Kathryn Haskins The Biology of Human Lymphoid Malignancies Revealed by Gene Expression Profiling Louis M. Staudt and Sandeep Dave New Insights into Alternative Mechanisms of Immune Receptor Diversification Gary W. Litman, John P. Cannon, and Jonathan P. Rast The Repair of DNA Damages/ Modifications During the Maturation of the Immune System: Lessons from Human Primary Immunodeficiency Disorders and Animal Models Patrick Revy, Dietke Buck, Françoise le Deist, and Jean-Pierre de Villartay Antibody Class Switch Recombination: Roles for Switch Sequences and Mismatch Repair Proteins Irene M. Min and Erik Selsing Index 133

143 134 Contents of Recent Volumes Volume 88 CD22: A Multifunctional Receptor That Regulates B Lymphocyte Survival and Signal Transduction Thomas F. Tedder, Jonathan C. Poe, and Karen M. Haas Tetramer Analysis of Human Autoreactive CD4-Positive T Cells Gerald T. Nepom Regulation of Phospholipase C-g2 Networks in B Lymphocytes Masaki Hikida and Tomohiro Kurosaki Role of Human Mast Cells and Basophils in Bronchial Asthma Gianni Marone, Massimo Triggiani, Arturo Genovese, and Amato De Paulis A Novel Recognition System for MHC Class I Molecules Constituted by PIR Toshiyuki Takai Dendritic Cell Biology Francesca Granucci, Maria Foti, and Paola Ricciardi-Castagnoli The Murine Diabetogenic Class II Histocompatibility Molecule I-A g7 : Structural and Functional Properties and Specificity of Peptide Selection Anish Suri and Emil R. Unanue RNAi and RNA-Based Regulation of Immune System Function Dipanjan Chowdhury and Carl D. Novina Index Volume 89 Posttranscriptional Mechanisms Regulating the Inflammatory Response Georg Stoecklin Paul Anderson Negative Signaling in Fc Receptor Complexes Marc Daëron and Renaud Lesourne The Surprising Diversity of Lipid Antigens for CD1-Restricted T Cells D. Branch Moody Lysophospholipids as Mediators of Immunity Debby A. Lin and Joshua A. Boyce Systemic Mastocytosis Jamie Robyn and Dean D. Metcalfe Regulation of Fibrosis by the Immune System Mark L. Lupher, Jr. and W. Michael Gallatin Immunity and Acquired Alterations in Cognition and Emotion: Lessons from SLE Betty Diamond, Czeslawa Kowal, Patricio T. Huerta, Cynthia Aranow, Meggan Mackay, Lorraine A. DeGiorgio, Ji Lee, Antigone Triantafyllopoulou, Joel Cohen-Solal Bruce, and T. Volpe Immunodeficiencies with Autoimmune Consequences Luigi D. Notarangelo, Eleonora Gambineri, and Raffaele Badolato Index Volume 90 Cancer Immunosurveillance and Immunoediting: The Roles of Immunity in Suppressing Tumor Development and Shaping Tumor Immunogenicity Mark J. Smyth, Gavin P. Dunn, and Robert D. Schreiber Mechanisms of Immune Evasion by Tumors Charles G. Drake, Elizabeth Jaffee, and Drew M. Pardoll Development of Antibodies and Chimeric Molecules for Cancer Immunotherapy Thomas A. Waldmann and John C. Morris

144 Contents of Recent Volumes 135 Induction of Tumor Immunity Following Allogeneic Stem Cell Transplantation Catherine J. Wu and Jerome Ritz Vaccination for Treatment and Prevention of Cancer in Animal Models Federica Cavallo, Rienk Offringa, Sjoerd H. van der Burg, Guido Forni, and Cornelis J. M. Melief Unraveling the Complex Relationship Between Cancer Immunity and Autoimmunity: Lessons from Melanoma and Vitiligo Hiroshi Uchi, Rodica Stan, Mary Jo Turk, Manuel E. Engelhorn, Gabrielle A. Rizzuto, Stacie M. Goldberg, Jedd D. Wolchok, and Alan N. Houghton Immunity to Melanoma Antigens: From Self-Tolerance to Immunotherapy Craig L. Slingluff, Jr., Kimberly A. Chianese-Bullock, Timothy N. J. Bullock, William W. Grosh, David W. Mullins, Lisa Nichols, Walter Olson, Gina Petroni, Mark Smolkin, and Victor H. Engelhard Checkpoint Blockade in Cancer Immunotherapy Alan J. Korman, Karl S. Peggs, and James P. Allison Combinatorial Cancer Immunotherapy F. Stephen Hodi and Glenn Dranoff Index Volume 91 A Reappraisal of Humoral Immunity Based on Mechanisms of Antibody-Mediated Protection Against Intracellular Pathogens Arturo Casadevall and Liise-anne Pirofski Accessibility Control of V(D)J Recombination Robin Milley Cobb, Kenneth J. Oestreich, Oleg A. Osipovich, and Eugene M. Oltz Targeting Integrin Structure and Function in Disease Donald E. Staunton, Mark L. Lupher, Robert Liddington, and W. Michael Gallatin Endogenous TLR Ligands and Autoimmunity Hermann Wagner Genetic Analysis of Innate Immunity Kasper Hoebe, Zhengfan Jiang, Koichi Tabeta, Xin Du, Philippe Georgel, Karine Crozat, and Bruce Beutler TIM Family of Genes in Immunity and Tolerance Vijay K. Kuchroo, Jennifer Hartt Meyers, Dale T. Umetsu, and Rosemarie H. DeKruyff Inhibition of Inflammatory Responses by Leukocyte Ig-Like Receptors Howard R. Katz Index Volume 92 Systemic Lupus Erythematosus: Multiple Immunological Phenotypes in a Complex Genetic Disease Anna-Marie Fairhurst, Amy E. Wandstrat, and Edward K. Wakeland Avian Models with Spontaneous Autoimmune Diseases Georg Wick, Leif Andersson, Karel Hala, M. Eric Gershwin,Carlo Selmi, Gisela F. Erf, Susan J. Lamont, and Roswitha Sgonc

145 136 Contents of Recent Volumes Functional Dynamics of Naturally Occurring Regulatory T Cells in Health and Autoimmunity Megan K. Levings, Sarah Allan, Eva d Hennezel, and Ciriaco A. Piccirillo BTLA and HVEM Cross Talk Regulates Inhibition and Costimulation Maya Gavrieli, John Sedy, Christopher A. Nelson, and Kenneth M. Murphy The Human T Cell Response to Melanoma Antigens Pedro Romero, Jean-Charles Cerottini, and Daniel E. Speiser Antigen Presentation and the Ubiquitin-Proteasome System in Host Pathogen Interactions Joana Loureiro and Hidde L. Ploegh Index Volume 93 Class Switch Recombination: A Comparison Between Mouse and Human Qiang Pan-Hammarström, Yaofeng Zhao, and Lennart Hammarström Anti-IgE Antibodies for the Treatment of IgE-Mediated Allergic Diseases Tse Wen Chang, Pheidias C. Wu, C. Long Hsu, and Alfur F. Hung Immune Semaphorins: Increasing Members and Their Diverse Roles Hitoshi Kikutani, Kazuhiro Suzuki, and Atsushi Kumanogoh Tec Kinases in T Cell and Mast Cell Signaling Martin Felices, Markus Falk, Yoko Kosaka, and Leslie J. Berg Integrin Regulation of Lymphocyte Trafficking: Lessons from Structural and Signaling Studies Tatsuo Kinashi Regulation of Immune Responses and Hematopoiesis by the Rap1 Signal Nagahiro Minato, Kohei Kometani, and Masakazu Hattori Lung Dendritic Cell Migration Hamida Hammad and Bart N. Lambrecht Index Volume 94 Discovery of Activation-Induced Cytidine Deaminase, the Engraver of Antibody Memory Masamichi Muramatsu, Hitoshi Nagaoka, Reiko Shinkura, Nasim A. Begum, and Tasuku Honjo DNA Deamination in Immunity: AID in the Context of Its APOBEC Relatives Silvestro G. Conticello, Marc-Andre Langlois, Zizhen Yang, and Michael S. Neuberger The Role of Activation-Induced Deaminase in Antibody Diversification and Chromosome Translocations Almudena Ramiro, Bernardo Reina San-Martin, Kevin McBride, Mila Jankovic, Vasco Barreto, André Nussenzweig, and Michel C. Nussenzweig Targeting of AID-Mediated Sequence Diversification by cis-acting Determinants Shu Yuan Yang and David G. Schatz AID-Initiated Purposeful Mutations in Immunoglobulin Genes Myron F. Goodman, Matthew D. Scharff, and Floyd E. Romesberg Evolution of the Immunoglobulin Heavy Chain Class Switch Recombination Mechanism Jayanta Chaudhuri, Uttiya Basu, Ali Zarrin, Catherine Yan, Sonia Franco, Thomas Perlot, Bao Vuong, Jing Wang, Ryan T. Phan, Abhishek Datta, John Manis, and Frederick W. Alt

146 Contents of Recent Volumes 137 Beyond SHM and CSR: AID and Related Cytidine Deaminases in the Host Response to Viral Infection Brad R. Rosenberg and F. Nina Papavasiliou Role of AID in Tumorigenesis Il-mi Okazaki, Ai Kotani, and Tasuku Honjo Pathophysiology of B-Cell Intrinsic Immunoglobulin Class Switch Recombination Deficiencies Anne Durandy, Nadine Taubenheim, Sophie Peron, and Alain Fischer Index Volume 95 Fate Decisions Regulating Bone Marrow and Peripheral B Lymphocyte Development John G. Monroe and Kenneth Dorshkind Tolerance and Autoimmunity: Lessons at the Bedside of Primary Immunodeficiencies Magda Carneiro-Sampaio and Antonio Coutinho B-Cell Self-Tolerance in Humans Hedda Wardemann and Michel C. Nussenzweig Manipulation of Regulatory T-Cell Number and Function with CD28-Specific Monoclonal Antibodies Thomas Hünig Osteoimmunology: A View from the Bone Jean-Pierre David Mast Cell Proteases Gunnar Pejler, Magnus Åbrink, Maria Ringvall, and Sara Wernersson Index Volume 96 New Insights into Adaptive Immunity in Chronic Neuroinflammation Volker Siffrin, Alexander U. Brandt, Josephine Herz, and Frauke Zipp Regulation of Interferon-g During Innate and Adaptive Immune Responses Jamie R. Schoenborn and Christopher B. Wilson The Expansion and Maintenance of Antigen-Selected CD8 þ T Cell Clones Douglas T. Fearon Inherited Complement Regulatory Protein Deficiency Predisposes to Human Disease in Acute Injury and Chronic Inflammatory States Anna Richards, David Kavanagh, and John P. Atkinson Fc-Receptors as Regulators of Immunity Falk Nimmerjahn and Jeffrey V. Ravetch Index Volume 97 T Cell Activation and the Cytoskeleton: You Can t Have One Without the Other Timothy S. Gomez and Daniel D. Billadeau HLA Class II Transgenic Mice Mimic Human Inflammatory Diseases Ashutosh K. Mangalam, Govindarajan Rajagopalan, Veena Taneja, and Chella S. David Roles of Zinc and Zinc Signaling in Immunity: Zinc as an Intracellular Signaling Molecule Toshio Hirano, Masaaki Murakami, Toshiyuki Fukada, Keigo Nishida, Satoru Yamasaki, and Tomoyuki Suzuki

147 138 Contents of Recent Volumes The SLAM and SAP Gene Families Control Innate and Adaptive Immune Responses Silvia Calpe, Ninghai Wang, Xavier Romero, Scott B. Berger, Arpad Lanyi, Pablo Engel, and Cox Terhorst Conformational Plasticity and Navigation of Signaling Proteins in Antigen-Activated B Lymphocytes Niklas Engels, Michael Engelke, and Jürgen Wienands Index Volume 98 Immune Regulation by B Cells and Antibodies: A View Towards the Clinic Kai Hoehlig, Vicky Lampropoulou, Toralf Roch, Patricia Neves, Elisabeth Calderon-Gomez, Stephen M. Anderton, Ulrich Steinhoff, and Simon Fillatreau Cumulative Environmental Changes, Skewed Antigen Exposure, and the Increase of Allergy Tse Wen Chang and Ariel Y. Pan New Insights on Mast Cell Activation via the High Affinity Receptor for IgE Juan Rivera, Nora A. Fierro, Ana Olivera, and Ryo Suzuki B Cells and Autoantibodies in the Pathogenesis of Multiple Sclerosis and Related Inflammatory Demyelinating Diseases Katherine A. McLaughlin and Kai W. Wucherpfennig Human B Cell Subsets Stephen M. Jackson, Patrick C. Wilson, Judith A. James, and J. Donald Capra Index Volume 99 Cis-Regulatory Elements and Epigenetic Changes Control Genomic Rearrangements of the IgH Locus Thomas Perlot and Frederick W. Alt DNA-PK: The Means to Justify the Ends? Katheryn Meek, Van Dang, and Susan P. Lees-Miller Thymic Microenvironments for T-Cell Repertoire Formation Takeshi Nitta, Shigeo Murata, Tomoo Ueno, Keiji Tanaka, and Yousuke Takahama Pathogenesis of Myocarditis and Dilated Cardiomyopathy Daniela Cihakova and Noel R. Rose Emergence of the Th17 Pathway and Its Role in Host Defense Darrell B. O Quinn, Matthew T. Palmer, Yun Kyung Lee, and Casey T. Weaver Peptides Presented In Vivo by HLA-DR in Thyroid Autoimmunity Laia Muixí, Iñaki Alvarez, and Dolores Jaraquemada Index Volume 100 Autoimmune Diabetes Mellitus Much Progress, but Many Challenges Hugh O. McDevitt and Emil R. Unanue CD3 Antibodies as Unique Tools to Restore Self-Tolerance in Established Autoimmunity: Their Mode of Action and Clinical Application in Type 1 Diabetes Sylvaine You, Sophie Candon, Chantal Kuhn, Jean-François Bach, and Lucienne Chatenoud GAD65 Autoimmunity Clinical Studies Raivo Uibo and Åke Lernmark

148 Contents of Recent Volumes 139 CD8þ T Cells in Type 1 Diabetes Sue Tsai, Afshin Shameli, and Pere Santamaria Dysregulation of T Cell Peripheral Tolerance in Type 1 Diabetes R. Tisch and B. Wang Gene Gene Interactions in the NOD Mouse Model of Type 1 Diabetes William M. Ridgway, Laurence B. Peterson, John A. Todd, Dan B. Rainbow, Barry Healy, and Linda S. Wicker Index Volume 101 TSLP in Epithelial Cell and Dendritic Cell Cross Talk Yong-Jun Liu Natural Killer Cell Tolerance: Licensing and Other Mechanisms A. Helena Jonsson and Wayne M. Yokoyama Biology of the Eosinophil Carine Blanchard and Marc E. Rothenberg Basophils: Beyond Effector Cells of Allergic Inflammation John T. Schroeder DNA Targets of AID: Evolutionary Link Between Antibody Somatic Hypermutation and Class Switch Recombination Jason A. Hackney, Shahram Misaghi, Kate Senger, Christopher Garris, Yonglian Sun, Maria N. Lorenzo, and Ali A. Zarrin Interleukin 5 in the Link Between the Innate and Acquired Immune Response Kiyoshi Takatsu, Taku Kouro, and Yoshinori Nagai Index Volume 102 Antigen Presentation by CD1: Lipids, T Cells, and NKT Cells in Microbial Immunity Nadia R. Cohen, Salil Garg, and Michael B. Brenner How the Immune System Achieves Self Nonself Discrimination During Adaptive Immunity Hong Jiang and Leonard Chess Cellular and Molecular Mechanisms in Atopic Dermatitis Michiko K. Oyoshi, Rui He, Lalit Kumar, Juhan Yoon, and Raif S. Geha Micromanagers of Immune Cell Fate and Function Fabio Petrocca and Judy Lieberman Immune Pathways for Translating Viral Infection into Chronic Airway Disease Michael J. Holtzman, Derek E. Byers, Loralyn A. Benoit, John T. Battaile, Yingjian You, Eugene Agapov, Chaeho Park, Mitchell H. Grayson, Edy Y. Kim, and Anand C. Patel Index Volume 103 The Physiological Role of Lysyl trna Synthetase in the Immune System Hovav Nechushtan, Sunghoon Kim, Gillian Kay, and Ehud Razin Kill the Bacteria and Also Their Messengers? Robert Munford, Mingfang Lu, and Alan Varley Role of SOCS in Allergic and Innate Immune Responses Suzanne L. Cassel and Paul B. Rothman

149 140 Contents of Recent Volumes Multitasking by Exploitation of Intracellular Transport Functions: The Many Faces of FcRn E. Sally Ward and Raimund J. Ober Index Volume 104 Regulation of Gene Expression in Peripheral T Cells by Runx Transcription Factors Ivana M. Djuretic, Fernando Cruz-Guilloty, and Anjana Rao Long Noncoding RNAs: Implications for Antigen Receptor Diversification Grace Teng and F. Nina Papavasiliou Pathogenic Mechanisms of Allergic Inflammation: Atopic Asthma as a Paradigm Patrick G. Holt, Deborah H. Strickland, Anthony Bosco, and Frode L. Jahnsen The Amplification Loop of the Complement Pathways Peter J. Lachmann Index Volume 105 Learning from Leprosy: Insight into the Human Innate Immune Response Dennis Montoya and Robert L. Modlin The Immunological Functions of Saposins Alexandre Darmoise, Patrick Maschmeyer, and Florian Winau OX40 OX40 Ligand Interaction in T-Cell-Mediated Immunity and Immunopathology Naoto Ishii, Takeshi Takahashi, Pejman Soroosh, and Kazuo Sugamura The Family of IL-10-Secreting CD4 þ T Cells Keishi Fujio, Tomohisa Okamura, and Kazuhiko Yamamoto Artificial Engineering of Secondary Lymphoid Organs Jonathan K. H. Tan and Takeshi Watanabe AID and Somatic Hypermutation Robert W. Maul and Patricia J. Gearhart BCL6: Master Regulator of the Germinal Center Reaction and Key Oncogene in B Cell Lymphomagenesis Katia Basso and Riccardo Dalla-Favera Index Volume 106 The Role of Innate Immunity in B Cell Acquisition of Antigen Within LNs Santiago F. Gonzalez, Michael P. Kuligowski, Lisa A. Pitcher, Ramon Roozendaal, and Michael C. Carroll Nuclear Receptors, Inflammation, and Neurodegenerative Diseases Kaoru Saijo, Andrea Crotti, and Christopher K. Glass Novel Tools for Modulating Immune Responses in the Host Polysaccharides from the Capsule of Commensal Bacteria Suryasarathi Dasgupta and Dennis L. Kasper

150 Contents of Recent Volumes 141 The Role of Mechanistic Factors in Promoting Chromosomal Translocations Found in Lymphoid and Other Cancers Yu Zhang, Monica Gostissa, Dominic G. Hildebrand, Michael S. Becker, Cristian Boboila, Roberto Chiarle, Susanna Lewis, and Frederick W. Alt Index Volume 107 Functional Biology of the IL-22-IL-22R Pathway in Regulating Immunity and Inflammation at Barrier Surfaces Gregory F. Sonnenberg, Lynette A. Fouser, David Artis Innate Signaling Networks in Mucosal IgA Class Switching Alejo Chorny, Irene Puga, and Andrea Cerutti Specificity of the Adaptive Immune Response to the Gut Microbiota Daniel A. Peterson and Roberto A. Jimenez Cardona Intestinal Dendritic Cells Maria Rescigno The Many Face-Lifts of CD4 T Helper Cells Daniel Mucida and Hilde Cheroutre GALT: Organization and Dynamics Leading to IgA Synthesis Keiichiro Suzuki, Shimpei Kawamoto, Mikako Maruya, and Sidonia Fagarasan Bronchus-Associated Lymphoid Tissue (BALT): Structure and Function Troy D. Randall Host Bacterial Symbiosis in Health and Disease Janet Chow, S. Melanie Lee, Yue Shen, Arya Khosravi, and Sarkis K. Mazmanian Index Volume 108 Macrophage Proinflammatory Activation and Deactivation: A Question of Balance Annabel F. Valledor, Monica Comalada, Luis Santamaría-Babi, Jorge Lloberas, and Antonio Celada Natural Helper Cells: A New Player in the Innate Immune Response against Helminth Infection Shigeo Koyasu, Kazuyo Moro, Masanobu Tanabe, and Tsutomu Takeuchi Mapping of Switch Recombination Junctions, a Tool for Studying DNA Repair Pathways during Immunoglobulin Class Switching Janet Stavnezer, Andrea Björkman, Likun Du, Alberto Cagigi, and Qiang Pan-Hammarström How Tolerogenic Dendritic Cells Induce Regulatory T Cells Roberto A. Maldonado and Ulrich H. von Andrian Index Volume 109 Dynamic Palmitoylation and the Role of DHHC Proteins in T Cell Activation and Anergy Nadejda Ladygina, Brent R. Martin, and Amnon Altman

151 142 Contents of Recent Volumes Transcriptional Control of Natural Killer Cell Development and Function David G. T. Hesslein and Lewis. L. Lanier The Control of Adaptive Immune Responses by the Innate Immune System Dominik Schenten and Ruslan Medzhitov The Evolution of Adaptive Immunity in Vertebrates Masayuki Hirano, Sabyasachi Das, Peng Guo, and Max D. Cooper T Helper Cell Differentiation: More than Just Cytokines Beata Zygmunt and Marc Veldhoen Index Volume 110 AID Targeting in Antibody Diversity Rushad Pavri and Michel C. Nussenzweig The IgH Locus 3 0 Regulatory Region: Pulling the Strings from Behind Eric Pinaud, Marie Marquet, Rémi Fiancette, Sophie Péron, Christelle Vincent-Fabert, Yves Denizot, and Michel Cogné Transcriptional and Epigenetic Regulation of CD4/CD8 Lineage Choice Ichiro Taniuchi and Wilfried Ellmeier Modeling a Complex Disease: Multiple Sclerosis Florian C. Kurschus, Simone Wörtge, and Ari Waisman Autoinflammation by Endogenous DNA Shigekazu Nagata and Kohki Kawane Index Volume 111 Early Steps of Follicular Lymphoma Pathogenesis Sandrine Roulland, Mustapha Faroudi, Emilie Mamessier, Stéphanie Sungalee, Gilles Salles, and Bertrand Nadel A Rose is a Rose is a Rose, but CVID is Not CVID: Common Variable Immune Deficiency (CVID), What do we Know in 2011? Patrick F. K. Yong, James E. D. Thaventhiran, and Bodo Grimbacher Role of Activation-Induced Cytidine Deaminase in Inflammation-Associated Cancer Development Hiroyuki Marusawa, Atsushi Takai, and Tsutomu Chiba Comparative Genomics and Evolution of Immunoglobulin-Encoding Loci in Tetrapods Sabyasachi Das, Masayuki Hirano, Chelsea McCallister, Rea Tako, and Nikolas Nikolaidis Pax5: A Master Regulator of B Cell Development and Leukemogenesis Jasna Medvedovic, Anja Ebert, Hiromi Tagoh, and Meinrad Busslinger Index Volume 112 Stability of Regulatory T-cell Lineage Shohei Hori Thymic and Peripheral Differentiation of Regulatory T Cells Hyang-Mi Lee, Jhoanne Lynne Bautista, and Chyi-Song Hsieh Regulatory T Cells in Infection Rick M. Maizels and Katherine A. Smith Biological Functions of Regulatory T Cells Ethan M. Shevach Extrathymic Generation of Regulatory T Cells Chances and Challenges for Prevention of Autoimmune Disease Carolin Daniel, and Harald von Boehmer Index

152 Contents of Recent Volumes 143 Volume 113 Studies with Listeria monocytogenes Lead the Way Emil R. Unanue and Javier A. Carrero Interactions of Listeria monocytogenes with the Autophagy System of Host Cells Grace Y. Lam, Mark A. Czuczman, Darren E. Higgins and John H. Brumell Virulence Factors That Modulate the Cell Biology of Listeria Infection and the Host Response Serge Mostowy and Pascale Cossart Dendritic Cells in Listeria monocytogenes Infection Brian T. Edelson Probing CD8 T Cell Responses with Listeria monocytogenes Infection Stephanie A. Condotta, Martin J. Richer, Vladimir P. Badovinac and John T. Harty Listeria monocytogenes and Its Products as Agents for Cancer Immunotherapy Patrick Guirnalda, Laurence Wood and Yvonne Paterson Monocyte-Mediated Immune Defense Against Murine Listeria monocytogenes Infection Natalya V. Serbina, Chao Shi and Eric G. Pamer Innate Immune Pathways Triggered by Listeria monocytogenes and Their Role in the Induction of Cell-Mediated Immunity Chelsea E. Witte, Kristina A. Archer, Chris S. Rae, John-Demian Sauer, Josh J. Woodward and Daniel A. Portnoy Mechanisms and Immunological Effects of Lymphocyte Apoptosis Caused by Listeria monocytogenes Javier A. Carrero, and Emil R. Unanue Index Volume 114 Nucleic Acid Adjuvants: Toward an Educated Vaccine Jasper G. van den Boorn, Winfried Barchet, and Gunther Hartmann Structure-Based Design for High-Hanging Vaccine Fruits Jaap W. Back and Johannes P. M. Langedijk Mechanisms of Peptide Vaccination in Mouse Models: Tolerance, Immunity, and Hyperreactivity Thorbald van Hall and Sjoerd H. van der Burg Experience with Synthetic Vaccines for Cancer and Persistent Virus Infections in Nonhuman Primates and Patients Esther D. Quakkelaar and Cornelis J. M. Melief Malaria Vaccine Development Using Synthetic Peptides as a Technical Platform Giampietro Corradin, Nora Céspedes, Antonio Verdini, Andrey V. Kajava, Myriam Arévalo-Herrera, and Sócrates Herrera Enhancing Cancer Immunotherapy by Intracellular Delivery of Cell-Penetrating Peptides and Stimulation of Pattern- Recognition Receptor Signaling Helen Y. Wang and Rong-Fu Wang TLR Ligand Peptide Conjugate Vaccines: Toward Clinical Application Gijs G. P. Zom, Selina Khan, Dmitri V. Filippov, and Ferry Ossendorp Behavior and Function of Tissue-Resident Memory T cells Silvia Ariotti, John B. Haanen, and Ton N. Schumacher Rational Design of Vaccines: Learning from Immune Evasion Mechanisms of Persistent Viruses and Tumors Ramon Arens Index

153 144 Contents of Recent Volumes Volume 115 The Immunobiology of IL-27 Aisling O Hara Hall, Jonathan S. Silver, and Christopher A. Hunter Autoimmune Arthritis: The Interface Between the Immune System and Joints Noriko Komatsu and Hiroshi Takayanagi Immunological Tolerance During Fetal Development: From Mouse to Man Jeff E. Mold and Joseph M. McCune Mapping Lupus Susceptibility Genes in the NZM2410 Mouse Model Laurence Morel Functional Heterogeneity in the Basophil Cell Lineage Mark C. Siracusa, Elia D. Tait Wojno, and David Artis An Emerging Role of RNA-Binding Proteins as Multifunctional Regulators of Lymphocyte Development and Function Martin Turner and Daniel J. Hodson Active and Passive Anticytokine Immune Therapies: Current Status and Development Hélène Le Buanec, Armand Bensussan, Martine Bagot, Robert C. Gallo, and Daniel Zagury Volume 116 Classical and Alternative End-Joining Pathways for Repair of Lymphocyte-Specific and General DNA Double-Strand Breaks Cristian Boboila, Frederick W. Alt, and Bjoern Schwer The Leukotrienes: Immune-Modulating Lipid Mediators of Disease Antonio Di Gennaro and Jesper Z. Haeggström Gut Microbiota Drives Metabolic Disease in Immunologically Altered Mice Benoit Chassaing, Jesse D. Aitken, Andrew T. Gewirtz, and Matam Vijay-Kumar What is Unique About the IgE Response? Huizhong Xiong, Maria A. Curotto de Lafaille, and Juan J. Lafaille Prostanoids as Regulators of Innate and Adaptive Immunity Takako Hirata and Shuh Narumiya Lymphocyte Development: Integration of DNA Damage Response Signaling Jeffrey J. Bednarski and Barry P. Sleckman Index Index

154 A O O HO O OH OH IDH1 or IDH2 O O OH O Mutant IDH1 or IDH2 OH Isocitrate OH Oxoglutarate O OH O OH OH 2-Hydroxyglutarate NH 2 N DNMTs CH 3 NH 2 N TETs OH NH 2 N N H O N O N O H H + + Oxoglutarate Succinate B (i) CpG CpG CpG RNAP2 (ii) DNMT DNMT DNMT CpG CpG CpG RNAP2 X CpG (iii) Unmodified CpG island TET2 TET2 TET2 CpG CpG CpG RNAP2? CpG Methylated CpG island CpG Hydroxy methylated CpG island Chapter 1, Figure 1.1 (See page 8 of this volume.)

155 A Polycomb repressive complex 2 B EZH2 JARID2 EED EZH2 Set SUZ12 RBBP4/7 CDKN2A/B HOXA NH 2 SANT SANT CXC SET Nonsense/InDels Missense Y641 T-ALL Myeloid disorders DLBCL C KDM6A ASH2L WDR5 KDM6B RBBP5 MLL Set COMPASS-like complex RNAP2 HOXA MEIS1 MLL-fusion methyltransferase complex MLL AF9 AF10 DOT1L ENL CBX8 TIP60 D MLL protein Breakpoint NH 2 CxxC AT Hooks PHD TA MLL-fusion proteins SET AT Hooks CxxC AF-9 H3K4me3 H3K79me2 H3K27me3 AT Hooks CxxC AF-4 AT CxxC Hooks Chapter 1, Figure 1.2 (See page 15 of this volume.) ENL

156 A KMTi PRC2 Set HATi HATs DNMT DNMTi vidaza decitabine CpG Sirtuins HDACs KDM KDMi SIRTi HDACi vorinostat romidepsin PRMT5 JAK2 (V617F) JAKi Ruxolitinib B Monoclonal antibodies EGFR Cell membrane Lysine methylation Lysine acetylation BCR-ABL Inhibitors of signal transduction Nuclear envelope Arginine methylation Epigenetic inhibitors Alkylating agents phosphorylation DNMT CpG CpG CpG Cisplatin Chapter 1, Figure 1.3 (See page 20 of this volume.)

157 Pathologic DNA double strand breaks (DSBs) ROS Ionizing radiations Stalled replication forks Common fragile sites and ERFSs Oncogene-induced replication breaks Topoisomerases DNA damage in micronuclei Off-target activity of RAG1/2 Off-target activity of AID Physiologic DNA double strand breaks (DSBs) RAG1/2 induced V(D)J recombination AID induced CSR and SHM DSB DSB Legitimate DNA repair C-NHEJ (all cell cycle) HR (S/G2 phases) FoSTeS (collapsed replication fork) MMBIR (collapsed replication fork) Illegitimate DNA repair C-NHEJ A-EJ FoSTeS MMBIR DNA integrity Translocations Duplications Chromothripsis Chapter 2, Figure 2.1 (See page 41 of this volume.) Chromosome territories Transcription factories Replication factories DNA repair centers Active A domain Inactive B domain mrna mrna RNA polymerases PCNA DNA polymerases C-NHEJ A-EJ mrna mrna Short chromosomes Long chromosomes Chapter 2, Figure 2.2 (See page 48 of this volume.)

158 AID-induced DSBs and translocations Mature B cells IgM + AID induction 4 days stimulation IL-4 + CD40 or LPS Translocations I-Scel-mediated DSBs DNA isolation Linker-mediated PCR Proliferation CSR to IgG1 + B cells Next-generation sequencing Translocation maps A-MuLV Pro-B cells G1 arrest RAG1/2 induction STI-571 Translocations DNA isolation Linker-mediated PCR I-Scel-mediated DSBs RAG1/2-induced DSBs and translocations Chapter 2, Figure 2.3 (See page 51 of this volume.)

159 Mitosis Chromosome shattering Micronucleus pulverization Radiation MMBIR Predisposition to cancer due to oncogenes and oncosuppressors alterations Postmitotic cell with chromothripsis NHEJ MMBIR DNA repair Chromosome territory P53 deficiency Mitosis exit Chapter 2, Figure 2.4 (See page 60 of this volume.)

160 Intestinal microbiota Type 2 diabetes Endotoxemia Insulitis Insulin resistance Steatosis Obesity Increased calorie extraction Cleavage of dietary polysaccharides Dyslipidemia Decreased choline metabolism Chapter 3, Figure 3.1 (See page 76 of this volume.) Steatosis Hepatocyte: TLR2-4 Kupffer cell: TLR2-4 Stellate cell: TLR1-9 Inflammatory response in the liver TNF IL-6 LSEC: TLR2 Flux of PRR ligands Enterocytes: NLRP6 Intestinal dysbiosis Chapter 3, Figure 3.2 (See page 83 of this volume.)

161 RIG-I CARD CARD ATPase/helicase RD/CTD MDA5 CARD CARD ATPase/helicase RD-like LGP2 11 ATPase/helicase RD/CTD MAVS CARD Pro TM Chapter 4, Figure 4.1 (See page 102 of this volume.) Influenza virus NDV SeV VSV HCV JEV TRIM25 Riplet RNF125 PKC-a/b P P P RIG-I NLRX1 WNV Dengue virus Reovirus MAVS MDA-5 EMCV Theiler s virus Cytoplasm IKK-i TBK1 IKK-a IKK-b IKK-g MAPKs? IRF3/7 NF-kB ATF2/c-Jun Type I IFN Cytokines ISGs Nucleus Chapter 4, Figure 4.2 (See page 103 of this volume.)