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Mahdy AKH, Lokes E, Schöpfel V, Kriukova V, Britanova OV, Steiert TA, Franke A, ElAbd H. Bulk T cell repertoire sequencing (TCR-Seq) is a powerful technology for understanding inflammation-mediated diseases. J Autoimmun 2024; 149:103337. [PMID: 39571301 DOI: 10.1016/j.jaut.2024.103337] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2024] [Revised: 10/12/2024] [Accepted: 11/09/2024] [Indexed: 12/15/2024]
Abstract
Multiple alterations in the T cell repertoire were identified in many chronic inflammatory diseases such as inflammatory bowel disease, multiple sclerosis, and rheumatoid arthritis, suggesting that T cells might, directly or indirectly, be implicated in these pathologies. This has sparked a deep interest in characterizing disease-associated T cell clonotypes as well as in identifying and quantifying their contribution to the pathophysiology of different autoimmune and inflammation-mediated diseases. Bulk T cell repertoire sequencing (TCR-Seq) has emerged as a powerful method to profile the T cell repertoire of a sample in a high throughput fashion. Given the increasing utilization of TCR-Seq, we aimed here to provide a comprehensive, up-to-date review of the method, its extensions, and its ability to investigate chronic and autoimmune diseases. Specifically, we started by introducing the immunological basis of TCR repertoire generation and features, followed by discussing different experimental approach to perform TCR-Seq, then we describe different methods and frameworks for analyzing the generated datasets. Subsequently, different experimental techniques for investigating the antigenicity of T cell clonotypes are described. Lastly, we discuss recent studies that utilized TCR-Seq to understand different inflammation-mediated diseases, discuss fallbacks of the technology and potential future directions to overcome current limitations.
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Affiliation(s)
- Aya K H Mahdy
- Institute of Clinical Molecular Biology, Kiel University & University Medical Centre Schleswig-Holstein, Kiel, 24105, Germany
| | - Evgeniya Lokes
- Institute of Clinical Molecular Biology, Kiel University & University Medical Centre Schleswig-Holstein, Kiel, 24105, Germany
| | - Valentina Schöpfel
- Institute of Clinical Molecular Biology, Kiel University & University Medical Centre Schleswig-Holstein, Kiel, 24105, Germany
| | - Valeriia Kriukova
- Institute of Clinical Molecular Biology, Kiel University & University Medical Centre Schleswig-Holstein, Kiel, 24105, Germany
| | - Olga V Britanova
- Institute of Clinical Molecular Biology, Kiel University & University Medical Centre Schleswig-Holstein, Kiel, 24105, Germany
| | - Tim A Steiert
- Institute of Clinical Molecular Biology, Kiel University & University Medical Centre Schleswig-Holstein, Kiel, 24105, Germany
| | - Andre Franke
- Institute of Clinical Molecular Biology, Kiel University & University Medical Centre Schleswig-Holstein, Kiel, 24105, Germany.
| | - Hesham ElAbd
- Institute of Clinical Molecular Biology, Kiel University & University Medical Centre Schleswig-Holstein, Kiel, 24105, Germany.
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2
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Kruta J, Carapito R, Trendelenburg M, Martin T, Rizzi M, Voll RE, Cavalli A, Natali E, Meier P, Stawiski M, Mosbacher J, Mollet A, Santoro A, Capri M, Giampieri E, Schkommodau E, Miho E. Machine learning for precision diagnostics of autoimmunity. Sci Rep 2024; 14:27848. [PMID: 39537649 PMCID: PMC11561187 DOI: 10.1038/s41598-024-76093-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2024] [Accepted: 10/10/2024] [Indexed: 11/16/2024] Open
Abstract
Early and accurate diagnosis is crucial to prevent disease development and define therapeutic strategies. Due to predominantly unspecific symptoms, diagnosis of autoimmune diseases (AID) is notoriously challenging. Clinical decision support systems (CDSS) are a promising method with the potential to enhance and expedite precise diagnostics by physicians. However, due to the difficulties of integrating and encoding multi-omics data with clinical values, as well as a lack of standardization, such systems are often limited to certain data types. Accordingly, even sophisticated data models fall short when making accurate disease diagnoses and presenting data analyses in a user-friendly form. Therefore, the integration of various data types is not only an opportunity but also a competitive advantage for research and industry. We have developed an integration pipeline to enable the use of machine learning for patient classification based on multi-omics data in combination with clinical values and laboratory results. The application of our framework resulted in up to 96% prediction accuracy of autoimmune diseases with machine learning models. Our results deliver insights into autoimmune disease research and have the potential to be adapted for applications across disease conditions.
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Affiliation(s)
- Jan Kruta
- School of Life Sciences, FHNW University of Applied Sciences and Arts Northwestern Switzerland, Hofackerstrasse 30, Muttenz, 4132, Switzerland
| | - Raphael Carapito
- Laboratoire d'ImmunoRhumatologie Moléculaire, plateforme GENOMAX, Faculté de Médecine, Fédération de Médecine Translationnelle de Strasbourg (FMTS), Institut Thématique Interdisciplinaire TRANSPLANTEX NG, INSERM UMR_S 1109, Fédération Hospitalo-Universitaire OMICARE, Université de Strasbourg, 4 rue Kirschleger, Strasbourg, 67085, France
- Service d'Immunologie Biologique, Pôle de Biologie, Plateau Technique de Biologie, Nouvel Hôpital Civil, 1 place de l'Hôpital, Strasbourg, 67091, France
| | - Marten Trendelenburg
- Division of Internal Medicine, University Hospital Basel, Basel, 4031, Switzerland
| | - Thierry Martin
- Laboratoire d'ImmunoRhumatologie Moléculaire, plateforme GENOMAX, Faculté de Médecine, Fédération de Médecine Translationnelle de Strasbourg (FMTS), Institut Thématique Interdisciplinaire TRANSPLANTEX NG, INSERM UMR_S 1109, Fédération Hospitalo-Universitaire OMICARE, Université de Strasbourg, 4 rue Kirschleger, Strasbourg, 67085, France
| | - Marta Rizzi
- Department of Rheumatology and Clinical Immunology, Medical Center, University of Freiburg, 79106, Freiburg, Germany
| | - Reinhard E Voll
- Department of Rheumatology and Clinical Immunology, Medical Center, University of Freiburg, 79106, Freiburg, Germany
| | - Andrea Cavalli
- FaBiT Department of Pharmacy and Biotechnology, Università di Bologna, Bologna, 40126, Italy
| | - Eriberto Natali
- School of Life Sciences, FHNW University of Applied Sciences and Arts Northwestern Switzerland, Hofackerstrasse 30, Muttenz, 4132, Switzerland
| | - Patrick Meier
- School of Life Sciences, FHNW University of Applied Sciences and Arts Northwestern Switzerland, Hofackerstrasse 30, Muttenz, 4132, Switzerland
| | - Marc Stawiski
- School of Life Sciences, FHNW University of Applied Sciences and Arts Northwestern Switzerland, Hofackerstrasse 30, Muttenz, 4132, Switzerland
| | - Johannes Mosbacher
- School of Life Sciences, FHNW University of Applied Sciences and Arts Northwestern Switzerland, Hofackerstrasse 30, Muttenz, 4132, Switzerland
| | - Annette Mollet
- Institute of Pharmaceutical Medicine, University of Basel, Basel, 4056, Switzerland
| | - Aurelia Santoro
- Department of Experimental, Diagnostic and Specialty Medicine (DIMES), University of Bologna, Bologna, 40126, Italy
| | - Miriam Capri
- Department of Experimental, Diagnostic and Specialty Medicine (DIMES), University of Bologna, Bologna, 40126, Italy
| | - Enrico Giampieri
- Department of Experimental, Diagnostic and Specialty Medicine (DIMES), University of Bologna, Bologna, 40126, Italy
| | - Erik Schkommodau
- School of Life Sciences, FHNW University of Applied Sciences and Arts Northwestern Switzerland, Hofackerstrasse 30, Muttenz, 4132, Switzerland
| | - Enkelejda Miho
- School of Life Sciences, FHNW University of Applied Sciences and Arts Northwestern Switzerland, Hofackerstrasse 30, Muttenz, 4132, Switzerland.
- SIB Swiss Institute of Bioinformatics, Lausanne, 1015, Switzerland.
- aiNET GmbH, Lichtstrasse 35, Basel, 4056, Switzerland.
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3
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Mhanna V, Barennes P, Vantomme H, Fourcade G, Coatnoan N, Six A, Klatzmann D, Mariotti-Ferrandiz E. Enhancing comparative T cell receptor repertoire analysis in small biological samples through pooling homologous cell samples from multiple mice. CELL REPORTS METHODS 2024; 4:100753. [PMID: 38614088 PMCID: PMC11045977 DOI: 10.1016/j.crmeth.2024.100753] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 01/28/2024] [Accepted: 03/19/2024] [Indexed: 04/15/2024]
Abstract
Accurate characterization and comparison of T cell receptor (TCR) repertoires from small biological samples present significant challenges. The main challenge is the low material input, which compromises the quality of bulk sequencing and hinders the recovery of sufficient TCR sequences for robust analyses. We aimed to address this limitation by implementing a strategic approach to pool homologous biological samples. Our findings demonstrate that such pooling indeed enhances the TCR repertoire coverage, particularly for cell subsets of constrained sizes, and enables accurate comparisons of TCR repertoires at different levels of complexity across T cell subsets with different sizes. This methodology holds promise for advancing our understanding of T cell repertoires in scenarios where sample size constraints are a prevailing concern.
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Affiliation(s)
- Vanessa Mhanna
- Sorbonne Université, INSERM, Immunology-Immunopathology-Immunotherapy (i3), 75005 Paris, France; AP-HP, Hôpital Pitié-Salpêtrière, Clinical Investigation Center for Biotherapies (CIC-BTi) and Immunology-Inflammation-Infectiology and Dermatology Department (3iD), Paris, France
| | - Pierre Barennes
- Sorbonne Université, INSERM, Immunology-Immunopathology-Immunotherapy (i3), 75005 Paris, France; AP-HP, Hôpital Pitié-Salpêtrière, Clinical Investigation Center for Biotherapies (CIC-BTi) and Immunology-Inflammation-Infectiology and Dermatology Department (3iD), Paris, France
| | - Hélène Vantomme
- AP-HP, Hôpital Pitié-Salpêtrière, Clinical Investigation Center for Biotherapies (CIC-BTi) and Immunology-Inflammation-Infectiology and Dermatology Department (3iD), Paris, France
| | - Gwladys Fourcade
- Sorbonne Université, INSERM, Immunology-Immunopathology-Immunotherapy (i3), 75005 Paris, France
| | - Nicolas Coatnoan
- AP-HP, Hôpital Pitié-Salpêtrière, Clinical Investigation Center for Biotherapies (CIC-BTi) and Immunology-Inflammation-Infectiology and Dermatology Department (3iD), Paris, France
| | - Adrien Six
- Sorbonne Université, INSERM, Immunology-Immunopathology-Immunotherapy (i3), 75005 Paris, France
| | - David Klatzmann
- Sorbonne Université, INSERM, Immunology-Immunopathology-Immunotherapy (i3), 75005 Paris, France; AP-HP, Hôpital Pitié-Salpêtrière, Clinical Investigation Center for Biotherapies (CIC-BTi) and Immunology-Inflammation-Infectiology and Dermatology Department (3iD), Paris, France
| | - Encarnita Mariotti-Ferrandiz
- Sorbonne Université, INSERM, Immunology-Immunopathology-Immunotherapy (i3), 75005 Paris, France; Institut Universitaire de France, France.
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4
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Peres A, Klein V, Frankel B, Lees W, Polak P, Meehan M, Rocha A, Correia Lopes J, Yaari G. Guidelines for reproducible analysis of adaptive immune receptor repertoire sequencing data. Brief Bioinform 2024; 25:bbae221. [PMID: 38752856 PMCID: PMC11097599 DOI: 10.1093/bib/bbae221] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Revised: 03/06/2024] [Accepted: 04/18/2024] [Indexed: 05/19/2024] Open
Abstract
Enhancing the reproducibility and comprehension of adaptive immune receptor repertoire sequencing (AIRR-seq) data analysis is critical for scientific progress. This study presents guidelines for reproducible AIRR-seq data analysis, and a collection of ready-to-use pipelines with comprehensive documentation. To this end, ten common pipelines were implemented using ViaFoundry, a user-friendly interface for pipeline management and automation. This is accompanied by versioned containers, documentation and archiving capabilities. The automation of pre-processing analysis steps and the ability to modify pipeline parameters according to specific research needs are emphasized. AIRR-seq data analysis is highly sensitive to varying parameters and setups; using the guidelines presented here, the ability to reproduce previously published results is demonstrated. This work promotes transparency, reproducibility, and collaboration in AIRR-seq data analysis, serving as a model for handling and documenting bioinformatics pipelines in other research domains.
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Affiliation(s)
- Ayelet Peres
- Faculty of Engineering, Bar Ilan University, 5290002 Ramat Gan, Israel
- Bar Ilan institute of nanotechnology and advanced materials, Bar Ilan university, 5290002 Ramat Gan, Israel
| | - Vered Klein
- Faculty of Engineering, Bar Ilan University, 5290002 Ramat Gan, Israel
- Bar Ilan institute of nanotechnology and advanced materials, Bar Ilan university, 5290002 Ramat Gan, Israel
| | - Boaz Frankel
- Faculty of Engineering, Bar Ilan University, 5290002 Ramat Gan, Israel
- Bar Ilan institute of nanotechnology and advanced materials, Bar Ilan university, 5290002 Ramat Gan, Israel
| | - William Lees
- Institute of Structural and Molecular Biology, Birkbeck College, University of London, London, United Kingdom
- INESC TEC – Institute for Systems and Computer Engineering, Technology and Science Porto, Portugal
| | - Pazit Polak
- Faculty of Engineering, Bar Ilan University, 5290002 Ramat Gan, Israel
- Bar Ilan institute of nanotechnology and advanced materials, Bar Ilan university, 5290002 Ramat Gan, Israel
| | - Mark Meehan
- INESC TEC – Institute for Systems and Computer Engineering, Technology and Science Porto, Portugal
| | - Artur Rocha
- INESC TEC – Institute for Systems and Computer Engineering, Technology and Science Porto, Portugal
| | - João Correia Lopes
- INESC TEC – Institute for Systems and Computer Engineering, Technology and Science Porto, Portugal
| | - Gur Yaari
- Faculty of Engineering, Bar Ilan University, 5290002 Ramat Gan, Israel
- Bar Ilan institute of nanotechnology and advanced materials, Bar Ilan university, 5290002 Ramat Gan, Israel
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5
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Elster C, Ommer-Bläsius M, Lang A, Vajen T, Pfeiler S, Feige M, Yau Pang T, Böttenberg M, Verheyen S, Lê Quý K, Chernigovskaya M, Kelm M, Winkels H, Schmidt SV, Greiff V, Gerdes N. Application and challenges of TCR and BCR sequencing to investigate T- and B-cell clonality in elastase-induced experimental murine abdominal aortic aneurysm. Front Cardiovasc Med 2023; 10:1221620. [PMID: 38034381 PMCID: PMC10686233 DOI: 10.3389/fcvm.2023.1221620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Accepted: 10/16/2023] [Indexed: 12/02/2023] Open
Abstract
Background An abdominal aortic aneurysm (AAA) is a life-threatening cardiovascular disease. Although its pathogenesis is still poorly understood, recent evidence suggests that AAA displays autoimmune disease characteristics. Particularly, T cells responding to AAA-related antigens in the aortic wall may contribute to an initial immune response. Single-cell RNA (scRNA) T cell receptor (TCR) and B cell receptor (BCR) sequencing is a powerful tool for investigating clonality. However, difficulties such as limited numbers of isolated cells must be considered during implementation and data analysis, making biological interpretation challenging. Here, we perform a representative single-cell immune repertoire analysis in experimental murine AAA and show a reliable bioinformatic processing pipeline highlighting opportunities and limitations of this approach. Methods We performed scRNA TCR and BCR sequencing of isolated lymphocytes from the infrarenal aorta of male C57BL/6J mice 3, 7, 14, and 28 days after AAA induction via elastase perfusion of the aorta. Sham-operated mice at days 3 and 28 and non-operated mice served as controls. Results Comparison of complementarity-determining region (CDR3) length distribution of 179 B cells and 796 T cells revealed neither differences between AAA and control nor between the disease stages. We found no clonal expansion of B cells in AAA. For T cells, we identified several clones in 11 of 16 AAA samples and one of eight control samples. Immune receptor repertoire comparison indicated that only a few clones were shared between the individual AAA samples. The most frequently used V-genes in the TCR beta chain in AAA were TRBV3, TRBV19, and the splicing variant TRBV12-2 + TRBV13-2. Conclusion We found no clonal expansion of B cells but evidence for clonal expansion of T cells in elastase-induced AAA in mice. Our findings imply that a more precise characterization of TCR and BCR distribution requires a more extensive number of lymphocytes to prevent undersampling and potentially detect rare clones. Thus, further experiments are necessary to confirm our findings. In summary, this paper examines TCR and BCR sequencing results, identifies limitations and pitfalls, and offers guidance for future studies.
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Affiliation(s)
- Christin Elster
- Division of Cardiology, Pulmonology, and Vascular Medicine, Medical Faculty and University Hospital, Heinrich Heine University, Düsseldorf, Germany
| | - Miriam Ommer-Bläsius
- Division of Cardiology, Pulmonology, and Vascular Medicine, Medical Faculty and University Hospital, Heinrich Heine University, Düsseldorf, Germany
| | - Alexander Lang
- Division of Cardiology, Pulmonology, and Vascular Medicine, Medical Faculty and University Hospital, Heinrich Heine University, Düsseldorf, Germany
| | - Tanja Vajen
- Division of Cardiology, Pulmonology, and Vascular Medicine, Medical Faculty and University Hospital, Heinrich Heine University, Düsseldorf, Germany
| | - Susanne Pfeiler
- Division of Cardiology, Pulmonology, and Vascular Medicine, Medical Faculty and University Hospital, Heinrich Heine University, Düsseldorf, Germany
| | - Milena Feige
- Division of Cardiology, Pulmonology, and Vascular Medicine, Medical Faculty and University Hospital, Heinrich Heine University, Düsseldorf, Germany
| | - Tin Yau Pang
- Division of Cardiology, Pulmonology, and Vascular Medicine, Medical Faculty and University Hospital, Heinrich Heine University, Düsseldorf, Germany
- Department of Biology, Institute for Computer Science, Heinrich Heine University, Düsseldorf, Germany
| | - Marius Böttenberg
- Division of Cardiology, Pulmonology, and Vascular Medicine, Medical Faculty and University Hospital, Heinrich Heine University, Düsseldorf, Germany
| | - Sarah Verheyen
- Division of Cardiology, Pulmonology, and Vascular Medicine, Medical Faculty and University Hospital, Heinrich Heine University, Düsseldorf, Germany
| | - Khang Lê Quý
- Department of Immunology, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Maria Chernigovskaya
- Department of Immunology, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Malte Kelm
- Division of Cardiology, Pulmonology, and Vascular Medicine, Medical Faculty and University Hospital, Heinrich Heine University, Düsseldorf, Germany
- Cardiovascular Research Institute Düsseldorf (CARID), Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
| | - Holger Winkels
- Department of Cardiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Susanne V. Schmidt
- Institute of Innate Immunity, Medical Faculty and University Hospital, Rheinische Friedrich-Wilhelms-University, Bonn, Germany
- Institute of Clinical Chemistry and Clinical Pharmacology, University Hospital Bonn, Bonn, Germany
| | - Victor Greiff
- Department of Immunology, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Norbert Gerdes
- Division of Cardiology, Pulmonology, and Vascular Medicine, Medical Faculty and University Hospital, Heinrich Heine University, Düsseldorf, Germany
- Cardiovascular Research Institute Düsseldorf (CARID), Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
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6
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Perruzza L, Strati F, Raneri M, Li H, Gargari G, Rezzonico-Jost T, Palatella M, Kwee I, Morone D, Seehusen F, Sonego P, Donati C, Franceschi P, Macpherson AJ, Guglielmetti S, Greiff V, Grassi F. Apyrase-mediated amplification of secretory IgA promotes intestinal homeostasis. Cell Rep 2022; 40:111112. [PMID: 35858559 DOI: 10.1016/j.celrep.2022.111112] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Revised: 05/15/2022] [Accepted: 06/28/2022] [Indexed: 11/25/2022] Open
Abstract
Secretory immunoglobulin A (SIgA) interaction with commensal bacteria conditions microbiota composition and function. However, mechanisms regulating reciprocal control of microbiota and SIgA are not defined. Bacteria-derived adenosine triphosphate (ATP) limits T follicular helper (Tfh) cells in the Peyer's patches (PPs) via P2X7 receptor (P2X7R) and thereby SIgA generation. Here we show that hydrolysis of extracellular ATP (eATP) by apyrase results in amplification of the SIgA repertoire. The enhanced breadth of SIgA in mice colonized with apyrase-releasing Escherichia coli influences topographical distribution of bacteria and expression of genes involved in metabolic versus immune functions in the intestinal epithelium. SIgA-mediated conditioning of bacteria and enterocyte function is reflected by differences in nutrient absorption in mice colonized with apyrase-expressing bacteria. Apyrase-induced SIgA improves intestinal homeostasis and attenuates barrier impairment and susceptibility to infection by enteric pathogens in antibiotic-induced dysbiosis. Therefore, amplification of SIgA by apyrase can be leveraged to restore intestinal fitness in dysbiotic conditions.
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Affiliation(s)
- Lisa Perruzza
- Institute for Research in Biomedicine, Faculty of Biomedical Sciences, Università della Svizzera Italiana, Bellinzona 6500, Switzerland
| | - Francesco Strati
- Institute for Research in Biomedicine, Faculty of Biomedical Sciences, Università della Svizzera Italiana, Bellinzona 6500, Switzerland
| | - Matteo Raneri
- Institute for Research in Biomedicine, Faculty of Biomedical Sciences, Università della Svizzera Italiana, Bellinzona 6500, Switzerland
| | - Hai Li
- Maurice Müller Laboratories, Department of Biomedical Research, Universitätsklinik für Viszerale Chirurgie und Medizin, Inselspital, University of Bern, Bern 3010, Switzerland
| | - Giorgio Gargari
- Division of Food Microbiology and Bioprocesses, Department of Food, Environmental and Nutritional Sciences (DeFENS), University of Milan, Milan 20133, Italy
| | - Tanja Rezzonico-Jost
- Institute for Research in Biomedicine, Faculty of Biomedical Sciences, Università della Svizzera Italiana, Bellinzona 6500, Switzerland
| | - Martina Palatella
- Institute for Research in Biomedicine, Faculty of Biomedical Sciences, Università della Svizzera Italiana, Bellinzona 6500, Switzerland
| | - Ivo Kwee
- Institute for Research in Biomedicine, Faculty of Biomedical Sciences, Università della Svizzera Italiana, Bellinzona 6500, Switzerland
| | - Diego Morone
- Institute for Research in Biomedicine, Faculty of Biomedical Sciences, Università della Svizzera Italiana, Bellinzona 6500, Switzerland
| | - Frauke Seehusen
- Institute of Veterinary Pathology, Vetsuisse Faculty, University of Zurich, Zurich 8057, Switzerland
| | - Paolo Sonego
- Unit of Computational Biology, Research and Innovation Centre, Fondazione Edmund Mach, San Michele all'Adige (TN) 38098, Italy
| | - Claudio Donati
- Unit of Computational Biology, Research and Innovation Centre, Fondazione Edmund Mach, San Michele all'Adige (TN) 38098, Italy
| | - Pietro Franceschi
- Unit of Computational Biology, Research and Innovation Centre, Fondazione Edmund Mach, San Michele all'Adige (TN) 38098, Italy
| | - Andrew J Macpherson
- Maurice Müller Laboratories, Department of Biomedical Research, Universitätsklinik für Viszerale Chirurgie und Medizin, Inselspital, University of Bern, Bern 3010, Switzerland
| | - Simone Guglielmetti
- Division of Food Microbiology and Bioprocesses, Department of Food, Environmental and Nutritional Sciences (DeFENS), University of Milan, Milan 20133, Italy
| | - Victor Greiff
- Department of Immunology and Oslo University Hospital, University of Oslo, Oslo 0372, Norway
| | - Fabio Grassi
- Institute for Research in Biomedicine, Faculty of Biomedical Sciences, Università della Svizzera Italiana, Bellinzona 6500, Switzerland.
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7
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Deng L, Yang F, Xu Z, Li F, Zhao J, Deng H, Jian Z, Lai S, Sun X, Zhu L. Characterization of B cell receptor H-CDR3 repertoire of spleen in PRV-infected mice. BMC Vet Res 2022; 18:228. [PMID: 35715782 PMCID: PMC9204683 DOI: 10.1186/s12917-022-03340-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Accepted: 06/06/2022] [Indexed: 11/23/2022] Open
Abstract
Pseudorabies virus (PRV), also known as suid Alphaherpesvirus 1 (SuHV-1), which is one of the most devastating infectious pathogen of swine industry worldwide. Vaccination is the safest and most effective PRV prevention and control strategy. B cell receptor (BCR) is membrane-bound immunoglobulin located on the surface of B cells capable of specifically binding foreign antigens, which is one of the most important molecules regulating the proliferation and function of B cells. Here, to assess the molecular diversity of BCR H-CDR3 repertoire after different PRV strains infection, we detected the IGHV, IGHD, IGHJ genes usage and CDR3 sequence changes of mice spleen with PRV vaccine strain (Bartha-K61), variant strain (XJ) and mock infection by high-throughput sequencing. We found that PRV-infected groups shared partial BCR sequences, which are most likely to be PRV-specific BCR candidates. However, there were still differences in the IGHV genes usage as well as the combined usage of IGHV and IGHJ genes between the Bartha-K61 strain and XJ strain infection groups. In addition, the CDR3 sequences exhibited large differences in the types and lengths in PRV infection groups. Our study contributes to a better understanding of the host adaptive immune response to PRV infection and provides a theoretical basis for further research on novel and efficient PRV vaccines in the future.
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Affiliation(s)
- Lishuang Deng
- College of Veterinary Medicine, Sichuan Agricultural University, Chengdu, China
| | - Fan Yang
- College of Veterinary Medicine, Sichuan Agricultural University, Chengdu, China
| | - Zhiwen Xu
- College of Veterinary Medicine, Sichuan Agricultural University, Chengdu, China
- Key Laboratory of Animal Diseases and Human Health of Sichuan Province, Chengdu, China
| | - Fengqin Li
- College of Veterinary Medicine, Sichuan Agricultural University, Chengdu, China
- College of Animal Science, Xichang University, Xichang, China
| | - Jun Zhao
- College of Veterinary Medicine, Sichuan Agricultural University, Chengdu, China
| | - Huidan Deng
- College of Veterinary Medicine, Sichuan Agricultural University, Chengdu, China
| | - Zhijie Jian
- College of Veterinary Medicine, Sichuan Agricultural University, Chengdu, China
| | - Siyuan Lai
- College of Veterinary Medicine, Sichuan Agricultural University, Chengdu, China
| | - Xiangang Sun
- College of Veterinary Medicine, Sichuan Agricultural University, Chengdu, China
| | - Ling Zhu
- College of Veterinary Medicine, Sichuan Agricultural University, Chengdu, China.
- Key Laboratory of Animal Diseases and Human Health of Sichuan Province, Chengdu, China.
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8
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Dahal-Koirala S, Balaban G, Neumann RS, Scheffer L, Lundin KEA, Greiff V, Sollid LM, Qiao SW, Sandve GK. TCRpower: quantifying the detection power of T-cell receptor sequencing with a novel computational pipeline calibrated by spike-in sequences. Brief Bioinform 2022; 23:bbab566. [PMID: 35062022 PMCID: PMC8921636 DOI: 10.1093/bib/bbab566] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Revised: 12/02/2021] [Accepted: 12/11/2021] [Indexed: 01/19/2023] Open
Abstract
T-cell receptor (TCR) sequencing has enabled the development of innovative diagnostic tests for cancers, autoimmune diseases and other applications. However, the rarity of many T-cell clonotypes presents a detection challenge, which may lead to misdiagnosis if diagnostically relevant TCRs remain undetected. To address this issue, we developed TCRpower, a novel computational pipeline for quantifying the statistical detection power of TCR sequencing methods. TCRpower calculates the probability of detecting a TCR sequence as a function of several key parameters: in-vivo TCR frequency, T-cell sample count, read sequencing depth and read cutoff. To calibrate TCRpower, we selected unique TCRs of 45 T-cell clones (TCCs) as spike-in TCRs. We sequenced the spike-in TCRs from TCCs, together with TCRs from peripheral blood, using a 5' RACE protocol. The 45 spike-in TCRs covered a wide range of sample frequencies, ranging from 5 per 100 to 1 per 1 million. The resulting spike-in TCR read counts and ground truth frequencies allowed us to calibrate TCRpower. In our TCR sequencing data, we observed a consistent linear relationship between sample and sequencing read frequencies. We were also able to reliably detect spike-in TCRs with frequencies as low as one per million. By implementing an optimized read cutoff, we eliminated most of the falsely detected sequences in our data (TCR α-chain 99.0% and TCR β-chain 92.4%), thereby improving diagnostic specificity. TCRpower is publicly available and can be used to optimize future TCR sequencing experiments, and thereby enable reliable detection of disease-relevant TCRs for diagnostic applications.
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Affiliation(s)
- Shiva Dahal-Koirala
- K.G. Jebsen Coeliac Disease Research Centre, University of Oslo, Oslo, 0372, Norway
- Department of Immunology, University of Oslo and Oslo University Hospital-Rikshospitalet, Oslo, 0372, Norway
| | - Gabriel Balaban
- Biomedical Informatics, Department of Informatics, University of Oslo, 0373, Oslo, Norway
- Department of Computational Physiology, Simula Research Laboratory, 1364, Fornebu, Norway
- PharmaTox Strategic Research Initiative, Faculty of Mathematics and Natural Sciences, University of Oslo, 0373, Oslo, Norway
| | - Ralf Stefan Neumann
- K.G. Jebsen Coeliac Disease Research Centre, University of Oslo, Oslo, 0372, Norway
| | - Lonneke Scheffer
- Biomedical Informatics, Department of Informatics, University of Oslo, 0373, Oslo, Norway
| | - Knut Erik Aslaksen Lundin
- K.G. Jebsen Coeliac Disease Research Centre, University of Oslo, Oslo, 0372, Norway
- Department of Gastroenterology, Oslo University Hospital-Rikshospitalet, 0372, Oslo, Norway
| | - Victor Greiff
- Department of Immunology, University of Oslo and Oslo University Hospital-Rikshospitalet, Oslo, 0372, Norway
| | - Ludvig Magne Sollid
- K.G. Jebsen Coeliac Disease Research Centre, University of Oslo, Oslo, 0372, Norway
- Department of Immunology, University of Oslo and Oslo University Hospital-Rikshospitalet, Oslo, 0372, Norway
| | - Shuo-Wang Qiao
- K.G. Jebsen Coeliac Disease Research Centre, University of Oslo, Oslo, 0372, Norway
- Department of Immunology, University of Oslo and Oslo University Hospital-Rikshospitalet, Oslo, 0372, Norway
| | - Geir Kjetil Sandve
- Biomedical Informatics, Department of Informatics, University of Oslo, 0373, Oslo, Norway
- PharmaTox Strategic Research Initiative, Faculty of Mathematics and Natural Sciences, University of Oslo, 0373, Oslo, Norway
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9
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Marquez S, Babrak L, Greiff V, Hoehn KB, Lees WD, Luning Prak ET, Miho E, Rosenfeld AM, Schramm CA, Stervbo U. Adaptive Immune Receptor Repertoire (AIRR) Community Guide to Repertoire Analysis. Methods Mol Biol 2022; 2453:297-316. [PMID: 35622333 PMCID: PMC9761518 DOI: 10.1007/978-1-0716-2115-8_17] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
Adaptive immune receptor repertoires (AIRRs) are rich with information that can be mined for insights into the workings of the immune system. Gene usage, CDR3 properties, clonal lineage structure, and sequence diversity are all capable of revealing the dynamic immune response to perturbation by disease, vaccination, or other interventions. Here we focus on a conceptual introduction to the many aspects of repertoire analysis and orient the reader toward the uses and advantages of each. Along the way, we note some of the many software tools that have been developed for these investigations and link the ideas discussed to chapters on methods provided elsewhere in this volume.
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Affiliation(s)
- Susanna Marquez
- Department of Pathology, Yale School of Medicine, New Haven, CT, USA
| | - Lmar Babrak
- Institute of Biomedical Engineering and Medical Informatics, School of Life Sciences, FHNW University of Applied Sciences and Arts Northwestern Switzerland, Muttenz, Switzerland
| | - Victor Greiff
- Department of Immunology, University of Oslo, Oslo University Hospital, Oslo, Norway
| | - Kenneth B Hoehn
- Department of Pathology, Yale School of Medicine, New Haven, CT, USA
| | - William D Lees
- Institute of Structural and Molecular Biology, Birkbeck College, University of London, London, UK
| | - Eline T Luning Prak
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Enkelejda Miho
- Institute of Biomedical Engineering and Medical Informatics, School of Life Sciences, FHNW University of Applied Sciences and Arts Northwestern Switzerland, Muttenz, Switzerland
- SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
- aiNET GmbH, Basel, Switzerland
| | - Aaron M Rosenfeld
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Chaim A Schramm
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA.
| | - Ulrik Stervbo
- Center for Translational Medicine, Immunology, and Transplantation, Medical Department I, Marien Hospital Herne, University Hospital of the Ruhr-University Bochum, Herne, Germany.
- Immundiagnostik, Marien Hospital Herne, University Hospital of the Ruhr-University Bochum, Herne, Germany.
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10
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Rettig TA, Tan JC, Nishiyama NC, Chapes SK, Pecaut MJ. An Analysis of the Effects of Spaceflight and Vaccination on Antibody Repertoire Diversity. Immunohorizons 2021; 5:675-686. [PMID: 34433623 PMCID: PMC10996920 DOI: 10.4049/immunohorizons.2100056] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Accepted: 07/26/2021] [Indexed: 11/19/2022] Open
Abstract
Ab repertoire diversity plays a critical role in the host's ability to fight pathogens. CDR3 is partially responsible for Ab-Ag binding and is a significant source of diversity in the repertoire. CDR3 diversity is generated during VDJ rearrangement because of gene segment selection, gene segment trimming and splicing, and the addition of nucleotides. We analyzed the Ab repertoire diversity across multiple experiments examining the effects of spaceflight on the Ab repertoire after vaccination. Five datasets from four experiments were analyzed using rank-abundance curves and Shannon indices as measures of diversity. We discovered a trend toward lower diversity as a result of spaceflight but did not find the same decrease in our physiological model of microgravity in either the spleen or bone marrow. However, the bone marrow repertoire showed a reduction in diversity after vaccination. We also detected differences in Shannon indices between experiments and tissues. We did not detect a pattern of CDR3 usage across the experiments. Overall, we were able to find differences in the Ab repertoire diversity across experimental groups and tissues.
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Affiliation(s)
- Trisha A Rettig
- Division of Biomedical Engineering Sciences, Department of Basic Sciences, Loma Linda University, Loma Linda, CA
- Division of Biology, Kansas State University, Manhattan, KS
| | - John C Tan
- Division of Biomedical Engineering Sciences, Department of Basic Sciences, Loma Linda University, Loma Linda, CA
| | - Nina C Nishiyama
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC; and
- Center for Gastrointestinal Biology and Disease, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | | | - Michael J Pecaut
- Division of Biomedical Engineering Sciences, Department of Basic Sciences, Loma Linda University, Loma Linda, CA;
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11
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Aizik L, Dror Y, Taussig D, Barzel A, Carmi Y, Wine Y. Antibody Repertoire Analysis of Tumor-Infiltrating B Cells Reveals Distinct Signatures and Distributions Across Tissues. Front Immunol 2021; 12:705381. [PMID: 34349765 PMCID: PMC8327180 DOI: 10.3389/fimmu.2021.705381] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Accepted: 06/29/2021] [Indexed: 12/12/2022] Open
Abstract
The role of B cells in the tumor microenvironment (TME) has largely been under investigated, and data regarding the antibody repertoire encoded by B cells in the TME and the adjacent lymphoid organs are scarce. Here, we utilized B cell receptor high-throughput sequencing (BCR-Seq) to profile the antibody repertoire signature of tumor-infiltrating lymphocyte B cells (TIL−Bs) in comparison to B cells from three anatomic compartments in a mouse model of triple-negative breast cancer. We found that TIL-Bs exhibit distinct antibody repertoire measures, including high clonal polarization and elevated somatic hypermutation rates, suggesting a local antigen-driven B-cell response. Importantly, TIL-Bs were highly mutated but non-class switched, suggesting that class-switch recombination may be inhibited in the TME. Tracing the distribution of TIL-B clones across various compartments indicated that they migrate to and from the TME. The data thus suggests that antibody repertoire signatures can serve as indicators for identifying tumor-reactive B cells.
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Affiliation(s)
- Ligal Aizik
- The Shmunis School of Biomedicine and Cancer Research, The George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Yael Dror
- The Shmunis School of Biomedicine and Cancer Research, The George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
| | - David Taussig
- The Shmunis School of Biomedicine and Cancer Research, The George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Adi Barzel
- The School of Neurobiology, Biochemistry and Biophysics, The George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Yaron Carmi
- Department of Pathology, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Yariv Wine
- The Shmunis School of Biomedicine and Cancer Research, The George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
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12
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Recapitulation of posttransfusion purpura by cross-strain platelet immunization in mice. Blood Adv 2021; 4:287-295. [PMID: 31968077 DOI: 10.1182/bloodadvances.2019000661] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2019] [Accepted: 12/13/2019] [Indexed: 02/07/2023] Open
Abstract
Posttransfusion purpura (PTP) is an uncommon but life-threatening condition characterized by profound thrombocytopenia occurring ∼1 week after a blood transfusion. The hallmark of PTP is a potent immunoglobulin G antibody specific for a transfused platelet-specific alloantigen, usually located on glycoprotein IIb/IIIa (GPIIb/IIIa; αIIb/β3 integrin). It is widely thought that this alloantibody somehow causes the thrombocytopenia, despite absence from host platelets of the alloantigen for which it is specific. In studies described here, we found that cross-strain platelet immunization in mice commonly induces GPIIb/IIIa-specific alloantibodies combined with platelet-specific autoantibodies and varying degrees of thrombocytopenia, and we identified 1 strain combination (129S1Svlm/PWKPhJ) in which 95% of immunized mice made both types of antibody and developed severe thrombocytopenia. There was a strong inverse correlation between autoantibody strength and platelet decline (P < .0001) and plasma from mice that produced autoantibodies caused thrombocytopenia when transfused to syngeneic animals, arguing that autoantibodies were the cause of thrombocytopenia. The findings define a model in which a routine alloimmune response to platelets regularly transitions to an autoimmune reaction capable of causing severe thrombocytopenia and support the hypothesis that PTP is an autoimmune disorder.
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13
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A single donor is sufficient to produce a highly functional in vitro antibody library. Commun Biol 2021; 4:350. [PMID: 33742103 PMCID: PMC7979914 DOI: 10.1038/s42003-021-01881-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Accepted: 02/19/2021] [Indexed: 01/31/2023] Open
Abstract
Antibody complementarity determining region diversity has been considered to be the most important metric for the production of a functional antibody library. Generally, the greater the antibody library diversity, the greater the probability of selecting a diverse array of high affinity leads. According to this paradigm, the primary means of elevating library diversity has been by increasing the number of donors. In the present study we explored the possibility of creating an in vitro antibody library from a single healthy individual, showing that the number of lymphocytes, rather than the number of donors, is the key criterion in the production of a diverse and functional antibody library. We describe the construction of a high-quality phage display library comprising 5 × 109 human antibodies by applying an efficient B cell extraction protocol from a single donor and a targeted V-gene amplification strategy favoring specific antibody families for their improved developability profiles. Each step of the library generation process was followed and validated by next generation sequencing to monitor the library quality and diversity. The functionality of the library was tested using several therapeutically relevant targets for which a vast number of different antibodies with desired biophysical properties were obtained.
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14
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Avram O, Kigel A, Vaisman-Mentesh A, Kligsberg S, Rosenstein S, Dror Y, Pupko T, Wine Y. PASA: Proteomic analysis of serum antibodies web server. PLoS Comput Biol 2021; 17:e1008607. [PMID: 33493161 PMCID: PMC7861515 DOI: 10.1371/journal.pcbi.1008607] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Revised: 02/04/2021] [Accepted: 12/06/2020] [Indexed: 01/17/2023] Open
Abstract
MOTIVATION A comprehensive characterization of the humoral response towards a specific antigen requires quantification of the B-cell receptor repertoire by next-generation sequencing (BCR-Seq), as well as the analysis of serum antibodies against this antigen, using proteomics. The proteomic analysis is challenging since it necessitates the mapping of antigen-specific peptides to individual B-cell clones. RESULTS The PASA web server provides a robust computational platform for the analysis and integration of data obtained from proteomics of serum antibodies. PASA maps peptides derived from antibodies raised against a specific antigen to corresponding antibody sequences. It then analyzes and integrates proteomics and BCR-Seq data, thus providing a comprehensive characterization of the humoral response. The PASA web server is freely available at https://pasa.tau.ac.il and open to all users without a login requirement.
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Affiliation(s)
- Oren Avram
- The Shmunis School of Biomedicine and Cancer Research, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Aya Kigel
- The Shmunis School of Biomedicine and Cancer Research, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Anna Vaisman-Mentesh
- The Shmunis School of Biomedicine and Cancer Research, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Sharon Kligsberg
- The Shmunis School of Biomedicine and Cancer Research, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Shai Rosenstein
- The Shmunis School of Biomedicine and Cancer Research, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Yael Dror
- The Shmunis School of Biomedicine and Cancer Research, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Tal Pupko
- The Shmunis School of Biomedicine and Cancer Research, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Yariv Wine
- The Shmunis School of Biomedicine and Cancer Research, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
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15
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Szikora B, Marx A, Jani PK, Pipek O, Müller V, Csabai I, Kacskovics I. FcRn Overexpression Expands Diversity of the Humoral Immune Response in bFcRn Transgenic Mice. Front Immunol 2020; 11:1887. [PMID: 32973781 PMCID: PMC7472951 DOI: 10.3389/fimmu.2020.01887] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2020] [Accepted: 07/13/2020] [Indexed: 11/30/2022] Open
Abstract
The neonatal Fc receptor (FcRn) plays key roles in IgG and albumin homeostasis, maternal IgG transport, and antigen presentation of IgG-opsonized antigens. Previously, we reported that transgenic (Tg) mice that overexpress bovine FcRn (bFcRn) have augmented T-dependent humoral immune response with increased IgG protection, higher level of antigen-specific antibodies, greater number of antigen-specific B cells, and effective immune response even against weakly immunogenic epitopes. In this study we analyzed the diversity of the humoral immune response of bFcRn Tg mice, using a length distribution analysis (spectratyping) and next generation sequencing (NGS) of the immunoglobulin heavy chain variable regions. Our analysis showed that in response to immunization with ovalbumin or transfected cells that expressed a unique membrane protein, our Tg animals developed a more diverse plasma cell repertoire than controls, which manifested in greater numbers of different clones, and clusters with fewer highly expanded large clones, as identified by the variable region (CDR3) of the immunoglobulin heavy chain. The increased antibody diversity in Tg mice after immunization was observed at both IgM and IgG levels, indicating that the increased humoral immune diversity in Tg mice is due to a higher number of both activated, antigen-specific naïve and isotype switched B cells. We thus demonstrated that the BCR repertoire of the immunized bFcRn Tg animals is more diverse compared to wild type mice, which likely makes these Tg mice a better choice for monoclonal antibody production against challenging antigens, including the extracellular regions of cell membrane proteins.
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Affiliation(s)
- Bence Szikora
- Department of Immunology, Institute of Biology, Eötvös Loránd University, Budapest, Hungary
| | - Anita Marx
- Department of Immunology, Institute of Biology, Eötvös Loránd University, Budapest, Hungary
| | | | - Orsolya Pipek
- Department of Physics of Complex Systems, Institute of Physics, Eötvös Loránd University, Budapest, Hungary
| | - Viktor Müller
- Department of Plant Systematics, Ecology and Theoretical Biology, Institute of Biology, Eötvös Loránd University, Budapest, Hungary
| | - István Csabai
- Department of Physics of Complex Systems, Institute of Physics, Eötvös Loránd University, Budapest, Hungary
| | - Imre Kacskovics
- Department of Immunology, Institute of Biology, Eötvös Loránd University, Budapest, Hungary.,ImmunoGenes Ltd., Budakeszi, Hungary
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16
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Mucosal or systemic microbiota exposures shape the B cell repertoire. Nature 2020; 584:274-278. [PMID: 32760003 DOI: 10.1038/s41586-020-2564-6] [Citation(s) in RCA: 134] [Impact Index Per Article: 26.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2019] [Accepted: 05/18/2020] [Indexed: 01/20/2023]
Abstract
Colonization by the microbiota causes a marked stimulation of B cells and induction of immunoglobulin, but mammals colonized with many taxa have highly complex and individualized immunoglobulin repertoires1,2. Here we use a simplified model of defined transient exposures to different microbial taxa in germ-free mice3 to deconstruct how the microbiota shapes the B cell pool and its functional responsiveness. We followed the development of the immunoglobulin repertoire in B cell populations, as well as single cells by deep sequencing. Microbial exposures at the intestinal mucosa generated oligoclonal responses that differed from those of germ-free mice, and from the diverse repertoire that was generated after intravenous systemic exposure to microbiota. The IgA repertoire-predominantly to cell-surface antigens-did not expand after dose escalation, whereas increased systemic exposure broadened the IgG repertoire to both microbial cytoplasmic and cell-surface antigens. These microbial exposures induced characteristic immunoglobulin heavy-chain repertoires in B cells, mainly at memory and plasma cell stages. Whereas sequential systemic exposure to different microbial taxa diversified the IgG repertoire and facilitated alternative specific responses, sequential mucosal exposure produced limited overlapping repertoires and the attrition of initial IgA binding specificities. This shows a contrast between a flexible response to systemic exposure with the need to avoid fatal sepsis, and a restricted response to mucosal exposure that reflects the generic nature of host-microbial mutualism in the mucosa.
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17
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Validation of Methods to Assess the Immunoglobulin Gene Repertoire in Tissues Obtained from Mice on the International Space Station. ACTA ACUST UNITED AC 2020. [DOI: 10.2478/gsr-2017-0001] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
Abstract
Spaceflight is known to affect immune cell populations. In particular, splenic B-cell numbers decrease during spaceflight and in ground-based physiological models. Although antibody isotype changes have been assessed during and after spaceflight, an extensive characterization of the impact of spaceflight on antibody composition has not been conducted in mice. Next Generation Sequencing and bioinformatic tools are now available to assess antibody repertoires. We can now identify immunoglobulin gene-segment usage, junctional regions, and modifications that contribute to specificity and diversity. Due to limitations on the International Space Station, alternate sample collection and storage methods must be employed. Our group compared Illumina MiSeq® sequencing data from multiple sample preparation methods in normal C57Bl/6J mice to validate that sample preparation and storage would not bias the outcome of antibody repertoire characterization. In this report, we also compared sequencing techniques and a bioinformatic workflow on the data output when we assessed the IgH and Igκ variable gene usage. Our bioinformatic workflow has been optimized for Illumina HiSeq® and MiSeq® datasets, and is designed specifically to reduce bias, capture the most information from Ig sequences, and produce a data set that provides other data mining options.
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18
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Pfister SP, Schären OP, Beldi L, Printz A, Notter MD, Mukherjee M, Li H, Limenitakis JP, Werren JP, Tandon D, Cuenca M, Hagemann S, Uster SS, Terrazos MA, Gomez de Agüero M, Schürch CM, Coelho FM, Curtiss R, Slack E, Balmer ML, Hapfelmeier S. Uncoupling of invasive bacterial mucosal immunogenicity from pathogenicity. Nat Commun 2020; 11:1978. [PMID: 32332737 PMCID: PMC7181798 DOI: 10.1038/s41467-020-15891-9] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2019] [Accepted: 03/30/2020] [Indexed: 11/17/2022] Open
Abstract
There is the notion that infection with a virulent intestinal pathogen induces generally stronger mucosal adaptive immunity than the exposure to an avirulent strain. Whether the associated mucosal inflammation is important or redundant for effective induction of immunity is, however, still unclear. Here we use a model of auxotrophic Salmonella infection in germ-free mice to show that live bacterial virulence factor-driven immunogenicity can be uncoupled from inflammatory pathogenicity. Although live auxotrophic Salmonella no longer causes inflammation, its mucosal virulence factors remain the main drivers of protective mucosal immunity; virulence factor-deficient, like killed, bacteria show reduced efficacy. Assessing the involvement of innate pathogen sensing mechanisms, we show MYD88/TRIF, Caspase-1/Caspase-11 inflammasome, and NOD1/NOD2 nodosome signaling to be individually redundant. In colonized animals we show that microbiota metabolite cross-feeding may recover intestinal luminal colonization but not pathogenicity. Consequent immunoglobulin A immunity and microbial niche competition synergistically protect against Salmonella wild-type infection.
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Affiliation(s)
- Simona P Pfister
- Institute for Infectious Diseases, University of Bern, Bern, Switzerland
- Graduate School GCB, University of Bern, Bern, Switzerland
| | - Olivier P Schären
- Institute for Infectious Diseases, University of Bern, Bern, Switzerland
- Graduate School GCB, University of Bern, Bern, Switzerland
| | - Luca Beldi
- Institute for Infectious Diseases, University of Bern, Bern, Switzerland
| | - Andrea Printz
- Institute for Infectious Diseases, University of Bern, Bern, Switzerland
| | - Matheus D Notter
- Institute for Infectious Diseases, University of Bern, Bern, Switzerland
- Graduate School GCB, University of Bern, Bern, Switzerland
| | - Mohana Mukherjee
- Institute for Infectious Diseases, University of Bern, Bern, Switzerland
- Graduate School GCB, University of Bern, Bern, Switzerland
| | - Hai Li
- Maurice Müller Laboratories (DBMR), Universitätsklinik für Viszerale Chirurgie und Medizin (UVCM) Inselspital, Bern, Switzerland
| | - Julien P Limenitakis
- Maurice Müller Laboratories (DBMR), Universitätsklinik für Viszerale Chirurgie und Medizin (UVCM) Inselspital, Bern, Switzerland
| | - Joel P Werren
- Institute for Infectious Diseases, University of Bern, Bern, Switzerland
- Graduate School GCB, University of Bern, Bern, Switzerland
| | - Disha Tandon
- Institute for Infectious Diseases, University of Bern, Bern, Switzerland
- Graduate School GCB, University of Bern, Bern, Switzerland
| | - Miguelangel Cuenca
- Institute for Infectious Diseases, University of Bern, Bern, Switzerland
| | - Stefanie Hagemann
- Institute for Infectious Diseases, University of Bern, Bern, Switzerland
| | - Stephanie S Uster
- Institute for Infectious Diseases, University of Bern, Bern, Switzerland
| | - Miguel A Terrazos
- Institute for Infectious Diseases, University of Bern, Bern, Switzerland
| | - Mercedes Gomez de Agüero
- Maurice Müller Laboratories (DBMR), Universitätsklinik für Viszerale Chirurgie und Medizin (UVCM) Inselspital, Bern, Switzerland
| | - Christian M Schürch
- Institute of Pathology, University of Bern, Bern, Switzerland
- Institute of Pathology and Neuropathology and Comprehensive Cancer Center, University Hospital Tübingen, Tübingen, Germany
- Baxter Laboratory for Stem Cell Biology, Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA, USA
| | - Fernanda M Coelho
- Institute for Infectious Diseases, University of Bern, Bern, Switzerland
| | - Roy Curtiss
- Biodesign Institute, Arizona State University, Tempe, AZ, USA
| | - Emma Slack
- Institute for Food, Nutrition and Health, D-HEST, ETH Zürich, Switzerland
| | - Maria L Balmer
- Department of Biomedicine, Immunobiology, University of Basel, Basel, Switzerland
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19
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Aversa I, Malanga D, Fiume G, Palmieri C. Molecular T-Cell Repertoire Analysis as Source of Prognostic and Predictive Biomarkers for Checkpoint Blockade Immunotherapy. Int J Mol Sci 2020; 21:ijms21072378. [PMID: 32235561 PMCID: PMC7177412 DOI: 10.3390/ijms21072378] [Citation(s) in RCA: 45] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2020] [Revised: 03/22/2020] [Accepted: 03/28/2020] [Indexed: 02/08/2023] Open
Abstract
The T cells are key players of the response to checkpoint blockade immunotherapy (CBI) and monitoring the strength and specificity of antitumor T-cell reactivity remains a crucial but elusive component of precision immunotherapy. The entire assembly of T-cell receptor (TCR) sequences accounts for antigen specificity and strength of the T-cell immune response. The TCR repertoire hence represents a “footprint” of the conditions faced by T cells that dynamically evolves according to the challenges that arise for the immune system, such as tumor neo-antigenic load. Hence, TCR repertoire analysis is becoming increasingly important to comprehensively understand the nature of a successful antitumor T-cell response, and to improve the success and safety of current CBI.
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Affiliation(s)
- Ilenia Aversa
- Research Center of Biochemistry and Advanced Molecular Biology, Department of Experimental and Clinical Medicine, University “Magna Græcia” of Catanzaro, 88100 Catanzaro, Italy;
| | - Donatella Malanga
- Interdepartmental Center of Services (CIS), Department of Experimental and Clinical Medicine, University “Magna Græcia” of Catanzaro, 88100 Catanzaro, Italy;
| | - Giuseppe Fiume
- Department of Experimental and Clinical Medicine, University “Magna Græcia” of Catanzaro, 88100 Catanzaro, Italy;
| | - Camillo Palmieri
- Department of Experimental and Clinical Medicine, University “Magna Græcia” of Catanzaro, 88100 Catanzaro, Italy;
- Correspondence:
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20
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Vaisman-Mentesh A, Rosenstein S, Yavzori M, Dror Y, Fudim E, Ungar B, Kopylov U, Picard O, Kigel A, Ben-Horin S, Benhar I, Wine Y. Molecular Landscape of Anti-Drug Antibodies Reveals the Mechanism of the Immune Response Following Treatment With TNFα Antagonists. Front Immunol 2019; 10:2921. [PMID: 31921180 PMCID: PMC6930160 DOI: 10.3389/fimmu.2019.02921] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2019] [Accepted: 11/28/2019] [Indexed: 12/25/2022] Open
Abstract
Drugs formulated from monoclonal antibodies (mAbs) are clinically effective in various diseases. Repeated administration of mAbs, however, elicits an immune response in the form of anti-drug-antibodies (ADA), thereby reducing the drug's efficacy. Notwithstanding their importance, the molecular landscape of ADA and the mechanisms involved in their formation are not fully understood. Using a newly developed quantitative bio-immunoassay, we found that ADA concentrations specific to TNFα antagonists can exceed extreme concentrations of 1 mg/ml with a wide range of neutralization capacity. Our data further suggest a preferential use of the λ light chain in a subset of neutralizing ADA. Moreover, we show that administration of TNFα antagonists result in a vaccine-like response whereby ADA formation is governed by the extrafollicular T cell-independent immune response. Our bio-immunoassay coupled with insights on the nature of the immune response can be leveraged to improve mAb immunogenicity assessment and facilitate improvement in therapeutic intervention strategies.
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Affiliation(s)
- Anna Vaisman-Mentesh
- George S. Wise Faculty of Life Sciences, School of Molecular Cell Biology and Biotechnology, Tel Aviv University, Tel Aviv-Yafo, Israel
| | - Shai Rosenstein
- George S. Wise Faculty of Life Sciences, School of Molecular Cell Biology and Biotechnology, Tel Aviv University, Tel Aviv-Yafo, Israel
| | - Miri Yavzori
- Gastroenterology Department, Sheba Medical Center and Sackler School of Medicine, Tel-Aviv University, Tel Aviv-Yafo, Israel
| | - Yael Dror
- George S. Wise Faculty of Life Sciences, School of Molecular Cell Biology and Biotechnology, Tel Aviv University, Tel Aviv-Yafo, Israel
| | - Ella Fudim
- Gastroenterology Department, Sheba Medical Center and Sackler School of Medicine, Tel-Aviv University, Tel Aviv-Yafo, Israel
| | - Bella Ungar
- Gastroenterology Department, Sheba Medical Center and Sackler School of Medicine, Tel-Aviv University, Tel Aviv-Yafo, Israel
| | - Uri Kopylov
- Gastroenterology Department, Sheba Medical Center and Sackler School of Medicine, Tel-Aviv University, Tel Aviv-Yafo, Israel
| | - Orit Picard
- Gastroenterology Department, Sheba Medical Center and Sackler School of Medicine, Tel-Aviv University, Tel Aviv-Yafo, Israel
| | - Aya Kigel
- George S. Wise Faculty of Life Sciences, School of Molecular Cell Biology and Biotechnology, Tel Aviv University, Tel Aviv-Yafo, Israel
| | - Shomron Ben-Horin
- Gastroenterology Department, Sheba Medical Center and Sackler School of Medicine, Tel-Aviv University, Tel Aviv-Yafo, Israel
| | - Itai Benhar
- George S. Wise Faculty of Life Sciences, School of Molecular Cell Biology and Biotechnology, Tel Aviv University, Tel Aviv-Yafo, Israel
| | - Yariv Wine
- George S. Wise Faculty of Life Sciences, School of Molecular Cell Biology and Biotechnology, Tel Aviv University, Tel Aviv-Yafo, Israel
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21
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Bartolomé-Casado R, Landsverk OJB, Chauhan SK, Richter L, Phung D, Greiff V, Risnes LF, Yao Y, Neumann RS, Yaqub S, Øyen O, Horneland R, Aandahl EM, Paulsen V, Sollid LM, Qiao SW, Baekkevold ES, Jahnsen FL. Resident memory CD8 T cells persist for years in human small intestine. J Exp Med 2019; 216:2412-2426. [PMID: 31337737 PMCID: PMC6781004 DOI: 10.1084/jem.20190414] [Citation(s) in RCA: 109] [Impact Index Per Article: 18.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2019] [Revised: 05/13/2019] [Accepted: 06/20/2019] [Indexed: 12/26/2022] Open
Abstract
Bartolomé-Casado et al. demonstrate that human gut contains large numbers of resident memory CD8 T cells that survive for years. Intestinal CD8 Trm cells have a clonally expanded immune repertoire that is stable over time and exhibit enhanced protective capabilities. Resident memory CD8 T (Trm) cells have been shown to provide effective protective responses in the small intestine (SI) in mice. A better understanding of the generation and persistence of SI CD8 Trm cells in humans may have implications for intestinal immune-mediated diseases and vaccine development. Analyzing normal and transplanted human SI, we demonstrated that the majority of SI CD8 T cells were bona fide CD8 Trm cells that survived for >1 yr in the graft. Intraepithelial and lamina propria CD8 Trm cells showed a high clonal overlap and a repertoire dominated by expanded clones, conserved both spatially in the intestine and over time. Functionally, lamina propria CD8 Trm cells were potent cytokine producers, exhibiting a polyfunctional (IFN-γ+ IL-2+ TNF-α+) profile, and efficiently expressed cytotoxic mediators after stimulation. These results suggest that SI CD8 Trm cells could be relevant targets for future oral vaccines and therapeutic strategies for gut disorders.
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Affiliation(s)
| | - Ole J B Landsverk
- Department of Pathology, Oslo University Hospital and University of Oslo, Oslo, Norway
| | - Sudhir Kumar Chauhan
- Department of Pathology, Oslo University Hospital and University of Oslo, Oslo, Norway.,Department of Cancer Immunology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
| | - Lisa Richter
- Department of Pathology, Oslo University Hospital and University of Oslo, Oslo, Norway.,Core Facility Flow Cytometry, Biomedical Center, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Danh Phung
- Department of Pathology, Oslo University Hospital and University of Oslo, Oslo, Norway
| | - Victor Greiff
- Department of Immunology, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Louise F Risnes
- Department of Immunology, Oslo University Hospital, Rikshospitalet, Oslo, Norway.,K.G. Jebsen Coeliac Disease Research Centre, University of Oslo, Oslo, Norway
| | - Ying Yao
- Department of Immunology, Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,K.G. Jebsen Coeliac Disease Research Centre, University of Oslo, Oslo, Norway
| | - Ralf S Neumann
- Department of Immunology, Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,K.G. Jebsen Coeliac Disease Research Centre, University of Oslo, Oslo, Norway
| | - Sheraz Yaqub
- Department of Gastrointestinal Surgery, Oslo University Hospital, Rikshospitalet, Oslo, Norway
| | - Ole Øyen
- Department of Transplantation Medicine, Section for Transplant Surgery, Oslo University Hospital, Rikshospitalet, Oslo, Norway
| | - Rune Horneland
- Department of Transplantation Medicine, Section for Transplant Surgery, Oslo University Hospital, Rikshospitalet, Oslo, Norway
| | - Einar Martin Aandahl
- Department of Cancer Immunology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway.,Department of Transplantation Medicine, Section for Transplant Surgery, Oslo University Hospital, Rikshospitalet, Oslo, Norway
| | - Vemund Paulsen
- Department of Gastroenterology, Oslo University Hospital, Rikshospitalet, Oslo, Norway
| | - Ludvig M Sollid
- Department of Immunology, Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Department of Immunology, Oslo University Hospital, Rikshospitalet, Oslo, Norway.,K.G. Jebsen Coeliac Disease Research Centre, University of Oslo, Oslo, Norway
| | - Shuo-Wang Qiao
- Department of Immunology, Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,K.G. Jebsen Coeliac Disease Research Centre, University of Oslo, Oslo, Norway
| | - Espen S Baekkevold
- Department of Pathology, Oslo University Hospital and University of Oslo, Oslo, Norway
| | - Frode L Jahnsen
- Department of Pathology, Oslo University Hospital and University of Oslo, Oslo, Norway
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22
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Grootjans J, Krupka N, Hosomi S, Matute JD, Hanley T, Saveljeva S, Gensollen T, Heijmans J, Li H, Limenitakis JP, Ganal-Vonarburg SC, Suo S, Luoma AM, Shimodaira Y, Duan J, Shih DQ, Conner ME, Glickman JN, Fuhler GM, Palm NW, de Zoete MR, van der Woude CJ, Yuan GC, Wucherpfennig KW, Targan SR, Rosenstiel P, Flavell RA, McCoy KD, Macpherson AJ, Kaser A, Blumberg RS. Epithelial endoplasmic reticulum stress orchestrates a protective IgA response. Science 2019; 363:993-998. [PMID: 30819965 PMCID: PMC6637967 DOI: 10.1126/science.aat7186] [Citation(s) in RCA: 53] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2018] [Revised: 09/16/2018] [Accepted: 02/08/2019] [Indexed: 12/25/2022]
Abstract
Immunoglobulin A (IgA) is the major secretory immunoglobulin isotype found at mucosal surfaces, where it regulates microbial commensalism and excludes luminal factors from contacting intestinal epithelial cells (IECs). IgA is induced by both T cell-dependent and -independent (TI) pathways. However, little is known about TI regulation. We report that IEC endoplasmic reticulum (ER) stress induces a polyreactive IgA response, which is protective against enteric inflammation. IEC ER stress causes TI and microbiota-independent expansion and activation of peritoneal B1b cells, which culminates in increased lamina propria and luminal IgA. Increased numbers of IgA-producing plasma cells were observed in healthy humans with defective autophagy, who are known to exhibit IEC ER stress. Upon ER stress, IECs communicate signals to the peritoneum that induce a barrier-protective TI IgA response.
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Affiliation(s)
- Joep Grootjans
- Division of Gastroenterology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA 02115, USA
- Amsterdam University Medical Center, University of Amsterdam, Department of Gastroenterology and Hepatology and Tygat Institute for Liver and Intestinal Research, Meibergdreef 9, Amsterdam, Netherlands
| | - Niklas Krupka
- Division of Gastroenterology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA 02115, USA
- Maurice Müller Laboratories (DBMR), Universitätsklinik für Viszerale Chirurgie und Medizin Inselspital, Murtenstrasse 35, University of Bern, 3010 Bern, Switzerland
| | - Shuhei Hosomi
- Division of Gastroenterology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA 02115, USA
- Department of Gastroenterology, Osaka City University Graduate School of Medicine, 1-4-3, Asahi-machi, Abeno-ku, Osaka 545-8585, Japan
| | - Juan D Matute
- Division of Gastroenterology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA 02115, USA
- Division of Neonatology, Department of Pediatrics, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Thomas Hanley
- Division of Gastroenterology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA 02115, USA
| | - Svetlana Saveljeva
- Division of Gastroenterology and Hepatology, Department of Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Thomas Gensollen
- Division of Gastroenterology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA 02115, USA
| | - Jarom Heijmans
- Amsterdam University Medical Center, University of Amsterdam, Department of Internal Medicine, Tygat Institute for Liver and Intestinal Research, Meibergdreef 9, Amsterdam, Netherlands
| | - Hai Li
- Maurice Müller Laboratories (DBMR), Universitätsklinik für Viszerale Chirurgie und Medizin Inselspital, Murtenstrasse 35, University of Bern, 3010 Bern, Switzerland
| | - Julien P Limenitakis
- Maurice Müller Laboratories (DBMR), Universitätsklinik für Viszerale Chirurgie und Medizin Inselspital, Murtenstrasse 35, University of Bern, 3010 Bern, Switzerland
| | - Stephanie C Ganal-Vonarburg
- Maurice Müller Laboratories (DBMR), Universitätsklinik für Viszerale Chirurgie und Medizin Inselspital, Murtenstrasse 35, University of Bern, 3010 Bern, Switzerland
| | - Shengbao Suo
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | - Adrienne M Luoma
- Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA 02215, USA
| | - Yosuke Shimodaira
- F. Widjaja Foundation, Inflammatory Bowel and Immunobiology Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Jinzhi Duan
- Division of Gastroenterology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA 02115, USA
| | - David Q Shih
- F. Widjaja Foundation, Inflammatory Bowel and Immunobiology Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Margaret E Conner
- Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX 77030, USA
| | - Jonathan N Glickman
- Department of Pathology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02215, USA
| | - Gwenny M Fuhler
- Department of Gastroenterology and Hepatology, Erasmus MC, University Medical Center, Rotterdam, Netherlands
| | - Noah W Palm
- Department of Immunobiology, Yale University School of Medicine, New Haven, CT 06519, USA
| | - Marcel R de Zoete
- Department of Infectious Diseases and Immunology, Faculty of Veterinary Medicine, Utrecht University, Utrecht, Netherlands
| | - C Janneke van der Woude
- Department of Gastroenterology and Hepatology, Erasmus MC, University Medical Center, Rotterdam, Netherlands
| | - Guo-Cheng Yuan
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | - Kai W Wucherpfennig
- Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA 02215, USA
| | - Stephan R Targan
- F. Widjaja Foundation, Inflammatory Bowel and Immunobiology Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Philip Rosenstiel
- Institute of Clinical Molecular Biology, Christian-Albrechts-University Kiel, Rosalind-Franklin-Str. 12, 24105 Kiel, Germany
| | - Richard A Flavell
- Department of Immunobiology, Yale University School of Medicine, New Haven, CT 06519, USA
- Howard Hughes Medical Institute, Yale University School of Medicine, New Haven, CT 06519, USA
| | - Kathy D McCoy
- Department of Physiology and Pharmacology, University of Calgary, Calgary, Alberta, Canada
| | - Andrew J Macpherson
- Maurice Müller Laboratories (DBMR), Universitätsklinik für Viszerale Chirurgie und Medizin Inselspital, Murtenstrasse 35, University of Bern, 3010 Bern, Switzerland
| | - Arthur Kaser
- Division of Gastroenterology and Hepatology, Department of Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Richard S Blumberg
- Division of Gastroenterology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA 02115, USA.
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23
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24
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Davydov AN, Obraztsova AS, Lebedin MY, Turchaninova MA, Staroverov DB, Merzlyak EM, Sharonov GV, Kladova O, Shugay M, Britanova OV, Chudakov DM. Comparative Analysis of B-Cell Receptor Repertoires Induced by Live Yellow Fever Vaccine in Young and Middle-Age Donors. Front Immunol 2018; 9:2309. [PMID: 30356675 PMCID: PMC6189279 DOI: 10.3389/fimmu.2018.02309] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2018] [Accepted: 09/17/2018] [Indexed: 12/25/2022] Open
Abstract
Age-related changes can significantly alter the state of adaptive immune system and often lead to attenuated response to novel pathogens and vaccination. In present study we employed 5′RACE UMI-based full length and nearly error-free immunoglobulin profiling to compare plasma cell antibody repertoires in young (19–26 years) and middle-age (45–58 years) individuals vaccinated with a live yellow fever vaccine, modeling a newly encountered pathogen. Our analysis has revealed age-related differences in the responding antibody repertoire ranging from distinct IGH CDR3 repertoire properties to differences in somatic hypermutation intensity and efficiency and antibody lineage tree structure. Overall, our findings suggest that younger individuals respond with a more diverse antibody repertoire and employ a more efficient somatic hypermutation process than elder individuals in response to a newly encountered pathogen.
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Affiliation(s)
- Alexey N Davydov
- Adaptive Immunity Group, Central European Institute of Technology, Brno, Czechia
| | - Anna S Obraztsova
- Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University, Moscow, Russia.,Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, Russia
| | - Mikhail Y Lebedin
- Genomics of Adaptive Immunity Department, Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
| | - Maria A Turchaninova
- Genomics of Adaptive Immunity Department, Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia.,Department of Molecular Technologies, Pirogov Russian National Research Medical University, Moscow, Russia.,Laboratory of Genomics of Antitumor Adaptive Immunity, Privolzhsky Research Medical University, Nizhny Novgorod, Russia
| | - Dmitriy B Staroverov
- Genomics of Adaptive Immunity Department, Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia.,Department of Molecular Technologies, Pirogov Russian National Research Medical University, Moscow, Russia
| | - Ekaterina M Merzlyak
- Genomics of Adaptive Immunity Department, Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia.,Department of Molecular Technologies, Pirogov Russian National Research Medical University, Moscow, Russia
| | - George V Sharonov
- Genomics of Adaptive Immunity Department, Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia.,Laboratory of Genomics of Antitumor Adaptive Immunity, Privolzhsky Research Medical University, Nizhny Novgorod, Russia
| | - Olga Kladova
- Department of Molecular Technologies, Pirogov Russian National Research Medical University, Moscow, Russia
| | - Mikhail Shugay
- Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, Russia.,Genomics of Adaptive Immunity Department, Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia.,Department of Molecular Technologies, Pirogov Russian National Research Medical University, Moscow, Russia.,Laboratory of Genomics of Antitumor Adaptive Immunity, Privolzhsky Research Medical University, Nizhny Novgorod, Russia
| | - Olga V Britanova
- Genomics of Adaptive Immunity Department, Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia.,Department of Molecular Technologies, Pirogov Russian National Research Medical University, Moscow, Russia.,Laboratory of Genomics of Antitumor Adaptive Immunity, Privolzhsky Research Medical University, Nizhny Novgorod, Russia
| | - Dmitriy M Chudakov
- Adaptive Immunity Group, Central European Institute of Technology, Brno, Czechia.,Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, Russia.,Genomics of Adaptive Immunity Department, Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia.,Department of Molecular Technologies, Pirogov Russian National Research Medical University, Moscow, Russia.,Laboratory of Genomics of Antitumor Adaptive Immunity, Privolzhsky Research Medical University, Nizhny Novgorod, Russia
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25
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Kovaltsuk A, Leem J, Kelm S, Snowden J, Deane CM, Krawczyk K. Observed Antibody Space: A Resource for Data Mining Next-Generation Sequencing of Antibody Repertoires. THE JOURNAL OF IMMUNOLOGY 2018; 201:2502-2509. [PMID: 30217829 DOI: 10.4049/jimmunol.1800708] [Citation(s) in RCA: 139] [Impact Index Per Article: 19.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/22/2018] [Accepted: 08/19/2018] [Indexed: 11/19/2022]
Abstract
Abs are immune system proteins that recognize noxious molecules for elimination. Their sequence diversity and binding versatility have made Abs the primary class of biopharmaceuticals. Recently, it has become possible to query their immense natural diversity using next-generation sequencing of Ig gene repertoires (Ig-seq). However, Ig-seq outputs are currently fragmented across repositories and tend to be presented as raw nucleotide reads, which means nontrivial effort is required to reuse the data for analysis. To address this issue, we have collected Ig-seq outputs from 55 studies, covering more than half a billion Ab sequences across diverse immune states, organisms (primarily human and mouse), and individuals. We have sorted, cleaned, annotated, translated, and numbered these sequences and make the data available via our Observed Antibody Space (OAS) resource at http://antibodymap.org The data within OAS will be regularly updated with newly released Ig-seq datasets. We believe OAS will facilitate data mining of immune repertoires for improved understanding of the immune system and development of better biotherapeutics.
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Affiliation(s)
- Aleksandr Kovaltsuk
- Department of Statistics, University of Oxford, Oxford OX1 3LB, United Kingdom; and
| | - Jinwoo Leem
- Department of Statistics, University of Oxford, Oxford OX1 3LB, United Kingdom; and
| | | | | | - Charlotte M Deane
- Department of Statistics, University of Oxford, Oxford OX1 3LB, United Kingdom; and
| | - Konrad Krawczyk
- Department of Statistics, University of Oxford, Oxford OX1 3LB, United Kingdom; and
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26
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Yermanos A, Greiff V, Krautler NJ, Menzel U, Dounas A, Miho E, Oxenius A, Stadler T, Reddy ST. Comparison of methods for phylogenetic B-cell lineage inference using time-resolved antibody repertoire simulations (AbSim). Bioinformatics 2018; 33:3938-3946. [PMID: 28968873 DOI: 10.1093/bioinformatics/btx533] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2016] [Accepted: 08/30/2017] [Indexed: 01/13/2023] Open
Abstract
Motivation The evolution of antibody repertoires represents a hallmark feature of adaptive B-cell immunity. Recent advancements in high-throughput sequencing have dramatically increased the resolution to which we can measure the molecular diversity of antibody repertoires, thereby offering for the first time the possibility to capture the antigen-driven evolution of B cells. However, there does not exist a repertoire simulation framework yet that enables the comparison of commonly utilized phylogenetic methods with regard to their accuracy in inferring antibody evolution. Results Here, we developed AbSim, a time-resolved antibody repertoire simulation framework, which we exploited for testing the accuracy of methods for the phylogenetic reconstruction of B-cell lineages and antibody molecular evolution. AbSim enables the (i) simulation of intermediate stages of antibody sequence evolution and (ii) the modeling of immunologically relevant parameters such as duration of repertoire evolution, and the method and frequency of mutations. First, we validated that our repertoire simulation framework recreates replicates topological similarities observed in experimental sequencing data. Second, we leveraged Absim to show that current methods fail to a certain extent to predict the true phylogenetic tree correctly. Finally, we formulated simulation-validated guidelines for antibody evolution, which in the future will enable the development of accurate phylogenetic methods. Availability and implementation https://cran.r-project.org/web/packages/AbSim/index.html. Contact sai.reddy@ethz.ch. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Alexander Yermanos
- Department of Biosystems Science and Engineering, ETH Zürich, 4058 Basel, Switzerland
| | - Victor Greiff
- Department of Biosystems Science and Engineering, ETH Zürich, 4058 Basel, Switzerland
| | | | - Ulrike Menzel
- Department of Biosystems Science and Engineering, ETH Zürich, 4058 Basel, Switzerland
| | - Andreas Dounas
- Department of Chemistry and Applied Biosciences, ETH Zürich, 8093 Zürich, Switzerland
| | - Enkelejda Miho
- Department of Biosystems Science and Engineering, ETH Zürich, 4058 Basel, Switzerland
| | | | - Tanja Stadler
- Department of Biosystems Science and Engineering, ETH Zürich, 4058 Basel, Switzerland
| | - Sai T Reddy
- Department of Biosystems Science and Engineering, ETH Zürich, 4058 Basel, Switzerland
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27
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Avram O, Vaisman-Mentesh A, Yehezkel D, Ashkenazy H, Pupko T, Wine Y. ASAP - A Webserver for Immunoglobulin-Sequencing Analysis Pipeline. Front Immunol 2018; 9:1686. [PMID: 30105017 PMCID: PMC6077260 DOI: 10.3389/fimmu.2018.01686] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2018] [Accepted: 07/09/2018] [Indexed: 12/16/2022] Open
Abstract
Reproducible and robust data on antibody repertoires are invaluable for basic and applied immunology. Next-generation sequencing (NGS) of antibody variable regions has emerged as a powerful tool in systems immunology, providing quantitative molecular information on antibody polyclonal composition. However, major computational challenges exist when analyzing antibody sequences, from error handling to hypermutation profiles and clonal expansion analyses. In this work, we developed the ASAP (A webserver for Immunoglobulin-Seq Analysis Pipeline) webserver (https://asap.tau.ac.il). The input to ASAP is a paired-end sequence dataset from one or more replicates, with or without unique molecular identifiers. These datasets can be derived from NGS of human or murine antibody variable regions. ASAP first filters and annotates the sequence reads using public or user-provided germline sequence information. The ASAP webserver next performs various calculations, including somatic hypermutation level, CDR3 lengths, V(D)J family assignments, and V(D)J combination distribution. These analyses are repeated for each replicate. ASAP provides additional information by analyzing the commonalities and differences between the repeats (“joint” analysis). For example, ASAP examines the shared variable regions and their frequency in each replicate to determine which sequences are less likely to be a result of a sample preparation derived and/or sequencing errors. Moreover, ASAP clusters the data to clones and reports the identity and prevalence of top ranking clones (clonal expansion analysis). ASAP further provides the distribution of synonymous and non-synonymous mutations within the V genes somatic hypermutations. Finally, ASAP provides means to process the data for proteomic analysis of serum/secreted antibodies by generating a variable region database for liquid chromatography high resolution tandem mass spectrometry (LC-MS/MS) interpretation. ASAP is user-friendly, free, and open to all users, with no login requirement. ASAP is applicable for researchers interested in basic questions related to B cell development and differentiation, as well as applied researchers who are interested in vaccine development and monoclonal antibody engineering. By virtue of its user-friendliness, ASAP opens the antibody analysis field to non-expert users who seek to boost their research with immune repertoire analysis.
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Affiliation(s)
- Oren Avram
- George S. Wise Faculty of Life Sciences, School of Molecular Cell Biology and Biotechnology, Tel Aviv University, Ramat Aviv, Israel
| | - Anna Vaisman-Mentesh
- George S. Wise Faculty of Life Sciences, School of Molecular Cell Biology and Biotechnology, Tel Aviv University, Ramat Aviv, Israel
| | - Dror Yehezkel
- George S. Wise Faculty of Life Sciences, School of Molecular Cell Biology and Biotechnology, Tel Aviv University, Ramat Aviv, Israel
| | - Haim Ashkenazy
- George S. Wise Faculty of Life Sciences, School of Molecular Cell Biology and Biotechnology, Tel Aviv University, Ramat Aviv, Israel
| | - Tal Pupko
- George S. Wise Faculty of Life Sciences, School of Molecular Cell Biology and Biotechnology, Tel Aviv University, Ramat Aviv, Israel
| | - Yariv Wine
- George S. Wise Faculty of Life Sciences, School of Molecular Cell Biology and Biotechnology, Tel Aviv University, Ramat Aviv, Israel
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28
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Friedensohn S, Lindner JM, Cornacchione V, Iazeolla M, Miho E, Zingg A, Meng S, Traggiai E, Reddy ST. Synthetic Standards Combined With Error and Bias Correction Improve the Accuracy and Quantitative Resolution of Antibody Repertoire Sequencing in Human Naïve and Memory B Cells. Front Immunol 2018; 9:1401. [PMID: 29973938 PMCID: PMC6019461 DOI: 10.3389/fimmu.2018.01401] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2018] [Accepted: 06/06/2018] [Indexed: 11/13/2022] Open
Abstract
High-throughput sequencing of immunoglobulin (Ig) repertoires (Ig-seq) is a powerful method for quantitatively interrogating B cell receptor sequence diversity. When applied to human repertoires, Ig-seq provides insight into fundamental immunological questions, and can be implemented in diagnostic and drug discovery projects. However, a major challenge in Ig-seq is ensuring accuracy, as library preparation protocols and sequencing platforms can introduce substantial errors and bias that compromise immunological interpretation. Here, we have established an approach for performing highly accurate human Ig-seq by combining synthetic standards with a comprehensive error and bias correction pipeline. First, we designed a set of 85 synthetic antibody heavy-chain standards (in vitro transcribed RNA) to assess correction workflow fidelity. Next, we adapted a library preparation protocol that incorporates unique molecular identifiers (UIDs) for error and bias correction which, when applied to the synthetic standards, resulted in highly accurate data. Finally, we performed Ig-seq on purified human circulating B cell subsets (naïve and memory), combined with a cellular replicate sampling strategy. This strategy enabled robust and reliable estimation of key repertoire features such as clonotype diversity, germline segment, and isotype subclass usage, and somatic hypermutation. We anticipate that our standards and error and bias correction pipeline will become a valuable tool for researchers to validate and improve accuracy in human Ig-seq studies, thus leading to potentially new insights and applications in human antibody repertoire profiling.
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Affiliation(s)
- Simon Friedensohn
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - John M Lindner
- Novartis Institutes for BioMedical Research, Basel, Switzerland
| | | | | | - Enkelejda Miho
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Andreas Zingg
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Simon Meng
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | | | - Sai T Reddy
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
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Chen Y, Chaudhary N, Yang N, Granato A, Turner JA, Howard SL, Devereaux C, Zuo T, Shrestha A, Goel RR, Neuberg D, Wesemann DR. Microbial symbionts regulate the primary Ig repertoire. J Exp Med 2018; 215:1397-1415. [PMID: 29588346 PMCID: PMC5940265 DOI: 10.1084/jem.20171761] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2017] [Revised: 01/23/2018] [Accepted: 03/09/2018] [Indexed: 01/26/2023] Open
Abstract
Symbiotic relationships help shape immune fitness. Chen et al. demonstrate that microbial symbionts influence host immunity by enriching frequencies of antibacterial specificities within the naive B cell receptor repertoire and that this may have consequences for mucosal and systemic immunity. The ability of immunoglobulin (Ig) to recognize pathogens is critical for optimal immune fitness. Early events that shape preimmune Ig repertoires, expressed on IgM+ IgD+ B cells as B cell receptors (BCRs), are poorly defined. Here, we studied germ-free mice and conventionalized littermates to explore the hypothesis that symbiotic microbes help shape the preimmune Ig repertoire. Ig-binding assays showed that exposure to conventional microbial symbionts enriched frequencies of antibacterial IgM+ IgD+ B cells in intestine and spleen. This enrichment affected follicular B cells, involving a diverse set of Ig-variable region gene segments, and was T cell–independent. Functionally, enrichment of microbe reactivity primed basal levels of small intestinal T cell–independent, symbiont-reactive IgA and enhanced systemic IgG responses to bacterial immunization. These results demonstrate that microbial symbionts influence host immunity by enriching frequencies of antibacterial specificities within preimmune B cell repertoires and that this may have consequences for mucosal and systemic immunity.
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Affiliation(s)
- Yuezhou Chen
- Department of Medicine, Division of Rheumatology, Immunology, and Allergy, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Neha Chaudhary
- Department of Medicine, Division of Rheumatology, Immunology, and Allergy, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Nicole Yang
- Department of Medicine, Division of Rheumatology, Immunology, and Allergy, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Alessandra Granato
- Department of Medicine, Division of Rheumatology, Immunology, and Allergy, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Jacob A Turner
- Department of Medicine, Division of Rheumatology, Immunology, and Allergy, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Shannon L Howard
- Department of Medicine, Division of Rheumatology, Immunology, and Allergy, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Colby Devereaux
- Department of Medicine, Division of Rheumatology, Immunology, and Allergy, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Teng Zuo
- Department of Medicine, Division of Rheumatology, Immunology, and Allergy, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Akritee Shrestha
- Department of Medicine, Division of Rheumatology, Immunology, and Allergy, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Rishi R Goel
- Department of Medicine, Division of Rheumatology, Immunology, and Allergy, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Donna Neuberg
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA
| | - Duane R Wesemann
- Department of Medicine, Division of Rheumatology, Immunology, and Allergy, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
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D'Angelo S, Ferrara F, Naranjo L, Erasmus MF, Hraber P, Bradbury ARM. Many Routes to an Antibody Heavy-Chain CDR3: Necessary, Yet Insufficient, for Specific Binding. Front Immunol 2018; 9:395. [PMID: 29568296 PMCID: PMC5852061 DOI: 10.3389/fimmu.2018.00395] [Citation(s) in RCA: 60] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2017] [Accepted: 02/13/2018] [Indexed: 12/11/2022] Open
Abstract
Because of its great potential for diversity, the immunoglobulin heavy-chain complementarity-determining region 3 (HCDR3) is taken as an antibody molecule’s most important component in conferring binding activity and specificity. For this reason, HCDR3s have been used as unique identifiers to investigate adaptive immune responses in vivo and to characterize in vitro selection outputs where display systems were employed. Here, we show that many different HCDR3s can be identified within a target-specific antibody population after in vitro selection. For each identified HCDR3, a number of different antibodies bearing differences elsewhere can be found. In such selected populations, all antibodies with the same HCDR3 recognize the target, albeit at different affinities. In contrast, within unselected populations, the majority of antibodies with the same HCDR3 sequence do not bind the target. In one HCDR3 examined in depth, all target-specific antibodies were derived from the same VDJ rearrangement, while non-binding antibodies with the same HCDR3 were derived from many different V and D gene rearrangements. Careful examination of previously published in vivo datasets reveals that HCDR3s shared between, and within, different individuals can also originate from rearrangements of different V and D genes, with up to 26 different rearrangements yielding the same identical HCDR3 sequence. On the basis of these observations, we conclude that the same HCDR3 can be generated by many different rearrangements, but that specific target binding is an outcome of unique rearrangements and VL pairing: the HCDR3 is necessary, albeit insufficient, for specific antibody binding.
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Affiliation(s)
| | | | | | | | - Peter Hraber
- Los Alamos National Laboratory, Los Alamos, NM, United States
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31
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Characterization of the naive murine antibody repertoire using unamplified high-throughput sequencing. PLoS One 2018; 13:e0190982. [PMID: 29320559 PMCID: PMC5761896 DOI: 10.1371/journal.pone.0190982] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2017] [Accepted: 12/22/2017] [Indexed: 12/22/2022] Open
Abstract
Antibody specificity and diversity are generated through the enzymatic splicing of genomic gene segments within each B cell. Antibodies are heterodimers of heavy- and light-chains encoded on separate loci. We studied the antibody repertoire from pooled, splenic tissue of unimmunized, adult female C57BL/6J mice, using high-throughput sequencing (HTS) without amplification of antibody transcripts. We recovered over 90,000 heavy-chain and over 135,000 light-chain immunoglobulin sequences. Individual V-, D-, and J-gene segment usage was uniform among the three mouse pools, particularly in highly abundant gene segments, with low frequency V-gene segments not being detected in all pools. Despite the similar usage of individual gene segments, the repertoire of individual B-cell CDR3 amino acid sequences in each mouse pool was highly varied, affirming the combinatorial diversity in the B-cell pool that has been previously demonstrated. There also was some skewing in the V-gene segments that were detected depending on chromosomal location. This study presents a unique, non-primer biased glimpse of the conventionally housed, unimmunized antibody repertoire of the C57BL6/J mouse.
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32
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Christley S, Levin MK, Toby IT, Fonner JM, Monson NL, Rounds WH, Rubelt F, Scarborough W, Scheuermann RH, Cowell LG. VDJPipe: a pipelined tool for pre-processing immune repertoire sequencing data. BMC Bioinformatics 2017; 18:448. [PMID: 29020925 PMCID: PMC5637252 DOI: 10.1186/s12859-017-1853-z] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2017] [Accepted: 10/02/2017] [Indexed: 12/20/2022] Open
Abstract
Background Pre-processing of high-throughput sequencing data for immune repertoire profiling is essential to insure high quality input for downstream analysis. VDJPipe is a flexible, high-performance tool that can perform multiple pre-processing tasks with just a single pass over the data files. Results Processing tasks provided by VDJPipe include base composition statistics calculation, read quality statistics calculation, quality filtering, homopolymer filtering, length and nucleotide filtering, paired-read merging, barcode demultiplexing, 5′ and 3′ PCR primer matching, and duplicate reads collapsing. VDJPipe utilizes a pipeline approach whereby multiple processing steps are performed in a sequential workflow, with the output of each step passed as input to the next step automatically. The workflow is flexible enough to handle the complex barcoding schemes used in many immunosequencing experiments. Because VDJPipe is designed for computational efficiency, we evaluated this by comparing execution times with those of pRESTO, a widely-used pre-processing tool for immune repertoire sequencing data. We found that VDJPipe requires <10% of the run time required by pRESTO. Conclusions VDJPipe is a high-performance tool that is optimized for pre-processing large immune repertoire sequencing data sets.
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Affiliation(s)
- Scott Christley
- Department of Clinical Sciences, UT Southwestern Medical Center, Dallas, TX, 75390, USA
| | | | - Inimary T Toby
- Department of Clinical Sciences, UT Southwestern Medical Center, Dallas, TX, 75390, USA
| | - John M Fonner
- Texas Advanced Computing Center, Austin, TX, 78758-4497, USA
| | - Nancy L Monson
- Department of Neurology and Neurotherapeutics, UT Southwestern Medical Center, Dallas, TX, 75390, USA.,Department of Immunology, UT Southwestern Medical Center, Dallas, TX, 75390, USA
| | - William H Rounds
- Department of Clinical Sciences, UT Southwestern Medical Center, Dallas, TX, 75390, USA
| | - Florian Rubelt
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | | | - Richard H Scheuermann
- J. Craig Venter Institute, La Jolla, CA, 92037, USA.,Department of Pathology, University of California, San Diego, CA, 92093, USA.,La Jolla Institute for Allergy & Immunology, La Jolla, CA, 92037, USA
| | - Lindsay G Cowell
- Department of Clinical Sciences, UT Southwestern Medical Center, Dallas, TX, 75390, USA.
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Greiff V, Weber CR, Palme J, Bodenhofer U, Miho E, Menzel U, Reddy ST. Learning the High-Dimensional Immunogenomic Features That Predict Public and Private Antibody Repertoires. THE JOURNAL OF IMMUNOLOGY 2017; 199:2985-2997. [DOI: 10.4049/jimmunol.1700594] [Citation(s) in RCA: 85] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/25/2017] [Accepted: 08/16/2017] [Indexed: 11/19/2022]
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34
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Khavrutskii IV, Chaudhury S, Stronsky SM, Lee DW, Benko JG, Wallqvist A, Bavari S, Cooper CL. Quantitative Analysis of Repertoire-Scale Immunoglobulin Properties in Vaccine-Induced B-Cell Responses. Front Immunol 2017; 8:910. [PMID: 28855898 PMCID: PMC5557726 DOI: 10.3389/fimmu.2017.00910] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2017] [Accepted: 07/17/2017] [Indexed: 12/15/2022] Open
Abstract
Recent advances in the next-generation sequencing of B-cell receptors (BCRs) enable the characterization of humoral responses at a repertoire-wide scale and provide the capability for identifying unique features of immune repertoires in response to disease, vaccination, or infection. Immunosequencing now readily generates 103–105 sequences per sample; however, statistical analysis of these repertoires is challenging because of the high genetic diversity of BCRs and the elaborate clonal relationships among them. To date, most immunosequencing analyses have focused on reporting qualitative trends in immunoglobulin (Ig) properties, such as usage or somatic hypermutation (SHM) percentage of the Ig heavy chain variable (IGHV) gene segment family, and on reducing complex Ig property distributions to simple summary statistics. However, because Ig properties are typically not normally distributed, any approach that fails to assess the distribution as a whole may be inadequate in (1) properly assessing the statistical significance of repertoire differences, (2) identifying how two repertoires differ, and (3) determining appropriate confidence intervals for assessing the size of the differences and their potential biological relevance. To address these issues, we have developed a technique that uses Wilcox’ robust statistics toolbox to identify statistically significant vaccine-specific differences between Ig repertoire properties. The advantage of this technique is that it can determine not only whether but also where the distributions differ, even when the Ig repertoire properties are non-normally distributed. We used this technique to characterize murine germinal center (GC) B-cell repertoires in response to a complex Ebola virus-like particle (eVLP) vaccine candidate with known protective efficacy. The eVLP-mediated GC B-cell responses were highly diverse, consisting of thousands of clonotypes. Despite this staggering diversity, we identified statistically significant differences between non-immunized, vaccine only, and vaccine-plus-adjuvant groups in terms of Ig properties, including IGHV-family usage, SHM percentage, and characteristics of the BCR complementarity-determining region. Most notably, our analyses identified a robust eVLP-specific feature—enhanced IGHV8-family usage in B-cell repertoires. These findings demonstrate the utility of our technique in identifying statistically significant BCR repertoire differences following vaccination. More generally, our approach is potentially applicable to a wide range of studies in infection, vaccination, auto-immunity, and cancer.
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Affiliation(s)
- Ilja V Khavrutskii
- Department of Defense Biotechnology High Performance Computing Software Applications Institute (BHSAI), Telemedicine and Advanced Technology Research Center, United States Army Medical Research and Materiel Command, Fort Detrick, MD, United States
| | - Sidhartha Chaudhury
- Department of Defense Biotechnology High Performance Computing Software Applications Institute (BHSAI), Telemedicine and Advanced Technology Research Center, United States Army Medical Research and Materiel Command, Fort Detrick, MD, United States
| | - Sabrina M Stronsky
- Molecular and Translational Sciences, United States Army Medical Research Institute of Infectious Diseases (USAMRIID), Fort Detrick, MD, United States
| | - Donald W Lee
- Department of Defense Biotechnology High Performance Computing Software Applications Institute (BHSAI), Telemedicine and Advanced Technology Research Center, United States Army Medical Research and Materiel Command, Fort Detrick, MD, United States
| | - Jacqueline G Benko
- Molecular and Translational Sciences, United States Army Medical Research Institute of Infectious Diseases (USAMRIID), Fort Detrick, MD, United States
| | - Anders Wallqvist
- Department of Defense Biotechnology High Performance Computing Software Applications Institute (BHSAI), Telemedicine and Advanced Technology Research Center, United States Army Medical Research and Materiel Command, Fort Detrick, MD, United States
| | - Sina Bavari
- Molecular and Translational Sciences, United States Army Medical Research Institute of Infectious Diseases (USAMRIID), Fort Detrick, MD, United States
| | - Christopher L Cooper
- Molecular and Translational Sciences, United States Army Medical Research Institute of Infectious Diseases (USAMRIID), Fort Detrick, MD, United States
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35
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Rettig TA, Ward C, Pecaut MJ, Chapes SK. Validation of Methods to Assess the Immunoglobulin Gene Repertoire in Tissues Obtained from Mice on the International Space Station. GRAVITATIONAL AND SPACE RESEARCH : PUBLICATION OF THE AMERICAN SOCIETY FOR GRAVITATIONAL AND SPACE RESEARCH 2017; 5:2-23. [PMID: 29270444 PMCID: PMC5736159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Spaceflight is known to affect immune cell populations. In particular, splenic B cell numbers decrease during spaceflight and in ground-based physiological models. Although antibody isotype changes have been assessed during and after space flight, an extensive characterization of the impact of spaceflight on antibody composition has not been conducted in mice. Next Generation Sequencing and bioinformatic tools are now available to assess antibody repertoires. We can now identify immunoglobulin gene- segment usage, junctional regions, and modifications that contribute to specificity and diversity. Due to limitations on the International Space Station, alternate sample collection and storage methods must be employed. Our group compared Illumina MiSeq sequencing data from multiple sample preparation methods in normal C57Bl/6J mice to validate that sample preparation and storage would not bias the outcome of antibody repertoire characterization. In this report, we also compared sequencing techniques and a bioinformatic workflow on the data output when we assessed the IgH and Igκ variable gene usage. This included assessments of our bioinformatic workflow on Illumina HiSeq and MiSeq datasets and is specifically designed to reduce bias, capture the most information from Ig sequences, and produce a data set that provides other data mining options. We validated our workflow by comparing our normal mouse MiSeq data to existing murine antibody repertoire studies validating it for future antibody repertoire studies.
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Affiliation(s)
| | - Claire Ward
- Division of Biology, Kansas State University, Manhattan, KS
| | - Michael J Pecaut
- Division of Radiation Research, Loma Linda University, Loma Linda University, CA
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36
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Fantini M, Pandolfini L, Lisi S, Chirichella M, Arisi I, Terrigno M, Goracci M, Cremisi F, Cattaneo A. Assessment of antibody library diversity through next generation sequencing and technical error compensation. PLoS One 2017; 12:e0177574. [PMID: 28505201 PMCID: PMC5432181 DOI: 10.1371/journal.pone.0177574] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2016] [Accepted: 04/28/2017] [Indexed: 12/30/2022] Open
Abstract
Antibody libraries are important resources to derive antibodies to be used for a wide range of applications, from structural and functional studies to intracellular protein interference studies to developing new diagnostics and therapeutics. Whatever the goal, the key parameter for an antibody library is its complexity (also known as diversity), i.e. the number of distinct elements in the collection, which directly reflects the probability of finding in the library an antibody against a given antigen, of sufficiently high affinity. Quantitative evaluation of antibody library complexity and quality has been for a long time inadequately addressed, due to the high similarity and length of the sequences of the library. Complexity was usually inferred by the transformation efficiency and tested either by fingerprinting and/or sequencing of a few hundred random library elements. Inferring complexity from such a small sampling is, however, very rudimental and gives limited information about the real diversity, because complexity does not scale linearly with sample size. Next-generation sequencing (NGS) has opened new ways to tackle the antibody library complexity quality assessment. However, much remains to be done to fully exploit the potential of NGS for the quantitative analysis of antibody repertoires and to overcome current limitations. To obtain a more reliable antibody library complexity estimate here we show a new, PCR-free, NGS approach to sequence antibody libraries on Illumina platform, coupled to a new bioinformatic analysis and software (Diversity Estimator of Antibody Library, DEAL) that allows to reliably estimate the complexity, taking in consideration the sequencing error.
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Affiliation(s)
- Marco Fantini
- Bio@SNS Laboratory, Scuola Normale Superiore, Pisa, Italy
| | | | - Simonetta Lisi
- Bio@SNS Laboratory, Scuola Normale Superiore, Pisa, Italy
| | | | - Ivan Arisi
- European Brain Research Institute, Roma, Italy
| | - Marco Terrigno
- Bio@SNS Laboratory, Scuola Normale Superiore, Pisa, Italy
| | | | | | - Antonino Cattaneo
- Bio@SNS Laboratory, Scuola Normale Superiore, Pisa, Italy
- European Brain Research Institute, Roma, Italy
- * E-mail:
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37
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Schellenberg JJ, Oh AY, Hill JE. Microbial profiling of cpn60 universal target sequences in artificial mixtures of vaginal bacteria sampled by nylon swabs or self-sampling devices under different storage conditions. J Microbiol Methods 2017; 136:57-64. [DOI: 10.1016/j.mimet.2017.03.003] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2016] [Revised: 03/05/2017] [Accepted: 03/06/2017] [Indexed: 01/08/2023]
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Systems Analysis Reveals High Genetic and Antigen-Driven Predetermination of Antibody Repertoires throughout B Cell Development. Cell Rep 2017; 19:1467-1478. [DOI: 10.1016/j.celrep.2017.04.054] [Citation(s) in RCA: 119] [Impact Index Per Article: 14.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2016] [Revised: 03/21/2017] [Accepted: 04/19/2017] [Indexed: 12/29/2022] Open
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39
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Langerak AW, Brüggemann M, Davi F, Darzentas N, van Dongen JJM, Gonzalez D, Cazzaniga G, Giudicelli V, Lefranc MP, Giraud M, Macintyre EA, Hummel M, Pott C, Groenen PJTA, Stamatopoulos K. High-Throughput Immunogenetics for Clinical and Research Applications in Immunohematology: Potential and Challenges. THE JOURNAL OF IMMUNOLOGY 2017; 198:3765-3774. [PMID: 28416603 DOI: 10.4049/jimmunol.1602050] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2016] [Accepted: 01/09/2017] [Indexed: 11/19/2022]
Abstract
Analysis and interpretation of Ig and TCR gene rearrangements in the conventional, low-throughput way have their limitations in terms of resolution, coverage, and biases. With the advent of high-throughput, next-generation sequencing (NGS) technologies, a deeper analysis of Ig and/or TCR (IG/TR) gene rearrangements is now within reach, which impacts on all main applications of IG/TR immunogenetic analysis. To bridge the generation gap from low- to high-throughput analysis, the EuroClonality-NGS Consortium has been formed, with the main objectives to develop, standardize, and validate the entire workflow of IG/TR NGS assays for 1) clonality assessment, 2) minimal residual disease detection, and 3) repertoire analysis. This concerns the preanalytical (sample preparation, target choice), analytical (amplification, NGS), and postanalytical (immunoinformatics) phases. Here we critically discuss pitfalls and challenges of IG/TR NGS methodology and its applications in hemato-oncology and immunology.
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Affiliation(s)
- Anton W Langerak
- Department of Immunology, Laboratory for Medical Immunology, Erasmus MC, University Medical Center, 3015 CN Rotterdam, the Netherlands;
| | - Monika Brüggemann
- Second Medical Department, University Hospital Schleswig-Holstein, 24105 Kiel, Germany
| | - Frédéric Davi
- Département d'Hématologie, Assistance Publique - Hôpitaux de Paris Hopital Pitié-Salpêtrière and Université Pierre et Marie Curie - Université Paris IV, 75005 Paris, France
| | - Nikos Darzentas
- Molecular Medicine Program, Central European Institute of Technology, Masaryk University, 625 00 Brno, Czech Republic
| | - Jacques J M van Dongen
- Department of Immunology, Laboratory for Medical Immunology, Erasmus MC, University Medical Center, 3015 CN Rotterdam, the Netherlands;
| | - David Gonzalez
- Centre for Cancer Research and Cell Biology, Queen's University Belfast, Belfast BT9 7AE, United Kingdom
| | - Gianni Cazzaniga
- Centro Ricerca Tettamanti, Clinica Pediatrica Università Milano-Bicocca, 20900 Monza, Italy
| | | | | | - Mathieu Giraud
- Centre de Recherche en Informatique Signal et Automatique de Lille, CNRS, Université de Lille, 59000 Lille, France
| | - Elizabeth A Macintyre
- Département d'Hématologie, Assistance Publique - Hôpitaux de Paris Necker-Enfants Malades and Paris Descartes, 75015 Paris, France
| | - Michael Hummel
- Institut für Pathologie, Charité - Universitätsmedizin Berlin, D-10117 Berlin, Germany
| | - Christiane Pott
- Second Medical Department, University Hospital Schleswig-Holstein, 24105 Kiel, Germany
| | - Patricia J T A Groenen
- Department of Pathology, Radboud University Nijmegen Medical Center, 6525 GA Nijmegen, the Netherlands; and
| | - Kostas Stamatopoulos
- Institute of Applied Biosciences, Center for Research and Technology Hellas, GR-57001 Thessaloniki, Greece
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40
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Broodman I, Lindemans J, van Sten J, Bischoff R, Luider T. Serum Protein Markers for the Early Detection of Lung Cancer: A Focus on Autoantibodies. J Proteome Res 2016; 16:3-13. [DOI: 10.1021/acs.jproteome.6b00559] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Affiliation(s)
| | | | | | - Rainer Bischoff
- Analytical
Biochemistry, Department of Pharmacy, University of Groningen, Antonius
Deusinglaan 1, 9713 AV Groningen, The Netherlands
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41
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Friedensohn S, Khan TA, Reddy ST. Advanced Methodologies in High-Throughput Sequencing of Immune Repertoires. Trends Biotechnol 2016; 35:203-214. [PMID: 28341036 DOI: 10.1016/j.tibtech.2016.09.010] [Citation(s) in RCA: 80] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2016] [Revised: 09/19/2016] [Accepted: 09/30/2016] [Indexed: 11/19/2022]
Abstract
In recent years, major efforts have been made to develop sophisticated experimental and bioinformatic workflows for sequencing adaptive immune repertoires. The immunological insight gained has been applied to fields as varied as lymphocyte biology, immunodiagnostics, vaccines, cancer immunotherapy, and antibody engineering. In this review, we provide a detailed overview of these advanced methodologies, focusing specifically on strategies to reduce sequencing errors and bias and to achieve high-throughput pairing of variable regions (e.g., heavy-light or alpha-beta chains). In addition, we highlight recent technologies for single-cell transcriptome sequencing that can be integrated with immune repertoires. Finally, we provide a perspective on advanced immune repertoire sequencing and its ability to impact basic immunology, biopharmaceutical drug discovery and development, and cancer immunotherapy.
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Affiliation(s)
- Simon Friedensohn
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Tarik A Khan
- Pharmaceutical Development & Supplies Biologics Europe, F. Hoffman-La Roche Ltd, Basel, Switzerland
| | - Sai T Reddy
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
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42
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Glanville J, D'Angelo S, Khan TA, Reddy ST, Naranjo L, Ferrara F, Bradbury ARM. Deep sequencing in library selection projects: what insight does it bring? Curr Opin Struct Biol 2016; 33:146-60. [PMID: 26451649 DOI: 10.1016/j.sbi.2015.09.001] [Citation(s) in RCA: 55] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2015] [Revised: 08/19/2015] [Accepted: 09/17/2015] [Indexed: 11/17/2022]
Abstract
High throughput sequencing is poised to change all aspects of the way antibodies and other binders are discovered and engineered. Millions of available sequence reads provide an unprecedented sampling depth able to guide the design and construction of effective, high quality naïve libraries containing tens of billions of unique molecules. Furthermore, during selections, high throughput sequencing enables quantitative tracing of enriched clones and position-specific guidance to amino acid variation under positive selection during antibody engineering. Successful application of the technologies relies on specific PCR reagent design, correct sequencing platform selection, and effective use of computational tools and statistical measures to remove error, identify antibodies, estimate diversity, and extract signatures of selection from the clone down to individual structural positions. Here we review these considerations and discuss some of the remaining challenges to the widespread adoption of the technology.
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Affiliation(s)
- J Glanville
- Program in Computational and Systems Immunology, Institute for Immunity, Transplantation and Infection, Stanford University School of Medicine, Stanford, CA, USA
| | - S D'Angelo
- University of New Mexico Comprehensive Cancer Center, and Division of Molecular Medicine, University of New Mexico School of Medicine, Albuquerque, NM, USA
| | - T A Khan
- ETH Zurich, Department of Biosystems Science and Engineering, Basel, Switzerland
| | - S T Reddy
- ETH Zurich, Department of Biosystems Science and Engineering, Basel, Switzerland
| | - L Naranjo
- Bioscience division, Los Alamos National Laboratory, Los Alamos, NM, USA
| | - F Ferrara
- University of New Mexico Comprehensive Cancer Center, and Division of Molecular Medicine, University of New Mexico School of Medicine, Albuquerque, NM, USA
| | - A R M Bradbury
- Bioscience division, Los Alamos National Laboratory, Los Alamos, NM, USA.
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43
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Turchaninova MA, Davydov A, Britanova OV, Shugay M, Bikos V, Egorov ES, Kirgizova VI, Merzlyak EM, Staroverov DB, Bolotin DA, Mamedov IZ, Izraelson M, Logacheva MD, Kladova O, Plevova K, Pospisilova S, Chudakov DM. High-quality full-length immunoglobulin profiling with unique molecular barcoding. Nat Protoc 2016; 11:1599-616. [DOI: 10.1038/nprot.2016.093] [Citation(s) in RCA: 134] [Impact Index Per Article: 14.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
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44
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Bashford-Rogers RJM, Nicolaou KA, Bartram J, Goulden NJ, Loizou L, Koumas L, Chi J, Hubank M, Kellam P, Costeas PA, Vassiliou GS. Eye on the B-ALL: B-cell receptor repertoires reveal persistence of numerous B-lymphoblastic leukemia subclones from diagnosis to relapse. Leukemia 2016; 30:2312-2321. [PMID: 27211266 PMCID: PMC5155029 DOI: 10.1038/leu.2016.142] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2015] [Revised: 05/02/2016] [Accepted: 05/12/2016] [Indexed: 02/08/2023]
Abstract
The strongest predictor of relapse in B-cell acute lymphoblastic leukemia (B-ALL) is the level of persistence of tumor cells after initial therapy. The high mutation rate of the B-cell receptor (BCR) locus allows high-resolution tracking of the architecture, evolution and clonal dynamics of B-ALL. Using longitudinal BCR repertoire sequencing, we find that the BCR undergoes an unexpectedly high level of clonal diversification in B-ALL cells through both somatic hypermutation and secondary rearrangements, which can be used for tracking the subclonal composition of the disease and detect minimal residual disease with unprecedented sensitivity. We go on to investigate clonal dynamics of B-ALL using BCR phylogenetic analyses of paired diagnosis-relapse samples and find that large numbers of small leukemic subclones present at diagnosis re-emerge at relapse alongside a dominant clone. Our findings suggest that in all informative relapsed patients, the survival of large numbers of clonogenic cells beyond initial chemotherapy is a surrogate for inherent partial chemoresistance or inadequate therapy, providing an increased opportunity for subsequent emergence of fully resistant clones. These results frame early cytoreduction as an important determinant of long-term outcome.
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Affiliation(s)
- R J M Bashford-Rogers
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK.,Department of Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
| | - K A Nicolaou
- The Center for the Study of Hematological Malignancies, Nicosia, Cyprus
| | - J Bartram
- Department of Haematology, Great Ormond Street Hospital for Children, London, UK.,Genetics and Genomic Medicine Programme, UCL Institute of Child Health, London, UK
| | - N J Goulden
- Department of Haematology, Great Ormond Street Hospital for Children, London, UK
| | - L Loizou
- Pediatric Oncology/Hematology Clinic, Nicosia, Cyprus
| | - L Koumas
- The Center for the Study of Hematological Malignancies, Nicosia, Cyprus
| | - J Chi
- The Center for the Study of Hematological Malignancies, Nicosia, Cyprus
| | - M Hubank
- Genetics and Genomic Medicine Programme, UCL Institute of Child Health, London, UK
| | - P Kellam
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK.,Division of Infection and Immunity, Research Department of Infection, University College London, London, UK
| | - P A Costeas
- The Center for the Study of Hematological Malignancies, Nicosia, Cyprus
| | - G S Vassiliou
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK.,The Center for the Study of Hematological Malignancies, Nicosia, Cyprus.,Cambridge Blood and Stem Cell Biobank and Cancer Molecular Diagnosis Laboratory, Cambridge Biomedical Research Centre, Cambridge, UK
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45
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Hershberg U, Luning Prak ET. The analysis of clonal expansions in normal and autoimmune B cell repertoires. Philos Trans R Soc Lond B Biol Sci 2016; 370:rstb.2014.0239. [PMID: 26194753 PMCID: PMC4528416 DOI: 10.1098/rstb.2014.0239] [Citation(s) in RCA: 89] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Clones are the fundamental building blocks of immune repertoires. The number of different clones relates to the diversity of the repertoire, whereas their size and sequence diversity are linked to selective pressures. Selective pressures act both between clones and within different sequence variants of a clone. Understanding how clonal selection shapes the immune repertoire is one of the most basic questions in all of immunology. But how are individual clones defined? Here we discuss different approaches for defining clones, starting with how antibodies are diversified during different stages of B cell development. Next, we discuss how clones are defined using different experimental methods. We focus on high-throughput sequencing datasets, and the computational challenges and opportunities that these data have for mining the antibody repertoire landscape. We discuss methods that visualize sequence variants within the same clone and allow us to consider collections of shared mutations to determine which sequences share a common ancestry. Finally, we comment on features of frequently encountered expanded B cell clones that may be of particular interest in the setting of autoimmunity and other chronic conditions.
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Affiliation(s)
- Uri Hershberg
- School of Biomedical Engineering, Science and Health Systems, Drexel University, Bossone 7-711, 3141 Chestnut Street, Philadelphia, PA 19104, USA Department of Immunology and Microbiology, College of Medicine, Drexel University, Bossone 7-711, 3141 Chestnut Street, Philadelphia, PA 19104, USA
| | - Eline T Luning Prak
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, 405B Stellar Chance Labs, 422 Curie Boulevard, Philadelphia, PA 19104, USA
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46
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Collins AM, Wang Y, Roskin KM, Marquis CP, Jackson KJL. The mouse antibody heavy chain repertoire is germline-focused and highly variable between inbred strains. Philos Trans R Soc Lond B Biol Sci 2016; 370:rstb.2014.0236. [PMID: 26194750 DOI: 10.1098/rstb.2014.0236] [Citation(s) in RCA: 69] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023] Open
Abstract
The human and mouse antibody repertoires are formed by identical processes, but like all small animals, mice only have sufficient lymphocytes to express a small part of the potential antibody repertoire. In this study, we determined how the heavy chain repertoires of two mouse strains are generated. Analysis of IgM- and IgG-associated VDJ rearrangements generated by high-throughput sequencing confirmed the presence of 99 functional immunoglobulin heavy chain variable (IGHV) genes in the C57BL/6 genome, and inferred the presence of 164 IGHV genes in the BALB/c genome. Remarkably, only five IGHV sequences were common to both strains. Compared with humans, little N nucleotide addition was seen in the junctions of mouse VDJ genes. Germline human IgG-associated IGHV genes are rare, but many murine IgG-associated IGHV genes were unmutated. Together these results suggest that the expressed mouse repertoire is more germline-focused than the human repertoire. The apparently divergent germline repertoires of the mouse strains are discussed with reference to reports that inbred mouse strains carry blocks of genes derived from each of the three subspecies of the house mouse. We hypothesize that the germline genes of BALB/c and C57BL/6 mice may originally have evolved to generate distinct germline-focused antibody repertoires in the different mouse subspecies.
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Affiliation(s)
- Andrew M Collins
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, 2052 NSW, Australia
| | - Yan Wang
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, 2052 NSW, Australia
| | - Krishna M Roskin
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA 94305-5324, USA
| | - Christopher P Marquis
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, 2052 NSW, Australia
| | - Katherine J L Jackson
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, 2052 NSW, Australia Department of Pathology, School of Medicine, Stanford University, Stanford, CA 94305-5324, USA
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47
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Safonova Y, Bonissone S, Kurpilyansky E, Starostina E, Lapidus A, Stinson J, DePalatis L, Sandoval W, Lill J, Pevzner PA. IgRepertoireConstructor: a novel algorithm for antibody repertoire construction and immunoproteogenomics analysis. Bioinformatics 2015; 31:i53-61. [PMID: 26072509 PMCID: PMC4542777 DOI: 10.1093/bioinformatics/btv238] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
UNLABELLED The analysis of concentrations of circulating antibodies in serum (antibody repertoire) is a fundamental, yet poorly studied, problem in immunoinformatics. The two current approaches to the analysis of antibody repertoires [next generation sequencing (NGS) and mass spectrometry (MS)] present difficult computational challenges since antibodies are not directly encoded in the germline but are extensively diversified by somatic recombination and hypermutations. Therefore, the protein database required for the interpretation of spectra from circulating antibodies is custom for each individual. Although such a database can be constructed via NGS, the reads generated by NGS are error-prone and even a single nucleotide error precludes identification of a peptide by the standard proteomics tools. Here, we present the IgRepertoireConstructor algorithm that performs error-correction of immunosequencing reads and uses mass spectra to validate the constructed antibody repertoires. AVAILABILITY AND IMPLEMENTATION IgRepertoireConstructor is open source and freely available as a C++ and Python program running on all Unix-compatible platforms. The source code is available from http://bioinf.spbau.ru/igtools. CONTACT ppevzner@ucsd.edu SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Yana Safonova
- Center for Algorithmic Biotechnology, St. Petersburg State University, St. Petersburg, Russia, Algorithmic Biology Laboratory, St. Petersburg Academic University, St. Petersburg, Russia, Bioinformatics Program, University of California, San Diego, CA, USA, Genentech, South San Francisco, CA, USA and Department of Computer Science and Engineering, University of California, San Diego, CA, USA Center for Algorithmic Biotechnology, St. Petersburg State University, St. Petersburg, Russia, Algorithmic Biology Laboratory, St. Petersburg Academic University, St. Petersburg, Russia, Bioinformatics Program, University of California, San Diego, CA, USA, Genentech, South San Francisco, CA, USA and Department of Computer Science and Engineering, University of California, San Diego, CA, USA
| | - Stefano Bonissone
- Center for Algorithmic Biotechnology, St. Petersburg State University, St. Petersburg, Russia, Algorithmic Biology Laboratory, St. Petersburg Academic University, St. Petersburg, Russia, Bioinformatics Program, University of California, San Diego, CA, USA, Genentech, South San Francisco, CA, USA and Department of Computer Science and Engineering, University of California, San Diego, CA, USA
| | - Eugene Kurpilyansky
- Center for Algorithmic Biotechnology, St. Petersburg State University, St. Petersburg, Russia, Algorithmic Biology Laboratory, St. Petersburg Academic University, St. Petersburg, Russia, Bioinformatics Program, University of California, San Diego, CA, USA, Genentech, South San Francisco, CA, USA and Department of Computer Science and Engineering, University of California, San Diego, CA, USA
| | - Ekaterina Starostina
- Center for Algorithmic Biotechnology, St. Petersburg State University, St. Petersburg, Russia, Algorithmic Biology Laboratory, St. Petersburg Academic University, St. Petersburg, Russia, Bioinformatics Program, University of California, San Diego, CA, USA, Genentech, South San Francisco, CA, USA and Department of Computer Science and Engineering, University of California, San Diego, CA, USA Center for Algorithmic Biotechnology, St. Petersburg State University, St. Petersburg, Russia, Algorithmic Biology Laboratory, St. Petersburg Academic University, St. Petersburg, Russia, Bioinformatics Program, University of California, San Diego, CA, USA, Genentech, South San Francisco, CA, USA and Department of Computer Science and Engineering, University of California, San Diego, CA, USA
| | - Alla Lapidus
- Center for Algorithmic Biotechnology, St. Petersburg State University, St. Petersburg, Russia, Algorithmic Biology Laboratory, St. Petersburg Academic University, St. Petersburg, Russia, Bioinformatics Program, University of California, San Diego, CA, USA, Genentech, South San Francisco, CA, USA and Department of Computer Science and Engineering, University of California, San Diego, CA, USA Center for Algorithmic Biotechnology, St. Petersburg State University, St. Petersburg, Russia, Algorithmic Biology Laboratory, St. Petersburg Academic University, St. Petersburg, Russia, Bioinformatics Program, University of California, San Diego, CA, USA, Genentech, South San Francisco, CA, USA and Department of Computer Science and Engineering, University of California, San Diego, CA, USA
| | - Jeremy Stinson
- Center for Algorithmic Biotechnology, St. Petersburg State University, St. Petersburg, Russia, Algorithmic Biology Laboratory, St. Petersburg Academic University, St. Petersburg, Russia, Bioinformatics Program, University of California, San Diego, CA, USA, Genentech, South San Francisco, CA, USA and Department of Computer Science and Engineering, University of California, San Diego, CA, USA
| | - Laura DePalatis
- Center for Algorithmic Biotechnology, St. Petersburg State University, St. Petersburg, Russia, Algorithmic Biology Laboratory, St. Petersburg Academic University, St. Petersburg, Russia, Bioinformatics Program, University of California, San Diego, CA, USA, Genentech, South San Francisco, CA, USA and Department of Computer Science and Engineering, University of California, San Diego, CA, USA
| | - Wendy Sandoval
- Center for Algorithmic Biotechnology, St. Petersburg State University, St. Petersburg, Russia, Algorithmic Biology Laboratory, St. Petersburg Academic University, St. Petersburg, Russia, Bioinformatics Program, University of California, San Diego, CA, USA, Genentech, South San Francisco, CA, USA and Department of Computer Science and Engineering, University of California, San Diego, CA, USA
| | - Jennie Lill
- Center for Algorithmic Biotechnology, St. Petersburg State University, St. Petersburg, Russia, Algorithmic Biology Laboratory, St. Petersburg Academic University, St. Petersburg, Russia, Bioinformatics Program, University of California, San Diego, CA, USA, Genentech, South San Francisco, CA, USA and Department of Computer Science and Engineering, University of California, San Diego, CA, USA
| | - Pavel A Pevzner
- Center for Algorithmic Biotechnology, St. Petersburg State University, St. Petersburg, Russia, Algorithmic Biology Laboratory, St. Petersburg Academic University, St. Petersburg, Russia, Bioinformatics Program, University of California, San Diego, CA, USA, Genentech, South San Francisco, CA, USA and Department of Computer Science and Engineering, University of California, San Diego, CA, USA Center for Algorithmic Biotechnology, St. Petersburg State University, St. Petersburg, Russia, Algorithmic Biology Laboratory, St. Petersburg Academic University, St. Petersburg, Russia, Bioinformatics Program, University of California, San Diego, CA, USA, Genentech, South San Francisco, CA, USA and Department of Computer Science and Engineering, University of California, San Diego, CA, USA Center for Algorithmic Biotechnology, St. Petersburg State University, St. Petersburg, Russia, Algorithmic Biology Laboratory, St. Petersburg Academic University, St. Petersburg, Russia, Bioinformatics Program, University of California, San Diego, CA, USA, Genentech, South San Francisco, CA, USA and Department of Computer Science and Engineering, University of California, San Diego, CA, USA
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48
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Bioinformatic and Statistical Analysis of Adaptive Immune Repertoires. Trends Immunol 2015; 36:738-749. [DOI: 10.1016/j.it.2015.09.006] [Citation(s) in RCA: 138] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2015] [Revised: 09/15/2015] [Accepted: 09/15/2015] [Indexed: 01/16/2023]
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49
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Galson JD, Trück J, Fowler A, Münz M, Cerundolo V, Pollard AJ, Lunter G, Kelly DF. In-Depth Assessment of Within-Individual and Inter-Individual Variation in the B Cell Receptor Repertoire. Front Immunol 2015; 6:531. [PMID: 26528292 PMCID: PMC4601265 DOI: 10.3389/fimmu.2015.00531] [Citation(s) in RCA: 62] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2015] [Accepted: 09/28/2015] [Indexed: 11/24/2022] Open
Abstract
High-throughput sequencing of the B cell receptor (BCR) repertoire can provide rapid characterization of the B cell response in a wide variety of applications in health, after vaccination and in infectious, inflammatory and immune-driven disease, and is starting to yield clinical applications. However, the interpretation of repertoire data is compromised by a lack of studies to assess the intra and inter-individual variation in the BCR repertoire over time in healthy individuals. We applied a standardized isotype-specific BCR repertoire deep sequencing protocol to a single highly sampled participant, and then evaluated the method in 9 further participants to comprehensively describe such variation. We assessed total repertoire metrics of mutation, diversity, VJ gene usage and isotype subclass usage as well as tracking specific BCR sequence clusters. There was good assay reproducibility (both in PCR amplification and biological replicates), but we detected striking fluctuations in the repertoire over time that we hypothesize may be due to subclinical immune activation. Repertoire properties were unique for each individual, which could partly be explained by a decrease in IgG2 with age, and genetic differences at the immunoglobulin locus. There was a small repertoire of public clusters (0.5, 0.3, and 1.4% of total IgA, IgG, and IgM clusters, respectively), which was enriched for expanded clusters containing sequences with suspected specificity toward antigens that should have been historically encountered by all participants through prior immunization or infection. We thus provide baseline BCR repertoire information that can be used to inform future study design, and aid in interpretation of results from these studies. Furthermore, our results indicate that BCR repertoire studies could be used to track changes in the public repertoire in and between populations that might relate to population immunity against infectious diseases, and identify the characteristics of inflammatory and immunological diseases.
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Affiliation(s)
- Jacob D. Galson
- Oxford Vaccine Group, Department of Paediatrics, The NIHR Oxford Biomedical Research Center, University of Oxford, Oxford, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Johannes Trück
- Oxford Vaccine Group, Department of Paediatrics, The NIHR Oxford Biomedical Research Center, University of Oxford, Oxford, UK
- Paediatric Immunology, University Children’s Hospital, Zürich, Switzerland
| | - Anna Fowler
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Márton Münz
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Vincenzo Cerundolo
- Medical Research Council Human Immunology Unit, Weatherall Institute of Molecular Medicine, Oxford, UK
| | - Andrew J. Pollard
- Oxford Vaccine Group, Department of Paediatrics, The NIHR Oxford Biomedical Research Center, University of Oxford, Oxford, UK
| | - Gerton Lunter
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Dominic F. Kelly
- Oxford Vaccine Group, Department of Paediatrics, The NIHR Oxford Biomedical Research Center, University of Oxford, Oxford, UK
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50
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Greiff V, Bhat P, Cook SC, Menzel U, Kang W, Reddy ST. A bioinformatic framework for immune repertoire diversity profiling enables detection of immunological status. Genome Med 2015; 7:49. [PMID: 26140055 PMCID: PMC4489130 DOI: 10.1186/s13073-015-0169-8] [Citation(s) in RCA: 128] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Lymphocyte receptor repertoires are continually shaped throughout the lifetime of an individual in response to environmental and pathogenic exposure. Thus, they may serve as a fingerprint of an individual's ongoing immunological status (e.g., healthy, infected, vaccinated), with far-reaching implications for immunodiagnostics applications. The advent of high-throughput immune repertoire sequencing now enables the interrogation of immune repertoire diversity in an unprecedented and quantitative manner. However, steadily increasing sequencing depth has revealed that immune repertoires vary greatly among individuals in their composition; correspondingly, it has been reported that there are few shared sequences indicative of immunological status ('public clones'). Disconcertingly, this means that the wealth of information gained from repertoire sequencing remains largely unused for determining the current status of immune responses, thereby hampering the implementation of immune-repertoire-based diagnostics. METHODS Here, we introduce a bioinformatics repertoire-profiling framework that possesses the advantage of capturing the diversity and distribution of entire immune repertoires, as opposed to singular public clones. The framework relies on Hill-based diversity profiles composed of a continuum of single diversity indices, which enable the quantification of the extent of immunological information contained in immune repertoires. RESULTS We coupled diversity profiles with unsupervised (hierarchical clustering) and supervised (support vector machine and feature selection) machine learning approaches in order to correlate patients' immunological statuses with their B- and T-cell repertoire data. We could predict with high accuracy (greater than or equal to 80 %) a wide range of immunological statuses such as healthy, transplantation recipient, and lymphoid cancer, suggesting as a proof of principle that diversity profiling can recover a large amount of immunodiagnostic fingerprints from immune repertoire data. Our framework is highly scalable as it easily allowed for the analysis of 1000 simulated immune repertoires; this exceeds the size of published immune repertoire datasets by one to two orders of magnitude. CONCLUSIONS Our framework offers the possibility to advance immune-repertoire-based fingerprinting, which may in the future enable a systems immunogenomics approach for vaccine profiling and the accurate and early detection of disease and infection.
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Affiliation(s)
- Victor Greiff
- ETH Zürich, Department of Biosystems Science and Engineering, Basel, 4058 Switzerland
| | - Pooja Bhat
- ETH Zürich, Department of Biosystems Science and Engineering, Basel, 4058 Switzerland
| | - Skylar C Cook
- ETH Zürich, Department of Biosystems Science and Engineering, Basel, 4058 Switzerland
| | - Ulrike Menzel
- ETH Zürich, Department of Biosystems Science and Engineering, Basel, 4058 Switzerland
| | - Wenjing Kang
- ETH Zürich, Department of Biosystems Science and Engineering, Basel, 4058 Switzerland
| | - Sai T Reddy
- ETH Zürich, Department of Biosystems Science and Engineering, Basel, 4058 Switzerland
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