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Zong F, Long C, Hu W, Chen S, Dai W, Xiao ZX, Cao Y. Abalign: a comprehensive multiple sequence alignment platform for B-cell receptor immune repertoires. Nucleic Acids Res 2023:7173809. [PMID: 37207341 DOI: 10.1093/nar/gkad400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2023] [Revised: 04/23/2023] [Accepted: 05/08/2023] [Indexed: 05/21/2023] Open
Abstract
The utilization of high-throughput sequencing (HTS) for B-cell receptor (BCR) immune repertoire analysis has become widespread in the fields of adaptive immunity and antibody drug development. However, the sheer volume of sequences generated by these experiments presents a challenge in data processing. Specifically, multiple sequence alignment (MSA), a critical aspect of BCR analysis, remains inadequate for handling massive BCR sequencing data and lacks the ability to provide immunoglobulin-specific information. To address this gap, we introduce Abalign, a standalone program specifically designed for ultrafast MSA of BCR/antibody sequences. Benchmark tests demonstrate that Abalign achieves comparable or even better accuracy than state-of-the-art MSA tools, and shows remarkable advantages in terms of speed and memory consumption, reducing the time required for high-throughput analysis from weeks to hours. In addition to its alignment capabilities, Abalign offers a broad range of BCR analysis features, including extracting BCRs, constructing lineage trees, assigning VJ genes, analyzing clonotypes, profiling mutations, and comparing BCR immune repertoires. With its user-friendly graphic interface, Abalign can be easily run on personal computers instead of computing clusters. Overall, Abalign is an easy-to-use and effective tool that enables researchers to analyze massive BCR/antibody sequences, leading to new discoveries in the field of immunoinformatics. The software is freely available at http://cao.labshare.cn/abalign/.
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Affiliation(s)
- Fanjie Zong
- Center of Growth, Metabolism and Aging, Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, China
- Animal Disease Prevention and Food Safety Key Laboratory of Sichuan Province, Microbiology and Metabolic Engineering Key Laboratory of Sichuan Province, Chengdu, China
| | - Chenyu Long
- Center of Growth, Metabolism and Aging, Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, China
- Animal Disease Prevention and Food Safety Key Laboratory of Sichuan Province, Microbiology and Metabolic Engineering Key Laboratory of Sichuan Province, Chengdu, China
| | - Wanxin Hu
- Center of Growth, Metabolism and Aging, Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, China
- Animal Disease Prevention and Food Safety Key Laboratory of Sichuan Province, Microbiology and Metabolic Engineering Key Laboratory of Sichuan Province, Chengdu, China
| | - Shuang Chen
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
| | - Wentao Dai
- NHC Key Laboratory of Reproduction Regulation & Shanghai-MOST Key Laboratory of Health and Disease Genomics, Shanghai Institute for Biomedical and Pharmaceutical Technologies, Shanghai, China
| | - Zhi-Xiong Xiao
- Center of Growth, Metabolism and Aging, Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, China
| | - Yang Cao
- Center of Growth, Metabolism and Aging, Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, China
- Animal Disease Prevention and Food Safety Key Laboratory of Sichuan Province, Microbiology and Metabolic Engineering Key Laboratory of Sichuan Province, Chengdu, China
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2
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Dascalu S, Preston SG, Dixon RJ, Flammer PG, Fiddaman S, Boyd A, Sealy JE, Sadeyen JR, Kaspers B, Velge P, Iqbal M, Bonsall MB, Smith AL. The influences of microbial colonisation and germ-free status on the chicken TCRβ repertoire. Front Immunol 2023; 13:1052297. [PMID: 36685492 PMCID: PMC9847582 DOI: 10.3389/fimmu.2022.1052297] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Accepted: 12/06/2022] [Indexed: 01/06/2023] Open
Abstract
Microbial colonisation is paramount to the normal development of the immune system, particularly at mucosal sites. However, the relationships between the microbiome and the adaptive immune repertoire have mostly been explored in rodents and humans. Here, we report a high-throughput sequencing analysis of the chicken TCRβ repertoire and the influences of microbial colonisation on tissue-resident TCRβ+ cells. The results reveal that the microbiome is an important driver of TCRβ diversity in both intestinal tissues and the bursa of Fabricius, but not in the spleen. Of note, public TCRβ sequences (shared across individuals) make a substantial contribution to the repertoire. Additionally, different tissues exhibit biases in terms of their V family and J gene usage, and these effects were influenced by the gut-associated microbiome. TCRβ clonal expansions were identified in both colonised and germ-free birds, but differences between the groups were indicative of an influence of the microbiota. Together, these findings provide an insight into the avian adaptive immune system and the influence of the microbiota on the TCRβ repertoire.
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Affiliation(s)
- Stefan Dascalu
- Department of Biology, University of Oxford, Oxford, United Kingdom
- Avian Influenza Research Group, The Pirbright Institute, Pirbright, United Kingdom
| | - Stephen G. Preston
- Department of Biology, University of Oxford, Oxford, United Kingdom
- UCL School of Pharmacy, University College London, London, United Kingdom
| | - Robert J. Dixon
- Department of Biology, University of Oxford, Oxford, United Kingdom
| | | | - Steven Fiddaman
- Department of Biology, University of Oxford, Oxford, United Kingdom
| | - Amy Boyd
- Department of Biology, University of Oxford, Oxford, United Kingdom
| | - Joshua E. Sealy
- Avian Influenza Research Group, The Pirbright Institute, Pirbright, United Kingdom
| | - Jean-Remy Sadeyen
- Avian Influenza Research Group, The Pirbright Institute, Pirbright, United Kingdom
| | - Bernd Kaspers
- Veterinary Faculty, Ludwig Maximillians University of Munich, Planegg, Germany
| | - Philippe Velge
- Institut National de la Recherche Agronomique (INRAE), Université François Rabelais de Tours, Unités Mixtes de Recherche, Infectiologie et Santé Publique (ISP), Nouzilly, France
| | - Munir Iqbal
- Avian Influenza Research Group, The Pirbright Institute, Pirbright, United Kingdom
| | | | - Adrian L. Smith
- Department of Biology, University of Oxford, Oxford, United Kingdom
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3
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de Souza-Silva TG, Gollob KJ, Dutra WO. T-cell receptor variable region usage in Chagas disease: A systematic review of experimental and human studies. PLoS Negl Trop Dis 2022; 16:e0010546. [PMID: 36107855 PMCID: PMC9477334 DOI: 10.1371/journal.pntd.0010546] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
T cells recognize their ligand, the peptide major histocompatibility complex (MHC), via the T-cell receptor (TCR), which is composed of covalently linked α and β or γ and δ chains. This recognition is critical for T-cell ontogeny and controls the selection, activation, and function of T lymphocytes. Specific TCR αβ variable regions have been associated with immunopathogenesis of Chagas disease. Here, we present a systematic review that compiles experimental in vivo and human data regarding the preferential expression of variable alpha (Vα) and variable beta (Vβ) chain regions in Trypanosoma cruzi infection. The original studies indexed in PubMed/Medline, Scopus, and Web of Science databases were screened according to the PRISMA strategy. The analysis showed that expression of TCR Vα subfamilies were evaluated in one human study, and, unlike TCR Vβ, TCR Vα presented a more restricted usage. Despite the great variability in the usage of TCR Vβ regions in human Chagas disease, a down-regulation of TCR Vβ5 expression by T cells from patients in the acute phase of the disease was shown. Opposingly, this TCR region was found overly expressed in CD4+ T cells from chronic Chagas patients. It was also demonstrated that murine Vβ9+ T cells derived from nonlymphoid organs of T. cruzi-infected animals had a modulatory profile, while splenic Vβ9+ T cells produced inflammatory cytokines, indicating that although they display the same TCR Vβ region usage, these cells are functionally distinct. Despite the limitations of few papers and year of publication of the studies, compiling the data derived from them reveals that further investigation of TCR usage will point to their potential role in protective or pathogenic responses, as biomarkers of disease progression, and in the search for dominant peptides potentially useful for the development of vaccines or therapies. Chagas disease is a neglected tropical disease, caused by infection with Trypanosoma cruzi. Differential expression of certain T-cell receptor (TCR) variable regions has been associated with the immunopathogenesis of Chagas disease. Here, we present a systematic review that compiled experimental in vivo and human data regarding the preferential expression of TCR alpha and beta chain variable regions in Chagas disease. The original studies indexed in the PubMed/Medline, Scopus, and Web of Science databases were screened according to the PRISMA strategy. Despite the great variability in the use of TCR Vβ in T. cruzi infection, the outcomes indicate that there is a down-regulation of TCR Vβ5 expression in T cells from patients in the acute phase of Chagas disease. However, this region is preferentially expressed by CD4+ T cells from chronic Chagas patients. Additionally, it has been demonstrated that murine Vβ9+ T cells derived from nonlymphoid organs displayed a modulatory profile, while splenic Vβ9+ T cells produced inflammatory cytokines, indicating that although they express the same TCR Vβ region, these cells are functionally distinct. Information on TCR expression, specificity and function have critical impact on vaccine design.
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Affiliation(s)
- Thaiany Goulart de Souza-Silva
- Institute of Biological Sciences, Department of Morphology, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Kenneth J. Gollob
- Hospital Israelita Albert Einstein, São Paulo, Brazil
- Instituto Nacional de Ciência e Tecnologia em Doenças Tropicais, Belo Horizonte, Minas Gerais, Brazil
| | - Walderez O. Dutra
- Institute of Biological Sciences, Department of Morphology, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
- Instituto Nacional de Ciência e Tecnologia em Doenças Tropicais, Belo Horizonte, Minas Gerais, Brazil
- * E-mail:
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4
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Ghraichy M, von Niederhäusern V, Kovaltsuk A, Galson JD, Deane CM, Trück J. Different B cell subpopulations show distinct patterns in their IgH repertoire metrics. eLife 2021; 10:73111. [PMID: 34661527 PMCID: PMC8560093 DOI: 10.7554/elife.73111] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 10/17/2021] [Indexed: 12/11/2022] Open
Abstract
Several human B cell subpopulations are recognised in the peripheral blood, which play distinct roles in the humoral immune response. These cells undergo developmental and maturational changes involving VDJ recombination, somatic hypermutation and class switch recombination, altogether shaping their immunoglobulin heavy chain (IgH) repertoire. Here, we sequenced the IgH repertoire of naïve, marginal zone, switched and plasma cells from 10 healthy adults along with matched unsorted and in silico separated CD19+ bulk B cells. Using advanced bioinformatic analysis and machine learning, we show that sorted B cell subpopulations are characterised by distinct repertoire characteristics on both the individual sequence and the repertoire level. Sorted subpopulations shared similar repertoire characteristics with their corresponding in silico separated subsets. Furthermore, certain IgH repertoire characteristics correlated with the position of the constant region on the IgH locus. Overall, this study provides unprecedented insight over mechanisms of B cell repertoire control in peripherally circulating B cell subpopulations.
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Affiliation(s)
- Marie Ghraichy
- Division of Immunology, University Children's Hospital and Children's Research Center, University of Zurich (UZH), Zurich, Switzerland
| | - Valentin von Niederhäusern
- Division of Immunology, University Children's Hospital and Children's Research Center, University of Zurich (UZH), Zurich, Switzerland
| | | | - Jacob D Galson
- Division of Immunology, University Children's Hospital and Children's Research Center, University of Zurich (UZH), Zurich, Switzerland.,Alchemab Therapeutics Ltd, London, United Kingdom
| | - Charlotte M Deane
- Department of Statistics, University of Oxford, Oxford, United Kingdom
| | - Johannes Trück
- Division of Immunology, University Children's Hospital and Children's Research Center, University of Zurich (UZH), Zurich, Switzerland
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5
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Barennes P, Quiniou V, Shugay M, Egorov ES, Davydov AN, Chudakov DM, Uddin I, Ismail M, Oakes T, Chain B, Eugster A, Kashofer K, Rainer PP, Darko S, Ransier A, Douek DC, Klatzmann D, Mariotti-Ferrandiz E. Benchmarking of T cell receptor repertoire profiling methods reveals large systematic biases. Nat Biotechnol 2021; 39:236-245. [PMID: 32895550 DOI: 10.1038/s41587-020-0656-3] [Citation(s) in RCA: 62] [Impact Index Per Article: 20.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2019] [Accepted: 07/28/2020] [Indexed: 12/13/2022]
Abstract
Monitoring the T cell receptor (TCR) repertoire in health and disease can provide key insights into adaptive immune responses, but the accuracy of current TCR sequencing (TCRseq) methods is unclear. In this study, we systematically compared the results of nine commercial and academic TCRseq methods, including six rapid amplification of complementary DNA ends (RACE)-polymerase chain reaction (PCR) and three multiplex-PCR approaches, when applied to the same T cell sample. We found marked differences in accuracy and intra- and inter-method reproducibility for T cell receptor α (TRA) and T cell receptor β (TRB) TCR chains. Most methods showed a lower ability to capture TRA than TRB diversity. Low RNA input generated non-representative repertoires. Results from the 5' RACE-PCR methods were consistent among themselves but differed from the RNA-based multiplex-PCR results. Using an in silico meta-repertoire generated from 108 replicates, we found that one genomic DNA-based method and two non-unique molecular identifier (UMI) RNA-based methods were more sensitive than UMI methods in detecting rare clonotypes, despite the better clonotype quantification accuracy of the latter.
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Affiliation(s)
- Pierre Barennes
- Sorbonne Université, INSERM, Immunology-Immunopathology-Immunotherapy (i3), Paris, France
- AP-HP, Hôpital Pitié-Salpêtrière, Biotherapy (CIC-BTi) and Inflammation-Immunopathology-Biotherapy Department (i2B), Paris, France
| | - Valentin Quiniou
- Sorbonne Université, INSERM, Immunology-Immunopathology-Immunotherapy (i3), Paris, France
- AP-HP, Hôpital Pitié-Salpêtrière, Biotherapy (CIC-BTi) and Inflammation-Immunopathology-Biotherapy Department (i2B), Paris, France
| | - Mikhail Shugay
- Center of Life Sciences, Skoltech, Moscow, Russia
- Genomics of Adaptive Immunity Department, Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Pirogov Russian National Research Medical University, Moscow, Russia
| | - Evgeniy S Egorov
- Genomics of Adaptive Immunity Department, Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
| | - Alexey N Davydov
- Adaptive Immunity Group, Central European Institute of Technology, Brno, Czechia
| | - Dmitriy M Chudakov
- Center of Life Sciences, Skoltech, Moscow, Russia
- Genomics of Adaptive Immunity Department, Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Pirogov Russian National Research Medical University, Moscow, Russia
- Adaptive Immunity Group, Central European Institute of Technology, Brno, Czechia
| | - Imran Uddin
- Division of Infection and Immunity, University College London, London, UK
| | - Mazlina Ismail
- Division of Infection and Immunity, University College London, London, UK
| | - Theres Oakes
- Division of Infection and Immunity, University College London, London, UK
| | - Benny Chain
- Division of Infection and Immunity, University College London, London, UK
| | - Anne Eugster
- DFG-Centre for Regenerative Therapies Dresden, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Karl Kashofer
- Diagnostic and Research Institute of Pathology, Medical University of Graz, Graz, Austria
| | - Peter P Rainer
- Division of Cardiology, Medical University of Graz, Graz, Austria
- BioTechMed-Graz, Graz, Austria
| | - Samuel Darko
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Amy Ransier
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Daniel C Douek
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - David Klatzmann
- Sorbonne Université, INSERM, Immunology-Immunopathology-Immunotherapy (i3), Paris, France
- AP-HP, Hôpital Pitié-Salpêtrière, Biotherapy (CIC-BTi) and Inflammation-Immunopathology-Biotherapy Department (i2B), Paris, France
| | - Encarnita Mariotti-Ferrandiz
- Sorbonne Université, INSERM, Immunology-Immunopathology-Immunotherapy (i3), Paris, France.
- AP-HP, Hôpital Pitié-Salpêtrière, Biotherapy (CIC-BTi) and Inflammation-Immunopathology-Biotherapy Department (i2B), Paris, France.
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6
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Sethna Z, Isacchini G, Dupic T, Mora T, Walczak AM, Elhanati Y. Population variability in the generation and selection of T-cell repertoires. PLoS Comput Biol 2020; 16:e1008394. [PMID: 33296360 PMCID: PMC7725366 DOI: 10.1371/journal.pcbi.1008394] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Accepted: 09/11/2020] [Indexed: 12/21/2022] Open
Abstract
The diversity of T-cell receptor (TCR) repertoires is achieved by a combination of two intrinsically stochastic steps: random receptor generation by VDJ recombination, and selection based on the recognition of random self-peptides presented on the major histocompatibility complex. These processes lead to a large receptor variability within and between individuals. However, the characterization of the variability is hampered by the limited size of the sampled repertoires. We introduce a new software tool SONIA to facilitate inference of individual-specific computational models for the generation and selection of the TCR beta chain (TRB) from sequenced repertoires of 651 individuals, separating and quantifying the variability of the two processes of generation and selection in the population. We find not only that most of the variability is driven by the VDJ generation process, but there is a large degree of consistency between individuals with the inter-individual variance of repertoires being about ∼2% of the intra-individual variance. Known viral-specific TCRs follow the same generation and selection statistics as all TCRs.
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Affiliation(s)
- Zachary Sethna
- Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America
| | - Giulio Isacchini
- Laboratoire de physique de l'École Normale Supérieure, PSL University, CNRS, Sorbonne Université, Université de Paris 24 rue Lhomond, Paris, France.,Max Planck Institute for Dynamics and Self-organization, Am Faßberg 17, Göttingen, Germany
| | - Thomas Dupic
- Laboratoire de physique de l'École Normale Supérieure, PSL University, CNRS, Sorbonne Université, Université de Paris 24 rue Lhomond, Paris, France
| | - Thierry Mora
- Laboratoire de physique de l'École Normale Supérieure, PSL University, CNRS, Sorbonne Université, Université de Paris 24 rue Lhomond, Paris, France
| | - Aleksandra M Walczak
- Laboratoire de physique de l'École Normale Supérieure, PSL University, CNRS, Sorbonne Université, Université de Paris 24 rue Lhomond, Paris, France
| | - Yuval Elhanati
- Computational Oncology, Department of Epidemiology and Biostatistics, and Parker Institute for Cancer Immunotherapy, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America
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7
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Sethna Z, Elhanati Y, Callan CG, Walczak AM, Mora T. OLGA: fast computation of generation probabilities of B- and T-cell receptor amino acid sequences and motifs. Bioinformatics 2020; 35:2974-2981. [PMID: 30657870 PMCID: PMC6735909 DOI: 10.1093/bioinformatics/btz035] [Citation(s) in RCA: 107] [Impact Index Per Article: 26.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2018] [Revised: 11/10/2018] [Accepted: 01/13/2019] [Indexed: 01/08/2023] Open
Abstract
MOTIVATION High-throughput sequencing of large immune repertoires has enabled the development of methods to predict the probability of generation by V(D)J recombination of T- and B-cell receptors of any specific nucleotide sequence. These generation probabilities are very non-homogeneous, ranging over 20 orders of magnitude in real repertoires. Since the function of a receptor really depends on its protein sequence, it is important to be able to predict this probability of generation at the amino acid level. However, brute-force summation over all the nucleotide sequences with the correct amino acid translation is computationally intractable. The purpose of this paper is to present a solution to this problem. RESULTS We use dynamic programming to construct an efficient and flexible algorithm, called OLGA (Optimized Likelihood estimate of immunoGlobulin Amino-acid sequences), for calculating the probability of generating a given CDR3 amino acid sequence or motif, with or without V/J restriction, as a result of V(D)J recombination in B or T cells. We apply it to databases of epitope-specific T-cell receptors to evaluate the probability that a typical human subject will possess T cells responsive to specific disease-associated epitopes. The model prediction shows an excellent agreement with published data. We suggest that OLGA may be a useful tool to guide vaccine design. AVAILABILITY AND IMPLEMENTATION Source code is available at https://github.com/zsethna/OLGA. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Zachary Sethna
- Joseph Henry Laboratories, Princeton University, Princeton, NJ, USA
| | - Yuval Elhanati
- Joseph Henry Laboratories, Princeton University, Princeton, NJ, USA
| | - Curtis G Callan
- Joseph Henry Laboratories, Princeton University, Princeton, NJ, USA.,Laboratoire de physique de l'Ecole normale supérieure (PSL University), Centre national de la recherche scientifique, Sorbonne University, University Paris-Diderot, Paris, France
| | - Aleksandra M Walczak
- Laboratoire de physique de l'Ecole normale supérieure (PSL University), Centre national de la recherche scientifique, Sorbonne University, University Paris-Diderot, Paris, France
| | - Thierry Mora
- Laboratoire de physique de l'Ecole normale supérieure (PSL University), Centre national de la recherche scientifique, Sorbonne University, University Paris-Diderot, Paris, France
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8
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Ghraichy M, Galson JD, Kelly DF, Trück J. B-cell receptor repertoire sequencing in patients with primary immunodeficiency: a review. Immunology 2017; 153:145-160. [PMID: 29140551 DOI: 10.1111/imm.12865] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2017] [Revised: 10/25/2017] [Accepted: 11/07/2017] [Indexed: 12/17/2022] Open
Abstract
The advent of next-generation sequencing (NGS) now allows a detailed assessment of the adaptive immune system in health and disease. In particular, high-throughput B-cell receptor (BCR) repertoire sequencing provides detailed information about the functionality and abnormalities of the B-cell system. However, it is mostly unknown how the BCR repertoire is altered in the context of primary immunodeficiencies (PID) and whether findings are consistent throughout phenotypes and genotypes. We have performed an extensive literature search of the published work on BCR repertoire sequencing in PID patients, including several forms of predominantly antibody disorders and combined immunodeficiencies. It is somewhat surprising that BCR repertoires, even from severe clinical phenotypes, often show only mild abnormalities and that diversity or immunoglobulin gene segment usage is generally preserved to some extent. Despite the great variety of wet laboratory and analytical methods that were used in the different studies, several findings are common to most investigated PIDs, such as the increased usage of gene segments that are associated with self-reactivity. These findings suggest that BCR repertoire characteristics may be used to assess the functionality of the B-cell compartment irrespective of the underlying defect. With the use of NGS approaches, there is now the opportunity to apply BCR repertoire sequencing to multiple patients and explore the PID BCR repertoire in more detail. Ultimately, using BCR repertoire sequencing in translational research could aid the management of PID patients by improving diagnosis, estimating functionality of the immune system and improving assessment of prognosis.
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Affiliation(s)
- Marie Ghraichy
- Division of Immunology, University Children's Hospital Zurich, Zurich, Switzerland.,Children's Research Center, University Children's Hospital, University of Zurich, Zurich, Switzerland
| | - Jacob D Galson
- Children's Research Center, University Children's Hospital, University of Zurich, Zurich, Switzerland.,University of Zurich, Zurich, Switzerland
| | - Dominic F Kelly
- Oxford Vaccine Group, Department of Paediatrics, University of Oxford, Oxford, UK
| | - Johannes Trück
- Division of Immunology, University Children's Hospital Zurich, Zurich, Switzerland.,Children's Research Center, University Children's Hospital, University of Zurich, Zurich, Switzerland.,University of Zurich, Zurich, Switzerland
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9
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Abstract
The rapid development of immunomodulatory cancer therapies has led to a concurrent increase in the application of informatics techniques to the analysis of tumors, the tumor microenvironment, and measures of systemic immunity. In this review, the use of tumors to gather genetic and expression data will first be explored. Next, techniques to assess tumor immunity are reviewed, including HLA status, predicted neoantigens, immune microenvironment deconvolution, and T-cell receptor sequencing. Attempts to integrate these data are in early stages of development and are discussed in this review. Finally, we review the application of these informatics strategies to therapy development, with a focus on vaccines, adoptive cell transfer, and checkpoint blockade therapies.
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Affiliation(s)
- J Hammerbacher
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York
- Department of Microbiology and Immunology, Medical University of South Carolina, Charleston
| | - A Snyder
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York
- Adaptive Biotechnologies, Seattle, USA
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10
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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: 17.0] [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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