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Martin Beem J, Venkatayogi S, Haynes BF, Wiehe K. ARMADiLLO: a web server for analyzing antibody mutation probabilities. Nucleic Acids Res 2023; 51:W51-W56. [PMID: 37260077 PMCID: PMC10320107 DOI: 10.1093/nar/gkad398] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 04/25/2023] [Accepted: 05/30/2023] [Indexed: 06/02/2023] Open
Abstract
Antibodies are generated by B cells that evolve receptor specificity to pathogens through rounds of mutation and selection in a process called affinity maturation. Somatic hypermutation is mediated by an enzyme with DNA sequence context-dependent targeting and substitution resulting in variable probabilities of amino acid substitutions during affinity maturation. We have previously developed a program called Antigen Receptor Mutation Analyzer for the Detection of Low Likelihood Occurrences (ARMADiLLO) that performs simulations of the somatic hypermutation process to estimate the probabilities of observed antibody mutations. Here we describe the ARMADiLLO web server (https://armadillo.dhvi.duke.edu), an easy-to-use web interface that analyzes input antibody sequences and displays the probability estimates for all possible amino acid changes over the full length of an antibody sequence. The probability of antibody mutations can be used by immunologists studying B cell ontogenies and by vaccine designers that are pursuing strategies to elicit broadly neutralizing antibodies which are enriched with developmentally rate-limiting improbable mutations. The ARMADiLLO web server also contains precomputed results reporting the probability of amino acid substitutions in all human V gene segments and in a collection of HIV broadly neutralizing antibodies.
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Affiliation(s)
- Joshua S Martin Beem
- Duke Human Vaccine Institute, Duke University Medical Center; Durham, NC27710, USA
| | - Sravani Venkatayogi
- Duke Human Vaccine Institute, Duke University Medical Center; Durham, NC27710, USA
| | - Barton F Haynes
- Duke Human Vaccine Institute, Duke University Medical Center; Durham, NC27710, USA
- Department of Immunology, Duke University Medical Center; Durham, NC27710, USA
| | - Kevin Wiehe
- Duke Human Vaccine Institute, Duke University Medical Center; Durham, NC27710, USA
- Department of Medicine, Duke University Medical Center; Durham, NC27710, USA
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Abstract
High-throughput sequencing for B cell receptor (BCR) repertoire provides useful insights for the adaptive immune system. With the continuous development of the BCR-seq technology, many efforts have been made to develop methods for analyzing the ever-increasing BCR repertoire data. In this review, we comprehensively outline different BCR repertoire library preparation protocols and summarize three major steps of BCR-seq data analysis, i. e., V(D)J sequence annotation, clonal phylogenetic inference, and BCR repertoire profiling and mining. Different from other reviews in this field, we emphasize background intuition and the statistical principle of each method to help biologists better understand it. Finally, we discuss data mining problems for BCR-seq data and with a highlight on recently emerging multiple-sample analysis.
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Slabodkin A, Chernigovskaya M, Mikocziova I, Akbar R, Scheffer L, Pavlović M, Bashour H, Snapkov I, Mehta BB, Weber CR, Gutierrez-Marcos J, Sollid LM, Haff IH, Sandve GK, Robert PA, Greiff V. Individualized VDJ recombination predisposes the available Ig sequence space. Genome Res 2021; 31:2209-2224. [PMID: 34815307 PMCID: PMC8647828 DOI: 10.1101/gr.275373.121] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Accepted: 10/20/2021] [Indexed: 11/25/2022]
Abstract
The process of recombination between variable (V), diversity (D), and joining (J) immunoglobulin (Ig) gene segments determines an individual's naive Ig repertoire and, consequently, (auto)antigen recognition. VDJ recombination follows probabilistic rules that can be modeled statistically. So far, it remains unknown whether VDJ recombination rules differ between individuals. If these rules differed, identical (auto)antigen-specific Ig sequences would be generated with individual-specific probabilities, signifying that the available Ig sequence space is individual specific. We devised a sensitivity-tested distance measure that enables inter-individual comparison of VDJ recombination models. We discovered, accounting for several sources of noise as well as allelic variation in Ig sequencing data, that not only unrelated individuals but also human monozygotic twins and even inbred mice possess statistically distinguishable immunoglobulin recombination models. This suggests that, in addition to genetic, there is also nongenetic modulation of VDJ recombination. We demonstrate that population-wide individualized VDJ recombination can result in orders of magnitude of difference in the probability to generate (auto)antigen-specific Ig sequences. Our findings have implications for immune receptor-based individualized medicine approaches relevant to vaccination, infection, and autoimmunity.
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Affiliation(s)
- Andrei Slabodkin
- Department of Immunology and Oslo University Hospital, University of Oslo, 0372 Oslo, Norway
| | - Maria Chernigovskaya
- Department of Immunology and Oslo University Hospital, University of Oslo, 0372 Oslo, Norway
| | - Ivana Mikocziova
- Department of Immunology and Oslo University Hospital, University of Oslo, 0372 Oslo, Norway
| | - Rahmad Akbar
- Department of Immunology and Oslo University Hospital, University of Oslo, 0372 Oslo, Norway
| | - Lonneke Scheffer
- Department of Informatics, University of Oslo, 0373 Oslo, Norway
| | - Milena Pavlović
- Department of Informatics, University of Oslo, 0373 Oslo, Norway
| | - Habib Bashour
- School of Life Sciences, University of Warwick, Coventry CV4 7AL, United Kingdom
| | - Igor Snapkov
- Department of Immunology and Oslo University Hospital, University of Oslo, 0372 Oslo, Norway
| | - Brij Bhushan Mehta
- Department of Immunology and Oslo University Hospital, University of Oslo, 0372 Oslo, Norway
| | - Cédric R Weber
- Department of Biosystems Science and Engineering, ETH Zurich, 4058 Basel, Switzerland
| | | | - Ludvig M Sollid
- Department of Immunology and Oslo University Hospital, University of Oslo, 0372 Oslo, Norway
| | | | | | - Philippe A Robert
- Department of Immunology and Oslo University Hospital, University of Oslo, 0372 Oslo, Norway
| | - Victor Greiff
- Department of Immunology and Oslo University Hospital, University of Oslo, 0372 Oslo, Norway
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Waltari E, McGeever A, Friedland N, Kim PS, McCutcheon KM. Functional Enrichment and Analysis of Antigen-Specific Memory B Cell Antibody Repertoires in PBMCs. Front Immunol 2019; 10:1452. [PMID: 31293598 PMCID: PMC6603168 DOI: 10.3389/fimmu.2019.01452] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2019] [Accepted: 06/10/2019] [Indexed: 01/16/2023] Open
Abstract
Phenotypic screening of antigen-specific antibodies in human blood is a common diagnostic test for infectious agents and a correlate of protection after vaccination. In addition to long-lived antibody secreting plasma cells residing in the bone marrow, memory B cells are a latent source of antigen-experienced, long-term immunity that can be found at low frequencies in circulating peripheral blood mononuclear cells (PBMCs). Assessing the genotype, clonal frequency, quality, and function of antibodies resulting from an individual's persistent memory B cell repertoire can help inform the success or failure of immune protection. Using in vitro polyclonal stimulation, we functionally expand the memory repertoire from PBMCs and clonally map monoclonal antibodies from this population. We show that combining deep sequencing of stimulated memory B cell repertoires with retrieving single antigen-specific cells is a promising approach in evaluating the latent, functional B cell memory in PBMCs.
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Affiliation(s)
- Eric Waltari
- Chan Zuckerberg Biohub, San Francisco, CA, United States
| | - Aaron McGeever
- Chan Zuckerberg Biohub, San Francisco, CA, United States
| | - Natalia Friedland
- Stanford ChEM-H and Department of Biochemistry, Stanford University School of Medicine, Stanford, CA, United States
| | - Peter S. Kim
- Chan Zuckerberg Biohub, San Francisco, CA, United States
- Stanford ChEM-H and Department of Biochemistry, Stanford University School of Medicine, Stanford, CA, United States
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Venturi V, Thomas PG. The expanding role of systems immunology in decoding the T cell receptor repertoire. ACTA ACUST UNITED AC 2018; 12:37-45. [PMID: 31106281 DOI: 10.1016/j.coisb.2018.09.005] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
T cells play a crucial role in the immune system's defense against many infectious diseases, including persistent infections for which no effective vaccines currently exist. The T cell component of the adaptive immune system is highly complex involving a constantly evolving landscape of various inter-related T cell populations. These T cell populations are characterized by their phenotypic and functional properties as well as the collection, or repertoire, of T cell receptors (TCR) that mediate T cell recognition of antigenic peptides derived from pathogens. Understanding the various processes and factors that impact the development and evolution of the broader T cell repertoire available to recognize and respond to pathogens and the characteristics of antigen-experienced T cell repertoires associated with effective immune control of pathogens is critical to the rational design of T cell-based vaccines and therapies. In this article we discuss, using examples of recent research, the promise that systems immunology approaches, involving quantitative analysis and mathematical and computational modeling of immunological data, hold for decoding the complex TCR repertoire system in the current era of advancing technologies.
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Affiliation(s)
- Vanessa Venturi
- Infection Analytics Program, Kirby Institute for Infection and Immunity, UNSW Australia, Sydney, NSW, Australia
| | - Paul G Thomas
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA
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