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Chicken immune repertoire sequencing12/29/2023 These approaches fail to capture other interesting aspects of the germline-encoded regions such as gene similarity, as well as the relative importance of the CDRs and framework regions for TCR binding specificity. As comparing full CDR3 sequences can be highly involved, one approach is to simply compare CDR3 length distributions. Most current methods of repertoire comparison involve reducing the TCR sequences into simpler summaries and then comparing these summaries. For example, the pair of datasets could be samples of an individual’s TCR repertoire before and after a vaccination, and the researcher might wish to determine the responding TCRs in the post-vaccination repertoire. Often, this reduces to a situation wherein a researcher wishes to compare two TCR repertoire datasets and extract meaningful differences between them. The arrival of high-throughput sequencing has given scientists the ability to sample TCR repertoires with unprecedented depth, paving the way for immense progress within the field of computational immunology. Thus, proper analysis of TCR repertoires as well as the immune context surrounding them presents a formidable but necessary challenge to computational biologists. Even after a series of productivity-based filters ensuring functionality and limiting self-reactivity, this process yields an astronomical diversity in the circulating pool of TCR sequences. The DNA sequences coding for TCRs arise by a complex stochastic recombination process called V(D)J recombination, which includes insertions and deletions in a region known as the complementarity determining region 3, or CDR3. Through the ability of their TCRs to bind to foreign invaders like viruses or bacteria, T cells are able to recognize and neutralize these invasions, ultimately allowing for robust and long-lasting immunological protection. T cell receptors (TCRs) are protein complexes found on the surfaces of T cells, important white blood cells to the adaptive immune response. The other authors declare that no competing interests exist. He has patents on methods related to T cell receptor biology. He has received travel reimbursement from 10X Genomics and Illumina. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Ĭompeting interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: Paul G Thomas consults for Johnson and Johnson, Immunoscape, Cytoagents, and PACT Pharma. FAM received funding from the National Institutes of Health ( ) R01 AI146028, U19 AI117891, a Faculty Scholar grant from the Howard Hughes Medical Institute ( ) and the Simons Foundation ( ). PB received funding from the National Institutes of Health ( ) R35 GM141457, R01 AI146028. SAS and PGT received funding from the National Institutes of Health ( ) R01 AI121832, R01 AI136514, U01 AI150747, and the American Lebanese Syrian Associated Charities at St. įunding: BJO received funding from the National Institutes of Health ( ) R01 AI146028, U19 AI117891. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.ĭata Availability: All relevant data are within the manuscript and corresponding GitHub repository. Received: MaAccepted: OctoPublished: December 7, 2022Ĭopyright: © 2022 Olson et al. PLoS Comput Biol 18(12):Ĭolumbia University Medical Center: Columbia University Irving Medical Center, UNITED STATES We demonstrate that our method can identify biologically meaningful repertoire differences using several case studies.Ĭitation: Olson BJ, Schattgen SA, Thomas PG, Bradley P, Matsen IV FA (2022) Comparing T cell receptor repertoires using optimal transport. We present a complementary method of comparing TCR repertoires that detects significantly different TCRs between two given repertoires using a distance rather than a model, summary statistics, or dimension reduction. Current methods of comparing TCR repertoires either rely on statistical models which may not adequately describe the data, use summary statistics that may lose information, or are difficult to interpret. Because of this, immunologists are often interested in comparing different sets (or repertoires) of these TCRs in hopes of identifying groups of particular interest, such as TCRs that are responding to a particular vaccination using pre- and post-vaccination samples. These T cell receptors (TCRs) recognize peptides that may be foreign invaders such as viruses or bacteria. T cells are critical for a successful adaptive immune response, largely due to the expression of highly diverse receptor proteins on their surfaces.
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