Vanessa Mhanna, Habib Bashour, Khang Lê Quý, Pierre Barennes, Puneet Rawat, Victor Greiff, Encarnita Mariotti-Ferrandiz
{"title":"Adaptive immune receptor repertoire analysis","authors":"Vanessa Mhanna, Habib Bashour, Khang Lê Quý, Pierre Barennes, Puneet Rawat, Victor Greiff, Encarnita Mariotti-Ferrandiz","doi":"10.1038/s43586-023-00284-1","DOIUrl":null,"url":null,"abstract":"B cell and T cell receptor repertoires compose the adaptive immune receptor repertoire (AIRR) of an individual. The AIRR is a unique collection of antigen-specific receptors that drives adaptive immune responses, which in turn is imprinted in each individual AIRR. This supports the concept that the AIRR could determine disease outcomes, for example in autoimmunity, infectious disease and cancer. AIRR analysis could therefore assist the diagnosis, prognosis and treatment of human diseases towards personalized medicine. High-throughput sequencing, high-dimensional statistical analysis, computational structural biology and machine learning are currently employed to study the shaping and dynamics of the AIRR as a function of time and antigenic challenges. This Primer provides an overview of concepts and state-of-the-art methods that underlie experimental and computational AIRR analysis and illustrates the diversity of relevant applications. The Primer also addresses some of the outstanding challenges in AIRR analysis, such as sampling, sequencing depth, experimental variations and computational biases, while discussing prospects of future AIRR analysis applications for understanding and predicting adaptive immune responses. The adaptive immune receptor repertoire (AIRR) drives adaptive immune responses, which could determine disease outcomes, infectious disease and cancer. Mhanna, Bashour et al. outline the approaches and challenges in AIRR analysis, as well as future developments towards predicting adaptive immune responses.","PeriodicalId":74250,"journal":{"name":"Nature reviews. Methods primers","volume":" ","pages":"1-25"},"PeriodicalIF":50.1000,"publicationDate":"2024-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature reviews. Methods primers","FirstCategoryId":"1085","ListUrlMain":"https://www.nature.com/articles/s43586-023-00284-1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
B cell and T cell receptor repertoires compose the adaptive immune receptor repertoire (AIRR) of an individual. The AIRR is a unique collection of antigen-specific receptors that drives adaptive immune responses, which in turn is imprinted in each individual AIRR. This supports the concept that the AIRR could determine disease outcomes, for example in autoimmunity, infectious disease and cancer. AIRR analysis could therefore assist the diagnosis, prognosis and treatment of human diseases towards personalized medicine. High-throughput sequencing, high-dimensional statistical analysis, computational structural biology and machine learning are currently employed to study the shaping and dynamics of the AIRR as a function of time and antigenic challenges. This Primer provides an overview of concepts and state-of-the-art methods that underlie experimental and computational AIRR analysis and illustrates the diversity of relevant applications. The Primer also addresses some of the outstanding challenges in AIRR analysis, such as sampling, sequencing depth, experimental variations and computational biases, while discussing prospects of future AIRR analysis applications for understanding and predicting adaptive immune responses. The adaptive immune receptor repertoire (AIRR) drives adaptive immune responses, which could determine disease outcomes, infectious disease and cancer. Mhanna, Bashour et al. outline the approaches and challenges in AIRR analysis, as well as future developments towards predicting adaptive immune responses.