Detecting T cell receptors involved in immune responses from single repertoire snapshots

• Published in: PLoS biology Vol. 17; no. 6; p. e3000314
• Main Authors: Pogorelyy, Mikhail V., Minervina, Anastasia A., Shugay, Mikhail, Chudakov, Dmitriy M., Lebedev, Yuri B., Mora, Thierry, Walczak, Aleksandra M.
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 13.06.2019; Public Library of Science (PLoS)
• Subjects: Adaptive immunity; Adaptive Immunity - genetics; Adaptive immunology; Amino acids; Ankylosing spondylitis; Antigen receptors, T cell; Antigens; Antigens, Viral; Arthritis; Autoimmune diseases; Biology and Life Sciences; Cancer immunotherapy; Cluster Analysis; Clustering; Complementarity Determining Regions - genetics; Complementarity Determining Regions - physiology; Data collection; Disease control; Funding; High-Throughput Nucleotide Sequencing - methods; Humans; Immune response; Immunity; Immunology; Immunotherapy; Information processing; Life Sciences; Lymphocytes; Lymphocytes T; Medical research; Medicine and Health Sciences; Next-generation sequencing; Observations; Physiological aspects; Receptors; Receptors, Antigen, T-Cell - immunology; Receptors, Antigen, T-Cell - metabolism; Receptors, Antigen, T-Cell - physiology; Research and Analysis Methods; Sequence Analysis, DNA - methods; Software; Spondylitis; Supervision; T cell receptors; T cells; T-cell receptor; Vaccines; Vector-borne diseases; Yellow fever; United States; Czech Republic; France; United States > US; Russia; Immune response; Lymphocytes; Protein sequencing; T cell receptors; Nucleotide sequencing; Cancer immunotherapy; Sequence motif analysis; Vaccination and immunization
• ISSN: 1545-7885; 1544-9173; 1545-7885
• DOI: 10.1371/journal.pbio.3000314

Hypervariable T cell receptors (TCRs) play a key role in adaptive immunity, recognizing a vast diversity of pathogen-derived antigens. Our ability to extract clinically relevant information from large high-throughput sequencing of TCR repertoires (RepSeq) data is limited, because little is known about TCR-disease associations. We present Antigen-specific Lymphocyte Identification by Clustering of Expanded sequences (ALICE), a statistical approach that identifies TCR sequences actively involved in current immune responses from a single RepSeq sample and apply it to repertoires of patients with a variety of disorders - patients with autoimmune disease (ankylosing spondylitis [AS]), under cancer immunotherapy, or subject to an acute infection (live yellow fever [YF] vaccine). We validate the method with independent assays. ALICE requires no longitudinal data collection nor large cohorts, and it is directly applicable to most RepSeq datasets. Its results facilitate the identification of TCR variants associated with diseases and conditions, which can be used for diagnostics and rational vaccine design.