bioRxivImmunology
Longitudinal immunosequencing in healthy people reveals persistent T cell receptors rich in public receptors
N. D. Chu, H. S. Bi, R. O. Emerson, A. M. Sherwood, M. E. Birnbaum, H. S. Robins, E. J. Alm
Abstract
BackgroundThe adaptive immune system maintains a diversity of T cells capable of recognizing a broad array of antigens. Each T cells specificity and affinity for antigens is determined by its T cell receptors (TCRs), which together across all T cells form a repertoire of tens of millions of unique receptors in each individual. Although many studies have examined how TCR repertoires change in response to disease or drugs, few have explored the temporal dynamics of the TCR repertoire in healthy individuals.\n\nResultsHere we report immunosequencing of TCR {beta} chains (TCR{beta}) from the blood of three healthy individuals at eight time points over one year. TCR{beta} repertoires from samples of all T cells and memory T cells clearly clustered by individual, confirming that TCR{beta} repertoires are specific to individuals across time. This individuality was absent from TCR{beta}s from naive T cells, suggesting that these differences result from an individuals antigen exposure history. Many characteristics of the TCR{beta} repertoire (e.g., alpha diversity, clonality) were stable across time, although we found evidence of T cell expansion dynamics even within healthy individuals. We further identified a subset of \"persistent\" TCR{beta}s present across all time points, and these receptors were rich in clonal and public receptors.\n\nConclusionsOur results revealed persistent receptors that may play a key role in immune system maintenance. They further highlight the importance of longitudinal sampling of the immune system and provide a much-needed baseline for TCR{beta} dynamics in healthy individuals. Such a baseline should help improve interpretation of changes in the TCR{beta} repertoire during disease or treatment.
- organism: human
- assay: CITE-seq
- research focus: cell type annotation
- research focus: clustering
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: experimental assay
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