Longitudinal immunosequencing in healthy people reveals persistent T cell receptors rich in highly public receptors

Abstract

Background: The adaptive immune system maintains a diversity of T cells capable of recognizing a broad array of antigens. Each T cell's specificity for antigens is determined by its T cell receptors (TCRs), which together across all T cells form a repertoire 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.

Results: Here we report immunosequencing of TCR β chains (TCRβ) from the blood of three healthy individuals at eight time points over one year. TCRβ repertoires of all peripheral-blood T cells and sorted memory T cells clustered clearly by individual, systematically demonstrating that TCRβ repertoires are specific to individuals across time. This individuality was absent from TCRβs from naive T cells, suggesting that the differences resulted from an individual's antigen exposure history, not genetic background. Many characteristics of the TCRβ repertoire (e.g., 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" TCRβs present across all time points. These receptors were rich in clonal and highly public receptors and may play a key role in immune system maintenance.

Conclusions: Our results highlight the importance of longitudinal sampling of the immune system, providing a much-needed baseline for TCRβ dynamics in healthy individuals. Such a baseline will improve interpretation of changes in the TCRβ repertoire during disease or treatment.

Keywords: Healthy controls; Immunosequencing; Memory T cell; Naive T cell; Persistent receptors; Public receptors; Repertoire sequencing; T cell receptor.

Fig. 1

The TCRβ repertoire displayed stability and individual-specific characteristics across time. a Experimental design of T cell sampling. b A heatmap of Jaccard indexes shows clear clustering of samples by individual. Samples of naive T cells clustered less by individual than did PBMC or memory T cell samples. Relative abundances of the 20 most abundant TCRβs (c) appeared stable through time. TCRβ abundances in PBMCs correlated within an individual across time points, including across a month (d, shared TCRβs = 33,601, Spearman rho = 0.55718, p < 10^− 6), and a year (e, shared TCRβs = 25,933, Spearman rho = 0.53810, p < 10^− 6), as well as across a month in naive (f, shared TCRβs = 15,873, Spearman rho = 0.37892, p < 10^− 6) and memory T cells (g, shared TCRβs = 47,866, Spearman rho = 0.64934, p < 10^− 6). TCRβs correlated much less across individuals (h, shared TCRβs = 5014, Spearman rho = 0.28554, p < 10^− 6). Shannon alpha diversity estimate (i) and clonality (defined as 1 – Pielou’s evenness, j) of the TCRβ repertoire were consistent over time

Fig. 2

A subset of the TCRβ repertoire occurred across all time points—the persistent TCRβ repertoire. a The number of TCRβs observed at n time points. Persistent TCRβs tended to have (b) greater abundance (Mann-Whitney U test, statistic = 26,297,052,589.5, p < 10^− 308) and (c) nucleotide sequence redundancy (Mann-Whitney U test, statistic = 25,851,211,348.0, p < 10^− 308) than other receptors. Mann-Whitney U tests between groups are in Additional file 2: Tables S6, S7. Persistent TCRβs had higher proportions of TCRβs in common with memory (d) and with naive (e) T cell populations and constituted a stable and significant fraction of overall TCRβ abundance across time (f)

Fig. 3

Persistent TCRβs were more functionally redundant. We created a network graph of TCRβs from each individual, drawing edges between TCRβs on the basis of sequence similarity (Levenshtein distances), which reflects antigen specificity. We then grouped TCRβs into decile bins based on the number of neighbors (similar TCRβs) of each TCRβ. In other words, TCRβs in the 0–10% bin had 0 to 10% of the maximum number of neighbors observed for any TCRβ—the fewest neighbors—while those in the 90–100% bin had near the maximum number of neighbors observed. For each decile bin, we then counted how many samples each TCRβ occurred in from our time series data. a Vertical histograms of these distributions indicate that TCRβs with few neighbors —and thus few similar observed TCRβs—tended to occur at only a single time point, while TCRβs with more neighbors—and thus higher numbers of similar TCRβs observed—tended to have a higher proportion of persistent TCRβs. b The number of TCRβs in each neighbor bin (Additional file 1: Figure S13a)

Fig. 4

Persistent TCRβs were enriched in highly public TCRβs. We identified public TCRβs occurring in 0–10%, 0–20%, . . . 90–100% of individuals in an independent, large cohort of similarly profiled subjects (N = 778). For each of these decile bins, we examined TCRβs shared across each of our three individuals’ time series data and tallied the number of time points at which we observed each TCRβ. a Vertical histograms of these distributions indicate that more-private TCRβs—TCRβs shared by few people—occurred most often at only a single time point, while more-public TCRβs tended to persist across time. b The number of TCRβs evaluated in each decile bin. The vast majority of receptors were not shared or were shared across few individuals (also see Additional file 1: Figure S13b). c In all three individuals in this study, persistent TCRβs included greater numbers of highly public TCRβs—defined here as receptors shared by over 70% of subjects from the large cohort—than receptors that only occurred once (independent t-test, statistic = − 4.508, p = 0.01). Asterisks indicate p < 0.05. d The three most public TCRβs (in over 90% of 778 individuals) were also persistent in all three individuals