A hierarchy of selection pressures determines the organization of the T cell receptor repertoire

Abstract

We systematically examine the receptor repertoire in T cell subsets in young, adult, and LCMV-infected mice. Somatic recombination generates diversity, resulting in the limited overlap between nucleotide sequences of different repertoires even within the same individual. However, statistical features of the repertoire, quantified by the V gene and CDR3 k-mer frequency distributions, are highly conserved. A hierarchy of immunological processes drives the evolution of this structure. Intra-thymic divergence of CD4+ and CD8+ lineages imposes subtle but dominant differences observed across repertoires of all subpopulations in both young and adult mice. Differentiation from naive through memory to effector phenotype imposes an additional gradient of repertoire diversification, which is further influenced by age in a complex and lineage-dependent manner. The distinct repertoire of CD4+ regulatory T cells is more similar to naive cells in young mice and to effectors in adults. Finally, we describe divergent (naive and memory) and convergent (CD8+ effector) evolution of the repertoire following acute infection with LCMV. This study presents a quantitative framework that captures the structure of the repertoire in terms of its fundamental statistical properties and describes how this structure evolves as individual T cells differentiate, migrate and mature in response to antigen exposure.

Viral infection reveals hidden sharing of TCR CDR3 sequences between individuals

“…We sequenced the TCR repertoire of naive, central memory and effector memory CD4+ and CD8+ T cells from the spleen and bone marrow of three to four C57BL/6 mice at 8 - and 40-days post LCMV infection (summarized in Figure 1A ). The library preparation incorporates molecular identifiers (UMI) for each cDNA molecule, which allows subsequent correction for PCR bias and sequencing error, allowing a robust and quantitative annotation of each sequence in terms of CDR3 sequence and frequency ( 22 , 23 , 30 ); About ~1.89 x10 6 annotated CDR3 nucleotide beta chains were obtained, including a varied number of sequences between compartments, tissues, and infection status ( SI Table 1 ), which positively correlates with the number of sorted cells ( SI Figure 1C ). Our analysis focuses mainly on the amino acid sequence of the TCR beta complementarity determining region 3 (CDR3βAA), which is the most diverse region of the TCR molecule and is associated with antigen epitope recognition ( 1 ).…”

“…We were interested in the impact of infection on driving convergence (increased sharing) versus divergence (decreased TCR sharing) between repertoires. In order to quantify repertoire overlap, while incorporating TCR abundance, we used the pairwise cosine distance between the abundance vectors for each repertoire (see M&M in ( 23 )) to create a matrix of similarities between all pairs of repertoires. We have previously shown that this measure is highly correlated to the Morisita overlap index.…”

“…The pipeline introduces unique molecular identifiers attached to individual cDNA molecules, which allows correction for sequencing error PCR bias, and provides a quantitative and reproducible method of library preparation. Full details pre-processing pipeline are published ( 23 ).…”

Chasing the chains by testing them twice

“…Technically, this implies a high purity of the samples, which is essential to characterise TCR repertoires. Biologically, it means not only that the TCR repertoire of CD4 and CD8 cells are different (Bergot et al, 2015;Camaglia et al, 2023;Mark et al, 2022), but that the CD4/CD8 lineage choice of T cells is completely TCR-driven, and that this choice is made consistently within and between mice. In other words, it shows that CD4/CD8 fate choice is largely deterministic, although it is based on the affinity of the TCR for a large variety of self-peptide/MHC complexes.…”