Age-Based Dynamics of a Stable Circulating Cd8 T Cell Repertoire Component

• Published in: Frontiers in immunology Vol. 10; p. 1717
• Main Authors: Naumova, Elena N, Yassai, Maryam B, Demos, Wendy, Reed, Erica, Unruh, Melissa, Haribhai, Dipica, Williams, Calvin B, Naumov, Yuri N, Gorski, Jack
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 06.08.2019
• Subjects: circulation as depot; computational immunology; human CD8 T cells; Immunology; repertoire maturation; senescence; senescence; computational immunology; repertoire maturation; human CD8 T cells; circulation as depot
• ISSN: 1664-3224; 1664-3224
• DOI: 10.3389/fimmu.2019.01717

T-cell memory to pathogens can be envisioned as a receptor-based imprint of the pathogenic environment on the naïve repertoire of clonotypes. Recurrent exposures to a pathogen inform and reinforce memory, leading to a mature state. The complexity and temporal stability of this system in man is only beginning to be adequately described. We have been using a rank-frequency approach for quantitative analysis of CD8 T cell repertoires. Rank acts as a proxy for previous expansion, and rank-frequency, the number of clonotypes at a particular rank, as a proxy for abundance, with the relation of the two estimating the diversity of the system. Previous analyses of circulating antigen-experienced cytotoxic CD8 T-cell repertoires from adults have shown a complex two-component clonotype distribution. Here we show this is also the case for circulating CD8 T cells expressing the BV19 receptor chain from five adult subjects. When the repertoire characteristic of clonotype stability is added to the analysis, an inverse correlation between clonotype rank frequency and stability is observed. Clonotypes making up the second distributional component are stable; indicating that the circulation can be a depot of selected clonotypes. Temporal repertoire dynamics was further examined for influenza-specific T cells from children, middle-aged, and older adults. Taken together, these analyses describe a dynamic process of system development and aging, with increasing distributional complexity, leading to a stable circulating component, followed by loss of both complexity and stability.