Precise tracking of vaccine-responding T-cell clones reveals convergent and personalized response in identical twins

TL;DR

This study introduces a statistical framework for analyzing T-cell receptor repertoire data to identify vaccine-responding T-cell clones, revealing both personalized and convergent immune responses in identical twins, with potential clinical applications.

Contribution

We developed a novel statistical method to detect TCR clone dynamics and demonstrated its effectiveness in identifying vaccine-responding T-cells in twin pairs, highlighting personalized and shared immune responses.

Findings

Identified 500-1500 responding TCRs per donor

Responding TCRs were mostly private but showed higher overlap in twins

Method predicts TCR responses using sequence similarity

Abstract

T-cell receptor (TCR) repertoire data contain information about infections that could be used in disease diagnostics and vaccine development, but extracting that information remains a major challenge. Here we developed a statistical framework to detect TCR clone proliferation and contraction from longitudinal repertoire data. We applied this framework to data from three pairs of identical twins immunized with the yellow fever vaccine. We identified 500-1500 responding TCRs in each donor and validated them using three independent assays. While the responding TCRs were mostly private, albeit with higher overlap between twins, they could be well predicted using a classifier based on sequence similarity. Our method can also be applied to samples obtained post-infection, making it suitable for systematic discovery of new infection-specific TCRs in the clinic.