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

Mikhail V. Pogorelyy(Pirogov Russian National Research Medical University), Anastasia A. Minervina(Institute of Bioorganic Chemistry), Maximilian Puelma Touzel(Centre National de la Recherche Scientifique), Anastasiia L. Sycheva(Institute of Bioorganic Chemistry), Ekaterina A. Komech(Pirogov Russian National Research Medical University), Elena I. Kovalenko(Institute of Bioorganic Chemistry), Galina G. Karganova(Sechenov University), Evgeniy S. Egorov(Pirogov Russian National Research Medical University), Alexander Komkov(Institute of Bioorganic Chemistry), Dmitriy M. Chudakov(Skolkovo Institute of Science and Technology), Ilgar Z. Mamedov(Pirogov Russian National Research Medical University), Thierry Mora(Centre National de la Recherche Scientifique), Aleksandra M. Walczak(Centre National de la Recherche Scientifique), Yuri B. Lebedev(Lomonosov Moscow State University)
Proceedings of the National Academy of Sciences
November 20, 2018
Cited by 142Open Access
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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 600 to 1,700 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 postinfection, making it suitable for systematic discovery of new infection-specific TCRs in the clinic.


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