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

MV. Pogorelyy, AA. Minervina, MP. Touzel, AL. Sycheva, EA. Komech, EI. Kovalenko, GG. Karganova, ES. Egorov, AY. Komkov, DM. Chudakov, IZ. Mamedov, T. Mora, AM. Walczak, YB. Lebedev,

. 2018 ; 115 (50) : 12704-12709. [pub] 20181120

Jazyk angličtina Země Spojené státy americké

Typ dokumentu časopisecké články, práce podpořená grantem

Perzistentní odkaz   https://www.medvik.cz/link/bmc19012130

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.

Biological Faculty Moscow State University 119991 Moscow Russia

Department of Genomics of Adaptive Immunity Shemyakin Ovchinnikov Institute of Bioorganic Chemistry 117997 Moscow Russia

Department of Genomics of Adaptive Immunity Shemyakin Ovchinnikov Institute of Bioorganic Chemistry 117997 Moscow Russia Department of Molecular Technologies Pirogov Russian National Research Medical University 117997 Moscow Russia

Department of Genomics of Adaptive Immunity Shemyakin Ovchinnikov Institute of Bioorganic Chemistry 117997 Moscow Russia Department of Molecular Technologies Pirogov Russian National Research Medical University 117997 Moscow Russia Center for Data Intensive Biomedicine and Biotechnology Skoltech 121205 Moscow Russia Central European Institute of Technology Masaryk University 62500 Brno Czech Republic

Department of Genomics of Adaptive Immunity Shemyakin Ovchinnikov Institute of Bioorganic Chemistry 117997 Moscow Russia Laboratory of Cytogenetics and Molecular Genetics Dmitry Rogachev National Medical Research Center of Pediatric Hematology Oncology and Immunology 117198 Moscow Russia

Department of Immunology Shemyakin Ovchinnikov Institute of Bioorganic Chemistry 117997 Moscow Russia

Department of Molecular Technologies Pirogov Russian National Research Medical University 117997 Moscow Russia Department of Genomics of Adaptive Immunity Shemyakin Ovchinnikov Institute of Bioorganic Chemistry 117997 Moscow Russia

Laboratoire de Physique Statistique CNRS Sorbonne Université Université Paris Diderot École Normale Supérieure 75005 Paris France

Laboratoire de Physique Théorique CNRS Sorbonne Université École Normale Supérieure 75005 Paris France

Laboratory of Biology of Arboviruses Chumakov Institute of Poliomyelitis and Viral Encephalitides 142782 Moscow Russia Department of Virology Sechenov 1st Moscow State Medical University 119146 Moscow Russia

Citace poskytuje Crossref.org

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$a Precise tracking of vaccine-responding T cell clones reveals convergent and personalized response in identical twins / $c MV. Pogorelyy, AA. Minervina, MP. Touzel, AL. Sycheva, EA. Komech, EI. Kovalenko, GG. Karganova, ES. Egorov, AY. Komkov, DM. Chudakov, IZ. Mamedov, T. Mora, AM. Walczak, YB. Lebedev,
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$a 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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$a Minervina, Anastasia A $u Department of Genomics of Adaptive Immunity, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, 117997 Moscow, Russia.
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$a Touzel, Maximilian Puelma $u Laboratoire de Physique Théorique, CNRS, Sorbonne Université, École Normale Supérieure (PSL), 75005 Paris, France.
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$a Sycheva, Anastasiia L $u Department of Genomics of Adaptive Immunity, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, 117997 Moscow, Russia.
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$a Komech, Ekaterina A $u Department of Genomics of Adaptive Immunity, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, 117997 Moscow, Russia. Department of Molecular Technologies, Pirogov Russian National Research Medical University, 117997 Moscow, Russia.
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$a Kovalenko, Elena I $u Department of Immunology, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, 117997 Moscow, Russia.
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$a Karganova, Galina G $u Laboratory of Biology of Arboviruses, Chumakov Institute of Poliomyelitis and Viral Encephalitides, 142782 Moscow, Russia. Department of Virology, Sechenov First Moscow State Medical University, 119146 Moscow, Russia.
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$a Egorov, Evgeniy S $u Department of Genomics of Adaptive Immunity, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, 117997 Moscow, Russia. Department of Molecular Technologies, Pirogov Russian National Research Medical University, 117997 Moscow, Russia.
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$a Komkov, Alexander Yu $u Department of Genomics of Adaptive Immunity, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, 117997 Moscow, Russia. Laboratory of Cytogenetics and Molecular Genetics, Dmitry Rogachev National Medical Research Center of Pediatric Hematology, Oncology and Immunology, 117198 Moscow, Russia.
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$a Chudakov, Dmitriy M $u Department of Genomics of Adaptive Immunity, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, 117997 Moscow, Russia. Department of Molecular Technologies, Pirogov Russian National Research Medical University, 117997 Moscow, Russia. Center for Data-Intensive Biomedicine and Biotechnology, Skoltech, 121205 Moscow, Russia. Central European Institute of Technology, Masaryk University, 62500 Brno, Czech Republic.
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$a Mamedov, Ilgar Z $u Department of Molecular Technologies, Pirogov Russian National Research Medical University, 117997 Moscow, Russia. Department of Genomics of Adaptive Immunity, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, 117997 Moscow, Russia.
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$a Mora, Thierry $u Laboratoire de Physique Statistique, CNRS, Sorbonne Université, Université Paris-Diderot, École Normale Supérieure (PSL), 75005 Paris, France; tmora@lps.ens.fr awalczak@lpt.ens.fr lebedev_yb@ibch.ru.
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$a Walczak, Aleksandra M $u Laboratoire de Physique Théorique, CNRS, Sorbonne Université, École Normale Supérieure (PSL), 75005 Paris, France; tmora@lps.ens.fr awalczak@lpt.ens.fr lebedev_yb@ibch.ru.
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$a Lebedev, Yuri B $u Department of Genomics of Adaptive Immunity, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, 117997 Moscow, Russia; tmora@lps.ens.fr awalczak@lpt.ens.fr lebedev_yb@ibch.ru. Biological Faculty, Moscow State University, 119991 Moscow, Russia.
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