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

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 lo...

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Vydané v:Proceedings of the National Academy of Sciences - PNAS Ročník 115; číslo 50; s. 12704
Hlavní autori: Pogorelyy, Mikhail V, Minervina, Anastasia A, Touzel, Maximilian Puelma, Sycheva, Anastasiia L, Komech, Ekaterina A, Kovalenko, Elena I, Karganova, Galina G, Egorov, Evgeniy S, Komkov, Alexander Yu, Chudakov, Dmitriy M, Mamedov, Ilgar Z, Mora, Thierry, Walczak, Aleksandra M, Lebedev, Yuri B
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: United States 11.12.2018
Predmet:
Antigens, Viral - immunology
Humans
Immunization - methods
Receptors, Antigen, T-Cell - immunology
T-Lymphocytes - immunology
Tissue Donors
Twins, Monozygotic
Vaccination - methods
Yellow Fever Vaccine - immunology
twins
RepSeq
T cell receptor
high-throughput sequencing
vaccination
ISSN:1091-6490, 1091-6490
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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.
AbstractList 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.
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.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.
Author Touzel, Maximilian Puelma
Mamedov, Ilgar Z
Egorov, Evgeniy S
Chudakov, Dmitriy M
Komkov, Alexander Yu
Walczak, Aleksandra M
Minervina, Anastasia A
Pogorelyy, Mikhail V
Sycheva, Anastasiia L
Kovalenko, Elena I
Karganova, Galina G
Mora, Thierry
Komech, Ekaterina A
Lebedev, Yuri B
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  givenname: Anastasia A
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  fullname: Minervina, Anastasia A
  organization: Department of Genomics of Adaptive Immunity, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, 117997 Moscow, Russia
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  givenname: Maximilian Puelma
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  givenname: Anastasiia L
  surname: Sycheva
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  organization: Department of Genomics of Adaptive Immunity, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, 117997 Moscow, Russia
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  organization: Department of Immunology, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, 117997 Moscow, Russia
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  givenname: Galina G
  surname: Karganova
  fullname: Karganova, Galina G
  organization: Department of Virology, Sechenov First Moscow State Medical University, 119146 Moscow, Russia
– sequence: 8
  givenname: Evgeniy S
  surname: Egorov
  fullname: Egorov, Evgeniy S
  organization: Department of Molecular Technologies, Pirogov Russian National Research Medical University, 117997 Moscow, Russia
– sequence: 9
  givenname: Alexander Yu
  surname: Komkov
  fullname: Komkov, Alexander Yu
  organization: Laboratory of Cytogenetics and Molecular Genetics, Dmitry Rogachev National Medical Research Center of Pediatric Hematology, Oncology and Immunology, 117198 Moscow, Russia
– sequence: 10
  givenname: Dmitriy M
  surname: Chudakov
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  organization: Central European Institute of Technology, Masaryk University, 62500 Brno, Czech Republic
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  givenname: Ilgar Z
  surname: Mamedov
  fullname: Mamedov, Ilgar Z
  organization: Department of Genomics of Adaptive Immunity, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, 117997 Moscow, Russia
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  givenname: Thierry
  surname: Mora
  fullname: Mora, Thierry
  email: tmora@lps.ens.fr, awalczak@lpt.ens.fr, lebedev_yb@ibch.ru
  organization: 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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  givenname: Aleksandra M
  surname: Walczak
  fullname: Walczak, Aleksandra M
  email: tmora@lps.ens.fr, awalczak@lpt.ens.fr, lebedev_yb@ibch.ru
  organization: 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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  surname: Lebedev
  fullname: Lebedev, Yuri B
  email: tmora@lps.ens.fr, awalczak@lpt.ens.fr, lebedev_yb@ibch.ru
  organization: Biological Faculty, Moscow State University, 119991 Moscow, Russia
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Keywords twins
RepSeq
T cell receptor
high-throughput sequencing
vaccination
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SubjectTerms Antigens, Viral - immunology
Humans
Immunization - methods
Receptors, Antigen, T-Cell - immunology
T-Lymphocytes - immunology
Tissue Donors
Twins, Monozygotic
Vaccination - methods
Yellow Fever Vaccine - immunology
Title Precise tracking of vaccine-responding T cell clones reveals convergent and personalized response in identical twins
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