Repertoire-based mapping and time-tracking of T helper cell subsets in scRNA-Seq
IntroductionThe functional programs of CD4+ T helper (Th) cell clones play a central role in shaping immune responses to different challenges. While advances in single-cell RNA sequencing (scRNA-Seq) have significantly improved our understanding of the diversity of Th cells, the relationship between...
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Frontiers Media S.A.
2025-04-01
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| Series: | Frontiers in Immunology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2025.1536302/full |
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| author | Daniil K. Lukyanov Daniil K. Lukyanov Valeriia V. Kriukova Kristin Ladell Irina A. Shagina Irina A. Shagina Dmitry B. Staroverov Dmitry B. Staroverov Bella E. Minasian Anna S. Fedosova Pavel Shelyakin Oleg N. Suchalko Alexander Y. Komkov Konstantin A. Blagodatskikh Kelly L. Miners Olga V. Britanova Olga V. Britanova Olga V. Britanova Andre Franke David A. Price David A. Price Dmitry M. Chudakov Dmitry M. Chudakov Dmitry M. Chudakov Dmitry M. Chudakov Dmitry M. Chudakov |
| author_facet | Daniil K. Lukyanov Daniil K. Lukyanov Valeriia V. Kriukova Kristin Ladell Irina A. Shagina Irina A. Shagina Dmitry B. Staroverov Dmitry B. Staroverov Bella E. Minasian Anna S. Fedosova Pavel Shelyakin Oleg N. Suchalko Alexander Y. Komkov Konstantin A. Blagodatskikh Kelly L. Miners Olga V. Britanova Olga V. Britanova Olga V. Britanova Andre Franke David A. Price David A. Price Dmitry M. Chudakov Dmitry M. Chudakov Dmitry M. Chudakov Dmitry M. Chudakov Dmitry M. Chudakov |
| author_sort | Daniil K. Lukyanov |
| collection | DOAJ |
| description | IntroductionThe functional programs of CD4+ T helper (Th) cell clones play a central role in shaping immune responses to different challenges. While advances in single-cell RNA sequencing (scRNA-Seq) have significantly improved our understanding of the diversity of Th cells, the relationship between scRNA-Seq clusters and the traditionally characterized Th subsets remains ambiguous.MethodsIn this study, we introduce TCR-Track, a method leveraging immune repertoire data to map phenotypically sorted Th subsets onto scRNA-Seq profiles.Results and discussionThis approach accurately positions the Th1, Th1-17, Th17, Th22, Th2a, Th2, T follicular helper (Tfh), and regulatory T-cell (Treg) subsets, outperforming mapping based on CITE-Seq. Remarkably, the mapping is tightly focused on specific scRNA-Seq clusters, despite 4-year interval between subset sorting and the effector CD4+ scRNA-Seq experiment. These findings highlight the intrinsic program stability of Th clones circulating in peripheral blood. Repertoire overlap analysis at the scRNA-Seq level confirms that the circulating Th1, Th2, Th2a, Th17, Th22, and Treg subsets are clonally independent. However, a significant clonal overlap between the Th1 and cytotoxic CD4+ T-cell clusters suggests that cytotoxic CD4+ T cells differentiate from Th1 clones. In addition, this study resolves a longstanding ambiguity: we demonstrate that, while CCR10+ Th cells align with a specific Th22 scRNA-Seq cluster, CCR10−CCR6+CXCR3−CCR4+ cells, typically classified as Th17, represent a mixture of bona fide Th17 cells and clonally unrelated CCR10low Th22 cells. The clear distinction between the Th17 and Th22 subsets should influence the development of vaccine- and T-cell-based therapies. Furthermore, we show that severe acute SARS-CoV-2 infection induces systemic type 1 interferon (IFN) activation of naive Th cells. An increased proportion of effector IFN-induced Th cells is associated with a moderate course of the disease but remains low in critical COVID-19 cases. Using integrated scRNA-Seq, TCR-Track, and CITE-Seq data from 122 donors, we provide a comprehensive Th scRNA-Seq reference that should facilitate further investigation of Th subsets in fundamental and clinical studies. |
| format | Article |
| id | doaj-art-a2570c81a9a9422faeb85902f7785ab9 |
| institution | DOAJ |
| issn | 1664-3224 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Immunology |
| spelling | doaj-art-a2570c81a9a9422faeb85902f7785ab92025-08-20T03:05:43ZengFrontiers Media S.A.Frontiers in Immunology1664-32242025-04-011610.3389/fimmu.2025.15363021536302Repertoire-based mapping and time-tracking of T helper cell subsets in scRNA-SeqDaniil K. Lukyanov0Daniil K. Lukyanov1Valeriia V. Kriukova2Kristin Ladell3Irina A. Shagina4Irina A. Shagina5Dmitry B. Staroverov6Dmitry B. Staroverov7Bella E. Minasian8Anna S. Fedosova9Pavel Shelyakin10Oleg N. Suchalko11Alexander Y. Komkov12Konstantin A. Blagodatskikh13Kelly L. Miners14Olga V. Britanova15Olga V. Britanova16Olga V. Britanova17Andre Franke18David A. Price19David A. Price20Dmitry M. Chudakov21Dmitry M. Chudakov22Dmitry M. Chudakov23Dmitry M. Chudakov24Dmitry M. Chudakov25Center for Molecular and Cellular Biology, Moscow, RussiaGenomics of Adaptive Immunity Department, Institute of Bioorganic Chemistry, Moscow, RussiaInstitute of Clinical Molecular Biology, Kiel University, Kiel, GermanyDivision of Infection and Immunity, Cardiff University School of Medicine, University Hospital of Wales, Cardiff, United KingdomGenomics of Adaptive Immunity Department, Institute of Bioorganic Chemistry, Moscow, RussiaInstitute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, RussiaGenomics of Adaptive Immunity Department, Institute of Bioorganic Chemistry, Moscow, RussiaInstitute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, RussiaAbu Dhabi Stem Cell Center, Al Muntazah, United Arab EmiratesAbu Dhabi Stem Cell Center, Al Muntazah, United Arab EmiratesAbu Dhabi Stem Cell Center, Al Muntazah, United Arab EmiratesAbu Dhabi Stem Cell Center, Al Muntazah, United Arab EmiratesAbu Dhabi Stem Cell Center, Al Muntazah, United Arab EmiratesInstitute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, RussiaDivision of Infection and Immunity, Cardiff University School of Medicine, University Hospital of Wales, Cardiff, United KingdomGenomics of Adaptive Immunity Department, Institute of Bioorganic Chemistry, Moscow, RussiaInstitute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, RussiaAbu Dhabi Stem Cell Center, Al Muntazah, United Arab EmiratesInstitute of Clinical Molecular Biology, Kiel University, Kiel, GermanyDivision of Infection and Immunity, Cardiff University School of Medicine, University Hospital of Wales, Cardiff, United KingdomSystems Immunity Research Institute, Cardiff University School of Medicine, University Hospital of Wales, Cardiff, United KingdomCenter for Molecular and Cellular Biology, Moscow, RussiaGenomics of Adaptive Immunity Department, Institute of Bioorganic Chemistry, Moscow, RussiaInstitute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, RussiaAbu Dhabi Stem Cell Center, Al Muntazah, United Arab EmiratesDepartment of Molecular Medicine, Central European Institute of Technology, Brno, CzechiaIntroductionThe functional programs of CD4+ T helper (Th) cell clones play a central role in shaping immune responses to different challenges. While advances in single-cell RNA sequencing (scRNA-Seq) have significantly improved our understanding of the diversity of Th cells, the relationship between scRNA-Seq clusters and the traditionally characterized Th subsets remains ambiguous.MethodsIn this study, we introduce TCR-Track, a method leveraging immune repertoire data to map phenotypically sorted Th subsets onto scRNA-Seq profiles.Results and discussionThis approach accurately positions the Th1, Th1-17, Th17, Th22, Th2a, Th2, T follicular helper (Tfh), and regulatory T-cell (Treg) subsets, outperforming mapping based on CITE-Seq. Remarkably, the mapping is tightly focused on specific scRNA-Seq clusters, despite 4-year interval between subset sorting and the effector CD4+ scRNA-Seq experiment. These findings highlight the intrinsic program stability of Th clones circulating in peripheral blood. Repertoire overlap analysis at the scRNA-Seq level confirms that the circulating Th1, Th2, Th2a, Th17, Th22, and Treg subsets are clonally independent. However, a significant clonal overlap between the Th1 and cytotoxic CD4+ T-cell clusters suggests that cytotoxic CD4+ T cells differentiate from Th1 clones. In addition, this study resolves a longstanding ambiguity: we demonstrate that, while CCR10+ Th cells align with a specific Th22 scRNA-Seq cluster, CCR10−CCR6+CXCR3−CCR4+ cells, typically classified as Th17, represent a mixture of bona fide Th17 cells and clonally unrelated CCR10low Th22 cells. The clear distinction between the Th17 and Th22 subsets should influence the development of vaccine- and T-cell-based therapies. Furthermore, we show that severe acute SARS-CoV-2 infection induces systemic type 1 interferon (IFN) activation of naive Th cells. An increased proportion of effector IFN-induced Th cells is associated with a moderate course of the disease but remains low in critical COVID-19 cases. Using integrated scRNA-Seq, TCR-Track, and CITE-Seq data from 122 donors, we provide a comprehensive Th scRNA-Seq reference that should facilitate further investigation of Th subsets in fundamental and clinical studies.https://www.frontiersin.org/articles/10.3389/fimmu.2025.1536302/fullhelper T cell subsetsscRNA-SeqscTCR-seqimmune repertoiresT cell memoryTh22 |
| spellingShingle | Daniil K. Lukyanov Daniil K. Lukyanov Valeriia V. Kriukova Kristin Ladell Irina A. Shagina Irina A. Shagina Dmitry B. Staroverov Dmitry B. Staroverov Bella E. Minasian Anna S. Fedosova Pavel Shelyakin Oleg N. Suchalko Alexander Y. Komkov Konstantin A. Blagodatskikh Kelly L. Miners Olga V. Britanova Olga V. Britanova Olga V. Britanova Andre Franke David A. Price David A. Price Dmitry M. Chudakov Dmitry M. Chudakov Dmitry M. Chudakov Dmitry M. Chudakov Dmitry M. Chudakov Repertoire-based mapping and time-tracking of T helper cell subsets in scRNA-Seq Frontiers in Immunology helper T cell subsets scRNA-Seq scTCR-seq immune repertoires T cell memory Th22 |
| title | Repertoire-based mapping and time-tracking of T helper cell subsets in scRNA-Seq |
| title_full | Repertoire-based mapping and time-tracking of T helper cell subsets in scRNA-Seq |
| title_fullStr | Repertoire-based mapping and time-tracking of T helper cell subsets in scRNA-Seq |
| title_full_unstemmed | Repertoire-based mapping and time-tracking of T helper cell subsets in scRNA-Seq |
| title_short | Repertoire-based mapping and time-tracking of T helper cell subsets in scRNA-Seq |
| title_sort | repertoire based mapping and time tracking of t helper cell subsets in scrna seq |
| topic | helper T cell subsets scRNA-Seq scTCR-seq immune repertoires T cell memory Th22 |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2025.1536302/full |
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