Repertoire-based mapping and time-tracking of helper T cell subsets in scRNA-Seq

The functional programs selected by CD4+ helper (Th) T cell clones fundamentally determine the architecture of the immune response to distinct challenges. Advances in scRNA-Seq have enhanced our understanding of the diversity of these programs, yet the correspondence between scRNA-Seq clusters and previously characterized Th subsets remains unclear. In this study, we use immune repertoires to position phenotypically sorted Th subsets within scRNA-Seq data from three healthy donors. This approach, termed TCR-Track, and accurately maps Th1, Th1-17, Th17, Th22, Th2a, Th2, Tfh, and Treg subsets, outperforming CITE-Seq-based mapping. Remarkably, the mapping is tightly focused on specific scRNA-Seq clusters despite a four-year interval between the sorting of subsets and the effector CD4+ scRNA-Seq experiment. Thus, while transient T cell plasticity is commonly observed in functionally active T cell populations, TCR-Track reveals high intrinsic program sustainability of Th clones circulating in peripheral blood. Repertoire overlap analysis at the scRNA-Seq level confirms that circulating Th1, Th2, Th2a, Th17, Th22, and Treg subsets are clonally independent. However, a prominent clonal overlap between corresponding clusters indicates that cytotoxic CD4+ T cells differentiate from Th1 clones. More specifically, we demonstrate that sorted CCR10+ Th cells correspond to a specific Th22 scRNA-Seq cluster, while CCR10-CCR6+CXCR3-CCR4+ cells, traditionally sorted as the Th17 subset, represent a mixture of bona fide Th17 and clonally unrelated CCR10low Th22 cells, which may have confounded investigators in previous studies. This clear distinction of Th17 and Th22 subsets should influence vaccine and T cell based therapies development. Additionally, we show that SARS-CoV-2 infection is associated with transient IFN type 1 activation of naive CD4+ T cells, and 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.