Human T cells coordinate adaptive immunity in diverse anatomic compartments through production of cytokines and effector molecules, but it is unclear how tissue site influences T cell persistence and function. Here, we use single cell RNA-sequencing (scRNA-seq) to define the heterogeneity of human T cells isolated from lungs, lymph nodes, bone marrow and blood, and their functional responses following stimulation. Through analysis of >50,000 resting and activated T cells, we reveal tissue T cell signatures in mucosal and lymphoid sites, and lineage-specific activation states across all sites including distinct effector states for CD8+ T cells and an interferon-response state for CD4+ T cells. Comparing scRNA-seq profiles of tumor-associated T cells to our dataset reveals predominant activated CD8+ compared to CD4+ T cell states within multiple tumor types. Our results therefore establish a high dimensional reference map of human T cell activation in health for analyzing T cells in disease.

Background: Smooth muscle cells (SMC) play significant roles in atherosclerosis via phenotypic switching, a pathological process in which SMC dedifferentiation, migration and transdifferentiation into other cell types. Yet, how SMC contribute to pathophysiology of atherosclerosis remains elusive. Methods: To reveal the trajectories of SMC transdifferentiation during atherosclerosis and to identify molecular targets for disease therapy, we combined SMC fate mapping and single-cell RNA sequencing of both mouse and human atherosclerotic plaques. We also performed cell biology experiments on isolated SMC-derived cells, conducted integrative human genomics, and employed pharmacological studies targeting SMC-derived cells both in vivo and in vitro . Results: We found that SMC transitioned to an intermediate cell state during atherosclerosis, which was also found in human atherosclerotic plaques of carotid and coronary arteries. SMC-derived intermediate cells, termed "SEM" cells, were multipotent and could differentiate into macrophage-like and fibrochondrocyte-like cells, as well as return towards SMC phenotype. Retinoic acid (RA) signaling was identified as a regulator of SMC to SEM cell transition and RA signaling was dysregulated in symptomatic human atherosclerosis. Human genomics revealed enrichment of genome wide association study (GWAS) signals for coronary artery disease (CAD) in RA signaling target gene loci and correlation between CAD risk alleles and repressed expression of these genes. Activation of RA signaling by all-trans retinoic acid (ATRA), an anti-cancer drug for acute promyelocytic leukemia, blocked SMC transition to SEM cells, reduced atherosclerotic burden and promoted fibrous cap stability. Conclusions: Integration of cell-specific fate mapping, single-cell genomics and human genetics adds novel insights into the complexity of SMC biology and reveals regulatory pathways for therapeutic targeting of SMC transitions in atherosclerotic cardiovascular disease.

BackgroundDespite extensive molecular characterization, we lack a comprehensive understanding of lineage identity, differentiation, and proliferation in high-grade gliomas (HGGs).MethodsWe sampled the cellular milieu of HGGs by profiling dissociated human surgical specimens with a high-density microwell system for massively parallel single-cell RNA-Seq. We analyzed the resulting profiles to identify subpopulations of both HGG and microenvironmental cells and applied graph-based methods to infer structural features of the malignantly transformed populations.ResultsWhile HGG cells can resemble glia or even immature neurons and form branched lineage structures, mesenchymal transformation results in unstructured populations. Glioma cells in a subset of mesenchymal tumors lose their neural lineage identity, express inflammatory genes, and co-exist with marked myeloid infiltration, reminiscent of molecular interactions between glioma and immune cells established in animal models. Additionally, we discovered a tight coupling between lineage resemblance and proliferation among malignantly transformed cells. Glioma cells that resemble oligodendrocyte progenitors, which proliferate in the brain, are often found in the cell cycle. Conversely, glioma cells that resemble astrocytes, neuroblasts, and oligodendrocytes, which are non-proliferative in the brain, are generally non-cycling in tumors.ConclusionsThese studies reveal a relationship between cellular identity and proliferation in HGG and distinct population structures that reflects the extent of neural and non-neural lineage resemblance among malignantly transformed cells.Electronic supplementary materialThe online version of this article (10.1186/s13073-018-0567-9) contains supplementary material, which is available to authorized users.

Tissue resident memory T cells (TRM) maintain immunity in diverse sites as determined in mouse models, while their establishment and role in human tissues has been difficult to assess. Here, we investigated human lung TRM generation, maintenance and function in airway samples obtained longitudinally from HLA-disparate lung transplant recipients, where donor and recipient T cells could be localized and tracked over time. Donor T cells persist specifically in the lungs (and not blood) of transplant recipients and express high levels of TRM signature markers including CD69, CD103, and CD49a, while lung-infiltrating recipient T cells gradually acquire TRM phenotypes over months in vivo. Single cell transcriptome profiling of airway T cells reveals that donor T cells comprise two TRM-like subsets with varying levels of expression of TRM-associated genes while recipient T cells comprised non-TRM and similar TRM-like subpopulations, suggesting de novo TRM generation. Transplant recipients exhibiting higher frequencies of persisting donor TRM experienced fewer adverse clinical events such as primary graft dysfunction and acute cellular rejection compared to recipients with low donor TRM persistence, suggesting that monitoring TRM dynamics could be clinically informative. Together, our results provide novel spatial and temporal insights into how human TRM develop, function, persist, and impact tissue integrity within the complexities of lung transplantation.

Common approaches to gene signature discovery in single‐cell RNA ‐sequencing (sc RNA ‐seq) depend upon predefined structures like clusters or pseudo‐temporal order, require prior normalization, or do not account for the sparsity of single‐cell data. We present single‐cell hierarchical Poisson factorization (sc HPF ), a Bayesian factorization method that adapts hierarchical Poisson factorization (Gopalan et al , 2015 , Proceedings of the 31st Conference on Uncertainty in Artificial Intelligence , 326) for de novo discovery of both continuous and discrete expression patterns from sc RNA ‐seq. sc HPF does not require prior normalization and captures statistical properties of single‐cell data better than other methods in benchmark datasets. Applied to sc RNA ‐seq of the core and margin of a high‐grade glioma, sc HPF uncovers marked differences in the abundance of glioma subpopulations across tumor regions and regionally associated expression biases within glioma subpopulations. sc HFP revealed an expression signature that was spatially biased toward the glioma‐infiltrated margins and associated with inferior survival in glioblastoma.