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.

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.

Common approaches to gene signature discovery in single cell RNA-sequencing (scRNA-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 (scHPF), a Bayesian factorization method that adapts Hierarchical Poisson Factorization [1] for de novo discovery of both continuous and discrete expression patterns from scRNA-seq. scHPF does not require prior normalization and captures statistical properties of single cell data better than other methods in benchmark datasets. Applied to scRNA-seq of the core and margin of a high-grade glioma, scHPF uncovers marked differences in the abundance of glioma subpopulations across tumor regions and subtle, regionally-associated expression biases within glioma subpopulations. scHFP revealed an expression signature that was spatially biased towards the glioma-infiltrated margins and associated with inferior survival in glioblastoma.

HDAC inhibitor Spiruchostatin A was synthesized via a route that differs significantly from previously reported routes. The key step involves a latent thioester that initiates a chemoselective transformation similar to native chemical ligation to form the macrocyclic alanine-cysteine amide bond. The easily prepared latent thioester--the first such moiety reported in enantiomerically pure form--is designed with a pendant carboxylic acid to serve as a solid-phase linker for the synthesis of cyclic, cysteine-containing, peptidic materials.

Core components of the secretory pathway have largely been identified and studied in single cell systems such as the budding yeast S. cerevisiae or in mammalian tissue culture. These studies provide details on the molecular functions of the secretory machinery; they fail, however, to provide insight into the role of these proteins in the context of specialized organs of higher eukaryotes. Here, we identify and characterize the first loss-of-function mutations in a KDEL receptor gene from higher eukaryotes. Transcripts from the Drosophila KDEL receptor gene KdelR – formerly known as dmErd2 – are provided maternally and, at later stages, are at elevated levels in several embryonic cell types, including the salivary gland secretory cells, the fat body and the epidermis. We show that, unlike Saccharomyces cerevisiae Erd2 mutants, which are viable, KdelR mutations are early larval lethal, with homozygous mutant animals dying as first instar larvae. KdelR mutants have larval cuticle defects similar to those observed with loss-of-function mutations in other core secretory pathway genes and with mutations in CrebA, which encodes a bZip transcription factor that coordinately upregulates secretory pathway component genes in specialized secretory cell types. Using the salivary gland, we demonstrate a requirement for KdelR in maintaining the ER pool of a subset of soluble resident ER proteins. These studies underscore the utility of the Drosophila salivary gland as a unique system for studying the molecular machinery of the secretory pathway in vivo in a complex eukaryote.