Summary Non-lymphoid tissues (NLTs) harbor a pool of adaptive immune cells with largely unexplored phenotype and development. We used single-cell RNA-seq to characterize 35,000 CD4 + regulatory (Treg) and memory (Tmem) T cells in mouse skin and colon, their respective draining lymph nodes (LNs) and spleen. In these tissues, we identified Treg cell subpopulations with distinct degrees of NLT phenotype. Subpopulation pseudotime ordering and gene kinetics were consistent in recruitment to skin and colon, yet the initial NLT-priming in LNs and the final stages of NLT functional adaptation reflected tissue-specific differences. Predicted kinetics were recapitulated using an in vivo melanoma-induction model, validating key regulators and receptors. Finally, we profiled human blood and NLT Treg and Tmem cells, and identified cross-mammalian conserved tissue signatures. In summary, we describe the relationship between Treg cell heterogeneity and recruitment to NLTs through the combined use of computational prediction and in vivo validation.

Innate lymphoid cells (ILCs) functionally resemble T lymphocytes in cytotoxicity and cytokine production but lack antigen-specific receptors, and they are important regulators of immune responses and tissue homeostasis. ILCs are generated from common lymphoid progenitors, which are subsequently committed to innate lymphoid lineages in the α-lymphoid progenitor, early innate lymphoid progenitor, common helper innate lymphoid progenitor and innate lymphoid cell progenitor compartments. ILCs consist of conventional natural killer cells and helper-like cells (ILC1, ILC2 and ILC3). Despite recent advances, the cellular heterogeneity, developmental trajectory and signalling dependence of ILC progenitors are not fully understood. Here, using single-cell RNA-sequencing (scRNA-seq) of mouse bone marrow progenitors, we reveal ILC precursor subsets, delineate distinct ILC development stages and pathways, and report that high expression of programmed death 1 (PD-1) marked a committed ILC progenitor that was essentially identical to an innate lymphoid cell progenitor. Our data defined PD-1IL-25R as an early checkpoint in ILC2 development, which was abolished by deficiency in the zinc-finger protein Bcl11b but restored by IL-25R overexpression. Similar to T lymphocytes, PD-1 was upregulated on activated ILCs. Administration of a PD-1 antibody depleted PD-1 ILCs and reduced cytokine levels in an influenza infection model in mice, and blocked papain-induced acute lung inflammation. These results provide a perspective for exploring PD-1 and its ligand (PD-L1) in immunotherapy, and allow effective manipulation of the immune system for disease prevention and therapy.

bThere are nearly 50 forkhead (FOX) transcription factors encoded in the human genome and, due to sharing a common DNA binding domain, they are all thought to bind to similar DNA sequences. It is therefore unclear how these transcription factors are targeted to specific chromatin regions to elicit specific biological effects. Here, we used chromatin immunoprecipitation followed by sequencing (ChIP-seq) to investigate the genome-wide chromatin binding mechanisms used by the forkhead transcription factor FOXM1. In keeping with its previous association with cell cycle control, we demonstrate that FOXM1 binds and regulates a group of genes which are mainly involved in controlling late cell cycle events in the G 2 and M phases. However, rather than being recruited through canonical RYAAAYA forkhead binding motifs, FOXM1 binding is directed via CHR (cell cycle genes homology region) elements. FOXM1 binds these elements through protein-protein interactions with the MMB transcriptional activator complex. Thus, we have uncovered a novel and unexpected mode of chromatin binding of a FOX transcription factor that allows it to specifically control cell cycle-dependent gene expression. There are nearly 50 different forkhead transcription factors encoded in mammalian genomes, and these proteins all contain the conserved forkhead DNA binding domain (reviewed in references 1 and 2). Forkhead transcription factors are involved in controlling a wide range of biological processes and are aberrantly expressed or regulated in disease states, including cancer (reviewed in reference 2). However, due to sharing a common DNA binding domain, forkhead transcription factors are generally believed to bind to variations of the RYAAAYA motif. Hence, it is unclear how individual forkhead proteins are specifically recruited to the regulatory regions of different cohorts of target genes to control defined biological responses. One key process which is controlled by forkhead transcription factors is the cell cycle and, in particular, the G 2 -M transition. The initial links to G 2 -M control were made with the Saccharomyces cerevisiae forkhead protein Fkh2, which controls the temporal expression of a cluster of genes at this phase of the cell cycle (reviewed in reference 3). More recently, members of the FOXO and FOXM classes of forkhead transcription factors have been linked with controlling the same process in mammalian cells (4-6). In both cases, forkhead transcription factors coordinate the integration of signals from the cell cycle regulatory machinery to transcriptional outputs. This is exemplified by the links to the cell cycle regulated Polo-like kinase PLK1, which is recruited to cell cycle-regulated promoters through promoter elements bound by the forkhead transcription factors FOXM1 and Fkh2, albeit indirectly in the case of Fkh2 (7,8).In mammalian cells, the transcriptional control of a cluster of genes at the G 2 -M transition, is coordinated through promoter elements which typically contain CHR (cell cycle genes homology region) and...

Summary As the first line of defence against pathogens, cells mount an innate immune response, which is highly variable from cell to cell. The response must be potent yet carefully controlled to avoid self-damage. How these constraints have shaped the evolution of innate immunity remains poorly understood. Here, we characterise this programme’s transcriptional divergence between species and expression variability across cells. Using bulk and single-cell transcriptomics in fibroblasts and mononuclear phagocytes from different species, challenged with immune stimuli, we reveal a striking architecture of the innate immune response. Transcriptionally diverging genes, including cytokines and chemokines, vary across cells and have distinct promoter structures. Conversely, genes involved in response regulation, such as transcription factors and kinases, are conserved between species and display low cell-to-cell expression variability. We suggest that this unique expression pattern, observed across species and conditions, has evolved as a mechanism for fine-tuned regulation, achieving an effective but balanced response.

The metabolome includes not just known but also unknown metabolites; however, metabolite annotation remains the bottleneck in untargeted metabolomics. Ion mobilitymass spectrometry (IM-MS) has emerged as a promising technology by providing multi-dimensional characterizations of metabolites. Here, we curate an ion mobility CCS atlas, namely AllCCS, and develop an integrated strategy for metabolite annotation using known or unknown chemical structures. The AllCCS atlas covers vast chemical structures with >5000 experimental CCS records and~12 million calculated CCS values for >1.6 million small molecules. We demonstrate the high accuracy and wide applicability of AllCCS with medium relative errors of 0.5-2% for a broad spectrum of small molecules. AllCCS combined with in silico MS/MS spectra facilitates multi-dimensional match and substantially improves the accuracy and coverage of both known and unknown metabolite annotation from biological samples. Together, AllCCS is a versatile resource that enables confident metabolite annotation, revealing comprehensive chemical and metabolic insights towards biological processes.

Highlights d scRNA-seq reveals the complex interplay among cells within the evolving tumor d T cells recruited from lymph nodes are activated and clonally expand in situ d Temporally regulated, functionally distinct stromal populations exist d Cross-compartment interactions can be identified using the CellPhoneDB database

Formation and segregation of cell lineages forming the heart have been studied extensively but the underlying gene regulatory networks and epigenetic changes driving cell fate transitions during early cardiogenesis are still only partially understood. Here, we comprehensively characterize mouse cardiac progenitor cells (CPCs) marked by Nkx2-5 and Isl1 expression from E7.5 to E9.5 using single-cell RNA sequencing and transposase-accessible chromatin profiling (ATAC-seq). By leveraging on cell-to-cell transcriptome and chromatin accessibility heterogeneity, we identify different previously unknown cardiac subpopulations. Reconstruction of developmental trajectories reveal that multipotent Isl1+ CPC pass through an attractor state before separating into different developmental branches, whereas extended expression of Nkx2-5 commits CPC to an unidirectional cardiomyocyte fate. Furthermore, we show that CPC fate transitions are associated with distinct open chromatin states critically depending on Isl1 and Nkx2-5. Our data provide a model of transcriptional and epigenetic regulations during cardiac progenitor cell fate decisions at single-cell resolution.

Summary T helper type 2 (Th2) cells are important regulators of mammalian adaptive immunity and have relevance for infection, autoimmunity, and tumor immunology. Using a newly developed, genome-wide retroviral CRISPR knockout (KO) library, combined with RNA-seq, ATAC-seq, and ChIP-seq, we have dissected the regulatory circuitry governing activation and differentiation of these cells. Our experiments distinguish cell activation versus differentiation in a quantitative framework. We demonstrate that these two processes are tightly coupled and are jointly controlled by many transcription factors, metabolic genes, and cytokine/receptor pairs. There are only a small number of genes regulating differentiation without any role in activation. By combining biochemical and genetic data, we provide an atlas for Th2 differentiation, validating known regulators and identifying factors, such as Pparg and Bhlhe40 , as part of the core regulatory network governing Th2 helper cell fates.