LGR5 expressing skin fibroblasts define a major cellular hub perturbed in scleroderma.

Systemic sclerosis (scleroderma, SSc) is an incurable autoimmune disease with high morbidity and mortality rates. Here, we conducted a population-scale single-cell genomic analysis of skin and blood samples of 56 healthy controls and 97 SSc patients at different stages of the disease. We found immune compartment dysfunction only in a specific subtype of diffuse SSc patients but global dysregulation of the stromal compartment, particularly in a previously undefined subset of LGR5+-scleroderma-associated fibroblasts (ScAFs). ScAFs are perturbed morphologically and molecularly in SSc patients. Single-cell multiome profiling of stromal cells revealed ScAF-specific markers, pathways, regulatory elements, and transcription factors underlining disease development. Systematic analysis of these molecular features with clinical metadata associates specific ScAF targets with disease pathogenesis and SSc clinical traits. Our high-resolution atlas of the sclerodermatous skin spectrum will enable a paradigm shift in the understanding of SSc disease and facilitate the development of biomarkers and therapeutic strategies.

Coupled scRNA-Seq and Intracellular Protein Activity Reveal an Immunosuppressive Role of TREM2 in Cancer.

Cell function and activity are regulated through integration of signaling, epigenetic, transcriptional, and metabolic pathways. Here, we introduce INs-seq, an integrated technology for massively parallel recording of single-cell RNA sequencing (scRNA-seq) and intracellular protein activity. We demonstrate the broad utility of INs-seq for discovering new immune subsets by profiling different intracellular signatures of immune signaling, transcription factor combinations, and metabolic activity. Comprehensive mapping of Arginase 1-expressing cells within tumor models, a metabolic immune signature of suppressive activity, discovers novel Arg1+ Trem2+ regulatory myeloid (Mreg) cells and identifies markers, metabolic activity, and pathways associated with these cells. Genetic ablation of Trem2 in mice inhibits accumulation of intra-tumoral Mreg cells, leading to a marked decrease in dysfunctional CD8+ T cells and reduced tumor growth. This study establishes INs-seq as a broadly applicable technology for elucidating integrated transcriptional and intra-cellular maps and identifies the molecular signature of myeloid suppressive cells in tumors.

Lipid-Associated Macrophages Control Metabolic Homeostasis in a Trem2-Dependent Manner.

Immune cells residing in white adipose tissue have been highlighted as important factors contributing to the pathogenesis of metabolic diseases, but the molecular regulators that drive adipose tissue immune cell remodeling during obesity remain largely unknown. Using index and transcriptional single-cell sorting, we comprehensively map all adipose tissue immune populations in both mice and humans during obesity. We describe a novel and conserved Trem2+ lipid-associated macrophage (LAM) subset and identify markers, spatial localization, origin, and functional pathways associated with these cells. Genetic ablation of Trem2 in mice globally inhibits the downstream molecular LAM program, leading to adipocyte hypertrophy as well as systemic hypercholesterolemia, body fat accumulation, and glucose intolerance. These findings identify Trem2 signaling as a major pathway by which macrophages respond to loss of tissue-level lipid homeostasis, highlighting Trem2 as a key sensor of metabolic pathologies across multiple tissues and a potential therapeutic target in metabolic diseases.

Dissecting Immune Circuits by Linking CRISPR-Pooled Screens with Single-Cell RNA-Seq.

In multicellular organisms, dedicated regulatory circuits control cell type diversity and responses. The crosstalk and redundancies within these circuits and substantial cellular heterogeneity pose a major research challenge. Here, we present CRISP-seq, an integrated method for massively parallel single-cell RNA sequencing (RNA-seq) and clustered regularly interspaced short palindromic repeats (CRISPR)-pooled screens. We show that profiling the genomic perturbation and transcriptome in the same cell enables us to simultaneously elucidate the function of multiple factors and their interactions. We applied CRISP-seq to probe regulatory circuits of innate immunity. By sampling tens of thousands of perturbed cells in vitro and in mice, we identified interactions and redundancies between developmental and signaling-dependent factors. These include opposing effects of Cebpb and Irf8 in regulating the monocyte/macrophage versus dendritic cell lineages and differential functions for Rela and Stat1/2 in monocyte versus dendritic cell responses to pathogens. This study establishes CRISP-seq as a broadly applicable, comprehensive, and unbiased approach for elucidating mammalian regulatory circuits.

Transcriptional Heterogeneity and Lineage Commitment in Myeloid Progenitors.

Within the bone marrow, stem cells differentiate and give rise to diverse blood cell types and functions. Currently, hematopoietic progenitors are defined using surface markers combined with functional assays that are not directly linked with in vivo differentiation potential or gene regulatory mechanisms. Here, we comprehensively map myeloid progenitor subpopulations by transcriptional sorting of single cells from the bone marrow. We describe multiple progenitor subgroups, showing unexpected transcriptional priming toward seven differentiation fates but no progenitors with a mixed state. Transcriptional differentiation is correlated with combinations of known and previously undefined transcription factors, suggesting that the process is tightly regulated. Histone maps and knockout assays are consistent with early transcriptional priming, while traditional transplantation experiments suggest that in vivo priming may still allow for plasticity given strong perturbations. These data establish a reference model and general framework for studying hematopoiesis at single-cell resolution.

The 'TranSeq' 3'-end sequencing method for high-throughput transcriptomics and gene space refinement in plant genomes.

High-throughput RNA sequencing has proven invaluable not only to explore gene expression but also for both gene prediction and genome annotation. However, RNA sequencing, carried out on tens or even hundreds of samples, requires easy and cost-effective sample preparation methods using minute RNA amounts. Here, we present TranSeq, a high-throughput 3'-end sequencing procedure that requires 10- to 20-fold fewer sequence reads than the current transcriptomics procedures. TranSeq significantly reduces costs and allows a greater increase in size of sample sets analyzed in a single experiment. Moreover, in comparison with other 3'-end sequencing methods reported to date, we demonstrate here the reliability and immediate applicability of TranSeq and show that it not only provides accurate transcriptome profiles but also produces precise expression measurements of specific gene family members possessing high sequence similarity. This is difficult to achieve in standard RNA-seq methods, in which sequence reads cover the entire transcript. Furthermore, mapping TranSeq reads to the reference tomato genome facilitated the annotation of new transcripts improving >45% of the existing gene models. Hence, we anticipate that using TranSeq will boost large-scale transcriptome assays and increase the spatial and temporal resolution of gene expression data, in both model and non-model plant species. Moreover, as already performed for tomato (ITAG3.0; www.solgenomics.net), we strongly advocate its integration into current and future genome annotations.

Each cell counts: Hematopoiesis and immunity research in the era of single cell genomics.

Hematopoiesis and immunity are mediated through complex interactions between multiple cell types and states. This complexity is currently addressed following a reductionist approach of characterizing cell types by a small number of cell surface molecular features and gross functions. While the introduction of global transcriptional profiling technologies enabled a more comprehensive view, heterogeneity within sampled populations remained unaddressed, obscuring the true picture of hematopoiesis and immune system function. A critical mass of technological advances in molecular biology and genomics has enabled genome-wide measurements of single cells - the fundamental unit of immunity. These new advances are expected to boost detection of less frequent cell types and fuzzy intermediate cell states, greatly expanding the resolution of current available classifications. This new era of single-cell genomics in immunology research holds great promise for further understanding of the mechanisms and circuits regulating hematopoiesis and immunity in both health and disease. In the near future, the accuracy of single-cell genomics will ultimately enable precise diagnostics and treatment of multiple hematopoietic and immune related diseases.

Distinct biological events generated by ECM proteolysis by two homologous collagenases.

It is well established that the expression profiles of multiple and possibly redundant matrix-remodeling proteases (e.g., collagenases) differ strongly in health, disease, and development. Although enzymatic redundancy might be inferred from their close similarity in structure, their in vivo activity can lead to extremely diverse tissue-remodeling outcomes. We observed that proteolysis of collagen-rich natural extracellular matrix (ECM), performed uniquely by individual homologous proteases, leads to distinct events that eventually affect overall ECM morphology, viscoelastic properties, and molecular composition. We revealed striking differences in the motility and signaling patterns, morphology, and gene-expression profiles of cells interacting with natural collagen-rich ECM degraded by different collagenases. Thus, in contrast to previous notions, matrix-remodeling systems are not redundant and give rise to precise ECM-cell crosstalk. Because ECM proteolysis is an abundant biochemical process that is critical for tissue homoeostasis, these results improve our fundamental understanding its complexity and its impact on cell behavior.

Chronic exposure to TGFß1 regulates myeloid cell inflammatory response in an IRF7-dependent manner.

Tissue microenvironment influences the function of resident and infiltrating myeloid-derived cells. In the central nervous system (CNS), resident microglia and freshly recruited infiltrating monocyte-derived macrophages (mo-MΦ) display distinct activities under pathological conditions, yet little is known about the microenvironment-derived molecular mechanism that regulates these differences. Here, we demonstrate that long exposure to transforming growth factor-ß1 (TGFß1) impaired the ability of myeloid cells to acquire a resolving anti-inflammatory phenotype. Using genome-wide expression analysis and chromatin immunoprecipitation followed by next-generation sequencing, we show that the capacity to undergo pro- to anti-inflammatory (M1-to-M2) phenotype switch is controlled by the transcription factor interferon regulatory factor 7 (IRF7) that is down-regulated by the TGFß1 pathway. RNAi-mediated perturbation of Irf7 inhibited the M1-to-M2 switch, while IFNß1 (an IRF7 pathway activator) restored it. In vivo induction of Irf7 expression in microglia, following spinal cord injury, reduced their pro-inflammatory activity. These results highlight the key role of tissue-specific environmental factors in determining the fate of resident myeloid-derived cells under both physiological and pathological conditions.

Modeling T cell temporal response to cancer immunotherapy rationalizes development of combinatorial treatment protocols.

Successful immunotherapy relies on triggering complex responses involving T cell dynamics in tumors and the periphery. Characterizing these responses remains challenging using static human single-cell atlases or mouse models. To address this, we developed a framework for in vivo tracking of tumor-specific CD8+ T cells over time and at single-cell resolution. Our tools facilitate the modeling of gene program dynamics in the tumor microenvironment (TME) and the tumor-draining lymph node (tdLN). Using this approach, we characterize two modes of anti-programmed cell death protein 1 (PD-1) activity, decoupling induced differentiation of tumor-specific activated precursor cells from conventional type 1 dendritic cell (cDC1)-dependent proliferation and recruitment to the TME. We demonstrate that combining anti-PD-1 therapy with anti-4-1BB agonist enhances the recruitment and proliferation of activated precursors, resulting in tumor control. These data suggest that effective response to anti-PD-1 therapy is dependent on sufficient influx of activated precursor CD8+ cells to the TME and highlight the importance of understanding system-level dynamics in optimizing immunotherapies.

XCR1+ type 1 conventional dendritic cells drive liver pathology in non-alcoholic steatohepatitis.

Non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH) are prevalent liver conditions that underlie the development of life-threatening cirrhosis, liver failure and liver cancer. Chronic necro-inflammation is a critical factor in development of NASH, yet the cellular and molecular mechanisms of immune dysregulation in this disease are poorly understood. Here, using single-cell transcriptomic analysis, we comprehensively profiled the immune composition of the mouse liver during NASH. We identified a significant pathology-associated increase in hepatic conventional dendritic cells (cDCs) and further defined their source as NASH-induced boost in cycling of cDC progenitors in the bone marrow. Analysis of blood and liver from patients on the NAFLD/NASH spectrum showed that type 1 cDCs (cDC1) were more abundant and activated in disease. Sequencing of physically interacting cDC-T cell pairs from liver-draining lymph nodes revealed that cDCs in NASH promote inflammatory T cell reprogramming, previously associated with NASH worsening. Finally, depletion of cDC1 in XCR1DTA mice or using anti-XCL1-blocking antibody attenuated liver pathology in NASH mouse models. Overall, our study provides a comprehensive characterization of cDC biology in NASH and identifies XCR1+ cDC1 as an important driver of liver pathology.

MARS-seq2.0: an experimental and analytical pipeline for indexed sorting combined with single-cell RNA sequencing.

Human tissues comprise trillions of cells that populate a complex space of molecular phenotypes and functions and that vary in abundance by 4-9 orders of magnitude. Relying solely on unbiased sampling to characterize cellular niches becomes infeasible, as the marginal utility of collecting more cells diminishes quickly. Furthermore, in many clinical samples, the relevant cell types are scarce and efficient processing is critical. We developed an integrated pipeline for index sorting and massively parallel single-cell RNA sequencing (MARS-seq2.0) that builds on our previously published MARS-seq approach. MARS-seq2.0 is based on >1 million cells sequenced with this pipeline and allows identification of unique cell types across different tissues and diseases, as well as unique model systems and organisms. Here, we present a detailed step-by-step procedure for applying the method. In the improved procedure, we combine sub-microliter reaction volumes, optimization of enzymatic mixtures and an enhanced analytical pipeline to substantially lower the cost, improve reproducibility and reduce well-to-well contamination. Data analysis combines multiple layers of quality assessment and error detection and correction, graphically presenting key statistics for library complexity, noise distribution and sequencing saturation. Importantly, our combined FACS and single-cell RNA sequencing (scRNA-seq) workflow enables intuitive approaches for depletion or enrichment of cell populations in a data-driven manner that is essential to efficient sampling of complex tissues. The experimental protocol, from cell sorting to a ready-to-sequence library, takes 2-3 d. Sequencing and processing the data through the analytical pipeline take another 1-2 d.

Deterministic Somatic Cell Reprogramming Involves Continuous Transcriptional Changes Governed by Myc and Epigenetic-Driven Modules.

The epigenetic dynamics of induced pluripotent stem cell (iPSC) reprogramming in correctly reprogrammed cells at high resolution and throughout the entire process remain largely undefined. Here, we characterize conversion of mouse fibroblasts into iPSCs using Gatad2a-Mbd3/NuRD-depleted and highly efficient reprogramming systems. Unbiased high-resolution profiling of dynamic changes in levels of gene expression, chromatin engagement, DNA accessibility, and DNA methylation were obtained. We identified two distinct and synergistic transcriptional modules that dominate successful reprogramming, which are associated with cell identity and biosynthetic genes. The pluripotency module is governed by dynamic alterations in epigenetic modifications to promoters and binding by Oct4, Sox2, and Klf4, but not Myc. Early DNA demethylation at certain enhancers prospectively marks cells fated to reprogram. Myc activity drives expression of the essential biosynthetic module and is associated with optimized changes in tRNA codon usage. Our functional validations highlight interweaved epigenetic- and Myc-governed essential reconfigurations that rapidly commission and propel deterministic reprogramming toward naive pluripotency.

Extracellular Matrix Proteolysis by MT1-MMP Contributes to Influenza-Related Tissue Damage and Mortality.

Mounting an effective immune response, while also protecting tissue integrity, is critical for host survival. We used a combined genomic and proteomic approach to investigate the role of extracellular matrix (ECM) proteolysis in achieving this balance in the lung during influenza virus infection. We identified the membrane-tethered matrix metalloprotease MT1-MMP as a prominent host-ECM-remodeling collagenase in influenza infection. Selective inhibition of MT1-MMP protected the tissue from infection-related structural and compositional tissue damage. MT1-MMP inhibition did not significantly alter the immune response or cytokine expression. The available flu therapeutic Oseltamivir did not prevent lung ECM damage and was less effective than anti-MT1-MMP in influenza virus Streptococcus pneumoniae coinfection paradigms. Combination therapy of Oseltamivir with anti-MT1-MMP showed a strong synergistic effect and resulted in complete recovery of infected mice. This study highlights the importance of tissue resilience in surviving infection and the potential of such host-pathogen therapy combinations for respiratory infections.

Stem cells. m6A mRNA methylation facilitates resolution of naïve pluripotency toward differentiation.

Naïve and primed pluripotent states retain distinct molecular properties, yet limited knowledge exists on how their state transitions are regulated. Here, we identify Mettl3, an N(6)-methyladenosine (m(6)A) transferase, as a regulator for terminating murine naïve pluripotency. Mettl3 knockout preimplantation epiblasts and naïve embryonic stem cells are depleted for m(6)A in mRNAs, yet are viable. However, they fail to adequately terminate their naïve state and, subsequently, undergo aberrant and restricted lineage priming at the postimplantation stage, which leads to early embryonic lethality. m(6)A predominantly and directly reduces mRNA stability, including that of key naïve pluripotency-promoting transcripts. This study highlights a critical role for an mRNA epigenetic modification in vivo and identifies regulatory modules that functionally influence naïve and primed pluripotency in an opposing manner.

Massively parallel single-cell RNA-seq for marker-free decomposition of tissues into cell types.

In multicellular organisms, biological function emerges when heterogeneous cell types form complex organs. Nevertheless, dissection of tissues into mixtures of cellular subpopulations is currently challenging. We introduce an automated massively parallel single-cell RNA sequencing (RNA-seq) approach for analyzing in vivo transcriptional states in thousands of single cells. Combined with unsupervised classification algorithms, this facilitates ab initio cell-type characterization of splenic tissues. Modeling single-cell transcriptional states in dendritic cells and additional hematopoietic cell types uncovers rich cell-type heterogeneity and gene-modules activity in steady state and after pathogen activation. Cellular diversity is thereby approached through inference of variable and dynamic pathway activity rather than a fixed preprogrammed cell-type hierarchy. These data demonstrate single-cell RNA-seq as an effective tool for comprehensive cellular decomposition of complex tissues.

Immunogenetics. Chromatin state dynamics during blood formation.

Chromatin modifications are crucial for development, yet little is known about their dynamics during differentiation. Hematopoiesis provides a well-defined model to study chromatin state dynamics; however, technical limitations impede profiling of homogeneous differentiation intermediates. We developed a high-sensitivity indexing-first chromatin immunoprecipitation approach to profile the dynamics of four chromatin modifications across 16 stages of hematopoietic differentiation. We identify 48,415 enhancer regions and characterize their dynamics. We find that lineage commitment involves de novo establishment of 17,035 lineage-specific enhancers. These enhancer repertoire expansions foreshadow transcriptional programs in differentiated cells. Combining our enhancer catalog with gene expression profiles, we elucidate the transcription factor network controlling chromatin dynamics and lineage specification in hematopoiesis. Together, our results provide a comprehensive model of chromatin dynamics during development.