Time-resolved single-cell transcriptomics defines immune trajectories in glioblastoma.

Deciphering the cell-state transitions underlying immune adaptation across time is fundamental for advancing biology. Empirical in vivo genomic technologies that capture cellular dynamics are currently lacking. We present Zman-seq, a single-cell technology recording transcriptomic dynamics across time by introducing time stamps into circulating immune cells, tracking them in tissues for days. Applying Zman-seq resolved cell-state and molecular trajectories of the dysfunctional immune microenvironment in glioblastoma. Within 24 hours of tumor infiltration, cytotoxic natural killer cells transitioned to a dysfunctional program regulated by TGFB1 signaling. Infiltrating monocytes differentiated into immunosuppressive macrophages, characterized by the upregulation of suppressive myeloid checkpoints Trem2, Il18bp, and Arg1, over 36 to 48 hours. Treatment with an antagonistic anti-TREM2 antibody reshaped the tumor microenvironment by redirecting the monocyte trajectory toward pro-inflammatory macrophages. Zman-seq is a broadly applicable technology, enabling empirical measurements of differentiation trajectories, which can enhance the development of more efficacious immunotherapies.

Lineage tracing reveals the phylodynamics, plasticity, and paths of tumor evolution.

Tumor evolution is driven by the progressive acquisition of genetic and epigenetic alterations that enable uncontrolled growth and expansion to neighboring and distal tissues. The study of phylogenetic relationships between cancer cells provides key insights into these processes. Here, we introduced an evolving lineage-tracing system with a single-cell RNA-seq readout into a mouse model of Kras;Trp53(KP)-driven lung adenocarcinoma and tracked tumor evolution from single-transformed cells to metastatic tumors at unprecedented resolution. We found that the loss of the initial, stable alveolar-type2-like state was accompanied by a transient increase in plasticity. This was followed by the adoption of distinct transcriptional programs that enable rapid expansion and, ultimately, clonal sweep of stable subclones capable of metastasizing. Finally, tumors develop through stereotypical evolutionary trajectories, and perturbing additional tumor suppressors accelerates progression by creating novel trajectories. Our study elucidates the hierarchical nature of tumor evolution and, more broadly, enables in-depth studies of tumor progression.

The single-cell epigenomic and transcriptional landscape of immunity to influenza vaccination.

Emerging evidence indicates a fundamental role for the epigenome in immunity. Here, we mapped the epigenomic and transcriptional landscape of immunity to influenza vaccination in humans at the single-cell level. Vaccination against seasonal influenza induced persistently diminished H3K27ac in monocytes and myeloid dendritic cells (mDCs), which was associated with impaired cytokine responses to Toll-like receptor stimulation. Single-cell ATAC-seq analysis revealed an epigenomically distinct subcluster of monocytes with reduced chromatin accessibility at AP-1-targeted loci after vaccination. Similar effects were observed in response to vaccination with the AS03-adjuvanted H5N1 pandemic influenza vaccine. However, this vaccine also stimulated persistently increased chromatin accessibility at interferon response factor (IRF) loci in monocytes and mDCs. This was associated with elevated expression of antiviral genes and heightened resistance to the unrelated Zika and Dengue viruses. These results demonstrate that vaccination stimulates persistent epigenomic remodeling of the innate immune system and reveal AS03's potential as an epigenetic adjuvant.

Polyamine metabolism is a central determinant of helper T cell lineage fidelity.

Polyamine synthesis represents one of the most profound metabolic changes during T cell activation, but the biological implications of this are scarcely known. Here, we show that polyamine metabolism is a fundamental process governing the ability of CD4+ helper T cells (TH) to polarize into different functional fates. Deficiency in ornithine decarboxylase, a crucial enzyme for polyamine synthesis, results in a severe failure of CD4+ T cells to adopt correct subset specification, underscored by ectopic expression of multiple cytokines and lineage-defining transcription factors across TH cell subsets. Polyamines control TH differentiation by providing substrates for deoxyhypusine synthase, which synthesizes the amino acid hypusine, and mice in which T cells are deficient for hypusine develop severe intestinal inflammatory disease. Polyamine-hypusine deficiency caused widespread epigenetic remodeling driven by alterations in histone acetylation and a re-wired tricarboxylic acid (TCA) cycle. Thus, polyamine metabolism is critical for maintaining the epigenome to focus TH cell subset fidelity.

Metabolic modeling of single Th17 cells reveals regulators of autoimmunity.

Metabolism is a major regulator of immune cell function, but it remains difficult to study the metabolic status of individual cells. Here, we present Compass, an algorithm to characterize cellular metabolic states based on single-cell RNA sequencing and flux balance analysis. We applied Compass to associate metabolic states with T helper 17 (Th17) functional variability (pathogenic potential) and recovered a metabolic switch between glycolysis and fatty acid oxidation, akin to known Th17/regulatory T cell (Treg) differences, which we validated by metabolic assays. Compass also predicted that Th17 pathogenicity was associated with arginine and downstream polyamine metabolism. Indeed, polyamine-related enzyme expression was enhanced in pathogenic Th17 and suppressed in Treg cells. Chemical and genetic perturbation of polyamine metabolism inhibited Th17 cytokines, promoted Foxp3 expression, and remodeled the transcriptome and epigenome of Th17 cells toward a Treg-like state. In vivo perturbations of the polyamine pathway altered the phenotype of encephalitogenic T cells and attenuated tissue inflammation in CNS autoimmunity.

Single-cell multiomic analysis of thymocyte development reveals drivers of CD4+ T cell and CD8+ T cell lineage commitment.

The development of CD4+ T cells and CD8+ T cells in the thymus is critical to adaptive immunity and is widely studied as a model of lineage commitment. Recognition of self-peptide major histocompatibility complex (MHC) class I or II by the T cell antigen receptor (TCR) determines the CD8+ or CD4+ T cell lineage choice, respectively, but how distinct TCR signals drive transcriptional programs of lineage commitment remains largely unknown. Here we applied CITE-seq to measure RNA and surface proteins in thymocytes from wild-type and T cell lineage-restricted mice to generate a comprehensive timeline of cell states for each T cell lineage. These analyses identified a sequential process whereby all thymocytes initiate CD4+ T cell lineage differentiation during a first wave of TCR signaling, followed by a second TCR signaling wave that coincides with CD8+ T cell lineage specification. CITE-seq and pharmaceutical inhibition experiments implicated a TCR-calcineurin-NFAT-GATA3 axis in driving the CD4+ T cell fate. Our data provide a resource for understanding cell fate decisions and implicate a sequential selection process in guiding lineage choice.

Induction of a colitogenic phenotype in Th1-like cells depends on interleukin-23 receptor signaling.

Interleukin-23 receptor plays a critical role in inducing inflammation and autoimmunity. Here, we report that Th1-like cells differentiated in vitro with IL-12 + IL-21 showed similar IL-23R expression to that of pathogenic Th17 cells using eGFP reporter mice. Fate mapping established that these cells did not transition through a Th17 cell state prior to becoming Th1-like cells, and we observed their emergence in vivo in the T cell adoptive transfer colitis model. Using IL-23R-deficient Th1-like cells, we demonstrated that IL-23R was required for the development of a highly colitogenic phenotype. Single-cell RNA sequencing analysis of intestinal T cells identified IL-23R-dependent genes in Th1-like cells that differed from those expressed in Th17 cells. The perturbation of one of these regulators (CD160) in Th1-like cells inhibited the induction of colitis. We thus uncouple IL-23R as a purely Th17 cell-specific factor and implicate IL-23R signaling as a pathogenic driver in Th1-like cells inducing tissue inflammation.

Neurological Manifestations of COVID-19 Feature T Cell Exhaustion and Dedifferentiated Monocytes in Cerebrospinal Fluid.

Patients suffering from Coronavirus disease 2019 (COVID-19) can develop neurological sequelae, such as headache and neuroinflammatory or cerebrovascular disease. These conditions-termed here as Neuro-COVID-are more frequent in patients with severe COVID-19. To understand the etiology of these neurological sequelae, we utilized single-cell sequencing and examined the immune cell profiles from the cerebrospinal fluid (CSF) of Neuro-COVID patients compared with patients with non-inflammatory and autoimmune neurological diseases or with viral encephalitis. The CSF of Neuro-COVID patients exhibited an expansion of dedifferentiated monocytes and of exhausted CD4+ T cells. Neuro-COVID CSF leukocytes featured an enriched interferon signature; however, this was less pronounced than in viral encephalitis. Repertoire analysis revealed broad clonal T cell expansion and curtailed interferon response in severe compared with mild Neuro-COVID patients. Collectively, our findings document the CSF immune compartment in Neuro-COVID patients and suggest compromised antiviral responses in this setting.

Single-Cell Genomics Unveils Critical Regulators of Th17 Cell Pathogenicity.

Extensive cellular heterogeneity exists within specific immune-cell subtypes classified as a single lineage, but its molecular underpinnings are rarely characterized at a genomic scale. Here, we use single-cell RNA-seq to investigate the molecular mechanisms governing heterogeneity and pathogenicity of Th17 cells isolated from the central nervous system (CNS) and lymph nodes (LN) at the peak of autoimmune encephalomyelitis (EAE) or differentiated in vitro under either pathogenic or non-pathogenic polarization conditions. Computational analysis relates a spectrum of cellular states in vivo to in-vitro-differentiated Th17 cells and unveils genes governing pathogenicity and disease susceptibility. Using knockout mice, we validate four new genes: Gpr65, Plzp, Toso, and Cd5l (in a companion paper). Cellular heterogeneity thus informs Th17 function in autoimmunity and can identify targets for selective suppression of pathogenic Th17 cells while potentially sparing non-pathogenic tissue-protective ones.

CD5L/AIM Regulates Lipid Biosynthesis and Restrains Th17 Cell Pathogenicity.

Th17 cells play a critical role in host defense against extracellular pathogens and tissue homeostasis but can induce autoimmunity. The mechanisms implicated in balancing "pathogenic" and "non-pathogenic" Th17 cell states remain largely unknown. We used single-cell RNA-seq to identify CD5L/AIM as a regulator expressed in non-pathogenic, but not in pathogenic Th17 cells. Although CD5L does not affect Th17 differentiation, it is a functional switch that regulates the pathogenicity of Th17 cells. Loss of CD5L converts non-pathogenic Th17 cells into pathogenic cells that induce autoimmunity. CD5L mediates this effect by modulating the intracellular lipidome, altering fatty acid composition and restricting cholesterol biosynthesis and, thus, ligand availability for Rorγt, the master transcription factor of Th17 cells. Our study identifies CD5L as a critical regulator of the Th17 cell functional state and highlights the importance of lipid metabolism in balancing immune protection and disease induced by T cells.

Critical role of IRF1 and BATF in forming chromatin landscape during type 1 regulatory cell differentiation.

Type 1 regulatory T cells (Tr1 cells) are induced by interleukin-27 (IL-27) and have critical roles in the control of autoimmunity and resolution of inflammation. We found that the transcription factors IRF1 and BATF were induced early on after treatment with IL-27 and were required for the differentiation and function of Tr1 cells in vitro and in vivo. Epigenetic and transcriptional analyses revealed that both transcription factors influenced chromatin accessibility and expression of the genes required for Tr1 cell function. IRF1 and BATF deficiencies uniquely altered the chromatin landscape, suggesting that these factors serve a pioneering function during Tr1 cell differentiation.

Deep generative modeling of transcriptional dynamics for RNA velocity analysis in single cells.

RNA velocity has been rapidly adopted to guide interpretation of transcriptional dynamics in snapshot single-cell data; however, current approaches for estimating RNA velocity lack effective strategies for quantifying uncertainty and determining the overall applicability to the system of interest. Here, we present veloVI (velocity variational inference), a deep generative modeling framework for estimating RNA velocity. veloVI learns a gene-specific dynamical model of RNA metabolism and provides a transcriptome-wide quantification of velocity uncertainty. We show that veloVI compares favorably to previous approaches with respect to goodness of fit, consistency across transcriptionally similar cells and stability across preprocessing pipelines for quantifying RNA abundance. Further, we demonstrate that veloVI's posterior velocity uncertainty can be used to assess whether velocity analysis is appropriate for a given dataset. Finally, we highlight veloVI as a flexible framework for modeling transcriptional dynamics by adapting the underlying dynamical model to use time-dependent transcription rates.

Self-guarding of MORC3 enables virulence factor-triggered immunity.

Pathogens use virulence factors to inhibit the immune system1. The guard hypothesis2,3 postulates that hosts monitor (or 'guard') critical innate immune pathways such that their disruption by virulence factors provokes a secondary immune response1. Here we describe a 'self-guarded' immune pathway in human monocytes, in which guarding and guarded functions are combined in one protein. We find that this pathway is triggered by ICP0, a key virulence factor of herpes simplex virus type 1, resulting in robust induction of anti-viral type I interferon (IFN). Notably, induction of IFN by ICP0 is independent of canonical immune pathways and the IRF3 and IRF7 transcription factors. A CRISPR screen identified the ICP0 target MORC34 as an essential negative regulator of IFN. Loss of MORC3 recapitulates the IRF3- and IRF7-independent IFN response induced by ICP0. Mechanistically, ICP0 degrades MORC3, which leads to de-repression of a MORC3-regulated DNA element (MRE) adjacent to the IFNB1 locus. The MRE is required in cis for IFNB1 induction by the MORC3 pathway, but is not required for canonical IFN-inducing pathways. As well as repressing the MRE to regulate IFNB1, MORC3 is also a direct restriction factor of HSV-15. Our results thus suggest a model in which the primary anti-viral function of MORC3 is self-guarded by its secondary IFN-repressing function-thus, a virus that degrades MORC3 to avoid its primary anti-viral function will unleash the secondary anti-viral IFN response.

MultiVI: deep generative model for the integration of multimodal data.

Jointly profiling the transcriptome, chromatin accessibility and other molecular properties of single cells offers a powerful way to study cellular diversity. Here we present MultiVI, a probabilistic model to analyze such multiomic data and leverage it to enhance single-modality datasets. MultiVI creates a joint representation that allows an analysis of all modalities included in the multiomic input data, even for cells for which one or more modalities are missing. It is available at scvi-tools.org .

The transcription factor BATF operates as an essential differentiation checkpoint in early effector CD8+ T cells.

The transcription factor BATF is required for the differentiation of interleukin 17 (IL-17)-producing helper T cells (TH17 cells) and follicular helper T cells (TFH cells). Here we identified a fundamental role for BATF in regulating the differentiation of effector of CD8(+) T cells. BATF-deficient CD8(+) T cells showed profound defects in effector population expansion and underwent proliferative and metabolic catastrophe early after encountering antigen. BATF, together with the transcription factors IRF4 and Jun proteins, bound to and promoted early expression of genes encoding lineage-specific transcription-factors (T-bet and Blimp-1) and cytokine receptors while paradoxically repressing genes encoding effector molecules (IFN-γ and granzyme B). Thus, BATF amplifies T cell antigen receptor (TCR)-dependent expression of transcription factors and augments the propagation of inflammatory signals but restrains the expression of genes encoding effector molecules. This checkpoint prevents irreversible commitment to an effector fate until a critical threshold of downstream transcriptional activity has been achieved.

Impulse control: temporal dynamics in gene transcription.

Regulatory circuits controlling gene expression constantly rewire to adapt to environmental stimuli, differentiation cues, and disease. We review our current understanding of the temporal dynamics of gene expression in eukaryotes and prokaryotes and the molecular mechanisms that shape them. We delineate several prototypical temporal patterns, including "impulse" (or single-pulse) patterns in response to transient environmental stimuli, sustained (or state-transitioning) patterns in response to developmental cues, and oscillating patterns. We focus on impulse responses and their higher-order temporal organization in regulons and cascades and describe how core protein circuits and cis-regulatory sequences in promoters integrate with chromatin architecture to generate these responses.

Combinatorial patterning of chromatin regulators uncovered by genome-wide location analysis in human cells.

Hundreds of chromatin regulators (CRs) control chromatin structure and function by catalyzing and binding histone modifications, yet the rules governing these key processes remain obscure. Here, we present a systematic approach to infer CR function. We developed ChIP-string, a meso-scale assay that combines chromatin immunoprecipitation with a signature readout of 487 representative loci. We applied ChIP-string to screen 145 antibodies, thereby identifying effective reagents, which we used to map the genome-wide binding of 29 CRs in two cell types. We found that specific combinations of CRs colocalize in characteristic patterns at distinct chromatin environments, at genes of coherent functions, and at distal regulatory elements. When comparing between cell types, CRs redistribute to different loci but maintain their modular and combinatorial associations. Our work provides a multiplex method that substantially enhances the ability to monitor CR binding, presents a large resource of CR maps, and reveals common principles for combinatorial CR function.

Systematic discovery of TLR signaling components delineates viral-sensing circuits.

Deciphering the signaling networks that underlie normal and disease processes remains a major challenge. Here, we report the discovery of signaling components involved in the Toll-like receptor (TLR) response of immune dendritic cells (DCs), including a previously unkown pathway shared across mammalian antiviral responses. By combining transcriptional profiling, genetic and small-molecule perturbations, and phosphoproteomics, we uncover 35 signaling regulators, including 16 known regulators, involved in TLR signaling. In particular, we find that Polo-like kinases (Plk) 2 and 4 are essential components of antiviral pathways in vitro and in vivo and activate a signaling branch involving a dozen proteins, among which is Tnfaip2, a gene associated with autoimmune diseases but whose role was unknown. Our study illustrates the power of combining systematic measurements and perturbations to elucidate complex signaling circuits and discover potential therapeutic targets.

Densely interconnected transcriptional circuits control cell states in human hematopoiesis.

Though many individual transcription factors are known to regulate hematopoietic differentiation, major aspects of the global architecture of hematopoiesis remain unknown. Here, we profiled gene expression in 38 distinct purified populations of human hematopoietic cells and used probabilistic models of gene expression and analysis of cis-elements in gene promoters to decipher the general organization of their regulatory circuitry. We identified modules of highly coexpressed genes, some of which are restricted to a single lineage but most of which are expressed at variable levels across multiple lineages. We found densely interconnected cis-regulatory circuits and a large number of transcription factors that are differentially expressed across hematopoietic states. These findings suggest a more complex regulatory system for hematopoiesis than previously assumed.

Optimizing sequence design strategies for perturbation MPRAs: a computational evaluation framework.

The advent of perturbation-based massively parallel reporter assays (MPRAs) technique has facilitated the delineation of the roles of non-coding regulatory elements in orchestrating gene expression. However, computational efforts remain scant to evaluate and establish guidelines for sequence design strategies for perturbation MPRAs. In this study, we propose a framework for evaluating and comparing various perturbation strategies for MPRA experiments. Within this framework, we benchmark three different perturbation approaches from the perspectives of alteration in motif-based profiles, consistency of MPRA outputs, and robustness of models that predict the activities of putative regulatory motifs. While our analyses show very similar results across multiple benchmarking metrics, the predictive modeling for the approach involving random nucleotide shuffling shows significant robustness compared with the other two approaches. Thus, we recommend designing sequences by randomly shuffling the nucleotides of the perturbed site in perturbation-MPRA, followed by a coherence check to prevent the introduction of other variations of the target motifs. In summary, our evaluation framework and the benchmarking findings create a resource of computational pipelines and highlight the potential of perturbation-MPRA in predicting non-coding regulatory activities.