Mapping the cellular biogeography of human bone marrow niches using single-cell transcriptomics and proteomic imaging.

Non-hematopoietic cells are essential contributors to hematopoiesis. However, heterogeneity and spatial organization of these cells in human bone marrow remain largely uncharacterized. We used single-cell RNA sequencing (scRNA-seq) to profile 29,325 non-hematopoietic cells and discovered nine transcriptionally distinct subtypes. We simultaneously profiled 53,417 hematopoietic cells and predicted their interactions with non-hematopoietic subsets. We employed co-detection by indexing (CODEX) to spatially profile over 1.2 million cells. We integrated scRNA-seq and CODEX data to link predicted cellular signaling with spatial proximity. Our analysis revealed a hyperoxygenated arterio-endosteal neighborhood for early myelopoiesis, and an adipocytic localization for early hematopoietic stem and progenitor cells (HSPCs). We used our CODEX atlas to annotate new images and uncovered mesenchymal stromal cell (MSC) expansion and spatial neighborhoods co-enriched for leukemic blasts and MSCs in acute myeloid leukemia (AML) patient samples. This spatially resolved, multiomic atlas of human bone marrow provides a reference for investigation of cellular interactions that drive hematopoiesis.

The Human Tumor Atlas Network: Charting Tumor Transitions across Space and Time at Single-Cell Resolution.

Crucial transitions in cancer-including tumor initiation, local expansion, metastasis, and therapeutic resistance-involve complex interactions between cells within the dynamic tumor ecosystem. Transformative single-cell genomics technologies and spatial multiplex in situ methods now provide an opportunity to interrogate this complexity at unprecedented resolution. The Human Tumor Atlas Network (HTAN), part of the National Cancer Institute (NCI) Cancer Moonshot Initiative, will establish a clinical, experimental, computational, and organizational framework to generate informative and accessible three-dimensional atlases of cancer transitions for a diverse set of tumor types. This effort complements both ongoing efforts to map healthy organs and previous large-scale cancer genomics approaches focused on bulk sequencing at a single point in time. Generating single-cell, multiparametric, longitudinal atlases and integrating them with clinical outcomes should help identify novel predictive biomarkers and features as well as therapeutically relevant cell types, cell states, and cellular interactions across transitions. The resulting tumor atlases should have a profound impact on our understanding of cancer biology and have the potential to improve cancer detection, prevention, and therapeutic discovery for better precision-medicine treatments of cancer patients and those at risk for cancer.

RUNX1 is required in granulocyte-monocyte progenitors to attenuate inflammatory cytokine production by neutrophils.

The transcription factor RUNX1 is mutated in familial platelet disorder with associated myeloid malignancy (FPDMM) and in sporadic myelodysplastic syndrome and leukemia. RUNX1 was shown to regulate inflammation in multiple cell types. Here we show that RUNX1 is required in granulocyte-monocyte progenitors (GMPs) to epigenetically repress two inflammatory signaling pathways in neutrophils: Toll-like receptor 4 (TLR4) and type I interferon (IFN) signaling. RUNX1 loss in GMPs augments neutrophils' inflammatory response to the TLR4 ligand lipopolysaccharide through increased expression of the TLR4 coreceptor CD14. RUNX1 binds Cd14 and other genes encoding proteins in the TLR4 and type I IFN signaling pathways whose chromatin accessibility increases when RUNX1 is deleted. Transcription factor footprints for the effectors of type I IFN signaling-the signal transducer and activator of transcription (STAT1::STAT2) and interferon regulatory factors (IRFs)-were enriched in chromatin that gained accessibility in both GMPs and neutrophils when RUNX1 was lost. STAT1::STAT2 and IRF motifs were also enriched in the chromatin of retrotransposons that were derepressed in RUNX1-deficient GMPs and neutrophils. We conclude that a major direct effect of RUNX1 loss in GMPs is the derepression of type I IFN and TLR4 signaling, resulting in a state of fixed maladaptive innate immunity.

FOXO1 is a master regulator of memory programming in CAR T cells.

A major limitation of chimeric antigen receptor (CAR) T cell therapies is the poor persistence of these cells in vivo1. The expression of memory-associated genes in CAR T cells is linked to their long-term persistence in patients and clinical efficacy2-6, suggesting that memory programs may underpin durable CAR T cell function. Here we show that the transcription factor FOXO1 is responsible for promoting memory and restraining exhaustion in human CAR T cells. Pharmacological inhibition or gene editing of endogenous FOXO1 diminished the expression of memory-associated genes, promoted an exhaustion-like phenotype and impaired the antitumour activity of CAR T cells. Overexpression of FOXO1 induced a gene-expression program consistent with T cell memory and increased chromatin accessibility at FOXO1-binding motifs. CAR T cells that overexpressed FOXO1 retained their function, memory potential and metabolic fitness in settings of chronic stimulation, and exhibited enhanced persistence and tumour control in vivo. By contrast, overexpression of TCF1 (encoded by TCF7) did not enforce canonical memory programs or enhance the potency of CAR T cells. Notably, FOXO1 activity correlated with positive clinical outcomes of patients treated with CAR T cells or tumour-infiltrating lymphocytes, underscoring the clinical relevance of FOXO1 in cancer immunotherapy. Our results show that overexpressing FOXO1 can increase the antitumour activity of human CAR T cells, and highlight memory reprogramming as a broadly applicable approach for optimizing therapeutic T cell states.

Control of ribosomal RNA synthesis by hematopoietic transcription factors.

Ribosomal RNAs (rRNAs) are the most abundant cellular RNAs, and their synthesis from rDNA repeats by RNA polymerase I accounts for the bulk of all transcription. Despite substantial variation in rRNA transcription rates across cell types, little is known about cell-type-specific factors that bind rDNA and regulate rRNA transcription to meet tissue-specific needs. Using hematopoiesis as a model system, we mapped about 2,200 ChIP-seq datasets for 250 transcription factors (TFs) and chromatin proteins to human and mouse rDNA and identified robust binding of multiple TF families to canonical TF motifs on rDNA. Using a 47S-FISH-Flow assay developed for nascent rRNA quantification, we demonstrated that targeted degradation of C/EBP alpha (CEBPA), a critical hematopoietic TF with conserved rDNA binding, caused rapid reduction in rRNA transcription due to reduced RNA Pol I occupancy. Our work identifies numerous potential rRNA regulators and provides a template for dissection of TF roles in rRNA transcription.

Efficient hemogenic endothelial cell specification by RUNX1 is dependent on baseline chromatin accessibility of RUNX1-regulated TGFß target genes.

Hematopoietic stem and progenitor cells (HSPCs) are generated de novo in the embryo from hemogenic endothelial cells (HECs) via an endothelial-to-hematopoietic transition (EHT) that requires the transcription factor RUNX1. Ectopic expression of RUNX1 alone can efficiently promote EHT and HSPC formation from embryonic endothelial cells (ECs), but less efficiently from fetal or adult ECs. Efficiency correlated with baseline accessibility of TGFß-related genes associated with endothelial-to-mesenchymal transition (EndoMT) and participation of AP-1 and SMAD2/3 to initiate further chromatin remodeling along with RUNX1 at these sites. Activation of TGFß signaling improved the efficiency with which RUNX1 specified fetal ECs as HECs. Thus, the ability of RUNX1 to promote EHT depends on its ability to recruit the TGFß signaling effectors AP-1 and SMAD2/3, which in turn is determined by the changing chromatin landscape in embryonic versus fetal ECs. This work provides insight into regulation of EndoMT and EHT that will guide reprogramming efforts for clinical applications.

Decade-long leukaemia remissions with persistence of CD4+ CAR T cells.

The adoptive transfer of T lymphocytes reprogrammed to target tumour cells has demonstrated potential for treatment of various cancers1-7. However, little is known about the long-term potential and clonal stability of the infused cells. Here we studied long-lasting CD19-redirected chimeric antigen receptor (CAR) T cells in two patients with chronic lymphocytic leukaemia1-4 who achieved a complete remission in 2010. CAR T cells remained detectable more than ten years after infusion, with sustained remission in both patients. Notably, a highly activated CD4+ population emerged in both patients, dominating the CAR T cell population at the later time points. This transition was reflected in the stabilization of the clonal make-up of CAR T cells with a repertoire dominated by a small number of clones. Single-cell profiling demonstrated that these long-persisting CD4+ CAR T cells exhibited cytotoxic characteristics along with ongoing functional activation and proliferation. In addition, longitudinal profiling revealed a population of gamma delta CAR T cells that prominently expanded in one patient concomitant with CD8+ CAR T cells during the initial response phase. Our identification and characterization of these unexpected CAR T cell populations provide novel insight into the CAR T cell characteristics associated with anti-cancer response and long-term remission in leukaemia.

Transcriptional regulatory network controlling the ontogeny of hematopoietic stem cells.

Hematopoietic stem cell (HSC) ontogeny is accompanied by dynamic changes in gene regulatory networks. We performed RNA-seq and histone mark ChIP-seq to define the transcriptomes and epigenomes of cells representing key developmental stages of HSC ontogeny in mice. The five populations analyzed were embryonic day 10.5 (E10.5) endothelium and hemogenic endothelium from the major arteries, an enriched population of prehematopoietic stem cells (pre-HSCs), fetal liver HSCs, and adult bone marrow HSCs. Using epigenetic signatures, we identified enhancers for each developmental stage. Only 12% of enhancers are primed, and 78% are active, suggesting the vast majority of enhancers are established de novo without prior priming in earlier stages. We constructed developmental stage-specific transcriptional regulatory networks by linking enhancers and predicted bound transcription factors to their target promoters using a novel computational algorithm, target inference via physical connection (TIPC). TIPC predicted known transcriptional regulators for the endothelial-to-hematopoietic transition, validating our overall approach, and identified putative novel transcription factors, including the broadly expressed transcription factors SP3 and MAZ. Finally, we validated a role for SP3 and MAZ in the formation of hemogenic endothelium. Our data and computational analyses provide a useful resource for uncovering regulators of HSC formation.

Unsupervised and supervised discovery of tissue cellular neighborhoods from cell phenotypes.

It is poorly understood how different cells in a tissue organize themselves to support tissue functions. We describe the CytoCommunity algorithm for the identification of tissue cellular neighborhoods (TCNs) based on cell phenotypes and their spatial distributions. CytoCommunity learns a mapping directly from the cell phenotype space to the TCN space using a graph neural network model without intermediate clustering of cell embeddings. By leveraging graph pooling, CytoCommunity enables de novo identification of condition-specific and predictive TCNs under the supervision of sample labels. Using several types of spatial omics data, we demonstrate that CytoCommunity can identify TCNs of variable sizes with substantial improvement over existing methods. By analyzing risk-stratified colorectal and breast cancer data, CytoCommunity revealed new granulocyte-enriched and cancer-associated fibroblast-enriched TCNs specific to high-risk tumors and altered interactions between neoplastic and immune or stromal cells within and between TCNs. CytoCommunity can perform unsupervised and supervised analyses of spatial omics maps and enable the discovery of condition-specific cell-cell communication patterns across spatial scales.

TCF-1 and LEF-1 act upstream of Th-POK to promote the CD4(+) T cell fate and interact with Runx3 to silence Cd4 in CD8(+) T cells.

The transcription factors TCF-1 and LEF-1 are essential for early T cell development, but their roles beyond the CD4(+)CD8(+) double-positive (DP) stage are unknown. By specific ablation of these factors in DP thymocytes, we demonstrated that deficiency in TCF-1 and LEF-1 diminished the output of CD4(+) T cells and redirected CD4(+) T cells to a CD8(+) T cell fate. The role of TCF-1 and LEF-1 in the CD4-versus-CD8 lineage 'choice' was mediated in part by direct positive regulation of the transcription factor Th-POK. Furthermore, loss of TCF-1 and LEF-1 unexpectedly caused derepression of CD4 expression in T cells committed to the CD8(+) lineage without affecting the expression of Runx transcription factors. Instead, TCF-1 physically interacted with Runx3 to cooperatively silence Cd4. Thus, TCF-1 and LEF-1 adopted distinct genetic 'wiring' to promote the CD4(+) T cell fate and establish CD8(+) T cell identity.

Influence of glycan structure on the colonization of Streptococcus pneumoniae on human respiratory epithelial cells.

Virtually all living cells are encased in glycans. They perform key cellular functions such as immunomodulation and cell-cell recognition. Yet, how their composition and configuration affect their functions remains enigmatic. Here, we constructed isogenic capsule-switch mutants harboring 84 types of capsular polysaccharides (CPSs) in Streptococcus pneumoniae. This collection enables us to systematically measure the affinity of structurally related CPSs to primary human nasal and bronchial epithelial cells. Contrary to the paradigm, the surface charge does not appreciably affect epithelial cell binding. Factors that affect adhesion to respiratory cells include the number of rhamnose residues and the presence of human-like glycomotifs in CPS. Besides, pneumococcal colonization stimulated the production of interleukin 6 (IL-6), granulocyte-macrophage colony-stimulating factor (GM-CSF), and monocyte chemoattractantprotein-1 (MCP-1) in nasal epithelial cells, which also appears to be dependent on the serotype. Together, our results reveal glycomotifs of surface polysaccharides that are likely to be important for colonization and survival in the human airway.

CD8+ T Cells Utilize Highly Dynamic Enhancer Repertoires and Regulatory Circuitry in Response to Infections.

Differentiation of effector and memory CD8+ T cells is accompanied by extensive changes in the transcriptome and histone modifications at gene promoters; however, the enhancer repertoire and associated gene regulatory networks are poorly defined. Using histone mark chromatin immunoprecipitation coupled with deep sequencing, we mapped the enhancer and super-enhancer landscapes in antigen-specific naive, differentiated effector, and central memory CD8+ T cells during LCMV infection. Epigenomics-based annotation revealed a highly dynamic repertoire of enhancers, which were inherited, de novo activated, decommissioned and re-activated during CD8+ T cell responses. We employed a computational algorithm to pair enhancers with target gene promoters. On average, each enhancer targeted three promoters and each promoter was regulated by two enhancers. By identifying enriched transcription factor motifs in enhancers, we defined transcriptional regulatory circuitry at each CD8+ T cell response stage. These multi-dimensional datasets provide a blueprint for delineating molecular mechanisms underlying functional differentiation of CD8+ T cells.

Pax6 limits the competence of developing cerebral cortical cells to respond to inductive intercellular signals.

The development of stable specialized cell types in multicellular organisms relies on mechanisms controlling inductive intercellular signals and the competence of cells to respond to such signals. In developing cerebral cortex, progenitors generate only glutamatergic excitatory neurons despite being exposed to signals with the potential to initiate the production of other neuronal types, suggesting that their competence is limited. Here, we tested the hypothesis that this limitation is due to their expression of transcription factor Pax6. We used bulk and single-cell RNAseq to show that conditional cortex-specific Pax6 deletion from the onset of cortical neurogenesis allowed some progenitors to generate abnormal lineages resembling those normally found outside the cortex. Analysis of selected gene expression showed that the changes occurred in specific spatiotemporal patterns. We then compared the responses of control and Pax6-deleted cortical cells to in vivo and in vitro manipulations of extracellular signals. We found that Pax6 loss increased cortical progenitors' competence to generate inappropriate lineages in response to extracellular factors normally present in developing cortex, including the morphogens Shh and Bmp4. Regional variation in the levels of these factors could explain spatiotemporal patterns of fate change following Pax6 deletion in vivo. We propose that Pax6's main role in developing cortical cells is to minimize the risk of their development being derailed by the potential side effects of morphogens engaged contemporaneously in other essential functions.

An atlas of combinatorial transcriptional regulation in mouse and man.

Combinatorial interactions among transcription factors are critical to directing tissue-specific gene expression. To build a global atlas of these combinations, we have screened for physical interactions among the majority of human and mouse DNA-binding transcription factors (TFs). The complete networks contain 762 human and 877 mouse interactions. Analysis of the networks reveals that highly connected TFs are broadly expressed across tissues, and that roughly half of the measured interactions are conserved between mouse and human. The data highlight the importance of TF combinations for determining cell fate, and they lead to the identification of a SMAD3/FLI1 complex expressed during development of immunity. The availability of large TF combinatorial networks in both human and mouse will provide many opportunities to study gene regulation, tissue differentiation, and mammalian evolution.

Single-shot dendritic cell targeting SARS-CoV-2 vaccine candidate induces broad, durable and protective systemic and mucosal immunity in mice.

Current coronavirus disease 2019 vaccines face limitations including waning immunity, immune escape by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants, limited cellular response, and poor mucosal immunity. We engineered a Clec9A-receptor binding domain (RBD) antibody construct that delivers the SARS-CoV-2 RBD to conventional type 1 dendritic cells. Compared with non-targeting approaches, single dose immunization in mice with Clec9A-RBD induced far higher RBD-specific antibody titers that were sustained for up to 21 months after vaccination. Uniquely, increasing neutralizing and antibody-dependent cytotoxicity activities across the sarbecovirus family was observed, suggesting antibody affinity maturation over time. Consistently and remarkably, RBD-specific follicular T helper cells and germinal center B cells persisted up to 12 months after immunization. Furthermore, Clec9A-RBD immunization induced a durable mono- and poly-functional T-helper 1-biased cellular response that was strongly cross-reactive against SARS-CoV-2 variants of concern, including Omicron subvariants, and with a robust CD8+ T cell signature. Uniquely, Clec9A-RBD single-shot systemic immunization effectively primed RBD-specific cellular and humoral immunity in lung and resulted in significant protection against homologous SARS-CoV-2 challenge as evidenced by limited body weight loss and approximately 2 log10 decrease in lung viral loads compared with non-immunized controls. Therefore, Clec9A-RBD immunization has the potential to trigger robust and sustained, systemic and mucosal protective immunity against rapidly evolving SARS-CoV2 variants.

Epigenetic state determines inflammatory sensing in neuroblastoma.

Immunotherapy has revolutionized cancer treatment, but many cancers are not impacted by currently available immunotherapeutic strategies. Here, we investigated inflammatory signaling pathways in neuroblastoma, a classically "cold" pediatric cancer. By testing the functional response of a panel of 20 diverse neuroblastoma cell lines to three different inflammatory stimuli, we found that all cell lines have intact interferon signaling, and all but one lack functional cytosolic DNA sensing via cGAS-STING. However, double-stranded RNA (dsRNA) sensing via Toll-like receptor 3 (TLR3) was heterogeneous, as was signaling through other dsRNA sensors and TLRs more broadly. Seven cell lines showed robust response to dsRNA, six of which are in the mesenchymal epigenetic state, while all unresponsive cell lines are in the adrenergic state. Genetically switching adrenergic cell lines toward the mesenchymal state fully restored responsiveness. In responsive cells, dsRNA sensing results in the secretion of proinflammatory cytokines, enrichment of inflammatory transcriptomic signatures, and increased tumor killing by T cells in vitro. Using single-cell RNA sequencing data, we show that human neuroblastoma cells with stronger mesenchymal signatures have a higher basal inflammatory state, demonstrating intratumoral heterogeneity in inflammatory signaling that has significant implications for immunotherapeutic strategies in this aggressive childhood cancer.

NGCN: Drug-target interaction prediction by integrating information and feature learning from heterogeneous network.

Drug-target interaction (DTI) prediction is essential for new drug design and development. Constructing heterogeneous network based on diverse information about drugs, proteins and diseases provides new opportunities for DTI prediction. However, the inherent complexity, high dimensionality and noise of such a network prevent us from taking full advantage of these network characteristics. This article proposes a novel method, NGCN, to predict drug-target interactions from an integrated heterogeneous network, from which to extract relevant biological properties and association information while maintaining the topology information. It focuses on learning the topology representation of drugs and targets to improve the performance of DTI prediction. Unlike traditional methods, it focuses on learning the low-dimensional topology representation of drugs and targets via graph-based convolutional neural network. NGCN achieves substantial performance improvements over other state-of-the-art methods, such as a nearly 1.0% increase in AUPR value. Moreover, we verify the robustness of NGCN through benchmark tests, and the experimental results demonstrate it is an extensible framework capable of combining heterogeneous information for DTI prediction.

Predictive modeling of single-cell DNA methylome data enhances integration with transcriptome data.

Single-cell DNA methylation data has become increasingly abundant and has uncovered many genes with a positive correlation between expression and promoter methylation, challenging the common dogma based on bulk data. However, computational tools for analyzing single-cell methylome data are lagging far behind. A number of tasks, including cell type calling and integration with transcriptome data, requires the construction of a robust gene activity matrix as the prerequisite but challenging task. The advent of multi-omics data enables measurement of both DNA methylation and gene expression for the same single cells. Although such data is rather sparse, they are sufficient to train supervised models that capture the complex relationship between DNA methylation and gene expression and predict gene activities at single-cell level. Here, we present methylome association by predictive linkage to expression (MAPLE), a computational framework that learns the association between DNA methylation and expression using both gene- and cell-dependent statistical features. Using multiple data sets generated with different experimental protocols, we show that using predicted gene activity values significantly improves several analysis tasks, including clustering, cell type identification, and integration with transcriptome data. Application of MAPLE revealed several interesting biological insights into the relationship between methylation and gene expression, including asymmetric importance of methylation signals around transcription start site for predicting gene expression, and increased predictive power of methylation signals in promoters located outside CpG islands and shores. With the rapid accumulation of single-cell epigenomics data, MAPLE provides a general framework for integrating such data with transcriptome data.

Homozygous missense variants in YKT6 result in loss of function and are associated with developmental delay, with or without severe infantile liver disease and risk for hepatocellular carcinoma.

PURPOSE: YKT6 plays important roles in multiple intracellular vesicle trafficking events but has not been associated with Mendelian diseases. METHODS: We report 3 unrelated individuals with rare homozygous missense variants in YKT6 who exhibited neurological disease with or without a progressive infantile liver disease. We modeled the variants in Drosophila. We generated wild-type and variant genomic rescue constructs of the fly ortholog dYkt6 and compared their ability in rescuing the loss-of-function phenotypes in mutant flies. We also generated a dYkt6KozakGAL4 allele to assess the expression pattern of dYkt6. RESULTS: Two individuals are homozygous for YKT6 [NM_006555.3:c.554A>G p.(Tyr185Cys)] and exhibited normal prenatal course followed by failure to thrive, developmental delay, and progressive liver disease. Haplotype analysis identified a shared homozygous region flanking the variant, suggesting a common ancestry. The third individual is homozygous for YKT6 [NM_006555.3:c.191A>G p.(Tyr64Cys)] and exhibited neurodevelopmental disorders and optic atrophy. Fly dYkt6 is essential and is expressed in the fat body (analogous to liver) and central nervous system. Wild-type genomic rescue constructs can rescue the lethality and autophagic flux defects, whereas the variants are less efficient in rescuing the phenotypes. CONCLUSION: The YKT6 variants are partial loss-of-function alleles, and the p.(Tyr185Cys) is more severe than p.(Tyr64Cys).