Translational genetics identifies a phosphorylation switch in CARD9 required for innate inflammatory responses

Population genetics continues to identify genetic variants associated with diseases of the immune system and offers a unique opportunity to discover mechanisms of immune regulation. Multiple genetic variants linked to severe fungal infections and autoimmunity are associated with caspase recruitment domain-containing protein 9 (CARD9). We leverage the CARD9 R101C missense variant to uncover a biochemical mechanism of CARD9 activation essential for antifungal responses. We demonstrate that R101C disrupts a critical signaling switch whereby phosphorylation of S104 releases CARD9 from an autoinhibited state to promote inflammatory responses in myeloid cells. Furthermore, we show that CARD9 R101C exerts dynamic effects on the skin cellular contexture during fungal infection, corrupting inflammatory signaling and cell-cell communication circuits. Card9 R101C mice fail to control dermatophyte infection in the skin, resulting in high fungal burden, yet show minimal signs of inflammation. Together, we demonstrate how translational genetics reveals molecular and cellular mechanisms of innate immune regulation.

A spatial cell atlas of neuroblastoma reveals developmental, epigenetic and spatial axis of tumor heterogeneity

Neuroblastoma is a pediatric cancer arising from the developing sympathoadrenal lineage with complex inter- and intra-tumoral heterogeneity. To chart this complexity, we generated a comprehensive cell atlas of 55 neuroblastoma patient tumors, collected from two pediatric cancer institutions, spanning a range of clinical, genetic, and histologic features. Our atlas combines single-cell/nucleus RNA-seq (sc/scRNA-seq), bulk RNA-seq, whole exome sequencing, DNA methylation profiling, spatial transcriptomics, and two spatial proteomic methods. Sc/snRNA-seq revealed three malignant cell states with features of sympathoadrenal lineage development. All of the neuroblastomas had malignant cells that resembled sympathoblasts and the more differentiated adrenergic cells. A subset of tumors had malignant cells in a mesenchymal cell state with molecular features of Schwann cell precursors. DNA methylation profiles defined four groupings of patients, which differ in the degree of malignant cell heterogeneity and clinical outcomes. Using spatial proteomics, we found that neuroblastomas are spatially compartmentalized, with malignant tumor cells sequestered away from immune cells. Finally, we identify spatially restricted signaling patterns in immune cells from spatial transcriptomics. To facilitate the visualization and analysis of our atlas as a resource for further research in neuroblastoma, single cell, and spatial-omics, all data are shared through the Human Tumor Atlas Network Data Commons at www.humantumoratlas.org.

Genetic vulnerability to Crohn's disease reveals a spatially resolved epithelial restitution program

Effective tissue repair requires coordinated intercellular communication to sense damage, remodel the tissue, and restore function. Here, we dissected the healing response in the intestinal mucosa by mapping intercellular communication at single-cell resolution and integrating with spatial transcriptomics. We demonstrated that a risk variant for Crohn's disease, hepatocyte growth factor activator (HGFAC) Arg509His (R509H), disrupted a damage-sensing pathway connecting the coagulation cascade to growth factors that drive the differentiation of wound-associated epithelial (WAE) cells and production of a localized retinoic acid (RA) gradient to promote fibroblast-mediated tissue remodeling. Specifically, we showed that HGFAC R509H was activated by thrombin protease activity but exhibited impaired proteolytic activation of the growth factor macrophage-stimulating protein (MSP). In Hgfac R509H mice, reduced MSP activation in response to wounding of the colon resulted in impaired WAE cell induction and delayed healing. Through integration of single-cell transcriptomics and spatial transcriptomics, we demonstrated that WAE cells generated RA in a spatially restricted region of the wound site and that mucosal fibroblasts responded to this signal by producing extracellular matrix and growth factors. We further dissected this WAE cell-fibroblast signaling circuit in vitro using a genetically tractable organoid coculture model. Collectively, these studies exploited a genetic perturbation associated with human disease to disrupt a fundamental biological process and then reconstructed a spatially resolved mechanistic model of tissue healing.

Inference of single cell profiles from histology stains with the Single-Cell omics from Histology Analysis Framework (SCHAF)

Tissue biology involves an intricate balance between cell-intrinsic processes and interactions between cells organized in specific spatial patterns, which can be respectively captured by single-cell profiling methods, such as single-cell RNA-seq (scRNA-seq), and histology imaging data, such as Hematoxylin-and-Eosin (H&E) stains. While single-cell profiles provide rich molecular information, they can be challenging to collect routinely and do not have spatial resolution. Conversely, histological H&E assays have been a cornerstone of tissue pathology for decades, but do not directly report on molecular details, although the observed structure they capture arises from molecules and cells. Here, we leverage adversarial machine learning to develop SCHAF (Single-Cell omics from Histology Analysis Framework), to generate a tissue sample's spatially-resolved single-cell omics dataset from its H&E histology image. We demonstrate SCHAF on two types of human tumors-from lung and metastatic breast cancer-training with matched samples analyzed by both sc/snRNA-seq and by H&E staining. SCHAF generated appropriate single-cell profiles from histology images in test data, related them spatially, and compared well to ground-truth scRNA-Seq, expert pathologist annotations, or direct MERFISH measurements. SCHAF opens the way to next-generation H&E2.0 analyses and an integrated understanding of cell and tissue biology in health and disease.

A small noncoding RNA links ribosome recovery and translation control to dedifferentiation during salamander limb regeneration

Building a blastema from the stump is a key step of salamander limb regeneration. Stump-derived cells temporarily suspend their identity as they contribute to the blastema by a process generally referred to as dedifferentiation. Here, we provide evidence for a mechanism that involves an active inhibition of protein synthesis during blastema formation and growth. Relieving this inhibition results in a higher number of cycling cells and enhances the pace of limb regeneration. By small RNA profiling and fate mapping of skeletal muscle progeny as a cellular model for dedifferentiation, we find that the downregulation of miR-10b-5p is critical for rebooting the translation machinery. miR-10b-5p targets ribosomal mRNAs, and its artificial upregulation causes decreased blastema cell proliferation, reduction in transcripts that encode ribosomal subunits, diminished nascent protein synthesis, and retardation of limb regeneration. Taken together, our data identify a link between miRNA regulation, ribosome biogenesis, and protein synthesis during newt limb regeneration.

SM-Omics is an automated platform for high-throughput spatial multi-omics

The spatial organization of cells and molecules plays a key role in tissue function in homeostasis and disease. Spatial transcriptomics has recently emerged as a key technique to capture and positionally barcode RNAs directly in tissues. Here, we advance the application of spatial transcriptomics at scale, by presenting Spatial Multi-Omics (SM-Omics) as a fully automated, high-throughput all-sequencing based platform for combined and spatially resolved transcriptomics and antibody-based protein measurements. SM-Omics uses DNA-barcoded antibodies, immunofluorescence or a combination thereof, to scale and combine spatial transcriptomics and spatial antibody-based multiplex protein detection. SM-Omics allows processing of up to 64 in situ spatial reactions or up to 96 sequencing-ready libraries, of high complexity, in a ~2 days process. We demonstrate SM-Omics in the mouse brain, spleen and colorectal cancer model, showing its broad utility as a high-throughput platform for spatial multi-omics.

Deep learning and alignment of spatially resolved single-cell transcriptomes with Tangram

Charting an organs' biological atlas requires us to spatially resolve the entire single-cell transcriptome, and to relate such cellular features to the anatomical scale. Single-cell and single-nucleus RNA-seq (sc/snRNA-seq) can profile cells comprehensively, but lose spatial information. Spatial transcriptomics allows for spatial measurements, but at lower resolution and with limited sensitivity. Targeted in situ technologies solve both issues, but are limited in gene throughput. To overcome these limitations we present Tangram, a method that aligns sc/snRNA-seq data to various forms of spatial data collected from the same region, including MERFISH, STARmap, smFISH, Spatial Transcriptomics (Visium) and histological images. Tangram can map any type of sc/snRNA-seq data, including multimodal data such as those from SHARE-seq, which we used to reveal spatial patterns of chromatin accessibility. We demonstrate Tangram on healthy mouse brain tissue, by reconstructing a genome-wide anatomically integrated spatial map at single-cell resolution of the visual and somatomotor areas.

COVID-19 tissue atlases reveal SARS-CoV-2 pathology and cellular targets

COVID-19, which is caused by SARS-CoV-2, can result in acute respiratory distress syndrome and multiple organ failure^1-4, but little is known about its pathophysiology. Here we generated single-cell atlases of 24 lung, 16 kidney, 16 liver and 19 heart autopsy tissue samples and spatial atlases of 14 lung samples from donors who died of COVID-19. Integrated computational analysis uncovered substantial remodelling in the lung epithelial, immune and stromal compartments, with evidence of multiple paths of failed tissue regeneration, including defective alveolar type 2 differentiation and expansion of fibroblasts and putative TP63⁺ intrapulmonary basal-like progenitor cells. Viral RNAs were enriched in mononuclear phagocytic and endothelial lung cells, which induced specific host programs. Spatial analysis in lung distinguished inflammatory host responses in lung regions with and without viral RNA. Analysis of the other tissue atlases showed transcriptional alterations in multiple cell types in heart tissue from donors with COVID-19, and mapped cell types and genes implicated with disease severity based on COVID-19 genome-wide association studies. Our foundational dataset elucidates the biological effect of severe SARS-CoV-2 infection across the body, a key step towards new treatments.

Single-cell analysis uncovers fibroblast heterogeneity and criteria for fibroblast and mural cell identification and discrimination

Many important cell types in adult vertebrates have a mesenchymal origin, including fibroblasts and vascular mural cells. Although their biological importance is undisputed, the level of mesenchymal cell heterogeneity within and between organs, while appreciated, has not been analyzed in detail. Here, we compare single-cell transcriptional profiles of fibroblasts and vascular mural cells across four murine muscular organs: heart, skeletal muscle, intestine and bladder. We reveal gene expression signatures that demarcate fibroblasts from mural cells and provide molecular signatures for cell subtype identification. We observe striking inter- and intra-organ heterogeneity amongst the fibroblasts, primarily reflecting differences in the expression of extracellular matrix components. Fibroblast subtypes localize to discrete anatomical positions offering novel predictions about physiological function(s) and regulatory signaling circuits. Our data shed new light on the diversity of poorly defined classes of cells and provide a foundation for improved understanding of their roles in physiological and pathological processes.

To define and distinguish fibroblasts from vascular mural cells have remained challenging. Here, using single-cell RNA sequencing and tissue imaging, the authors provide a molecular basis for cell type classification and reveal inter- and intra-organ diversity of these cell types.

Single-cell RNA sequencing of mouse brain and lung vascular and vessel-associated cell types

Vascular diseases are major causes of death, yet our understanding of the cellular constituents of blood vessels, including how differences in their gene expression profiles create diversity in vascular structure and function, is limited. In this paper, we describe a single-cell RNA sequencing (scRNA-seq) dataset that defines vascular and vessel-associated cell types and subtypes in mouse brain and lung. The dataset contains 3,436 single cell transcriptomes from mouse brain, which formed 15 distinct clusters corresponding to cell (sub)types, and another 1,504 single cell transcriptomes from mouse lung, which formed 17 cell clusters. In order to allow user-friendly access to our data, we constructed a searchable database (http://betsholtzlab.org/VascularSingleCells/database.html). Our dataset constitutes a comprehensive molecular atlas of vascular and vessel-associated cell types in the mouse brain and lung, and as such provides a strong foundation for future studies of vascular development and diseases.

A TRPV1-to-secretagogin regulatory axis controls pancreatic β-cell survival by modulating protein turnover

Ca2+-sensor proteins are generally implicated in insulin release through SNARE interactions. Here, secretagogin, whose expression in human pancreatic islets correlates with their insulin content and the incidence of type 2 diabetes, is shown to orchestrate an unexpectedly distinct mechanism. Single-cell RNA-seq reveals retained expression of the TRP family members in β-cells from diabetic donors. Amongst these, pharmacological probing identifies Ca2+-permeable transient receptor potential vanilloid type 1 channels (TRPV1) as potent inducers of secretagogin expression through recruitment of Sp1 transcription factors. Accordingly, agonist stimulation of TRPV1s fails to rescue insulin release from pancreatic islets of glucose intolerant secretagogin knock-out(-/-) mice. However, instead of merely impinging on the SNARE machinery, reduced insulin availability in secretagogin-/- mice is due to β-cell loss, which is underpinned by the collapse of protein folding and deregulation of secretagogin-dependent USP9X deubiquitinase activity. Therefore, and considering the desensitization of TRPV1s in diabetic pancreata, a TRPV1-to-secretagogin regulatory axis seems critical to maintain the structural integrity and signal competence of β-cells.

Single-Cell Transcriptome Profiling of Human Pancreatic Islets in Health and Type 2 Diabetes

Hormone-secreting cells within pancreatic islets of Langerhans play important roles in metabolic homeostasis and disease. However, their transcriptional characterization is still incomplete. Here, we sequenced the transcriptomes of thousands of human islet cells from healthy and type 2 diabetic donors. We could define specific genetic programs for each individual endocrine and exocrine cell type, even for rare δ, γ, ε, and stellate cells, and revealed subpopulations of α, β, and acinar cells. Intriguingly, δ cells expressed several important receptors, indicating an unrecognized importance of these cells in integrating paracrine and systemic metabolic signals. Genes previously associated with obesity or diabetes were found to correlate with BMI. Finally, comparing healthy and T2D transcriptomes in a cell-type resolved manner uncovered candidates for future functional studies. Altogether, our analyses demonstrate the utility of the generated single-cell gene expression resource.

Multiple RNA interactions position Mrd1 at the site of the small subunit pseudoknot within the 90S pre-ribosome

Ribosomal subunit biogenesis in eukaryotes is a complex multistep process. Mrd1 is an essential and conserved small (40S) ribosomal subunit synthesis factor that is required for early cleavages in the 35S pre-ribosomal RNA (rRNA). Yeast Mrd1 contains five RNA-binding domains (RBDs), all of which are necessary for optimal function of the protein. Proteomic data showed that Mrd1 is part of the early pre-ribosomal complexes, and deletion of individual RBDs perturbs the pre-ribosomal structure. In vivo ultraviolet cross-linking showed that Mrd1 binds to the pre-rRNA at two sites within the 18S region, in helix 27 (h27) and helix 28. The major binding site lies in h27, and mutational analyses shows that this interaction requires the RBD1-3 region of Mrd1. RBD2 plays the dominant role in h27 binding, but other RBDs also contribute directly. h27 and helix 28 are located close to the sequences that form the central pseudoknot, a key structural feature of the mature 40S subunit. We speculate that the modular structure of Mrd1 coordinates pseudoknot formation with pre-rRNA processing and subunit assembly.

Evolutionary conservation of the ribosomal biogenesis factor Rbm19/Mrd1: implications for function

Ribosome biogenesis in eukaryotes requires coordinated folding and assembly of a pre-rRNA into sequential pre-rRNA-protein complexes in which chemical modifications and RNA cleavages occur. These processes require many small nucleolar RNAs (snoRNAs) and proteins. Rbm19/Mrd1 is one such protein that is built from multiple RNA-binding domains (RBDs). We find that Rbm19/Mrd1 with five RBDs is present in all branches of the eukaryotic phylogenetic tree, except in animals and Choanoflagellates, that instead have a version with six RBDs and Microsporidia which have a minimal Rbm19/Mrd1 protein with four RBDs. Rbm19/Mrd1 therefore evolved as a multi-RBD protein very early in eukaryotes. The linkers between the RBDs have conserved properties; they are disordered, except for linker 3, and position the RBDs at conserved relative distances from each other. All but one of the RBDs have conserved properties for RNA-binding and each RBD has a specific consensus sequence and a conserved position in the protein, suggesting a functionally important modular design. The patterns of evolutionary conservation provide information for experimental analyses of the function of Rbm19/Mrd1. In vivo mutational analysis confirmed that a highly conserved loop 5-β4-strand in RBD6 is essential for function.