Modulation of FGF pathway signaling and vascular differentiation using designed oligomeric assemblies.

Many growth factors and cytokines signal by binding to the extracellular domains of their receptors and driving association and transphosphorylation of the receptor intracellular tyrosine kinase domains, initiating downstream signaling cascades. To enable systematic exploration of how receptor valency and geometry affect signaling outcomes, we designed cyclic homo-oligomers with up to 8 subunits using repeat protein building blocks that can be modularly extended. By incorporating a de novo-designed fibroblast growth factor receptor (FGFR)-binding module into these scaffolds, we generated a series of synthetic signaling ligands that exhibit potent valency- and geometry-dependent Ca2+ release and mitogen-activated protein kinase (MAPK) pathway activation. The high specificity of the designed agonists reveals distinct roles for two FGFR splice variants in driving arterial endothelium and perivascular cell fates during early vascular development. Our designed modular assemblies should be broadly useful for unraveling the complexities of signaling in key developmental transitions and for developing future therapeutic applications.

Proteostasis governs differential temperature sensitivity across embryonic cell types.

Embryonic development is remarkably robust, but temperature stress can degrade its ability to generate animals with invariant anatomy. Phenotypes associated with environmental stress suggest that some cell types are more sensitive to stress than others, but the basis of this sensitivity is unknown. Here, we characterize hundreds of individual zebrafish embryos under temperature stress using whole-animal single-cell RNA sequencing (RNA-seq) to identify cell types and molecular programs driving phenotypic variability. We find that temperature perturbs the normal proportions and gene expression programs of numerous cell types and also introduces asynchrony in developmental timing. The notochord is particularly sensitive to temperature, which we map to a specialized cell type: sheath cells. These cells accumulate misfolded protein at elevated temperature, leading to a cascading structural failure of the notochord and anatomic defects. Our study demonstrates that whole-animal single-cell RNA-seq can identify mechanisms for developmental robustness and pinpoint cell types that constitute key failure points.

Embryo-scale reverse genetics at single-cell resolution.

The maturation of single-cell transcriptomic technologies has facilitated the generation of comprehensive cellular atlases from whole embryos1-4. A majority of these data, however, has been collected from wild-type embryos without an appreciation for the latent variation that is present in development. Here we present the 'zebrafish single-cell atlas of perturbed embryos': single-cell transcriptomic data from 1,812 individually resolved developing zebrafish embryos, encompassing 19 timepoints, 23 genetic perturbations and a total of 3.2 million cells. The high degree of replication in our study (eight or more embryos per condition) enables us to estimate the variance in cell type abundance organism-wide and to detect perturbation-dependent deviance in cell type composition relative to wild-type embryos. Our approach is sensitive to rare cell types, resolving developmental trajectories and genetic dependencies in the cranial ganglia neurons, a cell population that comprises less than 1% of the embryo. Additionally, time-series profiling of individual mutants identified a group of brachyury-independent cells with strikingly similar transcriptomes to notochord sheath cells, leading to new hypotheses about early origins of the skull. We anticipate that standardized collection of high-resolution, organism-scale single-cell data from large numbers of individual embryos will enable mapping of the genetic dependencies of zebrafish cell types, while also addressing longstanding challenges in developmental genetics, including the cellular and transcriptional plasticity underlying phenotypic diversity across individuals.

Single-cell, whole-embryo phenotyping of mammalian developmental disorders.

Mouse models are a critical tool for studying human diseases, particularly developmental disorders1. However, conventional approaches for phenotyping may fail to detect subtle defects throughout the developing mouse2. Here we set out to establish single-cell RNA sequencing of the whole embryo as a scalable platform for the systematic phenotyping of mouse genetic models. We applied combinatorial indexing-based single-cell RNA sequencing3 to profile 101 embryos of 22 mutant and 4 wild-type genotypes at embryonic day 13.5, altogether profiling more than 1.6 million nuclei. The 22 mutants represent a range of anticipated phenotypic severities, from established multisystem disorders to deletions of individual regulatory regions4,5. We developed and applied several analytical frameworks for detecting differences in composition and/or gene expression across 52 cell types or trajectories. Some mutants exhibit changes in dozens of trajectories whereas others exhibit changes in only a few cell types. We also identify differences between widely used wild-type strains, compare phenotyping of gain- versus loss-of-function mutants and characterize deletions of topological associating domain boundaries. Notably, some changes are shared among mutants, suggesting that developmental pleiotropy might be 'decomposable' through further scaling of this approach. Overall, our findings show how single-cell profiling of whole embryos can enable the systematic molecular and cellular phenotypic characterization of mouse mutants with unprecedented breadth and resolution.

Predicting cellular responses to complex perturbations in high-throughput screens.

Recent advances in multiplexed single-cell transcriptomics experiments facilitate the high-throughput study of drug and genetic perturbations. However, an exhaustive exploration of the combinatorial perturbation space is experimentally unfeasible. Therefore, computational methods are needed to predict, interpret, and prioritize perturbations. Here, we present the compositional perturbation autoencoder (CPA), which combines the interpretability of linear models with the flexibility of deep-learning approaches for single-cell response modeling. CPA learns to in silico predict transcriptional perturbation response at the single-cell level for unseen dosages, cell types, time points, and species. Using newly generated single-cell drug combination data, we validate that CPA can predict unseen drug combinations while outperforming baseline models. Additionally, the architecture's modularity enables incorporating the chemical representation of the drugs, allowing the prediction of cellular response to completely unseen drugs. Furthermore, CPA is also applicable to genetic combinatorial screens. We demonstrate this by imputing in silico 5,329 missing combinations (97.6% of all possibilities) in a single-cell Perturb-seq experiment with diverse genetic interactions. We envision CPA will facilitate efficient experimental design and hypothesis generation by enabling in silico response prediction at the single-cell level and thus accelerate therapeutic applications using single-cell technologies.

High-capacity sample multiplexing for single cell chromatin accessibility profiling.

Single-cell chromatin accessibility has emerged as a powerful means of understanding the epigenetic landscape of diverse tissues and cell types, but profiling cells from many independent specimens is challenging and costly. Here we describe a novel approach, sciPlex-ATAC-seq, which uses unmodified DNA oligos as sample-specific nuclear labels, enabling the concurrent profiling of chromatin accessibility within single nuclei from virtually unlimited specimens or experimental conditions. We first demonstrate our method with a chemical epigenomics screen, in which we identify drug-altered distal regulatory sites predictive of compound- and dose-dependent effects on transcription. We then analyze cell type-specific chromatin changes in PBMCs from multiple donors responding to synthetic and allogeneic immune stimulation. We quantify stimulation-altered immune cell compositions and isolate the unique effects of allogeneic stimulation on chromatin accessibility specific to T-lymphocytes. Finally, we observe that impaired global chromatin decondensation often coincides with chemical inhibition of allogeneic T-cell activation.

Single-cell analysis of chromatin and expression reveals age- and sex-associated alterations in the human heart.

Sex differences and age-related changes in the human heart at the tissue, cell, and molecular level have been well-documented and many may be relevant for cardiovascular disease. However, how molecular programs within individual cell types vary across individuals by age and sex remains poorly characterized. To better understand this variation, we performed single-nucleus combinatorial indexing (sci) ATAC- and RNA-Seq in human heart samples from nine donors. We identify hundreds of differentially expressed genes by age and sex and find epigenetic signatures of variation in ATAC-Seq data in this discovery cohort. We then scale up our single-cell RNA-Seq analysis by combining our data with five recently published single nucleus RNA-Seq datasets of healthy adult hearts. We find variation such as metabolic alterations by sex and immune changes by age in differential expression tests, as well as alterations in abundance of cardiomyocytes by sex and neurons with age. In addition, we compare our adult-derived ATAC-Seq profiles to analogous fetal cell types to identify putative developmental-stage-specific regulatory factors. Finally, we train predictive models of cell-type-specific RNA expression levels utilizing ATAC-Seq profiles to link distal regulatory sequences to promoters, quantifying the predictive value of a simple TF-to-expression regulatory grammar and identifying cell-type-specific TFs. Our analysis represents the largest single-cell analysis of cardiac variation by age and sex to date and provides a resource for further study of healthy cardiac variation and transcriptional regulation at single-cell resolution.

High-Capacity Sample Multiplexing for Single Cell Chromatin Accessibility Profiling.

Single-cell chromatin accessibility has emerged as a powerful means of understanding the epigenetic landscape of diverse tissues and cell types, but profiling cells from many independent specimens is challenging and costly. Here we describe a novel approach, sciPlex-ATAC-seq, which uses unmodified DNA oligos as sample-specific nuclear labels, enabling the concurrent profiling of chromatin accessibility within single nuclei from virtually unlimited specimens or experimental conditions. We first demonstrate our method with a chemical epigenomics screen, in which we identify drug-altered distal regulatory sites predictive of compound- and dose-dependent effects on transcription. We then analyze cell type-specific chromatin changes in PBMCs from multiple donors responding to synthetic and allogeneic immune stimulation. We quantify stimulation-altered immune cell compositions and isolate the unique effects of allogeneic stimulation on chromatin accessibility specific to T-lymphocytes. Finally, we observe that impaired global chromatin decondensation often coincides with chemical inhibition of allogeneic T-cell activation.

Modulation of FGF pathway signaling and vascular differentiation using designed oligomeric assemblies.

Growth factors and cytokines signal by binding to the extracellular domains of their receptors and drive association and transphosphorylation of the receptor intracellular tyrosine kinase domains, initiating downstream signaling cascades. To enable systematic exploration of how receptor valency and geometry affects signaling outcomes, we designed cyclic homo-oligomers with up to 8 subunits using repeat protein building blocks that can be modularly extended. By incorporating a de novo designed fibroblast growth-factor receptor (FGFR) binding module into these scaffolds, we generated a series of synthetic signaling ligands that exhibit potent valency- and geometry-dependent Ca2+ release and MAPK pathway activation. The high specificity of the designed agonists reveal distinct roles for two FGFR splice variants in driving endothelial and mesenchymal cell fates during early vascular development. The ability to incorporate receptor binding domains and repeat extensions in a modular fashion makes our designed scaffolds broadly useful for probing and manipulating cellular signaling pathways.

Multipotent progenitors and hematopoietic stem cells arise independently from hemogenic endothelium in the mouse embryo.

During embryogenesis, waves of hematopoietic progenitors develop from hemogenic endothelium (HE) prior to the emergence of self-renewing hematopoietic stem cells (HSCs). Although previous studies have shown that yolk-sac-derived erythromyeloid progenitors and HSCs emerge from distinct populations of HE, it remains unknown whether the earliest lymphoid-competent progenitors, multipotent progenitors, and HSCs originate from common HE. In this study, we demonstrate by clonal assays and single-cell transcriptomics that rare HE with functional HSC potential in the early murine embryo are distinct from more abundant HE with multilineage hematopoietic potential that fail to generate HSCs. Specifically, HSC-competent HE are characterized by expression of CXCR4 surface marker and by higher expression of genes tied to arterial programs regulating HSC dormancy and self-renewal. Taken together, these findings suggest a revised model of developmental hematopoiesis in which the initial populations of multipotent progenitors and HSCs arise independently from HE with distinct phenotypic and transcriptional properties.

Embryo-scale, single-cell spatial transcriptomics.

Spatial patterns of gene expression manifest at scales ranging from local (e.g., cell-cell interactions) to global (e.g., body axis patterning). However, current spatial transcriptomics methods either average local contexts or are restricted to limited fields of view. Here, we introduce sci-Space, which retains single-cell resolution while resolving spatial heterogeneity at larger scales. Applying sci-Space to developing mouse embryos, we captured approximate spatial coordinates and whole transcriptomes of about 120,000 nuclei. We identify thousands of genes exhibiting anatomically patterned expression, leverage spatial information to annotate cellular subtypes, show that cell types vary substantially in their extent of spatial patterning, and reveal correlations between pseudotime and the migratory patterns of differentiating neurons. Looking forward, we anticipate that sci-Space will facilitate the construction of spatially resolved single-cell atlases of mammalian development.

SARS-CoV-2 Epidemiology on a Public University Campus in Washington State.

BACKGROUND: We aimed to evaluate a testing program to facilitate control of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission at a large university and measure spread in the university community using viral genome sequencing. METHODS: Our prospective longitudinal study used remote contactless enrollment, daily mobile symptom and exposure tracking, and self-swab sample collection. Individuals were tested if the participant was exposed to a known SARS-CoV-2-infected person, developed new symptoms, or reported high-risk behavior (such as attending an indoor gathering without masking or social distancing), if a member of a group experiencing an outbreak, or at enrollment. Study participants included students, staff, and faculty at an urban public university during the Autumn quarter of 2020. RESULTS: We enrolled 16 476 individuals, performed 29 783 SARS-CoV-2 tests, and detected 236 infections. Seventy-five percent of positive cases reported at least 1 of the following: symptoms (60.8%), exposure (34.7%), or high-risk behaviors (21.5%). Greek community affiliation was the strongest risk factor for testing positive, and molecular epidemiology results suggest that specific large gatherings were responsible for several outbreaks. CONCLUSIONS: A testing program focused on individuals with symptoms and unvaccinated persons who participate in large campus gatherings may be effective as part of a comprehensive university-wide mitigation strategy to control the spread of SARS-CoV-2.

Massively multiplex chemical transcriptomics at single-cell resolution.

High-throughput chemical screens typically use coarse assays such as cell survival, limiting what can be learned about mechanisms of action, off-target effects, and heterogeneous responses. Here, we introduce "sci-Plex," which uses "nuclear hashing" to quantify global transcriptional responses to thousands of independent perturbations at single-cell resolution. As a proof of concept, we applied sci-Plex to screen three cancer cell lines exposed to 188 compounds. In total, we profiled ~650,000 single-cell transcriptomes across ~5000 independent samples in one experiment. Our results reveal substantial intercellular heterogeneity in response to specific compounds, commonalities in response to families of compounds, and insight into differential properties within families. In particular, our results with histone deacetylase inhibitors support the view that chromatin acts as an important reservoir of acetate in cancer cells.