Biology subjects

Regev, A.

Publications and source records attributed to Regev, A..

At least 109 records · Page 6Linked to original sources

bioRxiv2020

Scalable, multimodal profiling of chromatin accessibility and protein levels in single cells

Recent technological advances have enabled massively parallel chromatin profiling with single-cell Assay for Transposase Accessible Chromatin by sequencing (scATAC-seq) in thousands of individual cells. Here, we extend these approaches and present ATAC with Select Antigen Profiling by sequencing, ASAP-seq, a tool to simultaneously profile accessible chromatin and protein levels in thousands of single cells. Our approach pairs sparse scATAC-seq data with robust detection of hundreds of cell surface and intracellular protein markers and optional capture of mitochondrial DNA (mtDNA) for clonal tracking, thus concomitantly capturing three distinct modalities in single cells. Importantly, ASAP-seq uses a novel bridging approach that repurposes antibody:oligo conjugates designed for existing technologies that pair protein measurements with single cell RNA-seq. We demonstrate the utility of ASAP-seq by revealing coordinated and distinct changes in chromatin, RNA, and surface proteins during native hematopoietic differentiation, peripheral blood mononuclear cell stimulation, and as a combinatorial decoder and reporter of multiplexed perturbations in primary T cells.

genomics↗

bioRxiv2020

Multi-modal pooled Perturb-CITE-Seq screens in patient models define novel mechanisms of cancer immune evasion

Resistance to immune checkpoint inhibitors (ICI) that activate T cell mediated anti-tumor immunity is a key challenge in cancer therapy, yet the underlying mechanisms remain poorly understood. To further elucidate those, we developed a new approach, Perturb-CITE-seq, for pooled CRISPR perturbation screens with multi-modal RNA and protein single-cell profiling readout and applied it to screen patient-derived autologous melanoma and tumor infiltrating lymphocyte (TIL) co-cultures. We profiled RNA and 20 surface proteins in over 218,000 cells under ~750 perturbations, chosen by their membership in an immune evasion program that is associated with immunotherapy resistance in patients. Our screen recovered clinically-relevant resistance mechanisms concordantly reflected in RNA, protein and perturbation effects on susceptibility to T cell mediated killing. These were organized in eight co-functional modules whose perturbation distinctly affect four co-regulated programs associated with immune evasion. Among these were defects in the IFN{gamma}-JAK/STAT pathway and in antigen presentation, and several novel mechanisms, including loss or downregulation of CD58, a surface protein without known mouse homolog. Leveraging the rich profiles in our screen, we found that loss of CD58 did not compromise MHC protein expression and that CD58 was not transcriptionally induced by the IFN{gamma} pathway, allowing us to distinguish it as a novel mechanism of immune resistance. We further show that loss of CD58 on cancer cells conferred immune evasion across multiple T cell and Natural Killer cell patient co-culture models. Notably, CD58 is downregulated in tumors with resistance to immunotherapy in melanoma patients. Our work identifies novel mechanisms at the nexus of immune evasion and drug resistance and provides a general framework for deciphering complex mechanisms by large-scale perturbation screens with multi-modal singlecell profiles, including in systems consisting of multiple cell types.

genomics↗

bioRxiv2020

Deep learning and alignment of spatially-resolved whole transcriptomes of single cells in the mouse brain with Tangram

Charting a biological atlas of an organ, such as the brain, requires us to spatially-resolve whole transcriptomes of single cells, and to relate such cellular features to the histological and anatomical scales. Single-cell and single-nucleus RNA-Seq (sc/snRNA-seq) can map cells comprehensively5,6, but relating those to their histological and anatomical positions in the context of an organs common coordinate framework remains a major challenge and barrier to the construction of a cell atlas7-10. Conversely, Spatial Transcriptomics allows for in-situ measurements11-13 at the histological level, but at lower spatial resolution and with limited sensitivity. Targeted in situ technologies1-3 solve both issues, but are limited in gene throughput which impedes profiling of the entire transcriptome. Finally, as samples are collected for profiling, their registration to anatomical atlases often require human supervision, which is a major obstacle to build pipelines at scale. Here, we demonstrate spatial mapping of cells, histology, and anatomy in the somatomotor area and the visual area of the healthy adult mouse brain. We devise Tangram, a method that aligns snRNA-seq data to various forms of spatial data collected from the same brain region, including MERFISH1, STARmap2, smFISH3, and Spatial Transcriptomics4 (Visium), as well as histological images and public atlases. Tangram can map any type of sc/snRNA-seq data, including multi-modal data such as SHARE-seq data5, which we used to reveal spatial patterns of chromatin accessibility. We equipped Tangram with a deep learning computer vision pipeline, which allows for automatic identification of anatomical annotations on histological images of mouse brain. By doing so, Tangram reconstructs a genome-wide, anatomically-integrated, spatial map of the visual and somatomotor area with [~]30,000 genes at single-cell resolution, revealing spatial gene expression and chromatin accessibility patterning beyond current limitation of in-situ technologies.

genomics↗

bioRxiv2020

L1CAM is not Associated with Extracellular Vesicles in Human Cerebrospinal Fluid or Plasma

Neuron-derived extracellular vesicles (NDEVs) present a tremendous opportunity to learn about the biochemistry of brain cells in living patients. L1CAM is a transmembrane protein expressed in neurons that is presumed to be found on NDEVs in human biofluids. Previous studies have used L1CAM immuno-isolation from human plasma to isolate NDEVs for neurodegenerative disease diagnostics. We developed a panel of ultrasensitive Single Molecule Array (Simoa) assays for known EV markers, as well as L1CAM, and applied it to study EVs in human plasma and cerebrospinal fluid (CSF). We fractionated plasma and CSF by size exclusion chromatography (SEC) and density gradient centrifugation (DGC) to separate EVs from free proteins. We observed that L1CAM did not elute in the EV fractions, but rather eluted in the free protein fractions. We found that L1CAM is present as a free protein in human plasma and CSF, possibly due to proteolytic cleavage and/or alternative splicing. We further demonstrate that the isoforms found in CSF and plasma are different. These data collectively establish that L1CAM in plasma is not EV associated and should therefore not be used for NDEV isolation. Importantly, the framework and tools described herein will allow for evaluation of other potential candidate markers for isolation of NDEVs.

neuroscience↗

bioRxiv2020

Mapping multicellular programs from single-cell profiles

Tissue homeostasis relies on orchestrated multicellular circuits, where interactions between different cell types dynamically balance tissue function. While single-cell genomics identifies tissues cellular components, deciphering their coordinated action remains a major challenge. Here, we tackle this problem through a new framework of multicellular programs: combinations of distinct cellular programs in different cell types that are coordinated together in the tissue, thus forming a higher order functional unit at the tissue, rather than only cell, level. We develop the open-access DIALOGUE algorithm to systematically uncover such multi-cellular programs not only from spatial data, but even from tissue dissociated and profiled as single cells, e.g., by single-cell RNA-Seq. Tested on spatial transcriptomes from the mouse hypothalamus, DIALOGUE recovered spatial information, predicted the properties of a cells environment only based on its transcriptome, and identified multicellular programs that mark animal behavior. Applied to brain samples and colon biopsies profiled by scRNA-Seq, DIALOGUE identified multicellular configurations that mark Alzheimers disease and ulcerative colitis (UC), including a program spanning five cell types that is predictive of response to anti-TNF therapy in UC patients and enriched for UC risk genes from GWAS, each acting in different cell types, but all cells acting in concert. Taken together, our study provides a novel conceptual and methodological framework to unravel multicellular regulation in health and disease.

systems biology↗

bioRxiv2020

Molecular Logic of Cellular Diversification in the Mammalian Cerebral Cortex

ABSTRACTThe neocortex has an unparalleled diversity of cell types, which are generated during development through a series of temporally orchestrated events that are under tight evolutionary constraint and are critical for proper cortical assembly and function. However, the molecular logic that governs the establishment and organization of cortical cell types remains elusive, largely due to the large number of cell classes undergoing dynamic cell-state transitions over extended developmental timelines. Here, we have generated a comprehensive single-cell RNA-seq and single-cell ATAC-seq atlas of the developing mouse neocortex, sampled every day throughout embryonic corticogenesis. We computationally reconstruct developmental trajectories across the diversity of cortical cell classes, and infer the gene regulatory programs that accompany their lineage bifurcation decisions and their differentiation trajectories. Finally, we demonstrate how this developmental map pinpoints the origin of lineage-specific developmental abnormalities linked to aberrant corticogenesis in mutant animals. The data provides the first global picture of the regulatory mechanisms governing cellular diversification in the neocortex.Competing Interest StatementP.A. is a SAB member in System 1 Biosciences and Foresite Labs and is a co-founder of FL60. A.R. is a co-founder of and equity holder in Celsius Therapeutics, equity holder in Immunitas, and a SAB member of ThermoFisher Scientific, Syros Pharmaceuticlas, Asimov, and Neogene Therapeutics.View Full Text

developmental biology↗

bioRxiv2020

RAAS blockade, kidney disease, and expression of ACE2, the entry receptor for SARS-CoV-2, in kidney epithelial and endothelial cells

SARS-CoV-2, the coronavirus that causes COVID-19, binds to angiotensin-converting enzyme 2 (ACE2) on human cells. Beyond the lung, COVID-19 impacts diverse tissues including the kidney. ACE2 is a key member of the Renin-Angiotensin-Aldosterone System (RAAS) which regulates blood pressure, largely through its effects on the kidney. RAAS blockers such as ACE inhibitors (ACEi) and Angiotensin Receptor Blockers (ARBs) are widely used therapies for hypertension, cardiovascular and chronic kidney diseases, and therefore, there is intense interest in their effect on ACE2 expression and its implications for SARS-CoV-2 pathogenicity. Here, we analyzed single-cell and single-nucleus RNA-seq of human kidney to interrogate the association of ACEi/ARB use with ACE2 expression in specific cell types. First, we performed an integrated analysis aggregating 176,421 cells across 49 donors, 8 studies and 8 centers, and adjusting for sex, age, donor and center effects, to assess the relationship of ACE2 with age and sex at baseline. We observed a statistically significant increase in ACE2 expression in tubular epithelial cells of the thin loop of Henle (tLoH) in males relative to females at younger ages, the trend reversing, and losing significance with older ages. ACE2 expression in tLoH increases with age in females, with an opposite, weak effect in males. In an independent cohort, we detected a statistically significant increase in ACE2 expression with ACEi/ARB use in epithelial cells of the proximal tubule and thick ascending limb, and endothelial cells, but the association was confounded in this small cohort by the underlying disease. Our study illuminates the dynamics of ACE2 expression in specific kidney cells, with implications for SARS-CoV-2 entry and pathogenicity.

genomics↗

bioRxiv2020

Chromatin potential identified by shared single cell profiling of RNA and chromatin

Cell differentiation and function are regulated across multiple layers of gene regulation, including the modulation of gene expression by changes in chromatin accessibility. However, differentiation is an asynchronous process precluding a temporal understanding of the regulatory events leading to cell fate commitment. Here, we developed SHARE-seq, a highly scalable approach for measurement of chromatin accessibility and gene expression within the same single cell. Using 34,774 joint profiles from mouse skin, we develop a computational strategy to identify cis-regulatory interactions and define Domains of Regulatory Chromatin (DORCs), which significantly overlap with super-enhancers. We show that during lineage commitment, chromatin accessibility at DORCs precedes gene expression, suggesting changes in chromatin accessibility may prime cells for lineage commitment. We therefore develop a computational strategy (chromatin potential) to quantify chromatin lineage-priming and predict cell fate outcomes. Together, SHARE-seq provides an extensible platform to study regulatory circuitry across diverse cells within tissues.

genomics↗

bioRxiv2020

Cycling cancer persister cells arise from lineages with distinct transcriptional and metabolic programs

Non-genetic mechanisms have recently emerged as important drivers of therapy failure in cancer (Salgia and Kulkarni, 2018), where some cancer cells can enter a reversible drug-tolerant persister state in response to treatment (Vallette et al., 2019). While most cancer persisters, like their bacterial counterparts, remain arrested in the presence of drug, a rare subset of cancer persisters can re-enter the cell cycle under constitutive drug treatment (Sharma et al., 2010). Little is known about the non-genetic mechanisms that enable cancer persisters to maintain proliferative capacity in the presence of drug. Here, using time-lapse imaging, we found that cycling persisters emerge early in the course of treatment of EGFR-mutant lung cancer cells with the EGFR inhibitor osimertinib. To study this rare, transiently-resistant, proliferative persister population we developed Watermelon, a new high-complexity expressed barcode lentiviral library for simultaneous tracing each cells clonal origin, proliferative state, and transcriptional state. Analysis of Watermelon-transduced PC9 cells demonstrated that cycling and non-cycling persisters arise from different pre-existing cell lineages with distinct transcriptional and metabolic programs. The proliferative capacity of persisters is associated with an upregulation of antioxidant gene programs and a metabolic shift to fatty acid oxidation in specific subpopulations of tumor cells. Mitigating oxidative stress or blocking metabolic reprograming significantly alters the fraction of cycling persister cells. In human tumors, programs associated with cycling persisters were induced in malignant cells in response to multiple tyrosine kinase inhibitors. The Watermelon system enabled the identification of rare persister lineages, that are preferentially poised through specific gene programs to proliferate under drug pressure, thus exposing new vulnerabilities that can be targeted to delay or even prevent disease recurrence.

cancer biology↗

bioRxiv2020

Expansion Sequencing: Spatially Precise In Situ Transcriptomics in Intact Biological Systems

AbstractMethods for highly multiplexed RNA imaging are limited in spatial resolution, and thus in their ability to localize transcripts to nanoscale and subcellular compartments. We adapt expansion microscopy, which physically expands biological specimens, for long-read untargeted and targeted in situ RNA sequencing. We applied untargeted expansion sequencing (ExSeq) to mouse brain, yielding readout of thousands of genes, including splice variants and novel transcripts. Targeted ExSeq yielded nanoscale-resolution maps of RNAs throughout dendrites and spines in neurons of the mouse hippocampus, revealing patterns across multiple cell types; layer-specific cell types across mouse visual cortex; and the organization and position-dependent states of tumor and immune cells in a human metastatic breast cancer biopsy. Thus ExSeq enables highly multiplexed mapping of RNAs, from nanoscale to system scale. One Sentence SummaryIn situ sequencing of physically expanded specimens enables multiplexed mapping of RNAs at nanoscale, subcellular resolution.

genomics↗

bioRxiv2020

LAMP-Seq: Population-Scale COVID-19 Diagnostics Using a Compressed Barcode Space

The ongoing SARS-CoV-2 pandemic has already caused devastating losses. Exponential spread can be slowed by social distancing and population-wide isolation measures, but those place a tremendous burden on society, and, once lifted, exponential spread can re-emerge. Regular population-scale testing, combined with contact tracing and case isolation, should help break the cycle of transmission, but current detection strategies are not capable of such large-scale processing. Here we present a protocol for LAMP-Seq, a barcoded Reverse-Transcription Loop-mediated Isothermal Amplification (RT-LAMP) method that is highly scalable. Individual samples are stabilized, inactivated, and amplified in three isothermal heat steps, generating barcoded amplicons that can be pooled and analyzed en masse by sequencing. Using unique barcode combinations per sample from a compressed barcode space enables extensive pooling, potentially further reducing cost and simplifying logistics. We validated LAMP-Seq on 28 clinical samples, empirically optimized the protocol and barcode design, and performed initial safety evaluation. Relying on world-wide infrastructure for next-generation sequencing, and in the context of population-wide sample collection, LAMP-Seq could be scaled to analyze millions of samples per day.

molecular biology↗

bioRxiv2020

Single cell profiling of immature human postnatal thymocytes resolves the complexity of intra-thymic lineage differentiation and thymus seeding precursors.

During postnatal life, thymopoiesis depends on the continuous colonization of the thymus by bone marrow derived hematopoietic progenitors that migrate through the bloodstream. In human, the nature of these thymus immigrants has remained unclear. Here, we employ single-cell RNA sequencing on approximately 70.000 CD34+ thymocytes to unravel the heterogeneity of the human immature postnatal thymocytes. Integration of bone marrow and peripheral blood precursors datasets identifies several putative thymus seeding precursors that display heterogeneity for currently used surface markers as revealed by CITEseq. Besides T cell precursors, we discover branches of intrathymic developing dendritic cells with predominantly plasmacytoid DCs. Trough trajectory inference, we delineate the transcriptional dynamics underlying early human T-lineage development from which we predict transcription factor modules that drive stage-specific steps of human T cell development. Thus, our work resolves the heterogeneity of thymus seeding precursors in human and reveals the molecular mechanisms that drive their in vivo cell fate.

immunology↗

bioRxiv2020

Transcriptional mediators of treatment resistance in lethal prostate cancer

Metastatic castration resistant prostate cancer (mCRPC) is primarily treated with therapies that prevent transcriptional activity of the androgen receptor (AR), cause DNA damage, or prevent cell division. Clinical resistance to these therapies, including second-generation androgen-targeting compounds such as enzalutamide and abiraterone, is nearly universal. Other treatment modalities, including immune checkpoint inhibitors, have provided minimal benefit except in rare subsets of patients1,2. Both tumour intrinsic and extrinsic cellular programs contributing to therapeutic resistance remain areas of active investigation. Here we use full-length single-cell RNA-sequencing (scRNA-seq) to identify the transcriptional states of cancer and immune cells in the mCRPC microenvironment. Within cancer cells, we identified transcriptional patterns that mediate a significant proportion of inherited risk for prostate cancer, extensive heterogeneity in AR splicing within and between tumours, and vastly divergent regulatory programs between adenocarcinoma and small cell carcinoma. Moreover, upregulation of TGF-{beta} signalling and epithelial-mesenchymal transition (EMT) were both associated with resistance to enzalutamide. We found that some lymph node metastases, but no bone metastases, were heavily infiltrated by dysfunctional CD8+ T cells, including cells undergoing dramatic clonal expansion during enzalutamide treatment. Our findings suggest avenues for rational therapeutic approaches targeting both tumour-intrinsic and immunological pathways to combat resistance to current treatment options.

genomics↗

bioRxiv2020

A transcriptomic atlas of the mouse cerebellum reveals regional specializations and novel cell types

The cerebellum is a well-studied brain structure with diverse roles in motor learning, coordination, cognition, and autonomic regulation. Nonetheless, a complete inventory of cerebellar cell types is presently lacking. We used high-throughput transcriptional profiling to molecularly define cell types across individual lobules of the adult mouse cerebellum. Purkinje and granule neurons showed considerable regional specialization, with the greatest diversity occurring in the posterior lobules. For multiple types of cerebellar interneurons, the molecular variation within each type was more continuous, rather than discrete. For the unipolar brush cells (UBCs)--an interneuron population previously subdivided into two discrete populations--the continuous variation in gene expression was associated with a graded continuum of electrophysiological properties. Most surprisingly, we found that molecular layer interneurons (MLIs) were composed of two molecularly and functionally distinct types. Both show a continuum of morphological variation through the thickness of the molecular layer, but electrophysiological recordings revealed marked differences between the two types in spontaneous firing, excitability, and electrical coupling. Together, these findings provide the first comprehensive cellular atlas of the cerebellar cortex, and outline a methodological and conceptual framework for the integration of molecular, morphological, and physiological ontologies for defining brain cell types.

genomics↗

bioRxiv2020

Thousands of novel unannotated proteins expand the MHC I immunopeptidome in cancer

Tumor epitopes - peptides that are presented on surface-bound MHC I proteins - provide targets for cancer immunotherapy and have been identified extensively in the annotated protein-coding regions of the genome. Motivated by the recent discovery of translated novel unannotated open reading frames (nuORFs) using ribosome profiling (Ribo-seq), we hypothesized that cancer-associated processes could generate nuORFs that can serve as a new source of tumor antigens that harbor somatic mutations or show tumor-specific expression. To identify cancer-specific nuORFs, we generated Ribo-seq profiles for 29 malignant and healthy samples, developed a sensitive analytic approach for hierarchical ORF prediction, and constructed a high-confidence database of translated nuORFs across tissues. Peptides from 3,555 unique translated nuORFs were presented on MHC I, based on analysis of an extensive dataset of MHC I-bound peptides detected by mass spectrometry, with >20-fold more nuORF peptides detected in the MHC I immunopeptidomes compared to whole proteomes. We further detected somatic mutations in nuORFs of cancer samples and identified nuORFs with tumor-specific translation in melanoma, chronic lymphocytic leukemia and glioblastoma. NuORFs thus expand the pool of MHC I-presented, tumor-specific peptides, targetable by immunotherapies.

cancer biology↗

bioRxiv2020

CELL ATLAS OF THE HUMAN FOVEA AND PERIPHERAL RETINA

Most irreversible blindness results from retinal disease. To advance our understanding of the etiology of blinding diseases, we used single-cell RNA-sequencing (scRNA-seq) to analyze the transcriptomes of [~]85,000 cells from the fovea and peripheral retina of seven adult human donors. Utilizing computational methods, we identified 58 cell types within 6 classes: photoreceptor, horizontal, bipolar, amacrine, retinal ganglion and non-neuronal cells. Nearly all types are shared between the two retinal regions, but there are notable differences in gene expression and proportions between foveal and peripheral cohorts of shared types. We then used the human retinal atlas to map expression of 636 genes implicated as causes of or risk factors for blinding diseases. Many are expressed in striking cell class-, type-, or region-specific patterns. Finally, we compared gene expression signatures of cell types between human and the cynomolgus macaque monkey, Macaca fascicularis. We show that over 90% of human types correspond transcriptomically to those previously identified in macaque, and that expression of disease-related genes is largely conserved between the two species. These results validate the use of the macaque for modeling blinding disease, and provide a foundation for investigating molecular mechanisms underlying visual processing.

neuroscience↗

bioRxiv2020

Cell Atlas of Aqueous Humor Outflow Pathways in Eyes of Humans and Four Model Species Provides Insights into Glaucoma Pathogenesis

Increased intraocular pressure (IOP) represents a major risk factor for glaucoma, a prevalent eye disease characterized by death of retinal ganglion cells that carry information from the eye to the brain; lowering IOP is the only proven treatment strategy to delay disease progression. The main determinant of IOP is the equilibrium between production and drainage of aqueous humor, with compromised drainage generally viewed as the primary contributor to dangerous IOP elevations. Drainage occurs through two pathways in the anterior segment of the eye, called conventional and uveoscleral. To gain insights into the cell types that comprise these pathways, we used high-throughput single cell RNA sequencing (scRNA-seq). From [~]24,000 single cell transcriptomes, we identified 19 cell types with molecular markers for each and used histological methods to localize each type. We then performed similar analyses on four organisms used for experimental studies of IOP dynamics and glaucoma: cynomolgus macaque (Macaca fascicularis), rhesus macaque (Macaca mulatta), pig (Sus scrofa) and mouse (Mus musculus). Many human cell types had counterparts in these models, but differences in cell types and gene expression were evident. Finally, we identified the cell types that express genes implicated in glaucoma in all five species. Together, our results provide foundations for investigating the pathogenesis of glaucoma, and for using model systems to assess mechanisms and potential interventions.

cell biology↗

bioRxiv2020

In Silico Modeling of Metabolic State in Single Th17 Cells Reveals Novel Regulators of Inflammation and Autoimmunity

Cellular metabolism, a key regulator of immune responses, is difficult to study with current technologies in individual cells Here, we present Compass, an algorithm to characterize the metabolic state of cells based on single-cell RNA-Seq and flux balance analysis. We applied Compass to associate metabolic states with functional variability (pathogenic potential) amongst Th17 cells and recovered a metabolic switch between glycolysis and fatty acid oxidation, akin to known differences between Th17 and Treg cells, as well as novel targets in amino-acid pathways, which we tested through targeted metabolic assays. Compass further predicted a particular glycolytic reaction (phosphoglycerate mutase -- PGAM) that promotes an anti-inflammatory Th17 phenotype, contrary to the common understanding of glycolysis as pro-inflammatory. We demonstrate that PGAM inhibition leads non-pathogenic Th17 cells to adopt a pro-inflammatory transcriptome and induce autoimmunity in vivo. Compass is broadly applicable for characterizing metabolic states of cells and relating metabolic heterogeneity to other cellular phenotypes.

genomics↗