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Wang B, Ma T, Chen T, Nguyen T, Crouse E, Fleming SJ, Walker AS, Valakh V, Nehme R, Miller EW, Farhi SL, Babadi M. Robust self-supervised denoising of voltage imaging data using CellMincer. bioRxiv 2024:2024.04.12.589298. [PMID: 38659950 PMCID: PMC11042234 DOI: 10.1101/2024.04.12.589298] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/26/2024]
Abstract
Voltage imaging enables high-throughput investigation of neuronal activity, yet its utility is often constrained by a low signal-to-noise ratio (SNR). Conventional denoising algorithms, such as those based on matrix factorization, impose limiting assumptions about the noise process and the spatiotemporal structure of the signal. While deep learning based denoising techniques offer greater adaptability, existing approaches fail to fully exploit the fast temporal dynamics and unique short- and long-range dependencies within voltage imaging datasets. Here, we introduce CellMincer, a novel self-supervised deep learning method designed specifically for denoising voltage imaging datasets. CellMincer operates on the principle of masking and predicting sparse sets of pixels across short temporal windows and conditions the denoiser on precomputed spatiotemporal auto-correlations to effectively model long-range dependencies without the need for large temporal denoising contexts. We develop and utilize a physics-based simulation framework to generate realistic datasets for rigorous hyperparameter optimization and ablation studies, highlighting the key role of conditioning the denoiser on precomputed spatiotemporal auto-correlations to achieve 3-fold further reduction in noise. Comprehensive benchmarking on both simulated and real voltage imaging datasets, including those with paired patch-clamp electrophysiology (EP) as ground truth, demonstrates CellMincer's state-of-the-art performance. It achieves substantial noise reduction across the entire frequency spectrum, enhanced detection of subthreshold events, and superior cross-correlation with ground-truth EP recordings. Finally, we demonstrate how CellMincer's addition to a typical voltage imaging data analysis workflow improves neuronal segmentation, peak detection, and ultimately leads to significantly enhanced separation of functional phenotypes.
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Affiliation(s)
- Brice Wang
- Data Sciences Platform (DSP), Broad Institute of MIT and Harvard, Cambridge, MA
| | - Tianle Ma
- Data Sciences Platform (DSP), Broad Institute of MIT and Harvard, Cambridge, MA
- Department of Computer Science and Engineering, Oakland University, Rochester, MI
| | - Theresa Chen
- Spatial Technology Platform (STP), Broad Institute of MIT and Harvard, Cambridge, MA
- Stanley Center for Psychiatric Research at the Broad Institute of MIT and Harvard, Cambridge, MA
| | - Trinh Nguyen
- Spatial Technology Platform (STP), Broad Institute of MIT and Harvard, Cambridge, MA
| | - Ethan Crouse
- Stanley Center for Psychiatric Research at the Broad Institute of MIT and Harvard, Cambridge, MA
| | - Stephen J. Fleming
- Data Sciences Platform (DSP), Broad Institute of MIT and Harvard, Cambridge, MA
| | - Alison S. Walker
- Departments of Molecular & Cell Biology and Chemistry and Helen Wills Neuroscience Institute, UC Berkeley
| | - Vera Valakh
- Spatial Technology Platform (STP), Broad Institute of MIT and Harvard, Cambridge, MA
- Stanley Center for Psychiatric Research at the Broad Institute of MIT and Harvard, Cambridge, MA
| | - Ralda Nehme
- Stanley Center for Psychiatric Research at the Broad Institute of MIT and Harvard, Cambridge, MA
| | - Evan W. Miller
- Departments of Molecular & Cell Biology and Chemistry and Helen Wills Neuroscience Institute, UC Berkeley
| | - Samouil L. Farhi
- Spatial Technology Platform (STP), Broad Institute of MIT and Harvard, Cambridge, MA
| | - Mehrtash Babadi
- Data Sciences Platform (DSP), Broad Institute of MIT and Harvard, Cambridge, MA
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2
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Al'Khafaji AM, Smith JT, Garimella KV, Babadi M, Popic V, Sade-Feldman M, Gatzen M, Sarkizova S, Schwartz MA, Blaum EM, Day A, Costello M, Bowers T, Gabriel S, Banks E, Philippakis AA, Boland GM, Blainey PC, Hacohen N. High-throughput RNA isoform sequencing using programmed cDNA concatenation. Nat Biotechnol 2024; 42:582-586. [PMID: 37291427 DOI: 10.1038/s41587-023-01815-7] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Accepted: 05/02/2023] [Indexed: 06/10/2023]
Abstract
Full-length RNA-sequencing methods using long-read technologies can capture complete transcript isoforms, but their throughput is limited. We introduce multiplexed arrays isoform sequencing (MAS-ISO-seq), a technique for programmably concatenating complementary DNAs (cDNAs) into molecules optimal for long-read sequencing, increasing the throughput >15-fold to nearly 40 million cDNA reads per run on the Sequel IIe sequencer. When applied to single-cell RNA sequencing of tumor-infiltrating T cells, MAS-ISO-seq demonstrated a 12- to 32-fold increase in the discovery of differentially spliced genes.
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Affiliation(s)
| | | | | | | | | | - Moshe Sade-Feldman
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA
| | | | | | - Marc A Schwartz
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
- Division of Hematology/Oncology, Boston Children's Hospital, Boston, MA, USA
- Department of Pediatric Oncology, Dana Farber Cancer Institute, Boston, MA, USA
| | - Emily M Blaum
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA
| | - Allyson Day
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | - Tera Bowers
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | - Eric Banks
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | - Genevieve M Boland
- Division of Surgical Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Paul C Blainey
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
- Koch Institute for Integrative Cancer Research at the Massachusetts Institute of Technology, Cambridge, MA, USA.
| | - Nir Hacohen
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Medicine, Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA.
- Harvard Medical School, Boston, MA, USA.
- Center for Immunology and Inflammatory Diseases, Massachusetts General Hospital, Charlestown, MA, USA.
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3
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Xu Y, Fleming S, Tegtmeyer M, McCarroll SA, Babadi M. Modeling interpretable correspondence between cell state and perturbation response with CellCap. bioRxiv 2024:2024.03.14.585078. [PMID: 38558987 PMCID: PMC10979976 DOI: 10.1101/2024.03.14.585078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Single-cell transcriptomics, in conjunction with genetic and compound perturbations, offers a robust approach for exploring cellular behaviors in diverse contexts. Such experiments allow uncovering cell-state-specific responses to perturbations, a crucial aspect in unraveling the intricate molecular mechanisms governing cellular behavior and potentially discovering novel regulatory pathways and therapeutic targets. However, prevailing computational methods predominantly focus on predicting average cellular responses, disregarding the inherent response heterogeneity associated with cell state diversity. In this study, we present CellCap, a deep generative model designed for the end-to-end analysis of single-cell perturbation experiments. CellCap employs sparse dictionary learning in a latent space to deconstruct cell-state-specific perturbation responses into a set of transcriptional response programs. These programs are then utilized by each perturbation condition and each cell at varying degrees. The incorporation of specific model design choices, such as dot-product cross-attention between cell states and response programs, along with a linearly-decoded latent space, underlay the interpretation power of CellCap. We evaluate CellCap's model interpretability through multiple simulated scenarios and apply it to two real single-cell perturbation datasets. These datasets feature either heterogeneous cellular populations or a complex experimental setup. Our results demonstrate that CellCap successfully uncovers the relationship between cell state and perturbation response, unveiling novel insights overlooked in previous analyses. The model's interpretability, coupled with its effectiveness in capturing heterogeneous responses, positions CellCap as a valuable tool for advancing our understanding of cellular behaviors in the context of perturbation experiments.
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Affiliation(s)
- Yang Xu
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA
| | - Stephen Fleming
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA
| | - Matthew Tegtmeyer
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA
- Present address: Department of Biological Sciences, Purdue University, West Lafayette, IN
| | - Steven A. McCarroll
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA
- Department of Genetics, Harvard Medical School, Boston MA
| | - Mehrtash Babadi
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA
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4
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Babadi M, Fu JM, Lee SK, Smirnov AN, Gauthier LD, Walker M, Benjamin DI, Zhao X, Karczewski KJ, Wong I, Collins RL, Sanchis-Juan A, Brand H, Banks E, Talkowski ME. Author Correction: GATK-gCNV enables the discovery of rare copy number variants from exome sequencing data. Nat Genet 2024; 56:553. [PMID: 38263447 DOI: 10.1038/s41588-024-01663-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2024]
Affiliation(s)
- Mehrtash Babadi
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Jack M Fu
- Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Samuel K Lee
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Andrey N Smirnov
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Laura D Gauthier
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Mark Walker
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - David I Benjamin
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Xuefang Zhao
- Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Konrad J Karczewski
- Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Isaac Wong
- Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Ryan L Collins
- Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Alba Sanchis-Juan
- Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Harrison Brand
- Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Eric Banks
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Michael E Talkowski
- Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
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Moshkov N, Bornholdt M, Benoit S, Smith M, McQuin C, Goodman A, Senft RA, Han Y, Babadi M, Horvath P, Cimini BA, Carpenter AE, Singh S, Caicedo JC. Learning representations for image-based profiling of perturbations. Nat Commun 2024; 15:1594. [PMID: 38383513 PMCID: PMC10881515 DOI: 10.1038/s41467-024-45999-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Accepted: 02/07/2024] [Indexed: 02/23/2024] Open
Abstract
Measuring the phenotypic effect of treatments on cells through imaging assays is an efficient and powerful way of studying cell biology, and requires computational methods for transforming images into quantitative data. Here, we present an improved strategy for learning representations of treatment effects from high-throughput imaging, following a causal interpretation. We use weakly supervised learning for modeling associations between images and treatments, and show that it encodes both confounding factors and phenotypic features in the learned representation. To facilitate their separation, we constructed a large training dataset with images from five different studies to maximize experimental diversity, following insights from our causal analysis. Training a model with this dataset successfully improves downstream performance, and produces a reusable convolutional network for image-based profiling, which we call Cell Painting CNN. We evaluated our strategy on three publicly available Cell Painting datasets, and observed that the Cell Painting CNN improves performance in downstream analysis up to 30% with respect to classical features, while also being more computationally efficient.
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Affiliation(s)
- Nikita Moshkov
- HUN-REN Biological Research Centre, 62 Temesvári krt, Szeged, 6726, Hungary
| | - Michael Bornholdt
- Broad Institute of MIT and Harvard, 415 Main St, Cambridge, MA, 02141, USA
| | - Santiago Benoit
- Broad Institute of MIT and Harvard, 415 Main St, Cambridge, MA, 02141, USA
- Carnegie Mellon University, 5000 Forbes Ave, Pittsburgh, PA, 15213, USA
| | - Matthew Smith
- Broad Institute of MIT and Harvard, 415 Main St, Cambridge, MA, 02141, USA
- Harvard College, 86 Brattle Street Cambridge, Cambridge, MA, 02138, USA
| | - Claire McQuin
- Broad Institute of MIT and Harvard, 415 Main St, Cambridge, MA, 02141, USA
| | - Allen Goodman
- Broad Institute of MIT and Harvard, 415 Main St, Cambridge, MA, 02141, USA
| | - Rebecca A Senft
- Broad Institute of MIT and Harvard, 415 Main St, Cambridge, MA, 02141, USA
| | - Yu Han
- Broad Institute of MIT and Harvard, 415 Main St, Cambridge, MA, 02141, USA
| | - Mehrtash Babadi
- Broad Institute of MIT and Harvard, 415 Main St, Cambridge, MA, 02141, USA
| | - Peter Horvath
- HUN-REN Biological Research Centre, 62 Temesvári krt, Szeged, 6726, Hungary
| | - Beth A Cimini
- Broad Institute of MIT and Harvard, 415 Main St, Cambridge, MA, 02141, USA
| | - Anne E Carpenter
- Broad Institute of MIT and Harvard, 415 Main St, Cambridge, MA, 02141, USA
| | - Shantanu Singh
- Broad Institute of MIT and Harvard, 415 Main St, Cambridge, MA, 02141, USA
| | - Juan C Caicedo
- Broad Institute of MIT and Harvard, 415 Main St, Cambridge, MA, 02141, USA.
- Morgridge Institute for Research, 330 N Orchard St, Madison, WI, 53715, USA.
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, 1300 University Ave, Madison, WI, 53706, USA.
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6
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Normandin E, Triana S, Raju SS, Lan TC, Lagerborg K, Rudy M, Adams GC, DeRuff KC, Logue J, Liu D, Strebinger D, Rao A, Messer KS, Sacks M, Adams RD, Janosko K, Kotliar D, Shah R, Crozier I, Rinn JL, Melé M, Honko AN, Zhang F, Babadi M, Luban J, Bennett RS, Shalek AK, Barkas N, Lin AE, Hensley LE, Sabeti PC, Siddle KJ. Natural history of Ebola virus disease in rhesus monkeys shows viral variant emergence dynamics and tissue-specific host responses. Cell Genom 2023; 3:100440. [PMID: 38169842 PMCID: PMC10759212 DOI: 10.1016/j.xgen.2023.100440] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Revised: 02/27/2023] [Accepted: 10/15/2023] [Indexed: 01/05/2024]
Abstract
Ebola virus (EBOV) causes Ebola virus disease (EVD), marked by severe hemorrhagic fever; however, the mechanisms underlying the disease remain unclear. To assess the molecular basis of EVD across time, we performed RNA sequencing on 17 tissues from a natural history study of 21 rhesus monkeys, developing new methods to characterize host-pathogen dynamics. We identified alterations in host gene expression with previously unknown tissue-specific changes, including downregulation of genes related to tissue connectivity. EBOV was widely disseminated throughout the body; using a new, broadly applicable deconvolution method, we found that viral load correlated with increased monocyte presence. Patterns of viral variation between tissues differentiated primary infections from compartmentalized infections, and several variants impacted viral fitness in a EBOV/Kikwit minigenome system, suggesting that functionally significant variants can emerge during early infection. This comprehensive portrait of host-pathogen dynamics in EVD illuminates new features of pathogenesis and establishes resources to study other emerging pathogens.
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Affiliation(s)
- Erica Normandin
- Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
- Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
| | - Sergio Triana
- Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
- Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA 02142, USA
- Department of Chemistry, Institute for Medical Engineering and Sciences (IMES), and Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA 02142, USA
- Ragon Institute of MGH, Harvard, and MIT, Cambridge, MA 02139, USA
| | - Siddharth S. Raju
- Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
- Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
| | - Tammy C.T. Lan
- Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
- Department of Molecular and Cellular Biology, Harvard University, Boston, MA, USA
| | - Kim Lagerborg
- Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
- Harvard Program in Biological and Biomedical Sciences, Harvard Medical School, Boston, MA, USA
| | - Melissa Rudy
- Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Gordon C. Adams
- Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
- Division of Infectious Diseases, Massachusetts General Hospital, Boston, MA 02114, USA
| | | | - James Logue
- Integrated Research Facility, Division of Clinical Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Frederick, MD 21702, USA
| | - David Liu
- Integrated Research Facility, Division of Clinical Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Frederick, MD 21702, USA
| | - Daniel Strebinger
- Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
- Howard Hughes Medical Institute, Chevy Chase, MD 20815-6789, USA
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Arya Rao
- Columbia University, New York, NY, USA
- Harvard/MIT MD-PhD Program, Harvard Medical School, Boston, MA 02115, USA
| | | | - Molly Sacks
- Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Ricky D. Adams
- Integrated Research Facility, Division of Clinical Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Frederick, MD 21702, USA
| | - Krisztina Janosko
- Integrated Research Facility, Division of Clinical Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Frederick, MD 21702, USA
| | - Dylan Kotliar
- Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
- Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
- Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA 02142, USA
| | - Rickey Shah
- Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Ian Crozier
- Clinical Monitoring Research Program Directorate, Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USA
| | - John L. Rinn
- Department of Biochemistry, University of Colorado Boulder, Boulder, CO 80303, USA
| | - Marta Melé
- Life Sciences Department, Barcelona Supercomputing Center, 08034 Barcelona, Catalonia, Spain
| | - Anna N. Honko
- Integrated Research Facility, Division of Clinical Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Frederick, MD 21702, USA
- National Emerging Infectious Diseases Laboratories, Boston University, Boston, MA 02118, USA
| | - Feng Zhang
- Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
- Howard Hughes Medical Institute, Chevy Chase, MD 20815-6789, USA
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Mehrtash Babadi
- Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Jeremy Luban
- Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
- Ragon Institute of MGH, Harvard, and MIT, Cambridge, MA 02139, USA
- Program in Molecular Medicine, University of Massachusetts Chan Medical School, Worcester, MA 01655, USA
| | - Richard S. Bennett
- Integrated Research Facility, Division of Clinical Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Frederick, MD 21702, USA
| | - Alex K. Shalek
- Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
- Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA 02142, USA
- Department of Chemistry, Institute for Medical Engineering and Sciences (IMES), and Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA 02142, USA
- Ragon Institute of MGH, Harvard, and MIT, Cambridge, MA 02139, USA
| | - Nikolaos Barkas
- Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Aaron E. Lin
- Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
- Harvard Program in Virology, Harvard Medical School, Boston, MA 02115, USA
- Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA
| | - Lisa E. Hensley
- Integrated Research Facility, Division of Clinical Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Frederick, MD 21702, USA
| | - Pardis C. Sabeti
- Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
- Howard Hughes Medical Institute, Chevy Chase, MD 20815-6789, USA
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Katherine J. Siddle
- Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
- Department of Molecular Microbiology and Immunology, Brown University, Providence, RI 02912, USA
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7
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Arduini A, Fleming SJ, Xiao L, Hall AW, Akkad AD, Chaffin M, Bendinelli KJ, Tucker NR, Papangeli I, Mantineo H, Babadi M, Stegmann CM, García-Cardeña G, Lindsay ME, Klattenhoff C, Ellinor PT. Transcriptional profile of the rat cardiovascular system at single cell resolution. bioRxiv 2023:2023.11.14.567085. [PMID: 38014050 PMCID: PMC10680727 DOI: 10.1101/2023.11.14.567085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
Background Despite the critical role of the cardiovascular system, our understanding of its cellular and transcriptional diversity remains limited. We therefore sought to characterize the cellular composition, phenotypes, molecular pathways, and communication networks between cell types at the tissue and sub-tissue level across the cardiovascular system of the healthy Wistar rat, an important model in preclinical cardiovascular research. We obtained high quality tissue samples under controlled conditions that reveal a level of cellular detail so far inaccessible in human studies. Methods and Results We performed single nucleus RNA-sequencing in 78 samples in 10 distinct regions including the four chambers of the heart, ventricular septum, sinoatrial node, atrioventricular node, aorta, pulmonary artery, and pulmonary veins (PV), which produced an aggregate map of 505,835 nuclei. We identified 26 distinct cell types and additional subtypes, including a number of rare cell types such as PV cardiomyocytes and non-myelinating Schwann cells (NMSCs), and unique groups of vascular smooth muscle cells (VSMCs), endothelial cells (ECs) and fibroblasts (FBs), which gave rise to a detailed cell type distribution across tissues. We demonstrated differences in the cellular composition across different cardiac regions and tissue-specific differences in transcription for each cell type, highlighting the molecular diversity and complex tissue architecture of the cardiovascular system. Specifically, we observed great transcriptional heterogeneities among ECs and FBs. Importantly, several cell subtypes had a unique regional localization such as a subtype of VSMCs enriched in the large vasculature. We found the cellular makeup of PV tissue is closer to heart tissue than to the large arteries. We further explored the ligand-receptor repertoire across cell clusters and tissues, and observed tissue-enriched cellular communication networks, including heightened Nppa - Npr1 / 2 / 3 signaling in the sinoatrial node. Conclusions Through a large single nucleus sequencing effort encompassing over 500,000 nuclei, we broadened our understanding of cellular transcription in the healthy cardiovascular system. The existence of tissue-restricted cellular phenotypes suggests regional regulation of cardiovascular physiology. The overall conservation in gene expression and molecular pathways across rat and human cell types, together with our detailed transcriptional characterization of each cell type, offers the potential to identify novel therapeutic targets and improve preclinical models of cardiovascular disease.
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8
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Fleming SJ, Chaffin MD, Arduini A, Akkad AD, Banks E, Marioni JC, Philippakis AA, Ellinor PT, Babadi M. Unsupervised removal of systematic background noise from droplet-based single-cell experiments using CellBender. Nat Methods 2023; 20:1323-1335. [PMID: 37550580 DOI: 10.1038/s41592-023-01943-7] [Citation(s) in RCA: 45] [Impact Index Per Article: 45.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2022] [Accepted: 06/13/2023] [Indexed: 08/09/2023]
Abstract
Droplet-based single-cell assays, including single-cell RNA sequencing (scRNA-seq), single-nucleus RNA sequencing (snRNA-seq) and cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq), generate considerable background noise counts, the hallmark of which is nonzero counts in cell-free droplets and off-target gene expression in unexpected cell types. Such systematic background noise can lead to batch effects and spurious differential gene expression results. Here we develop a deep generative model based on the phenomenology of noise generation in droplet-based assays. The proposed model accurately distinguishes cell-containing droplets from cell-free droplets, learns the background noise profile and provides noise-free quantification in an end-to-end fashion. We implement this approach in the scalable and robust open-source software package CellBender. Analysis of simulated data demonstrates that CellBender operates near the theoretically optimal denoising limit. Extensive evaluations using real datasets and experimental benchmarks highlight enhanced concordance between droplet-based single-cell data and established gene expression patterns, while the learned background noise profile provides evidence of degraded or uncaptured cell types.
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Affiliation(s)
- Stephen J Fleming
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Precision Cardiology Laboratory (PCL), Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Mark D Chaffin
- Precision Cardiology Laboratory (PCL), Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Alessandro Arduini
- Precision Cardiology Laboratory (PCL), Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Bayer US, LLC, Cambridge, MA, USA
| | - Amer-Denis Akkad
- Precision Cardiology Laboratory (PCL), Bayer US, LLC, Cambridge, MA, USA
| | - Eric Banks
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - John C Marioni
- Wellcome Sanger Institute, Hinxton, Cambridge, UK
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | | | - Patrick T Ellinor
- Precision Cardiology Laboratory (PCL), Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Mehrtash Babadi
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Precision Cardiology Laboratory (PCL), Broad Institute of MIT and Harvard, Cambridge, MA, USA.
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9
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Babadi M, Fu JM, Lee SK, Smirnov AN, Gauthier LD, Walker M, Benjamin DI, Zhao X, Karczewski KJ, Wong I, Collins RL, Sanchis-Juan A, Brand H, Banks E, Talkowski ME. GATK-gCNV enables the discovery of rare copy number variants from exome sequencing data. Nat Genet 2023; 55:1589-1597. [PMID: 37604963 PMCID: PMC10904014 DOI: 10.1038/s41588-023-01449-0] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Accepted: 06/16/2023] [Indexed: 08/23/2023]
Abstract
Copy number variants (CNVs) are major contributors to genetic diversity and disease. While standardized methods, such as the genome analysis toolkit (GATK), exist for detecting short variants, technical challenges have confounded uniform large-scale CNV analyses from whole-exome sequencing (WES) data. Given the profound impact of rare and de novo coding CNVs on genome organization and human disease, we developed GATK-gCNV, a flexible algorithm to discover rare CNVs from sequencing read-depth information, complete with open-source distribution via GATK. We benchmarked GATK-gCNV in 7,962 exomes from individuals in quartet families with matched genome sequencing and microarray data, finding up to 95% recall of rare coding CNVs at a resolution of more than two exons. We used GATK-gCNV to generate a reference catalog of rare coding CNVs in WES data from 197,306 individuals in the UK Biobank, and observed strong correlations between per-gene CNV rates and measures of mutational constraint, as well as rare CNV associations with multiple traits. In summary, GATK-gCNV is a tunable approach for sensitive and specific CNV discovery in WES data, with broad applications.
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Affiliation(s)
- Mehrtash Babadi
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Jack M Fu
- Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Samuel K Lee
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Andrey N Smirnov
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Laura D Gauthier
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Mark Walker
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - David I Benjamin
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Xuefang Zhao
- Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Konrad J Karczewski
- Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Isaac Wong
- Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Ryan L Collins
- Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Alba Sanchis-Juan
- Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Harrison Brand
- Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Eric Banks
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Michael E Talkowski
- Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
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10
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Wilson A, Babadi M. SynapseCLR: Uncovering features of synapses in primary visual cortex through contrastive representation learning. Patterns 2023; 4:100693. [PMID: 37123442 PMCID: PMC10140600 DOI: 10.1016/j.patter.2023.100693] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 11/23/2022] [Accepted: 01/25/2023] [Indexed: 03/09/2023]
Abstract
3D electron microscopy (EM) connectomics image volumes are surpassing 1 mm3, providing information-dense, multi-scale visualizations of brain circuitry and necessitating scalable analysis techniques. We present SynapseCLR, a self-supervised contrastive learning method for 3D EM data, and use it to extract features of synapses from mouse visual cortex. SynapseCLR feature representations separate synapses by appearance and functionally important structural annotations. We demonstrate SynapseCLR's utility for valuable downstream tasks, including one-shot identification of defective synapse segmentations, dataset-wide similarity-based querying, and accurate imputation of annotations for unlabeled synapses, using manual annotation of only 0.2% of the dataset's synapses. In particular, excitatory versus inhibitory neuronal types can be assigned with >99.8% accuracy to individual synapses and highly truncated neurites, enabling neurite-enhanced connectomics analysis. Finally, we present a data-driven, unsupervised study of synaptic structural variation on the representation manifold, revealing its intrinsic axes of variation and showing that representations contain inhibitory subtype information.
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11
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Mehta A, Bi L, Al'Khafaji A, Jankowiak M, Parikh M, Babadi M, Bloemendal A, Schwartz M, Munson G, Chan J, Burdziak C, Donnard E, Park R, Lu C, Rigollet P, Aguirre A, Subramanian V, Jones R, Lander ES, Ting DT, Pe'er D, Hacohen N. Abstract B016: Quantifying and dissecting pancreatic cancer cell phenotypic plasticity using lineage tracing, single-cell multiomics and CRISPR perturbations reveals novel regulators of plastic states. Cancer Res 2022. [DOI: 10.1158/1538-7445.panca22-b016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Abstract
Pancreatic cancer is a lethal disease in part because tumor cells exist in distinct transcriptional phenotypes (e.g. basal and classical states), each with a selective ability to evade current chemotherapy regimens. Two major mechanisms have been suggested for treatment evasion: 1) intrinsic resistance of certain phenotypes to particular chemotherapy regimens and 2) plasticity of treatment sensitive phenotypes to adopt more resistant phenotypes. However, the relative contribution of these mechanisms to treatment resistance is still poorly understood. Whereas previous work has described the redistribution of tumor cell states under selective treatment pressure, there is no direct evidence that tumor cells exhibit phenotypic plasticity at steady state or with treatment. By leveraging technological advancements in single-cell methods, lineage tracing and functional genomics, we have now shown direct evidence of phenotypic state switching in human pancreatic cancer cell lines. By performing single-cell RNA-seq on 5 barcoded PDAC cell lines over a steady state timecourse and under chemotherapy selective pressure (>600k cells total), we identify unique plasticity phenotypes within these cell lines and infer regulators of these plastic states. We validate the role of several of these regulators using bulk phenotypic CRISPRi screens in these cell lines. We next perform CRISPRi perturbations along with lineage tracing and single-cell multiomics (>300k cells) to dissect the regulatory relationships that underlie these cell states. We identify several novel epithelial and mesenchymal biasing factors, including those with unique roles in the most plastic clones. Collectively, we nominate several regulators that bias PDAC cell states thus posing a paradigm whereby perturbations may be used to homogenize tumor populations towards treatment-sensitive phenotypes. We believe this approach combined with current chemotherapy regimens could benefit pancreatic cancer patients by targeting residual, resistant tumor cells in the localized and metastatic disease settings to improve patient survival.
Citation Format: Arnav Mehta, Lynn Bi, Aziz Al'Khafaji, Martin Jankowiak, Milan Parikh, Mehrtash Babadi, Alex Bloemendal, Marc Schwartz, Glen Munson, Joeseph Chan, Cassandra Burdziak, Elisa Donnard, Ryan Park, Chen Lu, Philippe Rigollet, Andrew Aguirre, Vidya Subramanian, Ray Jones, Eric S. Lander, David T. Ting, Dana Pe'er, Nir Hacohen. Quantifying and dissecting pancreatic cancer cell phenotypic plasticity using lineage tracing, single-cell multiomics and CRISPR perturbations reveals novel regulators of plastic states [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer; 2022 Sep 13-16; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2022;82(22 Suppl):Abstract nr B016.
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Affiliation(s)
- Arnav Mehta
- 1Broad Institute of MIT and Harvard, Cambridge, MA,
| | - Lynn Bi
- 1Broad Institute of MIT and Harvard, Cambridge, MA,
| | | | | | - Milan Parikh
- 1Broad Institute of MIT and Harvard, Cambridge, MA,
| | | | | | | | - Glen Munson
- 1Broad Institute of MIT and Harvard, Cambridge, MA,
| | - Joeseph Chan
- 2Memorial Sloan Kettering Cancer Center, New York, NY,
| | | | | | - Ryan Park
- 1Broad Institute of MIT and Harvard, Cambridge, MA,
| | - Chen Lu
- 3Massachusetts Institute of Technology, Cambridge, MA,
| | | | | | | | - Ray Jones
- 1Broad Institute of MIT and Harvard, Cambridge, MA,
| | | | | | - Dana Pe'er
- 2Memorial Sloan Kettering Cancer Center, New York, NY,
| | - Nir Hacohen
- 1Broad Institute of MIT and Harvard, Cambridge, MA,
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12
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Pita-Juarez Y, Karagkouni D, Kalavros N, Melms JC, Niezen S, Delorey TM, Essene AL, Brook OR, Pant D, Skelton-Badlani D, Naderi P, Huang P, Pan L, Hether T, Andrews TS, Ziegler CGK, Reeves J, Myloserdnyy A, Chen R, Nam A, Phelan S, Liang Y, Amin AD, Biermann J, Hibshoosh H, Veregge M, Kramer Z, Jacobs C, Yalcin Y, Phillips D, Slyper M, Subramanian A, Ashenberg O, Bloom-Ackermann Z, Tran VM, Gomez J, Sturm A, Zhang S, Fleming SJ, Warren S, Beechem J, Hung D, Babadi M, Padera RF, MacParland SA, Bader GD, Imad N, Solomon IH, Miller E, Riedel S, Porter CBM, Villani AC, Tsai LTY, Hide W, Szabo G, Hecht J, Rozenblatt-Rosen O, Shalek AK, Izar B, Regev A, Popov Y, Jiang ZG, Vlachos IS. A single-nucleus and spatial transcriptomic atlas of the COVID-19 liver reveals topological, functional, and regenerative organ disruption in patients. bioRxiv 2022:2022.10.27.514070. [PMID: 36324805 PMCID: PMC9628199 DOI: 10.1101/2022.10.27.514070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
The molecular underpinnings of organ dysfunction in acute COVID-19 and its potential long-term sequelae are under intense investigation. To shed light on these in the context of liver function, we performed single-nucleus RNA-seq and spatial transcriptomic profiling of livers from 17 COVID-19 decedents. We identified hepatocytes positive for SARS-CoV-2 RNA with an expression phenotype resembling infected lung epithelial cells. Integrated analysis and comparisons with healthy controls revealed extensive changes in the cellular composition and expression states in COVID-19 liver, reflecting hepatocellular injury, ductular reaction, pathologic vascular expansion, and fibrogenesis. We also observed Kupffer cell proliferation and erythrocyte progenitors for the first time in a human liver single-cell atlas, resembling similar responses in liver injury in mice and in sepsis, respectively. Despite the absence of a clinical acute liver injury phenotype, endothelial cell composition was dramatically impacted in COVID-19, concomitantly with extensive alterations and profibrogenic activation of reactive cholangiocytes and mesenchymal cells. Our atlas provides novel insights into liver physiology and pathology in COVID-19 and forms a foundational resource for its investigation and understanding.
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Affiliation(s)
- Yered Pita-Juarez
- Department of Pathology, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Dimitra Karagkouni
- Department of Pathology, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Nikolaos Kalavros
- Department of Pathology, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Spatial Technologies Unit, HMS Initiative for RNA Medicine / Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Johannes C Melms
- Department of Medicine, Division of Hematology/Oncology, Columbia University Irving Medical Center, New York, NY, USA
- Columbia Center for Translational Immunology, New York, NY, USA
| | - Sebastian Niezen
- Harvard Medical School, Boston, MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Division of Gastroenterology, Hepatology and Nutrition, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, MA, USA
| | - Toni M Delorey
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Adam L Essene
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, MA, USA
- Division of Endocrinology, Diabetes, and Metabolism, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Boston Nutrition and Obesity Research Center Functional Genomics and Bioinformatics Core, Boston, MA, USA
| | - Olga R Brook
- Department of Radiology, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Deepti Pant
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, MA, USA
- Division of Endocrinology, Diabetes, and Metabolism, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Boston Nutrition and Obesity Research Center Functional Genomics and Bioinformatics Core, Boston, MA, USA
| | - Disha Skelton-Badlani
- Harvard Medical School, Boston, MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Division of Gastroenterology, Hepatology and Nutrition, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, MA, USA
| | - Pourya Naderi
- Department of Pathology, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Pinzhu Huang
- Harvard Medical School, Boston, MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Division of Gastroenterology, Hepatology and Nutrition, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, MA, USA
| | - Liuliu Pan
- NanoString Technologies, Inc., Seattle, WA, USA
| | | | - Tallulah S Andrews
- Ajmera Transplant Centre, Toronto General Research Institute, University Health Network, Toronto, ON, Canada
| | - Carly G K Ziegler
- Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Health Sciences & Technology, Harvard Medical School & Massachusetts Institute of Technology, Boston, MA, USA
- Institute for Medical Engineering & Science, Massachusetts Institute of Technology, Cambridge, MA, USA
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA
- Harvard Graduate Program in Biophysics, Harvard University, Cambridge, MA, USA
- Harvard Stem Cell Institute, Cambridge, MA, USA
- Program in Computational & Systems Biology, Massachusetts Institute of Technology, Cambridge, MA, USA
- Program in Immunology, Harvard Medical School, Boston, MA, USA
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, USA
| | | | - Andriy Myloserdnyy
- Harvard Medical School, Boston, MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Division of Gastroenterology, Hepatology and Nutrition, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, MA, USA
| | - Rachel Chen
- Harvard Medical School, Boston, MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Division of Gastroenterology, Hepatology and Nutrition, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, MA, USA
| | - Andy Nam
- NanoString Technologies, Inc., Seattle, WA, USA
| | | | - Yan Liang
- NanoString Technologies, Inc., Seattle, WA, USA
| | - Amit Dipak Amin
- Department of Medicine, Division of Hematology/Oncology, Columbia University Irving Medical Center, New York, NY, USA
- Columbia Center for Translational Immunology, New York, NY, USA
| | - Jana Biermann
- Department of Medicine, Division of Hematology/Oncology, Columbia University Irving Medical Center, New York, NY, USA
- Columbia Center for Translational Immunology, New York, NY, USA
| | - Hanina Hibshoosh
- Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, NY, USA
| | - Molly Veregge
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, MA, USA
- Division of Endocrinology, Diabetes, and Metabolism, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Boston Nutrition and Obesity Research Center Functional Genomics and Bioinformatics Core, Boston, MA, USA
| | - Zachary Kramer
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, MA, USA
- Division of Endocrinology, Diabetes, and Metabolism, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Christopher Jacobs
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, MA, USA
- Division of Endocrinology, Diabetes, and Metabolism, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Boston Nutrition and Obesity Research Center Functional Genomics and Bioinformatics Core, Boston, MA, USA
| | - Yusuf Yalcin
- Harvard Medical School, Boston, MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Division of Gastroenterology, Hepatology and Nutrition, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, MA, USA
| | - Devan Phillips
- Current address: Genentech, 1 DNA Way, South San Francisco, CA, USA
| | - Michal Slyper
- Current address: Genentech, 1 DNA Way, South San Francisco, CA, USA
| | | | - Orr Ashenberg
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Zohar Bloom-Ackermann
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Victoria M Tran
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - James Gomez
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Alexander Sturm
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Shuting Zhang
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Stephen J Fleming
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Precision Cardiology Laboratory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | | | - Deborah Hung
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
- Department of Molecular Biology and Center for Computational and Integrative Biology, Massachusetts General Hospital, Boston, MA, USA
| | - Mehrtash Babadi
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Precision Cardiology Laboratory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Robert F Padera
- Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA
| | - Sonya A MacParland
- Ajmera Transplant Centre, Toronto General Research Institute, University Health Network, Toronto, ON, Canada
- Department of Immunology, University of Toronto, Medical Sciences Building, 1 King's College Circle, Toronto, ON, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
| | - Gary D Bader
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
- The Donnelly Centre, Toronto, ON, Canada
| | - Nasser Imad
- Department of Pathology, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Isaac H Solomon
- Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA
| | - Eric Miller
- NanoString Technologies, Inc., Seattle, WA, USA
| | - Stefan Riedel
- Department of Pathology, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Caroline B M Porter
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Alexandra-Chloé Villani
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Immunology and Inflammatory Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Center for Cancer Research, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Linus T-Y Tsai
- Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, MA, USA
- Division of Endocrinology, Diabetes, and Metabolism, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Boston Nutrition and Obesity Research Center Functional Genomics and Bioinformatics Core, Boston, MA, USA
| | - Winston Hide
- Department of Pathology, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Gyongyi Szabo
- Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Division of Gastroenterology, Hepatology and Nutrition, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, MA, USA
| | - Jonathan Hecht
- Department of Pathology, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Orit Rozenblatt-Rosen
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Current address: Genentech, 1 DNA Way, South San Francisco, CA, USA
| | - Alex K Shalek
- Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Health Sciences & Technology, Harvard Medical School & Massachusetts Institute of Technology, Boston, MA, USA
- Institute for Medical Engineering & Science, Massachusetts Institute of Technology, Cambridge, MA, USA
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA
- Harvard Graduate Program in Biophysics, Harvard University, Cambridge, MA, USA
- Harvard Stem Cell Institute, Cambridge, MA, USA
- Program in Computational & Systems Biology, Massachusetts Institute of Technology, Cambridge, MA, USA
- Program in Immunology, Harvard Medical School, Boston, MA, USA
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Benjamin Izar
- Department of Medicine, Division of Hematology/Oncology, Columbia University Irving Medical Center, New York, NY, USA
- Columbia Center for Translational Immunology, New York, NY, USA
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY, USA
- Program for Mathematical Genomics, Columbia University Irving Medical Center, New York, NY, USA
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
| | - Aviv Regev
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Current address: Genentech, 1 DNA Way, South San Francisco, CA, USA
| | - Yury Popov
- Harvard Medical School, Boston, MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Division of Gastroenterology, Hepatology and Nutrition, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Z Gordon Jiang
- Harvard Medical School, Boston, MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Division of Gastroenterology, Hepatology and Nutrition, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, MA, USA
| | - Ioannis S Vlachos
- Department of Pathology, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Spatial Technologies Unit, HMS Initiative for RNA Medicine / Beth Israel Deaconess Medical Center, Boston, MA, USA
- Cancer Research Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Harvard Medical School Initiative for RNA Medicine, Boston, MA, USA
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13
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Pita-Juarez Y, Karagkouni D, Kalavros N, Melms JC, Niezen S, Delorey TM, Essene AL, Brook OR, Pant D, Skelton-Badlani D, Naderi P, Huang P, Pan L, Hether T, Andrews TS, Ziegler CGK, Reeves J, Myloserdnyy A, Chen R, Nam A, Phelan S, Liang Y, Amin AD, Biermann J, Hibshoosh H, Veregge M, Kramer Z, Jacobs C, Yalcin Y, Phillips D, Slyper M, Subramanian A, Ashenberg O, Bloom-Ackermann Z, Tran VM, Gomez J, Sturm A, Zhang S, Fleming SJ, Warren S, Beechem J, Hung D, Babadi M, Padera RF, MacParland SA, Bader GD, Imad N, Solomon IH, Miller E, Riedel S, Porter CBM, Villani AC, Tsai LTY, Hide W, Szabo G, Hecht J, Rozenblatt-Rosen O, Shalek AK, Izar B, Regev A, Popov Y, Jiang ZG, Vlachos IS. A single-nucleus and spatial transcriptomic atlas of the COVID-19 liver reveals topological, functional, and regenerative organ disruption in patients. bioRxiv 2022. [PMID: 36324805 DOI: 10.1101/2022.08.06.503037] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/09/2023]
Abstract
The molecular underpinnings of organ dysfunction in acute COVID-19 and its potential long-term sequelae are under intense investigation. To shed light on these in the context of liver function, we performed single-nucleus RNA-seq and spatial transcriptomic profiling of livers from 17 COVID-19 decedents. We identified hepatocytes positive for SARS-CoV-2 RNA with an expression phenotype resembling infected lung epithelial cells. Integrated analysis and comparisons with healthy controls revealed extensive changes in the cellular composition and expression states in COVID-19 liver, reflecting hepatocellular injury, ductular reaction, pathologic vascular expansion, and fibrogenesis. We also observed Kupffer cell proliferation and erythrocyte progenitors for the first time in a human liver single-cell atlas, resembling similar responses in liver injury in mice and in sepsis, respectively. Despite the absence of a clinical acute liver injury phenotype, endothelial cell composition was dramatically impacted in COVID-19, concomitantly with extensive alterations and profibrogenic activation of reactive cholangiocytes and mesenchymal cells. Our atlas provides novel insights into liver physiology and pathology in COVID-19 and forms a foundational resource for its investigation and understanding.
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14
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Fu JM, Satterstrom FK, Peng M, Brand H, Collins RL, Dong S, Wamsley B, Klei L, Wang L, Hao SP, Stevens CR, Cusick C, Babadi M, Banks E, Collins B, Dodge S, Gabriel SB, Gauthier L, Lee SK, Liang L, Ljungdahl A, Mahjani B, Sloofman L, Smirnov AN, Barbosa M, Betancur C, Brusco A, Chung BHY, Cook EH, Cuccaro ML, Domenici E, Ferrero GB, Gargus JJ, Herman GE, Hertz-Picciotto I, Maciel P, Manoach DS, Passos-Bueno MR, Persico AM, Renieri A, Sutcliffe JS, Tassone F, Trabetti E, Campos G, Cardaropoli S, Carli D, Chan MCY, Fallerini C, Giorgio E, Girardi AC, Hansen-Kiss E, Lee SL, Lintas C, Ludena Y, Nguyen R, Pavinato L, Pericak-Vance M, Pessah IN, Schmidt RJ, Smith M, Costa CIS, Trajkova S, Wang JYT, Yu MHC, Cutler DJ, De Rubeis S, Buxbaum JD, Daly MJ, Devlin B, Roeder K, Sanders SJ, Talkowski ME. Rare coding variation provides insight into the genetic architecture and phenotypic context of autism. Nat Genet 2022; 54:1320-1331. [PMID: 35982160 PMCID: PMC9653013 DOI: 10.1038/s41588-022-01104-0] [Citation(s) in RCA: 137] [Impact Index Per Article: 68.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 05/24/2022] [Indexed: 01/11/2023]
Abstract
Some individuals with autism spectrum disorder (ASD) carry functional mutations rarely observed in the general population. We explored the genes disrupted by these variants from joint analysis of protein-truncating variants (PTVs), missense variants and copy number variants (CNVs) in a cohort of 63,237 individuals. We discovered 72 genes associated with ASD at false discovery rate (FDR) ≤ 0.001 (185 at FDR ≤ 0.05). De novo PTVs, damaging missense variants and CNVs represented 57.5%, 21.1% and 8.44% of association evidence, while CNVs conferred greatest relative risk. Meta-analysis with cohorts ascertained for developmental delay (DD) (n = 91,605) yielded 373 genes associated with ASD/DD at FDR ≤ 0.001 (664 at FDR ≤ 0.05), some of which differed in relative frequency of mutation between ASD and DD cohorts. The DD-associated genes were enriched in transcriptomes of progenitor and immature neuronal cells, whereas genes showing stronger evidence in ASD were more enriched in maturing neurons and overlapped with schizophrenia-associated genes, emphasizing that these neuropsychiatric disorders may share common pathways to risk.
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Affiliation(s)
- Jack M Fu
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - F Kyle Satterstrom
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Minshi Peng
- Department of Statistics and Data Science, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Harrison Brand
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Pediatric Surgical Research Laboratories, Department of Surgery, Massachusetts General Hospital, Boston, MA, USA
| | - Ryan L Collins
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Program in Bioinformatics and Integrative Genomics, Harvard Medical School, Boston, MA, USA
| | - Shan Dong
- Department of Psychiatry, UCSF Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Brie Wamsley
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Lambertus Klei
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Lily Wang
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Bioinformatics and Integrative Genomics, Harvard Medical School, Boston, MA, USA
| | - Stephanie P Hao
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Pediatric Surgical Research Laboratories, Department of Surgery, Massachusetts General Hospital, Boston, MA, USA
| | - Christine R Stevens
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Caroline Cusick
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Mehrtash Babadi
- Data Sciences Platform, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Eric Banks
- Data Sciences Platform, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Brett Collins
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sheila Dodge
- Genomics Platform, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Stacey B Gabriel
- Genomics Platform, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Laura Gauthier
- Data Sciences Platform, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Samuel K Lee
- Data Sciences Platform, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Lindsay Liang
- Department of Psychiatry, UCSF Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Alicia Ljungdahl
- Department of Psychiatry, UCSF Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Behrang Mahjani
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Laura Sloofman
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Andrey N Smirnov
- Data Sciences Platform, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Mafalda Barbosa
- The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Catalina Betancur
- Sorbonne Université, INSERM, CNRS, Neuroscience Paris Seine, Institut de Biologie Paris Seine, Paris, France
| | - Alfredo Brusco
- Department of Medical Sciences, University of Torino, Turin, Italy
- Medical Genetics Unit, 'Città della Salute e della Scienza' University Hospital, Turin, Italy
| | - Brian H Y Chung
- Department of Pediatrics and Adolescent Medicine, Duchess of Kent Children's Hospital, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Edwin H Cook
- Institute for Juvenile Research, Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA
| | - Michael L Cuccaro
- The John P Hussman Institute for Human Genomics, The University of Miami Miller School of Medicine, Miami, FL, USA
| | - Enrico Domenici
- Department of Cellular, Computational and Integrative Biology, , University of Trento, Trento, Italy
| | | | - J Jay Gargus
- Center for Autism Research and Translation, University of California Irvine, Irvine, CA, USA
| | - Gail E Herman
- The Research Institute at Nationwide Children's Hospital, Columbus, OH, USA
| | - Irva Hertz-Picciotto
- MIND (Medical Investigation of Neurodevelopmental Disorders) Institute, University of California Davis, Davis, CA, USA
| | - Patricia Maciel
- Life and Health Sciences Research Institute, School of Medicine, University of Minho, Braga, Portugal
| | - Dara S Manoach
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Maria Rita Passos-Bueno
- Centro de Pesquisas sobre o Genoma Humano e Células tronco, Instituto de Biociências, Universidade de São Paulo, São Paulo, Brazil
| | - Antonio M Persico
- Interdepartmental Program 'Autism 0-90', 'Gaetano Martino' University Hospital, University of Messina, Messina, Italy
| | - Alessandra Renieri
- Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Siena, Italy
- Medical Genetics, , University of Siena, Siena, Italy
- Genetica Medica, Azienda Ospedaliera Universitaria Senese, Siena, Italy
| | - James S Sutcliffe
- Department of Molecular Physiology & Biophysics and Psychiatry, Vanderbilt University School of Medicine, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Flora Tassone
- MIND (Medical Investigation of Neurodevelopmental Disorders) Institute, University of California Davis, Davis, CA, USA
- Department of Biochemistry and Molecular Medicine, University of California Davis, School of Medicine, Sacramento, CA, USA
| | - Elisabetta Trabetti
- Department of Neurosciences, Biomedicine and Movement Sciences, Section of Biology and Genetics, University of Verona, Verona, Italy
| | - Gabriele Campos
- Centro de Pesquisas sobre o Genoma Humano e Células tronco, Instituto de Biociências, Universidade de São Paulo, São Paulo, Brazil
| | - Simona Cardaropoli
- Department of Public Health and Pediatrics, University of Torino, Turin, Italy
| | - Diana Carli
- Department of Public Health and Pediatrics, University of Torino, Turin, Italy
| | - Marcus C Y Chan
- Department of Pediatrics and Adolescent Medicine, Duchess of Kent Children's Hospital, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Chiara Fallerini
- Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Siena, Italy
- Medical Genetics, , University of Siena, Siena, Italy
| | - Elisa Giorgio
- Department of Medical Sciences, University of Torino, Turin, Italy
| | - Ana Cristina Girardi
- Centro de Pesquisas sobre o Genoma Humano e Células tronco, Instituto de Biociências, Universidade de São Paulo, São Paulo, Brazil
| | - Emily Hansen-Kiss
- Department of Diagnostic and Biomedical Sciences, University of Texas Health Science Center at Houston, School of Dentistry, Houston, TX, USA
| | - So Lun Lee
- Department of Pediatrics and Adolescent Medicine, Duchess of Kent Children's Hospital, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Carla Lintas
- Service for Neurodevelopmental Disorders, University Campus Bio-medico of Rome, Rome, Italy
| | - Yunin Ludena
- MIND (Medical Investigation of Neurodevelopmental Disorders) Institute, University of California Davis, Davis, CA, USA
| | - Rachel Nguyen
- Center for Autism Research and Translation, University of California Irvine, Irvine, CA, USA
| | - Lisa Pavinato
- Department of Medical Sciences, University of Torino, Turin, Italy
| | - Margaret Pericak-Vance
- The John P Hussman Institute for Human Genomics, The University of Miami Miller School of Medicine, Miami, FL, USA
| | - Isaac N Pessah
- MIND (Medical Investigation of Neurodevelopmental Disorders) Institute, University of California Davis, Davis, CA, USA
- Department of Molecular Biosciences, University of California Davis, School of Veterinary Medicine, Davis, CA, USA
| | - Rebecca J Schmidt
- MIND (Medical Investigation of Neurodevelopmental Disorders) Institute, University of California Davis, Davis, CA, USA
| | - Moyra Smith
- Center for Autism Research and Translation, University of California Irvine, Irvine, CA, USA
| | - Claudia I S Costa
- Centro de Pesquisas sobre o Genoma Humano e Células tronco, Instituto de Biociências, Universidade de São Paulo, São Paulo, Brazil
| | - Slavica Trajkova
- Department of Medical Sciences, University of Torino, Turin, Italy
| | - Jaqueline Y T Wang
- Centro de Pesquisas sobre o Genoma Humano e Células tronco, Instituto de Biociências, Universidade de São Paulo, São Paulo, Brazil
| | - Mullin H C Yu
- Department of Pediatrics and Adolescent Medicine, Duchess of Kent Children's Hospital, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - David J Cutler
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA
| | - Silvia De Rubeis
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Joseph D Buxbaum
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| | - Mark J Daly
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Harvard Medical School, Boston, MA, USA.
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.
| | - Bernie Devlin
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
| | - Kathryn Roeder
- Department of Statistics and Data Science, Carnegie Mellon University, Pittsburgh, PA, USA.
- Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA, USA.
| | - Stephan J Sanders
- Department of Psychiatry, UCSF Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA.
| | - Michael E Talkowski
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Program in Bioinformatics and Integrative Genomics, Harvard Medical School, Boston, MA, USA.
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15
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Obermeyer F, Jankowiak M, Barkas N, Schaffner SF, Pyle JD, Yurkovetskiy L, Bosso M, Park DJ, Babadi M, MacInnis BL, Luban J, Sabeti PC, Lemieux JE. Analysis of 6.4 million SARS-CoV-2 genomes identifies mutations associated with fitness. Science 2022; 376:1327-1332. [PMID: 35608456 PMCID: PMC9161372 DOI: 10.1126/science.abm1208] [Citation(s) in RCA: 108] [Impact Index Per Article: 54.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Repeated emergence of SARS-CoV-2 variants with increased fitness underscores the value of rapid detection and characterization of new lineages. We have developed PyR0, a hierarchical Bayesian multinomial logistic regression model that infers relative prevalence of all viral lineages across geographic regions, detects lineages increasing in prevalence, and identifies mutations relevant to fitness. Applying PyR0 to all publicly available SARS-CoV-2 genomes, we identify numerous substitutions that increase fitness, including previously identified spike mutations and many non-spike mutations within the nucleocapsid and nonstructural proteins. PyR0 forecasts growth of new lineages from their mutational profile, ranks the fitness of lineages as new sequences become available, and prioritizes mutations of biological and public health concern for functional characterization.
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16
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Obermeyer F, Jankowiak M, Barkas N, Schaffner SF, Pyle JD, Yurkovetskiy L, Bosso M, Park DJ, Babadi M, MacInnis BL, Luban J, Sabeti PC, Lemieux JE. Analysis of 6.4 million SARS-CoV-2 genomes identifies mutations associated with fitness. medRxiv 2022:2021.09.07.21263228. [PMID: 35194619 PMCID: PMC8863165 DOI: 10.1101/2021.09.07.21263228] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Repeated emergence of SARS-CoV-2 variants with increased fitness necessitates rapid detection and characterization of new lineages. To address this need, we developed PyR 0 , a hierarchical Bayesian multinomial logistic regression model that infers relative prevalence of all viral lineages across geographic regions, detects lineages increasing in prevalence, and identifies mutations relevant to fitness. Applying PyR 0 to all publicly available SARS-CoV-2 genomes, we identify numerous substitutions that increase fitness, including previously identified spike mutations and many non-spike mutations within the nucleocapsid and nonstructural proteins. PyR 0 forecasts growth of new lineages from their mutational profile, identifies viral lineages of concern as they emerge, and prioritizes mutations of biological and public health concern for functional characterization. ONE SENTENCE SUMMARY A Bayesian hierarchical model of all SARS-CoV-2 viral genomes predicts lineage fitness and identifies associated mutations.
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Affiliation(s)
- Fritz Obermeyer
- Broad Institute of MIT and Harvard; 415 Main Street, Cambridge, MA 02142, USA
- Pyro Committee, Linux AI & Data Foundation; 548 Market St San Francisco, California 94104
| | - Martin Jankowiak
- Broad Institute of MIT and Harvard; 415 Main Street, Cambridge, MA 02142, USA
- Pyro Committee, Linux AI & Data Foundation; 548 Market St San Francisco, California 94104
| | - Nikolaos Barkas
- Broad Institute of MIT and Harvard; 415 Main Street, Cambridge, MA 02142, USA
| | - Stephen F. Schaffner
- Broad Institute of MIT and Harvard; 415 Main Street, Cambridge, MA 02142, USA
- Department of Organismic and Evolutionary Biology, Harvard University; Cambridge, MA 02138, USA
- Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Harvard University; Boston, MA, USA
| | - Jesse D. Pyle
- Broad Institute of MIT and Harvard; 415 Main Street, Cambridge, MA 02142, USA
| | - Lonya Yurkovetskiy
- Program in Molecular Medicine, University of Massachusetts Medical School; Worcester, MA 01605, USA
| | - Matteo Bosso
- Program in Molecular Medicine, University of Massachusetts Medical School; Worcester, MA 01605, USA
| | - Daniel J. Park
- Broad Institute of MIT and Harvard; 415 Main Street, Cambridge, MA 02142, USA
| | - Mehrtash Babadi
- Broad Institute of MIT and Harvard; 415 Main Street, Cambridge, MA 02142, USA
| | - Bronwyn L. MacInnis
- Broad Institute of MIT and Harvard; 415 Main Street, Cambridge, MA 02142, USA
- Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Harvard University; Boston, MA, USA
- Massachusetts Consortium on Pathogen Readiness; Boston, MA 02115, USA
| | - Jeremy Luban
- Broad Institute of MIT and Harvard; 415 Main Street, Cambridge, MA 02142, USA
- Program in Molecular Medicine, University of Massachusetts Medical School; Worcester, MA 01605, USA
- Massachusetts Consortium on Pathogen Readiness; Boston, MA 02115, USA
- Ragon Institute of MGH, MIT, and Harvard; 400 Technology Square, Cambridge, MA 02139, USA
| | - Pardis C. Sabeti
- Broad Institute of MIT and Harvard; 415 Main Street, Cambridge, MA 02142, USA
- Department of Organismic and Evolutionary Biology, Harvard University; Cambridge, MA 02138, USA
- Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Harvard University; Boston, MA, USA
- Massachusetts Consortium on Pathogen Readiness; Boston, MA 02115, USA
- Howard Hughes Medical Institute; 4000 Jones Bridge Rd, Chevy Chase, MD 20815, USA
| | - Jacob E. Lemieux
- Broad Institute of MIT and Harvard; 415 Main Street, Cambridge, MA 02142, USA
- Division of Infectious Diseases, Massachusetts General Hospital; Boston, MA, USA
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17
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Delorey TM, Ziegler CGK, Heimberg G, Normand R, Yang Y, Segerstolpe Å, Abbondanza D, Fleming SJ, Subramanian A, Montoro DT, Jagadeesh KA, Dey KK, Sen P, Slyper M, Pita-Juárez YH, Phillips D, Biermann J, Bloom-Ackermann Z, Barkas N, Ganna A, Gomez J, Melms JC, Katsyv I, Normandin E, Naderi P, Popov YV, Raju SS, Niezen S, Tsai LTY, Siddle KJ, Sud M, Tran VM, Vellarikkal SK, Wang Y, Amir-Zilberstein L, Atri DS, Beechem J, Brook OR, Chen J, Divakar P, Dorceus P, Engreitz JM, Essene A, Fitzgerald DM, Fropf R, Gazal S, Gould J, Grzyb J, Harvey T, Hecht J, Hether T, Jané-Valbuena J, Leney-Greene M, Ma H, McCabe C, McLoughlin DE, Miller EM, Muus C, Niemi M, Padera R, Pan L, Pant D, Pe’er C, Pfiffner-Borges J, Pinto CJ, Plaisted J, Reeves J, Ross M, Rudy M, Rueckert EH, Siciliano M, Sturm A, Todres E, Waghray A, Warren S, Zhang S, Zollinger DR, Cosimi L, Gupta RM, Hacohen N, Hibshoosh H, Hide W, Price AL, Rajagopal J, Tata PR, Riedel S, Szabo G, Tickle TL, Ellinor PT, Hung D, Sabeti PC, Novak R, Rogers R, Ingber DE, Jiang ZG, Juric D, Babadi M, Farhi SL, Izar B, Stone JR, Vlachos IS, Solomon IH, Ashenberg O, Porter CB, Li B, Shalek AK, Villani AC, Rozenblatt-Rosen O, Regev A. COVID-19 tissue atlases reveal SARS-CoV-2 pathology and cellular targets. Nature 2021; 595:107-113. [PMID: 33915569 PMCID: PMC8919505 DOI: 10.1038/s41586-021-03570-8] [Citation(s) in RCA: 427] [Impact Index Per Article: 142.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Accepted: 04/19/2021] [Indexed: 02/02/2023]
Abstract
COVID-19, which is caused by SARS-CoV-2, can result in acute respiratory distress syndrome and multiple organ failure1-4, 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.
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Affiliation(s)
- Toni M. Delorey
- Klarman Cell Observatory, Broad Institute of MIT and
Harvard, Cambridge, MA 02142, USA, USA
| | - Carly G. K. Ziegler
- Broad Institute of MIT and Harvard, Cambridge, MA 02142,
USA,Program in Health Sciences & Technology, Harvard
Medical School & Massachusetts Institute of Technology, Boston, MA 02115,
USA,Institute for Medical Engineering & Science,
Massachusetts Institute of Technology, Cambridge, MA 02139, USA,Koch Institute for Integrative Cancer Research,
Massachusetts Institute of Technology, Cambridge, MA 02139, USA,Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA
02139, USA,Harvard Graduate Program in Biophysics, Harvard University,
Cambridge, MA 02138, USA
| | - Graham Heimberg
- Klarman Cell Observatory, Broad Institute of MIT and
Harvard, Cambridge, MA 02142, USA, USA
| | - Rachelly Normand
- Broad Institute of MIT and Harvard, Cambridge, MA 02142,
USA,Center for Immunology and Inflammatory Diseases, Department
of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA,Center for Cancer Research, Massachusetts General Hospital,
Harvard Medical School, Boston, MA 02114, USA,Harvard Medical School, Boston, MA 02115, USA,Massachusetts Institute of Technology, Cambridge, MA
02139, USA
| | - Yiming Yang
- Klarman Cell Observatory, Broad Institute of MIT and
Harvard, Cambridge, MA 02142, USA, USA,Center for Immunology and Inflammatory Diseases, Department
of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Åsa Segerstolpe
- Klarman Cell Observatory, Broad Institute of MIT and
Harvard, Cambridge, MA 02142, USA, USA
| | - Domenic Abbondanza
- Klarman Cell Observatory, Broad Institute of MIT and
Harvard, Cambridge, MA 02142, USA, USA,Broad Institute of MIT and Harvard, Cambridge, MA 02142,
USA
| | - Stephen J. Fleming
- Data Sciences Platform, Broad Institute of MIT and
Harvard, Cambridge, MA 02142,Precision Cardiology Laboratory, Broad Institute of MIT
and Harvard, Cambridge, MA 02142, USA
| | - Ayshwarya Subramanian
- Klarman Cell Observatory, Broad Institute of MIT and
Harvard, Cambridge, MA 02142, USA, USA
| | | | - Karthik A. Jagadeesh
- Klarman Cell Observatory, Broad Institute of MIT and
Harvard, Cambridge, MA 02142, USA, USA
| | - Kushal K. Dey
- Department of Epidemiology, Harvard School of Public
Health
| | - Pritha Sen
- Broad Institute of MIT and Harvard, Cambridge, MA 02142,
USA,Center for Immunology and Inflammatory Diseases, Department
of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA,Division of Infectious Diseases, Department of Medicine,
Massachusetts General Hospital, Boston, MA 02114, USA,Department of Medicine, Harvard Medical School, Boston,
MA 02115, USA
| | - Michal Slyper
- Klarman Cell Observatory, Broad Institute of MIT and
Harvard, Cambridge, MA 02142, USA, USA
| | - Yered H. Pita-Juárez
- Broad Institute of MIT and Harvard, Cambridge, MA 02142,
USA,Harvard Medical School, Boston, MA 02115, USA,Department of Pathology, Beth Israel Deaconess Medical
Center, Boston, MA 02115, USA,Harvard Medical School Initiative for RNA Medicine,
Boston, MA 02115, USA,Cancer Research Institute, Beth Israel Deaconess Medical
Center, Boston, MA 02115, USA
| | - Devan Phillips
- Klarman Cell Observatory, Broad Institute of MIT and
Harvard, Cambridge, MA 02142, USA, USA
| | - Jana Biermann
- Department of Medicine, Division of Hematology/Oncology,
Columbia University Irving Medical Center, New York, NY,Columbia Center for Translational Immunology, New York,
NY
| | - Zohar Bloom-Ackermann
- Infectious Disease and Microbiome Program, Broad
Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Nick Barkas
- Data Sciences Platform, Broad Institute of MIT and
Harvard, Cambridge, MA 02142
| | - Andrea Ganna
- Institute for Molecular Medicine Finland, Helsinki,
Finland,Analytical & Translational Genetics Unit,
Massachusetts General Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - James Gomez
- Infectious Disease and Microbiome Program, Broad
Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Johannes C. Melms
- Department of Medicine, Division of Hematology/Oncology,
Columbia University Irving Medical Center, New York, NY,Columbia Center for Translational Immunology, New York,
NY
| | - Igor Katsyv
- Department of Pathology and Cell Biology, Columbia
University Irving Medical Center, New York, NY
| | - Erica Normandin
- Broad Institute of MIT and Harvard, Cambridge, MA 02142,
USA,Harvard Medical School, Boston, MA 02115, USA
| | - Pourya Naderi
- Harvard Medical School, Boston, MA 02115, USA,Department of Pathology, Beth Israel Deaconess Medical
Center, Boston, MA 02115, USA,Harvard Medical School Initiative for RNA Medicine,
Boston, MA 02115, USA
| | - Yury V. Popov
- Harvard Medical School, Boston, MA 02115, USA,Department of Medicine, Beth Israel Deaconess Medical
Center, MA 02115, USA,Division of Gastroenterology, Hepatology and Nutrition,
Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA 02215,
USA
| | - Siddharth S. Raju
- Broad Institute of MIT and Harvard, Cambridge, MA 02142,
USA,Department of Systems Biology, Harvard Medical School,
Boston, MA 02115, USA,FAS Center for Systems Biology, Department of Organismic
and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
| | - Sebastian Niezen
- Harvard Medical School, Boston, MA 02115, USA,Department of Medicine, Beth Israel Deaconess Medical
Center, MA 02115, USA,Division of Gastroenterology, Hepatology and Nutrition,
Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA 02215,
USA
| | - Linus T.-Y. Tsai
- Broad Institute of MIT and Harvard, Cambridge, MA 02142,
USA,Harvard Medical School, Boston, MA 02115, USA,Department of Medicine, Beth Israel Deaconess Medical
Center, MA 02115, USA,Division of Endocrinology, Diabetes, and Metabolism, Beth
Israel Deaconess Medical Center, Boston, MA 02115,Boston Nutrition and Obesity Research Center Functional
Genomics and Bioinformatics Core Boston, MA 02115, USA
| | - Katherine J. Siddle
- Broad Institute of MIT and Harvard, Cambridge, MA 02142,
USA,Department of Organismic and Evolutionary Biology,
Harvard University, Cambridge, MA, USA
| | - Malika Sud
- Klarman Cell Observatory, Broad Institute of MIT and
Harvard, Cambridge, MA 02142, USA, USA
| | - Victoria M. Tran
- Infectious Disease and Microbiome Program, Broad
Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Shamsudheen K. Vellarikkal
- Broad Institute of MIT and Harvard, Cambridge, MA 02142,
USA,Divisions of Cardiovascular Medicine and Genetics,
Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115,
USA
| | - Yiping Wang
- Department of Medicine, Division of Hematology/Oncology,
Columbia University Irving Medical Center, New York, NY,Columbia Center for Translational Immunology, New York,
NY
| | - Liat Amir-Zilberstein
- Klarman Cell Observatory, Broad Institute of MIT and
Harvard, Cambridge, MA 02142, USA, USA
| | - Deepak S. Atri
- Broad Institute of MIT and Harvard, Cambridge, MA 02142,
USA,Divisions of Cardiovascular Medicine and Genetics,
Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115,
USA
| | | | - Olga R. Brook
- Department of Radiology, Beth Israel Deaconess Medical
Center, Boston, MA 02215, USA
| | - Jonathan Chen
- Broad Institute of MIT and Harvard, Cambridge, MA 02142,
USA,Department of Pathology, Massachusetts General Hospital,
Harvard Medical School, Boston, MA 02115, USA
| | | | - Phylicia Dorceus
- Klarman Cell Observatory, Broad Institute of MIT and
Harvard, Cambridge, MA 02142, USA, USA
| | - Jesse M. Engreitz
- Broad Institute of MIT and Harvard, Cambridge, MA 02142,
USA,Department of Genetics and BASE Initiative, Stanford
University School of Medicine
| | - Adam Essene
- Department of Medicine, Beth Israel Deaconess Medical
Center, MA 02115, USA,Division of Endocrinology, Diabetes, and Metabolism, Beth
Israel Deaconess Medical Center, Boston, MA 02115,Boston Nutrition and Obesity Research Center Functional
Genomics and Bioinformatics Core Boston, MA 02115, USA
| | - Donna M. Fitzgerald
- Massachusetts General Hospital Cancer Center, Department
of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Robin Fropf
- NanoString Technologies Inc., Seattle, WA 98109,
USA
| | - Steven Gazal
- Center for Genetic Epidemiology, Department of Preventive
Medicine, Keck School of Medicine, University of Southern California, Los Angeles,
CA, USA
| | - Joshua Gould
- Data Sciences Platform, Broad Institute of MIT and
Harvard, Cambridge, MA 02142
| | - John Grzyb
- Department of Pathology, Brigham and Women’s
Hospital, Boston, MA 02115
| | - Tyler Harvey
- Klarman Cell Observatory, Broad Institute of MIT and
Harvard, Cambridge, MA 02142, USA, USA
| | - Jonathan Hecht
- Harvard Medical School, Boston, MA 02115, USA,Department of Pathology, Beth Israel Deaconess Medical
Center, Boston, MA 02115, USA
| | - Tyler Hether
- NanoString Technologies Inc., Seattle, WA 98109,
USA
| | - Judit Jané-Valbuena
- Klarman Cell Observatory, Broad Institute of MIT and
Harvard, Cambridge, MA 02142, USA, USA
| | | | - Hui Ma
- Klarman Cell Observatory, Broad Institute of MIT and
Harvard, Cambridge, MA 02142, USA, USA,Center for Immunology and Inflammatory Diseases, Department
of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Cristin McCabe
- Klarman Cell Observatory, Broad Institute of MIT and
Harvard, Cambridge, MA 02142, USA, USA
| | - Daniel E. McLoughlin
- Massachusetts General Hospital Cancer Center, Department
of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | | | - Christoph Muus
- Broad Institute of MIT and Harvard, Cambridge, MA 02142,
USA,John A. Paulson School of Engineering and Applied
Sciences, Harvard University, Cambridge, MA 02138
| | - Mari Niemi
- Institute for Molecular Medicine Finland, Helsinki,
Finland
| | - Robert Padera
- Department of Pathology, Brigham and Women’s
Hospital, Boston, MA 02115,Harvard-MIT Division of Health Sciences and Technology,
Cambridge MA,Department of Pathology, Harvard Medical School, Boston,
MA 02115, USA
| | - Liuliu Pan
- NanoString Technologies Inc., Seattle, WA 98109,
USA
| | - Deepti Pant
- Department of Medicine, Beth Israel Deaconess Medical
Center, MA 02115, USA,Division of Endocrinology, Diabetes, and Metabolism, Beth
Israel Deaconess Medical Center, Boston, MA 02115,Boston Nutrition and Obesity Research Center Functional
Genomics and Bioinformatics Core Boston, MA 02115, USA
| | - Carmel Pe’er
- Klarman Cell Observatory, Broad Institute of MIT and
Harvard, Cambridge, MA 02142, USA, USA
| | | | - Christopher J. Pinto
- Department of Medicine, Harvard Medical School, Boston,
MA 02115, USA,Massachusetts General Hospital Cancer Center, Department
of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Jacob Plaisted
- Department of Pathology, Brigham and Women’s
Hospital, Boston, MA 02115
| | - Jason Reeves
- NanoString Technologies Inc., Seattle, WA 98109,
USA
| | - Marty Ross
- NanoString Technologies Inc., Seattle, WA 98109,
USA
| | - Melissa Rudy
- Broad Institute of MIT and Harvard, Cambridge, MA 02142,
USA
| | | | | | - Alexander Sturm
- Infectious Disease and Microbiome Program, Broad
Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Ellen Todres
- Klarman Cell Observatory, Broad Institute of MIT and
Harvard, Cambridge, MA 02142, USA, USA
| | - Avinash Waghray
- Harvard Stem Cell Institute, Cambridge, MA, USA,Center for Regenerative Medicine, Massachusetts General
Hospital, Boston, MA 02114, USA
| | - Sarah Warren
- NanoString Technologies Inc., Seattle, WA 98109,
USA
| | - Shuting Zhang
- Infectious Disease and Microbiome Program, Broad
Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | | | - Lisa Cosimi
- Infectious Diseases Division, Department of Medicine,
Brigham and Women’s Hospital, Boston, MA, USA
| | - Rajat M. Gupta
- Broad Institute of MIT and Harvard, Cambridge, MA 02142,
USA,Divisions of Cardiovascular Medicine and Genetics,
Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115,
USA
| | - Nir Hacohen
- Broad Institute of MIT and Harvard, Cambridge, MA 02142,
USA,Center for Cancer Research, Massachusetts General Hospital,
Harvard Medical School, Boston, MA 02114, USA,Department of Medicine, Massachusetts General Hospital,
Harvard Medical School, Boston, MA 02114, USA
| | - Hanina Hibshoosh
- Department of Pathology and Cell Biology, Columbia
University Irving Medical Center, New York, NY
| | - Winston Hide
- Harvard Medical School, Boston, MA 02115, USA,Department of Pathology, Beth Israel Deaconess Medical
Center, Boston, MA 02115, USA,Harvard Medical School Initiative for RNA Medicine,
Boston, MA 02115, USA,Cancer Research Institute, Beth Israel Deaconess Medical
Center, Boston, MA 02115, USA
| | - Alkes L. Price
- Department of Epidemiology, Harvard School of Public
Health
| | - Jayaraj Rajagopal
- Massachusetts General Hospital Cancer Center, Department
of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | | | - Stefan Riedel
- Harvard Medical School, Boston, MA 02115, USA,Department of Pathology, Beth Israel Deaconess Medical
Center, Boston, MA 02115, USA
| | - Gyongyi Szabo
- Broad Institute of MIT and Harvard, Cambridge, MA 02142,
USA,Harvard Medical School, Boston, MA 02115, USA,Department of Medicine, Beth Israel Deaconess Medical
Center, MA 02115, USA
| | - Timothy L. Tickle
- Klarman Cell Observatory, Broad Institute of MIT and
Harvard, Cambridge, MA 02142, USA, USA,Data Sciences Platform, Broad Institute of MIT and
Harvard, Cambridge, MA 02142
| | - Patrick T. Ellinor
- Cardiovascular Disease Initiative, The Broad Institute of
MIT and Harvard, Cambridge, MA
| | - Deborah Hung
- Infectious Disease and Microbiome Program, Broad
Institute of MIT and Harvard, Cambridge, MA 02142, USA,Department of Genetics, Harvard Medical School, Boston,
MA 02115, USA,Department of Molecular Biology and Center for
Computational and Integrative Biology, Massachusetts General Hospital, Boston, MA
02114, USA
| | - Pardis C. Sabeti
- Broad Institute of MIT and Harvard, Cambridge, MA 02142,
USA,Department of Organismic and Evolutionary Biology,
Harvard University, Cambridge, MA, USA,Department of Immunology and Infectious Diseases, Harvard
T.H. Chan School of Public Health, Harvard University, Boston, MA, USA,Howard Hughes Medical Institute, Chevy Chase, MD,
USA,Massachusetts Consortium on Pathogen Readiness, Boston,
MA, USA
| | - Richard Novak
- Wyss Institute for Biologically Inspired Engineering,
Harvard University
| | - Robert Rogers
- Department of Medicine, Beth Israel Deaconess Medical
Center, MA 02115, USA,Massachusetts General Hospital, MA 02114, USA
| | - Donald E. Ingber
- John A. Paulson School of Engineering and Applied
Sciences, Harvard University, Cambridge, MA 02138,Wyss Institute for Biologically Inspired Engineering,
Harvard University,Vascular Biology Program and Department of Surgery,
Boston Children’s Hospital, Harvard Medical School, Boston, MA USA
| | - Z. Gordon Jiang
- Harvard Medical School, Boston, MA 02115, USA,Department of Medicine, Beth Israel Deaconess Medical
Center, MA 02115, USA,Division of Gastroenterology, Hepatology and Nutrition,
Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA 02215,
USA
| | - Dejan Juric
- Department of Medicine, Harvard Medical School, Boston,
MA 02115, USA,Massachusetts General Hospital Cancer Center, Department
of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Mehrtash Babadi
- Data Sciences Platform, Broad Institute of MIT and
Harvard, Cambridge, MA 02142,Precision Cardiology Laboratory, Broad Institute of MIT
and Harvard, Cambridge, MA 02142, USA
| | - Samouil L. Farhi
- Klarman Cell Observatory, Broad Institute of MIT and
Harvard, Cambridge, MA 02142, USA, USA,Broad Institute of MIT and Harvard, Cambridge, MA 02142,
USA
| | - Benjamin Izar
- Department of Medicine, Division of Hematology/Oncology,
Columbia University Irving Medical Center, New York, NY,Columbia Center for Translational Immunology, New York,
NY,Herbert Irving Comprehensive Cancer Center, Columbia
University Irving Medical Center, New York, NY,Program for Mathematical Genomics, Columbia University
Irving Medical Center, New York, NY
| | - James R. Stone
- Department of Pathology, Massachusetts General Hospital,
Harvard Medical School, Boston, MA 02115, USA
| | - Ioannis S. Vlachos
- Broad Institute of MIT and Harvard, Cambridge, MA 02142,
USA,Harvard Medical School, Boston, MA 02115, USA,Department of Pathology, Beth Israel Deaconess Medical
Center, Boston, MA 02115, USA,Harvard Medical School Initiative for RNA Medicine,
Boston, MA 02115, USA,Cancer Research Institute, Beth Israel Deaconess Medical
Center, Boston, MA 02115, USA
| | - Isaac H. Solomon
- Department of Pathology, Brigham and Women’s
Hospital, Boston, MA 02115
| | - Orr Ashenberg
- Klarman Cell Observatory, Broad Institute of MIT and
Harvard, Cambridge, MA 02142, USA, USA
| | - Caroline B.M. Porter
- Klarman Cell Observatory, Broad Institute of MIT and
Harvard, Cambridge, MA 02142, USA, USA
| | - Bo Li
- Klarman Cell Observatory, Broad Institute of MIT and
Harvard, Cambridge, MA 02142, USA, USA,Center for Immunology and Inflammatory Diseases, Department
of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA,Department of Medicine, Harvard Medical School, Boston,
MA 02115, USA
| | - Alex K. Shalek
- Broad Institute of MIT and Harvard, Cambridge, MA 02142,
USA,Program in Health Sciences & Technology, Harvard
Medical School & Massachusetts Institute of Technology, Boston, MA 02115,
USA,Institute for Medical Engineering & Science,
Massachusetts Institute of Technology, Cambridge, MA 02139, USA,Koch Institute for Integrative Cancer Research,
Massachusetts Institute of Technology, Cambridge, MA 02139, USA,Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA
02139, USA,Harvard Graduate Program in Biophysics, Harvard University,
Cambridge, MA 02138, USA,Harvard Medical School, Boston, MA 02115, USA,Harvard Stem Cell Institute, Cambridge, MA, USA,Program in Computational & Systems Biology,
Massachusetts Institute of Technology, Cambridge, MA 02139, USA,Program in Immunology, Harvard Medical School, Boston, MA
02115, USA,Department of Chemistry, Massachusetts Institute of
Technology, Cambridge, MA 02139, USA
| | - Alexandra-Chloé Villani
- Broad Institute of MIT and Harvard, Cambridge, MA 02142,
USA,Center for Immunology and Inflammatory Diseases, Department
of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA,Center for Cancer Research, Massachusetts General Hospital,
Harvard Medical School, Boston, MA 02114, USA,Department of Medicine, Harvard Medical School, Boston,
MA 02115, USA
| | - Orit Rozenblatt-Rosen
- Klarman Cell Observatory, Broad Institute of MIT and
Harvard, Cambridge, MA 02142, USA, USA,Current address: Genentech, 1 DNA Way, South San
Francisco, CA, USA
| | - Aviv Regev
- Klarman Cell Observatory, Broad Institute of MIT and
Harvard, Cambridge, MA 02142, USA, USA,Koch Institute for Integrative Cancer Research,
Massachusetts Institute of Technology, Cambridge, MA 02139, USA,Howard Hughes Medical Institute, Chevy Chase, MD,
USA,Current address: Genentech, 1 DNA Way, South San
Francisco, CA, USA
| |
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18
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Delorey TM, Ziegler CGK, Heimberg G, Normand R, Yang Y, Segerstolpe A, Abbondanza D, Fleming SJ, Subramanian A, Montoro DT, Jagadeesh KA, Dey KK, Sen P, Slyper M, Pita-Juárez YH, Phillips D, Bloom-Ackerman Z, Barkas N, Ganna A, Gomez J, Normandin E, Naderi P, Popov YV, Raju SS, Niezen S, Tsai LTY, Siddle KJ, Sud M, Tran VM, Vellarikkal SK, Amir-Zilberstein L, Atri DS, Beechem J, Brook OR, Chen J, Divakar P, Dorceus P, Engreitz JM, Essene A, Fitzgerald DM, Fropf R, Gazal S, Gould J, Grzyb J, Harvey T, Hecht J, Hether T, Jane-Valbuena J, Leney-Greene M, Ma H, McCabe C, McLoughlin DE, Miller EM, Muus C, Niemi M, Padera R, Pan L, Pant D, Pe’er C, Pfiffner-Borges J, Pinto CJ, Plaisted J, Reeves J, Ross M, Rudy M, Rueckert EH, Siciliano M, Sturm A, Todres E, Waghray A, Warren S, Zhang S, Zollinger DR, Cosimi L, Gupta RM, Hacohen N, Hide W, Price AL, Rajagopal J, Tata PR, Riedel S, Szabo G, Tickle TL, Hung D, Sabeti PC, Novak R, Rogers R, Ingber DE, Jiang ZG, Juric D, Babadi M, Farhi SL, Stone JR, Vlachos IS, Solomon IH, Ashenberg O, Porter CB, Li B, Shalek AK, Villani AC, Rozenblatt-Rosen O, Regev A. A single-cell and spatial atlas of autopsy tissues reveals pathology and cellular targets of SARS-CoV-2. bioRxiv 2021:2021.02.25.430130. [PMID: 33655247 PMCID: PMC7924267 DOI: 10.1101/2021.02.25.430130] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
The SARS-CoV-2 pandemic has caused over 1 million deaths globally, mostly due to acute lung injury and acute respiratory distress syndrome, or direct complications resulting in multiple-organ failures. Little is known about the host tissue immune and cellular responses associated with COVID-19 infection, symptoms, and lethality. To address this, we collected tissues from 11 organs during the clinical autopsy of 17 individuals who succumbed to COVID-19, resulting in a tissue bank of approximately 420 specimens. We generated comprehensive cellular maps capturing COVID-19 biology related to patients' demise through single-cell and single-nucleus RNA-Seq of lung, kidney, liver and heart tissues, and further contextualized our findings through spatial RNA profiling of distinct lung regions. We developed a computational framework that incorporates removal of ambient RNA and automated cell type annotation to facilitate comparison with other healthy and diseased tissue atlases. In the lung, we uncovered significantly altered transcriptional programs within the epithelial, immune, and stromal compartments and cell intrinsic changes in multiple cell types relative to lung tissue from healthy controls. We observed evidence of: alveolar type 2 (AT2) differentiation replacing depleted alveolar type 1 (AT1) lung epithelial cells, as previously seen in fibrosis; a concomitant increase in myofibroblasts reflective of defective tissue repair; and, putative TP63+ intrapulmonary basal-like progenitor (IPBLP) cells, similar to cells identified in H1N1 influenza, that may serve as an emergency cellular reserve for severely damaged alveoli. Together, these findings suggest the activation and failure of multiple avenues for regeneration of the epithelium in these terminal lungs. SARS-CoV-2 RNA reads were enriched in lung mononuclear phagocytic cells and endothelial cells, and these cells expressed distinct host response transcriptional programs. We corroborated the compositional and transcriptional changes in lung tissue through spatial analysis of RNA profiles in situ and distinguished unique tissue host responses between regions with and without viral RNA, and in COVID-19 donor tissues relative to healthy lung. Finally, we analyzed genetic regions implicated in COVID-19 GWAS with transcriptomic data to implicate specific cell types and genes associated with disease severity. Overall, our COVID-19 cell atlas is a foundational dataset to better understand the biological impact of SARS-CoV-2 infection across the human body and empowers the identification of new therapeutic interventions and prevention strategies.
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Affiliation(s)
- Toni M. Delorey
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
| | - Carly G. K. Ziegler
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Program in Health Sciences & Technology, Harvard Medical School & Massachusetts Institute of Technology, Boston, MA 02115, USA
- Institute for Medical Engineering & Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA 02139, USA
- Harvard Graduate Program in Biophysics, Harvard University, Cambridge, MA 02138, USA
| | - Graham Heimberg
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
| | - Rachelly Normand
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Center for Immunology and Inflammatory Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
- Center for Cancer Research, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA
- Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Yiming Yang
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
- Center for Immunology and Inflammatory Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Asa Segerstolpe
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
| | - Domenic Abbondanza
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
| | - Stephen J. Fleming
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142
- Precision Cardiology Laboratory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Ayshwarya Subramanian
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
| | | | - Karthik A. Jagadeesh
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
| | - Kushal K. Dey
- Department of Epidemiology, Harvard School of Public Health
| | - Pritha Sen
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Center for Immunology and Inflammatory Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
- Division of Infectious Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Michal Slyper
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
| | - Yered H. Pita-Juárez
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Harvard Medical School, Boston, MA 02115, USA
- Department of Pathology, Beth Israel Deaconess Medical Center, Boston, MA 02115, USA
- Harvard Medical School Initiative for RNA Medicine, Boston, MA 02115, USA
- Cancer Research Institute, Beth Israel Deaconess Medical Center, Boston, MA 02115, USA
| | - Devan Phillips
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
| | - Zohar Bloom-Ackerman
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Nick Barkas
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142
| | - Andrea Ganna
- Institute for Molecular Medicine Finland, Helsinki, Finland
- Analytical & Translational Genetics Unit, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - James Gomez
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Erica Normandin
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Harvard Medical School, Boston, MA 02115, USA
| | - Pourya Naderi
- Harvard Medical School, Boston, MA 02115, USA
- Department of Pathology, Beth Israel Deaconess Medical Center, Boston, MA 02115, USA
- Harvard Medical School Initiative for RNA Medicine, Boston, MA 02115, USA
| | - Yury V. Popov
- Harvard Medical School, Boston, MA 02115, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, MA 02115, USA
- Division of Gastroenterology, Hepatology and Nutrition, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA
| | - Siddharth S. Raju
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
- FAS Center for Systems Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
| | - Sebastian Niezen
- Harvard Medical School, Boston, MA 02115, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, MA 02115, USA
- Division of Gastroenterology, Hepatology and Nutrition, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA
| | - Linus T.-Y. Tsai
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Harvard Medical School, Boston, MA 02115, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, MA 02115, USA
- Division of Endocrinology, Diabetes, and Metabolism, Beth Israel Deaconess Medical Center, Boston, MA 02115
- Boston Nutrition and Obesity Research Center Functional Genomics and Bioinformatics Core Boston, MA 02115, USA
| | - Katherine J. Siddle
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA
| | - Malika Sud
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
| | - Victoria M. Tran
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Shamsudheen K. Vellarikkal
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Divisions of Cardiovascular Medicine and Genetics, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Liat Amir-Zilberstein
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
| | - Deepak S. Atri
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Divisions of Cardiovascular Medicine and Genetics, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | | | - Olga R. Brook
- Department of Radiology, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA
| | - Jonathan Chen
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02115, USA
| | | | - Phylicia Dorceus
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
| | - Jesse M. Engreitz
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Genetics and BASE Initiative, Stanford University School of Medicine
| | - Adam Essene
- Department of Medicine, Beth Israel Deaconess Medical Center, MA 02115, USA
- Division of Endocrinology, Diabetes, and Metabolism, Beth Israel Deaconess Medical Center, Boston, MA 02115
- Boston Nutrition and Obesity Research Center Functional Genomics and Bioinformatics Core Boston, MA 02115, USA
| | - Donna M. Fitzgerald
- Massachusetts General Hospital Cancer Center, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Robin Fropf
- NanoString Technologies Inc., Seattle, WA 98109, USA
| | - Steven Gazal
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Joshua Gould
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142
| | - John Grzyb
- Department of Pathology, Brigham and Women’s Hospital, Boston, MA 02115
| | - Tyler Harvey
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
| | - Jonathan Hecht
- Harvard Medical School, Boston, MA 02115, USA
- Department of Pathology, Beth Israel Deaconess Medical Center, Boston, MA 02115, USA
| | - Tyler Hether
- NanoString Technologies Inc., Seattle, WA 98109, USA
| | - Judit Jane-Valbuena
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
| | | | - Hui Ma
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
- Center for Immunology and Inflammatory Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Cristin McCabe
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
| | - Daniel E. McLoughlin
- Massachusetts General Hospital Cancer Center, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | | | - Christoph Muus
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138
| | - Mari Niemi
- Institute for Molecular Medicine Finland, Helsinki, Finland
| | - Robert Padera
- Department of Pathology, Brigham and Women’s Hospital, Boston, MA 02115
- Harvard-MIT Division of Health Sciences and Technology, Cambridge MA
- Department of Pathology, Harvard Medical School, Boston, MA 02115, USA
| | - Liuliu Pan
- NanoString Technologies Inc., Seattle, WA 98109, USA
| | - Deepti Pant
- Department of Medicine, Beth Israel Deaconess Medical Center, MA 02115, USA
- Division of Endocrinology, Diabetes, and Metabolism, Beth Israel Deaconess Medical Center, Boston, MA 02115
- Boston Nutrition and Obesity Research Center Functional Genomics and Bioinformatics Core Boston, MA 02115, USA
| | - Carmel Pe’er
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
| | | | - Christopher J. Pinto
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
- Massachusetts General Hospital Cancer Center, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Jacob Plaisted
- Department of Pathology, Brigham and Women’s Hospital, Boston, MA 02115
| | - Jason Reeves
- NanoString Technologies Inc., Seattle, WA 98109, USA
| | - Marty Ross
- NanoString Technologies Inc., Seattle, WA 98109, USA
| | - Melissa Rudy
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | | | | | - Alexander Sturm
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Ellen Todres
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
| | - Avinash Waghray
- Harvard Stem Cell Institute, Cambridge, MA, USA
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Sarah Warren
- NanoString Technologies Inc., Seattle, WA 98109, USA
| | - Shuting Zhang
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | | | - Lisa Cosimi
- Infectious Diseases Division, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Rajat M. Gupta
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Divisions of Cardiovascular Medicine and Genetics, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Nir Hacohen
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Center for Cancer Research, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
- Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Winston Hide
- Harvard Medical School, Boston, MA 02115, USA
- Department of Pathology, Beth Israel Deaconess Medical Center, Boston, MA 02115, USA
- Harvard Medical School Initiative for RNA Medicine, Boston, MA 02115, USA
- Cancer Research Institute, Beth Israel Deaconess Medical Center, Boston, MA 02115, USA
| | - Alkes L. Price
- Department of Epidemiology, Harvard School of Public Health
| | - Jayaraj Rajagopal
- Massachusetts General Hospital Cancer Center, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | | | - Stefan Riedel
- Harvard Medical School, Boston, MA 02115, USA
- Department of Pathology, Beth Israel Deaconess Medical Center, Boston, MA 02115, USA
| | - Gyongyi Szabo
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Harvard Medical School, Boston, MA 02115, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, MA 02115, USA
| | - Timothy L. Tickle
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142
| | - Deborah Hung
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
- Department of Molecular Biology and Center for Computational and Integrative Biology, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Pardis C. Sabeti
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
- Massachusetts Consortium on Pathogen Readiness, Boston, MA, USA
| | - Richard Novak
- Wyss Institute for Biologically Inspired Engineering, Harvard University
| | - Robert Rogers
- Department of Medicine, Beth Israel Deaconess Medical Center, MA 02115, USA
- Massachusetts General Hospital, MA 02114, USA
| | - Donald E. Ingber
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138
- Wyss Institute for Biologically Inspired Engineering, Harvard University
- Vascular Biology Program and Department of Surgery, Boston Children’s Hospital, Harvard Medical School, Boston, MA USA
| | - Z. Gordon Jiang
- Harvard Medical School, Boston, MA 02115, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, MA 02115, USA
- Division of Gastroenterology, Hepatology and Nutrition, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA
| | - Dejan Juric
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
- Massachusetts General Hospital Cancer Center, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Mehrtash Babadi
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142
- Precision Cardiology Laboratory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Samouil L. Farhi
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
| | - James R. Stone
- Department of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Ioannis S. Vlachos
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Harvard Medical School, Boston, MA 02115, USA
- Department of Pathology, Beth Israel Deaconess Medical Center, Boston, MA 02115, USA
- Harvard Medical School Initiative for RNA Medicine, Boston, MA 02115, USA
- Cancer Research Institute, Beth Israel Deaconess Medical Center, Boston, MA 02115, USA
| | - Isaac H. Solomon
- Department of Pathology, Brigham and Women’s Hospital, Boston, MA 02115
| | - Orr Ashenberg
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
| | - Caroline B.M. Porter
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
| | - Bo Li
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
- Center for Immunology and Inflammatory Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Alex K. Shalek
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Program in Health Sciences & Technology, Harvard Medical School & Massachusetts Institute of Technology, Boston, MA 02115, USA
- Institute for Medical Engineering & Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA 02139, USA
- Harvard Graduate Program in Biophysics, Harvard University, Cambridge, MA 02138, USA
- Harvard Medical School, Boston, MA 02115, USA
- Harvard Stem Cell Institute, Cambridge, MA, USA
- Program in Computational & Systems Biology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Program in Immunology, Harvard Medical School, Boston, MA 02115, USA
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Alexandra-Chloé Villani
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Center for Immunology and Inflammatory Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
- Center for Cancer Research, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Orit Rozenblatt-Rosen
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
- Current address: Genentech, 1 DNA Way, South San Francisco, CA, USA
| | - Aviv Regev
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
- Current address: Genentech, 1 DNA Way, South San Francisco, CA, USA
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19
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Tucker NR, Chaffin M, Fleming SJ, Hall AW, Parsons VA, Bedi KC, Akkad AD, Herndon CN, Arduini A, Papangeli I, Roselli C, Aguet F, Choi SH, Ardlie KG, Babadi M, Margulies KB, Stegmann CM, Ellinor PT. Transcriptional and Cellular Diversity of the Human Heart. Circulation 2020; 142:466-482. [PMID: 32403949 PMCID: PMC7666104 DOI: 10.1161/circulationaha.119.045401] [Citation(s) in RCA: 250] [Impact Index Per Article: 62.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
BACKGROUND The human heart requires a complex ensemble of specialized cell types to perform its essential function. A greater knowledge of the intricate cellular milieu of the heart is critical to increase our understanding of cardiac homeostasis and pathology. As recent advances in low-input RNA sequencing have allowed definitions of cellular transcriptomes at single-cell resolution at scale, we have applied these approaches to assess the cellular and transcriptional diversity of the nonfailing human heart. METHODS Microfluidic encapsulation and barcoding was used to perform single nuclear RNA sequencing with samples from 7 human donors, selected for their absence of overt cardiac disease. Individual nuclear transcriptomes were then clustered based on transcriptional profiles of highly variable genes. These clusters were used as the basis for between-chamber and between-sex differential gene expression analyses and intersection with genetic and pharmacologic data. RESULTS We sequenced the transcriptomes of 287 269 single cardiac nuclei, revealing 9 major cell types and 20 subclusters of cell types within the human heart. Cellular subclasses include 2 distinct groups of resident macrophages, 4 endothelial subtypes, and 2 fibroblast subsets. Comparisons of cellular transcriptomes by cardiac chamber or sex reveal diversity not only in cardiomyocyte transcriptional programs but also in subtypes involved in extracellular matrix remodeling and vascularization. Using genetic association data, we identified strong enrichment for the role of cell subtypes in cardiac traits and diseases. Intersection of our data set with genes on cardiac clinical testing panels and the druggable genome reveals striking patterns of cellular specificity. CONCLUSIONS Using large-scale single nuclei RNA sequencing, we defined the transcriptional and cellular diversity in the normal human heart. Our identification of discrete cell subtypes and differentially expressed genes within the heart will ultimately facilitate the development of new therapeutics for cardiovascular diseases.
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Affiliation(s)
- Nathan R. Tucker
- Precision Cardiology Laboratory, The Broad Institute, Cambridge, MA, USA 02142
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA 02114
- Masonic Medical Research Institute, Utica, NY, USA 13501
| | - Mark Chaffin
- Precision Cardiology Laboratory, The Broad Institute, Cambridge, MA, USA 02142
| | - Stephen J. Fleming
- Precision Cardiology Laboratory, The Broad Institute, Cambridge, MA, USA 02142
- Data Sciences Platform, The Broad Institute of MIT and Harvard, Cambridge, MA, USA 02142
| | - Amelia W. Hall
- Precision Cardiology Laboratory, The Broad Institute, Cambridge, MA, USA 02142
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA 02114
| | - Victoria A. Parsons
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA 02114
| | - Kenneth C. Bedi
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA 19104
| | - Amer-Denis Akkad
- Precision Cardiology Laboratory, The Broad Institute, Cambridge, MA, USA 02142
- Precision Cardiology Laboratory, Bayer US LLC, Cambridge, MA, 02142
| | - Caroline N. Herndon
- Precision Cardiology Laboratory, The Broad Institute, Cambridge, MA, USA 02142
| | - Alessandro Arduini
- Precision Cardiology Laboratory, The Broad Institute, Cambridge, MA, USA 02142
| | - Irinna Papangeli
- Precision Cardiology Laboratory, The Broad Institute, Cambridge, MA, USA 02142
- Precision Cardiology Laboratory, Bayer US LLC, Cambridge, MA, 02142
| | - Carolina Roselli
- Precision Cardiology Laboratory, The Broad Institute, Cambridge, MA, USA 02142
- University Medical Center Groningen, University of Groningen, 9712 CP, Groningen, NL
| | - François Aguet
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA 02142
| | - Seung Hoan Choi
- Precision Cardiology Laboratory, The Broad Institute, Cambridge, MA, USA 02142
| | | | - Mehrtash Babadi
- Precision Cardiology Laboratory, The Broad Institute, Cambridge, MA, USA 02142
- Data Sciences Platform, The Broad Institute of MIT and Harvard, Cambridge, MA, USA 02142
| | - Kenneth B. Margulies
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA 19104
| | - Christian M. Stegmann
- Precision Cardiology Laboratory, The Broad Institute, Cambridge, MA, USA 02142
- Precision Cardiology Laboratory, Bayer US LLC, Cambridge, MA, 02142
| | - Patrick T. Ellinor
- Precision Cardiology Laboratory, The Broad Institute, Cambridge, MA, USA 02142
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA 02114
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20
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Abstract
Abstract
We propose, implement, and evaluate a novel method (GATK gCNV) for accurate discovery of rare and common copy-number variations (CNVs) from read-depth data obtained from whole genome sequencing (WGS), whole exome sequencing (WES), or custom gene panels. GATK gCNV utilizes a sophisticated Bayesian model to learn bias factors arising from sequencing and library preparation. This model accounts for ploidy of sex chromosomes and autosomal aneuploidies, treats GC bias probabilistically, and automatically determines the necessary level of model complexity in a data-driven manner. Unlike most existing read-depth methods, GATK gCNV maintains a high level of sensitivity in common CNV regions, due to a hierarchical hidden Markov model used for accurate genotyping of multi-allelic loci. Furthermore, GATK gCNV performs bias modeling and CNV discovery simultaneously and self-consistently, resulting in significantly improved sensitivity and precision. Our implementation utilizes the PyMC3/Theano framework for performing automatic differentiation variational inference (ADVI). In addition, GATK gCNV automatically scatters large tasks across multiple machines using the Cromwell/WDL framework, enabling the scalable processing of large cohorts.
We use GATK gCNV to compute copy-number transmission and de novo rates in a cohort of WES trios and observe consistency with observed population metrics. Furthermore, we benchmark GATK gCNV for sensitivity, precision, and reproducibility of both rare and common CNV calls. Using a cohort of WES blood normal samples from The Cancer Genome Atlas (TCGA), we show that GATK gCNV calls are in remarkable concordance with Genome STRiP calls on matched WGS data and gCNV substantially outperforms XHMM and CODEX. We also validate GATK gCNV calls on WGS data against calls made using PacBio long reads.
Citation Format: Mehrtash Babadi, Samuel K. Lee, Andrey Smirnov, Lee Lichtenstein, Laura D. Gauthier, Daniel P. Howrigan, Timothy Poterba. Precise common and rare germline CNV calling with GATK [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2287.
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21
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Savitz S, Babadi M, Lifshitz R. Multiple-scale structures: from Faraday waves to soft-matter quasicrystals. IUCrJ 2018; 5:247-268. [PMID: 29755742 PMCID: PMC5929372 DOI: 10.1107/s2052252518001161] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/27/2017] [Accepted: 01/18/2018] [Indexed: 06/08/2023]
Abstract
For many years, quasicrystals were observed only as solid-state metallic alloys, yet current research is now actively exploring their formation in a variety of soft materials, including systems of macromolecules, nanoparticles and colloids. Much effort is being invested in understanding the thermodynamic properties of these soft-matter quasicrystals in order to predict and possibly control the structures that form, and hopefully to shed light on the broader yet unresolved general questions of quasicrystal formation and stability. Moreover, the ability to control the self-assembly of soft quasicrystals may contribute to the development of novel photonics or other applications based on self-assembled metamaterials. Here a path is followed, leading to quantitative stability predictions, that starts with a model developed two decades ago to treat the formation of multiple-scale quasiperiodic Faraday waves (standing wave patterns in vibrating fluid surfaces) and which was later mapped onto systems of soft particles, interacting via multiple-scale pair potentials. The article reviews, and substantially expands, the quantitative predictions of these models, while correcting a few discrepancies in earlier calculations, and presents new analytical methods for treating the models. In so doing, a number of new stable quasicrystalline structures are found with octagonal, octadecagonal and higher-order symmetries, some of which may, it is hoped, be observed in future experiments.
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Affiliation(s)
- Samuel Savitz
- Condensed Matter Physics, California Institute of Technology, Pasadena, CA 91125, USA
| | - Mehrtash Babadi
- Condensed Matter Physics, California Institute of Technology, Pasadena, CA 91125, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Ron Lifshitz
- Condensed Matter Physics, California Institute of Technology, Pasadena, CA 91125, USA
- Raymond and Beverly Sackler School of Physics and Astronomy, Tel Aviv University, Tel Aviv 69978, Israel
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22
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Shukla SA, Bachireddy P, Schilling B, Galonska C, Zhan Q, Bango C, Langer R, Lee PC, Gusenleitner D, Keskin DB, Babadi M, Mohammad A, Gnirke A, Clement K, Cartun ZJ, Van Allen EM, Miao D, Huang Y, Snyder A, Merghoub T, Wolchok JD, Garraway LA, Meissner A, Weber JS, Hacohen N, Neuberg D, Potts PR, Murphy GF, Lian CG, Schadendorf D, Hodi FS, Wu CJ. Cancer-Germline Antigen Expression Discriminates Clinical Outcome to CTLA-4 Blockade. Cell 2018; 173:624-633.e8. [PMID: 29656892 DOI: 10.1016/j.cell.2018.03.026] [Citation(s) in RCA: 102] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2017] [Revised: 12/11/2017] [Accepted: 03/13/2018] [Indexed: 02/07/2023]
Abstract
CTLA-4 immune checkpoint blockade is clinically effective in a subset of patients with metastatic melanoma. We identify a subcluster of MAGE-A cancer-germline antigens, located within a narrow 75 kb region of chromosome Xq28, that predicts resistance uniquely to blockade of CTLA-4, but not PD-1. We validate this gene expression signature in an independent anti-CTLA-4-treated cohort and show its specificity to the CTLA-4 pathway with two independent anti-PD-1-treated cohorts. Autophagy, a process critical for optimal anti-cancer immunity, has previously been shown to be suppressed by the MAGE-TRIM28 ubiquitin ligase in vitro. We now show that the expression of the key autophagosome component LC3B and other activators of autophagy are negatively associated with MAGE-A protein levels in human melanomas, including samples from patients with resistance to CTLA-4 blockade. Our findings implicate autophagy suppression in resistance to CTLA-4 blockade in melanoma, suggesting exploitation of autophagy induction for potential therapeutic synergy with CTLA-4 inhibitors.
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Affiliation(s)
- Sachet A Shukla
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA; Broad Institute, Cambridge, MA 02142, USA
| | - Pavan Bachireddy
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA; Broad Institute, Cambridge, MA 02142, USA; Department of Medicine, Brigham & Women's Hospital, Boston, MA 02115, USA
| | - Bastian Schilling
- Department of Dermatology, University Hospital, University Duisburg-Essen, 45147 Essen, Germany; German Cancer Consortium (DKTK), 69121 Heidelberg, Germany; Department of Dermatology, Venereology and Allergology, University Hospital Würzburg, 97080 Würzburg, Germany
| | | | - Qian Zhan
- Program in Dermatopathology, Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Clyde Bango
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA
| | - Rupert Langer
- Department of Pathology, University of Bern, 3012 Bern, Switzerland
| | - Patrick C Lee
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA
| | - Daniel Gusenleitner
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA
| | - Derin B Keskin
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA; Broad Institute, Cambridge, MA 02142, USA; Department of Medicine, Brigham & Women's Hospital, Boston, MA 02115, USA
| | | | | | | | - Kendell Clement
- Broad Institute, Cambridge, MA 02142, USA; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, USA
| | - Zachary J Cartun
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA
| | - Eliezer M Van Allen
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA; Broad Institute, Cambridge, MA 02142, USA; Department of Medicine, Brigham & Women's Hospital, Boston, MA 02115, USA
| | - Diana Miao
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA; Broad Institute, Cambridge, MA 02142, USA
| | - Ying Huang
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA
| | - Alexandra Snyder
- Weill Cornell Medical College, New York, NY, USA; Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY 10016, USA
| | - Taha Merghoub
- Weill Cornell Medical College, New York, NY, USA; Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY 10016, USA
| | - Jedd D Wolchok
- Weill Cornell Medical College, New York, NY, USA; Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY 10016, USA
| | - Levi A Garraway
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA; Broad Institute, Cambridge, MA 02142, USA; Department of Medicine, Brigham & Women's Hospital, Boston, MA 02115, USA
| | - Alexander Meissner
- Broad Institute, Cambridge, MA 02142, USA; Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, USA
| | - Jeffrey S Weber
- New York University Langone Medical Center, New York, NY 10016, USA
| | | | - Donna Neuberg
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02115, USA
| | - Patrick R Potts
- Department of Cell and Molecular Biology, St. Jude Children's Research Hospital, Memphis, TN 38105-3678, USA
| | - George F Murphy
- Program in Dermatopathology, Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Christine G Lian
- Program in Dermatopathology, Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Dirk Schadendorf
- Department of Dermatology, University Hospital, University Duisburg-Essen, 45147 Essen, Germany; German Cancer Consortium (DKTK), 69121 Heidelberg, Germany
| | - F Stephen Hodi
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA; Department of Medicine, Brigham & Women's Hospital, Boston, MA 02115, USA
| | - Catherine J Wu
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA; Broad Institute, Cambridge, MA 02142, USA; Department of Medicine, Brigham & Women's Hospital, Boston, MA 02115, USA.
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23
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Pekker D, Babadi M, Sensarma R, Zinner N, Pollet L, Zwierlein MW, Demler E. Competition between pairing and ferromagnetic instabilities in ultracold Fermi gases near Feshbach resonances. Phys Rev Lett 2011; 106:050402. [PMID: 21405378 DOI: 10.1103/physrevlett.106.050402] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/26/2010] [Revised: 12/31/2010] [Indexed: 05/30/2023]
Abstract
We study the quench dynamics of a two-component ultracold Fermi gas from the weak into the strong interaction regime, where the short time dynamics are governed by the exponential growth rate of unstable collective modes. We obtain an effective interaction that takes into account both Pauli blocking and the energy dependence of the scattering amplitude near a Feshbach resonance. Using this interaction we analyze the competing instabilities towards Stoner ferromagnetism and pairing.
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Affiliation(s)
- David Pekker
- Physics Department, Harvard University, Cambridge, Massachusetts 02138, USA
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24
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Abstract
We have proposed an efficient parametrization method for a recent variant of the Gay Berne potential for dissimilar and biaxial particles [Phys. Rev. E 67, 041710 (2003)] and demonstrated it for a set of small organic molecules. Compared with the previously proposed coarse-grained models, the new potential exhibits a superior performance in close contact and large distant interactions. The repercussions of thermal vibrations and elasticity have been studied through a statistical method. The study justifies that the potential of mean force is representable with the same functional form, extending the application of this coarse-grained description to a broader range of molecules. Moreover, the advantage of employing coarse-grained models over truncated atomistic summations with large distance cutoffs has been briefly studied.
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Affiliation(s)
- M Babadi
- Department of Physics, Sharif University of Technology, P.O. Box 11365-9161, Tehran, Iran
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