301
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Turkalj S, Jakobsen NA, Groom A, Metzner M, Riva SG, Gür ER, Usukhbayar B, Salazar MA, Hentges LD, Mickute G, Clark K, Sopp P, Davies JOJ, Hughes JR, Vyas P. GTAC enables parallel genotyping of multiple genomic loci with chromatin accessibility profiling in single cells. Cell Stem Cell 2023; 30:722-740.e11. [PMID: 37146586 DOI: 10.1016/j.stem.2023.04.012] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Revised: 02/23/2023] [Accepted: 04/12/2023] [Indexed: 05/07/2023]
Abstract
Understanding clonal evolution and cancer development requires experimental approaches for characterizing the consequences of somatic mutations on gene regulation. However, no methods currently exist that efficiently link high-content chromatin accessibility with high-confidence genotyping in single cells. To address this, we developed Genotyping with the Assay for Transposase-Accessible Chromatin (GTAC), enabling accurate mutation detection at multiple amplified loci, coupled with robust chromatin accessibility readout. We applied GTAC to primary acute myeloid leukemia, obtaining high-quality chromatin accessibility profiles and clonal identities for multiple mutations in 88% of cells. We traced chromatin variation throughout clonal evolution, showing the restriction of different clones to distinct differentiation stages. Furthermore, we identified switches in transcription factor motif accessibility associated with a specific combination of driver mutations, which biased transformed progenitors toward a leukemia stem cell-like chromatin state. GTAC is a powerful tool to study clonal heterogeneity across a wide spectrum of pre-malignant and neoplastic conditions.
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Affiliation(s)
- Sven Turkalj
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK; Oxford Centre for Haematology, NIHR Oxford Biomedical Research Centre, Oxford, UK
| | - Niels Asger Jakobsen
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK; Oxford Centre for Haematology, NIHR Oxford Biomedical Research Centre, Oxford, UK; Department of Haematology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Angus Groom
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK; Oxford Centre for Haematology, NIHR Oxford Biomedical Research Centre, Oxford, UK
| | - Marlen Metzner
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK; Oxford Centre for Haematology, NIHR Oxford Biomedical Research Centre, Oxford, UK
| | - Simone G Riva
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK; MRC WIMM Centre for Computational Biology, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - E Ravza Gür
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK; MRC WIMM Centre for Computational Biology, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Batchimeg Usukhbayar
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK; Oxford Centre for Haematology, NIHR Oxford Biomedical Research Centre, Oxford, UK
| | - Mirian Angulo Salazar
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK; Oxford Centre for Haematology, NIHR Oxford Biomedical Research Centre, Oxford, UK
| | - Lance D Hentges
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK; MRC WIMM Centre for Computational Biology, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Gerda Mickute
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK; Oxford Centre for Haematology, NIHR Oxford Biomedical Research Centre, Oxford, UK
| | - Kevin Clark
- Flow Cytometry Facility, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Paul Sopp
- Flow Cytometry Facility, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - James O J Davies
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK; Oxford Centre for Haematology, NIHR Oxford Biomedical Research Centre, Oxford, UK; Department of Haematology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Jim R Hughes
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK; MRC WIMM Centre for Computational Biology, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Paresh Vyas
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK; Oxford Centre for Haematology, NIHR Oxford Biomedical Research Centre, Oxford, UK; Department of Haematology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
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302
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Paek A, Jose E, March-Steinman W, Wilson B, Shanks L. Temporal Coordination of the Transcription Factor Response to H 2O 2 stress. RESEARCH SQUARE 2023:rs.3.rs-2791121. [PMID: 37205449 PMCID: PMC10187433 DOI: 10.21203/rs.3.rs-2791121/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Oxidative stress from excess H2O2 activates transcription factors (TFs) that restore redox balance and repair oxidative damage. Though many TFs are activated by H2O2, it is unknown whether they are activated at the same H2O2 concentration or time after H2O2 stress. We found TF activation is tightly coordinated over time and dose dependent. We first focused on p53 and FOXO1 and found that in response to low H2O2, p53 is activated rapidly while FOXO1 remains inactive. In contrast, cells respond to high H2O2 in two temporal phases. In the first phase FOXO1 rapidly shuttles to the nucleus while p53 remains inactive. In the second phase FOXO1 shuts off and p53 levels rise. Other TFs are activated in the first phase with FOXO1 (NF-κB, NFAT1), or the second phase with p53 (NRF2, JUN), but not both. The two phases result in large differences in gene expression. Finally, we provide evidence that 2-Cys peroxiredoxins control which TF are activated and the timing of TF activation.
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303
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Zhang F, Jiao H, Wang Y, Yang C, Li L, Wang Z, Tong R, Zhou J, Shen J, Li L. InferLoop: leveraging single-cell chromatin accessibility for the signal of chromatin loop. Brief Bioinform 2023; 24:7150740. [PMID: 37139553 DOI: 10.1093/bib/bbad166] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Revised: 03/21/2023] [Accepted: 04/10/2023] [Indexed: 05/05/2023] Open
Abstract
Deciphering cell-type-specific 3D structures of chromatin is challenging. Here, we present InferLoop, a novel method for inferring the strength of chromatin interaction using single-cell chromatin accessibility data. The workflow of InferLoop is, first, to conduct signal enhancement by grouping nearby cells into bins, and then, for each bin, leverage accessibility signals for loop signals using a newly constructed metric that is similar to the perturbation of the Pearson correlation coefficient. In this study, we have described three application scenarios of InferLoop, including the inference of cell-type-specific loop signals, the prediction of gene expression levels and the interpretation of intergenic loci. The effectiveness and superiority of InferLoop over other methods in those three scenarios are rigorously validated by using the single-cell 3D genome structure data of human brain cortex and human blood, the single-cell multi-omics data of human blood and mouse brain cortex, and the intergenic loci in the GWAS Catalog database as well as the GTEx database, respectively. In addition, InferLoop can be applied to predict loop signals of individual spots using the spatial chromatin accessibility data of mouse embryo. InferLoop is available at https://github.com/jumphone/inferloop.
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Affiliation(s)
- Feng Zhang
- Department of Histoembryology, Genetics and Developmental Biology, Shanghai Key Laboratory of Reproductive Medicine, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Huiyuan Jiao
- Department of Histoembryology, Genetics and Developmental Biology, Shanghai Key Laboratory of Reproductive Medicine, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Yihao Wang
- Department of Ophthalmology, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai 200025, China
- Institute of Translational Medicine, National Facility for Translational Medicine, Shanghai Jiao Tong University, Shanghai 201109, China
| | - Chen Yang
- Department of Histoembryology, Genetics and Developmental Biology, Shanghai Key Laboratory of Reproductive Medicine, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Linying Li
- Department of Central Laboratory, Shanghai Children's Hospital, School of medicine, Shanghai Jiao Tong University, Shanghai 200062, China
| | - Zhiming Wang
- Department of Histoembryology, Genetics and Developmental Biology, Shanghai Key Laboratory of Reproductive Medicine, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Ran Tong
- Department of Histoembryology, Genetics and Developmental Biology, Shanghai Key Laboratory of Reproductive Medicine, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Junmei Zhou
- Department of Central Laboratory, Shanghai Children's Hospital, School of medicine, Shanghai Jiao Tong University, Shanghai 200062, China
| | - Jianfeng Shen
- Department of Ophthalmology, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai 200025, China
- Institute of Translational Medicine, National Facility for Translational Medicine, Shanghai Jiao Tong University, Shanghai 201109, China
| | - Lingjie Li
- Department of Histoembryology, Genetics and Developmental Biology, Shanghai Key Laboratory of Reproductive Medicine, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
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304
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Lareau CA, Liu V, Muus C, Praktiknjo SD, Nitsch L, Kautz P, Sandor K, Yin Y, Gutierrez JC, Pelka K, Satpathy AT, Regev A, Sankaran VG, Ludwig LS. Mitochondrial single-cell ATAC-seq for high-throughput multi-omic detection of mitochondrial genotypes and chromatin accessibility. Nat Protoc 2023; 18:1416-1440. [PMID: 36792778 PMCID: PMC10317201 DOI: 10.1038/s41596-022-00795-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Accepted: 11/11/2022] [Indexed: 02/17/2023]
Abstract
Natural sequence variation within mitochondrial DNA (mtDNA) contributes to human phenotypes and may serve as natural genetic markers in human cells for clonal and lineage tracing. We recently developed a single-cell multi-omic approach, called 'mitochondrial single-cell assay for transposase-accessible chromatin with sequencing' (mtscATAC-seq), enabling concomitant high-throughput mtDNA genotyping and accessible chromatin profiling. Specifically, our technique allows the mitochondrial genome-wide inference of mtDNA variant heteroplasmy along with information on cell state and accessible chromatin variation in individual cells. Leveraging somatic mtDNA mutations, our method further enables inference of clonal relationships among native ex vivo-derived human cells not amenable to genetic engineering-based clonal tracing approaches. Here, we provide a step-by-step protocol for the use of mtscATAC-seq, including various cell-processing and flow cytometry workflows, by using primary hematopoietic cells, subsequent single-cell genomic library preparation and sequencing that collectively take ~3-4 days to complete. We discuss experimental and computational data quality control metrics and considerations for the extension to other mammalian tissues. Overall, mtscATAC-seq provides a broadly applicable platform to map clonal relationships between cells in human tissues, investigate fundamental aspects of mitochondrial genetics and enable additional modes of multi-omic discovery.
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Affiliation(s)
- Caleb A Lareau
- Department of Pathology, Stanford University, Stanford, CA, USA.
- Parker Institute for Cancer Immunotherapy, San Francisco, CA, USA.
| | - Vincent Liu
- Department of Pathology, Stanford University, Stanford, CA, USA
| | - Christoph Muus
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
| | - Samantha D Praktiknjo
- Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Institute for Medical Systems Biology (BIMSB), Berlin, Germany
| | - Lena Nitsch
- Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Institute for Medical Systems Biology (BIMSB), Berlin, Germany
- Department of Biology, Chemistry, Pharmacy, Freie Universität Berlin, Berlin, Germany
| | - Pauline Kautz
- Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Institute for Medical Systems Biology (BIMSB), Berlin, Germany
- Institute of Biotechnology, Technische Universität Berlin, Berlin, Germany
| | - Katalin Sandor
- Department of Pathology, Stanford University, Stanford, CA, USA
| | - Yajie Yin
- Department of Pathology, Stanford University, Stanford, CA, USA
| | | | - Karin Pelka
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA
| | - Ansuman T Satpathy
- Department of Pathology, Stanford University, Stanford, CA, USA
- Parker Institute for Cancer Immunotherapy, San Francisco, CA, USA
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA
| | - Aviv Regev
- Genentech, South San Francisco, CA, USA.
| | - Vijay G Sankaran
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
| | - Leif S Ludwig
- Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany.
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Institute for Medical Systems Biology (BIMSB), Berlin, Germany.
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305
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Krup AL, Winchester SAB, Ranade SS, Agrawal A, Devine WP, Sinha T, Choudhary K, Dominguez MH, Thomas R, Black BL, Srivastava D, Bruneau BG. A Mesp1-dependent developmental breakpoint in transcriptional and epigenomic specification of early cardiac precursors. Development 2023; 150:dev201229. [PMID: 36994838 PMCID: PMC10259516 DOI: 10.1242/dev.201229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Accepted: 03/21/2023] [Indexed: 03/31/2023]
Abstract
Transcriptional networks governing cardiac precursor cell (CPC) specification are incompletely understood owing, in part, to limitations in distinguishing CPCs from non-cardiac mesoderm in early gastrulation. We leveraged detection of early cardiac lineage transgenes within a granular single-cell transcriptomic time course of mouse embryos to identify emerging CPCs and describe their transcriptional profiles. Mesp1, a transiently expressed mesodermal transcription factor, is canonically described as an early regulator of cardiac specification. However, we observed perdurance of CPC transgene-expressing cells in Mesp1 mutants, albeit mislocalized, prompting us to investigate the scope of the role of Mesp1 in CPC emergence and differentiation. Mesp1 mutant CPCs failed to robustly activate markers of cardiomyocyte maturity and crucial cardiac transcription factors, yet they exhibited transcriptional profiles resembling cardiac mesoderm progressing towards cardiomyocyte fates. Single-cell chromatin accessibility analysis defined a Mesp1-dependent developmental breakpoint in cardiac lineage progression at a shift from mesendoderm transcriptional networks to those necessary for cardiac patterning and morphogenesis. These results reveal Mesp1-independent aspects of early CPC specification and underscore a Mesp1-dependent regulatory landscape required for progression through cardiogenesis.
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Affiliation(s)
- Alexis Leigh Krup
- Biomedical Sciences Program, University of California, San Francisco, CA 94158, USA
- Gladstone Institutes of Cardiovascular Disease, Gladstone Institutes, San Francisco, CA 94158, USA
| | - Sarah A. B. Winchester
- Gladstone Institutes of Cardiovascular Disease, Gladstone Institutes, San Francisco, CA 94158, USA
| | - Sanjeev S. Ranade
- Gladstone Institutes of Cardiovascular Disease, Gladstone Institutes, San Francisco, CA 94158, USA
| | - Ayushi Agrawal
- Gladstone Institutes of Cardiovascular Disease, Gladstone Institutes, San Francisco, CA 94158, USA
| | - W. Patrick Devine
- Department of Pathology, University of California, San Francisco, CA 94158, USA
| | - Tanvi Sinha
- Cardiovascular Research Institute, University of California, San Francisco, CA 94158, USA
| | - Krishna Choudhary
- Gladstone Institutes of Cardiovascular Disease, Gladstone Institutes, San Francisco, CA 94158, USA
| | - Martin H. Dominguez
- Gladstone Institutes of Cardiovascular Disease, Gladstone Institutes, San Francisco, CA 94158, USA
- Cardiovascular Research Institute, University of California, San Francisco, CA 94158, USA
- Department of Medicine, Division of Cardiology, University of California, San Francisco, CA 94158, USA
- Cardiovascular Institute and Department of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Reuben Thomas
- Gladstone Institutes of Cardiovascular Disease, Gladstone Institutes, San Francisco, CA 94158, USA
| | - Brian L. Black
- Cardiovascular Research Institute, University of California, San Francisco, CA 94158, USA
- Department of Biochemistry and Biophysics, University of California, San Francisco, CA 94158, USA
| | - Deepak Srivastava
- Gladstone Institutes of Cardiovascular Disease, Gladstone Institutes, San Francisco, CA 94158, USA
- Department of Biochemistry and Biophysics, University of California, San Francisco, CA 94158, USA
- Department of Pediatrics, University of California, San Francisco, CA 94158, USA
- Roddenberry Center for Stem Cell Biology and Medicine, Gladstone Institutes, San Francisco, CA 94158, USA
| | - Benoit G. Bruneau
- Gladstone Institutes of Cardiovascular Disease, Gladstone Institutes, San Francisco, CA 94158, USA
- Department of Pediatrics, University of California, San Francisco, CA 94158, USA
- Roddenberry Center for Stem Cell Biology and Medicine, Gladstone Institutes, San Francisco, CA 94158, USA
- Institute of Human Genetics, University of California, San Francisco, CA 94158, USA
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, CA 94158, USA
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306
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Wong D, Auguste G, Cardenas CLL, Turner AW, Chen Y, Song Y, Ma L, Perry RN, Aherrahrou R, Kuppusamy M, Yang C, Mosquera JV, Dube CJ, Khan MD, Palmore M, Kalra JK, Kavousi M, Peyser PA, Matic L, Hedin U, Manichaikul A, Sonkusare SK, Civelek M, Kovacic JC, Björkegren JL, Malhotra R, Miller CL. FHL5 Controls Vascular Disease-Associated Gene Programs in Smooth Muscle Cells. Circ Res 2023; 132:1144-1161. [PMID: 37017084 PMCID: PMC10147587 DOI: 10.1161/circresaha.122.321692] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 03/21/2023] [Indexed: 04/06/2023]
Abstract
BACKGROUND Genome-wide association studies have identified hundreds of loci associated with common vascular diseases, such as coronary artery disease, myocardial infarction, and hypertension. However, the lack of mechanistic insights for many GWAS loci limits their translation into the clinic. Among these loci with unknown functions is UFL1-four-and-a-half LIM (LIN-11, Isl-1, MEC-3) domain 5 (FHL5; chr6q16.1), which reached genome-wide significance in a recent coronary artery disease/ myocardial infarction GWAS meta-analysis. UFL1-FHL5 is also associated with several vascular diseases, consistent with the widespread pleiotropy observed for GWAS loci. METHODS We apply a multimodal approach leveraging statistical fine-mapping, epigenomic profiling, and ex vivo analysis of human coronary artery tissues to implicate FHL5 as the top candidate causal gene. We unravel the molecular mechanisms of the cross-phenotype genetic associations through in vitro functional analyses and epigenomic profiling experiments in coronary artery smooth muscle cells. RESULTS We prioritized FHL5 as the top candidate causal gene at the UFL1-FHL5 locus through expression quantitative trait locus colocalization methods. FHL5 gene expression was enriched in the smooth muscle cells and pericyte population in human artery tissues with coexpression network analyses supporting a functional role in regulating smooth muscle cell contraction. Unexpectedly, under procalcifying conditions, FHL5 overexpression promoted vascular calcification and dysregulated processes related to extracellular matrix organization and calcium handling. Lastly, by mapping FHL5 binding sites and inferring FHL5 target gene function using artery tissue gene regulatory network analyses, we highlight regulatory interactions between FHL5 and downstream coronary artery disease/myocardial infarction loci, such as FOXL1 and FN1 that have roles in vascular remodeling. CONCLUSIONS Taken together, these studies provide mechanistic insights into the pleiotropic genetic associations of UFL1-FHL5. We show that FHL5 mediates vascular disease risk through transcriptional regulation of downstream vascular remodeling gene programs. These transacting mechanisms may explain a portion of the heritable risk for complex vascular diseases.
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Affiliation(s)
- Doris Wong
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, Virginia, USA
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
- Robert M. Berne Cardiovascular Research Center, University of Virginia, Charlottesville, Virginia, USA
| | - Gaëlle Auguste
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Christian L. Lino Cardenas
- Cardiovascular Research Center, Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Adam W. Turner
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Yixuan Chen
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Yipei Song
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Lijiang Ma
- Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, USA
| | - R. Noah Perry
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
- Robert M. Berne Cardiovascular Research Center, University of Virginia, Charlottesville, Virginia, USA
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
| | - Redouane Aherrahrou
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Maniselvan Kuppusamy
- Robert M. Berne Cardiovascular Research Center, University of Virginia, Charlottesville, Virginia, USA
| | - Chaojie Yang
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, Virginia, USA
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Jose Verdezoto Mosquera
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, Virginia, USA
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Collin J. Dube
- Department of Microbiology, Immunology, and Cancer Biology, University of Virginia, Charlottesville, Virginia, USA
| | - Mohammad Daud Khan
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Meredith Palmore
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Jaspreet K. Kalra
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, Virginia, USA
| | - Maryam Kavousi
- Department of Epidemiology, Erasmus University Medical Center, The Netherlands
| | | | - Ljubica Matic
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Ulf Hedin
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Ani Manichaikul
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, Virginia, USA
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
- Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia, USA
| | - Swapnil K. Sonkusare
- Robert M. Berne Cardiovascular Research Center, University of Virginia, Charlottesville, Virginia, USA
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, Virginia, USA
| | - Mete Civelek
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
- Robert M. Berne Cardiovascular Research Center, University of Virginia, Charlottesville, Virginia, USA
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
| | - Jason C. Kovacic
- Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York, USA
- Victor Chang Cardiac Research Institute, Darlinghurst, New South Wales, Australia
- St. Vincent’s Clinical School, University of New South Wales, Sydney, Australia
| | - Johan L.M. Björkegren
- Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, USA
- Integrated Cardio Metabolic Centre, Department of Medicine, Karolinska Institutet, Huddinge, Sweden
| | - Rajeev Malhotra
- Cardiovascular Research Center, Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Clint L. Miller
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, Virginia, USA
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
- Robert M. Berne Cardiovascular Research Center, University of Virginia, Charlottesville, Virginia, USA
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
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307
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Kaplow IM, Lawler AJ, Schäffer DE, Srinivasan C, Sestili HH, Wirthlin ME, Phan BN, Prasad K, Brown AR, Zhang X, Foley K, Genereux DP, Karlsson EK, Lindblad-Toh K, Meyer WK, Pfenning AR, Andrews G, Armstrong JC, Bianchi M, Birren BW, Bredemeyer KR, Breit AM, Christmas MJ, Clawson H, Damas J, Di Palma F, Diekhans M, Dong MX, Eizirik E, Fan K, Fanter C, Foley NM, Forsberg-Nilsson K, Garcia CJ, Gatesy J, Gazal S, Genereux DP, Goodman L, Grimshaw J, Halsey MK, Harris AJ, Hickey G, Hiller M, Hindle AG, Hubley RM, Hughes GM, Johnson J, Juan D, Kaplow IM, Karlsson EK, Keough KC, Kirilenko B, Koepfli KP, Korstian JM, Kowalczyk A, Kozyrev SV, Lawler AJ, Lawless C, Lehmann T, Levesque DL, Lewin HA, Li X, Lind A, Lindblad-Toh K, Mackay-Smith A, Marinescu VD, Marques-Bonet T, Mason VC, Meadows JRS, Meyer WK, Moore JE, Moreira LR, Moreno-Santillan DD, Morrill KM, Muntané G, Murphy WJ, Navarro A, Nweeia M, Ortmann S, Osmanski A, Paten B, Paulat NS, Pfenning AR, Phan BN, Pollard KS, Pratt HE, Ray DA, Reilly SK, Rosen JR, Ruf I, Ryan L, Ryder OA, Sabeti PC, Schäffer DE, Serres A, Shapiro B, Smit AFA, Springer M, Srinivasan C, Steiner C, Storer JM, Sullivan KAM, Sullivan PF, Sundström E, Supple MA, Swofford R, Talbot JE, Teeling E, Turner-Maier J, Valenzuela A, Wagner F, Wallerman O, Wang C, Wang J, Weng Z, Wilder AP, Wirthlin ME, Xue JR, Zhang X. Relating enhancer genetic variation across mammals to complex phenotypes using machine learning. Science 2023; 380:eabm7993. [PMID: 37104615 DOI: 10.1126/science.abm7993] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/29/2023]
Abstract
Protein-coding differences between species often fail to explain phenotypic diversity, suggesting the involvement of genomic elements that regulate gene expression such as enhancers. Identifying associations between enhancers and phenotypes is challenging because enhancer activity can be tissue-dependent and functionally conserved despite low sequence conservation. We developed the Tissue-Aware Conservation Inference Toolkit (TACIT) to associate candidate enhancers with species' phenotypes using predictions from machine learning models trained on specific tissues. Applying TACIT to associate motor cortex and parvalbumin-positive interneuron enhancers with neurological phenotypes revealed dozens of enhancer-phenotype associations, including brain size-associated enhancers that interact with genes implicated in microcephaly or macrocephaly. TACIT provides a foundation for identifying enhancers associated with the evolution of any convergently evolved phenotype in any large group of species with aligned genomes.
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Affiliation(s)
- Irene M Kaplow
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Alyssa J Lawler
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
- Department of Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Daniel E Schäffer
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Chaitanya Srinivasan
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Heather H Sestili
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Morgan E Wirthlin
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
| | - BaDoi N Phan
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
- Medical Scientist Training Program, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Kavya Prasad
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Ashley R Brown
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Xiaomeng Zhang
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Kathleen Foley
- Department of Biological Sciences, Lehigh University, Bethlehem, PA, USA
| | - Diane P Genereux
- Broad Institute, Cambridge, MA, USA
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Elinor K Karlsson
- Broad Institute, Cambridge, MA, USA
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Kerstin Lindblad-Toh
- Broad Institute, Cambridge, MA, USA
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Wynn K Meyer
- Department of Biological Sciences, Lehigh University, Bethlehem, PA, USA
| | - Andreas R Pfenning
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
- Department of Biology, Carnegie Mellon University, Pittsburgh, PA, USA
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Christmas MJ, Kaplow IM, Genereux DP, Dong MX, Hughes GM, Li X, Sullivan PF, Hindle AG, Andrews G, Armstrong JC, Bianchi M, Breit AM, Diekhans M, Fanter C, Foley NM, Goodman DB, Goodman L, Keough KC, Kirilenko B, Kowalczyk A, Lawless C, Lind AL, Meadows JRS, Moreira LR, Redlich RW, Ryan L, Swofford R, Valenzuela A, Wagner F, Wallerman O, Brown AR, Damas J, Fan K, Gatesy J, Grimshaw J, Johnson J, Kozyrev SV, Lawler AJ, Marinescu VD, Morrill KM, Osmanski A, Paulat NS, Phan BN, Reilly SK, Schäffer DE, Steiner C, Supple MA, Wilder AP, Wirthlin ME, Xue JR, Birren BW, Gazal S, Hubley RM, Koepfli KP, Marques-Bonet T, Meyer WK, Nweeia M, Sabeti PC, Shapiro B, Smit AFA, Springer MS, Teeling EC, Weng Z, Hiller M, Levesque DL, Lewin HA, Murphy WJ, Navarro A, Paten B, Pollard KS, Ray DA, Ruf I, Ryder OA, Pfenning AR, Lindblad-Toh K, Karlsson EK. Evolutionary constraint and innovation across hundreds of placental mammals. Science 2023; 380:eabn3943. [PMID: 37104599 PMCID: PMC10250106 DOI: 10.1126/science.abn3943] [Citation(s) in RCA: 60] [Impact Index Per Article: 60.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Accepted: 12/16/2022] [Indexed: 04/29/2023]
Abstract
Zoonomia is the largest comparative genomics resource for mammals produced to date. By aligning genomes for 240 species, we identify bases that, when mutated, are likely to affect fitness and alter disease risk. At least 332 million bases (~10.7%) in the human genome are unusually conserved across species (evolutionarily constrained) relative to neutrally evolving repeats, and 4552 ultraconserved elements are nearly perfectly conserved. Of 101 million significantly constrained single bases, 80% are outside protein-coding exons and half have no functional annotations in the Encyclopedia of DNA Elements (ENCODE) resource. Changes in genes and regulatory elements are associated with exceptional mammalian traits, such as hibernation, that could inform therapeutic development. Earth's vast and imperiled biodiversity offers distinctive power for identifying genetic variants that affect genome function and organismal phenotypes.
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Affiliation(s)
- Matthew J. Christmas
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 751 32 Uppsala, Sweden
| | - Irene M. Kaplow
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | | | - Michael X. Dong
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 751 32 Uppsala, Sweden
| | - Graham M. Hughes
- School of Biology and Environmental Science, University College Dublin, Belfield, Dublin 4, Ireland
| | - Xue Li
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Morningside Graduate School of Biomedical Sciences, UMass Chan Medical School, Worcester, MA 01605, USA
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Patrick F. Sullivan
- Department of Genetics, University of North Carolina Medical School, Chapel Hill, NC 27599, USA
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Allyson G. Hindle
- School of Life Sciences, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Gregory Andrews
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Joel C. Armstrong
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Matteo Bianchi
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 751 32 Uppsala, Sweden
| | - Ana M. Breit
- School of Biology and Ecology, University of Maine, Orono, ME 04469, USA
| | - Mark Diekhans
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Cornelia Fanter
- School of Life Sciences, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Nicole M. Foley
- Veterinary Integrative Biosciences, Texas A&M University, College Station, TX 77843, USA
| | - Daniel B. Goodman
- Department of Microbiology and Immunology, University of California San Francisco, San Francisco, CA 94143, USA
| | | | - Kathleen C. Keough
- Fauna Bio, Inc., Emeryville, CA 94608, USA
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA 94158, USA
- Gladstone Institutes, San Francisco, CA 94158, USA
| | - Bogdan Kirilenko
- Faculty of Biosciences, Goethe-University, 60438 Frankfurt, Germany
- LOEWE Centre for Translational Biodiversity Genomics, 60325 Frankfurt, Germany
- Senckenberg Research Institute, 60325 Frankfurt, Germany
| | - Amanda Kowalczyk
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Colleen Lawless
- School of Biology and Environmental Science, University College Dublin, Belfield, Dublin 4, Ireland
| | - Abigail L. Lind
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA 94158, USA
- Gladstone Institutes, San Francisco, CA 94158, USA
| | - Jennifer R. S. Meadows
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 751 32 Uppsala, Sweden
| | - Lucas R. Moreira
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Ruby W. Redlich
- Department of Biological Sciences, Mellon College of Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Louise Ryan
- School of Biology and Environmental Science, University College Dublin, Belfield, Dublin 4, Ireland
| | - Ross Swofford
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
| | - Alejandro Valenzuela
- Department of Experimental and Health Sciences, Institute of Evolutionary Biology (UPF-CSIC), Universitat Pompeu Fabra, 08003 Barcelona, Spain
| | - Franziska Wagner
- Museum of Zoology, Senckenberg Natural History Collections Dresden, 01109 Dresden, Germany
| | - Ola Wallerman
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 751 32 Uppsala, Sweden
| | - Ashley R. Brown
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Joana Damas
- The Genome Center, University of California Davis, Davis, CA 95616, USA
| | - Kaili Fan
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - John Gatesy
- Division of Vertebrate Zoology, American Museum of Natural History, New York, NY 10024, USA
| | - Jenna Grimshaw
- Department of Biological Sciences, Texas Tech University, Lubbock, TX 79409, USA
| | - Jeremy Johnson
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
| | - Sergey V. Kozyrev
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 751 32 Uppsala, Sweden
| | - Alyssa J. Lawler
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Department of Biological Sciences, Mellon College of Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Voichita D. Marinescu
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 751 32 Uppsala, Sweden
| | - Kathleen M. Morrill
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Morningside Graduate School of Biomedical Sciences, UMass Chan Medical School, Worcester, MA 01605, USA
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Austin Osmanski
- Medical Scientist Training Program, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Nicole S. Paulat
- Department of Biological Sciences, Texas Tech University, Lubbock, TX 79409, USA
| | - BaDoi N. Phan
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Medical Scientist Training Program, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Steven K. Reilly
- Department of Genetics, Yale School of Medicine, New Haven, CT 06510, USA
| | - Daniel E. Schäffer
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Cynthia Steiner
- Conservation Genetics, San Diego Zoo Wildlife Alliance, Escondido, CA 92027, USA
| | - Megan A. Supple
- Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Aryn P. Wilder
- Conservation Genetics, San Diego Zoo Wildlife Alliance, Escondido, CA 92027, USA
| | - Morgan E. Wirthlin
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - James R. Xue
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
| | | | - Bruce W. Birren
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
| | - Steven Gazal
- Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | | | - Klaus-Peter Koepfli
- Center for Species Survival, Smithsonian’s National Zoo and Conservation Biology Institute, Washington, DC 20008, USA
- Computer Technologies Laboratory, ITMO University, St. Petersburg 197101, Russia
- Smithsonian-Mason School of Conservation, George Mason University, Front Royal, VA 22630, USA
| | - Tomas Marques-Bonet
- Catalan Institution of Research and Advanced Studies (ICREA), 08010 Barcelona, Spain
- CNAG-CRG, Centre for Genomic Regulation, Barcelona Institute of Science and Technology (BIST), 08036 Barcelona, Spain
- Department of Medicine and Life Sciences, Institute of Evolutionary Biology (UPF-CSIC), Universitat Pompeu Fabra, 08003 Barcelona, Spain
- Institut Català de Paleontologia Miquel Crusafont, Universitat Autònoma de Barcelona, 08193 Cerdanyola del Vallès, Barcelona, Spain
| | - Wynn K. Meyer
- Department of Biological Sciences, Lehigh University, Bethlehem, PA 18015, USA
| | - Martin Nweeia
- Department of Comprehensive Care, School of Dental Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
- Department of Vertebrate Zoology, Canadian Museum of Nature, Ottawa, Ontario K2P 2R1, Canada
- Department of Vertebrate Zoology, Smithsonian Institution, Washington, DC 20002, USA
- Narwhal Genome Initiative, Department of Restorative Dentistry and Biomaterials Sciences, Harvard School of Dental Medicine, Boston, MA 02115, USA
| | - Pardis C. Sabeti
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
- Howard Hughes Medical Institute, Harvard University, Cambridge, MA 02138, USA
| | - Beth Shapiro
- Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, CA 95064, USA
- Howard Hughes Medical Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | | | - Mark S. Springer
- Department of Evolution, Ecology and Organismal Biology, University of California Riverside, Riverside, CA 92521, USA
| | - Emma C. Teeling
- School of Biology and Environmental Science, University College Dublin, Belfield, Dublin 4, Ireland
| | - Zhiping Weng
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Michael Hiller
- Faculty of Biosciences, Goethe-University, 60438 Frankfurt, Germany
- LOEWE Centre for Translational Biodiversity Genomics, 60325 Frankfurt, Germany
- Senckenberg Research Institute, 60325 Frankfurt, Germany
| | | | - Harris A. Lewin
- The Genome Center, University of California Davis, Davis, CA 95616, USA
- Department of Evolution and Ecology, University of California Davis, Davis, CA 95616, USA
- John Muir Institute for the Environment, University of California Davis, Davis, CA 95616, USA
| | - William J. Murphy
- Veterinary Integrative Biosciences, Texas A&M University, College Station, TX 77843, USA
| | - Arcadi Navarro
- Catalan Institution of Research and Advanced Studies (ICREA), 08010 Barcelona, Spain
- Department of Medicine and Life Sciences, Institute of Evolutionary Biology (UPF-CSIC), Universitat Pompeu Fabra, 08003 Barcelona, Spain
- BarcelonaBeta Brain Research Center, Pasqual Maragall Foundation, 08005 Barcelona, Spain
- CRG, Centre for Genomic Regulation, Barcelona Institute of Science and Technology (BIST), 08003 Barcelona, Spain
| | - Benedict Paten
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Katherine S. Pollard
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA 94158, USA
- Gladstone Institutes, San Francisco, CA 94158, USA
- Chan Zuckerberg Biohub, San Francisco, CA 94158, USA
| | - David A. Ray
- Department of Biological Sciences, Texas Tech University, Lubbock, TX 79409, USA
| | - Irina Ruf
- Division of Messel Research and Mammalogy, Senckenberg Research Institute and Natural History Museum Frankfurt, 60325 Frankfurt am Main, Germany
| | - Oliver A. Ryder
- Conservation Genetics, San Diego Zoo Wildlife Alliance, Escondido, CA 92027, USA
- Department of Evolution, Behavior and Ecology, School of Biological Sciences, University of California San Diego, La Jolla, CA 92039, USA
| | - Andreas R. Pfenning
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Kerstin Lindblad-Toh
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 751 32 Uppsala, Sweden
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
| | - Elinor K. Karlsson
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA 01605, USA
- Program in Molecular Medicine, UMass Chan Medical School, Worcester, MA 01605, USA
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309
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Bera BS, Thompson TV, Sosa E, Nomaru H, Reynolds D, Dubin RA, Maqbool SB, Zheng D, Morrow BE, Greally JM, Suzuki M. An optimized approach for multiplexing single-nuclear ATAC-seq using oligonucleotide-conjugated antibodies. Epigenetics Chromatin 2023; 16:14. [PMID: 37118773 PMCID: PMC10142415 DOI: 10.1186/s13072-023-00486-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 04/13/2023] [Indexed: 04/30/2023] Open
Abstract
BACKGROUND Single-cell technologies to analyze transcription and chromatin structure have been widely used in many research areas to reveal the functions and molecular properties of cells at single-cell resolution. Sample multiplexing techniques are valuable when performing single-cell analysis, reducing technical variation and permitting cost efficiencies. Several commercially available methods have been used in many scRNA-seq studies. On the other hand, while several methods have been published, multiplexing techniques for single nuclear assay for transposase-accessible chromatin (snATAC)-seq assays remain under development. We developed a simple nucleus hashing method using oligonucleotide-conjugated antibodies recognizing nuclear pore complex proteins, NuHash, to perform snATAC-seq library preparations by multiplexing. RESULTS We performed multiplexing snATAC-seq analyses on a mixture of human and mouse cell samples (two samples, 2-plex, and four samples, 4-plex) using NuHash. The analyses on nuclei with at least 10,000 read counts showed that the demultiplexing accuracy of NuHash was high, and only ten out of 9144 nuclei (2-plex) and 150 of 12,208 nuclei (4-plex) had discordant classifications between NuHash demultiplexing and discrimination using reference genome alignments. The differential open chromatin region (OCR) analysis between female and male samples revealed that male-specific OCRs were enriched in chromosome Y (four out of nine). We also found that five female-specific OCRs (20 OCRs) were on chromosome X. A comparative analysis between snATAC-seq and deeply sequenced bulk ATAC-seq on the same samples revealed that the bulk ATAC-seq signal intensity was positively correlated with the number of cell clusters detected in snATAC-seq. Moreover, when we categorized snATAC-seq peaks based on the number of cell clusters in which the peak was present, we observed different distributions over different genomic features between the groups. This result suggests that the peak intensities of bulk ATAC-seq can be used to identify different types of functional loci. CONCLUSIONS Our multiplexing method using oligo-conjugated anti-nuclear pore complex proteins, NuHash, permits high-accuracy demultiplexing of samples. The NuHash protocol is straightforward, works on frozen samples, and requires no modifications for snATAC-seq library preparation.
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Affiliation(s)
- Betelehem Solomon Bera
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, USA
- Center for Genetic Medicine, Children's National Medical Center, Washington, DC, USA
| | - Taylor V Thompson
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Eric Sosa
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Hiroko Nomaru
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, USA
- Thinkcyte Inc., Tokyo, Japan
| | - David Reynolds
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Robert A Dubin
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Shahina B Maqbool
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Deyou Zheng
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, USA
- Departments of Neurology and Neuroscience, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Bernice E Morrow
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, USA
| | - John M Greally
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Masako Suzuki
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, USA.
- Department of Nutrition, Texas A&M University, College Station, TX, USA.
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310
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Cimpean M, Keppel MP, Gainullina A, Fan C, Schedler NC, Swain A, Kolicheski A, Shapiro H, Young HA, Wang T, Artyomov MN, Cooper MA. IL-15 priming alters IFN-γ regulation in murine NK cells. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.23.537947. [PMID: 37163083 PMCID: PMC10168240 DOI: 10.1101/2023.04.23.537947] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
Natural killer (NK) effector functions can be triggered by inflammatory cytokines and engagement of activating receptors. NK cell production of IFN-γ, an important immunoregulatory cytokine, exhibits activation-specific IFN-γ regulation. Resting murine NK cells exhibit activation-specific metabolic requirements for IFN-γ production, which are reversed for activating receptor-mediated stimulation following IL-15 priming. While both cytokine and activating receptor stimulation leads to similar IFN-γ protein production, only cytokine stimulation upregulates Ifng transcript, suggesting that protein production is translationally regulated after receptor stimulation. Based on these differences in IFN-γ regulation, we hypothesized that ex vivo IL-15 priming of murine NK cells allows a switch to IFN-γ transcription upon activating receptor engagement. Transcriptional analysis of primed NK cells compared to naïve cells or cells cultured with low-dose IL-15 demonstrated that primed cells strongly upregulated Ifng transcript following activating receptor stimulation. This was not due to chromatin accessibility changes in the Ifng locus or changes in ITAM signaling, but was associated with a distinct transcriptional signature induced by ITAM stimulation of primed compared to naïve NK cells. Transcriptional analyses identified a common signature of c-Myc (Myc) targets associated with Ifng transcription. While Myc marked NK cells capable of Ifng transcription, Myc itself was not required for Ifng transcription using a genetic model of Myc deletion. This work highlights altered regulatory networks in IL-15 primed cells, resulting in distinct gene expression patterns and IFN-γ regulation in response to activating receptor stimulation.
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311
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Kwok AJ, Allcock A, Ferreira RC, Cano-Gamez E, Smee M, Burnham KL, Zurke YX, McKechnie S, Mentzer AJ, Monaco C, Udalova IA, Hinds CJ, Todd JA, Davenport EE, Knight JC. Neutrophils and emergency granulopoiesis drive immune suppression and an extreme response endotype during sepsis. Nat Immunol 2023; 24:767-779. [PMID: 37095375 DOI: 10.1038/s41590-023-01490-5] [Citation(s) in RCA: 54] [Impact Index Per Article: 54.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2022] [Accepted: 03/13/2023] [Indexed: 04/26/2023]
Abstract
Sepsis arises from diverse and incompletely understood dysregulated host response processes following infection that leads to life-threatening organ dysfunction. Here we showed that neutrophils and emergency granulopoiesis drove a maladaptive response during sepsis. We generated a whole-blood single-cell multiomic atlas (272,993 cells, n = 39 individuals) of the sepsis immune response that identified populations of immunosuppressive mature and immature neutrophils. In co-culture, CD66b+ sepsis neutrophils inhibited proliferation and activation of CD4+ T cells. Single-cell multiomic mapping of circulating hematopoietic stem and progenitor cells (HSPCs) (29,366 cells, n = 27) indicated altered granulopoiesis in patients with sepsis. These features were enriched in a patient subset with poor outcome and a specific sepsis response signature that displayed higher frequencies of IL1R2+ immature neutrophils, epigenetic and transcriptomic signatures of emergency granulopoiesis in HSPCs and STAT3-mediated gene regulation across different infectious etiologies and syndromes. Our findings offer potential therapeutic targets and opportunities for stratified medicine in severe infection.
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Affiliation(s)
- Andrew J Kwok
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Alice Allcock
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Ricardo C Ferreira
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Eddie Cano-Gamez
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK
| | - Madeleine Smee
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Katie L Burnham
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK
| | | | - Stuart McKechnie
- John Radcliffe Hospital, Oxford Universities Hospitals NHS Foundation Trust, Oxford, UK
| | - Alexander J Mentzer
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- John Radcliffe Hospital, Oxford Universities Hospitals NHS Foundation Trust, Oxford, UK
- NIHR Oxford Biomedical Research Centre, Oxford, UK
| | - Claudia Monaco
- Kennedy Institute of Rheumatology, University of Oxford, Oxford, UK
| | - Irina A Udalova
- Kennedy Institute of Rheumatology, University of Oxford, Oxford, UK
| | - Charles J Hinds
- William Harvey Research Institute, Faculty of Medicine and Dentistry, Queen Mary University, London, UK
| | - John A Todd
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- NIHR Oxford Biomedical Research Centre, Oxford, UK
| | - Emma E Davenport
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK
| | - Julian C Knight
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
- John Radcliffe Hospital, Oxford Universities Hospitals NHS Foundation Trust, Oxford, UK.
- NIHR Oxford Biomedical Research Centre, Oxford, UK.
- Chinese Academy of Medical Science Oxford Institute, University of Oxford, Oxford, UK.
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312
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Rommelfanger MK, Behrends M, Chen Y, Martinez J, Bens M, Xiong L, Rudolph KL, MacLean AL. Gene regulatory network inference with popInfer reveals dynamic regulation of hematopoietic stem cell quiescence upon diet restriction and aging. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.18.537360. [PMID: 37131596 PMCID: PMC10153203 DOI: 10.1101/2023.04.18.537360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Inference of gene regulatory networks (GRNs) can reveal cell state transitions from single-cell genomics data. However, obstacles to temporal inference from snapshot data are difficult to overcome. Single-nuclei multiomics data offer means to bridge this gap and derive temporal information from snapshot data using joint measurements of gene expression and chromatin accessibility in the same single cells. We developed popInfer to infer networks that characterize lineage-specific dynamic cell state transitions from joint gene expression and chromatin accessibility data. Benchmarking against alternative methods for GRN inference, we showed that popInfer achieves higher accuracy in the GRNs inferred. popInfer was applied to study single-cell multiomics data characterizing hematopoietic stem cells (HSCs) and the transition from HSC to a multipotent progenitor cell state during murine hematopoiesis across age and dietary conditions. From networks predicted by popInfer, we discovered gene interactions controlling entry to/exit from HSC quiescence that are perturbed in response to diet or aging.
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Affiliation(s)
- Megan K. Rommelfanger
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA
| | - Marthe Behrends
- Research Group on Stem Cell and Metabolism Aging, Leibniz Institute on Aging, Fritz Lipmann Institute (FLI), Jena, Germany
| | - Yulin Chen
- Research Group on Stem Cell and Metabolism Aging, Leibniz Institute on Aging, Fritz Lipmann Institute (FLI), Jena, Germany
| | - Jonathan Martinez
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA
| | - Martin Bens
- Core Facility Next Generation Sequencing, Leibniz Institute on Aging, Fritz Lipmann Institute (FLI), Jena, Germany
| | - Lingyun Xiong
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA
- Department of Stem Cell Biology and Regenerative Medicine, Broad-CIRM Center, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA
| | - K. Lenhard Rudolph
- Research Group on Stem Cell and Metabolism Aging, Leibniz Institute on Aging, Fritz Lipmann Institute (FLI), Jena, Germany
- Medical Faculty, Jena University Hospital, Friedrich Schiller University, Jena, Germany
| | - Adam L. MacLean
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA
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313
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Wei Y, Li G, Feng J, Wu F, Zhao Z, Bao Z, Zhang W, Su X, Li J, Qi X, Duan Z, Zhang Y, Vega SF, Jakola AS, Sun Y, Carén H, Jiang T, Fan X. Stalled oligodendrocyte differentiation in IDH-mutant gliomas. Genome Med 2023; 15:24. [PMID: 37055795 PMCID: PMC10103394 DOI: 10.1186/s13073-023-01175-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2022] [Accepted: 03/28/2023] [Indexed: 04/15/2023] Open
Abstract
BACKGROUND Roughly 50% of adult gliomas harbor isocitrate dehydrogenase (IDH) mutations. According to the 2021 WHO classification guideline, these gliomas are diagnosed as astrocytomas, harboring no 1p19q co-deletion, or oligodendrogliomas, harboring 1p19q co-deletion. Recent studies report that IDH-mutant gliomas share a common developmental hierarchy. However, the neural lineages and differentiation stages in IDH-mutant gliomas remain inadequately characterized. METHODS Using bulk transcriptomes and single-cell transcriptomes, we identified genes enriched in IDH-mutant gliomas with or without 1p19q co-deletion, we also assessed the expression pattern of stage-specific signatures and key regulators of oligodendrocyte lineage differentiation. We compared the expression of oligodendrocyte lineage stage-specific markers between quiescent and proliferating malignant single cells. The gene expression profiles were validated using RNAscope analysis and myelin staining and were further substantiated using data of DNA methylation and single-cell ATAC-seq. As a control, we assessed the expression pattern of astrocyte lineage markers. RESULTS Genes concordantly enriched in both subtypes of IDH-mutant gliomas are upregulated in oligodendrocyte progenitor cells (OPC). Signatures of early stages of oligodendrocyte lineage and key regulators of OPC specification and maintenance are enriched in all IDH-mutant gliomas. In contrast, signature of myelin-forming oligodendrocytes, myelination regulators, and myelin components are significantly down-regulated or absent in IDH-mutant gliomas. Further, single-cell transcriptomes of IDH-mutant gliomas are similar to OPC and differentiation-committed oligodendrocyte progenitors, but not to myelinating oligodendrocyte. Most IDH-mutant glioma cells are quiescent; quiescent cells and proliferating cells resemble the same differentiation stage of oligodendrocyte lineage. Mirroring the gene expression profiles along the oligodendrocyte lineage, analyses of DNA methylation and single-cell ATAC-seq data demonstrate that genes of myelination regulators and myelin components are hypermethylated and show inaccessible chromatin status, whereas regulators of OPC specification and maintenance are hypomethylated and show open chromatin status. Markers of astrocyte precursors are not enriched in IDH-mutant gliomas. CONCLUSIONS Our studies show that despite differences in clinical manifestation and genomic alterations, all IDH-mutant gliomas resemble early stages of oligodendrocyte lineage and are stalled in oligodendrocyte differentiation due to blocked myelination program. These findings provide a framework to accommodate biological features and therapy development for IDH-mutant gliomas.
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Affiliation(s)
- Yanfei Wei
- Department of Biology, Beijing Key Laboratory of Gene Resource and Molecular Development, School of Life Sciences, and Key Laboratory of Cell Proliferation and Regulation Biology, Ministry of Education, School of Life Sciences, Beijing Normal University, Beijing, China
| | - Guanzhang Li
- Beijing Neurosurgical Institute, Beijing, 100070, China
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China
| | - Jing Feng
- Department of Biology, Beijing Key Laboratory of Gene Resource and Molecular Development, School of Life Sciences, and Key Laboratory of Cell Proliferation and Regulation Biology, Ministry of Education, School of Life Sciences, Beijing Normal University, Beijing, China
| | - Fan Wu
- Beijing Neurosurgical Institute, Beijing, 100070, China
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China
| | - Zheng Zhao
- Beijing Neurosurgical Institute, Beijing, 100070, China
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China
| | - Zhaoshi Bao
- Beijing Neurosurgical Institute, Beijing, 100070, China
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China
| | - Wei Zhang
- Beijing Neurosurgical Institute, Beijing, 100070, China
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China
| | - Xiaodong Su
- Biodynamic Optical Imaging Center (BIOPIC), School of Life Sciences, Peking University, Beijing, 100871, China
| | - Jiuyi Li
- College of Life Sciences, Sichuan Normal University, Chengdu, 610101, China
| | - Xueling Qi
- Department of Pathology, San Bo Brain Hospital, Capital Medical University, Beijing, 100093, China
| | - Zejun Duan
- Department of Pathology, San Bo Brain Hospital, Capital Medical University, Beijing, 100093, China
| | - Yunqiu Zhang
- Center of Growth Metabolism & Aging, Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610065, China
| | - Sandra Ferreyra Vega
- Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, 41390, Sweden
- Sahlgrenska Center for Cancer Research, Department of Laboratory Medicine, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, 41390, Gothenburg, Sweden
| | - Asgeir Store Jakola
- Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, 41390, Sweden
- Department of Neurosurgery, Sahlgrenska University Hospital, Gothenburg, 41390, Sweden
| | - Yingyu Sun
- Department of Biology, Beijing Key Laboratory of Gene Resource and Molecular Development, School of Life Sciences, and Key Laboratory of Cell Proliferation and Regulation Biology, Ministry of Education, School of Life Sciences, Beijing Normal University, Beijing, China
| | - Helena Carén
- Sahlgrenska Center for Cancer Research, Department of Laboratory Medicine, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, 41390, Gothenburg, Sweden.
| | - Tao Jiang
- Beijing Neurosurgical Institute, Beijing, 100070, China.
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China.
- Chinese Glioma Genome Atlas Network (CGGA), Beijing, 100070, China.
| | - Xiaolong Fan
- Department of Biology, Beijing Key Laboratory of Gene Resource and Molecular Development, School of Life Sciences, and Key Laboratory of Cell Proliferation and Regulation Biology, Ministry of Education, School of Life Sciences, Beijing Normal University, Beijing, China.
- Chinese Glioma Genome Atlas Network (CGGA), Beijing, 100070, China.
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314
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Weinand K, Sakaue S, Nathan A, Jonsson AH, Zhang F, Watts GFM, Zhu Z, Rao DA, Anolik JH, Brenner MB, Donlin LT, Wei K, Raychaudhuri S. The Chromatin Landscape of Pathogenic Transcriptional Cell States in Rheumatoid Arthritis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.07.536026. [PMID: 37066336 PMCID: PMC10104143 DOI: 10.1101/2023.04.07.536026] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/18/2023]
Abstract
Synovial tissue inflammation is the hallmark of rheumatoid arthritis (RA). Recent work has identified prominent pathogenic cell states in inflamed RA synovial tissue, such as T peripheral helper cells; however, the epigenetic regulation of these states has yet to be defined. We measured genome-wide open chromatin at single cell resolution from 30 synovial tissue samples, including 12 samples with transcriptional data in multimodal experiments. We identified 24 chromatin classes and predicted their associated transcription factors, including a CD8+ GZMK+ class associated with EOMES and a lining fibroblast class associated with AP-1. By integrating an RA tissue transcriptional atlas, we found that the chromatin classes represented 'superstates' corresponding to multiple transcriptional cell states. Finally, we demonstrated the utility of this RA tissue chromatin atlas through the associations between disease phenotypes and chromatin class abundance as well as the nomination of classes mediating the effects of putatively causal RA genetic variants.
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Affiliation(s)
- Kathryn Weinand
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Saori Sakaue
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Aparna Nathan
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Anna Helena Jonsson
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Fan Zhang
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Rheumatology and the Center for Health Artificial Intelligence, University of Colorado School of Medicine, Aurora, CO, USA
| | - Gerald F. M. Watts
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Zhu Zhu
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | | | - Deepak A. Rao
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Jennifer H. Anolik
- Division of Allergy, Immunology and Rheumatology; Department of Medicine, University of Rochester Medical Center, Rochester, NY, USA
| | - Michael B. Brenner
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Laura T. Donlin
- Hospital for Special Surgery, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Kevin Wei
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Soumya Raychaudhuri
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Versus Arthritis Centre for Genetics and Genomics, Centre for Musculoskeletal Research, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK
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315
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Russell AJC, Weir JA, Nadaf NM, Shabet M, Kumar V, Kambhampati S, Raichur R, Marrero GJ, Liu S, Balderrama KS, Vanderburg CR, Shanmugam V, Tian L, Wu CJ, Yoon CH, Macosko EZ, Chen F. Slide-tags: scalable, single-nucleus barcoding for multi-modal spatial genomics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.01.535228. [PMID: 37066158 PMCID: PMC10103946 DOI: 10.1101/2023.04.01.535228] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Recent technological innovations have enabled the high-throughput quantification of gene expression and epigenetic regulation within individual cells, transforming our understanding of how complex tissues are constructed. Missing from these measurements, however, is the ability to routinely and easily spatially localise these profiled cells. We developed a strategy, Slide-tags, in which single nuclei within an intact tissue section are 'tagged' with spatial barcode oligonucleotides derived from DNA-barcoded beads with known positions. These tagged nuclei can then be used as input into a wide variety of single-nucleus profiling assays. Application of Slide-tags to the mouse hippocampus positioned nuclei at less than 10 micron spatial resolution, and delivered whole-transcriptome data that was indistinguishable in quality from ordinary snRNA-seq. To demonstrate that Slide-tags can be applied to a wide variety of human tissues, we performed the assay on brain, tonsil, and melanoma. We revealed cell-type-specific spatially varying gene expression across cortical layers and spatially contextualised receptor-ligand interactions driving B-cell maturation in lymphoid tissue. A major benefit of Slide-tags is that it is easily adaptable to virtually any single-cell measurement technology. As proof of principle, we performed multiomic measurements of open chromatin, RNA, and T-cell receptor sequences in the same cells from metastatic melanoma. We identified spatially distinct tumour subpopulations to be differentially infiltrated by an expanded T-cell clone and undergoing cell state transition driven by spatially clustered accessible transcription factor motifs. Slide-tags offers a universal platform for importing the compendium of established single-cell measurements into the spatial genomics repertoire.
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316
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Ma W, Lu J, Wu H. Cellcano: supervised cell type identification for single cell ATAC-seq data. Nat Commun 2023; 14:1864. [PMID: 37012226 PMCID: PMC10070275 DOI: 10.1038/s41467-023-37439-3] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Accepted: 03/15/2023] [Indexed: 04/05/2023] Open
Abstract
Computational cell type identification is a fundamental step in single-cell omics data analysis. Supervised celltyping methods have gained increasing popularity in single-cell RNA-seq data because of the superior performance and the availability of high-quality reference datasets. Recent technological advances in profiling chromatin accessibility at single-cell resolution (scATAC-seq) have brought new insights to the understanding of epigenetic heterogeneity. With continuous accumulation of scATAC-seq datasets, supervised celltyping method specifically designed for scATAC-seq is in urgent need. Here we develop Cellcano, a computational method based on a two-round supervised learning algorithm to identify cell types from scATAC-seq data. The method alleviates the distributional shift between reference and target data and improves the prediction performance. After systematically benchmarking Cellcano on 50 well-designed celltyping tasks from various datasets, we show that Cellcano is accurate, robust, and computationally efficient. Cellcano is well-documented and freely available at https://marvinquiet.github.io/Cellcano/ .
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Affiliation(s)
- Wenjing Ma
- Department of Computer Science, Emory University, 400 Dowman Drive, Atlanta, GA, 30322, USA
| | - Jiaying Lu
- Department of Computer Science, Emory University, 400 Dowman Drive, Atlanta, GA, 30322, USA
| | - Hao Wu
- Faculty of Computer Science and Control Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, 1068 Xueyuan Avenue, Shenzhen University Town, Shenzhen, 518055, P. R. China.
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, 1518 Clifton Road NE, Atlanta, GA, 30322, USA.
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317
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Muckenhuber M, Seufert I, Müller-Ott K, Mallm JP, Klett LC, Knotz C, Hechler J, Kepper N, Erdel F, Rippe K. Epigenetic signals that direct cell type-specific interferon beta response in mouse cells. Life Sci Alliance 2023; 6:e202201823. [PMID: 36732019 PMCID: PMC9900254 DOI: 10.26508/lsa.202201823] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Revised: 01/14/2023] [Accepted: 01/16/2023] [Indexed: 02/04/2023] Open
Abstract
The antiviral response induced by type I interferon (IFN) via the JAK-STAT signaling cascade activates hundreds of IFN-stimulated genes (ISGs) across human and mouse tissues but varies between cell types. However, the links between the underlying epigenetic features and the ISG profile are not well understood. We mapped ISGs, binding sites of the STAT1 and STAT2 transcription factors, chromatin accessibility, and histone H3 lysine modification by acetylation (ac) and mono-/tri-methylation (me1, me3) in mouse embryonic stem cells and fibroblasts before and after IFNβ treatment. A large fraction of ISGs and STAT-binding sites was cell type specific with promoter binding of a STAT1/2 complex being a key driver of ISGs. Furthermore, STAT1/2 binding to putative enhancers induced ISGs as inferred from a chromatin co-accessibility analysis. STAT1/2 binding was dependent on the chromatin context and positively correlated with preexisting H3K4me1 and H3K27ac marks in an open chromatin state, whereas the presence of H3K27me3 had an inhibitory effect. Thus, chromatin features present before stimulation represent an additional regulatory layer for the cell type-specific antiviral response.
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Affiliation(s)
- Markus Muckenhuber
- Division of Chromatin Networks, German Cancer Research Center (DKFZ) and Bioquant, Heidelberg, Germany
- Faculty of Biosciences, Heidelberg University, Heidelberg, Germany
| | - Isabelle Seufert
- Division of Chromatin Networks, German Cancer Research Center (DKFZ) and Bioquant, Heidelberg, Germany
- Faculty of Biosciences, Heidelberg University, Heidelberg, Germany
| | - Katharina Müller-Ott
- Division of Chromatin Networks, German Cancer Research Center (DKFZ) and Bioquant, Heidelberg, Germany
| | - Jan-Philipp Mallm
- Division of Chromatin Networks, German Cancer Research Center (DKFZ) and Bioquant, Heidelberg, Germany
- Single Cell Open Lab, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Lara C Klett
- Division of Chromatin Networks, German Cancer Research Center (DKFZ) and Bioquant, Heidelberg, Germany
- Faculty of Biosciences, Heidelberg University, Heidelberg, Germany
| | - Caroline Knotz
- Division of Chromatin Networks, German Cancer Research Center (DKFZ) and Bioquant, Heidelberg, Germany
| | - Jana Hechler
- Division of Chromatin Networks, German Cancer Research Center (DKFZ) and Bioquant, Heidelberg, Germany
| | - Nick Kepper
- Division of Chromatin Networks, German Cancer Research Center (DKFZ) and Bioquant, Heidelberg, Germany
| | - Fabian Erdel
- Division of Chromatin Networks, German Cancer Research Center (DKFZ) and Bioquant, Heidelberg, Germany
| | - Karsten Rippe
- Division of Chromatin Networks, German Cancer Research Center (DKFZ) and Bioquant, Heidelberg, Germany
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318
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Zhang D, Deng Y, Kukanja P, Agirre E, Bartosovic M, Dong M, Ma C, Ma S, Su G, Bao S, Liu Y, Xiao Y, Rosoklija GB, Dwork AJ, Mann JJ, Leong KW, Boldrini M, Wang L, Haeussler M, Raphael BJ, Kluger Y, Castelo-Branco G, Fan R. Spatial epigenome-transcriptome co-profiling of mammalian tissues. Nature 2023; 616:113-122. [PMID: 36922587 PMCID: PMC10076218 DOI: 10.1038/s41586-023-05795-1] [Citation(s) in RCA: 73] [Impact Index Per Article: 73.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Accepted: 02/03/2023] [Indexed: 03/17/2023]
Abstract
Emerging spatial technologies, including spatial transcriptomics and spatial epigenomics, are becoming powerful tools for profiling of cellular states in the tissue context1-5. However, current methods capture only one layer of omics information at a time, precluding the possibility of examining the mechanistic relationship across the central dogma of molecular biology. Here, we present two technologies for spatially resolved, genome-wide, joint profiling of the epigenome and transcriptome by cosequencing chromatin accessibility and gene expression, or histone modifications (H3K27me3, H3K27ac or H3K4me3) and gene expression on the same tissue section at near-single-cell resolution. These were applied to embryonic and juvenile mouse brain, as well as adult human brain, to map how epigenetic mechanisms control transcriptional phenotype and cell dynamics in tissue. Although highly concordant tissue features were identified by either spatial epigenome or spatial transcriptome we also observed distinct patterns, suggesting their differential roles in defining cell states. Linking epigenome to transcriptome pixel by pixel allows the uncovering of new insights in spatial epigenetic priming, differentiation and gene regulation within the tissue architecture. These technologies are of great interest in life science and biomedical research.
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Affiliation(s)
- Di Zhang
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Yanxiang Deng
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA.
- Yale Stem Cell Center and Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA.
- Department of Pathology and Laboratory Medicine, Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
| | - Petra Kukanja
- Laboratory of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Eneritz Agirre
- Laboratory of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Marek Bartosovic
- Laboratory of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Mingze Dong
- Department of Pathology, Yale University School of Medicine, New Haven, CT, USA
- Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
| | - Cong Ma
- Department of Computer Science, Princeton University, Princeton, NJ, USA
| | - Sai Ma
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Graham Su
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
- Yale Stem Cell Center and Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA
| | - Shuozhen Bao
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Yang Liu
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
- Yale Stem Cell Center and Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA
| | - Yang Xiao
- Department of Biomedical Engineering, Columbia University, New York, NY, USA
| | - Gorazd B Rosoklija
- Department of Psychiatry, Columbia University, New York, NY, USA
- Division of Molecular Imaging and Neuropathology, New York State Psychiatric Institute, New York, NY, USA
- Macedonian Academy of Sciences & Arts, Skopje, Republic of Macedonia
| | - Andrew J Dwork
- Department of Psychiatry, Columbia University, New York, NY, USA
- Division of Molecular Imaging and Neuropathology, New York State Psychiatric Institute, New York, NY, USA
- Macedonian Academy of Sciences & Arts, Skopje, Republic of Macedonia
- Department of Pathology and Cell Biology, Columbia University, New York, NY, USA
| | - J John Mann
- Department of Psychiatry, Columbia University, New York, NY, USA
- Division of Molecular Imaging and Neuropathology, New York State Psychiatric Institute, New York, NY, USA
- Department of Radiology, Columbia University, New York, NY, USA
| | - Kam W Leong
- Department of Biomedical Engineering, Columbia University, New York, NY, USA
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
| | - Maura Boldrini
- Department of Psychiatry, Columbia University, New York, NY, USA
- Division of Molecular Imaging and Neuropathology, New York State Psychiatric Institute, New York, NY, USA
| | - Liya Wang
- AtlasXomics, Inc., New Haven, CT, USA
| | | | - Benjamin J Raphael
- Department of Computer Science, Princeton University, Princeton, NJ, USA
| | - Yuval Kluger
- Department of Pathology, Yale University School of Medicine, New Haven, CT, USA
- Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
- Applied Mathematics Program, Yale University, New Haven, CT, USA
| | - Gonçalo Castelo-Branco
- Laboratory of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden.
- Ming Wai Lau Centre for Reparative Medicine, Stockholm Node, Karolinska Institutet, Stockholm, Sweden.
| | - Rong Fan
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA.
- Yale Stem Cell Center and Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA.
- Department of Pathology, Yale University School of Medicine, New Haven, CT, USA.
- Human and Translational Immunology Program, Yale School of Medicine, New Haven, CT, USA.
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319
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Amrute JM, Lai L, Ma P, Koenig AL, Kamimoto K, Bredemeyer A, Shankar TS, Kuppe C, Kadyrov FF, Schulte LJ, Stoutenburg D, Kopecky BJ, Navankasattusas S, Visker J, Morris SA, Kramann R, Leuschner F, Mann DL, Drakos SG, Lavine KJ. Defining cardiac functional recovery in end-stage heart failure at single-cell resolution. NATURE CARDIOVASCULAR RESEARCH 2023; 2:399-416. [PMID: 37583573 PMCID: PMC10426763 DOI: 10.1038/s44161-023-00260-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Accepted: 03/01/2023] [Indexed: 08/17/2023]
Abstract
Recovery of cardiac function is the holy grail of heart failure therapy yet is infrequently observed and remains poorly understood. In this study, we performed single-nucleus RNA sequencing from patients with heart failure who recovered left ventricular systolic function after left ventricular assist device implantation, patients who did not recover and non-diseased donors. We identified cell-specific transcriptional signatures of recovery, most prominently in macrophages and fibroblasts. Within these cell types, inflammatory signatures were negative predictors of recovery, and downregulation of RUNX1 was associated with recovery. In silico perturbation of RUNX1 in macrophages and fibroblasts recapitulated the transcriptional state of recovery. Cardiac recovery mediated by BET inhibition in mice led to decreased macrophage and fibroblast Runx1 expression and diminished chromatin accessibility within a Runx1 intronic peak and acquisition of human recovery signatures. These findings suggest that cardiac recovery is a unique biological state and identify RUNX1 as a possible therapeutic target to facilitate cardiac recovery.
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Affiliation(s)
- Junedh M. Amrute
- Cardiovascular Division, Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA
- These authors contributed equally: Junedh M. Amrute, Lulu Lai
| | - Lulu Lai
- Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, USA
- These authors contributed equally: Junedh M. Amrute, Lulu Lai
| | - Pan Ma
- Cardiovascular Division, Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA
| | - Andrew L. Koenig
- Cardiovascular Division, Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA
| | - Kenji Kamimoto
- Department of Developmental Biology, Washington University School of Medicine, St. Louis, MO, USA
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
- Center for Regenerative Medicine, Washington University School of Medicine, St. Louis, MO, USA
| | - Andrea Bredemeyer
- Cardiovascular Division, Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA
| | - Thirupura S. Shankar
- Division of Cardiovascular Medicine & Nora Eccles Harrison Cardiovascular Research and Training Institute, University of Utah Health & School of Medicine, Salt Lake City, UT, USA
| | - Christoph Kuppe
- Institute of Experimental Medicine and Systems Biology and Division of Nephrology, RWTH Aachen University, Aachen, Germany
| | - Farid F. Kadyrov
- Cardiovascular Division, Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA
| | - Linda J. Schulte
- Division of Cardiothoracic Surgery, Department of Surgery, Washington University School of Medicine, St. Louis, MO, USA
| | - Dylan Stoutenburg
- Cardiovascular Division, Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA
| | - Benjamin J. Kopecky
- Cardiovascular Division, Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA
| | - Sutip Navankasattusas
- Division of Cardiovascular Medicine & Nora Eccles Harrison Cardiovascular Research and Training Institute, University of Utah Health & School of Medicine, Salt Lake City, UT, USA
| | - Joseph Visker
- Division of Cardiovascular Medicine & Nora Eccles Harrison Cardiovascular Research and Training Institute, University of Utah Health & School of Medicine, Salt Lake City, UT, USA
| | - Samantha A. Morris
- Department of Developmental Biology, Washington University School of Medicine, St. Louis, MO, USA
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
- Center for Regenerative Medicine, Washington University School of Medicine, St. Louis, MO, USA
| | - Rafael Kramann
- Institute of Experimental Medicine and Systems Biology and Division of Nephrology, RWTH Aachen University, Aachen, Germany
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Florian Leuschner
- Department of Cardiology, University Hospital Heidelberg, Heidelberg, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Heidelberg, Heidelberg, Germany
| | - Douglas L. Mann
- Cardiovascular Division, Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA
| | - Stavros G. Drakos
- Division of Cardiovascular Medicine & Nora Eccles Harrison Cardiovascular Research and Training Institute, University of Utah Health & School of Medicine, Salt Lake City, UT, USA
| | - Kory J. Lavine
- Cardiovascular Division, Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA
- Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, USA
- Department of Developmental Biology, Washington University School of Medicine, St. Louis, MO, USA
- Center for Regenerative Medicine, Washington University School of Medicine, St. Louis, MO, USA
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320
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Taguchi YH, Turki T. Tensor decomposition discriminates tissues using scATAC-seq. Biochim Biophys Acta Gen Subj 2023; 1867:130360. [PMID: 37003566 DOI: 10.1016/j.bbagen.2023.130360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 02/14/2023] [Accepted: 02/19/2023] [Indexed: 04/03/2023]
Abstract
ATAC-seq is a powerful tool for measuring the landscape structure of a chromosome. scATAC-seq is a recently updated version of ATAC-seq performed in a single cell. The problem with scATAC-seq is data sparsity and most of the genomic sites are inaccessible. Here, tensor decomposition (TD) was used to fill in missing values. In this study, TD was applied to massive scATAC-seq datasets generated by approximately 200 bp intervals, and this number can reach 13,627,618. Currently, no other methods can deal with large sparse matrices. The proposed method could not only provide UMAP embedding that coincides with tissue specificity, but also select genes associated with various biological enrichment terms and transcription factor targeting. This suggests that TD is a useful tool to process a large sparse matrix generated from scATAC-seq.
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Affiliation(s)
- Y-H Taguchi
- Department of Physics, Chuo university, 1-13-27, Kasuga, Bunkyo-ku, Tokyo 112-8551, Japan.
| | - Turki Turki
- Department of Computer Science, King Abdulaziz University, Jeddah 21589, Saudi Arabia.
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321
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Lewis SA, Doratt BM, Qiao Q, Blanton MB, Grant KA, Messaoudi I. Integrated single cell analysis shows chronic alcohol drinking disrupts monocyte differentiation in the bone marrow niche. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.29.534727. [PMID: 37034734 PMCID: PMC10081177 DOI: 10.1101/2023.03.29.534727] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Chronic alcohol drinking rewires circulating monocytes and tissue-resident macrophages towards heightened inflammatory states with compromised anti-microbial defenses. As these effects remain consistent in short-lived monocytes after a 1-month abstinence period it is unclear whether these changes are restricted to the periphery or mediated through alterations in the progenitor niche. To test this hypothesis, we profiled monocytes/macrophages and hematopoietic stem cell progenitors (HSCP) of the bone marrow compartment from rhesus macaques after 12 months of ethanol consumption using a combination of functional assays and single cell genomics. Bone marrow-resident monocytes/macrophages from ethanol-consuming animals exhibited heightened inflammation. Differentiation of HSCP in vitro revealed skewing towards monocytes expressing neutrophil-like markers with heightened inflammatory responses to bacterial agonists. Single cell transcriptional analysis of HSCPs showed reduced proliferation but increased inflammatory markers in mature myeloid progenitors. We observed transcriptional signatures associated with increased oxidative and cellular stress as well as oxidative phosphorylation in immature and mature myeloid progenitors. Single cell analysis of the chromatin landscape showed altered drivers of differentiation in monocytes and progenitors. Collectively, these data indicate that chronic ethanol drinking results in remodeling of the transcriptional and epigenetic landscapes of the bone marrow compartment leading to altered functions in the periphery.
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Affiliation(s)
- Sloan A. Lewis
- Department of Molecular Biology and Biochemistry, University of California, Irvine CA 92697, USA
| | - Brianna M Doratt
- Department of Molecular Biology and Biochemistry, University of California, Irvine CA 92697, USA
- Department of Microbiology, Immunology and Molecular Genetics, College of Medicine, University of Kentucky, Lexington, KY 40536
| | - Qi Qiao
- Department of Microbiology, Immunology and Molecular Genetics, College of Medicine, University of Kentucky, Lexington, KY 40536
| | - Madison B. Blanton
- Department of Microbiology, Immunology and Molecular Genetics, College of Medicine, University of Kentucky, Lexington, KY 40536
| | - Kathleen A. Grant
- Oregon National Primate Research Center, Oregon Health and Science University, Beaverton, OR, USA
| | - Ilhem Messaoudi
- Department of Molecular Biology and Biochemistry, University of California, Irvine CA 92697, USA
- Department of Microbiology, Immunology and Molecular Genetics, College of Medicine, University of Kentucky, Lexington, KY 40536
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322
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Hu Y, Ma S, Kartha VK, Duarte FM, Horlbeck M, Zhang R, Shrestha R, Labade A, Kletzien H, Meliki A, Castillo A, Durand N, Mattei E, Anderson LJ, Tay T, Earl AS, Shoresh N, Epstein CB, Wagers A, Buenrostro JD. Single-cell multi-scale footprinting reveals the modular organization of DNA regulatory elements. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.28.533945. [PMID: 37034577 PMCID: PMC10081223 DOI: 10.1101/2023.03.28.533945] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Cis-regulatory elements control gene expression and are dynamic in their structure, reflecting changes to the composition of diverse effector proteins over time1-3. Here we sought to connect the structural changes at cis-regulatory elements to alterations in cellular fate and function. To do this we developed PRINT, a computational method that uses deep learning to correct sequence bias in chromatin accessibility data and identifies multi-scale footprints of DNA-protein interactions. We find that multi-scale footprints enable more accurate inference of TF and nucleosome binding. Using PRINT with single-cell multi-omics, we discover wide-spread changes to the structure and function of candidate cis-regulatory elements (cCREs) across hematopoiesis, wherein nucleosomes slide, expose DNA for TF binding, and promote gene expression. Activity segmentation using the co-variance across cell states identifies "sub-cCREs" as modular cCRE subunits of regulatory DNA. We apply this single-cell and PRINT approach to characterize the age-associated alterations to cCREs within hematopoietic stem cells (HSCs). Remarkably, we find a spectrum of aging alterations among HSCs corresponding to a global gain of sub-cCRE activity while preserving cCRE accessibility. Collectively, we reveal the functional importance of cCRE structure across cell states, highlighting changes to gene regulation at single-cell and single-base-pair resolution.
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Affiliation(s)
- Yan Hu
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142 USA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138 USA
| | - Sai Ma
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142 USA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138 USA
- Current address: Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029 USA
| | - Vinay K. Kartha
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142 USA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138 USA
| | - Fabiana M. Duarte
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142 USA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138 USA
| | - Max Horlbeck
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142 USA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138 USA
| | - Ruochi Zhang
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142 USA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138 USA
| | - Rojesh Shrestha
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142 USA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138 USA
| | - Ajay Labade
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142 USA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138 USA
| | - Heidi Kletzien
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138 USA
- Paul F. Glenn Center for the Biology of Aging, Harvard Medical School, Boston, MA 02115
| | - Alia Meliki
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142 USA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138 USA
| | - Andrew Castillo
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142 USA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138 USA
| | - Neva Durand
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142 USA
| | - Eugenio Mattei
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142 USA
| | - Lauren J. Anderson
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142 USA
| | - Tristan Tay
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142 USA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138 USA
| | - Andrew S. Earl
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142 USA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138 USA
| | - Noam Shoresh
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142 USA
| | - Charles B. Epstein
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142 USA
| | - Amy Wagers
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138 USA
- Paul F. Glenn Center for the Biology of Aging, Harvard Medical School, Boston, MA 02115
| | - Jason D. Buenrostro
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142 USA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138 USA
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323
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Vasaikar SV, Savage AK, Gong Q, Swanson E, Talla A, Lord C, Heubeck AT, Reading J, Graybuck LT, Meijer P, Torgerson TR, Skene PJ, Bumol TF, Li XJ. A comprehensive platform for analyzing longitudinal multi-omics data. Nat Commun 2023; 14:1684. [PMID: 36973282 PMCID: PMC10041512 DOI: 10.1038/s41467-023-37432-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Accepted: 03/17/2023] [Indexed: 03/29/2023] Open
Abstract
Longitudinal bulk and single-cell omics data is increasingly generated for biological and clinical research but is challenging to analyze due to its many intrinsic types of variations. We present PALMO ( https://github.com/aifimmunology/PALMO ), a platform that contains five analytical modules to examine longitudinal bulk and single-cell multi-omics data from multiple perspectives, including decomposition of sources of variations within the data, collection of stable or variable features across timepoints and participants, identification of up- or down-regulated markers across timepoints of individual participants, and investigation on samples of same participants for possible outlier events. We have tested PALMO performance on a complex longitudinal multi-omics dataset of five data modalities on the same samples and six external datasets of diverse background. Both PALMO and our longitudinal multi-omics dataset can be valuable resources to the scientific community.
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Affiliation(s)
| | - Adam K Savage
- Allen Institute for Immunology, Seattle, WA, 98109, USA
| | - Qiuyu Gong
- Allen Institute for Immunology, Seattle, WA, 98109, USA
| | - Elliott Swanson
- Allen Institute for Immunology, Seattle, WA, 98109, USA
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Aarthi Talla
- Allen Institute for Immunology, Seattle, WA, 98109, USA
| | - Cara Lord
- Allen Institute for Immunology, Seattle, WA, 98109, USA
- GlaxoSmithKline, Collegeville, PA, 19426, USA
| | | | | | | | - Paul Meijer
- Allen Institute for Immunology, Seattle, WA, 98109, USA
| | | | - Peter J Skene
- Allen Institute for Immunology, Seattle, WA, 98109, USA
| | | | - Xiao-Jun Li
- Allen Institute for Immunology, Seattle, WA, 98109, USA.
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324
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Ge Y, Chen X, Nan N, Bard J, Wu F, Yergeau D, Liu T, Wang J, Mu X. Key transcription factors influence the epigenetic landscape to regulate retinal cell differentiation. Nucleic Acids Res 2023; 51:2151-2176. [PMID: 36715342 PMCID: PMC10018358 DOI: 10.1093/nar/gkad026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 01/05/2023] [Accepted: 01/09/2023] [Indexed: 01/31/2023] Open
Abstract
How the diverse neural cell types emerge from multipotent neural progenitor cells during central nervous system development remains poorly understood. Recent scRNA-seq studies have delineated the developmental trajectories of individual neural cell types in many neural systems including the neural retina. Further understanding of the formation of neural cell diversity requires knowledge about how the epigenetic landscape shifts along individual cell lineages and how key transcription factors regulate these changes. In this study, we dissect the changes in the epigenetic landscape during early retinal cell differentiation by scATAC-seq and identify globally the enhancers, enriched motifs, and potential interacting transcription factors underlying the cell state/type specific gene expression in individual lineages. Using CUT&Tag, we further identify the enhancers bound directly by four key transcription factors, Otx2, Atoh7, Pou4f2 and Isl1, including those dependent on Atoh7, and uncover the sequential and combinatorial interactions of these factors with the epigenetic landscape to control gene expression along individual retinal cell lineages such as retinal ganglion cells (RGCs). Our results reveal a general paradigm in which transcription factors collaborate and compete to regulate the emergence of distinct retinal cell types such as RGCs from multipotent retinal progenitor cells (RPCs).
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Affiliation(s)
- Yichen Ge
- Department of Ophthalmology/Ross Eye Institute, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, USA
| | - Xushen Chen
- Department of Ophthalmology/Ross Eye Institute, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, USA
| | - Nan Nan
- Department of Ophthalmology/Ross Eye Institute, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, USA
- Department of Biostatistics, School of Public Health and Health Professions, University at Buffalo, Buffalo, NY, USA
| | - Jonathan Bard
- New York State Center of Excellence in Bioinformatics and Life Sciences, University at Buffalo, Buffalo, NY, USA
| | - Fuguo Wu
- Department of Ophthalmology/Ross Eye Institute, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, USA
| | - Donald Yergeau
- New York State Center of Excellence in Bioinformatics and Life Sciences, University at Buffalo, Buffalo, NY, USA
| | - Tao Liu
- Department of Biostatistics & Bioinformatics, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
| | - Jie Wang
- Correspondence may also be addressed to Jie Wang.
| | - Xiuqian Mu
- To whom correspondence should be addressed. Tel: +1 716 881 7463; Fax: +1 716 887 2991;
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325
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Grimm L, Mason E, Yu H, Dudczig S, Panara V, Chen T, Bower NI, Paterson S, Rondon Galeano M, Kobayashi S, Senabouth A, Lagendijk AK, Powell J, Smith KA, Okuda KS, Koltowska K, Hogan BM. Single-cell analysis of lymphatic endothelial cell fate specification and differentiation during zebrafish development. EMBO J 2023:e112590. [PMID: 36912146 DOI: 10.15252/embj.2022112590] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 01/24/2023] [Accepted: 02/03/2023] [Indexed: 03/14/2023] Open
Abstract
During development, the lymphatic vasculature forms as a second network derived chiefly from blood vessels. The transdifferentiation of embryonic venous endothelial cells (VECs) into lymphatic endothelial cells (LECs) is a key step in this process. Specification, differentiation and maintenance of LEC fate are all driven by the transcription factor Prox1, yet the downstream mechanisms remain to be elucidated. We here present a single-cell transcriptomic atlas of lymphangiogenesis in zebrafish, revealing new markers and hallmarks of LEC differentiation over four developmental stages. We further profile single-cell transcriptomic and chromatin accessibility changes in zygotic prox1a mutants that are undergoing a LEC-VEC fate shift. Using maternal and zygotic prox1a/prox1b mutants, we determine the earliest transcriptomic changes directed by Prox1 during LEC specification. This work altogether reveals new downstream targets and regulatory regions of the genome controlled by Prox1 and presents evidence that Prox1 specifies LEC fate primarily by limiting blood vascular and haematopoietic fate. This extensive single-cell resource provides new mechanistic insights into the enigmatic role of Prox1 and the control of LEC differentiation in development.
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Affiliation(s)
- Lin Grimm
- Organogenesis and Cancer Program, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia.,Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia.,Division of Genomics of Development and Disease, Institute for Molecular Bioscience, The University of Queensland, St Lucia, Brisbane, QLD, Australia
| | - Elizabeth Mason
- Organogenesis and Cancer Program, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia.,Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia
| | - Hujun Yu
- Organogenesis and Cancer Program, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia.,Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia
| | - Stefanie Dudczig
- Organogenesis and Cancer Program, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia.,Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia
| | - Virginia Panara
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Tyrone Chen
- Organogenesis and Cancer Program, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia.,Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia
| | - Neil I Bower
- Division of Genomics of Development and Disease, Institute for Molecular Bioscience, The University of Queensland, St Lucia, Brisbane, QLD, Australia
| | - Scott Paterson
- Organogenesis and Cancer Program, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia.,Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia.,Division of Genomics of Development and Disease, Institute for Molecular Bioscience, The University of Queensland, St Lucia, Brisbane, QLD, Australia
| | - Maria Rondon Galeano
- Organogenesis and Cancer Program, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia.,Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia
| | - Sakurako Kobayashi
- Organogenesis and Cancer Program, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia.,Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia
| | - Anne Senabouth
- Division of Genomics of Development and Disease, Institute for Molecular Bioscience, The University of Queensland, St Lucia, Brisbane, QLD, Australia.,Garvan Institute of Medical Research, Sydney, NSW, Australia
| | - Anne K Lagendijk
- Division of Genomics of Development and Disease, Institute for Molecular Bioscience, The University of Queensland, St Lucia, Brisbane, QLD, Australia
| | - Joseph Powell
- Division of Genomics of Development and Disease, Institute for Molecular Bioscience, The University of Queensland, St Lucia, Brisbane, QLD, Australia.,Garvan Institute of Medical Research, Sydney, NSW, Australia.,School of Medical Sciences, University of New South Wales, Kensington, Sydney, NSW, Australia.,Garvan-Weizmann Centre for Cellular Genomics, Garvan Institute of Medical Research, Sydney, NSW, Australia
| | - Kelly A Smith
- Department of Anatomy and Physiology, University of Melbourne, Melbourne, VIC, Australia
| | - Kazuhide S Okuda
- Organogenesis and Cancer Program, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia.,Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia
| | - Katarzyna Koltowska
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Benjamin M Hogan
- Organogenesis and Cancer Program, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia.,Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia.,Division of Genomics of Development and Disease, Institute for Molecular Bioscience, The University of Queensland, St Lucia, Brisbane, QLD, Australia.,Department of Anatomy and Physiology, University of Melbourne, Melbourne, VIC, Australia
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326
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Liuyang S, Wang G, Wang Y, He H, Lyu Y, Cheng L, Yang Z, Guan J, Fu Y, Zhu J, Zhong X, Sun S, Li C, Wang J, Deng H. Highly efficient and rapid generation of human pluripotent stem cells by chemical reprogramming. Cell Stem Cell 2023; 30:450-459.e9. [PMID: 36944335 DOI: 10.1016/j.stem.2023.02.008] [Citation(s) in RCA: 32] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Revised: 01/17/2023] [Accepted: 02/22/2023] [Indexed: 03/23/2023]
Abstract
We recently demonstrated the chemical reprogramming of human somatic cells to pluripotent stem cells (hCiPSCs), which provides a robust approach for cell fate manipulation. However, the utility of this chemical approach is currently hampered by slow kinetics. Here, by screening for small molecule boosters and systematically optimizing the original condition, we have established a robust, chemically defined reprogramming protocol, which greatly shortens the induction time from ∼50 days to a minimum of 16 days and enables highly reproducible and efficient generation of hCiPSCs from all 17 tested donors. We found that this optimized protocol enabled a more direct reprogramming process by promoting cell proliferation and oxidative phosphorylation metabolic activities at the early stage. Our results highlight a distinct chemical reprogramming pathway that leads to a shortcut for the generation of human pluripotent stem cells, which represents a powerful strategy for human cell fate manipulation.
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Affiliation(s)
- Shijia Liuyang
- MOE Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences and MOE Engineering Research Center of Regenerative Medicine, School of Basic Medical Sciences, State Key Laboratory of Natural and Biomimetic Drugs, Peking University Health Science Center, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Guan Wang
- MOE Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences and MOE Engineering Research Center of Regenerative Medicine, School of Basic Medical Sciences, State Key Laboratory of Natural and Biomimetic Drugs, Peking University Health Science Center, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China; State Key Laboratory of Chemical Oncogenomics, School of Chemical Biology and Biotechnology, Peking University Shenzhen Graduate School, Shenzhen, China
| | - Yanglu Wang
- Academy for Advanced Interdisciplinary Studies, The Center for Biomed-X Research, Peking University, Beijing, China
| | - Huanjing He
- MOE Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences and MOE Engineering Research Center of Regenerative Medicine, School of Basic Medical Sciences, State Key Laboratory of Natural and Biomimetic Drugs, Peking University Health Science Center, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Yulin Lyu
- School of Life Sciences, Center for Bioinformatics, Center for Statistical Science, Peking University, Beijing, China
| | - Lin Cheng
- MOE Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences and MOE Engineering Research Center of Regenerative Medicine, School of Basic Medical Sciences, State Key Laboratory of Natural and Biomimetic Drugs, Peking University Health Science Center, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Zhihan Yang
- MOE Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences and MOE Engineering Research Center of Regenerative Medicine, School of Basic Medical Sciences, State Key Laboratory of Natural and Biomimetic Drugs, Peking University Health Science Center, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Jingyang Guan
- MOE Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences and MOE Engineering Research Center of Regenerative Medicine, School of Basic Medical Sciences, State Key Laboratory of Natural and Biomimetic Drugs, Peking University Health Science Center, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Yao Fu
- MOE Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences and MOE Engineering Research Center of Regenerative Medicine, School of Basic Medical Sciences, State Key Laboratory of Natural and Biomimetic Drugs, Peking University Health Science Center, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Jialiang Zhu
- MOE Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences and MOE Engineering Research Center of Regenerative Medicine, School of Basic Medical Sciences, State Key Laboratory of Natural and Biomimetic Drugs, Peking University Health Science Center, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Xinxing Zhong
- MOE Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences and MOE Engineering Research Center of Regenerative Medicine, School of Basic Medical Sciences, State Key Laboratory of Natural and Biomimetic Drugs, Peking University Health Science Center, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China; State Key Laboratory of Chemical Oncogenomics, School of Chemical Biology and Biotechnology, Peking University Shenzhen Graduate School, Shenzhen, China
| | - Shicheng Sun
- MOE Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences and MOE Engineering Research Center of Regenerative Medicine, School of Basic Medical Sciences, State Key Laboratory of Natural and Biomimetic Drugs, Peking University Health Science Center, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Cheng Li
- School of Life Sciences, Center for Bioinformatics, Center for Statistical Science, Peking University, Beijing, China
| | - Jinlin Wang
- MOE Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences and MOE Engineering Research Center of Regenerative Medicine, School of Basic Medical Sciences, State Key Laboratory of Natural and Biomimetic Drugs, Peking University Health Science Center, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China.
| | - Hongkui Deng
- MOE Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences and MOE Engineering Research Center of Regenerative Medicine, School of Basic Medical Sciences, State Key Laboratory of Natural and Biomimetic Drugs, Peking University Health Science Center, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China; State Key Laboratory of Chemical Oncogenomics, School of Chemical Biology and Biotechnology, Peking University Shenzhen Graduate School, Shenzhen, China.
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327
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Sakamoto A, Kawakami R, Mori M, Guo L, Paek KH, Mosquera JV, Cornelissen A, Ghosh SKB, Kawai K, Konishi T, Fernandez R, Fuller DT, Xu W, Vozenilek AE, Sato Y, Jinnouchi H, Torii S, Turner AW, Akahori H, Kuntz S, Weinkauf CC, Lee PJ, Kutys R, Harris K, Killey AL, Mayhew CM, Ellis M, Weinstein LM, Gadhoke NV, Dhingra R, Ullman J, Dikongue A, Romero ME, Kolodgie FD, Miller CL, Virmani R, Finn AV. CD163+ macrophages restrain vascular calcification, promoting the development of high-risk plaque. JCI Insight 2023; 8:e154922. [PMID: 36719758 PMCID: PMC10077470 DOI: 10.1172/jci.insight.154922] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 01/20/2023] [Indexed: 02/01/2023] Open
Abstract
Vascular calcification (VC) is concomitant with atherosclerosis, yet it remains uncertain why rupture-prone high-risk plaques do not typically show extensive calcification. Intraplaque hemorrhage (IPH) deposits erythrocyte-derived cholesterol, enlarging the necrotic core and promoting high-risk plaque development. Pro-atherogenic CD163+ alternative macrophages engulf hemoglobin:haptoglobin (HH) complexes at IPH sites. However, their role in VC has never been examined to our knowledge. Here we show, in human arteries, the distribution of CD163+ macrophages correlated inversely with VC. In vitro experiments using vascular smooth muscle cells (VSMCs) cultured with HH-exposed human macrophage - M(Hb) - supernatant reduced calcification, while arteries from ApoE-/- CD163-/- mice showed greater VC. M(Hb) supernatant-exposed VSMCs showed activated NF-κB, while blocking NF-κB attenuated the anticalcific effect of M(Hb) on VSMCs. CD163+ macrophages altered VC through NF-κB-induced transcription of hyaluronan synthase (HAS), an enzyme that catalyzes the formation of the extracellular matrix glycosaminoglycan, hyaluronan, within VSMCs. M(Hb) supernatants enhanced HAS production in VSMCs, while knocking down HAS attenuated its anticalcific effect. NF-κB blockade in ApoE-/- mice reduced hyaluronan and increased VC. In human arteries, hyaluronan and HAS were increased in areas of CD163+ macrophage presence. Our findings highlight an important mechanism by which CD163+ macrophages inhibit VC through NF-κB-induced HAS augmentation and thus promote the high-risk plaque development.
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Affiliation(s)
| | | | | | - Liang Guo
- CVPath Institute, Inc., Gaithersburg, Maryland, USA
| | - Ka Hyun Paek
- CVPath Institute, Inc., Gaithersburg, Maryland, USA
| | - Jose Verdezoto Mosquera
- Department of Public Health Sciences, Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, Virginia, USA
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, Virginia, USA
| | | | | | - Kenji Kawai
- CVPath Institute, Inc., Gaithersburg, Maryland, USA
| | | | | | | | - Weili Xu
- CVPath Institute, Inc., Gaithersburg, Maryland, USA
| | | | - Yu Sato
- CVPath Institute, Inc., Gaithersburg, Maryland, USA
| | | | - Sho Torii
- CVPath Institute, Inc., Gaithersburg, Maryland, USA
| | - Adam W. Turner
- Department of Public Health Sciences, Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, Virginia, USA
| | - Hirokuni Akahori
- Department of Cardiovascular and Renal Medicine, Hyogo Medical University, Nishinomiya, Hyogo, Japan
| | - Salome Kuntz
- CVPath Institute, Inc., Gaithersburg, Maryland, USA
| | - Craig C. Weinkauf
- Division of Vascular and Endovascular Surgery, University of Arizona, Tucson, Arizona, USA
| | | | - Robert Kutys
- CVPath Institute, Inc., Gaithersburg, Maryland, USA
| | - Kathryn Harris
- University of Maryland School of Medicine, Baltimore, Maryland, USA
| | | | | | | | | | | | - Roma Dhingra
- CVPath Institute, Inc., Gaithersburg, Maryland, USA
| | | | | | | | | | - Clint L. Miller
- Department of Public Health Sciences, Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, Virginia, USA
| | - Renu Virmani
- CVPath Institute, Inc., Gaithersburg, Maryland, USA
| | - Aloke V. Finn
- CVPath Institute, Inc., Gaithersburg, Maryland, USA
- University of Maryland School of Medicine, Baltimore, Maryland, USA
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328
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Raths F, Karimzadeh M, Ing N, Martinez A, Yang Y, Qu Y, Lee TY, Mulligan B, Devkota S, Tilley WT, Hickey TE, Wang B, Giuliano AE, Bose S, Goodarzi H, Ray EC, Cui X, Knott SR. The molecular consequences of androgen activity in the human breast. CELL GENOMICS 2023; 3:100272. [PMID: 36950379 PMCID: PMC10025454 DOI: 10.1016/j.xgen.2023.100272] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 10/20/2022] [Accepted: 01/30/2023] [Indexed: 03/24/2023]
Abstract
Estrogen and progesterone have been extensively studied in the mammary gland, but the molecular effects of androgen remain largely unexplored. Transgender men are recorded as female at birth but identify as male and may undergo gender-affirming androgen therapy to align their physical characteristics and gender identity. Here we perform single-cell-resolution transcriptome, chromatin, and spatial profiling of breast tissues from transgender men following androgen therapy. We find canonical androgen receptor gene targets are upregulated in cells expressing the androgen receptor and that paracrine signaling likely drives sex-relevant androgenic effects in other cell types. We also observe involution of the epithelium and a spatial reconfiguration of immune, fibroblast, and vascular cells, and identify a gene regulatory network associated with androgen-induced fat loss. This work elucidates the molecular consequences of androgen activity in the human breast at single-cell resolution.
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Affiliation(s)
- Florian Raths
- Center for Bioinformatics and Functional Genomics, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Mehran Karimzadeh
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, USA
- Vector Institute, Toronto, ON, Canada
- Peter Munk Cardiac Centre, University Health Network, Toronto, ON, Canada
- Department of Urology, University of California, San Francisco, San Francisco, CA, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Nathan Ing
- Center for Bioinformatics and Functional Genomics, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Andrew Martinez
- Center for Bioinformatics and Functional Genomics, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Yoona Yang
- Center for Bioinformatics and Functional Genomics, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Ying Qu
- Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Tian-Yu Lee
- Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Brianna Mulligan
- Center for Bioinformatics and Functional Genomics, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Suzanne Devkota
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Wayne T. Tilley
- Dame Roma Mitchell Cancer Research Laboratories, Adelaide Medical School, University of Adelaide, Adelaide, SA, Australia
- Freemasons Centre for Male Health and Wellbeing, University of Adelaide, Adelaide, SA, Australia
| | - Theresa E. Hickey
- Dame Roma Mitchell Cancer Research Laboratories, Adelaide Medical School, University of Adelaide, Adelaide, SA, Australia
| | - Bo Wang
- Vector Institute, Toronto, ON, Canada
- Peter Munk Cardiac Centre, University Health Network, Toronto, ON, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
- Department of Computer Science, University of Toronto, Toronto, ON, Canada
| | | | - Shikha Bose
- Department of Pathology and Laboratory Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Hani Goodarzi
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, USA
- Department of Urology, University of California, San Francisco, San Francisco, CA, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Edward C. Ray
- Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Transgender Surgery and Health Program, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Xiaojiang Cui
- Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Simon R.V. Knott
- Center for Bioinformatics and Functional Genomics, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
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329
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Booth GT, Daza RM, Srivatsan SR, McFaline-Figueroa JL, Gladden RG, Furlan SN, Shendure J, Trapnell C. High-Capacity Sample Multiplexing for Single Cell Chromatin Accessibility Profiling. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.05.531201. [PMID: 36945538 PMCID: PMC10028990 DOI: 10.1101/2023.03.05.531201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/11/2023]
Abstract
Single-cell chromatin accessibility has emerged as a powerful means of understanding the epigenetic landscape of diverse tissues and cell types, but profiling cells from many independent specimens is challenging and costly. Here we describe a novel approach, sciPlex-ATAC-seq, which uses unmodified DNA oligos as sample-specific nuclear labels, enabling the concurrent profiling of chromatin accessibility within single nuclei from virtually unlimited specimens or experimental conditions. We first demonstrate our method with a chemical epigenomics screen, in which we identify drug-altered distal regulatory sites predictive of compound- and dose-dependent effects on transcription. We then analyze cell type-specific chromatin changes in PBMCs from multiple donors responding to synthetic and allogeneic immune stimulation. We quantify stimulation-altered immune cell compositions and isolate the unique effects of allogeneic stimulation on chromatin accessibility specific to T-lymphocytes. Finally, we observe that impaired global chromatin decondensation often coincides with chemical inhibition of allogeneic T-cell activation.
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Affiliation(s)
- Gregory T. Booth
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Riza M. Daza
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | | | - José L. McFaline-Figueroa
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Department of Biomedical Engineering, Columbia University, New York City, NY, USA
| | - Rula Green Gladden
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Scott N. Furlan
- Brotman Baty Institute for Precision Medicine, Seattle, WA, USA
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Department of Pediatrics, University of Washington, Seattle, WA, USA
| | - Jay Shendure
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Brotman Baty Institute for Precision Medicine, Seattle, WA, USA
- Allen Discovery Center for Cell Lineage Tracing, Seattle, WA, USA
- Howard Hughes Medical Institute, Seattle, WA, USA
| | - Cole Trapnell
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Brotman Baty Institute for Precision Medicine, Seattle, WA, USA
- Allen Discovery Center for Cell Lineage Tracing, Seattle, WA, USA
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330
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Jiang S, Huang Z, Li Y, Yu C, Yu H, Ke Y, Jiang L, Liu J. Single-cell chromatin accessibility and transcriptome atlas of mouse embryos. Cell Rep 2023; 42:112210. [PMID: 36881507 DOI: 10.1016/j.celrep.2023.112210] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Revised: 11/08/2022] [Accepted: 02/16/2023] [Indexed: 03/08/2023] Open
Abstract
Cis-regulatory elements regulate gene expression and lineage specification. However, the potential regulation of cis-elements on mammalian embryogenesis remains largely unexplored. To address this question, we perform single-cell assay for transposase-accessible chromatin using sequencing (ATAC-seq) and RNA-seq in embryonic day 7.5 (E7.5) and E13.5 mouse embryos. We construct the chromatin accessibility landscapes with cell spatial information in E7.5 embryos, showing the spatial patterns of cis-elements and the spatial distribution of potentially functional transcription factors (TFs). We further show that many germ-layer-specific cis-elements and TFs in E7.5 embryos are maintained in the cell types derived from the corresponding germ layers at later stages, suggesting that these cis-elements and TFs are important during cell differentiation. We also find a potential progenitor for Sertoli and granulosa cells in gonads. Interestingly, both Sertoli and granulosa cells exist in male gonads and female gonads during gonad development. Collectively, we provide a valuable resource to understand organogenesis in mammals.
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Affiliation(s)
- Shan Jiang
- China National Center for Bioinformation, Beijing 100101, China; CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
| | - Zheng Huang
- China National Center for Bioinformation, Beijing 100101, China; CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
| | - Yun Li
- China National Center for Bioinformation, Beijing 100101, China; CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
| | - Chengwei Yu
- China National Center for Bioinformation, Beijing 100101, China; CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; College of Future Technology College, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Hao Yu
- China National Center for Bioinformation, Beijing 100101, China; CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; College of Future Technology College, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yuwen Ke
- College of Biological Science, China Agricultural University, Beijing 100193, China
| | - Lan Jiang
- China National Center for Bioinformation, Beijing 100101, China; CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; College of Future Technology College, University of Chinese Academy of Sciences, Beijing 100049, China; Sino-Danish College, University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Jiang Liu
- China National Center for Bioinformation, Beijing 100101, China; CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; College of Future Technology College, University of Chinese Academy of Sciences, Beijing 100049, China; CAS Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China.
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331
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Romine KA, MacPherson K, Cho HJ, Kosaka Y, Flynn PA, Byrd KH, Coy JL, Newman MT, Pandita R, Loo CP, Scott J, Adey AC, Lind EF. BET inhibitors rescue anti-PD1 resistance by enhancing TCF7 accessibility in leukemia-derived terminally exhausted CD8 + T cells. Leukemia 2023; 37:580-592. [PMID: 36681742 PMCID: PMC9991923 DOI: 10.1038/s41375-023-01808-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Revised: 12/08/2022] [Accepted: 01/04/2023] [Indexed: 01/22/2023]
Abstract
Many acute myeloid leukemia (AML) patients exhibit hallmarks of immune exhaustion, such as increased myeloid-derived suppressor cells, suppressive regulatory T cells and dysfunctional T cells. Similarly, we have identified the same immune-related features, including exhausted CD8+ T cells (TEx) in a mouse model of AML. Here we show that inhibitors that target bromodomain and extra-terminal domain (BET) proteins affect tumor-intrinsic factors but also rescue T cell exhaustion and ICB resistance. Ex vivo treatment of cells from AML mice and AML patients with BET inhibitors (BETi) reversed CD8+ T cell exhaustion by restoring proliferative capacity and expansion of the more functional precursor-exhausted T cells. This reversal was enhanced by combined BETi and anti-PD1 treatment. BETi synergized with anti-PD1 in vivo, resulting in the reduction of circulating leukemia cells, enrichment of CD8+ T cells in the bone marrow, and increase in expression of Tcf7, Slamf6, and Cxcr5 in CD8+ T cells. Finally, we profiled the epigenomes of in vivo JQ1-treated AML-derived CD8+ T cells by single-cell ATAC-seq and found that JQ1 increases Tcf7 accessibility specifically in Tex cells, suggesting that BETi likely acts mechanistically by relieving repression of progenitor programs in Tex CD8+ T cells and maintaining a pool of anti-PD1 responsive CD8+ T cells.
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Affiliation(s)
- Kyle A Romine
- Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR, USA
| | - Kevin MacPherson
- Department of Molecular & Medical Genetics, Oregon Health & Science University, Portland, OR, USA
| | - Hyun-Jun Cho
- Department of Molecular Microbiology and Immunology, Oregon Health & Science University, Portland, OR, USA
| | - Yoko Kosaka
- Department of Molecular Microbiology and Immunology, Oregon Health & Science University, Portland, OR, USA
| | - Patrick A Flynn
- Department of Molecular Microbiology and Immunology, Oregon Health & Science University, Portland, OR, USA
| | - Kaelan H Byrd
- Department of Molecular Microbiology and Immunology, Oregon Health & Science University, Portland, OR, USA
| | - Jesse L Coy
- Department of Molecular Microbiology and Immunology, Oregon Health & Science University, Portland, OR, USA
| | - Matthew T Newman
- School of Medicine, Oregon Health & Science University, Portland, OR, USA
| | - Ravina Pandita
- Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR, USA
| | - Christopher P Loo
- Department of Molecular Microbiology and Immunology, Oregon Health & Science University, Portland, OR, USA
| | - Jaime Scott
- Department of Molecular Microbiology and Immunology, Oregon Health & Science University, Portland, OR, USA
| | - Andrew C Adey
- Department of Molecular & Medical Genetics, Oregon Health & Science University, Portland, OR, USA
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Knight Cardiovascular Institute, Oregon Health & Science University, Portland, OR, USA
- Center for Early Detection Advanced Research, Oregon Health & Science University, Portland, OR, USA
| | - Evan F Lind
- Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR, USA.
- Department of Molecular Microbiology and Immunology, Oregon Health & Science University, Portland, OR, USA.
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA.
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332
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ten Hacken E, Sewastianik T, Yin S, Hoffmann GB, Gruber M, Clement K, Penter L, Redd RA, Ruthen N, Hergalant S, Sholokhova A, Fell G, Parry EM, Broséus J, Guieze R, Lucas F, Hernández-Sánchez M, Baranowski K, Southard J, Joyal H, Billington L, Regis FFD, Witten E, Uduman M, Knisbacher BA, Li S, Lyu H, Vaisitti T, Deaglio S, Inghirami G, Feugier P, Stilgenbauer S, Tausch E, Davids MS, Getz G, Livak KJ, Bozic I, Neuberg DS, Carrasco RD, Wu CJ. In Vivo Modeling of CLL Transformation to Richter Syndrome Reveals Convergent Evolutionary Paths and Therapeutic Vulnerabilities. Blood Cancer Discov 2023; 4:150-169. [PMID: 36468984 PMCID: PMC9975769 DOI: 10.1158/2643-3230.bcd-22-0082] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 09/16/2022] [Accepted: 12/02/2022] [Indexed: 12/12/2022] Open
Abstract
Transformation to aggressive disease histologies generates formidable clinical challenges across cancers, but biological insights remain few. We modeled the genetic heterogeneity of chronic lymphocytic leukemia (CLL) through multiplexed in vivo CRISPR-Cas9 B-cell editing of recurrent CLL loss-of-function drivers in mice and recapitulated the process of transformation from indolent CLL into large cell lymphoma [i.e., Richter syndrome (RS)]. Evolutionary trajectories of 64 mice carrying diverse combinatorial gene assortments revealed coselection of mutations in Trp53, Mga, and Chd2 and the dual impact of clonal Mga/Chd2 mutations on E2F/MYC and interferon signaling dysregulation. Comparative human and murine RS analyses demonstrated tonic PI3K signaling as a key feature of transformed disease, with constitutive activation of the AKT and S6 kinases, downmodulation of the PTEN phosphatase, and convergent activation of MYC/PI3K transcriptional programs underlying enhanced sensitivity to MYC/mTOR/PI3K inhibition. This robust experimental system presents a unique framework to study lymphoid biology and therapy. SIGNIFICANCE Mouse models reflective of the genetic complexity and heterogeneity of human tumors remain few, including those able to recapitulate transformation to aggressive disease histologies. Herein, we model CLL transformation into RS through multiplexed in vivo gene editing, providing key insight into the pathophysiology and therapeutic vulnerabilities of transformed disease. This article is highlighted in the In This Issue feature, p. 101.
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Affiliation(s)
- Elisa ten Hacken
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Tomasz Sewastianik
- Harvard Medical School, Boston, Massachusetts
- Department of Oncologic Pathology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Department of Experimental Hematology, Institute of Hematology and Transfusion Medicine, Warsaw, Poland
| | - Shanye Yin
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | | | - Michaela Gruber
- CEMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Kendell Clement
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Molecular Pathology Unit, Center for Cancer Research and Center for Computational and Integrative Biology, Massachusetts General Hospital, Charlestown, Massachusetts
- Department of Pathology, Harvard Medical School, Boston, Massachusetts
| | - Livius Penter
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Department of Hematology, Oncology, and Tumorimmunology, Campus Virchow Klinikum, Berlin, Charité – Universitätsmedizin Berlin (corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin), Berlin, Germany
| | - Robert A. Redd
- Department of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Neil Ruthen
- Translational Immunogenomics Lab, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Sébastien Hergalant
- Inserm UMRS1256 Nutrition-Génétique et Exposition aux Risques Environnementaux (N-GERE), Université de Lorraine, Nancy, France
| | - Alanna Sholokhova
- Department of Applied Mathematics, University of Washington, Seattle, Washington
| | - Geoffrey Fell
- Department of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Erin M. Parry
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
- Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts
| | - Julien Broséus
- Inserm UMRS1256 Nutrition-Génétique et Exposition aux Risques Environnementaux (N-GERE), Université de Lorraine, Nancy, France
- Université de Lorraine, CHRU-Nancy, Service d'Hématologie Biologique, Pôle Laboratoires, Nancy, France
| | | | - Fabienne Lucas
- Harvard Medical School, Boston, Massachusetts
- Department of Pathology, Brigham and Women's Hospital, Boston, Massachusetts
| | - María Hernández-Sánchez
- Department of Biochemistry and Molecular Biology, Pharmacy School, Universidad Complutense de Madrid, Madrid, Spain
| | - Kaitlyn Baranowski
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Jackson Southard
- Translational Immunogenomics Lab, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Heather Joyal
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Leah Billington
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Fara Faye D. Regis
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Elizabeth Witten
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Mohamed Uduman
- Department of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Binyamin A. Knisbacher
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Cancer Research Center, Sheba Medical Center, Tel Hashomer, Israel
| | - Shuqiang Li
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Translational Immunogenomics Lab, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Haoxiang Lyu
- Translational Immunogenomics Lab, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Tiziana Vaisitti
- Department of Medical Sciences, University of Torino, Turin, Italy
| | - Silvia Deaglio
- Department of Medical Sciences, University of Torino, Turin, Italy
| | - Giorgio Inghirami
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, New York
| | - Pierre Feugier
- Inserm UMRS1256 Nutrition-Génétique et Exposition aux Risques Environnementaux (N-GERE), Université de Lorraine, Nancy, France
- Université de Lorraine, CHRU-Nancy, Service d'Hématologie Biologique, Pôle Laboratoires, Nancy, France
| | - Stephan Stilgenbauer
- Department III of Internal Medicine III, Division of CLL, Ulm University, Ulm, Germany
| | - Eugen Tausch
- Department III of Internal Medicine III, Division of CLL, Ulm University, Ulm, Germany
| | - Matthew S. Davids
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
- Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts
| | - Gad Getz
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Cancer Center and Department of Pathology, Massachusetts General Hospital, Boston, Massachusetts
| | - Kenneth J. Livak
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Translational Immunogenomics Lab, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Ivana Bozic
- Department of Applied Mathematics, University of Washington, Seattle, Washington
| | - Donna S. Neuberg
- Department of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Ruben D. Carrasco
- Harvard Medical School, Boston, Massachusetts
- Department of Oncologic Pathology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Department of Pathology, Brigham and Women's Hospital, Boston, Massachusetts
| | - Catherine J. Wu
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts
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333
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Lu ZJ, Ye JG, Wang DL, Li MK, Zhang QK, Liu Z, Huang YJ, Pan CN, Lin YH, Shi ZX, Zheng YF. Integrative Single-Cell RNA-Seq and ATAC-Seq Analysis of Mouse Corneal Epithelial Cells. Invest Ophthalmol Vis Sci 2023; 64:30. [PMID: 36943152 PMCID: PMC10043503 DOI: 10.1167/iovs.64.3.30] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/23/2023] Open
Abstract
Purpose Corneal epithelial homeostasis is maintained by coordinated gene expression across distinct cell populations, but the gene regulatory programs underlying this cellular diversity remain to be characterized. Here we applied single-cell multi-omics analysis to delineate the gene regulatory profile of mouse corneal epithelial cells under normal homeostasis. Methods Single cells isolated from the cornea epithelium (with marginal conjunctiva) of adult mice were subjected to scRNA-seq and scATAC-seq using the 10×Genomics platform. Cell types were clustered by the graph-based visualization method uniform manifold approximation and projection and unbiased computational informatics analysis. The scRNA-seq and scATAC-seq datasets were integrated following the integration pipeline described in ArchR and Seurat. Results We characterized diverse corneal epithelial cell types based on gene expression signatures and chromatin accessibility. We found that cell type-specific accessibility regions were mainly located at distal regions, suggesting essential roles of distal regulatory elements in determining corneal epithelial cell diversity. Trajectory analyses revealed a continuum of cell state transition and higher coordination between transcription factor (TF) motif accessibility and gene expression during corneal epithelial cell differentiation. By integrating transcriptomic and chromatin accessibility analysis, we identified cell type-specific and shared gene regulation programs. We also uncovered critical TFs driving corneal epithelial cell differentiation, such as nuclear factor I (NFI) family members, Rarg, Elf3. We found that nuclear factor-κB (NF-κB) family members were positive TFs in limbal cells and some superficial cells, but they were involved in regulating distinct biological processes. Conclusions Our study presents a comprehensive gene regulatory landscape of mouse cornea epithelial cells, and provides valuable foundations for future investigation of corneal epithelial homeostasis in the context of cornea pathologies and regenerative medicine.
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Affiliation(s)
- Zhao-Jing Lu
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China
- Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China
- Research Unit of Ocular Development and Regeneration, Chinese Academy of Medical Sciences, China
| | - Jin-Guo Ye
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China
| | - Dong-Liang Wang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China
| | - Meng-Ke Li
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China
| | - Qi-Kai Zhang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China
| | - Zhong Liu
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China
| | - Yan-Jing Huang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China
| | - Cai-Neng Pan
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China
| | - Yu-Heng Lin
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China
| | - Zhuo-Xing Shi
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China
| | - Ying-Feng Zheng
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China
- Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China
- Research Unit of Ocular Development and Regeneration, Chinese Academy of Medical Sciences, China
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334
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Tan L, Shi J, Moghadami S, Wright CP, Parasar B, Seo Y, Vallejo K, Cobos I, Duncan L, Chen R, Deisseroth K. Cerebellar Granule Cells Develop Non-neuronal 3D Genome Architecture over the Lifespan. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.25.530020. [PMID: 36865235 PMCID: PMC9980173 DOI: 10.1101/2023.02.25.530020] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2023]
Abstract
The cerebellum contains most of the neurons in the human brain, and exhibits unique modes of development, malformation, and aging. For example, granule cells-the most abundant neuron type-develop unusually late and exhibit unique nuclear morphology. Here, by developing our high-resolution single-cell 3D genome assay Dip-C into population-scale (Pop-C) and virus-enriched (vDip-C) modes, we were able to resolve the first 3D genome structures of single cerebellar cells, create life-spanning 3D genome atlases for both human and mouse, and jointly measure transcriptome and chromatin accessibility during development. We found that while the transcriptome and chromatin accessibility of human granule cells exhibit a characteristic maturation pattern within the first year of postnatal life, 3D genome architecture gradually remodels throughout life into a non-neuronal state with ultra-long-range intra-chromosomal contacts and specific inter-chromosomal contacts. This 3D genome remodeling is conserved in mice, and robust to heterozygous deletion of chromatin remodeling disease-associated genes (Chd8 or Arid1b). Together these results reveal unexpected and evolutionarily-conserved molecular processes underlying the unique development and aging of the mammalian cerebellum.
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Affiliation(s)
- Longzhi Tan
- Department of Neurobiology, Stanford University, Stanford, CA
- Department of Bioengineering, Stanford University, Stanford, CA
| | - Jenny Shi
- Department of Neurobiology, Stanford University, Stanford, CA
- Department of Bioengineering, Stanford University, Stanford, CA
- Department of Chemistry, Stanford University, Stanford, CA
| | - Siavash Moghadami
- Department of Neurobiology, Stanford University, Stanford, CA
- Department of Chemical and Systems Biology, Stanford University, Stanford, CA
| | - Cydney P. Wright
- Department of Neurobiology, Stanford University, Stanford, CA
- Department of Biology, Stanford University, Stanford, CA
| | - Bibudha Parasar
- Department of Neurobiology, Stanford University, Stanford, CA
| | - Yunji Seo
- Department of Neurobiology, Stanford University, Stanford, CA
| | | | - Inma Cobos
- Department of Pathology, Stanford University, Stanford, CA
| | - Laramie Duncan
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA
| | - Ritchie Chen
- Department of Bioengineering, Stanford University, Stanford, CA
| | - Karl Deisseroth
- Department of Bioengineering, Stanford University, Stanford, CA
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA
- Howard Hughes Medical Institute, Stanford, CA
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335
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Ludwig LS, Lareau CA. Concomitant Sequencing of Accessible Chromatin and Mitochondrial Genomes in Single Cells Using mtscATAC-Seq. Methods Mol Biol 2023; 2611:269-282. [PMID: 36807073 DOI: 10.1007/978-1-0716-2899-7_14] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/23/2023]
Abstract
Mitochondria are unique organelles of eukaryotic cells that carry their own multicopy number and circular genome. In most mammals, including humans and mice, the size of the chromosome is ~16,000 base pairs and unlike nuclear DNA, mitochondrial DNA (mtDNA) is not densely compacted. This results in mtDNA to be highly accessible for enzymes such as the Tn5 transposase, commonly used for accessible chromatin profiling of nuclear chromatinized DNA. Here, we describe a method for the concomitant sequencing of mtDNA and accessible chromatin in thousands of individual cells via the mitochondrial single-cell assay for transposase accessible chromatin by sequencing (mtscATAC-seq). Our approach extends the utility of existing scATAC-seq products and protocols as we (Nam et al, Nat Rev Genet 22:3-18, 2021) fix cells using formaldehyde to retain mitochondria and its mtDNA within its originating cell, (Buenrostro et al, Nat Methods 10:1213-1218, 2013) modify lysis conditions to permeabilize cells and mitochondria, and (Corces et al, Nat Methods 14:959-962, 2017) optimize bioinformatic processing protocols to collectively increase mitochondrial genome coverage for downstream analysis. Here, we discuss the essentials for the experimental and computational methodologies to generate and analyze thousands of multiomic profiles of single cells over the course of a few days, enabling the profiling of accessible chromatin and mtDNA genotypes to reconstruct clonal relationships and studies of mitochondrial genetics and disease.
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Affiliation(s)
- Leif S Ludwig
- Berlin Institute of Health at Charité Universitätsmedizin Berlin, Berlin, Germany
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association, Berlin Institute for Medical Systems Biology, Berlin, Germany
| | - Caleb A Lareau
- Departments of Genetics and Pathology, Stanford University, Stanford, CA, USA.
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336
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Simultaneous Single-Cell Profiling of the Transcriptome and Accessible Chromatin Using SHARE-seq. Methods Mol Biol 2023; 2611:187-230. [PMID: 36807070 DOI: 10.1007/978-1-0716-2899-7_11] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/23/2023]
Abstract
The ability to analyze the transcriptomic and epigenomic states of individual single cells has in recent years transformed our ability to measure and understand biological processes. Recent advancements have focused on increasing sensitivity and throughput to provide richer and deeper biological insights at the cellular level. The next frontier is the development of multiomic methods capable of analyzing multiple features from the same cell, such as the simultaneous measurement of the transcriptome and the chromatin accessibility of candidate regulatory elements. In this chapter, we discuss and describe SHARE-seq (Simultaneous high-throughput ATAC, and RNA expression with sequencing) for carrying out simultaneous chromatin accessibility and transcriptome measurements in single cells, together with the experimental and analytical considerations for achieving optimal results.
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337
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Ma A, Wang X, Li J, Wang C, Xiao T, Liu Y, Cheng H, Wang J, Li Y, Chang Y, Li J, Wang D, Jiang Y, Su L, Xin G, Gu S, Li Z, Liu B, Xu D, Ma Q. Single-cell biological network inference using a heterogeneous graph transformer. Nat Commun 2023; 14:964. [PMID: 36810839 PMCID: PMC9944243 DOI: 10.1038/s41467-023-36559-0] [Citation(s) in RCA: 25] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2022] [Accepted: 02/06/2023] [Indexed: 02/23/2023] Open
Abstract
Single-cell multi-omics (scMulti-omics) allows the quantification of multiple modalities simultaneously to capture the intricacy of complex molecular mechanisms and cellular heterogeneity. Existing tools cannot effectively infer the active biological networks in diverse cell types and the response of these networks to external stimuli. Here we present DeepMAPS for biological network inference from scMulti-omics. It models scMulti-omics in a heterogeneous graph and learns relations among cells and genes within both local and global contexts in a robust manner using a multi-head graph transformer. Benchmarking results indicate DeepMAPS performs better than existing tools in cell clustering and biological network construction. It also showcases competitive capability in deriving cell-type-specific biological networks in lung tumor leukocyte CITE-seq data and matched diffuse small lymphocytic lymphoma scRNA-seq and scATAC-seq data. In addition, we deploy a DeepMAPS webserver equipped with multiple functionalities and visualizations to improve the usability and reproducibility of scMulti-omics data analysis.
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Affiliation(s)
- Anjun Ma
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, USA
- Pelotonia Institute for Immuno-Oncology, The James Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA
| | - Xiaoying Wang
- School of Mathematics, Shandong University, Jinan, Shandong, China
| | - Jingxian Li
- School of Mathematics, Shandong University, Jinan, Shandong, China
| | - Cankun Wang
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, USA
| | - Tong Xiao
- Pelotonia Institute for Immuno-Oncology, The James Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA
| | - Yuntao Liu
- School of Mathematics, Shandong University, Jinan, Shandong, China
| | - Hao Cheng
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, USA
| | - Juexin Wang
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA
- Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO, USA
| | - Yang Li
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, USA
| | - Yuzhou Chang
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, USA
- Pelotonia Institute for Immuno-Oncology, The James Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA
| | - Jinpu Li
- Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO, USA
- Institute for Data Science and Informatics, University of Missouri, Columbia, MO, USA
| | - Duolin Wang
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA
- Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO, USA
| | - Yuexu Jiang
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA
- Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO, USA
| | - Li Su
- Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO, USA
- Institute for Data Science and Informatics, University of Missouri, Columbia, MO, USA
| | - Gang Xin
- Pelotonia Institute for Immuno-Oncology, The James Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA
| | - Shaopeng Gu
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, USA
| | - Zihai Li
- Pelotonia Institute for Immuno-Oncology, The James Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA
| | - Bingqiang Liu
- School of Mathematics, Shandong University, Jinan, Shandong, China.
| | - Dong Xu
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA.
- Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO, USA.
- Institute for Data Science and Informatics, University of Missouri, Columbia, MO, USA.
| | - Qin Ma
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, USA.
- Pelotonia Institute for Immuno-Oncology, The James Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA.
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338
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Cooley A, Madhukaran S, Stroebele E, Colon Caraballo M, Wang L, Akgul Y, Hon GC, Mahendroo M. Dynamic states of cervical epithelia during pregnancy and epithelial barrier disruption. iScience 2023; 26:105953. [PMID: 36718364 PMCID: PMC9883190 DOI: 10.1016/j.isci.2023.105953] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 12/01/2022] [Accepted: 01/05/2023] [Indexed: 01/13/2023] Open
Abstract
The cervical epithelium undergoes changes in proliferation, differentiation, and function that are critical to ensure fertility and maintain pregnancy. Here, we identify cervical epithelial subtypes in non-pregnant, pregnant, and in labor mice using single-cell transcriptome and spatial analysis. We identify heterogeneous subpopulations of epithelia displaying spatial and temporal specificity. Notably in pregnancy, two goblet cell subtypes are present in the most luminal layers with one goblet population expanding earlier in pregnancy than the other goblet population. The goblet populations express novel protective factors and distinct mucosal networks. Single-cell analysis in a model of cervical epithelial barrier disruption indicates untimely basal cell proliferation precedes the expansion of goblet cells with diminished mucosal integrity. These data demonstrate how the cervical epithelium undergoes continuous remodeling to maintain dynamic states of homeostasis in pregnancy and labor, and provide a framework to understand perturbations in epithelial health that increase the risk of premature birth.
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Affiliation(s)
- Anne Cooley
- Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - ShanmugaPriyaa Madhukaran
- Department of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Elizabeth Stroebele
- Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Mariano Colon Caraballo
- Department of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Lei Wang
- Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Yucel Akgul
- Department of Plastic Surgery, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Gary C. Hon
- Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
- Department of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
- Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Mala Mahendroo
- Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
- Department of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
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339
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Riegel D, Romero-Fernández E, Simon M, Adenugba AR, Singer K, Mayr R, Weber F, Kleemann M, Imbusch CD, Kreutz M, Brors B, Ugele I, Werner JM, Siska PJ, Schmidl C. Integrated single-cell profiling dissects cell-state-specific enhancer landscapes of human tumor-infiltrating CD8 + T cells. Mol Cell 2023; 83:622-636.e10. [PMID: 36657444 DOI: 10.1016/j.molcel.2022.12.029] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Revised: 11/22/2022] [Accepted: 12/23/2022] [Indexed: 01/19/2023]
Abstract
Despite extensive studies on the chromatin landscape of exhausted T cells, the transcriptional wiring underlying the heterogeneous functional and dysfunctional states of human tumor-infiltrating lymphocytes (TILs) is incompletely understood. Here, we identify gene-regulatory landscapes in a wide breadth of functional and dysfunctional CD8+ TIL states covering four cancer entities using single-cell chromatin profiling. We map enhancer-promoter interactions in human TILs by integrating single-cell chromatin accessibility with single-cell RNA-seq data from tumor-entity-matching samples and prioritize cell-state-specific genes by super-enhancer analysis. Besides revealing entity-specific chromatin remodeling in exhausted TILs, our analyses identify a common chromatin trajectory to TIL dysfunction and determine key enhancers, transcriptional regulators, and deregulated genes involved in this process. Finally, we validate enhancer regulation at immunotherapeutically relevant loci by targeting non-coding regulatory elements with potent CRISPR activators and repressors. In summary, our study provides a framework for understanding and manipulating cell-state-specific gene-regulatory cues from human tumor-infiltrating lymphocytes.
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Affiliation(s)
- Dania Riegel
- Leibniz Institute for Immunotherapy (LIT), 93053 Regensburg, Germany
| | | | - Malte Simon
- Faculty of Biosciences, Heidelberg University, 69120 Heidelberg, Germany; Division of Applied Bioinformatics, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | | | - Katrin Singer
- Department of Internal Medicine III, University Hospital Regensburg, 93053 Regensburg, Germany; Department of Otorhinolaryngology, University Hospital Regensburg, 93053 Regensburg, Germany
| | - Roman Mayr
- Department of Urology, Caritas St. Josef Medical Centre, University of Regensburg, 93053 Regensburg, Germany
| | - Florian Weber
- Institute of Pathology, University of Regensburg, 93053 Regensburg, Germany
| | - Mark Kleemann
- Leibniz Institute for Immunotherapy (LIT), 93053 Regensburg, Germany
| | - Charles D Imbusch
- Division of Applied Bioinformatics, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Marina Kreutz
- Leibniz Institute for Immunotherapy (LIT), 93053 Regensburg, Germany; Department of Internal Medicine III, University Hospital Regensburg, 93053 Regensburg, Germany
| | - Benedikt Brors
- Division of Applied Bioinformatics, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany; National Center for Tumor Diseases (NCT), 69120 Heidelberg, Germany; German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Ines Ugele
- Department of Otorhinolaryngology, University Hospital Regensburg, 93053 Regensburg, Germany
| | - Jens M Werner
- Department of Surgery, University Hospital Regensburg, 93053 Regensburg, Germany
| | - Peter J Siska
- Department of Internal Medicine III, University Hospital Regensburg, 93053 Regensburg, Germany
| | - Christian Schmidl
- Leibniz Institute for Immunotherapy (LIT), 93053 Regensburg, Germany.
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340
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Lin C, Jyotaki M, Quinlan J, Feng S, Zhou M, Jiang P, Matsumoto I, Huang L, Ninomiya Y, Margolskee RF, Reed DR, Wang H. Inflammation induces bitter taste oversensitization via epigenetic changes in Tas2r gene clusters. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.08.527520. [PMID: 36798225 PMCID: PMC9934667 DOI: 10.1101/2023.02.08.527520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/12/2023]
Abstract
T2R bitter receptors, encoded by Tas2r genes, are not only critical for bitter taste signal transduction but also important for defense against bacteria and parasites. However, little is known about whether and how Tas2r gene expression are regulated. Here we show that, in an inflammation model mimicking bacterial infection, the expression of many Tas2rs are significantly up-regulated and mice displayed markedly increased neural and behavioral responses to bitter compounds. Using single-cell assays for transposase-accessible chromatin with sequencing (scATAC-seq), we found that the chromatin accessibility of Tas2rs was highly cell type specific and inflammation increased the accessibility of many Tas2rs . scATAC-seq also revealed substantial chromatin remodeling in immune response genes in taste tissue stem cells, suggesting potential long-term effects. Together, our results suggest an epigenetic mechanism connecting inflammation, Tas2r gene regulation, and altered bitter taste, which may explain heightened bitter taste that can occur with infections and cancer treatments.
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341
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Zhang B, Zhang Z, Koeken VA, Kumar S, Aillaud M, Tsay HC, Liu Z, Kraft AR, Soon CF, Odak I, Bošnjak B, Vlot A, Swertz MA, Ohler U, Geffers R, Illig T, Huehn J, Saliba AE, Sander LE, Förster R, Xu CJ, Cornberg M, Schulte LN, Li Y. Altered and allele-specific open chromatin landscape reveals epigenetic and genetic regulators of innate immunity in COVID-19. CELL GENOMICS 2023; 3:100232. [PMID: 36474914 PMCID: PMC9715265 DOI: 10.1016/j.xgen.2022.100232] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Revised: 10/21/2022] [Accepted: 11/17/2022] [Indexed: 12/05/2022]
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection causes severe COVID-19 in some patients and mild COVID-19 in others. Dysfunctional innate immune responses have been identified to contribute to COVID-19 severity, but the key regulators are still unknown. Here, we present an integrative single-cell multi-omics analysis of peripheral blood mononuclear cells from hospitalized and convalescent COVID-19 patients. In classical monocytes, we identified genes that were potentially regulated by differential chromatin accessibility. Then, sub-clustering and motif-enrichment analyses revealed disease condition-specific regulation by transcription factors and their targets, including an interaction between C/EBPs and a long-noncoding RNA LUCAT1, which we validated through loss-of-function experiments. Finally, we investigated genetic risk variants that exhibit allele-specific open chromatin (ASoC) in COVID-19 patients and identified a SNP rs6800484-C, which is associated with lower expression of CCR2 and may contribute to higher viral loads and higher risk of COVID-19 hospitalization. Altogether, our study highlights the diverse genetic and epigenetic regulators that contribute to COVID-19.
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Affiliation(s)
- Bowen Zhang
- Department of Computational Biology for Individualised Infection Medicine, Centre for Individualised Infection Medicine (CiiM), a joint venture between the Helmholtz-Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany
- TWINCORE, a joint venture between the Helmholtz-Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany
- Beijing Normal University, College of Life Sciences, Beijing, China
| | - Zhenhua Zhang
- Department of Computational Biology for Individualised Infection Medicine, Centre for Individualised Infection Medicine (CiiM), a joint venture between the Helmholtz-Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany
- TWINCORE, a joint venture between the Helmholtz-Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany
- Genomics Coordination Center, University of Groningen and University Medical Center Groningen, Groningen, the Netherlands
- Department of Genetics, University of Groningen and University Medical Center Groningen, Groningen, the Netherlands
| | - Valerie A.C.M. Koeken
- Department of Computational Biology for Individualised Infection Medicine, Centre for Individualised Infection Medicine (CiiM), a joint venture between the Helmholtz-Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany
- TWINCORE, a joint venture between the Helmholtz-Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany
- Department of Internal Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Medical Center, Nijmegen, the Netherlands
| | - Saumya Kumar
- Department of Computational Biology for Individualised Infection Medicine, Centre for Individualised Infection Medicine (CiiM), a joint venture between the Helmholtz-Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany
- TWINCORE, a joint venture between the Helmholtz-Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany
| | - Michelle Aillaud
- Institute for Lung Research, Philipps University, Marburg, Germany
| | - Hsin-Chieh Tsay
- Department of Computational Biology for Individualised Infection Medicine, Centre for Individualised Infection Medicine (CiiM), a joint venture between the Helmholtz-Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany
- TWINCORE, a joint venture between the Helmholtz-Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany
| | - Zhaoli Liu
- Department of Computational Biology for Individualised Infection Medicine, Centre for Individualised Infection Medicine (CiiM), a joint venture between the Helmholtz-Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany
- TWINCORE, a joint venture between the Helmholtz-Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany
| | - Anke R.M. Kraft
- Department of Computational Biology for Individualised Infection Medicine, Centre for Individualised Infection Medicine (CiiM), a joint venture between the Helmholtz-Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany
- TWINCORE, a joint venture between the Helmholtz-Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany
- Department of Gastroenterology, Hepatology and Endocrinology, Hannover Medical School, Hannover, Germany
- German Centre for Infection Research (Deutsches Zentrum für Infektionsforschung [DZIF]), Partner Site Hannover-Braunschweig, Hannover, Germany
- Cluster of Excellence Resolving Infection Susceptibility (RESIST; EXC 2155), Hannover Medical School, Hannover, Germany
| | - Chai Fen Soon
- TWINCORE, a joint venture between the Helmholtz-Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany
- Department of Gastroenterology, Hepatology and Endocrinology, Hannover Medical School, Hannover, Germany
| | - Ivan Odak
- Institute of Immunology, Hannover Medical School, Hannover, Germany
| | - Berislav Bošnjak
- Institute of Immunology, Hannover Medical School, Hannover, Germany
| | - Anna Vlot
- Berlin Institute for Medical Systems Biology (BIMSB), Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
| | - Deutsche COVID-19 OMICS Initiative (DeCOI)
- Department of Computational Biology for Individualised Infection Medicine, Centre for Individualised Infection Medicine (CiiM), a joint venture between the Helmholtz-Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany
- TWINCORE, a joint venture between the Helmholtz-Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany
- Beijing Normal University, College of Life Sciences, Beijing, China
- Genomics Coordination Center, University of Groningen and University Medical Center Groningen, Groningen, the Netherlands
- Department of Genetics, University of Groningen and University Medical Center Groningen, Groningen, the Netherlands
- Department of Internal Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Medical Center, Nijmegen, the Netherlands
- Institute for Lung Research, Philipps University, Marburg, Germany
- Department of Gastroenterology, Hepatology and Endocrinology, Hannover Medical School, Hannover, Germany
- German Centre for Infection Research (Deutsches Zentrum für Infektionsforschung [DZIF]), Partner Site Hannover-Braunschweig, Hannover, Germany
- Cluster of Excellence Resolving Infection Susceptibility (RESIST; EXC 2155), Hannover Medical School, Hannover, Germany
- Institute of Immunology, Hannover Medical School, Hannover, Germany
- Berlin Institute for Medical Systems Biology (BIMSB), Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
- Genome Analytics, Helmholtz-Center for Infection Research (HZI), Braunschweig, Germany
- German Center for Lung Research (DZL), Giessen, Germany
- Hannover Unified Biobank, Hannover Medical School, Hannover, Germany
- Department of Experimental Immunology, Helmholtz Centre for Infection Research, Braunschweig, Germany
- Helmholtz Institute for RNA-based Infection Research (HIRI), Helmholtz-Centre for Infection Research (HZI), Wurzburg, Germany
- Charité–Universitätsmedizin Berlin, Department of Infectious Diseases and Respiratory Medicine, Charité, Universitätsmedizin Berlin, Berlin, Germany
| | - Morris A. Swertz
- Genomics Coordination Center, University of Groningen and University Medical Center Groningen, Groningen, the Netherlands
- Department of Genetics, University of Groningen and University Medical Center Groningen, Groningen, the Netherlands
| | - Uwe Ohler
- Berlin Institute for Medical Systems Biology (BIMSB), Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
| | - Robert Geffers
- Genome Analytics, Helmholtz-Center for Infection Research (HZI), Braunschweig, Germany
| | - Thomas Illig
- German Center for Lung Research (DZL), Giessen, Germany
- Hannover Unified Biobank, Hannover Medical School, Hannover, Germany
| | - Jochen Huehn
- Cluster of Excellence Resolving Infection Susceptibility (RESIST; EXC 2155), Hannover Medical School, Hannover, Germany
- Department of Experimental Immunology, Helmholtz Centre for Infection Research, Braunschweig, Germany
| | - Antoine-Emmanuel Saliba
- Helmholtz Institute for RNA-based Infection Research (HIRI), Helmholtz-Centre for Infection Research (HZI), Wurzburg, Germany
| | - Leif Erik Sander
- German Center for Lung Research (DZL), Giessen, Germany
- Charité–Universitätsmedizin Berlin, Department of Infectious Diseases and Respiratory Medicine, Charité, Universitätsmedizin Berlin, Berlin, Germany
| | - Reinhold Förster
- German Centre for Infection Research (Deutsches Zentrum für Infektionsforschung [DZIF]), Partner Site Hannover-Braunschweig, Hannover, Germany
- Cluster of Excellence Resolving Infection Susceptibility (RESIST; EXC 2155), Hannover Medical School, Hannover, Germany
- Institute of Immunology, Hannover Medical School, Hannover, Germany
| | - Cheng-Jian Xu
- Department of Computational Biology for Individualised Infection Medicine, Centre for Individualised Infection Medicine (CiiM), a joint venture between the Helmholtz-Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany
- TWINCORE, a joint venture between the Helmholtz-Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany
- Department of Internal Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Medical Center, Nijmegen, the Netherlands
- Department of Gastroenterology, Hepatology and Endocrinology, Hannover Medical School, Hannover, Germany
| | - Markus Cornberg
- Department of Computational Biology for Individualised Infection Medicine, Centre for Individualised Infection Medicine (CiiM), a joint venture between the Helmholtz-Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany
- TWINCORE, a joint venture between the Helmholtz-Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany
- Department of Gastroenterology, Hepatology and Endocrinology, Hannover Medical School, Hannover, Germany
- German Centre for Infection Research (Deutsches Zentrum für Infektionsforschung [DZIF]), Partner Site Hannover-Braunschweig, Hannover, Germany
- Cluster of Excellence Resolving Infection Susceptibility (RESIST; EXC 2155), Hannover Medical School, Hannover, Germany
| | - Leon N. Schulte
- Institute for Lung Research, Philipps University, Marburg, Germany
- German Center for Lung Research (DZL), Giessen, Germany
| | - Yang Li
- Department of Computational Biology for Individualised Infection Medicine, Centre for Individualised Infection Medicine (CiiM), a joint venture between the Helmholtz-Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany
- TWINCORE, a joint venture between the Helmholtz-Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany
- Department of Internal Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Medical Center, Nijmegen, the Netherlands
- Cluster of Excellence Resolving Infection Susceptibility (RESIST; EXC 2155), Hannover Medical School, Hannover, Germany
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342
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Manouchehri N, Salinas VH, Hussain RZ, Stüve O. Distinctive transcriptomic and epigenomic signatures of bone marrow-derived myeloid cells and microglia in CNS autoimmunity. Proc Natl Acad Sci U S A 2023; 120:e2212696120. [PMID: 36730207 PMCID: PMC9963604 DOI: 10.1073/pnas.2212696120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2022] [Accepted: 12/22/2022] [Indexed: 02/03/2023] Open
Abstract
In the context of autoimmunity, myeloid cells of the central nervous system (CNS) constitute an ontogenically heterogeneous population that includes yolk sac-derived microglia and infiltrating bone marrow-derived cells (BMC). We previously identified a myeloid cell subset in the brain and spinal cord that expresses the surface markers CD88 and CD317 and is associated with the onset and persistence of clinical disease in the murine model of the human CNS autoimmune disorder, experimental autoimmune encephalomyelitis (EAE). We employed an experimental platform utilizing single-cell transcriptomic and epigenomic profiling of bone marrow-chimeric mice to categorically distinguish BMC from microglia during CNS autoimmunity. Analysis of gene expression and chromosomal accessibility identified CD88+CD317+ myeloid cells in the CNS of EAE mice as originating from BMC and microglia. Interestingly, each cell lineage exhibited overlapping and unique gene expression patterns and transcription factor motifs that allowed their segregation. Our observations will facilitate determining pathogenic contributions of BMC and microglia in CNS autoimmune disease. Ultimately, this agnostic characterization of myeloid cells will be required for devising disease stage-specific and tissue-specific interventions for CNS inflammatory and neurodegenerative disorders.
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Affiliation(s)
- Navid Manouchehri
- Department of Neurology, University of Texas Southwestern Medical Center, Dallas, TX75390
| | - Victor H. Salinas
- Department of Neurology, University of Texas Southwestern Medical Center, Dallas, TX75390
- Neurology Section, Veterans Affairs North Texas Health Care System, Dallas, TX75216
| | - Rehana Z. Hussain
- Department of Neurology, University of Texas Southwestern Medical Center, Dallas, TX75390
| | - Olaf Stüve
- Department of Neurology, University of Texas Southwestern Medical Center, Dallas, TX75390
- Neurology Section, Veterans Affairs North Texas Health Care System, Dallas, TX75216
- Peter O’Donnell Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX75390
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343
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Yang BA, Larouche JA, Sabin KM, Fraczek PM, Parker SCJ, Aguilar CA. Three-dimensional chromatin re-organization during muscle stem cell aging. Aging Cell 2023; 22:e13789. [PMID: 36727578 PMCID: PMC10086523 DOI: 10.1111/acel.13789] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 12/29/2022] [Accepted: 01/11/2023] [Indexed: 02/03/2023] Open
Abstract
Age-related skeletal muscle atrophy or sarcopenia is a significant societal problem that is becoming amplified as the world's population continues to increase. The regeneration of damaged skeletal muscle is mediated by muscle stem cells, but in old age muscle stem cells become functionally attenuated. The molecular mechanisms that govern muscle stem cell aging encompass changes across multiple regulatory layers and are integrated by the three-dimensional organization of the genome. To quantitatively understand how hierarchical chromatin architecture changes during muscle stem cell aging, we generated 3D chromatin conformation maps (Hi-C) and integrated these datasets with multi-omic (chromatin accessibility and transcriptome) profiles from bulk populations and single cells. We observed that muscle stem cells display static behavior at global scales of chromatin organization during aging and extensive rewiring of local contacts at finer scales that were associated with variations in transcription factor binding and aberrant gene expression. These data provide insights into genome topology as a regulator of molecular function in stem cell aging.
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Affiliation(s)
- Benjamin A Yang
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA.,Biointerfaces Institute, University of Michigan, Ann Arbor, Michigan, USA
| | - Jacqueline A Larouche
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA.,Biointerfaces Institute, University of Michigan, Ann Arbor, Michigan, USA
| | - Kaitlyn M Sabin
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA.,Biointerfaces Institute, University of Michigan, Ann Arbor, Michigan, USA
| | - Paula M Fraczek
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA.,Biointerfaces Institute, University of Michigan, Ann Arbor, Michigan, USA
| | - Stephen C J Parker
- Program in Cellular and Molecular Biology, University of Michigan, Ann Arbor, Michigan, USA.,Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA.,Department of Human Genetics, University of Michigan, Ann Arbor, Michigan, USA
| | - Carlos A Aguilar
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA.,Biointerfaces Institute, University of Michigan, Ann Arbor, Michigan, USA.,Program in Cellular and Molecular Biology, University of Michigan, Ann Arbor, Michigan, USA
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344
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O'Connell BL, Nichols RV, Pokholok D, Thomas J, Acharya SN, Nishida A, Thornton CA, Co M, Fields AJ, Steemers FJ, Adey AC. Atlas-scale single-cell chromatin accessibility using nanowell-based combinatorial indexing. Genome Res 2023; 33:208-217. [PMID: 36792372 PMCID: PMC10069466 DOI: 10.1101/gr.276655.122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 12/08/2022] [Indexed: 02/17/2023]
Abstract
Here we present advancements in single-cell combinatorial indexed Assay for Transposase Accessible Chromatin (sciATAC) to measure chromatin accessibility that leverage nanowell chips to achieve atlas-scale cell throughput (>105 cells) at low cost. The platform leverages the core of the sciATAC workflow where multiple indexed tagmentation reactions are performed, followed by pooling and distribution to a second set of reaction wells for polymerase chain reaction (PCR)-based indexing. In this work, we instead leverage a chip containing 5184 nanowells at the PCR stage of indexing, enabling a 52-fold improvement in scale and reduction in per-cell preparation costs. We detail three variants that balance cell throughput and depth of coverage, and apply these methods to banked mouse brain tissue, producing maps of cell types as well as neuronal subtypes that include integration with existing single-cell Assay for Transposase Accessible Chromatin (scATAC) and scRNA-seq data sets. Our optimized workflow achieves a high fraction of reads that fall within called peaks (>80%) and low cell doublet rates. The high cell coverage technique produces high unique reads per cell, while retaining high enrichment for open chromatin regions, enabling the assessment of >70,000 unique accessible loci on average for each cell profiled. When compared to current methods in the field, our technique provides similar or superior per-cell information with very low levels of cell-to-cell cross talk, and achieves this at a cost point much lower than existing assays.
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Affiliation(s)
- Brendan L O'Connell
- Oregon Health & Science University, Department of Molecular and Medical Genetics, Portland, Oregon 97239, USA
| | - Ruth V Nichols
- Oregon Health & Science University, Department of Molecular and Medical Genetics, Portland, Oregon 97239, USA
| | | | | | - Sonia N Acharya
- Oregon Health & Science University, Department of Molecular and Medical Genetics, Portland, Oregon 97239, USA
| | - Andrew Nishida
- Oregon Health & Science University, Department of Molecular and Medical Genetics, Portland, Oregon 97239, USA
| | - Casey A Thornton
- Oregon Health & Science University, Department of Molecular and Medical Genetics, Portland, Oregon 97239, USA
| | - Marissa Co
- Oregon Health & Science University, Department of Molecular and Medical Genetics, Portland, Oregon 97239, USA
| | - Andrew J Fields
- Oregon Health & Science University, Department of Molecular and Medical Genetics, Portland, Oregon 97239, USA
| | | | - Andrew C Adey
- Oregon Health & Science University, Department of Molecular and Medical Genetics, Portland, Oregon 97239, USA; .,Oregon Health & Science University, Knight Cancer Institute, Portland, Oregon 97239, USA.,Oregon Health & Science University, Cancer Early Detection Advanced Research Center, Portland, Oregon 97239, USA.,Oregon Health & Science University, Knight Cardiovascular Institute, Portland, Oregon 97239, USA
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345
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Iqbal W, Zhou W. Computational Methods for Single-cell DNA Methylome Analysis. GENOMICS, PROTEOMICS & BIOINFORMATICS 2023; 21:48-66. [PMID: 35718270 PMCID: PMC10372927 DOI: 10.1016/j.gpb.2022.05.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Revised: 04/28/2022] [Accepted: 05/10/2022] [Indexed: 11/19/2022]
Abstract
Dissecting intercellular epigenetic differences is key to understanding tissue heterogeneity. Recent advances in single-cell DNA methylome profiling have presented opportunities to resolve this heterogeneity at the maximum resolution. While these advances enable us to explore frontiers of chromatin biology and better understand cell lineage relationships, they pose new challenges in data processing and interpretation. This review surveys the current state of computational tools developed for single-cell DNA methylome data analysis. We discuss critical components of single-cell DNA methylome data analysis, including data preprocessing, quality control, imputation, dimensionality reduction, cell clustering, supervised cell annotation, cell lineage reconstruction, gene activity scoring, and integration with transcriptome data. We also highlight unique aspects of single-cell DNA methylome data analysis and discuss how techniques common to other single-cell omics data analyses can be adapted to analyze DNA methylomes. Finally, we discuss existing challenges and opportunities for future development.
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Affiliation(s)
- Waleed Iqbal
- Center for Computational and Genomic Medicine, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Wanding Zhou
- Center for Computational and Genomic Medicine, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
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346
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Wu VH, Nordin JML, Nguyen S, Joy J, Mampe F, Del Rio Estrada PM, Torres-Ruiz F, González-Navarro M, Luna-Villalobos YA, Ávila-Ríos S, Reyes-Terán G, Tebas P, Montaner LJ, Bar KJ, Vella LA, Betts MR. Profound phenotypic and epigenetic heterogeneity of the HIV-1-infected CD4 + T cell reservoir. Nat Immunol 2023; 24:359-370. [PMID: 36536105 PMCID: PMC9892009 DOI: 10.1038/s41590-022-01371-3] [Citation(s) in RCA: 29] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Accepted: 10/24/2022] [Indexed: 12/24/2022]
Abstract
Understanding the complexity of the long-lived HIV reservoir during antiretroviral therapy (ART) remains a considerable impediment in research towards a cure for HIV. To address this, we developed a single-cell strategy to precisely define the unperturbed peripheral blood HIV-infected memory CD4+ T cell reservoir from ART-treated people living with HIV (ART-PLWH) via the presence of integrated accessible proviral DNA in concert with epigenetic and cell surface protein profiling. We identified profound reservoir heterogeneity within and between ART-PLWH, characterized by new and known surface markers within total and individual memory CD4+ T cell subsets. We further uncovered new epigenetic profiles and transcription factor motifs enriched in HIV-infected cells that suggest infected cells with accessible provirus, irrespective of reservoir distribution, are poised for reactivation during ART treatment. Together, our findings reveal the extensive inter- and intrapersonal cellular heterogeneity of the HIV reservoir, and establish an initial multiomic atlas to develop targeted reservoir elimination strategies.
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Affiliation(s)
- Vincent H Wu
- Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for AIDS Research, University of Pennsylvania, Philadelphia, PA, USA
| | - Jayme M L Nordin
- Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for AIDS Research, University of Pennsylvania, Philadelphia, PA, USA
| | - Son Nguyen
- Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Institute for Medical Engineering and Science, Department of Chemistry, and Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Jaimy Joy
- Center for AIDS Research, University of Pennsylvania, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Felicity Mampe
- Center for AIDS Research, University of Pennsylvania, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Perla M Del Rio Estrada
- Centro de Investigación en Enfermedades Infecciosas, Instituto Nacional de Enfermedades Respiratorias, Mexico City, Mexico
| | - Fernanda Torres-Ruiz
- Centro de Investigación en Enfermedades Infecciosas, Instituto Nacional de Enfermedades Respiratorias, Mexico City, Mexico
| | - Mauricio González-Navarro
- Centro de Investigación en Enfermedades Infecciosas, Instituto Nacional de Enfermedades Respiratorias, Mexico City, Mexico
| | - Yara Andrea Luna-Villalobos
- Centro de Investigación en Enfermedades Infecciosas, Instituto Nacional de Enfermedades Respiratorias, Mexico City, Mexico
| | - Santiago Ávila-Ríos
- Centro de Investigación en Enfermedades Infecciosas, Instituto Nacional de Enfermedades Respiratorias, Mexico City, Mexico
| | - Gustavo Reyes-Terán
- Institutos Nacionales de Salud y Hospitales de Alta Especialidad, Secretaría de Salud de México, Mexico City, Mexico
| | - Pablo Tebas
- Center for AIDS Research, University of Pennsylvania, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Luis J Montaner
- Center for AIDS Research, University of Pennsylvania, Philadelphia, PA, USA
- The Wistar Institute, Philadelphia, PA, USA
| | - Katharine J Bar
- Center for AIDS Research, University of Pennsylvania, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Laura A Vella
- Center for AIDS Research, University of Pennsylvania, Philadelphia, PA, USA.
- Division of Infectious Diseases, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
| | - Michael R Betts
- Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Center for AIDS Research, University of Pennsylvania, Philadelphia, PA, USA.
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347
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Wimmers F, Burrell AR, Feng Y, Zheng H, Arunachalam PS, Hu M, Spranger S, Nyhoff L, Joshi D, Trisal M, Awasthi M, Bellusci L, Ashraf U, Kowli S, Konvinse KC, Yang E, Blanco M, Pellegrini K, Tharp G, Hagan T, Chinthrajah RS, Grifoni A, Sette A, Nadeau KC, Haslam DB, Bosinger SE, Wrammert J, Maecker HT, Utz PJ, Wang TT, Khurana S, Khatri P, Staat MA, Pulendran B. Systems biological assessment of the temporal dynamics of immunity to a viral infection in the first weeks and months of life. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.01.28.23285133. [PMID: 36778389 PMCID: PMC9915811 DOI: 10.1101/2023.01.28.23285133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
The dynamics of innate and adaptive immunity to infection in infants remain obscure. Here, we used a multi-omics approach to perform a longitudinal analysis of immunity to SARS-CoV-2 infection in infants and young children in the first weeks and months of life by analyzing blood samples collected before, during, and after infection with Omicron and Non-Omicron variants. Infection stimulated robust antibody titers that, unlike in adults, were stably maintained for >300 days. Antigen-specific memory B cell (MCB) responses were durable for 150 days but waned thereafter. Somatic hypermutation of V-genes in MCB accumulated progressively over 9 months. The innate response was characterized by upregulation of activation markers on blood innate cells, and a plasma cytokine profile distinct from that seen in adults, with no inflammatory cytokines, but an early and transient accumulation of chemokines (CXCL10, IL8, IL-18R1, CSF-1, CX3CL1), and type I IFN. The latter was strongly correlated with viral load, and expression of interferon-stimulated genes (ISGs) in myeloid cells measured by single-cell transcriptomics. Consistent with this, single-cell ATAC-seq revealed enhanced accessibility of chromatic loci targeted by interferon regulatory factors (IRFs) and reduced accessibility of AP-1 targeted loci, as well as traces of epigenetic imprinting in monocytes, during convalescence. Together, these data provide the first snapshot of immunity to infection during the initial weeks and months of life.
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Affiliation(s)
- Florian Wimmers
- Institute for Immunity, Transplantation and Infection, Stanford University, Stanford, CA, USA
- Department of Molecular Medicine, Interfaculty Institute for Biochemistry, University of Tuebingen, Tuebingen, Germany
- DFG Cluster of Excellence 2180 ‘Image-guided and Functional Instructed Tumor Therapy’ (iFIT), University of Tuebingen, Tuebingen, Germany
- German Consortium for Translational Cancer Research (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Allison R. Burrell
- Department of Infectious Diseases, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA
- Department of Environmental and Public Health Sciences, Division of Epidemiology, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Yupeng Feng
- Institute for Immunity, Transplantation and Infection, Stanford University, Stanford, CA, USA
| | - Hong Zheng
- Institute for Immunity, Transplantation and Infection, Stanford University, Stanford, CA, USA
- Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, CA, 94305, USA
| | - Prabhu S. Arunachalam
- Institute for Immunity, Transplantation and Infection, Stanford University, Stanford, CA, USA
| | - Mengyun Hu
- Institute for Immunity, Transplantation and Infection, Stanford University, Stanford, CA, USA
| | - Sara Spranger
- Department of Infectious Diseases, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA
| | - Lindsay Nyhoff
- Department of Pediatrics, Division of Infectious Disease, Emory University School of Medicine
| | - Devyani Joshi
- Department of Pediatrics, Division of Infectious Disease, Emory University School of Medicine
| | - Meera Trisal
- Institute for Immunity, Transplantation and Infection, Stanford University, Stanford, CA, USA
| | - Mayanka Awasthi
- Division of Viral Products, Center for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland, 20993, USA
| | - Lorenza Bellusci
- Division of Viral Products, Center for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland, 20993, USA
| | - Usama Ashraf
- Institute for Immunity, Transplantation and Infection, Stanford University, Stanford, CA, USA
- Department of Medicine, Division of Infectious Diseases, Stanford University, Stanford, CA 94305, USA
| | - Sangeeta Kowli
- Institute for Immunity, Transplantation and Infection, Stanford University, Stanford, CA, USA
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford University, Stanford, CA, USA
| | - Katherine C. Konvinse
- Department of Pediatrics, Stanford University School of Medicine, Stanford University, Stanford, CA, USA
| | - Emily Yang
- Institute for Immunity, Transplantation and Infection, Stanford University, Stanford, CA, USA
- Department of Medicine, Division of Immunology and Rheumatology, Stanford University School of Medicine, Stanford, CA, USA
| | - Michael Blanco
- Stanford Genomics Service Center, Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | | | - Gregory Tharp
- Yerkes National Primate Research Center, Atlanta, GA, USA
| | - Thomas Hagan
- Department of Infectious Diseases, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - R. Sharon Chinthrajah
- Department of Medicine, Sean N. Parker Center for Allergy and Asthma Research, Stanford, CA 94305, USA
| | - Alba Grifoni
- Center for Infectious Disease and Vaccine Research, La Jolla Institute for Immunology (LJI), La Jolla, CA 92037, USA
| | - Alessandro Sette
- Center for Infectious Disease and Vaccine Research, La Jolla Institute for Immunology (LJI), La Jolla, CA 92037, USA
- Department of Medicine, Division of Infectious Diseases and Global Public Health, University of California, San Diego, La Jolla, CA 92037, USA
| | - Kari C. Nadeau
- Department of Medicine, Sean N. Parker Center for Allergy and Asthma Research, Stanford, CA 94305, USA
| | - David B. Haslam
- Department of Infectious Diseases, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Steven E. Bosinger
- Yerkes National Primate Research Center, Atlanta, GA, USA
- Department of Pathology, Emory University School of Medicine, Atlanta, GA, USA
| | - Jens Wrammert
- Department of Pediatrics, Division of Infectious Disease, Emory University School of Medicine
| | - Holden T. Maecker
- Institute for Immunity, Transplantation and Infection, Stanford University, Stanford, CA, USA
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford University, Stanford, CA, USA
| | - Paul J. Utz
- Institute for Immunity, Transplantation and Infection, Stanford University, Stanford, CA, USA
- Department of Medicine, Division of Immunology and Rheumatology, Stanford University School of Medicine, Stanford, CA, USA
| | - Taia T. Wang
- Institute for Immunity, Transplantation and Infection, Stanford University, Stanford, CA, USA
- Department of Medicine, Division of Infectious Diseases, Stanford University, Stanford, CA 94305, USA
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford University, Stanford, CA, USA
| | - Surender Khurana
- Division of Viral Products, Center for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland, 20993, USA
| | - Purvesh Khatri
- Institute for Immunity, Transplantation and Infection, Stanford University, Stanford, CA, USA
- Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, CA, 94305, USA
| | - Mary A. Staat
- Department of Infectious Diseases, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Bali Pulendran
- Institute for Immunity, Transplantation and Infection, Stanford University, Stanford, CA, USA
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford University, Stanford, CA, USA
- Department of Pathology, Stanford University School of Medicine, Stanford University, Stanford, CA, USA
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348
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Hölscher DL, Bouteldja N, Joodaki M, Russo ML, Lan YC, Sadr AV, Cheng M, Tesar V, Stillfried SV, Klinkhammer BM, Barratt J, Floege J, Roberts ISD, Coppo R, Costa IG, Bülow RD, Boor P. Next-Generation Morphometry for pathomics-data mining in histopathology. Nat Commun 2023; 14:470. [PMID: 36709324 PMCID: PMC9884209 DOI: 10.1038/s41467-023-36173-0] [Citation(s) in RCA: 36] [Impact Index Per Article: 36.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Accepted: 01/16/2023] [Indexed: 01/29/2023] Open
Abstract
Pathology diagnostics relies on the assessment of morphology by trained experts, which remains subjective and qualitative. Here we developed a framework for large-scale histomorphometry (FLASH) performing deep learning-based semantic segmentation and subsequent large-scale extraction of interpretable, quantitative, morphometric features in non-tumour kidney histology. We use two internal and three external, multi-centre cohorts to analyse over 1000 kidney biopsies and nephrectomies. By associating morphometric features with clinical parameters, we confirm previous concepts and reveal unexpected relations. We show that the extracted features are independent predictors of long-term clinical outcomes in IgA-nephropathy. We introduce single-structure morphometric analysis by applying techniques from single-cell transcriptomics, identifying distinct glomerular populations and morphometric phenotypes along a trajectory of disease progression. Our study provides a concept for Next-generation Morphometry (NGM), enabling comprehensive quantitative pathology data mining, i.e., pathomics.
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Affiliation(s)
- David L Hölscher
- Institute of Pathology, RWTH Aachen University Clinic, Aachen, Germany
| | - Nassim Bouteldja
- Institute of Pathology, RWTH Aachen University Clinic, Aachen, Germany
| | - Mehdi Joodaki
- Institute for Computational Genomics, RWTH Aachen University Clinic, Aachen, Germany
| | | | - Yu-Chia Lan
- Institute of Pathology, RWTH Aachen University Clinic, Aachen, Germany
| | | | - Mingbo Cheng
- Institute for Computational Genomics, RWTH Aachen University Clinic, Aachen, Germany
| | - Vladimir Tesar
- Department of Nephrology, 1st Faculty of Medicine and General University Hospital, Charles University, Prague, Czech Republic
| | | | | | - Jonathan Barratt
- John Walls Renal Unit, University Hospital of Leicester National Health Service Trust, Leicester, United Kingdom
- Department of Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom
| | - Jürgen Floege
- Department of Nephrology and Immunology, RWTH Aachen University Clinic, Aachen, Germany
| | - Ian S D Roberts
- Department of Cellular Pathology, Oxford University Hospitals National Health Services Foundation Trust, Oxford, United Kingdom
| | - Rosanna Coppo
- Fondazione Ricerca Molinette, Torino, Italy
- Regina Margherita Children's University Hospital, Torino, Italy
| | - Ivan G Costa
- Institute for Computational Genomics, RWTH Aachen University Clinic, Aachen, Germany
| | - Roman D Bülow
- Institute of Pathology, RWTH Aachen University Clinic, Aachen, Germany
| | - Peter Boor
- Institute of Pathology, RWTH Aachen University Clinic, Aachen, Germany.
- Department of Nephrology and Immunology, RWTH Aachen University Clinic, Aachen, Germany.
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349
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Liu C, Wang L, Liu Z. scGREAT: Graph-based regulatory element analysis tool for single-cell multi-omics data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.27.525916. [PMID: 36747664 PMCID: PMC9900895 DOI: 10.1101/2023.01.27.525916] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
Motivation With the development in single-cell multi-omics sequencing technology and data integration algorithms, we have entered the single-cell multi-omics era. Current multi-omics analysis algorithms failed to systematically dissect the heterogeneity within the datasets when inferring cis-regulatory events. Thus, there is a need for cis-regulatory element inferring algorithms that considers the cellular heterogeneity. Results Here, we propose scGREAT, a single-cell multi-omics regulatory state analysis Python package with a rapid graph-based correlation measurement L. The graph-based correlation method assigns each cell a local L index, pinpointing specific cell groups of certain regulatory states. Such single-cell resolved regulatory state information enables the heterogeneity analysis equipped in the package. Applying scGREAT to the 10X Multiome PBMC dataset, we demonstrated how it could help subcluster cell types, infer regulation-based pseudo-time trajectory, discover feature modules, and find cluster-specific regulatory gene-peak pairs. Besides, we showed that global L index, which is the average of all local L values, is a better replacement for Pearson's r in ruling out confounding regulatory relationships that are not of research interests. Availability https://github.com/ChaozhongLiu/scGREAT.
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Affiliation(s)
- Chaozhong Liu
- Graduate Program in Quantitative and Computational Biosciences, Baylor College of Medicine, Houston, USA
| | - Linhua Wang
- Graduate Program in Quantitative and Computational Biosciences, Baylor College of Medicine, Houston, USA
| | - Zhandong Liu
- Jan and Dan Duncan Neurological Research Institute at Texas Children’s Hospital, Houston, USA
- Department of Pediatrics, Baylor College of Medicine, Houston, USA
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350
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Ediriwickrema A, Gentles AJ, Majeti R. Single-cell genomics in AML: extending the frontiers of AML research. Blood 2023; 141:345-355. [PMID: 35926108 PMCID: PMC10082362 DOI: 10.1182/blood.2021014670] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Revised: 07/06/2022] [Accepted: 07/23/2022] [Indexed: 01/31/2023] Open
Abstract
The era of genomic medicine has allowed acute myeloid leukemia (AML) researchers to improve disease characterization, optimize risk-stratification systems, and develop new treatments. Although there has been significant progress, AML remains a lethal cancer because of its remarkably complex and plastic cellular architecture. This degree of heterogeneity continues to pose a major challenge, because it limits the ability to identify and therefore eradicate the cells responsible for leukemogenesis and treatment failure. In recent years, the field of single-cell genomics has led to unprecedented strides in the ability to characterize cellular heterogeneity, and it holds promise for the study of AML. In this review, we highlight advancements in single-cell technologies, outline important shortcomings in our understanding of AML biology and clinical management, and discuss how single-cell genomics can address these shortcomings as well as provide unique opportunities in basic and translational AML research.
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Affiliation(s)
- Asiri Ediriwickrema
- Division of Hematology, Department of Medicine, Stanford University School of Medicine, Stanford, CA
- Cancer Institute, Stanford University School of Medicine, Stanford, CA
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA
| | - Andrew J. Gentles
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA
| | - Ravindra Majeti
- Division of Hematology, Department of Medicine, Stanford University School of Medicine, Stanford, CA
- Cancer Institute, Stanford University School of Medicine, Stanford, CA
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA
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