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Mack KL, Talbott HE, Griffin MF, Parker JBL, Guardino NJ, Spielman AF, Davitt MF, Mascharak S, Downer M, Morgan A, Valencia C, Akras D, Berger MJ, Wan DC, Fraser HB, Longaker MT. Allele-specific expression reveals genetic drivers of tissue regeneration in mice. Cell Stem Cell 2023; 30:1368-1381.e6. [PMID: 37714154 PMCID: PMC10592051 DOI: 10.1016/j.stem.2023.08.010] [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: 08/05/2022] [Revised: 06/16/2023] [Accepted: 08/22/2023] [Indexed: 09/17/2023]
Abstract
In adult mammals, skin wounds typically heal by scarring rather than through regeneration. In contrast, "super-healer" Murphy Roths Large (MRL) mice have the unusual ability to regenerate ear punch wounds; however, the molecular basis for this regeneration remains elusive. Here, in hybrid crosses between MRL and non-regenerating mice, we used allele-specific gene expression to identify cis-regulatory variation associated with ear regeneration. Analyzing three major cell populations (immune, fibroblast, and endothelial), we found that genes with cis-regulatory differences specifically in fibroblasts were associated with wound-healing pathways and also co-localized with quantitative trait loci for ear wound-healing. Ectopic treatment with one of these proteins, complement factor H (CFH), accelerated wound repair and induced regeneration in typically fibrotic wounds. Through single-cell RNA sequencing (RNA-seq), we observed that CFH treatment dramatically reduced immune cell recruitment to wounds, suggesting a potential mechanism for CFH's effect. Overall, our results provide insights into the molecular drivers of regeneration with potential clinical implications.
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Affiliation(s)
- Katya L Mack
- Stanford University, Department of Biology, Stanford, CA, USA
| | - Heather E Talbott
- Stanford School of Medicine, Department of Surgery, Division of Plastic and Reconstructive Surgery, Stanford, CA, USA; Stanford Institute for Stem Cell Biology and Regenerative Medicine, Stanford, CA, USA
| | - Michelle F Griffin
- Stanford School of Medicine, Department of Surgery, Division of Plastic and Reconstructive Surgery, Stanford, CA, USA
| | - Jennifer B L Parker
- Stanford School of Medicine, Department of Surgery, Division of Plastic and Reconstructive Surgery, Stanford, CA, USA; Stanford Institute for Stem Cell Biology and Regenerative Medicine, Stanford, CA, USA
| | - Nicholas J Guardino
- Stanford School of Medicine, Department of Surgery, Division of Plastic and Reconstructive Surgery, Stanford, CA, USA
| | - Amanda F Spielman
- Stanford School of Medicine, Department of Surgery, Division of Plastic and Reconstructive Surgery, Stanford, CA, USA
| | - Michael F Davitt
- Stanford School of Medicine, Department of Surgery, Division of Plastic and Reconstructive Surgery, Stanford, CA, USA
| | - Shamik Mascharak
- Stanford School of Medicine, Department of Surgery, Division of Plastic and Reconstructive Surgery, Stanford, CA, USA; Stanford Institute for Stem Cell Biology and Regenerative Medicine, Stanford, CA, USA
| | - Mauricio Downer
- Stanford School of Medicine, Department of Surgery, Division of Plastic and Reconstructive Surgery, Stanford, CA, USA
| | - Annah Morgan
- Stanford School of Medicine, Department of Surgery, Division of Plastic and Reconstructive Surgery, Stanford, CA, USA
| | - Caleb Valencia
- Stanford School of Medicine, Department of Surgery, Division of Plastic and Reconstructive Surgery, Stanford, CA, USA
| | - Deena Akras
- Stanford School of Medicine, Department of Surgery, Division of Plastic and Reconstructive Surgery, Stanford, CA, USA
| | - Mark J Berger
- Stanford University, Department of Computer Science, Stanford, CA 94305, USA
| | - Derrick C Wan
- Stanford School of Medicine, Department of Surgery, Division of Plastic and Reconstructive Surgery, Stanford, CA, USA
| | - Hunter B Fraser
- Stanford University, Department of Biology, Stanford, CA, USA.
| | - Michael T Longaker
- Stanford School of Medicine, Department of Surgery, Division of Plastic and Reconstructive Surgery, Stanford, CA, USA; Stanford Institute for Stem Cell Biology and Regenerative Medicine, Stanford, CA, USA.
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Zhang Z, Wiencke JK, Kelsey KT, Koestler DC, Molinaro AM, Pike SC, Karra P, Christensen BC, Salas LA. Hierarchical deconvolution for extensive cell type resolution in the human brain using DNA methylation. Front Neurosci 2023; 17:1198243. [PMID: 37404460 PMCID: PMC10315586 DOI: 10.3389/fnins.2023.1198243] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 05/30/2023] [Indexed: 07/06/2023] Open
Abstract
Introduction The human brain comprises heterogeneous cell types whose composition can be altered with physiological and pathological conditions. New approaches to discern the diversity and distribution of brain cells associated with neurological conditions would significantly advance the study of brain-related pathophysiology and neuroscience. Unlike single-nuclei approaches, DNA methylation-based deconvolution does not require special sample handling or processing, is cost-effective, and easily scales to large study designs. Existing DNA methylation-based methods for brain cell deconvolution are limited in the number of cell types deconvolved. Methods Using DNA methylation profiles of the top cell-type-specific differentially methylated CpGs, we employed a hierarchical modeling approach to deconvolve GABAergic neurons, glutamatergic neurons, astrocytes, microglial cells, oligodendrocytes, endothelial cells, and stromal cells. Results We demonstrate the utility of our method by applying it to data on normal tissues from various brain regions and in aging and diseased tissues, including Alzheimer's disease, autism, Huntington's disease, epilepsy, and schizophrenia. Discussion We expect that the ability to determine the cellular composition in the brain using only DNA from bulk samples will accelerate understanding brain cell type composition and cell-type-specific epigenetic states in normal and diseased brain tissues.
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Affiliation(s)
- Ze Zhang
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States
| | - John K. Wiencke
- Department of Neurological Surgery, Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, United States
| | - Karl T. Kelsey
- Department of Epidemiology, Department of Pathology and Laboratory Medicine, Brown University School of Public Health, Providence, RI, United States
| | - Devin C. Koestler
- Department of Biostatistics and Data Science, University of Kansas Medical Center, Kansas City, KS, United States
| | - Annette M. Molinaro
- Department of Neurological Surgery, Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, United States
| | - Steven C. Pike
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States
- Department of Neurology, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States
| | - Prasoona Karra
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States
| | - Brock C. Christensen
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States
- Department of Molecular and Systems Biology, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States
| | - Lucas A. Salas
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States
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Griffin MF, Talbott HE, Guardino NJ, Guo JL, Spielman AF, Chen K, Parker JBL, Mascharak S, Henn D, Liang N, King M, Cotterell AC, Bauer-Rowe KE, Abbas DB, Diaz Deleon NM, Sivaraj D, Fahy EJ, Downer M, Akras D, Berry C, Cook J, Quarto N, Klein OD, Lorenz HP, Gurtner GC, Januszyk M, Wan DC, Longaker MT. Piezo inhibition prevents and rescues scarring by targeting the adipocyte to fibroblast transition. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.03.535302. [PMID: 37066136 PMCID: PMC10103999 DOI: 10.1101/2023.04.03.535302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/18/2023]
Abstract
While past studies have suggested that plasticity exists between dermal fibroblasts and adipocytes, it remains unknown whether fat actively contributes to fibrosis in scarring. We show that adipocytes convert to scar-forming fibroblasts in response to Piezo -mediated mechanosensing to drive wound fibrosis. We establish that mechanics alone are sufficient to drive adipocyte-to- fibroblast conversion. By leveraging clonal-lineage-tracing in combination with scRNA-seq, Visium, and CODEX, we define a "mechanically naïve" fibroblast-subpopulation that represents a transcriptionally intermediate state between adipocytes and scar-fibroblasts. Finally, we show that Piezo1 or Piezo2 -inhibition yields regenerative healing by preventing adipocytes' activation to fibroblasts, in both mouse-wounds and a novel human-xenograft-wound model. Importantly, Piezo1 -inhibition induced wound regeneration even in pre-existing established scars, a finding that suggests a role for adipocyte-to-fibroblast transition in wound remodeling, the least-understood phase of wound healing. Adipocyte-to-fibroblast transition may thus represent a therapeutic target for minimizing fibrosis via Piezo -inhibition in organs where fat contributes to fibrosis.
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Ding L, Li X, Zhu H, Luo H. Single-Cell Sequencing in Rheumatic Diseases: New Insights from the Perspective of the Cell Type. Aging Dis 2022; 13:1633-1651. [PMID: 36465169 PMCID: PMC9662270 DOI: 10.14336/ad.2022.0323] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Accepted: 03/23/2022] [Indexed: 11/02/2023] Open
Abstract
Rheumatic diseases are a group of highly heterogeneous autoimmune and inflammatory disorders involving multiple systems. Dysfunction of immune and non-immune cells participates in the complex pathogenesis of rheumatic diseases. Therefore, studies on the abnormal activation of cell subtypes provided a specific basis for understanding the pathogenesis of rheumatic diseases, which promoted the accuracy of disease diagnosis and the effectiveness of various treatments. However, there was still a far way to achieve individualized precision medicine as the result of heterogeneity among cell subtypes. To obtain the biological information of cell subtypes, single-cell sequencing, a cutting-edge technology, is used for analyzing their genomes, transcriptomes, epigenetics, and proteomics. Novel results identified multiple cell subtypes in tissues of patients with rheumatic diseases by single-cell sequencing. Consequently, we provide an overview of recent applications of single-cell sequencing in rheumatic disease and cross-tissue to understand the cell subtypes and functions.
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Affiliation(s)
- Liqing Ding
- The Department of Rheumatology and Immunology, Xiangya Hospital of Central South University, Changsha, Hunan, China.
| | - Xiaojing Li
- The Department of Rheumatology and Immunology, Xiangya Hospital of Central South University, Changsha, Hunan, China.
| | - Honglin Zhu
- The Department of Rheumatology and Immunology, Xiangya Hospital of Central South University, Changsha, Hunan, China.
- Provincial Clinical Research Center for Rheumatic and Immunologic Diseases, Xiangya Hospital, Changsha, Hunan, China.
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Changsha, Hunan, China.
| | - Hui Luo
- The Department of Rheumatology and Immunology, Xiangya Hospital of Central South University, Changsha, Hunan, China.
- Provincial Clinical Research Center for Rheumatic and Immunologic Diseases, Xiangya Hospital, Changsha, Hunan, China.
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Changsha, Hunan, China.
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