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      Dynamic Interstitial Cell Response during Myocardial Infarction Predicts Resilience to Rupture in Genetically Diverse Mice

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          Summary

          Cardiac ischemia leads to the loss of myocardial tissue and the activation of a repair process that culminates in the formation of a scar whose structural characteristics dictate propensity to favorable healing or detrimental cardiac wall rupture. To elucidate the cellular processes underlying scar formation, here we perform unbiased single-cell mRNA sequencing of interstitial cells isolated from infarcted mouse hearts carrying a genetic tracer that labels epicardial-derived cells. Sixteen interstitial cell clusters are revealed, five of which were of epicardial origin. Focusing on stromal cells, we define 11 sub-clusters, including diverse cell states of epicardial- and endocardial-derived fibroblasts. Comparing transcript profiles from post-infarction hearts in C57BL/6J and 129S1/SvImJ inbred mice, which displays a marked divergence in the frequency of cardiac rupture, uncovers an early increase in activated myofibroblasts, enhanced collagen deposition, and persistent acute phase response in 129S1/SvImJ mouse hearts, defining a crucial time window of pathological remodeling that predicts disease outcome.

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          Highlights

          • Longitudinal transcriptional profiling of cardiac interstitial cells post-infarct

          • Identification of epicardial versus endocardial origin of cardiac stromal cells

          • A distinct early injury-response signature precedes appearance of myofibroblasts

          • Modulation of early fibrosis predicts cardiac rupture and pathological remodeling

          Abstract

          Using single-cell transcriptional profiling of mouse hearts carrying a reporter for epicardial-derived cells, Forte et al. provide a dynamic view of cardiac interstitial responses across acute and chronic phases of remodeling post-infarction. Comparing responses on diverse genetic backgrounds reveals novel cellular and transcriptional features of cardiac rupture propensity.

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          Most cited references63

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          DoubletFinder: Doublet Detection in Single-Cell RNA Sequencing Data Using Artificial Nearest Neighbors

          Single-cell RNA sequencing (scRNA-seq) data are commonly affected by technical artifacts known as “doublets,” which limit cell throughput and lead to spurious biological conclusions. Here, we present a computational doublet detection tool—Doublet-Finder—that identifies doublets using only gene expression data. DoubletFinder predicts doublets according to each real cell’s proximity in gene expression space to artificial doublets created by averaging the transcriptional profile of randomly chosen cell pairs. We first use scRNA-seq datasets where the identity of doublets is known to show that DoubletFinder identifies doublets formed from transcriptionally distinct cells. When these doublets are removed, the identification of differentially expressed genes is enhanced. Second, we provide a method for estimating DoubletFinder input parameters, allowing its application across scRNA-seq datasets with diverse distributions of cell types. Lastly, we present “best practices” for DoubletFinder applications and illustrate that DoubletFinder is insensitive to an experimentally validated kidney cell type with “hybrid” expression features. scRNA-seq data interpretation is confounded by technical artifacts known as doublets—single-cell transcriptome data representing more than one cell. Moreover, scRNA-seq cellular throughput is purposefully limited to minimize doublet formation rates. By identifying cells sharing expression features with simulated doublets, DoubletFinder detects many real doublets and mitigates these two limitations.
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            Bias, robustness and scalability in single-cell differential expression analysis

            Many methods have been used to determine differential gene expression from single-cell RNA (scRNA)-seq data. We evaluated 36 approaches using experimental and synthetic data and found considerable differences in the number and characteristics of the genes that are called differentially expressed. Prefiltering of lowly expressed genes has important effects, particularly for some of the methods developed for bulk RNA-seq data analysis. However, we found that bulk RNA-seq analysis methods do not generally perform worse than those developed specifically for scRNA-seq. We also present conquer, a repository of consistently processed, analysis-ready public scRNA-seq data sets that is aimed at simplifying method evaluation and reanalysis of published results. Each data set provides abundance estimates for both genes and transcripts, as well as quality control and exploratory analysis reports.
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              Cardiac progenitor cells from adult myocardium: homing, differentiation, and fusion after infarction.

              Potential repair by cell grafting or mobilizing endogenous cells holds particular attraction in heart disease, where the meager capacity for cardiomyocyte proliferation likely contributes to the irreversibility of heart failure. Whether cardiac progenitors exist in adult myocardium itself is unanswered, as is the question whether undifferentiated cardiac precursor cells merely fuse with preexisting myocytes. Here we report the existence of adult heart-derived cardiac progenitor cells expressing stem cell antigen-1. Initially, the cells express neither cardiac structural genes nor Nkx2.5 but differentiate in vitro in response to 5'-azacytidine, in part depending on Bmpr1a, a receptor for bone morphogenetic proteins. Given intravenously after ischemia/reperfusion, cardiac stem cell antigen 1 cells home to injured myocardium. By using a Cre/Lox donor/recipient pair (alphaMHC-Cre/R26R), differentiation was shown to occur roughly equally, with and without fusion to host cells.
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                Author and article information

                Contributors
                Journal
                Cell Rep
                Cell Rep
                Cell Reports
                Cell Press
                2211-1247
                03 March 2020
                03 March 2020
                03 March 2020
                : 30
                : 9
                : 3149-3163.e6
                Affiliations
                [1 ]The Jackson Laboratory, Bar Harbor, ME 04609, USA
                [2 ]National Heart and Lung Institute, Imperial College London, London SW72BX, UK
                Author notes
                []Corresponding author elvira.forte@ 123456jax.org
                [∗∗ ]Corresponding author mfurtado@ 123456amgen.com
                [3]

                Present address: Amgen, 1120 Veterans Blvd., South San Francisco, CA 94080, USA

                [4]

                Lead Contact

                Article
                S2211-1247(20)30162-5
                10.1016/j.celrep.2020.02.008
                7059115
                32130914
                8f956cfa-f9c6-4b4b-b6cc-293a0e51db24
                © 2020 The Author(s)

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 28 July 2019
                : 8 December 2019
                : 3 February 2020
                Categories
                Article

                Cell biology
                myocardial infarction,single-cell biology,cardiac rupture,fibrosis,genetic diversity,heart,mouse,epicardial-derived,scrnaseq,seurat

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