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Han, J.-D. J.

Publications and source records attributed to Han, J.-D. J..

3 recordsLinked to original sources

Cardiomyocytes Undergo a Mesenchymal-Like Fate Transition in Myocardial Fibrosis

BACKGROUNDMyocardial fibrosis, a pathological hallmark of adverse cardiac remodeling and heart failure, has been conventionally attributed to the activation of resident fibroblasts. Although recent studies suggest contributions from non-fibroblast lineages, direct in vivo genetic evidence that cardiomyocytes can undergo a mesenchymal-like fate transition during myocardial fibrosis remains absent. This study aims to investigate whether such a transition occurs and to elucidate the underlying regulatory mechanisms. METHODSHuman myocardial infarction (MI) tissues were analyzed by immunohistochemistry and integrated with public single-nucleus RNA sequencing (snRNA-seq) data to detect mesenchymal-like signatures in cardiomyocytes. Genetic lineage-tracing was performed in MI mice, and in cardiomyocyte-specific Hgs (hepatocyte growth factor-regulated tyrosine kinase substrate) gene knockout mice, to map the fate of cardiomyocyte-derived cells. Mechanistic insights were obtained through proteomic and snRNA-seq analysis of Hgs knockout hearts and validated through gain- and loss-of-function experiments targeting Aldh1a2 (aldehyde dehydrogenase 1 family member A2). RESULTSIn human MI samples, a subset of cardiomyocytes showed reduced expression of cardiomyocyte markers concurrent with acquisition of mesenchymal-associated markers. Genetic lineage tracing demonstrated that adult cardiomyocytes can adopt a mesenchymal-like cell fate during post-MI remodeling. We identify HGS as a factor constraining this transition. Hgs knockout in adult cardiomyocytes upregulated Aldh1a2, triggered the mesenchymal-like fate transition, and gave rise to cells expressing markers of activated fibroblasts or osteoblasts, accompanied by pronounced myocardial fibrosis and calcification. Forced Aldh1a2 overexpression in cardiomyocytes drove the mesenchymal-like fate transition in vitro and in vivo, whereas Aldh1a2 deletion in cardiomyocytes mitigated MI-induced myocardial fibrosis. CONCLUSIONSThis study provides in vivo genetic evidence that adult cardiomyocytes possess the capacity to undergo a mesenchymal-like fate transition under pathological conditions. Our data suggest that HGS and ALDH1A2 serve as regulators of the transition, offering a new basis for understanding cellular and molecular mechanisms of myocardial fibrosis. Novelty and SignificanceO_ST_ABSWhat Is Known?C_ST_ABSO_LIMyocardial fibrosis is primarily driven by resident fibroblast activation, with additional contributions from cardiac CD34+ cells, pericytes, and macrophages. C_LIO_LIAdult cardiomyocytes exhibit phenotypic plasticity and transdifferentiate into epicardial-like or pacemaker cells under specific conditions. C_LI What New Information Does This Article Contribute?O_LIA subset of cardiomyocytes adopts a mesenchymal-like cell fate during myocardial fibrosis, marked by downregulation of cardiomyocyte identity markers and loss of aligned cell-cell contacts. C_LIO_LIThese cells acquire mesenchymal morphology and markers, ECM components, migratory gene signatures, and proliferative capacity. C_LIO_LIHGS and ALDH1A2 act as regulators of this mesenchymal-like fate transition. C_LI Myocardial fibrosis drives heart failure progression, yet the cellular sources of pathological fibroblasts remain incompletely defined. Here, we demonstrate that a subset of cardiomyocytes adopts a mesenchymal-like cell fate during myocardial fibrosis by using an integrated approach combining human MI samples, murine genetic lineage tracing, and snRNA-seq. Mechanistically, we identify HGS and ALDH1A2 as regulators of this transition. Cardiomyocyte-specific Hgs deletion upregulates Aldh1a2, triggering the mesenchymal-like fate transition. Furthermore, Aldh1a2 overexpression drives this transition, while its deletion attenuates MI-induced fibrosis. These findings reveal a previously unrecognized plasticity of adult cardiomyocytes and identify potential therapeutic targets for fibrotic heart disease.

genetics↗

Identification of the Metaphyseal Skeletal Stem Cell

Identification of novel regional skeletal stem cells (SSCs) will provide a new cellular paradigm for bone physiology and dysfunction. Several populations of SSCs have been identified at distinct skeletal sites. However, a bona fide SSC population has not yet been formally characterized in the bone marrow. Here, we identify a metaphyseal SSCs (mpSSCs) population whose transcriptional landscape is distinct from other bone mesenchymal stromal cells (bMSCs) in the bone marrow. These mpSSCs emerge at the postnatal stage and reside just underneath the growth plate, consistent with the fact that these mpSSCs are exclusively derived from hypertrophic chondrocytes (HCs). These mpSSCs possess SSC properties such as self-renewal and multipotency in vitro and in vivo, stand at the top of the HC de-differentiation path, and produce most HC progeny. Genetic block of the conversion from HCs to mpSSCs significantly compromises trabecular bone formation and bone regeneration. Thus, metaphysis houses a unique HC-derived SSC population, which is a major source of osteoblasts and bMSCs supporting postnatal trabecular bone formation.

developmental biology↗

Accurate loop calling for 3D genomic data with cLoops

Sequencing-based 3D genome mapping technologies can identify loops formed by interactions between regulatory elements hundreds of kilobases apart. Existing loop-calling tools are mostly restricted to a single data type, with accuracy dependent on a pre-defined resolution contact matrix or called peaks, and can have prohibitive hardware costs. Here we introduce cLoops ( see loops) to address these limitations. cLoops is based on the clustering algorithm cDBSCAN that directly analyzes the paired-end tags (PETs) to find candidate loops and uses a permuted local background to estimate statistical significance. These two data-type-independent processes enable loops to be reliably identified for both sharp and broad peak data, including but not limited to ChIA-PET, Hi-C, HiChIP and Trac-looping data. Loops identified by cLoops showed much less distance-dependent bias and higher enrichment relative to local regions than existing tools. Altogether, cLoops improves accuracy of detecting of 3D-genomic loops from sequencing data, is versatile, flexible, efficient, and has modest hardware requirements, and is freely available at: https://github.com/YaqiangCao/cLoops.

bioinformatics↗