Cardiac development relies on proper cardiomyocyte differentiation, including expression and assembly of cell-type-specific actomyosin subunits into a functional cardiac sarcomere. Control of this process involves not only promoting expression of cardiac sarcomere subunits but also repressing expression of noncardiac myofibril paralogs. This level of transcriptional control requires broadly expressed multiprotein machines that modify and remodel the chromatin landscape to restrict transcription machinery access. Prominent among these is the nucleosome remodeling and deacetylase (NuRD) complex, which includes the catalytic core subunit CHD4. Here, we demonstrate that direct CHD4-mediated repression of skeletal and smooth muscle myofibril isoforms is required for normal cardiac sarcomere formation, function, and embryonic survival early in gestation. Through transcriptomic and genome-wide analyses of CHD4 localization, we identified unique CHD4 binding sites in smooth muscle myosin heavy chain, fast skeletal α-actin, and the fast skeletal troponin complex genes. We further demonstrate that in the absence of CHD4, cardiomyocytes in the developing heart form a hybrid muscle cell that contains cardiac, skeletal, and smooth muscle myofibril components. These misexpressed paralogs intercalate into the nascent cardiac sarcomere to disrupt sarcomere formation and cause impaired cardiac function in utero. These results demonstrate the genomic and physiological requirements for CHD4 in mammalian cardiac development.
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http://dx.doi.org/10.1073/pnas.1722219115 | DOI Listing |
Cureus
November 2024
Department of Medical Genetics, Institute of Science Tokyo, Tokyo, JPN.
Filamin C (FLNC), recently identified as a causative gene of cardiomyopathy, is widely expressed in cardiomyocytes and is involved in signal transduction between the sarcomere and the plasma membrane. In general, the FLNC truncating variant causes severe dilated cardiomyopathy. A 70-year-old female was referred to our hospital with advanced conduction defects and underwent pacemaker implantation.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Clinical Sciences, College of Veterinary Medicine, North Carolina State University, 1060 William Moore Dr, Raleigh, NC, 27607, USA.
Hypertrophic cardiomyopathy (HCM) afflicts humans, cats, pigs, and rhesus macaques. Disease sequelae include congestive heart failure, thromboembolism, and sudden cardiac death (SCD). Sarcomeric mutations explain some human and cat cases, however, the molecular basis in rhesus macaques remains unknown.
View Article and Find Full Text PDFMetabolites
December 2024
Division of Metabolic and Cardiovascular Sciences, Burnett School of Biomedical Sciences, College of Medicine, University of Central Florida, Orlando, FL 32827, USA.
Cardiac diseases remain one of the leading causes of death globally, often linked to ischemic conditions that can affect cellular homeostasis and metabolism, which can lead to the development of cardiovascular dysfunction. Considering the effect of ischemic cardiomyopathy on the global population, it is vital to understand the impact of ischemia on cardiac cells and how ischemic conditions change different cellular functions through post-translational modification of cellular proteins. : To understand the cellular function and fine-tuning during stress, we established an ischemia model using neonatal rat ventricular cardiomyocytes.
View Article and Find Full Text PDFBackground: Hypertrophic cardiomyopathy (HCM) is a common heritable heart disease where the most frequently associated mutations occur in the myosin-binding protein C () sarcomere-associated gene. HCM is also a common veterinary clinical problem in certain cat breeds such as Maine Coons and Ragdolls, also most associated with mutations in . Mouse models of HCM in which mutations are introduced recapitulate some, but not all, features of human HCM.
View Article and Find Full Text PDFRecent advancements in flexible bioelectronics have enabled continuous, long-term stable interrogation and intervention of biological systems. However, effectively utilizing the interrogated data to modulate biological systems to achieve specific biomedical and biological goals remains a challenge. In this study, we introduce an AI-driven bioelectronics system that integrates tissue-like, flexible bioelectronics with cyber learning algorithms to create a long-term, real-time bidirectional b ioelectronic interface with o ptimized a daptive intelligent m odulation (BIO-AIM).
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