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Kass, D. A.

Publications and source records attributed to Kass, D. A..

21 records · Page 2Linked to original sources

PDE1 inhibition modulates Cav1.2 channel to stimulate cardiomyocyte contraction

RationaleCyclic adenosine monophosphate (cAMP) activation of protein kinase A (PKA) stimulates excitation-contraction coupling, increasing cardiac contractility. This is clinically leveraged by beta-adrenergic stimulation ({beta}-ARs) or phosphodiesterase-3 inhibition (PDE3i), though both approaches are limited by arrhythmia and chronic myocardial toxicity. Phosphodiesterase-1 inhibition (PDE1i) also augments cAMP and was recently shown in rabbit cardiomyocytes to augment contraction independent of {beta}-AR stimulation or blockade, and with less intracellular calcium rise than {beta}-ARs or PDE3i. Early testing of PDE1 inhibition in humans with neuro-degenerative disease and dilated heart failure has commenced. Yet, the molecular mechanisms for PDE1i inotropic effects remain largely unknown. ObjectiveDefine the mechanism(s) whereby PDE1i increases contractility. Methods and ResultsPrimary guinea pig myocytes which express the cAMP-hydrolyzing PDE1C isoform found in larger mammals and humans were studied. The potent, selective PDE1i (ITI-214) did not alter cell shortening or Ca2+ transients under resting conditions whereas both increased with {beta}-ARs or PDE3i. However, PDE1i enhanced shortening with less Ca2+ rise in a PKA-dependent manner when combined with low-dose adenylate cyclase stimulation (Forskolin). Unlike PDE3i, PDE1i did not augment {beta}-AR responses. Whereas {beta}-ARs reduced myofilament Ca2+ sensitivity and increased sarcoplasmic reticular Ca2+ content in conjunction with greater phosphorylation of troponin I, myosin binding protein C, and phospholamban, PDE1i did none of this. However, PDE1i increased Cav1.2 channel conductance similar to PDE3i in a PKA-dependent manner. Myocyte shortening and peak Ca2+ transients were more sensitive to Cav1.2 blockade with nitrendipine combined with PDE1i versus PDE3i. Lastly, PDE1i was found to be far less arrythmogenic than PDE3i. ConclusionsPDE1i enhances contractility by a PKA-dependent increase in Cav1.2 conductance without concomitant myofilament desensitization. The result is less rise in intracellular Ca2+ and arrhythmia compared to {beta}-ARs and/or PDE3i. PDE1i could be a novel positive inotrope for failing hearts without the toxicities of {beta}-ARs and PDE3i.

pharmacology and toxicology↗

PGC1/PPAR Drive Cardiomyocyte Maturation through Regulation of Yap1 and SF3B2

Cardiomyocytes undergo significant levels of structural and functional changes after birth--fundamental processes essential for the heart to produce the volume and contractility to pump blood to the growing body. However, due to the challenges in isolating single postnatal/adult myocytes, how individual newborn cardiomyocytes acquire multiple aspects of mature phenotypes remains poorly understood. Here we implemented large-particle sorting and analyzed single myocytes from neonatal to adult hearts. Early myocytes exhibited a wide-ranging transcriptomic and size heterogeneity, maintained until adulthood with a continuous transcriptomic shift. Gene regulatory network analysis followed by mosaic gene deletion revealed that peroxisome proliferator-activated receptor coactivator-1 signaling--activated in vivo but inactive in pluripotent stem cell-derived cardiomyocytes--mediates the shift. The signaling regulated key aspects of cardiomyocyte maturation simultaneously through previously unrecognized regulators, including Yap1 and SF3B2. Our study provides a single-cell roadmap of heterogeneous transitions coupled to cellular features and unveils a multifaceted regulator controlling cardiomyocyte maturation. Significance StatementHow the individual single myocytes achieve full maturity remains a black box, largely due to the challenges with the isolation of single mature myocytes. Understanding this process is particularly important as the immaturity and early developmental arrest of pluripotent stem cell-derived myocytes has emerged a major concern in the field. Here we present the first study of high-quality single-cell transcriptomic analysis of cardiac muscle cells from neonatal to adult hearts. We identify a central transcription factor and its novel targets that control key aspects of myocyte maturation, including cellular hypertrophy, contractility, and mitochondrial activity.

developmental biology↗

Proteogenomic single cell analysis of skeletal muscle myocytes

Skeletal muscle myocytes have evolved into slow and fast-twitch types. These types are functionally distinct as a result of differential gene and protein expression. However, an understanding of the complexity of gene and protein variation between myofibers is unknown. We performed deep, whole cell, single cell RNA-seq on intact and fragments of skeletal myocytes from the mouse flexor digitorum brevis muscle. We compared the genomic expression data of 171 of these cells with two human proteomic datasets. The first was a spatial proteomics survey of mosaic patterns of protein expression utilizing the Human Protein Atlas (HPA) and the HPASubC tool. The second was a mass-spectrometry (MS) derived proteomic dataset of single human muscle fibers. Immunohistochemistry and RNA-ISH were used to understand variable expression. scRNA-seq identified three distinct clusters of myocytes (a slow/fast 2A cluster and two fast 2X clusters). Utilizing 1,605 mosaic patterned proteins from visual proteomics, and 596 differentially expressed proteins by MS methods, we explore this fast 2X division. Only 36 genes/proteins had variable expression across all three studies, of which nine are newly described as variable between fast/slow twitch myofibers. An additional 414 genes/proteins were identified as variable by two methods. Immunohistochemistry and RNA-ISH generally validated variable expression across methods presumably due to species-related differences. In this first integrated proteogenomic analysis of mature skeletal muscle myocytes we confirm the main fiber types and greatly expand the known repertoire of twitch-type specific genes/proteins. We also demonstrate the importance of integrating genomic and proteomic datasets.

genomics↗