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Biology subjects

Calkins, H.

Publications and source records attributed to Calkins, H..

2 recordsLinked to original sources

Desmoplakin mutations in cardiac fibroblasts cause TGF?1-mediated pathological fibrogenesis in desmoplakin cardiomyopathy via beclin-1 regulation

BackgroundPathological fibrosis is a major finding in cardiovascular diseases and can result in arrhythmia and heart failure. Desmosome gene mutations can lead to arrhythmogenic cardiomyopathy (ACM). Among ACM, pathogenic desmoplakin (DSP) variants cause a distinctive cardiomyopathy with excessive cardiac fibrosis that could precede ventricular dysfunction. DSP variants are also linked to other fibrotic diseases. Whether DSP plays any role in pathological fibrosis remain unknown. MethodsMesenchymal stromal cells (MSCs) are resident fibroblast-like cells that are responsible for fibrogenesis in most organs, including hearts. We first used unbiased genome-wide analyses to generate cardiac fibroblasts-like, induced pluripotent stem cell-derived MSCs from normal donors and ACM patients with DSP mutations. We then studied the fibrogenic responses of cardiac MSCs to transforming growth factor beta-1 (TGF-{beta}1) using Western/Co-IP, autophagy assay, gene knockdowns/over-expressions, genomic analyses, mouse DSP knockdown models, immunostaining, and qPCR. ResultsTGF{beta}1 induced excessive accumulations of vimentin (VIM)/fibrillar collagens, and over-activated fibrotic genes in DSP-mutant MSCs when compared to normal MSCs. In normal MSCs, VIMs bind to wild-type DSP during normal fibrogenesis after TGF{beta}1. DSP-mutant MSCs exhibited a haplo-insufficient phenotype with increased DSP-unbound VIMs that sequestered beclin-1 (BECN1) from activating autophagy and caveolin-1 (CAV1)-mediated endocytosis. Decreased autophagy caused collagen accumulations and diminished CAV1 endocytosis resulted in abnormal CAV1 plaque formation that over-activated fibrotic genes [COL1A1, COL3A1, and fibronectin (FN)] via heightened p38 activities after TGF{beta}1. Genome-wide analysis and DSP knockdown in mouse fibroblasts confirmed this novel role of DSP mutations in pathological fibrosis. Overexpression of VIM-binding domains of DSP could suppress pathological fibrosis by increasing collagen autophagic degradation and decreasing fibrotic gene expressions. ConclusionsOur data reveal that DSP deficiency in MSCs/fibroblasts leads to exaggerated fibrogenesis in DSP-cardiomyopathy by decreasing BECN1 availability for autophagy and CAV1-endocytosis. Overexpression of VIM binding domains of DSP could be a new strategy to treat pathological fibrosis.

cell biology↗

A Template for Translational Bioinformatics: Facilitating Multimodal Data Analyses in Preclinical Models of Neurological Injury

BackgroundPediatric neurological injury and disease is a critical public health issue due to increasing rates of survival from primary injuries (e.g., cardiac arrest, traumatic brain injury) and a lack of monitoring technologies and therapeutics for the treatment of secondary neurological injury. Translational, preclinical research facilitates the development of solutions to address this growing issue but is hindered by a lack of available data frameworks and standards for the management, processing, and analysis of multimodal data sets. MethodsHere, we present a generalizable data framework that was implemented for large animal research at the Childrens Hospital of Philadelphia to address this technological gap. The presented framework culminates in an interactive dashboard for exploratory analysis and filtered data set download. ResultsCompared with existing clinical and preclinical data management solutions, the presented framework accommodates heterogeneous data types (single measure, repeated measures, time series, and imaging), integrates data sets across various experimental models, and facilitates dynamic visualization of integrated data sets. We present a use case of this framework for predictive model development for intra-arrest prediction of cardiopulmonary resuscitation outcome. ConclusionsThe described preclinical data framework may serve as a template to aid in data management efforts in other translational research labs that generate heterogeneous data sets and require a dynamic platform that can easily evolve alongside their research.

bioinformatics↗