Network model integrated with multi-omic data predicts MBNL1 signals that drive myofibroblast activation

Autor: Anders R. Nelson, Darrian Bugg, Jennifer Davis, Jeffrey J. Saucerman
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: iScience, Vol 26, Iss 4, Pp 106502- (2023)
Druh dokumentu: article
ISSN: 2589-0042
DOI: 10.1016/j.isci.2023.106502
Popis: Summary: RNA-binding protein muscleblind-like1 (MBNL1) was recently identified as a central regulator of cardiac wound healing and myofibroblast activation. To identify putative MBNL1 targets, we integrated multiple genome-wide screens with a fibroblast network model. We expanded the model to include putative MBNL1-target interactions and recapitulated published experimental results to validate new signaling modules. We prioritized 14 MBNL1 targets and developed novel fibroblast signaling modules for p38 MAPK, Hippo, Runx1, and Sox9 pathways. We experimentally validated MBNL1 regulation of p38 expression in mouse cardiac fibroblasts. Using the expanded fibroblast model, we predicted a hierarchy of MBNL1 regulated pathways with strong influence on αSMA expression. This study lays a foundation to explore the network mechanisms of MBNL1 signaling central to fibrosis.
Databáze: Directory of Open Access Journals