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

First Author  Nelson AR Year  2023
Journal  iScience Volume  26
Issue  4 Pages  106502
PubMed ID  37091233 Mgi Jnum  J:337846
Mgi Id  MGI:7506718 Doi  10.1016/j.isci.2023.106502
Citation  Nelson AR, et al. (2023) Network model integrated with multi-omic data predicts MBNL1 signals that drive myofibroblast activation. iScience 26(4):106502
abstractText  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 alphaSMA expression. This study lays a foundation to explore the network mechanisms of MBNL1 signaling central to fibrosis.
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