Network model integrated with multi-omic data predicts MBNL1 signals that drive myofibroblast activation
Anders R. Nelson,
Darrian Bugg,
Jennifer Davis,
Jeffrey J. Saucerman
Affiliations
Anders R. Nelson
Department of Pharmacology, University of Virginia, 1340 Jefferson Park Avenue, Pinn Hall, 5th Floor, PO Box 800735, Charlottesville, VA 22908-0735, USA
Darrian Bugg
Department of Lab Medicine & Pathology, University of Washington, 1959 NE Pacific Street Box 357470, Seattle, WA 98195, USA
Jennifer Davis
Department of Lab Medicine & Pathology, University of Washington, 1959 NE Pacific Street Box 357470, Seattle, WA 98195, USA; Department of Bioengineering, University of Washington, PO Box 355061, Seattle, WA 98195-5061, USA; Institute for Stem Cell & Regenerative Medicine, University of Washington, 850 Republican Street, PO Box 358056, Seattle, WA 98109, USA
Jeffrey J. Saucerman
Department of Biomedical Engineering, University of Virginia, PO Box 800759, Charlottesville, VA 22903 , USA; Corresponding author
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.
