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Publication : Computational model predicts paracrine and intracellular drivers of fibroblast phenotype after myocardial infarction.

First Author  Zeigler AC Year  2020
Journal  Matrix Biol Volume  91-92
Pages  136-151 PubMed ID  32209358
Mgi Jnum  J:299643 Mgi Id  MGI:6501293
Doi  10.1016/j.matbio.2020.03.007 Citation  Zeigler AC, et al. (2020) Computational model predicts paracrine and intracellular drivers of fibroblast phenotype after myocardial infarction. Matrix Biol 91-92:136-151
abstractText  The fibroblast is a key mediator of wound healing in the heart and other organs, yet how it integrates multiple time-dependent paracrine signals to control extracellular matrix synthesis has been difficult to study in vivo. Here, we extended a computational model to simulate the dynamics of fibroblast signaling and fibrosis after myocardial infarction (MI) in response to time-dependent data for nine paracrine stimuli. This computational model was validated against dynamic collagen expression and collagen area fraction data from post-infarction rat hearts. The model predicted that while many features of the fibroblast phenotype at inflammatory or maturation phases of healing could be recapitulated by single static paracrine stimuli (interleukin-1 and angiotensin-II, respectively), mimicking the reparative phase required paired stimuli (e.g. TGFbeta and endothelin-1). Virtual overexpression screens simulated with either static cytokine pairs or post-MI paracrine dynamic predicted phase-specific regulators of collagen expression. Several regulators increased (Smad3) or decreased (Smad7, protein kinase G) collagen expression specifically in the reparative phase. NADPH oxidase (NOX) overexpression sustained collagen expression from reparative to maturation phases, driven by TGFbeta and endothelin positive feedback loops. Interleukin-1 overexpression had mixed effects, both enhancing collagen via the TGFbeta positive feedback loop and suppressing collagen via NFkappaB and BAMBI (BMP and activin membrane-bound inhibitor) incoherent feed-forward loops. These model-based predictions reveal network mechanisms by which the dynamics of paracrine stimuli and interacting signaling pathways drive the progression of fibroblast phenotypes and fibrosis after myocardial infarction.
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