Abstract

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 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 of the proliferative phase required paired stimuli (e.g. TGFβ and angiotensin-II). Virtual overexpression screens with static cytokine pairs and after myocardial infarction predicted phase-specific regulators of collagen expression. Several regulators increased (Smad3) or decreased (Smad7, protein kinase G) collagen expression specifically in the proliferative phase. NADPH oxidase overexpression sustained collagen expression from proliferative to maturation phases, driven by TGFβ and endothelin positive feedback loops. Interleukin-1 overexpression suppressed collagen via NFκB and BAMBI (BMP and activin membrane-bound inhibitor) incoherent feedforward loops, but it then later sustained collagen expression due to the TGFβ positive feedback loop. 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.

Details

Title
Computational Model Predicts Paracrine and Intracellular Drivers of Fibroblast Phenotype After Myocardial Infarction
Author
Zeigler, Angela C; Nelson, Anders R; Chandrabhatla, Anirudha S; Brazhkina, Olga; Holmes, Jeffrey W; Saucerman, Jeffrey J
University/institution
Cold Spring Harbor Laboratory Press
Section
New Results
Publication year
2019
Publication date
Nov 13, 2019
Publisher
Cold Spring Harbor Laboratory Press
ISSN
2692-8205
Source type
Working Paper
Language of publication
English
ProQuest document ID
2314132385
Copyright
© 2019. This article is published under http://creativecommons.org/licenses/by/4.0/ (“the License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.