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

Angela C Zeigler,Anders R Nelson,Anirudha S Chandrabhatla,Olga Brazhkina,Jeffrey W Holmes,Jeffrey J Saucerman

doi:10.1016/j.matbio.2020.03.007

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 (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. TGFβ 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 TGFβ and endothelin positive feedback loops. Interleukin-1 overexpression had mixed effects, both enhancing collagen via the TGFβ positive feedback loop and suppressing collagen via NFκB 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.

Highlights

Wound healing is a complex process that involves a dynamic interplay between inflammatory and proliferative signaling
While the signaling model was originally developed and validated using a wealth of in vitro experimental data [23], we hypothesized that this model could be extended to predict post-myocardial infarction (MI) fibroblast dynamics because it is capable of predicting semi-quantitative time-dependent behavior and it incorporates many of the pathways involved in infarct healing (e.g. IL1, IL6, TGFβ, angiotensin II (AngII))
Post-MI paracrine stimuli exhibited a range of distinct dynamic behaviors, including rapid transients (IL6), slower transients (e.g. TGFβ, platelet-derived growth factor (PDGF)), and rapid transients followed by a distinct slower phase (e.g. IL1, NE)

Summary

Introduction

Wound healing is a complex process that involves a dynamic interplay between inflammatory and proliferative signaling. After myocardial infarction (MI), ACE inhibitors and beta blockers are prescribed to prevent adverse cardiac remodeling and heart failure [2], but the risk of heart failure and cardiac-related death post-MI remains high[3,4,5]. This is partly because wound healing is a balancing act between clearance of debris and formation of new scar, and the regulators of this dynamic process are not fully understood.

Methods

Results

Conclusion