Computational Analysis of Fibroblast Subpopulation Dynamics as a Driver of Fibrotic Foci Formation

Fibroblasts maintain the extracellular matrix (ECM) to support tissue homeostasis and wound healing. In fibrotic diseases, fibroblasts are a primary driver of disease progression through excess collagen secretion and enhanced contractility. Replacing native tissue with a collagen rich fibrotic scar leads to a decline in tissue function. Recent research into idiopathic pulmonary fibrosis (IPF) has identified fibroblast sub-populations that may be primed for the hyper-activation that leads to increased progression of fibrotic disease. Understanding the contribution of these sub-populations to disease progression requires integrating experimental and computational techniques to understand their dynamic contributions to tissue phenotype. Herein, we introduce a framework for modeling sub-populations using a multiscale mechanistic computational model to understand differences within sub-populations, at the intracellular level and how these differences contribute to cell- and tissue-level pathology. We build and validate this framework using two well-defined sub-populations of fibroblasts in IPF. The sub-populations are defined by the presence or absence of Thy-1, a cell-surface protein that regulates fibroblast mechanosensing. We first developed a logic-based network model of a fibroblast. We then applied this model to identify sub-networks that regulate myofibroblast marker expression in the two sub-populations. Coupling this with an agent-based model (ABM) of the lung microenvironment, we observed how different rules regulating cell fate decisions in each sub-population affected collagen content. Computational image outputs were analyzed with the open-source biological image analysis software QuPath to quantify how changes in sub-population dynamics change model-predicted foci characteristics such as size and collagen density. We find that the ability for Thy-1+ fibroblasts to transition to Thy-1-fibroblasts significantly increases total collagen content, as well as influences fibrotic foci characteristics. Overall, we present a combined experimental and computational framework for studying how dynamic changes in fibroblast sub-populations lead to tissue-level disease phenotypes.