Biology subjects

Csordas, D. J.

Publications and source records attributed to Csordas, D. J..

3 recordsLinked to original sources

bioRxiv2026

A novel in vitro assay for quantifying endothelial cell and pericyte interactions

ObjectiveStructural adaptations of capillary networks, through angiogenesis, arterialization, and regression, are implicated in many diseases, and gaining a better understanding of the cell-cell interactions that underpin these adaptations may lead to novel therapeutic discoveries for disease management. Endothelial cells and pericytes are the two cell types that comprise capillary networks. Experimental model systems have been developed to study the dynamic interactions between endothelial cells and pericytes, providing valuable insights into capillary development, cell-to-cell communication, and responses to growth factors and therapeutic agents. MethodsIn this study, we present a novel and simple co-culture system that uses commercially available primary human endothelial cells and pericytes, does not require microfluidic perfusion, and allows simultaneous observation of cell morphologies and interactions over time in 60 samples, enabling high-throughput analysis of multiple culture conditions with replicates. ResultsImage analysis pipelines were created to quantify microvascular adaptations, including one to measure colocalization between endothelial cells and pericytes, capturing dynamic coupling and uncoupling associated with capillary stability, angiogenesis, and regression. We validated the ability of our co-culture system to reproducibly represent the effects of fibrotic and angiogenic activation signals, including an FDA-approved drug, on endothelial cells, pericytes, and their coupling. ConclusionThis novel, high-throughput microvascular screening assay enables quantification of microvascular dynamics in response to disease-relevant stimuli and therapeutics in a repeatable, real-time manner.

bioengineering↗

bioRxiv2026

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 subpopulations that may be primed for the hyper-activation that leads to increased progression of fibrotic disease. Understanding the contribution of these subpopulations to disease progression requires integrating experimental and computational techniques to understand their dynamic contributions to tissue phenotype. Herein, we introduce a framework for modeling subpopulations using a multiscale mechanistic computational model to understand differences within subpopulations, 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 subpopulations of fibroblasts in IPF. The subpopulations 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 subpopulations. Coupling this with an agent-based model (ABM) of the lung microenvironment, we observed how different rules regulating cell fate decisions in each subpopulation affected collagen content. Computational image outputs were analyzed with the open-source biological image analysis software QuPath to quantify how changes in subpopulation 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 subpopulations lead to tissue-level disease phenotypes. Author SummaryIn wound healing fibroblasts are responsible for rebuilding the scaffolding, called the extracellular matrix (ECM), of the damaged tissue to aid in regeneration. In fibrosis, the normal wound healing processes are hijacked leading to overproduction of ECM proteins, such as collagen, by fibroblasts leading to fibrosis. In fibrotic diseases with no known cause, such as idiopathic pulmonary fibrosis (IPF), subpopulations of fibroblasts have been identified as possible drivers of disease. Herein, we use a multiscale computational model that represents intracellular, cellular, and tissue level signaling to study how the presence or absence of a single protein on a fibroblasts surface, Thy-1, affects the formation of fibrotic scar in IPF. Thy-1 regulates how a fibroblast senses the stiffness of the microenvironment. The absence of Thy-1 impacted intracellular signaling and when combined across many cells led to fibrosis at the tissue level. Additionally, if normal Thy-1+ fibroblasts could dynamically lose Thy-1 expression the amount of collagen they produced correlated with that in end stage IPF lungs. This model presents a framework for studying different fibroblast subpopulations using multiscale computational modeling to understand how changes in a single protein in one cell can, over an entire population, affect the dynamics of disease progression.

bioengineering↗

bioRxiv2024

Multi-Scale Computational Model of Microvascular Remodeling in Idiopathic Pulmonary Fibrosis

Investigating the molecular, cellular, and tissue-level changes caused by disease, and the effects of pharmacological treatments across these biological scales, necessitates the use of multiscale computational modeling in combination with experimentation. Many diseases dynamically alter the tissue microenvironment in ways that trigger microvascular network remodeling, which leads to the expansion or regression of microvessel networks. When microvessels undergo remodeling in idiopathic pulmonary fibrosis (IPF), functional gas exchange is impaired due to loss of alveolar structures and lung function declines. Here, we integrated a multiscale computational model with independent experiments to investigate how combinations of biomechanical and biochemical cues in IPF alter cell fate decisions leading to microvascular remodeling. Our computational model predicted that extracellular matrix (ECM) stiffening reduced microvessel area, which was accompanied by physical uncoupling of endothelial cell (ECs) and pericytes, the cells that comprise microvessels. Nintedanib, an FDA-approved drug for treating IPF, was predicted to further potentiate microvessel regression by decreasing the percentage of quiescent pericytes while increasing the percentage of pericytes undergoing pericyte-myofibroblast transition (PMT) in high ECM stiffnesses. Importantly, the model suggested that YAP/TAZ inhibition may overcome the deleterious effects of nintedanib by promoting EC-pericyte coupling and maintaining microvessel homeostasis. Overall, our combination of computational and experimental modeling can explain how cell decisions affect tissue changes during disease and in response to treatments.

bioengineering↗