A Proteomics-informed Mathematical Model Of TGFβ1-induced Aortic Valve Interstitial Cell Activation
Daniel P. Howsmon, Toni M. West, Robin Tuscher, Michael S. Sacks.
The University of Texas at Austin, Austin, TX, USA.
OBJECTIVE: With no pharmaceutical treatments that drastically prevent or delay the onset of calcific aortic valve disease (CAVD), treatment options consist of surgical repair or replacement. Valve interstitial cells (VICs) are the predominant cell type contributing to increased extracellular matrix (ECM) deposition and remodeling as well as calcification in CAVD. A detailed understanding of the signaling network driving VIC activation and expression of ECM-related genes would facilitate the rational discovery of suitable drug targets for mitigating, preventing, and/or reversing CAVD.
METHODS: As a first step, VICs were stimulated with transforming growth factor beta 1 (TGFβ1) to induce their phenotypic transition to myofibroblasts. VIC lysates were collected at various time points and subjected to bottom-up (phospho-)proteomics analysis. A separate set of lysates was subjected to subcellular fractionation to determine the ratio of G-/F-actin. The time course of a subset of the discovered phosphorylations were modeled as a dynamic reaction network.
RESULTS: A suitable model of TGFβ1-induced VIC activation was identified from phosphoproteomics data. Sensitivity analysis enables model simplification and the identification of key reactions that drive this phenotypic transition.
CONCLUSIONS: By coupling (phospho-)proteomics experiments with scientific computing, we can develop large, predictive models that enable the rational identification of suitable drug targets for combatting CAVD. These models can be extended in the future with other signals encountered in the development of CAVD.
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