Identifying regulators of aged fibroblast activation in 3D tissue models

Abstract

Robust 3D tissue culture models to activate aged fibroblasts for cell-based therapies and identify regulators of such activation are still missing. In our previous study, we showed that aged fibroblasts can be activated simply through applying compressive force, without the need for exogenous factors, leading to increased migration. In this study, we develop a pipeline to evaluate the role of specific pharmacological inhibitors for transcription factor inference and cell migration involved in aged fibroblast activation. By integrating RNA-seq data with bioinformatic tools (prize collecting Steiner tree method and iRegulon) we inferred 15 candidates. In addition, we used cell migration and heterochromatin content as readouts for validating these candidates. Furthermore, we identified three potential master regulators of fibroblast activation and rejuvenation: FOXO1, STAT3, and PDK1. These findings offer valuable insights for future drug discovery, disease modeling, and regenerative medicine.