Unveiling the transcription factors responsible for adipocyte transdifferentiation in humans though in silico analysis.

• Grant number: 23/10154-7
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: August 01, 2023
• End date: October 31, 2024
• Field of knowledge: Biological Sciences - Physiology - Physiology of Organs and Systems
• Principal Investigator: Licio Augusto Velloso
• Grantee: André Iba Kanashiro
• Host Institution: Faculdade de Ciências Médicas (FCM). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• Associated research grant: 13/07607-8 - OCRC - Obesity and Comorbidities Research Center, AP.CEPID

Abstract

Adipose tissue is divided into white adipose tissue, which is primarily responsible for storing energy in the form of triglycerides, and brown and beige adipose tissues, which expend energy in the form of heat (thermogenesis). Beige adipocytes can develop from local precursors (de novo adipogenesis) or transform mature white adipocytes into beige adipocytes through transdifferentiation. However, the molecular mechanisms involved in the transdifferentiation process remain unclear. Experimental methods (e.g., CRISPR/Cas9) capable of inducing the disruption of target genes in cells of interest are described in the literature, but present high operational costs and technical challenges. On the other hand, the use of computational methods inthe determination of gene-regulatory networks (GRN) represents an effective and low-cost way to evaluate in silico the function of genes of interest and, consequently, the cellular phenotype. In this regard, a computational methodknown as CellOracle, specifically designed to simulate changes in cell identity after disruption of transcription factors (TFs), has been recently developed. Thus, the purpose of this project will be to use the CellOracle computational method to identify transcriptional mediators responsible for the mechanism of transdifferentiation from white to beige adipocytes from single-cell human data.