Unraveling Metabolic Resilience: A Genomic Exploration Using Astyanax mexicanus Cavefish

Oklahoma Medical Research Foundation, Oklahoma City OK

Investigators

Abstract

Abstract Metabolic syndrome poses a significant health burden globally, necessitating innovative approaches for therapeutic discovery. This project aims to unravel the genetic basis of metabolic resilience using the unique Astyanax mexicanus cavefish system, a powerful model for studying evolutionary adaptations to metabolic challenges. The Astyanax system, featuring both river and cave-dwelling morphotypes, provides a unique opportunity to investigate how organisms adapt to metabolic syndrome-like conditions. The cave morphotypes, residing in light-deprived, nutrient-scarce caves, exhibit distinctive metabolic features such as high blood glucose and obesity without the typical detriments observed in humans such as inflammation. In stark contrast, the river- dwelling surface fish do not display these features leading to our hypothesis that the two morphotypes have evolved distinct gene regulatory networks to present divergent metabolic phenotypes. Thus, leveraging the interfertility and lab breeding capabilities of both morphotypes, the study focuses on three key aims. Aim 1 investigates the role of Hepatocyte Nuclear Factor 4A – a liver-enriched transcription factor that is mutated cavefish – in the metabolic resilience of cavefish. Aim 2 employs Weighted Gene Co-expression Network Analysis to identify gene regulatory networks associated with starvation resistance. Aim 3 explores hyperglycemia in early developmental stages, providing insights into glucose metabolism independent of adipogenesis. In total, the project integrates transcriptomics, epigenomics, and functional genomics to define genetic networks associated with metabolic resilience in the cavefish, contributing to a deeper understanding of metabolic disorders and potentially identify novel therapeutic targets. Through the project timeline, I will be supported by the Epigenomics and Artificial Intelligence Cores and mentored by two senior faculty members to develop an independent and successful research program.