Natural variation in Insulin signaling kinetics and its effect on health

University Of California At Davis, Davis CA

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Abstract

Project Summary In humans, common smaller-effect variants of genes belonging to the Insulin/IGF signaling (IIS) pathway are linked to increased prevalence in adult-onset diseases such as type-II diabetes and polycystic ovary syndrome. Interestingly, some IIS variants are linked to health benefits of increased life span and protection from metabolic disorders. What distinguishes variants associated with disease versus those associated with better long-term health? A limited number of studies from humans have shown that phosphorylation levels of IIS kinases are lower in individuals carrying disease-prone variants, suggesting that variants alter signal level to then influence health. Yet very few investigations focus on how small-effect variants affect IIS activity at the cellular level to in turn affect organismal phenotype. Flies, much like humans, carry natural variation in IIS genes that have been linked to changes in body size, stress tolerance and longevity. The proposed study takes advantage of the wealth of population genetic data, transgenic tools and cellular and organismal level analysis in Drosophila melanogaster to investigate how IIS gene variants alter IIS transduction kinetics and health. Strains carrying natural variants of IIS genes in a uniform genetic background will be used along with newly developed single-cell reporters for IIS kinases to characterize differences in kinetics of pathway activity using live-imaging of target tissues. In addition, adult health phenotypes of lines carrying SNPs will be investigated. Changes in pathway activity will then be computationally modeled to test whether signaling pathway dynamic can predict four important health phenotypes: growth, metabolism, reproduction and aging. By investigating the function of natural alleles at the cellular and organismal level, the proposed project will expand our understanding of IIS, and allow us to better interpret human IIS genetic variants and their effects on health.