Systems-based approaches for investigating tissue communication during exercise

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ABSTRACT Daily physical activity is a known intervention to prevent or ameliorate complications associated with metabolic-related diseases. However, the mechanisms underlying metabolic adaptations to chronic exercise training remain inadequately understood. Moreover, human studies show a broad range of exercise adaptation with some individuals refractory to specific metabolic improvements associated with training. Since conventional animal studies have focused primarily on few rodent strains, in the current application we will interrogate exercise training adaptations in ~100 diverse male and female strains of inbred mice known as the UCLA Hybrid Mouse Diversity Panel (HMDP), and integrate these data with existing MoTrPAC data repositories at the Bioinformatics Center (BIC), Stanford University. In Aim 1 we will determine the regulatory loci controlling exercise metabolism and integrate several “omics” platforms (transcriptomics, proteomics, metabolomics) using Bayesian analyses and Mergeomics to identify regulatory networks and key driver nodes underlying exercise training in mice and validate these findings with publicly available data from the MoTrPAC consortium studies of exercise training in rats and humans. In Aim 2 we will use Quantitative Endocrine Network Interaction Estimation (QENIE) to functionally annotate novel inter-tissue communication circuits (between cardiac and skeletal muscle, and liver, and fat) that are critical for endurance exercise adaptation. Our findings provided herein show remarkable, sex-specific tissue crosstalk that occurs to maintain metabolic homeostasis and in response to exercise. We will construct communication networks between the four tissues in mouse and validate these against the plasma proteome of human and rat (provided by the MoTrPAC consortium BIC) similar to multi-species validation studies published previously by our group (PMCID6399495, 5935137). Moreover, we will also perform molecular validation studies confirming exercise-stimulated changes in novel circulating factors, and determine functionality of these communication networks using conventional loss and gain of expression approaches. Our findings will be of strong scientific impact as we will identify novel exercise-induced regulatory nodes and key driver pathways underlying improvements in metabolism, determine novel exercise driven endocrine interactions, and generate a mouse sample biobank and data repository that will be integrated into the MoTrPAC data hub for novel hypothesis generation by the entire research community.