Systems-based approaches for investigating tissue communication during exercise

用于研究运动期间组织通讯的基于系统的方法

• 批准号: 10264084
• 负责人: Andrea L Hevener
• 金额: $ 35.45万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-30 至 2023-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10264084
• 关键词: Acute; Adipose tissue; Animals; Area; Bayesian Analysis; Bioinformatics; Cardiac; Chronic; Chronic Disease; Collaborations; Communication; Communities; Complex; Data; Data Set; Development; Disease; Endocrine; Exercise; Exercise Physiology; Fatty acid glycerol esters; Female; Generations; Genetic; Health; Homeostasis; Human; Hybrids; In Vitro; Inbred Mouse; Inbred Strains Mice; Inbreeding; Individual; Informatics; Insulin Resistance; Intervention; Liver; Metabolic; Metabolic dysfunction; Metabolism; Molecular; Molecular Biology; Mouse Strains; Mus; Myocardium; Non-Insulin-Dependent Diabetes Mellitus; Pathway interactions; Physical activity; Physiological; Plasma; Productivity; Proteome; Proteomics; Publications; Publishing; Rattus; Recombinants; Refractory; Research; Research Personnel; Resources; Rodent; Sampling; Scientist; Skeletal Muscle; System; Tissue Banks; Tissues; Training; Transducers; Universities; Validation; Variant; Work; advanced system; base; biobank; data hub; data repository; data resource; endurance exercise; exercise training; experience; human data; human subject; in vivo; male; metabolomics; multiple omics; new therapeutic target; next generation; novel; prevent; response; sex; skeletal; tissue resource; tool; trait; transcriptomics; validation studies

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.

摘要 日常体力活动是预防或改善与糖尿病相关的并发症的已知干预措施。 代谢相关疾病。然而，慢性运动的代谢适应机制 对培训的了解还不够。此外，对人体的研究表明， 一些个体对与训练相关的特定代谢改善难以适应。 由于常规的动物研究主要集中在少数啮齿动物品系上，因此在本申请中， 我们将在大约100只不同的雄性和雌性近交系小鼠中调查运动训练的适应性 被称为加州大学洛杉矶分校杂交小鼠多样性小组（HMDP），并将这些数据与现有的MoTrPAC 斯坦福大学生物信息学中心（BIC）的数据库。在目标1中，我们将确定 控制运动代谢的调节基因座并整合几个“组学”平台（转录组学， 蛋白质组学，代谢组学），使用贝叶斯分析和Mergeomics来识别调控网络， 小鼠运动训练的关键驱动节点，并利用公开数据验证这些发现 来自MoTrPAC联盟对大鼠和人类运动训练的研究。在目标2中，我们将使用 定量内分泌网络相互作用估计（QENIE），用于功能性地注释新的组织间 通信电路（心脏和骨骼肌，肝脏和脂肪之间），对于 耐力运动适应。我们在此提供的研究结果表明，显著的性别特异性组织串扰 维持代谢平衡和对运动的反应。了建设一 小鼠四种组织之间的通讯网络，并验证这些对血浆 人和大鼠的蛋白质组（由MoTrPAC consortium BIC提供）类似于多物种验证 我们小组先前发表的研究（PMCID 6399495，5935137）。此外，我们还将执行 分子验证研究证实了新循环因子的运动刺激变化，以及 使用表达的常规损失和增益来确定这些通信网络的功能 接近。我们的发现将具有强大的科学影响，因为我们将确定新的运动诱导的 调节节点和代谢改善的关键驱动途径，确定新的 运动驱动的内分泌相互作用，并生成一个小鼠样本生物库和数据库， 将其集成到MoTrPAC数据中心，以便整个研究界产生新的假设。