Mechanisms of ROS Balance and Cardiac Energy Metabolism in Diabetes Mellitus

描述(由申请人提供)：在这项建议中，我们旨在通过实验和计算建模，应用最近引入的两个概念：“氧化还原优化的ROS平衡”(R-OR平衡)和“扩散环控制”，研究ROS和能量学的综合新陈代谢。为了综合分析2型糖尿病(T2 DM)这一重要疾病中能量和ROS平衡的调控机制，我们将在2型糖尿病(T2 DM)大鼠模型上研究工作心肌，重点研究胰岛素和二甲双胍对能量和ROS通路的影响。在糖尿病心肌中，我们试图了解能量和ROS通量的相互依赖及其与氧化还原环境的关系，我们将重点关注胰岛素和二甲双胍(一种广泛使用的降血糖药物)对代谢控制的影响。这些研究将应用基于抑制剂滴定方法的代谢控制分析的最先进的定量工具，以及对稳态状态扰动后的瞬变的分析。我们计划在力传感器设备的工作条件下，监测装载有荧光指示剂的大鼠心脏小梁的代谢变量和ROS。实验结果将被用来约束和微调一个整合了机械、电生理和代谢活动的心肌细胞计算模型(ECME模型)。到目前为止，ECME模型已经能够成功地模拟以下行为：i)线粒体膜电位、NADH、谷胱甘肽和ROS的振荡；ii)线粒体NADH、钙和ADP在心脏供需变化期间的动态变化；以及iii)在经历心律失常的整个心脏中线粒体振荡期间的肌膜电位的动态变化。该模型将扩展到包括乙酰辅酶A上游的途径，即糖酵解、戊糖磷酸途径和β-氧化。对呼吸链的电子传输复合体和ROS清除途径进行更详细的数学描述，将能够解释ROS平衡的机制。计算模型将受到代谢控制，以努力确定参与控制和调节能量和ROS途径网络的步骤。我们相信，为了在心血管系统疾病的治疗和预防中进行合理的干预，需要对代谢网络的整合行为有更深入的了解。这证明了我们试图建立一个计算模型的尝试，该模型将导致对心脏生理学的功能障碍方面的定量了解，并指出可能用于治疗干预的潜在靶点，无论是药物干预、营养干预还是基因治疗。 公共卫生相关性：糖尿病中ROS平衡和心脏能量代谢的机制项目叙述糖尿病影响着全球1.5亿人和近6%的美国人口，预计到2030年将增长到3.66亿。了解代谢网络在糖尿病中的功能，是设计合理的治疗策略的先决条件，这些治疗策略旨在预防或管理疾病而不产生副作用。我们方法的创新优势在于对与细胞内能量和氧化还原系统相关的代谢网络的综合看法，这些系统的控制和调节对糖尿病至关重要。

DESCRIPTION (provided by applicant): In this proposal we aim to study the integrated metabolism of reactive oxygen species (ROS) and energetics, experimentally and by computational modeling, applying two recently introduced concepts: "Redox- optimized ROS balance" (R-OR balance), and "control by diffuse loops". In order to analyze in an integrated manner the mechanisms of control and regulation of energy and ROS balance in an important disease for public health, we will investigate working cardiac muscle in a type 2 diabetes mellitus (T2DM) rat model, focusing on the effects of insulin and metformin upon energy and ROS pathways. In the diabetic cardiac muscle, we seek to understand the interdependence of energy and ROS fluxes and their relation to the redox environment, We will focus on the effects of insulin and metformin (a widely-used anti-hyperglycemic drug) on metabolic control. These studies will apply state of the art quantitative tools of metabolic control analysis based on the inhibitor titration method, and on the analysis of transients after perturbation of the steady state regime. We plan to monitor metabolic variables and ROS in rat cardiac trabeculae loaded with fluorescent indicators, under working conditions in a force transducer device. The experimental results will be used to constrain and fine-tune a computational model of the cardiac myocyte that integrates mechanical, electrophysiological and metabolic activities (ECME model). So far, the ECME model has been able to successfully simulate the behavior of i) oscillations in mitochondrial membrane potential, NADH, glutathione, and ROS, ii) the dynamics of mitochondrial NADH, calcium, and ADP during changes in supply and demand in the heart, and iii) the dynamics of the sarcolemmal membrane potential during mitochondrial oscillations in whole hearts undergoing arrhythmias. The model will be extended to incorporate pathways upstream Acetyl CoA, namely glycolysis, pentose phosphate pathways and beta-oxidation. A more detailed mathematical description of the electron-transport complexes of the respiratory chain, and of the ROS scavenging pathways, will enable accounting for the mechanisms of ROS balance. The computational model will be subjected to metabolic control in an effort to identify the steps that participate in the control and regulation of the network of energy and ROS pathways. We are convinced that in order to perform a rational intervention in the treatment and prevention of a disease regarding the cardiovascular system, a deeper understanding of the integrated behavior of metabolic networks is needed. This justifies our attempt to build a computational model that will lead to a quantitative understanding of the dysfunctional aspects of heart physiology, and point out potential targets that could be used for therapeutic interventions, either pharmacological, nutritional or by gene therapy. PUBLIC HEALTH RELEVANCE: Mechanisms of ROS balance and cardiac energy metabolism in Diabetes mellitus Project Narrative Diabetes affects >150 million individuals worldwide and nearly 6% of the US population with a prospective growth to 366 million by 2030. Understanding the function of metabolic networks in diabetes, as proposed herein, is a prerequisite for designing rational therapeutic strategies directed to prevent or manage the disease without producing side effects. The innovative strength of our approach resides in the integrative view of metabolic networks associated with energetic and redox systems in the cell, whose control and regulation is critical for diabetes.