Metabolic interactions in the vascular wall: an integrated experimental and computational approach

项目摘要 近三分之一的美国成年人患有代谢综合征，这是一种由血液升高定义的复杂疾病 糖、胆固醇和甘油三酯。代谢综合征患者患心血管疾病的风险很高 由于升高的血液代谢物之间的相互作用。然而，由于我们没有好的方法来解决 研究整体和相互作用的代谢变化，我们单独治疗每一种代谢异常。作为一名 结果，患者经常服用多种药物，潜在地降低了每种药物恢复正常的能力 血液中的代谢物，增加了药物相互作用的风险。 在这个项目中，我们提出了一种新的集成实验和计算的生物工程方法来 研究代谢异常如何导致心血管疾病。具体来说，我们将研究新陈代谢 排列在血管内侧的内皮细胞与血管平滑肌之间的相互作用 细胞，当它们改变自己的功能时，它们会导致心血管疾病。我们将设计一种 计算同位素辅助代谢通量分析(IMFA)模型，该模型使用实验质量 用于估计细胞内代谢通量和代谢物运输的光谱数据。计算模型 将使我们能够开发新的假设，并计划研究新陈代谢如何变化(从改变的血液 代谢物或疗法)会影响血管壁。 我们假设，EC代谢功能障碍增加了代谢物的运输，从而促进VSMC 从收缩的表型转变为合成的表型。反过来，合成的vSMC增强EC代谢物的转运 支持扩散。为了探索这一假设，我们将结合体外、硅胶和体外研究：1) 确定在改变的代谢环境中EC功能障碍如何影响代谢物运输；2)测量 改变的代谢物协同将vSMC转变为合成表型；以及3)研究EC-vSMC如何 串扰影响细胞新陈代谢和维管壁的表型。 我们将从内皮细胞和血管平滑肌细胞的单细胞模型开始，它将模拟 人类营养水平的多样性。我们将整合这两种细胞类型，以了解它们在体外的串扰， 在硅胶和体外实验中。在每一步，我们都会将新陈代谢与细胞表型和功能联系起来，从而将模型与 心血管疾病。 整合的内皮-血管平滑肌细胞代谢，运输， 和功能将使我们能够开发新的假设，并计划研究新陈代谢如何从 血液代谢物的改变或治疗会影响血管壁。通过改变实质细胞类型，模型 然后可以扩展到研究其他组织(例如大脑)中的血管代谢相互作用，并揭示 其他将EC代谢和运输结合在一起的疾病(例如阿尔茨海默病)。

Project Summary Nearly 1 in 3 American adults has metabolic syndrome, a complex disorder defined by elevations in blood sugar, cholesterol, and triglycerides. Patients with metabolic syndrome have a high cardiovascular disease risk due to interactions among the elevated blood metabolites. However, since we do not have good methods for studying integrated and interacting metabolic changes, we treat each metabolic abnormality individually. As a result, patients are often on multiple medications, potentially decreasing the ability of each drug to normalize blood metabolites and raising the risk for negative drug interactions. In this project, we propose a novel integrated experimental and computational bioengineering approach to study how metabolic abnormalities contribute to cardiovascular disease. Specifically, we will study metabolic interactions between endothelial cells, which line the inside of the blood vessels, and vascular smooth muscle cells, which contribute to cardiovascular disease when they change their function. We will engineer a computational isotope-assisted metabolic flux analysis (iMFA) model, which uses experimental mass spectrometry data to estimate intracellular metabolic fluxes and metabolite transport. The computational model will enable us to develop new hypotheses for and plan studies into how metabolic changes (from altered blood metabolites or therapies) affect the vascular wall. We hypothesize that EC metabolic dysfunction increases the transport of metabolites that promote VSMC to switch from a contractile to a synthetic phenotype. In turn, synthetic vSMC enhance EC metabolite transport to support proliferation. To explore this hypothesis, we will combine in vitro, in silico, and ex vivo studies to: 1) Determine how EC dysfunction in altered metabolic environments impacts metabolite transport; 2) Measure how altered metabolites synergistically shift vSMC to a synthetic phenotype; and 3) Investigate how EC-vSMC crosstalk impacts cell metabolism and phenotype in the vascular wall. We will start with single cell models of endothelial and vascular smooth muscle cells, which will simulate the diversity of human nutrient levels. We will the integrate the two cell types to understand their crosstalk in vitro, in silico, and ex vivo. At each step, we will relate metabolism to cell phenotype and function to link the model to cardiovascular disease. The computational iMFA model of integrated endothelial-vascular smooth muscle cell metabolism, transport, and function will enable us to develop new hypotheses for and plan studies into how metabolic changes from altered blood metabolites or therapies affect the vascular wall. By changing the parenchymal cell type, the model can then be extended to study vascular metabolic interactions in other tissues (e.g., brain) and shed light into other diseases in which integrated EC metabolism and transport (e.g., Alzheimer’s disease).