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，这是一种复杂的疾病， 糖、胆固醇和甘油三酯。代谢综合征患者有很高的心血管疾病风险 因为血液代谢物之间的相互作用然而，由于我们没有很好的方法， 通过研究综合的和相互作用的代谢变化，我们对每一种代谢异常进行单独治疗。作为 因此，患者经常服用多种药物，可能会降低每种药物恢复正常的能力。 血液代谢产物和增加负面药物相互作用的风险。 在这个项目中，我们提出了一种新的综合实验和计算生物工程方法， 研究代谢异常如何导致心血管疾病。具体来说，我们将研究代谢 血管内皮细胞和血管平滑肌之间的相互作用 细胞，当它们改变功能时，会导致心血管疾病。我们将设计一个 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 光谱数据来估计细胞内代谢通量和代谢物转运。计算模型 将使我们能够发展新的假设，并计划研究如何代谢变化（从改变血液 代谢物或疗法）影响血管壁。 我们假设EC代谢功能障碍增加了促进VSMC向内皮细胞转运的代谢物， 从收缩型转变为合成型。反过来，合成的vSMC增强EC代谢物转运， 支持扩散。为了探索这一假设，我们将结合联合收割机体外、计算机模拟和离体研究，以：1） 确定EC功能障碍在改变的代谢环境中如何影响代谢物转运; 2）测量如何 改变的代谢物协同地将vSMC转变为合成表型;和3）研究EC-vSMC如何 串扰影响血管壁中的细胞代谢和表型。 我们将从内皮细胞和血管平滑肌细胞的单细胞模型开始， 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， in silico硅，and ex体外.在每一步中，我们将把代谢与细胞表型和功能联系起来， 心血管疾病 整合内皮-血管平滑肌细胞代谢、转运、 和功能将使我们能够发展新的假设，并计划研究代谢如何从 改变的血液代谢物或治疗会影响血管壁。通过改变实质细胞类型， 然后可以扩展到研究其他组织中的血管代谢相互作用（例如，脑），并阐明 其中整合EC代谢和运输的其它疾病（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).