The role of nitrogen metabolism in smooth muscle cell phenotypic plasticity

在美国，冠状动脉是主要的死亡原因。而降脂和降压药物则有 自20世纪80年代以来，这些疗法帮助降低了大约50%的CAD相关死亡率，这些疗法只改变了 冠心病危险因素。到目前为止，还没有批准的药物直接作用于血管壁来对抗动脉粥样硬化， 冠心病的根本原因。开发新疗法的一个机会是通过遗传学：冠心病部分是 可遗传的和最近的全基因组关联研究发现，超过200个基因座与高血压的风险增加有关 CAD。虽然40%的这些CAD基因座与已知的危险因素建立了关联，但分子和 其余60%的CAD基因座的细胞机制尚不清楚。这些未知基因中的大多数 预计通过调节疾病发生的血管壁中的基因表达来发挥作用。 血管平滑肌细胞(SMCs)是构成动脉中层的细胞，在动脉的生长发育中起着至关重要的作用。 动脉粥样硬化的进展，冠状动脉疾病的先兆。在开始和发展的过程中 动脉粥样硬化，SMC从静止(健康)表型转化为增殖(病理)表型 代表肌源性、骨软骨性和巨噬细胞样表型的表型 斑块堆积。识别SMC表型可塑性的分子机制将开辟新的 冠心病的治疗途径。基于RNAseq数据的共表达网络保存分析 151例多民族平滑肌细胞供者升主动脉的静止期和增殖期培养 在不同的条件下，分别显示了富含氮代谢的表型特定的网络结构 流程。先前的研究表明，代谢途径不仅与表型变化有关 血管壁中其他类型的细胞，但也有能力驱动它们。因此，这一目标是 建议对氮代谢在SMC表型可塑性中的作用进行表征，并找出关键 调控基因驱动着调控失调。该项目将通过两个AIMS解决这一问题。在《目标1》中，我将 研究氮代谢在动脉粥样硬化进展中的作用 代谢组学、细胞类型标记鉴定和细胞表型分析相结合的方法 对氮代谢途径的激活或沉默的反应。在目标2中，我将创建贝叶斯 基于基因表达数据的氮代谢过程基因网络(BN) 从时间序列实验中产生的转录因子-基因表达关系 促动脉粥样硬化的ATACseq峰和差异表达的RNAseq峰 刺激。然后我将确定氮代谢途径的关键驱动基因(KDS)，这些基因的表达 调节整个基因表达网络的变化。功能增益和功能损耗实验 对于在SMC中使用慢病毒颗粒的KDS，将通过细胞表型分析来量化 对SMC增殖、迁移和去分化的影响。

Coronary artery is the leading cause of death in the US. While lipid-lowering and anti-hypertensive drugs have helped decrease CAD-related mortality by approximately 50% since the 1980s, these therapies only modify CAD risk factors. To date, no approved drug acts at the vascular wall directly against atherosclerosis, the underlying cause of CAD. One opportunity to develop novel therapies is through genetics: CAD is partially heritable, and recent genome-wide association studies identified over 200 loci associated with elevated risk for CAD. While 40% of these CAD loci having established associations with known risk factors, the molecular and cellular mechanisms of the remaining 60% of the CAD loci are unknown. The majority of these unknown loci are predicted to function by regulating gene expression in the vascular wall where the disease develops. Vascular smooth muscle cells (SMCs), which make up the medial layer of arteries, play a critical role in the progression of atherosclerosis, the precursor to coronary artery disease. During initiation and progression of atherosclerosis, SMCs transdifferentiate from a quiescent (healthy) phenotype to a proliferative (pathological) phenotype representative of myogenic, osteochondrogenic, and macrophage-like phenotypes that contribute to plaque build-up. Identifying the molecular mechanisms driving SMC phenotypic plasticity will open up new avenues of treatment for CAD. Preservation analysis of co-expression networks from RNAseq data generated from the ascending aortas of 151 multi-ethnic smooth muscle cell donors cultured in quiescent and proliferative conditions, respectively, revealed phenotype-specific network architecture enriched for nitrogen metabolic processes. Previous studies have shown that metabolic pathways are not only involved in phenotypic changes of other cell types in the vascular wall, but also have the capability to drive them. Therefore, the goal of this proposal is to characterize the role nitrogen metabolism plays in SMC phenotypic plasticity and identify the key regulatory genes driving dysregulation. The project will address this problem through 2 aims. In aim 1, I will characterize the role nitrogen metabolism plays in SMCs during the progression of atherosclerosis using a combined approach of metabolomics, cell type marker identification, and cellular phenotyping assays in response to activation or silencing of the nitrogen metabolism pathway. In aim 2, I will create Bayesian networks (BNs) of genes involved in nitrogen metabolic processes using gene expression data and transcription factor-gene expression relationships generated from time-series experiments linking differentially expressed ATACseq peaks and differentially expressed RNAseq peaks in response to pro-atherogenic stimulus. I will then identify the key driver genes (KDs) of nitrogen metabolic pathways whose expression regulates the changes across the gene expression networks. Gain-of-function and loss-of-function experiments for KDs in SMCs using lentiviral particles will be completed with cellular phenotyping assays to quantify the impact on SMC proliferation, migration, and de-differentiation.