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Linking metabolic activity with drug sensitivity using metabolic influence networks

使用代谢影响网络将代谢活动与药物敏感性联系起来

基本信息

批准号：
10620835
负责人：
Sriram Chandrasekaran
金额：
$ 36.64万
依托单位：
UNIVERSITY OF MICHIGAN AT ANN ARBOR
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-08-01 至 2025-05-31
项目状态：
未结题

项目摘要

Project Summary The impact of cellular metabolism on drug susceptibility has been observed in a wide range of organisms and cell types. However, how metabolism influences the activity of diverse classes of drugs has not been systematically explored. Linking metabolism and drug sensitivity has been a challenge due to both the impact of metabolism on numerous cellular processes, and the complexity of drug response. To address this, a combination of cutting-edge experimental and computational systems-biology tools will be applied to dissect the mechanisms by which cellular metabolism impacts the activity of drugs. The overall goal of my lab is to develop systems biology algorithms to reconstruct metabolic regulation and harness it for drug discovery. Here we propose to develop a new approach to link metabolism with various cellular process, called the ‘metabolic influence network’. We will use it to predict the impact of metabolic activity of a cell on drugs that inhibit diverse cellular processes. This framework will be applied to E. coli, yeast and human cell lines, allowing us to uncover conserved principles linking metabolism with potency of drugs that target cellular processes such as replication, transcription or signaling. This approach will be tested experimentally by altering cellular metabolic state and drug sensitivity with nutrient screens, enzyme inhibitors and drug combinations. Our systems approach will allow us to quantify the myriad effects of cell metabolism on drug action, including uptake, collateral interactions, and efflux. Ultimately, this research program can help precision medicine efforts by matching therapy based on cellular metabolic activity and the in vivo metabolic environment.

项目摘要细胞代谢对药物敏感性的影响已在广泛的生物体中观察到，细胞类型。然而，代谢如何影响不同类别药物的活性还没有被证实。系统地探索。由于代谢和药物敏感性的影响，以及药物反应的复杂性。为了解决这个问题，A 结合尖端的实验和计算系统-生物学工具将被应用于解剖细胞代谢影响药物活性的机制。我实验室的总体目标是开发系统生物学算法，以重建代谢调节并利用它进行药物发现。这里我们建议开发一种新的方法，将代谢与各种细胞过程联系起来，称为“代谢影响网络”。我们将用它来预测细胞的代谢活动对抑制多种药物的影响。细胞过程该框架将应用于E.大肠杆菌，酵母和人类细胞系，使我们能够揭示将代谢与靶向细胞过程的药物效力联系起来的保守原则，复制、转录或信号传导。这种方法将通过改变细胞代谢来进行实验测试。状态和药物敏感性与营养筛选，酶抑制剂和药物组合。我们的系统这种方法将使我们能够量化细胞代谢对药物作用的无数影响，包括摄取，侧支相互作用和外排。最终，这项研究计划可以通过以下方式帮助精准医学工作：基于细胞代谢活性和体内代谢环境的匹配治疗。

项目成果

期刊论文数量（9）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Metabolic signatures of regulation by phosphorylation and acetylation.

DOI：
10.1016/j.isci.2021.103730
发表时间：
2022-01-21
期刊：
iScience
影响因子：
5.8
作者：
Smith K;Shen F;Lee HJ;Chandrasekaran S
通讯作者：
Chandrasekaran S

Next-Generation Genome-Scale Metabolic Modeling through Integration of Regulatory Mechanisms.

DOI：
10.3390/metabo11090606
发表时间：
2021-09-07
期刊：
Metabolites
影响因子：
4.1
作者：
Chung CH;Lin DW;Eames A;Chandrasekaran S
通讯作者：
Chandrasekaran S

Single-cell RNA-sequencing identifies anti-cancer immune phenotypes in the early lung metastatic niche during breast cancer.

DOI：
10.1007/s10585-022-10185-4
发表时间：
2022-12
期刊：
CLINICAL & EXPERIMENTAL METASTASIS
影响因子：
4
作者：
Orbach, Sophia M.;Brooks, Michael D.;Zhang, Yining;Campit, Scott E.;Bushnell, Grace G.;Decker, Joseph T.;Rebernick, Ryan J.;Chandrasekaran, Sriram;Wicha, Max S.;Jeruss, Jacqueline S.;Shea, Lonnie D.
通讯作者：
Shea, Lonnie D.

Acetyl-CoA metabolism drives epigenome change and contributes to carcinogenesis risk in fatty liver disease.