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DO 探针拉曼微光谱区分细胞器抗癌药物反应中大分子的代谢动力学。

DO-Probed Raman Microspectroscopy Distinguishes the Metabolic Dynamics of Macromolecules in Organellar Anticancer Drug Response.

机构信息

Single-Cell Center, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, 189 Songling Road, Qingdao 266101, Shandong, China.

University of Chinese Academy of Sciences, 19 Yuquan Road, Beijing 100049, China.

出版信息

Anal Chem. 2021 Feb 2;93(4):2125-2134. doi: 10.1021/acs.analchem.0c03925. Epub 2021 Jan 12.

Abstract

To profile the metabolic dynamics responding to drugs at the single-cell/organelle resolution, rapid and economical mechanism-revealing methods are required. Here, we introduced DO-probed Raman microspectroscopy in combination with the multivariate curve resolution-alternating least squares (MCR-ALS or MCR) algorithm. Exploiting MCR to deconvolute each macromolecular component specifically, the method is able to track and distinguish changes in lipid and protein metabolic activities in a human cancer cell line (MCF-7) and in , in response to the metabolism-inhibitory effect of rapamycin, which inhibits the mammalian/mechanistic target of rapamycin (mTOR) signaling. Under rapamycin, in the lipid bodies of cancer cells, metabolic activities of both protein and lipid are suppressed; in the nucleus, protein synthesis remains active, whereas lipid synthesis is inhibited; in the cytoplasm, syntheses of protein and lipid are both dose- and duration-dependent. Thus, rapamycin differentially influences protein and lipid synthesis in mTOR signaling. Moreover, the strong correlation between macromolecular-specific components of yeast and those in MCF-7 cytoplasm, nucleus, and lipid bodies revealed similarity in rapamycin response. Notably, highly metabolically active cancer cells after high-dosage rapamycin exposure (500 or 5000 × IC) were revealed, which escape detection by population-level cytotoxicity tests. Thus, by unveiling macromolecule-specific metabolic dynamics at the organelle level, the method is valuable to mechanism-based rapid screening and dissection of drug response.

摘要

为了在单细胞/细胞器分辨率下描绘药物代谢动力学,需要快速且经济的揭示机制的方法。在这里,我们引入了 DO 探针拉曼微光谱与多元曲线分辨交替最小二乘法(MCR-ALS 或 MCR)算法结合。利用 MCR 对每个大分子成分进行专门的解卷积,该方法能够跟踪和区分人癌细胞系(MCF-7)和酵母中脂类和蛋白质代谢活性的变化,以响应雷帕霉素的代谢抑制作用,雷帕霉素抑制哺乳动物/雷帕霉素机制靶点(mTOR)信号。在雷帕霉素作用下,在癌细胞的脂滴中,蛋白质和脂类的代谢活性均受到抑制;在细胞核中,蛋白质合成仍然活跃,而脂质合成受到抑制;在细胞质中,蛋白质和脂质的合成均呈剂量和时间依赖性。因此,雷帕霉素在 mTOR 信号中对蛋白质和脂质的合成有不同的影响。此外,酵母的大分子特异性成分与 MCF-7 细胞质、细胞核和脂滴中的成分之间的强相关性表明它们对雷帕霉素的反应具有相似性。值得注意的是,在高剂量雷帕霉素暴露(500 或 5000×IC)后,高度代谢活跃的癌细胞被揭示出来,这些细胞逃避了基于群体水平的细胞毒性测试的检测。因此,通过揭示细胞器水平的大分子特异性代谢动力学,该方法对于基于机制的快速筛选和药物反应的剖析具有重要价值。

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