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实时代谢组学分析饥饿和生长代谢转换。

Real-time metabolome profiling of the metabolic switch between starvation and growth.

机构信息

Institute of Molecular Systems Biology, Eidgenössische Technische Hochschule (ETH) Zurich, Zurich, Switzerland.

出版信息

Nat Methods. 2015 Nov;12(11):1091-7. doi: 10.1038/nmeth.3584. Epub 2015 Sep 14.

Abstract

Metabolic systems are often the first networks to respond to environmental changes, and the ability to monitor metabolite dynamics is key for understanding these cellular responses. Because monitoring metabolome changes is experimentally tedious and demanding, dynamic data on time scales from seconds to hours are scarce. Here we describe real-time metabolome profiling by direct injection of living bacteria, yeast or mammalian cells into a high-resolution mass spectrometer, which enables automated monitoring of about 300 compounds in 15-30-s cycles over several hours. We observed accumulation of energetically costly biomass metabolites in Escherichia coli in carbon starvation-induced stationary phase, as well as the rapid use of these metabolites upon growth resumption. By combining real-time metabolome profiling with modeling and inhibitor experiments, we obtained evidence for switch-like feedback inhibition in amino acid biosynthesis and for control of substrate availability through the preferential use of the metabolically cheaper one-step salvaging pathway over costly ten-step de novo purine biosynthesis during growth resumption.

摘要

代谢系统通常是对环境变化做出响应的第一道网络,而监测代谢物动态的能力是理解这些细胞反应的关键。由于监测代谢组变化在实验上既繁琐又费力,因此缺乏时间尺度在秒到小时范围内的动态数据。在这里,我们描述了通过将活细菌、酵母或哺乳动物细胞直接注入高分辨率质谱仪来进行实时代谢组分析的方法,该方法能够在几个小时内以 15-30 秒的周期自动监测大约 300 种化合物。我们观察到在碳饥饿诱导的大肠杆菌静止期,能量消耗大的生物量代谢物积累,以及在生长恢复时这些代谢物的快速利用。通过将实时代谢组分析与建模和抑制剂实验相结合,我们获得了证据表明在氨基酸生物合成中存在开关样反馈抑制,并且在生长恢复期间,通过优先利用代谢上更便宜的一步补救途径而不是昂贵的十步从头嘌呤生物合成来控制底物可用性。

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