Metabolite sensing and signaling in cell metabolism.
Metabolite sensing and signaling in cell metabolism.
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细胞代谢中的代谢传感和信号传导。
DOI：
10.1038/s41392-018-0024-7
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发表时间：
2018
影响因子：
39.3
通讯作者：
Lei QY
中科院分区：
文献类型：
--
作者：
Wang YP;Lei QY
代谢物感知是最基本的生物过程之一。在进化过程中，发展了多层机制来感知包括营养物质在内的广泛代谢物的波动，以协调细胞新陈代谢和生物网络。到目前为止，AMPK和mTOR信号通路是最被理解的代谢物感知和信号通路之一。在这里，我们提出了一个传感器-传感器-效应器模型来描述已知的代谢物感知和信号传递机制。我们根据其特异性、动态性和功能性来定义代谢物传感器。我们将代谢物感知的作用分为三种不同的模式：代谢物传感器介导的信号传递、代谢物感知模块和共轭感知。通过这些作用模式，我们提供了细胞如何感知糖、脂、氨基酸和代谢中间产物的系统视图。在未来的展望中，我们建议系统地筛选代谢物感知大分子，高通量地发现生物大分子-代谢物相互作用，以及功能代谢组学，以促进我们对代谢物感知和信号传递的了解。最重要的是，靶向代谢物感应在代谢性疾病的治疗干预和改善健康衰老方面有着巨大的前景。一个简单的三部分模型提供了细胞如何感知糖、脂、氨基酸和代谢中间体的系统视图。细胞快速而准确地感知细胞内外分子的变化，如营养物质，以应对不断变化的环境。上海复旦大学的王一平和雷群英在现有的AMPK和mTORC1信号转导知识的基础上，提出了一个模型，在该模型中，传感器、传感器和效应器三个组件使代谢传感和信号转导得以进行。传感器检测代谢物，并通过结合、构象变化或蛋白质-蛋白质相互作用，将这些信息传输到换能器，由换能器决定适当的反应。传感器然后向协调动作的效应器蛋白质发出命令。未来通过系统筛选识别新的代谢传感器可能导致对代谢和年龄相关疾病的新的治疗干预措施。
Metabolite sensing is one of the most fundamental biological processes. During evolution, multilayered mechanisms developed to sense fluctuations in a wide spectrum of metabolites, including nutrients, to coordinate cellular metabolism and biological networks. To date, AMPK and mTOR signaling are among the best-understood metabolite-sensing and signaling pathways. Here, we propose a sensor-transducer-effector model to describe known mechanisms of metabolite sensing and signaling. We define a metabolite sensor by its specificity, dynamicity, and functionality. We group the actions of metabolite sensing into three different modes: metabolite sensor-mediated signaling, metabolite-sensing module, and sensing by conjugating. With these modes of action, we provide a systematic view of how cells sense sugars, lipids, amino acids, and metabolic intermediates. In the future perspective, we suggest a systematic screen of metabolite-sensing macromolecules, high-throughput discovery of biomacromolecule-metabolite interactomes, and functional metabolomics to advance our knowledge of metabolite sensing and signaling. Most importantly, targeting metabolite sensing holds great promise in therapeutic intervention of metabolic diseases and in improving healthy aging. A simple, three-part model provides a systematic view of how cells sense sugars, lipids, amino acids and metabolic intermediates. Cells quickly and accurately perceive changes in intra- and extracellular molecules such as nutrients to respond to changing environments. Drawing on existing knowledge about AMPK and MTORC1 signaling, Yi-Ping Wang and Qun-Ying Lei at Fudan University in Shanghai propose a model in which three components: a sensor, transducer and effector enable metabolic sensing and signaling to proceed. The sensor detects the metabolite, and, through conjugation, conformational changes or protein–protein interactions, transmits this information to the transducer, which decides the appropriate response. The transducer then issues orders to effector proteins which coordinate the action. The future identification of novel metabolic sensors through systematic screening could lead to new therapeutic interventions for metabolic and age-related diseases.
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影响因子：
13.5
作者：
Dai H;Sinclair DA;Ellis JL;Steegborn C
通讯作者：
Steegborn C
AMP激活的蛋白激酶对ULK1（HATG1）的磷酸化将能量传感连接到线粒体。
DOI：
10.1126/science.1196371
发表时间：
2011-01-28
期刊：
Science (New York, N.Y.)
影响因子：
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Egan DF;Shackelford DB;Mihaylova MM;Gelino S;Kohnz RA;Mair W;Vasquez DS;Joshi A;Gwinn DM;Taylor R;Asara JM;Fitzpatrick J;Dillin A;Viollet B;Kundu M;Hansen M;Shaw RJ
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影响因子：
64.8
作者：
Dekel, E;Alon, U
通讯作者：
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丙酮酸激酶M2激活剂促进四聚体形成并抑制肿瘤发生。
影响因子：
14.8
作者：
Anastasiou, Dimitrios;Yu, Yimin;Israelsen, William J.;Jiang, Jian-Kang;Boxer, Matthew B.;Hong, Bum Soo;Tempel, Wolfram;Dimov, Svetoslav;Shen, Min;Jha, Abhishek;Yang, Hua;Mattaini, Katherine R.;Metallo, Christian M.;Fiske, Brian P.;Courtney, Kevin D.;Malstrom, Scott;Khan, Tahsin M.;Kung, Charles;Skoumbourdis, Amanda P.;Veith, Henrike;Southall, Noel;Walsh, Martin J.;Brimacombe, Kyle R.;Leister, William;Lunt, Sophia Y.;Johnson, Zachary R.;Yen, Katharine E.;Kunii, Kaiko;Davidson, Shawn M.;Christofk, Heather R.;Austin, Christopher P.;Inglese, James;Harris, Marian H.;Asara, John M.;Stephanopoulos, Gregory;Salituro, Francesco G.;Jin, Shengfang;Dang, Lenny;Auld, Douglas S.;Park, Hee-Won;Cantley, Lewis C.;Thomas, Craig J.;Heiden, Matthew G. Vander
通讯作者：
Heiden, Matthew G. Vander
DOI：
10.1126/science.aao3265
发表时间：
2017-11-10
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Gu X;Orozco JM;Saxton RA;Condon KJ;Liu GY;Krawczyk PA;Scaria SM;Harper JW;Gygi SP;Sabatini DM
通讯作者：
Sabatini DM