文献类型：期刊文献

中文题名：Spatiotemporal Imaging of Cellular Energy Metabolism with Genetically-Encoded Fluorescent Sensors in Brain

英文题名：Spatiotemporal Imaging of Cellular Energy Metabolism with Genetically-Encoded Fluorescent Sensors in Brain

作者：Zhuo Zhang[1,2];Weicai Chen[1,2];Yuzheng Zhao[1,2];Yi Yang[1,3]

机构：[1]Synthetic Biology and Biotechnology Laboratory, State Key Laboratory of Bioreactor Engineering, Shanghai Collaborative Innovation Center for Biomanufacturing Technology,East China University of Science and Technology;[2]Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology;[3]Optogenetics and Synthetic Biology Interdisciplinary Research Center, CAS Center for Excellence in Brain Science, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences

年份：2018

卷号：34

期号：5

起止页码：875

中文期刊名：Neuroscience Bulletin

外文期刊名：神经科学通报（英文版）

收录：CSTPCD;;Scopus;CSCD:【CSCD2017_2018】；PubMed;

基金：supported by the National Key Research and Development Program of China(2017YFA050400 and2017YFC0906900);the National Natural Science Foundation of China(31722033,91649123,31671484,31225008,and 31470833);the Shanghai Science and Technology Commission(14XD1401400,16430723100,and 15YF1402600);Young Elite Scientists Sponsorship Program by China Association for Science and Technology(to YZ);Shanghai Young Top-notch Talent(to YZ);the State Key Laboratory of Bioreactor Engineering(to YY);Fundamental Research Funds for the Central Universities(to YY and YZ)

语种：英文

中文关键词：Energy metabolism;Astrocyte;Neuron;Genetically encoded fluorescent sensor;Real time monitoring

外文关键词：Energy metabolism;Astrocyte;Neuron;Genetically encoded fluorescent sensor;Real time monitoring

摘要：The brain has very high energy requirements and consumes 20% of the oxygen and 25% of the glucose in the human body. Therefore, the molecular mechanism under- lying how the brain metabolizes substances to support neural activity is a fundamental issue for neuroscience studies. A well-known model in the brain, the astrocyte- neuron lactate shuttle, postulates that glucose uptake and glycolytic activity are enhanced in astrocytes upon neu- ronal activation and that astrocytes transport lactate into neurons to fulfill their energy requirements. Current evidence for this hypothesis has yet to reach a clear consensus, and new concepts beyond the shuttle hypothesis are emerging. The discrepancy is largely attributed to the lack of a critical method for real-time monitoring of metabolic dynamics at cellular resolution. Recent advances in fluorescent protein-based sensors allow the generation of a sensitive, specific, real-time readout of subcellular metabolites and fill the current technological gap. Here,we summarize the development of genetically encoded metabolite sensors and their applications in assessing cell metabolism in living cells and in vivo, and we believe that these tools will help to address the issue of elucidating neural energy metabolism.
The brain has very high energy requirements and consumes 20% of the oxygen and 25% of the glucose in the human body. Therefore, the molecular mechanism under- lying how the brain metabolizes substances to support neural activity is a fundamental issue for neuroscience studies. A well-known model in the brain, the astrocyte- neuron lactate shuttle, postulates that glucose uptake and glycolytic activity are enhanced in astrocytes upon neu- ronal activation and that astrocytes transport lactate into neurons to fulfill their energy requirements. Current evidence for this hypothesis has yet to reach a clear consensus, and new concepts beyond the shuttle hypothesis are emerging. The discrepancy is largely attributed to the lack of a critical method for real-time monitoring of metabolic dynamics at cellular resolution. Recent advances in fluorescent protein-based sensors allow the generation of a sensitive, specific, real-time readout of subcellular metabolites and fill the current technological gap. Here,we summarize the development of genetically encoded metabolite sensors and their applications in assessing cell metabolism in living cells and in vivo, and we believe that these tools will help to address the issue of elucidating neural energy metabolism.