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研究干细胞代谢的分析策略。

Analytical strategies for studying stem cell metabolism.

作者信息

Arnold James M, Choi William T, Sreekumar Arun, Maletić-Savatić Mirjana

机构信息

Department of Molecular and Cell Biology, Baylor College of Medicine, Houston, TX 77030, USA.

Program in Developmental Biology and Medical Scientist Training Program, Baylor College of Medicine; Jan and Dan Duncan Neurological Research Institute at Texas Children's Hospital, Houston, TX 77030, USA.

出版信息

Front Biol (Beijing). 2015 Apr;10(2):141-153. doi: 10.1007/s11515-015-1357-z.

Abstract

Owing to their capacity for self-renewal and pluripotency, stem cells possess untold potential for revolutionizing the field of regenerative medicine through the development of novel therapeutic strategies for treating cancer, diabetes, cardiovascular and neurodegenerative diseases. Central to developing these strategies is improving our understanding of biological mechanisms responsible for governing stem cell fate and self-renewal. Increasing attention is being given to the significance of metabolism, through the production of energy and generation of small molecules, as a critical regulator of stem cell functioning. Rapid advances in the field of metabolomics now allow for in-depth profiling of stem cells both and , providing a systems perspective on key metabolic and molecular pathways which influence stem cell biology. Understanding the analytical platforms and techniques that are currently used to study stem cell metabolomics, as well as how new insights can be derived from this knowledge, will accelerate new research in the field and improve future efforts to expand our understanding of the interplay between metabolism and stem cell biology.

摘要

由于干细胞具有自我更新和多能性的能力,通过开发治疗癌症、糖尿病、心血管疾病和神经退行性疾病的新型治疗策略,它们在革新再生医学领域方面具有巨大潜力。制定这些策略的核心是加深我们对负责控制干细胞命运和自我更新的生物学机制的理解。作为干细胞功能的关键调节因子,新陈代谢通过产生能量和生成小分子,其重要性正日益受到关注。代谢组学领域的快速发展现在使得能够对干细胞进行深入的分析,从而提供关于影响干细胞生物学的关键代谢和分子途径的系统观点。了解目前用于研究干细胞代谢组学的分析平台和技术,以及如何从这些知识中获得新的见解,将加速该领域的新研究,并改善未来扩大我们对新陈代谢与干细胞生物学之间相互作用理解的努力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5434/4512307/1993caee67b1/nihms686881f1.jpg

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本文引用的文献

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Extraction parameters for metabolomics from cultured cells.从培养细胞中提取代谢组学的参数。
Anal Biochem. 2015 Apr 15;475:22-8. doi: 10.1016/j.ab.2015.01.003. Epub 2015 Jan 19.
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In vivo single-cell detection of metabolic oscillations in stem cells.干细胞中代谢振荡的体内单细胞检测
Cell Rep. 2015 Jan 6;10(1):1-7. doi: 10.1016/j.celrep.2014.12.007. Epub 2014 Dec 24.
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Extraction for metabolomics: access to the metabolome.代谢组学提取:获取代谢组
Phytochem Anal. 2014 Jul-Aug;25(4):291-306. doi: 10.1002/pca.2505. Epub 2014 Feb 13.

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