Quantitative NMR Methods in Metabolomics.
Quantitative NMR Methods in Metabolomics.
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代谢组学中的定量 NMR 方法。
DOI：
10.1007/164_2022_612
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发表时间：
2023
影响因子：
--
通讯作者：
Raftery,Daniel
中科院分区：
文献类型：
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作者：
NaganaGowda,GA;Raftery,Daniel
核磁共振（NMR）光谱是代谢组学领域的两个主要分析平台之一，另一个是质谱（MS）。NMR的灵敏度低于MS，因此它只能检测到相对较少的代谢物。然而，NMR显示出许多独特的特性，包括其高重现性和非破坏性，其明确识别未知代谢物的能力，以及其获得所有检测到的代谢物的绝对浓度的能力，有时甚至没有内标。这些特征超过了NMR在代谢组学应用中相对较低的灵敏度和分辨率。由于生物混合物是高度复杂的，对新方法的需求不断增加，以改善检测，更好地识别未知的代谢物，并提供更准确的定量继续有增无减。迄今为止，技术和方法的进步有助于提高分辨率和灵敏度，并有助于检测大量代谢物信号。致力于测量未知代谢物信号的努力已经导致鉴定和定量扩大的代谢物池，包括不稳定的代谢物，如细胞氧化还原辅酶、能量辅酶和抗氧化剂。本章介绍了代谢组学中的定量NMR方法，重点是最近的方法学发展，同时强调了基于NMR的代谢组学的好处和挑战。
Nuclear Magnetic Resonance (NMR) spectroscopy is one of the two major analytical platforms in the field of metabolomics, the other being mass spectrometry (MS). NMR is less sensitive than MS and hence it detects a relatively small number of metabolites. However, NMR exhibits numerous unique characteristics including its high reproducibility and non-destructive nature, its ability to identify unknown metabolites definitively, and its capabilities to obtain absolute concentrations of all detected metabolites, sometimes even without an internal standard. These characteristics outweigh the relatively low sensitivity and resolution of NMR in metabolomics applications. Since biological mixtures are highly complex, increased demand for new methods to improve detection, better identify unknown metabolites, and provide more accurate quantitation continues unabated. Technological and methodological advances to date have helped to improve the resolution and sensitivity and detection of a larger number of metabolite signals. Efforts focused on measuring unknown metabolite signals have resulted in the identification and quantitation of an expanded pool of metabolites including labile metabolites such as cellular redox coenzymes, energy coenzymes, and antioxidants. This chapter describes quantitative NMR methods in metabolomics with an emphasis on recent methodological developments, while highlighting the benefits and challenges of NMR-based metabolomics.