Zhang Fengli, Dossey Aaron T, Zachariah Cherian, Edison Arthur S, Brüschweiler Rafael
National High Magnet Field Laboratory, Florida State University, Tallahassee, Florida 32310, USA.
Anal Chem. 2007 Oct 15;79(20):7748-52. doi: 10.1021/ac0711586. Epub 2007 Sep 7.
Elucidation of the composition of chemical-biological samples is a main focus of systems biology and metabolomics. Due to the inherent complexity of these mixtures, reliable, efficient, and potentially automatable methods are needed to identify the underlying metabolites and natural products. Because of its rich chemical information content, nuclear magnetic resonance (NMR) spectroscopy has a unique potential for this task. Here we present a generalization and application of a recently introduced NMR data collection, processing, and analysis strategy that circumvents the need for extensive purification and hyphenation prior to analysis. It uses covariance TOCSY NMR spectra measured on a 1-mm high-temperature cryogenic probe that are analyzed by a spectral trace clustering algorithm yielding 1D NMR spectra of the individual components for their unambiguous identification. The method is demonstrated on a metabolic model mixture and is then applied to the unpurified venom mixture of an individual walking stick insect that contains several slowly interconverting and closely related metabolites.
阐明化学生物学样品的组成是系统生物学和代谢组学的主要研究重点。由于这些混合物固有的复杂性，需要可靠、高效且可能自动化的方法来识别潜在的代谢物和天然产物。由于其丰富的化学信息含量，核磁共振（NMR）光谱在这项任务中具有独特的潜力。在此，我们展示了一种最近引入的NMR数据收集、处理和分析策略的推广及应用，该策略避免了在分析前进行广泛的纯化和联用。它使用在1毫米高温低温探头上测量的协方差TOCSY NMR光谱，通过光谱迹聚类算法进行分析，得到各个组分的一维NMR光谱以进行明确鉴定。该方法在代谢模型混合物上得到了验证，然后应用于单个竹节虫的未纯化毒液混合物，该毒液混合物含有几种缓慢相互转化且密切相关的代谢物。
