Advanced Methods in NMR Based Metabolomics

描述（由申请人提供）：拟议的工作重点是进一步开发用于代谢组学研究的核磁共振（NMR）光谱学先进方法。基于NMR的代谢组学已被证明是用于鉴定各种不同生物状态中的代谢扰动的有力方法， 样本类型。沿着质谱法，NMR光谱法是一个强大的和可重复的平台，用于进行代谢物分析，用于许多应用，包括早期疾病诊断，治疗监测，药物开发和系统生物学的基础研究。虽然已知代谢组提供生物状态的瞬时快照，但由于生物样品中重叠信号的复杂性，健康和疾病的潜在生物标志物的鉴定和验证具有挑战性。在过去的资助期间，我们开发了一套新的先进的NMR工具，可以用来解决这个问题，并表明我们可以显着提高NMR的能力，解剖复杂的样品，并确定敏感和特定的代谢物生物标志物候选人。特别是，我们表明，通过使用同位素标记策略，我们可以将检测限提高5至10倍，并将NMR可检测代谢物的数量增加相似的因子。我们表明，NMR和质谱法可以以互补的方式一起使用，以建立高度准确的代谢物谱。我们还表明，选择性TOCSY可用于消除不感兴趣的背景信号，以改善生物标志物的发现和样品的分类。并发展了LC-NMR和微线圈NMR方法用于代谢物的鉴定。目前的提案集中在将这些方法结合在一起，以建立一个强大的NMR平台，用于定量血液，尿液或细胞提取物样品中的100多种代谢物。我们将开发一个全面的方法，包括同位素标记的代谢物的扩展库未知的识别。我们建议对该系统进行优化，使其可以在适量（100 L）的样品上运行，同时保持定量约50种代谢物的能力。正如本文所提议的，这种方法的全面发展将改变当前基于核磁共振的代谢组学范式，并为当前基于MS的方法提供更强有力的补充。还讨论了这些方法在一组商业血清样本、尿液和细胞提取物上的验证，以及这些新方法与当前方法的比较。如果这项工作取得成功，我们将为先进的代谢组学研究提供一个大大改进的NMR平台，该平台将适用于从早期疾病检测和治疗监测到系统生物学基础研究的一系列研究。

DESCRIPTION (provided by applicant): The proposed work focuses on the further development of advanced methods in nuclear magnetic resonance (NMR) spectroscopy for metabolomics-based studies. NMR-based metabolomics has been shown to be a powerful methodology for identifying metabolic perturbations in a variety of different biological states and sample types. Along with mass spectrometry, NMR spectroscopy is a robust and reproducible platform for conducting metabolite profiling for a number of applications including early disease diagnosis, treatment monitoring, drug development and basic investigations in systems biology. While the metabolome is known to provide an instantaneous snap-shot of biological status, the identification and validation of potential biomarkers of health and disease is challenging due to the complexity of their overlapping signals in biological samples. During the past grant period we developed a new set of advanced NMR tools that can be brought to bear on this problem, and showed that we can significantly increase the ability of NMR to dissect the complex samples and identify sensitive and specific metabolite biomarker candidates. In particular we showed that by using an isotope tagging strategy we could improve the limit of detection by 5 to 10-fold and increase the number of NMR-detectible metabolites by a similar factor. We showed that the NMR and mass spectrometry can be used together in a complimentary fashion to build highly accurate metabolite profiles. We also showed that selective TOCSY could be used to eliminate uninteresting background signals to improve biomarker discovery and the classification of samples. And we developed LC-NMR and microcoil NMR methods for metabolite identification. The current proposal focuses on the bringing these approaches together to build out a robust NMR platform for quantifying over 100 metabolites in a blood, urine or cell extract sample. We will develop a comprehensive approach for unknown identification including an expanded library of isotope tagged metabolites. And we propose to miniaturize this system such that it can be run on a modest amount (100 ¿L) of sample while maintaining an ability to quantify approximately 50 metabolites. The full development of this approach, as proposed here, would change the current paradigm in NMR-based metabolomics and provide an even stronger complement to current MS-based methods. Validation of these methods on a set of commercial serum samples, urine and cell extracts, and a comparison of these new approaches to current methods are also discussed. If this work is successful, we will have provided a much improved NMR platform for advanced metabolomics studies that will be applicable to a range of studies from early disease detection and therapy monitoring to basic studies of systems biology.