Advanced Methods in NMR-Based Metabolomics

描述(由申请人提供)：拟议的工作重点是开发基于代谢组学研究的核磁共振(核磁共振)光谱的先进方法。代谢组学领域的迅速发展，基于小分子代谢物信号的多重变化，提供了有关生物扰动的新信息。核磁共振波谱的新进展及其与质谱学和多元统计方法的结合，为疾病早期诊断、治疗监测、药物开发和系统生物学基础研究等生物学应用提供了一条很有前途的途径。虽然已知代谢组提供了健康状态的瞬时快照，但由于生物样本中潜在的生物标记物信号重叠的复杂性，识别和验证潜在的健康和疾病生物标记物是具有挑战性的。在过去的几年里，我们已经开发了一套新的先进的核磁共振工具，可以用来解决这个问题，承诺我们可以显著提高核磁共振分析复杂样品的能力，并识别敏感和特定的代谢物生物标记物候选。特别是，我们提出了三种先进的核磁共振方法，有望将生物体液中代谢物的检测极限提高10倍，并以类似的系数增加核磁共振可检测代谢物的数量。这一发展将改变目前基于核磁共振的代谢组学的范式，并为目前的基于MS的方法提供更强大的补充。对这些方法在一组商业血清样本上的验证以及这些新方法与当前方法的比较也进行了讨论。如果这项工作成功，我们将为从早期疾病检测和治疗监测到系统生物学基础研究的应用大大改进代谢组学研究奠定基础。公共卫生相关性这个项目寻求开发新的和先进的方法来识别血清和尿样中的疾病生物标记物。一旦完全发展起来，这些方法可以用来检测血液或尿液中的小分子，这些小分子表明各种疾病的发生。

DESCRIPTION (provided by applicant): The proposed work focuses on the development of advanced methods in nuclear magnetic resonance (NMR) spectroscopy for metabolomics-based studies. The rapidly expanding field of metabolomics provides new information on biological perturbations based on multiple changes in small molecule metabolite signals. New advances in NMR spectroscopy and their combination with mass spectrometry (MS) and multivariate statistical methods provide a promising approach for a number of biological 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 health 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. Over the past several years, we have developed a new set of advanced NMR tools that can be brought to bear on this problem, with the promise 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 propose three advanced NMR methods that are expected to improve the limit of detection of metabolites in biofluids by 10-fold and increase the number of NMR-detectible metabolites by a similar factor. This development 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 and a comparison of these new approaches to current methods are also discussed. If this work is successful, we will have laid the foundation for much improved metabolomics studies for applications ranging from early disease detection and therapy monitoring to basic studies of systems biology. PUBLIC HEALTH RELEVANCE This project seeks to develop new and advanced methods for identifying biomarkers of disease in serum and urine samples. When fully developed these approaches could be used to detect small molecules in the blood or urine that indicate the onset of various diseases.