Acquisition of an Automated Sample Changer for Advanced Methods in NMR-Based Metabolomics

获取用于基于 NMR 的代谢组学先进方法的自动进样器

• 批准号: 9025352
• 负责人: DANIEL RAFTERY
• 金额: $ 5.63万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-07-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9025352
• 关键词: Advanced Development; Area; Biological; Biological Markers; Blood; Cell Extracts; Chemicals; Chromatography; Classification; Complement; Complex; Detection; Development; Diagnostic; Disease; Drug Compounding; Drug toxicity; Goals; Grant; Health; Human; Investigation; Isotope Labeling; Isotopes; Laboratories; Libraries; Liquid Chromatography; Mass Spectrum Analysis; Metabolic; Methodology; Methods; Monitor; NMR Spectroscopy; Nature; Nuclear Magnetic Resonance; Nutritional Study; Outcome; Protocols documentation; Reproducibility; Resolution; Running; Sampling; Serum; Signal Transduction; Spectrum Analysis; Structure; System; Systems Biology; TOCSY; Techniques; Time; Urine; Ursidae Family; Validation; Work; base; biological systems; diagnostic assay; disease diagnosis; drug development; improved; malignant breast neoplasm; metabolomics; miniaturize; novel strategies; personalized medicine; programs; research study; small molecule; tool

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.

描述(由申请人提供)：拟议的工作重点是进一步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。基于核磁共振的代谢组学已被证明是一种强大的方法，用于识别各种不同生物状态和 样本类型。与质谱学一样，核磁共振波谱是一个强大且可重复的平台，可用于进行代谢物分析，应用范围包括疾病早期诊断、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了生物状态的瞬时快照，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。在过去的资助期间，我们开发了一套新的高级核磁共振工具，可以用于解决这个问题，并表明我们可以显著提高核磁共振分析复杂样品和识别敏感和特定代谢物生物标记候选的能力。特别是，我们表明，通过使用同位素标记策略，我们可以将检测极限提高5到10倍，并以类似的因素增加核磁共振可检测代谢物的数量。我们证明了核磁共振和质谱学可以以互补的方式一起使用，以建立高度准确的代谢物图谱。我们还表明，选择性TOCSY可以用来消除不感兴趣的背景信号，以改进生物标记物的发现和样品的分类。并建立了LC-核磁共振和微线圈核磁共振的代谢物鉴定方法。目前的提案重点是将这些方法结合在一起，建立一个强大的核磁共振平台，用于量化血液、尿液或细胞提取物样本中的100多种代谢物。我们将开发一种用于未知鉴定的全面方法，包括扩大同位素标记代谢物库。我们建议将该系统微型化，以便它可以在适度(100 L)的样本上运行，同时保持对大约50种代谢物进行定量的能力。这一方法的全面发展，将改变当前基于核磁共振的代谢组学的范式，并为当前的基于MS的方法提供更强大的补充。还讨论了这些方法在一组商业血清样本、尿液和细胞提取液上的验证，以及这些新方法与现有方法的比较。如果这项工作成功，我们将为高级代谢组学研究提供一个大大改进的核磁共振平台，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。