ABI Innovation: A Metabolomics Toolkit for NMR and Mass Spectrometry

ABI Innovation：用于 NMR 和质谱分析的代谢组学工具包

• 批准号: 1660921
• 负责人: Robert Powers
• 金额: $ 69.5万
• 依托单位: University of Nebraska-Lincoln
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-05-15 至 2022-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1660921&HistoricalAwards=false
• 关键词: ABI; Innovation; Metabolomics; Toolkit; NMR

With support from the Advances in Biological Informatics in the Division of Biological Infrastructure, Professor Robert Powers and his research group at the University of Nebraska - Lincoln will further develop their MVAPACK software toolkit that analyzes data generated in metabolomics research. Metabolomics is the study of the chemical signatures of the small molecules, like sugars, that are the products of biological processes. Metabolite fingerprints reveal a great deal about the recent activities occurring in biological samples. Knowing how organisms respond to their surroundings gives important leads to understanding events in fields like plant biology and agriculture, environmental and water quality studies, and human health research into nutrition or diseases. The chemical fingerprints are generated using two different technologies, called nuclear magnetic resonance and mass spectrometry. The results can be very complex and difficult to merge. This means the challenges for data analysis are also high, and include requirements to develop new approaches, like multivariate statistical methods. This proposal aims to produce software tools that will extract the most possible information from the data, including data format conversion, preprocessing, validation, significance testing, visualization, and metabolite identification at defined levels of confidence. The MVAPACK toolkit will enable important, currently unavailable data processing functions in the form of freely available and open source software modules, with an impact on data quality, sharing, information content resulting in deeper biological insights from studies that include metabolite profiling. During the award period, this research project will further enhance the MVAPACK metabolomics toolkit by including additional and urgently needed capabilities. Such improvements will include adding features to load and process liquid chromatography (LC)-MS, gas chromatography(GC)-MS and multidimensional datasets; to expand capabilities to integrate multiple datasets for chemometrics; and to automate metabolite identification, which is one of the more challenging and time-consuming aspects of metabolomics. This work will employ, among other approaches, graph theory, covariance NMR, back-scaled pseudospectral loadings, and a combined NMR and MS approach to facilitate the accurate and rapid assignment of metabolites from complex biological samples. Overall, these efforts will lead to an improved MVAPACK software package (http://bionmr.unl.edu/mvapack.php) for the metabolomics scientific community that will enhance the information content, utility, and ease of processing and combining various types of NMR and MS datasets.

在生物基础设施部生物信息学进展的支持下，Robert Powers 教授和他在内布拉斯加大学林肯分校的研究小组将进一步开发他们的 MVAPACK 软件工具包，用于分析代谢组学研究中生成的数据。代谢组学是对小分子（如糖）化学特征的研究，这些小分子是生物过程的产物。代谢物指纹揭示了生物样品中最近发生的大量活动。了解生物体如何应对周围环境，对于理解植物生物学和农业、环境和水质研究以及人类健康营养或疾病研究等领域的事件具有重要意义。化学指纹是使用两种不同的技术生成的，称为核磁共振和质谱。结果可能非常复杂且难以合并。这意味着数据分析的挑战也很高，包括开发新方法的要求，例如多元统计方法。该提案旨在开发软件工具，从数据中提取最可能的信息，包括数据格式转换、预处理、验证、显着性测试、可视化和在定义的置信水平下的代谢物识别。 MVAPACK 工具包将以免费和开源软件模块的形式实现目前无法使用的重要数据处理功能，对数据质量、共享和信息内容产生影响，从而从包括代谢物分析在内的研究中获得更深入的生物学见解。 在奖励期间，该研究项目将通过包含额外的和迫切需要的功能来进一步增强 MVAPACK 代谢组学工具包。此类改进将包括添加加载和处理液相色谱 (LC)-MS、气相色谱 (GC)-MS 和多维数据集的功能；扩展集成化学计量学多个数据集的能力；并自动化代谢物识别，这是代谢组学中更具挑战性和耗时的方面之一。这项工作将采用图论、协方差 NMR、后缩放伪谱载荷以及 NMR 和 MS 组合方法等方法，以促进从复杂生物样品中准确、快速地分配代谢物。总体而言，这些努力将为代谢组学科学界带来改进的 MVAPACK 软件包 (http://bionmr.unl.edu/mvapack.php)，该软件包将增强信息内容、实用性以及处理和组合各种类型 NMR 和 MS 数据集的简易性。

项目成果

Evaluation of Non-Uniform Sampling 2D 1H–13C HSQC Spectra for Semi-Quantitative Metabolomics

半定量代谢组学非均匀采样 2D 1H–13C HSQC 谱图的评估

• DOI: 10.3390/metabo10050203
• 发表时间: 2020
• 期刊: Metabolites
• 影响因子: 4.1
• 作者: Zhang, Bo;Powers, Robert;O’Day, Elizabeth M.
• 通讯作者: O’Day, Elizabeth M.

Comparing normalization methods and the impact of noise

• DOI: 10.1007/s11306-018-1400-6
• 发表时间: 2018-08-01
• 期刊: METABOLOMICS
• 影响因子: 3.6
• 作者: Thao Vu;Riekeberg, Eli;Powers, Robert
• 通讯作者: Powers, Robert