Open source pipelines for integrated metabolomics analysis by NMR and mass spectrometry

通过 NMR 和质谱进行集成代谢组学分析的开源管道

• 批准号: BB/M020282/1
• 负责人: Andrew Jones
• 金额: $ 12.31万
• 依托单位: University of Liverpool
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2015
• 资助国家: 英国
• 起止时间: 2015 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FM020282%2F1
• 关键词: Open; source; pipelines; integrated; metabolomics

Research in the Life Sciences is now commonly performed using high-tech instrumentation, producing very large amounts of data about a system of interest. These techniques are collectively called 'omics (e.g. including genomics, proteomics and metabolomics) - and in different ways can measure how genes are switched on or off, how the proteins encoded by those genes behave in a cell or tissue of interest, or how the metabolites (biochemical molecules in cells) change in abundance, as the system behaves normally or is put under stress by disease, dysfunction or the introduction of toxic substances. The metabolites studied can include molecules that provide energy or structure to cells (e.g. fats, sugars etc), the structural building blocks of DNA and proteins (e.g. nucleotides, amino acids) and essential co-factors to biological processes (e.g. vitamins). In fundamental research, and in clinical situations, the presence of a particular metabolite at an unusual abundance can be an indicator (a biomarker) of a particular state - such as a disease. Indeed, metabolomics research is applied in studies on cancer, infectious disease, heart disease, diabetes and many others. One of the greatest challenges in metabolomics research is that the analysis of the data is very difficult. Multiple different processing steps are needed to get from the raw data as delivered by the instrument - primarily nuclear magnetic resonance (NMR) spectroscopy or mass spectrometry (MS), to the final results the researcher is interested in, i.e. quantitative and statistically significant differences in particular metabolites between samples. There are multiple software packages (both commercial and free) that can perform individual steps within a complete pipeline, but there is very little good software that makes it easy to perform a full analysis. In this project, we will build such software for data generated from NMR or MS, using a software framework called Galaxy. Galaxy has been designed to construct a web interface on top of other software packages, enabling different (previously disconnected) packages to be joined together into an easy to use pipeline. The joining together of modules needs data files in a standardized format as the input and output of each step, so we will also work within international organizations to help agree on a universally applied standard format to be used in our pipeline and by other software developers working in metabolomics. Our pipeline will make it much easier for scientists to analyse their data and, in particular, to compare or integrate data coming from both complementary techniques (NMR and MS) to get a more complete picture of the system being studied. This will facilitate many more researchers - who currently lack detailed knowledge in metabolomics - to embrace and exploit this powerful technology. Lastly, we will make it easier for scientists to put their data into public databases when they publish their research, enabling other scientists to verify their findings and in some cases re-analyse their data in their own labs.

生命科学的研究现在通常是使用高科技仪器进行的，产生关于感兴趣的系统的大量数据。这些技术统称为“组学”(例如，基因组学、蛋白质组学和代谢组学)--可以以不同的方式测量基因如何开启或关闭，由这些基因编码的蛋白质在相关细胞或组织中如何表现，或代谢产物(细胞中的生化分子)如何在系统正常运行或受到疾病、功能障碍或有毒物质引入的压力时发生变化。所研究的代谢物可以包括为细胞提供能量或结构的分子(例如脂肪、糖等)、DNA和蛋白质的结构构件(例如核苷酸、氨基酸)以及生物过程的基本辅助因素(例如维生素)。在基础研究和临床情况下，特定代谢物的异常丰度可以作为特定状态的指示器(生物标记物)--例如疾病。事实上，代谢组学研究被应用于癌症、传染病、心脏病、糖尿病和许多其他方面的研究。代谢组学研究中最大的挑战之一是数据的分析非常困难。需要多个不同的处理步骤才能从仪器提供的原始数据--主要是核磁共振(NMR)谱或质谱学(MS)--到研究人员感兴趣的最终结果，即样品之间特定代谢物的数量和统计上的显著差异。有多个软件包(商业的和免费的)可以在完整的管道中执行单独的步骤，但很少有好的软件可以轻松执行完整的分析。在这个项目中，我们将使用名为Galaxy的软件框架，为从核磁共振或MS生成的数据构建这样的软件。Galaxy的设计目的是在其他软件包的基础上构建一个网络界面，使不同的(以前断开的)软件包能够连接到一个易于使用的管道中。模块的结合需要标准化格式的数据文件作为每个步骤的输入和输出，因此我们还将在国际组织内部工作，以帮助就我们的流水线和其他从事代谢组学工作的软件开发商使用的通用标准格式达成一致。我们的管道将使科学家更容易分析他们的数据，特别是比较或整合来自两种互补技术(核磁共振和质谱仪)的数据，以获得正在研究的系统的更完整的图景。这将促进更多的研究人员--他们目前缺乏代谢组学方面的详细知识--接受和利用这项强大的技术。最后，我们将使科学家在发表研究成果时更容易将他们的数据输入公共数据库，使其他科学家能够验证他们的发现，在某些情况下还可以在他们自己的实验室重新分析他们的数据。