MetaboLights: Creating the missing Metabolomics community resource

代谢组学研究在环境变化、疾病或其他边界条件下，生物体、器官、组织、细胞以及最终细胞隔室中小分子量化合物（代谢物）浓度的发生和变化。它通过光谱和色谱技术，并通过观察一次不仅是少数，但所有的化合物可见的特定技术使用。为了理解光谱或色谱图中一个或多个信号的浓度变化最终意味着什么，需要揭示相应信号背后的化合物的身份和作用。这需要精心策划的数据库，其中包含分配给其光谱数据的生物代谢物化学结构的参考数据。它还需要了解在给定条件下感兴趣的生物系统中代谢物的参考浓度。在基因组和蛋白质科学中，存在大量的资源来记录在感兴趣的系统中的某些条件下发现或表达的基因或蛋白质。然而，在代谢组学中，具有这样的信息的一般系统尚未被实例化。相反，存在一些专门研究某些“生命王国”、物种或疾病或分析设备的资源。因此，我们建议在英国剑桥Hinxton的欧洲Binformatics研究所建立一个通用代谢组学数据库资源，为英国和全球的生物界提供这一关键信息。这个资源，与工作标题“MetaboLights”，将提供有关代谢物及其参考光谱和色谱数据的信息，它们在生物体，组织，细胞等中的发生和浓度，在明确定义的条件下，最后但并非最不重要的是关于如何进行代谢组学实验的文件。与所有其他EBI资源一样，MetaboLights数据库将完全向公众开放，包括对数据的开放访问。数据将以公开接受的开放标准提供。该软件将是开源的。MetaboLights并不意味着要取代Metabolomics的专家资源。相反，它将建立在现有技术的基础上并进行合作。我们致力于与所有参与创造这一现有技术的主要各方密切合作，例如代谢组学协会、代谢会面和代谢组学标准倡议。在当今的分子生物学领域，无论是在基因组学还是其他领域，没有一个大型数据库工作是孤立的。相反，有一个受监管的资源生态系统，如基因组科学的基因库、Encyclopedia和DDBJ，它们自由交换数据，并就如何提供这些数据及其分析展开竞争。我们的目标是与人类代谢组数据库、戈尔姆代谢组数据库或理研代谢组学平台等主要资源达成类似的数据共享协议。然而，MetaboLights将是第一个全面的，跨物种，跨技术的数据库，它结合了纯代谢物的策划参考数据，关于它们在各种条件下在物种，器官，组织和细胞类型中的发生和浓度的策划信息，以及导致这些发现的实验特征数据。

Metabolomics studies the occurrence and change of concentrations of small molecular weight chemical compounds (metabolites) in organisms, organs, tissues, cells and ultimately cell compartments in the context of environmental changes, disease or other boundary conditions. It does this by means of spectroscopic and chromatographic techniques and by observing at once not only a few but all compounds visible to the particular technique used. To understand what a change in concentration of one or more of the signals in a spectrum or chromatogram ultimately means, the identity and role of the chemical compounds underlying the respective signal needs to be revealed. This requires curated databases with reference data of chemical structures of biological metabolites assigned to their spectra data. It also requires the knowledge about reference concentrations of metabolites in the biological system of interest under given conditions. In genome and protein science large resources exist to document which genes or proteins are found or expressed under certain conditions in the system of interest. In metabolomics, however, a general system with such information has not yet been instantiated. Instead, a number of resources exist which specialize on certain 'kingdoms of life', species or diseases, or analytical devices. Here, we therefore propose to establish a general metabolomics database resource at the European Binformatics Institute in Hinxton, Cambridge, UK, which serves this crucial information to the biological community in the UK and worldwide. This resource, with the working title 'MetaboLights', will serve information about metabolites and their reference spectra and chromatographic data, their occurrence and concentrations in organisms, tissues, cells, etc, under well-defined conditions, and last but not least documentation about how metabolomics experiments were conducted. Like all other EBI resources, the MetaboLights databases will be completely open to the public, including open access to the data. Data will be made available in publicly accepted open standards. The software will be open source. MetaboLights is not meant to replace specialist resources for Metabolomics. Rather, it will build on prior art and collaborate. We are dedicated to close collaboration with all major parties involved in the creation of this prior art, such as the Metabolomics Society, Metabomeeting and the Metabolomics Standards Initiative. In the molecular biology universe as it exists today, none of the large database efforts, neither in genomics nor any other area, lives an isolated life. Rather, there is a regulated ecosystem of resources, such as GenBank, Ensemble and DDBJ for the genome sciences, which interchange data freely and compete on how to present this data and on its analysis. We aim to come to similar data sharing agreements with major resources such as the Human Metabolome Database, the Golm Metabolome Database or the Rikken Metabolomics Platform. However, MetaboLights will be the first comprehensive, cross-species, cross-technique database which combines curated reference data of pure metabolites, curated information about their occurrence and concentration in species, organs, tissues and cell types under various condition with data characterizing the experiment which lead to these findings.