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，小分子化合物(代谢物)在生物体、器官、组织、细胞以及最终细胞隔间中的发生和浓度变化。它通过光谱和层析技术来实现这一点，并通过立即观察到所使用的特定技术可见的不仅几种化合物，而是所有化合物。为了理解光谱或色谱图中一个或多个信号浓度的变化最终意味着什么，需要揭示作为各自信号基础的化合物的身份和作用。这需要将生物代谢物的化学结构的参考数据分配给它们的光谱数据的精选数据库。它还要求了解特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特定条件下在感兴趣的系统中发现或表达哪些基因或蛋白质。然而，在代谢组学中，具有这种信息的一般系统还没有被实例化。取而代之的是，有许多资源专门研究某些“生命王国”、物种或疾病或分析设备。因此，在这里，我们建议在英国剑桥欣克斯顿的欧洲生物信息学研究所建立一个普通代谢组学数据库资源，为英国和世界各地的生物界提供这一关键信息。这一资源的工作标题为“代谢光”，将提供关于代谢物及其参考光谱和层析数据的信息，在明确定义的条件下，它们在生物体、组织、细胞等中的出现和浓度，以及关于如何进行代谢组学实验的最后但并非最不重要的文件。与所有其他EBI资源一样，Metover Lights数据库将完全向公众开放，包括开放数据访问。数据将以公众接受的开放标准提供。该软件将是开源的。代谢之光并不是为了取代代谢组学的专家资源。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项现有技术的主要方面密切合作，如代谢组学学会、代谢会议和代谢组学标准倡议。在今天存在的分子生物学宇宙中，无论是在基因组学还是在任何其他领域，大型数据库的努力都不是孤立的。相反，有一个受监管的资源生态系统，如基因组科学的GenBank、EnSemble和DDBJ，它们自由交换数据，并就如何呈现这些数据及其分析展开竞争。我们的目标是与主要资源达成类似的数据共享协议，如人类代谢组数据库、Golm代谢组数据库或Rikken代谢组学平台。然而，MetaboLights将是第一个全面的、跨物种的、跨技术的数据库，它将纯代谢物的精选参考数据、不同条件下它们在物种、器官、组织和细胞类型中的出现和浓度的精选信息与导致这些发现的实验特征数据结合在一起。

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.