Next generation tools for the annotation of metabolites in global LC-MS metabolomic studies

活着的有机体的新陈代谢对环境变化、疾病状况或仅仅是有机体的年龄作出迅速而敏感的反应。捕捉新陈代谢和代谢物是如何变化的，可以提供对个人健康状况的精细洞察。代谢组学的学科试图描述一个细胞或组织中的整个代谢物群体。它的关键挑战是同时识别有时数千个不同的分子。凭借其无与伦比的精密度和灵敏度，质谱学已成为这种情况下的首选工具。然而，这项技术需要电离的代谢物，所以它们可以在电磁场中加速和分析。虽然电离技术已经很成熟，但人们对这一过程中产生的带电分子物种的多样性知之甚少。因此，许多代谢物没有被识别，而且质谱学实验提供的数据中只有一小部分真正反映了生物学结论。我们的工具箱中第一次有了足够的资产来组装和优化到一个新的工作流程中；这是我们将构建、验证和应用的工具，以为代谢组学社区生成新的计算资源，一个可公开访问的计算软件，用于执行代谢物注释并计算识别正确的统计概率。我们将通过BBSRC资助的MetabLights数据库提供这一信息，该数据库将在英国的欧洲生物信息学研究所得到长期支持。这一新资源将在国内和国际上被学术、政府和行业科学家广泛使用。所有数据都将免费访问，培训视频将包括在内，资源将得到广泛宣传。这项具有成本效益的提案将共同开发一种新工具和新资源，通过将其嵌入欧洲生物信息学研究所，将改变代谢组学社区将数据转化为新知识的能力，使代谢组学能够兑现其实现影响的承诺。

The metabolism of a living organism reacts rapidly and sensitively to environmental change, disease conditions or simply the organism's age. Capturing how metabolism and metabolites change provides an exquisite insight into the health status of an individual. The discipline of metabolomics seeks to describe the entire population of metabolites in a cell or tissue. Its key challenge is to identify sometimes thousands of different molecules simultaneously. With its unmatched precision and sensitivity, mass spectrometry has become the tool of choice in this context. However, this technique requires ionized metabolites, so they can be accelerated and analysed in an electro-magnetic field. While ionization techniques are well established, the diversity of charged molecular species generated in this process is poorly understood. As a result, many metabolites are not identified and only a fraction of the data a mass spectrometric experiment provides really informs the biological conclusions. For the first time we have enough assets in our toolbox to assemble and optimise into a new workflow; this is the TOOL we will construct, validate and apply to generate a new computational RESOURCE for the metabolomics community, a publicly accessible computational software for performing metabolite annotation and calculating the statistical probability that the identification is correct. We will make this available via the BBSRC-funded MetaboLights database to be supported long-term at the European Bioinformatics Institute in the UK. The new resource will be widely used, both nationally and internationally, by academic, government and industry scientists. All data will be free to access, training videos will be included and the resource will be widely publicised. This cost effective proposal will collectively develop a new TOOL and new RESOURCE, and by embedding it at the European Bioinformatics Institute will transform the metabolomics community's ability to transform data to new knowledge, allowing metabolomics to deliver on its promises to achieve impact.