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

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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.