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

ReferenceBB/N023013/1
Principal Investigator / Supervisor Professor Warwick Dunn
Co-Investigators /
Co-Supervisors		 Dr Shan He, Professor Mark Viant, Dr Ralf Weber
Institution University of Birmingham
DepartmentSch of Biosciences
Funding typeResearch
Value (£) 91,362
StatusCompleted
TypeResearch Grant
Start date 01/10/2016
End date 31/12/2017
Duration15 months

Abstract

The chemical identification of metabolites is a crucial step in untargeted metabolomic studies but is currently limited by our understanding of the complex processes operating in electrospray ion sources when coupled with liquid chromatography-mass spectrometry. Metabolite identification remains the rate limiting step in metabolomics studies. Research by the investigators has shown that a large number of different adducts, isotopic, multiply charged and fragment peaks can be observed when analyzing crude biological extracts applying liquid chromatography-electrospray mass spectrometry. Here we propose to further develop, validate and make publicly available an integrated computational workflow (PUTMEDID) for the grouping annotation of each metabolite with a molecular formula and metabolite name(s) with a statistical score of confidence. We will (i) for the first time fully characterize the large diversity of adducts, isotopic, multiply charged and fragment peaks detected when analyzing crude biological extracts applying liquid chromatography-electrospray mass spectrometry; (ii) further develop computational tools to identify all adducts, isotopic, multiply charged and fragment peaks in a sample, instrument and analytical method specificity; (iii) enhance a currently available computational resource (PUTMEDID) to increase the number of true positive annotations. To allow the greatest impact the bioinformatics resource and associated code will be made available to researchers globally through incorporation in the well-maintained and stable computational infrastructure at the European Bioinformatics Institute in the UK. In summary we will DEVELOP A COMPUTATIONAL TOOL for enhanced metabolite annotation, APPLY the tool to construct an OPEN ACCESS RESOURCE for all researchers and DISSEMINATE AND TRAIN the scientific community. This innovative new approach will significantly enhance our capabilities to annotate all metabolites detected in metabolomics studies.

Summary

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.

Impact Summary

WHO WILL BENEFIT FROM THE RESEARCH? There are many national and international groups who will benefit from the publicly accessible metabolite annotation bioinformatics resource to be constructed. These include (i) Academic researchers performing non-targeted metabolomics using LC-MS. The resource developed will benefit research in to microbes, plants and animals in areas including synthetic biology, crop production and human ageing. (ii) Industry scientists performing non-targeted metabolomics research with LC-MS. The resource developed will provide greater understanding of the metabolism underlying the production of pharmaceuticals and chemicals and in improved crop production. (iii) Government agencies in the UK performing non-targeted metabolomics research with LC-MS platforms. For example, the Department for Environment, Food and Rural Affairs in the UK who through the FERA facility apply non-targeted metabolomics for food safety and food authenticity testing and crop protection. (iv) Commercial instrument suppliers, specifically those supplying mass spectrometers as the resource will be applicable to a range of different mass spectrometers from different commercial instrument suppliers. (vi) A post-doctoral research associate employed during the research through training in different scientific disciplines and through personal development. HOW WILL THEY BENEFIT FROM THIS RESEARCH? There will be a number of direct or indirect benefits observed by academic and industrial research groups, commercial industrial companies, and the research staff employed for the proposed research. The first direct benefit will be the ability of academic and industrial research groups to perform higher quality biological research through increased abilities to annotate a larger number of metabolites in non-targeted metabolomics studies and therefore provide higher quality data for biological interpretation at the systems level. This will readily be achieved via the metabolite annotation bioinformatics resource. The ability of researchers to apply systems-level approaches to understand the interactions of metabolites with other metabolites and biochemicals and to be able to integrate large biochemical databases from holistic data acquisition at different functional levels is a growing requirement in biological research. The second benefit will be to provide a commercial impact through higher quality biological research performed in industry and which increases the efficiency of production of chemicals, pharmaceuticals and crops. The third benefit will be to provide a further commercial impact, specifically to mass spectrometer suppliers through their improved ability to annotate metabolites in biological studies and the impact this will have on mass spectrometer sales versus, for example, the relative decline in the use of NMR spectroscopy over the last few years. The public will indirectly benefit from the developed resource through higher quality biological research and the impact on improvements in crop and drug production and in our understanding of healthy ageing. Finally, the post-doctoral researcher and investigators performing the proposed research will benefit from training in new concepts in a multi-disciplinary environment. Mechanisms for dissemination to scientists and to the general public are described in our Pathways to Impact document.
Committee Research Committee A (Animal disease, health and welfare)
Research TopicsTechnology and Methods Development
Research PriorityX – Research Priority information not available
Research Initiative Tools and Resources Development Fund (TRDF) [2006-2015]
Funding SchemeX – not Funded via a specific Funding Scheme
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