2020BBSRC-NSF/BIO: Linking Mass Spectrometry Computational Ecosystems to Enhance Biological Insights of Publicly-Available Data

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The chemicals present in a biological system play many important roles including in reproduction, growth and survival. DNA contained in the genome provides a recipe for reproduction and is relatively static across an organism's lifetime. In comparison, metabolites contained in the metabolome are very dynamic in their presence and concentration in response to perturbations from within the organism or in response to external stimuli. Many studies to investigate the dynamics of metabolites apply a discovery-based approach called metabolic phenotyping (or metabolomics) where a chemical assay is applied to collect as great a volume of biological information as possible. However, the chemical structure or biological identity of many metabolites are not known prior to data collection and have to be derived from the data collected. This process of metabolite annotation is a significant hurdle because we do not yet have reference metabolomes and many metabolites are unavailable as chemical standards from which libraries metabolite identification can be applied. Many of the data deposited in metabolomics data repositories do not have an assigned chemical structure or metabolite name and therefore biological knowledge cannot be derived from these data. In the proposed research we will develop new open access computational tools and integrate these with existing open access tools to significantly increase the number of metabolites identified in two data repositories, MetaboLights in the UK and GNPS in the USA,. It will also establish common data standards for capturing and curating metabolomics data and for data exchange between the repositories. These approaches will increase the confidence in the annotations provided and greatly enhance the reusability of these data by the global scientific community.