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Your Environment. Your Health.

GENETICS AND QUANTUM CHEMISTRY AS TOOLS FOR UNKNOWN METABOLITE IDENTIFICATION

Export to Word (http://www.niehs.nih.gov//portfolio/index.cfm/portfolio/grantdetail/grant_number/U2CES030167/format/word)
Principal Investigator: Edison, Arthur S
Institute Receiving Award University Of Georgia
Location Athens, GA
Grant Number U2CES030167
Funding Organization National Institute of Environmental Health Sciences
Award Funding Period 01 Sep 2018 to 30 Jun 2022
DESCRIPTION (provided by applicant): Overall: Our project combines the significant advantages of a genetic model organism, sophisticated pathway mapping tools, high-throughput and accurate quantum chemistry (QM), and state-of-the-art experimental measurements. The result will be an efficient and cost-effective approach for unknown compound identification in metabolomics, which is one of the major limitations facing this growing field of medical science. Caenorhabditis elegans has several advantages for this study, including over 10,000 available genetic mutants, well-developed CRISPR/Cas9 technology, and a panel of over 500 wild C. elegans isolates with complete genomes. Half of C. elegans genes have homologs to human disease genes, making this model organism an outstanding choice to improve our understanding of metabolic pathways in human disease. We will develop an automated pipeline for sample preparation to reproducibly measure tens of thousands of unknown features by UHPLC-MS/MS. We will use the wild isolates to conduct metabolome-wide genetic association studies (m-GWAS), and SEM-path to locate unknowns in pathways using partial correlations. The relevance of the unknown metabolites to specific pathways will be tested by measuring UHPLC-MS/MS data from genetic mutants of those pathways. Molecular formula and pathway information will be the inputs for automated quantum mechanical calculations of all possible structures, which will be used to accurately calculate NMR chemical shifts that will be matched to experimental data. The correct structures will be validated by comparing them with 2D NMR data of the same compound. The validated computed structures will then be used to improve QM-based MS/MS fragment prediction, using the experimental UHPLC-MS/MS data. This project will enhance many areas of science beyond worms and model organisms. First, C. elegans is the simplest animal model available with significant homology to other animals and humans. The discoveries we make in metabolic pathways will have a direct impact on studies of several human diseases. Second, our approach is highly transferable to other genetic systems and with little modification can be applied to many other applications. Perhaps most important is the relevance to large-scale human precision medicine studies. The wild C. elegans isolates are “individuals” with diverse genomes that are a model for natural populations such as humans. It is true that we are using mutant animals that would not be available in a human precision medicine study, but the mutants are used primarily to validate pathways that are constructed entirely by wild isolate data. Once the approaches are fully developed and validated, the mutants will not be necessary. C. elegans and other genetic model organisms were instrumental in the development of modern genomics and DNA sequencing technologies. Our premise is that the worm will have a comparable impact in metabolomics.
Science Code(s)/Area of Science(s) Primary: 77 - Metabolomics Technology
Secondary: 03 - Carcinogenesis/Cell Transformation
Publications See publications associated with this Grant.
Program Officer David Balshaw
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