The Genomics Integration Core will advance metabolomics by making improvements in tools for interpreting and using metabolic data, specifically in the context of biochemical pathways and networks, but also by integrating data generated from genomics research, such as results from SNP genotyping, microbial genomics, or transcript and protein expression studies, into metabolomics studies. The core will be pivotal for conducting regional pilot and feasibility projects and critical for the success of the training and educational mission of the Promotion and Outreach Core. The Genomics Integration Core will be comprised of four different laboratories: the Weimer metagenomics laboratory, the Karp pathway informatics research group, the Pollard statistical genomics research group and the Lin and Perroud bioinformatics services core within the UC Davis Genome Center. The core will be responsible for both advancing the content of diverse metabolomics databases and tools and integrating the use of those tools and tools from other disciplines, particularly genomics, into metabolic studies such as pathway mapping. Newly developed tools will be employed in the Genome Center's bioinformatics service core as determined in coordination with the WC3MRC's Central Service Core. Specifically, the Genomics Integration Core will provide comprehensive bioinformatics and statistical tools for interpreting metabolomic data. The Core will collaborate with regional scientists on study design, data analysis and genomic interpretation of metabolomic data. The core will test and compare existing tools for linking genomic and metabolomic data, such as pathway mapping. Specifically, scientists in this core will work to advance genomics and pathway tools for metabolomic studies. The Genomics Integration Core will focus on advancing a range of existing tools in order to connect genomic pathways and disease phenotype data. Gene-enzyme annotations in the HumanCyc pathway database, integration of text-mining results into Cytoscape representations of metabolic networks, extension of current pathway enrichment approaches to include full metabolomic network statistics, development of tools for visualizing metabolite-centric network graphs with genomic information on demand, or other appropriate technologies will be explored in these efforts. The Genomics Integration Core will develop and test improvements in such tools and validate their utility and user friendliness by collaborating with regional scientists in clinical and preclinical research projects. Finally, this core will provide training and education in conjunction with the Promotion and Outreach Core.

Public Health Relevance

Sequencing of the human genome has opened new avenues for understanding health and the progression of diseases. We now begin to learn which parts of the genome enable metabolic responses in humans, and which parts of metabolism may be contributed by gut microbiota living in symbiosis. Integration of pathway modeling will enable a far better understanding and treatment of human diseases.

Project Start
Project End
Budget Start
2014-09-01
Budget End
2015-08-31
Support Year
3
Fiscal Year
2014
Total Cost
Indirect Cost
Name
University of California Davis
Department
Type
DUNS #
City
Davis
State
CA
Country
United States
Zip Code
95618
Killion, Elizabeth A; Reeves, Andrew R; El Azzouny, Mahmoud A et al. (2018) A role for long-chain acyl-CoA synthetase-4 (ACSL4) in diet-induced phospholipid remodeling and obesity-associated adipocyte dysfunction. Mol Metab 9:43-56
Garratt, Michael; Lagerborg, Kim A; Tsai, Yi-Miau et al. (2018) Male lifespan extension with 17-? estradiol is linked to a sex-specific metabolomic response modulated by gonadal hormones in mice. Aging Cell :e12786
Nagy-Szakal, Dorottya; Barupal, Dinesh K; Lee, Bohyun et al. (2018) Insights into myalgic encephalomyelitis/chronic fatigue syndrome phenotypes through comprehensive metabolomics. Sci Rep 8:10056
Gifford, Isaac; Battenberg, Kai; Vaniya, Arpana et al. (2018) Distinctive Patterns of Flavonoid Biosynthesis in Roots and Nodules of Datisca glomerata and Medicago spp. Revealed by Metabolomic and Gene Expression Profiles. Front Plant Sci 9:1463
Harris, Todd R; Kodani, Sean; Rand, Amy A et al. (2018) Celecoxib Does Not Protect against Fibrosis and Inflammation in a Carbon Tetrachloride-Induced Model of Liver Injury. Mol Pharmacol 94:834-841
Shearer, Gregory C; Borkowski, Kamil; Puumala, Susan L et al. (2018) Abnormal lipoprotein oxylipins in metabolic syndrome and partial correction by omega-3 fatty acids. Prostaglandins Leukot Essent Fatty Acids 128:1-10
Wandro, Stephen; Osborne, Stephanie; Enriquez, Claudia et al. (2018) The Microbiome and Metabolome of Preterm Infant Stool Are Personalized and Not Driven by Health Outcomes, Including Necrotizing Enterocolitis and Late-Onset Sepsis. mSphere 3:
Lai, Zijuan; Tsugawa, Hiroshi; Wohlgemuth, Gert et al. (2018) Identifying metabolites by integrating metabolome databases with mass spectrometry cheminformatics. Nat Methods 15:53-56
Carr, Tara F; Zeki, Amir A; Kraft, Monica (2018) Eosinophilic and Noneosinophilic Asthma. Am J Respir Crit Care Med 197:22-37
Mansour, Ahmed M; Abdelrahim, Mona; Laymon, Mahmoud et al. (2018) Epidermal growth factor expression as a predictor of chemotherapeutic resistance in muscle-invasive bladder cancer. BMC Urol 18:100

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