Metabolomics is a relatively new -omic technology experiencing exponential growth, and the opportunities associated with it allude to its almost limitless potential. There are however numerous obstacles that limit reaching its full potential. The development of bioinformatics tools such as XCMS Online, are needed to streamline the process from raw metabolic data analysis to its interpretation. Some examples of further development include the broad integration of data from orthogonal methods, autonomous metabolite annotation and identification, which we have just begun to address within the XCMS Online and METLIN platforms. Yet, perhaps the most interesting challenge is the identification of active metabolites using metabolomics and systems biology strategies, an area of research that will have a profound effect on the biomedical community. My overarching goal is not only to address these numerous obstacles, as we have a track record of doing, but also to make our developments freely available and user-friendly and allow the entire community and non-metabolomics experts from all fields (e.g. cancer, neurological disorders, diabetes, virology, environmental exposure, and so on) to harness the enormous opportunity of metabolomics. The funding will provide for the development of multiple connected strategic areas of metabolism-related biomedical research in areas that represent key gaps in metabolomics including: autonomous metabolomics data analysis, metabolite annotation and identification, metabolic guided system biology data integration, identification of phenotype modulating metabolites and global cooperative quantitative mass spectrometry analysis. As a part of the research described, it includes two junior faculty investigators (Lairson and Teijaro) as collaborators whose expertise are in developing approaches for neurodegeneration treatment and immunotherapy. For example, we will focus on identifying more potent metabolites to induce oligodendrocyte precursor cells maturation!for the treatment of multiple sclerosis, identifying metabolites capable of improving the immunological response in a T cell exhaustion model, to name a few. More broadly, our efforts will be to continue facilitating biomedical research in general, in this we are uniquely positioned through our cloud-based technologies, which currently serve over 22,000 registered users worldwide. The primary objective of our efforts is to develop metabolomics to advance biomedical research. Beyond developing the technology of measuring and analyzing metabolic data, correlating these measurements with activity is one of our prime goals. Biomarker discovery, pathway analysis and systems biology data integration, and cognitive computing are integral to the success of identifying metabolites that can actively modulate the system, essentially fixing biology with biology. A result of this effort in the further development of metabolomics is the underlying excitement, where, as technologists, we are no longer simply passive observers but active participants in solving biomedical problems. ! 1!

Public Health Relevance

Metabolomics will play a key role in identifying metabolites that are mechanistically important and biologically active. We will create a metabolomics platform that will build upon our previous key technologies within the context of biomedical applications to identify biomarkers, characterize pathway and systems biology perturbations, and facilitate the identification of active metabolites. Our platform will provide insight into disease mechanisms, facilitate existing drug therapies, and identify novel endogenous metabolite therapeutics.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Unknown (R35)
Project #
1R35GM130385-01
Application #
9626718
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Ravichandran, Veerasamy
Project Start
2019-03-01
Project End
2024-02-29
Budget Start
2019-03-01
Budget End
2020-02-29
Support Year
1
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Scripps Research Institute
Department
Type
DUNS #
781613492
City
La Jolla
State
CA
Country
United States
Zip Code
92037