As a member of the NIH Common Funds Metabolomics Consortium, the Michigan Compound Identification Development Core (MCIDC) will using cutting-edge computational and experimental methods to systematically identify metabolites among the high proportion of features in untargeted metabolomics data which are presently considered unknown. In so doing, we will address a long-standing challenge in the field of metabolomics and enhance biological insights from extant and future metabolomics data. Our data will greatly contribute to platform-agnostic, rapidly-searchable metabolite databases, and the methods we develop will facilitate future compound identification efforts. We will achieve these goals by carrying out the following aims: Through the computational core of MCIDC, we will refine software currently operational in our lab that aids in annotation of features in untargeted metabolomics data as either primary features or as artifacts or degenerate features (e.g., isotopes, fragments, adducts, contaminants). This software will help prioritize identification efforts on primary features, while allowing artifacts and degenerate features to be indexed and rapidly removed from future data sets. We will implement a `hybrid search' approach that will allow unknown metabolite spectra to be searched against both in-silico and experimentally-derived spectra of compounds with similar structural motifs. We expect this approach will improve certainty of metabolite identification compared to in-silico spectra alone. We will contribute our data output to the National Metabolomics Data Repository and other databases. Through the experimental core of MCIDC, we will develop and implement novel and cutting-edge analytical technologies to aid in compound identification, and will systematically apply these techniques to unknown primary features in metabolomics data determined to be of high priority based on survey of public metabolomics databases. Techniques we will use to identify metabolites include high-resolution tandem mass spectrometry (MSn), ion mobility spectrometry, high-resolution chromatographic methods including ultra-high pressure liquid chromatography, sample pre-fractionation and multidimensional separations, in-vivo stable isotope labeling for structural elucidation, chemical derivatization, pre-concentration followed by NMR analysis, and (when necessary) synthesis and characterization of novel metabolite standards. Finally, through our administrative core, we will ensure coordinated operation between our own experimental and computational cores, and with other members of the NIH common funds metabolomics consortium. By coordinating between CIDC sites and prioritizing compound identification tasks as a group, we will maximize productivity and improve outcome of the metabolomics consortium efforts. By carrying out these aims, we anticipate that our CIDC will yield a lasting, unifying impact on interpretation of biological findings from the rich and growing datasets yielded by untargeted metabolomics.

Public Health Relevance

The Michigan Compound Identification Development Core (MCIDC) will using cutting-edge technologies to help identify new and difficult-to-detect biological molecules in samples such as human blood or tissues using a technique termed metabolomics. We will work as a part of a larger consortium of metabolomics researchers to overcome major challenges in the field in a manner not possible on a smaller scale. Our efforts will allow future scientists make better use of their metabolomics data, potentially advancing discovery of biochemical pathways that are responsible for, or can be used to treat, major human diseases.

Agency
National Institute of Health (NIH)
Institute
National Institute of Environmental Health Sciences (NIEHS)
Type
Resource-Related Research Multi-Component Projects and Centers Cooperative Agreements (U2C)
Project #
1U2CES030164-01
Application #
9589595
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Balshaw, David M
Project Start
2018-08-15
Project End
2022-05-31
Budget Start
2018-08-15
Budget End
2019-05-31
Support Year
1
Fiscal Year
2018
Total Cost
Indirect Cost
Name
University of Michigan Ann Arbor
Department
Pathology
Type
Schools of Medicine
DUNS #
073133571
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109