The Southeast Resource Center for Integrated Metabolomics (SECIM) integrates existing strengths to create a comprehensive resource for basic and clinical scientists to obtain state-of-the-art metabolomics data and analyses. Core 2 provides NMR services to SECIM users using 3 existing 600 MHz instruments: 1) a Bruker AVIl with 5-mm cryoprobe and sample changer for 1H studies of abundant samples such as human serum and urine, 2) an Agilent VNMRS-600 equipped with a new 1.5-mm 13C optimized high temperature superconducting probe jointly developed by the National High Magnetic Field Laboratory (MagLab) and Agilent, and 3) a Bruker AVIII equipped with an HRMAS probe for direct tissue analysis. The 1.5-mm probe allows for 13C NMR measurements in addition to high sensitivity reduced volume IH measurements of limited samples such as mouse serum. This probe will also allow us to develop an NMR component of IROA, which is offered in Core 3 and is an LC-MS-based technique that uses 13C-labeled samples;NMR will be used to enhance the ability to positively identify biomarkers in IROA studies. In addition, the Bruker AVIl has a MagLab/Bruker 1-mm HTS probe that provides the highest possible sensitivity for biomarker discovery. We have partnered with the Bruschweiler lab at Florida State University to integrate COLMAR into the SECIM workflow. COLMAR allows for the analysis of complex mixtures by NMR and for the de novo identification of compounds through a combination of database matching and fragment generation. We have also partnered with the Nicholson group at Imperial College London with the goal of improving the correlation of NMR and MS data and developing more efficient methods for automating biomarker ID. This collaboration will be managed through Core 4 (Bioinformatics), which will provide statistical and programming support to this project. Core 2 will offer traditional natural products approaches of biomarker ID, should the automated methods fail to identify an important biomarker. Core 2 also provides users with substrates suitable for dynamic nuclear polarization (DNP) studies, which have the potential to monitor metabolic pathways in vivo using NMR and MRI techniques. In vivo studies will be conducted by our partner, the AMRIS Facility.

Public Health Relevance

The major goal of metabolomics is the measurement and characterization of metabolites from living organisms, including people. Small molecule metabolites are sensitive to disease, treatment, and many environmental factors, and they can be used as indicators of disease in diagnosis or as markers to assess the outcome of treatment.

Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
University of Florida
United States
Zip Code
Hattori, Ayuna; Tsunoda, Makoto; Konuma, Takaaki et al. (2017) Cancer progression by reprogrammed BCAA metabolism in myeloid leukaemia. Nature 545:500-504
Le Guennec, Adrien; Tayyari, Fariba; Edison, Arthur S (2017) Alternatives to Nuclear Overhauser Enhancement Spectroscopy Presat and Carr-Purcell-Meiboom-Gill Presat for NMR-Based Metabolomics. Anal Chem 89:8582-8588
Ulmer, Candice Z; Koelmel, Jeremy P; Ragland, Jared M et al. (2017) LipidPioneer : A Comprehensive User-Generated Exact Mass Template for Lipidomics. J Am Soc Mass Spectrom 28:562-565
Markley, John L; Br├╝schweiler, Rafael; Edison, Arthur S et al. (2017) The future of NMR-based metabolomics. Curr Opin Biotechnol 43:34-40
Reed, Laura K; Baer, Charles F; Edison, Arthur S (2017) Considerations when choosing a genetic model organism for metabolomics studies. Curr Opin Chem Biol 36:7-14
Liu, Haiyan; Garrett, Timothy J; Su, Zhihua et al. (2017) UHPLC-Q-Orbitrap-HRMS-based global metabolomics reveal metabolome modifications in plasma of young women after cranberry juice consumption. J Nutr Biochem 45:67-76
DeRatt, Barbara N; Ralat, Maria A; Lysne, Vegard et al. (2017) Metabolomic Evaluation of the Consequences of Plasma Cystathionine Elevation in Adults with Stable Angina Pectoris. J Nutr 147:1658-1668
Koelmel, Jeremy P; Kroeger, Nicholas M; Gill, Emily L et al. (2017) Expanding Lipidome Coverage Using LC-MS/MS Data-Dependent Acquisition with Automated Exclusion List Generation. J Am Soc Mass Spectrom 28:908-917
Koelmel, Jeremy P; Ulmer, Candice Z; Jones, Christina M et al. (2017) Common cases of improper lipid annotation using high-resolution tandem mass spectrometry data and corresponding limitations in biological interpretation. Biochim Biophys Acta 1862:766-770
Wang, Cheng; He, Lidong; Li, Da-Wei et al. (2017) Accurate Identification of Unknown and Known Metabolic Mixture Components by Combining 3D NMR with Fourier Transform Ion Cyclotron Resonance Tandem Mass Spectrometry. J Proteome Res 16:3774-3786

Showing the most recent 10 out of 55 publications