A three‐minute method for high‐throughput quantitative metabolomics and quantitative tracing experiments of central carbon and nitrogen pathways

• Published in: Rapid communications in mass spectrometry Vol. 31; no. 8; pp. 663 - 673
• Main Authors: Nemkov, Travis, Hansen, Kirk C., D'Alessandro, Angelo
• Format: Journal Article
• Language: English
• Published: England Wiley Subscription Services, Inc 30.04.2017
• Subjects: Animals; Biomarkers - analysis; Biomarkers - metabolism; Body Fluids - chemistry; Bronchoalveolar Lavage Fluid - chemistry; Carbon; Carbon - analysis; Carbon - metabolism; Chromatography, High Pressure Liquid - methods; High-Throughput Screening Assays - methods; Humans; In vivo methods and tests; Limit of Detection; Linear Models; Mass spectrometry; Mass Spectrometry - methods; Metabolites; Metabolomics - methods; Nitrogen - analysis; Nitrogen - metabolism; Pathways; Rats; Rats, Sprague-Dawley; Reproducibility of Results; Robustness
• ISSN: 0951-4198; 1097-0231; 1097-0231
• DOI: 10.1002/rcm.7834

Rationale The implementation of mass spectrometry (MS)‐based metabolomics is advancing many areas of biomedical research. The time associated with traditional chromatographic methods for resolving metabolites prior to mass analysis has limited the potential to perform large‐scale, highly powered metabolomics studies and clinical applications. Methods Here we describe a three‐minute method for the rapid profiling of central metabolic pathways through UHPLC/MS, tracing experiments in vitro and in vivo, and targeted quantification of compounds of interest using spiked in heavy labeled standards. Results This method has shown to be linear, reproducible, selective, sensitive, and robust for the semi‐targeted analysis of central carbon and nitrogen metabolism. Isotopically labeled internal standards are used for absolute quantitation of steady‐state metabolite levels and de novo synthesized metabolites in tracing studies. We further propose exploratory applications to biofluids, cell and tissue extracts derived from relevant biomedical/clinical samples. Conclusions While limited to the analysis of central carbon and nitrogen metabolism, this method enables the analysis of hundreds of samples per day derived from diverse biological matrices. This approach makes it possible to analyze samples from large patient populations for translational research, personalized medicine, and clinical metabolomics applications. Copyright © 2017 John Wiley & Sons, Ltd.