4.8 Article

NMR-Guided Mass Spectrometry for Absolute Quantitation of Human Blood Metabolites

期刊

ANALYTICAL CHEMISTRY
卷 90, 期 3, 页码 2001-2009

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acs.analchem.7b04089

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资金

  1. NIH [2R01GM085291]
  2. NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES [P30DK017047] Funding Source: NIH RePORTER
  3. NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES [R01GM085291] Funding Source: NIH RePORTER

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Broad-based, targeted metabolite profiling using mass spectrometry (MS) has become a major platform used in the field of metabolomics for a variety of applications. However, quantitative MS analysis is challenging owing to numerous factors including (1) the need for, ideally, isotope-labeled internal standards for each metabolite, (2) the fact that such standards may be unavailable or prohibitively costly, (3) the need to maintain the standards' concentrations close to those of the target metabolites, and (4) the alternative use of time-consuming calibration curves for each target metabolite. Here, we introduce a new method in which metabolites from a single serum specimen are quantified on the basis of a recently developed NMR method [Nagana Gowda et al. Anal. Chem. 2015, 87, 706] and then used as references for absolute metabolite quantitation using MS. The MS concentrations of 30 metabolites thus derived for test serum samples exhibited excellent correlations with the NMR ones (R-2 > 0.99) with a median CV of 3.2%. This NMR-guided-MS quantitation approach is simple and easy to implement and offers new avenues for the routine quantification of blood metabolites using MS. The demonstration that NMR and MS data can be compared and correlated when using identical sample preparations allows improved opportunities to exploit their combined strengths for biomarker discovery and unknown-metabolite identification. Intriguingly, however, metabolites including glutamine, pyroglutamic acid, glucose, and sarcosine correlated poorly with NMR data because of stability issues in their MS analyses or weak or overlapping signals. Such information is potentially important for improving biomarker discovery and biological interpretations. Further, the new quantitation method demonstrated here for human blood serum can in principle be extended to a variety of biological mixtures.

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