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  • Title: Non-targeted determination of (13)C-labeling in the Methylobacterium extorquens AM1 metabolome using the two-dimensional mass cluster method and principal component analysis.
    Author: Reaser BC, Yang S, Fitz BD, Parsons BA, Lidstrom ME, Synovec RE.
    Journal: J Chromatogr A; 2016 Feb 05; 1432():111-21. PubMed ID: 26787164.
    Abstract:
    A novel analytical workflow is presented for the analysis of time-dependent (13)C-labeling of the metabolites in the methylotrophic bacterium Methylobacterium extorquens AM1 using gas chromatography time-of-flight mass spectrometry (GC-TOFMS). Using (13)C-methanol as the substrate in a time course experiment, the method provides an accurate determination of the number of carbons converted to the stable isotope. The method also extracts a quantitative isotopic dilution time course profile for (13)C uptake of each metabolite labeled that could in principle be used to obtain metabolic flux rates. The analytical challenges encountered require novel analytical platforms and chemometric techniques. GC-TOFMS offers advanced separation of mixtures, identification of individual components, and high data density for the application of advanced chemometrics. This workflow combines both novel and traditional chemometric techniques, including the recently reported two-dimensional mass cluster plot method (2D m/z cluster plot method) as well as principal component analysis (PCA). The 2D m/z cluster plot method effectively indexed all metabolites present in the sample and deconvoluted metabolites at ultra-low chromatographic resolution (RS≈0.04). Using the pure mass spectra extracted, two PCA models were created. Firstly, PCA was used on the first and last time points of the time course experiment to determine and quantify the extent of (13)C uptake. Secondly, PCA modeled the full time course in order to quantitatively extract the time course profile for each metabolite. The 2D m/z cluster plot method found 152 analytes (metabolites and reagent peaks), with 54 pure analytes, and 98 were convoluted, with 65 of the 98 requiring mathematical deconvolution. Of the 152 analytes surveyed, 83 were metabolites determined by the PCA model to have incorporated (13)C while 69 were determined to be either metabolites or reagent peaks that remained unlabeled.
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