Streamlined pentafluorophenylpropyl column liquid chromatography-tandem quadrupole mass spectrometry and global (13)C-labeled internal standards improve performance for quantitative metabolomics in bacteria

简化的五氟苯丙基柱液相色谱-串联四极杆质谱联用技术和全局(13)C标记内标提高了细菌定量代谢组学的性能。

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Abstract

Streamlined quantitative metabolomics in central metabolism of bacteria would be greatly facilitated by a high-efficiency liquid chromatography (LC) method in conjunction with accurate quantitation. To achieve this goal, a methodology for LC-tandem quadrupole mass spectrometry (LC-MS/MS) involving a pentafluorophenylpropyl (PFPP) column and culture-derived global (13)C-labeled internal standards (I.Ss.) has been developed and compared to hydrophilic interaction liquid chromatography (HILIC)-MS/MS and published combined two-dimensional gas chromatography and LC methods. All 50 tested metabolite standards from 5 classes (amino acids, carboxylic acids, nucleotides, acyl-CoAs and sugar phosphates) displayed good chromatographic separation and sensitivity on the PFPP column. In addition, many important critical pairs such as isomers/isobars (e.g. isoleucine/leucine, methylsuccinic acid/ethylmalonic acid and malonyl-CoA/3-hydroxybutyryl-CoA) and metabolites of similar structure (e.g. malate/fumarate) were resolved better on the PFPP than on the HILIC column. Compared to only one (13)C-labeled I.S., the addition of global (13)C-labeled I.Ss. improved quantitative linearity and accuracy. PFPP-MS/MS with global (13)C-labeled I.Ss. allowed the absolute quantitation of 42 metabolite pool sizes in Methylobacterium extorquens AM1. A comparison of metabolite level changes published previously for ethylamine (C2) versus succinate (C4) cultures of M. extorquens AM1 indicated a good consistency with the data obtained by PFPP-MS/MS, suggesting this single approach has the capability of providing comprehensive metabolite profiling similar to the combination of methods. The more accurate quantification obtained by this method forms a fundamental basis for flux measurements and can be used for metabolism modeling in bacteria in future studies.

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