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1.
Methods Mol Biol ; 1730: 277-282, 2018.
Article in English | MEDLINE | ID: mdl-29363081

ABSTRACT

We here explain step by step the implementation of gas chromatography coupled with tandem mass spectrometry for the quantitative analysis of intracellular metabolites from the tricarboxylic acid (TCA) cycle such as citrate, isocitrate, alpha-ketoglutarate, succinate, malate, and fumarate. Isotope dilution is used to correct for potential metabolite losses during sample processing, matrix effects, incomplete derivatization, and liner contamination. All measurements are performed in selected reaction monitoring (SRM) mode. Standards and samples are first diluted with a fixed volume of a mixture of fully 13 C-labeled internal standards and then derivatized to give trimethylsilyl-methoxylamine derivatives prior GC-MS/MS analysis.


Subject(s)
Bacteria/chemistry , Metabolomics/methods , Saccharomyces cerevisiae/chemistry , Citric Acid Cycle , Gas Chromatography-Mass Spectrometry/methods , Hydroxylamines/analysis , Trimethylsilyl Compounds/analysis
2.
Metabolites ; 7(2)2017 May 17.
Article in English | MEDLINE | ID: mdl-28513556

ABSTRACT

Poly(3-hydroxybutyrate) (PHB) is an interesting biopolymer for replacing petroleum-based plastics, its biological production is performed in natural and engineered microorganisms. Current metabolic engineering approaches rely on high-throughput strain construction and screening. Analytical procedures have to be compatible with the small scale and speed of these approaches. Here, we present a method based on isotope dilution mass spectrometry (IDMS) and propanolysis extraction of poly(3-hydroxybutyrate) from an Escherichia coli strain engineered for PHB production. As internal standard (IS), we applied an uniformly labeled 13C-cell suspension, of an E. coli PHB producing strain, grown on U-13C-glucose as C-source. This internal 13C-PHB standard enables to quantify low concentrations of PHB (LOD of 0.01 µg/gCDW) from several micrograms of biomass. With this method, a technical reproducibility of about 1.8% relative standard deviation is achieved. Furthermore, the internal standard is robust towards different sample backgrounds and dilutions. The early addition of the internal standard also enables higher reproducibility and increases sensitivity and throughput by simplified sample preparation steps.

3.
Biotechnol Bioeng ; 113(5): 1137-47, 2016 May.
Article in English | MEDLINE | ID: mdl-26479486

ABSTRACT

Fluxomics and metabolomics are crucial tools for metabolic engineering and biomedical analysis to determine the in vivo cellular state. Especially, the application of (13)C isotopes allows comprehensive insights into the functional operation of cellular metabolism. Compared to single MS, tandem mass spectrometry (MS/MS) provides more detailed and accurate measurements of the metabolite enrichment patterns (tandem mass isotopomers), increasing the accuracy of metabolite concentration measurements and metabolic flux estimation. MS-type data from isotope labeling experiments is biased by naturally occurring stable isotopes (C, H, N, O, etc.). In particular, GC-MS(/MS) requires derivatization for the usually non-volatile intracellular metabolites introducing additional natural isotopes leading to measurements that do not directly represent the carbon labeling distribution. To make full use of LC- and GC-MS/MS mass isotopomer measurements, the influence of natural isotopes has to be eliminated (corrected). Our correction approach is analyzed for the two most common applications; (13)C fluxomics and isotope dilution mass spectrometry (IDMS) based metabolomics. Natural isotopes can have an impact on the calculated flux distribution which strongly depends on the substrate labeling and the actual flux distribution. Second, we show that in IDMS based metabolomics natural isotopes lead to underestimated concentrations that can and should be corrected with a nonlinear calibration. Our simulations indicate that the correction for natural abundance in isotope based fluxomics and quantitative metabolomics is essential for correct data interpretation.


Subject(s)
Metabolomics/methods , Saccharomyces cerevisiae/metabolism , Tandem Mass Spectrometry/methods , Carbon Isotopes/analysis , Carbon Isotopes/metabolism , Gas Chromatography-Mass Spectrometry , Isotope Labeling/methods
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