Investigation of The Derivatization Conditions for GC–MS Metabolomics of Biological Samples

Moros, Georgios; Chatziioannou, Anastasia Chrysovalantou; Gika, Helen; Raikos, Νikolaos; Theodoridis, Georgios

doi:10.4155/bio-2016-0224

Cited by 68 publications

(43 citation statements)

References 39 publications

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“…For a number of metabolites, including the TCA cycle intermediate α-ketoglutarate and aspartate, no 13 C isotopic enrichment was detected due to the combination of strongly diluted enrichment and low metabolite concentrations [ 41 , 42 ]. Moreover, it was not possible to reproducibly determine 13 C isotopic enrichment for pyruvate, due to instability of the derivative [ 43 ]. For the M3 isotopologue of glucose, representing a marker for gluconeogenesis [ 44 ], the isotopic enrichment was also too strongly diluted.…”

Section: Discussionmentioning

confidence: 99%

Quantification of Stable Isotope Traces Close to Natural Enrichment in Human Plasma Metabolites Using Gas Chromatography-Mass Spectrometry

et al. 2018

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Currently, changes in metabolic fluxes following consumption of stable isotope-enriched foods are usually limited to the analysis of postprandial kinetics of glucose. Kinetic information on a larger diversity of metabolites is often lacking, mainly due to the marginal percentage of fully isotopically enriched plant material in the administered food product, and hence, an even weaker 13C enrichment in downstream plasma metabolites. Therefore, we developed an analytical workflow to determine weak 13C enrichments of diverse plasma metabolites with conventional gas chromatography-mass spectrometry (GC-MS). The limit of quantification was increased by optimizing (1) the metabolite extraction from plasma, (2) the GC-MS measurement, and (3) most importantly, the computational data processing. We applied our workflow to study the catabolic dynamics of 13C-enriched wheat bread in three human subjects. For that purpose, we collected time-resolved human plasma samples at 16 timepoints after the consumption of 13C-labeled bread and quantified 13C enrichment of 12 metabolites (glucose, lactate, alanine, glycine, serine, citrate, glutamate, glutamine, valine, isoleucine, tyrosine, and threonine). Based on isotopomer specific analysis, we were able to distinguish catabolic profiles of starch and protein hydrolysis. More generally, our study highlights that conventional GC-MS equipment is sufficient to detect isotope traces below 1% if an appropriate data processing is integrated.

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Section: Discussionmentioning

confidence: 99%

Quantification of Stable Isotope Traces Close to Natural Enrichment in Human Plasma Metabolites Using Gas Chromatography-Mass Spectrometry

et al. 2018

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“…In metabolomics, derivatization usually uses oximation and a silylation/chloroformate reagent. This step is time consuming, hampers the throughput, and can introduce error by adding analytical variability (Moros et al 2017 ). Moreover, GC-MS metabolome coverage is limited by the stationary phase stability as well as the thermal stability of metabolites and their derivatives (Kaal and Janssen 2008 ).…”

Section: Analytical Strategies and Chemical Information Extractionmentioning

confidence: 99%

Advances in metabolome information retrieval: turning chemistry into biology. Part I: analytical chemistry of the metabolome

Tebani

Afonso

Bekri

2017

J of Inher Metab Disea

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Metabolites are small molecules produced by enzymatic reactions in a given organism. Metabolomics or metabolic phenotyping is a well-established omics aimed at comprehensively assessing metabolites in biological systems. These comprehensive analyses use analytical platforms, mainly nuclear magnetic resonance spectroscopy and mass spectrometry, along with associated separation methods to gather qualitative and quantitative data. Metabolomics holistically evaluates biological systems in an unbiased, data-driven approach that may ultimately support generation of hypotheses. The approach inherently allows the molecular characterization of a biological sample with regard to both internal (genetics) and environmental (exosome, microbiome) influences. Metabolomics workflows are based on whether the investigator knows a priori what kind of metabolites to assess. Thus, a targeted metabolomics approach is defined as a quantitative analysis (absolute concentrations are determined) or a semiquantitative analysis (relative intensities are determined) of a set of metabolites that are possibly linked to common chemical classes or a selected metabolic pathway. An untargeted metabolomics approach is a semiquantitative analysis of the largest possible number of metabolites contained in a biological sample. This is part I of a review intending to give an overview of the state of the art of major metabolic phenotyping technologies. Furthermore, their inherent analytical advantages and limits regarding experimental design, sample handling, standardization and workflow challenges are discussed.

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“…The metabolite compositions obtained after extraction have an impact on sample derivatization (Kanani et al, 2008). For the two-step method using methoximation followed by silylation, there are various conditions with different temperatures and incubation times ranging between 30-90 • C and from 0.5-6 h, respectively (Moros et al, 2016). Effective sample preparation methods have been developed for many fungi such as S. cerevisiae, Aspergillus sp., Monascus ruber, and Penicillium sp.…”

Section: Introductionmentioning

confidence: 99%

GC-MS-Based Metabolomics for the Smut Fungus Ustilago maydis: A Comprehensive Method Optimization to Quantify Intracellular Metabolites

Phan

Blank

2020

Front. Mol. Biosci.

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Ustilago maydis, a smut fungus, is an appealing model in fundamental research and an upcoming cell factory for industrial biotechnology. The genome of U. maydis has been sequenced and some synthesis pathways were biochemically described; however, the operation of the cellular metabolic network is not well-characterized. Thus, we conducted a comprehensive study to optimize the sample preparation procedure for metabolomics of U. maydis using GC-MS/MS. Due to the unique characteristics of U. maydis cell culture, two quenching solutions, different washing steps, eight extraction methods, and three derivatization conditions have been examined. The optimal method was then applied for stable isotope-assisted quantification of low molecular weight hydrophilic metabolites while U. maydis utilized different carbon sources including sucrose, glucose, and fructose. This study is the first report on a methodology for absolute quantification of intracellular metabolites in U. maydis central carbon metabolism such as sugars, sugar phosphates, organic acids, amino acids, and nucleotides. For biotechnological use, this method is crucial to exploit the full production potential of this fungus and can also be used to study other fungi of the family Ustilaginaceae.

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Investigation of The Derivatization Conditions for GC–MS Metabolomics of Biological Samples

Abstract: Formation and stability of derivatives among metabolites differ greatly, so derivatization should be studied before application in metabolomics studies.

Cited by 68 publications

References 39 publications

Quantification of Stable Isotope Traces Close to Natural Enrichment in Human Plasma Metabolites Using Gas Chromatography-Mass Spectrometry

Quantification of Stable Isotope Traces Close to Natural Enrichment in Human Plasma Metabolites Using Gas Chromatography-Mass Spectrometry

Advances in metabolome information retrieval: turning chemistry into biology. Part I: analytical chemistry of the metabolome

GC-MS-Based Metabolomics for the Smut Fungus Ustilago maydis: A Comprehensive Method Optimization to Quantify Intracellular Metabolites

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