GC-MS MCF-derivatization

GC-MS metabolomics with methyl chloroformate (MCF)


Gas Chromatography – Mass Spectometry (GC-MS) is one of the most applied analytical tools in metabolomics. Due to its high separation power, its capacity for reliable identification of hundreds of metabolites and its low cost, GC-MS is often the first choice for metabolite analysis. However, GC-MS systems are able to analyze only volatile compounds and, consequently, chemical derivatization of nonvolatile compounds is required.


Sample preparation: All samples are derivatized with methyl chloroformate (MCF). MCF converts amino and nonamino organic acids into volatile carbamates and esters. Although limited to compounds presenting amino and/or carboxyl groups, these include most metabolites of the central carbon metabolism, which are key intermediate of the cell metabolism.


GC-MS analysis: The samples are randomised and analysed by GC-MS. For quality control, a mixed pooled sample (QC sample) is created by taking a small aliquot from each sample. Every four-to-five samples this QC sample is analysed. Testing of matrix effects is performed by spiking/dilution of QC samples. It is assumed that the individual samples do not have matrix effects not found in the QC samples.


Data processing: The large amount of raw GC-MS data is processed by software developed by MS-Omics and collaborators. The software uses the powerful PARAFAC2 model and is able to extract more compounds and cleaner MS spectra than most other GC-MS software (see the data processing page for more information).


The extracted compounds undergo extensive data curation and quality control. Due to the derivatization some compounds will give more than one peak and the total number of compounds are therefore lower than the number of resolved peaks. In addition, some peaks originates from impurities in solvents. These redundant peaks are removed from the data. The absolute or relative concentrations of the curated compound are collected in an Excel file.


Finally the compounds showing significant variation are extracted to a “reduced dataset” and these data are visualized in the report to the customer.


An overview of the workflow from sample to the final results can be found in the figure below with the output from MS-Omics is in white boxes:

The final list of compounds are identified or annotated at four different levels:

1)Identified metabolites. Authentic chemical standards are compared to retention time and mass spectra.

2)Putatively annotated metabolites. The annotations are primarily based on library matching of the acquired MS spectra with the NIST library. The annotation might be incorrect; however, the compound will most likely be of similar structure.

3)Putatively characterized compound classes

4)Unknown compounds.