Traditional targeted analysis focuses on predefined metabolites using optimized methodology. Compounds are identified using analytical reference material. This approach is in general more sensitive and compound identification unambiguous.
Untargeted analysis Untargeted analysis includes the detection of metabolites without prior selection. This approach provides a more global view on the sample, and enables the discovery of unknown important compounds. Identification of compounds is based on comparison with an internal library of analytical reference material and various external libraries. The resulting datasets are in general more complex. Compounds are identified on different levels of certainty or remain unidentified.
For both GC-MS and LC-MS/MS data we work with three different levels of identification (in addition to the unidentified compounds).
|LC-MS/MS data||GC-MS data|
Annotations on this level are the most confident identifications. The annotations are based on three pieces of information: accurate mass, MSMS spectra and known retention time obtained from standards analysed on the same system.
Identified metabolites. Authentic chemical standards are compared to retention time and mass spectra.
Annotations on this level is based on two pieces of information and is divided into two sublevels; level 2a is based on accurate mass and known retention time as obtained from standards analysed on the same system; level 2b is based on accurate mass and MSMS spectra from an external library.
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.
Annotations on this level is based on library searches using the accurate mass and elemental composition alone. Be aware that annotations on this level should be used with care, as more than one elemental composition could be matched with the same accurate mass, even with the high accuracy on the instruments we use. It is impossible to distinguish between isomers on this annotation level.
For unidentified compounds the elemental composition is determined if a good match is found between the accurate mass obtained and the isotope pattern.
Putatively characterized compound classes
External calibration is based on the comparison of the response of a known amount of analytical reference material with the response of sample material to determine the amount of a metabolite in a sample. A drawback of this approach is that the sample matrix might modify the response of a metabolite from sample analysis. This is especially relevant in mass spectrometry, where so-called ion suppression is commonly observed. Therefore, metabolite amounts in samples might be underestimated.
Internal calibration is based on the comparison of the response of reference material very similar to a specific metabolite which is added to the sample matrix. As standard MS-Omics uses stable isotopes of a metabolite. This approach omits potential matrix effects giving more accurate results.
If neither an external nor internal reference is applied during analysis, no amounts of a metabolite can be estimated. In these cases, MS-Omics provides relative values, meaning the response of the same metabolite can be compared between samples. However, it is not possible to compare the response of one metabolite to another metabolite even in the same sample due to the nature of analysis.
We take a lot of effort to ensure that the data that we deliver are of the highest possible quality and to ensure that we do not introduce bias that can interfere with the interpretation of the results.
- A system suitability check of the analytical instrument is performed for every batch analysis.
- System suitability samples are analysed before and after batch analysis.
- We pool sample aliquots to create a representative QC sample.
- Every five-to-six samples a QC sample is analysed to monitor instrument performance throughout a batch analysis.
- Samples are randomised prior to analyses.