Metabolomics has demonstrated a great potential in numerous biomedical research fields in the last years, such as the study of the underlying pathology of diseases, discovery of diagnostic biomarkers or drug development. Nowadays, the main challenge in metabolomics is to obtain comprehensive and unbiased metabolomic profiles due to the huge complexity, heterogeneity and dynamism of metabolome. For this purpose, mass spectrometry represents a very interesting analytical platform, since complexity of metabolome may be overcome through the use of different orthogonal separation techniques, including liquid chromatography, gas chromatography and capillary electrophoresis. Alternatively, direct mass spectrometry analysis, either by direct infusion or flow injection, has been postulated as an alternative in metabolomics, complementing hyphenated approaches. These techniques exhibit several advantages such as the ability for high-throughput screening, fast analysis and wide metabolomic coverage, since there is not exclusion of compounds due to the separation device.
The present work explores the potential of metabolomic platforms based on direct infusion mass spectrometry for metabolic fingerprinting of serum samples. The most important issues to be considered in this type of approaches were reviewed, including sample handling, comprehensive analysis, data processing, as well as further identification of metabolites and global characterization of metabolomic fingerprints.
In this study, I didn't work with standards because obtaining a representative set of metabolites of the complex serum metabolome is a very complicated task. As previously reported, “matrix-based ion suppression effects were evaluated by analyzing several samples at different dilution factors, and by comparing the resulting TIC of infusion profiles and the number of peaks” (Anal. Bioanal. Chem. 2014, 406, 7137).
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Effectively, DIMS shows a great potential for the determination of high abundance lipids (e.g. phospholipids, triglycerides when choloform extracts are analyzed), while detection of low molecular weigh (hydrophilic) metabolites is hindered by ion suppression effects. Anyway, I previously used this metabolomic platform for fingerprinting multiple biological samples (serum, brain, liver), and I was able to detect some specific classes of metabolites, such as bile acids, acyl-carnitines or purines, among others (Electrophoresis, 2015, 36, 2237–2249; J Pharm Biomed Anal 2015, 102, 425–435; J Pharm Biomed Anal 2015, 107, 378-385).