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Metabolomic fingerprinting of serum samples by direct infusion mass spectrometry
Raúl González-Domínguez
1  Department of Chemistry, Faculty of Experimental Sciences. University of Huelva, Spain.


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.

Keywords: metabolomics; direct infusion mass spectrometry; serum
Comments on this paper
Margaret Coe
ion suppression
Have you tried spiking the serum with different classes of compounds; simulating metabolite fold changes; to see how the remaining classes are affected? Was ion suppression of certain classes more evident than in other classes of metabolites?

Raúl González-Domínguez
Dear Ms. Coe,

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).

Best regards

Jim Kapron
Ultrafast Statistical Profiling of bacterial metabolite extracts
Several years ago, Bruker published an application note on this subject using direct infusion. We found the resolution of the MS needed to be very high to have greater confidence in the results. Do you think serum is a sufficiently different matrix or would this FTMS technique also be applicable to your work?
Raúl González-Domínguez
Of course, FTMS presents a great potential for this purpose because of its ultra high resolution capabilities. Anway, the utility of TOF instruments has also been demostrated in múltiple studies, as recently reviewd (Bioanalysis, 2016, in press)

Daniel Raftery
ion suppresion in different metabolite classes
As far as measure lipids, DI seems to work well if sufficient standards are added, while polar metabolites are more complicated. I'm wondering if you've thought of trying to analyze more limited sets or specific classes of metabolites using DI, such as bile acids?

Raúl González-Domínguez
Dear Prof. Raftery,
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).