Abstract
Background: Profiling the whole metabolome with a single injection is not an easy process because the chemical and physical properties of metabolites are totally different with each other and the analytical methodologies and data mining procedures need lots of effort to make such an approach in real. This reality leads researchers to select an already applied methodology for metabolite profiling and analyze the samples through identical techniques.
Objective: In this study, it was focused on answer the question the sample preparation techniques on human blood samples prior to Q-TOF LC/MS analysis affect the number of detectable peaks and analyze the matched metabolites for these peaks. The results were compared with each other.
Methods: Precipitation of proteins with methanol, ultrafiltration (Amicon® Ultra 3 kDa 0.5 mL Centrifugal Filters), liquid-phase extraction (EXtrelut® NT 3 cartridges) and solid-phase extraction (Supelco HybridSPE®-Phospholipid Cartridge) were used for sample preparation on commercial pooled plasma samples. C18 column (Agilent Zorbax 1.8 μM, 50 x 2.1 mm) was used as the chromatography column. Q-TOF LC/MS analysis was performed on positive ionization mode. XCMS and MetaboAnalyst 4.0 - MS Peaks to Pathways utility were used to evaluate the raw data.
Results: Although the number of detected peaks through precipitation of proteins with methanol was the highest one (624 peaks), the detected peaks observed through ultrafiltration- based sample preparation technique matched with the highest number of metabolite peaks (151 metabolites). The number of the matched peaks with metabolites on liquid phase extraction (81 metabolites) was higher than the ones for solid phase extraction (29 metabolites).
Conclusion: The results in this study may provide a novel perspective for analytical chemists working with clinicians to select their sample preparation technique prior to Q-TOF LC/MS based untargeted metabolomic approaches.
Keywords: Metabolomics, XCMS, MetaboAnalyst, Q-TOF LC/MS, sample preparation, metabolic pathway analysis.
Graphical Abstract
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