In the past few years, the gut microbiome has been shown to play an important role in various disorders including in particular cardiovascular diseases. Especially the metabolite trimethylamine-N-oxide (TMAO), which is produced by gut microbial metabolism, has repeatedly been associated with an increased risk for cardiovascular events. Here we report a fast liquid chromatography tandem mass spectrometry (LC-MS/MS) method that can analyze the five most important gut metabolites with regards to TMAO in three minutes. Fast liquid chromatography is unconventionally used in this method as an on-line cleanup step to remove the most important ion suppressors leaving the gut metabolites in a cleaned flow through fraction, also known as negative chromatography. We compared different blood matrix types to recommend best sampling practices and found citrated plasma samples demonstrated lower concentrations for all analytes and choline concentrations were significantly higher in serum samples. We demonstrated the applicability of our method by investigating the effect of a standardized liquid meal (SLM) after overnight fasting of 25 healthy individuals on the gut metabolite levels. The SLM did not significantly change the levels of gut metabolites in serum.

A popular fragmentation technique for non-targeted analysis is called data-independent acquisition (DIA), because it provides fragmentation data for all analytes in a specific mass range. In this work, we demonstrated the strengths and weaknesses of DIA. Two types of chromatography (fractionation/3 min and hydrophilic interaction liquid chromatography (HILIC)/18 min) and three DIA protocols (variable sequential window acquisition of all theoretical mass spectra (SWATH), fixed SWATH and MSALL) were used to evaluate the performance of DIA. Our results show that fast chromatography and MSALL often results in product ion overlap and complex MS/MS spectra, which reduces the quantitative and qualitative power of these DIA protocols. The combination of SWATH and HILIC allowed for the correct identification of 20 metabolites using the NIST library. After SWATH window customization (i.e., variable SWATH), we were able to quantify ten structural isomers with a mean accuracy of 103% (91–113%). The robustness of the variable SWATH and HILIC method was demonstrated by the accurate quantification of these structural isomers in 10 highly diverse blood samples. Since the combination of variable SWATH and HILIC results in good quantitative and qualitative fragmentation data, it is promising for both targeted and untargeted platforms. This should decrease the number of platforms needed in metabolomics and increase the value of a single analysis.

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Metabolomics is emerging as an important field in life sciences. However, a weakness of current mass spectrometry (MS) based metabolomics platforms is the time-consuming analysis and the occurrence of severe matrix effects in complex mixtures. To overcome this problem, we have developed an automated and fast fractionation module coupled online to MS. The fractionation is realized by the implementation of three consecutive high performance solid-phase extraction columns consisting of a reversed phase, mixed-mode anion exchange, and mixed-mode cation exchange sorbent chemistry. The different chemistries resulted in an efficient interaction with a wide range of metabolites based on polarity, charge, and allocation of important matrix interferences like salts and phospholipids. The use of short columns and direct solvent switches allowed for fast screening (3 min per polarity). In total, 50 commonly reported diagnostic or explorative biomarkers were validated with a limit of quantification that was comparable with conventional LC–MS(/MS). In comparison with a flow injection analysis without fractionation, ion suppression decreased from 89% to 25%, and the sensitivity was 21 times higher. The validated method was used to investigate the effects of circadian rhythm and food intake on several metabolite classes. The significant diurnal changes that were observed stress the importance of standardized sampling times and fasting states when metabolite biomarkers are used. Our method demonstrates a fast approach for global profiling of the metabolome. This brings metabolomics one step closer to implementation into the clinic.

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