Literature DB >> 28613827

Tuning Metabolome Coverage in Reversed Phase LC-MS Metabolomics of MeOH Extracted Samples Using the Reconstitution Solvent Composition.

Anna Lindahl1, Siv Sääf2, Janne Lehtiö1, Anders Nordström2,1.   

Abstract

Considering the physicochemical diversity of the metabolome, untargeted metabolomics will inevitably discriminate against certain compound classes. Efforts are nevertheless made to maximize the metabolome coverage. Contrary to the main steps of a typical liquid chromatography-mass spectrometry (LC-MS) metabolomics workflow, such as metabolite extraction, the sample reconstitution step has not been optimized for maximal metabolome coverage. This sample concentration step typically occurs after metabolite extraction, when dried samples are reconstituted in a solvent for injection on column. The aim of this study was to evaluate the impact of the sample reconstitution solvent composition on metabolome coverage in untargeted LC-MS metabolomics. Lysogeny Broth medium samples reconstituted in MeOH/H2O ratios ranging from 0 to 100% MeOH and analyzed with untargeted reversed phase LC-MS showed that the highest number of metabolite features (n = 1500) was detected in samples reconstituted in 100% H2O. As compared to a commonly used reconstitution solvent mixture of 50/50 MeOH/H2O, our results indicate that the small fraction of compounds increasing in peak area response by the addition of MeOH to H2O, 5%, is outweighed by the fraction of compounds with decreased response, 57%. We evaluated our results on human serum samples from lymphoma patients and healthy control subjects. Reconstitution in 100% H2O resulted in a higher number of significant metabolites discriminating between these two groups than both 50% and 100% MeOH. These findings show that the sample reconstitution step has a clear impact on the metabolome coverage of MeOH extracted biological samples, highlighting the importance of the reconstitution solvent composition for untargeted discovery metabolomics.

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Year:  2017        PMID: 28613827     DOI: 10.1021/acs.analchem.7b00475

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   6.986


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