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Mass spectrometry in untargeted liquid chromatography/mass spectrometry metabolomics: Electrospray ionisation parameters and global coverage of the metabolome
Author(s) -
Tugizimana Fidele,
Steenkamp Paul A.,
Piater Lizelle A.,
Dubery Ian A.
Publication year - 2017
Publication title -
rapid communications in mass spectrometry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.528
H-Index - 136
eISSN - 1097-0231
pISSN - 0951-4198
DOI - 10.1002/rcm.8010
Subject(s) - metabolome , chemistry , metabolomics , mass spectrometry , chromatography , electrospray , electrospray ionization , analytical chemistry (journal) , resolution (logic) , capillary electrophoresis–mass spectrometry , principal component analysis , sample preparation , computer science , artificial intelligence
Rationale Liquid chromatography coupled to mass spectrometry (LC/MS) is a dominant analytical platform in metabolomics, because of the high sensitivity and resolution, thus enabling large‐scale coverage of metabolomes. Correspondingly, electrospray ionisation (ESI) is the favoured ionisation method in untargeted LC/MS metabolomics given the ability to produce large numbers of ions. In the workflow of LC/ESI‐MS metabolomics, maximising the ionisation efficiency over a wide mass range is inevitably an essential and determining step, subsequently defining the extent of coverage of the metabolome under investigation. Thus in this study, electronic factors related to the functioning of the ESI source, namely the capillary and sample cone voltages, were explored to investigate the influence on the data acquired in metabolomic investigations. Methods Hydromethanolic samples from an untargeted study (sorghum plants responding dynamically to fungal infection) were analysed on a high‐resolution/definition LC/ESI‐MS system. Here the capillary and sample cone voltages of the ZSpray™ ESI source were varied between 1.5–3.0 kV and 10.0–40.0 V, respectively. The acquired data were processed with MarkerLynx™ software and analysed using central composite design response surface methodology and chemometric approaches (principal component analysis and orthogonal projection latent structures‐discriminant analysis). Results The results evidently demonstrate that both capillary and sampling cone voltages not only significantly influence the recorded MS signals with regard to the number and abundance of features, but also the overall structure of the collected data. This consequently impacts on the information extracted from the data and thus affects coverage of the metabolome. Conclusions The observations postulate in that, untargeted LC/MS metabolomics, ' what you see is what you ionise '. Although there is convergence of collected data under different ESI conditions, the nuances observed indicate that the exploration of different ion source settings could be the best trade‐off in expanding and maximising the metabolome coverage in untargeted metabolomic experiments.