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:
| INTRODUCTIONUntargeted, global metabolite profiling, a scientific approach followed in metabolomics, is a rapidly growing and maturing research field, and has become an indispensable pillar for systems biology approaches, providing direct functional information for understanding biological systems. [1][2][3] Comprehensive analysis (qualitatively and quantitatively) of exo-and/or endo-metabolites, as readouts of cellular metabolism, is the focus of metabolomics. These small molecules (of molecular weight ≤ 1500 Da) represent functional entities that collectively define the developmental, physiological, or pathological status of a biological system. 4,5 Ideally, the holistic coverage of the metabolome in toto, in a given biosystem, is the ultimate aim of an untargeted metabolomic study.However, the realisation of such a goal is not yet possible at present, considering technological, analytical and algorithmic limitations.Another contributing factor is the inherent complexity of metabolomes due to the physicochemical diversity, instability, and rapid turnover of