Ultrahigh-performance supercritical fluid chromatography – mass spectrometry for the qualitative analysis of metabolites covering a large polarity range

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Abstract

The applicability of ultrahigh-performance supercritical fluid chromatography coupled with mass spectrometry (UHPSFC/MS) for the qualitative analysis of metabolites with a wide polarity range (log P: -3.89-18.95) was evaluated using a representative set of 78 standards belonging to nucleosides, biogenic amines, carbohydrates, amino acids, and lipids. The effects of the gradient shape and the percentage of water (1, 2, and 5%) were investigated on the Viridis BEH column. The screening of eight stationary phases was performed for columns with different interaction sites, such as hydrogen bonding, hydrophobic, π-π, or anionic exchange type interactions. The highest number of compounds (67) of the set studied was detected on the Torus Diol column, which provided a resolution parameter of 39. The DEA column had the second best performance with 58 detected standards and the resolution parameter of 54. The overall performance of other parameters, such as selectivity, peak height, peak area, retention time stability, asymmetry factor, and mass accuracy, led to the selection of the Diol column for the final method. The comparison of additives showed that ammonium acetate gave a superior sensitivity over ammonium formate. Moreover, the influence of the ion source on the ionization efficiency was studied by employing atmospheric pressure chemical ionization (APCI) and electrospray ionization (ESI). The results proved the complementarity of both ionization techniques, but also the superior ionization capacity of the ESI source in the negative ion mode, for which 53% of the analytes were detected compared to only 7% for the APCI source. Finally, optimized analytical conditions were applied to the analysis of a pooled human plasma sample. 44 compounds from the preselected set were detected in human plasma using ESI-UHPSFC/MS in MSE mode considering both ionization modes.

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MZmine 2: Modular framework for processing, visualizing, and analyzing mass spectrometry-based molecular profile data

Tomáš Pluskal, Sandra Castillo, Alejandro Villar-Briones … (2010)

Background Mass spectrometry (MS) coupled with online separation methods is commonly applied for differential and quantitative profiling of biological samples in metabolomic as well as proteomic research. Such approaches are used for systems biology, functional genomics, and biomarker discovery, among others. An ongoing challenge of these molecular profiling approaches, however, is the development of better data processing methods. Here we introduce a new generation of a popular open-source data processing toolbox, MZmine 2. Results A key concept of the MZmine 2 software design is the strict separation of core functionality and data processing modules, with emphasis on easy usability and support for high-resolution spectra processing. Data processing modules take advantage of embedded visualization tools, allowing for immediate previews of parameter settings. Newly introduced functionality includes the identification of peaks using online databases, MSn data support, improved isotope pattern support, scatter plot visualization, and a new method for peak list alignment based on the random sample consensus (RANSAC) algorithm. The performance of the RANSAC alignment was evaluated using synthetic datasets as well as actual experimental data, and the results were compared to those obtained using other alignment algorithms. Conclusions MZmine 2 is freely available under a GNU GPL license and can be obtained from the project website at: http://mzmine.sourceforge.net/. The current version of MZmine 2 is suitable for processing large batches of data and has been applied to both targeted and non-targeted metabolomic analyses.

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Procedures for large-scale metabolic profiling of serum and plasma using gas chromatography and liquid chromatography coupled to mass spectrometry.

Warwick B. Dunn, David I. Broadhurst, Paul Begley … (2011)

Metabolism has an essential role in biological systems. Identification and quantitation of the compounds in the metabolome is defined as metabolic profiling, and it is applied to define metabolic changes related to genetic differences, environmental influences and disease or drug perturbations. Chromatography-mass spectrometry (MS) platforms are frequently used to provide the sensitive and reproducible detection of hundreds to thousands of metabolites in a single biofluid or tissue sample. Here we describe the experimental workflow for long-term and large-scale metabolomic studies involving thousands of human samples with data acquired for multiple analytical batches over many months and years. Protocols for serum- and plasma-based metabolic profiling applying gas chromatography-MS (GC-MS) and ultraperformance liquid chromatography-MS (UPLC-MS) are described. These include biofluid collection, sample preparation, data acquisition, data pre-processing and quality assurance. Methods for quality control-based robust LOESS signal correction to provide signal correction and integration of data from multiple analytical batches are also described.