Search

Rationale: Atmospheric pressure drift tube ion mobility is a powerful addition to the Orbitrap mass spectrometer enabling direct separation of isomers. Apart from offering high resolving power in a compact design, it also facilitates optimization of the separation gas, as shown here for a series of biologically relevant isomer pairs., Methods: An Excellims MA3100 High-Resolution Atmospheric Pressure Ion Mobility Spectrometer (HR-IMS) was coupled to a Thermo Scientific™ Q Exactive™ Focus hybrid quadrupole-Orbitrap™ mass spectrometer, using an Excellims Directspray™ Electrospray Ionization source and a gas mixture setup to provide various drift gases (air, CO 2 and mixtures). This instrument combination was used to separate isomers of eight pairs of metabolites and gangliosides, optimizing drift gas conditions for best separation of each set., Results: All but one of the isomers pairs provided could be partially or fully separated by the HR-IMS-MS combination using ion mobility drift times. About half of the separated compounds showed significantly better analytical separation when analyzed in a mixture of CO 2 and air rather than air or CO 2 alone. Resolving power of up to 102 was achieved using the 10 cm atmospheric drift tube ion mobility add-on for the Orbitrap mass spectrometer., Conclusions: The present analysis demonstrates the usefulness of using atmospheric drift tube IMS on an Orbitrap mass spectrometer to characterize the isomeric composition of samples. It also highlights the potential benefits of being able to quickly optimize the drift gas composition to selectively maximize the mobility difference for isomer separation., (© 2019 John Wiley & Sons, Ltd.)

Motivation: Flow Injection Analysis coupled to High-Resolution Mass Spectrometry (FIA-HRMS) is a promising approach for high-throughput metabolomics. FIA-HRMS data, however, cannot be preprocessed with current software tools which rely on liquid chromatography separation, or handle low resolution data only., Results: We thus developed the proFIA package, which implements a suite of innovative algorithms to preprocess FIA-HRMS raw files, and generates the table of peak intensities. The workflow consists of 3 steps: (i) noise estimation, peak detection and quantification, (ii) peak grouping across samples and (iii) missing value imputation. In addition, we have implemented a new indicator to quantify the potential alteration of the feature peak shape due to matrix effect. The preprocessing is fast (less than 15 s per file), and the value of the main parameters (ppm and dmz) can be easily inferred from the mass resolution of the instrument. Application to two metabolomics datasets (including spiked serum samples) showed high precision (96%) and recall (98%) compared with manual integration. These results demonstrate that proFIA achieves very efficient and robust detection and quantification of FIA-HRMS data, and opens new opportunities for high-throughput phenotyping., Availability and Implementation: The proFIA software (as well as the plasFIA dataset) is available as an R package on the Bioconductor repository (http://bioconductor.org/packages/proFIA), and as a Galaxy module on the Main Toolshed (https://toolshed.g2.bx.psu.edu), and on the Workflow4Metabolomics online infrastructure (http://workflow4metabolomics.org)., Contact: alexis.delabriere@cea.fr or etienne.thevenot@cea.fr., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com)

Lipids are natural substances found in all living organisms. Essential to the integrity of cell membranes, they also have many biological functions linked to energy storage and cell signaling, and are involved in a large number of heterogeneous diseases such as cancer, diabetes, neurological disorders, and inherited metabolic diseases. Lipids are challenging to analyze because of their huge structural diversity and numerous species. Up to now, lipid analysis has been achieved by targeted approaches focusing on selected families and relying on extraction protocols and chromatographic methods coupled to various detectors including mass spectrometry. Thanks to the technological improvements achieved in the fields of chromatography, high-resolution mass spectrometry and bioinformatics, it is possible to perform global lipidomic analyses enabling the concomitant detection, identification and relative quantification of many lipid species belonging to different families. The aim of this review is to focus on mass spectrometry-based methods to perform lipid and lipidomic analyses and on their application to the analysis of cerebrospinal fluid.

The metabolome is the set of small molecular mass compounds found in biological media, and metabolomics, which refers to as the analysis of metabolome in a given biological condition, deals with the large scale detection and quantification of metabolites in biological media. It is a data driven and multidisciplinary approach combining analytical chemistry for data acquisition, and biostatistics, informatics and biochemistry for mining and interpretation of these data. Since the middle of the 2000s, high resolution mass spectrometry is widely used in metabolomics, mainly because the detection and identification of metabolites are improved compared to low resolution instruments. As the field of HRMS is quickly and permanently evolving, the aim of this work is to review its use in different aspects of metabolomics, including data acquisition, metabolite annotation, identification and quantification. At last, we would like to show that, thanks to their versatility, HRMS instruments are the most appropriate to achieve optimal metabolome coverage, at the border of other omics fields such as lipidomics and glycomics., (© 2013 Wiley Periodicals, Inc.)

Assessment of myocardial viability during ex situ heart perfusion (ESHP) is only based on lactate trends. Metabolomic profiling of hearts donated after circulatory death (DCD) was performed to investigate new biomarkers of myocardial viability during ESHP. Eighteen piglets were randomly allocated in three groups (N=6/per group): donor hearts procured either after 15 minutes of warm ischemia (DCD group); after brain-stem death (BSD group); or without DCD nor BSD (Control group). Blood normothermic ESHP was then initiated for 240 minutes. Plasma and myocardial samples were procured respectively every 30 and 60 minutes, and analyzed by liquid chromatography coupled to high-resolution mass spectrometry. Median duration of agonal phase was 24 minutes [22-29] in DCD animals, including 15 minutes of functional warm ischemia. Mean coronary flow and mean aortic pressure during ESHP ranged from 720 to 740 mL/min, and from 68 to 73 mmHg respectively, without differences between groups (P=0.544 and P=0.203). At T0, arterial lactate was higher in DCD (7.0±0.9) than in BSD (1.1±0.2) and Control groups (2.0±0.8 mmol/L, P<0.01), and progressively decreased until T240. Lactate level within myocardial biopsies was not significantly different between groups at T0 (P=0.281), and remained stable over the 4-hour period of ESHP. Three different metabolomic profiles corresponding to DCD, BSD and Control groups were remarkable from T30 to T240, including 300 different metabolites in plasma and tissue samples. Marked nucleotide degradation was observed in DCD group compared to BSD and Control groups (P<0.01). Plasma levels of inosine and guanosine were significantly higher in DCD group and progressively decreased over the time to reach control level after 210 minutes of ESHP (Figure 1). A specific metabolomic profile was observed in donor hearts exposed to warm ischemia. Considering plasma levels of inosine and guanosine, nucleotides could be relevant biomarkers for viability assessment of DCD hearts. [ABSTRACT FROM AUTHOR]