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Hydrophilic interaction liquid chromatography (HILIC) coupled to drift tube ion mobility spectrometry (DTIMS) was used to separate diastereomers of five-unit oligonucleotides containing 0, 1, 2 or 3 phosphorothioate (PS) linkages. Multiplexed DTIMS (where ions are pulsed into the drift tube according to a pre-encoded sequence) and post-acquisition processing using an innovative demultiplexing tool were investigated. The electric field inside the drift tube was optimized to achieve the highest resolving power. The entrance voltage providing the best two-peak resolution was −1000V with 3-bit multiplexing. Under optimized conditions, the eight diastereomers of an oligonucleotide with three PS linkages (5′-TC*G*T*G-3′) could be separated unambiguously. Indeed, those diastereomers differed in their collision cross section (CCS) values. The minimal CCS values difference between two adjacent diastereomers was 0.9% with maximal RSD on CCS values of 0.3%. The use of multiplexed ion mobility and the novel high-resolution demultiplexing tool represents a real breakthrough for resolution enhancement of diastereomers in linear DTIMS.

Volumetric absorptive microsampling (VAMS) enables the collection of small and accurate quantities of biological fluids. Therefore, this sampling technique is of great interest for volume-limited samples or serial collection of samples. In this study, we examined the potential of VAMS for targeted mass spectrometry (MS)-based metabolomics. The targeted analysis of 36 major metabolites from only 10 μL of whole blood was optimized. A design of experiments was carried out to maximize the extraction of metabolites. Moreover, critical steps in sample preparation and sample analysis were studied and characterized, such as the addition of internal standards to tips of VAMS devices before sample collection. A reversed-phase UHPLC–MS/MS method was used to analyze organic acids, whereas hydrophilic interaction chromatography (HILIC)–MS/MS was selected for the determination of amino acids. Overall, the optimum extraction solvent was acetonitrile-water in a proportion of 60:40 (v/v), providing good recoveries and resulting in the detection of all target metabolites in whole blood with good repeatability (less than 15% RSD on peak area). Furthermore, the stability of the analytes in dried whole blood, which is of critical importance in metabolomics studies, was investigated. The amino and organic acids were stable for at least 4 days when stored at room temperature. This is in contrast to the instability of these compounds in wet blood, thereby showing the great potential of VAMS in metabolomics studies.

Ion mobility (IM) mass spectrometry allows conducting data independent acquisition (DIA) where all ions entering the instrument are fragmented based on their drift time. In this work, DIA operational parameters were first optimized using a design of experiments. The optimization of data treatment involved a smoothing algorithm of the IM dimension, which increased the number of identified peptides. Then, classical DDA and IM-based DIA were compared injecting increasing amounts of a complex proteome digest (E. coli). Results revealed that compared to DDA, DIA allowed to identify from 2 to 3.3 times more proteins, depending on the injected quantity. To evaluate proteome coverage, endogenous proteins in E. coli cells were sorted by abundance deciles. A large majority of the proteins uniquely observed in DDA were part of the 10% most abundant protein groups. Interestingly, owing to the absence of ion-picking algorithm, DIA allowed to identify proteins coming from a broader concentration range therefore greatly improving proteome coverage. Furthermore, ion mobility separation improved coverage by separating co-eluting peptides. Physicochemical properties of peptides uniquely detected by DIA or DDA were also compared using supervised and unsupervised multivariate analysis. As a result, peptides having a higher mass and being relatively hydrophobic were significantly more identified in DIA. Finally, semi-quantitative performance of both methods was investigated and proved to be comparable, except that DIA demonstrated a better sensitivity than DDA. As a conclusion, we demonstrated in this study that both acquisition modes provide complementary information about the proteome under investigation.

The present review deals with the recent developments in metabolome analysis to improve the diagnosis of diseases and the identification of biomarkers. A particular focus has been put on the application of the non-invasive and up-to-date microsampling and microextraction procedures for the targeted/untargeted metabolome analysis from low volume of samples. These approaches aim to enhance sensitivity for the study of highly bioactive, short-lived, and low-abundant metabolites from complex matrices, especially when access to high sample volumes is not possible. The main strengths and weaknesses of those modern approaches as well as robust solutions to meet the undeniable challenges in metabolomics field are also presented. Moreover, some attractive alternatives for the better extraction of hydrophilic metabolites are discussed. Besides, information are given related to method validation results (such as recovery, matrix effect, detection limit, reproducibility, stability, etc.) as well as perspectives of these modern procedures in the context of diseases understanding, diagnosis, and follow up.