A major problem limiting reproducible use of liquid extraction surface analysis (LESA) array sampling of dried surface-deposited liquid samples is the unwanted spread of extraction solvent beyond the dried sample limits, resulting in unreliable data. Here, we explore the use of the Droplet Microarray (DMA), which consists of an array of superhydrophilic spots bordered by a superhydrophobic material giving the potential to confine both the sample spot and the LESA extraction solvent in a defined area. We investigated the DMA method in comparison with a standard glass substrate using LESA analysis of a mixture of biologically relevant compounds with a wide mass range and different physicochemical properties. The optimized DMA method was subsequently applied to urine samples from a human intervention study. Relative standard deviations for the signal intensities were all reduced at least 3-fold when performing LESA-MS on the DMA surface compared with a standard glass surface. Principal component analysis revealed more tight clusters indicating improved spectral reproducibility for a human urine sample extracted from the DMA compared to glass. Lastly, in urine samples from an intervention study, more significant ions (145) were identified when using LESA-MS spectra of control and test urine extracted from the DMA. We demonstrate that DMA provides a surface-assisted LESA-MS method delivering significant improvement of the surface extraction repeatability leading to the acquisition of more robust and higher quality data. The DMA shows potential to be used for LESA-MS for controlled and reproducible surface extraction and for acquisition of high quality, qualitative data in a high-throughput manner.

Volatile organic compounds (VOCs) in exhaled breath provide insights into various metabolic processes and can be used to monitor physiological response to exercise and medication. We integrated and validated in situ a sampling and analysis protocol using proton transfer reaction time-of-flight mass spectrometry (PTR-ToF-MS) for exhaled breath research. The approach was demonstrated on a participant cohort comprising users of the cholesterol-lowering drug statins and non-statin users during a field campaign of three days of prolonged and repeated exercise, with no restrictions on food or drink consumption. The effect of prolonged exercise was reflected in the exhaled breath of participants, and relevant VOCs were identified. Most of the VOCs, such as acetone, showed an increase in concentration after the first day of walking and subsequent decrease towards baseline levels prior to walking on the second day. A cluster of short-chain fatty acids including acetic acid, butanoic acid, and propionic acid were identified in exhaled breath as potential indicators of gut microbiota activity relating to exercise and drug use. We have provided novel information regarding the use of breathomics for non-invasive monitoring of changes in human metabolism and especially for the gut microbiome activity in relation to exercise and the use of medication, such as statins.

We present here a novel surface mass spectrometry strategy to perform untargeted metabolite profiling of formalinfixed paraffin-embedded pediatric ependymoma archives. Sequential Orbitrap secondary ion mass spectrometry (3D OrbiSIMS) and liquid extraction surface analysis-tandem mass spectrometry (LESA-MS/MS) permitted the detection of 887 metabolites (163 chemical classes) from pediatric ependymoma tumor tissue microarrays (diameter: <1 mm; thickness: 4 μm). From these 163 classes, 60 classes were detected with both techniques, whilst LESA-MS/MS and 3D OrbiSIMS individually allowed the detection of another 83 and 20 unique metabolite classes, respectively. Through data fusion and multivariate analysis, we were able to identify key metabolites and corresponding pathways predictive of tumor relapse, which were retrospectively confirmed by gene expression analysis with publicly available data. Altogether, this sequential mass spectrometry strategy has shown to be a versatile tool to perform high-throughput metabolite profiling on sample-limited tissue archives.

Human pluripotent stem cells (hPSCs) can be expanded and differentiated in vitro into almost any adult tissue cell type, and thus have great potential as a source for cell therapies with biomedical application. In this study, a fully‐defined polymer synthetic substrate is identified for hPSC culture in completely defined, xenogenic (xeno)‐free conditions. This system can overcome the cost, scalability, and reproducibility limitations of current hPSC culture strategies, and facilitate large‐scale production. A high‐throughput, multi‐generational polymer microarray platform approach is used to test over 600 unique polymers and rapidly assess hPSC‐polymer interactions in combination with the fully defined xeno‐free medium, Essential 8 (E8). This study identifies a novel nanoscale phase separated blend of poly(tricyclodecane‐dimethanol diacrylate) and poly(butyl acrylate) (2:1 v/v), which supports long‐term expansion of hPSCs and can be readily coated onto standard cultureware. Analysis of cell‐polymer interface interactions through mass spectrometry and integrin blocking studies provides novel mechanistic insight into the role of the E8 proteins in promoting integrin‐mediated hPSC attachment and maintaining hPSC signaling, including ability to undergo multi‐lineage differentiation. This study therefore identifies a novel substrate for long‐term serial passaging of hPSCs in serum‐free, commercial chemically‐defined E8, which provides a promising and economic hPSC expansion platform for clinical‐scale application.

Untargeted metabolite profiling of biological samples is a challenge for analytical science due to the high degree of complexity of biofluids. Isobaric species may also not be resolved using mass spectrometry alone. As a result of these factors, many potential biomarkers may not be detected or are masked by co-eluting interferences in conventional LC-MS metabolomic analyses. In this study, a comprehensive liquid chromatography-mass spectrometry workflow incorporating a fast-scanning miniaturised high-field asymmetric waveform ion mobility spectrometry separation (LC-FAIMS-MS) is applied to the untargeted metabolomic analysis of human urine. The time-of-flight mass spectrometer used in the study was scanned at a rate of 20 scans s −1 enabling a FAIMS CF spectrum to be acquired within a 1-s scan time, maintaining an adequate number of data points across each LC peak. The developed method is demonstrated to be able to resolve co-eluting isomeric species and shows good reproducibility (%RSD < 4.9%). The nested datasets obtained for fresh, aged, and QC urine samples were submitted for multivariate statistical analysis. Seventy unique biomarker ions showing a statistically significant difference between fresh and aged urine were identified with optimal transmission CF values obtained across the full CF spectrum. The potential of using FAIMS to select ions for in-source collision-induced dissociation is demonstrated for FAIMS-selected methylxanthine ions yielding characteristic fragment ion species indicative of the precursor. Graphical abstract Electronic supplementary material The online version of this article (10.1007/s00216-019-01790-6) contains supplementary material, which is available to authorized users.