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Lipids are biomolecules of crucial importance involved in critical biological functions. Yet, lipid content determination using mass spectrometry is still challenging due to their rich structural diversity. Preferential ionisation of the different lipid species in the positive or negative polarity is common, especially when using soft ionisation mass spectrometry techniques. Here, we demonstrate the potency of a dual-polarity approach using surface-assisted laser desorption/ionisation coupled to Fourier transform-ion cyclotron resonance (SALDI FT-ICR) mass spectrometry imaging (MSI) combined with Kendrick mass defect data filtering to (i) identify the lipids detected in both polarities from the same tissue section and (ii) show the complementarity of the dual-polarity data, both regarding the lipid coverage and the spatial distributions of the various lipids. For this purpose, we imaged the same mouse brain section in the positive and negative ionisation modes, on alternate pixels, in a SALDI FT-ICR MS imaging approach using gold nanoparticles (AuNPs) as dual-polarity nanosubstrates. Our study demonstrates, for the first time, the feasibility of (i) a dual-polarity SALDI-MSI approach on the same tissue section, (ii) using AuNPs as nanosubstrates combined with a FT-ICR mass analyser and (iii) the Kendrick mass defect data filtering applied to SALDI-MSI data. In particular, we show the complementarity in the lipids detected both in a given ionisation mode and in the two different ionisation modes. Graphical abstract.

Mass spectrometry imaging (MSI) is an analytical technique for the unlabeled and multiplex imaging of molecules in biological tissue sections. It therefore enables the spatial and molecular annotations of tissues complementary to histology. It has already been shown that MSI can guide subsequent material isolation technologies such as laser microdissection (LMD) to enable a more in-depth molecular characterization of MSI-highlighted tissue regions. However, with MSI now reaching spatial resolutions at the single-cell scale, there is a need for a precise co-registration between MSI and the LMD. As proof-of-principle, MSI of lipids was performed on a breast cancer tissue followed by a segmentation of the data to detect molecularly distinct segments within its tumor areas. After image processing of the segmentation results, the coordinates of the MSI-detected segments were passed to the LMD system by three co-registration steps. The errors of each co-registration step were quantified and the total error was found to be less than 13 μm. With this link established, MSI data can now accurately guide LMD to excise MSI-defined regions of interest for subsequent extract-based analyses. In our example, the excised tissue material was then subjected to ultrasensitive microproteomics in order to determine predominant molecular mechanisms in each of the MSI-highlighted intratumor segments. This work shows how the strengths of MSI, histology, and extract-based omics can be combined to enable a more comprehensive molecular characterization of in situ biological processes. Electronic supplementary material The online version of this article (10.1007/s00216-019-01983-z) contains supplementary material, which is available to authorized users.

MALDI mass spectrometry imaging (MSI) allows the mapping and the tentative identification of compounds based on their m/z value. In typical MSI, a spectrum is taken at incremental 2D coordinates (pixels) across a sample surface. Single pixel mass spectra show the resolving power of the mass analyzer. Mass shift, i.e., variations of the m/z of the same ion(s), may occur from one pixel to another. The superposition of shifted masses from individual pixels peaks apparently degrades the resolution and the mass accuracy in the average spectrum. This leads to low confidence annotations and biased localization in the image. Besides the intrinsic performances of the analyzer, the sample properties (local composition, thickness, matrix deposition) and the calibration method are sources of mass shift. Here, we report a critical analysis and recommendations to mitigate these sources of mass shift. Mass shift 2D distributions were mapped to illustrate its effect and explore systematically its origin. Adapting the sample preparation, carefully selecting the data acquisition settings, and wisely applying post-processing methods (i.e., m/z realignment or individual m/z recalibration pixel by pixel) are key factors to lower the mass shift and to improve image quality and annotations. A recommended workflow, resulting from a comprehensive analysis, was successfully applied to several complex samples acquired on both MALDI ToF and MALDI FT-ICR instruments.

Unregulated growth promoter use in food-producing animals is an issue of concern both from food safety and animal welfare perspectives. However, the monitoring of such practices is analytically challenging due to the concerted actions of users to evade detection. Techniques based on the monitoring of biological responses to exogenous administrations have been proposed as more sensitive methods to identify treated animals. This study has, for the first time, profiled plasma proteome responses in bovine animals to treatment with nortestosterone decanoate and 17β-oestradiol benzoate, followed by dexamethasone administration. Two-dimensional fluorescence differential in-gel electrophoresis analysis revealed a series of hepatic and acute-phase proteins within plasma whose levels were up- or down-regulated within phases of the treatment regime. Surface plasmon resonance (SPR) immuno-assays were developed to quantify responses of identified protein markers during the experimental treatment study with a view to developing methods which can be used as screening tools for growth promoter abuse detection. SPR analysis demonstrated the potential for plasma proteins to be used as indicative measures of growth promoter administrations and concludes that the sensitivity and robustness of any detection approach based on plasma proteome analysis would benefit from examination of a range of proteins representative of diverse biological processes rather being reliant on specific individual markers.

The study and extension of a simple automated clean-up method for polychlorinated dibenzo-p-dioxins (PCDD) and polychlorinated dibenzofurans (PCDF) to a broad range of polychlorinated biphenyls (PCB) is described. The isolation of seven PCDD, ten PCDF, and three coplanar PCB (cPCB) is extended to eight monoortho substituted PCB and seven so-called "marker PCB" (Aroclor 1260) for fatty food samples. This enables quantification of 35 compounds - including all congeners with a WHO toxic equivalent factor (TEF)--in a single extraction and single purification step. The chromatographic behaviour of mono-ortho PCB and marker PCB on a variety of adsorbents, including basic alumina, has been studied. Partitioning of analytes through multi-column sequences is described and correlated with their structural and electronic properties, by use of molecular modelling calculations. The fractionation process available with the Power-Prep automated clean-up system enables rapid independent analysis of the different groups of compounds. Gas chromatography with high resolution mass spectrometry (GC-HRMS) is used for the PCDD/F and cPCB fraction and quadrupole ion-storage tandem in time mass spectrometry (GC-QISTMS) for analysis of the remaining PCB. A comparison study was performed on quality-control samples and real fatty food samples to evaluate the robustness of the new strategy compared with a reference method. On the basis of this simultaneous clean-up, a rapid simplified strategy for PCDD/F and selected PCB analysis determination is proposed for fatty food samples.

G-protein-coupled receptors (GPCRs) constitute the largest family of transmembrane proteins. Although implicated in almost all physiological processes in the human body, most of them remain unexploited, mostly because of the lack of specific ligands. The objective of this work is to develop a new mass-spectrometry-based technique capable of identifying new peptide ligands for GPCRs. The strategy is based on the incubation of cellular membranes overexpressing GPCRs with a mixture of peptides that contains potential ligands. Peptide ligands bind to the receptors, whereas other peptides remain in the binding buffer. Bound peptides are eluted from membranes and directly detected, identified, and characterized by MALDI TOF–TOF. The results reveal the efficacy of the procedure for selecting a specific ligand of GPCRs in both simple and complex mixtures of peptides. This new approach may offer direct purification, identification, and characterization of the new ligand in a single workflow. The proposed method is labeling-free and, unlike radio-binding and other techniques, it does not require a previously known labeled ligand of the studied GPCR. All these properties greatly reduce the experimental constraints. Moreover, because it is not based on the principle of a competitive specific binding, this technique constitutes a new tool to discover new ligands not only for known GPCRs, but also for orphan GPCRs.

In the last few years, matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) has been successfully used to study the distribution of lipids within tissue sections. However, few efforts have been made to acquire reliable quantitative data regarding the localized concentrations of these molecules. Here we propose an approach based on brain homogenates for the quantification of phosphatidylcholines (PCs) in brain section by MALDI MSI. Homogenates were spiked with a range of PC(16:0 d31/18:1) concentrations. Sections from homogenates and intact brain were simultaneously prepared before being analyzed by MALDI MSI using a Fourier transform ion cyclotron resonance (FT-ICR) analyzer. Standard curves were generated from the signal intensity of the different PC(16:0 d31/18:1) ionic species ([M+H](+), [M+Na](+) and [M+K](+)) detected from the homogenate sections. Localized quantitative data were finally extracted by correlating the standard curves with the signal intensities of endogenous PC (especially PC(16:0/18:1)) ionic species detected on different areas of the brain section. They were consistent with quantitative values found in the literature. This work introduces a new method to take directly into account biological matrix effects for the quantification of lipids as well as other endogenous compounds, in tissue sections by MALDI MSI.

The quantitative detection of allergens in the food chain is a strategic health objective as the prevalence of allergy continues to rise. Food allergenicity is caused by proteins either in their native form or in forms resulting from food processing. Progress in mass spectrometry greatly opened up the field of proteomics. These advances are now available for the detection and the quantification of traces of allergenic proteins in complex mixtures, and complete the set of biological tests used until now, such as ELISA or PCR. We review methods classified according to their ability to simultaneously quantify and identify allergenic proteins and underline major advances in the mass-spectrometric methods.