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Recently, a novel technology was published, utilizing the strengths of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) and immunohistochemistry (IHC), achieving highly multiplexed, targeted imaging of biomolecules in tissue. This new technique, called MALDIIHC, opened up workflows to target molecules of interest using MALDI-MSI that are usually targeted by standard IHC. In this paper, the utility of targeted MALDIIHC and its complementarity with untargeted on-tissue bottom-up spatial proteomics is explored using breast cancer tissue. Furthermore, the MALDI-2 effect was investigated and demonstrated to improve MALDI-IHC. Formalin-fixed paraffin-embedded (FFPE) human breast cancer tissue sections were stained for multiplex MALDI-IHC with six photocleavable mass-tagged (PC-MT) antibodies constituting a breast cancer antibody panel (CD20, actin-alpha SM, HER2, CD68, vimentin, and panCK). K-means spatial clusters were created based on the MALDI-IHC images and cut out using laser-capture microdissection (LMD) for further untargeted LC-MS-based bottom-up proteomics analyses. Numerous peptides could be tentatively assigned to multiple proteins, of which three proteins were also part of the antibody panel (vimentin, keratins, and actin). Post-ionization with MALDI-2 showed an increased intensity of the PC-MTs and suggests options for the development of new mass-tags. Although the on-tissue digestion covered a wider range of proteins, the MALDI-IHC allowed for easy and straightforward identification of proteins that were not detected in untargeted approaches. The combination of the multiplexed MALDI-IHC with image-guided proteomics showed great potential to further investigate diseases by providing complementary information from the same tissue section and without the need for customized instrumentation.

Mass spectrometry imaging (MSI) is a surface analysis technique that produces chemical images and is commonly used for biological and biomedical research. Multimodal imaging combines multiple imaging modes in order to get a more comprehensive view of a sample. Multimodal MSI images are often acquired using multiple MSI instruments, which leads to issues regarding image registration and increases the chance of sample damage or degradation during sample transfer. These problems can be solved by using a single instrument that can image in multiple modes. In order to improve the efficiency of multimodal imaging and investigate complementary modes of MSI, we have modified a prototype Bruker timsTOF fleX by adding secondary ion mass spectrometry (SIMS) and secondary electron (SE) imaging capabilities while preserving the ability to perform matrix-assisted laser desorption/ionization (MALDI). We show multimodal images collected on this instrument that required only trivial registration and were acquired without sample transfer between imaging trials. Furthermore, we characterize the performance of SIMS, SE, and MALDI imaging and compare the performance of the modified instrument to a commercial timsTOF fleX.

Organoids are increasingly used as model systems in precision medicine, but they are delicate, making it difficult to get accurate spatial chemical information. This protocol describes how to prepare organoid samples for mass spectrometry imaging.Organoid culture systems are self-renewing, three-dimensional (3D) models derived from pluripotent stem cells, adult derived stem cells or cancer cells that recapitulate key molecular and structural characteristics of their tissue of origin. They generally form into hollow structures with apical-basolateral polarization. Mass spectrometry imaging (MSI) is a powerful analytical method for detecting a wide variety of molecules in a single experiment while retaining their spatiotemporal distribution. Here we describe a protocol for preparing organoids for MSI that (1) preserves the 3D morphological structure of hollow organoids, (2) retains the spatiotemporal distribution of a vast array of molecules (3) and enables accurate molecular identification based on tandem mass spectrometry. The protocol specifically focuses on the collection and embedding of the organoids in gelatin, and gives recommendations for MSI-specific sample preparation, data acquisition and molecular identification by tandem mass spectrometry. This method is applicable to a wide range of organoids from different origins, and takes 1 d from organoid collection to MSI data acquisition.

The analysis of samples with large height variations remains a challenge for mass spectrometry imaging (MSI), despite many technological advantages. Ambient sampling and ionization MS techniques allow for the molecular analysis of sample surfaces with height variations, but most techniques lack MSI capabilities. We developed a 3D MS scanner for the automated sampling and imaging of a 3D surface with laser-assisted rapid evaporative ionization mass spectrometry (LA-REIMS). The sample is moved automatically with a constant distance between the laser probe and sample surface in the 3D MS Scanner. The topography of the surface was scanned with a laser point distance sensor to define the MS measurement points. MS acquisition was performed with LA-REIMS using a surgical CO2 laser coupled to a qTOF instrument. The topographical scan and MS acquisition can be completed within 1 h using the 3D MS scanner for 300 measurement points on uneven samples with a spatial resolution of 2 mm in the top view, corresponding to 22.04 cm(2). Comparison between the automated acquisition with the 3D MS scanner and manual acquisition by hand showed that the automation resulted in increased reproducibility between the measurement points. 3D visualizations of molecular distributions related to structural differences were shown for an apple, a marrowbone, and a human femoral head to demonstrate the imaging feasibility of the system. The developed 3D MS scanner allows for the automated sampling of surfaces with uneven topographies with LA-REIMS, which can be used for the 3D visualization of molecular distributions of these surfaces.

RATIONALE: Isomeric separation of prostanoids is often a challenge and requires chromatography and time-consuming sample preparation. Multiple prostanoid isomers have distinct in vivo functions crucial to understand the inflammation process, including prostaglandins E2 (PGE2 ) and D2 (PGD2 ). High-resolution Ion Mobility Spectrometry (IMS) based on linear ion transport in low-to-moderate electric fields and nonlinear ion transport in strong electric fields emerges as a broad approach for rapid separations prior to mass spectrometry (MS).METHODS: Derivatization with Girard's reagent T (GT) was used to overcome inefficient ionization of prostanoids in negative ionization mode due to poor deprotonation of the carboxylic acid group. Three high-resolution IMS techniques including linear cyclic IMS (cIMS), linear Trapped IMS (TIMS), and nonlinear high-Field Asymmetric Waveform IMS (FAIMS) were compared for the isomeric separation and endogenous detection of prostanoids present in intestinal tissue.RESULTS: Direct infusion of GT derivatized prostanoids proved to increase the ionization efficiency in positive ionization mode by a factor of >10, which enabled detection of these molecules in endogenous concentration levels. The high-resolution IMS comparison revealed its potential for rapid isomeric analysis of biologically relevant prostanoids. Strengths and weaknesses of both linear and nonlinear IMS were discussed. Endogenous prostanoid detection in intestinal tissue extracts demonstrated the applicability of our approach in biomedical research.CONCLUSIONS: The applied derivatization strategy offers high sensitivity and improved stereoisomeric separation for screening of complex biological systems. The high-resolution IMS comparison indicated that the best sensitivity and resolution are achieved by linear and nonlinear IMS, respectively.

The Timepix (TPX) is a position- and time-sensitive pixelated charge detector that can be coupled with time-of-flight mass spectrometry (TOF MS) in combination with microchannel plates (MCPs) for the spatially and temporally resolved detection of biomolecules. Earlier generation TPX detectors used in previous studies were limited by a moderate time resolution (at best 10 ns) and single-stop detection for each pixel that hampered the detection of ions with high mass-to-charge (m/z) values at high pixel occupancies. In this study, we have coupled an MCP-phosphor screen-TPX3CAM detection assembly that contains a silicon-coated TPX3 chip to a matrix-assisted laser desorption/ionization (MALDI)-axial TOF MS. A time resolution of 1.5625 ns, per-pixel multihit functionality, simultaneous measurement of TOF and time-over-threshold (TOT) values, and kHz readout rates of the TPX3 extended the m/z detection range of the TPX detector family. The detection of singly charged intact Immunoglobulin M ions of m/z value approaching 1 × 106 Da has been demonstrated. We also discuss the utilization of additional information on impact coordinates and TOT provided by the TPX3 compared to conventional MS detectors for the enhancement of the quality of the mass spectrum in terms of signal-to-noise (S/N) ratio. We show how the reduced dead time and event-based readout in TPX3 compared to the TPX improves the sensitivity of high m/z detection in both low and high mass measurements (m/z range: 757-970,000 Da). We further exploit the imaging capabilities of the TPX3 detector for the spatial and temporal separation of neutral fragments generated by metastable decay at different locations along the field-free flight region by simultaneous application of deflection and retarding fields.

Mass spectrometry imaging (MSI) maps the spatial distributions of chemicals on surfaces. MSI requires improvements in throughput and spatial resolution, and often one is compromised for the other. In microprobe-mode MSI, improvements in spatial resolution increase the imaging time quadratically, thus limiting the use of high spatial resolution MSI for large areas or sample cohorts and time-sensitive measurements. Here, we bypass this quadratic relationship by combining a Timepix3 detector with a continuously sampling secondary ion mass spectrometry mass microscope. By reconstructing the data into large-field mass images, this new method, fast mass microscopy, enables orders of magnitude higher throughput than conventional MSI albeit yet at lower mass resolution. We acquired submicron, gigapixel images of fingerprints and rat tissue at acquisition speeds of 600,000 and 15,500 pixels s-1, respectively. For the first image, a comparable microprobe-mode measurement would take more than 2 months, whereas our approach took 33.3 min.

Mass spectrometry imaging (MSI) of lipids within tissues has significant potential for both biomolecular discovery and histopathological applications. Conventional MSI technologies are, however, challenged by the prevalence of phospholipid regioisomers that differ only in the location(s) of carbon-carbon double bonds and/or the relative position of fatty acyl attachment to the glycerol backbone (i.e., sn position). The inability to resolve isomeric lipids within imaging experiments masks underlying complexity, resulting in a critical loss of metabolic information. Herein, ozone-induced dissociation (OzID) is implemented on a mobility-enabled quadrupole time-of-flight (Q-TOF) mass spectrometer capable of matrix-assisted laser desorption/ionization (MALDI). Exploiting the ion mobility region in the Q-TOF, high number densities of ozone were accessed, leading to similar to 1000-fold enhancement in the abundance of OzID product ions compared to earlier MALDI-OzID implementations. Translation of this uplift into imaging resulted in a 50-fold improvement in acquisition rate, facilitating large-area mapping with resolution of phospholipid isomers. Mapping isomer distributions across rat brain sections revealed distinct distributions of lipid isomer populations with region-specific associations of isomers differing in double bond and sn positions. Moreover, product ions arising from sequential ozone- and collision-induced dissociation enabled double bond assignments in unsaturated fatty acyl chains esterified at the noncanonical sn-1 position.

The potential chondroprotective effect of celecoxib, a nonsteroidal anti-inflammatory drug and selective cyclooxygenase-2 inhibitor used to reduce pain and inflammation in knee osteoarthritis patients, is disputed. This study aimed at investigating the chondroprotective effects of celecoxib on (1) human articular cartilage explants and (2) in anArticular cartilage explants from 16 osteoarthritis patients were cultured for 24 hours with celecoxib or vehicle. Secreted prostaglandins (prostaglandin ESecretion of prostaglandins, target of Nesh-SH3 (ABI3BP), and osteonectin proteins decreased, whereas tissue inhibitor of metalloproteinase 2 (TIMP-2) increased significantly after celecoxib treatment in the human (Our data demonstrated that celecoxib acts chondroprotective on cartilage

Osteoarthritis (OA) is a multifactorial pathology and comprises a wide range of distinct phenotypes. In this context, the characterization of the different molecular profiles associated with each phenotype can improve the classification of OA. In particular, OA can coexist with type 2 diabetes mellitus (T2DM). This study investigates lipidomic and proteomic differences between human OA/T2DM(-) and OA/T2DM(+) cartilage through a multimodal mass spectrometry approach. Human cartilage samples were obtained after total knee replacement from OA/T2DM(-) and OA/T2DM(+) patients. Label-free proteomics was employed to study differences in protein abundance and matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) for spatially resolved-lipid analysis. Label-free proteomic analysis showed differences between OA/T2DM(-) and OA/T2DM(+) phenotypes in several metabolic pathways such as lipid regulation. Interestingly, phospholipase A2 protein was found increased within the OA/T2DM(+) cohort. In addition, MALDI-MSI experiments revealed that phosphatidylcholine and sphingomyelin species were characteristic of the OA/T2DM(-) group, whereas lysolipids were more characteristic of the OA/T2DM(+) phenotype. The data also pointed out differences in phospholipid content between superficial and deep layers of the cartilage. Our study shows distinctively different lipid and protein profiles between OA/T2DM(-) and OA/T2DM(+) human cartilage, demonstrating the importance of subclassification of the OA disease for better personalized treatments.

Mass spectrometry imaging (MSI) provides insight into the molecular distribution of a broad range of compounds and, therefore, is frequently applied in the pharmaceutical industry. Pharmacokinetic and toxicological studies deploy MSI to localize potential drugs and their metabolites in biological tissues but currently require other analytical tools to quantify these pharmaceutical compounds in the same tissues. Quantitative mass spectrometry imaging (Q-MSI) is a field with challenges due to the high biological variability in samples combined with the limited sample cleanup and separation strategies available prior to MSI. In consequence, more selectivity in MSI instruments is required. This can be provided by multiple reaction monitoring (MRM) which uses specific precursor ion-product ion transitions. This targeted approach is in particular suitable for pharmaceutical compounds because their molecular identity is known prior to analysis. In this work, we compared different analytical platforms to assess the performance of MRM detection compared to other MS instruments/MS modes used in a Q-MSI workflow for two drug candidates (A and B). Limit of detection (LOD), linearity, and precision and accuracy of high and low quality control (QC) samples were compared between MS instruments/modes. MRM mode on a triple quadrupole mass spectrometer (QqQ) provided the best overall performance with the following results for compounds A and B: LOD 35.5 and 2.5 μg/g tissue, R2 0.97 and 0.98 linearity, relative standard deviation QC R2 0.86–0.98 and 0.86–0.98 linearity, relative standard deviation QC Graphical abstract

Highlights • Lipids change overtime in normal fascial healing in the early post-surgery period. • Specific lipid species are correlated with the changes of inflammation cells and fibroblasts. • Lipid species in the present study are considered as predictive markers for the formation of incisional hernia., Background Failure of fascial healing in the abdominal wall can result in incisional hernia, which is one of the most common complications after laparotomy. Understanding the molecular healing process of abdominal fascia may provide lipid markers of incisional hernia or therapeutic targets that allow prevention or treatment of incisional hernias. Purpose This study aims to investigate temporal and in situ changes of lipids during the normal healing process of abdominal fascia in the first postoperative week. Methods Open hemicolectomy was performed in a total of 35 Wistar rats. The midline fascia was closed identically for all rats using a single continuous suturing technique. These animals were sacrificed with equal numbers (n = 5) at each of 7-time points (6, 12, 24, 48, 72, 120, and 168 h. The local and temporal changes of lipids were examined with mass spectrometry imaging and correlated to histologically scored changes during healing using hematoxylin and eosin staining. Results Two phosphatidylcholine lipid species (PC O-38:5 and PC 38:4) and one phosphatidylethanolamine lipid (PE O-16:1_20:4) were found to significantly correlate with temporal changes of inflammation. A phosphatidylcholine (PC 32:0) and a monosialodihexosylganglioside (GM3 34:1;2) were found to correlate with fibroblast cell growth. Conclusion Glycerophospholipids and gangliosides are strongly involved in the normal healing process of abdominal fascia and their locally fluctuating concentrations are considered as potential lipid markers and therapeutic targets of fascial healing.

Liver resident CD8 T cells have an essential role in immunopathology in a mouse model of nonalcoholic steatohepatitis, by becoming auto-aggressive following sequential transcriptional and metabolic activation steps . Nonalcoholic steatohepatitis (NASH) is a manifestation of systemic metabolic disease related to obesity, and causes liver disease and cancer(1,2). The accumulation of metabolites leads to cell stress and inflammation in the liver(3), but mechanistic understandings of liver damage in NASH are incomplete. Here, using a preclinical mouse model that displays key features of human NASH (hereafter, NASH mice), we found an indispensable role for T cells in liver immunopathology. We detected the hepatic accumulation of CD8 T cells with phenotypes that combined tissue residency (CXCR6) with effector (granzyme) and exhaustion (PD1) characteristics. Liver CXCR6(+) CD8 T cells were characterized by low activity of the FOXO1 transcription factor, and were abundant in NASH mice and in patients with NASH. Mechanistically, IL-15 induced FOXO1 downregulation and CXCR6 upregulation, which together rendered liver-resident CXCR6(+) CD8 T cells susceptible to metabolic stimuli (including acetate and extracellular ATP) and collectively triggered auto-aggression. CXCR6(+) CD8 T cells from the livers of NASH mice or of patients with NASH had similar transcriptional signatures, and showed auto-aggressive killing of cells in an MHC-class-I-independent fashion after signalling through P2X7 purinergic receptors. This killing by auto-aggressive CD8 T cells fundamentally differed from that by antigen-specific cells, which mechanistically distinguishes auto-aggressive and protective T cell immunity.

Real-time tissue classifiers based on molecular patterns are emerging tools for fast tumor diagnosis. Here, we used rapid evaporative ionization mass spectrometry (REIMS) and multivariate statistical analysis (principal component analysis–linear discriminant analysis) to classify tissues with subsequent comparison to gold standard histopathology. We explored whether REIMS lipid patterns can identify human liver tumors and improve the rapid characterization of their underlying metabolic features. REIMS-based classification of liver parenchyma (LP), hepatocellular carcinoma (HCC), and metastatic adenocarcinoma (MAC) reached an accuracy of 98.3%. Lipid patterns of LP were more similar to those of HCC than to those of MAC and allowed clear distinction between primary and metastatic liver tumors. HCC lipid patterns were more heterogeneous than those of MAC, which is consistent with the variation seen in the histopathological phenotype. A common ceramide pattern discriminated necrotic from viable tumor in MAC with 92.9% accuracy and in other human tumors. Targeted analysis of ceramide and related sphingolipid mass features in necrotic tissues may provide a new classification of tumor cell death based on metabolic shifts. Real-time lipid patterns may have a role in future clinical decision-making in cancer precision medicine. Real-time lipid patterns can identify liver tumors and their inter-tumor and intra-tumor heterogeneity. Ceramides and related sphingolipids are a common feature of necrotic tumors and can characterize the tumor phenotype based on metabolic shifts relevant for cell death pathways. Lipid patterns have the potential to improve clinical decision-making in the near future.

Mass spectrometry imaging (MSI) can analyze the spatial distribution of hundreds of different molecules directly from tissue sections usually placed on conductive glass slides to provide conductivity on the sample surface. Additional experiments are often required for molecular identification using consecutive sections on membrane slides compatible with laser capture microdissection (LMD). In this work, we demonstrate for the first time the use of a single conductive slide for both matrix-assisted laser desorption ionization (MALDI)-MSI and direct proteomics. In this workflow, regions of interest can be directly ablated with LMD while preserving protein integrity. These results offer an alternative for MSI-based multimodal spatial-omics.

Mass spectrometry imaging (MSI) has become an indispensible tool for spatially resolved molecular investigation of tissues. One of the key application areas is biomedical research, where matrix-assisted laser desorption/ionization (MALDI) MSI is predominantly used due to its high-throughput capability, flexibility in the molecular class to investigate, and ability to achieve single cell spatial resolution. While many of the initial technical challenges have now been resolved, so-called batch effects, a phenomenon already known from other omics fields, appear to significantly impede reliable comparison of data from particular midsized studies typically performed in translational clinical research. This critical insight will discuss at what levels (pixel, section, slide, time, and location) batch effects can manifest themselves in MALDI-MSI data and what consequences this might have for biomarker discovery or multivariate classification. Finally, measures are presented that could be taken to recognize and/or minimize these potentially detrimental effects, and an outlook is provided on what is still needed to ultimately overcome these effects.

Cell death & disease 12(1), 95 (2021). doi:10.1038/s41419-020-03379-9, Published by Nature Publishing Group, London [u.a.]

Radical resection for patients with oral cavity cancer remains challenging. Rapid evaporative ionization mass spectrometry (REIMS) of electrosurgical vapors has been reported for real-time classification of normal and tumor tissues for numerous surgical applications. However, the infiltrative pattern of invasion of oral squamous cell carcinomas (OSCC) challenges the ability of REIMS to detect low amounts of tumor cells. We evaluate REIMS sensitivity to determine the minimal amount of detected tumors cells during oral cavity cancer surgery. A total of 11 OSCC patients were included in this study. The tissue classification based on 185 REIMS ex vivo metabolic profiles from five patients was compared to histopathology classification using multivariate analysis and leave-one-patient-out cross-validation. Vapors were analyzed in vivo by REIMS during four glossectomies. Complementary desorption electrospray ionization-mass spectrometry imaging (DESI-MSI) was employed to map tissue heterogeneity on six oral cavity sections to support REIMS findings. REIMS sensitivity was assessed with a new cell-based assay consisting of mixtures of cell lines (tumor, myoblasts, keratinocytes). Our results depict REIMS classified tumor and soft tissues with 96.8% accuracy. In vivo REIMS generated intense mass spectrometric signals. REIMS detected 10% of tumor cells mixed with 90% myoblasts with 83% sensitivity and 82% specificity. DESI-MSI underlined distinct metabolic profiles of nerve features and a metabolic shift phosphatidylethanolamine PE(O-16:1/18:2))/cholesterol sulfate common to both mucosal maturation and OSCC differentiation. In conclusion, the assessment of tissue heterogeneity with DESI-MSI and REIMS sensitivity with cell mixtures characterized sensitive metabolic profiles toward in vivo tissue recognition during oral cavity cancer surgeries.

Human cells produce thousands of lipids that change during cell differentiation and can vary across individual cells of the same type. However, we are only starting to characterize the function of these cell-to-cell differences in lipid composition. Here, we measured the lipidomes and transcriptomes of individual human dermal fibroblasts by coupling high-resolution mass spectrometry imaging with single-cell transcriptomics. We found that the cell-to-cell variations of specific lipid metabolic pathways contribute to the establishment of cell states involved in the organization of skin architecture. Sphingolipid composition is shown to define fibroblast subpopulations, with sphingolipid metabolic rewiring driving cell-state transitions. Therefore, cell-to-cell lipid heterogeneity affects the determination of cell states, adding a new regulatory component to the self-organization of multicellular systems.

The molecular pathology of breast cancer is challenging due to the complex heterogeneity of cellular subtypes. The ability to directly identify and visualize cell subtype distribution at the single-cell level within a tissue section enables precise and rapid diagnosis and prognosis. Here, we applied mass spectrometry imaging (MSI) to acquire and visualize the molecular profiles at the single-cell and subcellular levels of 14 different breast cancer cell lines. We built a molecular library of genetically well-characterized cell lines. Multistep processing, including deep learning, resulted in a breast cancer subtype, the cancer's hormone status, and a genotypic recognition model based on metabolic phenotypes with cross-validation rates of up to 97%. Moreover, we applied our single-cell-based recognition models to complex tissue samples, identifying cell subtypes in tissue context within seconds during measurement. These data demonstrate "on the spot" digital pathology at the single-cell level using MSI, and they provide a framework for fast and accurate high spatial resolution diagnostics and prognostics.

Time-of-flight (TOF) systems are one of the most widely used mass analyzers in native mass spectrometry (nMS) for the analysis of non-covalent multiply charged bio-macromolecular assemblies (MMAs). Typically, microchannel plates (MCPs) are employed for high mass native ion detection in TOF MS. MCPs are well known for their reduced detection efficiency when impinged by large slow moving ions. Here, a position- and time-sensitive Timepix (TPX) detector has been added to the back of a dual MCP stack to study the key factors that affect MCP performance for MMA ions generated by nMS. The footprint size of the secondary electron cloud generated by the MCP on the TPX for each individual ion event is analyzed as a measure of MCP performance at each mass-to-charge (m/z) value and resulted in a Poisson distribution. This allowed us to investigate the dependency of ion mass, ion charge, ion velocity, acceleration voltage, and MCP bias voltage on MCP response in the high mass low velocity regime. The study of measurement ranges; ion mass = 195 to 802,000 Da, ion velocity = 8.4 to 67.4 km/s, and ion charge = 1+ to 72+, extended the previously examined mass range and characterized MCP performance for multiply charged species. We derived a MCP performance equation based on two independent ion properties, ion mass and charge, from these results, which enables rapid MCP tuning for single MMA ion detection.

Time-of-flight secondary ion mass spectrometry (TOF-SIMS) imaging provides molecular speciation at the micrometer scale, while the penetration depth of the primary ion beam is limited to the top-layers of a sample. These combined properties make TOF-SIMS potentially an ideal technique to study oil-gas interfaces. TOF-SIMS spectra of three crude oils were evaluated, and only low-mass fragment ions could be assigned to molecular structures unambiguously. Films of crude oils were incubated under air, oil vapor, or water vapor for various times. TOF-SIMS images of a polar crude oil revealed feeble structures of similar to 10 mu m large round patches that grew to similar to 30 mu m large crystals when incubated under air and oil vapor, respectively. Principal component analysis of the images showed that the continuous phase had typical aromatic signatures, while the patches and crystals had alkane-like characteristics. No features showed up when the oil film was incubated under water vapor, which indicated that saturated water vapor prevented the accumulation of nonpolar alkane-like compounds at the oil-gas interface. These examples showed that crude oils do not behave as dead fluids but that their constituents accumulate at the oil-gas interfaces in a dynamic way.

Mass spectrometry imaging (MSI) enables the visualization of molecular distributions on complex surfaces. It has been extensively used in the field of biomedical research to investigate healthy and diseased tissues. Most of the MSI studies are conducted in a 2D fashion where only a single slice of the full sample volume is investigated. However, biological processes occur within a tissue volume and would ideally be investigated as a whole to gain a more comprehensive understanding of the spatial and molecular complexity of biological samples such as tissues and cells. Mass spectrometry imaging has therefore been expanded to the 3D realm whereby molecular distributions within a 3D sample can be visualized. The benefit of investigating volumetric data has led to a quick rise in the application of single-sample 3D-MSI investigations. Several experimental and data analysis aspects need to be considered to perform successful 3D-MSI studies. In this review, we discuss these aspects as well as ongoing developments that enable 3D-MSI to be routinely applied to multi-sample studies.

The ability to spatially resolve the chemical distribution of compounds on a surface is important in many applications ranging from biological to material science. To this extent, we have recently introduced a hybrid atomic force microscopy (AFM)-mass spectrometry (MS) system for direct thermal desorption and pyrolysis of material with nanoscale chemical resolution. However, spatially resolved direct surface heating using local thermal desorption becomes challenging on material surfaces with low melting points, because the material will undergo a melting phase transition due to heat dissipation prior to onset of thermal desorption. Therefore, we developed an approach using mechanical sampling and collection of surface materials on an AFM cantilever probe tip for real-time analysis directly from the AFM tip. This approach allows for material to be concentrated directly onto the probe for subsequent MS analysis. We evaluate the performance metrics of the technique and demonstrate localized MS sampling from a candelilla wax matrix containing UV stabilizers avobenzone and oxinoxate from areas down to 250 nm × 250 nm. Overall, this approach removes heat dissipation into the bulk material allowing for a faster desorption and concentration of the gas phase analyte from a single heating pulse enabling higher signal levels from a given amount of material in a single sampling spot. Graphical abstract

In the past decades, matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) has been applied to a broad range of biological samples, e.g., forensics and preclinical samples. The use of MALDI-MSI for the analysis of bone tissue has been limited due to the insulating properties of the material but more importantly the absence of a proper sample preparation protocol for undecalcified bone tissue. Undecalcified sections are preferred to retain sample integrity as much as possible or to study the tissue-bone bio interface in particular. Here, we optimized the sample preparation protocol of undecalcified bone samples, aimed at both targeted and untargeted applications for forensic and preclinical applications, respectively. Different concentrations of gelatin and carboxymethyl cellulose (CMC) were tested as embedding materials. The composition of 20% gelatin and 7.5% CMC showed to support the tissue best while sectioning. Bone tissue has to be sectioned with a tungsten carbide knife in a longitudinal fashion, while the sections need to be supported with double-sided tapes to maintain the morphology of the tissue. The developed sectioning method was shown to be applicable on rat and mouse as well as human bone samples. Targeted (methadone and EDDP) as well as untargeted (unknown lipids) detection was demonstrated. DHB proved to be the most suitable matrix for the detection of methadone and EDDP in positive ion mode. The limit of detection (LOD) is estimated to approximately 50 pg/spot on bone tissue. The protocol was successfully applied to detect the presence of methadone and EDDP in a dosed rat femur and a dosed human clavicle. The best matrices for the untargeted detection of unknown lipids in mouse hind legs in positive ion mode were CHCA and DHB based on the number of tissue-specific peaks and signal-to-noise ratios. The developed and optimized sample preparation method, applicable on animal and human bones, opens the door for future forensic and (pre)clinical investigations. Electronic supplementary material The online version of this article (10.1007/s00216-020-02920-1) contains supplementary material, which is available to authorized users.

The large‐scale and label‐free molecular characterization of single cells in their natural tissue habitat remains a major challenge in molecular biology. We present a method that integrates morphometric image analysis to delineate and classify individual cells with their single‐cell‐specific molecular profiles. This approach provides a new means to study spatial biological processes such as cancer field effects and the relationship between morphometric and molecular features., Understanding how cells regulate their bioenergetic demands, adjust to the microenvironment, or respond to stimuli is the aim of molecular biology. Yet, methods able to describe the molecular content, histological identity, and spatial context of a single cell do not exist. The presented method integrates morphometric image analysis to delineate and classify individual cells with their cell‐specific molecular profiles obtained by MALDI‐MSI.

Common traumas to the skeletal system are bone fractures and injury-related articular cartilage damage. The healing process can be impaired resulting in non-unions in 5–10% of the bone fractures and in post-traumatic osteoarthritis (PTOA) in up to 75% of the cases of cartilage damage. Despite the amount of research performed in the areas of fracture healing and cartilage repair as well as non-unions and PTOA, still, the outcome of a bone fracture or articular cartilage damage cannot be predicted. Here, we discuss known risk factors and key molecules involved in the repair process, together with the main challenges associated with the prediction of outcome of these injuries. Furthermore, we review and discuss the opportunities for mass spectrometry (MS) – an analytical tool capable of detecting a wide variety of molecules in tissues – to contribute to extending molecular understanding of impaired healing and the discovery of predictive biomarkers. Therefore, the current knowledge and challenges concerning MS imaging of bone and cartilage tissue as well as in vivo MS are discussed. Finally, we explore the possibilities of in situ, real-time MS for the prediction of outcome during surgery of bone fractures and injury-related articular cartilage damage.