Desorption Ionization Mass Spectrometry Imaging Research Articles

Molecularly Imprinted Heterostructure-Assisted Laser Desorption Ionization Mass Spectrometry Analysis and Imaging of Quinolones.

Quinolone residues resulting from body metabolism and waste discharge pose a significant threat to the ecological environment and to human health. Therefore, it is essential to monitor quinolone residues in the environment. Herein, an efficient and sensitive matrix-assisted laser desorption/ionization mass spectrometry (MALDI/MS) method was devised by using a novel molecularly imprinted heterojunction (MIP-TNs@GCNs) as the matrix. Molecularly imprinted titanium dioxide nanosheets (MIP-TNs) and graphene-like carbon nitrides (GCNs) were associated at the heterojunction interface, allowing for the specific, rapid, and high-throughput ionization of quinolones. The mechanism of MIP-TNs@GCNs was clarified using their adsorption properties and laser desorption/ionization capability. The prepared oxygen-vacancy-rich MIP-TNs@GCNs heterojunction exhibited higher light absorption and ionization efficiencies than TNs and GCNs. The good linearity (in the quinolone concentration range of 0.5-50 pg/μL, R2 > 0.99), low limit of detection (0.1 pg/μL), good reproducibility (n = 8, relative standard deviation [RSD] < 15%), and high salt and protein resistance for quinolones in groundwater samples were achieved using the established MIP-TNs@GCNs-MALDI/MS method. Moreover, the spatial distributions of endogenous compounds (e.g., amino acids, organic acids, and flavonoids) and xenobiotic quinolones from Rhizoma Phragmitis and Rhizoma Nelumbinis were visualized using the MIP-TNs@GCNs film as the MALDI/MS imaging matrix. Because of its superior advantages, the MIP-TNs@GCNs-MALDI/MS method is promising for the analysis and imaging of quinolones and small molecules.

Abstract 7088: MALDI-IHC high-plex protein biomarker imaging for fast, non-iterative identification of lung carcinoma subtypes

Abstract Lung cancer is the second most common cancer worldwide, with over 2.2 million new cases in 2020 and is the leading cause of cancer-related deaths worldwide. Most lung cancer (80-85%) is non-small cell (NSCLC), comprising mostly adenocarcinoma and squamous cell carcinoma, while roughly 10-15% of lung cancer is small cell lung cancer (SCLC), also termed neuroendocrine lung cancer. Subtype identification is critical for determining treatment, and with limited samples, it is critical to get the most data possible from each tissue section. NSCLC subtypes can be treated with chemotherapy or targeted drugs, whereas SCLC tends to respond best to a combination of chemotherapy and radiation. While there have been many improvements in the detection and treatment of lung carcinoma, the immuno-histochemical (IHC) confirmation of subtype remains a prolonged and often iterative process. To overcome this limitation, we have developed a new IHC approach which uses antibodies labeled with novel photocleavable mass-tags combined with matrix assisted laser desorption ionization (MALDI) mass spectrometry imaging. The approach, termed MALDI-IHC, provides fast (1 hr/cm2 imaging time) and highly multiplexed IHC (100+-plex) without the need for iterative cycling procedures. Here, we present a 20+-plex panel for the determination of subtype in lung cancer. An antibody panel comprised of established clinical biomarkers was developed to differentiate between the lung carcinoma subtypes and provide potentially prognostic information. This included markers for adenocarcinoma (TTF-1, Napsin A), squamous cell carcinoma (p40, CK5), and small cell lung cancer (CD56, Chromogranin A and Synaptophysin), as well as general carcinoma markers for t cells, b cells, macrophages, and fibroblasts These markers were first validated individually by immunofluorescence and then compared to MALDI-IHC on annotated tissues. Here we present an overview of the antibody validation for the 20+-plex lung carcinoma panel. Biomarker presence and peak signal intensity for the various subtypes was then determined using pathologist classified tissues for normal lung, adenocarcinoma, squamous cell carcinoma and small cell lung cancer. We report application of the MALDI-IHC approach to the simultaneous determination of lung carcinoma subtypes on a 99-core human lung tissue microarray (TMA) comprised of normal, normal adjacent, cancer adjacent, and cancerous tissues. Moreover, because MALDI-IHC is a non-destructive process, it can be followed by conventional H&amp;E staining on the same tissue section for accurate co-registration of traditional pathology annotations with the highly multiplexed MALDI-IHC results. In the future, even larger, 100+-plex antibody panels can be used for precision medicine on a wide range of cancers, in order to determine the molecular subtypes and guide treatment paths. Citation Format: Catherine A. Kita, Kristina Schwamborn, Gargey Yagnik, Kenneth J. Rothschild, Mark J. Lim. MALDI-IHC high-plex protein biomarker imaging for fast, non-iterative identification of lung carcinoma subtypes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7088.

Lipid-related ion suppression on the herbicide atrazine in earthworm samples in ToF-SIMS and matrix-assisted laser desorption ionization mass spectrometry imaging and the role of gas-phase basicity.

In mass spectrometry imaging (MSI), ion suppression can lead to a misinterpretation of results. Particularly phospholipids, most of which exhibit high gas-phase basicity (GB), are known to suppress the detection of metabolites and drugs. This study was initiated by the observation that the signal of an herbicide, i.e., atrazine, was suppressed in MSI investigations of earthworm tissue sections. Herbicide accumulation in earthworms was investigated by time-of-flight secondary ion mass spectrometry and matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). Additionally, earthworm tissue sections without accumulation of atrazine but with a homogeneous spray deposition of the herbicide were analyzed to highlight region-specific ion suppression. Furthermore, the relationship of signal intensity and GB in binary mixtures of lipids, amino acids, and atrazine was investigated in both MSI techniques. The GB of atrazine was determined experimentally through a linear plot of the obtained intensity ratios of the binary amino acid mixtures, as well as theoretically. The GBs values for atrazine of 896 and 906 kJ/mol in ToF-SIMS and 933 and 987 kJ/mol in MALDI-MSI were determined experimentally and that of 913 kJ/mol by quantum mechanical calculations. Compared with the GB of a major lipid component, phosphatidylcholine (GBPC = 1044.7 kJ/mol), atrazine's experimentally and computationally determined GBs in this work are significantly lower, making it prone to ion suppression in biological samples containing polar lipids.

A Machine Learning-Driven Comparison of Ion Images Obtained by MALDI and MALDI-2 Mass Spectrometry Imaging.

Matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) enables label-free imaging of biomolecules in biological tissues. However, many species remain undetected due to their poor ionization efficiencies. MALDI-2 (laser-induced post-ionization) is the most widely used post-ionization method for improving analyte ionization efficiencies. Mass spectra acquired using MALDI-2 constitute a combination of ions generated by both MALDI and MALDI-2 processes. Until now, no studies have focused on a detailed comparison between the ion images (as opposed to the generated m/z values) produced by MALDI and MALDI-2 for mass spectrometry imaging (MSI) experiments. Herein, we investigated the ion images produced by both MALDI and MALDI-2 on the same tissue section using correlation analysis (to explore similarities in ion images for ions common to both MALDI and MALDI-2) and a deep learning approach. For the latter, we used an analytical workflow based on the Xception convolutional neural network, which was originally trained for human-like natural image classification but which we adapted to elucidate similarities and differences in ion images obtained using the two MSI techniques. Correlation analysis demonstrated that common ions yielded similar spatial distributions with low-correlation species explained by either poor signal intensity in MALDI or the generation of additional unresolved signals using MALDI-2. Using the Xception-based method, we identified many regions in the t-SNE space of spatially similar ion images containing MALDI and MALDI-2-related signals. More notably, the method revealed distinct regions containing only MALDI-2 ion images with unique spatial distributions that were not observed using MALDI. These data explicitly demonstrate the ability of MALDI-2 to reveal molecular features and patterns as well as histological regions of interest that are not visible when using conventional MALDI.

Assessment of MALDI matrices for the detection and visualization of phosphatidylinositols and phosphoinositides in mouse kidneys through matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI).

Phosphatidylinositols and their phosphorylated derivatives, known as phosphoinositides, are crucial in cellular processes, with their abnormalities linked to various diseases. Thus, identifying and measuring phosphoinositide levels in tissues are crucial for understanding their contributions to cellular processes and disease development. One powerful technique for mapping the spatial distribution of molecules in biological samples is matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). This technique allows for the simultaneous detection and analysis of multiple lipid classes in situ, making it invaluable for unbiased lipidomic studies. However, detecting phosphoinositides with MALDI-MSI is challenging due to their relatively low abundance in tissues and complex matrix effects. Addressing this, our study focused on optimizing matrix selection and thickness for better detection of phosphatidylinositols and their phosphorylated forms in mouse kidney tissues. Various matrices were assessed, including 9AA, DAN, CMBT, and DHA, adjusting their coating to improve ionization efficiency. Our results demonstrate that DAN, DHA, and CMBT matrices produced high-intensity chemical images of phosphatidylinositol distributions within kidney sections. These matrices, particularly DAN, DHA, and CMBT, allowed the identification of even low-abundance phosphoinositides, through tentative identifications. Notably, DAN and DHA served as optimal candidates due to their prominent detection and ability to map a majority of phosphatidylinositol species, while CMBT showed potential detection capability for phosphatidylinositol triphosphate compounds. These findings not only provide valuable insights for future research on the involvement of phosphoinositides in kidney pathophysiology, but also propose the use of the identified optimal matrices, particularly DAN and DHA, as the preferred choices for enhanced detection and mapping of these lipid species in future studies.

High-Throughput Miniaturized Synthesis of PROTAC-Like Molecules.

The development of miniaturized high-throughput in situ screening platforms capable of handling the entire process of drug synthesis to final screening is essential for advancing drug discovery in the future. In this study, an approach based on combinatorial solid-phase synthesis, enabling the efficient synthesis of libraries of proteolysis targeting chimeras (PROTACs) in an array format is presented. This on-chip platform allows direct biological screening without the need for transfer steps. UV-induced release of target molecules into individual droplets facilitates further on-chip experimentation. Utilizing a mitogen-activated protein kinase kinases (MEK1/2) degrader as a template, a series of 132 novel PROTAC-like molecules is synthesized using solid-phase Ugi reaction. These compounds are further characterized using various methods, including matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS) imaging, while consuming only a few milligrams of starting materials in total. Furthermore, the feasibility of culturing cancer cells on the modified spots and quantifying the effect of MEK suppression is demonstrated. The miniaturized synthesis platform lays a foundation for high-throughput in situ biological screening of potent PROTACs for potential anticancer activity and offers the potential for accelerating the drug discovery process by integrating miniaturized synthesis and biological steps on the same array.

Spatiotemporal Visualization of Paraquat Distribution, Toxicokinetics, and Its Detoxification in Zebrafish Using Matrix-Assisted Laser Desorption Ionization Mass Spectrometry Imaging.

Paraquat is a highly toxic quaternary ammonium herbicide. It can damage the functions of multiple organs and cause irreversible pulmonary fibrosis in the human body. However, the toxicological mechanism of paraquat is not yet fully understood, and due to the lack of specific antidotes, the clinical treatment of paraquat intoxication is still a great medical challenge. In-depth research on its toxicity mechanism, toxicokinetics, and effective antidotes is urgently demanded. A new molecular imaging technique, matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI), can simultaneously achieve quantitative and spatial analysis and offer an alternative, distinct, and useful technique for paraquat intoxication and consequent detoxication. Here, we visualized the spatial-temporal distribution and conducted toxicokinetic research on paraquat in zebrafish by using stable isotope-labeled internal-standard-aided MALDI-MSI for the first time. The results indicated that paraquat had a fast absorption rate and was widely distributed in different organs, such as the brain, gills, kidneys, and liver in zebrafish. Its half-life was long, and the elimination rate was slow. Paraquat reached its peak at 30 min and was mainly distributed in kidneys and intestines and then showed a tendency of declining first but mildly rising later at 6 h, accompanied by a wide distribution in kidneys and intestines again. It suggested that entero-systemic recirculation might lead to the observed secondary peaks, and perhaps it extended the residence time of paraquat in the body. In addition, we validated the potential detoxification effect of sodium salicylate as a potential antidote for paraquat from both the dimensions of distribution and quantification. In conclusion, MALDI-MSI conveniently provided the distinct and quantitative spatial-temporal distribution information on paraquat in the whole body of zebrafish; it will promote the understanding of its toxicokinetic characteristics and provide more valuable information for clinical treatment.

Spatial Omics Reveals that Cancer-Associated Glycan Changes Occur Early in Liver Disease Development in a Western Diet Mouse Model of MASLD.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a progressive disease and comprises different stages of liver damage; it is significantly associated with obese and overweight patients. Untreated MASLD can progress to life-threatening end-stage conditions, such as cirrhosis and liver cancer. N-Linked glycosylation is one of the most common post-translational modifications in the cell surface and secreted proteins. N-Linked glycan alterations have been established to be signatures of liver diseases. However, the N-linked glycan changes during the progression of MASLD to liver cancer are still unknown. Here, we induced different stages of MASLD in mice and liver-cancer-related phenotypes and elucidated the N-glycome profile during the progression of MASLD by quantitative and qualitative profiling in situ using matrix-assisted laser desorption ionization (MALDI) imaging mass spectrometry (IMS). Importantly, we identified specific N-glycan structures including fucosylated and highly branched N-linked glycans at very early stages of liver injury (steatosis), which in humans are associated with cancer development, establishing the importance of these modifications with disease progression. Finally, we report that N-linked glycan alterations can be observed in our models by MALDI-IMS before liver injury is identified by histological analysis. Overall, we propose these findings as promising biomarkers for the early diagnosis of liver injury in MASLD.

Ultrahigh-Mass Resolution Mass Spectrometry Imaging with an Orbitrap Externally Coupled to a High-Performance Data Acquisition System.

Matrix-assisted laser desorption ionization (MALDI) mass spectrometry imaging (MSI) is a powerful analytical tool that enables molecular sample analysis while simultaneously providing the spatial context of hundreds or even thousands of analytes. However, because of the lack of a separation step prior to ionization and the immense diversity of biomolecules, such as lipids, including numerous isobaric species, the coupling of ultrahigh mass resolution (UHR) with MSI presents one way in which this complexity can be resolved at the spectrum level. Until now, UHR MSI platforms have been restricted to Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometers. Here, we demonstrate the capabilities of an Orbitrap-based UHR MSI platform to reach over 1,000,000 mass resolution in a lipid mass range (600-950 Da). Externally coupling the Orbitrap Q Exactive HF with the high-performance data acquisition system FTMS Booster X2 provided access to the unreduced data in the form of full-profile absorption-mode FT mass spectra. In addition, it allowed us to increase the time-domain transient length from 0.5 to 10 s, providing improvement in the mass resolution, signal-to-noise ratio, and mass accuracy. The resulting UHR performance generates high-quality MALDI MSI images and simplifies the identification of lipids. Collectively, these improvements resulted in a 1.5-fold increase in annotations, demonstrating the advantages of this UHR imaging platform for spatial lipidomics using MALDI-MSI.

Advances in cellular and tissue-based imaging techniques for sarcoid granulomas

Sarcoidosis embodies a complex inflammatory disorder spanning multiple systems, with its origin remaining elusive. It manifests as the infiltration of inflammatory cells that coalesce into distinctive noncaseous granulomas within afflicted organs. Unraveling this disease necessitates the utilization of cellular or tissue-based imaging methods to both visualize and characterize the biochemistry of these sarcoid granulomas. Although hematoxylin and eosin stain, standard in routine use alongside cytological stains have found utility in diagnosis within clinical contexts, special stains such as Masson’s trichrome, reticulin, methenamine silver, and Ziehl–Neelsen provide additional varied perspectives of sarcoid granuloma imaging. Immunohistochemistry aids in pinpointing specific proteins and gene expressions further characterizing these granulomas. Finally, recent advances in spatial transcriptomics promise to divulge profound insights into their spatial orientation and three-dimensional (3-D) molecular mapping. This review focuses on a range of preexisting imaging methods employed for visualizing sarcoid granulomas at the cellular level while also exploring the potential of the latest cutting-edge approaches like spatial transcriptomics and matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI), with the overarching goal of shedding light on the trajectory of sarcoidosis research.

Loss of carnitine palmitoyltransferase 1a reduces docosahexaenoic acid-containing phospholipids and drives sexually dimorphic liver disease in mice

Background and aimsGenome and epigenome wide association studies identified variants in carnitine palmitoyltransferase 1a (CPT1a) that associate with lipid traits. The goal of this study was to determine the role of liver-specific CPT1a on hepatic lipid metabolism. Approach and resultsMale and female liver-specific knockout (LKO) and littermate controls were placed on a low-fat or high-fat diet (60% kcal fat) for 15 weeks. Mice were necropsied after a 16 h fast, and tissues were collected for lipidomics, matrix-assisted laser desorption ionization mass spectrometry imaging, kinome analysis, RNA-sequencing, and protein expression by immunoblotting. Female LKO mice had increased serum alanine aminotransferase levels which were associated with greater deposition of hepatic lipids, while male mice were not affected by CPT1a deletion relative to male control mice. Mice with CPT1a deletion had reductions in DHA-containing phospholipids at the expense of monounsaturated fatty acids (MUFA)-containing phospholipids in whole liver and at the level of the lipid droplet (LD). Male and female LKO mice increased RNA levels of genes involved in LD lipolysis (Plin2, Cidec, G0S2) and in polyunsaturated fatty acid metabolism (Elovl5, Fads1, Elovl2), while only female LKO mice increased genes involved in inflammation (Ly6d, Mmp12, Cxcl2). Kinase profiling showed decreased protein kinase A activity, which coincided with increased PLIN2, PLIN5, and G0S2 protein levels and decreased triglyceride hydrolysis in LKO mice. ConclusionsLiver-specific deletion of CPT1a promotes sexually dimorphic steatotic liver disease (SLD) in mice, and here we have identified new mechanisms by which females are protected from HFD-induced liver injury.

Use of X-ray Microscopy for Confirmation of Crystallinity Detection in Amorphous Formulations by Electrospray Laser Desorption Ionization Mass Spectrometry Imaging

The use of mass spectrometry imaging for crystallinity detection offers improved matrix selectivity and sensitivity over the techniques, such as X-ray microscopy and Raman spectrometry, that are traditionally used with this work. Crystallinity is observed in electrospray laser desorption ionization mass spectrometry imaging (ELDI-MSI) as a high-intensity agglomeration of the analyte in a spatially resolved image. As this is an indirect method of crystallinity detection, confirmation of this method’s ability to detect crystallization in amorphous formulations is needed by directly correlating observations of tablet crystallinity by ELDI-MSI to those of an established detection technique. Micro-computed tomography (micro-CT) has the necessary sensitivity for this investigation and is ideal for use in evaluating the correlation with crystallinity detection by ELDI-MSI. In this work, micro-CT followed by ELDI-MSI, in the same location on tablets of amorphous formulations of miconazole spiked with trace levels of crystalline miconazole, were analyzed. Crystals detected by ELDI-MSI as an agglomeration spatially matched with the detected crystals but were chemically unidentified by micro-CT. The results of this correlation study and a conclusion about the effectiveness of ELDI-MSI as a complimentary technique to indirectly detect crystallinity in enabling formations of an amorphous API are presented.

RMSIfragment: improving MALDI-MSI lipidomics through automated in-source fragment annotation

Matrix-Assisted Laser Desorption Ionization Mass Spectrometry Imaging (MALDI-MSI) spatially resolves the chemical composition of tissues. Lipids are of particular interest, as they influence important biological processes in health and disease. However, the identification of lipids in MALDI-MSI remains a challenge due to the lack of chromatographic separation or untargeted tandem mass spectrometry. Recent studies have proposed the use of MALDI in-source fragmentation to infer structural information and aid identification. Here we present rMSIfragment, an open-source R package that exploits known adducts and fragmentation pathways to confidently annotate lipids in MALDI-MSI. The annotations are ranked using a novel score that demonstrates an area under the curve of 0.7 in ROC analyses using HPLC–MS and Target-Decoy validations. rMSIfragment applies to multiple MALDI-MSI sample types and experimental setups. Finally, we demonstrate that overlooking in-source fragments increases the number of incorrect annotations. Annotation workflows should consider in-source fragmentation tools such as rMSIfragment to increase annotation confidence and reduce the number of false positives.

Visualization of metabolites and microbes at high spatial resolution using MALDI mass spectrometry imaging and in situ fluorescence labeling.

Label-free molecular imaging techniques such as matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) enable the direct and simultaneous mapping of hundreds of different metabolites in thin sections of biological tissues. However, in host-microbe interactions it remains challenging to localize microbes and to assign metabolites to the host versus members of the microbiome. We therefore developed a correlative imaging approach combining MALDI-MSI with fluorescence in situ hybridization (FISH) on the same section to identify and localize microbial cells. Here, we detail metaFISH as a robust and easy method for assigning the spatial distribution of metabolites to microbiome members based on imaging of nucleic acid probes, down to single-cell resolution. We describe the steps required for tissue preparation, on-tissue hybridization, fluorescence microscopy, data integration into a correlative image dataset, matrix application and MSI data acquisition. Using metaFISH, we map hundreds of metabolites and several microbial species to the micrometer scale on a single tissue section. For example, intra- and extracellular bacteria, host cells and their associated metabolites can be localized in animal tissues, revealing their complex metabolic interactions. We explain how we identify low-abundance bacterial infection sites as regions of interest for high-resolution MSI analysis, guiding the user to a trade-off between metabolite signal intensities and fluorescence signals. MetaFISH is suitable for a broad range of users from environmental microbiologists to clinical scientists. The protocol requires ~2 work days.

Validating MALDI-IMS Feasibility in Ex Vivo Brain Slices.

Matrix-assisted laser desorption ionization imaging mass spectrometry (MALDI-IMS) generates unique mass spectra in X/Y coordinates across a tissue sample, thus allowing for the spatial detection and relative quantification of biologic compounds in situ. The soft ionization of MALDI-IMS makes it an ideal technique for high-resolution imaging of complex lipid species. Lipid-based spatial chemical maps derived from MALDI-IMS provide critical insight into the unique molecular profiles of a variety of neurologic diseases. Ex vivo brain slice preparations are a prominent alternative to in vivo animal models for studying many different neurologic conditions. For the first time, we present a feasible protocol for achieving reproducible lipidomic MALDI-IMS data from ex vivo rat brain slices and provide evidence that ex vivo brain slices maintain spatiochemical lipidomic profiles representative of an intact whole brain. We conducted a methods comparison assessing the lipid profiles within the neocortex, striatum, and corpus callosum between coronal sections taken from ex vivo brain slices and the current gold standard tissue preparation method, fresh frozen whole brains. For the first time we demonstrate a technique by which 400 μm ex vivo brain slices can be extracted from an imaging chamber and prepared for MALDI-IMS in a way that preserves their lipidomic integrity. We demonstrate the feasibility of MALDI-IMS in ex vivo brain slices and provide a roadmap for MALDI-IMS utilization in uncharted neuroscience fields.

Chemical QuantArray: A Quantitative Tool for Mass Spectrometry Imaging.

Matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) is a powerful analytical technique that provides spatially preserved detection and quantification of analytes in tissue specimens. However, clinical translation still requires improved throughput, precision, and accuracy. To accomplish this, we created "Chemical QuantArray", a gelatin tissue microarray (TMA) mold filled with serial dilutions of isotopically labeled endogenous metabolite standards. The mold is then cryo-sectioned onto a tissue homogenate to produce calibration curves. To improve precision and accuracy, we automatically remove pixels outside of each TMA well and investigated several intensity normalizations, including the utilization of a second stable isotope internal standard (IS). Chemical QuantArray enables the quantification of several endogenous metabolites over a wide dynamic range and significantly improve over current approaches. The technique reduces the space needed on the MALDI slides for calibration standards by approximately 80%. Furthermore, removal of empty pixels and normalization to an internal standard or matrix peak provided precision (<20% RSD) and accuracy (<20% DEV). Finally, we demonstrate the applicability of Chemical QuantArray by quantifying multiple purine metabolites in 14 clinical tumor specimens using a single MALDI slide. Chemical QuantArray improves the analytical characteristics and practical feasibility of MALDI-MSI metabolite quantification in clinical and translational applications.

Metabolic changes and potential biomarkers in "Candidatus Liberibacter solanacearum"-infected potato psyllids: implications for psyllid-pathogen interactions.

Psyllid yellows, vein-greening (VG), and zebra chip (ZC) diseases, which are primarily transmitted by potato psyllid (PoP) carrying Candidatus Liberibacter solanacearum (CLso), have caused significant losses in solanaceous crop production worldwide. Pathogens interact with their vectors at the organic and cellular levels, while the potential changes that may occur at the biochemical level are less well reported. In this study, the impact of CLso on the metabolism of PoP and the identification of biomarkers from infected psyllids were examined. Using ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS) analysis, metabolomic changes in CLso-infected psyllids were compared to uninfected ones. A total of 34 metabolites were identified as potential biomarkers of CLso infection, which were primarily related to amino acid, carbohydrate, and lipid metabolism. The significant increase in glycerophospholipids is thought to be associated with CLso evading the insect vector's immune defense. Matrix-assisted Laser Desorption Ionization Mass Spectrometry Imaging (MALDI-MSI) was used to map the spatial distribution of these biomarkers, revealing that 15-keto-Prostaglandin E2 and alpha-D-Glucose were highly expressed in the abdomen of uninfected psyllids but down-regulated in infected psyllids. It is speculated that this down-regulation may be due to CLso evading surveillance by immune suppression in the PoP midgut. Overall, valuable biochemical information was provided, a theoretical basis for a better understanding of psyllid-pathogen interactions was offered, and the findings may aid in breaking the transmission cycle of these diseases.

Visualization of Differential Cardiolipin Profiles in Murine Retinal Cell Layers by High-Resolution MALDI Mass Spectrometry Imaging.

The precise fatty acyl chain configuration of cardiolipin (CL), a tetrameric mitochondrial-specific membrane lipid, exhibits dependence on cell and tissue types. A powerful method to map CL profiles in tissue sections in a spatially resolved manner is matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI). To build on and explore this potential, we employed a quadrupole time-of-flight mass spectrometer along with optimized sample preparation protocols. We imaged the CL profiles of individual murine retinal cell layers at a pixel size of 10 μm. In combination with tandem MS, we obtained detailed insights into the CL composition of individual retinal cell layers. In particular, we found differential expression of the polyunsaturated fatty acids (PUFA) linoleic, arachidonic, and docosahexaenoic acids. PUFAs are prone to peroxidation and hence regarded as critical factors in development and progression of retinal pathologies, such as age-related macular degeneration (AMD). The ability of MALDI-MSI to provide cues on the CL composition in neuronal tissue with close to single-cell resolution can provide important insights into retinal physiology in health and disease.

How the Oviduct Lipidomic Profile Changes over Time after the Start of an Obesogenic Diet in an Outbred Mouse Model.

We investigated whether a high-fat/high-sugar (HF/HS) diet alters the lipidomic profile of the oviductal epithelium (OE) and studied the patterns of these changes over time. Female outbred Swiss mice were fed either a control (10% fat) or HF/HS (60% fat, 20% fructose) diet. Mice (n = 3 per treatment per time point) were sacrificed and oviducts were collected at 3 days and 1, 4, 8, 12 and 16 weeks on the diet. Lipids in the OE were imaged using matrix-assisted laser desorption ionisation mass spectrometry imaging. Discriminative m/z values and differentially regulated lipids were determined in the HF/HS versus control OEs at each time point. Feeding the obesogenic diet resulted in acute changes in the lipid profile in the OE already after 3 days, and thus even before the development of an obese phenotype. The changes in the lipid profile of the OE progressively increased and became more persistent after long-term HF/HS diet feeding. Functional annotation revealed a differential abundance of phospholipids, sphingomyelins and lysophospholipids in particular. These alterations appear to be not only caused by the direct accumulation of the excess circulating dietary fat but also a reduction in the de novo synthesis of several lipid classes, due to oxidative stress and endoplasmic reticulum dysfunction. The described diet-induced lipidomic changes suggest alterations in the OE functions and the oviductal microenvironment which may impact crucial reproductive events that take place in the oviduct, such as fertilization and early embryo development.

Statistical Modelling Investigation of MALDI-MSI-Based Approaches for Document Examination

Questioned document examination aims to assess if a document of interest has been forged. Spectroscopy-based methods are the gold standard for this type of evaluation. In the past 15 years, Matrix-Assisted Laser Desorption Ionisation–Mass Spectrometry Imaging (MALDI-MSI) has emerged as a powerful analytical tool for the examination of finger marks, blood, and hair. Therefore, this study intended to explore the possibility of expanding the forensic versatility of this technique through its application to questioned documents. Specifically, a combination of MALDI-MSI and chemometric approaches was investigated for the differentiation of seven gel pens, through their ink composition, over 44 days to assess: (i) the ability of MALDI MSI to detect and image ink chemical composition and (ii) the robustness of the combined approach for the classification of different pens over time. The training data were modelled using elastic net logistic regression to obtain probabilities for each pen class and assess the time effect on the ink. This strategy led the classification model to yield predictions matching the ground truth. This model was validated using signatures generated by different pens (blind to the analyst), yielding a 100% accuracy in machine learning cross-validation. These data indicate that the coupling of MALDI-MSI with machine learning was robust for ink discrimination within the dataset and conditions investigated, which justifies further studies, including that of confounders such as paper brands and environmental factors.