Mass cytometry: blessed with the curse of dimensionality.

Immunologists are being compelled to develop new high-dimensional perspectives of cellular heterogeneity and to determine which applications best exploit the power of mass cytometry and associated multiplex approaches.

Multiscale biochemical mapping of the brain through deep-learning-enhanced high-throughput mass spectrometry.

Spatial omics technologies can reveal the molecular intricacy of the brain. While mass spectrometry imaging (MSI) provides spatial localization of compounds, comprehensive biochemical profiling at a brain-wide scale in three dimensions by MSI with single-cell resolution has not been achieved. We demonstrate complementary brain-wide and single-cell biochemical mapping using MEISTER, an integrative experimental and computational mass spectrometry (MS) framework. Our framework integrates a deep-learning-based reconstruction that accelerates high-mass-resolving MS by 15-fold, multimodal registration creating three-dimensional (3D) molecular distributions and a data integration method fitting cell-specific mass spectra to 3D datasets. We imaged detailed lipid profiles in tissues with millions of pixels and in large single-cell populations acquired from the rat brain. We identified region-specific lipid contents and cell-specific localizations of lipids depending on both cell subpopulations and anatomical origins of the cells. Our workflow establishes a blueprint for future development of multiscale technologies for biochemical characterization of the brain.

A risk assessment framework for multidrug-resistant Staphylococcus aureus using machine learning and mass spectrometry technology.

The emergence of multidrug-resistant bacteria is a critical global crisis that poses a serious threat to public health, particularly with the rise of multidrug-resistant Staphylococcus aureus. Accurate assessment of drug resistance is essential for appropriate treatment and prevention of transmission of these deadly pathogens. Early detection of drug resistance in patients is critical for providing timely treatment and reducing the spread of multidrug-resistant bacteria. This study aims to develop a novel risk assessment framework for S. aureus that can accurately determine the resistance to multiple antibiotics. The comprehensive 7-year study involved ˃20 000 isolates with susceptibility testing profiles of six antibiotics. By incorporating mass spectrometry and machine learning, the study was able to predict the susceptibility to four different antibiotics with high accuracy. To validate the accuracy of our models, we externally tested on an independent cohort and achieved impressive results with an area under the receiver operating characteristic curve of 0. 94, 0.90, 0.86 and 0.91, and an area under the precision-recall curve of 0.93, 0.87, 0.87 and 0.81, respectively, for oxacillin, clindamycin, erythromycin and trimethoprim-sulfamethoxazole. In addition, the framework evaluated the level of multidrug resistance of the isolates by using the predicted drug resistance probabilities, interpreting them in the context of a multidrug resistance risk score and analyzing the performance contribution of different sample groups. The results of this study provide an efficient method for early antibiotic decision-making and a better understanding of the multidrug resistance risk of S. aureus.

SpecieScan: semi-automated taxonomic identification of bone collagen peptides from MALDI-ToF-MS.

MOTIVATION: Zooarchaeology by Mass Spectrometry (ZooMS) is a palaeoproteomics method for the taxonomic determination of collagen, which traditionally involves challenging manual spectra analysis with limitations in quantitative results. As the ZooMS reference database expands, a faster and reproducible identification tool is necessary. Here we present SpecieScan, an open-access algorithm for automating taxa identification from raw MALDI-ToF mass spectrometry (MS) data. RESULTS: SpecieScan was developed using R (pre-processing) and Python (automation). The algorithm's output includes identified peptide markers, closest matching taxonomic group (taxon, family, order), correlation scores with the reference databases, and contaminant peaks present in the spectra. Testing on original MS data from bones discovered at Palaeothic archaeological sites, including Denisova Cave in Russia, as well as using publicly-available, externally produced data, we achieved >90% accuracy at the genus-level and ∼92% accuracy at the family-level for mammalian bone collagen previously analysed manually. AVAILABILITY AND IMPLEMENTATION: The SpecieScan algorithm, along with the raw data used in testing, results, reference database, and common contaminants lists are freely available on Github (https://github.com/mesve/SpecieScan).

Prospective on Imaging Mass Spectrometry in Clinical Diagnostics.

Imaging mass spectrometry (IMS) is a molecular technology utilized for spatially driven research, providing molecular maps from tissue sections. This article reviews matrix-assisted laser desorption ionization (MALDI) IMS and its progress as a primary tool in the clinical laboratory. MALDI mass spectrometry has been used to classify bacteria and perform other bulk analyses for plate-based assays for many years. However, the clinical application of spatial data within a tissue biopsy for diagnoses and prognoses is still an emerging opportunity in molecular diagnostics. This work considers spatially driven mass spectrometry approaches for clinical diagnostics and addresses aspects of new imaging-based assays that include analyte selection, quality control/assurance metrics, data reproducibility, data classification, and data scoring. It is necessary to implement these tasks for the rigorous translation of IMS to the clinical laboratory; however, this requires detailed standardized protocols for introducing IMS into the clinical laboratory to deliver reliable and reproducible results that inform and guide patient care.

Mass spectrometry imaging to explore molecular heterogeneity in cell culture.

Molecular analysis on the single-cell level represents a rapidly growing field in the life sciences. While bulk analysis from a pool of cells provides a general molecular profile, it is blind to heterogeneities between individual cells. This heterogeneity, however, is an inherent property of every cell population. Its analysis is fundamental to understanding the development, function, and role of specific cells of the same genotype that display different phenotypical properties. Single-cell mass spectrometry (MS) aims to provide broad molecular information for a significantly large number of cells to help decipher cellular heterogeneity using statistical analysis. Here, we present a sensitive approach to single-cell MS based on high-resolution MALDI-2-MS imaging in combination with MALDI-compatible staining and use of optical microscopy. Our approach allowed analyzing large amounts of unperturbed cells directly from the growth chamber. Confident coregistration of both modalities enabled a reliable compilation of single-cell mass spectra and a straightforward inclusion of optical as well as mass spectrometric features in the interpretation of data. The resulting multimodal datasets permit the use of various statistical methods like machine learning-driven classification and multivariate analysis based on molecular profile and establish a direct connection of MS data with microscopy information of individual cells. Displaying data in the form of histograms for individual signal intensities helps to investigate heterogeneous expression of specific lipids within the cell culture and to identify subpopulations intuitively. Ultimately, t-MALDI-2-MSI measurements at 2-µm pixel sizes deliver a glimpse of intracellular lipid distributions and reveal molecular profiles for subcellular domains.

Advancing rare cancer research by MALDI mass spectrometry imaging: Applications, challenges, and future perspectives in sarcoma.

MALDI mass spectrometry imaging (MALDI imaging) uniquely advances cancer research, by measuring spatial distribution of endogenous and exogenous molecules directly from tissue sections. These molecular maps provide valuable insights into basic and translational cancer research, including tumor biology, tumor microenvironment, biomarker identification, drug treatment, and patient stratification. Despite its advantages, MALDI imaging is underutilized in studying rare cancers. Sarcomas, a group of malignant mesenchymal tumors, pose unique challenges in medical research due to their complex heterogeneity and low incidence, resulting in understudied subtypes with suboptimal management and outcomes. In this review, we explore the applicability of MALDI imaging in sarcoma research, showcasing its value in understanding this highly heterogeneous and challenging rare cancer. We summarize all MALDI imaging studies in sarcoma to date, highlight their impact on key research fields, including molecular signatures, cancer heterogeneity, and drug studies. We address specific challenges encountered when employing MALDI imaging for sarcomas, and propose solutions, such as using formalin-fixed paraffin-embedded tissues, and multiplexed experiments, and considerations for multi-site studies and digital data sharing practices. Through this review, we aim to spark collaboration between MALDI imaging researchers and clinical colleagues, to deploy the unique capabilities of MALDI imaging in the context of sarcoma.

Feasibility of MALDI-MSI-Based Proteomics Using Bouin-Fixed Pathology Samples: Untapping the Goldmine of Nephropathology Archives.

The application of innovative spatial proteomics techniques, such as those based upon matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) technology, has the potential to impact research in the field of nephropathology. Notwithstanding, the possibility to apply this technology in more routine diagnostic contexts remains limited by the alternative fixatives employed by this ultraspecialized diagnostic field, where most nephropathology laboratories worldwide use bouin-fixed paraffin-embedded (BFPE) samples. Here, the feasibility of performing MALDI-MSI on BFPE renal tissue is explored, evaluating variability within the trypsin-digested proteome as a result of different preanalytical conditions and comparing them with the more standardized formalin-fixed paraffin-embedded (FFPE) counterparts. A large proportion of the features (270, 68.9%) was detected in both BFPE and FFPE renal samples, demonstrating only limited variability in signal intensity (10.22-10.06%). Samples processed with either fixative were able to discriminate the principal parenchyma regions along with diverse renal substructures, such as glomeruli, tubules, and vessels. This was observed when performing an additional "stress test", showing comparable results in both BFPE and FFPE samples when the distribution of several amyloid fingerprint proteins was mapped. These results suggest the utility of BFPE tissue specimens in MSI-based nephropathology research, further widening their application in this field.

Low-Invasive Sampling Method with Tape-Disc Sampling for the Taxonomic Identification of Archeological and Paleontological Bones by Proteomics.

Collagen from paleontological bones is an important organic material for isotopic measurement, radiocarbon analysis, and paleoproteomic analysis to provide information on diet, dating, taxonomy, and phylogeny. Current paleoproteomic methods are destructive and require from a few milligrams to several tens of milligrams of bone for analysis. In many cultures, bones are raw materials for artifacts that are conserved in museums, which hampers damage to these precious objects during sampling. Here, we describe a low-invasive sampling method that identifies collagen, taxonomy, and post-translational modifications from Holocene and Upper Pleistocene bones dated to 130,000 and 150 BC using dermatological skin tape discs for sampling. The sampled bone micropowders were digested following our highly optimized enhanced filter-aided sample preparation protocol and then analyzed by MALDI FTICR MS and LC-MS/MS for identifying the genus taxa of the bones. We show that this low-invasive sampling does not deteriorate the bones and achieves results similar to those obtained by more destructive sampling. Moreover, this sampling method can be carried out at archeological sites or in museums.

Spatio-Temporal Study of Galactolipid Biosynthesis in Duckweed Using Mass Spectrometry Imaging and in vivo Isotope Labeling.

Isotope labeling coupled with mass spectrometry imaging (MSI) presents a potent strategy for elucidating the dynamics of metabolism at cellular resolution, yet its application to plant systems is scarce. It has the potential to reveal the spatio-temporal dynamics of lipid biosynthesis during plant development. In this study, we explore its application to galactolipid biosynthesis of an aquatic plant, Lemna minor, with D2O labeling. Specifically, matrix-assisted laser desorption/ionization-MSI data of two major galactolipids in L. minor, monogalactosyldiacylglycerol and digalactosyldiacylglycerol, were studied after growing in 50% D2O media over a 15-day time period. When they were partially labeled after 5 d, three distinct binomial isotopologue distributions were observed corresponding to the labeling of partial structural moieties: galactose only, galactose and a fatty acyl chain and the entire molecule. The temporal change in the relative abundance of these distributions follows the expected linear pathway of galactolipid biosynthesis. Notably, their mass spectrometry images revealed the localization of each isotopologue group to the old parent frond, the intermediate tissues and the newly grown daughter fronds. Besides, two additional labeling experiments, (i) 13CO2 labeling and (ii) backward labeling of completely 50% D2O-labeled L. minor in H2O media, confirm the observations in forward labeling. Furthermore, these experiments unveiled hidden isotopologue distributions indicative of membrane lipid restructuring. This study suggests the potential of isotope labeling using MSI to provide spatio-temporal details in lipid biosynthesis in plant development.

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.

Spatialized Metabolomic Annotation Combining MALDI Imaging and Molecular Networks.

MALDI mass spectrometry imaging has gained major interest in the field of chemical imaging. This technique makes it possible to locate tens to hundreds of ionic signals on the sample surface without any a priori. One of the current challenges is still the limited ability to annotate signals in order to convert m/z values into probable chemical structures. At the same time, data obtained by LC-MS/MS have benefited from the development of numerous chemoinformatics tools, in particular molecular networks, for their efficient annotation. For the first time, we present here the combination of MALDI-FT-ICR imaging with molecular networks from MALDI-MS/MS data directly acquired on plant tissue sections. Annotation improvements are demonstrated, paving the way for new annotation pipelines for MALDI imaging.

2-Hydroxy-5-nitro-3-(trifluoromethyl)pyridine as a Novel Matrix for Enhanced MALDI Imaging of Tissue Metabolites.

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), which is a label-free imaging technique, determines the spatial distribution and relative abundance of versatile endogenous metabolites in tissues. Meanwhile, matrix selection is generally regarded as a pivotal step in MALDI tissue imaging. This study presents the first report of a novel MALDI matrix, 2-hydroxy-5-nitro-3-(trifluoromethyl)pyridine (HNTP), for the in situ detection and imaging of endogenous metabolites in rat liver and brain tissues by MALDI-MS in positive-ion mode. The HNTP matrix exhibits excellent characteristics, including strong ultraviolet absorption, µm-scale matrix crystals, high chemical stability, low background ion interference, and high metabolite ionization efficiency. Notably, the HNTP matrix also shows superior detection capabilities, successfully showing 185 detectable metabolites in rat liver tissue sections. This outperforms the commonly used matrices of 2,5-dihydroxybenzoic acid and 2-mercaptobenzothiazole, which detect 145 and 120 metabolites from the rat liver, respectively. Furthermore, a total of 152 metabolites are effectively detected and imaged in rat brain tissue using the HNTP matrix, and the spatial distribution of these compounds clearly shows the heterogeneity of the rat brain. The results demonstrate that HNTP is a new and powerful positive-ion mode matrix to enhance the analysis of metabolites in biological tissues by MALDI-MSI.

Imaging Mass Spectrometry of Isotopically Resolved Intact Proteins on a Trapped Ion-Mobility Quadrupole Time-of-Flight Mass Spectrometer.

In this work, we demonstrate rapid, high spatial, and high spectral resolution imaging of intact proteins by matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) on a hybrid quadrupole-reflectron time-of-flight (qTOF) mass spectrometer equipped with trapped ion mobility spectrometry (TIMS). Historically, untargeted MALDI IMS of proteins has been performed on TOF mass spectrometers. While advances in TOF instrumentation have enabled rapid, high spatial resolution IMS of intact proteins, TOF mass spectrometers generate relatively low-resolution mass spectra with limited mass accuracy. Conversely, the implementation of MALDI sources on high-resolving power Fourier transform (FT) mass spectrometers has allowed IMS experiments to be conducted with high spectral resolution with the caveat of increasingly long data acquisition times. As illustrated here, qTOF mass spectrometers enable protein imaging with the combined advantages of TOF and FT mass spectrometers. Protein isotope distributions were resolved for both a protein standard mixture and proteins detected from a whole-body mouse pup tissue section. Rapid (∼10 pixels/s) 10 µm lateral spatial resolution IMS was performed on a rat brain tissue section while maintaining isotopic spectral resolution. Lastly, proof-of-concept MALDI-TIMS data was acquired from a protein mixture to demonstrate the ability to differentiate charge states by ion mobility. These experiments highlight the advantages of qTOF and timsTOF platforms for resolving and interpreting complex protein spectra generated from tissue by IMS.

Development of Transmission Ambient Pressure Laser Desorption Ionization/Postphotoionization Mass Spectrometry Imaging.

Laser-based high-resolution mass spectrometry imaging at ambient conditions has promising applications in life science. However, the ion yield during laser desorption/ablation is poor. Here, transmission atmospheric pressure laser desorption ionization combined with a compact postphotoionization (t-AP-LDI/PI) assembly with a krypton discharge lamp was developed for the untargeted imaging of various biomolecules. The spatial distributions of numerous lipid classes, fatty acids, neurotransmitters, and amino acids in the subregions of mouse cerebellum tissue were obtained. Compared with single laser ablation, the sensitivities for most analytes were increased by 1 to 3 orders of magnitude by dopant-assisted postphotoionization. After careful optimization, a spatial resolution of 4 µm could be achieved for the metabolites in mouse hippocampus tissue. Finally, the melanoma tissue slices were analyzed using t-AP-LDI/PI MSI, which revealed the metabolic heterogeneity of the melanoma microenvironment and exhibited the phenomenon of abnormal proliferation and invasion trends in tumor cells.

Mass Spectrometry Imaging and Histology for the Analysis of Budding Intestinal Organoids.

Three-dimensional (3D) organoids have been at the forefront of regenerative medicine and cancer biology fields for the past decade. However, the fragile nature of organoids makes their spatial analysis challenging due to their budding structures and composition of single layer of cells. The standard sample preparation approaches can collapse the organoid morphology. Therefore, in this study, we evaluated several approaches to optimize a method compatible with both mass spectrometry imaging (MSI) and immunohistological techniques. Murine intestinal organoids were used to evaluate embedding in gelatin, carboxymethylcellulose (CMC)-gelatin-CMC-sucrose, or hydroxypropyl methylcellulose (HPMC) and polyvinylpyrrolidone (PVP) solutions. Organoids were assessed with and without aldehyde fixation and analyzed for lipid distributions by MSI coupled with hematoxylin and eosin (H&E) staining and immunofluorescence (IF) in consecutive sections from the same sample. While chemical fixation preserves morphology for better histological outcomes, it can lead to suppression of the matrix-assisted laser desorption/ionization (MALDI) lipid signal. By contrast, leaving organoid samples unfixed enhanced MALDI lipid signal. The method that performed best for both MALDI and histological analysis was embedding unfixed samples in HPMC and PVP. This approach allowed assessment of cell proliferation by Ki67 while also identifying putative phosphatidylethanolamine (PE(18:0/18:1)), which was confirmed further by tandem MS approaches. Overall, these protocols will be amenable to multiplexing imaging mass spectrometry analysis with several histological assessments and help advance our understanding of the biological processes that take place in district subsets of cells in budding organoid structures.

MALDI-MSI-LC-MS/MS Workflow for Single-Section Single Step Combined Proteomics and Quantitative Lipidomics.

We introduce a novel approach for comprehensive molecular profiling in biological samples. Our single-section methodology combines quantitative mass spectrometry imaging (Q-MSI) and a single step extraction protocol enabling lipidomic and proteomic liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis on the same tissue area. The integration of spatially correlated lipidomic and proteomic data on a single tissue section allows for a comprehensive interpretation of the molecular landscape. Comparing Q-MSI and Q-LC-MS/MS quantification results sheds new light on the effect of MSI and related sample preparation. Performing MSI before Q-LC-MS on the same tissue section led to fewer protein identifications and a lower correlation between lipid quantification results. Also, the critical role and influence of internal standards in Q-MSI for accurate quantification is highlighted. Testing various slide types and the evaluation of different workflows for single-section spatial multiomics analysis emphasized the need for critical evaluation of Q-MSI data. These findings highlight the necessity for robust quantification methods comparable to current gold-standard LC-MS/MS techniques. The spatial information from MSI allowed region-specific insights within heterogeneous tissues, as demonstrated for glioblastoma multiforme. Additionally, our workflow demonstrated the efficiency of a single step extraction for lipidomic and proteomic analyses on the same tissue area, enabling the examination of significantly altered proteins and lipids within distinct regions of a single section. The integration of these insights into a lipid-protein interaction network expands the biological information attainable from a tissue section, highlighting the potential of this comprehensive approach for advancing spatial multiomics research.

Lewis Acidic Metal-Organic Framework Assisted Ambient Liquid Extraction Mass Spectrometry Imaging for Enhancing the Coverage of Poorly Ionizable Lipids in Brain Tissue.

The spatial distribution of lipidomes in tissues is of great importance in studies of living processes, diseases, and therapies. Mass spectrometry imaging (MSI) has become a critical technique for spatial lipidomics. However, MSI of low-abundance or poorly ionizable lipids is still challenging because of the ion suppression from high-abundance lipids. Here, a metal-organic framework (MOF) Zr6O4(OH)4(1,3,5-Tris(4-carboxyphenyl) benzene)2(triflate)6(Zr6OTf-BTB) was prepared and used for selective on-tissue adsorption of phospholipids to reduce ion suppression from them to poorly ionizable lipids. The results show that Zr6OTf-BTB with strong Lewis acidic sites and a large specific surface area (647.9 m2·g-1) could selectively adsorb phospholipids under 1% FA-MeOH. Adsorption efficiencies of phospholipids are 88.4-144.9 times higher than those of other neutral lipids. Moreover, the adsorption capacity and the adsorption kinetic rate constant of the new material to phospholipids are higher than those of Zr6-BTB (242.72 vs 73.96 mg·g-1, 0.0442 vs 0.0220 g·mg-1·min-1). A Zr6OTf-BTB sheet was prepared by a lamination technique for on-tissue phospholipid adsorption from brain tissue. Then, the tissue section on the Zr6OTf-BTB sheet was directly imaged via ambient liquid extraction-MSI with 1% FA-MeOH as the sampling solvent. The results showed that phospholipids could be 100% removed directly on tissue, and the detection coverage of the Zr6OTf-BTB-enhanced MSI method to ceramides (Cers) and hexosylceramides (HexCers) was increased by 5-26 times compared with direct tissue MSI (26 vs 1 and 17 vs 3). The new method provides an efficient and convenient way to eliminate the ion suppression from phospholipids in MSI, largely improving the detection coverage of low-abundance and poorly ionizable lipids.

Nitro Indole Derivatives as Novel Dual-Polarity Matrices for MALDI Mass Spectrometry and Imaging with Broad Applications.

A new matrix framework is presented in this study for the improved ionization efficiency of complex mixtures by matrix-assisted laser desorption ionization (MALDI) mass spectrometry/imaging. Five nitro indole (NI) derivatives [3-methyl-4-nitro-1H-indole (3,4-MNI), 3-methyl-6-nitro-1H-indole (3,6-MNI), 2,3-dimethyl-4-nitro-1H-indole (2,3,4-DMNI), 2,3-dimethyl-6-nitro-1H-indole (2,3,6-DMNI), and 4-nitro-1H-indole (4-NI)] were synthesized and shown to produce both positive and negative ions with a broad class of analytes as MALDI matrices. NI matrices were compared to several common matrices, such as 2,5-dihydroxybenzoic acid (DHB), alpha-cyano-4-hydroxylcinnamic acid (CHCA), sinapinic acid (SA), 1,5-diaminonaphthelene (1,5-DAN), and 9-aminoacridine (9-AA), for the analysis of lipid, peptide, protein, glycan, and perfluorooctanesulfonic acid (PFOS) compounds. 3,4-MNI demonstrated the best performance among the NI matrices. This matrix resulted in reduced ion suppression and better detection sensitivity for complex mixtures, for example, egg lipids/milk proteins/PFOS in tap water, while 2,3,6-DMNI was the best matrix for blueberry tissue imaging. Several important aspects of this work are reported: (1) dual-polarity ion production with NI matrices and complex mixtures; (2) quantitative analysis of PFOS with a LOQ of 0.5 ppb in tap water and 0.05 ppb in MQ water (without solid phase extraction enrichment), with accuracy and precision within 5%; (3) MALDI imaging with 2,3,6-DMNI as a matrix for plant metabolite/lipid identification with ionization enhancement in the negative ion mode m/z 600-900 region; and (4) development of a thin film deposition under/above tissue method for MALDI imaging with a vacuum sublimation matrix on a high-vacuum MALDI instrument.

Highly Sensitive Spatial Glycomics at Near-Cellular Resolution by On-Slide Derivatization and Mass Spectrometry Imaging.

Glycans on proteins and lipids play important roles in maturation and cellular interactions, contributing to a variety of biological processes. Aberrant glycosylation has been associated with various human diseases including cancer; however, elucidating the distribution and heterogeneity of glycans in complex tissue samples remains a major challenge. Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) is routinely used to analyze the spatial distribution of a variety of molecules including N-glycans directly from tissue surfaces. Sialic acids are nine carbon acidic sugars that often exist as the terminal sugars of glycans and are inherently difficult to analyze using MALDI-MSI due to their instability prone to in- and postsource decay. Here, we report on a rapid and robust method for stabilizing sialic acid on N-glycans in FFPE tissue sections. The established method derivatizes and identifies the spatial distribution of α2,3- and α2,6-linked sialic acids through complete methylamidation using methylamine and PyAOP ((7-azabenzotriazol-1-yloxy)tripyrrolidinophosphonium hexafluorophosphate). Our in situ approach increases the glycans detected and enhances the coverage of sialylated species. Using this streamlined, sensitive, and robust workflow, we rapidly characterize and spatially localize N-glycans in human tumor tissue sections. Additionally, we demonstrate this method's applicability in imaging mammalian cell suspensions directly on slides, achieving cellular resolution with minimal sample processing and cell numbers. This workflow reveals the cellular locations of distinct N-glycan species, shedding light on the biological and clinical significance of these biomolecules in human diseases.