Mass Spectrometry Imaging: A Review of Emerging Advancements and Future Insights

Metabolic heterogeneity in tumor cells impacts immunology in lung squamous cell carcinoma

Metabolic processes are crucial in immune regulation, yet the impact of metabolic heterogeneity on immunological functions remains unclear. Integrating metabolomics into immunology allows the exploration of the interactions of multilayered features in the biological system and the molecular regulatory mechanism of these features. To elucidate such insight in lung squamous cell carcinoma (LUSC), we analyzed 106 LUSC tumor tissues. We performed high-resolution matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) to obtain spatial metabolic profiles, and immunohistochemistry to detect tumor-infiltrating T lymphocytes (TILs). Unsupervised k-means clustering and Simpson's diversity index were employed to assess metabolic heterogeneity, identifying five distinct metabolic tumor subpopulations. Our findings revealed that TILs are specifically associated with metabolite distributions, not randomly distributed. Integrating a validation cohort, we found that heterogeneity-correlated metabolites interact with CD8+ TIL-associated genes, affecting survival. High metabolic heterogeneity was linked to worse survival and lower TIL levels. Pathway enrichment analyses highlighted distinct metabolic pathways in each subpopulation and their potential responses to chemotherapy. This study uncovers the significant impact of metabolic heterogeneity on immune functions in LUSC, providing a foundation for tailoring therapeutic strategies.

Mapping the architecture of animal toxin systems by mass spectrometry imaging

Animal toxins are proteins, peptides or metabolites that cause negative effects against predators, prey or competitors following contact or injection. They work by interacting with enzymes, receptors and other targets causing pain, debilitation or leading even to death. Their biological significance and pharmacological effects in humans make them interesting to researchers, but much remains to be learned about their mechanisms of action, storage, tissue-specific distribution and maturation. Mass spectrometry imaging (MSI), a technique that determines the spatial distribution of molecules based on their molecular mass, is uniquely positioned to answer these key questions and pioneering studies have already confirmed its potential impact on the field of zootoxinology. We provide the first comprehensive review of MSI as a means to study animal toxins, the lessons learned thus far, and potential future applications. This fills an important gap in the literature and will facilitate future work on the structure, function, evolutionary history and medical uses of animal toxins.

Molecular mass spectrometric imaging of amino acids in dietary supplement tablets using laser ablation-atmospheric pressure chemical ionization-trapped ion mobility spectrometry-mass spectrometry

A UV laser ablation system coupled to atmospheric pressure chemical ionization-trapped ion mobility spectrometry-mass spectrometry (LA-APCI-TIMS-MS) is presented as a novel mass spectrometry imaging (MSI) tool to investigate the distribution of amino acids and vitamins in dietary supplement tablets. The setup employs a custom-built LA interface for commercially available APCI sources. Average single pulse response (SPR) durations of less than 0.2 s full peak width at 1 % maximum (FW0.01 M) were achieved. Imaging analyses resulted in the detection of 16 amino acids and 10 vitamins, all with unique and complementary distributions that are in most cases heterogeneously distributed over the sample surface. To differentiate between leucine and isoleucine, a second analysis was conducted on the same amino acid tablet with TIMS, showing distinct distributions for the two compounds. These results illustrate the potential of the presented setup to gain insight into the composition and manufacturing conditions of dietary supplements.

Reversible tuning of membrane sterol levels by cyclodextrin in a dialysis setting

Large unilamellar vesicles are popular membrane models for studying the impact of lipids and bilayer properties on the structure and function of transmembrane proteins. However, the functional reconstitution of transmembrane proteins in liposomes can be challenging, especially if the hydrophobic thickness of the protein does not match the thickness of the lipid bilayer. Such hydrophobic mismatch causes protein aggregation and low yields during the reconstitution procedure, which are exacerbated in sterol-rich membranes featuring low membrane compressibility. Here, we explore new approaches to reversibly tune the sterol content of (proteo)liposomes with methyl-β-cyclodextrin (mβCD) in a dialysis setting. Maintaining (proteo)liposomes in a confined compartment minimizes loss of material during cholesterol transfer and facilitates efficient removal of mβCD. We monitor the sterol concentration in the membrane with help of the solvatochromic probe C-Laurdan, which reports on lipid packing. Using Förster resonance energy transfer, we show that cholesterol delivery to proteoliposomes induces the oligomerization of a membrane property sensor, whereas a subsequent removal of cholesterol demonstrates full reversibility. We propose that tuning membrane compressibility by mβCD-meditated cholesterol delivery and removal in a dialysis setup provides a new handle to study the impact of sterols and membrane compressibility on membrane protein structure, function, and dynamics.

MSIght: A Modular Platform for Improved Confidence in Global, Untargeted Mass Spectrometry Imaging Annotation

Mass spectrometry imaging (MSI) has gained popularity in clinical analyses due to its high sensitivity, specificity, and throughput. However, global profiling experiments are often still restricted to LC-MS/MS analyses that lack spatial localization due to low-throughput methods for on-tissue peptide identification and confirmation. Additionally, the integration of parallel LC-MS/MS peptide confirmation, as well as histological stains for accurate mapping of identifications, presents a large bottleneck for data analysis, limiting throughput for untargeted profiling experiments. Here, we present a novel platform, termed MSIght, which automates the integration of these multiple modalities into an accessible and modular platform. Histological stains of tissue sections are coregistered to their respective MSI data sets to improve spatial localization and resolution of identified peptides. MS/MS peptide identifications via untargeted LC-MS/MS are used to confirm putative MSI identifications, thus generating MS images with greater confidence in a high-throughput, global manner. This platform has the potential to enable large-scale clinical cohorts to utilize MSI in the future for global proteomic profiling that uncovers novel biomarkers in a spatially resolved manner, thus widely expanding the utility of MSI in clinical discovery.

Spatially Resolved Metabolomics Reveals Metabolic Heterogeneity Among Pulmonary Fibrosis

Pulmonary fibrosis (PF) is a chronic and progressive lung disease with fatal consequences. The study of PF is challenging due to the complex mechanism involved, the need to understand the heterogeneity and spatial organization within lung tissues. In this study, we investigate the metabolic heterogeneity between two forms of lung fibrosis: idiopathic pulmonary fibrosis (IPF) and silicosis, using advanced spatially-resolved metabolomics techniques. Employing high-resolution mass spectrometry imaging, we spatially mapped and identified over 260 metabolites in lung tissue sections from mouse models of IPF and silicosis. Histological analysis confirmed fibrosis in both models, with distinct pathological features: alveolar destruction and collagen deposition in IPF, and nodule formation in silicosis. Metabolomic analysis revealed significant differences between IPF and silicosis in key metabolic pathways, including phospholipid metabolism, purine/pyrimidine metabolism, and the TCA cycle. Notably, phosphocholine was elevated in silicosis but reduced in IPF, while carnitine levels decreased in both conditions. Additionally, glycolytic activity was increased in both models, but TCA cycle intermediates showed opposing trends. These findings highlight the spatial metabolic heterogeneity of PF and suggest potential metabolic targets for therapeutic intervention. Further investigation into the regulatory mechanisms behind these metabolic shifts may open new avenues for fibrosis treatment.

TEMI: tissue-expansion mass-spectrometry imaging

The spatial distribution of diverse biomolecules in multicellular organisms is essential for their physiological functions. High-throughput in situ mapping of biomolecules is crucial for both basic and medical research, and requires high scanning speed, spatial resolution, and chemical sensitivity. Here we developed a tissue-expansion method compatible with matrix-assisted laser desorption/ionization mass-spectrometry imaging (TEMI). TEMI reaches single-cell spatial resolution without sacrificing voxel throughput and enables the profiling of hundreds of biomolecules, including lipids, metabolites, peptides (proteins), and N-glycans. Using TEMI, we mapped the spatial distribution of biomolecules across various mammalian tissues and uncovered metabolic heterogeneity in tumors. TEMI can be easily adapted and broadly applied in biological and medical research, to advance spatial multi-omics profiling.

Cell-Instructive Biomaterials with Native-Like Biochemical Complexity

Biochemical signals in native tissue microenvironments instruct cell behavior during many biological processes ranging from developmental morphogenesis and tissue regeneration to tumor metastasis and disease progression. The detection and characterization of these signals using spatial and highly resolved quantitative methods have revealed their existence as matricellular proteins in the matrisome, some of which are bound to the extracellular matrix while others are freely diffusing. Including these biochemical signals in engineered biomaterials can impart enhanced functionality and native-like complexity, ultimately benefiting efforts to understand, model, and treat various diseases. In this review, we discuss advances in characterizing, mimicking, and harnessing biochemical signals in developing advanced engineered biomaterials. An overview of the diverse forms in which these biochemical signals exist and their effects on intracellular signal transduction is also provided. Finally, we highlight the application of biochemically complex biomaterials in the three broadly defined areas of tissue regeneration, immunoengineering, and organoid morphogenesis.

Spatial metabolomics platform combining mass spectrometry imaging and in-depth chemical characterization with capillary electrophoresis

Spatial metabolomics offers the combination of molecular identification and localization. As a tool for spatial metabolomics, mass spectrometry imaging (MSI) can provide detailed information on localization. However, molecular annotation with MSI is challenging due to the lack of separation prior to mass spectrometric analysis. Contrarily, surface sampling capillary electrophoresis mass spectrometry (SS-CE-MS) provides detailed molecular information, although the size of the sampling sites is modest. Here, we describe a platform for spatial metabolomics where MSI using pneumatically assisted nanospray desorption electrospray ionization (PA-nano-DESI) is combined with SS-CE-MS to gain both in-depth chemical information and spatial localization from thin tissue sections. We present the workflow, including the user-friendly setup and switching between the techniques, compare the obtained data, and demonstrate a quantitative approach when using the platform for spatial metabolomics of ischemic stroke.

3D printer platform and conductance feedback loop for automated imaging of uneven surfaces by liquid microjunction-surface sampling probe mass spectrometry

RATIONALE

Molecular imaging of samples using mass spectrometric techniques, such as matrix-assisted laser desorption ionization or desorption electrospray ionization, requires the sample surface to be even/flat and sliced into thin sections (c. 10 μm). Furthermore, sample preparation steps can alter the analyte composition of the sample. The liquid microjunction-surface sampling probe (LMJ-SSP) is a robust sampling interface that enables surface profiling with minimal sample preparation. In conjunction with a conductance feedback system, the LMJ-SSP can be used to automatically sample uneven specimens.

METHODS

A sampling stage was built with a modified 3D printer where the LMJ-SSP is attached to the printing head. This setup can scan across flat and even surfaces in a predefined pattern ("static sampling mode"). Uneven samples are automatically probed in "conductance sampling mode" where an electric potential is applied and measured at the probe. When the probe contacts the electrically grounded sample, the potential at the probe drops, which is used as a feedback signal to determine the optimal position of the probe for sampling each location.

RESULTS

The applicability of the probe/sensing system was demonstrated by first examining the strawberry tissue using the "static sampling mode." Second, porcine tissue samples were profiled using the "conductance sampling mode." With minimal sample preparation, an area of 11 × 15 mm was profiled in less than 2 h. From the obtained results, adipose areas could be distinguished from non-adipose parts. The versatility of the approach was further demonstrated by directly sampling the bacteria colonies on agar and resected human kidney (intratumoral hemorrhage) specimens with thicknesses ranging from 1 to 4 mm.

CONCLUSION

The LMJ-SSP in conjunction with a conductive feedback system is a powerful tool that allows for fast, reproducible, and automated assessment of uneven surfaces with minimal sample preparation. This setup could be used for perioperative assessment of tissue samples, food screening, and natural product discovery, among others.

Mass Spectrometry-Based Applications of Spheroids in Cancer Biology

The use of cell culture techniques to model human disease is an indispensable tool that has helped improve the health and well-being of the world. Monolayer cultures have most often been used for biomedical research, although not accurately recapitulating an in vivo human tumor. Tumor spheroids are a form of three-dimensional cell culture that better mimics an avascularized human tumor through their cell-cell contacts in all directions, development of various chemical gradients, and distinct populations of cells found within the spheroid. In this review, we highlight how mass spectrometry has propelled the utility of the spheroid model to understand cancer biology. We discuss how mass spectrometry imaging can be utilized to determine the penetration efficiency of various chemotherapeutics, how proteomics can be used to understand the biology in the various layers of a spheroid, and how metabolomics and lipidomics are used to elucidate how various spheroids behave toward chemotherapeutics.

Progress in Characterization of Lipopolysaccharides and Lipid A by Mass Spectrometry

Lipopolysaccharides (LPS) are complex molecules embedded in the outer membrane of Gram-negative bacteria. LPS are highly heterogeneous across species and strains, posing a significant analytical challenge. This review article explores recent advances in the identification and characterization of LPS, with a particular focus on the role of mass spectrometry (MS) techniques. The review highlights how MS, in conjunction with various separation methods and spanning different ionization techniques and dissociation modes, has enabled more precise and sensitive determination of LPS composition, with a focus on lipid A structure. Finally, emerging trends in MS applications for LPS research are discussed and its potential to provide deeper insights into the development of antibiotic resistance among pathogenic bacteria.

Achieving Extra-High-Quality Images in ToF-SIMS Molecular Imaging of Insulating Samples Using a Low Current O2+ Auxiliary Beam and Back Side Au Coating

Molecular imaging enabled by ToF-SIMS has become increasingly desirable in many research fields in the last several decades. However, complex charging on highly insulating samples and at phase-separation boundaries may lead to dark edges and boundaries in ion images, presenting a big obstacle to obtaining high quality ion images, even with low energy electron charge compensation. Depositing a thin metal layer on the sample surface or using a combination of a low energy electron beam and a low energy Argon ion beam can be helpful. However, surface metal deposition may lead to serious contamination, and the extra low energy argon ion gun is not available in most ToF-SIMS instruments. In this work, we report that a combination of a low current O2+ ion beam and a low energy electron beam can be used to resolve complex charging conditions and yield extra-high-quality ion images. A sucrose thin film sample was used as a model system to show that molecular imaging with this approach can be very feasible due to minimal beam-induced damage. For highly insulating samples, back side Au coating can be further helpful when combined with a low current O2+ ion beam. A few representative real-world samples were examined to verify the effectiveness of our new method. Additionally, the principle of our new method was also discussed. Since an O2+ ion source is regularly available in most ToF-SIMS instruments, we believe our new method will be widely used in ToF-SIMS imaging and spectral analysis of various insulating samples.

Large-Scale Metabolite Imaging Gallery of Mouse Organ Tissues to Study Spatial Metabolism

Mass spectrometry imaging (MSI) has revolutionized the study of tissue metabolism by enabling the visualization of small molecule metabolites (SMMs) with high spatial resolution. However, comprehensive SMM imaging databases for different organ tissues are lacking, hindering our understanding of spatial organ metabolism. To address this resource gap, we present a large-scale SMM imaging gallery for mouse brain, kidney, and liver, capturing SMMs spanning eight chemical super classes and encompassing over 40 metabolic pathways. Manual curation and display of these imaging data sets unveil spatial patterns of metabolites that are less documented in the reported organs. Specifically, we identify 65 SMMs in brain coronal sections and 71 in sagittal tissue sections, including spatial patterns for neurotransmitters. Furthermore, we map 98 SMMs in kidneys and 66 SMMs in liver, providing insights into their amino acid and glutathione metabolism. Our insightful SMM imaging gallery serves as a critical resource for the spatial metabolism research community, filling a significant resource gap. This resource is freely available for download and can be accessed through the BioImage Archive and METASPACE repositories, providing high-quality annotated images for potential future computational models and advancing our understanding of tissue metabolism at the spatial level.

Unraveling the molecular dynamics of wound healing: integrating spatially resolved lipidomics and temporally resolved proteomics

Understanding the spatial-temporal molecular dynamics of wound healing is crucial for devising effective treatments. Three-dimensional mass spectrometry imaging (3D MSI) enables the comprehensive visualization of molecular distribution throughout skin layers, offering valuable insights into the wound healing process. However, traditional 3D MSI often faces challenges in maintaining data integrity and accurate image registration in the third dimension. To address this, we employed infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI), a hybrid ambient ionization technique capable of sequential imaging through consecutive ablation events for precise 3D image reconstruction. Herein, 3D IR-MALDESI MSI was used to compare the lipidome of fresh-frozen wound samples at three stages of wound healing (inflammation, proliferation, and remodeling) with the healthy skin of SKH- 1 mice. Supplementing this data with a refined LC-MS-based proteomics protocol on selected wound biopsies, our integrated approach deepens our understanding of the molecular intricacies inherent in tissue regeneration.

Multimodal Mass Spectrometry Imaging in Atlas Building: A Review

In the era of precision medicine, scientists are creating atlases of the human body to map cells at the molecular level, providing insight into what fundamentally makes each cell different. In these atlas efforts, multimodal imaging techniques that include mass spectrometry imaging (MSI) have revolutionized the way biomolecules, such as lipids, peptides, proteins, and small metabolites, are visualized in the native spatial context of biological tissue. As such, MSI has become a fundamental arm of major cell atlasing efforts, as it can analyze the spatial distribution of hundreds of molecules in diverse sample types. These rich molecular data are then correlated with orthogonal assays, including histologic staining, proteomics, and transcriptomics, to analyze molecular classes that are not traditionally detected by MSI. Additional computational methods enable further examination of the correlations between biomolecular classes and creation of visualizations that serve as a powerful resource for researchers and clinicians trying to understand human health and disease. In this review, we examine modern multimodal imaging methods and how they contribute to precision medicine and the understanding of fundamental disease mechanisms. Semin Nephrol 36:x-xx © 20XX Elsevier Inc. All rights reserved.

Universal Photosensitizer for Isomer-Selective Lipid Imaging with High Molecular Coverage

Spatial lipidomics is a powerful technique for understanding the complexity of the lipidome in biological systems through mass spectrometry imaging (MSI). Recent advancements have enabled isomer-selected MSI (iMSI) of lipids in biological samples using both online and off-line derivatization strategies. Despite these impressive developments, most iMSI techniques are limited to either positive or negative ion mode analysis, restricting the molecular coverage achievable in a single experiment. Additionally, derivatization efficiency often varies across lipid classes, presenting challenges for comprehensive lipid analysis. In this study, we introduce tetrakis(4-carboxyphenyl)porphyrin (TCPP) as a universal photosensitizer that facilitates online lipid derivatization in both positive and negative ionization modes via singlet oxygen (1O2) reaction. This method enables the identification and localization of both acyl chain compositions and lipid carbon-carbon (C═C) isomers in liquid extraction-based ambient ionization techniques. We have also employed sodium fluoride (NaF) as a solvent dopant to enhance the analysis of low-abundance and poorly ionizable biomolecules. By integrating these online derivatization and signal enhancement strategies with nanospray desorption electrospray ionization (nano-DESI), we achieved dual polarity iMSI within the same sample. We demonstrate imaging of low-abundance isomeric lipids, which were otherwise below the noise level. Notably, TCPP significantly enhances the efficiency of the online derivatization of unsaturated fatty acids, for which other photosensitizers are inefficient. This novel approach allows for the imaging of isomeric fatty acids and phospholipids from multiple classes in the same experiment, revealing their distinct spatial localization within biological tissues.

OzMALDI: A Gas-Phase, In-Source Ozonolysis Reaction for Efficient Double-Bond Assignment in Mass Spectrometry Imaging with Matrix-Assisted Laser Desorption/Ionization

Lipids make up an important class of biomolecules with diverse structures and varied chemical functions. This diversity is a major challenge in chemical analysis and limits our understanding of biological functions and regulation. A major way lipid isomers differ is by double-bond (db) position, and analyzing db-isomers is especially challenging for mass spectrometry imaging (MSI). Ozonolysis can be used to determine the db-position and has been paired with MSI before. However, previous techniques require increased analysis time to allow for gas-phase reactions within an ion trap or ion mobility cell or additional sample preparation time to allow for offline ozonation. Here, we introduce a new ozonolysis method inside the matrix-assisted laser desorption-ionization (MALDI) source, termed OzMALDI, that simultaneously produces ozonides from all unsaturated lipids. This allows us to determine db-positions without adding additional reaction time while maintaining the high mass resolution provided by Orbitrap MS. This new technique is especially effective at determining multiple db-positions in lipids containing polyunsaturated fatty acids, which is a limitation of many previous techniques. OzMALDI-MSI was applied to the analysis of rat brain and genetically engineered Camelina and soybean seed samples, demonstrating the utility of this method and uncovering novel biological information.

The Static Limit in MeV Secondary Ion Mass Spectrometry

Static limit in secondary ion mass spectrometry (SIMS) is defined as a threshold beam fluence, where secondary ions are desorbed only from the virgin surface. For the common SIMS technique, the static SIMS limit is set to approximately 1012 ions/cm2. Within the present paper, we investigated the applicability of the static limit for a mass spectrometry imaging technique known as MeV-SIMS, where the target surface is bombarded by primary ions within the MeV energy range domain. Here, desorption of secondary ions relies mainly on electronic excitations instead of collision cascades, as is the case for the lower energy primary ion beams. We have measured the disappearance cross sections of several organic targets for three different chlorine primary ion beam energies. Results show how the disappearance cross section depends on the primary ion beam energy. Generally, the static SIMS regime applies for a range of primary ion beam fluences similar to that for the common SIMS technique; however, the dependence of the disappearance cross section within the lower MeV energy domain (up to 10 MeV) exhibits somewhat unexpected characteristics. Further, we thoroughly investigated the dynamics of the secondary ion mass spectra after prolonged primary ion bombardment. Secondary ion yields of various peaks were monitored during analysis, and the corresponding data can be used to identify specific peaks and also to determine fragmentation patterns of analyzed organic molecules.

Exploring the protein signature of endometrial cancer: A comprehensive review through diverse samples and mass spectrometry-based proteomics

Endometrial cancer (EC) is increasing incidence among women, and it constitutes a health problem for women globally. An important aspect of EC management involves the use of protein biomarkers for early detection and monitoring. Protein biomarkers allow the identification of high-risk patients, the detection of the disease in its early stages, and the assessment of treatment responses. Mass spectrometry (MS)-based proteomics offers robust analytical techniques and a comprehensive understanding of proteins. Proteomics methods allow scientists to investigate both the quantities and functions of proteins. Thus, it provides valuable insights into how proteins are altered under different conditions. This review summarizes recent advances in MS-based proteomic biomarker discovery for EC, focusing on different sample types and MS-based techniques used in clinical studies. The review emphasized in detail the most commonly used key sources such as blood, urine, vaginal fluids and tissue. Furthermore, MS-based proteomics techniques such as untargeted, targeted, sequential window acquisition of all theoretical mass spectra (SWATH-MS) and mass spectrometry imaging used in the discovery and validation/validation phases were evaluated. This review highlights the importance of biomarker discovery and clinical translation to improve diagnostic and therapeutic outcomes in EC. It aims to provide a comprehensive overview of MS-based proteomics in EC, guiding future research and clinical applications.

Advancing atherosclerosis research: The Power of lipid imaging with MALDI-MSI

Atherosclerosis is a chronic inflammatory disease that is one of the leading causes of mortality globally. It is characterized by the formation of atheromatous plaques in the intima layer of larger arteries. The (fibro-)fatty plaques usually develop asymptomatically within the vessel until a serious event such as myocardial infarction or stroke occurs. Lipids play a pivotal role in disease progression, but while the causal role of cholesterol is beyond doubt, the distribution of numerous other lipids within the heterogeneous layers of atherosclerotic plaques, and their biological function remain unclear. A deeper understanding of the pathophysiological progression of the disease for prognostics, diagnostics, treatment, and prevention is of great need. Mass spectrometry imaging (MSI), in particular with matrix-assisted laser desorption/ionization (MALDI) offers an unprecedented untargeted characterization of the physiological microenvironment, unraveling the spatial distribution of numerous biochemical compounds. MALDI-MSI offers an advantageous balance of sample preparation, chemical sensitivity, and spatial resolution, and thus has been established as a key technology in modern biomedical analysis. This review focuses on the analysis of lipids in atherosclerotic lesions with MALDI-MSI, for which the past years showed major developments in the spatial characterization of lipids and their interaction within atherosclerotic plaques. We will cover main contributions with a focus on the recent decade, elaborate possibilities, limitations, main findings, and recent developments from sample handling to instrumentation, and estimate current challenges and potentials of MALDI-MSI with respect to a clinical application.

Branched-Chain Amino Acid Catabolism Promotes Ovarian Cancer Cell Proliferation via Phosphorylation of mTOR

SIGNIFICANCE

This study uncovers altered amino acid metabolism, specifically increased BCAA catabolism, at the interface of ovarian cancer cells and omental tissue in a coculture model of HGSOC secondary metastasis. Enhanced BCAA catabolism promotes cancer cell proliferation through mTOR signaling, presenting potential therapeutic value. These findings deepen our understanding of HGSOC pathogenesis and the metastatic tumor microenvironment, offering insights for developing new treatment strategies.

Novel Isotope-Coded Photochemical Derivatization Coupled with LC-MS and MS Imaging Platform Enables Sensitive Quantification and Accurate Localization of Amine Submetabolome in Pancreatic Disease

Alterations in amine metabolite levels are closely associated with the poor progression of pancreatic disease, including acute pancreatitis (AP) and pancreatic cancer (PC). However, effectively quantifying and visualizing these metabolites through mass spectrometry (MS) has proven to be challenging. Here, we have designed a novel and rapid strategy for analyzing the amine submetabolome within liquid chromatography-mass spectrometry (LC-MS) and air-flow-assisted desorption electrospray ionization mass spectrometry imaging (AFADESI-MSI) platforms by inducing a pair of isotope-labeling-based photochemical derivatization reagents. The simultaneous introduction of a 4-amino-1-methylpyridinium moiety renders a 160- to 1037-fold higher response in MS. Coupled with full MS-ddMS2 and precursor ion scan modes, this labeling strategy allows for straightforward detection of 423 peaks for indazolone derivatives and identification of 82 amine metabolites in biological samples. The semiquantitation of the 82 amines in plasma from AP patients and healthy controls resulted in the discovery of unreported aromatic amines and aminoaldehydes with significant changes in AP and employing ethanolamine for distinguishing the severities of AP in the early stage. In the MSI platform, the photochemical reagent can efficiently derivatize primary amine metabolites avoiding spatial deviation and significantly enhancing imaging sensitivity in rat brain and kidney. Further joint analysis of amine submetabolome in plasma and pancreas from PC patients by use of these two platforms allowed for identifying the significant metabolite, methylamine. These results together enhance the role of amine-driven biomarker discovery in the diagnosis of pancreatic disease and accelerate the application of on-tissue photochemical derivation in MSI.

Direct transfer of multicellular tumor spheroids grown in agarose microarrays for high-throughput mass spectrometry imaging analysis

Multicellular tumor spheroids (MCTSs) play an important role in biological studies and cancer research. There is an emerging research interest in molecular profiling and drug distribution of MCTSs by leveraging the superior sensitivity and molecular specificity of mass spectrometry imaging (MSI). Current methods for sample preparation of MCTSs can suffer from low throughput, as MCTSs are typically individually transferred from cell culture into an MSI embedding media and sectioned individually, or sometimes, a few spheroids are placed in a small block of embedding media in preparation for MSI. Here, we developed a method to minimize the sample preparation steps needed to create high-throughput MCTS frozen sections for MSI. Agarose-based microarrays created from Microtissues® molds were used during MCTS culturing, after which the entire MCTS agarose microarray was taken out of the cell culture well and then directly embedded in 5% gelatin, without the need for a transfer step for each individual MCTS into the embedding media. This method enables rapid profiling of up to 81 MCTSs for larger MCTSs (500-800 µm) or up to 256 MCTSs for smaller MCTSs (200-300 µm) in a single section, remarkably improving the throughput possible for MSI MCTS workflows. Notably, sectioning MCTSs together in the agarose microarray also improves MCTS visualization during sectioning, such that staining each MCTS section to ensure the presence of the MCTSs within the embedding media is not necessary during the sectioning process. The method described here provides a more direct, convenient strategy to achieve high-throughput sections. MSI MCTS sectioning throughput is an important advancement for both pharmaceutical testing of MCTS; the direct transfer 3D cell cultures grown within cell culture-compatible polymer scaffolding are also critical for expanding MSI for the characterization of microfluidic and complex in vitro models, where agarose is readily utilized as a non-adhesive 3D cell culture scaffold.

imzML Writer: An Easy-to-Use Python Pipeline for Conversion of Continuously Acquired Raw Mass Spectrometry Imaging Data to imzML Format

Mass spectrometry imaging (MSI) is a technique that uncovers the contextual distribution of biomolecules in tissue. This involves collecting large data sets with information-rich mass spectra in each pixel. To streamline image processing and interpretation, the MSI community has developed toolboxes for image preprocessing, segmentation, statistical analysis, and visualization. These generally require data to be input as imzML files, an Extensible Markup Language file with vocabulary for mass spectrometry and imaging-specific parameters. While commercial systems (e.g., MALDI) come with proprietary file converters, to our knowledge, no open-access user-friendly converters exist for continuously acquired imaging data (e.g., nano-DESI, DESI). Here, we present imzML Writer, an easy-to-use Python application with a graphical user interface to convert data from vendor format into pixel-aligned imzML files. We package this application with imzML Scout, allowing visualization of the resulting file(s) and batch export of ion images across a range of image and data formats (e.g., PNG, TIF, CSV). To demonstrate the utility of files generated by imzML Writer, we processed nano-DESI data with popular tools such as Cardinal MSI and METASPACE. Overall, this work provides a simple open-access tool for emerging MSI modality users to access advanced MSI processing tools reliant on imzML format. ImzML Writer is available as a distributable Python package via pip or as a standalone program for Mac and PC at https://github.com/VIU-Metabolomics/imzML_Writer.

Harnessing the Power of Metabolomics for Precision Oncology: Current Advances and Future Directions

Metabolic reprogramming is a hallmark of cancer, with cancer cells acquiring many unique metabolic traits to support malignant growth, and extensive intra- and inter-tumour metabolic heterogeneity. Understanding these metabolic characteristics presents opportunities in precision medicine for both diagnosis and therapy. However, despite its potential, metabolic phenotyping has lagged behind genetic, transcriptomic, and immunohistochemical profiling in clinical applications. This is partly due to the lack of a single experimental technique capable of profiling the entire metabolome, necessitating the use of multiple technologies and approaches to capture the full range of cancer metabolic plasticity. This review examines the repertoire of tools available for profiling cancer metabolism, demonstrating their applications in preclinical and clinical settings. It also presents case studies illustrating how metabolomic profiling has been integrated with other omics technologies to gain insights into tumour biology and guide treatment strategies. This information aims to assist researchers in selecting the most effective tools for their studies and highlights the importance of combining different metabolic profiling techniques to comprehensively understand tumour metabolism.

Multiplatform Lipid Analysis of the Brain of Aging Mice by Mass Spectrometry

Lipids are critical to brain structure and function, accounting for approximately 50% of its dry weight. However, the impact of aging on brain lipids remains poorly characterized. To address this, here we applied three complementary mass spectrometry techniques: multiple reaction monitoring (MRM) profiling, untargeted liquid chromatography tandem mass spectrometry (LC-MS/MS), and desorption electrospray ionization-MS imaging (DESI-MSI). We used brains from mice of three age groups: adult (3-4 months), middle-aged (10 months), and old (19-21 months). Phospholipids such as phosphatidylcholine, phosphatidylethanolamine, and phosphatidylglycerol were more abundant, while phosphatidylinositol and phosphatidylserine were reduced in old mice compared to adults or middle-aged mice. Key lipids such as polyunsaturated fatty acids, including DHA, AA, HexCer, SHexCer, and SM, were among the most abundant lipids in aged brains. DESI-MSI revealed spatial lipid distribution patterns consistent with findings from MRM profiling and LC-MS/MS. Integration of lipidomic data with the recently published proteomics data from the same tissues highlighted changes in proteins and phosphorylation levels of several proteins associated with Cer, HexCer, FA, PI, SM, and SHexCer metabolism, aligning with the multiplatform lipid surveillance. These findings shed insight into age-dependent brain lipid changes and their potential contribution to age-related cognitive decline.

From morphology to single-cell molecules: high-resolution 3D histology in biomedicine

High-resolution three-dimensional (3D) tissue analysis has emerged as a transformative innovation in the life sciences, providing detailed insights into the spatial organization and molecular composition of biological tissues. This review begins by tracing the historical milestones that have shaped the development of high-resolution 3D histology, highlighting key breakthroughs that have facilitated the advancement of current technologies. We then systematically categorize the various families of high-resolution 3D histology techniques, discussing their core principles, capabilities, and inherent limitations. These 3D histology techniques include microscopy imaging, tomographic approaches, single-cell and spatial omics, computational methods and 3D tissue reconstruction (e.g. 3D cultures and spheroids). Additionally, we explore a wide range of applications for single-cell 3D histology, demonstrating how single-cell and spatial technologies are being utilized in the fields such as oncology, cardiology, neuroscience, immunology, developmental biology and regenerative medicine. Despite the remarkable progress made in recent years, the field still faces significant challenges, including high barriers to entry, issues with data robustness, ambiguous best practices for experimental design, and a lack of standardization across methodologies. This review offers a thorough analysis of these challenges and presents recommendations to surmount them, with the overarching goal of nurturing ongoing innovation and broader integration of cellular 3D tissue analysis in both biology research and clinical practice.

On-Tissue Chemical Derivatization for Mass Spectrometry Imaging of Fatty Acids with Enhanced Detection Sensitivity

The dysregulation of fatty acid (FA) metabolism is linked to various brain diseases, including Alzheimer's disease (AD). Mass spectrometry imaging (MSI) allows for the visualization of FA distribution in brain tissues but is often limited by low detection sensitivity and high background interference. In this work, we introduce a novel on-tissue chemical derivatization method for FAs using Girard's Reagent T (GT) as a derivatization reagent combined with 2-chloro-1-methylpyridinium iodide (CMPI) as a coupling reagent and triethylamine (TEA) to provide a basic environment for the reaction. This method significantly enhances the detection sensitivity of FAs, achieving a 1000-fold improvement over traditional negative ion mode analysis. Our method enabled us to observe a notable depletion of oleic acid in the corpus callosum of AD mouse model brain tissue sections compared to wild-type control brain tissue sections. The reliability of our method was validated using LC-MS/MS, which confirmed the presence of eight distinct GT-labeled FAs across various tissue locations. This approach not only improves FA detection in brain tissues but also has the potential to provide a deeper understanding of FA dynamics associated with AD pathogenesis.

Three-dimensional mass spectrometry imaging (3D MSI): incorporating top-hat IR-MALDESI and automatic z-axis correction

Leveraging a depth profiling approach expands the chemical elucidation of mass spectrometry imaging techniques to another dimension. Three-dimensional MSI (3D MSI) reveals the distribution of analytes with greater anatomical detail to add another level of information in a biological study. Infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) has demonstrated utility for an ablation-based approach, enabling simplified sample preparation workflows and streamlined data processing pipelines compared to a serial-sectioning strategy. To improve 3D MSI on the IR-MALDESI platform, two technologies have been characterized in tandem for the intention of minimizing sampling bias: (1) a top-hat optical train and (2) a chromatic confocal probe (CA probe). While the modified optical train creates a square spot size to avoid a Gaussian ablation crater after the analysis of subsequent layers, the CA probe enables automatic z-axis correction (AzC) to maintain the laser's focus on the surface of the sample. The work herein demonstrates the integration and optimization of these technologies on mouse skin, motivated by the clear biological skin layers that result in differential lipid expression and subsequent detection. Results support that a laser energy of 1.3 mJ/burst with the top-hat optical train and a 120 µm step size in the X and Y dimensions presented a comparable depth resolution to previous studies at under 7 µm. Further, the optimized parameters were utilized on two biological replicates to evaluate method reproducibility where lipid annotations and their abundance were considered.

Photoionization of pyrenemethylamine-labeled oligosaccharides: a new MALDI-TOF precursor ion-type for efficient fragmentation

Oligosaccharides were covalently labeled with 1-pyrenemethylamine (1-PMA) in 15 min at 75 °C with high yield, separated by quantitative HPLC in less than 20 min, and characterized by off-line Matrix-Assisted Laser Desorption/Ionization (MALDI) Time-of-Flight (TOF) mass spectrometry (MS). A new MALDI mass spectral precursor ion for fragmentation studies was observed from 2,5-dihydroxybenzoic acid matrix (DHB, hydroquinone/benzoquinone redox system) through photo-induced reductive elimination. The resulting high-energy protonated glycosylamine provided excellent fragmentation efficiency (Y-, B-ions, and combination losses), with ions covering almost the entire structure of several oligosaccharides at the low picomol level. With the new method, glycans from commercially available standard glycoproteins and glycans from bioengineered β-lactoglobulin expressed in the bgs13 mutant of Pichia pastoris were analyzed.

Advanced multi-modal mass spectrometry imaging reveals functional differences of placental villous compartments at microscale resolution

The placenta is a complex and heterogeneous organ that links the mother and fetus, playing a crucial role in nourishing and protecting the fetus throughout pregnancy. Integrative spatial multi-omics approaches can provide a systems-level understanding of molecular changes underlying the mechanisms leading to the histological variations of the placenta during healthy pregnancy and pregnancy complications. Herein, we advance our metabolome-informed proteome imaging (MIPI) workflow to include lipidomic imaging, while also expanding the molecular coverage of metabolomic imaging by incorporating on-tissue chemical derivatization (OTCD). The improved MIPI workflow advances biomedical investigations by leveraging state-of-the-art molecular imaging technologies. Lipidome imaging identifies molecular differences between two morphologically distinct compartments of a placental villous functional unit, syncytiotrophoblast (STB) and villous core. Next, our advanced metabolome imaging maps villous functional units with enriched metabolomic activities related to steroid and lipid metabolism, outlining distinct molecular distributions across morphologically different villous compartments. Complementary proteome imaging on these villous functional units reveals a plethora of fatty acid- and steroid-related enzymes uniquely distributed in STB and villous core compartments. Integration across our advanced MIPI imaging modalities enables the reconstruction of active biological pathways of molecular synthesis and maternal-fetal signaling across morphologically distinct placental villous compartments with micrometer-scale resolution.

TEMI: Tissue Expansion Mass Spectrometry Imaging

The spatial distribution of diverse biomolecules in multicellular organisms is essential for their physiological functions. High-throughput in situ mapping of biomolecules is crucial for both basic and medical research, and requires high scanning speed, spatial resolution, and chemical sensitivity. Here, we developed a Tissue Expansion method compatible with matrix-assisted laser desorption/ionization Mass spectrometry Imaging (TEMI). TEMI reaches single-cell spatial resolution without sacrificing voxel throughput and enables the profiling of hundreds of biomolecules, including lipids, metabolites, peptides (proteins), and N-glycans. Using TEMI, we mapped the spatial distribution of biomolecules across various mammalian tissues and uncovered metabolic heterogeneity in tumors. TEMI can be easily adapted and broadly applied in biological and medical research, to advance spatial multi-omics profiling.

Synthetic Lipid Biology

Cells contain thousands of different lipids. Their rapid and redundant metabolism, dynamic movement, and many interactions with other biomolecules have justly earned lipids a reputation as a vexing class of molecules to understand. Further, as the cell's hydrophobic metabolites, lipids assemble into supramolecular structures─most commonly bilayers, or membranes─from which they carry out myriad biological functions. Motivated by this daunting complexity, researchers across disciplines are bringing order to the seeming chaos of biological lipids and membranes. Here, we formalize these efforts as "synthetic lipid biology". Inspired by the idea, central to synthetic biology, that our abilities to understand and build biological systems are intimately connected, we organize studies and approaches across numerous fields to create, manipulate, and analyze lipids and biomembranes. These include construction of lipids and membranes from scratch using chemical and chemoenzymatic synthesis, editing of pre-existing membranes using optogenetics and protein engineering, detection of lipid metabolism and transport using bioorthogonal chemistry, and probing of lipid-protein interactions and membrane biophysical properties. What emerges is a portrait of an incipient field where chemists, biologists, physicists, and engineers work together in proximity─like lipids themselves─to build a clearer description of the properties, behaviors, and functions of lipids and membranes.

Molecular Profiling of Glioblastoma Patient-Derived Single Cells Using Combined MALDI-MSI and MALDI-IHC

In recent years, mass spectrometry-based imaging techniques have improved at unprecedented speeds, particularly in spatial resolution, and matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) experiments can now routinely image molecular profiles of single cells in an untargeted fashion. With the introduction of MALDI-immunohistochemistry (IHC), multiplexed visualization of targeted proteins in their native tissue location has become accessible and joins the suite of multimodal imaging techniques that help unravel molecular complexities. However, MALDI-IHC has not been validated for use with cell cultures at single-cell level. Here, we introduce a workflow for combining MALDI-MSI and MALDI-IHC on single, isolated cells. Patient-derived cells from glioblastoma tumor samples were imaged, first with high-resolution MSI to obtain a lipid profile, followed by MALDI-IHC highlighting cell-specific protein markers. The multimodal imaging revealed cell type specific lipid profiles when comparing glioblastoma cells and neuronal cells. Furthermore, the initial MSI measurement and its sample preparation showed no significant differences in the subsequent MALDI-IHC ion intensities. Finally, an automated recognition model was created based on the MALDI-MSI data and was able to accurately classify cells into their respective cell type in agreement with the MALDI-IHC markers, with triglycerides, phosphatidylcholines, and sphingomyelins being the most important classifiers. These results show how MALDI-IHC can provide additional valuable molecular information on single-cell measurements, even after an initial MSI measurement without reduced efficacy. Investigation of heterogeneous single-cell samples has the potential of giving a unique insight into the dynamics of how cell-to-cell interaction drives intratumor heterogeneity, thus highlighting the perspective of this work.

A Low-Cost, High-Resolution Thermoplastic Microfluidic Probe for Mass Spectrometry Imaging of Biological Tissue Samples

Mass spectrometry imaging (MSI) using nanospray desorption electrospray ionization (nano-DESI) has been extensively used for label-free mapping of hundreds of molecules in biological samples with minimal sample pretreatment. While both nano-DESI probes made of two fused silica capillaries and glass microfluidic probes (MFP) have been developed for imaging biological tissues with high spatial resolution, MFPs significantly enhance the robustness and throughput of nano-DESI MSI experiments. Despite their advantages, the fabrication of glass microfluidic devices is costly and requires specialized equipment or cleanroom facilities. Meanwhile, plastic microfluidic devices often suffer from limited solvent compatibility and low fabrication precision, restricting their achievable spatial resolution. To overcome these limitations, we have developed a low-cost microfluidic probe made from cyclic olefin copolymer (COC), a widely used thermoplastic material known for its excellent chemical resistance. The probe is fabricated using wire imprinting and thermal bonding in a standard laboratory setting. We estimate the achievable spatial resolution of the COC-MFP of 5-7 μm and demonstrate its robustness by imaging a large (20.0 mm × 9.5 mm) human kidney tissue section with high sensitivity. This affordable thermoplastic probe makes high spatial resolution nano-DESI MSI more accessible, broadening its applications in the scientific community.

Enabling simultaneous photoluminescence spectroscopy and X-ray footprinting mass spectrometry to study protein conformation and interactions

X-ray footprinting mass spectrometry (XFMS) is a structural biology method that uses broadband X-rays for in situ hydroxyl radical labeling to map protein interactions and conformation in solution. However, while XFMS alone provides important structural information on biomolecules, as we move into the era of the interactome, hybrid methods are becoming increasingly necessary to gain a comprehensive understanding of protein complexes and interactions. Toward this end, we report the development of the first synergetic application of inline and real-time fluorescent spectroscopy at the Advanced Light Source's XFMS facility to study local protein interactions and global conformational changes simultaneously. To facilitate general use, we designed a flexible and optimum system for producing high-quality spectroscopy-XFMS hybrid data, with rapid interchangeable liquid jet or capillary sample delivery for multimodal inline spectroscopy, and several choices for optofluidic environments. To validate the hybrid system, we used the covalently interacting SpyCatcher-SpyTag split protein system. We show that our hybrid system can be used to detect the interaction of SpyTag and SpyCatcher via fluorescence resonance energy transfer (FRET), while elucidating key structural features throughout the complex at the residue level via XFMS. Our results highlight the usefulness of hybrid method in providing binding and structural details to precisely engineer protein interactions.

Wash-free fluorescent tools based on organic molecules: Design principles and biomedical applications

Fluorescence-assisted tools based on organic molecules have been extensively applied to interrogate complex biological processes in a non-invasive manner with good sensitivity, high resolution, and rich contrast. However, the signal-to-noise ratio is an essential factor to be reckoned with during collecting images for high fidelity. In view of this, the wash-free strategy is proven as a promising and important approach to improve the signal-to-noise ratio, thus a thorough introduction is presented in the current review about wash-free fluorescent tools based on organic molecules. Firstly, generalization and summarization of the principles for designing wash-free molecular fluorescent tools (WFTs) are made. Subsequently, to make the thought of molecule design more legible, a wash-free strategy is highlighted in recent studies from four diverse but tightly binding aspects: (1) special chemical structures, (2) molecular interactions, (3) bio-orthogonal reactions, (4) abiotic reactions. Meanwhile, biomedical applications including bioimaging, biodetection, and therapy, are ready to be accompanied by. Finally, the prospects for WFTs are elaborated and discussed. This review is a timely conclusion about wash-free strategy in the fluorescence-guided biomedical applications, which may bring WFTs to the forefront and accelerate their extensive applications in biology and medicine.

Bacterial metabolomics: current applications for human welfare and future aspects

An imbalanced microbiome is linked to several diseases, such as cancer, inflammatory bowel disease, obesity, and even neurological disorders. Bacteria and their by-products are used for various industrial and clinical purposes. The metabolites under discussion were chosen based on their biological impacts on host and gut microbiota interactions as established by metabolome research. The separation of bacterial metabolites by using statistics and machine learning analysis creates new opportunities for applications of bacteria and their metabolites in the environmental and medical sciences. Thus, the metabolite production strategies, methodologies, and importance of bacterial metabolites for human well-being are discussed in this review.

Exploring omics signature in the cardiovascular response to semaglutide: Mechanistic insights and clinical implications

BACKGROUND

Semaglutide, a glucagon-like peptide-1 (GLP-1) receptor agonist, is a widely used drug for the treatment of type 2 diabetes that offers significant cardiovascular benefits.

RESULTS

This review systematically examines the proteomic and metabolomic indicators associated with the cardiovascular effects of semaglutide. A comprehensive literature search was conducted to identify relevant studies. The review utilizes advanced analytical technologies such as mass spectrometry and nuclear magnetic resonance (NMR) to investigate the molecular mechanisms underlying the effects of semaglutide on insulin secretion, weight control, anti-inflammatory activities and lipid metabolism. These "omics" approaches offer critical insights into metabolic changes associated with cardiovascular health. However, challenges remain such as individual variability in expression, the need for comprehensive validation and the integration of these data with clinical parameters. These issues need to be addressed through further research to refine these indicators and increase their clinical utility.

CONCLUSION

Future integration of proteomic and metabolomic data with artificial intelligence (AI) promises to improve prediction and monitoring of cardiovascular outcomes and may enable more accurate and effective management of cardiovascular health in patients with type 2 diabetes. This review highlights the transformative potential of integrating proteomics, metabolomics and AI to advance cardiovascular medicine and improve patient outcomes.

From Complexity to Clarity: Expanding Metabolome Coverage With Innovative Analytical Strategies

Metabolomics, a powerful discipline within systems biology, aims at comprehensive profiling of small molecules in biological samples. The challenges of biological sample complexity are addressed through innovative sample preparation methods, including solid-phase extraction and microextraction techniques, enhancing the detection and quantification of low-abundance metabolites. Advances in chromatographic separation, particularly liquid chromatography (LC) and gas chromatography (GC), coupled with high-resolution (HR) mass spectrometry (MS), have significantly improved the sensitivity, selectivity, and throughput of metabolomic studies. Cutting-edge techniques, such as ion-mobility mass spectrometry (IM-MS) and tandem MS (MS/MS), further expand the capacity for comprehensive metabolite profiling. These advanced analytical platforms each offer unique advantages for metabolomics, with continued technological improvements driving deeper insights into metabolic pathways and biomarker discovery. By providing a detailed overview of current trends and techniques, this review aims to offer valuable insights into the future of metabolomics in human health research and its translational potential in clinical settings. Toward the end, this review also highlights the biomedical applications of metabolomics, emphasizing its role in biomarker discovery, disease diagnostics, personalized medicine, and drug development.

Pooled Nanoparticle Screening Using a Chemical Barcoding Approach

We report the development of a small molecule-based barcoding platform for pooled screening of nanoparticle delivery. Using aryl halide-based tags (halocodes), we achieve high-sensitivity detection via gas chromatography coupled with mass spectrometry or electron capture. This enables barcoding and tracking of nanoparticles with minimal halocode concentrations and without altering their physicochemical properties. To demonstrate the utility of our platform for pooled screening, we synthesized a halocoded library of polylactide-co-glycolide (PLGA) nanoparticles and quantified uptake in ovarian cancer cells in a pooled manner. Our findings correlate with conventional fluorescence-based assays. Additionally, we demonstrate the potential of halocodes for spatial mapping of nanoparticles using mass spectrometry imaging (MSI). Halocoding presents an accessible and modular nanoparticle screening platform capable of quantifying delivery of pooled nanocarrier libraries in a range of biological settings.

Comprehensive Approach for Sequential MALDI-MSI Analysis of Lipids, N-Glycans, and Peptides in Fresh-Frozen Rodent Brain Tissues

Multiomics analysis of single tissue sections using matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) provides comprehensive molecular insights. However, optimizing tissue sample preparation for MALDI-MSI to achieve high sensitivity and reproducibility for various biomolecules, such as lipids, N-glycans, and tryptic peptides, presents a significant challenge. This study introduces a robust and reproducible protocol for the comprehensive sequential analysis of the latter molecules using MALDI-MSI in fresh-frozen rodent brain tissue samples. The optimization process involved testing multiple organic solvents, which identified serial washing in ice-cold methanol, followed by chloroform as optimal for N-glycan analysis. Integrating this optimized protocol into MALDI-MSI workflows enabled comprehensive sequential analysis of lipids (in dual polarity mode), N-glycans, and tryptic peptides within the same tissue sections, enhancing both the efficiency and reliability. Validation across diverse rodent brain tissue samples confirmed the protocol's robustness and versatility. The optimized methodology was subsequently applied to a transgenic Alzheimer's disease (AD) mouse model (tgArcSwe) as a proof of concept. In the AD model, significant molecular alterations were observed in various sphingolipid and glycerophospholipid species, as well as in biantennary and GlcNAc-bisecting N-glycans, particularly in the cerebral cortex. These region-specific alterations are potentially associated with amyloid-beta (Aβ) plaque accumulation, which may contribute to cognitive and memory impairments. The proposed standardized methodology represents a significant advancement in neurobiological research, providing valuable insights into disease mechanisms and laying the foundation for potential preclinical applications. It could aid the development of diagnostic biomarkers and targeted therapies for AD and other neurodegenerative diseases, such as Parkinson's disease.

Promising mass spectrometry imaging: exploring microscale insights in food

This review focused on mass spectrometry imaging (MSI), a powerful tool in food analysis, covering its ion source schemes and procedures and their applications in food quality, safety, and nutrition to provide detailed insights into these aspects. The review presented a detailed introduction to both commonly used and emerging ionization sources, including nanoparticle laser desorption/ionization (NPs-LDI), air flow-assisted ionization (AFAI), desorption ionization with through-hole alumina membrane (DIUTHAME), plasma-assisted laser desorption ionization (PALDI), and low-temperature plasma (LTP). In the MSI process, particular emphasis was placed on quantitative MSI (QMSI) and super-resolution algorithms. These two aspects synergistically enhanced MSI's analytical capabilities: QMSI enabled accurate relative and absolute quantification, providing reliable data for composition analysis, while super-resolution algorithms improved molecular spatial imaging resolution, facilitating biomarker and trace substance detection. MSI outperformed conventional methods in comprehensively exploring food functional factors, biomarker discovery, and monitoring processing/storage effects by discerning molecular species and their spatial distributions. However, challenges such as immature techniques, complex data processing, non-standardized instruments, and high costs existed. Future trends in instrument enhancement, multispectral integration, and data analysis improvement were expected to deepen our understanding of food chemistry and safety, highlighting MSI's revolutionary potential in food analysis and research.

Metabolic Atlas of Human Eyelid Infiltrative Basal Cell Carcinoma

Purpose

Eyelid infiltrative basal cell carcinoma (iBCC) is the most common malignant tumor affecting the ocular adnexa, but studies on metabolic changes within its microenvironment and heterogeneity at the tumor invasive area are limited. This study aims to analyze metabolic differences among iBCC cell types using single-cell and spatial metabolomics analysis and to examine metabolic environment at the tumor invasive area.

Methods

Single-cell transcriptomic data of human basal cell carcinoma (BCC) were clustered and visualized using Uniform Manifold Approximation and Projection. Metabolic reprogramming was analyzed with single-cell flux estimation analysis. Spatial metabolomics data were obtained with the Timstof Flex MALDI 2 system, and Bruker software was used for region selection.

Results

Eight cell types were identified within the iBCC microenvironment. Differences between inflammatory cancer-associated fibroblasts and myofibroblastic cancer-associated fibroblasts were analyzed. Metabolic flux analysis showed increased glycolysis, glutamine, heme, and glutathione fluxes in the iBCC microenvironment. Spatial metabolomics revealed high levels of taurine, deoxy-GMP, O-phosphoethanolamine, and pyrithione. Both tumor and invasive regions had significant upregulation of fatty acid pathways, with marked increases in oleic and arachidonic acids at the invasive area. Specific upregulation of UDP-glucuronic acid and high UDP-glucose 6-dehydrogenase (UGDH) expression in the tumor region suggest UXS1 as a potential therapeutic target for iBCC.

Conclusions

This study establishes a metabolic microenvironment atlas of iBCC, revealing significant metabolic differences and the dominance of lipid and lysosome metabolism. Potential metabolic markers and characteristic substances in the invasive area offer new insights for immunotherapy and the exploration of BCC's metabolic mechanisms.

Spatial metabolomics method to reveal the differences in chemical composition of raw and honey-fried Stemona tuberosa Lour. by using UPLC-Orbitrap Fusion MS and desorption electrospray ionization mass spectrometry imaging

INTRODUCTION

Stemona tuberosa Lour. (ST) is a significant traditional Chinese medicine (TCM) renowned for its antitussive and insecticidal properties. ST is commonly subjected to processing in clinical practice before being utilized as a medicinal substance. Currently, the customary technique for processing ST is honey-fried. Nevertheless, the specific variations in chemical constituents of ST before and after honey-fried remain unclear.

OBJECTIVE

This work aimed to analyze the variations in chemical constituents of ST before and after honey-fried and to study the distribution of differential markers in the roots.

METHODS

UPLC-Orbitrap Fusion MS combined with molecular network analysis was used to analyze the metabolome of ST and honey-fried ST (HST) and to screen the differential metabolites by multivariate statistical analysis. Spatial metabolomics was applied to study the distribution of differential metabolites by desorption electrospray ionization mass spectrometry imaging (DESI-MSI).

RESULTS

The ST and HST exhibited notable disparities, with 56 and 61 chemical constituents found from each, respectively. After processing, the types of alkaloids decreased, and 12 differential metabolites were screened from the common compounds. The notable component variations were epibisdehydro-tuberostemonine J, neostenine, tuberostemonine, croomine, neotuberostemonine, and so forth. MSI visualized the spatial distribution of differential metabolites.

CONCLUSIONS

Our research provided a rapid and effective visualization method for the identification and spatial distribution of metabolites in ST. Compared with the traditional method, this method offered more convincing data supporting the processing mechanism investigations of Stemona tuberosa from a macroscopic perspective.

Exploring natural product biosynthesis in plants with mass spectrometry imaging

The biosynthesis of natural products (NPs) is a complex dynamic spatial and temporal process that requires the collaboration of multiple disciplines to explore the underlying mechanisms. Mass spectrometry imaging (MSI) is a powerful technique for studying NPs due to its high molecular coverage and sensitivity without the need for labeling. To date, many analysts still use MSI primarily for visualizing the distribution of NPs in heterogeneous tissues, although studies have proved that it can provide crucial insights into the specialized spatial metabolic process of NPs. In this review we strive to bring awareness of the importance of MSI, and we advocate further exploitation of the spatial information obtained from MSI to establish metabolite-gene expression relationships.

Navigating the complexity of lipid oxidation and antioxidation: A review of evaluation methods and emerging approaches

Lipid oxidative degradation contributes to the deterioration of food quality and poses potential health risks. A promising approach to counteract this is the use of plant-based antioxidants. However, accurately evaluating the antioxidant capacity and effectiveness of these compounds remains a challenge. While many rapid in vitro tests are available, they must be categorized according to their specific responses to avoid overinterpreting results. This review opens with an overview of current knowledge on lipid autoxidation and recent findings that highlight the challenges in measuring antioxidant capacity. We then examine various methods, addressing their limitations in accurately anticipating outcomes in complex compartmentalized lipid systems. The aim is to clarify the gap between predictions and real-world efficacy in final products. Additionally, the review compares the strengths and weaknesses of methods used to evaluate antioxidant capacity and assess oxidation degrees in complex environments, such as those found in food and cosmetics. Finally, new analytical techniques for multiproduct detection are introduced, paving the way for a more 'omic' and spatiotemporally defined approach.

Mass spectrometry imaging for unearthing and validating quality markers in traditional Chinese medicines

Quality marker (Q-Marker) is an innovative concept and model for quality control of Traditional Chinese medicines (TCMs), which will navigate the new direction of quality development of TCMs. Yet, how to characterize the overall quality attributes of TCMs and their biological effects is still debating. In view of this key scientific issue, this paper proposes a research method based on mass spectrometry imaging (MSI) technology for the discovery and confirmation of TCMs Q-Marker. MSI is powerful in investigating the spatial distribution of molecules in a variety of samples, and visualizing the information obtained from MS. On this basis, combine with the five principles of TCMs Q-Marker validation, i.e., specificity, transmission and traceability, testability, prescription compatibility, and validity, were applied to confirm the finalized Q-Marker. It will lead the new direction of quality development of TCMs.