Laser Desorption Ionization Mass Spectrometry Research Articles

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

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

Lipidomics Reveals Myocardial Lipid Composition in a Murine Model of Insulin Resistance Induced by a High-Fat Diet.

Ectopic fat accumulation in non-adipose tissues is closely related to diabetes-related myocardial dysfunction. Nevertheless, the complete picture of the lipid metabolites involved in the metabolic-related myocardial alterations is not fully characterized. The aim of this study was to characterize the specific lipid profile in hearts in an animal model of obesity/insulin resistance induced by a high-fat diet (HFD). The cardiac lipidome profiles were assessed via liquid chromatography-mass spectrometry (LC-MS)/MS-MS and laser desorption/ionization-mass spectrometry (LDI-MS) tissue imaging in hearts from C57BL/6J mice fed with an HFD or standard-diet (STD) for 12 weeks. Targeted lipidome analysis identified a total of 63 lipids (i.e., 48 triacylglycerols (TG), 5 diacylglycerols (DG), 1 sphingomyelin (SM), 3 phosphatidylcholines (PC), 1 DihydroPC, and 5 carnitines) modified in hearts from HFD-fed mice compared to animals fed with STD. Whereas most of the TG were up-regulated in hearts from animals fed with an HFD, most of the carnitines were down-regulated, thereby suggesting a reduction in the mitochondrial β-oxidation. Roughly 30% of the identified metabolites were oxidated, pointing to an increase in lipid peroxidation. Cardiac lipidome was associated with a specific biochemical profile and a specific liver TG pattern. Overall, our study reveals a specific cardiac lipid fingerprint associated with metabolic alterations induced by HFD.

Large-scale atomistic model construction of subbituminous and bituminous coals for solvent extraction simulations with reactive molecular dynamics

Large-scale atomistic models for complex polycyclic aromatic hydrocarbon systems help understand the chemical properties and behaviors of complex feedstocks such as coal or petroleum. However, the development and utilization of large-scale models remain limited due to the difficulty in achieving the varied structural characteristics necessary to capture stochastic nature of these feedstocks. We demonstrate a systematic workflow to construct stochastic molecular systems from a broad analytical suite: high-resolution transmission electron microscopy (HRTEM), carbon-13 nuclear magnetic resonance spectroscopy (13C NMR), laser desorption ionization mass spectroscopy (LDI-MS), and elemental analysis. We present a model construction and analysis utility of a new Python-based module. We selected one subbituminous and three high-volatile bituminous coals to construct large-scale models (∼40,000 atoms). The constructed models were utilized to examine the affinity for solvent extraction (naphthalene or tetralin) and the effect of structural properties (e.g., aromatic cluster size, functional groups, and cross-linking) in reactive molecular dynamics simulations. Complex chemical reactions were monitored with bond order transitions, intermediates formation, and mass distributions. Reactive molecular dynamics simulations suggest a plausible chemical extraction process and products for the complex fossil feedstocks. The results indicated that radical formations with bond breaking of bridging oxygens and carbons were required at high temperatures to facilitate hydrogeneration and extraction of gas molecules from radical-free molecules. We observed that aliphatic chains of tetralin were easily decomposed and combined with radicals to form small size of molecules with aryl bonding, mainly increasing molecules in the 500–1000 Da, while naphthalene had little impact on chemical extraction process.

Characterization of Regolith And Trace Economic Resources (CRATER): An Orbitrap-based laser desorption mass spectrometry instrument for in situ exploration of the Moon.

Characterization of Regolith And Trace Economic Resources (CRATER), an Orbitrap™-based laser desorption mass spectrometry instrument designed to conduct high-precision, spatially resolved analyses of planetary materials, is capable of answering outstanding science questions about the Moon's formation and the subsequent processes that have modified its (sub)surface. Here, we describe the baseline design of the CRATER flight model, which requires <20 000 cm3 volume, <10kg mass, and <60 W peak power. The analytical capabilities and performance metrics of a prototype that meets the full functionality of the flight model are demonstrated. The instrument comprises a high-power, solid-state, pulsed ultraviolet (213 nm) laser source to ablate the surface of the lunar sample, a custom ion optical interface to accelerate and collimate the ions produced at the ablation site, and an Orbitrap mass analyzer capable of discriminating competing isobars via ultrahigh mass resolution and high mass accuracy. The CRATER instrument can measure elemental and isotopic abundances and characterize the organic content of lunar surface samples, as well as identify economically valuable resources for future exploration. An engineering test unit of the flight model is currently in development to serve as a pathfinder for near-term mission opportunities.

Metabolomics unveils the exacerbating role of arachidonic acid metabolism in atherosclerosis.

Atherosclerosis is a complex vascular disorder characterized by the deposition of lipids, inflammatory cascades, and plaque formation in arterial walls. A thorough understanding of its causes and progression is necessary to develop effective diagnostic and therapeutic strategies. Recent breakthroughs in metabolomics have provided valuable insights into the molecular mechanisms and genetic factors involved in atherosclerosis, leading to innovative approaches for preventing and treating the disease. In our study, we analyzed clinical serum samples from both atherosclerosis patients and animal models using laser desorption ionization mass spectrometry. By employing methods such as orthogonal partial least-squares discrimination analysis (OPLS-DA), heatmaps, and volcano plots, we can accurately classify atherosclerosis (AUC = 0.892) and identify key molecules associated with the disease. Specifically, we observed elevated levels of arachidonic acid and its metabolite, leukotriene B4, in atherosclerosis. By inhibiting arachidonic acid and monitoring its downstream metabolites, we discovered the crucial role of this metabolic pathway in regulating atherosclerosis. Metabolomic research provides detailed insights into the metabolic networks involved in atherosclerosis development and reveals the close connection between abnormal metabolism and the disease. These studies offer new possibilities for precise diagnosis, treatment, and monitoring of disease progression, as well as evaluating the effectiveness of therapeutic interventions.

Cutinase Immobilization on a Supramolecular Cage Protein Scaffold

Background: Self-assembly of preformed nanoparticles into larger and more complex materials, termed nanoarchitectonics, is an area of great interest as the resulting higher-order architectures can exhibit advanced supramolecular properties important in sensor design, catalysis, and ferromagnetic properties. Objective: The aim of the current investigation is to explore the application of self-assembling protein networks to serve as molecular scaffolds for immobilization of enzyme catalysts. The use of 12 nm ferritin cage proteins to serve as components of these scaffolds would expand the application of these types of multifunctional proteins to the fabrication of advanced biomaterials. Method: Humicola insolens cutinase was immobilized on a supramolecular protein scaffold using bioconjugation to biotinylate the enzyme of interest. The protein-based scaffold consisted of a ferritin- biotin-avidin system, and the interaction of biotin and avidin was used to suspend the enzyme molecules onto this network. Matrix-assisted laser desorption mass spectrometry, scanning electron microscopy, and energy dispersive X-ray spectroscopy were employed to analyze the supramolecular cage protein scaffold at various stages of fabrication. Results: The activities of these scaffold-bound enzymes towards chromogenic esters and polyethylene terephthalate (PET) were analyzed and found to remain active towards both substrates following biotinylation and immobilization. Conclusion: Biotinylated Humicola insolens cutinase enzymes can be immobilized on nanodimensional protein networks composed of avidin and biotinylated horse spleen ferritin and exhibit catalytic activity toward a small substrate, p-nitrophenylbutyrate, as well as an industrial plastic. Selfassembling protein networks may provide new approaches for biomolecular immobilization.

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

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

Early Diagnosis and Prognosis Prediction of Pancreatic Cancer Using Engineered Hybrid Core-Shells in Laser Desorption/Ionization Mass Spectrometry.

Effective detection of bio-molecules relies on the precise design and preparation of materials, particularly in laser desorption/ionization mass spectrometry (LDI-MS). Despite significant advancements in substrate materials, the performance of single-structured substrates remains suboptimal for LDI-MS analysis of complex systems. Herein, designer Au@SiO2@ZrO2 core-shell substrates are developed for LDI-MS-based early diagnosis and prognosis of pancreatic cancer (PC). Through controlling Au core size and ZrO2 shell crystallization, signal amplification of metabolites up to 3 orders is not only achieved, but also the synergistic mechanism of the LDI process is revealed. The optimized Au@SiO2@ZrO2 enables a direct record of serum metabolic fingerprints (SMFs) by LDI-MS. Subsequently, SMFs are employed to distinguish early PC (stage I/II) from controls, with an accuracy of 92%. Moreover, a prognostic prediction scoring system is established with enhanced efficacy in predicting PC survival compared to CA19-9 (p < 0.05). This work contributes to material-based cancer diagnosis and prognosis.

Metabolomic profiling of human bladder tissue extracts.

Bladder cancer is a common malignancy affecting the urinary tract and effective biomarkers and for which monitoring therapeutic interventions have yet to be identified. Major aim of this work was to perform metabolomic profiling of human bladder cancer and adjacent normal tissue and to evaluate cancer biomarkers. This study utilized nuclear magnetic resonance (NMR) and high-resolution nanoparticle-based laser desorption/ionization mass spectrometry (LDI-MS) methods to investigate polar metabolite profiles in tissue samples from 99 bladder cancer patients. Through NMR spectroscopy, six tissue metabolites were identified and quantified as potential indicators of bladder cancer, while LDI-MS allowed detection of 34 compounds which distinguished cancer tissue samples from adjacent normal tissue. Thirteen characteristic tissue metabolites were also found to differentiate bladder cancer tumor grades and thirteen metabolites were correlated with tumor stages. Receiver-operating characteristics analysis showed high predictive power for all three types of metabolomics data, with area under the curve (AUC) values greater than 0.853. To date, this is the first study in which bladder human normal tissues adjacent to cancerous tissues are analyzed using both NMR and MS method. These findings suggest that the metabolite markers identified in this study may be useful for the detection and monitoring of bladder cancer stages and grades.

Self-Assembly of a Novel Pentapeptide into Hydrogelated Dendritic Architecture: Synthesis, Properties, Molecular Docking and Prospective Applications.

Currently, ultrashort oligopeptides consisting of fewer than eight amino acids represent a cutting-edge frontier in materials science, particularly in the realm of hydrogel formation. By employing solid-phase synthesis with the Fmoc/tBu approach, a novel pentapeptide, FEYNF-NH2, was designed, inspired by a previously studied sequence chosen from hen egg-white lysozyme (FESNF-NH2). Qualitative peptide analysis was based on reverse-phase high performance liquid chromatography (RP-HPLC), while further purification was accomplished using solid-phase extraction (SPE). Exact molecular ion confirmation was achieved by matrix-assisted laser desorption-ionization mass spectrometry (MALDI-ToF MS) using two different matrices (HCCA and DHB). Additionally, the molecular ion of interest was subjected to tandem mass spectrometry (MS/MS) employing collision-induced dissociation (CID) to confirm the synthesized peptide structure. A combination of research techniques, including Fourier-transform infrared spectroscopy (FTIR), fluorescence analysis, transmission electron microscopy, polarized light microscopy, and Congo red staining assay, were carefully employed to glean valuable insights into the self-assembly phenomena and gelation process of the modified FEYNF-NH2 peptide. Furthermore, molecular docking simulations were conducted to deepen our understanding of the mechanisms underlying the pentapeptide's supramolecular assembly formation and intermolecular interactions. Our study provides potential insights into amyloid research and proposes a novel peptide for advancements in materials science. In this regard, in silico studies were performed to explore the FEYNF peptide's ability to form polyplexes.

High-Throughput Miniaturized Synthesis of PROTAC-Like Molecules.

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

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

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

Utilizing multimodal mass spectrometry imaging for profiling immune cell composition and N-glycosylation across colorectal carcinoma disease progression.

Colorectal cancer (CRC) stands as a leading cause of death worldwide, often arising from specific genetic mutations, progressing from pre-cancerous adenomas to adenocarcinomas. Early detection through regular screening can result in a 90% 5-year survival rate for patients. However, unfortunately, only a fraction of CRC cases are identified at pre-invasive stages, allowing progression to occur silently over 10-15years. The intricate interplay between the immune system and tumor cells within the tumor microenvironment plays a pivotal role in the progression of CRC. Immune cell clusters can either inhibit or facilitate tumor initiation, growth, and metastasis. To gain a better understanding of this relationship, we conducted N-glycomic profiling using matrix-assisted laser desorption-ionization mass spectrometry imaging (MALDI-MSI). We detected nearly 100 N-glycan species across all samples, revealing a shift in N-glycome profiles from normal to cancerous tissues, marked by a decrease in high mannose N-glycans. Further analysis of precancerous to invasive carcinomas showed an increase in pauci-mannose biantennary, and tetraantennary N-glycans with disease progression. Moreover, a distinct stratification in the N-glycome profile was observed between non-mucinous and mucinous CRC tissues, driven by pauci-mannose, high mannose, and bisecting N-glycans. Notably, we identified immune clusters of CD20+ B cells and CD3/CD44+ T cells distinctive and predictive with signature profiles of bisecting and branched N-glycans. These spatial N-glycan profiles offer potential biomarkers and therapeutic targets throughout the progression of CRC.

Self-Assembled Hyperbranched Gold Nanoarrays Decode Serum United Urine Metabolic Fingerprints for Kidney Tumor Diagnosis.

Serum united urine metabolic analysis comprehensively reveals the disease status for kidney diseases in particular. Thus, the precise and convenient acquisition of metabolic molecular information from united biofluids is vitally important for clinical disease diagnosis and biomarker discovery. Laser desorption/ionization mass spectrometry (LDI-MS) presents various advantages in metabolic analysis; however, there remain challenges in ionization efficiency and MS signal reproducibility. Herein, we constructed a self-assembled hyperbranched black gold nanoarray (HyBrAuNA) assisted LDI-MS platform to profile serum united urine metabolic fingerprints (S-UMFs) for diagnosis of early stage renal cell carcinoma (RCC). The closely packed HyBrAuNA afforded strong electromagnetic field enhancement and high photothermal conversion efficacy, enabling effective ionization of low abundant metabolites for S-UMF collection. With a uniform nanoarray, the platform presented excellent reproducibility to ensure the accuracy of S-UMFs obtained in seconds. When it was combined with automated machine learning analysis of S-UMFs, early stage RCC patients were discriminated from the healthy controls with an area under the curve (AUC) > 0.99. Furthermore, we screened out a panel of 9 metabolites (4 from serum and 5 from urine) and related pathways toward early stage kidney tumor. In view of its high-throughput, fast analytical speed, and low sample consumption, our platform possesses potential in metabolic profiling of united biofluids for disease diagnosis and pathogenic mechanism exploration.

Organic metal chalcogenide-assisted metabolic molecular diagnosis of central precocious puberty.

Metabolic analysis in biofluids based on laser desorption/ionization mass spectrometry (LDI-MS), featuring rapidity, simplicity, small sample volume and high throughput, is expected to be a powerful diagnostic tool. Nevertheless, the signals of most metabolic biomarkers obtained by matrix-assisted LDI-MS are too limited to achieve a highly accurate diagnosis due to serious background interference. To address this issue, nanomaterials have been frequently adopted in LDI-MS as substrates. However, the "trial and error" approach still dominates the development of new substrates. Therefore, rational design of novel LDI-MS substrates showing high desorption/ionization efficiency and no background interference is extremely desired. Herein, four few-layered organic metal chalcogenides (OMCs) were precisely designed and for the first time investigated as substrates in LDI-MS, which allowed a favorable internal energy and charge transfer by changing the functional groups of organic ligands and metal nodes. As a result, the optimized OMC-assisted platform satisfyingly enhanced the mass signal by ≈10 000 fold in detecting typical metabolites and successfully detected different saccharides. In addition, a high accuracy diagnosis of central precocious puberty (CPP) with potential biomarkers of 12 metabolites was realized. This work is not only expected to provide a universal detection tool for large-scale clinical diagnosis, but also provides an idea for the design and selection of LDI-MS substrates.

Preparation and evaluation of in situ photocleavable mass tags with facile mass variation for matrix-free laser desorption ionization mass spectrometry.

Mass tags have been used for the precise identification, quantification, and characterization of macrobiomolecules and small organic molecules. Existing research has not yet demonstrated the preparation of a series of trityl-based photocleavable mass tags (PMTs) with similar structures but different molecular weights and mass variability. Herein, we introduce the design and synthesis of trityl-based in situ PMTs that generate heterolytic photocleavable cationic species upon laser irradiation. Mass variation of the PMTs was achieved via a simple conjugation reaction in the final step of synthesis. We prepared a series of PMTs with similar structures but different molecular weights and performed organic matrix-free laser desorption/ionization mass spectrometry (LDI MS) analysis. The practical applicability of the PMTs was evaluated by conjugating PMTs to oligonucleotides and utilizing them for detecting specific oligonucleotide targets combined with a mass signal amplification strategy. Quantitative aspects were also evaluated to verify the capability of the mass tags for multiplexed detection and the quantification of targets. The LDI MS analysis clearly demonstrated in situ heterolytic photocleavage that formed trityl cation peaks with high S/N ratios and high sensitivity. We strongly believe that the developed mass tags and LDI MS are useful alternatives to conventional signal transduction methods used for biosensors, such as surface plasmon resonance, electrochemical redox, and fluorescence.

Nutrient supplementation-induced metabolic profile changes and early appearance of free N-glycans in nutrient deficient tomato plants revealed by mass spectrometry.

Inorganic fertilizers are routinely used in large scale crop production for the supplementation of nitrogen, phosphorus, and potassium in nutrient poor soil. To explore metabolic changes in tomato plants grown on humic sand under different nutritional conditions, matrix-assisted laser desorption ionization (MALDI) mass spectrometry was utilized for the analysis of xylem sap. Variations in the abundances of metabolites and oligosaccharides, including free N-glycans (FNGs), were determined. Statistical analysis of the sample-related peaks revealed significant differences in the abundance ratios of multiple metabolites, including oligosaccharides, between the control plants, grown with no fertilizers, and plants raised under "ideal" and "nitrogen deficient" nutritional conditions, i.e., under the three treatment types. Among the 36 spectral features tentatively identified as oligosaccharides, the potential molecular structures for 18 species were predicted based on their accurate masses and isotope distribution patterns. To find the spectral features that account for most of the differences between the spectra corresponding to the three different treatments, multivariate statistical analysis was carried out by orthogonal partial least squares-discriminant analysis (OPLS-DA). They included both FNGs and non-FNG compounds that can be considered as early indicators of nutrient deficiency. Our results reveal that the potential nutrient deficiency indicators can be expanded to other metabolites beyond FNGs. The m/z values for 20 spectral features with the highest variable influence on projection (VIP) scores were ranked in the order of their influence on the statistical model.

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.

Analysis of Crude, Diverse, and Multiple Advanced Glycation End-Product Patterns May Be Important and Beneficial.

Lifestyle-related diseases (LSRDs), such as diabetes mellitus, cardiovascular disease, and nonalcoholic steatohepatitis, are a global crisis. Advanced glycation end-products (AGEs) have been extensively researched because they trigger or promote LSRDs. Recently, techniques such as fluorimetry, immunostaining, Western blotting, slot blotting, enzyme-linked immunosorbent assay, gas chromatography-mass spectrometry, matrix-assisted laser desorption-mass spectrometry (MALDI-MS), and electrospray ionization-mass spectrometry (ESI-MS) have helped prove the existence of intra/extracellular AGEs and revealed novel AGE structures and their modifications against peptide sequences. Therefore, we propose modifications to the existing categorization of AGEs, which was based on the original compounds identified by researchers in the 20th century. In this investigation, we introduce the (i) crude, (ii) diverse, and (iii) multiple AGE patterns. The crude AGE pattern is based on the fact that one type of saccharide or its metabolites or derivatives can generate various AGEs. Diverse and multiple AGE patterns were introduced based on the possibility of combining various AGE structures and proteins and were proven through mass analysis technologies such as MALDI-MS and ESI-MS. Kampo medicines are typically used to treat LSRDs. Because various compounds are contained in Kampo medicines and metabolized to exert effects on various organs or tissues, they may be suitable against various AGEs.

Characterization of Sulfur-Rich Microbial Organic Matter in Jurassic Carbonates Using Laser-Assisted Mass Spectrometry.

Laser desorption-ionization mass spectrometry (MS) shows great potential for in situ molecular analysis of planetary surfaces and microanalysis of space-returned samples or (micro)fossils. Coupled with pyrolysis gas chromatography-mass spectrometry (Py-GC-MS) in ESA's ExoMars project, this technique could help assess further the origin of sulfur-bearing organic matter (OM) recently detected on Mars. To unravel this potential, we analyzed sulfurized microbial OM from ca. 150 million year-old carbonates with laser desorption-ionization mass spectrometry (single- and two-step: LDI-MS and L2MS), in comparison with time-of-flight secondary-ion mass spectrometry (ToF-SIMS), gas chromatography-mass spectrometry (GC-MS), and Py-GC-MS. We show that LDI-MS and L2MS readily detect sulfur-bearing moieties such as (alkyl)thiophenes and (alkyl)benzothiophenes. The mineral matrix, however, made the identification of sulfur-bearing molecules challenging in our L2MS experiment. The dominance of small aromatic hydrocarbons (≤14 carbons) in the LDI-MS and L2MS of the extracted soluble and insoluble OM and of the bulk rock is consistent with the low thermal maturity of the sediment and contrasts with the predominance of larger polycyclic aromatic structures commonly observed in meteorites with these techniques. We detected inorganic ions, in particular VO+, in demineralized OM that likely originate from geoporphyrins, which derive from chlorophylls during sediment diagenesis. Finally, insoluble OM yielded distinct compositions compared with extracted soluble OM, with a greater abundance of ions of mass-to-charge ratio (m/z) over 175 and additional N-moieties. This highlights the potential of laser-assisted MS to decipher the composition of macromolecular OM, in particular to investigate the preservation of biomacromolecules in microfossils. Studies comparing diverse biogenic and abiogenic OM are needed to further assess the use of this technique to search for biosignatures.