Matrix ions as internal standard for high mass accuracy matrix-assisted laser desorption/ionization mass spectrometry imaging

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2021-2022

The use of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry for the analysis of carbohydrates and glycoconjugates is a well-established technique and this review is the 12th update of the original article published in 1999 and brings coverage of the literature to the end of 2022. As with previous review, this review also includes a few papers that describe methods appropriate to analysis by MALDI, such as sample preparation, even though the ionization method is not MALDI. The review follows the same format as previous reviews. It is divided into three sections: (1) general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation, quantification and the use of computer software for structural identification. (2) Applications to various structural types such as oligo- and polysaccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals, and (3) other general areas such as medicine, industrial processes, natural products and glycan synthesis where MALDI is extensively used. Much of the material relating to applications is presented in tabular form. MALDI is still an ideal technique for carbohydrate analysis, particularly in its ability to produce single ions from each analyte and advancements in the technique and range of applications show little sign of diminishing.

Improved Mass Calibration in MALDI MSI Using Neural Network-Based Recalibration

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) is a powerful imaging method for generating molecular maps of biological samples and has numerous applications in biomedical research. A key challenge in MALDI MSI is to reliably map observed mass peaks to theoretical masses, which can be difficult due to mass shifts that occur during the measurement process. In this paper, we propose MassShiftNet, a novel self-supervised learning framework for mass recalibration. We train a neural network on a data dependent and specifically augmented training data set to directly estimate and correct the mass shift in the observed spectra. In our evaluation, we show that this method is both able to reduce the absolute mass error and to increase the relative mass alignment between peptide MSI spectra acquired from FFPE-fixated tissue using a MALDI time-of-flight (TOF) instrument.

Advances in mass spectrometry imaging for spatial cancer metabolomics

Mass spectrometry (MS) has become a central technique in cancer research. The ability to analyze various types of biomolecules in complex biological matrices makes it well suited for understanding biochemical alterations associated with disease progression. Different biological samples, including serum, urine, saliva, and tissues have been successfully analyzed using mass spectrometry. In particular, spatial metabolomics using MS imaging (MSI) allows the direct visualization of metabolite distributions in tissues, thus enabling in-depth understanding of cancer-associated biochemical changes within specific structures. In recent years, MSI studies have been increasingly used to uncover metabolic reprogramming associated with cancer development, enabling the discovery of key biomarkers with potential for cancer diagnostics. In this review, we aim to cover the basic principles of MSI experiments for the nonspecialists, including fundamentals, the sample preparation process, the evolution of the mass spectrometry techniques used, and data analysis strategies. We also review MSI advances associated with cancer research in the last 5 years, including spatial lipidomics and glycomics, the adoption of three-dimensional and multimodal imaging MSI approaches, and the implementation of artificial intelligence/machine learning in MSI-based cancer studies. The adoption of MSI in clinical research and for single-cell metabolomics is also discussed. Spatially resolved studies on other small molecule metabolites such as amino acids, polyamines, and nucleotides/nucleosides will not be discussed in the context.

MALDI MS Imaging of Chickpea Seeds (Cicer arietinum) and Crab's Eye Vine (Abrus precatorius) after Tryptic Digestion Allows Spatially Resolved Identification of Plant Proteins

Matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS) imaging following in situ enzymatic digestion is a versatile analytical method for the untargeted investigation of protein distributions, which has rarely been used for plants so far. The present study describes a workflow for in situ tryptic digestion of plant seed tissue for MALDI MS imaging. Substantial modifications to the sample preparation procedure for mammalian tissues were necessary to cater to the specific properties of plant materials. For the first time, distributions of tryptic peptides were successfully visualized in plant tissue using MS imaging with accurate mass detection. Sixteen proteins were visualized and identified in chickpea seeds showing different distribution patterns, e.g., in the cotyledons, radicle, or testa. All tryptic peptides were detected with a mass resolution higher than 60,000 as well as a mass accuracy better than 1.5 ppm root-mean-square error and were matched to results from complementary liquid chromatography-MS/MS (LC-MS/MS) data. The developed method was also applied to crab's eye vine seeds for targeted MS imaging of the toxic protein abrin, showing the presence of abrin-a in all compartments. Abrin (59 kDa), as well as the majority of proteins visualized in chickpeas, was larger than 50 kDa and would thus not be readily accessible by top-down MS imaging. Since antibodies for plant proteins are often not readily available, in situ digestion MS imaging provides unique information, as it makes the distribution and identification of larger proteins in plant tissues accessible in an untargeted manner. This opens up new possibilities in the field of plant science as well as to assess the nutritional quality and/or safety of crops.

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

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

Expanded Coverage of Phytocompounds by Mass Spectrometry Imaging Using On-Tissue Chemical Derivatization by 4-APEBA

Probing the entirety of any species metabolome is an analytical grand challenge, especially on a cellular scale. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) is a common spatial metabolomics assay, but this technique has limited molecular coverage for several reasons. To expand the application space of spatial metabolomics, we developed an on-tissue chemical derivatization (OTCD) workflow using 4-APEBA for the confident identification of several dozen elusive phytocompounds. Overall, this new OTCD method enabled the annotation of roughly 280 metabolites, with only a 10% overlap in metabolic coverage when compared to analog negative ion mode MALDI-MSI on serial sections. We demonstrate that 4-APEBA outperforms other derivatization agents by providing: (1) broad specificity toward carbonyls, (2) low background, and (3) introduction of bromine isotopes. Notably, the latter two attributes also facilitate more confidence in our bioinformatics for data processing. The workflow detailed here trailblazes a path toward spatial hormonomics within plant samples, enhancing the detection of carboxylates, aldehydes, and plausibly other carbonyls. As such, several phytohormones, which have various roles within stress responses and cellular communication, can now be spatially profiled, as demonstrated in poplar root and soybean root nodule.

Autofocusing MALDI MS imaging of processed food exemplified by the contaminant acrylamide in German gingerbread

Acrylamide is a toxic reaction product occurring in dry-heated food such as bakery products. To meet the requirements laid down in recent international legal norms calling for reduction strategies in food prone to acrylamide formation, efficient chromatography-based quantification methods are available. However, for an efficient mitigation of acrylamide levels, not only the quantity, but also the contaminant's distributions are of interest especially in inhomogeneous food consisting of multiple ingredients. A promising tool to investigate the spatial distribution of analytes in food matrices is mass spectrometry imaging (MS imaging). In this study, an autofocusing MALDI MS imaging method was developed for German gingerbread as an example for highly processed and instable food with uneven surfaces. Next to endogenous food constituents, the process contaminant acrylamide was identified and visualized keeping a constant laser focus throughout the measurement. Statistical analyses based on relative acrylamide intensities suggest a higher contamination of nut fragments compared to the dough. In a proof-of-concept experiment, a newly developed in-situ chemical derivatization protocol is described using thiosalicylic acid for highly selective detection of acrylamide. This study presents autofocusing MS imaging as a suitable complementary method for the investigation of analytes' distributions in complex and highly processed food.

Mass spectrometry imaging: new eyes on natural products for drug research and development

Natural products (NPs) and their structural analogs represent a major source of novel drug development for disease prevention and treatment. The development of new drugs from NPs includes two crucial aspects. One is the discovery of NPs from medicinal plants/microorganisms, and the other is the evaluation of the NPs in vivo at various physiological and pathological states. The heterogeneous spatial distribution of NPs in medicinal plants/microorganisms or in vivo can provide valuable information for drug development. However, few molecular imaging technologies can detect thousands of compounds simultaneously on a label-free basis. Over the last two decades, mass spectrometry imaging (MSI) methods have progressively improved and diversified, thereby allowing for the development of various applications of NPs in plants/microorganisms and in vivo NP research. Because MSI allows for the spatial mapping of the production and distribution of numerous molecules in situ without labeling, it provides a visualization tool for NP research. Therefore, we have focused this mini-review on summarizing the applications of MSI technology in discovering NPs from medicinal plants and evaluating NPs in preclinical studies from the perspective of new drug research and development (R&D). Additionally, we briefly reviewed the factors that should be carefully considered to obtain the desired MSI results. Finally, the future development of MSI in new drug R&D is proposed.

Viral Biomarker Detection and Validation Using MALDI Mass Spectrometry Imaging (MSI)

(1) Background: MALDI imaging is a technique that still largely depends on time of flight (TOF)-based instrument such as the Bruker UltrafleXtreme. While capable of performing targeted MS/MS, these instruments are unable to perform fragmentation while imaging a tissue section necessitating the reliance of MS1 values for peptide level identifications. With this premise in mind, we have developed a hybrid bioinformatic/image-based method for the identification and validation of viral biomarkers. (2) Methods: Formalin-Fixed Paraffin-Embedded (FFPE) mouse samples were sectioned, mounted and prepared for mass spectrometry imaging using our well-established methods. Peptide identification was achieved by first extracting confident images corresponding to theoretical viral peptides. Next, those masses were used to perform a Peptide Mmass Fingerprint (PMF) searched against known viral FASTA sequences against a background mouse FASTA database. Finally, a correlational analysis was performed with imaging data to confirm pixel-by-pixel colocalization and intensity of viral peptides. (3) Results: 14 viral peptides were successfully identified with significant PMF Scores and a correlational result of >0.79 confirming the presence of the virus and distinguishing it from the background mouse proteins. (4) Conclusions: this novel approach leverages the power of mass spectrometry imaging and provides confident identifications for viral proteins without requiring MS/MS using simple MALDI Time Of Flight/Time Of Flight (TOF/TOF) instrumentation.

DDA-imaging with structural identification of lipid molecules on an Orbitrap Velos Pro mass spectrometer

Matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) is a useful technique for visualizing the spatial distribution of lipid molecules in tissues. Nevertheless, the use of MSI to investigate local lipid metabolic hallmarks has until recently been hampered by a lack of adequate technology that supports confident lipid identification. This limitation was recently mitigated by the development of DDA-imaging technology where high-resolution MSI is combined with parallel acquisition of lipid tandem MS² spectra on a hybrid ion trap-Orbitrap Elite mass spectrometer featuring a resolving power of 240,000 and a scan time of 1 s. Here, we report the key tenets related to successful transfer of the DDA-imaging technology onto an Orbitrap Velos Pro instrument featuring a resolving power of 120,000 and a scan time of 2 s. Through meticulous performance assessments and method optimization, we tuned the DDA-imaging method to be able to confidently identify 73 molecular lipid species in mouse brain sections and demonstrate that the performance of the technology is comparable with DDA-imaging on the Orbitrap Elite. Altogether, our work shows that DDA-imaging on the Orbitrap Velos Pro instrument can serve as a robust workhorse for lipid imaging in routine applications.

Do Anti-tuberculosis Drugs Reach Their Target?─High-Resolution Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging Provides Information on Drug Penetration into Necrotic Granulomas

Tuberculosis (TB) is characterized by mycobacteria-harboring centrally necrotizing granulomas. The efficacy of anti-TB drugs depends on their ability to reach the bacteria in the center of these lesions. Therefore, we developed a mass spectrometry (MS) imaging workflow to evaluate drug penetration in tissue. We employed a specific mouse model that─in contrast to regular inbred mice─strongly resembles human TB pathology. Mycobacterium tuberculosis was inactivated in lung sections of these mice by γ-irradiation using a protocol that was optimized to be compatible with high spatial resolution MS imaging. Different distributions in necrotic granulomas could be observed for the anti-TB drugs clofazimine, pyrazinamide, and rifampicin at a pixel size of 30 μm. Clofazimine, imaged here for the first time in necrotic granulomas of mice, showed higher intensities in the surrounding tissue than in necrotic granulomas, confirming data observed in TB patients. Using high spatial resolution drug and lipid imaging (5 μm pixel size) in combination with a newly developed data analysis tool, we found that clofazimine does penetrate to some extent into necrotic granulomas and accumulates in the macrophages inside the granulomas. These results demonstrate that our imaging platform improves the predictive power of preclinical animal models. Our workflow is currently being applied in preclinical studies for novel anti-TB drugs within the German Center for Infection Research (DZIF). It can also be extended to other applications in drug development and beyond. In particular, our data analysis approach can be used to investigate diffusion processes by MS imaging in general.

Imaging Method by Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry (MALDI-MS) for Tissue or Tumor: A Mini Review

Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) is an advanced technique that uses minimum fragmented ions from complex molecules for mass spectrometry (MS) analysis (tissue profiling by mass spectrometry). It is able to analyze spatially resolved tissue or tumor sections at the molecular level. It has become a valuable tool for tumor and tissue imaging, due to its ease of operation and high mass resolution, but it still has vast room for development in the instrumentation of larger proteins in some tissues. In this review, we focus on the main components of MALDI-MS instrumentation, sample handling and processing, the working principle of MALDI-MS, and its applications in diagnostic and prognostic assessments, tumor removal and drug development. Although it is less effective at detecting larger proteins in some tissues, it still shows huge potential because of its advancements in instrumentation and processing protocols. This article may benefit those who have interests in MALDI-MS for tissue or tumor imaging.

Interleukin-13 overexpressing mice represent an advanced pre-clinical model for detecting the distribution of anti-mycobacterial drugs within centrally necrotizing granulomas

The Mycobacterium tuberculosis-harboring granuloma with a necrotic center surrounded by a fibrous capsule is the hallmark of tuberculosis (TB). For a successful treatment, antibiotics need to penetrate these complex structures to reach their bacterial targets. Hence, animal models reflecting the pulmonary pathology of TB patients are of particular importance to improve the preclinical validation of novel drug candidates. M. tuberculosis-infected interleukin-13-overexpressing (IL-13^tg) mice develop a TB pathology very similar to patients and, in contrast to other mouse models, also share pathogenetic mechanisms. Accordingly, IL-13^tg animals represent an ideal model for analyzing the penetration of novel anti-TB drugs into various compartments of necrotic granulomas by matrix-assisted laser desorption/ionization–mass spectrometry imaging (MALDI-MS imaging). In the present study, we evaluated the suitability of BALB/c IL-13^tg mice for determining the antibiotic distribution within necrotizing lesions. To this end, we established a workflow based on the inactivation of M. tuberculosis by gamma irradiation while preserving lung tissue integrity and drug distribution, which is essential for correlating drug penetration with lesion pathology. MALDI-MS imaging analysis of clofazimine, pyrazinamide, and rifampicin revealed a drug-specific distribution within different lesion types, including cellular granulomas, developing in BALB/c wild-type mice, and necrotic granulomas in BALB/c IL-13^tg animals, emphasizing the necessity of preclinical models reflecting human pathology. Most importantly, our study demonstrates that BALB/c IL-13^tg mice recapitulate the penetration of antibiotics into human lesions. Therefore, our workflow in combination with the IL-13^tg mouse model provides an improved and accelerated evaluation of novel anti-TB drugs and new regimens in the preclinical stage.

Imaging lipids in biological samples with surface-assisted laser desorption/ionization mass spectrometry: A concise review of the last decade

Knowing the spatial location of the lipid species present in biological samples is of paramount importance for the elucidation of pathological and physiological processes. In this context, mass spectrometry imaging (MSI) has emerged as a powerful technology allowing the visualization of the spatial distributions of biomolecules, including lipids, in complex biological samples. Among the different ionization methods available, the emerging surface-assisted laser desorption/ionization (SALDI) MSI offers unique capabilities for the study of lipids. This review describes the specific advantages of SALDI-MSI for lipid analysis, including the ability to perform analyses in both ionization modes with the same nanosubstrate, the detection of lipids characterized by low ionization efficiency in MALDI-MS, and the possibilities of surface modification to improve the detection of lipids. The complementarity of SALDI and MALDI-MSI is also discussed. Finally, this review presents data processing strategies applied in SALDI-MSI of lipids, as well as examples of applications of SALDI-MSI in biomedical lipidomics.