High-Throughput Mass Spectrometry Imaging of Biological Systems: Current Approaches and Future Directions

Integrating the Preparation of a Tissue Section on Adhesive Tape with an Adsorption Platform Device for Simplified Ambient Mass Spectrometry Imaging Analysis

As a visualization technology for the in situ characterization of surface material molecules, mass spectrometry imaging (MSI) analysis is being increasingly used in various fields, especially in the biomedical field. However, the preparation of biological tissue section samples for MSI analysis remains time-consuming and labor-intensive, and sample loss or damage occurs frequently. The inability to stably and consecutively obtain suitable section samples and perform concise and efficient imaging analysis limits the analysis throughput. Herein, a preparation method is proposed. It enables consecutive sectioning, batch preservation, and dry processing through the use of ordinary adhesive tape, enhancing the adhesion between section and tape and rapid freeze-drying. Furthermore, based on the air flow assisted desorption electrospray ionization (AFADESI) MSI system, a vacuum adsorption platform is introduced, which simplifies the process of MSI analysis. Moreover, compared with general tape-based MSI methods, the signal intensity of 73%-85% of the annotated ions is improved for positive ion mode. The signal-to-noise (S/N) ratios of characteristic ions in the corresponding regions in the images of the tissue section samples increase by an average of more than two times, and a clearer organ outline can be seen in the images. By integrating the sample preparation method with the adsorption platform, high-throughput imaging of serial whole-body or scattered organ tissue sections can be conducted more easily and concise and efficient MSI analysis can be performed, which will provide a new strategy to meet rapidly growing MSI research demands.

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.

Spatial multi-omics analysis of metabolic heterogeneity in zebrafish exposed to microcystin-LR and its disinfection byproducts

Most studies on the biological effects of exogenous pollutants have focused on whole samples or cell populations, and lack spatial heterogeneity consideration due to technical limitations. Microcystin-LR (MC-LR) from cyanobacterial blooms threatens ecosystems and human health, while microcystin-LR disinfection by-products (MCLR-DBPs) in drinking water remain a concern for their toxin-like structure. This study introduces spatial multi-omics to investigate the disruptions caused by ingestion of MC-LR and MCLR-DBPs in zebrafish. The method integrates metabolomics, spatial metabolomics, and spatial transcriptomics to characterize the overall metabolic changes in whole zebrafish caused by MC-LR and MCLR-DBPs, then provides further insight into the variation of spatial distribution of metabolites and genes in MC-LR and MCLR-DBPs targeted organ. The results showed that MC-LR and MCLR-DBPs induced oxidative stress and metabolic imbalance, and disrupted the physiological homeostasis of zebrafish. Spatial multi-omics analysis further revealed that MC-LR and MCLR-DBPs exacerbate disruptions in energy and lipid metabolism, methylation processes, and immune pathways by modulating the expression of genes such as gatm, gnmt, cyp2p9, and tdo2b. In conclusion, this study developed a spatial multi-omics approach that not only enhances the understanding of the biological effects of MC-LR and MCLR-DBPs but also provides robust technical support for investigating other environmental pollutants.

Untargeted pixel-by-pixel metabolite ratio imaging as a novel tool for biomedical discovery in mass spectrometry imaging

Mass spectrometry imaging (MSI) is a powerful technology used to define the spatial distribution and relative abundance of metabolites across tissue cryosections. While software packages exist for pixel-by-pixel individual metabolite and limited target pairs of ratio imaging, the research community lacks an easy computing and application tool that images any metabolite abundance ratio pairs. Importantly, recognition of correlated metabolite pairs may contribute to the discovery of unanticipated molecules in shared metabolic pathways. Here, we describe the development and implementation of an untargeted R package workflow for pixel-by-pixel ratio imaging of all metabolites detected in an MSI experiment. Considering untargeted MSI studies of murine brain and embryogenesis, we demonstrate that ratio imaging minimizes systematic data variation introduced by sample handling, markedly enhances spatial image contrast, and reveals previously unrecognized metabotype-distinct tissue regions. Furthermore, ratio imaging facilitates identification of novel regional biomarkers and provides anatomical information regarding spatial distribution of metabolite-linked biochemical pathways. The algorithm described herein is applicable to any MSI dataset containing spatial information for metabolites, peptides or proteins, offering a potent hypothesis generation tool to enhance knowledge obtained from current spatial metabolite profiling technologies.

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.

Rapid and Robust Workflows Using Different Ionization, Computation, and Visualization Approaches for Spatial Metabolome Profiling of Microbial Natural Products in Pseudoalteromonas

Ambient mass spectrometry (MS) technologies have been applied to spatial metabolomic profiling of various samples in an attempt to both increase analysis speed and reduce the length of sample preparation. Recent studies, however, have focused on improving the spatial resolution of ambient approaches. Finer resolution requires greater analysis times and commensurate computing power for more sophisticated data analysis algorithms and larger data sets. Higher resolution provides a more detailed molecular picture of the sample; however, for some applications, this is not required. A liquid microjunction surface sampling probe (LMJ-SSP) based MS platform combined with unsupervised multivariant analysis based hyperspectral visualization is demonstrated for the metabolomic analysis of marine bacteria from the genus Pseudoalteromonas to create a rapid and robust spatial profiling workflow for microbial natural product screening. In our study, metabolomic profiles of different Pseudoalteromonas species are quickly acquired without any sample preparation and distinguished by unsupervised multivariant analysis. Our robust platform is capable of automated direct sampling of microbes cultured on agar without clogging. Hyperspectral visualization-based rapid spatial profiling provides adequate spatial metabolite information on microbial samples through red-green-blue (RGB) color annotation. Both static and temporal metabolome differences can be visualized by straightforward color differences and differentiating m/z values identified afterward. Through this approach, novel analogues and their potential biosynthetic pathways are discovered by applying results from the spatial navigation to chromatography-based metabolome annotation. In this current research, LMJ-SSP is shown to be a robust and rapid spatial profiling method. Unsupervised multivariant analysis based hyperspectral visualization is proven straightforward for facile/rapid data interpretation. The combination of direct analysis and innovative data visualization forms a powerful tool to aid the identification/interpretation of interesting compounds from conventional metabolomics analysis.

Untargeted Pixel-by-Pixel Imaging of Metabolite Ratio Pairs as a Novel Tool for Biomedical Discovery in Mass Spectrometry Imaging

Mass spectrometry imaging (MSI) is a powerful technology used to define the spatial distribution and relative abundance of metabolites across tissue cryosections. While software packages exist for pixel-by-pixel individual metabolite and limited target pairs of ratio imaging, the research community lacks an easy computing and application tool that images any metabolite abundance ratio pairs. Importantly, recognition of correlated metabolite pairs may contribute to the discovery of unanticipated molecules in shared metabolic pathways. Here, we describe the development and implementation of an untargeted R package workflow for pixel-by-pixel ratio imaging of all metabolites detected in an MSI experiment. Considering untargeted MSI studies of murine brain and embryogenesis, we demonstrate that ratio imaging minimizes systematic data variation introduced by sample handling, markedly enhances spatial image contrast, and reveals previously unrecognized metabotype-distinct tissue regions. Furthermore, ratio imaging facilitates identification of novel regional biomarkers and provides anatomical information regarding spatial distribution of metabolite-linked biochemical pathways. The algorithm described herein is applicable to any MSI dataset containing spatial information for metabolites, peptides or proteins, offering a potent hypothesis generation tool to enhance knowledge obtained from current spatial metabolite profiling technologies.

Nanospray Desorption Electrospray Ionization Mass Spectrometry Imaging (nano-DESI MSI): A Tutorial Review

Nanospray desorption electrospray ionization (nano-DESI) is a liquid-based ambient mass spectrometry imaging (MSI) technique that enables visualization of analyte distributions in biological samples down to cellular-level spatial resolution. Since its inception, significant advancements have been made to the nano-DESI experimental platform to facilitate molecular imaging with high throughput, deep molecular coverage, and spatial resolution better than 10 μm. The molecular selectivity of nano-DESI MSI has been enhanced using new data acquisition strategies, the development of separation and online derivatization approaches for isobar separation and isomer-selective imaging, and the optimization of the working solvent composition to improve analyte extraction and ionization efficiency. Furthermore, nano-DESI MSI research has underscored the importance of matrix effects and established normalization methods for accurately measuring concentration gradients in complex biological samples. This tutorial offers a comprehensive guide to nano-DESI experiments, detailing fundamental principles and data acquisition and processing methods and discussing essential operational parameters.

Spatial pharmacology using mass spectrometry imaging

The emerging and powerful field of spatial pharmacology can map the spatial distribution of drugs and their metabolites, as well as their effects on endogenous biomolecules including metabolites, lipids, proteins, peptides, and glycans, without the need for labeling. This is enabled by mass spectrometry imaging (MSI) that provides previously inaccessible information in diverse phases of drug discovery and development. We provide a perspective on how MSI technologies and computational tools can be implemented to reveal quantitative spatial drug pharmacokinetics and toxicology, tissue subtyping, and associated biomarkers. We also highlight the emerging potential of comprehensive spatial pharmacology through integration of multimodal MSI data with other spatial technologies. Finally, we describe how to overcome challenges including improving reproducibility and compound annotation to generate robust conclusions that will improve drug discovery and development processes.

A monolithic microfluidic probe for ambient mass spectrometry imaging of biological tissues

Ambient mass spectrometry imaging (MSI) is a powerful technique that allows for the simultaneous mapping of hundreds of molecules in biological samples under atmospheric conditions, requiring minimal sample preparation. We have developed nanospray desorption electrospray ionization (nano-DESI), a liquid extraction-based ambient ionization technique, which has proven to be sensitive and capable of achieving high spatial resolution. We have previously described an integrated microfluidic probe, which simplifies the nano-DESI setup, but is quite difficult to fabricate. Herein, we introduce a facile and scalable strategy for fabricating microfluidic devices for nano-DESI MSI applications. Our approach involves the use of selective laser-assisted etching (SLE) of fused silica to create a monolithic microfluidic probe (SLE-MFP). Unlike the traditional photolithography-based fabrication, SLE eliminates the need for the wafer bonding process and allows for automated, scalable fabrication of the probe. The chamfered design of the sampling port and ESI emitter significantly reduces the amount of polishing required to fine-tune the probe thereby streamlining and simplifying the fabrication process. We have also examined the performance of a V-shaped probe, in which only the sampling port is fabricated using SLE technology. The V-shaped design of the probe is easy to fabricate and provides an opportunity to independently optimize the size and shape of the electrospray emitter. We have evaluated the performance of SLE-MFP by imaging mouse tissue sections. Our results demonstrate that SLE technology enables the fabrication of robust monolithic microfluidic probes for MSI experiments. This development expands the capabilities of nano-DESI MSI and makes the technique more accessible to the broader scientific community.

Plasmonic alloys for quantitative determination and reaction monitoring of biothiols

Biothiols participate in numerous physiological and pathological processes in an organism. Quantitative determination and reaction monitoring of biothiols have important implications for evaluating human health. Herein, we synthesized plasmonic alloys as the matrix to assist the laser desorption and ionization (LDI) process of biothiols in mass spectrometry (MS). Plasmonic alloys were constructed with mesoporous structures for LDI enhancement and trimetallic (PdPtAu) compositions for noble metal-thiol hybridization, toward enhanced detection sensitivity and selectivity, respectively. Plasmonic alloys enabled direct detection of biothiols from complex biosamples without any enrichment or separation. We introduced internal standards into the quantitative MS system, achieving accurate quantitation of methionine directly from serum samples with a recovery rate of 103.19% ± 6.52%. Moreover, we established a rapid monitoring platform for the oxidation-reduction reaction of glutathione, consuming trace samples down to 200 nL with an interval of seconds. This work contributes to the development of molecular tools based on plasmonic materials for biothiol detection toward real-case applications.

Maximized Spatial Information and Minimized Acquisition Time of Top-Hat IR-MALDESI-MSI of Zebrafish Using Nested Regions of Interest (nROIs)

Increasing the spatial resolution of a mass spectrometry imaging (MSI) method results in a more defined heatmap of the spatial distribution of molecules across a sample, but it is also associated with the disadvantage of increased acquisition time. Decreasing the area of the region of interest to achieve shorter durations results in the loss of potentially valuable information in larger specimens. This work presents a novel MSI method to reduce the time of MSI data acquisition with variable step size imaging: nested regions of interest (nROIs). Using nROIs, a small ROI may be imaged at a higher spatial resolution while nested inside a lower-spatial-resolution peripheral ROI. This conserves the maximal spatial and chemical information generated from target regions while also decreasing the necessary acquisition time. In this work, the nROI method was characterized on mouse liver and applied to top-hat MSI of zebrafish using a novel optical train, which resulted in a significant improvement in both acquisition time and spatial detail of the zebrafish. The nROI method can be employed with any step size pairing and adapted to any method in which the acquisition time of larger high-resolution ROIs poses a practical challenge.

Nanospray Desorption Electrospray Ionization (Nano-DESI) Mass Spectrometry Imaging with High Ion Mobility Resolution

Untargeted separation of isomeric and isobaric species in mass spectrometry imaging (MSI) is challenging. The combination of ion mobility spectrometry (IMS) with MSI has emerged as an effective strategy for differentiating isomeric and isobaric species, which substantially enhances the molecular coverage and specificity of MSI experiments. In this study, we have implemented nanospray desorption electrospray ionization (nano-DESI) MSI on a trapped ion mobility spectrometry (TIMS) mass spectrometer. A new nano-DESI source was constructed, and a specially designed inlet extension was fabricated to accommodate the new source. The nano-DESI-TIMS-MSI platform was evaluated by imaging mouse brain tissue sections. We achieved high ion mobility resolution by utilizing three narrow mobility scan windows that covered the majority of the lipid molecules. Notably, the mobility resolution reaching up to 300 in this study is much higher than the resolution obtained in our previous study using drift tube IMS. High-resolution TIMS successfully separated lipid isomers and isobars, revealing their distinct localizations in tissue samples. Our results further demonstrate the power of high-mobility-resolution IMS for unraveling the complexity of biomolecular mixtures analyzed in MSI experiments.