Whole-body Mass Spectrometry Imaging by Infrared Matrix-assisted Laser Desorption Electrospray Ionization (IR-MALDESI)

Optimizing neurotransmitter pathway detection by IR-MALDESI-MSI in mouse brain

Mass spectrometry imaging (MSI) platforms such as infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) are advantageous for a variety of applications, including elucidating the localization of neurotransmitters (NTs) and related molecules with respect to ion abundance across a sample without the need for derivatization or organic matrix application. While IR-MALDESI-MSI conventionally uses a thin exogenous ice matrix to improve signal abundance, it has been previously determined that sucrose embedding without the ice matrix improves detection of lipid species in striatal, coronal mouse brain sections. This work considers components of this workflow to determine the optimal sample preparation and matrix to enhance the detection of NTs and their related metabolites in coronal sections from the striatal region of the mouse brain. The discoveries herein will enable more comprehensive follow-on studies for the investigation of NTs to enrich biological pathways and interpretation related to neurodegenerative diseases and ischemic stroke.

Time of acquisition and high spatial resolution mass spectrometry imaging

The field of mass spectrometry imaging (MSI) is constantly evolving to analyze a diverse array of biological systems. A common goal is the need to resolve cellular and subcellular heterogeneity with high spatial resolution. As the field continues to progress towards high spatial resolution, other parameters must be considered when developing a practical method. Here, we discuss the impacts of high spatial resolution on the time of acquisition and the associated implications they have on an MSI analysis (e.g., area of the region of interest). This work presents a brief tutorial serving to evaluate high spatial resolution MSI relative to time of acquisition and data file size.

Recent Advances of Ambient Mass Spectrometry Imaging and Its Applications in Lipid and Metabolite Analysis

Ambient mass spectrometry imaging (AMSI) has attracted much attention in recent years. As a kind of unlabeled molecular imaging technique, AMSI can enable in situ visualization of a large number of compounds in biological tissue sections in ambient conditions. In this review, the developments of various AMSI techniques are discussed according to one-step and two-step ionization strategies. In addition, recent applications of AMSI for lipid and metabolite analysis (from 2016 to 2021) in disease diagnosis, animal model research, plant science, drug metabolism and toxicology research, etc., are summarized. Finally, further perspectives of AMSI in spatial resolution, sensitivity, quantitative ability, convenience and software development are proposed.

Methods for Cryosectioning and Mass Spectrometry Imaging of Whole-Body Zebrafish

The zebrafish (Danio rerio) is an ideal model for whole animal studies of lipid metabolism and lipid-related disease. In this work, infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) mass spectrometry imaging (MSI) was applied for direct visualization of lipid and metabolite distributions across various organs in whole-body zebrafish tissue sections. Detailed methods for overcoming the challenges of cryosectioning adult male zebrafish for MSI and complementary histological imaging are described. Representative two-dimensional ion maps demonstrated organ specific localization of lipid analytes allowing for visualization of areas of interest including the brain, liver, intestines, and skeletal muscle. A high resolving power mass spectrometer was utilized for accurate mass measurements, which permitted the use of open-source, web-based tools for MS1 annotations including METASPACE and METLIN. Whole-body MSI with IR-MALDESI allowed for broad lipid coverage with high spatial resolution, illustrating the potential of this technique for studying lipid-related diseases using zebrafish as a model organism.

Determination of Optimal Electrospray Parameters for Lipidomics in Infrared-Matrix-Assisted Laser Desorption Electrospray Ionization Mass Spectrometry Imaging

Infrared matrix-assisted laser desorption ionization (IR-MALDESI) is an ambient mass spectrometry imaging (MSI) technique that relies on electrospray ionization (ESI) for ion generation of desorbed neutrals. Although many mechanisms in IR-MALDESI have been studied in depth, there has not yet been a comprehensive study of how the ESI parameters change the profiles of tissue specific lipids. Acetonitrile (ACN)/water and methanol (MeOH)/water solvent systems and compositions were varied across a series of applied ESI voltages during IR-MALDESI analysis of rat liver tissue. Gradients of 12 min were run from 5 to 95% organic solvent in both positive and negative polarities across 11 voltages between 2.25 and 4.5 kV. These experiments informed longer gradients (25-30 min) across shorter solvent gradient ranges with fewer voltages. Optimal ESI parameters for lipidomics were determined by the number and abundance of detected lipids and the relative proportion of background ions. In positive polarity, the best solvent composition was 60-75% ACN/40-25% H2O with 0.2% formic acid at 3.2 kV applied voltage. The best parameters for negative polarity analysis are 45-55% ACN/55-45% H2O with 1 mM of acetic acid for voltages between 2.25 and 3.2 kV. Using these defined parameters, IR-MALDESI positive polarity lipidomics studies can increase lipid abundances 3-fold, with 15% greater coverage, while an abundance increase of 1.5-fold and 10% more coverage can be achieved relative to commonly used parameters in negative polarity.

Mass Spectrometry Imaging (MSI) of Fresh Bones using Infrared Matrix-Assisted Laser Desorption Electrospray Ionization (IR-MALDESI)

We report an effective strategy for direct analysis and two-dimensional (2D) matrix-assisted laser desorption electrospray ionization (IR-MALDESI) mass spectrometry imaging (MSI) of mouse bones that underwent no chemical treatments prior to analysis. To unravel the chemistry in bones under near-physiological conditions, we cut a flash-frozen bone in half longitudinally, placed it in a mold facing flat side down, and poured Plaster of Paris on top of and around the bone. After Plaster of Paris had set, the bone with embedding material was removed from the mold, and placed on the IR-MALDESI imaging stage. Plaster of Paris acted as a fixture to keep every spot on the sample surface the same distance away from the laser focus. To demonstrate the feasibility of IR-MALDESI MSI for analyses of unmodified bones, we imaged bones derived from healthy and stroke-affected mice and generated ion heatmaps showing the spatial distribution of putatively annotated features.

Investigating host-pathogen meta-metabolic interactions of Magnaporthe oryzae infected barley using infrared matrix-assisted laser desorption electrospray ionization mass spectrometry

Infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) mass spectrometry imaging is a useful tool for identifying important meta-metabolomic features pertinent for enhancing our understanding of biological systems. Magnaporthe oryzae (M. oryzae) is a filamentous fungus that is the primary cause of rice blast disease. True to its name, M. oryzae primarily destroys rice crops and can also destroy other cereal crops as well. In a previous study, the F-box E3 ligase protein in M. oryzae was noted to be crucial for its growth and pathogenicity. In this study, we inoculated three separate sets of barley with wild-type M. oryzae, an F-box E3 ligase protein knock out of M. oryzae, and a control solution. Over the course of the infection (8 days), we imaged each treatment after development of an advanced polarity switching method, which allowed for the detection of low and high molecular weight compounds that ionize in positive or negative polarities. A set of features from initial experiments were chosen for another analysis using tandem mass spectrometry. Serotonin, a barley defense metabolite, was a compound identified in both positive and negative modes. Serotonin was putatively identified using MS1 data including carbon estimation and sulfur counting then confirmed based on tandem mass spectrometry fragmentation patterns. Metabolites in the melanin pathway, important for infection development of M. oryzae, were also identified using MS1 data but were unable to be confirmed with MS/MS due to their low abundances.

Internal Energy Deposition in Infrared Matrix-Assisted Laser Desorption Electrospray Ionization With and Without the Use of Ice as a Matrix

The internal energy deposited into analytes during the ionization process largely influences the extent of fragmentation, thus the appearance of the resulting mass spectrum. The internal energy distributions of a series of para-substituted benzyl pyridinium cations in liquid and solid-state generated by infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) were measured using the survival yield method, of which results were subsequently compared with conventional electrospray ionization (ESI). The comparable mean internal energy values (e.g., 1.8-1.9 eV at a collision energy of 15 eV) and peak widths obtained with IR-MALDESI and ESI support that IR-MALDESI are essentially a soft ionization technique where analytes do not gain considerable internal energy during the laser-induced desorption process and/or lose energy during uptake into charged electrospray droplets. An unusual fragment ion, protonated pyridine, was only found for solid IR-MALDESI at relatively high collision energies, which is presumably resulted from direct ionization of the pre-charged analytes in form of salts. Analysis of tissue with an ice layer consistently yielded ion populations with higher internal energy than its counterpart without an ice layer, likely due to a substantially enhanced number of IR absorbers with ice. Further measurements with holo-myoglobin show that IR-MALDESI-MS retains the noncovalently bound heme-protein complexes under both native-like and denaturing conditions, while complete loss of the heme group occurred in denaturing ESI-MS, showing that the softness of IR-MALDESI is equivalent or superior to ESI for biomolecules.

Heterogeneous antiretroviral drug distribution and HIV/SHIV detection in the gut of three species

HIV replication within tissues may increase in response to a reduced exposure to antiretroviral drugs. Traditional approaches to measuring drug concentrations in tissues are unable to characterize a heterogeneous drug distribution. Here, we used mass spectrometry imaging (MSI) to visualize the distribution of six HIV antiretroviral drugs in gut tissue sections from three species (two strains of humanized mice, macaques, and humans). We measured drug concentrations in proximity to CD3+ T cells that are targeted by HIV, as well as expression of HIV or SHIV RNA and expression of the MDR1 drug efflux transporter in gut tissue from HIV-infected humanized mice, SHIV-infected macaques, and HIV-infected humans treated with combination antiretroviral drug therapy. Serial 10-μm sections of snap-frozen ileal and rectal tissue were analyzed by MSI for CD3+ T cells and MDR1 efflux transporter expression by immunofluorescence and immunohistochemistry, respectively. The tissue slices were analyzed for HIV/SHIV RNA expression by in situ hybridization and for antiretroviral drug concentrations by liquid chromatography-mass spectrometry. The gastrointestinal tissue distribution of the six drugs was heterogeneous. Fifty percent to 60% of CD3+ T cells did not colocalize with detectable drug concentrations in the gut tissue. In all three species, up to 90% of HIV/SHIV RNA was found to be expressed in gut tissue with no exposure to drug. These data suggest that there may be gut regions with little to no exposure to antiretroviral drugs, which may result in low-level HIV replication contributing to HIV persistence.

Systematic evaluation of repeatability of IR-MALDESI-MS and normalization strategies for correcting the analytical variation and improving image quality

Mass spectrometry imaging is a powerful tool widely used in biological, clinical, and forensic research, but its often poor repeatability limits its application for quantitative and large-scale analysis. A systematic evaluation of infrared matrix-assisted laser desorption electrospray ionization mass spectrometry (IR-MALDESI-MS) repeatability in absolute ion abundances during short- and long-term experiments was carried out on liver slices from the same rat with minimal biological variability to be expected. Results of median %RSDs ranging from 14 to 45, pooled %RMADs ranging from 11 to 33, and Pearson correlation coefficients ranging from 0.83 to 1.00 demonstrated an acceptable repeatability of IR-MALDESI-MS. Normalization is commonly applied for the purpose of accounting for analytical variability of spectra generated from different runs so as to reveal real biological differences. Nine data normalization strategies were performed on the rat liver data sets to examine their effects on reducing analytical variation, and further on a hen ovary data set containing more morphological features for the investigation of their impact on ion images. Results demonstrated that the majority of normalization approaches benefit data quality to some extent, and local normalization methods significantly outperform their global counterparts, resulting in a reduction of median %RSD up to 22. Local median normalization was found to be promisingly robust for both homogeneous and heterogeneous samples.

Quantitative mass spectrometry imaging of glutathione in healthy and cancerous hen ovarian tissue sections by infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI)

A quantitative mass spectrometry imaging (QMSI) method for absolute quantification of glutathione (GSH) in healthy and cancerous hen ovarian tissues using infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) is presented. Using this technique, the ion abundance of GSH was normalized to that of a structural analogue, which was sprayed on the slide prior to mounting the tissue sections. This normalization strategy significantly improved the voxel-to-voxel variability; the variability is attributed to the overall ionization process. Subsequently, a series of calibration spots of stable isotope-labeled (SIL) GSH were pipetted on top of the tissue to construct a spatial calibration curve, and calculate the concentration of GSH in both tissue sections. The QMSI results were verified by LC-MS/MS quantification of GSH for the same tissues. GSH was extracted from tissue sections in a slightly acidic buffer and was then alkylated using N-ethylmaleimide to minimize autoxidation of GSH to glutathione disulfide. The alkylated GSH was separated from other contaminants using reversed phase liquid chromatography (RPLC) coupled to a triple quadrupole mass spectrometer, and the z-ion transition of NEM-GSH was used to quantify GSH in each tissue section. While the absolute values obtained using IR-MALDESI QMSI and LC-MS/MS were different, a ∼2-fold increase in the concentration of GSH in cancer tissue compared to the healthy tissue was observed using both techniques. Possible reasons for the difference between absolute concentration values obtained using IR-MALDESI QMSI and LC-MS/MS are also discussed.

MSiReader v1.0: Evolving Open-Source Mass Spectrometry Imaging Software for Targeted and Untargeted Analyses

A major update to the mass spectrometry imaging (MSI) software MSiReader is presented, offering a multitude of newly added features critical to MSI analyses. MSiReader is a free, open-source, and vendor-neutral software written in the MATLAB platform and is capable of analyzing most common MSI data formats. A standalone version of the software, which does not require a MATLAB license, is also distributed. The newly incorporated data analysis features expand the utility of MSiReader beyond simple visualization of molecular distributions. The MSiQuantification tool allows researchers to calculate absolute concentrations from quantification MSI experiments exclusively through MSiReader software, significantly reducing data analysis time. An image overlay feature allows the incorporation of complementary imaging modalities to be displayed with the MSI data. A polarity filter has also been incorporated into the data loading step, allowing the facile analysis of polarity switching experiments without the need for data parsing prior to loading the data file into MSiReader. A quality assurance feature to generate a mass measurement accuracy (MMA) heatmap for an analyte of interest has also been added to allow for the investigation of MMA across the imaging experiment. Most importantly, as new features have been added performance has not degraded, in fact it has been dramatically improved. These new tools and the improvements to the performance in MSiReader v1.0 enable the MSI community to evaluate their data in greater depth and in less time. Graphical Abstract ᅟ.

Infrared matrix-assisted laser desorption electrospray ionization mass spectrometry imaging analysis of biospecimens

Infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) mass spectrometry imaging (MSI) is a technique well suited for analysis of biological specimens. This tutorial review focuses on recent advancements and applications of IR-MALDESI MSI to better understand key biological questions. Through optimization of user-defined source parameters, comprehensive and quantitative MSI data can be obtained for a variety of analytes. The effect of an ice matrix layer is well defined in the context of desorption dynamics and resulting ion abundance. Optimized parameters and careful control of conditions affords quantitative MSI data which provides valuable information for targeted, label-free drug distribution studies and untargeted metabolomic datasets. Challenges and limitations of MSI using IR-MALDESI are addressed in the context of the bioimaging field.

TransOmic analysis of forebrain sections in Sp2 conditional knockout embryonic mice using IR-MALDESI imaging of lipids and LC-MS/MS label-free proteomics

Quantitative methods for detection of biological molecules are needed more than ever before in the emerging age of "omics" and "big data." Here, we provide an integrated approach for systematic analysis of the "lipidome" in tissue. To test our approach in a biological context, we utilized brain tissue selectively deficient for the transcription factor Specificity Protein 2 (Sp2). Conditional deletion of Sp2 in the mouse cerebral cortex results in developmental deficiencies including disruption of lipid metabolism. Silver (Ag) cationization was implemented for infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) to enhance the ion abundances for olefinic lipids, as these have been linked to regulation by Sp2. Combining Ag-doped and conventional IR-MALDESI imaging, this approach was extended to IR-MALDESI imaging of embryonic mouse brains. Further, our imaging technique was combined with bottom-up shotgun proteomic LC-MS/MS analysis and western blot for comparing Sp2 conditional knockout (Sp2-cKO) and wild-type (WT) cortices of tissue sections. This provided an integrated omics dataset which revealed many specific changes to fundamental cellular processes and biosynthetic pathways. In particular, step-specific altered abundances of nucleotides, lipids, and associated proteins were observed in the cerebral cortices of Sp2-cKO embryos.