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High spatial resolution is a key parameter in mass spectrometry imaging (MSI), enabling a greater understanding of system biology and cellular processes. Using a novel IR laser with good Gaussian beam quality ( M 2 = 4) coupled with spatial filtering and a reflective objective, 20 μm spatial resolution was obtained by IR-MALDESI. The optical train was optimized on burn paper before demonstrating feasibility for imaging of liver tissue. Finally, a mouse brain was analyzed using nested regions of interest at 20 and 140 μm spatial resolution, detecting neurotransmitters and lipids with high spatial resolution on the corpus callosum and surrounding brain tissue.

Quantitative mass spectrometry imaging (qMSI) provides the relative or absolute analyte quantities in a biological specimen in a spatially resolved manner. However, the chemical complexity and physical structure of biological specimens often require one to precisely account for matrix effects in qMSI platforms. Infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) completely ablates a volume of cryosectioned tissue. This enables the use of a normalization standard that is sprayed underneath the tissue for qMSI applications. Complete sampling has shown to be a significant advantage for qMSI by IR-MALDESI; however, the impact of high tissue heterogeneity has not been systematically studied or quantified. The bias introduced by tissue heterogeneity was investigated by uniformly spraying standards beneath and on top of a whole-body zebrafish section. The quantitative relationship between the signals of the two standards was investigated across this multi-organ model to serve future qMSI experiments by IR-MALDESI and other laser ablation-based sampling methods. The overall ratio between the standards sprayed on top of and beneath the tissue sections remained constant across the entire whole-body section despite significant tissue heterogeneity (e.g., gills, heart, and liver). Additionally, we noted that thinner and/or sucrose-embedded tissues improved these ratios, which will inform future qMSI investigations., Competing Interests: Declarations Animal husbandry Mouse husbandry procedures were approved by the NCSU Institutional Animal Care and Use Committee (IACUC, #19–811-B). Zebrafish husbandry was also in accordance with institutional standard procedures (IACUC, #22–738-B). Competing interests D.C.M. is the interim chief scientific officer and part-owner of MSI Software Solutions, LLC. The other authors declare no competing interests., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature.)

Quality control and system suitability testing are vital protocols implemented to ensure the repeatability and reproducibility of data in mass spectrometry investigations. However, mass spectrometry imaging (MSI) analyses present added complexity since both chemical and spatial information are measured. Herein, we employ various machine learning algorithms and a novel quality control mixture to classify the working conditions of an MSI platform. Each algorithm was evaluated in terms of its performance on unseen data, validated with negative control data sets to rule out confounding variables or chance agreement, and utilized to determine the necessary sample size to achieve a high level of accurate classifications. In this work, a robust machine learning workflow was established where models could accurately classify the instrument condition as clean or compromised based on data metrics extracted from the analyzed quality control sample. This work highlights the power of machine learning to recognize complex patterns in MSI data and use those relationships to perform a system suitability test for MSI platforms.

Infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) uses an infrared laser to desorb neutral biomolecules with postionization via ESI at atmospheric pressure. The Gaussian profile of the laser with conventional optics results in the heating of adjacent nonablated tissue due to the energy profile being circular. A diffractive optical element (DOE) was incorporated into the optical train to correct for this disadvantage. The DOE produces a top-hat beam profile and square ablation spots, which have uniform energy distributions. Although beneficial to mass spectrometry imaging (MSI), it is unknown how the DOE affects the ability to perform quantitative MSI (qMSI). In this work, we evaluate the performance of the DOE optical train against our conventional optics to define the potential advantages of the top-hat beam profile. Absolute quantification of glutathione (GSH) was achieved by normalizing the analyte of interest to homoglutathione (hGSH), spotting a dilution series of stable isotope labeled glutathione (SIL-GSH), and analyzing by IR-MALDESI MSI with either the conventional optical train or with the DOE incorporated. Statistical comparison indicates that there was no significant difference between the quantification of GSH by the two optical trains as evidenced by similar calibration curves. Results support that both optical trains can be used for qMSI without a change in the ability to carry out absolute quantification but providing the benefits of the top-hat optical train (i.e., flat energy profile and square ablation spots)-for future qMSI studies., (© 2024 The Author(s). Journal of Mass Spectrometry published by John Wiley & Sons Ltd.)

Rationale: Silver doping of electrospray is known to increase the abundance of olefinic compounds detected by mass spectrometry. While demonstrated in targeted experiments, this has yet to be investigated in an untargeted study. Utilizing infrared matrix-assisted laser desorption electrospray ionization mass spectrometry imaging (IR-MALDESI-MSI), an untargeted lipidomics experiment on mouse liver was performed to evaluate the advantages of silver-doped electrospray., Methods: 10 ppm silver nitrate was doped into the IR-MALDESI solvent consisting of 60% acetonitrile and 0.2% formic acid. Using an Orbitrap mass spectrometer in positive ionization mode, MSI was performed, analyzing from m/z 150 to m/z 2000 to capture all lipids with potential silver adducts. The lipids detected in the control and silver-doped electrosprays were compared by annotating using the LIPID MAPS Structural Database and eliminating false positives using the metabolite annotation confidence score., Results: Silver-doped electrospray allowed for the detection of such ions of lipid molecules as [M + H] + or [M + NH 4 ] + and as [M + Ag] + . Among the ions seen as [M + H] + or [M + NH 4 ] + , the signal was comparable between the control and silver-doped electrosprays. The silver-doped electrospray led to a 10% increase in the number of detected lipids, all of which contained a bay region increasing the interaction between silver and alkenes. Silver preferentially interacted with lipids that did not contain hard bases such as phosphates., Conclusions: Silver-doped electrospray enabled detection of 10% more olefinic lipids, all containing bay regions in their putative structures. This technique is valuable for detecting previously unobserved lipids that have the potential to form bay regions, namely fatty acyls, glycerolipids, prenol lipids, and polyketides., (© 2024 The Author(s). Rapid Communications in Mass Spectrometry published by John Wiley & Sons Ltd.)

Native mass spectrometry (MS) is a powerful analytical technique to directly probe noncovalent protein-protein and protein-ligand interactions. However, not every MS platform can preserve proteins in their native conformation due to high energy deposition from the utilized ionization source. Most small molecules approved as drugs and in development interact with their targets through noncovalent interactions. Therefore, rapid methods to analyze noncovalent protein-ligand interactions are necessary for the early stages of the drug discovery pipeline. Herein, we describe a method for analyzing noncovalent protein-ligand complexes by IR-MALDESI-MS with analysis times of ∼13 s per sample. Carbonic anhydrase and the kinase domain of Bruton's tyrosine kinase are paired with known noncovalent binders to evaluate the effectiveness of native MS by IR-MALDESI.

Mass spectrometry imaging (MSI) has become a significant tool for measuring chemical species in biological tissues, where much of the impact of these platforms lies in their capability to report the spatial distribution of analytes for correlation to sample morphology. As a result, enhancement of spatial resolution has become a frontier of innovation in the field, and necessary developments are dependent on the ionization source. More particularly, laser-based imaging sources may require modifications to the optical train or alternative sampling techniques. These challenges are heightened for systems with infrared (IR) lasers, as their operating wavelength generates spot sizes that are inherently larger than their ultraviolet counterparts. Recently, the infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) source has shown the utility of a diffractive optical element (DOE) to produce square ablation patterns, termed top-hat IR-MALDESI. If the DOE optic is combined with oversampling methods, smaller ablation volumes can be sampled to render higher spatial resolution imaging experiments. Further, this approach enables reproducible spot sizes and ablation volumes for better comparison between scans. Herein, we investigate the utility of oversampling with top-hat IR-MALDESI to enhance the spatial resolution of measured lipids localized within the head of sectioned zebrafish tissue. Four different spatial resolutions were evaluated for data quality (e.g., mass measurement accuracy, spectral accuracy) and quantity of annotations. Other experimental parameters to consider for high spatial resolution imaging are also discussed. Ultimately, 20 μm spatial resolution was achieved in this work and supports feasibility for use in future IR-MALDESI studies.

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., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature.)

With implications in several medical conditions, N-linked glycosylation is one of the most important posttranslation modifications present in all living organisms. Due to their nontemplate synthesis, glycan structures are extraordinarily complex and require multiple analytical techniques for complete structural elucidation. Mass spectrometry is the most common way to investigate N-linked glycans; however, with techniques such as liquid-chromatography mass spectrometry, there is complete loss of spatial information. Mass spectrometry imaging is a transformative analytical technique that can visualize the spatial distribution of ions within a biological sample and has been shown to be a powerful tool to investigate N-linked glycosylation. This review covers the fundamentals of mass spectrometry imaging and N-linked glycosylation and highlights important findings of recent key studies aimed at expanding and improving the glycomics imaging field., (© 2024 The Author(s). Mass Spectrometry Reviews published by John Wiley & Sons Ltd.)

Artemisinin is the leading medication for the treatment of malaria and is only produced naturally in Artemisia annua . The localization of artemisinin in both the glandular and non-glandular trichomes of the plant makes it an ideal candidate for mass spectrometry imaging (MSI) as a model system for method development. Infrared matrix-assisted laser desorption electrospray ionization MSI (IR-MALDESI-MSI) has the capability to detect hundreds to thousands of analytes simultaneously, providing abundance information in conjunction with species localization throughout a sample. The development of several new optical trains and their application to the IR-MALDESI-MSI platform has improved data quality in previous proof-of-concept experiments but has not yet been applied to analysis of native biological samples, especially the MSI analysis of plants. This study aimed to develop a workflow and optimize MSI parameters, specifically the laser optical train, for the analysis of Artemisia annua with the NextGen IR-MALDESI platform coupled to an Orbitrap Exploris 240 mass spectrometer. Two laser optics were compared to the conventional set up, of which include a Schwarzschild-like reflective objective and a diffractive optical element (DOE). These optics, respectively, enhance the spatial resolution of imaging experiments or create a square spot shape for top-hat imaging. Ultimately, we incorporated and characterized three different optical trains into our analysis of Artemisia annua to study metabolites in the artemisinin pathway. These improvements in our workflow, resulted in high spatial resolution and improved ion abundance from previous work, which will allow us to address many different questions in plant biology beyond this model system.

Rationale: Mass spectrometry imaging (MSI) elevates the power of conventional mass spectrometry (MS) to multidimensional space, elucidating both chemical composition and localization. However, the field lacks any robust quality control (QC) and/or system suitability testing (SST) protocols to monitor inconsistencies during data acquisition, both of which are integral to ensure the validity of experimental results. To satisfy this demand in the community, we propose an adaptable QC/SST approach with five analyte options amendable to various ionization MSI platforms (e.g., desorption electrospray ionization, matrix-assisted laser desorption/ionization [MALDI], MALDI-2, and infrared matrix-assisted laser desorption electrospray ionization [IR-MALDESI])., Methods: A novel QC mix was sprayed across glass slides to collect QC/SST regions-of-interest (ROIs). Data were collected under optimal conditions and on a compromised instrument to construct and refine the principal component analysis (PCA) model in R. Metrics, including mass measurement accuracy and spectral accuracy, were evaluated, yielding an individual suitability score for each compound. The average of these scores is utilized to inform if troubleshooting is necessary., Results: The PCA-based SST model was applied to data collected when the instrument was compromised. The resultant SST scores were used to determine a statistically significant threshold, which was defined as 0.93 for IR-MALDESI-MSI analyses. This minimizes the type-I error rate, where the QC/SST would report the platform to be in working condition when cleaning is actually necessary. Further, data scored after a partial cleaning demonstrate the importance of QC and frequent full instrument cleaning., Conclusions: This study is the starting point for addressing an important issue and will undergo future development to improve the efficiency of the protocol. Ultimately, this work is the first of its kind and proposes this approach as a proof of concept to develop and implement universal QC/SST protocols for a variety of MSI platforms., (© 2024 The Authors. Rapid Communications in Mass Spectrometry published by John Wiley & Sons Ltd.)

Mass spectrometry imaging (MSI) is an analytical technique that enables the simultaneous detection of hundreds to thousands of chemical species while retaining their spatial information; usually, MSI is applied to biological tissues. Combining these elements can create ion images, which allows for the identification and localization of multiple chemical species within the sample. Being able to produce molecular images of biological tissues has already impacted the study of health and disease; however, the next logical step is being able to combine MSI with quantitative mass spectrometry methods to both quantify and determine the localization of disease progression or drug action. In this tutorial, we will detail the main factors to consider when designing a qMSI experiment and highlight the methods that have been developed to overcome these added complexities, specifically for those newer to the field of MSI., (© 2024 The Authors. Journal of Mass Spectrometry published by John Wiley & Sons Ltd.)

Glycans are complex structures that require MS/MS for detailed structural elucidation. Incorporating metals can provide more structural information by inhibiting glycosidic cleavage and enhancing cross-ring fragmentation. A direct analysis was performed using lithium doping and IR-MALDESI to induce cross-ring fragmentation of glycans. The protonated and lithiated versions of the two glycans were isolated and subjected to HCD. For protonated glycans, only glycosidic cleavages were observed. Using lithium doping, MS/MS consisted of abundant cross-ring fragments. Seventeen cross-ring fragments were detected across both glycans using lithium-doped ESI. This is the first incorporation of metal doping in IR-MALDESI to achieve cross-ring fragments in MS/MS analysis.

Novel mass spectrometry (MS) based analytical platforms have enabled scientists to detect and quantify molecules within biological and environmental samples more accurately. Novel MS instrumentation starts as a prototype and, after years of development, can become a commercial product to be used by the larger MS community. Without the initial prototype, many MS-based instruments today would not be produced. Additionally, biotechnology companies are the main drivers for research, development, and production of novel instruments, but the tools for prototyping instrumentation have never been more accessible. Here, we present a tutorial on prototyping instrumentation through the case study of developing the Next Generation IR-MALDESI source to show that an engineering degree is not required to design and construct a prototype instrument with modern hardware and software. We discuss the prototyping process, the necessary skills required for efficient prototyping, and information about common hardware and software used within initial prototypes., (© 2023 The Authors. Journal of Mass Spectrometry published by John Wiley & Sons Ltd.)

Rationale: Infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) utilizes a 2970 nm mid-IR laser to desorb samples with depth resolutions (Z) on the order of micrometers. Conventionally, 5-20 μm thick tissue sections are used to characterize different applications of the IR-MALDESI source, but an optimal thickness has not been systematically investigated., Methods: Mouse liver was sectioned to various thicknesses and analyzed using IR-MALDESI mass spectrometry imaging (MSI). Height profiles of tissue sections of various cryosectioned thicknesses were acquired to affirm tissue thickness. Tissue sections of each thickness were measured using a Keyence microscope. Paraffin wax was cryosectioned, mounted on microscope slides, and measured using a chromatic confocal sensor system to determine the cryostat sectioning accuracy., Results: Analyzing sectioned tissues at higher thickness (>10 μm) leads to lower ion abundance, a decrease in signal over long analysis times, and more frequent instrument cleaning. Additionally, increasing tissue thickness above the optimum (7 μm) does not result in a significant increase in lipid annotations., Conclusions: This work defines an optimal sample thickness for IR-MALDESI-MSI and demonstrates the utility of optimizing tissue thickness for MSI platforms of comparable Z resolution., (© 2023 The Authors. Rapid Communications in Mass Spectrometry published by John Wiley & Sons Ltd.)

Infrared matrix-assisted laser desorption electrospray ionization mass spectrometry imaging (IR-MALDESI) conventionally utilizes fresh-frozen biological tissues with an ice matrix to improve the detection of analytes. Sucrose-embedding with paraformaldehyde fixation has demonstrated feasibility as an alternative matrix for analysis by IR-MALDESI by preserving tissue features and enhancing ionization of lipids. However, investigating multi-organ systems provides broader context for a biological study and can elucidate more information about a disease state as opposed to a single organ. Danio rerio, or zebrafish, are model organisms for various disease states and can be imaged as a multi-organ sample to analyze morphological and metabolomic preservation as a result of sample preparation. Herein, whole-body zebrafish were imaged to compare sucrose-embedding with paraformaldehyde fixation against conventional fresh-frozen sample preparation. Serial sections were analyzed with and without an ice matrix to evaluate if sucrose functions as an alternative energy-absorbing matrix for IR-MALDESI applications across whole-body tissues. The resulting four conditions were compared in terms of total putative lipid annotations and category diversity, coverage across the entire m/z range, and ion abundance. Ultimately, sucrose-embedded zebrafish had an increase in putative lipid annotations for the combination of putative annotations with and without the application of an ice matrix relative to fresh-frozen tissues which require the application of an ice matrix. Upon the use of an ice matrix, a greater number of high mass putative lipid annotations (e.g., glycerophospholipids, glycerolipids, and sphingolipids) were identified. Conversely, without an ice matrix, sucrose-embedded sections elucidated more putative annotations in lower molecular weight lipids, including fatty acyls and sterol lipids. Similar to the mouse brain model, sucrose-embedding increased putative lipid annotation and abundance for whole-body zebrafish., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature.)

Mass spectrometry imaging (MSI) is an analytical technique capable of measuring and visualizing the spatial distribution of thousands of ions across a sample. Measured ions can be putatively identified and annotated by comparing their mass-to-charge ratio ( m / z ) to a database of known compounds. For high-resolution, accurate mass (HRAM) imaging data sets, this is commonly performed by the annotation platform METASPACE. Annotations are reported with a metabolite-signal-match (MSM) score as a measure of the annotation's confidence level. However, the MSM scores reported by METASPACE often do not reflect a reasonable confidence level of an annotation and are not assigned consistently. The metabolite annotation confidence score (MACS) is an alternative scoring system based on fundamental mass spectrometry imaging metrics (mass measurement accuracy, spectral accuracy, and spatial distribution) to generate values that reflect the confidence of a specific annotation in HRAM-MSI data sets. Herein, the MACS system is characterized and compared to MSM scores from ions annotated by METASPACE.

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.

Mass spectrometry imaging (MSI) is an analytical technique that can detect and visualize thousands of m/z values resolved in two- and three-dimensional space. These m/z values lead to hundreds of molecular annotations, including on-tissue and background ions. Discrimination of sample-related analytes from ambient ions conventionally involves manual investigation of each ion heatmap, which requires significant researcher time and effort (for a single tissue image, it can take an hour to determine on-tissue and off-tissue species). Moreover, manual investigation lends itself to subjectivity. Herein, we present the utility of an ion classification tool (ICT) developed using object-based image analysis in MATLAB. The ICT functions by segmenting ion heatmap images into on-tissue and off-tissue objects through binary conversion. The binary images are analyzed and within seconds used to classify the ions as on-tissue or background using a binning approach based on the number of detected objects. In a representative dataset with 50 randomly selected annotations, the ICT was able to accurately classify 45/50 ions as on-tissue or background., (© 2023. Springer-Verlag GmbH Germany, part of Springer Nature.)

N -linked glycosylation represents a structurally diverse, complex, co- and posttranslational protein modification that bridges metabolism and cellular signaling. Consequently, aberrant protein glycosylation is a hallmark of most pathological scenarios. Due to their complex nature and non-template-driven synthesis, the analysis of glycans is faced with several challenges, underlining the need for new and improved analytical technologies. Spatial profiling of N -glycans through direct imaging on tissue sections reveals the regio-specific and/or disease pathology correlating tissue N -glycans that serve as a disease glycoprint for diagnosis. Infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) is a soft hybrid ionization technique that has been used for diverse mass spectrometry imaging (MSI) applications. Here, we report the first spatial analysis of the brain N -linked glycans by IR-MALDESI MSI, leading to a significant increase in the detection of the brain N -sialoglycans. A formalin-fixed paraffin-embedded mouse brain tissue was analyzed in negative ionization mode after tissue washing, antigen retrieval, and pneumatic application of PNGase F for enzymatic digestion of N -linked glycans. We report a comparative analysis of section thickness on the N -glycan detection using IR-MALDESI. One hundred thirty-six unique N -linked glycans were confidently identified in the brain tissue (with an additional 132 unique N -glycans, not reported in GlyConnect), where more than 50% contained sialic acid residues, which is approximately 3-fold higher than the previous reports. This work demonstrates the first application of IR-MALDESI in N -linked glycan imaging of the brain tissue, leading to a 2.5-fold increase in the in situ total brain N -glycan detection compared to the current gold standard of positive-mode matrix-assisted laser desorption/ionization mass spectrometry imaging. This is also the first report of the application of the MSI toward the identification of sulfoglycans in the rodent brain. Overall, IR-MALDESI-MSI presents a sensitive glycan detection platform to identify tissue-specific and/or disease-specific glycosignature in the brain while preserving the sialoglycans without any chemical derivatization.

Two-dimensional mass spectrometry imaging (2D MSI) experiments mainly involve samples with a flat surface and constant thickness, but some samples are challenging to section due to the texture and topography. Herein, we present an MSI method that automatically corrects for discernible height differences across surfaces during imaging experiments. A chromatic confocal sensor was incorporated into the infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) system to measure the sample surface height at the location of each analytical scan. The height profile is subsequently used for adjusting the z -axis position of the sample during MSI data acquisition. We evaluated this method using a tilted mouse liver section and an unsectioned Prilosec tablet due to their exterior quasi-homogeneity and height differences of approximately ∼250 μm. MSI with automatic z -axis correction showed consistent ablated spot sizes and shapes, revealing the measured ion spatial distribution across a mouse liver section and a Prilosec tablet. Conversely, irregular spots and reduced signals with large variability were observed when no z -axis correction was applied.

Sialic acids play several roles in both physiological and pathological processes; however, due to their labile nature, they are difficult to analyze using mass spectrometry. Previous work has shown that infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) is able to detect intact sialylated N -linked glycans without the use of chemical derivatization. In this work, we describe a new rule that can predict the number of sialic acids on a glycan. Formalin-fixed paraffin-embedded human kidney tissue was prepared using previously established methods and analyzed using IR-MALDESI in negative-ion mode mass spectrometry. Using the experimental isotopic distribution of a detected glycan, we can predict the number of sialic acids on the glycan; #sialic acids is equal to the charge state minus the number of chlorine adducts, or z - #Cl - . This new rule grants confident glycan annotations and compositions beyond accurate mass measurements, thereby further improving the capability of IR-MALDESI to study sialylated N -linked glycans within biological tissues.

The collection of profile data is standard practice within the field of mass spectrometry (MS). However, profile data collection often results in large data files that require extensive processing times, especially in mass spectrometry imaging (MSI) studies where thousands of high-resolution scans are recorded. Natively collecting centroid MS data is an alternative that effectively reduces both the resulting file size and the data processing time. Herein, high-resolution accurate mass (HRAM) Orbitrap MSI data on mouse liver tissue sections without automatic gain control (AGC) were natively collected in both profile and centroid modes and compared based on the file size and processing time. Additionally, centroid data were evaluated against the profile data with regard to the spectra integrity, mass measurement accuracy (MMA), and the number of lipid annotations to ensure that centroid data did not compromise the data quality. For both native and postacquisition centroided data, the variation in mass measurement accuracy decreased relative to the profile data collection. Furthermore, centroid data collection increased the number of METASPACE database annotations indicating higher sensitivity and greater accuracy for lipid annotation compared to native profile data collection. Profile MSI data was shown to have a higher likelihood of false positive identifications due to an increased number of data points on either side of the peaks, whereas the same trend was not observed in data collected in native centroid data collection. This publication explores and explains the importance in properly centroiding MSI data, either natively or by adequate centroiding methods, to obtain the most accurate information and come to the best conclusions. These data support that natively collecting centroid data significantly improves MMA to sub-ppm levels without AGC and reduces false positive annotations.

Numerous preparatory methods have been developed to preserve the cellular and structural integrity of various biological tissues for different -omics studies. Herein, two preparatory methods for mass spectrometry imaging (MSI) were evaluated, fresh-frozen and sucrose-embedded, paraformaldehyde (PFA) fixed, in terms of ion abundance, putative lipid identifications, and preservation of analyte spatial distributions. Infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI)-MSI was utilized to compare the preparatory methods of interest with and without the use of the conventional ice matrix. There were 2.5-fold and 1.6-fold more lipid species putatively identified in positive- and negative-ion modes, respectively, for sucrose-embedded, PFA-fixed tissues without an ice matrix relative to the current IR-MALDESI-MSI gold-standard, fresh-frozen tissue preparation with an exogenous ice matrix. Furthermore, sucrose-embedded tissues demonstrated improved spatial distribution of ions resulting from the cryo-protective property of sucrose and paraformaldehyde fixation. Evidence from these investigations supports sucrose-embedding without ice matrix as an alternative preparatory technique for IR-MALDESI-MSI.

Biospecimens with nearly flat surfaces on a flat stage are typically required for laser-based mass spectrometry imaging (MSI) techniques. However, sampling stages are rarely perfectly level, and accounting for this and the need to accommodate non-flat samples requires a deeper understanding of the laser beam depth of focus. In ablation-based MSI methods, a laser is focused on top of the sample surface, ensuring that the sample is at the focal point or remains within depth of focus. In general, the depth of focus of a given laser is related to the beam quality (M 2 ) and the wavelength (λ). However, because laser is applied on a biological sample, other variables can also impact the depth of focus, which could affect the robustness of the MSI techniques for diverse sample types. When the height of a sample ranges outside of the depth of focus, ablated area and the corresponding ion abundances may vary as well, increasing the variability of results. In this tutorial, we examine the parameters and equations that describe the depth of focus of a Gaussian laser beam. Additionally, we describe several approaches that account for surface roughness exceeding the depth of focus of the laser., (© 2023 The Authors. Journal of Mass Spectrometry published by John Wiley & Sons Ltd.)

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., (© 2023 The Authors. Journal of Mass Spectrometry published by John Wiley & Sons Ltd.)

Mass spectrometry imaging (MSI) is an important analytical technique that simultaneously reports the spatial location and abundance of detected ions in biological, chemical, clinical, and pharmaceutical studies. As MSI grows in popularity, it has become evident that data reporting varies among different research groups and between techniques. The lack of consistency in data reporting inherently creates additional challenges in comparing intra- and inter-laboratory MSI data. In this tutorial, we propose a unified data reporting system, SMART, based on the common features shared between techniques. While there are limitations to any reporting system, SMART was decided upon after significant discussion to more easily understand and benchmark MSI data. SMART is not intended to be comprehensive but rather capture essential baseline information for a given MSI study; this could be within a study (e.g., effect of spot size on the measured ion signals) or between two studies (e.g., different MSI platform technologies applied to the same tissue type). This tutorial does not attempt to address the confidence with which annotations are made nor does it deny the importance of other parameters that are not included in the current SMART format. Ultimately, the goal of this tutorial is to discuss the necessity of establishing a uniform reporting system to communicate MSI data in publications and presentations in a simple format to readily interpret the parameters and baseline outcomes of the data., (© 2023 The Authors. Journal of Mass Spectrometry published by John Wiley & Sons Ltd.)

Many mass spectrometry imaging (MSI) applications such as infrared matrix-assisted electrospray ionization (IR-MALDESI) employ an infrared (IR) laser with a Gaussian profile where laser irradiance is highest in the center and decreases exponentially. To enable full ablation of a square region of interest, oversampling is often needed, which results in nonuniform ablation and leads to decreased image quality. A diffractive optical element (DOE) was integrated into the optical path to generate homogeneous intensity distributions while maintaining laser energy above the ablation threshold, to enable complete sample removal from laser pulses without oversampling. 2D and 3D imaging with the DOE inserted show clear and sharp ablation patterns with satisfactory biological signals gained. Further improvements will optimize the beam profile and generate a square top-hat laser beam for MSI application at higher spatial resolution.

In the past 15 years, ambient ionization techniques have witnessed a significant incursion into the field of mass spectrometry imaging, demonstrating their ability to provide complementary information to matrix-assisted laser desorption ionization. Matrix-assisted laser desorption electrospray ionization is one such technique that has evolved since its first demonstrations with ultraviolet lasers coupled to Fourier transform-ion cyclotron resonance mass spectrometers to extensive use with infrared lasers coupled to orbitrap-based mass spectrometers. Concurrently, there have been transformative developments of this imaging platform due to the high level of control the principal group has retained over the laser technology, data acquisition software (RastirX), instrument communication, and image processing software (MSiReader). This review will discuss the developments of MALDESI since its first laboratory demonstration in 2005 to the most recent advances in 2021., (© 2021 John Wiley & Sons Ltd.)

High-throughput screening (HTS) is a technique mostly used by pharmaceutical companies to rapidly screen multiple libraries of compounds to find drug hits with biological or pharmaceutical activity. Mass spectrometry (MS) has become a popular option for HTS given that it can simultaneously resolve hundreds to thousands of compounds without additional chemical derivatization. For this application, it is convenient to do direct analysis from well plates. Herein, we present the development of an infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) source coupled directly to an Agilent 6545 for direct analysis from well plates. The source is coupled to a quadrupole time-of-flight (Q-TOF) mass spectrometer to take advantage of the high acquisition rates without sacrificing resolving power as required with Orbitrap or Fourier-transform ion cyclotron resonance (FTICR) instruments. The laser used for this source operates at 100 Hz, firing 1 pulse-per-burst, and delivers around 0.7 mJ per pulse. Continuously firing this laser for an extended duration makes it a quasi-continuous ionization source. Additionally, a metal capillary was constructed to extend the inlet of the mass spectrometer, increase desolvation of electrospray charged droplets, improve ion transmission, and increase sensitivity. Its efficiency was compared with the conventional dielectric glass capillary by measured signal and demonstrated that the metal capillary increased ionization efficiency due to its more uniformly distributed temperature gradient. Finally, we present the functionality of the source by analyzing tune mix directly from well plates. This source is a proof of concept for HTS applications using IR-MALDESI coupled to a different MS platform., (© 2023 The Authors. Journal of Mass Spectrometry published by John Wiley & Sons Ltd.)

Rationale: The level of visual detail of a mass spectrometry image is dependent on the spatial resolution with which it is acquired, which is largely determined by the focal diameter in infrared laser ablation-based techniques. While the use of mid-IR light for mass spectrometry imaging (MSI) has advantages, it results in a relatively large focal diameter and spatial resolution. The continual advancement of infrared matrix-assisted electrospray ionization (IR-MALDESI) for MSI warranted novel methods to decrease laser ablation areas and thus improve spatial resolution., Methods: In this work, a Schwarzschild-like reflective objective was incorporated into the novel NextGen IR-MALDESI source and characterized on both burn paper and mammalian tissue using an ice matrix. Ablation areas, mass spectra, and annotations obtained using the objective were compared against the current optical train on the NextGen system without modification., Results: The effective resolution was determined to be 55 μm by decreasing the step size until oversampling was observed. Use of the objective improved the spatial resolution by a factor of three as compared against the focus lens., Conclusions: A Schwarzschild-like reflective objective was successfully incorporated into the NextGen source and characterized on mammalian tissue using an ice matrix. The corresponding improvement in spatial resolution facilitates the future expansion of IR-MALDESI applications to include those that require fine structural detail., (© 2022 The Authors. Rapid Communications in Mass Spectrometry published by John Wiley & Sons Ltd.)

Mass spectrometry imaging (MSI) data visualization relies on heatmaps to show the spatial distribution and measured abundances of molecules within a sample. Nonuniform color gradients such as jet are still commonly used to visualize MSI data, increasing the probability of data misinterpretation and false conclusions. Also, the use of nonuniform color gradients and the combination of hues used in common colormaps make it challenging for people with color vision deficiencies (CVDs) to visualize and accurately interpret data. Here we present best practices for choosing a colormap to accurately display MSI data, improve readability, and accommodate all CVDs. We also provide other resources on the misuse of color in the scientific field and resources on scientifically derived colormaps presented herein., (© 2022 The Authors. Journal of Mass Spectrometry published by John Wiley & Sons Ltd.)

Rationale: The development and characterization of the novel NextGen infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) source catalyzed new advancements in IR-MALDESI instrumentation, including the development of a new analysis geometry., Methods: A vertically oriented transmission mode (tm)-IR-MALDESI setup was developed and optimized on thawed mouse tissue. In addition, glycerol was introduced as an alternative energy-absorbing matrix for tm-IR-MALDESI because the new geometry does not currently allow for the formation of an ice matrix. The tm geom was evaluated against the optimized standard geometry for the NextGen source in reflection mode (rm)., Results: It was found that tm-IR-MALDESI produces comparable results to rm-IR-MALDESI after optimization. The attempt to incorporate glycerol as an alternative matrix provided little improvement to tm-IR-MALDESI ion abundances., Conclusions: This work has successfully demonstrated the adaptation of the NextGen IR-MALDESI source through the feasibility of tm-IR-MALDESI mass spectrometry imaging on mammalian tissue, expanding future biological applications of the method., (© 2022 The Authors. Rapid Communications in Mass Spectrometry published by John Wiley & Sons Ltd.)

Although glutathione plays a key role in cancer cell viability and therapy response there is no clear trend in relating the level of this antioxidant to clinical stage, histological grade, or therapy response in patient tumors. The likely reason is that static levels of glutathione are not a good indicator of how a tissue deals with oxidative stress. A better indicator is the functional capacity of the tissue to maintain glutathione levels in response to this stress. However, there are few methods to assess glutathione metabolic function in tissue. We have developed a novel functional mass spectrometry imaging (fMSI) method that can map the variations in the conversion of glycine to glutathione metabolic activity across tumor tissue sections by tracking the fate of three glycine isotopologues administered in a timed sequence to tumor-bearing anesthetized mice. This fMSI method generates multiple time point kinetic data for substrate uptake and glutathione production from each spatial location in the tissue. As expected, the fMSI data shows glutathione metabolic activity varies across the murine 4T1 mammary tumor. Although glutathione levels are highest at the tumor periphery there are regions of high content but low metabolic activity. The timed infusion method also detects variations in delivery of the glycine isotopologues thereby providing a measure of tissue perfusion, including evidence of intermittent perfusion, that contributes to the observed differences in metabolic activity. We believe this new approach will be an asset to linking molecular content to tissue function., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Amyotrophic lateral sclerosis (ALS) is an idiopathic, fatal neurodegenerative disease characterized by progressive loss of motor function with an average survival time of 2-5 years after diagnosis. Due to the lack of signature biomarkers and heterogenous disease phenotypes, a definitive diagnosis of ALS can be challenging. Comprehensive investigation of this disease is imperative to discovering unique features to expedite the diagnostic process and improve diagnostic accuracy. Here, we present untargeted metabolomics by mass spectrometry imaging (MSI) for comparing sporadic ALS (sALS) and C9orf72 positive (C9Pos) post-mortem frontal cortex human brain tissues against a control cohort. The spatial distribution and relative abundance of metabolites were measured by infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) MSI for association to biological pathways. Proteomic studies on the same patients were completed via LC-MS/MS in a previous study, and results were integrated with imaging metabolomics results to enhance the breadth of molecular coverage. Utilizing METASPACE annotation platform and MSiPeakfinder, nearly 300 metabolites were identified across the sixteen samples, where 25 were identified as dysregulated between disease cohorts. The dysregulated metabolites were further examined for their relevance to alanine, aspartate, and glutamate metabolism, glutathione metabolism, and arginine and proline metabolism. The dysregulated pathways discussed are consistent with reports from other ALS studies. To our knowledge, this work is the first of its kind, reporting on the investigation of ALS post-mortem human brain tissue analyzed by multiomic MSI.

Infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) is a hybrid, ambient ionization source that combines the advantages of electrospray ionization and matrix-assisted laser desorption/ionization, making it a versatile tool for both high-throughput screening (HTS) and mass spectrometry imaging (MSI) studies. To expand the capabilities of the IR-MALDESI source, an entirely new architecture was designed to overcome the key limitations of the previous source. This next-generation (NextGen) IR-MALDESI source features a vertically mounted IR-laser, a planar translation stage with computerized sample height control, an aluminum enclosure, and a novel mass spectrometer interface plate. The NextGen IR-MALDESI source has improved user-friendliness, improved overall versatility, and can be coupled to numerous Orbitrap mass spectrometers to accommodate more research laboratories. In this work, we highlight the benefits of the NextGen IR-MALDESI source as an improved platform for MSI and direct analysis. We also optimize the NextGen MALDESI source component geometries to increase target ion abundances over a wide m / z range. Finally, documentation is provided for each NextGen IR-MALDESI part so that it can be replicated and incorporated into any lab space.

Most mass spectrometry imaging (MSI) methods provide a molecular map of tissue content but little information on tissue function. Mapping tissue function is possible using several well-known examples of "functional imaging" such as positron emission tomography and functional magnetic resonance imaging that can provide the spatial distribution of time-dependent biological processes. These functional imaging methods represent the net output of molecular networks influenced by local tissue environments that are difficult to predict from molecular/cellular content alone. However, for decades, MSI methods have also been demonstrated to provide functional imaging data on a variety of biological processes. In fact, MSI exceeds some of the classic functional imaging methods, demonstrating the ability to provide functional data from the nanoscale (subcellular) to whole tissue or organ level. This Perspective highlights several examples of how different MSI ionization and detection technologies can provide unprecedented detailed spatial maps of time-dependent biological processes, namely, nucleic acid synthesis, lipid metabolism, bioenergetics, and protein metabolism. By classifying various MSI methods under the umbrella of "functional MSI", we hope to draw attention to both the unique capabilities and accessibility with the aim of expanding this underappreciated field to include new approaches and applications.

In mass spectrometry imaging (MSI) applications of infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI), an exogenous ice layer is the gold standard for an energy-absorbing matrix. However, the formation of the ice matrix requires additional time and instrument hardware, so glycerol was investigated herein as an alternative to the ice matrix to potentially improve spatial resolution and ionization, while decreasing experiment time. Glycerol solutions of varying concentrations were sprayed over top of rat liver tissue sections for analysis by IR-MALDESI and compared to the typical ice matrix condition. Additionally, we tested if combining the ice matrix and glycerol matrix would further improve analyses. Matrix conditions were evaluated by comparing ion abundance of six lipid species, the laser ablation spot diameter, and number of METASPACE annotations. The ion abundances were also normalized to the volume of tissue ablated to correct for lower abundance values due to less ablated tissue. It was observed that utilizing a 50% glycerol matrix without ice provides improved spatial resolution with lipid abundances and annotations comparable to the ice matrix standard, while decreasing the time required to complete an IR-MALDESI tissue imaging experiment., (© 2022 The Authors. Journal of Mass Spectrometry published by John Wiley & Sons Ltd.)

Ependymal cells (ECs) line the ventricular surfaces of the mammalian central nervous system (CNS) and their development is indispensable to structural integrity and functions of the CNS. We previously reported that EC-specific genetic deletion of the myristoylated alanine-rich protein kinase C substrate (Marcks) disrupts barrier functions and elevates oxidative stress and lipid droplet accumulation in ECs causing precocious cellular aging. However, little is known regarding the mechanisms that mediate these changes in ECs. To gain insight into Marcks-mediated mechanisms, we performed mass spectrometric analyses on Marcks-associated proteins in young and aged ECs in the mouse forebrain using an integrated approach. Network analysis on annotated proteins revealed that the identified Marcks-associated complexes are in part involved in protein transport mechanisms in young ECs. In fact, we found perturbed intracellular vesicular trafficking in cultured ECs with selective deletion of Marcks (Marcks-cKO mice), or upon pharmacological alteration to phosphorylation status of Marcks. In comparison, Marcks-associated protein complexes in aged ECs appear to be involved in regulation of lipid metabolism and responses to oxidative stress. Confirming this, we found elevated signatures of inflammation in the cerebral cortices and the hippocampi of young Marcks-cKO mice. Interestingly, behavioral testing using a water maze task indicated that spatial learning and memory is diminished in young Marcks-cKO mice similar to aged wildtype mice. Taken together, our study provides first line of evidence for potential mechanisms that may mediate differential Marcks functions in young and old ECs, and their effect on forebrain homeostasis during aging., (© 2022. The Author(s), under exclusive licence to American Aging Association.)

Dietary fructose, especially in the context of a high-fat western diet, has been linked to type 2 diabetes. Although the effect of fructose on liver metabolism has been extensively studied, a significant portion of the fructose is first metabolized in the small intestine. Here, we report that dietary fat enhances intestinal fructose metabolism, which releases glycerate into the blood. Chronic high systemic glycerate levels induce glucose intolerance by slowly damaging pancreatic islet cells and reducing islet sizes. Our findings provide a link between dietary fructose and diabetes that is modulated by dietary fat., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Native Americans domesticated maize ( Zea mays ssp. mays ) from lowland teosinte parviglumis ( Zea mays ssp. parviglumis) in the warm Mexican southwest and brought it to the highlands of Mexico and South America where it was exposed to lower temperatures that imposed strong selection on flowering time. Phospholipids are important metabolites in plant responses to low-temperature and phosphorus availability and have been suggested to influence flowering time. Here, we combined linkage mapping with genome scans to identify High PhosphatidylCholine 1 ( HPC1 ), a gene that encodes a phospholipase A1 enzyme, as a major driver of phospholipid variation in highland maize. Common garden experiments demonstrated strong genotype-by-environment interactions associated with variation at HPC1, with the highland HPC1 allele leading to higher fitness in highlands, possibly by hastening flowering. The highland maize HPC1 variant resulted in impaired function of the encoded protein due to a polymorphism in a highly conserved sequence. A meta-analysis across HPC1 orthologs indicated a strong association between the identity of the amino acid at this position and optimal growth in prokaryotes. Mutagenesis of HPC1 via genome editing validated its role in regulating phospholipid metabolism. Finally, we showed that the highland HPC1 allele entered cultivated maize by introgression from the wild highland teosinte Zea mays ssp. mexicana and has been maintained in maize breeding lines from the Northern United States, Canada, and Europe. Thus, HPC1 introgressed from teosinte mexicana underlies a large metabolic QTL that modulates phosphatidylcholine levels and has an adaptive effect at least in part via induction of early flowering time.

Untargeted analyses in mass spectrometry imaging produce hundreds of ion images representing spatial distributions of biomolecules in biological tissues. Due to the large diversity of ions detected in untargeted analyses, normalization standards are often difficult to implement to account for pixel-to-pixel variability in imaging studies. Many normalization strategies exist to account for this variability, but they largely do not improve image quality. In this study, we present a new approach for improving image quality and visualization of tissue features by application of sequential paired covariance (SPC). This approach was demonstrated using previously published tissue datasets such as rat brain and human prostate with different biomolecules like metabolites and N-linked glycans. Data transformation by SPC improved ion images resulting in increased smoothing of biological features compared with commonly used normalization approaches., (© 2022 The Authors. Journal of Mass Spectrometry published by John Wiley & Sons Ltd.)

Rationale: The ability to perform absolute quantitation and non-targeted analysis on a single mass spectrometry instrument would be advantageous to many researchers studying per- and polyfluoroalkyl substances (PFAS). High-resolution accurate mass (HRAM) instrumentation (typically deployed for non-targeted work) carries several advantages over traditional triple quadrupole workflows when performing absolute quantitation. Processing this data using a vendor-neutral software would promote collaboration for these environmental studies., Methods: LC-MS (Orbitrap Exploris 240) was used for absolute quantitation of 45 PFAS using precursor (MS1) peak areas for quantitation, whereas isotope pattern matching and fragmentation (MS2) pattern matching were used for qualitative identification. In addition, a fluorinated chromatographic column achieved superior separation compared to the typical C18 columns typically used in PFAS analyses. This method was validated across eight different chemical classes using recommended guidelines found in EPA Method 537.1 and Skyline data processing software., Results: The validated limits of all 45 compounds, as well as metrics or accuracy and reproducibility, are reported. Most compounds achieved limits of quantitation in the range of 2-50 ng/L. Four newly released Chemours-specific compounds (PEPA, PFO3OA, PFO4DA, and PFO5DoA) were also validated. Aspects of data analysis specific to high resolving power absolute quantitation are reviewed as are the details of processing these data via Skyline., Conclusions: This method shows the feasibility of performing reproducible absolute quantitation of PFAS on an HRAM platform and does so using an open-source vendor-neutral data processing software to facilitate sharing of data across labs and institutions., (© 2022 The Authors. Rapid Communications in Mass Spectrometry published by John Wiley & Sons Ltd.)

Mass spectrometry (MS) is an effective analytical tool for high-throughput screening (HTS) in the drug discovery field. Infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) MS is a high-throughput platform that has achieved analysis times of sub-seconds-per-sample. Due to the high-throughput analysis speed, methods are needed to increase the analyte signal while decreasing the variability in IR-MALDESI-MS analyses to improve data quality and reduce false-positive hits. The Z-factor is used as a statistic of assay quality that can be improved by reducing the variation of target ion abundances or increasing signal. Herein we report optimal solvent compositions for increasing measured analyte abundances with direct analysis by IR-MALDESI-MS. We also evaluate normalization strategies, such as adding a normalization standard that is similar or dissimilar in structure to the model target drug, to reduce the variability of measured analyte abundances with direct analyses by IR-MALDESI-MS in both positive and negative ionization modes., (© 2022 The Authors. Journal of Mass Spectrometry published by John Wiley & Sons Ltd.)

Due to the high association of glutathione metabolism perturbation with a variety of disease states, there is a dire need for analytical techniques to study glutathione kinetics. Additionally, the elucidation of microenvironmental effects on changes in glutathione metabolism would significantly improve our understanding of the role of glutathione in disease. We therefore present a study combining a multiple infusion start time protocol, stable isotope labeling technology, infrared matrix-assisted laser desorption electrospray ionization, and high-resolution accurate mass-mass spectrometry imaging to study spatial changes in glutathione kinetics across in sectioned mouse liver tissues. After injecting a mouse with the isotopologues [2- 13 C, 15 N]-glycine, [1,2- 13 C 2 ]-glycine, and [1,2- 13 C 2 , 15 N]-glycine at three different time points, we were able to fully resolve and spatially map their metabolism into three isotopologues of glutathione and calculate their isotopic enrichment in glutathione. We created a tool in the open-source mass spectrometry imaging software MSiReader to accurately compute the percent isotope enrichment (PIE) of these labels in glutathione and visualize them in heat-maps of the tissue sections. In areas of high flux, we found that each label enriched an approximate median of 1.6%, 1.8%, and 1.5%, respectively, of the glutathione product pool measured in each voxel. This method may be adapted to study the heterogeneity of glutathione flux in diseased versus healthy tissues.