Multimodal Image Fusion Workflow Incorporating MALDI Imaging Mass Spectrometry and Microscopy for the Study of Small Pharmaceutical Compounds.

Multimodal imaging analyses of dosed tissue samples can provide more comprehensive insights into the effects of a therapeutically active compound on a target tissue compared to single-modal imaging. For example, simultaneous spatial mapping of pharmaceutical compounds and endogenous macromolecule receptors is difficult to achieve in a single imaging experiment. Herein, we present a multimodal workflow combining imaging mass spectrometry with immunohistochemistry (IHC) fluorescence imaging and brightfield microscopy imaging. Imaging mass spectrometry enables direct mapping of pharmaceutical compounds and metabolites, IHC fluorescence imaging can visualize large proteins, and brightfield microscopy imaging provides tissue morphology information. Single-cell resolution images are generally difficult to acquire using imaging mass spectrometry but are readily acquired with IHC fluorescence and brightfield microscopy imaging. Spatial sharpening of mass spectrometry images would thus allow for higher fidelity coregistration with other higher-resolution microscopy images. Imaging mass spectrometry spatial resolution can be predicted to a finer value via a computational image fusion workflow, which models the relationship between the intensity values in the mass spectrometry image and the features of a high-spatial resolution microscopy image. As a proof of concept, our multimodal workflow was applied to brain tissue extracted from a Sprague-Dawley rat dosed with a kratom alkaloid, corynantheidine. Four candidate mathematical models, including linear regression, partial least-squares regression, random forest regression, and two-dimensional convolutional neural network (2-D CNN), were tested. The random forest and 2-D CNN models most accurately predicted the intensity values at each pixel as well as the overall patterns of the mass spectrometry images, while also providing the best spatial resolution enhancements. Herein, image fusion enabled predicted mass spectrometry images of corynantheidine, GABA, and glutamine to approximately 2.5 µm spatial resolutions, a significant improvement compared to the original images acquired at 25 µm spatial resolution. The predicted mass spectrometry images were then coregistered with an H&E image and IHC fluorescence image of the µ-opioid receptor to assess colocalization of corynantheidine with brain cells. Our study also provides insights into the different evaluation parameters to consider when utilizing image fusion for biological applications.

Enhancing Spatial Resolution in Tandem Mass Spectrometry Ion/Ion Reaction Imaging Experiments through Image Fusion.

We have recently developed a charge inversion ion/ion reaction to selectively derivatize phosphatidylserine lipids via gas-phase Schiff base formation. This tandem mass spectrometry (MS/MS) workflow enables the separation and detection of isobaric lipids in imaging mass spectrometry, but the images acquired using this workflow are limited to relatively poor spatial resolutions due to the current time and limit of detection requirements for these ion/ion reaction imaging mass spectrometry experiments. This trade-off between chemical specificity and spatial resolution can be overcome by using computational image fusion, which combines complementary information from multiple images. Herein, we demonstrate a proof-of-concept workflow that fuses a low spatial resolution (i.e., 125 µm) ion/ion reaction product ion image with higher spatial resolution (i.e., 25 µm) ion images from a full scan experiment performed using the same tissue section, which results in a predicted ion/ion reaction product ion image with a 5-fold improvement in spatial resolution. Linear regression, random forest regression, and two-dimensional convolutional neural network (2-D CNN) predictive models were tested for this workflow. Linear regression and 2D CNN models proved optimal for predicted ion/ion images of PS 40:6 and SHexCer d38:1, respectively.

Indole-3-pyruvate: Analysis and Control of Tautomerism and Reactivity.

It is well-known in biochemistry that structure confers function, meaning that chemical structural elucidation is critical to truly understanding the function of a given metabolite. Indole-3-pyruvate (IPyA) exists in an equilibrium between the keto and enol tautomeric forms. IPyA is suggested to play a role in immune function; however, determining whether the tautomeric forms function differently can only be studied if an analytical method is capable of distinguishing between the two forms. Herein, we describe the use of UHPLC-HRMS to gain insight into the physical variables that govern IPyA tautomer equilibrium, reactivity, and detection limit. We use hydrogen-deuterium exchange (HDX) to identify enol and keto peaks, and we show that tautomers exhibit a valley of fronting followed by a tailing peak shape (though separation is still attainable) and identical MS/MS spectra. We observed drastically different ratios of keto and enol forms in different solvents, which is an important consideration for in vitro studies. IPyA was found to be highly unstable with accelerated reactivity in peroxides. Through in vitro reactivity studies, IPyA produced a myriad of known and unknown metabolites via nonenzymatic processes, many of which were mapped in vivo via the analysis of human plasma. Finally, we show that vitamin C (ascorbic acid) can slow this reactivity and enable sensitive detection in whole blood.

Structural Elucidation and Relative Quantification of Fatty Acid Double Bond Positional Isomers in Biological Tissues Enabled by Gas-Phase Charge Inversion Ion/Ion Reactions.

Fatty acids (FAs) contain a vast amount of structural diversity, and differences in fatty acid structure have been associated with various disease states. Accurate identification and characterization of fatty acids is critical to fully understand the biochemical roles these compounds play in disease progression. Conventional tandem mass spectrometry (MS/MS) workflows do not provide sufficient structural information, necessitating alternative dissociation methods. Gas-phase charge inversion ion/ion reactions can be used to alter the ion type subjected to activation to provide improved or complementary structural information. Herein, we have used an ion/ion reaction between fatty acid (FA) anions and magnesium tris-phenanthroline [Mg(Phen)3] dications to promote charge remote fragmentation of carbon-carbon bonds along the fatty acid chain, allowing for localization of carbon-carbon double bond (C=C) positions to successfully differentiate monounsaturated fatty acid isomers. Relative quantification was also performed to obtain the relative abundance of fatty acid isomers in different biological tissues. For example, the relative abundance of FA 18:1 (9) was determined to vary across regions of rat brain, rat kidney, and mouse pancreas, and FA 16:1 (9) was found to have a higher relative abundance in the dermis layer compared to the sebaceous glands in human skin tissue.

Structural characterization of sphingomyelins from tissue using electron-induced dissociation.

RATIONALE: Sphingomyelins (SMs) and resulting metabolic products serve important functional and cell signaling roles and can act as potential biomarkers and therapeutic targets in many pathological disorders. SMs each contain a sphingoid base, an amide-linked fatty acyl chain, and a phosphocholine headgroup. Despite these simple building blocks, variations and modifications of both the sphingoid base and the fatty acyl chain result in a diverse array of structurally complicated SM compounds. Conventional tandem mass spectrometry (MS/MS) using the collision-induced dissociation (CID) method only provides limited structural information, necessitating other tools to unravel the structural complexity of these lipids. METHODS: We utilize electron-induced dissociation (EID) and sequential CID/EID approaches to elucidate detailed structural features of SMs. Integrating the CID/EID method into an imaging MS workflow enables accurate identification of SMs directly from kidney tissue. RESULTS: The application of EID enables identification of SMs at the molecular species level, identifying the sphingosine base and the amide-linked fatty acyl chains. Furthermore, removal of the phosphocholine headgroup via CID followed by sequential EID in an MS3 analysis (CID/EID) enhances the structural information obtained. CID/EID provides diagnostic fragmentation patterns revealing the hydroxylation site and double bond position in both the sphingosine base and amide-linked fatty acyl chains. CONCLUSIONS: Detailed structural information of SMs from synthetic standards and biological tissue samples is obtained using an alternative electron-based dissociation method. Accurate characterization of SMs promises to better inform studies of tissue biochemistry, lipid metabolism, and molecular pathology.

Structural Elucidation of Ubiquitin via Gas-Phase Ion/Ion Cross-Linking Reactions Using Sodium-Cationized Reagents Coupled with Infrared Multiphoton Dissociation.

Accurate structural determination of proteins is critical to understanding their biological functions and the impact of structural disruption on disease progression. Gas-phase cross-linking mass spectrometry (XL-MS) via ion/ion reactions between multiply charged protein cations and singly charged cross-linker anions has previously been developed to obtain low-resolution structural information on proteins. This method significantly shortens experimental time relative to conventional solution-phase XL-MS but has several technical limitations: (1) the singly deprotonated N-hydroxysulfosuccinimide (sulfo-NHS)-based cross-linker anions are restricted to attachment at neutral amine groups of basic amino acid residues and (2) analyzing terminal cross-linked fragment ions is insufficient to unambiguously localize sites of linker attachment. Herein, we demonstrate enhanced structural information for alcohol-denatured A-state ubiquitin obtained from an alternative gas-phase XL-MS approach. Briefly, singly sodiated ethylene glycol bis(sulfosuccinimidyl succinate) (sulfo-EGS) cross-linker anions enable covalent cross-linking at both ammonium and amine groups. Additionally, covalently modified internal fragment ions, along with terminal b-/y-type counterparts, improve the determination of linker attachment sites. Molecular dynamics simulations validate experimentally obtained gas-phase conformations of denatured ubiquitin. This method has identified four cross-linking sites across 8+ ubiquitin, including two new sites in the N-terminal region of the protein that were originally inaccessible in prior gas-phase XL approaches. The two N-terminal cross-linking sites suggest that the N-terminal half of ubiquitin is more compact in gas-phase conformations. By comparison, the two C-terminal linker sites indicate the signature transformation of this region of the protein from a native to a denatured conformation. Overall, the results suggest that the solution-phase secondary structures of the A-state ubiquitin are conserved in the gas phase. This method also provides sufficient sensitivity to differentiate between two gas-phase conformers of the same charge state with subtle structural variations.

Sequencing of Phosphopeptides Using a Sequential Charge Inversion Ion/Ion Reaction and Electron Capture Dissociation Workflow.

Protein phosphorylation, a common post-translational modification (PTM), is fundamental in a plethora of biological processes, most importantly in modulating cell signaling pathways. Matrix-assisted laser desorption/ionization (MALDI) coupled to tandem mass spectrometry (MS/MS) is an attractive method for phosphopeptide characterization due to its high speed, low limit of detection, and surface sampling capabilities. However, MALDI analysis of phosphopeptides is constrained by relatively low abundances in biological samples and poor relative ionization efficiencies in positive ion mode. Additionally, MALDI tends to produce singly charged ions, generally limiting the accessible MS/MS techniques that can be used for peptide sequencing. For example, collision induced dissociation (CID) is readily amendable to the analysis of singly charged ions, but results in facile loss of phosphoric acid, precluding the localization of the PTM. Electron-based dissociation methods (e.g., electron capture dissociation, ECD) are well suited for PTM localization, but require multiply charged peptide cations to avoid neutralization during ECD. Conversely, phosphopeptides are readily ionized using MALDI in negative ion mode. If the precursor ions are first formed in negative ion mode, a gas-phase charge inversion ion/ion reaction could then be used to transform the phosphopeptide anions produced via MALDI into multiply charged cations that are well-suited for ECD. Herein we demonstrate a multistep workflow combining a charge inversion ion/ion reaction that first transforms MALDI-generated phosphopeptide monoanions into multiply charged cations, and then subjects these multiply charged phosphopeptide cations to ECD for sequence determination and phosphate bond localization.

Formation of multiple ion types during MALDI imaging mass spectrometry analysis of Mitragyna speciosa alkaloids in dosed rat brain tissue.

Mitragyna speciosa, more commonly known as kratom, has emerged as an alternative to treat chronic pain and addiction. However, the alkaloid components of kratom, which are the major contributors to kratom's pharmaceutical properties, have not yet been fully investigated. In this study, matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry was used to map the biodistribution of three alkaloids (corynantheidine, mitragynine, and speciogynine) in rat brain tissues. The alkaloids produced three main ion types during MALDI analysis: [M + H]+, [M - H]+, and [M - 3H]+. Contrary to previous reports suggesting that the [M - H]+ and [M - 3H]+ ion types form during laser ablation, these ion types can also be produced during the MALDI matrix application process. Several strategies are proposed to accurately map the biodistribution of the alkaloids. Due to differences in the relative abundances of the ions in different biological regions of the tissue, differences in ionization efficiencies of the ions, and potential overlap of the [M - H]+ and [M - 3H]+ ion types with endogenous metabolites of the same empirical formula, a matrix that mainly produces the [M + H]+ ion type is optimal for accurate mapping of the alkaloids. Alternatively, the most abundant ion type can be mapped or the intensities of all ion types can be summed together to generate a composite image. The accuracy of each of these approaches is explored and validated.

Extended similarity methods for efficient data mining in imaging mass spectrometry.

Imaging mass spectrometry is a label-free imaging modality that allows for the spatial mapping of many compounds directly in tissues. In an imaging mass spectrometry experiment, a raster of the tissue surface produces a mass spectrum at each sampled x, y position, resulting in thousands of individual mass spectra, each comprising a pixel in the resulting ion images. However, efficient analysis of imaging mass spectrometry datasets can be challenging due to the hyperspectral characteristics of the data. Each spectrum contains several thousand unique compounds at discrete m/z values that result in unique ion images, which demands robust and efficient algorithms for searching, statistical analysis, and visualization. Some traditional post-processing techniques are fundamentally ill-equipped to dissect these types of data. For example, while principal component analysis (PCA) has long served as a useful tool for mining imaging mass spectrometry datasets to identify correlated analytes and biological regions of interest, the interpretation of the PCA scores and loadings can be non-trivial. The loadings often contain negative peaks in the PCA-derived pseudo-spectra, which are difficult to ascribe to underlying tissue biology. Herein, we have utilized extended similarity indices to streamline the interpretation of imaging mass spectrometry data. This novel workflow uses PCA as a pixel-selection method to parse out the most and least correlated pixels, which are then compared using the extended similarity indices. The extended similarity indices complement PCA by removing all non-physical artifacts and streamlining the interpretation of large volumes of imaging mass spectrometry spectra simultaneously. The linear complexity, O(N), of these indices suggests that large imaging mass spectrometry datasets can be analyzed in a 1 : 1 scale of time and space with respect to the size of the input data. The extended similarity indices algorithmic workflow is exemplified here by identifying discrete biological regions of mouse brain tissue.

Imaging with mass spectrometry: Which ionization technique is best?

The use of mass spectrometry (MS) to acquire molecular images of biological tissues and other substrates has developed into an indispensable analytical tool over the past 25 years. Imaging mass spectrometry technologies are widely used today to study the in situ spatial distributions for a variety of analytes. Early MS images were acquired using secondary ion mass spectrometry and matrix-assisted laser desorption/ionization. Researchers have also designed and developed other ionization techniques in recent years to probe surfaces and generate MS images, including desorption electrospray ionization (DESI), nanoDESI, laser ablation electrospray ionization, and infrared matrix-assisted laser desorption electrospray ionization. Investigators now have a plethora of ionization techniques to select from when performing imaging mass spectrometry experiments. This brief perspective will highlight the utility and relative figures of merit of these techniques within the context of their use in imaging mass spectrometry.

A multi-modal image fusion workflow incorporating MALDI imaging mass spectrometry and microscopy for the study of small pharmaceutical compounds.

Multi-modal imaging analyses of dosed tissue samples can provide more comprehensive insight into the effects of a therapeutically active compound on a target tissue compared to single-modal imaging. For example, simultaneous spatial mapping of pharmaceutical compounds and endogenous macromolecule receptors is difficult to achieve in a single imaging experiment. Herein, we present a multi-modal workflow combining imaging mass spectrometry with immunohistochemistry (IHC) fluorescence imaging and brightfield microscopy imaging. Imaging mass spectrometry enables direct mapping of pharmaceutical compounds and metabolites, IHC fluorescence imaging can visualize large proteins, and brightfield microscopy imaging provides tissue morphology information. Single-cell resolution images are generally difficult to acquire using imaging mass spectrometry, but are readily acquired with IHC fluorescence and brightfield microscopy imaging. Spatial sharpening of mass spectrometry images would thus allow for higher fidelity co-registration with higher resolution microscopy images. Imaging mass spectrometry spatial resolution can be predicted to a finer value via a computational image fusion workflow, which models the relationship between the intensity values in the mass spectrometry image and the features of a high spatial resolution microscopy image. As a proof of concept, our multi-modal workflow was applied to brain tissue extracted from a Sprague Dawley rat dosed with a kratom alkaloid, corynantheidine. Four candidate mathematical models including linear regression, partial least squares regression (PLS), random forest regression, and two-dimensional convolutional neural network (2-D CNN), were tested. The random forest and 2-D CNN models most accurately predicted the intensity values at each pixel as well as the overall patterns of the mass spectrometry images, while also providing the best spatial resolution enhancements. Herein, image fusion enabled predicted mass spectrometry images of corynantheidine, GABA, and glutamine to approximately 2.5 µm spatial resolutions, a significant improvement compared to the original images acquired at 25 µm spatial resolution. The predicted mass spectrometry images were then co-registered with an H&E image and IHC fluorescence image of the µ-opioid receptor to assess co-localization of corynantheidine with brain cells. Our study also provides insight into the different evaluation parameters to consider when utilizing image fusion for biological applications.

Multiple ion isolation and accumulation events for selective chemical noise reduction and dynamic range enhancement in MALDI imaging mass spectrometry.

Abundant chemical noise in MALDI imaging mass spectrometry experiments can impede the detection of less abundant compounds of interest. This chemical noise commonly originates from the MALDI matrix as well as other endogenous compounds present in high concentrations and/or with high ionization efficiencies. MALDI imaging mass spectrometry of biological tissues measures numerous biomolecular compounds that exist in a wide range of concentrations in vivo. When ion trapping instruments are used, highly abundant ions can dominate the charge capacity and lead to space charge effects that hinder the dynamic range and detection of lowly abundant compounds of interest. Gas-phase fractionation has been previously utilized in mass spectrometry to isolate and enrich target analytes. Herein, we have characterized the use of multiple continuous accumulations of selected ions (Multi CASI) to reduce the abundance of chemical noise and diminish the effects of space charge in MALDI imaging mass spectrometry experiments. Multi CASI utilizes the mass-resolving capability of a quadrupole mass filter to perform multiple sequential ion isolation events prior to a single mass analysis of the combined ion population. Multi CASI was used to improve metabolite and lipid detection in the MALDI imaging mass spectrometry analysis of rat brain tissue.

Liberation of host heme by Clostridioides difficile-mediated damage enhances Enterococcus faecalis fitness during infection.

IMPORTANCE: Clostridioides difficile and Enterococcus faecalis are two pathogens of great public health importance. Both bacteria colonize the human gastrointestinal tract where they are known to interact in ways that worsen disease outcomes. We show that the damage associated with C. difficile infection (CDI) releases nutrients that benefit E. faecalis. One particular nutrient, heme, allows E. faecalis to use oxygen to generate energy and grow better in the gut. Understanding the mechanisms of these interspecies interactions could inform therapeutic strategies for CDI.

Relative Quantification of Lipid Isomers in Imaging Mass Spectrometry Using Gas-Phase Charge Inversion Ion/Ion Reactions and Infrared Multiphoton Dissociation.

Accurate structural identification of lipids in imaging mass spectrometry is critical to properly contextualizing spatial distributions with tissue biochemistry. Gas-phase charge inversion ion/ion reactions alter the ion type prior to dissociation to allow for more structurally informative fragmentation and improve lipid identification at the isomeric level. In this work, infrared multiphoton dissociation (IRMPD) was interfaced with a commercial hybrid Qh-FT-ICR mass spectrometer to enable the rapid fragmentation of gas-phase charge inversion ion/ion reaction products at every pixel in imaging mass spectrometry experiments. An ion/ion reaction between phosphatidylcholine (PC) monocations generated from rat brain tissue via matrix-assisted laser desorption/ionization (MALDI) and 1,4-phenylenediproprionic acid reagent dianions generated via electrospray ionization (ESI) followed by IRMPD of the resulting product ion complex produces selective fatty acyl chain cleavages indicative of fatty acyl carbon compositions in the lipid. Ion/ion reaction images using this workflow allow for mapping of the relative spatial distribution of multiple PC isomers under a single sum composition lipid identification. Lipid isomers display significantly different relative spatial distributions within rat brain tissue, highlighting the importance of resolving isomers in imaging mass spectrometry experiments.

Imaging and Structural Characterization of Phosphatidylcholine Isomers from Rat Brain Tissue Using Sequential Collision-Induced Dissociation/Electron-Induced Dissociation.

The chemical complexity of biological tissues creates challenges in the analysis of lipids via imaging mass spectrometry. The presence of isobaric and isomeric compounds introduces chemical noise that makes it difficult to unambiguously identify and accurately map the spatial distributions of these compounds. Electron-induced dissociation (EID) has previously been shown to profile phosphatidylcholine (PCs) sn-isomers directly from rat brain tissue in matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry. However, the acquisition of true pixel-by-pixel images, as opposed to regional profiling measurements, using EID is difficult due to low fragmentation efficiency and precursor ion signal dilution into multiple fragment ion channels, resulting in low sensitivity. In this work, we have developed a sequential collision-induced dissociation (CID)/EID method to visualize the distribution of sn-isomers in MALDI imaging mass spectrometry experiments. Briefly, CID is performed on sodium-adducted PCs, which results in facile loss of the phosphocholine headgroup. This ion is then subjected to an EID analysis. Since the lipid headgroup is removed prior to EID, a major fragmentation pathway common to EID ion activation is eliminated, resulting in a more sensitive analysis. This sequential CID/EID workflow generates sn-specific fragment ions allowing for the assignment of the sn-positions. Carbon-carbon double-bond (C═C) positions are also localized along the fatty acyl tails by the presence of a 2 Da shift pattern in the fragment ions arising from carbon-carbon bond cleavages. Moreover, the integration of the CID/EID method into MALDI imaging mass spectrometry enables the mapping of the absolute and relative distribution of sn-isomers at every pixel. The localized relative abundances of sn-isomers vary throughout brain substructures and likely reflect different biological functions and metabolism.

Structural Elucidation and Relative Quantification of Sodium- and Potassium-Cationized Phosphatidylcholine Regioisomers Directly from Tissue Using Electron Induced Dissociation.

Comprehensive structural characterization of phosphatidylcholines (PCs) is essential to understanding their biological functions and roles in metabolism. Electron induced dissociation (EID) of protonated PCs directly generated from biological tissues has previously been shown to provide in-depth structural information on the lipid headgroup, regiosiomerism of fatty acyl tails and double bond positions. Although phosphatidylcholine ions formed via alkali metal cationization (i.e., [M + Na]+ and [M + K]+) are commonly generated during matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry experiments, the gas-phase ion chemistry behavior of EID on sodium- and potassium-cationized phosphatidylcholine ion types has not been studied for ions generated directly from tissue. Herein, we demonstrate EID on [M + Na]+ and [M + K]+ ion types in a MALDI imaging mass spectrometry workflow for lipid structural characterization. Briefly, near-complete structural information can be obtained upon EID of sodium- and potassium-cationized PCs, including diagnostic fragmentation of the lipid headgroup as well as identification of fatty acyl chain positions and double bond position. EID of cationized lipids generates sn-specific glycerol backbone cleavages as well as a favorable combined loss of sn-2 fatty acid with choline over sn-1, allowing for facile differentiation and relative quantification of PC regioisomers. Moreover, relative quantification of sn-positional isomers from biological tissue reveals that the relative percentages of sodium- and potassium-cationized sn-positional isomers varies significantly in different regions of rat brain tissue.

Extended Similarity Methods for Efficient Data Mining in Imaging Mass Spectrometry.

Imaging mass spectrometry is a label-free imaging modality that allows for the spatial mapping of many compounds directly in tissues. In an imaging mass spectrometry experiment, a raster of the tissue surface produces a mass spectrum at each sampled x, y position, resulting in thousands of individual mass spectra, each comprising a pixel in the resulting ion images. However, efficient analysis of imaging mass spectrometry datasets can be challenging due to the hyperspectral characteristics of the data. Each spectrum contains several thousand unique compounds at discrete m/z values that result in unique ion images, which demands robust and efficient algorithms for searching, statistical analysis, and visualization. Some traditional post-processing techniques are fundamentally ill-equipped to dissect these types of data. For example, while principal component analysis (PCA) has long served as a useful tool for mining imaging mass spectrometry datasets to identify correlated analytes and biological regions of interest, the interpretation of the PCA scores and loadings can be non-trivial. The loadings often containing negative peaks in the PCA-derived pseudo-spectra, which are difficult to ascribe to underlying tissue biology. Herein, we have utilized extended similarity indices to streamline the interpretation of imaging mass spectrometry data. This novel workflow uses PCA as a pixel-selection method to parse out the most and least correlated pixels, which are then compared using the extended similarity indices. The extended similarity indices complement PCA by removing all non-physical artifacts and streamlining the interpretation of large volumes of IMS spectra simultaneously. The linear complexity, O(N), of these indices suggests that large imaging mass spectrometry datasets can be analyzed in a 1:1 scale of time and space with respect to the size of the input data. The extended similarity indices algorithmic workflow is exemplified here by identifying discrete biological regions of mouse brain tissue.

Quantification of pharmaceutical compounds in tissue and plasma samples using selective ion accumulation with multiple mass isolation windows.

Quantification of pharmaceutical compounds using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS) is an alternative to traditional liquid chromatography (LC)-MS techniques. Benefits of MALDI-based approaches include rapid analysis times for liquid samples and imaging mass spectrometry capabilities for tissue samples. As in most quantification experiments, the use of internal standards can compensate for spot-to-spot and shot-to-shot variability associated with MALDI sampling. However, the lack of chromatographic separation in traditional MALDI analyses results in diminished peak capacity due to the chemical noise background, which can be detrimental to the dynamic range and limit of detection of these approaches. These issues can be mitigated by using a hybrid mass spectrometer equipped with a quadrupole mass filter (QMF) that can be used to fractionate ions based on their mass-to-charge ratios. When the masses of the analytes and internal standards are sufficiently disparate in mass, it can be beneficial to effect multiple narrow mass isolation windows using the QMF, as opposed to a single wide mass isolation window, to minimize chemical noise while allowing for internal standard normalization. Herein, we demonstrate a MALDI MS quantification workflow incorporating multiple sequential mass isolation windows enabled on a QMF, which divides the total number of MALDI laser shots into multiple segments (i.e., one segment for each mass isolation window). This approach is illustrated through the quantitative analysis of the pharmaceutical compound enalapril in human plasma samples as well as the simultaneous quantification of three pharmaceutical compounds (enalapril, ramipril, and verapamil). Results show a decrease in the limit of detection, relative standard deviations below 10%, and accuracy above 85% for drug quantification using multiple mass isolation windows. This approach has also been applied to the quantification of enalapril in brain tissue from a rat dosed in vitro. The average concentration of enalapril determined by imaging mass spectrometry is in agreement with the concentration determined by LC-MS, giving an accuracy of 104%.

Separation of Isobaric Lipids in Imaging Mass Spectrometry Using Gas-Phase Charge Inversion Ion/Ion Reactions.

The diverse array of chemical compounds present in tissue samples results in many isobaric (i.e., same nominal mass) compounds in imaging mass spectrometry experiments. Adequate separation and differentiation of these compounds is necessary to ensure accurate analyte identification and avoid composite images comprising multiple compounds. High-resolution accurate mass (HRAM) measurements are able to resolve these compounds in some instances, but HRAM measurements are not always feasible depending on the instrument platform and the desired experimental time scale. Alternatively, tandem mass spectrometry (MS/MS) can be used to perform gas-phase transformations that improve molecular specificity. While conventional MS/MS methods employ collision induced dissociation (CID) to fragment compounds of interest and then analyze the product masses, gas-phase ion/ion reactions can be used to instead selectively react with desired classes of analytes. Herein, we have used gas-phase charge inversion ion/ion reactions to selectively resolve phosphatidylcholines (PCs) in isobaric lipid mixtures. A 1,4-phenylenedipropionic acid (PDPA) reagent dianion readily reacts with [M + H]+, [M + Na]+, and [M + K]+ ion types to produce demethylated product anions for each PC, [PC - CH3]-. These product anions are no longer isobaric and now differ in mass by 22 Da (protonated versus sodiated) and 16 Da (sodiated versus potassiated), respectively. This reaction has been used to differentiate isobaric lipids in the imaging mass spectrometry analysis of rat brain tissue.

SMART: A data reporting standard for mass spectrometry imaging.

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.