The development and application of matrix assisted laser desorption electrospray ionization: The teenage years

Improved detection in untargeted lipidomics through silver-doped infrared matrix-assisted laser desorption electrospray ionization

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 + NH4]+ and as [M + Ag]+. Among the ions seen as [M + H]+ or [M + NH4]+, 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.

Incorporation of Three Different Optical Trains into the IR-MALDESI Mass Spectrometry Imaging Platform to Characterize Artemisia annua

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.

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

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

Imaging plant metabolism in situ

Mass spectrometry imaging (MSI) has emerged as an invaluable analytical technique for investigating the spatial distribution of molecules within biological systems. In the realm of plant science, MSI is increasingly employed to explore metabolic processes across a wide array of plant tissues, including those in leaves, fruits, stems, roots, and seeds, spanning various plant systems such as model species, staple and energy crops, and medicinal plants. By generating spatial maps of metabolites, MSI has elucidated the distribution patterns of diverse metabolites and phytochemicals, encompassing lipids, carbohydrates, amino acids, organic acids, phenolics, terpenes, alkaloids, vitamins, pigments, and others, thereby providing insights into their metabolic pathways and functional roles. In this review, we present recent MSI studies that demonstrate the advances made in visualizing the plant spatial metabolome. Moreover, we emphasize the technical progress that enhances the identification and interpretation of spatial metabolite maps. Within a mere decade since the inception of plant MSI studies, this robust technology is poised to continue as a vital tool for tackling complex challenges in plant metabolism.

Ultra-high-throughput mass spectrometry in drug discovery: fundamentals and recent advances

INTRODUCTION

Ultra-high-throughput mass spectrometry, uHT-MS, is a technology that utilizes ionization and sample delivery technologies optimized to enable sampling from well plates at > 1 sample per second. These technologies do not need a chromatographic separation step and can be utilized in a wide variety of assays to detect a broad range of analytes including small molecules, lipids, and proteins.

AREAS COVERED

This manuscript provides a brief historical review of high-throughput mass spectrometry and the recently developed technologies that have enabled uHT-MS. The report also provides examples and references on how uHT-MS has been used in biochemical and chemical assays, nuisance compound profiling, protein analysis and high throughput experimentation for chemical synthesis.

EXPERT OPINION

The fast analysis time provided by uHT-MS is transforming how biochemical and chemical assays are performed in drug discovery. The potential to associate phenotypic responses produced by 1000's of compound treatments with changes in endogenous metabolite and lipid signals is becoming feasible. With the augmentation of simple, fast, high-throughput sample preparation, the scope of uHT-MS usage will increase. However, it likely will not supplant LC-MS for analyses that require low detection limits from complex matrices or characterization of complex biotherapeutics such as antibody-drug conjugates.

A high-throughput platform enables in situ screening of fatty acid-producing strains using laser ablation electrospray ionization mass spectrometry and a Python package

Microbial fatty acid-producing strains are commonly engineered to improve their performance for industrial applications. However, it is challenging to efficiently and rapidly screen target strains for engineering. This study reported an in situ analytical platform using laser ablation electrospray ionization mass spectrometry (LAESI-MS) for fast profiling of triacylglycerols in cellular lipid droplets of Aurantiochytrium sp. colonies cultured on agar plates. LAESI-MS approach allowed for the direct acquisition of a colony cell's characteristic fingerprint mass spectrum and MS/MS facilitated the identification of triacylglycerol species containing three fatty acyl groups. The fatty acid contents of colony cells were calculated based on the intensities of triacylglycerols from their characteristic fingerprint mass spectrum. A Python package called TAFA-LEMS (Triacylglycerol to Fatty Acid by LAESI-MS) was also developed to process the high-throughput MS data and extract fatty acid contents in colony cells. The results demonstrated that the LAESI-MS platform is fast, stable, and reproducible, with a data acquisition rate of ≤2 s per sampling point and ≤13.69% RSDs of the relative contents of fatty acids. In addition, LAESI-MS was successfully performed on the analysis of P. tricornutum and Y lipolytica strains. This in situ MS platform has the potential to become a common biotechnology platform for microbial strain engineering.

Prototyping an ionization source for non-engineers

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.

Evaluating the optimal tissue thickness for mass spectrometry imaging using infrared matrix-assisted laser desorption electrospray ionization

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.

Combining LAESI Imaging and Tissue Spray Ionization Mass Spectrometry To Unveil Pesticides Contaminants in Fruits

There is an increasing need for developing a strategy to analyze the penetration of pesticides in cultures during postharvest control with minimal or no sample preparation. This study explores the combined use of laser ablation electrospray ionization mass spectrometry imaging (LAESI imaging) and tissue spray ionization mass spectrometry (TSI-MS) to investigate the penetration of thiabendazole (TBZ) in fruits, simulating a postharvest procedure. Slices of guava and apple were prepared, and an infrared laser beam was used, resulting in the ablation of TBZ directly ionized by electrospray and analyzed by mass spectrometry. The experiments were conducted for 5 days of fruit storage after TBZ administration to simulate a postharvest treatment. During postharvest treatment, TBZ is applied directly to the fruit peel after harvesting. Consequently, TBZ residues may remain on the peel if the consumer does not wash the fruit properly before its consumption. To evaluate the effectiveness of household washing procedures, TSI-MS was employed as a rapid and straightforward technique to monitor the remaining amount of TBZ in guava and apple peels following fruit washing. This study highlights the advantages of LAESI imaging for evaluating TBZ penetration in fruits. Moreover, the powerful capabilities of TSI-MS are demonstrated in monitoring and estimating TBZ residues after pesticide application, enabling the comprehensive unveiling of pesticide contaminants in fruits.

Comparative analysis of sucrose-embedding for whole-body zebrafish MSI by IR-MALDESI

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.

Metabolite Annotation Confidence Score (MACS): A Novel MSI Identification Scoring Tool

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.

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

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

Enhanced Detection of Charged N-Glycans in the Brain by Infrared Matrix-Assisted Laser Desorption Electrospray Ionization Mass Spectrometric Imaging

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.

Development of an object-based image analysis tool for mass spectrometry imaging ion classification

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.

Lipidomic Analysis of Mouse Brain to Evaluate the Efficacy and Preservation of Different Tissue Preparatory Techniques by IR-MALDESI-MSI

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.

Achieving Sub-Parts-per-Million Mass Measurement Accuracy on an Orbitrap Mass Spectrometry Imaging Platform without Automatic Gain Control

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.

New Platform for Label-Free, Proximal Cellular Pharmacodynamic Assays: Identification of Glutaminase Inhibitors Using Infrared Matrix-Assisted Laser Desorption Electrospray Ionization Mass Spectrometry

Cellular pharmacodynamic assays are crucial aspects of lead optimization programs in drug discovery. These assays are sometimes difficult to develop, oftentimes distal from the target and frequently low throughput, which necessitates their incorporation in the drug discovery funnel later than desired. The earlier direct pharmacodynamic modulation of a target can be established, the fewer resources are wasted on compounds that are acting via an off-target mechanism. Mass spectrometry is a versatile tool that is often used for direct, proximal cellular pharmacodynamic assay analysis, but liquid chromatography-mass spectrometry methods are low throughput and are unable to fully support structure-activity relationship efforts in early medicinal chemistry programs. Infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) is an ambient ionization method amenable to high-throughput cellular assays, capable of diverse analyte detection, ambient and rapid laser sampling processes, and low cross-contamination. Here, we demonstrate the capability of IR-MALDESI for the detection of diverse analytes directly from cells and report the development of a high-throughput, label-free, proximal cellular pharmacodynamic assay using IR-MALDESI for the discovery of glutaminase inhibitors and a biochemical assay for hit confirmation. We demonstrate the throughput with a ∼100,000-compound cellular screen. Hits from the screening were confirmed by retesting in dose-response with mass spectrometry-based cellular and biochemical assays. A similar workflow can be applied to other targets with minimal modifications, which will speed up the discovery of cell active lead series and minimize wasted chemistry resources on off-target mechanisms.

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.

Transforming a Mid-infrared Laser Profile from Gaussian to a Top-Hat with a Diffractive Optical Element for Mass Spectrometry Imaging

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.

Quasi-continuous infrared matrix-assisted laser desorption electrospray ionization source coupled to a quadrupole time-of-flight mass spectrometer for direct analysis from well plates

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.

Mass Spectrometry Imaging of Lipids Using MALDI Coupled with Plasma-Based Post-Ionization on a Trapped Ion Mobility Mass Spectrometer

Here we report the development and optimization of a mass spectrometry imaging (MSI) platform that combines an atmospheric-pressure matrix-assisted laser desorption/ionization platform with plasma postionization (AP-MALDI-PPI) and trapped ion mobility spectrometry (TIMS). We discuss optimal parameters for operating the source, characterize the behavior of a variety of lipid classes in positive- and negative-ion modes, and explore the capabilities for lipid imaging using murine brain tissue. The instrument generates high signal-to-noise for numerous lipid species, with mass spectra sharing many similarities to those obtained using laser postionization (MALDI-2). The system is especially well suited for detecting lipids such as phosphatidylethanolamine (PE), as well as numerous sphingolipid classes and glycerolipids. For the first time, the coupling of plasma-based postionization with ion mobility is presented, and we show the value of ion mobility for the resolution and identification of species within rich spectra that contain numerous isobaric/isomeric signals that are not resolved in the m/z dimension alone, including isomeric PE and demethylated phosphatidylcholine lipids produced by in-source fragmentation. The reported instrument provides a powerful and user-friendly approach for MSI of lipids.

Improved spatial resolution of infrared matrix-assisted laser desorption electrospray ionization mass spectrometry imaging using a reflective objective

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.

Developing transmission mode for infrared matrix-assisted laser desorption electrospray ionization mass spectrometry imaging

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.

Interrogating the Metabolomic Profile of Amyotrophic Lateral Sclerosis in the Post-Mortem Human Brain by Infrared Matrix-Assisted Laser Desorption Electrospray Ionization (IR-MALDESI) Mass Spectrometry Imaging (MSI)

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.

Next-Generation Infrared Matrix-Assisted Laser Desorption Electrospray Ionization Source for Mass Spectrometry Imaging and High-Throughput Screening

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.

Normalization techniques for high-throughput screening by infrared matrix-assisted laser desorption electrospray ionization mass spectrometry

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.

Using Molecular Tools to Understand Microbial Carbonates

Here we review the application of molecular biological approaches to mineral precipitation in modern marine microbialites. The review focuses on the nearly two decades of nucleotide sequencing studies of the microbialites of Shark Bay, Australia; and The Bahamas. Molecular methods have successfully characterized the overall community composition of mats, pinpointed microbes involved in key metabolisms, and revealed patterns in the distributions of microbial groups and functional genes. Molecular tools have become widely accessible, and we can now aim to establish firmer links between microbes and mineralization. Two promising future directions include “zooming in” to assess the roles of specific organisms, microbial groups, and surfaces in carbonate biomineralization and “zooming out” to consider broader spans of space and time. A middle ground between the two can include model systems that contain representatives of important microbial groups, processes, and metabolisms in mats and simplify hypothesis testing. These directions will benefit from expanding reference datasets of marine microbes and enzymes and enrichments of representative microbes from mats. Such applications of molecular tools should improve our ability to interpret ancient and modern microbialites and increase the utility of these rocks as long-term recorders of microbial processes and environmental chemistry.

Simultaneous Measurement of Striatal Dopamine and Hydrogen Peroxide Transients Associated with L-DOPA Induced Rotation in Hemiparkinsonian Rats

Parkinson's disease (PD) is a neurodegenerative disorder commonly treated with levodopa (L-DOPA), which eventually induces abnormal involuntary movements (AIMs). The neurochemical contributors to these dyskinesias are unknown; however, several lines of evidence indicate an interplay of dopamine (DA) and oxidative stress. Here, DA and hydrogen peroxide (H2O2) were simultaneously monitored at discrete recording sites in the dorsal striata of hemiparkinsonian rats using fast-scan cyclic voltammetry. Mass spectrometry imaging validated the lesions. Hemiparkinsonian rats exhibited classic L-DOPA-induced AIMs and rotations as well as increased DA and H2O2 tone over saline controls after 1 week of treatment. By week 3, DA tone remained elevated beyond that of controls, but H2O2 tone was largely normalized. At this time point, rapid chemical transients were time-locked with spontaneous bouts of rotation. Striatal H2O2 rapidly increased with the initiation of contraversive rotational behaviors in lesioned L-DOPA animals, in both hemispheres. DA signals simultaneously decreased with rotation onset. The results support a role for these striatal neuromodulators in the adaptive changes that occur with L-DOPA treatment in PD and reveal a precise interplay between DA and H2O2 in the initiation of involuntary locomotion.

Multimodal Mass Spectrometry Imaging of Rat Brain Using IR-MALDESI and NanoPOTS-LC-MS/MS

Multimodal mass spectrometry imaging (MSI) is a critical technique used for deeply investigating biological systems by combining multiple MSI platforms in order to gain the maximum molecular information about a sample that would otherwise be limited by a single analytical technique. The aim of this work was to create a multimodal MSI approach that measures metabolomic and proteomic data from a single biological organ by combining infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) for metabolomic MSI and nanodroplet processing in one pot for trace samples (nanoPOTS) LC-MS/MS for spatially resolved proteome profiling. Adjacent tissue sections of rat brain were analyzed by each platform, and each data set was individually analyzed using previously optimized workflows. IR-MALDESI data sets were annotated by accurate mass and spectral accuracy using HMDB, METLIN, and LipidMaps databases, while nanoPOTS-LC-MS/MS data sets were searched against the rat proteome using the Sequest HT algorithm and filtered with a 1% FDR. The combined data revealed complementary molecular profiles distinguishing the corpus callosum against other sampled regions of the brain. A multiomic pathway integration showed a strong correlation between the two data sets when comparing average abundances of metabolites and corresponding enzymes in each brain region. This work demonstrates the first steps in the creation of a multimodal MSI technique that combines two highly sensitive and complementary imaging platforms. Raw data files are available in METASPACE (https://metaspace2020.eu/project/pace-2021) and MassIVE (identifier: MSV000088211).

Optimized C-Trap Timing of an Orbitrap 240 Mass Spectrometer for High-Throughput Screening and Native MS by IR-MALDESI

Infrared matrix-assisted laser desorption ionization (IR-MALDESI) is a hybrid mass spectrometry ionization source that combines the benefits of electrospray ionization (ESI) and matrix-assisted laser desorption ionization (MALDI) making it a great analytical tool for high-throughput screening (HTS) analyses. IR-MALDESI is coupled to an Orbitrap Exploris 240 mass spectrometer that utilizes a bent quadrupole (C-trap) to inject accumulated ions into the high-field Orbitrap mass analyzer. Here, we present a study on the optimized C-trap timing for HTS analyses by IR-MALDESI mass spectrometry. The timing between initial ion generation and the C-trap opening time was optimized to reduce unnecessary ambient ion accumulation in the mass spectrometer. The time in which the C-trap was held open, the ion accumulation time, was further optimized to maximize the accumulation of analyte ions generated using IR-MALDESI. The resulting C-trap opening scheme benefits small-molecule HTS analyses by IR-MALDESI by maximizing target ion abundances, minimizing ambient ion abundances, and minimizing the total analysis time per sample. The proposed C-trap timing scheme for HTS does not translate to large molecules; a NIST monoclonal antibody standard reference material was analyzed to demonstrate that larger analytes require longer ion accumulation times and that IR-MALDESI can measure intact antibodies in their native state.

Enhancing Metabolomic Coverage in Positive Ionization Mode Using Dicationic Reagents by Infrared Matrix-Assisted Laser Desorption Electrospray Ionization

Mass spectrometry imaging is a powerful tool to analyze a large number of metabolites with their spatial coordinates collected throughout the sample. However, the significant differences in ionization efficiency pose a big challenge to metabolomic mass spectrometry imaging. To solve the challenge and obtain a complete data profile, researchers typically perform experiments in both positive and negative ionization modes, which is time-consuming. In this work, we evaluated the use of the dicationic reagent, 1,5-pentanediyl-bis(1-butylpyrrolidinium) difluoride (abbreviated to [C5(bpyr)2]F2) to detect a broad range of metabolites in the positive ionization mode by infrared matrix-assisted laser desorption electrospray ionization mass spectrometry imaging (IR-MALDESI MSI). [C5(bpyr)2]F2 at 10 µM was doped in 50% MeOH/H2O (v/v) electrospray solvent to form +1 charged adducted ions with anionic species (-1 charged) through post-electrospray ionization. This method was demonstrated with sectioned rat liver and hen ovary. A total of 73 deprotonated metabolites from rat liver tissue sections were successfully adducted with [C5(bpyr)2]2+ and putatively identified in the adducted positive ionization polarity, along with 164 positively charged metabolite ions commonly seen in positive ionization mode, which resulted in 44% increased molecular coverage. In addition, we were able to generate images of hen ovary sections showing their morphological features. Following-up tandem mass spectrometry (MS/MS) indicated that this dicationic reagent [C5(bpyr)2]2+ could form ionic bonds with the headgroup of glycerophospholipid ions. The addition of the dicationic reagent [C5(bpyr)2]2+ in the electrospray solvent provides a rapid and effective way to enhance the detection of metabolites in positive ionization mode.

Multiple Infusion Start Time Mass Spectrometry Imaging of Dynamic SIL-Glutathione Biosynthesis Using Infrared Matrix-Assisted Laser Desorption Electrospray Ionization

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 [2-¹³C,¹⁵N]-glycine, [1,2-¹³C₂]-glycine, and [1,2-¹³C₂,¹⁵N]-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.

Review of Recent Advances in Lipid Analysis of Biological Samples via Ambient Ionization Mass Spectrometry

The rapid and direct structural characterization of lipids proves to be critical for studying the functional roles of lipids in many biological processes. Among numerous analytical techniques, ambient ionization mass spectrometry (AIMS) allows for a direct molecular characterization of lipids from various complex biological samples with no/minimal sample pretreatment. Over the recent years, researchers have expanded the applications of the AIMS techniques to lipid structural elucidation via a combination with a series of derivatization strategies (e.g., the Paternò–Büchi (PB) reaction, ozone-induced dissociation (OzID), and epoxidation reaction), including carbon–carbon double bond (C=C) locations and sn-positions isomers. Herein, this review summarizes the reaction mechanisms of various derivatization strategies for C=C bond analysis, typical instrumental setup, and applications of AIMS in the structural elucidation of lipids from various biological samples (e.g., tissues, cells, and biofluids). In addition, future directions of AIMS for lipid structural elucidation are discussed.

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

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