Characterization of the Spectral Accuracy of an Orbitrap Mass Analyzer Using Isotope Ratio Mass Spectrometry

A statistical approach to system suitability testing for mass spectrometry imaging

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.

Quantitative mass spectrometry imaging (qMSI): A tutorial

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.

Natural Abundance Isotope Ratio Measurements of Organic Molecules Using 21 T FTICR MS

Subtle variations in stable isotope ratios at natural abundance are challenging to measure but can yield critical insights into biological, physical, and geochemical processes. Well-established methods, particularly multicollector, gas-source, or plasma isotope ratio mass spectrometry, are the gold standard for stable isotope measurement, but inherent limitations in these approaches make them ill-suited to determining site-specific and multiply substituted isotopic abundances of all but a few compounds or to characterizing larger intact molecules. Fourier transform mass spectrometry, namely, Orbitrap mass spectrometry, has recently demonstrated the ability to measure natural abundance isotope ratios with chemically informative accuracy and precision. Here, we report the first use of Fourier transform ion cyclotron resonance mass spectrometry for the accurate (<1‰) and precise (<1‰ standard error) simultaneous determination of δ13C and δ15N in caffeine isotopologues and provide a discussion of the critical instrumental parameters necessary to make such measurements. We further report the ability to make these measurements with online liquid chromatography, expanding the ability of this technique to explore mixtures in the future.

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.

Coupling of the Liquid Sampling-Atmospheric Pressure Glow Discharge to Orbitrap Mass Analyzers for Uranium Isotope Ratio Analysis: Evolution of the Methodology and Implications to the Field

Just over a decade ago, a truly outside-of-the-box approach to isotope ratio mass spectrometry (IRMS) was undertaken between research groups at Clemson University and the Pacific Northwest National Laboratory. The original motivation dealt with projections as to whether or not microplasmas could be developed into practical elemental ionization sources, perhaps for transportable analysis applications. In particular, the use of the liquid sampling-atmospheric pressure glow discharge (LS-APGD) was pursued. Its interfacing to an ultra-high resolution Orbitrap platform, proved not only facile, but opened up a wealth of potential applications. Here, we lay out a historical, tutorial description of the interfacing and the evolution of the methodology regarding IRMS of uranium. Practical challenges and opportunities are described, which hopefully provide guidance to further applications in high resolution IRMS. It is hoped that, while detailed and lengthy, the didactic nature of the presentation provides experimental insights and tips, and also serves as an homage to our very good friend, Professor Gary M. Hieftje, whose scientific inspiration and comradery have been immeasurably important in our own careers.

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

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.

Fine Structure in Isotopic Peak Distributions Measured Using Fourier Transform Ion Cyclotron Resonance Mass Spectrometry: A Comparison between an Infinity ICR Cell and a Dynamically Harmonized ICR Cell

The fine structure of isotopic peak distributions of glutathione in mass spectra is measured using Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) at 12 and 15 T magnetic field, with an infinity cell and a dynamically harmonized cell (DHC) respectively. The resolved peaks in the fine structure of glutathione consist of ²H, ¹³C, ¹⁵N, ¹⁷O, ¹⁸O, ³³S, ³⁴S, ³⁶S, and combinations of them. The positions of the measured fine structure peaks agree with the simulated isotopic distributions with the mass error less than 250 ppb in broadband mode for the infinity cell and no more than 125 ppb with the DHC after internal calibration. The 15 T FT-ICR MS with DHC cell also resolved around 30 isotopic peaks in broadband with a resolving power (RP) of 2 M. In narrowband (m/z 307-313), our current highest RP of 13.9 M in magnitude mode was observed with a 36 s transient length by the 15 T FT-ICR MS with the DHC and 2ω detection on the 15 T offers slightly higher RP (14.8 M) in only 18 s. For the 12 T FT-ICR MS with the infinity cell, the highest RP achieved was 15.6 M in magnitude mode with a transient length of 45 s. Peak decay was observed for low abundance peaks, which could be due to the suppression effects from the most abundant peak, as result of ion cloud Coulombic interactions (space-charge).

Simultaneous, High-Precision Measurements of δ2H and δ13C in Nanomole Quantities of Acetate Using Electrospray Ionization-Quadrupole-Orbitrap Mass Spectrometry

Stable hydrogen isotope compositions (²H/¹H ratios) have been an invaluable tool for studying biogeochemical processes in nature, but the diversity of molecular targets amenable to such analysis is limited. Here, we demonstrate a new technique for measuring δ²H of biomolecules via Orbitrap mass spectrometry (MS) using acetate as a model analyte. Acetate was chosen as a target molecule because its production and consumption are central to microbial carbon cycling, yet the mechanisms behind acetate turnover remain poorly understood. δ²H of acetate could provide a useful constraint on these processes; however, it remains uncharacterized in nature due to analytical challenges. Electrospray ionization (ESI)-Orbitrap MS circumvents these challenges and delivers methyl-specific H-isotope compositions of acetate with nanomole sensitivity, enough to enable analyses of environmental samples. This approach quantifies the methyl-specific δ²H and molecular-average δ¹³C of acetate simultaneously while achieving <3 and <0.5‰ uncertainty, respectively. Using optimized ionization and Orbitrap parameters, this level of precision is obtained within 15 min using only 15 nmol of acetate. As a demonstration of our analytical approach, we cultured three acetogenic bacteria and found a large ²H-fractionation between acetate and water (>310‰ depletion) associated with the Wood-Ljungdahl pathway, while fermentation expressed a muted (∼80‰) fractionation. With its high precision and sensitivity, Orbitrap MS is a promising tool for investigating these signals in nature after offline purification. Furthermore, the ESI-Orbitrap method presented here could be applied to other molecules amenable to ESI, including central metabolites and sugars, greatly expanding the molecular targets used in hydrogen isotope biogeochemistry.

Direct Imaging of Plant Metabolites in the Rhizosphere Using Laser Desorption Ionization Ultra-High Resolution Mass Spectrometry

The interplay of rhizosphere components such as root exudates, microbes, and minerals results in small-scale gradients of organic molecules in the soil around roots. The current methods for the direct chemical imaging of plant metabolites in the rhizosphere often lack molecular information or require labeling with fluorescent tags or isotopes. Here, we present a novel workflow using laser desorption ionization (LDI) combined with mass spectrometric imaging (MSI) to directly analyze plant metabolites in a complex soil matrix. Undisturbed samples of the roots and the surrounding soil of Zea mays L. plants from either field- or laboratory-scale experiments were embedded and cryosectioned to 100 μm thin sections. The target metabolites were detected with a spatial resolution of 25 μm in the root and the surrounding soil based on accurate masses using ultra-high mass resolution laser desorption ionization Fourier-transform ion cyclotron resonance mass spectrometry (LDI-FT-ICR-MS). Using this workflow, we could determine the rhizosphere gradients of a dihexose (e.g., sucrose) and other plant metabolites (e.g., coumaric acid, vanillic acid). The molecular gradients for the dihexose showed a high abundance of this metabolite in the root and a strong depletion of the signal intensity within 150 μm from the root surface. Analyzing several sections from the same undisturbed soil sample allowed us to follow molecular gradients along the root axis. Benefiting from the ultra-high mass resolution, isotopologues of the dihexose could be readily resolved to enable the detection of stable isotope labels on the compound level. Overall, the direct molecular imaging via LDI-FT-ICR-MS allows for the first time a non-targeted or targeted analysis of plant metabolites in undisturbed soil samples, paving the way to study the turnover of root-derived organic carbon in the rhizosphere with high chemical and spatial resolution.

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.

A feasible strategy to improve confident elemental composition determination of compounds in complex organic mixture such as natural organic matter by FTICR-MS without internal calibration

Confident elemental composition determination of compounds in complex samples such as natural organic matter (NOM) by ultrahigh resolution Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) is challenging due to the interference between multiple components in these samples during detection. Here the performance of Solarix 15T-FTICR-MS in terms of accurate relative natural isotope abundance (RIA) and mass measurements for elemental composition determination of compounds in complex samples such as NOM was systematically evaluated. The optimal sweep excitation power values ranging from 20% to 22% was found to significantly diminish the underestimation of RIA measurement for ¹³C₁ peaks of NOM components by FTICR-MS. Random error was found to be one of the main sources for the RIA errors of ¹³C₁ peaks with S/N ratios <25. The mean averaged RIA errors of less than 10% could be obtained by averaging the measured RIAs of each ¹³C₁ peaks in five replicated runs. By adjusting the total ion abundance of NOM complex sample between 3.8-E7 and 1.4-E8 which was simultaneously similar to that of external calibrant during detection, mass errors of lower than 1 ppm for NOM components with m/z lower than 700 Da could be obtained without internal calibration. Meanwhile, a linear correlation between mass errors of ions in NOM complex sample and their m/z values could be obtained. The mass error deviation derived from the linearity was firstly used as new criterion to reduce the number of false formula candidates. A novel strategy of combination of high mass accuracy, high spectral accuracy, and mass error deviation for elemental composition determination of unknown compounds in complex sample such as NOM by FTICR-MS was proposed and applied for different complex samples. Compared to the traditional method, about one fold increasement in the number of the unique formula assignments for measured ions was obtained by using our strategy.

A simplified strategy for molecular formula determination of chemical constituents in traditional Chinese medicines based on accurate mass, A + 1 and A + 2 isotopic peaks using Fourier transform ion cyclotron resonance mass spectrometry

RATIONALE

Recently, isotopic fine structures derived from Fourier transform ion cyclotron resonance mass spectrometry have been used to determine the molecular formula for unknown compounds in many complex systems. However, a simplified strategy for molecular formula determination of chemical constituents in traditional Chinese medicines (TCMs) based on accurate mass, A + 1 and A + 2 isotopic peaks is necessary.

METHODS

Salviae miltiorrhizae was selected as a representative species. First, the chemical constituents were chromatographically separated and their accurate masses were obtained. The A + 1 and A + 2 isotopic peaks of all chemical constituents were then also acquired. Finally, the chemical formulae of the chemical constituents were determined.

RESULTS

In the sample of Salviae miltiorrhizae, the formulae of 38 CHO-containing chemical constituents were quickly determined, and all chemical constituents were identified using their tandem mass spectrometric data. Moreover, the method was validated by comparison of the A + 1 and A + 2 isotopic peaks, their fragmentation patterns and the retention times of six selected standard substances.

CONCLUSIONS

The results demonstrate that the described strategy performs well for molecular formula determination of chemical constituents in TCMs. This also indicates that this method will be meaningful for the structural identification of chemical constituents of TCMs.

3D Imaging and metabolomic profiling reveal higher neuroactive kavalactone contents in lateral roots and crown root peels of Piper methysticum (kava)

BACKGROUND

Kava is an important neuroactive medicinal plant. While kava has a large global consumer footprint for its clinical and recreational use, factors related to its use lack standardization and the tissue-specific metabolite profile of its neuroactive constituents is not well understood.

RESULTS

Here we characterized the metabolomic profile and spatio-temporal characteristics of tissues from the roots and stems using cross-platform metabolomics and a 3D imaging approach. Gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry revealed the highest content of kavalactones in crown root peels and lateral roots. Infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) imaging revealed a unique tissue-specific presence of each target kavalactone. X-ray micro-computed tomography analysis demonstrated that lateral roots have morphological characteristics suitable for synthesis of the highest content of kavalactones.

CONCLUSIONS

These results provide mechanistic insights into the social and clinical practice of the use of only peeled roots by linking specific tissue characteristics to concentrations of neuroactive compounds.

Infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) mass spectrometry imaging analysis of endogenous metabolites in cherry tomatoes

We report the spatially resolved metabolic profiling of cherry tomatoes using infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI), a mass spectrometry imaging (MSI) technique that operates at ambient conditions and requires no sample derivatization. Tomatoes were flash frozen, cryosectioned and imaged with adequate spatial resolution to distinguish between the major tissue structures of a tomato including the skin, mesocarp, endocarp, locular tissue, septum, placenta, seed and seed coating. Metabolites were imaged from 100-1200 m/z, enabling significant coverage of a diverse array of metabolites including amino acids and lipids along with the major secondary metabolite classes: terpenes, phenolics, glycosides, and alkaloids. During the metabolic profiling, we found endogenous carotenoid hydrocarbons, namely lycopene or its structural isomer β-carotene, ionized as radical cations. To our knowledge, this is the first demonstration of ionizing hydrocarbons in the MSI field.

Enabling Isotope Ratio Measurements on an Ion Trap Mass Spectrometer

For portable, remotely operated systems in space and defense, relaxed vacuum requirements are a strong advantage of ion trap mass analyzers. However, ion traps are believed to have insufficient capability for isotope ratio measurement because they fundamentally restrict sampling capacity. Focusing on modifications to the detection sequence of a digitally driven 3D quadrupole ion trap, operating in resonance ejection mode, we investigated improved performance for isotope ratio precision and accuracy. Due to xenon's inert nature and wide span of isotopes, xenon isotope ratios provide an excellent marker of processes (e.g. radioactive decay and planetary atmospheric escape) which would be ideally measured by in situ mass spectrometry. To target xenon isotope ratio analysis specifically, we implemented data acquisition system modifications for enhanced y-axis resolution measurements and signal filtering. In this manner, we show measurement precision improvements from ~±100 0/00 to ~±0.1 0/00 and accuracy improvements from ~30 0/00 to ~0.5 0/00 for our targeted isotopes of interest.

Direct Analysis of Native N-Linked Glycans by IR-MALDESI

Glycan analysis by mass spectrometry has rapidly progressed due to the interest in understanding the role of glycans in disease and tumor progression. Glycans are complex molecules that pose analytical challenges due to their isomeric compositions, labile character, and ionization preferences. This study sought to demonstrate infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) as a novel approach for the direct analysis of N-linked glycans. The glycoprotein bovine fetuin was chosen for this analysis as its glycome is well-characterized and heavily composed of sialylated glycans. Native N-linked glycans produced by enzymatic cleavage (via PNGase F) of bovine fetuin were analyzed directly by IR-MALDESI in both positive and negative ionization mode. In this study, we detected 12 N-linked glycans in negative mode and 4 N-linked glycans in positive mode, a significant increase in the amount of underivatized glycans detected by other ionization sources. Importantly, all N-linked glycans detected contained at least one sialic acid residue, which are known to be labile. This work represents a critical first step for N-linked glycan analysis by IR-MALDESI with future efforts directed at mass spectrometry imaging.

Analysis of neurotransmitters in rat placenta exposed to flame retardants using IR-MALDESI mass spectrometry imaging

Chemical exposures can adversely impact fetal development. For many compounds, including common flame retardants, the mechanisms by which this occurs remain unclear, but emerging evidence suggests that disruption at the level of the placenta may play a role. Understanding how the placenta might be vulnerable to chemical exposures is challenging due to its complex structure. The primary objective of this study was to develop a method for detecting placental neurotransmitters and related metabolites without chemical derivatization so changes in the abundance and spatial distribution of neurotransmitters in rat placenta following chemical exposure could be determined using infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) mass spectrometry imaging. Without chemical derivatization, 49 neurotransmitters and their related metabolites were putatively identified in untreated rat placenta sections using mass measurement accuracy and spectral accuracy. A few neurotransmitters were less abundant in placentas that were exposed to various flame retardants and were further investigated by KEGG metabolic pathway analysis. Many of these downregulated neurotransmitters shared the same enzyme responsible for metabolism, aromaticl-amino acid decarboxylase, suggesting a mechanistic role. These data constitute a new approach that could help identify novel mechanisms of toxicity in complex tissues. Graphical abstract.

Simultaneous Measurement of Metabolite Concentration and Isotope Incorporation by Mass Spectrometry

Studies of the topology, functioning, and regulation of metabolic systems are based on two main types of information that can be measured by mass spectrometry: the (absolute or relative) concentration of metabolites and their isotope incorporation in ¹³C-labeling experiments. These data are currently obtained from two independent experiments because the ¹³C-labeled internal standard (IS) used to determine the concentration of a given metabolite overlaps the ¹³C-mass fractions from which its ¹³C-isotopologue distribution (CID) is quantified. Here, we developed a generic method with a dedicated processing workflow to obtain these two sets of information simultaneously in a unique sample collected from a single cultivation, thereby reducing by a factor of 2 both the number of cultivations to perform and the number of samples to collect, prepare, and analyze. The proposed approach is based on an IS labeled with other isotope(s) that can be resolved from the ¹³C-mass fractions of interest. As proof-of-principle, we analyzed amino acids using a doubly labeled ¹⁵N¹³C-cell extract as IS. Extensive evaluation of the proposed approach shows a similar accuracy and precision compared to state-of-the-art approaches. We demonstrate the value of this approach by investigating the dynamic response of amino acids metabolism in mammalian cells upon activation of the protein kinase R (PKR)-like endoplasmic reticulum kinase (PERK), a key component of the unfolded protein response. Integration of metabolite concentrations and isotopic profiles reveals a reduced de novo biosynthesis of amino acids upon PERK activation. The proposed approach is generic and can be applied to other (micro)organisms, analytical platforms, isotopic tracers, or classes of metabolites.

Three-Dimensional Imaging with Infrared Matrix-Assisted Laser Desorption Electrospray Ionization Mass Spectrometry

Mass spectrometry imaging as a field has pushed its frontiers to three dimensions. Most three-dimensional mass spectrometry imaging (3D MSI) approaches require serial sectioning that results in a loss of biological information between analyzed slices and difficulty in reconstruction of 3D images. In this contribution, infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) was demonstrated to be applicable for 3D MSI that does not require sectioning because IR laser ablates material on a micrometer scale. A commercially available over-the-counter pharmaceutical was used as a model to demonstrate the feasibility of IR-MALDESI for 3D MSI. Depth resolution (i.e., z-resolution) as a function of laser energy levels and density of ablated material was investigated. The best achievable depth resolution from a pill was 2.3 μm at 0.3 mJ/pulse. 2D and 3D MSI were performed on the tablet to show the distribution of pill-specific molecules. A 3D MSI analysis on a region of interest of 15 × 15 voxels across 50 layers was performed. Our results demonstrate that IR-MALDESI is feasible with 3D MSI on a pill, and future work will be focused on analyses of biological tissues.

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

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

Calculation of the Protein Turnover Rate Using the Number of Incorporated 2H Atoms and Proteomics Analysis of a Single Labeled Sample

Rate constant estimation with heavy water requires a long-term experiment with data collection at multiple time points (3-4 weeks for mitochondrial proteome dynamics in mice and much longer in other species). When tissue proteins are analyzed, this approach requires euthanizing animals at each time point or multiple tissue biopsies in humans. Although short-term protocols are available, they require knowledge of the maximum number of isotope labels (N) and accurate quantification of observed ²H-enrichment in the peptide. The high-resolution accurate mass spectrometers used for proteome dynamics studies are characterized by a systematic spectral error that compromises these measurements. To circumvent these issues, we developed a simple algorithm for the rate constant calculation based on a single labeled sample and comparable unlabeled (time 0) sample. The algorithm determines N for all proteogenic amino acids from a long-term experiment to calculate the predicted plateau ²H-labeling of peptides for a short-term protocol and estimates the rate constant based on the measured baseline and the predicted plateau ²H-labeling of peptides. The method was validated based on the rate constant estimation in a long-term experiment in mice and dogs. The improved 2 time-point method enables the rate constant calculation with less than 10% relative error compared to the bench-marked multi-point method in mice and dogs and allows us to detect diet-induced subtle changes in ApoAI turnover in mice. In conclusion, we have developed and validated a new algorithm for protein rate constant calculation based on 2-time point measurements that could also be applied to other biomolecules.

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

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

Selenium-isotopic signature toward mass spectrometric identification and enzyme activity assay

The unraveling of enzymatic reactions, especially identification of enzymatic substrates or products, is important to elucidate biological processes. Here a selenium-isotopic signature for mass spectrometric identification of enzymatic-related species is demonstrated by using selenium-containing peptides (SePeps) as substrates. Thus a strategy is proposed for rapid and precise assay of multiple enzyme activity. These SePeps can be synthesized by introduction of one selenomethionine residue in the sequence and simply identified in the full-scan mode with the feature of distinctive selenium-isotopic distribution without MS/MS verifications, which proposes a novel solution to the specific identification of enzyme-related species, allows to exclude the interferences of species with tiny mass differences in bio-samples, and meanwhile can offer a judgement on data accuracy for the analysis of enzyme activities. As a proof-of-concept, a method for multiple analysis of two representative enzymes in MCF-7 cell lysate has been developed with the isotopic peak areas of either SePep substrates or enzymatic products with the top intensities. These results could be the foundation to extend the method for more complicated enzyme systems. The selenium-isotopic signature provides a powerful protocol for high-throughput assays of peptide-metabolizing enzymes with enhanced confidence and can be extended to screen enzymatic reaction-related substrates.

Discriminating normal regions within cancerous hen ovarian tissue using multivariate hyperspectral image analysis

RATIONALE

Identification of subregions under different pathological conditions on cancerous tissue is of great significance for understanding cancer progression and metastasis. Infrared matrix-assisted laser desorption electrospray ionization mass spectrometry (IR-MALDESI-MS) can be potentially used for diagnostic purposes since it can monitor spatial distribution and abundance of metabolites and lipids in biological tissues. However, the large size and high dimensionality of hyperspectral data make analysis and interpretation challenging. To overcome these barriers, multivariate methods were applied to IR-MALDESI data for the first time, aiming at efficiently resolving mass spectral images, from which these results were then used to identify normal regions within cancerous tissue.

METHODS

Molecular profiles of healthy and cancerous hen ovary tissues were generated by IR-MALDESI-MS. Principal component analysis (PCA) combined with color-coding built a single tissue image which summarizes the high-dimensional data features. Pixels with similar color indicated similar composition. PCA results from healthy tissue were further used to test each pixel in cancerous tissue to determine if it is healthy. Multivariate curve resolution-alternating least squares (MCR-ALS) was used to obtain major spatial features existing in ovary tissues, and group molecules with the same distribution patterns simultaneously.

RESULTS

PCA as the predominating dimensionality reduction approach captured over 90% spectral variances by the first three PCs. The PCA images show the cancerous tissue is more chemically heterogeneous than healthy tissue, where at least four regions with different m/z profiles can be differentiated. PCA modeling assigns top regions of cancerous tissue as healthy-like. MCR-ALS extracted three and four major compounds from healthy and cancerous tissue, respectively. Evaluating similarities of resolved spectra uncovered the chemical components that were distinct in some regions on cancerous tissue, serving as a supplementary way to differentiate healthy and cancerous regions.

CONCLUSIONS

Two unsupervised chemometric methods including PCA and MCR-ALS were applied for resolving and visualizing IR-MALDESI-MS data acquired from hen ovary tissues, improving the interpretation of mass spectrometry imaging results. Then possible normal regions were differentiated from cancerous tissue sections. No prior knowledge is required using either chemometric method, so our approach is readily suitable for unstained tissue samples, which allows one to reveal the molecular events happening during disease progression.

Distinguishing malignant from benign microscopic skin lesions using desorption electrospray ionization mass spectrometry imaging

Detection of microscopic skin lesions presents a considerable challenge in diagnosing early-stage malignancies as well as in residual tumor interrogation after surgical intervention. In this study, we established the capability of desorption electrospray ionization mass spectrometry imaging (DESI-MSI) to distinguish between micrometer-sized tumor aggregates of basal cell carcinoma (BCC), a common skin cancer, and normal human skin. We analyzed 86 human specimens collected during Mohs micrographic surgery for BCC to cross-examine spatial distributions of numerous lipids and metabolites in BCC aggregates versus adjacent skin. Statistical analysis using the least absolute shrinkage and selection operation (Lasso) was employed to categorize each 200-µm-diameter picture element (pixel) of investigated skin tissue map as BCC or normal. Lasso identified 24 molecular ion signals, which are significant for pixel classification. These ion signals included lipids observed at m/z 200-1,200 and Krebs cycle metabolites observed at m/z < 200. Based on these features, Lasso yielded an overall 94.1% diagnostic accuracy pixel by pixel of the skin map compared with histopathological evaluation. We suggest that DESI-MSI/Lasso analysis can be employed as a complementary technique for delineation of microscopic skin tumors.