Laser Desorption Electrospray Ionization Mass Research Articles

Collaborative robotics to enable ultra-high-throughput IR-MALDESI

Over the last 5 years, IR-MALDESI-MS (Infrared Matrix-Assisted Laser Desorption Electrospray Ionization Mass Spectrometry) has been demonstrated for use in a range of high-throughput biochemical and cellular assays with remarkable sample acquisition rates up to 22 Hz for a single 384-well assay plate. With such high single plate acquisition rates, the rate limiting step becomes how fast subsequent plates can be presented to the MS for analysis. To make this transfer as fast as possible while maintaining safe operation in a laboratory environment, we developed a collaborative robotic plate transfer system (CRPTS) that combines a 6-axis robot with dual plate grippers, a 7th axis conveyor stage, and a 420-plate capacity sample loading window. As a demonstration of the throughput and flexibility of CRPTS, we performed a biochemical assay that monitored the oxidation of tris(2-carboxyethyl)phosphine (TCEP) to screen for nuisance compounds. Using continuous and step motion scan profiles, we analyzed 158,799 compounds contained in 448 assay plates over the course of 12.5 h (Z-Factor=0.87) and 17.5 h (Z-factor=0.99), respectively. Extrapolating these results enables the screening of a million compounds within 6–7 working days.

Use of X-ray Microscopy for Confirmation of Crystallinity Detection in Amorphous Formulations by Electrospray Laser Desorption Ionization Mass Spectrometry Imaging

The use of mass spectrometry imaging for crystallinity detection offers improved matrix selectivity and sensitivity over the techniques, such as X-ray microscopy and Raman spectrometry, that are traditionally used with this work. Crystallinity is observed in electrospray laser desorption ionization mass spectrometry imaging (ELDI-MSI) as a high-intensity agglomeration of the analyte in a spatially resolved image. As this is an indirect method of crystallinity detection, confirmation of this method’s ability to detect crystallization in amorphous formulations is needed by directly correlating observations of tablet crystallinity by ELDI-MSI to those of an established detection technique. Micro-computed tomography (micro-CT) has the necessary sensitivity for this investigation and is ideal for use in evaluating the correlation with crystallinity detection by ELDI-MSI. In this work, micro-CT followed by ELDI-MSI, in the same location on tablets of amorphous formulations of miconazole spiked with trace levels of crystalline miconazole, were analyzed. Crystals detected by ELDI-MSI as an agglomeration spatially matched with the detected crystals but were chemically unidentified by micro-CT. The results of this correlation study and a conclusion about the effectiveness of ELDI-MSI as a complimentary technique to indirectly detect crystallinity in enabling formations of an amorphous API are presented.

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.

Application of infrared matrix-assisted laser desorption electrospray ionization mass spectrometry for morphine imaging in brain tissue

Here, we present a method developed for the analysis of spatial distributions of morphine in mouse brain tissue using infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) coupled to a Q Exactive Plus mass spectrometer. The method is also capable of evaluating spatial distributions of the antiretroviral drug abacavir. To maximize sensitivity to morphine, we analyze various Orbitrap mass spectrometry acquisition modes utilizing signal abundance and frequency of detection as evaluation criteria. We demonstrate detection of morphine in mouse brain and establish that the selected ion monitoring mode provides 2.5 times higher sensitivity than the full-scan mode. We find that distributions of morphine and abacavir are highly correlated with the Pearson correlation coefficient R = 0.87. Calibration showed that instrument response is linear up to 40 pg/mm2 (3.8 μg/g of tissue).Graphical abstract

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.

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.

Ultra-High-Throughput Ambient MS: Direct Analysis at 22 Samples per Second by Infrared Matrix-Assisted Laser Desorption Electrospray Ionization Mass Spectrometry.

Infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) mass spectrometry is an ambient-direct sampling method that is being developed for high-throughput, label-free, biochemical screening of large-scale compound libraries. Here, we report the development of an ultra-high-throughput continuous motion IR-MALDESI sampling approach capable of acquiring data at rates up to 22.7 samples per second in a 384-well microtiter plate. At top speed, less than 1% analyte carryover is observed from well-to-well, and signal intensity relative standard deviations (RSD) of 11.5% and 20.9% for 3 μM 1-hydroxymidazolam and 12 μM dextrorphan, respectively, are achieved. The ability to perform parallel kinetics studies on 384 samples with a ∼30 s time resolution using an isocitrate dehydrogenase 1 (IDH1) enzyme assay is shown. Finally, we demonstrate the repeatability and throughput of our approach by measuring 115200 samples from 300 microtiter plate reads consecutively over 5.54 h with RSDs under 8.14% for each freshly introduced plate. Taken together, these results demonstrate the use of IR-MALDESI at sample acquisition rates that surpass other currently reported direct sampling mass spectrometry approaches used for high-throughput compound screening.

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.

Spatially resolved metabolomic characterization of muscle invasive bladder cancer by mass spectrometry imaging.

Muscle invasive bladder cancer (MIBC) is an advanced stage of bladder cancer which poses a severe threat to life. Cancer development is usually accompanied by remarkable alterations in cell metabolism, and hence deep insights into MIBC at the metabolomic level can facilitate the understanding of the biochemical mechanisms involved in the cancer development and progression. In this proof-of-concept study, the optimal cutting temperature (OCT)-embedded MIBC samples were first washed with pure water to remove the polymer compounds which could cause severe signal suppression during mass spectrometry. Further, the tissue sections were analyzed by infrared matrix-assisted laser desorption electrospray ionization mass spectrometry imaging (IR-MALDESI MSI), providing an overview on the spatially resolved metabolomic profiles. The MSI dataenabled the discrimination between not only the cancerous and normal tissues, but also the subregions within a tissue section associated with different disease states. Using t-Distributed Stochastic Neighbor Embedding (t-SNE), the hyperdimensional MSI data was mapped into a two-dimensional space to visualize the spectral similarity, providing evidence that metabolomic alterations might have occurred outside the histopathological tumor border. Least absolute shrinkage and selection operator (LASSO) was further employed to classify sample pathology in a pixel-wise manner, yielding excellent prediction sensitivity and specificity up to 96% based on the statistically characteristic spectral features. The results demonstrate great promise of IR-MALDESI MSI to identify molecular changes derived from cancer and unveil tumor heterogeneity, which can potentially promote the discovery of clinically relevant biomarkers and allow for applications in precision medicine.

In situ detection of fatty acid C=C positional isomers by coupling on-tissue mCPBA epoxidation with infrared matrix-assisted laser desorption electrospray ionization mass spectrometry.

Unsaturated fatty acids (UFAs) play vital roles in regulating cellular functions. In-depth structural characterization of UFAs such as localizing carbon-carbon double bonds is fundamentally important but poses considerable challenges in mass spectrometry (MS) given that the most widely accessible ion activation method, low-energy collision-induced dissociation (CID), primarily generates uninformative fragments (e.g., neutral loss of CO2 ) that are not suggestive of the double-bond positions. m-Chloroperoxybenzoic acid (mCPBA) was uniformly deposited onto the sample slides using a TM Sprayer, converting the carbon-carbon double bonds into epoxides under ambient conditions. The epoxidation product was ionized in situ by infrared matrix-assisted laser desorption electrospray ionization mass spectrometry (IR-MALDESI-MS), and subsequently cleaved via CID, generating a diagnostic ion pair associated with the double-bond position. The reaction efficiency, sensitivity and relative quantification capability of the method were validated with five UFA standards dried on glass slides, and then this strategy was demonstrated on thin tissue sections of rat liver and human bladder. The mCPBA reaction yielded conversion rates in the range of 44-60% in 10min with high specificity and sensitivity. Further tandem mass spectrometry (MS/MS) of the mono-epoxidized products generated informative fragment ions specific to the double-bond positions, and relative quantification of positional isomers in binary mixtures was performed across a wide mole fraction from 0 to 1. An innovative spiral scan pattern was utilized during data acquisition, elucidating the major isomeric compositions of multiple UFAs from a tissue section in a single run. The on-tissue mCPBA epoxidation was implemented into an ambient MS imaging workflow to offer a rapid and simple way for in situ identification and relative quantification of double-bond positional isomers without the requirement for instrument modification. The method can be readily implemented on many other MS platforms to reveal the role of double-bond positional isomers in lipid biology and to discover potential biomarkers.

Diagnosis of Agglomeration and Crystallinity of Active Pharmaceutical Ingredients in Over the Counter Headache Medication by Electrospray Laser Desorption Ionization Mass Spectrometry Imaging.

Agglomeration of active pharmaceutical ingredients (API) in tablets can lead to decreased bioavailability in some enabling formulations. In a previous study, we determined that crystalline APIs can be detected as agglomeration in tablets formulated with amorphous acetaminophen tablets. Multiple method advancements are presented to better resolve agglomeration caused by crystallinity in standard tablets. In this study, we also evaluate three “budget” over-the-counter headache medications (subsequently labeled as brands A, B, and C) for agglomeration of the three APIs in the formulation: Acetaminophen, aspirin, and caffeine. Electrospray laser desorption ionization mass spectrometry imaging (ELDI-MSI) was used to diagnose agglomeration in the tablets by creating molecular images and observing the spatial distributions of the APIs. Brand A had virtually no agglomeration or clustering of the active ingredients. Brand B had extensive clustering of aspirin and caffeine, but acetaminophen was observed in near equal abundance across the tablet. Brand C also had extensive clustering of aspirin and caffeine, and minor clustering of acetaminophen. These results show that agglomeration with active ingredients in over-the-counter tablets can be simultaneously detected using ELDI-MS imaging.

Lipidomic profiling of single mammalian cells by infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI).

To better understand cell-to-cell heterogeneity, advanced analytical tools are in a growing demand for elucidating chemical compositions of each cell within a population. However, the progress of single-cell chemical analysis has been restrained by the limitations of small cell volumes and minute cellular concentrations. Here, we present a rapid and sensitive method for investigating the lipid profiles of isolated single cells using infrared matrix-assisted laser desorption electrospray ionization mass spectrometry (IR-MALDESI-MS). In this work, HeLa cells were dispersed onto a glass slide, and the cellular contents were ionized by IR-MALDESI and measured using a Q-Exactive HF-X mass spectrometer. Importantly, this approach does not require extraction and/or enrichment of analytes prior to MS analysis. Using this approach, 45 distinct lipid species, predominantly phospholipids, were detected and putatively annotated from the single HeLa cells. The proof-of-concept study demonstrates the feasibility and efficacy of IR-MALDESI-MS for rapid lipidomic profiling of single cells, which provides an important basis for future work on differentiation between normal and diseased cells at various developmental states, which can offer new insights into cellular metabolic pathways and pathological processes. Although not yet accomplished, we believe this approach can be readily used as an assessment tool to compare the number of identified species during source evolution and method optimization (intra-laboratory), and also disclose the complementary nature of different direct analytical approaches for the coverage of different types of endogenous analytes (inter-laboratory).Graphical abstract.

Development of a relative quantification method for infrared matrix-assisted laser desorption electrospray ionization mass spectrometry imaging of Arabidopsis seedlings.

Mass spectrometry imaging of young seedlings is an invaluable tool in understanding how mutations affect metabolite accumulation in plant development. However, due to numerous biological considerations, established methods for the relative quantification of analytes using infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) mass spectrometry imaging are not viable options. In this study, we report a method for the quantification of auxin-related compounds using stable-isotope-labelled (SIL) indole-3-acetic acid (IAA) doped into agarose substrate. Wild-type Arabidopsis thaliana seedlings, sur2 and wei8 tar2 loss-of-function mutants, and YUC1 gain-of-function line were grown for 3 days in the dark in standard growth medium. SIL-IAA was doped into a 1% low-melting-point agarose gel and seedlings were gently laid on top for IR-MALDESI imaging with Orbitrap mass spectrometry analysis. Relative quantification was performed post-acquisition by normalization of auxin-related compounds to SIL-IAA in the agarose. Amounts of auxin-related compounds were compared between genotypes to distinguish the effects of the mutations on the accumulation of indolic metabolites of interest. IAA added to agarose was found to remain stable, with repeatability and abundance features of IAA comparable with those of other compounds used in other methods for relative quantification in IR-MALDESI analyses. Indole-3-acetaldoxime was increased in sur2 mutants compared with wild-type and other mutants. Other auxin-related metabolites were either below the limits of quantification or successfully quantified but showing little difference among mutants. Agarose was shown to be an appropriate sampling surface for IR-MALDESI mass spectrometry imaging of Arabidopsis seedlings. SIL-IAA doping of agarose was demonstrated as a viable technique for relative quantification of metabolites in live seedlings or tissues with similar biological considerations.

Rapid diagnosis of drug agglomeration and crystallinity in pharmaceutical preparations by electrospray laser desorption ionization mass spectrometry imaging

In this study we evaluate the applicability of electrospray laser desorption ionization mass spectrometry imaging (ELDI-MSI) to interrogate tablet formulations for the spatial distributions of ingredients. Tablet formulations with varying amounts of crystalline acetaminophen (the active pharmaceutical ingredient, API) were analyzed to determine if crystallinity could be evaluated via ELDI-MSI. ELDI-MSI concurrently imaged the (API, binders, and surfactants. The spatial distributions of amorphous API were very similar to that of the surfactants and different from that of crystalline API. The higher the crystallinity in the tablet formulation, the more agglomeration of the active ingredient was observed by ELDI-MSI. This study shows the capability of ELDI-MSI to diagnose agglomeration and crystallinity content in pharmaceutical preparations with little to no sample preparation. The ability to concurrently image APIs with other components provides valuable information as to their form in the tablet.

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

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

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

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. 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. 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. 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.

Rapid identification of herbal toxins using electrospray laser desorption ionization mass spectrometry for emergency care

The unintentional ingestion of toxic compounds in herbs is not uncommon in many parts of the world. To provide timely and life-saving care in the emergency department, it is essential to develop a point-of-care analytical method that can rapidly identify these toxins in herbs. Since electrospray laser desorption ionization mass spectrometry (ELDI/MS) has been successfully used to characterize non-volatile chemical compounds without sample preparation, it was used to identify toxic herbal compounds in this study. The herbal toxins were collected either by sweeping a metallic probe across the surface of a freshly cut herb section or by directly sampling extracts of ground herbal powder. The analytes on the probe were then desorbed, ionized and detected using ELDI/MS, wherein analysis of the herbal toxins was completed within 30 s. This approach allows for the rapid morphological recognition of herbs and early point-of-care identification of herbal toxins for emergency management and is promising in providing important toxicological information to ensure appropriate medical treatment.

Determination of elemental composition of metals using ambient organic mass spectrometry

Conventional inorganic mass spectrometric (MS) analysis of metals can require time-consuming and tedious sample preparation. We thus report the novel and direct characterization of metals in solid samples using an organic MS technique known as electrospray laser desorption ionization mass spectrometry (ELDI/MS). No sample pretreatment was needed, and results were rapidly obtained due to the ambient and laser-based nature of ELDI/MS. Metals from samples were desorbed and ionized by laser irradiation, after which they reacted with EDTA and then post-ionized and detected as metal-EDTA complexes. Aluminum, copper, iron, lead, nickel, and zinc from plates, foils, and coins were characterized in seconds. This study demonstrates that an ESI/MS system can be easily modified to analyze metal elements in solids by involving a chelating agent, indicating a potentially promising development in MS towards the analysis of metals using organic MS.

Analysis of Antiretrovirals in Single Hair Strands for Evaluation of Drug Adherence with Infrared-Matrix-Assisted Laser Desorption Electrospray Ionization Mass Spectrometry Imaging

Analysis of Antiretrovirals in Single Hair Strands for Evaluation of Drug Adherence with Infrared-Matrix-Assisted Laser Desorption Electrospray Ionization Mass Spectrometry Imaging

Analysis of Antiretrovirals in Single Hair Strands for Evaluation of Drug Adherence with Infrared-Matrix-Assisted Laser Desorption Electrospray Ionization Mass Spectrometry Imaging.

Adherence to a drug regimen can be a strong predictor of health outcomes, and validated measures of adherence are necessary at all stages of therapy from drug development to prescription. Many of the existing metrics of drug adherence (e.g., self-report, pill counts, blood monitoring) have limitations, and analysis of hair strands has recently emerged as an objective alternative. Traditional methods of hair analysis based on LC-MS/MS (segmenting strands at ≥1 cm length) are not capable of preserving a temporal record of drug intake at higher resolution than approximately 1 month. Here, we evaluated the detectability of HIV antiretrovirals (ARVs) in hair from a range of drug classes using infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) mass spectrometry imaging (MSI) with 100 μm resolution. Infrared laser desorption of hair strands was shown to penetrate into the strand cortex, allowing direct measurement by MSI without analyte extraction. Using optimized desorption conditions, a linear correlation between IR-MALDESI ion abundance and LC-MS/MS response was observed for six common ARVs with estimated limits of detection less than or equal to 1.6 ng/mg hair. The distribution of efavirenz (EFV) was then monitored in a series of hair strands collected from HIV infected, virologically suppressed patients. Because of the role hair melanin plays in accumulation of basic drugs (like most ARVs), an MSI method to quantify the melanin biomarker pyrrole-2,3,5-tricarboxylic acid (PTCA) was evaluated as a means of normalizing drug response between patients to develop broadly applicable adherence criteria.