Modular, Scalable, and Customizable LC-HRMS for Exposomics.

In this chapter, we describe a multi-purpose, reversed-phase liquid chromatography-high-resolution mass spectrometry (LC-HRMS) workflow for acquiring high-quality, non-targeted exposomics data utilizing data-dependent acquisition (DDA) combined with the use of toxicant inclusion lists for semi-targeted analysis. In addition, we describe expected retention times for >160 highly diverse xenobiotics in human plasma and serum samples. The method described is intended to serve as a generic LC-HRMS exposomics workflow for research and educational purposes. Moreover, it may be employed as a primer, allowing for further adaptations according to specialized research needs, e.g., by including reference and/or internal standards, by expanding to data-independent acquisition (DIA), or by modifying the list of compounds prioritized in fragmentation experiments (MS2).

Recommendations for Accurate Lipid Annotation and Semi-absolute Quantification from LC-MS/MS Datasets.

Recent developments in LC-MS instrumentation and analytical technologies together with bioinformatics tools supporting high-throughput processing of large omics datasets significantly enhanced our capabilities and efficiency of identification and quantification of lipids in diverse biological materials. However, each biological matrix is characterized by its unique lipid composition, thus requiring optimization of analytical and bioinformatics workflows for each studied lipidome. Here, we describe an integrated workflow for deep lipidome profiling, accurate annotation, and semi-absolute quantification of complex lipidomes based on reversed phase chromatography and high resolution mass spectrometry. This chapter provides details on selection of the optimal extraction protocol, acquisition of LC-MS/MS data for accurate annotation of lipid molecular species, and design of lipidome-specific mixtures of internal standards to assist quantitative analysis of complex, native lipidomes.

Detailed lipid investigation of edible seaweeds by photochemical derivatization and untargeted lipidomics.

Seaweeds are macrophytic algae that have been gaining interest as alternative healthy foods, renewable drug sources, and climate change mitigation agents. In terms of their nutritional value, seaweeds are renowned for their high content of biologically active polyunsaturated fatty acids. However, little is known about the regiochemistry-the geometry and position of carbon-carbon double bonds-of free and conjugated fatty acids in seaweeds. In the present work, a detailed characterization of the seaweed lipidome was achieved based on untargeted HRMS-based analysis and lipid derivatization with a photochemical aza-Paternò-Büchi reaction. A triple-data processing strategy was carried out to achieve high structural detail on the seaweed lipidome, i.e., (i) a first data processing workflow with all samples for aligning peak and statistical analysis that led to the definition of lipid sum compositions (e.g., phosphatidylglycerol (PG) 34:1), (ii) a second data processing workflow in which the samples of each seaweed were processed separately to annotate molecular lipids with known fatty acyl isomerism (e.g., PG 16:0_18:1), and (iii) the annotation of lipid regioisomers following MS/MS annotation of the lipid derivatives obtained following the aza-Paternò-Büchi reaction (e.g., PG 16:0_18:1 ω-9). Once the platform was set up, the lipid extracts from 8 seaweed species from different seaweed families were characterized, describing over 900 different lipid species, and information on the regiochemistry of carbon-carbon double bonds uncovered unknown peculiarities of seaweeds belonging to different families. The overall analytical approach helped to fill a gap in the knowledge of the nutritional composition of seaweeds.

Metabolomics-based biomarkers of fermented dairy and red meat intake: a randomized controlled trial in healthy adults.

Background: Dietary assessment is usually performed through imprecise tools, leading to error-prone associations between diet and health-related outcomes. Metabolomics has been applied in recent years to develop biomarkers of food intake (BFIs) and to study metabolites in the diet-microbiome crosstalk. Candidate BFIs exist to detect intake of meat and to a lesser extent dairy, but validation and further development of BFIs are needed. Here, we aim to identify biomarkers that differentiate between intakes of red meat and dairy, to validate previously reported BFIs for these foods, and to explore the effect of protein-matched meals on selected microbial metabolites. Methods: We conducted a randomized, controlled, cross-over single-meal study comparing a meal with highly fermented yogurt and cheese, and a meal with beef and pork meatballs. Postprandial urine samples from 17 subjects were collected sequentially after each meal up to 24 h and analyzed by untargeted metabolomics through ultra-high-performance-liquid chromatography (UHPLC) coupled via electrospray (ESI) source to a qTOF mass spectrometer. Univariate (repeated measures ANOVA) and multivariate (PLSDA, ML-PLSDA) data analyses were used to select BFIs differentiating the two meals. 3-Indoxyl sulfate, p-cresol sulfate, and several other microbial amino acid catabolites were additionally explored within the urine profiles. Results: Thirty-eight markers of meat and dairy intake were selected and are presented along with their excretion kinetics. Carnosine, taurine, and creatine, as well as hydroxyproline-based dipeptides are confirmed as meat BFIs. For dairy, previously reported metabolites such as acyl-glycines are confirmed, while proline-based dipeptides are reported as novel putative BFIs. Microbial metabolites showed only marginal evidence of differential formation after the two meals. Conclusion: This study allowed us to validate the postprandial kinetics of previously suggested biomarkers of meat and dairy intake and to identify new potential biomarkers. The excretion kinetics are useful to ensure that the collection of urine covers the correct time window in future dietary studies. The BFIs add to the existing body of biomarkers and may further be used in combination to provide a more reliable assessment of meat and dairy intake. Proteolytic microbial metabolites should be further investigated to assess the effect of different protein sources on health.

Antiproliferative Effects of Methanolic Fruit Extract of Solanum xenthocarpum (L.) on Human Breast Cancer Cells.

Solanum xanthocarpum, a perennial herb native to India, contains steroidal glycoalkaloids with notable anticancer properties. This study investigated the antioxidant and antiproliferative effects of methanolic fruit extract of S. xanthocarpum on human breast cancer cells (MDA-MB-231). Phytochemical screening and LC-HRMS analysis confirmed presence of various primary and secondary metabolites. Antioxidant activity was assessed through DPPH, ABTS radical scavenging, reducing power, and phosphomolybdate assays. The extract demonstrated significant antioxidant potential with EC50 values of 60.10 ± 0.88 µg/mL (DPPH) and 392.29 ± 3.93 µg/mL (ABTS). Cytotoxicity against MDA-MB-231 cells was evaluated via morphological analysis, MTT assays, and IC50 determination (24.19 ± 0.56 µg/L). Apoptosis was confirmed using dual staining techniques (AO/EB, Hoechst 33342/PI, DAPI), revealing condensed nuclei, apoptotic bodies, and reduced mitochondrial membrane potential, as indicated by Rhodamine staining. Additionally, increased reactive oxygen species (ROS) levels were observed using H2-DCF-DA staining. The total phenolic and flavonoid contents of the extract were 127.78 ± 3.547 mg GAE/g and 98.06 ± 4.289 mg QE/g, respectively. These findings suggest that the methanolic fruit extract of S. xanthocarpum possesses strong antioxidant and anticancer activities, indicating its potential role in cancer treatment. Further studies are warranted to explore its bioactive compounds for developing novel anticancer therapies.

Evidence for high-risk pollutants and emerging microbial contaminants at two major bathing ghats of the river Ganga using high-resolution mass spectrometry and metagenomics.

An efficient wastewater treatment plant is imperative to limit the entry of emerging pollutants (EPs) and emerging microbial contaminants (EMCs) in the river ecosystem. The detection of emerging EPs in aquatic environments is challenging due to complex sample preparation methods, and the need for sophisticated accurate analytical tools. In Varanasi (India), the river Ganga holds immense significance as a holy river but is consistently polluted with municipal (MWW) and hospital wastewater (HWW). We developed an efficient method for untargeted detection of EPs in the water samples using High-resolution mass spectrometry (HRMS), and identified 577 and 670 chemicals (or chemical components) in the water samples from two major bathing ghats, Assi Ghat (AG) and Dashashwamedh Ghat (DG), respectively. The presence of EPs of different categories viz chemicals from research labs, diagnostic labs, lifestyle and industrial chemicals, toxins, flavor and food additives indicated the unsafe disposal of MWW and HWW or inefficient wastewater treatment plants (WWTPs). Besides, shotgun metagenomic analysis depicted the presence of bacteria associated with MWW viz Cloacibacterium normanse, Sphaerotilus natans (sewage fungi), E. coli, and Prevotella. Also, the presence of human pathogens Arcobacter, Polynucleobacter, Pseudomonas, Klebsiella, Aeromonas, Acinetobacter, Vibrio, and Campylobacter suggests the discharge of HWW. EPs are linked to the development, and transmission of antimicrobial resistance (AMR). Occurrence of antibiotic resistance genes (ARGs), plasmid-borne ß-lactamases, aminoglycoside transferases, and ARGs associated with integrons, transposons and plasmids viz mcr-3 gene that confer resistance to colistin, the last resort of antibiotics confirmed the presence of emerging microbial contaminants. Subsequent genome reconstruction studies showed the presence of uncultivable ARB and transmission of ARGs through horizontal gene transfer. This study can be used to monitor the health of aquatic bodies as well as the efficiency of WWTPs and raise an urgent need for efficient WWTPs to safeguard the river, Ganga.

Revealing the sterilization impact on paprika fingerprint: Key markers identified using untargeted metabolomics by liquid chromatography-Orbitrap high-resolution mass spectrometry.

Paprika (Capsicum annuum L.) is a popular spice known for its unique properties. Spices are susceptible to microbiological risks arising from harvest factors such as high moisture or environmental contamination. To ensure microbiological safety, post-harvest processing based on heat sterilization, free of chemicals and radiation, is becoming essential in the European market. This study introduces a novel metabolomics approach using ultra-high performance liquid chromatography (UHPLC) coupled with quadrupole-Orbitrap-high-resolution mass spectrometry (HRMS) to assess the sterilization impact on paprika's metabolomic composition. Sterilized and untreated samples were distinguished by OPLS-DA, achieving perfect predictability with high-quality parameters (R2Y = 0.988, Q2 = 0.904). The methodology identified 19 key markers, including fatty acids, amino acids, etc. Sterilization reduced fatty acids such as linoleic acid but increased other metabolites such as DL-malic acid and flazin. This research introduces new metabolomics strategies to ensure paprika quality and other valuable spices, focusing on unexplored sterilization processes.

Exploring the Metabolism of Flubrotizolam, a Potent Thieno-Triazolo Diazepine, Using Human Hepatocytes and High-Resolution Mass Spectrometry.

BACKGROUND: The abuse of psychoactive substances presents challenges in clinical and forensic toxicology. The emergence of novel and potent drugs that pose significant health risks, in particular towards frequent abusers and users unaware of the ingredients, further complicates the situation. Designer benzodiazepines have become a fast-growing subgroup of these new psychoactive substances (NPSs), and their overdose may potentially turn fatal, especially when combined with other central nervous system depressants. In 2021, flubrotizolam, a potent thieno-triazolo designer benzodiazepine, emerged on the illicit market, available online as a "research chemical". The identification of markers of consumption for this designer benzodiazepine is essential in analytical toxicology, especially in clinical and forensic cases. METHODS: We therefore aimed to identify biomarkers of flubrotizolam uptake in ten-donor-pooled human hepatocytes, applying liquid chromatography high-resolution mass spectrometry and software-aided data mining supported by in silico prediction tools. RESULTS: Prediction studies resulted in 10 and 13 first- and second-generation metabolites, respectively, mainly transformed through hydroxylation and sulfation, methylation, and glucuronidation reactions. We identified six metabolites after 3 h human hepatocyte incubation: two hydroxylated metabolites (α- and 6-hydroxy-flubrotizolam), two 6-hydroxy-glucuronides, a reduced-hydroxy-N-glucuronide, and an N-glucuronide. CONCLUSIONS: We suggest detecting flubrotizolam and its hydroxylated metabolites as markers of consumption after the glucuronide hydrolysis of biological samples. The results are consistent with the in vivo metabolism of brotizolam, a medically used benzodiazepine and a chloro-phenyl analog of flubrotizolam.

Untargeted Liquid Chromatography-High-Resolution Mass Spectrometry Metabolomic Investigation Reveals Altered Lipid Content in Leishmania infantum Lacking Lipid Droplet Protein Kinase.

Leishmaniasis is a complex disease caused by different species of Leishmania. To date, no vaccine for humans or ideal therapy has been developed owing to the limited efficacy and toxicity of available drugs, as well as the emergence of resistant strains. Therefore, it is necessary to identify novel therapeutic targets and discover therapeutic options for leishmaniasis. In this study, we evaluated the impact of deleting the lipid droplet protein kinase (LDK) enzyme in Leishmania infantum using an untargeted metabolomics approach performed using liquid chromatography and high-resolution mass spectrometry. LDK is involved in lipid droplet biogenesis in trypanosomatids. Thirty-nine lipid metabolites altered in the stationary and logarithmic growth phases were noted and classified into five classes: (1) sterols, (2) fatty and conjugated acids, (3) ceramides, (4) glycerophosphocholine and its derivatives, and (5) glycerophosphoethanolamine and its derivatives. Our data demonstrated that glycerophosphocholine and its derivatives were the most affected after LDK deletion, suggesting that the absence of this enzyme promotes the remodeling of lipid composition in L. infantum, thus contributing to a better understanding of the function of LDK in this parasite.

A comprehensive approach for N-nitrosamine determination in pharmaceuticals using a novel HILIC-based solid phase extraction and LC-HRMS.

N-nitrosamines (NAs) are potentially highly carcinogenic compounds that have recently been detected in traces in various drug products (DPs). Due to the different physicochemical properties of NAs and active pharmaceutical ingredients (APIs), there is a lack of appropriate analytical methods for simultaneously determining multiple NAs in various DPs. To overcome these limitations, a versatile and innovative analytical approach was developed using a unique sample clean-up procedure by solid phase extraction based on hydrophilic interaction chromatography, which retains high amounts of APIs and polar excipients while allowing NAs of interest to pass through. The samples were analyzed by liquid chromatography coupled with electrospray ionization high-resolution mass spectrometry. The proposed highly sensitive, selective, and robust method was successfully validated, resulting in excellent linearity (R2 > 0.999), accuracy (85-115 %), and precision (RSD <10 %) with adequate recoveries (>80 %), achieving limits of quantitation of at least 42.5 % of regulatory limits. Furthermore, robustness was confirmed for ten DPs (recoveries >80 % and RSD <15 % for all NAs), including those containing up to three APIs. The analytical approach was utilized to examine 26 commercially available and expired DPs. Three NAs (N-nitrosodimethylamine (NDMA), N-nitrosodiethylamine, and N-nitroso-di-n-butylamine) were detected, only NDMA exceeded the limits in expired DPs by up to 32-fold. It was found that special care should be taken when handling samples as NDMA content can be decreased by almost 50 % if samples are not prepared immediately. The approach was tested on 59 different APIs and was confirmed as reliable tool for routine monitoring of 15 NAs in various DPs. Due to its flexibility, the method can be further adapted to the specific API of interest or extended to the newly emerging NA drug substance-related impurities to ensure the safety of DPs and thereby mitigate potential health risks.

Investigating the effects of thermal processing on bitter substances in atemoya (Annona cherimola × Annona squamosa) through sensory-guided separation.

Atemoya (Annona cherimola × Annona squamosa) is a specialty crop in Taiwan. Thermal treatment induces bitterness, complicating seasonal production adjustments and surplus reduction. In this research, sensory-guided separation, metabolomics, and orthogonal partial least squares discrimination analysis (OPLS-DA) are used for identifying the bitterness in atemoya which originates from catechins, epicatechin trimers, and proanthocyanidins. Different thermal treatments (65 °C, 75 °C, and 85 °C) revealed that the glucose and fructose contents in atemoya significantly decreased, while total phenols, flavonoids, and tannins significantly increased. The concentration of 5-hydroxymethylfurfural (5-HMF) increased from 23.16 ng/g in untreated samples to 400.71 ng/g (AP-65), 1208.59 ng/g (AP-75), and 2838.51 ng/g (AP-85). However, these levels are below the 5-HMF bitterness threshold of 3780 ng/g. Combining mass spectrometry analysis with sensory evaluation, OPLS-DA revealed that atemoya treated at 65 °C, 75 °C, and 85 °C exhibited significant bitterness, with the main bitter components being proanthocyanidin dimers and trimers.

Longitudinal Exposomics in a Multiomic Wellness Cohort Reveals Distinctive and Dynamic Environmental Chemical Mixtures in Blood.

Chemical exposomes can now be comprehensively measured in human blood, but knowledge of their variability and longitudinal stability is required for robust application in cohort studies. Here, we applied high-resolution chemical exposomics to plasma of 46 adults, each sampled 6 times over 2 years in a multiomic cohort, resulting in 276 individual exposomes. In addition to quantitative analysis of 83 priority target analytes, we discovered and semiquantified substances that have rarely or never been reported in humans, including personal care products, pesticide transformation products, and polymer additives. Hierarchical cluster analysis for 519 confidently annotated substances revealed unique and distinctive coexposures, including clustered pesticides, poly(ethylene glycols), chlorinated phenols, or natural substances from tea and coffee; interactive heatmaps were publicly deposited to support open exploration of the complex (meta)data. Intraclass correlation coefficients (ICC) for all annotated substances demonstrated the relatively low stability of the exposome compared to that of proteome, microbiome, and endogenous small molecules. Implications are that the chemical exposome must be measured more frequently than other omics in longitudinal studies and four longitudinal exposure types are defined that can be considered in study design. In this small cohort, mixed-effect models nevertheless revealed significant associations between testosterone and perfluoroalkyl substances, demonstrating great potential for longitudinal exposomics in precision health research.

Application of a molecular networking approach using LC-HRMS combined with the MetWork webserver for clinical and forensic toxicology.

Backgrounds and aims: In toxicology, LC-HRMS for untargeted screening yields a great deal of high quality spectral data. However, there we lack tools to visualize/organize the MS data. We applied molecular networking (MN) to untargeted screening interpretation. Our aims were to compare theoretical MS libraries obtained in silico with our experimental dataset in patients to broaden its application, and to use the MetWork web application for metabolite identification. Methods: Samples were analyzed using an LC-HRMS system. For MN, data was generated using MZmine, and analyzed and visualized using MetGem. MetWork annotations were filtered and this file was used for annotation of the previously obtained MN. Results: 155 compounds including drugs found in patients were recorded. Using this dataset, we confirmed in 60 patients intake of tramadol, amitriptyline bromazepam, and cocaine. The results obtained by the reference methods were confirmed by MN approaches. Eighty percent of the compounds were common to both conventional and MN approaches. Using MetWork, metabolites and parent drugs such as amitriptyline, its metabolite nortriptyline and amitriptyline glucuronide phase 2 metabolites were anticipated and proposed as putative annotations. Conclusion: The workflow increases confidence in toxicological screening by highlighting putative structures in biological matrices in combination with CFM-ID (Competitive Fragmentation Modeling for Metabolite Identification) and MetWork to extend the annotation of potential drugs even without a reference standard.

Tracing pesticide dynamics: High resolution offers new insights to karst groundwater quality.

Generally, karst aquifers and springs are highly susceptible to contamination due to the high permeability and, therefore, groundwater flow velocities. The often thin soil cover, accompanied by dolines, can lead to fast infiltration of precipitation water loaded with mobilized contaminants such as pesticides and their transformation products. To date, continuous, temporally highly resolved in-situ monitoring to decipher concentration dynamics for a broad range of pesticides is missing. Therefore, a transportable HPLC-HRMS/MS system (MS2field) was positioned at two karst study sites in the Swiss Jura. Water samples were collected and analyzed for pesticides and their transformation products in-situ every 20 min for 6 weeks in 2021 and 8 weeks in 2022. During the spraying season in 2021, six rain events at site 1 and three at site 2 in 2022 were captured. Concurrently, the water quality parameters electrical conductivity, pH, nitrate, turbidity, and water level, were monitored continuously at high temporal resolution. Further, bacterial cell counts were monitored via online flow cytometry. In 2021, several pesticides and pesticide transformation products were detected in peak concentrations after rain events, of which metamitron showed the highest concentration of up to 1000 ng/L. In one rain event, the Swiss federal and EU drinking water limit of 100 ng/L was exceeded for up to 38 h. Compared with highly frequent MS2field samples collected every 20 min, 42-hours composite samples severely underestimated peak concentrations for all compounds, especially for labile ones. Therefore, it was demonstrated that exceedences of the regulatory limit would have been missed if just composite sampling would have been conducted. Peak concentrations of pesticides coincided with peaks in nitrate concentration and bacterial cell counts following rain events. The correlation analysis showed strong correlations between the three analyzed contaminants (pesticides, nitrate and bacteria), and the proxy parameters electrical conductivity, and pH. The investigation of a second spring revealed similar dynamics indicating that these can be expected in other karst aquifers as well.

[Application of chromatographic retention time correction in untargeted screening].

OBJECTIVE: Chromatographic retention time correction is one of the important steps to effectively improve the accuracy of identification. This article proposed a strategy for untargeted screening of biological samples based on retention time correction. METHODS: A pre-treatment method for biological samples was established. The conditions of liquid chromatography and mass spectrometry were optimized. Fourteen compounds were selected as calibration agents. The retention time correction of different samples, different injection time, different brands of instruments, changing chromatographic column and changing mobile phase were investigated. RESULTS: Calibration agents had a wide coverage, good stability and no interference with sample determination. They could be uniformly distributed in the chromatogram in both positive and negative ion modes. The chromatogram was divided into several time intervals. Calibration agents in each time period were used for retention time linear correction, and the correction effects were good. CONCLUSION: The retention time correction method could eliminate the retention time drift caused by experimental conditions, improve the accuracy of qualitative analysis, and help to solve the problem of high false positive result based on mass spectrum information.

LC-HRMS analysis of phospholipids bearing oxylipins.

BACKGROUND: Several oxylipins including hydroxy- and epoxy-polyunsaturated fatty acids act as lipid mediators. In biological samples they can be present as non-esterified form, but the major part occurs esterified in phospholipids (PL) or other lipids. Esterified oxylipins are quantified indirectly after alkaline hydrolysis as non-esterified oxylipins. However, in this indirect analysis the information in which lipid class oxylipins are bound is lost. In this work, an untargeted liquid chromatography high-resolution mass spectrometry (LC-HRMS) method for the direct analysis of PL bearing oxylipins was developed. RESULTS: Optimized reversed-phase LC separation achieved a sufficient separation of isobaric and isomeric PL from different lipid classes bearing oxylipin positional isomers. Individual PL species bearing oxylipins were identified based on retention time, precursor ion and characteristic product ions. The bound oxylipin could be characterized based on product ions resulting from the α-cleavage occurring at the hydroxy/epoxy group. PL sn-1/sn-2 isomers were identified based on the neutral loss of the fatty acyl in the sn-2 position. A total of 422 individual oxPL species from 7 different lipid classes i.e., PI, PS, PC, PE, PC-P, PC-O, and PE-P were detected in human serum and cells. This method enabled to determine in which PL class supplemented oxylipins are incorporated in HEK293 cells: 20:4;15OH, 20:4;14Ep, and 20:5;14Ep were mostly bound to PI. 20:4;8Ep and 20:5;8Ep were esterified to PC and PE while other oxylipins were mainly found in PC. SIGNIFICANCE: The developed LC-HRMS method enables the comprehensive detection as well as the semi-quantification of isobaric and isomeric PL species bearing oxylipins. With this method, we show that the position of the oxidation has a great impact and directs the incorporation of oxylipins into the different PL classes in human cells.

Dual column chromatography combined with high-resolution mass spectrometry improves coverage of non-targeted analysis of plant root exudates.

BACKGROUND: Within the plant kingdom, there is an exceptional amount of chemical diversity that has yet to be annotated. It is for this reason that non-targeted analysis is of interest for those working in novel natural products. To increase the number and diversity of compounds observable in root exudate extracts, several workflows which differ at three key stages were compared: 1) sample extraction, 2) chromatography, and 3) data preprocessing. RESULTS: Plants were grown in Hoagland's solution for two weeks, and exudates were initially extracted with water, followed by a 24-h regeneration period with subsequent extraction using methanol. Utilizing the second extraction showed improved results with less ion suppression and reduced retention time shifting compared to the first extraction. A single column method, utilizing a pentafluorophenyl column, paired with high-resolution mass spectrometry ionized and correctly identified 34 mock root exudate compounds, while the dual column method, incorporating a pentafluorophenyl column and a porous graphitic carbon column, retained and identified 43 compounds. In a pooled quality control sample of exudate extracts, the single column method detected 1,444 compounds. While the dual method detected fewer compounds overall (1,050), it revealed a larger number of small polar compounds. Three preprocessing methods (targeted, proprietary, and open source) successfully identified 43, 31, and 38 mock root exudate compounds to confidence level 1, respectively. SIGNIFICANCE: Enhancing signal strength and analytical method stability involves removing the high ionic strength nutrient solution before sampling root exudate extracts. Despite signal intensity loss, a dual column method enhances compound coverage, particularly for small polar metabolites. Open-source software proves a viable alternative for non-targeted analysis, even surpassing proprietary software in peak picking.

Rapid analysis of amatoxins in human urine by means of affinity column chromatography and liquid chromatography-high-resolution tandem mass spectrometry.

Analysis of amatoxins is of great importance as these cyclic peptides contribute to a high number of fatalities each year. Development of analytical approaches needs to focus on rapid, sensitive, and reliable methods. By establishing an affinity column chromatography-based assay using the monoclonal amanitin antibody AMA9G3 and liquid chromatography (LC) coupled to high-resolution mass spectrometry (HRMS) for the trace detection of α-, ß-, and γ-amanitin in human urine samples to confirm ingestion, we report the first approach that extents the current status of amatoxin analysis. The presented procedure allows detection of amatoxins in human urine down to 1 ng/mL. The method was successfully validated qualitatively for α- and γ-amanitin according to international recommendations. A proof of concept was performed by analyzing 37 urine samples after suspected amatoxin consumption submitted for regular clinical toxicological analysis. Using this antibody-based enrichment strategy, acute amatoxin intoxications can be determined within 90 min and due to the high sensitivity and selectivity, a comparable approach using target specific antibodies may also be used for other toxicological relevant peptides.

Identifying Key Markers for Monofloral (Eucalyptus, Rosemary, and Orange Blossom) and Multifloral Honey Differentiation in the Spanish Market by UHPLC-Q-Orbitrap-High-Resolution Mass Spectrometry Fingerprinting and Chemometrics.

Honey differentiation based on the botanical origin is crucial to guarantee product authenticity, especially considering the increasing number of fraud cases. This study assessed the metabolomic differences arising from various botanical origins in honey products sold in Spanish markets, focusing on two goals: (1) discrimination within monofloral samples (eucalyptus, rosemary, and orange blossom honey) and (2) differentiation between multifloral vs. monofloral honey samples. An omics strategy based on ultra-high-performance liquid chromatography coupled with quadrupole-Orbitrap-high-resolution mass spectrometry (UHPLC-Q-Orbitrap-HRMS) was applied for the reliable identification of specific honey markers selected by orthogonal partial least squares discriminant analysis (OPLS-DA) (R2Y = 0.929-0.981 and Q2 = 0.868-0.952), followed by the variable importance in projection (VIP) approach. Key amino acid, alkaloid, and trisaccharide markers were identified to distinguish between honey samples. Some Amadori compounds were highlighted as eucalyptus honey markers, suggesting their potential use for honey aging and botanical origin differentiation. L-phenylalanine and raffinose were markers of rosemary honey. Four markers (e.g., trigonelline, L-isoleucine, and N-(1-deoxy-1-fructosyl)isoleucine) were found in higher levels in multifloral samples, indicating a greater availability of amino acids, potentially increasing the Maillard reaction. This research is the first to address the botanical origin's impact on honey by identifying novel markers not previously described.

Determining the Degree of Sulfo-tag Conjugation to AAV5 Vectors by LC-HRMS and Evaluating the Effects on Antibody Binding Affinity and Bridging Assay Sensitivity.

Pre-existing anti-AAV antibodies can be detected using ligand binding-based assay formats. One such format is the MSD-based bridging assay, which uses sulfo-tag-labeled AAV vectors as detection reagents. However, no method has been developed to accurately measure the degree of sulfo-tag labeling on AAV vectors. To fill this gap, we developed a liquid chromatography-high resolution mass spectrometry (LC-HRMS) method to assess the degree of labeling (DoL) of sulfo-tag on AAV5 vectors, enabling the measurement of the DoL on AAV5 at six increasing levels of sulfo-tag challenge ratio. In addition, a Biacore-based assay was used to evaluate the binding affinity between an anti-AAV5 monoclonal antibody and various sulfo-tag labeled AAV5 vectors. The results indicated that increased DoL of sulfo-tag labeling on AAV5 did not compromise the binding affinity.Our study further employed the MSD-bridging assay to detect the binding Signal/Noise (S/N) ratios of four anti-AAV5 monoclonal antibodies (mAbs) to various sulfo-tag-labeled AAV5 vectors. The findings revealed a strong correlation between the degree of sulfo-tag labeling and both the S/N ratios and the sensitivity of MSD bridging assays. This result underscores the importance of optimizing the labeling of detection reagents to enhance assay sensitivity for detecting anti-AAV5 antibodies.