Miniaturized Two-Dimensional Heart Cutting for LC-MS-Based Metabolomics.

Liquid chromatography-mass spectrometry (LC-MS)-based metabolomics usually combines hydrophilic interaction liquid chromatography (HILIC) and reversed-phase (RP) chromatography to cover a wide range of metabolomes, requiring both significant sample consumption and analysis time for separate workflows. We developed an integrated workflow enabling the coverage of both polar and nonpolar metabolites with only one injection of the sample for each ionization mode using heart-cutting trapping to combine HILIC and RP separations. This approach enables the trapping of some compounds eluted from the first chromatographic dimension for separation later in the second dimension. In our case, we applied heart-cutting to non-retained metabolites in the first dimension. For that purpose, two independent miniaturized one-dimensional HILIC and RP methods were developed by optimizing the chromatographic and ionization conditions using columns with an inner diameter of 1 mm. They were then merged into one two-dimensional micro LC-MS method by optimization of the trapping conditions. Equilibration of the HILIC column during elution on the RP column and vice versa reduced the overall analysis time, and the multidimensionality allows us to avoid signal measurements during the solvent front. To demonstrate the benefits of this approach to metabolomics, it was applied to the analysis of the human plasma standard reference material SRM 1950, enabling the detection of hundreds of metabolites without the significant loss of some of them while requiring an injection volume of only 0.5 µL.

Harmonized Quality Assurance/Quality Control Provisions for Nontargeted Measurement of Urinary Pesticide Biomarkers in the HBM4EU Multisite SPECIMEn Study.

A set of quality assurance/quality control (QA/QC) criteria for nontargeted measurement of pesticide exposure markers in a large-scale study of human urine has been proposed and applied across five laboratories within the HBM4EU project. Quality control material, including reference standards and fortified pooled urine samples (QC urine) were prepared in a centralized way and distributed across participants to monitor analytical performance and consistency of the liquid chromatography coupled to high-resolution mass spectrometry data generated with a harmonized workflow. Signal intensities, mass accuracy, and retention times of selected QA/QC markers covering a broad range of physicochemical properties were monitored across QC solvent standards, QC urine samples, study urine samples, and procedural blanks, setting acceptance thresholds for repeatability and accuracy. Overall, results showed high repeatability of the collected data. The RSDs of the signal intensities were typically below 20-30% in QC and study samples, with good stability of the chromatographic separation (retention time drift within 2-4 s intrabatch and 5 s interbatch) and excellent mass accuracy (average error < 2 ppm). The use of the proposed criteria allowed for the identification of handling errors, instrumental issues, and potential batch effects. This is the first elaboration of harmonized QA/QC criteria applied across multiple laboratories to assess the quality of data generated by nontargeted analysis of human samples.

PeakForest: a multi-platform digital infrastructure for interoperable metabolite spectral data and metadata management.

INTRODUCTION: Accuracy of feature annotation and metabolite identification in biological samples is a key element in metabolomics research. However, the annotation process is often hampered by the lack of spectral reference data in experimental conditions, as well as logistical difficulties in the spectral data management and exchange of annotations between laboratories. OBJECTIVES: To design an open-source infrastructure allowing hosting both nuclear magnetic resonance (NMR) and mass spectra (MS), with an ergonomic Web interface and Web services to support metabolite annotation and laboratory data management. METHODS: We developed the PeakForest infrastructure, an open-source Java tool with automatic programming interfaces that can be deployed locally to organize spectral data for metabolome annotation in laboratories. Standardized operating procedures and formats were included to ensure data quality and interoperability, in line with international recommendations and FAIR principles. RESULTS: PeakForest is able to capture and store experimental spectral MS and NMR metadata as well as collect and display signal annotations. This modular system provides a structured database with inbuilt tools to curate information, browse and reuse spectral information in data treatment. PeakForest offers data formalization and centralization at the laboratory level, facilitating shared spectral data across laboratories and integration into public databases. CONCLUSION: PeakForest is a comprehensive resource which addresses a technical bottleneck, namely large-scale spectral data annotation and metabolite identification for metabolomics laboratories with multiple instruments. PeakForest databases can be used in conjunction with bespoke data analysis pipelines in the Galaxy environment, offering the opportunity to meet the evolving needs of metabolomics research. Developed and tested by the French metabolomics community, PeakForest is freely-available at https://github.com/peakforest .

Prospective association between dietary pesticide exposure profiles and type 2 diabetes risk in the NutriNet-Santé cohort.

BACKGROUND: Studies focusing on dietary pesticides in population-based samples are scarce and little is known about potential mixture effects. We aimed to assess associations between dietary pesticide exposure profiles and Type 2 Diabetes (T2D) among NutriNet-Santé cohort participants. METHODS: Participants completed a Food Frequency Questionnaire at baseline, assessing conventional and organic food consumption. Exposures to 25 active substances used in European Union pesticides were estimated using the Chemisches und Veterinäruntersuchungsamt Stuttgart residue database accounting for farming practices. T2D were identified through several sources. Exposure profiles were established using Non-Negative Matrix Factorization (NMF), adapted for sparse data. Cox models adjusted for known confounders were used to estimate hazard ratios (HR) and 95% confidence interval (95% CI), for the associations between four NMF components, divided into quintiles (Q) and T2D risk. RESULTS: The sample comprised 33,013 participants aged 53 years old on average, including 76% of women. During follow-up (median: 5.95 years), 340 incident T2D cases were diagnosed. Positive associations were detected between NMF component 1 (reflecting highest exposure to several synthetic pesticides) and T2D risk on the whole sample: HRQ5vsQ1 = 1.47, 95% CI (1.00, 2.18). NMF Component 3 (reflecting low exposure to several synthetic pesticides) was associated with a decrease in T2D risk, among those with high dietary quality only (high adherence to French dietary guidelines, including high plant foods consumption): HRQ5vsQ1 = 0.31, 95% CI (0.10, 0.94). CONCLUSIONS: These findings suggest a role of dietary pesticide exposure in T2D risk, with different effects depending on which types of pesticide mixture participants are exposed to. These associations need to be confirmed in other types of studies and settings, and could have important implications for developing prevention strategies (regulation, dietary guidelines). TRIAL REGISTRATION: This study is registered in ClinicalTrials.gov ( NCT03335644 ).

Fate of Sulfonamides and Tetracyclines in Meat during Pan Cooking: Focus on the Thermodegradation of Sulfamethoxazole.

Although antimicrobials are generally found in trace amounts in meat, the human health risk they bear cannot be ignored. With the ultimate aim of making a better assessment of consumer exposure, this study explored the effects of pan cooking on sulfonamides and tetracyclines in meat. Screening of these antimicrobials in cooked meat was first performed by the European Union Reference Laboratory on the basis of HPLC-MS/MS analyses. A proof of concept approach using radiolabeling was then carried out on the most cooking-sensitive antimicrobial-sulfamethoxazole-to assess if a thermal degradation could explain the observed cooking losses. Degradation products were detected thanks to separation by HPLC and monitoring by online radioactivity detection. HPLC-Orbitrap HRMS analyses completed by 1D and 2D NMR experiments allowed the structural characterization of these degradation compounds. This study revealed that cooking could induce significant antimicrobial losses of up to 45% for sulfamethoxazole. Six potential degradation products of 14C-sulfamethoxazole were detected in cooked meat, and a thermal degradation pattern was proposed. This study highlights the importance of considering the cooking step in chemical risk assessment procedures and its impact on the level of chemical contaminants in meat and on the formation of potentially toxic breakdown compounds.

Lactose and Fructo-oligosaccharides Increase Visceral Sensitivity in Mice via Glycation Processes, Increasing Mast Cell Density in Colonic Mucosa.

BACKGROUND & AIMS: Irritable bowel syndrome (IBS) is characterized by abdominal pain, bloating, and erratic bowel habits. A diet low in fermentable oligosaccharides, disaccharides, monosaccharides, and polyols (FODMAPs) can reduce symptoms of IBS, possibly by reducing microbial fermentation products. We investigated whether ingestion of FODMAPs can induce IBS-like visceral hypersensitivity mediated by fermentation products of intestinal microbes in mice. METHODS: C57Bl/6 mice were gavaged with lactose, with or without the antiglycation agent pyridoxamine, or saline (controls) daily for 3 weeks. A separate group of mice were fed a diet containing fructo-oligosaccharides, with or without pyridoxamine in drinking water, or a normal chow diet (controls) for 6 weeks. Feces were collected and analyzed by 16S ribosomal RNA gene sequencing and bacterial community analyses. Abdominal sensitivity was measured by electromyography and mechanical von Frey filament assays. Colon tissues were collected from some mice and analyzed by histology and immunofluorescence to quantify mast cells and expression of advanced glycosylation end-product specific receptor (AGER). RESULTS: Mice gavaged with lactose or fed fructo-oligosaccharides had increased abdominal sensitivity compared with controls, associated with increased numbers of mast cells in colon and expression of the receptor for AGER in proximal colon epithelium. These effects were prevented by administration of pyridoxamine. Lactose and/or pyridoxamine did not induce significant alterations in the composition of the fecal microbiota. Mass spectrometric analysis of carbonyl compounds in fecal samples identified signatures associated with mice given lactose or fructo-oligosaccharides vs controls. CONCLUSIONS: We found that oral administration of lactose or fructo-oligosaccharides to mice increases abdominal sensitivity, associated with increased numbers of mast cells in colon and expression of AGER; these can be prevented with an antiglycation agent. Lactose and/or pyridoxamine did not produce alterations in fecal microbiota of mice. Our findings indicate that preventing glycation reactions might reduce abdominal pain in patients with IBS with sensitivity to FODMAPs.

Osmolality-based normalization enhances statistical discrimination of untargeted metabolomic urine analysis: results from a comparative study.

INTRODUCTION: Because of its ease of collection, urine is one of the most commonly used matrices for metabolomics studies. However, unlike other biofluids, urine exhibits tremendous variability that can introduce confounding inconsistency during result interpretation. Despite many existing techniques to normalize urine samples, there is still no consensus on either which method is most appropriate or how to evaluate these methods. OBJECTIVES: To investigate the impact of several methods and combinations of methods conventionally used in urine metabolomics on the statistical discrimination of two groups in a simple metabolomics study. METHODS: We applied 14 different strategies of normalization to forty urine samples analysed by liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS). To evaluate the impact of these different strategies, we relied on the ability of each method to reduce confounding variability while retaining variability of interest, as well as the predictability of statistical models. RESULTS: Among all tested normalization methods, osmolality-based normalization gave the best results. Moreover, we demonstrated that normalization using a specific dilution prior to the analysis outperformed post-acquisition normalization. We also demonstrated that the combination of various normalization methods does not necessarily improve statistical discrimination. CONCLUSIONS: This study re-emphasized the importance of normalizing urine samples for metabolomics studies. In addition, it appeared that the choice of method had a significant impact on result quality. Consequently, we suggest osmolality-based normalization as the best method for normalizing urine samples. TRIAL REGISTRATION NUMBER: NCT03335644.

Estimated dietary pesticide exposure from plant-based foods using NMF-derived profiles in a large sample of French adults.

PURPOSE: This study, conducted in participants of the NutriNet-Santé cohort, aims to identify dietary pesticide exposure profiles (derived from Non-negative Matrix Factorization) from conventional and organic foods among a large sample of general population French adults. METHODS: Organic and conventional dietary intakes were assessed using a self-administered semi-quantitative food frequency questionnaire. Exposure to 25 commonly used pesticides was evaluated using food contamination data from Chemisches und Veterinäruntersuchungsamt Stuttgart accounting for farming system (organic or conventional). Dietary pesticide exposure profiles were identified using Non-Negative Matrix factorization (NMF), especially adapted for non-negative data with excess zeros. The NMF scores were introduced in a hierarchical clustering process. RESULTS: Overall, the identified clusters (N = 34,193) seemed to be exposed to the same compounds with gradual intensity. Cluster 1 displayed the lowest energy intake and estimated dietary pesticide exposure, high organic food (OF) consumption (23.3%) and a higher proportion of male participants than other groups. Clusters 2 and 5 presented intermediate energy intake, lower OF consumption and intermediate estimated pesticide exposure. Cluster 3 showed high conventional fruits and vegetable (FV) intake, high estimated pesticide exposure, and fewer smokers. Cluster 4 estimated pesticide exposure varied more across compounds than for other clusters, with highest estimated exposures for acetamiprid, azadirachtin, cypermethrin, pyrethrins, spinosad. OF proportion in the diet was the highest (31.5%). CONCLUSION: Estimated dietary pesticide exposures appeared to vary across the clusters and to be related to OF proportion in the diet. TRIAL REGISTRATION: Clinical Trial Registry: NCT03335644.

Safety assessment of cosmetics by read across applied to metabolomics data of in vitro skin and liver models.

As a result of the cosmetics testing ban, safety evaluations of cosmetics ingredients must now be conducted using animal-free methods. A common approach is read across, which is mainly based on structural similarities but can also be conducted using biological endpoints. Here, metabolomics was used to assess biological effects to enable a read across between a candidate cosmetic ingredient, DIV665, only studied using in vitro assays, and a structurally similar reference compound, PA102, previously investigated using traditional in vivo toxicity methods. The (1) cutaneous distribution after topical application, (2) skin metabolism, (3) liver metabolism and (4) effect on the intracellular metabolomic profiles of in vitro skin and hepatic models, SkinEthic®RHE model and HepaRG® cells were investigated. The compounds exhibited similar skin penetration and skin and liver metabolism, with small differences attributed to their physicochemical properties. The effects of both compounds on the metabolome of RHE and HepaRG® cells were similarly small, both in terms of the metabolites modulated and the magnitude of changes. The patterns of metabolome changes did not fit with any known signature relating to a mode of action known to be linked to liver toxicity e.g. modification of the Krebs cycle, urea synthesis and lipid metabolism, were more reflective of transient adaptive responses. Overall, these studies indicate that PA102 is biologically similar to DIV665, allowing read across of safety endpoints, such as in vivo sub-chronic (but not reproduction toxicity) studies, for the former to be applied to DIV665. Based on this, in the absence of animal data (which is prohibited for new chemicals), it could be concluded that DIV665 applied according to the consumer topical use scenario, is similar to PA102, and is predicted to exhibit low local skin and systemic toxicity.

Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology.

Omics methodologies are widely used in toxicological research to understand modes and mechanisms of toxicity. Increasingly, these methodologies are being applied to questions of regulatory interest such as molecular point-of-departure derivation and chemical grouping/read-across. Despite its value, widespread regulatory acceptance of omics data has not yet occurred. Barriers to the routine application of omics data in regulatory decision making have been: 1) lack of transparency for data processing methods used to convert raw data into an interpretable list of observations; and 2) lack of standardization in reporting to ensure that omics data, associated metadata and the methodologies used to generate results are available for review by stakeholders, including regulators. Thus, in 2017, the Organisation for Economic Co-operation and Development (OECD) Extended Advisory Group on Molecular Screening and Toxicogenomics (EAGMST) launched a project to develop guidance for the reporting of omics data aimed at fostering further regulatory use. Here, we report on the ongoing development of the first formal reporting framework describing the processing and analysis of both transcriptomic and metabolomic data for regulatory toxicology. We introduce the modular structure, content, harmonization and strategy for trialling this reporting framework prior to its publication by the OECD.

High Heterogeneity of Multidrug-Resistant Enterobacteriaceae Fecal Levels in Hospitalized Patients Is Partially Driven by Intravenous ß-Lactams.

Multidrug-resistant Enterobacteriaceae (MRE) colonize the intestine asymptomatically from where they can breach into the bloodstream and cause life-threatening infections, especially in heavily colonized patients. Despite the clinical relevance of MRE colonization levels, we know little about how they vary in hospitalized patients and the clinical factors that determine those levels. Here, we conducted one of the largest studies of MRE fecal levels by tracking longitudinally 133 acute leukemia patients and monitoring their MRE levels over time through extensive culturing. MRE were defined as Enterobacteriaceae species that acquired nonsusceptibility to ≥1 agent in ≥3 antimicrobial categories. In addition, due to the selective media used, the MRE had to be resistant to third-generation cephalosporins. MRE were detected in 60% of the patients, but their fecal levels varied considerably among patients and within the same patient (>6 and 4 orders of magnitude, respectively). Multivariate analysis of clinical metadata revealed an impact of intravenous beta-lactams (i.e., meropenem and piperacillin-tazobactam), which significantly diminished the fecal MRE levels in hospitalized patients. Consistent with a direct action of beta-lactams, we found an effect only when the patient was colonized with strains sensitive to the administered beta-lactam (P < 0.001) but not with nonsusceptible strains. We report previously unobserved inter- and intraindividual heterogeneity in MRE fecal levels, suggesting that quantitative surveillance is more informative than qualitative surveillance of hospitalized patients. In addition, our study highlights the relevance of incorporating antibiotic treatment and susceptibility data of gut-colonizing pathogens for future clinical studies and in clinical decision-making.

Global Profiling of Toxicologically Relevant Metabolites in Urine: Case Study of Reactive Aldehydes.

Among the numerous unknown metabolites representative of our exposure, focusing on toxic compounds should provide more relevant data to link exposure and health. For that purpose, we developed and applied a global method using data independent acquisition (DIA) in mass spectrometry to profile specifically electrophilic compounds originating metabolites. These compounds are most of the time toxic, due to their chemical reactivity toward nucleophilic sites present in biomacromolecules. The main line of cellular defense against these electrophilic molecules is conjugation to glutathione, then metabolization into mercapturic acid conjugates (MACs). Interestingly, MACs display a characteristic neutral loss in MS/MS experiments that makes it possible to detect all the metabolites displaying this characteristic loss, thanks to the DIA mode, and therefore to highlight the corresponding reactive metabolites. As a proof of concept, our workflow was applied to the toxicological issue of the oxidation of dietary polyunsaturated fatty acids, leading in particular to the formation of toxic alkenals, which lead to MACs upon glutathione conjugation and metabolization. By this way, dozens of MACs were detected and identified. Interestingly, multivariate statistical analyses carried out only on extracted HRMS signals of MACs yield a better characterization of the studied groups compared to results obtained from a classic untargeted metabolomics approach.

Combination of Isotope Labeling and Molecular Networking of Tandem Mass Spectrometry Data To Reveal 69 Unknown Metabolites Produced by Penicillium nordicum.

The secondary metabolome of Penicillium nordicum is poorly documented despite its frequent detection on contaminated food and its capacity to produce toxic metabolites such as ochratoxin A. To characterize metabolites produced by this fungi, we combined a full stable isotopes labeling with the dereplication of tandem mass spectrometry (MS/MS) data by molecular networking. First, the untargeted metabolomic analysis by high-resolution mass spectrometry of a double stable isotope labeling of P. nordicum enabled the specific detection of its metabolites and the unambiguous determination of their elemental composition. Analyses showed that infection of substrate by P. nordicum lead to the production of at least 92 metabolites and that 69 of them were completely unknown. Then, curated molecular networks of MS/MS data were generated with GNPS and MetGem, specifically on the features of interest, which allowed highlighting 13 fungisporin-related metabolites that had not previously been identified in this fungus and 8 that had never been observed in any fungus. The structures of the unknown compounds, namely, a native fungisporin and seven linear peptides, were characterized by tandem mass spectrometry experiments. The analysis of P. nordicum growing on its natural substrates, i.e. pork ham, turkey ham, and cheese, demonstrated that 10 of the known fungisporin-related metabolites and three of the new metabolites were also synthesized. Thus, the curation of data for molecular networking using a specific detection of metabolites of interest with stable isotopes labeling allowed the discovery of new metabolites produced by the food contaminant P. nordicum.

Clay-Na as a sorbent for the extraction of anti-inflammatory compounds in water samples.

In this work, clay-Na particles are used as the adsorbent for the solid-phase extraction of acidic compounds. The novel sorbent under study is based on high-specific surface area, cation-exchange capacity designed specifically to offer ion-exchange properties with the goal being to selectively extract a group of acidic compounds. The effects of the extraction parameters including extraction elution solvent, sample volume and pH. In optimum conditions, the repeatability for one fiber (n = 3), expressed as % relative standard deviation, was between 0.3 and 4.3% for the acid compounds. The detection limits for the studied acidic compounds were between 0.1-0.6 µg/L. The developed method offers the advantages of being simple to use and having a low cost of equipment.

Detection of plasmid-mediated colistin resistance, mcr-1 gene, in Escherichia coli isolated from high-risk patients with acute leukemia in Spain.

BACKGROUND: Bacterial infections in immunocompromised patients are associated with a high mortality and morbidity rate. In this high-risk group, the presence of multidrug-resistant (MDR) bacteria, particularly bacteria that harbor a transferable antibiotic resistance gene, complicates the management of bacterial infections. In this study, we investigated the presence of the transferable colistin resistance mcr genes in patients with leukemia in Spain. METHODS: 217 fecal samples collected in 2013-2015 from 56 patients with acute leukemia and colonized with MDR Enterobacteriaceae strains, were screened on September 2017 for the presence of the colistin resistance mcr genes (mcr-1 to -5) by multiplex PCR. mcr positive strains selected on LBJMR and MacConkey supplemented with colistin (2 µg/ml) media were phenotypically and molecularly characterized by antimicrobial susceptibility testing, minimum inhibitory concentration, multilocus sequence typing and plasmid characterization. RESULTS: Among 217 fecal samples, 5 samples collected from 3 patients were positive for the presence of the mcr-1 colistin-resistance gene. Four Escherichia coli strains were isolated and exhibited resistance to colistin with MIC = 4 µg/ml. Other genes conferring the resistance to ß-lactam antibiotics have also been identified in mcr-1 positive strains, including blaTEM-206 and blaTEM-98. Three different sequence types were identified, including ST1196, ST140 and ST10. Plasmid characterization allowed us to detect the mcr-1 colistin resistance gene on conjugative IncP plasmid type. CONCLUSION: To the best of our knowledge, we have identified the mcr-1 gene for the first time in leukemia patients in Spain. In light of these results, strict measures have been implemented to prevent its dissemination.

Solid-phase extraction of drugs with cuttlefish bone powder as a sorbent.

We investigated cuttlefish bone powder for the solid-phase extraction of naproxen, ibuprofen, and carbamazepine. The basic principles controlling the extraction are presented to aid in the choice of the nature and quantity of the extracting phase according to the sample matrix and the solute properties, based on the mechanisms of phase retention. Their retention mechanism is based on hydrogen bonding and electrostatic interactions. The results show a significant recovery rate for the three drugs, selectivity, and low cost. The method has successfully reduced the amount of tested pharmaceuticals with recoveries >87% at pH 4.

An efficient data-filtering strategy for easy metabolite detection from the direct analysis of a biological fluid using Fourier transform mass spectrometry.

RATIONALE: High-throughput analyses require an overall analytical workflow including not only a robust and high-speed technical platform, but also dedicated data-processing tools able to extract the relevant information. This work aimed at evaluating post-acquisition data-mining tools for selective extraction of metabolite species from direct introduction high-resolution mass spectrometry data. METHODS: Investigations were performed on spectral data in which seven metabolites of vinclozolin, a dicarboximide fungicide containing two chloride atoms, were previously manually identified. The spectral data obtained from direct introduction (DI) and high-resolution mass spectrometry (HRMS) detection were post-processed by plotting the mass defect profiles and applying various data-filtering methods based on accurate mass values. RESULTS: Exploration of mass defect profiles highlighted, in a specific plotting region, the presence of compounds containing common chemical elements and pairs of conjugated and non-conjugated metabolites resulting from classical metabolic pathways. Additionally, the judicious application of mass defect and/or isotope pattern filters removed many interfering ions from DI-HRMS data, greatly facilitating the detection of vinclozolin metabolites. Compared with previous results obtained by manual data treatment, three additional metabolites of vinclozolin were detected and putatively annotated. CONCLUSIONS: Tracking simultaneously several specific species could be efficiently performed using data-mining tools based on accurate mass values. The selectivity of the data extraction was improved when the isotope filter was used for halogenated compounds, facilitating metabolite ion detection even for low-abundance species. Copyright © 2016 John Wiley & Sons, Ltd.

Biological and environmental influence on tissue fatty acid compositions in wild tropical tunas.

This study examined the fatty acid composition of three sympatric tropical tuna species (bigeye Thunnus obesus, yellowfin T. albacares and skipjack tuna Kastuwonus pelamis) sampled in the Western Indian Ocean in 2013. The fatty acid compositions of neutral and polar lipids, respectively involved in energy storage and cell membrane structure, were explored and compared in four tissues (red and white muscles, liver and gonads), according to biological (size, sex and maturity) and environmental (season and area) factors. The liver and the red muscle were the fattest tissues (i.e., higher levels of storage lipids) in all species and polar lipids were the lowest in the white muscle. Species and tissue types explained most differences in fatty acid compositions, while environmental factors had limited effects, except in the hepatic cell membrane where fatty acid composition varied with monsoons. Docosahexaenoic acid (22:6n-3) was the major fatty acid in both polar and neutral lipid fractions, especially in muscles. Eicosapentaenoic acid (20:5n-3) and oleic acid (18:1n-9) were in higher proportion in neutral than in polar lipids. Arachidonic acid (20:4n-6) and 22:6n-3, together with docosapentaenoic acid (22:5n-6) and stearic acid (18:0), showed preferential accumulation in polar lipids. 20:4n-6 was particularly involved in cell membranes of ovary and white muscle. Overall, an important inter-individual variability in fatty acid compositions of structural lipids was found within tissue types despite considering biological factors that are most likely to influence this type of lipids. It suggests that fatty acid profiles are influenced by individual-specific behaviors.

Cell-specific biotransformation of benzophenone-2 and bisphenol-s in zebrafish and human in vitro models used for toxicity and estrogenicity screening.

Several human and fish bioassays have been designed to characterize the toxicity and the estrogenic activity of chemicals. However, their biotransformation capability (bioactivation/detoxification processes) is rarely reported, although this can influence the estrogenic potency of test compounds. The fate of two estrogenic chemicals, the UV filter benzophenone-2 (BP2) and the bisphenol A substitute bisphenol S (BPS) was deciphered in eight human and zebrafish in vitro cell models, encompassing hepatic and mammary cellular contexts. BP2 and BPS were metabolized into a variety of gluco- and sulfo-conjugated metabolites. Similar patterns of BP2 and BPS biotransformation were observed among zebrafish models (primary hepatocytes, ZFL and ZELH-zfER cell lines). Interestingly, metabolic patterns in zebrafish models and in the human hepatic cell line HepaRG shared many similarities, while biotransformation rates in cell lines widely used for estrogenicity testing (MELN and T47D-KBLuc) were quantitatively low and qualitatively different. This study provides new data on the comparative metabolism of BP2 and BPS in human and fish cellular models that will help characterize their metabolic capabilities, and underlines the relevance of using in vitro zebrafish-based bioassays when screening for endocrine disrupting chemicals.

Identification of xenobiotic metabolites from biological fluids using flow injection analysis high-resolution mass spectrometry and post-acquisition data filtering.

RATIONALE: Concern for public health entails the need to evaluate the degree of exposure of population to toxicants. To do this, robust high-throughput approaches are required to be able to perform a large number of analyses in cohort studies. In this study, a data-filtering procedure was applied to mass spectral data acquired by direct analysis of biological fluids leading to rapid detection of metabolites in a model xenobiotic system. METHODS: Flow injection analysis (FIA) coupled to negative electrospray ionization (ESI)-LTQ Orbitrap Fourier transform mass spectrometry was used to directly analyze urine of rats treated with vinclozolin. Tandem mass spectrometry (MS/MS) experiments were subsequently performed for confirmation of a new metabolite structure. The isotope filtering based on the difference between accurate masses of (35)Cl and (37)Cl was applied to the raw data for the specific detection of ions containing at least one chlorine atom. RESULTS: Seven metabolites of vinclozolin were manually identified thanks to the characteristic isotope pattern of dichlorinated compounds. A new metabolite of vinclozolin was detected for the first time and identified as a sulfate conjugate. The application of an isotope-filtering procedure allowed the selective extraction of pertinent signals from the data. The processed mass spectrum was greatly simplified, significantly facilitating the detection of the seven metabolites previously identified. CONCLUSIONS: The use of FIA-HRMS in combination with dedicated bio-informatics data processing is shown to be an efficient approach for the rapid detection of metabolites in biological fluids. This is a very promising high-throughput approach for rapid characterization of the exposure status to xenobiotics.