Chemical Exposure Highlighted without Any A Priori Information in an Epidemiological Study by Metabolomic FT-ICR-MS Fingerprinting at High Throughput and High Resolution.

Epidemiological studies aim to assess associations between diseases and risk factors. Such investigations involve a large sample size and require powerful analytical methods to measure the effects of risk factors, resulting in a long analysis time. In this study, chemical exposure markers were detected as the main variables strongly affecting two components coming from a principal component analysis (PCA) exploration of the metabolomic data generated from urinary samples collected on a cohort of about 500 individuals using direct introduction coupled with a Fourier-transform ion cyclotron resonance instrument. The assignment of their chemical identity was first achieved based on their isotopic fine structures detected at very high resolution (Rp > 900,000). Their identification as dimethylbiguanide and sotalol was obtained at level 1, thanks to the available authentic chemical standards, tandem mass spectrometry (MS/MS) experiments, and collision cross section measurements. Epidemiological data confirmed that the subjects discriminated by PCA had declared to be prescribed these drugs for either type II diabetes or cardiac arrhythmia. Concentrations of these drugs in urine samples of interest were also estimated by rapid quantification using an external standard calibration method, direct introduction, and MS/MS experiments. Regression analyses showed a good correlation between the estimated drug concentrations and the scores of individuals distributed on these specific PCs. The detection of these chemical exposure markers proved the potential of the proposed high-throughput approach without any prior drug exposure knowledge as a powerful emerging tool for rapid and large-scale phenotyping of subjects enrolled in epidemiological studies to rapidly characterize the chemical exposome and adherence to medical prescriptions.

Metabolomic signatures in elite cyclists: differential characterization of a seeming normal endocrine status regarding three serum hormones.

INTRODUCTION: Serum phenotyping of elite cyclists regarding cortisol, IGF1 and testosterone is a way to detect endocrine disruptions possibly explained by exercise overload, non-balanced diet or by doping. This latter disruption-driven approach is supported by fundamental physiology although without any evidence of any metabolic markers. OBJECTIVES: Serum samples were distributed through Low, High or Normal endocrine classes according to hormone concentration. A 1H NMR metabolomic study of 655 serum obtained in the context of the longitudinal medical follow-up of 253 subjects was performed to discriminate the three classes for every endocrine phenotype. METHODS: An original processing algorithm was built which combined a partial-least squares-based orthogonal correction of metabolomic signals and a shrinkage discriminant analysis (SDA) to get satisfying classifications. An extended validation procedure was used to plan in larger size cohorts a minimal size to get a global prediction rate (GPR), i.e. the product of the three class prediction rates, higher than 99.9%. RESULTS: Considering the 200 most SDA-informative variables, a sigmoidal fitting of the GPR gave estimates of a minimal sample size to 929, 2346 and 1408 for cortisol, IGF1 and testosterone, respectively. Analysis of outliers from cortisol and testosterone Normal classes outside the 97.5%-confidence limit of score prediction revealed possibly (i) an inadequate protein intake for outliers or (ii) an intake of dietary ergogenics, glycine or glutamine, which might explain the significant presence of heterogeneous metabolic profiles in a supposedly normal cyclists subgroup. CONCLUSION: In a next validation metabolomics study of a so-sized cohort, anthropological, clinical and dietary metadata should be recorded in priority at the blood collection time to confirm these functional hypotheses.

ASICS: an R package for a whole analysis workflow of 1D 1H NMR spectra.

MOTIVATION: In metabolomics, the detection of new biomarkers from Nuclear Magnetic Resonance (NMR) spectra is a promising approach. However, this analysis remains difficult due to the lack of a whole workflow that handles spectra pre-processing, automatic identification and quantification of metabolites and statistical analyses, in a reproducible way. RESULTS: We present ASICS, an R package that contains a complete workflow to analyse spectra from NMR experiments. It contains an automatic approach to identify and quantify metabolites in a complex mixture spectrum and uses the results of the quantification in untargeted and targeted statistical analyses. ASICS was shown to improve the precision of quantification in comparison to existing methods on two independent datasets. In addition, ASICS successfully recovered most metabolites that were found important to explain a two level condition describing the samples by a manual and expert analysis based on bucketing. It also found new relevant metabolites involved in metabolic pathways related to risk factors associated with the condition. AVAILABILITY AND IMPLEMENTATION: ASICS is distributed as an R package, available on Bioconductor. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Potential of dynamically harmonized Fourier transform ion cyclotron resonance cell for high-throughput metabolomics fingerprinting: control of data quality.

Due to the presence of pollutants in the environment and food, the assessment of human exposure is required. This necessitates high-throughput approaches enabling large-scale analysis and, as a consequence, the use of high-performance analytical instruments to obtain highly informative metabolomic profiles. In this study, direct introduction mass spectrometry (DIMS) was performed using a Fourier transform ion cyclotron resonance (FT-ICR) instrument equipped with a dynamically harmonized cell. Data quality was evaluated based on mass resolving power (RP), mass measurement accuracy, and ion intensity drifts from the repeated injections of quality control sample (QC) along the analytical process. The large DIMS data size entails the use of bioinformatic tools for the automatic selection of common ions found in all QC injections and for robustness assessment and correction of eventual technical drifts. RP values greater than 106 and mass measurement accuracy of lower than 1 ppm were obtained using broadband mode resulting in the detection of isotopic fine structure. Hence, a very accurate relative isotopic mass defect (RΔm) value was calculated. This reduces significantly the number of elemental composition (EC) candidates and greatly improves compound annotation. A very satisfactory estimate of repeatability of both peak intensity and mass measurement was demonstrated. Although, a non negligible ion intensity drift was observed for negative ion mode data, a normalization procedure was easily applied to correct this phenomenon. This study illustrates the performance and robustness of the dynamically harmonized FT-ICR cell to perform large-scale high-throughput metabolomic analyses in routine conditions. Graphical abstract Analytical performance of FT-ICR instrument equipped with a dynamically harmonized cell.

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.

Cell proliferation and migration during early development of a symbiotic scleractinian coral.

In scleractinian reef-building corals, patterns of cell self-renewal, migration and death remain virtually unknown, limiting our understanding of cellular mechanisms underlying initiation of calcification, and ontogenesis of the endosymbiotic dinoflagellate relationship. In this study, we pulse-labelled the coral Stylophora pistillata for 24 h with BrdU at four life stages (planula, early metamorphosis, primary polyp and adult colony) to investigate coral and endosymbiont cell proliferation during development, while simultaneously recording TUNEL-positive (i.e. apoptotic) nuclei. In the primary polyp, the fate of BrdU-labelled cells was tracked during a 3-day chase. The pharynx and gastrodermis were identified as the most proliferative tissues in the developing polyp, and BrdU-labelled cells accumulated in the surface pseudostratified epithelium and the skeletogenic calicodermis during the chase, revealing cell migration to these epithelia. Surprisingly, the lowest cell turnover was recorded in the calicodermis at all stages, despite active, ongoing skeletal deposition. In dinoflagellate symbionts, DNA synthesis was systematically higher than coral host gastrodermis, especially in planula and early metamorphosis. The symbiont to host cell ratio remained constant, however, indicating successive post-mitotic control mechanisms by the host of its dinoflagellate density in early life stages, increasingly shifting to apoptosis in the growing primary polyp.

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.

Innovative direct introduction-ion mobility-mass spectrometry (DI-IM-MS) approach for fast and robust isomer-specific quantification in a complex matrix: Application to 2'-fucosyllactose (2'-FL) in breast milk.

Identification and specific quantification of isomers in a complex biological matrix by mass spectrometry alone is not an easy task due to their identical chemical formula and therefore their same mass-to-charge ratio (m/z). Here, the potential of direct introduction combined with ion mobility-mass spectrometry (DI-IM-MS) for rapid quantification of isomers as human milk oligosaccharides (HMOs) was investigated. Differences in HMO profiles between various analyzed breast milk samples were highlighted using the single ion mobility monitoring (SIM2) acquisition for high ion mobility resolution detection. Furthermore, the Se+ (secretor) or Se- (non-secretor) phenotype could be assigned to breast milk samples studied based on their HMO contents, especially on the response of 2'-fucosyllactose (2'-FL) and lacto-N-fucopentaose I (LNFP I). The possibility of quantifying a specific isomer in breast milk by DI-IM-MS was also investigated. The standard addition method allowed the determination of the 2'-FL despite the presence of other oligosaccharides, including 3-fucosyllactose (3-FL) isomer in breast milk. This proof-of-concept study demonstrated the high potential of such an approach for the rapid and convenient quantification of isomers in complex mixtures.

Low doses of bisphenol A induce gene expression related to lipid synthesis and trigger triglyceride accumulation in adult mouse liver.

UNLABELLED: Changes in lifestyle are suspected to have strongly influenced the current obesity epidemic. Based on recent experimental, clinical, and epidemiological work, it has been proposed that some food contaminants may exert damaging effects on endocrine and metabolic functions, thereby promoting obesity and associated metabolic diseases such as nonalcoholic fatty liver disease (NAFLD). In this work, we investigated the effect of one suspicious food contaminant, bisphenol A (BPA), in vivo. We used a transcriptomic approach in male CD1 mice exposed for 28 days to different doses of BPA (0, 5, 50, 500, and 5,000 µg/kg/day) through food contamination. Data analysis revealed a specific impact of low doses of BPA on the hepatic transcriptome, more particularly on genes involved in lipid synthesis. Strikingly, the effect of BPA on the expression of de novo lipogenesis followed a nonmonotonic dose-response curve, with more important effects at lower doses than at the higher dose. In addition to lipogenic enzymes (Acc, Fasn, Scd1), the expression of transcription factors such as liver X Receptor, the sterol regulatory element binding protein-1c, and the carbohydrate responsive element binding protein that govern the expression of lipogenic genes also followed a nonmonotonic dose-response curve in response to BPA. Consistent with an increased fatty acid biosynthesis, determination of fat in the liver showed an accumulation of cholesteryl esters and of triglycerides. CONCLUSION: Our work suggests that exposure to low BPA doses may influence de novo fatty acid synthesis through increased expression of lipogenic genes, thereby contributing to hepatic steatosis. Exposure to such contaminants should be carefully examined in the etiology of metabolic diseases such as NAFLD and nonalcoholic steatohepatitis.

The Human Meconium Metabolome and Its Evolution during the First Days of Life.

Meconium represents the first newborn stools, formed from the second month of gestation and excreted in the first days after birth. As an accumulative and inert matrix, it accumulates most of the molecules transferred through the placenta from the mother to the fetus during the last 6 months of pregnancy, and those resulting from the metabolic activities of the fetus. To date, only few studies dealing with meconium metabolomics have been published. In this study, we aimed to provide a comprehensive view of the meconium metabolic composition using 33 samples collected longitudinally from 11 healthy newborns and to analyze its evolution during the first 3 days of life. First, a robust and efficient methodology for metabolite extraction was implemented. Data acquisition was performed using liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS), using two complementary LC-HRMS conditions. Data preprocessing and treatment were performed using the Workflow4Metabolomics platform and the metabolite annotation was performed using our in-house database by matching accurate masses, retention times, and MS/MS spectra to those of pure standards. We successfully identified up to 229 metabolites at a high confidence level in human meconium, belonging to diverse chemical classes and from different origins. A progressive evolution of the metabolic profile was statistically evidenced, with sugars, amino acids, and some bacteria-derived metabolites being among the most impacted identified compounds. Our implemented analytical workflow allows a unique and comprehensive description of the meconium metabolome, which is related to factors, such as maternal diet and environment.

Loss of hepatocyte nuclear factor 1alpha function in human hepatocellular adenomas leads to aberrant activation of signaling pathways involved in tumorigenesis.

UNLABELLED: Hepatocellular adenomas (HCAs) are benign liver tumors that usually develop in women who are taking oral contraceptives. Among these tumors, biallelic inactivating mutations of the hepatocyte nuclear factor 1alpha (HNF1A) transcription factor have been frequently identified and in rare cases of hepatocellular carcinomas developed in noncirrhotic liver. Because HNF1A meets the genetic criteria of a tumor suppressor gene, we aimed to elucidate the tumorigenic mechanisms related to HNF1alpha inactivation in hepatocytes. We searched for signaling pathways aberrantly activated in human HNF1A-mutated HCA (H-HCA) using a genome-wide transcriptome analysis comparing five H-HCA with four normal livers. We validated the main pathways by quantitative reverse transcription polymerase chain reaction (RT-PCR) and western blotting in a large series of samples. Then, we assessed the role of HNF1alpha in the observed deregulations in hepatocellular cell models (HepG2 and Hep3B) by silencing its endogenous expression using small interfering RNA. Along with the previously described induction of glycolysis and lipogenesis, H-HCA also displayed overexpression of several genes encoding growth factor receptors, components of the translation machinery, cell cycle, and angiogenesis regulators, with, in particular, activation of the mammalian target of rapamycin (mTOR) pathway. Moreover, estradiol detoxification activities were shut down, suggesting a hypersensitivity of H-HCA to estrogenic stimulation. In the cell model, inhibition of HNF1alpha recapitulated most of these identified transcriptional deregulations, demonstrating that they were related to HNF1alpha inhibition. CONCLUSION: H-HCA showed a combination of alterations related to HNF1alpha inactivation that may cooperate to promote tumor development. Interestingly, mTOR appears as a potential new attractive therapeutic target for treatment of this group of HCAs.

Integrating variability in half-lives and dietary intakes to predict mercury concentration in hair.

Methylmercury (MeHg) is a bioaccumulative environmental toxin that exerts its effect on fetal and infant neurodevelopment. Mercury concentration in hair is a good biomarker of MeHg accumulation in the body, with seafood being the main source of MeHg in humans. Therefore, modeling the link between food intake and mercury concentration in hair is a key step in assessing the risk of MeHg exposure. Using repeated measurements of diet and mercury concentration in hair, we studied 125 French pregnant women who consumed seafood (e.g., fish, mollusks and crustaceans) and compared their individual estimated dietary MeHg intakes with their hair mercury concentrations. We used a one-compartment toxicokinetic model for these comparisons. We integrated and estimated the between-person variability in MeHg half-life into the model. In a second model, we took into account an intra-individual MeHg intake variability to improve the performance of the toxicokinetic model.

Mass spectrometry-based metabolomics for an in-depth questioning of human health.

Today, metabolomics is becoming an indispensable tool to get a more comprehensive analysis of complex living systems, providing insights on multiple aspects of physiology. Although its application in large scale population-based studies is very challenging due to the processing of large sample sets as well as the complexity of data information, its potential to characterize human health is well recognized. Technological advances in metabolomics pave the way for the efficient biomarker discovery of disease etiology, diagnosis and prognosis. Here, different steps of the metabolomics workflow, particularly mass spectrometry-based approaches, are discussed to demonstrate the potential of metabolomics to address biological questioning in human health. First an overview of metabolomics is provided with its interest in human health studies. Analytical development and advances in mass spectrometry instrumentation and computational tools are discussed regarding their application limits. Advancing metabolomics for applicability in human health and large-scale studies is presented and discussed in conclusion.

The maturity in fetal pigs using a multi-fluid metabolomic approach.

In mammalian species, the first days after birth are an important period for survival and the mortality rate is high before weaning. In pigs, perinatal deaths average 20% of the litter, with important economic and societal consequences. Maturity is one of the most important factors that influence piglet survival at birth. Maturity can be defined as the outcome of complex mechanisms of intra-uterine development and maturation during the last month of gestation. Here, we provide new insights into maturity obtained by studying the end of gestation at two different stages (3 weeks before term and close to term) in two breeds of pigs that strongly differ in terms of neonatal survival. We used metabolomics to characterize the phenotype, to identify biomarkers, and provide a comprehensive understanding of the metabolome of the fetuses in late gestation in three fluids (plasma, urine, and amniotic fluid). Our results show that the biological processes related to amino acid and carbohydrate metabolisms are critical for piglet maturity. We confirm the involvement of some previously described metabolites associated with delayed growth (e.g., proline and myo-inositol). Altogether, our study proposes new routes for improved characterization of piglet maturity at birth.

Identification of potential mechanisms of toxicity after di-(2-ethylhexyl)-phthalate (DEHP) adult exposure in the liver using a systems biology approach.

Phthalates are industrial additives widely used as plasticizers. In addition to deleterious effects on male genital development, population studies have documented correlations between phthalates exposure and impacts on reproductive tract development and on the metabolic syndrome in male adults. In this work we investigated potential mechanisms underlying the impact of DEHP on adult mouse liver in vivo. A parallel analysis of hepatic transcript and metabolic profiles from adult mice exposed to varying DEHP doses was performed. Hepatic genes modulated by DEHP are predominantly PPARalpha targets. However, the induction of prototypic cytochrome P450 genes strongly supports the activation of additional NR pathways, including Constitutive Androstane Receptor (CAR). Integration of transcriptomic and metabonomic profiles revealed a correlation between the impacts of DEHP on genes and metabolites related to heme synthesis and to the Rev-erbalpha pathway that senses endogenous heme level. We further confirmed the combined impact of DEHP on the hepatic expression of Alas1, a critical enzyme in heme synthesis and on the expression of Rev-erbalpha target genes involved in the cellular clock and in energy metabolism. This work shows that DEHP interferes with hepatic CAR and Rev-erbalpha pathways which are both involved in the control of metabolism. The identification of these new hepatic pathways targeted by DEHP could contribute to metabolic and endocrine disruption associated with phthalate exposure. Gene expression profiles performed on microdissected testis territories displayed a differential responsiveness to DEHP. Altogether, this suggests that impacts of DEHP on adult organs, including testis, could be documented and deserve further investigations.

Genomic consequences of cytochrome P450 2C9 overexpression in human hepatoma cells.

Cytochrome P450 2C9 (P450 2C9) is one of the most important P450 isoforms in the human liver, as it metabolizes numerous exogenous and endogenous substrates. Moreover, it is inducible by several compounds, such as rifampicin, phenobarbital, and NSAIDs (nonsteroidal anti-inflammatories). The aim of this study was to investigate the global cellular consequences of P450 2C9 overexpression at the transcriptional level using an untargeted approach: pangenomic microarrays. Recombinant adenovirus was used to express P450 2C9 instead of an inducer to prevent a per se effect of inducer or its metabolites. P450 2C9 overexpression induced endoplasmic reticulum (ER) stress and regulated genes implicated in the unfolded protein response (UPR) as heat shock protein (HSP) (we studied particurlarly HSPA5 and HSPB1) and in the endoplasmic reticulum associated degradation (ERAD) system as Sec61 and ubiquitin and proteasome pathways. UPR and ERAD are two mechanisms of adaptative response to ER stress. Moreover, activation of Akt was observed in HepG2 cells that overexpress P450 2C9 and might participate in the cellular adaptive response to stress, thus leading to the activation of cell survival pathways. UPR and ERAD should be caused by accumulation of native and misfolded P450 2C9 protein. Our results indicated that P450 2C9 overexpression did not lead to toxicity but induced an ER stress due to protein overexpression rather than mono-oxygenase activity. The ER stress triggered activation of the adaptative response and of pathways leading to cell survival.

Bacterial-Fungal Interactions in the Kelp Endomicrobiota Drive Autoinducer-2 Quorum Sensing.

Brown macroalgae are an essential component of temperate coastal ecosystems and a growing economic sector. They harbor diverse microbial communities that regulate algal development and health. This algal holobiont is dynamic and achieves equilibrium via a complex network of microbial and host interactions. We now report that bacterial and fungal endophytes associated with four brown algae (Ascophyllum nodosum, Pelvetia canaliculata, Laminaria digitata, and Saccharina latissima) produce metabolites that interfere with bacterial autoinducer-2 quorum sensing, a signaling system implicated in virulence and host colonization. Additionally, we performed co-culture experiments combined to a metabolomic approach and demonstrated that microbial interactions influence production of metabolites, including metabolites involved in quorum sensing. Collectively, the data highlight autoinducer-2 quorum sensing as a key metabolite in the complex network of interactions within the algal holobiont.

Tracking main environmental factors masking a minor steroidal doping effect using metabolomic analysis of horse urine by liquid chromatography-high-resolution mass spectrometry.

There is an urgent need to implement holistic and untargeted doping control protocols with improved discriminatory power, compared to conventional methods that only target doping agents. Metabolomics, which aims to characterize all metabolites present in biological matrices, could fulfill this need. In this context, the aim of this study was to evaluate the impact of environmental factors on the ability to obtain a metabolic signature of stanozolol administration in horse doping situation. Urine samples from 16 horses breeded in two different places were collected over a one-year period, before, during and seven months after the administration of stanozolol, a horse doping agent. Metabolomic analysis was performed using ultra-high pressure reverse phase liquid chromatography coupled to quadrupole-time-of-flight mass spectrometry (MS). Results showed a major impact of the nutritional regimen, drug administration (for de-worming purpose) and breeding place on the metabolite profiles of horse urines, which hampered the detection of metabolic perturbations induced by stanozolol administration. After having used MS/MS experiments to characterize some MS features related to these environmental factors, we showed that highlighting and then removing the features impacted by these confounding factors before performing supervised multivariate statistical analyses could address this issue. In conclusion, adequate consideration should be given to environmental and physiological factors; otherwise, they can emerge as confounding factors and conceal doping administration.

Specificity of the metabolic signatures of fish from cyanobacteria rich lakes.

With the increasing impact of the global warming, occurrences of cyanobacterial blooms in aquatic ecosystems are becoming a main worldwide ecological concern. Due to their capacity to produce potential toxic metabolites, interactions between the cyanobacteria, their cyanotoxins and the surrounding freshwater organisms have been investigated during the last past years. Non-targeted metabolomic analyses have the powerful capacity to study simultaneously a high number of metabolites and thus to investigate in depth the molecular signatures between various organisms encountering different environmental scenario, and potentially facing cyanobacterial blooms. In this way, the liver metabolomes of two fish species (Perca fluviatilis and Lepomis gibbosus) colonizing various peri-urban lakes of the Île-de-France region displaying high biomass of cyanobacteria, or not, were investigated. The fish metabolome hydrophilic fraction was analyzed by 1H NMR analysis coupled with Batman peak treatment for the quantification and the annotation attempt of the metabolites. The results suggest that similar metabolome profiles occur in both fish species, for individuals collected from cyanobacterial blooming lakes compared to organism from non-cyanobacterial dominant environments. Overall, such environmental metabolomic pilot study provides new research perspectives in ecology and ecotoxicology fields, and may notably provide new information concerning the cyanobacteria/fish ecotoxicological interactions.

Evaluation and validation of an analytical approach for high-throughput metabolomic fingerprinting using direct introduction-high-resolution mass spectrometry: Applicability to classification of urine of scrapie-infected ewes.

Direct injection-mass spectrometry can be used to perform high-throughput metabolomic fingerprinting. This work aims to evaluate a global analytical workflow in terms of sample preparation (urine sample dilution), high-resolution detection (quality of generated data based on criteria such as mass measurement accuracy and detection sensitivity) and data analysis using dedicated bioinformatics tools. Investigation was performed on a large number of biological samples collected from sheep infected or not with scrapie. Direct injection-mass spectrometry approach is usually affected by matrix effects, eventually hampering detection of some relevant biomarkers. Reference compounds were spiked in biological samples to help evaluate the quality of direct injection-mass spectrometry data produced by Fourier Transform mass spectrometry. Despite the potential of high-resolution detection, some drawbacks still remain. The most critical is the presence of matrix effects, which could be minimized by optimizing the sample dilution factor. The data quality in terms of mass measurement accuracy and reproducible intensity was evaluated. Good repeatability was obtained for the chosen dilution factor (i.e., 2000). More than 150 analyses were performed in less than 16 hours using the optimized direct injection-mass spectrometry approach. Discrimination of different status of sheeps in relation to scrapie infection (i.e., scrapie-affected, preclinical scrapie or healthy) was obtained from the application of Shrinkage Discriminant Analysis to the direct injection-mass spectrometry data. The most relevant variables related to this discrimination were selected and annotated. This study demonstrated that the choice of appropriated dilution faction is indispensable for producing quality and informative direct injection-mass spectrometry data. Successful application of direct injection-mass spectrometry approach for high throughput analysis of a large number of biological samples constitutes the proof of the concept.