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.

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.

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.

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.

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.

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.

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.

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.

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.

Author Correction: Metabolic changes in Medaka fish induced by cyanobacterial exposures in mesocosms: an integrative approach combining proteomic and metabolomic analyses.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

Exposure of livestock to GM feeds: Detectability and measurement.

This review explores the possibilities to determine livestock consumption of genetically modified (GM) feeds/ingredients including detection of genetically modified organism (GMO)-related DNA or proteins in animal samples, and the documentary system that is in place for GM feeds under EU legislation. The presence and level of GMO-related DNA and proteins can generally be readily measured in feeds, using established analytical methods such as polymerase chain reaction and immuno-assays, respectively. Various technical challenges remain, such as the simultaneous detection of multiple GMOs and the identification of unauthorized GMOs for which incomplete data on the inserted DNA may exist. Given that transfer of specific GMO-related DNA or protein from consumed feed to the animal had seldom been observed, this cannot serve as an indicator of the individual animal's prior exposure to GM feeds. To explore whether common practices, information exchange and the specific GM feed traceability system in the EU would allow to record GM feed consumption, the dairy chain in Catalonia, where GM maize is widely grown, was taken as an example. It was thus found that this system would neither enable determination of an animal's consumption of specific GM crops, nor would it allow for quantitation of the exposure.

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.

Physiological effects caused by microcystin-producing and non-microcystin producing Microcystis aeruginosa on medaka fish: A proteomic and metabolomic study on liver.

Cyanobacterial blooms have become a common phenomenon in eutrophic freshwater ecosystems worldwide. Microcystis is an important bloom-forming and toxin-producing genus in continental aquatic ecosystems, which poses a potential risk to Human populations as well as on aquatic organisms. Microcystis is known to produce along with various bioactive peptides, the microcystins (MCs) that have attracted more attention notably due to their high hepatotoxicity. To better understand the effects of cyanobacterial blooms on fish, medaka fish (Oryzias latipes) were sub-chronically exposed to either non-MC-producing or MC-producing living strains and, for this latter, to its subsequent MC-extract of Microcystis aeruginosa. Toxicological effects on liver have been evaluated through the combined approach of histopathology and 'omics' (i.e. proteomics and metabolomics). All treatments induce sex-dependent effects at both cellular and molecular levels. Moreover, the modalities of exposure appear to induce differential responses as the direct exposure to the cyanobacterial strains induce more acute effects than the MC-extract treatment. Our histopathological observations indicate that both non-MC-producing and MC-producing strains induce cellular impairments. Both proteomic and metabolomic analyses exhibit various biological disruptions in the liver of females and males exposed to strain and extract treatments. These results support the hypothesis that M. aeruginosa is able to produce bioactive peptides, other than MCs, which can induce toxicological effects in fish liver. Moreover, they highlight the importance of considering cyanobacterial cells as a whole to assess the realistic environmental risk of cyanobacteria on fish.

Metabolic changes in Medaka fish induced by cyanobacterial exposures in mesocosms: an integrative approach combining proteomic and metabolomic analyses.

Cyanobacterial blooms pose serious threats to aquatic organisms and strongly impact the functioning of aquatic ecosystems. Due to their ability to produce a wide range of potentially bioactive secondary metabolites, so called cyanotoxins, cyanobacteria have been extensively studied in the past decades. Proteomic and metabolomic analyses provide a unique opportunity to evaluate the global response of hundreds of proteins and metabolites at a glance. In this study, we provide the first combined utilization of these methods targeted to identify the response of fish to bloom-forming cyanobacteria. Medaka fish (Oryzias latipes) were exposed for 96 hours either to a MC-producing or to a non-MC-producing strain of Microcystis aeruginosa and cellular, proteome and metabolome changes following exposure to cyanobacteria were characterized in the fish livers. The results suggest that a short-term exposure to cyanobacteria, producing or not MCs, induces sex-dependent molecular changes in medaka fish, without causing any cellular alterations. Globally, molecular entities involved in stress response, lipid metabolism and developmental processes exhibit the most contrasted changes following a cyanobacterial exposure. Moreover, it appears that proteomic and metabolomic analyses are useful tools to verify previous information and to additionally bring new horizons concerning molecular effects of cyanobacteria on fish.

Global metabolome changes induced by cyanobacterial blooms in three representative fish species.

Cyanobacterial blooms induce important ecological constraints for aquatic organisms and strongly impact the functioning of aquatic ecosystems. In the past decades, the effects of the cyanobacterial secondary metabolites, so called cyanotoxins, have been extensively studied in fish. However, many of these studies have used targeted approaches on specific molecules, which are thought to react to the presence of these specific cyanobacterial compounds. Since a few years, untargeted metabolomic approaches provide a unique opportunity to evaluate the global response of hundreds of metabolites at a glance. In this way, our study provides the first utilization of metabolomic analyses in order to identify the response of fish exposed to bloom-forming cyanobacteria. Three relevant fish species of peri-urban lakes of the European temperate regions were exposed for 96h either to a microcystin (MC)-producing or to a non-MC-producing strain of Microcystis aeruginosa and metabolome changes were characterized in the liver of fish. The results suggest that a short-term exposure to those cyanobacterial biomasses induces metabolome changes without any response specificity linked to the fish species considered. Candidate metabolites are involved in energy metabolism and antioxidative response, which could potentially traduce a stress response of fish submitted to cyanobacteria. These results are in agreement with the already known information and could additionally bring new insights about the molecular interactions between cyanobacteria and fish.

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.

Deep sexual dimorphism in adult medaka fish liver highlighted by multi-omic approach.

Sexual dimorphism describes the features that discriminate between the two sexes at various biological levels. Especially, during the reproductive phase, the liver is one of the most sexually dimorphic organs, because of different metabolic demands between the two sexes. The liver is a key organ that plays fundamental roles in various physiological processes, including digestion, energetic metabolism, xenobiotic detoxification, biosynthesis of serum proteins, and also in endocrine or immune response. The sex-dimorphism of the liver is particularly obvious in oviparous animals, as the female liver is the main organ for the synthesis of oocyte constituents. In this work, we are interested in identifying molecular sexual dimorphism in the liver of adult medaka fish and their sex-variation in response to hepatotoxic exposures. By developing an integrative approach combining histology and different high-throughput omic investigations (metabolomics, proteomics and transcriptomics), we were able to globally depict the strong sexual dimorphism that concerns various cellular and molecular processes of hepatocytes comprising protein synthesis, amino acid, lipid and polysaccharide metabolism, along with steroidogenesis and detoxification. The results of this work imply noticeable repercussions on the biology of oviparous organisms environmentally exposed to chemical or toxin issues.

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.