NMR metabolite quantification of a synthetic urine sample: an inter-laboratory comparison of processing workflows.

INTRODUCTION: Absolute quantification of individual metabolites in complex biological samples is crucial in targeted metabolomic profiling. OBJECTIVES: An inter-laboratory test was performed to evaluate the impact of the NMR software, peak-area determination method (integration vs. deconvolution) and operator on quantification trueness and precision. METHODS: A synthetic urine containing 32 compounds was prepared. One site prepared the urine and calibration samples, and performed NMR acquisition. NMR spectra were acquired with two pulse sequences including water suppression used in routine analyses. The pre-processed spectra were sent to the other sites where each operator quantified the metabolites using internal referencing or external calibration, and his/her favourite in-house, open-access or commercial NMR tool. RESULTS: For 1D NMR measurements with solvent presaturation during the recovery delay (zgpr), 20 metabolites were successfully quantified by all processing strategies. Some metabolites could not be quantified by some methods. For internal referencing with TSP, only one half of the metabolites were quantified with a trueness below 5%. With peak integration and external calibration, about 90% of the metabolites were quantified with a trueness below 5%. The NMRProcFlow integration module allowed the quantification of several additional metabolites. The number of quantified metabolites and quantification trueness improved for some metabolites with deconvolution tools. Trueness and precision were not significantly different between zgpr- and NOESYpr-based spectra for about 70% of the variables. CONCLUSION: External calibration performed better than TSP internal referencing. Inter-laboratory tests are useful when choosing to better rationalize the choice of quantification tools for NMR-based metabolomic profiling and confirm the value of spectra deconvolution tools.

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 .

Developmental Stage, Solid Food Introduction, and Suckling Cessation Differentially Influence the Comaturation of the Gut Microbiota and Intestinal Epithelium in Rabbits.

BACKGROUND: In mammals, the establishment around weaning of a symbiotic relationship between the gut microbiota and its host determines long-term health. OBJECTIVES: The aim of this study was to identify the factors driving the comaturation of the gut microbiota and intestinal epithelium at the suckling-to-weaning transition. We hypothesized that the developmental stage, solid food ingestion, and suckling cessation contribute to this process. METHODS: From birth to day 18, Hyplus rabbits were exclusively suckling. From day 18 to day 25, rabbits were 1) exclusively suckling; 2) suckling and ingesting solid food; or 3) exclusively ingesting solid food. The microbiota (16S amplicon sequencing), metabolome (nuclear magnetic resonance), and epithelial gene expression (high-throughput qPCR) were analyzed in the cecum at days 18 and 25. RESULTS: The microbiota structure and metabolic activity were modified with age when rabbits remained exclusively suckling. The epithelial gene expression of nutrient transporters, proliferation markers, and innate immune factors were also regulated with age (e.g., 1.5-fold decrease of TLR5). Solid food ingestion by suckling rabbits had a major effect on the gut microbiota by increasing its α diversity, remodeling its structure (e.g., 6.3-fold increase of Ruminococcaceae), and metabolic activity (e.g., 4.6-fold increase of butyrate). Solid food introduction also regulated the gene expression of nutrient transporters, differentiation markers, and innate immune factors in the epithelium (e.g., 3-fold increase of nitric oxide synthase). Suckling cessation had no effect on the microbiota, while it regulated the expression of genes involved in epithelial differentiation and immunoglobulin transport (e.g., 2.5-increase of the polymeric immunoglobulin receptor). CONCLUSIONS: In rabbits, the maturation of the microbiota at the suckling-to-weaning transition is driven by the introduction of solid food and, to a lesser extent, by the developmental stage. In contrast, the maturation of the intestinal epithelium at the suckling-to-weaning transition is under the influence of the developmental stage, solid food introduction, and suckling cessation.

Gut Microbiota-Derived Metabolite Signature in Suckling and Weaned Piglets.

The gut microbiota plays a key role in intestinal development at the suckling-to-weaning transition. The objective of this study was to analyze the production of metabolites by the gut microbiota in suckling and weaned piglets. We studied piglets raised in two separate maternity farms and weaned at postnatal day 21 in the same farm. The fecal metabolome (1H nuclear magnetic resonance) and the microbiota composition (16S rRNA gene amplicon sequencing) and its predicted functions (PICRUSt2) were analyzed in the same piglets during the suckling period (postnatal day 13) and 2 days after weaning (postnatal day 23). The relative concentrations of the bacterial metabolites methylamine, dimethylamine, cadaverine, tyramine, putrescine, 5-aminovalerate, succinate, and 3-(4-hydroxyphenylpropionate) were higher during the suckling period than after weaning. In contrast, the relative concentrations of the short-chain fatty acids acetate and propionate were higher after weaning than during the suckling period. The maternity of origin of piglets also influenced the level of some bacterial metabolites (propionate and isobutyrate). The fecal metabolome signatures observed in suckling and weaned piglets were associated with specific microbiota-predicted functionalities, structure, and diversity. Gut microbiota-derived metabolites, which are differentially abundant between suckling and weaned piglets (e.g., short-chain fatty acids and biogenic amines), are known to regulate gut health. Thus, identification of metabolome signatures in suckling and weaned piglets paves the way for the development of health-promoting nutritional strategies, targeting the production of bacterial metabolites in early life.

Joint Automatic Metabolite Identification and Quantification of a Set of 1H NMR Spectra.

Metabolomics is a promising approach to characterize phenotypes or to identify biomarkers. It is also easily accessible through NMR, which can provide a comprehensive understanding of the metabolome of any living organisms. However, the analysis of 1H NMR spectrum remains difficult, mainly due to the different problems encountered to perform automatic identification and quantification of metabolites in a reproducible way. In addition, methods that perform automatic identification and quantification of metabolites are often designed to process one given complex mixture spectrum at a time. Hence, when a set of complex mixture spectra coming from the same experiment has to be processed, the approach is simply repeated independently for every spectrum, despite their resemblance. Here, we present new methods that are the first to either align spectra or to identify and quantify metabolites by integrating information coming from several complex spectra of the same experiment. The performances of these new methods are then evaluated on both simulated and real datasets. The results show an improvement in the metabolite identification and in the accuracy of metabolite quantifications, especially when the concentration is low. This joint procedure is available in version 2.0 of ASICS package.

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.

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.

Milk metabolome reveals variations on enteric methane emissions from dairy cows fed a specific inhibitor of the methanogenesis pathway.

Metabolome profiling in biological fluids is an interesting approach for exploring markers of methane emissions in ruminants. In this study, a multiplatform metabolomics approach was used for investigating changes in milk metabolic profiles related to methanogenesis in dairy cows. For this purpose, 25 primiparous Holstein cows at similar lactation stage were fed the same diet supplemented with (treated, n = 12) or without (control, n = 13) a specific antimethanogenic additive that reduced enteric methane production by 23% with no changes in intake, milk production, and health status. The study lasted 6 wk, with sampling and measures performed in wk 5 and 6. Milk samples were analyzed using 4 complementary analytical methods, including 2 untargeted (nuclear magnetic resonance and liquid chromatography coupled to a quadrupole-time-of-flight mass spectrometer) and 2 targeted (liquid chromatography-tandem mass spectrometry and gas chromatography coupled to a flame ionization detector) approaches. After filtration, variable selection and normalization data from each analytical platform were then analyzed using multivariate orthogonal partial least square discriminant analysis. All 4 analytical methods were able to differentiate cows from treated and control groups. Overall, 38 discriminant metabolites were identified, which affected 10 metabolic pathways including methane metabolism. Some of these metabolites such as dimethylsulfoxide, dimethylsulfone, and citramalic acid, detected by nuclear magnetic resonance or liquid chromatography-mass spectrometry methods, originated from the rumen microbiota or had a microbial-host animal co-metabolism that could be associated with methanogenesis. Also, discriminant milk fatty acids detected by targeted gas chromatography were mostly of ruminal microbial origin. Other metabolites and metabolic pathways significantly affected were associated with AA metabolism. These findings provide new insight on the potential role of milk metabolites as indicators of enteric methane modifications in dairy cows.

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.

Longitudinal analysis of the salivary metabolome of breast-fed and formula-fed infants over the first year of life.

INTRODUCTION: The salivary metabolome has been increasingly studied over the past ten years due to the potential of saliva as a non-invasive source of biomarkers. However, although saliva has been studied in relation to various diseases, its dynamic evolution during life is not known. This is particularly true for the first months of life. Infancy is indeed a critical period during which numerous behavioural and physiological events occur, such as dietary transitions and tooth eruption, which can lead to important biological modifications in the oral cavity. OBJECTIVES: The aim of this work was therefore to study the evolution of the salivary metabolome during the first months of life by 1H NMR. METHODS: Saliva of 32 infants with different milk feeding histories (breast vs formula) was collected at 6 stages, including 3 months old, 15 days before the onset of complementary feeding (CF), approximately 15 days after the onset of CF, approximately 21 days after the onset of CF and at approximately 11 and 15 months, and analysed. RESULTS: The longitudinal analysis showed a significant modification of the profiles of 18 metabolites over time; 14 presented an increase in abundance whereas 4 presented a decrease. These modifications seemed to be linked, for the most part, to an increase in oral microbial metabolism. Milk feeding history during the first months of life had no effect on metabolites. CONCLUSION: This work shows that the salivary metabolome should be considered when studying the changes occurring during infancy.

Large-Scale Modeling Approach Reveals Functional Metabolic Shifts during Hepatic Differentiation.

Being able to explore the metabolism of broad metabolizing cells is of critical importance in many research fields. This article presents an original modeling solution combining metabolic network and omics data to identify modulated metabolic pathways and changes in metabolic functions occurring during differentiation of a human hepatic cell line (HepaRG). Our results confirm the activation of hepato-specific functionalities and newly evidence modulation of other metabolic pathways, which could not be evidenced from transcriptomic data alone. Our method takes advantage of the network structure to detect changes in metabolic pathways that do not have gene annotations and exploits flux analyses techniques to identify activated metabolic functions. Compared to the usual cell-specific metabolic network reconstruction approaches, it limits false predictions by considering several possible network configurations to represent one phenotype rather than one arbitrarily selected network. Our approach significantly enhances the comprehensive and functional assessment of cell metabolism, opening further perspectives to investigate metabolic shifts occurring within various biological contexts.

Patulin transformation products and last intermediates in its biosynthetic pathway, E- and Z-ascladiol, are not toxic to human cells.

Patulin is the main mycotoxin contaminating apples. During the brewing of alcoholic beverages, this mycotoxin is degraded to ascladiol, which is also the last precursor of patulin. The present study aims (1) to characterize the last step of the patulin biosynthetic pathway and (2) to describe the toxicity of ascladiol. A patE deletion mutant was generated in Penicillium expansum. In contrast to the wild strain, this mutant does not produce patulin but accumulates high levels of E-ascladiol with few traces of Z-ascladiol. This confirms that patE encodes the patulin synthase involved in the conversion of E-ascladiol to patulin. After purification, cytotoxicities of patulin and E- and Z-ascladiol were investigated on human cell lines from liver, kidney, intestine, and immune system. Patulin was cytotoxic for these four cell lines in a dose-dependent manner. By contrast, both E- and Z-ascladiol were devoid of cytotoxicity. Microarray analyses on human intestinal cells treated with patulin and E-ascladiol showed that the latter, unlike patulin, did not alter the whole human transcription. These results demonstrate that E- and Z-ascladiol are not toxic and therefore patulin detoxification strategies leading to the accumulation of ascladiol are good approaches to limit the patulin risk.

Potential input from metabolomics for exploring and understanding the links between environment and health.

Humans may be exposed via their environment to multiple chemicals as a consequence of human activities and use of synthetic products. Little knowledge is routinely generated on the hazards of these chemical mixtures. The metabolomic approach is widely used to identify metabolic pathways modified by diseases, drugs, or exposures to toxicants. This review, based on the state of the art of the current applications of metabolomics in environmental health, attempts to determine whether metabolomics might constitute an original approach to the study of associations between multiple, low-dose environmental exposures in humans. Studying the biochemical consequences of complex environmental exposures is a challenge demanding the development of careful experimental and epidemiological designs, in order to take into account possible confounders associated with the high level of interindividual variability induced by different lifestyles. The choices of populations studied, sampling and storage procedures, statistical tools used, and system biology need to be considered. Suggestions for improved experimental and epidemiological designs are described. Evidence indicates that metabolomics may be a powerful tool in environmental health in the identification of both complex exposure biomarkers directly in human populations and modified metabolic pathways, in an attempt to improve understanding the underlying environmental causes of diseases. Nevertheless, the validity of biomarkers and relevancy of animal-to-human extrapolation remain key challenges that need to be properly explored.

Metabolomic study of fatty livers in ducks: Identification by 1H-NMR of metabolic markers associated with technological quality.

The control of fatty liver fat loss during cooking is a major issue. Previous studies showed that fat loss was influenced by bird production factors and liver technological treatments. However, part of the variability in fat loss remained uncontrolled. To provide enhanced insights into the determinism of fatty liver quality, liver hydrophilic metabolite profiles were measured by nuclear magnetic resonance of the proton ((1)H-NMR). The study aimed at i) comparing fatty livers with extreme fat loss values and ii) at characterizing the effect of postmortem evolution of livers during chilling. A group of 240 male mule ducks (Cairina moschata × Anas platyrhynchos) was reared and overfed. Their livers were sampled at 20 min and 6 h postmortem. Of these birds, 2 groups of ducks were built with extreme values on the technological yield (TY; TY = 100 - % fat loss; the low-fat-loss group, TY = 89.9%, n = 13; and the high-fat-loss group, TY = 68.3%, n = 12, P < 0.001). The (1)H-NMR analyses showed that the high-fat-loss livers were more advanced in postmortem biochemical and structural changes than low-fat-loss livers early postmortem. The high-fat-loss livers were characterized by hydrolysis of glycogen into glucose, worse integrity of cell membrane with diminution of compounds of phospholipids, and higher catabolic processes. The accelerated postmortem processes may be the origin of the differences in fat loss during cooking. During the early postmortem period, the adenosine triphosphate amount in liver cells was strongly reduced and lipolysis of triglycerides seemed to be enhanced. The glycogen stored in liver was first converted into glucose, but contrary to what happens in postmortem muscles, glucose was not converted into lactate.

Integrative Multimodal Metabolomics to Early Predict Cognitive Decline Among Amyloid Positive Community-Dwelling Older Adults.

Alzheimer's disease is strongly linked to metabolic abnormalities. We aimed to distinguish amyloid-positive people who progressed to cognitive decline from those who remained cognitively intact. We performed untargeted metabolomics of blood samples from amyloid-positive individuals, before any sign of cognitive decline, to distinguish individuals who progressed to cognitive decline from those who remained cognitively intact. A plasma-derived metabolite signature was developed from Supercritical Fluid chromatography coupled with high-resolution mass spectrometry (SFC-HRMS) and nuclear magnetic resonance (NMR) metabolomics. The 2 metabolomics data sets were analyzed by Data Integration Analysis for Biomarker discovery using Latent approaches for Omics studies (DIABLO), to identify a minimum set of metabolites that could describe cognitive decline status. NMR or SFC-HRMS data alone cannot predict cognitive decline. However, among the 320 metabolites identified, a statistical method that integrated the 2 data sets enabled the identification of a minimal signature of 9 metabolites (3-hydroxybutyrate, citrate, succinate, acetone, methionine, glucose, serine, sphingomyelin d18:1/C26:0 and triglyceride C48:3) with a statistically significant ability to predict cognitive decline more than 3 years before decline. This metabolic fingerprint obtained during this exploratory study may help to predict amyloid-positive individuals who will develop cognitive decline. Due to the high prevalence of brain amyloid-positivity in older adults, identifying adults who will have cognitive decline will enable the development of personalized and early interventions.

Pharmacological activation of constitutive androstane receptor induces female-specific modulation of hepatic metabolism.

Background & Aims: The constitutive androstane receptor (CAR) is a nuclear receptor that binds diverse xenobiotics and whose activation leads to the modulation of the expression of target genes involved in xenobiotic detoxification and energy metabolism. Although CAR hepatic activity is considered to be higher in women than in men, its sex-dependent response to an acute pharmacological activation has seldom been investigated. Methods: The hepatic transcriptome, plasma markers, and hepatic metabolome, were analysed in Car+/+ and Car-/- male and female mice treated either with the CAR-specific agonist 1,4-bis[2-(3,5-dichloropyridyloxy)]benzene (TCPOBOP) or with vehicle. Results: Although 90% of TCPOBOP-sensitive genes were modulated in a sex-independent manner, the remaining 10% showed almost exclusive female liver specificity. These female-specific CAR-sensitive genes were mainly involved in xenobiotic metabolism, inflammation, and extracellular matrix organisation. CAR activation also induced higher hepatic oxidative stress and hepatocyte cytolysis in females than in males. Hepatic expression of flavin monooxygenase 3 (Fmo3) was almost abolished and was associated with a decrease in hepatic trimethylamine-N-oxide (TMAO) concentration in TCPOBOP-treated females. In line with a potential role in the control of TMAO homeostasis, CAR activation decreased platelet hyper-responsiveness in female mice supplemented with dietary choline. Conclusions: More than 10% of CAR-sensitive genes are sex-specific and influence hepatic and systemic responses such as platelet aggregation. CAR activation may be an important mechanism of sexually-dimorphic drug-induced liver injury. Impact and implications: CAR is activated by many drugs and pollutants. Its pharmacological activation had a stronger impact on hepatic gene expression and metabolism in females than in males, and had a specific impact on liver toxicity and trimethylamine metabolism. Sexual dimorphism should be considered when testing and/or prescribing xenobiotics known to activate CAR.

Obesity promotes fumonisin B1 hepatotoxicity.

Obesity, which is a worldwide public health issue, is associated with chronic inflammation that contribute to long-term complications, including insulin resistance, type 2 diabetes and non-alcoholic fatty liver disease. We hypothesized that obesity may also influence the sensitivity to food contaminants, such as fumonisin B1 (FB1), a mycotoxin produced mainly by the Fusarium verticillioides. FB1, a common contaminant of corn, is the most abundant and best characterized member of the fumonisins family. We investigated whether diet-induced obesity could modulate the sensitivity to oral FB1 exposure, with emphasis on gut health and hepatotoxicity. Thus, metabolic effects of FB1 were assessed in obese and non-obese male C57BL/6J mice. Mice received a high-fat diet (HFD) or normal chow diet (CHOW) for 15 weeks. Then, during the last three weeks, mice were exposed to these diets in combination or not with FB1 (10 mg/kg body weight/day) through drinking water. As expected, HFD feeding induced significant body weight gain, increased fasting glycemia, and hepatic steatosis. Combined exposure to HFD and FB1 resulted in body weight loss and a decrease in fasting blood glucose level. This co-exposition also induces gut dysbiosis, an increase in plasma FB1 level, a decrease in liver weight and hepatic steatosis. Moreover, plasma transaminase levels were significantly increased and associated with liver inflammation in HFD/FB1-treated mice. Liver gene expression analysis revealed that the combined exposure to HFD and FB1 was associated with reduced expression of genes involved in lipogenesis and increased expression of immune response and cell cycle-associated genes. These results suggest that, in the context of obesity, FB1 exposure promotes gut dysbiosis and severe liver inflammation. To our knowledge, this study provides the first example of obesity-induced hepatitis in response to a food contaminant.

Cytotoxicity and genotoxicity of versicolorins and 5-methoxysterigmatocystin in A549 cells.

Aspergillus versicolor and A. flavus are primary colonizers in damp dwellings, and they produce sterigmatocystin (ST) and aflatoxin B1 (AFB(1)), respectively. These hepatotoxic and carcinogenic mycotoxins and their precursors and derivates possess a furofuran ring, which has proven responsible for their toxicity. The aim of this study was to investigate the cytotoxicity and genotoxicity of versicolorin A (VER A) and versicolorin B (VER B), as the furofuran precursors of aflatoxins and ST, and of 5-methoxysterigmatocystin (5-MET-ST), a methoxy derivative of ST, in human adenocarcinoma lung cells A549. The IC(50) values of the tested compounds were obtained by the cell proliferation MTT test as follows: 109 ± 3.5 µM (VER A), 172 ± 4 µM (VER B) and 181 ± 2.6 µM (5-MET-ST). The comet assay and micronucleus test were used to assess their genotoxic potential after 24 h of treatment with concentrations corresponding to ½ and » IC(50) in comparison with AFB(1) and ST, applied in concentrations corresponding to ½ IC(50), as previously determined in A549 cells. DNA damage parameters assessed by the comet assay were tail length, tail intensity and tail moment, while the level of DNA damage in the micronucleus test was evaluated by the number of formed micronuclei (MN), nuclear buds (NB) and nucleoplasmic bridges (NPB) in 1,000 binucleated cells. Considering the three comet parameters, all applied toxins exerted significant DNA damage compared to the control, while ST and VER B produced the highest DNA damage. All toxins provoked a statistically significant increase in MN, and a slightly decreased formation of NB and NPB. AFB(1), ST and 20 µM VER A showed a statistically significant increase in all three micronucleus parameters compared to the control, and the highest increase in the number of MN occurred in cells treated with 50 µM VER A. The differences between results obtained by the micronucleus test and comet assay could be explained by the fact that the micronucleus detects irreversible DNA damage, which is usually correlated with the previously determined cytotoxic potential of the AFB(1) precursors.

Slightly different metabolomic profiles are associated with high or low weight duck foie gras.

Understanding the evolution of fatty liver metabolism of ducks is a recurrent issue for researchers and industry. Indeed, the increase in weight during the overfeeding period leads to an important change in the liver metabolism. However, liver weight is highly variable at the end of overfeeding within a batch of animals reared, force-fed and slaughtered in the same way. For this study, we performed a proton nuclear magnetic resonance (1H-NMR) analysis on two classes of fatty liver samples, called low-weight liver (weights between 550 and 599 g) and high-weight liver (weights above 700 g). The aim of this study was to identify the differences in metabolism between two classes of liver weight (low and high). Firstly, the results suggested that increased liver weight is associated with higher glucose uptake leading to greater lipid synthesis. Secondly, this increase is probably also due to a decline in the level of export of triglycerides from the liver by maintaining them at high hepatic concentration levels, but also of hepatic cholesterol. Finally, the increase in liver weight could lead to a significant decrease in the efficiency of aerobic energy metabolism associated with a significant increase in the level of oxidative stress. However, all these hypotheses will have to be confirmed in the future, by studies on plasma levels and specific assays to validate these results.

NMR-based metabolic profiling and discrimination of wild tropical tunas by species, size category, geographic origin, and on-board storage condition.

Tunas are among the most traded and valued fish species, and good traceability of tuna products in the world market is needed to protect both consumers and tuna stocks. To that purpose, high-resolution proton nuclear magnetic resonance (1H NMR) spectroscopy combined with multivariate data analysis was used to investigate the molecular components of the aqueous extract of white and red muscles in three species of wild tropical tuna species, namely yellowfin tuna (Thunnus albacares), skipjack tuna (Katsuwonus pelamis) and bigeye tuna (T. obesus). Principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) applied to the processed 1H NMR spectra showed significant separation according to the species and size category (i.e., small tunas < 80 cm fork length vs large tunas > 80 cm fork length), the storage conditions on-board the purse-seine vessels (i.e., brine- vs deep-freezing), and the geographical origin (i.e., where the tuna was caught: Mozambique Channel vs western-central Indian Ocean). The major groups of metabolites responsible for differentiation in PLS-DA score plots were the dipeptides (anserine, carnosine) and organic acids (lactate, creatine/phosphocreatine) in the white muscle, and the free amino acids, essential nutrients (choline and its derivatives, phosphatidylethanolamine), dipeptides and organic acids in the red muscle. Our results showed that NMR-based metabolomics is a powerful tool to efficiently discriminate specific profiles among wild tuna species, raw muscle tissues, fish storage conditions and tuna geographical origin.