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.

Urinary Metabolome Analysis Reveals Potential Microbiota Alteration and Electrophilic Burden Induced by High Red Meat Diet: Results from the French NutriNet-Santé Cohort and an In Vivo Intervention Study in Rats.

SCOPE: High red and processed meat consumption is associated with several adverse outcomes such as colorectal cancer and overall global mortality. However, the underlying mechanisms remain debated and need to be elucidated. METHODS AND RESULTS: Urinary untargeted Liquid Chromatography-Mass Spectrometry (LC-MS) metabolomics data from 240 subjects from the French cohort NutriNet-Santé are analyzed. Individuals are matched and divided into three groups according to their consumption of red and processed meat: high red and processed meat consumers, non-red and processed meat consumers, and at random group. Results are supported by a preclinical experiment where rats are fed either a high red meat or a control diet. Microbiota derived metabolites, in particular indoxyl sulfate and cinnamoylglycine, are found impacted by the high red meat diet in both studies, suggesting a modification of microbiota by the high red/processed meat diet. Rat microbiota sequencing analysis strengthens this observation. Although not evidenced in the human study, rat mercapturic acid profile concomitantly reveals an increased lipid peroxidation induced by high red meat diet. CONCLUSION: Novel microbiota metabolites are identified as red meat consumption potential biomarkers, suggesting a deleterious effect, which could partly explain the adverse effects associated with high red and processed meat consumption.

Identification of bacterial lipopeptides as key players in IBS.

OBJECTIVES: Clinical studies revealed that early-life adverse events contribute to the development of IBS in adulthood. The aim of our study was to investigate the relationship between prenatal stress (PS), gut microbiota and visceral hypersensitivity with a focus on bacterial lipopeptides containing γ-aminobutyric acid (GABA). DESIGN: We developed a model of PS in mice and evaluated, in adult offspring, visceral hypersensitivity to colorectal distension (CRD), colon inflammation, barrier function and gut microbiota taxonomy. We quantified the production of lipopeptides containing GABA by mass spectrometry in a specific strain of bacteria decreased in PS, in PS mouse colons, and in faeces of patients with IBS and healthy volunteers (HVs). Finally, we assessed their effect on PS-induced visceral hypersensitivity. RESULTS: Prenatally stressed mice of both sexes presented visceral hypersensitivity, no overt colon inflammation or barrier dysfunction but a gut microbiota dysbiosis. The dysbiosis was distinguished by a decreased abundance of Ligilactobacillus murinus, in both sexes, inversely correlated with visceral hypersensitivity to CRD in mice. An isolate from this bacterial species produced several lipopeptides containing GABA including C14AsnGABA. Interestingly, intracolonic treatment with C14AsnGABA decreased the visceral sensitivity of PS mice to CRD. The concentration of C16LeuGABA, a lipopeptide which inhibited sensory neurons activation, was decreased in faeces of patients with IBS compared with HVs. CONCLUSION: PS impacts the gut microbiota composition and metabolic function in adulthood. The reduced capacity of the gut microbiota to produce GABA lipopeptides could be one of the mechanisms linking PS and visceral hypersensitivity in adulthood.

Plasma Metabolome Analysis Suggests That L-Arginine Supplementation Affects Microbial Activity Resulting in a Decrease in Trimethylamine N-oxide-A Randomized Controlled Trial in Healthy Overweight Adults with Cardiometabolic Risk Factors.

Background: The effects of supplementation with L-arginine (L-arg), the precursor of nitric oxide (NO), on vascular and cardiometabolic health have largely been explored. Whether other mechanisms of the action of L-arg exist remains unknown, as arginine metabolism is complicated. Objective: We aimed to characterize the effect of low dose L-arg supplementation on overall human metabolism both in a fasting state and in response to an allostatic stress. Methods: In a randomized, double-blind, crossover study, 32 healthy overweight adults (mean age 45 y) with cardiometabolic risk (fasting plasma triglycerides >150 mg/dL; waist circumference >94 cm [male] or >80 cm [female]) were treated with 1.5 g sustained-release L-arg 3 times/d (4.5 g/d) or placebo for 4 wk. On the last day of treatment, volunteers consumed a high-fat meal challenge (900 kcal, 80% as fat, 13% as carbohydrate, and 7% as protein). Plasma was collected at fasting, 2, 4, and 6 h after the challenge, and the metabolome was analyzed by high-resolution liquid chromatography-mass spectrometry. Metabolic profiles were analyzed using linear mixed models-principal component analysis. Results: The challenge meal explained most of the changes in the metabolome. The overall effect of L-arg supplementation significantly explained 0.5% of the total variance, irrespective of the response to the challenge meal (P < 0.05). Among the metabolites that explain most of the L-arg effect, we found many amino acids, including branched-chain amino acids, that were decreased by L-arg supplementation. L-arg also decreased trimethylamine N-oxide (TMAO). Other changes suggest that L-arg increased methyl demand. Conclusions: Analysis of the effect of 4 wk of L-arg supplementation on the metabolome reveals important effects on methyl balance and gut microbiota activity, such as a decrease in TMAO. Further studies are needed to investigate those mechanisms and the implications of these changes for long-term health.This trial was registered at clinicaltrials.gov as NCT02354794.

Lactobacillus supports Clostridiales to restrict gut colonization by multidrug-resistant Enterobacteriaceae.

Infections by multidrug-resistant Enterobacteriaceae (MRE) are life-threatening to patients. The intestinal microbiome protects against MRE colonization, but antibiotics cause collateral damage to commensals and open the way to colonization and subsequent infection. Despite the significance of this problem, the specific commensals and mechanisms that restrict MRE colonization remain largely unknown. Here, by performing a multi-omic prospective study of hospitalized patients combined with mice experiments, we find that Lactobacillus is key, though not sufficient, to restrict MRE gut colonization. Lactobacillus rhamnosus and murinus increase the levels of Clostridiales bacteria, which induces a hostile environment for MRE growth through increased butyrate levels and reduced nutrient sources. This mechanism of colonization resistance, an interaction between Lactobacillus spp. and Clostridiales involving cooperation between microbiota members, is conserved in mice and patients. These results stress the importance of exploiting microbiome interactions for developing effective probiotics that prevent infections in hospitalized patients.

Gestational exposure to bisphenol A induces region-specific changes in brain metabolomic fingerprints in sheep.

Fetal brain development depends on maternofetal thyroid function. In rodents and sheep, perinatal BPA exposure is associated with maternal and/or fetal thyroid disruption and alterations in central nervous system development as demonstrated by metabolic modulations in the encephala of mice. We hypothesized that a gestational exposure to a low dose of BPA affects maternofetal thyroid function and fetal brain development in a region-specific manner. Pregnant ewes, a relevant model for human thyroid and brain development, were exposed to BPA (5 µg/kg bw/d, sc). The thyroid status of ewes during gestation and term fetuses at delivery was monitored. Fetal brain development was assessed by metabolic fingerprints at birth in 10 areas followed by metabolic network-based analysis. BPA treatment was associated with a significant time-dependent decrease in maternal TT4 serum concentrations. For 8 fetal brain regions, statistical models allowed discriminating BPA-treated from control lambs. Metabolic network computational analysis revealed that prenatal exposure to BPA modulated several metabolic pathways, in particular excitatory and inhibitory amino-acid, cholinergic, energy and lipid homeostasis pathways. These pathways might contribute to BPA-related neurobehavioral and cognitive disorders. Discrimination was particularly clear for the dorsal hippocampus, the cerebellar vermis, the dorsal hypothalamus, the caudate nucleus and the lateral part of the frontal cortex. Compared with previous results in rodents, the use of a larger animal model allowed to examine specific brain areas, and generate evidence of the distinct region-specific effects of fetal BPA exposure on the brain metabolome. These modifications occur concomitantly to subtle maternal thyroid function alteration. The functional link between such moderate thyroid changes and fetal brain metabolomic fingerprints remains to be determined as well as the potential implication of other modes of action triggered by BPA such as estrogenic ones. Our results pave the ways for new scientific strategies aiming at linking environmental endocrine disruption and altered neurodevelopment.

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 .

Investigating the Postprandial Metabolome after Challenge Tests to Assess Metabolic Flexibility and Dysregulations Associated with Cardiometabolic Diseases.

This review focuses on the added value provided by a research strategy applying metabolomics analyses to assess phenotypic flexibility in response to different nutritional challenge tests in the framework of metabolic clinical studies. We discuss findings related to the Oral Glucose Tolerance Test (OGTT) and to mixed meals with varying fat contents and food matrix complexities. Overall, the use of challenge tests combined with metabolomics revealed subtle metabolic dysregulations exacerbated during the postprandial period when comparing healthy and at cardiometabolic risk subjects. In healthy subjects, consistent postprandial metabolic shifts driven by insulin action were reported (e.g., a switch from lipid to glucose oxidation for energy fueling) with similarities between OGTT and mixed meals, especially during the first hours following meal ingestion while differences appeared in a wider timeframe. In populations with expected reduced phenotypic flexibility, often associated with increased cardiometabolic risk, a blunted response on most key postprandial pathways was reported. We also discuss the most suitable statistical tools to analyze the dynamic alterations of the postprandial metabolome while accounting for complexity in study designs and data structure. Overall, the in-depth characterization of the postprandial metabolism and associated phenotypic flexibility appears highly promising for a better understanding of the onset of cardiometabolic diseases.

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.

Transgenerational metabolomic fingerprints in mice ancestrally exposed to the obesogen TBT.

BACKGROUND: Endocrine disrupting chemicals (EDCs) contribute to the etiology of metabolic disorders such as obesity, insulin resistance and hepatic dysfunction. Concern is growing about the consequences of perinatal EDC exposure on disease predisposition later in life. Metabolomics are promising approaches for studying long-term consequences of early life EDC exposure. These approaches allow for the identification and characterization of biomarkers of direct or ancestral exposures that could be diagnostic for individual susceptibility to disease and help to understand mechanisms through which EDCs act. OBJECTIVES: We sought to identify metabolomic fingerprints in mice ancestrally exposed to the model obesogen tributyltin (TBT), to assess whether metabolomics could discriminate potential trans-generational susceptibility to obesity and recognize metabolic pathways modulated by ancestral TBT exposure. METHODS: We used non-targeted 1H NMR metabolomic analyses of plasma and liver samples collected from male and female mice ancestrally exposed to TBT in two independent transgenerational experiments in which F3 and F4 males became obese when challenged with increased dietary fat. RESULTS: Metabolomics confirmed transgenerational obesogenic effects of environmentally relevant doses of TBT in F3 and F4 males, in two independent studies. Although females never became obese, their specific metabolomic fingerprint evidenced distinct transgenerational effects of TBT in female mice consistent with impaired capacity for liver biotransformation. DISCUSSION: This study is the first application of metabolomics to unveil the transgenerational effects of EDC exposure. Very early, significant changes in the plasma metabolome were observed in animals ancestrally exposed to TBT. These changes preceded the onset of obesogenic effects elicited by increased dietary fat in the TBT groups, and which ultimately resulted in significant changes in the liver metabolome. Development of metabolomic fingerprints could facilitate the identification of individuals carrying the signature of ancestral obesogen exposure that might increase their susceptibility to other risk factor such as increased dietary fat.

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.

Statistical Integration of 'Omics Data Increases Biological Knowledge Extracted from Metabolomics Data: Application to Intestinal Exposure to the Mycotoxin Deoxynivalenol.

The effects of low doses of toxicants are often subtle and information extracted from metabolomic data alone may not always be sufficient. As end products of enzymatic reactions, metabolites represent the final phenotypic expression of an organism and can also reflect gene expression changes caused by this exposure. Therefore, the integration of metabolomic and transcriptomic data could improve the extracted biological knowledge on these toxicants induced disruptions. In the present study, we applied statistical integration tools to metabolomic and transcriptomic data obtained from jejunal explants of pigs exposed to the food contaminant, deoxynivalenol (DON). Canonical correlation analysis (CCA) and self-organizing map (SOM) were compared for the identification of correlated transcriptomic and metabolomic features, and O2-PLS was used to model the relationship between exposure and selected features. The integration of both 'omics data increased the number of discriminant metabolites discovered (39) by about 10 times compared to the analysis of the metabolomic dataset alone (3). Besides the disturbance of energy metabolism previously reported, assessing correlations between both functional levels revealed several other types of damage linked to the intestinal exposure to DON, including the alteration of protein synthesis, oxidative stress, and inflammasome activation. This confirms the added value of integration to enrich the biological knowledge extracted from metabolomics.

Untargeted Lipidomic Profiling of Dry Blood Spots Using SFC-HRMS.

Lipids are essential cellular constituents that have many critical roles in physiological functions. They are notably involved in energy storage and cell signaling as second messengers, and they are major constituents of cell membranes, including lipid rafts. As a consequence, they are implicated in a large number of heterogeneous diseases, such as cancer, diabetes, neurological disorders, and inherited metabolic diseases. Due to the high structural diversity and complexity of lipid species, the presence of isomeric and isobaric lipid species, and their occurrence at a large concentration scale, a complete lipidomic profiling of biological matrices remains challenging, especially in clinical contexts. Using supercritical fluid chromatography coupled with high-resolution mass spectrometry, we have developed and validated an untargeted lipidomic approach to the profiling of plasma and blood. Moreover, we have tested the technique using the Dry Blood Spot (DBS) method and found that it allows for the easy collection of blood for analysis. To develop the method, we performed the optimization of the separation and detection of lipid species on pure standards, reference human plasma (SRM1950), whole blood, and DBS. These analyses allowed an in-house lipid data bank to be built. Using the MS-Dial software, we developed an automatic process for the relative quantification of around 500 lipids species belonging to the 6 main classes of lipids (including phospholipids, sphingolipids, free fatty acids, sterols, and fatty acyl-carnitines). Then, we compared the method using the published data for SRM 1950 and a mouse blood sample, along with another sample of the same blood collected using the DBS method. In this study, we provided a method for blood lipidomic profiling that can be used for the easy sampling of dry blood spots.

Does the Phytochemical Diversity of Wild Plants Like the Erythrophleum genus Correlate with Geographical Origin?

Secondary metabolites are essential for plant survival and reproduction. Wild undomesticated and tropical plants are expected to harbor highly diverse metabolomes. We investigated the metabolomic diversity of two morphologically similar trees of tropical Africa, Erythrophleum suaveolens and E. ivorense, known for particular secondary metabolites named the cassaine-type diterpenoids. To assess how the metabolome varies between and within species, we sampled leaves from individuals of different geographic origins but grown from seeds in a common garden in Cameroon. Metabolites were analyzed using reversed phase LC-HRMS(/MS). Data were interpreted by untargeted metabolomics and molecular networks based on MS/MS data. Multivariate analyses enabled us to cluster samples based on species but also on geographic origins. We identified the structures of 28 cassaine-type diterpenoids among which 19 were new, 10 were largely specific to E. ivorense and five to E. suaveolens. Our results showed that the metabolome allows an unequivocal distinction of morphologically-close species, suggesting the potential of metabolite fingerprinting for these species. Plant geographic origin had a significant influence on relative concentrations of metabolites with variations up to eight (suaveolens) and 30 times (ivorense) between origins of the same species. This shows that the metabolome is strongly influenced by the geographical origin of plants (i.e., genetic factors).

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

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

Transgenerational metabolic disorders and reproduction defects induced by benzo[a]pyrene in Xenopus tropicalis.

Metabolic disorders induced by endocrine disruptors (ED) may contribute to amphibian population declines but no transgenerational studies have evaluated this hypothesis. Here we show that Xenopus tropicalis, exposed from the tadpole stage, to the ED benzo[a]pyrene (BaP, 50 ng.L-1) produced F2 progeny with delayed metamorphosis and sexual maturity. At the adult stage, F2-BaP females displayed fatty liver with inflammation, tissue disorganization and metabolomic and transcriptomic signatures typical of nonalcoholic steato-hepatitis (NASH). This phenotype, similar to that observed in F0 and F1 females, was accompanied by a pancreatic insulin secretory defect. Metabolic disrupted F2-BaP females laid eggs with metabolite contents significantly different from the control and these eggs did not produce viable progeny. This study demonstrated that an ED can induce transgenerational disruption of metabolism and population collapse in amphibians under laboratory conditions. These results show that ED benzo[a]pyrene can impact metabolism over multiple generations and support epidemiological studies implicating environmental EDs in metabolic diseases in humans.

Postprandial NMR-Based Metabolic Exchanges Reflect Impaired Phenotypic Flexibility across Splanchnic Organs in the Obese Yucatan Mini-Pig.

The postprandial period represents one of the most challenging phenomena in whole-body metabolism, and it can be used as a unique window to evaluate the phenotypic flexibility of an individual in response to a given meal, which can be done by measuring the resilience of the metabolome. However, this exploration of the metabolism has never been applied to the arteriovenous (AV) exploration of organs metabolism. Here, we applied an AV metabolomics strategy to evaluate the postprandial flexibility across the liver and the intestine of mini-pigs subjected to a high fat-high sucrose (HFHS) diet for 2 months. We identified for the first time a postprandial signature associated to the insulin resistance and obesity outcomes, and we showed that the splanchnic postprandial metabolome was considerably affected by the meal and the obesity condition. Most of the changes induced by obesity were observed in the exchanges across the liver, where the metabolism was reorganized to maintain whole body glucose homeostasis by routing glucose formed de novo from a large variety of substrates into glycogen. Furthermore, metabolites related to lipid handling and energy metabolism showed a blunted postprandial response in the obese animals across organs. Finally, some of our results reflect a loss of flexibility in response to the HFHS meal challenge in unsuspected metabolic pathways that must be further explored as potential new events involved in early obesity and the onset of insulin resistance.

The food contaminant, deoxynivalenol, modulates the Thelper/Treg balance and increases inflammatory bowel diseases.

The incidence of inflammatory bowel diseases (IBD) is increasing in both Western and developing countries. IBD are multifactorial disorders involving complex interactions between genetic, immune, and environmental factors such as exposure to food contaminants. Deoxynivalenol (DON) is the most prevalent mycotoxin that contaminates staple food and induces intestinal breakdown and inflammatory response. To delineate the role of DON oral exposure in IBD, we used a Dextran sulfate sodium (DSS) colitis model in rats fed with a DON-contaminated diet or a control diet for 4 weeks. Colitis was induced in the 4th week by increasing concentrations of DSS in the drinking water (0, 2, 3 or 5%). DON exacerbated body weight loss and accelerated the appearance of symptoms in animals treated with DSS. DON increased morphological damage, pro-inflammatory markers (myeloperoxidase, CXCL-1 and IL-1ß) and immune cell responses. In lamina propria of the rat with colitis, DON increased adaptive and innate immune responses after anti-CD3/28 or LPS stimulation, respectively. In the spleen, DON increased IFNγ secretion and reduced Treg populations. Interestingly, De-epoxy-DON (DOM-1) a detoxified form of DON did not have any consequences on colitis. These results suggest that DON is a risk factor in the onset of IBD.

Hepatocyte-specific deletion of Pparα promotes NAFLD in the context of obesity.

Peroxisome proliferator activated receptor α (PPARα) acts as a fatty acid sensor to orchestrate the transcription of genes coding for rate-limiting enzymes required for lipid oxidation in hepatocytes. Mice only lacking Pparα in hepatocytes spontaneously develop steatosis without obesity in aging. Steatosis can develop into non alcoholic steatohepatitis (NASH), which may progress to irreversible damage, such as fibrosis and hepatocarcinoma. While NASH appears as a major public health concern worldwide, it remains an unmet medical need. In the current study, we investigated the role of hepatocyte PPARα in a preclinical model of steatosis. For this, we used High Fat Diet (HFD) feeding as a model of obesity in C57BL/6 J male Wild-Type mice (WT), in whole-body Pparα- deficient mice (Pparα-/-) and in mice lacking Pparα only in hepatocytes (Pparαhep-/-). We provide evidence that Pparα deletion in hepatocytes promotes NAFLD and liver inflammation in mice fed a HFD. This enhanced NAFLD susceptibility occurs without development of glucose intolerance. Moreover, our data reveal that non-hepatocytic PPARα activity predominantly contributes to the metabolic response to HFD. Taken together, our data support hepatocyte PPARα as being essential to the prevention of NAFLD and that extra-hepatocyte PPARα activity contributes to whole-body lipid homeostasis.

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.