FragHub: A Mass Spectral Library Data Integration Workflow.

Open mass spectral libraries (OMSLs) are critical for metabolite annotation and machine learning, especially given the rising volume of untargeted metabolomic studies and the development of annotation pipelines. Despite their importance, the practical application of OMSLs is hampered by the lack of standardized file formats, metadata fields, and supporting ontology. Current libraries, often restricted to specific topics or matrices, such as natural products, lipids, or the human metabolome, may limit the discovery potential of untargeted studies. The goal of FragHub is to provide users with the capability to integrate various OMSLs into a single unified format, thereby enhancing the annotation accuracy and reliability. FragHub addresses these challenges by integrating multiple OMSLs into a single comprehensive database, supporting various data formats, and harmonizing metadata. It also proposes some generic filters for the mass spectrum using a graphical user interface. Additionally, a workflow to generate in-house libraries compatible with FragHub is proposed. FragHub dynamically segregates libraries based on ionization modes and chromatography techniques, thereby enhancing data utility in metabolomic research. The FragHub Python code is publicly available under a MIT license, at the following repository: https://github.com/eMetaboHUB/FragHub. Generated data can be accessed at 10.5281/zenodo.11057687.

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 .

Untargeted plasma metabolomic profiles associated with overall diet in women from the SU.VI.MAX cohort.

PURPOSE: Dietary intakes are reflected in plasma by the presence of hundreds of exogenous metabolites and variations in endogenous metabolites. The exploration of diet-related plasma metabolic profiles could help to better understand the impact of overall diet on health. Our aim was to identify metabolomic signatures reflecting overall diet in women from the French general population. METHODS: This cross-sectional study included 160 women in the SU.VI.MAX cohort with detailed dietary data (≥ 10 24-h dietary records) selected according to their level of adherence to the French dietary recommendations, represented by the validated score mPNNS-GS; 80 women from the 10th decile of the score were matched with 80 women from the 1st decile. Plasma metabolomic profiles were acquired using untargeted UPLC-QToF mass spectrometry analysis. The associations between metabolomic profiles and the mPNNG-GS, its components and Principal Component Analyses-derived dietary patterns were investigated using multivariable conditional logistic regression models and partial correlations. RESULTS: Adherence to the dietary recommendations was positively associated with 3-indolepropionic acid and pipecolic acid (also positively associated with fruit and vegetable intake and a healthy diet)-2 metabolites linked to microbiota and inversely associated with lysophosphatidylcholine (LysoPC(17:1)), acylcarnitine C9:1 (also inversely associated with a healthy diet), acylcarnitine C11:1 and 2-deoxy-D-glucose. Increased plasma levels of piperine and Dihydro4mercapto-3(2H) furanone were observed in women who consumed a Western diet and a healthy diet, respectively. Ethyl-ß-D-glucopyranoside was positively associated with alcohol intake. Plasma levels of LysoPC(17:1), cholic acid, phenylalanine-phenylalanine and phenylalanine and carnitine C9:1 decreased with the consumption of vegetable added fat, sweetened food, milk and dairy products and fruit and vegetable intakes, respectively. CONCLUSION: This study highlighted several metabolites from both host and microbial metabolism reflecting the long-term impact of the overall diet. TRIAL REGISTRATION: SU.VI.MAX, clinicaltrials.gov NCT00272428. Registered 3 January 2006, https://clinicaltrials.gov/show/NCT00272428.

A combined LC-MS and NMR approach to reveal metabolic changes in the hemolymph of honeybees infected by the gut parasite Nosema ceranae.

Nosema ceranae is an emerging and invasive gut pathogen in Apis mellifera and is considered as a factor contributing to the decline of honeybee populations. Here, we used a combined LC-MS and NMR approach to reveal the metabolomics changes in the hemolymph of honeybees infected by this obligate intracellular parasite. For metabolic profiling, hemolymph samples were collected from both uninfected and N. ceranae-infected bees at two time points, 2 days and 10 days after the experimental infection of emergent bees. Hemolymph samples were individually analyzed by LC-MS, whereas each NMR spectrum was obtained from a pool of three hemolymphs. Multivariate statistical PLS-DA models clearly showed that the age of bees was the parameter with the strongest effect on the metabolite profiles. Interestingly, a total of 15 biomarkers were accurately identified and were assigned as candidate biomarkers representative of infection alone or combined effect of age and infection. These biomarkers included carbohydrates (α/ß glucose, α/ß fructose and hexosamine), amino acids (histidine and proline), dipeptides (Glu-Thr, Cys-Cys and γ-Glu-Leu/Ile), metabolites involved in lipid metabolism (choline, glycerophosphocholine and O-phosphorylethanolamine) and a polyamine compound (spermidine). Our study demonstrated that this untargeted metabolomics-based approach may be useful for a better understanding of pathophysiological mechanisms of the honeybee infection by N. ceranae.

Evaluation of oxidized phospholipids analysis by LC-MS/MS.

Phospholipids (PLs) represent a class of metabolites of interest for evaluating the relationship between diet and the development of several metabolic diseases. Given that PLs are rich in unsaturated fatty acids, they can be oxidized. Because of their structure and reactivity, oxidized phospholipids (PLs-Ox) are increasingly recognized as markers of oxidative stress and of various diseases associated with inflammation. Therefore, there is a growing interest in studying PLs-Ox in lipidomics. Because of their limited commercial availability, very little information is currently available in databases to identify these molecules. The aim of this study is to acquire new knowledge about PLs-Ox in order to propose an analytical strategy for their analyses. For this purpose, a synthesis method of PLs-Ox, in auto-oxidation, has been developed and applied on phosphatidylcholine and phosphatidylethanolamine molecular species with various chain lengths, degree, and position of unsaturations. An analysis method based on mass (MS) and tandem mass spectrometry coupled to electrospray ionization was then developed and enabled the identification of a great diversity of long- and short-chain oxidation products. Formation kinetics of oxidation products was evaluated. Results showed that the formation of oxidized compounds was largely influenced by the degree of unsaturation on fatty acid chains. Oxidation time promotes the formation of some biologically important oxidation products. Coupling the MS method with liquid chromatography in flow injection analysis mode enabled the development of a full analytical strategy. Structural analysis of PLs-Ox allowed the enrichment of databases with important information to identify these molecules in biological matrices.

Systems Metabolomics for Prediction of Metabolic Syndrome.

The evolution of human health is a continuum of transitions, involving multifaceted processes at multiple levels, and there is an urgent need for integrative biomarkers that can characterize and predict progression toward disease development. The objective of this work was to perform a systems metabolomics approach to predict metabolic syndrome (MetS) development. A case-control design was used within the French occupational GAZEL cohort (n = 112 males: discovery study; n = 94: replication/validation study). Our integrative strategy was to combine untargeted metabolomics with clinical, sociodemographic, and food habit parameters to describe early phenotypes and build multidimensional predictive models. Different models were built from the discriminant variables, and prediction performances were optimized either when reducing the number of metabolites used or when keeping the associated signature. We illustrated that a selected reduced metabolic profile was able to reveal subtle phenotypic differences 5 years before MetS occurrence. Moreover, resulting metabolomic markers, when combined with clinical characteristics, allowed improving the disease development prediction. The validation study showed that this predictive performance was specific to the MetS component. This work also demonstrates the interest of such an approach to discover subphenotypes that will need further characterization to be able to shift to molecular reclassification and targeting of MetS.

Metabolomic study of the response to cold shock in a strain of Pseudomonas syringae isolated from cloud water.

INTRODUCTION: Active microorganisms have been recently discovered in clouds, thus demonstrating the capacity of microorganisms to exist in harsh environments, including exposure to UV and oxidants, osmotic and cold shocks, etc. It is important to understand how microorganisms respond to and survive such stresses at the metabolic level. OBJECTIVES: The objective of this work is to assess metabolome modulation in a strain of Pseudomonas syringae isolated from cloud water and facing temperature downshift from 17 to 5 °C by identifying key molecules and pathways of the response/adaptation to cold shock. METHODS: Bacterial extracts from suspensions of cells grown at 17 °C and further incubated in microcosms at 5 and 17 °C to mimic cloud conditions were analysed by combining LC-MS and NMR; the results were evaluated in comparison to similar suspensions kept at constant temperature. The differences in the metabolome profiles were deciphered using multivariate statistics (PLS-DA). RESULTS: Key cold shock biomarkers were observed, including cryoprotectants (trehalose, glucose, glycerol, carnitine, glutamate), antioxidants (glutathione and carnitine) and their precursors, alkaloids (bellendine and slaframine) and metabolites involved in energy metabolism (ATP, carbohydrates). Furthermore, new short peptides (nine dipeptides and a tetrapeptide) were found that have no known function. CONCLUSIONS: This study shows that in response to cold temperatures, Pseudomonas syringae PDD-32b-74 demonstrates numerous metabolism modifications to counteract the impacts of low temperatures.

Time Course of Molecular and Metabolic Events in the Development of Insulin Resistance in Fructose-Fed Rats.

We aimed to determine the time-course of metabolic changes related to the early onset of insulin resistance (IR), trying to evidence breaking points preceding the appearance of the clinical IR phenotype. The model chosen was the fructose (FRU)-fed rat compared to controls fed with starch. We focused on the hepatic metabolism after 0, 5, 12, 30, or 45 days of FRU intake. The hepatic molecular metabolic changes followed indeed a multistep trajectory rather than a continuous progression. After 5 d of FRU feeding, we observed deep modifications in the hepatic metabolism, driven by the induction of lipogenic genes and important glycogen depletion. Thereafter, a steady-state period between days 12 and 30 was observed, characterized by a switch from carbohydrate to lipid utilization at the hepatic level and increased insulin levels aiming at alleviating lipid accumulation and hyperglycemia, respectively. The FRU-fed animals were only clinically IR at day 45 (altered homeostasis model assessment-estimated insulin resistance and muscle glucose transport). Furthermore, the urine metabolome revealed even earlier metabolic trajectory changes that precede the hepatic alterations. We identified several candidate metabolites linked to the tryptophan-nicotinamide metabolism and the installation of fasting hyperglycemia that suggest a role of this metabolic pathway on the development of the IR phenotype in the FRU-fed rats.

GPR40, a free fatty acid receptor, differentially impacts osteoblast behavior depending on differentiation stage and environment.

GPR40 is a free fatty acid receptor that has been recently shown to impact bone remodeling. This receptor protects skeleton by inhibiting bone resorbing osteoclast differentiation. Consistent with GPR40 expression on bone forming cells, we assumed that this receptor may also influence osteoblast activity. To further investigate this hypothesis, biological effects of GW9508, a synthetic agonist for GPR40, was first tested on osteoblast differentiation parameters. Assays were performed in two different cell models: the MC3T3-E1 osteoblastic cell line and primary bone marrow cultures extracted from wild-type and GPR40 knock-out mice. Both models showed a dual role of GPR40 on osteoblasts. Although receptor stimulation induced early stimulation of differentiation marker expression, it finally led to inhibition of mineralization process during late differentiation stages. To further elucidate this discrepancy, mice were ovariectomized to induce bone loss and received GPR40 agonist by gavage. Data revealed a weak influence of GPR40 agonist on osteoblast markers expression. Nevertheless, a significant increase in OPG expression was observed upon GW9508 treatment that contribute to explain the GPR40-related osteoporosis prevention. To conclude, our results confirm the relevance of this new opportunity in the management of bone loss.

Development of a LC-MS/MS method for the simultaneous screening of seven water-soluble vitamins in processing semi-coarse wheat flour products.

Wheat is the second largest crop cultivated around the world and constitutes a major part of the daily diet in Europe. It is therefore important to determine the content of micronutrient in wheat and wheat-based food products to define the contribution of wheat-based foods to the nutrition of the consumers. The aim of the present work was to develop a simple and rapid method based on liquid chromatography tandem mass spectrometry (LC-MS/MS) for the simultaneous determination of seven water-soluble vitamins in various wheat-based food materials. The vitamins present in the test material were separated in less than 15 min by using a reverse-phase C18 column, and analyzed by positive ion electrospray selected reaction monitoring MS/MS. The MS response for all the vitamins was linear over the working range (0.05 to 9 µg/mL) with correlation coefficients ranging between 0.991 and 1. Limits of quantification in the different food materials ranged from 0.09 to 3.5 µg/g. Intra-day and inter-day precision were found satisfactory. The developed method was applied for the simultaneous analysis of the water-soluble vitamin natural content of different semi-coarse wheat flours and in their corresponding baking products.

Mass spectrometry-based metabolomics for the discovery of biomarkers of fruit and vegetable intake: citrus fruit as a case study.

Elucidation of the relationships between genotype, diet, and health requires accurate dietary assessment. In intervention and epidemiological studies, dietary assessment usually relies on questionnaires, which are susceptible to recall bias. An alternative approach is to quantify biomarkers of intake in biofluids, but few such markers have been validated so far. Here we describe the use of metabolomics for the discovery of nutritional biomarkers, using citrus fruits as a case study. Three study designs were compared. Urinary metabolomes were profiled for volunteers that had (a) consumed an acute dose of orange or grapefruit juice, (b) consumed orange juice regularly for one month, and (c) reported high or low consumption of citrus products for a large cohort study. Some signals were found to reflect citrus consumption in all three studies. Proline betaine and flavanone glucuronides were identified as known biomarkers, but various other biomarkers were revealed. Further, many signals that increased after citrus intake in the acute study were not sensitive enough to discriminate high and low citrus consumers in the cohort study. We propose that urine profiling of cohort subjects stratified by consumption is an effective strategy for discovery of sensitive biomarkers of consumption for a wide range of foods.

Enterohaemorrhagic Escherichia coli gains a competitive advantage by using ethanolamine as a nitrogen source in the bovine intestinal content.

The bovine gastrointestinal tract is the main reservoir for enterohaemorrhagic Escherichia coli (EHEC) responsible for food-borne infections. Characterization of nutrients that promote the carriage of these pathogens by the ruminant would help to develop ecological strategies to reduce their survival in the bovine gastrointestinal tract. In this study, we show for the first time that free ethanolamine (EA) constitutes a nitrogen source for the O157:H7 EHEC strain EDL933 in the bovine intestinal content because of induction of the eut (ethanolamine utilization) gene cluster. In contrast, the eut gene cluster is absent in the genome of most species constituting the mammalian gut microbiota. Furthermore, the eutB gene (encoding a subunit of the enzyme that catalyses the release of ammonia from EA) is poorly expressed in non-pathogenic E. coli. Accordingly, EA is consumed by EHEC but is poorly metabolized by endogenous microbiota of the bovine small intestine, including commensal E. coli. Interestingly, the capacity to utilize EA as a nitrogen source confers a growth advantage to E. coli O157:H7 when the bacteria enter the stationary growth phase. These data demonstrate that EHEC strains take advantage of a nitrogen source that is not consumed by the resident microbiota, and suggest that EA represents an ecological niche favouring EHEC persistence in the bovine intestine.

Multiplatform metabolomics for an integrative exploration of metabolic syndrome in older men.

BACKGROUND: Metabolic syndrome (MetS), a cluster of factors associated with risks of developing cardiovascular diseases, is a public health concern because of its growing prevalence. Considering the combination of concomitant components, their development and severity, MetS phenotypes are largely heterogeneous, inducing disparity in diagnosis. METHODS: A case/control study was designed within the NuAge longitudinal cohort on aging. From a 3-year follow-up of 123 stable individuals, we present a deep phenotyping approach based on a multiplatform metabolomics and lipidomics untargeted strategy to better characterize metabolic perturbations in MetS and define a comprehensive MetS signature stable over time in older men. FINDINGS: We characterize significant changes associated with MetS, involving modulations of 476 metabolites and lipids, and representing 16% of the detected serum metabolome/lipidome. These results revealed a systemic alteration of metabolism, involving various metabolic pathways (urea cycle, amino-acid, sphingo- and glycerophospholipid, and sugar metabolisms…) not only intrinsically interrelated, but also reflecting environmental factors (nutrition, microbiota, physical activity…). INTERPRETATION: These findings allowed identifying a comprehensive MetS signature, reduced to 26 metabolites for future translation into clinical applications for better diagnosing MetS. FUNDING: The NuAge Study was supported by a research grant from the Canadian Institutes of Health Research (CIHR; MOP-62842). The actual NuAge Database and Biobank, containing data and biologic samples of 1,753 NuAge participants (from the initial 1,793 participants), are supported by the Fonds de recherche du Québec (FRQ; 2020-VICO-279753), the Quebec Network for Research on Aging, a thematic network funded by the Fonds de Recherche du Québec - Santé (FRQS) and by the Merck-Frost Chair funded by La Fondation de l'Université de Sherbrooke. All metabolomics and lipidomics analyses were funded and performed within the metaboHUB French infrastructure (ANR-INBS-0010). All authors had full access to the full data in the study and accept responsibility to submit for publication.

Diet-Related Metabolomic Signature of Long-Term Breast Cancer Risk Using Penalized Regression: An Exploratory Study in the SU.VI.MAX Cohort.

BACKGROUND: Diet has been recognized as a modifiable risk factor for breast cancer. Highlighting predictive diet-related biomarkers would be of great public health relevance to identify at-risk subjects. The aim of this exploratory study was to select diet-related metabolites discriminating women at higher risk of breast cancer using untargeted metabolomics. METHODS: Baseline plasma samples of 200 incident breast cancer cases and matched controls, from a nested case-control study within the Supplémentation en Vitamines et Minéraux Antioxydants (SU.VI.MAX) cohort, were analyzed by untargeted LC-MS. Diet-related metabolites were identified by partial correlation with dietary exposures, and best predictors of breast cancer risk were then selected by Elastic Net penalized regression. The selection stability was assessed using bootstrap resampling. RESULTS: 595 ions were selected as candidate diet-related metabolites. Fourteen of them were selected by Elastic Net regression as breast cancer risk discriminant ions. A lower level of piperine (a compound from pepper) and higher levels of acetyltributylcitrate (an alternative plasticizer to phthalates), pregnene-triol sulfate (a steroid sulfate), and 2-amino-4-cyano butanoic acid (a metabolite linked to microbiota metabolism) were observed in plasma from women who subsequently developed breast cancer. This metabolomic signature was related to several dietary exposures such as a "Western" dietary pattern and higher alcohol and coffee intakes. CONCLUSIONS: Our study suggested a diet-related plasma metabolic signature involving exogenous, steroid metabolites, and microbiota-related compounds associated with long-term breast cancer risk that should be confirmed in large-scale independent studies. IMPACT: These results could help to identify healthy women at higher risk of breast cancer and improve the understanding of nutrition and health relationship.

Human fasting plasma concentrations of vitamin E and carotenoids, and their association with genetic variants in apo C-III, cholesteryl ester transfer protein, hepatic lipase, intestinal fatty acid binding protein and microsomal triacylglycerol transfer protein.

Plasma concentrations of vitamin E and carotenoids are governed by several factors, including genetic factors. Single nucleotide polymorphisms (SNP) in some genes involved in lipid metabolism have recently been associated with fasting plasma concentrations of these fat-soluble micronutrients. To further investigate the role of genetic factors that modulate the plasma concentrations of these micronutrients, we assessed whether SNP in five candidate genes (apo C-III, CETP, hepatic lipase, I-FABP and MTP) were associated with the plasma concentrations of these micronutrients. Fasting plasma vitamin E and carotenoid concentrations were measured in 129 French Caucasian subjects (forty-eight males and eighty-one females). Candidate SNP were genotyped by PCR amplification followed by restriction fragment length polymorphisms. Plasma gamma-tocopherol, alpha-carotene and beta-carotene concentrations were significantly different (P < 0.05) in subjects who carried different SNP variants in hepatic lipase. Plasma alpha-tocopherol concentrations were significantly different in subjects who had different SNP variants in apo C-III and cholesteryl ester transfer protein (CETP). Plasma lycopene concentrations were significantly different (P < 0.05) in women who had different SNP variants in intestinal fatty acid binding protein (I-FABP). Finally, there was no effect of SNP variants in microsomal TAG transfer protein upon the plasma concentrations of these micronutrients. Most of the observed differences remained significant after the plasma micronutrients were adjusted for plasma TAG and cholesterol. These results suggest that apo C-III, CETP and hepatic lipase play a role in determining the plasma concentrations of tocopherols while hepatic lipase and I-FABP may modulate plasma concentrations of carotenoids.

Analytic Correlation Filtration: A New Tool to Reduce Analytical Complexity of Metabolomic Datasets.

Metabolomics generates massive and complex data. Redundant different analytical species and the high degree of correlation in datasets is a constraint for the use of data mining/statistical methods and interpretation. In this context, we developed a new tool to detect analytical correlation into datasets without confounding them with biological correlations. Based on several parameters, such as a similarity measure, retention time, and mass information from known isotopes, adducts, or fragments, the algorithm principle is used to group features coming from the same analyte, and to propose one single representative per group. To illustrate the functionalities and added-value of this tool, it was applied to published datasets and compared to one of the most commonly used free packages proposing a grouping method for metabolomics data: 'CAMERA'. This tool was developed to be included in Galaxy and will be available in Workflow4Metabolomics (http://workflow4metabolomics.org). Source code is freely available for download under CeCILL 2.1 license at https://services.pfem.clermont.inra.fr/gitlab/grandpa /tool-acf and implement in Perl.

Metabolic modulations of Pseudomonas graminis in response to H2O2 in cloud water.

In cloud water, microorganisms are exposed to very strong stresses especially related to the presence of reactive oxygen species including H2O2 and radicals, which are the driving force of cloud chemistry. In order to understand how the bacterium Pseudomonas graminis isolated from cloud water respond to this oxidative stress, it was incubated in microcosms containing a synthetic solution of cloud water in the presence or in the absence of H2O2. P. graminis metabolome was examined by LC-MS and NMR after 50 min and after 24 hours of incubation. After 50 min, the cells were metabolizing H2O2 while this compound was still present in the medium, and it was completely biodegraded after 24 hours. Cells exposed to H2O2 had a distinct metabolome as compared to unexposed cells, revealing modulations of certain metabolic pathways in response to oxidative stress. These data indicated that the regulations observed mainly involved carbohydrate, glutathione, energy, lipid, peptides and amino-acids metabolisms. When cells had detoxified H2O2 from the medium, their metabolome was not distinguishable anymore from unexposed cells, highlighting the capacity of resilience of this bacterium. This work illustrates the interactions existing between the cloud microbial metabolome and cloud chemistry.

Proposal for a chemically consistent way to annotate ions arising from the analysis of reference compounds under ESI conditions: A prerequisite to proper mass spectral database constitution in metabolomics.

Nowadays, high-resolution mass spectrometry is widely used for metabolomic studies. Thanks to its high sensitivity, it enables the detection of a large range of metabolites. In metabolomics, the continuous quest for a metabolite identification as complete and accurate as possible has led during the last decade to an ever increasing development of public MS databases (including LC-MS data) concomitantly with bioinformatic tool expansion. To facilitate the annotation process of MS profiles obtained from biological samples, but also to ease data sharing, exchange, and exploitation, the standardization and harmonization of the way to describe and annotate mass spectra seemed crucial to us. Indeed, under electrospray (ESI) conditions, a single metabolite does not produce a unique ion corresponding to its protonated or deprotonated form but could lead to a complex mixture of signals. These MS signals result from the existence of different natural isotopologues of the same compound and also to the potential formation of adduct ions, homomultimeric and heteromultimeric ions, fragment ions resulting from "prompt" in-source dissociations. As a joint reflection process within the French Infrastructure for Metabolomics and Fluxomics (MetaboHUB) and with the purpose of developing a robust and exchangeable annotated MS database made from pure reference compounds (chemical standards) analysis, it appeared to us that giving the metabolomics community some clues to standardize and unambiguously annotate each MS feature was a prerequisite to data entry and further efficient querying of the mass spectral database. The use of a harmonized notation is also mandatory for interlaboratory MS data exchange. Additionally, thorough description of the variety of MS signals arising from the analysis of a unique metabolite might provide greater confidence on its annotation.

Plasma Metabolomic Signatures Associated with Long-term Breast Cancer Risk in the SU.VI.MAX Prospective Cohort.

BACKGROUND: Breast cancer is a major cause of death in occidental women. The role of metabolism in breast cancer etiology remains unclear. Metabolomics may help to elucidate novel biological pathways and identify new biomarkers to predict breast cancer long before symptoms appear. The aim of this study was to investigate whether untargeted metabolomic signatures from blood draws of healthy women could contribute to better understand and predict the long-term risk of developing breast cancer. METHODS: A nested case-control study was conducted within the SU.VI.MAX prospective cohort (13 years of follow-up) to analyze baseline plasma samples of 211 incident breast cancer cases and 211 matched controls by LC/MS. Multivariable conditional logistic regression models were computed. RESULTS: A total of 3,565 ions were detected and 1,221 were retained for statistical analysis. A total of 73 ions were associated with breast cancer risk (P < 0.01; FDR ≤ 0.2). Notably, we observed that a lower plasma level of O-succinyl-homoserine (OR = 0.70, 95%CI = [0.55-0.89]) and higher plasma levels of valine/norvaline [1.45 (1.15-1.83)], glutamine/isoglutamine [1.33 (1.07-1.66)], 5-aminovaleric acid [1.46 (1.14-1.87)], phenylalanine [1.43 (1.14-1.78)], tryptophan [1.40 (1.10-1.79)], γ-glutamyl-threonine [1.39 (1.09-1.77)], ATBC [1.41 (1.10-1.79)], and pregnene-triol sulfate [1.38 (1.08-1.77)] were associated with an increased risk of developing breast cancer during follow-up.Conclusion: Several prediagnostic plasmatic metabolites were associated with long-term breast cancer risk and suggested a role of microbiota metabolism and environmental exposure. IMPACT: After confirmation in other independent cohort studies, these results could help to identify healthy women at higher risk of developing breast cancer in the subsequent decade and to propose a better understanding of the complex mechanisms involved in its etiology.

Wheat germ supplementation of a low vitamin E diet in rats affords effective antioxidant protection in tissues.

BACKGROUND: Oxidative stress is implicated in the etiology of many diseases, but most of clinical trials failed to demonstrate beneficial effects of antioxidant supplementation. METHODS: In the present experiment, we assessed the mean-term effect of wheat germ supplementation, as a dietary source of vitamin E, on antioxidant protection in rat. RESULTS: Feeding rats a 20% wheat germ diet significantly increased plasma and liver vitamin E levels, compared to the low vitamin E basal diet. Concurrently, wheat germ diet consumption strongly decreased the susceptibility of heart and liver lipids to oxidation, as well as the plasma. Wheat germ feeding did not change triglycerides (TG) nor total cholesterol concentrations in plasma or liver, resulting in higher vitamin E/TG ratio compared to controls. Similar results were found with a diet in which wheat germ oil provided the same amount of vitamin E. CONCLUSIONS: Wheat germ appears thus very effective to improve antioxidant defense status, especially in tissues, irrespective of modifications of lipids status.