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56 results on '"Plateforme d'Exploration du Métabolisme PFEM"'

1. Specific Proteomic Identification of Collagen-Binding Proteins in Escherichia coli O157:H7: Characterisation of OmpA as a Potent Vaccine Antigen

Author

Monteiro, Ricardo, Chafsey, Ingrid, Caccia, Nelly, Ageorges, Valentin, Leroy, Sabine, Viala, Didier, Hébraud, Michel, Livrelli, Valérie, Pizza, Mariagrazia, Pezzicoli, Alfredo, Desvaux, Mickaël, Microbiologie Environnement Digestif Santé (MEDIS), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Clermont Auvergne (UCA), GlaxoSmithKline [Siena, Italy] (GSK), Universidade do Porto = University of Porto, Plateforme Exploration du Métabolisme (PFEM), MetaboHUB-Clermont, MetaboHUB-MetaboHUB-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Clermont Auvergne (UCA), Microbes, Intestin, Inflammation et Susceptibilité de l'Hôte (M2iSH), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre de Recherche en Nutrition Humaine d'Auvergne (CRNH d'Auvergne)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Clermont Auvergne (UCA), Imperial College London, ANR-17-CE21-0002,PathoFood,Décrypter l'hétérogénéité cellulaire et la distribution spatiale de pathogènes dans les matrices alimentaires en interaction avec les communautés microbiennes(2017), and European Project: 607611,EC:FP7:PEOPLE,FP7-PEOPLE-2013-ITN,DISCO(2014)

Subjects
collagen, host cell-bacteria interaction, [SDV]Life Sciences [q-bio], Escherichia coli, cell aggregation, intestinal epithelial cell, cell adhesion, cell surface protein, extracellular matrix (ECM), conserved antigens, diarrhoeagenic and intestinal bacterial pathogen
Abstract

International audience; Escherichia coli is a versatile commensal species of the animal gut that can also be a pathogen able to cause intestinal and extraintestinal infections. The plasticity of its genome has led to the evolution of pathogenic strains, which represent a threat to global health. Additionally, E. coli strains are major drivers of antibiotic resistance, highlighting the urgent need for new treatment and prevention measures. The antigenic and structural heterogeneity of enterohaemorrhagic E. coli colonisation factors has limited their use for the development of effective and cross-protective vaccines. However, the emergence of new strains that express virulence factors deriving from different E. coli diarrhoeagenic pathotypes suggests that a vaccine targeting conserved proteins could be a more effective approach. In this study, we conducted proteomics analysis and functional protein characterisation to identify a group of proteins potentially involved in the adhesion of E. coli O157:H7 to the extracellular matrix and intestinal epithelial cells. Among them, OmpA has been identified as a highly conserved and immunogenic antigen, playing a significant role in the adhesion phenotype of E. coli O157:H7 and in bacterial aggregation. Furthermore, antibodies raised against recombinant OmpA effectively reduced the adhesion of E. coli O157:H7 to intestinal epithelial cells. The present work highlights the role of OmpA as a potent antigen for the development of a vaccine against intestinal pathogenic E. coli.

Published
2023

2. Anti-TNF Agents Restrict Adherent-invasive Escherichia coli Replication Within Macrophages Through Modulation of Chitinase 3-like 1 in Patients with Crohn’s Disease

Author

Clara Douadi, Emilie Vazeille, Christophe Chambon, Michel Hébraud, Margot Fargeas, Marie Dodel, Dilek Coban, Bruno Pereira, Aurélien Birer, Pierre Sauvanet, Anthony Buisson, Nicolas Barnich, Microbes, Intestin, Inflammation et Susceptibilité de l'Hôte (M2iSH), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre de Recherche en Nutrition Humaine d'Auvergne (CRNH d'Auvergne)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Clermont Auvergne (UCA), Qualité des Produits Animaux (QuaPA), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Plateforme Exploration du Métabolisme (PFEM), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-MetaboHUB-Clermont, MetaboHUB-MetaboHUB, Microbiologie Environnement Digestif Santé (MEDIS), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Clermont Auvergne (UCA), and Département gastroentérologie

Subjects
Proteomics, Macrophages, [SDV]Life Sciences [q-bio], Gastroenterology, Membrane Proteins, anti-TNF, General Medicine, Bacterial Adhesion, Crohn's disease, Crohn Disease, chitinase 3-like 1, Escherichia coli, Humans, Tumor Necrosis Factor Inhibitors, Chitinase-3-Like Protein 1, Intestinal Mucosa, Escherichia coli Infections, AIEC
Abstract

Background and Aims The mechanism of action of anti-tumour necrosis factor [anti-TNF] agents could implicate macrophage modulation in Crohn’s disease [CD]. As CD macrophages are defective in controlling CD-associated adherent-invasive Escherichia coli [AIEC], anti-TNF agents could limit AIEC replication within macrophages. We assessed the effect of anti-TNF agents on AIEC survival within monocyte-derived macrophages [MDMs] from CD patients and attempted to identify the proteins involved. Methods Peripheral blood MDMs were obtained from 44 CD patients [22 with and 22 without anti-TNF agents]. MDMs were infected with reference strain AIEC-LF82. Proteomic analysis was performed before and 6 h after AIEC-LF82 infection. Results AIEC-LF82 survival was lower in MDMs from CD patients receiving anti-TNF agents compared to those who did not [−73%, p = 0.006]. After AIEC-LF82 infection, the levels of CD82 [p = 0.007], ILF3 [Interleukin enhancer-binding factor 3; p = 0.001], FLOT-1 [Flotillin-1; p = 0.007] and CHI3L1 [Chitinase 3-like 1; p = 0.035] proteins were different within CD-MDMs depending on anti-TNF exposure. FLOT-1 [ϱ = −0.44; p = 0.038] and CHI3L1 [ϱ = 0.57, p = 0.006] levels were inversely and positively correlated with AIEC survival within MDMs from CD patients with or without anti-TNF, respectively. We observed a dose-dependent decrease of AIEC-LF82 survival after adjunction of anti-TNF within MDMs, inducing an increase of FLOT-1 and decrease of CHI3L1 mRNA levels. Neutralization of intra-macrophagic CHI3L1 protein using anti-CHI3L1 antibodies reduced AIEC survival within macrophages 6 h after infection [p < 0.05]. Conclusion Anti-TNF agents are able to restrict replication of pathobionts, such as AIEC, within macrophages by modulating FLOT-1 and CHI3L1 expression in CD patients.

Published
2022

3. Effect of subtherapeutic and therapeutic sulfamethazine concentrations on transcribed genes and translated proteins involved in Microbacterium sp. C448 resistance and degradation

Author

Paris, Laurianne, Devers-Lamrani, Marion, Joly, Muriel, Viala, Didier, de Antonio, Marie, Pereira, Bruno, Rouard, Nadine, Besse-Hoggan, Pascale, Hébraud, Michel, Topp, Edward, Martin-Laurent, Fabrice, Batisson, Isabelle, Laboratoire Microorganismes : Génome et Environnement (LMGE), Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA), Institut de Chimie de Clermont-Ferrand (ICCF), Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), Agroécologie [Dijon], Université de Bourgogne (UB)-Université Bourgogne Franche-Comté [COMUE] (UBFC)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Dijon, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Plateforme Exploration du Métabolisme (PFEM), MetaboHUB-Clermont, MetaboHUB-MetaboHUB-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Clermont Auvergne (UCA), Biostatistics unit (DRCI), CHU Clermont-Ferrand, Unité de Biostatistiques [CHU Clermont-Ferrand], Direction de la recherche clinique et de l’innovation [CHU Clermont-Ferrand] (DRCI), CHU Clermont-Ferrand-CHU Clermont-Ferrand, Microbiologie Environnement Digestif Santé (MEDIS), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Clermont Auvergne (UCA), London Research and Development Centre (LRDC), and University of Western Ontario (UWO)

Subjects
[SDV]Life Sciences [q-bio]
Abstract

International audience; Abstract Microbacterium sp. C448, isolated from a soil regularly exposed to sulfamethazine (SMZ), can use various sulphonamide antibiotics as the sole carbon source for growth. The basis for the regulation of genes encoding the sulphonamide metabolism pathway, the dihydropteroate synthase sulphonamide target (folP), and the sulphonamide resistance (sul1) genes, is unknown in this organism. In the present study, the response of the transcriptome and proteome of Microbacterium sp. C448 following exposure to subtherapeutic (33 µM) or therapeutic (832 µM) SMZ concentrations was evaluated. Therapeutic concentration induced the highest sad expression and Sad production, consistent with the activity of SMZ degradation observed in cellulo. Following complete SMZ degradation, Sad production tended to return to the basal level observed prior to SMZ exposure. Transcriptomic and proteomic kinetics were concomitant for the resistance genes and proteins. The abundance of Sul1 protein, 100-fold more abundant than FolP protein, did not change in response to SMZ exposure. Moreover, non-targeted analyses highlighted the increase of a deaminase RidA and a putative sulphate exporter expression and production. These two novel factors involved in the 4-aminophenol metabolite degradation and the export of sulphate residues formed during SMZ degradation, respectively, provided new insights into Microbacterium sp. C448 SMZ detoxification process.

Published
2023

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

Author

Diego P. Morgavi, Hamid Boudra, Bénédict Yanibada, Stéphanie Durand, Ulli Hohenester, Fabien Jourdan, Cécile Canlet, Anne Ferlay, Mélanie Pétéra, LESUR, Hélène, Unité Mixte de Recherche sur les Herbivores - UMR 1213 (UMRH), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Plateforme Exploration du Métabolisme-MetaboHUB (PFEM-MetaboHUB), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP), ToxAlim (ToxAlim), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Ecole d'Ingénieurs de Purpan (INPT - EI Purpan), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Metatoul AXIOM (E20 ), MetaboHUB-MetaToul, Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-ToxAlim (ToxAlim), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Ecole d'Ingénieurs de Purpan (INPT - EI Purpan), Métabolisme et Xénobiotiques (ToxAlim-MeX), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Unité de Nutrition Humaine (UNH), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Clermont Auvergne (UCA), Analyse de Xénobiotiques, Identification, Métabolisme (E20 Metatoul-AXIOM), MetaToul-MetaboHUB, Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Plateforme Exploration du Métabolisme (PFEM), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-MetaboHUB-Clermont, MetaboHUB-MetaboHUB, Université de Toulouse (UT)-Université de Toulouse (UT)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Ecole d'Ingénieurs de Purpan (INP - PURPAN), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), MetaboHUB-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-MetaboHUB-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-ToxAlim (ToxAlim), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Ecole d'Ingénieurs de Purpan (INP - PURPAN), and Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3)

Subjects
Rumen, multiplatform metabolomics, [SDV.BA] Life Sciences [q-bio]/Animal biology, Methanogenesis, [SDV]Life Sciences [q-bio], Gas Chromatography-Mass Spectrometry, 03 medical and health sciences, Metabolomics, Lactation, Genetics, Metabolome, medicine, Animals, [SDV.SA.SPA] Life Sciences [q-bio]/Agricultural sciences/Animal production studies, Food science, microbial metabolite, 030304 developmental biology, 2. Zero hunger, milk, 0303 health sciences, methane biomarker, Chemistry, dairy cow, [SDV.BA]Life Sciences [q-bio]/Animal biology, 0402 animal and dairy science, 04 agricultural and veterinary sciences, Metabolism, 040201 dairy & animal science, Diet, [SDV] Life Sciences [q-bio], Metabolic pathway, medicine.anatomical_structure, 13. Climate action, [SDV.SA.SPA]Life Sciences [q-bio]/Agricultural sciences/Animal production studies, Fermentation, Cattle, Female, Animal Science and Zoology, Gas chromatography, Methane, Food Science
Abstract

International audience; 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.

Published
2021

5. Metaproteomics Approach and Pathway Modulation in Obesity and Diabetes: A Narrative Review

Author

Francesco Maria, Calabrese, Annalisa, Porrelli, Mirco, Vacca, Blandine, Comte, Katharina, Nimptsch, Mariona, Pinart, Tobias, Pischon, Estelle, Pujos-Guillot, Maria, De Angelis, Department of Biology [University of Bari], Università degli studi di Bari Aldo Moro = University of Bari Aldo Moro (UNIBA), Plateforme Exploration du Métabolisme (PFEM), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-MetaboHUB-Clermont, MetaboHUB-MetaboHUB, Unité de Nutrition Humaine (UNH), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Clermont Auvergne (UCA), Molecular Epidemiology Research Group, Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), 13125 Berlin, Germany, MetaboHUB-Clermont, MetaboHUB, and Department of Soil, Plant and Food Sciences, University of Bari Aldo Moro, 70126 Bari, Italy

Subjects
Adult, Male, Proteomics, [SDV.OT]Life Sciences [q-bio]/Other [q-bio.OT], obesity, Adolescent, Review, metabolic diseases, Feces, Young Adult, Bacterial Proteins, low-grade inflammation, Humans, TX341-641, Child, Aged, Aged, 80 and over, Inflammation, diabetes, gut microbiota, Nutrition. Foods and food supply, Middle Aged, Gastrointestinal Microbiome, Diabetes Mellitus, Type 1, Diabetes Mellitus, Type 2, Child, Preschool, Dysbiosis, Female, metaproteomics
Abstract

International audience; Low-grade inflammatory diseases revealed metabolic perturbations that have been linked to various phenotypes, including gut microbiota dysbiosis. In the last decade, metaproteomics has been used to investigate protein composition profiles at specific steps and in specific healthy/pathologic conditions. We applied a rigorous protocol that relied on PRISMA guidelines and filtering criteria to obtain an exhaustive study selection that finally resulted in a group of 10 studies, based on metaproteomics and that aim at investigating obesity and diabetes. This batch of studies was used to discuss specific microbial and human metaproteome alterations and metabolic patterns in subjects affected by diabetes (T1D and T2D) and obesity. We provided the main up- and down-regulated protein patterns in the inspected pathologies. Despite the available results, the evident paucity of metaproteomic data is to be considered as a limiting factor in drawing objective considerations. To date, ad hoc prepared metaproteomic databases collecting pathologic data and related metadata, together with standardized analysis protocols, are required to increase our knowledge on these widespread pathologies.

Published
2022

6. Plasma proteomics reveals crosstalk between lipid metabolism and immunity in dairy cows receiving essential fatty acids and conjugated linoleic acid

Author

Arash Veshkini, Harald M. Hammon, Laura Vogel, Didier Viala, Mylène Delosière, Arnulf Tröscher, Sébastien Déjean, Fabrizio Ceciliani, Helga Sauerwein, Muriel Bonnet, Leibniz Institute for Farm Animal Biology (FBN), Universität Bonn = University of Bonn, Unité Mixte de Recherche sur les Herbivores - UMR 1213 (UMRH), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Università degli Studi di Milano = University of Milan (UNIMI), Plateforme Exploration du Métabolisme (PFEM), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-MetaboHUB-Clermont, MetaboHUB-MetaboHUB, BASF SE, Institut de Mathématiques de Toulouse UMR5219 (IMT), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), and Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Proteomics, Multidisciplinary, Fatty Acids, Essential, [SDV]Life Sciences [q-bio], Fatty Acids, food and beverages, Lipid Metabolism, Diet, Milk, Dietary Supplements, Animals, Lactation, Cattle, Female, Linoleic Acids, Conjugated, lipids (amino acids, peptides, and proteins)
Abstract

Essential fatty acids (EFA) and conjugated linoleic acids (CLA) are unsaturated fatty acids with immune-modulatory effects, yet their synergistic effect is poorly understood in dairy cows. This study aimed at identifying differentially abundant proteins (DAP) and their associated pathways in dairy cows supplied with a combination of EFA and CLA during the transition from antepartum (AP) to early postpartum (PP). Sixteen Holstein cows were abomasally infused with coconut oil as a control (CTRL) or a mixture of EFA (linseed + safflower oil) and CLA (Lutalin, BASF) (EFA + CLA) from − 63 to + 63 days relative to parturition. Label-free quantitative proteomics was performed on plasma samples collected at days − 21, + 1, + 28, and + 63. During the transition time, DAP, consisting of a cluster of apolipoproteins (APO), including APOE, APOH, and APOB, along with a cluster of immune-related proteins, were related to complement and coagulation cascades, inflammatory response, and cholesterol metabolism. In response to EFA + CLA, specific APO comprising APOC3, APOA1, APOA4, and APOC4 were increased in a time-dependent manner; they were linked to triglyceride-enriched lipoprotein metabolisms and immune function. Altogether, these results provide new insights into metabolic and immune adaptation and crosstalk between them in transition dairy cows divergent in EFA + CLA status.

Published
2022

7. Untargeted metabolomics confirms the association between plasma branched chain amino acids and residual feed intake in beef heifers

Author

Ezequiel Jorge-Smeding, Sergio Polakof, Muriel Bonnet, Stephanie Durand, Delphine Centeno, Mélanie Pétéra, Sébastien Taussat, Gonzalo Cantalapiedra-Hijar, Unité Mixte de Recherche sur les Herbivores - UMR 1213 (UMRH), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Plateforme Exploration du Métabolisme (PFEM), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-MetaboHUB-Clermont, MetaboHUB-MetaboHUB, Génétique Animale et Biologie Intégrative (GABI), AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Eliance

Subjects
Male, Plasma, Eating, Multidisciplinary, [SDV.BA.MVSA]Life Sciences [q-bio]/Animal biology/Veterinary medicine and animal Health, [SDV]Life Sciences [q-bio], Disease Progression, Animals, Metabolomics, Cattle, Female, [SDV.AEN]Life Sciences [q-bio]/Food and Nutrition, Amino Acids, Branched-Chain
Abstract

This study explored plasma biomarkers and metabolic pathways underlying feed efficiency measured as residual feed intake (RFI) in Charolais heifers. A total of 48 RFI extreme individuals (High-RFI, n = 24; Low-RFI, n = 24) were selected from a population of 142 heifers for classical plasma metabolite and hormone quantification and plasma metabolomic profiling through untargeted LC-MS. Most efficient heifers (Low-RFI) had greater (P = 0.03) plasma concentrations of IGF-1 and tended to have (P = 0.06) a lower back fat depth compared to least efficient heifers. However, no changes were noted (P ≥ 0.10) for plasma concentrations of glucose, insulin, non-esterified fatty acids, β-hydroxybutyrate and urea. The plasma metabolomic dataset comprised 3,457 ions with none significantly differing between RFI classes after false discovery rate correction (FDR > 0.10). Among the 101 ions having a raw P < 0.05 for the RFI effect, 13 were putatively annotated by using internal databases and 6 compounds were further confirmed with standards. Metabolic pathway analysis from these 6 confirmed compounds revealed that the branched chain amino acid metabolism was significantly (FDR < 0.05) impacted by the RFI classes. Our results confirmed for the first time in beef heifers previous findings obtained in male beef cattle and pointing to changes in branched-chain amino acids metabolism along with that of body composition as biological mechanisms related to RFI. Further studies are warranted to ascertain whether there is a cause-and-effect relationship between these mechanisms and RFI.

Published
2022

8. The Plasma Oxylipin Signature Provides a Deep Phenotyping of Metabolic Syndrome Complementary to the Clinical Criteria

Author

Céline Dalle, Jérémy Tournayre, Malwina Mainka, Alicja Basiak-Rasała, Mélanie Pétéra, Sophie Lefèvre-Arbogast, Jessica Dalloux-Chioccioli, Mélanie Deschasaux-Tanguy, Lucie Lécuyer, Emmanuelle Kesse-Guyot, Léopold K. Fezeu, Serge Hercberg, Pilar Galan, Cécilia Samieri, Katarzyna Zatońska, Philip C. Calder, Mads Fiil Hjorth, Arne Astrup, André Mazur, Justine Bertrand-Michel, Nils Helge Schebb, Andrzej Szuba, Mathilde Touvier, John W. Newman, Cécile Gladine, Unité de Nutrition Humaine (UNH), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Clermont Auvergne (UCA), University of Wuppertal, Wrocław Medical University, Plateforme Exploration du Métabolisme (PFEM), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-MetaboHUB-Clermont, MetaboHUB-MetaboHUB, Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), MetaboHUB-MetaToul, MetaboHUB-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut des Maladies Métaboliques et Casdiovasculaires (UPS/Inserm U1297 - I2MC), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM), Equipe 3: EREN- Equipe de Recherche en Epidémiologie Nutritionnelle (CRESS - U1153), Université Sorbonne Paris Nord-Centre de Recherche Épidémiologie et Statistique Sorbonne Paris Cité (CRESS (U1153 / UMR_A_1125 / UMR_S_1153)), Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), University Hospital Southampton NHS Foundation Trust, University of Southampton, Novo Nordisk Inc, NOVO NORDISK PARK, University of California [Davis] (UC Davis), University of California (UC), and Western Human Nutrition Research Center

Subjects
metabolic phenotyping, oxylipins, lipid mediators, Catalysis, metabolic syndrome, Inorganic Chemistry, Clinical Research, Genetics, Humans, 2.1 Biological and endogenous factors, [SDV.BBM]Life Sciences [q-bio]/Biochemistry, Molecular Biology, Physical and Theoretical Chemistry, Aetiology, Molecular Biology, Spectroscopy, Nutrition, Metabolic Syndrome, Chemical Physics, Organic Chemistry, lipidomics, General Medicine, Computer Science Applications, Good Health and Well Being, Cardiovascular Diseases, Case-Control Studies, Other Biological Sciences, Other Chemical Sciences, [SDV.AEN]Life Sciences [q-bio]/Food and Nutrition
Abstract

International audience; Metabolic syndrome (MetS) is a complex condition encompassing a constellation of cardiometabolic abnormalities. Oxylipins are a superfamily of lipid mediators regulating many cardiometabolic functions. Plasma oxylipin signature could provide a new clinical tool to enhance the phenotyping of MetS pathophysiology. A high-throughput validated mass spectrometry method, allowing for the quantitative profiling of over 130 oxylipins, was applied to identify and validate the oxylipin signature of MetS in two independent nested case/control studies involving 476 participants. We identified an oxylipin signature of MetS (coined OxyScore), including 23 oxylipins and having high performances in classification and replicability (cross-validated AUCROC of 89%, 95% CI: 85–93% and 78%, 95% CI: 72–85% in the Discovery and Replication studies, respectively). Correlation analysis and comparison with a classification model incorporating the MetS criteria showed that the oxylipin signature brings consistent and complementary information to the clinical criteria. Being linked with the regulation of various biological processes, the candidate oxylipins provide an integrative phenotyping of MetS regarding the activation and/or negative feedback regulation of crucial molecular pathways. This may help identify patients at higher risk of cardiometabolic diseases. The oxylipin signature of patients with metabolic syndrome enhances MetS phenotyping and may ultimately help to better stratify the risk of cardiometabolic diseases.

Published
2022

9. A project-scale map of metadata to improve future data management

Author

Pétéra, Mélanie, Cabasson, Cecile, Comte, Blandine, Duperier, Christophe, Filangi, Olivier, Prigent, Sylvain, Pujos-Guillot, Estelle, Giacomoni, Franck, Plateforme Exploration du Métabolisme (PFEM), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-MetaboHUB-Clermont, MetaboHUB-MetaboHUB, Biologie du fruit et pathologie (BFP), Université de Bordeaux (UB)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Plateforme Bordeaux Metabolome, Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-MetaboHUB-Bordeaux, Institut de Génétique, Environnement et Protection des Plantes (IGEPP), Université de Rennes (UR)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Rennes Angers, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), ANR-11-INBS-0010,METABOHUB,Développement d'une infrastructure française distribuée pour la métabolomique dédiée à l'innovation(2011), Petera, Mélanie, and Développement d'une infrastructure française distribuée pour la métabolomique dédiée à l'innovation - - METABOHUB2011 - ANR-11-INBS-0010 - INBS - VALID

Subjects
[CHIM.OTHE] Chemical Sciences/Other, Gestion de données de la recheche, [CHIM.OTHE]Chemical Sciences/Other, Métabolomique, FAIR, Méta-données
Abstract

International audience; Today, the intra-lab application of best practices in the metabolomics field usually guarantees an adequate data exploitation within a single lab. However, the growing interest in multi-analyses designs (e.g. complementary analytical platforms, variety of matrices, multi-omics), as well as the need of data sharing and reuse, increase the difficulty of data management. Indeed, managing the multiplicity and the heterogeneity of information involved is required to achieve relevant knowledge extraction from metabolomics data. Within the MetaboHUB national infrastructure, one objective is to optimize data handling, especially metadata, to facilitate large-scale analyses, multi-platforms studies, and data FAIRisation (Findability, Accessibility, Interoperability, Reusability). In particular, this fits in the MetaboHUB scientific roadmap that promotes the open science development in the field of metabolomics.In the context of metabolomic and lipidomic studies, data production and analysis come along with a large diversity of metadata (data of the data). To identify clearly-defined bottlenecks and targets for future improvement in data management, the objective of this work was to build a metadata map at the scale of a scientific project. Aiming for completeness, this map was constructed in a collaborative and multidisciplinary way involving chemists, biologists, data stewards as well as computer scientists, combining their respective experience and knowledge. Based on the resulting metadata map, targets (areas and topics) to be further investigated were identified, enabling the construction of transversal working groups at the consortium scale. In particular, this work enables to focus efforts on clearly defined issues to improve standardisation of practices regarding data management and metadata documentation. In conclusion, this collaborative map construction has been shown to be an efficient tool to draw a clear « where do we stand / where do we go » picture inside a national infrastructure like MetaboHUB regarding project-scale metadata. This facilitates the definition of a precise data management. Such an approach could be translated within other infrastructures, consortia and/or communities.

Published
2022

10. Update on technological developments and opportunities with Workflow4Metabolomics

Author

Pavot, Lain, Pétéra, Mélanie, Paulhe, Nils, Guitton, Yann, Le Corguillé, Gildas, Saint-Vanne, Julien, Tremblay-Franco, Marie, Canlet, Cécile, Martin, Jean-François, Weber, Ralf, Delporte, Cédric, Souard, Florence, Dalle, Céline, Giacomoni, Franck, Plateforme Exploration du Métabolisme (PFEM), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-MetaboHUB-Clermont, MetaboHUB-MetaboHUB, Laboratoire d'étude des Résidus et Contaminants dans les Aliments (LABERCA), École nationale vétérinaire, agroalimentaire et de l'alimentation Nantes-Atlantique (ONIRIS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), ABiMS - Informatique et bioinformatique = Analysis and Bioinformatics for Marine Science (ABIMS), Fédération de recherche de Roscoff (FR2424), Station biologique de Roscoff (SBR), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Station biologique de Roscoff (SBR), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), ToxAlim (ToxAlim), Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Ecole d'Ingénieurs de Purpan (INP - PURPAN), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Metatoul AXIOM (E20 ), MetaboHUB-MetaToul, MetaboHUB-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-MetaboHUB-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-ToxAlim (ToxAlim), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Ecole d'Ingénieurs de Purpan (INP - PURPAN), University of Birmingham [Birmingham], Université libre de Bruxelles (ULB), Institut de Recherche Biomédicale des Armées [Brétigny-sur-Orge] (IRBA), Plateforme Exploration du Métabolisme-MetaboHUB (PFEM-MetaboHUB), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Ecole d'Ingénieurs de Purpan (INPT - EI Purpan), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-ToxAlim (ToxAlim), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Ecole d'Ingénieurs de Purpan (INPT - EI Purpan), Institut de Recherche Biomédicale des Armées (IRBA), and Petera, Mélanie

Subjects
Métabolomique non ciblée, [CHIM.ANAL] Chemical Sciences/Analytical chemistry, Galaxy web interface, [CHIM.ANAL]Chemical Sciences/Analytical chemistry, [CHIM.CHEM] Chemical Sciences/Cheminformatics, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], Traitement de données, [CHIM.CHEM]Chemical Sciences/Cheminformatics, [INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM]
Abstract

International audience; IntroductionMetabolomics data analysis is a complex and multistep process, which is constantly evolving with the development of new analytical technologies, mathematical methods, bioinformatics tools and databases. The Workflow4Metabolomics (W4M) infrastructure[1] provides tools in a single online web interface (through Galaxy[1]). During the last two years, W4M has evolved with new upgrades for LC-MS, LC-MSMS, GC-MS and NMR pipelines, including preprocessing, quality control, statistical analysis and annotation tools. W4M also proposes new community resources promoting open science in metabolomics.Technological and methodological innovationW4M major updates include: Specific Galaxy interactive tools with NMRPro[2] for NMR spectra visualization and Xseeker for visualization and annotation of LC-MSMS data (In collaboration with CHOPIN ANR project[3]); An improved MSMS pipeline; New annotation tools suite allowing connexion with PeakForest[4], a new spectral data manager infrastructure for laboratories; New functionalities regarding mixed model computation for repeated measure designs, and improvements in annotation of complex mixture bidimensional NMR spectra. New training resources through the Galaxy Training Network (GTN) are also proposed, and Training Infrastructure as a Service (TIass) is available through the new usegalaxy.fr host.Results and impactW4M’s improvements increase raw data input management and LC/GC-MS(MS) workflow efficiency. We highlight how current advances, along with community training as through the yearly international school Workflow4Experimenters, contribute to open data analysis practices worldwide. In addition the W4M organization on Github repository aims to review code, annotate tools and propose a showcase for contributors from the metabolomics community.References[1] Giacomoni F., Le Corguillé et al (2015). Workflow4Metabolomics: A collaborative research infrastructure for computational metabolomics. Bioinformatics 2015, May 1;31(9):1493-5. doi: 10.1093/bioinformatics/btu813[2] Mohamed A, Nguyen CH, Mamitsuka H. NMRPro: an integrated web component for interactive processing and visualization of NMR spectra. Bioinformatics. 2016 Jul 1;32(13):2067-8. doi: 10.1093/bioinformatics/btw102. Epub 2016 Feb 26. PMID: 27153725.[3] https://anr.fr/ProjetIA-16-RHUS-0007[4] Paulhe, N., Canlet, C., Damont, A. et al. PeakForest: a multi-platform digital infrastructure for interoperable metabolite spectral data and metadata management. Metabolomics 18, 40 (2022). doi: 10.1007/s11306-022-01899-3[5] Afgan E. et al. The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2016 update. Nucleic Acids Res. 2016 Jul 8;44(W1):W3-W10. doi: 10.1093/nar/gkw343

Published
2022

11. Metabolite reporting in large-scale studies within different metabolomics communities: DO WE SPEAK THE SAME LANGUAGE?

Author

Hajjar, Ghina, Benaben, David, Paulhe, Nils, Duperier, Christophe, Filangi, Olivier, Giacomoni, Franck, Comte, Blandine, Pujos-Guillot, Estelle, Plateforme Exploration du Métabolisme (PFEM), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-MetaboHUB-Clermont, MetaboHUB-MetaboHUB, Biologie du fruit et pathologie (BFP), Université de Bordeaux (UB)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut de Génétique, Environnement et Protection des Plantes (IGEPP), Université de Rennes (UR)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Rennes Angers, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), and Hajjar, Ghina

Subjects
[SDV.AEN] Life Sciences [q-bio]/Food and Nutrition, [CHIM.ANAL] Chemical Sciences/Analytical chemistry, [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB], [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, [CHIM.ANAL]Chemical Sciences/Analytical chemistry, [INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB], [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], [SDV.AEN]Life Sciences [q-bio]/Food and Nutrition, [INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM]
Abstract

International audience; Since the emergence of high throughput metabolomics, there has been a growing number of scientific communities performing metabolomic studies. Therefore, it has become crucial to standardize reporting and sharing of metabolites. Although minimum reporting standards for analytical practices and data processing are available, there are no established standards for metabolite reporting. In this context, our objective was to review the existing practices in terms of metabolite reporting in different scientific communities both in published results and across databases.In this context, we considered plasma metabolites reported in human large-scale studies from different communities, namely analytical chemistry, medicine and epidemiology. We focused only on metabolites reported as level 1 identification according to the Metabolomics Standard Initiative. We applied a data curation workflow on the list of annotated metabolites given by the authors. First, we performed a manual curation that included the addition of missing identifiers and the editing of some incoherent metadata. Second, we applied an automatic query algorithm in order to obtain additional information from available databases such as the compact hash code of the IUPAC International Chemical Identifier “InChIKey”. Identified metabolites were then compared between the selected studies using either the names given by the authors or the InChIKeys added after data curation. Regular inconsistencies were observed in metabolite reporting both in published results and across different databases. In the former, incoherence was observed in the metabolite information (identifiers not referring to the same isomer, metabolite name not corresponding to the molecular formula). Besides, isomers were listed with their corresponding retention times, yet without any indication of the isomers’ identity. On the other hand, cross-linking provided across databases presented some incoherent information regarding nomenclatures, optical isomerism, stereochemistry of asymmetric carbons, and molecular structure (acid/base; zwitterionic or canonical forms, molecules with a permanent charge) in addition to a mismatch between two structurally different compounds. The evaluation of metabolite reporting across different databases for instance HMDB, PubChem and ChEBI was performed with the help of the Metabolomics Semantic DataLake (MSD) team. Information was calculated from latest public versions of the aforementioned databases, under a Big Data infrastructure (Apache Spark) and Scala programming language. Based on the InChIKey, we were able to identify all incorrect metabolite matches in HMDB, PubChem and ChEBI and to categorize them into “structurally different compounds”, “optical isomerism” or “structural isomerism”.Although not yet required, the InChIKey was found to be the most suitable identifier for comparing reported metabolites between studies and across databases. It is therefore recommended either to use this identifier or to perform a deep data curation when reporting identified metabolites. This work will allow providing guidelines for a more effective and reproducible metabolomics data sharing.

Published
2022

12. Optimization of metabolome extraction procedures and implementation of a PeakForest database for the identification of microorganisms compounds by LC-HRMS

Author

Mansouri, Wiam, Jousse, Cyril, Lagrée, Marie, Paulhe, Nils, Diémé, Binta, Plateforme Exploration du Métabolisme (PFEM), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-MetaboHUB-Clermont, MetaboHUB-MetaboHUB, and Diémé, Binta

Subjects
[CHIM.ANAL] Chemical Sciences/Analytical chemistry, [CHIM.ANAL]Chemical Sciences/Analytical chemistry, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], [INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM]
Abstract

International audience; The investigation of microbial communities and their interactions with their environments is a field of research that engaged the scientific community for several decades. We study in the laboratory microorganisms isolated from freshwater and atmospheric ecosystems in different conditions. The aim of this internship was to optimize the metabolomic workflows of four microorganisms (Pseudomonas syringae, Rhodococcus rhodococcus, Microcystis aeruginosa, Chlorella spp.) from extraction to annotation of compounds. Objectives: i) Optimize metabolome extraction protocol for each microorganism, ii) Implementation of a PeakForest database with MetaCyc and NPATLAS databases, iii) Annotation of microorganism's metabolomes.

Published
2022

13. Metabolite reporting within large-scale studies: where do we stand?

Author

Hajjar, Ghina, Giacomoni, Franck, Comte, Blandine, Pujos-Guillot, Estelle, Plateforme Exploration du Métabolisme (PFEM), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-MetaboHUB-Clermont, MetaboHUB-MetaboHUB, and Hajjar, Ghina

Subjects
[SDV.AEN] Life Sciences [q-bio]/Food and Nutrition, [CHIM.ANAL] Chemical Sciences/Analytical chemistry, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, [CHIM.ANAL]Chemical Sciences/Analytical chemistry, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], [SDV.AEN]Life Sciences [q-bio]/Food and Nutrition, [INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM]
Abstract

International audience

Published
2022

14. Global and partial effect assessment in metabolic syndrome explored by metabolomics

Author

Marion Brandolini-Bunlon, Benoit Jaillais, Véronique Cariou, Blandine Comte, Estelle Pujos-Guillot, Evelyne Vigneau, Unité de Nutrition Humaine (UNH), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Clermont Auvergne (UCA), Plateforme Exploration du Métabolisme (PFEM), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-MetaboHUB-Clermont, MetaboHUB-MetaboHUB, Statistique, Sensométrie et Chimiométrie (StatSC), École nationale vétérinaire, agroalimentaire et de l'alimentation Nantes-Atlantique (ONIRIS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Société Française de Statistiques (SFdS), Groupe Français de Chimiométrie (GFC), and Brandolini-Bunlon, Marion

Subjects
multiblock, [STAT.AP]Statistics [stat]/Applications [stat.AP], metabolomics, clinical data, global effect, partial effect, partial correlation, metabolic syndrome, NuAge cohort, Partial effect, Endocrinology, Diabetes and Metabolism, Global effect, Biochemistry, [STAT]Statistics [stat], [STAT.AP] Statistics [stat]/Applications [stat.AP], [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, effects, Molecular Biology, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology, ComputingMilieux_MISCELLANEOUS
Abstract

In nutrition and health research, untargeted metabolomics is actually analyzed simultaneously with clinical data to improve prediction and better understand pathological status. This can be modeled using a multiblock supervised model with several input data blocks (metabolomics, clinical data) being potential predictors of the outcome to be explained. Alternatively, this configuration can be represented with a path diagram where the input blocks are each connected by links directed to the outcome—as in multiblock supervised modeling—and are also related to each other, thus allowing one to account for block effects. On the basis of a path model, we show herein how to estimate the effect of an input block, either on its own or conditionally to other(s), on the output response, respectively called “global” and “partial” effects, by percentages of explained variance in dedicated PLS regression models. These effects have been computed in two different path diagrams in a case study relative to metabolic syndrome, involving metabolomics and clinical data from an older men′s cohort (NuAge). From the two effects associated with each path, the results highlighted the complementary information provided by metabolomics to clinical data and, reciprocally, in the metabolic syndrome exploration.

Published
2022

15. HDHL-INTIMIC: A European Knowledge Platform on Food, Diet, Intestinal Microbiomics, and Human Health

Author

Valeria, Agamennone, Peter M, Abuja, Marijana, Basic, Maria, De Angelis, André, Gessner, Bart, Keijser, Martin, Larsen, Mariona, Pinart, Katharina, Nimptsch, Estelle, Pujos-Guillot, Kristina, Schlicht, Itai, Sharon, Eva, Untersmayr, Matthias, Laudes, Tobias, Pischon, Jildau, Bouwman, On Behalf Of The Consortium, Plateforme Exploration du Métabolisme (PFEM), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-MetaboHUB-Clermont, MetaboHUB-MetaboHUB, and European Project: 277673,EC:FP7:KBBE,FP7-JPROG-2011-RTD,HDHL CSA(2011)

Subjects
standardization, Nutrition and Dietetics, data sharing, networking, microbiome, health, metabolomics, Gastrointestinal Microbiome, Intestines, Diabetes Mellitus, Type 2, Cardiovascular and Metabolic Diseases, Food, Humans, diet, FAIR, data integration, reference microbiome, Technology Platforms, [SDV.AEN]Life Sciences [q-bio]/Food and Nutrition, Food Science
Abstract

International audience; Studies indicate that the intestinal microbiota influences general metabolic processes in humans, thereby modulating the risk of chronic diseases such as type 2 diabetes, allergy, cardiovascular disease, and colorectal cancer (CRC). Dietary factors are also directly related to chronic disease risk, and they affect the composition and function of the gut microbiota. Still, detailed knowledge on the relation between diet, the microbiota, and chronic disease risk is limited. The overarching aim of the HDHL-INTIMIC (INtesTInal MICrobiomics) knowledge platform is to foster studies on the microbiota, nutrition, and health by assembling available knowledge of the microbiota and of the other aspects (e.g., food science and metabolomics) that are relevant in the context of microbiome research. The goal is to make this information findable, accessible, interoperable, and reusable (FAIR) to the scientific community, and to share information with the various stakeholders. Through these efforts a network of transnational and multidisciplinary collaboration has emerged, which has contributed to further develop and increase the impact of microbiome research in human health. The roles of microbiota in early infancy, during ageing, and in subclinical and clinically manifested disease are identified as urgent areas of research in this knowledge platform.

Published
2022

16. PeakForest: a multi-platform digital infrastructure for interoperable metabolite spectral data and metadata management

Author

Nils Paulhe, Cécile Canlet, Annelaure Damont, Lindsay Peyriga, Stéphanie Durand, Catherine Deborde, Sandra Alves, Stephane Bernillon, Thierry Berton, Raphael Bir, Alyssa Bouville, Edern Cahoreau, Delphine Centeno, Robin Costantino, Laurent Debrauwer, Alexis Delabrière, Christophe Duperier, Sylvain Emery, Amelie Flandin, Ulli Hohenester, Daniel Jacob, Charlotte Joly, Cyril Jousse, Marie Lagree, Nadia Lamari, Marie Lefebvre, Claire Lopez-Piffet, Bernard Lyan, Mickael Maucourt, Carole Migne, Marie-Francoise Olivier, Estelle Rathahao-Paris, Pierre Petriacq, Julie Pinelli, Léa Roch, Pierrick Roger, Simon Roques, Jean-Claude Tabet, Marie Tremblay-Franco, Mounir Traïkia, Anna Warnet, Vanessa Zhendre, Dominique Rolin, Fabien Jourdan, Etienne Thévenot, Annick Moing, Emilien Jamin, François Fenaille, Christophe Junot, Estelle Pujos-Guillot, Franck Giacomoni, Unité de Nutrition Humaine (UNH), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Clermont Auvergne (UCA), Metatoul AXIOM (E20 ), MetaboHUB-MetaToul, MetaboHUB-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-MetaboHUB-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-ToxAlim (ToxAlim), Université de Toulouse (UT)-Ecole d'Ingénieurs de Purpan (INP - PURPAN), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Ecole d'Ingénieurs de Purpan (INP - PURPAN), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), ToxAlim (ToxAlim), Médicaments et Technologies pour la Santé (MTS), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Plateforme Exploration du Métabolisme (PFEM), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-MetaboHUB-Clermont, MetaboHUB-MetaboHUB, Biologie du fruit et pathologie (BFP), Université de Bordeaux (UB)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Plateforme Bordeaux Metabolome, Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-MetaboHUB-Bordeaux, MetaToul FluxoMet (TBI-MetaToul), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Toulouse Biotechnology Institute (TBI), Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), The PeakForest project is supported by the French National Facility in Metabolomics & Fluxomics, MetaboHUB (11-INBS-0010), launched by the French Ministry of Research and Higher Education and the French ANR funding agency within the Programme 'Investissements d’Avenir', and ANR-11-INBS-0010,METABOHUB,Développement d'une infrastructure française distribuée pour la métabolomique dédiée à l'innovation(2011)

Subjects
Metadata, [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB], Endocrinology, Diabetes and Metabolism, [SDV]Life Sciences [q-bio], Clinical Biochemistry, Metabolite identification, Spectral library, Interoperability, Biochemistry, Mass Spectrometry, Curation, Database, Metabolome, [CHIM]Chemical Sciences, Metabolomics, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], Data Curation, FAIR
Abstract

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.

Published
2022

17. Untargeted metabolomics approach to study polymers biodegradation by Rhodococcus Rhodochrous using LC-HRMS

Author

Diémé, Binta, Lagrée, Marie, Leremboure, Martin, Traïkia, Mounir, Jousse, Cyril, Delort, Anne-Marie, Eyheraguibel, Boris, Diémé, Binta, Plateforme Exploration du Métabolisme (PFEM), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-MetaboHUB-Clermont, and MetaboHUB-MetaboHUB

Subjects
[STAT]Statistics [stat], [SDE] Environmental Sciences, [CHIM.ANAL] Chemical Sciences/Analytical chemistry, [CHIM.ANAL]Chemical Sciences/Analytical chemistry, [SDE]Environmental Sciences, [STAT] Statistics [stat]
Abstract

International audience; Many environmental studies have identified contaminations of marine, soil, freshwater and atmospheric ecosystems by (micro) plastics. Some studies have highlighted microorganism enable of using plastics polymers as a carbon source. However, the metabolic pathways involved in polymer biodegradation are largely unknown. In order to evaluate these processes, we used a metabolomics approach.A bacterial strain Rhodococcus Rhodochrous was grown with or without different carbon sources: glucose (GLU) or oleic acid (OA) or poly-ethylene (PE) or no carbon source (Minimum Medium, MM).Objective: highlight the metabolic pathways involved in the biodegradation of PE

Published
2022

18. Genomic and Metabolic Characteristics of the Pathogenicity in Pseudomonas aeruginosa

Author

Gilberto Igrejas, Carlos Alonso-Calleja, Rosa Capita, Patrícia Poeta, Telma de Sousa, Luís Maltez, José Eduardo Pereira, Michel Hébraud, Maria L. N. Enes Dapkevicius, Universidade de Trás-os-Montes e Alto Douro (UTAD), Universidade do Trás-os-Montes e Alto Douro, Microbiologie Environnement Digestif Santé (MEDIS), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Clermont Auvergne (UCA), INRAE, Plateforme d’Exploration du Métabolisme, Composante Protéomique (PFEMcp), 63122 Saint-Genès Champanelle, University of the Azores, University of Trás-os-Montes and Alto Douro [Portugal] (UTAD), University of Sierra Leone (USL), NOVA University of Lisbon, Plateforme Exploration du Métabolisme (PFEM), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-MetaboHUB-Clermont, MetaboHUB-MetaboHUB, and Universidade Nova de Lisboa = NOVA University Lisbon (NOVA)

Subjects
QH301-705.5, medicine.drug_class, medicine.medical_treatment, [SDV]Life Sciences [q-bio], Antibiotics, multidrug-resistant, virulence factors, Virulence, Review, Biology, medicine.disease_cause, Catalysis, biofilm, Microbiology, Targeted therapy, Inorganic Chemistry, Sepsis, 03 medical and health sciences, medicine, Animals, Humans, pathogenicity, Pseudomonas Infections, Biology (General), Physical and Theoretical Chemistry, QD1-999, Molecular Biology, Pathogen, Spectroscopy, 030304 developmental biology, 0303 health sciences, 030306 microbiology, Pseudomonas aeruginosa, Organic Chemistry, General Medicine, Genomics, medicine.disease, Antimicrobial, 3. Good health, Computer Science Applications, Anti-Bacterial Agents, Chemistry, Pneumonia (non-human), Metabolic Networks and Pathways
Abstract

In recent years, the effectiveness of antimicrobials in the treatment of Pseudomonas aeruginosa infections has gradually decreased. This pathogen can be observed in several clinical cases, such as pneumonia, urinary tract infections, sepsis, in immunocompromised hosts, such as neutropenic cancer, burns, and AIDS patients. Furthermore, Pseudomonas aeruginosa causes diseases in both livestock and pets. The highly flexible and versatile genome of P. aeruginosa allows it to have a high rate of pathogenicity. The numerous secreted virulence factors, resulting from its numerous secretion systems, the multi-resistance to different classes of antibiotics, and the ability to produce biofilms are pathogenicity factors that cause numerous problems in the fight against P. aeruginosa infections and that must be better understood for an effective treatment. Infections by P. aeruginosa represent, therefore, a major health problem and, as resistance genes can be disseminated between the microbiotas associated with humans, animals, and the environment, this issue needs be addressed on the basis of an One Health approach. This review intends to bring together and describe in detail the molecular and metabolic pathways in P. aeruginosa’s pathogenesis, to contribute for the development of a more targeted therapy against this pathogen.

Published
2021

19. Pea Proteins Have Anabolic Effects Comparable to Milk Proteins on Whole Body Protein Retention and Muscle Protein Metabolism in Old Rats

Author

Jérôme Salles, Corinne Pouyet, Marine Gueugneau, Alexandre Berry, Christelle Guillet, Olivier Le Bacquer, Heidi Jacobs, Yves Boirie, Christophe Giraudet, Stéphane Walrand, Carmen Malnero-Fernandez, Philippe Denis, Véronique Patrac, Unité de Nutrition Humaine (UNH), Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Clermont Auvergne (UCA), Plateforme Exploration du Métabolisme (PFEM), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-MetaboHUB-Clermont, MetaboHUB-MetaboHUB, Service de Nutrition Clinique [CHU Clermont-Ferrand], CHU Gabriel Montpied [Clermont-Ferrand], and CHU Clermont-Ferrand-CHU Clermont-Ferrand

Subjects
Male, pea proteins, protein digestibility, Nitrogen balance, Net protein utilization, Anabolism, 030309 nutrition & dietetics, [SDV]Life Sciences [q-bio], Muscle Proteins, 030209 endocrinology & metabolism, Article, sarcopenia, 03 medical and health sciences, chemistry.chemical_compound, Anabolic Agents, 0302 clinical medicine, Casein, medicine, Protein biosynthesis, Animals, muscle protein metabolism, TX341-641, Food science, Amino Acids, Rats, Wistar, skeletal muscle, Muscle, Skeletal, 2. Zero hunger, 0303 health sciences, Nutrition and Dietetics, Nutrition. Foods and food supply, Pea protein, Caseins, Skeletal muscle, food and beverages, Metabolism, Milk Proteins, plant proteins, Rats, Whey Proteins, medicine.anatomical_structure, chemistry, Proteolysis, Digestion, Nutritive Value, [SDV.AEN]Life Sciences [q-bio]/Food and Nutrition, Food Science
Abstract

International audience; Plant proteins are attracting rising interest due to their pro-health benefits and environmental sustainability. However, little is known about the nutritional value of pea proteins when consumed by older people. Herein, we evaluated the digestibility and nutritional efficiency of pea proteins compared to casein and whey proteins in old rats. Thirty 20-month-old male Wistar rats were assigned to an isoproteic and isocaloric diet containing either casein (CAS), soluble milk protein (WHEY) or Pisane™ pea protein isolate for 16 weeks. The three proteins had a similar effect on nitrogen balance, true digestibility and net protein utilization in old rats, which means that different protein sources did not alter body composition, tissue weight, skeletal muscle protein synthesis or degradation. Muscle mitochondrial activity, inflammation status and insulin resistance were similar between the three groups. In conclusion, old rats used pea protein with the same efficiency as casein or whey proteins, due to its high digestibility and amino acid composition. Using these plant-based proteins could help older people diversify their protein sources and more easily achieve nutritional intake recommendations.

Published
2021
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20. Plasma Metabolomic Signatures Associated with Long-term Breast Cancer Risk in the SU.VI.MAX Prospective Cohort

Author

Mélanie Pétéra, Lucie Lécuyer, Aicha Demidem, Stéphanie Durand, Delphine Centeno, Nathalie Druesne-Pecollo, Emmanuelle Kesse-Guyot, Mélanie Deschasaux, Valentin Partula, Pilar Galan, Adrien Rossary, Bernard Lyan, Marie-Paule Vasson, Bernard Srour, Serge Hercberg, Mathilde Touvier, Marie Lagree, Thomas Ferreira, Estelle Pujos-Guillot, Paule Latino-Martel, Céline Dalle, Centre de Recherche Épidémiologie et Statistique Sorbonne Paris Cité (CRESS (U1153 / UMR_A_1125 / UMR_S_1153)), Institut National de la Recherche Agronomique (INRA)-Université Paris Diderot - Paris 7 (UPD7)-Université Paris Descartes - Paris 5 (UPD5)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM), Unité de Nutrition Humaine - Clermont Auvergne (UNH), Institut National de la Recherche Agronomique (INRA)-Université Clermont Auvergne (UCA), Plateforme d'Exploration du Métabolisme, MetaboHUB, Institut de Chimie, Université Clermont Auvergne (UCA), Unité de Nutrition Humaine (UNH), Institut National de la Recherche Agronomique (INRA)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020]), Plateforme Exploration du Métabolisme (PFEM), MetaboHUB-Clermont, MetaboHUB-MetaboHUB-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Clermont Auvergne (UCA), and Université Clermont Auvergne [2017-2020] (UCA [2017-2020])

Subjects
Adult, 0301 basic medicine, Oncology, medicine.medical_specialty, Epidemiology, Breast Neoplasms, [SDV.CAN]Life Sciences [q-bio]/Cancer, Mass Spectrometry, 03 medical and health sciences, 0302 clinical medicine, Breast cancer, Risk Factors, Internal medicine, Biomarkers, Tumor, medicine, Humans, Metabolomics, Prospective Studies, Prospective cohort study, Cell Proliferation, Cause of death, business.industry, Blood Proteins, Environmental exposure, Middle Aged, medicine.disease, 3. Good health, Glutamine, Oxidative Stress, 030104 developmental biology, Case-Control Studies, 030220 oncology & carcinogenesis, Etiology, Female, Energy Metabolism, business, Chromatography, Liquid, Follow-Up Studies, Cohort study, Blood drawing
Abstract

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.

Published
2019

21. Early life dietary intervention in dairy calves results in a long-term reduction in methane emissions

Author

Meale, S.J., Popova, M., Saro, C., Martín, C., Bernard, A., Lagree, M., Yáñez-Ruiz, David R., Boudra, H., Duval, S., Morgavi, Diego P., Fundación Alfonso Martín Escudero, Agence Nationale de la Recherche (France), Saro Higuera, Cristina [0000-0002-1887-4529], Unité Mixte de Recherche sur les Herbivores - UMR 1213 (UMRH), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Central Queensland University (CQU), Universidad de León [León], Plateforme Exploration du Métabolisme-Composante Protéomique (PFEM-CP), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Clermont Auvergne (UCA), Plateforme Exploration du Métabolisme (PFEM), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-MetaboHUB-Clermont, MetaboHUB-MetaboHUB, Consejo Superior de Investigaciones Científicas [Spain] (CSIC), European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie Grant658126Fundacion Alfonso Martin EscuderoFrench National Research Agency (ANR), European Project: 0226575(2003), MetaToul-MetaboHUB, Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Saro Higuera, Cristina

Subjects
Rumen, Propanols, Science, Body Weight, Microbial communities, [SDV.BBM.BM]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Molecular biology, Weaning, Animal Feed, Archaea, Article, Body Fluids, Diet, Microbial ecology, Applied microbiology, [SDV.MP]Life Sciences [q-bio]/Microbiology and Parasitology, Fermentation, Medicine, Animals, Lactation, Cattle, Female, Methane, Ecosystem
Abstract

13 páginas, 4 figuras, 1 tabla., Recent evidence suggests that changes in microbial colonization of the rumen prior to weaning may imprint the rumen microbiome and impact phenotypes later in life. We investigated how dietary manipulation from birth influences growth, methane production, and gastrointestinal microbial ecology. At birth, 18 female Holstein and Montbéliarde calves were randomly assigned to either treatment or control (CONT). Treatment was 3-nitrooxypropanol (3-NOP), an investigational anti-methanogenic compound that was administered daily from birth until three weeks post-weaning (week 14). Samples of rumen fluid and faecal content were collected at weeks 1, 4, 11, 14, 23, and 60 of life. Calves were tested for methane emissions using the GreenFeed system during the post-weaning period (week 11-23 and week 56-60 of life). Calf physiological parameters (BW, ADG and individual VFA) were similar across groups throughout the trial. Treated calves showed a persistent reduction in methane emissions (g CH4/d) throughout the post-weaning period up to at least 1 year of life, despite treatment ceasing three weeks post-weaning. Similarly, despite variability in the abundance of individual taxa across weeks, the rumen bacterial, archaeal and fungal structure differed between CONT and 3-NOP calves across all weeks, as visualised using sparse-PLS-DA. Similar separation was also observed in the faecal bacterial community. Interestingly, despite modest modifications to the abundance of rumen microbes, the reductive effect of 3-NOP on methane production persisted following cessation of the treatment period, perhaps indicating a differentiation of the ruminal microbial ecosystem or a host response triggered by the treatment in the early development phase., SM received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie Grant Agreement #658126. CS received a fellowship from the Fundación Alfonso Martín Escudero. This research was partially funded by the French National Research Agency (ANR) through the FACCE-JPI project RumenStability. The authors wish to thank Florence Fournier and personnel at the Her-bipole for animal care, and Dominique Graviou for laboratory technical support. We are grateful to the INRAE MIGALE bioinformatics platform (http://migal e.jouy.inra.fr) for providing computational resources

Published
2021

22. Data sharing in PredRet for accurate prediction of retention time: Application to plant food bioactive compounds

Author

Mark Philo, Kateřina Valentová, Ana Rodriguez-Mateos, Pierre Micheau, F. A. T. Barberán, Ville M. Koistinen, Pedro Mena, Gözde Gürdeniz, Marynka Ulaszewska, Sonia de Pascual-Teresa, Christof Van Poucke, László Abrankó, Stéphanie Durand, Conceição Almeida, Dorrain Yanwen Low, Dilip K. Rai, Wiesław Wiczkowski, Letizia Bresciani, Jan Stanstrup, Cristina Andres-Lacueva, Gesine Schmidt, Andreia Bento da Silva, Lars O. Dragsted, Senem Kamiloglu, Claudine Manach, Raúl González-Domínguez, Lucie Petrásková, Kati Hanhineva, Maria Rosário Bronze, Fulvio Mattivi, Esra Capanoglu, Rocío García-Villalba, European Cooperation in Science and Technology, European Commission, European Research Council, Nanyang Technological University, Prime Minister's Office Singapore, Agence Nationale de la Recherche (France), Czech Science Foundation, Universidade Nova de Lisboa, Fundação para a Ciência e a Tecnologia (Portugal), Lantmännen Research Foundation, Academy of Finland, University of Eastern Finland, Instituto de Salud Carlos III, Ministerio de Economía y Competitividad (España), Generalitat de Catalunya, Agencia Estatal de Investigación (España), Ministerio de Ciencia, Innovación y Universidades (España), Institución Catalana de Investigación y Estudios Avanzados, Consejo Superior de Investigaciones Científicas (España), Fundación Séneca, Gobierno de la Región de Murcia, Norwegian Institute of Food, Fisheries and Aquaculture Research, Carlsberg Foundation, Hungarian Academy of Sciences, Unité de Nutrition Humaine (UNH), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Clermont Auvergne (UCA), Institute of Public Health and Clinical Nutrition, University of Turku, Szent István University, King‘s College London, Universidade Nova de Lisboa = NOVA University Lisbon (NOVA), University Institute of Lisbon (ISCTE), Research Institute for Agricultural, Fisheries and Food (ILVO), University of Barcelona, CIBER de Fragilidad y Envejecimiento Saludable, Teagasc Ashtown Food Research Centre (Teagasc), Istanbul Technical University (ITÜ), Centro de Edafologia y Biologia aplicada del Segura (CEBAS - CSIC), Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), Taif University (TU), Partenaires INRAE, Fdn Edmund Mach, IASMA Research and Innovation Centre, University of Trento [Trento], Norwegian Institute of Food,Fisheries and Aquaculture Research (NOFIMA), IT University of Copenhagen (ITU), Institute of Microbiology of the Czech Academy of Sciences [Prague, Czech Republic] (MBU / CAS), Czech Academy of Sciences [Prague] (CAS), Università degli studi di Parma = University of Parma (UNIPR), Department of Nutrition, Exercise and Sports [Copenhagen], Faculty of Science [Copenhagen], University of Copenhagen = Københavns Universitet (UCPH)-University of Copenhagen = Københavns Universitet (UCPH), Quadram Institute Bioscience [Norwich, U.K.] (QIB), Biotechnology and Biological Sciences Research Council (BBSRC), Fondazione Edmund Mach - Edmund Mach Foundation [Italie] (FEM), Department of Food & Drugs, Institute of Food Science, Technology and Nutrition (ICTAN-CSIC), Plateforme Exploration du Métabolisme (PFEM), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-MetaboHUB-Clermont, MetaboHUB-MetaboHUB, and Institute of Animal Reproduction and Food Research of Polish Academy of Sciences

Subjects
Mean squared prediction error, Computational biology, Plant foods, 01 natural sciences, Plant food bioactive compounds, Analytical Chemistry, 0404 agricultural biotechnology, Metabolomics, [CHIM.ANAL]Chemical Sciences/Analytical chemistry, UHPLC, Faculty of Science, Metabolites, liquid chromatography, Settore CHIM/10 - CHIMICA DEGLI ALIMENTI, 2. Zero hunger, Predicted retention time, 010401 analytical chemistry, External validation, Metabolomikk, 04 agricultural and veterinary sciences, General Medicine, NUTRITION&DIETETICS, 040401 food science, 0104 chemical sciences, Data sharing, Untargeted metabolomics, Predicted retention time, metabolomics, plant food bioactive compounds, metabolites, data sharing, PredRet, liquid chromatography, HPLC, UHPLC, HPLC, PredRet, [SDV.AEN]Life Sciences [q-bio]/Food and Nutrition, Retention time, Food Science
Abstract

Prediction of retention times (RTs) is increasingly considered in untargeted metabolomics to complement MS/MS matching for annotation of unidentified peaks. We tested the performance of PredRet (http://predret.org/) to predict RTs for plant food bioactive metabolites in a data sharing initiative containing entry sets of 29–103 compounds (totalling 467 compounds, >30 families) across 24 chromatographic systems (CSs). Between 27 and 667 predictions were obtained with a median prediction error of 0.03–0.76 min and interval width of 0.33–8.78 min. An external validation test of eight CSs showed high prediction accuracy. RT prediction was dependent on shape and type of LC gradient, and number of commonly measured compounds. Our study highlights PredRet’s accuracy and ability to transpose RT data acquired from one CS to another CS. We recommend extensive RT data sharing in PredRet by the community interested in plant food bioactive metabolites to achieve a powerful community-driven open-access tool for metabolomics annotation., The authors acknowledge networking support by the European Cooperation in Science and Technology (COST) Action FA 1403 POSITIVe (Interindividual Variation in Response to Consumption of Plant Food Bioactives and Determinants Involved). Dorrain Low has received the support of EU H2020 in the framework of the FP7-Marie Curie-COFUND People Programme, through award of the AgreenSkills+ Fellowship (grant number 609398) and Nanyang Technological University, Singapore, through award of the Presidential Postdoctoral Fellowship (grant number 001991-00001). The MetaboHUB French infrastructure has supported the INRAE platform (PFEM, MetaboHUB-Clermont) involved in this work (grant number ANR-INBS-0010). Kateřina Valentová and Lucie Petrásková acknowledge financial support from the Czech Science Foundation (grant number 19-00043S). The Faculty of Pharmacy of Lisbon University acknowledges FUNDAÇÃO PARA A CIÊNCIA E TECNOLOGIA and PORTUGAL 2020 for financial support of the Portuguese Mass Spectrometry Network (grant number LISBOA-01-0145-FEDER-402-022125). Kati Hanhineva and Ville Koistinen have received funding from the Academy of Finland (grant numbers 277986 and 312550), Lantmännen Foundation and EU H2020 FP7-Marie Curie-COFUND MoRE Programme (grant number 754412). Biocenter Finland has financially supported the LC-MS metabolomics unit of University of Eastern Finland. Cristina Andres-Lacueva and Raúl González-Domínguez thank CIBERFES and ISCIII projects AC19/00111 and AC19/00096 (co-funded by FEDER Program from EU, “A way to make Europe”), Generalitat de Catalunya’s Agency AGAUR (grant number 2017SGR1546), “Juan de la Cierva” program from MINECO (grant number IJC2019-041867-I) and ICREA Academia award 2018. Francisco A. Tomás-Barberán has received financial support from the Spanish National Research program (grant numbers AGL-2015-73107-EXP/AEI, CSIC 201870E014) and Fundación Seneca Región de Murcia (grant number 19900/GERM/15). Gesine Schmidt acknowledges support through the Norwegian Agriculture and Food Industry Research Funds (grant number 262300). Lars Dragsted and Jan Stanstrup thank the Carlsberg Foundation for a Semper Ardens grant to support this work. László Abrankó acknowledges the Hungarian Academy of Sciences for the János Bolyai Scholarship, and support of the EU and ESF co-financed project of SZIU (grant number EFOP-3.6.3-VEKOP-16-2017-00005). Sonia de Pascual-Teresa thanks the Spanish MINECO for financial support (grant number AGL2016-76832-R). Dilip K. Rai acknowledges Teagasc for the financial support through the Walsh Fellowship (grant number 2016038).

Published
2021

23. Elevated gut microbiome abundance of Christensenellaceae, Porphyromonadaceae and Rikenellaceae is associated with reduced visceral adipose tissue and healthier metabolic profile in Italian elderly

Author

Tavella, Teresa, Rampelli, Simone, Guidarelli, Giulia, Bazzocchi, Alberto, Gasperini, Chiara, Pujos-Guillot, Estelle, Comte, Blandine, Barone, Monica, Biagi, Elena, Candela, Marco, Nicoletti, Claudio, Kadi, Fawzi, Battista, Giuseppe, Salvioli, Stefano, O'Toole, Paul, Franceschi, Claudio, Brigidi, Patrizia, Turroni, Silvia, Santoro, Aurelia, O’Toole, Paul, Université Clermont Auvergne (UCA), Unité de Nutrition Humaine (UNH), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Clermont Auvergne (UCA), Plateforme Exploration du Métabolisme (PFEM), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-MetaboHUB-Clermont, MetaboHUB-MetaboHUB, Tavella, Teresa, Rampelli, Simone, Guidarelli, Giulia, Bazzocchi, Alberto, Gasperini, Chiara, Pujos-Guillot, Estelle, Comte, Blandine, Barone, Monica, Biagi, Elena, Candela, Marco, Nicoletti, Claudio, Kadi, Fawzi, Battista, Giuseppe, Salvioli, Stefano, O'Toole, Paul W, Franceschi, Claudio, Brigidi, Patrizia, Turroni, Silvia, and Santoro, Aurelia

Subjects
0301 basic medicine, Microbiology (medical), Rikenellaceae, media_common.quotation_subject, [SDV]Life Sciences [q-bio], Porphyromonadaceae, Physiology, Adipose tissue, RC799-869, Ageing, microbiota, Gut flora, Microbiology, 03 medical and health sciences, 0302 clinical medicine, Metabolome, visceral adipose tissue, media_common, 2. Zero hunger, biology, Microbiota, aging, Gastroenterology, Longevity, Diseases of the digestive system. Gastroenterology, biology.organism_classification, 3. Good health, 030104 developmental biology, Infectious Diseases, Ageing, Cohort, 030211 gastroenterology & hepatology, inflammaging, diet, serum metabolome
Abstract

International audience; Aging is accompanied by physiological changes affecting body composition and functionality, including accumulation of fat mass at the expense of muscle mass, with effects upon morbidity and quality of life. The gut microbiome has recently emerged as a key environmental modifier of human health that can modulate healthy aging and possibly longevity. However, its associations with adiposity in old age are still poorly understood. Here we profiled the gut microbiota in a well-characterized cohort of 201 Italian elderly subjects from the NU-AGE study, by 16S rRNA amplicon sequencing. We then tested for association with body composition from dual-energy X-ray absorptiometry (DXA), with a focus on visceral and subcutaneous adipose tissue. Dietary patterns, serum metabolome and other health-related parameters were also assessed. This study identified distinct compositional structures of the elderly gut microbiota associated with DXA parameters, diet, metabolic profiles and cardio-metabolic risk factors.

Published
2021

24. Deep learning in systems medicine

Author

Wang, Haiying, Pujos-Guillot, Estelle, Comte, Blandine, de Miranda, Joao Luis, Spiwok, Vojtech, Chorbev, Ivan, Castiglione, Filippo, Tieri, Paolo, Watterson, Steven, McAllister, Roisin, de Melo Malaquias, Tiago, Zanin, Massimiliano, Rai, Taranjit Singh, Zheng, Huiru, University of Connecticut (UCONN), Plateforme d'Exploration du Métabolisme, MetaboHUB, Unité de Nutrition Humaine (UNH), Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Department of Biochemistry and Microbiology, Institute of Chemical Technology [Prague] (ICT), Politecnico di Milano [Milan] (POLIMI), IAC Institute for Applied Computing, University of Ulster, European Commission, European Cooperation in Science and Technology, Ministry of Education, Youth and Sports (Czech Republic), Fundação para a Ciência e a Tecnologia (Portugal), Ministerio de Ciencia, Innovación y Universidades (España), Agencia Estatal de Investigación (España), Public Health Agency (Northern Ireland), Western Health and Social Care Trust (Northern Ireland), Plateforme Exploration du Métabolisme (PFEM), MetaboHUB-Clermont, and MetaboHUB-MetaboHUB-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Clermont Auvergne (UCA)

Subjects
Proteomics, 0301 basic medicine, Systems Analysis, AcademicSubjects/SCI01060, Computer science, computer.software_genre, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], 0302 clinical medicine, deep learning (DL), biomarker discovery, Electronic Health Records, Disease, Precision Medicine, Interpretability, Genomics, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], 3. Good health, Systems medicine, Deep learning (DL), Data integration, Biomarker discovery, Algorithms, Information Systems, systems medicine (SM), Systems medicine (SM), disease classification, 03 medical and health sciences, Deep Learning, Humans, Metabolomics, Relevance (information retrieval), Set (psychology), Molecular Biology, data integration, Method Review, business.industry, Deep learning, Precision medicine, Data science, Disease classification, 030104 developmental biology, Key (cryptography), Neural Networks, Computer, Artificial intelligence, Transcriptome, business, computer, Biomarkers, 030217 neurology & neurosurgery
Abstract

Systems medicine (SM) has emerged as a powerful tool for studying the human body at the systems level with the aim of improving our understanding, prevention and treatment of complex diseases. Being able to automatically extract relevant features needed for a given task from high-dimensional, heterogeneous data, deep learning (DL) holds great promise in this endeavour. This review paper addresses the main developments of DL algorithms and a set of general topics where DL is decisive, namely, within the SM landscape. It discusses how DL can be applied to SM with an emphasis on the applications to predictive, preventive and precision medicine. Several key challenges have been highlighted including delivering clinical impact and improving interpretability. We used some prototypical examples to highlight the relevance and significance of the adoption of DL in SM, one of them is involving the creation of a model for personalized Parkinson’s disease. The review offers valuable insights and informs the research in DL and SM., This publication is based upon work from COST Action Open Multiscale Systems Medicine (OpenMultiMed, CA15120), supported by COST (European Cooperation in Science and Technology). COST is funded by the Horizon 2020 Framework Programme of the European Union. HZ and HYW are also supported by the MetaPlat(690998), SenseCare(690862) and STOP(823978) projects funded by H2020 RISE programme. FC and PT acknowledge the support of H2020 project iPC “individualized Paediatric Cure” (826121). Participation of V.S. in OpenMultiMed is supported by the Czech Ministry of Education, Youth and Sports (project LTC18074). JLM. thanks Escola Superior de Tecnologia e Gestão, Instituto Politécnico de Portalegre (ESTG/IPP); and Centro de Recursos Naturais e Ambiente, Instituto Superior Técnico (CERENA/IST) within the support of FCT-Fundação para a Ciência e a Tecnologia through the strategic project FCT-UIDB/04028/2020. MZ acknowledges the Spanish State Research Agency, through the Severo Ochoa and María de Maeztu Program for Centers and Units of Excellence in R&D (MDM-2017-0711) and the funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (851255). The Northern Ireland Centre for Stratified Medicine has been financed by a grant awarded to AJ Bjourson under the European Union Regional Development Fund (ERDF) EU Sustainable Competitiveness Programme for Northern Ireland & the Northern Ireland Public Health Agency (HSC R&D). TSR also acknowledges funding from PHA R&D Division and the Western Health & Social Care.

Published
2021
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25. Targeting Mitochondrial Complex I Overcomes Chemoresistance in High OXPHOS Pancreatic Cancer

Author

Fabrice Tranchida, Odile Gayet, Alice Carrier, Gabriela Reyes-Castellanos, Laurie Cormareche, Tristan Gicquel, Juan L. Iovanna, Samir Dou, Nelson Dusetti, Eddy Pasquier, Laurence Borge, Binta Diémé, Laetitia Shintu, Julie Garcia, Rawand Masoud, Abdessamad El Kaoutari, Nadine Abdel Hadi, Sophie Lac, Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Institut des Sciences Moléculaires de Marseille (ISM2), Aix Marseille Université (AMU)-École Centrale de Marseille (ECM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Plateforme Exploration du Métabolisme (PFEM), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-MetaboHUB-Clermont, MetaboHUB-MetaboHUB, is work was supported by InstitutNational de la Sante ́et de la Recherche Me ́dicale, Centre National de la Re-cherche Scientifique, Institut National Du Cancer (INCa), Fondation ARCpour la Recherche sur le Cancer (PJA 20151203544), La Ligue Nationalecontre le Cancer (LNCC), DGOS (labelization SIRIC), Fondation Amidex, andFondation de France. This work also benefited from grants from Cancerop^oleProvence-Alpes-C^ote d’Azur (PACA) and Fe ́de ́ration GEFLUC for the acquisi-tion of the Seahorse XFe24 device., Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Aix Marseille Université (AMU), PFEM, MetaboHUB, CARRIER, Alice, Plateforme Exploration du Métabolisme-MetaboHUB (PFEM-MetaboHUB), and Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)

Subjects
Male, endocrine system diseases, medicine.medical_treatment, [SDV]Life Sciences [q-bio], pancreatic cancer, cancer metabolism, Mitochondrion, Phenformin, Deoxycytidine, Oxidative Phosphorylation, chemistry.chemical_compound, Mice, 0302 clinical medicine, 0303 health sciences, personalized medicine, OXPHOS, 3. Good health, Mitochondria, [SDV] Life Sciences [q-bio], 030220 oncology & carcinogenesis, PC-3 Cells, Female, Mitochondrial Complex I, medicine.drug, Carcinoma, Pancreatic Ductal, energetic metabolism, Cell Respiration, Mice, Nude, Oxidative phosphorylation, General Biochemistry, Genetics and Molecular Biology, Article, 03 medical and health sciences, Pancreatic cancer, Cell Line, Tumor, medicine, Animals, Humans, therapeutic strategy, 030304 developmental biology, Cell Proliferation, Chemotherapy, Electron Transport Complex I, business.industry, metabolic heterogeneity, medicine.disease, mitochondrial Complex I, Xenograft Model Antitumor Assays, Gemcitabine, digestive system diseases, Mice, Inbred C57BL, Pancreatic Neoplasms, chemistry, Drug Resistance, Neoplasm, Cancer research, Personalized medicine, business
Abstract

Summary Mitochondrial respiration (oxidative phosphorylation, OXPHOS) is an emerging target in currently refractory cancers such as pancreatic ductal adenocarcinoma (PDAC). However, the variability of energetic metabolic adaptations between PDAC patients has not been assessed in functional investigations. In this work, we demonstrate that OXPHOS rates are highly heterogeneous between patient tumors, and that high OXPHOS tumors are enriched in mitochondrial respiratory complex I at protein and mRNA levels. Therefore, we treated PDAC cells with phenformin (complex I inhibitor) in combination with standard chemotherapy (gemcitabine), showing that this treatment is synergistic specifically in high OXPHOS cells. Furthermore, phenformin cooperates with gemcitabine in high OXPHOS tumors in two orthotopic mouse models (xenografts and syngeneic allografts). In conclusion, this work proposes a strategy to identify PDAC patients likely to respond to the targeting of mitochondrial energetic metabolism in combination with chemotherapy, and that phenformin should be clinically tested in appropriate PDAC patient subpopulations., Graphical Abstract, Highlights Pancreatic ductal adenocarcinoma (PDAC) displays OXPHOS heterogeneity High OXPHOS PDAC tumors are enriched in mitochondrial respiratory complex I Complex I inhibitor phenformin synergizes with chemotherapy in high OXPHOS cells Phenformin cooperates with gemcitabine antitumoral activity in high OXPHOS tumors, Masoud et al. reveal that pancreatic cancer patients can be stratified according to their mitochondrial oxidative phosphorylation (OXPHOS) activity and to the expression of mitochondrial respiratory complex I. Targeting mitochondrial respiration with the complex I inhibitor phenformin cooperates with gemcitabine to eradicate high OXPHOS pancreatic cancer cells.

Published
2020

26. Natural Variation of Hazelnut Allergenicity: Is There Any Potential for Selecting Hypoallergenic Varieties?

Author

Gilberto Igrejas, Sandra Cabo, Ana Paula Silva, Berta Gonçalves, Mélanie Hillion, Michel Hébraud, Joana Costa, Isabel Mafra, Miguel Ribeiro, Universidade de Trás-os-Montes e Alto Douro (UTAD), Universidade do Trás-os-Montes e Alto Douro, LAQV-REQUIMTE, Universidade NOVA de Lisboa, Departamento de Quimica (REQUIMTE), Universidade de Lisboa (ULISBOA)-Centro de Quimica Fina e Biotecnologia, Centro de Investigação e de Tecnologias Agro-Ambientais e Biológicas (CITAB), University of Trás-os-Montes and Alto Douro [Portugal] (UTAD), INRAE, Plateforme d’Exploration du Métabolisme, Composante Protéomique (PFEMcp), 63122 Saint-Genès Champanelle, Microbiologie Environnement Digestif Santé (MEDIS), Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Associate Laboratory for Green Chemistry-LAQV - Fundacao para a Ciencia e Tecnologia (FCT) UIDB 50006/2020national project AlleRiskAssess PTDC/BAA-AGR/31720/2017NORTE-01-0145-FEDER-00001national project HazelOmics (LAQV-REQUIMTE) INTERACT project-'Integrative Research in Environment, Agro-Chains and Technology' NORTE-01-0145-FEDER-000017European Union (EU), Universidade Nova de Lisboa = NOVA University Lisbon (NOVA), Universidade de Lisboa = University of Lisbon (ULISBOA)-Centro de Quimica Fina e Biotecnologia, Plateforme Exploration du Métabolisme (PFEM), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-MetaboHUB-Clermont, and MetaboHUB-MetaboHUB

Subjects
0301 basic medicine, Male, Proteomics, medicine.medical_treatment, 0302 clinical medicine, immunoblot, Exclusion diet, Food science, Desensitization (medicine), Plant Proteins, 2. Zero hunger, Nutrition and Dietetics, genetic diversity, respiratory system, Middle Aged, [SDV.MP]Life Sciences [q-bio]/Microbiology and Parasitology, nutrition, Hazelnut allergy, Child, Preschool, proteogenomics, Female, Nut Hypersensitivity, lcsh:Nutrition. Foods and food supply, Food Hypersensitivity, Adult, Adolescent, lcsh:TX341-641, Biology, Natural variation, hazelnut-allergic patients’ sera, Article, 03 medical and health sciences, Young Adult, Corylus, Food allergy, medicine, Humans, hazelnut allergy, Aged, Genetic diversity, Genetic Variation, Hypoallergenic, Allergens, Antigens, Plant, Immunoglobulin E, medicine.disease, hazelnut-allergic patients' sera, respiratory tract diseases, 030104 developmental biology, Human nutrition, 030228 respiratory system, Food Science
Abstract

International audience; Hazelnuts (Corylus avellanaL.) have an important role in human nutrition and health. However, they are a common cause of food allergy. Due to hazelnut varietal diversity, variety-dependent differences in the IgE-binding properties may be suspected, which could allow therapeutic strategies based on the use of hypoallergenic varieties to induce desensitization. In a proteogenomic approach, we aimed to evaluate the allergenic potential of a genetically diverse set of hazelnuts (n = 13 varieties). Minor differences were found at the level of genes encoding important allergens, namely Cor a 8, Cor a 9, and Cor a 14. Nevertheless, IgE-reactivity was similar for all varieties using sera from seven allergic individuals. The predominant IgE-reactive proteins were Cor a 9 (100%) and Cor a 1.04 (60%), with the former being the most frequently identified by a two-dimensional gel electrophoresis (2-DE)-based proteomic approach. Therefore, it seems that the conventional exclusion diet will hold its ground for the time being.

Published
2020

27. Next-Generation Sequencing and MALDI Mass Spectrometry in the Study of Multiresistant Processed Meat Vancomycin-Resistant Enterococci (VRE)

Author

Gilberto Igrejas, Richard Bonnet, Christophe Chambon, Michel Hébraud, Patrícia Poeta, Racha Beyrouthy, Laetitia Théron, Didier Viala, Telma de Sousa, Soraia Oliveira, Manuela Caniça, Carolina Sabença, University of Trás-os-Montes and Alto Douro [Portugal] (UTAD), Laboratorio Associado Para a Quimica Verde (LAQV/REQUIMTE), Universidade Nova de Lisboa = NOVA University Lisbon (NOVA), Unité Mixte de Recherche sur les Herbivores - UMR 1213 (UMRH), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Qualité des Produits Animaux (QuaPA), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Plateforme Exploration du Métabolisme (PFEM), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-MetaboHUB-Clermont, MetaboHUB-MetaboHUB, Microbiologie Environnement Digestif Santé (MEDIS), Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centre National de Référence de la Résistance aux Antibiotiques (CNR), Centre Hospitalier Régional Universitaire de Besançon (CHRU Besançon), Microbes, Intestin, Inflammation et Susceptibilité de l'Hôte (M2iSH), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre de Recherche en Nutrition Humaine d'Auvergne (CRNH d'Auvergne)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), National Reference Laboratory of Antibiotic Resistances and Healthcare Associated Infections (NRL-AMR-HAI), Department of Infectious Diseases, Instituto Nacional de Saùde Dr Ricardo Jorge [Portugal] (INSA), Faculty of Science Oporto University, Centre for the Studies of Animal Science, Institute of Agrarian and Agri-Food Sciences and Technologies, Oporto University, 4051-401 Oporto, 'Espectrometria de massa e sequenciacao aplicadas a microbiologia clinica moderna: pesquisa e identificacao de biomarcadores em especies bacterianas multiresistentes' (Programa de Accoes Universitarias Integradas Luso-Francesas) TC-14/2017Associate Laboratory for Green Chemistry, LAQV - FCT/MCTES UID/QUI/50006/2020CT/MCTES UIDB/00211/2020, LAQV@REQUIMTE, Plateforme Exploration du Métabolisme-MetaboHUB (PFEM-MetaboHUB), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP), ROSSI, Sabine, VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and INRAE, Plateforme d’Exploration du Métabolisme, Composante Protéomique (PFEMcp), 63122 Saint-Genès Champanelle

Subjects
0301 basic medicine, antibiotic resistance, Tetracycline, Antibiotic resistance, [SDV]Life Sciences [q-bio], 030106 microbiology, Processed meat, General Biochemistry, Genetics and Molecular Biology, Article, Microbiology, 03 medical and health sciences, Immunology and Microbiology(all), medicine, MALDI-TOF MS, lcsh:QH301-705.5, Enterococcus spp, processed meat, General Immunology and Microbiology, biology, Agricultural and Biological Sciences(all), Resistência aos Antimicrobianos, Teicoplanin, Biochemistry, Genetics and Molecular Biology(all), Kanamycin, biochemical phenomena, metabolism, and nutrition, biology.organism_classification, 3. Good health, [SDV] Life Sciences [q-bio], 030104 developmental biology, Enterococcus, lcsh:Biology (General), Streptomycin, Next-generation sequencing, Gentamicin, next-generation sequencing, General Agricultural and Biological Sciences, medicine.drug, Enterococcus faecium
Abstract

Vancomycin-resistant enterococci (VRE), due to their intrinsic resistance to various commonly used antibiotics and their malleable genome, make the treatment of infections caused by these bacteria less effective. The aims of this work were to characterize isolates of Enterococcus spp. that originated from processed meat, through phenotypic and genotypic techniques, as well as to detect putative antibiotic resistance biomarkers. The 19 VRE identified had high resistance to teicoplanin (89%), tetracycline (94%), and erythromycin (84%) and a low resistance to kanamycin (11%), gentamicin (11%), and streptomycin (5%). Based on a Next-Generation Sequencing NGS technique, most isolates were vanA-positive. The most prevalent resistance genes detected were erm(B) and aac(6')-Ii, conferring resistance to the classes of macrolides and aminoglycosides, respectively. MALDI-TOF mass spectrometry (MS) analysis detected an exclusive peak of the Enterococcus genus at m/z (mass-to-charge-ratio) 4428 &plusmn, 3, and a peak at m/z 6048 &plusmn, 1 allowed us to distinguish Enterococcus faecium from the other species. Several statistically significant protein masses associated with resistance were detected, such as peaks at m/z 6358.27 and m/z 13237.3 in ciprofloxacin resistance isolates. These results reinforce the relevance of the combined and complementary NGS and MALDI-TOF MS techniques for bacterial characterization.

Published
2020
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28. Diet-Related Metabolomic Signature of Long-Term Breast Cancer Risk Using Penalized Regression: An Exploratory Study in the SU.VI.MAX Cohort

Author

Paule Latino-Martel, Pietro Ferrari, Céline Dalle, Emmanuelle Kesse-Guyot, Mathilde Touvier, Pierre Micheau, Adrien Rossary, Sophie Lefèvre-Arbogast, Pilar Galan, Cécilia Samieri, Mélanie Deschasaux, Delphine Centeno, Lucie Lécuyer, Bernard Lyan, Marie-Paule Vasson, Valentin Partula, Marie Lagree, Bernard Srour, Nada Assi, Serge Hercberg, Mélanie Pétéra, Nathalie Druesne-Pecollo, Vivian Viallon, Aicha Demidem, Stéphanie Durand, Claudine Manach, Estelle Pujos-Guillot, Equipe 3: EREN- Equipe de Recherche en Epidémiologie Nutritionnelle (CRESS - U1153), Université Sorbonne Paris Nord-Centre de Recherche Épidémiologie et Statistique Sorbonne Paris Cité (CRESS (U1153 / UMR_A_1125 / UMR_S_1153)), Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Paris (UP)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Paris (UP)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Unité de Nutrition Humaine (UNH), Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Plateforme d'Exploration du Métabolisme, MetaboHUB, Institut de Chimie de Clermont-Ferrand (ICCF), SIGMA Clermont (SIGMA Clermont)-Institut de Chimie du CNRS (INC)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS), Hôpital Avicenne [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Centre de Recherche en Cancérologie de Lyon (UNICANCER/CRCL), Centre Léon Bérard [Lyon]-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Centre Jean Perrin [Clermont-Ferrand] (UNICANCER/CJP), UNICANCER, ANR-11-INBS-0010,METABOHUB,Développement d'une infrastructure française distribuée pour la métabolomique dédiée à l'innovation(2011), Centre de Recherche Épidémiologie et Statistique Sorbonne Paris Cité (CRESS (U1153 / UMR_A_1125 / UMR_S_1153)), Institut National de la Recherche Agronomique (INRA)-Université Paris Diderot - Paris 7 (UPD7)-Université Paris Descartes - Paris 5 (UPD5)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM), Unité de Nutrition Humaine - Clermont Auvergne (UNH), Institut National de la Recherche Agronomique (INRA)-Université Clermont Auvergne (UCA), UMR 1219, Centre de Recherche Inserm-Université de Bordeaux, Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Bordeaux, Institut de Chimie, Université Clermont Auvergne (UCA), International Agency for Research on Cancer, Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Plateforme Exploration du Métabolisme (PFEM), MetaboHUB-Clermont, MetaboHUB-MetaboHUB-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Clermont Auvergne (UCA), and Université Paris Diderot - Paris 7 (UPD7)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de la Recherche Agronomique (INRA)-Université Paris Descartes - Paris 5 (UPD5)-Université Sorbonne Paris Cité (USPC)

Subjects
Adult, 0301 basic medicine, Oncology, medicine.medical_specialty, Epidemiology, Metabolite, education, Breast Neoplasms, [SDV.CAN]Life Sciences [q-bio]/Cancer, Risk Assessment, Mass Spectrometry, LEHA, 03 medical and health sciences, chemistry.chemical_compound, 0302 clinical medicine, Metabolomics, Breast cancer, Risk Factors, Internal medicine, Biomarkers, Tumor, medicine, Humans, Steroid sulfate, Risk factor, Randomized Controlled Trials as Topic, Penalized regression, business.industry, Feeding Behavior, Middle Aged, medicine.disease, 3. Good health, Logistic Models, 030104 developmental biology, Clinical Trials, Phase III as Topic, chemistry, Case-Control Studies, 030220 oncology & carcinogenesis, Piperine, Cohort, Female, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, business, [SDV.AEN]Life Sciences [q-bio]/Food and Nutrition
Abstract

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.

Published
2020

29. Multiblock PLS-DA on fecal and plasma visible-near-infrared spectra for discriminating young bulls according to their efficiency. Preliminary results

Author

Andueza, Donato, Picard, Fabienne, Constant, Isabelle, Fossaert, Clément, De La Torre Capitan, Anne, Renand, Gilles, Pourrat, Juliane, Brandolini-Bunlon, Marion, Unité Mixte de Recherches sur les Herbivores - UMR 1213 (UMRH), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Institut National de la Recherche Agronomique (INRA), Institut de l'Elevage, Génétique Animale et Biologie Intégrative (GABI), AgroParisTech-Institut National de la Recherche Agronomique (INRA), Unité de Nutrition Humaine - Clermont Auvergne (UNH), Institut National de la Recherche Agronomique (INRA)-Université Clermont Auvergne (UCA), Unité Mixte de Recherche sur les Herbivores - UMR 1213 (UMRH), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Université Paris-Saclay-AgroParisTech-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Unité de Nutrition Humaine (UNH), Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut de l'élevage (IDELE), AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Plateforme Exploration du Métabolisme (PFEM), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-MetaboHUB-Clermont, and MetaboHUB-MetaboHUB

Subjects
chemometric treatments, [SDV.OT]Life Sciences [q-bio]/Other [q-bio.OT], classification, NIRS, feed conversion efficiency, bovine animals, Autre (Sciences du Vivant)
Abstract

Multiblock PLS-DA on fecal and plasma visible-near-infrared spectra for discriminating young bulls according to their efficiency. Preliminary results. Conférence Chimiométrie 2020

Published
2020

30. Metabolomic and Lipidomic Signatures of Metabolic Syndrome and its Physiological Components in Adults: A Systematic Review

Author

Blandine Comte, Pierrette Gaudreau, José A. Morais, Daniela Ziegler, Stéphanie Monnerie, Estelle Pujos-Guillot, Unité de Nutrition Humaine (UNH), Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centre Hospitalier Universitaire de Montréal, Université de Montréal (UdeM), Département de Gériatrie, McGill University = Université McGill [Montréal, Canada], Plateforme d’Exploration du Métabolisme, Institut National de la Recherche Agronomique (INRA), Centre de Recherche du Centre Hospitalier de l’Université de Montréal (CR CHUM), Centre Hospitalier de l'Université de Montréal (CHUM), Université de Montréal (UdeM)-Université de Montréal (UdeM), Département de médecine, Centre Léon Bérard [Lyon], Plateforme Exploration du Métabolisme (PFEM), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-MetaboHUB-Clermont, MetaboHUB-MetaboHUB, Unité de Nutrition Humaine - Clermont Auvergne (UNH), Institut National de la Recherche Agronomique (INRA)-Université Clermont Auvergne (UCA), Université McGill [Montréal], and Centre de Recherche du CHUM

Subjects
Adult, Male, Risk, 0301 basic medicine, [SDV.OT]Life Sciences [q-bio]/Other [q-bio.OT], Population, MEDLINE, lcsh:Medicine, 030209 endocrinology & metabolism, Type 2 diabetes, Computational biology, Article, 03 medical and health sciences, 0302 clinical medicine, Metabolomics, Lipidomics, Prevalence, Humans, Medicine, lcsh:Science, education, Aged, Glycemic, Metabolic Syndrome, education.field_of_study, Multidisciplinary, business.industry, Incidence, lcsh:R, Middle Aged, Lipid Metabolism, medicine.disease, Phenotype, 030104 developmental biology, Diabetes Mellitus, Type 2, Homogeneous, Female, lcsh:Q, Metabolic syndrome, business, Biomarkers
Abstract

The aim of this work was to conduct a systematic review of human studies on metabolite/lipid biomarkers of metabolic syndrome (MetS) and its components, and provide recommendations for future studies. The search was performed in MEDLINE, EMBASE, EMB Review, CINHAL Complete, PubMed, and on grey literature, for population studies identifying MetS biomarkers from metabolomics/lipidomics. Extracted data included population, design, number of subjects, sex/gender, clinical characteristics and main outcome. Data were collected regarding biological samples, analytical methods, and statistics. Metabolites were compiled by biochemical families including listings of their significant modulations. Finally, results from the different studies were compared. The search yielded 31 eligible studies (2005–2019). A first category of articles identified prevalent and incident MetS biomarkers using mainly targeted metabolomics. Even though the population characteristics were quite homogeneous, results were difficult to compare in terms of modulated metabolites because of the lack of methodological standardization. A second category, focusing on MetS components, allowed comparing more than 300 metabolites, mainly associated with the glycemic component. Finally, this review included also publications studying type 2 diabetes as a whole set of metabolic risks, raising the interest of reporting metabolomics/lipidomics signatures to reflect the metabolic phenotypic spectrum in systems approaches.

Published
2020

31. Create, run, share, publish, and reference your LC–MS, FIA–MS, GC–MS, and NMR data analysis workflows with the Workflow4Metabolomics 3.0 Galaxy online infrastructure for metabolomics

Author

Cécile Canlet, Franck Giacomoni, Sophie Goulitquer, Jean-François Martin, Patrick Tardivel, Rémi Servien, Etienne A. Thévenot, Alexis Delabrière, Marie Tremblay-Franco, Yann Guitton, Mélanie Pétéra, Gildas Le Corguillé, Christophe Duperier, Pierrick Roger-Mele, Christophe Caron, Misharl Monsoor, Laboratoire d'étude des Résidus et Contaminants dans les Aliments (LABERCA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire, Agroalimentaire et de l'alimentation Nantes-Atlantique (ONIRIS), Institut de Recherche en Génie Civil et Mécanique (GeM), Université de Nantes - Faculté des Sciences et des Techniques, Université de Nantes (UN)-Université de Nantes (UN)-École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS), ToxAlim (ToxAlim), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Ecole d'Ingénieurs de Purpan (INPT - EI Purpan), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Recherche Agronomique (INRA), ABiMS - Informatique et bioinformatique = Analysis and Bioinformatics for Marine Science (FR2424), Station biologique de Roscoff (SBR), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Unité de Nutrition Humaine (UNH), Institut National de la Recherche Agronomique (INRA)-Université d'Auvergne - Clermont-Ferrand I (UdA)-Clermont Université, Plateforme d'Exploration du Métbolisme, MetaboHUB, Laboratoire d'analyse des données et d'intelligence des systèmes (LADIS), Département Métrologie Instrumentation & Information (DM2I), Laboratoire d'Intégration des Systèmes et des Technologies (LIST), Université Paris-Saclay-Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Laboratoire d'Intégration des Systèmes et des Technologies (LIST), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Génétique, génomique fonctionnelle et biotechnologies (UMR 1078) (GGB), EFS-Université de Brest (UBO)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Brestois Santé Agro Matière (IBSAM), Université de Brest (UBO), Laboratoire Universitaire de Biodiversité et Ecologie Microbienne (LUBEM), Ingenum, Institut National de la Recherche Agronomique (INRA), ANR-11-INBS-0013/11-INBS-0013,ReNaBi-IFB,Institut français de bioinformatique(2011), ANR-11-INBS-0010/11-INBS-0010,METABOHUB,Développement d’une infrastructure française distribuée pour la métabolomique dédiée à l’innovation(2011), ANR-10-BTBR-04-01/10-BTBR-0004,IDEALG,IDEALG(2010), Institut National de la Recherche Agronomique (INRA)-École nationale vétérinaire, agroalimentaire et de l'alimentation Nantes-Atlantique (ONIRIS), Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST), MetaToul AXIOM (E20), Institut National de la Recherche Agronomique (INRA)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Ecole d'Ingénieurs de Purpan (INP - PURPAN), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National de la Recherche Agronomique (INRA)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-MetaboHUB-MetaToul, MetaboHUB-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-MetaboHUB-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), ABiMS - Informatique et bioinformatique = Analysis and Bioinformatics for Marine Science (ABIMS), Fédération de recherche de Roscoff (FR2424), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Station biologique de Roscoff (SBR), Plateforme Exploration du Métabolisme (PFEM), MetaboHUB-Clermont, MetaboHUB-MetaboHUB-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Clermont Auvergne (UCA), Institut National de la Recherche Agronomique (INRA)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020]), Laboratoire d'Intégration des Systèmes et des Technologies (LIST (CEA)), Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Laboratoire d'Intégration des Systèmes et des Technologies (LIST (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Université de Toulouse (UT)-Université de Toulouse (UT), Laboratoire Sciences des Données et de la Décision (LS2D), French Institute of Bioinformatics (IFB) ANR-11-INBS-0013, French Infrastructure for Metabolomics and Fluxomics (MetaboHUB) ANR-11-INBS-0010, IDEALG project ANR-10-BTBR-04, ANR-11-INBS-0013,IFB (ex Renabi-IFB),Institut français de bioinformatique(2011), ANR-11-INBS-0010,METABOHUB,Développement d'une infrastructure française distribuée pour la métabolomique dédiée à l'innovation(2011), ANR-10-BTBR-0004,IDEALG,Biotechnologies pour la valorisation des macroalgues(2010), Analyse de Xénobiotiques, Identification, Métabolisme (E20 Metatoul-AXIOM), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Ecole d'Ingénieurs de Purpan (INPT - EI Purpan), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Recherche Agronomique (INRA)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-MetaToul-MetaboHUB, Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Laboratoire d'Intégration des Systèmes et des Technologies (LIST), Institut Brestois Santé Agro Matière (IBSAM), and Université de Brest (UBO)-Université de Brest (UBO)-EFS-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
MASS SPECTROMETRY, 0301 basic medicine, Web server, Magnetic Resonance Spectroscopy, Computer science, Data analysis, CHROMATOGRAPHY, spectrum analysis, Bioinformatics, computer.software_genre, Quantitative Biology - Quantitative Methods, Biochemistry, Workflow, 03 medical and health sciences, Annotation, Resource (project management), [SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN], Digital Object Identifier, Animals, Humans, Metabolomics, [INFO.INFO-DL]Computer Science [cs]/Digital Libraries [cs.DL], Preprocessor, signal processing, Quantitative Methods (q-bio.QM), Electronic Data Processing, ADULT URINARY METABOLOME, IDENTIFICATION, BIOINFORMATICS, MASS-SPECTROMETRY, Cell Biology, COMPUTATIONAL METABOLOMICS, Data science, GENOME, Galaxy, Identification (information), 030104 developmental biology, FOS: Biological sciences, WEB SERVER, E-infrastructure, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], computer, Software, REPOSITORY, STANDARDS
Abstract

Metabolomics is a key approach in modern functional genomics and systems biology. Due to the complexity of metabolomics data, the variety of experimental designs, and the variety of existing bioinformatics tools, providing experimenters with a simple and efficient resource to conduct comprehensive and rigorous analysis of their data is of utmost importance. In 2014, we launched the Workflow4Metabolomics (W4M, http://workflow4metabolomics.org) online infrastructure for metabolomics built on the Galaxy environment, which offers user-friendly features to build and run data analysis workflows including preprocessing, statistical analysis, and annotation steps. Here we present the new W4M 3.0 release, which contains twice as many tools as the first version, and provides two features which are, to our knowledge, unique among online resources. First, data from the four major metabolomics technologies (i.e., LC-MS, FIA-MS, GC-MS, and NMR) can be analyzed on a single platform. By using three studies in human physiology, alga evolution, and animal toxicology, we demonstrate how the 40 available tools can be easily combined to address biological issues. Second, the full analysis (including the workflow, the parameter values, the input data and output results) can be referenced with a permanent digital object identifier (DOI). Publication of data analyses is of major importance for robust and reproducible science. Furthermore, the publicly shared workflows are of high-value for e-learning and training. The Workflow4Metabolomics 3.0 e-infrastructure thus not only offers a unique online environment for analysis of data from the main metabolomics technologies, but it is also the first reference repository for metabolomics workflows., The International Journal of Biochemistry \& Cell Biology, Elsevier, 2017

Published
2017

32. Identification of Pre-frailty Sub-Phenotypes in Elderly Using Metabolomics

Author

Pujos-Guillot, Estelle, Pétéra, Mélanie, Jacquemin, Jérémie, Centeno, Delphine, Lyan, Bernard, Montoliu, Ivan, Madej, Dawid, Pietruszka, Barbara, Fabbri, Cristina, Santoro, Aurelia, Brzozowska, Anna, Franceschi, Claudio, Comte, Blandine, Unité de Nutrition Humaine - Clermont Auvergne (UNH), Institut National de la Recherche Agronomique (INRA)-Université Clermont Auvergne (UCA), Plateforme d'Exploration du Métabolisme, Institut National de la Recherche Agronomique (INRA), Nestlé Institute of Health Sciences SA [Lausanne, Switzerland], Human Nutrition, Szkoła Główna Gospodarstwa Wiejskiego w Warszawie, Warsaw University of Life Sciences (SGGW), Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Centro Interdipartimentale « L. Galvani» (CIG), Institute of Neurological Sciences of Bologna IRCCS, European Union's Seventh Framework Program 266486, MetaboHUB French infrastructure ANR-INBS-0010, Unité de Nutrition Humaine (UNH), Institut National de la Recherche Agronomique (INRA)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020]), European Project: 266486,EC:FP7:KBBE,FP7-KBBE-2010-4,NU-AGE(2011), Plateforme Exploration du Métabolisme (PFEM), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-MetaboHUB-Clermont, MetaboHUB-MetaboHUB, Alma Mater Studiorum Università di Bologna [Bologna] (UNIBO), Pujos-Guillot, Estelle, Pétéra, Mélanie, Jacquemin, Jérémie, Centeno, Delphine, Lyan, Bernard, Montoliu, Ivan, Madej, Dawid, Pietruszka, Barbara, Fabbri, Cristina, Santoro, Aurelia, Brzozowska, Anna, Franceschi, Claudio, and Comte, Blandine

Subjects
untargeted metabolomics, pre-frailty, sub-phenotypes, Physiology, gender differences, [CHIM.ANAL]Chemical Sciences/Analytical chemistry, gender difference, [SDV.MHEP.PHY]Life Sciences [q-bio]/Human health and pathology/Tissues and Organs [q-bio.TO], biomarker, biomarkers, sub-phenotype, elderly, Original Research
Abstract

Aging is a dynamic process depending on intrinsic and extrinsic factors and its evolution is a continuum of transitions, involving multifaceted processes at multiple levels. It is recognized that frailty and sarcopenia are shared by the major age-related diseases thus contributing to elderly morbidity and mortality. Pre-frailty is still not well understood but it has been associated with global imbalance in several physiological systems, including inflammation, and in nutrition. Due to the complex phenotypes and underlying pathophysiology, the need for robust and multidimensional biomarkers is essential to move toward more personalized care. The objective of the present study was to better characterize the complexity of pre-frailty phenotype using untargeted metabolomics, in order to identify specific biomarkers, and study their stability over time. The approach was based on the NU-AGE project (clinicaltrials.gov , NCT01754012) that regrouped 1,250 free-living elderly people (65-79 y.o., men and women), free of major diseases, recruited within five European centers. Half of the volunteers were randomly assigned to an intervention group (1-year Mediterranean type diet). Presence of frailty was assessed by the criteria proposed by Fried et al. (2001). In this study, a sub-cohort consisting in 212 subjects (pre-frail and non-frail) from the Italian and Polish centers were selected for untargeted serum metabolomics at T0 (baseline) and T1 (follow-up). Univariate statistical analyses were performed to identify discriminant metabolites regarding pre-frailty status. Predictive models were then built using linear logistic regression and ROC curve analyses were used to evaluate multivariate models. Metabolomics enabled to discriminate sub-phenotypes of pre-frailty both at the gender level and depending on the pre-frailty progression and reversibility. The best resulting models included four different metabolites for each gender. They showed very good prediction capacity with AUCs of 0.93 (95% CI = 0.87-1) and 0.94 (95% CI = 0.87-1) for men and women, respectively. Additionally, early and/or predictive markers of pre-frailty were identified for both genders and the gender specific models showed also good performance (three metabolites; AUC = 0.82; 95% CI = 0.72-0.93) for men and very good for women (three metabolites; AUC = 0.92; 95% CI = 0.86-0.99). These results open the door, through multivariate strategies, to a possibility of monitoring the disease progression over time at a very early stage.

Published
2019

33. Profound Changes in Net Energy and Nitrogen Metabolites Fluxes within the Splanchnic Area during Overfeeding of Yucatan Mini Pigs That Remain Euglycemic

Author

Savary-Auzeloux, Isabelle, Mohamed, Ahmed Ben, Cohade, Benoit, Dardevet, Dominique, David, Jérémie, Hafnaoui, Noureddine, Migné, Carole, Pujos-Guillot, Estelle, Rémond, Didier, Polakof, Sergio, Unité de Nutrition Humaine (UNH), Institut National de la Recherche Agronomique (INRA)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020]), Plateforme Exploration du Métabolisme (PFEM), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-MetaboHUB-Clermont, MetaboHUB-MetaboHUB, PFEM, MetaboHUB, Unité de Nutrition Humaine - Clermont Auvergne (UNH), and Institut National de la Recherche Agronomique (INRA)-Université Clermont Auvergne (UCA)

Subjects
Blood Glucose, obesity, Nitrogen, Swine, Nutritional Status, short chain fatty acid, lcsh:TX341-641, Hyperphagia, liver, Article, nutrient flux, Animals, Bile, Insulin, Urea, Lactic Acid, Amino Acids, glucose, lactate, Gluconeogenesis, minipig, Fatty Acids, Volatile, Postprandial Period, Adaptation, Physiological, Gastrointestinal Tract, Hyperglycemia, Carbohydrate Metabolism, Swine, Miniature, gut, Female, Energy Intake, Energy Metabolism, lcsh:Nutrition. Foods and food supply, [SDV.AEN]Life Sciences [q-bio]/Food and Nutrition, amino acid
Abstract

A dysregulation of nutrient exchange between tissues (gut, liver, muscles, adipose) occurs during overnutrition and could induce obesity and metabolic diseases. We aimed to evaluate how, in overfed mini pigs, nutrients use and partition were regulated in the gut and liver. Net nutrients fluxes were assessed in the fed (PP) and post absorptive (PA) states at 1, 14 and 60 days of adaptation to overfeeding in five adult Yucatan female multicatheterized minipigs. Pigs PA glycaemia and PP-induced hyperglycemia remained unchanged over the experimental period, suggesting that the management of the excess of energy intake allowed the maintenance of glucose levels. This was associated with (1) an increased PA plasma insulin, (2) an increased gut lactate production (increased lactate net release +89%, 1 h PP, D1 vs. D60) probably from an increased glucose oxidation, (3) a shift in utilization of gluconeogenic precursor (lactate, propionate) in the liver, and (4) a reduced gut utilization of nitrogen moieties for energy purposes (glutamine), a nitrogen sparing effect at the whole body level (decreased plasma urea in PA (&minus, 24% D1 vs. D60) and PP states) and a specific increased level of AA involved in lipids handling and bile recycling in the gut lumen (taurine and glycine).

Published
2019

34. Diet-Related Metabolites Associated with Cognitive Decline Revealed by Untargeted Metabolomics in a Prospective Cohort

Author

Low, Dorrain, Lefèvre-Arbogast, Sophie, Dominguez-Gonzalez, Raúl, Urpi Sarda, Mireia, Micheau, Pierre, Pétéra, Mélanie, Centeno, Delphine, Durand, Stéphanie, Pujos-Guillot, Estelle, Korosi, Aniko, Lucassen, Paul J., Aigner, Ludwig., Proust-Lima, Cecile, Manach, Claudine, Hejblum, Boris P., Helmer, Catherine, Andres-Lacueva, Cristina, Thuret, Sandrine, Samieri, Cecilia, Unité de Nutrition Humaine (UNH), Institut National de la Recherche Agronomique (INRA)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020]), Nanyang Technological University [Singapour], Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut National de la Santé et de la Recherche Médicale (INSERM), University of Barcelona, Instituto de Salud Carlos III [Madrid] (ISC), Plateforme Exploration du Métabolisme (PFEM), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-MetaboHUB-Clermont, MetaboHUB-MetaboHUB, University of Amsterdam [Amsterdam] (UvA), Paracelsus Medizinische Privatuniversität = Paracelsus Medical University (PMU), Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), King‘s College London, Unité de Nutrition Humaine - Clermont Auvergne (UNH), Institut National de la Recherche Agronomique (INRA)-Université Clermont Auvergne (UCA), Instituto de Salud Carlos III (ISC), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Epidémiologie et Biostatistique [Bordeaux], Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Epidémiologie et Biostatistique [Bordeaux], Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), and Structural and Functional Plasticity of the nervous system (SILS, FNWI)

Subjects
Male, Aging, Cognitive decline, Coffea, Coffee, Eating, Fish Products, Metabolites, Humans, Metabolomics, Cognitive Dysfunction, Longitudinal Studies, Research Articles, Aged, Aged, 80 and over, Dietary biomarkers, Untargeted metabolomics, Metabòlits, Diet, Blood, Case-Control Studies, Dieta, Dementia, Female, [SDV.AEN]Life Sciences [q-bio]/Food and Nutrition, Blood Chemical Analysis, Research Article
Abstract

Scope Untargeted metabolomics may reveal preventive targets in cognitive aging, including within the food metabolome. Methods and results A case‐control study nested in the prospective Three‐City study includes participants aged ≥65 years and initially free of dementia. A total of 209 cases of cognitive decline and 209 controls (matched for age, gender, education) with slower cognitive decline over up to 12 years are contrasted. Using untargeted metabolomics and bootstrap‐enhanced penalized regression, a baseline serum signature of 22 metabolites associated with subsequent cognitive decline is identified. The signature includes three coffee metabolites, a biomarker of citrus intake, a cocoa metabolite, two metabolites putatively derived from fish and wine, three medium‐chain acylcarnitines, glycodeoxycholic acid, lysoPC(18:3), trimethyllysine, glucose, cortisol, creatinine, and arginine. Adding the 22 metabolites to a reference predictive model for cognitive decline (conditioned on age, gender, education and including ApoE‐ε4, diabetes, BMI, and number of medications) substantially increases the predictive performance: cross‐validated Area Under the Receiver Operating Curve = 75% [95% CI 70–80%] compared to 62% [95% CI 56–67%]. Conclusions The untargeted metabolomics study supports a protective role of specific foods (e.g., coffee, cocoa, fish) and various alterations in the endogenous metabolism responsive to diet in cognitive aging., The Three‐City cohort of older persons with a 12‐year follow‐up for cognition is leveraged to identify, in the serum of initially non‐demented participants, metabolites associated with subsequent cognitive decline. Untargeted metabolomics reveals a signature of 22 metabolites improving cognitive decline prediction. It includes diet‐derived metabolites (e.g., from coffee, citrus juice, cocoa, fish), as well as endogenous metabolites responsive to diet.

Published
2019

35. Nutrimetabolomics: An Integrative Action for Metabolomic Analyses in Human Nutritional Studies

Author

Mar Garcia-Aloy, Gianfranco Picone, Christoph H. Weinert, Claudine Manach, Edith J. M. Feskens, Beate Ott, Marynka Ulaszewska, Lieven Van Meulebroek, Samantha Riccadonna, Thomas Skurk, Bjoern Egert, René Badertscher, Joachim Kopka, Manuela J. Rist, Fulvio Mattivi, Kati Hanhineva, Rafael Llorach, Reto Portmann, Caroline Rombouts, Marta Cialiè Rosso, Francesco Capozzi, Josep Rubert, Chiara Cordero, Lorraine Brennan, Lynn Vanhaecke, Grégory Pimentel, Carole Migné, Guy Vergères, Achim Bub, Sabine E. Kulling, Franck Giacomoni, Cristina Andres Lacueva, Carl Brunius, Hannelore Daniel, Pietro Franceschi, Pedapati S. C. Sri Harsha, Alessia Trimigno, Pieter Giesbertz, Raúl González-Domínguez, Linda H. Münger, Stéphanie Durand, Rosa Vázquez-Fresno, Lieselot Hemeryck, Paola G. Ferrario, David S. Wishart, Estelle Pujos-Guillot, Marynka M. Ulaszewska, Christoph H. Weinert, Alessia Trimigno, Reto Portmann, Cristina Andres Lacueva, Rene Badertscher, Lorraine Brennan, Carl Brunius, Achim Bub, Francesco Capozzi, Marta Cialie Rosso, Chiara E. Cordero, Hannelore Daniel,Stephanie Durand, Bjoern Egert, Paola G. Ferrario, Edith J.M. Feskens, Pietro Franceschi, Mar Garcia-Aloy, Franck Giacomoni, Pieter Giesbertz, Raul Gonzalez-Domınguez,Kati Hanhineva, Lieselot Y. Hemeryck, Joachim Kopka, Sabine E. Kulling, Rafael Llorach, Claudine Manach, Fulvio Mattivi, Carole Migne, Linda H. Munger, Beate Ott, Gianfranco Picone, Gregory Pimentel, Estelle Pujos-Guillot, Samantha Riccadonna, Manuela J. Rist, Caroline Rombouts, Josep Rubert, Thomas Skurk, Pedapati S. C. Sri Harsha, Lieven Van Meulebroek, Lynn Vanhaecke, Rosa Vazquez-Fresno, David Wishart,Guy Vergeres, Department of Food Quality and Nutrition, Research and Innovation Centre, Department of Safety and Quality of Fruit and Vegetables, Federal Research Institute for Nutrition and Food, Department of Agricultural and Food Science, University of Bologna, Method Development and Analytics Research Division, Agroscope, Department of Nutrition and Food Sciences, Utah State University (USU), Universitat de Barcelona, Centro de Investigación Biomédica en Red Fragilidad y Envejecimiento Saludable, Instituto de Salud Carlos III [Madrid] (ISC), Institute of Food and Health, University College Dublin [Dublin] (UCD), Department of Biology and Biological Engineering, Chalmers University of Technology [Göteborg], Department of Physiology and Biochemistry of Nutrition, Max Rubner-Institut, Dipartimento di Scienza e Tecnologia, Farmaco Università degli Studi di Torino, Nutritional Physiology, Technische Universität Munchen - Université Technique de Munich [Munich, Allemagne] (TUM), Unité de Nutrition Humaine (UNH), Institut National de la Recherche Agronomique (INRA)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020]), Plateforme d'Exploration du Métabolisme, Institut National de la Recherche Agronomique (INRA), Division of Human Nutrition, Wageningen University and Research [Wageningen] (WUR), Computational Biology Unit [Bergen] (CBU), University of Bergen (UiB), Molecular Nutrition Unit, Department of Clinical Nutrition, Research Centre for Endocrinology and Metabolism, Sahlgrenska University Hospital, University of Eastern Finland, Department of Veterinary Public Health and Food Safety, Istituto Superiore di Sanita [Rome], Ghenth University, Department of Molecular Physiology, Applied Metabolome Analysis, Max Planck Institute of Molecular Plant Physiology (MPI-MP), Max-Planck-Gesellschaft-Max-Planck-Gesellschaft, Center Agriculture Food Environment, Università degli Studi di Trento (UNITN), Food Microbial Systems Research Division, Else Kröner Fresenius Center for Nutritional Medicine, Technische Universität München, ZIEL Institute for Food and Health, Departments of Biological Sciences and Computing Science, University of Alberta, BioNH call under the Joint Programming Initiative 'A Healthy Diet for a Healthy Life' (JPI-HDHL) Ministry of Education, Universities and Research (MIUR)2075Ministry of Economy and Competitiveness (MINECO) PCIN-2014-133Agencia de Gestio D'Ajuts Universitaris de Recerca Agaur (AGAUR) 2017SGR1566CIBERFES [European Regional Development Fund (FEDER) program from the European Union (EU)] Swiss National Science Foundation (SNSF) 40HD40 160618'Juan de la Cierva' program from MINECO FJCI-2015-26590, Instituto de Salud Carlos III (ISC), Technical University of Munich (TUM), Unité de Nutrition Humaine - Clermont Auvergne (UNH), Institut National de la Recherche Agronomique (INRA)-Université Clermont Auvergne (UCA), Wageningen University and Research Centre [Wageningen] (WUR), Computational Biology Unit (BCCS), University of Bergen (UIB), University of Bologna/Università di Bologna, Università degli studi di Torino = University of Turin (UNITO), Plateforme Exploration du Métabolisme (PFEM), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-MetaboHUB-Clermont, MetaboHUB-MetaboHUB, Istituto Superiore di Sanità (ISS), Universiteit Gent = Ghent University (UGENT), Manach, Claudine, and Vergeres, G.

Subjects
0301 basic medicine, Settore CHIM/01 - CHIMICA ANALITICA, Nutritional Sciences, Computer science, [SDV]Life Sciences [q-bio], Eating, Data Mining, GC–MS, 2. Zero hunger, Chromatography, Life sciences, metabolomics, Food Analysis, Molecular analysis, GC-MS, LC-MS, metabolomics, NMR, nutrition, nutrition, Metabolòmica, GC-MS, LC-MS, NMR, Alimentation et Nutrition, Biotechnology, metabolomic, Nutritional Status, LC–MS, 03 medical and health sciences, Metabolomics, Humans, Food and Nutrition, Expert Testimony, VLAG, Global Nutrition, Electronic Data Processing, Wereldvoeding, Models, Statistical, 030109 nutrition & dietetics, Clinical study design, Reproducibility of Results, Healthy diet, Data science, Biomarker (cell), 030104 developmental biology, Workflow, Action (philosophy), Multivariate Analysis, Ciències de la vida, Biomarkers, Food Science
Abstract

The life sciences are currently being transformed by an unprecedented wave of developments in molecular analysis, which include important advances in instrumental analysis as well as biocomputing. In light of the central role played by metabolism in nutrition, metabolomics is rapidly being established as a key analytical tool in human nutritional studies. Consequently, an increasing number of nutritionists integrate metabolomics into their study designs. Within this dynamic landscape, the potential of nutritional metabolomics (nutrimetabolomics) to be translated into a science, which can impact on health policies, still needs to be realized. A key element to reach this goal is the ability of the research community to join, to collectively make the best use of the potential offered by nutritional metabolomics. This article, therefore, provides a methodological description of nutritional metabolomics that reflects on the state‐of‐the‐art techniques used in the laboratories of the Food Biomarker Alliance (funded by the European Joint Programming Initiative "A Healthy Diet for a Healthy Life" (JPI HDHL)) as well as points of reflections to harmonize this field. It is not intended to be exhaustive but rather to present a pragmatic guidance on metabolomic methodologies, providing readers with useful "tips and tricks" along the analytical workflow.

Published
2019

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

Author

Cyril Jousse, Isabelle Canet, Mounir Traïkia, Ludovic Besaury, Binta Diémé, Marie Lagree, Nolwenn Wirgot, Bernard Lyan, Pierre Amato, Martine Sancelme, Anne-Marie Delort, Institut de Chimie de Clermont-Ferrand (ICCF), SIGMA Clermont (SIGMA Clermont)-Institut de Chimie du CNRS (INC)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS), PFEM, MetaboHUB, Unité de Nutrition Humaine (UNH), Institut National de la Recherche Agronomique (INRA)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020]), Plateforme Exploration du Métabolisme (PFEM), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-MetaboHUB-Clermont, MetaboHUB-MetaboHUB, Delort, Anne-Marie, Institut de Chimie de Clermont-Ferrand - Clermont Auvergne (ICCF), Sigma CLERMONT (Sigma CLERMONT)-Université Clermont Auvergne (UCA)-Centre National de la Recherche Scientifique (CNRS), Unité de Nutrition Humaine - Clermont Auvergne (UNH), and Institut National de la Recherche Agronomique (INRA)-Université Clermont Auvergne (UCA)

Subjects
0301 basic medicine, Atmospheric chemistry, Microorganism, Chimie analytique, Air Microbiology, lcsh:Medicine, medicine.disease_cause, complex mixtures, Article, Mass Spectrometry, 03 medical and health sciences, chemistry.chemical_compound, 0302 clinical medicine, Adenosine Triphosphate, Pseudomonas, Metabolome, medicine, Metabolomics, lcsh:Science, chemistry.chemical_classification, Reactive oxygen species, Multidisciplinary, biology, lcsh:R, Humidity, Glutathione, Hydrogen Peroxide, biology.organism_classification, [SDV.MP.BAC]Life Sciences [q-bio]/Microbiology and Parasitology/Bacteriology, Metabolic pathway, Oxidative Stress, 030104 developmental biology, chemistry, Biochemistry, lcsh:Q, sense organs, Microcosm, [CHIM.OTHE]Chemical Sciences/Other, Analytical chemistry, 030217 neurology & neurosurgery, Bacteria, Oxidative stress, Autre (Sciences du Vivant)
Abstract

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.

Published
2019

37. Listeria monocytogenes Biofilm Adaptation to Different Temperatures Seen Through Shotgun Proteomics

Author

Santos, Tiago, Viala, Didier, Chambon, Christophe, Esbelin, Julia, Hébraud, Michel, Microbiologie Environnement Digestif Santé (MEDIS), INRA Clermont-Ferrand-Theix-Université Clermont Auvergne [2017-2020] (UCA [2017-2020]), Qualité des Produits Animaux (QuaPA), Institut National de la Recherche Agronomique (INRA), Plateforme d'Exploration du Métabolisme, European Union's Horizon 2020 research and Innovation programme under the Marie-Slodowska Curie grant 641984, Agence Nationale de la Recherche (ANR) (France) as part of an EcoSec contract, Institut National de la Recherche Agronomique (INRA)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020]), Plateforme Exploration du Métabolisme (PFEM), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-MetaboHUB-Clermont, MetaboHUB-MetaboHUB, Microbiologie Environnement Digestif Santé - Clermont Auvergne (MEDIS), and Université Clermont Auvergne (UCA)-INRA Clermont-Ferrand-Theix

Subjects
subproteomes, shotgun proteomics, temperature adaptation, [SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN], [SDV.IDA]Life Sciences [q-bio]/Food engineering, listeria monocytogenes, biofilm, listeria monocytogènes, protéome, Listeria monocytogenes, [SDV.MP.BAC]Life Sciences [q-bio]/Microbiology and Parasitology/Bacteriology, Nutrition, Original Research
Abstract

International audience; Listeria monocytogenes is a foodborne pathogen that can cause invasive severe human illness (listeriosis) in susceptible patients. Most human listeriosis cases appear to be caused by consumption of refrigerated ready-to-eat foods. Although initial contamination levels in foods are usually low, the ability of these bacteria to survive and multiply at low temperatures allows it to reach levels high enough to cause disease. This study explores the set of proteins that might have an association with L. monocytogenes adaptation to different temperatures. Cultures were grown in biofilm, the most widespread mode of growth in natural and industrial realms. Protein extractions were performed from three different growth temperatures (10, 25, and 37°C) and two growth phases (early stage and mature biofilm). L. monocytogenes subproteomes were targeted using three extraction methods: trypsin-enzymatic shaving, biotin-labeling and cell fractionation. The different subproteomes obtained were separated and analyzed by shotgun proteomics using high-performance liquid chromatography combined with tandem mass spectrometry (LC-OrbiTrap LTQVelos, ThermoFisher Scientific). A total of 141 (biotinylation), 98 (shaving) and 910 (fractionation) proteins were identified. Throughout the 920 unique proteins identified, many are connected to basic cell functions, but some are linked with thermoregulation. We observed some noteworthy protein abundance shifts associated with the major adaptation to cold mechanisms present in L. monocytogenes, namely: the role of ribosomes and the stressosome with a higher abundance of the general stress protein Ctc (Rl25) and the general stress transcription factor sigma B (σB), changes in cell fluidity and motility seen by higher levels of foldase protein PrsA2 and flagellin (FlaA), the uptake of osmolytes with a higher abundance of glycine betaine (GbuB) and carnitine transporters (OpucA), and the relevance of the overexpression of chaperone proteins such as cold shock proteins (CspLA and Dps). As for 37°C, we observed a significantly higher percentage of proteins associated with transcriptional or translational activity present in higher abundance upon comparison with the colder settings. These contrasts of protein expression throughout several conditions will enrich databases and help to model the regulatory circuitry that drives adaptation of L. monocytogenes to environments.

Published
2019

38. 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

Author

François Fenaille, Estelle Pujos-Guillot, Anna Warnet, Jean-Claude Tabet, Annelaure Damont, Laurent Debrauwer, Marie-Françoise Olivier, Bernard Lyan, Christophe Junot, Stéphane Bernillon, Emilien L. Jamin, Commissariat à l'Energie Atomique et aux Energies Alternatives (CEA), MetaboHUB, Université Paris Saclay (COmUE), Institut National de la Recherche Agronomique (INRA), Service de Pharmacologie et Immunoanalyse (SPI), Médicaments et Technologies pour la Santé (MTS), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Unité de Nutrition Humaine (UNH), Institut National de la Recherche Agronomique (INRA)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020]), Plateforme Exploration du Métabolisme (PFEM), MetaboHUB-Clermont, MetaboHUB-MetaboHUB-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Clermont Auvergne (UCA), MetaToul AXIOM (E20), ToxAlim (ToxAlim), Institut National de la Recherche Agronomique (INRA)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Ecole d'Ingénieurs de Purpan (INP - PURPAN), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National de la Recherche Agronomique (INRA)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-MetaboHUB-MetaToul, MetaboHUB-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-MetaboHUB-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Biologie du fruit et pathologie (BFP), Université Bordeaux Segalen - Bordeaux 2-Institut National de la Recherche Agronomique (INRA)-Université Sciences et Technologies - Bordeaux 1 (UB), Institut Parisien de Chimie Moléculaire (IPCM), Chimie Moléculaire de Paris Centre (FR 2769), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Ecole Nationale Supérieure de Chimie de Paris - Chimie ParisTech-PSL (ENSCP), Université Paris sciences et lettres (PSL)-Ecole Superieure de Physique et de Chimie Industrielles de la Ville de Paris (ESPCI Paris), Université Paris sciences et lettres (PSL)-Institut de Chimie du CNRS (INC)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Institut de Chimie du CNRS (INC)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS), Sorbonne Université (SU), METABOHUB, ANR-11-INBS-0010, Service de Pharmacologie et d'Immunoanalyse (SPI), Institut National de la Recherche Agronomique (INRA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Plateforme d'Exploration du Métabolisme, Analyse de Xénobiotiques, Identification, Métabolisme (E20 Metatoul-AXIOM), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Ecole d'Ingénieurs de Purpan (INPT - EI Purpan), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Recherche Agronomique (INRA)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Recherche Agronomique (INRA)-MetaToul-MetaboHUB, Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Université Bordeaux Segalen - Bordeaux 2-Institut National de la Recherche Agronomique (INRA)-Université Sciences et Technologies - Bordeaux 1, Institut de Chimie du CNRS (INC)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Ecole Nationale Supérieure de Chimie de Paris - Chimie ParisTech-PSL (ENSCP), Université Paris sciences et lettres (PSL)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut de Chimie du CNRS (INC)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Université Fédérale Toulouse Midi-Pyrénées-Ecole d'Ingénieurs de Purpan (INPT - EI Purpan), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-MetaToul-MetaboHUB, Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut de Chimie du CNRS (INC)-École normale supérieure - Paris (ENS-PSL), and Université Paris sciences et lettres (PSL)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut de Chimie du CNRS (INC)-École normale supérieure - Paris (ENS-PSL)

Subjects
Electrospray, High-resolution mass spectrometry, Spectrometry, Mass, Electrospray Ionization, Databases, Factual, Annotation, Computational biology, Mass spectrometry, 01 natural sciences, Metabolomics, [CHIM.ANAL]Chemical Sciences/Analytical chemistry, Tandem Mass Spectrometry, Mass spectra, Fluxomics, Spectroscopy, Chromatography, High Pressure Liquid, Data Curation, Principal Component Analysis, Chemistry, 010405 organic chemistry, 010401 analytical chemistry, Computational Biology, MS databases, 0104 chemical sciences, Identification (information), Data exchange, Mass spectrum, Mass spectral database
Abstract

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.

Published
2018

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

Author

Spiro Khoury, Bernard Lyan, Estelle Pujos-Guillot, Corinne Pouyet, Unité de Nutrition Humaine (UNH), Institut National de la Recherche Agronomique (INRA)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020]), Plateforme d'Exploration du Métabolisme, MetaboHUB, ANR-11-INBS-0010,METABOHUB,Développement d'une infrastructure française distribuée pour la métabolomique dédiée à l'innovation(2011), Unité de Nutrition Humaine - Clermont Auvergne (UNH), Institut National de la Recherche Agronomique (INRA)-Université Clermont Auvergne (UCA), Plateforme Exploration du Métabolisme (PFEM), MetaboHUB-Clermont, and MetaboHUB-MetaboHUB-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Clermont Auvergne (UCA)

Subjects
0301 basic medicine, phospholipide, Spectrometry, Mass, Electrospray Ionization, Electrospray ionization, mass spectrum analysis, Autoxidation, Tandem mass spectrometry, Mass spectrometry, 01 natural sciences, Biochemistry, Analytical Chemistry, 03 medical and health sciences, chemistry.chemical_compound, Oxidized phospholipids, Tandem Mass Spectrometry, Fragmentation, spectrométrie de masse, [CHIM.ANAL]Chemical Sciences/Analytical chemistry, Phosphatidylcholine, Lipidomics, oxidative stress, Chromatography, High Pressure Liquid, Phospholipids, phospholipid, chemistry.chemical_classification, Phosphatidylethanolamine, Degree of unsaturation, Chromatography, unsaturated fatty acid, 010401 analytical chemistry, Fatty acid, stress oxydatif, acide gras insaturé, maladie métabolique, 0104 chemical sciences, 030104 developmental biology, chemistry, Oxidation-Reduction, [SDV.AEN]Life Sciences [q-bio]/Food and Nutrition, composé oxyde
Abstract

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.

Published
2018

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

Author

Cédric Mendes, Isabelle Canet, Martine Sancelme, Pierre Amato, Anne-Marie Delort, Cyril Jousse, Marie Lagree, Mounir Traïkia, Céline Dalle, Bernard Lyan, Institut de Chimie de Clermont-Ferrand (ICCF), SIGMA Clermont (SIGMA Clermont)-Institut de Chimie du CNRS (INC)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS), Plateforme d'Exploration du Métabolisme, MetaboHUB, Unité de Nutrition Humaine (UNH), Institut National de la Recherche Agronomique (INRA)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020]), Plateforme d’exploration du métabolisme, Institut National de la Recherche Agronomique (INRA), Plateforme Exploration du Métabolisme (PFEM), MetaboHUB-Clermont, MetaboHUB-MetaboHUB-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Clermont Auvergne (UCA), Institut de Chimie de Clermont-Ferrand - Clermont Auvergne (ICCF), Sigma CLERMONT (Sigma CLERMONT)-Université Clermont Auvergne (UCA)-Centre National de la Recherche Scientifique (CNRS), Unité de Nutrition Humaine - Clermont Auvergne (UNH), and Institut National de la Recherche Agronomique (INRA)-Université Clermont Auvergne (UCA)

Subjects
0301 basic medicine, Magnetic Resonance Spectroscopy, 010504 meteorology & atmospheric sciences, Endocrinology, Diabetes and Metabolism, influence de la température, Clinical Biochemistry, mass spectrum analysis, Pseudomonas syringae, 01 natural sciences, Biochemistry, Antioxidants, Mass Spectrometry, chemistry.chemical_compound, Cryoprotective Agents, spectrométrie de masse, oxidative stress, cloud, activité microbienne, bactérie, biology, Strain (chemistry), Pseudomonas, ROS, bacterium, Adaptation, Physiological, peptide, Cold Temperature, eau de nuage, Water Microbiology, [SDU.STU]Sciences of the Universe [physics]/Earth Sciences, microbial activity, analyse métabolomique, 03 medical and health sciences, Alkaloids, Metabolomics, [CHIM.ANAL]Chemical Sciences/Analytical chemistry, Metabolome, 0105 earth and related environmental sciences, Cold-Shock Response, stress oxydatif, Metabolism, MS, biology.organism_classification, Trehalose, [SDE.ES]Environmental Sciences/Environmental and Society, NMR, 030104 developmental biology, chemistry, peptides, cold stress, Database Management Systems, Energy Metabolism, Bacteria
Abstract

This research has been supported by the ANR French program MetaboHUB. We would like to thank Mélanie Pétéra for her valuable technical assistance; AbstractIntroduction: 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.

Published
2018

41. Evaluation de méthodes statistiques pour l’intégration de données métabolomiques, cliniques et alimentaires

Author

Brandolini-Bunlon, Marion, Petera, Mélanie, Monnerie, Stéphanie, Joly, Charlotte, Morais, José, Payette, Hélène, Gaudreau, Pierrette, Boccard, Julien, Pujos-Guillot, Estelle, Unité de Nutrition Humaine (UNH), Institut National de la Recherche Agronomique (INRA)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020]), Plateforme d'Exploration du Métabolisme, MetaboHUB, McGill University = Université McGill [Montréal, Canada], Université de Sherbrooke (UdeS), Centre de Santé et de Services Sociaux, Département de médecine, Centre Léon Bérard [Lyon], Centre Hospitalier Universitaire de Montréal, Ecole de pharmacie Genève-Lausanne (EPGL), Société Française de Spectrométrie de Masse (SFSM). FRA., Société Française d'Electrophorèse et d'Analyse Protéomique (SFEAP). FRA., Réseau Francophone de Métabolomique et Fluxomique (RFMF). FRA., Plateforme Exploration du Métabolisme (PFEM), MetaboHUB-Clermont, and MetaboHUB-MetaboHUB-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Clermont Auvergne (UCA)

Subjects
Bioinformatics, Chimie analytique, nutrition, maladies métaboliques chroniques, spectrométrie de masse, [CHIM.ANAL]Chemical Sciences/Analytical chemistry, Alimentation et Nutrition, PLS multiblocs, Food and Nutrition, Bio-informatique, intégration de données, AFM, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], biomarqueurs, Analytical chemistry, ACP multiblocs, [SDV.AEN]Life Sciences [q-bio]/Food and Nutrition
Abstract

Intégration des données et approches multi-omiques; National audience; Du fait de la prévalence croissante des maladies métaboliques chroniques, la compréhension de leurs mécanismes et du rôle de la nutrition dans leur développement et leur prévention est aujourd’hui un enjeu majeur. Leur complexité (maladies de systèmes) requiert une approche populationnelle, intégrée et multifactorielle.L’objectif de ce travail est de proposer une stratégie d’intégration de données afin de construire des modèles multidimensionnels, descriptifs ou discriminants de pathologies pour la découverte de biomarqueurs, et de contribuer à une meilleure compréhension des processus physiopathologiques impliqués. Pour cela, cette étude s’est basée sur des données et échantillons biologiques de sujets de la cohorte NuAge du Réseau Québécois de Recherche sur le vieillissement : 123 hommes (68-82 ans) ont été sélectionnés pour une étude cas/témoins (61/62 sujets) du syndrome métabolique. Ils ont été suivis annuellement avec des prélèvements biologiques, la mesure de paramètres cliniques et le recueil de données par questionnaires. Des analyses métabolomiques ont été réalisées par spectrométrie de masse sur des échantillons de sérum collectés en 2003-2005 (T1) et 3 ans plus tard (T4). Trois blocs de données ont ainsi été identifiés : métabolomiques (863 ions), cliniques (29 variables) et alimentaires (41 variables), par temps et par groupe de sujets. Ils ont été analysés avec le logiciel R, simultanément ou deux à deux, après normalisation UV ou Pareto, par des méthodes d’analyses multiblocs, à des fins descriptives (ACP multiblocs et Analyse Factorielle Multiple (AFM)) ou discriminantes (PLS multiblocs). Les résultats sont comparés sur la base de critères statistiques (pourcentage de variance expliquée, Q2, R2, matrice de confusion...) et de leur adéquation aux objectifs biologiques : discrimination cas/témoins, identification de marqueurs, découverte de sous-groupes, adéquation aux connaissances du domaine... Ce travail a permis d’établir une stratégie d’intégration de données pour mettre en oeuvre une approche multidimensionnelle d’étude des pathologies systémiques

Published
2017

42. A Proof of Concept to Bridge the Gap between Mass Spectrometry Imaging, Protein Identification and Relative Quantitation: MSI~LC-MS/MS-LF

Author

Michel Hébraud, Frédéric Roche, Thierry Astruc, Christophe Chambon, Cécile Coudy-Gandilhon, Laetitia Théron, Delphine Centeno, Léonard Féasson, Didier Rémond, Jean-Claude Barthélémy, Estelle Pujos-Guillot, Daniel Béchet, Tissus animaux, nutrition, digestion, écosystème et métabolisme (TANDEM), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-INP. Ecole Nationale Supérieure Agronomique de Toulouse, Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Unité de Nutrition Humaine (UNH), Institut National de la Recherche Agronomique (INRA)-Université d'Auvergne - Clermont-Ferrand I (UdA)-Clermont Université, Qualité des Produits Animaux (QuaPA), Institut National de la Recherche Agronomique (INRA), Service de Physiologie Clinique et de l’Exercice, Faculté de Médecine Jacques Lisfranc, Biologie, Ingénierie et Imagerie de la Greffe de Cornée (EA 2521, JE2521, IFR143), Université Jean Monnet [Saint-Étienne] (UJM), Laboratoire Interuniversitaire de Biologie de la Motricité (LIBM ), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Université Jean Monnet [Saint-Étienne] (UJM)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), Microbiologie Equipe Qualité et Sécurité des Aliments (INRA), Unité de Nutrition Humaine - Clermont Auvergne (UNH), Institut National de la Recherche Agronomique (INRA)-Université Clermont Auvergne (UCA), Plateforme d'Exploration du Métabolisme, Université d'Auvergne - Clermont-Ferrand I (UdA)-Clermont Université-Institut National de la Recherche Agronomique (INRA), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Université Jean Monnet [Saint-Étienne] (UJM), Plateforme Exploration du Métabolisme (PFEM), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-MetaboHUB-Clermont, MetaboHUB-MetaboHUB, Service de Physiologie Clinique et de l'Exercice [CHU de Saint-Etienne], Centre Hospitalier Universitaire de Saint-Etienne [CHU Saint-Etienne] (CHU ST-E)-Université Jean Monnet - Saint-Étienne (UJM), Biologie, Ingénierie et Imagerie pour l'Ophtalmologie (BIIO), Université Jean Monnet - Saint-Étienne (UJM), Université de Lyon-Université de Lyon-Université Jean Monnet - Saint-Étienne (UJM)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), SECurité des ALIments et Microbiologie, and Institut National de la Recherche Agronomique (INRA)-École nationale d'ingénieurs des techniques des industries agricoles et alimentaires (ENITIAA)-École nationale vétérinaire, agroalimentaire et de l'alimentation Nantes-Atlantique (ONIRIS)

Subjects
0301 basic medicine, [SDV]Life Sciences [q-bio], Clinical Biochemistry, MALDI mass spectrometry imaging, protein identification, label-free quantitation, skeletal muscle, lcsh:QR1-502, Biochemistry, Article, Mass spectrometry imaging, lcsh:Microbiology, Matrix (chemical analysis), 03 medical and health sciences, Structural Biology, spectrométrie de masse, Lc ms ms, Protein purification, Molecular Biology, neoplasms, ComputingMilieux_MISCELLANEOUS, Chromatography, Laser ablation, Chemistry, muscle squelettique, digestive system diseases, quantification, Label-free quantification, 030104 developmental biology, Tissue sections, protéine, identification, Protein identification
Abstract

International audience; Mass spectrometry imaging (MSI) is a powerful tool to visualize the spatial distribution of molecules on a tissue section. The main limitation of MALDI-MSI of proteins is the lack of direct identification. Therefore, this study focuses on a MSI~LC-MS/MS-LF workflow to link the results from MALDI-MSI with potential peak identification and label-free quantitation, using only one tissue section. At first, we studied the impact of matrix deposition and laser ablation on protein extraction from the tissue section. Then, we did a back-correlation of the m/z of the proteins detected by MALDI-MSI to those identified by label-free quantitation. This allowed us to compare the label-free quantitation of proteins obtained in LC-MS/MS with the peak intensities observed in MALDI-MSI. We managed to link identification to nine peaks observed by MALDI-MSI. The results showed that the MSI~LC-MS/MS-LF workflow (i) allowed us to study a representative muscle proteome compared to a classical bottom-up workflow; and (ii) was sparsely impacted by matrix deposition and laser ablation. This workflow, performed as a proof-of-concept, suggests that a single tissue section can be used to perform MALDI-MSI and protein extraction, identification, and relative quantitation.

Published
2016

43. Repeated cures with paracetamol worsen sarcopenia in old rats with suboptimal food intake

Author

Carole Mast, Isabelle Savary-Auzeloux, Didier Remond, Corinne Pouyet, Delphine Centeno, Guillaume Voyard, Lydie Combaret, Dominique Dardevet, Isabelle Papet, Unité de Nutrition Humaine (UNH), Institut National de la Recherche Agronomique (INRA)-Université d'Auvergne - Clermont-Ferrand I (UdA)-Clermont Université, Plateforme d'Exploration du Métabolisme, Institut National de la Recherche Agronomique (INRA), Département de chimie, Université Blaise Pascal - Clermont-Ferrand 2 (UBP), Université Blaise Pascal (Clermont Ferrand 2) (UBP), Plateforme Exploration du Métabolisme (PFEM), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-MetaboHUB-Clermont, and MetaboHUB-MetaboHUB

Subjects
Male, Médicaments, Aging, masse musculaire, Muscle Proteins, Medication, liver, sarcopenia, personne âgée, Eating, [SDV.SP.MED]Life Sciences [q-bio]/Pharmaceutical sciences/Medication, sarcopenie, Animals, Food and Nutrition, paracétamol, Amino Acids, Rats, Wistar, glutathione, skeletal muscle, Muscle, Skeletal, senior citizens, acetaminophen, digestive, oral, and skin physiology, muscle squelettique, sulfur amino acids, voluntary muscle, muscle mass, protein metabolism, Alimentation et Nutrition, [SDV.AEN]Life Sciences [q-bio]/Food and Nutrition
Abstract

The authors thank Medhi Djelloul-Mazouz, Philippe Lhoste, Arlette Cissoire and Philippe Denis from the Installation Experimentale en Nutrition (INRA Clermont-Ferrand-Theix, France) for their excellent assistance with animal care.This work was supported by Institut National de la Recherche Agronomique (INRA, France); The availability of all amino acids is of prime importance to prevent the ageing-associated decrease in skeletal muscle mass i.e. sarcopenia. Cysteine is the precursor of sulfate and glutathione that are both utilized in the liver to detoxify paracetamol (APAP). Cysteine availability could become limiting under repeated cures with APAP, especially when food intake is suboptimal. The aim of the study was to determine whether repeated cures with APAP could worsen sarcopenia. Twenty-two-month-old male Wistar rats received 3 two-week-long cures of APAP (1% of the diet) intercalated with washout periods of two weeks (APAP group). They were compared to untreated control rats euthanatized prior to the experiment (CT group) and rats pair-fed to the APAP group (PF group). Skeletal muscle mass and protein metabolism, as well as plasma amino acids and glutathione were assessed at the end of the third cure. APAP cures reduced food intake by 33, 23 and 33 % during the successive cures leading to an overall body weight loss of 8%. APAP rats lost lean mass during the experiment (-11%). This loss tended (P = 0.09) to be higher than in the PF group (-9%). The mass of hind limb muscles and the absolute synthesis rate of muscle proteins were 13 and 17% lower in the APAP group than the PF group, respectively. Plasma free cyst(e)ine (i.e. all free forms of cysteine not bound to proteins) and glutathione were 25% lower in the APAP group than the PF group. Repeated cures with APAP worsened sarcopenia in old rats with suboptimal food intake likely as a consequence of the APAP-induced shortage in cysteine/glutathione. Clinical studies are needed to clarify the effect of repeated treatments with paracetamol on skeletal muscle mass in older persons having suboptimal or insufficient dietary intakes

Published
2016

44. Workflow4Metabolomics: A collaborative research infrastructure for computational metabolomics

Author

Petera, Mélanie, Le Corguille, Gildas, Landi, Marion, Monsoor, Misharl, Tremblay-Franco, Marie, Martin, Jean-Francois, Duperier, Christophe, Jacob, Daniel, Guitton, Yann, Lefebvre, Marie, Pujos-Guillot, Estelle, Giacomoni, Franck, Thévenot, Etienne, Caron, Christophe, Unité de Nutrition Humaine (UNH), Université d'Auvergne - Clermont-Ferrand I (UdA)-Clermont Université-Institut National de la Recherche Agronomique (INRA), Université Pierre et Marie Curie - Paris 6 (UPMC), ABiMS - Informatique et bioinformatique = Analysis and Bioinformatics for Marine Science (FR2424), Station biologique de Roscoff (SBR), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Analyse de Xénobiotiques, Identification, Métabolisme (E20 Metatoul-AXIOM), ToxAlim (ToxAlim), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Ecole d'Ingénieurs de Purpan (INPT - EI Purpan), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Recherche Agronomique (INRA)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Recherche Agronomique (INRA)-MetaToul-MetaboHUB, Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Biologie du fruit et pathologie (BFP), Université Sciences et Technologies - Bordeaux 1-Université Bordeaux Segalen - Bordeaux 2-Institut National de la Recherche Agronomique (INRA), Platetorme Métabolome Bordeaux, Institut National de la Recherche Agronomique (INRA), Dynamics, Logics and Inference for biological Systems and Sequences (Dyliss), Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-GESTION DES DONNÉES ET DE LA CONNAISSANCE (IRISA-D7), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), CentraleSupélec-Télécom Bretagne-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de Recherche en Informatique et en Automatique (Inria)-École normale supérieure - Rennes (ENS Rennes)-Université de Bretagne Sud (UBS)-Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Télécom Bretagne-Université de Rennes 1 (UR1), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-École normale supérieure - Rennes (ENS Rennes)-Université de Bretagne Sud (UBS)-Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA), Laboratoire d'Informatique de Nantes Atlantique (LINA), Centre National de la Recherche Scientifique (CNRS)-Mines Nantes (Mines Nantes)-Université de Nantes (UN), Plateforme Metabolome Bordeaux, Laboratoire d'analyse des données et d'intelligence des systèmes (LADIS), Département Métrologie Instrumentation & Information (DM2I), Laboratoire d'Intégration des Systèmes et des Technologies (LIST), Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Laboratoire d'Intégration des Systèmes et des Technologies (LIST), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, MetaboHUB, Centre National de la Recherche Scientifique (CNRS), Université d'Auvergne - Clermont-Ferrand I (UdA). Clermont-Ferrand, FRA., Institut National de la Recherche Agronomique (INRA)-Université d'Auvergne - Clermont-Ferrand I (UdA)-Clermont Université, Station biologique de Roscoff [Roscoff] (SBR), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), Toxicologie Alimentaire (UTA), Institut National de la Recherche Agronomique (INRA)-Université de Bourgogne (UB)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, Université Bordeaux Segalen - Bordeaux 2-Institut National de la Recherche Agronomique (INRA)-Université Sciences et Technologies - Bordeaux 1, Université Paris-Saclay-Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Laboratoire d'Intégration des Systèmes et des Technologies (LIST), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), IDEALG [ANR-10-BTBR-04], IFB [ANR-11- INBS-0013], MetaboHUB [ANR-11-INBS-0010], ANR-10-BTBR-04-01/10-BTBR-0004,IDEALG,IDEALG(2010), ANR-11-INBS-0013/11-INBS-0013,ReNaBi-IFB,Institut français de bioinformatique(2011), ANR-11-INBS-0010/11-INBS-0010,METABOHUB,Développement d’une infrastructure française distribuée pour la métabolomique dédiée à l’innovation(2011), MetaToul AXIOM (E20), Institut National de la Recherche Agronomique (INRA)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Ecole d'Ingénieurs de Purpan (INP - PURPAN), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National de la Recherche Agronomique (INRA)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-MetaboHUB-MetaToul, MetaboHUB-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-MetaboHUB-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Proteomic Facility [Bordeaux] (Functional Genomic Center), Université de Bordeaux (UB), Laboratoire d'Intégration des Systèmes et des Technologies (LIST (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Laboratoire d'Intégration des Systèmes et des Technologies (LIST (CEA)), ANR-10-BTBR-0004,IDEALG,Biotechnologies pour la valorisation des macroalgues(2010), ANR-11-INBS-0013,IFB (ex Renabi-IFB),Institut français de bioinformatique(2011), ANR-11-INBS-0010,METABOHUB,Développement d'une infrastructure française distribuée pour la métabolomique dédiée à l'innovation(2011), ABiMS - Informatique et bioinformatique = Analysis and Bioinformatics for Marine Science (ABIMS), Fédération de recherche de Roscoff (FR2424), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Station biologique de Roscoff (SBR), Université Bordeaux Segalen - Bordeaux 2-Institut National de la Recherche Agronomique (INRA)-Université Sciences et Technologies - Bordeaux 1 (UB), Plateforme Bordeaux Metabolome, Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-MetaboHUB-Bordeaux, MetaboHUB-MetaboHUB, Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Mines Nantes (Mines Nantes)-Université de Nantes (UN)-Centre National de la Recherche Scientifique (CNRS), Laboratoire Outils d'Analyse des Données (LOAD), Plateforme Exploration du Métabolisme (PFEM), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-MetaboHUB-Clermont, This work was supported by Biogenouest R©, Lifegrid (Auvergne), and by the IDEALG project [ANR-10-BTBR-04], IFB [ANR-11-INBS-0013] and MetaboHUB [ANR-11-INBS-0010] grants., Université Sciences et Technologies - Bordeaux 1-Institut National de la Recherche Agronomique (INRA)-Université Bordeaux Segalen - Bordeaux 2, Université Fédérale Toulouse Midi-Pyrénées-Ecole d'Ingénieurs de Purpan (INPT - EI Purpan), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-MetaToul-MetaboHUB, Unité de Nutrition Humaine ( UNH ), Institut National de la Recherche Agronomique ( INRA ) -Université d'Auvergne - Clermont-Ferrand I ( UdA ) -Clermont Université, Université Pierre et Marie Curie - Paris 6 ( UPMC ), ABiMS - Informatique et bioinformatique = Analysis and Bioinformatics for Marine Science ( FR2424 ), Station Biologique de Roscoff, Toxicologie Alimentaire ( UTA ), Institut National de la Recherche Agronomique ( INRA ) -Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, MetaToul-AXIOM, Plateforme de Métabolomique et de Chimie Analytique en Toxicologie, Institut National de la Recherche Agronomique ( INRA ), Biologie du fruit et pathologie ( BFP ), Université Bordeaux Segalen - Bordeaux 2-Institut National de la Recherche Agronomique ( INRA ) -Université Sciences et Technologies - Bordeaux 1, Dynamics, Logics and Inference for biological Systems and Sequences ( Dyliss ), Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -GESTION DES DONNÉES ET DE LA CONNAISSANCE ( IRISA-D7 ), Institut de Recherche en Informatique et Systèmes Aléatoires ( IRISA ), CentraleSupélec-Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -Télécom Bretagne-Institut National des Sciences Appliquées ( INSA ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -École normale supérieure - Rennes ( ENS Rennes ) -Centre National de la Recherche Scientifique ( CNRS ) -Université de Bretagne Sud ( UBS ) -CentraleSupélec-Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -Télécom Bretagne-Institut National des Sciences Appliquées ( INSA ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -École normale supérieure - Rennes ( ENS Rennes ) -Centre National de la Recherche Scientifique ( CNRS ) -Université de Bretagne Sud ( UBS ) -Institut de Recherche en Informatique et Systèmes Aléatoires ( IRISA ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -Télécom Bretagne-Institut National des Sciences Appliquées ( INSA ) -École normale supérieure - Rennes ( ENS Rennes ) -Centre National de la Recherche Scientifique ( CNRS ) -Université de Bretagne Sud ( UBS ), UMR 6241, Laboratoire d'Informatique de Nantes-Atlantique ( LINA ), Laboratoire d’Intégration des Systèmes et Technologies ( LIST/LADIS ), Commissariat à l'Energie Atomique et aux Energies Alternatives ( CEA ), Centre National de la Recherche Scientifique ( CNRS ), Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Université de Bretagne Sud (UBS)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-CentraleSupélec-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Université de Rennes (UNIV-RENNES)-CentraleSupélec-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Université de Bretagne Sud (UBS)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Rennes (ENS Rennes)-Télécom Bretagne-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-CentraleSupélec, Université de Toulouse (UT)-Ecole d'Ingénieurs de Purpan (INPT - EI Purpan), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Station biologique de Roscoff [Roscoff] ( SBR ), Université Pierre et Marie Curie - Paris 6 ( UPMC ) -Centre National de la Recherche Scientifique ( CNRS ), LADIS, Commissariat à l'énergie atomique et aux énergies alternatives ( CEA ), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), and Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
Computer science, [ SDV.AEN ] Life Sciences [q-bio]/Food and Nutrition, data analysis, Gene Expression, SOFTWARE, computer.software_genre, Biochemistry, Field (computer science), Workflow, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, plateforme collaborative, analyse statistique, collaborative online platform, bioinformatics, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], metabolomics, Computer Science Applications, Computational Mathematics, Identification (information), Computational Theory and Mathematics, annotation, Statistical analysis, statistics, WEB SERVER, Alimentation et Nutrition, Algorithms, data processing, Statistics and Probability, Signal processing, [ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR], analyse métabolomique, World Wide Web, Metabolomics, [SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN], Food and Nutrition, Molecular Biology, [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB], IDENTIFICATION, business.industry, expertise collective, Computational Biology, Applications Notes, MASS-SPECTROMETRY DATA, Virtual machine, [INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR], Data pre-processing, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], Software engineering, business, computer, [SDV.AEN]Life Sciences [q-bio]/Food and Nutrition
Abstract

Paper reference: Giacomoni et al. (2014) Workflow4Metabolomics: A collaborative research infrastructure for com- putational metabolomics. Bioinformatics http://dx.doi.org/10.1093/bioinformatics/btu813Paper reference: Giacomoni et al. (2014) Workflow4Metabolomics: A collaborative research infrastructure for computational metabolomics. Bioinformatics http://dx.doi.org/10.1093/bioinformatics/btu813; In the context of an emergent and fast evolving science, the development of various tools dedicated to metabolomic data processing and data analysis increased. Because metabolomic analyses require a variety of steps involving various disciplines from analytical chemistry to statistics and bioinformatics, it requires many skills and expertise. However, despite this abundance of tools, standardization is lacking in these diversity of programs, as well as infrastructure to handle and link the different steps of metabolomic analyses. We recently implemented Workflow4Metabolomics (W4M), a collaborative online platform hosting and providing a full pipelinefor metabolomics from data preprocessing to annotation including statistical analysis. It is not designed to respond to only one specific type of metabolomic analysis, but to cover a maximum range of possible approaches - as metabolomics is a complex science that can be studied through various complementary analytical techniques. Thus, more than just gathering programs, W4M provides relevant combinations of generic and specific tools, a large part of which being developed and sustained by the partners providing this virtual research environment (VRE). Moreover, using Galaxy, a web-based platform technology, W4M provides modules from various sources and of various types. This platform allows hosted tools to be run and linked together via an instinctive and ergonomic interface, which is beneficial for both beginners and experts in metabolomics. W4M gets its strength from the collaboration of complementary teams from bioinformatics and metabolomics environment. Initiated by the collaboration between two platforms, it gathers today six research teams and platforms with a higher diversity in skills and expertise. It allows a continuous enrichment in the service provided, with addition of new modules and new possible workflows dedicated to cover a large scope of the increasing needs of the metabolomic community. Moreover,the ‘open-source’ aspect of this platform allows to open it to new collaborators bringing specific expertise that can be highlighted and disseminated in the metabolomic community

Published
2015

45. Quantifying Diet-Induced Metabolic Changes of the Human Gut Microbiome

Author

Shoaie, Saeed, Ghaffari, Pouyan, Kovatcheva-Datchary, Petia, Mardinoglu, Adil, Sen, Partho, Pujos-Guillot, Estelle, De Wouters, Tomas, Juste, Catherine, Rizkalla, Salwa, Chilloux, Julien, Hoyles, Lesley, Nicholson, Jeremy K., Consortium, MICRO-Obes, Doré, Joël, Dumas, Marc E., Clément, Karine, Bäckhed, Fredrik, Nielsen, Jens, Kennedy, Sean P., Prifti, Edi, Pons, Nicolas, Le Chatelier, Emmanuelle, Almeida, Mathieu, Quinquis, Benoit, Levenez, Florence, Galleron, Nathalie, Batto, Jean-Michel, Ehrlich, Stanislav, Blottiere, Herve, Lepage, Patricia, Maguin, Emmanuelle, Van De Guchte, Maarten, Department of Biology and Biological Engineering, Chalmers University of Technology [Göteborg], University of Gothenburg (GU), Unité de Nutrition Humaine (UNH), Institut National de la Recherche Agronomique (INRA)-Université d'Auvergne - Clermont-Ferrand I (UdA)-Clermont Université, Plateforme d'Exploration du Métabolisme, Institut National de la Recherche Agronomique (INRA), MICrobiologie de l'ALImentation au Service de la Santé (MICALIS), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, MetaGenoPolis, CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Unité de Recherche sur les Maladies Cardiovasculaires, du Métabolisme et de la Nutrition = Institute of cardiometabolism and nutrition (ICAN), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Imperial College London, University of Copenhagen = Københavns Universitet (KU), Département Microbiologie et Chaîne Alimentaire (MICA), Knut and Alice Wallenberg Foundation, Bill & Melinda Gates Foundation, Torsten Soderbergs Stiftelse, European Commission HEALTH-F4-2012-305312, Fondation Coeur et Arteres, French National Agency of Research (ANR MicroObes and 'Investissements d'avenir') ANR-10-IAHU-05, ProdInra, Migration, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Unité de Recherche sur les Maladies Cardiovasculaires, du Métabolisme et de la Nutrition = Research Unit on Cardiovascular and Metabolic Diseases (ICAN), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Institut de Cardiométabolisme et Nutrition = Institute of Cardiometabolism and Nutrition [CHU Pitié Salpêtrière] (IHU ICAN), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-CHU Pitié-Salpêtrière [AP-HP], University of Copenhagen = Københavns Universitet (UCPH), Plateforme Exploration du Métabolisme (PFEM), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-MetaboHUB-Clermont, MetaboHUB-MetaboHUB, Commission of the European Communities, and Université d'Auvergne - Clermont-Ferrand I (UdA)-Clermont Université-Institut National de la Recherche Agronomique (INRA)

Subjects
Male, HOST, Interactive optimization, Physiology, Genome scale, Microbial metabolism, Computational biology, Gut flora, Bioinformatics, Models, Biological, MICROFLORA, Endocrinology & Metabolism, RECONSTRUCTIONS, 03 medical and health sciences, 0302 clinical medicine, Human gut, MICRO-Obes Consortium, 1101 Medical Biochemistry And Metabolomics, Humans, Metabolic modeling, AMINO-ACIDS, Microbiome, Intestinal Mucosa, Molecular Biology, Feces, 030304 developmental biology, 0303 health sciences, Science & Technology, biology, Microbiota, 0601 Biochemistry And Cell Biology, Cell Biology, biology.organism_classification, GENE, Intestines, PROTEIN-COUPLED RECEPTOR, [SDV.AEN] Life Sciences [q-bio]/Food and Nutrition, CHAIN FATTY-ACIDS, HUMAN LARGE-INTESTINE, BACTERIA, Female, ADIPOSITY, Life Sciences & Biomedicine, [SDV.AEN]Life Sciences [q-bio]/Food and Nutrition, 030217 neurology & neurosurgery
Abstract

International audience; The human gut microbiome is known to be associated with various human disorders, but a major challenge is to go beyond association studies and elucidate causalities. Mathematical modeling of the human gut microbiome at a genome scale is a useful tool to decipher microbe-microbe, diet-microbe and microbe-host interactions. Here, we describe the CASINO (Community And Systems-level INteractive Optimization) toolbox, a comprehensive computational platform for analysis of microbial communities through metabolic modeling. We first validated the toolbox by simulating and testing the performance of single bacteria and whole communities in vitro. Focusing on metabolic interactions between the diet, gut microbiota, and host metabolism, we demonstrated the predictive power of the toolbox in a diet-intervention study of 45 obese and overweight individuals and validated our predictions by fecal and blood metabolomics data. Thus, modeling could quantitatively describe altered fecal and serum amino acid levels in response to diet intervention.

Published
2015

46. MetaboHUB and RFMF : two tools at the service of metabolomics and fluxomics in France

Author

Rolin, Dominique, Bellvert, Floriant, Bertrand-Michel, Justine, Canlet, Cécile, Cole, Richard, Colombie, Sophie, Deborde, Catherine, Debrauwer, Laurent, Ferrara, Marc, Fouillen, Laetitia, Jourdan, Fabien, Jousse, Cyril, Junot, Christophe, Moing, Annick, Portais, Jean-Charles, Pujos-Guillot, Estelle, Sautot, Caroline, Thévenot, Etienne, Biologie du fruit et pathologie (BFP), Université Bordeaux Segalen - Bordeaux 2-Institut National de la Recherche Agronomique (INRA)-Université Sciences et Technologies - Bordeaux 1, Plateforme Metabolome Bordeaux-MetaboHUB, Institut National de la Recherche Agronomique (INRA)-Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Ingénierie des Systèmes Biologiques et des Procédés (LISBP), Institut National de la Recherche Agronomique (INRA)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS), MetaToul-MetaboHUB, Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM), Laboratoire d'analyse des données et d'intelligence des systèmes (LADIS), Département Métrologie Instrumentation & Information (DM2I), Laboratoire d'Intégration des Systèmes et des Technologies (LIST), Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Laboratoire d'Intégration des Systèmes et des Technologies (LIST), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Plateforme Metabolome-IDF- MetaboHUB, Institut National de la Recherche Agronomique (INRA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Unité de Nutrition Humaine (UNH), Institut National de la Recherche Agronomique (INRA)-Université d'Auvergne - Clermont-Ferrand I (UdA)-Clermont Université, Plateforme Exploration du Métabolisme-MetaboHUB (PFEM-MetaboHUB), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP), Institut de Chimie de Clermont-Ferrand (ICCF), Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-SIGMA Clermont (SIGMA Clermont)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), INRA-Transfert, Institut National de la Recherche Agronomique (INRA), Université Bordeaux Segalen - Bordeaux 2-Institut National de la Recherche Agronomique (INRA)-Université Sciences et Technologies - Bordeaux 1 (UB), Plateforme Bordeaux Metabolome, Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-MetaboHUB-Bordeaux, MetaboHUB-MetaboHUB, Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS), MetaboHUB-MetaToul, MetaboHUB-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Laboratoire d'Intégration des Systèmes et des Technologies (LIST (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Laboratoire d'Intégration des Systèmes et des Technologies (LIST (CEA)), MetaboHUB-IDF, Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-MetaboHUB-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Plateforme Exploration du Métabolisme (PFEM), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-MetaboHUB-Clermont, Laboratoire de biogenèse membranaire (LBM), Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS), INRA Transfert, ProdInra, Migration, Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut National des Sciences Appliquées (INSA)-Université Fédérale Toulouse Midi-Pyrénées-Institut National des Sciences Appliquées (INSA)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), and Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)

Subjects
standardization, human biofluids, [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, plants, metabolome annotations, health, spectrum analysis, nutrition, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN], [SDV.BBM.GTP] Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN], Metabolomics, biochemistry, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, [SDV.BV] Life Sciences [q-bio]/Vegetal Biology, animal cell extracts, microorganisms, signal processing, environment, metabolites, ComputingMilieux_MISCELLANEOUS, Fluxomics, agriculture, biotechnology
Abstract

International audience; MetaboHUB and RFMF are two tools developed in France to serve the scientific community in Metabolomics and Fluxomics (M&F). The French Metabolomics and Fluxomics Network (RFMF, https://www.bordeaux.inra.fr/ifr103/reseau_metabolome/) is a scientific society which contributes to the development of M&F and more broadly to the overall analysis of metabolism in France through various actions:• Foster relationships between French researchers working in the world of M&F (public and private sectors);• Promote and structure education and training in M&F;• Organize and support the organization of conferences in France and abroad;• Encourage the participation of young researchers to national and international conferences through grants;• Allocate funds mission or prizes for accomplished work in M&F.MetaboHUB project (http://www.metabohub.fr/en/) aims at creating a national infrastructure that will place France among the European leaders for advanced research services in M&F. MetaboHUB provides equipment and services to academic research and industrial partners in nutrition, health, agriculture, environment and biotechnology. MetaboHUB is the merging of 4 existing facilities (Bordeaux, Paris-Saclay, Toulouse and Clermont-Ferrand) into a unique infrastructure sharing common regulations and complementary M&F tools. Besides providing state-of-the-art services and support to national and international projects, a major ambition of MetaboHUB is to develop innovative tools and methods to address critical biological questions. MetaboHUB will provide custom solutions for (i) high-throughput, quantitative technologies for biochemical phenotyping of large sets of samples and for systems biology through standardization and combination of state–of-art technologies, (ii) identification of metabolites in human biofluids, plants, microorganisms and animal cell extracts, through the implementation and maintenance of centralized and open spectral repositories for metabolome annotations, (iii) large-scale flux profiling and sub-cellular fluxomics through integration of analytical data from multiple analytical devices, (iv) access to high-impact services to the national scientific community and industrial actors and, (v) attracting and training a new generation of scientists and students.

Published
2014

47. Spectral Database: from data model to web interface

Author

Paulhe, Nils, Duperier, Christophe, Jacob, Daniel, Thévenot, Etienne, Martin, Jean-Francois, Lopez, Claire, Giacomoni, Franck, Unité de Nutrition Humaine (UNH), Institut National de la Recherche Agronomique (INRA)-Université d'Auvergne - Clermont-Ferrand I (UdA)-Clermont Université, Plateforme d'Exploration du Métabolisme, MetaboHUB, Biologie du fruit et pathologie (BFP), Université Sciences et Technologies - Bordeaux 1-Université Bordeaux Segalen - Bordeaux 2-Institut National de la Recherche Agronomique (INRA), Analyse de Xénobiotiques, Identification, Métabolisme (E20 Metatoul-AXIOM), ToxAlim (ToxAlim), Institut National de la Recherche Agronomique (INRA)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Ecole d'Ingénieurs de Purpan (INPT - EI Purpan), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Recherche Agronomique (INRA)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-MetaToul-MetaboHUB, Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut National de la Santé et de la Recherche Médicale (INSERM), ANR-11-INBAS-0010 project, Région Rhône Alpes. FRA., Université d'Auvergne - Clermont-Ferrand I (UdA)-Clermont Université-Institut National de la Recherche Agronomique (INRA), Université Bordeaux Segalen - Bordeaux 2-Institut National de la Recherche Agronomique (INRA)-Université Sciences et Technologies - Bordeaux 1, Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Plateforme Exploration du Métabolisme (PFEM), MetaboHUB-Clermont, MetaboHUB-MetaboHUB-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Clermont Auvergne (UCA), Université Bordeaux Segalen - Bordeaux 2-Institut National de la Recherche Agronomique (INRA)-Université Sciences et Technologies - Bordeaux 1 (UB), MetaToul AXIOM (E20), Université de Toulouse (UT)-Université de Toulouse (UT)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Ecole d'Ingénieurs de Purpan (INP - PURPAN), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National de la Recherche Agronomique (INRA)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-MetaboHUB-MetaToul, MetaboHUB-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-MetaboHUB-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), and Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)

Subjects
composé chimique, plateforme métabolome-fluxome, spectra, Alimentation et Nutrition, Food and Nutrition, biostatistique, spectrométrie, analyse spectrale, database, metabolomics, bioinformatique, [SDV.AEN]Life Sciences [q-bio]/Food and Nutrition
Abstract

Acknowledgements: MetaboHUB (ANR-11-INBAS-0010 project) Présentation poster Pauhle Nils; National audience; MetaboHUB is a metabolomics and fluxomics infrastructure that provides tools to research teams and partners. The Bioinformatics and Biostatistics service is specialized in NMR, GC- and LC-MS data processing and analysis, from raw data to metabolite identification. To challenge the annotation of these data and centralize knowledge, a dedicated team is building a software to assist in identification, including a compound and spectra database. The core of the “MetaboHUB Spectral Database”, called "data-model", is a computational representation of each entity involved in Spectra analysis and Chemical Compounds identification. One of the strengths of the project is the common work between chemical experts and bioinformaticians in data model design permitting respect of logics and constraints uses in Metabolomics during data manipulation and storage. The software architecture allows us to use parts of the project as standalone software, available for the community. The data-model seems to be able to manage several types of chemical compounds (like standards or sub-structures) and different types of Spectra (MS, MS/MS and NMR, simple, JRES and multidimensional). We will be able to approve the data-model with data from the chemical libraries provided by MetaboHUB members. One of the final goals of the spectral database is to provide a computed aided spectra identification tool, using all these data.thought a web-portal. Two milestones are coming: a first to provide a mechanism to import spectral data in the data-model (which means in the database too), a second to define metadata around spectral analysis.

Published
2014

48. Lipid profiling following intake of the Omega 3 fatty acid DHA identifies the peroxidized metabolites F-4-Neuroprostanes as the best predictors of atherosclerosis prevention

Author

Céline Demougeot, Theresa L. Pedersen, John W. Newman, Thierry Durand, Cécile Gladine, Olivier Berdeaux, Blandine Comte, Andrzej Mazur, Estelle Pujos-Guillot, Jean-Marie Galano, Unité de Nutrition Humaine ( UNH ), Clermont Université-Université d'Auvergne - Clermont-Ferrand I ( UdA ) -Institut National de la Recherche Agronomique ( INRA ), Department of Nutrition, University of California [Davis] ( UC Davis ), Obesity and Metabolism Research Unit, Institut des Biomolécules Max Mousseron [Pôle Chimie Balard] ( IBMM ), Ecole Nationale Supérieure de Chimie de Montpellier ( ENSCM ) -Université de Montpellier ( UM ) -Centre National de la Recherche Scientifique ( CNRS ), Fonctions et dysfonctions épithéliales - UFC (EA 4267) ( FDE ), Université de Franche-Comté ( UFC ), Centre des Sciences du Goût et de l'Alimentation [Dijon] ( CSGA ), Institut National de la Recherche Agronomique ( INRA ) -Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique ( CNRS ), Plateforme d'Exploration du métabolisme, Institut National de la Recherche Agronomique ( INRA ), INRA, USDA-ARS, Unité de Nutrition Humaine (UNH), Institut National de la Recherche Agronomique (INRA)-Université d'Auvergne - Clermont-Ferrand I (UdA)-Clermont Université, University of California [Davis] (UC Davis), University of California-University of California, Institut des Biomolécules Max Mousseron [Pôle Chimie Balard] (IBMM), Ecole Nationale Supérieure de Chimie de Montpellier (ENSCM)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Fonctions et dysfonctions épithéliales - UFC (EA 4267) (FDE), Université de Franche-Comté (UFC), Centre des Sciences du Goût et de l'Alimentation [Dijon] (CSGA), Institut National de la Recherche Agronomique (INRA)-Université de Bourgogne (UB)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS), Institut National de la Recherche Agronomique (INRA), Schunck, Wolf-Hagen, University of California (UC)-University of California (UC), Ecole Nationale Supérieure de Chimie de Montpellier (ENSCM)-Institut de Chimie du CNRS (INC)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC), Institut National de la Recherche Agronomique (INRA)-Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS), Plateforme Exploration du Métabolisme (PFEM), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-MetaboHUB-Clermont, MetaboHUB-MetaboHUB, intramural French National Institute for Agricultural Research (INRA), United States Department of Agriculture-Agricultural Research Service (USDA-ARS) [5306-51530-019-00D], Université d'Auvergne - Clermont-Ferrand I (UdA)-Clermont Université-Institut National de la Recherche Agronomique (INRA), Université de Montpellier (UM), Western Human Nutrition Research Center, Pathologies et épithéliums : prévention, innovation, traitements, évaluation (EA 4267) (PEPITE), Centre des Sciences du Goût et de l'Alimentation (CSGA), Centre National de la Recherche Scientifique (CNRS)-Institut de Chimie du CNRS (INC)-Université de Montpellier (UM)-Ecole Nationale Supérieure de Chimie de Montpellier (ENSCM), ProdInra, Migration, and Pathologies et épithéliums : prévention, innovation, traitements, évaluation (UR 4267) (PEPITE)

Subjects
Mouse, Blood Pressure, Cardiovascular, Biochemistry, Mice, 0302 clinical medicine, Tandem Mass Spectrometry, Aetiology, lcsh:Science, chemistry.chemical_classification, Liquid, 0303 health sciences, [CHIM.ORGA]Chemical Sciences/Organic chemistry, Fatty Acids, anti-atherogenic, omega 3 fatty acids, epa, dha, bioactive lipid, atherosclerosis, pufas, effects, molecular, Lipids, 3. Good health, Fatty Acids, Unsaturated, Medicine, medicine.medical_specialty, Knockout, Aortic Diseases, Médecine humaine et pathologie, Gas Chromatography-Mass Spectrometry, LDL, Dose-Response Relationship, Lipid Mediators, 03 medical and health sciences, [ CHIM.ORGA ] Chemical Sciences/Organic chemistry, acide gras n 3, Complementary and Integrative Health, Biology, Dose-Response Relationship, Drug, Prevention, lcsh:R, athérosclérose, EPA, Lipid Metabolism, Prevention of disease and conditions, medicine.disease, Endocrinology, chemistry, Neuroprostanes, lcsh:Q, Human health and pathology, Biomarkers, and promotion of well-being, lcsh:Medicine, 030204 cardiovascular system & hematology, medicine.disease_cause, Oral and gastrointestinal, Heart Rate, Receptors, Blood plasma, Cluster Analysis, 2.1 Biological and endogenous factors, Mice, Knockout, Unsaturated, Chromatography, Multidisciplinary, Fatty liver, Animal Models, DHA, Liver, Docosahexaenoic acid, lipids (amino acids, peptides, and proteins), Drug, Research Article, Polyunsaturated fatty acid, Docosahexaenoic Acids, Clinical Research Design, General Science & Technology, Model Organisms, Internal medicine, medicine, Animals, Animal Models of Disease, 3.3 Nutrition and chemoprevention, Omega 3 fatty acid, Nutrition, 030304 developmental biology, Analysis of Variance, acide docosahexaénoique, Lipid metabolism, Atherosclerosis, [SDV.AEN] Life Sciences [q-bio]/Food and Nutrition, Receptors, LDL, PUFAs, [SDV.AEN]Life Sciences [q-bio]/Food and Nutrition, Oxidative stress, Chromatography, Liquid
Abstract

International audience; The anti-atherogenic effects of omega 3 fatty acids, namely eicosapentaenoic (EPA) and docosahexaenoic acids (DHA) are well recognized but the impact of dietary intake on bioactive lipid mediat or profiles remains unclear. Such a profiling effort may offer novel targets for future studies into the mechanism of action of omega 3 fatty acids. The present study aimed to determine the impact of DHA supplementation on the profiles of polyunsaturated fatty acids (PUFA) oxygenated metabolites and to investigate their contribution to therosclerosis prevention. A special emphasis was given to the non-enzymatic metabolites knowing the high susceptibility of DHA to free radical-mediated peroxidation and the increased oxidative stress associated with plaque formation. Atherosclerosis prone mice (LDLR -/-) received increasing doses of DHA (0, 0.1, 1 or 2% of energy) during 20 weeks leading to a dose -dependent reduction of atherosclerosis (R2=0.97, p=0.02), trig lyceridemia (R2=0.97, p=0.01) and cholesterolemia (R2=0.96, p

Published
2014

49. New biomarkers of coffee consumption identified by non targeted metabolomic profiling in cohort study subjects

Author

Fillatre, Yoann, Rothwell, Joe, Touvier, Mathilde, Lyan, Bernard, Martin, Jean-Francois, Joly, Charlotte, GUEHO, Soizic, Fezeu Kamedjie, Léopold, Arnault, Nathalie, Sébédio, Jean-Louis, Comte, Blandine, Hercberg, Serge, Pujos-Guillot, Estelle, Galan, Pilar, Manach, Claudine, Unité de Nutrition Humaine (UNH), Institut National de la Recherche Agronomique (INRA)-Université d'Auvergne - Clermont-Ferrand I (UdA)-Clermont Université, Unité de Recherche en Epidémiologie Nutritionnelle (UREN), Université Paris 13 (UP13)-Institut National de la Recherche Agronomique (INRA)-Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM), Plate-Forme d'Exploration du Métabolisme, Institut National de la Recherche Agronomique (INRA), ANR Phenomenep ALIA-2010-007, Conseil Regional Auvergne-FEDER post-doc grant (YF), Metabolomics Society., Université Paris 13 (UP13)-Institut National de la Recherche Agronomique (INRA)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM), Plateforme Exploration du Métabolisme (PFEM), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-MetaboHUB-Clermont, and MetaboHUB-MetaboHUB

Subjects
facteur de risque, [CHIM.ANAL]Chemical Sciences/Analytical chemistry, Alimentation et Nutrition, Chimie analytique, Food and Nutrition, bénéfice, consommateur, café, Analytical chemistry, biomarqueur, [SDV.AEN]Life Sciences [q-bio]/Food and Nutrition, ComputingMilieux_MISCELLANEOUS, caféine
Abstract

Communication orale Yoann Fillâtre; International audience

Published
2013

50. Cloud metabolomics-Response to cold shock in bacteria originating from clouds

Author

Dalle, Céline, Mendes, Cédric, Canet, Isabelle, Sancelme, Martine, Lagrée, Marie, Traïkia, Mounir, Delort, Anne-Marie, Amato, Pierre, Jousse, Cyril, Institut de Chimie de Clermont-Ferrand (ICCF), Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-SIGMA Clermont (SIGMA Clermont)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Unité de Nutrition Humaine (UNH), Institut National de la Recherche Agronomique (INRA)-Université d'Auvergne - Clermont-Ferrand I (UdA)-Clermont Université, Université Blaise Pascal - Clermont-Ferrand 2 (UBP), Plate-Forme d'Exploration du Métabolisme, Institut National de la Recherche Agronomique (INRA), Institut de Chimie, Metabolomics Society., Plateforme Exploration du Métabolisme (PFEM), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-MetaboHUB-Clermont, and MetaboHUB-MetaboHUB

Subjects
bactérie, atmosphère, microorganisme, stress au froid, Alimentation et Nutrition, Food and Nutrition, cellule, biomarqueur, nuage, [SDV.AEN]Life Sciences [q-bio]/Food and Nutrition, profil métabolique, ComputingMilieux_MISCELLANEOUS
Abstract

Présentation poster Cyril Jousse; International audience

Published
2013

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