Publications
157 results found
Hoyles L, Abbott JC, Holmes E, et al., 2015, IMP: Imperial Metagenomics Pipeline for high-throughput sequence data, Exploring Human Host-Microbiome Interactions in Health and Disease
McCartney AL, Hoyles L, Jiménez-Pranteda ML, et al., 2015, Reduction of trimethylamine N-oxide to trimethylamine by the human gut microbiota: supporting evidence for ‘metabolic retroversion’, Exploring Human Host-Microbiome Interactions in Health and Disease
Dietary sources of methylamines such as choline, trimethylamine (TMA), trimethylamine N-oxide (TMAO), phosphatidylcholine (PC) and carnitine are present in a number of foodstuffs, including meat, fish, nuts and eggs. It is recognized that the gut microbiota is able to convert choline to TMA in a fermentation-like process. Similarly, PC and carnitine are converted to TMA by the gut microbiota. It has been suggested that TMAO is subject to ‘metabolic retroversion’ in the gut (i.e. it is reduced to TMA by the gut microbiota, with this TMA being oxidized to produce TMAO in the liver). Sixty-six strains of human faecal and caecal bacteria were screened on solid and liquid media for their ability to utilize trimethylamine N-oxide (TMAO), with metabolites in spent media profiled by Proton Nuclear Magnetic Resonance (1H NMR) spectroscopy. Enterobacteriaceae produced mostly TMA from TMAO, with caecal/small intestinal isolates of Escherichia coli producing more TMA than their faecal counterparts. Lactic acid bacteria (enterococci, streptococci, bifidobacteria) produced increased amounts of lactate when grown in the presence of TMAO, but did not produce large amounts of TMA from TMAO. The presence of TMAO in media increased the growth rate of Enterobacteriaceae; while it did not affect the growth rate of lactic acid bacteria, TMAO increased the biomass of these bacteria. The positive influence of TMAO on Enterobacteriaceae was confirmed in anaerobic, stirred, pH-controlled batch culture fermentation systems inoculated with human faeces, where this was the only bacterial population whose growth was significantly stimulated by the presence of TMAO in the medium. We hypothesize that dietary TMAO is used as an alternative electron acceptor by the gut microbiota in the small intestine/proximal colon, and contributes to microbial population dynamics upon its utilization and retroversion to TMA, prior to absorption and secondary conversion to TMAO by hepatic flavin-contai
Hedjazi L, Gauguier D, Zalloua PA, et al., 2015, MQTL.NMR: An integrated suite for genetic mapping of quantitative variations of <sup>1</sup>H NMR-based metabolic profiles, Analytical Chemistry, Vol: 87, Pages: 4377-4384, ISSN: 0003-2700
High-throughput <sup>1</sup>H nuclear magnetic resonance (NMR) is an increasingly popular robust approach for qualitative and quantitative metabolic profiling, which can be used in conjunction with genomic techniques to discover novel genetic associations through metabotype quantitative trait locus (mQTL) mapping. There is therefore a crucial necessity to develop specialized tools for an accurate detection and unbiased interpretability of the genetically determined metabolic signals. Here we introduce and implement a combined chemoinformatic approach for objective and systematic analysis of untargeted <sup>1</sup>H NMR-based metabolic profiles in quantitative genetic contexts. The R/Bioconductor mQTL.NMR package was designed to (i) perform a series of preprocessing steps restoring spectral dependency in collinear NMR data sets to reduce the multiple testing burden, (ii) carry out robust and accurate mQTL mapping in human cohorts as well as in rodent models, (iii) statistically enhance structural assignment of genetically determined metabolites, and (iv) illustrate results with a series of visualization tools. Built-in flexibility and implementation in the powerful R/Bioconductor framework allow key preprocessing steps such as peak alignment, normalization, or dimensionality reduction to be tailored to specific problems. The mQTL.NMR package is freely available with its source code through the Comprehensive R/Bioconductor repository and its own website (http://www.ican-institute.org/tools/). It represents a significant advance to facilitate untargeted metabolomic data processing and quantitative analysis and their genetic mapping.
Dumas M-E, Davidovic L, 2015, Metabolic profiling and phenotyping of central nervous system diseases: metabolites bring insights into brain dysfunctions, Journal of Neuroimmune Pharmacology, Vol: 10, Pages: 402-424, ISSN: 1557-1904
Metabolic phenotyping corresponds to the large-scale quantitative and qualitative analysis of the metabolome i.e., the low-molecular weight <1 KDa fraction in biological samples, and provides a key opportunity to advance neurosciences. Proton nuclear magnetic resonance and mass spectrometry are the main analytical platforms used for metabolic profiling, enabling detection and quantitation of a wide range of compounds of particular neuro-pharmacological and physiological relevance, including neurotransmitters, secondary messengers, structural lipids, as well as their precursors, intermediates and degradation products. Metabolic profiling is therefore particularly indicated for the study of central nervous system by probing metabolic and neurochemical profiles of the healthy or diseased brain, in preclinical models or in human samples. In this review, we introduce the analytical and statistical requirements for metabolic profiling. Then, we focus on key studies in the field of metabolic profiling applied to the characterization of animal models and human samples of central nervous system disorders. We highlight the potential of metabolic profiling for pharmacological and physiological evaluation, diagnosis and drug therapy monitoring of patients affected by brain disorders. Finally, we discuss the current challenges in the field, including the development of systems biology and pharmacology strategies improving our understanding of metabolic signatures and mechanisms of central nervous system diseases.
Venkatesh M, Mukherjee S, Wang H, et al., 2014, Symbiotic bacterial metabolites regulate gastrointestinal barrier function via the Xenobiotic sensor PXR and toll-like receptor 4, Immunity, Vol: 41, Pages: 296-310, ISSN: 1074-7613
Intestinal microbial metabolites are conjectured to affect mucosal integrity through an incompletely characterized mechanism. Here we showed that microbial-specific indoles regulated intestinal barrier function through the xenobiotic sensor, pregnane X receptor (PXR). Indole 3-propionic acid (IPA), in the context of indole, is a ligand for PXR in vivo, and IPA downregulated enterocyte TNF-α while it upregulated junctional protein-coding mRNAs. PXR-deficient (Nr1i2−/−) mice showed a distinctly “leaky” gut physiology coupled with upregulation of the Toll-like receptor (TLR) signaling pathway. These defects in the epithelial barrier were corrected in Nr1i2−/−Tlr4−/− mice. Our results demonstrate that a direct chemical communication between the intestinal symbionts and PXR regulates mucosal integrity through a pathway that involves luminal sensing and signaling by TLR4.
Sarafian MH, Gaudin M, Lewis MR, et al., 2014, Objective Set of Criteria for Optimization of Sample Preparation Procedures for Ultra-High Throughput Untargeted Blood Plasma Lipid Profiling by Ultra Performance Liquid Chromatography-Mass Spectrometry, ANALYTICAL CHEMISTRY, Vol: 86, Pages: 5766-5774, ISSN: 0003-2700
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- Citations: 193
Chilloux J, Fearnside J, Rothwell A, et al., 2014, Gut Microbial Metabolite Trimethylamine Inhibits the Toll-Like Receptor (TLR) Inflammation Pathway, Diabetes, Vol: 63
Martin FP, Boulange CL, Montoliu Roura I, et al., 2014, Trimethylamine-N-oxide as biomarker for the predisposition for weight gain and obesity, WO2014086604
The present invention relates generally to the field of nutrition and health. In particular, the present invention relates to a new biomarker, its use and a nnethod that allows it to diagnose the likelihood to resist diet induced weight gain, and/or to be susceptible to a diet induced weight gain. For example, the biomarker may be trimethylamine-N-oxide.
Martin FP, BOULANGE CL, MONTOLIU ROURA I, et al., 2014, Isovalerylglycine as biomarker for the predisposition for weight gain and obesity, WO2014086605
The present invention relates generally to the field of nutrition and health. In particular, the present invention relates to a new biomarker, its use and a method that allows it to diagnose the likelihood to resist diet induced weight gain, and/or to be susceptible to a diet induced weight gain. For example, the biomarker may be isovalerylglycine.
MARTIN FP, Boulange CL, Montoliu Roura I, et al., 2014, Hexanoylglycine as biomarker for the predisposition for weight gain and obesity, WO 2014/086603
The present invention relates generally to the field of nutrition and health. In particular, the present invention relates to a new biomarker, its use and a method that allows it to diagnose the likelihood to resist diet induced weight gain, and/or to be susceptible to a diet induced weight gain. For example, the biomarker may be hexanoylglycine.
Chilloux J, Fearnside JF, Rothwell AR, et al., 2014, Gut Microbial Metabolite Trimethylamine Inhibits the Toll-Like Receptor (TLR) Inflammation Pathway, Publisher: AMER DIABETES ASSOC, Pages: A451-A451, ISSN: 0012-1797
Dumas ME, Hoyles L, Chilloux J, et al., 2014, Gut Microbial Metabolomic Predictors of Dietary-induced Obesity and Diabetes, Publisher: AMER DIABETES ASSOC, Pages: A497-A497, ISSN: 0012-1797
Dumas M-E, Kinross J, Nicholson JK, 2014, Metabolic Phenotyping and Systems Biology Approaches to Understanding Metabolic Syndrome and Fatty Liver Disease, GASTROENTEROLOGY, Vol: 146, Pages: 46-62, ISSN: 0016-5085
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- Citations: 122
Russell WR, Hoyles L, Flint HJ, et al., 2013, Colonic bacterial metabolites and human health, Current Opinion in Microbiology
The influence of the microbial–mammalian metabolic axis is becoming increasingly important for human health. Bacterial fermentation of carbohydrates (CHOs) and proteins produces short-chain fatty acids (SCFA) and a range of other metabolites including those from aromatic amino acid (AAA) fermentation. SCFA influence host health as energy sources and via multiple signalling mechanisms. Bacterial transformation of fibre-related phytochemicals is associated with a reduced incidence of several chronic diseases. The ‘gut–liver axis’ is an emerging area of study. Microbial deconjugation of xenobiotics and release of aromatic moieties into the colon can have a wide range of physiological consequences. In addition, the role of the gut microbiota in choline deficiency in non-alcoholic fatty liver disease (NAFLD) and insulin resistance is receiving increased attention.
Boulange CL, Claus SP, Chou CJ, et al., 2013, Early Metabolic Adaptation in C57BL/6 Mice Resistant to High Fat Diet Induced Weight Gain Involves an Activation of Mitochondrial Oxidative Pathways, JOURNAL OF PROTEOME RESEARCH, Vol: 12, Pages: 1956-1968, ISSN: 1535-3893
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- Citations: 48
Snouber LC, Bunescu A, Naudot M, et al., 2013, Metabolomics-on-a-Chip of Hepatotoxicity Induced by Anticancer Drug Flutamide and Its Active Metabolite Hydroxyflutamide Using HepG2/C3a Microfluidic Biochips, TOXICOLOGICAL SCIENCES, Vol: 132, Pages: 8-20, ISSN: 1096-6080
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- Citations: 62
Dumas M-E, Davidovic L, 2013, Metabolic phenotyping and systems biology approaches to understanding neurological disorders., F1000Prime Rep, Vol: 5, ISSN: 2051-7599
The development of high-throughput metabolic profiling and the study of the metabolome are particularly important in brain research where small molecules or metabolites play fundamental signalling roles: neurotransmitters, signalling lipids, osmolytes and even ions. Metabolic profiling has shown that metabolic perturbations in the brain go beyond alterations of neurotransmission and that variations in brain metabolic homeostasis are associated with neurological disorders. In this report, we will focus on recent developments in the field of metabolic phenotyping that have contributed to unravelling the pathophysiology of neurological diseases. Also, we will highlight the necessity of implementing systems biology approaches to integrate metabolic data and tackle the structural and functional complexity of the brain in normal and pathological conditions.
Dumas ME, Gauguier D, 2012, Mapping metabolomic quantitative trait loci (mQTL): A link between metabolome-wide association studies and systems biology, Genetics Meets Metabolomics: From Experiment to Systems Biology, Pages: 233-254, ISBN: 9781461416883
The comprehensive understanding of metabolism in health and disease has reached a new level with the introduction of Metabolome-Wide Association Studies. Quantitative Trait Locus mapping of metabolic phenotypes (mQTL) is a powerful approach to unravel the genetic component associated with metabolic profiles, and typically identifies genes associated with metabolic markers of disease. In this chapter we describe the various stages of the mQTL mapping strategy, which typically involves a genetically heterogeneous cohort, modern genotyping platforms, hypothesis-free metabolic profiling using high-throughput nuclear magnetic resonance (NMR) spectroscopy or mass spectrometry (MS), generating up to 20,000 metabolic traits per sample and the statistical tools required to map these traits onto the genome of this experimental population. Finally we describe network and systems biology strategies enhancing the biological interpretation of haplotype - metabotype association networks derived from mQTL studies for a better understanding of pathophysiological mechanisms.
Merrifield CA, Lewis MC, Claus SP, et al., 2012, Weaning diet induces sustained metabolic phenotype shift in the pig and influences host response to Bifidobacterium lactis NCC2818, Gut
Background The process of weaning causes a major shift in intestinal microbiota and is a critical period for developing appropriate immune responses in young mammals.Objective To use a new systems approach to provide an overview of host metabolism and the developing immune system in response to nutritional intervention around the weaning period.Design Piglets (n=14) were weaned onto either an egg-based or soya-based diet at 3 weeks until 7 weeks, when all piglets were switched onto a fish-based diet. Half the animals on each weaning diet received Bifidobacterium lactis NCC2818 supplementation from weaning onwards. Immunoglobulin production from immunologically relevant intestinal sites was quantified and the urinary 1H NMR metabolic profile was obtained from each animal at post mortem (11 weeks).Results Different weaning diets induced divergent and sustained shifts in the metabolic phenotype, which resulted in the alteration of urinary gut microbial co-metabolites, even after 4 weeks of dietary standardisation. B lactis NCC2818 supplementation affected the systemic metabolism of the different weaning diet groups over and above the effects of diet. Additionally, production of gut mucosa-associated IgA and IgM was found to depend upon the weaning diet and on B lactis NCC2818 supplementation.Conclusion The correlation of urinary 1H NMR metabolic profile with mucosal immunoglobulin production was demonstrated, thus confirming the value of this multi-platform approach in uncovering non-invasive biomarkers of immunity. This has clear potential for translation into human healthcare with the development of urine testing as a means of assessing mucosal immune status. This might lead to early diagnosis of intestinal dysbiosis and with subsequent intervention, arrest disease development. This system enhances our overall understanding of pathologies under supra-organismal control.
Robinette SL, Holmes E, Nicholson JK, et al., 2012, Genetic determinants of metabolism in health and disease: from biochemical genetics to genome-wide associations, GENOME MEDICINE, Vol: 4, ISSN: 1756-994X
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- Citations: 22
Prot J-M, Bunescu A, Elena-Herrmann B, et al., 2012, Predictive toxicology using systemic biology and liver microfluidic "on chip" approaches: Application to acetaminophen injury, TOXICOLOGY AND APPLIED PHARMACOLOGY, Vol: 259, Pages: 270-280, ISSN: 0041-008X
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- Citations: 53
Shintu L, Baudoin R, Navratil V, et al., 2012, Metabolomics-on-a-Chip and Predictive Systems Toxicology in Microfluidic Bioartificial Organs, ANALYTICAL CHEMISTRY, Vol: 84, Pages: 1840-1848, ISSN: 0003-2700
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- Citations: 84
Mestdagh R, Dumas M-E, Rezzi S, et al., 2012, Gut Microbiota Modulate the Metabolism of Brown Adipose Tissue in Mice, JOURNAL OF PROTEOME RESEARCH, Vol: 11, Pages: 620-630, ISSN: 1535-3893
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- Citations: 72
Cazier J-B, Kaisaki PJ, Argoud K, et al., 2012, Untargeted Metabolome Quantitative Trait Locus Mapping Associates Variation in Urine Glycerate to Mutant Glycerate Kinase, JOURNAL OF PROTEOME RESEARCH, Vol: 11, Pages: 631-642, ISSN: 1535-3893
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- Citations: 21
Prot JM, Bunescu A, Elena-Herrmann B, et al., 2012, Integration of transcriptomic, proteomic and metabolomic profiles in microfluidic bioartificial organs applied to mechanistic interpretation of acetaminophen injury, Pages: 1531-1533
Microfluidic bioartificial organs allow the reproduction of in vivo-like properties such as cell culture in a 3D dynamical micro environment [1]. In this work, we established a method and a protocol for performing the integration of transcriptomic, proteomic and metabolomic profiles in order to investigate xenobiotic toxicity. For that purpose, we present the example of the analysis of HepG2/C3A treated with acetaminophen (APAP) and cultivated in a liver microfluidic biochip.
Ouattara DA, Prot J-M, Bunescu A, et al., 2012, Metabolomics-on-a-chip and metabolic flux analysis for label-free modeling of the internal metabolism of HepG2/C3A cells, MOLECULAR BIOSYSTEMS, Vol: 8, Pages: 1908-1920, ISSN: 1742-206X
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- Citations: 34
Dumas M-E, 2012, Metabolome 2.0: quantitative genetics and network biology of metabolic phenotypes, MOLECULAR BIOSYSTEMS, Vol: 8, Pages: 2494-2502, ISSN: 1742-206X
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- Citations: 42
Dumas ME, Leclerc E, Shintu L, et al., 2011, Method of toxicological evaluation, method of toxicological screening and associated system, WO 2011/151148
The present invention relates to a method of toxicological evaluation of a candidate substance on at least one tissue or organ, characterized in that it comprises the steps of: (a) obtaining a bioartificial tissue or organ by simulation or modelling of the metabolic activity of said tissue or organ by at least one bioreactor; (b) exposure of said bioartificial tissue or organ to said substance; (c) observation of the metabolic response of the bioartificial tissue or organ and acquisition without a priori of an associated multidimensional data set; (d) identification by means of a method of multivariate statistical analysis of the components of the multidimensional data set which are quantitatively correlated with predetennined variables; (e) generation of a predictive model on the basis of the components of the data set that are actually retained; (f) testing of the predictive nature of said model by at least one statistical method of estimating reliability; (g) identification of the metabolic response of the bioartificial tissue or organ in the fonn of biomarkers associated with the components of the data set that are adopted for the model. The present invention also relates to a method of toxicological screening and to a system for this purpose.
Davidovic L, Navratil V, Bonaccorso CM, et al., 2011, A metabolomic and systems biology perspective on the brain of the Fragile X syndrome mouse model, GENOME RESEARCH, Vol: 21, Pages: 2190-2202, ISSN: 1088-9051
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- Citations: 84
Nicholson G, Rantalainen M, Li JV, et al., 2011, A Genome-Wide Metabolic QTL Analysis in Europeans Implicates Two Loci Shaped by Recent Positive Selection, PLOS GENETICS, Vol: 7, ISSN: 1553-7404
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- Citations: 99
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