987 results found
McDonald JAK, Kimhofer T, West K, et al., Role of the gut microbiota in autism spectrum disorder, ISME17, Publisher: Nature Publishing Group
McDonald JAK, Mullish BH, Pechlivanis A, et al., 2018, 24 - A novel route to controlling Clostridioides Difficile growth via short chain fatty acid and bile acid modulation, Digestive Diseases Week, Publisher: Elsevier, Pages: S8-S8, ISSN: 0016-5085
Hoyles L, Jiménez-Pranteda MJ, Chilloux J, et al., 2018, Metabolic retroconversion of trimethylamine N-oxide and the gut microbiota, Microbiome, Vol: 6, ISSN: 2049-2618
Background:The dietary methylamines choline, carnitine, and phosphatidylcholine are used by the gut microbiota to produce a range of metabolites, including trimethylamine (TMA). However, little is known about the use of trimethylamine N-oxide (TMAO) by this consortium of microbes.Results:A feeding study using deuterated TMAO in C57BL6/J mice demonstrated microbial conversion of TMAO to TMA, with uptake of TMA into the bloodstream and its conversion to TMAO. Microbial activity necessary to convert TMAO to TMA was suppressed in antibiotic-treated mice, with deuterated TMAO being taken up directly into the bloodstream. In batch-culture fermentation systems inoculated with human faeces, growth of Enterobacteriaceae was stimulated in the presence of TMAO. Human-derived faecal and caecal bacteria (n = 66 isolates) were screened on solid and liquid media for their ability to use TMAO, with metabolites in spent media analysed by 1H-NMR. As with the in vitro fermentation experiments, TMAO stimulated the growth of Enterobacteriaceae; these bacteria produced most TMA from TMAO. Caecal/small intestinal isolates of Escherichia coli produced more TMA from TMAO than their faecal counterparts. Lactic acid bacteria produced increased amounts of lactate when grown in the presence of TMAO but did not produce large amounts of TMA. Clostridia (sensu stricto), bifidobacteria, and coriobacteria were significantly correlated with TMA production in the mixed fermentation system but did not produce notable quantities of TMA from TMAO in pure culture.Conclusions:Reduction of TMAO by the gut microbiota (predominantly Enterobacteriaceae) to TMA followed by host uptake of TMA into the bloodstream from the intestine and its conversion back to TMAO by host hepatic enzymes is an example of metabolic retroconversion. TMAO influences microbial metabolism depending on isolation source and taxon of gut bacterium. Correlation of metabolomic and abundance data from mixed microbiota fermenta
Hoyles L, Snelling T, Umlai UK, et al., 2018, Microbiome–host systems interactions: protective effects of propionate upon the blood–brain barrier, Microbiome, Vol: 6, ISSN: 2049-2618
Background: Gut microbiota composition and function are symbiotically linked with host health, and altered in metabolic, inflammatory and neurodegenerative disorders. Three recognized mechanisms exist by which the microbiome influences the gut--brain axis: modification of autonomic/sensorimotor connections, immune activation, and neuroendocrine pathway regulation. We hypothesized interactions between circulating gut-derived microbial metabolites and the blood--brain barrier (BBB) also contribute to the gut--brain axis. Propionate, produced from dietary substrates by colonic bacteria, stimulates intestinal gluconeogenesis and is associated with reduced stress behaviours, but its potential endocrine role has not been addressed. Results: After demonstrating expression of the propionate receptor FFAR3 on human brain endothelium, we examined the impact of a physiologically relevant propionate concentration (1 μM) on BBB properties in vitro. Propionate inhibited pathways associated with non-specific microbial infections via a CD14-dependent mechanism, suppressed expression of LRP-1 and protected the BBB from oxidative stress via NRF2 (NFE2L2) signaling. Conclusions: Together, these results suggest gut-derived microbial metabolites interact with the BBB, representing a fourth facet of the gut--brain axis that warrants further attention.
Hoyles L, Snelling T, Umlai U-K, et al., 2018, Propionate has protective and anti-inflammatory effects on the blood–brain barrier, Alzheimer's Research UK Research Conference 2018
Propionate is a short-chain fatty acid (SCFA) produced by the human gut microbiota from dietary substrates, and is biologically active via the G protein coupled receptors FFAR2 and FFAR3. It is taken up from the gut and reaches systemic circulation in micromolar quantities. The blood–brain barrier (BBB) is the major interface between the circulation and central nervous system. FFAR3 is expressed on the vascular endothelium and a likely target for propionate in the BBB. We hypothesized exposure of the BBB to propionate influences barrier integrity and function.Methods and materialsWe investigated the in vitro effects of a physiologically relevant concentration (1 μM) of propionate upon the human immortalised cerebromicrovascular endothelial cell line hCMEC/D3. FFAR3 was present on these cells. We, therefore, performed an unbiased transcriptomic analysis of confluent hCMEC/D3 monolayers treated or not for 24 h with 1 μM propionate, supported by in vitro validation of key findings and assessment of functional endothelial permeability barrier properties.ResultsPropionate treatment had a significant (PFDR < 0.1) effect on the expression of 1136 genes. It inhibited several inflammation-associated pathways: TLR-specific signalling, NFkappaB signalling, and cytosolic DNA-sensing. Functional validation of these findings confirmed the down-regulation of TLR signalling by propionate, achieved primarily through down-regulation of endothelial CD14 expression. Accordingly, propionate prevented LPS-induced increases in paracellular permeability to 70 kDa FITC-dextran and loss of transendothelial electrical resistance. Propionate activated the NFE2L2 (NRF2)-driven protective response against oxidative stress. Confirming these data, propionate limited free reactive oxygen species induction by the mitochondrial respiratory inhibitor rotenone. ConclusionsOur data strongly suggest the SCFA propionate contributes to maintaining BBB integrity and protecting against inflamm
McArthur S, Carvalho A, Fonseca S, et al., 2018, Effects of gut-derived trimethylamines on the blood–brain barrier, Alzheimer's Research UK Research Conference 2018
Introduction: The gut microbiota and its metabolites exert significant effects on host health, with disturbances to composition and function associated with conditions including obesity, type II diabetes and, more recently, Alzheimer’s disease (AD). Communication between microbes and the host can take a number of forms, but central to all of them is a role for gut-derived microbial metabolites, with trimethylamine N-oxide (TMAO) and its precursor trimethylamine (TMA) being important examples. TMA produced by gut bacteria is converted to TMAO in the liver by flavin monooxygenases whereupon it enters the circulation. TMAO was recently identified as potentially important in genetic pathways associated with AD, and has been shown to influence peripheral vascular function. Given these links, the key position of the cerebral vasculature as the major interface between circulating molecules and the brain, and evidence that deficits in blood–brain barrier (BBB) function occur early in AD, we investigated the effects of TMAO and TMA on key BBB properties in vitro and in vivo.Materials and Methods: Male C57Bl/6 mice (n=4-5) were used to examine the effect of TMAO treatment (1.8 mg/kg, 2 h, dose equivalent to circulating human concentrations) upon BBB permeability in vivo, assessed by Evans’ blue dye extravasation. TMA was not investigated as the average mouse plasma concentration of this methylamine is substantially greater than that seen in humans (TMAO-to-TMA ratio 1:10 in mice, 10:1 in humans).Human hCMEC/D3 cerebromicrovascular cells were used as an in vitro model of the BBB to investigate the effects of 24 h treatment with human physiologically relevant doses of TMAO (40 μM) and TMA (0.4 μM), studying (i) functional barrier properties of cell monolayers and (ii) gene expression. Results: Administration of TMAO to mice enhanced BBB integrity above baseline after 2 h treatment (p<0.05). Similarly, in vitro exposure of hCMEC/D3 cells to TMAO enhanc
Hoyles L, Snelling T, Umlai U-K, et al., 2018, Microbiome–host interactions: protective effects of propionate upon the blood–brain barrier, Publisher: biorixiv
Breakdown of foodstuffs by the gut microbiota results in the production of the short-chain fatty acids (SCFAs) acetate, propionate and butyrate. SFCAs are potent bioactive molecules, providing energy for intestinal cells, enhancing satiety and positively influencing metabolic health. They also influence the gut–brain axis. The gut microbiota and/or its bioactive molecules contribute to maintaining the integrity of the blood–brain barrier (BBB), the primary defensive structure of the brain. Propionate is produced by the gut microbiota from the breakdown of glucans found in whole grains, mushrooms and yeast products. It is found in the blood at ≤1 μM. At this physiologically relevant concentration, propionate enhances BBB integrity, mitigating against deleterious inflammatory and oxidative stimuli known to contribute to neurological and psychological diseases. Therefore, there is the potential that dietary supplementation with glucan-containing products may offer protection of the brain against detrimental stimuli.
Athersuch TJ, Antoine DJ, Boobis AR, et al., 2018, Paracetamol metabolism, hepatotoxicity, biomarkers and therapeutic interventions: a perspective, Toxicology Research, Vol: 7, Pages: 347-357, ISSN: 2045-452X
After over 60 years of therapeutic use in the UK, paracetamol (acetaminophen, N-acetyl-p-aminophenol, APAP) remains the subject of considerable research into both its mode of action and toxicity. The pharmacological properties of APAP are the focus of some activity, with the role of the metabolite N-arachidonoylaminophenol (AM404) still a topic of debate. However, that the hepatotoxicity of APAP results from the production of the reactive metabolite N-acetyl-p-benzoquinoneimine (NAPQI/NABQI) that can deplete glutathione, react with cellular macromolecules, and initiate cell death, is now beyond dispute. The disruption of cellular pathways that results from the production of NAPQI provides a source of potential biomarkers of the severity of the damage. Research in this area has provided new diagnostic markers such as the microRNA miR-122 as well as mechanistic biomarkers associated with apoptosis, mitochondrial dysfunction, inflammation and tissue regeneration. Additionally, biomarkers of, and systems biology models for, glutathione depletion have been developed. Furthermore, there have been significant advances in determining the role of both the innate immune system and genetic factors that might predispose individuals to APAP-mediated toxicity. This perspective highlights some of the progress in current APAP-related research.
Veselkov KA, Sleeman J, Claude E, et al., 2018, BASIS: High-performance bioinformatics platform for processing of large-scale mass spectrometry imaging data in chemically augmented histology, Scientific Reports, Vol: 8, ISSN: 2045-2322
Mass Spectrometry Imaging (MSI) holds significant promise in augmenting digital histopathologic analysis by generating highly robust big data about the metabolic, lipidomic and proteomic molecular content of the samples. In the process, a vast quantity of unrefined data, that can amount to several hundred gigabytes per tissue section, is produced. Managing, analysing and interpreting this data is a significant challenge and represents a major barrier to the translational application of MSI. Existing data analysis solutions for MSI rely on a set of heterogeneous bioinformatics packages that are not scalable for the reproducible processing of large-scale (hundreds to thousands) biological sample sets. Here, we present a computational platform (pyBASIS) capable of optimized and scalable processing of MSI data for improved information recovery and comparative analysis across tissue specimens using machine learning and related pattern recognition approaches. The proposed solution also provides a means of seamlessly integrating experimental laboratory data with downstream bioinformatics interpretation/analyses, resulting in a truly integrated system for translational MSI.
van Golen RF, Olthof PB, de Haan LR, et al., 2018, The pathophysiology of human obstructive cholestasis is mimicked in cholestatic Gold Syrian hamsters, BIOCHIMICA ET BIOPHYSICA ACTA-MOLECULAR BASIS OF DISEASE, Vol: 1864, Pages: 942-951, ISSN: 0925-4439
Loo RL, Zou X, Appel LJ, et al., 2018, Characterization of metabolic responses to healthy diets and association with blood pressure: application to the Optimal Macronutrient Intake Trial for Heart Health (OmniHeart), a randomized controlled study, AMERICAN JOURNAL OF CLINICAL NUTRITION, Vol: 107, Pages: 323-334, ISSN: 0002-9165
BackgroundInterindividual variation in the response to diet is common, but the underlying mechanism for such variation is unclear.ObjectiveThe objective of this study was to use a metabolic profiling approach to identify a panel of urinary metabolites representing individuals demonstrating typical (homogeneous) metabolic responses to healthy diets, and subsequently to define the association of these metabolites with improvement of risk factors for cardiovascular diseases (CVDs).Design24-h urine samples from 158 participants with pre-hypertension and stage 1 hypertension, collected at baseline and following the consumption of a carbohydrate-rich, a protein-rich, and a monounsaturated fat–rich healthy diet (6 wk/diet) in a randomized, crossover study, were analyzed by proton (1H) nuclear magnetic resonance (NMR) spectroscopy. Urinary metabolite profiles were interrogated to identify typical and variable responses to each diet. We quantified the differences in absolute excretion of metabolites, distinguishing between dietary comparisons within the typical response groups, and established their associations with CVD risk factors using linear regression.ResultsGlobally all 3 diets induced a similar pattern of change in the urinary metabolic profiles for the majority of participants (60.1%). Diet-dependent metabolic variation was not significantly associated with total cholesterol or low-density lipoprotein (LDL) cholesterol concentration. However, blood pressure (BP) was found to be significantly associated with 6 urinary metabolites reflecting dietary intake [proline-betaine (inverse), carnitine (direct)], gut microbial co-metabolites [hippurate (direct), 4-cresyl sulfate (inverse), phenylacetylglutamine (inverse)], and tryptophan metabolism [N-methyl-2-pyridone-5-carboxamide (inverse)]. A dampened clinical response was observed in some individuals with variable metabolic responses, which could be attributed to nonadherence to diet (≤25.3%), variation in gut mi
Posma JM, Garcia Perez I, Ebbels TMD, et al., 2018, Optimized phenotypic biomarker discovery and confounder elimination via covariate-adjusted projection to latent structures from metabolic spectroscopy data, Journal of Proteome Research, Vol: 17, Pages: 1586-1595, ISSN: 1535-3893
Metabolism is altered by genetics, diet, disease status, environment and many other factors. Modelling either one of these is often done without considering the effects of the other covariates. Attributing differences in metabolic profile to one of these factors needs to be done while controlling for the metabolic influence of the rest. We describe here a data analysis framework and novel confounder-adjustment algorithm for multivariate analysis of metabolic profiling data. Using simulated data we show that similar numbers of true associations and significantly less false positives are found compared to other commonly used methods. Covariate-Adjusted Projections to Latent Structures (CA-PLS) is exemplified here using a large-scale metabolic phenotyping study of two Chinese populations at different risks for cardiovascular disease. Using CA-PLS we find that some previously reported differences are actually associated with external factors and discover a number of previously unreported biomarkers linked to different metabolic pathways. CA-PLS can be applied to any multivariate data where confounding may be an issue and the confounder-adjustment procedure is translatable to other multivariate regression techniques.
MacIntyre DA, Brown R, Marchesi J, et al., 2018, Vaginal dysbiosis increases risk of preterm fetal membrane rupture, neonatal sepsis and is exacerbated by erythromycin, BMC Medicine, Vol: 16, ISSN: 1741-7015
Background: Preterm prelabour rupture of the fetal membranes (PPROM) precedes 30% of preterm births and is a risk factor for early onset neonatal sepsis. As PPROM is strongly associated with ascending vaginal infection prophylactic antibiotics are widely used. The evolution of vaginal microbiota composition associated with PPROM and the impact of antibiotics on bacterial composition is unknown. Methods: We prospectively assessed vaginal microbiota prior to and following PPROM using MiSeq-based sequencing of 16S rRNA gene amplicons and examined the impact of erythromycin prophylaxis on bacterial load and community structures.Results: In contrast to pregnancies delivering at term, vaginal dysbiosis characterised by Lactobacillus spp. depletion, was present prior to the rupture of fetal membranes in approximately a third of cases (0% versus 27%, P= 0.026) and persisted following membrane rupture (31%, P= 0.005). Vaginal dysbiosis was exacerbated by erythromycin treatment (47%, P= 0.00009) particularly in women initially colonised by Lactobacillus species. Lactobacillus depletion and increased relative abundance of Sneathia spp. was associated with subsequent funisitis and early onset neonatal sepsis. Conclusions:Our data show that vaginal microbiota composition is a risk-factor for subsequent PPROM and is associated with adverse short-term maternal and neonatal outcomes. This highlights vaginal microbiota as a potentially modifiable antenatal risk factor for PPROM and suggests that routine use of erythromycin for PPROM be re-examined.
Hoyles L, Jiménez-Pranteda ML, Chilloux J, et al., 2017, Metabolic retroconversion of trimethylamine N-oxide and the gut microbiota, Publisher: Cold Spring Harbor Laboratory
<jats:title>ABSTRACT</jats:title><jats:sec><jats:title>BACKGROUND</jats:title><jats:p>The dietary methylamines choline, carnitine and phosphatidylcholine are used by the gut microbiota to produce a range of metabolites, including trimethylamine (TMA). However, little is known about the use of trimethylamine <jats:italic>N</jats:italic>-oxide (TMAO) by this consortium of microbes.</jats:p></jats:sec><jats:sec><jats:title>RESULTS</jats:title><jats:p>A feeding study using deuterated TMAO in C57BL6/J mice demonstrated microbial conversion of TMAO to TMA, with uptake of TMA into the bloodstream and its conversion to TMAO. Microbial activity necessary to convert TMAO to TMA was suppressed in antibiotic-treated mice, with deuterated TMAO being taken up directly into the bloodstream. In batch-culture fermentation systems inoculated with human faeces, growth of <jats:italic>Enterobacteriaceae</jats:italic> was stimulated in the presence of TMAO. Human-derived faecal and caecal bacteria (<jats:italic>n</jats:italic> = 66 isolates) were screened on solid and liquid media for their ability to use TMAO, with metabolites in spent media analysed by <jats:sup>1</jats:sup>H-NMR. As with the <jats:italic>in vitro</jats:italic> fermentation experiments, TMAO stimulated the growth of <jats:italic>Enterobacteriaceae</jats:italic>; these bacteria produced most TMA from TMAO. Caecal/small intestinal isolates of <jats:italic>Escherichia coli</jats:italic> produced more TMA from TMAO than their faecal counterparts. Lactic acid bacteria produced increased amounts of lactate when grown in the presence of TMAO, but did not produce large amounts of TMA. Clostridia (<jats:italic>sensu stricto</jats:italic>), bifidobacteria and coriobacteria were significantly correlated with TMA production in the mixed fermentation system but did
Galea D, Inglese P, Cammack L, et al., 2017, Translational utility of a hierarchical classification strategy in biomolecular data analytics., Scientific Reports, Vol: 7, ISSN: 2045-2322
Hierarchical classification (HC) stratifies and classifies data from broad classes into more specific classes. Unlike commonly used data classification strategies, this enables the probabilistic prediction of unknown classes at different levels, minimizing the burden of incomplete databases. Despite these advantages, its translational application in biomedical sciences has been limited. We describe and demonstrate the implementation of a HC approach for "omics-driven" classification of 15 bacterial species at various taxonomic levels achieving 90-100% accuracy, and 9 cancer types into morphological types and 35 subtypes with 99% and 76% accuracy, respectively. Unknown bacterial species were probabilistically assigned with 100% accuracy to their respective genus or family using mass spectra (n = 284). Cancer types were predicted by mRNA data (n = 1960) for most subtypes with 95-100% accuracy. This has high relevance in clinical practice where complete datasets are difficult to compile with the continuous evolution of diseases and emergence of new strains, yet prediction of unknown classes, such as bacterial species, at upper hierarchy levels may be sufficient to initiate antimicrobial therapy. The algorithms presented here can be directly translated into clinical-use with any quantitative data, and have broad application potential, from unlabeled sample identification, to hierarchical feature selection, and discovery of new taxonomic variants.
Rodriguez-Martinez A, Posma JM, Ayala R, et al., 2017, J-Resolved (1)H NMR 1D-Projections for Large-Scale Metabolic Phenotyping Studies: Application to Blood Plasma Analysis., Analytical Chemistry, Vol: 89, Pages: 11405-11412, ISSN: 0003-2700
(1)H nuclear magnetic resonance (NMR) spectroscopy-based metabolic phenotyping is now widely used for large-scale epidemiological applications. To minimize signal overlap present in 1D (1)H NMR spectra, we have investigated the use of 2D J-resolved (JRES) (1)H NMR spectroscopy for large-scale phenotyping studies. In particular, we have evaluated the use of the 1D projections of the 2D JRES spectra (pJRES), which provide single peaks for each of the J-coupled multiplets, using 705 human plasma samples from the FGENTCARD cohort. On the basis of the assessment of several objective analytical criteria (spectral dispersion, attenuation of macromolecular signals, cross-spectral correlation with GC-MS metabolites, analytical reproducibility and biomarker discovery potential), we concluded that the pJRES approach exhibits suitable properties for implementation in large-scale molecular epidemiology workflows.
Bray R, Cacciatore S, Jimenez B, et al., 2017, Urinary metabolic phenotyping of women with lower urinary tract symptoms, Journal of Proteome Research, Vol: 16, Pages: 4208-4216, ISSN: 1535-3893
Lower urinary tract symptoms (LUTS), including urinary incontinence, urgency and nocturia, affect approximately half of women worldwide. Current diagnostic methods for LUTS are invasive and costly, while available treatments are limited by side effects leading to poor patient compliance. In this study, we aimed to identify urine metabolic signatures associated with LUTS using proton nuclear magnetic resonance (1H NMR) spectroscopy. A total of 214 urine samples were collected from women attending tertiary urogynecology clinics (cases; n = 176) and healthy control women attending general gynecology clinics (n = 36). Despite high variation in the urine metabolome across the cohort, associations between urine metabolic profiles and BMI, parity, overactive bladder syndrome, frequency, straining, and bladder storage were identified using KODAMA (knowledge discovery by accuracy maximization). Four distinct urinary metabotypes were identified, one of which was associated with increased urinary frequency and low BMI. Urine from these patients was characterized by increased levels of isoleucine and decreased levels of hippurate. Our study suggests that metabolic profiling of urine samples from LUTS patients offers the potential to identify differences in underlying etiology, which may permit stratification of patient populations and the design of more personalized treatment strategies.
Hoyles L, Fernández-Real JM, Federici M, et al., 2017, Integrated systems biology to study the contribution of the gut microbiome to steatosis in obese women, Exploring Human Host-Microbiome Interactions in Health and Disease
Non-alcoholic fatty liver disease (NAFLD) is one of the most common causes of chronic liver disease, increasing in worldwide prevalence as a result of the obesity epidemic. It manifests in hepatic cells as steatosis with or without lobular inflammation and/or ballooning. Animal and human studies have suggested the gut microbiome contributes to steatosis/NAFLD. The aim of this study was to use an integrated approach with various -omics and clinical data to evaluate the contribution of the gut microbiome to the molecular phenome (hepatic transcriptome, metabonome) of steatosis. Metagenomic (faecal microbiome), transcriptomic (liver biopsy), metabonomic (plasma and urine, 1H-NMR) and clinical data were collected for 56 morbidly obese (BMI >35) women from Italy (n = 31) and Spain (n = 25) who elected for bariatric surgery. Confounder analyses of clinical data were done using linear modelling. Histological examination of liver biopsies was used to grade steatosis. Faecal metagenomes were generated and analysed using the SCalable Automated Metagenomics Pipeline (SCAMP). Differentially expressed genes were identified in hepatic transcriptomes, and analysed using a range of different bioinformatics tools. 1H-NMR data were generated for plasma and urinary metabonomes. Clinical, metagenomic, transcriptomic and metabonomic data were integrated in the context of steatosis using partial Spearman's correlation, taking confounders (age, body mass index and cohort) into account. Steatosis was anti-correlated with microbial gene richness, and correlated with abundance of Proteobacteria. KEGG analyses of metagenomic data suggested increased microbial processing of dietary lipids and amino acids, as well as endotoxin-related processes related to Proteobacteria. Steatosis-associated hepatic transcriptomes were associated with branched-chain amino acid (BCAA) metabolism, endoplasmic reticulum/phagosome, and immune responses associated with non-specific microbial infections. Metabonom
Hoyles L, Snelling T, Umlai UK, et al., 2017, Propionate has protective and anti-inflammatory effects on the blood–brain barrier, Exploring Human Host-Microbiome Interactions in Health and Disease
Production of short-chain fatty acids (SCFAs) from dietary substrates by the gut microbiota is associated with health, with these metabolites influencing the host via the ‘gut–brain axis’. Micromolar quantities of microbially derived SCFAs are taken up from the gut and reach systemic circulation, where they can influence host gene expression through a variety of largely unknown mechanisms. The blood–brain barrier (BBB) is the major interface between the circulation and central nervous system, and is critically involved in the pathogenesis of neuroinflammatory disorders such as stroke and vascular dementia. We hypothesized exposure of the BBB to SCFAs influences barrier integrity and function.To test our hypothesis, we investigated the in vitro effects of a physiologically relevant concentration (1 μM) of propionate upon the human immortalised cerebromicrovascular endothelial cell line hCMEC/D3. Propionate is produced by the microbiota from dietary glucans, and is biologically active via the G protein coupled receptors FFAR2 and FFAR3. It is a highly potent FFAR2 agonist (agonist activity 3.99) and has close to optimal ligand efficiency (-ΔG=1.19 kcal mol-1 atom-1) for this receptor. Notably, FFAR3 is expressed on the vascular endothelium and a likely target for propionate in the BBB.After confirming the presence of FFAR3 on hCMEC/D3 cells, we undertook an unbiased transcriptomic analysis of confluent hCMEC/D3 monolayers treated or not for 24 h with 1 μM propionate, supported by in vitro validation of key findings and assessment of functional endothelial permeability barrier properties.Propionate treatment had a significant (PFDR < 0.1) effect on the expression of 1136 genes: 553 upregulated, 583 downregulated. Propionate inhibited several inflammation-associated pathways: namely, TLR-specific signalling, NFkappaB signalling, and cytosolic DNA-sensing. Functional validation of these findings confirmed the down-regulation of TLR
Kinross J, Mirnezami R, Alexander J, et al., 2017, A prospective analysis of mucosal microbiome-metabonome interactions in colorectal cancer using a combined MAS 1HNMR and metataxonomic strategy, Scientific Reports, Vol: 7, ISSN: 2045-2322
Colon cancer induces a state of mucosal dysbiosis with associated niche specific changes in the gut microbiota. However, the key metabolic functions of these bacteria remain unclear. We performed a prospective observational study in patients undergoing elective surgery for colon cancer without mechanical bowel preparation (n = 18). Using 16 S rRNA gene sequencing we demonstrated that microbiota ecology appears to be cancer stage-specific and strongly associated with histological features of poor prognosis. Fusobacteria (p < 0.007) and ε- Proteobacteria (p < 0.01) were enriched on tumour when compared to adjacent normal mucosal tissue, and fusobacteria and β-Proteobacteria levels increased with advancing cancer stage (p = 0.014 and 0.002 respecitvely). Metabonomic analysis using 1H Magic Angle Spinning Nuclear Magnetic Resonsance (MAS-NMR) spectroscopy, demonstrated increased abundance of taurine, isoglutamine, choline, lactate, phenylalanine and tyrosine and decreased levels of lipids and triglycerides in tumour relative to adjacent healthy tissue. Network analysis revealed that bacteria associated with poor prognostic features were not responsible for the modification of the cancer mucosal metabonome. Thus the colon cancer mucosal microbiome evolves with cancer stage to meet the demands of cancer metabolism. Passenger microbiota may play a role in the maintenance of cancer mucosal metabolic homeostasis but these metabolic functions may not be stage specific.
castagne R, Boulange CL, Karaman I, et al., 2017, Improving visualisation and interpretation of metabolome-wide association studies (MWAS): an application in a population-based cohort using untargeted 1H NMR metabolic profiling., Journal of Proteome Research, Vol: 16, Pages: 3623-3633, ISSN: 1535-3893
1H NMR spectroscopy of biofluids generates reproducible data allowing detection and quantification of small molecules in large population cohorts. Statistical models to analyze such data are now well-established, and the use of univariate metabolome wide association studies (MWAS) investigating the spectral features separately has emerged as a computationally efficient and interpretable alternative to multivariate models. The MWAS rely on the accurate estimation of a metabolome wide significance level (MWSL) to be applied to control the family wise error rate. Subsequent interpretation requires efficient visualization and formal feature annotation, which, in-turn, call for efficient prioritization of spectral variables of interest. Using human serum 1H NMR spectroscopic profiles from 3948 participants from the Multi-Ethnic Study of Atherosclerosis (MESA), we have performed a series of MWAS for serum levels of glucose. We first propose an extension of the conventional MWSL that yields stable estimates of the MWSL across the different model parameterizations and distributional features of the outcome. We propose both efficient visualization methods and a strategy based on subsampling and internal validation to prioritize the associations. Our work proposes and illustrates practical and scalable solutions to facilitate the implementation of the MWAS approach and improve interpretation in large cohort studies.
Rodriguez Martinez A, Posma JM, Ayala R, et al., 2017, MWASTools: an R/Bioconductor package for metabolome-wide association studies, Bioinformatics, Vol: 34, Pages: 890-892, ISSN: 1367-4803
Summary: MWASTools is an R package designed to provide an integrated pipeline to analyze metabonomic data in large-scale epidemiological studies. Key functionalities of our package include: quality control analysis; metabolome-wide association analysis using various models (partial correlations, generalized linear models); visualization of statistical outcomes; metabolite assignment using statistical total correlation spectroscopy (STOCSY); and biological interpretation of MWAS results.Availability: The MWASTools R package is implemented in R (version > =3.4) and is available from Bioconductor: https://bioconductor.org/packages/MWASTools/
Lewis MC, Merrifield CA, Berger B, et al., 2017, Early intervention with Bifidobacterium lactis NCC2818 modulates the host-microbe interface independent of the sustained changes induced by the neonatal environment., Scientific Reports, Vol: 7, ISSN: 2045-2322
Inflammatory and metabolic diseases can originate during early-life and have been correlated with shifts in intestinal microbial ecology. Here we demonstrate that minor environmental fluctuations during the early neonatal period had sustained effects on the developing porcine microbiota and host-microbe interface. These inter-replicate effects appear to originate during the first day of life, and are likely to reflect very early microbiota acquisition from the environment. We statistically link early systemic inflammation with later local increases in inflammatory cytokine (IL-17) production, which could have important enteric health implications. Immunity, intestinal barrier function, host metabolism and host-microbiota co-metabolism were further modified by Bifidobacterium lactis NCC2818 supplementation, although composition of the in situ microbiota remained unchanged. Finally, our robust model identified novel, strong correlations between urinary metabolites (eg malonate, phenylacetylglycine, alanine) and mucosal immunoglobulin (IgM) and cytokine (IL-10, IL-4) production, thus providing the possibility of the development of urinary 'dipstick' tests to assess non-accessible mucosal immune development and identify early precursors (biomarkers) of disease. These results have important implications for infants exposed to neonatal factors including caesarean delivery, antibiotic therapy and delayed discharge from hospital environments, which may predispose to the development of inflammatory and metabolic diseases in later life.
Dumas M, Rothwell AR, Hoyles L, et al., 2017, Microbial-host co-metabolites are prodromal markers predicting phenotypic heterogeneity in behavior, obesity and impaired glucose tolerance, Cell Reports, Vol: 20, Pages: 136-148, ISSN: 2211-1247
The influence of the gut microbiome on metabolic and behavioral traits is now widely accepted, though the microbiome-derived metabolites involved remain unclear. We carried out untargeted urine 1H NMR spectroscopy-based metabolic phenotyping in an isogenic C57BL/6J mouse population (n=50) and show that microbial-host co-metabolites are prodromal (i.e., early) markers predicting future divergence in metabolic (obesity and glucose homeostasis) and behaviorial (anxiety and activity) outcomes with 94-100% accuracy. Some of these metabolites also modulate disease phenotypes, best illustrated by trimethylamine-N-oxide (TMAO), a product of microbial-host co-metabolism predicting future obesity, impaired glucose tolerance (IGT) and behavior, whilst reducing endoplasmic reticulum stress and lipogenesis in 3T3-L1 adipocytes. Chronic in vivo TMAO treatment limits IGT in HFD-fed mice and isolated pancreatic islets by increasing insulin secretion. We highlight the prodromal potential of microbial metabolites to predict disease outcomes and their potential in shaping mammalian phenotypic heterogeneity.
Hoyles L, Fernández-Real JM, Federici M, et al., 2017, Integrated systems biology to study non-alcoholic fatty liver disease in obese women, International Scientific Association for Probiotics and Prebiotics
Metagenomic (faecal microbiome), transcriptomic (liver biopsy), metabonomic (plasma and urine, 1H-NMR) and clinical (28 variables) data were collected for 56 morbidly obese (BMI >35) women from Italy (n = 31) and Spain (n = 25) who elected for bariatric surgery. Data were integrated to evaluate the contribution of the gut microbiome to the molecular phenome (hepatic transcriptome, plasma and urine metabonome) of NAFLD independent of clinical confounders (age, BMI, cohort) using partial Spearman’s correlation. NAFLD activity score (NAS) was anti-correlated with microbial gene richness, and correlated with abundance of Proteobacteria. KEGG analyses of metagenomic data suggested increased microbial processing of dietary lipids and amino acids, as well as endotoxin-related processes related to Proteobacteria. Metabonomic profiles highlighted imbalances in choline metabolism, branched-chain amino acid (BCAA) metabolism and gut-derived microbial metabolites resulting from metabolism of amino acids. NAFLD-associated hepatic transcriptomes were associated with BCAA metabolism, endoplasmic reticulum/phagosome, and immune responses associated with non-specific microbial infections. Molecular phenomic signatures were stable and predictive regardless of sample size, and consistent with the microbiome making a significant contribution to the NAFLD phenome. There is disruption of the gut– liver axis in NAFLD, which can be seen in the gut microbiome, hepatic transcriptome and urinary and plasma metabonomes. Consistency of phenome signatures strongly supports a relationship between microbial amino acid metabolism and microbial gene richness, hepatic gene expression and biofluid metabonomes, and ultimately NAS.
Rainville PD, Wilson ID, Nicholson JK, et al., 2017, Ion Mobility Spectrometry Combined With Ultra Performance Liquid Chromatography/Mass Spectrometry For Metabolic Phenotyping of Urine: Effects of Column Length, Gradient Duration and Ion Mobility Spectrometry on Metabolite Detection., Analytica Chimica Acta, Vol: 982, Pages: 1-8, ISSN: 1873-4324
The need for rapid and efficient high throughput metabolic phenotyping (metabotyping) in metabolomic/metabonomic studies often requires compromises to be made between analytical speed and metabolome coverage. Here the effect of column length (150, 75 and 30 mm) and gradient duration (15, 7.5 and 3 min respectively) on the number of features detected when untargeted metabolic profiling of human urine using reversed-phase gradient ultra performance chromatography with, and without, ion mobility spectrometry, has been examined. As would be expected, reducing column length from 150 to 30 mm, and gradient duration, from 15 to 3 min, resulted in a reduction in peak capacity from 311 to 63 and a similar reduction in the number of features detected from over ca. 16,000 to ca. 6500. Under the same chromatographic conditions employing UPLC/IMS/MS to provide an additional orthogonal separation resulted in an increase in the number of MS features detected to nearly 20,000 and ca. 7500 for the 150 mm and the 30 mm columns respectively. Based on this limited study the potential of LC/IMS/MS as a tool for improving throughput and increasing metabolome coverage clearly merits further in depth study.
Hoyles L, Fernandez-Real JM, Federici M, et al., 2017, Integrated systems biology to study non-alcoholic fatty liver disease in obese women, Tranlsational Bioinformatics
Non-alcoholic fatty liver disease (NAFLD) is a multifactorial condition and one of the most common causes of chronic liver disease, with increasing worldwide prevalence. Microbiome-associated lipopolysaccharides (LPS) are associated with NAFLD in rodent models, but their relevance in human liver disease is not understood. In addition, microbiome-driven degradation of dietary choline – and its subsequent removal from host-associated metabolic processes – is thought to contribute to development of NAFLD. The FLORINASH study set out to determine the contribution of the gut microbiome to the NAFLD-associated molecular phenome (transcriptome, metabonome) independent of clinical confounders.Morbidly obese women [body mass index (BMI) >35] from Italy (n = 31) and Spain (n = 25) who elected for bariatric surgery were recruited to the study. Clinical data (28 variables) were recorded. Faecal samples, liver biopsies, blood and urine samples were collected. Faecal metagenomes were analysed using an in-house metagenomics pipeline (SCaleble Automated Metagenomics Pipeline). NAFLD activity score (NAS; 0, 1, 2, 3) was determined by histological examination of liver biopsies. Differentially expressed genes in hepatic transcriptomes were identified, and analysed using several complementary tools. 1H-NMR data were generated for plasma and urinary metabonomes. Clinical, metagenomic, transcriptomic and metabonomic data were integrated using partial Spearman’s correlation, taking identified confounders (age, BMI and cohort) into account.NAS was anti-correlated with microbial gene richness, and correlated with abundance of Gram-negative Proteobacteria. KEGG analyses of metagenomic data suggested increased microbial processing of dietary lipids and amino acids, as well as LPS-related processes associated with Proteobacteria in NAFLD. Activation of immune responses associated with Gram-negative (LPS-associated) microbial infections was correlated with NAS in hepatic tr
Swann JR, Garcia-Perez I, Braniste V, et al., 2017, Application of 1H NMR spectroscopy to the metabolic phenotyping of rodent brain extracts: a metabonomic study of gut microbial influence on host brain metabolism, Journal of Pharmaceutical and Biomedical Analysis, Vol: 143, Pages: 141-146, ISSN: 1873-264X
H NMR Spectroscopy has been applied to determine the neurochemical profiles of brain extracts from the frontal cortex and hippocampal regions of germ free and normal mice and rats. The results revealed a number of differences between germ free (GF) and conventional (CV) rats or specific pathogen-free (SPF) mice with microbiome-associated metabolic variation found to be both species- and region-dependent. In the mouse, the GF frontal cortex contained lower amounts of creatine, N-acetyl-aspartate (NAA), glycerophosphocholine and lactate, but greater amounts of choline compared to that of specific pathogen free (SPF) mice. In the hippocampus, the GF mice had greater creatine, NAA, lactate and taurine content compared to those of the SPF animals, but lower relative quantities of succinate and an unidentified lipid-related component. The GF rat frontal cortex contained higher relative quantities of lactate, creatine and NAA compared to the CV animals whilst the GF hippocampus was characterized by higher taurine and phosphocholine concentrations and lower quantities of NAA, N-acetylaspartylglutamate and choline compared to the CV animals. Of note is that, in both rat and mouse brain extracts, concentrations of hippocampal taurine were found to be greater in the absence of an established microbiome. The results provide further evidence that brain biochemistry can be influenced by gut microbial status, specifically metabolites involved in energy metabolism demonstrating biochemical dialogue between the microbiome and brain.
Wolfer AM, Scott AJ, Rueb C, et al., 2017, Longitudinal analysis of serum oxylipin profile as a novel descriptor of the inflammatory response to surgery, JOURNAL OF TRANSLATIONAL MEDICINE, Vol: 15, ISSN: 1479-5876
Background:Oxylipins are potent lipid mediators demonstrated to initiate and regulate inflammation yet little is known regarding their involvement in the response to surgical trauma. As key modulators of the inflammatory response, oxylipins have the potential to provide novel insights into the physiological response to surgery and the pathophysiology of post-operative complications. We aimed to investigate the effects of major surgery on longitudinal oxylipin profile.Methods:Adults patients undergoing elective laparoscopic or open colorectal resections were included. Primary outcomes were serum oxylipin profile quantified by ultra high-performance liquid chromatography-mass spectrometry, serum white cell count and C-reactive protein concentration. Serum samples were taken at three time-points: pre-operative (day zero), early post-operative (day one) and late post-operative (day four/five).Results:Some 55 patients were included, of which 33 (60%) underwent surgery that was completed laparoscopically. Pre-operative oxylipin profiles were characterised by marked heterogeneity but surgery induced a common shift resulting in more homogeneity at the early post-operative time-point. By the late post-operative phase, oxylipin profiles were again highly variable. This evolution was driven by time-dependent changes in specific oxylipins. Notably, the levels of several oxylipins with anti-inflammatory properties (15-HETE and four regioisomers of DHET) were reduced at the early post-operative point before returning to baseline by the late post-operative period. In addition, levels of the pro-inflammatory 11-HETE rose in the early post-operative phase while levels of anti-thrombotic mediators (9-HODE and 13-HODE) fell; concentrations of all three oxylipins then remained fairly static from early to late post-operative phases. Compared to those undergoing laparoscopic surgery, patients undergoing open surgery had lower levels of some anti-inflammatory oxylipins (8,9-DHET and 17-HD
Xie G, Wang X, Zhao A, et al., 2017, Sex-dependent effects on gut microbiota regulate hepatic carcinogenic outcomes., Sci Rep, Vol: 7
Emerging evidence points to a strong association between sex and gut microbiota, bile acids (BAs), and gastrointestinal cancers. Here, we investigated the mechanistic link between microbiota and hepatocellular carcinogenesis using a streptozotocin-high fat diet (STZ-HFD) induced nonalcoholic steatohepatitis-hepatocellular carcinoma (NASH-HCC) murine model and compared results for both sexes. STZ-HFD feeding induced a much higher incidence of HCC in male mice with substantially increased intrahepatic retention of hydrophobic BAs and decreased hepatic expression of tumor-suppressive microRNAs. Metagenomic analysis showed differences in gut microbiota involved in BA metabolism between normal male and female mice, and such differences were amplified when mice of both sexes were exposed to STZ-HFD. Treating STZ-HFD male mice with 2% cholestyramine led to significant improvement of hepatic BA retention, tumor-suppressive microRNA expressions, microbial gut communities, and prevention of HCC. Additionally the sex-dependent differences in BA profiles in the murine model can be correlated to the differential BA profiles between men and women during the development of HCC. These results uncover distinct male and female profiles for gut microbiota, BAs, and microRNAs that may contribute to sex-based disparity in liver carcinogenesis, and suggest new possibilities for preventing and controlling human obesity-related gastrointestinal cancers that often exhibit sex differences.
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