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  • Journal article
    Zhang Q, Cox M, Liang Z, Brinkmann F, Cardenas PA, Duff R, Bhavsar P, Cookson W, Moffatt M, Chung KFet al., 2016,

    Airway microbiota in severe asthma and relationship to asthma severity and phenotypes

    , PLOS One, Vol: 11, ISSN: 1932-6203

    Background: The lower airways harbor a community of bacterial species which is altered in asthma. Objectives: We examined whether the lower airway microbiota were related to measures of asthma severityMethods: We prospectively recruited 26 severe asthma, 18 non-severe asthma and 12 healthy subjects. DNA was extracted from induced sputum and PCR amplification of the V3-V5 region of bacterial 16S rRNA gene was performed. Results: We obtained 138,218 high quality sequences which were rarefied at 133 sequences/sample. Twenty OTUs had sequences ≥1% of total. There were marked differences in the distribution of Phyla between groups (P=2.8x10-118). Bacteroidetes and Fusobacteria were reduced in non-severe and severe asthmatic groups. Proteobacteria were more common in non-severe asthmatics compared to controls (OR=2.26; 95% CI=1.94-2.64) and Firmicutes were increased in severe asthmatics compared to controls (OR=2.15; 95%CI=1.89-2.45). Streptococcal OTUs amongst the Firmicutes were associated with recent onset asthma, rhinosinusitis and sputum eosinophilia.Conclusions: Sputum microbiota in severe asthma differs from healthy controls and non-severe asthmatics, and is characterized by the presence of Streptococcus spp with eosinophilia. Whether these organisms are causative for the pathophysiology of asthma remains to be determined.

  • Journal article
    Dumas M-E, 2016,

    Is the way we're dieting wrong?

    , Genome Medicine, Vol: 8, ISSN: 1756-994X

    Progress in personalized medicine is now beingtranslated to personalized nutrition. A recent proofof-conceptstudy shows that the increase in bloodglucose levels after a meal is highly variable betweenindividuals, but can be predicted by using acomputational model that combines information fromgut microbiome profiles and dietary questionnaires.This study raises questions about the usefulness ofuniversal diet recommendations, and suggests wemight need to move on to personalized diets.

  • Journal article
    Neves AL, Chilloux J, Sarafian MH, Rahim MBA, Boulange CL, Dumas M-Eet al., 2015,

    The microbiome and its pharmacological targets: therapeutic avenues in cardiometabolic diseases

    , Current Opinion in Pharmacology, Vol: 25, Pages: 36-44, ISSN: 1471-4892

    Consisting of trillions of non-pathogenic bacteria living in a symbiotic relationship with their mammalian host, the gut microbiota has emerged in the past decades as one of the key drivers for cardiometabolic diseases (CMD). By degrading dietary substrates, the gut microbiota produces several metabolites that bind human pharmacological targets, impact subsequent signalling networks and in fine modulate host's metabolism. In this review, we revisit the pharmacological relevance of four classes of gut microbial metabolites in CMD: short-chain fatty acids (SCFA), bile acids, methylamines and indoles. Unravelling the signalling mechanisms of the microbial–mammalian metabolic axis adds one more layer of complexity to the physiopathology of CMD and opens new avenues for the development of microbiota-based pharmacological therapies.

  • Journal article
    Sarafian MH, Lewis MR, Pechlivanis A, Ralphs S, McPhail MJW, Patel VC, Dumas M-E, Holmes E, Nicholson Jet al., 2015,

    Bile Acid Profiling and Quantification in Biofluids Using Ultra-Performance Liquid Chromatography Tandem Mass Spectrometry

    , Analytical Chemistry, Vol: 87, Pages: 9662-9670, ISSN: 1520-6882

    Bile acids are important end products of cholesterol metabolism. While they have been identified as key factors in lipid emulsification and absorption due to their detergent properties, bile acids have also been shown to act as signaling molecules and intermediates between the host and the gut microbiota. To further the investigation of bile acid functions in humans, an advanced platform for high throughput analysis is essential. Herein, we describe the development and application of a 15 min UPLC procedure for the separation of bile acid species from human biofluid samples requiring minimal sample preparation. High resolution time-of-flight mass spectrometry was applied for profiling applications, elucidating rich bile acid profiles in both normal and disease state plasma. In parallel, a second mode of detection was developed utilizing tandem mass spectrometry for sensitive and quantitative targeted analysis of 145 bile acid (BA) species including primary, secondary, and tertiary bile acids. The latter system was validated by testing the linearity (lower limit of quantification, LLOQ, 0.25–10 nM and upper limit of quantification, ULOQ, 2.5–5 μM), precision (≈6.5%), and accuracy (81.2–118.9%) on inter- and intraday analysis achieving good recovery of bile acids (serum/plasma 88% and urine 93%). The ultra performance liquid chromatography–mass spectrometry (UPLC-MS)/MS targeted method was successfully applied to plasma, serum, and urine samples in order to compare the bile acid pool compositional difference between preprandial and postprandial states, demonstrating the utility of such analysis on human biofluids.

  • Journal article
    Cox MJ, Moffatt MF, Cookson WOC, 2015,

    Outside In: Sequencing the Lung Microbiome

    , American Journal of Respiratory and Critical Care Medicine, Vol: 192, Pages: 403-404, ISSN: 1535-4970
  • Journal article
    Shoaie S, Ghaffari P, Kovatcheva-Datchary P, Mardinoglu A, Sen P, Pujos-Guillot E, de Wouters T, Juste C, Rizkalla S, Chilloux J, Hoyles L, Nicholson JK, MICRO-Obes consortium, Dore J, Dumas ME, Clement K, Bäckhed F, Nielsen Jet al., 2015,

    Quantifying Diet-Induced Metabolic Changes of the Human Gut Microbiome

    , Cell Metabolism, Vol: 22, Pages: 320-331, ISSN: 1932-7420

    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.

  • Journal article
    Brill S, Law M, El-Emir E, Allinson JP, James PL, Maddox V, Donaldson GC, McHugh TD, Cookson WO, Moffatt MF, Nazareth I, Hurst JR, Calverley PMA, Sweeting MJ, Wedzicha JAet al., 2015,

    Effects of different antibiotic classes on airwaybacteria in stable COPD using culture and molecularQ1 techniques: a randomised controlled trial

    , Thorax, Vol: 70, Pages: 930-938, ISSN: 1468-3296

    BackgroundLong term antibiotic therapy is used to prevent exacerbations of chronic obstructive pulmonary disease (COPD) but there is uncertainty over whether this reduces airway bacteria. The optimum antibiotic choice remains unknown. We conducted an exploratory trial in stable patients with COPD comparing three antibiotic regimens against placebo. MethodsThis was a single-centre, single-blind, randomised placebo-controlled trial (clinicaltrials.gov number NCT01398072). Patients ≥45 years with COPD, FEV1<80% predicted and chronic productive cough were randomised to receive either moxifloxacin 400mg daily for 5 days/4 weeks, doxycycline 100mg/day, azithromycin 250mg 3x/week or one placebo tablet daily for 13 weeks. The primary outcome was the change in total cultured bacterial load in sputum from baseline; secondary outcomes included bacterial load by 16S qPCR, sputum inflammation and antibiotic resistance. Results99 patients were randomised; 86 completed follow-up, were able to expectorate sputum and were analysed. After adjustment, there was a mean reduction in bacterial load of 0.42 log10 cfu/ml (95% CI -0.08, 0.91, p=0.10) with moxifloxacin, 0.11 (-0.33, 0.55, p=0.62) with doxycycline, and 0.08 (-0.38, 0.54, p=0.73) with azithromycin from placebo, respectively. There were also no significant changes in bacterial load measured by 16S qPCR or in airway inflammation. More treatment-related adverse events occurred with moxifloxacin. Of note, mean inhibitory concentrations of cultured isolates increased by at least 3 times over placebo in all treatment arms.ConclusionsTotal airway bacterial load did not decrease significantly after three months of antibiotic therapy. Large increases in antibiotic resistance were seen in all treatment groups and this has important implications for future studies.

  • Journal article
    Shaw AG, Sim K, Randell P, Cox M, McClure Z, Li MS, Donaldson H, Langford P, Cookson WOCM, Moffatt MF, Kroll JSet al., 2015,

    Late-onset bloodstream infection and perturbed maturation of the gastrointestinal microbiota in premature infants

    , PLOS One, Vol: 10, ISSN: 1932-6203
  • Journal article
    Sim K, Shaw AG, Randell P, Cox MJ, McClure ZE, Li M-S, Haddad M, Langford PR, Cookson WOCM, Moffatt MF, Kroll JSet al., 2015,

    Dysbiosis anticipating necrotizing enterocolitis in very premature infants

    , Clinical Infectious Diseases, Vol: 60, Pages: 389-397, ISSN: 1537-6591

    Background. Necrotizing enterocolitis (NEC) is a devastating inflammatory bowel disease of premature infants speculatively associated with infection. Suspected NEC can be indistinguishable from sepsis, and in established cases an infant may die within hours of diagnosis. Present treatment is supportive. A means of presymptomatic diagnosis is urgently needed. We aimed to identify microbial signatures in the gastrointestinal microbiota preceding NEC diagnosis in premature infants.Methods. Fecal samples and clinical data were collected from a 2-year cohort of 369 premature neonates. Next-generation sequencing of 16S ribosomal RNA gene regions was used to characterize the microbiota of prediagnosis fecal samples from 12 neonates with NEC, 8 with suspected NEC, and 44 controls. Logistic regression was used to determine clinical characteristics and operational taxonomic units (OTUs) discriminating cases from controls. Samples were cultured and isolates identified using matrix-assisted laser desorption/ionization–time of flight. Clostridial isolates were typed and toxin genes detected.Results. A clostridial OTU was overabundant in prediagnosis samples from infants with established NEC (P = .006). Culture confirmed the presence of Clostridium perfringens type A. Fluorescent amplified fragment-length polymorphism typing established that no isolates were identical. Prediagnosis samples from NEC infants not carrying profuse C. perfringens revealed an overabundance of a Klebsiella OTU (P = .049). Prolonged continuous positive airway pressure (CPAP) therapy with supplemental oxygen was also associated with increased NEC risk.Conclusions. Two fecal microbiota signatures (Clostridium and Klebsiella OTUs) and need for prolonged CPAP oxygen signal increased risk of NEC in presymptomatic infants. These biomarkers will assist development of a screening tool to allow very early diagnosis of NEC.Clinical Trials Registration. NCT01102738.

  • Journal article
    Salter SJ, Cox MJ, Turek EM, Calus ST, Cookson WO, Moffatt MF, Turner P, Parkhill J, Loman NJ, Walker AWet al., 2014,

    Reagent and laboratory contamination can critically impact sequence-based microbiome analyses

    , BMC Biology, Vol: 12, ISSN: 1741-7007

    BackgroundThe study of microbial communities has been revolutionised in recent years by the widespread adoption of culture independent analytical techniques such as 16S rRNA gene sequencing and metagenomics. One potential confounder of these sequence-based approaches is the presence of contamination in DNA extraction kits and other laboratory reagents.ResultsIn this study we demonstrate that contaminating DNA is ubiquitous in commonly used DNA extraction kits and other laboratory reagents, varies greatly in composition between different kits and kit batches, and that this contamination critically impacts results obtained from samples containing a low microbial biomass. Contamination impacts both PCR-based 16S rRNA gene surveys and shotgun metagenomics. We provide an extensive list of potential contaminating genera, and guidelines on how to mitigate the effects of contamination.ConclusionsThese results suggest that caution should be advised when applying sequence-based techniques to the study of microbiota present in low biomass environments. Concurrent sequencing of negative control samples is strongly advised.

This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.

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