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      Stool consistency is strongly associated with gut microbiota richness and composition, enterotypes and bacterial growth rates

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          Abstract

          Objective

          The assessment of potentially confounding factors affecting colon microbiota composition is essential to the identification of robust microbiome based disease markers. Here, we investigate the link between gut microbiota variation and stool consistency using Bristol Stool Scale classification, which reflects faecal water content and activity, and is considered a proxy for intestinal colon transit time.

          Design

          Through 16S rDNA Illumina profiling of faecal samples of 53 healthy women, we evaluated associations between microbiome richness, Bacteroidetes:Firmicutes ratio, enterotypes, and genus abundance with self-reported, Bristol Stool Scale-based stool consistency. Each sample’s microbiota growth potential was calculated to test whether transit time acts as a selective force on gut bacterial growth rates.

          Results

          Stool consistency strongly correlates with all known major microbiome markers. It is negatively correlated with species richness, positively associated to the Bacteroidetes:Firmicutes ratio, and linked to Akkermansia and Methanobrevibacter abundance. Enterotypes are distinctly distributed over the BSS-scores. Based on the correlations between microbiota growth potential and stool consistency scores within both enterotypes, we hypothesise that accelerated transit contributes to colon ecosystem differentiation. While shorter transit times can be linked to increased abundance of fast growing species in Ruminococcaceae- Bacteroides samples, hinting to a washout avoidance strategy of faster replication, this trend is absent in Prevotella-enterotyped individuals. Within this enterotype adherence to host tissue therefore appears to be a more likely bacterial strategy to cope with washout.

          Conclusions

          The strength of the associations between stool consistency and species richness, enterotypes and community composition emphasises the crucial importance of stool consistency assessment in gut metagenome-wide association studies.

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          Most cited references31

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          Dirichlet Multinomial Mixtures: Generative Models for Microbial Metagenomics

          We introduce Dirichlet multinomial mixtures (DMM) for the probabilistic modelling of microbial metagenomics data. This data can be represented as a frequency matrix giving the number of times each taxa is observed in each sample. The samples have different size, and the matrix is sparse, as communities are diverse and skewed to rare taxa. Most methods used previously to classify or cluster samples have ignored these features. We describe each community by a vector of taxa probabilities. These vectors are generated from one of a finite number of Dirichlet mixture components each with different hyperparameters. Observed samples are generated through multinomial sampling. The mixture components cluster communities into distinct ‘metacommunities’, and, hence, determine envirotypes or enterotypes, groups of communities with a similar composition. The model can also deduce the impact of a treatment and be used for classification. We wrote software for the fitting of DMM models using the ‘evidence framework’ (http://code.google.com/p/microbedmm/). This includes the Laplace approximation of the model evidence. We applied the DMM model to human gut microbe genera frequencies from Obese and Lean twins. From the model evidence four clusters fit this data best. Two clusters were dominated by Bacteroides and were homogenous; two had a more variable community composition. We could not find a significant impact of body mass on community structure. However, Obese twins were more likely to derive from the high variance clusters. We propose that obesity is not associated with a distinct microbiota but increases the chance that an individual derives from a disturbed enterotype. This is an example of the ‘Anna Karenina principle (AKP)’ applied to microbial communities: disturbed states having many more configurations than undisturbed. We verify this by showing that in a study of inflammatory bowel disease (IBD) phenotypes, ileal Crohn's disease (ICD) is associated with a more variable community.
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            Inflammation-associated enterotypes, host genotype, cage and inter-individual effects drive gut microbiota variation in common laboratory mice

            Background Murine models are a crucial component of gut microbiome research. Unfortunately, a multitude of genetic backgrounds and experimental setups, together with inter-individual variation, complicates cross-study comparisons and a global understanding of the mouse microbiota landscape. Here, we investigate the variability of the healthy mouse microbiota of five common lab mouse strains using 16S rDNA pyrosequencing. Results We find initial evidence for richness-driven, strain-independent murine enterotypes that show a striking resemblance to those in human, and which associate with calprotectin levels, a marker for intestinal inflammation. After enterotype stratification, we find that genetic, caging and inter-individual variation contribute on average 19%, 31.7% and 45.5%, respectively, to the variance in the murine gut microbiota composition. Genetic distance correlates positively to microbiota distance, so that genetically similar strains have more similar microbiota than genetically distant ones. Specific mouse strains are enriched for specific operational taxonomic units and taxonomic groups, while the 'cage effect' can occur across mouse strain boundaries and is mainly driven by Helicobacter infections. Conclusions The detection of enterotypes suggests a common ecological cause, possibly low-grade inflammation that might drive differences among gut microbiota composition in mammals. Furthermore, the observed environmental and genetic effects have important consequences for experimental design in mouse microbiome research.
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              Molecular microbial diversity of an anaerobic digestor as determined by small-subunit rDNA sequence analysis.

              The bacterial community structure of a fluidized-bed reactor fed by vinasses (wine distillation waste) was analyzed. After PCR amplification, four small-subunit (SSU) rDNA clone libraries of Bacteria, Archaea, Procarya, and Eucarya populations were established. The community structure was determined by operational taxonomic unit (OTU) phylogenetic analyses of 579 partial rDNA sequences (about 500 bp long). A total of 146 OTUs were found, comprising 133, 6, and 7 from the Bacteria, Archaea, and Eucarya domains, respectively. A total of 117 bacterial OTU were affiliated with major phyla: low-G+C gram-positive bacteria, Cytophaga-Flexibacter-Bacteroides, Proteobacteria, high-G+C gram-positive bacteria, and Spirochaetes, where the clone distribution was 34, 26, 17, 6, and 4%, respectively. The other 16 bacterial OTUs represent 13% of the clones. They were either affiliated with narrow phyla such as Planctomyces-Chlamydia, green nonsulfur bacteria, or Synergistes, or deeply branched on the phylogenetic tree. A large number of bacterial OTUs are not closely related to any other hitherto determined sequences. The most frequent bacterial OTUs represents less than 5% of the total bacterial SSU rDNA sequences. However, the 20 more frequent bacterial OTUs describe at least 50% of these sequences. Three of the six Archaea OTUs correspond to 95% of the Archaea population and are very similar to already known methanogenic species: Methanosarcina barkeri, Methanosarcina frisius, and Methanobacterium formicicum. In contrast, the three other Archaea OTUs are unusual and are related to thermophilic microorganisms such as Crenarchaea or Thermoplasma spp. Five percent of the sequences analyzed were chimeras and were removed from the analysis.
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                Author and article information

                Journal
                Gut
                Gut
                gutjnl
                gut
                Gut
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                0017-5749
                1468-3288
                January 2016
                11 June 2015
                : 65
                : 1
                : 57-62
                Affiliations
                [1 ]Department of Microbiology and Immunology, KU Leuven, Rega Institute , Leuven, Belgium
                [2 ]VIB, Center for the Biology of Disease , Leuven, Belgium
                [3 ]Faculty of Sciences and Bioengineering Sciences, Microbiology Unit, Vrije Universiteit Brussel, Brussels, Belgium
                Author notes
                [Correspondence to ] Jeroen Raes, Department of Microbiology and Immunology, KU Leuven, Rega Institute, Herestraat 49, Leuven B-3000, Belgium; jeroen.raes@ 123456med.kuleuven.be

                DV and GF contributed equally.

                Article
                gutjnl-2015-309618
                10.1136/gutjnl-2015-309618
                4717365
                26069274
                28455f32-ee5a-47dd-bea9-f018a955cfcd
                Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

                This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/

                History
                : 19 March 2015
                : 11 May 2015
                : 25 May 2015
                Categories
                1506
                Gut Microbiota
                Original article
                Custom metadata
                unlocked

                Gastroenterology & Hepatology
                intestinal bacteria,intestinal microbiology
                Gastroenterology & Hepatology
                intestinal bacteria, intestinal microbiology

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