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      Rabbit Microbiota Changes Throughout the Intestinal Tract

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          To gain insight into the importance of carefully selecting the sampling area for intestinal microbiota studies, cecal and fecal microbial communities of Caldes meat rabbit were characterized. The animals involved in the study were divided in two groups according to the feed intake level they received during the fattening period; ad libitum ( n = 10) or restricted to 75% of ad libitum intake ( n = 11). Cecum and internal hard feces were sampled from sacrificed animals. Assessment of bacterial and archaeal populations was performed by means of Illumina sequencing of 16S rRNA gene amplicons in a MiSeq platform. A total of 596 operational taxonomic units (OTUs) were detected using QIIME software. Taxonomic assignment revealed that microbial diversity was dominated by phyla Firmicutes (76.42%), Tenericutes (7.83%), and Bacteroidetes (7.42%); kingdom Archaea was presented at low percentage (0.61%). No significant differences were detected between sampling origins in microbial diversity or richness assessed using two alpha-diversity indexes: Shannon and the observed number of OTUs. However, the analysis of variance at genus level revealed a higher presence of genera Clostridium, Anaerofustis, Blautia, Akkermansia, rc4-4, and Bacteroides in cecal samples. By contrast, genera Oscillospira and Coprococcus were found to be overrepresented in feces, suggesting that bacterial species of these genera would act as fermenters at the end of feed digestion process. At the lowest taxonomic level, 83 and 97 OTUs in feces and cecum, respectively, were differentially represented. Multivariate statistical assessment revealed that sparse partial least squares discriminant analysis (sPLS-DA) was the best approach for this purpose. Interestingly, the majority of the most discriminative OTUs selected by sPLS-DA were found to be differentially represented between sampling origins in univariate analysis. Our study provides evidence that the choice of intestinal sampling area is relevant due to important differences in some taxa’s relative abundance that have been revealed between rabbits’ cecal and fecal microbiota. An appropriate sampling intestinal area should be chosen in each microbiota assessment.

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          Most cited references 58

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          Subsampled open-reference clustering creates consistent, comprehensive OTU definitions and scales to billions of sequences

          We present a performance-optimized algorithm, subsampled open-reference OTU picking, for assigning marker gene (e.g., 16S rRNA) sequences generated on next-generation sequencing platforms to operational taxonomic units (OTUs) for microbial community analysis. This algorithm provides benefits over de novo OTU picking (clustering can be performed largely in parallel, reducing runtime) and closed-reference OTU picking (all reads are clustered, not only those that match a reference database sequence with high similarity). Because more of our algorithm can be run in parallel relative to “classic” open-reference OTU picking, it makes open-reference OTU picking tractable on massive amplicon sequence data sets (though on smaller data sets, “classic” open-reference OTU clustering is often faster). We illustrate that here by applying it to the first 15,000 samples sequenced for the Earth Microbiome Project (1.3 billion V4 16S rRNA amplicons). To the best of our knowledge, this is the largest OTU picking run ever performed, and we estimate that our new algorithm runs in less than 1/5 the time than would be required of “classic” open reference OTU picking. We show that subsampled open-reference OTU picking yields results that are highly correlated with those generated by “classic” open-reference OTU picking through comparisons on three well-studied datasets. An implementation of this algorithm is provided in the popular QIIME software package, which uses uclust for read clustering. All analyses were performed using QIIME’s uclust wrappers, though we provide details (aided by the open-source code in our GitHub repository) that will allow implementation of subsampled open-reference OTU picking independently of QIIME (e.g., in a compiled programming language, where runtimes should be further reduced). Our analyses should generalize to other implementations of these OTU picking algorithms. Finally, we present a comparison of parameter settings in QIIME’s OTU picking workflows and make recommendations on settings for these free parameters to optimize runtime without reducing the quality of the results. These optimized parameters can vastly decrease the runtime of uclust-based OTU picking in QIIME.
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            Microbes inside--from diversity to function: the case of Akkermansia.

             W Vos,  Clara Belzer (2012)
            The human intestinal tract is colonized by a myriad of microbes that have developed intimate interactions with the host. In healthy individuals, this complex ecosystem remains stable and resilient to stressors. There is significant attention on the understanding of the composition and function of this intestinal microbiota in health and disease. Current developments in metaomics and systems biology approaches allow to probe the functional potential and activity of the intestinal microbiota. However, all these approaches inherently suffer from the fact that the information on macromolecules (DNA, RNA and protein) is collected at the ecosystem level. Similarly, all physiological and other information collected from isolated strains relates to pure cultures grown in vitro or in gnotobiotic systems. It is essential to integrate these two worlds of predominantly chemistry and biology by linking the molecules to the cells. Here, we will address the integration of omics- and culture-based approaches with the complexity of the human intestinal microbiota in mind and the mucus-degrading bacteria Akkermansia spp. as a paradigm.
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              Effect of DNA Extraction Methods and Sampling Techniques on the Apparent Structure of Cow and Sheep Rumen Microbial Communities

              Molecular microbial ecology techniques are widely used to study the composition of the rumen microbiota and to increase understanding of the roles they play. Therefore, sampling and DNA extraction methods that result in adequate yields of microbial DNA that also accurately represents the microbial community are crucial. Fifteen different methods were used to extract DNA from cow and sheep rumen samples. The DNA yield and quality, and its suitability for downstream PCR amplifications varied considerably, depending on the DNA extraction method used. DNA extracts from nine extraction methods that passed these first quality criteria were evaluated further by quantitative PCR enumeration of microbial marker loci. Absolute microbial numbers, determined on the same rumen samples, differed by more than 100-fold, depending on the DNA extraction method used. The apparent compositions of the archaeal, bacterial, ciliate protozoal, and fungal communities in identical rumen samples were assessed using 454 Titanium pyrosequencing. Significant differences in microbial community composition were observed between extraction methods, for example in the relative abundances of members of the phyla Bacteroidetes and Firmicutes . Microbial communities in parallel samples collected from cows by oral stomach-tubing or through a rumen fistula, and in liquid and solid rumen digesta fractions, were compared using one of the DNA extraction methods. Community representations were generally similar, regardless of the rumen sampling technique used, but significant differences in the abundances of some microbial taxa such as the Clostridiales and the Methanobrevibacter ruminantium clade were observed. The apparent microbial community composition differed between rumen sample fractions, and Prevotellaceae were most abundant in the liquid fraction. DNA extraction methods that involved phenol-chloroform extraction and mechanical lysis steps tended to be more comparable. However, comparison of data from studies in which different sampling techniques, different rumen sample fractions or different DNA extraction methods were used should be avoided.

                Author and article information

                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                13 September 2018
                : 9
                1Animal Breeding and Genetics, Institute for Food and Agriculture Research and Technology (IRTA) , Barcelona, Spain
                2Integral Management of Organic Waste, Institute for Food and Agriculture Research and Technology (IRTA) , Barcelona, Spain
                Author notes

                Edited by: David William Waite, University of Auckland, New Zealand

                Reviewed by: Huan Li, Lanzhou University, China; Neil Ross McEwan, Aberystwyth University, United Kingdom

                *Correspondence: María Velasco-Galilea, maria.velasco@

                This article was submitted to Microbial Symbioses, a section of the journal Frontiers in Microbiology

                Copyright © 2018 Velasco-Galilea, Piles, Viñas, Rafel, González-Rodríguez, Guivernau and Sánchez.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                Page count
                Figures: 4, Tables: 6, Equations: 0, References: 82, Pages: 14, Words: 0
                Funded by: Horizon 2020 10.13039/501100007601
                Award ID: 633531
                Funded by: Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria 10.13039/100007652
                Award ID: RTA2011-00064-00-00
                Award ID: RTA2014-00015-C2-01
                Original Research


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