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      Evaluating DNA Extraction Methods for Community Profiling of Pig Hindgut Microbial Community

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      PLoS ONE
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          Abstract

          Recovery of high quality PCR-amplifiable DNA has been the general minimal requirement for DNA extraction methods for bulk molecular analysis. However, modern high through-put community profiling technologies are more sensitive to representativeness and reproducibility of DNA extraction method. Here, we assess the impact of three DNA extraction methods (with different levels of extraction harshness) for assessing hindgut microbiomes from pigs fed with different diets (with different physical properties). DNA extraction from each sample was performed in three technical replicates for each extraction method and sequenced by 16S rRNA amplicon sequencing. Host was the primary driver of molecular sequencing outcomes, particularly on samples analysed by wheat based diets, but higher variability, with one failed extraction occurred on samples from a barley fed pig. Based on these results, an effective method will enable reproducible and quality outcomes on a range of samples, whereas an ineffective method will fail to generate extract, but host (rather than extraction method) remains the primary factor.

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          Pyrosequencing study of fecal microflora of autistic and control children.

          There is evidence of genetic predisposition to autism, but the percent of autistic subjects with this background is unknown. It is clear that other factors, such as environmental influences, may play a role in this disease. In the present study, we have examined the fecal microbial flora of 33 subjects with various severities of autism with gastrointestinal symptoms, 7 siblings not showing autistic symptoms (sibling controls) and eight non-sibling control subjects, using the bacterial tag encoded FLX amplicon pyrosequencing (bTEFAP) procedure. The results provide us with information on the microflora of stools of young children and a compelling picture of unique fecal microflora of children with autism with gastrointestinal symptomatology. Differences based upon maximum observed and maximum predicted operational taxonomic units were statistically significant when comparing autistic and control subjects with p-values ranging from <0.001 to 0.009 using both parametric and non-parametric estimators. At the phylum level, Bacteroidetes and Firmicutes showed the most difference between groups of varying severities of autism. Bacteroidetes was found at high levels in the severely autistic group, while Firmicutes were more predominant in the control group. Smaller, but significant, differences also occurred in the Actinobacterium and Proteobacterium phyla. Desulfovibrio species and Bacteroides vulgatus are present in significantly higher numbers in stools of severely autistic children than in controls. If the unique microbial flora is found to be a causative or consequent factor in this type of autism, it may have implications with regard to a specific diagnostic test, its epidemiology, and for treatment and prevention. Copyright (c) 2010 Elsevier Ltd. All rights reserved.
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            WebMGA: a customizable web server for fast metagenomic sequence analysis

            Background The new field of metagenomics studies microorganism communities by culture-independent sequencing. With the advances in next-generation sequencing techniques, researchers are facing tremendous challenges in metagenomic data analysis due to huge quantity and high complexity of sequence data. Analyzing large datasets is extremely time-consuming; also metagenomic annotation involves a wide range of computational tools, which are difficult to be installed and maintained by common users. The tools provided by the few available web servers are also limited and have various constraints such as login requirement, long waiting time, inability to configure pipelines etc. Results We developed WebMGA, a customizable web server for fast metagenomic analysis. WebMGA includes over 20 commonly used tools such as ORF calling, sequence clustering, quality control of raw reads, removal of sequencing artifacts and contaminations, taxonomic analysis, functional annotation etc. WebMGA provides users with rapid metagenomic data analysis using fast and effective tools, which have been implemented to run in parallel on our local computer cluster. Users can access WebMGA through web browsers or programming scripts to perform individual analysis or to configure and run customized pipelines. WebMGA is freely available at http://weizhongli-lab.org/metagenomic-analysis. Conclusions WebMGA offers to researchers many fast and unique tools and great flexibility for complex metagenomic data analysis.
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              A renaissance for the pioneering 16S rRNA gene.

              Culture-independent molecular surveys using the 16S rRNA gene have become a mainstay for characterizing microbial community structure over the past quarter century. More recently this approach has been overshadowed by metagenomics, which provides a global overview of a community's functional potential rather than just an inventory of its inhabitants. However, the pioneering 16S rRNA gene is making a comeback in its own right thanks to a number of methodological advancements including higher resolution (more sequences), analysis of multiple related samples (e.g. spatial and temporal series) and improved metadata, and use of metadata. The standard conclusion that microbial ecosystems are remarkably complex and diverse is now being replaced by detailed insights into microbial ecology and evolution based only on this one historically important marker gene.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                11 November 2015
                2015
                : 10
                : 11
                : e0142720
                Affiliations
                [1 ]Advanced Water Management Centre, The University of Queensland, St. Lucia, Brisbane, Queensland, Australia
                [2 ]Australian Centre for Ecogenomics, School of Chemistry and Molecular Biosciences and Institute of Molecular Bioscience, The University of Queensland, St. Lucia, Brisbane, Queensland, Australia
                U.S. Geological Survey, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist. This research was funded by Australian Pork Limited and the Pork CRC, both Australian Federally funded research bodies. This funding generates no competing interests, and does not alter the authors' adherence to PLOS ONE policies on sharing data and materials.

                Conceived and designed the experiments: YL PH DB. Performed the experiments: YL. Analyzed the data: YL DB. Contributed reagents/materials/analysis tools: PH DB. Wrote the paper: YL.

                Article
                PONE-D-15-18110
                10.1371/journal.pone.0142720
                4641665
                26560873
                ddc9fe9d-4d25-4947-9769-b562ae994faf
                Copyright @ 2015

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

                History
                : 29 April 2015
                : 26 October 2015
                Page count
                Figures: 4, Tables: 0, Pages: 10
                Funding
                Funding was provided by Australian Pork Limited, Grant numbers: 2010/1011.334, http://australianpork.com.au/; Pork CRC, Grant numbers:4C106, http://porkcrc.com.au/. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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                Research Article
                Custom metadata
                All relevant data are within the paper and its Supporting Information files.

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