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      MIPE: A metagenome-based community structure explorer and SSU primer evaluation tool

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      PLoS ONE

      Public Library of Science

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          Abstract

          An understanding of microbial community structure is an important issue in the field of molecular ecology. The traditional molecular method involves amplification of small subunit ribosomal RNA (SSU rRNA) genes by polymerase chain reaction (PCR). However, PCR-based amplicon approaches are affected by primer bias and chimeras. With the development of high-throughput sequencing technology, unbiased SSU rRNA gene sequences can be mined from shotgun sequencing-based metagenomic or metatranscriptomic datasets to obtain a reflection of the microbial community structure in specific types of environment and to evaluate SSU primers. However, the use of short reads obtained through next-generation sequencing for primer evaluation has not been well resolved. The software MIPE (MIcrobiota metagenome Primer Explorer) was developed to adapt numerous short reads from metagenomes and metatranscriptomes. Using metagenomic or metatranscriptomic datasets as input, MIPE extracts and aligns rRNA to reveal detailed information on microbial composition and evaluate SSU rRNA primers. A mock dataset, a real Metagenomics Rapid Annotation using Subsystem Technology (MG-RAST) test dataset, two PrimerProspector test datasets and a real metatranscriptomic dataset were used to validate MIPE. The software calls Mothur (v1.33.3) and the SILVA database (v119) for the alignment and classification of rRNA genes from a metagenome or metatranscriptome. MIPE can effectively extract shotgun rRNA reads from a metagenome or metatranscriptome and is capable of classifying these sequences and exhibiting sensitivity to different SSU rRNA PCR primers. Therefore, MIPE can be used to guide primer design for specific environmental samples.

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          Most cited references 30

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          Examining the global distribution of dominant archaeal populations in soil.

          Archaea, primarily Crenarchaeota, are common in soil; however, the structure of soil archaeal communities and the factors regulating their diversity and abundance remain poorly understood. Here, we used barcoded pyrosequencing to comprehensively survey archaeal and bacterial communities in 146 soils, representing a multitude of soil and ecosystem types from across the globe. Relative archaeal abundance, the percentage of all 16S rRNA gene sequences recovered that were archaeal, averaged 2% across all soils and ranged from 0% to >10% in individual soils. Soil C:N ratio was the only factor consistently correlated with archaeal relative abundances, being higher in soils with lower C:N ratios. Soil archaea communities were dominated by just two phylotypes from a constrained clade within the Crenarchaeota, which together accounted for >70% of all archaeal sequences obtained in the survey. As one of these phylotypes was closely related to a previously identified putative ammonia oxidizer, we sampled from two long-term nitrogen (N) addition experiments to determine if this taxon responds to experimental manipulations of N availability. Contrary to expectations, the abundance of this dominant taxon, as well as archaea overall, tended to decline with increasing N. This trend was coupled with a concurrent increase in known N-oxidizing bacteria, suggesting competitive interactions between these groups.
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            Comparative Analysis of Pyrosequencing and a Phylogenetic Microarray for Exploring Microbial Community Structures in the Human Distal Intestine

            Background Variations in the composition of the human intestinal microbiota are linked to diverse health conditions. High-throughput molecular technologies have recently elucidated microbial community structure at much higher resolution than was previously possible. Here we compare two such methods, pyrosequencing and a phylogenetic array, and evaluate classifications based on two variable 16S rRNA gene regions. Methods and Findings Over 1.75 million amplicon sequences were generated from the V4 and V6 regions of 16S rRNA genes in bacterial DNA extracted from four fecal samples of elderly individuals. The phylotype richness, for individual samples, was 1,400–1,800 for V4 reads and 12,500 for V6 reads, and 5,200 unique phylotypes when combining V4 reads from all samples. The RDP-classifier was more efficient for the V4 than for the far less conserved and shorter V6 region, but differences in community structure also affected efficiency. Even when analyzing only 20% of the reads, the majority of the microbial diversity was captured in two samples tested. DNA from the four samples was hybridized against the Human Intestinal Tract (HIT) Chip, a phylogenetic microarray for community profiling. Comparison of clustering of genus counts from pyrosequencing and HITChip data revealed highly similar profiles. Furthermore, correlations of sequence abundance and hybridization signal intensities were very high for lower-order ranks, but lower at family-level, which was probably due to ambiguous taxonomic groupings. Conclusions The RDP-classifier consistently assigned most V4 sequences from human intestinal samples down to genus-level with good accuracy and speed. This is the deepest sequencing of single gastrointestinal samples reported to date, but microbial richness levels have still not leveled out. A majority of these diversities can also be captured with five times lower sampling-depth. HITChip hybridizations and resulting community profiles correlate well with pyrosequencing-based compositions, especially for lower-order ranks, indicating high robustness of both approaches. However, incompatible grouping schemes make exact comparison difficult.
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              CAMERA: A Community Resource for Metagenomics

              The CAMERA (Cyberinfrastructure for Advanced Marine Microbial Ecology Research and Analysis) community database for metagenomic data deposition is an important first step in developing methods for monitoring microbial communities.
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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
                28 March 2017
                2017
                : 12
                : 3
                Affiliations
                Department of Microbiology and Microbial Engineering, School of Life Sciences, Fudan University, Shanghai, People’s Republic of China
                Oklahoma State University, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                • Conceptualization: ZXQ BZ JFL QZ.

                • Data curation: BZ JFL QZ.

                • Formal analysis: BZ JFL.

                • Funding acquisition: ZXQ.

                • Methodology: ZXQ.

                • Project administration: ZXQ.

                • Software: BZ JFL QZ.

                • Supervision: ZXQ.

                • Visualization: BZ.

                • Writing – original draft: BZ JFL.

                • Writing – review & editing: BZ ZXQ.

                [¤]

                Current address: CAS-MPG Partner Institute for Computational Biology (PICB), Shanghai Institutes for Biological Sciences (SIBS), Chinese Academy of Sciences (CAS), Shanghai, People’s Republic of China.

                Article
                PONE-D-16-47704
                10.1371/journal.pone.0174609
                5370157
                28350876
                © 2017 Zou et al

                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.

                Page count
                Figures: 4, Tables: 0, Pages: 15
                Product
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 31170114
                Award Recipient :
                This work was supported by the National Natural Science Foundation of China (31170114) http://www.nsfc.gov.cn/.
                Categories
                Research Article
                Research and Analysis Methods
                Database and Informatics Methods
                Biological Databases
                Sequence Databases
                Research and Analysis Methods
                Database and Informatics Methods
                Bioinformatics
                Sequence Analysis
                Sequence Databases
                Research and Analysis Methods
                Database and Informatics Methods
                Bioinformatics
                Sequence Analysis
                Sequence Alignment
                Biology and life sciences
                Biochemistry
                Nucleic acids
                RNA
                Non-coding RNA
                Ribosomal RNA
                Biology and life sciences
                Biochemistry
                Ribosomes
                Ribosomal RNA
                Biology and life sciences
                Cell biology
                Cellular structures and organelles
                Ribosomes
                Ribosomal RNA
                Research and Analysis Methods
                Computational Techniques
                Split-Decomposition Method
                Multiple Alignment Calculation
                Research and Analysis Methods
                Database and Informatics Methods
                Bioinformatics
                Sequence Analysis
                Biology and Life Sciences
                Taxonomy
                Computer and Information Sciences
                Data Management
                Taxonomy
                Biology and Life Sciences
                Molecular Biology
                Molecular Biology Techniques
                Artificial Gene Amplification and Extension
                Polymerase Chain Reaction
                Research and Analysis Methods
                Molecular Biology Techniques
                Artificial Gene Amplification and Extension
                Polymerase Chain Reaction
                Biology and Life Sciences
                Genetics
                Genomics
                Metagenomics
                Custom metadata
                All data underlying the findings are fully available without restriction. Software and data are freely available from https://github.com/zoubinok/MIPE.git.

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