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Introducing EzBioCloud: a taxonomically united database of 16S rRNA gene sequences and whole-genome assemblies.

ABSTRACT: The recent advent of DNA sequencing technologies facilitates the use of genome sequencing data that provide means for more informative and precise classification and identification of members of the Bacteria and Archaea. Because the current species definition is based on the comparison of genome sequences between type and other strains in a given species, building a genome database with correct taxonomic information is of paramount need to enhance our efforts in exploring prokaryotic diversity and discovering novel species as well as for routine identifications. Here we introduce an integrated database, called EzBioCloud, that holds the taxonomic hierarchy of the Bacteria and Archaea, which is represented by quality-controlled 16S rRNA gene and genome sequences. Whole-genome assemblies in the NCBI Assembly Database were screened for low quality and subjected to a composite identification bioinformatics pipeline that employs gene-based searches followed by the calculation of average nucleotide identity. As a result, the database is made of 61?700 species/phylotypes, including 13?132 with validly published names, and 62?362 whole-genome assemblies that were identified taxonomically at the genus, species and subspecies levels. Genomic properties, such as genome size and DNA G+C content, and the occurrence in human microbiome data were calculated for each genus or higher taxa. This united database of taxonomy, 16S rRNA gene and genome sequences, with accompanying bioinformatics tools, should accelerate genome-based classification and identification of members of the Bacteria and Archaea. The database and related search tools are available at www.ezbiocloud.net/.

SUBMITTER: Yoon SH

PROVIDER: S-EPMC5563544 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

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Introducing EzBioCloud: a taxonomically united database of 16S rRNA gene sequences and whole-genome assemblies.

Yoon Seok-Hwan SH Ha Sung-Min SM Kwon Soonjae S Lim Jeongmin J Kim Yeseul Y Seo Hyungseok H Chun Jongsik J

International journal of systematic and evolutionary microbiology 20170530 5

The recent advent of DNA sequencing technologies facilitates the use of genome sequencing data that provide means for more informative and precise classification and identification of members of the Bacteria and Archaea. Because the current species definition is based on the comparison of genome sequences between type and other strains in a given species, building a genome database with correct taxonomic information is of paramount need to enhance our efforts in exploring prokaryotic diversity a ...[more]

PMID: 28005526

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Project description:16S rRNA gene sequences are commonly analyzed for taxonomic and phylogenetic studies because they contain variable regions that can help distinguish different genera. However, intra-genus distinction using variable region homology is often impossible due to the high overall sequence identities among closely related species, even though some residues may be conserved within respective species. Using a computational method that included the allelic diversity within individual genomes, we discovered that certain Escherichia and Shigella species can be distinguished by a multi-allelic 16S rRNA variable region single nucleotide polymorphism (SNP). To evaluate the performance of 16S rRNAs with altered variable regions, we developed an in vivo system that measures the acceptance and distribution of variant 16S rRNAs into a large pool of natural versions supporting normal translation and growth. We found that 16S rRNAs containing evolutionarily disparate variable regions were underpopulated both in ribosomes and in active translation pools, even for an SNP. Overall, this study revealed that variable region sequences can substantially influence the performance of 16S rRNAs and that this biological constraint can be leveraged to justify refining taxonomic assignments of variable region sequence data. IMPORTANCE This study reevaluates the notion that 16S rRNA gene variable region sequences are uninformative for intra-genus classification and that single nucleotide variations within them have no consequence to strains that bear them. We demonstrated that the performance of 16S rRNAs in Escherichia coli can be negatively impacted by sequence changes in variable regions, even for single nucleotide changes that are native to closely related Escherichia and Shigella species; thus, biological performance is likely constraining the evolution of variable regions in bacteria. Further, the native nucleotide variations we tested occur in all strains of their respective species and across their multiple 16S rRNA gene copies, suggesting that these species evolved beyond what would be discerned from a consensus sequence comparison. Therefore, this work also reveals that the multiple 16S rRNA gene alleles found in most bacteria can provide more informative phylogenetic and taxonomic detail than a single reference allele.

Project description:A curated murine oral microbiome database to be used as a reference for mouse-based studies has been constructed using a combination of bacterial culture, 16S rRNA gene amplicon, and whole-genome sequencing. The database comprises a collection of nearly full-length 16S rRNA gene sequences from cultured isolates and draft genomes from representative taxa collected from a range of sources, including specific-pathogen-free laboratory mice, wild Mus musculus domesticus mice, and formerly wild wood mouse Apodemus sylvaticus At present, it comprises 103 mouse oral taxa (MOT) spanning four phyla-Firmicutes, Proteobacteria, Actinobacteria, and Bacteroidetes-including 12 novel undescribed species-level taxa. The key observations from this study are (i) the low diversity and predominantly culturable nature of the laboratory mouse oral microbiome and (ii) the identification of three major murine-specific oral bacterial lineages, namely, Streptococcus danieliae (MOT10), Lactobacillus murinus (MOT93), and Gemella species 2 (MOT43), which is one of the novel, still-unnamed taxa. Of these, S. danieliae is of particular interest, since it is a major component of the oral microbiome from all strains of healthy and periodontally diseased laboratory mice, as well as being present in wild mice. It is expected that this well-characterized database should be a useful resource for in vitro experimentation and mouse model studies in the field of oral microbiology.IMPORTANCE Mouse model studies are frequently used in oral microbiome research, particularly to investigate diseases such as periodontitis and caries, as well as other related systemic diseases. We have reported here the details of the development of a curated reference database to characterize the oral microbial community in laboratory and some wild mice. The genomic information and findings reported here can help improve the outcomes and accuracy of host-microbe experimental studies that use murine models to understand health and disease. Work is also under way to make the reference data sets publicly available on a web server to enable easy access and downloading for researchers across the world.

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Dataset Information

Introducing EzBioCloud: a taxonomically united database of 16S rRNA gene sequences and whole-genome assemblies.

Publications

Introducing EzBioCloud: a taxonomically united database of 16S rRNA gene sequences and whole-genome assemblies.

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