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      Aquimarina atlantica sp. nov., isolated from surface seawater of the Atlantic Ocean

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          Introducing EzTaxon-e: a prokaryotic 16S rRNA gene sequence database with phylotypes that represent uncultured species.

          Despite recent advances in commercially optimized identification systems, bacterial identification remains a challenging task in many routine microbiological laboratories, especially in situations where taxonomically novel isolates are involved. The 16S rRNA gene has been used extensively for this task when coupled with a well-curated database, such as EzTaxon, containing sequences of type strains of prokaryotic species with validly published names. Although the EzTaxon database has been widely used for routine identification of prokaryotic isolates, sequences from uncultured prokaryotes have not been considered. Here, the next generation database, named EzTaxon-e, is formally introduced. This new database covers not only species within the formal nomenclatural system but also phylotypes that may represent species in nature. In addition to an identification function based on Basic Local Alignment Search Tool (blast) searches and pairwise global sequence alignments, a new objective method of assessing the degree of completeness in sequencing is proposed. All sequences that are held in the EzTaxon-e database have been subjected to phylogenetic analysis and this has resulted in a complete hierarchical classification system. It is concluded that the EzTaxon-e database provides a useful taxonomic backbone for the identification of cultured and uncultured prokaryotes and offers a valuable means of communication among microbiologists who routinely encounter taxonomically novel isolates. The database and its analytical functions can be found at http://eztaxon-e.ezbiocloud.net/.
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            Digital DNA-DNA hybridization for microbial species delineation by means of genome-to-genome sequence comparison

            The pragmatic species concept for Bacteria and Archaea is ultimately based on DNA-DNA hybridization (DDH). While enabling the taxonomist, in principle, to obtain an estimate of the overall similarity between the genomes of two strains, this technique is tedious and error-prone and cannot be used to incrementally build up a comparative database. Recent technological progress in the area of genome sequencing calls for bioinformatics methods to replace the wet-lab DDH by in-silico genome-to-genome comparison. Here we investigate state-of-the-art methods for inferring whole-genome distances in their ability to mimic DDH. Algorithms to efficiently determine high-scoring segment pairs or maximally unique matches perform well as a basis of inferring intergenomic distances. The examined distance functions, which are able to cope with heavily reduced genomes and repetitive sequence regions, outperform previously described ones regarding the correlation with and error ratios in emulating DDH. Simulation of incompletely sequenced genomes indicates that some distance formulas are very robust against missing fractions of genomic information. Digitally derived genome-to-genome distances show a better correlation with 16S rRNA gene sequence distances than DDH values. The future perspectives of genome-informed taxonomy are discussed, and the investigated methods are made available as a web service for genome-based species delineation.
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              Standard operating procedure for calculating genome-to-genome distances based on high-scoring segment pairs

              DNA-DNA hybridization (DDH) is a widely applied wet-lab technique to obtain an estimate of the overall similarity between the genomes of two organisms. To base the species concept for prokaryotes ultimately on DDH was chosen by microbiologists as a pragmatic approach for deciding about the recognition of novel species, but also allowed a relatively high degree of standardization compared to other areas of taxonomy. However, DDH is tedious and error-prone and first and foremost cannot be used to incrementally establish a comparative database. Recent studies have shown that in-silico methods for the comparison of genome sequences can be used to replace DDH. Considering the ongoing rapid technological progress of sequencing methods, genome-based prokaryote taxonomy is coming into reach. However, calculating distances between genomes is dependent on multiple choices for software and program settings. We here provide an overview over the modifications that can be applied to distance methods based in high-scoring segment pairs (HSPs) or maximally unique matches (MUMs) and that need to be documented. General recommendations on determining HSPs using BLAST or other algorithms are also provided. As a reference implementation, we introduce the GGDC web server (http://ggdc.gbdp.org).
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                Author and article information

                Journal
                Antonie van Leeuwenhoek
                Antonie van Leeuwenhoek
                Springer Nature
                0003-6072
                1572-9699
                August 2014
                June 7 2014
                : 106
                : 2
                : 293-300
                Article
                10.1007/s10482-014-0196-2
                24906660
                35c69fea-0374-4508-a823-e061424225a5
                © 2014
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