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/.

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/.

Among available genome relatedness indices, average nucleotide identity (ANI) is one of the most robust measurements of genomic relatedness between strains, and has great potential in the taxonomy of bacteria and archaea as a substitute for the labour-intensive DNA–DNA hybridization (DDH) technique. An ANI threshold range (95–96 %) for species demarcation had previously been suggested based on comparative investigation between DDH and ANI values, albeit with rather limited datasets. Furthermore, its generality was not tested on all lineages of prokaryotes. Here, we investigated the overall distribution of ANI values generated by pairwise comparison of 6787 genomes of prokaryotes belonging to 22 phyla to see whether the suggested range can be applied to all species. There was an apparent distinction in the overall ANI distribution between intra- and interspecies relationships at around 95–96 % ANI. We went on to determine which level of 16S rRNA gene sequence similarity corresponds to the currently accepted ANI threshold for species demarcation using over one million comparisons. A twofold cross-validation statistical test revealed that 98.65 % 16S rRNA gene sequence similarity can be used as the threshold for differentiating two species, which is consistent with previous suggestions (98.2–99.0 %) derived from comparative studies between DDH and 16S rRNA gene sequence similarity. Our findings should be useful in accelerating the use of genomic sequence data in the taxonomy of bacteria and archaea.

Species demarcation in Bacteria and Archaea is mainly based on overall genome relatedness, which serves a framework for modern microbiology. Current practice for obtaining these measures between two strains is shifting from experimentally determined similarity obtained by DNA–DNA hybridization (DDH) to genome-sequence-based similarity. Average nucleotide identity (ANI) is a simple algorithm that mimics DDH. Like DDH, ANI values between two genome sequences may be different from each other when reciprocal calculations are compared. We compared 63 690 pairs of genome sequences and found that the differences in reciprocal ANI values are significantly high, exceeding 1 % in some cases. To resolve this problem of not being symmetrical, a new algorithm, named OrthoANI, was developed to accommodate the concept of orthology for which both genome sequences were fragmented and only orthologous fragment pairs taken into consideration for calculating nucleotide identities. OrthoANI is highly correlated with ANI (using BLASTn) and the former showed approximately 0.1 % higher values than the latter. In conclusion, OrthoANI provides a more robust and faster means of calculating average nucleotide identity for taxonomic purposes. The standalone software tools are freely available at http://www.ezbiocloud.net/sw/oat.

Advancement of DNA sequencing technology allows the routine use of genome sequences in the various fields of microbiology. The information held in genome sequences proved to provide objective and reliable means in the taxonomy of prokaryotes. Here, we describe the minimal standards for the quality of genome sequences and how they can be applied for taxonomic purposes.