Genomic Metrics Applied to (): Species Reclassification, Identification of Unauthentic Genomes and False Type Strains.

Taxonomic decisions within the order have relied heavily on the interpretations of highly conserved 16S rRNA sequences and DNA-DNA hybridizations (DDH). Currently, bacterial species are defined as including strains that present 95-96% of average nucleotide identity (ANI) and 70% of digital DDH (dDDH). Thus, ANI values from 520 genome sequences of type strains from species of order were computed. From the resulting 270,400 comparisons, a ≥95% cut-off was used to extract high identity genome clusters through enumerating maximal cliques. Coupling this graph-based approach with dDDH from clusters of interest, it was found that: (i) there are synonymy between and , and , "," and , , and , , and , , and , and and ; (ii) is not a synonym of ; (iii) "" subsp. and "" subsp. represent members of different species; (iv) the genome accessions GCF_003024615.1 (" LMG 6,125"), GCF_003024595.1 (" LMG 11,892"), GCF_003096615.1 (" DSM 760"), and GCF_000373025.1 (" R-602 sp") are not from the genuine type strains used for the respective species descriptions; and v) "" Py2 and "" KCTC 2,477 represent cases of misuse of the term "type strain". comb. nov. and the reclassification of as is also proposed. To facilitate the downstream analysis of large ANI matrices, we introduce here ProKlust ("Prokaryotic Clusters"), an R package that uses a graph-based approach to obtain, filter, and visualize clusters on identity/similarity matrices, with settable cut-off points and the possibility of multiple matrices entries.