Fujita Medical Journal
Online ISSN : 2189-7255
Print ISSN : 2189-7247
ISSN-L : 2189-7247
Original Article
Taxonomic classification of genus Aeromonas using open reading frame-based binarized structure network analysis
Aki SakuraiMasahiro SuzukiKengo HayashiYohei Doi
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Supplementary material

2024 Volume 10 Issue 1 Pages 8-15

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Abstract

Objectives: Taxonomic assignment based on whole-genome sequencing data facilitates clear demarcation of species within a complex genus. Here, we applied a unique pan-genome phylogenetic method, open reading frame (ORF)-based binarized structure network analysis (OSNA), for taxonomic inference of Aeromonas spp., a complex taxonomic group consisting of 30 species.

Methods: Data from 335 publicly available Aeromonas genomes, including the reference genomes of 30 species, were used to build a phylogenetic tree using OSNA. In OSNA, whole-genome structures are expressed as binary sequences based on the presence or absence of ORFs, and a tree is generated using neighbor-net, a distance-based method for constructing phylogenetic networks from binary sequences. The tree built by OSNA was compared to that constructed by a core-genome single-nucleotide polymorphism (SNP)-based analysis. Furthermore, the orthologous average nucleotide identity (OrthoANI) values of the sequences that clustered in a single clade in the OSNA-based tree were calculated.

Results: The phylogenetic tree constructed with OSNA successfully delineated the majority of species of the genus Aeromonas forming conspecific clades for individual species, which was corroborated by OrthoANI values. Moreover, the OSNA-based phylogenetic tree demonstrated high compositional similarity to the core-genome SNP-based phylogenetic tree, supported by the Fowlkes–Mallows index.

Conclusions: We propose that OSNA is a useful tool in predicting the taxonomic classification of complex bacterial genera.

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