Integrating ANI and phylogenies for re-evaluation of Fusobacterium taxonomy and disease associations

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Authors: Dexi Bi, Yuli Wu, Guo Ji, Xingchen Zhu, Hui Li, Ruting Xie, Yan Gao, Zixin Deng, Dongyan Han, H L Qin, Qing Wei
Cited by: 3
References: 59

Abstract

The genus Fusobacterium encompasses significant pathogens implicated in diseases spanning from infections to cancer. However, taxonomic ambiguities persist within the genus, particularly concerning Fusobacterium nucleatum (sensu lato). Through genus-wide average nucleotide identity (ANI) and phylogenetic analyses of 540 Fusobacterium genomes, we identify an ANI gap (93.38%−93.89%) for species delineation, leading to comprehensive taxonomic revisions that resolve these ambiguities. We further establish gyrB and rpoB as high-resolution taxonomic markers with phylogenies consistently supporting the revised taxonomy. Leveraging these markers, we develop B&B, a general strategy for precise species identification without whole-genome sequencing, and validate its accuracy in clinically relevant strains. Integrating the revised taxonomy with genomic/metagenomic toolkits demonstrate broad utilities, reinterpreting key colorectal cancer-associated species. This work establishes a unified taxonomic framework and enables standardised species classification for Fusobacterium isolates and microbiomes, highlighting the genetic divergence among Fusobacterium species and providing the taxonomic precision essential for advancing Fusobacterium-related research. Bacteria of the genus Fusobacterium are associated with diverse diseases, but taxonomic ambiguities complicate species-level identification. Here, the authors describe practical methods for Fusobacterium species identification, which allows a reinterpretation of disease associations.

Fields of Study & Subjects

Otolaryngology and Infectious Diseases Gut microbiota and health Bacterial Identification and Susceptibility Testing

Publication details

Journal / source
Nature Communications
Publisher
Springer Science and Business Media LLC
Volume
17
Issue
1
Publication date
10 March 2026
Language
EN