| Literature DB >> 33803862 |
Dann Turner1, Andrew M Kropinski2,3, Evelien M Adriaenssens4.
Abstract
Bacteriophage (phage) taxonomy has been in flux since its inception over four decades ago. Genome sequencing has put pressure on the classification system and recent years have seen significant changes to phage taxonomy. Here, we reflect on the state of phage taxonomy and provide a roadmap for the future, including the abolition of the order Caudovirales and the families Myoviridae, Podoviridae, and Siphoviridae. Furthermore, we specify guidelines for the demarcation of species, genus, subfamily and family-level ranks of tailed phage taxonomy.Entities:
Keywords: Caudovirales; Myoviridae; Podoviridae; Siphoviridae; demarcation criteria; phage classification; phage taxonomy
Mesh:
Year: 2021 PMID: 33803862 PMCID: PMC8003253 DOI: 10.3390/v13030506
Source DB: PubMed Journal: Viruses ISSN: 1999-4915 Impact factor: 5.048
Figure 1Line drawing of bacteriophage morphotypes, adapted from Ackermann, 2005 [6].
Figure 2Dendrogram generated by GRAViTy (http://gravity.cvr.gla.ac.uk, accessed on 5 February 2021) for DB-B: Baltimore Group Ib—Prokaryotic and archaeal dsDNA viruses (VMRv34) and annotated using iTOL [16,42]. The inside coloured ring indicates the morphotype and the outside ring the new proposed and ratified families as of 2021. The distance from tip to node, indicated by the scale rings, represents the composite generalised Jaccard distance (0–1) between two genomes calculated based on relatedness of the proteins and the genome organisation, where 0 is identical and 1 is no measurable relation between two genomes. The Jaccard distance of 0.8, unifying the majority of eukaryotic virus families is indicated in blue for illustration purposes. Bootstrap values (0–1) are indicated by branch colour on a greyscale, from light grey (0) to black (1), showing that the majority of branches are well-supported. Bootstrap values were calculated as described by Aiewsakun and Simmonds [16] by random resampling of the protein profile hidden Markov models that form the basis of the protein relatedness score, recomputing the pairwise distance matrix and then recomputing the dendrogram and repeating this 100 times.