ArticlePloS one2024
Evaluation of sequence-based tools to gather more insight into the positioning of rhizogenic agrobacteria within the Agrobacterium tumefaciens species complex.
Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Novel LyticViruses · 2026Article
- Latent Dirichlet Allocation reveals tomato root-associated bacterial interactions responding to hairy root disease.Environmental microbiome · 2025Article
- Effect of Selected Truffle-Associated Bacteria and Fungi on the Mycorrhization ofBiotech (Basel (Switzerland)) · 2025Article
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5 authors.
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Abstract
Rhizogenic Agrobacterium, the causative agent of hairy root disease (HRD), is known for its high phenotypic and genetic diversity. The taxonomy of rhizogenic agrobacteria has undergone several changes in the past and is still somewhat controversial. While the classification of Agrobacterium strains was initially mainly based on phenotypic properties and the symptoms they induced on plants, more and more genetic information has been used along the years to infer Agrobacterium taxonomy. This has led to the definition of the so-called Agrobacterium tumefaciens species complex (Atsc), which comprises several genomospecies. Interestingly, the rhizogenic Agrobacterium strains are found in several of these genomospecies. Nevertheless, even up until today Agrobacterium strains, and in particular rhizogenic agrobacteria, are prone to misclassification and considerable confusion in literature. In this study, we evaluated different phylogenetic analysis approaches for their use to improve Agrobacterium taxonomy and tried to gain more insight in the classification of strains into this complex genus, with a particular focus on rhizogenic agrobacteria. The genome sequence analysis of 580 assemblies, comprising Agrobacterium, Allorhizobium and Rhizobium strains demonstrated that phylogenies based on single marker genes, such as the commonly used 16S rRNA and recA gene, do not provide sufficient resolution for proper delineation of the different genomospecies within the Atsc. Our results revealed that (in silico) multi-locus sequences analysis (MLSA) in combination with average nucleotide identity (ANIb) at a 94.0% threshold delineates genomospecies accurately and efficiently. Additionally, this latter approach permitted the identification of two new candidate genomospecies.
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