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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.

Plant pathogenic microorganisms cause substantial yield losses in several economically important crops, resulting in economic and social adversity. The spread of such plant pathogens and the emergence of new diseases is facilitated by human practices such as monoculture farming and global trade. Therefore, the early detection and identification of pathogens is of utmost importance to reduce the associated agricultural losses. In this review, techniques that are currently available to detect plant pathogens are discussed, including culture-based, PCR-based, sequencing-based, and immunology-based techniques. Their working principles are explained, followed by an overview of the main advantages and disadvantages, and examples of their use in plant pathogen detection. In addition to the more conventional and commonly used techniques, we also point to some recent evolutions in the field of plant pathogen detection. The potential use of point-of-care devices, including biosensors, have gained in popularity. These devices can provide fast analysis, are easy to use, and most importantly can be used for on-site diagnosis, allowing the farmers to take rapid disease management decisions.