Complete and Circularized Genome Sequences of 17 Xanthomonas Strains Responsible for Common Bacterial Blight of Bean

A stage-dependent seed defense response to explain efficient seed transmission of Xanthomonas citri pv. fuscans to common bean

Although seed represents an important means of plant pathogen dispersion, the seed-pathogen dialogue remains largely unexplored. A multiomic approach was performed at different seed developmental stages of common bean (Phaseolus vulgaris L.) during asymptomatic colonization by Xanthomonas citri pv. fuscans (Xcf), At the early seed developmental stages, we observed high transcriptional changes both in seeds with bacterial recognition and defense signal transduction genes, and in bacteria with up-regulation of the bacterial type 3 secretion system. This high transcriptional activity of defense genes in Xcf-colonized seeds during maturation refutes the widely diffused assumption considering seeds as passive carriers of microbes. At later seed maturation stages, few transcriptome changes indicated a less intense molecular dialogue between the host and the pathogen, but marked by changes in DNA methylation of plant defense genes, in response to Xcf colonization. We showed examples of pathogen-specific DNA methylations in colonized seeds acting as plant defense silencing to repress plant immune response during the germination process. Finally, we propose a novel plant-pathogen interaction model, specific to the seed tissues, highlighting the existence of distinct phases during seed-pathogen interaction with seeds being actively interacting with colonizing pathogens, then both belligerents switching to more passive mode at later stages.

Improving Common Bacterial Blight Phenotyping by Using Rub Inoculation and Machine Learning: Cheaper, Better, Faster, Stronger

Accurate assessment of plant symptoms plays a key role for measuring the impact of pathogens during plant-pathogen interaction. Common bacterial blight caused by Xanthomonas phaseoli pv. phaseoli and X. citri pv. fuscans is a major threat to common bean. The pathogenicity of these bacteria is variable among strains and depends mainly on a type III secretion system and associated type III effectors such as transcription activator-like effectors. Because the impact of a single gene is often small and difficult to detect, a discriminating methodology is required to distinguish the slight phenotype changes induced during the progression of the disease. Here, we compared two different inoculation and symptom assessment methods for their ability to distinguish two tal mutants from their corresponding wild-type strains. Interestingly, rub inoculation of the first leaves combined with symptom assessment by machine learning-based imaging allowed significant distinction between wild-type and mutant strains. By contrast, dip inoculation of first-trifoliate leaves combined with chlorophyll fluorescence imaging did not differentiate the strains. Furthermore, the new method developed here led to the miniaturization of pathogenicity tests and significant time savings.