New Multilocus Variable-Number Tandem-Repeat Analysis (MLVA) Scheme for Fine-Scale Monitoring and Microevolution-Related Study of Ralstonia pseudosolanacearum Phylotype I Populations

Bacterial wilt caused by the species complex (RSSC) is considered one of the most harmful plant diseases in the world. Special attention should be paid to phylotype I due to its large host range, its worldwide distribution, and its high evolutionary potential. So far, the molecular epidemiology and population genetics of this bacterium are poorly understood. Until now, the genetic structure of the RSSC has been analyzed on the worldwide and regional scales. Emerging questions regarding evolutionary forces in RSSC adaptation to hosts now require genetic markers that are able to monitor RSSC field populations. In this study, we aimed to evaluate the multilocus variable-number tandem-repeat analysis (MLVA) approach for its ability to discriminate genetically close phylotype I strains and for population genetics studies. We developed a new MLVA scheme (MLVA-7) allowing us to genotype 580 phylotype I strains extracted from susceptible and resistant hosts and from different habitats (stem, soil, and rhizosphere). Based on specificity, polymorphism, and the amplification success rate, we selected seven fast-evolving variable-number tandem-repeat (VNTR) markers. The newly developed MLVA-7 scheme showed higher discriminatory power than the previously published MLVA-13 scheme when applied to collections sampled from the same location on different dates and to collections from different locations on very small scales. Our study provides a valuable tool for fine-scale monitoring and microevolution-related study of phylotype I populations. Understanding the evolutionary dynamics of adaptation of plant pathogens to new hosts or ecological niches has become a key point for the development of innovative disease management strategies, including durable resistance. Whereas the molecular mechanisms underlying virulence or pathogenicity changes have been studied thoroughly, the population genetics of plant pathogen adaptation remains an open, unexplored field, especially for plant-pathogenic bacteria. MLVA has become increasingly popular for epidemiosurveillance and molecular epidemiology studies of plant pathogens. However, this method has been used mostly for genotyping and identification on a regional or global scale. In this study, we developed a new MLVA scheme, targeting phylotype I of the soilborne species complex (RSSC), specifically to address the bacterial population genetics on the field scale. Such a MLVA scheme, based on fast-evolving loci, may be a tool of choic