A novel method and model system to investigate plant–microbiome coevolution

<ns5:p> Background Interactions between plants and microorganisms are well studied and have revealed numerous beneficial microbes and genetic determinants underlying these associations. However, the coevolutionary processes shaping plant–microbiome relationships remain poorly understood. In particular, little information exists on the dynamics of these interactions across successive plant generations, limiting our ability to evaluate long-term effects of microbial inoculants. To address this gap, we developed a novel experimental evolution model coupling <ns5:italic>Brassica rapa</ns5:italic> fast-cycling plants, a fungal pathogen ( <ns5:italic>Rhizoctonia solani</ns5:italic> ), and <ns5:italic>ad hoc</ns5:italic> –designed microbial communities. Methods We established a complete seed-to-seed framework to characterize how microbial communities influence plants over multiple generations, and in turn, how the host genotype shapes plant microbiota. First, we optimized a protocol to produce gnotobiotic <ns5:italic>Brassica rapa</ns5:italic> fast-cycling plants and we inoculated them with defined microbial communities using a soil-based method. We then developed a reproducible pathosystem using <ns5:italic>Rhizoctonia solani</ns5:italic> to assess plant health and quantify the effects of microbial communities. Finally, we implemented a standardized procedure to track plant responses and evolutionary changes across successive cycles. Results Our experimental evolution framework enabled to test three <ns5:italic>ad hoc</ns5:italic> –designed microbial communities under greenhouse conditions and generate biological material suitable for future evolutionary analyses. Starting from a diverse pool of fast-cycling plant families, we observed phenotypic responses across plant generations, particularly in response to <ns5:italic>R. solani.</ns5:italic> The methods presented here form the foundation of a broader study aimed at elucidating how microbial communities shape plant evolution in the holobiont context under biotic constraints. Conclusions Our model provides a versatile and accessible approach to study plant–microbiome interactions and their evolutionary impact over multiple generations. It can be readily implemented in other laboratories without the need for costly equipment, making it a valuable tool for exploring how microbial communities influence plant adaptation to biotic stresses. </ns5:p>