PRJNA803042
BCMicrobiome Wheat
Plants are associated with a huge diversity of interacting microorganisms. Deciphering these microbial interactions is crucial since they underpin the regulation of plant diseases. These microbial interactions are usually identified using co-culture experiments. Without methods to predict likely interactions between species, this is a tedious and time-consuming process that cannot, therefore, be extended to the whole microbial community with which a pathogen could interact. The challenge is to predict interactions between microbial species and reconstruct interaction networks directly from environmental DNA. The BCMicrobiome project will: (1) develop generic methods for learning microbial interaction networks from metabarcoding data; and, (2) demonstrate that these new methods inform biological control of pathogens because they reveal antagonistic interactions between pathogen species and other microorganisms. This proof-of-concept study will be performed by using foliar pathogens of grapevine and wheat as model systems.