ena-STUDY-INRA Bordeaux-Aquitaine (Biodiversity, Genes and Communities)-18-09-2014-15:52:38:947-278
Deciphering the pathobiome: intra-and inter-kingdom interactions involving the pathogen Erysiphe alphitoides.
Plant-inhabiting microorganisms interact directly with each other, forming complex microbial interaction networks. These networks may be disrupted by the arrival of a new species, such as a pathogen infecting the plant. Here we decipher intra-kingdom and cross-kingdom interactions involving a pathogen species, by using a Bayesian method of network inference.  We use this method to highlight the most likely interactions between Erysiphe alphitoides, the causal agent of oak powdery mildew, and other foliar microorganisms of pedunculate oak (Quercus robur L.). Our results showed that infection by E. alphitoides is accompanied by drastic changes in the foliar fungal community composition but no significant change in the bacterial community composition. Our analyses highlighted 13 fungal Operational Taxonomic Units (OTUs) and 13 bacterial OTUs that are likely to interact directly with E. alphitoides. Four of the fungal OTUs were phyllosphere yeasts. The fungal endophytes Mycosphaerella punctiformis and Monochaetia kansensis were highlighted as potential antagonists of E. alphitoides. These potential interactions will have to be validated experimentally. The study of the temporal dynamics of microbial networks during the course of infection also appears to be a promising research avenue, that will undoubtedly give deeper insights into the ecology of this disease. Overall, we showed that combining metagenomics and network ecology may improve biological control of plant diseases, by highlighting potential antagonists of pathogen species.
Plant-inhabiting microorganisms interact directly with each other, forming complex microbial interaction networks. These networks may be disrupted by the arrival of a new species, such as a pathogen infecting the plant. Here we decipher intra-kingdom and cross-kingdom interactions involving a pathogen species, by using a Bayesian method of network inference.  We use this method to highlight the most likely interactions between Erysiphe alphitoides, the causal agent of oak powdery mildew, and other foliar microorganisms of pedunculate oak (Quercus robur L.). Our results showed that infection by E. alphitoides is accompanied by drastic changes in the foliar fungal community composition but no significant change in the bacterial community composition. Our analyses highlighted 13 fungal Operational Taxonomic Units (OTUs) and 13 bacterial OTUs that are likely to interact directly with E. alphitoides. Four of the fungal OTUs were phyllosphere yeasts. The fungal endophytes Mycosphaerella punctiformis and Monochaetia kansensis were highlighted as potential antagonists of E. alphitoides. These potential interactions will have to be validated experimentally. The study of the temporal dynamics of microbial networks during the course of infection also appears to be a promising research avenue, that will undoubtedly give deeper insights into the ecology of this disease. Overall, we showed that combining metagenomics and network ecology may improve biological control of plant diseases, by highlighting potential antagonists of pathogen species.