Jakuschkin Boris, Fievet Virgil, Schwaller Loïc, Fort Thomas, Robin Cécile, Vacher Corinne
BIOGECO, INRA, University of Bordeaux, F-33615, Bordeaux, Pessac, France.
AgroParisTech, UMR 518 MIA, F-75005, Paris, France.
Microb Ecol. 2016 Nov;72(4):870-880. doi: 10.1007/s00248-016-0777-x. Epub 2016 May 5.
Plant-inhabiting microorganisms interact directly with each other, forming complex microbial interaction networks. These interactions can either prevent or facilitate the establishment of new microbial species, such as a pathogen infecting the plant. Here, our aim was to identify the most likely interactions between Erysiphe alphitoides, the causal agent of oak powdery mildew, and other foliar microorganisms of pedunculate oak (Quercus robur L.). We combined metabarcoding techniques and a Bayesian method of network inference to decipher these interactions. Our results indicate that infection with E. alphitoides is accompanied by significant changes in the composition of the foliar fungal and bacterial communities. They also highlight 13 fungal operational taxonomic units (OTUs) and 13 bacterial OTUs likely to interact directly with E. alphitoides. Half of these OTUs, including the fungal endophytes Mycosphaerella punctiformis and Monochaetia kansensis, could be antagonists of E. alphitoides according to the inferred microbial network. Further studies will be required to validate these potential interactions experimentally. Overall, we showed that a combination of metabarcoding and network inference, by highlighting potential antagonists of pathogen species, could potentially improve the biological control of plant diseases.
栖息于植物的微生物相互直接作用,形成复杂的微生物相互作用网络。这些相互作用既可能阻止也可能促进新微生物物种的定殖,比如一种感染植物的病原体。在此,我们的目标是确定引起橡树白粉病的白粉菌(Erysiphe alphitoides)与欧洲栓皮栎(Quercus robur L.)的其他叶部微生物之间最可能的相互作用。我们结合了宏条形码技术和一种贝叶斯网络推断方法来解析这些相互作用。我们的结果表明,感染白粉菌会伴随着叶部真菌和细菌群落组成的显著变化。结果还突出显示了13个可能与白粉菌直接相互作用的真菌操作分类单元(OTU)和13个细菌OTU。根据推断出的微生物网络,这些OTU中有一半,包括真菌内生菌点状球腔菌(Mycosphaerella punctiformis)和堪萨斯单毛孢(Monochaetia kansensis),可能是白粉菌的拮抗剂。需要进一步研究以通过实验验证这些潜在的相互作用。总体而言,我们表明,宏条形码技术和网络推断相结合,通过突出病原体物种的潜在拮抗剂,可能会改善植物病害的生物防治。