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Microbial Ecology

, Volume 72, Issue 4, pp 870–880 | Cite as

Deciphering the Pathobiome: Intra- and Interkingdom Interactions Involving the Pathogen Erysiphe alphitoides

  • Boris Jakuschkin
  • Virgil Fievet
  • Loïc Schwaller
  • Thomas Fort
  • Cécile Robin
  • Corinne VacherEmail author
Environmental Microbiology

Abstract

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.

Keywords

Plant microbiota Plant-pathogen interaction Pathobiome Microbial network Network inference Disease resistance Biocontrol Powdery mildew 

Notes

Acknowledgments

We thank Xavier Capdevielle, Olivier Fabreguettes, Laure Villate, and Martine Martin-Clotté (INRA, BioGeCo) for technical assistance and advice during preliminary experiments and during the course of the study. We also thank Franck Salin, Thibaut Decourcelle, Adline Delcamp, and Christophe Hubert (CGFB, Bordeaux) for sequencing the samples. The costs of sampling and sequencing were covered by the AIP Bioressource METAPHORE. Computing facilities were provided by the MCIA (Mésocentre de Calcul Intensif Aquitain) of the Université de Pau et des Pays de l’Adour. BJ received a grant from the French Ministry of Research and Education (MENRT no. 2011/AF/57). We thank Cindy E. Morris for helpful discussions about the phyllosphere. We thank Sarah Ouadah and Stéphane Robin for supervising the network analyses. We thank Marie-Laure Desprez-Loustau, Arndt Hampe, Samantha Yeo, and David Bohan and four anonymous reviewers for their very helpful comments. We also thank Julie Sappa from Alex Edelman & Associates for English language revision.

Supplementary material

248_2016_777_MOESM1_ESM.pdf (1002 kb)
ESM 1 Methods S1 – Preliminary experiment assessing the effect of oak leaf storage on fungal community composition. Table S1 - 454 pyrosequencing primer sequences used for fungi. Table S2 - Illumina primer sequences used for bacteria. Figure S1 - Taxonomic distribution of the fungal OTUs. Figure S2 - Taxonomic distribution of the bacterial OTUs (a) at the phylum level and (b) at the order level. Figure S3 – Principal coordinates analysis showing Bray-Curtis dissimilarities in bacterial community composition between the leaves of an oak tree (Quercus robur L.) highly susceptible to the fungal pathogen Erysiphe alphitoides. Table S3 - Fungal and bacterial OTUs significantly associated to samples highly infected with E. alphitoides. Text S1 - Representative sequences of the fungal OTUs associated with infected leaves or interacting directly with E. alphitoides. Text S2 Representative sequences of the bacterial OTUs associated infected leaves or interacting directly with E. alphitoides. (PDF 1002 kb)

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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Boris Jakuschkin
    • 1
  • Virgil Fievet
    • 1
  • Loïc Schwaller
    • 2
    • 3
  • Thomas Fort
    • 1
  • Cécile Robin
    • 1
  • Corinne Vacher
    • 1
    Email author
  1. 1.BIOGECO, INRAUniversity of BordeauxBordeauxFrance
  2. 2.AgroParisTechUMR 518 MIAParisFrance
  3. 3.INRA, UMR 518 MIAParisFrance

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