Biotic Stress

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Ben M'Barek
Laboratory of Molecular Plant Physiology, Biotechnology Center of Borj Cedria (CBBC)
Mahmoud Gargouri, Hesham A.Y Gibriel, Richard B. Todd, Michael F. Seidl, Gerrit H.J. Kema
Poster or Plenary?: 
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Septoria tritici blotch disease, caused by the fungus Zymoseptoria tritici, is a major threat to global wheat production. With the recent advances in high-throughput DNA-based technologies, Z. tritici has become a powerful model system for the discovery of candidate determinants that underlie virulence and host specialization. Although a few important virulence/regulatory genes have been identified, a global understanding of the larger regulatory network has not been developed. Therefore, to uncover the transcriptional regulatory networks of the infection cycle and most particularly the regulatory hubs that control the switch between the biotrophic and necrotrophic phases, we applied an integrated approach combining transcriptomics, proteomics, and metabolomics analyses based on the identification of plant and fungal transcription factors and regulators, which we characterized from the newly annotated genome sequence of the reference isolate IPO323 (Grandaubert et al., 2015) and using datasets from Rudd et al. (2015). Bread wheat transcription factors and regulators were identified by querying the proteome and subsequent categorization from the Plant Transcription Factor database (PTFDB). Similarly, Z. tritici transcription factors and regulators were identified and categorized using the PFAM TF family databases, and following fungal transcription factor rules as outlined by Todd et al. (2014) and rules we developed for fungal transcription regulators. Insights into transcription factors and regulators will enable synthetic biology approaches to alter the Z. tritici-wheat interaction and lead to rewiring of the regulatory networks thereby turning off the fungal infection process. Beyond providing insights into the regulatory systems-levels involved in Z. tritici-wheat interaction, we believe that our dataset and approach sets the stage for an emerging series of studies that will decipher the dynamic regulatory networks in other plant-pathogen interactions.

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