Decoding plant pathogen strategies: exploring effector structural insights for enhanced plant resistance
2023
Louet, Clémentine | Li de la Sierra-Gallay, Inès | van Tilbeurgh, Herman | Fudal, Isabelle | BIOlogie et GEstion des Risques en agriculture (BIOGER) ; Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) | Institut de Biologie Intégrative de la Cellule (I2BC) ; Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)
International audience
Afficher plus [+] Moins [-]anglais. The main strategy to control the fungus Leptosphaeria maculans, the causal agent of stem canker in Brassica napus, is genetic control by plant varieties carrying resistance (R) proteins. However, the massive deployment of a single source of resistance in the fields exerts strong selection pressures towards pathogen populations, leading to the rapid breakdown of the resistance. Recently, advances in effector repertoire prediction, in effector protein heterologous production and structural prediction algorithms have resulted in the identification of several effector families in L. maculans, these families being also present in other plant pathogenic fungi, mainly from the Dotheomycetes and Sordariomycetes. Furthermore, some of the structural analogues identified both in L. maculans and other plant pathogenic fungi share conserved functions during plant infection, suggesting an interesting evolutionary model. In addition, using transcriptomic data collected along the L. maculans life-cycle highlighted expression waves of distinct structural families, suggesting a striking coordination of them during the infection process. Here, we will review the recent advances in structural prediction / structure determination among L. maculans secretome and their implication to gain insight into the putative functions of candidate effectors. We will also propose possible strategies to improve resistance management or increase R proteins recognition spectrum using structural effector families.
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