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Poster

Session: Session 2 Presenting Authors at Posters (Evens)

P-138 - Mapping the physical and genetic interactome of Pseudomonas syringae effectors

Thursday, July 17, 2025
13:30 - 15:15  
Location: Confex Hall 3
Effector Interference Mechanisms

    Presenting Author(s)

  • JC

    Janis HT Cheng

    University of Toronto
    Markham, Ontario, Canada

    • Author(s)

  • BL

    Bradley Laflamme

    Department of Cell and Systems Biology, University of Toronto
    Toronto, Ontario, Canada

  • JM

    John MacPherson

    University of Toronto
    Toronto, Ontario, Canada

  • CB

    Charles Boone

    Professor
    Department of Molecular Genetics, University of Toronto
    Toronto, Ontario, Canada

  • AE

    Alexander W. Ensminger

    Professor
    Department of Biochemistry, University of Toronto
    Toronto, Ontario, Canada

  • DG

    David S. Guttman

    Professor
    Department of Cell and Systems Biology, University of Toronto
    Toronto, Ontario, Canada

  • DD

    Darrell Desveaux

    Professor
    Department of cell and Systems Biology, University of Toronto
    Toronto, Ontario, Canada

The dynamic relationships between pathogen effectors have been shown to dramatically influence the outcome of host-pathogen interactions. Despite the importance of effector coordination in modulating host responses and pathogen fitness, few have systematically studied this phenomenon. Here, I describe a study to comprehensively and systematically map all genetic and physical interactions between a library of ~500 effectors representing the pangenome Pseudomonas syringae effector repertoire. Using high-throughput yeast screens, our work has interrogated >200,000 pairwise effector combinations thus far, covering ~80% of the effector-effector interaction space across the P. syringae species complex. We constructed a network representing all captured binary interactions, revealing metaeffector candidates and patterns of specificity in effector-pairing, demonstrating complexity in effector repertoire composition. This data will provide testable hypotheses regarding mechanisms underlying infection strategies and regulatory relationships that play central roles in virulence.