Algorithms for Effector Prediction in Plant Pathogens and Pests: Achievements and Current Challenges

Effectors are key organism-associated molecules that aid in the establishment of interactions with other organisms. Effectoromics has become an important area of research in phytopathology. The lack of sequence conservation among effectors, even in closely related organisms, has led us to believe that effectors from organisms of different kingdoms are completely unrelated, which has fostered the independent development of effector identification strategies in bacteria, fungi, phytoplasmas, etc. This review focuses on the different algorithms available for effector identification in different plant pathogens and pests, using the following classification: (1) translocated effectors (bacteria, oomycete) and (2) secreted effectors (phytoplasmas, fungi, insects, nematodes). The objective of this type of classification is to identify, for the first time, the common features that exist among these organisms to streamline future effectoromics identification strategies. Among the organisms’ commonalities, certain bacteria, fungi, phytoplasmas, and nematodes may cause similar symptoms, and some of their effectors may target the same proteins or biological processes in the plant hosts. The integration of effector analyses of organisms of different living kingdoms, through the identification of common short linear motifs, domains, and three-dimensional structures, may aid in the development of novel algorithms for effectoromics. Future algorithms may contemplate these highlighted features and will be better equipped to identify not only canonical effectors but highly elusive non-canonical effectors as well.