A Bioinformatic Guide to Identify Protein Effectors from Phytopathogens

Methods Mol Biol. 2023:2659:95-101. doi: 10.1007/978-1-0716-3159-1_8.

Abstract

Phytopathogenic fungi are a diverse and widespread group that has a significant detrimental impact on crops with an estimated annual average loss of 15% worldwide. Understanding the interaction between host plants and pathogenic fungi is critical to delineate underlying mechanisms of plant defense to mitigate agricultural losses. Fungal pathogens utilize suites of secreted molecules, called effectors, to modulate plant metabolism and immune response to overcome host defenses and promote colonization. Effectors come in many flavors including proteinaceous products, small RNAs, and metabolites such as mycotoxins. This review will focus on methods for identifying protein effectors from fungi. Excellent reviews have been published to identify secondary metabolites and small RNAs from fungi and therefore will not be part of this review.

Keywords: Bioinformatics; Co-expression networks; Fusarium graminearum; Protein effectors; RNA-seq; Systems biology.

Publication types

  • Review

MeSH terms

  • Computational Biology / methods
  • Fungal Proteins* / analysis
  • Fungi* / chemistry
  • Fungi* / classification
  • Fungi* / metabolism
  • Host Microbial Interactions
  • Machine Learning
  • Plant Diseases* / microbiology
  • Secretome*

Substances

  • Fungal Proteins