PHI-Nets

PHI-Nets reconstructs and analyzes protein–protein interaction (PPI) networks for Ascomycete fungal pathogens to identify putative virulence-interacting proteins and small interfering RNA (siRNA) targets.

Key Features:

• Interactome reconstruction: Computational reconstruction of interactomes for 15 Ascomycete fungal species spanning nine orders, including Aspergillus fumigatus, Bipolaris sorokiniana, Blumeria graminis f. sp. hordei, Botrytis cinerea, Colletotrichum gloeosporioides, Colletotrichum graminicola, Fusarium graminearum, Fusarium oxysporum f. sp. lycopersici, Fusarium verticillioides, Leptosphaeria maculans, Magnaporthe oryzae, Saccharomyces cerevisiae, Sclerotinia sclerotiorum, Verticillium dahliae, and Zymoseptoria tritici.
• Interolog and domain-based inference: Prediction of PPIs using interolog mapping and domain-based approaches that transfer known interactions from other species.
• Network cartography analysis: Use of network cartography to associate functional patterns with genes annotated for pathogenicity by examining network topology.
• Random walk with restart profiling: Application of a random walk with restart algorithm in Fusarium graminearum to profile the distribution of annotated genes and suggest co-location of virulence-related genes.
• siRNA target mapping: Mapping of previously identified small silencing plant RNAs to their fungal targets in Botrytis cinerea and Fusarium graminearum.
• Phenotypic network analysis: Phenotypic network analysis that highlighted eight targets from Botrytis cinerea and 35 predicted interacting proteins in Fusarium graminearum as candidate virulence genes.
• Identification of candidate virulence factors: Prioritization of putative virulence-interacting proteins and siRNA targets for further experimental validation.

Scientific Applications:

• PPI annotation in fungal pathogens: Elucidating and annotating protein–protein interactions among Ascomycete fungal pathogens to inform functional genomics.
• Comparative interactomics: Comparative analysis across 15 Ascomycete species to investigate conserved and species-specific pathogenic mechanisms.
• Pathogenicity gene prioritization: Using network cartography and random walk profiling to associate topology with pathogenicity annotations and prioritize candidate virulence genes for validation.
• Host–pathogen RNA interactions: Identifying fungal targets of small silencing plant RNAs to study host-induced gene silencing and cross-kingdom RNA interference.
• Experimental target selection: Prioritizing candidate virulence genes and interacting proteins for follow-up experimental validation relevant to disease control research.

Methodology:

Computational reconstruction of interactomes for 15 Ascomycete species using interolog and domain-based inference, followed by network cartography analysis, application of a random walk with restart algorithm for Fusarium graminearum, mapping of small silencing plant RNAs to targets, and phenotypic network analysis.