Integrated inference and evaluation of host-fungi interaction networks.

摘要: Fungal microorganisms frequently lead to life-threatening infections. Within this group of pathogens, the commensal Candida albicans and filamentous fungus Aspergillus fumigatus are by far most important causes invasive mycoses in Europe. A key capability for host invasion immune response evasion specific molecular interactions between fungal pathogen its human host. Experimentally validated knowledge about these crucial is rare literature even specialized host-pathogen databases mainly focus on bacterial viral whereas information fungi still sparse. To establish large-scale host-fungi interaction networks a systems biology scale, we develop an extended inference approach based protein orthology data gene functions. Using yeast intraspecies as template, derive large network pathogen-host interactions. Rigorous filtering refinement steps cellular localization pathogenicity predicted interactors yield primary scaffold fungi-human fungi-mouse networks. Specific enrichment known pathogenicity-relevant genes indicates biological relevance detailed inspection functionally relevant subnetworks reveals novel host-fungal candidates such virulence factor PLB1 anti-fungal APP. Our results demonstrate applicability interolog-based predication methods underline importance attain biologically more This integrated framework can serve basis future analyses high-throughput transcriptome proteome data.