Deciphering pathogenicity mechanisms of phytopathogenic fungi and Oomycetes using protein network analysis
2Plant Pathology and Weed Research, Agricultural Research Organization (ARO), Volcani Center, Rishon LeZion, Israel
3Postharvest and Food Sciences, Agricultural Research Organization (ARO), Volcani Center, Rishon LeZion, Israel
Filamentous eukaryotic pathogens (FEPs, i.e., fungi and oomycetes) cause extensive yield losses of staple crops worldwide. Yet, there is scarce amount of studies using large-scale comparative genomic analysis to identify their pathogenicity associated functions and pathways.
To study pathogenicity mechanism in FEPs, we are using systematic computational comparison, followed by functional validation on economically significant pathogens. We have constructed protein similarity network 1-2 based on complete proteomes of 82 FEPs exhibiting diverse lifestyles, and the major pathogenicity strategies: 22 necrotrophs, 20 hemibiotrophs, 18 biotrophs, and 17 saprophytes. Our analysis identified 60 core pathogenicity functions that were found in at least 70% of the organisms representing each of the pathogenicity strategies. Enrichment analysis of KEGG orthologs and InterPro domains, revealed that these core functions contain a specific arsenal of proteins participating in carbohydrates metabolism, proteolysis, antioxidant activity, plant-toxicity, and transcription regulation. Transcription profiling of Botrytis cinerea infection on tomato have demonstrated that 50% of these 60 pathogenicity determinants were upregulated in the course of pathogenicity. We are currently validating the role of selected pathogenicity determinants in the infection process, using functional molecular approach, on pathogens representing pathogenicity strategies: B. cinerea (necrotroph), Colletotrichum gloeosporioides (hemibiotrophs), and Erysiphe necator (biotroph).
Results from this study should increase our understanding of plant pathogenicity mechanisms, and consequently open new avenues for control of these pathogens. Pathogenicity determinants discovered in this work may empower screening for resistant traits (using effectoromics), and accelerate breeding programs for resistant plants.
1 Harel A, Karkar S, Falkowski P, and Bhattacharya D. (2015). Deciphering primordial cyanobacterial genome functions from network analysis of proteins. Curr Biol. 25:628-34.
2 Harel A , Bromberg Y, Falkowski P, and Bhattacharya D. (2013). The evolutionary history of redox metal-binding domains across the tree of life. Proc Natl Acad Sci USA. 111:7042-47.
Equal contribution - E. Pandaranayaka PJ and D.A. Srivastava
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