Proteomic analysis of exudate of Cercospora armoraciae from Armoracia rusticana

Cercospora armoraciae causes leaf spot disease on Armoracia rusticana. Exudation of droplets, when grown on PDA, distinguishes this fungi from other members of the genus Cercospora. The role this exudate plays in the virulence of this pathogen has not been elucidated. To explore this, we characterized the transcriptome of C. armoraciae and the proteome of exudate associated with this plant pathogen.

Transcriptome and GO analysis of C. armoraciae found most proteins in the exudate. GO analysis suggested that a considerable proportion of proteins were involved in cellular process and metabolic process, which suggests exudates maintain the metabolic balance of this fungi. Some proteins annotated to the phenylalanine metabolism, which suggests that the exudates may enhance the virulence of this pathogen. Some proteins annotated to the phenylalanine metabolism, which suggests that the exudates may enhance the pathogenicity of the pathogen. Also some proteins were annotated to the peroxisome metabolic pathway and the fatty acid biosynthesis pathways. These pathways may confer antifungal, antioxidant and antimicrobial activity on the exudates.

Virulence of three strains of C. armoraciae was evaluated in greenhouse assays. De novo sequencing was applied to assemble transcriptome from these strains. Nano-HPLC-MS/MS analysis was used to identify proteins in the pathogen exudate. Identified proteins were functionally classified and annotated using GO, KEGG, and COG/KOG bioinformatics analysis methods.

When treated with the exudate of C. armoraciae strain SCa-01, leaves of A. rusticana showed yellowing and necrosis of the leaves and similar symptoms to plants inoculated with this fungi. A total of 14,937 unigenes were assembled from C. armoraciae, and 576 proteins comprising 1,538 peptides, 1,524 unique peptide, were identified from the exudate. GO annotation classified 411 proteins (71%) into 27 functional categories, namely, 12, seven and eight biological process, cellular component, and molecular function subcategories, respectively. KEGG analysis assigned 314 proteins to 84 signaling/metabolic pathways, and 450 proteins were annotated against the COG/KOG database.