Proteome analysis of the plant pathogenic fungus Monilinia laxa showing host specificity

Brown rot fungus Monilinia laxa (Aderh. & Ruhl.) Honey is an important plant pathogen in stone and pome fruits in Europe. We applied a proteomic approach in a study of M. laxa isolates obtained from apples and apricots in order to show the host specifity of the isolates and to analyse differentially expressed proteins in terms of host specifity, fungal pathogenicity and identification of candidate proteins for diagnostic marker development. Extracted mycelium proteins were separated by 2-D electrophoresis (2-DE) and visualized by Coomassie staining in a non-linear pH range of 3-11 and [M.sub.r] of 14-116 kDa. We set up a 2-DE reference map of M. laxa, resolving up to 800 protein spots, and used it for image analysis. The average technical coefficient of variance (13%) demonstrated a high reproducibility of protein extraction and 2-D polyacrylamide gel electrophoresis (2-DE PAGE), and the average biological coefficient of variance (23%) enabled differential proteomic analysis of the isolates. Multivariate statistical analysis (principal component analysis) discriminated isolates from two different hosts, providing new data that support the existence of a M. laxa specialized form f. sp. mali, which infects only apples. A total of 50 differentially expressed proteins were further analyzed by LC-MS/MS, yielding 41 positive identifications. The identified mycelial proteins were functionally classified into 6 groups: amino acid and protein metabolism, energy production, carbohydrate metabolism, stress response, fatty acid metabolism and other proteins. Some proteins expressed only in apple isolates have been described as virulence factors in other fungi. The acetolactate synthase was almost 11-fold more abundant in apple-specific isolates than in apricot isolates and it might be implicated in M. laxa host specificity. Ten proteins identified only in apple isolates are potential candidates for the development of M. laxa host-specific diagnostic markers. Key words: proteomics, fungi, two-dimensional electrophoresis