Wheat leaf rust is caused by the fungus Puccinia triticina. The genetics of resistance follows the gene-for-gene hypothesis, and thus the presence or absence of a single host resistance gene renders a plant resistant or susceptible to a leaf rust race bearing the corresponding avirulence gene. To investigate some of the changes in the proteomes of both host and pathogen during disease development, a susceptible line of wheat infected with a virulent race of leaf rust were compared to mock-inoculated wheat using 2-DE (with IEF pH 4-8) and MS. Up-regulated protein spots were excised and analyzed by MALDI-QqTOF MS/MS, followed by cross-species protein identification. Where possible MS/MS spectra were matched to homologous proteins in the NCBI database or to fungal ESTs encoding putative proteins. Searching was done using the MASCOT search engine. Remaining unmatched spectra were then sequenced de novo and queried against the NCBInr database using the BLAST and MS BLAST tools. A total of 32 consistently up-regulated proteins were examined from the gels representing the 9-day post-infection proteome in susceptible plants. Of these 7 are host proteins, 22 are fungal proteins of known or hypothetical function and 3 are unknown proteins of putative fungal origin.

Puccinia triticina causes leaf rust, a disease that causes annual yield losses in wheat. It is an obligate parasite that invades the host leaf and forms intracellular structures called haustoria, which obtain nutrients and suppress host immunity using secreted proteins called effectors. Since effector proteins act at the frontier between plant and pathogen and help determine the outcome of the interaction, it is critical to understand their functions. Here, we used a direct proteomics approach to identify effector candidates from P. triticina Race 1 haustoria isolated with a specific monoclonal antibody. Haustoria were >95% pure and free of host contaminants. Using high resolution MS we have identified 1192 haustoria proteins. These were quantified using normalized spectral counts and spanned a dynamic range of three orders of magnitude, with unknown proteins and metabolic enzymes as the most highly represented. The dataset contained 140 candidate effector proteins, based on the presence of a signal peptide and the absence of a known function for the protein. Some of these candidates were significantly enriched with cysteine, with up to 13 residues per protein and up to 6.8% cysteine in composition.