Bioinformatic Elucidation of Consensus Phosphorylation Motifs Utilizing Inter-Species Functional Data.

RP-4 It is estimated that the world needs to produce 40% more rice by 2030 to feed its more than five billion rice consumers. Fungal disease, particularly that caused by the rice blast fungus Magnaporthe oryzae, is a major factor limiting rice production. A key to controlling rice blast disease is a better understanding of M. oryzae's pathogenic mechanisms; an important part of which resides in the ability of cellular signaling molecules (kinases) to phosphorylate a core set of transcription factors (TF) in a direct and controlled manner. Therefore, the more we know about the downstream targets of kinases, their associated pathways, and TF-regulated genes, the more effective controlling pathogenicity efforts will be. Previous pathway and network structure research in S. cerevisiae and H. sapiens may be utilized to better understand cellular signaling in M. oryzae when investigating similar proteins. Large scale protein phosphorylation microarrays can be used to accurately identify functional TF targets of homologous kinases across these species. Potentially phosphorylated binding motifs were identified in these TFs using the Pratt algorithm that detects sequence patterns. 1These TF phosphorylation motifs were used to examine the shared functionality between homologous kinases. Such motifs may also provide potential chemical targets and aid in developing disease control strategies. Our findings showed that in all three species there were slightly more kinases that fell into the MAPK kinases family, and within M. oryzae enriched MAPK TFs reached 75.64% and 77.54% and 90.78% in H. sapiens and S. cerevisiae respectively. In our continued mission to fully understand the transcriptional control of each gene and the targets of each TF involved in controlling infection related development and pathogenicity, future research includes comparing the data compiled from Pratt with other motif-finding programs and eventually composing an open-to-the-public online M. oryzae TF database.