Phytophthora sojae causes severe damage in soybean crops and results in $1–2 million in annual losses for commercial farmers in the United States. Phytophthora ramorum, which causes sudden oak death, has attacked and killed tens of thousands of oak trees in California and Oregon. The sequences of both genomes have served as a resource for the entire scientific community, revealing a recent, large expansion and diversification of many deadly genes involved in infection of the plant hosts of Phytophthora.
Virginia Bioinformatics Institute Professor Brett Tyler and his research group who worked on the Phytophthora genome sequences analyzed the genetic information using bioinformatic tools and identified an enormous superfamily of pathogen genes involved in the infection of plants1. These genes produce virulence proteins that manipulate how plant cells work in such a way as to make the plant hosts more susceptible to infection. The researchers subsequently identified the region of these virulence proteins containing the amino acid sequence motifs RXLR and dEER that enables them to enter the cells of their hosts by carrying the virulence proteins across the membrane surrounding plant cells without any additional machinery from the pathogen2, as well as the fundamental entry mechanism that actually allows dangerous fungal microbes to infect plants and cause disease3. These discoveries pave the way for the development of new intervention strategies to protect plant, and even some animal cells, from deadly fungal infections.
The project to sequence the genomes of Phytophthora ramorum and Phytophthora sojae started in 2002. The sequencing of Phytophthora ramorum represented the fastest sequencing of a newly emerged pathogen other than the Severe Acute Respiratory Syndrome virus; Phytophthora ramorum was identified in 2000 and its draft sequence was complete by 2004. The work, which was funded by the National Science Foundation, the United States Department of Agriculture’s National Research Initiative, and the Department of Energy, was carried out by an international team of scientists led by the Department of Energy’s Joint Genome Institute and the Virginia Bioinformatics Institute.
“Both evolutionary biologists and plant pathologists have shown strong interest in our paper,” Tyler explained. “But the greatest impact by far has stemmed from the extensive knowledge of oomycete virulence proteins that has originated from the genome sequences.”
Read the original paper outlining the draft genome sequences of Phytophthora sojae and Phytophthora ramorum:
Tyler BM, Tripathy S, Zhang X, et al. (2006) Phytophthora genome sequences uncover evolutionary origins and mechanisms of pathogenesis. Science 313:1261–1266. [PMID: 16946064]
1 Jiang, RHY, Tripathy S, Govers F, Tyler BM (2008) RXLR effector reservoir in two Phytophthora species is dominated by a single rapidly evolving super-family with more than 700 members. Proceedings of the National Academy of Sciences 105(12):4874-4879.
2 Daolong D, Kale SD, Wang X, Jiang RHY, Bruce NA, Arredondo FD, Zhang X, Tyler BM (2008) RXLR-mediated entry of Phytophthora sojae effector Avr1b into soybean cells does not require pathogen-encoded machinery. Plant Cell 20:1930–1947.
3 Kale S, Gu B, Capelluto DGS, Dou D, Feldman E, Rumore A, Arredondo FD, Hanlon R, Fudal I, Rouxel T, Lawrence CB, Shan W, Tyler BM (2010) External lipid phophatidylinositol 3-phosphate mediates entry of eukaryotic pathogen effectors into plant and animal host cells. Cell 142(2):284-95.
The Virginia Bioinformatics Institute at Virginia Tech is a premier bioinformatics, computational biology, and systems biology research facility that uses transdisciplinary approaches to science combining information technology, biology, and medicine. These approaches are used to interpret and apply vast amounts of biological data generated from basic research to some of today’s key challenges in the biomedical, environmental, and agricultural sciences. With more than 240 highly trained multidisciplinary, international personnel, research at the institute involves collaboration in diverse disciplines such as mathematics, computer science, biology, plant pathology, biochemistry, systems biology, statistics, economics, synthetic biology, and medicine. The large amounts of data generated by this approach are analyzed and interpreted to create new knowledge that is disseminated to the world’s scientific, governmental, and wider communities.