2008 Annual Report
1a.Objectives (from AD-416)
Objective 1: Discover and characterize plant and pathogen genes important for resistance or pathogenicity at the molecular level with special emphasis on, but not limited to soybean interactions with soybean rust and soybean cyst nematode. Hypothesis: There are detectable gene and protein differences between uninfected and pathogen-infected plants and between susceptible and resistant plants, and there are pathogen virulence factors critical to pathogen infection, development and survival.
Objective 2: Determine modes of action for plant disease resistance genes, pathogen virulence factors and molecular signals responsible for host-parasite interactions through analysis and characterization of genetic, molecular, protein and metabolite networks. Hypothesis: Examination of the many genes involved in plant-pathogen interactions will reveal critical molecular networks with specific modes of action that are essential to resistance in soybean and to virulence in soybean pathogens. These networks may share commonalities to networks in other plants and pathogens.
Objective 3: Engineer and evaluate new methods for obtaining resistance, such as gene silencing, over-expression and protein antagonism, and chemical inhibition of host and pathogen processes, with special emphasis on soybean rust and the soybean cyst nematode. Hypothesis: Expression of gene silencing constructs or of proteins inhibitory to important aspects of pathogen infection, development or maintenance can result in increased tolerance or resistance to a particular pest or pathogen.
1b.Approach (from AD-416)
We have soybean genotypes resistant to one or more rust isolates, but susceptible to all others. These soybean genotypes will be challenged with specific pathogen isolates to study the resistance and susceptible response. Gene and protein expression in both plants and pathogens will be monitored using microarrays, membrane arrays, expressed sequence tag analysis, in situ hybridization, and RT-PCR. Proteins will be detected by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Cell fractionation, laser capture microdissection, and subtractive hybridization will be used to isolate specific tissues, organelles, or materials involved in disease processes or responses. Other methods such as antibody localization, gene silencing, plant hairy root transformation (for SCN studies) and mutant analysis will be used to determine the function of genes and proteins and to evaluate their importance in resistance and susceptibility.
The disease and pest resistance responses to infection in soybeans will be elucidated systematically using microarrays, proteomics and metabolomics to resolve the biological network evoked. A comparison of differential gene expression and protein accumulation in the resistant and susceptible response of soybean to pathogens will identify components of the network. These networks will be built, examined, and perturbed to confirm function of components using an array of tools, including bioinformatics, yeast two-hybrid screens, mutation analysis, immuno-localization, immuno-precipitation, affinity purification, protein tagging, gene over-expression, phage library display, and other methods that will resolve protein-protein interactions and interactions among molecules. Based on these data, we can identify candidate members of pathways and networks involved in signaling and evoking the resistance response. Other plant systems, including common bean and Medicago truncatula, will be used as needed in parallel investigations studying host-pathogen responses and interactions to take advantage of the knowledge and specific traits of the resistance response in these systems.
Approaches for achieving pathogen control include engineering transgenic plant tissue and organs to express genes that boost the natural defense system of the plant or to provide the plant with a new trait that confers resistance by blocking pathogen attack or survival. Genes shown to have important roles in plant defense may be over-expressed in transgenic plants. Likewise genes that are critical to survival of the SCN in the host or that make the plant susceptible to SCN may be silenced in transgenic roots using hairy root transformation techniques. Additionally, genes that express antibodies or protein antagonists will be engineered into soybean to block the survival and development of the pest or pathogen.
Nematodes and fungi cause billions of dollars in crop losses each year throughout the world. Genes were identified from fungal and nematode cDNA libraries that may be targets for developing resistance to these pests. Soybean root tissue was grown and collected that was infected with soybean cyst nematode (SCN) for gene expression analysis. From a set of 7,500 genes, we identified those genes expressed in SCN at 12 hours, 3 days, and 8 days post inoculation. Common bean rust cDNA libraries were constructed and 22,000 sequences were obtained to identify potential targets for developing plant resistance to the rust fungi using biotechnology. Genes were annotated and then full-length epitope tagged versions cloned into transformation vectors to study protein-protein interactions between the fungal protein and plant proteins using our developed mass spectrometry techniques and software. This research under National Program 302- Plant Biological and Molecular Processes addresses component 1 and 2, because it uses plant genomics and biochemical and molecular processes involved in the response of plants to plant pests and diseases to improve crop productivity and quality. This research also falls under NP303- Plant Diseases and addresses component II and III as described in the National Program Action Plan, because it defines the relationship between soybean and plant pathogens and resistance of soybean to these pests and pathogens.
Development of software to enable proteomics-based discovery. Mass spectrometry is a technology that is used to find the weight, or mass, of single molecules and has wide applications in the identification of molecules including proteins. Commercially available software is used to convert the mass information into peptide identifications. However, the peptides must also be reassembled into proteins if the proteins are to be understood. We developed a computer algorithm that efficiently organizes peptide and protein information so computational efforts for assembling the puzzle can perform quickly. This algorithm will enable government, academic, and private researchers to implement software packages designed to efficiently organize and sort large mass spectrometry data sets or any other large data set such as public record files. This research under National Program 302 - Plant Biological and Molecular Processes addresses component 1 and 2 and also falls under NP303 - Plant Diseases and addresses component V as described in the National Program Action Plan.
Identification of proteins associated with disease resistance. Discovery of proteins that are important for disease resistance to pathogens may help improve bean cultivars through breeding or transgenic technology. Comparison between plants that are naturally resistant and plants naturally susceptible revealed a set of proteins that contribute to the resistance response, while a separate set of proteins was found to help the fungus survive in susceptible plants. These results have helped identify disease resistance proteins that could eventually be used to protect susceptible plants. These data are of interest to scientists at universities, government agencies, and companies who are searching for new genes to fight rust diseases. This research under National Program 302 - Plant Biological and Molecular Processes addresses component 1 and 2 and also falls under NP303 - Plant Diseases and addresses component V as described in the National Program Action Plan.
GUS/GFP analysis of cell wall hydrolase genes. Cell wall hydrolases are essential to the formation of the nematode feeding structure in soybean roots. Using nematode infection-specific hydrolase promoters, we have prepared three GUS reporter gene constructs to analyze the expression patterns for cell wall hydrolase genes in soybean plants. Two additional constructs were prepared with one of the hydrolase gene promoters to target expression of mRNAs that inhibit ethylene synthesis to the infection site. These data are important to scientists at universities, government agencies, and companies who are designing new methods to fight nematodes using biotechnology. This research under National Program 302 - Plant Biological and Molecular Processes addresses component 1 and 2 and falls under NP303 - Plant Diseases and addresses component V as described in the National Program Action Plan.
Identification of fungal genes by DNA sequencing. Genes important to the life cycle of fungi need to be identified, so targets can be selected to develop soybean resistant to fungi. We analyzed 22,000 sequences collected from bean rust cDNA libraries and 1000 sequences from cDNA libraries of Asian soybean rust. We identified and began studies on a subset of fungal proteins that are good candidates for being secreted from the fungus into the plant host where they alter plant metabolic processes to enable nutrient uptake into the fungi and suppress host defense responses. These data are important to scientists at universities, government agencies, and companies who are designing new methods to fight rust diseases using biotechnology. This research under National Program 302 - Plant Biological and Molecular Processes addresses component 1 and 2 and also falls under NP303 - Plant Diseases and addresses component V as described in the National Program Action Plan.
5.Significant Activities that Support Special Target Populations
|Number of the New MTAs (providing only)||3|
|Number of Web Sites Managed||1|
|Number of Non-Peer Reviewed Presentations and Proceedings||4|
Klink, V.P., Overall, C., Macdonald, M.H., Matthews, B.F. 2007. A time-course comparative microarray analysis of an incompatible and compatible response by Glycine max (soybean) to Heterodera glycines (soybean cyst nematode) infection. Planta. 226:1423-1447.
Klink, V.P., Overall, C.C., Aklharouf, N.W., Macdonald, M.H., Matthews, B.F. 2007. Laser capture microdissection (LCM) and comparative microarray expression analysis of syncytial cells isolated from incompatible and compatible soybean roots infected by soybean cyst nematode (Heterodera glycines). Planta. 226:1389-1409.
Klink, V.P., Matthews, B.F. 2007. Glycine max (soybean) roots and syncytia isolated by laser capture microdissection (LCM) exhibit differential gene expression. Plant Signaling and Behavior. 3(2):105-107.
Klink, V.P., Macdonald, M.H., Martins, V., Park, S., Kim, K., Baek, S., Matthews, B.F. 2007. MiniMax, a new diminutive Glycine max genotype with a rapid life cycle, embryonic potential and transformation capabilities. Plant Cell Tissue And Organ Culture. 92:183-195.
Feng, J., Naiman, D., Cooper, B. 2007. Probability-Based Pattern Recognition and Statistical Framework for Randomization: Modeling Tandem Mass Spectrum/Peptide Sequence False Match Frequencies. Bioinformatics. 23:2210-2217.
Lee, J., Garrett, W.M., Cooper, B. 2007. Shotgun Proteomic Analysis of Arabidopsis thaliana Leaves. Journal of Separation Science. 30:2225-2230.
Cooper, B., Padliya, N., Garrett, W.M., Campbell, K., Tabb, D. 2007. Tandem Mass Spectrometry for the Detection of Plant Pathogenic Fungi and the Effects of Database Composition on Protein Inferences. Proteomics. 7:3932-3942.
Feng, J., Naiman, D., Cooper, B. 2008. Combined Dynamic Arrays for Storing and Searching Semi-Ordered Tandem Mass Spectrometry Data. Journal of Computational Biology. 15:457-468.