Plant peroxisomes are essential components in various physiological and metabolic pathways, yet our knowledge of the protein composition and metabolic and regulatory networks associated with these organelles is far from complete. This 2010 project will generate a 'parts list' of peroxisomal matrix and membrane, using bioinformatics and proteomics, followed by fluorescence microscopy and protein fractionation. Further, the functions of peroxisome-targeted proteins will be analyzed with various assays on sequence-indexed T-DNA insertion mutants. Finally, peroxisomal protein complexes and networks will be explored, using gel-based methods in combination with mass spectrometry. Approximately 300-500 genes encoding peroxisomal proteins will be associated with biological functions, which is a critical step toward developing a comprehensive model for plant peroxisome function. This project will provide the scientific community with a much-needed comprehensive inventory of peroxisomal proteins and a large set of tagged reporter constructs for follow-up studies. All information will be integrated into the AraPeroX database (www.araperox.uni-goettingen.de/) and mirrored on the project website www.peroxisome.msu.edu. Information and materials generated will be available to the public in a timely fashion through our project website, TAIR, and ABRC. Given that different cell compartments are often linked via peroxisomal functions and that peroxisomes are crucial during stress responses, this project will benefit several fields in the plant community and achieve synergistic impact with other ongoing 2010 projects, such as the plastid functional genomics project. Results from this research will also expand our knowledge of eukaryotic cell biology and provide useful information to engineering crop plants for increased stress resistance and improved oil production.
Broader Impacts: Research and education will be integrated by multidisciplinary training of undergraduates, high school students and teachers, and teachers from primarily undergraduate colleges. The data, resources, and techniques generated in the project will be useful to a broad community of scientists.
