Predicted Protein-Protein Interactions in the Moss Physcomitrella patens: A New Bioinformatic Resource
Predicted Protein-Protein Interactions in the Moss Physcomitrella patens: A New Bioinformatic Resource
Scott Schuette (1), Aaron Corley (1), Daniel Lang (2), Matt Geisler (1)
(1) Department of Plant Biology, Southern Illinois University, Carbondale IL, USA
(2) Plant Biotechnology, University of Freiburg, Sonnastr. 5, D-79104, Freiburg Germany
Physcomitrella patens, the model moss for plant biology, has a protein-coding genome similar in size to Arabidopsis, but is similar to yeast in efficiency of gene targeting experiments and has a haploid dominant form making an interesting and useful molecular genetic tool for plants. The availability of the moss genome has made possible the exploration of plant diversity at the molecular level. The model moss is fast becoming a tool for bioinformatic and molecular work due to its key phylogenetic position as sister to land plant lineages. We present here the first predicted protein-protein PPI for a bryophyte based on the interolog method. Whole genome sequences from reference species including yeast, nematode worm, fruitfly, mouse, rat, human, bacteria and Arabidopsis were compared to the genome of Physcomitrella patens in a pairwise fashion using reciprocal blasts to separate inparalogs from orthologs and outparalogs with INPARANOID software package. A reference interaction database was assembled using MySQL by compiling BioGrid, BIND, DIP, and Intact databases. The reference database was queried for which moss orthologs existed for both interacting partners. We predicted more than 60000 total interactions from different predicting references including 41,936 unique interactions from 4062 different P. patens proteins that were visualized in Cytoscape, a Java-based software package. The twenty most interactive proteins represent strongly conserved pathways that have not altered significantly during eukaryotic evolution. Analysis of gene ontology revealed the most significant categories represented include metabolic processes, intracellular and cytoplasmic likely due to their conserved nature, and protein binding due to physical interaction requirement for inclusion, and catalytic activities. The utility of predicted interactomes lies in the “guilt-by-association” model of predicting proteins in a pathway under the assumption that orthologous proteins have similar functions. For example, we constructed a Calvin Cycle network to determine the number of proteins associated with this all-important process and discovered an uncharacterized protein with phosphoglycerate kinase activity that interacts directly with NADP-ME, an enzyme involved in C4 photosynthesis. The addition of moss, a plant representative 200 million years diverged from Arabidopsis, to interactomic research greatly expands the possibility of conducting comparative analyses thus giving tremendous insight into network evolution of land plants.
