ABSTRACT
Protein interaction maps can reveal novel pathways and functional complexes, allowing 'guilt by association' annotation of uncharacterized proteins. To address the need for large-scale protein interaction analyses, a bacterial two-hybrid system was coupled with a whole genome shotgun sequencing approach for microbial genome analysis. We report the first large-scale proteomics study using this system, integrating de novo genome sequencing with functional interaction mapping and annotation in a high-throughput format. We apply the approach by shotgun sequencing and annotating the genome of Rickettsia sibirica strain 246, an obligate intracellular human pathogen among the Spotted Fever Group rickettsiae. The bacteria invade endothelial cells and cause lysis after large amounts of progeny have accumulated. Little is known about specific Rickettsial virulence factors and their mode of pathogenicity. Analysis of the combined genomic sequence and protein-protein interaction data for a set of virulence related Type IV secretion system (T4SS) proteins revealed over 250 interactions and will provide insight into the mechanism of Rickettsial pathogenicity.
Subject(s)
Bacterial Proteins/metabolism , Protein Interaction Mapping/methods , Rickettsia/genetics , Bacterial Proteins/genetics , Base Sequence , Genome, Bacterial , Genomic Library , Rickettsia/metabolism , Rickettsia/pathogenicityABSTRACT
The National Institutes of Health Mammalian Gene Collection (MGC) Program is a multiinstitutional effort to identify and sequence a cDNA clone containing a complete ORF for each human and mouse gene. ESTs were generated from libraries enriched for full-length cDNAs and analyzed to identify candidate full-ORF clones, which then were sequenced to high accuracy. The MGC has currently sequenced and verified the full ORF for a nonredundant set of >9,000 human and >6,000 mouse genes. Candidate full-ORF clones for an additional 7,800 human and 3,500 mouse genes also have been identified. All MGC sequences and clones are available without restriction through public databases and clone distribution networks (see http:mgc.nci.nih.gov).
