From PNNL Labs
Finally some good news from a US D.O.E. Lab in 2011.
Sequenced Genomes Make Good Neighbors
Comparing mass spectra among organisms enables protein identification
“To study the proteomes of organisms, a first step often involves using sequenced genomes in conjunction with mass spectrometric measurements for global protein identifications. But, how do you identify the proteins in an organism yet to be sequenced? One way is to look at its sequenced neighbors, which is what scientists at Pacific Northwest National Laboratory (PNNL) did. They demonstrated a trans-organism search strategy for determining the extent to which near-neighbor genome sequences can be effective for global protein identifications in unsequenced organisms isolated from environmental samples.
In this strategy, mass spectra from an unsequenced organism were searched against the genome sequences for progressively more genetically distant neighbor organisms to determine how much proteome information could be obtained about one species when using the genomic sequence of another. The work appeared in PLoS ONE in November 2010.
Protein identifications from Columbia River isolates are mapped to the reference genomes of S. oneidensis MR-1 (A) and S. putrefaciens CN32 (B). While all organisms were grown under the same conditions, observation of no protein expression compared to the reference proteome reveals these organisms have undergone evolutionary divergence. The protein identifications for each of the Shewanella species mapped onto their respective genomes, as well as the protein orthologs across species, also are shown. Two regions of “missing” proteome information from the Hanford Reach isolates are highlighted.
Read the full article here.
I might also point here to the World Community Grid (WCG) project in Human Proteome Folding (hpf2). WCG projects employ thousands of individual computer users and their machines to “crunch” data in what is called Public Distributed Computing. These projects run on software from Berkeley Open Infrastructure for Network Computing (BOINC). In fact, hpf2 uses software developed by a BOINC project, Rosetta@home , which is based in the Baker Lab at the University of Washington.