Sampling Sites

<p>The circles represent the sampling locations in the Sargasso Sea (SAR), Gulf of Mexico (GOM), British Columbia (BBC), and the Arctic Ocean. The number of samples taken at each location and combined for sequencing, as well as the date and depth range, are shown in the boxes.</p

Types of Phages in the Four Metagenomes

<p>A new version of the Phage Proteomic Tree (left panel) was constructed from 510 complete phage and prophage genomes using the previously described method [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0040368#pbio-0040368-b023" target="_blank">23</a>]. The metagenomic sequences were compared to the phage on the Phage Proteomic Tree using TBLASTX, and the colored bars on the right represent significant similarities (<i>E</i>-value < 0.0001). Names of prophages are in red and the <i>Prochlorococcus</i> phage genomes are in green. An electronic version of the tree and a FASTA list of phage and prophage genomes used to make the tree are available at the SDSU Center for Universal Microbe Sequencing website (<a href="http://scums.sdsu.edu/phage/Oceans" target="_blank">http://scums.sdsu.edu/phage/Oceans</a>).</p

Monte Carlo Simulation of Cross-Contigs between Metagenomic Samples

<p>(A) For the intersample analysis, the maximum likelihood occurred at 35% fraction permuted and 100% fraction shared. (B) The maximum likelihood was between 0% and 0.5% fraction permuted and 85% and 95 % fraction shared for the intrasample controls.</p

Relationship between Geographic and Genetic Distances of Marine Viral Assemblages

<p>In addition to the four metagenomes sequenced for this study, the previous viral metagenomes from the San Diego area (California coast) were also included in this analysis [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0040368#pbio-0040368-b010" target="_blank">10</a>]. There was a significant correlation of 3.28 × 10⁻⁵ Φ_ST / km (Mantel test, <i>Z</i> = ₋78.9, <i>p</i> < 0.017, <i>r</i> = 0.585).</p

Application of Off-Rate Screening in the Identification of Novel Pan-Isoform Inhibitors of Pyruvate Dehydrogenase Kinase

Libraries of nonpurified resorcinol amide derivatives were screened by surface plasmon resonance (SPR) to determine the binding dissociation constant (off-rate, <i>k</i>_d) for compounds binding to the pyruvate dehydrogenase kinase (PDHK) enzyme. Parallel off-rate measurements against HSP90 and application of structure-based drug design enabled rapid hit to lead progression in a program to identify pan-isoform ATP-competitive inhibitors of PDHK. Lead optimization identified selective sub-100-nM inhibitors of the enzyme which significantly reduced phosphorylation of the E1α subunit in the PC3 cancer cell line <i>in vitro</i>

Application of Off-Rate Screening in the Identification of Novel Pan-Isoform Inhibitors of Pyruvate Dehydrogenase Kinase

Libraries of nonpurified resorcinol amide derivatives were screened by surface plasmon resonance (SPR) to determine the binding dissociation constant (off-rate, <i>k</i>_d) for compounds binding to the pyruvate dehydrogenase kinase (PDHK) enzyme. Parallel off-rate measurements against HSP90 and application of structure-based drug design enabled rapid hit to lead progression in a program to identify pan-isoform ATP-competitive inhibitors of PDHK. Lead optimization identified selective sub-100-nM inhibitors of the enzyme which significantly reduced phosphorylation of the E1α subunit in the PC3 cancer cell line <i>in vitro</i>