Graduation date: 2007
Candidatus Pelagibacter ubique is the first cultured representative of the SAR11 clade, a clade that is found throughout the oceans and accounts for approximately 25% of all bacterial cells [1]. It has a streamlined genome that is the smallest of any known free-living organism. In this study the complete genome sequence of Candidatus Pelagibacter ubique (strains HTCC1062 and HTCC1002) is used to explore the genomic variability of this organism by taking advantage of the large amount of DNA sequence data collected by Venter et.al. [2] from the Sargasso Sea.
Pelagibacter gene homologues in the metagenomic data were identified by tblastn and screened by a reciprocal best blastx test against the NCBI database to identify fragments of probable SAR11 origin. Fragments passing both tests covered 97.8% of the HTCC1062 genome. A subset of fragments spanning two or more SAR11 genes was used to study the conservation of gene order between the Oregon coast isolates and the Sargasso Sea SAR11 population. Boundaries between genes matched the gene order of the HTCC1062 genome in 96% of the cases (> 85,000 observations), although the average amino acid similarity of the genes encoded was only 71%. Alternate gene orders observed in the remaining 3432 fragments indicated that gene rearrangements within the Sargasso Sea population are more likely at boundaries between operons than within operons. Comparisons of the genomes of strains HTCC1062 and HTCC1002, and analysis of the metagenomic data, indicated four regions of genome variability, including a 48 kb cassette between the 23S rRNA gene and the 5S rRNA gene that encodes genes determining cell surface properties.
These findings indicate that the temperate gyre population of SAR11 is divergent in nucleotide and amino acid sequence from the coastal isolates, but shares similar gene order and composition in core regions of the genome. The methodology of binning environmental DNA fragments by using sequence similarity and gene-order conservation with known query genomes is validated and shows promise as a general technique to decipher the flood of metagenomic data that is accumulating.