Between 1996 and 2006, the US Centers for Disease Control reported that the only category of food-borne infections increasing in frequency were those caused by members of the genus Vibrio. The Gram-negative bacterium Vibrio vulnificus is a ubiquitous inhabitant of estuarine waters, and is the number one cause of seafood-related deaths in the US. Many V. vulnificus isolates have been studied, and it has been shown that two genetically distinct subtypes, distinguished by 16S rDNA and other gene polymorphisms, are associated predominantly with either environmental or clinical isolation. While local genetic differences between the subtypes have been probed, only the genomes of clinical isolates have so far been completely sequenced. In order to better understand V. vulnificus as an agent of disease and to identify the molecular components of its virulence mechanisms, we have completed whole genome shotgun sequencing of three diverse environmental genotypes using a pyrosequencing approach. V. vulnificus strain JY1305 was sequenced to a depth of 33×, and strains E64MW and JY1701 were sequenced to lesser depth, covering approximately 99.9% of each genome. We have performed a comparative analysis of these sequences against the previously published sequences of three V. vulnificus clinical isolates. We find that the genome of V. vulnificus is dynamic, with 1.27% of genes in the C-genotype genomes not found in the E- genotype genomes. We identified key genes that differentiate between the genomes of the clinical and environmental genotypes. 167 genes were found to be specifically associated with environmental genotypes and 278 genes with clinical genotypes. Genes specific to the clinical strains include components of sialic acid catabolism, mannitol fermentation, and a component of a Type IV secretory pathway VirB4, as well as several other genes with potential significance for human virulence. Genes specific to environmental strains included several that may have implications for the balance between self-preservation under stress and nutritional competence.
Many important questions in biology are, fundamentally, comparative, and this extends to our analysis of a growing number of sequenced genomes. Existing genomic analysis tools are often organized around literal views of genomes as linear strings. Even when information is highly condensed, these views grow cumbersome as larger numbers of genomes are added. Data aggregation and summarization methods from the field of visual analytics can provide abstracted comparative views, suitable for sifting large multi-genome datasets to identify critical similarities and differences. We introduce a software system for visual analysis of comparative genomics data. The system automates the process of data integration, and provides the analysis platform to identify and explore features of interest within these large datasets. GenoSets borrows techniques from business intelligence and visual analytics to provide a rich interface of interactive visualizations supported by a multi-dimensional data warehouse. In GenoSets, visual analytic approaches are used to enable querying based on orthology, functional assignment, and taxonomic or user-defined groupings of genomes. GenoSets links this information together with coordinated, interactive visualizations for both detailed and high-level categorical analysis of summarized data. GenoSets has been designed to simplify the exploration of multiple genome datasets and to facilitate reasoning about genomic comparisons. Case examples are included showing the use of this system in the analysis of 12 Brucella genomes. GenoSets software and the case study dataset are freely available at http://genosets.uncc.edu. We demonstrate that the integration of genomic data using a coordinated multiple view approach can simplify the exploration of large comparative genomic data sets, and facilitate reasoning about comparisons and features of interest.
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