BACKGROUND: Cancer is a disease driven by the accumulation of genomic alterations, including the integration of exogenous DNA into the human somatic genome. We previously identified in silico evidence of DNA fragments from a Pseudomonas-like bacteria integrating into the 5'-UTR of four proto-oncogenes in stomach cancer sequencing data. The functional and biological consequences of these bacterial DNA integrations remain unknown. RESULTS: Modeling of these integrations suggests that the previously identified sequences cover most of the sequence flanking the junction between the bacterial and human DNA. Further examination of these reads reveals that these integrations are rich in guanine nucleotides and the integrated bacterial DNA may have complex transcript secondary structures. CONCLUSIONS: The models presented here lay the foundation for future experiments to test if bacterial DNA integrations alter the transcription of the human genes.

There are 10× more bacterial cells in our bodies from the microbiome than human cells. Viral DNA is known to integrate in the human genome, but the integration of bacterial DNA has not been described. Using publicly available sequence data from the human genome project, the 1000 Genomes Project, and The Cancer Genome Atlas (TCGA), we examined bacterial DNA integration into the human somatic genome. Here we present evidence that bacterial DNA integrates into the human somatic genome through an RNA intermediate, and that such integrations are detected more frequently in (a) tumors than normal samples, (b) RNA than DNA samples, and (c) the mitochondrial genome than the nuclear genome. Hundreds of thousands of paired reads support random integration of Acinetobacter-like DNA in the human mitochondrial genome in acute myeloid leukemia samples. Numerous read pairs across multiple stomach adenocarcinoma samples support specific integration of Pseudomonas-like DNA in the 5'-UTR and 3'-UTR of four proto-oncogenes that are up-regulated in their transcription, consistent with conversion to an oncogene. These data support our hypothesis that bacterial integrations occur in the human somatic genome and may play a role in carcinogenesis. We anticipate that the application of our approach to additional cancer genome projects will lead to the more frequent detection of bacterial DNA integrations in tumors that are in close proximity to the human microbiome.

MOTIVATION: Analysis of multiple genomes requires sophisticated tools that provide search, visualization, interactivity and data export. Comparative genomics datasets tend to be large and complex, making development of these tools difficult. In addition to scalability, comparative genomics tools must also provide user-friendly interfaces such that the research scientist can explore complex data with minimal technical expertise. RESULTS: We describe a new version of the Sybil software package and its application to the important human pathogen Streptococcus pneumoniae. This new software provides a feature-rich set of comparative genomics tools for inspection of multiple genome structures, mining of orthologous gene families and identification of potential vaccine candidates. AVAILABILITY: The S.pneumoniae resource is online at http://strepneumo-sybil.igs.umaryland.edu. The software, database and website are available for download as a portable virtual machine and from http://sourceforge.net/projects/sybil.

BACKGROUND: Rapid annotation and comparisons of genomes from multiple isolates (pan-genomes) is becoming commonplace due to advances in sequencing technology. Genome annotations can contain inconsistencies and errors that hinder comparative analysis even within a single species. Tools are needed to compare and improve annotation quality across sets of closely related genomes. RESULTS: We introduce a new tool, Mugsy-Annotator, that identifies orthologs and evaluates annotation quality in prokaryotic genomes using whole genome multiple alignment. Mugsy-Annotator identifies anomalies in annotated gene structures, including inconsistently located translation initiation sites and disrupted genes due to draft genome sequencing or pseudogenes. An evaluation of species pan-genomes using the tool indicates that such anomalies are common, especially at translation initiation sites. Mugsy-Annotator reports alternate annotations that improve consistency and are candidates for further review. CONCLUSIONS: Whole genome multiple alignment can be used to efficiently identify orthologs and annotation problem areas in a bacterial pan-genome. Comparisons of annotated gene structures within a species may show more variation than is actually present in the genome, indicating errors in genome annotation. Our new tool Mugsy-Annotator assists re-annotation efforts by highlighting edits that improve annotation consistency.