Characterization of probiotic Escherichia coli isolates with a novel pan-genome microarray

pan-genome microarra

Bayesian prediction of bacterial growth temperature range based on genome sequences

<p>Abstract</p> <p>Background</p> <p>The preferred habitat of a given bacterium can provide a hint of which types of enzymes of potential industrial interest it might produce. These might include enzymes that are stable and active at very high or very low temperatures. Being able to accurately predict this based on a genomic sequence, would thus allow for an efficient and targeted search for production organisms, reducing the need for culturing experiments.</p> <p>Results</p> <p>This study found a total of 40 protein families useful for distinction between three thermophilicity classes (thermophiles, mesophiles and psychrophiles). The predictive performance of these protein families were compared to those of 87 basic sequence features (relative use of amino acids and codons, genomic and 16S rDNA AT content and genome size). When using naïve Bayesian inference, it was possible to correctly predict the optimal temperature range with a Matthews correlation coefficient of up to 0.68. The best predictive performance was always achieved by including protein families as well as structural features, compared to either of these alone. A dedicated computer program was created to perform these predictions.</p> <p>Conclusions</p> <p>This study shows that protein families associated with specific thermophilicity classes can provide effective input data for thermophilicity prediction, and that the naïve Bayesian approach is effective for such a task. The program created for this study is able to efficiently distinguish between thermophilic, mesophilic and psychrophilic adapted bacterial genomes.</p

CBS Genome Atlas Database: a dynamic storage for bioinformatic results and sequence data

Summary: Currently, new bacterial genomes are being published on a monthly basis. With the growing amount of genome sequence data, there is a demand for a flexible and easy-to-maintain structure for storing sequence data and res-ults from bioinformatic analysis. More than 150 sequenced bacterial genomes are now available, and comparisons of properties for taxonomically similar organisms are not read-ily available to many biologists. In addition to the most basic information, such as AT content, chromosome length, tRNA count and rRNA count, a large number of more complex calcu-lations are needed to perform detailed comparative genomics. DNA structural calculations like curvature and stacking energy, DNA compositions like base skews, oligo skews and repeats at the local and global level are just a few of the analysis that are presented on the CBS Genome Atlas Web page. Com-plex analysis, changing methods and frequent addition of new models are factors that require a dynamic database layout. Using basic tools like the GNU Make system, csh, Perl and MySQL, we have created a flexible database environment for storing and maintaining such results for a collection of com-plete microbial genomes. Currently, these results counts to more than 220 pieces of information. The backbone of this solution consists of a program package written in Perl, which enables administrators to synchronize and update the data-base content. The MySQL database has been connected to the CBS web-server via PHP4, to present a dynamic web con-tent for users outside the center. This solution is tightly fitted to existing server infrastructure and the solutions proposed here can perhaps serve as a template for other research groups to solve database issues. Availability: A web based user interface which is dynamically linked to the Genome Atlas Database can be accessed via www.cbs.dtu.dk/services/GenomeAtlas/ Contact