Enabling comparative modeling of closely related genomes: example genus Brucella.

For many scientific applications, it is highly desirable to be able to compare metabolic models of closely related genomes. In this short report, we attempt to raise awareness to the fact that taking annotated genomes from public repositories and using them for metabolic model reconstructions is far from being trivial due to annotation inconsistencies. We are proposing a protocol for comparative analysis of metabolic models on closely related genomes, using fifteen strains of genus Brucella, which contains pathogens of both humans and livestock. This study lead to the identification and subsequent correction of inconsistent annotations in the SEED database, as well as the identification of 31 biochemical reactions that are common to Brucella, which are not originally identified by automated metabolic reconstructions. We are currently implementing this protocol for improving automated annotations within the SEED database and these improvements have been propagated into PATRIC, Model-SEED, KBase and RAST. This method is an enabling step for the future creation of consistent annotation systems and high-quality model reconstructions that will support in predicting accurate phenotypes such as pathogenicity, media requirements or type of respiration.

SEED servers: high-performance access to the SEED genomes, annotations, and metabolic models.

The remarkable advance in sequencing technology and the rising interest in medical and environmental microbiology, biotechnology, and synthetic biology resulted in a deluge of published microbial genomes. Yet, genome annotation, comparison, and modeling remain a major bottleneck to the translation of sequence information into biological knowledge, hence computational analysis tools are continuously being developed for rapid genome annotation and interpretation. Among the earliest, most comprehensive resources for prokaryotic genome analysis, the SEED project, initiated in 2003 as an integration of genomic data and analysis tools, now contains >5,000 complete genomes, a constantly updated set of curated annotations embodied in a large and growing collection of encoded subsystems, a derived set of protein families, and hundreds of genome-scale metabolic models. Until recently, however, maintaining current copies of the SEED code and data at remote locations has been a pressing issue. To allow high-performance remote access to the SEED database, we developed the SEED Servers (http://www.theseed.org/servers): four network-based servers intended to expose the data in the underlying relational database, support basic annotation services, offer programmatic access to the capabilities of the RAST annotation server, and provide access to a growing collection of metabolic models that support flux balance analysis. The SEED servers offer open access to regularly updated data, the ability to annotate prokaryotic genomes, the ability to create metabolic reconstructions and detailed models of metabolism, and access to hundreds of existing metabolic models. This work offers and supports a framework upon which other groups can build independent research efforts. Large integrations of genomic data represent one of the major intellectual resources driving research in biology, and programmatic access to the SEED data will provide significant utility to a broad collection of potential users.

Cohesion group approach for evolutionary analysis of TyrA, a protein family with wide-ranging substrate specificities.

Many enzymes and other proteins are difficult subjects for bioinformatic analysis because they exhibit variant catalytic, structural, regulatory, and fusion mode features within a protein family whose sequences are not highly conserved. However, such features reflect dynamic and interesting scenarios of evolutionary importance. The value of experimental data obtained from individual organisms is instantly magnified to the extent that given features of the experimental organism can be projected upon related organisms. But how can one decide how far along the similarity scale it is reasonable to go before such inferences become doubtful? How can a credible picture of evolutionary events be deduced within the vertical trace of inheritance in combination with intervening events of lateral gene transfer (LGT)? We present a comprehensive analysis of a dehydrogenase protein family (TyrA) as a prototype example of how these goals can be accomplished through the use of cohesion group analysis. With this approach, the full collection of homologs is sorted into groups by a method that eliminates bias caused by an uneven representation of sequences from organisms whose phylogenetic spacing is not optimal. Each sufficiently populated cohesion group is phylogenetically coherent and defined by an overall congruence with a distinct section of the 16S rRNA gene tree. Exceptions that occasionally are found implicate a clearly defined LGT scenario whereby the recipient lineage is apparent and the donor lineage of the gene transferred is localized to those organisms that define the cohesion group. Systematic procedures to manage and organize otherwise overwhelming amounts of data are demonstrated.

The RAST Server: rapid annotations using subsystems technology.

BACKGROUND: The number of prokaryotic genome sequences becoming available is growing steadily and is growing faster than our ability to accurately annotate them. DESCRIPTION: We describe a fully automated service for annotating bacterial and archaeal genomes. The service identifies protein-encoding, rRNA and tRNA genes, assigns functions to the genes, predicts which subsystems are represented in the genome, uses this information to reconstruct the metabolic network and makes the output easily downloadable for the user. In addition, the annotated genome can be browsed in an environment that supports comparative analysis with the annotated genomes maintained in the SEED environment. The service normally makes the annotated genome available within 12-24 hours of submission, but ultimately the quality of such a service will be judged in terms of accuracy, consistency, and completeness of the produced annotations. We summarize our attempts to address these issues and discuss plans for incrementally enhancing the service. CONCLUSION: By providing accurate, rapid annotation freely to the community we have created an important community resource. The service has now been utilized by over 120 external users annotating over 350 distinct genomes.

Characterization of the Staphylococcus aureus heat shock, cold shock, stringent, and SOS responses and their effects on log-phase mRNA turnover.

Despite its being a leading cause of nosocomal and community-acquired infections, surprisingly little is known about Staphylococcus aureus stress responses. In the current study, Affymetrix S. aureus GeneChips were used to define transcriptome changes in response to cold shock, heat shock, stringent, and SOS response-inducing conditions. Additionally, the RNA turnover properties of each response were measured. Each stress response induced distinct biological processes, subsets of virulence factors, and antibiotic determinants. The results were validated by real-time PCR and stress-mediated changes in antimicrobial agent susceptibility. Collectively, many S. aureus stress-responsive functions are conserved across bacteria, whereas others are unique to the organism. Sets of small stable RNA molecules with no open reading frames were also components of each response. Induction of the stringent, cold shock, and heat shock responses dramatically stabilized most mRNA species. Correlations between mRNA turnover properties and transcript titers suggest that S. aureus stress response-dependent alterations in transcript abundances can, in part, be attributed to alterations in RNA stability. This phenomenon was not observed within SOS-responsive cells.

Characterizing the effect of the Staphylococcus aureus virulence factor regulator, SarA, on log-phase mRNA half-lives.

Bacterial pathogens regulate virulence factor expression at both the level of transcription initiation and mRNA processing/turnover. Within Staphylococcus aureus, virulence factor transcript synthesis is regulated by a number of two-component regulatory systems, the DNA binding protein SarA, and the SarA family of homologues. However, little is known about the factors that modulate mRNA stability or influence transcript degradation within the organism. As our entree to characterizing these processes, S. aureus GeneChips were used to simultaneously determine the mRNA half-lives of all transcripts produced during log-phase growth. It was found that the majority of log-phase transcripts (90%) have a short half-life (<5 min), whereas others are more stable, suggesting that cis- and/or trans-acting factors influence S. aureus mRNA stability. In support of this, it was found that two virulence factor transcripts, cna and spa, were stabilized in a sarA-dependent manner. These results were validated by complementation and real-time PCR and suggest that SarA may regulate target gene expression in a previously unrecognized manner by posttranscriptionally modulating mRNA turnover. Additionally, it was found that S. aureus produces a set of stable RNA molecules with no predicted open reading frame. Based on the importance of the S. aureus agr RNA molecule, RNAIII, and small stable RNA molecules within other pathogens, it is possible that these RNA molecules influence biological processes within the organism.