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The U.S. Department of Energy Systems Biology Knowledgebase (KBase) is an open-source software and data platform designed to meet the grand challenge of systems biology — predicting and designing biological function from the biomolecular (small scale) to the ecological (large scale). KBase is available for anyone to use, and enables researchers to collaboratively generate, test, compare, and share hypotheses about biological functions; perform large-scale analyses on scalable computing infrastructure; and combine experimental evidence and conclusions that lead to accurate models of plant and microbial physiology and community dynamics. The KBase platform has (1) extensible analytical capabilities that currently include genome assembly, annotation, ontology assignment, comparative genomics, transcriptomics, and metabolic modeling; (2) a web-browser-based user interface that supports building, sharing, and publishing reproducible and well-annotated analyses with integrated data; (3) access to extensive computational resources; and (4) a software development kit allowing the community to add functionality to the system.

BackgroundComputing of sequence similarity results is becoming a limiting factor in metagenome analysis. Sequence similarity search results encoded in an open, exchangeable format have the potential to limit the needs for computational reanalysis of these data sets. A prerequisite for sharing of similarity results is a common reference.DescriptionWe introduce a mechanism for automatically maintaining a comprehensive, non-redundant protein database and for creating a quarterly release of this resource. In addition, we present tools for translating similarity searches into many annotation namespaces, e.g. KEGG or NCBI's GenBank.ConclusionsThe data and tools we present allow the creation of multiple result sets using a single computation, permitting computational results to be shared between groups for large sequence data sets.

The release of the 1000th complete microbial genome will occur in the next two to three years. In anticipation of this milestone, the Fellowship for Interpretation of Genomes (FIG) launched the Project to Annotate 1000 Genomes. The project is built around the principle that the key to improved accuracy in high-throughput annotation technology is to have experts annotate single subsystems over the complete collection of genomes, rather than having an annotation expert attempt to annotate all of the genes in a single genome. Using the subsystems approach, all of the genes implementing the subsystem are analyzed by an expert in that subsystem. An annotation environment was created where populated subsystems are curated and projected to new genomes. A portable notion of a populated subsystem was defined, and tools developed for exchanging and curating these objects. Tools were also developed to resolve conflicts between populated subsystems. The SEED is the first annotation environment that supports this model of annotation. Here, we describe the subsystem approach, and offer the first release of our growing library of populated subsystems. The initial release of data includes 180 177 distinct proteins with 2133 distinct functional roles. This data comes from 173 subsystems and 383 different organisms.

Cell wall-anchored surface proteins of gram-positive pathogens play important roles during the establishment of many infectious diseases, but the contributions of surface proteins to the pathogenesis of anthrax have not yet been revealed. Cell wall anchoring in Staphylococcus aureus occurs by a transpeptidation mechanism requiring surface proteins with C-terminal sorting signals as well as sortase enzymes. The genome sequence of Bacillus anthracis encodes three sortase genes and eleven surface proteins with different types of cell wall sorting signals. Purified B. anthracis sortase A cleaved peptides encompassing LPXTG motif-type sorting signals between the threonine (T) and the glycine (G) residues in vitro. Sortase A activity could be inhibited by thiol-reactive reagents, similar to staphylococcal sortases. B. anthracis parent strain Sterne 34F2, but not variants lacking the srtA gene, anchored the collagen-binding MSCRAMM (microbial surface components recognizing adhesive matrix molecules) BasC (BA5258/BAS4884) to the bacterial cell wall. These results suggest that B. anthracis SrtA anchors surface proteins bearing LPXTG motif sorting signals to the cell wall envelope of vegetative bacilli.

Abstract 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.

We reconstructed the complete 2.4 Mb-long genome of a previously uncultivated epsilonproteobacterium, C andidatus Sulfuricurvum sp. RIFRC-1, via assembly of short-read shotgun metagenomic data using a complexity reduction approach. Genome-based comparisons indicate the bacterium is a novel species within the S ulfuricurvum genus, which contains one cultivated representative, S. kujiense. Divergence between the species appears due in part to extensive genomic rearrangements, gene loss and chromosomal versus plasmid encoding of certain (respiratory) genes by RIFRC-1. Deoxyribonucleic acid for the genome was obtained from terrestrial aquifer sediment, in which RIFRC-1 comprised ∼ 47% of the bacterial community. Genomic evidence suggests RIFRC-1 is a chemolithoautotrophic diazotroph capable of deriving energy for growth by microaerobic or nitrate-/nitric oxide-dependent oxidation of S0, sulfide or sulfite or H2 oxidation. Carbon may be fixed via the reductive tricarboxylic acid cycle. Consistent with these physiological attributes, the local aquifer was microoxic with small concentrations of available nitrate, small but elevated concentrations of reduced sulfur and NH4+/ NH3-limited. Additionally, various mechanisms for heavy metal and metalloid tolerance and virulence point to a lifestyle well-adapted for metal(loid)-rich environments and a shared evolutionary past with pathogenic E psilonproteobacteria. Results expand upon recent findings highlighting the potential importance of sulfur and hydrogen metabolism in the terrestrial subsurface. [ABSTRACT FROM AUTHOR]

The democratized world of sequencing is leading to numerous data analysis challenges; MG-RAST addresses many of these challenges for diverse datasets, including amplicon datasets, shotgun metagenomes, and metatranscriptomes. The changes from version 2 to version 3 include the addition of a dedicated gene calling stage using FragGenescan, clustering of predicted proteins at 90% identity, and the use of BLAT for the computation of similarities. Together with changes in the underlying software infrastructure, this has enabled the dramatic scaling up of pipeline throughput while remaining on a limited hardware budget. The Web-based service allows upload, fully automated analysis, and visualization of results. As a result of the plummeting cost of sequencing and the readily available analytical power of MG-RAST, over 78,000 metagenomic datasets have been analyzed, with over 12,000 of them publicly available in MG-RAST., (© 2013 Elsevier Inc. All rights reserved.)

This report summarizes the proceedings of the 2(nd) Annual Argonne Soils Workshop held at Argonne National Laboratory October 6-8, 2010. The workshop assembled a diverse group of soil ecologists, microbiologists, molecular biologists, and computational scientists to discuss the challenges and opportunities related to implementation of metagenomics approaches in soil microbial ecology. The overarching theme of the workshop was "designing ecologically meaningful soil metagenomics research", which encouraged presentations on both ecological and computational topics. The workshop fostered valuable cross-discipline communication and delivered the message that soil metagenomics research must be based on an iterative process between biological inquiry and bioinformatics tools.