Motivation: Molecular biotechnology now makes it possible to build elaborate systems models, but the systems biology community needs information standards if models are to be shared, evaluated and developed cooperatively. Results: We summarize the Systems Biology Markup Language (SBML) Level 1, a free, open, XML-based format for representing biochemical reaction networks. SBML is a software-independent language for describing models common to research in many areas of computational biology, including cell signaling pathways, metabolic pathways, gene regulation, and others. Availability: The specification of SBML Level 1 is freely available from http://www.sbml.org/ Contact: sysbio-team@caltech.edu * To whom correspondence should be addressed.

The metabolic modeling community has curated information from five models to create the most comprehensive model of human metabolism to date. Multiple models of human metabolism have been reconstructed, but each represents only a subset of our knowledge. Here we describe Recon 2, a community-driven, consensus 'metabolic reconstruction', which is the most comprehensive representation of human metabolism that is applicable to computational modeling. Compared with its predecessors, the reconstruction has improved topological and functional features, including ∼2× more reactions and ∼1.7× more unique metabolites. Using Recon 2 we predicted changes in metabolite biomarkers for 49 inborn errors of metabolism with 77% accuracy when compared to experimental data. Mapping metabolomic data and drug information onto Recon 2 demonstrates its potential for integrating and analyzing diverse data types. Using protein expression data, we automatically generated a compendium of 65 cell type–specific models, providing a basis for manual curation or investigation of cell-specific metabolic properties. Recon 2 will facilitate many future biomedical studies and is freely available at http://humanmetabolism.org/ .

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Exoelectrogenic bacteria are organisms that can transfer electrons to extracellular insoluble electron acceptors and have the potential to be used in devices such as microbial fuel cells (MFCs). Currently, exoelectrogens have been identified in the Alpha -, Beta -, Gamma - and Deltaproteobacteria , as well as in the Firmicutes and Acidobacteria . Here, we describe use of culture-independent methods to identify two members of the genus Arcobacter in the Epsilon p roteobacteria that are selectively enriched in an acetate-fed MFC. One of these organisms, Arcobacter butzleri strain ED-1, associates with the electrode and rapidly generates a strong electronegative potential as a pure culture when it is supplied with acetate. A mixed-community MFC in which ∼90% of the population is comprised of the two Arcobacter species generates a maximal power density of 296 mW/liter. This demonstration of exoelectrogenesis by strain ED-1 is the first time that this property has been shown for members of this genus.