BioModels Database (), part of the international initiative BioModels.net, provides access to published, peer-reviewed, quantitative models of biochemical and cellular systems. Each model is carefully curated to verify that it corresponds to the reference publication and gives the proper numerical results. Curators also annotate the components of the models with terms from controlled vocabularies and links to other relevant data resources. This allows the users to search accurately for the models they need. The models can currently be retrieved in the SBML format, and import/export facilities are being developed to extend the spectrum of formats supported by the resource.

We report the sequence of the Halobacterium salinarum strain R1 chromosome and its four megaplasmids. Our set of protein-coding genes is supported by extensive proteomic and sequence homology data. The structures of the plasmids, which show three large-scale duplications (adding up to 100 kb), were unequivocally confirmed by cosmid analysis. The chromosome of strain R1 is completely colinear and virtually identical to that of strain NRC-1. Correlation of the plasmid sequences revealed 210 kb of sequence that occurs only in strain R1. The remaining 350 kb shows virtual sequence identity in the two strains. Nevertheless, the number and overall structure of the plasmids are largely incompatible. Also, 20% of the protein sequences differ despite the near identity at the DNA sequence level. Finally, we report genome-wide mobility data for insertion sequences from which we conclude that strains R1 and NRC-1 originate from the same natural isolate. This exemplifies evolution in the laboratory.

HaloLex is a software system for the central management, integration, curation, and web-based visualization of genomic and other -omics data for any given microorganism. The system has been employed for the manual curation of three haloarchaeal genomes, namely Halobacterium salinarum (strain R1), Natronomonas pharaonis, and Haloquadratum walsbyi. HaloLex, in particular, enables the integrated analysis of genome-wide proteomic results with the underlying genomic data. This has proven indispensable to generate reliable gene predictions for GC-rich genomes, which, due to their characteristically low abundance of stop codons, are known to be hard targets for standard gene finders, especially concerning start codon assignment. The proteomic identification of more than 600 N-terminal peptides has greatly increased the reliability of the start codon assignment for Halobacterium salinarum. Application of homology-based methods to the published genome of Haloarcula marismortui allowed to detect 47 previously unidentified genes (a problem that is particularly serious for short protein sequences) and to correct more than 300 start codon misassignments.

Applying systems biology tools to study n-butanol degradation in Pseudomonas putida KT2440To smoothen the process of n-butanol formation in Pseudomonas putida KT2440, detailed knowledge of the impact of this organic solvent on cell physiology and regulation is of outmost importance. Here, we conducted a detailed systems biology study to elucidate cellular responses at the metabolic, proteomic, and transcriptional level. Pseudomonas putida KT2440 was cultivated in multiple chemostat fermentations using n-butanol either as sole carbon source or together with glucose. Pseudomonas putida KT2440 revealed maximum growth rates (μ) of 0.3 h −1 with n-butanol as sole carbon source and of 0.4 h −1 using equal C-molar amounts of glucose and nbutanol. While C-mole specific substrate consumption and biomass/substrate yields appeared equal at these growth conditions, the cellular physiology was found to be substantially different: adenylate energy charge levels of 0.85 were found when n-butanol served as sole carbon source (similar to glucose as sole carbon source), but were reduced to 0.4 when n-butanol was coconsumed at stable growth conditions. Furthermore, characteristic maintenance parameters changed with increasing n-butanol consumption. 13 C flux analysis revealed that central metabolism was split into a glucose-fueled Entner-Doudoroff/pentose-phosphate pathway and an n-butanol-fueled tricarboxylic acid cycle when both substrates were coconsumed. With the help of transcriptome and proteome analysis, the degradation pathway of n-butanol could be unraveled, thus representing an important basis for rendering P. putida KT2440 from an n-butanol consumer to a producer in future metabolic engineering studies.

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