SurreyFBA: a command line tool and graphics user interface for constraint-based modeling of genome-scale metabolic reaction networks.

UNLABELLED: Constraint-based modeling of genome-scale metabolic networks has been successfully used in numerous applications such as prediction of gene essentiality and metabolic engineering. We present SurreyFBA, which provides constraint-based simulations and network map visualization in a free, stand-alone software. In addition to basic simulation protocols, the tool also implements the analysis of minimal substrate and product sets, which is useful for metabolic engineering and prediction of nutritional requirements in complex in vivo environments, but not available in other commonly used programs. The SurreyFBA is based on a command line interface to the GLPK solver distributed as binary and source code for the three major operating systems. The command line tool, implemented in C++, is easily executed within scripting languages used in the bioinformatics community and provides efficient implementation of tasks requiring iterative calls to the linear programming solver. SurreyFBA includes JyMet, a graphics user interface allowing spreadsheet-based model presentation, visualization of numerical results on metabolic networks represented in the Petri net convention, as well as in charts and plots. AVAILABILITY: SurreyFBA is distributed under GNU GPL license and available from http://sysbio3.fhms.surrey.ac.uk/SurreyFBA.zip.

Acorn: a grid computing system for constraint based modeling and visualization of the genome scale metabolic reaction networks via a web interface.

BACKGROUND: Constraint-based approaches facilitate the prediction of cellular metabolic capabilities, based, in turn on predictions of the repertoire of enzymes encoded in the genome. Recently, genome annotations have been used to reconstruct genome scale metabolic reaction networks for numerous species, including Homo sapiens, which allow simulations that provide valuable insights into topics, including predictions of gene essentiality of pathogens, interpretation of genetic polymorphism in metabolic disease syndromes and suggestions for novel approaches to microbial metabolic engineering. These constraint-based simulations are being integrated with the functional genomics portals, an activity that requires efficient implementation of the constraint-based simulations in the web-based environment. RESULTS: Here, we present Acorn, an open source (GNU GPL) grid computing system for constraint-based simulations of genome scale metabolic reaction networks within an interactive web environment. The grid-based architecture allows efficient execution of computationally intensive, iterative protocols such as Flux Variability Analysis, which can be readily scaled up as the numbers of models (and users) increase. The web interface uses AJAX, which facilitates efficient model browsing and other search functions, and intuitive implementation of appropriate simulation conditions. Research groups can install Acorn locally and create user accounts. Users can also import models in the familiar SBML format and link reaction formulas to major functional genomics portals of choice. Selected models and simulation results can be shared between different users and made publically available. Users can construct pathway map layouts and import them into the server using a desktop editor integrated within the system. Pathway maps are then used to visualise numerical results within the web environment. To illustrate these features we have deployed Acorn and created a web server allowing constraint based simulations of the genome scale metabolic reaction networks of E. coli, S. cerevisiae and M. tuberculosis. CONCLUSIONS: Acorn is a free software package, which can be installed by research groups to create a web based environment for computer simulations of genome scale metabolic reaction networks. It facilitates shared access to models and creation of publicly available constraint based modelling resources.

New approach to produce water free of bacteria, viruses, and halogens in a recyclable system.

The antimicrobial activity of a new cross-linked N-halamine polymer against bacteria and viruses was evaluated. The polymer achieved a 9-log(10) reduction of bacteria (both Escherichia coli and Staphylococcus aureus) in 1.5 h and a 5-log(10) reduction of bacteriophage PRD1 in 3 h. At the same time, the ability of the nonhalogenated polymer to trap halide ions was examined. The polymer was incorporated into a multifiltration system to study the ability to produce water free of bacteria, viruses, and halide ions. The antimicrobial activity, useful lifetime, halide ion level, and recycling possibilities of the system were quantified on a laboratory scale. A design for a large-scale multifiltration system based on this polymer is proposed.

Selection of objective function in genome scale flux balance analysis for process feed development in antibiotic production.

Using flux variability analysis of a genome scale metabolic network of Streptomyces coelicolor, a series of reactions were identified, from disparate pathways that could be combined into an actinorhodin-generating mini-network. Candidate process feed nutrients that might be expected to influence this network were used in process simulations and in silico predictions compared to experimental findings. Ranking potential process feeds by flux balance analysis optimisation, using either growth or antibiotic production as objective function, did not correlate with experimental actinorhodin yields in fed processes. However, the effect of the feeds on glucose assimilation rate (using glucose uptake as objective function) ranked them in the same order as in vivo antibiotic production efficiency, consistent with results of a robustness analysis of the effect of glucose assimilation on actinorhodin production.

Segregation of the Anodic Microbial Communities in a Microbial Fuel Cell Cascade.

Metabolic interactions within microbial communities are essential for the efficient degradation of complex organic compounds, and underpin natural phenomena driven by microorganisms, such as the recycling of carbon-, nitrogen-, and sulfur-containing molecules. These metabolic interactions ultimately determine the function, activity and stability of the community, and therefore their understanding would be essential to steer processes where microbial communities are involved. This is exploited in the design of microbial fuel cells (MFCs), bioelectrochemical devices that convert the chemical energy present in substrates into electrical energy through the metabolic activity of microorganisms, either single species or communities. In this work, we analyzed the evolution of the microbial community structure in a cascade of MFCs inoculated with an anaerobic microbial community and continuously fed with a complex medium. The analysis of the composition of the anodic communities revealed the establishment of different communities in the anodes of the hydraulically connected MFCs, with a decrease in the abundance of fermentative taxa and a concurrent increase in respiratory taxa along the cascade. The analysis of the metabolites in the anodic suspension showed a metabolic shift between the first and last MFC, confirming the segregation of the anodic communities. Those results suggest a metabolic interaction mechanism between the predominant fermentative bacteria at the first stages of the cascade and the anaerobic respiratory electrogenic population in the latter stages, which is reflected in the observed increase in power output. We show that our experimental system represents an ideal platform for optimization of processes where the degradation of complex substrates is involved, as well as a potential tool for the study of metabolic interactions in complex microbial communities.

Straw N-halamines: evaluation in single and multistage filtration systems.

New N-halamines (I-Cl and II-Cl) based on cellulose extracted from rice straw have been evaluated in single and multistage filtration systems against bacteria and viruses. Escherichia coli and Staphylococcus aureus were used as examples of Gram-negative and Gram-positive bacteria respectively while PRD1 bacteriophage was used as an example for viruses. II-Cl has achieved 9 log reductions in viable counts against E. coli in 2 h and S. aureus in 1h while it has achieved 7 log reductions against PRD1 in 5 h. The particle size of prepared materials was modified as well as the flow rate through the filtration systems. The antimicrobial activity of modified cellulose was proved to be comparable to some synthetic biocidal polymers from the same type in similar water treatment systems.

GSMN-TB: a web-based genome-scale network model of Mycobacterium tuberculosis metabolism.

BACKGROUND: An impediment to the rational development of novel drugs against tuberculosis (TB) is a general paucity of knowledge concerning the metabolism of Mycobacterium tuberculosis, particularly during infection. Constraint-based modeling provides a novel approach to investigating microbial metabolism but has not yet been applied to genome-scale modeling of M. tuberculosis. RESULTS: GSMN-TB, a genome-scale metabolic model of M. tuberculosis, was constructed, consisting of 849 unique reactions and 739 metabolites, and involving 726 genes. The model was calibrated by growing Mycobacterium bovis bacille Calmette Guérin in continuous culture and steady-state growth parameters were measured. Flux balance analysis was used to calculate substrate consumption rates, which were shown to correspond closely to experimentally determined values. Predictions of gene essentiality were also made by flux balance analysis simulation and were compared with global mutagenesis data for M. tuberculosis grown in vitro. A prediction accuracy of 78% was achieved. Known drug targets were predicted to be essential by the model. The model demonstrated a potential role for the enzyme isocitrate lyase during the slow growth of mycobacteria, and this hypothesis was experimentally verified. An interactive web-based version of the model is available. CONCLUSION: The GSMN-TB model successfully simulated many of the growth properties of M. tuberculosis. The model provides a means to examine the metabolic flexibility of bacteria and predict the phenotype of mutants, and it highlights previously unexplored features of M. tuberculosis metabolism.

Manipulation of the physiology of clavulanic acid production in Streptomyces clavuligerus.

This paper reports a novel use of cluster analysis for the identification of intermediary metabolites that are produced at rates closely correlated with those of antibiotic biosynthesis. This information was used to devise culture feeds resulting in enhanced production of clavulanic acid, an antibiotic of current worldwide commercial interest. The feeding strategies apparently alleviated a rate-limiting supply of the C3 precursor of clavulanic acid. C3 limitation may be a consequence of unusual nitrogen and carbon metabolism in Streptomyces clavuligerus. This approach has potential as a generic method for influencing biosynthetic pathway fluxes using feeds without knowledge of the biosynthetic pathway.