Michael E. Bushell

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.

The present study represents a genome-wide transcriptomic analysis of the response of the model streptomycete Streptomyces coelicolor A3(2) M145 to fermentor culture in Modified Evans Media limited, respectively, for nitrogen, phosphate and carbon undertaken as part of the ActinoGEN consortium to provide a publicly available reference microarray dataset.

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.

The presence of a plasmid, containing gene sequences for DNA immunotherapy that are not expressed in microbial culture, imposed a degradation in bioreactor performance in cultures of the host E. coli strain. Significant decreases in growth rate (24%) and biomass yield (7%) and a corresponding increase in overflow metabolism were observed in a strain containing a therapeutic sequence (a hepatitis B antigen under the control of a CMV promotor). The observed increase in overflow metabolism was incorporated into a Metabolic Flux Analysis (MFA) model (as acetate secretion). Metabolic flux analysis revealed an increase in TCA cycle flux, consistent with an increased respiration rate observed in plasmid‐containing cells. These effects are thought to result from increased ATP synthesis requirements (24%) arising from the expression of the Kan^r plasmid marker gene whose product accounted for 18% of the cell protein of the plasmid‐containing strain. These factors will necessitate significantly higher aeration and agitation rates or lower nutrient feed rates in high‐density cultures than would be expected for plasmid‐free cultures.

Mutation and selection for increased resistance to cell‐wall synthesis inhibitors led to alterations in the hyphal branching rate of Saccharopolyspora erythraea NRRL 2338. Mutants with decreased branching frequency exhibited increased hyphal strength (estimated by in vitro micromanipulation). As the hyphal strength was increased, this led to a greater proportion of hyphal particles in liquid culture with a hyphal fragment diameter of greater than 88 μm. This, in turn, coincided with proportionately increased antibiotic production. © 2002 Wiley Periodicals, Inc. Biotechnol Bioeng 78: 141–146, 2002; DOI 10.1002/bit.10210

Antibiotic production in Saccharopolyspora erythraea was significantly enhanced in cyclic fed batch culture (c.f.b.c) compared to batch culture, whereas chemostat culture resulted in reduced production. C.f.b.c. allowed the specific growth rate to be varied, with time, according to an asymptotically decreasing trajectory without the necessity for nutrient exhaustion. It was, therefore, possible to increase productivity by increasing the growth-limiting substrate concentration. It was necessary to apply the c.f.b.c regime to early-exponential-phase cultures in order to obtain a stable, nutrient-limited, c.f.b.c. The antibiotic production rate during any c.f.b.c. cycle was dependent on the relationship between the specific growth rate at the time and the growth rate at the start of the cycle.