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Harmer, N.

Publications and source records attributed to Harmer, N..

2 recordsLinked to original sources

Drug screening to identify compounds to act as co-therapies for the treatment of pathogenic Burkholderia

Burkholderia pseudomallei is a soil-dwelling organism present throughout the tropics, and is the causative agent of melioidosis, a disease that is believed to kill 89,000 people per year. It is naturally resistant to most currently available antibiotics. The most efficacious treatment for melioidosis requires at least two weeks of intravenous treatment with ceftazidime or meropenem. This places a large treatment burden on the predominantly middle income nations where the majority of disease occurs. We have established a high-throughput assay for compounds that could be used as a co-therapy to potentiate the effect of ceftazidime, using the related non-pathogenic bacterium Burkholderia thailandensis as a surrogate. Optimization of the assay gave a Z factor of 0.68. We screened a library of 61,250 compounds, and identified 29 compounds with a pIC50 (-log10(IC50)) greater than five. Detailed investigation allowed us to down select to six \"best in class\" compounds, which included the licensed drug chloroxine. Co-treatment of B. thailandensis with ceftazidime and chloroxine reduced culturable cell numbers by two orders of magnitude over 48 hours compared to treatment with ceftazidime alone. Hit expansion around chloroxine was performed using commercially available compounds. Minor modifications to the structure abolished activity, suggesting that chloroxine likely acts against a specific target. Finally, preliminary data also demonstrates the utility of chloroxine to act as a co-therapy to potentiate the effect of ceftazidime against B. pseudomallei. This approach successfully identified potential co-therapies for a recalcitrant Gram-negative bacterial species. Our assay could be used more widely to aid in chemotherapy against these bacteria.

microbiology

Engineering a seven enzyme biotransformation using mathematical modelling and characterized enzyme parts

Multi-step enzyme reactions offer considerable cost and productivity benefits. Process models offer a route to understanding the complexity of these reactions, and allow for their optimization. Despite the increasing prevalence of multi-step biotransformations, there are few examples of process models for enzyme reactions. From a toolbox of characterized enzyme parts, we demonstrate the construction of a process model for a seven enzyme, three step biotransformation using isolated enzymes. Enzymes for cofactor regeneration were employed to make this in vitro reaction economical. Good modelling practice was critical in evaluating the impact of approximations and experimental error. We show that the use and validation of process models was instrumental in realizing and removing process bottlenecks, identifying divergent behavior, and for the optimization of the entire reaction using a genetic algorithm. We validated the optimized reaction to demonstrate that complex multi-step reactions with cofactor recycling involving at least seven enzymes can be reliably modelled and optimized.\n\nSignificance statementThis study examines the challenge of modeling and optimizing multi-enzyme cascades. We detail the development, testing and optimization of a deterministic model of a three enzyme cascade with four cofactor regeneration enzymes. Significantly, the model could be easily used to predict the optimal concentrations of each enzyme in order to get maximum flux through the cascade. This prediction was strongly validated experimentally. The success of our model demonstrates that robust models of systems of at least seven enzymes are readily achievable. We highlight the importance of following good modeling practice to evaluate model quality and limitations. Examining deviations from expected behavior provided additional insight into the model and enzymes. This work provides a template for developing larger deterministic models of enzyme cascades.

biochemistry