Modelling the Enzymatic Deacylation of Penicillin G: Equilibrium and Kinetic Considerations

A General Model for Biofilm-Driven Microbial Electrosynthesis of Carboxylates From CO2

Up to now, computational modeling of microbial electrosynthesis (MES) has been underexplored, but is necessary to achieve breakthrough understanding of the process-limiting steps. Here, a general framework for modeling microbial kinetics in a MES reactor is presented. A thermodynamic approach is used to link microbial metabolism to the electrochemical reduction of an intracellular mediator, allowing to predict cellular growth and current consumption. The model accounts for CO₂ reduction to acetate, and further elongation to n-butyrate and n-caproate. Simulation results were compared with experimental data obtained from different sources and proved the model is able to successfully describe microbial kinetics (growth, chain elongation, and product inhibition) and reactor performance (current density, organics titer). The capacity of the model to simulate different system configurations is also shown. Model results suggest CO₂ dissolved concentration might be limiting existing MES systems, and highlight the importance of the delivery method utilized to supply it. Simulation results also indicate that for biofilm-driven reactors, continuous mode significantly enhances microbial growth and might allow denser biofilms to be formed and higher current densities to be achieved.

Kinetics of β-lactam antibiotics synthesis by penicillin G acylase (PGA) from the viewpoint of the industrial enzymatic reactor optimization

Competition with well-established, fine-tuned chemical processes is a major challenge for the industrial implementation of the enzymatic synthesis of beta-lactam antibiotics. Enzyme-based routes are acknowledged as an environmental-friendly approach, avoiding organochloride solvents and working at room temperatures. Among different alternatives, the kinetically controlled synthesis, using immobilized penicillin G acylase (PGA) in aqueous environment, with the simultaneous crystallization of the product, is the most promising one. However, PGA may act either as a transferase or as a hydrolase, catalyzing two undesired side reactions: the hydrolysis of the acyl side-chain precursor (an ester or amide, a parallel reaction) and the hydrolysis of the antibiotic itself (a consecutive reaction). This review focuses specially on aspects of the reactions' kinetics that may affect the performance of the enzymatic reactor.

Evaluation of the performance of immobilized penicillin G acylase using active-site titration

Penicillin G acylase from Escherichia coli was immobilized on Eupergit C with different enzyme loading. The activity of the immobilized preparations was assayed in the hydrolysis of penicillin G and was found to be much lower than would be expected on the basis of the residual enzyme activity in the immobilization supernatant. Active-site titration demonstrated that the immobilized enzyme molecules on average had turnover rates much lower than that of the dissolved enzyme. This was attributed to diffusion limitations of substrate and product inhibition. Indeed, when the immobilized preparations were crushed, the activity increased from 587 U g-1 to up to 974 U g-1. The immobilized preparations exhibited up to 15% lower turnover rates than the dissolved enzyme in cephalexin synthesis from 7-ADCA and D-(-)-phenylglycine amide. The synthesis over hydrolysis ratios of the immobilized preparations were also much lower than that of the dissolved enzyme. This was partly due to diffusion limitations but also to an intrinsic property of the immobilized enzyme because the synthesis over hydrolysis ratio of the crushed preparations was much lower than that of the dissolved enzyme.

Computer applications in bioprocessing

Biotechnologists have stayed at the forefront for practical applications for computing. As hardware and software for computing have evolved, the latest advances have found eager users in the area of bioprocessing. Accomplishments and their significance can be appreciated by tracing the history and the interplay between the computing tools and the problems that have been solved in bioprocessing.