MODELLING AND SIMULATION OF LARGE SCALE STREPTOKINASE PRODUCTION USING E. coli AS A HOST

Abstract

The enzyme streptokinase is secreted by β-hemolytic streptococcus sp., which is often used to treat acute myocardial infarction and pulmonary embolism, being a vital drug it is required to be produced in recombinant form for thrombolytic therapy. This enzyme can be produced by using recombinant E. coli cells. The unstructured model factors were found to apparently influence the existence of active cells in the bioreactor environment. Our endeavour was to make out obligatory constraints that deal with the plasmid instability with an approach to apply composite model, which explained the relevant part of dynamics in bioreactor operation. Computational models were developed utilizing structured and unstructured approaches. A range of dilution rates were selected starting from 0.1 to 0.65. On simulation of the process, the patterns obtained noticeably depicts the role of relevant parameters governing bioprocess system, particularly metabolite concentration and dilution rate, to present segregational instability and competitive dynamics in cell population. A set of parameters, including plasmid bearing cell population, plasmid lacking cell population, substrate concentration, metabolite concentration and probability of plasmid loss were taken into account. The idea was to measure the instability of plasmid, which could be directly derived from the growth of plasmid lacking cell population. This strategy ensures high flexibility in bioprocess modelling framework since it has a number of adjustable parameters. Other bioprocess models were assumed to reveal the significance of dilutions and antibiotic concentration regulation during continuous culture. The structural machinery of a cell itself could assume to be an entire structured system that presented the functional role of various sub-cellular entities. The rate of failure of any cellular entity was found to be governed by prime metabolic events and partitioning phenomenon. Plasmid copy number dynamics trend was observed to evaluate the effect of metabolite concentration in time dependent manner. The copy number was estimated particularly after 2-6 hours of induction to understand its variability. Firstly, the production media was statistically assessed using Plackett Burman design and later central composite design was used to estimate the interacting media components and culture condition factors. The four selected media components were put for CCD analysis and optimization. The production of streptokinase with optimized vi medium and culture conditions was found up to 40% higher in magnitude in comparison to usual based conditions. An effective numerical system had been further considered using neural network and statistical method together where the prior one served as a potent tool for identifying and optimizing the output parameter. The statistical and neural network approaches were compared in predicting the output of different set of optimization systems; the later had revealed results that are more accurate. The different inputs of population dynamics simulation had been taken to neural network and prediction accuracy with high value of r2 0.98 was achieved in estimation product formation. The production of highly valuable recombinant enzymes is being done using fermentation technology and in similar way the computational bioprocess methodologies can be used for its large scale production.