Statistical optimization of culture medium to produce recombinant viral protein by Escherichia coli host for diagnostic kit to detect human immunodeficiency virus (HIV) infection

Design of experiments and design space approaches in the pharmaceutical bioprocess optimization

The optimization of pharmaceutical bioprocesses suffers from several challenges like complexity, upscaling costs, regulatory approval, leading to the risk of delivering substandard drugs to patients. Bioprocess is very complex and requires the evaluation of multiple components that need to be monitored and controlled in order to attain the desired state when the process ends. Statistical design of experiments (DoE) is a powerful tool for optimizing bioprocesses because it plays a critical role in the quality by design strategy as it is useful in exploring the experimental domain and providing statistics of interest that enable scientists to understand the impact of critical process parameters on the critical quality attributes. This review summarizes selected publications in which DoE methodology was used to optimize bioprocess. The main objective of the critical review was to clearly demonstrate potential benefits of using the DoE and design space methodologies in bioprocess optimization.

Investigation of fermentation conditions of biodiesel by-products for high production of β-farnesene by an engineered Escherichia coli

Recently, the research on conversion of biodiesel by-products to high value-added products has received much attention, due to the adverse effects of large accumulations of biodiesel by-products caused by the rapid increase in biodiesel production. Herein, this study investigated the utilization of by-products crude glycerol (CG-1 and CG-2) from two different industrial methods of biodiesel production and the favorable fermentation conditions for the high yield of β-farnesene by an engineered Escherichia coli F4, which harbored an optimized mevalonate pathway. Through analyzing by-products' components and fermentation performance, we found that CG-2 did not contain harmful impurities such as methanol and black solid impurities, and the β-farnesene production was up to 2.7 g/L from CG-2, which was similar to that from pure glycerol (2.5 g/L) and higher than that (2.21 g/L) from CG-1. Therefore, CG-2 was more suitable for β-farnesene production than CG-1, which might provide a reference for choosing a more suitable method on practical biodiesel production. Afterward, a variety of important fermentation conditions were explored using CG-2 as a substrate in shaken flasks. Under the optimal conditions (including induced cell density 1.0, initial cell density 0.25, temperature after induction 33 °C, initial medium pH 6.5), the yield of β-farnesene from CG-2 reached 10.31 g/L in a 5-L bioreactor, which was 2.8-fold higher than initial conditions in shake flasks and was the highest yield of β-farnesene produced from biodiesel by-products by fermentation as well. The recommended fermentation conditions in this work will provide a valuable reference for the industrial production of β-farnesene utilizing biodiesel by-products.

Optimization of medium composition for propagation of recombinant Escherichia coli

Recombinant protein production in heterologous hosts often seems a simpler and more effective way than its production by natural producer. The secretion of recombinant protein inEscherichia colihas many advantages comparing to than in insect or mammalian cells. The important factor for high-level recombinant protein production is the sufficient amount ofE. colibiomass. Therefore, the aim of this study was to optimize the composition of propagation medium resulting in the maximum biomass yield of recombinantE. colias the part of fermentation strategy for neuraminidase (NA) production. Three independent variables including glucose, asparagine and phosphate concentrations, and four dependent variables, such as biomass yield, residual concentrations of glucose or asparagine and pH of the propagation medium after fermentation, were chosen to the optimization by Response Surface Methodology (RSM). The optimal conditions for the maximum biomass yield expressed as dry cell weight (DCW) (16.57±0.55 g DCW.L−1) were as follows: glucose concentration of 39.37 mM, asparagine concentration of 62.68 mM and phosphate concentration of 14.80 mM. For this model, the predicted values for the responses are close to the experimental values. The yield of desired pET15b-neu plasmid fromE. colicells cultivated in optimized propagation medium was almost 23 % higher than in commonly used Luria-Bertani (LB) medium suggesting that asparagine may be involved in the induction of plasmid amplification.