Statistical optimization of medium for the production of pyruvate oxidase by the recombinant Escherichia coli

Abstract

Pyruvate oxidase (PyOD) is a very useful enzyme for clinical diagnostic applications and environmental monitor. Optimization of the fermentation medium for maximization of PyOD constitutively, production by Escherichia coli DH5alpha/pSMLPyOD was carried out. Response surface methodology (RSM) was used to optimize the medium constituents. A 2(6-2) fractional factorial design (first order model) was carried out to identify the significant effect of medium components towards PyOD production. Statistical analysis of results shows that yeast extract, ammonium sulfate and composite phosphate were significant factors on PyOD production. The optimized values of these three factors were obtained by RSM based on the result of a 2(3) central composite rotatable design. Under these proposed optimized medium, the model predicted a PyOD activity of 610 U/L and via experimental rechecking the model, an activity of 670 U/L was attained.

Optimization of medium formulation and seed conditions for expression of mature PsaA (pneumococcal surface adhesin A) in Escherichia coli using a sequential experimental design strategy and response surface methodology

“…For other proteins described in the literature [23], and pneumolysin from S. pneumoniae expressed in the same system as PsaA [14], tryptone had a positive effect on protein production in E. coli. The enhancement of recombinant protein expression in E. coli with a higher yeast extract concentration was also described in other works using similar shake flask conditions and in the same range of concentrations in the culture medium [4,29,30]. Chen et al [4] reported that yeast extract was effective as a nitrogen source to improve recombinant protein expression.…”

“…As no single set of culture conditions can be applied to different kinds of cells, a screening and development approach is necessary for optimal performance and for reducing time and costs. Statistical optimization and experimental design have proved to be very effective when several variables have to be considered and the relative importance of each one is not yet known [16,30]. Experimental design can be used to evaluate which variables and which variable interactions influence recombinant protein expression, information that cannot be obtained from methods that vary one variable at a time.…”

“…Recently, researchers have given more attention to the effect of culture medium on protein expression, and more articles have been published that make use of experimental design tools. Experimental design has been used by other research groups to optimize the culture medium composition for recombinant protein expression in E. coli [4,6,9,11,16,19,20,23,29,30] or seed conditions and inoculum level/density [11,21,27]. Table 2, and estimated effects of each variable and p values in Table 3.…”

Experimental design approach in recombinant protein expression: determining medium composition and induction conditions for expression of pneumolysin from Streptococcus pneumoniae in Escherichia coliand preliminary purification process

“…Statistical methods through factorial experimental designs not only offer the simultaneous study of many variables, but also allow the study of interactive effects of many factors together, facilitating the prediction of the response for the values of variables not tested in the experiment [7,21]. In recent years, factorial designs - which are statistical techniques for designing experiments, defined significant effects, building models, evaluating the effects of variables and searching for optimum conditions - have successfully been used to optimize many bioprocesses [22,23]; however, they are not yet the most common strategies used to evaluate heterologous protein expression. The use of statistically designed experiments allows the rapid and economical determination of optimal culture conditions with fewer experiments and minimal resources [24].…”

Application of fractional factorial design (FFD) for screening of significant factor in influencing succinic acid production from biodiesel based glycerol: Using Escherichia coli

“…The p-valu which is indicates the model the lack of fit test is not sign non-significant lack of fit ind good fit. [23 ].The "Curva implies there is significant cur measured by difference betw center points and the averag [24]. Meanwhile, the signifi also shown in the half normal The data obtained calculate approximately the l in order to gain the optimum production.…”