Optimization of amorphadiene production in engineered yeast by response surface methodology

Abstract

Isoprenoids are among the most diverse bioactive compounds synthesized by biological systems. The superiority of these compounds has expanded their utility from pharmaceutical to fragrances, including biofuel industries. In the present study, an engineered yeast strain Saccharomyces cerevisiae (YCF-AD1) was optimized for production of Amorpha-4, 11-diene, a precursor of anti-malarial drug using response surface methodology. The effect of four critical parameters such as KH2PO4, methionine, pH and temperature were evaluated both qualitatively and quantitatively and further optimized for enhanced amorphadiene production by using a central composite design and model validation. The “goodness of fit” of the regression equation and model fit (R2) of 0.9896 demonstrate this study to be an effective model. Further, this model will be used to validate theoretically and experimentally at the higher level of amorphadiene production with the combination of the optimized values of KH2PO4 (4.0), methionine (1.49), pH (5.4) and temperature (33 °C).

Optimization of bioactive compounds production by endophytic Chaetosphaeronema sp. (KY321184) using experimental design method

“…The adjusted R 2 value was 0.9877. The adjusted R 2 value corrects the R 2 value for the sample size and for the number of terms in the model (Baadhe et al, 2014). That value of the adjusted R 2 is also good, supporting the significance of this developed model.…”

“…Correlation coefficient (R 2 ) value equals 0.9981 which implies that the model equation could explain 99.81% of the total variation which suggested a good agreement between predicated values and experimental data. R 2 is the coefficient of variance of response under test and whose values are always between 0 and 1; closer the value of R 2 to 1, the stronger is the statistical model and better is the prediction (Baadhe et al, 2014). The adjusted R 2 value was 0.9877.…”

“…Response surface methodology (RSM) answers the question of how to select the levels for the applied factors to obtain the desirable value of the response in a reduced number of experiments (Bai et al, 2015). Moreover, it has been widely used to evaluate and understand the interactions between the different process parameters (Baadhe et al, 2014). Box-Behnken design is a RSM technique which has been widely studied by many researchers as an established and promising method for the optimization and formulation of various types Figure 9: 1 HNMR for compound produced in trail number 15 in PBD of processes (Ding et al, 2016).…”

Response surface methodology‐mediated improvement of the irradiated endophytic fungal strain, Alternaria brassicae AGF041 for Huperzine A‐hyperproduction

“…Values of R 2 are from 0 to 1; when R 2 value comes near to 1, it reflects stronger statistical model and better prediction (Uma and Satyanarayana 2003; Baadhe et al . 2014). Here, the model coefficient of determination R 2 equals 0·9859, the adjusted R 2 equals 0·9772, and the predicted R 2 equals 0·9533, which indicated the high model correlation with the experimental values and fitness of model, and supported the model significance.…”

Metabolic engineering strategies for sesquiterpene production in microorganism

“…PCTR3 repressed by cheap CuSO4 was slight better to suppress ERG9 expression to reduce FPP flux to squalene than PMET3 repressed by methionine (Paddon et al , 2013, Peng et al , 2017. To achieve high sesquiterpene, fermentation process needs to be optimized via such as response surface methodology (Baadhe et al , 2014) and feeding various carbon sources. Feedback-controlled ethanol pulse feed has several significant advantages over restricted glucose feed.…”