Central Composite Design-based Optimization of Staphylococcus sp. strain Amr-15 Growth on Acrylamide as a Nitrogen Source

Abstract

As an approach for bioremediation, the decomposition of acrylamide by microorganisms has received gradual but persistent worldwide interest. Prior to this study, a molybdenum-reducing bacteria had been identified and exhibited the ability to breakdown amides. Its key growth parameters on acrylamide were further investigated. A Central Composite Design (CCD) was employed to optimize the two previously identified key factors (incubation time and acrylamide concentration). For the examination of the significant factors or parameters, ANOVA, the perturbation plot, and numerous other diagnostic plots were employed. Using the "Numerical Optimisation" toolbox of Design Expert software, predicted ideal conditions were calculated. There were two ideal conditions investigated. The first was to determine the optimal growth under the employed range of variables, while the second was to forecast the optimal growth at the greatest acceptable acrylamide concentration of 1 g/L. The solution for the first predicted model predicted a maximum growth of 8.96 Log CFU/mL (95 percent confidence interval from 8.19 to 9.73), which was confirmed by experimental results with a growth of 9.88 Log CFU/mL (95 percent confidence interval from 9.79 to 9.97), which was close to the predicted values but significantly greater than the predicted values. The second numerical optimization for maximum growth with the highest acrylamide content. The solution had a predicted maximum growth of 7.81 Log CFU/mL (95 percent C.I. from 7.06 to 8.57) and was experimentally confirmed to have a growth of 8.74 Log CFU/mL (95 percent C.I. from 8.56 to 8.92), with the difference not being statistically significant (p0.05) indicating close agreement between predicted and experimental values. The findings of the RSM exercise demonstrated that growth on acrylamide may be optimized more efficiently with RSM than with OFAT, indicating that RSM is more useful in this regard than OFAT.