Genetic improvement of a locally isolated Bacillus cereus AUST-7 strain via mutagenesis for alkaline protease production and its optimization using artificial neural network (ANN)

The present study was conducted on culture improvement of locally isolated Bacillus cereus AUST-7 (NR_112630) strain and optimization by using an artificial neural network. The strain was isolated from a soil sample of a slaughterhouse from the University of Veterinary and Animal Sciences Lahore. The physical ultraviolet (UV) and chemical mutagens (ethyl methane sulphonate, methyl methane sulphonate, and ethidium bromide) were used for strain improvement. Artificial neural network (ANN) was used to optimize the effect of five variables including, tannery waste, molasses, temperature, pH, and incubation period for protease production. UV-1 showed maximum clearance zone and enzyme activity (1073.00 IU/ml) followed by MMS 90–1 and EMS 90–7 respectively as compared to wild strain 449.65 IU/ml. The values of R 2 (0.968) and adjusted R 2 (0.925) with AAD and RSME (1.104, 29.41) represent the significance of the model. Tannery waste shows the maximum effect on enzyme production. Next are molasses, pH, temperature, and incubation period respectively. The optimal levels obtained were 1% tannery waste, 1% molasses, 30 ℃ temperature, 9.3 pH, and an incubation period of 96 h with a predicted value of 1550.667 IU/ml, and the experimental value was 1692.2 IU/ml. Strain improvement and optimization enhanced protease production by 50%.