Czech J. Food Sci., 2024, 42(4):225-234 | DOI: 10.17221/193/2023-CJFS

Optimisation of experimental variables for extracellular amylase production by Bacillus cereus AS2Original Paper

Aneela Rehman¹, Asma Saeed², Wajeeha Asad², Ibrar Khan¹, Mujaddadur Rehman¹, Azam Hayat¹, Tawaf Ali Shah³, Turki Mohammed Dawoud⁴, Mohammed Bourhia⁵

¹ Department of Microbiology, Abbottabad University of Science and Technology, Havelian, Pakistan

² Department of Microbiology, University of Karachi, Karachi, Pakistan

³ College of Agriculture Engineering and Food Sciences, Shandong University of Technology, Zibo, China

⁴ Department of Botany and Microbiology, College of Science, King Saud University, Riyadh, Saudi Arabia

⁵ Department of Chemistry and Biochemistry, Faculty of Medicine and Pharmacy, Ibn Zohr University, Laayoune, Morocco

Amylases are one of the biotechnologically important enzymes that have multiple applications in the food, pharmaceutical, cosmetics, textile, detergent, paper and pulp, bioremediation and nano-biotechnology industries. Amylases can be isolated from animals, plants and microbial regions, but nowadays enzymes from prokaryotic species have gained more importance. Among the microbes, amylases from Bacillus cereus have gained considerable demand in various industrial sectors. Growing industrial demand for enzymes compels the availability of enzymes in large quantities that can only be achieved by employing efficient fermentation techniques. Therefore, the current study is aimed at the statistical optimisation of the production conditions for extracellular amylase production from Bacillus strain AS2. In a recent study, the optimum amylase producing AS2 strain was identified on a molecular level, and it was found that it has close relation with the already reported strains of Bacillus cereus. The further enzyme production was optimised by using a statistical optimisation tool. A full-factorial central composite design (CCD) consisting of 53 experiments was designed using six significant variables (incubation period, pH, temperature, carbon and nitrogen source and metal ion). The analysis revealed that the optimal media concentrations were 54.34 g·L^–1 starch, 0.63 g·L^–1 CaCl₂, 1 g·L^–1 glycine, pH 7.0, 76 h, and 40 °C, respectively. A 1.23-fold increase in the enzyme yield (1 050 IU·mL^–1·min^–1) was noticed as compared to the original production level. The statistical optimisation approach gives the exact variables that influence the enzyme production and, hence, offers the best way to optimise the bioprocess. The optimised enzyme can be used in industries for various purposes such as de-sizing, de-inking, hydrolysing starch residues, etc.

Keywords: amylases; statistical optimisation; response surface methodology; central composite design; bioprocess

Received: November 20, 2023; Revised: June 29, 2024; Accepted: July 12, 2024; Prepublished online: August 8, 2024; Published: August 28, 2024  Show citation