Strain improvement, artificial intelligence optimization, and sensitivity analysis of asparaginase-mediated acrylamide reduction in sweet potato chips

Ernest Akwagiobe; Maurice Ekpenyong; Atim Asitok; Andrew Amenaghawon; David Ubi; Eloghosa Ikharia; Heri Kusuma; Sylvester Antai

doi:10.1007/s13197-023-05757-5

Strain improvement, artificial intelligence optimization, and sensitivity analysis of asparaginase-mediated acrylamide reduction in sweet potato chips

J Food Sci Technol. 2023 Sep;60(9):2358-2369. doi: 10.1007/s13197-023-05757-5. Epub 2023 May 3.

Authors

Ernest Akwagiobe¹, Maurice Ekpenyong^{2

3}, Atim Asitok^{2

3}, Andrew Amenaghawon⁴, David Ubi¹, Eloghosa Ikharia³, Heri Kusuma⁵, Sylvester Antai^{2

3}

Affiliations

¹ Food and Industrial Microbiology Unit, Department of Microbiology, Faculty of Biological Sciences, University of Calabar, Calabar, Nigeria.
² Environmental Microbiology and Biotechnology Unit, Department of Microbiology, University of Calabar, Calabar, Nigeria.
³ University of Calabar Collection of Microorganisms (UCCM), University of Calabar, Calabar, Nigeria.
⁴ Department of Chemical Engineering, Faculty of Engineering, University of Benin, Benin City, Nigeria.
⁵ Department of Chemical Engineering, Faculty of Industrial Technology, Universitas Pembangunan Nasional "Veteran" Yogyakarta, Yogyakarta, Indonesia.

PMID: 37424578
PMCID: PMC10326208 (available on 2024-09-01)
DOI: 10.1007/s13197-023-05757-5

Abstract

In recent times, L-asparaginase has emerged as a potential anti-carcinogen through hydrolysis of L-asparagine in the blood for anti-leukemic application, and in carbohydrate-based foods, for acrylamide reduction applications. In this study, Aspergillus sydowii strain UCCM 00124 produced an L-asparaginase with a baseline acrylamide reduction potential of 64.5% in sweet potato chips. Plasma mutagenesis at atmospheric pressure and room temperature (ARTP) was employed to improve L-asparaginase production while artificial neural network embedded with genetic algorithm (ANN-GA) and global sensitivity analysis were used to identify and optimize process conditions for improved acrylamide reduction in sweet potato chips. The ARTP mutagenesis generated a valine-deficient mutant, Val^-Asp-S-180-L with 2.5-fold L-asparaginase improvement. The ANN-GA hybrid evolutionary intelligence significantly improved process efficiency to 98.18% under optimized conditions set as 118.6 °C, 726.37 g/L asparagine content, 9.92 µg/mL L-asparaginase, 4.54% NaCl, and soaking time of 15 h without significant changes in sensory properties. The sensitivity index revealed initial asparagine content as the most sensitive parameter to the bioprocess. The enzyme demonstrated significant thermo-stability with Arrhenius deactivation rate constant, K_d, of 0.00562 min^-1 and half-life, t_1/2, of 123.35 min at 338 K. These conditions are recommended for sustainable healthier, and safer sweet potato chips processing in the food industry.

Supplementary information: The online version contains supplementary material available at 10.1007/s13197-023-05757-5.

Keywords: ANN-GA optimization; ARTP mutagenesis; Acrylamide mitigation; L-asparaginase; Sensitivity analysis; Sweet potato chips.

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