Artificial Neural Networks and Response Surface Methodology Approach for Optimization of an Eco-Friendly and Detergent-Stable Lipase Production from Actinomadura Keratinilytica Strain Cpt29

Acta Chim Slov. 2021 Sep;68(3):575-586.

Abstract

This work mainly focused on the production of an efficient, economical, and eco-friendly lipase (AKL29) from Actinomadura keratinilytica strain Cpt29 isolated from poultry compost in north east of Algeria, for use in detergent industries. AKL29 shows a significant lipase activity (45 U/mL) towards hydrolyzed triacylglycerols, indicating that it is a true lipase. For maximum lipase production the modeling and optimization of potential culture parameters such as incubation temperature, cultivation time, and Tween 80 (v/v) were built using RSM and ANN approaches. The results show that both the two models provided good quality predictions, yet the ANN showed a clear superiority over RSM for both data fitting and estimation capabilities. A 4.1-fold increase in lipase production was recorded under the following optimal condition: incubation temperature (37.9 °C), cultivation time (111 h), and Tween 80 (3.27%, v/v). Furthermore, the partially purified lipase showed good stability, high compatibility, and significant wash performance with various commercial laundry detergents, making this novel lipase a promising potential candidate for detergent industries.

MeSH terms

  • Actinomadura / enzymology*
  • Bacterial Proteins / chemistry*
  • Bacterial Proteins / isolation & purification
  • Detergents / chemistry*
  • Enzyme Stability
  • Fungal Proteins / chemistry
  • Kinetics
  • Lipase / chemistry*
  • Lipase / isolation & purification
  • Neural Networks, Computer
  • Saccharomycetales / enzymology
  • Triglycerides / chemistry

Substances

  • Bacterial Proteins
  • Detergents
  • Fungal Proteins
  • Triglycerides
  • Lipase

Supplementary concepts

  • Actinomadura keratinilytica
  • Diutina rugosa