Lipases are the enzymes of choice for laundry detergent industries owing to their triglyceride removing ability from the soiled fabric which eventually reduces the usage of phosphate-based chemical cleansers in the detergent formulation. In the present study, a partially purified bacterial lipase from Staphylococcus arlettae JPBW-1 isolated from the rock salt mine has been assessed for its triglyceride removing ability by developing a presoak solution so as to use lipase as an additive in laundry detergent formulations. The effects of selected surfactants, commercial detergents, and oxidizing agents on lipase stability were studied in a preliminary evaluation for its further usage in the industrial environment. Partially purified lipase has shown good stability in presence of surfactants, commercial detergents, and oxidizing agents. Washing efficiency has been found to be enhanced while using lipase with 0.5% nonionic detergent than the anioinic detergent. The wash performance using 0.5% wheel with 40 U lipase at 40°C in 45 min results in maximum oil removal (62%) from the soiled cotton fabric. Hence, the present study opens the new era in enzyme-based detergent sector for formulation of chemical-free detergent using alkaline bacterial lipase.

Studies on lipase production and characterization were carried out with a bacterial strain Staphylococcus arlettae JPBW-1 isolated from rock salt mine, Darang, HP, India. Higher lipase activity has been obtained using 10 % inoculum with 5 % of soybean oil as carbon source utilizing a pH 8.0 in 3 h at 35 °C and 100 rpm through submerged fermentation. Partially purified S. arlettae lipase has been found to be active over a broad range of temperature (30-90 °C), pH (7.0-12.0) and NaCl concentration (0-20 %). It has shown extreme stability with solvents such as benzene, xylene, n-hexane, methanol, ethanol and toluene up to 30 % (v/v). The lipase activity has been found to be inhibited by metal ions of K(+), Co(2+) and Fe (2+) and stimulated by Mn(2+), Ca(2+) and Hg(2+). Lipase activity has been diminished with denaturants, but enhanced effect has been observed with surfactants, such as Tween 80, Tween 40 and chelator EDTA. The K m and V max values were found to be 7.05 mM and 2.67 mmol/min, respectively. Thus, the lipase from S. arlettae may have considerable potential for industrial application from the perspectives of its tolerance towards industrial extreme conditions of pH, temperature, salt and solvent.

Microbial enzymes from extremophilic regions such as hot spring serve as an important source of various stable and valuable industrial enzymes. The present paper encompasses the modeling and optimization approach for production of halophilic, solvent, tolerant, and alkaline lipase from Staphylococcus arlettae through response surface methodology integrated nature inspired genetic algorithm. Response surface model based on central composite design has been developed by considering the individual and interaction effects of fermentation conditions on lipase production through submerged fermentation. The validated input space of response surface model (with R 2 value of 96.6%) has been utilized for optimization through genetic algorithm. An optimum lipase yield of 6.5 U/mL has been obtained using binary coded genetic algorithm predicted conditions of 9.39% inoculum with the oil concentration of 10.285% in 2.99 hrs using pH of 7.32 at 38.8°C. This outcome could contribute to introducing this extremophilic lipase (halophilic, solvent, and tolerant) to industrial biotechnology sector and will be a probable choice for different food, detergent, chemical, and pharmaceutical industries. The present work also demonstrated the feasibility of statistical design tools integration with computational tools for optimization of fermentation conditions for maximum lipase production.

Lipase-based detergent formulations are a viable substitute for chemical detergents that pose health and environmental hazards to customers and society. In this study, the efficacy of Staphylococcus arlettae JPBW-1 lipase as an additive in laundry detergent was assessed for oil removal through modeling and optimization using a response-surface-methodologyintegrated genetic algorithm. A three-level five-factorial central composite design was used to evaluate the interactive effects on oil removal percentage from cotton fabric of process conditions, namely, detergent concentration, lipase concentration, buffer pH, washing temperature, and washing time. The input space of the validated response surface methodology (RSM) model (R 2 value of 97.7%) was utilized for genetic algorithm (GA) optimization. An optimum value of 79.6% oil removal was achieved with the GA-predicted process variables of 0.69% detergent, 47.37 U of lipase, buffer pH of 7.2, and washing temperature of 37.18°C in 26.11 min, which was 27% more than the oil removal without lipase. Hence, lipase from S. arlettae JPBW-1 can be effectively used as an additive in laundry detergent for oil removal from soiled fabric and introduces a new lipase into the biobased detergent industry.

A three‐step purification of a unique lipase with halo‐, solvent‐, detergent‐, and thermo‐tolerance from Staphylococcus arlettae JPBW‐1 gave raise to a 27‐fold purification with a specific activity of 32.5 U/mg. The molecular weight of the purified lipase was estimated to be 45 kDa using SDS–PAGE, and its amino acid sequence was characterized using MALDI‐TOF‐MS analysis. The sequence obtained from MALDI‐TOF‐MS showed significant similarity with the capsular polysaccharide biosynthesis protein (CapD) of Staphylococcus aureus through comparative modeling approach using ROBETTA server. Identification of responsible fragments for homodimer formation was performed using comparative modeling and substrate binding domain through C‐terminus matching of this new lipase with the CapD of Staphylococcus aureus was executed. Thus, the experimental coupled molecular modeling postulated a structure–activity relationship of lipase from S. arlettae JPBW‐1, a potential candidate for detergent, leather, pulp, and paper industries.