Bioprocess optimization for glycopeptide biosurfactant production by means of Lactobacillus delbrueckii : Design expert laden approach

Abstract

A bacterial strain, Lactobacillus delbrueckii, was isolated and screened for high potential of biosurfactant (BS) production yield. The current research emphasizes the optimization of process parameters through OFAT (one factor at a time) and RSM (response surface methodology) to achieve optimal BS production. Therefore, xylose and peptone were screened as the best carbon and nitrogen sources respectively by means of OFAT, along with temperature (37°C), inoculum size (5%), and fermentation time (39 h). Furthermore, optimization of xylose (1% w/v), peptone (0.5%w/v), and pH (6.5) through Box–Behnken statistical design was validated by ANOVA (analysis of variance) and found significant (p < .05) with optimal BS yield (7.31 g/L). The solvent‐extracted glycopeptide BS displayed cationic nature, with thermal (0–120°C), pH (2–12), and NaCl (2%–12% w/v) stability. The functional attributes of BS like antiadhesive and antimicrobial activity toward Gram‐positive and Gram‐negative bacteria and emulsifying potency against various vegetable oils make it worthwhile and applicable. Practical applications The recent applications of BS and hazards of pathogenic biofilm make it challenging to produce enhanced yield of BS. In light of this, present work is focused to optimize yield from Lactobacillus delbrueckii for its applications as antibiofilm and bioemulsifier agent in various industries. Furthermore, the glycoproteinaceous BS from microbe in question is itself unique and novel. Additionally, the statistical design of optimization provides experiment modeling, production rate, and significance of opted design which makes the whole process feasible to explore new possibilities for BS production.

Optimization of the Operational Conditions to Produce Extracellular and Cell-Bound Biosurfactants by Aneurinibacillus aneurinilyticus Using Corn Steep Liquor as a Unique Source of Nutrients

“…Thus, linear models have a monotonic growth (that is, they are always increasing or decreasing), while the quadratic function increases in one section and decreases in another, which is more in agreement with the kinetic followed in the fermentative process. Several authors have applied these kinds of models that optimize fermentation conditions for biosurfactant production [40][41][42][43].…”