Optimized phenol degradation and lipid production by Rhodosporidium toruloides using response surface methodology and...

Area of Science:

• Biotechnology
• Environmental Science
• Microbiology

Background:

• Phenol is a common industrial pollutant.
• Oleaginous yeast offers a sustainable solution for phenol degradation and valuable lipid production.
• Optimizing these dual processes is crucial for effective wastewater treatment.

Purpose of the Study:

• To identify key factors influencing phenol degradation and lipid production by *Rhodotorula toruloides* 9564^T.
• To develop and compare predictive models for optimizing these processes.
• To experimentally validate the optimized conditions for maximum phenol removal and lipid yield.

Main Methods:

• Plackett-Burman Design (PBD) for factor screening.
• Central Composite Design (CCD) for response surface methodology.
• Development of quadratic and artificial neural network (ANN) models.
• Multi-objective optimization and experimental validation.

Main Results:

• Temperature, inoculum size, and agitation significantly impacted both phenol degradation and lipid production.
• ANN models demonstrated superior predictive accuracy (R² > 0.98) compared to quadratic models.
• Optimized conditions yielded 100% phenol degradation and a 3.35-fold increase in lipid production (0.918 g/L).

Conclusions:

• *Rhodotorula toruloides* 9564^T is effective for simultaneous phenol removal and lipid biosynthesis.
• Mathematical modeling, particularly ANN, is valuable for optimizing bioremediation processes.
• The study provides a robust framework for enhancing yeast-based wastewater treatment and oleochemical production.