Journal Article

·2020

Determining the optimum model parameters for oligosaccharide production efficiency using response surface integrated particle swarm optimization method: an experimental validation study

Abdullah Tahir Şensoy , Hümeyra İspirli YTU , Enes Dertli̇ YTU

Preparative Biochemistry & Biotechnology

Abstract

Glucansucrases (GTFs) catalyzes the synthesis of α-glucans from sucrose and oligosaccharides in the presence of an acceptor sugar by transferring glucosyl units to the acceptor molecule with different linkages. The acceptor reactions can be affected by several parameters and this study aimed to determine the optimal reaction parameters for the production of glucansucrase-based oligosaccharides using sucrose and maltose as the donor and acceptor sugars, respectively via a hybrid technique of Response Surface Method (RSM) and Particle Swarm Optimization (PSO). The experimental design was performed using Central Composite Design and the tested parameters were enzyme concentration, acceptor:donor ratio and the reaction period. The optimization studies showed that enzyme concentration was the most effective parameter for the final oligosaccharides yields. The optimal values of the significant parameters determined for enzyme concentration and acceptor:donor ratio were 3.45 U and 0.62, respectively. Even the response surface plots for input parameters verified the PSO results, an experimental validation study was performed for the reverification. The experimental verification results obtained were also consistent with the PSO results. These findings will help our understanding in the role of different parameters for the production of oligosaccharides in the acceptor reactions of GTFs.

Keywords

Response surface methodology Acceptor Central composite design Chemistry Particle swarm optimization Maltose Oligosaccharide Sucrose Chromatography Biochemistry Mathematics Mathematical optimization Physics

Subject Areas

Enzyme Production and Characterization ·Biotechnology ·Life Sciences
Microbial Metabolites in Food Biotechnology ·Nutrition and Dietetics ·Health Sciences
Biofuel production and bioconversion ·Biomedical Engineering ·Physical Sciences

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