Mathematical Modelling of Galactooligosaccharides Synthesis: Insights into Aspergillus oryzae Derived β-Galactosidase Kinetics

The objective of this study was to adapt experimental data with a mathematical model based on transgalactosylation mechanisms identified in the literature for the synthesis of galactooligosaccharides and lactose hydrolysis. Galactooligosaccharides, synthesized from lactose through β-galactosidase-catalyzed transgalactosylation reactions, are acknowledged as specific bifidogenic factors among prebiotic carbohydrates. Modelling galactooligosaccharide synthesis is challenging due to simultaneous hydrolysis and transferase reactions with identical nucleophiles and substrates. Therefore, researchers tried to simplify the mechanism by ignoring intermediate reactions or inhibitory effects of glucose and galactose. This study explored various kinetic models, considering the complexity of the reaction mechanism and balancing accuracy with feasibility. Experimental data from galactooligosaccharide synthesis using a continuous stirred tank reactor was adapted to kinetic models (Models A and B) with modifications, incorporating glucose and galactose inhibitions. The COPASI software was used for testing fitness of reaction models. Eight models were evaluated for their suitability, utilizing six replicated experimental datasets under specific reaction conditions, including a temperature of 45°C, lactose concentration of 18.25°Brix, and enzyme concentration of 10-unit g lactose solution-1. The analysis was conducted using the "random research" and "particle swarm" algorithms. Model evaluations revealed that Model B, augmented with glucose and galactose inhibitions, provided the closest alignment between experimental and simulated data. The study underscored the significance of glucose and galactose impacts on galactooligosaccharide synthesis efficiency. The Model B, with addition of glucose and galactose inhibitions, emerged as a valuable tool for predicting galactooligosaccharide yield, contributing to a deeper understanding of A.oryzae-derived β-galactosidase kinetics due to its significant influence on parameters such as productivity, conversion of lactose, and composition of product. The findings will guide optimization strategies for enhanced galactooligosaccharide production efficiency, advancing knowledge in enzymatic galactooligosaccharide synthesis.

Authors

Institutions

Publication Details

Journal
Tekirdağ Ziraat Fakültesi Dergisi
Published
2025-05-08
DOI
https://doi.org/10.33462/jotaf.1426086
Primary Topic
Microbial Metabolic Engineering and Bioproduction
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Mathematical Modelling of Galactooligosaccharides Synthesis: Insights into Aspergillus oryzae Derived β-Galactosidase Kinetics

Hacı Ali Güleç, Kadir Çınar, Gürbüz Güneş
Tekirdağ Ziraat Fakültesi Dergisi
Microbial Metabolic Engineering and Bioproduction
article

Mathematical Modelling of Galactooligosaccharides Synthesis: Insights into Aspergillus oryzae Derived β-Galactosidase Kinetics

Hacı Ali Güleç, Kadir Çınar, Gürbüz Güneş
article en

Abstract

The objective of this study was to adapt experimental data with a mathematical model based on transgalactosylation mechanisms identified in the literature for the synthesis of galactooligosaccharides and lactose hydrolysis. Galactooligosaccharides, synthesized from lactose through β-galactosidase-catalyzed transgalactosylation reactions, are acknowledged as specific bifidogenic factors among prebiotic carbohydrates. Modelling galactooligosaccharide synthesis is challenging due to simultaneous hydrolysis and transferase reactions with identical nucleophiles and substrates. Therefore, researchers tried to simplify the mechanism by ignoring intermediate reactions or inhibitory effects of glucose and galactose. This study explored various kinetic models, considering the complexity of the reaction mechanism and balancing accuracy with feasibility. Experimental data from galactooligosaccharide synthesis using a continuous stirred tank reactor was adapted to kinetic models (Models A and B) with modifications, incorporating glucose and galactose inhibitions. The COPASI software was used for testing fitness of reaction models. Eight models were evaluated for their suitability, utilizing six replicated experimental datasets under specific reaction conditions, including a temperature of 45°C, lactose concentration of 18.25°Brix, and enzyme concentration of 10-unit g lactose solution-1. The analysis was conducted using the "random research" and "particle swarm" algorithms. Model evaluations revealed that Model B, augmented with glucose and galactose inhibitions, provided the closest alignment between experimental and simulated data. The study underscored the significance of glucose and galactose impacts on galactooligosaccharide synthesis efficiency. The Model B, with addition of glucose and galactose inhibitions, emerged as a valuable tool for predicting galactooligosaccharide yield, contributing to a deeper understanding of A.oryzae-derived β-galactosidase kinetics due to its significant influence on parameters such as productivity, conversion of lactose, and composition of product. The findings will guide optimization strategies for enhanced galactooligosaccharide production efficiency, advancing knowledge in enzymatic galactooligosaccharide synthesis.

Tekirdağ Ziraat Fakültesi DergisiVol. 22(2)
Trakya University (TR), Istanbul Technical University (TR)
Istanbul Teknik Üniversitesi
Openalex Percentile: Top 91%
Microbial Metabolic Engineering and Bioproduction
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.