| Autor: |
Kouka T; Department of Bioinformatics, Graduate School of Engineering, Soka University, Tokyo 192-8577, Japan.; Department of Cardiology, Keio University School of Medicine, Tokyo 160-8582, Japan., Akase S; Department of Bioinformatics, Graduate School of Engineering, Soka University, Tokyo 192-8577, Japan., Sogabe I; Department of Bioinformatics, Graduate School of Engineering, Soka University, Tokyo 192-8577, Japan., Jin C; Proteomics Core Facility at Sahlgrenska Academy, University of Gothenburg, 405 30 Gothenburg, Sweden., Karlsson NG; Department of Life Sciences and Health, Faculty of Health Sciences, Oslo Metropolitan University, 0167 Oslo, Norway., Aoki-Kinoshita KF; Department of Bioinformatics, Graduate School of Engineering, Soka University, Tokyo 192-8577, Japan.; Glycan & Life Systems Integration Center (GaLSIC), Soka University, Tokyo 192-8577, Japan. |
| Abstrakt: |
Glycan biosynthesis simulation research has progressed remarkably since 1997, when the first mathematical model for N -glycan biosynthesis was proposed. An O -glycan model has also been developed to predict O -glycan biosynthesis pathways in both forward and reverse directions. In this work, we started with a set of O -glycan profiles of CHO cells transiently transfected with various combinations of glycosyltransferases. The aim was to develop a model that encapsulated all the enzymes in the CHO transfected cell lines. Due to computational power restrictions, we were forced to focus on a smaller set of glycan profiles, where we were able to propose an optimized set of kinetics parameters for each enzyme in the model. Using this optimized model we showed that the abundance of more processed glycans could be simulated compared to observed abundance, while predicting the abundance of glycans earlier in the pathway was less accurate. The data generated show that for the accurate prediction of O -linked glycosylation, additional factors need to be incorporated into the model to better reflect the experimental conditions. |
