RESUMO
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.
Assuntos
Polissacarídeos , Animais , Células CHO , Simulação por Computador , Cricetinae , Cricetulus , Glicosilação , Polissacarídeos/metabolismoRESUMO
Laser microdissection-assisted lectin microarray has been used to obtain quantitative and qualitative information on glycans on proteins expressed in microscopic regions of formalin-fixed paraffin-embedded tissue sections. For the effective visualization of this "tissue glycome mapping" data, a novel online tool, LM-GlycomeAtlas (https://glycosmos.org/lm_glycomeatlas/index), was launched in the freely available glycoscience portal, the GlyCosmos Portal (https://glycosmos.org). In LM-GlycomeAtlas Version 1.0, nine tissues from normal mice were used to provide one data set of glycomic profiles. Here we introduce an updated version of LM-GlycomeAtlas, which includes more spatial information. We designed it to deposit multiple data sets of glycomic profiles with high-resolution histological images, which included staining images with multiple lectins on the array. The additionally implemented interfaces allow users to display multiple histological images of interest (e.g., diseased and normal mice), thereby facilitating the evaluation of tissue glycomic profiling and glyco-pathological analysis. Using these updated interfaces, 451 glycomic profiling data and 42 histological images obtained from 14 tissues of normal and diseased mice were successfully visualized. By easy integration with other tools for glycoproteomic data and protein glycosylation machinery, LM-GlycomeAtlas will be one of the most valuable open resources that contribute to both glycoscience and proteomics communities.
Assuntos
Glicômica , Lectinas , Animais , Histocitoquímica , Camundongos , Análise em Microsséries , Polissacarídeos , ProteômicaRESUMO
Systems glycobiology aims to provide models and analysis tools that account for the biosynthesis, regulation, and interactions with glycoconjugates. To facilitate these methods, there is a need for a clear glycan representation accessible to both computers and humans. Linear Code, a linearized and readily parsable glycan structure representation, is such a language. For this reason, Linear Code was adapted to represent reaction rules, but the syntax has drifted from its original description to accommodate new and originally unforeseen challenges. Here, we delineate the consensuses and inconsistencies that have arisen through this adaptation. We recommend options for a consensus-based extension of Linear Code that can be used for reaction rule specification going forward. Through this extension and specification of Linear Code to reaction rules, we aim to minimize inconsistent symbology thereby making glycan database queries easier. With a clear guide for generating reaction rule descriptions, glycan synthesis models will be more interoperable and reproducible thereby moving glycoinformatics closer to compliance with FAIR standards. Here, we present Linear Code for Reaction Rules (LiCoRR), version 1.0, an unambiguous representation for describing glycosylation reactions in both literature and code.