A Knowledge-Based System for Display and Prediction of O-Glycosylation Network Behaviour in Response to Enzyme Knockouts

作者:McDonald Andrew G*; Tipton Keith F; Davey Gavin P*
来源:PLoS Computational Biology, 2016, 12(4): e1004844.
DOI:10.1371/journal.pcbi.1004844

摘要

O-linked glycosylation is an important post-translational modification of mucin-type protein, changes to which are important biomarkers of cancer. For this study of the enzymes of O-glycosylation, we developed a shorthand notation for representing GalNAc-linked oligosaccharides, a method for their graphical interpretation, and a pattern-matching algorithm that generates networks of enzyme-catalysed reactions. Software for generating glycans from the enzyme activities is presented, and is also available online. The degree distributions of the resulting enzyme-reaction networks were found to be Poisson in nature. Simple graphtheoretic measures were used to characterise the resulting reaction networks. From a study of in-silico single-enzyme knockouts of each of 25 enzymes known to be involved in mucin O-glycan biosynthesis, six of them, beta-1,4-galactosyltransferase (beta 4Gal-T4), four glycosyl-transferases and one sulfotransferase, play the dominant role in determining O-glycan heterogeneity. In the absence of beta 4Gal-T4, all Lewis X, sialyl-Lewis X, Lewis Y and Sd(a)/Cad glycoforms were eliminated, in contrast to knockouts of the N-acetylglucosaminyltransferases, which did not affect the relative abundances of O-glycans expressing these epitopes. A set of 244 experimentally determined mucin-type O-glycans obtained from the literature was used to validate the method, which was able to predict up to 98% of the most common structures obtained from human and engineered CHO cell glycoforms.

  • 出版日期2016-4