z-logo
open-access-imgOpen Access
A Knowledge-Based System for Display and Prediction of O-Glycosylation Network Behaviour in Response to Enzyme Knockouts
Author(s) -
Andrew G. McDonald,
Keith F. Tipton,
Gavin P. Davey
Publication year - 2016
Publication title -
plos computational biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.628
H-Index - 182
eISSN - 1553-7358
pISSN - 1553-734X
DOI - 10.1371/journal.pcbi.1004844
Subject(s) - glycosylation , glycan , glycomics , in silico , gene knockout , computational biology , chemistry , glycosyltransferase , enzyme , biochemistry , galactosyltransferase , biology , gene , glycoprotein
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 graph-theoretic 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, β -1,4-galactosyltransferase ( β 4Gal-T4), four glycosyltransferases and one sulfotransferase, play the dominant role in determining O -glycan heterogeneity. In the absence of β 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.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom