title: A computational framework for the automated construction of glycosylation reaction networks.
abstract: Glycosylation is among the most common and complex post-translational modifications identified to date. It proceeds through the catalytic action of multiple enzyme families that include the glycosyltransferases that add monosaccharides to growing glycans, and glycosidases which remove sugar residues to trim glycans. The expression level and specificity of these enzymes, in part, regulate the glycan distribution or glycome of specific cell/tissue systems. Currently, there is no systematic method to describe the enzymes and cellular reaction networks that catalyze glycosylation. To address this limitation, we present a streamlined machine-readable definition for the glycosylating enzymes and additional methodologies to construct and analyze glycosylation reaction networks. In this computational framework, the enzyme class is systematically designed to store detailed specificity data such as enzymatic functional group, linkage and substrate specificity. The new classes and their associated functions enable both single-reaction inference and automated full network reconstruction, when given a list of reactants and/or products along with the enzymes present in the system. In addition, graph theory is used to support functions that map the connectivity between two or more species in a network, and that generate subset models to identify rate-limiting steps regulating glycan biosynthesis. Finally, this framework allows the synthesis of biochemical reaction networks using mass spectrometry (MS) data. The features described above are illustrated using three case studies that examine: i) O-linked glycan biosynthesis during the construction of functional selectin-ligands; ii) automated N-linked glycosylation pathway construction; and iii) the handling and analysis of glycomics based MS data. Overall, the new computational framework enables automated glycosylation network model construction and analysis by integrating knowledge of glycan structure and enzyme biochemistry. All the implemented features are provided as part of the Glycosylation Network Analysis Toolbox (GNAT), an open-source, platform-independent, MATLAB based toolbox for studies of Systems Glycobiology.
authors: Department of Chemical and Biological Engineering, and The NY State Center for Excellence in Bioinformatics and Life Sciences, State University of New York, Buffalo, New York, United States of America.
authors: Gang
authors: G
authors: Liu
authors: Department of Chemical and Biological Engineering, and The NY State Center for Excellence in Bioinformatics and Life Sciences, State University of New York, Buffalo, New York, United States of America.
authors: Sriram
authors: S
authors: Neelamegham
mesh_terms: D002240:Carbohydrate Sequence; D054794:Glycomics / Q000379:methods* / Q000706:statistics & numerical data; D006026:Glycoside Hydrolases / Q000737:chemistry* / Q000378:metabolism; D006031:Glycosylation; D016695:Glycosyltransferases / Q000737:chemistry* / Q000378:metabolism; D013058:Mass Spectrometry / Q000706:statistics & numerical data; D053858:Metabolic Networks and Pathways; D008969:Molecular Sequence Data; D011134:Polysaccharides / Q000096:biosynthesis / Q000737:chemistry*; D012984:Software; D013379:Substrate Specificity
chemical_list: D011134:Polysaccharides; D016695:Glycosyltransferases; D006026:Glycoside Hydrolases