title: A Markov chain model for N-linked protein glycosylation--towards a low-parameter tool for model-driven glycoengineering.
abstract: Glycosylation is a critical quality attribute of most recombinant biotherapeutics. Consequently, drug development requires careful control of glycoforms to meet bioactivity and biosafety requirements. However, glycoengineering can be extraordinarily difficult given the complex reaction networks underlying glycosylation and the vast number of different glycans that can be synthesized in a host cell. Computational modeling offers an intriguing option to rationally guide glycoengineering, but the high parametric demands of current modeling approaches pose challenges to their application. Here we present a novel low-parameter approach to describe glycosylation using flux-balance and Markov chain modeling. The model recapitulates the biological complexity of glycosylation, but does not require user-provided kinetic information. We use this method to predict and experimentally validate glycoprofiles on EPO, IgG as well as the endogenous secretome following glycosyltransferase knock-out in different Chinese hamster ovary (CHO) cell lines. Our approach offers a flexible and user-friendly platform that can serve as a basis for powerful computational engineering efforts in mammalian cell factories for biopharmaceutical production.
authors.affiliation: Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, United States; The Novo Nordisk Foundation Center for Biosustainability at the University of California, San Diego, La Jolla, CA 92093, United States.
authors.forename: Philipp N
authors.initials: PN
authors.lastname: Spahn
authors.affiliation: The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Hørsholm, Denmark.
authors.forename: Anders H
authors.initials: AH
authors.lastname: Hansen
authors.affiliation: The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Hørsholm, Denmark.
authors.forename: Henning G
authors.initials: HG
authors.lastname: Hansen
authors.affiliation: The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Hørsholm, Denmark.
authors.forename: Johnny
authors.initials: J
authors.lastname: Arnsdorf
authors.affiliation: The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Hørsholm, Denmark.
authors.forename: Helene F
authors.initials: HF
authors.lastname: Kildegaard
authors.affiliation: Department of Pediatrics, University of California, San Diego, School of Medicine, La Jolla, CA 92093, United States; The Novo Nordisk Foundation Center for Biosustainability at the University of California, San Diego, La Jolla, CA 92093, United States. Electronic address: nlewisres@ucsd.edu.
authors.forename: Nathan E
authors.initials: NE
authors.lastname: Lewis
mesh_terms: D000818:Animals; D016466:CHO Cells; D003198:Computer Simulation; D003412:Cricetulus; D006023:Glycoproteins / Q000737:chemistry / Q000235:genetics / Q000378:metabolism*; D006031:Glycosylation; D008390:Markov Chains; D060847:Metabolic Engineering / Q000379:methods*; D064688:Metabolic Flux Analysis / Q000379:methods*; D008954:Models, Biological; D015233:Models, Statistical; D011134:Polysaccharides / Q000737:chemistry / Q000235:genetics / Q000378:metabolism*
chemical_list: D006023:Glycoproteins; D011134:Polysaccharides
keywords: Flux-balance analysis; Glycoengineering; Glycosylation; Markov chains