6 research outputs found
Centralized Modularity of N-Linked Glycosylation Pathways in Mammalian Cells
Glycosylation is a highly complex process to produce a diverse repertoire of
cellular glycans that are attached to proteins and lipids. Glycans are involved
in fundamental biological processes, including protein folding and clearance,
cell proliferation and apoptosis, development, immune responses, and
pathogenesis. One of the major types of glycans, N-linked glycans, is formed by
sequential attachments of monosaccharides to proteins by a limited number of
enzymes. Many of these enzymes can accept multiple N-linked glycans as
substrates, thereby generating a large number of glycan intermediates and their
intermingled pathways. Motivated by the quantitative methods developed in
complex network research, we investigated the large-scale organization of such
N-linked glycosylation pathways in mammalian cells. The N-linked glycosylation
pathways are extremely modular, and are composed of cohesive topological
modules that directly branch from a common upstream pathway of glycan
synthesis. This unique structural property allows the glycan production between
modules to be controlled by the upstream region. Although the enzymes act on
multiple glycan substrates, indicating cross-talk between modules, the impact
of the cross-talk on the module-specific enhancement of glycan synthesis may be
confined within a moderate range by transcription-level control. The findings
of the present study provide experimentally-testable predictions for
glycosylation processes, and may be applicable to therapeutic glycoprotein
engineering
Inclusion of maintenance energy improves the intracellular flux predictions of CHO
Chinese hamster ovary (CHO) cells are the leading platform for the production of biopharmaceuticals with human-like glycosylation. The standard practice for cell line generation relies on trial and error approaches such as adaptive evolution and high-throughput screening, which typically take several months. Metabolic modeling could aid in designing better producer cell lines and thus shorten development times. The genome-scale metabolic model (GSMM) of CHO can accurately predict growth rates. However, in order to predict rational engineering strategies it also needs to accurately predict intracellular fluxes. In this work we evaluated the agreement between the fluxes predicted by parsimonious flux balance analysis (pFBA) using the CHO GSMM and a wide range of 13C metabolic flux data from literature. While glycolytic fluxes were predicted relatively well, the fluxes of tricarboxylic acid (TCA) cycle were vastly underestimated due to too low energy demand. Inclusion of computationally estimated maintenance energy significantly improved the overall accuracy of intracellular flux predictions. Maintenance energy was therefore determined experimentally by running continuous cultures at different growth rates and evaluating their respective energy consumption. The experimentally and computationally determined maintenance energy were in good agreement. Additionally, we compared alternative objective functions (minimization of uptake rates of seven nonessential metabolites) to the biomass objective. While the predictions of the uptake rates were quite inaccurate for most objectives, the predictions of the intracellular fluxes were comparable to the biomass objective function.COMET center acib: Next Generation
Bioproduction, which is funded by BMK, BMDW,
SFG, Standortagentur Tirol, Government of Lower
Austria and Vienna Business Agency in the
framework of COMET - Competence Centers for
Excellent Technologies. The COMET-Funding
Program is managed by the Austrian Research
Promotion Agency FFG; D.S., J.S., M.W., M.H., D.
E.R. This work has also been supported by the PhD
program BioToP of the Austrian Science Fund
(FWF Project W1224)info:eu-repo/semantics/publishedVersio