RT Journal Article
SR Electronic
T1 Glycosylation flux analysis reveals dynamic changes of intracellular glycosylation flux distribution in Chinese hamster ovary fed-batch cultures
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 121517
DO 10.1101/121517
A1 Sandro Hutter
A1 Thomas K. Villiger
A1 David Brühlmann
A1 Matthieu Stettler
A1 Hervé Broly
A1 Miroslav Soos
A1 Rudiyanto Gunawan
YR 2017
UL http://biorxiv.org/content/early/2017/03/28/121517.abstract
AB N-linked glycosylation of proteins has both functional and structural significance. Importantly, the glycan structure of a therapeutic protein influences its efficacy, pharmacokinetics, pharmacodynamics and immunogenicity. In this work, we developed glycosylation flux analysis (GFA) for predicting intracellular production and consumption rates (fluxes) of glycoforms, and applied this method to CHO fed-batch monoclonal antibody (mAb) production using two different media compositions, with and without additional manganese feeding. The GFA is based on a constraint-based modelling of the glycosylation network, employing a pseudo steady state assumption. While the glycosylation fluxes in the network are balanced at each time point, the GFA allows the fluxes to vary with time by way of two scaling factors: (1) an enzyme-specific factor that captures the temporal changes among glycosylation reactions catalyzed by the same enzyme, and (2) the cell specific productivity factor that accounts for the dynamic changes in the mAb production rate. The GFA of the CHO fed-batch cultivations showed that regardless of the media composition, the fluxes of galactosylation decreased with the cultivation time in comparison to the other glycosylation reactions. Furthermore, the GFA showed that the addition of Mn, a cofactor of galactosyltransferase, has the effect of increasing the galactosylation fluxes but only during the beginning of the cultivation period. The results thus demonstrated the power of the GFA in delineating the dynamic alterations of the glycosylation fluxes by local (enzyme-specific) and global (cell specific productivity) factors.αEnzyme specific factorβSpecific productivitycConcentrationcEExtracellular concentrationfFractionKNumber of time pointsmNumber of glycoformsMWMolecular weightnNumber of reactionsSStoichiometric matrixTTitertTimeVVolumeVESecretion fluxVIIntracellular fluxVrefIReference fluxXXvViable cell densityCBMConstraint-based modellingCHOChinese hamster ovarianEREndoplasmic reticulumFBAFlux balance analysisGFAGlycosylation flux analysisIgGImmunoglobulin GMFAMetabolic flux analysisPATProcess analytical technologyQbDQuality by designUPLCUltra performance liquid chromatographyManMannosidaseGnTN-AcetylglucosaminyltransferaseFucTFucosyltransferaseGalTGalactosyltransferaseSiaTSialyltransferaseM9Man9GlcNAc2M8Man8GlcNAc2M7Man7GlcNAc2M6Man6GlcNAc2M5Man5GlcNAc2A1GlcNAcMan3GlcNAc2A2GlcNAc2Man3GlcNAc2FA1GlcNAcMan3GlcNAc2FucFA2GlcNAc2Man3GlcNAc2FucFA1G1GalGlcNAcMan3GlcNAc2FucFA2G1-1α(1-6)GalGlcNAc2Man3GlcNAc2FucFA2G2S1-2α(1 -3)GalGlcNAc2Man3GlcNAc2FucFA2G2Gal2GlcNAc2Man3GlcNAc2FucFA2G2S1-1α(1 -6)SiaGal2GlcNAc2Man3GlcNAc2FucFA2G2S1-2α(1-3)SiaGal2GlcNAc2Man3GlcNAc2Fuc