In the biopharmaceutical industry, mammalian cell culture systems, especially Chinese hamster ovary (CHO) cells, are predominantly used for the production of therapeutic glycoproteins. Glycosylation is a critical protein quality attribute that can modulate the efficacy of a commercial therapeutic glycoprotein. Obtaining a consistent glycoform profile in production is desired due to regulatory concerns because a molecule can be defined by its carbohydrate structures. An optimal profile may involve a spectrum of product glycans that confers a desired therapeutic efficacy, or a homogeneous glycoform profile that can be systemically screened for. Studies have shown some degree of protein glycosylation control in mammalian cell culture, through cellular, media, and process effects. Studies upon our own bioprocesses to produce fusion proteins and monoclonal antibodies have shown an intricate relationship between these variables and the resulting protein quality. Glycosylation optimization will improve therapeutic efficacy and is an ongoing goal for researchers in academia and industry alike. This review will focus on the advancements made in glycosylation control in a manufacturing process, as well as the next steps in understanding and controlling protein glycosylation.

N-glycosylation plays a key role in the quality of many therapeutic glycoprotein biologics. The biosynthesis reactions of these oligosaccharides are a type of network in which a relatively small number of enzymes give rise to a large number of N-glycans as the reaction intermediates and terminal products. Multiple glycans appear on the glycoprotein molecules and give rise to a heterogeneous product. Controlling the glycan distribution is critical to the quality control of the product. Understanding N-glycan biosynthesis and the etiology of microheterogeneity would provide physiological insights, and facilitate cellular engineering to enhance glycoprotein quality. We developed a mathematical model of glycan biosynthesis in the Golgi and analyzed the various reaction variables on the resulting glycan distribution. The Golgi model was modeled as four compartments in series. The mechanism of protein transport across the Golgi is still controversial. From the viewpoint of their holding time distribution characteristics, the two main hypothesized mechanisms, vesicular transport and Golgi maturation models, resemble four continuous mixing-tanks (4CSTR) and four plug-flow reactors (4PFR) in series, respectively. The two hypotheses were modeled accordingly and compared. The intrinsic reaction kinetics were first evaluated using a batch (or single PFR) reactor. A sufficient holding time is needed to produce terminally-processed glycans. Altering enzyme concentrations has a complex effect on the final glycan distribution, as the changes often affect many reaction steps in the network. Comparison of the glycan profiles predicted by the 4CSTR and 4PFR models points to the 4PFR system as more likely to be the true mechanism. To assess whether glycan heterogeneity can be eliminated in the biosynthesis of biotherapeutics the 4PFR model was further used to assess whether a homogeneous glycan profile can be created through metabolic engineering. We demonstrate by the spatial localization of enzymes to specific compartments all terminally processed N-glycans can be synthesized as homogeneous products with a sufficient holding time in the Golgi compartments. The model developed may serve as a guide to future engineering of glycoproteins.

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Protein glycosylation is a post-translational modification of paramount importance for the function, immunogenicity, and efficacy of recombinant glycoprotein therapeutics. Within the repertoire of post-translational modifications, glycosylation stands out as having the most significant proven role towards affecting pharmacokinetics and protein physiochemical characteristics. In mammalian cell culture, the understanding and controllability of the glycosylation metabolic pathway has achieved numerous successes. However, there is still much that we do not know about the regulation of the pathway. One of the frequent conclusions regarding protein glycosylation control is that it needs to be studied on a case-by-case basis since there are often conflicting results with respect to a control variable and the resulting glycosylation. In attempts to obtain a more multivariate interpretation of these potentially controlling variables, gene expression analysis and systems biology have been used to study protein glycosylation in mammalian cell culture. Gene expression analysis has provided information on how glycosylation pathway genes both respond to culture environmental cues, and potentially facilitate changes in the final glycoform profile. Systems biology has allowed researchers to model the pathway as well-defined, inter-connected systems, allowing for the in silico testing of pathway parameters that would be difficult to test experimentally. Both approaches have facilitated a macroscopic and microscopic perspective on protein glycosylation control. These tools have and will continue to enhance our understanding and capability of producing optimal glycoform profiles on a consistent basis.

Glycosylation has profound effects on the quality of recombinant proteins produced in mammalian cells. The biosynthetic pathways of N-linked glycans on glycoproteins involves a relatively small number of enzymes and nucleotide sugars. Many of these glycoconjugate enzymes can utilize multiple N-glycans as substrates, thus generating a large number of glycan intermediates, and making the biosynthetic pathway resemble a network with diverging and converging paths. The N-glycans on secreted glycoprotein molecules include not only terminal glycans, but also pathway intermediates. To better assess the glycan distribution and the potential route of their synthesis, we created GlycoVis, a visualization program that displays the distribution and the potential reaction paths leading to each N-glycan on the reaction network. The substrate specificities of the enzymes involved were organized into a relationship matrix. With the input of glycan distribution data, the program outputs a reaction pathway map which labels the relative abundance levels of different glycans with different colors. The program also traces all possible reaction paths leading to each glycan and identifies each pathway on the map. Glycoform distribution of Chinese Hamster Ovary cell-derived tissue plasminogen activator (TPA), and human and mouse IgG were used as illustrations for the application of GlycoVis. In addition, the intracellular and secreted IgG from an NS0 producer cell line were isolated, and their glycoform profiles were displayed using GlycoVis for comparison. This visualization tool facilitates the analysis of potential reaction paths utilized under different physiological or culture conditions, and may provide insight on the potential targets for metabolic engineering.