Project Report

Introduction/Background Biopharmaceuticals represent the largest growing class of therapeutics with a US market of approximately $50 billion in 2009 and an expected steady increase in future sales (1). Many biopharmaceuticals, such as the therapeutic monoclonal antibodies (Mabs) are produced as recombinant proteins from Chinese hamster ovary (CHO) cells that are cultivated in bioreactors. These therapeutic proteins are effective only when their product quality attributes (bioactivity, potency, purity, etc.) lie within a specific range of values. Of the many factors that affect the quality and bioactivity of these proteins, arguably the most important is glycosylation, a post-translational modification in which a carbohydrate chain, termed a glycan, is added to the protein. To function as intended, most therapeutic protein treatments validated for human use must have a precise distribution of glycans (i.e., precise percentages of glycans with specific sugar monomers such as galactose, sialic acid, or fucose). Unlike other cellular processes such as DNA replication and protein production, however, glycosylation has no master template, and, as a result, glycan formation and attachment are subject to variability and are highly heterogeneous and often non-uniform. As a method to ensure consistent MAb quality, researchers at the A*STAR Bioprocessing Technology Institute developed new vectors of expression. In preliminary studies, the MAb produced by 5 top expressing clones transfected with the new expression vector exhibited a uniform glycan distribution. These results are promising, however more clones and another MAb must be tested for confirmation. Project Objective Characterize and compare the glycan distribution of 18 clones from two 2 different recombinant MAb (IgG84 & Anti-Her2) produced by the two transfection strategies. Work and Achievement The glycan distribution of 18 clones from two different recombinant MAbs (IgG84 and Anti-Her2) produced with two different transfection strategies were characterized in duplicate and compared. The method for glycan analysis used PNGase F to first cleave the glycans from the MAb. The free glycans were then purified, permethylated and analyzed via MALDI TOF Mass Spectrometry (MS). A OneWay ANOVA test was then performed on the clone data of 20 different glycan structures that are typically present in recombinant MAbs. Results from the study was not conclusive and work is on-going at the Bioprocess Technology Institute to characterize and compare the glycan distribution of additional MAbs produced with the two transfection strategies. In addition to assessing the vector’s ability to produce a uniform glycan distribution between clones, another major objective of the EAPSI project was to master various glycosylation characterization methods. I learned methods for glycan cleavage and permethylation as well as 2-AB labeling and HPAEC-PAD analysis, which does not require glycan derivatization. Other methods I learned include high throughput sialic acid concentration quantification and sugar nucleotide extraction and analysis with capillary electrophoresis. I also developed a Matlab script to automate the analysis of glycan data acquired by MALDI-TOF MS. Linking EAPSI Project with Current Thesis Research The primary goal of my thesis research at the University of Delaware is to develop-and validate experimentally- a strategy for on-line control of protein glycosylation during monoclonal antibody production through the use of a novel multi-loop, on-line control system incorporating a multi-scale glycosylation process model integrated with a comprehensive multi-rate bioreactor measurement system. Before such a control strategy can be implemented, however, it is important to have a method in place to characterize glycan distribution of the monoclonal antibody products. However, most methods used to determine glycan distribution include liquid chromatography (LC), mass spectrometry (MS), or a combination of both and require extensive and complex sample preparation. Without glycosylation experts at my home university to consult with, developing accurate and reliable glycosylation assays for quantifying protein glycosylation would be extremely challenging. After mastering such glycosylation characterization methods as permethylation and 2-AB labeling this summer as part of the EAPSI program, I have now been able to establish and apply these methods back in my home laboratory to analyze the glycan distribution of monoclonal antibody products that I generate as part of my thesis research. Not only has the program been beneficial to my thesis research, but a fellow graduate student at the University of Delaware has also begun glycosylation research and I have been teaching him what I learned about glycosylation and training him on the protocols for the various methods of glycomics analysis. The hope is to establish a proficiency in glycosylation analysis at the University of Delaware which did not exist prior to my experience in Singapore as an EAPSI fellow.

National Science Foundation (NSF)
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Carter Kimsey
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Stamand Melissa M
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