A genetic model to study O-GlcNAc cycling in immortalized mouse embryonic fibroblasts.

O-GlcNAcylation is an abundant posttranslational protein modification in which the monosaccharide O-GlcNAc is added to Ser/Thr residues by O-GlcNAc transferase and removed by O-GlcNAcase. Analyses of O-GlcNAc-mediated signaling and metabolic phenomena are complicated by factors including unsatisfactory inhibitors and loss-of-function cell lines lacking identical genetic backgrounds. In this work, we generated immortalized WT, Oga knockout, and Ogt floxed allele (Ogt floxed) mouse embryonic fibroblast (MEF) cell lines with similar genetic backgrounds. These lines will facilitate experiments and serve as a platform to study O-GlcNAc cycling in mammals. As a test paradigm, we used the immortalized MEF lines to investigate how changes in O-GlcNAcylation affected pathological phosphorylation of the tau protein. The activity of glycogen synthase kinase 3ß (GSK3ß), a kinase that phosphorylates tau, decreases when expressed in Oga knockout MEFs compared with WT cells. Phosphorylation at Thr231 in recombinant, tauopathy-associated tau with a proline-to-leucine mutation at position 301 (P301L) was altered when expressed in MEFs with altered O-GlcNAc cycling. In aggregate, our data support that O-GlcNAc cycling indirectly affects tau phosphorylation at Thr231, but tau phosphorylation was highly variable, even in genetically stable, immortalized MEF cells. The variable nature of tau phosphorylation observed here supports the need to use cells akin to those generated here with genetically defined lesions and similar backgrounds to study complex biological processes.

Identification of manipulated variables for a glycosylation control strategy.

N-linked glycan distribution affects important end-use characteristics such as the bioactivity and efficacy of many therapeutic proteins, (including monoclonal antibodies), in vivo. Yet, obtaining desired glycan distributions consistently during batch-to-batch production can be challenging for biopharmaceutical manufacturers. While an appropriately implemented on-line glycosylation control strategy during production can help to ensure a consistent glycan distribution, to date no such strategies have been reported. Our goal is to develop and validate a comprehensive strategy for effective on-line control of glycosylation, the successful achievement of which requires first identifying appropriate manipulated variables that can be used to direct the glycan distribution to a desired state. While various culture conditions such as bioreactor process variables, media type, and media supplements have been shown to affect the glycan distribution, in this study we focus on the latter. Specifically, we implemented a statistically designed series of experiments to determine the significant main effects (as well as interaction effects) of media supplementation with manganese, galactose, ammonia and found that each had significant effects on certain glycans. We also include data indicating the glycosylation enzyme gene transcript levels as well as the intracellular nucleotide sugar concentrations in the presence of the media supplements to provide insight into the intracellular conditions that may be contributing to the changes in glycan distribution. The acquired experimental data sets were then used to identify which glycans can be controlled by the media supplements and to what degree. We determined that MnCl2 can be used as a manipulated variable to increase the relative abundance of M51 and decrease FA2 simultaneously, and galactose can be used as a manipulated variable to increase the relative abundance of FA2G1 and decrease FA2 and A2 simultaneously.

Identifying a robust design space for glycosylation during monoclonal antibody production.

Glycan distribution has been identified as a "critical quality attribute" for many biopharmaceutical products, including monoclonal antibodies. Consequently, determining quantitatively how process variables affect glycan distribution is important during process development to control antibody glycosylation. In this work, we assess the effect of six bioreactor process variables on the glycan distribution of an IgG1 produced in CHO cells. Our analysis established that glucose and glutamine media concentration, temperature, pH, agitation rate, and dissolved oxygen (DO) had small but significant effects on the relative percentage of various glycans. In addition, we assessed glycosylation enzyme transcript levels and intracellular sugar nucleotide concentrations within the CHO cells to provide a biological explanation for the observed effects on glycan distributions. From these results we identified a robust operating region, or design space, in which the IgG1 could be produced with a consistent glycan distribution. Since our results indicate that perturbations to bioreactor process variables will cause only small (even if significant) changes to the relative percentage of various glycans (<±1.5%)-changes that are too small to affect the bioactivity and efficacy of this IgG1 significantly-it follows that the glycan distribution obtained will be consistent even with relatively large variations in bioreactor process variables. However, for therapeutic proteins where bioactivity and efficacy are affected by small changes to the relative percentage of glycans, the same analysis would identify the manipulated variables capable of changing glycan distribution, and hence can be used to implement a glycosylation control strategy. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1149-1162, 2016.

Controllability analysis of protein glycosylation in CHO cells.

To function as intended in vivo, a majority of biopharmaceuticals require specific glycan distributions. However, achieving a precise glycan distribution during manufacturing can be challenging because glycosylation is a non-template driven cellular process, with the potential for significant uncontrolled variability in glycan distributions. As important as the glycan distribution is to the end-use performance of biopharmaceuticals, to date, no strategy exists for controlling glycosylation on-line. However, before expending the significant amount of effort and expense required to develop and implement on-line control strategies to address the problem of glycosylation heterogeneity, it is imperative to assess first the extent to which the very complex process of glycosylation is controllable, thereby establishing what is theoretically achievable prior to any experimental attempts. In this work, we present a novel methodology for assessing the output controllability of glycosylation, a prototypical example of an extremely high-dimensional and very non-linear system. We first discuss a method for obtaining the process gain matrix for glycosylation that involves performing model simulations and data analysis systematically and judiciously according to a statistical design of experiments (DOE) scheme and then employing Analysis of Variance (ANOVA) to determine the elements of process gain matrix from the resulting simulation data. We then discuss how to use the resulting high-dimensional gain matrix to assess controllability. The utility of this method is demonstrated with a practical example where we assess the controllability of various classes of glycans and of specific glycoforms that are typically found in recombinant biologics produced with Chinese Hamster Ovary (CHO) cells. In addition to providing useful insight into the extent to which on-line glycosylation control is achievable in actual manufacturing processes, the results also have important implications for genetically engineering cell lines design for enhanced glycosylation controllability.