Understanding and Controlling Sialylation in a CHO Fc-Fusion Process

Abstract

A Chinese hamster ovary (CHO) bioprocess, where the product is a sialylated Fc-fusion protein, was operated at pilot and manufacturing scale and significant variation of sialylation level was observed. In order to more tightly control glycosylation profiles, we sought to identify the cause of variability. Untargeted metabolomics and transcriptomics methods were applied to select samples from the large scale runs. Lower sialylation was correlated with elevated mannose levels, a shift in glucose metabolism, and increased oxidative stress response. Using a 5-L scale model operated with a reduced dissolved oxygen set point, we were able to reproduce the phenotypic profiles observed at manufacturing scale including lower sialylation, higher lactate and lower ammonia levels. Targeted transcriptomics and metabolomics confirmed that reduced oxygen levels resulted in increased mannose levels, a shift towards glycolysis, and increased oxidative stress response similar to the manufacturing scale. Finally, we propose a biological mechanism linking large scale operation and sialylation variation. Oxidative stress results from gas transfer limitations at large scale and the presence of oxygen dead-zones inducing upregulation of glycolysis and mannose biosynthesis, and downregulation of hexosamine biosynthesis and acetyl-CoA formation. The lower flux through the hexosamine pathway and reduced intracellular pools of acetyl-CoA led to reduced formation of N-acetylglucosamine and N-acetylneuraminic acid, both key building blocks of N-glycan structures. This study reports for the first time a link between oxidative stress and mammalian protein sialyation. In this study, process, analytical, metabolomic, and transcriptomic data at manufacturing, pilot, and laboratory scales were taken together to develop a systems level understanding of the process and identify oxygen limitation as the root cause of glycosylation variability.

Fig 1. Large Scale Cell Culture Performance.

Cell culture performance attributes titer (A) and NANA level (B) are shown over culture duration for 45 bioreactor runs at 50-L, 500-L, 900-L and 5000-L scale. Data was normalized to range from 0 to 1. Median is indicated by the horizontal line, interquartile range by the height of the box, and the full range by the vertical line. Outliers are shown as dots.

Fig 2. Links between glucose metabolism and NANA.

Untargeted metabolomics & glucose consumption calculations were performed on samples ranging from 50-L to 5000-L scale. A. Relative mannose levels, a metabolite not provided in the cell culture media, were compared across runs with normal (red) and low (blue) NANA levels. Error bars represent the mannose range associated with each time point. B. Maximum specific glucose consumption was calculated for each run and found to be significantly inversely correlated to day 10 NANA (p<0.001). C. Residuals of maximum specific glucose consumption were calculated for each run and found to be significantly inversely correlated to day 10 NANA (p<0.0001).

Fig 3. Targeted transcriptomics show upregulation of key oxidative stress and glucose metabolism genes at low NANA levels.

PCR arrays were used for targeted transcriptomics of CHO oxidative stress pathway (A) and glucose metabolism (B). A P-value was found for each gene corresponding to the null hypothesis that no correlation existed between expression level and Relative NANA. Genes were considered significantly correlated at p<0.05. The log fold change in expression level between samples is indicated by color, where red indicates higher expression and blue indicates lower expression relative to the sample with the highest NANA level. The maximum change in expression is 5.5 log-fold.

Fig 4. Reduced DO level impacts 5-L cell culture performance and sialylation.

5-L bioreactors were operated under control (50% DO, blue circle) and low DO (20% grey triangle, 15% yellow square, 10% red diamond, and 10% shifted to 20% DO on day 5 green diamond) conditions and compared to 5000-L operation (50% DO, orange circle). Viability (A), lactate (B) and ammonia (C) profiles were established for up to 14 days of bioreactor operation. D. Day 10 titer, day 12 NANA and NANA slope values were normalized to the 5-L control (50% DO) condition. Replicate bioreactors were used for control (n = 6), 5000-L (n = 8) and 15% DO (n = 4) conditions. Statistical differences were determined using a student t-test, * indicates p<0.05 and ** indicates p<0.01.

Fig 5. Reduced DO level impacts 5-L cell culture gene expression.

5-L bioreactors were operated under control (50% DO, blue) and low DO (20% gray, 15% yellow, and 10% shifted to 20% DO on day 5 green) conditions. Gene expression, relative to the control (50% DO) is shown for oxidative stress (A) and glucose metabolism (B) markers. Replicate bioreactors were used for control (n = 3), and 15% DO (n = 2) conditions. Statistical differences were determined using a student t-test, * indicates p<0.05 and ** indicates p<0.01.

Fig 6. N-Glycan Structures.

The N-glycan assay method quantifies the percent distribution of N-glycan species. Five key structures were quantified in samples generated from 5-L bioreactors were operated under normal (50%) and low (15%) DO conditions. G0F, G1F and G2F are unsialylated, S1G1F is monosialylated, and S2G2F is disialylated.

Fig 7. Proposed biological mechanism for manufacturing and low oxygen laboratory scale bioreactors.

Reduced oxygen levels trigger an oxidative stress response and shift in glucose metabolism, resulting in upregulation of glycolysis and mannose synthesis, and downregulation of the hexosamine pathway and acetyl-CoA formation. This metabolic shift results in reduced GlcNAc levels, as well as levels of metabolites formed from GlcNAc including UDP-GlcNAc and CMP-NANA, triggering a reduction in terminal sialylation of N-glycans. Metabolite or gene expression levels directly measures as increased (green arrows) or decreased (red arrows) are shown. Abbreviations are as follows: CMP, cytidine monophosphate; CMP-SAT, CMP sialic acid transporter; CoA, coenzyme A; CTP, cytidine triphosphate; Frc-6-P, fructose-6-phosphate; Glc-6-P, glucose-6-phosphate; GlcN, glucosamine; GlcNAc, N-acetyl glucosamine; Gln, glutamine; Glu, glutamate; GTP, guanosine triphosphate; Man, mannose; Man-6-P, mannose-6-phosphate; ManNAc, N-acetyl mannosamine; MK, mannosekinase; NANA, N-acetylneuraminic acid; NH₃, ammonia; PDH, pyruvate dehydrogenase; PDK, pyruvate dehydrogenase kinase; PFK, phosphofructokinase; PMI, mannose phosphate isomerase; UDP, uridine diphosphate; UMP, uridine monophosphate; UTP, uridine triphosphate.