Integrating real-time OUR monitoring with adaptive feeding for enhanced antibody production

Abstract

Background

Fed-batch culture is a well-established and widely adopted platform for industrial antibody production using Chinese Hamster Ovary (CHO) cells. However, conventional fixed feeding strategies often fall short in meeting the dynamically changing nutrient demands of cells, leading to metabolic imbalance and suboptimal productivity. Oxygen Uptake Rate (OUR), as a real-time indicator of cellular respiratory activity, is tightly coupled to nutrient metabolism and holds strong potential for guiding adaptive, demand-driven feeding strategies.

Methods

To understand the decline in specific productivity (Q_P) during the late stationary phase (LSP) under a conventional reference feeding (RF) strategy, we examined whether it stemmed from cell-intrinsic metabolic changes or from environmental stressors such as nutrient imbalance, by-product accumulation, and osmotic pressure. Based on these insights, we developed an OUR-based continuous feeding (OBCF) strategy and benchmarked its performance against the RF strategy. Mechanistic understanding was elucidated through metabolic flux and transcriptional analyses.

Results

The RF strategy resulted in a mismatch between nutrient supply and cellular demand during LSP, triggering osmotic stress and limiting antibody expression. In contrast, the OBCF strategy dynamically aligned nutrient delivery with cellular respiration, thereby mitigating osmotic stress and reshaping intracellular metabolism. Notably, OBCF enhanced pyruvate utilization and TCA cycle activity, promoted amino acid catabolism, and suppressed by-product accumulation. These metabolic improvements led to a 52% increase in specific productivity (Q_P) and a 32% increase in total antibody yield during LSP, along with reduced batch-to-batch variability.

Graphical abstract

Keywords

Oxygen uptake rate (OUR) / Fed-batch culture / Chinese hamster ovary (CHO) cells / Process analytical technologies (PAT) / Continuous feeding strategy

References

[1] Bethune Q, Harrington C, Mulukutla B (2021) Lactate control enhances growth advantage in fed-batch cultures of metabolically engineered CHO cells with reduced novel growth-inhibitory compound formation. Authorea Preprints. https://doi.org/10.22541/AU.161100207.71294164/V1

[2] Casablancas A, Gámez X, Lecina M, Solà C, Cairó JJ, Gòdia F. Comparison of control strategies for fed-batch culture of hybridoma cells based on on-line monitoring of oxygen uptake rate, optical cell density and glucose concentration. J Chem Technol Biotechnol, 2013, 88: 1680-1689.

[3] Domján J, Fricska A, Madarász L, Gyürkés M, Köte Á, Farkas A, Vass P, Fehér C, Horváth B, Könczöl K, Pataki H, Nagy ZK, Marosi GJ, Hirsch E. Raman-based dynamic feeding strategies using real-time glucose concentration monitoring system during adalimumab producing CHO cell cultivation. Biotechnol Prog, 2020, 36: e3052.

[4] Gagnon M, Hiller G, Luan Y, Kittredge A, DeFelice J, Drapeau D. High-end pH-controlled delivery of glucose effectively suppresses lactate accumulation in CHO fed-batch cultures. Biotech Bioeng, 2011, 108: 1328-1337.

[5] Gálvez J, Lecina M, Solà C, Cairó JJ, Gòdia F. Optimization of HEK-293S cell cultures for the production of adenoviral vectors in bioreactors using on-line OUR measurements. J Biotechnol, 2012, 157: 214-222.

[6] Gambhir A, Korke R, Lee J, Fu P-C, Europa A, Hu W-S. Analysis of cellular metabolism of hybridoma cells at distinct physiological states. J Biosci Bioeng, 2003, 95: 317-327.

[7] Gupta SK, Sharma A, Kushwaha H, Shukla P. Over-expression of a codon optimized yeast cytosolic pyruvate carboxylase (PYC2) in CHO cells for an augmented lactate metabolism. Front Pharmacol, 2017, 8: 463.

[8] Ha TK, Kim D, Kim CL, Grav LM, Lee GM. Factors affecting the quality of therapeutic proteins in recombinant Chinese hamster ovary cell culture. Biotechnol Adv, 2022, 54: 107831.

[9] Hiller GW, Ovalle AM, Gagnon MP, Curran ML, Wang W. Cell-controlled hybrid perfusion fed-batch CHO cell process provides significant productivity improvement over conventional fed-batch cultures. Biotechnol Bioeng, 2017, 114: 1438-1447.

[10] Kim SH, Lee GM. Functional expression of human pyruvate carboxylase for reduced lactic acid formation of Chinese hamster ovary cells (DG44). Appl Microbiol Biotechnol, 2007, 76: 659-665.

[11] Li J, Wong CL, Vijayasankaran N, Hudson T, Amanullah A. Feeding lactate for CHO cell culture processes: impact on culture metabolism and performance. Biotechnol Bioeng, 2012, 109: 1173-1186.

[12] Li W, Fan Z, Lin Y, Wang T-Y. Serum-free medium for recombinant protein expression in Chinese hamster ovary cells. Front Bioeng Biotechnol, 2021

[13] Lu F, Toh PC, Burnett I, Li F, Hudson T, Amanullah A, Li J. Automated dynamic fed-batch process and media optimization for high productivity cell culture process development. Biotechnol Bioeng, 2013, 110: 191-205.

[14] Martínez-Monge I, Martínez C, Decker M, Udugama IA, Marín de Mas I, Gernaey KV, Nielsen LK. Soft-sensors application for automated feeding control in high-throughput mammalian cell cultures. Biotechnol Bioeng, 2022, 119: 1077-1090.

[15] Mulukutla BC, Kale J, Kalomeris T, Jacobs M, Hiller GW. Identification and control of novel growth inhibitors in fed-batch cultures of Chinese hamster ovary cells. Biotech Bioeng, 2017, 114: 1779-1790.

[16] Nasseri SS, Ghaffari N, Braasch K, Jardon MA, Butler M, Kennard M, Gopaluni B, Piret JM. Increased CHO cell fed-batch monoclonal antibody production using the autophagy inhibitor 3-MA or gradually increasing osmolality. Biochem Eng J, 2014, 91: 37-45.

[17] Romanova N, Schmitz J, Strakeljahn M, Grünberger A, Bahnemann J, Noll T. Single-cell analysis of CHO cells reveals clonal heterogeneity in hyperosmolality-induced stress response. Cells, 2022, 11: 1763.

[18] Synoground BF, McGraw CE, Elliott KS, Leuze C, Roth JR, Harcum SW, Sandoval NR. Transient ammonia stress on Chinese hamster ovary (CHO) cells yield alterations to alanine metabolism and IgG glycosylation profiles. Biotechnol J, 2021, 16: 2100098.

[19] Templeton N, Dean J, Reddy P, Young JD. Peak antibody production is associated with increased oxidative metabolism in an industrially relevant fed-batch CHO cell culture. Biotech Bioeng, 2013, 110: 2013-2024.

[20] Townsend DR, Towers DM, Lavinder JJ, Ippolito GC. Innovations and trends in antibody repertoire analysis. Curr Opin Biotechnol, 2024, 86: 103082.

[21] Viña J, Sáez G, Gambini J, Gomez-Cabrera M, Borras C. Role of NAD+/NADH redox ratio in cell metabolism. Arch Biochem Biophys, 2016, 595: 176-180.

[22] Wilkens CA, Vishwanathan N, Baltes NJ, Lucero AT, Hu W-S, Gerdtzen ZP. An LDHa single allele CHO cell mutant exhibits altered metabolic state and enhanced culture performance. J Chem Technol Biotechnol, 2019, 94: 1488-1498.

[23] Xu W-J, Lin Y, Mi C-L, Pang J-Y, Wang T-Y. Progress in fed-batch culture for recombinant protein production in CHO cells. Appl Microbiol Biotechnol, 2023, 107: 1063-1075.

[24] Yu M, Hu Z, Pacis E, Vijayasankaran N, Shen A, Li F. Understanding the intracellular effect of enhanced nutrient feeding toward high titer antibody production process. Biotech Bioeng, 2011, 108: 1078-1088.

[25] Zhang A, Tsang VL, Moore B, Shen V, Huang Y, Kshirsagar R, Ryll T. Advanced process monitoring and feedback control to enhance cell culture process production and robustness. Biotech Bioeng, 2015, 112: 2495-2504.

[26] Zhang L, Zhang W, Wang C, Liu J, Deng X, Liu X, Fan L, Tan W. Responses of CHO-DHFR cells to ratio of asparagine to glutamine in feed media: cell growth, antibody production, metabolic waste, glutamate, and energy metabolism. Bioresour Bioprocess, 2016, 3: 5.

[27] Zhang X-R, He Y-M, Zhao L, Tan W-S, Ye Q. A real-time oxygen uptake rate monitoring approach suitable for the antibody production process. Biochem Eng J, 2024, 211: 109463.

[28] Zhou T, Reji R, Kairon RS, Chiam KH. A review of algorithmic approaches for cell culture media optimization. Front Bioeng Biotechnol, 2023

[29] Zhou W, Rehm J, Hu W. High viable cell concentration fed-batch cultures of hybridoma cells through on-line nutrient feeding. Biotech Bioeng, 1995, 46: 579-587.

[30] Zhu MM, Mollet M, Hubert RS, Kyung YS, Zhang GGKent JA, Bommaraju TV, Barnicki SD. Industrial production of therapeutic proteins: cell lines, cell culture, and purification. Handbook of industrial chemistry and biotechnology, 2017, Cham. Springer International Publishing1639-1669.

[31] Zorova LD, Popkov VA, Plotnikov EY, Silachev DN, Pevzner IB, Jankauskas SS, Babenko VA, Zorov SD, Balakireva AV, Juhaszova M, Sollott SJ, Zorov DB. Mitochondrial membrane potential. Anal Biochem Mitochondrial Biochem Bioenerg, 2018, 552: 50-59.

[32] Zou M, Zhou Z-W, Fan L, Zhang W-J, Zhao L, Liu X-P, Wang H-B, Tan W-S. A novel method based on nonparametric regression with a Gaussian kernel algorithm identifies the critical components in CHO media and feed optimization. J Ind Microbiol Biotechnol, 2020, 47: 63-72.

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