Advertisement

BioDrugs

, Volume 32, Issue 6, pp 571–584 | Cite as

Recombinant Antibody Production in CHO and NS0 Cells: Differences and Similarities

  • Venkata Gayatri Dhara
  • Harnish Mukesh Naik
  • Natalia I. Majewska
  • Michael J. Betenbaugh
Review Article
  • 95 Downloads

Abstract

The commercial production of monoclonal antibodies (mAbs) has revolutionized the treatment of many diseases, including cancer, multiple sclerosis, and rheumatoid arthritis. These biotherapeutics have the potential to generate a global annual revenue of more than US$150 billion. Two cell hosts are predominantly utilized to produce these mAbs: Chinese hamster ovary (CHO) cells and murine myeloma cells (NS0). By 2017, nearly one-quarter of all approved mAbs in the market were produced using the NS0 host cell line, and around two-thirds were produced in CHO cells. Several different expression platforms are available: CHO-GS (glutamine synthetase), CHO-DHFR (dihydrofolate reductase), NS0, and GS-NS0, which have been characterized with respect to cell line and process development. Even though the major components of the cell culture media are common for both CHO and NS0 cells, specific growth media have been modified based on individual cellular requirements, such as cholesterol for NS0 cells. Additionally, understanding genomic and metabolic differences between the two cell hosts from an ‘omics perspective has created a reference for media composition and antibody quality improvements.

Notes

Compliance with Ethical Standards

Funding

This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. DGE-1746891.

Conflicts of Interest

Venkata Gayatri Dhara, Harnish Mukesh Naik, Natalia I. Majewska, and Michael J. Betenbaugh have no conflicts of interest that might be relevant to the contents of this manuscript.

References

  1. 1.
    Birch JR, Onakunle Y. Biopharmaceutical proteins: opportunities and challenges, in therapeutic proteins, vol. 308. New Jersey: Humana Press; 2005. p. 001–16.Google Scholar
  2. 2.
    Kelley B. Very large scale monoclonal antibody purification: the case for conventional. Biotechnol Prog. 2007;23(5):995–1008.PubMedGoogle Scholar
  3. 3.
    Shukla AA, Gottschalk U. Single-use disposable technologies for biopharmaceutical manufacturing. Trends Biotechnol. 2013;31(3):147–54.CrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    Walsh G. Biopharmaceutical benchmarks 2006. Nat Biotechnol. 2006;24(7):831–3.CrossRefGoogle Scholar
  5. 5.
    Liu JKH. The history of monoclonal antibody development - Progress, remaining challenges and future innovations. Ann Med Surg. 2014;3(4):113–6.CrossRefGoogle Scholar
  6. 6.
    Nissim A, Chernajovsky Y. Historical development of monoclonal antibody therapeutics. Handb Exp Pharmacol. 2008;181:3–18.CrossRefGoogle Scholar
  7. 7.
    Chadd HE, Chamow SM. Therapeutic antibody expression technology. Curr Opin Biotechnol. 2001;12(2):188–94.CrossRefPubMedGoogle Scholar
  8. 8.
    Ecker DM, Jones SD, Levine HL. The therapeutic monoclonal antibody market. MAbs. 2015;7(1):9–14.CrossRefPubMedGoogle Scholar
  9. 9.
    Reichert J. Monoclonal antibodies as innovative therapeutics. Curr Pharm Biotechnol. 2008;9(6):423–30.CrossRefPubMedGoogle Scholar
  10. 10.
    Aggarwal S. What’s fueling the biotech engine—2008. Nat Biotechnol. 2009;27(11):987–93.CrossRefPubMedGoogle Scholar
  11. 11.
    Aggarwal S. What’s fueling the biotech engine–2008. Nat Biotechnol. 2009;27(11):987–93.CrossRefPubMedGoogle Scholar
  12. 12.
    Aggarwal S. What’s fueling the biotech engine—2008. Nat Biotechnol. 2009;27(11):987–93.CrossRefPubMedGoogle Scholar
  13. 13.
    Aggarwal S. What’s fueling the biotech engine—2011 to 2012. Nat Biotechnol. 2012;30(12):1191–7.CrossRefPubMedGoogle Scholar
  14. 14.
    Aggarwal SR. What’s fueling the biotech engine—2012 to 2013. Nat Biotechnol. 2014;32(1):32–9.CrossRefPubMedGoogle Scholar
  15. 15.
  16. 16.
    Freshney RI. Freshney’s culture of animal cells: a multimedia guide. Hoboken: Wiley-Liss; 1999.Google Scholar
  17. 17.
    Kuroda Y. Drosophila tissue culture: retrospect and prospect. In: Maramorosch K, Mitsuhashi J, editors. Invertebrate cell culture application. New York: Academic Press; 1982. p. 53–104.CrossRefGoogle Scholar
  18. 18.
    Lucey BP, Nelson-Rees WA, Hutchins GM. Henrietta Lacks, HeLa cells, and cell culture contamination. Arch Pathol Lab Med. 2009;133(9):1463–7.PubMedGoogle Scholar
  19. 19.
    Yao T, Asayama Y. Animal-cell culture media: history, characteristics, and current issues. Reprod Med Biol. 2017;16(2):99–117.CrossRefPubMedPubMedCentralGoogle Scholar
  20. 20.
    Kim DY, Lee JC, Chang HN, Oh DJ. Development of serum-free media for a recombinant CHO cell line producing recombinant antibody. Enzyme Microb Technol. 2006;39(3):426–33.CrossRefGoogle Scholar
  21. 21.
    Jayapal K, Wlaschin K, Hu W-S, Yap MGS. Recombinant protein therapeutics from CHO cells—20 years and counting. Chem Eng Prog. 2007;103(10):40–7.Google Scholar
  22. 22.
    Hauser H, Wagner R. Animal cell biotechnology : in biologics production.Google Scholar
  23. 23.
    Kaas CS, Kristensen C, Betenbaugh MJ, Andersen MR. Sequencing the CHO DXB11 genome reveals regional variations in genomic stability and haploidy. BMC Genomics. 2015;16(1):1–9.CrossRefGoogle Scholar
  24. 24.
    Köhler G, Milstein C. Derivation of specific antibody-producing tissue culture and tumor lines by cell fusion. Eur J Immunol. 1976;6(7):511–9.CrossRefPubMedGoogle Scholar
  25. 25.
    Galfre G, Milstein C. Preparation of monoclonal antibodies: strategies and procedures. Methods Enzymol. 1981;73(Pt B):3–46.CrossRefGoogle Scholar
  26. 26.
    Barnes LM, Bentley CM, Dickson AJ. Advances in animal cell recombinant protein production: GS-NS0 expression system. Cytotechnology. 2000;32:109–23.CrossRefPubMedPubMedCentralGoogle Scholar
  27. 27.
    Li F, Vijayasankaran N, Shen AY, Kiss R, Amanullah A. Cell culture processes for monoclonal antibody production. MAbs. 2010;2(5):466–77.CrossRefPubMedPubMedCentralGoogle Scholar
  28. 28.
    Romanova N, Noll T. Engineered and natural promoters and chromatin-modifying elements for recombinant protein expression in CHO Cells. Biotechnol J. 2018;13(3):e1700232.CrossRefPubMedGoogle Scholar
  29. 29.
    Kim JY, Kim Y-G, Lee GM. CHO cells in biotechnology for production of recombinant proteins: current state and further potential. Appl Microbiol Biotechnol. 2012;93(3):917–30.CrossRefPubMedGoogle Scholar
  30. 30.
    Bussow K. Stable mammalian producer cell lines for structural biology. Curr Opin Struct Biol. 2015;32:81–90.CrossRefPubMedGoogle Scholar
  31. 31.
    Shim H. Therapeutic antibodies by phage display. Curr Pharm Des. 2016;22(43):6538–59.CrossRefPubMedGoogle Scholar
  32. 32.
    Urlaub G, Chasin LA. Isolation of Chinese hamster cell mutants deficient in dihydrofolate reductase activity. Proc Natl Acad Sci. 1980;77(7):4216–20.CrossRefPubMedGoogle Scholar
  33. 33.
    Brown ME, Renner G, Field RP, Hassell T. Process development for the production of recombinant antibodies using the glutamine synthetase (GS) system. Cytotechnology. 1992;9(1–3):231–6.CrossRefPubMedGoogle Scholar
  34. 34.
    Cockett MI, Bebbington CR, Yarranton GT. High level expression of tissue inhibitor of metalloproteinases in Chinese hamster ovary cells using glutamine synthetase gene amplification. Biotechnology (NY). 1990;8(7):662–7.Google Scholar
  35. 35.
    Bebbington CR, Renner G, Thomson S, King D, Abrams D, Yarranton GT. High-level expression of a recombinant antibody from myeloma cells using a glutamine synthetase gene as an amplifiable selectable marker. Biotechnology (NY). 1992;10(2):169–75.Google Scholar
  36. 36.
    DiStefano DJ, Mark GE, Robinson DK. Feeding of nutrients delays apoptotic death in fed-batch cultures of recombinant NSO myeloma cells. Biotechnol Lett. 1996;18(9):1067–72.CrossRefGoogle Scholar
  37. 37.
    Jun SC, Kim MS, Hong HJ, Lee GM. Limitations to the development of humanized antibody producing Chinese hamster ovary cells using glutamine synthetase-mediated gene amplification. Biotechnol Prog. 2006;22(3):770–80.CrossRefPubMedGoogle Scholar
  38. 38.
    Lai T, Yang Y, Ng SK. Advances in Mammalian cell line development technologies for recombinant protein production. Pharmaceuticals (Basel). 2013;6(5):579–603.CrossRefGoogle Scholar
  39. 39.
    Bandaranayake AD, Almo SC. Recent advances in mammalian protein production. FEBS Lett. 2014;588(2):253–60.CrossRefPubMedGoogle Scholar
  40. 40.
    Lalonde M-E, Durocher Y. Therapeutic glycoprotein production in mammalian cells. J Biotechnol. 2017;251:128–40.CrossRefPubMedGoogle Scholar
  41. 41.
    Okonkowski J, et al. Cholesterol delivery to NS0 cells: challenges and solutions in disposable linear low-density polyethylene-based bioreactors. J Biosci Bioeng. 2007;103(1):50–9.CrossRefPubMedGoogle Scholar
  42. 42.
    Sato JD, et al. Effects of proximate cholesterol precursors and steroid hormones on mouse myeloma growth in serum-free medium. Vitro Cell. Dev. Biol. 1988;24(12):1223–8.CrossRefGoogle Scholar
  43. 43.
    Keen MJ, Steward TW. Adaptation of cholesterol-requiring NS0 mouse myeloma cells to high density growth in a fully defined protein-free and cholesterol-free culture medium. Cytotechnology. 1995;17(3):203–11.CrossRefPubMedGoogle Scholar
  44. 44.
    Gorfien S, Paul B, Walowitz J, Keem R, Biddle W, Jayme D. Growth of NS0 cells in protein-free, chemically defined medium. Biotechnol Prog. 2000;16(5):682–7.CrossRefPubMedGoogle Scholar
  45. 45.
    Kadarusman J, Bhatia R, McLaughlin J, Lin WR. Growing cholesterol-dependent NS0 myeloma cell line in the wave bioreactor system: overcoming cholesterol-polymer interaction by using pretreated polymer or inert fluorinated ethylene propylene. Biotechnol Prog. 2005;21(4):1341–6.CrossRefPubMedGoogle Scholar
  46. 46.
    Burky JE, et al. Protein-free fed-batch culture of non-GS NS0 cell lines for production of recombinant antibodies. Biotechnol Bioeng. 2007;96(2):281–93.CrossRefPubMedGoogle Scholar
  47. 47.
    Hartman TE, et al. Derivation and characterization of cholesterol-independent non-GS NS0 cell lines for production of recombinant antibodies. Biotechnol Bioeng. 2007;96(2):294–306.CrossRefPubMedGoogle Scholar
  48. 48.
    Li J, et al. Generation of a cholesterol-independent, non-GS NS0 cell line through chemical treatment and application for high titer antibody production. Biotechnol Bioeng. 2012;109(7):1685–92.CrossRefPubMedGoogle Scholar
  49. 49.
    Sampey D, Courville P, Acree D, Hausfeld J, Bentley WE. Enhanced expression of a biosimilar monoclonal antibody with a novel NS0 platform. Biotechnol Prog. 2018;34(2):455–62.CrossRefPubMedGoogle Scholar
  50. 50.
    Zhang J, Robinson D. Development of animal-free, protein-free and chemically-defined media for NS0 cell culture. Cytotechnology. 2005;48(1–3):59–74.CrossRefPubMedPubMedCentralGoogle Scholar
  51. 51.
    Mcgrew JT, Richards CL, Smidt P, Dell B, Price V. Lipid requirements of a recombinant chinese hamster ovary cell line (CHO)”, in new developments and new applications in animal cell technology. Dordrecht: Kluwer Academic Publishers; 1998. p. 205–7.Google Scholar
  52. 52.
    Landauer K. Designing media for animal cell culture: CHO cells, the industrial standard. Methods Mol Biol. 2014;1104:89–103.CrossRefPubMedGoogle Scholar
  53. 53.
    Dahodwala H, Sharfstein ST. The omics revolution in CHO Biology: roadmap to improved CHO productivity. In: Meleady P, editor. Heterologous protein production in CHO cells. New York: Humana Press; 2017. p. 153–68.CrossRefGoogle Scholar
  54. 54.
    Lewis NE, et al. resource Genomic landscapes of Chinese hamster ovary cell lines as revealed by the Cricetulus griseus draft genome. Nat Biotechnol. 2013;31(8):759–65.CrossRefPubMedGoogle Scholar
  55. 55.
    Adams DJ, Doran AG, Lilue J, Keane TM. The mouse genomes project : a repository of inbred laboratory mouse strain genomes. Mamm Genome. 2015;26(9–10):403–12.CrossRefPubMedGoogle Scholar
  56. 56.
    Swiderek H, Al-rubeai M. Functional genome-wide analysis of antibody producing NS0 cell line cultivated at different temperatures. Biotechnol Appl Biochem. 2007;98(3):616–30.Google Scholar
  57. 57.
    Khoo HS, Falciani F, Al-rubeai M. A genome-wide transcriptional analysis of producer and non-producer NS0 myeloma cell lines. Biotechnol Appl Biochem. 2007;47:85–95.CrossRefPubMedGoogle Scholar
  58. 58.
    Chen C, Le H, Goudar CT. An automated RNA-Seq analysis pipeline to identify and visualize differentially expressed genes and pathways in CHO Cells. Biotechnol Bioeng. 2015;30(5):1150–62.Google Scholar
  59. 59.
    Singh A, Kildegaard HF, Andersen MR. An online compendium of CHO RNA-Seq data allows identification of CHO cell line-specific transcriptomic signatures. Biotechnol J. 2018;13(10):1–11.CrossRefGoogle Scholar
  60. 60.
    Monger C, Kelly PS, Gallagher C, Clynes M, Barron N, Clarke C. Towards next generation CHO cell biology: bioinformatics methods for RNA-Seq-based expression profiling. Biotechnol. 2015;Bioeng:950–66.Google Scholar
  61. 61.
    Dinnis DM, et al. Functional proteomic analysis of GS-NS0 murine myeloma cell lines with varying recombinant monoclonal antibody production rate. Biotechnol Bioeng. 2006;94(5):830–41.CrossRefPubMedGoogle Scholar
  62. 62.
    Alete DE, Racher AJ, Birch JR, Stansfield SH, James DC, Smales CM. Proteomic analysis of enriched microsomal fractions from GS-NS0 murine myeloma cells with varying secreted recombinant monoclonal antibody productivities. Proteomics. 2005;5:4689–704.CrossRefPubMedGoogle Scholar
  63. 63.
    Prieto Y, et al. Towards the molecular characterization of the stable producer phenotype of recombinant antibody-producing NS0 myeloma cells. Cytotechnology. 2011;63:351–62.CrossRefPubMedPubMedCentralGoogle Scholar
  64. 64.
    Krampe B, Swiderek H, Al-rubeai M. Transcriptome and proteome analysis of antibody-producing mouse myeloma NS0 cells cultivated at different cell densities in perfusion culture. Biotechnol Appl Biochem. 2008;50:133–41.CrossRefPubMedGoogle Scholar
  65. 65.
    Baycin-hizal D, et al. Proteomic analysis of chinese hamster ovary cells. J Proteome Res. 2012;11:5265–76.CrossRefPubMedPubMedCentralGoogle Scholar
  66. 66.
    Ley D, et al. Multi-omic profiling of EPO-producing Chinese hamster ovary cell panel reveals metabolic adaptation to heterologous protein production. Biotechnol Bioeng. 2015;112(11):2373–87.CrossRefPubMedPubMedCentralGoogle Scholar
  67. 67.
    Liu Z, et al. A quantitative proteomic analysis of cellular responses to high glucose media in chinese hamster ovary cells. Biotechnol Prog. 2015;31(4):1026–38.CrossRefPubMedGoogle Scholar
  68. 68.
    Baik JY, et al. Initial transcriptome and proteome analyses of low culture temperature-induced expression in CHO Cells producing erythropoietin. Biotechnol Bioeng. 2005;93(2):361–71.CrossRefGoogle Scholar
  69. 69.
    Nissom PM, et al. Transcriptome and proteome profiling to understanding the biology of high productivity CHO cells. Mol Biotechnol. 2006;34:125–40.CrossRefPubMedGoogle Scholar
  70. 70.
    Valente KN, Levy NE, Lee KH, Lenhoff AM. Applications of proteomic methods for CHO host cell protein characterization in biopharmaceutical manufacturing. Curr Opin Biotechnol. 2018;53:144–50.CrossRefPubMedGoogle Scholar
  71. 71.
    Zhang P, Lifen D, Heng D, Wang T, Yang Y, Song Z. A functional analysis of N-glycosylation-related genes on sialylation of recombinant erythropoietin in six commonly used mammalian cell lines. Metab Eng. 2010;12:526–36.CrossRefPubMedGoogle Scholar
  72. 72.
    Sheeley DM, Merrill BM, Taylor LC. Characterization of monoclonal antibody glycosylation: comparison of expression systems and identification of terminal alpha-linked galactose. Anal Biochem. 1997;247(1):102–10.CrossRefPubMedGoogle Scholar
  73. 73.
    Baker KN, Rendall MH, Hills AE, Hoare M, Freedman RB, James DC. Metabolic control of recombinant protein N-glycan processing in NS0 and CHO Cells. Biotechnol Bioeng. 2001;73(3):188–202.CrossRefPubMedGoogle Scholar
  74. 74.
    Borrebaeck CK, Malmborg AC, Ohlin M. Does endogenous glycosylation prevent the use of mouse monoclonal antibodies as cancer therapeutics? Immunol Today. 1993;14(10):477–9.CrossRefPubMedGoogle Scholar
  75. 75.
    Galili U, Anaraki F, Thall A, Hill-Black C, Radic M. One percent of human circulating B lymphocytes are capable of producing the natural anti-Gal antibody. Blood. 1993;82(8):2485–93.PubMedGoogle Scholar
  76. 76.
    Datta P, Linhardt RJ, Sharfstein ST. An ‘omics approach towards CHO cell engineering. Biotechnol Bioeng. 2013;110(5):1255–71.CrossRefPubMedGoogle Scholar
  77. 77.
    Kildegaard HF, Baycin-Hizal D, Lewis NE, Betenbaugh MJ. The emerging CHO systems biology era: harnessing the ‘omics revolution for biotechnology. Curr Opin Biotechnol. 2013;24(6):1102–7.CrossRefPubMedGoogle Scholar
  78. 78.
    Stolfa G, et al. CHO-omics review: the impact of current and emerging technologies on Chinese hamster ovary based bioproduction. Biotechnol J. 2018;13:1–14.CrossRefGoogle Scholar
  79. 79.
    Heffner KM, Wang Q, Hizal DB, Can Ö, Betenbaugh MJ (2018) Glycoengineering of mammalian expression systems on a cellular level. In: Advances in biochemical engineering/biotechnology. Berlin: Springer; 2018. p. 1–33.Google Scholar
  80. 80.
    Mohmad-Saberi SE, Hashim YZH-Y, Mel M, Amid A, Ahmad-Raus R, Packeer-Mohamed V. Metabolomics profiling of extracellular metabolites in CHO-K1 cells cultured in different types of growth media. Cytotechnology. 2013;65(4):577–86.CrossRefPubMedGoogle Scholar
  81. 81.
    Chong WPK, et al. Metabolomics-driven approach for the improvement of Chinese hamster ovary cell growth: overexpression of malate dehydrogenase II. J Biotechnol. 2010;147(2):116–21.CrossRefPubMedGoogle Scholar
  82. 82.
    Ma N, Ellet J, Okediadi C, Hermes P, McCormick E, Casnocha S. A single nutrient feed supports both chemically defined NS0 and CHO fed-batch processes: improved productivity and lactate metabolism. Biotechnol Prog. 2009;25(5):1353–63.CrossRefPubMedGoogle Scholar
  83. 83.
    Dietmair S, et al. Metabolite profiling of CHO cells with different growth characteristics. Biotechnol Bioeng. 2012;109(6):1404–14.CrossRefPubMedGoogle Scholar
  84. 84.
    Selvarasu S, et al. Combined in silico modeling and metabolomics analysis to characterize fed-batch CHO cell culture. Biotechnol Bioeng. 2012;109(6):1415–29.CrossRefPubMedGoogle Scholar
  85. 85.
    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. Biotechnol Bioeng. 2017;114(8):1779–90.CrossRefPubMedGoogle Scholar
  86. 86.
    Ahn WS, Antoniewicz MR. Metabolic flux analysis of CHO cells at growth and non-growth phases using isotopic tracers and mass spectrometry. Metab Eng. 2011;13(5):598–609.CrossRefPubMedGoogle Scholar
  87. 87.
    McAtee Pereira AG, Walther JL, Hollenbach M, Young JD. 13C flux analysis reveals that rebalancing medium amino acid composition can reduce ammonia production while preserving central carbon metabolism of CHO cell cultures. Biotechnol J. 2018;13(10):1700518.CrossRefGoogle Scholar
  88. 88.
    Templeton N, et al. Application of (13)C flux analysis to identify high-productivity CHO metabolic phenotypes. Metab Eng. 2017;43(Pt B):218–25.CrossRefPubMedGoogle Scholar
  89. 89.
    De la Luz-Hdez K. Metabolomics and mammalian cell culture. In: Roessner U, editor. Metabolomics. Rijeka: InTech; 2012. p. 3–18.Google Scholar
  90. 90.
    Lambert JM, Berkenblit A. Antibody-drug conjugates for cancer treatment. Annu Rev Med. 2018;69:191–207.CrossRefPubMedGoogle Scholar
  91. 91.
    Laux H. Industry perspective on Chinese hamster ovary cell ‘omics’. Pharm Bioprocess. 2014;2(5):377–81.CrossRefGoogle Scholar
  92. 92.
    Pereira J, Rajendra Y, Baldi L, Hacker DL, Wurm FM. Transient gene expression with CHO cells in conditioned medium: a study using TubeSpin((R)) bioreactors. BMC Proc. 2011;5(Suppl 8):P38.CrossRefPubMedPubMedCentralGoogle Scholar
  93. 93.
    Galliher PM (2007) Review of single use technologies in biomanufacturing. http://www.wpi.edu/Images/CMS/BEI/parrishgalliher.pdf. Accessed 9 Apr 2018.
  94. 94.
    Langer ES, Rader RA. Single-use technologies in biopharmaceutical manufacturing: a 10-year review of trends and the future. Eng Life Sci. 2014;14(3):238–43.CrossRefGoogle Scholar
  95. 95.
    Jacquemart R, Vandersluis M, Zhao M, Sukhija K, Sidhu N, Stout J. A Single-use strategy to enable manufacturing of affordable biologics. Comput Struct Biotechnol J. 2016;14:309–18.CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Venkata Gayatri Dhara
    • 1
  • Harnish Mukesh Naik
    • 1
  • Natalia I. Majewska
    • 1
  • Michael J. Betenbaugh
    • 1
  1. 1.Department of Chemical and Biomolecular EngineeringJohns Hopkins UniversityBaltimoreUSA

Personalised recommendations