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Cited by 786Viral Infectious Diseases and Gene Expression in InsectsFungal and yeast genetics researchMonoclonal and Polyclonal Antibodies Research

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The genomic sequence of the Chinese hamster ovary (CHO)-K1 cell line

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Xu, Xun, Nagarajan, Harish, Lewis, Nathan E, Pan, Shengkai, Cai, Zhiming, Liu, Xin, Chen, Wenbin, Xie, Min, Wang, Wenliang, Hammond, Stephanie, Andersen, Mikael R, Neff, Norma, Passarelli, Benedetto, Koh, Winston, Fan, H Christina, Wang, Jianbin, Gui, Yaoting, Lee, Kelvin H, Betenbaugh, Michael J, Quake, Stephen R, Famili, Iman, Palsson, Bernhard O, Wang, Jun·2011·Nature Biotechnology
DOI 10.1038/nbt.1932PMC PMC3164356
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Abstract

Since 1987, immortalized cells from the ovary of a Chinese hamster have been the workhorse for producing recombinant therapeutics, including monoclonal antibodies, blood factors, hormones, growth factors and enzymes. Xu et al. provide the genome sequence of the ancestral CHO-K1 cell line, which should aid in the optimization of current production cell lines. Chinese hamster ovary (CHO)–derived cell lines are the preferred host cells for the production of therapeutic proteins. Here we present a draft genomic sequence of the CHO-K1 ancestral cell line. The assembly comprises 2.45 Gb of genomic sequence, with 24,383 predicted genes. We associate most of the assembled scaffolds with 21 chromosomes isolated by microfluidics to identify chromosomal locations of genes. Furthermore, we investigate genes involved in glycosylation, which affect therapeutic protein quality, and viral susceptibility genes, which are relevant to cell engineering and regulatory concerns. Homologs of most human glycosylation-associated genes are present in the CHO-K1 genome, although 141 of these homologs are not expressed under exponential growth conditions. Many important viral entry genes are also present in the genome but not expressed, which may explain the unusual viral resistance property of CHO cell lines. We discuss how the availability of this genome sequence may facilitate genome-scale science for the optimization of biopharmaceutical protein production.

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Figure 1 Chromosomal assignment to scaffolds. (a) Chromosomal preparations from CHO-K1 were sequenced and the reads were aligned to the scaffolds. For each of the N50 scaffolds, a vector was used to represent the read alignments in the 22 preparations. Using this metric, a correlation matrix was generated between all the N50 scaffolds. Upon clustering the matrix, 21 clusters of highly correlated scaffolds emerged, suggesting that the scaffolds are associated with 21 chromosomes in CHO-K1. (b) Classical karyotyping of CHO-K1 reveals 21 chromosomes.
Figure 1 Chromosomal assignment to scaffolds. (a) Chromosomal preparations from CHO-K1 were sequenced and the reads were aligned to the scaffolds. For each of the N50 scaffolds, a vector was used to represent the read alignments in the 22 preparations. Using this metric, a correlation matrix was generated between all the N50 scaffolds. Upon clustering the matrix, 21 clusters of highly correlated scaffolds emerged, suggesting that the scaffolds are associated with 21 chromosomes in CHO-K1. (b) Classical karyotyping of CHO-K1 reveals 21 chromosomes.CC BY-NC-SA · PubMed Central
Figure 2 Comparative analysis of functional categories and gene content. For each GOslim biological process category, the fraction of all GO terms in that category is shown for human, mouse, rat and CHO genomes. GOslim classes that are significantly enriched and show the highest and lowest coverage of human and mouse genes in the CHO genome are highlighted in red (*) and green (**), respectively. P value cutoff and coverage in human and mouse were used to determine significance.
Figure 2 Comparative analysis of functional categories and gene content. For each GOslim biological process category, the fraction of all GO terms in that category is shown for human, mouse, rat and CHO genomes. GOslim classes that are significantly enriched and show the highest and lowest coverage of human and mouse genes in the CHO genome are highlighted in red (*) and green (**), respectively. P value cutoff and coverage in human and mouse were used to determine significance.CC BY-NC-SA · PubMed Central
Figure 3 A global view of the expression of CHO-K1 glycosylation genes. (a) While homologs were identified for 99% of the human glycosylation-associated transcripts, only 53% had detectable expression. Glycosylation gene classes enriched in expressed genes (denoted with **) include hyaluronoglucosaminidases, sugar-nucleotide synthesis, mannosyltransferases and lysozomal enzymes. Significantly depleted classes (P < 0.06) in expressed genes (denoted with *) include the sulfotransferases, fucosyltransferases and GalNAc transferases. (b) A selection of CHO N-linked glycosylation pathways are detailed to demonstrate the effects of CHO glycosylation gene expression on the possible glycoforms. (i) A difference between human and CHO glycosylation is seen in the lack of expression of MGAT3, which is responsible for the bisecting β(1,4) GlcNAc that occurs on ∼10% of human antibodies. (ii) The only N-glycan-modifying fucosyltransferase expressed in CHO-K1 is FUT8, which adds fucose to the core glycan by an α(1,6) linkage. (iii) Sialylation of a terminal galactose can occur through α(2,3) or α(2,6) linkages in human. However, CHO ST6Gal genes are not expressed, so CHO glycans primarily have α(2,3) linkages. (iv) The two most abundant sialic acids are Neu5Ac and Neu5Gc. Neu5Gc is immunogenic in humans. Thus, the lack of CMAH expression in the CHO-K1 sample minimizes this response by limiting the conversion of Neu5Ac to Neu5Gc. Pathways are adapted loosely from ref. 55. Abbreviations are defined in Supplementary Table 18.
Figure 3 A global view of the expression of CHO-K1 glycosylation genes. (a) While homologs were identified for 99% of the human glycosylation-associated transcripts, only 53% had detectable expression. Glycosylation gene classes enriched in expressed genes (denoted with **) include hyaluronoglucosaminidases, sugar-nucleotide synthesis, mannosyltransferases and lysozomal enzymes. Significantly depleted classes (P < 0.06) in expressed genes (denoted with *) include the sulfotransferases, fucosyltransferases and GalNAc transferases. (b) A selection of CHO N-linked glycosylation pathways are detailed to demonstrate the effects of CHO glycosylation gene expression on the possible glycoforms. (i) A difference between human and CHO glycosylation is seen in the lack of expression of MGAT3, which is responsible for the bisecting β(1,4) GlcNAc that occurs on ∼10% of human antibodies. (ii) The only N-glycan-modifying fucosyltransferase expressed in CHO-K1 is FUT8, which adds fucose to the core glycan by an α(1,6) linkage. (iii) Sialylation of a terminal galactose can occur through α(2,3) or α(2,6) linkages in human. However, CHO ST6Gal genes are not expressed, so CHO glycans primarily have α(2,3) linkages. (iv) The two most abundant sialic acids are Neu5Ac and Neu5Gc. Neu5Gc is immunogenic in humans. Thus, the lack of CMAH expression in the CHO-K1 sample minimizes this response by limiting the conversion of Neu5Ac to Neu5Gc. Pathways are adapted loosely from ref. 55. Abbreviations are defined in Supplementary Table 18.CC BY-NC-SA · PubMed Central
Figure 4 An assessment of the expression state of viral susceptibility genes in CHO-K1. (a) A global view of viral susceptibility genes in CHO-K1 demonstrates no measurable expression for 158 of these genes. The enriched GO cell compartment terms among the nonexpressed susceptibility genes shows that membrane proteins and DNA binding proteins are primarily not expressed. The expression state of all members of the “external side of plasma membrane” GO class is shown (blue and red for expressed and not expressed, respectively). (b) A schematic of entry mechanisms used by HSV-1. Viral entry receptors that are not expressed in CHO are shown by their gene names in red, and missing receptors are shown with a dashed outline. WT, wild type; Mut, mutant; Bov, bovine.
Figure 4 An assessment of the expression state of viral susceptibility genes in CHO-K1. (a) A global view of viral susceptibility genes in CHO-K1 demonstrates no measurable expression for 158 of these genes. The enriched GO cell compartment terms among the nonexpressed susceptibility genes shows that membrane proteins and DNA binding proteins are primarily not expressed. The expression state of all members of the “external side of plasma membrane” GO class is shown (blue and red for expressed and not expressed, respectively). (b) A schematic of entry mechanisms used by HSV-1. Viral entry receptors that are not expressed in CHO are shown by their gene names in red, and missing receptors are shown with a dashed outline. WT, wild type; Mut, mutant; Bov, bovine.CC BY-NC-SA · PubMed Central
Figure 5 The CHO-K1 genome will aid in cell line engineering, generate hypotheses for biological discovery, and serve as a context to facilitate sequencing efforts and sequence analysis for additional cell lines. Although significant advances in CHO biology have occurred over the past decades, the accessibility of the CHO-K1 genome will have an impact on at least three major areas. (a) The CHO genome will aid cell line engineering by facilitating the application of experimental and computational sequence-based tools for genetic manipulation and genome analysis. For example, BLAST can be used to identify the CHO sequence of a desired gene, whereas siRNA and site-directed mutagenesis methods can be used to directly modulate gene expression levels and protein activities. Moreover, the genome sequence can be used to reconstruct models of CHO-K1 metabolism, which allow the assessment of how genetic manipulations affect other pathways and can predict nonintuitive genetic changes to improve product yield or quality. (b) The biomolecular mechanisms underlying many phenotypic properties of CHO are poorly characterized (e.g., viral susceptibility). The components underlying these phenotypes can be identified through the comparison of CHO gene content and gene expression with other organisms or cell lines. (c) Although large genomic changes can occur in immortalized and engineered cell lines such as CHO, the CHO-K1 genome can serve as a context for the assembly and analysis of genome sequences from additional CHO cell lines.
Figure 5 The CHO-K1 genome will aid in cell line engineering, generate hypotheses for biological discovery, and serve as a context to facilitate sequencing efforts and sequence analysis for additional cell lines. Although significant advances in CHO biology have occurred over the past decades, the accessibility of the CHO-K1 genome will have an impact on at least three major areas. (a) The CHO genome will aid cell line engineering by facilitating the application of experimental and computational sequence-based tools for genetic manipulation and genome analysis. For example, BLAST can be used to identify the CHO sequence of a desired gene, whereas siRNA and site-directed mutagenesis methods can be used to directly modulate gene expression levels and protein activities. Moreover, the genome sequence can be used to reconstruct models of CHO-K1 metabolism, which allow the assessment of how genetic manipulations affect other pathways and can predict nonintuitive genetic changes to improve product yield or quality. (b) The biomolecular mechanisms underlying many phenotypic properties of CHO are poorly characterized (e.g., viral susceptibility). The components underlying these phenotypes can be identified through the comparison of CHO gene content and gene expression with other organisms or cell lines. (c) Although large genomic changes can occur in immortalized and engineered cell lines such as CHO, the CHO-K1 genome can serve as a context for the assembly and analysis of genome sequences from additional CHO cell lines.CC BY-NC-SA · PubMed Central

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Authors
Xu, X., Nagarajan, H., Lewis, N. E., Pan, S., Cai, Z., Liu, X., Chen, W., Xie, M., Wang, W., Hammond, S., Andersen, M. R., Neff, N., Passarelli, B., Koh, W., Fan, H. C., Wang, J., Gui, Y., Lee, K. H., Betenbaugh, M. J., Quake, S. R., Famili, I., Palsson, B. O., & Wang, J.
Affiliations
  • BGI Group (China) (CN)
  • Peking University Shenzhen Hospital (CN)
  • Delaware Biotechnology Institute (US)
  • Technical University of Denmark (DK)
  • Howard Hughes Medical Institute (US)
  • Johns Hopkins University (US)
Corresponding author
  • Wang, Jianbin
  • Wang, Jun
ORCID
Venue
Nature Biotechnology
Publisher
Springer Science and Business Media LLC
Published
2011-08
Volume
29
Issue
8
Pages
735-741
ISSN
  • 0733-222X (ISSN-L)
  • 1087-0156
  • 1546-1696
DOI
10.1038/nbt.1932
PMC
PMC3164356
OpenAlex
W2093343938
Cited by
785
References
53
Citations by year
2026: 22 · 2025: 25 · 2024: 37 · 2023: 35 · 2022: 39 · 2021: 58 · 2020: 38 · 2019: 45 · 2018: 78 · 2017: 57 · 2016: 59 · 2015: 77 · 2014: 79 · 2013: 64 · 2012: 53
FWCI
27.29
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Biotechnology (publishedVersion, cc-by-nc-sa)
  • PubMed Central (publishedVersion, cc-by-nc-sa)
  • PubMed (publishedVersion)
  • Research at the University of Copenhagen (University of Copenhagen) (submittedVersion)
  • Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU) (submittedVersion)
Funders
  • Novo Nordisk Fonden (NNF10CC1016517)
  • National Cancer Institute (R44CA139977)
  • National Center for Research Resources (P20RR016472)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Viral Infectious Diseases and Gene Expression in Insects
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Fungal and yeast genetics research
  • Life Sciences › Immunology and Microbiology › Immunology › Monoclonal and Polyclonal Antibodies Research
Keywords
CHO-K1 cells, CHO cells, draft genome sequence, therapeutic protein production, monoclonal antibodies, virus resistance, cell line engineering, genome assembly, gene expression
MeSH terms
Animals, Chromosome Mapping, Cricetulus, Glycosylation, Cricetinae, Models, Biological, Molecular Sequence Data, CHO Cells, Genome, Sequence Analysis, DNA, Genomics

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