Applying disruptive technologies in
mammalian cell line development
L.P. Pybus, F. L. Saunders, and A.J. Porter
Mammalian Cell Culture, Fujifilm Diosynth Biotechnologies, Billingham, U.K.
www.fujifilmdiosynth.com
Applying disruptive technologies in mammalian cell line development
L.P. Pybus, F. L. Saunders, and A.J. Porter
Mammalian Cell Culture, Fujifilm Diosynth Biotechnologies, Billingham, U.K.
Abstract
Recombinant monoclonal antibodies (MAbs) maintain their ranking as the best-selling class of biologic
drugs. The introduction of high titre bioprocessing for the majority of these MAb products has focused
efforts towards maintaining desired quality attributes and reducing time to market. Furthermore, patents
covering several blockbuster MAbs and the expression technologies, which facilitate their high-level
expression, are due to expire over the next decade. A wave of second generation or “follow-on”
biopharmaceuticals/bioprocesses will therefore be vying for market share and regulatory approval.
Consequently, should biopharmaceutical manufacturing companies rely on traditional “platform” methods
of cell line development (CLD), which are well known but yield extensive variation and unpredictable
stability of expression, or invest in emerging technologies, which offer the potential of greater
reproducibility and speed? Enabling technologies in this area include host cell engineering, engineered
expression vectors, and rapid transient gene expression. Given the well-known mantra “the product is the
process”, implementation of these disruptive technologies will require a thorough understanding of how
changes at the CLD-phase affect key production process characteristics such as high cell-specific
productivity, correct product processing and rapid cell proliferation. Traditionally, CLD optimisation is
carried out using a lengthy trial-and-error approach where cells are treated as a “black box” and
characteristics are iteratively improved. Further advancement in CLD is therefore likely to benefit from the
tools of systems biology. These tools will ensure that future CLD manipulations will be informed by an
understanding of the genetic, regulatory, and metabolic networks that determine key process
characteristics during a production process.
Introduction
Today, the most prominent blockbuster biopharmaceuticals are MAb-based products which constitute five
of the top ten top selling biopharmaceuticals, generating 18 billion US$ in sales in 2009 (Walsh 2010). To
meet the large market demand of MAb therapeutics, bioprocessing technology for their production has
advanced greatly since the introduction of OKT3 into the market in 1986. Whereas these early cell culture
processes were typically low yielding (<1 g L-1), two decades of intensive development work has shifted
product titres into the g L-1 range for most MAb products, and blockbuster titres of ~ 10 g/L have been
reported (Huang et al 2010). This enhancement has been achieved by both advances in CLD processes
to produce and identify highly productive clones and by optimisation of media composition and bioreactor
operation. The advent of high titre process technology has now shifted production bottlenecks towards
downstream processing and the focus of cell culture process development has moved away from
2
www.fujifilmdiosynth.com
pursuing higher titres to controlling product quality and process consistency, while reducing CLD
timelines.
Indeed, as biosimilars and second-generation therapeutics become increasingly popular (Walsh
2010) should CLD continue to rely on conventional “platform” technologies or invest in new technologies,
which offer the potential of superior performance? Central to making these decisions will be the ability to
predict and successfully improve at the CLD stage cell factory performance in a bioprocess environment.
Such a level of process understanding will require the biopharmaceutical industry to move away from
conventional trial- and-error experimentation and utilise systems biology based techniques that integrate
high information content –omic technologies, bioinformatics data organisation and mathematical
modelling to allow an understanding of how to control complex cellular phenotypes (O’Callaghan and
James 2008).
In this review, we describe the current status of CLD with a particular focus on MAb production.
We also analyse how disruptive CLD technologies and an increased understanding of what determines
mammalian cell factory performance in a bioprocess environment can facilitate not only improvements in
MAb production, but also next generation and biosimilar products.
Production hosts for industrial MAb production
Despite the availability of a variety of alternative expression systems, including microbial, insect,
transgenic animals and plants, among the 58 biopharmaceuticals approved from 2006 to 2010, 32 are
produced using mammalian hosts (Walsh 2010). Furthermore, despite the availability of numerous
mammalian host cell lines such as baby hamster kidney (BHK), mouse myeloma NS0, human embryonic
kidney (HEK-293), and human retina-derived PerC6, nearly 70% of all recombinant therapeutic proteins
produced today utilise Chinese hamster ovary (CHO) cells (Jayapal et al 2007).
The popularity of CHO cells as production hosts can be attributed to the following reasons. Firstly, CHO
cells have been demonstrated to be safe production hosts over the past two decades, making it easier to
obtain regulatory authority approval. Secondly, CHO cells produce human-like glycoforms that are
compatible with and bioactive in humans. Finally, CHO cells are easily adapted to regulatory friendly
animal component-free conditions and grow to high viable cell densities in suspension culture, which are
two important characteristics for large-scale bioreactor culture.
It is important to note that “CHO” encompasses a large number of very different cell lines which
may differ in respect to large-scale genomic rearrangements and therefore phenotypic outputs (Xu et al
2011). The first ancestral CHO cell line was established by Dr. Theodore T. Puck and was noted to
display rapid cellular proliferation and high cellular viability during in vitro culture (Puck et al 1958). Early
work involving mutagenesis studies allowed the isolation of several auxotrophs and facilitated the
identification of CHO-K1 (a proline auxotroph; Kao and Puck 1968), which is the ancestral cell line of
many cell lines used within the biopharmaceutical industry today. Other commonly used cell lines include
two dihyrdofolate reductase (DHFR) negative cell lines which were developed by the lab of Prof.
3
www.fujifilmdiosynth.com
Lawrence Chasin in Columbia University as a result of genetic modification by chemical and gamma
irradiation: DUXB11 (with deletion of one DHFR allele and a mutation in the other; Urlaub and Chasin,
1980) and DG44 (with deletion of both alleles; Urlaub et al 1983). Yet another CHO-derived cell line
commonly used for therapeutic protein production is the Life Technologies™ owned CHO-S cell line (Life
Technologies, A1136401). Although these authors are not aware of any published records of the lineage
of CHO-S, it is believed to be a suspension variant of the original CHO cell line.
Strategies for efficient CHO cell line development
Wide ranges of cellular phenotypes are obtained during the CLD process that constructs and selects a
cell line for antibody manufacture. This heterogeneous pool of transfectants must therefore be screened
to identify a cell line with the most desirable characteristics, which typically include high volumetric
product titre (which is a function of high specific production rate (Qp) and/or a large value for the time
integral of viable cell concentration), acceptable growth in an inoculum process and production of a
product with the required quality attributes. The process by which a cell line for therapeutic protein
production is derived must also follow strict regulatory defined criteria. To meet regulatory guidelines,
mammalian derived cell lines should be cloned from a single cell progenitor and remain ‘stable’ over
several cell generations covering the time from thawing the cryopreserved working cell bank to the limit of
the in vitro cell age for production (ICH Q5D).
A traditional CLD strategy typically involves multiple evaluation stages from which a proportion of
cell lines are discarded and the most highly ranked cell lines retained (Figure 1).
4
www.fujifilmdiosynth.com
Figure 1. A schematic representation of a typical cell line development strategy
Typically a complete data set of cell line characteristics is only available at the later stages of a
CLD process as earlier CLD screens are largely conducted in unfed, low-volume vessels/plates.
Therefore, due to this and the lack of high-throughput analytical technologies, early stage CLD selection
decisions have often been made solely on product concentration. Furthermore, as cells are largely grown
in static environments and analysed during batch culture, it is therefore no surprise that the behaviour of
a cell line early in a CLD process may not reflect the behaviour of the cell line in a final production
process in which parameters such as nutrient feed, pH, pCO2 and dissolved oxygen tension (DOT) are
tightly controlled (Porter et al 2010a; Porter et al 2010b). Significant efforts have therefore been made to
introduce high-throughput fed-batch miniaturised cell cultivation screens that are more predictive of cell
line performance in a bioreactor. Examples include TubeSpin bioreactors (De Jesus et al 2004),
microbioreactors in various multi-well plate formats, which can be combined with non-invasive fluorescent
sensor technology for monitoring dissolved oxygen (DO) and pH (Chen et al 2009), and small-scale
bioreactor systems with bioprocess control such as the Pall™ Micro24® MicroReactor system and the
ambr™ micro bioreactor from TAP biosystems®. The application of high-throughput methods to quantify
5
www.fujifilmdiosynth.com
other characteristics such as product quality (Doherty et al, in press) and cellular density/viability (Wang
et al 2007) also hold great promise in the development of more effective CLD screens.
Traditional transfection, selection, cloning and screening methods such as those, which include
limiting dilution methods, are time consuming and labour intensive. Therefore, there has been an
increasing use of efficient automated cell screening systems (Browne and Al-Rubeai 2007), such as
fluorescence-activating cell sorting (FACS), the ClonePix™ system (Molecular Devices), the LEAP™
system (Cyntellect), the CellCelector system (Aviso), and the CloneSelect™ Imager (Molecular Devices).
The introduction of these, along with liquid handling robots can increase the number of cell lines that can
be handled and assessed in later screens and when compared to manual processing have been reported
to improve CLD project capacity up to three-fold (Lingren et al 2009).
Another important cell line characteristic is cell line stability; regulators regard this as a cell that
retains constant product quality (e.g. glycosylation profile) for extensive periods of culture (the period
required to scale-up to production volume) beyond the production of a working cell bank (ICH Q5D).
However, there also remains a commercial consequence and regulatory concern if there are substantial
changes in growth or productivity characteristics over a stability study. Although we are gaining an
increased understanding of the molecular basis of cell line instability (Chusainow et al 2009; Kennard et
al 2009b; Kim and Lee 1999; Kim et al 1998; Kim et al 2011; Paredes et al 2013), there still remains little
understanding of the cellular mechanisms that stimulate cell line instability during prolonged cell culture.
A greater understanding of the mechanisms involved would enable possible intervention strategies to be
implemented and allow the early prediction of cell line instability (Bailey et al 2012; Dorai et al 2011;
Osterlehner et al 2011).
Rapid screening of lead candidates by high-yielding transient gene expression
systems
Stable expression will continue to be used for the production of gram to kilogram quantities of
recombinant proteins in mammalian cells. However, the time and expense to establish, characterise and
optimise stable expression systems is considerable. To minimise preclinical development time, there is
often the need to produce milligrams to grams of representative product in a short time period to fuel
early development activities. Therefore, transient gene expression (TGE) systems are increasingly
becoming an attractive option for the rapid production of pre-clinical material. The key difference between
transient production systems and stable expression systems is the lack of stable gene integration into the
host cell genome and subsequent cell clone screening/isolation applied to the former, allowing product to
be produced in weeks rather than months.
Traditionally, HEK293 has been the host cell line of choice for TGE as they have been generally
higher yielding than CHO cell lines (Baldi et al 2007). However, the product quality of product produced
from these two systems differs (van den Nieuwenhof et al 2000; Ye et al 2009). Therefore CHO cells are
the preferred host when producing recombinant proteins for the pre-clinical assessment of lead candidate
6
www.fujifilmdiosynth.com
therapeutics. As a result, effective strategies to provide scalable high yielding CHO-based expression
systems are being sought. However, such approaches are typically complex with regard to the numerous
factors that have been shown to influence TGE process yield.
Critical to improvements in TGE has been the implementation of optimised transfection methods
using either calcium phosphate (Batard et al 2001; Grosjean et al 2002; Grosjean et al 2006), cationic
lipids (lipofection) (Felgner et al 1987; Liu et al 2008; Rosser et al 2005), cationic polymers such as PEI
(Bertschinger et al 2008; Boussif et al 1995; Godbey et al 2000; Thompson et al 2012), or large scale
®
electroporation using the MaxCyte transfection system. Due to its effectiveness and high efficiency, it is
PEI that has attracted the most research, and high-yielding transfection methodologies scalable to 10 L
working volume have been described (Ye et al 2009). However, future developments in nanotechnology
to produce novel polymers for gene delivery hold great promise (Park and Kim 2012). Other process
control parameters that have proven successful include reducing the culture temperature (Galbraith et al
2006), the addition of extrinsic modifiers of expression, e.g. insulin-like growth factor (Galbraith et al
2006), microtubule disrupting anti-mitotic agents such as nocodazole (Tait et al 2004), and histone
deactetylase inhibitors (HDACi) such as sodium butyrate and valproic acid (Backliwal et al 2008;
Wulhfard et al 2010).
A significant challenge for TGE is rapid plasmid copy number dilution during cell division, which
results in a significant reduction in recombinant protein titers at the end stages of the process. The
development of episomal systems to maintain plasmid copy number after transfection has therefore
proven beneficial in improving TGE yields. Such systems incorporate viral elements, such as expression
of Epstein-barr virus nuclear antigen 1 (EBNA-1) with a plasmid(s) containing an Epstein-barr virus latent
origin of replication (OriP) to facilitate plasmid maintenance (Muller et al 2007). Elements from murine
polyomavirus can also be added to this expression technology to allow plasmid replication and
maintenance (Kunaparaju et al 2005).
Stably transfected pools for rapid production of large quantities of preclinical
material
As TGE systems have been typically low yielding an alternative strategy for rapid protein production of
preclinical material is to use transfected pools. Transfected pools refer to the heterogenous population of
host cells that have been transfected with a recombinant expression vector and can survive selective
pressure. Stable transfected pools are used to generate large amounts of pre-clinical material quickly and
clonal production lines can be isolated from these populations (Birch and Racher 2006). As stable
transfection pools exist as a heterogeneous population of individual cell lines with a range of expression
rates, the expression levels of transfected pools are usually lower than clonal stable cell lines and will
lose productivity over time as low producers with higher growth rates take over the population. However,
-1
titres exceeding 1 g L have been reported (Girod et al 2012). In comparison with TGE, transfected pools
7
www.fujifilmdiosynth.com
are easily scalable up to 200 L, generating milligrams to grams of recombinant protein rapidly and with
product quality attributes similar to those expressed by clonal cell lines (Ye et al 2010).
Advances in cell culture media development
Cell culture media for mammalian cells has improved significantly since the development of the first
approved biologic therapeutics in the 1980s. Initially cell culture processes required the presence of
serum, however, regulatory concerns over a high risk of adventitious agents has resulted in animal
component free (ACF) processes becoming an industry standard. All culture processes during CLD e.g.
transfection, selection, limiting dilution, cryopreservation, and recovery can now use ACF methods. In
addition to the generation of ACF processes, general improvements in culture media formulation over
recent years has led to significant enhancement in overall production processes titres across the industry
(Huang et al 2010; Wurm 2004). Initially animal derived and then recombinant proteins such as albumin,
transferrin, and insulin replaced serum. Hydrolysates were also generally added as a feed providing a
source of soluble amino acids, peptides, vitamins, and essential elements for cell growth. Today,
chemically defined, animal component free (CD-ACF) media and feeds, which contain only a carbon
source, amino acids, vitamins, and trace elements, are becomingly increasingly popular as they minimise
lot-to-lot variation in fed-batch performance and simplify downstream processing by incorporating fewer
contaminants.
The introduction of novel expression technologies
The most common gene expression systems used in industry today continue to be metabolic selection
techniques
using
either
the
dihydrofolate
reductase
(DHFR)
–based
methotrexate
(MTX)
selection/amplification systems or glutamine synthetase (GS)-based methionine sulfoximine (MSX)
selection (Figure 2).
Figure 2. Comparison of glutamine synthetase (GS)-based methionine sulfoximine (MSX)
selection (A) and dihydrofolate reductase (DHFR) –based methotrexate (MTX) selection (B)
systems.
CHO-DG44 and CHO-DUXB11 cell lines deficient in DHFR activity have been widely used for
stable expression with an exogenous DHFR gene via selection in hypoxanthine, and thymidine (HT)
minus medium. Historically, CLD processes utilising the DHFR expression system require one or several
rounds of gene amplification to improve productivity (Zettlmeissl et al 1988). These amplification steps
involve a gradual increase in MTX treatment, with surviving cells typically containing several hundred or a
thousand recombinant gene copies (Wurm et al 1986). However, these amplification steps lead to a
8
www.fujifilmdiosynth.com
longer CLD timeline with each amplification step taking three to four weeks. Furthermore, the use of MTX
amplification introduces a genetic stability risk due to loss of gene copies after the removal of MTX
selection pressure (Kim and Lee 1999). Therefore, industrial CLD platforms utilising DHFR expression
systems typically look to reduce or remove these amplification steps. Another limitation to using the
DHFR expression system is that the cell lines that facilitate its expression (DG44 and DUXB11 cell lines)
typically display comparatively poor bioprocess characteristics when compared to other CHO-K1 cell
lines utilizing GS expression technology (Hu et al, in press; Kennard et al 2009a). Therefore, the
introduction of CHO-K1 cell lines with a DHFR gene disrupted using zinc finger nuclease (ZFN)
technology (Santiago et al 2008) may prove an attractive alternative. Nevertheless, the DHFR expression
system has been utilised in a number of industrial CLD processes to identify cell lines capable of
producing > 10 g L-1 in fed-batch production processes (Huang et al 2010).
In contrast, the GS system uses the GS gene as a dominant selection marker. Without glutamine
in the growth medium, the GS gene is essential for survival. It is reported that major advantage of the GS
system is that it offers far reduced development times, as it does not require amplification steps to obtain
high producing cell lines. However, CHO cells have endogenous GS activity and can survive in medium
lacking glutamine. For the selection system to be successful a GS inhibitor, MSX, must be added so that
only transfectants with high-level recombinant GS activity can survive. Therefore, cell line instability
remains an issue for GS expression systems, especially after MSX removal (Jun 2006). The development
of GS negative CHO cell lines may help to address this stability issue whilst also promising shorter time
lines for cell line generation (Fan et al 2012).
To achieve high levels of gene expression, vectors usually have strong promoters such as the
cytomegalovirus (CMV) promoter to drive high-level messenger RNA transcription (mRNA) of the
recombinant product (Cacciatore et al 2010) and weak promoters (e.g. SV40) to drive expression of the
metabolic selection marker (Birch and Racher 2006). Codon optimisation (Kalwy et al 2006), and signal
sequence optimisation (Kober et al 2013) has also been shown to accelerate mRNA processing and
improve secretion. Other developments in mammalian gene expression technology include the use of
genetic elements that enhance and stabilise transgene expression (Kwaks and Otte 2006). However,
results have been mixed as to the functionality of these elements and they may increase the proportion of
stable transfectants with higher specific productivity (Zahn-Zabal et al 2001) rather than create a step
change increase. The use of site-specific integration sites has also promised more predictable protein
production (Wirth et al 2007). However, the specific productivity of cell lines utilising this technology has
so far been moderate and more active transcriptional “hot-spots” need to be identified (Agrawal and Bal
2012).
The provision of “tailor-made” cell lines
Current CLD platforms typically rely on processes that are lengthy and require large-scale screening of
clonal derivatives in order to identify the most productive cell line. Although this approach has proven
9
www.fujifilmdiosynth.com
successful, innate or introduced (i.e. from recombinant DNA) genetic heterogeneity is harnessed
effectively but blindly, and crucial cell line characteristics such as correct product processing are typically
only screened for during the later stages of the CLD process. Therefore, directed genetic or metabolic
engineering approaches hold great promise in cutting CLD timelines and improving the quality of cell
lines that are progressed during CLD via optimisation of specific productivity, product processing and cell
proliferation.
Consequently, a great deal of effort has been invested in engineering key cell line characteristics.
Various genetic engineering strategies have been employed to improve product titres. These include
delaying apoptosis, increasing the rate of proliferation, enhancing protein-processing capacity, and
increasing metabolic efficiency (Dietmair et al 2011). However, the outcomes of these manipulations are
mixed, with only a few studies reporting significant improvements in productivity. Nevertheless, recent
efforts to improve TGE titre, have proven successful (e.g. overexpression of XBP1 and ERO1-Lα; Cain et
al 2013). Indeed the lack of functional screening applied to TGE systems may make them a more suitable
candidate for cell engineering than stable expression systems. This is because the transfection of large
amounts of DNA into heterogeneous cell populations is more likely to create bottlenecks within the MAb
synthesis and secretion pathway (Mason et al 2012).
Figure 3. The main glycoforms of MAbs produced in CHO cells are close to human ones and
recently glycol-engineering has allowed the production of MAbs with increased effector function.
The use of engineered cell lines for the development of “biosuperior” MAbs with enhanced
pharmacological properties has shown great promise (Figure 3), with at least 16 glycoengineered MAbs
having entered clinical trials (Beck and Reichert 2012). The main target for glycoengineering has been to
increase ADCC activation by either reducing or removing core fucosylation of N-linked oligosaccharides.
10
www.fujifilmdiosynth.com
One approach has been to knockout intrinsic α-1,6-fucosyltransferasse (FUT8) enzyme activity, which is
responsible for core fucosylation (POTELLIGENT
®
technology; Yamane-Ohnuki et al 2004).
Other
recombinant DNA-based glycoengineering approaches have been achieved through overexpression of
heterologous β-1,4-N-acetylglucosaminyltransferase III (GnT-III), GnT-III adds a bisecting GlcNAc to an
®
oligosaccharide, which sterically blocks core-fucosylation (GlycoMAb ; Umana et al 1999), and
overexpression of heterologous GDP-6-deoxy-D-lyxo-4-hexulose reductase (GlymaxX®; von Horsten et al
2010). A different approach to produce glycol-engineered MAbs is to enhance CDC activity by, for
example, feeding uridine, manganese chloride, and galactose during a fed-batch process, which
promotes antibody galactosylation and therefore enhances CDC activity (Gramer et al 2012).
A key enabling technology for cell line engineering has been the introduction of gene knockout
out technologies such as meganucleases (Kramer et al 2010), transcription activator-like effector
nucleases (TALENs) (Sun and Zhao 2013), and zinc finger nucleases (ZFNs) (Sun et al 2012). These
have provided an efficient yet stringent approach for the development of ‘tailor-made’ cell lines, which
have been previously too laborious or difficult to generate. A major barrier to such an approach in CHO
cells has been the lack of publicly available genome data, however, the recent release of the genomic
sequence of a CHO-K1 cell line (Hammond et al 2012; Xu et al 2012) allows these approaches to be
rationally designed. Another technology benefitting from the release of the CHO-K1 genome is that of
microRNA (miRNA) engineering. miRNAs are single-stranded, non-coding RNA (18-25 nucleotides in
length), which can regulate global gene expression at the post-transcriptional level by mRNA cleavage
and/or translation repression. The use of miRNAs for CHO cell engineering offers an attractive alternative
to other more traditional methods due to regulation of multiple targets, easy introduction into cells, and
reduction of metabolic burden (Muller et al 2008).
To date, cell engineering strategies have typically analysed the effect of only a few engineering
manipulations on a single functional attribute (e.g. product titre) and with one specific recombinant
therapeutic. Given that even the expression of seemingly “easy-to-express” molecules such as MAbs can
vary extensively (Bentley et al 1998), ideal glycation patterns for a given therapeutic can vary (e.g.
terminal galactosylation of Rituximab; Jefferis, 2005), and multiple pathways may need to be engineered
for efficacious results (Seth et al 2007), bioprocesses of the future may require the availability of a panel
cell lines with (multiple) engineered functional attributes that are “tailor-made” to a particular recombinant
therapeutic. Furthermore, whereas cellular engineering approaches aim to make disruptive step change
advances in cellular performance, it has been the utilisation of rapid clone isolation and screening
technologies that have to date provided the identification of optimal CHO cell phenotypes. However, the
utilisation of directed evolution approaches to harness and control the phenotypic heterogeneity in
parental host cell populations offers exciting new opportunities for future cell engineering strategies
(Majors et al 2009).
11
www.fujifilmdiosynth.com
Systems biology: The road to prediction?
A barrier to the implementation of novel technologies within CLD is the incomplete understanding of how
we can predict or improve during CLD key production process characteristics such as high cell-specific
productivity, correct product processing and rapid cell proliferation. Indeed, whilst we may have a detailed
understanding of certain biological processes (e.g. apoptosis), our knowledge of how such networks and
individual components interact within a complex integrated system and give rise to a given phenotype, is
limited.
To enable implementation of superior bioprocesses, we first need a better understanding of how
complex cellular phenotypes are controlled. It is thought that systems biology (the combination of high
information content –omic technologies, bioinformatics data organisation, and mathematical modelling)
will allow us to gain such knowledge. The information gained from these studies allows us to implement
engineering strategies based on knowledge of the biological networks that determine the functional
competence of mammalian cell factories (O’Callaghan and James 2008). This possibility has triggered a
range of studies aimed at characterising the functional basis of a number of process characteristics
(Dietmair et al 2012a). However, whilst these studies have provided a wealth of information about the
cellular changes associated with a given production characteristic the majority of studies have not yet
been translated into an improved phenotype. This would suggest that several limitations need to be
overcome before –omics approaches can be reliably utilised, these include technical (e.g. measurement
bias and limited coverage), biological (e.g. high variability and complexity), experimental (e.g. small
contrast and use of single –omics technology), and interpretational (e.g. lack of computational methods)
difficulties (Dietmair et al 2012a).
Conclusions
-1
Although the current platforms for CLD can robustly identify cell lines capable of producing multi g L
quantities of MAb product there remains a need for systems that rapidly and reliably produce these as
well as next generation biopharmaceuticals with a defined product quality and high product titre. The
modification of existing CLD strategies by implementing new expression systems, incorporating new
technologies to enhance expression stability and product quality, and the introduction of large-scale TGE
are all approaches that will help address this problem. Importantly, the challenge remains how to reliably
incorporate these recent technological advances into CLD processes. It is thought that a better
understanding of complex cellular phenotypes through the use of systems biology will allow us to
implement these strategies in a more rational manner; however, meaningful interpretation of such studies
in mammalian cells has proven difficult. Previous -omics based studies have had their limitations.
However, it is thought that in this new era of CHO genomics (Lewis et al 2013; Xu et al 2011) the recent
availability of relevant informatics tools/resources to aid CHO cell re-design (Hammond et al 2012;
Hyduke et al 2013; Lewis et al 2012), coupled to multi-omic approaches (Dietmair et al 2012b), will allow
such approaches to be widely applicable.
12
www.fujifilmdiosynth.com
References
Agrawal V, Bal M (2012) Strategies for rapid production of therapeutic proteins in mammalian cells.
BioProcess Int 10: 32-48.
Backliwal G, Hildinger M, Kuettel I, Delegrange F, Hacker DL, Wurm FM (2008) Valproic acid: a viable
alternative to sodium butyrate for enhancing protein expression in mammalian cell cultures. Biotechnol
Bioeng 101: 182-189.
Bailey LA, Hatton D, Field R, Dickson AJ (2012) Determination of Chinese hamster ovary cell line stability
and recombinant antibody expression during long-term culture. Biotechnol Bioeng 109: 2093-2103.
Baldi L, Hacker DL, Adam M, Wurm FM (2007) Recombinant protein production by large-scale transient
gene expression in mammalian cells: state of the art and future perspectives. Biotechnol Lett 29: 677-684.
Batard P, Jordan M, Wurm F (2001) Transfer of high copy number plasmid into mammalian cells by
calcium phosphate transfection. Gene 270: 61-68.
Beck A, Reichert JM (2012) Marketing approval of mogamulizab: A triumph for glycol-engineering. mAbs
4: 419-425.
Bentley KJ, Gewert R, Harris WJ (1998) Differential efficiency of expression of humanized antibodies in
transiently transfected mammalian cells. Hybridoma 17: 559-567.
Bertschinger M, Schertenleib A, Cevet J, Hacker DL, Wurm FM (2008) The kinetics of polyethyleniminemediated transfection in suspension cultures by Chinese hamster ovary cells. Mol Biotechnol 40: 136-143.
Birch JR, Racher AJ (2006) Antibody production. Adv Drug Deliv Rev 58: 671-685.
Boussif O, Lezoualc’h F, ZantaMA, Mergny MD, Scherman D, Demeneix B, Behr JP (1995) A versatile
tool for gene and oligonucleotide transfer into cells in culture and in vivo: polyethylenimine. Proc Natl
Acad Sci USA 92: 7297-7301.
Browne SM, Al-Rubeai M (2007) Selection methods for high-producing mammalian cell lines. Trends
Biotechnol 25: 425-432.
Cacciatore JJ, Chasin LA, Leonard EF (2010) Gene amplification and vector engineering to achieve rapid
and high-level therapeutic protein production using the Dhfr-based CHO selection system. Biotechnol
Adv 28: 673-681.
Cain K, Peters S, Hailu H, Sweeney B, Stephen P, Heads J, Sarkar K, Ventom A, Page C, Dickson A
(2013) A CHO cell line engineered to express XBP1 and ERO1-Lα has increased levels of transient
protein expression. Biotechnol Prog 29: 697-706.
Chen A, Chitta R, Chang D, Amanullah A (2009) Twenty-four well plate miniature bioreactor system as a
scale-down model for cell culture process development. Biotechnol Bioeng 102: 148-160.
Chusainow J, Yang Y, Yeo JHM, Toh PC, Asvadi P, Wong NSC, Yap MGS (2009) A study of monoclonal
antibody-producing CHO cell lines: What makes a stable high producer? Biotechnol Bioeng 102: 11821196.
de Jesus MJ, Girard P, Bourgeois M, Baumgartner G, Jacko B, Amstutz H, Wurm FM (2004) TubeSpin
satellites: a fast track approach for process development with animal cells using shaking technology.
Biochem Eng J 17: 217-223.
13
www.fujifilmdiosynth.com
Dietmair S, Nielsen LK, Timmins NE (2011) Engineering a mammalian super producer. J Chem Technol
Biotechnol 86: 905-914.
Dietmair S, Nielsen LK, Timmins NE (2012a) Mammalian cells as biopharmaceutical production hosts in
the age of omics. Biotechnol J 7: 75-89.
Dietmair S, Hodson MP, Quek LE, Timmins NE, Gray P, Nielsen LK (2012b) A multi-omic analysis of
recombinant protein production in Hek293 cells. PLoS One 7: e43394.
Doherty M, Bones J, McLoughlin N, Telford JE, Harmon B, Defelippis MR, Rudd PM (in press) An
automated robotic platform for rapid profiling oligosaccharide analysis of monoclonal antibodies directly
from cell culture. Anal Biochem.
Dorai H, Corisdeo S, Ellis D, Kinney C, Chomo M, Hawley-Nelson P, Moore G, Betenbaugh M, Ganguly
S (2011) Early prediction of instability of chinese hamster ovary cell lines expressing recombinant
antibodies and antibody-fusion proteins. Biotechnol Bioeng 109: 1016-1030.
Fan L, Kadura I, Krebs LE, Hatfielld CC, Shaw MM, Frye CC (2012) Improving the efficiency of CHO cell
line generation using glutamine synthetase gene knockout cells. Biotechnol Bioeng 109: 1007-1015.
Felgner PL, Gadek TR, Holm M, Roman R, Chan HW, Wenz M, Northrop JP, Ringold GM, Danielsen M
(1987) Lipofection: a highly efficient, lipid-mediated DNA-transfection procedure. Proc Natl Acad Sci USA
84: 7413-7417.
Galbraith DJ, Tait AS, Racher AJ, Birch JR, James DC (2006) Control of culture environment for
improved polyethylenimine-mediated transient production of recombinant monoclonal antibodies by CHO
cells. Biotechnol Prog 22: 753-762.
Girod P-A (2012) Rapid production of functional proteins of a combinatorial IgG library in CHO cells.
BioProcess Int 10: 58-61.
Godbey WT, Barry MA, Saggau P, Wu KK, Mikos AG (2000) Poly(ethylenimine)-mediated transfection: a
new paradigm for gene delivery. J Biomed Mater Res 51: 321-328.
Gramer MJ, Eckblad JJ, Donahue R, Brown J, Shultz C, Vickerman K, Priem P, van den Bremer ET,
Gerritsen J, van Berkel PH (2011) Modulation of antibody galactosylation through fedding of uridine,
manganese chloride, and galactose. Biotechnol Bioeng 108: 1591-1602.
Grosjean F, Batard P, Jordan M, Wurm FM (2002) S-phase synchronized CHO cells show elevated
transfection efficiency and expression using CaPi. Cytotechnology 38: 57-62.
Grosjean F, Bertschinger M, Hacker DL, Wurm FM (2006) Multiple glycerol shocks increase the calcium
phosphate transfection of non-synchronized CHO cells. Biotechnol Lett 28: 1827-1833.
Hammond S, Kaplarevic M, Borth N, Betenbaugh MJ, Lee KH (2012) Chinese hamster genome
database: an online resource for the CHO community at www.CHOgenome.org. Biotechnol Bioeng 109:
1353-1356.
Hu Z, Guo D, Yip SS, Zhan D, Misaghi S, Joly JC, Snedecor BR, Shen AY (in press) Chinese hamster
ovary (CHO) K1 host cells enables stable cell line development for antibody molecules which are difficult
to express in DUXB11-derived dihydrofolate reductase (DHFR) deficient host cell. Biotechnol Prog.
Huang Y-M, Hu W, Rustandi E, Chang K, Yusuf-Makagiansar H, Ryll T (2010) Maximizing productivity of
CHO cell-based fed-batch culture using chemically defined media conditions and typical manufacturing
equipment. Biotechnol Prog 26: 1400-1410.
14
www.fujifilmdiosynth.com
Hyduke DR, Lewis NR, Palsson BO (2013) Analysis of omics data with genome-scale models of
metabolism. Mol Biosyst 9: 167-174.
Jayapal KP, Wlaschin KF, Hu W-S, Yap MGS (2007) Recombinant protein therapeutics from CHO cells –
20 years and counting. Chem Eng Prog 103: 40-47.
Jefferis R (2005) Glycosylation of recombinant antibody therapeutics. Biotechnol. Prog. 21:11-16.
Jun SC, Kim MS, Hong HJ, Lee GM (2006) Limitations to the development of humanized antibody
producing Chinese hamster ovary cells using glutamine synthetase-mediated gene amplification.
Biotechnol Prog 22: 770-780.
Kalwy S, Rance J, Young R (2006) Toward more efficient protein expression: keep the message simple.
Mol Biotechnol 34: 151-156.
Kao FT, Puck TT (1968) Genetics of somatic mammalian cells, VII. Induction and isolation of nutritional
mutants in Chinese hamster cells. Proc Natl Acad Sci USA 60: 1275-1281.
Kennard ML, Goosney DL, Monteith D, Roe S, Fischer D, Mott J (2009a) Auditioning of CHO host cell
lines using the artificial chromosome expression (ACE) technology. Biotechnol Bioeng 104: 526-539.
Kennard ML, Goosney DL, Monteith D, Zhang L, Moffat M, Fischer D, Mott J (2009b) The generation of
stable, high MAb expressing CHO cell lines based on the artificial chromosome expression (ACE)
technology. Biotechnol Bioeng 104: 540-553.
Kim SJ, Lee GM (1999) Cytogenetic analysis of chimeric antibody-producing CHO cells in the course of
dihydrofolate reductase-mediated gene amplification and their stability in the absence of selective
pressure. Biotechnol Bioeng 64: 741-749.
Kim NS, Kim SJ, Lee GM (1998) Clonal variability within dihydrofolate reductase-mediated gene
amplified Chinese hamster ovary cells: Stability in the absence of selective pressure. Biotechnol Bioeng
60: 679-688.
Kim M, O’Callaghan PM, Droms KA, James DC (2011) A mechanistic understanding of production
instability in CHO cell lines expressing recombinant monoclonal antibodies. Biotechnol Bioeng 108: 24342446.
Kober L, Zehe C, Bode J (2013) Optimized signal peptides for the development of high expressing CHO
cell lines. Biotechnol Bioeng 110: 1164-1173.
Kramer O, Klausing S, Noll T (2010) Methods in mammalian cell line engineering: from random
mutagenesis to sequence-specific approaches. Appl Microbiol Biotechnol 88: 425-436.
Kunaparaju R, Liao M, Sunstrom NA (2005) Epi-CHO, an episomal expression system for recombinant
protein production in CHO cells. Biotechnol Bioeng 91: 670-671.
Kwaks TH, Otte AP (2006) Employing epigenetics to augment the expression of therapeutic proteins in
mammalian cells. Trends Biotechnol 24: 137-142.
Lewis NE, Nagarajan H, Palsson BO (2012) Constraining the metabolic genotype-phenotype relationship
using a phylogeny of in silico methods. Nat Rev Microbiol 10: 291-305.
Lewis NE, Liu X, Li Y, Nagarajan H, Yerganian G, O’Brien E, Bordbar A, Roth AM, Rosenbloom J, Bian C,
Xie M, Chen W, Li N, Baycin-Hizal D, Latif H, Forster J, Betenbaugh MJ, Famili I, Xu X, Wang J, Palsson
BO (2013) Genomic landscapes of Chinese hamster ovary cell lines as revealed by the Cricetulus
griseus draft genome. Nat Biotechnol 31: 759-765.
15
www.fujifilmdiosynth.com
Lingren K, Salmen A, Lundgren M, Bylund L, Ebler A, Faldt E, Sorvick L, Fenge C, Skoging-Nyberg U
(2009) Automation of cell line development. Cytotechnology 59: 1-10.
Liu C, Dalby B, Chen W, Kilzer JM, Chiou HC (2008) Transient transfection factors for high-level
recombinant protein production in suspension cultured mammalian cells. Mol Biotechnol 39: 141-153.
Majors BS, Chiang GG, Betenbaugh MJ (2009) Protein and genome evolution in mammalian cells for
biotechnology applications. Mol Biotechnol 42: 216-223.
Mason M, Sweeney B, Cain K, Stephens P, Sharfstein ST (2012) Identifying bottlenecks in transient and
stable production of recombinant monoclonal-antibody sequence variants in Chinese hamster ovary cells.
Biotechnol Prog 28: 846-855.
Muller N, Derouazi M, van Tilborgh F, Wulhfard S, Hacker DL, Jordan M, Wurm FM (2007) Scalable
transient gene expression in Chinese hamster ovary cells in instrumented and non-instrumented
cultivation systems. Biotechnol Lett 29: 703-711.
Muller D, Katinger H, Grillari J (2008) MicroRNAs as targets for engineering of CHO cell factories. Trends
Biotechnol 26: 359-365.
O’Callaghan PM, James DC (2008) Systems biotechnology of mammalian cell factories. Brief Funct
Genomic Proteomic 7: 95-110.
Osterlehner A, Silke S, Gopfert U (2011) Promoter methylation and transgene copy numbers predict
unstable protein production in recombinant chinese hamster ovary cell lines. Biotechnol Bioeng 108:
2670-2681.
Paredes V, Park JS, Jeong Y, Yoon J, Baek K (2013) Unstable expression of recombinant antibody
during long-term culture of CHO cells is accompanied by histone H3 hypoacetylation. Biotechnol Lett 35:
987-993.
Park J, Kim WJ (2012) Current status of gene delivery: spotlight on nanomaterial-polymer hybrids. J Drug
Target 20: 648-666.
Porter AJ, Dickson AJ, Racher AJ (2010a) Strategies for selecting recombinant CHO cell lines for cGMP
manufacturing: realizing the potential in bioreactors. Biotechnol Prog 26: 1446-1454.
Porter AJ, Racher AJ, Preziosi R, Dickson AJ (2010b) Strategies for selecting recombinant CHO cell lines
for cGMP manufacturing: Improving the efficiency of cell line generation. Biotechnol Prog 26: 1455-1464.
Puck TT, Cieciura SJ, Robinson A (1958) Genetics of somatic mammalian cells. III. Long-term cultivation
of euploid cells from human and animal subjects. J Exp Med 108: 945-956
Rosser MP, Xia W, Hartsell S, McCaman M, Zhu Y, Wang S, Harvey S, Bringmann P, Cobb RR (2005)
Transient transfection of CHO-K1-S using serum-free medium in suspension: a rapid mammalian protein
expression system. Protein Expr Purif 40: 237-2243.
Santiago Y, Chan E, Liu PQ, Orlando S, Zhang L, Urnov FD, Holmes MC, Guschin D, Waite A, Miller JC,
Rebar EJ, Gregory PD, Klug A, Collingwood TN (2008) Targeted gene knockout in mammalian cells by
using engineered zinc-finger nucleases. Proc Natl Acad Sci USA 105: 5809-5814.
Seth G, Charaniya S, Wlaschin KF, Hu WS (2007) In pursuit of a super producer-alternative paths to high
producing recombinant mammalian cells. Curr Opin Biotechnol 18: 557-564.
16
www.fujifilmdiosynth.com
Sun N, Abil Z, Zhao H (2012) Recent advances in targeted genome engineering in mammalian systems.
Biotechnol J 7: 1074-1087.
Sun N, Zhao H (2013) Transcription activator-like effector nucleases (TALENs): a highly efficient and
versatile tool for genome editing. Biotechnol Bioeng 110: 1811-1121.
Tait AS, Brown CJ, Galbraith DJ, Hines MJ, Hoare M, Birch JR, James DC (2004) Transient production of
recombinant proteins by Chinese hamster ovary cells using polyethyleneimine/DNA complexes in
combination with microtubule disrupting anti-mitotic agents. Biotechnol Bioeng 20: 707-721.
Thompson BC, Segarra CR, Mozley OL, Daramola O, Field R, Levison PR, James DC (2012) Cell line
specific control of polyethylenimine-mediated transient transfection optimized with “Design of experiments”
methodology. Biotechnol Prog 28: 179-187.
Umana P, Jean-Mairet J, Moudry R, Amstutz H, Bailey JE (1999) Engineered glycoforms of an
antineuriblastoma IgG1 with optimized antibody-dependent cellular cytotoxic activity. Nat Biotechnol 17:
176-180.
Urlaub G, Chasin LA (1980) Isolation of Chinese hamster mutants deficient in dihydrofolate reductase
activity. Proc Natl Acad Sci USA 77: 4216-4220.
Urlaub G, Kas E, Carothers AM, Chasin LA (1983) Deletion of the diploid dihydrofolate reductase locus
from cultured mammalian cells. Cell 33: 405-412.
van den Nieuwenhof IM, Koistinen H, Easton RL, Koistinen R, Kamarainen M, Morris HR, van Die I,
Seppala M, Dell A, van den Eijnden DH (2000) Recombinant glycodelin carring the same type of glycan
structures as contraceptive glycodelin-A can be produced in human kidney 293 cells but not in chinese
hamster ovary cells. Eur J Biochem 267: 4753-4762.
von Horsten HH, Ogorek C, Blanchard V, Demmler C, Giese C, Winkler K, Kaup M, Berger M, Jordan I,
Sandig V (2010) Production of non-fucosylated antibodies by co-expression of heterologous GDP-6deoxy-D-lyxo-4-hexulose reductase. Glycobiology 20: 1607-1618.
Walsh G (2010) Biopharmaceutical benchmarks 2010. Nat Biotechnol 28: 917-924.
Wang Z, Kim MC, Marquez M, Thorsen T (2007) High-density microfluidic arrays for cell cytotoxicity
analysis. Lab Chip 7: 740-745.
Wirth D, Gama-Norton L, Riemer P, Sandhu U, Schucht R, Hauser H (2007) Road to precision:
recombinase-based targeting technologies for genome engineering. Curr Opin Biotechnol 18: 411-419.
Wulhfard S, Baldi L, Hacker DL, Wurm F (2010) Valproic acid enhances recombinant mRNA and protein
levels in transiently transfected Chinese hamster ovary cells. J Biotechnol 148: 128-132.
Wurm FM, Gwinn KA, Kingston RE (1986) Inducible overproduction of the mouse c-myc protein in
mammalian cells. Proc Natl Acad Sci USA 83: 5414-5418.
Wurm FM (2004) Production of recombinant protein therapeutics in cultivated mammalian cells. Nat
Biotechnol 22: 1393-1398.
Xu X, Nagarajan H, Lewis NE, Pan S, Cai Z, Liu X, Chen W, Xie M, Wang W, Hammond S, Anderson MR,
Neff N, Passarelli B, Koh W, Fan HC, Wang J, Gui Y, Lee KH, Betenbaugh MJ, Quake SR, Famili I,
Palsson BO, Wang J (2011) The genomic sequence of the Chinese hamster ovary (CHO)-K1 cell line.
Nat Biotechnol 29: 735-741.
17
www.fujifilmdiosynth.com
Yamane-Ohnuki N, Kinoshita S, Inoue-Urakubo M, Kusunoki M, Iida S, Nakano R, Wakitani M, Niwa R,
Sakurada M, Uchide K, Shitara K, Satoh M (2004) Establishment of FUT8 knockout Chinese hamster
ovary cells: an ideal host cell line for producing completely defucosylated antibodies with enhanced
antibody-dependent cellular cytotoxicity. Biotechnol Bioeng 87: 614-622.
Ye J, Kober V, Tellers M, Naji Z Salmon P, Markusen JF (2009) High-level protein expression in scalable
CHO transient transfection. Biotechnol Bioeng 103: 542-551.
Ye J, Alvin K, Latif H, Hsu A, Parikh V, Whitmer T, Tellers M, de la Cruz Edmonds MC, Ly J, Salmon P,
Markusen JF (2010) Rapid protein production using CHO stable transfection pools. Biotechnol Prog 26:
1431-1437.
Zahn-Zabal M, Kobr M, Girod PA, Imhof M, Chatellard P, de Jesus M, Wurm F, Mermod N (2001)
Development of stable cell lines for production or regulated expression using matrix attachment regions.
J Biotechnol 87: 29-42.
Zettlmeissl G, Wirth M, Hauser H, Kupper HA (1988) Efficient expression system for human antithrombin
III in baby hamster kidney cells. Behring Inst Mitt 82: 26-34.
18
www.fujifilmdiosynth.com
Figure legends
Figure 1. A schematic representation of a typical cell line development strategy
Figure 2. Comparison of glutamine synthetase (GS)-based methionine sulfoximine (MSX)
selection (A) and dihydrofolate reductase (DHFR) –based methotrexate (MTX) selection (B)
systems.
Figure 3. The main glycoforms of MAbs produced in CHO cells are close to human ones and
recently glycol-engineering has allowed the production of MAbs with increased effector function.
19