Ana Rita Martins Costa - core.ac.uk · Trago uma caixinha mágica, à qual recorro com frequência,...
Transcript of Ana Rita Martins Costa - core.ac.uk · Trago uma caixinha mágica, à qual recorro com frequência,...
Ana Rita Martins Costa
October 2012UM
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Expression and characterization ofa therapeutic monoclonal antibodyin mammalian cells
Universidade do Minho
Escola de Engenharia
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Doctoral dissertation for PhD degree inBiomedical Engineering
Supervisor:Professor Joana AzeredoCo-supervisor:Professor Mariana Henriques
Ana Rita Martins Costa
October 2012
Expression and characterization ofa therapeutic monoclonal antibodyin mammalian cells
Universidade do Minho
Escola de Engenharia
Para os meus Pais
“Success is not final, failure is not fatal: it is the courage to continue that counts”
O sucesso não é final, o fracasso não é fatal: é a coragem para continuar que conta.
Winston Churchill
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ACKNOWLEDGMENTS
Cheguei ao meu destino. A viagem foi longa e dura, mas valeu a pena. Olho para trás e traço
os caminhos percorridos, revejo os dias intensos, os desafios e as conquistas, as desilusões e as
alegrias. E vejo que não vim sozinha. Trago comigo companhia, e uma mala cheia de tesouros.
Trago um livro que consulto, quando estou numa encruzilhada, tem nas folhas palavras amigas,
tem ideias impensadas. Inclui mapas do caminho, incentiva à aventura, uma edição especial,
que faz crescer a cada leitura. Professora Joana
Trago um pequeno raio de sol, de luz intensa e generosa, que faz nascer da escuridão a
primavera harmoniosa. Tem o brilho da coragem, tem a cor da alegria, traz escondidos na sua
luz, uns pozinhos de magia. Professora Mariana
Trago um conjunto precioso e raro, de sabedoria e bondade, que mantenho bem guardado, num
cantinho recatado, para sempre admirar. Professora Rosário
Trago uma caixinha mágica, à qual recorro com frequência, transforma incertezas e
preocupações, em sorrisos, gargalhadas, histórias partilhadas e confidências.
Susana M., Paula, Dina, Sílvia P., Cláudia B., Melyssa, Sónia, Eva, Cristina, Isabel C.,
Isabel P., Joana C., Yun Lei, Pedro, Filipa, Patrícia e todos os colegas do LCCT
I bring chocolates of irish cream, with many flavors mixed within, a little wit, a touch of warmth,
joyfulness and even charm, but of them all my favorite is, the unexpected kindness they release.
Eoin, Li, Niaobh, Karina, Barbara, Jo, Tharmala, Jayne, Radka, Mark and Pauline. Larry and the
nice irish lady who once offered me pancakes on a bus stop, just because I was having a bad day
ACKNOWLEDGMENTS│
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Trago as cores da amizade, todas elas tão diferentes, pintam a tela da minha vida, com o pincel
da sua presença. Amélia, Elisa A., Roberto, Mariana, David, Inês, Cristina
Trago uma ave delicada, que ainda não sabe (receia) voar, tem forças escondidas, tem vontade
de cantar. Para já canta baixinho, alguns dos cantos sei de cor, partilhamos confidências,
trocamos o nosso melhor. A minha ave favorita, um dia vai arriscar, vai atirar-se ao vento, tenho
a certeza que irá voar. Elisa
Trago um postal antigo, que me acorda a memória, que me lembra a saudade, que me conta a
história, de olhos verdes que nunca julgaram, de gentileza e carinho, de tantos saberes que
resultaram da sua presença no meu caminho. Padrinho
Mas acima de tudo trago amor, um amor inigualável. Este guardado dentro de mim, no fundo do
meu ser, junto das minhas raízes, das minhas asas, e do amor que tenho para vos oferecer.
Os meus Pais, José e Rosa
É um facto curioso, este que noto ao chegar, os tesouros tornam a mala mais leve, em vez de a
carregar…
O trabalho apresentado nesta tese foi financiado pela Fundação para a Ciência e Tecnologia
(FCT), através da bolsa referência SFRH/BD/46660/2008.
O anticorpo monoclonal utilizado neste trabalho foi gentilmente cedido pela Biotecnol S.A.
(Lisboa, Portugal).
The authorization to evaluate the OSCARTM technology was gently conceded by the University of
Edinburgh.
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ABSTRACT
The advent of therapeutic recombinant proteins has revolutionized modern medicine. Since
the approval of recombinant insulin in 1982 to treat diabetes, many other recombinant proteins
have emerged for a diversity of previously incurable conditions. In these years, the manufacturing
processes have greatly evolved, but have also often disregarded product quality, an issue only
recently addressed and currently a major challenge in biopharmaceutical industry. Regulatory
agencies require now a tight control of product quality during production, which typically involves
characterization of the protein’s glycosylation, known to affect properties like serum half-life,
biological activity and immunogenicity. However, control of this property is not simple due to its
intrinsic high variability and its high sensitivity to small changes in the manufacturing process, in
ways that are far from being understood. Therefore, the development of products of consistent
high-quality requires a deeper understanding on the effect of the production parameters/
processes on glycosylation. In this context, the work described in this thesis intended to
contribute to this field of knowledge by evaluating changes on glycosylation of a monoclonal
antibody (mAb) produced by Chinese hamster ovary (CHO) cells during different stages of
process development, namely cell line transfection, serum-free media adaptation and culture.
To accomplish the main goal, a mAb-producing CHO-K1 cell line was initially established,
through a novel expression system (OSCARTM), potentially more expeditious than the traditional
methods. OSCARTM was indeed considerably faster, requiring about two months to obtain
producer cells compared to the minimum six months usually required. OSCARTM did not affect cell
growth and reached high levels of productivity (10 pg/cell/day) without requiring the typical
processes of amplification. The levels of productivity were initially difficult to stabilize, with a 10-
fold decay observed in the first weeks of culture, but remained stable thereafter for at least two
years. Furthermore, minigene selection was critical and seemed to be cell/product-specific. This
work also evaluated two methods for the initial selection of the highest producer clones obtained
after transfection, based on: absorbance values of supernatants; or mAb productivity calculated
using mAb yield determined by enzyme-linked immunosorbent assay and cell concentration
obtained from cell counting with a haemocytometer. It was shown that the methodology chosen
is highly influential on the product yield achievable in the final process of production, and that the
ABSTRACT│
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productivity-based method, albeit more laborious, is much more reliable than the commonly used
absorbance method. Additionally, the highest-producer clones were evaluated for mAb
glycosylation by high-performance liquid chromatography, with no differences detected.
Glycosylation was also assessed during the adaptation of mAb-producing cells to serum-free
medium using a gradual methodology and supplementation with trace elements. This process
was long and highlighted the importance of using proper media supplements, avoiding aggressive
procedures (centrifugation, enzymes), and giving cells enough time to adapt at each stage. More
importantly, it was shown that adaptation alters glycosylation: in the middle stages, fucosylation
decreased and galactosylation, sialylation and glycoform heterogeneity increased, with the first
two being positive and the last two undesirable for efficacy; in the final stages and after full
adaptation, fucosylation returned to the initial (serum-supplemented) levels, while galactosylation,
fucosylation and heterogeneity decreased, with the last two being positive. Divergences between
the stages were related to lower cell concentrations and viabilities in the middle stages of
adaptation, and to a shift of the growth mode of cells from adherent to suspended.
The impact of a microporous microcarrier culture on mAb glycosylation was evaluated and
compared to common T-flask cultures. The influence of several culture conditions was assessed,
including initial culture volume and cell concentration, rocking mechanism and speed, and
culture vessel. The microcarrier cultures led to a different mAb glycosylation compared to that
obtained in the T-flask culture, attributed to different mAb productivities, as well as to the use of
rocking and the generation of microenvironments (pH, accumulation of extracellular enzymes) in
the microcarrier cultures. Specifically, higher galactosylation and decreased fucosylation, both
beneficial changes, and a variable sialylation were found in the microcarrier cultures. Sialylation
was more sensitive to the culture parameters, particularly the type of culture vessel, being almost
absent in shake flask cultures. In addition to this advantageous modification, shake flasks also
led to a more homogeneous glycosylation, potentially due to improved cell densities.
In summary, the work described in this thesis contributes to a better understanding of how
glycosylation is affected by technologies used in process development, highlighting the need to
implement quality control at early stages. By increasing knowledge on this subject, it will be
possible to control and improve the quality and efficacy of therapeutic proteins, which will
ultimately lead to their administration at lower doses and frequency.
Keywords: Chinese hamster ovary cells; Monoclonal antibody; Glycosylation; Transfection;
Serum-free medium; Adaptation; Microcarriers; Quality control
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SUMÁRIO
EXPRESSÃO E CARACTERIZAÇÃO DE UM ANTICORPO MONOCLONAL TERAPÊUTICO EM CÉLULAS ANIMAIS
O desenvolvimento de proteínas terapêuticas recombinantes revolucionou a medicina atual,
trazendo novas formas de tratamento a doenças que se pensava incuráveis. A sua produção tem
sido alvo de grandes evoluções, que quase sempre negligenciaram a qualidade do produto.
Recentemente, este tornou-se um dos maiores desafios da indústria biofarmacêutica, com as
agências reguladoras a exigirem controlo da qualidade durante a produção. Este controlo envolve
normalmente a caracterização da glicosilação da proteína devido à sua influência em propriedades
como tempo de meia vida, imunogenicidade e atividade biológica, mas é dificultado pela sua
variabilidade intrínseca e pela sensibilidade a pequenas alterações nos processos de fabrico, de
forma ainda não compreendida. De facto, é necessário aprofundar o conhecimento atual sobre o
efeito dos parâmetros/processos de produção na glicosilação para a obtenção de produtos de
qualidade consistente. Neste contexto, o trabalho descrito na presente dissertação pretende
contribuir para o aumento do conhecimento na área, avaliando a glicosilação de um anticorpo
monoclonal (AcM) produzido por células animais durante diferentes estágios do desenvolvimento
de processos, nomeadamente transfecção, adaptação a meio sem soro e cultura.
Com este fim, foi estabelecida uma linha de células de ovário de hamster chinês (CHO-K1)
produtora de AcM, tendo-se avaliado um sistema de expressão (OSCARTM) recente e potencialmente
mais expedito do que os métodos tradicionais. De facto, este sistema foi mais célere, obtendo-se
células produtoras em apenas dois meses comparando com o mínimo de seis meses
normalmente necessário. Por outro lado, o sistema OSCARTM não afetou o crescimento celular e
permitiu obter elevadas produtividades (10 pg/cél/dia) sem recorrer a processos de amplificação.
Estes níveis de produtividade foram inicialmente difíceis de estabilizar, tendo-se observado um
decréscimo abrupto do seu valor nas primeiras semanas, mas mantendo-se posteriormente
estáveis por dois anos. Foram ainda avaliados dois métodos para seleção inicial dos clones mais
produtivos obtidos após transfeção, com base nos valores de absorvência dos sobrenadantes, ou
na produtividade calculada através das concentrações celular (contagem com hemocitómetro) e de
AcM (ensaio immunoenzimático) de cada clone. Demonstrou-se que a metodologia selecionada
tem uma grande influência nos níveis de produção atingidos no processo final de produção, sendo
SUMÁRIO│EXPRESSÃO E CARACTERIZAÇÃO DE UM ANTICORPO MONOCLONAL TERAPÊUTICO EM CÉLULAS ANIMAIS
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o método da produtividade o mais aconselhado, pois embora mais trabalhoso é sem dúvida o de
maior precisão. Avaliou-se ainda a glicosilação do AcM produzido pelos clones selecionados, por
cromatografia líquida de alta eficiência, não se tendo detetado diferenças.
A glicosilação do AcM foi avaliada durante a adaptação celular gradual a meio sem soro, com
suplementação de oligoelementos. Este longo processo realçou a importância de usar suplementos
adequados, evitar procedimentos agressivos (centrifugação, enzimas) e permitir tempo suficiente
de adaptação a cada estágio. Demonstrou-se ainda que a glicosilação é alterada pelo processo:
nos passos intermédios houve decréscimo da fucosilação e aumento da galactosilação, sialilação e
heterogeneidade de glicoformas, sendo as duas primeiras positivas e as últimas indesejáveis; nos
últimos passos a fucosilação retomou os valores iniciais, e a galactosilação, fucosilação e
heterogeneidade diminuiram, sendo as duas últimas desejáveis. As diferenças entre passos
intermédios e finais estarão relacionadas com a concentração e viabilidade celular, inferiores nos
primeiros, e com a mudança no modo de crescimento celular de aderido para suspenso.
O impacto da cultura em suportes microporosos (Cytodex 3) na glicosilação do AcM foi
avaliada e comparada com a cultura aderida em frascos comuns. Analisou-se ainda a influência de
diferentes condições de cultura, como o volume e concentração celular iniciais, mecanismo e
velocidade de agitação, e frasco de cultura nos perfis de glicosilação. A cultura em suportes
microporosos originou diferentes padrões de glicosilação comparada com a cultura em frascos
comuns, atribuída a produtividades divergentes, assim como ao uso de agitação e à criação de
microambientes (pH, acumulação de enzimas extracelulares) nas culturas em suportes
microporosos. Em concreto, a galactosilação aumentou e a fucosilação diminuiu (mudanças
positivas), tendo a sialilação demonstrado ser mais sensível a parâmetros de cultura específicos,
particularmente ao tipo de frasco usado, sendo praticamente ausente em frascos agitados. Para
além desta modificação desejável, a cultura em frascos permitiu ainda uma glicosilação mais
homogénea, possivelmente devido a densidades celulares mais elevadas.
Resumindo, o trabalho efetuado contribui para uma melhor compreensão do efeito de
tecnologias envolvidas no desenvolvimento de processos na glicosilação do produto, salientando a
necessidade de implementar um controlo de qualidade já nos estágios iniciais. O aumento do
conhecimento sobre este tema irá, a longo prazo, permitir uma melhoria da eficácia das proteínas
terapêuticas, podendo resultar na redução da dose e frequência de administração necessárias.
Palavras-chave: Células de ovário de hamster chinês; Anticorpo monoclonal; Glicosilação;
Transfecção; Meio sem soro; Adaptação; Suportes microporosos; Controlo de qualidade
xi
TABLE OF CONTENTS
ACKNOWLEDGMENTS ................................................................................................................................................... v
ABSTRACT .................................................................................................................................................................... vii
SUMÁRIO ....................................................................................................................................................................... ix
LIST OF FIGURES .......................................................................................................................................................... xv
LIST OF TABLES ...........................................................................................................................................................xix
LIST OF ABBREVIATIONS, ACRONYMS AND SYMBOLS ........................................................................................... xxiii
THESIS PREAMBLE .................................................................................................................................................... xxxi
LIST OF PUBLICATIONS ............................................................................................................................................ xxxv
CHAPTER 1
GENERAL INTRODUCTION
1.1. INTRODUCTION ........................................................................................................................... 5
1.2. THERAPEUTIC PROTEINS AND THE SPECIFICITIES OF MONOCLONAL ANTIBODIES ..................... 6
1.3. EXPRESSION SYSTEM ................................................................................................................ 11
1.4. TRANSFECTION ......................................................................................................................... 13
1.4.1. EXPRESSION VECTOR ...................................................................................................................... 15
1.4.2. SELECTABLE MARKERS FOR STABLE TRANSFECTION ..................................................................... 17
1.4.3. DELIVERY METHODS ....................................................................................................................... 20
1.4.4. SELECTION...................................................................................................................................... 23
1.5. PROCESS OPTIMIZATION AT SMALL SCALE ................................................................................ 24
1.5.1. MODE OF GROWTH ......................................................................................................................... 24
1.5.2. MEDIUM .......................................................................................................................................... 26
1.5.3. PROCESS OPTIMIZATION ................................................................................................................. 27
1.6. GLYCOSYLATION........................................................................................................................ 28
1.6.1. BASIC CONCEPTS OF GLYCOSYLATION ........................................................................................... 29
1.6.2. BIOSYNTHESIS OF O-GLYCANS IN HUMAN CELLS ........................................................................... 30
1.6.3. BIOSYNTHESIS OF N-GLYCANS IN HUMAN CELLS ........................................................................... 32
1.6.4. GLYCOSYLATION AND THERAPEUTIC PROTEIN EFFICACY ............................................................... 38
1.6.5. EXTERNAL FACTORS INFLUENCING GLYCOSYLATION ..................................................................... 40
TABLE OF CONTENTS│
xii
1.6.6. GLYCOENGINEERING FOR IMPROVED THERAPEUTIC EFFICACY ...................................................... 53
1.6.7. STRATEGIES FOR GLYCOSYLATION ANALYSIS ................................................................................. 57
1.7. CONCLUDING REMARKS ............................................................................................................ 67
1.8. REFERENCES............................................................................................................................. 68
CHAPTER 2
THE OSCARTM SYSTEM FOR THE TRANSFECTION OF CHO CELLS FOR MONOCLONAL ANTIBODY PRODUCTION
2.1. INTRODUCTION ....................................................................................................................... 103
2.2. MATERIALS AND METHODS ..................................................................................................... 105
2.2.1. CELLS, PLASMIDS AND MINIGENES ............................................................................................... 105
2.2.2. SELECTION AND VALIDATION OF HPRT-DEFICIENT CLONES .......................................................... 105
2.2.3. TRANSFECTION ............................................................................................................................. 106
2.2.4. SELECTION OF THE HIGHEST MONOCLONAL ANTIBODY PRODUCERS ........................................... 107
2.2.5. ANTIBODY QUANTIFICATION BY ENZYME-LINKED IMMUNOSORBENT ASSAY ................................. 107
2.2.6. CELL GROWTH CHARACTERISTICS ................................................................................................ 109
2.2.7. ANALYSIS OF THE GLYCOSYLATION PROFILE ................................................................................. 109
2.3. RESULTS AND DISCUSSION ..................................................................................................... 113
2.3.1. ANALYSIS OF THE TWO MAIN PHASES OF THE OSCARTM TECHNOLOGY .......................................... 113
2.3.2. LEVEL AND STABILITY OF CLONE PRODUCTIVITY ........................................................................... 114
2.3.3. EFFECT OF TRANSFECTION ON CELL GROWTH CHARACTERISTICS ............................................... 118
2.3.4. ANALYSIS OF THE MONOCLONAL ANTIBODY GLYCOSYLATION PROFILE ........................................ 119
2.4. CONCLUSION .......................................................................................................................... 121
2.5. REFERENCES........................................................................................................................... 122
CHAPTER 3
IMPACT OF THE PROCESS OF CELL ADAPTATION TO SERUM-FREE CONDITIONS ON PRODUCT QUALITY
3.1. INTRODUCTION ....................................................................................................................... 129
3.2. MATERIALS AND METHODS ..................................................................................................... 131
3.2.1. CELL LINE AND CULTURE CONDITIONS ......................................................................................... 131
3.2.2. CELL ADAPTATION TO SERUM-FREE CONDITIONS ......................................................................... 131
3.2.3. ANALYSIS OF THE MONOCLONAL ANTIBODY GLYCOSYLATION PROFILE ........................................ 132
3.3. RESULTS AND DISCUSSION ..................................................................................................... 137
3.4. CONCLUSION .......................................................................................................................... 148
3.5. REFERENCES........................................................................................................................... 149
│TABLE OF CONTENTS
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CHAPTER 4
IMPACT OF MICROCARRIER CULTURE ON PRODUCT QUALITY
4.1. INTRODUCTION ....................................................................................................................... 161
4.2. MATERIALS AND METHODS ..................................................................................................... 163
4.2.1. CELL LINE AND CELL CULTURE ..................................................................................................... 163
4.2.2. MICROCARRIER PREPARATION ...................................................................................................... 163
4.2.3. MICROCARRIER CULTURE ............................................................................................................. 163
4.2.4. CULTURE MONITORING ................................................................................................................. 164
4.2.5. ANTIBODY QUANTIFICATION BY ENZYME-LINKED IMMUNOSORBENT ASSAY ................................. 165
4.2.6. ANALYSIS OF THE MONOCLONAL ANTIBODY GLYCOSYLATION PROFILE ........................................ 166
4.3. RESULTS AND DISCUSSION ..................................................................................................... 170
4.4. CONCLUSION .......................................................................................................................... 178
4.5. REFERENCES........................................................................................................................... 179
CHAPTER 5
GENERAL CONCLUSIONS AND CONSIDERATIONS FOR FUTURE WORK
5.1. GENERAL CONCLUSIONS ........................................................................................................ 187
5.2. CONSIDERATIONS FOR FUTURE WORK .................................................................................... 192
xv
LIST OF FIGURES
CHAPTER 1
FIGURE 1.1. Representation of the structure of a human IgG antibody, composed of two light chains (L,
represented by traced rectangles) and two heavy chains (H, represented by empty rectangles). Both
L and H chains contain variable (VL, VH) and constant (CL, CH1-3) regions. The light chains are
connected to the heavy chains by disulfide bonds forming three independent protein moieties, two
fragment antigen binding (Fab) and one fragment crystallisable (Fc), which are connected through
the hinge region. The CH2 domains in the Fc region contain a highly conserved site (represented by
a star) for the covalent attachment of a glycan. ............................................................................... 9
FIGURE 1.2. Illustration of the antibody mechanisms for the elimination of antigen by (a) apoptosis, (b)
antibody-dependent cellular cytotoxicity (ADCC) mediated by cross-linking of leucocyte IgG-Fc
receptors, (c) engagement and activation of the C1 component of complement ............................. 10
FIGURE 1.3. Schematic diagram of (a) transient transfection and (b) stable transfection of foreign genetic
material (DNA, grey wave) into mammalian cells. In transient transfection (a) the foreign DNA enters
the nucleus and is expressed only temporarily due to a rapid loss of the foreign genetic material by
environmental factors and cell division. In stable transfection (b) the foreign DNA enters the nucleus
and is integrated into the genome of the host cell, allowing its stable expression over extended
periods of time. ............................................................................................................................ 14
FIGURE 1.4. Representation of the eight known core structures of mucin-type O-glycans. Core 1 to 4 are
the most prevalent; Core 7 has not been observed in humans. Core 1 has a Gal attached in a β1-3
linkage to the core GalNAc. Core 2 forms by the addition of a GlcNAc β1-6 linked to the GalNAc of
Core 1. Core 3 has a GlcNAc attached in a β1-3 linkage to the core GalNAc. Core 4 forms by the
addition of another GlcNAc β1-6 linked to the GalNAc of Core 3. Core 5 has a GalNAc attached in a
α1-3 linkage to the core GalNAc, Core 6 has a GlcNAc in a β1-6 linkage, Core 7 has a GalNAc in a
β1-6 linkage, and Core 8 has a Gal α1-3 linked to the core GalNAc. .............................................. 31
FIGURE 1.5. Pathway for the biosynthesis of the dolichol glycan precursor for protein N-glycosylation and
transfer of the precursor to asparagine residues (Asn-X-Thr/Ser) on nascently translated proteins by
the oligosaccharyltransferase (OST) complex. ................................................................................ 33
LIST OF FIGURES│
xvi
FIGURE 1.6. Processing of the initial high mannose N-glycan in the endoplasmic reticulum and cis-Golgi to
generate the core N-glycan substrate used for further diversification in the Golgi. ........................... 34
FIGURE 1.7. Representation of the N-glycan diversification in the Golgi, which generates three subtypes:
high-mannose, hybrid, and complex glycans.................................................................................. 36
FIGURE 1.8. Structures exemplifying complex N-glycans with varying number of antennae: biantennary,
triantennary, and tetra-antennary. ................................................................................................. 36
FIGURE 1.9. Schematic representation of N-glycan structures found in human cells and in the different
expression systems available for recombinant protein production. ................................................. 42
FIGURE 1.10. Approaches for the glycosylation analysis of proteins. The glycoprotein can be analyzed intact
or fractioned into glycopeptides, glycans or monosaccharides for more detailed assessment. The
analysis by one approach can be followed by another, with the most and less common analytical
pathways shown as full and dashed lines, respectively. ................................................................. 58
CHAPTER 2
FIGURE 2.1. Initial clone selection after transfection based on two approaches: (a) absorvance values of
supernatant read at 450 nm (ABS450), and (b) productivity (qmAb). The interrupted line denotes the
cutoff limit established for clone selection: (a) ABS450 of 100, and (b) qmAb of 10 pg/cell/day; and the
dark color highlights the selected clones. ............................................................................................. 115
FIGURE 2.2. Values of productivity (qmAb) of the selected clones obtained initially and after three weeks in
culture. .................................................................................................................................................... 116
FIGURE 2.3. Evolution of the productivity (qmAb) levels of clones 18, 27, 32, and 95 during 6 weeks in
culture. .................................................................................................................................................... 117
CHAPTER 3
FIGURE 3.1. N-glycosylation profile of the monoclonal antibody produced by CHO-K1 cells cultured in
different conditions during a process of gradual adaptation to serum-free medium ......................... 140
│LIST OF FIGURES
xvii
CHAPTER 5
FIGURE 5.1. Summary of the modifications, and potential biological effects, detected in the glycosylation
profile of the monoclonal antibody produced by CHO-K1 cells during adaptation to growth in serum-
free conditions. The divergences found in the glycosylation profile were divided into two stages:
during adaptation, and at the final stages of adaptation and thereafter. Probable causes for the
differences found are mentioned on the right....................................................................................... 189
FIGURE 5.2. Summary of the modifications, and potential biological effects, detected in the glycosylation
profile of the monoclonal antibody produced by CHO-K1 cells during microcarrier culture. Probable
causes for the differences found in comparison to the normal adherent culture in T-flasks are
mentioned on the left. ............................................................................................................................ 191
xix
LIST OF TABLES
CHAPTER 1
TABLE 1.1. The top-ten-selling biopharmaceutical products of 2010 ................................................................ 8
TABLE 1.2. Advantages and limitations of different expression systems for therapeutic glycoprotein production
................................................................................................................................................................... 12
TABLE 1.3. Characteristics of selective markers commonly used in expression vectors for the stable
transfection of mammalian cells ............................................................................................................. 18
TABLE 1.4. Comparison of biological, chemical and physical methods for the delivery of genetic material
into cells ...................................................................................................................................... 21
TABLE 1.5. Monosaccharides commonly present in mammalian glycoproteins, with respective abbreviation
and symbolic notation .............................................................................................................................. 30
TABLE 1.6. Divergences found on protein glycosylation occurring in different expression systems in
comparison to the glycosylation obtained in human cells, and respective effects on protein activity ..... 42
TABLE 1.7. Structural differences in the N-glycans produced by the main mammalian cells used as hosts
for glycoprotein production, concerning human glycosylation ............................................................... 44
TABLE 1.8. List of the main results reported on the effects of different variables of cell culture processes on
product glycosylation ................................................................................................................................ 47
TABLE 1.9. Exoglycosidase enzymes used for glycan analysis and respective monosaccharide and linkage
specificity ................................................................................................................................................... 62
TABLE 1.10. Incremental glucose unit (GU) values of different monosaccharides and linkages for the
structural assignment of 2-AB labeled N-glycans ................................................................................... 63
TABLE 1.11. Analytical techniques to characterize glycosylation, their basic principle, approaches in which
they apply, information provided and main advantages and limitations ............................................... 65
LIST OF TABLES│
xx
CHAPTER 2
TABLE 2.1. Characteristics of the disabled HPRT minigenes used in the OSCARTM expression system, in
comparison with the fully functional HPRT gene pBT/PGK-HPRT[RI] ................................................. 105
TABLE 2.2. Comparison of cloning rings and cloning disks for the isolation of HPRT-deficient clones
obtained during the first phase of the OSCARTM expression system, considering simplicity, speed and
cell recovery ............................................................................................................................................ 113
TABLE 2.3. Comparison of the three HPRT minigenes with varying degrees of expression disability for the
co-transfection of the CAB051 plasmid into the CHO-K1 cells using the OSCARTM expression system
................................................................................................................................................................. 114
TABLE 2.4. Values of productivity (qmAb) obtained for Clone 18 and Clone 32 after two years in culture..... 118
TABLE 2.5. Doubling times (tD) of the original CHO-K1 cells and of Clones 18 and 32, after two years in
culture ..................................................................................................................................................... 118
TABLE 2.6. Data of mean glucose unit (GU) value, tentative structure assignment, and relative area (%) of
the peaks obtained by high performance liquid chromatography for the monoclonal antibody
produced by Clones 18 and 32 ............................................................................................................. 119
CHAPTER 3
TABLE 3.1. Composition of the five combinations of supplements assessed for the adaptation of
monoclonal antibody-producing CHO-K1 cells to growth in serum-free conditions ............................ 132
TABLE 3.2. Description of the samples taken at different stages of the process of adaptation of monoclonal
antibody-producing CHO-K1 cells to serum-free medium, for the evaluation of the glycosylation
profile of the monoclonal antibody produced ....................................................................................... 133
TABLE 3.3. Timeline of the process of adaptation of the monoclonal antibody-producing CHO-K1 cells to
serum-free culture conditions ................................................................................................................ 138
TABLE 3.4. Data of mean glucose unit (GU) value, tentative assignment, and percentage of area of the
different peaks detected on the monoclonal antibody produced by CHO-K1 cells during the process
of adaptation to serum-free conditions. ................................................................................................. 142
TABLE 3.5. Galactose, core fucose and sialic acid composition of the monoclonal antibody produced by
CHO-K1 cells during the different steps of the process of adaptation to serum-free conditions ....... 144
│LIST OF TABLES
xxi
CHAPTER 4
TABLE 4.1. Conditions tested for the culture of the monoclonal antibody-producing CHO-K1 cells in Cytodex
3 (CY) microcarriers ............................................................................................................................... 164
TABLE 4.2. Data of mean glucose unit (GU) value, tentative structure assignment, and relative (%) area of
the peaks of the monoclonal antibody produced by CHO-K1 cells under different culture conditions
................................................................................................................................................................. 171
TABLE 4.3. Data of average cell concentration and productivity of monoclonal antibody-producing CHO-K1
cells cultured in different conditions ...................................................................................................... 172
TABLE 4.4. Galactose, core fucose and sialic acid composition of the monoclonal antibody produced by
CHO-K1 cells during microcarrier culture in different conditions ........................................................ 173
xxiii
LIST OF ABBREVIATIONS, ACRONYMS AND SYMBOLS
$ Dollar
% Percentage
® Registered trademark
µm Micrometer
µM Micromolar
2-AA 2-aminoanthranilic acid
2-AB 2-aminobenzamide
2-AP 2-aminopyridine
2D-PAGE Two-dimensional polyacrylamide gel electrophoresis
a Estimated response at zero concentration
ABS Absorbance
Abs Arthrobacter ureafaciens sialidase
ABSx Absorbance read at x nanometers
ADCC Antibody-dependent cellular cytotoxicity
AMAC 2-aminoacridone
Amf Almond meal fucosidase
ANOVA One-way analysis of variance
ANTS 8-aminonaphtalene-1,3,6-trisulfonic acid
Aph Aminoglycoside phosphotransferase
APS Ammonium peroxisulphate
Asn Asparagine
Asp Aspartate
ATCC American Type Culture Collection
b Slope factor
BHK Baby hamster kidney
Bkf Bovine kidney focusidase
BSA Bovine serum albumin
BSA-PBS Bovine serum albumin in phosphate buffered saline
Btg Bovine testis galactosidase
c Mid-range concentration
LIST OF ABBREVIATIONS, ACRONYMS AND SYMBOLS│
xxiv
C1 Complement component 1
C1q Complement component 1, q subcomponent
CaCl2 Calcium chloride
Cbg Coffee bean α-galactosidase
Ccell Cell concentration, in cells per milliliter
Ccell/microcarrier Cell concentration, in cells per microcarrier
CDC Complement-dependent cytotoxicity
CE Capillary electrophoresis
CE-LIF Capillary electrophoresis with laser-induced fluorescence detection
CE-LIF-MS Capillary electrophoresis with laser-induced fluorescence detection and mass
spectrometry
CE-MS Capillary electrophoresis and mass spectrometry
CH1-3 Constant region of the heavy chains, domain 1-3
CHO Chinese hamster ovary
CmAb Concentration of monoclonal antibody, in micrograms per mL
Cmicrocarriers in g/mL Concentration of microcarriers in grams of dry weight per milliliter
Cmicrocarriers/mL Concentration of microcarriers in number of microcarriers per milliliter
CMV Cytomegalovirus
CO2 Carbon dioxide
CuSO4 Copper sulfate
Cx Cell concentration at time x, in cells per milliliter
d Estimated response at infinite concentration
Da Dalton
DHFR Dihydrofolate reductase
DMEM Dulbecco’s Modified Eagle’s Medium
DMSO Dimethylsulfoxide
DNA Deoxyribonucleic acid
DO Dissolved oxygen
Dol-P Dolichol phosphate
DTT Dithiothreitol
e.g. Exempli gratia (for example)
EASE Expression augmenting sequence elements
ELISA Enzyme-linked immunosorbent assay
ENGase Endo-β-N-acetylglucosaminidase
EPO Erythropoietin
│ LIST OF ABBREVIATIONS, ACRONYMS AND SYMBOLS
xxv
ER Endoplasmic reticulum
ESI-MS Electrospray ionization mass spectrometry
et al Et alii (and others)
F Dilution factor
Fab Fragment antigen binding
FBS Fetal bovine serum
Fc Fragment crystallisable
FcγR Fragment crystallisable gamma receptor
FcRn Neonatal fragment crystallisable receptor
FDA Food and Drug Administration
FeC6H5O7.NH4OH Ammonium iron citrate
FG0 Core fucosylated agalactosylated
FG1 Core fucosylated monogalactosylated
FG2 Core fucosylated digalactosylated
FG3 Core fucosylated trigalactosylated
Fuc, F Fucose
fut8 α1,6-fucosyltransferase gene
g Centrifugal force relative to the gravitational force of the earth
g Gram
G0 Agalactosylated
G1 Monogalactosylated
G2 Digalactosylated
G3 Trigalactosylated
G418 Geneticin
GAG Glycosaminoglycan
Gal, G Galactose
GalNAc N-acetylgalactosamine
GalT Galactosyltransferase
GC Gas chromatography
GC-MS Gas chromatography and mass spectrometry
GDP Guanosine diphosphate
Glc Glucose
GlcA Glucoronic acid
GlcNAc, A N-acetylglucosamine
Glu Glutamate
LIST OF ABBREVIATIONS, ACRONYMS AND SYMBOLS│
xxvi
GnT N-acetylglucosaminyltransferase
GS Glutamine synthetase
GU Glucose unit
h Hour
HAT Hypoxanthine, aminopterin, thymidine
HBS Hydroxyethyl piperazineethanesulfonic acid-buffered salt solution
HCO3- Bicarbonate
HEK Human embryonic kidney
HEPES Hydroxyethyl piperazineethanesulfonic acid
HILIC Hydrophilic interaction chromatography
hisD Histidinoldehydrogenase
HPAEC High performance anion exchange chromatography
HPAEC-PAD High performance anion exchange chromatography with pulse amperometric
detection
Hph Hygromycin-B phosphotransferase
HPLC High performance liquid chromatography
HPRT Hypoxanthine phosphoribosyltransferase
i.e. Id est (that is, in other words)
IAA Iodoacetamide
IBM International Business Machines
IEF-PAGE Isoelectric focusing polyacrylamide gel electrophoresis
IFN Interferon
Ig Imunoglobulin
Jbh Jack bean N-acetylhexosaminidase
Jbm Jack bean mannosidase
KCl Potassium chloride
KDa Kilodalton
KH2PO4 Potassium dihydrogen phosphate
L Liter
LC-MS Liquid chromatography and mass spectrometry
Leu Leucine
Log Logarithm
m Meter
M Molar
mAb Monoclonal antibody
│ LIST OF ABBREVIATIONS, ACRONYMS AND SYMBOLS
xxvii
MALDI Matrix assisted laser desorption ionization
MALDI-MS Matrix assisted laser desorption ionization mass spectrometry
MALDI-MS-TOF Matrix assisted laser desorption ionization mass spectrometry with time of flight
analysis
Man, M Mannose
ManNAc N-acetyl mannosamine
MARS Matrix-attachment regions
MDCK Madin Darby canine kidney cells
mg Milligram
min Minute
mL Milliliter
mM Millimolar
mm2 Square millimeter
mRNA Messenger ribonucleic acid
MS Mass spectrometry
MSX Methionine sulfoxamide
MTX Methotrexate
MWCO Molecular weight cut-off
MΩ.cm Mega omega centimeter, measure of resistivity
Na2HPO4 Sodium phosphate dibasic
Na2HPO4.2H2O Sodium phosphate dibasic dihydrate
Na2SeO3 Sodium selenite
NaCl Sodium chloride
Nan1 Streptococcus pneumoniae sialidase
Ncells Number of cells
NeuGc N-glycolylneuraminic acid
NeuNAc N-acetylneuraminic acid
NH4Fe(SO4)2 Ferrous ammonium sulfate
NH4VO3 Ammonium metavanadate
NIBRT National Institute for Bioprocessing, Research and Training
NiCl2 Nickel chloride
NK cells Natural killer cells
nm Nanometer
Nmicrocarriers in sample Number of microcarriers in a sample
Nmicrocarriers/g dry weight Approximate number of microcarriers per gram of dry weight
LIST OF ABBREVIATIONS, ACRONYMS AND SYMBOLS│
xxviii
NMR Nuclear magnetic resonance
NP-HPLC Normal-phase high-performance liquid chromatography
NS0 Murine myeloma cells
º Degree
ºC Celsius degrees
OST Oligosaccharyltransferase
Pac Puromycin N-acetyltransferase
PAD Pulsed amperometric detection
PAS Periodic acid Schiff
PBS Phosphate buffered saline
pDWM128 Hypoxanthine phosphoribosyltransferase minigene
pDWM129 Hypoxanthine phosphoribosyltransferase minigene
pDWM130 Hypoxanthine phosphoribosyltransferase minigene
PER.C6 Human embryonic retinal cells
pg Picogram
Phe Phenylalanine
pI Isoelectric point
PNGase Peptide N-glycosidase
Pro Proline
qmAb Monoclonal antibody productivity, in picograms per cell per day
rhInsulin Recombinant human insulin
RNA Ribonucleic acid
RP-HPLC Reverse phase high-performance liquid chromatography
rpm Revolutions per minute
S Sialic acid
SA Anonymous society
S1 Monosialylated
S1G1 Monosialylated monogalactosylated
S1G2 Monosialylated digalactosylated
S2 Disialylated
S2G2 Disialylated digalactosylated
S2G3 Disialylated trigalactosylated
S3 Trisialylated
S3G3 Trisialylated trigalactosylated
SARS Scaffold-attachment regions
│ LIST OF ABBREVIATIONS, ACRONYMS AND SYMBOLS
xxix
SDS Sodium dodecyl sulfate
SDS-PAGE Sodium dodecyl sulfate polyacrylamide gel electrophoresis
Ser Serine
sh ble Zeocin/bleomycin resistance gene
SnCl2 Stannous chloride
SOP Standard operating procedure
Sp2/0 Murine myeloma cells
Spg Streptococcus pneumoniae galactosidase
Sph Streptococcus pneumoniae N-acetylhexosaminidase
SPSS Statistical Package for the Social Sciences
SV40 Simian virus 40
t Time
tD Cell doubling time, in hours
TEMED Tetramethylethylenediamine
Thr Threonine
TIMP Tissue inhibitor of metalloproteinases
TK Thymidine kinase
TM Trademark
TMB 3,3’,5,5’-Tetramethylbenzidine
tPA Tissue plasminogen activator
Trp Tryptophan
UDP Uridine diphosphate
UK United Kingdom
USA United States of America
v/v Volume to volume
Vsample Volume of sample, mL
WAX-HPLC Weak anion exchange high-performance liquid chromatography
Xyl Xylose
ZnSO4 Zinc sulfate
xxxi
THESIS PREAMBLE
SCOPE OF THE THESIS
For many years, the biopharmaceutical industry has centered its efforts on increasing the
capacity of their processes to obtain higher quantities of the product at lower costs. Only recently
concerns about the quality of the therapeutic products obtained in these processes have risen,
resulting in a change of priorities to accommodate this crucial parameter. Indeed, the regulatory
agencies have now settled several requirements for the approval of new therapeutics that include
the characterization of properties related to their quality/efficacy, and which must be performed
throughout the lifecycle of the product. Of those properties, glycosylation has been considered as
one of the most critical, and has drawn the attention of the biopharmaceutical industry. This post-
translational modification is known to be affected by several process changes, ranging from the
choice of the expression system to the final culture conditions, which may change the therapeutic
efficacy of the product, the frequency and dosage required, and even its potential side effects. As
a result, biopharmaceutical industry is trying to understand the ways in which the incredible
diversity of parameters involved in process development for the production of therapeutics affect
glycosylation. As a more far-reaching objective, glycosylation is being regarded as a potential
means to improve the quality of the product, which may be accomplished with glycoengineering
methods or more simply through the manipulation of the culture conditions.
THESIS PREAMBLE│
xxxii
AIM OF THE THESIS
Taking into consideration the facts exposed, it is clear that a more in-depth understanding
about how glycosylation is affected by different processes of biopharmaceutical manufacturing is
crucial for the development of high quality therapeutics. The work described in the present thesis
intended to contribute to the progress in this field by evaluating the impact of different steps of
early process development on the glycosylation profile of a monoclonal antibody (mAb) produced
by mammalian cells.
The first step of process development is to establish a producer cell line by transfecting cells
with the product gene. This is commonly a time-consuming process that yields a high number of
cell clones, which must be screened for the selection of the highest-producers. The clones
obtained have different growth and production characteristics and could therefore also yield a
product with divergent glycosylation profiles. Therefore, the first aim of the study presented
herein was to evaluate a novel, potentially faster, methodology for the transfection of a Chinese
hamster ovary (CHO) cell line for mAb production, followed by clone selection and comparison of
the mAb glycosylation profile among the highest-producer clones.
Another important stage of process development is the adaptation of the producing cells to
serum-free culture, due to regulatory and safety concerns that require the elimination of any
animal components from the culture media. This process of adaptation has repercussions on cell
growth, viability and product yield, and may also affect product quality. Consequently, a second
aim of the work was to assess the impact of each of the steps of a gradual adaptation of mAb-
producting cells to serum-free culture on the resulting mAb glycosylation profile, including the test
of different combinations of media supplements.
Biopharmaceutical processes are typically performed with cells growing in suspension due
to the highest cell and product yields provided when compared to adherent culture. However,
alternative systems for high-yield anchorage-dependent culture are now being established and
used, with microcarriers currently regarded as the most successful technology in the field. The
establishment of microcarrier culture requires the optimization of several parameters that affect
cell growth, product yield and potentially quality. Therefore, the final task of this work was to
assess the impact of microcarrier culture on mAb glycosylation, in comparison to normal T-flask
cultures, and to evaluate the profile obtained under different culture conditions.
│THESIS PREAMBLE
xxxiii
OUTLINE OF THE THESIS
The work developed to accomplish the scientific goals previously outlined is reported in this
thesis in the form of five chapters, according to the following organization:
CHAPTER 1 overviews the most relevant steps of process development for biopharmaceutical
production of therapeutic proteins. Particular emphasis is given to glycosylation, covering its
influence on the therapeutic efficacy of the product, the current knowledge about the process
parameters that affect its profile, the methods employed for its monitoring, and the advances
made in the field of glycoengineering to improve product quality.
CHAPTER 2 evaluates the novel OSCARTM expression system for the transfection of CHO cells for
mAb expression. It covers the impact of this methodology on cell growth characteristics and
levels and stability of production, and compares the glycosylation profile obtained with different
cell clones.
CHAPTER 3 is centered on a process of gradual adaptation of mAb-producing CHO cells to
serum-free culture, and the analysis of the effects of its different steps on the glycosylation profile
of the product.
CHAPTER 4 assesses the impact of microcarrier culture on mAb glycosylation, evaluating the
influence of several culture parameters typically used for its optimization.
CHAPTER 5 closes the thesis by connecting the most significant conclusions of the former
chapters and suggesting paths for future research.
xxxv
LIST OF PUBLICATIONS
The work developed during the four years of the PhD program resulted in several
publications in peer-reviewed international journals and book chapters, as well as abstracts in
proceedings of international conferences. These publications are compiled below.
PAPERS IN PEER-REVIEWD INTERNATIONAL JOURNALS
ANA RITA COSTA, Maria Elisa Rodrigues, Mariana Henriques, Rosário Oliveira, Joana Azeredo
(2010). Guidelines to cell engineering for monoclonal antibody production. European Journal
of Pharmaceutics and Biopharmaceutics, 74 (2):127-138.
Maria Elisa Rodrigues, ANA RITA COSTA, Mariana Henriques, Joana Azeredo, Rosário Oliveira
(2010). Technological progresses in monoclonal antibody production systems. Biotechnology
Progress, 26 (2):332-351.
ANA RITA COSTA, Maria Elisa Rodrigues, Mariana Henriques, David W Melton, Philip Cunnah,
Rosário Oliveira, Joana Azeredo (2012). Evaluation of the OSCARTM system for the production
of monoclonal antibodies by CHO-K1 cells. International Journal of Pharmaceutics, 430 (1-
2):42-6.
ANA RITA COSTA, Joanne Withers, Maria Elisa Rodrigues, Niaobh McLoughlin, Mariana Henriques,
Rosário Oliveira, Pauline M Rudd, Joana Azeredo (2012). The impact of cell adaptation to
serum-free conditions on the glycosylation profile of a monoclonal antibody produced by CHO
cells. Submitted to New Biotechnology.
ANA RITA COSTA, Joanne Withers, Maria Elisa Rodrigues, Niaobh McLoughlin, Mariana Henriques,
Rosário Oliveria, Pauline M Rudd, Joana Azeredo (2012). The impact of microcarrier culture
optimization on the glycosylation profile of a monoclonal antibody. Submitted to Journal of
Industrial Microbiology and Biotechnology.
LIST OF PUBLICATIONS│
xxxvi
ANA RITA COSTA, Maria Elisa Rodrigues, Mariana Henriques, Rosário Oliveira, Joana Azeredo
(2012). Glycosylation: impact, control and improvement during therapeutic protein
production. Submitted to Critical Reviews in Biotechnology.
ANA RITA COSTA, Maria Elisa Rodrigues, Mariana Henriques, Joana Azeredo, Rosário Oliveira
(2012). Comparison of commercial serum-free media for CHO-K1 cell growth and monoclonal
antibody production. International Journal of Pharmaceutics, 437(1-2):303-305.
Maria Elisa Rodrigues, ANA RITA COSTA, Mariana Henriques, Joana Azeredo, Rosário Oliveira
(2012). Wave characterization for mammalian cell culture: residence time distribution. New
Biotechnology, 29 (3):402-408.
Maria Elisa Rodrigues, ANA RITA COSTA, Mariana Henriques, Philip Cunnah, Joana Azeredo,
David W Melton, Rosário Oliveira (2012). Advances and drawbacks of the adaptation to
serum-free culture of CHO-K1 cells for monoclonal antibody production. Submitted to Applied
Biochemistry and Biotechnology.
Maria Elisa Rodrigues, ANA RITA COSTA, Pedro Fernandes, Mariana Henriques, Philip Cunnah,
David W Melton, Joana Azeredo, Rosário Oliveira (2012). Evaluation of macroporous and
microporous carriers for CHO-K1 cell growth and monoclonal antibody production. Submitted
to Biotechnology Progress.
Maria Elisa Rodrigues, ANA RITA COSTA, Mariana Henriques, Joana Azeredo, Rosário Oliveira
(2012). Evaluation of microcarriers for the production of a monoclonal antibody by suspended
CHO-K1 cells in serum-free media. Submitted to Journal of Biotechnology.
BOOK CHAPTERS
ANA RITA COSTA, Maria Elisa Rodrigues, Mariana Henriques, Rosário Oliveira, Joana Azeredo.
Feed optimization in fed-batch culture. In: Portner, R (ed.). Animal Cell Biotechnology:
Methods and Protocols, third edition. Humana Press. Forthcoming 2013.
│LIST OF PUBLICATIONS
xxxvii
Maria Elisa Rodrigues, ANA RITA COSTA, Mariana Henriques, Joana Azeredo, Rosário Oliveira.
Evaluation of solid and porous microcarriers for cell growth and production. In: Portner, R
(ed.). Animal Cell Biotechnology: Methods and Protocols, third edition. Humana Press.
Forthcoming 2013.
ABSTRACTS AND PROCEEDINGS IN INTERNATIONAL CONFERENCES
ANA RITA COSTA, Maria Elisa Rodrigues, Mariana Henriques, Joana Azeredo, Rosário Oliveira.
Assessment of different approaches for the adaptation of CHO cells to serum-free medium.
BIT’s Life Sciences 2nd Annual International Congress of Antibodies, Beijing, China, 24-26
March 2010. Book of Abstracts, p. 493.
Maria Elisa Rodrigues, ANA RITA COSTA, Mariana Henriques, Joana Azeredo, Rosário Oliveira.
Wave bioreactor characterization: residence time distribution. BIT’s Life Sciences 2nd Annual
International Congress of Antibodies, Beijing, China, 24-26 March 2010. Book of Abstracts, p.
494.
Maria Elisa Rodrigues, ANA RITA COSTA, Mariana Henriques, Joana Azeredo, Rosário Oliveira.
Characterization of the Wave bioreactor: residence time distribution determination. HAH 2010
– Human Antibodies and Hybridomas, Porto, Portugal, 14-16 April 2010.
ANA RITA COSTA, Maria Elisa Rodrigues, Mariana Henriques, Rosário Oliveira, Joana Azeredo.
Strategies for adaptation of mAb-producing CHO cells to serum-free medium. 22nd European
Society for Animal Cell Technology (ESACT) Meeting on Cell Based Technologies, Vienna,
Austria, 15-18 May 2011. BMC Proceedings, 5(Suppl 8):112.
Maria Elisa Rodrigues, Pedro Fernandes, ANA RITA COSTA, Mariana Henriques, Joana Azeredo,
Rosário Oliveira. Preliminary evaluation of microcarrier culture for growth and monoclonal
antibody production of CHO-K1 cells. 22nd European Society for Animal Cell Technology
(ESACT) Meeting on Cell Based Technologies, Vienna, Austria, 15-18 May 2011. BMC
Proceedings, 5(Suppl 8):111.
hapter hapter hapter hapter 1111
General introduction
CC
THE PRESENT CHAPTER WAS ADAPTED FROM THE FOLLOWING REVIEW PAPERS
ANA RITA COSTA, Maria Elisa Rodrigues, Mariana Henriques, Joana Azeredo, Rosário
Oliveira (2012). Glycosylation: impact, control and improvement during therapeutic
protein production. Submitted to Critical Reviews in Biotechnology.
ANA RITA COSTA, Maria Elisa Rodrigues, Mariana Henriques, Joana Azeredo, Rosário
Oliveira (2010). Guidelines to cell engineering for monoclonal antibody production.
European Journal of Pharmaceutics and Biopharmaceutics, 74:127-138.
3
he emergence of biopharmaceutical industry represented a major revolution for
modern medicine, through the development of recombinant therapeutic proteins that brought a
new breath of hope for many patients with previously untreatable diseases. The ever-growing
demand for this type of therapeutics forces the industry to be in constant evolution to increase
product yields while simultaneously reducing associated costs. However, process changes may
also affect the quality of the product, for example by modifying its glycosylation profile, a factor
that was initially overlooked but whose monitoring and control is now a major concern in
biopharmaceutical manufacturing and a requirement of regulatory agencies. In this scope, the
present chapter provides a review of the current status of process development for the
manufacture of therapeutic proteins, with emphasis on monoclonal antibodies, and of the
present knowledge about the impact of its different stages on product quality, particularly on the
glycosylation profile. The current approaches used to monitor this parameter are addressed, as
well as the strategies that are being explored to use glycosylation control as a means to improve
the therapeutic efficacy of the product.
Keywords: Therapeutic proteins; Monoclonal antibody; Expression system; Mammalian cells;
Transfection; Process optimization; Small-scale; Glycosylation; Glycoengineering; Analytical
methodologies
TT
CHAPTER 1 │ GENERAL INTRODUCTION
5
1.1. INTRODUCTION
The biopharmaceutical industry has revolutionized the treatment of many previously unmet
medical needs (Li and d’Anjou 2009) and currently represents the most significant and fastest
growing segment of the overall pharmaceutical market (Walsh 2010). An annual growth of 7-15 %
is expected in the next several years (Hillor 2009), having therapeutic proteins and particularly
monoclonal antibodies (mAbs) as the main drivers of this growth (Walsh 2010; Li and d’Anjou
2009). The relevance of mAbs is highlighted by a consistent and significant increase on the
number of mAbs approved in the last years for a wide range of therapeutic applications (Walsh
2010, 2003; Nilsang et al. 2007) that include the treatment of cancer, autoimmune disorders
and allergic diseases (Ozturk and Hu 2006).
The development of processes for the production of mAbs and other biopharmaceutical
proteins still faces many technological challenges at different stages of process development,
encompassing the selection of an appropriate expression system, the establishment of a suitable
producing cell line (transfection), the process optimization, and the scale-up and bioreactor
production (Baker, Flatman, and Birch 2007).
The primary goal of process development has been the improvement of volumetric
productivity (Woolley and Al-Rubeai 2009), with the current values of 10-15 g/L demonstrating a
major progress from the 100 mg/L initially obtained (Huang et al. 2010; Wurm 2004). This
upgrade is mainly attributed to advances on expression vectors (Aldrich, Viaje, and Morris 2003),
process control (Gagnon et al. 2011; Rodriguez et al. 2005; Trummer et al. 2006; Yoon et al.
2006) and host cell engineering (Seth et al. 2006), as well as to optimizations of culture medium
and feeding strategies (Huang et al. 2010; Wurm 2004; Altamirano et al. 2004).
Recently, the awareness about the potential impact of process changes on the quality of the
product has risen concerns that proteins lacking structural fidelity may provoke an immune
response that ultimately impacts therapeutic efficacy and/or causes harmful reactions (side
effects) (Baker, Flatman, and Birch 2007; Smalling et al. 2004). As a consequence of this
knowledge, biopharmaceutical industry is now considering both product yield and product quality
during process development, and the regulatory agencies have added product control and
characterization to their requirements. This characterization must be performed throughout the
product lifecycle, and is mainly focused on post-translational modifications, in special
CHAPTER 1 │ GENERAL INTRODUCTION
6
glycosylation, due to their known impact on a vast range of critical protein properties that
ultimately affect therapeutic efficacy (Baker, Flatman, and Birch 2007; Walsh and Jefferis 2006;
Spearman et al. 2005).
This chapter presents an up-to-date review about the early stages of process development
for the manufacture of therapeutic proteins, in particular mAbs, including the construction and
selection of an adequate cell line and the optimization of the process at small scale. The potential
impact of these steps on the quality of the product, more precisely on the glycosylation profile, is
discussed, as well as the current strategies employed to control and improve this property.
1.2. THERAPEUTIC PROTEINS AND THE SPECIFICITIES OF MONOCLONAL ANTIBODIES
Therapeutic proteins have been around for more than a century, since the pioneer work of
Behring and Kitasato, which resulted in the market launch of the first therapeutic protein in
1894, an anti-diphtheria serum to combat a serious diphtheria epidemic in Europe (Strohl 2009).
After this, other therapeutic proteins derived from human or animal sources emerged, as
exemplified by the remarkable introduction of heterologous insulin purified from pigs and cows
(Iletin®) by Eli Lilly in 1923, which started a life-saving treatment for patients with type I diabetes
mellitus (Strohl 2009).
However, concerns about the purity, consistency and, in particular, safety (potential viral
contamination) of these human/animal-derived products, resulted in a slow increment of their
therapeutic use (Sethuraman and Stadheim 2006). This changed in the last 30 years with the
emergence of recombinant protein technology (Strohl and Knight 2009; Sethuraman and
Stadheim 2006), which basically consists on the expression of cloned genetic material (the
protein) within living cells (the in vitro biological production system) (Jayapal et al. 2007). Once
again, insulin led the path and was the first recombinant human protein to be approved and
marketed, as Humulin®, in 1982 by Genentech and Eli Lilly, eliminating the issues of immune
response directed against the former heterologous insulins obtained from livestock (Strohl 2009;
Strohl and Knight 2009).
CHAPTER 1 │ GENERAL INTRODUCTION
7
Since the advent of Humulin®, more than 200 therapeutic proteins, majorly of recombinant
sources, have been brought to the market for a broad array of therapeutic diseases, having a
huge impact on modern medicine by bringing novel and life-saving therapies to patients
(Durocher and Butler 2009; Walsh 2010). According to their application/function, these
biopharmaceutical proteins can be categorized into four major groups: protein therapeutics with
enzymatic and regulatory activity (e.g. insulin, human growth hormone), protein therapeutics with
special targeting activity (e.g. mAbs), protein vaccines (e.g. human papilloma virus vaccine), and
protein diagnostics (e.g. biomarkers and imaging agents) (Leader, Baca, and Golan 2008).
All categories together totaled sales of $99 billion by 2009, representing the fastest growing
segment of the pharmaceutical industry. In particular, mAb-based products constitute the most
preeminent group of the biopharmaceutical market, as demonstrated by the presence of five
mAb products in the top-ten-selling biopharmaceuticals of 2010 (and four in the top five) (Table
1.1) (Walsh 2010; Huggett, Hodgson, and Lahteenmaki 2011). Indeed, the recombinant mAbs
currently licensed represent a substantial success both in terms of revenue generated and
clinical benefit delivered, with therapeutic applications ranging from the dominant areas of
oncology, rheumatoid and autoimmune diseases, to other indications such as organ
transplantation, cardiology, viral infection, allergy, tissue growth and repair, and hemoglobinuria
(Beck et al. 2008; Jefferis 2009). Furthermore, with 240 mAb products currently in clinical trials,
along with an additional 120 recombinant proteins, it is expected that mAb-based approvals will
continue to dominate the market in the coming years (Sheridan 2010).
The efficacy of mAbs is a result of their specificity for target antigens and of their biological
activities, also called ‘effector functions’, which might be activated by the immune complexes
formed (Jefferis 2006; Jefferis 2009; Natsume, Niwa, and Satoh 2009). These effector functions
of mAbs diverge among the five distinct classes defined within human antibodies
(imunoglobulins, Ig): IgM, IgG, IgA, IgD and IgE (Burton and Woof 1992). Of these, the IgG class
has been the most studied due to its predominance in serum, and as a result of the accumulated
knowledge about its structure and function it became the class of choice in recombinant
technology for therapeutic application, currently comprising all the approved mAbs (Jefferis
2009; Wagner-Rousset et al. 2008; Natsume, Niwa, and Satoh 2009; Beck et al. 2008).
CHAPTER 1 │ GENERAL INTRODUCTION
8
TABLE 1.1. The top-ten-selling biopharmaceutical products of 2010 (adapted from Huggett, Hodgson, and
Lahteenmaki 2011)
NAME CLASS INDICATION SALES $ billions
COMPANY
ENBREL
(etanercept)
Fusion protein Rheumatoid and psoriatic arthritis, ankylosing
spondylitis, psoriasis
6.808 Amgen
HUMIRA
(adalimumab)
Monoclonal
antibody
Rheumatoid and psoriatic arthritis, psoriasis, ulcerative
colitis, ankylosing spondylitis, Crohn’s disease
6.548 Abbott
REMICADE
(infliximab)
Monoclonal
antibody
Psoriasis, ulcerative colitis, ankylosing spondylitis,
Crohn’s disease, psoriatic and rheumatoid arthritis
6.478 Johnson &
Johnson
AVASTIN
(bevicuzumab)
Monoclonal
antibody
Colorectal, breast, brain, renal cell, and non-small cell
lung cancers
6.193 Roche
RITUXAN
(rituximab)
Monoclonal
antibody
Non-Hodgkin’s lymphoma, rheumatoid arthritis, chronic
lymphocytic leukemia
6.088 Biogen-Idec
HERCEPTIN
(trastuzumab)
Monoclonal
antibody
Breast cancer 5.210 Roche
LANTUS
(insulin glargine)
Hormone Diabetes mellitus, type 1 and 2 4.653 Sanofi
LOVENOX
(enoxaparin)
Low molecular
weight heparin
Venous thromboembolism, acute coronary syndrome 3.722 Sanofi
NEULASTA
(pegfilgrastim)
Growth factor Neutropenia/leucopenia 3.558 Amgen
COPAXONE
(glatiramer)
Immunomodulator Multiple sclerosis 3.315 Teva
MAbs of the IgG class have a basic structure of two light and heavy chains in covalent and
non-covalent association, with variable and constant regions, that result in the formation of three
independent protein moieties – two fragment antigen binding (Fab) regions and one fragment
crystallisable (Fc) region – which are connected through a flexible linker named the hinge region
(Figure 1.1) (Natsume, Niwa, and Satoh 2009; Beck et al. 2008).
CHAPTER 1 │ GENERAL INTRODUCTION
9
FIGURE 1.1. Representation of the structure of a human IgG antibody, composed of two light chains (L, represented
by traced rectangles) and two heavy chains (H, represented by empty rectangles). Both L and H chains contain
variable (VL, VH) and constant (CL, CH1-3) regions. The light chains are connected to the heavy chains by disulfide
bonds forming three independent protein moieties, two fragment antigen binding (Fab) and one fragment
crystallisable (Fc), which are connected through the hinge region. The CH2 domains in the Fc region contain a highly
conserved site (represented by a star) for the covalent attachment of a glycan (adapted from Natsume, Niwa, and
Satoh 2009).
Both Fab regions of an individual antibody are identical in structure and express a specific
antigen-binding site. For its turn, the Fc region expresses interaction sites for ligands that activate
the effector mechanisms (Jefferis, Lund, and Pound 1998; Jefferis and Lund 2002). These
effector ligands include three homologous cellular Fc receptor types (FcγRI, FcγRIIa-c,
FcγRIIIa,b), the C1q component of the complement, and the neonatal Fc receptor (FcRn)
(Nimmerjahn and Ravetch 2008; Burton and Woof 1992). The interaction sites of the Fc region
to the effector ligands are mostly located in the hinge and in the second domain of the constant
region of the heavy chains (CH2) (Figure 1.1). These CH2 domains bear a highly conserved site
(asparagine 297, Asn-297) for the covalent attachment of a glycan, which strongly influences the
conformation of the Fc region and its effector functions (Wuhrer et al. 2007; Clark 1997; Morgan
et al. 1995; Burton and Woof 1992).
As a consequence of the IgG structure, the physiological activities may be mediated by three
mechanisms (Figure 1.2): the direct neutralization of the antigen and/or induction of apoptosis
through the specific and bivalent binding to the target antigen in the Fab region; the activation of
the complement cascade through the initial binding and activation of the C1q molecule in the Fc
CHAPTER 1 │ GENERAL INTRODUCTION
10
region, which culminates in complement
inflammatory and immunoregulatory molecules;
macrophage, natural killer (NK) cells) and mediation of antibody
(ADCC) through the binding of the Fc receptor in the IgG to the IgG
leucocytes. Additionally, the FcRn receptor controls the catabolic half
has a role in placental transpor
Woof 1992; Nimmerjahn and Ravetch 2008
FIGURE 1.2. Illustration of the antibody mechanisms for the elimination of antigen by (a) apoptosis, (b) antibody
dependent cellular cytotoxicity (ADCC)
activation of the C1 component of complement
The IgG class of mAbs is further divided into four subclasses, defined by different heavy
chains and numbered according to their relative concentration in serum: IgG1, IgG2, IgG3, and
IgG4 (Beck et al. 2008). Each subclass
choice when developing recombinant mAb therapeutics is being
critical decision, and may vary with the specific therapeutic application
Braslawsky 2002). For example, in oncology it seems beneficial to maximize the potential to
region, which culminates in complement-dependent cytotoxicity (CDC) and generation of
inflammatory and immunoregulatory molecules; and the stimulation of effector cells (
macrophage, natural killer (NK) cells) and mediation of antibody-dependent cellular cytotoxicity
(ADCC) through the binding of the Fc receptor in the IgG to the IgG-Fc receptors present in
leucocytes. Additionally, the FcRn receptor controls the catabolic half-life of the IgG molecule and
has a role in placental transport from mother to fetus (Wagner-Rousset et al. 2008
Nimmerjahn and Ravetch 2008; Basta 2008; Kibe et al. 1996).
Illustration of the antibody mechanisms for the elimination of antigen by (a) apoptosis, (b) antibody
(ADCC) mediated by cross-linking of leucocyte IgG-Fc receptors, (c) engagement and
activation of the C1 component of complement (adapted from Jefferis 2009).
The IgG class of mAbs is further divided into four subclasses, defined by different heavy
chains and numbered according to their relative concentration in serum: IgG1, IgG2, IgG3, and
. Each subclass expresses a unique profile of effector functions, and
choice when developing recombinant mAb therapeutics is being increasingly considered as a
critical decision, and may vary with the specific therapeutic application (Reff, Hariharan, and
mple, in oncology it seems beneficial to maximize the potential to
dependent cytotoxicity (CDC) and generation of
ation of effector cells (e.g.
ependent cellular cytotoxicity
Fc receptors present in
life of the IgG molecule and
Rousset et al. 2008; Burton and
Illustration of the antibody mechanisms for the elimination of antigen by (a) apoptosis, (b) antibody-
Fc receptors, (c) engagement and
The IgG class of mAbs is further divided into four subclasses, defined by different heavy
chains and numbered according to their relative concentration in serum: IgG1, IgG2, IgG3, and
expresses a unique profile of effector functions, and its
increasingly considered as a
Reff, Hariharan, and
mple, in oncology it seems beneficial to maximize the potential to
CHAPTER 1 │ GENERAL INTRODUCTION
11
induce ADCC and CDC to eliminate the target cancer cells; however, in chronic diseases the
central objective might be the neutralization of a soluble target, without excessive effector activity,
which could be detrimental if the target is also a membrane protein on host cells (Jefferis 2009;
Jefferis 2006). Therefore, although the predominant choice for therapeutic applications is
currently IgG1, as a consequence of its long-life in serum (about 21 days) and its enhanced
effector functions, the other IgG subclasses are now also being evaluated (Burton and Woof
1992; Wuhrer et al. 2007; Clark 1997; Jefferis 2009, 2007; Beck et al. 2008). In particular, the
IgG2 appears as a good alternative when minimum effector functions are desired, also
demonstrating a long serum half-life and stability (Jefferis 2006; Jefferis 2007).
1.3. EXPRESSION SYSTEM
The choice of an expression system (host cell) for the production of therapeutic proteins has a
profound impact on the product characteristics and the maximum expression yields that are
possible to obtain (Jayapal et al. 2007). Therefore, a number of requirements should be met by
the cells to be apt for biopharmaceutical application. First, cells should be amenable to genetic
modifications, allowing the easy introduction of foreign deoxyribonucleic acid (DNA), and be able
to support high-level product expression over long periods of time while maintaining high viable
cell density and genetic stability. Secondly, from an industrial perspective it is highly desirable
that cells are able to adapt to growth in suspension and serum-free conditions to allow for
volumetric and simple scalability, and to reduce safety concerns about the presence of animal-
derived components. Thirdly, for the production of complex proteins with correct pharmacokinetic
and pharmacodynamic properties, cells should be capable of performing adequate (human-like)
post-translational processing. Lastly, cells should be safe for human use, not allowing the
propagation of any adventitious pathogenic agents that may eventually find their way into humans
(Ozturk and Hu 2006; Jayapal et al. 2007).
Considering these characteristics, a diversity of expression systems have been considered for
the production of therapeutic proteins, including bacteria (Waegeman and Mey 2012), yeast
(Cereghino and Cregg 2000; Schumann and Ferreira 2004), insect (Kost, Condreay, and Jarvis
CHAPTER 1 │ GENERAL INTRODUCTION
12
2005; Kirkpatrick et al. 1995), plant (Hellwig et al. 2004; Soderquist and Lee 2005) and
mammalian (Dingermann 2008; Durocher and Butler 2009) cells, each system possessing
different advantages and limitations, as resumed in Table 1.2.
TABLE 1.2. Advantages and limitations of different expression systems for therapeutic glycoprotein production (Dasgupta
et al. 2007; Durocher and Butler 2009; Zhu 2011; Altmann et al. 1999; Harcum 2006; Hellwig et al. 2004)
EXPRESSION SYSTEM MARKETED PRODUCTS MAIN ADVANTAGES (+) AND LIMITATIONS (-)
BACTERIA
Insulin, human growth
hormone
+ Simple and fast production, low costs, high productivity
- Unable to perform glycosylation
YEAST
Insulin, human growth
hormone, hirudin, albumin
+ Robust expression, scalable fermentation, high titers
- Glycosylation potentially immunogenic to humans
INSECT CELLS None + Low costs, simple and fast production, safety
- Glycosylation potentially immunogenic to humans
PLANT CELLS Glucocerebrosidase (2012
approval)
+ Inexpensive and simple culture, intrinsically safe
(neither harbor pathogens nor produce endotoxins)
- Glycosylation potentially immunogenic to humans
MAMMALIAN CELLS Many, including interferon,
mAbs, erythropoietin, and
tissue plasminogen activator
+ Human-like glycosylation
- High cost of goods, potential to propagate infectious
agents, long development time
At the moment, biopharmaceutical manufacturing is mostly relying on mammalian cell
expression systems, as indicated by the preeminence of therapeutics approved by the Food and
Drug Administration (FDA) produced in these cells (Zhu 2011; Walsh 2010; Wurm 2004;
Andersen and Reilly 2004). The main motivator of this preference is the ability of mammalian
cells to synthesize proteins that are similar to those naturally occurring in humans with respect to
structure and biochemical properties (Zhu 2011).
Among mammalian systems, the Chinese hamster ovary (CHO) cells are undoubtedly the
dominant choice, accounting for nearly 70 % of all recombinant protein therapeutics currently
produced (Jayapal et al. 2007; Walsh 2010), which include four of the top-five selling
biopharmaceuticals in 2010 (Enbrel, Humira, Avastin and Rituxan) (Huggett, Hodgson, and
Lahteenmaki 2011). The extensive use of CHO cells is related to the compliance with most of the
CHAPTER 1 │ GENERAL INTRODUCTION
13
requirements mentioned above, which include ease of transfection, presence of a powerful gene
amplification system, ease of adaptation to growth in suspension and serum-free medium, ability
to grow at high densities, ability to perform human-like post-translational modifications, and
safety of the product (Wurm 2004; Butler 2004; Trill, Shatzman, and Ganquly 1995; Mohan et
al. 2008). Additionally, the knowledge and expertise accumulated during two decades of
commercial production with CHO cells will ease the process of FDA approval for production of
new CHO-based therapeutics (Jayapal et al. 2007; Durocher and Butler 2009).
Other mammalian cells have also been used, although to a lower extent, including murine
myeloma (NS0 and Sp2/0) and baby hamster kidney (BHK-21) cells (Birch and Racher 2006;
Zhang 2010; Walsh 2010). Similarly to CHO, these cells are able to grow at high densities, in
suspension and serum-free culture, and are readily transfected (Trill, Shatzman, and Ganquly
1995; Butler 2004).
More recently, human cells have become quite attractive to the biopharmaceutical industry,
mainly due to their ability to produce genuine human post-translational modifications (Swiech,
Picanço-Castro, and Covas 2012; Niklas et al. 2011; Schräder et al. 2011). Some cell lines (e.g.
human embryonic kidney (HEK) and human embryonic retinal (PER.C6) cells) have shown
efficient production at laboratory scale, but their application in commercial biopharmaceutical
production is still on its very beginning and is therefore still limited (Swiech, Picanço-Castro, and
Covas 2012; Schiedner et al. 2008; Zhu 2011). In particular, the human retina-derived PER.C6
cell line has shown interesting characteristics for therapeutic protein expression, particularly high
production titers and rapid development of high-producing stable clones (in a few months) due to
the absence of requirements for gene amplification or selective marker (Wurm et al. 1992; Jones
et al. 2003; Zhu 2011).
1.4. TRANSFECTION
Transfection is the process that introduces foreign nucleic acids into cells to genetically
modify them (Kim and Eberwine 2010). In biopharmaceutical manufacturing, this process is
applied to introduce the gene of the desired therapeutic protein into the selected mammalian
CHAPTER 1 │ GENERAL INTRODUCTION
14
host cell to obtain producer cells. Two types of transfections, transient and stable (Figure 1.3),
are routinely performed in mammalian systems, depending on the nature of the genetic materials
(Kim and Eberwine 2010; Kingston 2003).
FIGURE 1.3. Schematic diagram of (a) transient transfection and (b) stable transfection of foreign genetic material
(DNA, grey wave) into mammalian cells. In transient transfection (a) the foreign DNA enters the nucleus and is
expressed only temporarily due to a rapid loss of the foreign genetic material by environmental factors and cell
division. In stable transfection (b) the foreign DNA enters the nucleus and is integrated into the genome of the host
cell, allowing its stable expression over extended periods of time.
Transient transfection relies on the introduction of the foreign genetic material into the
nucleus of the host cell where it is replicated as an extrachromosomal unit (Ozturk and Hu 2006;
Recillas-Targa 2006; Ma and Chen 2005). This results in a fast process of transfection, but with
temporary levels of production due to the rapid loss of the genetic material by environmental
factors and cell division (Kim and Eberwine 2010; Ozturk and Hu 2006; Liao and Sunstrom
2006). In stable transfection, the foreign genetic material is introduced into the nucleus and
integrated into the genome of the host cell, which permits sustaining the gene expression over
extended periods of time (Glover, Lipps, and Jans 2005; Ozturk and Hu 2006; Ma and Chen
2005). Approximately one in ten thousand cells in a transfection will stably integrate the nucleic
acid (Mortensen and Kingston 2009); therefore, selectable markers can be used to enable the
identification and selection of these stably transfected cells by the characteristics provided by the
(a)
Nucleus
Expression
Transfection
DNA
(b)
Nucleus
Expression
Transfection
Integration
DNA
CHAPTER 1 │ GENERAL INTRODUCTION
15
marker. This form of transfection ultimately delivers larger quantities of protein from cells (Rosser
et al. 2005), but it is labor-intensive, time-consuming, and requires considerable investment on
resources/equipment (Ozturk and Hu 2006; Rosser et al. 2005).
The choice between stable or transient transfection depends on the objective of the
experiment. For clinical or commercial (large-scale) purposes stable transfection is usually the
preferred method (Wurm 2004), while transient transfection is mostly valuable for high-
throughput screening in drug discovery processes, in vivo evaluation and early product analysis
(Liao and Sunstrom 2006; Ozturk and Hu 2006; Rosser et al. 2005).
1.4.1. EXPRESSION VECTOR
The expression of heterologous proteins in mammalian cells requires the use of specialized
vectors to transfer the gene of the product into the cells (Özdemir 1998). These vectors should
display three main features: expression levels independent from the site of integration in the
genome, expression levels correlated to the number of integrated transgene copies, and
maintenance of expression efficiency over time (Blaas et al. 2009). As a consequence of these
requirements, mammalian vectors are usually plasmids, circular DNA molecules that exist in
bacterial cells apart from their main chromosome, and are able to replicate within cells
independently from bacterial or eukaryotic chromosomes (Özdemir 1998; Nehlsen et al. 2009).
For the expression of recombinant proteins in mammalian cells, plasmids should include the
following elements: (i) a promoter/enhancer that drives the expression of the coding regions of
the gene of interest, a critical element for efficient expression which typically consists of a strong
viral promoter/enhancer such as cytomegalovirus (CMV) and simian virus 40 (SV40) (Mortensen
and Kingston 2009; Carswell and Alwine 1989; Ozturk and Hu 2006; Liao and Sunstrom 2006);
(ii) sequences that stabilize or enhance translation, such as polyadenylation signals (to extend the
half-life of messenger ribonucleic acid (mRNA) in cytoplasm), Kozak sequence (to improve the
translational initiation of mRNA of the gene of interest), and intervening sequences (to improve
mRNA stability and export from the nucleus to the cytoplasm) (Jeffs 2007; Kozak 1986; Kozak
1995; Huang and Gorman 1990; Wurm 2004). Additionally, the generation of a stable producing
cell line requires the use of a sequence encoding a selectable marker gene, either on a separate
CHAPTER 1 │ GENERAL INTRODUCTION
16
or on the same expression vector as the recombinant gene (Wurm 2004; Mortensen and
Kingston 2009).
The integration of the expression vector into the genome of the host mammalian cell occurs
randomly, being simple and straight forward but lacking reproducibility (Blaas et al. 2009).
Indeed, it has been shown that the site of integration influences the transcription rate of the
recombinant gene, a phenomenon known as the position effect (Wurm 2004; Eszterhas et al.
2002). Depending on the surrounding chromatin by the integration site, expression of the
product can be high, low or even null (Wurm 2004). Furthermore, the expression of the
recombinant gene tends to be inactivated (silenced) over time (Wurm 2004; Blaas et al. 2009).
Consequently, the selection of suitable high-producing clones becomes tedious and time
consuming (Wurm 2004). To overcome the position effects different strategies have been
developed (Kwaks et al. 2003; Huang et al. 2007; Wang, Yang, et al. 2008) and include the use
of anti-repressor elements flanking the vectors (e.g. expression augmenting sequence elements,
EASE) (Kwaks et al. 2003), the integration of vectors specifically into chromosomal loci with open
chromatin (highly transcribed) (Huang et al. 2007), and the use of nuclear regulatory factors
(matrix-attachment regions (MARS) or scaffold-attachment regions (SARS)) (Girod, Zahn-Zabal,
and Mermod 2005; Wang, Yang, et al. 2008).
The design of expression vectors presents additional issues when mAbs are concerned.
Indeed, the structure of heavy and light chain subunits, whose interaction influences the kinetics
of mAb assembly, (Li et al. 2007) results in the need to express these subunits at optimal
stoichiometric ratios (of equal extent) (Li et al. 2007; Schlatter et al. 2005). This has led to the
development of different strategies for vector design (Ozturk and Hu 2006), with the most
common consisting of the use of two vectors, one for each chain, for co-transfection into the cells
(Schlatter et al. 2005; Leitzgen, Knittler, and Haas 1997). Their relative expression is controlled
by the proportion of each gene used in the co-transfection cocktail. Nevertheless, this control is
not accurate (Fussenegger et al. 1999; Kaufmann and Fussenegger 2003) and this approach is
considered to be the least efficient to obtain a balanced expression of both chains (Wurm 2004).
Alternatively, a single vector using two identical promoters, one for each chain, can be used (Li et
al. 2007). Although a single vector system has the advantage of assuring equal introduction of
genes into cells, the randomness of their integration into the cell genome remains a problem that
results in inaccurate control of the relative expression of these genes (Yuansheng et al. 2009). A
more accurate control of the relative expression of multiple genes across a transfected cell pool
CHAPTER 1 │ GENERAL INTRODUCTION
17
can be achieved with a single vector containing multiple compatible inducible promoters, with
each gene under the control of one independent promoter (Yahata et al. 2005; Kunes et al.
2009). This allows the introduction of an equal amount of different genes into each cell (Belshaw
et al. 1996), and also the simultaneous variation of the expression level of different genes by
changing the concentration of the corresponding chemical inducers (Belshaw et al. 1996;
Hartenbach et al. 2007; Mijakovic, Petranovic, and Jensen 2005).
1.4.2. SELECTABLE MARKERS FOR STABLE TRANSFECTION
As mentioned above, the difference between a transient and a stable transfection is the
incorporation of the nucleic acid into the genome of the host cell in the latter. To isolate the
stably transfected cells, a selection strategy must be implemented to provide the transfected cell
with a growth advantage in culture. For this, a selectable marker is transfected into the cells
along with the gene of interest (Mortensen and Kingston 2009; Wurm 2004). There are several
types of markers available for mammalian expression systems, which can be divided into
recessive and dominant classes (Shen et al. 2006). The markers providing recessive resistance
have specific requirements for the host cells, which must be deficient in the activity by which they
will be selected; whereas the genes conferring dominant resistance can be used independently of
the phenotype of the cell (Castillo 2008; Keown, Campbell, and Kucherlapati 1990; Shen et al.
2006). Some common selection markers are shown in Table 1.3.
The selection systems using a dominant marker are based on resistance to antibiotics or
detoxification of the effects of a protein synthesis inhibitor on the cell. A large number of drugs
are available for this purpose, including the most routinely used aminoglycoside
phosphotransferase (Aph), hydromycin-B phosphotransferase (Hph) and puromycin N-
acetyltransferase (Pac) (Castillo 2008; Shen et al. 2006). The antibiotic-resistance marker allows
the transfected cells to survive in a culture containing the corresponding antibiotic (G418,
hygromycin B and puromycin, respectively), while cells that do not have the marker stably
integrated into their genome perish after several weeks in culture (Mortensen and Kingston
2009).
CHAPTER 1 │ GENERAL INTRODUCTION
18
TA
BLE
1.3
. Characteristics of selective markers commonly used in expression vectors for the stable transfection of mammalian cells (Li et al. 2010; Shen et al. 2006; Mortensen and
Kingston 2009; Castillo 2008)
SELECTABLE MARKER
REQUIREMENTS
SELECTIVE AGENT
INHIBITOR FOR
AMPLIFICATION
BASIS FOR SELECTION
DOMINANT
Aminoglycoside
phosphotransferase (Aph)
Geneticin (G418)/Neomycin
G418 blocks protein synthesis in mammalian cells. Gene expression results in
detoxification of G418.
Hygromycin-B phosphotransferase
(Hph)
Hygromycin-B
Hygromycin-B inhibits protein synthesis. Gene expression detoxifies hygromycin-B
by phosphorilation.
Puromycin N-acetyltransferase
(Pac)
Puromycin
Puromycin inhibits protein synthesis. The gene encodes an enzyme for the
inactivation of puromycin by acetylation.
Zeocin/Bleomycin resistance gene
(sh ble)
Zeocin/Bleomycin
The gene encodes a protein that stoichiometrically binds the zeocin/bleomycin and
inactivates it.
Histidinol dehydrogenase
(hisD)
Histidinol
Medium deficient in histidine and containing histidinol will not support cell growth.
The gene encodes an enzyme that detoxifies histidinol.
RECESSIVE
Thymidine kinase
(TK)
Cells deficient in TK activity
Media containing hypoxanthine,
aminopterin, thymidine (HAT)
TK is essential for cell growth in the presence of aminopterin, blocker of thymidine
synthesis. The gene allows cell survival in HAT media (contains aminopterin).
Dihydrofolate reductase
(DHFR)
Cells lacking DHFR activity (it can
be used in cells expressing DHFR
through the application of MTX)
Media lacking glycine,
hypoxanthine and thymidine
Methotrexate
(MTX)
DHFR is required for purine biosynthesis. The gene allows cell growth without
exogenous purines. Amplification is obtained by increasing MTX concentrations, an
inhibitor of DHFR.
Glutamine synthase
(GS)
Cells not expressing glutamine (it
can be used with cells expressing
GS though the application of MSX)
Glutamine-free media
Methionine
sulfoximine
(MSX)
GS is essential for glutamine formation. MSX inhibits endogenous GS activity, so
without glutamine supplemented in the medium, only cells transfected with GS are
able to survive.
Hypoxanthine phosphoribosyl
transferase (HPRT)
Cells lacking HPRT activity
Media containing HAT
HPRT is essential for purine synthesis via the normal salvage pathway. HAT blocks
the de novo purine synthesis. Cells expressing HPRT are able to survive through
the salvage pathway.
CHAPTER 1 │ GENERAL INTRODUCTION
19
In selection systems relying on recessive markers, selection is based on restoring an
enzyme or protein that is critical for cell survival, and therefore requires host cells that are
deficient in that activity. In the non-transfected host cell, the requirement for the activity is
replaced by supplementing the media with the metabolic byproduct of the enzyme’s action. But
upon withdrawal of these media components, only cells that acquired the needed activity through
transfection are able to survive (Shen et al. 2006). Some of the recessive markers promote a
phenomenon called gene amplification, which consists of applying increasing concentrations of
the selection agent to stimulate cells to increase the number of copies of the marker gene
(Mortensen and Kingston 2009; Castillo 2008). The significant feature of gene amplification is
that regions of the chromosome which are adjacent to the marker gene are also amplified, hence
the gene of the product of interest that is co-transfected with the marker gene will also be
amplified and overexpressed (Mortensen and Kingston 2009). The two most commonly used
amplifiable systems are based on dihydrofolate reductase (DHFR) with methotrexate (MTX)
amplification in DHFR- CHO cells, and glutamine synthetase (GS) with methionine sulfoxamide
(MSX) amplification in both CHO-K1 and murine myeloma NS0 cells (Bebbington et al. 1992;
Jeffs 2007; Wurm 2004; Page and Sydenham 1991; Castillo 2008).
The DHFR expression system is based on the dhfr gene coding for the DHFR enzyme, which
is involved in nucleotide metabolism (Wurm 2004) by catalyzing the conversion of dihydrofolate
to tetrahydrofolate (Chusainow et al. 2009). In the absence of tetrahydrofolate, the primary
pathway for synthesis of purines and pyrimidines is inhibited, and the salvage pathway that
involves the conversion of hypoxanthine and thymidine can be used. Therefore, if cells deficient
in HPRT are supplied with glycine, hypoxanthine, and thimidine from an exogenous source, they
are able to survive. However, if the media is not supplemented with these precursors, the cells
will die unless they have acquired the ability to express DHFR through transfection (Shen et al.
2006; Wurm 2004). The process of amplification in this system is based on the use of MTX, a
potent inhibitor of the DHFR enzyme. Using increasing concentrations of MTX, transfected cells
containing the dhfr gene will have to increase their capacity for DHFR synthesis in order to
survive, by amplifying the dhfr gene (Chusainow et al. 2009; Andersen and Reilly 2004). The
gene of interest that is located in the same expression vector as the dhfr gene or adjacently
resides in the host chromosomal DNA will also be co-amplified (Kaufman 1990).
In the GS systemTM (Lonza), the glutamine metabolism in mammalian cells is explored.
Glutamine formation follows an enzymatic pathway of biosynthesis from glutamate and
CHAPTER 1 │ GENERAL INTRODUCTION
20
ammonium which is dependent of the GS enzyme. Without glutamine in the growth medium, this
GS enzyme is essential for the survival of mammalian cells in culture (Wurm 2004; Shen et al.
2006). Since some cell lines do not express sufficient GS to survive, it is possible to use a
transfected GS gene as a selectable marker by permitting growth in a glutamine-free medium
(Barnes, Bentley, and Dickson 2000; Shen et al. 2006). Cell lines that express sufficient GS to
survive can also be used with the GS system through the application of MSX, an inhibitor of the
endogenous GS activity (Castillo 2008; Shen et al. 2006). Thus, only the transfectants with
additional GS activity are able to survive. It is also possible to perform gene amplification using
increasing levels of MSX, in a similar manner to MTX in the DHRF system. It has been shown
that the GS system has a time advantage over the DHFR system during development, and
requires fewer copies of the recombinant gene per cell (Brown et al. 1992), allowing a faster
selection of high-producing cell lines.
A more recently explored selectable marker consists of the HPRT gene. A system developed
at University of Edinburgh, known as OSCARTM system, relies on a series of partially disabled
minigene vectors that encode for hypoxanthine phosphoribosyltransferase (HPRT), essential for
purine synthesis via the normal cellular salvage pathway (Barnes, Bentley, and Dickson 2001).
HPRT-deficient mammalian cells transfected with one of these minigenes along with the gene of
interest are placed in a selective hypoxanthine aminopterin thymidine (HAT) medium that blocks
the de novo purine synthesis. Consequently, cell survival becomes dependent on the salvage
pathway using a disabled HPRT enzyme, and only the transfected cells are able to grow.
Furthermore, since large amounts of the disabled HPRT enzyme are required for cell survival,
gene amplification occurs. This implies that selection and amplification occur in a single step,
providing a time advantage of the OSCARTM system over both DHFR and GS systems which
require multiple rounds of amplification after selection (Melton et al. 2001).
1.4.3. DELIVERY METHODS
For both transient and stable transfection, the introduction of the gene of interest into the
mammalian cells can be accomplished by several delivery methods, whose ideal characteristics
include high transfection efficiency, low cell toxicity, minimal effects on normal cell physiology,
ease to use, and reproducibility (Kim and Eberwine 2010). The methods which are commonly
CHAPTER 1 │ GENERAL INTRODUCTION
21
used today can be generally divided into three categories: biological, chemical and physical, as
shown in Table 1.4, and their choice is dependent on cell type, purpose intended, as well as
economic and technical factors (Ma and Chen 2005).
TABLE 1.4. Comparison of biological, chemical and physical methods for the delivery of genetic material into cells
BIOLOGICAL CHEMICAL PHYSICAL
CHARACTERISTIC Vírus-
mediated
Cationic
polymer
Cationic
lipid
Calcium
phosphate
Electroporation Microinjection Biolistic
Immunogenicity + - +/- - - - -
Cytotoxicity + + + + - - +/-
Limited insert size + - - - - - -
Safety risk + - - - - - -
Simple handling - + + + + - +
Expeditious - + + + + + +
Efficiency in adherent cells + +/- + +/- + + +
Efficiency in suspended
cells + - - - - - +
Viability High High High High Low High Low
Costs High Low Low Low Moderate High High
The biological method of virus-mediated transfection, also known as transduction, is highly
efficient and easy to achieve due to the viral nature of integration into the host genome,
characteristics that make it the most commonly used method in clinical research (Kim and
Eberwine 2010; Pfeifer and Verma 2001). However, the potential dangers of immunogenicity and
cytotoxicity associated with this form of transfection, particularly for applications in gene therapy
and manufacturing of therapeutics, has led to the development of safer and more adequate non-
viral approaches (Glover, Lipps, and Jans 2005; Wurm 2004; Cavazzana-Calvo, Thrasher, and
Mavilio 2004).
In contemporary research, chemical methods are the most widely used, relying on carrier
molecules to overcome the cell-membrane barrier (Kim and Eberwine 2010), and include
cationic polymer, calcium phosphate, and cationic lipid transfection (Holmen et al. 1995;
Schenborn and Goiffon 2000; Washbourne and McAllister 2002; Jordan, Schallhorn, and Wurm
1996; Derouazi et al. 2004; Tait et al. 2004). The principle of these methods consists on the
interaction between the negatively charged nucleic acids with the positively charged chemicals
CHAPTER 1 │ GENERAL INTRODUCTION
22
(i.e. polymers and lipids), forming a positively-charged complex that is attracted to the negatively
charged cell membrane and is then incorporated into the cell apparently by endocytosis (Kim and
Eberwine 2010; Graham and van der Eb 1973; Wilson and Smith 1997; Ozturk and Hu 2006).
They have the advantages of simple performance, absence of mutagenesis, and no limitation on
the size of the packaged nucleic acid. However, the transfection efficiency is highly variable,
depending on factors such as the cell type, the relative concentrations of reagents and nucleic
acid, as well as environmental (pH, temperature) and cell membrane conditions (Ozturk and Hu
2006; Kim and Eberwine 2010; Gao and Huang 1995).
More recently, physical transfection methods have been developed to enable the direct
transfer of nucleic acids into the cell cytoplasm or nucleus by physical or mechanical means.
These methods include electroporation, microinjection, and biolistic particle delivery. Of these,
electroporation is the most widely used for being very simple and fast (Ozturk and Hu 2006;
Chusainow et al. 2009; Kim and Eberwine 2010). In this technique, a pulsed electric field
disrupts the voltage gradient across the plasma membrane, presumably creating reversible pores
that allow the entry of the nucleic acid into the cell (Canatella et al. 2001; Kingston 2003). This
method is very efficient and can be used with virtually any type of cell, but requires the
optimization of parameters like amplitude and length of pulse for each case (Ozturk and Hu
2006; Kingston 2003). Furthermore, due to a low cell viability after transfection, electroporation
requires more cells and nucleic acid than other transfection methods (Ozturk and Hu 2006;
Potter and Heller 2010).
In microinjection, the nucleic acid is directly injected into the cytoplasm or nucleus of the
cell, creating a highly efficient transfection, but with the limitations of a very time-consuming and
expensive procedure (Kim and Eberwine 2010) that requires specialized operator skills, and of
the inadequacy to the transfection of a large number of cells (Rose 2007).
In biolistic particle delivery, the nucleic acid adheres to biological inert particles (i.e. gold or
tungsten) forming conjugates that are shot into recipient cells at a high velocity (Kim and
Eberwine 2010; Ma and Chen 2005). This method is reliable but requires expensive instruments
and causes physical damage to the cells, therefore requiring the use of high cell numbers (Kim
and Eberwine 2010).
CHAPTER 1 │ GENERAL INTRODUCTION
23
1.4.4. SELECTION
To generate stable producer cell lines, the transfected cells are subjected to a process of
screening to select those with the most desirable characteristics.
In a first stage of screening, the cell pool obtained after transfection is cultured under
conditions that allow the selective survival of the cells successfully transfected with the marker
gene (e.g. using medium lacking glycine, hypoxanthine and thymidine, and containing low levels
of MTX, for DHFR) (Chisholm 1995; Jayapal et al. 2007). The surviving cells, presumably
expressing the product of interest, are recovered and can be subjected to gene amplification, by
repetitive rounds of exposure to higher concentrations of inhibitors of selective markers (i.e. MTX
for DHFR) (Ozturk and Hu 2006; Li et al. 2005), which in most cases leads to the generation of a
pool of cells containing clones with enhanced expression levels (Ozturk and Hu 2006; Li et al.
2005). However, this pool is heterogeneous, composed of cells with different integration sites,
copy numbers, and varying specific productivities; therefore, a series of limiting dilutions are
performed in multi-well plates, to generate single colonies with uniform cell populations that can
be isolated (Jayapal et al. 2007; Li et al. 2010), and expanded to produce clonal populations
(Wurm 2004). Each population is then evaluated, usually in terms of growth and product titer,
and the highest producers are selected for additional round(s) of cultivation and analysis (Wurm
2004; Li et al. 2005). This analysis typically includes cell growth, cell specific productivity and
volumetric productivity (titer), but may or should also incorporate product quality attributes such
as the glycosylation profile (Li et al. 2010) and other important characteristics specific to the type
of process to be used, as for example the ability to grow in serum-free medium or the resistance
to the stress and shear conditions found in bioreactors (Lloyd et al. 2000; Böhm et al. 2004).
The cell line stability is another critical factor that should be considered during selection,
since volumetric and specific productivities may decline with cell age (Li et al. 2010), and the
scale-up of the culture process to industrial levels takes significant time. Usually, cells maintained
in the presence of selective agents exhibit stable production during many months in culture
(Shen et al. 2006). However, due to the toxicity, high costs and complicated downstream
purification associated with these agents, it would be important to guaranty stability of production
without depending on their use (Barnes, Bentley, and Dickson 2001; Böhm et al. 2004; Li et al.
2005; Wurm 2004). Studies have shown that in the absence of selective pressure there are signs
of instability, with decreasing levels of production, which is often attributed to a loss of
CHAPTER 1 │ GENERAL INTRODUCTION
24
recombinant gene copies during long-term culture (Page and Sydenham 1991; Kim, Kim, and
Lee 1998; Brown et al. 1992). This is particularly critical for cells in continuous production
cultures that run over long periods in the absence of the selective agent, so care should be taken
to screen the cell line for stability or to devise expression strategies that minimize the need for
amplification (Shen et al. 2006).
The screening and selection of a highly productive and stable clone in a short time frame is
still currently a major challenge because the desired characteristics are often dependent on cell
culture conditions (Li et al. 2005; Li et al. 2010). In this sense, the use of miniaturized high
throughput bioreactors that allow full control of process parameters could help identify the best
production clone at a very early stage, by mimicking the intended final large-scale bioreactor
environment (e.g. feeding regime, final production medium) (Li et al. 2005; Li et al. 2010;
Jayapal et al. 2007).
1.5. PROCESS OPTIMIZATION AT SMALL SCALE
After transfection of the host cells with the gene of interest and selection of the clones with
the most desirable characteristics, the next step on biopharmaceutical process development is
the adaptation of cells to grow in the culture environment most suitable for production at large-
scale. This transition on cultivation conditions may impart drastic changes in cellular physiology
and consequently alter cell growth, product yield and product quality. Therefore, it is also an
established practice to monitor and optimize different culture parameters to improve these
characteristics, while simultaneously searching for ways to reduce the costs associated.
1.5.1. MODE OF GROWTH
The production of therapeutic proteins usually requires large-scale processes to satisfy the
market demands. In these processes, cells are commonly grown in suspension due to several
advantages provided over the adherent mode of growth. Of these, perhaps the major advantage
CHAPTER 1 │ GENERAL INTRODUCTION
25
is that suspension cultures are not limited by the surface available to adhesion, therefore offering
a higher surface-to-volume ratio that results in increased cell densities and productivities (Ozturk
and Hu 2006). Additional benefits related to simpler scale-up and process control support the
current preference for suspension culture (Chu and Robinson 2001).
However, since the majority of mammalian cells are attachment-dependent, a period of
adaptation is required to obtain cells growing is suspension (Kwaks et al. 2003). This is usually
accomplished at low scale, by culturing the cells in adequate vessels (e.g. spinner flasks, shake
flasks or roller bottlers) and under rocking conditions (Ozturk and Hu 2006; Zahn-Zabal et al.
2001; Berson and Friederichs 2008). Some critical parameters must be considered to guarantee
a successful adaptation, such as initiating the culture with a suitable high cell density and
optimizing the rocking conditions according to the capacities of each cell type to avoid death
caused by shear (Shen et al. 2006). In fact, the sensitivity of mammalian cells to shear stresses
is one of the main problems related to suspension cultures. It limits the rocking velocities that
can be applied in the processes of production and, consequently, has strong implications on the
oxygen and nutrient distribution in large bioreactors, ultimately affecting the final product yield
(Zhu, Mollet, and Hubert 2007). Mostly for this reason, the use of adherent culture for large-scale
production has not been completely put aside, with several developments made in the field.
These have mainly focused on maximizing the surface-to-volume ratio of adherent culture, with
the most successful system currently available being microcarrier culture (Ziao et al. 2002;
Tharmalingam et al. 2011; Knibbs et al. 2003). Microcarriers are small beads that may be solid
(microporous microcarriers) or porous (macroporous microcarriers), which allow growth of cells
in their external and internal (only for macroporous) surface and are maintained in suspension in
the culture medium (Wurm 2004; Blüml 2007; Ozturk and Hu 2006). Therefore, this system
provides a pseudo-suspension culture for anchorage-dependent cells with increased surface area
available for cell adhesion and growth, combining the advantages of both adherent and
suspension cultures (Blüml 2007; Hirtenstein et al. 1980; Rudolph et al. 2008). Among them are
improved cell densities and productivities, protection against shear stress, easy scale-up, and
simplified downstream processing due to cell retention (Blüml 2007; Ozturk and Hu 2006;
Tharmalingam et al. 2011).
CHAPTER 1 │ GENERAL INTRODUCTION
26
1.5.2. MEDIUM
The supplementation of basal culture media with animal serum is essential for cell growth
and proliferation, due to its rich composition of hormones, growth factors, lipids, and trace
elements (Brunner et al. 2010). It also offers protection against potentially adverse conditions
such as pH fluctuations or shear forces, consequence of its high albumin content (Butler 2005).
However, the use of animal serum in cell culture bears a number of disadvantages for the
production of therapeutics. These include the high lot-to-lot component variability that jeopardizes
process consistency, the burden put on downstream processing due to increased protein
content, the high costs, and the risk of transmission of diseases from animals to humans
(Brunner et al. 2010; LeFloch et al. 2006; Zhang and Robinson 2005; Liu and Chang 2006).
Consequently, the removal of serum and all animal-derived components from the culture
medium is now a required step in process development for therapeutic protein production, for
both economical and safety reasons (Butler 2005; Froud 1999; Ozturk and Hu 2006; LeFloch et
al. 2006). This poses a considerable challenge for media development since it has been found
that the producer cell lines are quite fastidious in their growth requirements and these
requirements vary considerably among cell lines. Indeed, it has not been possible to develop a
single serum-free formulation to act as a serum substitute suitable for the growth of all cell lines,
like serum does. Therefore, serum-free and animal-component-free formulations are developed
according to the needs of each specific producer cell line (Butler 2005).
The adaptation of the producer cell line to these serum-free media is technologically more
challenging than the adaptation of cells to suspension growth in serum-containing media (Shen et
al. 2006). Basically two approaches are commonly used: direct adaptation, with the complete
removal of serum in a single step; or the more common gradual adaptation, by the sequential
reduction of serum concentration in the medium (Doyle and Griffiths 1998; Sinacore, Drapeau,
and Adamson 2000). Both approaches represent a major change in the cell environment,
consequently affecting cell growth, viability, and potentially product yield and quality (Shen et al.
2006; LeFloch et al. 2006; Ozturk et al. 2003). Extensive investigations to optimize medium
composition for a specific cell line are required to recover equivalent performances (Castro et al.
1992; Liu, Chu, and Hwang 2001; Liu and Chang 2006).
CHAPTER 1 │ GENERAL INTRODUCTION
27
1.5.3. PROCESS OPTIMIZATION
After cell line generation, clone selection, and cell adaptation, a stage of process
optimization is required before establishing the final process of production at large scale. This
typically involves the control and evaluation of culture parameters that influence the cell
environment, aiming to achieve a maximum product yield while maintaining acceptable product
quality profiles (Li et al. 2010; Woolley and Al-Rubeai 2009; Jain and Kumar 2008). Common
parameters include physical factors such as temperature, gas flow rate and agitation speed, and
chemical factors like dissolved oxygen (DO), carbon dioxide (CO2), pH, osmolality, and nutrient
and metabolite levels (Li et al. 2010; Jain and Kumar 2008). For example, it has been shown
that a reduction of the typical cell culture temperature (37 ºC) causes a decrease in cell growth
but may improve the specific productivity and product quality (Stiens et al. 2000; Bollati-Fogolín
et al. 2005; Yoon et al. 2005; Mohan et al. 2008; Fox et al. 2004; Oguchi et al. 2006). DO has
also been shown to influence product quality although cell growth and production levels are kept
stable within a large range (Kunkel et al. 1998; Li et al. 2005; Griffiths 2000). The nutrient and
metabolite concentrations are another limiting factor in cell culture, particularly glucose,
glutamine, lactate and ammonia levels, and have led to the development of different feeding
strategies to reduce their negative effects on the course of the culture (Kontoravdi et al. 2007;
Lao and Toth 1997; Europa et al. 2000; Altamirano et al. 2004).
Another important factor in process development is the selection of an adequate mode of
operation of the bioreactor. The most commonly used are batch, fed-batch and perfusion, each
having their advantages and limitations. Batch culture is the simplest process, consisting of an
initial inoculation of the bioreactor without any further additions or withdrawals performed during
the culture (Pierce and Shabram 2004; Noe et al. 1992; Fenge and Lüllau 2006). Consequently,
the nutrient concentration decreases over time while the concentration of waste products
increases, leading to a gradual deterioration of the cell environment that leads to reduced cell
concentrations and negative impacts on both product yield and quality (Fenge and Lüllau 2006;
Wong et al. 2010). To overcome the limitations of batch, a controlled nutrient feeding may be
performed during the course of the culture, resulting in a fed-batch mode of operation, with
increased culture longevity, cell yield and overall productivity (Fenge and Lüllau 2006; Sandadi,
Ensari, and Kearns 2005; Dorka et al. 2009; Huang et al. 2010). However, the accumulation of
waste products still occurs and may impact the product quality (Wong et al. 2010). Therefore, to
CHAPTER 1 │ GENERAL INTRODUCTION
28
provide a continuous renewal of medium with the introduction of fresh nutrients and removal of
metabolites, a perfusion process can be used (Fenge and Lüllau 2006; Voisard et al. 2003;
Adams et al. 2011). This mode of culture provides the highest cell concentrations and product
yield, and due to the reduced residence time of the product in the culture environment, the
product quality is also generally improved (Yang et al. 2000; Voisard et al. 2003; Ryll et al. 2000;
Lipscomb et al. 2005).
1.6. GLYCOSYLATION
Glycosylation is the most prevalent and structurally complex post-translational modification
naturally occurring in proteins, with more than half of the human proteins and more than one-
third of approved biopharmaceuticals being glycosylated (Wong 2005; Walsh and Jefferis 2006;
Solá and Griebenow 2010). It is a complex process that occurs in the endoplasmic reticulum
(ER) and in the Golgi apparatus, involving more than a hundred different enzymes that define the
glycan composition of the protein (Dingermann 2008; Li and d’Anjou 2009). This glycan moiety
is often critical in determining the pharmacological properties of therapeutic glycoproteins,
including conformation, stability, solubility, pharmacokinetics, in vivo activity, and immunogenicity
(Li and d’Anjou 2009; Helenius and Aebi 2001).
However, glycosylation is naturally highly variable and is also dependent of cell type- and
species-specific factors (i.e. levels of specific enzymes and availability of appropriate
monosaccharides) as well as of local environmental factors (Serrato et al. 2004; Yoon et al.
2005; Trummer et al. 2006; Crowell et al. 2007). Therefore, the choice of the expression system
(host cell) and of the culture conditions for glycoprotein production have a strong impact on the
glycosylation profile and consequently on the functionality of the protein (Royle et al. 2007). As a
result, this modification has become a major concern in biopharmaceutical production, which
now regards the quantitative analysis and monitoring of glycosylation as a means to control the
efficacy and safety of therapeutics (Hossler 2012; Hossler, Khattak, and Li 2009; Li and d’Anjou
2009).
CHAPTER 1 │ GENERAL INTRODUCTION
29
1.6.1. BASIC CONCEPTS OF GLYCOSYLATION
The tremendous diversity observed in the process of glycosylation begins with the natural
diversity of its most simple component, the monosaccharides, both in chemical structure and
connectivity. Concerning chemical structure, monosaccharides can be divided into two general
classes according to their carbonyl group: the aldoses (aldehyde group, -CH=O) and the ketoses
(ketone group, C=O). The monosaccharides of both classes (with the exception of triketose) have
at least one asymmetric carbon atom (stereocentre), which allows them to have different possible
isomeric forms (stereoisomers, same molecular formula but different three-dimensional
orientation), generating variability. An absolute configuration, D or L, is attributed to each
monosaccharide considering the configuration of the stereocentre which is further from the
anomeric center (the carbon in the carbonyl group) (D on the right and L on the left, in the Fisher
projection) (Bertozzi and Rabuka 2009). Furthermore, the monosaccharides can exist in an open
form or undergo a cyclization reaction that yields a cyclic form and produces two possible
isomers of the anomeric carbon (α and β) (Bertozzi and Rabuka 2009; Marino et al. 2010).
Regarding the chemical connectivity, the cyclic monosaccharides establish connections
between the anomeric carbon of one monosaccharide and the hydroxyl group of another to form
higher-order structures (glycans). The linkages established have a high variability due to the α
and β isomers of the anomeric carbon and the diverse hydroxyl groups that are available for
connection in the monosaccharides. Furthermore, the presence of different hydroxyl groups also
enables the involvement of the same monosaccharide in more than two linkages, which results in
the formation of branches. This branching phenomenon is unique to glycans and creates very
different three-dimensional structures that contribute to their wide diversity, and also influences
its compactness, flexibility and diverse physical and biochemical properties (Bertozzi and Rabuka
2009; Marino et al. 2010; Marth 1999; Brooks 2009).
The glycans formed possess a reducing end that bears a free anomeric center that may
establish a bond to other structures, such as a polypeptide, by the process of glycosylation
(Bertozzi and Rabuka 2009; Marth 1999). The glycans associated with glycoproteins are typically
composed of up to a dozen monosaccharides, and may be divided into two general types, as
defined by the linkage established with the protein: N-glycans, which attach to the nitrogen atom
of asparagine side chains; and O-glycans, which bind to the oxygen atom of serine or threonine
side chains (Bertozzi and Rabuka 2009; Marino et al. 2010; Wopereis et al. 2006). Of these, N-
CHAPTER 1 │ GENERAL INTRODUCTION
30
glycans are the most prevalent and widely studied, and are the main focus of this chapter (Bañó-
Polo et al. 2011; Lin et al. 2012).
In animals, the glycans attached to proteins mostly contain ten types of monosaccharides,
with seven being more prevalent in humans (Brooks 2009; Bertozzi and Rabuka 2009). These
are represented in Table 1.5 with the abbreviation and symbolic notation adopted in this work.
TABLE 1.5. Monosaccharides commonly present in mammalian glycoproteins, with respective abbreviation and
symbolic notation (Harcum 2006; Merry et al. 2004; Brooks 2009; Bertozzi and Rabuka 2009)
MONOSACCHARIDE ABBREVIATION SYMBOLIC NOTATION
Neutral Glucose Glc
Galactose Gal
Fucose Fuc
Mannose Man
Xylose Xyl
Amino N-acetylglucosamine GlcNAc
N-acetylgalactosamine GalNAc
Acidic N-acetylneuraminic acid NeuNAc
N-glycolylneuraminic acid NeuGc
Glucoronic acid GlcA
1.6.2. BIOSYNTHESIS OF O-GLYCANS IN HUMAN CELLS
O-linked protein glycosylation is much less well understood than N-linked glycosylation due
to the existence of few inhibitors of O-linked glycosylation compared to the range of inhibitors of
specific steps of N-glycosylation that has facilitated its study in detail (Brooks, Dwek, and
Schumacher 2002; Elbein 1987, 1991). Nevertheless, there are seven types of O-linked glycans
found in humans, classified on the basis of the first sugar attached to a serine (Ser) or threonine
(Thr) residue of a protein: O-linked N-acetylgalactosamine (GalNAc) or mucin-type; O-linked
glycosaminoglycan (GAG); O-linked N-acetylglucosamine (GlcNAc); O-linked galactose (Gal); O-
linked mannose (Man); O-linked glucose (Glc); and O-linked fucose (Fuc) (Wopereis et al. 2006;
CHAPTER 1 │ GENERAL INTRODUCTION
31
Haltiwanger 2004). Of these, the mucin-type O-glycan, with GalNAc at the reducing end, is the
most common form found in humans, occurring in over 10 % of human proteins (Roth, Yehezkel,
and Khalaila 2012; Wopereis et al. 2006).
This post-translational modification is normally initiated in the Golgi apparatus by the
transfer of a GalNAc monosaccharide from the nucleotide uridine diphosphate (UDP)-GalNAc into
a Ser or Thr residue of a fully folded and assembled protein, through the action of a N-acetyl
galactosaminyltransferase (GalNAc transferase) (Butler 2004; Van den Steen et al. 1998). No
general consensus sequence has yet been identified for O-glycosylation, but the glycosylated Ser
or Thr residues are often flanked by proline (Pro) (Brooks 2004; Spiro 2002). Subsequently, a
sialic acid residue may be added, terminating the chain, or a stepwise enzymatic elongation by
specific glycosyltransferases can occur yielding different long linear or branching chains that
compose the core structures (Van den Steen et al. 1998; Brooks 2004; Spiro 2002). There are
eight core structures currently identified, as shown in Figure 1.4, which can be distinguished by
the second monosaccharide and respective linkage (Wopereis et al. 2006).
FIGURE 1.4. Representation of the eight known core structures of mucin-type O-glycans. Core 1 to 4 are the most
prevalent; Core 7 has not been observed in humans. Core 1 has a Gal attached in a β1-3 linkage to the core
GalNAc. Core 2 forms by the addition of a GlcNAc β1-6 linked to the GalNAc of Core 1. Core 3 has a GlcNAc
attached in a β1-3 linkage to the core GalNAc. Core 4 forms by the addition of another GlcNAc β1-6 linked to the
GalNAc of Core 3. Core 5 has a GalNAc attached in a α1-3 linkage to the core GalNAc, Core 6 has a GlcNAc in a β1-
6 linkage, Core 7 has a GalNAc in a β1-6 linkage, and Core 8 has a Gal α1-3 linked to the core GalNAc.
CORE 1 CORE 2 CORE 3 CORE 4
CORE 5 CORE 6 CORE 7 CORE 8
CHAPTER 1 │ GENERAL INTRODUCTION
32
The Core 1 structure is formed by the addition of Gal in a β1-3 linkage to GalNAc by the
core 1 β1-3 galactosyltransferase. Core 2 O-glycans are branched Core 1 structures, synthesized
by the addition of a GlcNAc in a β1-6 linkage to the GalNAc of the Core 1 structure through the
action of one of three core 2 β1-6 N-acetylglucosaminyltransferases (C2GnTs) (Brockhausen,
Schachter, and Stanley 2009; Tarp and Clausen 2008).
Alternatively to Core 1 O-glycan formation, Core 3 may be formed through the addition of
GlcNAc in a β1-3 linkage to the GalNAc attached to Ser/Thr by the enzyme Core 3 β1-3 GnT
(C3GnT). The synthesis of Core 3 O-glycans is required for the synthesis of Core 4 by the M-type
β1-6 GnT (C2GnT-2), which adds another GlcNAc in a β1-6 linkage to the GalNAc attached to
Ser/Thr. In addition, Cores 5 to 8 O-glycans exist (Core 7 has not been found in humans) but are
rare and the enzymes responsible for their synthesis remain to be characterized (Brockhausen,
Schachter, and Stanley 2009; Tarp and Clausen 2008).
The core structures may be further elongated or modified by sialylation, fucosylation,
sulfatation, methylation or acetylation, given rise to a multitude of O-glycan structures (Van den
Steen et al. 1998; Butler 2004). The final O-linked glycans are smaller and less complex than
typical N-linked glycans, usually containing 1 to 20 monosaccharide residues (Harcum 2006).
1.6.3. BIOSYNTHESIS OF N-GLYCANS IN HUMAN CELLS
The biosynthesis of glycans occurs in the ER and Golgi apparatus and involves the intricate
and concerted activity of a multitude of specific transmembrane enzymes, namely
glycosyltransferases and glycosidases (van den Eijnden and Joziasse 1993; Sears and Wong
1998; Burda and Aebi 1999).
SYNTHESIS OF THE DOLICHOL GLYCAN PRECURSOR AND TRANSFER TO NASCENT PROTEINS
N-linked glycosylation begins with the synthesis of a dolichol glycan precursor which consists
of the lipid dolichol phosphate (Dol-P) linked to a glycan composed of 14 specific
monosaccharide linkages (Glc3Man9GlcNAc2), a structure that has been conserved among all
eukaryotes (Brooks 2004; Marth 1999; Taylor and Drickamer 2006). The assembly of this
precursor is outlined in Figure 1.5. The process begins on the cytosolic side of the ER
CHAPTER 1 │ GENERAL INTRODUCTION
33
membrane, with the linkage of two core GlcNAc and five Man monosaccharides donated by UDP-
GlcNAc and guanosine diphosphate (GDP)-Man, respectively (Marth 1999; Butler 2004). Then,
by a mechanism not fully understood (Helenius and Aebi 2002), the precursor formed
(Man5GlcNAc2-Dol) flips across the membrane bilayer into the lumen of the ER, where four Man
and three Glc residues are added using the Dol-P-Man and Dol-P-Glc donors, completing the
assembly of the dolichol glycan precursor Glc3Man9GlcNAc2 (Marth 1999; Butler 2004).
The dolichol glycan precursor is transferred to an asparagine (Asn) residue on a nascently
translated protein, through the action of a multi subunit transmembrane protein complex termed
oligosaccharyltransferase (OST), present in the ER membrane, which cleaves the high-energy
GlcNAc-P bond, causing the release of Dol-P-P in the process (Figure 1.5) (Butters 2002;
Dempski Jr and Imperiali 2002; Marth 1999).
FIGURE 1.5. Pathway for the biosynthesis of the dolichol glycan precursor for protein N-glycosylation and transfer of
the precursor to asparagine residues (Asn-X-Thr/Ser) on nascently translated proteins by the
oligosaccharyltransferase (OST) complex. Dol-P: dolichol phosphate; GDP: guanosine diphosphate; UDP: uridine
diphosphate; Man:mannose; Glc: glucose; ER: endoplasmic reticulum.
Dol-PUDP-
GlcNAcGDP-Man
Dol-P-Man
Dol-P-Glc
Dol-P
GDP-Man
Dol-P-Man
Dol-P-Glc
OST OST OST
Ribosome RibosomeRibosome
ER LUMEN
CYTOSOL
CYTOSOL
UDP-Glc
Asn-X-Thr/Ser
CHAPTER 1 │ GENERAL INTRODUCTION
34
A consensus sequence is required for the attachment of the glycan to the acceptor Asn. This
Asn must have a minimal surrounding sequence of Asn-X-Thr/Ser, where X can be any amino
acid except Pro (Brooks 2004). However, among the polypeptides bearing this consensus
sequence (potential N-glycosylation sites) only about 30 % appear to be used (Marth 1999).
EARLY PROCESSING STEPS IN THE ENDOPLASMIC RETICULUM
Following the attachment of the precursor to the Asn residues, a series of processing
reactions occurs (Figure 1.6).
FIGURE 1.6. Processing of the initial high mannose N-glycan in the endoplasmic reticulum and cis-Golgi to generate
the core N-glycan substrate used for further diversification in the Golgi.
The first several steps occur in the lumen of the ER and appear to be conserved among all
eukaryotic cells. These steps are associated with quality control of correct protein folding and are
essential for subsequent transport of the newly synthesized glycoprotein to the Golgi apparatus
(Parodi 2000; Ellgaard and Helenius 2001; Marth 1999). The initial steps of trimming consist of
the sequential removal of the three Glc residues by the action of glucosidases I and II, to yield
Dol-P
Glucosidase I
Glucosidase II
Endo-mannosidase
Mannosidase IA
Mannosidase IB
Oligosaccharyl-
transferase
ENDOPLASMIC RETICULUM
CIS-GOLGI
CHAPTER 1 │ GENERAL INTRODUCTION
35
Man9GlcNAc2. This process of Glc removal is associated with protein folding mechanisms and
contributes to the ER retention time of the glycoprotein. Proteins that become improperly folded
are re-glucosylated by an α-glucosyltransferase and retained in the ER, where they are either
refolded into a proper conformation or deglucosylated and degraded (Marth 1999).
The correctly folded precursors are then acted on by an endo-mannosidase that generates a
Man8GlcNAc2 glycan structure than can proceed in the N-glycan processing and secretory
pathways (Marth 1999).
LATE PROCESSING STEPS IN THE GOLGI APPARATUS
The Man8GlcNAc2 structure produced in the ER is released to the cis-Golgi where it is
sequentially processed by distinct class I α-mannosidases (1A and 1B) that act specifically on
α1-2-linked Man residues (Figure 1.6). This processing most often results in a Man5GlcNAc2
glycan that becomes the core N-glycan substrate for diversification in the Golgi (Marth 1999;
Brooks 2004).
DIVERSIFICATION/MATURATION OF N-GLYCANS
The Man5GlcNAc2 structure can be trimmed and extended by the addition of other
monosaccharides or extended without further trimming, given rise to a diversification of N-glycans
in the Golgi (Brooks 2004). The structures of N-glycans created fall into three main categories:
high-mannose, hybrid, and complex types, which share a common trimannosyl core
(Man3GlcNAc2) but differ in their outer branches (Figure 1.7) (Marth 1999; Brooks 2004; Butler
2004).
The high-mannose type N-glycans may have between two and six additional Man residues
linked to the core; the complex type has no further Man residues and has two or more outer
branches containing GlcNAc (attached to the core), Gal and/or sialic acids; the hybrid type has
one outer branch of the high-mannose type and the other of the complex type (Marth 1999;
Brooks 2004; Butler 2004).
The enzyme GnT-I is the first involved in N-glycan diversification, adding a GlcNAc in β1-2
linkage to produce the hybrid N-glycan structure GlcNAc1Man5GlcNAc2. In the medial Golgi, α-
mannosidase II acts to remove the α1-3- and α1-6-linked Man residues as shown in Figure 1.7.
CHAPTER 1 │ GENERAL INTRODUCTION
36
The resulting GlcNAc1Man3GlcNAc2 hybrid N-glycan is the specific substrate for the enzyme GnT-II
that catalyzes the conversion from hybrid to complex N-glycans (Marth 1999).
FIGURE 1.7. Representation of the N-glycan diversification in the Golgi, which generates three subtypes: high-
mannose, hybrid, and complex glycans.
The hybrid and complex N-glycans may have two or more GlcNAc-bearing branches which
are termed antennae. Branching reactions are very complex and may result in biantennary,
triantennary, and tetra-antennary glycans, as shown in Figure 1.8 (Harcum 2006).
FIGURE 1.8. Structures exemplifying complex N-glycans with varying number of antennae: biantennary, triantennary,
and tetra-antennary.
GlcNAc
transferase I
Mannosidase II GlcNAc
transferase II
Glactosyl-
transferase
Sialyl-
transferases
MEDIAL GOLGI
TRANS GOLGI
HYBRIDHIGH MANNOSE COMPLEX
BIANTENNARY TRIANTENNARY TETRA-ANTENNARY
CHAPTER 1 │ GENERAL INTRODUCTION
37
The development of multi-antennary N-glycan structures requires the action, sometimes
competing, of four additional GnTs (GnT III to VI) to the already mentioned GnT-I and GnT-II
(Marth 1999). All GlcNAc residues except that added by GnT-III to the Man linked to the core
GlcNAc (termed bisecting GlcNAc) can be extended with additional monosaccharide linkages,
including Gal, sialic acid, and Fuc (Marth 1999). Galactosylation (the addition of Gal) is catalyzed
by a number of enzymes such as the β1-4 and β1-3 galactosyltransferases (GalTs). Sialylation
(the addition of sialic acids) may be catalyzed by different sialyltransferases specific for different
sialic acids and linkages, with the most common in humans being the linkage of N-
acetylneuraminic acid (NeuNAc) to the terminal Gal by either α2,3 sialyltransferase or α-2,6
sialyltransferase. Fuc is added by a fucosyltransferase in a α1-6 linkage to the GlcNAc residue
attached to Asn (core fucosylation). Fuc can be added at any time after the formation of the
Man5GlcNAc2 structure, but not after the action of GnT-III (bisecting GlcNAc) (Butler 2004; Marth
1999; Harcum 2006).
MACROHETEROGENEITY AND MICROHETEROGENEITY
Unlike the biosynthesis of a protein from mRNA, where the nucleic acid codes for only one
sequence, the attachment of a glycan to a protein is not template driven, and the presence of the
consensus sequence Asn-X-Ser/Thr does not guarantee glycosylation (Harcum 2006; Butler
2004). Additionally, a protein contains several potential glycosylation sites at different positions
that may remain unoccupied, adding variability and complexity to the process. This glycosylation
or non-glycosylation variability at a specific site in a protein is termed macroheterogeneity
(Harcum 2006). Influencing this macroheterogeneity may be factors such as the spatial
arrangement of the peptide during translation, which can expose or hide the consensus
sequence; the amino acids (X) surrounding the consensus sequence Asn-X-Ser/Thr, with high
occupancy level for Ser and Phenylalanine (Phe), intermediate for Leucine (Leu) and Glutamate
(Glu), and very low for Aspartate (Asp) and Tryptophan (Trp); and the availability of UDP and GDP
monosaccharide precursors (Butler 2004).
The generation of different N-glycan structures and their variable addition to the glycosylation
sites on a protein results in considerable glycosylation diversity, and is known has
microheterogeneity (Bill, Revers, and Wilson 1998; Royle et al. 2007; Harcum 2006).
Microheterogeneity is influenced by factors that include nucleotide metabolism, transport rates in
CHAPTER 1 │ GENERAL INTRODUCTION
38
the ER and Golgi, and the localization and level of expression of the glycosyltransferases in the
Golgi apparatus (Walsh and Jefferis 2006).
Both macro- and microheterogeneity affect the biological activity of the glycoproteins
produced, which makes the prediction and/or control of their impact a concern for the
biopharmaceutical industry, for safety and regulatory reasons (Hossler, Khattak, and Li 2009).
1.6.4. GLYCOSYLATION AND THERAPEUTIC PROTEIN EFFICACY
Glycosylation often plays a critical role in establishing or maintaining the integrity of
glycoproteins. Indeed, the addition of glycans to a protein can result in a diverse set of changes
in the physicochemical and biological properties, which include stability, circulatory half-life,
efficacy, solubility and immunogenicity (Harcum 2006; Lowe and Marth 2003; Li and d’Anjou
2009; Van den Steen et al. 1998; Baker, Flatman, and Birch 2007).
The maintenance and stabilization of the physical properties of therapeutic proteins are
central for the storage and in vivo efficacy of the product, but may be hindered by many
physicochemical instabilities caused by inappropriate glycosylation (Yamane-Ohnuki and Satoh
2009). For example, the size and mass of the protein are affected by the number and type of
glycans attached, and the charge and solubility properties are influenced by the presence of
charged monosaccharides such as sialic acid residues (Lis and Sharon 1993; Narhi et al. 1991;
Reuter and Gabius 1999). Furthermore, the number, length, branching and charge of the glycans
have also been related to proteolytic stabilization, with the negative charge of sialic acids
improving the resistance to proteolysis and, consequently, enhancing the in vivo stability of the
protein (Solá and Griebenow 2009; Sareneva et al. 1993; Raju and Scallon 2007; Runkel et al.
1998). The attachment of glycans to some proteins also aids in folding (e.g. erythropoietin (EPO))
(Helenius and Aebi 2001; Narhi et al. 1991).
In addition to the physicochemical effects, glycosylation can also affect the efficacy of
therapeutic proteins by influencing their biological activity and clearance rate, especially through
the modulation of the pharmacokinetic properties. The pharmacokinetic profile of the protein
informs about the dosing size and frequency, which are key attributes for patient compliance and
acceptance of a drug (Li and d’Anjou 2009). Of the pharmacokinetic properties, the protein half-
life in circulation is one of the most important, and it has been shown to be improved by
CHAPTER 1 │ GENERAL INTRODUCTION
39
glycosylation in different therapeutics (e.g. interferon (IFN), EPO) (Erbayraktar et al. 2003; Runkel
et al. 1998; Walsh and Jefferis 2006; Sareneva et al. 1996). In particular, the presence of sialic
acid residues can have a major influence in this property (Baker, Flatman, and Birch 2007; Zhu
2011; Egrie and Browne 2001), with increased levels of terminal sialylation improving protein
half-life apparently by ‘hiding’ the Gal residues that when exposed prompt a fast removal of the
protein from the circulation due to endocytosis-mediated uptake by Gal-specific receptors in the
hepatocytes (Kompella and Lee 1991; Baker, Flatman, and Birch 2007; Morell et al. 1971;
Wileman, Harding, and Stahl 1985; Raju 2003). Similarly, glycoproteins exposing glycans that
terminate in Man, GlcNAc or Fuc residues may also be more rapidly removed from the circulation
due to specific interactions with other lectin-like receptors expressed at different cell types
(Townsend and Stahl 1981; Weigel and Yik 2002; Raju 2003; Jones et al. 2007). This type of
clearance does not apply to all glycosylated therapeutics, as is the case of mAbs whose
clearance is mediated by other type of receptors (FcRn) that are not influenced by glycosylation
(Jefferis 2009). In fact, in the specific case of mAb-based therapeutics, glycosylation of the Fc
portion exerts a profound influence on the effector functions, and therefore on in vivo efficacy,
through the modulation of the binding affinities for other type of receptors, specifically the FcγR
receptors (Li and d’Anjou 2009; Jefferis 2009; Raju 2008; Crispin et al. 2009; Mimura et al.
2009). Of the glycan structures, Fuc residues are currently considered as the major influents on
mAb effector functions. Typically, the glycans at the Fc portion of mAbs contain a core Fuc
residue (Mizuochi et al. 1982); however, studies have shown that non-fucosylated variants exhibit
improved binding to FcγRIII receptors of up to 50-fold (Shields et al. 2002; Iida et al. 2006),
which results in dramatically enhanced ADCC (up to 100-fold) (Iida et al. 2006; Shields et al.
2002; Yamane-Ohnuki and Satoh 2009; Kanda et al. 2007). Furthermore, this improved affinity
for FcγRIII provides an advantage to the non-fucosylated therapeutic mAbs in the competition
with the human serum IgGs for binding to these receptors on NK cells (Vugmeyster and Howell
2004; Jefferis 2009; Preithner et al. 2006; Shinkawa et al. 2003).
The same enhanced ADCC can be accomplished by the attachment of bisecting GlcNAc, an
effect that has been attributed to the low Fuc content that is always associated with the presence
of this residue (since the bisecting GlcNAc inhibits further addition of Fuc during the N-glycan
biosynthesis) (Umana et al. 1999; Ferrara, Stuart, et al. 2006; Abès and Teillaud 2010).
Other variations of the Fc glycan structure have also been proven to alter the functional
effects of therapeutic mAbs, such as the levels of sialic acid, Gal and Man residues. In contrast to
CHAPTER 1 │ GENERAL INTRODUCTION
40
other glycoproteins, where higher contents of sialic acid result in extended circulatory half-life and
improved efficacy, increased levels of sialylation have an adverse effect on mAb efficacy by
reducing ADCC activity (Scallon et al. 2007). It was proposed that these effects could be related
to a reduction of the flexibility of the mAb at the hinge region, which could have the following
effects: reduced binding to FcγRIIIa due to a greater difficulty in assuming the required sharp 90º
bend of the hinge region; or reduced bivalent (and increased monovalent) binding to the antigen
as a result of the mAb molecules not being able to orient themselves to enable both Fab arms to
simultaneously bind the antigen (Sondermann, Kaiser, and Jacob 2001; Scallon et al. 2007;
Kaneko, Nimmerjahn, and Ravetch 2006).
Contrarily to Fuc and sialic acid residues, the terminal content of Gal has no effects on
ADCC, but has shown to improve CDC as a result of increased antibody binding to C1q in
hypergalactosylated variants of the IgG (Hodoniczky, Zheng, and James 2005; Boyd, Lines, and
Patel 1995).
Additionally, the presence of high-mannose structures in mAbs, similarly to glycoproteins,
has been related to a rapid clearance from serum due to the binding of the exposed Man
residues to Man receptors expressed in phagocytic cells (Abès and Teillaud 2010; Wright et al.
2000).
1.6.5. EXTERNAL FACTORS INFLUENCING GLYCOSYLATION
The control and maintenance of a consistent glycosylation/glycoform profile during
glycoprotein manufacturing is a major concern and currently still a considerable challenge to the
biopharmaceutical industry (Walsh and Jefferis 2006). This is a consequence of the combination
of several factors. First, the high variability already inherent to the process of glycosylation
(macro- and microheterogeneity); second, the impact of glycosylation on protein functionality; and
third, the variability on the glycan profile introduced by several culture and process parameters,
whose mechanisms are still under investigation and therefore are hard to control. These
parameters include cell type- and species-specific factors (e.g. expression system) and
environmental factors and culture conditions (e.g. culture media, mode of culture) (Wong et al.
2005; Kunkel et al. 2000; Crowell et al. 2007; Gawlitzek et al. 1995; Hossler, Khattak, and Li
2009; Serrato et al. 2004; Trummer et al. 2006).
CHAPTER 1 │ GENERAL INTRODUCTION
41
Therefore, to maintain product consistency and avoid unexpected changes during the
process of production of therapeutic glycoproteins it is crucial to understand how and at what
extent cell culture parameters affect glycosylation. As a more far-reaching objective, it may be
reasonable to control culture conditions in favor of reducing heterogeneity or even producing a
specific and more favorable glycoform (Butler 2004).
CELL TYPE- AND SPECIES-SPECIFIC FACTORS
Bacteria, yeast, insect, plant, and mammalian cells have evolved as the major recombinant
protein expression hosts. However, these expression systems vary widely in their ability to
perform human-like post-translational modifications such as glycosylation (Butler 2004;
Sethuraman and Stadheim 2006), so the choice of the most adequate host will depend on the
product and of the intended application. Some therapeutic proteins, such as insulin or human
growth hormone, do not need to be glycosylated for efficiency, so the ability to perform
glycosylation is not a critical parameter to be considered in host selection. However, most of the
therapeutics currently approved or in development are glycoproteins and, therefore, require
proper glycosylation for biological activity (e.g. tissue plasminogen activator (tPA), EPO, mAbs). In
this case, the choice of the expression system becomes crucial, since non-human glycoforms can
adversely impact the pharmacokinetic properties of the protein and raise immunogenicity and
safety concerns (James and Baker 2002; Sasaki et al. 1987; Beck et al. 2008; Jefferis 2005).
Indeed, the potential for significant changes in the biological activity of therapeutic proteins
depending on the expression system is a real concern from a pharmacological point-of-view,
particularly for mAbs because of their obvious complexity and their intended interaction with the
immune system of the patient (Beck et al. 2008; Sheeley, Merrill, and Taylor 1997).
The early events in the N-glycan biosynthesis pathway are largely conserved among
organisms. However, the latter steps of glycan diversification in the Golgi apparatus seem to have
been evolutionarily diversified (James and Baker 2002; Brooks 2004; Goochee et al. 1991).
These divergences can be related to differences found among species in the relative
expression/activity of several glycosyltransferases, which are a key factor in the synthesis of N-
glycans (Butler 2004; Butler 2005). In addition to the enzyme repertoire, other factors
contributing to the cell- and species-specific variability of the glycan profile are the competition
between different enzymes for one substrate, the transit time of the glycoproteins in the ER and
CHAPTER 1 │ GENERAL INTRODUCTION
42
Golgi apparatus, the levels of sugar and nucleotide donors, and the competition between
glycosylation sites on the protein for the same pool of enzymes (Butler 2004).
An example of the N-glycan structures commonly obtained in humans and the different
expression systems available for therapeutic glycoprotein production can be seen in Figure 1.9.
FIGURE 1.9. Schematic representation of N-glycan structures found in human cells and in the different expression
systems available for recombinant protein production.
A more detailed list of the divergences found between glycan structures of different species
compared to human cells, and their respective effects on protein activity, is shown in Table 1.6.
TABLE 1.6. Divergences found on protein glycosylation occurring in different expression systems in comparison to the
glycosylation obtained in human cells, and respective effects on protein activity
EXPRESSION SYSTEM DIFFERENCES TO HUMAN EFECT
Bacteria No glycosylation Reduced or absent biological activity
Yeast High-mannose glycans Fast clearance, immunogenic
Insect High-mannose glycans
Paucimannose glycans
α1,3-fucose
Absence of sialylation
Fast clearance, immunogenic
Fast clearance, immunogenic
Immunogenic
Poor half-life
Plant α1,3-fucose
β1,2-xylose
Absence of sialylation
Absence of terminal Gal
Immunogenic
Immunogenic
Poor half-life
Mammalian Typically human-like
YEAST PLANT INSECT MAMMALIAN HUMAN
CHAPTER 1 │ GENERAL INTRODUCTION
43
BACTERIA
Bacteria are generally regarded as unable to glycosylate proteins due to the absence of the
N-linked glycosylation machinery (Sethuraman and Stadheim 2006; Harcum 2006; Dingermann
2008). However, Eubacteria and Archaebacteria have shown ability to glycosylate surface
proteins (of the bacteria cell wall), with the biosynthetic pathways for this glycosylation still not
well characterized (Upreti, Kumar, and Shankar 2003; Schäffer, Graninger, and Messner 2001;
Benz and Schmidt 2002). Since the prokaryotic bacterial cells lack internal membrane-bound
organelles (including the ER and Golgi apparatus), glycan processing takes place on the outside
of the cell membrane and the glycans synthesized are mostly chemically very different from those
found on human cells (e.g. rhamnose, galactofuranose, N-acetylmannosamine). Nevertheless,
although possessing some glycosylation mechanisms, glycoproteins appear to be uncommonly
synthesized by bacteria, and the recombinant proteins currently produced in these organisms are
not glycosylated (e.g. insulin and human growth hormone produced in Escherichia coli) (Harcum
2006; Butler 2004; Brooks 2004).
YEAST
Yeast-based expression systems have been used for the production of some approved
therapeutic proteins (e.g. insulin, human growth hormone, hirudin, and albumin) (Sethuraman
and Stadheim 2006). However, the presence of yeast-specific glycans of the high-mannose type,
with up to 15 Man residues (hiper-mannosylation, Figure 1.9) (Marth 1999), in the proteins
produced is a concern since these groups are not common in humans and can be immunogenic
(Lam, Huang, and Levitz 2007; Dasgupta et al. 2007; Luong et al. 2007).
INSECT CELLS
Insect cells infected by baculovirus have been reported as efficient expression hosts for the
production of many glycoproteins, including mAbs (Altmann et al. 1999; Kost, Condreay, and
Jarvis 2005; Sethuraman and Stadheim 2006). They are capable of performing N-glycosylation
with similar core structures to other eukaryotic organisms, including humans (Harcum 2006;
Liang et al. 1997; Li et al. 2006). However, proteins expressed in insect cells also contain
glycans that are not of the complex type, such as hybrid, high-mannose and paucimannose
glycans (Figure 1.9) (Kim et al. 2005; Durocher and Butler 2009). Furthermore, in some insect
cell lines, non-human α1,3-Fuc may be added to the glycans, which raises immunogenicity and
CHAPTER 1 │ GENERAL INTRODUCTION
44
safety concerns (Harcum 2006; Garcia-Casado et al. 1996; Altmann et al. 1999), and the
absence of sialic acid residues has also been detected (Altmann et al. 1999; Marchal et al.
2001). As a consequence of these modifications, which could compromise in vivo bioactivity and
potentially induce allergenic reactions, no approved therapeutic proteins are currently produced
in this system (Durocher and Butler 2009).
PLANT
Plant-based expression systems produce non-human glycan structures where Gal and sialic
acid residues are absent (Figure 1.9). Also, the presence of the potentially immunogenic α1,3-
Fuc and β1,2-xylose (β1,2-Xyl) residues are major limitations to the use of these systems for the
expression of therapeutic glycoproteins (Jin et al. 2008; Gomord and Faye 2004; Bardor et al.
2003).
MAMMALIAN CELLS
The N-glycosylation machinery is highly conserved across different mammalian species,
constituting the primary factor for the current preference for mammalian cells as the expression
host for the production of human-like therapeutic glycoproteins. Glycans produced are majorly of
the complex type, but some marginal differences between human and non-human mammalian
glycosylation exist, varying with the cell type, as summarized in Table 1.7 (Chung et al. 2008;
Dingermann 2008; Butler 2004).
TABLE 1.7. Structural differences in the N-glycans produced by the main mammalian cells used as hosts for
glycoprotein production, concerning human glycosylation
CELL LINE DIFFERENCE TO HUMAN EFFECT
Chinese hamster ovary (CHO) Absence of α2,6-linked sialic acids Undersialylation, reduced serum half-life
Absence of bisecting GlcNAc Reduced biological activity of mAbs
NeuGc produced at minor fractions Not immunogenic at the levels produced
Baby hamster kidney (BHK) Absence of α2,6-linked sialic acids Undersialylation, reduced serum half-life
NeuGc produced at minor fractions Not immunogenic at the levels produced
Murine myeloma (NS0, Sp2/0) Presence of α1,3-Gal Immunogenic
Predominance of NeuGc sialic acids Immunogenic
CHAPTER 1 │ GENERAL INTRODUCTION
45
Among mammalian cell lines, CHO are the most widely used for the production of
therapeutics. These cells have not been implicated in any obvious adverse effects, but some
differences have been found in their potential for glycosylation compared to human cells
(Durocher and Butler 2009; Sethuraman and Stadheim 2006). One of the differences is on the
type of linkage established between sialic acid and Gal residues in the glycans. In humans, the
sialic acids are attached to Gal in a mixture of α2,6- and α2,3-linkages, with preference to the
former (Tarelli 2007). However, CHO cells lack the enzyme α2,6-sialyltransferase and thus can
only produce α2,3-linked terminal sialic acid residues, which can result in undersialylation and
consequently affect circulatory lifetime and other protein properties (Butler 2004; Tarelli 2007).
CHO cells also lack a functional GnT-III enzyme present in human cells, which prevents the
addition of bisecting GlcNAc residues and may impact the activity of certain glycoproteins, such
as mAbs (Jefferis 2005; Butler 2004; Jenkins and Curling 1994; Umana et al. 1999).
BHK cells are other common expression system in recombinant protein production, and like
CHO cells they only produce α2,3-linked terminal sialic acids due to the absence of a functional
α2,6-sialyltransferase (Butler 2004).
The differences found in the glycosylation potential of CHO and BHK cells, compared to
human cells, do not appear to result in glycoproteins that are immunogenic (Butler 2005).
However, immunogenic concerns appear for murine myeloma cells (e.g. NS0, SP2/0), another
expression system that is considered for glycoprotein production. These cells express the enzyme
α1,3-galactosyltransferase, which generates α1,3-Gal residues that are not present in humans
and are found to be highly immunogenic (Butler 2004; Harcum 2006; Jenkins, Parekh, and
James 1996). Indeed, about 1-2 % of circulating antibodies in humans are directed against these
α1,3-Gal residues (also known as the Galili antigen) (Galili et al. 1984), and therefore may
recognize therapeutic glycoproteins produced in these non-human expression systems (Durocher
and Butler 2009). Indeed, some reports about hypersensitivity reactions in patients receiving
treatment with a mAb produced in these cells have been reported due to the presence of the
α1,3-Gal epitope, which only highlight the concerns, especially if the therapeutic is to be
administered chronically in large doses, where severe immune responses may arise (Chung et al.
2008; Harcum 2006).
Murine myeloma cells also express glycoforms with terminal sialic acid that differ from those
present in humans. NeuNAc is the sialic acid produced by human cells, and although murine
cells also produce NeuNAc, the N-glycolylneuramic acid (NeuGc) is the sialic acid predominantly
CHAPTER 1 │ GENERAL INTRODUCTION
46
present in their glycoproteins (Beck et al. 2008; Jenkins, Parekh, and James 1996; Tarelli 2007).
These NeuGc residues are potentially immunogenic in humans and can reduce the efficacy of the
therapeutic glycoprotein due to a rapid clearance by the immune system (Padler-Karavani et al.
2008; Jenkins, Parekh, and James 1996; Durocher and Butler 2009; Sheeley, Merrill, and Taylor
1997). CHO and BHK cells also produce these NeuGc residues but only as a minor fraction,
which does not seem to elicit any anti-NeuGc response (Dingermann 2008; Padler-Karavani et al.
2008; Beck et al. 2008).
Human cell-based expression systems, such as HEK and PER.C6 cells, are expected to
produce recombinant proteins with post-translational modifications more similar to their natural
counterpart. Therefore, the expression of therapeutic proteins in human cells could reduce
potential immunogenic reactions against the non-human epitopes found in other mammalian cell
lines as described above (Durocher and Butler 2009).
ENVIRONMENTAL FACTORS AND CULTURE CONDITIONS
Usually, several parameters of the cell culture environment are optimized during therapeutic
production with the intent to optimize cell growth and product yield. These parameters can also
change the protein glycosylation and consequently affect the biological activity of the product
(Gawlitzek et al. 1995; Hossler, Khattak, and Li 2009; Butler 2004; Yuen et al. 2003). The
parameters may be divided into the following categories: medium and nutrients, culture
conditions, technology platform, and cell-related factors. It is essential to acquire a better
understanding of the impact of these cell culture parameters on the resulting glycosylation to
improve the control of protein quality and maintain a consistent glycoform profile within the strict
limits required by the regulatory authorities (Walsh and Jefferis 2006). An extensive list of studies
on the effects of different culture conditions on glycosylation is provided in Table 1.8.
CHAPTER 1 │ GENERAL INTRODUCTION
47
TA
BLE
1.8
. List of the main results reported on the effects of different variables of cell culture processes on product glycosylation
FACTORS
EFFECT
REFERENCE
MEDIUM AND NUTRIENTS
GLUCOSE
Glucose limitation reduced site occupancy of an IgG produced in mouse myeloma cells
(Stark and Heath, 1979)
Glucose limitation produced less glycosylated IFN-γ in CHO cells
(Hayter et al., 1992)
Glucose addition to the culture medium slightly improved galactosylation of an anti-Rhesus D antibody
(Nahrgang et al., 1999)
Glucose limitation led to decreased sialylation and increased hybrid and high-mannose type glycans of IFN-γ
produced in fed-batch cultures of CHO cells
(Wong et al., 2005)
GALACTOSE
Galactose feeding facilitated a more fully galactosylated N-glycan profile
(Andersen, 2004)
GLUTAMINE/AMMONIA
Increased ammonia led to a decrease in terminal galactosylation and sialylation of a recombinant tumor
necrosis factor receptor-IgG in CHO cells
(Gawlitzek et al., 2000)
Ammonia decreased sialylation of O-glycans even at low levels
(Andersen and Goochee, 1994)
High ammonia concentrations increased heterogeneity, decreased the terminal sialylation of O- and N- glycans
and decreased the content of O-glycans of EPO
(Yang and Butler, 2000a, b, 2002)
SERUM
Serum-free improved N- and O-glycosylation of IL-2, with enhanced terminal sialylation and proximal
fucosylation, in suspension and microcarrier cultures of BHK-12 cells
(Gawlitzek et al., 1995)
Serum-free culture increased terminal sialylation and galactosylation in a IgG1 monoclonal antibody produced
by murine hybridoma
(Patel et al., 1992)
Serum provided slightly higher terminal galactosylation of a mAb produced by CHO cells
(Lifely et al., 1995)
Serum caused proteolysis of IFN-γ produced by CHO cells
(Castro et al., 1995)
AMINO ACIDS
Supplementation with amino acids that have been depleted from the culture (cysteine, isoleucine, tryptophan,
valine, asparagine, aspartic acid, and glutamate) increased sialylation of EPO in CHO cell cultures
(Crowell et al., 2007)
MANGANESE
Manganese added to the culture increased galactosylation which in turn facilitated O- and N-glycosylation of
EPO in CHO cell cultures
(Crowell et al., 2007)
SODIUM-BUTYRATE
Sodium-butyrate added to a culture of CHO cells increased the sialylation of IFN-γ
(Lamotte et al., 1999)
Sodium-butyrate added to a culture of CHO cells increased the microheterogeneity and decrease the sialylation
and in vivo biological activity of human thrombopoietin
(Sung et al., 2004)
CHAPTER 1 │ GENERAL INTRODUCTION
48
FACTORS
EFFECT
REFERENCE
GLYCEROL
Glycerol stabilized and enhanced sialylation of IFN-β in CHO cell cultures
(Rodriguez et al., 2005)
DIMETHYLSULFOXIDE
Dimethylsulfoxide (DMSO) decreased sialylation of IFN-β in CHO cell cultures
(Rodriguez et al., 2005)
LIPIDS
Lipids improved the N-glycan site occupancy of IFN- γ produced by CHO cells
(Castro et al., 1995)
Lipoprotein supplementation increased the amount of fully glycosylated IFN-γ produced by CHO cells
(Jenkins et al., 1994)
NUCLEOTIDE PRECURSORS
Cystidine and uridine increased the availability of nucleotide precursors and modified protein glycosylation
(Kornfeld and Kornfeld, 1985)
N-acetyl mannosamine (ManNAc), a direct precursor of CMP-NeuAc, added to CHO cell cultures increased
significantly the sialylation of IFN-γ
(Gu and Wang, 1998)
ManNAc added to NS0 cultures improved the NeuAc to NeuGc ratio of tissue inhibitor of metalloproteinase 1
(TIMP-1) to more favorable (human) levels
(Baker et al., 2001)
Glucosamine/uridine supplementation increased the antennarity of N-glycans of tissue inhibitor of
metalloproteinase-1 in CHO cells, but not in NS0 cells, and caused a decrease in sialylation in both CHO and
NS0 cultures
(Baker et al., 2001)
Glucosamine decreased sialylation and the proportion of tetraantennary glycans of EPO in CHO-K1 cells
(Yang and Butler, 2002)
CULTURE CONDITIONS
DISSOLVED OXYGEN
A decrease of the dissolved oxygen (DO) level led to a gradual decrease in the galactosylation (mainly digalacto
glycans) of an IgG in murine myeloma cell cultures
(Kunkel et al., 1998)
High levels of DO enhanced sialylation of a recombinant follicle-stimulating hormone in CHO cell cultures
(Chotigeat et al., 1994)
DO concentrations affected the final glycosylation state of a alkaline phosphatase protein in insect cell culture,
with optimal glycosylation occurring at intermediate DO levels
(Zhang et al., 2002)
pH
Culture pH shifted the glycosylation pattern of a mouse placental lactogen expressed in CHO cells
(Borys et al., 1993, 1994)
Culture pH affected the galactosylation and sialylation levels of a mAb produced by hybridoma cells
(Müthing et al., 2003)
Decreases in culture pH caused an increase in the proportion of acidic (sialylated) isoforms of EPO produced
by CHO cells, with an optimal range of pH 6.8-7.2 favoring sialylation
(Yoon et al., 2005)
TA
BLE
1.8
. List of the main results reported on the effects of different variables of cell culture processes on product glycosylation (continuation)
CHAPTER 1 │ GENERAL INTRODUCTION
49
FACTORS
EFFECT
REFERENCE
CARBON DIOXIDE
Elevated carbon dioxide (CO
2) slightly decreased tPA sialylation in CHO cultures in serum-free media
(Kimura and Miller, 1997)
Increases in CO
2 decreased polysialylation in CHO cell cultures
(Zanghi et al., 1999)
TEMPERATURE
Lowering temperature from 37 ºC to 33 ºC and 30 ºC caused a decrease of the sialic acid ratio in a EPO-Fc
protein expressed in CHO cells
(Trummer et al., 2006a)
TECHNOLOGY PLATFORM
MODE OF CULTURE
Perfusion cultures increased overall sialylation compared to fed-batch cultures
(Lipscomb et al., 2005)
Perfusion culture of CHO cells immobilized in macroporous microcarriers, in a fluidized bed bioreactor, showed
an increasing level of N-glycan sialylation of IFN-γ during the culture
(Goldman et al., 1998)
The glycosylation pattern of transferrin varies during standard batch culture of HepG2
(Hahn and Goochee, 1992)
BIOREACTOR
Culture of CHO cells in a stirred tank bioreactor showed a decline of the N-glycan sialylation of IFN-γ late in
culture, coincident with the onset of cell death and lysis
(Goldman et al., 1998)
A stirred tank bioreactor provided higher levels of galactosylation of an IgG produced in SP2/0 cells than a
hollow fiber bioreactor
(Nahrgang et al., 1999)
MODE OF GROWTH
Microcarrier culture of CHO cells resulted in a recombinant human tissue kallikrein protein with lower
sialylation than suspension cultures
(Watson et al., 1994)
Stationary culture resulted in hypergalactosylation of an IgG
(Lund et al., 1993)
CELL RELATED FACTORS
CELL GROWTH
Slower growing cells facilitated a more glycosylated protein secreted by CHO cells
(Lipscomb et al., 2005)
CHO cells in the death phase produced less galactosylated antibodies
(Kaneko et al., 2010)
CELL DENSITY
Low density cultures gave rise to hypergalactosylation of a human IgG monoclonal antibody produced by
lymphoblastoid cells
(Kumpel et al., 1994)
Confluent HepG2 cells produced more active (biantennary) transferrin that subconfluent cultures
(Hahn and Goochee, 1992)
SPECIFIC PRODUCTIVITY
An increased specific productivity correlated to decreased levels of sialylation
(Trummer et al., 2006b)
EXPRESSION RATE
A lower rate of protein expression in MDCK cells increased the number of polylactosamine residues
(Nabi and Dennis, 1998)
A lower protein synthesis rate improved the glycosylation site occupancy of recombinant human prolactin
produced by C127 murine cells
(Shelikoff et al., 1994)
TA
BLE
1.8
. List of the main results reported on the effects of different variables of cell culture processes on product glycosylation (continuation)
CHAPTER 1 │ GENERAL INTRODUCTION
50
MEDIUM AND NUTRIENTS
The cell culture medium determines the cell growth environment and physical conditions,
with a crucial influence on the course of the culture and on product quality (Zhu 2011; Walsh and
Jefferis 2006). The mammalian cell culture media is typically a mixture of 50-100 different
chemically-defined and sometimes undefined (e.g. peptones, yeast extracts, plant hydrolysates,
and serum) components (Hossler, Khattak, and Li 2009). The effects of some of these
components on protein glycosylation have been evaluated.
Glucose is the major energy source in mammalian cell culture (Burgener and Butler 2006;
Zhao and Keating 2007), and cell growth under glucose limitation seems to produce
abnormalities in the glycoprotein synthesis, such as the attachment of aberrant precursors to the
protein, reduced site occupancy, or the absence of glycosylation (Hayter et al. 1992; Hayter et al.
1993; Nyberg et al. 1999). These effects have been attributed to a shortage of glucose-derived
glycan precursors and/or to an intracellular-energy-depleted state (Kornfeld and Kornfeld 1985;
Rearick, Chapman, and Kornfeld 1981), but seem to be variable with the type of cell and product
(Hayter et al. 1993; Nahrgang et al. 1999; Wong et al. 2005; Cruz et al. 2000). The use of
galactose feeding as an alternative source of energy may facilitate a more fully galactosylated N-
glycan profile (Hossler, Khattak, and Li 2009; Andersen and Reilly 2004).
Glutamine is normally added to the culture medium to provide an energy source for cells
and is also an essential precursor for nucleotide synthesis. However, glutamine is also a major
source of ammonia accumulation in the medium, which inhibits cell growth and affects protein
glycosylation (Yang and Butler 2000; Andersen and Goochee 1994; Valley et al. 1999), with its
major effect being a decrease in terminal sialylation (Andersen and Goochee 1994; Gawlitzek et
al. 2000; Yang and Butler 2002). This effect on glycosylation could be explained by an increase
in the pH of the Golgi caused by ammonia, which could decrease the activity of some
glycosyltransferases (Gawlitzek et al. 2000; Butler 2004).
Serum is commonly used in cell culture to promote cell growth and improve shear
resistance, but due to safety and regulatory reasons it is now avoided in the biopharmaceutical
industry. This requires an adaptation procedure of the cell line to the new environmental
conditions, which can impact cell growth, product yield, and product glycosylation (LeFloch et al.
2006; Harcum 2006; Restelli and Butler 2002; Geigert 2004). The effects of serum and serum-
free medium on protein glycosylation have been attributed to the variable presence of proteolytic
activities of extracellular enzymes (e.g. sialydase, galactosydase) that may alter glycan
CHAPTER 1 │ GENERAL INTRODUCTION
51
composition (Castro et al. 1995; Gawlitzek et al. 1995; Yang and Butler 2002). Furthermore,
these effects seem to be conflicting and very dependent on the type of cell and product (LeFloch
et al. 2006; Patel et al. 1992; Lifely et al. 1995), and may also vary with the different
formulations of serum-free media (Restelli and Butler 2002).
Other supplements used for the enhancement of production have been evaluated for their
potential effect on protein glycosylation, including lipids (Castro et al. 1995), amino acids,
manganese (Crowell et al. 2007), dimethylsulfoxide (DMSO), glycerol (Rodriguez et al. 2005),
and sodium butyrate (Sung et al. 2004; Mimura et al. 2001), with varying effects on
glycosylation, but typically affecting the level of sialylation.
The availability of nucleotide monosaccharide precursors may be a limiting factor for
glycosylation. The addition of some precursors to cell culture has been evaluated, including
glucosamine, cystidine, uridine, and N-acetyl mannosamine (ManNAc), with effects mainly on
sialylation and antennary levels. These effects have been variable with the type of product and
cells, leading to glycosylation enhancements (Kornfeld and Kornfeld 1985; Baker et al. 2001),
deterioration (Yang and Butler 2002), or no alteration (Baker et al. 2001).
CULTURE CONDITIONS
Several control parameters which are critical for the success of cell culture and product yield
have also been shown to affect protein glycosylation, including dissolved oxygen (DO), pH, carbon
dioxide (CO2), and temperature.
Oxygen plays a dominant role in the metabolism and viability of cells, but has low solubility
in the culture medium (Butler 2004). Therefore, it is important to continuously monitor and
control the DO level in cell culture, to maintain optimal metabolism and growth of producer cells
in bioprocesses (Zhu 2011; Hossler, Khattak, and Li 2009). DO has also shown to influence
glycosylation, apparently in a cell line- and/or protein-specific manner, but generally observed on
the levels of galactosylation (Kunkel et al. 1998) and sialylation (Chotigeat et al. 1994).
Culture pH is also an important parameter in cell culture and has been found to affect
protein glycosylation, specifically the levels of galactosylation (Müthing et al. 2003; Rothman et
al. 1989), sialylation (Müthing et al. 2003; Yoon et al. 2005), and glycan occupancy (Borys,
Linzer, and Papoutsakis 1993). The external culture pH may change the internal pH of the Golgi
apparatus, influencing the activities of key glycosylating enzymes and thereby changing the
glycan profile of the proteins produced (Butler 2004).
CHAPTER 1 │ GENERAL INTRODUCTION
52
The effect of CO2 on glycosylation is also a very important bioprocess consideration, since
media pH is commonly maintained via the bicarbonate (HCO3-)/CO2 equilibrium. Some effects of
CO2 on sialylation levels have been reported (Kimura and Miller 1997; Zanghi et al. 1999).
Temperature shifts from the usual 37 ºC to lower values have been used as a means to
increase product titers (Moore et al. 1997; Yoon, Kim, and Lee 2003; Clark, Chaplin, and
Harcum 2004; Bollati-Fogolín et al. 2005). These shifts in some cases do not affect glycosylation
(Yoon, Song, and Lee 2003; Bollati-Fogolín et al. 2005), but there have also been reports of
changes in the sialylation levels (Trummer et al. 2006).
TECHNOLOGY PLATFORM
The technology platform (bioreactor and mode of culture) can have a pronounced effect on
the resulting glycoform profile (Kunkel et al. 2000). The three most common production modes
are batch, fed-batch, and perfusion (Hossler, Khattak, and Li 2009). In batch culture, due to
nutrient consumption and product accumulation that change the cellular environment, the
glycosylation pattern varies over the course of the culture (Hahn and Goochee 1992). For its turn,
fed-batch may be vulnerable to glycan degradation by extracellular enzymes secreted by the cells
or released upon cell lyses (Butler 2004; Gramer and Goochee 1993), which may result in
significant heterogeneity of glycoforms. The early extraction of the product from the medium
reduces the residence time of the glycoprotein in culture and may lessen glycoform heterogeneity
(Butler 2004). It has also been reported that the use of perfusion culture seems to increase
sialylation in comparison to fed-batch cultures (Lipscomb et al. 2005).
The type of reactor also appears to affect protein glycosylation, with differences found on the
levels of sialylation (Goldman et al. 1998) and galactosylation (Nahrgang et al. 1999).
Furthermore, mammalian cells can be grown as anchorage-dependent cells in T-flasks or
microcarriers, or can be alternatively adapted to suspension culture. This adaptation process
leads to changes in the expression of cell surface proteins and may also affect glycosylation, in
particular the sialylation levels (Watson et al. 1994). Additionally, static culture may produce
proteins with higher levels of galactosylation (Lund et al. 1993; Kumpel et al. 1994).
CELL RELATED FACTORS
The culture conditions mentioned above affect the cell metabolism, in particular the cell
growth rate, density, viability, and specific productivity. These cell-specific parameters have been
CHAPTER 1 │ GENERAL INTRODUCTION
53
shown to modify the glycosylation pathway by affecting the levels of extracellular glycosidases in
the medium, which can step-wise remove monosaccharides from the glycans (Gramer and
Goochee 1993; Trummer et al. 2006; Gramer et al. 1995). They may also alter the residence
time of the protein in the Golgi, which might facilitate a more fully glycosylated structure (Wang et
al. 1991; Nabi and Dennis 1998; Shelikoff, Sinskey, and Stephanopoulos 1994), although some
studies have reported no effect (Bulleid et al. 1992).
1.6.6. GLYCOENGINEERING FOR IMPROVED THERAPEUTIC EFFICACY
As reflected in the previous sections, the control of glycosylation to a homogeneous
glycoform of desired characteristics is still a challenge that results in most of the glycoprotein-
based therapeutics currently being produced as mixtures of glycoforms. Such variability reduces
the therapeutic efficacy of the product, requiring its administration at higher doses and/or
frequency to obtain the desired effect in the patient (Beck et al. 2008; Wang and Lomino 2011).
This is a particularly relevant concern for therapeutic mAbs since their specific mode of action,
through binding to the target, is inhibited by the competition between undesired and desired
glycoforms, which further reduces the in vivo efficacy (Kanda et al. 2007; Iida et al. 2006; Satoh,
Iida, and Shitara 2006). To overcome these hurdles, a new approach has been explored in the
past decade, based on glycoengineering technologies that modify the glycans associated to the
proteins for an enhanced therapeutic efficacy. These technologies are applied to the glycoprotein
itself or to the host cell used for its production and have already achieved important
improvements on glycan quality (Wang and Lomino 2011; Shen et al. 2006; Sinclair and Elliott
2005; Yamane-Ohnuki and Satoh 2009).
CELL GLYCOENGINEERING
Perhaps the most intensely pursued glycoengineering approach in recent years has been the
engineering of the host cells through modifications of the glycosylation pathway to obtain a final
product with advantageous properties (Restelli and Butler 2002; Lim et al. 2010; Wang and
Lomino 2011). This approach has been used to improve the characteristics of the glycoproteins
produced by the currently preferred mammalian cell systems, but also to modify the glycosylation
CHAPTER 1 │ GENERAL INTRODUCTION
54
mechanisms of non-mammalian cells to permit their application in therapeutic glycoprotein
production.
MAMMALIAN CELLS
Although considered as the most adequate cell host for the expression of therapeutic
glycoproteins, due to their mostly human-like glycosylation, mammalian cells still impart
glycoproteins with some differences compared to the native human counterpart. Consequently,
glycoengineering of mammalian cells has focused on modifying the glycosylation pathways of
mammalian cells to obtain more uniform and human-like glycoproteins, and to improve their
therapeutic efficacy. Different approaches have been explored to achieve this more defined
glycosylation, including:
(i) Knock-out mutagenesis, which consists of the knock-out of specific genes along the
glycosylation pathways. A major target of this method has been the α1,6-fucosyltransferase
gene (fut8), which encodes for the fucosyltransferase enzyme responsible for the
attachment of a core Fuc residue to the glycan. The successful knock-out of fut8 has led to
the development of a knockout CHO cell line that produces completely defucosylated
antibodies (Natsume, Niwa, and Satoh 2009; Yamane-Ohnuki et al. 2004), which exhibit
enhanced ADCC (Satoh, Iida, and Shitara 2006; Masuda et al. 2007) and induce high
cellular cytotoxicity against tumor cells that express low levels of antigen (Niwa et al. 2005),
therefore achieving therapeutic efficacy at low doses (Shinkawa et al. 2003; Yamane-Ohnuki
et al. 2004).
(ii) Ribonucleic acid (RNA) interference, which uses specific small-molecule inhibitors to block
selected enzymes in the biosynthetic pathway (Wang and Lomino 2011; Zhou et al. 2008).
For example, the introduction of small interfering RNA to silence the fut8 gene is one of the
methods used to defucosylate mammalian cells for the production of mAbs with enhanced
ADCC activity (Mori et al. 2004; Omasa et al. 2008). Other example of this methodology is
the antisense knockdown of the enzyme CMP-sialic acid hydroxylase, responsible for the
conversion of NeuNAc to NeuGc, which results in the reduction of the levels of the
potentially immunogenic NeuGc (Chenu et al. 2003).
(iii) Overexpression of specific glycoprocessing enzymes in the host cells, an approach that can
also change the glycosylation profile and enrich the production of desired glycoforms. A
successful example is the combined overexpression of the enzymes α2,3-sialyltransferase
CHAPTER 1 │ GENERAL INTRODUCTION
55
and β1,4-galactosyltransferase, or of the enzymes α2,3-sialyltransferase and/or α2,6-
sialyltransferase, in the host cells, which resulted in increased sialylation of the glycoproteins
and consequently improved serum half-life (not applicable to mAbs) (Weikert et al. 1999;
Fukuta, Yokomatsu, et al. 2000; Jeong et al. 2008; Bork, Horstkorte, and Weidemann
2009). The overexpression of the enzymes GnT-I, GnT-IV, and GnT-V has also been
associated with improvements in sialylation due to an increase of the proportion of
branching structures and hence of the number of potential sites for sialylation (Fukuta, Abe,
et al. 2000; Goh et al. 2010). Another example of the use of this approach is the
overexpression of GnT-III to enhance the number of glycoforms containing bisecting GlcNAc
to improve the activity of mAbs via ADCC, since this residue blocks the attachment of core
Fuc, a monosaccharide known to be detrimental to ADCC (Davies et al. 2001; Ferrara,
Brünker, et al. 2006; Schuster et al. 2005). The combined overexpression of GnT-III and α-
mannosidase II has also been used to this effect (Matsumiya et al. 2007; Schuster et al.
2005; Ferrara, Brünker, et al. 2006).
NON-MAMMALIAN CELLS
Non-mammalian expression systems have several advantages over mammalian cells,
namely lower costs, high product yield, and simplicity of processes. However, due to their limited
capacity for glycosylation or to the introduction of potentially immunogenic residues in the
glycoproteins, they are not suitable for the production of therapeutic glycoproteins. Therefore,
glycoengineering emerges has a promising technology to overcome these limitations, by
providing means to humanize the glycoproteins produced in non-mammalian systems.
This humanization has been achieved using the same approaches described for mammalian
cells (gene knock-out, RNA interference, enzyme overexpression), but with different targets.
Indeed, in non-mammalian cells, the first objective is to avoid or eliminate the production of non-
human glycoforms, such as hypermannosylated glycans or glycans with immunogenic residues
(e.g. β1-2-Xyl and core α1-3-Fuc), which has been achieved by either gene knockout or RNA
interference methods (Chiba and Jigami 2007; Vervecken et al. 2004; Abe et al. 2009; Strasser
et al. 2008). After accomplishing this, a second objective of fully glycoprotein humanization may
be achieved through the functional transfer of mammalian glycan processing enzymes into the
non-mammalian cells, which essentially creates a mammalian biosynthetic pathway (De Pourcq,
De Schutter, and Callewaert 2010; Bobrowicz et al. 2004; Castilho et al. 2011).
CHAPTER 1 │ GENERAL INTRODUCTION
56
One of the successful examples of the application of this strategy is the recent engineering
of the glycosylation pathways in the yeast Pichia pastoris that allowed the expression of
recombinant proteins with human-type complex glycans. This entailed knocking out four genes to
prevent yeast specific glycosylation, and introducing 14 additional glycosylation genes encoding
for glycosylation enzymes (Hamilton and Gerngross 2007).
PROTEIN GLYCOENGINEERING
Glycoengineering technologies have also been used to modify the glycan moiety itself, which
may be accomplished by different strategies:
(i) Incorporation of additional glycosylation sites into the protein backbone: in this strategy, new
N-glycosylation consensus sequences (Asn-X-Ser/Thr) are inserted into desired positions in
the protein backbone by site-directed mutagenesis. It has been used to create glycoproteins
with increased levels of glycosylation and consequently sialylation, leading to extended
serum half-life and improved in vivo activity (Elliott et al. 2003; Perlman et al. 2003).
(ii) Chemoselective and site-specific glycosylation of proteins: while the incorporation of
additional glycosylation sites into the protein backbone improves the therapeutic efficacy of
the protein by increasing the overall level of glycosylation, this approach acts in a more
specific manner. Here, the aim is to insert specific glycans into glycosylation sites that have
been pre-indentified as critical for proper biological activity. This is accomplished by the
introduction of specific tags (e.g. the natural cisteine or unnatural azide-, aldehyde-, alkyne-
and alkene-containing residues) at predetermined glycosylation sites by site-directed
mutagenesis. The tags are then selectively reacted with a modified glycan, containing an
appropriate functional group, via bio-orthogonal chemoselective ligation (Wang and Lomino
2011; Hirano et al. 2009; Wang, Winblade Nairn, et al. 2008). Since different tags can be
selectively introduced at different sites in a protein, it becomes possible to insert multiple
distinct glycans in a given protein through orthogonal chemoselective ligations (Wang and
Lomino 2011; van Kasteren et al. 2007), thereby controlling and improving the biological
efficacy of the glycoprotein.
(iii) Chemoenzymatic glycosylation remodeling: this strategy provides an attractive approach
toward glycan-defined glycoforms (Wang and Lomino 2011), and can be performed using
two strategies. In one of the strategies, the glycosylated recombinant proteins obtained in
CHAPTER 1 │ GENERAL INTRODUCTION
57
the host cells are enzymatically trimmed down (deglycosylated) to the innermost GlcNAc,
giving a homogeneous GlcNAc-containing protein. The homogenous glycans are then
extended by selected enzymes such as glycosyltransferases and endoglycosidases to provide
a mature, glycan-defined glycoprotein (Wang and Lomino 2011; Wei et al. 2008; Zou et al.
2011). However, this strategy of sequential extension does not guarantee the homogeneity
of the end product, and mixtures of glycoforms may be produced (Wang and Lomino 2011).
An alternative to this sequential extension is the en block transfer of a presynthesized large
glycan to the protein in a single step under the catalysis of natural or mutant endo-β-N-
acetylglucosaminidase (ENGase) (Wang and Lomino 2011; Wang 2008; Walsh 2010; Zhu et
al. 2005). It should be noted that although efficient, these enzymatic strategies are generally
associated with cost issues (Yamane-Ohnuki and Satoh 2009).
1.6.7. STRATEGIES FOR GLYCOSYLATION ANALYSIS
The analysis of protein glycosylation for quality control, product optimization, and safety
reasons is of huge concern to the biotechnology industry, but presents technical challenges.
Indeed, owing to the complexity and heterogeneity of glycans, the chemical similarity in their
monosaccharide subunits, and the possibility of many different types of linkages between them, a
single analytical method rarely provides full compositional and structural analysis (Brooks 2009;
Dalpathado and Desaire 2008). On their own, each method provides helpful information, but for
a reliable and detailed analysis, several complimentary approaches need to be employed in
combination (Brooks 2009; Roth, Yehezkel, and Khalaila 2012). For this reason, regulatory
agencies require the use of at least two or more orthogonal analytical methods to fully
characterize therapeutic glycoproteins, such as mAbs (Harcum 2006; Raju 2008; Marino et al.
2010). The selection of the appropriate analytical techniques depends, among other things, on
the amount and purity of sample available for analysis, cost per sample, the resources and
technical expertise available, and the level of compositional and structural detail required (Brooks
2009; Harcum 2006).
Broadly, glycosylation analysis can be divided into four strategies: glycoprotein, glycopeptide,
glycan, and monosaccharide analysis (Figure 1.10) (Harcum 2006). All the strategies require
prior purification of the protein of interest, usually achieved by gel electrophoresis or affinity
CHAPTER 1 │ GENERAL INTRODUCTION
58
chromatography (e.g. protein A or protein G for mAb purification) (Küster et al. 2001; Wang, Wu,
and Hancock 2006; Huhn et al. 2009).
FIGURE 1.10. Approaches for the glycosylation analysis of proteins. The glycoprotein can be analyzed intact or
fractioned into glycopeptides, glycans or monosaccharides for more detailed assessment. The analysis by one
approach can be followed by another, with the most and less common analytical pathways shown as full and dashed
lines, respectively.
GLYCOPROTEIN ANALYSIS
The analysis of intact glycoproteins is an easy, fast and inexpensive approach, but limited by
the relatively low level of resolution obtained (Harcum 2006). Consequently, this approach is
most commonly used to obtain preliminary information on molecular mass, to judge the outcome
of enzymatic reactions, to assess the sites of heterogeneity, and for purposes of purification and
fractioning prior to mass spectrometry analysis used in other approaches. Additionally, intact
glycoprotein analysis can be used for a fast monitoring during the optimization of manufacturing
processes and to assess the variability and lot-to-lot consistency (Taverna et al. 1998; Huhn et al.
2009).
Different techniques are used to analyze intact glycoproteins, based on their separation
according to molecular weight, charge, or affinity.
MOLECULAR WEIGHT
Proteins can be separated according to their molecular weight by conventional sodium
dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE), and then identified as
GLYCOPROTEIN GLYCOPEPTIDE
GLYCAN
MONOSACCHARIDE
CHAPTER 1 │ GENERAL INTRODUCTION
59
glycosylated proteins (glycoproteins) by staining the gel with the periodic acid Schiff (PAS)
reaction (Patton 2001; Osborne and Brooks 2006; Roth, Yehezkel, and Khalaila 2012). For a
more specific identification, the separated glycoproteins can be transferred onto a supporting
membrane to be probed for the binding of lectins or antibodies (see below for affinity-based
analysis) (Osborne and Brooks 2006).
CHARGE
The use of two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) allows the
separation of glycoproteins by both molecular weight and charge. This technique, also followed
by PAS staining, provides a more powerful approach than simple SDS-PAGE for the separation of
glycoproteins from complex and heterogeneous mixtures (Brooks 2009; Wilson et al. 2002; Dwek
and Rawlings 2006).
AFFINITY
Affinity-based procedures are more specific and allow the determination of the type of
glycosylation (e.g. N- or O-linked) (Roth, Yehezkel, and Khalaila 2012). They mostly rely on
lectins, which are proteins that bind highly selectively to all monosaccharides or glycans on the
glycoprotein, or sometimes on anti-glycan mAbs that are more specific for certain glycan
determinants and more expensive (Cummings and Etzler 2009; Brooks 2009). Probing
glycoproteins with a variety of lectins and antibodies (in a format similar to enzyme-linked
immunosorbent assays) is especially useful to determine whether two samples differ in
glycosylation (Cummings and Etzler 2009; Roth, Yehezkel, and Khalaila 2012).
Recently there has been interest in using lectins and antibodies in arrays or ‘chips’ for
qualitative and quantitative glycan profiling of purified glycoproteins or mixtures of glycoproteins
(Hsu and Mahal 2006; Pilobello, Slawek, and Mahal 2007). This technology provides an
indication of the range of glycan structures present and may become important for a fast, low-
tech, and high-throughput analysis (Brooks 2009; Patwa et al. 2010).
GLYCOPEPTIDE ANALYSIS
Glycopeptide analysis is the least established approach, but is currently showing rapid
development. The interest of this strategy is the possibility of correlating the glycan composition
to the attachment site, a characteristic that makes it often referred as a glycosylation site-specific
CHAPTER 1 │ GENERAL INTRODUCTION
60
analysis. The assignment of a structure to a specific site may provide an indication of the function
of the glycan and shed light on the glycosylation profile and microheterogeneity of a protein, and
consequently on its activity (Dalpathado and Desaire 2008; Roth, Yehezkel, and Khalaila 2012).
Glycopeptide analysis can be applied to both N- and O-linked glycans, although the former is
more common, and involves different steps. Initially the glycoprotein is isolated from complex
biological mixtures, traditionally by gel electrophoresis or affinity chromatography (using
antibodies for protein-specific analysis or lectins to isolate a broad range of glycoproteins) (Küster
et al. 2001; Geng et al. 2001; Wang, Wu, and Hancock 2006; Dalpathado and Desaire 2008).
The isolated glycoprotein is then typically denatured (i.e. by reduction and alkylation) to improve
the efficiency of the following step of proteolysis (Dalpathado and Desaire 2008). Proteolysis is
performed to obtain both glycosylated and non-glycosylated peptides from the glycoprotein, which
can be achieved with a variety of enzymes (e.g. trypsin, which cleaves the protein at well-defined
sites, or non-specific proteinase K and pronase) (Dalpathado and Desaire 2008; Larsen, Højrup,
and Roepstorff 2005; Wuhrer et al. 2004). The peptides may then be purified for glycopeptide
enrichment, which consists on the separation of glycopeptides from non-glycosylated peptides
and is usually accomplished by reverse phase high-performance liquid chromatography (RP-
HPLC) on its own or combined with other purification methods (e.g. lectin affinity
chromatography or size exclusion chromatography), by hydrophilic interaction chromatography
(HILIC) or normal-phase HPLC (NP-HPLC) (Peterman and Mulholland 2006; Wuhrer et al. 2004;
Hemström and Irgum 2006). Finally, the glycopeptides are analyzed, typically by mass
spectrometry (MS) techniques (Dalpathado and Desaire 2008; Wuhrer et al. 2007).
GLYCAN ANALYSIS
Glycan analysis is the approach of choice for in-depth structural characterization, including
linkage information. The overall strategy for glycan analysis includes glycan release, derivatization
and sequencing, to obtain a final structure assignment.
Depending on its nature, glycans can be removed from the protein by chemical or enzymatic
means. The chemical removal can be applied to both N- and O-linked glycans, and includes the
methods of β-elimination, either alkaline (reductive, may cause glycan degradation) or ammonia-
based (non-reductive, prevents degradation), and the widely used and high-yielding hydrazinolysis
(Brooks 2009; Merry et al. 2002; Huang, Mechref, and Novotny 2001). On the other hand, the
CHAPTER 1 │ GENERAL INTRODUCTION
61
enzymatic release relies on specific enzymes (glycanases) that cleave the glycans from the
glycoprotein, and is mostly used for N-glycans, with limited application in O-glycans. This is a
consequence of the inability to find a generic glycanase that acts on all O-glycan core structures
(only one specific enzyme was found against Core 1), making the chemical methods the current
best approach for their release (Marino et al. 2010; Merry et al. 2004). The most efficient
cleaving enzyme for N-glycan release is the peptide N-glycosidase F (PNGase F), which cleaves
the bond between the core GlcNAc and the Asn residue of all classes of N-glycans, with the
exception of those containing a core α1,3-Fuc (Tretter, Altmann, and März 1991; Roth, Yehezkel,
and Khalaila 2012). To cleave N-glycans containing the core α1,3-Fuc, PNGAse A should be used
(Royle et al. 2007; Tretter, Altmann, and März 1991). Alternatively, endoglycosidases that cleave
N-glycans between the two core GlcNAcs can be used, such as endo-H and endo-F1,2,3 (Trimble
and Tarentino 1991; Roth, Yehezkel, and Khalaila 2012; Marino et al. 2010).
After being released, glycans are commonly labeled using a fluorescent tag to enable their
detection and quantitation at the fentomole level. This labeling is performed by derivatization with
a fluorophore, with the most common including 2-aminobenzamide (2-AB), 2-aminopyridine (2-
AP), 2-aminoanthranilic acid (2-AA), 2-aminoacridone (AMAC), and 8-aminonaphtalene-1,3,6-
trisulfonic acid (ANTS) (Merry et al. 2004; Bigge et al. 1995; Domann et al. 2007). The labeled
glycans may then be separated by high-resolution techniques for sequence analysis by
chromatographic, electrophoretic and mass spectrometry methods (Merry et al. 2004).
CHROMATOGRAPHIC METHODS
Chromatography is one of the most widely used, and most accessible, approaches for the
analysis of glycans. Depending on the specific method, it is possible to separate the glycans
according to different physical characteristics, and it is common to use more than one approach
in parallel to obtain more complete compositional or structural data. Furthermore, to obtain a full
structural analysis, chromatographic methods are often used in conjunction with other
approaches like MS (see below) (Brooks 2009). The most commonly used chromatographic
methods in glycan analysis include: high performance anion exchange chromatography (HPAEC)
usually combined with pulse amperometric detection (HPAEC-PAD), for the analysis of
underivatized glycans (Townsend and Hardy 1991); weak anion exchange (WAX-HPLC), which
separates glycans by charge (Tran et al. 2000; Royle et al. 2002; Guile, Wong, and Dwek 1994);
RP-HPLC, which separates glycans on the basis of their hydrophobicity (Royle et al. 2002; Brooks
CHAPTER 1 │ GENERAL INTRODUCTION
62
2009); and NP-HPLC, which separates glycans on amine columns where the retention time
mainly depends on the first approximation of the size of the glycan (Royle et al. 2002; Guile et al.
1996). This latter method is the most widely used for glycan analysis due a high resolution and
reproducibility. By using an external standard (e.g. hydrolyzed dextran), it is possible to convert
the retention times of the separated glycans to glucose units (GU), and compare them to those of
a database of GU values from known structures (e.g. Glycobase). The GU value of each individual
glycan structure is directly related to the number and linkage of its constituent monosaccharides,
so the GU values can be used to obtain a preliminary structure assignment that nevertheless
needs further confirmation (Guile et al. 1996; Brooks 2009; Campbell et al. 2008). For this,
digestion with exoglycosidases (enzymes that specifically cleave terminal monosaccharides from
the glycans, Table 1.9), are often used, either individually or in arrays, followed by profiling of the
digestion products by NP-HPLC (Royle et al. 2007).
TABLE 1.9. Exoglycosidase enzymes used for glycan analysis and respective monosaccharide and linkage specificity
(Royle et al. 2007)
ENZYME ABBREVIATION SPECIFICITY
Arthrobacter uerafaciens sialidase Abs Sialic acid α2-6>3,8
Streptococcus pneumoniae sialidase Nan1 Sialic acid α2-3,8
Bovine testis galactosidase Btg Gal β1-3,4>6
Streptococcus pneumoniae galactosidase Spg Gal β1-4
Coffee bean α galactosidase Cbg Gal α1-3,4,6
Bovine kidney focusidase Bkf Fuc β1-6>2>>3,4
Almond meal fucosidase Amf Fuc β1,3-4
Streptococcus pneumoniae N-acetylhexosaminidase Sph GlcNAc β1-2>3,4,6
Jack bean N-acetylhexosaminidase Jbh GlcNAc, GalNAc β1-2,3,4,6
Jack bean mannosidase Jbm Man α1-2,3,6
The existence of peak shifts after digestion with the exoglycosidases is indicative of the
specific activity of the enzymes and can be related to both the type and the number of
monosaccharides removed (Table 1.10), enabling detailed structural assignments (Guile et al.
1996; Brooks 2009; Royle, Dwek, and Rudd 2001).
CHAPTER 1 │ GENERAL INTRODUCTION
63
TABLE 1.10. Incremental glucose unit (GU) values of different monosaccharides and linkages for the structural
assignment of 2-AB labeled N-glycans (Royle et al. 2007)
MONOSACCHARIDE LINKAGE TO GU INCREMENT
Man α1-2,3,6 Man 0.7-0.9
GlcNAc β1-2,4,6 α-Man 0.5
GlcNAc (bisecting) β1-4 β-Man 0.2-0.4
Gal α or β1-3,4 GlcNAc or Gal 0.8-0.9
Fuc (core) α1-6 Core GlcNAc 0.5
Fuc (outer arm) α1-3,4 GlcNAc 0.8
Fuc (outer arm) α1-2 Gal 0.5
NeuAc α2-3,6 Gal 0.7-1.2
Additionally, it is possible to obtain relative glycan quantification by calculating the peak area
of each glycan in relation to the total repertoire, when using the 2-AB fluorescent label, due to the
direct correlation between its fluorescence intensity and the number of moles of the labeled
glycans (Royle et al. 2007; Roth, Yehezkel, and Khalaila 2012).
ELECTROPHORETIC METHODS
Electrophoretic methods such as capillary electrophoresis (CE) efficiently separate charged
molecules. In particular, CE with laser-induced fluorescence detection (CE-LIF) provides a
promising method for glycan analysis, offering high sensitivity, high resolution, and a separation
time considerably shorter than HPLC (Beck et al. 2008; Kamoda and Kakehi 2006; Marino et al.
2010). The combination of CE and MS (CE-MS/CE-LIF-MS) also holds promise as a powerful tool
for the structural analysis of glycans (Kamoda and Kakehi 2006; Gennaro and Salas-Solano
2008).
MASS SPECTROMETRY METHODS
MS analysis is based on glycan ionization, fragmentation, and mass identification of the
fragments, providing a link between mass and composition of the glycans (Marino et al. 2010;
Roth, Yehezkel, and Khalaila 2012). It requires prior derivatization of the glycans due to their low
ionization efficiency (Kang, Mechref, and Novotny 2008; Marino et al. 2010). Two main types of
MS are currently used for glycan analysis, namely matrix assisted laser desorption ionization
(MALDI-MS) and electrospray (ESI-MS) (Merry et al. 2004; Marino et al. 2010; Roth, Yehezkel,
and Khalaila 2012). MALDI-MS gives some indication of glycan identity and is often used in
CHAPTER 1 │ GENERAL INTRODUCTION
64
conjunction with time of flight analysis (MALDI-MS-TOF) (Wada et al. 1994). ESI-MS provides data
that can be interpreted to determine monosaccharide linkage and position (Fenn et al. 1989).
Although MALDI and ESI spectra can be used for the elucidation of glycan composition and
structure, full glycan characterization by MS is rather difficult due to common glycan quantity
limitations and, more importantly, the identical molecular weight of some monosaccharides that
hinders their specific identification based solely on the number of carbon atoms (Roth, Yehezkel,
and Khalaila 2012; Brooks 2009). Therefore, MS techniques are often used in combination with
HPLC or CE (Roth, Yehezkel, and Khalaila 2012; Kamoda and Kakehi 2006; Marino et al. 2010).
MONOSACCHARIDE ANALYSIS
Monosaccharides can be obtained directly from an intact glycoprotein or glycopeptide pool,
or even from released glycans (Figure 1.10). They are cleaved through acid hydrolysis and
identified by chromatography or electrophoresis; or alternatively released through methanolysis
and identified and quantified by gas chromatography (GC) combined with MS (GC-MS) (Manzi
and Varki 1993; Tarelli 2007; Marino et al. 2010).
This approach provides preliminary information on identity and composition of the
monosaccharides, which is a good indicator of the type and relative amount of glycans present in
the glycoprotein (Tarelli 2007; Brooks 2009; Harcum 2006). This information is valuable for the
rational planning of further investigations, and can be used as a very basic measure of product
consistency and extent of glycosylation for recombinant glycoprotein therapeutics at all stages of
production (Marino et al. 2010; Brooks 2009; Tarelli 2007). Additionally, the use of methylation
followed by GC-MS can provide information about the linkage positions of individual
monosaccharides (Tarelli 2007; Brooks 2009).
In this brief description of the strategies for glycosylation analysis, several analytical
techniques were mentioned. Each of these techniques measures glycosylation based on diverse
physical and chemical characteristics of the glycoprotein and offers different information (Harcum
2006). No technique on its own is currently able to provide full glycan characterization, and their
integration is often used to obtain more in-depth profiling. Table 1.11 summarizes the major
techniques used in glycosylation analysis, indicating their basic principle, approaches of analysis
in which they apply, information gathered, and main advantages and limitations.
CHAPTER 1 │ GENERAL INTRODUCTION
65
ANALYTICAL METHOD
PRINCIPLE
APPROACH
INFORMATION / USE
MAIN ADVANTAGES AND LIMITATION
ELECTROPHORETIC
SDS-PAGE
Molecular weight
Glycoprotein, glycopeptide
Separation by molecular weight, degree of glycosylation
+ Cheap, fast, adaptable to high-throughput
- Limited resolution, labor-intensive
IEF-PAGE
Charge
Glycoprotein, Glycopeptide
Separation by isoelectric point (pI), glycoform profiling
+ Cheap, fast
2D-PAGE
Molecular weight,
charge
Glycoprotein
Separation by pI and molecular weight, glycoform profiling
+ Cheap, fast, high resolution
- Low reproducibility, inability to resolve too large/small/acidic/
basic, low abundant or hydrophobic proteins
CE / CE-LIF
Charge
Glycoprotein, Glycopeptide, Glycan
Separation, profiling, site occupancy
+ Cheap, fast, high specificity, versatile, adaptable to high-
throughput
CHROMATOGRAPHIC
GC
Partition
Monosaccharide
Monosaccharide composition and quantification
+ Robust and high resolution
HPAEC-PAD
Charge, linked
isomers
Glycan, Monosaccharide
Separation without need for derivatization, glycan profiling,
monosaccharide identification
+ It does not require derivatization, high resolution
- Aggressive eluents, relatively extensive analysis time
WAX-HPLC
Charge, size (to a
less extent)
Glycoprotein, Glycan
Separation, determination of acidic and neutral
monosaccharides
+ High sensitivity
RP-HPLC
Polarity
Glycopeptide, Glycan, Monosaccharide
Separation, glycan profiling and sequencing, monosaccharide
identification
+ High resolution, simple
- Relatively extensive analysis time
NP-HPLC
Polarity, size
Glycopeptide, Glycan, Monosaccharide
Separation, glycan profiling and sequencing, monosaccharide
identification and relative quantification
+ High resolution, simple
- Relatively extensive analysis time
HILIC
Polarity, size
Glycopeptide, Glycan
Improved separation of glycans, including resolution of
structural isomers
+ High sensitivity, high reproducibility
TA
BLE
1.1
1. Analytical techniques to characterize glycosylation, their basic principle, approaches in which they apply, information provided and main advantages and limitations (Roth,
Yehezkel, and Khalaila 2012; Harcum 2006; Brooks 2009; Marino et al. 2010; Dalpathado and Desaire 2008; Huhn et al. 2009)(Roth, Yehezkel, and Khalaila 2012; Harcum 2006;
Brooks 2009; Marino et al. 2010; Dalpathado and Desaire 2008; Huhn et al. 2009)(Roth, Yehezkel, and Khalaila 2012; Harcum 2006; Brooks 2009; Marino et al. 2010; Dalpathado and
Desaire 2008; Huhn et al. 2009)(Roth, Yehezkel, and Khalaila 2012; Harcum 2006; Brooks 2009; Marino et al. 2010; Dalpathado and Desaire 2008; Huhn et al. 2009)
CHAPTER 1 │ GENERAL INTRODUCTION
66
ANALYTICAL METHOD
PRINCIPLE
APPROACH
INFORMATION / USE
MAIN ADVANTAGES AND LIMITATION
MASS SPECTROMETRY
ESI-MS
Mass
Glycoprotein, Glycopeptide, Glycan
Relative proportion of glycoforms, glycan sequencing,
monosaccharide linkage and position
+ Fast, detailed information, easily coupled to HPLC and CE
- Laborious sample preparation, complex data analysis
MALDI-MS
Mass
All
Relative proportion of glycoforms, heterogeneity in mass,
glycan sequencing
+ Fast, adaptable to high-throughput
- Laborious sample preparation, Quantitation not very reliable
MALDI-TOF-MS
Mass
All
Relative proportion of glycoforms, heterogeneity in mass,
glycan sequencing, site occupancy
+ Fast, adaptable to high-throughput
- Laborious sample preparation
GC-MS
Partition, mass
Monosaccharide
Identification and quantification of monosaccharides,
determination of monosaccharide linkage positions
+ Reliable, powerful
- Laborious sample preparation, complex data analysis
LC-MS
Polarity, mass
Glycopeptide, Glycan
Glycopeptide/glycan mass and profiling
+ High sensitivity and selectivity, less sample preparation
requirements
- Expensive equipment, complex data analysis
CE-MS / CE-LIF-MS
Charge, mass
Glycoprotein, Glycopeptide, Glycan
Mapping of glycosylation sites, glycan mass and sequencing
+ High sensitivity and resolution
OTHER
Excoglycosidase digestion
Glycoprotein, Glycopeptide, Glycan
Glycan linkage and sequencing
+ Detailed glycan fingerprinting, versatile
- Time-consuming and limited to the scope of enzymes available
NMR
Electromagnetism
Glycan, Monosaccharide
Full (tri-dimensional) structural information of complex glycans,
including monosaccharide anomericity
+ Non destructive
- Expensive equipment, complex data analysis, requires large
amounts and highly purified glycans
Immunoblotting /
Affinity assay
Affinity
Glycoprotein
Partial glycan characterization: differentiation between O- and
N-glycosylation, detection of sialic acids
+ Simple, fast
TA
BLE
1.1
1. Analytical techniques to characterize glycosylation, their basic principle, approaches in which they apply, information provided and main advantages and limitations (Roth,
Yehezkel, and Khalaila 2012; Harcum 2006; Brooks 2009; Marino et al. 2010; Dalpathado and Desaire 2008; Huhn et al. 2009)(Roth, Yehezkel, and Khalaila 2012; Harcum 2006;
Brooks 2009; Marino et al. 2010; Dalpathado and Desaire 2008; Huhn et al. 2009)(Roth, Yehezkel, and Khalaila 2012; Harcum 2006; Brooks 2009; Marino et al. 2010; Dalpathado
and Desaire 2008; Huhn et al. 2009)(Roth, Yehezkel, and Khalaila 2012; Harcum 2006; Brooks 2009; Marino et al. 2010; Dalpathado and Desaire 2008; Huhn et al. 2009)
CHAPTER 1 │ GENERAL INTRODUCTION
67
1.7. CONCLUDING REMARKS
In spite of recent advances in the field, the characterization and control of glycosylation
during the diverse stages of therapeutic protein production is currently hindered by the scarce
understanding on the effect of different parameters and culture conditions in this property, as
well as by the lack of adequate analytical methodologies available. It is expected that in the
future, a more in-depth knowledge on the relationship between glycosylation and protein
functionality and on the influence of culture parameters on glycosylation will not only allow a
proper control of this modification but also enable manipulation of culture conditions towards a
more desirable glycoform profile. In this context, glycoengineering appears as a promising
technology, enabling the engineering of the glycoprotein itself or the glycan biosynthetic pathway
in the host cell, to produce glycoproteins with improved functionality. In particular,
glycoengineering opens new horizons to the application of non-mammalian expression systems to
produce therapeutic glycoproteins, by humanizing glycan biosynthesis and/or eliminating
potentially immunogenic structures.
Nevertheless, further progresses in the field will largely depend of the development of fast,
simple, high sensitive, and high-throughput analytical methodologies, which provide complete
structural analysis for glycosylation monitoring during different stages of process development
and production. In particular, the protocols for sample preparation and purification will have to be
addressed since they are currently a major time-consuming step of glycosylation analysis.
Ultimately, these developments will lead to therapeutic products with improved efficacy,
which will reduce the dose and frequency of administration required and therefore improve
patient compliance with the therapy.
CHAPTER 1 │ GENERAL INTRODUCTION
68
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hapter hapter hapter hapter 2222
The OSCARTM system for the transfection
of Chinese hamster ovary cells for
monoclonal antibody production
CC
THE PRESENT CHAPTER WAS ADAPTED FROM THE FOLLOWING RESEARCH PAPER
ANA RITA COSTA, Maria Elisa Rodrigues, Mariana Henriques, David Melton, Philip
Cunnah, Rosário Oliveira, Joana Azeredo (2012). Evaluation of the OSCARTM system
for the production of monoclonal antibodies by CHO-K1 cells. International Journal of
Pharmaceutics, 430:42-46.
101
iopharmaceutical production of complex recombinant protein therapeutics currently
relies on mammalian cell systems. The development of high-yielding stable cell lines requires
processes of transfection, selection and adaptation. With several technologies available, selection
has been most frequently based on dihydrofolate reductase or glutamine synthetase systems,
which can be very time-consuming. Due to the pressure to reduce development costs and speed
up time to market, new technologies are emerging, as the promising OSCARTM expression system
that could provide more rapid development of high-yielding stable cell lines than the traditional
systems. However, further evaluation of its application in a wider range of cell types and media is
still necessary. In this chapter, the application of OSCARTM for the transfection of a Chinese
hamster ovary (CHO-K1) cell line with a monoclonal antibody (mAb) was evaluated. OSCARTM was
reasonably fast and simple, without negative impact on cell growth characteristics. However,
minigene selection proved to be critical, with only the most disabled minigene (pDWM128)
working for the cell line assessed. Furthermore, the initial relatively high levels of production
decreased significantly in the first few weeks of culture, remaining relatively stable although with
low yield thereafter. This study also suggests a strong impact of the methodology of clone
selection on the outcome of the process, recommending the use of an accurate method such as
productivity assessment. Additionally, glycosylation analysis of the mAb produced was performed
by high performance liquid chromatography and indicated a similar product quality among the
clones obtained after transfection. As a whole, the results of this work prove that the OSCARTM
expression system has significant value to the biopharmaceutical industry.
Keywords: Chinese hamster ovary cells; Transfection; OSCARTM expression system; Monoclonal
antibody; Glycosylation
BB
CHAPTER 2 │ TRANSFECTION WITH THE OSCARTM EXPRESSION SYSTEM
103
2.1. INTRODUCTION
Therapeutic proteins, and monoclonal antibodies (mAbs) in particular, have assumed an
increasing importance in the last years, which is corroborated by their significant market growth
(Li and d’Anjou 2009; Durocher and Butler 2009). They are applied in a wide range of areas that
include treatment of diseases such as cancer, diabetes, anaemia, haemophilia, allergies, and
blood clotting disorders, as well as research applications (Bhopale and Nanda 2005). For their
commercial production, several expression systems can be used, with mammalian cells as the
current preference (Mohan et al. 2008; Melton et al. 2001; Chu and Robinson 2001; Andersen
and Reilly 2004) due to their ability to perform in-vivo correct refolding and post-translational
modifications (Werner et al. 1998), which guarantee a proper biological function of the protein.
In order to maximize the protein yield in mammalian cells, gene expression systems are
routinely used, which through selection and amplification can provide relatively high expressing
stable cell lines to use in manufacture (Page and Sydenham 1991; Wurm 2004; Bebbington et
al. 1992). The most commonly used gene expression systems include the dihydrofolate
reductase (DHFR) and the glutamine synthetase (GS) systems that exploit different metabolic
pathways (nucleotide metabolism for DHFR and glutamine metabolism for GS) (Wurm 2004;
Lonza), but similarly require multiple rounds of amplification after transfection through the use of
increasing concentrations of specific drugs (methotrexate in DHFR and methionine sulphoximine
in GS) (Chusainow et al. 2009; Lonza ; Andersen and Reilly 2004). This results in extended
development times and has high costs associated with the use of specialized media and toxic
chemicals.
Recently, a novel expression system known as OSCARTM has been developed at the
University of Edinburgh (Melton et al. 2001). This system relies on partially disabled minigene
vectors that encode for hypoxanthine phosphoribosyltransferase (HPRT), essential for purine
synthesis via the normal cellular salvage pathway (Barnes, Bentley, and Dickson 2001; Melton et
al. 2001). HPRT-deficient mammalian cells transfected with one of these minigenes and a gene
of interest are placed in a selective Hypoxanthine Aminopterin Thymidine (HAT) medium that
blocks the de novo purine synthesis. This makes cell survival reliant on the salvage pathway
using a disabled HPRT enzyme (Melton et al. 2001). Since large amounts of this enzyme are
required for cell survival, selection and amplification in the OSCARTM system takes place in a
CHAPTER 2 │ TRANSFECTION WITH THE OSCARTM EXPRESSION SYSTEM
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single step which potentially provides a time advantage over the traditional DHFR and GS
systems. In addition to being more expedite, OSCARTM is also said to provide cells with higher (7-
fold) and stable (Melton et al. 2001) expression yields at lower (7-fold) costs of goods
(Nicholson), due to the absence of specialized media and toxic chemicals that are required by
traditional systems. Furthermore, by providing HPRT minigenes with varying degrees of
expression disability, OSCARTM can be used in a wide range of cell types with different
requirements for HPRT expression, and enables the optimization of the production of different
proteins.
Although with many potential advantages, the recentness of OSCARTM demands for a deeper
evaluation of its applicability in a wider range of cell types and media, as well as its scalability
and performance in bioreactor cultures (Costa et al. 2010). Thus, the work described in the
present chapter evaluates the application of OSCARTM for the transfection of a CHO-K1 cell line
expressing a mAb. This covered the impact of the expression system on cell growth
characteristics, the levels and stability of mAb production achieved, as well as the ease of the
implementation/execution of the methodology. Additionally, the glycosylation profile of the mAb
obtained from the highest-producer cell clones was compared to evaluate possible differences in
product quality among the clones obtained using the OSCARTM expression system.
CHAPTER 2 │ TRANSFECTION WITH THE OSCARTM EXPRESSION SYSTEM
105
2.2. MATERIALS AND METHODS
2.2.1. CELLS, PLASMIDS AND MINIGENES
The CHO-K1 cell line was obtained from the American Type Culture Collection (ATCC, CCL-
61, Spain). The HPRT-deficient cells CHO-K1 TG-2 were kindly provided by the University of
Edinburgh (Scotland), which also supplied the disabled HPRT minigenes pDWM131, pDWM129
and pDWM128 required for transfection with their proprietary OSCARTM system. The
characteristics of these minigenes in comparison with the fully functional HPRT gene (pBT/PGK-
HPRT[RI]) are shown in Table 2.1. The minigenes were linearized with BamHI by the company
Biotecnol SA (Lisbon, Portugal), which also provided the gene/plasmid of their monoclonal
antibody CAB051 for cell transfection.
TABLE 2.1. Characteristics of the disabled HPRT minigenes used in the OSCARTM expression system, in comparison
with the fully functional HPRT gene pBT/PGK-HPRT[RI]
HPRT GENE/MINIGENE LEVEL OF EXPRESSION DISABILITY
pBT/PGK-HPRT[RI] Fully functional gene, contains nine introns
pDWM131 Least disabled minigene, contains truncated introns 1 and 2, and introns 7 and 8
pDWM129 Minigene contains truncated intron 1 and a more truncated intron 2
pDWM128 Most disabled minigene, contains only the truncated intron 1
2.2.2. SELECTION AND VALIDATION OF HPRT-DEFICIENT CLONES
CHO-K1 cells were seeded into petri dishes (Frilabo, Portugal) at 5x104 cells/mL in Growth
medium composed of Dulbecco’s Modified Eagle’s Medium (DMEM, Sigma-Aldrich, United
Kingdom) supplemented with 10 % fetal bovine serum (FBS, Sigma-Aldrich) and 200 mM L-
glutamine (Sigma-Aldrich), and grown overnight at 37 ºC and 5 % carbon dioxide (CO2). The
medium was replaced by Growth medium supplemented with 20 µg/mL 6-thioguanine (Sigma-
Aldrich) and the cells incubated for additional 14-15 days. Then, individual clones of HPRT-
CHAPTER 2 │ TRANSFECTION WITH THE OSCARTM EXPRESSION SYSTEM
106
deficient cells were selected and isolated using either cloning rings or cloning disks (Sigma-
Aldrich), according to manufacturer’s instructions. Briefly, the bottom part of the cloning rings
was coated with silicone grease (Sigma-Aldrich) and placed over individual cell colonies. Cells
isolated within the ring were detached using trypsin (Sigma-Aldrich), transferred to 24-well plates
(Frilabo) and sequentially expanded to 6-well plates, 25 cm2 and 75 cm2 culture flasks (Frilabo).
Cloning disks, for their turn, were soaked in trypsin and placed directly over individual cell
colonies. After 5-10 minutes, the disks containing the detached cells were transferred to 24-well
plates and expanded as described above for the cloning rings.
The clones isolated were validated for HPRT-deficiency and mutation stability, by seeding
into petri dishes at 1.3x105 cells/mL in Growth medium supplemented with 50x HAT (final
working concentration of 100 µM hypoxanthine, 0.4 µM aminopterin, and 16 µM thymidine)
(Sigma-Aldrich) (hereafter named HAT medium), at 37 ºC and 5 % CO2. A control was performed
with the parental CHO-K1 cells using the same conditions. Clones were validated by their inability
to grow in the HAT medium in contrast with the normal growth of the control cells.
2.2.3. TRANSFECTION
The validated HPRT-deficient clones and the HPRT-deficient CHO-K1 TG-2 cells were seeded
into petri dishes at 1.3x105 cells/mL in Growth medium, and incubated overnight at 37 ºC and 5
% CO2 for transfection by calcium phosphate co-precipitation.
The CAB051 gene/plasmid was co-transfected with each linearized HPRT minigene. For
this, 1 mL of 1x hydroxyethyl piperazineethanesulfonic acid (HEPES)-buffered salt solution (HBS,
137 mM sodium chloride (NaCl), 4.96 mM potassium chloride (KCl), 417 mM sodium phosphate
dibasic dihydrate (Na2HPO4.2H2O), 5.55 mM D-glucose, and 17.6 mM HEPES, pH 7.05) (Sigma-
Aldrich) was added to a deoxyribonucleic acid (DNA) mixture of 20 µg HPRT minigene and 20 µg
CAB051 plasmid (less than 100 µL of DNA). Then, 62 µL of 2 M calcium chloride (CaCl2, Sigma-
Aldrich) was added dropwise to the mixture and left for 45 min at room temperature until a
precipitate was formed. The precipitate was slowly dropped over the cells in the petri dishes after
removal of the culture medium. After incubation at room temperature for 20 min with frequent
spreading of the precipitate by tilting, Growth medium was added and the cells were incubated
overnight at 37 ºC and 5 % CO2.
CHAPTER 2 │ TRANSFECTION WITH THE OSCARTM EXPRESSION SYSTEM
107
Cells were then seeded into 24-well plates (at least two for each transfection) at a density of
10,000, 20,000, and 40,000 cells/well for pDWM131, and at 40,000 cells/well for pDWM129
and -128, in Growth medium, to provide an average of one HAT-resistant colony per well. After
24 h the medium was replaced by HAT medium to allow for the selective growth of the cells
successfully transfected, and the cells were incubated for 3-4 weeks with medium changes after
the first 2-3 days and every 10-14 days thereafter.
2.2.4. SELECTION OF THE HIGHEST MONOCLONAL ANTIBODY PRODUCERS
The individual well colonies obtained after transfection were assessed for expansion of the
highest mAb-producers using two methodologies: (i) measurement of absorbance, and (ii)
determination of productivity. For the first methodology, samples of the supernatant were taken
from each well containing a colony, and the absorbance read at 450 nm (Biotek Synergy HT
multi-mode microplate reader, Izasa, Portugal). In this case, a direct relationship between
absorbance values and mAb concentration is assumed. For the methodology based on
productivity, supernatant samples were taken from each well containing a colony to determine
mAb concentration by enzyme-linked immunosorbent assay (ELISA). Cell concentration was also
assessed by enzymatic release of the cells with trypsin and cell counting in a haemocytometer
using the trypan blue (Sigma-Aldrich) exclusion method, which allowed the subsequent
determination of mAb productivity, as described in section 2.2.5.
Clones selected were expanded into 25 cm2 culture flasks under selective conditions (HAT
medium). The stability of production of these clones was assessed periodically for several weeks,
as well as after two years (with the culture subjected to periods of both continuous splitting and
cryopreservation), following the methodology of productivity assessment described above.
2.2.5. ANTIBODY QUANTIFICATION BY ENZYME-LINKED IMMUNOSORBENT ASSAY
Samples were analyzed for mAb productivity by ELISA following an optimized procedure
described in the confidential and proprietary standard operating procedure (SOP) 2008-01 ANL
from Biotecnol SA. Briefly, 96 well plates (CoStar, United States of America) were coated with a
CHAPTER 2 │ TRANSFECTION WITH THE OSCARTM EXPRESSION SYSTEM
108
capture antibody (Sigma-Aldrich) overnight. After a 45 min blocking at room temperature with 1 %
bovine serum albumin in phosphate buffered saline (BSA-PBS, 11.5 µM BSA in 137mM NaCl,
2.68 mM KCl, 1.76 mM potassium dihydrogen phosphate (KH2PO4), and 12.72 mM sodium
phosphate dibasic (Na2HPO4), pH 7.4) (Sigma-Aldrich), sample dilutions in 0.2 % BSA-PBS (3.03
mM BSA in PBS), a standard of known concentration and a quality control (Biotecnol SA), were
added to the plates and incubated for 2 h at 37 ºC. The detection antibody was added and the
plates incubated for additional 2 h at room temperature. A 3,3’,5,5’-Tetramethylbenzidine (TMB,
Sigma-Aldrich) substrate solution was added and allowed to react for 10 min at room
temperature. After stopping the reaction with Phosphoric acid 75 % (Phosphoric acid 85 % in
water) (Frilabo), the absorbance was read at 450 nm and mAb production determined. For this,
the calibration curve of the ELISA assay was determined using the R software (version 2.6.2, The
R Foundation for Statistical Computing) to obtain the values of the four parameter logistic of
Equation 2.1.
Abs���=d+a-d
1+ �C�c �b
EQUATION 2.1. Four parameter logistic equation used as the calibration curve for the determination of monoclonal
antibody concentration from the absorbance values obtained by enzyme-linked immunosorbent assay. Abs450 -
absorbance read at 450 nm; a - estimated response at zero concentration; b - slope factor; c - mid-range
concentration; d - estimated response at infinite concentration; and CmAb - mAb concentration in µg/mL.
MAb concentration (production, CmAb) of the samples was then determined using the
functional inverse of Equation 2.1, as represented in Equation 2.2.
C� = �� ����������� − 1�
�� × c
EQUATION 2.2. Determination of monoclonal antibody concentration (CmAb) in µg/mL. a - estimated response at zero
concentration; b - slope factor; c - mid-range concentration; d - estimated response at infinite concentration; and
Abs450 - absorbance read at 450 nm.
Additionally, the specific mAb production (productivity, qmAb) of each sample was calculated
according to Equation 2.3, using the cell concentration (Ccell) determined by Equation 2.4.
CHAPTER 2 │ TRANSFECTION WITH THE OSCARTM EXPRESSION SYSTEM
109
�� = �� � Ccell⁄t
× 10#
EQUATION 2.3. Determination of the monoclonal antibody productivity (qmAb) in pg/cell/day. CmAb - mAb concentration in
µg/mL; Ccell - cell concentration in cells/mL; and t - time of production in days.
C%&'' = ()*++� × 10� × F
EQUATION 2.4. Determination of cell concentration (Ccell) in cells/mL. Ncell - total number of cells counted in the
haemocytometer; and F - dilution factor of the sample.
Data of clone productivity and stability of production were statistically analyzed using the
Statistical Package for the Social Sciences (SPSS) software (International Business Machines,
IBM, USA), using one-way analysis of variance (ANOVA) with Bonferroni test, with a confidence
level of 95 %.
2.2.6. CELL GROWTH CHARACTERISTICS
The growth characteristics, specifically the cell doubling time (tD), of the original CHO-K1
cells and of two transfected clones (selected clones 18 and 32) were evaluated and compared.
For this, cells were seeded at 1x105 cells/mL into 6-well plates and allowed to grow at 37 ºC and
5 % CO2, for 2, 4, 6, 10, 24 and 48 h before direct cell counting with an haemocytometer and
trypan blue staining. The tD values were determined according to Equation 2.5.
t. = /t0 − t12 × '34/02'34/�5 ��⁄ 2
EQUATION 2.5. Determination of the cell doubling time (tD) in hours, assuming a constant growth rate (exponential
phase of cell growth). C1 and C2 - cell concentrations, in cells/mL, at times t1 and t2, in hours, respectively.
2.2.7. ANALYSIS OF THE GLYCOSYLATION PROFILE
The glycosylation profile of the mAb produced by Clone 18 and Clone 32 was assessed as
described below. To note that all water used in the following procedures was type 1 ultra-pure,
CHAPTER 2 │ TRANSFECTION WITH THE OSCARTM EXPRESSION SYSTEM
110
resistivity of 18 MΩ.cm, particle-free (> 0.22 µm), and total organic content of less than ten parts
per billion.
IGG PURIFICATION
Prior to IgG purification, samples were concentrated to volumes of 200 µL using 15 mL spin
concentrators of 5 KDa molecular weight cutoff (Agilent Technologies, Ireland). Then, the IgG
from the concentrated samples was purified with Protein A spin plates (Thermo Scientific,
Ireland) according to manufacturer instructions, with slight modifications. Briefly, the wells of a
spin plate were equilibrated with two washes of 200 µL of 1x PBS (pH 7.2, Merck, UK). Samples
were diluted two-fold in 1x PBS and added (200 µL) to the plate for a period of incubation of 30
min with moderate agitation. The resin was washed three times with 500 µL of PBS, and the
purified IgG eluted three times with 300 µL of 0.5 M acetic acid (pH 2.5, AnalaR, UK) and
neutralized with 20 µL of 1 M ammonium bicarbonate (pH 7-8.5, Sigma-Aldrich). The neutralized
elutions were dried overnight in a vacuum centrifuge.
IN GEL BLOCK IMMOBILIZATION
The dried samples were reduced with a solution containing 13.88 mM sodium dodecyl
sulfate (SDS, BDH, UK), 12.5 mM Tris (pH 6.6, AnalaR) and 0.05 M dithiothreitol (DTT, Sigma-
Aldrich) for 15 min at 65 ºC; and alkylated with 100 mM iodoacetamide (IAA, Sigma-Aldrich) for
30 min in the dark. The gel blocks were formed by adding a mixture of 22.5 µL of Protogel (30 %,
National Diagnostics, UK), 11.25 µL of 1.5 mM Tris, 1 µL of 35 mM SDS, and 1 µL of 34.7 mM
ammonium peroxisulphate (APS, AnalaR), and finally adding 1 µL of tetramethylethylenediamine
(TEMED, Sigma-Aldrich) to the samples, letting set for 15 min.
N-GLYCAN RELEASE AND FLUORESCENT LABELING
Each gel block was cut into small pieces (≈ 2 mm2), washed alternately with acetonitrile
(Sigma-Aldrich) and 20 mM sodium bicarbonate (pH 7, Merck), vortexed and mixed for 10 min
after each wash, and dried in a vacuum centrifuge.
CHAPTER 2 │ TRANSFECTION WITH THE OSCARTM EXPRESSION SYSTEM
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For the release of N-linked glycans, the dried gel pieces were incubated for 15 min in a mix
of 2 µL of Peptide N-glycosidase F (PNGase F, Prozyme, USA) and 48 µL of 20 mM sodium
bicarbonate (pH 7), and a further 12-16 h at 37 ºC after adding extra 50 µL of 20 mM sodium
bicarbonate. The supernatant was then removed (13,000 rpm, 5 min), and the samples
subjected to a series of washes with water and acetonitrile, with a 15 min sonication for each
wash. The supernatants obtained were collected and dried in a vacuum centrifuge. The dried
samples were redissolved in 20 µL of formic acid (1 %, Sigma-Aldrich), incubated for 40 min at
room temperature and dried in a vacuum centrifuge.
The released N-glycans were labeled for fluorescent detection using the LudgerTagTM 2-
aminobenzamide (2-AB) Glycan Labeling Kit (Ludger, UK), according to manufacturer
instructions. Briefly, 5 µL of the 2-AB labeling mix were added to each dried glycan sample,
incubated 30 min at 65 ºC, vortexed, spun down, and incubated for further 90 min.
Excess 2-AB label from labeled N-glycans was cleaned-up using Normal Phase 1 PhyNexus
tips (PhyNexus, USA). Briefly, samples were diluted in 95 µL of water and 900 µL of acetonitrile.
The PhyNexus tips were prepared by washing with ten 500 µL uptakes of 95 % acetonitrile (v/v in
water), ten 500 µL uptakes of 20 % acetonitrile (v/v in water), and another ten 500 µL uptakes of
95 % acetonitrile. Samples were loaded into the PhyNexus tips through ten 1 mL in-out cycles,
followed by washing of the tips with ten 1 mL uptakes of 95 % acetonitrile. The glycans were then
eluted with five uptakes of 200 µL of 20 % acetonitrile, and the elutions collected and dried in a
vacuum centrifuge.
NORMAL PHASE-HIGH PERFORMANCE LIQUID CHROMATOGRAPHY
For normal phase-high performance liquid chromatography (NP-HPLC), each dried sample
was ressuspended in 20 µL of water and 80 µL of acetonitrile. NP-HPLC was performed using a
TSKgel Amide-80 3 µm (150 x 4.6 mm) column (Tosoh Bioscience, UK) for 60 min runs, at 30
ºC, using 50 mM ammonium formate (Sigma-Aldrich) as Solvent A and acetonitrile as Solvent B.
The runs were performed on a 2695 Alliance separations module (Waters, Ireland) with a
2475 multi-wavelength fluorescence detector (Waters), with excitation and emission wavelengths
at 330 and 420 nm, respectively. Conditions of the 60 min method were a linear gradient of 35
to 47 % Solvent A over 48 min at a flow rate of 0.48 mL/min, followed by a minute at 47 to 100
CHAPTER 2 │ TRANSFECTION WITH THE OSCARTM EXPRESSION SYSTEM
112
% Solvent A and 4 min at 100 % Solvent A, returning to 35 % solvent A over 1 min and then
finishing with 35 % solvent A for 6 min.
The systems were calibrated by running an external standard of 2-AB dextran ladder (2-AB
labeled glucose homopolymer) alongside the sample runs.
PROCESSING OF SAMPLES
A fifth-order polynomial distribution curve was fitted to the dextran ladder and used to
allocate glucose unit (GU) values from retention times, using Empower GPC software (Waters).
Tentative assignment of structures to the peaks was then made by matching the GU values
obtained with those available in GlycoBase (http://glycobase.nibrt.ie/), and using the known
immunoglobulin G1 (IgG1) profile as a guide. A confirmation of the structures through
exoglycosidase digestion was not possible due to a limited amount of sample. Nevertheless, for
the purposes of comparison of this study, such final allocation was not essential.
CHAPTER 2 │ TRANSFECTION WITH THE OSCARTM EXPRESSION SYSTEM
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2.3. RESULTS AND DISCUSSION
2.3.1. ANALYSIS OF THE TWO MAIN PHASES OF THE OSCARTM TECHNOLOGY
In the first phase of the OSCARTM technology, consisting of the selection of HPRT-deficient
clones, two methodologies for clone isolation were assessed, specifically cloning rings and
cloning disks. Their comparison in terms of simplicity, speed, and efficiency of cell recovery is
shown in Table 2.2.
TABLE 2.2. Comparison of cloning rings and cloning disks for the isolation of HPRT-deficient clones obtained during
the first phase of the OSCARTM expression system, considering simplicity, speed and cell recovery
MONOSACCHARIDE CLONING RINGS CLONING DISKS
Simplicity - +
Speed - +
Cell recovery + -
In terms of procedure, cloning disks had the simplest and fastest procedure. However,
considering efficiency, cloning rings were clearly superior by allowing the recovery of a higher
number of cells. Therefore, cloning rings proved to be the best choice when maximum cell
recovery is desired and/or crucial, such as in the present work where the amount of cells
isolated was very low.
For the second phase of the OSCARTM expression system – the transfection itself – three
HPRT minigenes with different degrees of expression disability are provided, to determine the
best choice for each cell line and/or product. These minigenes were evaluated for the co-
transfection of the CHO-K1 cells with the CAB051 plasmid, with the results obtained shown in
Table 2.3.
CHAPTER 2 │ TRANSFECTION WITH THE OSCARTM EXPRESSION SYSTEM
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TABLE 2.3. Comparison of the three HPRT minigenes with varying degrees of expression disability for the co-
transfection of the CAB051 plasmid into the CHO-K1 cells using the OSCARTM expression system
HPRT GENE/MINIGENE LEVEL OF EXPRESSION DISABILITY TRANSFECTION SUCCESS
pDWM131 Least disabled +
pDWM129 -
pDWM128 Most disabled -
The successful transfection of the CHO-K1 cells for mAb production was only possible using
the most disabled minigene - pDWM128, with the others not providing any cell colonies. This was
an unexpected result, since the most disabled minigene is the one that requires extra
amplification, which may not allow the survival of cells with more fastidious requirements for
HPRT expression; so the most obvious outcome would be the inverse of what was observed in
this study. These results highlight the importance of testing all minigenes, since its success
seems to be dependent on the type of cells used.
Indeed, the possibility of selection from different minigenes has the potential advantage of
making the OSCARTM expression system adaptable to the requirements of different cell lines, and
allows tailoring of the system to the desired levels of expression (the most disabled minigene
usually provides the highest yields). However, testing different minigenes requires additional lab
work and increases costs. These problems may be attenuated over time with further studies that
will result in the build-up of information that may allow the knowledge beforehand of the
applicability of each minigene to different cell lines and clones, products and/or plasmids. In this
sense, the construction of a database to collect all the information would be of great value.
2.3.2. LEVEL AND STABILITY OF CLONE PRODUCTIVITY
After transfection, the clones obtained were assessed for the selection of the most
productive. This initial selection is typically based on the absorbance values of the clone
supernatants, a fast process but not the most accurate approach. A more precise, although time-
consuming and labor-intensive, alternative consists on determining productivity by measuring
both cell and antibody concentrations. Both methodologies were used and compared in the
present work, as shown in Figure 2.1.
CHAPTER 2 │ TRANSFECTION WITH THE OSCARTM EXPRESSION SYSTEM
115
FIG
UR
E 2
.1. Initial clone selection after transfection based on two approaches: (a) absorvance values of supernatant read at 450 nm (ABS 4
50), and (b) productivity (q m
Ab). The
interrupted line denotes the cutoff limit established for clone selection: (a) ABS 450 of 1, and (b) q
mAb of 10 pg/cell/day; and the dark color highlights the selected clones.
0.0
0.5
1.0
1.5
2.0
2.5
3.0
0
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4
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82
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86
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90
92
94
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102
104
106
108
110
112
ABS450
Clo
ne
0
10
20
30
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50
60
0
2
4
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qmAb(pg/cell/day)
Clo
ne
(b)
(a)
CHAPTER 2 │ TRANSFECTION WITH THE OSCARTM EXPRESSION SYSTEM
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Differences between the two methodologies are clearly observed, primarily in the higher
number of clones that seem to be high-producers when the selection is based in absorbance.
However, more noteworthy are the divergences in which clones are selected with each method.
Indeed, setting the selection criteria on absorbance above 1 (clones 27, 30, 34, 49, 65, 73, 75,
and 93) and productivity above 10 pg/cell/day (clones 6, 18, 27, 32, and 73), there are only two
clones in common for both approaches (clones 27 and 73). Additionally, in cases such as clones
6 and 93, the results obtained with each methodology are opposite. These results reveal a strong
impact of the methodology on the outcome of the process of selection. Therefore, although the
determination of productivity for each clone is less straight-forward and more time-consuming
than the assessment of absorbance, the fact that it contemplates both cell and mAb
concentrations makes it more accurate and therefore the favored method to base clone selection.
Considering these findings, the clones with productivities above 10 pg/cell/day (clones 6,
18, 27, 32, and 73) were selected to further assess the stability of production. Additionally, a
clone with lower productivities (clone 95) was also selected to enable the comparison between
high- and low-producing clones. The stability of production was evaluated by periodic monitoring
of clone productivity during 6 weeks, with additional measurements after two years. The first
measurement was performed after 3 weeks in culture (splitting three times a week), and the
productivity levels obtained are shown in Figure 2.2.
FIGURE 2.2. Values of productivity (qmAb) of the selected clones obtained initially and after three weeks in culture.
0
10
20
30
40
50
6 18 27 32 73 95
qm
Ab
(pg
/ce
ll/d
ay)
Clone
Initial
3 weeks
CHAPTER 2 │ TRANSFECTION WITH THE OSCARTM EXPRESSION SYSTEM
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The evolution of productivity with time was evaluated for additional 3 weeks, as shown in
Figure 2.3. It should be noted that since clones 6 and 73 have shown very low levels of
production already at 3 weeks, they were not considered in this evaluation.
FIGURE 2.3. Evolution of the productivity (qmAb) levels of clones 18, 27, 32, and 95 during 6 weeks in culture.
In the first evaluation of the stability of production (Figure 2.2), a substantial decrease of
production, between 70 and 99 %, was noticeable for all clones. Further assessment (Figure 2.3)
shows that, although not so abruptly as before, the levels of production continue to decrease over
time and, after 6 weeks in culture, become significantly (p < 0.05) inferior to those of the first
measurements.
Comparing the clones, an attenuation of the differences in the productivity levels is observed
over time (Figure 2.3). Indeed, although clone 18 was the highest-producer (p < 0.05) in the first
weeks, at the end of the period of evaluation all clones showed similar levels of productivity (p >
0.05).
To further assess production stability, clones 18 and 32 were cultured for two years, after
which additional measurements of productivity were performed. The selection of these clones
was based on the globally better (although not significantly) levels of productivity demonstrated in
the first six weeks in culture. The results obtained after two years are shown in Table 2.4.
0.00
0.25
0.50
0.75
1.00
1.25
1.50
1.75
2.00
2.25
18 27 32 95
qm
Ab
(pg
/ce
ll/d
ay)
Clone
3 weeks
4 weeks
5 weeks
6 weeks
CHAPTER 2 │ TRANSFECTION WITH THE OSCARTM EXPRESSION SYSTEM
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TABLE 2.4. Values of productivity (qmAb) obtained for Clone 18 and Clone 32 after two years in culture
CELLS qmAb (pg/cell/day)
Clone 18 0.21
Clone 32 0.31
The levels obtained were similar (p > 0.05) to those of the previous period of analysis (6
weeks) indicating a tendency to stabilize production. Nevertheless, there is a considerable loss of
the ability of the clones to produce mAb after two years in culture in comparison with the initial
measurements. Therefore, in opposition to what has been observed in studies with other cell
lines/proteins (Melton et al. 2001), the OSCARTM system does not provide stability of high yield
production when applied to the CHO-K1 cells producing the CAB051 mAb.
It should be noted that the clones with better levels of production and stability (clones 18 and
32) would not have been selected if the absorbance method of clone selection had been used,
highlighting the importance of the methodology of clone selection for the outcome of the process.
2.3.3. EFFECT OF TRANSFECTION ON CELL GROWTH CHARACTERISTICS
The growth characteristics of the CHO-K1 cells before and after transfection with OSCARTM
were evaluated. For this, the doubling times of the original CHO-K1 cells and of the mAb-
producing clones 18 and 32 were determined after two years in culture, as shown in Table 2.5.
TABLE 2.5. Doubling times (tD) of the original CHO-K1 cells and of Clones 18 and 32, after two years in culture
CELLS tD (h)
CHO-K1 20.97 ± 3.76
Clone 18 21.86 ± 4.30
Clone 32 22.69 ± 0.98
The OSCARTM expression system is said not to compromise the growth rate of cells, even if
generating a high gene copy number (Melton et al. 2001). This is a common problem after
transfection, since the ability to produce foreign proteins can be a metabolic burden to the cells and
therefore affect their growth (Gu et al. 1992; Gu, Todd, and Kompala 1995). However, in this work,
the presence of the gene does not appear to significantly affect the doubling times of the
CHAPTER 2 │ TRANSFECTION WITH THE OSCARTM EXPRESSION SYSTEM
119
transfected clones (Table 2.5). This may be an advantage of the OSCARTM system over more
traditional methodologies, but may also be caused by the clones not being expressing at particularly
high levels and therefore being capable to maintain growth rates similar to those of the parent cells.
2.3.4. ANALYSIS OF THE MONOCLONAL ANTIBODY GLYCOSYLATION PROFILE
The different mAb-producing clones obtained after transfection with the OSCARTM expression
system have shown different capacities of production. Likewise, they may also produce mAbs
with divergent patterns of glycosylation, which has potential effects on product quality. To
evaluate this possibility, the glycan profile of the mAb produced by clones 18 and 32 was
assessed. The peaks obtained and the corresponding GU values, tentative structure assignment,
and relative area are shown in Table 2.6.
TABLE 2.6. Data of mean glucose unit (GU) value, tentative structure assignment, and relative area (%) of the peaks
obtained by high performance liquid chromatography for the monoclonal antibody produced by Clones 18 and 32
PEAK MEAN GU 1 TENTATIVE ASSIGNMENT 2 % AREA
CLONE 18 CLONE 32
1 4.91 ± 0.02 A1 1.86 2.09
2 5.34 ± 0.01 FA1 / A2 2.05 2.01
3 5.82 ± 0.02 FA2 40.59 40.99
4 6.18 ± 0.01 M5 1.75 1.50
5 6.64 ± 0.02 FA2G1[6] 23.28 23.52
6 6.75 ± 0.03 FA2G1[3] 7.56 9.11
7 7.16 ± 0.03 A2G2 / M6 1.55 1.65
8 7.61 ± 0.02 FA2G2 8.19 8.40
9 7.98 ± 0.01 FA2G1S1 3.01 2.73
10 8.46 ± 0.02 A2G2S1 2.56 0.91
11 8.89 ± 0.01 FA2G2S(6)1 - 0.98
12 9.59 ± 0.09 A2G2S2 2.34 1.99
13 9.99 ± 0.17 FA2G2S2 1.46 0.95
14 10.45 ± 0.02 FA3G3S2[6] 1.24 1.14
15 10.67 ± 0.01 FA3G3S2[3,6] 0.95 0.92
Main structures (FA2+FA2G1+FA2G2) 79.62 82.02
Other structures 20.39 17.98
1 Average of the GU value of all samples containing the peak.
2 A – N-Acetylglucosamine, F – fucose, G – galactose, M – mannose, and S – sialic acid.
CHAPTER 2 │ TRANSFECTION WITH THE OSCARTM EXPRESSION SYSTEM
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As it can be observed, Clones 18 and 32 produce mAbs with similar glycan profiles, with
one additional peak present at small percentage for Clone 32 (peak 11). Both profiles are in
accordance with the known human IgG1 glycan pattern (Serrato et al. 2004; Takahashi and
Tomiya 1992; Masuda et al. 2000; Raju et al. 2000; Saba et al. 2002), having the three typical
main structures present in the usual order of prevalence: core fucosylated agalactosylated (peak
3, FA2), core fucosylated monogalactosylated (peaks 5 and 6, two isoforms of FA2G1), and core
fucosylated digalactosylated (peak 8, FA2G2) glycans (Routier et al. 1997; Serrato et al. 2007;
Jenkins, Parekh, and James 1996; Jefferis and Lund 1997). Furthermore, the relation between
the two FA2G1 isoforms (peaks 5 and 6) matches the ratio of 3:1 usually displayed in
endogenous human IgG1 (Flynn et al. 2010; Jefferis et al. 1990).
The results of the glycan analysis indicate that the clones selected after transfection with the
OSCARTM system do not differ in the quality of the mAb produced, although having divergent
capacities of production.
CHAPTER 2 │ TRANSFECTION WITH THE OSCARTM EXPRESSION SYSTEM
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2.4. CONCLUSION
The OSCARTM expression system appears as a feasible alternative to the more traditional
methods. It is potentially faster for cell line development, by combining selection and
amplification in one step, and provides cells with higher and more stable expression yields,
without significant impact on cell growth characteristics. In this study, its applicability for the
expression of a mAb in CHO-K1 cells was tested. Globally, the OSCARTM technology proved to be
reasonably fast and simple, with mAb-producing cells obtained after 6-8 weeks. However, the
selection of the minigene proved critical, with only the most disabled minigene (pDWM128)
working for the CHO-K1 cells assessed in this work. Furthermore, it was found that the growth
characteristics of the cells are not hindered by the process. However, the relatively high
expression level of 10 pg/cell/day initially obtained, rapid and sharply decayed in the first few
weeks of culture to less than 1 pg/cell/day, and remained low but stable when evaluated over an
extended period of two years.
This study also underlines the strong impact of the methodology of clone selection on the
outcome of the process, advising for the use of productivity analysis instead of the simple and
common comparison of the absorbance values of culture supernatants.
Finally, the glycosylation analysis of the mAb produced by the transfected cells indicates a
similar quality of the product among the clones obtained after transfection with the OSCARTM
expression system.
CHAPTER 2 │ TRANSFECTION WITH THE OSCARTM EXPRESSION SYSTEM
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Biotechnology 22 (11):1393-1398.
hapter hapter hapter hapter 3333
Impact of the process of cell adaptation to
serum-free conditions on product quality
CC
THE PRESENT CHAPTER WAS ADAPTED FROM THE FOLLOWING RESEARCH PAPERS
ANA RITA COSTA, Joanne Withers, Maria Elisa Rodrigues, Niaobh McLaughlin,
Mariana Henriques, Rosário Oliveira, Pauline Rudd, Joana Azeredo (2012). The
impact of cell adaptation to serum-free conditions on the glycosylation profile of a
monoclonal antibody produced by CHO cells. Submitted to New Biotechnology.
Maria Elisa Rodrigues, ANA RITA COSTA, Mariana Henriques, Philip Cunnah, David
Melton, Joana Azeredo, Rosário Oliveira (2012). Advances and drawbacks of the
adaptation to serum-free culture of CHO-K1 cells for monoclonal antibody
production. Submitted to Applied Biochemistry and Biotechnology.
127
lycosylation is one of the most critical parameters affecting the biological activity of
therapeutic proteins, and should be closely monitored and controlled to guarantee a consistent
and high-quality product in biopharmaceutical processes. This requires understanding the factors
influencing glycosylation during production. Among these, the adaptation of producer cells,
typically mammalian, to culture in the serum-free conditions required for regulatory and safety
reasons is one of the most challenging steps, with potential effects on product quality.
Considering this, the work described in this chapter evaluated a process of gradual adaptation of
monoclonal antibody (mAb)-producing Chinese hamster ovary (CHO-K1) cells to serum-free
culture using different combinations of medium supplements, and assessed its impact on the
glycosylation pattern of the product.
The selection of an adequate combination of supplements proved to be critical for the
success of adaptation. Furthermore, analysis by high-performance liquid chromatography
revealed important changes in the glycosylation patterns of the mAb for all the steps of serum
reduction, which could be grouped into intermediate (2.5 % to 0.15 % serum) and final (0.075 %
and 0 % serum) stages. The intermediate levels of serum demonstrated the advantageous
increase of galactosylation and decrease of fucosylation, but also an undesirable increase in
sialylation. The inverse was obtained at the final stages of adaptation. These divergences could
be related to the reduction of serum supplementation, to variations observed in the levels of cell
density and viability achieved at these stages, as well as to the fact that cells naturally shifted
their mode of growth from adherent to suspended. The divergent glycan profiles obtained in this
study demonstrate a strong influence of the process of adaptation on mAb glycosylation,
suggesting that control and monitoring of product quality should be implemented at the early
stages of process development.
Keywords: Monoclonal antibody; Chinese hamster ovary cells; Serum-free; Adaptation;
Glycosylation
GG
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3.1. INTRODUCTION
Immunoglobulin G (IgG) monoclonal antibodies (mAbs) are currently one of the most
successful drug classes in the biopharmaceutical industry (Primack, Flynn, and Pan 2011; Reichert
et al. 2005; Carter 2006; Reichert and Valge-Archer 2007). For the production of these therapeutic
mAbs, mammalian cells are the preferred system due to their innate ability to perform post-
translational processing that closely resembles that found in humans (Rodrigues et al. 2009;
LeFloch et al. 2006; Hossler, Khattak, and Li 2009; Primack, Flynn, and Pan 2011). Of the post-
translational modifications, glycosylation is one of the most critical for protein quality (Hossler,
Khattak, and Li 2009). In particular, the glycosylation of the Fc region of the IgG plays essential
roles in structural integrity, effector functions, immunogenicity, plasmatic clearance, solubility,
and resistance toward proteases (Hossler, Khattak, and Li 2009; Lowe and Marth 2003; Mimura
et al. 2000; Davies et al. 2001; Krapp et al. 2003; Magdelaine-Beuzelin et al. 2007).
These functions and, consequently, the therapeutic efficacy of the mAb are also dependent
on the specific glycoforms present (Elliott et al. 2003; Primack, Flynn, and Pan 2011), which are
highly variably due to the different types of monosaccharides available and their combinational
pairing (Hashimoto et al. 2006; Fernandes 2005). For example, terminal galactose, core fucose,
sialic acid, bisecting N-acetylglucosamine (GlcNAc), and high mannose species are known as
important glycosylation elements that affect the effector functions of the antibody (Tsuchiya et al.
1989; Shields et al. 2002; Goetze et al. 2012; Kanda et al. 2007). Indeed, higher levels of
galactosylation (Abès and Teillaud 2010; Serrato et al. 2007; Jefferis and Lund 1997;
Hodoniczky, Zheng, and James 2005) and bisecting GlcNAc (Ferrara et al. 2006; Fernandes
2005), as well as reduced core fucosylation (Sibéril et al. 2006; Shields et al. 2002; Shinkawa et
al. 2003) and sialylation (Scallon et al. 2007; Kaneko, Nimmerjahn, and Ravetch 2006; Anthony
and Ravetch 2010; Anthony et al. 2008), have been shown to enhance the clinical efficacy of
mAbs that exert their therapeutic effect by antibody-dependent cellular cytotoxicity (ADCC) or
complement dependent cytotoxicity (CDC) mediated killing. This is particularly relevant for core
fucosylation, whose absence can improve ADCC activity by up to 100-fold (Shields et al. 2002).
Additionally, the presence of high mannose structures has been associated with reduced ADCC
and CDC (Kanda et al. 2007), and with higher clearance rates (Abès and Teillaud 2010).
The glycan profile (glycoforms) of glycosylated therapeutics can be affected by several factors
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that include: the host cell expression system (Jenkins, Parekh, and James 1996; Sethuraman and
Stadheim 2006; Raju 2003); environmental factors such as dissolved oxygen (Chotigeat et al.
1994; Serrato et al. 2004), pH (Müthing et al. 2003; Yoon et al. 2005), and temperature (Yoon,
Kim, and Lee 2003; Trummer et al. 2006); as well as the cell culture media and mode of culture
(e.g. batch, fed-batch, and continuous) (Gu et al. 1997; Patel et al. 1992; Wong et al. 2005; Kunkel
et al. 2000; Jenkins, Parekh, and James 1996; Andersen and Goochee 1994).
The cell culture media is typically a mixture of 50-100 chemically defined components and a
handful of undefined components that are supplemented (Hossler, Khattak, and Li 2009). Of
these, serum is the most common for its positive effects on mammalian cell growth. However, its
ill-defined composition and animal origin raises several concerns, including lot-to-lot variability,
complex purification of the product, risk of transmission of diseases to humans, and high costs
(Rodrigues et al. 2009; Brunner et al. 2010; LeFloch et al. 2006; Zhang and Robinson 2005; Liu
and Chang 2006). Therefore, due to regulatory and safety issues, chemically-defined culture
conditions, without supplementation of serum or any other animal-derived components, are
considered fundamental to the manufacture of highly purified products of consistent quality
(Serrato et al. 2007; Ozturk and Hu 2006; Geigert 2004). Consequently, mammalian cells that
typically grow in serum-containing media need to be adapted to serum-free conditions, a process
that usually consists of progressive reductions of serum concentration in the medium to consent
the self-adjustment of cells to the new environment and increase the possibility of a successful
adaptation (Ozturk and Palsson 1991; Doyle and Griffiths 1998; Kovář 1989; Griffiths 1987).
Additional supplementation of the culture medium with commercial serum substitutes, defined
proteins, or small molecules such as amino acids and trace elements can also be attempted to
support adaptation (Doyle and Griffiths 1998). This process of adaptation is very time-consuming
and can affect cell growth, product yield, and product quality (e.g. glycosylation) (Crowell et al.
2007; Doyle and Griffiths 1998; Ozturk et al. 2003; Griffiths 1987). Therefore, to assure a
consistent quality of glycosylated therapeutics that meet the requirements of the regulatory
agencies, it is essential to understand how these processes at early phases of development affect
glycosylation (Raju 2003). In the present work, mAb-producing CHO-K1 cells were adapted to
culture under serum-free conditions using a gradual methodology of adaptation that involved the
additional test of different combinations of supplements. The effect of each step of the process
on mAb glycosylation was assessed by high performance liquid chromatography, and the
potential effects on biological activity were discussed.
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3.2. MATERIALS AND METHODS
3.2.1. CELL LINE AND CULTURE CONDITIONS
MAb-producing Chinese hamster ovary (CHO) cells, previously obtained (Costa et al. 2012)
through the transfection of a CHO-K1 cell line (CCL-61, American Type Culture Collection, Spain)
for the production of a recombinant human mAb (CAB051, Biotecnol SA, Portugal) were used in
this work. These cells were grown in Dulbecco’s Modified Eagle’s Medium (DMEM, Sigma-Aldrich,
United Kingdom) supplemented with 10 % fetal bovine serum (FBS, Sigma-Aldrich) and 1x
hypoxanthine aminopterin thymidine (HAT, Sigma-Aldrich) at 37 ºC and 5 % carbon dioxide (CO2).
3.2.2. CELL ADAPTATION TO SERUM-FREE CONDITIONS
The mAb-producing CHO-K1 cells were gradually adapted from growth in serum-containing
DMEM to serum-free conditions. For this, cells were seeded into 24-well plates or 25 cm2 culture
flasks (Frilabo, Portugal) at a viable density of 2x105 cells/mL or 4x105 cells/mL, respectively, in
DMEM with 10 % FBS, 1x HAT and additional supplementation with one of five combinations of
insulin and trace elements (Sigma-Aldrich), whose composition is described in Table 3.1.
The serum percentage supplemented in the medium was then reduced stepwise from the
initial 10 % to the stages of 5, 2.5, 1.25, 0.625, 0.31, 0.15, 0.075, and 0 %. At the stage of
0.625 % serum, the basal culture medium was gradually switched from DMEM to the chemically-
defined and serum-free EXCELL CHO DHFR- medium (Sigma-Aldrich). The remaining steps of
adaptation were performed in EXCELL. A control of mAb-producing CHO-K1 cells subjected to the
same process of adaptation without the support of a combination of supplements was included in
the study.
During this process of adaptation, cell concentration and viability were assessed using a
haemocytometer and the trypan blue (Sigma-Aldrich) exclusion method.
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TABLE 3.1. Composition of the five combinations of supplements assessed for the adaptation of monoclonal
antibody-producing CHO-K1 cells to growth in serum-free conditions
SUPPLEMENT FUNCTION COMBINATION
1 2 3 4 5
Recombinant human insulin (rhInsulin) Growth Factor X X X X X
Copper sulfate (CuSO4) Proliferation X X X X
Zinc sulfate (ZnSO4) Proliferation X X X X
Sodium selenite (Na2SeO3) Antioxidant X X X X
Ammonium iron citrate (FeC6H5O7.NH4OH) Proliferation X X
Ferrous ammonium sulfate (NH4Fe(SO4)2) Proliferation X X
Ammonium metavanadate (NH4VO3) Unknown X X X
Nickel chloride (NiCl2) Unknown X X X
Stannous chloride (SnCl2) Unknown X X X
3.2.3. ANALYSIS OF THE MONOCLONAL ANTIBODY GLYCOSYLATION PROFILE
During the adaptation to serum-free conditions several samples were taken to assess the
glycosylation profile of the mAb produced. A description of these samples including the stage of
serum, media and combination of supplements, and sampling day, is provided in Table 3.2.
Combinations C1 and C4 were not included in this analysis due to an early exclusion from the
study (see section 3.3).
To note that in the following procedures all water used was of type 1 ultra-pure, resistivity of
18 MΩ.cm, particle-free (> 0.22 µm), and total organic content of less than ten parts per billion.
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TABLE 3.2. Description of the samples taken at different stages of the process of adaptation of monoclonal antibody-
producing CHO-K1 cells to serum-free medium, for the evaluation of the glycosylation profile of the monoclonal
antibody produced
STAGE OF SERUM MEDIUM COMBINATIONS OF SUPPLEMENTS SAMPLING DAY SAMPLE NAME
10 % 1 DMEM None 1 D 10 %
5 % DMEM C2, C3, C5 3 -
2.5 % DMEM
C2
12
C1 D 2.5 %
C3 C2 D 2.5 %
C5 C3 D 2.5 %
1.25 % DMEM C2, C3, C5 20 -
0.625 %
DMEM C2, C5 - -
C3 24 C3 D 0.625 %
75% DMEM: 25% EXCELL C2, C3, C5 - -
50% DMEM: 50% EXCELL C2, C3, C5 - -
25% DMEM: 75% EXCELL C2, C3, C5 - -
EXCELL
C2
66
C1 E 0.625 %
C3 C2 E 0.625 %
C5 C3 E 0.625 %
0.31 % 3 EXCELL
C2, C5 2 - -
C3 86 C3 E 0.31 % i
167 C3 E 0.31 % f
0.15 % EXCELL C3 194 C3 E 0.15 %
0.075 % EXCELL C3 237 C3 E 0.075 %
0 % EXCELL C3 280 C3 E 0 %
1 Normal serum-supplemented culture conditions.
2 Cells growing in combinations C2 and C5 died at this stage.
3 This stage was the most time-consuming, so samples at the initial (i) and final (f) phases were assessed.
ANTIBODY PURIFICATION
Prior to IgG purification, samples were concentrated to volumes of 200 µL using 15 mL spin
concentrators of 5 KDa molecular weight cutoff (Agilent Technologies, Ireland). Then, the IgG
from the concentrated samples was purified with Protein A spin plates (Thermo Scientific,
Ireland) according to manufacturer instructions, with slight modifications. Briefly, the wells of a
spin plate were equilibrated with two washes of 200 µL of 1x PBS (pH 7.2, Merck, UK). Samples
were diluted two-fold in 1x PBS and added (200 µL) to the plate for a period of incubation of 30
min with moderate agitation. The resin was washed three times with 500 µL of PBS, and the
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purified IgG eluted three times with 300 µL of 0.5 M acetic acid (pH 2.5, AnalaR, UK) and
neutralized with 20 µL of 1 M ammonium bicarbonate (pH 7-8.5, Sigma-Aldrich). The neutralized
elutions were dried overnight in a vacuum centrifuge.
IN GEL BLOCK IMMOBILIZATION
The dried samples were reduced with a solution containing 13.88 mM sodium dodecyl
sulfate (SDS, BDH, UK), 12.5 mM Tris (pH 6.6, AnalaR) and 0.05 M dithiothreitol (DTT, Sigma-
Aldrich) for 15 min at 65 ºC; and alkylated with 100 mM iodoacetamide (IAA, Sigma-Aldrich) for
30 min in the dark. The gel blocks were formed by adding a mixture of 22.5 µL of Protogel (30 %,
National Diagnostics, UK), 11.25 µL of 1.5 mM Tris, 1 µL of 35 mM SDS, and 1 µL of 34.7 mM
ammonium peroxisulphate (APS, AnalaR), and finally adding 1 µL of tetramethylethylenediamine
(TEMED, Sigma-Aldrich) to the samples, letting set for 15 min.
N-GLYCAN RELEASE AND FLUORESCENT LABELING
Each gel block was cut into small pieces (≈ 2 mm2), washed alternately with acetonitrile
(Sigma-Aldrich) and 20 mM sodium bicarbonate (pH 7, Merck, UK), vortexed and mixed for 10
min after each wash, and dried in a vacuum centrifuge.
For the release of N-linked glycans, the dried gel pieces were incubated for 15 min in a mix
of 2 µL of PNGase F (Prozyme, USA) and 48 µL of 20 mM sodium bicarbonate (pH 7), and a
further 12-16 h at 37 ºC after adding extra 50 µL of 20 mM sodium bicarbonate. The
supernatant was then removed (13,000 rpm, 5 min), and the samples subjected to a series of
washes with water and acetonitrile, with a 15 min sonication for each wash. The supernatants
obtained were collected and dried in a vacuum centrifuge. The dried samples were redissolved in
20 µL formic acid (1 %, Sigma-Aldrich), incubated for 40 min at room temperature and dried in a
vacuum centrifuge.
The released N-glycans were labeled for fluorescent detection using the LudgerTagTM 2-
aminobenzamide (2-AB) Glycan Labeling Kit (Ludger, UK), according to manufacturer
instructions. Briefly, 5 µL of the 2-AB labeling mix were added to each dried glycan sample,
incubated 30 min at 65 ºC, vortexed, spun down, and incubated for further 90 min.
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Excess 2-AB label from labeled N-glycans was cleaned-up using Normal Phase 1 PhyNexus
tips (PhyNexus, United States of America). Briefly, samples were diluted in 95 µL of water and
900 µL of acetonitrile. The PhyNexus tips were prepared by washing with ten 500 µL uptakes of
95 % acetonitrile (v/v in water), ten 500 µL uptakes of 20 % acetonitrile (v/v in water), and
another ten 500 µL uptakes of 95 % acetonitrile. Samples were loaded into the PhyNexus tips
through ten 1 mL in-out cycles, followed by washing of the tips with ten 1 mL uptakes of 95 %
acetonitrile. The glycans were then eluted with five uptakes of 200 µL of 20 % acetonitrile, and
the elutions collected and dried in a vacuum centrifuge.
NORMAL PHASE-HIGH PERFORMANCE LIQUID CHROMATOGRAPHY
For normal phase-high performance liquid chromatography (NP-HPLC), each dried sample
was resuspended in 20 µL of water and 80 µL of acetonitrile. NP-HPLC was performed using a
TSKgel Amide-80 3 µm (150 x 4.6 mm) column (Tosoh Bioscience, UK) for 60 min runs, at 30
ºC, using 50 mM ammonium formate (Sigma-Aldrich) as Solvent A and acetonitrile as Solvent B.
The runs were performed on a 2695 Alliance separations module (Waters, Ireland) with a
2475 multi-wavelength fluorescence detector (Waters), with excitation and emission wavelengths
at 330 and 420 nm, respectively. Conditions of the 60 min method were a linear gradient of 35
to 47 % Solvent A over 48 min at a flow rate of 0.48 mL/min, followed by a minute at 47 to 100
% Solvent A and 4 min at 100 % Solvent A, returning to 35 % solvent A over 1 min and then
finishing with 35 % solvent A for 6 min.
The systems were calibrated by running an external standard of 2-AB dextran ladder (2-AB
labeled glucose homopolymer) alongside the sample runs.
PROCESSING OF SAMPLES
A fifth-order polynomial distribution curve was fitted to the dextran ladder and used to
allocate glucose unit (GU) values from retention times, using Empower GPC software (Waters).
Tentative assignment of structures to the peaks was then made by matching the GU values
obtained with those available in GlycoBase (http://glycobase.nibrt.ie/), and using the known
IgG1 profile as a guide. A confirmation of the structures through exoglycosidase digestion was not
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possible due to a limited amount of sample. Nevertheless, for the purposes of comparison of this
study, such final allocation was not essential.
After structure assignment, the relative percentage of N-linked glycans was calculated for
agalactosylated (G0), monogalactosylated (G1), digalactosylated (G2), trigalactosylated (G3),
galactosylated (G1+G2+G3), core fucosylated (F), core fucosylated agalactosylated (FG0), core
fucosylated monogalactosylated (FG1), core fucosylated digalactosylated (FG2), core fucosylated
trigalactosylated (FG3), monosialylated (S1), disialylated (S2), trisialylated (S3), sialylated
(S1+S2+S3), monosialylated monogalactosylated (S1G1), monosialylated digalactosylated
(S1G2), disialylated digalactosylated (S2G2), disialylated trigalactosylated (S2G3), high mannose,
and complex glycan structures. The relative percentages were determined by summing the
percentage of area of the peaks pertaining to each of the abovementioned structures.
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3.3. RESULTS AND DISCUSSION
In this work, mAb-producing CHO-K1 cells were adapted to growth in serum-free conditions
and the impact of the process of adaptation on the glycosylation profile of the mAb produced was
evaluated.
For the adaptation to serum-free conditions, a gradual methodology was implemented. A
first attempt of this process was not successful, with cells dying before reaching the expected
serum-free growth. Indeed, it was observed that cells growing in medium supplemented with the
combinations of supplements C1 and C4 showed a decrease in viability very early in the process
(at 2.5 % serum) and died on day 29 of culture at the stage of 0.625 % serum. For the remaining
combinations of supplements (C2, C3, and C5) cells were able to reach the next level of serum
(0.31 %), but eventually died on day 45 of culture. The early cell death observed for combinations
C1 and C4 is most likely related to the trace element ammonium iron citrate that is present in
these combinations and absent in C2, C3, and C5.
The initial failed attempt at adaptation was associated with the following problems: (i) the
use of a low initial cell concentration (2x105 cells/mL) and of small culture flasks (24-well plates),
which resulted in a low number of cells surviving at each step of the demanding process of
adaptation; (ii) employing subculture procedures that could be damaging to the cells, such as
centrifugation and the use of enzymes (e.g. trypsin), which resulted in decreased cell viability and
morphological alterations (smaller and irregular cells); (iii) insufficient amount of time given at
each step of the process, which prevented a full cell adaptation.
The abovementioned problems were amended in a second attempt at cell adaptation to
growth in the absence of serum. So, higher initial cell concentration (4x105 cells/mL) and larger
culture flasks (25 cm2 T-flasks) were used, and enough time was given for the recovery of a
healthy appearance (viability) and proliferation of the cells at each step of serum reduction.
Furthermore, combinations of supplements C1 and C4 were not used in this second attempt due
to their observed worse effects on cell adaptation.
After these changes in the procedure, it was possible to successfully obtain cells fully
adapted to growth in serum-free conditions. The time spent at each step of the process and the
main events observed are shown in Table 3.3.
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TABLE 3.3. Timeline of the process of adaptation of the monoclonal antibody-producing CHO-K1 cells to serum-free
culture conditions
SERUM MEDIUM DAYS OF CULTURE OBSERVATIONS
10 % DMEM 0 – 1 (1)
5 % DMEM 1 – 3 (2)
2.5 % DMEM 3 – 12 (9)
1.25 % DMEM 12 – 20 (8)
0.625 % 20 – 66 (46) total
100 % DMEM 20 – 24 (4)
75 % DMEM: 25% EXCELL 24 – 26 (2)
50 % DMEM: 25 % EXCELL 26 – 28 (2)
25 % DMEM: 75 % EXCELL 28 – 30 (2)
100 % EXCELL 30 – 66 (36)
0.31 % EXCELL 66 – 167 (101)
72 Cells started growing detached
146 Death of cells growing in C2 and C5, as well
as of the control without supplementation
0.15 % EXCELL 167 – 194 (27)
0.075 % EXCELL 194 – 237 (43)
0 % EXCELL 237 – 280 (43) Cells became fully adapted
Approximately 280 days were necessary to reach the stage of growth in full serum-free
conditions. The first four stages of adaptation, (10, 5, 2.5, and 1.25 %) were the least
contributors for this extended period of time, with cells maintaining their growth and
morphological characteristics. Likewise, at the stage of 0.625 % serum, the shift from growth in
DMEM to growth in the chemically-defined EXCELL medium occurred smoothly and was achieved
in just 10 days. After this point, the process of adaptation became more time-consuming,
requiring a greater effort from the cells to adapt. This was particularly critical at the stage of 0.31
% serum, which lasted for 101 days, mainly due to the changes occurring in the mode of growth
of the cells. Indeed, the percentage of serum supplemented in the medium at this point was
probably not providing enough specific factors that aid cell adhesion (e.g. fibronectin, vitronectin,
and laminin), which resulted in the shift of the cell growth mode from adherent to suspended
(without rocking). This was further enhanced by the use of EXCELL, a medium that is specifically
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139
formulated for the culture of suspended cells. This change in cell behavior had the advantage of
allowing the expansion to new culture flasks without having to resort to the typical procedures of
splitting required in adherent culture (using trypsin and centrifugation) that have already shown to
be harmful to the cells during adaptation.
It was also at this stage of 0.31 % serum that differences between the combinations of
supplements were noticeable. Cells growing in medium supplemented with C2 and C5
demonstrated a clear decline of proliferation and viability over time, ultimately dying at day 146.
Cells growing in medium without addition of any combination of supplements (control, data not
shown) had a similar behavior and also died at this point, showing that the use of combinations
C2 and C5 had no advantage for adaptation. In contrast, combination C3 proved to be
advantageous for the adaptation of the mAb-producing CHO-K1 cells to serum-free culture,
allowing a full adaptation. It is therefore clear that the composition and concentration of the
supplements used in the growth medium strongly influence the ability of the cells to adapt to
serum-free conditions, as already seen in previous studies with PER.C6, HEK293, HeLa, CHO-S,
and C6 rat glioma cells (Jacobia et al. 2006; Ho and Ames 2002).
It is somewhat unexpected that only combination C3 allowed the full adaptation of the cells,
since the trace elements copper, zinc, selenite, and iron, present in the remaining combinations,
are often reported in the literature as the most important trace elements to use in media
optimization (Jacobia et al. 2006; Ho and Ames 2002; Haase and Beyersmann 1999; Bai et al.
2011; Zhang, Robinson, and Salmon 2006). However, for the cells in study, the less researched
trace elements of nickel, stannous, and metavanadate, whose particular functions are not yet
understood, were the most valuable. A possible explanation may be the fact that the influence of
the trace elements in the culture is not simply additive, so the unexpected results may be a
consequence of synergistic and antagonistic effects caused by their interaction (Jacobia et al.
2006).
After adapting to the challenging stage of 0.31 % serum, the cell viability increased and
persisted at high levels during the remaining steps of the process, resulting in an easier and
faster adaptation, as proved by the shorter time spent in the latter stages. Furthermore, a visible
improvement of cell proliferation was observed at the end of the step of 0.075 % serum and
during 0 %, reaching levels similar to those observed during cultivation in the typical 10 % serum-
supplemented conditions, which indicates a complete adaptation of the cells to the new culture
conditions.
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As mentioned, the main aim of this work was to assess how the glycosylation profile of the
mAb produced by the CHO-K1 cells was affected during the adaptation to serum-free conditions.
In Figure 3.1 it is possible to observe the profile obtained at the different stages of this process.
To note that for the combinations of supplements C2 and C5, only two samples were assessed
(D 2.5 % and E 0.625 %) due to the early death of cells at the stage of 0.31 % serum. In addition,
for combination C3, the extended time of adaptation to stage 0.31% serum led to the analysis of
samples from both the initial (E 0.31% i) and final (E 0.31% f) phases of this step.
FIGURE 3.1. N-glycosylation profile of the monoclonal antibody produced by CHO-K1 cells cultured in different
conditions during a process of gradual adaptation to serum-free medium. D – DMEM, E – EXCELL, Cx – combination
of supplements x (x = 2, 3, and 5), % referent to the percentage of serum supplemented in the culture medium.
The N-glycosylation profile of the mAb produced in the normal serum-supplemented culture
conditions (D 10 %) was in accordance with the known human IgG1 profile (Serrato et al. 2004;
C3 D 0.625 %
C3 E 0.625 %
C3 E 0.31 % i
C3 E 0.31% f
C3 E 0.15 %
C3 E 0.075 %
C3 E 0 %
15 20 25 30 35 40 45 50
6
C2 D 2.5 %
C2 E 0.625 %
C5 D 2.5 %
C5 E 0.625 %
C3 D 2.5 %
D 10 %
1 2
4
5
8
9
11 23222112
13 14 16 17 18 20
19
3
10
7
15
15 20 25 30 35 40 45 50
Time (minutes)
Time (minutes)
CHAPTER 3 │ IMPACT OF SERUM-FREE ADAPTATION ON PRODUCT QUALITY
141
Takahashi and Tomiya 1992; Masuda et al. 2000; Raju et al. 2000; Saba et al. 2002), with the
three main structures present: core fucosylated agalactosylated (peak 4, FG0),
monogalactosylated (peaks 8 and 9, two isoforms of FG1), and digalactosylated glycans (peak
12, FG2) (Routier et al. 1997; Serrato et al. 2007; Jenkins, Parekh, and James 1996; Jefferis
and Lund 1997). Moreover, the relation between the two FG1 isoforms (peaks 8 and 9) matches
the ratio usually displayed in endogenous human IgG1 (approximately 3:1) (Flynn et al. 2010;
Jefferis et al. 1990). However, it is clear from Figure 3.1 that this profile undergoes several
modifications during the process of adaptation to the absence of serum, as a consequence of the
changes in the culture conditions. The proportions of the main structures vary, as well as the
presence/absence of other glycan structures. Such variations of the main and less abundant
glycoforms can affect product quality and bioactivity (Mimura et al. 2001; Kanda et al. 2007).
Table 3.4 presents more detailed data for the analysis of the modifications observed in Figure
3.1, including the glucose unit (GU) values, tentative structure assignments, and percentage of
area of the peaks obtained at the different stages of the process of cell adaptation.
CHAPTER 3 │ IMPACT OF SERUM-FREE ADAPTATION ON PRODUCT QUALITY
142
TA
BLE
3.4
. Data of mean glucose unit (GU) value, tentative assignment, and percentage of area of the different peaks detected on the monoclonal antibody produced by CHO-
K1 cells during the process of adaptation to serum-free conditions. D – DMEM, E – EXCELL, GU – glucose units, Cx – combination of supplements x (x = 2, 3, 5), % referent
to the percentage of serum supplemented in the culture media
PEAK
MEAN GU 1
TENTATIVE
ASSIGNMENT
2
% AREA
D
10 %
C2 D
2.5 %
C2 E
0.625 %
C5 D
2.5 %
C5 E
0.625 %
C3 D
2.5 %
C3 D
0.625 %
C3 E
0.625 %
C3 E
0.31 % i
C3 E
0.31 % f
C3 E
0.15 %
C3 E
0.075 %
C3 E
0 %
1 4.91 ± 0.02
A1
2.09
0.84
8.08
4.67
5.42
8.12
2.60
9.89
5.67
0.53
2.31
3.60
2.97
2 5.34 ± 0.01
FA1 / A2
2.01
1.92
- -
3.82
3.62
5.63
2.37
3.55
1.11
2.51
2.28
2.61
3 5.68 ± 0.07
A1G1
- -
25.72
20.32
9.27
11.06
- 14.85
- -
3.38
- -
4 5.82 ± 0.02
FA
2 4
0.99
41
.51
15
.34
1
8.14
1
9.2
4
29.3
1
37.
53
19.3
6
22.6
1
25.1
2
14.1
9
37.6
9
50.2
1
5 6.18 ± 0.01
M5
1.50
1.98
- -
3.42
4.40
4.80
1.90
3.76
1.84
1.83
1.79
1.62
6 6.30 ± 0.01
A2G1[6]
- -
- -
- -
2.02
- 1.88
0.80
1.90
- -
7 6.43 ± 0.00
A2G1[3]
- -
- -
5.43
5.52
- 7.47
- -
- -
-
8 6.64 ± 0.02
FA
2G1
[6]
23.
52
24.2
1
17.8
6
14.
96
15.
31
18
.50
2
3.42
13
.75
20
.31
21
.67
10
.10
26
.27
23
.27
9 6.75 ± 0.03
FA
2G1
[3]
9.11
6.
41
23.8
9
27.
84
8.66
6
.21
1
0.38
6.2
9
9.20
9.
31
8.4
2
8.3
0
7.89
10
7.12
M6
- -
- 1.03
- -
- -
- -
- -
-
11
7.16 ± 0.03
A2G2 / M6
1.65
1.50
2.08
1.03
3.77
3.60
2.17
4.43
2.51
1.23
1.34
2.44
1.94
12
7.61 ± 0.02
FA
2G2
8.
40
8.55
7.03
11.15
10.
45
7.26
9.24
8.04
12.7
9
9.27
8.50
10.0
0
7.34
13
7.98 ± 0.01
FA2G1S1
2.73
3.25
- 0.85
2.91
2.39
1.52
3.47
2.33
2.07
1.49
3.32
2.16
14
8.46 ± 0.02
A2G2S1
0.91
1.62
- -
1.33
- 0.67
0.82
1.72
2.76
3.19
1.20
-
15
8.75 ± 0.00
FA2G2S(3)1
- -
- -
1.28
- -
1.78
- -
- -
-
16
8.89 ± 0.01
FA2G2S(6)1
0.98
1.23
- -
0.95
- -
0.77
1.70
2.37
2.64
2.03
-
17
9.59 ± 0.09
A2G2S2
1.99
1.13
- -
1.46
- -
1.56
1.76
2.71
3.83
1.08
-
18
9.99 ± 0.17
FA2G2S2
0.95
1.64
- -
2.44
- -
1.24
3.86
6.81
11.94
- -
19
10.19 ± 0.10
A3G3S2
- 1.12
- -
- -
- -
0.69
1.13
2.25
- -
20
10.45 ± 0.02
FA3G3S2[6]
1.14
1.00
- -
3.63
- -
2.00
4.22
7.58
14.33
- -
21
10.67 ± 0.01
FA3G3S2[3,6]
0.92
0.86
- -
- -
- -
- -
- -
-
22
10.97 ± 0.05
A3G3S3
0.84
0.89
- -
1.21
- -
- 1.45
3.68
5.85
- -
23
11.41 ± 0.02
FA3G3S3
0.27
0.34
- -
- -
- -
- -
- -
-
Main structures
82.02
80.68
64.12
72.09
53.66
61.28
80.57
47.44
64.91
65.37
41.21
82.26
88.71
Other structures
17.98
19.32
35.88
27.90
46.34
38.71
19.41
52.55
35.10
34.62
58.79
17.74
11.30
1 Average of the GU value of all samples containing the peak.
2 A – N-Acetylglucosamine, F – fucose, G – galactose, M – mannose, and S – sialic acid.
CHAPTER 3 │ IMPACT OF SERUM-FREE ADAPTATION ON PRODUCT QUALITY
143
The results shown in Table 3.4 confirm the variation on the proportions of the main
structures observed in Figure 3.1 for some samples. Indeed, cells growing in C5 E 2.5 % produce
a mAb where FA2G1 is the main glycan. Furthermore, in some cases the typically less abundant
structures become more prevalent than the usual three main glycans, as is the case of A1G1 for
samples C5 D 2.5 %, C3 D 2.5 %, C2 E 0.625 %, and C3 0.625 %, all at the expense of the
FA2G2 structure. For C3 E 0.15 %, FA3G3S2 and A2G2S2 substitute FA2G1 and FA2G2 as the
main glycans.
It is curious to note that the reduction on the global proportion of the main glycan structures,
which goes from the initial 82 % down to 54 %, occurs only at the middle stages of the process of
adaptation. Indeed, at the final stages of adaptation (C3 E 0.075 % and C3 E 0 %), the main
structures reach percentages even superior (89 %) to those of the initial culture conditions. This
may be related to the behavior of the cells during adaptation. Indeed, as mentioned, at this final
phase cells have reacquired proliferation rates and viabilities similar to those observed initially,
contrasting with the low cell densities and viabilities obtained during the middle steps of
adaptation. The low cell viabilities may cause the accumulation of extracellular glycosidases in
the medium, and potentially alter the glycan profile of the mAb produced (Gramer and Goochee
1993, 1994). Furthermore, at the stage of 0.31 % serum, cells shifted their mode of growth from
adherent to suspended, which may have led to modifications of the mAb glycosylation profile
thereafter.
It should be noted that structures with higher GU values, corresponding to glycans
containing sialic acids, are absent in some of the samples, which may impact the biological
activity of the mAb produced. Indeed, biological activity is closely related to the glycosylation
pattern, particularly to the following functional elements: galactose, core fucose, sialic acid and
bisecting N-acetylglucosamine (GlcNAc) (Cabrera et al. 2005; Kanda et al. 2007). Concerning the
latter, it is known that CHO cells lack the enzyme N-acetylglucosaminyl transferase III (GnT III)
that mediates the transfer of bisecting GlcNAc to complex glycans, so no particular attention will
be given to this element. In contrast, the degrees of galactosylation, fucosylation, and sialylation
of the mAb produced, and their possible impacts on mAb biological activity, will be discussed in
more detail. For this, Table 3.5 shows the levels of the abovementioned functional elements
composing the mAb obtained at the different stages of the process of adaptation to serum-free
conditions.
CHAPTER 3 │ IMPACT OF SERUM-FREE ADAPTATION ON PRODUCT QUALITY
144
TA
BLE
3
.5. Galactose, core fucose and sialic acid composition of the monoclonal antibody produced by CHO-K1 cells during the different steps of the process of
adaptation to serum-free conditions. D – DMEM, E – EXCELL, Cx – combination of supplements x (x = 2, 3, 5), % referent to the percentage of serum supplemented
in the culture media
GLYCAN STRUCTURE
% AREA
D
10 %
C2 D
2.5 %
C2 E
0.625 %
C5 D
2.5 %
C5 E
0.625 %
C3 D
2.5 %
C3 D
0.625 %
C3 E
0.625 %
C3 E
0.31 % i
C3 E
0.31 % f
C3 E
0.15 %
C3 E
0.075 %
C3 E
0 %
Agalactosylated (G0)
47.03
47.00
24.46
24.36
33.79
47.25
51.65
35.74
36.85
29.22
21.51
46.58
58.38
Galactosylated (G1+G2+G3)
52.99
53.00
75.54
75.64
66.22
52.74
48.34
64.26
63.17
70.78
78.49
53.42
41.63
Monogalactosylated (G1)
33.85
33.87
67.47
63.97
41.58
43.68
37.34
45.83
33.72
33.85
25.29
37.89
33.32
Digalactosylated (G2)
15.33
14.92
8.07
11.67
19.80
9.06
11.00
16.43
23.09
24.54
30.77
15.53
8.31
Trigalactosylated (G3)
3.81
4.21
0.00
0.00
4.84
0.00
0.00
2.00
6.36
12.39
22.43
0.00
0.00
Core fucosylated (F)
86.85
89.00
64.12
72.94
64.87
63.67
82.09
56.70
77.02
84.20
71.61
87.61
90.87
Core fucosylated agalactosylated (FG0)
40.59
41.51
15.34
18.14
19.24
29.31
37.53
19.36
22.61
25.12
14.19
37.69
50.21
Core fucosylated monogalactosylated (FG1)
33.85
33.87
41.75
43.65
26.88
27.10
35.32
23.51
31.84
33.05
20.01
37.89
33.32
Core fucosylated digalactosylated (FG2)
9.65
11.42
7.03
11.15
15.12
7.26
9.24
11.83
18.35
18.45
23.08
12.03
7.34
Core fucosylated trigalactosylated (FG3)
2.76
2.20
0.00
0.00
3.63
0.00
0.00
2.00
4.22
7.58
14.33
0.00
0.00
Sialylated (S1+S2+S3)
13.18
13.08
0.00
0.85
15.21
2.39
2.19
11.64
17.73
29.11
45.52
7.63
2.16
Monosialylated (S1)
5.57
6.10
0.00
0.85
6.47
2.39
2.19
6.84
5.75
7.20
7.32
6.55
2.16
Disialylated (S2)
5.99
5.75
0.00
0.00
7.53
0.00
0.00
4.80
10.53
18.23
32.35
1.08
0.00
Trisialylated (S3)
1.62
1.23
0.00
0.00
1.21
0.00
0.00
0.00
1.45
3.68
5.85
0.00
0.00
Monosialylated monogalactosylated (S1G1)
3.01
3.25
0.00
0.85
2.91
2.39
1.52
3.47
2.33
2.07
1.49
3.32
2.16
Monosialylated digalactosylated (S1G2)
2.56
2.85
0.00
0.00
3.56
0.00
0.67
3.37
3.42
5.13
5.83
3.23
0.00
Disialylated digalactosylated (S2G2)
3.80
2.77
0.00
0.00
3.90
0.00
0.00
2.80
5.62
9.52
15.77
1.08
0.00
Disialylated trigalactosylated (S2G3)
2.19
2.98
0.00
0.00
3.63
0.00
0.00
2.00
4.91
8.71
16.58
0.00
0.00
Complex glycans
97.68
97.49
97.27
98.96
98.45
94.70
93.79
94.10
95.88
95.00
97.54
97.50
96.99
High mannose structures
2.32
2.52
2.73
1.04
1.55
5.31
6.21
5.91
4.13
5.01
2.46
2.50
3.01
CHAPTER 3 │ IMPACT OF SERUM-FREE ADAPTATION ON PRODUCT QUALITY
145
GALACTOSYLATION
Galactosylation is one of the most studied glycosylation features of any glycoprotein (Pučić et
al. 2011). However, the effect of terminal galactose on mAb effector functions is still not fully
understood. Nevertheless, it is suggested that higher levels of galactosylation are desirable (Abès
and Teillaud 2010; Serrato et al. 2007), since agalactosylated (G0) structures in antibodies are
correlated with several pathologies (Parekh et al. 1985). Antibodies with higher galactose content
could have a more effective action through improvements of CDC (Hodoniczky, Zheng, and
James 2005; Boyd, Lines, and Patel 1995).
In the present study, the levels of galactosylation of the mAb obtained in the normal culture
conditions (D 10 %, 53 % galactosylation) are comparable to those obtained previously for normal
human IgG (Serrato et al. 2007; Routier et al. 1998). These levels are increased for serum levels
between 0.625 % and 0.15 % for the three combinations of supplements assessed (C2, C3, and
C5). This is mainly due to the increase of monogalacto (G1) structures, except for C3 E 0.31 %
and C3 E 0.15 %, where digalacto (G2) and trigalacto (G3) structures contribute majorly to levels
of galactosylation close to 80 %. It has been suggested that hypergalactosylation arises when
cells are grown in stationary culture (Lund et al. 1993) or low density static culture (Kumpel et al.
1994); so the fact that at these stages of the process cells were growing at low densities may
justify the higher levels of galactosylation observed. The antibody produced in these conditions
may be more effective with improved CDC (Davies et al. 2001; Hodoniczky, Zheng, and James
2005; Boyd, Lines, and Patel 1995). However, with further reduction of serum percentage in the
medium (C3 E 0.075% and C3 E 0%), galactosylation decreases to levels below those observed at
the initial culture conditions. The lower proportions of glycans with terminal galactose obtained in
this study for cells growing in serum-free conditions in comparison with those of serum-containing
media are in accordance with previous works concerning CHO (Lifely et al. 1995) and hybridoma
cells (Serrato et al. 2007), and may reduce the efficacy of the mAb.
FUCOSYLATION
Core fucosylation of IgG mAbs has been intensively studied as a consequence of its role in
ADCC (Pučić et al. 2011). Fucose interferes with binding of the IgG to the FcyRIIIa receptor and
dampens its ability to destroy target cells through ADCC (Hossler, Khattak, and Li 2009;
Nimmerjahn and Ravetch 2008; Kanda et al. 2007; Kanda et al. 2006). Consequently, lack of
core fucose enhances the clinical efficacy of mAbs that exert their therapeutic effect by ADCC
CHAPTER 3 │ IMPACT OF SERUM-FREE ADAPTATION ON PRODUCT QUALITY
146
mediated killing (Sibéril et al. 2006; Shields et al. 2002; Shinkawa et al. 2003). Indeed, it has
been shown that IgGs deficient in core fucose have ADCC activity enhanced by up to 100-fold
(Shields et al. 2002).
In the present study, the lowest and therefore most favorable levels of core fucose were
generally obtained in the middle stages of the process of adaptation. However, these positive
changes on mAb structure are lost at the final stages of adaptation, with core fucose levels at C3
E 0 % (serum-free culture) of approximately 90 %, which are similar to those of D 10 %, and in
accordance with the normal levels observed in human and CHO cell derived antibodies (Raju
2003).
In IgGs, a ratio of fucosylated structures of 1:2:1 for agalacto:monogalacto:digalacto
(FG0/FG1/FG2) structures has been observed (Jones et al. 2003; Beck et al. 2005).
Interestingly, this ratio is not observed in the mAb produced in the initial culture conditions (D 10
%), with FG0 as the predominant fucosylated structure. This initial ratio changes through the
process of adaptation, with values closer to those expected in C3 E 0.625 % and C3 E 0.31 %,
FG2 predominant at C3 E 0.15 %, and the initial FG0 predominance returned at C3 E 0.075 %
and C3 E 0 %.
SIALYLATION
The effects of sialylation of IgG have recently attracted much attention, since it was shown
that the addition of sialic acid monosaccharides dramatically changes the physiological role of
IgGs by converting them from pro-inflammatory into anti-inflammatory agents (Kaneko,
Nimmerjahn, and Ravetch 2006; Anthony and Ravetch 2010; Anthony et al. 2008). Reports have
shown that higher sialylation of IgG associates with low ADCC, due to reduced binding to specific
Fc receptors such as FcγRIII (Scallon et al. 2007).
In general, the degree of sialylation reported for IgG has been below 20 % (Pučić et al. 2011;
Arnold et al. 2007; Serrato et al. 2007). These values are in accordance with those obtained in
this study, except for C3 E 0.31 % and C3 E 0.15 %, which show higher sialic acid contents
(29.11 and 45.52 %, respectively). These increased levels are mainly related to a higher
prevalence of disialylated structures, both digalacto (S2G2) and trigalacto (S2G3). In contrast,
sialylated structures are less present at C2 E 0.625 %, C5 D 2.5 %, and at the lowest serum
stages of the process of adaptation, C3 E 0.075 % and C3 E 0 %, with monosialic acids (S1) as
the most prevalent sialylated structure. These results of lower mAb sialylation in serum-free
CHAPTER 3 │ IMPACT OF SERUM-FREE ADAPTATION ON PRODUCT QUALITY
147
conditions when compared to serum-containing media are in accordance to previous studies with
hibridoma cells (Serrato et al. 2007), and suggest an improvement of mAb efficacy through
ADCC.
OTHER ELEMENTS
In addition to the functional elements already discussed (galactose, fucose and sialic acid),
other less abundant glycoforms may also have an important effect on the biological activity of
therapeutic IgGs. The presence of high mannose structures, for example, has been associated
with reduced ADCC and CDC (Kanda et al. 2007), as well as with a rapid IgG clearance from
serum (Abès and Teillaud 2010). In this work, mAb produced at all stages of the process of
adaptation had low levels of high mannose structures, with 94 to 99 % of the glycoforms
pertaining to complex glycans. The high mannose structures were slightly more present at the
middle steps of adaptation (with combination C3), returning to the initial lower levels at the end
of the process.
Although the presence of IgG from fetal bovine serum in the samples could have influenced
the glycosylation profiles obtained, the likelihood of such contamination in this work was reduced
since the methodology used for IgG purification had a high specificity for human IgG while
providing weak purification for bovine IgG. Furthermore, other studies in similar conditions have
shown a low contribution of bovine IgG to the peaks of the glycosylation profile (between 0.1 and
2.0 % for most peaks, with 4.7 % for the FA2G2 peak) (Serrato et al. 2007). Therefore, the
conclusions of the present study are most probably not affected by the presence of bovine IgG.
CHAPTER 3 │ IMPACT OF SERUM-FREE ADAPTATION ON PRODUCT QUALITY
148
3.4. CONCLUSION
The establishment of processes for the large-scale production of therapeutic proteins, like
mAbs, comprises several steps that aim to maximize product yield. However, it is essential to
understand and monitor the effect of these processes on product quality (e.g. glycosylation) to
assure that therapeutic activity is not affected. One of the most challenging and time-consuming
steps of process development is the adaptation of producer cells to serum-free conditions, with
potential impact on product quality. In this work, the effects of such a process of adaptation on
the glycosylation profile of a mAb produced by CHO-K1 cells were evaluated.
Concerning the adaptation itself, the results of this work highlight the importance of selecting
adequate medium supplements to support cell adaptation to serum-free culture, with only one of
the five combinations assessed being successful (C3). Additionally, the amount of time given at
each step of the process has also proved to be a determinant factor.
As for glycosylation, it was clear that cell adaptation to serum-free conditions had a strong
impact on mAb glycosylation. The initial profile (DMEM, 10 % serum) was in accordance with the
typical IgG1 profile, but the prevalence of the main structures (fucosylated agalacto-, monogalacto-
and digalactosylated) decreased from 82 to 54 % during the middle stages of the process, and
increased to 89 % in the final steps. Indeed, it was interesting to note different behaviors of mAb
glycosylation for the middle and final steps of adaptation. At the middle stages, galactosylation
increased and fucosylation reduced, both having a positive impact on the clinical efficacy of the
mAb through improvements of ADCC and CDC activity. Conversely, sialylation increased and
exceeded the levels usually reported (below 20 %), particularly for combination C3 with EXCELL at
0.15 % serum (45.52 % sialic acid content), potentially reducing ADCC and, consequently, the mAb
efficiency. At the final steps of adaptation, in serum-free medium, fucosylation was similar to that of
the initial serum-supplemented conditions, but galactosylation and sialylation were decreased, with
divergent potential effects (negative and positive, respectively) on the biological activity of the mAb.
The divergences may be associated with a low cell density and viability observed at the middle
steps, as well as to a shift of the cell growth mode from adherent to suspension.
The final result of the interplay of these different mAb characteristics are not easy to predict
and would need to be assessed in vivo. However, it is clear that the process of cell adaptation to
serum-free conditions impacts the quality of the product, suggesting that product quality control
and monitoring should be implemented at these initial stages of process development.
CHAPTER 3 │ IMPACT OF SERUM-FREE ADAPTATION ON PRODUCT QUALITY
149
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hapter hapter hapter hapter 4444
Impact of microcarrier culture on product
quality
CC
THE PRESENT CHAPTER WAS ADAPTED FROM THE FOLLOWING RESEARCH PAPERS
ANA RITA COSTA, Joanne Withers, Maria Elisa Rodrigues, Niaobh McLaughlin,
Mariana Henriques, Rosário Oliveira, Pauline Rudd, Joana Azeredo (2012). The
impact of microcarrier culture optimization on the glycosylation profile of a
monoclonal antibody. Submitted to Journal of Industrial Microbiology and
Biotechnology.
Maria Elisa Rodrigues, ANA RITA COSTA, Pedro Fernandes, Mariana Henriques, Philip
Cunnah, David Melton, Joana Azeredo, Rosário Oliveira (2012). Evaluation of
macroporous and microporous carriers for CHO-K1 cell growth and monoclonal
antibody production. Submitted to Biotechnology Progress.
159
icrocarriers are widely used for the large-scale culture of attachment-dependent
cells, providing increased cell density and product yield. However, the specific culture conditions
used in these processes can affect the quality of the product, which is closely related to its
glycosylation pattern. The lack of studies in the area reinforces the need to better understand the
effects of these microcarrier cultures on product glycosylation. Consequently, this chapter centers
on the evaluation of the glycosylation profile of a monoclonal antibody (mAb) produced by
Chinese hamster ovary (CHO-K1) cells grown in Cytodex 3, comparing different culture conditions
(initial culture volume and cell concentration, rocking methodology and speed, and culture
vessel). The glycosylation profile of the microcarrier cultures is also compared to that obtained of
typical adherent cultures.
It was found that microcarriers resulted in a glycosylation profile with different
characteristics from T-flask cultures, with a general increase in galactosylation and decrease in
fucosylation levels, both with a potentially positive impact on mAb efficacy. The levels of
sialylation also diverged, but without a general tendency. This study then showed that the specific
culture conditions used in microcarrier culture influenced the mAb glycan profile, and that each
functional element (galactose, core fucose, sialic acid) was independently affected by these
conditions. In particular, great reductions of fucosylation were obtained with a lower initial volume
of culture, and notable decreases in sialylation and glycoform heterogeneity were observed for
shake flask culture, with these last modifications being associated with improved cell densities
achieved in these culture vessels.
Keywords: Monoclonal antibody; Chinese hamster ovary cells; Microcarrier; Cytodex 3;
Glycosylation
MM
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4.1. INTRODUCTION
The currently preferred system for the large-scale production of therapeutics is the
suspended culture of mammalian cells. These systems provide surface-to-volume ratios higher
that the common anchorage-dependent cultures and consequently result in improved cell
densities and product yields (Ozturk and Hu 2006). Despite this, there are still continuous efforts
to develop anchorage-dependent systems that can compete with the suspended culture, either
due to some limitations of suspended systems, the impossibility of growing certain cell types in
suspension, or the inevitable use of adherent cells to obtain specific products. Among the diverse
technologies developed to the effect, microcarrier systems are the most successful and well-
known (Chu and Robinson 2001; Ziao et al. 2002; Kong et al. 1999), with large application in the
production of viral vaccines (Berry et al. 1999; Wu and Huang 2002; Mendonça et al. 1993; Wu,
Huang, and Liu 2002; Butler et al. 2000) and recombinant proteins (Hu et al. 2000; Wang et al.
2002; Blüml 2007; Wang and Ouyang 1999; Cosgrove et al. 1995). These systems improve the
surface area available for cell adhesion and consequently result in improved cell density and
product yield (Hirtenstein et al. 1980; Blüml 2007; Van Wezel 1967; Schürch, Cryz, and Lang
1992; Rudolph et al. 2008).
Generally, microcarriers can be structurally divided into micro- and macroporous, according
to the size of the porous. In the microporous carriers (e.g. Cytodex) cells are able to grow only on
the external surface, while in macroporous carriers (e.g. CultiSpher, Cytoline, and Cytopore) cells
can also colonize the inner spaces (Ozturk and Hu 2006; Almgren et al. 1991; Spearman et al.
2005; Yokomizo et al. 2004). The characteristics of the microcarriers are important for the
success of the culture (Ozturk and Hu 2006; Butler 1996), but other factors must be considered,
such as the scale and type of culture vessel (Wu, Hsieh, and Liau 1998; Wang et al. 2002), and
the culture environment (Ng, Berry, and Butler 1996; Nam et al. 2008). Furthermore, it is
important to recognize that the specific conditions of the culture can influence not only cell and
product yields, but also the product quality, for example through effects on protein glycosylation.
Indeed, it has become evident that glycosylation plays critical roles in protein effectiveness in
vivo (Jenkins and Curling 1994), and the ability to perform this post-translational modification is a
major reason for the current choice of mammalian cells as hosts for recombinant therapeutic
production (Nam et al. 2008). It is therefore essential to ensure that glycosylation of recombinant
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proteins in microcarrier culture is consistent with the desired product (Spearman et al. 2005).
However, to date, there are limited studies examining the effects of changing between adherent,
suspension, and microcarrier cultures on glycosylation of the recombinant product (Nam et al.
2008). Furthermore, the few studies performed typically compare microcarrier culture to
suspension culture (Watson et al. 1994; Hooker et al. 2007; Wang et al. 2002), and not to the
normal adherent cell culture conditions, and have shown results that seem to be specific to the
type of cell, product, and microcarrier used. For example, increased sialylation was found in
Cytodex culture for recombinant human tissue kallikrein production (Watson et al. 1994) and in
Cytoline culture of Chinese hamster ovary (CHO) cells in a fluidized bed bioreactor for interferon-γ
production (Hooker et al. 2007), while no differences were found in human recombinant
erythropoietin (EPO) produced by CHO cells in fluidized bed bioreactor cultures with Cytoline
(Wang et al. 2002).
In an effort to elucidate the effects of microcarrier culture on protein glycosylation, the
present work evaluated the glycan profile of a monoclonal antibody (mAb) produced by CHO-K1
cells grown in microcarriers. Different culture conditions were assessed to determine their
influence on mAb glycosylation, particularly on the galactosylation, fucosylation, and sialylation
levels, and the potential impact on the biological effectiveness of the mAb. Additionally, the
glycosylation profiles obtained in microcarrier cultures were compared to those of adherent
culture in common culture vessels (T-flasks).
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4.2. MATERIALS AND METHODS
4.2.1. CELL LINE AND CELL CULTURE
MAb-producing CHO-K1 cells, previously obtained (Costa et al. 2012) through the
transfection of a CHO-K1 cell line (CCL-61, American Type Culture Collection, Spain) for the
production of a recombinant human mAb (CAB051, Biotecnol SA, Portugal) was used. These
cells were grown in Dulbecco’s Modified Eagles Medium (DMEM, Sigma-Aldrich, United Kingdom)
supplemented with 10 % fetal bovine serum (FBS, Sigma-Aldrich) and 1x hypoxanthine
aminopterin thymidine (HAT, Sigma-Aldrich), at 37 ºC and 5 % carbon dioxide (CO2), in 75 cm2
culture flasks (T-flasks, Frilabo, Portugal). For microcarrier culture, cells were detached after
reaching a 70-80 % confluence and the concentration of the cell suspension adjusted to the
values needed for each assay (see section 4.2.3.).
4.2.2. MICROCARRIER PREPARATION
The microporous Cytodex 3 carriers (Sigma-Aldrich) were prepared according to the
manufacturer instructions. Briefly, the dry microcarriers were swollen and hydrated in calcium-
and magnesium-free phosphate buffered saline (Ca2+/Mg2+-free PBS, 137 mM sodium chloride
(NaCl), 2.7 mM potassium chloride (KCl), 10 mM sodium phosphate dibasic (Na2HPO4), and 2
mM potassium dihydrogen phosphate (KH2PO4), pH 7.4) (Sigma-Aldrich) for at least 3 h at room
temperature, sterilized (121 ºC, 15 min, 15 psi), and stored at 4 ºC. Prior to use, the sterilized
microcarriers were washed twice with culture medium and once with Ca2+/Mg2+-free PBS.
4.2.3. MICROCARRIER CULTURE
Microcarrier cultures were initially performed in 50 mL vented conical tubes (Inopat,
Portugal) and latter in 250 mL shake flasks (Sigma-Aldrich). In vented conical tubes, 5 mL
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cultures of mAb-producing CHO-K1 cells were performed with 3 g/L of Cytodex 3, and different
conditions were assessed as described in Table 4.1.
TABLE 4.1. Conditions tested for the culture of the monoclonal antibody-producing CHO-K1 cells in Cytodex 3 (CY)
microcarriers
ASSAY INOCULUM CONCENTRATION
(cells/ml)
ROCKING MECHANISM ROCKING SPEED
(rpm)
VOLUME AT
INOCULATION
CULTURE VESSEL
CY1 2x105 Pulse followed by continuous 60 Total Vented conical tube
CY2 2x105 Continuous 60 Total Vented conical tube
CY3 2x105 Pulse followed by continuous 40 Total Vented conical tube
CY4 2x105 Continuous 40 Total Vented conical tube
CY5 2x105 Pulse followed by continuous 60 Half Vented conical tube
CY6 4x105 Pulse followed by continuous 60 Total Vented conical tube
CY7 4x105 Continuous 60 Total Vented conical tube
CYS 4x105 Pulse followed by continuous 60 Total Shake flask
All cultures were incubated at 37 ºC and 5 % CO2, with a fixed angle of inclination of 30º.
The rocking mechanism of ‘pulse followed by continuous’ refers to the use of a pulse rocking (60
or 40 rpm for 1 min at each 30 min) during the first six hours of culture (considered as the
critical phase for initial cell adhesion) followed by continuous rocking for the remaining time of
culture; the ‘continuous rocking’ mechanism uses a continuous rocking throughout the whole
culture. The assays using half the volume of medium at inoculation were completed with the
remaining volume after the first six hours of culture. For all assays, the medium was renewed
daily by replacing half of the culture volume with fresh growth medium.
In shake flasks, cultures of 20 mL were performed as described for the vented conical
tubes, with the exception of the 30 º inclination that has no application in these vessels.
4.2.4. CULTURE MONITORING
Cell growth was monitored in T-flask and microcarrier cultures. For this, cells were released
from the microcarriers by enzymatic digestion with trypsin (Sigma-Aldrich) and enumerated in a
haemocytometer with trypan blue staining (Sigma-Aldrich) for cell concentration and viability
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assessment. In microcarrier cultures, the cell concentration in the sample was standardized with
the number of microcarriers counted microscopically in the sample (Nmicrocarriers in sample), and the
concentration of cells per microcarrier (Ccell/microcarrier) determined according to Equation 4.1.
Ccell/microcarrier=6(Ncell 4⁄ )×1047×F×VsampleNmicrocarriers in sample
EQUATION 4.1. Determination of the cell concentration per microcarrier (Ccell/microcarrier). Ncells - total number of cells counted
in the haemocytometer; F - sample dilution factor; Vsample - volume of sample in mL; and Nmicrocarriers in sample - total number of
microcarriers counted in the sample.
The cell concentration in the culture (Ccell/mL) was then determined according to Equation 4.2,
using the concentration of microcarriers (Cmicrocarriers/mL) obtained from Equation 4.3.
Ccell/mL= Ccell/microcarrier×Cmicrocarriers/mL
EQUATION 4.2. Determination of the cell concentration in the culture (Ccell/mL) in cells/mL. Ccell/microcarrier – cell concentration
per microcarrier; and Cmicrocarriers/mL- concentration of microcarriers in the culture in number of microcarriers per mL.
Cmicrocarriers/mL=Cmicrocarriers in g/mL×Nmicrocarriers g dry weight⁄
EQUATION 4.3. Determination of the concentration of microcarriers in the culture in number of microcarriers per mL
(Cmicrocarriers/mL); Cmicrocarriers in g/mL – concentration of microcarriers used in the culture in grams of dry weight per mL; and
Nmicrocarriers/g dry weight - approximate number of microcarriers per gram of dry weight (data provided by the manufacturer).
4.2.5. ANTIBODY QUANTIFICATION BY ENZYME-LINKED IMMUNOSORBENT ASSAY
Cell productivity was assessed by enzyme-linked immunosorbent assay (ELISA), following an
optimized procedure described in the confidential and proprietary standard operating procedure
(SOP) 2008-01 ANL from Biotecnol SA. Briefly, 96 well plates (CoStar, United States of America)
were coated with a capture antibody (Sigma-Aldrich) overnight. After a 45 min blocking at room
temperature with 1 % bovine serum albumin in phosphate buffered saline (BSA-PBS, 11.5 µM
BSA in 137mM NaCl, 2.68 mM KCl, 1.76 mM KH2PO4, and 12.72 mM Na2HPO4, pH 7.4) (Sigma-
Aldrich), sample dilutions in 0.2 % BSA-PBS (3.03 mM BSA in PBS), a standard of known
concentration and a quality control (Biotecnol SA), were added to the plates and incubated for 2
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166
h at 37 ºC. The detection antibody was added and the plates incubated for additional 2 h at room
temperature. A 3,3’,5,5’-Tetramethylbenzidine (TMB, Sigma-Aldrich) substrate solution was
added and allowed to react for 10 min at room temperature. After stopping the reaction with
Phosphoric acid 75 % (Phosphoric acid 85 % in water, Frilabo), the absorbance was read at 450
nm. MAb concentration (CmAb) was determined using Equation 4.4 and the productivity (qmAb)
calculated according to Equation 4.5.
C� = �� ����������� − 1�
�� × c
EQUATION 4.4. Determination of monoclonal antibody concentration (CmAb) in µg/mL. Abs450 - absorbance read at 450
nm; a - estimated response at zero concentration; b - slope factor; c - mid-range concentration; and d - estimated
response at infinite concentration (parameters determined using the R software, version 2.6.2, from the R
Foundation for Statistical Computing).
q� (pg/cell/day)= �� � Ccell/mL⁄t
× 10#
EQUATION 4.5. Determination of monoclonal antibody productivity (qmAb) in pg/cell/day. CmAb - mAb concentration in
µg/mL; Ccell/mL - cell concentration in cells/mL; and t - time of production in days.
4.2.6. ANALYSIS OF THE MONOCLONAL ANTIBODY GLYCOSYLATION PROFILE
The glycosylation profile of the mAb obtained from the T-flask and microcarrier cultures at
different conditions was assessed as described below. To note that in the following procedures,
all water used was of type 1 ultra-pure, resistivity of 18 MΩ cm, particle-free (> 0.22 µm), and
total organic content of less than ten parts per billion.
ANTIBODY PURIFICATION
Prior to immunoglobulin G (IgG) purification, samples were concentrated to volumes of 200
µL using 15 mL spin concentrators of 5 KDa molecular weight cutoff (Agilent Technologies,
Ireland). Then, the IgG from the concentrated samples was purified with Protein A spin plates
(Thermo Scientific, Ireland) according to manufacturer instructions, with slight modifications.
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Briefly, the wells of a spin plate were equilibrated with two washes of 200 µL of 1x PBS (pH 7.2,
Merck). Samples were diluted two-fold in 1x PBS and added (200 µL) to the plate for a period of
incubation of 30 min with moderate agitation. The resin was washed three times with 500 µL of
PBS, and the purified IgG eluted three times with 300 µL of 0.5 M acetic acid (pH 2.5, AnalaR,
UK) and neutralized with 20 µL of 1 M ammonium bicarbonate (pH 7-8.5, Sigma-Aldrich). The
neutralized elutions were dried overnight in a vacuum centrifuge.
IN GEL BLOCK IMMOBILIZATION
The dried samples were reduced with a solution containing 13.88 mM sodium dodecyl
sulfate (SDS, BDH, UK), 12.5 mM Tris (pH 6.6, AnalaR) and 0.05 M dithiothreitol (DTT, Sigma-
Aldrich) for 15 min at 65 ºC; and alkylated with 100 mM iodoacetamide (IAA, Sigma-Aldrich) for
30 min in the dark. The gel blocks were formed by adding a mixture of 22.5 µL of Protogel (30 %,
National Diagnostics, UK), 11.25 µL of 1.5 mM Tris, 1 µL of 35 mM SDS, and 1 µL of 34.7 mM
ammonium peroxisulphate (APS, AnalaR), and finally adding 1 µL of tetramethylethylenediamine
(TEMED, Sigma-Aldrich) to the samples, letting set for 15 min.
N-GLYCAN RELEASE AND FLUORESCENT LABELING
Each gel block was cut into small pieces (≈ 2 mm2), washed alternately with acetonitrile
(Sigma-Aldrich) and 20 mM sodium bicarbonate (pH 7, Merck, UK), vortexed and mixed for 10
min after each wash, and dried in a vacuum centrifuge.
For the release of N-linked glycans, the dried gel pieces were incubated for 15 min in a mix
of 2 µL of Peptide N-glycosidase F (PNGase F, Prozyme, USA) and 48 µL of 20 mM sodium
bicarbonate (pH 7), and a further 12-16 h at 37 ºC after adding extra 50 µL of 20 mM sodium
bicarbonate. The supernatant was then removed (13,000 rpm, 5 min), and the samples
subjected to a series of washes with water and acetonitrile, with a 15 min sonication for each
wash. The supernatants obtained were collected and dried in a vacuum centrifuge. The dried
samples were redissolved in 20 µL of formic acid (1 %, Sigma-Aldrich), incubated for 40 min at
room temperature and dried in a vacuum centrifuge.
The released N-glycans were labeled for fluorescent detection using the LudgerTagTM 2-
aminobenzamide (2-AB) Glycan Labeling Kit (Ludger, UK), according to manufacturer
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instructions. Briefly, 5 µL of the 2-AB labeling mix were added to each dried glycan sample,
incubated 30 min at 65 ºC, vortexed, spun down, and incubated for further 90 min.
Excess 2-AB label from labeled N-glycans was cleaned-up using Normal Phase 1 PhyNexus
tips (PhyNexus, USA). Briefly, samples were diluted in 95 µL water and 900 µL acetonitrile. The
PhyNexus tips were prepared by washing with ten 500 µL uptakes of 95 % acetonitrile (v/v in
water), ten 500 µL uptakes of 20 % acetonitrile (v/v in water), and another ten 500 µL uptakes of
95 % acetonitrile. Samples were loaded into the PhyNexus tips through ten 1 mL in-out cycles,
followed by washing of the tips with ten 1 mL uptakes of 95 % acetonitrile. The glycans were then
eluted with five uptakes of 200 µL of 20 % acetonitrile, and the elutions collected and dried in a
vacuum centrifuge.
NORMAL PHASE-HIGH PERFORMANCE LIQUID CHROMATOGRAPHY
For normal phase-high performance liquid chromatography (NP-HPLC), each dried sample
was ressuspended in 20 µL water and 80 µL acetonitrile. NP-HPLC was performed using a
TSKgel Amide-80 3 µm (150 x 4.6 mm) column (Tosoh Bioscience, UK) for 60 min runs, at 30
ºC, using 50 mM ammonium formate (Sigma-Aldrich) as Solvent A and acetonitrile as Solvent B.
The runs were performed on a 2695 Alliance separations module (Waters, Ireland) with a
2475 multi-wavelength fluorescence detector (Waters), with excitation and emission wavelengths
at 330 and 420 nm, respectively. Conditions of the 60 min method were a linear gradient of 35
to 47 % Solvent A over 48 min at a flow rate of 0.48 mL/min, followed by a minute at 47 to 100
% Solvent A and 4 min at 100 % Solvent A, returning to 35 % solvent A over 1 min and then
finishing with 35 % solvent A for 6 min.
The systems were calibrated by running an external standard of 2-AB dextran ladder (2-AB
labeled glucose homopolymer) alongside the sample runs.
PROCESSING OF SAMPLES
A fifth-order polynomial distribution curve was fitted to the dextran ladder and used to
allocate glucose unit (GU) values from retention times, using Empower GPC software (Waters).
Tentative assignment of structures to the peaks was then made by matching the GU values
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169
obtained with those available in GlycoBase (http://glycobase.nibrt.ie/), and using the known
IgG1 profile as a guide.
The relative percentage of N-linked glycans was calculated for agalactosylated (G0),
monogalactosylated (G1), digalactosylated (G2), trigalactosylated (G3), galactosylated
(G1+G2+G3), core fucosylated (F), core fucosylated agalactosylated (FG0), core fucosylated
monogalactosylated (FG1), core fucosylated digalactosylated (FG2), core fucosylated
trigalactosylated (FG3), monosialylated (S1), disialylated (S2), trisialylated (S3), sialylated
(S1+S2+S3), monosialylated monogalactosylated (S1G1), monosialylated digalactosylated
(S1G2), disialylated digalactosylated (S2G2), disialylated trigalactosylated (S2G3), trisialylated
trigalactosylated (S3G3), high mannose, and complex glycan structures. The relative percentages
were determined by summing the percentage of area of the peaks pertaining to each of the
abovementioned structures.
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4.3. RESULTS AND DISCUSSION
Microcarriers have emerged as one of the most promising technologies for the culture of
adherent cell types at scales adequate for biopharmaceutical production. To establish a
successful microcarrier culture, several parameters are typically manipulated to optimize the final
cell and product yields. However, these changes in the culture parameters may also affect the
quality of the product, for example, by inducing modifications on the glycosylation profile. Since
an appropriate glycosylation of therapeutic proteins such as mAbs is important for their biological
activity and clinical efficacy (Spearman et al. 2005), it is essential to ensure that glycosylation in
microcarrier cultures is consistent with the desired product. In this study, mAb-producing CHO-
K1 cells were cultured in microporous Cytodex 3 carriers, under different culture conditions to
evaluate their impact on the glycosylation profile of the mAb. Additionally, the glycosylation
obtained in microcarrier cultures was compared to that of normal adherent culture conditions in
T-flasks.
The glucose unit (GU) values and the tentative structure assignments of the peaks identified
by normal phase HPLC, as well as the relative peak area (%) obtained in each assay, are shown
in Table 4.2.
Glycans found in all conditions are mainly complex biantennary structures with a high
degree of heterogeneity, containing different terminal sugars, including sialic acid, galactose, N-
acetylglucosamine and core fucose. However, differences can be found between the microcarrier
cultures and the typical adherent culture in T-flask in the prevalence of certain glycans,
particularly of the most typical IgG1 structures: FA2, FA2G1 (6 and 3 arms), and FA2G2. Indeed,
FA2 and FA2G1 (6 arm) show a general tendency to decrease, while FA2G1 (3 arm) and FA2G2
increase in microcarrier cultures. The reduction of the prevalence of these main structures in
microcarrier culture is obviously accompanied by an increase in the remaining structures,
particularly of core fucosylated disialylated glycans such as FA2G2S2 and FA3G3S2, and of A1
and A1G1.
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TABLE 4.2. Data of mean glucose unit (GU) value, tentative structure assignment, and relative (%) area of the peaks
of the monoclonal antibody produced by CHO-K1 cells under different culture conditions: T-flask; CYi – Cytodex 3 in
vented conical tubes; CYS – Cytodex 3 in shake flask
PEAK MEAN GU 1 TENTATIVE
ASSIGNMENT 2
% AREA
T-FLASK CY1 CY2 CY3 CY4 CY5 CY6 CY7 CYS
1 4.9 ± 0.01 A1 2.09 3.33 3.54 3.03 3.76 10.54 4.48 1.77 6.10
2 5.33 ± 0.01 FA1 / A2 2.01 1.75 1.59 2.54 3.03 3.40 1.56 1.74 3.32
3 5.66 ± 0.01 A1G1 - 5.69 5.76 5.15 5.31 14.16 5.70 - 8.60
4 5.80 ± 0.01 FA2 40.99 22.01 16.59 20.59 21.24 16.93 16.87 30.92 27.57
5 6.18 ± 0.01 M5 / A2G1 1.50 1.93 1.68 2.44 2.39 3.13 1.77 2.45 2.82
6 6.31 ± 0.04 A2G1[6] - 1.61 1.19 1.97 2.55 - 1.36 1.29 4.86
7 6.42 ± 0.01 A2G1[3] - 2.34 2.49 1.82 1.88 6.22 2.77 - -
8 6.64 ± 0.01 FA2G1[6] 23.52 20.74 15.60 16.12 17.10 13.20 15.62 25.59 23.46
9 6.75 ± 0.01 FA2G1[3] 9.11 15.18 10.53 11.45 12.98 7.33 11.77 13.23 9.85
10 7.15 ± 0.02 A2G2 / M6 1.65 2.59 2.15 1.94 2.37 3.25 2.72 1.81 2.59
11 7.59 ± 0.01 FA2G2 8.40 14.65 11.74 9.86 11.60 7.76 12.61 13.43 9.27
12 7.97 ± 0.01 FA2G1S1 2.73 2.16 2.18 1.91 1.83 2.86 2.54 1.72 1.56
13 8.46 ± 0.01 A2G2S1 0.91 1.29 2.12 2.03 1.58 2.44 1.98 1.09 -
14 8.70 ± 0.02 FA2G2S1[3] - - - - - 0.85 1.08 - -
15 8.88 ± 0.01 FA2G2S1[6] 0.98 1.26 2.38 2.19 1.71 0.78 1.68 1.06 -
16 9.17 ± 0.02 A2G2S2[3] - - - - - - - - -
17 9.36 A3G3S1 - - - - - - - - -
18 9.58 ± 0.01 A2G2S2[6] 1.99 0.73 3.70 2.31 1.88 1.95 2.64 0.94 -
19 10.03 ± 0.01 FA2G2S2 0.95 1.25 6.43 5.66 3.17 2.84 4.94 1.54 -
20 10.22 ± 0.00 A3G3S2 - - 1.18 1.11 0.54 - 1.04 - -
21 10.43 ± 0.01 FA3G3S2[3] 1.14 1.49 4.56 5.85 3.73 2.35 5.08 1.40 -
22 10.56 ± 0.01 FA3G3S2[6] - - 2.05 - - - - - -
23 10.68 FA3G3S2[3,6] 0.92 - - - - - - - -
24 10.93 ± 0.04 A3G3S3 0.84 - 2.54 2.01 1.34 - 1.79 - -
25 11.12 ± 0.01 A3G3S3[3] - - - - - - - - -
26 11.43 FA3G3S3 0.27 - - - - - - - -
Main structures 82.02 72.58 54.46 58.02 62.92 45.22 56.87 83.17 70.15
Other structures 17.98 27.42 45.54 41.96 37.07 54.77 43.13 16.81 29.85
1 Average of the GU value of all samples containing the peak.
2 A – N-Acetylglucosamine, F – fucose, G – galactose, M – mannose, and S – sialic acid.
The changes on the mAb glycosylation profile observed between the T-flask and the
microcarrier cultures may result from the creation of a different microenvironment for the cells in
the microcarriers (Spearman et al. 2005). This may impact glycosylation directly or through
variations caused on cell growth characteristics and mAb productivity, such as the ones observed
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172
in this study (Table 4.3). Effectively, it is clear from Table 4.3 that microcarriers provide variable
cell concentrations but mAb productivities are always enhanced when compared to T-flasks.
Furthermore, it is known that CHO cells produce enzymes such as sialidase, beta-galactosidase,
and fucosidase that can accumulate extracellularly in culture and potentially lead to extracellular
modifications of the glycans (Gramer and Goochee 1993). By affecting cell characteristics,
microcarrier culture may influence the production of such enzymes and potentially interfere with
glycosylation.
TABLE 4.3. Data of average cell concentration and productivity of monoclonal antibody-producing CHO-K1 cells
cultured in different conditions: T-flask; CYi – Cytodex 3 in vented conical tubes; CYS – Cytodex 3 in shake flask
ASSAY AVERAGE CELL CONCENTRATION
(x105 cells/mL)
qmAb
(pg/cell/day)
T-flask 8.51 ± 0.06 0.21 ± 0.05
CY1 6.86 ± 1.06 2.57 ± 1.38
CY2 16.02 ± 1.98 0.84 ± 0.35
CY3 3.73 ± 0.63 3.89 ± 1.17
CY4 6.21 ± 0.62 2.16 ± 0.94
CY5 7.63 ± 0.76 1.75 ± 0.66
CY6 18.51 ± 1.08 1.26 ± 0.99
CY7 10.25 ± 0.73 1.51 ± 0.30
CYS 104.1 ± 6.00 1.86 ± 0.58
Furthermore, microcarrier cultures were performed under rocking conditions, which were
not present in the typical T-flask cultures, and which may also be a factor leading to the
differences found between the glycosylation profile of the mAb obtained in these two types of
cultures.
Several studies have focused on the effect of specific elements of the glycan profile on the
effector function of glycosylated proteins. Known as functional elements, these include galactose,
core fucose, and sialic acid, and have been shown to influence antibody-dependent cellular
cytotoxicity (ADCC) and complement-dependent cytotoxicity (CDC). In fact, higher levels of
galactosylation (Abès and Teillaud 2010; Serrato et al. 2007; Jefferis and Lund 1997;
Hodoniczky, Zheng, and James 2005), reduced core fucosylation (Sibéril et al. 2006; Shields et
CHAPTER 4 │ IMPACT OF MICROCARRIER CULTURE ON PRODUCT QUALITY
173
al. 2002; Shinkawa et al. 2003) or reduced sialylation (Scallon et al. 2007; Kaneko, Nimmerjahn,
and Ravetch 2006; Anthony and Ravetch 2010; Anthony et al. 2008) are suggested to enhance
the clinical efficacy of mAbs that exert their therapeutic effect by ADCC and CDC mediated killing.
This is particularly relevant for core fucosylation, whose absence can improve ADCC activity by
up to 100-fold (Shields et al. 2002).
The relative percentages of the main functional elements of the mAb produced under the
different culture conditions evaluated in this study are shown in Table 4.4.
TABLE 4.4. Galactose, core fucose and sialic acid composition of the monoclonal antibody produced by CHO-K1 cells
during culture in different conditions: T-flask; CYi – Cytodex 3 in vented conical tubes; CYS – Cytodex 3 in shake
flask
GLYCAN STRUCTURES % AREA
T-FLASK CY1 CY2 CY3 CY4 CY5 CY6 CY7 CYS
Total number of peaks 17 17 20 19 19 17 20 15 11
Agalactosylated (G0) 46.67 29.35 23.64 28.35 30.41 34.06 25.16 36.56 39.70
Galactosylated (G1+G2+G3) 53.34 70.65 76.37 71.63 69.58 65.93 74.85 63.42 60.31
Monogalactosylated (G1) 36.11 48.69 38.59 39.64 42.85 45.34 40.65 43.06 49.74
Digalactosylated (G2) 14.06 20.48 27.45 23.02 21.13 18.25 26.29 18.97 10.57
Trigalactosylated (G3) 3.17 1.49 10.33 8.97 5.61 2.35 7.91 1.40 0.00
Core fucosylated (F) 89.01 78.74 72.06 73.63 73.36 54.90 72.19 88.89 71.71
Core fucosylated agalactosylated (FG0) 40.99 22.01 16.59 20.59 21.24 16.93 16.87 30.92 27.57
Core fucosylated monogalactosylated (FG1) 35.36 38.08 28.31 29.48 31.91 23.39 29.93 40.54 34.87
Core fucosylated digalactosylated (FG2) 10.33 17.16 20.55 17.71 16.48 12.23 20.31 16.03 9.27
Core fucosylated trigalactosylated (FG3) 2.33 1.49 6.61 5.85 3.73 2.35 5.08 1.40 0.00
Sialylated (S1+S2+S3) 10.73 8.18 27.14 23.07 15.78 14.07 22.77 7.75 1.56
Monosialylated (S1) 4.62 4.71 6.68 6.13 5.12 6.93 7.28 3.87 1.56
Disialylated (S2) 5.00 3.47 17.92 14.93 9.32 7.14 13.70 3.88 0.00
Trisialylated (S3) 1.11 0.00 2.54 2.01 1.34 0.00 1.79 0.00 0.00
Monosialylated monogalactosylated (S1G1) 2.73 2.16 2.18 1.91 1.83 2.86 2.54 1.72 1.56
Monosialylated digalactosylated (S1G2) 1.89 2.55 4.50 4.22 3.29 4.07 4.74 2.15 0.00
Monosialylated trigalactosylated (S1G3) 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Disialylated digalactosylated (S2G2) 2.94 1.98 10.13 7.97 5.05 4.79 7.58 2.48 0.00
Disialylated trigalactosylated (S2G3) 2.06 1.49 7.79 6.96 4.27 2.35 6.12 1.40 0.00
Trisialylated trigalactosylated (S3G3) 1.11 0.00 2.54 2.01 1.34 0.00 1.79 0.00 0.00
Complex glycans 98.43 97.74 98.09 97.81 97.62 96.81 97.76 97.87 97.30
High mannose 1.58 2.26 1.92 2.19 2.38 3.19 2.25 2.13 2.71
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174
In a first assessment it is possible to detect a general increase of galactosylation (mainly
digalacto (G2) and trigalacto (G3) structures) and decrease of fucosylation in microcarrier
cultures compared to T-flasks, both having a potential positive effect on mAb activity. On the
other hand, although also diverging from the T-flask cultures, the levels of sialylation in the
microcarrier assays are more variable, without showing a common tendency, which indicates a
possible higher susceptibility of this element to the culture conditions here evaluated. As said
above, it has been shown that CHO cells produce an extracellular sialidase capable of modifying
the sialic acid content of glycoproteins (Gramer and Goochee 1993), and that the
production/accumulation of this enzyme may be influenced by culture conditions, therefore
affecting the degree of sialylation. Additionally, it should be noted that the reported degree of
sialylation in human IgG has been below 20 % (Pučić et al. 2011; Arnold et al. 2007; Serrato et
al. 2007), but some of the microcarrier cultures resulted in superior levels (e.g. CY2), mainly due
to a higher prevalence of disialylated (S2) structures, both digalacto (S2G2) and trigalacto
(S2G3)), with potential negative effects on mAb activity by reducing ADCC.
Hypergalactosylation has been associated with low cell densities in previous studies (Kumpel
et al. 1994), but there was no correlation found in this work between the higher levels of mAb
galactosylation (Table 4.4) and the cell densities (Table 4.3) achieved in microcarrier cultures.
For core fucose, it is interesting to note that in addition to the global decrease of fucosylation,
there are also variations in the ratio of the agalacto:monogalacto:digalacto:trigalacto
(FG0:FG1:FG2:FG3) structures, with a general switch from the FG0 prevalence in T-flask cultures
to a FG1 prominence in microcarriers. In both cases, the divergences observed between
microcarrier and T-flask cultures may have been caused by the use of rocking in the former.
Furthermore, it should be noted that the potentially better levels (in terms of mAb activity) of
each of the functional elements are not obtained in the same conditions. For example, in terms
of galactosylation, mAb with improved characteristics (higher galactose) was produced in CY2;
while for fucosylation, the best quality mAb (less core fucose) was obtained in CY5; and for
sialylation, the lower and best levels were obtained in CY1, CY7, and CYS.
It has been suggested that increases in productivity, such as the ones observed in the
microcarrier cultures, may potentially lead to decreased effectiveness of recombinant proteins
(Nam et al. 2008). However, in this work, the higher productivities of microcarrier cultures (Table
4.3) do not seem to correlate with a lower quality of the mAb.
CHAPTER 4 │ IMPACT OF MICROCARRIER CULTURE ON PRODUCT QUALITY
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In a more specific analysis, the different conditions evaluated for the microcarrier cultures
were considered.
Rocking speed influenced the mAb glycosylation profile, but this effect was highly dependent
on the rocking methodology. For example, when using pulse/continuous rocking methodology,
60 rpm enabled the production of mAbs with lower levels of sialylation (reduced S2 structures)
compared to 40 rpm (CY1 versus CY3), which are potentially more effective through ADCC.
However, using a continuous rocking (CY2 versus CY4), these observations are reversed, and 40
rpm (CY4) appears as the advantageous rocking speed. There seems to be no correlation
between these results and the cell concentrations and productivities achieved in these assays
(Table 4.3). Nevertheless, the combination of rocking speed and mechanism should be
considered for mAb quality.
It is mentioned in the literature that the success of the microcarrier culture is dependent on
the initial colonization of the microcarriers with the cells (Butler 1996; Voigt and Zintl 1999;
Blüml 2007), so the culture conditions during the first hours of culture should be optimized to
improve this initial cell adhesion. In this work, two parameters that have been related to the
efficiency of initial cell adhesion were assessed, namely the rocking methodology used for the
first six hours of culture and the volume of the culture at inoculation.
Regarding the rocking methodology, it was found that this culture parameter affected the
glycosylation profile, but diverged with the concentration of cell inoculum used. Indeed, when
using 2x105 cells/mL (CY1 versus CY2), continuous rocking (CY2) resulted in increased levels of
sialylation, mainly due to a higher presence of S2 structures, which potentially results in a less
efficient mAb due to a decreased ADCC activity. However, when using a cell inoculum of 4x105
cells/mL (CY6 versus CY7), the continuous rocking (CY7) led to a mAb with lower galactosylation
and sialylation, and higher fucosylation, whose biological impact is difficult to predict due to the
opposite effects of these functional elements, although a decline of mAb effectiveness would be
expected due to the greater impact of fucosylation on mAb functionality (Shields et al. 2002).
Nevertheless, the combination of rocking methodology at the beginning of the culture and
concentration of cell inoculum seems to be important for mAb quality.
Concerning the culture volume, the use of total (5 mL) or half (2.5 mL) volume was tested
(CY1 versus CY5), with half (CY5) leading to a higher sialylation (mainly due to increased S2) and
to a great reduction of the levels of fucosylation. Due to the known strong impact of fucosylation
on IgG activity through ADCC (Shields et al. 2002), it is expected that the positive effects
CHAPTER 4 │ IMPACT OF MICROCARRIER CULTURE ON PRODUCT QUALITY
176
associated with its reduction in these conditions will surpass the negative effects of an increased
sialylation, and result in a mAb with improved activity. The use of different volumes at inoculation
may affect the microenvironment of the cells and therefore influence glycosylation. Furthermore,
although it has been suggested that the use of half volume during the initial hours of culture may
improve cell adhesion and consequently the final cell and product yields, such effect was not
observed in this study.
In addition to the functional elements already discussed, other less abundant glycoforms
may also have an important effect on the biological activity of therapeutic IgGs. The presence of
high mannose structures, for example, has been related to reduced ADCC and CDC (Kanda et al.
2007), as well as to a rapid IgG clearance from serum (Abès and Teillaud 2010). In this study,
the levels of high mannose are, in general, slightly increased in microcarrier cultures (particularly
for CY5).
The influence of the culture vessel on the glycosylation profile of the mAb produced by CHO-
K1 cells in microcarriers was also considered in this work, by comparing vented conical tubes
with shake flasks. The culture vessel was highly influential particularly in the sialylation levels of
the mAb, which greatly decreased to practically absent sialylation in shake flasks, predicting a
positive outcome on the biological activity of the mAb. Additionally, shake flasks seem to provide
a less heterogeneity of glycoforms, as demonstrated by the lowest number of peaks obtained (11
peaks, Table 4.4). Since cell concentrations are highly improved in shake flasks when compared
to the vented conical tube cultures, it is possible that these improved levels, or the factors that
led to them (e.g. better oxygenation and mass transfer), have caused these modifications on
sialylation and heterogeneity.
Some additional cultures were performed with a different type of microcarrier, specifically
the macroporous CultiSpher-S, for effects of comparison. The global influence of CultiSpher-S
cultures on glycosylation, in comparison with T-flask cultures, was similar to that previously
observed with Cytodex 3, causing a general reduction on the percentage of main structures, an
increase of galactosylation, a slightly reduction of fucosylation, and a variable effect on sialylation.
Furthermore, two culture variables tested with CultiSpher-S (initial culture volume and culture
vessel) also demonstrated effects on glycosylation similar to those of Cytodex 3 cultures. Of note
is the strong impact of the culture vessel on the glycosylation profile obtained with both
microcarrier cultures, with shake flasks confirming to be the best option by decreasing the
heterogeneity of glycoforms and leading to remarkable decreases of mAb sialylation with
CHAPTER 4 │ IMPACT OF MICROCARRIER CULTURE ON PRODUCT QUALITY
177
CultiSpher-S. The cell densities achieved in these microcarriers were also significantly improved
in shake flasks, reinforcing the possibility of this being the cause for the positive changes
observed in the glycosylation profile of the mAb.
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178
4.4. CONCLUSION
An understanding of the role of culture conditions on glycosylation is becoming increasingly
important to ensure a consistent quality of the product. In this study, the effect of microcarrier
culture and different culture conditions on the glycosylation pattern of a mAb produced by CHO-
K1 cells was evaluated. Higher levels of galactosylation (main di- and trigalacto structures) and
lower degrees of fucosylation were found in mAb produced by cells grown in microcarriers when
compared to the typical T-flask culture, both potentially improving the mAb effectiveness. On the
other hand, sialylation was found to be highly variable without a specific tendency. Furthermore,
contrarily to what has been suggested, the increased productivities obtained in microcarrier
cultures did not correlate with a lower quality of the mAb. On the other hand, the fact that
microcarrier cultures are performed under rocking conditions, in opposition to T-flask cultures,
may be a cause for the divergences found between them in the glycosylation profile of the mAb
produced.
All the culture conditions assessed in microcarrier culture led to modifications on the mAb
glycan profile, with each of the functional elements (galactose, core fucose, sialic acid) being
divergently affected by these conditions. In particular, the choice of the culture vessel appears to
have a strong influence in mAb sialylation, with great and desirable reductions achieved in shake
flask cultures. This is potentially related to highly improved cell densities achieved in these
vessels, which may have also been the cause for a reduction of the glycoform heterogeneity of
the mAb.
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hapter hapter hapter hapter 5555
General conclusions and considerations
for future work
CC
185
he work compiled in the present thesis is a contribute to the path into
biopharmaceutical processes with improved control of the quality of the product. Specifically, it
provides novel information about the influence of different processes and parameters involved in
the development stages of production on the glycosylation profile of the product.
The present chapter closes the work by providing a summary of the main conclusions of the
work performed, and proposing ideas to be addressed in future works in the field.
TT
CHAPTER 5 │ GENERAL CONCLUSIONS AND CONSIDERATIONS FOR FUTURE WORK
187
5.1. GENERAL CONCLUSIONS
In its still relatively short existence, biopharmaceutical industry has already revolutionized
modern medicine by applying recombinant technology in therapeutic protein production for the
treatment of several conditions that were previously thought incurable. Simultaneously, the industry
has faced many technological challenges in the pursuit of improved high-yielding processes capable
of fulfilling the market needs, while controlling and reducing the costs of said processes. One of the
most recent and important challenges is related to the control and maintenance of the product’s
quality during process development and at the final stages of production. The quality of the product
is majorly related to its glycosylation profile, a characteristic that has a strong impact on several
protein properties, such as serum half-life, in vivo activity, and immunogenicity. Unfortunately,
glycosylation is highly variable and can be affected by many parameters of process development.
So, to ensure the production of a consistent high-quality product it is essential to gain a deeper
understanding about the influence of these parameters on glycosylation. Such knowledge will
ultimately allow not only the preservation of the efficacy and safety characteristics of the product
during production, but also the manipulation of the culture parameters towards the enhancement of
these characteristics. The work presented in this thesis intended to be a contribute to this purpose,
by evaluating the glycosylation profile of a monoclonal antibody (mAb) produced by Chinese
hamster ovary (CHO-K1) cells during different stages of process development.
To complete this major goal, a mAb-producing CHO-K1 cell line was initially established using
the novel OSCARTM expression system as an alternative to traditional methods that typically require
long development times. OSCARTM showed several advantages over the most traditional systems:
first, transfection was simple and considerably faster, taking about two-three months compared to
the minimum six required by the common methods; second, the growth characteristics of the CHO-
K1 cells were maintained after transfection, as opposed to the common growth impair caused by
this type of processes; and third, the levels of mAb productivity initially obtained were high (10
pg/cell/day), without the need to perform the traditional process of amplification. This productivity
showed an abrupt decay in the first weeks in culture (1 pg/cell/day), but remained stable thereafter
for at least two years, indicating that if the initial decrease is controlled, the OSCARTM system may
provide producer cell lines with very stable expressions over time without the need to use the costly
toxic compounds required by the traditional technologies. Additionally, this work demonstrated that
CHAPTER 5 │ GENERAL CONCLUSIONS AND CONSIDERATIONS FOR FUTURE WORK
188
a critical step for the successful transfection using the OSCARTM system is the choice of the most
adequate minigene. In fact, only one of the three minigenes assayed, pDMW128, worked with the
CHO-K1 cells tested, showing that the choice of minigene is cell line and/or product type-specific,
and its selection represents an additional workload of this methodology. In this context, it would be
useful to create a database to collect all data of studies performed with the OSCARTM expression
system involving different cells and products, so that in the future the selection of the best minigene
for each application will require less trial-and-error experimentation.
During the development of the mAb-producing CHO-K1 cell line, several producing cell clones
were obtained, which had to be subjected to a selection of the highest and most stable producers.
The methodology used for the first selection proved to be highly influent on the outcome of the
process. Although the typically used method of comparison of absorbance values of the culture
supernatants is the simplest and fastest approach, which is advantageous considering the high
number of clones that usually need to be screened, it does not certify that the highest cell
producers are selected. Indeed, the use of a more labor-intensive but accurate approach based on
the analysis of productivity clearly demonstrated that there is no guarantee that the highest-
producing clones are selected when using the first methodology. This has a huge impact on the
product yields that will be achievable in the final process of production, so this study recommends
the assessment of productivity as the approach of choice for the initial selection. Still in this stage of
cell-line development, it was found that the highest-producer cell clones express mAbs with similar
glycosylation profiles.
The glycosylation profile was also assessed during the adaptation of mAb-producing CHO-K1
cells to serum-free medium, a process currently required by regulatory agencies for the production
of therapeutics to avoid safety problems related to the presence of animal-derived components.
Since serum provides many essential elements for cell proliferation and viability, its removal from
the culture is typically challenging and time-consuming, as shown in the present study. The work
performed also highlights the importance of selecting adequate media supplements to support cells
in this process of adaptation, and of avoiding aggressive procedures like centrifugation and the use
of enzymes, as well as the need to give the time needed for cells to reacquire a healthy growth at
each stage. Furthermore, this work clearly demonstrated that the process of adaptation strongly
influences mAb glycosylation. During the different steps involved in this process, the number of
glycoforms (heterogeneity) and the levels of certain functional elements of glycosylation, specifically
galactose, core fucose, and sialic acids, varied considerably, being possible to separate the effects
CHAPTER 5 │ GENERAL CONCLUSIONS AND CONSIDERATIONS FOR FUTURE WORK
189
into two stages. At the middle steps of adaptation, an increase of galactosylation and a decrease of
fucosylation were observed, potentially having positive outcomes on mAb efficacy by improving the
antibody-dependent cellular cytotoxicity (ADCC) and the complement-dependent cytotoxicity (CDC).
Sialylation, on the other hand, increased to higher levels than those normally reported, potentially
reducing mAb efficacy. A higher level of heterogeneity of glycoforms was also found for the middle
stages of adaptation, going against the intended homogeneity of glycosylation that improves efficacy
by reducing the presence of less efficient glycoforms. These results were related to the lower cell
concentrations and cell viabilities observed in this phase. Indeed, at the final steps of the process of
adaptation, where cells have reacquired a cell growth similar to the initial values, the glycosylation
profile became less heterogeneous and the levels of core fucose became similar to those initially
observed. However, galactosylation and sialylation of the serum-free cultures were decreased in
comparison to the initial serum-supplemented conditions, having divergent potential impacts on the
biological activity of the mAb (negative and positive, respectively). A graphical summary of the main
conclusions on this subject can be seen on Figure 5.1.
FIGURE 5.1. Summary of the modifications, and potential biological effects, detected in the glycosylation profile of the
monoclonal antibody produced by CHO-K1 cells during adaptation to growth in serum-free conditions. The
divergences found in the glycosylation profile were divided into two stages: during adaptation, and at the final stages
of adaptation and thereafter. Probable causes for the differences found are mentioned on the right.
Higher galactosylation
Lower fucosylation
Higher sialylation
Higher heterogeneity
Similar highmannose
Improved CDC
Improved ADCC
Reduced ADCC
Reduced efficacy due to the presence of
unefficient glycoforms
CELLS GROWING IN SERUM-SUPPLEMENTED MEDIUM
CELLS DURING ADAPTATION TO SERUM-FREE MEDIUM
Lower sialylation
Lower galactosylation
Similar fucosylation
Similar heterogeneity
Similar highmannose
Improved ADCC
Reduced CDC
CELLS AFTER ADAPTATION TO SERUM-FREE MEDIUM
+
-
+
-
Cell density and viability decrease
Growth and production rate
decrease
Cells shift from adherent to
suspended growth
Recovery of initial cell growth rate
Cells grow in suspension
Recovery of initial cell density and viability
CHAPTER 5 │ GENERAL CONCLUSIONS AND CONSIDERATIONS FOR FUTURE WORK
190
The work reported in this thesis has also shown that glycosylation is influenced by cell
culture in microcarriers. Microcarriers are a successful, and increasingly used, alternative
technology for the culture of anchorage-dependent cells with high cell and product yields. In this
study, the glycosylation of the mAb produced by CHO-K1 cells growing adherently in Cytodex 3
microcarriers was different from the profile obtained in normal T-flask cultures. The changes
observed were attributed to divergences between the two types of culture in terms of mAb
productivity (higher in microcarriers), to the use of rocking in the microcarrier cultures, and to the
possible generation of a specific microenvironment in the microcarriers that may affect pH
and/or potentiate the accumulation of extracellular enzymes (e.g. sialidases, fucosidases,
galactosidases) that alter the glycan content of the mAb. To specify the differences found, the
mAb produced in microcarrier cultures had an increase on galactosylation and a decrease of
fucosylation when compared to the initial T-flask culture, with both modifications potentially
leading to a more efficient mAb. Sialylation, for its turn, was found to be highly variable without a
general tendency, demonstrating to be more sensitive to specific variations in the culture
conditions. Indeed, this study assessed the impact of several parameters commonly included in
the optimization of microcarrier culture, such as cell concentration at inoculum, initial culture
volume, rocking mechanism and rocking speed, as well as culture vessel. All these culture
parameters led to modifications on the mAb glycosylation profile, affecting the functional
elements of galactose, core fucose, and sialic acid divergently. In particular, fucosylation
appeared to be more affected by the volume of the culture at inoculation; galactosylation by the
combination of rocking mechanism and speed; and sialylation by the volume of the culture at
inoculation, the combination of rocking mechanism, speed and cell concentration, and especially
by the culture vessel. Indeed, it was found that the choice of the culture vessel is highly influent
on the sialylation of the mAb, with shake flasks resulting on its reduction to almost absent levels,
which potentially improves mAb activity. Furthermore, the use of shake flasks also led to a more
desired homogeneous glycosylation. These positive changes were related to the highly improved
cell densities obtained in these vessels, which may have resulted from better oxygenation and
mass transfer. A graphical summary of the main conclusions regarding glycosylation in
microcarrier culture can be seen in Figure 5.2.
CHAPTER 5 │ GENERAL CONCLUSIONS AND CONSIDERATIONS FOR FUTURE WORK
191
FIGURE 5.2. Summary of the modifications, and potential biological effects, detected in the glycosylation profile of a
monoclonal antibody produced by CHO-K1 cells during microcarrier culture. Probable causes for the differences
found in comparison to the normal adherent culture in T-flasks are mentioned on the left.
In summary, the information resulting from this thesis contributes to a better understanding
of the effects of different technologies on product quality (glycosylation) in biopharmaceutical
processes, and highlights the need to extend quality monitoring and control to the early stages of
process development and not just limited to the final production process. The results obtained
open the doors to other investigations, and will hopefully contribute to a better control of product
quality in the near future, and perhaps to the improvement of the therapeutic efficacy of the
product through the simple manipulation of the culture conditions. A higher-quality product will
ultimately result in increased therapeutic efficacy, which will reduce the dose and frequency of
administration required, as well as the side effects, and consequently improve the patient
compliance with the treatment.
MICROCARRIER CULTURE
IN GENERAL SPECIFIC CULTURE CONDITIONS
T-FLASK CULTURE
Higher galactosylation
Lower fucosylation
Improved CDC
Improved ADCC+
Variable sialylation
Using half volume at inoculation
Using continuous rocking of 60 rpm
Using continuous rocking of 60 rpm
Using half volume at inoculation
Using shake flasks (it also reducesheterogeneity) – associated with highlyimproved cell densities
Using continuous rocking of 40 rpm,
cell inoculum of 4x105 cells/mL
Using pulse followed by continuous rocking
of 60 rpm, cell inoculum of 2x105 cells/mL
Reduced ADCC
Improved ADCC
Variable cell density
Increase ofprodutivity
Microenvironment
onmicrocarriers -
pH, extracellular
accumulation of
enzymes such as
sialidases,
galactosidases, and
fucosidases
Rockingparticularly
particularly
CHAPTER 5 │ GENERAL CONCLUSIONS AND CONSIDERATIONS FOR FUTURE WORK
192
5.2. CONSIDERATIONS FOR FUTURE WORK
Although the present work is a step forward into the understanding of how glycosylation
varies with culture parameters, it is clear that this field still has many challenges to tackle.
First, it is important to understand that glycosylation is no longer seen merely as a form to
evaluate the quality of the product, but it is now regarded as a means to improve the therapeutic
function of the product. To this purpose, it is essential to develop a better understanding on the
relationship between glycans and the physiological functions of the protein. This should consider
three aspects: (i) the different components of the glycosylation pathway should not be addressed
individually, but instead should be analyzed for the results of their interplay; (ii) the optimization
of a glycan structure for one activity may compromise another property equally important, so the
global effect should be evaluated; and (iii) the optimal glycoform profile must be addressed in a
case-by-case basis, considering that the biological functions to optimize depend on the type of
product and therapeutic application intended. The structure-function relationships can only be
assessed by direct experimentation, creating another challenge related to the development of
animal models more adequate than those currently employed, since the effects observed in these
do not correctly simulate what happens in humans.
Second, knowing the optimal glycoform profile to target for during process development and
production, the control of culture conditions in order to meet this profile would present a simple
and economical way to obtain a more effective product. This goal will require more fundamental
studies on the dependence of glycosylation on different process conditions, such as those
performed in the work described herein, but the wide range of culture conditions imply that major
works will be necessary to reach the level of knowledge required for such control. Some of the
conditions to assess include: temperature, pH, culture media, culture mode (adherent,
suspension, microcarriers), type of bioreactor, mode of operation (batch, fed-batch, continuous),
rocking, as well as transfection, scale-up and adaptation processes.
Third, cells have a major impact on the glycosylation profile of the product, as proven by the
current reliance on mammalian cells for therapeutic protein production for their capacity to
produce glycoproteins similar to those of human. The differences on glycosylation among cells
are related to their specific sets of gene/protein expression levels, and availability and spatial
localization of glycoenzymes and nucleotide-sugar precursors. Consequently, it would be
CHAPTER 5 │ GENERAL CONCLUSIONS AND CONSIDERATIONS FOR FUTURE WORK
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important to identify the critical cell characteristics for glycosylation and to have the capacity to
implement their evaluation during early cell clone selection, in addition to the already assessed
properties of cell growth and productivity, so that the best clone for both product yields and
quality can be chosen.
Fourth, the understanding and control of glycosylation will, to a great extent, depend on
progresses made in the analytical methodologies. Currently, a complete structural analysis of
glycosylation can only be accomplished by combining different methodologies, therefore being
time-consuming and complex. So, future developments on the area will have to focus on the
following: (i) shortening total analysis time, to enable the use of the analytical data to regulate
process development or production, which will require the simplification or elimination of the
current protocols for sample preparation/purification; (ii) capacity to analyze a large number of
samples; (iii) improve sensitivities to allow the analysis of low-abundance samples; (iv) simplify
and automate the analysis to make the methodology more robust and accessible to non-
specialist laboratories with minimal user expertise; and (v) allow the accurate and complete
structural analysis of complex glycans and heterogeneous samples.
Fifth, the engineering of glycosylation offers great potential for the production of therapeutic
proteins with improved efficacy. Current researches are exploring different techniques to either:
(i) modify the biosynthetic pathway of the host cells, for example to avoid potential immunogenic
structures, humanize glycosylation, or increase the presence of desired glycans, an approach
that may enable the use of non-mammalian expression systems that have some advantages from
an economical and product yield perspective; or (ii) directly alter the protein glycosylation, which
may ultimately allow the rational design of desired glycoprotein structures.
To conclude, major progresses are expected in the next few years concerning glycosylation
understanding, control, and analysis. The relevance of glycosylation for product quality, the
diversity of paths that remain to explore, and the certainty that many challenges will still emerge,
make this a particularly appealing field of research.
“It always
seems
impossible
until it’s
done.”
Nelson Mandela