IMPERIAL COLLEGE LONDON
Amino acid metabolism in Chinese
hamster ovary cell culture
Kyriakopoulos, Sarantos
January 2014
Department of Chemical Engineering and Chemical Technology
Imperial College London
South Kensington Campus
London SW7 2AZ
A thesis submitted to Imperial College London in partial fulfilment of the requirements of the
degree of Doctor of Philosophy
i
Abstract
The present thesis focuses on amino acids (a.a.) and their metabolism by Chinese
hamster ovary cells, the workhorse of the multibillion dollar biopharmaceutical industry. The
aim of the research was to explore a.a. transport and metabolism and define optimal operating
conditions during fed-batch culture, which is the most common process mode used
industrially. A fast and reliable way to calculate a.a. concentration ranges in media and feeds
is of vital importance, as a.a. are the monomers of proteins, which account for 70% of dry
cell weight. The desired recombinant product of bioprocesses is typically also a protein.
The transport of a.a. into the cells was studied at the mRNA level of a.a. transporters
for the first time in a bioprocessing context. The presented results demonstrate that a.a.
transport is not the limiting step for recombinant protein formation. Also, the study allowed
for a staged feeding strategy to be designed, where a.a. were not fed altogether.
Following linear projection of an integral of viable cell concentration target and using
the specific a.a. consumption rates during batch culture, six feeds were formulated containing
a.a. and glucose. Three designs were based on the results of the a.a. transport study; however,
they underperformed in comparison to the other feeds. In the latter, all nutrients were fed at
the same time, resulting in cell culture performance comparable to that obtained with a
commercial feed that was tested in parallel. This renders the presented method the first to
define a traceable quantitative way to calculate amount of nutrients in the feeds.
Flux balance analysis, a powerful technique that allows for investigation of
intracellular dynamics, was used to analyse the metabolic data. An enhanced intracellular
network was created by coupling two pre-existing in the literature that also for the first time
included the glycosylation of the host proteins in the biomass equation.
Finally, a novel methodology was developed and coded in R to calculate specific rates
of consumption/production of various metabolites in cell culture. The methodology couples
mass balances for fed-batch culture operation with constructed vectors of the sampling and
feeding schemes. This can be further developed to a bioprocess relevant software platform for
analysing cell culture data.
ii
Acknowledgments
Firstly, I would like to thank my supervisor Dr Cleo Kontoravdi for her support,
guidance and trust throughout my studies. This few lines are just not enough to express my
gratitude. Secondly, I would like to thank Dr Karen Polizzi for her relentless patience while
teaching a chemical engineer molecular biology techniques. Also, I would like to thank
Karen for her guidance and special attention to detail.
I am really grateful that I met Dr Ioscani Jimenez del Val and had the opportunity to
discuss and receive feedback on my work. I would also like to thank the rest members of Dr
Kontoravdis lab for their help, discussions and support: Ioanna Stefani, Philip Jdrzejewski
(for the glycan data and patience while discussing about it), Susie/Sou Si, Goey Cher (for
subculturing my cells every now and then), Ning Chen, Kate Royle and Kealan Exley. Here, I
would also like to thank Gian Ntzik for teaching me how to code and think algorithmically.
Special thanks should also go to the people that largely influenced my decision
towards enrolling in a PhD course. Specifically, I would like to thank Professor Paul
Christakopoulos, Dr Evangelos Topakas and Dr Christina Vafiadi that accommodated me in
my final year project during my undergraduate studies.
Last but not least, I am very thankful to my parents and sisters. Their support was
vital in order for me to reach the point of submitting this thesis.
iii
Declaration of originality
I hereby certify that all material in this thesis which is not my own work has been
appropriately acknowledged.
Sarantos Kyriakopoulos
London, U.K.
iv
Copyright declaration
The copyright of this thesis rests with the author and is made available under a
Creative Commons Attribution Non-Commercial No Derivatives licence. Researchers are
free to copy, distribute or transmit the thesis on the condition that they attribute it, that they
do not use it for commercial purposes and that they do not alter, transform or build upon it.
For any reuse or redistribution, researchers must make clear to others the licence terms of this
work.
v
Notation
Latin Letters
a Artificial vector of feeding
a.a. Amino acid
ADP Adenosine diphosphate
Ala Alanine
Amm Ammonia
Arg Arginine
Asn Asparagine
Asp Aspartate
AT Active transport
ATC Anatomical therapeutic chemical classification
ATP Adenosine triphosphate
b Artificial vector of sampling
Batch_300mL Batch culture with a starting volume of 300mL in CD CHO medium
(Invitrogen, UK)
Batch_50mL Batch culture with a starting volume of 50mL in CD CHO medium
(Invitrogen, UK)
BCAA Branched chain amino acids (Ile, Leu and Val)
BCH 2- aminobicyclo-(2,2,1)-heptane-2-carboxylic acid
C Concentration of a metabolite
c Artificial vector of sampling after feed
CCD Central composite design
CCL Continuous cell line
Ccomp Artificial/computed vector of the concentration of a metabolite
CD Chemically defined
CHO Chinese hamster ovary cells
Cin Concentration of a metabolite in a feed
Notation vi
Cit Citrate
CoA Coenzyme A
CS_total Total required culture concentration of substrate S in feed
csv Comma-separated values
Cys Cysteine
DAE Differential algebraic equations
DCW Dry cell weight
DNA Deoxyribonucleic acid
DOE Design of experiments
E.C. Enzyme commission
EAA Essential amino acids
EMA European medicines agency
ER Endoplasmic reticulum
F_all Feed all. Fed-batch culture with 50mL starting volume, prepared from scaling
up the observed in Batch_300mL a.a. and Glc rates and diluting one to one
in the medium (CD CHO, Invitrogen, UK)
F_all_pl40 Feed all plus 40% more. Feed containing 40% more than the ingredients in
F_all and diluted one to one in CD CHO medium (Invitrogen, UK)
F_all_pl40_NO_CD_CHO Feed all plus 40% more, no CD CHO medium. Exact same feed
as F_all_pl40, however, not diluted one to one in CD CHO
(Invitrogen, UK);
F_BC_TM_1hr First Branched Chain a.a. Then Most at 1hr interval. Reverse staged
feeding strategy as the one for feed F_M_TBC_1hr
F_C_Inv Feed C Invitrogen. Commercially available feed for GS-CHO cells lines (CD
EfficientFeedTM C AGTTM, Invitrogen, UK)
F_M_TBC_1hr First Most Then Branched Chain a.a. at 1hr interval. Fed-batch culture
with 50mL starting volume and feed prepared based on F_all.
Branched amino acids (BC) follow the addition of most amino acids
(M) at 1hr intervals
F_M_TBC_pl40_12hr First Most Then Branched Chain a.a. plus 40% more, 12hr
interval. Feed similar with F_M_TBC_1hr, however, now
staged feeding occurs at 12 hour intervals and the feed is
prepared based on F_all_pl40
F6P Fructose-6-phosphate
Notation vii
FBA Flux balance analysis
FDA Food and Drug administration
Fin Volumetric rate of feeding
Fout Volumetric rate of sampling
FoutafF Volumetric rate of sampling after feed
Fuc Fucose
Gal Galactose
GalNAc N-acetylgalactosamine
GC-MS Gas chromatography- mass spectrometry
gDCW Grams of dry cell weight
Glc Glucose
Glclss Glycolysis
GlcNAc N-acetylglucosamine
Gln Glutamine
Glu Glutamate
Gly Glycine
Glyc Glycerol
Glyc3PC Glycero-3-phosphocholine
GOI Gene of interest
GS Glutamine synthetase
GS35 Low-producing cell line (rprotein is an IgG4 mAb)
GS46 High-producing cell line (rprotein is an IgG4 mAb)
GSn8 Null cell line (not producing any rprotein)
HEK Human embryonic kidney
His Histidine
hr Hour
IgG4 Immunoglobulin of isotype and 4 subclass
Ile Isoleucine
Isobut Isobutyrate
Isoval Isovalerate
IVC Integral of viable cells
IVCC Integral viable cell concentration
IVCCestimate_tharvest IVCC estimate at the day of harvest
k Degradation rate of a metabolite
Notation viii
kd Specific death rate
KEGG Kyoto encyclopaedia of genes and genome
Km Michaelis-Menten constant
KS Monod model substrate constant
Lac Lactate
Leu Leucine
LP Linear programming
Lys Lysine
mAb Monoclonal antibodies
Mann Mannose
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