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