Increasing IFN-y Productivity in CHO Cells through CDK Inhibition
MASSACHUSETTS INSTITUTE
OF TECHNOLOGY
David Alan McClain
JUN 3 0 2010
B.S. Chemical Engineering
Cornell University, Ithaca, NY, 2004
LIBRARIES
ARCHNES
SUBMITTED TO THE DEPARTMENT OF CHEMICAL ENGINEERING IN PARTIAL
FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY IN CHEMICAL ENGINEERING
at the
MASSACHUSETTS INSTITUTE OF TECHNOLOGY
MAY 2010
0 2010 Massachusetts Institute of Technology. All Rights Reserved.
Author:
Department of Chemical Engineering
May 2010
Certified by:
Daniel I.C. Wang
Institute Professor
Thesis Supervisor
Accepted by:
William M. Deen
Professor Chemical Engineering
Chairman, Committee for Graduate Students
2
Increasing IFN-y Productivity in CHO Cells through CDK Inhibition
by
David Alan McClain
Submitted to the Department of Chemical Engineering on May 2010
In Partial Fulfillment of the Requirements for the Degree of
Doctor of Philosophy in Chemical Engineering
ABSTRACT
Approximately 60-70% of all recombinant human glycoproteins are produced in Chinese
Hamster Ovary (CHO) cells. Production in CHO cells, however, is often plagued by low
productivity when compared with other host cell lines, including bacteria and yeast. For this
reason, investigating ways of improving the productivity of CHO cells producing recombinant
proteins has been an active area of research for many decades. The induction of growth arrest is
one such area that shows particular promise. Through the use of siRNA and chemical cyclin
dependent kinase (CDK) inhibitors, we have developed new methods to improve and better
understand recombinant protein production during growth arrest.
In this study, we have shown that the specific inhibition of the CDK2-CcnE complex through
chemical inhibition leads to growth arrest and a subsequent increase in specific productivity. In
addition, we have shown that the knockdown of CcnEl alone leads to increases in specific
productivity. With the advent of improved shRNA expression systems, we believe that the
targeted knockdown of CcnE1 has the potential to induce growth arrest and improve total
recombinant protein production
The relationship between growth-arrested cell cycle phase and productivity is very poorly
understood. In this work, we have used various CDK inhibitors to better understand the
relationship between growth-arrested cell cycle phase, specific growth rate, and productivity.
We have shown that increases in specific productivity are cell-cycle independent following
growth arrest induced by CDK inhibition. Instead, specific productivity increases correlate
strongly with a decreasing specific growth rate.
Lastly, in this work, we have identified an interesting CDK2 inhibitor that inhibits mitosis and
induces a subsequent growth arrest. Following its addition, we observe a decrease in specific
growth rate, an increase in DNA content, and a drastic increase in the specific productivity of a
recombinant protein (IFN-y). We used this inhibitor to increase total IFN-y productivity by 73%
in a modified batch culture. With the development of an optimized feed medium, we believe that
this CDK2 inhibitor could also be used to increase recombinant protein production in fed-batch
cultures.
Thesis Supervisor:
Title:
Daniel I.C. Wang
Institute Professor
4
DEDICATION
This work is dedicated to my parents, Richard and Sara McClain, and my sister, Erin McClain.
You instilled in me the importance of life-long learning from a young age. Without your
constant support and encouragement, none of this work would have been possible.
ACKNOWLEDGEMENTS
As I sit here, I'm overwhelmed by the thought of trying to thank everyone who has helped me up
until to this point in my life, thesis, and career. I'm particularly glad that I'm writing this section
last, as the crippling writer's block that has set in would surely have discouraged me from
writing the rest of this thesis. I'd like to take this time to thank all of those people who have
been particularly influential and supportive throughout my thesis.
I'd first like to thank my thesis committee members: Professor Charlie Cooney, Professor
Harvey Lodish, Professor Kris Prather, and Professor Greg Stephanopoulos. Your advice and
support, especially during the times when my experiments just weren't working, is greatly
appreciated. Having five committee members made it particularly challenging to get everyone in
the same room at one time, and I appreciate your patience in helping to ensure that we could all
get together at least a few times.
I also would like to thank my thesis advisor, Professor Daniel Wang. I truly appreciate the
intellectual freedom you gave me, both inside and outside of lab. You provided me with many
opportunities that I would not have otherwise had and have been very encouraging of my career
goals. For that I thank you.
I'd also like to thank a number of members of the Stephanopoulos and Colton groups that helped
me throughout the years. Thanks to both Jeff Millman and Jit Hit Tan for putting up with my use
of the Guava. Thanks to Dr. Keith Tyo for initial help with my qRT-PCR work, and Paulo
Gameiro for putting up with my use of the iCycler and help with the YSI. I'd also like to thank
both past and present members (and visitors) of our own lab: Frederyk Ngantung, Lam Raga
Markeley, Andres Abin, and Jin Kiat Ng (SMA). Our conversations have had an immeasurable
impact on this thesis.
Notably absence from this previous list is Sohan Patel, who deserves particular mention. It
wasn't until you left for Singapore that I realized how important it was to have someone with
whom to share the highs and the lows of lab work. Your calming presence was certainly
something I took for granted, and was missed over these past months.
A number of people in the Chemical Engineering Department deserve special recognition.
Thank you to the ChemE Student Office, especially Suzanne Easterly, Mary Wesolowski, and
Katie Lewis for you help throughout the years. Also, a special thank you to Susan Lanza for
everything she has done for the Wang Lab, even while working in BCS.
At MIT, we are lucky to have a number of world-class facilities at our fingertips. All of which
made my work possible. Thank you to a number of the core facilities at the CCR: the FACS
Facility, specifically Glen Paradis, the Biopolymers Facility, and the Microscopy and Imaging
Facility. Special thanks also to the Biotechnology Process Engineering Center (BPEC),
especially the members of the Griffith group (past and present), Michelle Berry, Dan Darling,
Cathy Greene, and Aran Parillo. You've done more than I can thank you for to make my life at
MIT easier. I'd also like to say a special thank you to the VWR Stockroom, especially Steve and
Monica. I don't think a week (or sometimes day) went by without me frantically searching the
shelves for that reagent I forgot to order the week before. Lastly, thanks to Rich Lay and Sara
Darcy in the ASO. You were always polite with your reminders that I hadn't submitted my
packing slips in months.
"I'm not sure what is more amazing, that the people I've met at MIT are as weird as I expected
or that I was able to find people who I had so much in common with." That quote is attributed to
Brower, who couldn't have put it any better. Thanks to all of the great friends I've made at MIT,
specifically the trivia team (Kevin and Jenny, Nate, Dave, and Matt), the lunch group (Melanie,
John, Kurt, and Sohan), and Kevin and Rachel Krogman for the Derby and Holiday parties that
brought us all back to our "Louisville" roots.
I would also like to thank Christos Tsokos for thoughtful discussion. It was your suggestion
nearly 3 years ago that led me to work with CDK inhibitors, which eventually formed the
backbone of my thesis. Although that conversation has had an immeasurable impact on my
work, in comparison with others we have had, it was one of the least important. Christos, thank
you for being a true friend.
Lastly, I want to thank Leslie Mebane. It is rare to have the opportunity to thank one's
significant other for contributions made to a thesis. Thank you for lending your time and
microscopy expertise. Without you, the microscope images in Chapter 6 would not have been
possible. More importantly, your love and support over this past year have been amazing. I
couldn't have done this without you.
TABLE OF CONTENTS
ABSTRACT ..................................................................
3
...-...---......
.......
DEDICATION ..............................................................
ACKNOW LEDGEMENTS .......................................................................
........
5
.....
7
TABLE OF CONTENTS.................................................................
... 9
LIST OF FIGURES........................................................................
...
LIST OF TABLES ..................................................................
...13
........... 15
1 INTRODUCTION ......................................................................
1.1
1.2
1.3
1.4
2
3
BACKGROUND .............................................-----..----------------------------.................................
17
17
18
--....................................................
-......
MOTIVATION .........................................-18
..........................
..
THESIS OBJECTIVES ...........................................
19
THESIS ORGANIZATION ..........................................................................
21
LITERATURE REVIEW ...............................................................................
.................... 21
2.1 DEFINING PRODUCTIVITY ..................................................
22
2.2 INCREASING INTEGRATED VIABLE CELL DENSITY (IVCD) ...........................................
22
2.2.1 Medium Design andNutritional Control..............................................................
2.2.2 Anti-apoptosis Engineering....................................................................................23
23
2.2.2.1 Gene overexpression......................................................................................
25
2.2.2.2 RNA interference (RNAi) ..................................................................................
2.3 INCREASING SPECIFIC PRODUCTIVITY THROUGH CONTROLLED PROLIFERATION............26
28
2.3.1 Cell Cycle Overview .............................................................................................
33
2.3.2 Hypothermic Cell Culture ......................................................................................
34
2.3.3 Culture A dditives ...................................................................................................
36
2.3.4 CellularEngineering.............................................................................................
38
2.3.5 Cell Cycle P hase....................................................................................................
MATERIALS AND METHODS.....................................43
43
43
..........................
3 .1.1 CellL in es .......................................................................................
3.1.2 Culture Medium and Maintenance.........................................................................43
43
3.1.2.1 Adherent Cell Cultures ....................................................................................
44
3.1.2.2 Suspension Cell Cultures...............................................................................
44
.................................................................................
3.1.2.3 Cell Bank Maintenance
45
3.1.3 Cell Enum eration....................................................................................................
3.1.3.1 Trypan Blue Staining......................................................................................45
45
3.1.3.2 Guava ViaCount ............................................................................................
46
.............................................
Plates
Culture
3.1.4 Pseudo-perfusionCulture in Tissue
46
3.1.5 Fed-batch Culture in Shake Flasks ........................................................................
47
Concentration.................................
Lactate
3.1.6 Measuring Glucose, Glutamine and
47
3.2 CYCLIN-DEPENDENT KINASE ATP-COMPETITIVE INHIBITORS .......................................
49
......
3.3 MRNA ANALYSIS...........................................................................
3.1
CELL CU LTURE .......................................................----..-
.. --------------------------------------------
3.3.1
3.3.2
3.3.3
3 .3 .4
3.3.5
3.3.6
3.4
RNA Pur f cation .......................................................................................................
RNA Quantificationand Quality Assessment ........................................................
First-StrandcDNA Synthesis..................................................................................50
R T-P CR ......................................................................................................................
Real-time PCR Quantification of Ccnel and /-Actin cDNA Levels .....................
CalculatingRelative mRNA Expression...............................................................
49
49
50
51
58
CYCLIN El sIRNA METHODOLOGY ..............................................................................
58
3.4.1 Cyclin Sequencing .................................................................................................
3.4.2 Cyclin El siRNA Design........................................................................................
3.4.3 PreparationofsiRNA Duplexes ............................................................................
3.4.4 siRNA Transfection and RNA Collection................................................................61
3.5 CREATION OF AN INDUCIBLE SHRNA IFN-y CELL LINE ....................................................
3.5.1 PlasmidDescription and Design...........................................................................
3.5.2 PlasmidProduction and Purification....................................................................
3.5.3 Transfection and Selection of Stable Cell Lines ....................................................
3.5.4 Stable Cell Line Screening: tTS Expression...........................................................68
3.5.5 Stable Cell Line Screening: Inducible shRNA Expression ....................................
3.6 IFN -y EL ISA .....................................................................................................................
3.7 CALCULATING IFN-y SPECIFIC PRODUCTIVITY .............................................................
3.7.1 Specific Productivity, qp ..........................................................................................
59
61
61
3.7.2 DifferentialSpecific Productivity, qp sif5....................................................................
3.8 CELL CYCLE ANALYSIS.................................................................................................73
3.9 IMMUNOSTAINING AND CELL IMAGING .........................................................................
3.10 GENOMIC DNA PURIFICATION AND QUANTIFICATION ................................................
3.11 MEASUREMENT OF INTRACELLULAR PROTEIN CONTENT.............................................76
3.12 NOTE ON STATISTICAL ANALYSIS/SIGNIFICANCE ........................................................
4 CDK2-CCNE1 TARGET VALIDATION ....................................................
4 .1
4.2
4.3
4 .4
IN TR OD U CTION ..................................................................................................................
CDK2 INHIBITION WITH A SELECTIVE ATP-COMPETITIVE INHIBITOR ............................
CcNEI SIRNA KNOCKDOWN........................................................................................
C ON CLU SION S ...................................................................................................................
62
62
68
68
70
72
72
73
73
74
75
76
77
77
78
82
92
5 STABLE SHRNA EXPRESSING CELL LINE: A PATH FORWARD ....... 93
5.1
IN TROD U CTION ..................................................................................................................
93
5.2
5.3
5.4
PSINGLE-TTS-ANTI CCNE1 SHRNA ...............................................................................
94
5.5
TETRACYCLINE-CONTROLLED TRANSCRIPTIONAL SUPPRESSOR (TTS) CELL LINE ............ 96
PSILENCER-TETO 7 -CMV-ANTI CCNE1 SHRNA EXPRESSING CELL LINE ........................ 102
C ON CLU SION S .................................................................................................................
114
6 SHORT TERM CDK INHIBITION: GROWTH, CELL CYCLE, AND
PRODUCTIVITY ............................................................................................
6.1
6.2
6.3
6.4
6.5
IN TRODU CTION ................................................................................................................
115
115
116
RELATIONSHIP BETWEEN SPECIFIC PRODUCTIVITY AND CELL CYCLE DISTRIBUTION ..... 130
RELATIONSHIP BETWEEN SPECIFIC PRODUCTIVITY AND SPECIFIC GROWTH RATE .......... 133
FURTHER CHARACTERIZATION OF INHIBITOR CDK2IV .....................................................
137
CDK INHIBITOR CHARACTERIZATION .............................................................................
6.6
C ON CLU SION S .................................................-----..-.
-------------------------------------------.------
146
INCREASING TOTAL PRODUCTIVITY THROUGH CDK...........149
..... 149
INHIBITION.......................................................................--149
7.1 IN TRODU CTION ..................................................---....----.-.------.---.------------.------.-----.-.------.--149
7.2 ADDITION OF CDK INHIBITORS IN BATCH CULTURES .....................................................
7
7.3
7.4
7.5
8
ADDITION OF INHIBITOR CDK2IV IN A MODIFIED BATCH CULTURE ..................................
ADDITION OF INHIBITOR CDK2IV IN A MODIFIED FED-BATCH CULTURE .........................
CONCLUSIONS ....................................................----.....................................................
CONCLUSIONS AND RECOMMENDATIONS ....................
8.1 THESIS CONCLUSIONS ......................................................
8.2 RECOMMENDATIONS FOR FUTURE WORK.......................................................
153
158
164
167
167
169
169
8.2.1 Inducible shRNA Expression Systems......................................................................
1 70
....
..
...................................
8.2.2 Overexpression of m iRNA .....................................
1 71
8.2.3 Screeningfor Less Toxic Inhibitors.........................................................................
171
...................................
Culture
Cell
Arrested
Growth
8.2.4 Optimized Feed Medium for
172
8.2.5 InhibitorAddition in Perfusion Culture ..................................................................
1 72
8 .2 .6 Con clusion ...............................................................................................................
NOMENCLATURE..............................................................................................175
REFERENCES........................................................................................179
APPENDIX ................................................................................
11
-........
191
12
LIST OF FIGURES
FIGURE 2-1. REGULATION OF THE G1 TO S-PHASE CHECKPOINT IN THE MAMMALIAN CELL CYCLE.31
FIGURE 2-2. REGULATION OF THE G2 TO M-PHASE CHECKPOINT IN THE MAMMALIAN CELL CYCLE.
.3 2
. ----------------------------------------- .---------............................ .........................................................
FIGURE 3-1. REAL-TIME PCR FLUORESCENCE VERSUS PCR CYCLE NUMBER. ........................... 54
FIGURE 3-2. THRESHOLD CYCLE (CT) AS A FUNCTION OF THE LOG OF DNA COPY NUMBER...........55
FIGURE 3-3. MELTING CURVE ANALYSIS...............................................56
64
FIGURE 3-4. PLASMID MAP OF PSINGLE-TTS-SHRNA VECTOR. ............................................
FIGURE 3-5. PLASMID MAPS OF PTTS-NEO AND A MODIFIED PSILENCER 4.1 VECTOR.................65
66
.... ..........................
FIGURE 3-6. THE TTS SYSTEM............................................
FIGURE 3-7. PLASMID MAP OF THE MODIFIED PSINGLE VECTOR, PSINGLE-NO TTS-ANTI-LUC
71
SHRN A ..................................................................-.........................................................
FIGURE 4-1. GROWTH CURVES OF ADHERENT CULTURES WITH OR WITHOUT THE ADDITION OF 2 [iM
80
- - - - - - --.....................................................
INHIBITOR CDK2III. ............................................--..-..
FIGURE 4-2. IFN-y PRODUCTION VERSUS INTEGRATED VIABLE CELL DENSITY (IVCD) WITH AND
81
WITHOUT THE ADDITION OF 2 IM INHIBITOR CDK2III. .................................................
FIGURE 4-3. RELATIVE CCNE] MRNA EXPRESSION IN CHO CELLS TRANSFECTED WITH 13 UNIQUE
86
SIR N AS . .................................................................................................................................
FIGURE 4-4. GRAPHICAL REPRESENTATION OF FIGURE 4-3..........................................87
FIGURE 4-5. CONSISTENCY OF RELATIVE CcNE1 MRNA EXPRESSION FOLLOWING TRANSFECTION
88
W ITH MOST EFFECTIVE SIRN A S ..........................................................................................
97
5-1. RT-PCR OF TTS EXPRESSING SINGLE CELL COLONIES. ............................................
100
5-2. LUCIFERASE KNOCKDOWN IN TTS EXPRESSING CELL LINES. ...................................
FIGURE 5-3. INDUCTION OF LUCIFERASE KNOCKDOWN IN TTS-2..................................................101
FIGURE 5-4. FIRST ROUND SCREEN OF PSILENCER-TETO 7-ANTI CCNEl SHRNA EXPRESSING SINGLE
-----......................................................-- 104
CELL COLONIES......................................................
FIGURE 5-5. SECOND ROUND SCREEN OF BEST PERFORMING SINGLE CELL COLONIES FROM THE FIRST
FIGURE
FIGURE
105
. - - - - - . - - --......................................................
ROUND SCREEN. .................................................DOXYCYCLINE.
OF
LEVELS
INCREASING
TO
FIGURE 5-6. DOSE-RESPONSE OF SINGLE CELL COLONIES
10 7
.............................................................................................................................................
100
OF
ADDITION
THE
WITHOUT
OR
WITH
CLONES
CELL
SINGLE
FIGURE 5-7. GROWTH CURVES OF
12
....
NG MUL DOXYCYCLINE......................................................---............
CELL GROWTH CURVES IN THE PRESENCE OF INHIBITORS CDK2III AND CDKlIV......... 118
CELL GROWTH CURVES IN THE PRESENCE OF INHIBITORS CDK4 AND CDK2IV............ 119
CELL CYCLE DISTRIBUTION IN EXPONENTIALLY GROWING CELLS. ........................... 123
CUMULATIVE IFN-y PRODUCTION PLOTTED AGAINST INTEGRATED VIABLE CELL
129
DENSITY (IVCD) FOR EACH INHIBITOR .............................................................
CYCLE
CELL
AND
FIGURE 6-8. CORRELATIONS BETWEEN NORMALIZED SPECIFIC PRODUCTIVITY
132
PHASE FOLLOWING INHIBITOR ADDITION. ..................................................................
SPECIFIC
FIGURE 6-9. COR RELATION BETWEEN NORMALIZED SPECIFIC PRODUCTIVITY AND
FIGURE 6-1.
FIGURE 6-2.
FIGURE 6-3.
FIGURE 6-7.
GROWTH RATE FOLLOWING INHIBITOR ADDITION. ..............................................................
135
FIGURE
6-10.
FIGURE
6-11.
FIGURE
6-14.
THE EFFECT OF NORMALIZED SPECIFIC PRODUCTIVITY AND SPECIFIC GROWTH RATE
ON TOTAL IFN -y PRODUCTION . .............................................................................................
136
CELL CYCLE DISTRIBUTIONS FOLLOWING THE ADDITION OF THE INHIBITOR CDK2IV.
.............................................................................................................................................
13 9
FIGURE 6-12. 60X IMAGES OF STAINED 7-CHO CELLS 24 HOURS POST-INHIBITOR TREATMENT... 140
FIGURE 6-13. CELL GROWTH CURVES FOLLOWING THE ADDITION AND SUBSEQUENT REMOVAL OF
IN H IBITO R CD K 2IV . ...............................................................................................................
143
CUMULATIVE IFN-y PRODUCTION PLOTTED AGAINST INTEGRATED VIABLE CELL
DENSITY (IVCD) FOLLOWING THE ADDITION OF INHIBITOR CDK2IV.....................................144
FIGURE 6-15. RELATIVE GENOMIC DNA CONTENT FOLLOWING INHIBITOR CDK2IV ADDITION. ... 145
7-1. SUSPENSION y-CHO GROWTH AND VIABILITY CURVES IN THE PRESENCE OF
IN H IB IT O R S. ..........................................................................................................................
FIGURE
FIGURE
7-2.
CDK
15 1
CDK INHIBITORS............152
FIGURE 7-3. CUMULATIVE IFN-7 TITER PLOTTED AGAINST INTEGRATED VIABLE CELL DENSITY
FOR EA CH IN H IBITOR .............................................................................................................
152
FIGURE 7-4. SUSPENSION CHO-IFNy GROWTH AND VIABILITY CURVES IN THE PRESENCE OF CDK
INHIBITORS IN A MODIFIED BATCH CULTURE .........................................................................
154
CUMULATIVE IFN-y TITER FOLLOWING THE ADDITION OF
FIGURE 7-5. CUMULATIVE IFN-y TITER FOLLOWING THE ADDITION AND REMOVAL OF A CDK
INHIBITOR IN A MODIFIED BATCH CULTURE...........................................................................156
FIGURE 7-6. CUMULATIVE IFN-y TITER PLOTTED AGAINST INTEGRATED VIABLE CELL DENSITY
FOLLOWING THE ADDITION AND REMOVAL OF A CDK INHIBITOR IN A MODIFIED BATCH
CU L TUR E ...............................................................................................................................
15 6
FIGURE 7-7. TOTAL PROTEIN CONTENT FOLLOWING THE ADDITION OF INHIBITOR CDK2IV. .......... 157
CHO-IFNy GROWTH AND VIABILITY CURVES IN THE PRESENCE OF
INHIBITOR CDK2IV IN A MODIFIED FED-BATCH CULTURE.......................................................159
FIGURE 7-9. OVERLAY OF MODIFIED BATCH AND FED-BATCH CHO-IFNr' SUSPENSION GROWTH
FIGURE 7-8. SUSPENSION
CURVES FOLLOWING THE ADDITION OF INHIBITOR CDK2IV. ..................................................
160
FIGURE 7-10. CUMULATIVE IFN-y TITER FOLLOWING THE ADDITION AND REMOVAL OF INHIBITOR
CK2IV IN A MODIFIED FED-BATCH CULTURE..........................................................................162
FIGURE 7-11. CUMULATIVE IFN-y TITER PLOTTED AGAINST INTEGRATED VIABLE CELL DENSITY
FOLLOWING THE ADDITION AND REMOVAL OF INHIBITOR CDK2IV IN A MODIFIED FED-BATCH
CU L TU RE ...............................................................................................................................
FIGURE 7-12. OVERLAY OF CUMULATIVE IFN-7 TITER PLOTTED AGAINST IVCD FOR MODIFIED
BATCH AND FED-BATCH CULTURES FOLLOWING THE ADDITION OF INHIBITOR CDK2IV. ........
16 2
163
LIST OF TABLES
TABLE 2-1. SUMMARY OF METHODS TO IMPROVE VOLUMETRIC PRODUCTIVITY BY INCREASING THE
IVCD .....................................................................----------------------------------------.........................
TABLE 2-2. SUMMARY OF METHODS TO IMPROVE VOLUMETRIC PRODUCTIVITY BY INCREASING
41
SPECIFIC PRODUCTIVITY, Qp...................................................................--42
3-1. 1C5 0 AND K, VALUES OF ATP-COMPETITIVE CDK INHIBITORS ..................................... 48
52
TABLE 3-2. REAL-TIM E PCR PRIMERS .......................................................................................
TABLE 3-3. QRT-PCR EFFICIENCY FOR CDNA STANDARD CURVES............................................57
TABLE 3-4. PRIMER SEQUENCES FOR THE AMPLIFICATION OF CYCLIN CDNA TEMPLATES.............60
TABLE 3-5. SHRNA HAIRPIN SEQUENCES FOR INSERTION INTO INDUCIBLE EXPRESSION VECTORS.67
TABLE
4-1. A SUMMARY OF THE EFFECT OF INHIBITOR CDK2III ON SPECIFIC..................................81
TABLE 4-2. CCNE1 SIRNA SEQUENCES DESIGNED USING MODIFIED TUSCHL RULES DEVELOPED BY
85
REYNOLDS ET AL. (2004) AND UI-TEI ET AL. (2004) ..........................................................
TABLE 4-3. FOLD-INCREASE IN Qp, DIFF RELATIVE TO A NON-SILENCING CONTROL FOLLOWING
...... 91
SIRNA KNOCKDOWN OF CcNEJ EXPRESSION (N=2) ..............................................
TABLE
TABLE 5-1. SCREENING SUMMARY OF INDUCED CcNE1 KNOCKDOWN FOLLOWING 100 NG ML'
109
...........................
DOXYCYCLINE ADDITION ..................................................
1
CELL
SINGLE
TO
ADDITION
TABLE 5-2. SUMMARY OF THE EFFECTS OF 100 NG ML DOXYCYCLINE
CLONES.......................................................-----....................................................................
TABLE
6-1.
TIME-INTEGRATED (WEIGHTED) CELL CYCLE DISTRIBUTION .....................................
TABLE Al. SEQUENCING SUMMARY OF KNOWN
CHO CYCLINS
.............................................
13
127
191
16
1
INTRODUCTION
1.1
Background
There are currently over 165 biopharmaceuticals approved for use in humans with a projected
market size of $70 billion by the end of 2010 (Durocher and Butler, 2009; Walsh, 2006).
Approximately 60-70% of these are recombinant proteins produced in mammalian cells, and the
most common production host is the immortalized Chinese hamster ovary (CHO) cell (Birch and
Racher et al., 2006; Durocher and Butler, 2009; Hacker et al., 2009; Wurm, 2004). In 2006,
CHO cells were used to produce 62 of the approximately 107 protein therapeutics (58%)
manufactured in mammalian cells (Walsh, 2006).
Mammalian cell culture is the preferred
method of producing recombinant proteins because of its inherent ability to provide posttranslational modification, specifically glycosylation, to secreted proteins.
CHO cells, in
particular, produce glycan structures that are very similar to those naturally isolated from humans
(Walsh and Jefferis, 2006).
In addition to their ability to perform post-translational modifications, CHO cells are used in
industrial scale production of therapeutic proteins for a number of other reasons. CHO cells
allow for the stable introduction of chromosomally integrated heterologous transgenes (Schimke,
1984), they have the ability to adapt to protein-free suspension culture (Meents et al., 2002) and
there are readily available dihydrofolate reductase mutants (DHFR~) that enable the amplification
of recombinant product-encoding regions of chromosomes (Kaufman et al., 1983; Urlaub and
Chasin, 1980) which results in high expression levels (Fox, 2005a). In this work, we use a CHO
cell line expressing interferon-gamma (IFN-y) created from a DHFR- CHO cell line (Scahill et
al., 1983).
One disadvantage of using CHO cells, when compared with bacteria and yeast cells, is that they
produce comparatively smaller amounts of recombinant proteins. Over the past two decades,
order-of-magnitude improvements have been made to the productivity of CHO cells (Wurm,
2004).
However, work is still ongoing to improve the production of glycoproteins from
mammalian cells by improving glycosylation quality and consistency, and increasing overall
productivity.
1.2
Motivation
It is estimated that 15 different protein therapeutics with total sales of over $20 billion will lose
patent protection over the next 5 years (Lanthier et al., 2008). Also, according to the PhRMA,
there are currently more than 600 biopharmaceuticals currently in the clinic. Any improvements
that can be made in the production of therapeutic proteins will result in substantial cost savings
for the biotechnology industry and patients taking these medications.
Our work specifically
focuses on improving total volumetric recombinant protein production in CHO cells.
1.3
Thesis Objectives
The central goal of this thesis is to develop new ways of increasing total volumetric productivity
through induced growth arrest. Within this main goal, the thesis has three major objectives.
First, to determine if the inhibition or silencing of the CcnE 1-CDK2 protein complex is sufficient
to induce growth arrest and subsequently increase specific productivity.
Second, to better
understand the relationship between the specific growth rate, cell cycle phase, and the specific
productivity of IFN-y. Third, to develop a method to improve total productivity through growth
arrest by inhibiting the CcnEl-CDK2 protein complex.
1.4
Thesis Organization
This thesis is divided into eight chapters. Chapter 2 provides a literature review of the previous
methods used to improve productivity in CHO cell cultures. In Chapter 3, the materials and
methods used in this thesis are explained in detail. Chapter 4 demonstrates that the silencing or
inhibition of the CcnEl-CDK2 complex results in growth arrest and increases specific IFN-y
productivity.
Chapter 5 details the work performed towards the creation of a stable cell line
expressing shRNA against CcnE1. In Chapter 6, the relationship between specific growth rate,
cell cycle distribution, and specific productivity is analyzed. In addition, the characterization of
an interesting CDK2 inhibitor, cdk2iv, is described. In Chapter 7, the inhibitor cdk2iv is used to
improve total volumetric productivity of IFN-y in suspension culture. Chapter 8 presents the
concluding remarks and recommendations for future research. A nomenclature section and a list
of cited references follow Chapter 8. The mRNA sequences of CHO cyclins are presented in the
Appendix.
20
2
LITERATURE REVIEW
Our main goal in this thesis is to develop methods for improving total recombinant protein
production. Towards this end, it is useful to better understand the work that has already been
done in this area. To begin, we would like to briefly describe how productivity is defined and
what key factors contribute to it.
2.1
Defining Productivity
The specific productivity, qp (g protein cell-' day-'), is a measure of the amount of protein
produced per cell per unit of time. At any give time, it is defined as the slope of the production,
P (g protein mL'), vs. time curve, divided by the total number of viable cells,
dP
=
dt
qpN,,ajlf
Nviable
(viable cells
(2-1)
Because we assume that all of the recombinant protein that is produced is secreted from the cell,
and not released by cell death or following cell lysis, we can also assume that the qp remains
constant over the course of a cell culture (Renard et al., 1988). This allows us to define the total
volumetric production of recombinant protein, P, as:
P = qpJ Ndt = qp -IVCD
(2-2)
The total amount of protein produced is therefore directly related to the specific productivity, qp,
and the Integrated Viable Cell Density, IVCD (cells day mL'), which can be visualized as the
area under the viable cell density curve (Renard et al., 1988). Therefore, in order to increase
total volumetric production one must increase the specific productivity, the IVCD, or both. We
will focus this review on past approaches that have led to increases in total volumetric
productivity. A summary of all of the methods used to increase total volumetric productivity is
shown at the end of this chapter in Tables 2-1 and 2-2.
2.2
Increasing Integrated Viable Cell Density (IVCD)
The approaches for improving productivity by increasing the IVCD in a cell culture generally
fall into one of two categories: (1) medium design and nutritional control and (2) cellular
engineering.
2.2.1
Medium Design and Nutritional Control
Nutritional control and medium design are ways that cell cultures can be improved without
changing or modifying the CHO cells that are used in a production process. Using cell culture
medium to increase the IVCD was one of the major motivations behind fed-batch cell culture
development. It is well understood that ammonia and lactate, waste metabolites of glycolysis
and glutamine catabolism, inhibit cell growth which results in a decrease in the maximum
achievable cell density and limits recombinant protein production (Hassell et al., 1991; Lao and
Toth, 1997). The presence of high concentrations of glucose in culture medium results in the
majority being converted to lactate by lactate dehydrogenase (LDH) (Kim and Lee, 2007;
Neermann and Wagner, 1996). Ammonia is the direct byproduct of glutamine degradation to
glutamate by glutaminase and the end product of glutamine catabolism (Glacken et al., 1986;
Nelson and Cox, 2000). By feeding glucose, glutamine, and other nutrients into cell cultures at
controlled rates, waste metabolite formation can be minimized.
Stoichiometric fed-batch
cultures have been used in a number of different cell culture systems to drastically extend culture
time, to increase the maximum achievable cell density, and to improve the overall production of
recombinant proteins (Xie et al., 1997; Xie and Wang, 1994).
Xie et al. (1997) performed
nutrient feeding every 12-24 hours, which resulted in a 10-fold increase in IVCD and a resulting
4.5-fold increase in the final IFN-y titer. Although an improvement from batch culture, the
addition of nutrients every 12-24 hours still results in the addition of excess glucose and
glutamine to a cell culture. Improved dynamic online feeding strategies have been developed to
further tighten control of nutrient feeding, resulting in more efficient metabolism (Glacken et al.,
1986; Wong et al., 2004; Zhou et al., 1995). As an example, in a 12-hour feeding strategy, the
glutamine setpoint is typically 1 mM (Lim et al., 2006). However, by dynamically feeding to a
glutamine set point of 0.3 mM, Wong et al. (2004) increased total IFN-y productivity by 10-fold.
2.2.2 Anti-apoptosis Engineering
The prolonged culturing of cells is almost always limited by cell death caused by a multitude of
factors including nutrient deprivation, oxygen limitation, and shear stress. The largest source of
cell death in bioreactors has been attributed to apoptosis or programmed cell death (Goswami et
al., 1999; Vives et al., 2003). Apoptosis occurs in fed-batch cultures even when there are no
oxygen or nutrient limitations, and is the result of a complex network of signaling pathways that
ultimately activate cyteine aspartate proteases (caspases) that perform the final stages of cell
death (Wong et al., 2006a; Majors et al., 2007). Inhibiting or decreasing apoptotic signaling can
extend cell cultures, leading to increases in IVCD.
2.2.2.1 Gene overexpression
Possibly the most common genetic approach to minimizing apoptotic signaling is through the
overexpression of Bcl-2 (Goswami et al., 1999; Meents et al., 2002; Tey et al., 2000) and Bcl-xL.
(Chiang and Sisk, 2005; Meents et al., 2002). Both Bcl-2 and Bcl-xL, are characterized as antiapoptotic proteins and act to maintain the mitochondria membrane potential and prevent the
release of cytochrome c during apoptotic insults (Majors et al., 2007).
Although the
overexpression of both Bcl-2 and Bcl-xL has been shown to increase cell viability and extend
culture time, only the overexpression of Bcl-xL consistently results in an increase in overall
productivity (Meents et al., 2002). Chiang and Sisk (2005) increased both specific and total
productivity of a monoclonal antibody by 2-fold through the overexpression of Bcl-xL.
In
addition, the overexpression of Bcl-xL has been shown to increase specific productivity,
contributing to increases in product titer (Fussenegger et al., 1998; Meents et al., 2002). The use
of selection markers, such as neomycin, has been shown to enhance naturally occurring levels of
Bcl-2 and makes it more difficult to determine the effect of Bcl-2 overexpression on productivity
(Tey et al., 2000).
Another approach towards increasing the IVCD is the overexpression of naturally occurring
caspase inhibitors like the X-linked inhibitor of apoptosis protein (XIAP) (Sauerwald et al.,
2002).
While the overexpression of XIAP has been shown to inhibit apoptosis and protect
against various insults including serum deprivation and viral infection, the impact on
recombinant protein production is not known.
With the advent of new genomic tools, production cell lines can be examined in entirely new
ways (Kantardjieff et al., 2009). Most recently, the transcriptome analysis of apoptosis signaling
pathways in fed-batch cultures, showed downregulation of Faim, a pro-survival gene, and
upregulation of FADD, which is involved in death receptor apoptosis signaling, upon entry into
stationary phase (Wong et al., 2006a). By overexpressing Faim and a dominant negative of
FADD (FADD DN), apoptosis was inhibited, resulting in increases in. IVCD and 1.5-fold
increases in recombinant IFN-y product titer (Wong et al., 2006b).
Dominant negative
overexpression is one of the easiest ways to down regulate the activity of a particular protein.
However, it is often the case that the functional domains of particular proteins are not well
defined, making it difficult to design a dominant negative approach to down-regulation (Wong et
al., 2006b). In these cases, RNA interference represents a potential solution.
2.2.2.2 RNA interference (RNAi)
RNA interference (RNAi) refers to the specific post-transcriptional down-regulation of gene
expression by small-double stranded RNA (Dykxhoorn et al., 2003; McManus and Sharp, 2002).
Originally discovered in C. elegans (Fire et al., 1998), RNAi has been shown to occur in a
number of other cell types including CHO cells. The mechanism of RNAi is comprised of two
main steps: (1) the processing of long double-stranded RNA by the RNase III-like enzyme Dicer
to 21-23 bp small interfering RNA (siRNA) and (2) the cleavage of the homologous mRNA
through incorporation of siRNA into RNA-induced silencing complex (RISC). (Dykxhoorn et
al., 2003).
The use of RNAi has been used extensively in the recent past to improve the
productivity of CHO cells (Wu, 2009). One striking advantage of RNAi when compared with
gene overexpression is that it does not overcharge the translational machinery of the host cell
(Muller et al., 2008).
A number of groups have recently targeted the pro-apoptotic genes Bax and Bak (Lim et al.,
2006), Alg-2 and Requiem (Wong et al., 2006b), and Caspase-3 and Caspase-7 (Sung et al.,
2007) with RNAi.
The simultaneous knockdown of Bax and Bak, increased resistance to a
variety of apoptotic stimuli like nutrient depletion and high-osmolality medium, extended the
culture lifespan, and increased total IFN-y product titer by 35% (Lim et al., 2006). The separate
knockdown of Alg-2 and Requiem suppressed caspase activation, drastically increased the
maximum achievable cell density in a fed-batch bioreactor, and increased overall IFN-y product
titer by 2.5-fold (Wong et al., 2006b). Lastly, the simultaneous knockdown of caspase-3 and
caspase-7 increased the achievable maximum cell density, extended the culture lifespan, and
increased the final product titer of thrombopoietin by 1.5-fold in the presence of 1 mM sodium
butyrate (Sung et al. 2007).
Often, anti-apoptotic engineering increases IVCD mainly through the extension of culture time
and not by increasing the maximum attainable cell density.
In these cases, the benefits of
increased product titer must be balanced with the cost of bioreactor maintenance.
2.3
Increasing Specific Productivity through Controlled Proliferation
The alternative to increasing the IVCD, either by increasing the maximum achievable cell density
or culture lifetime, is to increase the amount of recombinant protein produced per cell per time.
This can be done in a number of ways, including by improving expression technology (Ng et al.,
2007; Prentice et al., 2007b), by secretion engineering (Tigges and Fussenegger, 2006), by host
cell development (Prentice et al., 2007a), and by targeted vector insertion (Barron et al., 2007).
All of these techniques are considered outside the scope of this thesis. Another common method
used to increase specific productivity is through controlled proliferation. Controlled proliferation
has a number of advantages: (i) it extends culture times, sometimes resulting in increases in
IVCD, (ii) it lowers the release of intracellular proteases and glycosidases resulting in improved
product quality, (iii) it decreases medium and nutrient consumption, (iv) it lowers genetic drift of
the cell population because of reduced cell growth, and most importantly (v) it increases specific
productivity as intracellular resources can be redirected towards product production in the
absence of growth (Fussenegger and Bailey, 1999). We will be focusing on this last point for the
remainder of this thesis.
The potential of controlled proliferation was demonstrated in the pioneering modeling and
experimental work of Suzuki and Ollis (1989; 1999), who showed an inverse relationship
between growth and productivity (Fussenegger and Bailey, 1999). This initial work in controlled
proliferation involved the addition of toxic chemicals to the culture medium of hybridoma cells,
including the DNA-synthesis inhibitors hydroxyurea and thymidine (Al-Rubeai at. al., 1992;
Suzuki and Ollis, 1990), the protein synthesis inhibitors cycloheximide and potassium acetate,
and the rRNA synthesis inhibitor Actinomycin D (Suzuki and Ollis, 1990).
Hydroxyurea,
thymidine, and potassium acetate addition all led to a slowed growth and a subsequent increase
in specific productivity.
However, the toxicity of these compounds prevented extended
cultivation in their presence.
Interestingly, the addition of chemicals inhibiting protein
elongation and rRNA synthesis produced non-growth or positive-growth associated responses
(Suzuki and Ollis, 1990). It is important to note that the addition of some chemicals may slow
growth through metabolic or unknown mechanisms that are detrimental to recombinant protein
production, and should not be used in controlled proliferation studies.
While most of this pioneering work was performed in hybridoma cells, an inverse relationship
between growth and productivity in CHO cells has also been shown by a number of researchers.
The first such demonstration was performed by Jenkins and Hovey (1993) where the use of
temperature to control growth resulted in increases in the productivity of recombinant tissue
inhibitor of metalloproteinases (TIMP).
2.3.1
Cell Cycle Overview
We will begin with a brief overview of cell cycle progression because the mechanisms involved
are critically important in controlled proliferation strategies. The cell cycle can be described as
an organized series of events that leads to cell division and the creation of two daughter cells
each with a pair of chromosomes identical to the parent cell (Lodish et al., 2004). The cell cycle
itself was originally thought to compose two distinct phases: interphase and mitosis. Interphase
is further comprised of three phases, S-phase where the genetic material of the cell is replicated
and two gap phases, G1 and G2, where the cell prepares for entry into either S-phase or mitosis
(M-phase) respectively (Sunley and Butler, 2010; Vermeulen et al., 2003). Progression through
the cell cycle is tightly controlled by a network of signaling pathways referred to as cell cycle
checkpoints that are shown in Figures 2-1 and 2-2 (Lukas et al., 2004). The key regulatory
proteins in this process are the cyclin-dependent kinases (CDK), which are activated following
the association with their positive regulatory subunit, the cyclin (Ekholm and Reed, 2000; van
den Heuvel and Harlow, 1993).
CDK activity can be repressed by cell cycle inhibitory proteins (CKI), which either bind to the
CDK alone or the CDK-cyclin complex (Vermeulen et al., 2003). There are two distinct families
of CKIs, the INK4 family (p1 5 INK4b
INK4a
INK4c
4
INK d),
which specifically inactive
the G1 CDKs (CDK4 and CDK6) prior to cyclin binding, and the Cip/Kip family (p21 wafi/cipI and
p27 Cip2), which specifically inactivate G1 CDK-cyclin complexes after cyclin binding (Harper et
al., 1993; Toyoshima and Hunter, 1994; Vermeulen et al., 2003). To prevent entry into S-phase
with damaged DNA, checkpoint kinases phosphorylate Cdc25A phosphatase and the p53
transcription factor (Kastan et al., 1991; Lukas et al., 2004). The phosphorylation of Cdc25a
prevents the activating dephosphorylation of CDK2 (Falck et al., 2001; Mailand et al., 2000).
Phosphorylation of p53 contributes to its stabilization and increased activity. The key effector of
p53-dependent transcription is the p21 wafi/cip CKI (El-Deiry et al., 1994; Lukas et al., 2004).
The accumulation of p21wafl/ciPl to levels capable of blocking the Gi/S-promoting complex
CDK2-cyclin E (CKD2-CcnE) can require several hours, which complements the more transient
and acute inhibition of CDK2 through Cdc25A. Once cells pass the restriction point (R) in G,
and then enter S-phase they are committed to progress through the entire cell cycle. Additional
controls and checkpoints also mediated by Cdc25A and p53 exist to ensure an orderly sequence
of events (Vermeulen et al., 2003).
The downstream target of G-phase CDK regulation is the retinoblastoma protein (Rb), which
upon phosphorylation leads to the disruption of its complex with histone deacetylase protein
(HDAC) and the release of transcription factors E2F-1 and DP-1. E2F-1 and DP-1 positively
regulate the transcription of genes whose products are necessary for S phase progression (Magae
et al., 1996; Vermeulen et al., 2003; Weinberg, 1995).
Cancer can be described as a breakdown in the cell cycle regulatory process caused by DNA
damage (Kastan and Bartek 2004). This results in fundamental alterations in the genetic control
of cell cycle progression, which often results in unrestrained cell division. Some examples of
these alternations include, inactivation of tumor suppressor genes like pRb and p53, and
mutations of proteins important at different levels of the cell cycle like CDKs, cyclins, CKIs, and
checkpoint proteins (Vermeulen et al., 2003). The evidence that CDKs, their regulators, and
substrates are often targets of genetic alterations in different types of human cancers has
encouraged the search for CDK inhibitors. All of the CDK inhibitors that have been identified
act by competitively inhibiting the binding of ATP to the CDK (Vermeulen et al., 2003). A
larger number of these inhibitors are commercially available, many of which we use in our work
and will be described in more detail later.
Growth Factor
Receptor Activation
1-Ubiquination
Genes:
E2F/DP Target
Tb
A
FOFasL
--- > Apopioss
TRAIL
-
EF2c2.
-RanGAP,
c-Myc. p107,
TK, DHFR,
PCNA. K2A, etc.
-I
'popiois
OFF
ON
Figure 2-1. Regulation of the G, to S-phase checkpoint in the mammalian cell cycle.
Diagram reproduced from Cell Signaling Technology, Inc. (www.cellsignal.com).
PLNuctir Exusio n
cdc,25
sCF
Figure 2-2. Regulation of the G2 to M-phase checkpoint in the mammalian cell cycle.
Diagram reproduced from Cell Signaling Technology, Inc. (www.cellsignal.com).
2.3.2
Hypothermic Cell Culture
Typically, mammalian cells are cultured at 37 *C. However, a number of researchers have
shown that culturing CHO cells at temperatures below 37 "C results in a decrease in specific
growth rate and a subsequent increase in specific productivity (Furukawa and Ohsuye, 1998;
Hendrick et al., 2001; Kaufmann et al., 1999; Yoon et al., 2003).
This increase in specific
productivity has been shown to be due, at least in part, to an increase in mRNA stability (Fox et
al., 2005b; Furukawa and Ohsuye, 1998; Sonna et al., 2002).
In addition to increases in
productivity, decreasing culture temperature causes a specific Go/Gi-phase growth arrest,
suppression of apoptosis, and an overall reduction in metabolism (Moore et al., 1997). The
Go/Gi-phase arrest has been shown to occur through p21 Wavf/cIP by a p53-dependent mechanism
(Ohnishi et al., 1998).
A decrease in specific growth rate is related to a decrease in IVCD and therefore the increase in
specific productivity caused by low temperature cultivation does not necessarily result in an
increase in volumetric productivity. In a number of circumstances, cultivation at 30 "C did not
result in an increase in total recombinant protein productivity (Furukawa and Ohsuye, 1998). In
order to increase total productivity, one must balance decreases in IVCD with increases in qp,
which can be done in one of two ways: (1) a biphasic culture, where cells are grown to an
elevated cell density at 37 C followed by a temperature shift to 30-32 "C, or (2) a slightly
hypothermic culture (i.e. 33-35 0C).
A number of researchers have utilized biphasic growth to improve the production of human
granulocyte macrophage colony stimulating factor (Bollati-Fogolin et al., 2005), t-PA (Hendrick
et al., 2001), secreted alkaline phosphatase (Kaufmann et al., 1999), and an X-amidating enzyme
(Furukawa and Ohsuye, 1999). The time at which the temperature shift occurs can be optimized
to yield the largest possible increase in recombinant protein productivity. In the case of IFN-y
production, Fox et al. (2004) showed that a temperature shift to 32 "C after 3 days of growth
resulted in a 90% increase in total production when compared to a 37 "C control.
Rather than utilizing a temperature shift culture, researchers culturing CHO cells at 35 C were
able to increase the total production of an a-amidating enzyme by 1.8-fold (Furukawa and
Ohsuye, 1998) and researchers culturing CHO cells at 33 "C and lower were able to increase the
total production of erythropoietin in both batch (Yoon et al., 2003) and perfusion cultures (Ahn
et al., 2008) by 2.5- and 6.5-fold, respectively. Lastly, a particularly novel approach, developed
by members in our own lab, involves mutagenizing and selecting for cells that grow under
hypothermic conditions. By growing cells under hypothermic conditions, specific productivity
can be increased without a subsequent decrease in IVCD resulting in a 7.7-fold increase in total
productivity when compared to a 37 "C control (Fox, 2005a; Fox et al., 2005c). This work also
suggests that improvements in specific productivity in low temperature culture may mainly be
caused by increases in mRNA stability rather than growth arrest.
2.3.3
Culture Additives
The addition of chemicals to cell cultures with the purpose of improving specific productivity
began with toxic chemicals like thymidine and hydroxyurea (Suzuki and Ollis, 1990).
The
disadvantages of using these chemicals have been described previously. The most common
culture additive used industrially is sodium butyrate (NaBu), a sodium salt of butyric acid. It has
been used extensively in CHO cells to increase the productivity of t-PA (Hendrick et al., 2001;
Palermo et al., 1991), EPO (Chang et al., 1999), IFN-
(Rodriguez et al., 2005), and other
recombinant proteins (Dorner et al., 1989). It has long been known that butyrate is a reversible
non-competitive inhibitor of histone deacetylase and causes the accumulation of hyperacetylated
histones (Cousens et al., 1979; Riggs et al., 1977). Histones are the DNA-binding proteins that
comprise nucleosomes, which bind DNA and repress transcription in vivo and in vitro. In
unacetylated histones, the positively charged n-terminal lysines interact strongly with negatively
charged DNA phosphates. The addition of butyrate acts to make DNA more accessible, resulting
in an increase in transcription and translation (Berger, 2002; Grunstein, 1997; Jiang and
Sharfstein, 2008). In addition, butyrate is also known to cause a Go/Gi-phase arrest (D'Anna et
al., 1980; Hendrick et al., 2001). It does this in two ways, by activating the p2 1
WAF/Cip1
promoter
in a p53-independent manner (Lagger et al., 2002; Nakano et al., 1997) and by inhibiting
phosphorylation and inducing dephosphorylation of Rb (Buquet-Fagot et al., 1996; Schwartz et
al., 1998).
Unfortunately, the addition of butyrate is also known to induce apoptosis, preventing its use in
extended fermentations (Kim and Lee, 2001). In order to increase total recombinant protein
production, anti-apoptosis engineering methods have been combined with butyrate addition. By
adding butyrate to CHO cells overexpressing Bcl-2 (Kim and Lee, 2001) or silencing Caspase-3
and Caspase-7 (Sung et al., 2007), recombinant protein production was increased by 2- and 1.5fold respectively.
A number of other small molecule additives have been screened for their effect on total
volumetric recombinant protein productivity.
Following an extensive screening of common
nucleotides, nucleosides and bases, Carvalhal et al. (2003b) found that the addition of adenosine
monophosphate (AMP) to CHO cells producing secreted alkaline phosphatase (SEAP) resulted
in a 1.6-fold increase in total productivity. However, the culture time was also extended by more
than 2-fold. Interestingly, it was observed that AMP caused an accumulation of cells in S-phase,
though the exact reason for this accumulation is unknown.
2.3.4
Cellular Engineering
So far we have discussed a number of externally applied methods that induce growth arrest and
subsequently increase the specific productivity of recombinant protein producing cell lines.
These methods, including the lowering of culture temperature and the addition of chemicals to
the culture media, impact the cell cycle signaling network by up and down regulating the
expression of a number of different genes. Genetic engineering, on the other hand, allows for the
specific modification in the expression of a small number of genes. One of the first attempts to
control cell growth genetically was by overexpressing interferon regulatory factor 1 (IRF-1)
(Koster et al., 1995).
IRF-1 acts as a tumor suppressor and its overexpression caused an
inhibition in cell growth.
In addition, reporter gene expression driven by IRF-1 responsive
promoters increased up to 20-fold following overexpression.
However, the effect on total
recombinant protein productivity was not shown, and cell viability was not enhanced nor was the
cell culture extended.
Both sodium butyrate treatment and hypothermic cell culture up-regulate the expression of a
number of CKIs, including: p21ciP1, p 2 7KPJ, and p53. The first successful attempts to induce
growth arrest and increase productivity through genetic means began with the overexpression of
these particular proteins (Fussenegger et al., 1997; Fussenegger et al., 1998; Mazur et al., 1998;
Sunley and Butler, 2010). Initially, the transient transfection of plasmids coexpressing SEAP
and either p21, p27 or p53175P (a p53 mutant showing specific loss of apoptotic function)
inhibited cell proliferation and increased the specific SEAP productivity 4.6-fold, 3.9-fold, and
3.9-fold respectively (Fussenegger et al., 1997).
However, when stably expressed, only p27
resulted in an increase in specific SEAP productivity (Mazur et al., 1998). It wasn't until p21
was stably overexpressed along with the CCAAT/enhancer-binding protein a (C/EBPa) that
growth arrest was induced and multi-fold increases in specific SEAP productivity were observed
(Fussenegger et al., 1998). C/EBPa stabilizes p21 at the protein level, increasing its half-life,
which suggests that it is difficult to stably overexpress p21 to effective levels. Bi et al. (2004),
were able to stably overexpress p21 using a LacSwitch expression system driven by a RSV
promoter, as opposed to the Tet-off/minCMV system used by Mazur et al. (1998), and observed
4-fold increases in specific IgG4 productivity. In all of the above systems, the Gi-phase of the
cell cycle was specifically targeted for arrest.
There are two major disadvantages to the overexpression of CKIs. Although the induced growth
arrest results in an increase in specific productivity, the resulting decrease in cell density (and
IVCD) does not result in a volumetric productivity increase. Secondly, the cells overexpressing
CKIs eventually escape growth arrest, either because of the strong selective pressure to grow or
because of a damaged or genetically unstable expression system. Certainly more work could be
performed in this area to determine if it is possible to increase total volumetric productivity by
inhibiting cell cycle progression with a genetic engineering approach.
Lastly, non-cell-cycle related proteins have also been overexpressed with some success. Cells
trigger an active response to hypothermic culture, resulting in the up and down-regulation of
particular proteins, including the cold-inducible RNA-binding protein (CIRP) (Sonna et al.,
2002). Tan et al. (2008) recently overexpressed CIRP in actively growing cultures at 37 "C, a
temperature at which it is not normally expressed. The overexpression led to a 1.4-fold increase
in both specific and volumetric productivity with no impact on cell growth.
2.3.5
Cell Cycle Phase
In the vast majority of controlled proliferation studies, cells are arrested in the Gi-phase of the
cell cycle because it is believed to be the ideal phase for recombinant protein production. In
some cases, like in hypothermic culture (Furukawa and Ohsuye, 1998; Hendrick et al., 2001;
Kaufmann et al., 1999; Moore et al., 1997; Yoon et al., 2003) and following butyrate addition
(Chang et al., 1999; Hendrick et al., 2001; Palermo et al., 1991; Rodriguez et al., 2005), arrest in
the Gi-phase is a secondary effect of the changes made to the culture. And in other cases, like
CKI overexpreesion (Carvalhal et al., 2003a; Fussenegger et al., 1997; Fussenegger et al., 1998;
Mazur et al,. 1998), arrest is specifically targeted to occur in Gi-phase.
The mechanisms
responsible for increases in specific productivity during G1 have not been described (Sunley and
Butler, 2010). In addition, both S-phase (Carvalhal et al., 2003b; Lloyd et al., 2000; Fox et al.,
2005) and G2/M-phases (Tey and Al-Rubeai, 2005) have been shown to correlate with an
increase in recombinant protein productivity. Clearly, the relationship between cell cycle and
specific productivity during growth arrest is not very well understood. No systematic studies
have been performed using the same expression and culture system to try and elucidate such a
relationship, and work could still be done in this area.
40
Table 2-1. Summary of methods to improve volumetric productivity by incr
Increasing IVCD
Fed-batch
Dynamic Feeding
12 hour sampling
12 hour sampling
On-line Feeding
Wong et al., 2004
Xie et al., 1997
Xie and Wang, 1994
Zhou et al., 1995
Anti-apoptosis Engineering
Gene Overexpression
Bc-XL
Bc/2
XIAP
Faim/Fadd
Chiang and Sisk, 2005
Fussenegger et al., 1998
Meents et al., 2002
Goswami et al., 1999
Meents et al., 2002
Tey et al., 2000
Sauerwald et al., 2002
Wong et al., 2006b
CHO
CHO
Hybridoma
Hybridoma
IFN-y
IFN-y
IgG
1.2-fold
1.1-fold
2.0-fold
10-fold
4.5-fold
11-fold
IgG
-
-
CHO
CHO
CHO
CHO
CHO
CHO
CHO / 293 HEK
CHO
mAb
SEAP
slCAM
IFN-y
sICAM
cB72.3
N/A
IFN-y
2-fold
30-fold*
1.3-fold
2-fold
decreased
no increase
-
CHO
CHO
CHO
IFN-y
IFN-y
hTPO
no increase
RNA Interference
Bax/Bak
Alg2/Requiem
Caspase-3/7
Lim et al., 2006
Wong et al., 2006b
Sung et al., 2007
Note: '-': no data available; *: overexpression of Bcl-xL and p27
-
-
no increase
-
1.5-fold
1.4-fold
2.5-fold
1.5-fold
G2 /M
Table 2-2. Summary of methods to imnrove volumetric nrndietivitv hv inertnc
Increasing qp
Hypothermic Cell Culture
35 C
33 OC
Furukawa and Ohsuye, 1998
Yoon et al., 2003
CHO
CHO
799Bg/llx-AE
EPO
Ahn et al., 2008
Bollati-Fogolin et al., 2005
Fox et al., 2004
Furukawa and Ohsuye, 1999
Hendrick et al., 2001
Kaufmann et al., 1999
Rodriguez et al., 2005
CHO
CHO
CHO
CHO
CHO
CHO
CHO
EPO
hGM-CSF
IFN-y
799Bg/lla-AE
t-PA
SEAP
IFN-
Fox et al., 2005c
CHO
Chang et al., 1999
Hendrick et al., 2001
Rodriguez et al., 2005
Kim and Lee, 2001
Sung et al,. 2007
Carvalhal et al,. 2003b
-
4-fold
1.8-fold
2.5-fold
G1
Biphasic Temperature Shift
37
0C
to 33
0C
37 0C to 32 'C
37 *C to 30
0C
4-fold
-
6.5-fold
6-fold
1.9-fold
1.6-fold
1.7-fold
3.4-fold
4-fold
IFN-y
-
7.7-fold
CHO
CHO
CHO
CHO
CHO
CHO
EPO
t-PA
IFN-P
SH-0.32
hTPO
SEAP
-
3-fold
3-fold
2.7-fold
no increase
3.1-fold
2-fold
2.1-fold
no increase
2-fold
1.5-fold
1.6-fold
Tan et al., 2008
CHO
IFN-y
1.4-fold
1.4-fold
Bi et al., 2004
Fussenegger et al., 1998
CHO
CHO
IgG
Carvalhal et al., 2003a
Fussenegger et al., 1998
SEAP
4-fold
15-fold
-
CHO
CHO
SEAP
SEAP
2-fold
30-fold
-
-
2-fold
2-fold
1.7-fold
G1
G1
G1
Active Growth
S
Culture Additives
Butyrate alone
Butyrate w/ Bc/2
Butyrate w/o caspases 3 & 7
AMP
G1
S
Gene Overexpression (stable)
CIRP
p21 CipI
p21 C' w/ c/ebpa
p27K'l
p27K'P'w/ BcI-xL
Note:
'-':
no data available
-
G1
G1
G1
3
MATERIALS AND METHODS
3.1
Cell Culture
3.1.1
Cell Lines
The main cell line used in this thesis was a Chinese Hamster Ovary (CHO) cell line expressing
IFN-y driven by the SV40 promoter. The CHO IFN-y (y-CHO) cell line was obtained many
years ago from Dr. Walter Fiers (Scahill et al., 1983) and has been used extensively in our
laboratory (Ngantung, 2005; Fox, 2005a; Yuk, 2001; Nyberg, 1998; Gu, 1997). The cell line
was created from a DHFR CHO cell line by cotransfecting the cells with genes for both DHFR
and IFN-y.
CHO IFN-y is grown in the presence of methotrexate, which is a competitive
inhibitor of DHFR, and increases the copy number of genes cotransfected with DHFR. This cell
line has also been adapted to suspension culture (Nyberg, 1998), and both formats were used
throughout this thesis. The cell lines have been passaged several hundred times prior to this
project.
3.1.2
Culture Medium and Maintenance
3.1.2.1 Adherent Cell Cultures
The basal medium used for all adherent cultures was Dulbecco's Modified Eagle Medium
(DMEM) (Invitrogen, Grand Island, NY). All supplements were obtained from Invitrogen and
all chemicals were obtained from Sigma Aldrich (St. Louis, MO) unless otherwise noted. Prior
to 0.22 gm filtration DMEM was supplemented with 0.25 jiM methotrexate, 20 U/mL penicillin
- 20 gg/mL streptomycin mix, and 10% heat inactivated fetal bovine serum (IFS). Adherent cell
cultures were incubated at 37 'C with a 5-10% CO 2 overlay in a humidified incubator. Cells
were grown in surface-treated 6-well plates and T-75 flasks. The cells were passaged every 3-4
days at 1x10 5 cells/mL.
3.1.2.2 Suspension Cell Cultures
The basal medium used for all suspension cultures discussed in this thesis was protein-free HyQ
PF-CHO (HyClone, Logan, UT). Prior to 0.22 pm filtration, HyQ-PF CHO was supplemented
with 4mM L-glutamine, 0.25 gM methotrexate, 20 U/mL penicillin - 20 Rg/mL streptomycin
mix, and 0.1% Pluronic-F68. Suspension cell cultures were incubated at 37 *C with a 5% CO
2
overlay on shaker platforms set at 115 RPM in a humidified incubator. The cells were grown in
125-mL Erlenmeyer flasks and passaged every 3-4 days at 2.5x10 5 cells/mL.
3.1.2.3 Cell Bank Maintenance
Frozen stocks were prepared from cells in their growth phase with viability greater than 95%.
Cells were centrifuged at 1000 RPM for 5 minutes and resuspended to 107 cells/mL in fresh
growth medium containing 14% (v/v) dimethylsulfoxide (DMSO).
Freezing medium for
adherent cells also contained 10% IFS. Cryogenic vials containing 1 mL of the cell suspension
were placed in a NalgeneTM Cryo 1 0 C min-' freezing container and placed in a -80 C freezer
overnight. The following day, the vials were transferred to a liquid nitrogen cell bank for longterm storage.
New cultures were started from the stock vials by quickly thawing the cells in a 37 0 C water bath
for 5-10 minutes. The cryovials were gently flicked and sprayed with 70% ethanol before being
opened in a sterile biosafety cabinet.
These cells were immediately diluted into 25 mL of
prewarmed growth medium and transferred to the appropriate growth vessel (either T-75 or 125
mL Erlenmeyer flask). Growth medium was changed within 24 hours of plating.
3.1.3
Cell Enumeration
3.1.3.1 Trypan Blue Staining
Cell enumeration was performed with a hemacytometer. Briefly, anchorage dependent CHO
cells were collected in suspension after washing with Dulbecco's PBS (DPBS) (Invitrogen,
0
Grand Island, NY) and treating with 0.05% Trypsin/EDTA (Invitroen) for 2 minutes at 37 C
The cells were stained with trypan blue and diluted appropriately.
Viable cells exclude the
trypan blue dye while non-viable cells, which lack membrane integrity, are stained blue. The
cell number was then determined by counting the stained and unstained cells under a microscope
and multiplying by the known dilution number.
3.1.3.2 Guava ViaCount
Cells were collected in suspension following the same protocol as in Trypan Blue Staining
5
(Section 3.1.3.1) and diluted to a concentration no higher than 5x10 cells/mL using the Guava
ViaCount Reagent (Guava Technologies, Millipore).
Similarly to trypan blue, the ViaCount
Reagent differentially stains viable and non-viable cells based on their permeability to the DNAbinding dyes in the reagent.
Samples were then analyzed using a flow cytometer (Guava
Personal Cell Analysis (PCA) System, Guava Technologies, Hayward, CA). Typically, PM1
voltage was set at 430V and PM2 voltage at 450V.
PM2 threshold was usually set to
approximately 100. Forward scatter (FSC) gain was set at 2x, and the FSC gate was set to about
100 and debris was excluded. Data analysis was performed using the Guava Express Software
and 1000 events were acquired per sample.
3.1.4
Pseudo-perfusion Culture in Tissue Culture Plates
Following 2-4 passages of stock cells, between 1 to 2x1 05 mid exponential cells with viability
greater then 95% were seeded in fresh growth medium in 6-well plates. Cells were incubated at
37 C in humidified incubators with 5% CO 2 overlay. Cultures were run in batch mode for the
first 2 to 4 days, at which point 2-mL medium changes occurred every 2 days. At each time
point, 3 wells per condition were sacrificed for cell counting.
The supernatant from the
sacrificed wells was centrifuged at 1000 RPM for 5 minutes and stored at -80 C for later
analysis and the cells were saved for RNA analysis and/or fixed for cell cycle analysis, using the
procedure outlined below.
3.1.5
Fed-batch Culture in Shake Flasks
Feb-batch cultures were performed in 125-mL Erlenmeyer flasks. Cultures were seeded 2x1 05
cells mL 1 in 25-mL volumes and incubated at 37 0 C under 5% CO 2 and agitated at 115 RPM.
The basal medium was the same for both batch and fed-batch cultures and was HyQ PF-CHO
(Hyclone) supplemented with 4 mM L-glutamine, 0.1% Pluronic F-68, 0.25 gM methotrexate,
and 20 U/mL penicillin - 20 gg/mL streptomycin. Feed forward control was employed in the
fed-batch setup. Control of glutamine and glucose concentrations was achieved by feeding the
projected amount of glutamine and glucose that will be consumed by the cells over the forecast
interval. Glucose and glutamine set points were 0.5 and 0.15 g L-, respectively. The glutamine
feed was prepared from a
loX
nutrient concentrate of salt free DMEM/F12 and IX DMEM/F12
salts (Hyclone), 100 mM L-glutamine, 0.1% Pluronic F-68 (Invitrogen), 0.25 gM methotrexate
(Sigma), and 20 U/mL penicillin - 20 [tg/mL streptomycin (Invitrogen). The glucose feed was a
2M glucose solution (Sigma). Samples were taken every 8 to 12 hours for offline analysis and
feeding.
3.1.6
Measuring Glucose, Glutamine and Lactate Concentration
Glucose, glutamine and lactate concentrations in the medium were measured using the YSI
Model 2700 SELECT Biochemistry Analyzers (YSI Incorporated, Yellow Springs, OH).
Glutamine was also often measured using a Glutamine and Glutamate Determination Kit
(Sigma).
3.2
Cyclin-dependent Kinase ATP-competitive Inhibitors
A number of different ATP-competitive inhibitors of CDKs are used in our work, including:
CDK2 Inhibitor III (cdk2iii)( (Cat. No. 238803; Brooks et al., 1997; Bhattacharjee et al., 2001),
CDK2 Inhibitor IV (cdk2iv) (Cat. No. 238804; Pennati et al., 2005), CDK1 Inhibitor IV (cdkliv)
Cat. No. 217699; Vassilev et al., 2006), and CDK4 Inhibitor (cdk4) (Cat. No. 219476; RetzerLidl et al., 2007). All inhibitors were purchased from Calbiochem (EMD Biosciences). Stock
solutions were made by dissolving inhibitors in dimethyl sulfoxide (DMSO) to a final
concentration of 2 mM and stored at -20 "C. These inhibitors are used in our experiments at a
number of different concentrations based mostly on their IC50 values, which are summarized in
Table 3-1, below. It should be noted that the inhibitors generally have selectivity towards a
particular CDK, but also bind to other CDKs at elevated concentrations.
Table 3-1. 1C 5 o and Ki values of ATP-compeetitive CDK inhibitors
Inhibitor
Structure
ICSo/K
ID
Concentration
CcnA/E-CDK2 (0.5 gM)>
CcnB-CDK1 (4.2 gM) >
CcnD-CDK4 (215 pM)
cdk2iii
cdk2iv
Typical
N0
CcnA-CDK2 (0.41 jM) >
CcnD-CDK2 (5.5 pM) >
CcnB-CDK1 (6.6 pM)
0
N
N
H4
cdkliv
N
1-15 gM
1-10 piM
H
0
CcnB-CDK1 (Ki = 35 nM) >
N
5-20 gM
CcnA-CDK1 (Ki= 110 nM)>
VN
S
CDK2 (Ki
=340 nM)
H
O
7
N
O
cdk4
______
CcnD-CDK4 (76 nM) >
CcnE-CDK2 (520
nM) >
CcnB-CDK1 (2.1 gM)
H
H_
1-5 M
_
_
_
_
3.3
mRNA Analysis
3.3.1
RNA Purification
RNA isolation was performed on at least 1x106 cells with the RNeasy Mini Kit (Qiagen)
following the manufacturer's instructions. Cell lysis was performed with a QIAShredder column
(Qiagen) as suggested. On-column digestion with RNAse free DNAse (Qiagen) was performed
during the RNA purification to eliminate genomic DNA contamination.
During the development and screening of a cell line that inducibly expresses anti-CcnEl shRNA,
we performed RNA isolation with the TurboCapture 96 mRNA Kit (Qiagen) following the
manufacturer's protocol. This kit allows for higher throughput RNA isolation and subsequent
quantitative reverse transcription PCR (qRT-PCR) in a single plate
3.3.2
RNA Quantification and Quality Assessment
Total purified RNA was diluted 25-fold in RNase free water and the concentration and quality of
RNA was determined from the absorbance at 260nm and 280nm. Absorbance measurements
were performed on either an Eppendorf Biophotometer (cuvettes) or a Molecular Devices
SpectraMax M2 Microplate Reader (microplates). The RNA concentration is calculated from
the absorbance at 260nm (assuming 40 gg mL' for 1.0 OD of single-stranded RNA) and the
RNA quality can be estimated from the ratio of the absorbance at 260nm to the absorbance at
280nm. A ratio greater than 1.8 is considered an indication of high RNA quality and was
achieved regularly.
3.3.3
First-Strand cDNA Synthesis
First-strand cDNA was synthesized from 1 pg of total RNA using Superscript III Reverse
Transcriptase (Invitrogen) as follows. In a nuclease-free tube, 1 gg of RNA was combined with
1 gL of oligo-dT mix, 1 gL of 10 mM dNTP mix, and DEPC-treated water was added to a
volume of 10 gL. The mixture was heated at 65 "C for 5 minutes and placed on ice briefly.
Then, 10 pL of cDNA Synthesis Mix (2X RT Buffer, 4 gL 25mM MgCl 2, 2 gL O.1M DTT, 1
mL 40 U gL 1 RNaseOUT, and 1 pL 200U gL- 1) was added and the final solution was incubated
for 50 minutes at 50 "C and for 5 minutes at 85 "C. Finally, 1 gL of RNase H was added and the
solution incubated for 20 minutes at 37 C.
3.3.4 RT-PCR
Reverse transcription PCR (RT-PCR) was frequently used to check primer specificity, amplify
cDNA standards, and prepare samples for cDNA sequencing. RT-PCR was typically performed
with Platinum PCR Supermix (Invitrogen) following the manufacturer's instructions. Briefly,
the first strand reaction was chilled on ice before the addition of 45 gL Platinum PCR Supermix
and 0.5 gL of each primer stock (20 gM) to 1 pL of cDNA. Cycling conditions were 94 "C for 2
minutes followed by 20-30 cycles of 94 "C for 30 seconds, 55 *C for 30 seconds, and 72 C for 2
minutes.
The product was stored at 4 "C following PCR, and analyzed via agarose gel
electrophoresis.
3.3.5 Real-time PCR Quantification of Ccnel and /-Actin cDNA Levels
Real-time PCR assays were developed for a number of CHO cDNAs, including: CcnA2, CcnB1,
CcnD], CcnE1, CcnE2, and Rnl8s. We also performed real-time PCR on
#-A ctin, which
acted
as an internal control with the assumption that its expression was constant over most
experimental conditions. We also refer to real-time PCR as quantitative reverse transcription
PCR (qRT-PCR). This assay was previously developed and performed by a number of other
researchers in our group (Ngantung, 2005; Fox, 2005a). Primers sequences were selected based
on trial and error RT-PCR experiments with many different sets of primers. The specificity and
efficacy of each primer was assessed qualitatively by observing the gel-electrophoresis of the
RT-PCR products.
The primers for these assays can be found in Table 3-1.
Annealing
temperatures were selected based on gradient PCR optimization by testing annealing
temperatures between 50 and 60 0C. An annealing temperature of 55 *C was chosen for all genes
0
with the exception of CcnB1, which used an annealing temperature of 52 C.
A qRT-PCR assay was performed in a total reaction volume of 50 pL. This consists of 25 gL iQ
SYBR Green Supermix (Bio-Rad, Hercules, CA), 0.2 gM of each primer, 2 pL of cDNA, and
RNase free water. Real-time PCR was conducted in 96-well plates using the iCycler RT-PCR
'machine (Bio-Rad). Cycling conditions were 3 minutes at 95 "C followed by 50 cycles of 30
seconds at 95 "C, 1 minute at the Tanneai, and 1 minute at 72 "C, during which time the
fluorescence was measured. Melting curve analysis was performed by adding a cycle consisting
of 1 minute at 95 *C followed by a temperature decrease in 1 "C increments to reach 4 C. A 10
second hold was introduced between every step decrease.
Table 3-2. Real-time PCR primers
cDNA
Real-time PCR Primers
Product Size (bp)
/#-Actin
5'5'-
AGCTGAGAGGGAAATTGTGCG -3'
GCAACGGAACCGCTCATT -3'
163
CcnA2
5'-
GGAAAGCAACCAGTAAACAGCC -3'
136
5'-
CCAGGTAAAGAGACAGCAGCATT
5'-
ACTGTGTACCCAAGAAGATGCTGC -3'
5'-
CGAAGTCACCTATTTCTGGAGGG
CcnD]
5'5'-
AGAGGCGGATGAGAACAAGC -3'
GGGTGGGTTGGAAATGAACTTC -3'
94
CcnE1
5'5'-
ATAGCAGTCAGCCTTGGGATG -3'
CATGATCCTCCAAACCTCTTCTC -3'
194
CcnE2
5'5'-
128
Rn]8s
5'-
ATCTGTGTATCCTCGGCATTGACT -3'
AGGCACCATCCAGTCTACACATTC -3'
TTGACGGAAGGGCACCACCA -3'
5'-
GCACCACCACCCACGGAATCG
CcnB1
-3'
-3'
99
-3'
109
SYBR Green dye binds double stranded DNA. The resulting DNA-dye complex absorbs blue
light
(Xmax
= 488 nm) and emits green light
(kmax
= 522 nm), and therefore the fluorescence
measured at the end of each amplification cycle is proportional to the amount of DNA in the
reaction vessel. The cycle at which a given sample crosses a threshold cycle (CT) during the
exponential part of the amplification is used to calculate the initial template concentration. A
standard curve is generated by simultaneously running real-time PCR on 10-fold serial dilutions
of
#-Actin,
Cyclin, or Rn18s cDNA standards of known concentration.
analysis was performed on CcnE1 and
#-Actin,
The most common
and examples of fluorescence versus cycle
number for these two genes are shown in Figure 3-1.
A plot of CT versus the log of
concentration is linear and can be extrapolated to find the concentration of unknown samples.
Example standard curves are shown in Figure 3-2. Both the samples and standards were at least
run in duplicate and final CT values represent the average of these samples. Melting curve
analysis of CcnE] and #-Actin RT-PCR products from control cells is shown in Figure 3-3. A
single peak ensures that only one PCR product was amplified and ensures the specificity of the
RT-PCR assay.
In order to use the AACT Method, Section 3.3.6, the efficiencies (E)of the target (CcnE1) and
endogenous control (3-Actin) must be approximately the same. The efficiency values (E) were
measured using the CT slope method and are shown in Table 3-2. Using the slopes from Figure
3-2, we calculate efficiency using the following equation:
E=
slope
-1
(3-1)
A:
-Actin
4500
4500
4000
3500
-3500
u.3000
U_
u-.
300
U
U
2500
a
2000-'
C
~-
1500
00
000
445000
0
_30
-500
-- -1-I- -a
~
2-500
0 2 4 6 8 10121416182022242628303234363840424446485052
Cycle
BOCcnE1
5000TTT
-5000
4500--t
*
U
0V
UU'U
-o
W,
U,
.44
4
4
4
4
4500
.44
4000-
-4000
3500
-3500
3000 -
1
4
4
*3000
~44
2500
2500
4
2000?
44
In 1000
4
4
44.4.44.4.4444444..
t
1500
~
44
2000
.1.
*1500
A
T T
4
L~
~
4
~-4 4
44
1000
44
r
r .4
500.
500
~~1__
0
0
0
2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52
Cycle
Figure 3-1. Real-time PCR fluorescence versus PCR cycle number.
An example of normalized fluorescence versus PCR cycle number for triplicates of (A) /-Actin
standards (108-103 copies mL-1) and (B) CcnE1 standards (106-101 copies mL-). Threshold
fluorescence was calculated using iCycler Software Version 3.1 and is shown by the horizontal
red line.
A:
-Actin
y = -3.3229x + 36.815
R2 = 0.9994
8
4
6
log (copies mL-1)
2
B: CcnE1
y = -3.3914x + 34.12
R2 = 0.9999
0
2
4
log (copies mL1)
6
8
Figure 3-2. Threshold cycle (Ct) as a function of the log of DNA copy number.
The date from Figure 3-1 is plotted here. The concentration of known standards is plotted
against the threshold cycle determined by the iCycler Software Version 3.1. (A) /#-Actin and (B)
CcnEl.
A: $-Actin
800700600-
i~
~.,-----~
i-i
4
~~t 4
500- ~
400300200
100-
20
25
30
35
40
~
44
144
....
-100
45
55
50
60
65
70
75
80
85
90
95
100
Temperature, Celsius
B: CcnE1
900
800
700
600..
u
400
m 300
200
20
100
20
25
30
35
40
45
50
55
60 65
70
Temperature, Celsius
75
80
85
90
95
100
Figure 3-3. Melting curve analysis.
The presence of a single sharp peak in the melting curve analysis indicates that our method is
specific for our cDNA of interest. The absence of smaller broad peaks indicates that our primers
are not amplifying off-target cDNAs. (A) #-Actin and (B) CcnE1.
Table 3-3. gRT-PCR efficiency for cDNA standard curves
fiiny(PC
~
~
cDNA
#-Actin
1.00
CcnA2
1.01
CcnBi
0.929
CcnDl
1.00
CcnEJ
0.972
CcnE2
1.00
Rn18s
0.935
3.3.6
Calculating Relative mRNA Expression
Relative mRNA expression was calculated using the
2001).
2 -AACt
method (Livak and Schmittgen,
For the AACT method to be valid, the amplification efficiencies of the target and
reference must be approximately equal, Table 3-2. In addition, the internal control (f-Actin)
must be expressed at a constant level over all of the experimental conditions.
All relative
expression calculations are calculated with respect to a non-silencing, 'mock', siRNA control
(Dharmacon) and normalized against P-Actin expression.
3.4
Cyclin El siRNA Methodology
The cyclin El (CcnEl) CHO mRNA represented a challenging target for silencing RNA
(siRNA). The CHO genome is not available publicly, so we first had to sequence any mRNA
that we wished to target with siRNA.
Secondly, we are not aware of any validated primary
antibodies against CHO CcnE], nor were we able to validate any ourselves (data not shown).
Therefore we were not able to confirm knockdown of CcnElat the protein level. Nevertheless,
by following well-annotated methods for confirming the specificity of RNAi experiments
(Cullen, 2006), we are confident that we were able to determine the phenotype of CcnE]
knockdown. Namely, we observed a similar phenotype following transfection with multiple
unrelated and effective siRNAs targeting different regions of the CcnE] mRNA.
When
quantifying siRNA knockdown we always compare to a non-silencing 'mock'
siRNA
(Dharmacon).
3.4.1
Cyclin Sequencing
Sequencing primers were designed based on the open reading frames of cyclins from the mus
musculus transcriptome and ordered from Integrated DNA Technologies (Coralville, IA). The
cDNA sequencing templates for each cyclin were amplified with primer sets in Table 3-4.
These templates were also used as standards in our real-time PCR assays, Section 3.3.5.
Effective sequencing primers were validated through touchdown PCR
(Tanneal
= 65 to 55 0 C)
with the specific cyclin template, and submitted along with the template for sequencing.
Sequencing was performed by the Biopolymers Laboratory at the Center for Cancer Research at
MIT using the Applied Biosystems Model 3730 capillary DNA sequencer which employs the
Sanger method (Sanger et al., 1977).
I able .- 4. Primer se uences for the amplification of cyclin cDNA temp late s
mRNA Targret
CcnA2
Primers
5' -ACTCGACGGGTTGCTCCTCTTA-3'
5'-CTGGTGGGTTGAGAAGAGAAAC-3'
CcnB]
5' -CTCAGGGTCACTAGGAACACGA-3'
5'-GACTACATTCTTAGCCAGGTGCTG-3'
CcnDl
5' -TGTGCTGCGAAGTGGAGA-3'
5'-GGAGGGTGGGTTGGAAATGA-3'
CcnE1
5' -CGCTCCAGAAAAAGGAAGGC-3'
5'-CGAACGGAACCATCCATTTG-3'
CcnE2
5' -CACCCCATAAAGAAATAGGAACAAG-3'
5' -GCTTCACTGGACTCACACTTTTTAC-3'
3.4.2
Cyclin El siRNA Design
An updated modification to the Tuschl rules (Elbashir et al., 2002), developed by Dharmacon,
(Reynolds et al., 2004) was used to design highly effective siRNAs. Briefly, the eight criteria
used to design siRNA were: G/C content between 36% and 52%, three or more A/U base pairs at
positions 15-19 of the sense strand (low internal stability of the 3' end of the sense strand), a lack
of internal repeats, A at positions 3 and 19 of the sense strand, U at position 10 at the sense
strand, no G/C at position 19 of the sense strand, and no G at position 13 of the sense strand. All
siRNA sequences were generated with siDirect (http://des]itn.RNAi.jp/) (Naito et al., 2004) and
ordered from Dharmacon Research (Lafayette, CO).
At least 12 sequences from different
locations along the CcnE1 cDNA sequence were selected. A BLAST search against the mus
musculus transcriptome was performed to minimize potential off-target effects. Both unlabelled
(ON-TARGET plus Non-Targeting siRNA, Dharmacon) and fluorescein (FAM)-labeled
(Invitrogen, cat. 2013) non-silencing siRNAs were used as transfection and experimental
controls.
3.4.3
Preparation of siRNA Duplexes
The siRNA was shipped from Dharmacon as a dried pellet in the 2'-deprotected and duplexed
form. The pellet was centrifuged briefly and resuspended to 20 RM in siRNA universal buffer.
The concentration of each siRNA oligo was verified using an Eppendorf Biophotometer.
3.4.4
siRNA Transfection and RNA Collection
CHO cells were typically plated at a concentration of 2x1 05 cells/well in a 6-well plate 18 hours
prior to transfection. On the day of transfection, 100 pmol of siRNA duplex was added to 250
RL of OptiMEM (Invitrogen). Separately 5 gL of Lipofectamine 2000 (Invitrogen) was added to
250 pL of OptiMEM.
After a five minute incubation, the two solutions were mixed and
incubated for twenty minutes at room temperature. During the incubation period, the CHO cell
cultures were aspirated and the cells washed with DPBS and 1.5 mL of warmed DMEM (no
additives) was added to each well. Next, 500 gL of siRNA-Lipo2000 solution was added to each
well and allowed to incubate at 37 0 C for 24 hours. After 24 hours, each well was washed once
with DPBS and fresh DMEM (supplemented with 10% IFS) was added.
The transfection
controls (FAM-labeled siRNA) are analyzed via FACS to ensure >95% transfection efficiency.
At 48 hours post-transfection, the cells were harvested, washed with DPBS and pelleted prior to
RNA purification.
3.5
Creation of an Inducible shRNA IFN-y Cell Line
3.5.1
Plasmid Description and Design
A number of different plasmid vectors were used in this study. Figure 3-4 shows the vector map
of pSingle-tTS-shRNA which is a commercially available vector (Clontech, Mountain View,
CA) for the single step selection of inducible mRNA knockdown. Figure 3-5, shows the vector
maps of the two commercially available plasmids (Clontech) necessary for a two-step selection
strategy. The inducible shRNA expression vector, shown in Figure 3-5B, is a modification of
the commercially available pSilencer 4.1 -CMV-hygro vector. Seven repeats of the tetracycline
operon (tetO 7) were inserted upstream of the CMV promoter. The cDNA encoding these seven
repeats of the tetracycline operon (tetO7 ) were amplified from the pSingle-tTS-shRNA, Figure
3-4, (Clontech) vector using the 5' primer CGCCCGGTACCTCTTCACTTGAGTTTACTCCC
with
an
underline
showing
an
added
KpnJ
site
and
3'
primer
GGCCAGATCTTACACGCCTACCTCGACATA with an underline showing an added BgII
site. The effectiveness of this modification has previously been shown to control the knockdown
of GFP expression in CHO cells (Malphettes and Fussenegger, 2004). The insertion was verified
by DNA sequencing.
A visual description of the tetracycline transcriptional silencer (tTS) controlled shRNA
expression is shown in Figure 3-5. In the absence of doxycycline the tTS binds to the tet operon
(tetO7 ) and represses shRNA expression. Upon addition, doxycycline preferentially binds to the
tTS, which allows for expression of shRNA driven by either a U6 or CMV promoter. The tTS is
a fusion of the Tet repressor protein (TetR) and the KRAB-AB silencing domain of the Kid-1
protein (SDKid%1), which is a powerful transcriptional suppressor (Freundlieb et al., 1999;
Witzgall et al., 1994).
shRNA expression vectors were created to express the shRNA hairpins: El-1, El-2, El-5, El-6,
El-7 and El-8. Hairpins were annealed and inserted into the appropriate vectors by digestion
with either HindIl and XhoI (pSingle-tTS-shRNA) or BamHI and HindIII (pSilencer-tetO7CMV-shRNA). All hairpins were order from Integrated DNA Technologies (Coralville, IA) and
the appropriate sequences are shown in Table 3-5.
sequencing.
All insertions were verified by DNA
SV40 Promoter
Ampicillin
Neomycin
TK pA
CoIE1 origin
pSingle-tTS-shRNA
7.0 kb
Promoter
ICMV
-EcoRI(2199)
shRNA Xho
HindIll(4717)
tTS
Tight(tetO7)U6
Promoter
b-globin pA
Figure 3-4. Plasmid map of pSingle-tTS-shRNA vector.
This is a vector map of the commercially available plasmid pSingle-tTS-shRNA (Clontech,
Mountain View, CA). An shRNA of interest can be directionally inserted downstream of the
inducible U6 promoter using the HindIIl and XhoI restriction sites. This plasmid allows for
transfection and a single-step selection with neomycin for the inducible knockdown of a target
mRNA.
A
SV40 Promoter
Ampicillin
TK pA
CoIE1 Origin
CMV Promoter
b-globin pA
SV40 pA
B
HindIII(463)
BamHI(517)
--
SV40 Promoter
shRNA
KpnI(1 118)
tet 7
Hygromycin
pSilencer 4.1 - tetO7 CMV hygro
5.5 kb
-
8g111(1390)
CoIE1 origin
SV40 pA
Ampicillin
Figure 3-5. Plasmid maps of ptTS-Neo and a modified pSilencer 4.1 vector.
Both vectors are commercially available pre-modification (Clontech, Mountain View, CA).
These plasmids allow for a two-step transfection and selection process for the inducible
knockdown of a target mRNA. A ptTS-Neo (A) transfection and neomycin selection is followed
by a pSilencer 4.1 -tetO 7-CMV-hygro (B) selection and hygromycin selection.
The tTS System
tTS ( 1)
Remove
Dox
bindsTRE,
and suppresses transcription
in the absence of Dox
tTS
/
1TS
Transcription
Knockdown
TetR
SDKid-l
TRE
U6
TRE.
U6
Anti-X
shRNA
Add Dox
TREmod
U6
Figure 3-6. The tTS System.
This diagram shows how U6-driven shRNA expression responds to the addition or removal of
doxycycline. Also applies to CMV-driven expression in the case of the two-step selection CMVdriven shRNA expression system. (KnockoutTM Single Vector Inducible RNAi System User
Manual, 2007).
Table 3-5. ShK.NA hair in seguences tor inserton into inuuile expresswin
vectors
pSingle-tTS-shRNA
El-i
3'
5' TCGAGGGAGAAGATTTACCTAAGATTCAAGAGATCTTAGGTAAATCTTCTCCTTTTTTACGCGTA
CCCTCTTCTAAATGGATTCTAAGTTCTCTAGAATCCATTTAGAAGAGGAAAAAATGCGCATTCGA 5'
3'
El-2
3'
5' TCGAGGTTACATGGCATCACAACAATTCAAGAGATTGTTGTGATGCCATGTAACTTTTTTACGCGTA
CCAATGTACCGTAGTGTTGTTAAGTTCTCTAACAACACTACGGTACATTGAAAAAATGCGCATTCGA 5'
3'
El-5
3'
5' TCGAGGTTTGGAGGATCATGTTAAATTCAAGAGATTTAACATGATCCTCCAAACTTTTTTACGCGTA
CCAAACCTCCTAGTACAATTTAAGTTCTCTAAATTGTACTAGGAGGTTTGAAAAAATGCGCATTCGA 5'
3'
El-6
3'
5' TCGAGGACAGCTCATTGGGATTTCATTCAAGAGATGAAATCCCAATGAGCTGTCTTTTTTACGCGTA
CCTGTCGAGTAACCCTAAAGTAAGTTCTCTACTTTAGGGTTACTCGACAGAAAAAATGCGCATTCGA 5'
3'
El-7
3'
5' TCGAGGCCAGTTTGCTTACGTTACATTCAAGAGATGTAACGTAAGCAAACTGGCTTTTTTACGCGTA
5'
CCGGTCAAACGAATGCAATGTAAGTTCTCTACATTGCATTCGTTTGACCGAAAAAATGCGCATTCGA
3'
EI-8
3'
5' TCGAGGCCCTTAAGTGGCGTTTAATTCAAGAGATTAAACGCCACTTAAGGGCTTTTTTACGCGTA
CCGGGAATTCACCGCAAATTAAGTTCTCTAATTTGCGGTGAATTCCCGAAAAAATGCGCATTCGA 5'
3'
pSilencer-tetO 7-CMV-shRNA
El-
3'
5' GATCCGGAGAAGATTTACCTAAGATTCAAGAGATCTTAGGTAAATCTTCTCCTTA
GCCTCTTCTAAATGGATTCTAAGTTCTCTAGAATCCATTTAGAAGAGGAATTCGA 5'
3'
El-2
3'
5' GATCCTTACATGGCATCACAACAATTCAAGAGATTGTTGTGATGCCATGTAACGA
GAATGTACCGTAGTGTTGTTAAGTTCTCTAACAACACTACGGTACATTGCTTCGA 5'
3
El-5
3'
5' GATCCTTTGGAGGATCATGTTAAATTCAAGAGATTTAACATGATCCTCCAAACCA
3'
GAAACCTCCTAGTACAATTTAAGTTCTCTAAATTGTACTAGGAGGTTTGGTTCGA 5'
El-6
3'
5' GATCCACAGCTCATTGGGATTTCATTCAAGAGATGAAATCCCAATGAGCTGTAAA
'
GTGTCGAGTAACCCTAAAGTAAGTTCTCTACTTTAGGGTTACTCGACATTTTCGA 5'
El3-
3'
5' GATCCCCAGTTTGCTTACGTTACATTCAAGAGATGTAACGTAAGCAAACTGGTGA
GGGTCAAACGAATGCAATGTAAGTTCTCTACATTGCATTCGTTTGACCACTTCGA 5'
El-8
3'
5' GATCCGCCCTTAAGTGGCGTTTAATTCAAGAGATTAAACGCCACTTAAGGGCCTA
3'
GCGGGAATTCACCGCAAATTAAGTTCTCTAATTTGCGGTGAATTCCCGGATTCGA 5'
3.5.2
Plasmid Production and Purification
Plasmids were produced by transformation in DH5a competent cells (Invitrogen) grown in LB
medium and selected using 100 jig mUL ampicillin. Plasmids were purified with a QIAfilter
Plasmid Maxi Kit (Qiagen).
3.5.3
Transfection and Selection of Stable Cell Lines
Cells were plated at 1x10 5 cells mUL in 6-well plates one day prior to transfection.
All
transfections were performed with CLONfectin (Clontech) according to the manufacturer's
instructions. Briefly, on the day of transfection 2 pg of plasmid was combined with 4 pg of
diluted CLONfectin in DMEM and allowed to incubate for 20 minutes before being added to the
cells. The CLONfectin/DNA solution was removed after 4 hours, cells were washed once with
DPBS, and growth medium was added to the cells. Selection with either Geneticin/G418 (600
jg mL-1) or hygromycin (600 jg mL-') was initiated 48 hours post-transfection.
Once colonies began to appear in our 6-well plates, single cells were separated by serial dilution
into 96-well plates. Cells were plated at 1x10 4 cells ml' in the upper-left most well and diluted
down and across a 96-well plate. Conditioned medium was added to each well and selection at
600 jg ml' was continued. Wells with single cells were expanded with either neomycin or
hygromycin at a concentration of 100 pg mUL and screened.
3.5.4
Stable Cell Line Screening: tTS Expression
Following neomycin selection single cell colonies expressing tTS were screened by RT-PCR for
tTS mRNA expression and iWith a functi<onal luciferase expression assay to test the induction of
shRNA
expression.
RT-PCR
was
performed
with
forward
primer
5'-
GAGTTGGCAGCAGTTTCTCC-3' and reverse primer 5'-AAACCCTGCATCGCATAGAC-3'
on all single cell colonies to find the colonies with the highest levels of tTS mRNA transcript.
Cells that were shown to have high levels of the tTS mRNA transcript were then screened with a
luciferase knockdown assay.
In the luciferase knockdown assay, the luciferase expression vector pGL2 (Clontech) was
cotransfected with a modified pSingle vector, Figure 3-7, expressing anti-luciferase shRNA
(pSingle-no tTS-anti-luc shRNA). The pSingle vector has been modified through the removal of
its tTS expression cassette by digestion with EcoRI followed by religation. This ensures that the
only tTS involved in silencing the expression of the anti-luciferase shRNA is the tTS that is
stably expressed from within the cell. Elimination of the tTS cassette was verified through both a
restriction digest and DNA sequencing.
Luciferase expression was quantified using the
Luciferase Assay System (Promega, Madison, WI).
5
Briefly, on the day before transfection, cells were plated at a density of 1x10 cells well-' in 6-
well plates. On the day of transfection, 1 Rg of pGL2, 1 gg of pSingle-no tTS-anti-luc shRNA,
and 4 pg of CLONfectin (Clontech) (2:4 DNA:CLONfectin) were combined in DMEM and
incubated for 20 minutes before applying the solution to the cells. Four hours following the
transfection, growth medium was added to the cultures along with varying amounts of
doxycycline (from 0-10,000 ng mL-1). Two days later, Reporter Lysis Buffer (Promega) was
added to each sample followed by subjecting the samples to a single freeze-thaw cycle.
Luciferase expression was quantified using a SpectraMax Luminometer Micorplate Reader
(Molecular Devices, Sunnyvale, CA), by adding 100 gL of Luciferase Assay Reagent (Promega)
to 20 gL of cell lysate in white opaque 96-well plates, and measuring the luminescence for a
period of 10 seconds.
3.5.5
Stable Cell Line Screening: Inducible shRNA Expression
Cell lines that were selected for the insertion of vectors inducibly expressing shRNA were first
screened in 24-well plates by measuring CcnE1 knockdown 48 hours after the addition of 1000
ng mL- 1 (pSingle-tTS-shRNA) or 100 ng mL-1 (pSilencer-tetO 7-CMV-shRNA) doxycyline.
RNA purification was performed using the RNeasy Mini Kit for pSingle screening and the
TurboCapture Kit for pSilencer screening.
In the first screen of the pSilencer colonies,
knockdown was not normalized to P-Actin. Cell colonies that showed an induced knockdown in
CcnE1 expression were expanded and rescreened in triplicate in 6-well plates.
SV40 Promoter
Ampicillin
Neomycin
TK pA
pSingle - no tTS - anti-luc shRNA
5.5 kb
CoIE1 Origin
shRNA
EcoRI(2199)
Xhol(3
Hindill(3217)
Tight(tetO7)/U6
Promoter
Figure 3-7. Plasmid map of the modified pSingle vector, pSingle-no tTS-anti-luc shRNA.
This is a vector map of the commercially available pSingle vector (Clontech) with the tTS
expression cassette removed.
3.6
IFN-y ELISA
IFN-y concentration was measured using an ELISA kit (Invitrogen) by following the
manufacturer's protocol. Cell culture supernatants were centrifuged for 5 minutes at 1600 RPM
and stored at -80 "C for future analysis. On the day of analysis, supernatants were thawed and
serially diluted using phosphate buffer saline (PBS) and diluent buffer (provided in kit) to obtain
samples within the range of the standard curve (15.6 - 1000 pg mL').
Each sample was
measured in duplicate.
3.7
Calculating IFN-y Specific Productivity
The specific productivity, or the amount of IFN-y produced on a per cell basis in a given amount
of time, qp, is generally defined by the following equation, where P is the total cumulative IFNy production and Nviable is the total number of viable cells:
dP
=
dt
PN,,ab,,
(2-1)
By rearranging Equation 2-1 we are able to calculate qp in two different ways depending on the
data that is available. The first is through the integral method which is described in Section 3.7.1
and is used when more than three data points are taken over the course of an experiment. We
will refer to this specific productivity as qp. The second method is a differential method, which
is described in Section 3.7.2 and is used when two data points are known. We will refer to this
specific productivity as qp, diff-
3.7.1
Specific Productivity, qp
The integral method of calculating specific productivity is performed by plotting the cumulative
production of IFN-y against the integrated viable cell density (IVCD) at each time point. The
slope of a linear regressive fit of the data is the specific productivity, as is seen in the following
equation:
JdP= qp Ndt= qp -IVCD
(3-2)
A typical plot and regressive fit is shown in Figure 4-2.
3.7.2
DifferentialSpecific Productivity, qp. diff
The differential specific productivity, qp. dif; simply involves calculating the amount of IFN-y
produced in a given time and dividing by the average number of viable cells, Nv,avg, in that time,
as seen below:
AP
qPp, dAt
diff
N"
(3-2)
The differential specific productivity is used to compare productivity over very short time
frames. Notably, differential specific productivity is used to compare the effects of CcnE]
knockdown on IFN-y productivity.
3.8
Cell Cycle Analysis
At least 1 x 106 cells were collected by centrifugation (5 minutes at 1600 RPM) and washed once
with 1 mL of PBS. After a second centrifugation step, 500 tL of cells were added drop-wise to
1 mL of ice cold 100% ethanol stored at -20 "C. Ethanol fixed cells cin be stored up to one
month at -20 C prior to analysis. On the day of analysis, fixed cells were underlayed with 300500 jiL of IFS, centrifuged (5 minutes at 400 G) and the ethanol/IFS was aspirated. The cells
were washed once with PBS and centrifuged again (5 minutes at 400 G). Finally the cells were
resuspended in 1 mL of the propidium iodide (PI)/Triton X-100 straining solution [0.1% (v/v)
Triton X-100; 10 gg mL
PI; and 0.2 mg mL-1 RNase A in PBS] and incubated at room
temperature for at least 1 hour prior to flow cytometry analysis. The PI/Triton X-100 straining
solution is prepared as a IOX stock and is stored at 4 C for up to one month.
Flow cytometry analysis was performed using the FACScan flow cytometer (Becton Dickinson,
NJ). The laser was tuned to 488 nm, and a band-pass of 585/42 filter (FL2) was used for red
fluorescence detection.
The intensity of fluorescence was characterized by its area (FL2-A).
Single cells were selected for analysis by using the distribution of PI area (FL2-A) against PI
width (FL2-W) to discriminate doublets and debris. The number of events collected per sample
was set at 25,000 and the fluorescence parameter (FL2-A) was always collected in linear mode.
Histogram fitting was performed with ModFit LT Software.
3.9
Immunostaining and Cell Imaging
Round glass coverslips, #1 thickness, were treated with 1 mL of 5 jig mL-1 fibronectin (Sigma)
for 45 minutes at 37 0 C before being plated with 10,000 cells mL-1 in 12-well plates. On the day
following plating, the cells were treated with our CDK ATP-competitive inhibitors for 24 hours
before being fixed prior to immunostaining. On the day of fixation cells were washed once with
PBS and then 1 mL of pre-warmed fixation buffer (0.2% Triton-X 100, 20 mM PIPES pH 6.8, 1
mM MgCl- 10 mM EGTA, 4% p-formaldehyde) was added to each well and allowed to sit for at
least 20 minutes. The slides were then washed three times with PBS and stored at 4 0 C for up to
two weeks.
The coverslips were blocked in a 3% bovine serum albumin (BSA)/PBS solution at room
temperature for 30 minutes and washed once in PBS. The coverslips were then incubated with
0
the y-tubulin primary antibody, Gtu.88 y-tubulin (Sigma), in 3% BSA/PBS at 37 C for 1 hour.
The anti-mouse Gtu.88 y-tubulin antibody is used as a centrosome marker and was used at a
dilution of 1:5000. The coverslips were washed three times before being incubated with the
secondary antibody and phalloidin. We incubated the coverslipes in Alexa Fluor 488 donkeyanti-mouse secondary antibody (Invitrogen) at a 1:250 dilution (8 jig mL) and Alexa Fluor 594
0
phalloidin (Invitrogen) at a 1:100 dilution (2 U mL-) in 3% BSA/PBS at 37 C for 1 hour. Alex
Fluor 594 phalloidin is a high affinity probe for F-actin that is conjugated with a photostable
Alexa Fluor 594.
The coverslips were again washed three times before a final 5 minute
treatment with 10 gg mL Hoechst 33258 (Invitrogen), a DNA binding dye.
Stained cells were imaged with a DeltaVision Core deconvolution microscope (MIT CCR) with
a 60X objective. Gtu.88 y-tubulin was detected using a green, fluorescein, filter, Alexa Fluor
594 phalloidin was detected using a red, Texas Red, filter, and Hoechst 33528 was detected
using a blue, DAPI, filter. Image processing was performed with Deltavision Softworx.
3.10
Genomic DNA Purification and Quantification
Genomic DNA was typically purified from 5 x 105 cells after washing 1X with PBS using the
Wizard SV Genomic DNA Purification System (Promega, Madison, WI). DNA was quantified
using the Quant-iT PicoGreen dsDNA Reagant (Invitrogen) using spectrophotometer cuvettes.
Briefly, a standard curve was created from 2000 to 0 ng mL' using Salmon Sperm. DNA
samples and the standard curve were diluted in 1X TE (10 mM Tris-HCl, 1 mM EDTA, pH 8.0).
A working solution of the Quant-iT PicoGreen Reagent was made by diluting the concentrated
buffer 20-fold with DNase-free water. 1 mL of the diluted Quant-iT PicoGreen Reagent was
added to 1 mL of diluted standards and samples. The sample fluorescence was measured using a
SpectraMax M2 Spectrophotometer and standard fluorescein wavelengths (Xex = 480 nm;
Xem=
520 nm). Genomic DNA content was normalized to growth control cultures at all time points.
3.11
Measurement of Intracellular Protein Content
Typically, 2.50 x 105 suspension CHO cells were centrifuged for 5 minutes at 1600 RPM. Cell
pellets were lysed with 125 gL CelLytic TM Cell Lysis Reagant (Sigma) and frozen at -80 0 C until
further analysis.
On the day of analysis, cell lysates were thawed and protein content was
measured using the Pierce BCA Assay Kit (Pierce, Rockford, IL). Bovine serum albumin (BSA)
was used to make a standard curve.
3.12
Note on Statistical Analysis/Significance
In general, data is analyzed following the statistical rules outlined by Cumming et al. (2007).
Unless otherwise noted, all error bars are standard error bars. The number of experiments for
each graph and/or table will be noted. Statistical significance is assumed to occur when p < 0.05
and will also be noted.
4
CDK2-CcnEl TARGET VALIDATION
4.1
Introduction
Most controlled proliferation strategies are known to slow cell growth by inhibiting the cell cycle
machinery. Some of these strategies, like lowering culture temperature (Yoon et al., 2003) and
cell engineering based approaches, like overexpressing cyclin-dependent kinase inhibitors
(CKIs) (Mazur et al., 1998), arrest growing cell populations in the Gi-phase of the cell cycle and
lead to an increase in specific recombinant protein productivity. Decreasing culture temperature
stabilizes p53 (Ohnishi et al., 1998), a transcription factor that under normal conditions is
extremely unstable, and subsequently increases p21cipi protein levels (Ohnishi et al., 1998). It is
well understood that p53 transcriptionally activates p21cipI expression by directly interacting
with its regulatory elements (El-Diery et al., 1994). p2lc'P itself is known as a potent, tightbinding inhibitor of cyclin A-CDK2, cyclin E-CDK2, cyclin D1-CDK4, and cyclin D2-CDK4
complexes, all of which act at the Gi-S phase transition (Harper et al., 1993).
Cell engineering based approaches are inspired by the effects of hypothermic cell culture. In
these approaches, the CKIs p2lciP, p2 7 KP,
and a non-apoptotic p53 mutant, p53175P, are
inducibly overexpressed to induce growth arrest in the Giphase of the cell cycle (Mazur et al.,
1998). Unlike p2 1 ci1, p 2 7 KiP1 is not induced by p53 but rather is expressed in response to the
anti-mitogenic cytokine transforming growth factor b (TGF-$) (Reynisdottir et al., 1995). Like
p21cipI, p2 7 KiP1 exerts G1 cell-cycle arrest by binding to cyclin E-CDK2, cyclin A-CDK2, and
cyclin D-CDK4 (Toyoshima and Hunter, 1994). These approaches are shown to dramatically
increase the specific productivity of secreted alkaline phosphatase (SEAP), a model protein.
For these reasons, inhibition of the cyclin-cyclin dependent kinase (Ccn-CDK) complex
represents a good starting point for developing new growth arrest strategies. We wanted to first
determine if specifically inhibiting only the cyclin El-CDK2 (CcnEl-CDK2) complex was
sufficient to induce growth arrest and increase recombinant protein specific productivity. We did
this in two distinct ways: by adding a selective ATP-competitive CDK2 inhibitor to CHO cell
cultures, and by using RNA interference (RNAi) to knockdown CcnE1 expression.
We targeted CcnE1 for RNAi knockdown, as opposed to directly knocking down CDK2, for a
number of reasons. In a wide variety of cell lines, CDKl has been shown to compensate for loss
in CDK2 activity (Berthet and Kaldis, 2007) and cell cycle progression can occur even in the
absence of CDK2. In addition, CcnE] expression fluctuates throughout the cell cycle (Lodish et
al., 2004) making it a more natural target for knockdown. Also, its interaction with CDK2 is
known to promote progression from the G1 to S-phase of the cell cycle (Malumbres, 2008).
Lastly, the targeted knockdown in CcnE] by siRNA in various hepatocellular carcinoma (HCC)
cell lines reduced cell growth following transfection (Li et al., 2003).
4.2
CDK2 Inhibition with a Selective ATP-competitive Inhibitor
In order to determine if inhibiting only CDK2 was sufficient to induce growth arrest we added
the CDK2 inhibitor, cdk2iii, to adherent y-CHO cell cultures 2 days after plating at 1 x 105 cells
mL' in 6-well plates. Inhibitor cdk2iii was added to a concentration of 2 gM based on its known
IC50 of 0.5 pM in vitro (Brooks et al., 1997). Growth curves with and without inhibitor addition
are shown in Figure 4-1. Although viability data is not shown, viability is greater than 90%
across all data points. The slight decrease in viable cell count on day 6, four, ays following
inhibitor addition, can be explained by a small amount of cells detaching from the plates.
Slowed growth was observed by day 4, two days following inhibitor addition. The effect of
growth arrest on specific IFN-y productivity is shown in Figure 4-2, a representative plot of the
cumulative IFN-y production versus the integrated viable cell density for this 6-day period. On
day 6, the cumulative IFN-y production following the addition of the inhibitor cdk2iii is equal to
that of the growth control even though the final viable cell density is approximately 50% lower.
This suggests that by timing the induction of growth arrest, we may be able to strike a balance
between cell density and productivity, potentially improving total IFN-y titer.
Table 4-1 summarizes the results of three independent inhibitor cdk2iii experiments. By adding
the cd2iii inhibitor to y-CHO cell cultures we were able to increase specific productivity by 66%,
or 1.66-fold, over the 6 day time period.
7
-9- cdk2iii
65 .a;
0
S4 -
2 1 -
0
0
2
4
6
8
Time (days)
Figure 4-1. Growth curves of adherent cultures with or without the addition of 2 gM
inhibitor cdk2iii.
Cells were grown with (o) and without (0) the addition of 2 gM inhibitor cdk2iii for 6 days.
Starred points represent a statistically significant difference in cell density (*: p < 0.05, **: p <
0.01) (Error bars: S.E., n = 3)
80
* Growth Control
o cdk2iii
5-
+
0
4V
0
a-
z
3-
LL
2E
015
Integrated Viable Cell Density (106 cells d)
5
0
10
z
Figure 4-2. IFN-y production versus Integrated Viable Cell Density (IVCD) with and
without the addition of 2 gM inhibitor cdk2iii.
The slope of each line is the calculated specific productivity with (o) and without (C) the
addition of 2 gM of inhibitor cdk2iii. The regression lines are linear least-squares fits of each
data set. (Error bars: S.E., n = 1)
Table 4-1. A summary of the effect of inhibitor cdk2iii on specific
Specific Productivity ( xg 10~6 cell d')
Growth
cdk2iii
Avg
0.28
0.46
0.39
0.38
0.04
0.05
0.06
0.43
0.75
0.71
0.63
0.08
0.01
0.06
Foldincrease (X)
1.53
1.63
1.82
11.66 ± 0.09
4.3
CcnEJ siRNA Knockdown
Now that we have shown that specifically inhibiting CDK2 is sufficient to induce growth arrest
and increase productivity, we next sought to determine if inhibiting the CDK2-CcnEl complex
alone using RNAi produced similar results.
To do this we specifically target CcnE1 for
knockdown. This is necessary because CDK2 is known to interact with CcnEl, CcnE2, and
CcnA2 during cell cycle progression from G1 to S phase.
The first step that we took in determining the effect of CcnE1 knockdown by siRNA was
validating that we could reproducibly knockdown CcnE1 mRNA. Because we were unable to
validate knockdown on the protein level, due to a lack of primary antibodies against CHO
cyclins, we needed to ensure that we observed the same phenotype following knockdown with
multiple unique siRNAs targeting different parts of the CcnE1 mRNA (Cullen, 2006). Prior to
designing our siRNAs, we first needed to sequence the CHO cyclin mRNA because it is not
available in public databases. The reader can refer to the Appendix for a summary of the cyclin
mRNA sequences and a summary of our sequencing coverage.
We then designed siRNAs
targeting the entirety of the CcnE] mRNA, outlined in Table 4-2, using rules developed by
Reynolds et al. (2004) and Ui-Tei et al. (2004).
A screen of all siRNAs was performed following the protocol outlined in Section 3.4 and the
results are shown in Figure 4-3, which shows relative CcnE] expression 48 hours posttransfection. Measurement of mRNA expression at 48 hours post-transfection was shown to be
optimal by previous members of our lab group (Ngantung, 2005). As described in Section 3.3.6,
all expression calculations were performed relative to a non-silencing siRNA control, and
utilized an internal control (either
p-Actin
or Rnl8s) to adjust for differences in initial RNA
levels. As one can see, a number of siRNA sequences (El-7, -1, -8, -5, -2, and -6) reduced
CcnEl expression to less than 10% of that in the non-silencing controls.
Because off-target effects are often a problem when using RNAi, we calculated relative
expression compared with two different non-silencing controls to verify knockdown consistency.
In addition, in order to ensure that we are using an appropriate internal control, we calculated
relative expression using both /-Actin and Rn18s (ribosomal RNA) and compared our results.
As seen in Figure 4-3, we observe consistency across all non-silencing and internal controls,
especially when the largest levels of knockdown were observed.
Figure 4-4 is a reinterpretation of the data from Figure 4-3. Moving forward, we wanted to
choose one internal control and one non-silencing control for all of our future experiments.
Based on the data in Figure 4-4, we chose to use
#-Actin
and non-silencing control #1 for a
couple of reasons. For the AACT method to be valid, the amplification efficiencies of control and
target mRNA primers must be approximately equal. The amplification efficiency of our #-Actin
primers is closest to the efficiency of our CcnE1 primers (Table 3-3).
combination of
#-Actin
In addition, the
and non-silencing control #1 provides more conservative expression
levels when expression was knocked down by at least 60%, or in other words the relative
expression was less than 0.4. This is reflected in the inset graph, where the slopes of the best-fit
lines are both less than unity, and the CcnE1 mRNA levels are all slightly higher with NS #1
than with NS #2. Ultimately, this choice of controls should matter very little because we observe
very good agreemeint amongst all of them
The siRNA transfections were than repeated 2 more times with the most highly effective siRNA
sequences (El-1, -2, -5, -6, -7, and -8), and the data is shown in Figure 4-5. Each of these
siRNAs consistently reduces CcnEl expression to < 10% of the non-silencing control.
In
addition, the transfection itself does not significantly alter the levels of CcnE] expression at 48
hours when we compare the non-silencing control with the growth control.
Table 4-2. CcnE1 siRNA sequences designed using modified Tuschl rules developed by
Reynolds et al. (2004) and Ui-Tei et al. (2004)
sIRNA ID
El-I
Target sequence
starting position
Design
Rules (R/U)
GGAGAAGAUUUACCTAAGAUU 3'
5'
36l
361
R
siRNA Sequence
5'
3'
UUCCUCUUCUAAAUGGAUUCU
E1-2
5'
UUACAUGGCAUCACAACAAUU 3'
5'
517
R
E1-3
UCAGCCUUGGGAUGAUAAUUU 3'
5'
51
3' UUAGUCGGAACCCUACUAUUA
166
R
E1-4
5'
GCCUUGGGAUGAUAAUUCAUU 3'
5#
169
E1-5
UUUGGAGGAUCAUGUUAAAUU
5'
3E' UUAAACCUCCUAGUACAAUUU
3'
5 '
339
R
E1-6
5'
ACAGCUCAUUGGGAUUUCAUU 3'
5'
556
R
E1-7
CCAGUUUGCUUACGUUACAUU 3'
5'
51
3' UUGGUCAAACGAAUGCAAUGU
625
R
U
E1-8
5'
GCCCUUAAGUGGCGUUUAAUU 3'
5'
698
R
U
E1-9
5'
E1-10
5'
3'
UUGGUUCACCGAAUACAGUUA
754
R
U
E1-11
5'
3'
AGAAAGCCAUAUUGUCAGAUU
UUUCUUUCGGUAUAACAGUCU
E1-12
5'
E1-13
CUAAACUUGAGGAAAUCUAUU 3'
5'
51
3' UUGAUUUGAACUCCUUUAGAU
3' UUAAUGUACCGUAGUGUUGUU
3' UUCGGAACCCUACUAUUAAGU
3'
3'
3'
UUUGUCGAGUAACCCUAAAGU
UUCGGGAAUUCACCGCAAAUU
UAAGCCCAAUGACCAUUGUUU
UUAUUCGGGUUACUGGUAACA
U
R
3'
51
CCAAGUGGCUUAUGUCAAUUU 3'
51
3'
5 '
1119
R
UGAGCAAACCUGCCAAAGAUU 3'
5'
1223
R
591
RU
3' UUACUCGUUUGGACGGUUUCU
(Note: R/U refers to Reynolds et al. (2004) and Ui-Tei et al. (2004), respectively)
DActin NS #1
Rn18s NS #1
SActin NS #2
Rn 18s NS #2
rr-6..rfL
E1-7
E1-1
rFLM .Rita. ffl Lmm,.
E1-8
E1-5
E1-2
EI-6
E1-4
EI-10
sIRNA Sequence
~rii
E1-13
E1-3
E1-12
El-11
E1-9
Figure 4-3. Relative Ccnel mRNA expression in CHO cells transfected with 13 unique
siRNAs.
mRNA expression at 48 hours post-transfection is calculated relative to two different nonsilencing controls (NS #1 and NS #2). Two different housekeeping genes (#-Actin and Rn18s)
were used as internal controls.
0.4
1.4
slope
0.3
0-91
0.19
0.2
V1.2
0
01
COe
slope 0.84
0.17
0.1
1.0
0 0l
0--
0.2
0-1
0.0
08
0-3
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-0.6
QNon-silencing control #2
0.0
0.0
0.1
0.2
0.7
0.6
0.5
0.4
0.3
(fiActin
Control)
Relative CCnEI mRNA Expression
0.8
0.9
1.0
Figure 4-4. Graphical representation of Figure 4-3.
The inset graph shows those data points with a relative expression level <40% of the internal
controls. mRNA expression is calculated relative to non-silencing control #1 (dashed) and nonsilencing control #2 (solid). Best fit lines are linear regressions of either data set (slope ±S.E.).
E
0.4
,0.8
0.2
>
NS
Control
Growth
Control
E1-1
E1-2
E1I-5
siRNA Sequence
E1-6
E1-7
E1-8
Figure 4-5. Consistency of relative CcnE1 mRNA expression following transfection with
most effective siRNAs.
Relative expression is calculated 48 hours post-transfections and is relative to non-silencing
control #1 with 8-Actin used as an internal control. The 'Growth Control' is an untransfected
cell population. (Error bars: S.E., n = 3)
Now that we have identified a number of unique and highly effective siRNAs that target
different parts of the CcnEl mRNA we wanted to determine the effect of CcnE1 knockdown on
IFN-y productivity. We sought determine if targeting CcnE1 alone was sufficient to improve
recombinant protein production.
Differential specific productivities were calculated and
compared between day 2 and 4 following siRNA transfection.
Our experiments were not
continued beyond day 4 as mRNA knockdown generally recovers within 96 hours post-siRNA
transfection (Ngantung, 2005). The fold-increases in differential specific productivity, qp,
diff,
following CcnE1 siRNA transfection relative to a non-silencing control are shown in Table 4-3.
When comparing the growth, or untransfected, control with the non-silencing control it is clear
that the transfection with siRNA alone negatively impacts IFN-y productivity. However, in order
to understand the effect of CcnE 1 knockdown, we compare changes in productivity with the nonsilencing control.
In all but one case, transfection with El-5, we are able to significantly
increase IFN-y productivity (p < 0.01) by knocking down CcnE1 expression. On average, we are
able to increase productivity by 137 ± 35% when compared with the non-silencing control, and
by 159 ± 13% when El-5 is not included. When compared with the growth control, the specific
productivity is halved following transfection with the non-silencing control.
However, this
reduction either does not occur or is not as drastic following transfection with all of the CcnE1
siRNA. In other words, knockdown in CcnE1 expression appears to cause the transfected cells
to recover from the negative effects of the transfection.
In addition to determining the effect CcnE] knockdown has on productivity, we also hoped to
determine the effect of knockdown on cell growth. Referring back to Figure 4-1, it is clear that
large differences in cell density are not generally observed on day 4. In our experiments, three of
the siRNA transfections (El-5, -6, and -8) showed a reduction in growth (data not shown, p <
0.05) by day 4 when compared with the non-silencing control. One of the drawbacks of transient
transfection is that we cannot draw conclusions about the effect of knockdown beyond day 4.
We are encouraged that some of the knockdowns showed a reduction in growth by day 4 and
believe that extended shRNA expression may lead to a reduction in growth beyond day 4.
Table 4-3. Fold-increase in qp, diff relative to a non-silencing control following siRNA
knockdown of CcnEl expression (n=2)
Fold-increase (X) in
p < 0.01?
qp,diff (D2-D4)
SE
0.00
0.95
0.53
0.55
0.36
0.21
0.93
0.22
NS Control #1 1.00
Growth Control 2.07
E1-1 2.35
E1-2 3.76
E1-5 1.27
E1-6 2.44
E1-7 2.64
E1-8 1.76
Avg
2.37
±
0.35
Avg (w/o E1-5)1 2.59
±
0.13
4.4
Conclusions
This chapter has shown that inhibiting the CcnEl-CDK2 complex, both through chemical
inhibitors and siRNA targeting of CcnE1, results in a significant increase in IFN-y specific
productivity.
In addition, prolonged chemical inhibition (more than 48 hours) of the CcnEl-
CDK2 complex also results in growth arrest. Since the time that we began our initial study into
CcnE1 and CDK2 inhibition, March and Bentley (2007) have performed similar work in
Drosphila S2.
In their work, the transient transfection of antisense RNA against CcnE]
increased the specific productivity of green fluorescent protein (GFP). Interestingly, they found
that complete silencing of CcnE1 had detrimental effects on GFP expression and that there was
an optimal level of silencing that resulted in the greatest increase in per cell GFP expression.
GFP, however, is not the best model protein to use in these types of studies because it is not a
secreted recombinant protein. In addition, the effect of long term CcnE] silencing on overall
productivity was not analyzed. Our work, on the other hand, aims to apply CcnE1 knockdown to
a production relevant cell line, secreting a recombinant protein. In addition, by designing an
inducible shRNA expression system we will be able to tune the level of CcnE] knockdown to its
optimum level.
Because of limitations associated with transient transfection methods, namely the relatively
quick recovery of mRNA knockdown, we are unable to determine the long-term effects of
CcnE1 siRNA knockdown on growth and productivity in these experiments. We address this
limitation in the next chapter, where we discuss the work we performed in developing a cell line
that inducibly expresses shRNA targeting CcnE] over extended periods of time.
5
STABLE shRNA EXPRESSING CELL LINE: A PATH FORWARD
5.1
Introduction
RNA interference (RNAi) technology, or the stable expression of shRNAs, has been used to
improve recombinant protein production in CHO cells in a number of different ways. These
approaches include the silencing of apoptotic genes (Lim et al., 2006; Sung et al., 2007; Wong et
al., 2006b), silencing genes involved in glycosylation (Ngantung et al., 2006; Mori et al., 2004),
and silencing lactate dehydrogenase (Kim and Lee, 2007).
The typical shRNA expression
systems employed in all of these studies are either the pSUPER system (H1
promoter,
OligoEngine, Seattle, WA) or the pSilencer system (U6 or CMV promoter, Ambion, Austin,
TX). In all of these cases, the shRNA is continuously expressed from a U6, HI, or CMV
promoter.
We planned to use a similar expression system for our work. However, because our target is
CcnE], which acts to control progression through the cell cycle, we needed to modify these
systems to control CcnEl shRNA expression.
Controllable systems for the expression of
proteins (Tet-On/Tet-Off, Clontech, Mountain View, CA) and shRNA (Tet-Inducible shRNA
System, Clontech, Mountain View, CA) are commercially available and consist of a modified
tetracycline repressor (tetR) protein, which binds to the tetracycline operon (tetO) placed
upstream of a promoter of interest. The CKIs p21 and p27 along with the CCAAT/enhancerbinding protein a (C/EBPa) and the survival factor bcl-xL have been controllably over expressed
with a Tet-On system in CHO cells (Fussenegger et al., 1998; Mazur et al., 1998). In the Tet-On
system, the tetR protein is fused with the activating domain of virion protein 16 (VP16) of the
herpes simplex virus (Gossen and Bujard, 1992), which in the presence of tetracycline or
doxycycline, binds to tetO sequences and activates expression from a minimal CMV promoter.
As far as we are aware, there have been no reports in the literature involving the controlled
expression of shRNA targeting a native constitutively expressed gene in CHO cells. However,
such a systems has been shown to be able to control the knockdown of green fluorescent protein
(GFP) expression in CHO cells (Malphettes and Fussenegger, 2004). In this work, anti-GFP
shRNA expression was suppressed in the absence of tetracycline or doxycycline by a
tetracycline-controlled transcriptional suppressor (tTS) protein, which is a fusion of the tetR
protein and the KRAB domain of human Kox1 (Deuschle et al., 1995). Following the addition
of doxycycline, the shRNA is expressed from a CMV promoter and GFP expression is knocked
down.
Our work represents, to the best of our knowledge, the first attempt to inducibly knockdown a
native CHO gene with RNAi. We tried two different systems for the controllable expression of
shRNA: (1) pSingle-tTS-shRNA, a commercially available expression vector that allows for the
one-step selection of shRNA inducible expression, and (2) a modified version of pSilencer 4.1CMV, which requires first stably selecting for a cell population expressing the tTS protein and
then selecting for inducible shRNA expression.
5.2
pSingle-tTS-anti CcnEl shRNA
y- CHO cell lines were created that stably express the pSingle-tTS-anti CcnE 1 shRNA expressing
each of our highly effective shRNA sequences. Following transfection, the cells were selected
with 600 pg mL-1 neomycin for over 2 weeks followed by the isolation of single cell colonies by
serial dilution in 96-well plates. In total, 58 single cell colonies were isolated and screened for
CcnE1 mRNA knockdown, compared with the manufacturer's recommendation
of 30
(Knockout TM Single Vector Inducible RNAi System User Manual, 2007). CcnE] knockdown
was quantified 72 hours following the addition of 1000 ng mL- to the medium. None of the
isolated colonies were able to induce a knockdown that was greater than 30% (data not shown).
Our hypothesis is that the U6 pol II promoter is not strong enough to express the necessary
amount of shRNA needed to silence CcnE1.
A number of previous researchers have reported some difficulty using U6 driven shRNA
expression in y-CHO cells (Ngantung et al., 2006; Lim et al., 2006). Ngantung et al. (2006)
screened over 500 single cell colonies expressing anti-sialidase shRNA driven by a U6 promoter
and was unable to identify a single clone with over 50% reduction in sialidase activity. Lim et
al. (2006) screened approximately 350 single cell colonies expressing anti-Bax or anti-Bak
shRNA and found only 3 colonies that significantly reduced Bax or Bak expression. Lastly,
Mori et al. (2004) were unable to detect any significant reduction in al,6 fucosyltransferase
(FUT8) expression in puromycin-resistant colonies expressing siRNA driven by a U6 promoter.
One alternative to the U6 pol II promoter is a CMV pol III promoter (Malphettes and
Fussenegger, 2004). CMV driven expression has been shown to be a more effective in reducing
mRNA expression in our y-CHO cell line (Ngantung et al., 2006).
In addition, during
discussions with colleagues familiar with the induced expression of proteins, it was mentioned
that it is easier to develop inducible systems via a two-step process. In this two-step process, we
would first create a cell line stably expressing the tetracycline-controlled transcriptional silencer
(tTS) followed by the introduction of the shRNA expression plasmid. For these reasons, we
chose to stop our work with the pSingle vector and instead focus on developing the modified
pSilencer system discussed in Section 5.3.
5.3
Tetracycline-controlled Transcriptional Suppressor (tTS) Cell Line
The first step in creating our CMV driven shRNA expressing cell line was to first create a stable
cell line expressing the tetracycline-controlled transcriptional suppressor (tTS).
As was
mentioned previously, the tTS protein is a fusion of the tetracycline repressor (tetR) protein and
the KRAB silencing domain of human Koxl (SDKid-) (Deuschle et al., 1995). When 7 repeats
of the tetracycline operator (tetO7 ) are placed upstream of a CMV promoter, the tTS protein
binds to tetO 7 and represses expression from the upstream promoter.
The tTS protein
preferentially binds to doxycycline or tetracycline, and CMV driven expression is induced
following doxycycline addition, reaching a peak expression at 48 hours post-addition. Stable
expression of the tTS occurs following stable transfection with the commercially available
plasmid ptTS-neo (Clontech, Mountain View, CA) and selection with 600 pg mL- neomycin.
Once single cell colonies were isolated and expanded, we performed RT-PCR to determine
which colonies had the highest expression levels of tTS. Figure 5-1 shows the results from the
four best single cell colonies. All four single cell colonies show reasonable expression of the tTS
mRNA. The negative control is the original IFN-y CHO cell line, which was transfected with
ptTS-neo vector and, as expected, showed no tTS expression. The expression of /3-Actin was
used as a positive control.
tTS
Actin
2 15 18 2D . +
Figure 5-1. RT-PCR of tTS expressing single cell colonies.
Gel electrophoresis of the four highest tTS expressing single cell colonies. The tTS product is
shown on the top of the gel. The original IFN-y CHO cell line acted as the negative control (-),
while the positive control (+) was the mRNA from a commercially available HeLa tTS cell line
(Clontech, Mountain View, CA).
Once we had a handful of single cell colonies that showed high levels of tTS expression, we
screened them for their ability to control shRNA expression.
This was done with an anti-
luciferase shRNA induction assay. In this assay, we introduce two vectors via transfection,
pGL2 (a luciferase expression plasmid) and a modified version of the pSingle-anti-luciferase
shRNA plasmid (Figure 3-7) in which the tTS expression cassette has been removed. Varying
amounts of doxycycline were added to the medium 4 hours post-transfection and luciferase
expression was quantified 48 hours post-addition, the results are shown in Figure 5-2. All data
is normalized to luciferase expression with no doxycycline addition.
As one can see, the
addition of doxycycline has a small impact on luciferase expression in the growth control.
However, we observe a marked decline in luciferase expression when compared to the growth
control in the cells that are transfected with the pSingle-anti-luciferase shRNA plasmid. This
suggests that we are able to control expression of shRNA in our tTS cell lines.
Of the four single cell colonies that were tested, tTS-2 (Figure 5-2A) performed the best in this
assay. Ideally we would like to observe the induction of knockdown at the lowest possible
concentration of doxycycline (dox). Doxycycline can be cytotoxic at concentrations as low as
200 ng mL-1 and can have begin to have detrimental effects in tet-on systems at concentrations
nearing 2000 ng mL-1 (Ermak et al., 2003). We hypothesize that this cytotoxicity is the reason
for the reduction in luciferase expression in the growth control as the doxycycline concentration
increases. We would like to minimize these cytotoxic effects by choosing the cell colony that
responds to the lowest concentrations of doxycycline. Both tTS-2 and tTS-6 showed significant
reduction in luciferase activity at 10 ng mL-I. Comparing these two single cell colonies over the
range of doxycycline concentrations used, the tTS-2 cell line performs slightly better over all
concentrations. Luciferase expression continues to predictably decrease as more dox is added
the medium.
In addition, the tTS-2 cell line reduces luciferase expression 2-fold upon the
addition of 10000 ng mL-1 doxycycline.
We then repeated the same luciferase assay with only the tTS-2 cell line, and the results are
shown in Figure 5-3. The data is shown in two different ways, luciferase expression is shown
relative to no doxycycline addition in A and is normalized to the growth control in B. As one
can see, we are able to reproducibly induce the expression of anti-luciferase shRNA and
knockdown luciferase expression with the addition of as little as 1 ng mL' of doxycycline. In
addition, we are able to knockdown luciferase expression up to 3-fold, which compares
favorably to other protein level knockdowns by shRNA in our IFN-y CHO cell line (Ngantung et
al., 2006).
1.2
1.2
00
Z 1.01.0
a00
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0.8 -
X 0.8-
0.6
0.6
ig
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0.2
-- Growth
--
0.0
Growth
0.0
0
10
100
1000
Doxycycline (ng mL-)
10000
0
10
100
1000
Doxycycline (ng mL)
10000
1.2 -1.2
0
-
0
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0.2-
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Growth
10
100
1000
Doxycycline (ng mL')
-o- tTS-20
--+-
0.0 11
0
10000
Growth
10
100
1000
Doxycycline (ng mL~)
10000
Figure 5-2. Luciferase knockdown in tTS expressing cell lines.
Relative luciferase expression is shown for 4 tTS expressing cell lines: tTS-2 (A), tTS-6 (B),
tTS-18 (C), tTS-20 (D). Luciferase expression is measured 48 hours post doxycycline addition
and is shown relative to no doxycycline addition. The growth control is the original y-CHO cell
line.
100
1.4
1.2
1
0.8
0.6
0.4
0.2
0.1
10
1
100
1000
10000
1000
10000
Doxycycline (ng mL1 )
1.2
1
0.8
0.6
0.4
0.2
0
0.1
10
1
100
Doxycycline (ng mL')
Figure 5-3. Induction of luciferase knockdown in tTS-2.
Repeat of the luciferase knockdown experiment with only the tTS-2 colony. Data is shown in
two ways: (A) Expression relative to no doxycycline addition and (B) expression relative to no
doxycyline addition and normalized against the growth control at each doxycycline
concentration. (Error bars: S.E., n=3)
101
5.4
pSilencer-tetO 7-CMV-anti CcnE1 shRNA Expressing Cell Line
We stably transfected our tTS IFN-y CHO, from Section 5.3, cell line with our modified
pSilencer plasmids expressing four different shRNAs: El-1, El-2, E1-6, and E1-7. We decided
to focus our efforts on the best performing shRNAs from our initial siRNA screening (Chapter
4). Referring back to Table 4-3, El-1, E1-2, E1-6, and E1-7 all yielded the largest increases in
specific productivity.
The appropriate shRNAs were then designed from these siRNA
sequences, as can be seen in Table 3-5. Following transfection, selection, and single cell colony
isolation, we performed a series of screens to determine which single cell colonies had the ability
to consistently induce CcnE] knockdown following the addition of doxycycline to the medium.
All of the initial screening experiments used 100 ng mL
of doxycycline for induction.
Although Figure 5-3 suggests that as little as 1 ng mL' doxycycline is enough to induce shRNA
expression, knocking down constitutively expressed native genes likely requires higher levels of
intracellular shRNA. Also, because doxycycline can potentially be cytotoxic at 200 ng mL'
(Ermak et al., 2003) we used a concentration slightly lower to ensure the doxycycline itself did
not cause any aberrant observations
The first round screen was performed in duplicate in 24-well plates, and a sampling of the
knockdown results 48 hours after doxycycline addition are shown in Figure 5-4. Overall we
screened 139 single cell clones across all 4 shRNA sequences (El-1: 38, El-2: 33, El-6: 32, El7: 36) and found 22 clones (20%) that reduced CcnE1 mRNA expression by 30% or greater.
This further strengthened our initial hypothesis that the polymerase III promoter in the pSingle
expression system, from Section 5.1, did not yield high levels of intracellular shRNA. Only five
colonies reduced CcnE] expression greater than 50% (El-1BD, El-2BF, El-2BC, El-2E and
102
El-7Q). The El-2 shRNA seems to be the most effective shRNA sequence in this first screen,
with 3 of the best performing clones expressing this shRNA.
A second follow-up screen was performed on 24 single cells colonies (the 22 colonies that
showed greater than 30% knockdown, plus 2 colonies with 29% knockdown).
This second
screen was performed in triplicate and in 6-well plates and the results are shown in Figure 5-5.
Of the 24 total screens that were performed, 20 are shown in the figure. The single cell colonies
that were omitted showed an increase in CcnE1 expression 48 hours following doxycycline
addition. Overall, 7 single cell colonies showed an induced CcnE] knockdown of greater than
30% (El-H, El-2J, El-2BD, El-61, El-7K, El-7AI, El-7AF). This second screen had a slightly
higher success rate than the first (29% compared with 20%); however, we would have expected
it to be much larger. In addition, none of the five colonies that reduced CcnE1 expression below
50% in the first screen, showed any effectiveness in this second screen. We are inclined to
believe that the results of the second follow-up screen are more accurate because it was
performed in triplicate and the data was normalized to
should be noted, that
#-Actin
#-Actin
mRNA levels.
However, it
normalization does not drastically affect the final results (data not
shown).
103
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0.7 -
C.
W 0.6
z
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w
r~
0.4 -
-
0.3 0.2 0.1 0
1
.
.
.
.
.
.
. .
1
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C
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.
..
D
LUJ U
-
LU
-LU
LLU
LU
W
U
W
LU
-
LU
LU
LU
WL
Colony ID
Figure 5-4. First round screen of pSilencer-tetO 7 -anti CcnE1 shRNA expressing single cell
colonies.
Relative knockdown is measured 48 hours after the addition of 100 ng mL-1 of doxycycline, and
all CcnE1 mRNA expression levels are shown relative to no doxycycline addition. CcnE1
mRNA levels are not normalized to #-A ctin in this first round screen.
104
1.4
E1-1
I
I
EI-2
EI-6
I
E1-7
1.2-
0
1
0
C.
z
0.8-
E
0.6-
0.4-
004
0.2-
-
0ZM
CC
-
'
M
CM
M
M
LU
uCj
UJ
.
-
-
-
-1
-
Colony ID
Figure 5-5. Second round screen of best performing single cell colonies from the first round
screen.
Relative knockdown is measured 48 hours after the addition of 100 ng mL- of doxycycline and
all CcnE1 mRNA expression is shown relative to no doxycycline addition. -Actin is used as an
internal control in this screen.
105
According to well-annotated methods for confirming the specificity and consistency of shRNA
knockdown (Cullen, 2006), it is important to test for a dose-response when inducing shRNA
expression. Therefore, we further analyzed our 7 best single cell colonies by adding increasing
amounts of doxycycline to them (0, 10, 100, and 1000 ng mL-) and measured the effect that this
had on CcnE] mRNA expression. The results are shown in Figure 5-6. As expected CcnE1
mRNA levels do not change drastically in the tTS control colony until the addition of 1000 ng
mL' doxycycline when CcnE1 expression is reduced by 36%. This further validates our initial
assumption that all screening should be done with doxycycline concentrations of 100 ng mUL1 .
The five colonies that exhibited a dose-response behavior are also shown. Colonies El-2BD and
E -7K have lost the ability to induce CcnE] knockdown and are not shown. Of the remaining 5
colonies, both El-1H and El-2J showed an induction of CcnE] expression following the
addition of 10 ng mL- of doxycycline, but did show an induced knockdown at the elevated
doxycycline concentration of 100 ng mUL.
Single cell colonies El-61, El-7AI, and El-7AF
showed reasonable reductions in CcnE1 expression following the addition of 10 ng mL
doxycycline.
106
2
1.8 1.6 1.4
0 ng/mL
10 ng/mL
100 ng/mL
1000 ng/mL
-
1.2 1
0.8
0.6
0.4
0.2
tTS
E1-1H
E1-2J
E1-61
E1-7Al
E1-7AF
Colony ID
Figure 5-6. Dose-response of single cell colonies to increasing levels of doxycycline.
Relative knockdown is measured 48 hours after the addition of doxycycline and all CcnE1
mRNA expression is shown relative to no doxycycline addition. #-Actin is used as an internal
control (Error bars: S.E., n=1).
107
The results of all the screens have been summarized in Table 5-1. None of the 5 best performing
single cell colonies from the first screen showed any knockdown in the subsequent screen and
were not brought forward for further analysis. Of the 22 single cell colonies, 7 exhibited a
knockdown in CcnE1 expression of greater than 30% in the second screen and are also shown in
the table. - The extremely low relative CcnE1 expression for clone El -7AF in the second round
screen is likely a result of the loss of some sample during the screening process and was not
included in the final average for that clone.
During the third 'dose-response' screen, 2 of the single cell colonies (E1-7K and El-2BD) lost
the ability to induce CcnE1 knockdown. A total of 5 single cell colonies, however, showed the
ability to consistently knockdown CcnE1 levels 48 hours following the addition of 100 ng mL I
doxycycline in all of the screens. These results are combined in the table and show that clone
El-61 was able to induce the largest decrease in CcnE1 expression, while clone El-7AI was the
most consistent.
108
Table 5-1. Screening summary of induced CcnEJ knockdown following 100 ng mLdoxycycline addition
Most Successful 1" Round screens
El-1BD
0.46
0.93
E1-2BF
0.17
1.13
E1-2BC
0.26
0.79
E1-2E
0.44
2.31
E1-7Q
0.44
4.12
Lost Ability to Induce Knockdown
El-7K
0.54
0.23
2.01
El-2BD
0.56
0.60
1.85
Most Consistent Colonies Overall
El-1H
0.71
0.22
0.80
0.58
0.18
E1-2J
0.70
0.43
0.83
0.65
0.12
El-61
0.71
0.37
0.61
0.56
E1-7AI
0.61
0.67
0.63
0.63
0.02
E1-7AF
0.68
0.04
0.81
0.75
0.07
109
t
0.10
We then further analyzed our 5 best performing clones to determine what affect the induction of
CcnE1 knockdown had on cell growth and specific productivity. There experiments were again
performed in 6-well plates in triplicate and lasted 6 days. We measured relative CcnE1 mRNA
levels, cell density, and IFN-y titer in the supernatant.
The growth curves from these
experiments are shown in Figure 5-7. Viability remained above 95% for all clones throughout
the experiment (data not shown). We observe a decrease in cell growth following the addition of
doxycycline to clones El-2J and El-7AF. Importantly, the growth of the base tTS cell line was
unaffected by doxycycline addition.
None of the other clones slowed in growth following
doxycycline addition.
Table 5-2 further summarizes the results from our 5 best performing clones on the induced
knockdown of CcnE1 and the impact of knockdown on specific productivity. In addition, clone
E 1-61 is the only single cell clone that maintains CcnE1 knockdown until day 3. We hypothesize
that this is because our expression system is not expressing or maintaining high levels of
intracellular shRNA. For this reason, the actual phenotypes that we observe are called into
question. Nevertheless, only two colonies, El-2J and El-7AF, show a reduction in growth.
Although CcnE1 levels are reduced for the longest time in the clone El-61, it does not slow in
growth. Clone El-2J is the only clone that shows an increase in specific productivity and a
decrease in growth following doxycycline addition
In general, there is very little consistency over time amongst our results. Knockdown does not
necessarily result in the slowing of growth (El-7AI, for example), and the slowing of growth
does not necessarily result in an increase in specific productivity (El-7AF, for example). We
110
hypothesize that this is likely because our expression system is not expressing shRNA to levels
high enough to induce a consistent phenotype. In addition, it is conceivable that expression from
the shRNA cassette is reduced or eliminated through common cellular events like DNA
methylation or the inherent genetic instability of CHO cells.
111
tTS
-- -dox
--
0
+dox
2
---..
-9-
0
2
0
2
4
6
8
4
Time (d)
6
8
Time (d)
Time (d)
6
8
E1-61
ox
+dox
2
0
4
2
0
4
Time (d)
2
4
Time (d)
6
4
6
Time (d)
8
Figure 5-7. Growth curves of single cell clones with or without the addition of 100 ng mL 1
doxycycline.
Total viable cells per 6-well plate is shown as a function of time. Single cell clones were grown
in the (o) presence or (+) absence of 100 ng mL' doxycycline. Doxycycline addition occurred
on day 2. (Asterisk represents a statistically significant difference in cell density, Ip< 0.05)
112
Table 5-2. Summary of the effects of 100 ng mL 1 doxycycline addition to single cell clones
tTS
1.15 ± 0.00
0.87 ± 0.09
El-1H
0.89
0.08
1.18
0.25
N
N
0.56
El-2J
0.80
0.06
1.17+0.37
Y
Y
1.55
El-61
0.72
0.04
0.66
0.15
N
N
0.90
El-7AF
0.92
0.09
1.18
0.37
Y
N
0.62
El-7AI
0.40 ±0.15
1.24
0.49
N
N
1.15
+
0.80
113
5.5
Conclusions
We created a functional tetracycline-controlled transcriptional silencer (tTS) expressing IFN-y
CHO cell line expressing high levels of the tTS protein with the ability to control shRNA
expression. However, we were unable to express shRNA to high enough levels, regardless of
promoter type, to consistently knockdown CcnE] mRNA levels by more than 30%.
We
hypothesize that this level of knockdown is not large enough to induce a consistent functional
change in phenotype. Although tTS controlled shRNA expression systems have been used to
control to the expression of GFP (Malphettes and Fussenegger, 2004), in these systems, GFP
mRNA is likely not expressed to the same high levels as an endogenously expressed gene like
CcnE1.
In addition, over time the single cell colonies slowly lost their modest ability to
knockdown CcnE] mRNA. The reason for this is currently unknown, however we hypothesize
that common cellular events, like DNA methylation and genetic instability, could lead to loss of
shRNA expression. Because of these issues with our expression system, we are unable to answer
the over-arching question of whether prolonged CcnE1 knockdown can result in overall
increases in total IFN-y productivity.
We think that this type of system, however, has the potential to work in the future.
With
improvements in shRNA expression systems, that can express very high levels of shRNA with
low levels of inducing chemicals (doxycycline), this approach could be quite successful. Our
proof-of-concept experiments provide compelling evidence to suggest that inhibition or
knockdown of CcnE] can, at the very least, result in improvements in specific productivity.
114
6
SHORT TERM CDK INHIBITION: GROWTH, CELL CYCLE, AND
PRODUCTIVITY
6.1
Introduction
It is important to understand the relationships between cell cycle, growth and productivity when
developing a recombinant protein production process in order to best optimize the medium,
culture conditions, and bioreactor operations.
A number of studies have been performed
attempting to systematically determine the relationship between cell cycle and the specific
productivity of both secreted (i.e. tPA, IFN-y and SEAP) and intracellular proteins (i.e. PGalactosidase and DHFR).
The vast majority of these studies were performed in normal
exponentially growing CHO cell cultures and these studies have elucidated relationships between
productivity and Gi-phase (de Boer et al., 2004; Kubbies and Stockinger, 1990), S-phase (Gu et
al., 1993; Kubbies and Stockinger, 1990; Lloyd et al., 1999, Mariani et al., 1981), G2/M-phase
(Lloyd et al., 2000; Yokota and Tanji, 2008), aphasic (Feder et al., 1989) and inversely related to
Gi-phase (Yamaji et al., 2004).
These apparently contradictory results generally can be
explained by differences in the expression system, protein of interest, promoter construct, culture
conditions, and experimental design.
Very few systematic studies have been performed that elucidate the relationship between cell
cycle and productivity in growth arrested cells. Increases in the specific and total productivity of
recombinant proteins have been shown to occur during Gi-phase growth arrest in low
temperature culture (Hendrick et al., 2001; Kaufmann et al., 1999; Yoon et al., 2003), following
the addition of butyrate to cell cultures (D'Anna et al., 1980, Hendrick et al., 2001), and
following. the overexpression of CKIs (Bi et al., 2004; Carvalhal et al., 2003a; Fussenegger et al.,
1997). In most of the above work, the G, phase of the cell cycle was specifically targeted for
115
growth arrest. In addition, increases in productivity have also been shown to occur during Sphase growth arrest following the addition of various nucleotides and nucleosides, including
AMP, to culture medium (Carvalhal et al., 2003b). It is unclear whether these improvements in
productivity are directly related to the specific cell cycle phase in which arrest occurs, or if
growth arrest alone is sufficient to improve productivity. To our knowledge, there have been no
reports of studies that determine the effect of specific differences in cell cycle distribution have
on either arrested or slowly growing cells.
We proposed to induce specific changes in cell cycle distribution through the addition of
exogenous chemical CDK inhibitors, Table 3-1. We have shown previously (Chapter 3) that the
addition of a CDK2 inhibitor results in extended growth arrest and increases in specific
productivity. By adding inhibitors of other CDKs, we were able alter cell cycle distribution in
slowly growing or arrested cells and quantitatively assess the impact on specific productivity.
Most importantly, because we are targeting highly specific cell cycle regulating proteins, we
believe we are able to determine the relationship between cell cycle, productivity, and growth
without metabolic disruption.
6.2
CDK Inhibitor Characterization
All of the inhibitors that were used in this thesis have been previously characterized in the
literature (Brooks et al., 1997; Bhattacharjee et al., 2001; Pennati et al., 2005; Vassilev et al.,
2006; Retzer-Lidl et al., 2007). Starting from the known IC50 concentrations (Table 3-1), we
added varying amounts of the inhibitors to growing y-CHO cells. Cells were plated at 1x10 5
cells/well and inhibitors were typically added during exponential growth 2 days later when the
116
viable cell density was approximately 1x10 6 cells well-1. In addition, because our inhibitors are
dissolved in DMSO, we added equal volumes of DMSO to our control cultures to ensure that our
observations are not caused by DMSO-induced growth arrest (Fiore and Degrassi, 1999).
Finally, we added inhibitors at a cell density of 1x106 cells well' to prevent cell density related
growth arrest within our experimental time frame of 36 hours.
Figures 6-1 and 6-2 show
representative growth curves following the addition of inhibitors cdk2iii, cdkliv, cdk4, and
cdk2iv at varying concentrations.
Viability remained above 90% across all inhibitors and
concentrations (data not shown).
We are able to drastically slow cell growth following the addition of the inhibitors cdk2iii and
cdkliv as can be seen in Figure 6-1. Shedding occurs following the addition of 10 and 20 gM
cdk2iii, and is the reason for the decline in viable cell density. The actual growth rate in these
cultures is actually zero.
Shown in Figure 6-2, 2.5 gM was the only cdk4 inhibitor
concentration that slowed growth without killing the cells. All concentrations higher than 2.5
gM that were tried resulted in massive cell death prior to 36 hours. This cell death even occurred
following the addition of only 3.5 gM cdk4 inhibitor.
The addition of inhibitor cdk2iv
drastically slowed cell growth, Figure 6-2. We will go into more detail regarding inhibitor
cdk2iv in Section 6.3.
The specific growth rate was estimated for each inhibitor concentration assuming an exponential
model of cell growth and assuming no cell death was occurring.
assumptions given the short time frame of our experiments.
117
These are both reasonable
3-
Growth Control
A cdk2iii - 10 uM
x cdk2iii - 20 uM
= 2.5 0
2cdk2iii - 5 pM
1.5 -
cdk2iii -10 pM
0.5cdk2iii - 20 pLM
0
20
40
Time (hours)
60
80
3.5
Growth Control
o Growth
A cdkliv- 10 uM
x cdkliv - 20 uM
B
cdkliv - 10 piM
2.5 -
)2
.01.5
204
0
08
0.5
0
20
40
60
80
Time (hours)
Figure 6-1. Cell growth curves in the presence of inhibitors cdk2iii and cdkliv.
The figures show representative growth curves of y-CHO cells in the presence of inhibitors (A)
cdk2iii and (B) cdkliv. (Error bars: S.E., n=1)
118
6
* Growth
Growth Control
o cdk2iv - 5 uM
A cdk4 - 2.5 uM
5
O
cdk4 - 2.5 jM
3 -
a]
0
20
40
Time (hours)
c dk2iv - 5
60
MN
80
Figure 6-2. Cell growth curves in the presence of inhibitors cdk4 and cdk2iv.
The figure shows representative growth curves of y-CHO cells in the presence of inhibitors (A)
cdk4 and (o) cdk2iv, and in control cultures (Error bars: S.E., n=1)
119
We also determined the effect of each inhibitor on cell cycle distribution and compared our
results with those previously reported in the literature. Cells that were growing in 6-well plates,
in the presence and absence of inhibitors, were sacrificed at predetermined intervals, fixed in
ethanol, propidium iodide (PI) stained, and analyzed by FACS. Figure 6-3A, shows the cell
cycle distribution over a 36 hour time frame in exponentially growing y-CHO cells. Between 8
and 12 hours we observe cells transitioning from the Go/Gj to the S-phase of the cell cycle.
Between 12 and 16 hours we observe cells transitioning from the S to the G2/M-phase of the cell
cycle. Also, it is clear that accumulation begins to occur in the Go/Gi-phase of the cell cycle
after 36 hours, Figure 6-3B. The accumulation of cells in G, during confluence is observed in
nontransformed and immortalized cell lines (Fiore and Degrassi, 1999) and is the reason we stop
our experiments at 36 hours. In this way, we can eliminate the effects that cell density can have
on cell cycle distribution.
Figures 6-4, 6-5, and 6-6, show the effect of each of the inhibitors on cell cycle distribution.
The inhibitor cdkliv, Figure 6-4, noticeably increases the number of cells in G2 /M, in a
concentration dependent manner. The G2 /M peak is much larger in Figure 6-4B when compared
to 6-4A. In addition, the G2 /M peak is delayed at the higher inhibitor concentration. This is
partially because inhibitor was added to cells with different cell cycle distributions at time 0.
Part of this delay can be explained by the fact that these two experiments were performed at
different times, and the inhibitors were added at different cell densities. The delay is also due, in
part, to the inhibition of CDK2, which is also inhibited by cdkliv at elevated concentrations.
120
The inhibitor cdk2iii acts by delaying progression from the Gi to the S-phase of the cell cycle,
Figure 6-5, and like the inhibitor cdkliv this delay is concentration dependent. Although we did
not take a 12-hour time point when we added 5 tM cdk2iii, we can still compare the data in
Figure 6-5 to the growth control, Figure 6-3. Comparing Figure 6-5B to Figure 6-3A, the peak
in S-phase cells is delayed by 4 hours and slightly decreased following the addition of 10 pM
inhibitor cdk2iii. Comparing Figure 6-5A and Figure 6-3B, when a smaller amount of inhibitor
is added, we do not observe a large change in the S-phase peak, however, progression through Sphase is delayed. In addition, inhibitor cdk2iii also causes an increase in the number of cells in
G2/M, which is caused the inhibition of CDK1, a secondary target of cdk2iii.
Lastly, the inhibitor cdk4 acts by drastically increasing the number of cells in the Gi-phase of the
cell cycle, and inhibits normal progression through the cell cycle, as can be seen in Figure 6-6.
This change in cell cycle progression occurs even though cell growth is only slowed slightly. As
we mentioned previously, increased concentrations of cdk4 rapidly kill cells in culture. It is not
clear if the inhibitor is the cause of death or if cells cannot remain in G1 for extended periods of
time. It should be noted that because CDK4 is inhibited these cells are likely accumulating in
early-G 1 , although there is no way to distinguish between early and late-G 1 with PI staining.
In order to quantify these changes in cell-cycle distribution, we calculated a time-integrated cell
cycle distribution for the entire 36-hour experiment. This time-integrated cell cycle distribution
is the area under the cell cycle distribution curves from Figures 6-3, 6-4, 6-5, and 6-6 divided by
the total experiment time of 36 hours. This takes the cell cycle distribution and time-weights the
average distribution, capturing the general changes that occur over the entire 36-hour period.
121
This value is also sometimes referred to as the average value of the cell cycle distribution. We
hypothesized that a relationship may exist between this quantitative metric and overall changes
in specific productivity.
Table 6-1, shows our calculated values for the time integrated cell cycle distribution for the
growth control and all inhibitors.
These values verify our qualitative observations: cdkliv
increases cells in G2 /M, cdk4 drastically increases cells in G1 , and cdk2iii slightly increases cells
in G2 /M. Perhaps most interesting, and slightly unexpected, is the effect that the inhibitor cdk2iii
has on cells in G1 . Because the inhibitor cdk2ii acts to slow progression through the cell cycle,
we observe an overall decrease in the proportion of cells in G1 when compared to the growth
control.
122
A
7060.
[8
UG2AM
G1G
-+-
-M--S
-G2IM
8
0
16
12
Time (hours)
24
8
0
36
G2/M
16
12
Time (hours)
24
36
B
80
80
70
70
GOG1
+
GO/G1
-BS
*GZ'Mv
60
60
3 50
a
50
40
40
$
30
30
G21M
0
8
24
16
Time (hours)
36
60
0
8
24
16
Time (hours)
36
60
Figure 6-3. Cell cycle distribution in exponentially growing cells.
The cell cycle distribution is shown as a function of time over two slightly different time periods:
(A) 0-36 hours and (B) 0-60 hours. The same data is plotted in two different ways.
123
A 10 tM
70
70
1GO/GI1
60
50
-p-GOiG 1
-ES
S
GOYG1
+G21M
A G2M
~40
)40
30
0 30
20
20
10
G2M
0
0
8
12
16
Time (hours)
24
16
12
Time (hours)
24
36
0
8
12
16
Time (hours)
B 20 M
0
8
36
0
8
12
16
24
36
Time (hours)
Figure 6-4. Cell cycle distribution following the addition of inhibitor cdkliv.
Representative cell cycle distributions are shown as a function of time and the same data is
plotted in two different ways. Inhibitors were added at (A) 10 pM and (B) 20 pM.
124
A 5gM
80
.
70 -
-*-
GO/G1
--
S
-k-- G2/M
60 -
2 50 40 -
$
30 20 10 -
0 0
8
12
16
Time (hours)
24
36
0
8
12
16
Time (hours)
24
36
B 10 tM
70
70
60
60
50
50
40
0%40
30
30
20
20
10
10
0
0
0
8
12
16
Time (hours)
24
0
36
0
8
12
16
Time (hours)
24
36
Figure 6-5. Cell cycle distribution following the addition of inhibitor cdk2iii.
Representative cell cycle distributions are shown as a function of time and the same data is
plotted in two different ways. Inhibitors were added at (A) 5 pM and (B) 10 pM. Data was not
available at 12 hours in the top graph (A).
125
80
70
60
50
40
30
20
10
0
0
8
12
16
24
36
- -
--.....
Time (hours)
I-
80
70
-
60
-
50
-
40
-
-
-
-
-
-
---
GOIG1
-I
SO/G1
&S
A-
G2/M
30-
S
0--
0
8
12
16
24
36
Time (hours)
Figure 6-6. Cell cycle distribution following the addition of inhibitor cdk4.
A representative cell cycle distribution is shown as a function of time and the same data is
plotted in two different ways. The cdk4 inhibitor was added to 2.5 M.
126
Table 6-1. Time-integrated (w
ted) cell cycle distribution
± 1.1
± 2.2
37.6
±
RM
34.7
2.2
38.5
± 1.9
26.8 ± 3.5
20 jtM
28.9
1.7
28.8
± 1.0
42.3
± 2.8
5 ptM
43.8
0.1
33.8
± 0.0
22.4
± 0.1
10 M
36.7
3.4
39.1
± 2.0
24.2
± 2.5
2.5 gM
67.1
3.6
24.5
± 5.5
8.4
± 1.9
10
3.5
10.9
51.3
Growth
cdkliv
cdk2iii
cdk4
(Error bars: ± S.E.)
127
We also determined the effect that inhibitor addition had on specific productivity, qp. Specific
productivity is a measure of the amount of IFN-y produced per cell in a given amount of time,
and is calculated as shown in Section 3.7.1. To reiterate, it is the slope of a linear regression of
cumulative IFN-y production and the integrated viable cell density (IVCD), as shown in Figure
6-7. We show a representative sampling of this data for all of our inhibitors. In most cases, the
addition of CDK inhibitors acts to increase specific productivity, with the lone exception being
10 gM of inhibitor cdkliv, Figure 6-7A, which has little impact on qp. In addition, as more
inhibitor is added to the cell cultures we generally observe an increase in specific productivity.
Now that we have fully characterized our CDK inhibitors in terms of how they effect changes in
growth, cell cycle distribution, and specific productivity, we used this information to determine
the relationships between qp, growth, and cell cycle distribution.
128
A
1.8
1.6
Growth Control
(0.026)
1.4
cdkliv 20 pM
(0033)
. 1.2
cdkliv 10 IM
(0,025)
1
0.8
0.6
*Growth Control
0.4
Ucdktiv - 10 pM
0.2
Ocdkliv - 20 pM
0
0
50
40
30
20
10
70
60
80
Integrated Viable Cell Density (10' cells hr)
2
B
1.8
1.6
cdk2li 10
(0.046)
pM
4
14
Growth Control
(0.026)
cdk2i 20 pM
(0053)
1.2
1
0.8
+Gfowth Contro
0.6
cdk2i - 5 pi
0.4
Ocdk,2i-
0.2
10pM
Ocdk2ini- 20 OM
0
20
10
0
50
40
30
60
70
80
Integrated Viable Cell Density (10' cells hr)
C
Growth Control
(0.042)
4
z
3
IOcdk4
OGrowth Control
-2.5
pM
0
0
20
40
60
80
100
120
140
Integrated Viable Cell Density (100cells hr)
Figure 6-7. Cumulative IFN-y production plotted against Integrated Viable Cell Density
(IVCD) for each inhibitor.
Data is plotted for inhibitors (A) cdkliv (B) cdk2iii and (C) cdk4. The slope of a best-fit line
through the plotted data is defined as the specific productivity, qp. Specific productivity for each
inhibitor concentration is shown in parentheses in units of pg cell' h- (Error bars: S.E., n=1)
129
6.3
Relationship between Specific Productivity and Cell Cycle Distribution
If a relationship exists between a specific cell cycle phase and specific productivity we should be
able to observe a correlation between the two. While this approach does not reveal any causality
between cell cycle phase and productivity, it can reveal the best cell cycle phase to target in a
growth arrest strategy. A typical way of quantifying cell cycle distributions involves calculating
the time spent in each cell cycle phase during one doubling (Hendrick et al. 2001; Slater et al.
1977). We cannot employ this method using our experimental data, because our doubling times
approach infinity as cell growth decreases. Instead, we were able to capture the drastic changes
we made in cell cycle distribution quantitatively by defining a time-integrated cell cycle
distribution. We then sought to determine if there was a correlation between this quantitative
metric and specific productivity.
The time-integrated cell distributions are plotted against
normalized specific productivity below in Figure 6-8. Each of the inhibitor experiments was
performed two or more times and the specific productivities were normalized to the growth
control in each experiment. As one can see from the linear regression correlation coefficients
(Pearson's correlation coefficients), there is a very weak inverse relationship between G1 and
specific productivity and a weak positive relationship between G2/M and specific productivity.
In general, we do not observe any strong correlations between specific productivity and cell
cycle distribution. Interestingly, regardless of the type of inhibitor added we almost always
observe an increase in specific productivity, regardless of the changes made to cell cycle
progression.
It is possible that a linear regression is not the best metric to determine whether a relationship
exists between cell cycle distribution and specific productivity.
130
Another commonly used
correlation coefficient is the Spearman's rank correlation coefficient, which is a non-parametric
measure of dependence between two variables. It determines how well the relationship between
two variables, in our case cell cycle distribution and specific productivity, can be described by a
monotonic function. The Spearman's rank correlation coefficients agree extremely well with the
Pearson's correlation coefficients and are as follows: Go/G 1 - -0.43, S - 0.09, and G2/M - 0.43.
Lastly, rather than using a time-integrated cell cycle distribution to capture the changes in cell
cycle distribution, we could have used the normalized time distributions defined by Slater et al.
(1977). This analysis yields the fraction of time that is spent in each cell cycle phase during a
single doubling. This approach does not substantially change any of the correlation coefficients
(data not shown).
Had we taken a more qualitative approach to this analysis, we could have easily determined that
the G2/M-phase of the cell cycle has a much stronger impact on specific productivity that it
actually does. The inhibitors cdk2iii and cdkliv increase specific productivity the most and also
increase the proportion of cells in the G2/M-phase of the cell cycle. Rather, our analysis with
CDK inhibitors shows that specific productivity does not depend strongly on cell cycle
distribution in slowed growth and growth-arrested cell cultures. This emphasizes the importance
of taking a more quantitative approach to determining the relationship between cell cycle and
productivity.
131
n Growth
o cdk2iii
2.0 - * cdkl iv
x cdk4
2.5
R = -0.43
R = 0.13
* Growth
10 pM
2.0
o cdk2iii
-
* cdkliv
10 PM
x cdk4
20 pM
5PM
25pM
10
PM
Fi
0.5
-
-
1.5 -
20pM
1.0 -
2 5M
0.5
A
5pM
B
-
nn
0
20
40
% GoIG 1
0
10
20
30
40
50
2.5 -
o Growth
o cdk2iii
2.0 - +4cdk1iv
cdk4
1.5
-
R = 0.43
0 PM
5 PM
2.5 pM
1.0
20 pM
-
0.5 -
00 0
C
.
10
20
30
40
50
% G2IM
Figure 6-8. Correlations between normalized specific productivity and cell cycle phase
following inhibitor addition.
qp is shown normalized to the growth control and plotted with respect to the time-weighted
average cell cycle distribution over the entire 36 hour experiment (A) Go/G 1 (B) S and (C) G2 /M.
R = Pearson's correlation coefficients. (Error bars: S.E; n = 6: Growth; n = 3: 10 p.M cdkliv,
1ORM cdk2iii; n = 2: 5 p.M cdk2iii, 20 gM cdkliv, and 2.5 pM cdk4)
132
6.4
Relationship between Specific Productivity and Specific Growth Rate
We also sought to determine the relationship between specific productivity and specific growth
rate following the addition of our CDK inhibitors. Figure 6-9 below shows the same normalized
productivity shown in Figure 6-8 plotted against specific growth rate for all of our inhibitor
experiments.
As one can see from the linear correlation coefficients (Pearson's correlation
coefficients) there is a very strong relationship between specific growth rate and specific
productivity. Most importantly, regardless of the type of inhibitor that was added to the culture,
specific productivity always increased as growth decreased. The only exception is that 10 gM of
inhibitor cdkliv had no impact on productivity.
While increasing specific productivity is a notable achievement in itself, it is only the first step in
increasing overall productivity of a cell culture system. As we know, there is often a trade-off
between specific productivity and the IVCD, and balancing them is necessary to improve total
recombinant protein productivity, (Equation 3-2). The total IFN-y production at a specific time
can be expressed as a function of specific productivity and specific growth rate, p, as shown in
Equation 6-2:
J dP= qp
Ndt
(3-2)
eudt
(6-1)
t
N
P=q,
0
=
]
PNvO[
kt
133
(6-2)
In Figure 6-10, we have added a dashed line to the data from Figure 6-9 that is defined by
Equation 6-3, where P is a constant, and represents total IFN-y production in the growth control
at 36 hours, and No,, refers to the number of viable cells during inoculation.
qp =
N,, 0 [e#' -1]
(6-3)
From Figure 6-10, it is clear that there are a number of inhibitor concentrations, 10 gM cdk2iii
and 20 gM cdkl iv, that can cause an increase in total IFN-y production over the course of our 36
hour batch experiments. This theoretical calculation also agrees with our experimental results,
both cdk2iii and cdkliv have been shown to slightly increase IFN-y production over 36 hours.
Although these experiments do not represent a production relevant cell culture system, this
observation does provide us with some optimism that these inhibitors may be able to improve
total productivity in a batch or fed-batch production scale cell culture.
134
2.5
2.0 -
o Growth
o cdk2iii
+cdkliv
x cdk4
-10 MN
C 1.5
E;VV
N
E
0 1.0Z -
2. M
-
10 pUM
=-0.93
0.5R
I
0.0 -
-0.01
0.00
0.02
0.01
0.03
0.04
t (hr-)
Figure 6-9. Correlation between normalized specific productivity and specific growth rate
following inhibitor addition.
qp is shown relative to the growth control and plotted with respect to the specific growth rate, p.
R = Pearson's correlation coefficients. (Error bars: S.E; n = 6: Growth; n = 3: 10 gM cdkliv,
10gM cdk2iii; n = 2: 5 gM cdk2iii, 20 gM cdkliv, and 2.5 pM cdk4)
135
2.5
2.0 -..
10 M
+ cdkl1iv
x cdk4
L1.5 --
1.5
20 M
M.
M
0 1.0
2.5gM
Z
.
10M
....
0.5 -
0.0-
-0.01
0.00
0.01
0.02
0.03
0.04
p (hr')
Figure 6-10. The effect of normalized specific productivity and specific growth rate on
total IFN-y production.
qp is shown relative to the growth control and plotted with respect to the specific growth rate, p.
The dashed line represents a line of constant total production at 36 hours and is defined by
Equation 6-3. (Error bars: S.E; n = 6: Growth; n = 3: 10 gM cdkliv, 10 gM cdk2iii; n = 2: 5 [tM
cdk2iii, 20 gM cdkliv, and 2.5 gM cdk4)
136
6.5
Further Characterization of Inhibitor cdk2iv
While we have observed that the addition of inhibitor cdk2iv results in an apparent growth arrest
as shown in Figure 6-2, we have not included it in our previous analysis. The reason for this is
that inhibitor cdk2iv behaves differently from the other CDK inhibitors. Rather than induce an
accumulation of cells in G2 /M, as suggested by the manufacturer (Pennati et al., 2005), we
observe that cdk2iv actually induces tetraploidy, or an increase in chromosomes or chromosomal
DNA, in our y-CHO cells. We first observed this behavior during the cell cycle analysis shown
in Figure 6-11, which shows the cell cycle distribution 0, 8, and 24 hours after the addition of 5
gM inhibitor cdk2iv to growing cells.
Within 24 hours, we observe that the entire cell
population is in a tetraploid state.
To further verify that the inhibitor cdk2iv was inducing tetraploidy we visualized the cells postinhibitor treatment using immunofluorescence.
Cells were plated on fibronectin-treated
coverslips and fixed 24 hours after the addition of each inhibitor (cdk2iii, cdkliv, cdk4, and
cdk2iv). The cells were stained with three different dyes/antibodies. DNA was stained with
Hoechst 33258 and detected with a DAPI (blue) filter. y-tubulin, which is found mainly in
centrosomes, was detected with a primary antibody (Gtu.88 y-tubulin antibody) followed by an
AlexaFluor 488 secondary antibody and detected with a fluorescein (green) filter. F-Actin was
stained with AlexaFluor 594 phalloidin and detected with a Texas Red (red) filter. The cells
were then imaged at 60X with a DeltaVision Core deconvolution microscope.
The merged
images are shown in Figure 6-12. The right hand pictures in each group are cropped versions of
the original 60X image on the left. This was done to enhance visualization of the centrosome.
137
Normal cells have one centrosome comprised of two centrioles (Lodish et al., 2004).
The
centrosome is the primary microtubule-organizing center in G2-phase cells. During mitosis, the
two centrioles separate and migrate to opposite sides of the cell, separate the duplicated
chromosomes, and establish the bipolarity of a dividing cell (Lodish et al., 2004). The addition
of inhibitors cdk2iii, cdkliv, and cdk4 does not affect the ploidy of our y-CHO cell line and,
therefore, these cells all have two centrioles as can be seen in Figure 6-12A, B, C, and D.
However, following cdk2iv treatment, Figure 6-12 E, we observe a significant increase in the
number of centrioles present in our cells, which is a characteristic of polyploidy. In addition, we
see a noticeable increase in both the cell size as well as the DNA content (stained blue) in our
cells. Taken together, these observations verify that we are inhibiting mitosis and inducing
tetraploidy in our cell line through the addition of inhibitor cdk2iv.
138
A
8-
50
0
0
50
0n
15
Channals(FL2-A)
100
290
25
150
Channels
(FL2-A)
C
0
50
150
100
Channels(FL2-A)
200
250
Figure 6-11. Cell cycle distributions following the addition of the inhibitor cdk2iv.
Cell cycle distributions are shown (A) Oh, (13) 8h, and (C) 24h after the addition of the cdk2iv
inhibitor. The graphs are histograms of DNA content (FL2-A). 2N cells in Go/Gi have an FL2A of 50, 4N cells in G2/M have an FL2-A of 100, and 8N cells have an FL2-A of 200.
139
Figure 6-12. 60X images of stained y-CHO cells 24 hours post-inhibitor treatment.
CHO cells were treated for 24 hours with (A) DMSO control, (B) 5 iM cdk2iii, (C) 10 gM
cdkliv, (D) 5 [LM cdk4, and (E) 5 pM cdk2iv. Cells were fixed prior to immunostaining. FActin was stained with AlexaFluor 594 phalloidin and detected with a Texas Red (red) filter.
DNA was stained with Hoechst 33258 and detected with a DAPI (blue) filter. y-tubulin was
detected with a primary antibody followed by an AlexaFluor 488 secondary antibody and
detected with a fluorescein (green) filter. All images were taken with a DeltaVision Core
deconvolution microscope.
140
We wanted to further determine the effect that inhibitor cdk2iv has on growth and specific
productivity. Figure 6-13 shows growth curves following the addition of 2.5 gM of inhibitor
cdk2iv, and following the addition and subsequent removal of the same inhibitor 24 hours later.
Time points were taken every 12 hours for 48 hours total. The viability remained above 90%
throughout the experiment. As can be seen in the graph, the cells undergo a strong growth arrest
following addition of the inhibitor cdk2iv, which we also observed in Figure 6-2. By adding the
inhibitor cdk2iv and subsequently removing it through a medium replacement 24 hours later, the
cells are able to start growing again.
Figure 6-14 plots the total cumulative IFN-y production against the IVCD. As can be seen, the
addition of the inhibitor cdk2iv drastically increases specific productivity. This observation is
somewhat expected, partly because we observe large increases in cell size following inhibitor
addition. Intuitively, larger cells are likely to produce more IFN-y on a per cell basis. It is also
interesting to note, that after removing the inhibitor cdk2iv at 24 hours, the specific productivity
still remains quite high.
We hypothesized that the increase in specific productivity may also be caused by an increase in
intracellular genomic DNA content. At each 12-hour time point we purified the genomic DNA
from 500,000 cells and measured the DNA content with Picogreen dye. In Figure 6-15 we show
that exposure to the cdk2iv inhibitor doubles the genomic DNA content in a cell within 12 hours
of addition when compared with a regularly growing cell. Following the removal of the inhibitor
after 24 hours (light gray bars), the amount of genomic DNA in the cells levels out at
approximately double the genomic DNA content of a regularly growing cell. Interestingly, the
141
increase in specific productivity, with and without the removal of the inhibitor, trends with DNA
content. The specific productivity increases 2.39 (± 0.5)-fold (± S.E., n=2) without the removal
of the inhibitor and 2.17 (± 0.2)-fold with the removal of the inhibitor while the DNA content
increases 2.8-fold (n=1) without the removal of the inhibitor and 2.3-fold with the removal of the
inhibitor.
The genomic and phenotypic instability of CHO cells have been shown to be proportional to
their degree of aneuploidy (Duesberg et al., 1998). For this reason, the addition and subsequent
removal of the inhibitor cdk2iv may represent an interesting strategy to balance the advantages
of tetraploid cells, increased specific productivity, with the disadvantages, genetic instability and
eventual cell death. Such a strategy may increase total IFN-y production in an extended cell
culture.
142
*'Growth Control
Acdk2jv
Ocdk2iv w/ Arnedia
5
4w
0
40
20
60
80
Time (hours)
4C'
Figure 6-13. Cell growth curves following the addition and subsequent removal of
inhibitor cdk2iv.
Total viable cell density is shown over time following the addition of the inhibitor cdk2iv to
growing cells. The cdk2iv inhibitor was either (0) not added, (n) added at 5 gM, or (x) added at
5 piM and removed 24 hours later. (Error bars: S.E., n=1)
143
cdk2iv w/ Lrmedia
(0.08)
6
4
(0.08)
Growth Control
(0.04)
2
dGrowth Control
1Ocdk2iv
6cdk2iv w/ Amedia
0
20
40
60
80
100
120
140
IVCD (106 cells h)
Figure 6-14. Cumulative IFN-y production plotted against Integrated Viable Cell Density
(IVCD) following the addition of inhibitor cdk2iv.
The slope of a best-fit line through the plotted data is defined as the specific productivity, qp.
The cdk2iv inhibitor was either (0) not added, (o) added at 5 RM, or (A) added at 5 [LM and
removed 24 hours later. Specific productivity for each data set is shown in parentheses in units
of pg cell-1 h-1. (Error bars: S.E., n=1)
144
4 -
Ocdk2iv
0 cdk2iv w!Amedia
3.5
3
2.5
2-
1.5-
0.5
-
0
-
24
Time (hours)
36
Figure 6-15. Relative genomic DNA content following inhibitor cdk2iv addition.
Genomic DNA content is measured with PicoGreen dye and shown relative to the growth
control, either without (black) or with (gray) the removal of the inhibitor at 23 hours.
145
6.6
Conclusions
We were successfully able to use a variety of CDK inhibitors to explore the relationship between
cell cycle, growth, and productivity. Although qualitatively it appears that the G2/M phase of the
cell cycle positively impacts specific productivity, we have shown that cell cycle only has a very
modest effect. To our knowledge we are the first to report even a mild relationship between the
G2/M-phase of the cell cycle and specific productivity.
It is possible, however, that this
relationship is merely coincidental. Both of the CDK inhibitors that have the largest impact on
cell growth, cdkliv and cdk2iii, at least partially target CDK1 and increase the number of cells in
G2/M-phase. This is analogous to inferring a qualitative relationship between the Gi-phase of
the cell cycle and specific productivity in past studies involving low temperature (Hendrick et al.,
2001; Kaufmann et al., 1999; Yoon et al., 2003), butyrate (Hendrick et al., 2001), and CKI
overexpression (Bi et al., 2004; Carvalhal et al., 2003a; Fussenegger et al., 1997). Instead it is
likely that growth arrest alone contributed to those specific productivity increases.
We are not the first group to suggest that cell cycle may not play an important role in increasing
specific productivity in both growing and arrested cultures. A number of previous researchers
have suggested that other factors like size (Lloyd et al., 2000), medium composition (Lloyd et
al., 1999), and mRNA transcript level (Fox et al., 2005b; Yoon et al., 2003) can have a much
more important effect on productivity than cell cycle phase.
In our y-CHO cell line, IFN-y expression is driven by the SV40 promoter. Although the SV40
promoter is known to be S-phase specific (Banik et al., 1996), we did not observe any
relationship between the proportion of cells in S-phase and productivity as has often been
146
predicted. This may be due, in part, to the fact that our cells continued to cycle in the presence
of the CDK inhibitors.
We were able to show that the specific growth rate inversely correlates with specific
productivity, or in other words, as cell growth decreases specific productivity increases. This
inverse relationship has been observed previously in hybridoma cultures (Suzuki and Ollis,
1990). Perhaps our most interesting observation is that irrespective of which inhibitor we added
to the culture, whenever growth slowed we observed an increase in productivity.
This
contradicts a previous study where various nucleosides and nucleotides were added to cell
cultures (Carvalhal et al., 2003b). In this study, growth arrest led to an increase in specific
productivity with the exception of the addition of ATP, NAD, NADH, NADP and NADPH.
Because the precise mechanisms by which these molecules induce growth arrest is unknown, it is
possible that they are drastically changing intracellular metabolism resulting in decreased
productivity.
During our inhibitor characterization, we found an interesting CDK2 inhibitor that induces
tetraploidy in our CHO cells. This inhibitor cdk2iv drastically increases the size of our y-CHO
cells, intracellular genomic DNA content, and specific productivity. We hypothesize that by
adding the inhibitor cdk2iv and subsequently removing it after 24 hours we may be able to
drastically increase total production of IFN-y in an extended culture.
147
148
7
INCREASING TOTAL PRODUCTIVITY THROUGH CDK
INHIBITION
7.1
Introduction
In Chapter 6, we hypothesized that we may be able to use our chemical CDK inhibitors to
increase total IFN-y production in an extended culture. In this chapter, we aim to increase total
recombinant protein production by adding these CDK inhibitors to suspension y-CHO cells in
batch, modified batch, and fed-batch cultures. Adding small molecules to cultures in order to
improve volumetric productivity is not uncommon.
The addition of butyrate (Kim and Lee,
2001; Sung et al., 2007), AMP (Carvalhal et al., 2003b), and hexanohydroxamic acid (HHA)
(Allen et al., 2008) has been shown to increase total productivity in various culture systems. The
effects of AMP and HHA on recombinant protein production were determined following the
screening of dozens of compounds in the case of AMP, and hundreds of compounds in the case
of HHA. To our knowledge, our study represents the first rational addition of small molecules to
cell cultures, since the addition of butyrate, with the goal of inducing growth arrest and
improving total recombinant protein production.
7.2
Addition of CDK Inhibitors in Batch Cultures
We used the effective inhibitor concentrations from our short-term studies (Chapter 6) as a
starting point for longer-term shake flask experiments. Shake flasks were inoculated at 2x10 5
cells mL- and allowed to grow for two days before inhibitors were added. After 48 hours and
once the viable cell density exceeded 1x10
6
cells mL,
the CDK inhibitors were added to the
cultures at the following concentrations: 2.5 gM cdk2iii, 1 gM cdk2iv, 10 pM cdkliv, and 2.5
pM cdk4. The inhibitors cdk2iii and cdk4 drastically decrease the viability of the suspension
149
CHO cells (data not shown). This effect is not entirely surprising, as these two inhibitors were
the most toxic in the short-term studies.
Elevated concentrations of cdk4 resulted in rapid
decreases in viability in out 36-hour experiments and extended exposure to cdk2iii resulted in the
shedding of the viable cells from 6 well plates. For these reasons we immediately stopped using
these inhibitors in extended cultures. The effect of inhibitors cdkliv and cdk2iv on growth is
shown in Figure 7-1.
Both inhibitors slow cell growth following their addition at 48 hours
without substantially affecting viability, and the results reinforce our observations from the
short-term experiments. The addition of inhibitor cdkliv results in a slight decrease in growth
rate while the addition of cdk2iv results in a strong growth arrest following inhibitor addition.
The addition of the inhibitors cdkliv and cdk2iv does not result in a statistically significant
increase in total volumetric IFN-y production, as can be seen in Figure 7-2. Rather, there is no
change in total IFN-y production following inhibitor addition, even though the IVCD decreased
in both cases. In other words, the addition of inhibitors cdkliv and cdk2iv increased the specific
IFN-y productivity from 0.7 pg IFN-y cell-' day~', by 1.5-fold (1.09 pg IFN-y cell-' day-) and
1.8-fold (1.24 pg IFN-y cell-' day-) respectively (Figure 7-3). As we know, increasing total
production in growth-arrested cells involves a trade-off between increasing specific productivity
and decreasing IVCD. Although we have not fully optimized the concentration of inhibitors or
the timing of addition, we do not expect to achieve drastic increases in total productivity in this
batch system. One reason, in particular, is that the nutrient depletion that occurs by the time
inhibitors are added prevents an extended culture, which is necessary to increase total production
in a growth-arrested culture. Secondly, inhibitor toxicity can limit culture time.
150
A
-6 Growth
-9- cdk2iv
3
-- -cdkliv
2
E2.5
105
1
00
0.5
0
24
48
72
96
120
144
168
192
Time (hours)
I0
90
- 6- Growth
80
D-cdk2iv
B
0-cdkliv
70
Q
60
50
40
30
20
10
0
0
24
48
72
96
120
144
168
192
Time (hours)
Suspension y-CHO growth and viability curves in the presence of CDK
Figure 7-1.
inhibitors.
Both (A) viable cell density and (B) viability curves are shown following the addition of (A)
DMSO, (0) 1 jiM cdk2iv, and (0) 10 gM cdkliv at 48 hours. (Error bars: SsE., n=2)
151
IU
-A-Growth
-B- cdk2iv
-0 cdkliv
8
7
6
5
4
3
2
0
24
48
72
96
120
144
168
192
216
Time (hours)
Figure 7-2. Cumulative IFN-y titer following the addition of CDK inhibitors.
Data is plotted following the addition of (A) DMSO, (0) 1 gM cdk2iv, and (0) 10 jiM cdklv.
(Error bars: S.E., n=2)
7
6
S4
z
2
A Growth
Ncdk2iv
0 cdkliv
0
-----
0
50
150
100
200
250
IVCD (101 cells mL hr)
Figure 7-3. Cumulative IFN-y titer plotted against Integrated Viable Cell Density for each
inhibitor.
Data is plotted following the addition of (A) DMSO, (E) 1 piM cdk2iv, and (0) 10 RM cdklv.
The slope of a best-fit line through the plotted data is defined as the specific productivity, qp.
(n=2)
152
7.3
Addition of Inhibitor cdk2iv in a Modified Batch Culture
Looking back to Section 6.5, the addition and subsequent removal of cdk2iv resulted in an
increase in JVCD with only a marginal change specific productivity, Figures 6-13 and 6-14. We
hypothesized that we may be able to increase total volumetric IFN-y productivity by applying a
similar methodology in shake flask cultures. After inoculating 125-mL shake flask at 2 x 105
cells mL- 1 in 25 mL, we allowed the cultures to grow for 48 hours, reaching a cell density of at
least 1 x 106 cells mL'. We then added the inhibitor cdk2iv to a concentration of 1 gM, and
subsequently removed the inhibitor 24 hours later by performing a full medium change. The
same process was performed in a control culture where DMSO was added in place of the
inhibitor. Figure 7-4 shows the affect of inhibitor cdk2iv addition and its subsequent removal on
growth in this modified batch culture. Comparing the growth curve to that in Figure 7-1, the
maximum viable cell density in the control culture was significantly higher. This is the result of
the complete medium change that occurred at 72 hours. As in the batch culture, the addition of
cdk2iv does not have any significantly detrimental effects on viability. While viability does
begin to drop slightly faster at 144 hours, ultimately the culture is extended by approximately 1
day. In addition, the culture length is the same in both batch and modified batch cultures.
Interestingly, unlike in the 6-well plate cultures, the removal of the inhibitor cdk2iv through
medium replacement did not induce growth in the shake flask cultures.
The 6-well plate
experiments were performed in the presence of serum, which is the likely cause of growth
following medium replacement.
Although the culture time is not extended when comparing
batch and modified batch cultures, the medium change did act to maintain a higher viable cell
density in the cdk2iv cultures through 144 hours.
153
A
-- Growth Control
-8- cdk2iv
5
4
3
2
0
24
48
72
96
120
144
168
192
216
Time (hours)
100
90
-*-Growth Control
& cdk2Iv
B1
80
70
50
40
30
20
10
24
48
72
120
96
Time (hours)
144
168
192
216
Figure 7-4. Suspension CHO-IFNy growth and viability curves in the presence of CDK
inhibitors in a modified batch culture.
Both (A) viable cell density and (B) viability curves are shown following the addition of (A)
DMSO and (E) 1 uM cdk2iv at 48 hours. Full medium change was performed at 72 hours
(Error bars: S.E., n=4)
154
The effect of inhibitor treatment and its subsequent removal on the total volumetric productivity
of IFN-y is significant, as shown in Figure 7-5. The addition of the inhibitor cdk2iv results in
1.73-fold or 73% increase in total recombinant protein titer. This translates into an over 4-fold
increase in specific productivity, from 0.8 to 3.3 pg IFN-y cell-1 day' as shown in Figure 7-6.
Moreover, the final IFN-y titer in the modified batch culture is even higher than that achieved in
a normal batch culture (Figure 7-2).
We also sought to ensure that the cells were metabolically active following the addition of the
inhibitor cdk2iv. We did this by measuring the total intracellular protein content following the'
addition of the cdk2iv inhibitor. Every 12 hours following inhibitor addition, 2.5 x 10 5 cells
were lysed and the total protein was measured with a BCA assay for both the growth control
culture and the inhibitor culture, and the results are shown in Figure 7-7. Following the inhibitor
addition at 48 hours, and subsequent medium change at 72 hours, intracellular protein content
continues to increase in the inhibitor culture while remaining constant in the growth control as
expected. In the growth control, cell division maintains an approximately constant intracellular
protein content of 3.2 ng cell-'. In the cdk2iv inhibitor culture, the inhibition of cell division
causes a continued increase in intracellular protein content, reaching a maximum of 11.9 ng cell'
at 108 hours.
The cell cultures are still metabolically active following inhibitor addition,
allowing for the continued replication of DNA (Figure 6-15) and creation of intracellular
protein.
155
14
-6- Grx wth Control
-B- ed k21v
12
10
8
LA.
4
2
0
0
24
72
48
96
120
Time (hours)
144
168
192
Figure 7-5. Cumulative IFN-y titer following the addition and removal of a CDK inhibitor
in a modified batch culture.
Data is plotted following the addition of (A) DMSO and (E) 1 gM cdk2iv at 48 hours and the
full medium change that was performed at 72 hours (Error bars: S.E., n=4) (*: p < 0.05)
AGrowth Control
12
Ocdk2ov
0 cdk2lv
10
(0.14)
/
Growth Control
(0.03)
2
0~
0
50
100
150
200
250
300
Integrated Viable Cell Density (105 cells mL-1 hr)
Figure 7-6. Cumulative IFN-y titer plotted against Integrated Viable Cell Density
following the addition and removal of a CDK inhibitor in a modified batch culture.
Data is plotted following the addition of (A) DMSO and (E) 1 pM cdk2iv at 48 hours and the
full medium change that was performed at 72 hours. The slope of a best-fit line through the
plotted data is defined ao the specific productivity, qp, and is in parentheses (pg cell-1 hr1) (n=4)
156
14
1 3Growth Control
4*cdk2iv
S12
12
o 10
C
C
IWO
8
A media
0
4
0
2
48
60
72
84
96
108
120
Time (hours)
Figure 7-7. Total protein content following the addition of inhibitor cdk2iv.
Total protein content per cell is shown following the addition of either DMSO (white) or 1 pLM
cdk2iv (black) at 48 hours. Full medium change was performed at 72 hours (modified batch).
(n=1)
157
7.4
Addition of Inhibitor cdk2iv in a Modified Fed-Batch Culture
We next sought to determine if the addition of inhibitor cdk2iv could improve total productivity
in a fed-batch culture. Fed-batch cultures were started in the same way as the batch cultures.
Shake flasks were inoculated 2 x 105 cells mL- 1 and allowed to grow for 48 hours, reaching a cell
density of at least 1 x 106 cells mL~1. We then added the inhibitor cdk2iv to a concentration of 1
pM, and subsequently removed the inhibitor 24 hours later through a full medium change. We
then followed the fed-batch strategy described by Lim et al. (2006) and outlined in Section 3.1.5,
by feeding glucose and glutamine to set points of 0.5 and 0.15 g L-1 every 8 to 12 hours
Growth and viability curves for the fed-batch cultures are shown in Figure 7-8. These growth
curves compare well with those achieved by Lim et al. (2006). Interestingly, the addition of the
inhibitor cdk2iv had a detrimental affect on viability starting at 168 hours in the fed-batch culture
when compared with the growth control. This observation was not made in the batch culture.
Figure 7-9 shows an overlay of the growth curves for both the batch and fed-batch cultures. The
fed-batch culture growth control reaches a slightly higher maximum cell density, 5.87x1 06 cells
ml compared with 4.94x106 cells mL-1. Because we perform a medium change in the batch
culture at 72 hours, we already achieve a higher than normal maximum cell density in those
experiments, and this is the reason that we do not observe a larger increase in maximum cell
density in the fed-batch cultures.
The increase in maximum cell density, along with the
extension of the culture by a day, increases the IVCD by 39% in the growth control before
viability declines. We do not expect there to be as large of an increase in IVCD in the inhibitor
cultures, because the maximum cell density does not increase. The extension of the culture by a
day increases in IVCD by 11% following inhibitor addition in the fed-batch culture.
158
-a- Growth
A
-02 cdk2iv
6
6
E
5
0
0
24
48
72
96
120
144
168
192
216
240
Time (hours)
100
90
Growth
80
-9-cdk2"B
70
i60
K
150
>
40
30
20
10
0
0
24
48
72
96
120
144
168
192
216
240
Time (hours)
Figure 7-8. Suspension CHO-IFNy growth and viability curves in the presence of inhibitor
cdk2iv in a modified fed-batch culture.
Both (A) viable cell density and (B) viability curves are shown following the addition of (A)
DMSO and (LI) 1 pM cdk2iv at 48 hours. Full medium change was performed at 72 hours
followed by fed-batch feeding at 8-hour intervals.
159
-
6 '
Growth - Batch
&-cdk2iv - Batch
- Fed-batch
+Growtlh
-U- cdk2iv - Fed-batch
0
24
48
72
96
120
144
168
192
216
240
Time (hours)
Figure 7-9. Overlay of modified batch and fed-batch CHO-IFNy suspension growth curves
following the addition of inhibitor cdk2iv.
Data from batch (open symbols) and fed-batch (closed symbols) cultures are shown for easy
comparison. Inhibitor cdk2iv or DMSO was added at 48 hours followed by a full medium
change at 72 hours. Fed-batch feedings occurred at 8-hour intervals. (Error bars: S.E., n=4)
160
The addition of the inhibitor cdk2iv does not increase the total production of IFN-y in this fedbatch culture, as shown in Figure 7-10. In fact, total IFN-y production decreases by 43% (or
0.57-fold lower than the growth control).
Part of this decrease can be explained by the
comparatively larger increase in IVCD in the growth control. The extension of the cultures by a
day in the fed-batch cultures has a much larger impact on the growth control because the
maximum cell density is much higher than in the inhibitor cultures.
The decrease in total
productivity is also partly explained by a decrease in specific productivity in the fed-batch
inhibitor cultures. While the specific productivity increases in the fed-batch culture following
inhibitor cdk2iv addition, Figure 7-11, it actually decreases when compared with the batch
culture, Figure 7-12. Typically, specific productivity should not change from a batch to a fedbatch culture (Xie et al., 1997), as can be seen in Figure 7-12. This 2-fold decrease in specific
productivity following inhibitor addition severely limits the amount of total IFN-y that can be
produced in the culture. We hypothesize that this decrease is the result of the feed medium
having been optimized for growing CHO cells, and not for maintaining cells in a growth arrested
state. By using an optimized medium, that at least maintains specific productivity following
inhibitor addition, inhibitor cdk2iv has the potential to increase total productivity in a fed-batch
culture
161
--
Growth
8- cdk2iv
14
12
10
_j
S6;
4'
0
0
24
48
96
72
120
144
168
192
216
240
Time (hours)
Figure 7-10. Cumulative IFN-y titer following the addition and removal of inhibitor ck2iv
in a modified fed-batch culture.
Data is plotted following the addition of (A) DMSO and (0) 1 gM cdk2iv at 48 hours and the
full medium change that was performed at 72 hours followed by fed-batch feedings at 8-hour
intervals.
A Growth
*cdk2iv
14
12
10
8
6
4
2
0
100
200
300
400
500
600
VCD (106 cells mL I hr)
Figure 7-11. Cumulative IFN-y titer plotted against Integrated Viable Cell Density
following the addition and removal of inhibitor cdk2iv in a modified fed-batch culture.
Data is plotted following the addition of (A) DMSO and (U) 1 pM cdk2iv at 48 hours and the
full medium change that was performed at 72 hours. The slope of a best-fit line through the
plotted data is defined as the specific productivity, qp.
162
AGrowth - Batch
14
Ocdk2iv - Batch
AGrowth - Fed-batch
12
Ucdk2iv - Fed-batch
10
100
200
300
400
500
600
IVCD (106 cells mL-1 hr)
Figure 7-12. Overlay of cumulative IFN-y titer plotted against IVCD for modified batch
and fed-batch cultures following the addition of inhibitor cdk2iv.
Data from batch (open symbols) and fed-batch (closed symbols) cultures are shown for easy
comparison. Inhibitor cdk2iv or DMSO was added at 48 hours followed by a full medium
change at 72 hours. Fed-batch feedings occurred at 8-hour intervals. The slope of a best-fit line
through the plotted data is defined as the specific productivity, qp.
163
7.5
Conclusions
In this chapter, we have shown the potential of using a CDK2 inhibitor to improve total
volumetric IFN-y productivity. In addition to improving the specific productivity of IFN-Y by
over 4-fold, we were also able to increase total productivity in a modified batch culture by 73%.
The addition of nocodazole, an anti-mitotic microtubule disrupting agent, causes growth arrest in
the G2/M-phase of the cell cycle and is often characterized by an increase in both cell size and
DNA content. Tait et al. (2004) used nocodazole to enhance the transient production of both
SEAP and an IgG 4 monoclonal antibody. Nocodazole addition was shown to increase both the
transfection efficiency and the specific production rate of transfected cells. However, when
nocodazole was added to GS-CHO cells stably transfected with IgG 4 , no significant increase in
total productivity was observed, although specific productivity was increased. We attribute this
apparent discrepancy with our results to a number of causes. Most importantly, the effect of our
modified batch culture on productivity cannot be overstated.
When we added our cdk2iv
inhibitor to cultures in a batch format, we also observed no increase in total productivity. Only
by performing a single medium replacement at 72 hours were we able to drive total productivity
higher in our inhibitor cultures. We hypothesize that the nutrient depletion that occurs in batch
cultures over the first 48 hours prevents the drastic increase in productivity following inhibitor
addition from being observed.
In addition, while growth arrest following the addition of
inhibitor cdk2iv exhibits a number of the same traits as a nocodazole induced arrest, notably an
increase in cell size and DNA content, the mechanism of arrest is different. Nocodazole induces
arrest by disrupting microtubules, while cdk2iv specifically inhibits CDK2 (Pennati et al., 2005).
164
The addition of inhibitor cdk2iv in a modified fed-batch culture does not lead to an increase in
total IFN-y production. This observed decrease in total production following inhibitor addition
was caused by both a decrease in IVCD and specific productivity. While a decrease in IVCD in
the fed-batch inhibitor culture was expected, we did not expect to observe a decrease in specific
productivity.
We hypothesize that our feed medium is not properly optimized for use in a
growth arrested culture. By improving the feed medium and maintaining specific productivity,
we believe that we can increase total IFN-y productivity though the addition of inhibitor cdk2iv
in fed-batch cultures.
While we are not the first group to utilize a G2 /M-like arrest to increase total productivity (Tait et
al., 2004) in a cell culture system, we are the first to increase recombinant protein titer from a
stable recombinant protein expressing cell line. The ability to increase total recombinant protein
production through the addition of a small molecule to the culture medium has many advantages.
Such an addition could potentially be used in current batch and fed-batch processes without
many modifications. In addition, like other general methods to improve protein production such
as hypothermic culture and the addition of butyrate, cell engineering and cell line development is
not required, decreasing the time to implementation. Lastly, the addition of a small molecule
enhancer could be used in many types of cell culture systems, making it generally applicable.
165
166
8
CONCLUSIONS AND RECOMMENDATIONS
8.1
Thesis Conclusions
Past researchers have shown that growth arrested CHO cell cultures can lead to increases in both
the specific and total productivity of recombinant proteins. The majority of these studies utilize
general methodologies (i.e. hypothermic culture and butyrate addition) that induce growth arrest
through multiple cellular mechanisms.
The overexpression of CKIs represents the first
successful attempt to induce growth arrest and increase specific productivity through a single
cellular mechanism. However, total productivity was not improved. In this thesis, we have
sought to determine if growth arrest can be induced through the specific inhibition of the cell
cycle and what effect this inhibition has on specific and total productivity. In addition, the
relationship between growth-arrested cell cycle phase and productivity is very poorly understood
and no studies have sought to elucidate such a relationship. In this work, we have established
such a relationship between cell cycle phase, growth, and productivity.
We have shown that the specific inhibition of the CDK2-CcnE complex through chemical
inhibition leads to growth arrest and a subsequent increase in specific productivity. In addition,
through the use of chemical inhibitors we have been able to increase specific productivity
through the inhibition of CDK1 and CDK4. By inhibiting different CDKs, we were able to slow
cell cycle progression and alter cell cycle distribution. Through this work, we have shown that
increases in specific productivity are independent of cell cycle phase, and instead are strongly
correlated with a decreasing specific growth rate. This implies that the targeting of specific cell
cycle phases for growth arrest is largely unnecessary.
167
Instead, focus should be placed on
maintaining cells at an elevated cell density and in a growth arrested state for the longest period
of time, independent of cell cycle phase.
We have also shown that the knockdown of CcnE1 leads to increases in specific productivity.
However, we were unable to determine if these increases in specific productivity can be
translated into increases in total productivity because of limitations with our expression system.
It would be interesting to revisit this work when controllable shRNA expression systems have
improved, allowing the complete repression and the strong induction of shRNA expression.
Lastly, we have shown that the addition of CDK inhibitors directly to suspension cultures may be
a promising strategy to increase recombinant protein productivity. Unfortunately, commercially
available CDK inhibitors are quite toxic and prevent extended culturing in their presence. The
inhibitor cdk2iv has shown particular promise towards increasing total productivity.
When
added to suspension cultures, inhibitor cdk2iv induces growth arrest, increases both cell size and
DNA content, and drastically increases specific productivity.
Through its addition and
subsequent removal, we are able to increase total IFN-y production by 73% when compared with
a control culture. We believe that with the development of an optimized supplemental feed
medium for growth arrested cells, this methodology could also be applied to fed-batch cultures.
In summary, we have shown that chemical CDK inhibitors not only represent an interesting tool
to explore the effects of cell cycle phase and growth rate on productivity, but can also be used to
improve total productivity in commercially relevant cell cultures.
168
8.2
Recommendations for Future Work
8.2.1
Inducible shRNA Expression Systems
One of the major limitations in our anti-CcnEl shRNA expression work was the expression
system itself. The potential for the success of an inducible shRNA expression system can be
determined based on two general criteria: (1) the ability of the system to drive high levels of
shRNA expression, and (2) the ability to finely control shRNA expression.
A number of researchers have used shRNA to silence gene expression in CHO cell lines (Kim
and Lee, 2007; Lim et al., 2006; Mori et al., 2004; Ngantung et al., 2006; Sung et al., 2007;
Wong et al., 2006b).
In all of these studies, shRNA expression was constitutive and the
researchers only had to screen for the knockdown of their target.
Even so, hundreds and
sometimes thousands of clones had to be screened in order to find a handful that had high levels
of shRNA expression. Alternatively, high levels of shRNA expression can be driven by either
the directed insertion of the expression system into highly active regions of the CHO
chromosome, or the engineering of stronger promoters. Any improvements in either insertion
location or expression level should make the screening for high expressing clones faster and
more likely to yield a desired phenotype.
We are not aware of any researchers who have successfully expressed a stable and inducible
shRNA expression system targeting an endogenous gene in CHO cells.
We believe this is
because commercially available systems to do not adequately control shRNA expression, neither
fully repressing nor fully inducing expression when necessary. The most common system to
control shRNA expression is the tetracycline responsive system used in this study, and we have
169
shown that this system does not fully repress shRNA expression nor induce shRNA expression to
adequate levels. Improvements in controllable systems still need to be made before a study like
ours should be carried out again.
8.2.2
Overexpression of miRNA
MicroRNAs (miRNAs) are a class of non-coding and naturally expressed RNAs that are
structurally and mechanistically similar to siRNA (Bartel, 2004). Most importantly, a single
miRNA can post-transcriptionally regulate the gene expression of up to 100 targets (Lim et al.,
2005).
miRNAs are known to be critical in the regulation of cell proliferation and death
(Brennecke et al., 2003; Liu et al., 2008), and apoptosis (Xu et al., 2003), all of which are, for
reasons covered extensively in this thesis, important to the production of recombinant proteins in
CHO cells. It has been suggested that the overexpression of miRNAs may serve as a useful tool
for improving the production of recombinant proteins (Muller et al., 2008). Like hypothermic
culture and butyrate addition, miRNA expression has the potential to regulate the expression of
multiple genes at one time, potentially increasing the chance of success when compared to an
single shRNA expression strategy. In addition, another advantage of miRNA expression is that it
does not overcharge the transcriptional machinery of the host cell.
As
of the
writing
of this
thesis,
only
one
CHO-derived
miRNA,
cgr-miR-21
(http://microrna.sanger.ac.uk/), can be found in the miRNA registry. Both miR-21 and miR-24
have been shown to modulate growth, and are up regulated in stationary phase cultures induced
by either temperature shift or during normal batch culture (Gammell et al., 2007).
The
overexpression of either of these miRNAs during exponential growth phase may lead to an
170
induced growth arrest and a subsequent improvement in productivity. In addition miR-16 and
let-7b have been shown to down regulate CcnE] and CDK6 expression respectively in the
production cell line, HEK-293 (Koh et al., 2009), and the expression of miR-16 alone is known
to induce cell cycle arrest (Liu et al., 2008). The overexpression of either of these miRNAs may
have the potential to induce growth arrest and increase recombinant protein productivity in other
cell lines.
8.2.3
Screening for Less Toxic Inhibitors
The chemical inhibitors used in this study were originally created as potential cancer treatments.
For this reason, they have toxicity profiles that may make them well suited as chemotherapy, but
not well suited for use in extended cultures. All of the inhibitors are known to induce apoptosis
in cells following exposure at elevated concentrations. Although it is not known whether the
induction of apoptosis is the result of inhibitor toxicity or the result of CDK inhibition, it would
be useful to screen for compounds that selectively inhibit CDKs without inducing apoptosis.
The screening of small molecules for enhancements in recombinant protein production is not
uncommon (Allen et al., 2008; Carvalhal et al., 2003b), and may represent an easy way to find
less toxic inhibitors.
8.2.4
Optimized Feed Medium for Growth Arrested Cell Culture
In order to achieve improvements in recombinant protein production through the addition of
inhibitor cdk2iv in fed-batch cultures, a supplemental feed medium optimized for a growth
arrested cell culture needs to be designed. During growth arrest, many changes occur to the cells
that ultimately yield drastic increases in the specific productivity of recombinant proteins.
171
Although not measured in this thesis, there are likely lots of metabolic changes following growth
arrest that likely result in different nutritional demands when compared with growing cells.
These changing nutritional demands are likely not met by the feed and supplemental media used
in this thesis because they have been designed for growing cells. Newly optimized feed and
supplemental media for growth-arrested cell cultures would go a long way towards improving
the potential of growth-arrested cultures.
8.2.5
Inhibitor Addition in Perfusion Culture
While we have shown that our inhibitors are potentially effective at increasing productivity in
both batch and fed-batch cultures, it would be useful to extend the application of these inhibitors
to other culture systems. Long-term perfusion cultures may present a particularly challenging
application because of the toxicity issues mentioned in Section 8.2.3. However, if less toxic
CDK inhibitors could be identified, it would be interesting to determine their effect in long-term
culture. Perfusion cultures offer a unique opportunity to employ an inhibitor removal strategy
similar to our modified batch culture experiments. G2/M arrest and the induction of tetraploidy
could be achieved by spiking inhibitor cdk2iv into the perfusion medium over a short period of
time. The following flow of fresh medium would remove the inhibitor from the cells, potentially
allowing for its application in extended perfusion cultures.
8.2.6
Conclusion
Growth arrest methodologies have the potential to drastically improve the production of
recombinant therapeutic proteins. By expanding on the genetic approaches introduced in this
thesis, developing new methods to induce growth arrest, and designing media and cell culture
172
processes that are optimized for growth arrested cultures, we can capitalize on the advantages
that growth arrested cultures offer.
173
174
NOMENCLATURE
IVCD
Integrated viable cell density (cell hr)
Nviable
Viable cell density (viable cell mL-1)
Nv, avg
Average viable cell density (viable cell mL~')
N, o
Initial viable cell density (viable cell mL')
P
Volumetric IFN-y production (gg mL')
qp
Specific IFN-y production rate (pg cell-' hr~')
qP,diff
Differential specific IFN-y production rate (jg cell~ hr- )
t
Time (hr)
Tanneal
Annealing temperature ("C)
Greek Letters
E
qPCR efficiency
Xem
Emission wavelength (nm)
Xex
Excitation wavelength (nm)
Specific growth rate (hr-d)
Abbreviations
AMP
Adenosine 5'-monophosphate
ATP
Adenosine triphosphate
cDNA
complementary DNA
C/EPBax
CCAAT/enhancer-binding protein x
175
CcnX
Cyclin X [where X is A1, A2, B1, B2, D1, D2, D3, E1, E2]
CDK
Cyclin dependent kinase
CHO
Chinese hamster ovary
CIRP
Cold-inducible RNA-binding protein
CKI
Cyclin dependent kinase inhibitor
CMV
Cytomegalovirus
Ct
quantitative PCR threshold cycle
DHFR
Dihydrofolate reductase
DMEM
Dulbecco's modified Eagle's medium
DMSO
Dimethyl sulfoxide
Dox
Doxycycline
DPBS
Dulbecco's phosphate buffered saline
DTT
Dithiothreitol
EDTA
Ethylene diamine tetraacetic acid
ELISA
Enzyme-linked Immunosorbent Assay
EPO
Erythropoietin
FACS
Fluorescence activated cell sorting
FAM
Fluorescein
FBS
Fetal Bovine Serum
FUT8
al,6 fucosyltransferase
y-CHO
Chinese hamster ovary cells expressing recombinant human interferon-gamma
Go
Quiescent cell state indistinguishable from G1
G1
First gap phase of the cell cycle
176
G2
Second gap phase of the cell cycle
G2 /M
Combined G2 and M phases of the cell cycle
GFP
Green fluorescent protein
HI
Polymerase III promoter that drives small RNA expression (rRNA, tRNA, etc.)
IC5 0
Half maximal inhibitory concentration
IFN-y
Interferon-gamma
IFS
Heat-inactivated fetal bovine serum
IRF- 1
Interferon regulatory factor 1
kDa
Kilo-dalton
Ki
Dissociation constant for inhibitor binding
LDH
Lactate dehydrogenase
M
Mitosis phase of the cell cycle
mRNA
Messenger RNA
NaBu
Sodium butyrate
Oligo(dT)
Oligodeoxythymidine
PBS
Phosphate buffered saline
PCR
Polymerase chain reaction
PhRMA
Pharmaceutical Researchers and Manufacturers of America
PI
Propidium iodide
pRb
Retinoblastoma protein
qRT-PCR
Quantitative reverse-transcription PCR (a.k.a. Real time PCR)
RNAi
RNA interference
rRNA
Ribosomal RNA
177
RT-PCR
Reverse-transcription PCR
S
DNA synthesis phase of the cell cycle
SDKid-I
Silencing KRAB domain of human Kox-1
SEAP
Secreted alkaline phosphatase
shRNA
Short hairpin RNA
siRNA
Silencing RNA
SV40
Simian virus 40
TE
Tris-EDTA
Tet
Tetracycline
tetO 7
7 repeats of the tetracycline operon
tetR
Tetracycline repressor
TIMP
Tissue inhibitor of metalloproteinases
t-PA
Tissue-type plasminogen activator
Tris
Tris(hydroxymethyl)aminomethane
tRAN
Transfer RNA
tTS
Tetracycline-controlled transcriptional suppressor
U6
Polymerase III promoter that drives small RNA expression (rRNA, tRNA, etc.)
VP16
Virion protein 16
XIAP
X-linked inhibitor of apoptosis
178
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APPENDIX
Cyclin Sequences
This section contains the cDNA sequences of six of the eight known cyclins that are expressed in
CHO cells. Sequencing was performed following the methodology outlined in Section 3.2.1.
Capital letters represent CHO base pairs, while lower case letters are taken from mus musculus
cDNA. Table 9-1 outlines our sequencing coverage.
Table Al. Sequencing summary of known CHO cyclins
Gene
Mouse ORF (bp)
CHO ORF (bp)
% complete
NOT TRANSCRIBED IN MATURE CHO CELLS
CcnA]
(ONLY SEX CELLS)
CcnA2
1266
1080
85.3
CcnB1
1290
1287
100
CcnB2
PRESENT - NOT SEQUENCED YET
CcnD1
885
591
66.8
CcnD2
867
867
100
CcnD3
PRESENT - NOT SEQUENCED YET
CcnE]
1473
1227
83.3
CcnE2
1215
1119
92.1
191
Cyclin A2 (CcnA2)
1
61
121
181
241
301
361
421
481
541
601
661
721
781
841
901
961
1021
1081
1141
1201
1261
atgccgggca
caggaagacc
caggcggtgc
CGACGGGTTG
TCATGGAAAG
ACTCAGAAAA
GCTGCTGTCT
GGTAGCTTTG
GTGAATGTTA
GAGGTTAAAT
ATGCGGGCCA
GAGACTCTGC
AGAGGAAAGC
ATATACCCCC
CAGGTTCTGA
ACAGTAAATC
GAAAGCTTAG
TATTTGCCAT
CAAAGCTGGC
TGTCTCATGG
AGGGAAAAGT
ctaagtgtgt
cctcgaggca
aagagaatgt
tgaaggccgg
CTCCTCTTAA
CAACCAGTAA
TGCCAGCTGA
CTTTACCTGG
AATCACCACA
ATGAAGTACC
GTAAACCTAA
TCCTTGTGGA
ATTTGGCTGT
TTCAACTTGT
CAGAAGTAGC
GAATGGAGCA
AGTTTCTTAA
CAATGTTTTT
CACTCATTGC
CTGAGTCATT
ACCTTCACCA
ACAAACATTC
ga
ttcgggtcgc
caaccccgaa
gaacgtgcgt
AGACCTTTCT
ACAGCCGGCC
ACATAAAGAA
AGCAAGAAAA
TGCTATGGAC
CGACTATCAT
AGTGGGTTAT
CTGGCTAGTT
GAACTACATT
GGGCACTGCT
AGAGTTTGTG
CCTAGTATTG
CCAGTACTTT
GGGAGAATTA
TGGAGCTGCC
GGTACAAAAG
GACCTACCTC
AAAATACCAT
cagccctgct
cagcccagca
cgcagcagaa
AACATGTCGC
ATGTGGATGA
AAGATGCCCT
CTCTTGATTA
TCTTAGAAGA
ACACATACCT
AGCCAGACAT
AAGAATATAA
TCTCTTCCAT
TAGCTTCAAA
ACGATACCTA
CTTTTGACTT
AGCCTGCAAA
ATGCTGACCC
CACTCTATAC
CCCTGGAAAG
AGCATGCTCA
TTCTCAACCC
ctcgctgca.t
gccgcgggcg
gctcaaTACT
CGTTGGTCCT
AGAAGAGGAG
GGCTTTTAAT
TCCAATGGAT
CGAAAAGCCA
TAGGGAAATG
CACTAACAGT
ATTACAGAAT
GTCTGTGTTA
ATTTGAAGAA
TTCCAAGAAG
AGCTGCGCCA
CTGCAAAGTT
ATACCTAAAG
AGTCACAGGA
TCTTAAACCT
ACAGTCAATA
ACCAGAgaca
CTTAACACAG AAAATAAGGC
ATTGCTGCAG CCTCCAAGCC
AAAGTCAGCG AACAGGCACA
ACTGGAAAAG TTTCAGCTAA
GAGCCAGAGG TGGAACTTGC
CTTTCTCCTG AACCTATCTT
TGTGCCCCTG CAGAAGAATA
GATGTGGATG CAGATGATGG
TATGCTTATC TCAGACAGCT
CGTGAAGTCA CTGGAAACAT
AAATTTAGGC TGCTGCAAGA
CAGGATAACT GTGTACCCAA
GCAAGCAAAT ATGAAGAAAT
AATACTTACA CTAAGCACCA
TTCAGTTTGG GTCGCCCTCT
GTTGACGTTG AACAGCATAC
GACATGGTGC ACTTTGCTCC
ATTCTTGACA ACGGTGAATG
TCCCTTCTGC CTGTCATGCA
ACAAAGCACA TGACTATCAA
CTGGCACAGC TGAATTGTAC
CTCAAGTGGA CCACTACACT
TAGTATACAG TGTTTACTTG
ATTTGAATGT TGGTTGTTCT
ATTTTTGAAA CTGCTTTTAG
TATGTTTATG TACTTCCTTC
AGCCCTCTGC CTAGCTCTTG
CAAGGTCAGC
CGGGCTGAGA
GGCAAGAGTG
AATCCCACCA
TGAGCCTGAA
GGTTGATAAT
CCTGTGTCAG
CGCTGATCCA
GGAGGAAGAA
GAGAGCCATC
GACTATGTAC
GAAGATGCTG
GTACCCTCCA
AATCAGACAG
GCCTCTGCAC
TTTGGCCAAA
TTCTCAGATT
GACACCGACC
GCACCTGGCT
GAACAAGTAT
ACTAGTTCAG
ACATCGGCAA
CTCTTCAATA
GACTCTAGGA
TTTAACAGAG
TT TAATGTGT
TTTAAACTGT
gatgcgggct
aaactggcgc
ggacccgcgc
ATAAACGATG
TTCACTATTC
ACACAGTGTG
CCACTGGTAC
ATGTCTATTG
GAAGATATTC
ATGAAGAAGC
GAAGTGGGAG
GATCGGTTCC
GCTATGCTGC
TATATTACAG
AAAGTCCTTG
CTGCACCAGC
AGTTTGATAG
TTTCATTTAG
ACTGGATATA
AGAGCAGCAC
GGTGTTTCTC
Cyclin B1 (CcnBi)
1
61
121
181
241
301
361
421
481
541
601
661
721
781
841
901
961
1021
1081
1141
1201
1261
1321
1381
1441
1501
1561
ATGGCTCTCA
ATGACAGGCG
CCGAGAACCG
CCTCTGAAAA
CCAAAACCTC
CCTGAACCTG
CCCTCTCCAA
GCTTTCTCTG
AACCTCTGTA
CAATCAGTTA
CTAATTGACT
ATGACTGTTT
CAGCTAGTTG
GAAATAGGTG
ATGGAAATGA
TTCCTCCGTA
TACCTCATGG
GCAGCTGGAG
CTGCAGCACT
AAGAATGTAG
GCAACATCCA
AATTTGTCCA
ATGCAATTGG
AAGGCTGTTT
TAACAAGGGT
AATCCAAGTA
CCTGGTCATA
GGGTCACTAG GAACACGAAA
CCAAGCGTGT GCCTGTGGCG
CTCTAGGGGA TATTGGTAAC
AGGAACTAAA AACCTCAGTT
AGGAGAAGGT TCCTGTGAGT
AACCTGTTAT GGAGGAAAAG
GCCCAATGGA AACATCTGGA
ATGTAATTCT TGCCGTGAGC
GTGAATATGT GAAAGACATA
GACCAAGATA TCTACTGGGC
GGCTGATACA GGTTCAAATG
CCATTATTGA CCGGTTCATG
GTGTGACTGC CATGTTTATT
ACTTCGCTTT TGTGACTAAT
AGATTCTAAG AGTTCTAAAC
GAGCCTCTAA GATTGGAGAG
AGCTCACTAT GTTGGACTAT
CTTTTTGCTT AGCACTGAAA
ACCTGTCCTA TACTGAAGAA
TCATGGTGAA CCGTGGCCTT
AGCATGCTAA GATCAGCACT
AGGCTGTGTC AAAGGCATAA
CACCATGTGC CACCTGTACA
TACTTTTCAT AGCTTACCTC
TGTCTAAAAC ATTTAGGATT
ATGTACGTAA TTGTAGCCTA
,TCTTTTAAGT CATCCTGCAA
192
1621
1681
1741
1801
1861
1921
CAATTTACCA
CTGTGTCTTG
TTGTTAATTG
TTAATCTCAA
ATTTTTTTCA
ACTGTATGTA
GCTTGTCCTT
AGCTATGGAC
GCTTGGGAAA
TGTCCTATAT
ACAATATTCC
ATGTATTCAG
AGTTCCCTTT
TTTCAGATCT
TAGCATGTTT
AAATGTAATC
TTTTAATGCC
TGATCCTTTA
TCTATTTCTT
GAACCCCAGT
AAAATTAAAG
ATGCATATGT
TATATTGCAT
CAATACATTC
CAGGTGGTTG
TTTCTTGTGT
GTATAAAAAG
TGTCAAGGAG
TTCCTAAGTG
AAATTGCATT
CTGTCCTTCA
AATTATTTAT
AATTTGCCCC
ATATGGACTC
TACATTTCAT
CTCTC
agcTCCTGTG
ACGACCGAGT
ACTTCAAGTG
TGCTGGAGGT
ACCTGGACCG
CCACCTGCAT
TGTGCATCTA
TGGTGAACAA
TCCTCTCCAA
CCTTTGTGGC
ctgctgggag
tctcctgcta
tccgtgcctg
agaacgtcga
cctgcacgcc
CTGCGAAGTG
GCTGCGAGCC
CGTGCAGAGG
CTGCGAGGAG
TTTCCTGTCT
GTTCGTGGCC
CACTGACAAC
ACTTAAGTGG
AATGCCAGAG
CCTCTGTGCC
cgtggtggct
ccgcacaacg
ccaggaacag
ccccaaggcc
caccgacgtg
GAGACCATCC
ATGCTCAAGA
GAGATTGTGC
CAGAAGTGCG
CTGGAGCCCC
TCCAAGATGA
TCTATCCGGC
AACCTGGCCG
GCGGATGAGA
ACAGACGTGA
gcgatgcaag
cactttcttt
attgaagccc
actgaggagg
cgagatgtgg
GCCGCGCGTA
CCGAGGAGAC
CGTCCATGCG
AAGAGGAGGT
TAAAAAAGAG
AGGAGACCAT
CCGAGGAGCT
CCATGACTCC
ACAAGCAGAT
AGTTCATTTC
gcctgaacct
ccagagtcat
ttctggagtc
agggggaagt
acatctga
CCCTGACACC
CTGCGCGCCC
GAAAATCGTG
CTTCCCTCTG
CCGCCTGCAG
TCCTTTGACC
GCTGCAAATG
CCACGATTTC
CATCCGCAAG
CAACCCACCC
gggcagcccc
caagtgtgac
aagcctgcgc
ggaggaagag
TGTGCTGCGA
GCGTCCTGCA
AGTGCGTGCA
AGGTCTGCGA
ACCGTTTTTT
GCATGTTCCT
TTTACACCGA
GAAAACTGAA
GCAAGCTGCC
TCGCTCTGTG
GAAGTGTGGG
GTGATGCACT
CCTGCCAGGA
AGCATAATGG
GGGATGTTGA
GGTGGACCCG
GAACCTGTTG
GAAGGACATT
GGAACAGAAG
GGCTGGAGTC
AGCCTCTAAG
CAACTCCGTG
GTGGAACCTG
CCAGCAGAAG
TGCTACAGAC
AGCAGCCATC
GACTGAGCTG
GCAGATTGAA
ATCCAAGTCT
CCTGTGA
GTCCGCAGGG
ACCATCGAGG
CAGCCATACA
TGTGAAGAGG
CCGACTCCTA
CTCAAAGAGA
AAGCCCCAGG
GCGGCAGTCA
GAGAAGCTAT
TTCAAGTTTG
TGTGGGCTTC
CTGGCCAAGA
GCTGTGCTGC
GTGGAAGATC
CTGTGCCGGA
AGCGCTACCT
TGCGCAGGAT
AAGTCTTTCC
AGACCCACCT
CCATCCCCCT
AGCTGCTGGA
CCCCTCACGA
CCCTGATTCG
CCATGTACCC
AGCAGGATGA
TCACCCACAC
TCAACAGCCT
TGGACCAAGC
CCGCAACCTG
CCCGCAGTGC
GGTGGCCACC
TTTGGCCATG
TCAGCTCCTG
GACGGCTGAG
GTGGGAGCTG
CTTCATTGAG
CAAGCATGCG
ACCATCGATG
AGAAGAGAAC
TGATGTGGAT
GCAGCAGTTC
CACCACCCCT
agagagactc
gctccagaaa
CCAGAGTTGA
CCTGTGTGGA
AGTACCCCAA
CAGTCTTGAA
gacggaccac
aaggaaggca
CAAGACTGTG
CCCATGCGCT
GACTGCGTTT
CTGGGGCAAT
agcaacatga
aaGGCGGCTG
AAAAGCCAGG
TTCATCCCCA
CAGCCTCGGA
AGAGAAGAGG
aagaagaagg
TTTTTCAACA
ATAGCAGTCA
CCCCTAATAA
AAATCAGGCC
TTTGGAGGAT
tggctccgac
TGCTCCAGAA
GCCTTGGGAT
AGAAGAGGAC
ACCCAGGGCC
CATGTTAAAC
Cyclin Dl (CcnDi)
1
61
121
181
241
301
361
421
481
541
601
661
721
781
841
atggaacacc
AACCTCCTGA
TCCGTGTCTT
GCCACCTGGA
GCCATGAACT
CTGCTAGGGG
GCCGAGAAGT
GAACTCCTTC
ATCGAACACT
CATGCGCAGA
TCCAtggtag
aacaacttcc
ccggactgcc
caggcccagc
gctggtctgg
Cyclin D2 (CcnD2)
1
61
121
181
241
301
361
421
481
541
601
661
721
781
841
ATGGAGCTGC
CTGGAAGACC
TCCTATTTCA
TGGATGCTAG
AATTATCTGG
GGCGCAGTGT
AAGCTGTGTA
GTGGTCCTGG
CATATCCTGC
CAGACCTTCA
ATCGCAACCG
ACACTCACGT
TGTCTCAAAG
CGTCAAGAGC
ACAGATGTGC
Cyclin E1 (CcnEl)
1
61
121
181
241
301
atgccaaggg
ctttcagtcc
GAAGTAATCG
GATAATTCAG
GATGAGCTTG
TCCCCACTTC
193
361
421
481
541
601
661
721
781
841
901
961
1021
1081
1141
1201
1261
1321
1381
1441
1501
AAGGAGAAGA
AGGATGCGAG
AGGGAGACAT
ATACTGAAAA
GAGGAAATCT
GGAGATGAAA
CCAATGACCA
AGCGAGGTGC
GATCTGTGTG
GCCTTGTATC
GACATAGAGA
AGCTCCAAGC
CACGCCAACA
CAGAACAGGA
CAGAACAGTG
CTGCCTGGAG
GGCGTATCTC
TGGAATGCTA
GAGTGCTCCA
CAAAAGCTTG
TTTACCTAAG
CAGTTCTTCT
TCTATCTGGC
CACTTTTACA
ACCCTCCAAA
TTCTCCAGAT
TTGTGTCCTG
TACTGCCTCA
TCCTGGATGT
ATTTCTCCTC
AATGTGTCAA
TCAAGCACTT
GCTTGGATTT
TCTCTCCTCC
AGGAGGAGAC
CTCCTTTGCT
TTCCAGAGCA
GTTGTTTTAA
GAAGCTGCTA
AAATTAAGGA
AGATGAGCAC
GGATTGGCTA
GCAAGACTTC
GCTCATTGGG
GTTGCACCAG
GGAATTAATG
GCTGAACGTG
GTACCCACAG
CGGCTGCTTA
CATGGAACTG
GTGGATGGTT
CCGGGGAGTT
GCTGGACAAA
TCCCAGTGGG
AGAATGAGCA
GCCTAGGAGG
GCGGGCGTCT
CAATAGGGTT
AGGAGGGTGC
GGCCACGGTT
TTTCTGCAAC
ATGGAGGTGT
TTTGATCGTT
ATTTCAGCTT
TTTGCTTACG
ATGATGAAGG
TATGTCCAAG
CAGGTCTTTG
GAATTTCCTT
ATGCAGAAGG
CCGTTCGCCA
CCCATGGAAA
GCCCAGGCAA
GTCCTGACAC
AACCTGCCAA
TTGGGAGCCC
TCAAAATGGC
GAGGACACCA
TACTTGACCC
GCTGCTGGCC
GCCATCCTCT
GCGAAGTCTA
ACATGGCATC
TATTTATTGC
TTACAGATGG
CCCTTAAGTG
TGGCTTATGT
TGCAGATTGC
ATGGTGTCCT
TTTCAGGGTA
TGGCCTTCCG
ACGCCCACAA
AGAAAGCCAT
CCCCACCCAG
AGACAGTGTT
CTGCTGATGC
CTCGGACAGA
GCCACCTCCA
ACTGGACTCT
TCTGCCCGGG
CCTGCAGGCA
TAAGCTTCAC
ACAACAAAAT
TTCTAAACTT
CGCTTGTTCC
GCGTTTAAGC
CAATGACACA
TGAGCTTTTA
TGCTGCTTCT
TCAGTGGTGC
GGAGGTGGGA
CATCCAGACC
ATTGTCAGAA
CAGTAAGAAG
GTGGAAGCAG
TCTGCGGAAA
AGTGCTTGTA
GAACGCCGCT
TCACACATGA
TGTTGTA
Cyclin E2 (CcnE2)
1
61
121
181
241
301
361
421
481
541
601
661
721
781
841
901
961
1021
1081
1141
1201
atgtcaagac gcagtagccg tttacaagct aagcaacatg cccagcccaa ccagccagac
tctcCGCAAG
AAAAGAAAAG
GTACTGTCTG
ACAAGTGACT
CCTCTGCCAG
GAGAGCAGAT
ATGAGGTCAA
GAGACATTTT
AATAAAAATA
GAAATCTACG
GTAGATATCT
GTAACAGTCA
AAGGTTCTTC
CTGTGTATCC
TTGTGCCATT
ATTTCAGAAT
GTGAAGCTGA
ACGAATTATT
CAGTTGTCAC
ccaggaaaac
AAGTCCAGAT
AGGAGATCAC
GAGGAATCAG
TCTCTAGATT
ATTTAAGCTG
ACGTGCATGA
TACTTTTAGA
ACCTTGCCCA
TGCTTCAACT
CTCCCAAACT
TAAAGATGGA
TTTCCTGGTT
TACCTCAATA
TCGCCATTGA
TTACCTCCAT
GTGTAGACTG
AGACTTTTAA
TGGCTTTGCT
CAGTGTGTAA
actga
AATTCAGGCC
CAAGAAGCAT
TCCTTGCATT
TACAAATTAC
GGGGTGTTCA
CAAACATTTT
CTGGCTTTTA
AGACTTTTTT
CATTGGGATT
CCAAGAGTTT
ACTCTCTATA
GAATCTTTTT
TTCTCAGGAG
CTCATTAGAA
TGAAGTAGTT
GATGGTGCCT
GAAGATACCC
GAATGAAGTA
TGGAGGCATT
194
AAGAAGAGAA
CAGTATGAGA
ATCATTGAAA
AGATTTAAAA
CAGGAGGTTT
GAAGTTCTGC
GAGGTTTGTG
GACAGATTTA
ACCTCATTGT
GCTTATGTCA
TTAAAGGCTT
CTCCAAGTTG
ACATTCATCC
TTCCAATACA
AAGAAAGCCT
TTTGTCAGTG
ATGGAAGACA
AACTACGTGA
ATGACACCAC
AAACAGCACA
TCAGGAATTG
CGCCCCATAA
ATCTTTTTAT
GGCTAAACAT
ATTCTGACCT
AAGTATACAC
TGTTGACACA
TCATTGCTTC
CTGATGGTGC
TAAAATGGGA
ATGCTGTTAA
AGATAGCTCA
GAATTCTGGC
CAGGTTTGGA
TAGTAAAAAG
GACATAATAT
ACACCTTCAG
CAAagagtac
GGATGTCAAA
TTGGCCACCT
AGAAATAGAA
TAATCCTTCA
GCTACAAAAG
GGAACCACAG
ACTTCATAGG
GAAAGATGTA
TAAACTTGAG
TTGCAGTGAA
ACTTTGTCCT
AGATGTTCCT
GCTTTTAGAT
AGCTGCTGCT
ATGGGATGAC
TGTAAGTCCA
CCAGACACAC
AAAAGGAGGG
tgaaaaacca