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Generation of Anti-CD133 Human Synthetic Antibodies as Tools for Exploring CD133 Function
by
Rashida Williams
A thesis submitted in conformity with the requirements for the degree of Master of Science Department of Molecular Genetics
University of Toronto
© Copyright by Rashida Williams 2013
ii
Generation of Anti-CD133 Human Synthetic Antibodies as Tools for
Exploring CD133 Function
Rashida Williams
Master of Science
Department of Molecular Genetics University of Toronto
2013
Abstract
Two synthetic human antibody fragments against the human pentaspan membrane protein
CD133 were isolated using a novel selection method involving direct selections on cells coupled
with Illumina deep sequencing. The antibody fragments were isolated through a PCR-based
recovery strategy developed in the lab and subsequently converted to full length IgGs. Termed
RW01 and RW03, the antibodies bind separate epitopes on CD133 and are able to detect the
protein using various molecular techniques. Finally, experiments have shown that RW01 and
RW03 treatment affect the stability of CD133 on live cells. Additional experiments are required
to reveal the specific epitope recognized by each antibody, which organelles they are targeted to
when internalized and whether they have an effect on cellular differentiation or cellular viability.
In addition to the therapeutic potential of these antibodies, they will have many applications
towards expanding our knowledge concerning the CD133 protein and its role in cancer.
iii
Acknowledgments
I want to thank God for sending me down this path of self-discovery. I would like to thank my
supervisors, Jason Moffat and Sachdev Sidhu for all of their help, guidance and encouragement
throughout my Masters degree. I would like to thank my Committee Members Stephane Angers
and Jim Dennis for their guidance, and advice throughout this process. I would like to thank
Sarav Rajan as my mentor when I first began in the lab. Although he has moved on, he played an
instrumental role in getting my project off the ground and helping me to be a better scientist and
researcher. I want to thank Amandeep Gakhal and Nish Patel for mentoring me after Sarav;
without their guidance, my project would not have come as far as it has. I want to thank Anthony
Mak for pioneering the way for my project and providing me with publication opportunities
throughout my time in the lab. I would like to thank my parents and my boyfriend for always
encouraging me when I was discouraged and helping me through major milestones in my life
while I undertook my Masters degree. I would like to give an enormous thank you to Esther Lau
for being the tic to my tac, for being my support system through the rough research days and the
exciting ones and for always being an ear to talk to and a shoulder to cry on and a smile to count
on both inside and outside of the lab. I want to thank everyone in the lab for your input that
helped my project turn into something that I never thought it could and I want to thank the
Genome Canada and GL2 funding agencies for funding.
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Table of Contents
Table of Contents
ACKNOWLEDGMENTS .................................................................................................................................. III
TABLE OF CONTENTS .................................................................................................................................... IV
LIST OF FIGURES ............................................................................................................................................. VI
LIST OF APPENDICES ................................................................................................................................... VII
INTRODUCTION .......................................................................................................................................... 1 1
1.1 IDENTIFICATION ............................................................................................................................................................. 2 1.2 GENOMIC ORGANIZATION AND GENE REGULATION ................................................................................................. 2 1.3 PROTEIN FEATURES, GLYCOFORMS AND EPITOPES ................................................................................................. 3 1.4 CELLULAR FEATURES ..................................................................................................................................................... 5 1.5 PRESENCE ON DIFFERENTIATED AND STEM CELLS ................................................................................................. 5 1.6 FUNCTION AND ROLE OF CD133 IN CANCER ........................................................................................................... 6 1.7 ANTIBODIES .................................................................................................................................................................... 8
METHODS .................................................................................................................................................... 13 2
2.1 CELLECTSEQ SELECTIONS .......................................................................................................................................... 13 2.2 ILLUMINA SEQUENCING PREPARATION AND ANALYSIS ....................................................................................... 15 2.3 CELLECTSEQ RESCUE .................................................................................................................................................. 16 2.4 CONVERSION TO IGG ................................................................................................................................................... 18 2.5 CELL-‐BASED ELISA .................................................................................................................................................... 19 2.6 IPTG-‐INDUCIBLE PROTEIN EXPRESSION ................................................................................................................. 20 2.7 IMMUNOFLUORESCENCE ............................................................................................................................................ 20 2.8 FLOW CYTOMETRY ..................................................................................................................................................... 21 2.9 WESTERN BLOT .......................................................................................................................................................... 22 2.10 IMMUNOPRECIPITATION-‐MASS SPECTROMETRY ............................................................................................... 22
RESULTS ........................................................................................................................................................ 24 3
3.1 CELL SELECTIONS AND SEQUENCING DATA ........................................................................................................... 24 3.2 FAB RESCUE AND VALIDATION ................................................................................................................................. 27 3.3 SCFV RESCUE AND IGG CONVERSION ....................................................................................................................... 29 3.4 IGG VALIDATION ......................................................................................................................................................... 29
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3.5 IGG APPLICATIONS ...................................................................................................................................................... 32 3.6 EPITOPES ...................................................................................................................................................................... 34 3.7 FUNCTIONAL DATA ..................................................................................................................................................... 35
SUMMARY AND FUTURE DIRECTIONS ......................................................................................... 40 4
4.1 SUMMARY ................................................................................................................................................................... 40 4.2 FUTURE DIRECTIONS ............................................................................................................................................... 41
APPENDICES ................................................................................................................................................. 44 5
REFERENCES ............................................................................................................................................. 58 6
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List of Figures
Figure 1: CD133: A Five-pass Transmembrane Domain Protein. (pg. 4)
Figure 2: IgG Schematic. (pg. 10)
Figure 3: The Cellectseq Method. (pg. 14)
Figure 4: Cellectseq Rescue strategy. (pg. 18)
Figure 5: Phage-Fab and Phage-scFv Cell-based ELISAs (p. 26)
Figure 6: RW03 Phage-Fab is specific to CD133 Overexpressing Cells. (pg. 27)
Figure 7: Purified RW03 binds to CD133 Expressing Cells. (pg. 28)
Figure 8: EC50 Measurements for RW01 IgG and RW03 IgG. (pg. 30)
Figure 9: RW01 and RW03 IgGs Identify Endogenously Expressed CD133 by Flow Cytometry.
(pg. 31)
Figure 10: RW01 and RW03 IgGs can localize CD133 by Immunofluorescence. (pg. 32)
Figure 11: RW01 and RW03 can be used in Western Blotting. (pg. 33)
Figure 12: RW01 and RW03 bind separate epitopes on CD133. (pg. 35)
Figure 13: RW01 and RW03 IgGs reduce CD133 in Caco-2 cells after 24-hours. (pg. 37)
Figure 14: RW01 and RW03 IgGs destabilize surface CD133 in SEM cells. (pg. 38)
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List of Appendices
Appendix A: Library F Illumina Sequencing Data
Appendix B: Library G Illumina Sequencing Data
Appendix C: IP-MS data
Appendix D: SEM Time Course: All data points
1
Introduction 1Cancer is a complex disease that has become the focus of many research laboratories over
the past century. Due to the range of tissues, aggressive or benign forms, typologies of the
disease and its emergence as a leading cause of mortality across the globe, cancer research has
made its way to the forefront of our attention in medical fields. The focus of this research for
many groups has turned to elucidating the cells of origin of the disease, the mechanisms which
lead to their transformation and the pathways involved in the maintenance of the disease state.
Perhaps the most important step in this process is the identification of the cells of origin of the
disease. From the discovery of the existence of somatic stem cells that replenish tissues within
organs, emerged the idea of Cancer Stem Cells (CSCs): cells of stem cell phenotype that can
maintain and propagate the tumor (Lobo, Shimono, Qian, & Clarke, 2007). The theories as to
how CSCs arise abound and there is evidence to support many of them.
The initial school of thought, based on observations of Leukemic cells, suggested that
tumor initiating cells may be stem cells that acquire mutations in the correct pathways to become
cancerous thus explaining the stem-like phenotype that distinguish such cells (Bonnet & Dick,
1997; Lapidot et al., 1994). Other evidence suggests that a progenitor cell may have gained the
ability to self-renew through multiple oncogenic mutations (Cozzio, 2003; Huntly et al., 2004;
Krivtsov et al., 2006; Lavau, 1997; Wagner, 2006). Despite a lack of definitive answers into the
origin of these cells, a picture of their characteristics has emerged. CSCs have been shown to
remain in a quiescent stage of the cell cycle, which allows them to evade conventional
chemotherapies that generally target highly proliferative cells (L. Li & Bhatia, 2011). They have
also been shown to overexpress membrane transporters, allowing these cells to become drug
resistant by expelling chemotherapeutic drugs (Dean, Fojo, & Bates, 2005). Finally, they have
been shown to evade radiotherapy due to their increased DNA damage repair and reactive
oxygen scavenging abilities (Bao et al., 2006; Diehn et al., 2009). Due to this emerging and
evolving description of the CSC’s ability to evade current methods of treatment, there is a need
for a better understanding of the way in which these cells propagate.
2
Many surface proteins have been identified as markers of these cells and this has greatly
increased our abilities to isolate and study their behavior and characteristics. In many cases
however, the role of these markers in the maintenance of the disease phenotype is not fully
understood. One such marker is the cellular surface protein Prominin-1 (CD133).
1.1 Identification
The CD133 protein was identified in 1997 through the characterization of novel
monoclonal antibodies (mAbs) by groups searching for novel markers of mouse neural and
human hematopoietic stem and progenitor cells (Weigmann, Corbeil, Hellwig, & Huttner, 1997;
Yin et al., 1997). The protein was immediately interesting due to several initial observations.
First, the AC133 antibody was determined to bind an epitope on the protein referred to as the
AC133 antigen. This epitope originally appeared to be restricted to CD34-positive cells (Yin
1997), however, there were some contradictions concerning the detection of the AC133 antigen.
This included mRNA data that contradicted with the detection of the AC133 epitope (i.e. a
strong mRNA signal was detected in kidneys, despite lack of AC133 immunoreactivity in the
tissue) (Miraglia et al., 1997; Yin et al., 1997). Also, some groups have observed the
disappearance of AC133 immunoreactivity upon Caco-2 differentiation although mRNA levels
appear to increase (Corbeil et al., 2000). These observations led to the indication that expression
of the AC133 antigen may be more restricted than general expression of the CD133 protein
(Fargeas, 2003) and that the reactivity of the protein with this particular antibody may depend
on specific protein conformations or glycosylation patterns.
1.2 Genomic organization and Gene regulation
Located on Chromosome 4 in humans, CD133 has five alternative promoters (Shmelkov,
2004). Of these, promoters 1-3 are located within a CpG island and partially regulated by
methylation (PLESHKAN, VINOGRADOVA, & SVERDLOV, 2008; Shmelkov, 2004). There
are up to 10 alternative promoters located in the 5’ untranslated region (Shmelkov, 2004). In
addition, the protein has been found to be subject to alternative splicing (Corbeil et al., 2009;
Jászai et al., 2011; Miraglia, Godfrey, & Buck, 1998; Shmelkov, 2004), where 12 alternative
3
splicing variants have been identified in mammalian prominin-1 (Fargeas, 2004; Fargeas,
Huttner, & Corbeil, 2007) and 10 alternative exons have been identified for exon 1 alone. The
regulation and expression of these variants may be tissue specific (Fargeas, 2004; Yu, 2002).
In keeping with the complexity of the splicing associated with the protein, the regulation
of the expression of CD133 is also complex and incudes many factors. DNA hypomethylation
contributes to tumorigenesis by inducing oncogene activation and genomic instability (Gaudet,
2003). Abnormal hypomethylation of the first three promoters of CD133 has been positively
correlated with increased expression of the protein in cancer stem cells of various backgrounds
(Baba et al., 2008; Tabu et al., 2008; Yi et al., 2008). In addition to the epigenetic regulation,
three different transcription factors have been shown to regulate expression of CD133: Sox17
regulates CD133 in gastric epithelial tumors (Fukamachi, Shimada, Ito, Ito, & Yuasa, 2011),
while AF4 knockdown decreased CD133 expression in AML cells (Mak, Nixon, & Moffat,
2012a). Finally, through ETS binding sites in one of the CD133 promoters, the RAS/ERK
pathway regulates expression of the protein (Tabu et al., 2010). Other factors affecting CD133
expression stem from the extracellular environment and include upregulation of CD133 in
hypoxic states (McCord, Jamal, Williams, Camphausen, & Tofilon, 2009), decreased expression
of CD133 in low iron conditions in colon cancer cells (Gilbertson & Rich, 2007) and an increase
in CD133 and CSC properties associated with low mitochondrial activity (Griguer et al., 2008).
1.3 Protein features, Glycoforms and Epitopes
CD133 is a transmembrane protein that has an extracellular N-terminal region, five
transmembrane domains with alternating short and long intra- and extracellular domains,
respectively, and an intracellular C-terminal region (Figure 1). The total protein contains
approximately 850 amino acids, depending on the splice variant, and the two large extracellular
loops contain eight N-glycosylation sites (Corbeil, Fargeas, & Huttner, 2001a; Fargeas, 2004;
Han & Papermaster, 2011; Miraglia et al., 1997; Weigmann et al., 1997). The amino acid
sequence of the protein is poorly conserved across species with only 60% identity between
primates and rodents (Corbeil et al., 2001a), less conservation between mammalian sequences
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and fish, amphibian and bird (45%) and only 25% between mammalian and invertebrate
sequences (Fargeas, 2003; Han & Papermaster, 2011; Jászai et al., 2011; Zelhof, Hardy, Becker,
& Zuker, 2006). While the amino acid sequence varies among species, the protein sequences
share common features. There are six conserved cysteines in the EC2 and EC3 domains, which
may form disulfide bridges, as well as a cysteine rich domain between TM1 and IC1.
Additionally, there is a consensus core sequence between the EC3 and TM5 regions of the
protein (Zelhof et al., 2006). Post-translational modifications to the protein include N-
glycosylation, which accounts for 15-20% of the molecular weight of the protein (Corbeil et al.,
2000; Miraglia et al., 1997; Visvader & Lindeman, 2008; Weigmann et al., 1997) and sialylation
(F. Zhou et al., 2010a), however, no O-linked glycans have been detected (Sgambato et al.,
2010). Researchers have discovered that while individual glycosylation sites are not required for
surface expression of the protein, these sites are collectively required for proper expression of
CD133 on the surface of cells (Mak et al., 2011). While researchers have made great strides in
characterizing the protein, a crystal structure has yet to be determined for CD133. Additionally,
there is currently no known ligand for the protein.
Figure 1: CD133: A Five-pass Transmembrane Domain Protein. The membrane protein CD133 is
depicted. The protein has an extracellular N-terminal region, and an intracellular C-terminal region. It
contains five transmembrane domains, and alternating short and long intracellular and extracellular loops.
The two large extracellular loops contain eight N-glycosylation sites (indicated as red branched
structures).
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1.4 Cellular features
In the cellular context, CD133 has been associated with membrane protrusions (Visvader
& Lindeman, 2008; Weigmann et al., 1997) and has been found to interact directly with
membrane bound cholesterol (Corbeil, Marzesco, Fargeas, & Huttner, 2010; Florek et al., 2006;
W. B. Huttner, Röper, & Corbeil, 2000). The protein is also released in body fluids in association
with small membranous vesicles (Marzesco, 2005) and has been detected in CSF, seminal fluid,
urine and saliva (Florek et al., 2006; H. B. Huttner et al., 2008; Marzesco, 2005).
1.5 Presence on Differentiated and Stem Cells
While the main function of the CD133 protein has been as a marker of cancer stem cells
and hematopoietic progenitor cells, the protein has been shown to be expressed at all stages of
development. Expression of the protein has been detected in kidneys (Corbeil et al., 2000;
Fargeas, 2003; Florek et al., 2006), colon (Horst, Kriegl, Engel, Kirchner, & Jung, 2008; Horst et
al., 2009; Kojima et al., 2008; C.-Y. Li et al., 2009), prostate (Mizrak, Brittan, & Alison, 2007),
pancreas (Koblas et al., 2008; Sugiyama, Rodriguez, McLean, & Kim, 2007), liver (Karbanova
et al., 2008), mammary glands (Florek et al., 2006; Immervoll, Hoem, Sakariassen, Steffensen, &
Molven, 2008), the epithelium of the epididymal duct (Gashaw et al., 2007) and in cephalic
exocrine glands (Karbanova et al., 2008). Furthermore, CD133 potentially labels progenitor cells
in a number of tissues including muscle (Alessandri et al., 2004), skin (Belicchi et al., 2004), and
intestines (Zhu et al., 2008). Additionally, CD133-expressing cells with self-renewal capacity
have been identified in many of the aforementioned differentiated tissues, as well as in the brain
(Hemmati, 2003; Singh et al., 2003), lung (Chen et al., 2008; Eramo et al., 2007), and ovary
(Curley et al., 2009). Due to the widespread expression of the protein in tissues ranging from
differentiated types to cells with self-renewal capacities, it comes as no surprise that CD133 is
expressed broadly in human differentiated tumors (Visvader & Lindeman, 2008).
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1.6 Function and Role of CD133 in Cancer
Despite the vast array of data concerning the various aspects of the protein, the function
of CD133 has yet to be elucidated. Due to the membrane localization of the protein and the
association with membrane protrusions, CD133 is widely thought to be a scaffolding protein or
involved in the organization or remodeling of membrane protrusions. Additionally, due to the
association of the protein with membrane lipids and cholesterol, it has been suggested that the
protein is involved in maintaining the dynamics of the plasma membrane (Corbeil, Röper,
Fargeas, Joester, & Huttner, 2001b; W. B. Huttner et al., 2000). Mutations in the protein have
been shown to lead to photoreceptor degeneration in humans and CD133 knockout mice display
macular photoreceptor degeneration (Maw et al., 2000; Zacchigna et al., 2009). Other evidence
has emerged that indicates that the extracellular release of CD133 occurs in conjunction with
progenitor cell differentiation (Bauer et al., 2011).
The concept of a role for CD133 in cancer has begun to be investigated in a wide array of
cancer types by assessing the usefulness of CD133 as a marker of CSCs in these various cancer
types. In 2003, Singh and colleagues identified CD133 as a marker for CSCs in brain tumors
(Singh et al., 2003) and subsequently demonstrated that as few as 100 CD133+ cells from brain
tumor fractions were required to generate a tumor in NOD/SCID mice (Singh et al., 2004).
Additionally, CD133+ glioma cells were shown to have increased resistance to radiation in a
DNA checkpoint dependent manner as compared with CD133- cells (Bao et al., 2006).
In pancreatic cancer cells, Hermann and colleagues were able to isolate pancreatic CSCs
using anti-CD133 antibodies and demonstrated that these cells were tumorigenic and highly
resistant to standard chemotherapy (Hermann et al., 2007). Corroborating this evidence, other
groups have linked cues in the tumor environment to induce CD133+ pancreatic cancer cells to
have a more aggressive nature including increased migration and invasion and heightened tumor
aggressiveness (Moriyama et al., 2010). In spite of this, the ultimate test of CD133+ pancreatic
cancer cells possessing stem-cell like properties will be the ability of these cells to reconstitute
the heterogeneity of a pancreatic tumor upon engraftment of a single cell.
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In prostate cancer, Collins et al. identified the first stem-like cells from prostate cancer
tissues (Collins, 2005). Since this observation, several groups have demonstrated stem cell
features in CD133+ cells isolated from prostate cancer tissues and in an immortalized prostate
cancer cell line (Miki et al., 2007; Wei, Guomin, Yujun, & Ruizhe, 2007), however other groups
have failed to confirm the presence of stem-cell properties in prostate cancer samples (Missol-
Kolka et al., 2010) and do not observe the stem-cell characteristics others attribute to pancreatic
cancer lines like the DU145 line (Pfeiffer & Schalken, 2010).
Another cancer type for which CD133 is used as a CSC marker is colorectal carcinoma.
CD133 was identified by two separate groups as a marker of CSCs in colon cancer (O'Brien,
Pollett, Gallinger, & Dick, 2006; Ricci-Vitiani et al., 2006) and both groups demonstrated that
CD133+ cells readily recapitulated tumors in SCID mice (Ricci-Vitiani et al., 2006), and that
there was an enrichment of colon cancer initiating cells in the CD133+ suspension of cells
compared to the unfractionated tumor cells (O'Brien et al., 2006). However, Shmelkov and
colleagues demonstrated that both CD133+ and CD133- expressing cells from colon metastases
were able to form colon-spheres and recapitulate tumors in NOD/SCID mice (Shmelkov, 2004).
Additionally, several groups have concluded that CD133 is associated with worse clinical
prognosis, risk of disease progression and metastasis and that the protein can be used as an
independent prognostic marker for colorectal cancer patients (Horst et al., 2009). However, other
groups have failed to find a relationship between CD133 and disease progression or survival in
colon cancer patients but have instead found a relationship between the expression of the protein
and tumor stage (Lugli et al., 2010). In each case, there is conflicting data concerning the role of
CD133 as a marker of CSCs as well as some discrepancy as to the clinical usefulness of the
protein as a diagnostic tool.
There is however, the case of metastatic melanoma, which provides promising insights
into the role of CD133 in a diseased state. In 2008, Rappa and colleagues demonstrated that
downregulation of CD133 in a metastatic melanoma cell line, FEMX-I, resulted in slower cell
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growth, decreased cell motility, decreased ability to form spheres in stem-cell growth conditions
and a reduced metastatic capacity of tumor xenografts (Rappa, Fodstad, & Lorico, 2008). Based
on reports that AC133 conjugated to monomethyl auristatin F inhibited the growth of
hepatocellular and gastric cancer cells in vitro (Smith et al., 2008), they were able to show that
secondary antibody conjugated to saporin in the presence of AC133 was toxic to FEMX-I cells
but not control human fibroblasts (Rappa et al., 2008). Additionally, AC133 directly conjugated
to saporin was more effective against FEMX-I cells than FEMX-I cells with CD133 expression
knocked down (Rappa et al., 2008). To add to their conclusions, they noted that in cells in which
CD133 is knocked down, genes that became upregulated coded for wnt inhibitors, a result
corroborated by Mak et al. (Mak, Nixon, & Moffat, 2012a). These results provide exciting
insights and implications into the value of pursuing the discovery of the role of CD133 in cancer
as well as targeting the protein for effective therapeutic development.
The results of the metastatic melanoma studies along with those of the brain, prostate,
pancreatic and colon cancer studies have demonstrated that while there is indeed the promise of
therapeutic development of CD133 antibodies, there is still much to be discovered concerning
the function of the protein, its potential role in the maintenance of a stem-like phenotype and its
role in tumor aggressiveness. Thus, the development of tools to continue to investigate this
aspect of CD133 function is paramount.
1.7 Antibodies
In recent decades antibodies have proven invaluable as tools and therapeutics. As
reagents, antibodies are widely used in many common molecular and cellular techniques. As
therapeutics, the FDA has approved 35 antibody-based therapies with 17 of those targeting cell-
surface receptors (Scott, Wolchok, & Old, 2012; Y. Zhou, Zhao, & Marks, 2012). Indeed,
proteins at the cell surface prove to be important targets due to their inter- and intracellular
signaling capabilities as well as their involvement in cancer and tumor maintenance and
recognition (Adams & Weiner, 2005; Weiner, Surana, & Wang, 2010). Hybridoma technology
has been largely employed as the production methodology for antibody development however,
9
limitations and challenges relating specifically to cell surface proteins have become evident.
Examples of such limitations include the need for purified proteins for animal injection, as cell-
surface proteins are not easily purified and usually require the membrane environment for proper
folding and epitope display. Additionally, the humanization of antibodies requires an extra step
that is a lengthy and costly process. As well, for evolutionarily conserved proteins, selection of
antibodies proves difficult, as animals will not make antibodies to native epitopes.
In order to circumvent these issues, phage and yeast displayed libraries have been
developed and employed in antibody selection methods. In antibody phage-display technology,
genes that encode antibody fragment proteins are fused to coat proteins on the M13 filamentous
bacteriophage. In this way, the antibody fragments are “displayed” on the bacteriophage surface
(Sidhu, 2001). The expression of these fusion proteins and subsequent assembly of the M13
bacteriophage occurs inside its host, the bacterium Escherichia coli. The most common form of
antibody is the Immunoglobulin G (IgG) (Fellouse & Sidhu, 2007; Sidhu & Fellouse, 2006).
IgGs are heterotetrameric proteins consisting of two heavy chains and two light chains. To add to
this complexity, the protein contains both inter- and intra-molecular disulfide bonds and is
glycosylated on the heavy chain (Sidhu & Fellouse, 2006). This level of complexity proves
difficult to maintain in bacterial hosts, however, the entire protein is not required for antigen
recognition (Fellouse & Sidhu, 2007). The antigen-binding site of an IgG is contained in the
antigen binding fragment (Fab) portion of the protein, which amounts to a single unglycosylated
arm of the IgG molecule. Smaller still is the single-chain variable fragment (scFv) of the Fab, in
which the constant heavy and light chain regions are eliminated and solely the variable heavy
and light chain regions persist, connected by a linker sequence (Figure 2) (Rader & Barbas,
1997). The specific regions that primarily mediate antigen recognition are the complimentarity
determining regions (CDRs), of which there are six: three contained in the variable region of the
light chain (CDRL1-3) and three contained in the variable region of the heavy chain (CDRH1-3)
(Hoogenboom, 2005). Thus, due to the location of the CDRs in the variable heavy and light
regions of the antibody fragments, both Fabs and scFvs are able to mediate antigen binding and
are employed in the Sidhu and Moffat labs in the form of phage-displayed libraries. These
libraries vary in their levels of diversity with the Fab library (termed Library F) containing amino
acid diversity in CDRs H1 and H2 and amino acid as well as length diversity in CDRL3 and H3.
10
In contrast, the scFv library (termed Library G) contains solely amino acid diversity in CDRs L2
and H2 and amino acid diversity coupled with length diversity in the remaining CDRs (Library
G, manuscript in preparation). These libraries are non-immunogenic naïve libraries, which are
able to target a broader range of epitopes including those unable to be targeted through animal
immunization. Additionally, synthetic libraries can reach diversities 10 to 100 times greater than
that which is covered by the human immune system let alone animal systems (Persson, 2009).
Finally, these libraries allow for the production of human proteins and thus the likelihood of the
resultant proteins showing high immunogenicity is reduced (Sidhu & Fellouse, 2006).
Figure 2: IgG schematic. A common IgG molecule is depicted. The protein contains two heavy and two
light chains connected by a series of disulfide bridges (four shown for simplicity). Fab and scFv portions
of the IgG are indicated. The CDRs are contained within the variable heavy and variable light portions of
the protein.
Great strides have been made in the development of methods to by-pass the need for
purified proteins during the antibody selection process. Notably, yeast-displayed antigens have
been incorporated in the selection process (Y. Zhou, Zou, Zhang, & Marks, 2010b) as well as
VH VH
VL
CL
CH1 CH1
VL
CL
CH2CH2
CH3 CH3
-s-s--s-s-
-s-s- -s-s-
Fab
Fc
scFv
Heavy chain
Light chain
11
direct selections on blood cells (Huie et al., 2001) and cancer cell lines (Conrad et al., 2009;
Heitner et al., 2001; Poul, Becerril, Nielsen, Morisson, & Marks, 2000). While these processes
have shown success, one issue that remains difficult to remedy concerns the high level of phage
binding to background proteins on cells. Many methods have emerged to reduce these
background phage including multiple rounds of pre-selection or depletion on cell types related to
the positive line used (Ridgway et al., 1999; Van Ewijk et al., 1997) in addition to techniques
such as centrifugation and solvent separation (Giordano, Cardó-Vila, Lahdenranta, Pasqualini, &
Arap, 2001; B. R. B. Williams & Sharon, 2002). Phage-displayed libraries have also been used
to select for antibodies that can be internalized and thus may have the potential to deliver
cytotoxic substances upon endocytosis (Abraham et al., 2007; Nielsen & Marks, 2000). Finally,
many of the methods described result in a panel of antibodies against antigens specific to a cell
type but the antigen identities are unknown to the researcher. In these cases, laborious protocols
involving immunoprecipitation coupled with mass spectrometry (Poul et al., 2000) or antibody
screening on multiple cells lines in tandem with screening on yeast-displayed antigen libraries to
narrow down or identify the potential antigen are required (Y. Zhou et al., 2010b).
While antibody development using phage-displayed libraries has seen many
improvements for the isolation of high affinity antibodies specific to target cell types and
antigens, a more high-throughput method for identification of larger numbers of antibodies
would provide an ideal avenue for development of a panel of antibodies against a panel of
epitopes. In the Sidhu and Moffat labs such a method was developed and incorporated many of
the recent methodological advancements in phage-display technology with a high-throughput
approach to identify high-affinity binders to specific antigens and avoid isolation of non-specific
antibody binders. The method, termed Cellectseq, employed phage-displayed antibody libraries
in whole cell selections on both negative and positive cells coupled to Illumina sequencing to
provide the sequencing depth needed to recover sequences occurring at as low as 0.3% of the
output phage pool. A PCR based recovery strategy was developed to rescue desired clones and
antibody fragments (Cellectseq Manuscript, in preparation).
With a promising target and the technology to develop tools to be able to study this
target, the stage is set for the goal of my project. The aim of my project is to use Cellectseq to
12
develop a panel of human antibodies against CD133 that target distinct epitopes on the protein.
Upon generation of these antibodies, the affinity and specificity for the target will be assessed as
well as the usefulness in applications in molecular biology techniques that will aid in the
investigation of the function of the protein in future experiments. Finally, the beginnings of a
functional analysis of the antibodies will compare the effect of the antibodies with CD133
knockdown experiments.
13
Chapter 2
Methods 2
2.1 Cellectseq Selections
Library F (phage-Fab) and Library G (phage-scFv) were used to perform the Cellectseq
selections. At the time that the selections were performed, the preparation of Library F had a
diversity of 3 x 1010 and the stock used was diluted to 8 x 1012 cfu/mL (colony forming units).
After precipitation and resuspension of Library F, it was calculated that each cell line was
exposed to 100x the diversity of the library. Similarly, the preparation of Library G had a
diversity of 1 x 1011 and the stock was diluted to 4.6 x 1012 cfu/mL. After precipitation and
resuspension of Library G, it was calculated that each cell line was exposed to 46x the diversity
of Library G.
Prior to the selection process, the libraries were precipitated by adding 4 mL of the
library F stock to 26 mL PBS and 7 mL of the Library G stock to 23 mL PBS and precipitating
with 7.5 mL PEG/NaCl. This mixture was incubated on ice for 20 minutes, centrifuged for 20
minutes at 20,000g and resuspended in binding buffer (DMEM containing 10% FBS, 50 mM
HEPES, 2 mM EDTA).
Libraries F and G were subjected to four rounds of selection with each round consisting
of a pre-absorption step followed by a positive selection step (figure 3). For the pre-absorption
step, HEK293 cells were washed once with PBS and lifted with an EDTA solution (0.3 g/L
disodium EDTA, 8 g/L NaCl, 0.56 g/L sodium bicarbonate, 1 g/L D-glucose, 0.4 g/L KCl) and
resuspended in DMEM with 10% heat inactivated fetal bovine serum (IFS). Ten million cells
were then resuspended with approximately 1012 cfu of either library F or Library G phage in a
cell-binding buffer. The cells were incubated with the library for 1.5 hours at 4°C with gentle
rocking. The cells were then centrifuged for 5 minutes at 1500 rpm and the supernatant
containing unbound phage was used for the positive selection.
14
Figure 3: The Cellectseq Method. Cell selections were performed with Library F (phage-Fab) or Library
G (Phage-scFv) (Library F depicted here). The libraries are subjected to a pre-adsorption step in which
the libraries are incubated with cells that do not express the protein of interest to reduce non-specific
binders. Following pre-adsorption, the cells and any bound phage are pelleted and the supernatant is used
in a positive selection step. In this step pre-adsorbed libraries are incubated on cells over-expressing the
protein of interest. After several washing steps the phage are eluted and re-infected into E. coli for
amplification in further rounds of selection. Output phagemids are extracted and prepared for Illumina
sequencing by adding barcode sequences through PCR.
In the positive selection, HEK293 cells stably overexpressing CD133 were harvested in
the same manner as cells in the pre-absorption step and 5 million cells were resuspended with
either pre-adsorbed Library F or G. Cells were incubated with the libraries for 2 hours at 4°C
with gentle rocking. Following incubation, cells were centrifuged for 5 minutes at 1500 rpm. The
supernatant was removed and the cells were washed with 10 mL cold PBS and transferred to a
15
new tube after which the cells were again centrifuged for 5 minutes at 1500 rpm. This washing
process was repeated three times. After the last wash cells were pelleted and wash buffer was
completely removed. The cell pellets were incubated with 0.1N HCL for 5 minutes at room
temperature to elute the phage particles. The eluate was neutralized with 1M Tris-HCl. Half of
the elution was used to infect actively growing XL1-blue E. coli cells for 30 minutes at 37°C.
After the initial infection, XL1-blue cells were co-infected with M13K07 at a final concentration
of 1010 pfu and incubated for 45 minutes at 37°C. After the co-infection period, infected cells
were transferred to a 25 mL flask of 2YT culture medium with 100 µg/mL carbenicillan and 25
µg/mL kanamycin and grown overnight. The next day, the cells were pelleted, and the phage was
precipitated from the supernatant using PEG/NaCl. This phage was used in a second round of
pre-absorption and positive selection after which the entire process was repeated for two more
rounds of selection.
In parallel, a negative selection was performed on parental HEK293 cells by eluting the
phage from the pre-adsorption step, neutralizing this phage and infecting XL1-blue cells with a
portion of this eluate. This process was started at selection round 2.
2.2 Illumina Sequencing Preparation and Analysis
The output phage was infected into XL1 blue cells and grown overnight in 2YT culture
media with 100 µg/mL carbenicillin. Cultures were miniprepped using a Qiagen kit to obtain
phagemid DNA to use as the template for PCR with individual forward primers. Each primer
consisted of an adaptor sequence
(5’AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACGACGCTCTTCCGA
TCT-3’), a five base pair barcode sequence specific to the positive or negative pool (positive
pool: 5’-GAGTA-’3; negative pool: 5’-CCAAA-‘3), and an annealing site to the third antibody
framework region of the heavy chain (5’-GTCTATTATTGTGCTCGC-3’). For all phage pools,
a reverse primer containing a second Illumina-compatible adaptor region (5’-
CAAGCAGAAGACGGCATACGAGCTCTTC-3’) and an annealing site to the phagemid vector
(5’-TCCTTGACCCCAGTAGTC-3’) was used. The output amplicons extended from CDR L3 to
CDR H3 so that a paired-read strategy could be used for the sequencing analysis. Determining
both major CDR sequences as a pair facilitated the use of a modified PCR recovery strategy
16
designed to rescue all six CDR sequences. PCR reactions were performed with the high fidelity
polymerase Phusion (Finnzyme) and 400 to 600 ng of template DNA. Reactions were subjected
to 15 cycles of annealing and extension, consisting of 30 s at 57°C and 45 s at 72°C. PCR
products were digested with ExoI (USB), SAP (USB), and Dpn1 (NEB) and then purified on a
PCR purification column (Qiagen). Successful amplification of the correct DNA fragment from
each phage pool was verified by agarose gel electrophoresis. The amplified DNA fragments were
pooled and subjected to Illumina DNA sequencing on an Illimina GAII, with 72 base pair reads,
using the GAII chemistry V3 and SCS (Sequencing Control Software) version 2.4. Each
sequencing read was assigned to its correct pool on the basis of its unique barcode sequence. The
reads were filtered according to their Phred score (Cock, Fields, Goto, Heuer, & Rice, 2010).
Since a constant aligner region was sequenced, these regions were used to optimize the Phred
score cutoffs. Briefly, all sequences with Phred scores of 20 and higher for every base were kept.
A tolerance number (Cock et al., 2010) of medium quality (Phred score higher than 15) was
allowed. DNA sequences were translated to decode the sequence of the light chain CDRL3 and
the heavy chain CDRH3.
2.3 Cellectseq Rescue
The output phage was infected into XL1 blue cells and grown overnight in 2YT culture
media with 100 µg/mL carbenicillin. Cultures were miniprepped using a Qiagen kit to obtain
phagemid DNA to use as the template for the recovery strategy. A region of the output phage
DNA was amplified with a nested PCR that amplified the scFv encoding region. Primers used
were specific to the phagemid backbone and lay upstream of the variable light chain and
downstream of the variable heavy chain regions. The product was PCR purified with a Qiagen
PCR purification kit, quantified, normalized to 25 ng/ul and served as the template for three
parallel nested PCR reactions. The first reaction rescued the VL region, including CDR L1, L2
and L3 sequences using a forward primer (termed ss149) specific to a region upstream of the VL
framework and encompassing an NsiI restriction site and a reverse primer (termed p3) specific to
the CDRL3. The second reaction generated a fragment encompassing the linker region between
the heavy and light chains and the heavy chain variable domain, rescuing CDR H1, H2, and H3
sequences. Here the forward primer (termed p1) was specific to the CDRL3 and the reverse
17
primer (termed p2) annealed to the CDRH3. The third reaction amplified from a region in the
VH framework (primer termed ss147) to a constant region of the vector containing an NheI
restriction site (primer termed ss148). Each reaction was subjected to 27 cycles of annealing and
extension consisting of 30s at 98°C, 10s at 98°C, 30s at 55°C, 1 minute 30s at 72°C, and 10
minutes at 72°C. The products of the three reactions were cleaned up using ExoI and SAP (37°C
for 15 minutes, 80°C for 15 minutes) and combined together with the high fidelity polymerase
Phusion (NEB) and annealed and subjected to extension PCR without primers for 10 cycles (30s
at 98°C, 10s at 98°C, 1 minutes at 55°C, 1 minute at 72°C and 10 minutes at 72°C). A solution
containing primers was added as well as more Phusion, dNTPs resulting in a double stranded
fragment containing all six CDR regions and subcloned into an expression vector (Figure 4).
18
Figure 4: Cellectseq Rescue strategy. A Nested PCR amplifies a region encompassing the heavy and
light variable regions. Parallel PCR reactions are set up using primers specific to the CDRL3 and CDRH3
regions. The CDR-specific products are amplified, digested and ligated into an expression vector.
2.4 Conversion to IgG
Upon rescue and sequence verification of the anti-CD133 scFv, a PCR-based strategy
was used to convert the scFv into an IgG. The heavy and light chains were cloned into separate
vectors to be co-transfected into mammalian cells for expression. Four PCR reactions were
Restriction digest and subclone
dsDNA poolA
B
(1) PCR ampli!cation ofVL to VH regions
12
3
(5) Extension PCR
12
3
(2) Parallel PCRs(3) ExoI, SAP clean up(4) Anneal products
Adapted from Cellectseq Manuscript
19
setup, two for the heavy chain and two for the light chain, which was followed by a PCR clean
up using Qiagen PCR purification columns. Equal amounts of the two PCR reactions were mixed
per heavy chain or light chain and re-annealed, and the re-annealed products were
phosphorylated in preparation for ligation. The phosphorylated products were cloned into the
pFUSE series of expression vectors from Invivogen. The vectors containing the scFv heavy and
light chains were transformed and single colonies were picked, miniprepped using a Qiagen
miniprep kit and sent for sequencing to confirm heavy and light chain sequences.
2.5 Cell-based ELISA
Single colonies of phage-fab or phage-scFv-infected XL1-blue cells were picked,
inoculated into 350ul 2YT containing 100 µg/mL carbenicillan and 25 µg/mL kanamycin and
allowed to grow overnight at 37°C. The same day, two 96-well tissue culture treated Costar
plates were treated with 50 µg/mL poly-L-lysine (Sigma) for 10 minutes at Room temperature in
the tissue culture hood. Coated wells were washed once with PBS and 50,000 HEK293 or
HEK293-CD133 cells were seeded per well and allowed attach to the plate overnight. After 24
hours, the bacterial cultures were spun down and 50ul of culture supernatant was added to a
HEK293/HEK293-CD133 pair of wells (each clone picked was added to a well with HEK293
cells as a control and a HEK293-CD133 well to test for binding). Cells were incubated with the
phage for 1.5 hours at 37°C. After the incubation period, the media was removed and the cells
were washed twice with PBS. The cells were subsequently fixed with 3.2% Paraformaldehyde
(PFA, Electron Microscopy Sciences) for 20 minutes at room temperature. The cells were then
washed and blocked with a PB buffer (0.2%BSA in PBS) and incubated with anti-M13
conjugated to Horseradish peroxidase (anti-M13-HRP) at a 1:5000 dilution for 30 minutes at
room temperature. After the incubation period, the cells were washed three times with PBS with
five-minute incubations between each wash. The plate was developed by adding 50 µL of a 1:1
mixture of TMB Peroxidase substrate and Peroxidase substrate solution B (KPL) and incubating
at room temperature for 5-10 minutes. The reaction was stopped with 50 µL 1M Phosphoric acid.
20
2.6 IPTG-inducible Protein Expression
A stop codon was introduced between the variable heavy chain and the p3 phage protein
through an oligo-directed process (Kunkel 1985). The phagemid containing the stop codon was
digested with NsiI and SalI to obtain an insert containing the RW03 Fab sequence, and the insert
was ligated into the IPTG-inducible expression vector. Once sequence verified, the vector was
transformed into BL21 E. coli cells for protein expression. Cultures were grown in 2YT
supplemented with 100 µg/mL carbenicillin to an optical density of 0.6-0.8 and IPTG was added
to a final concentration of 1mM to induce protein expression. The cells were spun down, frozen
to promote lysis, thawed and resuspended in lysis buffer (containing Triton X-100, benzonase,
Magnesium chloride, PMSF, lysozyme and PBS). The pellets were lysed for 1hr (with shaking at
4°C) and lysed pellets were spun down for 40 minutes at 12,000 rpm. The supernatant was
transferred to a new tube and 1 mL of protein A Sepharose beads (GE Healthcare) was added
and allowed to mix for 30 minutes at 4°C. The beads were spun down at 500 rpm for 2 minutes,
and using a transfer pipette, were packed into a 10 mL column. The column containing the beads
was washed with a total 25 ml PBS and the Fab was eluted from the column in 2 ml fractions
using elution buffer and neutralized with 0.5 mL 1M Tris pH 8.0.
2.7 Immunofluorescence
Immunofluorescence was performed on intact CD133 overexpressing HEK293 cells and
parental HEK293 cells. Cells were seeded onto poly-L-Lysine coated glass coverslips in 12-well
plates. Forty-eight hours post-seeding, the cells were washed with cold PBS+ (containing 1 mM
MgCl2 and 1 mM CaCl2) and incubated on ice. The cells were then fixed for 20 minutes (5
minutes on ice and 15 minutes at room temperature) with 4% PFA and then washed three times
with PBS+. Cells were blocked for 10 minutes at room temperature with 1% BSA in PBS+. The
blocking solution was aspirated and the RW01 or RW03 antibodies were added at 5 µg/ml in
blocking solution and incubated for 1 hour. Cells were washed twice with cold PBS+ and
incubated with an APC-conjugated anti-human secondary in blocking solution at a dilution of
1:1000 and incubated for 30 minutes. The cells were washed five times with PBS+ and the nuclei
were stained with a 1:1000 dilution of Hoechst. Cells were washed twice with cold PBS+ and
mounted on slides with Prolong anti-fade reagent (Invitrogen). The images were acquired using
21
the WaveFX spinning disk confocal microscope by Quorom Technologies Inc. Composite
images of the ‘xy’ and ‘yz’ planes are represented (scale bar, 16 µm).
Immunofluorescence to assess induction of internalization of the IgGs was performed
similarly with the following changes: After a 30 minute incubation with RW01 or RW03, cells
were washed in cold Hank’s Buffered Saline Solution (HBSS) and moved to 37°C to promote
antibody internalization, for 30 minutes. Cells were subsequently returned to ice and washed
twice with cold HBSS. Alexa-647 conjugated anti-human secondary was added in HBSS plus
5% donkey serum at a dilution of 1:50 and incubated on ice for 10 minutes with a goat-anti-
transferrin antibody at a dilution of 1:1000. Cells were washed twice with cold HBSS and fixed
at room temperature with 4% PFA in PBS for 20 minutes. Cells were washed and permeabilized
with ice-cold methanol for 10 minutes at -20°C. Methanol was removed and cells were washed
with HBSS. Alexa-594 conjugated anti-human secondary was added in HBSS plus 5% donkey
serum at a dilution of 1:50 and incubated for 10 minutes with a 1:1000 dilution of Hoechst for
nuclear staining. Cells were washed three times with HBSS and mounted on slides with DAKO.
The images were acquired using the WaveFX spinning disk confocal microscope by Quorom
Technologies Inc. Composite images of the ‘xy’ and ‘yz’ planes are represented (scale bar, 16
µm).
2.8 Flow Cytometry
Cells were lifted from 10-cm tissue culture treated dishes with an EDTA solution and
resuspended in PBS supplemented with 2% FBS. Cells were counted and seeded at 200,000 cells
per well in a deep 96-well plate. The cells were blocked for 30 minutes on ice in 2% FBS-PBS.
The plate was spun down at 1500 rpm for 5 minutes and excess blocking solution was removed.
The cells were incubated with 5 µg/ml primary antibody solution on ice for one hour and washed
three times with 2% FBS-PBS. An anti-Fab’2-APC conjugated secondary antibody (Jackson
Immunoresearch) was added to the cells at a 1:1000 dilution in blocking solution and incubated
on ice for 30 minutes. The cells were washed three times, resuspended in 1% PFA and analyzed
on a FACScalibur.
22
2.9 Western Blot
Cells were seeded in 10-cm dishes and allowed to reach 80% confluency. The media was
aspirated and the cells were washed twice with ice-cold PBS. One hundred microliters of cell
lysis buffer (10% glycerol, 50 mM Hepes KOH pH 8.0, 100 mM KCl, 2 mM EDTA, 0.1% NP-
40, 2 mM DTT, 10 mM NaF, 0.25 mM NaOVO3) was added to the cells and the cells were
scraped with a cell scraper (Costar). The lysates were incubated on ice for 15 minutes, spun
down at 13,000 rpm for 10 minutes and transferred to a new tube. Lysates were normalized to 1
µg/ul and 10 µg of lysates were loaded on a 4-15% Mini-PROTEAN TGX Tris-Glycine gel (Bio-
Rad). Gels were run for 1 hour and 10 minutes at 100 V and transferred to ethanol-activated
PVDF membranes (GE Healthcare) using a Bio-Rad transfer box for 1 hour at 100 V on ice. The
membranes were washed once with Tris Buffered Saline with 0.1% Tween-20 (TBST) wash
buffer and blocked for 30 minutes in 5% skim milk in TBST. The membranes were washed once
with TBST for 5 minutes and membranes were incubated with RW01 or RW03 IgGs as primary
antibodies at 5 µg/ml diluted in 5% BSA at 4°C overnight. The membranes were washed three
times for 5 minutes per wash and an anti-human HRP conjugated secondary antibody (Jackson
Immunoresearch) was added at 1:1000 diluted in 5% BSA. Membranes were incubated with
secondary antibody for one hour at room temperature and washed three times for 10 minutes per
wash. Membranes were then bathed in developing solution (SuperSignal, Thermo Scientific) for
one minute before exposing the membranes on film (Blue. Other antibodies including β-actin
(Sigma) and AC133 (Millipore) were diluted in 5% skim milk and the secondary antibody used
was an anti-mouse HRP conjugated antibody from (Santa Cruz).
2.10 Immunoprecipitation-Mass Spectrometry
Immunoprecipitation was performed as follows: Caco-2 cells were seeded in twelve 15-
cm dishes and allowed to grow to ~80% confluency. Cells were scraped using cell scrapers,
collected in one 50 mL falcon tube and frozen at -20°C. The thawed cells were resuspended in 10
mL lysis buffer. Lysed cells were spun down for 10 minutes at 20,000g and the resulting
supernatant was spun again for 1 hour at 4°C to reduce ribosomal proteins. Lysates were
quantified using the Pierce BCA assay (Thermo Scientific) and 10 µg of precipitating antibodies
were added to 10 mg lysate. After the overnight incubation, 50 µL of beads were added to the
23
antibody-lysate suspension and incubated for two hours at 4°C. The beads were spun down at
1600 rpm and the supernatant was aspirated. The beads were washed three times with cell lysis
buffer and subsequently twice with ultrapure sterile water (Invitrogen). Following the washes, 40
µL of 0.15% Trifluoroacetic acid (TFA) was added to the beads to elute the protein. The beads
were spun down, the elution was removed and this was repeated twice more with 30 uL of 0.15%
TFA added in subsequent elutions. The elutions were combined and 10 µL of 1 M NH4HCO3
was added in order to adjust the pH to 8. This was followed by the addition of 10 µL of 45 mM
DTT and incubation for 20 minutes at 60°C. The suspensions were spun down, cooled to room
temperature and 10 ul of 100 mM Iodoacetamide (Bioshop) was added and incubated at room
temperature for 15 minutes in the dark. Finally, 1 µL of trypsin was added and samples were
incubated at room temperature overnight with gentle rocking. C18 StageTip (Thermo Scientific)
filters were used to purify the peptides before analysis by mass spectrometry.
Mass Spectrometry for the identification of immunoprecipitated proteins was performed
at the Toronto Mars Discovery Tower Mass Spectrometry Facility. Analysis was performed on a
Q-Exactive hybrid quadrupole-orbitrap mass spectrometer. Data was acquired using Xcalibur
software. The SEQUEST and X!Tandem search engines were used to analyze spectrometric data
and compare hits to the human Uniprot database. Results were viewed using the Scaffold4
viewer.
24
Chapter 3
Results 3
3.1 Cell Selections and Sequencing Data
In order to develop antibodies against CD133, I employed the Cellectseq method
developed in the Sidhu and Moffat labs. I used two phage-display libraries in the selections:
Library F and Library G. Library F is a Fab library with diversity in the third light chain CDR
(L3) and all three of the heavy chain CDRs (H1, H2 and H3). Library G is an scFv library with
diversity in all six CDR regions. The cells used for the selections included HEK293 cells
engineered to overexpress CD133 for the positive selection and the parental HEK293 cells were
used for the negative selection.
After four rounds of positive and negative selection, I made serial dilutions of the round
four output phage (10-1 to 10-3) for each library, infected XL1-blue cells and plated the infected
cells for single colonies to use in a clonal cell-based ELISA to isolate CD133-specific binders.
Clones that bound to the CD133 expressing cells and generated an ELISA signal that was greater
than 1.5 fold above binding to background HEK293 cells were considered to be CD133-specific
binders. As shown in Figure 5a, none of the library G clones picked displayed any specificity
towards CD133 expressing cells. In contrast, 77 of 94 clones picked from the Library F output
showed binding above background (>1.5 fold). All 94 library F phage-fab clones picked for the
ELISA were sent for sequencing by amplifying the VL and VH regions with M13-tagged
sequencing primers. The sequencing results indicated that 89 of 94 clones shared the same
sequence and two other individual clones had unique sequences. Three clones were unable to be
sequenced. Figure 5b shows the representative ELISA results for the three unique phage-Fab
binders. In parallel, the Library F and G round three and four positive and negative outputs were
prepared and sent for Illumina sequencing.
I proceeded to test the three unique phage-Fab binders from the Library F output in an
immunofluorescence (IF) assay, the results of which are shown in figure 6. The IF showed that
phage-Fab clones C12 and F5 bound non-specifically to both the CD133 overexpressing line as
well as the parental line. However, the RW03 phage-Fab demonstrated highly specific binding to
the CD133 over-expressing line with very little binding to the parental background line. These
25
results were consistent with the Illumina sequencing results in which the sequences
corresponding to phage-Fab clones C12 and F5 appeared in both the positive as well as the
negative selection output pools whereas the sequence of RW03 appears in only the positive
selection pool (Appendix A). Additionally, the RW03 sequence was the most abundant sequence
in both the round 3 and 4 output pools, which is also consistent with the results of the small scale
cell-based ELISA in which 94% of the sequences were that of RW03.
A direct consequence of the Cellectseq method of coupling of cell selections with
Illumina deep sequencing is the bank of sequences that are identified and that can be specifically
rescued from the output pool. Thus, while the small-scale rescue of Library G binders did not
yield any CD133-specific scFv binders, the Illumina sequencing data provided a list of sequences
that could be chosen for rescue from the selection output pools.
26
Figure 5: Phage-Fab and Phage-scFv Cell-based ELISAs. Following cell selections, round four output
phage for each library was plated for single colonies. These colonies were grown up in an overnight
culture and tested for binding to cells by cell-based ELISA. The plates were read and OD 450 nm was
27
detected and recorded. In (a) the results of the Library F and Library G cell-based ELISAs are shown.
Seventy-seven clones showed binding 1.5 times above background binding. All clones were sequenced
and in (b) the ELISA data for the three unique clones are shown.
Figure 6: RW03 Phage-Fab is specific to CD133 Overexpressing Cells. The three clones with unique
sequences obtained from the Library F cell-based ELISA were used in an immunofluorescence assay. The
C12 and F5 Phage-Fab clones are shown to bind to the HEK293 parental cell line non-specifically
whereas the RW03 clone binds to the HEK293-CD133 overexpressing line specifically with little
background binding to the HEK293 cell line.
3.2 Fab Rescue and Validation
The IF data prompted the purification of the RW03 fab for further testing. This was
accomplished by introducing the Fab sequence into an IPTG-inducible vector for protein
expression. Once purified, I tested the Fab for binding by cell based ELISA and found that the
purified Fab bound to the CD133 overexpressing cells ~8 fold greater than to the parental cells
28
(figure 7a). I also tested the RW03 Fab for binding to the CD133 overexpressing HEK293 cells,
the parental HEK293 cells and a CD133 overexpressing colon cancer cell line, Caco-2 by
immunofluorescence (figure 7b). I found that the RW03 Fab readily stained both the CD133
overexpressing line as well as Caco-2 cell line, with no staining of the parental HEK293 line
detected.
Figure 7: Purified RW03 binds to CD133 Expressing Cells. The RW03 Fab was purified and tested for
binding by (a) cell-based ELISA and (b) Immunofluorescence assays.
29
3.3 scFv rescue and IgG conversion
In addition to isolating binders from Library F, I also analyzed the Library G Illumina
sequencing data and chose fourteen scFvs to rescue (Appendix B) using the PCR-based rescue
strategy described above (section 2.3). The primers designated p1, p2 and p3 were specific to
each scFv rescued. Of the fourteen scFvs chosen for rescue, twelve were successfully rescued,
sequence verified and immediately cloned into vectors for IgG expression using the conversion
to IgG protocol described above (section 2.4). Of the twelve scFv sequences obtained, one IgG
(RW01) validated for binding to cells by flow cytometry analysis. Similarly, I converted the
RW03 Fab into an IgG and both RW01 as well as RW03 were tested in parallel.
3.4 IgG Validation
I began testing the RW01 and RW03 IgGs by obtaining an effective binding
concentration measurement (EC50) for each antibody. Due to the inability to obtain stable,
purified recombinant CD133 protein, I used flow cytometry to estimate the half maximal binding
concentration of each antibody on cells. I incubated CD133 overexpressing cells with serial
dilutions of each antibody, detected binding with an anti-human Fab’2 secondary antibody and fit
the data to a line of best fit using the Sigma Plot graphing program. Figure 8 shows the EC50
curve for RW01, which had a calculated EC50 of 2.5nM and the curve for RW03, which had a
calculated EC50 of 0.5 nM.
30
Figure 8: EC50 Measurements for RW01 IgG and RW03 IgG. Cells were incubated with stepwise
dilutions of either RW01 or RW03 IgG to determine a half-maximal binding curve for the antibodies.
Using the SigmaPlot graphing software the EC50 for RW01 (a) was calculated as 2.5 nM and the EC50 for
RW03 (b) was calculated as 0.5 nM.
Both IgGs were tested for binding to the cell surface by flow cytometry. The antibodies
were assessed for binding to CD133 overexpressing cells, Caco-2 cells, a cancer cell line shown
to highly express CD133, and a number of pancreatic cell lines that exhibit differing levels of
CD133 expression. The parental HEK293 cells were used as a negative control. As shown in
figure 9, both antibodies, at 5 µg/ml, bind CD133 expressing cells to varying degrees which may
be due to varying levels of expression of CD133 in the different cell lines. Interesting patterns of
staining are observed in the HPAC and PL45 populations, with the emergence of bimodal peaks
in these cell types. Broader peaks such as those observed for the engineered cell line HEK293-
CD133 are most likely a result of a heterogeneously expressing population of cells, contrasted
with the narrow peak observed with RWP-1 cells indicating a more homogeneously expressing
cell population.
31
Figure 9: RW01 and RW03 IgGs can Identify Endogenously Expressed CD133 by Flow Cytometry.
Either RW01 (Green trace) or RW03 (blue trace) was incubated on various cancer cell lines including a
number of pancreatic cell lines. Red traces indicate secondary only binding.
Both IgGs were tested for binding in an immunofluorescence assay to assess localization
of CD133 by IF. Figure 10a and b show the results of RW01 and RW03 binding to CD133
overexpressing cells and parental HEK293 cells which were used as a negative control. The
assay was repeated with Caco-2 cells to assess the capacity of the IgGs to induce internalization
of CD133 by permeabilizing and co-staining the cells with transferrin, an endosomal marker. As
shown in figure 10c, after a 30-minute incubation period to allow for internalization, there was
32
very little colocalization of transferrin with RW03 and RW01 IgGs. This may be a result of an
insufficient internalization period, as the internalization of AC133 was detected after 72 hours
(Rappa et al., 2008).
Figure 10: RW01 and RW03 IgGs can localize CD133 by Immunofluorescence. IgGs were tested for
binding by Immunofluorescence to (a) HEK293 parental cells (b) HEK293-CD133 cells and (c) Caco-2
cells. The IgGs were incubated on Caco-2 cells at 37°C for 30 minutes to allow internalization and
costained with transferrin, an endosomal vesicle marker. Nuclei are stained in Blue and an anti-human
APC-conjugated or 647-conjugated secondary antibody was used. Transferrin staining is shown in green.
3.5 IgG Applications
I tested the RW01 and RW03 IgGs for their application in various molecular assays. The
ability of the antibodies to be used for detection of CD133 by flow cytometry was previously
demonstrated in figure 8, when I used the antibodies to determine EC50 measurements and in
figure 9, as they were able to bind CD133 expressed by various cancer cell lines.
33
Another assay widely used in molecular biology is western blotting, in which proteins are
denatured and run on a gel in order to separate them based on molecular weight. As a
consequence of the selection process, the IgGs were enriched for binding to CD133 in its native
conformation. Therefore, I assessed the ability of the IgGs to detect the protein in a denatured
configuration. The IgGs were used as primary antibodies to detect CD133 from whole cell
lysates of CD133 overexpressing HEK293 cells, Caco-2 cells and the parental HEK293 cells as a
negative control. Figure 11 shows that both IgGs were able to detect CD133 in the two highly
expressing lines, while no CD133 was detected in the HEK293 negative control cell line.
Additionally, both IgGs were used in an immunoprecipitation coupled to Mass Spectrometry (IP-
MS) assay to assess whether the antibodies could pull down CD133 in this context. Appendix C
shows an excerpt from the IP-MS data in which both IgGs were able to pull down CD133 as
demonstrated by the high number of spectral counts for peptides composing the Prominin-1
protein. This preliminary data will be repeated to confirm the results. Additionally, replicates can
be compared to identify true binding partners of CD133 and eliminate ubiquitously expressed
“sticky” proteins that appear in the output. In addition, a comparison of the lists of proteins
pulled down by the two IgGs may distinguish differing functional epitopes bound by the two
antibodies and further shed light onto a functional distinction between epitopes of the protein.
Figure 11: RW01 and RW03 can be used in Western Blotting. The IgGs were tested for their ability to
bind the denatured form of CD133 by western blot. Whole cell lysates of HEK293, HEK293-CD133 and
Caco-2 cells were probed with RW01 and RW03 and binding was detected with an anti-human HRP-
conjugated secondary antibody. Beta-actin was used as a loading control.
34
3.6 Epitopes
When developing tools to study a protein, it is crucial to note that protein domains and
epitopes can have important functional implications. In addition, while protein sequences can
vary greatly from protein to protein, antibodies with similar amino acid side chains can bind
similar epitopes. In order to determine whether the RW01 and RW03 IgGs bound similar
epitopes on the CD133 protein, I co-stained CD133 over expressing cells with the antibodies,
initially incubating the cells with a saturating concentration (25 nM) of one antibody and adding
the second antibody in serial dilutions. The results for each antibody can be seen in figure 12 and
indicate that RW01 can bind the cells in the presence of saturating RW03 and RW03 can bind in
the presence of saturating RW01. The ability of each antibody to bind in the presence of
saturating concentrations of the other indicates that the antibodies bind different epitopes of
CD133. This can also be inferred from the CDR L3 and H3 sequences that have very different
side chain composition. This has implications for the effect each antibody may have on the
function of the protein.
35
Figure 12: RW01 and RW03 bind separate epitopes on CD133. RW01 and RW03 were tested for
binding to CD133 in a competitive flow cytometry experiment. In (a) cells were incubated with stepwise
dilutions of RW01 (blue trace) or RW01 in the presence of RW03 (red trace). Similarly, in (b) cells were
incubated stepwise with dilutions of RW03 (blue trace) or RW03 in the presence of RW01 (red trace).
3.7 Functional data
Although CD133 is mainly used as a marker of tumor initiating cells, the functional role
of the protein in maintaining this primitive phenotype has yet to be elucidated. Mak et al. used
shRNA to show that CD133 function may be linked to regulation of β-catenin in the Wnt
signaling pathway (Mak, Nixon, & Moffat, 2012a). To investigate the effect that the RW01 and
RW03 IgGs had on stability of CD133 in vitro, I incubated Caco-2 cells with either RW01 or
RW03 IgGs for 24 hours, harvested the cells and made whole cell lysates to evaluate the status of
36
CD133 by western blot. I included an anti-human (H+L) antibody (Jackson Immunoreseach)
treated condition and an untreated condition as controls and CD133 status was assessed with the
AC133 antibody (Miltenyi Biotec). As figure 13 shows, after a 24-hour incubation with the
RW01 and RW03 IgGs, CD133 protein levels are- significantly decreased in Caco-2 cells as
compared with the untreated and anti-human control treatments. To assess the effect of the
observed CD133 destabilization on Wnt signaling in the cells, I also probed for β-catenin,
however there were no observed differences on β-catenin protein stability between control and
IgG treated samples. Due to the observed loss of AC133 reactivity upon Caco-2 differentiation
(Marzesco, 2005), it is possible that treatment with the RW01 and RW03 IgGs may be inducing
differentiation in the cells rather than having an affect on a proliferative signaling pathway. This
will be examined in future studies.
Mak et al. have also demonstrated through shRNA knockdown of CD133 that the protein
is essential in an AML cell line, SEM-k2 (Mak et al., 2011). In order to investigate the effect of
the RW01 and RW03 IgGs on protein stability and cell viability in SEM cells, I performed a time
course in which SEM cells were treated with 5ug/ml of either RW01 or RW03 everyday for 7
days. The cells were then stained with AC133 conjugated to APC as well as SYTOX green and
Annexin-V to assess CD133 status at the cell surface as well as stage of apoptosis, respectively.
In apoptotic cells phosphatidylserine, which is normally located on the cytoplasmic side of the
cell membrane, translocates to the outer leaf of the plasma membrane (van Engeland, Nieland,
Ramaekers, Schutte, & Reutelingsperger, 1998). This allows Annexin V, a phospholipid-binding
protein with high affinity for phosphatidylserine, to label and identify apoptotic cells (Koopman
et al., 1994). The SYTOX Green dye is impermeable to live and apoptotic cells, but binds to
nucleic acids of dead cells, staining them an intense green. Figure 14 shows the results for days
1, 3 and 7 of the time course (all time points analyzed are presented in Appendix D). As seen in
Figure 14a, the anti-human IgG treatments did not have an effect on CD133 status or cell
viability. RW03 had a profound effect on CD133 by reducing detection of the protein by AC133.
RW01 appears to have an effect on CD133 stability, although not as dramatic as RW03. In
addition, there is a population of cells that retain the expression of CD133 but can be categorized
as undergoing apoptosis. This population however diminishes over time. The staining patterns of
these antibodies are very different from those seen for knockdown of CD133 with shRNA
(Figure 15b). However, the shProm1-1 hairpin was more effective than that of the shProm1-2,
37
and the significance of the level of cell death caused by the shProm1-1 will have to be re-
evaluated especially in light of the high level of cell death in the uninfected sample at Day 7 (See
appendix D).
Figure 13. RW01 and RW03 IgGs reduce CD133 in Caco-2 cells after 24-hours. IgGs were incubated
on Caco-2 cells for 24-hours at 37°C. Whole cell lysates were made and CD133 and beta-catenin levels
were assessed. GAPDH was used as a loading control.
38
39
Figure 14: RW01 and RW03 IgGs destabilize surface CD133 in SEM cells. (a) IgGs were tested for
their effect on SEM cells in a time course experiment. Cells were incubated with 5ug/ml IgG everyday for
7 days. CD133 status at the surface and apoptosis/cell death were assessed at the time points indicated. (b)
Cells were infected with shRNA against CD133 and CD133 as well as apoptosis/cell death were assessed
at day 7 as controls. APC on the x-axis indicates level of AC133 staining. Alexa-488 on the y-axis
indicates level of Annexin V (low) or SYTOX Green (high) staining.
40
Chapter 4
Summary and Future Directions 4
4.1 Summary
By employing the Cellectseq method, I was able to develop specific, high affinity
antibodies against the CD133 protein while in its native conformation. The antibodies were
isolated from two different phage-display libraries, which displayed different types of antibody
fragments and were engineered with different degrees of variation in the complementarity
determining regions.
The RW03 antibody was selected from a phage-Fab library, Library F with four of the six
CDRs diversified. RW03 was rescued through a small-scale approach and cloned first into a Fab
expression vector and subsequently into vectors for IgG expression. The Fab form of RW03 was
tested for binding by immunofluorescence as well as by flow cytometry and was able to detect
CD133 expression in both cases. Similarly, the IgG form of RW03 was tested by IF and flow
cytometry, demonstrating the ability of the IgG to detect CD133 in both assays. The applications
of the antibody were extended to western blotting and IP-MS, where the RW03 antibody was
able to detect the denatured form of CD133 and able to pull down the protein from whole cell
lysates. Moreover, I demonstrated the ability of the RW03 IgG to induce the turnover of the
protein in Caco-2 cells after a 24-hour incubation period and I was able to test the effectiveness
of the IgG over a longer time period through a time course experiment involving SEM-k2 cells.
While effectively decreasing the surface level of CD133 as assessed by AC133, RW03 treatment
resulted in 8-10% cell death by 24-hours post-incubation. Lastly, I demonstrated that the RW03
antibody has an EC50 of 0.5 nM and that it binds to an epitope different from the other antibody
developed, RW01.
The RW01 antibody was developed in a similar manner to the RW03 antibody with a few
very distinct differences. The RW01 antibody was selected from Library G, a phage-scFv library
in which all six CDRs were diversified. The antibody was rescued using a PCR-based strategy
from the round four output pool using the Illumina sequencing data obtained through the
Cellectseq protocol. The RW01 antibody was specifically isolated and cloned directly into
vectors for IgG expression. In parallel with the RW03 antibody, the RW01 IgG was tested by IF
41
and flow cytometry and found to successfully detect CD133 in both assays. The antibody was
also tested by western blot as well as IP-MS and found to detect the denatured form of CD133 as
well as complex with CD133 peptides in whole cell lysates. The RW01 antibody was also found
to induce a heightened rate of turnover of CD133 upon incubation of Caco-2 cells with the IgG
for 24 hours. Finally, when tested over a longer period of time in a time course to assess the
effect of the antibody on viability of CD133 in SEM-k2 cells, the RW01 antibody was shown to
be slow to knockdown CD133 but have an early effect on cell viability.
The development of the RW01 and RW03 human IgGs against the CD133 protein
represents another step in our ability to identify the function and molecular mechanisms of
CD133. These already “humanized” synthetic antibodies will have lower immunogenicity in vivo
and later in clinic if shown to be as effective as the AC133 antibody. Now that the antibodies
have been isolated, expressed and validated for binding to CD133, there are a number of
experiments that can be used to expand our understanding of CD133 function.
4.2 Future Directions
As mentioned previously, the epitopes targeted on a protein are paramount in the
investigation of protein function as well as the assessment of the therapeutic value of the protein.
From this study, the IgGs developed have been shown to bind distinct separate epitopes on the
protein, although those epitopes remain unknown. There are a number of methods that can be
employed to determine these epitopes. One such method involves using a peptide phage display
library to perform selections on the IgGs and once the peptide sequences that bind the IgGs have
been confirmed, they can be aligned with the CD133 protein sequence to determine potential
epitopes bound by the antibodies. Another method that can be used is to make tagged truncation
mutants of the protein, specifically truncations of the extracellular loops. These mutants can be
expressed in cells and their expression can be confirmed by western blot or by flow cytometry
using an antibody against the tag. Following confirmation of the expression of the mutants, the
RW01 and RW03 antibodies can be tested for binding to these mutants by western blotting or by
flow cytometry as both antibodies are able to detect CD133 by both of these molecular
techniques.
42
In addition to the finding that the IgGs bind separate epitopes on CD133, the ability of
both antibodies to induce a dramatic reduction of the protein was an intriguing result and lead to
a number of other questions that include whether the IgGs are causing an internalization of the
protein through the endocytic pathway or whether the protein is being reduced in other ways.
Additionally, does this loss of CD133 result in a phenotypic change in the cells that can be
assessed in a tangible way? In order to answer these questions, several experiments can be
performed. First, if incubation with the IgGs is resulting in an internalization of the protein, what
compartment or compartments is the protein being targeted to? This can be resolved by using the
fluorophore-conjugated form of the IgGs and incubating cells at 37°C to promote internalization.
Live-cell imaging can then be used to track the cells as internalization progresses. The cells can
be co-incubated with antibodies against markers of early- and late-endocytic compartments such
as CD63 and transferrin or with markers of other organelles such as EBAG9 for the golgi (Wolf
et al., 2010). The cellular compartment(s) to which the antibodies are targeted could have major
implications for the use of the antibodies in a clinical/ therapeutic context.
Furthermore, it is known that CD133 is released into bodily fluids via external vesicles
termed exosomes (Florek et al., 2006; H. B. Huttner et al., 2008; Marzesco, 2005). This process
may also be induced by the RW01 and RW03 IgGs and this can be assessed by incubation of
Caco-2 cells (known to display membrane pearling) with the IgGs and using transmission
electron microscopy to evaluate whether these structures are present. Finally, it is known that
differentiation of Caco-2 cells results in a loss of AC133 immunoreactivity (Corbeil et al., 2000).
Due to the observation that AC133 detection diminished upon incubation with RW01 and RW03
but not with an irrelevant human IgG, it is possible that the IgGs are causing the cells to
differentiate. In order to assess this, lysates obtained from cells incubated with the IgGs for 24
hours can be probed for markers of epithelial differentiation such as MUC2, CK20 and FABP2,
or markers of enterocytic differentiation such as alkaline phosphatase (Mak, Nixon, Kittanakom,
Stewart, et al., 2012b). Upregulation of genes involved in colon specific differentiation including
sucrase isomaltase or glucose transporter 5 can also be investigated. Finally, as demonstrated by
Mak et al. (Mak, Nixon, Kittanakom, Stewart, et al., 2012b), loss of CD133 caused Caco-2 cells
to differentiate into cells resembling the colon brush border as demonstrated by upregulation of
alanyl aminopeptidase, mucin13 and myosin-1, therefore these genes can also be analyzed for
upregulation.
43
To a similar effect, the reported connection between knockdown of CD133 and increased
expression of wnt inhibitors (Mak, Nixon, Kittanakom, Stewart, et al., 2012b; Rappa et al., 2008)
can also be explored further. In Caco-2 cells, the cells used to interrogate the effect of 24-hour
incubation with the antibody on beta-catenin levels, there is a mutation in APC that results in
decreased degradation of beta-catenin. This mutation may effectively mask the true effect, if any,
that the antibodies may have with regards to an influence on beta-catenin/wnt signaling. Another
approach currently being optimized in the lab is the luciferase-based TopFlash assay in the
context of the TCF/LEF binding sites to investigate the effect of incubation with the antibodies
on the functional role beta-catenin plays in wnt signaling. One other approach to assess effects
on Wnt signaling would be to look for upregulation of Wnt inhibitors such as those discovered to
be upregulated with knockdown of CD133 by (Rappa et al., 2008) including DKK1.
Finally, the results of the IP-MS experiment are much more valuable than simply a
measure of the ability of the IgGs to interact with CD133. There were over 400 other protein hits
identified in the experiment and any one of those hits could be a participant in the ultimate
function of CD133. Additionally, as the experiment was performed with both IgGs, one can
compare the proteins pulled down by the two antibodies to investigate whether there is functional
relevance to the respective epitopes targeted by the proteins. This principal can also be extended
to other cell lines to investigate whether expression of the epitopes targeted by the IgGs is
important to the function of the protein in a particular cellular background.
In summary, two human IgGs against CD133 were isolated using a novel selection
method involving direct selections on cells coupled with deep sequencing. These antibodies are
able to identify the CD133 protein both on the cell surface as well as in various molecular
techniques. Finally, the antibodies have preliminarily been shown to effect stability of the protein
on live cells. Further testing of these antibodies will reveal the specific epitope they bind, which
organelles they are targeted to when internalized and whether they have an effect on cellular
differentiation or cellular viability. Regardless of the therapeutic potential of these antibodies,
they will have many applications towards furthering our knowledge about CD133 and its role in
cancer.
44
Appendices 5Appendix A: Library F Illumina Data
45
46
47
Appendix B: Library G Illumina Data
48
49
50
51
52
53
54
55
56
Appendix C: IP-MS Data
RW01 and RW03 IgGs can Immunoprecipitate CD133 Peptides. IgGs were tested for their ability to
precipitate CD133 by immunoprecipitation coupled to mass spectrometry. The samples were injected in
the following order in order to reduce carry over into experimental samples: Beads only 1, RW01-1,
Beads only 2, RW01-2, Beads only 3, RW03, Beads only 4, AC133. The total spectral counts for the
antibody treatments as well as control beads only treatments are shown. Color legend is shown with green
indicating the probability of positive identification of a peptide immunoprecipitated in a treatment.
57
Appendix D: SEM Time Course
58
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