GENERATION OF DNA APTAMERS FOR HEPATOCELLULAR CARCINOMA EXOSOMES
By
SENA CANSIZ
A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY
UNIVERSITY OF FLORIDA
2016
© 2016 Sena Cansiz
To my beloved parents Nevin & Mehmet and my better half Mert
“So long, and thanks for all the fish”
4
ACKNOWLEDGMENTS
This dissertation could not have been completed without the great support that I
have received from so many people over the years. I wish to offer my most heartfelt
thanks to the following people.
First and for most, I would like to gratefully and sincerely thank my advisor, Dr.
Weihong Tan for his support, encouragement, guidance and understanding. This path
was not easy, but he always tried to show me the right way of not only doing research
but the life itself. He is one of the most hard-working people that I have ever known and
this accounts for the fact that success does not come by luck, it only comes from hard
work. I am deeply indebted to him for his support and valuable guidance. I also want to
express my gratitude to Ms. Weijun Chen for being “the mother of the group” and for her
help in my molecular biology experiments. If she did not share the SW28 rotor with us,
exosome projects would have been just a dream.
I would also like to express my honest appreciation to my committee members,
for their support and constructive criticism. Dr. Polfer was always the first to respond to
my emails, and I really appreciate his cooperative manner. I learned a lot from Dr.
Fanucci’s questions, critics and feedbacks during my proposal, departmental seminar
and individual meetings. I admire her scientific thinking and consider myself lucky to
have her as my committee member. Similarly, Dr. Horenstein is one of the best scientist
whom I have ever met. There is no one time in seminars that she did not impress me
with the question she asked to the speaker. I don’t remember how many times that I
wished to be as a good scientist as she is. Finally, Dr. Schultz is the best committee
member and perhaps the advisor that one can ever ask. He was never without an idea
or a kind word, and I always appreciated both.
5
Special thanks go to Dr. Ben Smith and Ms. Lori Clark for helping me to deal with
administrative problems, to Dr. Jim Horwath for being the best and most colorful
teaching adviser and to Dr. Katherine Williams (magician of words) for making my
manuscript readable.
It would be unfair not to acknowledge Dr. Tahir Bayrac and Dr. Basri Gulbakan,
for their valuable mentoring. I could not be here without their help. I would also like to
thank to Dr. Meghan Altman for letting me be a part of her project and Dr. Kwame Sefah
for his valuable guidance. I wish, I had the opportunity to spend more time with them so
that I could learn more from them.
I owe a big gratitude to my “lab sisters”, Eliza, Xiangling, Carole and my “lab
brothers”: Liqin, Cheng, Sam for their valuable friendship, support and encouragement.
A special thanks go to all past and current members of Tan Family, especially to Dalia,
Dimitri, Diane, Ismail, Emir, Tao, Mingxu, Da, I-Ting, Stefanie, Weijia, Yanyue, Yuan
Wu, Kimberly, Yuan Liu, Yian, Sai, Shuo, Xigao, Liping, Juan, Dr. Jiang, Dr. Liu, Long,
Danny, Xiaoshu, Xiaowei and many others for their sincere friendship. I would also like
to thank to Dr. Gonca Yildirim, Dr. Nail Tanrioven and Eray Caliskan for their sincere
help.
Above all, I would like to acknowledge the tremendous sacrifices that my parents
made to keep me going. Words are not enough to express my gratitude to them, without
whom I could not make this far. I deeply appreciate their endless love and support.
Last but not least, I would like to thank my rock, my loving husband, Mert. He is
the best colleague, friend, and lover that one can ask and my biggest luck in this life.
6
His encouragement made me through many long nights of lab work and many stressful
days. I will be forever in his debt. Counting down the days until we reunite.
7
TABLE OF CONTENTS page
ACKNOWLEDGMENTS .................................................................................................. 4
LIST OF TABLES .......................................................................................................... 10
LIST OF FIGURES ........................................................................................................ 11
LIST OF ABBREVIATIONS ........................................................................................... 13
ABSTRACT ................................................................................................................... 15
CHAPTER
1 INTRODUCTION .................................................................................................... 17
Cancer .................................................................................................................... 17 Extracellular Vesicles: Message in a bottle ............................................................. 18
History .............................................................................................................. 19 Classification of Extracellular Vesicles ............................................................. 20
Exosomes ............................................................................................................... 21 Protein Composition of Exosomes ................................................................... 21 Biogenesis and Release of Exosomes ............................................................. 22
Aptamers ................................................................................................................ 24 SELEX .............................................................................................................. 24 Cell-SELEX ...................................................................................................... 25
Overview of Dissertation ......................................................................................... 26
2 ISOLATION AND CHARACTERIZATION OF EXOSOMES FROM DIFFERENT CELL LINES ........................................................................................................... 31
Background and Significance ................................................................................. 31 Materials and Methods............................................................................................ 32
General Materials ............................................................................................. 32 Cell Lines and Culturing ................................................................................... 32 Exosome Isolation from Cells ........................................................................... 32 Exosome Isolation from Whole Human Blood .................................................. 33 Nanoparticle-Tracking Analysis (NTA) ............................................................. 34 Western Blot Analysis ...................................................................................... 34 Exosome-Bead Attachment .............................................................................. 35 Flow Cytometer Analysis of Exosome Bound Beads ........................................ 35 Immunogold Labelling TEM .............................................................................. 36
Results and Discussion........................................................................................... 37 Exosome Isolation from Cell Culture Media and Blood: Ultracentrifugation
and Ultrafiltration ........................................................................................... 37
8
Size and Concentration Analysis of Particles by Nanoparticle-Tracking Assay ............................................................................................................ 38
Measuring the Protein Content of Exosomes Using the BCA Assay ................ 39 Flow Cytometric Detection of Exosomes .......................................................... 40
Concluding Remarks............................................................................................... 40
3 DEVELOPMENT OF EV-SELEX METHODOLOGY AND SELECTION OF DNA APTAMERS AGAINST HEPATOCELLULAR CARCINOMA EXOSOMES ............. 49
Background and Significance ................................................................................. 49 Materials and Methods............................................................................................ 51
General Materials ............................................................................................. 51 Synthesis and Purification of Six Nucleotides (GACTZP) Libraries .................. 51 Cell Culture and Buffers ................................................................................... 52 Exosome Extraction from Hep G2 Cells for Positive Selection ......................... 52 Exosome Isolation from Whole Human Blood for Negative Selection .............. 53 Exosome-Bead Attachment .............................................................................. 53 Detailed Experimental Flow of EV-SELEX ....................................................... 54
Incubation step ........................................................................................... 54 PCR cycle optimization and amplification step........................................... 55 Preparation of single-stranded DNA .......................................................... 55 Monitoring of the pool enrichment .............................................................. 56
Results .................................................................................................................... 57 EV-SELEX Method and Generation of DNA Aptamers against
Hepatocellular Carcinoma Exosomes ........................................................... 57 Deep sequencing of GACTZP DNA survivors using Next Generation
sequencing technology. ................................................................................ 59 Discussion and Conclusion ..................................................................................... 60
4 IDENTIFICATION OF DNA APTAMER ANALOGS IN GENOMIC DNA ................. 69
Introductory Remarks.............................................................................................. 69 Protein Tyrosine Kinase 7 ................................................................................ 69 Wnt Signaling ................................................................................................... 70
Background and Significance ................................................................................. 71 Results .................................................................................................................... 74
Sequence Similarity between Different Aptamers ............................................ 74 Competition Experiments ................................................................................. 75 BLAST of the Consensus Sequence against the Human Genome .................. 75 Investigation of the Interaction of PTK7 with DIXDC1b DNA ............................ 76
Discussion and Conclusion ..................................................................................... 77 Materials and Methods............................................................................................ 80
Buffers and Cell Culture ................................................................................... 80 DNA Sequences ............................................................................................... 81 Bioinformatics ................................................................................................... 81 Significance Simulations................................................................................... 82 Competition Assays .......................................................................................... 83
9
Western Blot ..................................................................................................... 83 Gel Shift Assay (EMSA) ................................................................................... 83
5 CONCLUSION AND FUTURE DIRECTIONS ......................................................... 92
Summary and Conclusion ....................................................................................... 92 Future Directions .................................................................................................... 93
APPENDIX
A COMPLEX TARGET SELEX DNA APTAMER DATABASE ................................... 95
B PREDICTED SECONDARY STRUCTURES OF PTK7 APTAMERS ................... 102
LIST OF REFERENCES ............................................................................................. 103
BIOGRAPHICAL SKETCH .......................................................................................... 113
10
LIST OF TABLES
Table page 3-1 Sequences used for EV-SELEX ......................................................................... 63
3-2 Summary of EV-SELEX process ........................................................................ 63
3-3 Compendium of the aptamer candidates selected by EV-SELEX. ..................... 64
4-1 PTK7 aptamer sequences with their identical nucleotides .................................. 85
4-2 BLAST hits 14/15nt identity for consensus sequence ......................................... 86
4-3 Aptamers share sequence similarity with DIXDC1b DNA sequence .................. 87
A-1 Complex Target SELEX DNA Aptamer Database .............................................. 96
11
LIST OF FIGURES
Figure page 1-1 Exocytosis of MVEs releases exosomes containing transferrin receptor ............ 27
1-2 Histogram of exosomal studies over the past 40 years ...................................... 28
1-3 Schematic for extracellular vesicle trafficking. .................................................... 29
1-4 Biogenesis of extracellular vesicles and their interactions with recipient cells. ... 30
2-1 Flow chart for the exosome purification procedure based on differential ultracentrifugation and ultrafiltration .................................................................... 41
2-2 BCA experiment schematic. ............................................................................... 42
2-3 Schematic of optical configuration used in NTA. ................................................ 43
2-4 Size distribution from NTA measurements ......................................................... 44
2-5 Characterization of exosome preparations from different cell lines or human whole blood by western blot ............................................................................... 45
2-6 Schematic of capture and fluorescent analysis of extracellular vesicles. ............ 46
2-7 Binding test of different Hep G2 aptamers with blood exosomes by flow cytometry ............................................................................................................ 47
2-8 Validation of isolated exosomes and interaction between aptamer LZH8 and HepG2 exosomes ............................................................................................... 48
3-1 Schematic of EV-SELEX with both positive and negative selections.................. 65
3-2 PCR applications of EV-SELEX .......................................................................... 66
3-3 Verification of the enrichment of the library in binding sequences after 6 rounds. ............................................................................................................... 67
3-4 Monitoring the progress of EV-SELEX using flow cytometer .............................. 68
4-1 Simplified schemes showing the main WNT pathways directed by specific WNT, Frizzled and WNT co-receptor interactions .............................................. 88
4-2 Competition studies between different aptamers for PTK7 ................................. 89
4-3 Interaction of PTK7 with DIXDC1b DNA. ............................................................ 90
12
4-4 Confocal immunocytochemistry image of HeLa cells co-stained for PTK7 with sgc8-TMR ........................................................................................................... 90
4-5 Electrophoretic mobility shift assay (EMSA) for the ds DNA surrounding the consensus region on DIXDC1b .......................................................................... 91
B-1 Predicted secondary structures for PTK7 aptamers. ........................................ 102
13
LIST OF ABBREVIATIONS
5’UTR 5’-untranslated region
AMA Ammonium hydroxide: methylamine 1:1
ATCC American Type Culture Collection
BB Binding Buffer
BLAST Basic local alignment search tool
bp Base pair
BSA Bovine serum albumin
CEM Human T-Cell Acute Lymphoblastic Leukemia cell line
CLUSTAL Multiple sequence alignment computer program
DBU 1,8-Diazabicyclo[5.4.0]undec-7-ene
DIXDC1 DIX domain containing 1 protein
DMEM Dulbecco’s modified eagle media
DNA Deoxyribonucleic acid
dsDNA Double-stranded DNA
ESPRIT Bioinformatics algorithm for sequence alignment
EVs Extracellular vesicles
HEK293 Human embryonic kidney cell line
HeLa Henrietta Lacks's cervical cancer cell line
HPLC High pressure liquid chromatography
HRP Horseradish peroxidase
kDa KiloDalton
MV Microvesicle
PCR Polymerase chain reaction
14
RNA Ribonucleic acid
SELEX Systematic Evolution of Ligands by EXponential enrichment
ssDNA Single stranded deoxyribonucleic acid
TEM Transmission Electron Microscopy
WB Washing buffer
15
Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy
GENERATION OF DNA APTAMERS FOR HEPATOCELLULAR CARCINOMA
EXOSOMES
By
Sena Cansiz
December 2016
Chair: Weihong Tan Major: Chemistry
Extracellular vesicles (EVs), which were first discovered more than thirty years
ago, are now attracting considerable interest due to their key role in intercellular
communication. They affect various physiological and pathological functions of recipient
cells by transferring their cargo composed of proteins, lipids and nucleic acids. There
are several types of vesicles, which are categorized according to their size and
functions. Among them, exosomes are the most abundantly studied one, due to many
reasons, such as acting as a messenger between cells and participating in different
cellular homeostatic pathways. In addition, the molecular contents of the exosomes that
are secreted into body fluids have proven to be highly specific and a precious
biomedical tool. In order to take advantage of their functions and develop a way of
detection, here we designed and performed the first extracellular vesicle SELEX (EV-
SELEX) to generate DNA aptamers against hepatocellular carcinoma exosomes with a
counter selection against human blood exosomes.
In the second part of this dissertation, the interaction of a membrane protein
PTK7 and genomic DNA was elaborated. Analysis of DNA aptamers, selected
independently against different target cells by whole cell-SELEX, identified 4 aptamers
16
with a common target protein, PTK7, by competition experiments. The 4 aptamers
share significant sequence identity to both strands of a DNA sequence in the 5’-
untranslated region for protein DIXDC1 Further analysis of the PTK7 aptamers and
DIXDC1 gene revealed more sequence identities (22 nucleotides total) which is a
unique occurrence in the human genome. In addition, western blot analysis of PTK7 in
different cellular compartments indicated a PTK7 accumulation in the nucleus.
Moreover, a gel shift assay proved the interaction between PTK7 and the DIXDC1
gene. Taken together, these findings indicate that these DNA aptamers may have an
analog in genomic DNA.
17
CHAPTER 1 INTRODUCTION
Cancer
By the end of 2016, it is estimated that about six hundred thousand Americans
and more than 6 million humans around the world will die of cancer. In the United
States, one in two men will develop cancer during their lifetime.1 A quarter of all
American deaths and about 15% of all deaths worldwide will be attributed to cancer.2
Looking at the bitter statistical data provided above, it would be fair to say cancer is a
major public health problem worldwide. In fact, cancer is not one disease but many
diseases, which share a fundamental feature: the abnormal growth of the cell. In
addition, cancer is a clonal disease, that is, nearly every known cancer originates from
one ancestral cell that, having acquired the capacity of limitless cell division and
survival. Indeed, Greaves and Maley have recently reviewed inherently Darwinian
character of cancer and discussed the fact that clonally evolving nature of the disease is
the primary reason for the failure of a universal therapeutic.3 Before 1980s, the cancer
therapy was largely depend on two fundamental vulnerabilities of cancer cells: originate
as a local disease before it becomes malignant and the rapid growth rate, which can be
targeted by chemotherapeutic drugs.4 Later on, more specific and effective treatment
methods were developed such as nanocarriers and molecules that can selectively
target tumours.5 Nonetheless, prevention and/or early diagnosis is yet the best cure. By
attacking precancer rather than cancer, progression can be prevented.6 As stated by Dr.
Sidney Farber in November 1967,
the greatest need we have today in the human cancer problem, except for a universal cure, is a method of detecting the presence of cancer before there are any clinical signs of symptoms.7
18
Extracellular Vesicles: Message in a Bottle
Cells do not live in isolation, indeed cell-to cell communication is crucial for all
multicellular organism. Their survival depends on receiving and processing information
from the outside environment, whether that information is related to the availability of
nutrients, changes in temperature or in light levels. There are different ways of basic cell
communication, such as through the secretion of soluble factors (e.g. hormones,
cytokines) 8,9, by direct interaction10,11 and release of membrane derived vesicles. In this
particular chapter, extracellular vesicles will be under the magnifying glass.
Extracellular vesicles (EVs) is a generic term that refers to all membrane vesicles
secreted in the extracellular space. Indeed, they are spherical membrane derived
particles with a diameter ranging from 10 nm up to 5 μm, which possess different
functions, biophysical properties and have different biogenesis routes.12–14 The power of
EVs is the ability to transfer information to another cell and thus influence the recipient
cell function. Like a message in a bottle, EV-assisted signaling can be transferred by
different biomolecule categories such as, protein, lipids, nucleic acids and the unique
package of this information provides the option of simultaneous delivery of multiple
different messengers even to sites far from the parent cell.15,16
Major improvements in the detection of EVs have been made recently (Figure 1-
2).17 Due to their contribution to health and disease, the clinical interest in EVs as
noninvasive biomarkers for diagnosis or prognosis is emerging. Also, EVs may have
several potential therapeutic applications, which are currently being explored. Before
going more into detail about their clinical usage, the history and biogenesis will be
discussed initially.
19
History
EVs were observed as procoagulant platelet-derived particles in normal plasma,
originally reported in 1946 by Chargaff and West18 and referred to as ‘‘platelet dust’’ by
Wolf in 1967.19 However, the story of exosome biogenesis and secretion begins with the
discovery of the lysosome by Christian De Duve et al in 1955.20 A membrane isolates
the lysosome's acidic environment, preventing its enzymes from harming the rest of the
cell. By using ultracentrifugation method, they were able to isolate lysosomes in cell
fractions, which later were imaged by electron microscopy.21 In the 1970-1980s,
separate independent EV observations included the release of plasma membrane
vesicles from rectal adenoma microvillus cells22, reports on virus-like particles in human
cell cultures and bovine serum and23 the detection of vesicles, later termed
prostasomes.24 In 1983, two papers were published within a week of each other, which
are contributing exosomes and exosome secretion as well as Endosome-Lysosome
Pathway. Harding et al, were able to show a novel mechanism for the loss of transferrin
receptors during maturation of reticulocytes.25 In their study, internalized AuTf particles
were located primarily and predominantly on the many small vesicles which were
observed within multivesicular bodies, and therefore these organelles are called
multivesicular endosomes (MVE) (Figure 1-1). In parallel, exosomes were discovered
when vesicles were isolated from sheep reticulocytes. These vesicles contain the
plasma membrane receptor transferrin, which is absent on mature erythrocytes,
suggesting that “vesicle externalization could be a mechanism for shedding of specific
membrane functions, which are known to decrease during maturation of reticulocytes to
erythrocytes”.26,27 More than a decade later, Raposo et al demonstrated that these
vesicles, now termed exosomes, isolated from Epstein-Barr virus transformed B
20
lymphocytes, were antigen-presenting and able to induce T-cell responses.28 In 2006-
2007, with the discovery that EVs contain RNA, including microRNA, EVs acquired
substantially renewed interest as mediators of cell-to-cell communication.29,30 Advancing
on these pioneering studies, EVs have been isolated from most cell types and biological
fluids such as saliva, urine, nasal and bronchial lavage fluid, amniotic fluid, breast milk,
plasma, serum and seminal fluid.31–35
Classification of Extracellular Vesicles
There are mainly three types of EVs: Apoptotic Bodies, Microvesicles
(Ectosomes) and Exosomes. They differ in terms of size, components and functions.
Although, apoptotic bodies comprise a type of extracellular vesicles, they originate from
apoptotic cells and are fragments of dying cells.36 The change of osmotic pressure
arising from the apoptosis mechanism leads to blebbing and release of apoptotic bodies
which can be engulfed by macrophages. The vesicles formed have a size of 1-5 μm and
the mechanism leading to their release is well-understood compared to that of
exosomes and microvesicles.37 Microvesicles (MV), on the other hand, are formed by
outward budding of the plasma membrane. They are defined as close lipid bilayer sacs
which contain information capable of influencing the environment such as tumor growth.
They are heterogeneous in shape and size (100-1000 nm).38 The release of MV is a
regulated mechanism induced by activation of cell surface receptors and increase in
intracellular Ca2+ concentration.39 In addition, the release rate is enhanced for tumor
cells in comparison to normal healthy cells. A third and most widely studied type of EVs
is exosomes, which is one of the main focus of this dissertation.
21
Exosomes
Exosomes, membranous vesicles of endocytic origin, are signaling organelles
secreted by normal and disease cells.40,41 Originally described three decades ago27,
exosomes contain a subproteome of the cells and are found in many bodily fluids.
Released upon fusion of multivesicular bodies (MVBs) with the plasma membrane (PM),
exosomes are of 40–100 nm in diameter, are of endocytic origin, have a cup shaped
appearance as visioned by electron microscopy, have a buoyant density in sucrose of
1.10–1.21 g/mL and sediment at 100,000 g.42 They harbor proteins/RNA/lipids that
reflect the functionality of the host cell and possess molecular signatures or footprints
resembling the diseased cell from which they were secreted.40,43 There has been an
extensive research going on related with exosomes, especially in recent years. The
increasing trend in the number of researches, which are related with exosomes was
shown as a histogram in Figure 1-2. This enormous interest in exosomal studies can be
attributed to three main reasons: 1) Important role of exosomes in intercellular
signaling42; 2) use as delivery vehicles for vaccines and drugs41 and 3) as possible
sources of disease biomarkers44.
Protein Composition of Exosomes
The size of exosomes is related with their origin. Since they are indeed vesicles,
their minimum size is dependent on the structures of a lipid bilayer. A lipid bilayer has a
thickness of about 5 nm, and the bilayer has enough stiffness that the smallest vesicle
possible is on the range of 30 nm. Since they derive by budding off inside endosomes
(200–500 nm), their maximum diameter realistically should be on the order of 100 nm.
The implication of this small size is that the “cargo hold” for these particles is on the
order of 20–90 nm across. This is comparable to the volume of a eukaryotic ribosome,
22
so the total cargo per exosome is probably ≤100 proteins and ≤10,000 net nucleotides
of nucleic acid.45 Standard negative staining methods for transmission electron
microscopy (TEM) allow visualization of round vesicles with obvious lipid bilayers as
well as some bodies with a characteristic cup-shaped morphology.46 Besides a
characteristic morphology, exosomes are thought to be somewhat unique in their
protein and lipid composition, providing additional traits for their identification. Due to
their endosomal origin, all exosomes contain membrane transport and fusion proteins
(GTPases, Annexins, flotillin), tetraspannins (CD9, CD63, CD81, CD82)47,48, heat shock
proteins (Hsc70, Hsp 90)36,49, proteins involved in multivesicular body biogenesis (Alix,
TSG101)48,50, as well as lipid-related proteins and phospholipases.51 Beyond these
membrane-associated proteins, over 4400 different proteins have been identified in
association with exosomes, usually by mass spectrometry, presumably serving as cargo
for inter-cell communication.52
Biogenesis and Release of Exosomes
Exosomes are formed within the endosomal network, a membranous
compartment that sorts the various intraluminal vesicles and directs them to their
appropriate destinations, including lysosomes and cell surface membranes. In doing so,
endosomes target some proteins/lipids for lysosomal degradation while targeting others
for recycling or exocytosis.53 The machinery that drives MVB formation is directly
relevant to exosome production. A model for MVB formation was proposed more than
30 years ago.41 Two sequential steps have been discerned for protein sorting in MVBs.
The first step involves the lateral segregation or selection of proteins at the limiting
membrane. The second step is the formation of inwardly budding vesicles with the
concomitant incorporation of selected cargo. Only recently, a few aspects of the
23
responsible molecular mechanisms have been uncovered. In yeast, at least 15 class
EVPS genes are required for protein sorting into MVBs and these have orthologs in
mammalian cells, indicating that the molecular mechanism for MVB sorting was
conserved during evolution. Lipid metabolism appears to be important for the
biogenesis of MVBs. The MVB pathway in yeast and mammalian cells requires
phosphatidyl-inositol (PI) 3-kinase as well as PI (3)P 5- kinase activities , but the precise
roles of their reaction products, PI(3)P and PI(3,5)P2, for this process remain to be
established. Interference with the mammalian PI 3-kinase VPS34 did not affect the
sorting of EGF-receptor into aggregates at the MVB-limiting membrane, but did prevent
the formation of internal vesicles. A number of protein complexes have recently been
shown to be important for the biogenesis of MVBs. Hrs is a PI (3)Pbinding protein, and
disruption of Hrs expression results in aberrant MVB formation. Hrs has been
demonstrated to recruit clathrin to endosomes and to be important for EGFreceptor
down-regulation. Both activated EGF-receptor and Hrs associate with flat clathrin
lattices on vacuolar maturing endosomes, suggesting a role for such clathrin lattices in
the assembly of proteins for packaging in MVB internal vesicles. In addition, Hrs
interacts with sorting nexin 1 (SNX1), and this interaction is equally important for the
down-regulation of EGF receptor in MVBs. Furthermore, EGF-receptor sorting in MVBs
is dependent on c-Cbl, a ubiquitin ligase for EGF-receptor. Also in yeast, ubiquitination
of endosomal cargo serves as a signal for sorting in MVBs. Here, a hetero-oligomeric
protein complex, ESCRT-1, has been identified that contains the yeast ortholog of
mammalian Tsg101, Vps23. ESCRT-1 is thought to recruit ubiquitinated proteins for
MVB sorting through a direct interaction with VPS23. Apparently, all components that
24
are required to recruit proteins into the MVB pathway, including ubiquitin, ESCRT-1 and
the clathrin coat, are released from assembled cargo prior to the actual packaging into
inwardly budding vesicles at the MVB-limiting membrane. A schematic for the
biogenesis of exosomes was presented on Figure1-4.54
Aptamers
Aptamers are single-stranded oligonucleotides (RNA/DNA) which fold into well-
defined three-dimensional structure for specific recognition and interaction with their
target.55 The name “aptamer”, which originates from the Latin word “aptus” meaning “to
fit” and the Greek word “meros” meaning “part”, was used in 1990 by Ellington and
Szostak in their initial work selecting an RNA aptamer recognizing an organic dye.56 In
the same year, Gold and Tuerk selected an RNA aptamer recognizing bacteriophage T4
DNA polymerase and named the selection process SELEX, short for Systematic
Evolution of Ligands by EXponential enrichment.57 Still in the same year, Robertson and
Joyce adapted a class I ribozyme so that it would specifically cleave DNA instead of
ssRNA.58 In these papers, they independently introduced the concept of in vitro
selection of RNA molecules able to specifically recognize a target. Since then, DNA
aptamers have emerged and many RNA and DNA aptamers have been generated
towards many targets including, small organic molecules metal ions, proteins,
carbohydrates, toxins, and transcription factors, as well as whole cells, viruses, bacteria,
and as inhibitors of protein functions.
SELEX
The SELEX process has four major steps: 1) incubation of a library composed of
thousands of different oligonucleotide sequences with the target; 2) separation of the
bound sequences from the unbound sequences; 3) recovery of the bound sequences by
25
dissociation from the target; 4) amplification of the recovered sequences by polymerase
chain reaction (PCR).57
These steps are repeated until enrichment of the library in
binding sequences is attained. At this point, the pool containing the enriched sequence
is sequenced and further analyzed by informatics. The binding sequences are aptamers
which can be further shortened and modified to be more resistant to nuclease
degradation, to make them fluorescent or to carry a tag molecule for further coupling
with yet another molecule. One of the major limitations of the SELEX process is the
uncertainty of the success of the selection a priori. It is impossible to predict with
certainty the generation of an aptamer against the target chosen, this being even truer if
the target is a protein. Since aptamers are negatively charged due to their phosphate
backbones, it would appear that positively charged proteins at physiological pH should
be the best candidates. However, some aptamers have been successfully generated
against protein having isoelectric points below 7.4.59 Cell-SELEX
To select aptamers for whole cells, a negative control is usually included either
as a normal cell line or different cancer cell line. Cell-SELEX begins with the binding
event between the initially synthesized library and the target cells, unbound and weakly-
bound sequences are washed off. Bound sequences are collected and (if negative
selection is to be performed) are incubated with the negative cells. This time the,
unbound sequences are collected and further PCR amplified. Then, dsDNA is converted
to ssDNA and a new round starts. This process is continued until the initial library is
enriched with sequences that bind to the cancer cell but no to the control cell.60 Once
26
enrichment has been achieved, the pool is sequenced and analyzed using alignment
programs to identify conserved sequences.61
Overview of Dissertation
The research data presented in the first part of this dissertation demonstrate how
to select DNA aptamers against hepatocellular carcinoma exosomes. It includes how to
characterize exosomes and how to develop a method to select aptamers. Chapter 2
describes the characterization process and Chapter 3 focuses on selection process.
The second part of the dissertation, Chapter 4, focuses on a study related with PTK7
aptamer and it is discovery among the genome. The concluding chapter recapitulates
the significance of developing a new SELEX technology and the importance of
screening downstream effects of aptamers.
27
Figure 1-1. Exocytosis of MVEs releases exosomes containing transferrin receptor. A)
Small vesicles and tubules in the reticulocyte cytoplasm are labeled with AuTf. Bar 200nm B) View of an MVE in a reticulocyte that was incubated with AuTf.Bar 100nm. C) View of an MVE sparsely labeled with AuTf. Bar 100nm. D) View of MVE exocytosis in an unfixed reticulocyte. Bar 200nm E) Exocytosis of a small AuTf-labeled MVE. Bar 100nm F) An adherent membrane vesicle with associated AuTf. This presumably represents the remnant of an MVE exocytosis. Bar 100nm. Figure and legend adapted from Harding et al. (1983)25. Used under the permission of Rockefeller University Press.
28
Figure 1-2. Histogram of exosomal studies over the past 40 years. An increasing interest in exosome research was seen during the last decade. The statistics is generated based on PubMed indexed exosomal studies (keywords: exosomes or exosome-like).
29
Figure 1-3. Schematic for extracellular vesicle trafficking.
30
Figure 1-4 Biogenesis of extracellular vesicles and their interactions with recipient cells. Figure adapted from reference EL Andoloussi et al.54
31
CHAPTER 2 ISOLATION AND CHARACTERIZATION OF EXOSOMES FROM DIFFERENT CELL
LINES
Background and Significance
As it was explained in the introductory chapter, extracellular vesicles hold a great
importance in terms of cell-to-cell communication, intercellular signaling, waste
management, coagulation, etc. They are largely released in biological fluids, such as
plasma, urine, cerebrospinal fluid, amniotic fluid, malignant and pleural effusions of
ascites and breast milk, hinting a diverse role in the exchange of information among
different body compartments. 32,62,63 In addition, it has been showed that in particular
disease conditions, exosomes may play regulatory functions. There are a number of
evidences indicating the relationship between exosomes and some neurodegenerative
disease such as prion, Alzheimer’s and Parkinson’s disease. It was found out that
exosomes are carrying some neurodegenerative disease associated proteins such as β-
amyloid and α-synuclein and they facilitate their spread from their cells of origin to the
extracellular environment.64 For example, β-amyloid peptides, associated with
Alzheimer's disease, are carried with exosomes and that exosomal proteins were found
to accumulate in the plaques of AD patients’ brains.65 Moreover, in a research done by
Fevrier et al prion proteins are shown to be released from cells in association with
exosomes and travelling in the body as an infectious route for propagation of disease.66
Consequently, there is a growing interest in the clinical applications of vesicles.
However, because of the small size and heterogeneity of vesicles, their isolation and
detection is challenging. Currently, there is no one single method which can accurately
phenotype, size, and detect the concentration of the whole range of EVs and therefore
provide all the necessary information to understand the biology of extracellular vesicles.
32
In this particular chapter, we will discuss about the isolation and characterization of
exosomes from different human primary cell lines including Hep G2, HeLa, CEM,
Ramos and whole blood. This can be considerate as a preliminary step for the EV-
SELEX, which will be discussed in Chapter 3.
Materials and Methods
General Materials
Unless specified otherwise, all the reagents were purchased either from Thermo-
Fisher or Sigma Aldrich and used without further purification. All DNA synthesis
reagents were purchased from Glen Research.
Cell Lines and Culturing
All the cell lines used either for exosome collection or general binding
experiments were purchased from American Tissue Culture Collection (ATCC). Ramos
cells (CRL-1596, B lymphocyte, human Burkitt's lymphoma) were grown in complete
RPMI 1640 medium (Sigma) supplemented with 10% (v/v) fetal bovine serum (FBS)
(heat inactivated, GIBCO) and 100 IU/mL penicillin-streptomycin (PS) (Cellgro). HeLa
cells (cervical adenocarcinoma (CCL-2)) were grown in Dulbecco’s Modified Eagle’s
Medium (DMEM) supplemented with sodium bicarbonate (1.5g/L), 10% (v/v) FBS and
100 IU/mL PS. Hep G2 cells (CRL-11997, human liver hepatocellular carcinoma) were
grown in Eagle’s Minimum Essential Media (EMEM) supplemented with sodium
bicarbonate (1.5g/L), 10% (v/v) FBS and 100 IU/mL PS. All cell lines were sub-cultured
in either T-75 flasks (Corning) or in 35 mm cell culture dishes at 37°C with 5% CO2.
Exosome Isolation from Cells
Exosomes were obtained from supernatant of cells, which are cultured as
previously described. In order to collect a higher number of exosomes, cells were grown
33
in T-225 cm2 flasks (Corning) in complete growth media until they reached a confluency
of 80–90%. Then, the media was discarded and the cell, which are still attached to the
flask were washed with 10mM PBS. Following the washing step, the cells were cultured
in complete growth media, which is supplemented with 10% v/v exosome depleted FBS
(Thermo Fisher Scientific) rather than the regular FBS for 48h. Next, the media was
collected and centrifuged at 800g for 5 min to discard the cells, followed by a
centrifugation step of 2,000g for 10 min to discard cellular debris. Then, the media was
filtered using a 0.2-μm pore filter (Grainger, 11L832). The collected media (~200mL)
was then split in 6 UltraClear™ thinwall tubes (Beckman Coulter, 342204) and
ultracentrifuged at 100,000g for 2h at 4 °C with SW28 Ti rotor. The exosome pellet in
each tube was washed with 6 mL 10mM PBS, collected in a single tube and filtered
using 0.2-μm pore filter (syringe filter, 6786-1302, GE Healthcare), followed by a second
step of ultracentrifugation at 100,000g for 2h at 4 °C. Finally, the supernatant was
discarded carefully and the pellet is resuspended in 150 μL 10mM PBS and stored at -
80 °C. The schematic representation of the isolation process is summarized in Figure 2-
1.
Exosome Isolation from Whole Human Blood
Whole Human Blood was purchased from Life South (1 unit, R259). Upon arrival,
the whole blood was split in 50mL of Falcon Tubes and centrifuged at 1,500 x g for 20
min at 4 °C to initiate separation of cells from plasma. Next, the supernatant (plasma)
was transferred in to a new Falcon Tube and centrifuged at 2,800 x g for 20 min at 4 °C
twice to remove all cells from plasma. Then, cell-free plasma (CFP) was filtered using a
0.2-μm pore filter (Grainger, 11L832). The CFP (~250mL) was then split in 6
UltraClear™ thinwall tubes (Beckman Coulter, 342204) and ultracentrifuged at
34
100,000g for 2h at 4 °C with SW28 Ti rotor. The exosome pellet in each tube was
washed with 6 mL 10mM PBS, collected in a single tube and filtered using 0.2-μm pore
filter (syringe filter, 6786-1302, GE Healthcare), followed by a second step of
ultracentrifugation at 100,000g for 2h at 4°C. Finally, the supernatant was discarded
carefully and the pellet is resuspended in 500 μL 10mM PBS and stored at -80 °C.
Nanoparticle-Tracking Analysis (NTA)
NTA measurements were performed with a NanoSight LM20, equipped with a
sample chamber with a 640-nm laser and a Viton fluoroelastomer O-ring. The samples
were diluted in 10mM PBS with either 1:10 or 1:100 ratio depending on the initial
concentration. The samples were then injected in the sample chamber with sterile Luer-
Lok syringes (BD) until the liquid reached the tip of the nozzle. All measurements were
performed at room temperature.
Western Blot Analysis
Exosome samples from different cell lines were lysed in Lysis 250 Buffer (50mM
Tris-HCl, pH 7.4, 0.5% NP-40, 250mM NaCl, 5mM EDTA, 50mM NaF) containing 5
μg/Ml leupeptin, 1 μg/mL pepstatin and 1 mM phenylmethylsulphonyl fluoride (PMSF).
Lysates were collected and centrifuged at 14,000 rpm for 15 min, and the supernatants
were collected. Protein quantification was determined by bicinchoninic acid (BCA)
Assay and the information related with standard curve and mean standard
concentrations summarized in Figure 2-2. Following this, 50 μg of protein from each
sample was boiled in 4X NuPAGE® LDS Sample Buffer (Thermo Fisher) at 95°C for 5
min. Proteins were resolved by 8% SDS-PAGE and then transferred to Polyvinilyidene
difluoride (PVDF) membrane by semi-dry transfer. The protein blot was blocked for 1 h
at room temperature with 5% non-fat dry milk in PBS/0,05% Tween and incubated
35
overnight at 4 °C with the following primary antibodies: Exosome CD63 (Thermo-
Fisher). In order to, remove the nonspecific and unbound antibodies, the blot was
washed with PBS 0.05% Tween-20 5 times for 8 min each. Next, horseradish
peroxidase (HRP)-conjugated secondary antibodies (GE Healthcare) were incubated for
1 h at room temperature. Washes after secondary antibody incubations were done on
an orbital shaker, 6 times at 8 min intervals, with PBS 0.05% Tween-20. Blots were
developed with chemiluminescent reagents from Pierce.
Exosome-Bead Attachment
10μL exosomes (1013 exosomes/mL) were mixed with 10 μL Aldehyde Sulfate
Latex (ASL) (Thermo Fisher Scientific) beads for 15 min at room temperature with
continuous rotation. This suspension was diluted to 1 ml with PBS and left for 30 min
rotating at room temperature. The reaction was stopped with stop solution (100 mM
glycine and 2% BSA in 10 mM PBS) and left rotating for 30 min at room temperature.
Exosomes-bound beads were washed once in 2% BSA in 10mM PBS and centrifuged
for 1 min at 14,800g and blocked with blocking solution (10% BSA, 0.1mg/mL salmon
sperm DNA in 10mM PBS) with rotation at room temperature for 30 min. Then the
beads were washed second time in 2% BSA and centrifuged for 1 min at 14,800 g.
Finally, the exosome-bound beads are recovered in 10mM PBS and stored at 4°C
temporarily.
Flow Cytometer Analysis of Exosome Bound Beads
Bead concentration is optimized for 10,000 events and 1.2 µg/mL of exosome-
bound beads were used as the optimum (minimum) concentration for all the binding
assays. Beads were centrifuged at 14,800g for 1 min in order to be recovered from the
storage solution and washed with bead-washing buffer (5mM MgCl2, 2% (w/v) BSA in
36
10mM PBS). Beads then mixed with 250nM of biotin labelled sequence to be analyzed
and incubated with rotation at 4°C for 30 min. Afterwards, the beads were washed in
bead-washing buffer and centrifuged at 14,800g for 1 min in order to remove the
unbound sequences. Next, the recovered beads were resuspended in streptavidin
conjugated R-phycoerythrin (SA-PE) (Thermo Fisher Scientific) in washing buffer with a
1:400 dilution rate and incubated with rotation for 15 min at 4°C. In order to remove
excess SA-PE, the beads were washed twice with bead-washing buffer and recovered
by centrifugation at 14,800g. Finally, washed exosome-bound beads were resuspended
in 100µL of bead-binding buffer. The fluorescence was analyzed using BD Accuri C6
flow cytometer (BD Biosciences) and the results were interpreted by FlowJo™ software.
Immunogold Labelling TEM
For the TEM observation of pure HepG2 exosomes, the optimal concentration of
the samples was directly absorbed on a f-carbon-coated copper grid and dried at room
temperature. For immunogold labeling samples, optimal concentration of HepG2
exosomes were placed onto grids and allowed to be absorbed. The grids were blocked
with 1% BSA/PBS for 1h, and then placed on biotin-labeled LZH8 aptamer solution for
1h at 4 °C, and rinsed with PBS for 5 times. After washing, grids were floated on drops
of streptavidin-gold nanoparticles for 30 min at 4 °C. Finally, the grids were rinsed with
10mM PBS for 5 times and dried at room temperature. As controls, grids were not
exposed to LZH8 aptamer. The dried sample was observed on a Hitachi H-7000 NAR
transmission electron microscope using a working voltage of 100 kV.
37
Results and Discussion
Exosome Isolation from Cell Culture Media and Blood: Ultracentrifugation and Ultrafiltration
A major problem in EV research is the lack of characterization of current methods
evaluating their usability, vesicle purity and yield from cell media, and complex
biological fluids such as whole blood.67,68 The current “gold standard” for the purification
of a subset of exosomes is differential centrifugation. Differential centrifugation consists
of successive centrifugation steps with increasing centrifugation forces and durations,
generally aimed at isolating smaller from larger objects. Larger particles, assigned to be
removed in the first centrifugation steps, sediment faster and leave most of the smaller
particles in the supernatant. The supernatant will be centrifuged in subsequent steps.69
Larger particles refer to cells and large vesicles which typically will be removed by low-
speed centrifugation and the supernatant contains smaller vesicles, such as exosomes,
which will be ultra-centrifuged to pellet. Even tough, separation of exosomes by
ultracentrifugation method is one of the most effectively and commonly used one, it still
needs to be further optimized or combined by different techniques. It has been
suggested in the literature that repeated ultracentrifugation steps can damage vesicles
and reduce yields, thereby potentially impacting proteomic and RNA analysis of
exosome content.70 Besides, the pellet collected might be contaminated by other types
of vesicles, rather than being a homogenous exosome population. In order to overcome
all these potential problems, we combined differential centrifugation method with several
ultrafiltration steps (Figure 2-1). According to the data that we collected from several
characterization steps, we can claim that exosomes constitutes majority of the vesicle
38
population but not the whole. Further immunoprecipitation steps might be necessary to
obtain more homogenous exosome extraction in the future.
Size and Concentration Analysis of Particles by Nanoparticle-Tracking Assay
One of the challenges with identifying the size and structure of exosomes is that
they are one of several extracellular nano/micro-scaled vesicles that are produced by
cells all the time and vary in size, molecular composition, and biological function.42,71
Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) are
one of the mainly used tools for the analysis of particle size and morphology of
exosomes.35,72 However, both SEM and TEM have the disadvantage that the
preparation of samples is time-consuming, both methods involve labor-intensive steps
and each has some risk of artifact generation. Neither method is suitable for high
sample throughput and characterization of thousands of single particles of one sample.
A highly sensitive method for visualization and analysis of exosomes is NTA.73 This
method takes advantage of two different principles of physics: First, particles are
detected by the light scattered when they are irradiated with a laser beam (Figure 2-3).
The second phenomenon is known as Brownian motion, according to which the
diffusion of different particles in a liquid suspension is inversely proportional to their
size.74 In the latter case, the movement also depends on the temperature and the
viscosity of the liquid. Using software-based analysis, digital images of scattered light
from single particles are recorded. Plots of scattered light spots and their speed of
motion provide the data that facilitate the determination of total particle count and size
distribution.
We used NTA in our experiments to determine size distribution and the
concentration of the collected exosomes. According to data we collected, size
39
distribution curves of the particles were constructed. Mean size for Hep G2 exosomes
was 77.35 nm whereas it is 88.95 (Figure 2-4) for whole blood exosomes. Even though
the mean size of the exosomes collected is within the range, there are still some particle
population which has a bigger size than an average exosome. Besides, despite the fact
that all particles having a size bigger than 220nm were eliminated by ultracentrifugation,
we observed particles around or more than 300nm. This is either a contamination or an
artifact of aggregated particles. Based on the information on the literature, this
technique is particularly powerful for analyzing particles with a mean diameter of less
than 100 nm, which is consistent with our results.
Measuring the Protein Content of Exosomes Using the BCA Assay
Measuring the amount of total proteins present in the exosome preparations
gives a rough idea of the number of exosomes secreted by the cells. When performing
immunoblots with exosomes and total cell lysates, or when comparing different
exosome preparations on the same immunoblot, it is important to perform the protein
quantification by the BCA or Bradford assay on all the samples at the same time.
According to the results that we got (Figure 2-2), the exosome lysates obtained from cell
culture media were able to measured easily and the value obtained stayed in the
standard range. On the other hand, in the case of blood exosome lysates, the protein
concentration was too high, even though the initial exosome concentration inside fair.
Clearly, the plasma contains too much protein contaminants which is interfering with
exosome protein content. For the future experiments, in order detect the concentration
of blood exosome lysate, the value obtained from NTA measurement might be used
instead of using BSA or Bradford Assays.
40
Flow Cytometric Detection of Exosomes
Standard Flow Cytometer detects vesicles above approximately 200 nm, and
therefore exosomes and smaller MVs cannot be analyzed directly by this method. Thus,
it has to be emphasized that MVs smaller than the detection limit of the used flow
cytometer cannot be discriminated from the instrument noise, leading to an inadequate
numbering of MVs.75, unless they are conjugated with beads. In our experiments, we
were targeting exosomes, which are between 40-100nm in size. Therefore, it is
impossible to detect them by flow cytometry, unless they conjugated with a bigger
material. In order to do so exosomes are attached to ASL beads as described in
experimental section (Figure 2-5). Further, the flow cytometry experiment was
performed with exosome-beads conjugates. Blood exosomes are tested with HepG2
aptamers which was recently selected76 and unfortunately we discovered that they all
bind to blood exosomes (Figure 2-6).
Concluding Remarks
There is an urgent need for more efficient, reliable and reproducible EVs
extraction methods, so that all downstream studies in the field of EVs can be more
standardized and efficient. Here in this chapter, we were able to perform a serious of
characterization experiments for the exosomes isolated from different cell lines. First,
the size and the concentration of the exosomes were detected by NTA. It is overall a
reliable method since the size of the exosomes are less than 100nm. Further, the
exosome lysates were subjected to western blot to confirm their CD 63 content. Flow
cytometer detection of ASL bead conjugates blood exosome beads reveled the fact that
all HepG2 aptamers have an affinity blood exosomes.
41
Figure 2-1. Flow chart for the exosome purification procedure based on differential ultracentrifugation and ultrafiltration. The speed and length of each centrifugation are indicated to the right of the arrows.
42
Figure 2-2. BCA experiment schematic. A) Schematic for the 96 plate design used for the experiment with unknowns and
standards labelled. B) Standard curve for the BSA. C) Mean absorbance and protein concentrations for exosome cell lysates extracted from different cell lines and whole human blood.
43
Figure 2-3. Schematic of optical configuration used in NTA. A laser beam is passed through the sample chamber, and the particles in suspension in the path of this beam scatter light in such a manner that they can easily be visualized via a 20x magnification microscope onto which is mounted a camera. The camera operates approximately at 30 frames per second (fps), captures a video file of the particles moving under Brownian motion.
44
Figure 2-4. Size distribution from NTA measurements of Hep G2 exosomes A) and whole human blood exosomes B) with the corresponding NTA video frame (left panels)
45
Figure 2-5. Characterization of exosome preparations from different cell lines or human
whole blood by Western blot. Common exosome marker anti-CD63 was used as the primary antibody.
46
Figure 2-6. Schematic of capture and fluorescent analysis of extracellular vesicles.
Extracellular vesicles are captured by ALS beads and tagged by biotin conjugated aptamers and then stained with streptavidin conjugated fluorophore. The beads are analyzed by flow cytometry.
47
Figure 2-7. Binding test of different Hep G2 aptamers with blood exosomes by flow cytometry. A random sequence
(library) indicated the background. Right panel shows the dot blot for the related experiment.
48
Figure 2-8. Validation of isolated exosomes and interaction between aptamer LZH8 and
HepG2 exosomes. A) TEM observation of purified exosomes. B) Immunogold labeling TEM observation showing that the SA-AuNP could be attached on exosome surface via conjugation with biotinylated aptamers. C) Flow cytometry verification of exosomes using anti-EpCAM antibody. Isotype antibody indicated the background. D) Binding test using aptamer LZH8 with flow cytometry. A random sequence indicated the background.
49
CHAPTER 3 DEVELOPMENT OF EV-SELEX METHODOLOGY AND SELECTION OF DNA
APTAMERS AGAINST HEPATOCELLULAR CARCINOMA EXOSOMES
Background and Significance
There are a number of evidences, which indicate the importance of EVs in a
variety of fundamental physiological and pathological processes.54,77,78 Among all, their
contribution to tumor growth and spread is the most striking one. The number of
circulating EVs in cancer patients is higher than in healthy individuals and has been
found to related with poor prognosis.79 In addition, a recent research suggests that,
exosomes may play a role in the distant spread, or metastasis, of cancer cells in the
body. Understanding this process could open new avenues of research on preventing
metastasis, which causes most deaths from cancer.80 The researchers found that
exosomes released from cancer cells had traveled to distant sites in the body and fused
with specific cells at these distant sites. These interactions made the local environments
suitable for the development of new tumors.81,82 In this regard, exosomes act as
communicative vehicles between tumor cells and the metastasis environment having
great potential as cancer biomarkers in personalized medicine for several reasons.
Firstly, exosomes travel across the body and can be collected from different body fluids
such as, serum, plasma, urine83 and breastmilk84 and thus eliminates the requirement
for invasive tissue biopsy. Secondly, exosomes carry cargos, which they are inherited
from their parent cells. Those cargoes in exosomes are protected by the phospholipid
bilayer from degradation by proteinases and nucleases. Consequently, biomarkers at a
relatively low expression are much easier to be detected through isolating exosomes.17
As described in the first chapter, aptamers are single-stranded oligonucleotides
capable of strong and specific binding to a target marker based on their unique three-
50
dimensional folding.55 They are often compared to antibodies, since they exhibit similar
recognition mechanisms, specificity and selectivity. Aptamers are selected from an
initially large oligonucleotide pool (1012-1015 sequences) by a process called Systematic
Evolution of Ligands by EXponential enrichment (SELEX).60 The mode of selection and
the methodology used to generate these aptamers, as well as all the assays used in the
identification of the potential aptamer candidates, depend to a large extent on the target
of interest. In view of this, various selection modes have emerged. For the last decade,
Tan Group is a pioneer in cell-SELEX. We generated many DNA aptamers by using this
methodology.85–90
Recently, we extended our cell-SELEX knowledge to artificial bases and
developed artificially expanded genetic information systems (AEGIS)-cell-SELEX
technology.76,91 First, Sefah et al demonstrated the first example of a successful AEGIS
cell-SELEX against an adenocarcinoma breast cancer cell line by using GACTZP
library. Then, Zhang et al applied the same technology to select an aptamer against
hepatocarcinoma cell line with an addition of counter selection. This indeed increased
the selectivity of the selected aptamer. Yet, in both cases, it has been shown that the
aptamers containing artificial bases bound to their target molecule with a higher affinity
than their natural DNA replicas.
Herein this project, we developed a novel SELEX methodology targeting
extracellular vesicles rather than cultured cells. To date, it is the first example of a
SELEX method targeting exosomes. Besides, we used AEGIS technology to make the
selection more powerful. Hepatocarcinoma liver cancer cell line, Hep G2, exosomes
were used as the target molecule and whole human blood exosomes used for the
51
counter selection. Two main goals of this study are firstly to develop the know-how
required for the EV-SELEX and secondly to generate DNA aptamers targeting a cancer
cell exosome in blood for clinical usage.
Materials and Methods
General Materials
Unless specified otherwise, all the reagents were purchased either from Thermo-
Fisher or Sigma Aldrich and used without further purification. All standard DNA
synthesis reagents were purchased from Glen Research.
Synthesis and Purification of Six Nucleotides (GACTZP) Libraries
All dZ and dP containing oligonucleotides (Table 3-1) were synthesized using
standard phosphoramidite chemistry on glass support (CPG) on an ABI 394 DNA
synthesizer. Protected dZ and dP phosphoramidites were purchased from Firebird
Biomolecular Sciences LLC (Alchua, FL). The primers were designed to satisfy the
following characteristics: a minimum hairpin structure, similar melting temperature (Tm)
and minimal base pairing. The forward primer (20nt) was labeled with Fluorescein
Isothiocyanate (FITC) at the 5’-end, and the reverse primer (20 nt) was labeled with
Biotin at the 5’-end. The library consisted of a randomized 30 nucleotide region
containing GACTZP at each site with a ratio 1:1:1:1:2:2, respectively. Coupling times
were 60 seconds. The CPG-bound DMT-off DNA molecules were incubated with
acetonitrile-triethylamine (1:1 v/v) for 1h at 25°C, followed by removal of supernatant.
The CPG-bound oligonucleotides were then incubated in acetonitrile-triethylamine (1:1
v/v) for overnight at 25°C. After removal of the supernatant, the CPG-bound
oligonucleotides were incubated with 1.0 mL of 1,8-Diazabicyclo[5.4.0]undec-7-ene
(DBU) in anhydrous CH3CN (1M) at room temperature for ~18 hours to remove the
52
protecting groups on dZ. After removal of CH3CN, dZ and dP containing
oligonucleotides were retreated with NH4OH overnight at 55°C. The product mixture
was resolved by denaturating PAGE (7M urea) and extracted with TEAA buffer (0.2, pH
7.0). The product was then desalted by Sep-Pac® Plus C18 cartridges. All 5’
biotinylated dZ and dP containing sequences were synthesized, deprotected and
purified in house based on the above methods.
Cell Culture and Buffers
Hep G2 (CRL-11997, human liver hepatocellular carcinoma) cell line used either
for exosome collection or general binding experiments was purchased from ATCC.
They were grown in Eagle’s Minimum Essential Media (EMEM) supplemented with
sodium bicarbonate (1.5g/L), 10% (v/v) FBS and 100 IU/mL PS and subcultured in
either T-182 cm2 flasks (Corning) or in 35 mm cell culture dishes at 37°C with 5% CO2.
Washing buffer was prepared by adding 5mM MgCl2 and 2% (w/v) BSA in 10mM PBS.
Similarly, 10X binding buffer was prepared by mixing 50mM MgCl2, 1 mg/mL tRNA and
10mg/mL BSA in 10mM PBS, where tRNA and BSA serves as the stringency factors in
order to decrease non-specific binding.
Exosome Extraction from Hep G2 Cells for Positive Selection
Exosomes were collected using conventional centrifugation from supernatant
media of HepG2 cells. Cells were harvested in T-182 cm2 flasks in exosomes-depleted
FBS supplemented DMEM until they reached a confluency of 80~ 90%. Media was
collected and centrifuged at 800 g for 5 min at 4 °C, and the supernatant was then
centrifuged at 2,000 g for 10 min at 4 °C to discard cellular debris, followed by filtration
using a 0.22 µm filter (vacuum-driven filter, Genesee Scientific). The filtered media was
then ultracentrifuged at 100,000 x g for 2h at 4 °C. Pellet was then washed with 35 mL
53
PBS, and centrifuged again at 100,000 x g for 2h at 4 °C. Finally, the supernatant was
discarded and exosomes were resuspended in 100 µL PBS. After several times
collection, the purity and concentration of exosomes was tested and measured by
NanoSight (NanoSight Ltd., Malvern). A stock solution of 1013 HepG2-derived
exosomes/mL was obtained.
Exosome Isolation from Whole Human Blood for Negative Selection
Whole Human Blood was purchased from Life South (1 unit, R259). Upon arrival,
the whole blood was split in several 50mL of Falcon tubes and centrifuged at 1,500 x g
for 20 min at 4 °C to initiate separation of cells from plasma. Next, the supernatant
(plasma) was transferred in to a new Falcon tube and centrifuged at 2,800 x g for 20
min at 4 °C twice in order to remove all cells from plasma. Then, cell-free plasma (CFP)
was filtered using a 0.2-μm pore filter (Grainger, 11L832). The CFP (~250mL) was then
split in 6 UltraClear™ thinwall tubes (Beckman Coulter, 342204) and ultracentrifuged at
100,000g for 2h at 4 °C with SW28 Ti rotor. The exosome pellet in each tube was
washed with 6 mL 10mM PBS, collected in a single tube and filtered using 0.2-μm pore
filter (syringe filter, 6786-1302, GE Healthcare), followed by a second step of
ultracentrifugation at 100,000 x g for 2h at 4°C. Finally, the supernatant was discarded
carefully and the pellet is resuspended in 500 μL 10mM PBS and stored at -80 °C.
Exosome-Bead Attachment
1 mL exosomes (1013 exosomes/mL) were mixed with 1 mL of Aldehyde Sulfate
Latex (ASL) beads (4µm) (Thermo Fisher Scientific) for 15 min at room temperature
with continuous rotation. This suspension was diluted to 100 mL with PBS and left for
30 min rotating at room temperature. The reaction was stopped with stop solution (100
mM glycine and 2% BSA in 10 mM PBS) and left rotating for 30 min at room
54
temperature. Exosomes-bound beads were washed once in 2% BSA in 10mM PBS and
centrifuged for 1 min at 14,800g and blocked with blocking solution (10% BSA,
0.1mg/mL salmon sperm DNA in 10mM PBS) with rotation at room temperature for 30
min. Then the beads were washed second time in 2% BSA and centrifuged for 1 min at
14,800 g. Finally, the exosome-bound beads are recovered in 10mM PBS, aliquoted
and stored at-80°C.
Detailed Experimental Flow of EV-SELEX
The optimum annealing temperature of the primers and the library concentration were
determined before starting the selection process. All the PCR conditions, except for the
annealing temperature, were adapted according to AEGIS SELEX protocol.91 Annealing
temperature was optimized by running the same PCR mixture at different annealing
temperatures ranging from 55°C to 65°C. (Figure 3-2) Takara Taq (Clontech
Labroratories) was used as the DNA polymerase but Taq Buffer and dNTPs (dG, dC,
dT, dA, dZ, dP) were purchased from Firebird Biomedical Science (Alachua, FL).
Incubation step
As explained earlier, exosomes were attached with ASL beads which and for
each round of SELEX same exosome-bead conjugates were used to keep the
consistency. First, the beads were spun down at 14,800 x g for 1 min in order to remove
the storage solution. Meanwhile, 20 nmol of 300 µL of six-nucleotide library (or 250 nM
of recovered pool) was denaturated by heating at 85°C for 10 min and then immediately
“snap cooled” on ice for 10 min. This step is crucial for the sequence to form its 3D
structure. The library was then mixed with 10X Binding Buffer and incubated with bead-
exosome conjugates at 37°C for 30 min with rocking. Following the incubation, the
beads were washed twice with washing buffer and then recovered by centrifugation at
55
14,800 x g for 1 min. Afterwards, the beads-exosome conjugates with bound sequences
on them were resuspended in 200µL of 10mM PBS and incubated at 85°C for 15 min in
order to denaturate the bound sequences. The beads were then removed from the
solution and the survivors were collected in the supernatant. Once the enriched
sequences were obtained, they were ready for the next step, which is PCR cycle
optimization.
PCR cycle optimization and amplification step
Optimization of the number of cycles was performed to obtain the best amplification of
the library pool without observing any nonspecific amplification. For this reason, it is
necessary to optimize the number of PCR cycle repeats for each round. All the PCR
reagents were mixed and a negative control with no template was included for each run.
A master mix containing 10x Taq buffer, dNTPs, primers and water was prepared. Taq
polymerase enzyme and the template were added lastly to the master mix and it was
aliquoted into the PCR tubes. The DNA template was amplified in a C1000
ThermoCycler (Bio-Rad). The number of cycle was varied by increment of 2 between 8
and 24 cycles (Figure 3-2). The cycle showing single band (no-specific amplification)
with the highest product quantity was chosen (Figure 3-2) was provided as an example
for the cycle optimization products, which were run on 3 % agarose gel. Once the
optimum cycle was determined, the amplification of the whole enriched pool was
performed with the selected cycle number and the results were screened similarly, by
3% agarose gel electrophoresis.
Preparation of single-stranded DNA
After PCR amplification, the selected pool was turned into dsDNA, where the sense
strand is FITC-labeled and the antisense strand is biotin-labeled. Since SELEX requires
56
the use of an ssDNA pool, the PCR amplified pool needed to be converted back into
ssDNA. For this purpose, streptavidin coated high performance Sepharose beads (GE
Healthcare) were used to make a small affinity column. The dsDNA product was passed
through the column five times, allowing the binding of biontiylated dsDNA to the
streptavidin beads. The beads were then washed with 2.5 mL of PBS to remove any
remaining forward primer. After washing, the dsDNA was dehybridized with 200 nM
NaOH solution, separating the double strand and releasing the fluorophore-labeled
strand (sense strand). In order to remove the sodium salts, a size exclusion NAP-5™
column (GE Healthcare) was used to desalt the pool. The ssDNA was loaded on the
column, allowed to interact with it and eluted with water. The larger DNA molecules
were eluted first leaving the salts in the column. The desalted ssDNA was quantified by
a UV spectrophotometer and vacuum dried. The PCR products were resuspended in
binding buffer just before use in next round of selection. The next round starts again
with a denaturating step at 85°C for 10 min and a quick snap cool step. This process
was repeated for the following rounds. The negative selection (blood exosomes) was
introduced with Round 4 and the stringency was increased gradually (Table 3-2). The
entire selection process was repeated until a significant enrichment was obtained.
Please refer to Figure 3-1 for the schematic of EV-SELEX.
Monitoring of the pool enrichment
Flow cytometry was used to monitor the enrichment of ssDNA-bound sequences
within the pools during the selection process, as well as to evaluate the binding affinity
and specificity of the selected aptamers. Bead concentration is optimized for 10,000
events and 1.2 µg/mL of exosome-bound beads were used as the optimum (minimum)
concentration for all the binding assays. Beads were centrifuged at 14,800g for 1 min in
57
order to be recovered from the storage solution and washed with bead-washing buffer
Beads then mixed with 250nM of the FITC ssDNA library or pool, and incubated with
rotation at 4°C for 30 min. Following this, the beads were washed in bead-washing
buffer and centrifuged at 14,800g for 1 min in order to remove the unbound sequences.
Finally, washed exosome-bound beads were resuspended in 100µL of bead-binding
buffer. The fluorescence was analyzed using BD Accuri C6 flow cytometer (BD
Biosciences) and the results were interpreted by FlowJo™ software.
Results
EV-SELEX Method and Generation of DNA Aptamers against Hepatocellular Carcinoma Exosomes
A stock solution of 1013 Hep G2 exosomes/mL was prepared before starting the
selection. In order to initiate the selection process, a DNA library was designed using
the parameters described in the Materials and Methods section. A 70 nt long ssDNA
library with a randomized core of 30 nt flanked on both, the 3' and 5'ends by a 20 mer
fixed primer binding sites was designed, synthesized and HPLC purified. FITC-labeled
library was synthesized in order to use in binding experiments as the control sequence.
PCR efficiency is critical in cell-based SELEX because eluted DNA sequences
for each round of selection have to be amplified by PCR. In order to achieve a
reproducible and efficient PCR with minimum unspecific binding, the reaction conditions
must be optimized. Besides, in order to retain maximum number of Z and P nucleotides,
PCR cycle repeats should be kept minimum. The optimum annealing temperature for
primers was determined as 59°C and the following PCRs are performed accordingly.
The selection process is explained in detail in the experimental section of this
chapter. In total, 9 rounds were performed, and the details in terms of quantity of
58
positive, negative extracellular vesicles and incubation time summarized in Table 3-2. A
liver cancer cell line, Hep G2, derived exosomes were used as the target molecule for
the positive selection, whereas human whole blood derived exosomes were used for the
counter selection. The exosomes and ASL beads were conjugated in advance, as
explained in the experimental part.
Selection was started by incubating 20 nmol of library at 85°C for 10 min followed
by a snap cooling on ice to force DNA sequences to form their kinetically most
accessible secondary structures. The library was then incubated with target exosome-
bead conjugate at 37°C for 30 min with rocking. In order to remove the unbound
sequences, the beads were washed with washing buffer twice and the bound
sequences on exosome-bead conjugate were recovered by centrifugation at 14,800 x g
for 1 min. After the washing steps the bound DNA was released by heat (85°C, 15 min)
and separated from the beads by centrifugation. This process is practiced from round 1
to 3 and with the beginning of 4th round counter selection was incorporated. The only
difference in the process is pre-incubating the enriched pool with the negative blood-
exosome beads first for 30 min at 37°C. After the incubation, the unbound survivors
were collected and the process described above was reapplied. The incubation step
was followed by a PCR amplification. Single stranded biotinylated DNA was recovered
from double stranded amplicon DNA by capturing on solid-phase streptavidin followed
by elution with 200 mM NaOH. This was repeated a total of 9 rounds and counter
selection incorporated with the round 4.
The enrichment of the library through successive selection rounds was monitored
by flow cytometry. As the selection progresses, the number of sequences binding to the
59
target cell line increases. Therefore, the enriched pool shows an increase in mean
fluorescence intensity. Once the pool shows no increase in fluorescence intensity, the
pool has been fully enriched and the selection has been completed. The first monitoring
was performed after round 6, for rounds 3,4,5 and 6 (Figure 3.4) An enrichment was
observed for rounds 3 and 4 but lost in round 5 and 6 (Figure 3-4A). We suspect this
might be due to the increase in negative beads and thus repeated the rounds 5 and 6
with a smaller number of blood exosome-bead conjugate. We felt confident when doing
so, since there was no binding between any enriched pool and negative bead-exosome
conjugates (Figure 3-4B). The bulk affinity increased from rounds 6 to 9, where no
enrichment was observed for negative control beads (Figure 3-5). The selection was
ceased at Round 13 and the sample was prepared for deep sequencing.
Deep Sequencing of GACTZP DNA Survivors Using Next Generation Sequencing Technology
Solutions containing enriched GACTZP DNA survivors after the 9th round of EV-
SELEX were divided into two equal parts. These were separately converted into
standard DNA under two conversion conditions using primers that carried barcodes for
the Ion Torrent deep sequencing. Following conversion, the samples were combined,
purified by native agarose gel, and submitted for Ion Torrent S6 “next generation”
sequencing at the University of Florida, ICBR sequencing core facility. The products
were aligned to identify sequences derived from a single common aptamer ancestor.
Ion Torrent sequencing reads that did not contain exact matches to the barcode,
forward and reverse priming sequences were discarded. To minimize miscalling, any
read present in less than 45 copies was removed from the analysis. The remaining
reads were then clustered using software custom designed at the FfAME, which ignored
60
differing barcodes during the clustering and accepted single-step changes within
sequence reads. Clustered sequences were then separated by barcode, with variable
sites being compared between each barcode (differentiating the two conversion
conditions). The clustered sequences obtained under the first conversion conditions
(Barcode A, Z to C and P to G conversion) serve as reference for the clustered
sequences obtained under the second conversion conditions (Barcode B, Z to T/A and
P to C/G conversion). Sites where C and T were found in approximately equal amounts
after conversion under the second conditions were assigned as Z in their “parent”. Sites
where G and A were found in approximately equal amounts after conversion under the
second conditions were assigned as P in their “parent”. The eight most abundant
families were given in Table 3-3.
Discussion and Conclusion
EVs are becoming increasingly important as a source for novel cancer diagnostic
tools. Early detection of cancer is crucial to reduce mortality and increase survival.
Thus, it is essential to explore novel biomarkers that can distinguish cancer patients
from normal individuals. In some solid tumor types, certain biological proteins in the
body fluids, especially in the blood, offer such biomarkers, such as carcinoembryonic
antigen for colon cancer92 and prostate-specific antigen for prostate cancer93. However,
low specificity is a serious problem for these cancer biomarkers. For this reason,
additional biomarkers and detection tools are required to establish better early detection
methods. In this regard, EVs are expected to be noninvasive biomarkers for cancer
since they are present in various body fluids including serum, plasma, urine, and
contain a series of biological molecules that reflect the physiological and pathological
status.47,94,95 Also, source specific markers that represent the proteome of the cell of
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origin can also be used for exosome identification. For example, urinary exosomes of
patient’s with non-small cell lung cancer were found to carry proteins representative of
their primary tumor.96 Taken together, it is urgently necessary to develop biomarkers
targeting specific exosomes for clinical usage.
Since their discovery, aptamers have been generated against various targets,
including proteins,97 peptides,98 and living cells.89,90,99
The most tedious part of the project was the exosome collection experiments. It
took nearly two months to collect all the required number of exosomes from Hep G2
cells before starting the selection process. As discussed in the previous chapter, one
batch of exosome collection requires several, minimum two hours long ultra-
centrifugation steps. Besides, it includes culturing and maintaining a minimum of 15 T-
182 flasks of cells, which is a laborious task. On the other hand, it was crucial and
essential to perform each round of SELEX with the same batch of exosomes in order to
keep the consistency of positive selection. Otherwise, we might introduce new target
molecules to each round of selection. Although we optimized the exosome collection
process at its best to obtain a homogeneous population, it would not be fair to claim that
all the collected vesicles were exosomes. Hence, an immunoaffinity capture step with
exosome specific antibodies might be necessary to isolate pure exosome samples.100
On the other hand, this would be very costly, especially if the sample size is big like in
this case.
The top three sequences with the highest percentile were synthesized only, since
the relative percentages of the other sequences were less than 1% and were
considered less important. On the other hand, that might not reflect the absolute truth.
62
There is a possibility that better aptamers (with a better specificity and/or affinity) might
be present in lower percentiles. It is actually more likely in this case than a regular cell-
SELEX, if we consider the fact that we kept the round number as small as possible and
terminated the selection process immediately after observing a significant
binding/enrichment. An average cell-SELEX takes 10-20 rounds101 thus the enrichment
percentile is usually higher for certain candidates. Nevertheless, a computational and
bioinformatics modelling might provide researchers a better insight about selection
process or potential aptamer candidates with lower percentiles.
63
Table 3-1. Sequences used for EV-SELEX
Oligonucleotides Sequence
Library 5’-CCTTCGTTGTCTGCCTTCGTCGACT-N30-
ACCCTTCAGAATTCGCACCA-3’
Forward Primer 5’FAM-CCTTCGTTGTCTGCCTTCGT-3’ Tm 57.6C
Reverse Primer 5’BIO-TGGTGCGAATTCTGAAGGGT- Tm 56.8C
Table 3-2. Summary of EV-SELEX process
Round # PCR Cycle #
Target Exo-Beads
(µL)
Target Incubation Time (min)
Negative beads (µL)
Negative Incubation Time (min)
Round 1 25 100 30 N/A N/A
Round 2 24 100 N/A N/A N/A
Round 3 17 50 30 N/A N/A
Round 4 18 50 30 50 30
Round 5 14 40 30 50 30
Round 6 15 40 30 100 30
Round 7 16 50 30 50 30
Round 8 13 50 30 100 30
Round 9 16 50 30 100 30
Round 10 15 50 30 100 30
64
Table 3-3. Compendium of the aptamer candidates selected by EV-SELEX against Hepatocellular Carcinoma Cells (Hep G2). Primer parts are removed and only the random sequences are provided. Artificial bases are marked as bold.
Aptamer Candidates Sequence
SEV1 5’-ACCCGCPCCGTCACACATCACACCGCCGCZ-3’
SEV2 5’-CCCPCACZPTGCTGCCCGTTACCACTCTCC-3’
SEV3 5’-CPCZGCCCCTTGTCTCCATCAGGCGGCCCC-3’
SEV4 5’-CCZTPCPCCCTGTCCAGTCGGCGGCCTTGT-3’
SEV5 5’-CCPCCACCTZGCTCCTTACATCGGCCTCAC-3’
SEV6 5’-CCPGCTCZTCACTATCCCTTGTCTGTCTCC-3’
SEV7 5’-CCPGCZCTGTCCCCAZCTCACCTGCCCTTA-3’
SEV8 5’-CCCZACPTCTGCCGTCTGTGTCCTGCCCGC-3’
65
Figure 3-1. Schematic of EV-SELEX with both positive and negative selections. Briefly, ssDNA library is incubated with target bead conjugated-exosomes (Hep G2). After washing the unbound sequences, the bound DNAs are eluted by heating in binding buffer. The eluted DNAs are then incubated with control exosomes (counter selection, blood exosomes) for counter-selection. After centrifugation, the unbounded ssDNAs in supernatant are collected, and then amplified by PCR. The amplified DNAs are used for the next round of selection. The selection process is monitored using fluorescent analysis by flow cytometry. Once an enrichment has achieved, the final pool is sequenced.
66
Figure 3-2. PCR applications of EV-SELEX. A) Agarose gel electrophoresis image of annealing temperature optimization experiment. 59°C was selected as the optimum annealing temperature B) PCR conditions schematic C) Agarose gel electrophoresis image of cycle optimization experiment.
67
Figure 3-3. Verification of the enrichment of the library in binding sequences after 6 rounds. The DNA solutions generated at rounds 3, 4, 5 and 6 were incubated with both A) the target exosomes and B) the negative exosomes to verify the binding profile.
68
Figure 3-4. Monitoring the progress of EV-SELEX using flow cytometer. The binding affinity of survivors was monitored in bulk from 6th round up to 9th round of selection. The vertical axis (Events) indicates the number of cells counted having the fluorescence intensity indicated by the horizontal axis. A higher intensity indicates a larger number of fluorescein labelled aptamer candidates bound per cell. A) Binding profile of the enriched pools with target exosomes B) Binding profile of the enriched pools with negative exosomes.
69
CHAPTER 4 IDENTIFICATION OF DNA APTAMER ANALOGS IN GENOMIC DNA1
Introductory Remarks
Protein Tyrosine Kinase 7
PTK7 is an ancient and conserved protein.102 It was characterized in 1995 103
and various mutation experiments have identified a central role for PTK7 in a process
called planar cell polarity (PCP).104,105 As with many proteins important for development,
dysregulation of PTK7 expression is also a factor in many different cancers especially
colon cancer106, leukemia107 and melanoma.108 Structurally, PTK7 is a transmembrane
molecule; it consists of seven extracellular immunoglobuline-like domains, a single
transmembrane region and intracellularly, a kinase domain. This protein is structurally
unique among tyrosine kinases because its extracellular domain is composed of only Ig
domains, which in humans and zebrafish contain a matrix metalloprotease (MMP)
cleavage site. Besides, its transmembrane domain is more conserved than those of any
other receptor tyrosine kinase and its catalytically dead pseudo Tyrosine Kinase
domain, is also inert in all known orthologs.109 The extracellular portion of PTK7 is
composed of seven Ig-like domains, held together with an Ig fold. There is a MT1-
MMP/MMP14 cleavage site in the extracellular domain of PTK7 between the sixth and
seventh immunoglobuline domain.110 MT1-MMP is a membrane-bound endopeptidase
that cleaves extracellular matrix (ECM) proteins, other soluble MMPs and other
membrane-bound signaling receptors, including, PTK7.
1 Portions of work done this chapter were completed by Dr. Meghan Altman, a previous Tan Group
member, and were reproduced with her permission.141
70
It has been shown that it is overexpressed in cancer, with a higher level of expression
result in more invasive and malignant tumors.111,112 Moreover, Golubkov et al. (2010)
confirmed that MT1-MMP cleaves PTK7 into two pieces: a 50kDa C-Terminal
membrane-bound pTK fragment and a 70kDa soluble PTK7 (sPTK7) fragment made up
of the first 6 Ig-like domains. They found these sPTK7 fragments in the cell media and
bound to full-length PTK7 on the surface of the cells. Following this work, Strongin
group followed up on this work by characterizing a mutant PTK7 protein with not one,
but two MT1-MMP cleavage sites. This mutant PTK7 protein was made in a mouse
strain, chuzhoi (chz), created by exposing the mice to the mutagen Nethyl-N-
nitrosourea. The mutant mice showed signs of classic PCP signaling problems,
including neural tube defects and disrupted hairs in the inner ear.113 In addition to the
normal MT1-MMP cleavage site in the 7th Ig-like domain, this mutant’s PTK7 contained
a second cleavage site in the linker between the 5th and 6th Ig-like domain.
Wnt Signaling
PTK7 is one of the key elements of Planar Cell Polarity (PCP), a process
controlling uniformly polarized cellular behavior across the plane of the
epithelium104,105,113 and is very critical for many developmental processes.114 PCP is
regulated by the Wnt signaling pathway, where Wnts comprise a group of signaling
molecules, controlling many processes of development and adult tissue homeostasis
through several different pathways. They interact with various receptors and therefore
activate different downstream pathways. Even though the actual situation is more
complex, the Wnt pathways can be simply classified as -catenin dependent and -
catenin independent pathways, which in turn can be subcategorized as PCP/Wnt and
71
Wnt/Ca2+ signaling. In the -catenin pathway, Wnt ligands bind to cell-surface receptor
Frizzled (Fz) which in turn recruits the co-receptor low-density lipoprotein receptor-
related protein5/6 (LRP5/6) on the cell surface to bind the cytoplasmic protein
Disheveled (DVL) Through several cytoplasmic cascades the signal is transduced to -
catenin, which enters the nucleus, where it activates the transcription of target genes
under the control of T cell factor (TCF), among others. These genes are mainly involved
in regulation of cell differentiation and proliferation.115,116 On the other hand, as its name
implies, -catenin independent pathways use other ways of downstream signaling
instead of -catenin-TCF. These non-canonical Wnt signaling pathways control cellular
polarity and cell movement, and they signal, for example, via small GTPases of the Rho
family resulting in modification of the cytoskeleton 117. PCP/Wnt signaling is the best
characterized -catenin independent pathway. However, although Wnt ligand binds to
Fz and activates DVL, the co-receptor recruited is different. Upon binding of PCP/Wnt
ligand to Fz instead of LRP5/6, PCP/Wnt co-receptors are activated. Several functional
studies point to a role for PTK7 as a PCP/Wnt co-receptor determining PCP.118,119
Please refer to Figure 4-1 for wnt signaling pathway schematic.
Background and Significance
Cell-SELEX generates artificial, single-stranded DNA and RNA molecules, called
aptamers, that can bind specifically to a cell type of interest. It is a well-established,
iterative method 60 and has been used to select aptamers mainly targeting whole cancer
cells, such as colon86, leukemia120, liver90, lung121 and other cancers. Each whole cell-
SELEX uses a large (ca 1015) library of random DNA sequences usually having less
than 100 nucleotides, flanked by primers. The target cell membranes may contain as
72
many as 10000 proteins122, any of which could be attracted to one or more of the library
sequences. During the iterative binding process, cells are equilibrated with library
sequences and only the bound sequences are retained and PCR amplified for the next
round equilibration, separation, PCR. Binding with target cells is alternated with
equilibration with a different cell line (negative selection) to remove sequences that bind
to common membrane markers. After an enrichment achieved, the binding sequences
are amplified and then subjected to Next Generation Sequencing.
Sgc8 is one of the DNA aptamers selected by whole-cell SELEX for a target T-
Cell leukemia cell line, CEM-CCRF, using Ramos B-Cell leukemia cells for the negative
cell line. Further investigations revealed that Protein Kinase 7 (PTK7) is the specific
target on the CEM-CCRF cell surface surface.123 PTK7 is an ancient and conserved
integral membrane protein with 7 immunoglobulin-like domains that hang outside the
cell, a single transmembrane domain, and a tyrosine pseudokinase domain inside the
cell. Several studies have shown overexpression of PTK7 in colorectal tumors 124,
erythroleukemia125 acute myloid leukemia126, glioma127 and prostate cancer. 128 In
contrast, PTK7 is downregulated in some other cancers, such as melanoma108,
ovarian129 and hepatocellular carcinoma.130 In addition, it has been recently shown that
there is an MT1-MMP endopeptidase cleavage site in the 7th Ig fold, above the
transmembrane domain, which cleaves the protein into two parts: membrane bound and
soluble PTK7 (sPTK7).110
Functionally, PTK7 is one of the key elements of Planar Cell Polarity (PCP), a
process controlling uniformly polarized cellular behavior across the plane of the
epithelium,104,105,113 and is very critical for many developmental processes.114 PCP is
73
regulated by the Wnt signaling pathway, where Wnts comprise a group of signaling
molecules, controlling many processes of development and adult tissue homeostasis
through several different pathways. They interact with various receptors and therefore
activate different downstream pathways. Even though the actual situation is more
complex, the Wnt pathways can be simply classified as -catenin dependent and -
catenin independent pathways, which in turn can be subcategorized as PCP/Wnt and
Wnt/Ca2+ signaling. In the -catenin dependent pathway, through several cytoplasmic
cascades the signal is transduced to -catenin, which enters the nucleus, where it
activates the transcription of target genes under the control of T cell factor (TCF),
among others (Figure 4-1).116 These genes are mainly involved in regulation of cell
differentiation and proliferation.115,116 Among many others, a scaffolding protein ,DIX
Domain Containing 1 protein (DIXDC1) has recently been shown as the positive
regulator of -catenin dependent pathway.131,132 On the other hand, as the name
implies, -catenin independent pathways use other ways of downstream signaling
instead of -catenin-TCF. These non-canonical Wnt signaling pathways control cellular
polarity and cell movement, and they signal resulting in modification of the cytoskeleton
117 PCP/Wnt signaling is the best characterized -catenin independent pathway where
PTK7 acts as one of the main co-receptors. Several functional studies point to a role for
PTK7, which shifts the pathway to PCP/Wnt signaling upon its activation by certain Wnt
lignads.118,119
In this work, we investigated the possibility of DNA aptamer analogs in genomic
DNA. Analysis of DNA sequences, selected independently against different target cells
by whole cell-SELEX, identified 4 aptamers, including sgc8, with a common target
74
protein, PTK7. Deeper investigation of these aptamer sequences revealed a 15 base
consensus region, which was searched for a match in the human genome.
BLAST results revealed a sequence identity of the consensus region minus one
G base on the 5’ untranslated region (5’-UTR) of DIXDC1 coding gene. As explained
above, PTK7 and DIXDC1 are both regulating Wnt signaling pathway but they have
opposite effects; PTK7 switches the pathway toward PCP/Wnt signaling whereas
DIXDC1 favors -catenin dependent pathway. These results revealed the possibility that
PTK7 is interacting with DIXDC1 gene perhaps in order to regulate expression of the
latter.
Results
Sequence Similarity between Different Aptamers
Close examination of several different cell-SELEX aptamers, targeting different
cancer cell lines and selected independently at different times by different researchers,
revealed binding patterns similar to that of sgc8. Sequence alignment by CLUSTELx133
revealed that aptamers sgc8 and KC2D886 share 38 consecutive nucleotides, the former
selected against T-Cell leukemia cell line CCRF-CEM and the latter independently
against colorectal adenocarcinoma DLD1. In light of this evidence, a dataset of all DNA
aptamers identified by complex selection or against membrane-bound targets was
constructed. This yielded 148 unique aptamer sequences from 33 different selections.
The aptamers’ primer regions were removed to avoid interference during alignment, and
their correspondences were determined by alignment with ESPRIT134 The results
revealed two more aptamers, H01 and KMF9b88, having sequence identity with each
other, as well as with sgc8 and KC2D8. When these sequences were aligned with sgc8,
75
their similarities were clustered around a core 15nt GC rich region:
GCTGCGCCGCCGGGA. (Table 4-1).
Competition Experiments
Even though the four aptamers (sgc8, KC2D8, KMF9b and H01) have similar
affinities to the same cancer cell lines and share a consensus region, it was still
necessary to determine whether they bind to the same target molecule on the target
cell, PTK7 in this case. In order to do so, all aptamers were subjected to a competition
assay against sgc8. According to the results, all four aptamers competed with each
other but not with a control sequence, scrambled-sgc8 (Figure 4-2). In addition, it was
clear that H01 was driven off the cell surface faster than the other aptamers. Addition of
unlabeled sgc8 first, followed by H01 labeled with biotin (H01-B, purple line) showed no
binding of the label by flow cytometry, but addition of unlabeled H01, followed by sgc8
labeled with (sgc8-B, dark blue line) or addition of unlabeled H01 followed H01-B (light
blue line) resulted in reduced binding, but to a much lower extent. This means, if
unlabeled sgc8 binds PTK7 first, H01 is not able to bind the PTK7. By contrast, H01 is
readily replaced by both biotinylated sgc8 and 10x unlabeled H01.
BLAST of the Consensus Sequence Against the Human Genome
In light of bioinformatic analysis and competition experiments, it was
hypothesized that these aptamers may be mimics for a naturally occurring interaction
between PTK7 protein and natural DNA. If this is the case, the consensus sequence
should be found in a target sequence in the DNA. To investigate this possibility, the
consensus sequence was BLASTed against the human genome using the NCBI
nucleotide BLASTn algorithm, adjusted for short sequences. Eight matches were
identified with a 14/15 nucleotide identity. Of these, Dix Domain Containing 1 protein
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(DIXDC1b) was the only one which carries the consensus sequence on the 5’
untranslated region (5’ UTR). and which is also related to the Wnt signaling pathway
together with PTK7. In light of these findings, PTK7-aptamers were aligned with
DIXDC1b DNA, which contained a 1nt mismatch with sgc8 and KC2D8, 3nt mismatches
with KMF9b, and 5nt mismatches with H01. Although H01 and KMF9b had more
mismatches within the consensus region, they both had additional bases in common
with the DIXDC1b DNA adjacent to the consensus sequence (Table 4-3). Moreover,
another sequence match between KC2D486 aptamer and the negative strand of
DIXDC1b DNA was detected (Table 4-3). Despite the fact that KC2D4 also competes
with sgc8, no sequence identity was observed with PTK7 aptamers. Surprisingly,
CLUSTALx analysis revealed an 11 nucleotide match between DIXDC1b DNA and
KC2D4 five nucleotides downstream of the consensus region on positive DIXDC1b
DNA.
Investigation of the Interaction of PTK7 with DIXDC1b DNA
A western blot was performed in order to demonstrate nuclear localization of
sPTK7. Cell fractionation of PTK7 overexpressed cells (HEK293, HeLa) was followed by
anti-PTK7 probing, as well as by cytoplasmic and nuclear control antibodies. According
to the results, cleaved PTK7(sPTK7) was detected in all three fractions, and at much
higher levels in the nuclear fraction, whereas full length PTK7 was observed at higher
levels in the pellet, which would contain the membrane (Figure 4-3). In addition, a gel
shift experiment was designed to show the interaction between PTK7 and the DNA
coding DIXDC1. An 87 base part of DIXDC1b DNA which included the consensus
region was PCR amplified with biotin labelled primers and incubated with nuclear
extracts from HeLa or Ramos (negative control) cells. Then, the nuclear extract-probe
77
complexes were separated on a native gel and observed with a typhoon scanner. The
shift proved the interaction of the sequence of interest with the HeLa nuclear extract
(Figure 4-5). No shift was observed for the nuclear extract of Ramos, which does not
express PTK7. In addition, confocal immunohistochemistry experiments showed the
colocalization of sgc8 aptamer inside the nucleus. HeLa cells were incubated with
TAMRA labelled sgc8 and a random sequence. DAPI was used for nuclear staining.
After 2 hours of incubation, aptamers can be observed inside the cell, as well as inside
the nucleus (Figure 4-4B). On the other hand, no fluorescence was observed for control
sequence, meaning no internalization. (Figure 4-4A)
Discussion and Conclusion
By means of cell-SELEX technology, the Tan Group has generated a number of
DNA aptamers targeting cancer cells. One of the most widely used is Sgc8, which was
discovered to bind the extracellular part of PTK7, which has a central role in PCP/Wnt
signaling. It was later found that several different aptamers, selected against different
cell lines with different starting primer sets, showed binding affinity very similar to that of
sgc8 towards PTK7 overexpressing cell lines. In order to investigate this phenomenon
deeper, a series of bioinformatics and competition analyses were conducted. A total of
148 aptamer sequences selected by whole cell-SELEX revealed significant sequence
identity between sgc8 and 3 other aptamers (KMF9b, KC2D8, H01) within a 15nt
consensus region (GCTGCGCCGCCGGGA). As predicted, all 4 aptamers competed
with each other and bound to the cells with similar affinity, implying that they bind to the
same place on the PTK7 protein. Repeating the same selection and selecting the same
sequences by coincidence is unlikely for several reasons: First of all, each selection
started from a large pool of potential targets because, neglecting lipids and peripheral
78
proteins and considering integral proteins alone, 20-30% of human proteins have a
transmembrane domain122 and a significant portion of these proteins are exported to the
cell surface. This means that upwards of 10,000 different proteins are expressed on
each cell's surface. In addition, these proteins can be further modified by
carbohydrates, creating many more sites for possible aptamer interaction and
subsequent selection. (An ovarian cancer selection that produced aptamers insensitive
to proteases has been postulated to bind these glycoproteins. 85) Second, a large
aptamer library with different primers is used for each selection, calculated to include
1015 unique sequences. Thus, there are so many possible sequence/target
combinations that random coincidence is unfeasible. Third, aptamers are routinely
selected against a wide array of specific single targets (small ions, peptides, and
purified proteins). A search of the literature did not reveal a single target that evaded
selection. Building on this, it is assumed that each potential target on the cell surface
had an equal probability of binding one of the sequences in the library.60
The similarity between all four PTK7 aptamers indicated that one of the above
considerations did not hold. Since the first two are not questionable, the third
consideration may not be completely applicable to cell-SELEX. Instead of detailed,
complete profiling of the cell surface, perhaps cell-SELEX preferentially selects for
aptamers with a biological function; for instance, those with an underlying affinity for
DNA binding.
In order to investigate the repetitive selection of the consensus sequence, it was
BLASTed on genomic DNA. According to the results, the consensus region, minus the
first G base, appears 5 times in the human genome. One of these sites is in the 5'-
79
untranslated region (5’-UTR) of human DIXDC1b DNA, which, along with PTK7, is a
regulator of non-canonical Wnt signaling. DIXDC1b is one of the three known DIX
domain-containing proteins and is a positive regulator of -catenin-dependent Wnt
signaling.135–137 It has been previously demonstrated that downregulation of DIXDC1, as
in squamous cell carcinoma of the lung, leads to aberrant upregulation of Wnt/PCP
signaling138. Considering that PTK7 is one of the co-receptors of the PCP/Wnt pathway,
we can conclude that PTK7 and DIXDC1 have opposite effects on Wnt signaling. PTK7
switches Wnt signaling from being β-catenin dominant to being PCP dominant, whereas
DIXDC1 switches Wnt signaling from being PCP dominant to being β-catenin dominant.
As discussed in the Results section, aligning DIXDC1b DNA with four PTK7
aptamers revealed additional sequence identities in addition to the consensus region. In
addition, a new sequence match between the DIXDC1b DNA negative strand and
KC2D4 was discovered. In total, DIXDC1b DNA and PTK7 aptamers share 22 identical
nucleotides, which is a unique occurrence in the human genome. As a result of these
findings, the aptamers’ sequence identity to both the positive and negative strands of
DIXDC1b DNA could be consistent with the protein PTK7 melting the genomic DNA and
interacting with the resulting ssDNA hairpins, which share sequence identity to the
aptamers formed by each melted strand. If this possibility is indeed the case, it could
affect DIXDC1b transcription.
Further, nuclear localization of sPTK7 was demonstrated by cell fractionation
followed by western blot. A large accumulation of sPTK7 was demonstrated inside the
nucleus, which perhaps is evidence for the interaction of PTK7 with the DIXDC1b gene.
Consistent with this hypothesis, a matrix metalloprotease cleavage site that frees the
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extracellular portion of PTK7 has been recently reported. Adding this protease to PTK7-
expressing cells caused PTK7 to be removed from the cell membrane and to
accumulate around the nucleus.110 On the other hand, the presence of a faint full length
PTK7 band in the nuclear fraction is inconsistent with accumulation of only the
extracellular portion around the nucleus. This weak full-length band may have occurred
due to leakage during fractionation. In addition, a gel shift experiment showed binding
between the PCR amplified dsDIXDC1b DNA including consensus region and the
nuclear extract of HeLa cells. Together with the nuclear localization of sPTK7, this may
be evidence for the interaction of PTK7 with genomic DNA to alter DIXDC1b
expression.
Materials and Methods
Unless specified otherwise, all the reagents were purchased either from Thermo-Fisher
or Sigma Aldrich.
Buffers and Cell Culture
Washing buffer (WB) contained glucose (4.5g/L) and magnesium chloride (5mM)
in 10mM Dulbecco’s phosphate buffered saline. Binding buffer (BB) was prepared by
adding bovine serum albumin (1mg/mL) and transfer ribonucleic acid (tRNA)
(0.1mg/mL) to washing buffer. All cell lines were obtained from American Type Culture
Collection (ATCC). CCRF-CEM (CCL-119, a T-cell line, Acute Lymphoplastic Leukemia)
and Ramos (CRL-1596 a B-cell line Burkitt’s lymphoma) cell lines were cultured in
RPMI-1640 medium (Sigma) with 10% FBS (GIBCO) and 100 units/mL penicillin-
streptomycin (Cellgro) at 37°C under 5% CO2. HeLa (CCL-2, human cervical
adenocarcinoma) and HEK 293 (CRL-1573) cell lines were cultured in DMEM-1640
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medium (Sigma) with 10% FBS (GIBCO) and 100 units/mL penicillin-streptomycin.
Cultures were routinely monitored for Mycoplasma infection.
DNA Sequences
All DNA sequences were synthesized in-house at a 1 μmol-scale using an ABI
3400 DNA/RNA synthesizer (Applied Biosystems). Sequences were deprotected from
CPG beads with AMA (ammonium hydroxide: methylamine 1:1) at 60C for 30 minutes.
All sequences were either unlabeled or labeled at the 3’ end with biotin and re-
suspended in 1M TEAA and purified on a reverse phase Prostar HPLC (Varian) using a
C18 column (Econosil, 5U 250 x 4.6 mm from Alltech Associates) with a linear elution
gradient of acetonitrile:trietylammonium acetate. These sequences were vacuum dried,
detritylated with 20% acetic acid and re-suspended in 1M TEAA buffer. The
concentration was determined by UV-vis spectrophotometry (Beckman Coulter DU800)
at 260nm. The primers used for the experiments were ordered from Integrated DNA
Technology (IDT).
Bioinformatics
A dataset of 148 aptamer sequences from 33 different cell-SELEX procedures
was compiled with their primers removed and aligned with ESPRIT134. The p-values
were calculated by comparing each alignment score with those of 1,000,000 random
pairs of the same length. Using the convergent property of SELEX139, the p-value (p)
obtained in our simulation indicated that, given a target sequence S1, a reference
sequence R, which has a known similarity value t to S1, and a random sequence S2,
with the same length as R, the probability that S2 is at least as similar as R to S1 is p.
Under this non-deterministic model, we supposed we have n (here n ~10,000) aptamers
in the system. The probability that a random aptamer can be more similar than R is 1-
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(1-p)n. If we examine k targets (here k=148), the probability of one random hit will be 1-
(1-p)nk, which is approximately nk*p when p is small. Hence, if nk*p << 1, we claim that
R is not likely a random match. This means that R should be identical, or at least
correlated to S1. Ranked by p-value, sgc8 and KC2D8 had the highest alignment, and.
KMF9b showed sequence identity to sgc8. Based on this result, a GenBank BLASTn140
was performed on the consensus region: GCTGCGCCGCCGGGA.
Significance Simulations
According to classical probability law, the probability that a random pair of
sequences has the same sequence similarity with a real pair assigned p-value p, is
P0=n(n-1)/2*p with n sequences. Following this law, KC2D8 is a non-coincident match,
with P0<0.01. The probability that a third sequence has that similarity is P1=2*(1-P0)*(n-
2)* p. Here KMF9b is matched to sgc8-KC2D8, with significance level P1<0.03. Thus,
each of the 3 sequence alignments cannot be explained by coincidence, and the
common region between the three PTK7 aptamers and DIXDC1b DNA is unique in the
human genome. The probability that another random sequence could match the same
DNA in adjacent regions was examined by simulating 1,000,000 random 39nt long
sequences, and aligning them with FASTA to a 52bp segment in the 5’-UTR of
DIXDC1b DNA.
The simulation showed that 2,554 sequences out of 1,000,000 sequences, or
their reverse complement, have at least one 13bp window sharing at least a 12nt
identity with the DIXDC1b segment, the same as KC2D4. Hence, the chance that a
random sequence has the same similarity to the target region is p=0.0025.
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Competition Assays
For each aptamer-competition experiment, cells were washed with washing
buffer, probed with the first aptamer followed by the second aptamer, washed, stained
with 1:400 streptavidin-PE, washed again, and analyzed using a FACScan flow
cytometer (Becton Dickenson). Aptamer treatments were: no aptamer; 80nM scrambled
sgc8-biotin; 80nM aptamer-biotin; 800nM unlabeled-aptamer, then 80nM aptamer-
biotin; 800nM unlabeled-sgc8, then 80nM aptamer-biotin; and 800nM unlabeled-
aptamer, then 80nM sgc8-biotin. The results revealed that scrambled-sgc8 (scr-sgc8)
does not compete with sgc8, while all the other aptamers do.
Western Blot
HEK293 cells were fractionated using a NE-PER kit (Pierce), run on a 4-20%
Tris-Glycine gel (Invitrogen), and probed with α-PTK7 M02 (Abnova), then re-probed for
α-GAPDH (ABcam), a cytosolic marker, and Lamin B1 1:1000 (ABcam), a nuclear
marker. Then the membrane was treated with, α-Rabbit HRP 1:5000 (Pierce) and
imaged on Kodak film.
Gel Shift Assay (EMSA)
CCRF-CEM genomic DNA from 5x106 cells was extracted and RNase treated.
An 87 bp long ds DNA surrounding the consensus region on DIXDC1b was PCR
amplified with 5’-biotin tagged primers and the PCR product was purified via purification
kit (Qiagen, Valencia, CA). A small scale nuclear extract method was used for HeLa and
Ramos (negative control) cells and protein concentration was determined by BCA
assay. A LightShift Chemiluminescent EMSA kit from Pierce (Thermo Fisher) was used
for the binding experiment according to manufacturer’s instructions. The reactions were
loaded on 6% non-denaturating neutral polyacrylamide gel and transferred to a nylon
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membrane. The biotinylated oligonucleotides were detected with streptavidin-linked
horseradish peroxidase with a typhoon scanner.
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Table 4-1. PTK7 aptamer sequences with their identical nucleotides marked as bold. Primer sets used for the selection of aptamers were included
Aptamer Primers Sequence
sgc8 F-ATACCAGGCTTATTCAATT R-GATAGTAAGTGCAATC
ATCTAACTGCTGCGCCGCCGGGAAAATACTGTACGGTTAGA
KMF9b F-AGGCGGCAGTCTCAGAGT R-CTGAGCGACGAAGACCCC
AGCGCAGCAGCTGTGCCACCGGGAGAATTTACGTACGGCTGAGC
KC2D8 F-ATCGTCCGCCACCACCACTACTC R-GTGAGACTGCCTGCCTGCCGATGT
TACTAACTGCTGCGCCGCCGGGAAAATACTGTACGGTTAGTT
H01 F-ATCGTCTGCTCCGTCCAATAT R-TTTGGTGTGAGGTCGTGC
AAGCAGCAGCTGTGCCATCGGGTTCGGATTTTCTTCCTACGACT
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Table 4-2. BLAST hits 14/15nt identity for consensus sequence (GCTGCGCCGCCGGGA) in human genome
Protein Name, Abbreviation Locus Location in Gene
DIX Domain Containing 1, isoform b, DIXDC1b NM_033425.3 5’ UTR
Mucolipin 1, MCOLN1 NM_020533.2 Coding region
Membrane-bound transcription factor peptidase NM_003791.2 Intron
Ubiquitin-conjugating Enzyme E2D2, UBE2D2 NM_003339.2 Intron
Myc Induced Nuclear Antigen, MINA NM_032778.4 Intron
SH3 and multiple ankyrin repeat domains protein NT_011109.16 Intron
Nearest protein KIAA1875 NR_024207.1 Unknown
Nearest miRNA MIR302F NW_001838467.2 Unknown
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Table 4-3. Aptamers share sequence similarity with DIXDC1b DNA sequence. Lettering in bold shows identity inside
consensus sequence with DIXDC1b positive strand DNA (+); letters in square brackets show additional bases in common after alignment with DIXDC1b DNA; letters in curly brackets show identity with DIXDC1b negative strand DNA (-).
Aptamer Sequence
sgc8 ATCTAACTGCTGCGCCGCCGGGAAAATACTGTACGGTTAGA
KMF9b A[GCGCAGC]AGCTGTGCCACCGGGA[G]AATTTACGTACGGCTGAGCGA
KC2D8 TACTAACTGCTGCGCCGCCGGGAAAATACTGTACGGTTAGTT
H01 AAGCAGCAGCTGTGCCATCGGGTTCGGATTTTCTTCCTACGACT
DIXDC1b
DNA
+G[GCGCAGC]CTGCGCCGCCGGGA[G]CCTCCCTCCCAGTGGGAGATGGGTTGAGA
-CCGCGTCGGACGCGGCGGCCCTCGGAGG{GAGGGT}C{ACC}C{TC}TACCCAACTCT
KC2D4 {GAGGGT}G{AC}CA{TC}GGTAAGGCGGGAATTGGCCCGGTAGC
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Figure 4-1. Simplified schemes showing the main WNT pathways directed by specific
WNT, Frizzled and WNT co-receptor interactions. A) Planar cell polarity (PCP) signalling triggers activation of the small GTPases RHOA and RAC1, which in turn activate RHO kinase (ROCK) and JUN-N-terminal kinase (JNK) B) (GSK3) phosphorylates β-catenin, which triggers its degradation. However, in the presence of WNT ligand, the destruction complex is recruited to the WNT–receptor complex and inactivated. This allows β-catenin to accumulate and translocate to the nucleus, where it activates the transcription of target genes under the control of T cell factor (TCF), among others. C) The WNT–Ca2+ pathway activates Ca2+- and CAMKII, protein kinase C (PKC) and calcineurin. PCP and Ca2+pathways antagonize β-catenin signaling at various levels. D) Major pathways used by WNT receptors and co-receptors. Only the three best-characterized WNT pathways are shown. Figure adapted from Nature Reviews: Molecular Cell Biology116. Reprinting with permission Nature Publishing Group.
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Figure 4-2. Competition studies between different aptamers for PTK7.The aptamers
with sequence identity (sgc8, H01, KMF9b, KC2D8) were synthesized as unlabeled or biotin-labelled and detected by flow cytometry. Green line shows the binding of the aptamer of interest. Light blue line shows the binding when the target cells were saturated first with the unlabeled aptamer of interest (10x) and then incubated with labelled aptamer (1x). Purple line indicates the binding when target cells were saturated first with unlabeled sgc8 aptamer (10x) and labelled aptamer of interest (1x) and vice versa (dark blue line). A loss of binding indicates that the unlabeled aptamer (10x) occupied the target region and saturated it, so that the labelled aptamer could not bind and thus no signal was detected. Panel A shows the control experiment with a non-binding sequence and Panel B the experiments with aptamers of interest. B: Biotin, label; Scr-sgc8: Scrambled sgc8, a negative control; Apparent Kd for each aptamer on CCRF-CEM cells is given under the aptamer’s name.
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Figure 4-3. Interaction of PTK7 with DIXDC1b DNA. A) Western blot analysis of various
cellular compartments of HEK293 cells. Full-length PTK7 is ~118kDa, cleaved ~68kDa. GAPDH is a cytoplasmic marker. Lamin B1 is a nuclear membrane marker B)
Figure 4-4. Confocal immunocytochemistry image of HeLa cells co-stained for PTK7
with sgc8-TMR. A) HeLa cells were co-stained with a control sequence labelled with TMR. DAPI staining was applied as the nuclear staining. No nuclear signal for TMR was observed. B) HeLa cells were co-stained with sgc8-TMR. DAPI staining was applied as the nuclear staining.
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Figure 4-5. Electrophoretic mobility shift assay (EMSA) for the ds DNA surrounding the consensus region on DIXDC1b. A)
Schematic representation of the experiment rationale. B) EMSA gel image. Experiment was performed by binding of biotinylated oligonucleotides with either HeLa or Ramos nuclear extracts. Binding reactions as shown were performed using the LightShift Chemiluminescent EMSA Kit. Ebna control system, provided in the kit, was used as an experimental control.
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CHAPTER 5
CONCLUSIONS AND FUTURE DIRECTIONS
Summary and Conclusions
This material could be divided into two main parts: In the first part EV-SELEX
methodology was developed and utilized for the generation of a panel of aptamers
capable of distinguishing exosomes isolated from Hepatocellular carcinoma cell line,
HepG2, from exosomes isolated from human whole blood. However, before starting the
selection process, a serious of exosome isolation and characterization methods were
studied initially. The characterization experiments were actually a preparatory step for
the EV-SELEX. It was necessary to perform a quality check of the target material before
implementing a new methodology. Based on the NTA and western blot results, the
vesicles we isolated were less than 100nm in size and expressing CD 63 marker which
all consistent with exosomes. On the other hand, NTA results also revealed that there
are particles bigger than 200nm indicating the population we collected is not entirely
pure. Next, we used this exosome isolates
In the second part of this study, the interaction between PTK7 and genomic DNA
was elaborated. Whole cell-SELEX method uses a large library of random DNA
sequences (~1015) amplified by unique primers, against 10,000 unique protein targets.
As discussed in introduction part, sgc8c was selected by whole-cell SELEX for a target
T-Cell leukemia cell line, CEM-CCRF, and against a B-Cell leukemia cell line Ramos.
Another aptamer KC2D8, was selected several years later using a colon cancer cell
line, DLD1, as the target, and no negative cell line. In the process of analyzing colon
cancer aptamers he has selected, he noticed that several aptamers had the same
binding profile as sgc8c. These three aptamers, all bound the same cell types with
93
similar affinities, and competed with each other for binding. CLUSTALx alignment
showed sgc8c and KC2D8 share 38 contiguous nucleotides. These two selections used
two different primer pairs to PCR-amplify the portion of the library. The sgc8 aptamer
cannot prime the KC2D8 library, making the chance of contamination by sgc8c during
KC2D8 selection unlikely. A bigger analysis was performed by comparing 148 different
ssDNA aptamer from more than 30 different selections using the software program
ESPRIT. When these sequences were aligned with sgc8c, their similarities were
clustered around a core 15nucleotide GC rich region: GCTGCGCCGCCGGGA
Future Directions
The future directions for the EV-SELEX part of this study could be approached
from two different angels: a) near future studies b) far future studies. So far, a novel
SELEX method was designed, optimized and performed against liver cancer exosomes
and the binding of the aptamers to target and counter exosomes were determined. On
the other hand, the project is still immature and requires a serious of characterization
experiments for the selected aptamers. First of all, binding affinities, Kd, of the selected
aptamers should be determined. In addition, specificity of the aptamers towards
different exosomes, collected from different cancer or normal cell lines should be
elaborated. Finding the target molecule of the selected aptamers on the vesicle could
be the next step of the project. This would also reveal the molecule, specific to the liver
cancer cells. All these experiments discussed so far are actually classic characterization
steps of a newly selected aptamers. The second and a bigger step could be testing
aptamers for clinical use. Firstly, the aptamers can be tested in liver cancer exosome
spiked human plasma in vitro. If the results are promising, then in vivo testing of the
aptamers should be considered. At this point, we are evolving our discussion towards
94
far future studies. Once the aptamers passed all the characterization experiments, there
is a whole new world waiting for them to be discovered.
Generally, conclusions regarding the functional role of exosomes in facilitating
cell-to-cell communication are based on in vitro experiments in isolated culture systems
using concentrations of exosomes that are rough approximations and may not be
physiologically relevant. Therefore in vivo studies to address the functional role of
exosomes in cancer can be studied. Using exosomes to deliver drugs could also offer
new treatment options for the clinic.
Future directions for the second part of this dissertation would be understanding
the molecular mechanism behind the DIXDC1b –Wnt pathway. The progress in this
project is, unfortunately, very slow. The bioinformatic studies indicated that the selecting
aptamers sharing same sequence cannot be coincidence. Yet, proving the unusual
mechanism of PTK7 cleavage, internalization and interacting with genomic DNA to
change DIXDC1 expression is challenging, especially considering there is no such
example has been reported so far. One thing, that needs
In addition, this finding is probably not a one-time occurrence. Our bioinformatic
analysis of 148 DNA sequences selected by whole-cell SELEX identified other
aptamers from disparate selections, like those for Vaccinia infected cells and pure virus,
which share significant sequence identity. Further comparison of existing DNA and RNA
aptamers may yield other examples of SELEX identifying natural DNA or RNA
sequences with functional roles, not initially envisioned. Future selections should also
not be considered complete until the newly selected aptamers are compared with all
other existing aptamers for sequence identity.
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APPENDIX A COMPLEX TARGET SELEX DNA APTAMER DATABASE
96
Table A-1. Complex Target SELEX DNA Aptamer Database
SELEX Target Name Nt Sequence
1 hnRNP-A1 BC-15 74
TGTGGCGAGGTAGGTGGGGTGTGTGTGTAT
2 IgE IgE 21
TTTATCCGTTCCTCCTAGTGG
3 small cell lung cancer 16-1 25
GAATCCTTCTTTGTCCCGGGCCCGT
small cell lung cancer 0-25 25
TACTCAATTACTCTCTTGTCCCTCT
4 Shp2 Phosphatse HJ24 80
GGGGTTTTGGTGGGGGGGGCTGGGTTGTCTTGGGGGTGGG
5 Tenascin-C GB-10 34
CCCAGAGGGAAGACTTTAGGTTCGGTTCACGTCC
6 Mucin S1.3/S2.2 72
GCAGTTGATCCTTTGGATACCCTGG
7 RET Kinase D24 50
GCGCGGGAATAGTATGGAAGGATACGTATACCGTGCAATCCAGGGCAACG
8 Nucleolin AS1411 26
GGTGGTGGTGGTTGTGGTGGTGGTGG
9 IL-17RA RA10-2 30
CTAAGGATCGGATCCACGGCCTACCAGGTC
IL-17RA RA10-6 30
CTTGGATCACCATAGTCGCTAGTCGAGGCT
IL-17RA RA10-7 30
ACGCGCTAGGATCAAAGCTGCACTGAAGTG
IL-17RA RA10-13 30
CCAGAAGAAGCCCACTAGCGTGCTTTTGTC
IL-17RA RA10-14 30
CCAGACGTGAGCACTAGATCAGTACGGAAG
10 NSCLC: A549 v HLAMP S1 45
GGTTGCATGCCGTGGGGAGGGGGGTGGGTTTTATAGCGTACTCAG
NSCLC: A549 v HLAMP S6 45
GTGGCCAGTCACTCAATTGGGTGTAGGGGTGGGGATTGTGGGTTG
NSCLC: A549 v HLAMP S11a 45
AGAGTGGGGGGGTGGGTGGATTTGACAGGTGGCATGCTGGAGAGT
NSCLC: A549 v HLAMP S11b 45
TGGGGTTATTAATTTTGGGTGGGGGGGAAGATGTAGCATCCGACG
NSCLC: A549 v HLAMP S11c 45
AGCTTGAGGGTGGGCGGGTGGACGCGGTAGTGGTATATAGGTCGG
NSCLC: A549 v HLAMP S11d 45
GATCGGTGGGTGGGGGGGTTGGAGATCATCCTCAGGGATTACGTC
NSCLC: A549 v HLAMP S11e 45
ATGCGAACAGGTGGGTGGGTTGGGTGGATTGTTCGGCTTCTTGAT
NSCLC: A549 v HLAMP S11f 45
GGTCGCAGATGGATTAAGTATGTGGGTGGGGGGGTGGAAGTTAAT
NSCLC: A549 v HLAMP S15 45
GCTATCTTATGGAAATTTCGTGTAGGGTTTGGTGTGGCGGGGCTA
11 PigPen III.1 96
AGGCGGTGCATTGTGGTTGGTAGTATACATGAGGTTTGGTTGAGACTAGTCGCA
12 RBC Ghost: CD71 C56t 26
AACTCAGTAATGCCAAGGTAACGGTT
RBC Ghost Motif 2a 33
CGAATCGCATTGCCCAACGTTGCCCAAGATTCG
97
Table A-1. Continued
SELEX Target Name Nt Sequence
13 Differentiated PC12 1 25
TGGTTGGGGATAGAGGTGGGTGTTT
Differentiated PC12 2 25
TGAGGGTCTAGGGTGGTGGGGTGGA
Differentiated PC12 3 25 TGATGGATGTGGGGATGCGGGGGCG
Differentiated PC12 4 25
TATGGGGGTGGGTCAGGTTTCGGTA
Differentiated PC12 5 24
GGGAGGTTGGGGTATCAGGGGGGG
Differentiated PC12 7 25
GGGTGTGGGAGGTGATGGGGTAGGT
Differentiated PC12 8 24
AGGGGGGTTCGGCGGAGGTATCAG
Differentiated PC12 10 25
GCTGGGGTGTTGGGTGTGGGGGTGA
Differentiated PC12 12 25
GTGCGACATAGCTAAACCGGTTCGT
Differentiated PC12 13 25
GAGGAGGGAGAATAGGGGTGGGTGG
Differentiated PC12 14 24
AGTCAGACAGGGGGGAGGATCCGT
Differentiated PC12 15 25
TGGGTAGGTTCGAGGGGTGGGTGTG
Differentiated PC12 16 25
AGAGTGGGGGGGATGTAGGTGGGTT
Differentiated PC12 17 25
GGTTGGATGTAAGGTTGGAGGGGGG
Differentiated PC12 18 25
GTGTCCGTGGACTAAACCGGCCTGT
Differentiated PC12 20 24
GTGGAAGCCTCCTAAGCGGTGTGT
Differentiated PC12 22 24
TGGGTGAGTTCAATGGGGGTATGT
Differentiated PC12 23 25
GGGTGTGAGAGGTTGAGGGGGTTCG
14 Vaccinia Virus A549 TVO1 25
GTGCATTGAAACTTCTGCATCCTCG
Vaccinia Virus A550 TVO2 24
CCTGCATATACACTTTGCATGTGG
Vaccinia Virus A551 TVO4 33
AACCTGCATAATTTATAAGTCTAGACTGCTGCA
Vaccinia Virus A552 TVO6 27
GGACCGATAGGAACCACGGACTGCATG
15 Vaccinia Virus Hela PP2 38
ACACCGTTTGTATTCTGCATTGTTTTGCATTCTACATG
Vaccinia Virus Hela PP5 31
CACTTGCATATACACTTTGCATTATAGGGTG
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Table A-1. Continued
SELEX Target Name Nt Sequence
16 Mucin MUC15TR1 25
GAAGTGAAAATGACAGAACACAACA
Mucin MUC15TR2 25
GGCTATAGCACATGGGTAAAACGAC
Mucin MUC15TR3 25
CAAACAATCAAACAGCAGTGGGGTG
Mucin MUC15TR4 25
TACTGCATGCACACCACTTCAACTA
17 HL60/CEM KH1C12 42
TGCCCTAGTTACTACTACTCTTTTTAGCAAACGCCCTCGCTT
HL60/CEM KHG11 45
TGCTCATCCACGATTCTGGCGAATTTAGTGCCTGTCTTTTTCTCT
HL60 KH2B05 42
CACACAACCTGCTCATAAACTTTACTCTGCTCGAACCATCTC
Ramos KH1A02 44 GGCATAGATGTGCAGCTCCAAGGAGAAGAAGGAGTTCTGTGTAT
Ramos KK1B10 45
GATCAGTCTATCTTCTCCTGATGGGTTCCTATTTATAGGTGAAGC
HL60, NB4, K562/CEM KH1B08 45
TTCAAATCACACGACGCATTGAAACACTCTACAATATCACATTTA
HL60, NB4, K562/CEM KH3H03 45
CTGGCGCCTTCTACTTCAAGGCAATAAGCTCAATCAATATCATCG
18 CEM H01 46
AAGCAGCAGCTGTGCCATCGGGTTCGGATTTTCTTCCTACGACTGC
CEM H04 45
TATCAAAGGCGAATTTTGTCAAGGTGTTAAACGATAGTCCCTACC
CEM, Ramos, Toledo H11 44
TCGCCTGTACATAGACTGTTGCGTTAGGGTCTGCCTTTATCTTG
CEM, Ramos, Toledo B07 44
CATAGAGACTTGGATGCAACTTAGCTACTAACGCTAGCTCTATG
19 Ramos TD05 47
AACACCGTGGAGGATAGTTCGGTGGCTGTTCAGGGTCTCCTCCGGTG
Ramos, CEM, Toledo TD08 85
TACTCTAATTGCCGTATAAGGTCAGGGGGTTGGTTGGTTCCTAGTGCTT
Ramos TE02 44
GCAGTGGTTTGACGTCCGCATGTTGGGAATAGCCACGCCTCGGG
Ramos, CEM TE04 44
CACTCCTCGATGCACCAGTTCACCTTATTTGCTTCTTCTCTCTG
Ramos, CEM, Toledo TE13 42
GCCCCCAGGCTCGGTGGATGCAAACACATGACTATGGGCCCG
Ramos TE17 52
ACCTGCTTGACCGACCGATACAGCTACGCAATACAAAACTCCGAACACCTGC
20 CEM, Ramos, Toledo TC01 33
CCAAACACAGATGCAACCTGACTTCTAACGTCA
CEM TC02 46
AGCATCAACAAGGTCATAAAAACACGTCAGCTCCTTCACATTTGCC
21 CEM, Jurkat sgd3 53
AGGGGGAGCTTGCGCGCATCAAGGTGCTAAACGAAAGCCTCATGGCTTCTATA
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Table A-1. Continued
SELEX Target Name Nt Sequence
CEM, Jurkat, Ramos sgc4a 36
CGAGTGCGGATGCAAACGCCAGACAGGGGGACAGGA
CEM, Jurkat sgc5 45
ACCGACGACGAACTATCTATCACTATCTTACACATCATACCTCGA
CEM, Jurkat sgc7 52
ACCGCAGCGACTATCTCGACTACATTACTAGCTTATACTCCGATCATCTCTA
CEM, Jurkat Sgd2 53
GAGTGAAGCAAGGATGCAACCTCGGCTCCAACCCGTGAGAGTCGCGAAACTCA
CEM, Jurkat, Toledo Sgd5a 66
ACTTATTCAATTATCGTGGGTCACAGCAGCGGTTGTGAGGAAGAAAGGCGGATAA
CAGATAATAAG
CEM, Jurkat sgc8c 41
ATCTAACTGCTGCGCCGCCGGGAAAATACTGTACGGTTAGA
CEM, Jurkat sgc3b 51
ACTTATTCAATTCCTGTGGGAAGGCTATAGAGGGGCCAGTCTATGAATAAG
22 Liver Cancer mouse: IMEA TLS1c 55
ACAGGAGTGATGGTTGTTATCTGGCCTCAGAGGTTCTCGGGTGTGGTCACTCCTG
Liver Cancer mouse: IMEA TLS3 45
TGGGAATATTAGTACCGTTATTCGGACTCCGCCATGACAATCTGG
Liver Cancer mouse: IMEA TLS4 45
ACGGTGGTCGTACACGGCCATTTTATTCCCGGAATATTTGTCAAC
Liver Cancer mouse: IMEA TLS7 45
TGCGCCCAAAGTTCCCATATTGCTTCCCTGTTGGTGAGTGCCGAT
Liver Cancer mouse: IMEA TLS11a 63
ACAGCATCCCCATGTGAACAATCGCATTGTGATTGTTACGGTTTCCGCCTCATGG
ACGTGCTG
Small Cell Lung Cancer HCH07 35
GCCGATGTCAACTTTTTCTAACTCACTGGTTTTGC
23 Small Cell Lung Cancer HCA12 35
GTGGATTGTTGTGTTCTGTTGGTTTTTGTGTTGTC
Small Cell Lung Cancer HCC03 35
CCGGGGACCGGGGCACCGGGGGCCAGTGGCACGGA
Small Cell Lung Cancer HCH01 71
GTCAACCGAATGCGTCAGCTGGATCTTAAAGATTGCATGCGCTCACTATGGGACT
GAGCATCGCACTGGTA
24 Colon Cancer KMF2-1a 42
GAATAGGGGATGTACAGGTCTGCACCCACTCGAGGAGTGACT
Colon Cancer KMF3 42
AGGATAGCCATACCACCGGGGAGTTTATAACGGTACGGTCCT
Colon Cancer KMF9b 46
AGCGCAGCAGCTGTGCCACCGGGAGAATTTACGTACGGCTGAGCGA
25 Colon Cancer KDED1 39
CTAAACAAAATACGAGCAGGGAGACTTCTATCCGATTGT
Colon Cancer KDED2 55
AACTGCTATTACGTGTGAGAGGAAAGATCACGCGGGTTCGTGGACACGGTGGCTT
Colon Cancer KDED3 39
GGGGTGGTTTTCAAAGAGTCTTGCCTGACTCCCCTGTGG
Colon Cancer KDED7 40
GCGGACGCACTTTTAGCAAGCAAGTCGACAATGGAGGTTT
Colon Cancer KDED9 40
GCAACTGAAGCTAGAACTGTGTGGGGTTTGGGGTATAATT
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Table A-1. Continued
SELEX Target Name Nt Sequence
Colon Cancer KDED20 45
TAGGTTGGATAGGGATGGTAGAGCAGGCTAAGCACTTTTTTTTAT
26 Colon Cancer KCHA10a 59
ACGCAGCAGGGGAGGCGAGAGCGCACAATAACGATGGTTGGGACCCAACTGTTTG
GACA
Colon Cancer KCHB10 63
ATCCAGAGTGACGCAGCAGATCTGTGTAGGATCGCAGTGTAGTTGACATTTGATA
CGACTGGC
27 Colon Cancer KC2D3 37
CGGGAAAGGAACAAACTGCTATTAGGTCGCAGGCCGG
Colon Cancer KC2D4 37
CCCACTGGTAGCCATTCCGCCCTTAACCGGGCCATCG
Colon Cancer KC2D8 38
AACTGCTGCGCCGCCGGGAAAATACTGTACGGTTAGTT
Ovarian TOV Cells aptTOVl 45
GATCTGTGTAGGATCGCAGTGTAGTGGACATTTGATACGACTGGC
Ovarian TOV Cells aptTOV2a 42
CAATCTCTACAGGCGCATGTAATATAATGGAGCCTATCCACG
Ovarian TOV Cells aptTOV3 42
CTCACTCTGACCTTGGATCGTCACATTACATGGGATCATCAG
Ovarian TOV Cells aptTOV4 42
GGCACTCTTCACAACACGACATTTCACTACTCACAATCACTC
Ovarian TOV Cells aptTOV5 42
CAACATCCACTCATAACTTCAATACATATCTGTCACTCTTTC
Ovarian TOV Cells aptTOV6 42
CGGCACTCACTCTTTGTTAAGTGGTCTGCTTCTTAACCTTCA
Ovarian TOV Cells aptTOV7 42
CCAACTCGTACATCCTTCACTTAATCCGTCAATCTACCACTC
Ovarian TOV Cells aptTOV8 42
CCAGTCCATCCCAAAATCTGTCGTCACATACCCTGCTGCGCC
Ovarian TOV Cells aptTOV9 42
GCAACACAAACCCAACTTCTTATCTTTTCGTTCACTCTTCTC
29 Ovarian DOV Cells DOV3 37
ATGCAGAGGCTAGGATCTATAGGTTCGGACGTCGATG
Ovarian DOV Cells DOV6 37
AATGTTGGGGTAGGTAGAAGGTGAAGGGGTTTCAGTT
30 Adenocarcinoma: H23 EJD1 42
CCCTCACCACCAAACAACAATATTAGAGACAATGAGTTCCCT
Adenocarcinoma: H23 EJD2 41
AGTGGTCGAACTACACATCCTTGAACTGCGGAATTATCTAC
Adenocarcinoma: H23 EJD4 41
GAAGACGAGCGGCGAGTGTTATTACGCTTGGAAACAACCCC
Adenocarcinoma: H23 EJD5 41
TACGGGCTGGATCCACTGTTACGGCGTGTATCCGCTATCAA
Adenocarcinoma: H23 EJD7 42
CAACTCTTAAGTAAATACCTTTTTCTGGCGTGTAAGAAAATG
Adenocarcinoma: H23 ADE1 42
GGCAAAGCACGACGACATGGTATTACACGAACTACAATCCCT
Adenocarcinoma: H23 ADE2 42
GAGCCCTATCTCACACCGCACCCGCAAACTATCATCCTACAT
101
Table A-1. Continued
SELEX Target Name Nt Sequence
31 Cancer Stem Cells: DU145 CSC01 40
AGGTGGTTTGCTGCGGTGGGCTCAAGAAGAAAGCGCAAAG
Cancer Stem Cells: DU146 CSC08 43
GCTCTGAGCCTAGCTTGACCACTTTTCTTTATTCGCTCTGAGG
Cancer Stem Cells: DU147 CSC13 43
GGGGTGTCGTATCTTTCGTGTCTTATTATTTTCTAGGTGGAGG
Cancer Stem Cells: DU148 CSC17 42
CACCAGCTCCATAACGACACGACCCTCATTCCAACACACAGG
Cancer Stem Cells: DU149 CSC22 43
GTGGGGCTGTGATACTTTACATCTTATTTCTCTAGTGACTAGG
32 Activated Protein C HS02-52G 52
GCCTCCTAACTGAGCTGTACTCGACTTATCCCGGATGGGGCTCTTAGGAGGC
33 Mesenchymal Stem Cells 1MSC 40
CGACTTCGGTTATTACGTTGTTGGCCTCACAAGGACGCCC
Mesenchymal Stem Cells 2MSC 39
CACGATCCAGATGTCATAGTTTAGGCTCTCTCTACTACT
Mesenchymal Stem Cells 3MSC 40
GGCGGGAGGTCACGTTGAGAATTTACGAGGCAGGGGGCAC
Mesenchymal Stem Cells 4MSC 39
GAGGGGCCGCCAAAGCTAGCTCAAGTGATATCCTGTACT
Mesenchymal Stem Cells 5MSC 41
CACCCGTATGCCAAGTCAGATCCAGTGTAGATGCGCGCCCC
Mesenchymal Stem Cells 6MSC 41
CGACACGCGCACGGTTCTCATCAATACTGCCTCGCCGGTAC
Mesenchymal Stem Cells 7MSC 38
CAGCATGCAGAGGCGTCAAATAACGGGACCTCTCGGAC
Mesenchymal Stem Cells 8MSC 53
GGGGAGTGGTGGAGAAAGGCTTACAGGGTAGATAAGGTTCAGGTGCTTCGTTC
Mesenchymal Stem Cells 9MSC 50
GGGTCATTGCAGGGTAAGGTTGGATTTATTGATGCCTCGGAGTTGGGTGG
Mesenchymal Stem Cells 10MSC 50
GTAGGCGTTGCCTTAGTTATTGTTTTGAGGTAGAGCAGAGTTTTACTCAG
Mesenchymal Stem Cells 11MSC 50
CGAGGTGGATGACAGGGTATGTGGATTGGTAGTGTGTTTGGTGCTAACGC
Mesenchymal Stem Cells 12MSC 50
GGAGGAAGGGTTACGGAGGAAGAGTTAGGATCGGTGGGGATGATGATGGG
Mesenchymal Stem Cells 13MSC 50
GGTTTAATGTGTGGGTAGTTGGGCGTGACGGGGTAGTCCTGGGGGTTAGG
Mesenchymal Stem Cells 14MSC 50
GTGGAGTGGCCGTAGTCTGGCCAGGTCCCGTTGGTGATGGGTAGAGTGGG
Mesenchymal Stem Cells 15MSC 50
TTTGCGCTGGATGCGATAACGTGTTCGACATGAGGCCCGGATCCACTCCC
Mesenchymal Stem Cells 16MSC 50
TGTGCTTATGCTCGAGATGGTGTTATCCGTGTTGCCACGATGGGGGGACC
Mesenchymal Stem Cells 17MSC 50
TGGATGGGTGGGCGTAGGTGAGGTGTTGTAAGAGCCTCTCCACAGGTGCG
102
APPENDIX B PREDICTED SECONDARY STRUCTURES OF PTK7 APTAMERS
Figure B-1. Predicted secondary structures for PTK7 aptamers. Green labelled parts depict to the consensus region.
A)H01, B)KC2D8, C)KMF9, D)sgc8
103
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BIOGRAPHICAL SKETCH
Sena Cansiz was born in Ankara, Turkey. She earned her Bachelor of Science
Degree in biology at Middle East Technical University in 2008. She did her master’s in
biotechnology in the same school before starting her PhD studies in chemistry at the
University of Florida (2011) under the direction and guidance of Dr. Weihong Tan. Her
graduate work focused on the development of exosome aptamers and aptamer
protein interactions. She received her PhD in chemistry in 2016.
