COMMITTEE CERTIFICATION OF APPROVED
VERSION
The committee for Carla Jean Kinslow certifies that this is the approved version of
the following dissertation:
GENETIC DETERMINANTS OF NEIL2 TRANSCRIPTION
Committee:
___________________________________
Sherif Z. Abdel-Rahman, Ph.D., Chair
___________________________________
Mary Treinen-Moslen, Ph.D.
___________________________________
Jonathan B. Ward, Jr., Ph.D.
___________________________________
Tapas K. Hazra, Ph.D.
___________________________________
Randa El-Zein, M.D., Ph.D.
________________________________
Dean, Graduate School
GENETIC DETERMINANTS OF NEIL2 TRANSCRIPTION
by
Carla Jean Kinslow, B.A., M.S.
Dissertation
Presented to the Faculty of The University of Texas Graduate School of
Biomedical Sciences at Galveston
in Partial Fulfillment of the Requirements
for the Degree of
Doctor of Philosophy
Approved by the Supervisory Committee
Sherif Z. Abdel-Rahman, Ph.D.
Mary Treinen-Moslen, Ph.D.
Jonathan B. Ward, Jr., Ph.D.
Tapas K. Hazra, Ph.D.
Randa El-Zein, M.D., Ph.D.
March, 2008
Galveston, Texas
Key words: NEIL2, DNA repair, single nucleotide polymorphism
© 2008, Carla Jean Kinslow
Dedicated to my son, Benjamin Ellet-Kinslow and my partner, Jenifer Wagley.
I could not have done this without their love and support.
ACKNOWLEDGEMENTS
I would like to thank my mentor, Dr. Sherif Abdel-Rahman for his patience,
support, open-door, training, and respect he has given to me over the years. I would also
like to thank my committee members: Drs. Jonathan Ward, Mary Moslen, Randa El-Zein,
and Tapas Hazra for their support and advice. I am also grateful to Dr. Jeff Wickliffe and
Dr. Marinel M. Ammenheuser for advice and critical review of the manuscript, as well as
Dr. Golda Leonard for her guidance through this program.
I would also like to thank all my fellow students, especially Courtney Hill for her
time and patience in helping me truly understand my ‘stats’.
The majority of this work was supported in part by a NIEHS Center award
(ES06676), by a John Sealy Memorial Endowment (JSME) grant and by predoctoral
fellowships (to C.J.K. ) from NIEHS (T32-07454). Studies were conducted with the
assistance of the General Clinical Research Center at UTMB, funded by a M01 RR00073 grant from the National Center for Research Resources, NIH, USPHS.
iv
GENETIC DETERMINANTS OF NEIL2 TRANSCRIPTION
Publication No._______________
Carla Jean Kinslow, Ph.D.
The University of Texas Graduate School of Biomedical Sciences at Galveston, 2005
Supervisor: Sherif Z. Abdel-Rahman
The human genome is constantly damaged by reactive oxygen species (ROS)
which produce a multitude of oxidative DNA lesions that can lead to mutations, genomic
instability, and ultimately, to the development of cancer and other diseases. The DNA
base excision repair (BER) pathway is initiated by a DNA glycosylase and subsequently,
includes several other proteins that function in a step-wise fashion to repair the mutagenic
site resulting from oxidative damage. The importance of maintaining the integrity of this
pathway in order to reduce disease risk has been demonstrated by many studies. NEIL2
is a novel BER glycosylase that has been associated with transcription-coupled DNA
repair and has a preference for oxidative products of cytosine. Because this enzyme is
thought to be involved in transcription-coupled DNA repair, it could play a substantial
role in maintaining genomic stability, not only in highly proliferating cells but also in
non-dividing cells, such as nerve cells, that remain transcriptionally active. Thus,
alterations in the expression levels of this gene could impact DNA repair capabilities and
could contribute to disease risk, especially in individuals exposed to mutagenic agents at
the beginning of the study. Genetic determinants that influence NEIL2 transcription,
including cis-regulatory sequences and sequence polymorphisms, were unknown. We
hypothesize that cis-regulatory sequences in the 5’ upstream region of NEIL2 regulate
gene transcript levels and that SNPs proximal to these sequences impact gene regulation
and thus affect DNA repair efficiency, especially in individuals exposed to environmental
mutagens. Consistent with these hypothesizes, we found that individual NEIL2
transcription levels varied by 63 fold amongst individuals and that sequence variations in
the promoter region of the NEIL2 gene influences gene transcription levels. These
sequence variations were also associated with DNA repair capacity of the cell, indicating
a role for NEIL2 in regulation of global DNA repair. By characterizing the underlying
mechanisms that may, in part, be responsible for variations in NEIL2 expression, we have
shown that the NEIL2 promoter contains both negative and positive regulatory regions.
When exposed to oxidative stress, expression from the positive regulatory region is
decreased. Site directed mutagenesis of an NF-kappaB/Sp-1 site in this region abolishes
this transcriptional response to oxidative stress, indicating specific cis-elements were
responsible for alterations in NEIL2 in the presence of oxidative stress. Taken together,
this study provides the first in vivo and in vitro descriptions of the genetic mechanisms
the govern NEIL2 expression.
vi
TABLE OF CONTENTS
PAGE
ACKNOWLEDGEMENTS ............................................................................................... iv
GENETIC DETERMINANTS OF NEIL2 TRANSCRIPTION........................................ vi
TABLE OF CONTENTS .................................................................................................. vii
LIST OF TABLES .............................................................................................................. x
LIST OF FIGURES ........................................................................................................... xi
LIST OF ABREVIATIONS ............................................................................................. xii
CHAPTER 1: INTRODUCTION ....................................................................................... 1
General Background ........................................................................................................... 1
Oxidative DNA Damage and Disease................................................................................. 2
Base Excision Repair (BER) ............................................................................................... 4
The monofunctional glycosylases ............................................................................... 5
Bi-functional-elimination ........................................................................................ 6
Bi- functional -elimination ..................................................................................... 6
NEIL2 ................................................................................................................................. 7
Transcriptional Regulation.................................................................................................. 8
NEIL2 and transcriptional regulation .......................................................................... 9
Redox-sensitive transcription factors ........................................................................ 10
Gene Expression Studies................................................................................................... 11
The luciferase assay system ...................................................................................... 11
Single Nucleotide Polymorphisms and Gene Expression................................................. 12
Biomarkers For DNA Damage ......................................................................................... 13
Mutagen sensitivity assay ................................................................................................. 14
Tobacco-specific nitrosamines.......................................................................................... 15
Site Directed Mutagenesis ................................................................................................ 16
Objectives of the Present Study ........................................................................................ 16
CHAPTER 2: INTERINDIVIDUAL VARIABILITY IN NEIL2 GENE
TRANSCRIPTION LEVELS: INFLUENCE OF SINGLE NUCLEOTIDE
POLYMORPHISMS 5’ UPSTREAM OF THE CODING REGION .............................. 19
Introduction ....................................................................................................................... 19
Materials and Methods ...................................................................................................... 20
Study subjects and collection of blood samples ....................................................... 20
RNA extraction and absolute quantitation of copy numbers of NEIL2 transcript by
AQ-RTPCR ............................................................................................................... 21
Determination of allelic variants in the 5’-upstream region of the NEIL2 gene ....... 22
Cytogenetic cultures for the mutagen-sensitivity assay ............................................ 23
Cell culture harvest and cytogenetic analysis for the mutagen-sensitivity assay ..... 24
Statistical analysis. .................................................................................................... 24
Results ............................................................................................................................... 25
vii
Demographics of the study population. .................................................................... 25
Transcript copy numbers of NEIL2 in isolated human lymphocytes ........................ 26
Association of NEIL2 expression levels with demographic characteristics ............. 28
Relationship between NEIL2 expression and mutagen sensitivity ................................... 31
Discussion ......................................................................................................................... 32
CHAPTER 3: REGULATORY ELEMENTS RESPONSIVE TO OXIDATIVE STRESS
IN THE PROMOTER REGION OF NEIL2, A HUMAN DNA GLYCOSYLASE GENE
........................................................................................................................................... 36
Introduction ....................................................................................................................... 36
Materials and methods ...................................................................................................... 37
Cell culture ................................................................................................................ 37
Mapping of the NEIL2 transcriptional start site ........................................................ 37
Cloning of the NEIL2 5’- upstream region into luciferase reporter vectors ............. 39
Sub-clone constructs of the p1200 and pSTEP3 fragments ...................................... 43
Transient transfection of MRC-5 cells with NEIL2 promoter constructs and
luciferase assay ......................................................................................................... 43
Response of the p1200C and NEIL1 construct to oxidative stress ........................... 44
Statistical analysis ..................................................................................................... 44
Results ............................................................................................................................... 45
Mapping of the NEIL2 transcriptional start site and identification of cis-elements in
the NEIL2 promoter. ................................................................................................. 45
Partial characterization of the NEIL2 promoter region. ............................................ 45
Response of the p1200C construct (-206 to +90 fragment) and pNEIL1-luc to
oxidative stress .......................................................................................................... 49
Discussion ......................................................................................................................... 50
Chapter 4: NEIL2 gene expression is influenced by polymorphic sites as well as an NFkappaB binding motif in the promoter region................................................................... 56
Introduction ....................................................................................................................... 56
Materials and Methods ...................................................................................................... 56
In silico search for putative transcriptional binding sites ......................................... 56
Cell culture, transfection and glucose oxidase treatment.......................................... 61
Statistical analysis. .................................................................................................... 62
Results ............................................................................................................................... 62
CHAPTER 5: CONCLUSIONS ....................................................................................... 70
FUTURE STUDIES.......................................................................................................... 74
Delineation of NEIL2 regulatory motifs ................................................................... 74
Haplotype analysis of the NEIL2 promoter region ................................................... 74
Transfection of NEIL2 promoter constructs into other cell types ............................. 75
Appendix ........................................................................................................................... 76
REFERENCES ................................................................................................................. 80
VITA ................................................................................................................................. 92
Education .......................................................................................................................... 92
viii
Publications ....................................................................................................................... 92
ix
LIST OF TABLES
PAGE
Table I: Selected demographic characteristics of the study population ............................ 25
Table II: Single nucleotide polymorphism (SNP) frequency in the study population. ..... 30
Table III: Relationship between NEIL2 ss74800504 and ss74800505 polymorphisms and
mutagen-induced genetic damage ..................................................................................... 32
Table IV - Primer sequences for luciferase constructs ..................................................... 42
Table V: Forward oligo primers used to introduce point mutations into luciferase
plasmids. ....................................................................................................................... 57
Table VI – point mutations in pSTEP1 or p1200C constructs.......................................... 58
Table VII: Distribution of NEIL2 and XPD expression in the study population. ............ 76
Table VIII: Distribution of ethnicities, high or low NEIL2 and accumulated chromosome
breaks in study population. ............................................................................................... 77
Table IX: Mean luciferase expression in NEIL2 promoter clones. ................................. 78
Table X: Mean luciferase expression in pSV-40-luciferase clones .................................. 78
Table XI: Mean luciferase expression in p1200C clones exposed to GO. ....................... 78
Table XII: Mean luciferase expression in pSTEP1 clones ............................................... 79
Table XIII: Mean luciferase expression in p1200C clones ............................................... 79
Table XIV: Mean luciferase expression in p1200C clone with mutation in the NFkB/Sp1
site. .................................................................................................................................... 79
x
LIST OF FIGURES
PAGE
Figure 1 – Schematic model for the three BER sub-pathways in mammalian cells,
modified and used with permission from Weiderhold et al. (2004). .................................. 5
Figure 2 – Distribution of NEIL2 expression in the study population (n=129).
Individuals having higher than 6900 copies/g of total RNA were designated as “high
expressers” (12%) and those having less than 4150 copies/g total RNA were designated
as “low expressers” (88%). ............................................................................................... 27
Figure 3 (a) – Distribution of NEIL2 expression stratified by ethnicity (grey bars).
*P<0.05 for comparison between White non-Hispanics and other ethnic groups
combined, indicate a significantly higher mean NEIL2 transcript copy numbers in White
non-Hispanic subjects. Values are expressed in mean ± SE. ........................................... 29
Figure 3 (b) Distribution of NEIL2 transcript copy numbers amongst the different ethnic
groups. ............................................................................................................................... 29
Figure 4: RACE methodology .......................................................................................... 39
Figure 5: Schematic representation of the NEIL2 gene and the relative locations of the
promoter fragments isolated, cloned, and sub-cloned into luciferase reporter vectors. ... 40
Figure 6: The DNA sequence, encompassing the pSTEP1 fragment, that includes the
NEIL2 gene sequence flanking 5’ upstream and 3’ downstream of the identified
transcriptional start site (+1). ............................................................................................ 42
Figure 7: A, Luciferase constructs containing DNA fragments of the 5'-regulatory region
that were cloned upstream of the luciferase-coding sequence; B, Promoter activity ....... 46
Figure 8: A, Luciferase constructs containing the pSTEP3 DNA fragment inserted 5’ of a
SV-40 promoter; B, Promoter activity relative to a pSV-40 control vector is shown in
relative light units (RLUs) per mL, normalized to total protein in the sample. ................ 47
Figure 9: A, Luciferase sub-clone constructs containing fragments (A, B, and C) of the
p1200 DNA fragment inserted upstream of luc-coding sequence; B, Promoter activity . 49
Figure 10: Luciferase reporter activity in cells transfected with the p1200C and pNEIL1
constructs and then treated with glucose oxidase (100 ng/mL) for 1, 6, and 12 hrs......... 50
Figure 11: The DNA sequence, encompassing the pSTEP1 fragment, that includes the
NEIL2 gene sequence flanking 5’ upstream and 3’ downstream of the identified
transcriptional start site (+1). ............................................................................................ 61
Figure 12: Promoter activity from pSTEP1 constructs containing site-directed mutations
........................................................................................................................................... 63
Figure 13: Promoter activity from p1200C constructs containing site directed mutations
........................................................................................................................................... 64
Figure 14 Promoter activity for p1200C wild type and p1200C + mutation in NFkappaB
site (104 GtoC) with and without 1 hr GO treatments ...................................................... 65
xi
LIST OF ABREVIATIONS
DNA; deoxyribonucleic acid
RNA; ribonucleic acid
ROS; reactive oxygen species
APE; apurinic/apyrimidinic endonuclease
NF-kappaB; nuclear factor kappa B
OGG1; 8-oxoguanine DNA glycosylase
NTH1; endonuclease III homolog
SNP; single nucleotide polymorphism
LUC; luciferase gene
RLU; relative light units
CAT; chloramphenicol acetyl transferase
CA; chromosome aberration
GO; glucose oxidase
NNK; 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone
PHA; phytohemagglutinin
PBL; peripheral blood lymphocyte
PCR; polymerase chain reaction
AQ-RTPCR; absolute quantitative reverse transcription PCR
xii
CHAPTER 1:
INTRODUCTION
General Background
Just prior to initiation of the Human Genome Project, James D. Watson stated,
“When finally interpreted, the implications of the genetic messages encoded within our
DNA molecules will provide the ultimate answers to the chemical underpinnings of
human existence” (Watson, 1990, p.44). This full sequence of the human genome was
sequenced in 2000 by a private group of researchers headed by J. Craig Venter and very
shortly thereafter by a NIH-backed group led by Fransis Collins (Venter et al., 2001;
Lander et al., 2001). This sequence was thought to somehow, perhaps magically, reveal
the answers to all of our unanswered biological questions (Venter et al., 2001). One of
the most obvious and critical question to answer was, “What makes some people acquire
a disease and others not?” Unfortunately the sequence, itself, did not give researchers the
answer to this broad question but is now allowing molecular epidemiologists to ask more
specific questions, such as“What are the environmental and genetic factors that determine
whether a specific group of people acquire a disease, when other groups do not?”
Because the entire genome is now available for analysis, researchers can identify
subtle, inheritable differences, such as single nucleotide polymorphisms (SNPs, single
base changes occurring in greater than 1% of a population) amongst diseased and nondiseased groups. After establishing associations between SNPs and to disease risk,
scientists are now able to better identify the common genetic and environmental factors
amongst diseased and non-diseased populations. This is the first step in understanding
the dual contribution of biological and environmental factors to disease risk. In this way,
studies showed that individual disease susceptibility does not depend solely on genetic
factors, but environmental factors, including diet, exercise, exposure to toxins, and levels
of stress are important as well.
1
Oxidative stress is one of the most common and the most detrimental
environmental factors linked to disease risk (reviewed by Karihtala and Soini, 2007;
Flora, 2007). Humans are constantly exposed to oxidative stress from both endogenous
and exogenous agents that generate free radicals and reactive oxygen species (ROS), such
as hydrogen peroxide (H2O2), superoxide (O•2-) and the highly reactive hydroxyl (•OH)
radicals (Pages and Fuchs, 2002; Gros et al., 2002). Fortunately, human cells have
inherent mechanisms available to detoxify ROS. These mechanisms include simple
defenses, such as those provided by the antioxidants vitamin C and vitamin E, which
react with, and lessen the reactive nature of the ROS (Evans et al., 2004).
Other
mechanisms involve the actions of detoxifying enzymes, such as superoxide dismutase,
to intercept and neutralize ROS (Evans et al., 2004). The protective effect of the cell is
directly associated with the capability of the cell to remove these damaging molecules;
however, excessive oxidative stress can overwhelm the protective machinery (Hazra and
Roy, 2007; Gros et al., 2002). Excessive amounts of ROS, if not detoxified can cause
severe cellular injury or even cell death (Gros et al., 2002). In the presence of excessive
oxidative stress, ROS attack the DNA, frequently producing pro-mutagenic DNA lesions
(Weiderhold et al., 2004). These lesions have been linked to several disease processes,
including aging and cancer (Gros et al., 2002).
Oxidative DNA Damage and Disease
Mitochondria are the primary intracellular sources of ROS, which are generated
from re-dox reactions during normal cellular metabolism (Evans et al., 2004). ROS are
produced from as much as 5% of the consumed O2 during the process of energy
production in the mitochondria (Hazra and Roy 2007). External sources of ROS include
UV radiation and tobacco smoke (Weston and Harris, 2003; Karihtala et al., 2007)
leading to deregulation and damage. Such sources can increase cellular oxidative stress,
creating an environment conducive to depleting the cellular antioxidant defenses (Weston
and Harris, 2003; Karihtala et al., 2007). In the cytoplasm, ROS can readily enter the
2
nucleus and attack DNA (Pages and Fuchs, 2002). Oxygen radicals can attack various
sites throughout the DNA double-helix, including each of the four bases (Kuraoka et al.,
2007). Oxidative attack on DNA bases can result in at least 80 different forms of DNA
base modifications (Kuraoka et al., 2007).
The frequency, persistence in reactivity, and the large number of oxidized DNA
bases that are produced from ROS can lead to genomic instability. This instability has
been associated with the development of various diseases (Karihtala et al., 2007; Evans et
al., 2004). Cancer is one of the most thoroughly characterized diseases associated with
the effects of oxidative stress (Evans et al., 2004; Flora, 2007). Several oxidized DNA
bases have been identified as appropriate biomarkers for cancer and certain other
diseases, indicating that oxidative DNA damage has a direct impact on disease risk
(Evans et al., 2004). For example, 8-hydroxydeoxyguanosine (8-OH-dG) is a wellcharacterized mutagenic lesion, in addition to being a known biomarker for oxidative
stress (Evans et al., 2004). This damaging lesion has been found in liver cancer, skin
cancer, and lung cancer (Jungst et al., 2004; Nishigori, 2004; Paz-Elizur et al., 2005).
There is also an association between inflammation and elevated levels of 8-OH-dG.
Elevated levels of this lesion were reported in lymphocytes of patients with rheumatoid
arthritis and systemic lupus erythematosus (Evans et al., 2004). The results from several
studies have also suggested that oxidized lesions are associated with neurological
diseases, (including Alzheimer’s, Huntington’s, and Parkinson’s disease) as well as
cardiovascular disease and aging (reviewed by Evans et al., 2004; Flora, 2007).
The removal of oxidized DNA bases is essential in order to prevent diseases that
are associated with these lesions (Fortini et al., 2003). The base excision repair (BER)
pathway recognizes and removes oxidized base lesions; however, inefficiencies in this
enzymatic cascade can result in an accumulation of oxidized bases in DNA, leading to
genomic instability. Epidemiological studies have shown that polymorphisms in several
BER
enzymes,
including
8-oxoguanine
DNA
glycosylase
(OGG1)
and
apurinic/apyrimidinic endonuclease are associated with cancer (Zidnoddiny et al., 2005;
Paz-Elizur et al., 2005; Kiyohara et al., 2006; Li et al., 2007). Specifically, certain non3
synonomous SNPs, that alter structure in the coded protein, in the BER enzyme OGG1
have been associated with reduced activity of this enzyme in humans. This reduced
activity was associated with elevated cancer risk (Fortini et al., 2003). Also, an increased
risk of lung cancer was reported in aging Ogg1 knock-out mice (Sakumi et al., 2003).
Base Excision Repair (BER)
The role of the BER pathway is in preserving DNA integrity and cellular stability
(Krokan et al., 2000). The first step (Step 1) of the BER pathway is the removal of the
damaged base by a DNA glycosylase. This is followed by abasic site priming (Step 2),
gap filling, and ligation (Figure 1, Step 3) of the DNA (Evans et al., 2004). In humans,
there are two groups of DNA glycosylases that initiate the first step. They are defined by
their method of base removal, which is either as monofuctional or bi-functional
glycosylase (Weiderhold et al., 2004; Figure 1).
The importance of this repair process has prompted researchers to investigate
imbalance in expression levels of BER enzymes. For example, Fortini et al. (2003) found
that a burst in activity of alkylpurine-DNA-glycosylase (MPG, a BER enzyme that
removes N-alkylpurines) creates partially repaired sites. Furthermore, up-regulation of
this gene has been seen in breast cancers (Fortini et al., 2003), suggesting that the
imbalance of the enzymes in the BER pathway can potentially lead to un-repaired DNA
damage in cells that, in turn, can lead to increased disease risk.
4
Step 1
Step 2
Step 3
Each sub-pathway is characterized by its respective
glycosylases OGG1 and NTH1, monofunctional glycosylases
(M), or NEIL1 and NEIL2.
Figure 1 – Schematic model for the three BER sub-pathways in mammalian
cells, modified and used with permission from Weiderhold et al. (2004).
The monofunctional glycosylases
Some of the earliest studies on BER suggested a streamlined theory with regard to
the mechanism of oxidized lesion repair, where a specific glycosylase would remove only
one type of oxidized lesion (Izumi et al., 2003).
The types of glycosylases in this
pathway include uracil-DNA glycosylases, which remove uracils from the DNA strand
and 3-methyl-DNA glycosylases, which remove alkylated DNA bases (Korolev, 2005).
Today, it is known that these enzymes are monofunctional glycosylases.
These
glycosylaes use an activated water molecule to catalyze a hydrolytic reaction across the
5
glycosydic bond (McCullough et al., 1999). This removes the damage base and results in
the formation of an abasic site (McCullough et al., 1999; Izumi et al., 2003; Weiderhold
et al., 2004). After this step, the 3’ terminus of the AP site must then be modified to 3’OH prior to complete strand repair. This is accomplished by the action of the APendonuclase (APE) enzyme, followed by final repair of the strand by DNA polymerase
and DNA ligase (Evans et al., 2004).
Bi-functional-elimination
-elimination of oxidized bases is initiated by either the OGG1 or endonuclease
III homolog (NTH1) glycosylases (Weiderhold, 2004).
These are bi-functional
glycosylases that belong to the endonuclease III (Nth) superfamily and have glycosylase
as well as intrinsic lyase activity that can modify the abasic site to an --unsaturated
aldehyde after -elimination (Weiderhold et al., 2004). The --unsaturated aldehyde is
further modified by addition of a 3’OH by APE (Weiderhold et al, 2004). Although both
of these enzymes remove the damaged base by using the same process, the OGG1
enzyme specifically removes the oxidized guanine, 8-oxo-dG, whereas NTH1 removes
oxidized pyrimidines (Weiderhold et al., 2004).
Bi- functional -elimination
In 2002, a new sub-class of DNA glycosylases was characterized in which both
-elimination and AP lyase activity were used to remove and modify the damaged base,
as shown above in Figure 1 (Wiederhold et al., 2004, Hazra, et al., 2002).
Initial
characterization of this novel class of enzymes revealed that these proteins demonstrate
enzymatic activity similar to that of the E. coli enzymes, Nei and Fpg, thus they were
named Nei-like (NEIL) (Bandaru et al., 2002; Hazra et al., 2002a, 2002b; Morland et al.,
2002; and Takao et al., 2002a). The NEILs recognize and remove the damaged base,
leaving an abasic site and a break in the DNA strand (Weiderhold et al., 2004). These
enzymes then catalyze the  elimination at the AP site, which leaves a 3’ phosphate in
the strand break (Weiderhold et al., 2004).
6
This site is further modified by
polynucleotide kinase (PNK) (Weiderhold et al., 2004). An inorganic phosphate is
removed from the 5’ side of the AP site to generate a typical 3’OH, which can be used in
a base addition reaction. Repair of the site is completed by DNA polymerase and DNA
ligase (Weiderhold et al., 2004). Further characterization of the NEILs has shown that
they excise 5-hydroxyuracil (5-OHU) and thymine glycol, as well as 8-oxo-dG
(Wiederhold et al., 2004). To date, three NEIL proteins have been described, NEIL1,
NEIL2, and NEIL3 (Hazra et al., 2002b; Morland et al., 2002).
Of these three, NEIL1 and NEIL2 have been most characterized. These two
proteins have a preference for excising the highly mutagenic 5-hydroxyuracil from a
DNA bubble and from double strand structures, suggesting that they are likely associated
with repair during transcription (Hazra et al., 2002). Specifically, NEIL2 has an affinity
for oxidized cytosine, which is one of the most mutagenic and prevalent of the oxidized
lesions (Dou et al., 2003; Hazra et al., 2002a; Hazra et al., 2002b; Dou et al., 2003). The
results from many studies indicate that NEIL2 holds an influential role in DNA repair.
Thus, an alteration in the amount or the activity of this enzyme could have profound and
long-term impacts on overall genetic stability (Dou et al., 2003; Hazra et al., 2002a;
Hazra et al., 2002b; Dou et al., 2003). Yet, due to its novelty, the factors that could alter
the levels of NEIL2 protein expression and the down-stream affects of such alterations
have yet to be elucidated. The current project investigates these genetic factors and how
they could be related to disease risk.
NEIL2
NEIL2 has quite a unique enzymatic nature.
In addition to its substrate
preference, it has a high affinity for excising damage (such as the DNA lesions
spiroiminodihydantoin and guanidinohydantoin) caused by carcinogenic metals, whereas
other BER enzymes, such as OGG1 and NTH1, have almost no affinity for these lesions
(Hailer et al., 2004). Furthermore, there is growing evidence that the NEIL2 enzyme has
a distinct affinity for repairing lesions in DNA bubble structures (Dou et al., 2003). This
7
is exceptional and is in contrast to other BER proteins, such as OGG1 and NTH1 that
only act on duplex DNA (Dou et al., 2003).
The ability of NEIL2 to repair lesions in
DNA bubble structures suggests that alteration in expression and/or function of NEIL2
could impair the efficiency of repairing oxidative damage during transcription. This also
suggests that NEIL2 could play a particularly important role in DNA repair of highly
proliferating tissues, a hallmark process in cancer development. Consistent with this
suggestion, in a recent study, Broderick et al. (2006) reported an association between a
silent mutation in the NEIL2 gene and increase risk for gastric cancer. This study
suggests a genetic link between NEIL2 and disease risk; however, the mechanisms
underlying this association have not been characterized. Furthermore, to our knowledge,
the genetic factors regulating the expression of NEIL2 have not been investigated. For
example, there are several reported SNPs in the 5’-upstream region of NEIL2; however,
their effects on the transcription of the gene, and/or their associations with disease risk,
are still unknown (National Center for Biotechnology Information, dbSNP).
A growing number of studies have characterized the NEIL2 protein; yet, few
studies have delved into the genetics of this gene. Thus, there are several gaps in
knowledge regarding the understanding of how the transcription of NEIL2 is regulated,
how polymorphisms in the promoter of this gene impact its expression in vivo, and how
changes in its expression could be associated with disease risk. These are gaps in
knowledge that are addressed in the current project.
Transcriptional Regulation
Transcriptional regulation is the most common form of gene control in eukaryotes
(Alberts et al., 2002). Usually, transcription is initiated at or near a specific location in
the template DNA (the start site) (Alberts et al., 2002). Transcription is regulated by
trans-acting proteins (transcription factors) that bind to specific DNA sequence motifs
(cis-acting sequences). Cis-acting sequences can be located in various regions of the
gene, commonly the region 5’-upstream of the transcriptional start site (Hasselbach et al.,
8
2005). The transcriptional regulatory proteins that bind to these sites play a role in
recruiting the transcriptional machinery, such as RNA polymerase, to the start site
(Hasselbach et al., 2005; Gazzoli and Kolodner, 2003). Control of gene expression is
accomplished through a complex interplay between the position of these DNA sequences
and the transcriptional activating proteins that bind to them. In this way, both protein and
DNA sequence are involved in the regulation of gene expression.
The DNA binding motifs not only site for the bind of positive-regulating proteins,
to initiate gene expression, but also for the binding of repressor proteins to silence
transcription (Ogbourne and Antalis, 1998). If there is a sequence change (such as a
polymorphism, for example) in or near one of these DNA motifs, the respective
transcriptional protein element might not recognize it and bind to it, resulting in an
alteration in the levels of transcription. In fact, several epidemiological studies that have
associated promoter polymorphisms in several genes to increased disease risk (Taioli et
al., 2007; Pereira et al., 2007; Hoshi et al., 2007; Wang et al., 2008). On the other hand,
changes in the sequence of these motifs could result in the enhancement of transcription.
This would not always be a favorable response since in a pathway such as BER that
depends on precise interplay of protein function, an excess of one enzyme in the
enzymatic cascade could result in dysfunctional DNA repair. In this way, integrity of the
promoter sequence must be retained in order to maintain proper equilibrium of gene
transcription, thus protein balance.
NEIL2 and transcriptional regulation
During the initial characterization of NEIL2, Hazra et al. (2000 and 2002a)
showed that NEIL2 was differentially expressed in multiple human tissues (Hazra et al.,
2002a; Hazra, et al., 2002b). Although all tissues of an individual have the same gene
sequence, differential gene expression patterns between tissues can be caused by several
factors, including: (1) localized exposure to external sources of cellular stress (such as
tobacco smoke in the lungs), (2) localized cellular damage (such as inflammation at a site
9
of injury), and (3) normal metabolism of that tissue (such as the high rate of metabolism
of muscle cells that creates excess ROS leakage from the mitochondria) (Niess and
Simon, 2007; Ji, 2007). Hazra et al. (2002a) showed that NEIL2 expression was highest
in muscle tissue, suggesting that it may be over expressed in a highly metabolic tissue,
which creates substantial intercellular ROS (Niess and Simon, 2007; Hazra et al., 2002a;
Ji, 2007). Thus, ROS may play a role in up-regulation of the NEIL2 gene. Furthermore,
the differential expression of NEIL2 suggests that it’s level of transcript is not static, thus
it could be affected by external or localized factors. This may be related to regulatory
regions in the NEIL2 gene that may respond to different cellular conditions found in
different tissues.
As such, the patterns of protein expression may vary amongst
individuals, and amongst other tissues, if there are SNPs in cis-acting motifs found in the
5’-upstream region regulating level of gene expression. Such a sequence change could
impact the binding affinity of the trans-acting proteins, resulting in a differential
expression of the transcript (Wang et al., 2006). Such alterations were exemplified in a
study of the ABCB1 gene, where 5’-upstream haplotype (a set of closely linked
polymorphisms) appears to be associated with a decrease in transcription levels in HeLa
(epithelial) cells, but with an increase in levels in HEK293 (kidney) cells (Wang et al.,
2006). The transcript of NEIL2 could be regulated in a similar manner by SNPs in the in
the promoter region of the NEIL2 gene.
Redox-sensitive transcription factors
There are several groups of transcriptional proteins that are activated during
increased oxidative stress, but the most characterized include nuclear factor kappa-B
(NF-kB), activator protein-1 (AP-1), and the p53 family of proteins (Evans et al., 2004;
Rahman, 2003; Marthy-Hartert et al., 2003). Of these, NF-kB and AP-1 are associated
with the expression of various DNA-repair-related associated proteins such as NEIL1,
ERCC1, MGMT, and APE (Li et al., 1999; Das et al., 2005; Boldogh et al., 1998, Xu et
al., 1997). Several studies have shown that ROS induces DNA repair by mechanisms
10
mediated by transcription factors (Evans et al., 2004). Das et al. (2005) has shown that
NEIL1 gene expression is induced by acute exposure to glucose oxidase (a strong ROS
generator), suggesting that the genes in this sub-pathway respond to oxidative stress (Das
et al., 2005). Excessive oxidative DNA damage has been shown to block transcription of
the BER glycosylase, OGG1 (Hailer-Morrison et al., 2003). However, how such a
situation affects the NEIL2 gene is unknown.
Gene Expression Studies
The luciferase assay system
The firefly luciferase protein was initially purified in 1978, and functional
characterization of this very stable bio-luminescent protein soon followed (DeLuca and
McElroy, 1978). A decade later, the gene was cloned from a gt11 Photinus pyralis
cDNA library by De Wit et al. (1987). This began a new and dynamic direction for
mammalian expression studies with the development of the luciferase expression system
(De Wit et al., 1987). This expression system overcame several short-comings of other
expression systems such as bacterial -galactosidase (-gal) and chloramphenicol acetyl
transferase (CAT). The advantages of luciferase over these other systems include easier
one-step quantification of promoter activity, increased protein stability, higher sensitivity,
lower requirements of initial material (1/10 the cells used in the CAT system), and a
shorter time from transfection to quantitative measurement of promoter activity
(Williams et al., 1989). Since then, the design and application of the firefly luciferase
gene in genetic reporter systems have contributed greatly to the understanding of gene
expression and regulation (Gould and Subramani, 1988).
For use in most gene expression studies, the luciferase reporter gene is joined to a
promoter sequence in an expression plasmid. The newly constructed plasmid is then
transfected into living cells and then the cells are assayed for the presence of the reporter
gene by measuring the enzymatic activity of the reporter protein. This technique allows
for gene expression to be assayed within a human cell under a host of experimental
11
conditions. The luciferase reporter gene is very close to an ideal reporter gene for our
studies because it is not endogenously expressed in mammalian cells, is a sensitive assay
that is quantitative, rapid, easy, reproducible and safe (Gould and Subramani, 1988).
In the current studies, this reporter assay system was utilized to characterize the
NEIL2 promoter region.
Briefly, fragments of genomic DNA corresponding to the
putative NEIL2 promoter region were cloned in front of the luciferase gene and then
evaluated by promoter-driven expression of each fragment. The design of this assay
system allowed for the evaluation of expression from various plasmids that contained
engineered polymorphisms as well as the ability to evaluate NEIL2 promoter-driven
expression during conditions of cellular oxidative stress.
Single Nucleotide Polymorphisms and Gene Expression
Single nucleotide polymorphisms (SNPs) are single base differences in the DNA
strand that occur at a frequency greater than 1% in the population (National Center for
Biotechnology Information, online SNP database; Weiss, 1998). A SNP can occur in
several places throughout a gene. Many of the SNPs that have been reported occur in the
non-coding regions. For several genes, SNPs in promoter sequences result in alterations
in gene expression (Wang et al., 2006; Kim et al., 2006; Southam et al., 2007;Faniello et
al., 2006). In a number of studies, significant increases or decreases in gene expression
in the presence of promoter SNPs have been described (Wang et al., 2006; Kim et al.,
2006; Southam et al., 2007; Faniello et al., 2006). Because promoter regions contain
both positive and negative regulatory sequences, promoter SNPs have been associated
with increased as well as decreased expression (Wang et al., 2006; Kim et al., 2006;
Southam et al., 2007;Fanielle et al., 2006). A single base change could cause an increase
in expression by creating a new protein binding site or by enhancing the binding of a
transcriptional protein to a DNA sequence. Alternatively, it may abolish the binding of a
positive regulatory protein or even create a site for the binding of a negative regulatory
protein, resulting in decreased gene expression.
12
Thus, a change in expression is,
presumably, due to an alteration in factor binding due to modification of the DNA
sequence. Precedents are known for several DNA repair genes, including MSH6 and
Rad51 (Gazzoli and Kolodner, 2003).
For example, there is a polymorphism that
disrupts a Sp-1 binding site of the MSH6 repair gene promoter and results in a 50% drop
in expression (Gazzoli and Kolodner, 2003). Several researchers have reported a possible
link between the presence of 5’-upstream SNPs in DNA repair genes and progression of
cancers such as gastroesophageal, breast, and melanoma (Hasselbach et al., 2005, Tan et
al., 2005, and Egyhazi, 2002).
Furthermore, there is a growing body of epidemiologic data associating promoter
polymorphisms to disease risk (Villard, 2004; Taioli et al., 2007; Pereira et al., 2007;
Hoshi et al., 2007; Wang et al., 2008). In patients with the disease hemophilia B Leyden,
a mutation at the -20 site (20 base pair 5’ of the transcriptional start site) disrupts the
binding of hepatocyte nuclear factor 4 (NFN4) (Villard, 2004).
This prevents the
transcription of plasma factor IX. Thus, these individuals do not have some of the
essential clotting factors (Vallard, 2004). Other examples of promoter polymorphisms
that are associated with disease include a SNP in the tumor necrosis factor alpha (TNF
promoter that result in an increased risk of death from cerebral malaria and a SNP
producing a promoter variant of the CCR5 gene (which encodes for a cell surface
chemokine) that is associated with the progression of AIDS (Vallard, 2004), however the
exact mechanisms are not known.
Biomarkers For DNA Damage
Biomarkers are measurable characteristics that can be used as indicators of
biological response (Dalle-Done et al., 2006). Biomarkers often are selected as a means
to identify subtle cellular changes that occur early in a well-characterized disease
pathway (Dalle-Done et al., 2006). Important characteristics of biomarkers are that they
can be objectively evaluated, have a high specificity, and are not too invasive for use in
13
an in vivo investigation (Dalle-Done et al., 2006). In the present study, chromosome
aberrations were used as a biomarker of early biological effect.
Chromosome aberrations (CA) are distinct changes in chromosome structure,
such as strand breaks and rearrangements (Bonassi, 1995). They are indications of
dynamic genotoxicity and are the only biomarker that has been shown to be a predictor of
cancer susceptibility (Hagmar 1994; Bonassai, 1995; Bonassai and Hagmar, 1998).
Several studies have shown that environmental sources of reactive oxygen species, such
as tobacco smoking and ionizing radiation, are associated with genomic instability and
chromosome aberrations (El-Zein et al., 2000; Jones et al., 2007; Williams et al., 2005;
Luo et al., 2004).
Mutagen sensitivity assay
The mutagen-sensitivity assay is a well-established technique that has been used to
elvaluate an individual’s response to the mutagenic effects of using cells from that
individual, (reviewed by Wu et al., 2005). This assay, developed by T.C.Hsu in 1989, is
based on isolating cells, such as peripherial blood lymphocytes (PBL’s), from an
individual and then exposing these cells to genotypic compounds. After exposure, cells
are evaluated for genotoxic effects, such as chromosome aberrations or sister chromatid
exchanges. This assay reflects an individual’s sensitivity to the mutagen used in the
assay, as well as the DNA repair capacity of that individual. This assay has been used in
several studies to show that PBL’s from subjects with tobacco-related cancer have higher
mutagen-sensitivity when compared to the cells of non-cancer control subjects (Wu et a;.,
2006; Shen et al., 2003). Furthermore, a study by Blasiack et al., (2004) reported that
PBL’s of breast cancer patients have reduced DNA repair kinetics and increased DNA
damage following exposure to hydrogen peroxide (a strong ROS generator) and
doxorubicin. Thus, we chose to use this assay to test the PBL’s from our population for
genotoxic effects of the tobacco-specific mutagen, using the tobacco-specific nitrosamine
4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) as our mutagen.
14
Tobacco-specific nitrosamines
Cigarette smoke contains over 60 carcinogens (Hoffmannet al., 2001). The
tobacco-specific nitrosamine 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) is a
strong pulmonary carcinogen and a potent inducer of lung adenocarcinoma, now the
leading lung cancer subtype in the United States (Thun et al., 1997). NNK induces lung
cancer independent of route of administration, in both susceptible and resistant strains of
mice (Hecht and Hoffmann, 1989). Studies on the metabolism of NNK have shown that
it induces cross-links in DNA; interacts with DNA, forming different types of adducts;
and increases the frequency of chromosome aberrations (Weitberg and Corvese, 1993,
Berwick and Vineis, 2000).
DNA adducts are generated by NNK through the
methylation or the pyridyloxobutylation pathway. Another study by Chuang and Hu
(2006) has shown that preincubation of stimulated white blood cells with NNK, followed
by UV irradiation synergistically increased DNA damage, lipid peroxidation, and the
level of intracellular ROS.
Thus, exposure to NNK can cause a diverse genotoxic
response, resulting in various types of DNA adducts and lesions. Many of these adducts
have been detected in cells and tissues susceptible to NNK carcinogenesis in rodents and
humans (Hecht, 1999). Therefore, maintaining the integrity of the cellular DNA repair
process is essential in protecting the cell from genomic instability that results in
carcinogenesis.
The repair kinetics for NNK-induced genetic damage has not been
clearly elucidated but may involve several DNA-repair pathways, including base excision
and nucleotide excision repair pathways (Cloutier et al., 2001). In the current study, we
used NNK to induce genotoxic effects in th ePBL’s of our population.
15
Site Directed Mutagenesis
Site-directed mutagenesis is a molecular technique that enables the researcher to
make a deliberate, one base pair change in a sequence, while leaving the remaining
sequence unchanged. This technique was initially developed in 1974 by Flavell et al. and
since then, has been used in thousands of experiments (NCBI, 2008), thus it has become
one of the essential molecular techniques used today. This technique was used in the
present study to introduce single base changes in the NEIL2 promoter luciferase reporter
plasmids at the locations of previously reported SNPs. In this way, the effects of a single
base change on the relative activity of the promoter were characterized, independent of
other SNPs within the sequence. The effects of combinations of these SNPs engineered
into these constructs were also be characterized.
Objectives of the Present Study
The objective of the current study was to address a number of gaps in the
understanding of NEIL2 transcriptional regulation as well as its potential role in disease
risk. In order to better understand the effect of variation in NEIL2 gene transcription on
levels of genetic damage in humans, an absolute quantitative reverse transcription PCR
(Q-RT-PCR) analysis of NEIL2 gene expression within a population of smokers and nonsmokers was conducted. The hypothesis is that NEIL2 transcription varies considerably
among individuals, and that this variability is influenced by genetic, as well as, by
environmental factors. A secondary hypothesis is that reduction in transcription is
associated with increased genetic damage in subjects exposed to environmental
mutagens, such as those found in tobacco smoke.
In order to characterize the underlying genetic mechanisms that could, in part, be
responsible for variation in NEIL2 expression, an in silico analysis was performed using
the web-based TESS (Transcriptional Element Search System). This web-based software
program was used to search the sequence proximal to the NEIL2 start site and is designed
to identify cis-regulatory sequences corresponding to various transcription factors. The
results of this analysis will be used to generate a putative map containing the locations of
16
the cis-regulatory sequences in the NEIL2 5’-upstream region. This map was used to
guide the generation of luciferase reporter vectors encompassing regions of the NEIL2
upstream region that are rich in cis-acting motifs. These reporter plasmids were tested in
an in vitro luciferase reporter assay system and the level of reporter gene expression was
related to the impact of each sequence on gene expression. The hypothesis was that
NEIL2 transcript level is regulated by the sequence located 5′-upstream of the
transcriptional start site. The premise was that the cis-acting regulatory motifs located
within this 5’ upstream region that govern this transcriptional regulation can be identified
by applying site directed mutagenesis to alter the putative regulatory sequence in the
reporter plasmid. The level of promoter-driven expression from these mutated plasmids
was then addressed in vitro and related to that of the wild-type plasmids.
In order to integrate the information generated from the studies above, an a priori
exploratory genotype-phenotype analysis was performed using lymphocyte samples from
a study population composed of healthy individuals. A sub-population of individuals was
selected for sampling and a fragment in the NEIL2 promoter region was sequenced. The
frequencies of SNPs was evaluated for associations with numbers of NEIL2 gene
transcripts and with mutagen sensitivity. Results from these analyses drove further
investigations towards a mechanistic understanding of how the associated promoter SNPs
in NEIL2 could be associated with these factors.
The mechanistic relationships of relevant SNPs was studied in vitro using site
directed mutagenesis and the luciferase expression system. NEIL2 reporter plasmids that
were created in the studies described above, were used as templates for site-directed
mutagenesis to introduce SNPs into the promoter fragment of the plasmids. The effect of
each of the SNPs on luciferase-driven expression was tested in vitro. These experiments
will provide a mechanistic explanation for associations with either NEIL2 expression or
mutagen-induced genetic damage observed in vivo.
Collectively, results from these experiments will provide a linear mechanistic link
between levels of NEIL2 expression variability in vivo and the genetic factors that are
responsible for such differences in NEIL2 expression. From a scientific perspective, the
17
goal was to provide a better understanding the factors regulating this important gene.
From a public health perspective, the goal was to help identify sub-groups of the
population that could be at a higher risk of disease from external environmental factors
that increase levels of RIS, such as those associated with tobacco smoking.
18
CHAPTER 2:
INTERINDIVIDUAL VARIABILITY IN NEIL2 GENE
TRANSCRIPTION LEVELS: INFLUENCE OF SINGLE
NUCLEOTIDE POLYMORPHISMS 5’ UPSTREAM OF THE
CODING REGION
Introduction
Several SNPs have been reported in genomic regions located 5’ of the coding
region of the NEIL2 gene (NCBI on line data base, 2008). These SNPs, designated as
regulatory SNPs (rSNPs), could affect transcriptional regulation (Mottagui-Tabar et al.,
2005, Cheung et al., 2005; Mohrenweiser, 2007). The regions contain key transcriptional
regulatory elements (cis-elements) that encode short (less than 25 bp) sequences that
serve as binding motifs for important transcriptional proteins (Mottagui-Tabar et al.,
2005, Cheung et al., 2005; Mohrenweiser, 2007). Regulatory SNPs have been reported in
various DNA repair genes, and studies have clearly indicated that these rSNPs could
seriously impact the regulation of gene transcription (Mohrenweiser, 2007; Hasselbach et
al., 2005; Tan et al., 2005), and accordingly, could affect disease risk (Wang et al.,
2006a; Wang et al., 2006b; Wang et al., 2006c; Lu et al., 2007; Hu et al., 2007).
Nevertheless, rSNPs in the 5’ upstream regions of DNA repair genes have not been
thoroughly studied with respect to disease risk compared to SNPs in the coding regions.
The effects of SNPs in the 5’ upstream region of the NEIL2 gene on gene
transcription and/or their associations with disease risk, either individually or as a part of
common haplotypes, are still unknown. In the current study, we test the hypothesis that
NEIL2 transcription is influenced, at least in part, by the inheritance of SNPs in the
5’region of the gene. In addition, we also test the hypothesis that perturbation of NEIL2
expression is associated with increased genetic damage in individuals exposed to
genotoxic environmental agents such as those found in tobacco smoke. In the current
studies, the mutagen-sensitivity assay (Hsu et al., 1989) was used, with the tobaccospecific nitrosamine, 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) as the test
19
mutagen. This assay measures the DNA repair capacity of cells exposed to this mutagen.
NNK stimulates the formation of ROS (Kim and Wells, 1996; Rioux and Castonguay,
2000; Wells et al., 1997; Chuang and Hu, 2006) that form oxidative DNA lesions, as well
as strand breaks and chromosome aberrations (Chuang and Hu, 2006; Weitberg and
Corvese, 1993; Affatato et al., 2004; Wolfe et al., 2007). We chose to look at the
formation of chromosome aberrations as our endpoint for genetic damage. This approach
has been utilized successfully by several groups, including ours, as a marker of disease
susceptibility and to elucidate the genotype-phenotype relationships (Abdel-Rahman et
al., 2000; Affatato et al., 2004; Wolfe et al., 2007; El-Zein et al., 2006).
Materials and Methods
Study subjects and collection of blood samples
A total of 129 subjects participated in the current study. They were recruited from
the staff and student population of the University of Texas Medical Branch (UTMB) in
Galveston, Texas.
The subjects were volunteers who responded to posted notices
throughout the campus, and who were recruited without regard to age, sex, or ethnicity.
Individuals were defined as non-smokers if they had smoked less than 100 cigarettes
during their lifetime. Individuals were defined as smokers if they had smoked at least 5
cigarettes per day for at least one year prior to enrollment in the study. All study subjects
were asked to fill out a questionnaire that provided demographic, occupational, and
medical information. Additional information that was collected included details about
smoking habits, such as the number of cigarettes smoked per day, preferred brand,
duration of smoking, former tobacco use, and use of other tobacco products. All subjects
signed a consent that was approved by the UTMB Institutional Review Board and that
described the purpose of the study, which is to understand the functional and biological
significance of sequence variability in DNA repair genes. Exclusion criteria for all
volunteers included a recent acute viral or bacterial infection, a major chronic illness such
as cancer or an autoimmune disorder, recent blood transfusion, treatment with mutagenic
agents such as chemotherapy or radiotherapy, excessive alcohol consumption, and
20
employment involving exposure to potentially mutagenic chemicals (such as polycyclic
aromatic hydrocarbons and nitrosamines) or radiation. Because of these criteria, only
apparently healthy volunteers were included in the study to control for potential
confounders. After informed consent was obtained, a 50-70 ml blood sample was drawn
from each volunteer. A portion of this blood sample was used for DNA extraction for
analysis of genetic variations located upstream of the NEIL2 transcriptional start site
(identified as the region in chromosome 8 from location 11,663,721 bp to 11,664,692 bp).
Another portion was used for RNA isolation and gene expression quantization using
absolute quantitative reverse transcription PCR (AQ-RTPCR). The remainder of the
blood sample was used for the mutagen-sensitivity assay and, also, for lymphocyte
isolation and cryopreservation to provide cells for future studies.
RNA extraction and absolute quantitation of copy numbers of NEIL2
transcript by AQ-RTPCR
Lymphocytes were isolated from whole blood, as previously described (Affatato
et al., 2004; Wolfe et al., 2007; Abdel-Rahman, 2000; El-Zein et al., 2000). Total RNA
was isolated from 20x106 frozen lymphocytes using the RNaqueous RNA isolation kit
(Ambion, Inc., Austin, TX). RNA samples were initially quantified using a Nanodrop
Spectrophotometer (Nanodrop Technologies, Wilmington, DE) and qualified by analysis
on an RNA Nano chip. The RNA was further quantified from this chip by using an
Agilent 2100 Bioanalyzer (Agilent Technologies; Santa Clara, CA). One µg of total
RNA and a NEIL2 mRNA-specific oligo probe, engineered based on data from the NCBI,
(Bethesda, MD; NEIL2 accession number NM 145043.1) was used for each reverse
transcription reaction. The TaqMan® Reverse Transcription Reagents Kit (ABI, Foster
City, CA) was used to generate cDNA for the Q-PCR amplifications. The primers for
amplification of NEIL2-specific cDNA were 5’GCTATACACTGCTGGACCAGAGATAC-3’ (forward) and 5’GATGGATCCCAGCTCTGTACAAG-3’ (reverse). The fluorescent TaqMan® probe
used for quantification of the NEIL2 transcript was 5’-6FAMCAGGGCTAGGGAACAT-3’. The AQ-RTPCR amplifications (performed in triplicate)
21
were done with 2µl of cDNA in a total volume of 25µl, using either TaqMan MGB
probes with the TaqMan Universal PCR Master Mix (ABI) or using SYBR green with the
SYBR Green PCR Master Mix (ABI), as specified by the manufacturer. The final
concentration of the probe was 250 nM and that of the primers was 900 nM. Absolute
quantitation of copy numbers was performed using known amounts of a synthetic
transcript of NEIL2 that was generated by amplifying a 1.0 Kb fragment from NEIL2
cDNA in pET 22b using primers 5’- GAATTCATGCCAGAAGGGCCGTTGGTGAG-3’
and 5’- AAGCTTAGGAGAACTGGCACTGCTCTGGC-3’. The PCR conditions were:
denaturation 94ºC, 30 sec; annealing 62ºC, 30 sec; 20 cycles; then synthesis 72ºC, 4 min.
A TA clone using the TA Cloning Kit (Invitrogen, Inc., Carlsbad, CA) was created with
this fragment, and the integrity of the fragment was verified through direct sequencing.
The NEIL2 fragment was then sub-cloned into an EcoRI/HinDIII site of the plasmid
T7PA. All PCR assays were run in the ABI Prism 7000 Sequence Detection System
(ABI) and the conditions were: 50ºC, 2 min; 95ºC, 10 min; 40 cycles: 95ºC, 15 sec; 60ºC,
1 min. Fifteen percent of the samples were randomly selected for a second AQ-RTPCR
in order to ensure accuracy of the analysis. For a positive control, we evaluated
expression of the XPD gene in the same samples using AQ-RTPCR, since we have
previously shown that XPD expression was decreased in smokers relative to non-smokers
(Wolfe et al., 2007). In addition, a sub-set of cells from individuals with previously
characterized XPD gene expression levels were used as positive controls for the current
study.
Determination of allelic variants in the 5’-upstream region of the NEIL2 gene
A 1113 bp fragment of the NEIL2 5’- upstream region was amplified using PCR
primers (upper primer 5’-GGCTCCCCATCCTCCTT-3’ and lower primer 5’GGCCCGCCCTCCCTTCCT-3’). This fragment was sequenced in both directions using
the upper and lower primers described above, as well as two internal primers (internal
lower primer 5’-TGGCGCCCGGCTAATTTTTGTAT-3’ and internal upper primer 5’TAGCCGGGCGCCAGTAATCC-3’).
These sequences were aligned using DNAsis
22
software (Hitachi, Inc., US) and compared with the known sequence from the NCBI
database. Genotype and allelic frequencies were determined from these data.
Cytogenetic cultures for the mutagen-sensitivity assay
Cell cultures were established according to standard procedures (Wolfe et al.,
2007; El-Zein et al., 2000; Hill et al., 2005). In brief, aliquots of 1 ml of blood were
cultured with 9 ml of RPMI 1640 medium supplemented with 100 U/ml penicillin, 100
µg/ml streptomycin, 10% fetal bovine serum, and 2% L-glutamine (Gibco-Invitrogen,
Carlsbad, CA).
Stimulation of the peripheral blood lymphocytes (PBLs) was
accomplished by the addition of 1% phytohemagglutinin (PHA, reagent grade; Remel,
Lenexa, KS). Two cultures were set up in parallel for each study subject; one culture was
untreated to represent baseline in vivo chromosome aberration (CA) frequency, and the
second culture was used for the mutagen-sensitivity assay. After 46 hours, the cells were
centrifuged and the growth medium reserved. The PBLs were then resuspended in 5 ml
serum-free RPMI 1640 supplemented with 0.24 mM NNK (98% purity; CAS No 6409191-4, National Cancer Institute, Midwest Carcinogen Repository, Kansas City, MO) and
incubated at 37oC in the presence of 5% CO2 for 1 hr. Following NNK treatment, the
cells were washed twice with serum-free RPMI 1640, transferred to clean tubes, and
resuspended in the original growth medium until harvested. Harvesting was performed at
24 hrs after NNK treatment. Cultures for baseline determination did not receive the NNK
treatment. The NNK concentration, exposure duration and harvest time had been
established by previous studies (Affatato et al., 2000; Wolfe et al., 2007; Abdel-Rahman
et al., 2000; El-Zein et al., 2000; Hill et al., 2005) to produce measurable levels of genetic
damage and low levels of toxicity over a period of time that allows the effects of DNA
repair to be manifest.
23
Cell culture harvest and cytogenetic analysis for the mutagen-sensitivity assay
Prior to harvesting, cells from all cultures were treated with 0.1 µg/ml colcemid
(Gibco-Invitrogen) for 1 hr to arrest the cells in metaphase.
The cultures were
centrifuged and the cells resuspended in hypotonic solution (0.075 M potassium
chloride), fixed with Carnoy’s fixative (3 parts methanol/1 part acetic acid, vol/vol), and
stored at 40oC. Slides for cytogenetic analysis were prepared, stained with Giemsa, and
air dried. Slides were then coded to protect against scorer bias. One hundred metaphase
cells on each slide were scored for CA’s, according to standard procedures (International
System for Human Cytogenetic Nomenclature), using a Nikon 400 light microscope.
Aberrations were recorded as chromosome breaks or chromatid breaks. Chromatid breaks
were counted as one break and chromosome breaks as two breaks. The average number
of breaks/100 cells was then calculated.
Statistical analysis.
The Student's t-test, Chi-square, ANOVA, and Aspin-Welch Unequal-Variance Test were
used, when appropriate, to compare the mean or median SNP frequencies, between high- and
low-NEIL2-expressing groups.
Analysis of variance and the Tukey–Kramer multiple
comparison tests were used to test differences in CA and NEIL2 expression levels between
groups as a function of NEIL2 genotypes. We tested the effects of the SNPs on expression levels
using a dominant model. Pearson’s correlation was used to correlate replicates for the AQRTPCR. We also conducted linkage disequilibrium (LD) analysis between the SNPs using
Linkage Disequilibrium Analyzer ver. 1.0 (Keyue et al., 2003). The degree of LD among the
SNPs was measured using Lewontin’s D′. Statistical tests of the significance (P < 0.05) of LD
among these SNPs were conducted using a Likelihood-Ratio test. All statistical analyses were
performed using NCSS 2004 (Kaysville, UT).
statistically significant.
24
A two-sided
P<0.05
value was considered
Results
Demographics of the study population.
Selected demographic information for the study population is presented in Table
I.
Table I: Selected demographic characteristics of the study population
____________________________________________________________________
N (%)
Agea
Age range
All subjects
129 (100)
41.60 (1.07)
21-73
Sex
Male
30 (23)
42.73 (2.21)
23-73
Female
99 (77)
39.95 (1.22)
21-65
Smoking status
Smokers
69 (53)
40.10 (1.61)
21-73
Non-Smokers
60 (47)
41.17(1.38)
22-72
Ethnicity
White non-Hispanic 92 (71)
African American
16 (12)
Hispanic
10 (8)
Asian
10 (8)
Native American
1 (1)
________________________________________________________
a
Age in years, expressed as mean (±SE) .
The majority of the study subjects were White non-Hispanic (71%). The
remaining subjects (29%) were African American, Hispanic, Asian, and one Native
American. There were more females (77%) in the study than males. There was no
significant difference between the mean ages of the females (mean ± SD=39.95 ± 12.10)
compared to the males (mean ± SD =42.73± 12.10). There were 69 non-smokers and 60
smokers.
There was no difference between the ages of smokers and non-smokers.
Smoking intensity, expressed as pack years (defined as the number of packs of cigarettes
smoked per day times the number of years of smoking) ranged between 1 and 75 pack
years, with a median of 10 pack years (mean pack years ±SE =16±2.3). There was no
significant difference in the smoking habits (number of years of smoking, number of
25
cigarettes smoked per day, and pack years) between the different ethnicities. The age of
the participants ranged between 21 and 73 years, with a median age of 42 years.
Transcript copy numbers of NEIL2 in isolated human lymphocytes
The absolute transcript copy number of NEIL2 in PBL samples from of all the
study participants (N=129) was measured using AQ-RTPCR.
To verify the
reproducibility of our assay, we randomly repeated the quantization of NEIL2 transcript
copy numbers for 15% of the samples. A correlation coefficient of 0.88 (P<0.001)
between the two series of measurements was obtained. The NEIL2 expression level
varied up to 63 fold in the study population, with a range of NEIL2 transcript copy
numbers between 429 and 27,183 copies/g total RNA. The mean number of copies ± SE
of the NEIL2 transcript in the study population was 3438±397. This variability was not
normally distributed. Visual examination of the data (Figure 2) revealed a distribution of
NEIL2 expression levels in the population that segregated into two distinct categories.
26
Dot Plot
NEIL2 transcript/g total RNA
30000.0
20000.0
High expresser
10000.0
Low expresser
0.0
NEIL2_expressio
Variables
Figure 2 – Distribution of NEIL2 expression in the study population (n=129).
Individuals having higher than 6900 copies/g of total RNA were designated as “high
expressers” (12%) and those having less than 4150 copies/g total RNA were designated
as “low expressers” (88%).
In the first category, which included the majority of the subjects (N=114), the
transcript copy numbers were all less than 4150, with a range of 429 to 4139 copies. In
the second category, which included 15 subjects (12% of the total population) the NEIL2
transcript copy numbers were all greater than 6900, with a range of 6972 to 27,183
copies/μg of total mRNA (Figure 2). Based on this distribution, all individuals exhibiting
an expression value above 6900 copies of NEIL2/μg total RNA were designated as “high
expressers” and individuals with a value lower than 4150 copies/μg total RNA were
designated as “low expressers”.
27
Association of NEIL2 expression levels with demographic characteristics
When levels of NEIL2 expression were evaluated with respect to ethnicity, we
observed that average expression levels were significantly higher (mean number of
transcript copies ±SE = 3876.34±540.24) in White non-Hispanic subjects (N=92)
compared with all other ethnicities combined [N=37; mean±SE=2099.05±214.93,
P=0.03; Figure 3 (a)].
Within the White non-Hispanic population, there was also a bimodal pattern of
gene expression, where 26% of White non-Hispanics were found to be high expressers
[Figure 3 (b)]. This was twice as high as the observed 13% of high expressers found in
the group composed of the other ethnicities combined. These results suggest ethnic
differences, and imply that copy numbers of NEIL2 expression could be associated with
certain ethnic haplotypes.
When NEIL2 expression was evaluated with respect to smoking status (smokers
vs non-smokers), we observed no significant effect of smoking on NEIL2 transcript copy
numbers. The mean number of transcripts ±SE was 3008.98±475.58 in smokers versus
3810.86±615.37 in non-smokers. Similarly, no significant difference in expression was
observed with respect to gender (mean±SE for males = 3175 ±707; for females =
3517.564±471.96) or with age (linear regression P value = 0.59).
To characterize the frequency of allelic variants in the NEIL2 promoter region, 24
subjects (12 from the high-expresser group and 12 from the low-expresser group) who
were matched with respect to age, smoking status, ethnicity, and sex were evaluated.
From PBLs of each of these subjects, a 971 bp DNA fragment that corresponds to a
location in chromosome 8 from 11,663,721 bp to 11,664,692 bp (a sequence immediately
upstream from the NEIL2 coding region) was isolated and sequenced. Notably, this
sequence was rich in both previously documented SNPs and predicted cis-elementbinding sites (based on NCBI reports and a query of results obtained from the
Transcriptional Element Search System, University of Pennsylvania).
28
Copies NEIL2 transcript/ug total RNA
NEIL2 expression by ethnicity
P=0.03
#
*
5000
4000
3000
2000
1000
0
White
non-Hispanic
Caucasian
N=92
All other ethnicities
N=37
Figure 3 (a)
Dot Plot
NEIL2NEIL2_expression
transcript number
30000.0
20000.0
10000.0
0.0
0
1
Non-Hispanic
Other ethnicities
White_and_other
White
Figure 3 (b)
Figure 3 (a) – Distribution of NEIL2 expression stratified by ethnicity (grey
bars). *P<0.05 for comparison between White non-Hispanics and other ethnic groups
combined, indicate a significantly higher mean NEIL2 transcript copy numbers in White
non-Hispanic subjects. Values are expressed in mean ± SE.
Figure 3 (b) Distribution of NEIL2 transcript copy numbers amongst the
different ethnic groups.
29
Table II: Single nucleotide polymorphism (SNP) frequency in the study
population.
Table
II
: Single nucleotide polymorphism (SNP) frequency in the study
population.
Report ed
range of SNP
frequencies d
NCBI
Reference
SNP
rs7464968
G>T
11664458
0 to 0.0 5
rs8191515
G>A
11664565
0.0 6
rs8191514
rs8191516
rs8191517
rs8191518
ss74800504
ss74800505
a
C>G
C>T
C>T
Position in
chromosom
e8
11664522
11664641
11664650
C>
G
11664670
G>T
11664692
C>A
11664623
Ethnicities
represented
in the
reported
frequencies
Europea
n, Asia
n c
NR
c
Minor allele
frequency in
study
population
N=24 b
Minor allele
frequency in
high
expressers
N=12 b
Minor allele
fre quency in
low
expressers
N=12 b
0.04
0.04
0.04
0.06
0
0.13
0. 14
NR
0.13
0.13
0.13
0.0 2
c
0.04
0.08
0
NR
c
0. 00 7
NR
0.02
0.04
0
0. 10 to 0. 30
Europea
n,Africa
America
n
n, Asia
n c
NR
0.33
0.58
0.08
0.10
0.08
0.13
0.33
0.29
0.30
NR
c
NR
c
c
NR
a
SNP designation reported in the National Center for Biotechnology Information (NCBI) database under
the
corresponding SNP accession (minor allele is T for rs7464968, A for rs8191515, G for rs8191514, T for
number
rs8191516,
T for 517, G for rs8191518, T for ss74800504 and A for ss74800505)
b
.
rs8191
N=
number of chromosomes evaluated in the study population
c
NR = not reported .
d
N
Frequencies are expressed as percentages of the minor allele
This approach allowed the determination in our study population of the frequency
of six SNPs previously reported by NCBI. During the sequencing process of these 24
samples, two new previously unreported SNPs, designated as ss74800504 and
ss74800505 (a G>T at position 11664692 and a C>A at position 11664623 of
chromosome 8, respectively) were identified, for a total of 8 SNPs evaluated (Table II).
We compared the SNP frequencies observed in our study population and the
frequencies reported in the NCBI SNP database and found that, while most of the SNPs
had comparable frequencies (Table II), the minor allele frequencies for the rs8191516
and rs8191517 SNPs in our study population varied by a magnitude of at least one fold
for each of these SNPs compared to that reported in the SNP database. Estimation of
linkage disequilibrium (LD) for the 8 studied SNPs in the 24 subjects studied, indicated a
30
significant LD between the newly discovered ss74800505 and rs8191518 (D’=0.73;
P<0.05).
When categorized as high or low expressers, the minor allele frequencies were not
randomly distributed. The rs8191515 SNP was exclusively found in subjects with the
low-expresser phenotype, and the rs8191516 and rs8191517 SNPs were only found in
high expressers (Table II). SNP rs8191518 was found at a significantly higher (P=0.01)
frequency (0.58) in high expressers than in low expressers (0.08). Collectively, these
data suggest that SNPs found in the 5’ upstream region of NEIL2, especially the
rs8191518 SNP, may differentially modify the regulation of NEIL2 gene transcription.
Relationship between NEIL2 expression and mutagen sensitivity
In this study population, the baseline (background) in vivo CA frequencies ranged
between 0 and 7 breaks per 100 cells (mean + SE = 0.9 + 0.11). Using linear regression
analysis, no relationship was observed between the level of NEIL2 gene expression and
the baseline in vivo CA. Similarly, no association was observed between baseline CA
frequencies and the presence of the SNPs evaluated. Using the mutagen-sensitivity assay
we were able to measure sensitivity of an individual to a specific mutagen by treating the
lymphocytes with the potent mutagen, NNK. The results indicate that the mean ± SE
frequencies of NNK-induced CAs per 100 cells, after controlling for the baseline in vivo
level for each subject, was 2.2 ± 0.25, with a range of 0 to 9 breaks/100cells. Using a
two-tailed Students t-test, a significant increase in NNK-induced CA was observed in the
cells with either the heterozygous or the homozygous variant form of ss74800504 and
ss74800505 compared to cells homozygous for the referent allele (Table III).
31
Table III: Relationship between NEIL2 ss74800504 and ss74800505
polymorphisms and mutagen-induced genetic damage
________________________________________________________________
Genotype
N
mutagen-induced genetic damagea
____
P value____
ss74800504
G/G
14
1.42 (±0.29)
G/T or T/T
4
3.00 (±0.91)
C/C
9
1.00 (±0.23)
C/A or A/A
10
2.60 (±0.45)
0.04*
ss74800505
0.01*
___________________________________________________________________________
* Statistically significant (Student’s t-test two-sided P<0.05). P-values are for comparisons
between heterozygous and homozygous variant allele carriers and homozygous wild-type.
a
Data expressed as mean ± SE net increase in mutagen-induced chromosome aberrations per
100 cells.
None of the other SNPs studied showed a significant association with mutagen-induced
genetic damage.
Discussion
In the current study, the NEIL2 transcription levels in lymphocytes of healthy
volunteers were evaluated. A dramatic variation in the NEIL2 transcription level among
individuals was observed. This variability in expression levels (up to 63 fold) is relatively
high compared to that observed with other human genes, for example -actin and
GAPD(H) and other DNA repair genes, such as XPD and MGMT (Wolfe et al., 2007;
Leong et al., 2007; Bustin, 2000; Tanaka et al., 2005). Interindividual variability in the
expression levels observed was not correlated with smoking status, as indicated by the
lack of association between smoking and levels of NEIL2 gene expression. This finding is
in contrast to previous findings from a study with another DNA repair gene, XPD, where
32
XPD transcript levels were decreased in heavy smokers compared to light smokers or
non-smokers (Wolfe et al., 2007). In the current study, the transcript levels of both
NEIL2 and XPD in a subset of individuals (N=78 of our total population of 129, data not
shown) were compared. While a significant decrease in XPD transcript copy numbers in
smokers was observed, as expected, no significant change in NEIL2 transcript numbers in
relation to smoking status was observed. Several in vitro studies have evaluated the effect
of tobacco smoke condensate in various cell types on overall gene expression using
micro-arrays. These studies used similar micro-array gene panels and while some of
these studies illustrate changes in the expression of other DNA-repair genes, none
reported NEIL2 to be responsive to such exposure (Mohrenweiser, 2007; Maunders et al.,
2007; van Leeuwen et al., 2005). Maunders et al. (2007) found that exposure of human
bronchial epithelial cells to tobacco smoke increased the expression of genes coding for
several DNA repair enzymes such as POL and POL, as well as the NER-associated
enzyme, GADD 35. Van Leeuwen et al. (2005) showed, in peripheral blood cells, that
tobacco smoke exposure did not affect the expression of several genes associated with the
repair of DNA damage, such as XRCC1, XRCC5, and ERCC5. But to our knowledge, no
studies have illustrated the effects of tobacco smoke exposure on DNA glycosylases,
such as NEIL2, in human cells.
In the current study, a significant association between levels of expression and
ethnicity was observed. Proportionally, white non-Hispanic subjects constituted the
majority of the high expressers, and as such, they had significantly higher levels of
NEIL2 expression than subjects from all other ethnicities combined. These findings are
consistent with reports indicating that gene expression phenotypes vary significantly
between different populations (Spielman et al., 2007) and that ethnicity plays a
significant role in gene expression patterns as well as in disease risk (Spielman et al.,
2007). While the exact mechanisms explaining ethnic variability in gene expression
levels are still unclear, we hypothesized that SNPs could, at least in part, contribute to the
observed differences in gene expression (Spielman et al., 2007; Lefstin and Yamamoto,
1998). The observed ethnic variability for NEIL2 expression also strongly suggests that
33
high expression of this DNA repair enzyme could be associated with certain haplotypes
found predominantly in non-Hispanic white groups.
For many genes, the 5’ region upstream of the transcriptional start site is known
to contain important motifs that are specific for the binding of transcription-regulating
proteins. Inherited differences in these upstream cis-element-sequences (such as the
presence of certain SNPs) could, therefore, alter the binding of these transcriptional
regulating proteins, resulting in a change in the recruitment or activity of these proteins.
This could, in turn, result in an alteration in transcriptional levels, which provides a
plausible mechanism that could explain the variations in NEIL2 expression that we
observed. In the current study, we evaluated the effect on gene expression of 8 SNPs in
the 5’ region of NEIL2 (six had been reported in the NCBI SNP database and two were
newly identified in our study). Our data indicate that the rs8191518 SNPs is significantly
associated with reduced gene expression levels. The exact mechanism by which this SNP
alters expression is still not known. However, we hypothesize that, given that their
existence in close proximity to or in areas rich in putative cis-element-sequences as
determined by our TESS analysis, they could change the architecture of the DNA binding
site, thus altering the affinity of the transcription factor for that site, and subsequently,
affecting the transcript level(s) responsive to this factor. Another possibility is that
structural changes in the DNA could also create allosteric changes in the transcriptional
protein-binding site, which could alter the formation of a complete transcription complex,
ultimately leading to altered levels of gene expression, as suggested by Lefstin and
Yamamoto (1998).
In order to elucidate the effect of the NEIL2 promoter region SNPs on genomic
integrity, we characterized the genotype-phenotype relationship using the mutagensensitivity approach. This assay is based on the quantization of mutagen-induced CA in
cultured lymphocytes of an individual and it reflects the sensitivity of that individual to
the mutagen tested, as well as her/his DNA repair capacity in response to a mutagenic
insult (Hsu et al., 1989). Our data indicate that only the two newly identified SNPs had a
significant effect on mutagen-sensitivity.
34
The presence in PBLs of the variant
ss74800504 or ss74800505 alleles was associated with a significantly higher frequency of
mutagen-induced genetic damage when compared to cells with the homozygous wildtype form. This suggests a possible effect of these two newly identified SNPs on DNA
repair efficiency. While the exact mechanism(s) underlying this relationship is yet to be
determined, it is plausible that SNPs in the NEIL2 promoter could be associated with an
alteration in NEIL2 expression levels, or may be in linkage disequilibrium with other
functional SNPs in the coding region of the gene, which could result in alterations in
NEIL2 protein function. The frequency of the ss74800504 and ss74800505 alleles in our
subjects was similar in both high and low expressers, suggesting that these SNPs do not
affect expression levels; however they were only evaluated in a relatively small
population (N=24). Also, because of the relatively small sample size studied, we could
not evaluate the effects of polymorphic combinations on gene expression levels.
Additional studies with a larger population are clearly warranted to clarify the observed
findings. Such studies would also address the relationship between gene expression levels
and NEIL2 protein levels and function.
Taken together, our results indicate that variability of NEIL2 expression is, at least
in part, influenced by SNPs in the promoter region of the gene, and this variability
appears to be affected by ethnicity.
Because of the observed mutagen sensitivity
associated with both the ss74800504 and ss74800505 SNPs, the potential role of these
two new SNPs as risk modifiers for disease susceptibility warrants further investigation.
35
CHAPTER 3:
REGULATORY ELEMENTS RESPONSIVE TO OXIDATIVE
STRESS IN THE PROMOTER REGION OF NEIL2, A HUMAN DNA
GLYCOSYLASE GENE
Introduction
As described in the previous chapter, NEIL2 expression varies greatly in vivo.
Furthermore, at lest one polymorphic site in the promoter region of the gene appears to be
related to gene expression.
This suggests that NEIL2 expression is governed by
regulatory motifs in the 5’ upstream region where single base changes in these motifs
could result in modified gene expression. In an effort to characterize the factors in the
promoter region that affect the expression of NEIL2, the transcriptional start site was
mapped using the random amplification of cDNA ends (RACE) primer extension kit.
RACE is a technique commonly used to identify transcriptional start sites (Alberts et al.,
2002). It entailed the amplification of the 5’ end of
mRNA
transcripts using a reverse
transcription PCR. Primers were designed to aneal within the mRNA transcript. This
allowed for the amplification of the 5’ end of the mRNA. This fragment was then
sequenced and resultant sequence was compared to the human genome using alignment
software provided by the National Center for Biotechnology. The alignment revealed the
exact genomic loction of the first DNA nucleotide that corresponded to the mRNA
transcript.
We then constructed several luciferase plasmids containing fragments of the
NEIL2 promoter region, using the transcriptional start site as a guide to estimate the
location of the NEIL2 promoter region. We chose to test these constructs in the normal
human lung cell line, MRC-5, for several reasons. First, studies have shown that lung
tissue is particularly vulnerable to damage from ROS because of its constant exposure to
oxygen as well as air-born environmental pollutants, which can be strong generators of
oxidative radicals (reviewed by Langen et al., 2003). Also, the NEIL2 protein has been
extracted from MRC-5 cells in other experiments, thus these cells should have the
36
transcriptional machinery needed to drive NEIL2 expression from a transient plasmid
(Hazra et al., 2002). These cells have been used for reporting promoter-driven expression
using the luciferase reporter assays by other groups (Liao et al., 2006; Wang YP et al.,
2006) Finally, MRC-5 cells are an economical and practical choice for studies such as
this one where several constructs were tested in numerous conditions.
Subsequently, the hypothesis that NEIL2 transcription is responsive to oxidative
stress was tested. To induce oxidative stress in our cell line, we chose the persistent H2O2
generator, glucose oxidase (GO). This chemical was used by Das et al. (2005), to induce
reactive oxygen species in vitro and to induce the expression of NEIL1expression. Our
study identified a positive and a negative regulatory region within the NEIL2 promoter.
Expression from the positive regulatory region decreased in the presence of oxidative
stress, suggesting that ROS may play a role in NEIL2 expression.
Materials and methods
Cell culture
MRC-5 cells (normal embryonic human lung fibroblasts) were acquired from
ATCC (lot no. 3929228; American Type Culture Collection, Manassas, VA) and were
cultured in flasks containing Eagle’s Minimal Essential Medium (EMEM, Cellgro Inc.,
Manassas, VA) with Earle’s basal salts and 2 mM L-glutamine, supplemented with 1.0
mM sodium pyruvate, 0.1 mM nonessential amino acids, 1.5 g/L sodium bicarbonate,
100 U/mL penicillin, 100 g/mL streptomycin, and 10% fetal bovine serum (GibcoInvitrogen, Carlsbad, CA). The cultures were incubated at 37 °C with 5% CO2. Twentyfour hours prior to transfection, cells were harvested from the flasks, counted, and seeded
in 6-well plates at a concentration of 3.5x105 cells/well.
Mapping of the NEIL2 transcriptional start site
The NEIL2 transcriptional start site was mapped by first isolating total RNA from
the growing MRC-5 cells. The FirstChoice RLM-RACE primer extension kit (Ambion,
Inc., Austin, TX) was used to identify the transcriptional start site according to the
instructions of the manufacturer. Basically, the primer extension kit involves ligating the
37
5’ RACE adaptor directly to the 5’ end of the mRNA transcripts. This provides a primer
template for sequencing through the adapter and into the mRNA transcript. The sequence
found immediately after the adaptor denotes the earliest nucleic acid residue in the
transcript, which is the transcriptional start site (Figure 4). Briefly, total RNA was
isolated from MRC-5, cells and 10 g of the total RNA was treated with calf intestine
alkaline phosphatase (CIP) and then treated with tobacco acid pyrophosphatase (TAP) to
specifically modify the full length mRNA for adapter ligation. The 5’ RACE adapter
(included with the primer extension kit) was ligated to the 5’ end of the full length
mRNA, which provided a template for primer extension during the subsequent reverse
transcription and PCR amplifications. In the first reaction, the 5’ RACE outer primer
(also included with the kit) was used in combination with the NEIL2 gene-specific
primers
(RACE1,
5’-TCTTCCGAGTGCCCGAGGTG-3’
and
RACE2,
5’
-
GGGGTTGTCTCCGCCGTTC - 3’) that were designed based on GenBank mRNA
(NM_145043) sequence data.
Then a second PCR reaction was used to amplify the region using the same genespecific primers and the 5’ RACE inner primer (included with the extension kit).
Products of this latter reaction were sequence-verified using the ABI Prism 3100
Sequence Detection system (Applied Biosystems, Foster City, CA) and BLASTn
software (NCBI, Bethesda, MD). Following identification of the transcriptional start site
through sequencing through the adapter region to the junction of the NEIL2 transcript, the
transcription element search system (TESS, University of Pennsylvania), which allows
the identification of functional cis-acting binding sites within the DNA strand (Schug and
Overton, 1997), was subsequently used to search for putative cis-elements located near
the transcriptional start site.
38
Figure 4: RACE methodology
mRNA cap
AAA… mRNA transcript
CIP
AAA…
TAP
5’OH
AAA…
adapter
Ligation
AAA…
Gene-specific sequencing primer
AAA…
Adapter-specific sequencing primer
Cloning of the NEIL2 5’- upstream region into luciferase reporter vectors
The results obtained from the TESS analysis guided the design of NEIL2
promoter constructs within a 1871 bp region encompassing from bp -1161 to +710 of the
NEIL2 gene (Figures 5 and 6).
39
-1161
Untranslated region
Coding region
+710
+1
-1161
Chomosome 8 –
11664692
Chomosome 8 –
116682263
pSTEP1
-1161
+710
pSTEP2
-513
+49
p1200
-1161
-1161
p1200A
-702
+710
pSTEP3
+710
+90
-661
p1200B
-104
-206
p1200C
+90
Figure 5: Schematic representation of the NEIL2 gene and the relative locations
of the promoter fragments isolated, cloned, and sub-cloned into luciferase
reporter vectors. The identified transcriptional start site is designated as +1.
The first and longest construct encompassing this region (1871 bp) was
designated as pSTEP1 and was found to include several putative transcriptional binding
sites (Figure 6). The term STEP was used because we used a step-wise truncation pattern
to reduce the size of the DNA fragment contained in each of our clones. The second
construct, the pSTEP2 construct (1223 bp, from bp -513 to +710) was then designed as a
40
(-1161)
AP-1
GACGGTGGGCTGGGCTTGTTTCCCTGTGCTGACCAAGTCCTTCCCCAGGGACCCCTCAGCTAG
NFkB
AP-1/CREB
GGTCCATGGTGACTTCACCCCAGCCTATTTCCTGAACACCTGCTGGGGAGTTCCCCAGACTTTC
CTCCCAACTTCCTGGAAAGTGCTGGCTCCCCATCCTCCTTCGAGAACTAAAGACAAGAAAACA
TATGTATCTTTAAACAGCCTATTGTTTTATCTCTTTTATTCTATGAAATAAAAAATTTAATACA
CAAATACTTTAAGCAAAATTTGCTTATAGTAAAAATTCAAGTAATAAAATTCAAATAATAGAA
AGCAAAAAAATCCCACCCGTTCAACATTTCACGAGTCTTGAACACCTGTTTCCTTTGCACCCG
ACTTCATTAGGCTCGGAGGCCAAGCAGAACCCACAGAAAGGCTTGCCATTGTGGGAACACCC
AGGCTGTCCCATTCACACACCCATTGACTTTTCCCTATAACTGTCTCCTTGAGACAAGAAATGT
TCCAAAAGGGCCGGGTGCGGTGGCTCACGCCTGTAATCCCACCACTTTGGGAGGCCGAGGAG
GGCGGCTCACCTGAGATCAGGAGTTCAAGACCAGCCTGGCCAACATGGTGAAACCCGGTCTC
TACTAAAAATACAAAAATTAGCCGGGCGCCAGTAATCCCAGCTACTCGGGAGGCTGAGGCAG
GAGAATGGCTTAAGCCCAGGAGGCGGAGGTTGCAGTGAGCCGAGATCGCGCCACTGCACTCC
AP-1
AGCCTGGGTGACACAGCGAGACTATCTCCCCCCGCAAAAAAAAAAAGTTTCCAAGAGCGTCT
CTCCAATGTTAGTCCCAGCCTGCACCCTTCTTCCATCCCTGCTTTCACTCGCGACCCTCTAATG
CAGCCCTGCCTCCAGCGACCCCCGGGATGGAACCCCTCGCCCACCCACAAAAGAGCAGCCTC
GACCTAGACCCACTTTCCAGGGAATGAGCCCTGCGCCTGCGCGCACCCCGCCACCCCCTCCAG
NFkB SP1
GCCGGAGTCCACGCCCACTTGGGGGAGGAGCCCCGCAGCCTCCACCTACAGGGGCGTCCCCT
AP-1/NFkB
AAGGGGACGGAGGCCGCATGGGCCGCCGAGCCGGGAAATCTCCGCCCCCAGCTGGAGCGGCT
USF
SP1
+1
GTGCGGGCTGCGTAGCGGTGCTGGGTCGGGCCGACGTGCCACCCACCCGGAGCCGGTGAGTG
CAGCCGCCCGCCCTCCGGTAGATCTGCGGCCTGGCGGAGAAGTCGGGAGGGGACAGGAAGGG
AGGGCGGGCCCCGGGCCCTCCTCCGTCTCAGCCGCCTGCGGAGGTGCTGCCCACGCCTGGAGG
CCCCCACTGACCCTCAGACCCGCGTCTGCGCCCCTCTCCCCGCACCCCGAGGCAGAGTTGGGA
AAGCAGTGGTCTTAGACCCCCCACCTCGGGCACTCGGAAGAGAACGGCGGAGACAACCCCTC
CTCTTCCCTGGCTGGCGCAGCGCCAGCCTCGAGCTCCTCGGTAGCCCCCGGGCAGGGAGGGCC
GGAGGGTGGGCGCGGCATCTTCAGCGACTCTTCGAAGTCCCTTCCGCGTCTCATCTTTCAAGG
CTGTTGCAGAGGCGGCTTGCTTCCCACCTGTCCATCTCCATAAAAATCCCTAAACGAAACATG
AP-1/CREB
CCCACGTGTCCGGAGATTTTCAGGACTTGGTGCATTTCAGATGAAGGCTTTTCCAGAAGCTTCC
CCGTAGAAGAGGATCAGGCATCCAACTGGTTAAGGTCAGCAGCGTTTGGCACGTCTCCTTCCA
GCCTGGCGGTTTTGTCAGGATTCCCTGGGGAGTGTCTGGAAAGCCTGATGAGGGGAAATAGTA
CATCTCAGCGAATCGGCACCAGCGAGTGTAAGATGCGCGTTATTGAATGTG(+710).
41
Figure 6: The DNA sequence, encompassing the pSTEP1 fragment, that
includes the NEIL2 gene sequence flanking 5’ upstream and 3’ downstream of
the identified transcriptional start site (+1). Putative consensus sequences for
binding to regulatory factors are activating protein – 1 (AP-1; highlighted), cAMP
response element-binding (CREB; italicized), nuclear factor –kappa B (NF-B;
underlined), and polyomavirus enhancer A factor 3 (PEA3; bold and italicized).
truncation of pSTEP1 (Figure 5), which eliminated several putative regulatory elements,
including an NFB site (see Figure 6). The third construct we designed, the pSTEP3,
contained a region 3’ of pSTEP1 (661 bp, from +49 to +710). This pSTEP3 construct was
designed to include the downstream putative transcriptional cis-elements of pSTEP1. As
shown in Figure 4, we also designed the construct p1200 containing only the 5’ portion of
pSTEP1 (1250 bp, from bp -1161 to +90). This p1200 construct was designed so that it
retained the putative transcriptional elements upstream of the transcriptional start site. As
such, each of these constructs was engineered to contain a unique set of cis-elements
(Figure 6). This design allowed us to evaluate the independent contribution of each
region in driving NEIL2 expression.
The 5’ gene region of NEIL2 was amplified from genomic DNA through PCR.
We used primers that were specifically designed to amplify the regions of interest (Table
IV).
Table IV - Primer sequences for luciferase constructs
Luciferase
construct
Forward primer
Reverse primer
pSTEP 1
5' - GAGCTGGTGGGCTGGGCTTGTTT - 3'
(5' - CACATTCAATAACGCGCATC - 3'
pSTEP 2
5' - TAGCCGGGCGCCAGTAATCC - 3'
5' - CACATTCAATAACGCGCATC - 3'
pP1200
5' - GAGCTGGTGGGCTGGGCTTGTTT - 3'
5' - GAAGCTTTCCCCTCCCGACTTCTC - 3'
p1200A
5' - GAGCTGGTGGGCTGGGCTTGTTT - 3'
5' - CTTGTCTCAAGGACACAGTT - 3'
p1200B
5' - CACCCATTGACTTTTCCC - 3'
5' - TGTAGGTGGAGGCTGCGG - 3'
p1200C
5' - TTTCCAGGGAATGAGCCCT - 3'
5' - GAAGCTTTCCCCTCCCGACTTCTC - 3'
42
The resulting fragments were then cloned into the pCR2.1 vector, using the TA Cloning
Kit (Invitrogen, Inc., Carlsbad, CA), and then sub-cloned into the KpnI/EcoRI restriction
sites in the promoter-less luciferase expression plasmid, pGL3-Basic (Promega, Inc.,
Madison, WI), to create the three plasmids: pSTEP1, pSTEP2, and p1200. Construct
pSTEP3 was created by cloning a 661 bp fragment of the region from +49 to +710 into
the BglII site of the pGL3-Basic vector.
Sub-clone constructs of the p1200 and pSTEP3 fragments
In addition to the constructs described above, three fragments were amplified
from the p1200 construct (see Figure 5) using the primers shown in Table IV. The
fragment encompassing the 5’ region of the p1200 insert (from -1161 to -661) was used
to create the p1200A construct. The central fragment (from -702 to -104) was used to
create the p1200B construct. The 3’ region (from -206 to +90) was used to create the
p1200C construct.
In addition to these p1200 sub-clones, to evaluate the characteristics of the
pSTEP3 fragment (661 bp, from +49 to +710), we cloned this fragment into a pGLcontrol vector containing the strong, ubiquitous SV-40 promoter. The pSV40-STEP3
construct was created by ligating the BglII fragment from pSTEP3 into the BglII site of
the pSV40 vector.
The integrity of the cloned fragments was verified by direct
sequencing. Plasmid DNA used for transfections was isolated using the Qiagen EndoFree Maxi-prep (Qiagen, Inc., USA). The stock DNA extract was diluted in endotoxinfree water to a final concentration of 1g/uL prior to transfection. In order to ensure
plasmid integrity, all plasmid preps were performed three days prior to transfection.
Transient transfection of MRC-5 cells with NEIL2 promoter constructs and
luciferase assay
MRC-5 cells were transfected with the constructs described above for 4.5 hours in
a mixture of 1.0µg luciferase and 0.5 µg Renilla DNA/well at a Lipofectamine
(Invitrogen, Inc.) concentration of 6
of Lipofectamine/µg plasmid DNA.
Transfection efficiency was tested using the Dual Luciferase Reporter System (Promega,
43
Inc.). After transfection, cells were allowed to recover for 48 hours and then were
harvested in 1x Passive Lysis Buffer (Promega, Inc.). Luciferase reporter gene expression
was detected using the Luciferase Detection Kit (Promega, Inc.). Briefly, cells were
washed in phosphate buffered saline and incubated in 200 μl of cell lysis buffer.
Luciferase activity was measured according to the manufacturer’s instructions and
detected on a GENios Pro micro-plate reader (Tecan, Inc., Durham, NC). The total
cellular protein concentration was determined using a Bradford-based assay from Bio
Rad (Bio Rad Protein Assay, Bio-Rad Laboratories, Hercules, CA). Total recoverable
cellular protein concentration was determined by calibration relative to a standard curve
generated using known concentrations (between 0-24 mg/ml) of aqueous bovine serum
albumin. Luminescence was measured in relative light units (RLUs) per L. The
relative luciferase activity in each sample was normalized to the total concentration of
protein. Each experiment was repeated at least five times.
Response of the p1200C and NEIL1 construct to oxidative stress
MRC-5 cells were transfected with either the p1200C construct (the fragment
from bp -206 to +90) or the pNEIL1 luciferase construct and treated with 100 ng/ml of
the cellular oxidant glucose oxidase (GO; Roche, Inc. Basel, Switzerland). Glucose
oxidase is a strong generator of cellular hydrogen peroxide (H2O2) which produces an
environment conducive to oxidative DNA damage (Das et al., 2005). Prior to treatment,
cultures were allowed to recover in fresh medium for 24 hrs after transfection. Cells were
continually treated with GO, and luciferase expression levels were determined at 1, 6, and
12 hrs after treatment. The experimental conditions used did not affect cell viability, as
determined by trypan blue exclusion.
Statistical analysis The Student's t-test and ANOVA were used, when appropriate, to compare
the means between treatment groups.
A two-sided P<0.05 was considered statistically
significant. A Tukey’s test was used when appropriate to designate different groups. All
statistical analyses were performed using NCSS 2004 (Kaysville, UT).
44
Results
Mapping of the NEIL2 transcriptional start site and identification of ciselements in the NEIL2 promoter.
Using the FirstChoice RLM-RACE kit, we determined that the guanine residue at
location 11664692G on chromosome 8 was the transcriptional start site (designated as +1
in Figures 5 and 6). The TESS software (Schug and Overton, 1997) was used to identify,
in this region, several potential cis-elements for transcription factors, including a nuclear
factor-kappa B (NF-kappaB) protein, a cAMP response element-binding protein (CREB),
and an AP-1 site (a heterodimer formed from C-jun and C-Fos) (Figure 6).
Partial characterization of the NEIL2 promoter region.
As shown in Figure 7A, the largest construct of the NEIL2 promoter fragment
pSTEP1 (the fragment from bp -1161 to +710) drove minimal gene expression. we then
used the TESS software to search the sequence for sequence areas that were enriched in
transcriptional elements. The results of this search showed that the region from bp -1161
to +90 had several transcriptional binding motifs. Therefore, the p1200 construct (from
bp -1161 to +90), which contained the first 1251 bp of the -1161 to +710 fragment,
including the transcription start site was designed. This was equivalent to deleting the
pSTEP3 fragment (bp +49 to +710) located in the -1161 to +710 fragment. The -1161 to
+90 fragment (p1200) showed a 5-fold higher expression level compared to the -1161 to
+710 fragment (pSTEP1), suggesting that it contained positive regulatory elements
(Figure 7B).
A plausible reason for the higher expression from the -1161 to +90
compared to the longer -1161 to +710 fragment is that the missing +49 to +710 fragment
contains negative regulatory elements that repress the induction of NEIL2 expression
observed with the pSTEP1 construct.
To further evaluate potential repressive
characteristics of the +49 to +710 fragment (pSTEP3), it was cloned into a pGL-control
vector containing the SV-40 promoter (Figure 8).
45
A
-1161
+710
-513
LUC
pSTEP1
LUC
pSTEP2
LUC
pSTEP3
+710
+49
+710
-1161
+90
LUC
p1200
B
pSTEP1
pSTEP2
pSTEP3
*
P1200
0
50
100
150
200
250
300
Relative light units/g total protein
Figure 7: A, Luciferase constructs containing DNA fragments of the 5'regulatory region that were cloned upstream of the luciferase-coding sequence;
B, Promoter activity (determined as described in Materials and Methods and show in
means ± SE). * P < 0.05 compared to pSTEP1.
46
A
+49
pSTEP3 fragment
SV-40
LUC
SV-40
LUC
+710
pSV40
pSV40-STEP3
B
pSV40
pSV40-Step3
*
0
1000
2000
3000
4000
5000
6000
7000
RLU's/mg total protein
Relative light units/g total protein
Figure 8: A, Luciferase constructs containing the pSTEP3 DNA fragment
inserted 5’ of a SV-40 promoter; B, Promoter activity relative to a pSV-40
control vector is shown in relative light units (RLUs) per mL, normalized to total
protein in the sample. *P<0.05.
47
Inserting the +49 to +710 fragment proximal to the SV-40 promoter (pSV40-Step3)
resulted in a 91% decrease in SV-40-driven luciferase expression (Figure 8B), further
confirming the presence of repressive elements in this region.
Further characterization of the key regions responsible for positive regulation of
the NEIL2 gene was completed by sub-cloning segments of the -1161 to +90 fragment
(p1200) into three constructs (p1200A, p1200B, and p1200C; Figure 9A).
A
-1161
+90
-1161
LUC
p1200
LUC
p1200A
LUC
p1200B
LUC
p1200C
-661
-702
-104
-206
+90
B
P1200
**
p1200A
*
p1200B
p1200C
0
50
100
150
200
Relative light units/g total protein
48
250
300
Figure 9: A, Luciferase sub-clone constructs containing fragments (A, B, and
C) of the p1200 DNA fragment inserted upstream of luc-coding sequence; B,
Promoter activity (determined as described under Materials and Methods in relative
light units/g total protein). *P < 0.05 compared to p1200C. **P<0.05 compared to
p1200B.
While the relative promoter activity of the p1200C construct (containing the fragment
from bp-206 to +90 and the transcriptional start site) was comparable to the relative
promotor activity of the -1161 to +90 fragment (p1200), the relative promoter activity of
the p1200A construct (the fragment from bp -1161 to -661) was 5-fold lower than that of
p1200C (P<0.01) and significantly lower that p1200B (P<0.05).
In addition, the
promoter activity of the fragment from bp -702 to -104 (p1200B) was 3-fold lower than
that of p1200C (P<0.01; Figure 9). These observations are consistent with the p1200C
fragment containing the positive regulatory region of the NEIL2 promoter.
Response of the p1200C construct (-206 to +90 fragment) and pNEIL1-luc to
oxidative stress
Because the fragment from bp -206 to +90 (p1200C) drove the highest level of
luciferase expression and, presumably, had positive regulatory elements for NEIL2, the
next step was to examine whether this fragment was responsive to oxidative stress. The 206 to +90 fragment responded to GO treatment, with a rapid and significant decrease of
29% in luciferase expression from 1 hr (P=0.04) to 6hr (P<0.01) of continual treatment
(Figure 10 followed by a recovery to untreated levels at 12hr.
49
4
3.5
3
*
*
2.5
2
1.5
1
*
*
6hr
12hr
0.5
0
0hr
1hr
6hr
p1200C
12hr
0hr
1hr
pNEIL1
Figure 10: Luciferase reporter activity in cells transfected with the p1200C and
pNEIL1 constructs and then treated with glucose oxidase (100 ng/mL) for 1, 6,
and 12 hrs. Comparisons are between GO treated at 1, 6, and 12 hrs vs. untreated. *P <
0.05.
At 12 hr, expression completely recovered to the same level as the untreated (Figure 10).
After no response at 1hr, the pNEIL1-luc construct had a progressive, significant decrease
in expression, from 6hr to 12hr.
Discussion
A growing body of evidence indicates that NEIL2 plays an important role in
transcription-coupled DNA repair and, potentially, in cancer susceptibility (Hazra et al.,
2002; Hazra et al., 2003; Broderick et al., 2006). In view of the relative importance of
NEIL2 in maintaining genomic stability, this study initially characterized the NEIL2
promoter and mapped the transcriptional start site of this gene. To our knowledge, the
promoter region of the human NEIL2 gene has not been characterized before, nor have
any attempts been made to identify the transcriptional start site of this gene.
The
Luciferase Reporter System was used to evaluate the expression characteristics of several
fragments of the NEIL2 promoter region. Our evaluation of the expression activities
associated with these fragments revealed that the 1871 bp fragment from -1161 to +710
50
(pSTEP1 construct) did not drive expression in MRC-5 cells, even though this fragment
contained the transcriptional start site as well as several putative transcriptional element
binding sites.
These findings suggested that this fragment could contain negative
regulatory regions that suppress expression. In fact, sub-cloning of this fragment
demonstrated that it contains both positive and negative regulatory regions that seem to
be affecting gene expression. A positive regulatory region was localized in the fragment
encompassing bp -206 to +90 that includes the transcriptional start site (the p1200C
construct). However, the expression from this region was found contingent upon its
being isolated from the adjacent fragment (+49 to +710, pSTEP3), suggesting the
presence of silencing elements in this region.
In order to further characterize the gene-silencing potential of this region, the +49
to +710 fragment was inserted next to the SV40 promoter of the pGL3-control vector to
test whether it would repress the expression of this promoter. The SV40 promoter is
commonly used in the pGL3-control vector as a positive transfection control because it
promotes strong reporter-gene expression in various mammalian cell types (Wildeman,
1988). As such, repressing its expression would, presumably, require robust repression
elements. We observed a 91% reduction in SV40-driven luciferase expression associated
with this fragment, consistent with it, containing repression elements that negatively
regulate NEIL2 gene expression.
This study further showed that the fragment from bp -1161 to +90 (p1200) drove
substantial luciferase expression. As such, this fragment likely contains positive
regulatory elements. Most of the p1200 fragment was 5’ of the transcriptional start site.
The majority of the well-characterized gene regulatory elements are usually found within
a region that is approximately 2000 bp upstream of a gene transcriptional start site
(Mottagui-Tabar et al., 2005). Indeed, TESS analysis indicated the presence of multiple
putative cis-binding sites for various transcription factors within the -1161 to +90
fragment, particularly within the -206 to +90 region, including NFB and AP-1 sites that
are known to be responsive to ROS (Muller and Gawlik, 1997). The results from the
experiments comparing the three constructs (p1200A, p1200B, and p1200C), each
51
containing different regions of the -1161 to +90 insert (Figure 5, clearly indicate that the 206 to +90 fragment contained essential positive regulatory elements.
Because the NEIL2 protein repairs oxidative DNA damage, we hypothesized that
NEIL2 expression would be responsive to ROS. Consistent with this hypothesis, these
results indicate that GO treatment of MRC-5 cells transiently transfected with the p1200C
plasmid (the -206 to +90 fragment) was associated with a down-regulation of expression
at the 1hr and 6hr time points (Figure 10 These results are consistent with observations
of other investigators who identified other genes whose transcription was down-regulated
by ROS, including genes of other BER proteins such as OGG1, cytokines, and TNFα in
T-cells, as well as pro-inflammatory genes in human chondrocytes (Sun and Oberley,
1996; Morel and Barouki, 1999; Mathy-Hartert et al., 2003). These investigators have
suggested that such transcriptional down-regulation appears to be due to the inhibition of
particular transcription factors by oxidative stress (Sun and Oberley, 1996; Morel and
Barouki, 1999; Mathy-Hartert et al., 2003). Specifically, trans-activation by the Sp1
factor, the E26 transformation-specific (ETS) transcription factor, and the upstream
stimulatory factor (USF) are known to be inhibited in the presence of ROS (Morel and
Barouki, 1999). For several of these factors, protein/DNA binding is inhibited by the
abnormal protein structures that are induced by an oxidative environment (Muller and
Gawlik, 1997). It is interesting to note that there are putative USF and several putative
SP-1 sites in the -206 to +90 fragment (P1200C), located upstream but close to the
transcriptional start site (Figure 6. These sites are not identified either in the -1161 to 661 fragment (p1200A) or in the -702 to -1104 (p1200B) fragment.
A plausible
explanation for our findings with the p1200C construct could be that the oxidative
conditions induced by GO resulted in the inhibition of the binding of transcriptional
binding proteins to the DNA, thus reducing luciferase expression in cells transfected with
the p1200C construct. Additional studies are clearly needed to further explain the
observed response following GO treatment. It should be noted, however, that a recent
study by Das et al. (2007) indicated that NEIL2 protein activity is enhanced in the
presence of ROS (Das et al., 2006). This suggests that NEIL2-related repair of oxidative
52
DNA damage could be mediated through induction of protein activity, rather than by the
induction of transcription.
Expression studies involving the NEIL1 promoter by Das et al. (2006) indicate
that NEIL1 expression was induced by a short (1 hr) exposure to 100 ng/mL GO. In the
current study, the pNEIL1-luc construct was used as a positive control for oxidative
stress. Interestingly, in our study the NEIL1 promoter-driven expression decreased with
prolonged exposure to GO (Figure 10
A possible explanation for the observed
differences in results could lie in the observation that the Das et al. study (2006) used
acute exposure to GO whereas we used the prolonged exposure to GO. It has been well
established that ROS act as intracellular messengers, inducing enzymatic cascades that
affect a variety of biochemical processes; however, the length of exposure determines the
pathways that are involved (Verweih and Gringhuis, 2002). In the review by Verweih
and Gringhuis (2002), they list many different proteins that are activated during acute and
chronic exposure to ROS in lymphocytes. These are proteins involved in signaling
various enzymatic cascades, including those involved in transcriptional regulation.
During acute GO exposure, NEIL1 expression is influenced by binding of the AP-1
transcriptional activator to the NEIL1 promoter region; however, the binding factors that
could affect NEIL1 transcription during chronic exposure are unknown (Das et al., 2006).
One possible explanation for the gradual decrease in NEIL1 transcription seen in our
study is that the chronic GO exposure that we used induces repression elements of the
gene.
Also, NEIL1 expression is known to be cell cycle dependent, with highest
expression during S phase (Hazra et al., 2002). It is widely known that H2O2 is a potent
intercellular messenger. It has also been shown to induce cellular proliferation in vitro by
orchestrating S phase entry (Manasija-Radisavljevic and González-Flecha, 2003). Thus,
a plausible explanation for the decrease in pNEIL1 luciferase driven expression is that the
persistent H2O2 created by the GO is signaling the cells to move from S-phase and into
G2/M phase. In this way, pNEIL1 expression would decline with the change in cell
cycle. These explanations seem plausible and open new avenues of future studies to
examine the mechanism NEIL1 and NEIL2 expression.
53
We also note that NEIL2-driven luciferase expression from the p1200C construct,
when exposed to GO, resulted in a decrease and then a recovery of expression over time
(Figure 10 We suggest that the p1200C fragment contains DNA binding motifs for
transcriptional regulating proteins that are temporally responsive. Mauders et al. (2007)
showed that tobacco smoke, which is an ROS generator, created a temporal variation in
the expression of genes involved in the activation of trans-acting proteins. Expression of
both the SMAD4 and FOS proteins exhibited little or no change in expression at 1 hr
after exposure, then, there was a boost in expression at 6hr. At 24 hr after exposure,
expression of these proteins decreased (Mauders et al., 2007). Future studies will help to
elucidate the trans-acting proteins involved in NEIL2 expression.
This initial down-regulation and then recovery by this NEIL2 promoter region
could indicate cellular adaptation of persistent oxidative stress. If this is so and we
consider that NEIL2 expression is not cell cycle regulated, we can suggest that the role of
NEIL2 protein in oxidative DNA repair is that it is responsible for maintaining genomic
stability under normal circumstances. Furthermore, this suggests that the induction of
NEIL1 transcription observed by Das et al. (2006) is in response to acute and excessive
oxidative stress. These observations denote yet another plausible difference in the roles
of NEIL1 and NEIL2 proteins in DNA repair.
In conclusion, this study is the first to provide an initial characterization of the
NEIL2 promoter and identifies important genetic factors regulating NEIL2 expression.
Potential regions in the promoter of the gene that could affect NEIL2 transcription levels
and that are responsive to oxidative stress were identified. The results provide novel
insight into the inherent genetic mechanisms that could influence interindividual
differences in expression and, accordingly, in DNA repair capacity. This study also
identifies gaps in knowledge that need to be addressed by future studies. A particularly
vital issue is the biological effect of down-regulation of NEIL2 in response to oxidative
stress, given the potential importance of this protein in transcription-coupled DNA repair.
In rapidly proliferating tissues, reduced NEIL2 transcription could lead to increased DNA
damaged from oxidative stress and genomic instability.
54
55
CHAPTER 4:
NEIL2 GENE EXPRESSION IS INFLUENCED BY POLYMORPHIC
SITES AS WELL AS AN NF-KAPPAB BINDING MOTIF IN THE
PROMOTER REGION
Introduction
Previous chapters have described inherent and genetic factors which regulate
NEIL2 gene transcription.
The NEIL2 promoter was discovered to have a unique
structure containing a positive regulatory region from -206 to +90, as well as a negative
regulatory region from +49 to +710 (Figure 8and 9. Also, SNPs within the positive
regulatory region of the NEIL2 promoter were determined to be associated with increased
sensitivity to mutagenic environmental agents, and were found to be associated with
NEIL2 gene expression levels in humans (Table II and III). In addition, we hypothesized
that SNPs proximal to key regulatory regions impact gene regulation and DNA repair,
especially in the presence of cellular stress. To test this hypothesis, we engineered single
base pair modifications into luciferase constructs containing fragments of the NEIL2
promoter region using site directed mutagenesis. These constructs were transfected into
MRC-5 cells and luciferase expression was measured.
Materials and Methods
In silico search for putative transcriptional binding sites
The Transcriptional Element Search System (TESS) software (Schug and
Overton, 1997) was used to predict how single base changes corresponding to the newly
discovered ss74800504, ss74800505 SNPs, and the rs8191518 SNP would eliminate
existing, or create additional, cis-regulatory elements in the NEIL2 promoter sequence.
The weighted matrix function of TESS was used to identify essential base changes that
were predicted to abolish existing cis-regulatory elements. This information was used to
target specific base pairs for site directed mutagenesis. This technique allowed testing
56
the effect of base changes on NEIL2-promoter-driven expression under two
circumstances: (1) in the presence each SNP(s), and (2) in the event of a mutation that
was predicted to eliminate the binding of strong trans-acting factors.
Site directed mutagenesis and luciferase expression constructs
pSTEP1 mutations
Plasmid pSTEP1 was constructed, as previously described in Figure 4 and 6.
Briefly, pSTEP1 was created by cloning a 1871 bp fragment of the NEIL2 promoter
region (-1161 to +710) into the multiple cloning site of plasmid pGL3-basic luciferase
reporter vector (Promega, Inc., Madison, WI).
The plasmid pSTEP1 contained a
fragment of the NEIL2 promoter from base pair -1161 to +710, including previously
described positive and negative regulatory regions (Figures 7-9 For the pSTEP1
construct, the Quickchange Site Directed Mutagenesis Kit was used as per
manufacturers’ instructions (Stratagene, Inc., La Jolla, CA), to introduce three,
independent mutations.
These mutations corresponded to the SNPs rs8191518,
ss74800505, and ss74800504 (Table V).
Table V: Forward oligo primers used to introduce point mutations into
luciferase plasmids.
Primer name
rs8191518
NFkB-1
(-104 G to C)
ss74800505
ss74800504
Briefly, mutagenesis
Sequence – Single base change indicated in bold
TCTGCGGGCTGCGTAGGGGTGCTGGGTCGGGCCGAC
GCCTCCACCTACAGGCGCGTCCCCTAAGGGG
CATGGGCCGCCGAGACGGGAAATCTCCGC
TGGGTCGGGCCGACGTTCCACCCACCCGGAGC
was completed by denaturing the plasmids and then re-annealing
them in the presence of oligo primers (Table V), each containing one single base
mutation (underlined and in bold) at the intended site. These oligos acted as primers for
subsequent PCR cycles, creating a replicon that contained the intended site of mutation.
The resultant double stranded plasmid was then digested with restriction endonuclease
DpnI to selectively digest the bacterial plasmid template from the synthetic replicon.
57
This plasmid was then transformed into competent E.coli cells for amplification of the
double-stranded plasmid, containing the altered base pair. Each point mutation was
verified by direct sequencing. In this way, three sub-clones of pSTEP1 were created,
each containing single base changes corresponding to SNPs ss74800504, ss74800505,
and rs8191518 (Table VI).
Table VI – point mutations in pSTEP1 or p1200C constructs.
Constructed Plasmids
pSTEP1 with one base
change
rs8191518, ss74800505, ss74800504
pSTEP1 with two base
changes
ss74800505 + rs8191518, ss74800505 + ss74800504,
ss74800505 + (-104 GtoC)
p1200C with one base
change
ss74800505, ss74800504, (-104 GtoC)
p1200C with two base
changes
ss74800505 + rs8191518, ss74800505 + ss74800504
ss74800505 + (-104 GtoC)
p1200C mutations
Plasmid p1200C was constructed by using PCR primers to isolate a 296 bp
fragment from the pSTEP1 (-1161 to +710) insert and cloning it into the multiple cloning
site of the pGL3-basic luciferase reporter vector (Figure 9.
The p1200C plasmid
contained the putative, minimal, positive regulatory region encompassing base pair -206
to +90 (Figures 9. The Quickchange Site Directed Mutagenesis Kit was used as per
manufacturers’ instructions (Stratagene, Inc., La Jolla, CA), to introduce three
independent mutations into p1200C. Two of these mutations corresponded to the SNPs
ss74800504 and ss74800505 (Table V). In addition to these changes, a single base
change at a location 104 bp 5’ of the transcriptional start site (denoted as -104 GtoC), was
58
predicted to abolish the binding sites for the NF-kappaB and Sp-1 transcription factors.
Therefore, this base change was also engineered into the p1200C plasmid (Table VI;
Figure 11
59
(-1161)
AP-1
GACGGTGGGCTGGGCTTGTTTCCCTGTGCTGACCAAGTCCTTCCCCAGGGACCCCTCAGCTAG
AP-1/CREB
NFkB
GGTCCATGGTGACTTCACCCCAGCCTATTTCCTGAACACCTGCTGGGGAGTTCCCCAGACTTTC
CTCCCAACTTCCTGGAAAGTGCTGGCTCCCCATCCTCCTTCGAGAACTAAAGACAAGAAAACA
TATGTATCTTTAAACAGCCTATTGTTTTATCTCTTTTATTCTATGAAATAAAAAATTTAATACA
CAAATACTTTAAGCAAAATTTGCTTATAGTAAAAATTCAAGTAATAAAATTCAAATAATAGAA
AGCAAAAAAATCCCACCCGTTCAACATTTCACGAGTCTTGAACACCTGTTTCCTTTGCACCCG
ACTTCATTAGGCTCGGAGGCCAAGCAGAACCCACAGAAAGGCTTGCCATTGTGGGAACACCC
AGGCTGTCCCATTCACACACCCATTGACTTTTCCCTATAACTGTCTCCTTGAGACAAGAAATGT
TCCAAAAGGGCCGGGTGCGGTGGCTCACGCCTGTAATCCCACCACTTTGGGAGGCCGAGGAG
GGCGGCTCACCTGAGATCAGGAGTTCAAGACCAGCCTGGCCAACATGGTGAAACCCGGTCTC
TACTAAAAATACAAAAATTAGCCGGGCGCCAGTAATCCCAGCTACTCGGGAGGCTGAGGCAG
GAGAATGGCTTAAGCCCAGGAGGCGGAGGTTGCAGTGAGCCGAGATCGCGCCACTGCACTCC
AP-1
AGCCTGGGTGACACAGCGAGACTATCTCCCCCCGCAAAAAAAAAAAGTTTCCAAGAGCGTCT
CTCCAATGTTAGTCCCAGCCTGCACCCTTCTTCCATCCCTGCTTTCACTCGCGACCCTCTAATG
CAGCCCTGCCTCCAGCGACCCCCGGGATGGAACCCCTCGCCCACCCACAAAAGAGCAGCCTC
-206
GACCTAGACCCACTTTCCAGGGAATGAGCCCTGCGCCTGCGCGCACCCCGCCACCCCCTCCAG
USF
NFkB
B
SP1
GCCGGAGTCCACGCCCACTTGGGGGAGGAGCCCCGCAGCCTCCACCTACAGGGGCGTCCCCT
C
AP-1/NFkB
SP1
AAGGGGACGGAGGCCGCATGGGCCGCCGAGCCGGGAAATCTCCGCCCCCAGCTGGAGCGGCT
A
+1
D
GTGCGGGCTGCGTAGCGGTGCTGGGTCGGGCCGACGTGCCACCCACCCGGAGCCGGTGAGTG
+90
CAGCCGCCCGCCCTCCGGTAGATCTGCGGCCTGGCGGAGAAGTCGGGAGGGGACAGGAAGGG
AGGGCGGGCCCCGGGCCCTCCTCCGTCTCAGCCGCCTGCGGAGGTGCTGCCCACGCCTGGAGG
CCCCCACTGACCCTCAGACCCGCGTCTGCGCCCCTCTCCCCGCACCCCGAGGCAGAGTTGGGA
AAGCAGTGGTCTTAGACCCCCCACCTCGGGCACTCGGAAGAGAACGGCGGAGACAACCCCTC
CTCTTCCCTGGCTGGCGCAGCGCCAGCCTCGAGCTCCTCGGTAGCCCCCGGGCAGGGAGGGCC
GGAGGGTGGGCGCGGCATCTTCAGCGACTCTTCGAAGTCCCTTCCGCGTCTCATCTTTCAAGG
CTGTTGCAGAGGCGGCTTGCTTCCCACCTGTCCATCTCCATAAAAATCCCTAAACGAAACATG
AP-1/CREB
CCCACGTGTCCGGAGATTTTCAGGACTTGGTGCATTTCAGATGAAGGCTTTTCCAGAAGCTTCC
CCGTAGAAGAGGATCAGGCATCCAACTGGTTAAGGTCAGCAGCGTTTGGCACGTCTCCTTCCA
GCCTGGCGGTTTTGTCAGGATTCCCTGGGGAGTGTCTGGAAAGCCTGATGAGGGGAAATAGTA
CATCTCAGCGAATCGGCACCAGCGAGTGTAAGATGCGCGTTATTGAATGTG (+710)
60
Figure 11: The DNA sequence, encompassing the pSTEP1 fragment, that
includes the NEIL2 gene sequence flanking 5’ upstream and 3’ downstream of
the identified transcriptional start site (+1). Putative consensus sequences for
binding to regulatory factors are AP-1 (highlighted), CREB (italicized), NFkappaB
(underlined). Rectangles indicate locations of single base pair mutations: A = rs8191518,
B = NFkappaB-1 (-104 G to C), C = SNP ss74800505, D = SNP ss74800504.
This yielded three variations of the wild type p1200C plasmid with single
mutations (Table VI). A second mutation was then introduced into each of the p1200C
and pSTEP1 plasmids that already had the ss74800505 mutation, using the same
technique and respective oligos (Table V) as described above, and using the p1200C and
pSTEP1 + ss74800505 as the template for PCR amplification. This created a total of six
variations of each wild type plasmid (Table VI). The accuracy of the second base change
was verified by direct sequencing as well.
Cell culture, transfection and glucose oxidase treatment
MRC-5 cells were cultured as previously described in Chapter 2, Materials and
Methods. Twenty-four hours prior to transfection, cells were harvested from the flasks,
counted and seeded in 6-well plates at a concentration of 1.6x105 cells/well.
MRC-5 cells were transfected with the constructs as described in Chapter 2,
Materials and Methods using a mixture of 1.0 µg luciferase and 0.5 µg Renilla DNA/well
at a Lipofectamine (Invitrogen, Inc.) concentration of 6
of Lipofectamine/µg plasmid
DNA. Transfection efficiency was tested using the Dual Luciferase Reporter System
(Promega, Inc.).
Luciferase reporter gene expression was detected as described in
Chapter 2, Materials and Methods using the Dual Luciferase Reporter System (Promega,
Inc.).
Luminescence was measured in relative light units (RLUs) per L.
Each
experiment was repeated at least three times.
In addition, MRC-5 cells transfected with either the p1200C wild type (bp -206 to
+90) or p1200C (-104 GtoC) luciferase construct were treated with 100 ng/ml the cellular
oxidant GO for one hour as described in Chapter 2.(GO; Roche, Inc. Basel, Switzerland).
61
Statistical analysis.
The Student's t-test or ANOVA was used, when appropriate, to compare the mean
luciferase and Renilla expression between different plasmid constructs. All experiments were
repeated at least three times, in duplicate. All data are presented as means ± standard error (SE).
A two-sided P<0.05 was considered statistically significant.
All statistical analyses were
performed using NCSS 2004 (Kaysville, UT) or EXCEL (Microsoft, Inc.) software.
Results
Table VI shows the combinations of mutations engineered into each plasmid
using site directed mutagenesis. Point mutations corresponding to reported SNPs as well
as in a robust transcriptional element binding site were introduced into each plasmid.
The previously reported location of each SNP was used to dictate the sitedirected
mutagenesis for plasmids containing SNPs rs8191518, ss74800504 and ss74800505
(dbSNP, NCBI). The TESS software was then used to analyze the NEIL2 promoter
region in each of the plasmids for putative transcription-factor binding motifs (TESS,
University of Pennsylvania, PA). The results of this analysis showed several motifs,
including an overlapping site for the binding of NF-kappaB and Sp-1 trans-acting factors
at the -104 site (Figure 11. This binding site was chosen as a target because both of these
trans-acting factors are activated by oxidative stress (Muller and Gawlik, 1997; Schreck
et al., 1991). The weighted matrix option of the TESS software was used to show that a
G to C mutation at -104 bp 5’ from the transcriptional start site would confer a sequence
change that would disrupt the binding of both the NF-kappaB and Sp-1 proteins, thus one
mutation would test if one of these factors played a role in the regulation of the NEIL2
transcript (Figure 11.
The data indicate that insertion of single base changes corresponding to SNP
ss74800505, ss74800504 and rs8191518 resulted in no significant change in expression
compared to the wildtype pSTEP1 plasmid (Figure 12)
62
*
Relative light units
6
*
5
4
3
2
1
0
pSTEP1 wt
pSTEP1 +
pSTEP1 +
ss74800505 ss74800504
pSTEP1 +
rs8191518
pSTEP1 +
pSTEP1 +
pSTEP1 +
ss74800505 ss74800505 ss74800505
+
+ rs8191518 + (-104 GtoC)
ss74800504
Figure 12: Promoter activity from pSTEP1 constructs containing site-directed
mutations (determined in relative light units as described in Materials and Methods) * P
< 0.05.
Similarly, SNPs ss74800505, and ss74800504, and a mutation at the NF-kappaB site (104 GtoC) resulted in no significant change in expression compared to the levels of
expression from the wild type p1200C plasmid (Figure 13.
The SNP ss74800504
moderately induced expression levels above the level observed with the wild type
p1200C plasmid (P=0.054; Figure 13.
63
Relative light units
60
50
40
30
20
*
*
10
0
p1200Cwt
p1200C +
ss74800505
p1200C +
ss74800504
p1200C + (p1200C +
p1200C +
p1200C +
104 GtoC) ss74800505 + ss74800505 + ss74800505 +
ss74800504 rs8191518
(-104 GtoC)
Figure 13: Promoter activity from p1200C constructs containing site directed
mutations (determined in relative light units as described in Materials and Methods) * P
< 0.05.
To test how combinations of base changes would affect NEIL2 expression, a set
of point mutations were engineered into each plasmid (Figure 11 Table V). Insertion of
mutations corresponding to the combination of SNP ss74800505 and SNP rs8191518 into
pSTEP1 resulted in a 2-fold increase in expression over wild type (P=0.03), and a 2.6fold increase over SNP ss74800505 alone (P=0.02; Figure 12. Insertion of mutations
corresponding to the SNP ss74800505 and the -104 GtoC mutation in NF-kappaB/Sp-1
resulted in a 3-fold increase in expression over that observed with the wild type (P<0.01)
and a 3.7- fold increase over that observed with SNP ss74800505 alone (P<0.01; Figure
12.
In contrast, insertion of both SNPs ss74800505 together with rs8191518 into the
p1200C plasmid resulted in a 53% reduction in expression relative to the wild type form
(P<0.01), and a 69% reduction relative to the ss74800505 SNP alone (P<0.01; Figure 13.
Insertion of the ss74800505 SNP, together with the mutation in NF-kappaB (-104 GtoC),
resulted in a 47% decrease in expression relative to the level observed with the wildtype
(P=0.02) and a 53% decrease in expression relative to ss74800505 alone (P<0.01).
To test the response of our NEIL2 promoter constructs to excessive ROS, we
exposed transfected cells to GO. Glucose oxidase treatment of cells containing the
64
p1200C wild type construct resulted in a 46% decrease in expression relative to untreated
transfected cells (P<0.01; Figure 14. No change in expression was observed between
untreated cells and treated cells transfected with the p1200C plasmid containing the -104
GtoC mutation in the NF-kappaB/Sp-1 binding site (Figure 14.
*
25
20
15
10
5
0
p1200Cwt
p1200Cwt + GO
p1200C + (-104
GtoC)
p1200C + (-104
GtoC) + GO
Figure 14 Promoter activity for p1200C wild type and p1200C + mutation in
NFkappaB site (104 GtoC) with and without 1 hr GO treatments (determined in
relative light units as described in Materials and Methods) * P < 0.05
DISCUSSION
The goal of this study was to test the hypothesis that single base mutations in the
NEIL2-promoter region affect gene expression, in vitro. To our knowledge, this is the
first study to evaluate the mechanistic role of NEIL2 SNPs or to test the effect of a
mutation in the putative NF-kappaB and Sp-1 site (-104 GtoC) on gene transcription.
In previous studies presented in Chapter 1 of this dissertation, we showed that
SNP rs8191518 was primarily present in high expressers of NEIL2 and that SNP
ss74800505 was associated with an increase in mutagen sensitivity, indicating a potential
relationship between these SNPs and disease risk (Table II, III). Furthermore, the data
presented in Chapter 1 of this dissertation showed that SNPs ss74800505 and rs8191518
were present in a frequency of 0.33 in the population, and with a linkage disequilibrium
65
of D’=0.73 (see Chapter 1). Taken together, these data suggests that the presence of
these two SNPs, either independently or together, could alter NEIL2 gene expression and,
thus, could affect disease risk. Therefore, investigations into the mechanistic role of the
co-occurrence of SNPs ss74800505 and rs8191518 were conducted.
In the current study, an increase in NEIL2-driven expression from plasmid
pSTEP1 was observed, when both SNP ss74800505 and SNP rs8191518 were present.
These results support our in vivo findings that showed a higher frequency of SNP
rs8191518 in high expressers (Table II). Interestingly, in silico analyses of these base
changes did not predict that there would be a direct disruption of transcription factor
binding. However, SNP ss74800505 lies near an NF-kappaB/AP-1 motif (Figure 11, thus
a change at this location could potentially enhance the activation of transcription from an
NF-kappaB or AP-1 trans-acting protein in this construct. Such an affect could lead to
tighter binding or increased recruitment of these positive transcription factors.
Alternatively, this might be an additive positive effect of both SNPs, resulting in
increased gene expression.
Another possible explanation of our findings is that these base changes could be
affecting transcriptional regulation further down-stream of the SNPs.
Our previous
studies in Chapter 2 of this dissertation have shown that the pSTEP1 plasmid contains a
negative regulatory region (+49 to +710) that suppresses the adjacent, positive (-206to
+90) regulatory region (Figures 7-9 Although the silencing motif in the NEIL2 promoter
(+49 to +710) has not been completely characterized, we hypothesize that mutations
upstream of this region could change the architecture of the DNA, so that the respective
silencing factors cannot recognize the binding motif. This hypothesis is consistent with
results from several studies that have shown that transcriptional regulation is, in part,
dependent on the flexibility of the DNA, and that single base changes near the gene
transcription start site can change the ability of the DNA to bend to accommodate the
transcriptional protein complex (Breit et al., 2008; Strahs et al., 2003; Stepanek et al.,
2007; Huet et al., 2005). An example of this is the TATA element, present in many
eukaryotic promoters, and which is recognized by the TATA box binding protein (TBP)
66
through its intrinsic shape (Strahs et al., 2003). Single base changes in this element
promote less favorable geometries and result in decreased transcriptional activity (Strahs
et al., 2003). One hypothesis that is worthwhile pursuing in the future is that the base
changes introduced into the pSTEP1 construct have altered transcription in a similar
manner by disrupting the silencing mechanism that lies downstream of the start site. This
would result in an impedance of the silencing properties, and therefore, an increase in
gene expression.
The p1200C plasmid contains a strong transcription-enhancing region (-206 to
+90) isolated from the NEIL2 promoter (Figure 9. Insertion of both SNPs ss74800505
and SNP rs8191518 into this region resulted in a 2-fold decrease in expression (Figure
13. One possible explanation for this decreased expression is that two nucleic acid base
changes resulted in architectural alterations in the DNA such that binding of
transcriptional proteins was limited. This result is in contrast to the observations of the
single base change effects in the larger pSTEP1 fragment. This result is not unexpected
considering the p1200C plasmid contained only a portion of the length and regulatory
motifs as that of the pSTEP1 plasmid. Thus, single base changes in the p1200C fragment
could result in dramatically different architectural changes than that of the pSTEP1
fragment and result in the binding of different transcriptional regulating proteins.
An in silico search for putative DNA binding motifs identified several strong cisacting elements, including an over-lapping NF-kappaB and SP-1 site (-104; Figure 1).
These sites are interesting because they bind ROS-responsive transcription factors
(Schoonbroodt and Piette, 2000). Thus, one could propose that single base changes at
this location could change the transcription factor binding affinity to this site and result in
an alteration of gene transcription, particularly in the presence of oxidative stress.
Consistent with this hypothesis, the single mutation at the NF-kappaB/Sp-1 site in
combination with SNP ss74800505, increased expression significantly compared to levels
observed when the SNP ss74800505 was introduced alone into the pSTEP1 plasmid
(Figure 12.
A mutation at this site also conferred an increase in expression in
combination with SNP ss74800505 in the p1200C construct. These findings suggest and
67
integral role for SNP ss74800505 in combination with the NF-kappaB/Sp-1 in regulation
of NEIL2 promoter activity.
In our studies described in Chapter 2, we have shown that promoter-driven
expression of the 1200C construct is decreased after treatment with GO (Figure 10 In
this study, the mutation at the NF-kappaB/Sp-1 site (-104 GtoC) was found to abolished
this response. These results indicate that the NF-kappaB/Sp-1 motif at bp -104 plays a
critical role in regulating NEIL2 gene expression in response to oxidative stress. The
mechanism by which NF-kappaB is activated in the present of oxidative stress, and how
it promotes gene expression in response to increased cellular ROS and inflammatory
events is well known (Schoonbroodt and Piette, 2000).
Breifly, NF-kappaB is
sequestered in the cellular cytoplasm by binding to I-kappaB (Schoonbroodt and Piette,
2000). ROS induces a signaling cascade that results in the release of NF-kappaB from IkappaB (Schoonbroodt and Piette, 2000). NF-kappaB then moves into the nucleus to act
as a transcription factor (Schoonbroodt and Piette, 2000). Several studies have shown
that NF-kappaB binds and induces gene transcription (Schoonbroodt and Piette, 2000).
In contrast to the enhancement of expression, other studies have shown that oxidative
stress-mediated activation of NF-kappaB repressed expression of several genes, including
human 25-hydroxyvitamine D3 1-hydrolase, estrogen receptor, and 1-adrenoceptor
(Zhang et al., 2007; Van Laere et al., 2007, and Ebert et al., 2008). These studies have
shown that ROS activates the translocation of NF-kappaB protein into the nucleus, where
it binds to promoter regions of specific genes to repress expression (Zhang et al., 2007;
Van Laere et al., 2007, and Ebert et al., 2008). We hypothesize that NF-kappaB down
regulates the NEIL2 promoter fragment in the p1200C wild type construct by binding to
and repressing transcription because this response was abolished with the point mutation
in the NF-kappaB site (-104 GtoC) and no down-regulation of gene expression was
observed in the presence of GO.
Taken together, the studies described in this chapter show that combinations of
single base changes in the NEIL2 promoter region alter gene expression in vitro. Also,
the findings indicate that NF-kappaB signaling plays a critical role in NEIL2 expression
68
in the presence of oxidative stress.
These results provide suitable mechanistic
explanation for the observed inter-individual differences in NEIL2 expression observed in
population studies described in Chapter 1 of this dissertation (Figure 2). Results from
these studies open several avenues for future investigations, including further
characterization of the diverse nature of the NEIL2 promoter and larger population
studies to help understand the role of NEIL2 promoter SNPs and disease risk.
69
CHAPTER 5:
CONCLUSIONS
We found that transcription levels of the NEIL2 gene displayed a wide
interindividual variation in our population of subjects and that this variation could depend
on the presence of SNPs in the promoter region.
This implies a wide range of
interindividual variability in NEIL2-mediated DNA repair. Results presented in Table II
of Chapter 1, illustrate that several SNPs were associated with a high expresser
phenotype, while others were associated with a low expresser phenotype. This indicates
that NEIL2 expression is influenced by polymorphic variations in the promoter region of
the gene. The expression level was associated with ethnicity (Figure 3). Ethnicity is well
known to be an important determining factor for susceptibility to diseases associated with
oxidative stress, such as heart disease and diabetes, for example (Davidson et al., 2007;
Gaskin et al, 2001). Thus, ethnic groups with higher NEIL2 transcript levels could be at
lower risk for disease, relative to other groups. Our mechanistic studies have shown that
NEIL2 promoter SNPs ss74800505 and ss74800504 were associated with increased
mutagen sensitivity (Table III). As such, these studies identify critical, heritable factors
in the promoter region of the NEIL2 gene that could be considered, in the future, to
project an individual’s response to mutagenic insults.
Results from the mechanistic studies show that the combination of SNP
rs8191518 and the newly identified SNP ss74800505 significantly changes NEIL2
promoter-driven expression in vitro (Figures 11=2nd 13. These observations open the
door for several hypothesis that could be tested. One hypothesis is that polymorphic
regions are modifying the binding affinity of transcriptional proteins along the NEIL2
promoter region. In vitro results of luciferase constructs containing these polymorphic
sites support this hypothesis, by showing that constructs containing these SNPs have
altered expression levels. Furthermore, we have shown in Figure 14 that modifying an
70
NF-kappaB/Sp-1 binding motif, lying upstream of the transcriptional start site influences
NEIL2 expression when under excessive cellular oxidative stress. The identification of
an NF-kappaB/Sp-1 binding motif as a potential important regulatory region is significant
because these proteins are influenced by intra-cellular ROS.
In most studies, ROS induce the expression of genes through the activation of
transcription factors, but there are exceptions in the literature that demonstrate decreased
transcription factor binding in the presence of ROS (Reviewed by Allen and Tresini,
2000). For example, ROS reduced the DNA binding affinity of the CRE-binding protein
(CREB) and hypoxia-inducable factor 1 (HIF1) transcription factors. Furthermore, ROS
are also associated with reduced expression of several genes, including c-fos, IL-2,
CYP1A1, and CYP1A2 (Allen and Tresini, 2000). ROS also influence gene transcription
through the activation of transcriptional regulatory pathway proteins, such as NF-kappaB
and AP-1 (Allen and Tresini, 2000). This includes the activation of BER enzymes, such
as APE1 and NEIL1 (Allen and Tresini, 2000, Das et al., 2005).
ROS can also influence proteins in a post-transcriptional manner. Das et al.
(2007) showed that NEIL2 glycosylase activity was enhanced in the presence of
oxidative stress through enhanced protein-protein binding of NEIL2 to the Y-box-binding
protein-1 (YB-1). With enhanced activity, NEIL2 could play a larger role in BER. This
also suggests that the BER pathway is a fluid mechanism that reacts to external,
damaging influences, such as oxidative stress. For example, ROS are known to enhance
the activation of the DNA repair-associated protein, p53 as well as enzymes in several
transcriptional regulatory pathways (Reviewed by Allen and Tresini, 2000).
The current project shows that NEIL2 is regulated at the transcriptional level, but
in contrast to the report of reported enhanced activation of this glycosylase in the
presence of oxidative stress (Das et al., 2007), NEIL2 gene transcription is repressed in
the presence of oxidative stress produced by GO. Sequence analysis shows that this
response could be influenced by the presence of SNPs in the promoter region of this
gene. Thus, there could be a genetic component influencing the down regulation of
NEIL2 transcription in response to oxidative stress.
71
One possible explanation for why NEIL2 activity would be enhanced in the
presence of ROS, as reported by Das et al., (2007), while transcription is repressed, is that
the initial response to oxidative stress may be through the activation of the NEIL2
enzyme that is already present, followed by conservation of the transcriptional regulatory
machinery for the activation of other proteins. Because NEIL2 glycosylase/AP lyase
activity is the first step in BER, it would be logical for it to be quickly activated to initiate
the repair process.
That leaves time and cellular resources (such as transcriptional
regulatory factors) for the transcription and translation of other BER enzymes that are
responsible for later repair steps. Thus, transcriptional conservation of NEIL2 could be
part of the diversion of important transcriptional factors to the up-regulation of genes that
are important for steps farther down the enzymatic pathway. In this way, the cell could
use stored resources to efficiently initiate damage repair. In vitro studies presented in
Chapter 2 of this dissertation showed that the NEIL2 expression level decreased and then
rebound after twelve hours of exposure to GO. This may illustrate an initial conservation
of transcription by repression, followed by a release of this repression once the cellular
stores of NEIL2 protein were depleted due to oxidative stress.
The results of these studies also suggest that NEIL2 expression patterns could be
related to the global coordination of cellular DNA repair that is needed to ensure genetic
stability. ROS and ionizing radicals create highly diverse types of single-strand breaks
that are repaired by the coordinated action of proteins in the BER pathway (Dianov and
Parsons, 2007). The complexity of these lesions could require unique subsets of BER
enzymes to work together. However, uncertainty persists about which subset of proteins
repair which lesion(s) (Dianov and Parsons, 2007). Because of the novelty of the NEIL2
protein, little is known about how it interacts with other glycosylases, or how its protein
activity or gene expression could be affected by the type of lesion formed. Furthermore,
DNA glycosylases are known to interact with other non-BER pathways and this
relationship has an increasing important role in directing repair of DNA lesions (Kovtun
and McMurray, 2007). DNA glycosylases have been reported to interact with mismatch
repair (MMR) as well as nucleotide excision repair pathways (Kovtun and McMurray,
72
2007). For example, when the highly mutagenic lesion 8-oxoG is paired with a cytosine,
it is removed by the BER-specific glycosylase OGG1 (Kovtun and McMurray, 2007).
However, if it is paired with an adenine, the adenine is first removed by the MMRspecific enzyme, MYH (Kovtun and McMurray, 2007). This leaves the 8-oxoG paired
with a cytosine, the base-pair substrate for OGG1 (Kovtun and McMurray, 2007). These
observations suggest that NEIL2 could be involved in other DNA repair pathways. As
such, the observed decrease in expression of this gene in the presence of GO could be due
to cellular conservation and the balancing of available proteins to optimize DNA repair
under excessive oxidative stress. These logical explanations could be tested in future
studies.
The information gained from this project could have substantial implications for
basic research as well as clinical applications. Our mechanistic studies paved the way for
future projects that could use our NEIL2 plasmid constructs as ‘molecular tools’ to
examine the effects of other environmental factors, such as UV light, on NEIL2
expression patterns in vitro.
Such experimental studies would provide a better
understanding of the role of NEIL2 expression in disease prevention, particularly in the
presence of environmental stresses. This project also has significant practical clinical
implications in the area of cancer treatment. As discussed in the introduction, disruption
of the BER pathway has been considered as a supplementary treatment to enhance
chemotherapeutic efficacy. Understanding the factors that influence the regulation of this
gene, could help enhance cancer treatment by disrupting the BER pathway by altering
NEIL2 transcription. Furthermore, we found that two promoter SNPs are in linkage
disequilibrium and that the co-occurrence of these SNPs alters NEIL2 transcription in
vitro.
This implies that certain haplotypes in the NEIL2 promoter region could
predispose certain individuals for developing adverse health affects from ROS generating
agents. Alternatively, it could be used it identify people at low risk for developing
genetic-damage based disease as complications of conditions associated with an increase
in ROS, such as arthrosclerosis or diabetes (American Lung Society, 2008).
73
Future studies
Delineation of NEIL2 regulatory motifs
We have shown that the NEIL2 gene has several distinctive regulatory regions.
Additional studies are needed to further delineate the exact sequences responsible for
induction and suppression of NEIL2 expression. Such studies could include DNA footprint analysis to identify transcription factor proteins that bind directly to the sequences
within the positive (-206 to +90) and negative (+49 to +710) regions. Such investigations
have been informative for the promoter element of the NEIL1 gene (Das et al., 2005).
These assays could be performed under the conditions of low and high oxidative stress to
define the influence of these conditions on the binding of the factors that drive NEIL2
expression.
Haplotype analysis of the NEIL2 promoter region
Our laboratory has isolated and frozen, in accordance with a previously
established protocol, samples of DNA from human subjects. This has created a bank of
genomic DNA from over 700 individuals.
We also have extensive demographic
information on these individuals, including age, medications used, and smoking status,
and other lifestyle factors, as well as data regarding the sensitivity of the lymphocytes
from these individuals to certain mutagens. Because of the availability of these DNA
samples, new sequencing studies could be designed for specific questions. For example,
sequencing a larger portion of the NEIL2 promoter region would allow one to create
haplotype tags that could be associated with mutagen sensitivity and possible disease
risk. Such studies have been completed for several genes, including genes that code for
the repair enzyme, XRCC1, and ERCC2 (Affatato et al., 2004; Hao et al., 2004; Ng et al.,
2008; Pakakasama et al., 2007).
74
Transfection of NEIL2 promoter constructs into other cell types
The constructs created in this study should be tested in other cell lines that have
been associated with exposure to ROS in vivo. For example, muscle cells are known to
have very high metabolic activity and would be more likely to have a higher internal
level of ROS. Northern blot analysis by Hazra et al., (2000) showed muscle tissue had
the highest amount of NEIL2 expression, relative to several other tissues. It would be
worthwhile to evaluate how muscle cells regulate NEIL2 expression differently than other
tissues which have a lower expression. If one could elucidate the factors that bind and
enhance NEIL2 expression, then the next step is to identify how modifications in the
binding motif for these factors affect gene transcription.
75
APPENDIX
Table VII: Distribution of NEIL2 and XPD expression in the study population.
ID
S-310
S-311
S-385
S-294
S-271
S-305
S-315
S-295
S-246
S-418
S-475
S-407
S-379
S-360
S-404
S-155
S-417
S-391
S-218
S-296
S-558
S-297
S-617
S-301
S-421
S-448
S-346
S-648
S-344
S-200
S-291
S-357
S-317
S-309
S-347
S-832
S-402
S-711
S-744
S-469
S-447
S-863
S-489
S-427
S-638
S-767
S-520
S-490
S-461
S-838
S-444
S-170
S-375
S-669
S-470
S-401
S-422
S-728
S-434
S-864
S-672
S-705
S-677
S-451
S-458
S-843
S-268
XPD
expression
11054
14864
12024
21785
15098
21244
6682
12911
9945
11823
14666
13715
15206
16658
13742
17146
10941
7906
12552
37360
9739
9626
9511
14856
25981
9484
10033
11250
19178
13765
13633
18791
15182
17554
11974
22391
14588
14281
13267
14453
21251
15927
6909
15705
24996
24309
Smoking status
NEIL2
expression
non-smoker
non-smoker
smoker
smoker
ex-smoker
ex-smoker
ex-smoker
non-smoker
Smoker
ex-smoker
non-smoker
non-smoker
non-smoker
non-smoker
smoker
ex-smoker
ex-smoker
smoker
smoker
smoker
ex-smoker
smoker
non-smoker
non-smoker
ex-smoker
smoker
non-smoker
smoker
ex-smoker
smoker
non-smoker
ex-smoker
non-smoker
non-smoker
non-smoker
smoker
ex-smoker
ex-smoker
non-smoker
non-smoker
non-smoker
smoker
smoker
non-smoker
ex-smoker
non-smoker
non-smoker
non-smoker
non-smoker
non-smoker
ex-smoker
Smoker
non-smoker
ex-smoker
ex-smoker
non-smoker
ex-smoker
non-smoker
non-smoker
smoker
non-smoker
non-smoker
non-smoker
smoker
non-smoker
non-smoker
non-smoker
429.13
455
560.29
574.38
630.65
633.02
644.23
847.97
882.32
893.69
951.96
1015.67
1022.78
1042.01
1046.51
1051.44
1054.99
1082.43
1087.51
1100.4
1119.69
1126.13
1127.5
1140.25
1165.02
1186.61
1188.54
1197.9
1199.9
1270.26
1337.38
1368.24
1378.55
1401.2
1433.06
1448
1465.93
1477.96
1509.17
1519.94
1520.41
1573
1592.05
1595.37
1616.12
1628.91
1668.86
1696.37
1753.97
1755
1772.01
1772.16
1866.76
1886.39
1898.15
1949.12
1968.27
1979.29
1997.88
2004
2031.86
2035.78
2105.63
2164.01
2168.62
2172
2184.07
ID
S-199
S-674
S-367
S-387
S-322
S-725
S-527
S-438
S-693
S-670
S-365
S-465
S-801
S-352
S-555
S-409
S-594
S-800
S-733
S-853
S-437
S-307
S-509
S-720
S-668
S-579
S-736
S-828
S-140
S-580
S-856
S-425
S-399
S-543
S-703
S-574
S-782
S-618
S-664
S-454
S-860
S-865
S-453
S-521
S-554
S-545
S-126
S-785
S-234
S-764
S-147
S-467
S-338
S-715
S-396
S-612
S-667
S-436
S-629
S-587
S-538
S-150
76
XPD
expression
13946
14910
19630
27341
19190
11913
40107
29465
14179
12988
18584
19645
16536
37897
34008
15369
6533
10912
8661
14002
7152
25185
10754
15325
11668
13466
19376
12882
27654
18035
14918
22488
Smoking
status
NEIL2
expression
Smoker
non-smoker
non-smoker
smoker
smoker
ex-smoker
non-smoker
non-smoker
non-smoker
smoker
ex-smoker
ex-smoker
non-smoker
non-smoker
non-smoker
non-smoker
non-smoker
non-smoker
non-smoker
non-smoker
non-smoker
non-smoker
smoker
smoker
ex-smoker
ex-smoker
ex-smoker
non-smoker
non-smoker
non-smoker
non-smoker
non-smoker
non-smoker
non-smoker
non-smoker
non-smoker
smoker
non-smoker
non-smoker
ex-smoker
smoker
smoker
ex-smoker
non-smoker
non-smoker
smoker
smoker
smoker
smoker
smoker
non-smoker
smoker
non-smoker
smoker
non-smoker
non-smoker
smoker
non-smoker
non-smoker
non-smoker
smoker
non-smoker
2185.41
2210.74
2231.35
2232.94
2280.5
2285.16
2318.81
2327.67
2327.99
2328.38
2346.76
2357.81
2383
2390.75
2489.53
2512.53
2519.25
2537
2580.66
2584
2584.71
2619.86
2654.1
2672.27
2699.32
2715.73
2795.85
2823
2827.18
2959
2973
3027.81
3031.7
3153.87
3234.27
3259.82
3346.79
3351
3383
3396.3
3564
3580
3591.34
3711.61
3857.51
3863.21
4139.71
6971.99
7179.33
7964.3
10109.11
10982.44
11771.25
11834.52
14703.24
14911.98
17037.57
17466.16
18847.63
19835.65
20019.61
27183.42
Table VIII: Distribution of ethnicities, high or low NEIL2 and accumulated
chromosome breaks in study population.
ID
Ethnicity
S-310
S-311
S-385
S-294
S-271
S-305
S-315
S-295
S-246
S-418
S-475
S-407
S-379
S-360
S-404
S-155
S-417
S-391
S-218
S-296
S-558
S-297
S-617
S-301
S-421
S-448
S-346
S-648
S-344
S-200
S-291
S-357
S-317
S-309
S-347
S-832
S-402
S-711
S-744
S-469
S-447
S-863
S-489
S-427
S-638
S-767
S-520
S-490
S-461
S-838
S-444
S-170
S-375
S-669
S-470
S-401
S-422
S-728
S-434
S-864
S-672
S-705
S-677
S-451
S-458
S-843
S-268
non-Hispanic White
non-Hispanic White
African American
African American
non-Hispanic White
non-Hispanic White
Hispanic
non-Hispanic White
non-Hispanic White
non-Hispanic White
African American
African American
non-Hispanic White
non-Hispanic White
non-Hispanic White
non-Hispanic White
non-Hispanic White
non-Hispanic White
non-Hispanic White
non-Hispanic White
non-Hispanic White
non-Hispanic White
Asian
African American
non-Hispanic White
Hispanic
non-Hispanic White
African American
non-Hispanic White
non-Hispanic White
non-Hispanic White
non-Hispanic White
non-Hispanic White
Asian
Hispanic
non-Hispanic White
African American
non-Hispanic White
African American
non-Hispanic White
Asian
non-Hispanic White
Hispanic
Asian
non-Hispanic White
African American
Asian
non-Hispanic White
Asian
non-Hispanic White
Hispanic
non-Hispanic White
non-Hispanic White
non-Hispanic White
non-Hispanic White
non-Hispanic White
non-Hispanic White
non-Hispanic White
Asian
non-Hispanic White
non-Hispanic White
non-Hispanic White
non-Hispanic White
Hispanic
non-Hispanic White
non-Hispanic White
non-Hispanic White
High or low
NEIL2
expression
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
low NEIL2
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
expression
Accumulated
breaks 48 hr
after
stimulation
1
1
0
3
3
0
0
4
1
1
2
4
0
1
1
1
0
4
1
1
7
0
1
0
2
2
5
9
4
3
2
77
ID
Ethnicity
S-199
S-674
S-367
S-387
S-322
S-725
S-527
S-438
S-693
S-670
S-365
S-465
S-801
S-352
S-555
S-409
S-594
S-800
S-733
S-853
S-437
S-307
S-509
S-720
S-668
S-579
S-736
S-828
S-140
S-580
S-856
S-425
S-399
S-543
S-703
S-574
S-782
S-618
S-664
S-454
S-860
S-865
S-453
S-521
S-554
S-545
S-126
S-785
S-234
S-764
S-147
S-467
S-338
S-715
S-396
S-612
S-667
S-436
S-629
S-587
S-538
S-150
non-Hispanic White
non-Hispanic White
non-Hispanic White
American Indian
non-Hispanic White
non-Hispanic White
non-Hispanic White
non-Hispanic White
African American
African American
non-Hispanic White
non-Hispanic White
non-Hispanic White
non-Hispanic White
Asian
non-Hispanic White
African American
non-Hispanic White
non-Hispanic White
non-Hispanic White
African American
African American
Hispanic
non-Hispanic White
non-Hispanic White
non-Hispanic White
non-Hispanic White
non-Hispanic White
non-Hispanic White
non-Hispanic White
non-Hispanic White
Asian
Hispanic
Hispanic
non-Hispanic White
African American
non-Hispanic White
non-Hispanic White
non-Hispanic White
non-Hispanic White
non-Hispanic White
non-Hispanic White
non-Hispanic White
African American
Asian
non-Hispanic White
non-Hispanic White
non-Hispanic White
non-Hispanic White
Hispanic
non-Hispanic White
non-Hispanic White
non-Hispanic White
non-Hispanic White
non-Hispanic White
non-Hispanic White
non-Hispanic White
non-Hispanic White
non-Hispanic White
non-Hispanic White
non-Hispanic White
non-Hispanic White
Accumulated
breaks 48 hr
High or low
after
NEIL2 expression stimulation
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
low NEIL2 expression
high NEIL2 expression
high NEIL2 expression
high NEIL2 expression
high NEIL2 expression
high NEIL2 expression
high NEIL2 expression
high NEIL2 expression
high NEIL2 expression
high NEIL2 expression
high NEIL2 expression
high NEIL2 expression
high NEIL2 expression
high NEIL2 expression
high NEIL2 expression
high NEIL2 expression
3
0
0
5
2
5
-1
1
4
5
1
3
5
3
3
1
2
6
3
1
4
2
0
1
2
1
1
3
3
2
3
Table IX: Mean luciferase expression in NEIL2 promoter clones.
Plasmid
P1200
pSTEP3
pSTEP2
pSTEP1
p1200C
p1200B
p1200A
P1200
Mean
RLU's/g
total
protein
241.36
33.78
48.53
43.57
219.82
63.10
32.23
241.36
SE
39.64
5.69
1.72
2.71
25.87
8.54
3.89
39.64
Table X: Mean luciferase expression in pSV-40-luciferase clones
Plasmid
Mean
RLU's/g
total protein
SE
5473.63
568.24
516.17
64.70
pSV40
pSV40Step3
Table XI: Mean luciferase expression in p1200C clones exposed to GO.
Plasmid Time
p1200C
P1200c
p1200C
p1200C
pNEIL1
pNEIL1
pNEIL1
pNEIL1
0hr
1hr
6hr
12hr
0hr
1hr
6hr
12hr
Mean
RLU’s
SE
3.27
2.29
1.98
2.83
1.13
1.25
0.49
0.29
0.25
0.24
0.14
0.23
0.07
0.12
0.11
0.10
78
Table XII: Mean luciferase expression in pSTEP1 clones
Plasmid with mutation
Mean
RLU's
SE
pSTEP1 wt
pSTEP1 + ss74800505
pSTEP1 + ss74800504
pSTEP1 + rs8191518
pSTEP1 + ss74800505 + ss74800504
pSTEP1 + ss74800505 + rs8191518
pSTEP1 + ss74800505 + (-104 GtoC)
1.71
1.38
2.10
1.33
1.95
3.70
5.15
0.34
0.45
0.27
0.28
0.31
0.47
0.30
Table XIII: Mean luciferase expression in p1200C clones
Plasmid with mutation
RLU's
SE
p1200Cwt
p1200C + ss74800505
p1200C + ss74800504
p1200C + (-104 GtoC)
p1200C + ss74800505 + ss74800504
p1200C + ss74800505 + rs8191518
p1200C + ss74800505 + (-104 GtoC)
16.37
18.55
38.74
14.84
12.90
7.80
8.75
2.62
3.01
9.90
1.20
1.74
0.56
0.58
Table XIV: Mean luciferase expression in p1200C clone with mutation in the
NFkB/Sp1 site.
Plasmid with mutation
RLU's
SE
1200C wt
1200C wt + GO
1200C wt + (-104 GtoC)
1200C wt + (-104 GtoC) + GO
16.37
9.02
14.84
16.87
2.62
0.62
1.20
1.64
79
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VITA
Carla Jean Kinslow was born to parents Barbara Jean Newby-Kinslow and Gus Tavis
Kinslow in Jeffersonville, Indiana on November 27th, 1969 (just missing Thanksgiving
diner). She attended Charlestown High School and subsequently Indiana University
Southeast to earn a Bachelor of Arts in Science in 1992. During her sophomore year, she
began her research experience by taking a research associate position in the laboratories
of Gretchen Kirchner, Ph.D (Doc) and David Taylor, Ph.D. In 1993, she began graduate
school at Michigan Technological University as a Challenge Fellow in the laboratory of
Gopi Podilla, Ph.D. In 1997, Carla received her Master of Science in Biology and went
on to take a position as Scientist at Gene Medicine, Inc. (later, Valentis, Inc.) in The
Woodlands, Texas. She then took a research associate position with Dr. Robert Giles in
the Vector Core Facility at MD Anderson Cancer Center, Houston, Texas. She then
began her own environmental consulting business, Kinslow Consulting, and subsequently
created environmental groups for other engineering companies. In 2003, she entered into
the Graduate School of Biological Sciences program at the University of Texas Medical
Branch, Galveston, Texas. While there, she joined the laboratory of Sherif AbdelRahman, Ph.D. to explore genetic associations to disease risk. While at graduate school,
Carla received several honors. In 2003, she received an NIEHS Toxicology Scholarship
and subsequently a Toxicology Fellowship in 2005. In 2006 she received the Who’s
Who Among American Colleges and Universities award from UTMB. Since 2003, Carla
has been invited to present at eight regional and national platform presentations and
competed an internship with the Proctor and Gamble Company in Cincinnati, OH.
Education
B.A. Science, May 1992, Indiana University Southeast, New Albany, IN
M.S. Biology, November 1997, Michigan Technological University, Houghton, MI
Publications
Carla J. Kinslow, Randa A. El-Zein, Courtney E. Hill, Jeffrey K. Wickliffe and Sherif Z.
Abdel-Rahman. (2007) Interindividual Variability in NEIL2 Gene Transcription in
Human Peripheral Blood Lymphocytes, Carcinogenesis, Submitted
Hill CE, Wickliffe JK, Guerin AT, Kinslow CJ, Wolfe KJ, Ammenheuser MM, AbdelRahman SZ. The L84F polymorphism in the O6-Methylguanine-DNA-Methyltransferase
(MGMT) gene is associated with increased hypoxanthine phosphoribosyltransferase
(HPRT) mutant frequency in lymphocytes of tobacco smokers. Pharmacogenet
Genomics. 2007 Sep;17(9):743-53.
The L84F and the I143V polymorphisms in the O6-methylguanine-DNAmethyltransferase (MGMT) gene increase human sensitivity to the genotoxic effects of
92
the tobacco-specific nitrosamine carcinogen NNK.
Aug;15(8):571-8.
Pharmacogenet Genomics. 2005
C.J. Kinslow (1997) Master’s thesis – Molecular Biology of the marine diatom
Achnanthesis longipes. Michigan Technological University.
G. Kirchner, C.J. Kinslow, G.C. Bloom, and D.W. Taylor (1993). Nonlethal assay
system of b-Glucuronidase activity in transgenic tobacco roots. Plant Molecular Biology
Reporter 11(4); pages 320-325.
93