1. Effects of ethanol-induced oxidative stress
on antioxidant enzyme gene expression in three
tissues of the zebrafish, Danio rerio
Under Graduate Senior Thesis
Submitted to the Division of Biology
at Bard College
by
Hannah Shapero
Annandale-on-Hudson, New York
May 2, 2012

2. 2
TABLE OF CONTENTS
Acknowledgements………………………………………………………………………………3
Abstract….………………………………………………………………………………………..4
Introduction……………………………………………………………………………………....5
Oxidative stress……………………………………………….…………………………...5
Sources of ROS…………………………………………………………………………...5
Mechanisms of oxidative DNA damage…………………………………………………..8
Antioxidant Protective Mechanisms……………………………………………………..10
Oxidative Stress and Cancer……………………………………………………………..11
Affect of Ethanol on Oxidative Stress…………………………………………………...13
Danio rerio as a Model…………………………………………………………………...16
Diverse Tissue Analysis……………………………………………………………….....17
Objectives………………………………………………………………………………..18
Materials and Methods………………………………………………………………………....20
Animal Care……………………………………………………………………………...20
Exposure………………………………………………………………………………....20
Dissection………………………………………………………………………………..22
RNA Extraction……………………………………………………………………….....23
Reverse Transcription…………………………………………………………………....23
Quantitative PCR………………………………………………………………………...25
Data Analysis………………………………………………………………………….....25
Results…………………………………………………………………………………………...28
Brain Enzyme Expression Levels………………………………………………………..28
Liver Enzyme Expression Levels………………………………………………………..29
Gonad Enzyme Expression Levels……………………………………………………....30
Discussion…………………………………………………………………………………….....31
Brain Tissue……………………………………………………………………………...31
Liver Tissue……………………………………………………………………………...32
Gonad Tissue………………………………………………………………………….....34
General Conclusions……………………………………………………………………..35
Future Direction……………………………………………………………………….....39
References…………………………………………………………………………………….....41
Tables…………………………………………………………………………………………....44
Figures…………………………………………………………………………………………...45
Appendix………………………………………………………………………………………...49

3. 3
ACKNOWLEDGEMENTS
Board members
Philip Johns (Adv.), Assistant Professor of Biology, Bard College
Mike Tibbetts, Associate Professor of Biology, Bard College
Celia Bland, Writer in Residence, Bard College
Lab Technicians
Maureen O’Callaghan-Scholl, Lab Manager, Bard College
Dwane Decker, Lab Technician, Bard College
Diana Gutierrez, Lab Technician, Bard College
Peer Editing
Katherine Hoople, Assistant Researcher, Astor Services
Sarah Taylor, Graduated Student, Bard College
Ella Jacobson, Student, Bard College
Tyler Martinez, Graduated Student, Vassar College

4. 4
ABSTRACT
All aerobic organisms rely on oxygen for survival. Oxygen is an essential component of many
cellular processes including cellular metabolism, intercellular and intracellular signaling and
immune system response. Oxygen through generation of reactive oxygen species (ROS) can
severely damage with DNA, proteins and other cellular components becoming problematic
(Kryston et al. 2011). Organisms have evolved ways to balance the essential and detrimental
effects of oxygen within the cellular environment. Antioxidant enzymes are proteins produced by
cells to minimize the harmful affects of oxidative damage caused by ROS (Barzilai and
Yamamoto, 2004). Ethanol, which is a widely consumed drug, can exacerbate the damaging
effects of oxygen through the production of excess ROS involved in ethanol metabolism. This
study measured the production levels of 3 key antioxidant enzymes (CuZnSOD, MnSOD and
CAT) in the brain, gonads and liver of zebrafish during and after exposure to ethanol.
Antioxidant enzyme production will be measured by qPCR of cDNA transcribed from RNA
samples extracted directly from tissue. It was found that different tissues show remarkably
different expression patterns of antioxidant enzymes under the same conditions of acute alcohol
exposure. Brain tissues show no significant change in antioxidant expression levels. The highest
expression levels were found in gonad tissue. This study gives insight into the beneficial effects
and transcriptional mechanisms of antioxidant enzymes in response to oxidative damage, which
may protect DNA from excess reactive oxygen species produced by acute ethanol exposure.

5. 5
INTRODUCTION
The oxygen paradox is possibly the most frustrating aspect of aging and disease research,
strongly implicated in cancer tumerogenesis and other age related diseases. The oxygen paradox
refers to how oxygen is dangerous to the life forms for which it is essential. Oxygen plays a
significant role in many processes of the human body including cellular metabolism, intercellular
and intracellular signaling and immune system response. Oxygen through generation of reactive
oxygen species (ROS) can react with DNA, proteins and other cellular components and become
problematic. (Kryston et al. 2011). There is a narrow nomoxic range of oxygen which must be
steadily maintained by the production and function of antioxidant enzymes within cells to
minimize the harmful affects of oxidative damage caused by excessive oxygen (hyperoxia) and
metabolic demise caused by insufficient oxygen (hypoxia) (Barzilai and Yamamoto 2004)
Oxidative Stress:
Reactive oxygen species are small, highly reactive, oxygen-containing molecules that can react
with and damage complex cellular molecules, particularly in the liver (Wu and Cederbaum
2003). ROS are constantly produced within living cells during normal metabolic processes

6. 6
within cellular mitochondria and pathological processes such as inflammation as well as during
incomplete metabolism of ethanol. At normal physiological levels, ROS play a vital role in
regulating signaling pathways and gene expression. Maintaining their production below a toxic
threshold is important to normal cellular function (Barzilai and Yamamoto 2004). Approximately
2 x 104 DNA damaging events have been estimated to occur in every cell of the human body
every day. A significant portion of this damage is caused by reactive oxygen species, because
they are generated as by-products of respiration.
ROS are the most abundant toxic agents found in aerobic organisms (Barzilai and Yamamoto
2004). The most commonly detrimental ROS are the hydroxyl radical, the superoxide radical and
non-radical hydrogen peroxide (Evans et al. 2003). Cellular targets for these ROS include DNA,
lipids and proteins. Modified lipids and proteins are readily removed by the normal turnover of
cellular molecules, but damage to DNA is not easily dealt with and must be repaired.
Living cells have evolved a number of defenses against damage from ROS and other free
radicals. Low molecular weight compounds, known as antioxidants intercept free radicals,
becoming radicals themselves; complex antioxidant enzyme reactions such as superoxide
dismutase, catalase and glutathione peroxidase limit cellular levels of ROS. Even under normal
functional conditions there is a propensity for ROS to evade these defenses, resulting in low
levels of damage, which in the short term do not appear detrimental to the cell (Evanset al.
2003). It is when an imbalance arises between ROS-producing factors and antioxidant defenses,
which cellular damage occurs.

7. 7
Sources of ROS:
Oxidative stress is inflicted on cells both endogenously and exogenously. Intracellular
attacks corresponding with a number of regular cell processes such as cell signaling,
inflammation and metabolism cause more extensive damage to DNA then environmental factors.
Endogenously induced DNA lesions contribute significantly to the accumulation of DNA
mutations in cells and tissues. ROS are generally accepted as the major source of oxidative injury
in all aerobic organisms, and are constantly being produced as byproducts of normal cellular
processes such as mitochondrial respiration and chronic inflammation (Kryston et al. 2011).
Mitochondrial electron transport constitutes the majority intracellular source of ROS (Bailey and
Cunningham 2002). Mitochondria are also intimately involved in the generation and defense
process involved with reactive oxygen species. Mitochondria are both targets of oxidative stress
directly and involved in the mechanisms by which oxidative stress-related signals can lead to
apoptosis. Formation of ROS within the mitochondria promotes activation of the mitochondrial
permeability transition, which in turn leads cells towards pro-apoptotic pathways, and eventually,
complete apoptosis.
A second common source of ROS is the O2 and H2O2 generated during the respiratory burst of
invading neutrophils, macrophages and eosinophils associated with inflammation and defense
against infection. Inflammation initiates a cycle of events in which ROS-damaged tissues release
cytokines, which promote the infiltration of further inflammatory cells, in a positive feedback
loop responsible for chronic infection. Chronic infection, and the associated rise in oxidative

8. 8
stress can lead to severe tissue damage in the surrounding tissue. Continuous inflammation can
lead to cellular damage and cancer (Reuter et al. 2010). Under sustained oxidative stress,
significant damage has been shown to occur to surrounding cells and tissue structures (Reuter et
al. 2010). Damage may induce somatic mutations and neoplastic transformations within ROS
exposed tissue.
Mechanisms of oxidative DNA damage:
DNA is a main target of oxidative damage. ROS interact with biological molecules and disrupt
the normal synthesis and repair processes of DNA. ROS can cause a number of changes to DNA
structure, including strand breaks, point mutations and aberrant DNA cross-linking. These can
create mutations in both proto-oncogenes and tumor-suppressor genes, all of which promote
neoplastic transformation (Reuter et al. 2010). The cumulative effects of the interaction of DNA
with ROS are determined by several factors, including DNA repair, transcriptional and
functional levels of antioxidant enzymes, and accessibility of free radicals to react with DNA.
Highly reactive hydroxyl radicals lead to a number of complex oxidative reactions within the
DNA molecule and it’s nucleic acids (Evans et al. 2003). Hydroxyl radicals add to double bonds
of heterocyclic DNA bases and remove an H atom from the methyl group of thymine and from
each of the C-H bonds of 2’-deoxyribose, Covalent DNA-protein cross-links are shown to form
in cells in vivo by exposure to free radical-generating systems (Evans et al. 2003). The
mechanism of DNA-protein cross-linking involves the addition of the allyl radical of thymine in
DNA to tyrosine in a protein, fallowed by oxidation. Oxidative damage to DNA produces a

9. 9
number of purine and pyrimidine-derived base lesions (Evans et al. 2003). The removal of these
lesions by cellular repair processes is crucial in terms of limiting mutagenesis.
DNA mutation is perhaps the most important consequence of lesion persistence (Evans et al.
2003). Cells have multiple systems in place to prevent lesion formation and ensure rapid repair.
There is some overlap in substrates of DNA repair systems. Under normal conditions, cellular
systems are continually generating ROS, creating a great potential for cellular damage, despite
cellular protective mechanisms. DNA is one of the most important cellular targets with which
these damaging species interact (Evans et al. 2003). ROS damage various cellular proteins
responsible for DNA repair, cell cycle control, cell death etc. This creates a positive feedback
loop leading to the accelerated accumulation of oxidative damage to DNA. (Kryston et al. 2011)
Every cell of an organism is continuously exposed to exogenous and endogenous agents that
damage its DNA. There are many types of lesions, which these harmful exposures can cause the
most dangerous DNA lesion is the double-strand break. A single double stranded break can
cause apoptosis, gene inactivation or lead to serious chromosomal aberrations (Barzilai and
Yamamoto 2004). Cells have evolved a number of mechanisms to deal with this damage by
limiting its occurrence and developing repair mechanisms.
When considering the role of oxidative DNA damage in disease, it is important to remember that
ROS cause damage to many structures besides DNA and these disruptions most likely play a key
role in the development of disease. ROS do not need direct access to cellular DNA to have

10. 10
dramatic cellular effects. Modification to other proteins such as DNA polymerases can be just as
mutagenic as disruptions to the DNA itself. (Evans et al. 2003).
Antioxidant Protective Mechanisms
A variety of protective cellular mechanisms exist to control the balance between production and
removal of ROS. These include both endogenous and exofenous as well as enzymatic and non-
enzymatic components. Antioxidant enzymes are the most specific and efficient in protecting
cells from ROS (Reuter et al. 2010). Superoxide dismutases (SOD’s) and catylase (CAT) are key
enzymes for the detection and clearance of ROS, found in all aerobic organisms (Ballesteros et
al. 2008). Both endogenous exymatic and non-enzymatic antioxidants participate in the
conversion of ROS to harmless substances and for protection of normal cellular function.
Antioxidant enzymes have large potential for use in disease treatment, but little is known about
their regulation by cells in response to different damaging ROS. Potentially, up-regulation of
specific antioxidant enzymes could limit cell damage or even reduce disease risk (Mruk et al.
2002). Removal of free radicals from the cellular environment involves multiple intricate
cascades of enzymes.
Super oxide dismutases are a specific category of antioxidant enzymes that dismutate superoxide
radicals (O2
-) into hydrogen peroxide (H2O2). Hydrogen peroxide is then converted into H2O by
catalase. Catalase (CAT) is a heme protein located predominantly in the peroxisome in the inner
mitochondrial membrane (Mruk et al. 2002). SODs are categorized and labeled by the transition

11. 11
metal found at their active site. Manganese-superoxide dismutase (MnSOD) is found most
commonly within the mitochondria of eukaryotes and copper-zinc-superoxide dismutase
(CuZnSOD) is most abundant in the cytosol. There is a third type of SOD, iron-superoxide
dismutase but it was not examined in this study because it is never found in eukaryotes.
SODs were the first characterized antioxidant enzymes and are of vital importance in protecting
cells from oxidative damage by ROS. Both CuZnSOD and MnSOD are able to dismutate
reactive oxygen (O2
-) anions into H2O2 and stable oxygen (Reuter et al. 2010). H2O2 is still
reactive and harmful to cells. Catalase is the main enzyme responsible for the breakdown of
H2O2 into water (Reuter et al. 2010). This 2-step process neutralizes and removes harmful ROS
from the cellular environment and protects cellular structures, including DNA, from damage.
The antioxidant defense system is of increasing interest to researchers because of its ability to
provide biochemical biomarkers of oxidative stress and damage (Bellesteros et al. 2008.)
Oxidative Stress and Cancer:
Reactive oxygen species are implicated in various pathological events such as DNA mutations,
carcinogenesis, aging, atherosclerosis, radiation damage, inflammation, neurodegenerative
diseases, and toxic injuries (Evans et al. 2003). Through a diverse range of mechanism ROS have
been clearly implicated in various phases of tumorigenesis (Reuter et al. 2010). ROS are
produced readily during normal processes of metabolization and has many negative effects on
the body; the most widely studied of which are its implications in tumerogenesis and cancer.

12. 12
Recent evidence supports the implication of persistent or chronic oxidative stress and damage in
human cancer. No direct mechanism has yet to be determined, but is thought to involve the
conversion of unrepaired DNA lesions into mutations, leading to cell transformation and
carcinogenesis (Evans et al. 2003). Recent studies make it clear that mutations involving genes
for DNA repair, cell growth and apoptosis related proteins plays a role in the promotion of
chromosomal instability and malignancy. (Kryston et al. 2011)
Carcinogenesis is a complex, multistep process dependant on an accumulation of genetic
mutations leading to malignancy. Included in this process is often, activation of proto-oncogenes
and inactivation or loss of tumor suppressor genes. Oxidative mechanisms have been shown to
have a potential role in all of these steps (Evens et al. 2003). Evidence for this necessary
accumulation of mutations, known as the multiple hit hypothesis, relies mainly on the cumulative
cancer risk increase with the fourth power of age, associated with an accumulation of DNA
damage due to incomplete cellular maintenance and repair.
Because cellular systems are continually generative ROS, the potential for damage to cellular
targets, such as DNA, is high. These high levels of oxidative DNA lesions along with their
propensity for guanine-containing regions are shown to correspond with observed mutations in
tumor suppressing genes ras and p53, both of which are implicated in malignant transformation.
GCTA transversions have been observed in both the ras oncogene and the p53 tumor
suppressor gene (Evenas et al. 2003). Because 8oxydG is a common product of DNA lesions to
guanine-containing regions, it is not only an accurate biomarker of oxidative stress.

13. 13
Oxidative DNA damage is gaining recognition as an important risk factor in various forms of
cancer. The transformation relies on persistent oxidative stress in cancer, derived from an
environment low in antioxidant enzymes and high in ROS. This damage leads to the irregular
activation of transcription factors, such as proto-oncogenes, leading to increased genomic
instability and sometimes leading to cellular malignancy (Evans et al., 2003). ROS are important
in carcinogenesis. This is supported by the close link between ROS formation and oxidative
DNA damage and the implication of DNA damage and mutation in carcinogenesis (Evans et al.
2003). There are numerous reports of oxidative DNA damage being caused by known
carcinogens and elevated levels of such damage associated with a wide range of malignant
tumors (Evans et al. 2003).
Effect of Ethanol on Oxidative Stress:
Ethanol (EtOH) is a popular drug widely consumed throughout the world. The consumption of
alcohol has been linked to a number of pathological conditions including several forms of
cancer, liver failure, brain damage and fetal injury (Rosenberg et al. 2010). Because of the
severity of these conditions and the high rate of alcohol consumption, it is worth looking more
closely at the processes by which damage occurs and mechanisms by which organisms prevent
and repair this damage. An understanding of these mechanisms could yield therapeutic benefits.
There are three distinct enzymatic pathways responsible for alcohol metabolism within the liver.
Hepatocytes are specialized liver cells capable of detoxification and are responsible for the
metabolization of alcohol (Dey and Cederbaum 2006). The cytosolic hepatic alcohol

14. 14
dehydrogenase (ALDH) pathway is the main pathway responsible for the metaboliaztion of
EtOH, accounting for 90% of alcohol oxidation and metabolism within hepatocytes exposed to
ethanol (Lassen et al. 2005). This oxidation leads to the production of acetaldehyde, which can
accumulate within cells and cause severe damage if not properly and quickly metabolized.
Acetaldehydrogenases (ALDH’s) are responsible for detoxification and metabolism of
acetaldehyde, making this process of utmost importance to cells.
Ethanol has been shown to lead to an increase in ROS within tissues in a number of ways
creating a complex positive feedback loop, leading to extensive tissue damage. Ethanol is not
stored in the body and therefore whatever is ingested is oxidized. Ethanol metabolism by the
ADLH pathway is directly involved in the production of reactive oxygen species, and also
creates a cellular environment favorable to oxidative stress which can lead to further ROS
production such as hypoxia, endotoxaemia and cytokine release (sergent et al. 2001). At the
same time, alcohol reduces the levels of antioxidants present that are constantly working to
eliminate ROS (Das and Vasudevan 2007).
Alcohol changes the structure of the mitochondria within liver cells, where metabolism takes
place. Alcohol damaged mitochondria are enlarged and distorted with distorted or broken cristae
(Swift 2003). These changes lead to less effective metabolism by mitochondria, which are
intimately involved in the generation and defense against intercellular ROS. In all cells ethanol
decreases the capacity for the mitochondrion to carry out protein synthesis, which can lead to
further ROS production in a positive feedback loop.

15. 15
Damage to cellular proteins and lipids occurs as a result of chronic ethanol consumption.
Proteins are targets of free radicals and ROS, Which further compromise the mitochondrial
membrane polarization. Membrane polarization is essential for ATP synthesis within the
mitochondria (Reuter et al. 2010). Acetaldehyde and aldehyde (oxidized lipids) can bind to
proteins and form stable adducts, which can lead to interference with protein function, and in
some cases, induce an inappropriate immune response and inflammation.
With repeated ethanol exposure, levels of antioxidant enzymes and other, cellular defenses are
gradually diminished. This leads to an again increased toxicity as a result of prolonged ethanol
exposure. Constructing a better understanding of the mechanisms by which alcohol promotes
oxidative stress and the role of free radicals in alcohol-induced tissue injury are clearly important
in attempts to look for effective therapies to prevent or diminish the toxic effects of alcohol. (Das
and Vasudevan 2007).
Alcohol is a major risk factor for disease (Das and Vasudevan 2007). There is a great potential
for the usage of oxidatively generated DNA damage biomarkers (such as 8-oxydG and
transcriptional levels of key proteins) towards detection and treatment of cancer and other
diseases. The exploitation of new ‘cancer biomarkers’ has the potential to contribute
significantly to early prognosis and design of more efficient therapeutic treatments especially in
oxidative stress-related malignancies. (Kryston et al. 2011)

16. 16
Danio rerio as a Model:
The zebrafish (Danio rerio) is emerging as a promising model organism for experimentation in
biochemical research. Zebrafish are inexpensive, low maintenance and share 70-80% genetic
homology to humans (Rosenberg et al. 2010). Zebrafish have been shown to react to exposure to
oxidative stress on a cellular level. Specifically, alterations in the antioxidant defense system of
fish have been observed in response to sub-lethal concentrations of certain harmful substances,
which may be due to an adaptive response to ROS (Bellesteros et al. 2008) Dlugos and Rabin
(2002) present data that zebrafish are an excellent model for studying genetic interactions with
alcohol. In fish, as in humans, sensitivity and response to alcohol are highly influenced by
genetics.
Zebrafish have been extensively used for biomedical research and as a result a huge database of
information is available and the genome has been entirely sequenced (Dlugos and Rabin 2002).
Zebrafish are more closely related to humans then c. eligans or Drosophila while still being easy
and inexpensive to maintain. This homology makes findings more relevant to human disease
research. Fish readily absorb alcohol from their environment and reach steady-state brain-ethanol
levels at 90% the concentration of their environment within 15 minutes of exposure (Dlugos and
Rabin 2002). These levels can be maintained for over a week constant exposure. Based on this,
blood alcohol levels of fish can be assumed without having to do invasive tests.
Previous studies have demonstrated behavioral changes induced by acute EtOH exposure during
1 hour and that EtOH-mediated toxicity in zebrafish embryos can be partially attenuated by
antioxidants (Reimers et al. 2006). Zebrafish are ideal for modeling the effects of EtOH because

17. 17
of the simplicity of alcohol delivery into their system from their immediate environment. EtOH
is absorbed by the blood vessels of the gill and the skin so that blood alcohol levels reach
equilibrium with the external alcohol concentration (Rosenburg et al. 2010).
Diverse Tissue Analysis:
Little has been done to examine how the effects of oxidative stress may be different between
different tissues within a single organism. This is important in understanding cellular and tissue
defenses and how they may differ between differentiated cell types. Certain tissues, such as
cardiac and brain tissues have been shown to be far more sensitive to oxidative damage.
The work of Bellesteros et al. (2008) concluded that SOD and other antioxidant enzymes
respond to oxidative stress differently within different organs. This emphasizes the need to
evaluate biomarkers in several different organs of fully asses the adaptive response of cellular
tissues to ROS (Bellesteros et al. 2008).
Ethanol exposure leads to a number of cerebral effects in both zebrafish and humans. Impairment
of motor coordination, sensory perception and cognition can be related to oxidative damage to
nervous system tissue in the brain (Rosenberg et al. 2010).
Sperm are particularly sensitive to oxidative damage because their plasma membranes are
enriched with unsaturated fatty acids, which are easily oxidized by ROS (Aiteken and Krausz
2001). The addition of catalase has been shown to partially alleviate these effects. Mutations

18. 18
within germ-line DNA are more detrimental then in other cells because they are passed directly
onto the next generation (Aiteken and Krausz 2001). Based on these facts it is assumable that
germ-line cells within the gonads may respond differently to an increased presence of ROS
produced by alcohol metabolism.
Objectives:
Little is known about the effects of EtOH on the adult zebrafish and on the specific pathways it
may induce during digestion. Rosenburg et al. (2010) examined the effects of EtOH induced
oxidative stress on the brains of adult zebrafish; but the influence of acute EtOH exposure on
oxidative stress and antioxidant response pathways that may inhibit cellular damage in different
tissues of the adult fish still remain unexamined.
This study aims to explore mechanisms of reactive oxygen species production within aerobic
tissues induced by moderate exposure to ethanol. Closely observing and quantifying the effects
of induced oxidative stress in living tissues may lead to a better understanding of this process and
it’s immediate effects to living tissue. This study will focus on the production levels of 3 key
antioxidant enzymes (CuZnSOD, MnSOD and CAT) in the brain, gonads and liver of zebrafish
during and after exposure to ethanol. Antioxidant enzyme production will be measured by qPCR
of cDNA transcribed from RNA samples extracted from tissue. This study aims to investigate the
beneficial effects and transcriptional mechanisms of antioxidant enzymes in response to
oxidative stress, which may protect DNA from excess reactive oxygen species and lessen the
detrimental effects of oxidative stress.

19. 19
I hypothesize that exposing adult zebrafish to ethanol will cause an increase in oxidative damage
to DNA in all tissues; the damage will be greater in tissues where ethanol is metabolized and
those most sensitive to reactive oxygen species. This increase in oxidative stress is expected to
correlate with an early rise in the production of SOD molecules.

20. 20
MATERIALS AND METHODS
Animal Care:
Adult zebrafish (3-6 months) of the wild type (Short Fin- SF) Danio rerio strain between 3 and 6
months old were obtained from a local supplier (Petsmart, Kingston NY). 20 Fish were kept in a
10-gallon tank for 3 days prior to exposure experiments. During this time fish were acclimated at
standard conditions. The tank was filled with 10 gallons of water treated with 5mL Aqueon
Water Conditioner (Central aquatics, Franklin WI) circulated by a single TopFin Power Filter
(Petsmart, Phoenix AZ). Fish were fed once a day with Tetramin Tropical Flakes (Tetra Holding,
Blacksberg VA). Fish for each experimental treatment group were randomly selected at the time
of the experiment.
Exposure:
Immediately before exposure, 4 fish were randomly selected and removed from the 10-gallon
tank for dissection. This is referred to as 0H and this first group is the control group, with no
ethanol exposure. Ethanol was then added to the 10-gallon tank with the remaining 16 fish to a
final concentration of 1.0% EtOH by the addition of 10mL 100% EtOH. 4 hours later, 4 more
fish were randomly selected and removed for dissection. This is the 4H group, exposed to 4

21. 21
hours of EtOH. Fish were removed for dissection again at 8 hours (4 hours later). After these fish
were removed for the 8H group, all remaining fish were moved to a smaller tank of fresh
conditioned water to recreate the initial conditions before ethanol exposure. 4 hours after being
moved to the pure water tank 4 more fish were randomly selected for dissection as the 12H
group. Remaining fish were returned to population tanks and not used again.
Figure 1: Diagrams the experimental procedure for ethanol exposure. 0h refers to the
control group, which was removed from the tank (pictured in the middle top) just prior to
the addition to ethanol. 4h refers to the group of 4 fish, which were removed and dissected
after 4 hours of ethanol exposure. 8h refers to the fish removed after 8 hours of ethanol
exposure. After fish were removed for the 8h group, the remaining fish were moved to a
new tank of pure whater, represented here as EtOH removal. Time increases moving down
the figure from the tank to the clock.

22. 22
Dissection:
Fish were randomly chosen and removed from the 10-gallon tank and anesthetized in ice water
for 5-10 minutes. A single fish was pined onto the dissecting mat in the prone position with two
pins. The dissecting mat was placed on the field of a dissecting microscope. A scalpel was used
to cut the skin along the plantar surface from the anal fin along the belly of the fish to the
operculum. Dissecting scissors were used to remove the operculum, pectoral fin and pectoral
girdle.
Forceps and blunt dissection with a scalpel were used to open the thoracic cavity starting from
the lower jaw along the cut line to the anal fin. Liver and intestines were carefully removed from
the cavity in one piece and placed on the dissecting mat. All extraneous connective tissue was
removed from the liver and intestines (left in one piece) using forceps and dissecting scissors.
The liver and intestines were then placed in a labeled 2.5mL micro-centrifuge tube and placed on
ice. The intestines were used along with the liver because the livers themselves were difficult to
identify and too small to yield sufficient RNA. It is assumed that damage to liver tissue is
comparable to damage to the intestines as both take part in digestion of EtOH.
At this point the gonads can be identified easily within the empty body cavity. Forceps and blunt
dissection were used to remove both testes (one from each side of the open cavity). Both were
placed together in the same, labeled 2.5mL micro-centrifuge tube and placed on ice.
Next the fish was unpinned and the head was removed using a scalpel. The body was removed
and the head was pinned back to the dissecting mat ventral side up. Forceps were used to

23. 23
carefully break the scull and remove as much bone and connective tissue as possible. The brain
was carefully removed using forceps and dissecting scissors. Once removed and clean of bone
fragment the brain was placed in a labeled 2mL micro-centrifuge tube and placed on ice. The
three individual and labeled tubes were placed in liquid nitrogen immediately for storage. This
process was repeated for the other 3 fish. Dissection occurred immediately fallowing removal
from the tank.
RNA Extraction
Total RNA extraction was preformed on each sample using mirVana isolation kit (Life
Technologies, Grand Island, NY). RNA was extracted and isolated according to the maufacturers
protocol (mirVana miRNA isolation kit protocol, Life Technologies Corporation 2011). Tissues
were frozen homogenized manually by grinding them thoroughly with a pestle while still frozen.
Aqueous layers were separated by chloroform and total RNA was collected and washed on
collection filters. Total RNA was eluted in elution solution into 1.5uL microcentrifuge tubes.
Nucleic Acid concentration for each sample was measured using a nanodrop. Samples were
immediately placed in a -20˚ freezer. Experiments were done previously (data not shown) to
determine the mirVana isolation kit to be the most effective method of RNA extraction from
frozen tissue.
Reverse Transcription:
Extracted RNA was used to create cDNA by reverse transcription (rtPCR) using applied
biosystems RNA-to-cDNA kit and mastermix according to the manufacturer’s protocol (Applied

24. 24
Biosystems, Foster City CA). RNA samples were first diluted to comparable concentrations.
This was done in standard 96 well plates (Fig 3), which was the standard organization for the rest
of the data collection and analysis. PCR (DNAenfine peltier thermal cycler, BioRad, Foster City,
CA) settings were programmed according to manufacture’s protocol. 8uL of RNA was used for
each reaction, and each sample was transcribed 4 separate times as it appears on the two plates in
preparation for qPCR. Nucleic acid concentrations for each sample were measured using
nanodrop. Samples were immediately.
Figure 2: Diagrams the experimental procedure for RNA extraction, rtPCR and qPCR. There
were a number of steps used to measure expression levels of antioxidant enzymes, which
are listed in this flow chart.

25. 25
Quantitative PCR:
Quantitative PCR (qPCR) was used run on all samples for each MnSOD, CuZnSOD, CAT and
Actin-ß using primers (table 1). Actin-ß was used as to control in differences in overall
expression levels as it is a standard housekeeping gene expressed at a relatively constant level.
Actin-ß was used as an internal control and each expression level of antioxidant enzyme was
normalized to the Actin-ß expression level for the corresponding sample. PCR was run on a BIO
RAD CFX96 reaction system (BIO RAD, Hercules CA) using SYBRGreen supermix (Applied
Biosystems, Foster City CA) and the corresponding manufacturers manual. Each reaction was
prepared by mixing 2.0uL of a premade mix of mix of forward and reverse primers each at 10x,
1.0uL of cDNA template, 10.0uL of 2x SYBRgreen super mix and 7.0uL of DI water.
Specific primer sequences are shown below (table 1) and were taken from Jin et al. (2010) whose
group looked at expression levels in response to certain toxins. PCR program was run on all
samples on two plates for the fallowing program: denaturation for 1 minute at 95˚C, followed by
40 cycles of 15 seconds at 95˚C and one minute at 60˚C.
Data Analysis:
Quantitative PCR measures the number of cycles of mRNA replication each sample takes to
reach a threshold level, called the Ct value, which is measured by fluorescence. The more
mRNAs present the fewer cycles it takes to generate the same quantity (threshold) of product.
Because each additional cycle represents a doubling in product, a 1-cycle difference in Ct
represents a 2-fold difference in starting mRNA. In this way, the relative abundance of mRNA
for a specific gene (selected for with specific primers added to the sample) can be measured and

26. 26
compared to a control. When using qPCR there are two controls, both an internal and an external
control. The internal control is a housekeeping gene, Actin-ß , whose expression levels should
not be affected by EtOH exposure and should remain constant. The external control is the
baseline expression of the target gene (this is the OH group, and is distinct for each measured
antioxidant enzyme). This is the Ct value for each SOD before exposure to EtOH under control
conditions (table #2).
Ct values are normalized to the internal control by subtracting the Actin-ß Ct of the
corresponding sample. This value is known as ∆Ct and controls for any variability in cDNA
concentration on final expression levels. ∆Ct is divided by the external control of the
corresponding untreated expression group (appendix 1). The resulting value is known as ∆ ∆Ct
and represents the relative mRNA expression level in control and treatment groups. In untreated
groups this value is 1 because it is a value divided by itself. Finally the relative expression is
determined by raising 2 to the power of the negative value of ∆ ∆Ct for each sample. This is the
RQ-value. This shows the fold-increase in expression of each sample (appendix). For each
untreated group the RQ value is 1. There were four biological replicates (4 different dissected
fish) measured by QPCR for each treatment group, and the average of these 4 RQ values is what
is analyzed.
Average RQ value and standard error were calculated and tested for each treatment group.
Treatment groups refer to expression levels of the 4 biological replicates of each of the 3
antioxidant enzymes for each separate organ type. RQ-values were analyzed for each treatment
group using a one-way ANOVA of the 4 contributing RQ-values calculated for each treatment

27. 27
group to test for significance. Post-Hok analysis was preformed on treatment groups that proved
significant (p<0.05) to determine where the significant variation was coming from and graphs
were labeled accordingly (fig 4).

28. 28
RESULTS
Brain Enzyme Expression Levels:
Visual inspection of the average expression levels of brain tissues, normalized to a control value
of 1.0, shows that none of the antioxidant enzymes increase significantly over a period of 12
hours (Fig.2A). For MnSOD after 4 hours, average RQ was 1.7 times the control level, after 8
hours, average RQ was 1.9 times the control level and after 12 hours it was 2.0 times the control
level (table 3A). A one-way ANOVA showed no significant expression differences among EtOH
treatments (F =0.9 , P = 0.5). For CuZnSOD after 4 hours, average RQ was 2.2 times the control
level, after 8 hours, average RQ was 3.1 times the control level and after 12 hours it was 1.5
times the control level (table 3A). A one-way ANOVA showed no significant expression
differences among EtOH treatments (F =0.9 , P = 0.5. For CAT after 4 hours, average RQ was
4.2 times the control level, after 8 hours, average RQ was 5.2 times the control level and after 12
hours it was 2.2 times the control level (table 3A). A one-way ANOVA showed no significant
expression differences among EtOH treatments (F = 1.6, P = 0.2).

29. 29
Liver enzyme Expression Levels:
Visual inspections of the average expression levels of liver tissues, normalized to a control value
of 1.0, suggest that MnSOD did not significantly increase, but both CuZnSOD and CAT show
significant increase in average expression levels normalized to the pretreatment control after
either 8 or 4 hours of exposure (Fig. 2B). For MnSOD After 4 hours, average RQ was 1.3 times
the control level, after 8 hours, average RQ was 3.4 times the control level and after 12 hours it
was 1.4 times the control level (table 3B). A one-way ANOVA showed no significant expression
differences among EtOH treatments (F= 3.4, P = 0.06).
For CuZnSOD After 4 hours, average RQ was 1.6 times the control level and after 8 hours,
average RQ was 2.6 times the control level; but after 12 hours it was only 1.6 times the control
level (table 3B). A one-way ANOVA showed a significant expression differences among EtOH
treatments (F= 4.6, P = 0.02), and post-hoc analysis revealed that this was entirely due to the
difference between the 8-hour treatment and control (Tukey-Kramer q = 2.97, P = 0.016 between
8-hour and control; all other P > 0.3). For CAT After 4 hours, average RQ was 4.8 times the
control level but after 8 hours, average RQ was 2.9 times the control level and after 12 hours it
was 2.5 times the control level (table 3B). A one-way ANOVA showed a significant expression
differences among EtOH treatments (F = 5.04, P = 0.02). Post-hoc analysis revealed that this was
entirely due to the difference between the 4-hour treatment and control (Tukey-Kramer q = 3.01,
P = 0.012 between 4-hour and control; all other P > 0.3).

30. 30
Gonad Enzyme Expression Levels:
Visual inspection of the average expression levels of gonad tissues, normalized to a
control value of 1.0, suggest that MnSOD expression did not inrease, CuZnSOD increased
significantly at 4 hours but not at 8 or12 hours and CAT was significantly increased at both 4 and
8 hours of exposre (fig.2C). For MnSODfter 4 hours, average RQ was 4.0 times the control level
and after 8 hours, average RQ was 2.9 times the control level; but after 12 hours it was only 2.9
times the control level. A one-way ANOVA showed no significant expression differences among
EtOH treatments for MnSOD (F = 2.9, P = 0.07).
For CuZnSOD after 4 hours, average RQ was 2.7 times the control level but after 8 hours,
average RQ was 2.0 times the control level and after 12 hours it was also 2.0 times the control
level (Fig. 2C). A one-way ANOVA showed a significant expression differences among EtOH
treatments (F = 3.96, P = 0.04), and post-hoc analysis revealed that this was entirely due to the
difference between the 4-hour treatment and control (Tukey-Kramer q = 2.97, P = 0.023 between
8-hour and control; all other P > 0.3). For CAT aftter 4 hours, average RQ was 6.9 times the
control level and after 8 hours, average RQ was 7.1 times the control level; but after 12 hours it
was only 5.7 times the control level. A one-way ANOVA showed a significant expression
differences among EtOH treatments (F = 5.04, P = 0.02), and post-hoc analysis revealed that this
was due to the difference between the 8-hour treatment and the control (Tukey-Kramer q = 2.97,
P = 0.01 between 8-hour and control); and the 4-hour treatment and the control (Tukey-Kramer q
= 2.97, P = 0.02 between 4-hour and control); all other P > 0.3).

31. 31
DISCUSSION
Brain Tissue:
Brain tissue showed the lowest relative expression level of all 3 antioxidant enzymes. The
highest expression was seen at 8 hours of exposure and only MnSOD showed a significant
increase at this time (Figure 4A). This suggests that MnSOD may be the main protective factor,
or at least the main acting scavenger of ROS in zebrafish brain tissue. The brain is known to
have a relatively low antioxidant denfense system (Rico, et al. 2007).
Bellesteros et al (2008) found that enzymatic activity in response to oxidative damage from
environmental pollutants are lower in the brain then in other fish organs such as the gills and
liver. This may explain, at least in part, why brain tissue is known to be particularly susceptible
to oxidative damage (Bellesteros et al. 2008). This is consistent with the findings of the current
study and suggests that the low relative expression seen in brain tissue is due to the fish not
having a robust defense system. This does not give any information as to whether or not the
ethanol treatment lead to oxidative damage within zebrafish brain tissue or not.

32. 32
Liver Tissue:
Ethanol is metabolized by a 2 step process within liver hepacocytes. First, alcohol
dehydrogenase (ADH) converts ethanol to acetaldehyde, the first byproduct of ethanol
metabolism. Secondly, acetaldehyde is metabolized to acetate by aldehyde dehydrogenase
(ALDH) forming acetate (Swift 2003). This process of alcohol metabolism is similar in
zebrafish as to in humans, and zebrafish ADH shares a common ancestor with mammalian
ADH, which is found in humans (Rico et al. 2007).
Increased production of superoxide, H2O2 and hydroxyl radicals have been observed in the
livers of EtOH fed rats. Dey and Cederbaum (2006) found that in rat liver, mitochondrial DNA
(mtDNA) was affected after just a single dose of EtOH treatment, but cellular DNA was not.
The current study looked at cellular DNA and would not have detected any changes in
mitochondrial functioning as a result of acute ethanol exposure. Changes in the structure and
function of mitochondrial proteins are one of the earliest effects of ethanol metabolization (Das
and Vasudevan 207). Given the short exposure times used in the current study it is likely that
unobserved damage took place within the mitochondria of hepatocytes. The destruction of
mitochondria associated with alcohol metabolization contributes to the development of alcohol
induces liver diseases (Hoek 2002). Although treatments were not long enough to show changes
in expression levels of cellular DNA there may have been damage that occurred to mtDNA.
Increase in expression of mtDNA for transcription factors may have shown an increase in liver
tissue.

33. 33
By visual analysis, liver tissue shows generally higher expression levels of all 3 antioxidant
enzymes then brain tissue, but lower expression levels then in gonads when compared to
baseline pretreatment expression (Figure 4B). Liver tissue shows a steady increase in relative
expression levels of all 3 antioxidant enzymes looked at, which peaks at 8 hours. This may have
continued to increase if given longer exposure times but fish were removed from the EtOH
treatment after 8 hours and by 12 hours the 3 SODs show some recovery. At this time, MnSOD
and CAT expression levels are still significantly higher then baseline, pretreatment expression
levels; suggesting a small, but significant, cellular response to toxic byproducts of alcohol
taking place within liver tissue.
Exposure treatments were comparatively short, lasting no more then 8 hours. Changes in gene
expression may not take effect that quickly. Koch et al (2004) found no transcriptional
modification in response to acute ethanol exposure, but significantly increased transcription of
MnSOD after chronic exposure (Koch et al. 2004). A number of intermediate steps exist
between initial alcohol exposure and the transcriptional response of cellular DNA (Dey and
Cederbaum 2006).
This multistep process of metabolization and cellular response to EtOH may be taking longer
then 8 hours to activate an actual, significant response that could be detected by measurement of
antioxidant enzyme transcription levels. There could still be significant oxidative damage
occurring within liver tissue, which would lead to expression of antioxidant enzymes given
more time.

34. 34
Average RQ values calculated for liver tissue show the lowest standard error compared to brain
and gonad tissue. Liver tissue samples tended to be larger by mass then brain and gonad tissues
(data not shown) and offered the highest yield or RNA. This was controlled for by standardizing
RNA concentrations before rtPCR, but may still have had some effect on the accuracy of
measured transcriptional levels.
Gonad Tissue:
Tissue dissected from the gonads of zebrafish show the most interesting results of this study,
responding to EtOH exposure with the most immediate and highest increase in expression levels
of the 3 antioxidant enzymes. The highest level of expression for gonad tissue was seen at 4
hours of EtOH exposure. Expression levels stayed high and relatively consistent through 8 hours
of exposure and then through 4 hours of recover (figure 4C). Gonads show the most consistently
significant increases in expression levels when compared to pretreatment controls.
Oxidative stress disrupts the fertilizing capacity of sperm and attacks it’s DNA as in other cells.
DNA fragmentation in sperm is of great importance because it is known to negatively affect
both the fertilizing capacity of sperm and the ability of a resulting embryo to survive to term
(Aitken and Krausz 2001); both of which directly affect an organisms reproductive capacity and
fitness. Because sperm are so easily damaged by ROS, secretions of the male reproductive tract
and of the gonads themselves have been shown (in humans) to contain specialized antioxidants,
which surround and protect the germ-line cells within the extracellular space (Aitken and
Krausz, 2001). This suggests that gonad tissue has a strong and effective response system to

35. 35
deal with oxidative damage, and that this defense involves the production of antioxidant
enzymes.
Female oocytes of zebrafish are bathed in interstitial fluid (similar to the sperm), which
contains protective antioxidant enzymes (Lessman 2009). The developed egg remains dormant
within the gonad until it is activated by exposure to freshwater at which point it becomes ready
for fertilization (Lessman 2009). damages or mutations in the DNA of reproductive cells (found
within gonads) lays the groundwork for a developing organism (Lessman 2009) during
development. The viability of these reproductive cells is directly related to the fitness of an
organism. Protecting these cells is evolutionarily advantageous, which supports the findings of
the current study in which there was a significant increase in expression of antioxidant enzymes
in as little as 4 hours of EtOH exposure.
General Conclusions:
This study measured the expression levels of 3 key antioxidant enzymes, but there are a number
of other protective mechanisms (including other non enzymatic antioxidant molecules), which
the cell utilizes in defense of oxidative damage (Koch et al, 2004). Mechanisms capable of
neutralizing ROS include SODs, catalase, two kinds of glutathione (GSH) and a number of
vitamins (McDonough 2003). Reduced glutathione (GSH) is an important antioxidant enzyme
involved in detoxification of toxic agents within the cell. GSH is particularly important within
the mitochondria. GSH was not looked at specifically in the current study and may have had an
effect on the outcome of ethanol exposure. Metabolites of Alcohol can have inhibitory effects
on gene expression, enhancing the negative effects of ethanol produced ROS (Rico et al. 2007).

36. 36
Increased production of superoxide, H2O2 and hydroxyl radicals have been observed in
the livers of EtOH fed rats. Dey and Cederbaum (2006) found that in rat liver, mitochondrial
DNA (mtDNA) was affected after just a single dose of EtOH treatment, but cellular DNA was
not. This study looked at cellular DNA exclusively and not mtDNA; which may be why so few
significant changes were seen in antioxidant expression levels. Primary damage occurs to the
mitochondria and mtDNA, the effects of which could not be seen in the present study because
only cellular DNA was examined for transcriptional changes.
The most noticeable effect of acute ethanol exposure on liver tissue is a change in the structure
of mitochondria (Dey and Cederbaum 2006). They become enlarged and distorted which effects
their ability to function and can lead to the greater production of ROS (Das and Vasudevan
2007). EtOH induced oxidative stress has been shown to cause mitochondrial dysfunction and
permeability changes, which precede and partially are responsible for liver injury associated
with ethanol exposure (Dey and Cederbaum, 2006). Ethanol exposure affects mitochondrial free
radical generation and induces expression changes in mitochondrial proteins (Koch et al. 2004).
Dysfunctional mitochondria, whose proteins have been affected by ethanol, can lead to
increased production of O2- (Koch et al. 2004). This increase in ROS likely causes heightened
oxidative damage within associated tissue but could not have been detected in the current study.
Mitochondria are constantly exposed to ROS during normal cell functioning because
ROS are byproducts of metabolization, which occurs continuously within mitochondria (Das
and Vasudevan 2007). Because they are constantly exposed, mtDNA is well protected and

37. 37
responds with the up regulation of protective mechanisms more quickly then other cellular
components (Dey and Cederbaum 2006). Cellular DNA is less directly affected by ROS within
the mitochondria and as a result does not need to respond as effectively to oxidative damage
caused by distorted or dysfunctional mitochondria.
Oxidative damage to the mitochondria interferes with the metabolic process leading to
heightened production of ROS. This combined with the increased ROS due to alcohol exposure
directly, leads to extensive damage to the mitochondria. More so then other structures, leading
to a cascade of mitochondrial produced ROS (Das and Vasudevan 2002). It is important that the
mitochondria respond quickly to avoid this cascade production of ROS. Mitochondrial GSH is
the main cellular antioxidant responsible for detoxification of ethanol, and was not measured in
the current study, but may have shown a more significant change in expression levels had it
been analyzed.
Acetylcholinesterase (AChE) is another enzyme involved in cellular protection from
oxidative damage caused by alcohol, which is known to be expressed in the zebrafish brain
(Bertrand et al. 2001). AChE is an enzyme found in zebrafish, encoded by a single gene. AChE
is involved in the process of cleaving Ach into acetate during alcohol metabolism and is
considered a protective mechanism within zebrafish tissues responding to several environmental
contaminants (Rico et al. 2007). AChE expression was not measured in the current study but is
likely an important part of the overall mechanism of cellular response to ethanol exposure.

38. 38
Rico et al. (2007) measured transcription levels of AChE in response to ethanol exposure
and although AChE activity was shown to increase, mRNA levels were significantly decreased.
This seemingly contradictory result suggests that an increase in gene activity is not directly
related to higher gene expression levels (Rico et al. 2007). This may be true for the gene
products measured in the current study as well; no tests were preformed to see if antioxidant
enzyme activity was increased.
Complex signaling and feedback loops are responsible for regulating transcription, and
measuring mRNA by qPCR only looks at one aspect of this process. Rico et al. (2007) suggest
that ethanol may regulate AChE post-transcriptionally which explains why higher activity is
seen but not higher transcription levels. The same could be true for the 3 antioxidant enzymes
examined in the current study. Metabolites of Alcohol can have inhibitory effects on gene
expression, enhancing the negative effects of ethanol produced ROS (Rico et al. 2007).
Any post transcriptional control of the antioxidant defense system could not be seen in
the current study, leaving an incomplete picture of the cellular response to acute alcohol
exposure. Relative expression levels of antioxidant enzymes offers important insight into the
mechanism associated with response to oxidative damage but it is only a small part of the
overall cellular response system which protects DNA from excessive oxidative damage.

39. 39
Future Direction:
General trends from this study show an increase in expression levels in the first 4 and 8 hours of
treatment. The levels of increase seen here are minimal and will likely continue to increase
steadily if exposure treatments were continued for 12 or even 24 hours. Further experiments are
needed to determine if this is the case and at which point expression of antioxidant enzymes
peaks or levels off. This study does not look at oxidative damage, but at response to presumed
oxidative damage, it would be interesting to have a direct measure of the actual oxidative
damage to DNA against which to interpret antioxidant enzyme expression level results.
Identification of oxidatively damaged DNA can be used as a reliable indicator of oxidative
stress in vivo. 8-oxydG is as a reliable marker of high levels of oxidative stress and damage to
tissues associated with cancer (Barzilai and Yamamoto 2004). This alteration in DNA from 8-
oxydG is involved in the recognition site utilized by DNA glycosylases to detect damaged
guanine bases. These lesions are not lethal to the cell but are highly mutagenic (Barzilai and
Yamamoto 2004).
The acute alcohol exposure may not have lasted long enough to cause the kind of damage that
would elicit a significant enzymatic response, which could be controlled for by directly
measuring the level of oxidative DNA damage which occurred. It would be advantageous to
have a direct measure of oxidative damage within different tissues to create a more complete
picture of how cells are responding to oxidative damage caused by EtOH.

40. 40
The high standard error seen throughout this experiment can be contributed to individual
differences between fish (biological replicates). The internal control of Actin-ß ensured that
differences between samples was not due to a difference in RNA concentration or overall
expression level differences between fish. There was no control for age or gender of fish, both
of which have been shown to have an impact on oxidative damage (Bellesteros et al. 2008). In
the future it would be interesting to look at these variables specifically as a possible determinant
of relative expression levels of different antioxidant enzymes and the effect of EtOH exposure
on diverse tissues of zebrafish.
It would be useful to compare baseline expression levels (listed as ∆Ct in appendix 1)
between different tissues to create a more complete picture of cellular defense against oxidative
damage by antioxidant enzymes. As it is the study looks only at expression levels relative to this
standard assuming it is stable between tissues, but this may not be the case.
A number of fallow-up experiments are needed to create a complete picture of the cellular
defense mechanisms induced within various tissues of zebrafish in response to acute alcohol
exposure. The current study establishes a useful protocol and jumping off point for the
execution of further experiments.

41. 41
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Cooke M. 2002. Progress in the analysis of urinary oxidative DNA damage. Free Radical
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Dey A, Cederbaum AI. 2006. Alcohol and Oxidative Liver Injury. Hepatology 43: S63-74.
Dlugos CA, Rabin RA. 2003. Ethanol effects on three strains of Zebrafish: model system for
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Hagar H. 2004. The protective effect of Taurine against Cyclosporine A-induced axidative stress
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Koch O. 2004. Oxidative stress and antioxidant defenses in ethanol-induced cell Injury.
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44. 44
FIGURES ANDTABLES
Table 1: Sequences of primer pairs used in the quantitative PCR reaction to measure
expression levels of corresponding enzymes against the internal control of Actin-ß
Gene of
Interest
Primer name Sequence Annealing
temperature
Product
Length
MnSOD
MnSOD-F 5’-CCGGACTATGTTAAGGCCATCT-3’ 56.4ºC
123bp
MnSOD-R 5’-ACACTCGGTTGCTCTCTTTTCTCT-3’ 58.1ºC
CuZnSOD
CuZnSOD-F 5’-GTCGCTGGCTTGTGGAGTG-3’ 58.2ºC
113bp
CuZnSOD-R 5’-TGTCAGCGGGCTAGTGCTT-3’ 59.3ºC
CAT
CAT-F 5’-AGGGCAACTGGGATCTTACA-3’ 55.9ºC
499bp
CAT-R 5’-TTTATGGGACCAGACCTTGG-3’ 54.3ºC
Actin-ß
Actin-F 5’-ATGGATGAGGAAATCGCTGCC-3’ 57.7ºC
106bp
Actin-R 5’-CTCCCTGATGTCTGGGTCGTC-3’ 59.2ºC

45. 45
Figure 3: A diagram of the 2 96 well plates, which were run through QPCR for this experiment;
and the layout, which was used to organize samples and treatment groups throughout the
experiment. Outlines the basic logic behind the experimental design in regard to data analysis.

46. 46
Figure 4A: Relative antioxidant expression levels in Brain Tissue.
Compares antioxidant enzyme expression in brain tissue. Relative expression level
(measured by RQ value) of 3 different antioxidant enzymes expressed in brain tissue
extracted from Danio rerio after 4 and 8 hours of exposure to a 1% EtOH treatment, 4
hours after removal from EtOH (12H) and a pretreatment control (0H) to which each value
is compared for significance of increase. Vertical bars represent standard error. Data taken
from appendix 2.
0
1
2
3
4
5
6
7
8
9
10
0H 4H 8H 12H
AverageRQValue
Length of Treatment
MnSOD
CuZnSOD
CAT

47. 47
Figure 4B: Relative Antioxidant Expression Levels in Liver Tissue
Compares SOD expression in liver tissue. Relative expression level (measured by RQ value)
of 3 different SODs expressed in liver tissue extracted from Danio rerio after 4 and 8 hours
of exposure to a 1% EtOH treatment, 4 hours after removal from EtOH (12H) and a
pretreatment control (0H) to which each value is compared for significance of increase.
Vertical bars represent standard error. Data taken from appendix 2.
0
1
2
3
4
5
6
7
8
9
10
0H 4H 8H 12H
AverageRQValue
Length of Treatment
MnSOD
CuZnSOD
CAT

48. 48
Figure 4C: Relative Antioxidant Expression Levels in Gonad Tissue
Compares SOD expression in gonad tissue. Relative expression level (measured by RQ
value) of 3 different antioxidant enzymes expressed in gonad tissue extracted from Danio
rerio after 4 and 8 hours of exposure to a 1% EtOH treatment, 4 hours after removal from
EtOH (12H) and a pretreatment control (0H) to which each value is compared for
significance of increase. Vertical bars represent standard error. Data taken from appendix
2.
-1
0
1
2
3
4
5
6
7
8
9
10
0H 4H 8H 12H
AverageRQValue
Length of Treatment
MnSOD
CuZnSOD
CAT

49. 49
APPENDIXES
Appendix 1: Raw data for expression levels measured by QPCR (given as Ct value) and
intermediate values used to determine average RQ values for each sample individually.

50. 50