Faculty of Science
CAPILLARY ELECTROPHORESIS STUDY OF INTERACTION BETWEEN OMEGA-3
FATTY ACIDS AND EPIGALLOCATECHIN GALLATE
2016 | CARLEE DAWN DORIS POLESCHUK

B.Sc. Honours thesis

Capillary Electrophoresis Study of Interaction between Omega-3 Fatty Acids
and Epigallocatechin Gallate
by
Carlee Dawn Doris Poleschuk

A THESIS SUBMITTED IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
BACHELOR OF SCIENCE (HONS.)
in the
DEPARTMENT OF BIOLOGICAL AND PHYSICAL SCIENCES
(CHEMICAL BIOLOGY)

We accept this thesis as conforming to the required standards:

Kingsley Donkor (Ph.D.), Thesis Supervisor, Dept. Physical Sciences

Naowarat Cheeptham (Ph.D.), Co-supervisor, Dept. Biological Sciences

Dipesh Prema (Ph.D.), Committee Member, Dept. Physical Sciences

Dated this 22nd day of April, 2016, in Kamloops, British Columbia, Canada

© Carlee Dawn Doris Poleschuk, 2016

ABSTRACT
Cancer, a global disease affecting millions of people, is characterized by uncontrolled cell
division due to mutations within the cell. The resulting cell mass continues to rapidly grow,
resulting in tumours. Epigallocatechin gallate is a polyphenolic catechin found in green tea leaves
that has been shown to have antioxidant and anti-inflammatory properties. Recently, it has also
been shown to have anti-cancerous effects on various breast cancer cell lines. The effects include
inhibiting cancer cell line growth, down-regulating estrogen receptor function, inducing apoptosis,
inhibiting tumour promotion, and exhibiting antioxidant properties. This shows that
epigallocatechin gallate is a potential cancer therapeutic agent. Although these are promising in
vitro results, epigallocatechin gallate does not readily cross the cellular phospholipid bilayer in
vivo. It is hypothesized that epigallocatechin gallate could be carried through the plasma membrane
and into the cell when attached to a lipid molecule. The molecule that is currently being tested as
a carrier molecule is the omega-3 fatty acid docosahexaenoic acid. The analytical technique
affinity capillary electrophoresis has been used to determine that epigallocatechin gallate and
docosahexaenoic acid have a reasonably strong interaction of 4.0 (± 1.2) x 104 at physiological
pH.
Thesis Supervisor: Associate Professor Dr. Kingsley Donkor

i

ACKNOWLEDGMENTS
I want to thank my supervisor Dr. Kingsley Donkor for all of his support and guidance
throughout my project. I also want to thank Matthew Drayton for training on the CE and for helping
me analyze my data. A special thank you to the Thompson Rivers University Chemistry
department, the Thompson Rivers University Honours coordinators, and the Thompson Rivers
University Research office for funding through UREAP. Finally, thank you to Dr. Naowarat
Cheeptham and Dr. Dipesh Prema for agreeing to be on my honours committee.

ii

TABLE OF CONTENTS
ABSTRACT .............................................................................................................................. I
ACKNOWLEDGMENTS ..................................................................................................... II
LIST OF FIGURES .............................................................................................................. IV
LIST OF TABLES ................................................................................................................ VI
1

INTRODUCTION ............................................................................................................ 1

2

MATERIALS AND METHODS ..................................................................................... 5
2.1 REAGENTS ..................................................................................................................... 5
2.2 CAPILLARY ELECTROPHORESIS ..................................................................................... 5
2.3 PREPARATION OF THE EGCG AND DHA STOCK SOLUTIONS ........................................ 6
2.4 PREPARATION OF BUFFER AND BACKGROUND ELECTROLYTE SOLUTIONS ................... 6
2.5 PREPARATION OF RUN BUFFER AND EGCG SAMPLES WITH DMF ................................ 6

3

RESULTS AND DISCUSSION ....................................................................................... 6
3.1 EGCG CONCENTRATION OPTIMIZATION ...................................................................... 7
3.2 NEUTRAL MARKER OPTIMIZATION ............................................................................... 7
3.3 BGE CONCENTRATION OPTIMIZATION ......................................................................... 8
3.4 INTERACTION STUDIES ................................................................................................ 10
3.4.1 Interaction Study at pH 9.0.................................................................................. 10
3.4.2 Interaction Study at pH 8.5.................................................................................. 11
3.4.3 Interaction Study at pH 8.0.................................................................................. 11
3.4.4 Interaction Study at pH 7.5.................................................................................. 12
3.5 BINDING CONSTANT.................................................................................................... 13

4

CONCLUSION AND FUTURE WORK ...................................................................... 14

5

LITERATURE CITED .................................................................................................. 16

6

APPENDIX ...................................................................................................................... 18
6.1 LINEAR REGRESSION METHOD FOR CALCULATING BINDING CONSTANTS .................. 18
6.2 LINEAR REGRESSION PLOTS ........................................................................................ 19

iii

LIST OF FIGURES
Page
Figure 1.

Figure 2.

Figure 3.

Figure 4.
Figure 5.

Figure 6.

Figure 7.

The chemical structure of epigallocatechin gallate, a green tea catechin
that has been show to exhibit antioxidant properties, down-regulate
estrogen receptor alpha function, induce apoptosis and inhibit tumour
promotion (Farabegoli et al. 2007; Feng 2006; Fujiki 2005; Ishii et al.
2008; Lee et al. 2012).
The chemical structure of docosahexaenoic acid, an omega-3 fatty acid
that is readily obtained in the diet from cold-water fish (Scarsi et al.
2015).
A diagram depicting EOF including the separation of ions based on size
and charge between the anode and cathode (Laboratoire Suisse
d’Analyse du Dopage 2008).
The formula and constants for the effective electrophoretic mobility
that is used to quantify binding interactions..
The electropherogram showing various concentrations of EGCG peaks.
The top run contained 50 ppm (A), the middle contained 100 ppm (B)
and the bottom contained 150 ppm (C). The first peak is the neutral
marker (DMF) and the second smaller peak is the EGCG. Conditions:
detection, UV; applied voltage, 10 kV; BGE concentration, 50 mM;
BGE pH, 7.5; temperature, 25oC.
The electropherogram that compares the two potential neutral markers.
The top three peaks consisted of a 1 µL aliquot added to samples
containing 50 ppm (A), 100 ppm (B) and 150 ppm (C) of EGCG. The
bottom three peaks consisted of a 1 µL aliquot also added to samples
containing 50 ppm (D), 100 ppm (E) and 150 ppm (F) of EGCG. Based
on this data, DMF was used as the neutral marker for the following
interaction studies. Conditions: detection, UV; applied voltage, 10 kV;
BGE concentration, 50 mM; BGE pH, 7.5; temperature, 25oC.
The electropherogram displaying the various BGE concentrations at pH
7.5. Each run was run in duplicates at the concentrations of 25 mM (A),
50 mM (B), 75 mM (C) and 100 mM (D). The first peak is the neutral
marker (DMF) and the second peak is the EGCG (100 ppm). Based on
the obtained results, 25 mM appeared to give the best EGCG peak
shape and baseline separation. Therefore, this concentration was used
for all following interaction studies. Conditions: detection, UV; applied
voltage, 10 kV; BGE pH, 7.5; temperature, 25oC.

1

3

4

4
7

8

9

iv

Figure 8.

Figure 9.

Figure 10.

Figure 11.

The electropherogram of the interaction study between EGCG and
DHA with a 25 mM BGE solution of pH 9.0. The sample consisted of a
5 µL aliquot of a 1:50 DMF dilution as well as a constant concentration
of 100 ppm EGCG. The 25 mM BGE solution contained various
concentrations of DHA: 0 ppm (A), 50 ppm (B), 100 ppm (C), 150 ppm
(D), 200 ppm (E), 250 ppm (F). The formation of a complex as the
concentration of DHA increases is evident due to the increase in
migration of the EGCG peak. Conditions: detection, UV; applied
voltage, 10 kV; BGE concentration, 25 mM; temperature, 25oC.
The electropherogram of the interaction study between EGCG and
DHA with a 25 mM BGE solution of pH 8.5. The sample consisted of a
5 µL aliquot of a 1:50 DMF dilution as well as a constant concentration
of 100 ppm EGCG. The 25 mM BGE solution contained various
concentrations of DHA: 0 ppm (A), 50 ppm (B), 100 ppm (C), 150 ppm
(D), 200 ppm (E), 250 ppm (F). The formation of a complex as the
concentration of DHA increases is evident due to the increase in
migration of the EGCG peak. Conditions: detection, UV; applied
voltage, 10 kV; BGE concentration, 25 mM; temperature, 25oC.
The electropherogram of the interaction study between EGCG and
DHA with a 25 mM BGE solution of pH 8.0. The sample consisted of a
5 µL aliquot of a 1:50 DMF dilution as well as a constant concentration
of 100 ppm EGCG. The 25 mM BGE solution contained various
concentrations of DHA: 0 ppm (A), 50 ppm (B), 100 ppm (C), 150 ppm
(D), 200 ppm (E), 250 ppm (F). The formation of a complex as the
concentration of DHA increases is evident due to the increase in
migration of the EGCG peak. Conditions: detection, UV; applied
voltage, 10 kV; BGE concentration, 25 mM; temperature, 25oC.
The electropherogram of the interaction study between EGCG and
DHA with a 25 mM BGE solution of pH 8.0. The sample consisted of a
5 µL aliquot of a 1:50 DMF dilution as well as a constant concentration
of 100 ppm EGCG. The 25 mM BGE solution contained various
concentrations of DHA: 0 ppm (A), 50 ppm (B), 100 ppm (C), 150 ppm
(D), 200 ppm (E), 250 ppm (F). The formation of a complex as the
concentration of DHA increases is evident due to the increase in
migration of the EGCG peak. Conditions: detection, UV; applied
voltage, 10 kV; BGE concentration, 25 mM; temperature, 25oC.

10

11

12

13

v

LIST OF TABLES
Table 1.

The binding constants determined for EGCG and DHA at pH 7.5 that
were calculated using linear regression plots.

Page
14

vi

1

INTRODUCTION
The health benefits of green tea are becoming more and more prominent in today’s society.

The numerous benefits that are typically advertised include lowering cholesterol, inhibiting the
increase of blood pressure and preventing plaque formation that leads to cavities (the tea spot
2016). Green tea has also been shown to contain high levels of antioxidant and anti-inflammatory
properties with loose-leaf green teas having the most benefit (Fujiki 2005). The class of molecules
responsible for these vast and favourable health benefits are green tea catechins. Catechins account
for 30-40% of the dry weight of solids in steeped green teas and of the four major polyphenolic
catechins present in green tea, EGCG, a flaven-3-ol polyphenol, is the most abundant and
biologically active (Ishii et al. 2008; Ranzato et al. 2014; Zeng et al. 2014).
Epigallocatechin gallate (EGCG), shown in Figure 1, has been reported to contain many anticancerous effects. It prevents cancer formation by exhibiting antioxidant properties such as
neutralizing radical oxygen species before they induce cell mutations that lead to tumours (Ishii et
al. 2007). It also down-regulates estrogen receptor alpha function that normally controls the growth
of breast cancers (Lee et al. 2012). EGCG has also been shown to induce apoptosis of cancerous
cells and inhibit tumour promotion (Fujiki 2005; Farabegoli et al. 2007; Ishii et al. 2008). Because
of these many anti-cancerous effects, ECGC has been determined to be a possible therapeutic agent
for cancer treatments.

Figure 1. The chemical structure of epigallocatechin gallate, a green tea catechin that has been
shown to exhibit antioxidant properties, down-regulate estrogen receptor alpha function, induce
apoptosis and inhibit tumour promotion (Farabegoli et al. 2007; Feng 2006; Fujiki 2005; Ishii et
al. 2008; Lee et al. 2012).

1

Cancer is a global disease affecting millions of people on a daily basis. It is characterized as
uncontrolled cell division due to mutations within the cell (National Cancer Institute 2016). The
resulting cell mass then continues to rapidly grow resulting in tumours. Of all cancers affecting
women, breast cancer is the most common in developed countries (excluding non-melanoma skin
cancers). It is also the second leading cause of death from cancer in Canadian women (Canadian
Cancer Society 2016). Recent research aims to identify new therapeutic possibilities for breast
cancer that includes using EGCG.
Zeng and colleagues (2014) investigated the effects of therapeutic EGCG on various breast
cancer cell lines. They determined that physiological concentrations of EGCG inhibited growth in
estrogen receptor (ER) positive MCF-7 cells by increasing regulation of tumour suppressing genes
p53/p21. It also significantly increased cell death in the aggressive ER negative cell line MDAMB 231. Therapeutics with a potential of targeting MDA-MB 231 cell lines are extremely
important as this cell line is extremely aggressive, has poor prognosis and does not respond to
common therapies due to its triple negative characteristic (Holliday and Speirs 2011).
Other research conducted by Ranzato and colleagues (2014) also used EGCG as a therapeutic
agent with the breast carcinoma cell line MCF-7. Calcium is essential in cell survival, proliferation
and growth and disruption of intracellular calcium normally leads to cell death. They showed that
EGCG induces a [Ca2+] spike by targeting Ca2+ channels, thus suggesting that EGCG deregulates
[Ca2+] and leads to decreased MCF-7 viability (Ranzato et al. 2014). Although these in vitro results
are promising, EGCG is not readily absorbed into the body since it cannot easily cross the
phospholipid bilayer (Epstein 2009). However, the therapeutic properties of this catechin may be
applicable to humans if it was carried through the plasma membrane via a carrier molecule. Carrier
molecules that would be considered are molecules that can easily cross the phospholipid bilayer
and enter the cancerous cells. These include lipid molecules such as various omega-3 fatty acids.
Omega-3 fatty acids are essential nutrients that can be found in many dietary foods such as
fish oils, flax seeds, eggs, milk and cheese. The body readily absorbs them because they are not
endogenously produced (Scarsi et al. 2015). This is an advantage of omega-3 fatty acids as opposed
to other potential lipid carriers. Docosahexaenoic acid (DHA) is an omega-3 fatty acid that has a
structure of 22:6n-3, shown in Figure 2. DHA can be obtained by eating cold-water fish and from
ingesting fish oil supplements. DHA is vital for the growth and cognitive function of the adult
brain and is absolutely essential in the brain development of children and is obtained by breast
2

milk (Horrocks and Yeo 1999). Dietary DHA appears to reduce the risk of heart disease, arthritis,
and cognitive and behavioural diseases (Kiruthika 2015; Crauste 2016). Structurally, DHA is a
highly unsaturated derivative of alpha-linolenic acid (ALA) (Bougnoux et al. 2010). Although
DHA is an ALA derivative, it is not easily converted to DHA in the body; therefore, it must be
ingested separately by consuming cold-water fish and fish oil supplements (Horrocks and Yeo
1999; Kiruthika 2015).

Figure 2. The chemical structure of docosahexaenoic acid, an omega-3 fatty acid that is readily
obtained in the diet from cold-water fish (Scarsi et al. 2015).
Recently, the effectiveness of DHA as an addition to common cancer treatments has been
studied, specifically in breast cancer treatments. It has been shown to have the potential to increase
cancer treatment efficience without serious or aversive side effects (Bougnoux et al. 2010).
Research conducted by Hardman and colleagues (2001) determined that rats with xenographs of
the triple negative breast cancer cell line MDA-MB 231 were more susceptible to anti-cancer
agents that resulted in tumour shrinkage when supplemented with 0.7 grams of DHA on a daily
basis (Hardman et al. 2001). These results show that diet may influence or play a significant role
in the effectiveness of cancer treatment.
Overall, EGCG and DHA, and their therapeutic effects on breast cancer, have been studied
separately, however there is very little in the literature about their interactions. Therefore, by
studying the interaction of this EGCG with DHA, we may be able to determine a method that
would allow EGCG to have increased permeability to the plasma membrane and thus increase the
subsequent effects as a cancer therapeutic agent. An efficient, cheap and time effective analytical
method for studying the interaction of these two molecules is capillary electrophoresis.
Capillary electrophoresis (CE) is an analytical method that differentiates and separates
charged species on the basis of mobility under the influence of an electric field gradient (Chu et
al. 1995). When voltage is applied, electroosmotic flow (EOF) is generated through the buffer
solution along the capillary. The sample is then injected into the buffer and is separated and

3

analyzed based on size and charge. Therefore, small positive ions are detected before small
negatively charged ions. This process can be seen below in Figure 3.

Figure 3. A diagram depicting EOF including the separation of ions based on size and charge
between the anode and cathode (Laboratoire Suisse d’Analyse du Dopage 2008).
Non-covalent molecular interactions, such as the suspected interaction of EGCG and DHA,
can be quantified using a sub-category method of CE called affinity capillary electrophoresis
(ACE). In ACE, the electrophoretic mobility is measured as a function of concentration that a
ligand binds the analyte in the electrophoresis buffer (Chu et al. 1995). As the molecules interact
inside the capillary, a complex is formed which results in slower migration throughout the capillary
and a longer migration time to the detector. The binding constant can then be estimated by the
changes in the migration time of the analyte alone compared to the migration time of the complex.
In order to determine the change in migration time, a neutral marker is also needed. This compound
has no effect on the binding affinity and serves as a reference point when calculating the effective
electrophoretic mobility is used to generate the binding constant of EGCG and DHA. The formula
for the effective electrophoretic mobility can be seen below in Figure 4.

µ

 Lt Ld  1 1   I 
 −   
=
e  V  tc tm   I o 



L : total length of capillary
t

L : effective length of capillary (to detector)
d

V: applied voltage
t : migration time of complex
c

t : migration time of neutral marker
m

I: measured current at zero additive concentration
I : measured current at given additive concentration
o

Figure 4. The formula and constants for the effective electrophoretic mobility that is used to
quantify binding interactions (Harris 2010).

4

In this experiment, the capillary will be filled with buffer solution containing varying amounts of
DHA with a sample solution at a constant concentration of EGCG. It is expected to see larger
EGCG peak shifts with increasing concentrations of DHA. The binding constant can then be
estimated by the changes in migration time of EGCG as a function of DHA. This interaction study
will be optimized for physiological conditions in order to infer the results to possible therapeutic
approaches for breast cancer.

2

MATERIALS AND METHODS

2.1

Reagents
The EGCG standard, the DHA standard, dimethylformamide (DMF) and sodium

tetraborate were all purchased from Sigma-Aldrich Canada Ltd., Oakville, Ontario, Canada and
were all of analytical-reagent grade. The pH of the sodium borate buffers and background
electrolyte (BGE) solutions were adjusted by using 1.0 M hydrochloric acid (HCl) and 1.0 M of
sodium hydroxide (NaOH). All solutions were prepared using filtered 18 MΩ water and were
filtered once again using a 0.45 µm nylon filter before use in the instrument.
2.2

Capillary Electrophoresis
All of the experiments were performed using a Beckman P/ACE™ MDQ Capillary

Electrophoresis System (Beckman Coulter, Inc., Fullerton, CA) equipped with an ultraviolet (UV)
detector and interfaced to a shared lab computer. Uncoated fused-silica capillary (50 µm internal
diameter, 50 cm total length, 40 cm effective length) was used and purchased from Polymicro
Technologies (Pheonix, AZ). Galden® HT-110 perfluoropolyether coolant (Ideal Vacuum
Products LLC, Albuquerque, NM, USA) was used in the capillary cartridge to keep the
temperature at a consistent 25 °C. Detection was set at a wavelength of 214 nm. This wavelength
is within the ultraviolet range, which is absorbed by the conjugated double bonds of the EGCG
molecule and, to a much lesser degree, by the excess pi electrons in the DHA molecule.
Initially, the capillary was conditioned by flushing 1.0 NaOH through the capillary for 60
minutes, 0.1 M NaOH for 30 min and 18 MΩ water for 10 min. Prior to the sample injection of
each run, the capillary was rinsed for 5 minutes with 0.1 M NaOH, 18 MOhm water for 1 min and
the run buffer for 4 min. The sample solutions were then injected into the capillary for 5.0 seconds
with a pressure of 1.0 psi. Separation of the samples occurred under normal polarity at an applied
5

voltage of 10 kV. Each run was allowed to separate for 20 min, with the total time for each run
being 30 min.
2.3

Preparation of the EGCG and DHA Stock Solutions
A 1000 ppm stock solution of EGCG was prepared by dissolving 5 mg in 5 mL of filtered

18 MΩ water. The stock solution was placed in a glass vial and stored in the fridge at 4oC. A 1000
ppm stock solution of DHA was also prepared by combining 53 µL DHA into 50 mL of filtered
methanol. The DHA stock solution was transferred to a brown glass container, as the solution is
light sensitive. It was also stored in the fridge at 4oC. All stock solutions were filtered again using
a 0.45 µm nylon filter prior to transfer into their storage containers.
2.4

Preparation of Buffer and Background Electrolyte Solutions
A 100 mM stock solution of sodium borate buffer was prepared by dissolving an

appropriate amount of sodium tetraborate into filtered 18 MΩ water. The pH of each buffer
solution was then adjusted using a pH reader and either 1.0 M HCl or 1.0 M NaOH. A total of
three buffer solutions were made with pH’s of 9.0, 8.5 and 8.0 and one BGE solution was made
with a pH of 7.5.
2.5

Preparation of Run Buffer and EGCG Samples with DMF
The 100 mM borate buffer solution was subsequently diluted to 25 mM borate buffer

solution by transferring 250 µL into the CE vial. Filtered 18 MΩ water was then added to each
vial to dilute the buffer solution. Various amounts of the 1000 ppm DHA stock solution (0-250
µL) were then added to the vials to equal 0-250 ppm. Each CE vial had a total of 1 mL and were
vortexed well. For the samples, 40 µL of the 1000 ppm EGCG stock solution were added to each
sample vial, along with 5 µL of a 1:50 DMF solution. Filtered 18 MΩ water was then added to
each vial to equal 400 µL and each sample was vortexed well.

3

RESULTS AND DISCUSSION
Prior to conducting the interaction study between EGCG and DHA, many instrumental and

experimental parameters had to be optimized. These conditions included the sodium borate buffer
and BGE concentration, the concentration of EGCG and the neutral marker.

6

3.1

EGCG Concentration Optimization
First, the optimal concentration of EGCG was determined. This concentration is important,

as it will form a complex with the DHA present in the BGE solution. In this experiment, various
concentrations of EGCG (50-150 ppm) were analyzed at a 50 mM BGE solution, as seen below in
Figure 5. This work was conducted prior to buffer optimization and the concentration was chosen
based on previous studies. A 1 µL aliquot of DMF was added to each sample vial prior to running.
The EGCG peaks appear much smaller than the neutral marker peak because of the large quantity
of neutral marker added to the EGCG sample. Based on the observed peaks, 100 ppm was selected
as the constant EGCG concentration to use in the interactions studies. This also confirms the
concentration of previous studies.

A

B

C

Figure 5. The electropherogram showing various concentrations of EGCG peaks. The top run
contained 50 ppm (A), the middle contained 100 ppm (B) and the bottom contained 150 ppm (C).
The first peak is the neutral marker (DMF) and the second smaller peak is the EGCG. Conditions:
detection, UV; applied voltage, 10 kV; BGE concentration, 50 mM; BGE pH, 7.5; temperature,
25oC.

3.2

Neutral Marker Optimization
The use of a neutral marker is essential when using ACE and serves many purposes. First,

it gives an indication of EOF rate and allows for easy observation of any differences of EOF that
7

may occur across runs. It also serves as a reference point to determine the migration shift of the
EGCG and DHA complex peak. Optimization of the amount to add of the neutral marker is
important because it should be detectable and proportional to the EGCG peak. Mesityl oxide and
DMF were both tested as potential neutral markers. In this experiment, 1 µL of each were added
to the EGCG sample vials and their peaks were observed as seen in Figure 6. The height of the
mesityl oxide peaks appeared to greatly decrease over the course of the entire experiment. This
indicates that it is not very stable and therefore was not chosen for further experiments. DMF,
however, showed excellent peak heights consistent over the entire run. Therefore, DMF was used
in the following experiments. For these experiments, a 5 µL aliquot of a 1:50 DMF dilution was
used in order to obtain appropriate peak heights relative to the EGCG peak.

A
B
C

D
E
F

Figure 6. The electropherogram that compares the two potential neutral markers. The top three
peaks consisted of a 1 µL aliquot added to samples containing 50 ppm (A), 100 ppm (B) and 150
ppm (C) of EGCG. The bottom three peaks consisted of a 1 µL aliquot also added to samples
containing 50 ppm (D), 100 ppm (E) and 150 ppm (F) of EGCG. Based on this data, DMF was
used as the neutral marker for the following interaction studies. Conditions: detection, UV; applied
voltage, 10 kV; BGE concentration, 50 mM; BGE pH, 7.5; temperature, 25oC.

3.3

BGE Concentration Optimization
The BGE concentration is a very important factor when using CE. It affects the EOF, and

can also influence the degree of analyte separate and detection. Initially, four different
8

concentrations were tested in order to determine the concentration that gave the best EGCG peak
shape and baseline separation. These concentrations included 25 mM, 50 mM, 75 mM and 100
mM. The optimal BGE concentration was tested at pH 7.5 in order to apply to physiological pH.
As seen below in Figure 7, the optimal BGE concentration appeared to occur at 25 mM. This
concentration had the shortest separation time between the neutral marker and the EGCG peaks,
which is beneficial because once the EGCG complexes with the DHA, it will migrate further from
the neutral marker. If the baseline separation between these two peaks is large without the addition
of DHA, then the run time would have to be greatly increased. The 25 mM concentration also gave
the best EGCG peak shape compared to the other concentrations. The EGCG peak can be seen to
decrease in sharpness and height as the concentration increases until it completely disappears in
the 100 mM concentration.

A

B

C

D

Figure 7. The electropherogram displaying the various BGE concentrations at pH 7.5. Each run
was run in duplicates at the concentrations of 25 mM (A), 50 mM (B), 75 mM (C) and 100 mM
(D). The first peak is the neutral marker (DMF) and the second peak is the EGCG (100 ppm).
Based on the obtained results, 25 mM appeared to give the best EGCG peak shape and baseline
separation. Therefore, this concentration was used for all following interaction studies. Conditions:
detection, UV; applied voltage, 10 kV; BGE pH, 7.5; temperature, 25oC.

9

3.4

Interaction Studies
Once the experimental conditions were optimized, experiments that determined the

interaction between EGCG and DHA were conducted. Because the goal of this work is to observe
the interaction mimicking physiological conditions, studying the interaction at physiological pH
was essential. A similar trend is seen in all of the following interaction studies – as the
concentration of DHA increases in the migration of the EGCG complex peak increases as well.
This shows that a complex is being formed between EGCG and DHA. The changes in migration
can then be used to calculate the binding constant between these two molecules. Another trend that
is seen in every interaction study is a slight migration of the neutral marker peak. This occurs due
to an increase of viscosity in the BGE solution as the concentration of DHA increases. This
migration can be corrected for in the binding constant calculations.
3.4.1

Interaction Study at pH 9.0

The first interaction study was run with a BGE solution of pH 9.0. This pH was chosen because
it is an optimal pH to use with a sodium borate buffer and similar work has previously been
successful at this pH. The results of the interaction study can be seen in Figure 8.

A
B
C
D
E

F

Figure 8. The electropherogram of the interaction study between EGCG and DHA with a 25 mM
BGE solution of pH 9.0. The sample consisted of a 5 µL aliquot of a 1:50 DMF dilution as well as
a constant concentration of 100 ppm EGCG. The 25 mM BGE solution contained various
concentrations of DHA: 0 ppm (A), 50 ppm (B), 100 ppm (C), 150 ppm (D), 200 ppm (E), 250
ppm (F). The formation of a complex as the concentration of DHA increases is evident due to the

10

increase in migration of the EGCG peak. Conditions: detection, UV; applied voltage, 10 kV; BGE
concentration, 25 mM; temperature, 25oC.

3.4.2

Interaction Study at pH 8.5

The second interaction study was run with a BGE solution of pH 8.5. The results of the
interaction study can be seen below in Figure 9.

A
B
C
D
E
F

Figure 9. The electropherogram of the interaction study between EGCG and DHA with a 25 mM
BGE solution of pH 8.5. The sample consisted of a 5 µL aliquot of a 1:50 DMF dilution as well as
a constant concentration of 100 ppm EGCG. The 25 mM BGE solution contained various
concentrations of DHA: 0 ppm (A), 50 ppm (B), 100 ppm (C), 150 ppm (D), 200 ppm (E), 250
ppm (F). The formation of a complex as the concentration of DHA increases is evident due to the
increase in migration of the EGCG peak. Conditions: detection, UV; applied voltage, 10 kV; BGE
concentration, 25 mM; temperature, 25oC.

3.4.3

Interaction Study at pH 8.0

The third interaction study was run at a with a BGE solution of pH 8.0. The results of the
interaction study can be seen below in Figure 10.

11

A
B
C
D
E
F
Figure 10. The electropherogram of the interaction study between EGCG and DHA with a 25 mM
BGE solution of pH 8.0. The sample consisted of a 5 µL aliquot of a 1:50 DMF dilution as well as
a constant concentration of 100 ppm EGCG. The 25 mM BGE solution contained various
concentrations of DHA: 0 ppm (A), 50 ppm (B), 100 ppm (C), 150 ppm (D), 200 ppm (E), 250
ppm (F). The formation of a complex as the concentration of DHA increases is evident due to the
increase in migration of the EGCG peak. Conditions: detection, UV; applied voltage, 10 kV; BGE
concentration, 25 mM; temperature, 25oC.

3.4.4

Interaction Study at pH 7.5

The fourth interaction study was run at a with a BGE solution pH of 7.5. The results of the
interaction study can be seen below in Figure 11. Based on these results, an interaction does occur
between EGCG and DHA at physiological pH.

12

A
B
C
D
E
F

Figure 11. The electropherogram of the interaction study between EGCG and DHA with a 25 mM
BGE solution of pH 8.0. The sample consisted of a 5 µL aliquot of a 1:50 DMF dilution as well as
a constant concentration of 100 ppm EGCG. The 25 mM BGE solution contained various
concentrations of DHA: 0 ppm (A), 50 ppm (B), 100 ppm (C), 150 ppm (D), 200 ppm (E), 250
ppm (F). The formation of a complex as the concentration of DHA increases is evident due to the
increase in migration of the EGCG peak. Conditions: detection, UV; applied voltage, 10 kV; BGE
concentration, 25 mM; temperature, 25oC.

Based on these results, it appears that an interaction does occur between EGCG and DHA at
physiological pH. This study was run in duplicates in order to obtain enough data to derive a
significant binding constant.
3.5

Binding Constant
The binding constant between the molecules EGCG and DHA was calculated from the data

obtained from the pH 7.5 experiments. It was analyzed using the linear regression method as
outlined in detail in the appendix. From this the x-reciprocal, the y-reciprocal and the double
reciprocal plots were obtained. The plots had R2 values of 0.8585, 0.9997 and 0.8548, respectively.
From these plots, the equation of the lines were used to calculate the binding constants. The
calculations that were used can be found in the appendix. The binding constants from the xreciprocal, y-reciprocal and double reciprocal were determined to be 4.41 x 104, 4.92 x 104 and
2.65 x 104, respectively. These values gave an average binding constant value of 4.0 x 104 (±1.2
x 104), as seen in Table 1. This value implies that there is a reasonably strong interaction between
13

EGCG and DHA at physiological pH. This value is also very close to previous work that
determined the binding constants of fatty acids with beta-cyclodextrin (Parker and Stalcup 2008).
Table 1. The binding constants determined for EGCG and DHA at pH 7.5 that were calculated
using linear regression plots.
Plot

Binding Constant

X-Reciprocal

4.41 x 104

Y-Reciprocal

4.92 x 104

Double Reciprocal

2.65 x 104

Average

4.0 (±1.2) x 104

As seen in the appendix, all three linear regression plots resulted in large and significant
R2 values that were greater than 0.85. Because ACE assumes a 1:1 binding system, the binding
stoichiometry cannot be confirmed unless further analysis is conducted. However, the benefit of
using the linear regression model over other models to derive binding constants is that the binding
stoichiometry can be inferred from the x-reciprocal plot. A linear plot is indicative of a 1:1 binding
stoichiometry compared to a nonlinear plot that may imply a 1:2 binding stoichiometry. In this
experiment, I would expect a 1:1 binding stoichiometry of EGCG and DHA based on the xreciprocal plot.

4

CONCLUSION AND FUTURE WORK
ACE was shown to be a successful technique for studying the interaction between EGCG

and DHA at physiological conditions. By using optimized instrumental conditions for ACE
(detection, UV; applied voltage, 10 kV; BGE concentration, 25 mM; BGE pH, 7.5; temperature,
25oC), the strength of the interaction between EGCG and DHA could be determined. With these
conditions, the migration times for the EGCG peak and the EGCG/DHA complex peak were
measured and analyzed. They were analyzed using the linear regression method (outlined in the
appendix) that assumes a 1:1 binding system. At physiological pH the binding constant was
determined to be 4.0 (± 1.2) x 104 by using the linear regression method. This binding constant
value indicates that a reasonably strong interaction occurs between EGCG and DHA at
14

physiological pH and 25oC. Also, based on the linear plot obtained from the x-reciprocal plot
shown in the appendix, I would assume a 1:1 binding stoichiometry between EGCG and DHA.
Therefore, DHA can be selected as a potential carrier molecule that would bind and subsequently
transport EGCG through the plasma membrane and into the cancerous cell. More investigation
into the specifics of this interaction must be studied in order to determine the potential of this
cancer therapeutic strategy.
Future work for this research would be to run the triplicate of the interaction study with a
BGE solution of pH 7.5 in order to obtain more statistically significant results. Also, the type of
interaction should be determined by conducting a thermodynamic study. Because we want to study
this interaction as close to physiological conditions as possible, the temperature the interaction
occurs at should be modified to 37oC (the temperature inside the body). The sites of binding should
also be investigated because ACE assumes a 1:1 interaction. This can be done either by capillary
electrophoresis-frontal analysis or by studying proton nuclear magnetic resonance (1H-NMR).
Finally, other Omega-3 fatty acids should be investigated with these instrumental conditions such
as ALA.

15

5

LITERATURE CITED

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Sensitization to treatments and prevention of metastatic re-growth. Progress in Lipid
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Canadian Cancer Society [Internet]. c2016. Breast Cancer Statistics [cited 2016 Mar 30].
Available from http://www.cancer.ca/en/cancer-information/cancer
type/breast/statistics/?region=on
Chu YH, Avila L, Gao J, Whitesides G. 1995. Affinity Capillary Electrophoresis. Accounts
of Chemical Research. 28(11): 461-468
Causte C, Rosell M, Durand T, Vercauteren J. 2016. Omega-3 polyunsaturated lipophenols, how
and why? Biochimie. 120: 62-74
Epstein H. 2009. Cosmeceuticals and polyphenols. Clinics in Dermatology. 27: 475-478.
Farabegoli F, Barbi C, Lambertini E, Piva R. 2007. (-)-Epigallocatechin-3-gallate downregulates
estrogen receptor alpha function in MCF-7 breast carcinoma cells. Cancer Detection and
Prevention. 31(6): 499-504
Feng WY. 2006. Metabolism of Green Tea Catechins: An Overview. Current Drug Metabolism.
7: 755-809
Fujiki H. 2005 Green tea: health benefits as cancer preventive for humans. The Chemical
Record. 5: 119-132
Hardman W.E, Avula C.P, Fernandes G, Cameron I.L. (2001). Three percent dietary fish oil
concentrate increased efficacy of doxorubicin against MDA-MB 231 breast cancer
xenographs. Clinical Cancer Research. 7: 2041-2049
Harris D. 2010. Quantitative Chemical Analysis. 8th ed. New York (NY): W.H Freeman and
Company. 635p
Holliday DL, Speirs V. 2011. Choosing the right cell line for breast cancer research. Breast
Cancer Reasearch. 13: 215
Horrocks LA and Yeo YK. 1999. Health benefits of docosahexaenoic acid (DHA).
Pharmacological Research. 40(3): 211-225.
16

Ishii T, Mori T, Tanaka T, Mizuno D, Yamaji R, Kumazawa S, Nakayama T, Akagawa M.
2008. Covalent modification of proteins by green tea polyphenol (-)-epigallocatechin3-gallate through autoxidation. Free Radical Biology & Medicine. 45: 1384-1394
Kiruthika TK. 2015. Docosahexaenoic Acid (Dha) – The Magic of Master Brain. Asian Journal
of Nursing Education and Research. 5(3): 425-428.
Laboratoire Suisse d’Analyse du Dopage. c2008. Capillary Electrophoresis. [cited 2016 Mar 10].
Available from: http://www.doping.chuv.ch/en/lad_home/lad-prestations-laboratoire/ladprestations-laboratoire-appareils/lad-prestations-laboratoire-appareils-ec.htm
Lee HR, Kim TH, Choi KC. 2012. Functions and physiological roles of two types of estrogen
receptors, ERα and ERβ, identified by estrogen receptor knockout mouse. Laboratory
Animal Research. 28(2): 71-76.
National Cancer Institute. c2016. What is cancer? [cited 2016 Mar 31]. Available from:
http://www.cancer.gov/about-cancer/what-is-cancer
Parker K, Stalcup A. 2008. Affinity capillary electrophoresis and isothermal titration calorimetry
for the determination of fatty acid binding with beta-cyclodextrin. Journal of
Chromotography A. 1204: 171-182.
Ranzato E, Magnelli V, Martinotti S, Waheed Z, Cain S, Snutch T, Marchetti C, Burlando B.
2014. Epigallocatechin-3-gallate elicits Ca2+ spike on MCF-7 breast cancer cells:
Essential role of Cav3.2 channels. Cell Calcium. 56(4): 285-295.
Scarsi C, Levesque A, Lisi L, Navarra P. 2015. The free fractions of circulating docosahexaenoic
acid and eicosapentenoic acid as optimal end-point of measure in bioavailability studies
on n-3 fatty acids. Prostaglandins, Leukotrienes and Essential Fatty Acids. 96: 11-16
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17

6

APPENDIX

6.1

Linear Regression Method for Calculating Binding Constants
During the formation of the EGCG and DHA complex, a rapid equilibrium is occurring

that favours the formation of the complex. The complex occurs in a 1:1 stoichiometry that can be
seen in Equation 1.
EGCG + DHA ⇌ EGCGDHA (1)

The binding constant (K) is then calculated in Equation 2 as follows:
K=

[EGCGDHA]
[EGCG][DHA]

(2)

The electrophoretic mobility (µe), discussed in the intro, can then be calculated using Equation 3.
µe = �

Lt Ld 1
1
Io
� − �� � �
V tc tm
I

(3)

Equation 3 can also be given as Equation 4 to determine the electrophoretic mobility of the free
analyte, μo, given in Equation 5, as well as the electrophoretic mobility of the complex, μc in
Equation 6.
µe =

µo + µc K[DHA]
1 + K[DHA]

µo =
µc =

Ld Lt
Vt o

Ld Lt
Vt c

(4)

(5)

(6)

Finally, the electrophoretic mobility equation can be rearranged to give three linear equations.
These linear equations are then used to plot the double reciprocal (Equation 7), the y-reciprocal
(Equation 8) and the x-reciprocal (Equation 9).
1
1
1
1
=
·
+
µe − µo
�µc − µo �K DHA µc − µo

(7)
18

[DHA]
1
1
=
· [DHA] +
µe − µo
�µc − µo �
�µc − µo �K

(8)

µe − µo
= −K�µe − µo � + K �µc − µo � (9)
[DHA]
1

1

For the double reciprocal, the values of µ − µ are plotted against DHA and the binding constant is
e

o

[DHA]

calculated by dividing the y-intercept by the slope of the equation. For the y-reciprocal, the µ − µ
e

o

values are plotted against the [DHA]. The y-reciprocal binding constant is then calculated by
µ − µo

dividing the slope of the equation by the y-intercept. Lastly, the x-reciprocal is plotted with e

[DHA]

values against �µe − µo � values. This binding constant is then determined by taking the negative
of the slope of the equation. All of the binding constant values can then be averaged to obtain a
significant binding constant value.
6.2

Linear Regression Plots

X-Reciprocal
-0.00068

-0.00066

-0.00064

-0.00062

-0.0006

-0.00058

-0.00056

(µe-µo)/[DHA]

0
-0.00054
-1

y = 44115x + 24.14
R² = 0.8585

-2

µe-µo

-3

-4

-5

-6

19

Y-Reciprocal

0
0

0.0001

0.0002

0.0003

0.0004

0.0005

0.0006

0.0007

0.0008

[DHA]

-0.2

[DHA]/(µe-µo)

-0.4
-0.6
-0.8
-1
-1.2
y = -1812.1x + 0.0368
R² = 0.9997

-1.4
-1.6

Double Reciprocal

-3000
0
-3200

2000

3000

4000

5000

6000

7000

1/[DHA]
y = 0.1644x - 4361.5
R² = 0.8548

1/(µe-µo)

-3400

1000

-3600
-3800
-4000
-4200
-4400

20