The Metabolic and Performance Effects of Caffeine
Compared to Coffee during Endurance Exercise
Adrian B. Hodgson1, Rebecca K. Randell1, Asker E. Jeukendrup1,2*
1 Human Performance Laboratory, School of Sport and Exercise Science, University Of Birmingham, Birmingham, United Kingdom, 2 Gatorade Sport Science Institute,
PepsiCo, Barrington, Illinois, United States of America
Abstract
There is consistent evidence supporting the ergogenic effects of caffeine for endurance based exercise. However, whether
caffeine ingested through coffee has the same effects is still subject to debate. The primary aim of the study was to
investigate the performance enhancing effects of caffeine and coffee using a time trial performance test, while also
investigating the metabolic effects of caffeine and coffee. In a single-blind, crossover, randomised counter-balanced study
design, eight trained male cyclists/triathletes (Mean6SD: Age 4167y, Height 1.8060.04 m, Weight 78.964.1 kg, VO2 max
5863 mlNkg21Nmin21) completed 30 min of steady-state (SS) cycling at approximately 55% VO2max followed by a 45 min
energy based target time trial (TT). One hour prior to exercise each athlete consumed drinks consisting of caffeine (5 mg
CAF/kg BW), instant coffee (5 mg CAF/kg BW), instant decaffeinated coffee or placebo. The set workloads produced similar
relative exercise intensities during the SS for all drinks, with no observed difference in carbohydrate or fat oxidation.
Performance times during the TT were significantly faster (,5.0%) for both caffeine and coffee when compared to placebo
and decaf (38.3561.53, 38.2761.80, 40.2361.98, 40.3161.22 min respectively, p,0.05). The significantly faster performance
times were similar for both caffeine and coffee. Average power for caffeine and coffee during the TT was significantly
greater when compared to placebo and decaf (294621 W, 291622 W, 277614 W, 276623 W respectively, p,0.05). No
significant differences were observed between placebo and decaf during the TT. The present study illustrates that both
caffeine (5 mg/kg/BW) and coffee (5 mg/kg/BW) consumed 1 h prior to exercise can improve endurance exercise
performance.
Citation: Hodgson AB, Randell RK, Jeukendrup AE (2013) The Metabolic and Performance Effects of Caffeine Compared to Coffee during Endurance Exercise. PLoS
ONE 8(4): e59561. doi:10.1371/journal.pone.0059561
Editor: Conrad P. Earnest, University of Bath, United Kingdom
Received November 26, 2012; Accepted February 15, 2013; Published April 3, 2013
Copyright: ß 2013 Hodgson et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: The authors have no funding or support to report.
Competing Interests: AEJ is employed by Pepsi Co. There are no patents, products in development or marketed products to declare. This does not alter the
authors’ adherence to all the PLOS ONE policies on sharing data and materials, as detailed online in the guide for authors.
* E-mail: a.e.jeukendrup@bham.ac.uk
confirmed the ergogenic effects of caffeine using time trial
protocols [3–5,7,8], which involves completing an energy based
target or set distance in as fast as time possible, thus simulating
variable intensities that are likely to occur during competitive
events. In most of these studies pure (anhydrous) caffeine was
ingested through capsules or dissolved in water. Based on this
research it is often assumed that ingesting caffeine in a variety of
dietary sources, such as coffee, will result in the same ergogenic
effect.
Very few studies, however, have shown a positive effect of coffee
on exercise performance. Coffee improved performance in some
[9,19–21], but not all studies [22–24]. This may seem surprising as
reports have shown that coffee is the most concentrated dietary
source of caffeine as well as being one of the largest sources of
caffeine used by athletes prior to competition [25]. Amongst the
current studies, only two investigations have actually used coffee
rather than decaffeinated coffee plus anhydrous caffeine [21,22],
with only one of these studies showing an ergogenic effect of the
coffee [21]. This further identifies the equivocal evidence
surrounding the performance effects of coffee. The most cited
study is perhaps a study by Graham et al [22], who showed that
running time to exhaustion (85% VO2 max) was only improved
when runners ingested pure caffeine (4.5 mg CAF/kg BW), prior
to exercise, but not when they ingested either regular coffee
Introduction
Numerous studies to date have shown that caffeine ingested
prior to [1–7] and during [8] prolonged sub-maximal and high
intensity exercise can improve performance. Since the seminal
work by Costill and colleagues [9] it is often cited that caffeine
induces its ergogenic effects by an increase in fat oxidation through
the sympathetic nervous system, and a sequential sparing of
muscle glycogen [2]. However, there is very little support for an
increase in fat oxidation [10,11] or an enhancement to the
sympathetic nervous system [12] being the principal mechanism of
caffeine’s ergogenic effect. Since, recent investigations have
elucidated that the principal mechanism of caffeine’s ergogenic
effects is through its ability to act as an adenosine receptor
antagonist to induce effects on both central and peripheral nervous
system [13] to reduce pain and exertion perception [14], improve
motor recruitment [13] and excitation-contraction coupling [15–
17].
In the literature to date, the ergogenic effects are well
documented with the time to exhaustion test at a fixed power
output being the predominant performance measure used [1,2,9–
11]. It was questioned whether assessing endurance capacity in this
way would have sufficient ecological validity to translate results to
real life events [18]. However since then, a number of studies have
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Caffeine and Coffee on Exercise Performance
trials, each separated by 7 days. Each trial consisted of consuming:
caffeine (5 mg CAF/kg BW) (CAF), coffee (5 mg CAF/kg BW)
(COF), decaffeinated coffee (DECAF) or placebo (PLA) in the
overnight fasted state (8 hrs) 1 h before completing 30-min steady
state cycle exercise bout (SS) (55% V_ O2 max). Following this each
participant was instructed to complete a time trial lasting
approximately 45-min.
(4.5 mg CAF/kg BW), decaffeinated coffee plus caffeine (4.5 mg
CAF/kg BW), decaffeinated coffee and a placebo control. The
authors reported that the difference in performance could not be
explained by the caffeine or methylxanthine plasma concentrations 1 h following intake or at end of exercise, as no difference
was observed between trials that contained caffeine.
Graham et al [22] suggested that other components in coffee
known as chlorogenic acids, may have antagonised the physiological responses of caffeine. However, in this study [22] chlorogenic
acids in the coffee or in the plasma were not measured.
Chlorogenic acids are a group of phenolic compounds that possess
a quinic acid ester of hydroxycinnamic acid [26]. The consumption of chlorogenic acids varies significantly in coffee ranging from
20–675 mg per serving [26]. It has previously been shown in vitro
that chlorogenic acids antagonize adenosine receptor binding of
caffeine [27] and cause blunting to heart rate, blood pressure and
cause a dose-dependent relaxation of smooth muscle [28]. For this
reason, it is unclear what role chlorogenic acids, found in coffee,
will have on the physiological and metabolic effects of coffee and
caffeine during exercise in humans. Therefore, due to the large
variation of chlorogenic acids between coffee beverages and the
unclear performance effects of coffee to date, it is yet to be
determined if coffee causes differences in the performance and
metabolic effects during exercise when compared to caffeine alone.
Therefore the primary aim of the present study was to
investigate whether acute intake of coffee (5 mg CAF/kg BW)
and anhydrous caffeine (5 mg CAF/kg BW) are ergogenic to
cycling performance compared to decaffeinated coffee or placebo
beverages when using a validated 45-minute time trial performance test. In addition, completing a steady state exercise bout
prior to the time trial performance test is a routine protocol used in
our laboratory [18,29]. For this reason it provided any opportunity
to also investigate the effect of acute anhydrous caffeine or coffee
intake on substrate oxidation and plasma metabolite responses
during 30-min steady state exercise (55% VO2 max). The study
hypothesis was that despite the previous work by Graham et al
[22], 5 mg CAF/kg BW regardless of the form of administration
(anhydrous or coffee) would be ergogenic to performance similarly
when compared to decaffeinated coffee or placebo, but this effect
would not be mediated through changes in fat metabolism.
Preliminary Trial
Before the experimental trial, participants visited the Human
Performance Laboratory at the University of Birmingham on two
separate occasions separated by 7 days. During the first visit
participants completed an incremental exercise test on an
electronically braked cycle ergometer (Lode Excalibur Sport,
Groningen, Netherlands) to volitional exhaustion (V_ O2 max test).
Prior to beginning the test participants firstly had weight (OHaus,
Champ II scales, USA) and height (Seca stadiometer, UK)
recorded. Participants mounted the cycle ergometer, which was
followed by a 5-min warm up at 75 W, participants then started
the test at 95 W for 3-min. The resistance was increased every 3min, in incremental steps of 35 W, until they reached voluntary
exhaustion. Wmax was calculated using the following equation:
W max ~Woutz½ðt=180Þ|35
Where Wout is the power output of the last stage completed
during the test, and t is the time spent, in seconds, in the final
stage. Throughout the test respiratory gas measurements (V_ O2
and V_ CO2 ) were collected continuously using an Online Gas
Analyser (Oxycon Pro, Jaeger). V_ O2 was considered maximal if 2
out of the 4 following criteria were met: 1) if V_ O2 levelled off even
when workload increased 2) a respiratory exchange ratio (RER) of
.1.05 3) a heart rate within 10 beats/min of age predicted
maximal heart rate 4) a cadence of 50 rpm could not be
maintained. Heart rate (HR) was recorded during each stage of
the test using a HR monitor (Polar, Warwick, UK). Wmax was
used to determine the work load for the steady state exercise bouts
throughout all subsequent experimental trials (50% Wmax). Wmax
was also used to calculate the total amount of work to be
completed during the 45-min time trial and the linear factor, both
calculated according to the formula derived by Jeukendrup et al
[18]. The bike position was recorded following the test to be
replicated in all other trials.
Approximately 7 days later participants reported back to the
lab, for the second preliminary trial, between 0600 and 0800
having undergone an 8 hr fast. The purpose of the trial was to
familiarise each subject to the experimental trial and time trial
protocol. All participants completed 30-min SS at 50% Wmax
(55% V_ O2 max). Expired breath samples were collected every 10min for measures ofV_ O2 , V_ CO2 , and RER (Oxycon Pro, Jaeger).
Immediately following all participants completed a time trial
lasting ,45 min. The data collected during the familiarisation trial
was not used for any of the final analysis.
Materials and Methods
Participants
Eight trained cyclists/triathletes (Mean 6 SD: Age 4167y,
Height
1.8060.04 m,
Weight
78.964.1 kg,
V_ O2 max
5863 mlNkg21Nmin21) were recruited from local Birmingham
cycling and triathlon clubs. Inclusion criteria included participants
who trained 3 or more times per week (.90-min/session), had
been training for .2 years, and had a low habitual caffeine intake
of #300 mg/d (approximately #3 cups coffee/d).
Ethics statement
All participants were fully informed of the experimental trials
and all risks and discomforts associated before providing written
informed consent to participate in the study. All procedures and
protocols were approved by the Life and Environmental Sciences
Ethical Review Committee at the University of Birmingham.
Experimental Trial
All participants reported to the Human Performance Lab
between 0600 and 0800 having completed an 8 h overnight fast.
On arrival weight was recorded (Seca Alpha, Hamburg, Germany)
and a flexible 20-gauge Teflon catheter (Venflon; Becton
Dickinson, Plymouth, United Kingdom) was inserted into an
antecubital vein. A 3-way stopcock (Connecta; Becton Dickinson)
was attached to the catheter to allow for repeated blood sampling
General Study design
The study followed a single blinded, cross over, randomised
counter-balanced study design. Maximal oxygen uptake
(V_ O2 max) and power (Wmax) was assessed during a preliminary
trial. Following this each participant completed 4 experimental
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Caffeine and Coffee on Exercise Performance
and served in an opaque sports drinks bottle. The exact dose of
quinine sulphate was preliminary tested in our lab. A dose of 8 mg
was sufficient to prevent the blinded researchers from distinguishing between the placebo and caffeine trial.
The coffee and decaffeinated coffee samples were further
analysed externally for chlorogenic acids (5-CQA) (Eurofins
Scientific, Italy). Based on the analysis, total 5-CQA was
33.91 mg/g and 28.29 mg/g for COF and DECAF respectively.
This was then used to calculate the average concentration of total
5-CQA and related isomers for each participants drinks, based on
the weight of instant COF and DECAF. The average chlorogenic
acid intake in COF and DECAF are presented in Table 1. All of
the beverages were prepared in 600 ml of water. This was firstly to
avoid any difference in uptake and bioavailability of each of the
ingested ingredients, as well as replicating the format of coffee
consumption from everyday life. Secondly 600 ml of coffee
dissolved in water was not only considered tolerable, based on
taste testing by researchers within our laboratory, but also
matched similar volumes as used by Graham et al [22]. Once
participants received each of the beverages at the beginning of the
trial, they had 15 min to consume the entire 600 ml.
during the experimental period. An initial 15 ml fasting blood
sample was collected (EDTA-containing tubes, BD vacutainers).
Following this all participants consumed one of the treatment
beverages and rested for 1 h, with further samples taken at 30 min
and 60 min (10 ml EDTA). After the rest period, participants then
mounted the cycle ergometer, in an identical bike position as
recorded during the preliminary trial, and began a 30-min SS at
50% Wmax (55% V_ O2 max). Blood samples (15 ml) and 5-min
respiratory breath samples, VO2, VCO2 and RER, (Oxycon Pro,
Jaeger) were collected every 10-min during the exercise. The
catheter was kept patent during both the rest and exercise period
by flushing it with 5 mL isotonic saline (0.9% w/v; B Braun) after
every blood sample. In addition, heart rate (HR) was recorded
(Polar RS800CX) every 15 min at rest and every 10 min during
SS. Ratings of Perceived Exertion (RPE) scale were recorded every
10 min during SS using the 6–20 Borg scale [30]. Upon
completion of the SS, the subject was instructed to stop exercising
for ,1 min, and the cycle ergometer was set in the linear mode.
The participants were instructed to complete an energy-based
target amount of work at 70% Wmax in the quickest time possible.
The total amount of work (650637 KJ) was calculated for the
45 min time trial. A linear factor, 70% Wmax divided by (90 rpm)2
was entered into the cycle ergometer. The time trial protocol
employed has previously been validated and has been shown to be
highly reliable [18]. Participants received a countdown prior to
starting the time trial and received no verbal or visual feedback
regarding performance time or physiological measures throughout
the test. No additional measures, blood or respiratory, were taken
through the test. Participants received no feedback about their
performance until they had completed all 4 experimental trials.
Following the completion of the TT, each participant completed a
questionnaire to guess the test beverage consumed prior to the
commencement of the trial, as well as report any GI distress
experienced during the trial.
Diet and Exercise Control
Participants were instructed to record their food intake the day
prior to the preliminary familiarisation trial. Participants had to
replicate this diet in the 24 h prior to each experimental trial, as
well as refraining from any exercise, consume no alcohol and
withdraw from any caffeinated products.
Calculations
Substrate metabolism was measured during the SS. From the
respiratory output measurements of V_ O2 and V_ CO2 (L/min),
carbohydrate [1] (CHO) and fat oxidation [2] was calculated
every 10 min during the SS. In order to calculate CHO and fat
oxidation stoichiometric equations [31] were used, which assume
that each of the participants were exercising at a steady state and
that protein oxidation was negligible.
Treatment Beverages
During each visit to the lab, participants ingested one of four
treatment beverages. This included caffeine (5 mg CAF/kg BW),
regular coffee (5 mg CAF/kg BW), decaffeinated coffee and
placebo. Therefore decaffeinated coffee and placebo acted as
controls to both of the caffeinated trials. Caffeine (Anhydrous
caffeine, 99.8% pure, Blackburn Distributions Ltd, Nelson, United
Kingdom) was weighed (394.467.0 mg) prior to the trial, and was
immediately dissolved and vortexed for 15 min in 600 ml of water
prior to consumption and served in an opaque sports drinks bottle.
Coffee was prepared using instant coffee (Nescafe Original). In
order to select the correct weight of coffee to equal 5 mg CAF/kg
BW, Nescafe states that Nescafe Original instant coffee provides
3.4 g caffeine/100 g of instant coffee. This information was
confirmed using a HPLC method (see below), and based on the
analysis it was calculated that 0.15 g coffee/kg/BW equalled 5 mg
CAF/kg BW. Therefore prior to each trial, coffee was weighed
(11.861.0 g) and dissolved in 600 ml hot water (9462uC) and
served in a mug.
DECAF (Nescafe Original Decaffeinated coffee, ,97% caffeine
free) was prepared in an identical fashion, with the same amount
of decaffeinated coffee as the COF beverage. Using a HPLC
method, decaffeinated coffee provided minimal caffeine throughout each of the prepared beverages (0.17 mg CAF/kg BW or
mean intake of 13.4160.70 mg). In order to blind the participants
from the taste of the caffeine trial, the placebo trial consisted of
8 mg of Quinine sulphate (Sigma, UK). Quinine sulphate is a food
ingredient found in tonic water to give a bitter taste. The quinine
sulphate was dissolved in 600 ml of water, vortexed for 15 min,
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½1~4:210 V_ CO2 {2:962 V_ O2
½2~1:65 V_ O2 {1:701 V_ CO2
Blood Analysis
Following collection, all tubes were placed in ice until the end of
the experimental trial. Following this each tube was centrifuged at
3500 rpm for 15 min at 4uC. Aliquots of plasma were immediately
frozen in liquid nitrogen and stored at 280uC for later analysis.
Each blood sample taken throughout each experimental trial were
analysed for plasma glucose (Glucose Oxidase; Instrumentation
Laboratories, England), fatty acids (FA) [NEFA-C; Randox,
England], glycerol (Glycerol; Randox, England) and lactate
[Lactate, Randox, England] using an ILAB 650 (Instrumentation
Laboratory, Cheshire, United Kingdom).
Plasma Caffeine and Chlorogenic Acid analysis
Plasma caffeine were analysed externally (City Hospital,
Dudley, Birmingham) using a reversed-HPLC-UV method. The
sample preparation included: 200 mL of plasma were added to
100 mL internal standard (Proxyphylline, Sigma, United Kingdom) before mixing, heating and adding 500 mL of acetic acid.
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The supernatant was the injected (5 mL) onto a Phenomenex
Prodigy 15064.60 mm 5 m Octadecyl Silane (ODS) column using
an auto sampler and detected at a UV of 273 nm. Caffeine
concentrations were quantified using one point calibration from a
calibrator that had previously been internally validated against a 9
point calibration curve (City Hospital, Dudley, Birmingham). With
each batch two QC (High and Low) were run, with reference to
the internal standard to account for any loses.
The caffeine content of coffee and decaffeinated coffee were
confirmed at the School of Sport and Exercise Sciences. In brief,
coffee and decaf coffee samples were prepared (identical to
preparation described above) and cooled before 5 mL of each
sample were injected onto a Phenomenex Luna 10 m C18 (2)
column using an auto sampler (WPS 3000, Dionex, United
Kingdom). The mobile phase consisted of 0.1 M acetic acid in
water and 0.1 M acetic acid in acetonitrile. Caffeine concentrations were quantified using a 10-point caffeine calibration curve in
water.
Coffee and Decaf coffee were analysed for chlorogenic acids.
The analysis was conducted externally (Eurofins Scientific, Italy)
using a reverse HPLC methodology at 325 nm (Water Symmetry
C18, 25064.6 mm, 5 mm) with external 5-QCA standards for
quantification on a 3 point calibration (10–250 mg/kg). The
mobile phase consisted of aqueous 0.5% formic acid and
acetonitrile.
Abbreviations: CQA Caffeoylquinic acid, 5-CQA 5-O-Caffeoylquinic acid, 4-CQA 4-O-Caffeoylquinic acid, 5-FQA 5-O-Feruloylquinic acid, 4-FQA 4-O-Feruloylquinic acid, 3,5-diCQA 3,5-O-Dicaffeoylquinic acid, 3,4-diCQA 3,4-ODicaffeoylquinic acid, 4,5-diCQA 4,5-O-Dicaffeoylquinic acid, 4,5-CFQA 4,5-O-Dicaffeoylquinic acid, ml millilitres, mg milligrams, CAF Caffeine, COF Coffee, DECAF Decaffeinated Coffee, PLA Placebo.
doi:10.1371/journal.pone.0059561.t001
600
PLA
-
-
-
24%
33%
600
DECAF
13.460.2
328.166.1
23%
7%
-
2%
1%
2%
1%
-
7%
3%
3%
-
2%
3%
7%
8%
-
32%
22%
-
21%
393.367.3
600
COF
394.467.0
600
CAF
394.467.0
-
-
4-FQA
5-FQA
4-CQA
5-CQA
CQA
% of Total 5-CQA
Total 5-CQA
(mg/serving)
Caffeine content
(mg/serving)
Serving
Volume (ml)
Treatment
beverage
Table 1. Mean caffeine and chlorogenic acid (Total 5-QCA) concentration in each treatment beverage serving.
3,5-diCQA 3,4-diCQA
4,5-diCQA
4,5-CFQA
Caffeine and Coffee on Exercise Performance
Statistical Analysis
Data analysis was performed using SPSS for WINDOWS
software (version 17; SPSS Inc, Chicago, IL). Data are expressed
as means 6 SEMs, unless otherwise stated. A repeated measure
ANOVA was used to assess differences in respiratory, substrate
metabolism, plasma metabolite and caffeine concentration as well
as time trial performance measurements during each trial. In order
to detect differences across time and between treatments a Fisher
protected least significant differences post hoc test was used
Significance was set at P,0.05.
Results
Steady State Exercise
Whole body respiratory measures, HR and RPE. The
selected workload of 50% Wmax during the SS (17167 W)
resulted in similar oxygen uptake (V_ O2 ) (2590679, 2595689,
2465679, 2522671 mL/min for CAF, COF, DECAF and PLA
respectively P = 0.278). As a result the relative exercise intensity
during the SS was similar throughout each trial (5862%, 5862%,
5561% and 5561% for CAF, COF, DECAF and PLA
respectively P = 0.337). Energy expended during SS was also
shown to be similar (1607649 KJ, 1611654 KJ, 1531650 KJ,
1565643) for CAF, COF, DECAF and PLA respectively
P = 0.248). In addition no significant difference was observed in
average HR during exercise (11964, 11964, 11964, 12065 bpm
for CAF, COF, DECAF and PLA respectively P = 0.281) or RPE
values (1060, 1060, 1160 and 1160 for CAF, COF, DECAF
and PLA respectively P = 0.091) during SS between trials.
Carbohydrate and Fat oxidation. Carbohydrate oxidation
rates during SS significantly reduced in all treatments across time
(P = 0.001). However there was no significant difference in
carbohydrate oxidation between each of the treatments
(Figure 1A P = 0.288). Similarly, fat oxidation rates significantly
increased during SS in all treatments (P = 0.001). No significant
difference in fat oxidation was observed between each of the
treatments (Figure 1B P = 0.445). Accordingly the contribution of
carbohydrate and fat to total energy expenditure during SS was
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Caffeine and Coffee on Exercise Performance
Figure 1. Carbohydrate oxidation (g/min) (A) and fat oxidation (g/min) (B) rates during 30 min steady state exercise (55% VO2 max)
1 hour following ingestion of caffeine, coffee, decaf or placebo beverages. Data represented seen as Closed circles – Caffeine Open circles
– Caffeinated Coffee Closed triangles – Decaffeinated coffee Open triangles – Placebo. Means 6 SE n = 8
doi:10.1371/journal.pone.0059561.g001
not significantly different between any of the treatments
(P = 0.463).
Plasma metabolite concentrations. Plasma metabolite
responses at rest and exercise are displayed in Figure 2 A–D.
Plasma glucose concentrations (Figure 2A) were significantly
elevated at the end of rest compared to the beginning of rest
following CAF and COF (p,0.05 for both), while no significant
difference occurred following DECAF or PLA (P = 0.676 and
0.188 respectively). The elevation in glucose concentrations with
CAF following the rest period was significantly higher compared
to DECAF only (P,0.05). During exercise, plasma glucose
increased over time following CAF and COF, however only
COF reached statistical significance (P,0.05). DECAF and PLA
glucose concentrations fell during the onset of exercise with a
significant increase in both treatments later in exercise (T = 10–30
P,0.05 for both). As a result, CAF had significantly higher glucose
concentrations within the first 20 minutes of exercise compared to
DECAF and PLA (P,0.05 for both), while at end of exercise CAF
and COF had significantly higher glucose concentrations compared to PLA only (P,0.05 for both). Plasma FAs concentration
(Figure 2B) were significantly elevated at the end of rest compared
to beginning of rest following CAF (P = 0.010), while DECAF and
PLA had reduced FA concentration, with only DECAF reaching
statistical significance (P = 0.007 and P = 0.072 respectively).
Therefore, CAF had significantly higher FAs concentration
compared to DECAF and PLA at end of rest period (P,0.05
for both). During the beginning of exercise, CAF continued to
have significantly elevated FAs concentration compared to
DECAF only (P = 0.037). FA concentration significantly increased
during exercise (T = 10–30 P = 0.030) with no significant differences observed between treatments (P = 0.231).
Plasma glycerol concentrations (Figure 2C) did not significantly
change at rest for CAF (P = 0.066), COF (P = 0.392) and DECAF
(P = 0.104) but PLA significantly fell (P = 0.022). DECAF was
significantly lower at end of rest compared to CAF, COF and PLA
(P,0.05 for all), with no significant differences observed between
any other beverage. During exercise there was a significant
increase in glycerol concentrations for all treatments over time
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(P = 0.001), with significantly higher concentrations observed for
CAF (P = 0.027) and COF (P = 0.003) at beginning of exercise
compared to DECAF only. Plasma lactate concentrations
(Figure 2D), were significantly increased following the consumption of CAF and COF only during the rest period compared to
DECAF (P = 0.050 and P = 0.003 respectively) and PLA (P = 0.002
and P = 0.001 respectively). In addition DECAF had significantly
elevated lactate compared to PLA at end of rest period (P = 0.012).
All treatments lactate concentrations significantly increased at the
onset of exercise (P = 0.004) with CAF and COF being significantly higher compared to PLA (P = 0.037 and P = 0.010
respectively). CAF and COF had sustained lactate concentrations
at the end of exercise, with significantly higher concentrations
compared to DECAF (P = 0.008 and P = 0.028 respectively) and
PLA (P = 0.050 and P = 0.005 respectively).
Plasma caffeine concentrations. The plasma caffeine
concentrations following each beverage are displayed in Figure 3.
At baseline plasma caffeine concentrations were very low for all
treatments (,3 mM), with no significant differences observed
(P = 0.478). Plasma caffeine significantly increased following CAF
and COF when compared to DECAF (P = 0.000 and P = 0.009
respectively) and PLA (P = 0.000 and P = 0.010 respectively), with
peak concentrations observed 60 min after intake (38.262.8 mM
and 33.565.0 mM respectively). No significant difference was
observed in the plasma caffeine concentrations between CAF or
COF (P = 0.156) and DECAF or PLA (P = 0.558) throughout the
trials.
Time trial performance
CAF and COF significantly improved TT finishing times when
compared to both DECAF (P,0.05 for both) and PLA (P = 0.007
and P = 0.010) (Figure 4). As a result mean power output during
the TT was significantly greater for both CAF and COF compared
to DECAF and PLA (29466, 29167, 27667, 27764 W,
respectively P,0.05 for both). However no significant differences
were seen in average heart rate during the TT between CAF,
COF, DECAF and PLA (17063, 16764, 16463, 16564 BPM,
respectively P = 0.516). CAF significantly improved TT perfor5
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Caffeine and Coffee on Exercise Performance
Figure 2. Plasma metabolite responses at rest (t = -60-0) and during 30 min steady state exercise (55% VO2 max) (t = 0–30) following
ingestion of caffeine, coffee, decaf or placebo beverages. A Glucose. B Fatty acids (FA). C Glycerol. D Lactate. Data represented seen as Closed
circles – Caffeine Open circles – Caffeinated Coffee Closed triangles – Decaffeinated coffee Open triangles – Placebo. a Sig. different between CAF and
DECAF (p,0.05) b Sig. different between CAF and PLA (p,0.05) c Sig. different between COF and DECAF (p,0.05) d Sig. different between COF and
PLA (p,0.05). Means 6 SE n = 7.
doi:10.1371/journal.pone.0059561.g002
acute caffeine ingestion for improving prolonged endurance
exercise performance [1–7]. The effects of caffeine on time trial
endurance performance (.5 min) have recently been reviewed in
a well conducted meta-analysis [7]. The authors concluded that of
the 12 studies that investigated caffeine intake (1–6 mg CAF/kg
BW), performance was improved by ,3%. Fewer studies have
investigated the ergogenic effects of coffee, with results being
mixed thus far. In agreement with the literature, the current study
found an improvement in performance following caffeine intake of
4.9% and 4.5% when compared to decaf coffee and placebo,
respectively (Table 2). Interestingly, the current study also showed
that coffee improved performance to the same extent as caffeine
when compared to decaf coffee and placebo, 4.7% and 4.3%
respectively. Thus, this is the first study to date to demonstrate that
coffee consumed 1 h prior to exercise, at a high caffeine dose
(5 mg CAF/kg BW), is equally as effective as caffeine at improving
endurance exercise performance.
Our findings are in line with a number of studies that have
shown improvements to performance following coffee intake
[9,19–21]. Costill et al [9] were the first to show that decaf coffee
plus caffeine (330 mg), improved exercise time to exhaustion (80%
mance by 4.9% (95% confidence interval (CI) = 2.3–6.8%) and
4.5% (95% confidence interval (CI) = 2.3–6.2%) compared to PLA
and DECAF respectively (p,0.05 for both). Equally, COF
significantly improved TT performance by 4.7% (95% confidence
interval (CI) = 2.3–6.7%) and 4.3% (95% confidence interval
(CI) = 2.5–7.1%) compared to PLA and DECAF respectively
(p,0.05 for both) (Table 2). In addition there were no significant
differences in TT finishing time between CAF and COF
(P = 1.000) or PLA and DECAF (P = 1.000).
Following the completion of the TT, 3/8 participants were able
to successfully guess the correct order of test beverages consumed
prior to the trial. The correct guesses were more consistent for
detecting CAF compared to the other drinks, with 6/8 of the
participants guessing correctly. None of the participants reported
any serious symptoms of GI distress at the end of any of the trials.
Discussion
The present study examined the effects of acute intake of coffee
(5 mg CAF/kg BW) and caffeine (5 mg CAF/kg BW) on time trial
cycling performance, as well as substrate utilisation during SS
exercise. Numerous studies to date have shown the efficacy of
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Caffeine and Coffee on Exercise Performance
Figure 3. Plasma caffeine concentrations following ingestion of caffeine, coffee, decaf or placebo beverages. a CAF significantly
different to DECAF and PLA (p,0.001) b COF significantly different to DECAF and PLA (p,0.05). Data represented seen as Closed circles – Caffeine
Open circles – Caffeinated Coffee Closed triangles – Decaffeinated coffee Open triangles – Placebo Means 6 SE n = 7.
doi:10.1371/journal.pone.0059561.g003
Figure 4. Time trial finishing time (min) for caffeine, coffee, decaf or placebo beverages a CAF significantly different to DECAF and
PLA (p,0.05) b COF significantly different to DECAF and PLA (p,0.05). Data represented seen as Closed bar– Caffeine Open bar –
Caffeinated Coffee Dark grey bar– Decaffeinated coffee Light grey bar– Placebo. Means 6 SE n = 8.
doi:10.1371/journal.pone.0059561.g004
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Caffeine and Coffee on Exercise Performance
Table 2. Time trial performance data for each treatment.
Improvement compared to
PLA % (95% confidence
intervals)
P value
Improvement compared to DECAF
% (95% confidence intervals)
P value
CAF
38.3560.48
a
4.9 (2.326.8)
0.007
4.5 (2.326.2)
0.012
COF
38.2760.57b
4.7 (2.326.7)
0.010
4.3 (2.527.1)
0.012
DECAF
40.2360.63
20.4 (24.023.1)
1.000
-
-
PLA
40.0660.39
-
-
0.3(20.323.9)
1.000
Treatment
TT finish time (min)
Means 6 SE n = 8 a significantly different to DECAF and PLA (p,0.05) b significantly different to DECAF and PLA (p,0.05) Abbreviations: CAF Caffeine, COF Coffee,
DECAF Decaffeinated Coffee, PLA Placebo.
doi:10.1371/journal.pone.0059561.t002
bioavailability of plasma caffeine and paraxanthines did not differ
to caffeine [22], which is in line with the present study (Figure 4).
Further, in vitro studies suggest that chlorogenic acids antagonize
adenosine receptor binding of caffeine [27] and cause blunting to
heart rate and blood pressure in rats [28]. Yet, in vivo there is no
evidence to suggest that chlorogenic acids, especially at the low
nanomolar concentration typically observed [32], impact on the
mechanisms of action of caffeine that lead to the ergogenic effects.
In support of this notion, and in agreement with the current study,
regular coffee (1.1 mg/kg/BW) consumed prior to the ingestion of
different doses of caffeine (3–7 mg/kg/BW) has been shown not to
affect the ergogenic effects of caffeine [21].
The improvement in performance in the current study is
unlikely to be explained by alterations to fat oxidation, as no
difference during the SS exercise bout was observed (Figure 1B).
This is in agreement with a number of investigations that do not
support the thesis that caffeine improves exercise performance by
augmenting fat metabolism [33,34]. In addition these effects are
apparent despite consistent increases in adrenaline though
activation of the SNS [33,34] and a subsequent elevation in FA
appearance in the circulation following caffeine intake [33,34]. It
is evident that the improvement in performance is likely through
caffeine’s direct antagonism of adenosine receptors (A1 and A2A) on
the skeletal muscle membrane to improve excitation-contraction
coupling [13] via a greater release of Ca2+ from the SR [16] and/
or improved Na+/K+ ATPase pump activity [15]. In support of
this notion, Mohr et al [12] observed that tetrapelegic patients,
who have an impaired sympathoadrenal response [35], showed
that caffeine improved exercise performance, while RER did not
change during an electrical stimulated cycling test. Further, the
authors also observed a significant increase in FA and glycerol at
rest and during exercise following caffeine intake, despite a lack of
an adrenaline response. This is due to the fact that adenosine has
been shown to inhibit lipolysis [36] and enhance insulin stimulated
glucose uptake in contracting skeletal muscle in vitro [37]. In
support, the current studyobserved a significant increase in plasma
glucose, FA and glycerol concentrations following caffeine
(Figure 2 A, B, C). In addition, the consistently reported elevation
in adrenaline concentrations [33] combined with adenosine
receptor antagonism following caffeine intake during exercise
may work synergistically to activate glycogenolysis in exercising
and non-exercising tissues [34] as well as adipose tissue/skeletal
muscle lipolysis [33]. This supports the fact that the current study
(Figure 2 D) and others have shown that caffeine increase plasma
lactate concentrations at rest and during exercise [33,34]. Though
to date there is little supporting evidence that caffeine stimulates
exercising skeletal muscle glycogenolysis [33,38], with early studies
showing a paradoxical glycogen sparing effect with caffeine [2].
The elevated lactate concentrations are more likely due to a
VO2 max) compared with decaffeinated coffee (,18%). More
recently, Wiles et al [19] showed that coffee was able to improve
1500 m treadmill running performance when compared to
decaffeinated coffee (,3%). However, the current study results
are in contrast to a number of other studies [22–24]. For example,
the work conducted by Graham et al [22] showed that coffee
(4.5 mg CAF/kg BW), regardless of the format of intake (regular
coffee or decaffeinated coffee plus caffeine) did not result in an
improvement to running time to exhaustion (75% VO2 max),
where as caffeine (4.5 mg CAF/kg BW) significantly improved
performance. Therefore it was concluded by Graham et al [22]
that the performance effects of coffee may be inferior to caffeine.
Despite this evidence, the current study clearly demonstrates that
coffee is as effective as caffeine at improving endurance exercise
performance.
The discrepancy in the performance effects of caffeine and
coffee between the present study and Graham et al [22] might be
explained by the type of performance test implemented. Time to
exhaustion tests have been shown to be highly variable from day to
day, with a coefficient of variation (CV) ,27% in one study [18].
It is possible that this large variability may have contributed to the
lack of performance effects found by Graham et al [22]. Whereas
using a time trial performance measure, as used in the current
study, has previously been shown to be highly reproducible
(CV,3%) and could detect smaller differences in performance
[18]. Also the number of comparisons in the study by Graham et
al [22] was greater than in the present study with a similar subject
number, indicating that their statistical power was smaller.
Perhaps for these reasons, the current study was able to detect
similar changes in performance following caffeine and coffee
intake (,5%) (Table 2), whereas Graham et al [22] did not.
The composition and preparation of coffee in each of the studies
[9,19–24] may also explain the discrepancies in the ergogenic
effects of coffee. Coffee is ,2% caffeine, with the remainder
composed of chlorogenic acids, ferulic acid, caffeic acid, nicotinic
acid as well as other unidentifiable compounds [26]. It is evident
that the source of coffee beans, roasting, storage and preparation
(brewing and filtering) dramatically alters the caffeine and
chlorogenic acid content of the coffee [26]. In accordance, recent
evidence has shown that the chlorogenic acid content of
commercially available espresso coffees range from 24–422 mg/
serving [26]. In support, the current study observes a high
chlorogenic acid content in both coffee and decaffeinated coffee
samples (Table 1). Graham et al [22] speculated that chlorogenic
acids found in coffee may have blunted the physiological effects of
caffeine, preventing an improvement in exercise performance.
However the authors did not report measurements of chlorogenic
acids in coffee or in plasma to support this speculation. Despite the
compounds present in coffee, the authors reported that the
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Caffeine and Coffee on Exercise Performance
reduced clearance by the exercising muscle and a greater release
by non exercising tissues [33]. Consequently, due to the healthy
participants tested in the current study it is likely that the
adenosine receptor antagonism by caffeine plays a crucial role in
inducing the ergogenic effects of caffeine while regulating the
metabolite response synergistically with the SNS.
Interestingly, despite coffee producing similar ergogenic effects
as caffeine, the metabolite responses were not identical (Figure 2).
The current study observed that the significant increase in plasma
glucose, FA and glycerol with caffeine was paralleled with an
attenuated response for coffee, and a significantly blunted response
with decaf coffee when compared to placebo (Figure 2 A, B, C).
This is likely due to the compounds in coffee [39] inducing subtle
effects on antagonism of adenosine receptors (A1 and A2A) in a
variety of exercising and non exercising tissues. In accordance,
Graham et al [22] previously showed that coffee resulted in a
blunted adrenaline response when compared to caffeine at rest in
humans, which was attributed to chlorogenic acids antagonizing
adenosine receptor binding of caffeine [27]. In addition nicotinic
acid, a fatty acid ester found in coffee known to inhibit lipolysis,
has been shown to lower FA concentrations in patients suffering
from hyperlipidemia [40]. Chlorogenic acids are also believed to
improve glucose uptake at the skeletal muscle when compared to
caffeine [41], also by altering the antagonism of adenosine
receptors. More recently, caffeic acid has been found to stimulate
skeletal muscle glucose transport, independent of insulin, when
accompanied with an elevation in AMPK in vitro [42]. Despite the
aforementioned evidence, it remains unclear why compounds in
coffee appear to modulate the metabolite response but not the
ergogenic effects of coffee in the current study.
The current study provided a large bolus of caffeine in the form
of anhydrous caffeine or coffee one hour prior to exercise (5 mg/
kg BW). The chlorogenic acid content of the coffee beverages was
different, which is worth highlighting as a potential limitation of
the current study. Previous studies have failed to make comparisons between coffee and decaf coffee and instead have used decaf
plus anhydrous caffeine [9,19-21,23,43]. In addition these studies
did not examine the chlorogenic acid content of the test beverages.
Thus, the novelty of the current study was that the performance
effects were investigated between caffeine and coffee, independent
of the combined effects of decaffeinated coffee plus caffeine.
Adding a decaf plus caffeine trial would have been successful in
controlling for chlorogenic acid content of the beverage. However,
firstly, investigating the effect of chlorogenic acids on the metabolic
and performance effects of caffeine was not the primary aim of the
current study. Secondly, and more importantly, the low nanomolar concentration of chlorogenic acids in vivo [32] is unlikely to
impact on the mechanisms of action of caffeine when compared to
the physiological effects observed in vitro from supra physiological
concentrations of chlorogenic acids [27,28]. Yet, as differences in
the metabolic effects of caffeine compared to coffee were observed
in the current study, it may be important for future studies to
control for chlorogenic acid content in coffee beverages or
additionally increase the dose of chlorogenic acids to raise the
bioavailability in vivo. In turn this will provide further insights into
the metabolic differences between caffeine and coffee. In
conclusion, the present study showed that caffeine and coffee
(5 mg CAF/kg BW) were both able to improve exercise
performance to the same extent, when compared to both
decaffeinated coffee and placebo. Our data does not support the
notion that chlorogenic acids found in coffee impair the ergogenic
effects of caffeine. However, the compounds found in coffee may
alter the metabolic effects, as the current study observed
differences between caffeine and coffee at rest and during exercise.
It is yet to be determined if lower doses of caffeine, when ingested
as coffee, offer the same ergogenic effects. This would offer a more
applicable and realistic nutritional strategy for athletes.
Acknowledgments
The authors express appreciation to Dr Gareth Wallis for his input and
advice in the preparation of this paper.
Author Contributions
Critically reviewed the paper: ABH RKR AEJ. Conceived and designed
the experiments: ABH RKR AEJ. Performed the experiments: ABH RKR.
Analyzed the data: ABH AEJ. Wrote the paper: ABH AEJ.
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RESEARCH ARTICLE
Polyphenolic extract of InsP 5-ptase
expressing tomato plants reduce the
proliferation of MCF-7 breast cancer cells
Mohammad Alimohammadi1☯, Mohamed Hassen Lahiani1☯, Diamond McGehee1☯,
Mariya Khodakovskaya1,2*
a1111111111
a1111111111
a1111111111
a1111111111
a1111111111
1 Department of Biology, University of Arkansas at Little Rock, Little Rock, Arkansas, United States of
America, 2 Institute of Biology and Soil Sciences, Far-Eastern Branch of Russian Academy of Sciences,
Vladivostok, Russia
☯ These authors contributed equally to this work.
* mvkhodakovsk@ualr.edu
Abstract
OPEN ACCESS
Citation: Alimohammadi M, Lahiani MH, McGehee
D, Khodakovskaya M (2017) Polyphenolic extract
of InsP 5-ptase expressing tomato plants reduce
the proliferation of MCF-7 breast cancer cells.
PLoS ONE 12(4): e0175778. https://doi.org/
10.1371/journal.pone.0175778
Editor: Rajeev Samant, University of Alabama at
Birmingham, UNITED STATES
Received: October 30, 2016
Accepted: March 9, 2017
Published: April 27, 2017
Copyright: © 2017 Alimohammadi et al. This is an
open access article distributed under the terms of
the Creative Commons Attribution License, which
permits unrestricted use, distribution, and
reproduction in any medium, provided the original
author and source are credited.
In recent years, by extensive achievements in understanding the mechanisms and the pathways affected by cancer, the focus of cancer research is shifting from developing new chemotherapy methods to using natural compounds with therapeutic properties to reduce the
adverse effects of synthetic drugs on human health. We used fruit extracts from previously
generated human type I InsP 5-ptase gene expressing transgenic tomato plants for assessment of the anti-cancer activity of established genetically modified tomato lines. Cellular
assays (MTT, Fluorescent microscopy, Flow Cytometry analysis) were used to confirm that
InsP 5-ptase fruit extract was more effective for reducing the proliferation of breast cancer
cells compared to wild-type tomato fruit extract. Metabolome analysis of InsP 5-ptase
expressing tomato fruits performed by LC-MS identified tomato metabolites that may play a
key role in the increased anti-cancer activity observed for the transgenic fruits. Total transcriptome analysis of cancer cells (MCF-7 line) exposed to an extract of transgenic fruits
revealed a number of differently regulated genes in the cells treated with transgenic extract
compared to untreated cells or cells treated with wild-type tomato extract. Together, this
data demonstrate the potential role of the plant derived metabolites in suppressing cell viability of cancer cells and further prove the potential application of plant genetic engineering
in the cancer research and drug discovery.
Data Availability Statement: All relevant data are
within the manuscript and the Supporting
Information files.
Introduction
Funding: Authors are grateful to Arkansas Space
Grant Consortium for providing a stipend to
Diamond McGehee. This project was supported by
National Space Grant College Fellowship Program
(NNXISAR7H) through Research Infrastructure
Award provided by Arkansas Space Grant
Consortium (award to MK). The funders had no
role in study design, data collection and analysis,
Cancer is one of the leading causes of death in humans. Scientific advances in recent years and
the use of chemoprevention therapy has led to a significant reduction in death rates for different types of cancers [1–3]. Recently, natural compounds with cancer preventive properties
have been more widely used in cancer therapy [4]. Natural compounds with antioxidant activity can be categorized into three major groups: compounds that can directly inhibit cell proliferation, compounds that affect tissues outside the cancer cells, and immune-stimulating
compounds [5]. Epidemiological studies have shown a positive correlation between the long-
PLOS ONE | https://doi.org/10.1371/journal.pone.0175778 April 27, 2017
1 / 21
Polyphenolic extract of InsP 5-ptas tomato plants reduce the proliferation of cancer cells
decision to publish, or preparation of the
manuscript.
Competing interests: The authors have declared
that no competing interests exist.
term consumption of fruits and vegetables containing naturally occurring antioxidants with a
reduced risk of several types of cancer [6–10]. One of such naturally occurring antioxidants
are polyphenols that can be found in various amounts in many types of fruits and vegetables
[11–13]. They can be classified into two main groups according to their chemical structure: flavonoids and non-flavonoid compounds. These compounds are particularly valuable because
of their high antioxidant activity [14–16]. Several clinical studies indicate that dietary intake of
flavonoids and some other phenolic compounds such as caffeic acid and chlorogenic acid can
significantly reduce the risk of multiple types of cancer including breast, lung, prostate, and
pancreatic cancers [17–20]. Studies have also shown that the use of dietary phenolic compounds can have better preventive and therapeutic results compared to the common synthetic
drugs used for cancer treatment since these natural compounds demonstrate less toxicity compared to synthetic chemo-preventive medicines [21].
Dietary flavonoids and other important phenylpropanoids naturally exist in plants. A good
example of the commonly used crop plants with a high content of phenolic compounds is
tomato (Solanum lycopersicum) [22]. Consumption of tomato has preventive and therapeutic
effects on several types of diseases, including cancer [23]. The observed anti-cancer effects of
tomato are mainly related to the properties of phenolic compounds that allow them to bind to
or interact with a wide range of molecules, affect cell signaling processes, or even serve as a signaling molecule [24–27].
Several attempts have been made to improve the level of health promoting compounds in
tomato through conventional breeding techniques as well as genetic engineering tools [28,29].
We recently generated transgenic tomato lines with increased biosynthesis of antioxidants
such as lycopene, vitamin C and several flavonoids [30]. Particularly, the transgenic lines were
generated by overexpression of InsP 5-ptase gene which affects the phosphoinositol stress
signaling pathway through changes in the metabolism of InsP3, the key metabolite of the phosphoinositol pathway [31]. We also reported that the increase in metabolism of InsP3 in transgenic plants positively affects the biosynthesis of several flavonoids, such as chlorogenic acid
and rutin, by changing the expression level of the main components of the light-signaling
pathway that is linked to secondary metabolism in plants [32]. The observed increase in biosynthesis of phenolics and other secondary metabolites with antioxidant properties in InsP
5-ptase overexpressing transgenic plants suggest an increase in health beneficial properties of
these transgenic tomato plants. Despite the obvious potential of the genetically enhanced crop
plants with enhanced nutraceutical value, general concerns regarding consumption of food
products containing genetically modified (GM) ingredients significantly limits the use of GM
crops in medicine. In such circumstances, the extraction of desirable pharmaceuticals from
GM crops can serve as an alternative approach to the direct consumption of GM crops [33–
35]. These compounds can then be purified and used in medicine as drugs or supplements.
Here, we tested the anti-cancer activity of the total metabolite extract containing flavonoids
and other phenolic compounds from InsP 5-ptase expressing tomato fruits in vitro. Anti-proliferative effects of extracts obtained from transgenic fruits on breast cancer cell line (MCF-7)
were documented by a number of standard assays including cell viability assay, cell morphological analysis, and flow cytometry. Total transcriptome analysis of cancer cells treated with a
mix of metabolites extracted from InsP 5-ptase fruits suggested possible pathways involved in
anti-cancer effects of applied extracts. To identify metabolites that may play a role in the antiproliferative activity of InsP 5-ptase fruit extracts, we analyzed and compared extracts from
wild-type tomato fruits (control) and extracts from transgenic fruits using LC-MS as a powerful and modern metabolomics tool. LC-MS data confirmed the up-regulation of a number of
phenolic compounds with strong anti-proliferative potential in InsP 5-ptase fruit extracts. The
design of our study is shown in Fig 1.
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Materials and methods
Plant growth conditions
InsP 5-ptase tomato lines were generated and described in details in our previous publication
(30). Tomato (cv. Micro-Tom) seeds of control lines (wild-type, empty vector control, and transgenic lines (lines 6 and 7) were germinated in pots containing a combination of 75% Sun Gro
Redi-earth ‘Plug and Seedling’ Mix (Sun Gro Horticulture, Bellevue, WA) and 25% sand. The
seeds were germinated in a growth chamber under high-light conditions (800 μmol m-2 s-1) with
intervals of 16 h light (25˚C) and 8 h dark (22˚C). The red fruits were collected between 6 to 8
weeks of growth under controlled environment and exposure to high-light. The red tomato fruits
were immediately frozen in liquid nitrogen after harvest and stored at -80˚C or immediately
used in the experiment. For phenolic extraction, fruit samples were immediately lyophilized and
stored in the dark environment at room temperature before being used in the experiment.
Total phenolic compounds extraction and quantification
Total phenolics were extracted based on the method described by Ainsworth and Gillespie
(2007) [36]. The colorimetric assay works based on the transfer of electrons in alkaline
medium from phenolic compounds to phosphomolybdic/ phosphotungstic acid complexes. A
three step sequential aqueous/methanol extractions method was used to extract Polyphenols,
hydroxycinnamates, flavonoids, and their glycosides from lyophilized red tomato fruits. One
milliliter of the methanol/water (2:1) solution was mixed with 100 mg of each fruit sample
after which the samples were vortexed for 30 minutes. Next, the sample extracts were centrifuged at 10, 000 g for 5 minutes at 4˚C and the supernatant was collected. One milliliter of
fresh extraction solution was added to the pellet and the above extraction process was repeated
twice and at the end of each extraction, the supernatant was collected. It is important to protect
the samples from light throughout the extraction process. Folin-Ciocalteau micro method
as described by Slinkard et al. (1977) was used to measure the concentration of the phenolic
compounds in the extraction solution [37]. Twenty microliters of the tomato extract were
diluted in 1.58 ml of H2O and 100 μl of the Folin-Ciocalteau reagent was added to the solution.
The mixture was vortexed for 5 minutes after which 300 microliters of sodium carbonate solution (250 μg/ml) were added to the reaction, mixed and incubated for 30 minutes at 4˚C. Following the incubation period, absorbance was read at 765 nm against the blank. A galic acid
Fig 1. Overview of applied research strategy. Total metabolites of transgenic tomato fruits were analyzed for their potential anti-cancer properties by
application of the total metabolite mixture to MCF-7 cancer cells followed by cell viability assays and transcriptome analysis of the cancer cells. The total
tomato wild-type and transgenic fruit extracts were scanned for the potential metabolite with antioxidant and anti-cancer properties by using LC-MS.
https://doi.org/10.1371/journal.pone.0175778.g001
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calibration curve (0–1 g/L) was used as standard and the flavonoid concentrations were
expressed as galic acid equivalents.
Fruit tissue preparation for LC-MS analysis
Whole, intact tomatoes were pulverized using a mortar and pestle with liquid nitrogen to keep
tissue frozen. Approximately 20 mg of frozen tissue powder was then extracted using 80%
methanol by using a bead beater for each of the three technical replicates for each line. Samples
were then vortexed, sonicated, and centrifuged. The supernatant was filtered through 13 mm
syringe filters into microcentrifuge tubes and dried overnight in a 45˚C vacufuge. Samples
were then stored at -80˚C for future use. Extraction solution (80% methanol) was used to
reconstitute samples to equal volumes. Samples were vortexed and sonicated to ensure all residues had dissolved before they were centrifuged. The supernatant was transferred to a labeled
autosampler vial and analyzed immediately.
Chromatography and mass spectrometry
Samples were analyzed using a Grace C-18 (Grace Davison Discovery Sciences, USA) reverse
phase column on an Agilent 1100 series LCMS (Agilent Technologies, Waldbronn, Germany)
equipped with a G1379A degasser, G1312A binary pump, G1329A autosampler, G1316A column oven, G13158B diode array detector, and G2445C MS. The aqueous phase was acidified
HPLC-grade water (0.05% formic acid), and the organic phase was HPLC-grade methanol.
Ten microliter injections were pumped at 0.6 mL/min with the following elution gradient:
0–2 min, 5% B; 2–22 min, 75% B; 22–27 min, 75% B; 27–28 min, 5% B; 28–32 min. A fiveminute wash was included after each sample run. Negative-mode electrospray ionization was
used to detect the metabolites by utilizing a trap mass spectrometer scanning of 100–1500
m/z. The target was set at 10,000 and maximum accumulation time at 100.00 ms with two
averages. Chemstation software (http://www.agilent.com/en-us/products/software-informatics/
massspec-workstations/lc-ms-chemstation-software), provided with the Agilent machine used
to analyze samples and collect data was used to convert files to netCDF format. Further conversion to mzXML format was completed with msConvert (http://proteowizard.sourceforge.net/
tools.shtml) [38]. Files were then loaded into MZmine software (http://mzmine.github.io/) and
processed [39]. The Kyoto Encyclopedia of Genes and Genomes (KEGG) database, available at
http://www.genome.jp/kegg/tool/map_pathway1.html, was used for tentative online compound
identification and was completed through MZmine using the gap-filled peak list [40]. Further
statistical analysis was carried out by uploading the identified peak list to Metaboanalyst (http://
www.metaboanalyst.ca/) for analysis and by comparison to publications [41–43]. More information regarding data structure can be found in S4 Fig.
Cell culture conditions
MCF-7 breast cancer cells (ATCC) were seeded in T-75 culture flasks (Thermo Scientific) and
maintained in Dulbecco’s modified Eagle‘s medium (DMEM) media, supplemented with 10%
fetal bovine serum (FBS), 100 U/ml penicillin and 100 U/ml streptomycin. The culture plates
were maintained at 37˚C with 5% carbon dioxide. The medium was changed every two days,
and the cells were passaged at 80% confluency before the experiment.
MTT assay
Cells were divided into six groups: blank group (no cells), control group (no treatment) and
four experimental groups (WT, EV, L6 and L7 lines extract treatments). Cells were seeded in
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96-well plates 24 hours prior the experiment at the density of 104 cells/well. The next day, the
medium was changed and metabolite extract (34 μg/μl was supplemented to the fresh medium.
The cells were incubated 24 hours with the medium containing the metabolite extract. After the
incubation period, 3-(4,5-dim ethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide (MTT)
was then added to each well at the concentration of 5 mg/ml. The cells were incubated for 4
hours, after which the supernatant was replaced with 200 μL of dimethyl sulfoxide (DMSO).
The absorption was measured at 570 nm using a micro-plate reader. The results were presented
as OD 570–620 using the following formula: MTT OD 570–620 = (Mean A 570–560)—(Mean
A of Blank) / (Mean A Negative Control)—(Mean A of Blank). The results are based on two
independent experiment with each experiment consisting of 3 technical replicates.
Double immuno-staining and microscopy
MCF-7 were seeded into each well of Lab-Tek 2 chamber slide (Thermo Scientific Nunc. NY)
and incubated for 4 hours at 37˚C (5x105 cells in each chamber) in a humidified, 5% carbon
dioxide atmosphere to attach. Cells were divided into five groups: control group (no treatment) and four experimental groups (WT, EV, L6 and L7 lines extract treatments). Total
metabolite extract (34 μg/μl) was then added to fresh DMEM medium and applied to the wells
and incubated for 24 hours. After incubation, cells were washed once with phosphate buffer
saline (PBS) and stained with 1% Acridine orange/Ethidium bromide solution in PBS for 1
minute. Chambers were then washed two times with PBS after which slides were detached
from the chamber and air dried. Images were then taken by fluorescence microscopy. A Nikon
Eclipse 90i microscope equipped with a 12V-100W halogen lamp, external transformer, flyeye lens built-in and NCB11, ND8, ND32 filters, was used to visualize the stained samples. The
following Nikon filters were used: barrier filter BP365, reflector filter FT 395 and exciter filter
LP395. Live/dead cells were counted using Image J software. Live cells fluoresce green (FITC/
green) and dead cells fluoresce red/orange (Texas Red/red).
Flow cytometry analysis
Cells of MCF-7 breast cancer cell line were seeded in 6-well plates at a density of 5 x105 cells
per well and incubated for 24 hours at 37˚C in an incubator with 5% carbon dioxide to attach.
After the initial seeding, the cells were incubated with fresh medium containing 34 micrograms per microliters of extract and were incubated for 24 hours at 37˚C. Next day, cells were
trypsinized and collected in 2 ml tubes. Samples were centrifuged for 15 minutes at 1,300 rpm
at 37˚C. The supernatant was discarded and the cells were resuspended by addition of cold
PBS. Samples were briefly vortexed, transferred to Flow Cytometry tubes, and then placed on
ice. Components of YO-PRO kit (Life Technologies) were used for labeling the samples. One
sample was kept as a control (without label). One microliter of the YO-PRO -1 stock solution
(Component A) was added directly to the mixture in each tube followed by one microliter of
the propidium iodide (PI) stock solution (Component B). Labeled tubes were incubated on ice
for 30 minutes. Cells were analyzed by flow cytometry using BD LSRFortessa Cell Analyzer
(BD biosciences, CA) (to detect green (YO-PRO-1) and red (propidium iodide) signals.
Gene expression analysis using microarray (Affymetrix platform)
Breast cancer cell line MCF-7 cells were seeded in 6 well plates at a concentration of 106 cells/
well, 24 hours prior to the experiment. Afterwards, cells were washed two times with warm
media and were incubated for 24 hours with fresh medium containing tomato extracts from
different plant lines (WT, EV, L6, L7) at a concentration of 34 μg/μl. RNeasy Mini Kit (Qiagen
Sciences, Maryland, USA) was used to isolate RNA samples with modification of standard
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Qiagen protocol. Cells were disrupted briefly by using Trizol reagent (Ambion, Grand Island,
NY), and total RNA was extracted by using chloroform extraction method. After the RNA
purification, on-column DNA digestion using the RNase-free DNase Kit (Qiagen Inc. Valencia, CA) was used to remove the residual DNA. The purity of RNA samples was confirmed by
electrophoresis and the concentration was quantified by using Nanodrop spectrophotometer
(Thermo Scientific. Wilmington, DE). Affymetrix Human Genome Arrays were used as the
microarray platform. Biotinylated cRNA targets were synthesized by Affymetrix IVT Express
target labeling assay as specified in the Affymetrix GeneChip Expression Analysis Technical
Manual. Hybridization reactions to the Affymetrix Human GeneChips were carried out by
Expression Analysis, Inc. (Durham, NC).
Statistical analysis
The cell viability data were analyzed by Tukey’s test and expressed as mean ±S.D. by which
the significant differences (P value < 0.05) between groups were determined. To analyze the
microarray raw data, column-wise normalization using a reference sample (control)was
applied. The resulting data was then visualized using Multi Experiment viewer (Mev). The
data was further analyzed by ANOVA and Tukey test with a p-value of 0.001 while assuming
variance between variables are equal. The genes with significantly different expression were
clustered by hierarchical clustering. In addition, all the known and unknown genes with
changes in expression were functionally analyzed using the Database for Annotation, Visualization and Integrated Discovery (DAVID) v6.7 and PANTHER for gene classification. Microarray data were deposited in GEO database (GEO number: GSE94548).
Results
Effect of InsP 5-ptase overexpression in tomatoes on total phenolic
content in transgenic fruits
InsP 5-ptase overexpressing (two independent transgenic lines) and control (two control lines)
tomato fruits were tested for their total content of metabolites with phenolic nature. Results of
the experiment demonstrated that the fruits of transgenic tomato lines contain more phenolic
compounds (37% for L6, 50% for L7) compared to control lines (Fig 2). These results confirm
Fig 2. Total phenolic content in mature (red) InsP 5-ptase expressing and wild-type tomato fruits. (A) Standard curve using galic acid (0–1000
mg) as a standard reagent. (B) Total phenolic content in the mature tomato fruits of InsP 5-ptase transgenic lines (L6 and L7) and control lines (WT and
EV). The total phenolic content is expressed as mg/g galic acid equivalent. The different letters (a,b) means statistically different groups (p
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