Identification of Thyroid Receptor Ant/Agonists in Water
Sources Using Mass Balance Analysis and Monte Carlo
Simulation
Wei Shi1, Si Wei1, Xin-xin Hu1, Guan-jiu Hu2, Cu-lan Chen2, Xin-ru Wang3, John P. Giesy1,4,5,6,7, Hongxia Yu1*
1 State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, People’s Republic of China, 2 State
Environmental Protection Key Laboratory of Monitoring and Analysis for Organic Pollutants in Surface Water, Jiangsu Provincial Environmental Monitoring Center,
Nanjing, People’s Republic of China, 3 Key Laboratory of Reproductive Medicine and Institute of Toxicology, Nanjing Medical University, Nanjing, People’s Republic of
China, 4 Department of Veterinary Biomedical Sciences and Toxicology Centre, University of Saskatchewan, Saskatoon, Saskatchewan, Canada, 5 Department of Zoology,
and Center for Integrative Toxicology, Michigan State University, East Lansing, Michigan, United States of America, 6 Department of Biology and Chemistry and State Key
Laboratory in Marine Pollution, City University of Hong Kong, Kowloon, Hong Kong, SAR, China, 7 School of Biological Sciences, University of Hong Kong, Hong Kong, SAR,
China
Abstract
Some synthetic chemicals, which have been shown to disrupt thyroid hormone (TH) function, have been detected in surface
waters and people have the potential to be exposed through water-drinking. Here, the presence of thyroid-active chemicals
and their toxic potential in drinking water sources in Yangtze River Delta were investigated by use of instrumental analysis
combined with cell-based reporter gene assay. A novel approach was developed to use Monte Carlo simulation, for
evaluation of the potential risks of measured concentrations of TH agonists and antagonists and to determine the major
contributors to observed thyroid receptor (TR) antagonist potency. None of the extracts exhibited TR agonist potency, while
12 of 14 water samples exhibited TR antagonistic potency. The most probable observed antagonist equivalents ranged from
1.4 to 5.6 mg di-n-butyl phthalate (DNBP)/L, which posed potential risk in water sources. Based on Monte Carlo simulation
related mass balance analysis, DNBP accounted for 64.4% for the entire observed antagonist toxic unit in water sources,
while diisobutyl phthalate (DIBP), di-n-octyl phthalate (DNOP) and di-2-ethylhexyl phthalate (DEHP) also contributed. The
most probable observed equivalent and most probable relative potency (REP) derived from Monte Carlo simulation is useful
for potency comparison and responsible chemicals screening.
Citation: Shi W, Wei S, Hu X-x, Hu G-j, Chen C-l, et al. (2013) Identification of Thyroid Receptor Ant/Agonists in Water Sources Using Mass Balance Analysis and
Monte Carlo Simulation. PLoS ONE 8(10): e73883. doi:10.1371/journal.pone.0073883
Editor: Bin He, Baylor College of Medicine, United States of America
Received March 20, 2013; Accepted July 23, 2013; Published October 25, 2013
Copyright: ß 2013 Shi 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: This work was supported by the National Natural Science Foundation of China (21307054), the Science Foundation in Jiangsu Province (BK20130551),
the National High-tech R&D Program of China (2013AA062709), the Science Foundation in Jiangsu Province (BK2011032), the Major Science and Technology
Program for Water Pollution Control and Treatment (2012ZX07506-004-004) and the Program for Environmental Monitoring in Jiangsu Province (1212). Prof. Giesy
was supported by the program of 2012 ‘‘High Level Foreign Experts’’ (#GDW20123200120) funded by the State Administration of Foreign Experts Affairs, the P.R.
China to Nanjing University and the Einstein Professor Program of the Chinese Academy of Sciences. He was also supported by the Canada Research Chair
program, and a large Chair Professorship at the Department of Biology and Chemistry and State Key Laboratory in Marine Pollution, City University of Hong Kong.
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: yuhx@nju.edu.cn
biological and environmental screening to detect endocrine
disrupting effects. The green monkey kidney fibroblast (CV-1)
cell line based TH reporter gene assay is useful for predicting
effects of some thyroid hormone disrupting chemicals and/or
environmental samples [6]. In transient transformation assays, fold
induction could be quite large. The transient transformation assay
can also give more control over the specificity of response for
agonists and antagonists.
Thyroid hormone disrupting effects have been detected in
environmental samples including sediment extracts, indoor dust,
industrial effluents and even water sources [7,8]. Normal
treatment processes in sewage treatment plants, including filtration, coagulation, aerobic biodegradation and ozonation are not
considered to be effective for removal of endocrine disrupting
chemicals [7]. Little information is available for thyroid hormone
Introduction
Increasing attention has been given to contaminants that can
potentially interfere with the endocrine system [1]. Most research
has especially been focused on androgen and estrogen homeostasis, and less information is available regarding disruption of the
thyroid system [2]. Thyroid hormone (TH) is a key molecule
involved in normal development of the brain of higher vertebrates
and postembryonic development in lower vertebrates. Disruption
of TH homeostasis during development of the central nervous
system of children might cause neurological deficits and irreversible mental retardation [3]. Several synthetic chemicals from
agriculture and industry, such as plasticizers and pesticides, exert
toxic effects on the thyroid gland [4,5].
Reporter gene-based whole-cell assays, which have high
sensitivity and low background noise, have been widely used for
PLOS ONE | www.plosone.org
1
October 2013 | Volume 8 | Issue 10 | e73883
Thyroid Receptor Ant/Agonists Identification
source of drinking water, agriculture, aquaculture and industrial
plants [24,25]. The Huai River is a densely populated and
industrialized urban area in Chain, and serves more than 50
million people as source of drinking water [26,27]. Moreover,
more than 20% of the Yangtze River Delta population depends on
ground water for drinking water from either a public source or
private wells. The drinking water treatment processes including
coagulation, sedimentation, filtration and chlorination are commonly used. The advanced treatment processes, such as activated
carbon adsorption, ultra filtration membrane and magnetic ion
exchange resin, have also been adapted in these waterworks.
disrupting effects, although a range of thyroidal system inhibiting
chemicals such as pesticides have previously been detected in the
surface waters [9,10].
To simplify data interpretation and facilitate quantitative risk
assessment, the toxic potency of complex mixtures to modulate a
defined biological response is often expressed relative to that of a
well characterized standard chemical such as 5a-dihydrotestosterone (DHT) and flutamide for androgenic agonist and antagonist
effect, or 17-b-estradiol [E2] for effects of estrogen agonists [11].
Relative potency (REP) related to the receptor mediated potencies
is generally calculated as the ECi (i % relative inhibitory
concentration) of a well characterized standard divided by the
ECi of a sample or the tested chemicals, such that the ratio
describes the potency of the sample relative to the standard [12].
Relative potencies based on such a ratio of point estimates are
valid only under limited conditions [13]. It is assumed that doseresponse relationships for chemicals and the well characterized
standard are parallel. As a result, the REP of one chemical or
sample at different inhibitory concentrations exhibit equal efficacy.
However, there is little reason to assume that dose–response
relationships for the complex mixtures analyzed by the same in
vitro bioassay will be parallel or exhibit equal efficacy [14]. For
nonparallel dose–response relationships, the REP is a function of
dose or concentration factor. The relationship described at single
levels of response, such as the EC20, EC50 and EC80 are not
constant over the entire range of responses [15]. As a result the
REP ranges were recognized to identify the effects of environmental samples and tested chemicals to provide a quantitative
estimate of relative potency that is valuable for comparing among
samples [16]. Because REP ranges describe the uncertainty due to
nonparallel slopes, the standard range has been defined as 20 to
80% (REP20–80 range) of the maximum response achieved for the
standard compound (20–80% std. max.). The REP20–80 ranges are
valuable for comparing samples, however, they are not sufficient
for mass balance analysis considering about the uncertainty
induced. Moreover, the distributions of the REP values and the
most probable values were also ignored. Monte Carlo simulation
can be employed to further accommodate the uncertainties and
quantify variability [17]. Monte Carlo simulation is the most
commonly used method to quantify variability to accommodate
the uncertainties in risk assessments recommended by the National
Academy of Sciences and USEPA [18,19]. Through repetitive
calculations, a probability density function or cumulative density
function for the output can be generated [20,21]. This technique
could provide a quantitative way to estimate the probability
distributions for REPi within the validity of the assessment model.
Moreover, the most probable values can be estimated.
The three objectives of the study were to: 1) Build an assessment
technique based on Monte Carlo simulation to determine REP
ranges and chemicals responsible for the observed potency by use
of mass balance analysis; 2) Evaluate the TR antagonist potencies
in waters in the Yangtze River Delta; 3) Identify the compounds
responsible for thyroid-active potency of extracts using Monte
Carlo simulation based mass balance analysis.
Chemicals
According to our previous studies, phthalates and pyrethroids
which exhibited strong thyroid hormone disrupting activities were
selected [6,28]. The information of the chosen chemicals was
given in Table 1. All phthalate standards were 99.5% pure, and
pyrethroid standards were 99% pure. Internal standards, di-nbutyl phthalate-d4, bis(2-ethylhexyl)Phthalate-3,4,5,6-d4 and 13CPCB 141 were purchased from Sigma Chemical Co. (St. Louis,
MO, USA). Chemicals for bioassays including L-3,5,39-triiodothyronine (T3) and 3-(4,5-dimethylthiazol-2-ol)-2,5-diphenyltetrasodium bromide tetrazolium (MTT) with the purity of over 97%
were obtained from Sigma Chemical Co. (St. Louis, MO, USA).
The plasmid phRL-tk (used as internal control for transfection
efficiency), containing Renilla luciferase gene, was purchased from
Promega (Promega, Madison, WI, USA). No specific permissions
were required for these locations/activities and the field study did
not involve endangered or protected species.
Sample preparation and analysis
Fourteen water samples were collected from locations in the
Yangtze River Delta in May 2009 (Figure 1). Sampling locations
were from the Yangtze River (1-NT, 2-NT and 3-TZ), Tai Lake
(4-SZ, 5-SZ and 6-WX), Huai River (7-XZ, 8-YC, 9-YC, 10-YZ
and 11-LYG), and ground water (12-XZ, 13-XZ and 14-XZ). A
water sample of 15 L (10 L for bioassay and 5 L for chemical
analysis) were collected at each location. The water samples were
collect in water sources near the intake pipe of the drinking water
treatment plants.
Samples and procedure blanks (Milli-Q water) were extracted
by use of a modification of a previously published protocol [29,30].
Solid phase extraction (SPE, 500 mg Oasis HLB cartridges,
Waters, USA) was performed. Cartridges were activated and
conditioned with high-purity hexane (Merck), dichloromethane
(TEDIA), acetone (TEDIA) and methanol (TEDIA) sequentially.
Absorbed compounds were eluted stepwise with 10 mL hexane,
10 mL hexane: dichloromethane (4:1), followed by 10 mL
acetone: methanol (1:1). Extracts for bioassays were reconstituted
in DMSO and were diluted 12.5, 25, 50, 100, and 200 times the
original concentration in source water.
Plasticizers were quantified using a Thermo TSQ Quantum
Discovery triple-quadrupole mass spectrometer (San Jose, CA,
USA) in multiple-reaction monitoring (SRM) mode. The precision
of the method was quantified by relative standard deviation (SD),
and was determined by replicate extractions (n = 3) of a single
sample.
Materials and Methods
Study locations
Cell culture and transfection
Yangtze River, Tai Lake, Huai River and groundwater are
sources of drinking water in Yangtze River Delta region, which
include more than 30 water sources. The Yangtze River is the
most important source of drinking water to more than 50 million
residents in 8 large cities in the Yangtze River Delta [22,23]. Tai
Lake serves 3% of the population in China as an indispensable
PLOS ONE | www.plosone.org
A green monkey kidney fibroblast (CV-1) cell line lacking
functional TR was obtained from the Institute of Biochemistry and
Cell Biology in Shanghai, Chinese Academy of Science [31]. The
cell line was cultured in Dulbecco’s modified Eagle’s medium
(DMEM) (Sigma, St. Louis, MO, USA) supplemented with 10%
2
October 2013 | Volume 8 | Issue 10 | e73883
Thyroid Receptor Ant/Agonists Identification
Table 1. Sources, formula and CAS of tested chemicals.
Classes (Providers)
Name
CAS
Formula
Plasticizers (Labor Dr.Ehrenstorfer-Schafers, Germany)
Dibutyl phthalate (DNBP)
84-74-2
C16H22O4
di-2-ethylhexyl phthalate (DEHP)
117-81-7
C24H38O4
dimethyl phthalate (DMP)
131-11-3
C10H10O4
diethyl phthalate (DEP)
84-66-2
C12H14O4
benzyl butyl phthalate (BBP)
85-68-7
C19H20O4
bis(2-ethylhexyl) adipate (DEHA)
103-23-1
C22H42O4
diisobutyl phthalate (DIBP)
84-69-5
C16H22O4
di-n-octyl phthalate (DNOP)
117-84-0
C24H38O4
Cyfluthrin
68359-37-5
C22H18Cl2FNO3
Cypermethrin
52315-07-8
C22H19Cl2NO3
Deltamethrin
52918-63-5
C22H19Br2NO3
Dichloran
99-30-9
C6H4 Cl2 N2 O2
Fenvalerate
51630-58-1
C25H22CINO3
Pyrethroid Insecticides (Sigma Chemical Co., St. Louis, MO, USA)
L-Cyhalothrin
91465-08-6
C23H19ClF3NO3
Pendimethalin
40487-42-1
C13H19N3O4
Permethrin
52645-53-1
C21H20Cl2O3
Tefluthrin
79538-32-2
C17H14ClF7O2
Tetrachlorvinphos
7696-12-0
C19H25NO4
Cycloprothrin
63935-38-6
C26H21Cl2NO4
Cyhalothrin
91465-08-6
C23H19ClF3NO3
Etofenprox
80844-07-1
C25H28O3
doi:10.1371/journal.pone.0073883.t001
fetal bovine serum (FBS; Gibco, Invitrogen Corporation, Carlsbad, CA, USA), 100 U/mL penicillin (Sigma) and 100 mg/mL
streptomycin (Sigma) in an atmosphere containing 5% CO2 at
37uC. Cells were seeded in 48-well microplates at a density of
5.06104 cells per well. Twelve hours later, cells were transfected
with 0.25 mg Gal4 responsive luciferase reporter pUAS-tkluc,
Figure 1. Map of the chosen water sources from Yangtze River, Taihu Lake, Huaihe River and groundwater.
doi:10.1371/journal.pone.0073883.g001
PLOS ONE | www.plosone.org
3
October 2013 | Volume 8 | Issue 10 | e73883
Thyroid Receptor Ant/Agonists Identification
0.1 mg pGal4-L-TR using 2.5 mg Sofast TM transfection reagent
per well. The transfection efficiency of the transfection was
6564%. After further 12 h incubation, cells were exposed to
various concentrations of standard compounds and sample
extracts dissolved in medium for 24 h. Our previous study has
indicated that the relative potency for inducing luciferase activity
of natural thyroid hormone T3 is greater than T4 [32]. Moreover
T4 is prone to be metabolized and T3-dependent activation was
chosen to study thyroid hormone disrupting potencies in this study
(see Figure S1 in File S1) [33].
REPi ~
The TR agonistic and antagonistic equivalents were calculated
to measure the TH disrupting potencies and assess potential health
risks of the tested waters. The dose-response curves of tested
samples and chemicals were fitted to experimental data by use of a
three parameter sigmoid model (Eq. 1):
a-b
1z10(x-c)
ð1Þ
PrTH{EQi ~
where a, b and c are curve-fitting parameters of the model and x is
the concentration.
For antagonist potencies, all the effect are compared with the
control level of the agonist and this level should be comparable in
analogous biochemical processes. For example, 5.061029 mol
T3/L were always employed as control in the ant-thyroid hormone
effect detecting assays and this level could also be defined as std.
max (100%). Di-n-butyl phthalate (DNBP) was chosen as the well
characterized standard for the TR antagonist potency in this study
[34].
The observed equivalent (ObTH-EQ) for environmental
samples were derived from the concentration factor at which the
ECi (i% relative inhibitory concentration, inhibition by i%) of
sample was obtained based on the following equation and reflected
the bioassay results (Eq 2).
ObTH{EQi ~
ECi of standard chemical
Sample dilution factor at inhibition i%
to maximum ObTH EQ
X
Contaminanti concentration(c)|ReP{pro ð5Þ
Data analysis
Values were reported as mean 6 SD (n = 3). In the bioassays
triplicate wells were done for each treatment. For agonistic
potencies, treatments were compared to the vehicle control; while
for antagonistic potencies, treatments were compared to
5.061029 mol/L T3 positive control groups respectively. Data
were analyzed by use of one-way ANOVA, followed by Duncan’s
multiple comparisons test when appropriate using SPSS statistical
software (version 11, SPSS Inc., Chicago, Illinois). Curve-fitting
analysis was carried out with GraphPad 5.4 (San Diego, CA,
USA). The level of significance was set at ** p,0.01. To
accommodate the uncertainties associated within the REP and
equivalent calculation process due to the use of point concentration data, Monte Carlo simulation technique was applied in this
study. The fitted distribution functions of the inhibition data were
used as simulated data sets. The next, 10000 Monte Carlo
iterations were performed based on the @Risk software (5.7
version, Palisade Corporation, Newfield, NY, USA). A probabilistic distribution of REP for standard and equivalent for mixture
instead of the point values, were then generated as calculation
results.
ð2Þ
In most cases, the dose-response relationships for sample
extracts or model chemical are not parallel, and the ObTH-EQi
is not a single point but a range (Eq. 3). The range is calculated
based on Monte Carlo simulation using the algorithm @ Risk (5.7
version, Palisade Corporation, Newfield, NY, USA). At the same
time, the maximum, minimum, mean value and distribution of
ObTH-EQi were obtained. ObTH-EQi is the equivalent determined at a defined probability level as Yi. The ObTH-EQpro is
defined as the ObTH-EQ with the highest probability level.
ObTH EQ range~minimum ObTH EQ
ð4Þ
In most cases, dose-response relationships for different chemicals are not parallel, and the REPi is also not a single point. This
REPi of a chemical could be arbitrarily defined as the REP20 or
REP50 as well as a range which is not sufficient for mass balance
analysis. The most appropriate REPi was defined as a function of
concentration.
Predicted EQs represented estimates of sample toxicity based on
measured chemical concentrations in environmental samples
based on equation 4. Concentration addition was used for mixture
toxicity estimation. Predicted EQ (PrTH-EQi) was calculated by
multiplying the contaminant concentration in water (c) by the
most probable REP (REP-pro) values of the related chemical
detected based on Monte Carlo simulation.
Toxic equivalents estimation for antagonist potencies
Inhibition(i%)~bz
ECi of standard chemical
ECi of tested chemical
Results and Discussion
Cell viability and system creditability
None of the individual chemicals or extracts affected viability or
proliferation of CV-1 cells alone or in the presence of
5.061029 mol T3/L. No cytotoxic effects of solvent or water
extracts were observed by microscopic examination throughout
the transfection assay. The natural TR ligand T3 induced
luciferase activity in a concentration-dependent manner in the
CV-1 reporter assay ranging from 1.0610210 mol/L to
1.061026 mol/L. No significant induction of luciferase was
observed in any of the solvent controls (data not shown).
Recoveries of chemicals in instrumental analysis were between
82% and 110% (see Table S1 in File S1).
ð3Þ
The relative potency (REP) for chemicals could be derived from
the concentrations at which the ECi (i% relative inhibitory
concentration, inhibition by i%) of sample was obtained based on
the following equation and reflected the bioassay results (Eq. 4).
TR ant/agonist potency
None of the tested extracts displayed any TR agonistic potency.
However, twelve of the fourteen tested source water extracts
PLOS ONE | www.plosone.org
4
October 2013 | Volume 8 | Issue 10 | e73883
Thyroid Receptor Ant/Agonists Identification
Figure 2. Concentration-dependent TR antagonist activities in the water extracts measured by the CV-1 cell line TR reporter gene
assay. Water extracts were tested at 25, 50, 100 and 200 times the original concentration. Cells were exposed to extracts in parallel with 5 nmol T3 as
indicated by the dashed line. The TR antagonist activity was expressed as relative expression versus the untreated cells with 5 nmol T3 (control)
(mean 6 SD). Significant differences were indicated by asterisks (** p,0.01). The results of statistical analysis at higher concentrations which also
exhibited significant differences (**p,0.01) were not shown.
doi:10.1371/journal.pone.0073883.g002
1.26104 ng/L and 4.06101 to 2.16103 ng/L, respectively.
Pyrethroid insecticides were detected in none of the samples.
Great concentrations of DIBP were also detected. This is in
accordance with previous studies regarding the concentrations of
phthalate esters in water, soil and dust sample in China
[35,36,37,38]. The results indicated the common use of DIBP in
the Yangtze River Delta. Concentrations of DEHP were less than
DNBP or DIBP, which is consistent with the results of previous
studies in China [35]. Concentrations of DNBP, DEHA, DEP and
deltamethrin in waters were less than the national standard for tap
water in China, which are 8, 300 and 20 mg/L, respectively [39].
However, there is no standard for concentrations of DIBP in
source water. Concentrations of phthalate esters in Tai Lake were
greater than those in most of the other samples. This result
indicated that in more urbanized areas, infiltration of treated or
exhibited TR antagonistic potencies in a concentration-dependent
manner (Figure 2). All the water extracts from Tai Lake, the
Yangtze River and Huai River displayed TR antagonist potency.
The two extracts which exhibited no antagonist potency were both
from ground water. Extracts of all the surface water with the
maximal concentration factors (200 times the original concentration in the source water) decreased luciferase expressions to less
than 40% of 5 nmol/L T3 potency, respectively.
Concentrations of TR antagonist
Individual concentrations of phthalate esters, and pyrethroid
insecticides in source water were shown (Table 2). Phthalate esters
were detectable in all samples analyzed except DNOP at location
1-NT. Concentrations of DNBP, DIBP and DEHP were the
highest, ranging from 2.16101 to 3.26103 ng/L, 1.96102 to
Table 2. Concentrations of thyroid hormone disrupting compounds (ng/L) in water sources.
Chemicals
Locations
1-NT
2-NT
3-TZ
4-SZ
5-SZ
1.9610
DNBP
1.3610
3
BBP
1.76102 3.16102 9.46101 1.16101
1.56101 1.46100 4.56101 3.56101 5.36102 2.96101 4.76101
1.36101 2.56101 1.16101
DEHA
2.06102 3.36101 4.06102 2.861021
2.26100 5.46103 7.26102 5.46100 2.36102 2.26101 5.96102
1.06100 3.86100 7.26100
DEHP
9.2610
2
4
2
3
3
2
3
12-XZ 13-XZ 14-XZ
3
1
1
10-YZ 11-LYG
3.8610
DIBP
0
9-YC
1
DEP
2
8-YC
2.7610
DMP
1
6-WX 7-XZ
0
4.1610 2.0610 7.4610
4.2610 3.7610 1.1610
1.2610 1.9610 3.6610
1.4610 2.1610 2.1610
3
3
1
2
3
1
1.8610 2.1610 5.5610
1
1
1
1
1
1
1
5.46101 7.06101 1.96101
2
1
1
1
1
1
2
3.76100 7.56101 1.96101
3
3
3
3
3
3
3
1.96102 3.06102 2.66103
3
3
3
2
3
3
3
1.46102 2.06101 1.36103
8.0610 3.1610 7.5610 1.9610 4.8610 2.8610 2.4610
1.2610 4.5610 9.0610 2.9610 7.4610 4.1610 1.2610
4.4610 1.7610 2.1610 1.8610 2.1610 2.1610 3.2610
1.7610 1.1610 1.4610 9.0610 1.2610 1.4610 3.2610
2
1
1
2
2
2
2
4.06101 1.66102 1.86102
1
2
2
1
2
1
2
2.16101 2.86102 2.76101
7.3610 4.5610 8.6610 1.3610 4.5610 1.7610 2.8610
DNOP
N.D
1.0610 3.6610 1.2610
1.7610 2.2610 2.7610 3.0610 5.7610 6.4610 5.4610
SPyrethroid Insecticides
N.D
N.D
N.D
N.D
N.D
N.D
N.D
N.D
N.D
N.D
N.D
N.D
N.D
N.D
N.D: not detectable, ,LOD.
doi:10.1371/journal.pone.0073883.t002
PLOS ONE | www.plosone.org
5
October 2013 | Volume 8 | Issue 10 | e73883
Thyroid Receptor Ant/Agonists Identification
Figure 3. The probability density distributions of relative potency (REP) for the detected phthalate esters (mmol tested
chemical?L21/mmol DNBP?L21).
doi:10.1371/journal.pone.0073883.g003
esters except DEHA exhibited measurable TR antagonistic
potencies. The probability density distributions of REP (mmol
tested chemical?L21/mmol DNBP?L21) for phthalate esters were
developed based on Monte Carlo simulation (Figure 3). Most of
the values distributed closely to the maximal values. The maximal
REP (MAX), mean REP (MEAN) and the most probable REP
(REP-pro) were similar. The REP ranges (mmol tested chemical?L21/mmol DNBP?L21) for the detected chemicals are shown
in Figure 4. DNOP exhibited the greatest REP ranges while BBP
exhibited the least REP ranges. The REP values for the other
phthalate esters were similar. The dose-response curves for REP
untreated sewage maybe the source of pollution in Tai Lake.
Phthalate esters were also detectable in all three ground water,
with the greatest concentration found in 14-XZ, and thus may
potentially serve as a precautionary indicator of ground water
contamination.
Toxic equivalents
TR antagonistic potencies of detected phthalate esters were
evaluated by use of reporter gene assay and the dose-response
curves were fitted to these experimental data by use of the threeparameter, sigmoid model (see Table S2 in File S1). All phthalate
PLOS ONE | www.plosone.org
6
October 2013 | Volume 8 | Issue 10 | e73883
Thyroid Receptor Ant/Agonists Identification
Figure 4. Relative potency (REP) ranges for the detected phthalate esters (mmol tested chemical?L21/mmol DNBP?L21).
doi:10.1371/journal.pone.0073883.g004
was defined as the most probable REP was used to predict the
PrTH-EQ of the samples at the greatest probability (Table 3). The
REP-pro derived PrTH-EQ (PrTH-EQ-pro) for the water sources
ranged from 1.861021 to 4.0 mg/DNBP L, with the greatest
concentration of TH equivalents found at location 11-LYG from
the Huai River (Table 3).
The probability density distributions of ObTH-EQs were
developed based on Monte Carlo simulation (see Figure S3 in
File S1). The ObTH-EQs of the detected water sources were
equivalent. The minimum values ranged from 6.99610212 to
2.58610210 mmol DNBP/L. The maximal values (MIN) ranged
from 5.1361026 to 2.9561025 mmol DNBP/L. The mean values
were similar to or equivalent to the most probable values (see
Figure S4 in File S1), with the greatest values occurring at location
11-LYG. The most probable ObTH-EQs (ObTH-EQs–pro) for
the water sources ranged from 8.361021 to 5.6 mg DNBP/L
(Table 3).
When the amounts of ObTH-EQs measured by the bioassay
were compared with those calculated from the concentrations of
detected TR antagonists (PrTH-EQ) based on the REP-pro, more
than 55.8% of the total ObTH-EQs in water sources were
contributed by detected phthalate esters (Figure 5). With the
greatest concentration and greatest TR antagonist potency, DNBP
accounted for most of the ObTH-EQs in most locations. DIBP,
DNOP and DEHP accounted for 1.2% to 35.9%, 0 to 36.5%,
0.4% to 16.2% of the ObTH-EQs, respectively. Contributions of
DIBP and DNOP were relatively great, a result that has not been
reported previously. This can be attributed to use of DIBP and
DNOP in the Yangtze River Delta, which is consistent with results
of previous studies conducted in Guangdong, China [35]. DNBP is
the major TR antagonist potency in water sources at all the
detected sites, while DIBP, DNOP and DEHP also contributed.
Standards established in July, 2012 for drinking water quality have
added 71 monitoring objectives. However, DIBP and DNOP were
not included. Less than 50% of the potencies were contributed by
the detected chemicals for sample from Yangtze River. This
indicated that unknown chemicals contributed most of the TR
antagonist potency in groundwater. These thyroid-disrupting
chemicals in source water could be a major concern if drinking
water treatment does not remove these compounds. Previous
studies have indicated that phthalate could be efficiently removed
by macroporous OH-type strongly basic anion exchange resin [40]
and inhibition of the detected chemicals are shown in Figure S2 in
File S1, and totally different shapes of curves were observed for
these phthalate esters. According to these dose-response curves
inhibition ranges for the REP-pro were obtained (see Table S2 in
File S1). The result indicated that the most probable inhibition
ranges were from 75% to 93%, but not 50%. However, EC50 has
always been employed in previous studies to determine REPs of
chemicals, which might have resulted in underestimation or
overestimation because of non-parallelism of the dose-response
curves [16]. Inhibition ranges were quite different for the various
chemicals and REP-pro was employed to evaluate the effect of the
related chemical. Previous studies have indicated that the REP
ranges are not suitable for mass balance analysis, because the
range is not a settled number. In this study, the REP-pro which
Table 3. The most probable observed equivalent (ObTH-EQ–
pro) derived from reporter gene assays and the most
probable predicted equivalent (PrTH-EQ-pro) derived from
instrumental analysis (mg/DNBP L).
ObTH-EQ–pro
PrTH-EQ-pro
1-NT
2.26100
1.46100
2-NT
2.86100
2.66100
3-TZ
1.4610
0
8.261021
2.8610
0
2.46100
2.8610
0
2.26100
2.2610
0
1.46100
8.3610
21
1.96100
1.4610
0
1.16100
1.4610
0
2.06100
4-SZ
5-SZ
6-WX
7-XZ
8-YC
9-YC
10-YZ
8.361021
1.76100
11-LYG
5.66100
4.06100
12-XZ
N.E
1.861021
13-XZ
N.E
14-XZ
2.8610
3.261021
0
1.56100
N.E: No effect was observed.
doi:10.1371/journal.pone.0073883.t003
PLOS ONE | www.plosone.org
7
October 2013 | Volume 8 | Issue 10 | e73883
Thyroid Receptor Ant/Agonists Identification
Figure 5. Contributions of individual chemicals to the ObTH-EQs in water samples.
doi:10.1371/journal.pone.0073883.g005
and modified activated carbon [41]. However limited information
is available for the removal efficiency of other advanced treatment
processes combined with the commonly used process for more
thyroid-disrupting chemicals. Further study is needed to evaluate
the associated removal efficiency in water works, which could be
benefit the risk assessment for human health.
Dose-response curves for complex mixtures and standard
chemicals analyzed by in vitro bioassay will not be parallel or
exhibit equal efficacy to the standard [42,43]. As a result, REP
ranges including 20% inhibition, 50% inhibition and 80%
inhibition were recommended for toxicity identification. However,
REP ranges have been considered unsuitable for mass balance
analysis. Choice of an appropriate model to describe a concentration–response curve is often arbitrary, so when the estimation
technique involves extrapolation beyond the range of observed
data the results could be misleading. In such cases, REP ranges,
especially the 50% inhibition and 80% inhibition will not be
estimated exactly. In this study, a new approach was developed
based on Monte Carlo simulation for the estimation of REP and
equivalent for standard and mixture for the very first time. Using
this approach, REP values for the standard and the equivalent
values for the mixture can be calculated rapidly for thousands of
points along the standardized range of response, and the
maximum, mean, minimum and most probable values could be
generated. The most probable observed equivalent concentration
derived from reporter gene assays and the most probable REP for
detected chemicals could further be combined for the mass
balance analysis. This method could provide REP ranges and
equivalent ranges for comparison of risk potential posed by
different standard or mixture and also for responsible chemicals
searching. This could avoid inaccurate estimates of risk, due to the
limitation of the relative studies. The most probable observed
equivalent and most probable REP derived from Monte Carlo
simulation are not only suitable for comparative purposes but also
improve the accuracy of mass balance analysis.
PLOS ONE | www.plosone.org
Conclusion
In conclusion, a novel approach was developed based on Monte
Carlo simulation for the estimation of relative potency (REP) and
thyroid hormone (TH) equivalents for standard compounds and
mixtures. Using this approach, REP values for the model
compound standards and concentrations of equivalents for
mixtures can be rapidly calculated and thousands of points along
the standardized range of response, and the maximum, mean,
minimum and most probable values were generated. The most
probable observed equivalent derived from reporter gene assays
and the most probable REP for detected chemicals could further
be combined for use in a mass balance analysis. This method could
provide REP ranges and equivalent ranges for comparison of risk
potential posed by different standard or mixture and also for
responsible chemicals searching. Using this approach the presence
of thyroid active chemicals and their toxicity potential in the most
commonly used drinking water sources in the Yangtze River Delta
was investigated. None of the water extract exhibited thyroid
receptor (TR) agonist activity, but the occurrences of strong
antagonist activities were more common in all the commonly used
water sources except ground water. DNBP, DIBP, DNOP and
DEHP contributed most for the observed antagonist toxic unit.
More attention should be paid to these chemicals for the further
management consideration. The most probable observed equivalent and most probable REP derived from Monte Carlo
simulation are not only suitable for comparative purposes but
also the estimate for risk assessment or mass balance analysis.
Supporting Information
File S1
Supporting information.
(DOC)
Author Contributions
Conceived and designed the experiments: WS SW HXY. Performed the
experiments: WS XXH. Analyzed the data: WS GJH CLC. Contributed
reagents/materials/analysis tools: WS SW XRW. Wrote the paper: WS
JG.
8
October 2013 | Volume 8 | Issue 10 | e73883
Thyroid Receptor Ant/Agonists Identification
References
1. Colborn T, Saal FSV, Soto AM (1993) Developmental effects of endocrinedisrupting chemicals in wildlife and humans. Environ Health Perspect 101: 378–
384.
2. Jugan ML, Oziol L, Bimbot M, Huteau V, Tamisier-Karolak S, et al. (2009) In
vitro assessment of thyroid and estrogenic endocrine disruptors in wastewater
treatment plants, rivers and drinking water supplies in the greater Paris area
(France). Sci Total Environ 407: 3579–3587.
3. Howdeshell KL (2002) A model of the development of the brain as a construct of
the thyroid system. Environ Health Perspect 110: 337–348.
4. Brucker-Davis F (1998) Effects of environmental synthetic chemicals on thyroid
function. Thyroid 8: 827–856.
5. Darnerud PO, Lignell S, Glynn A, Aune M, Tornkvist A, et al. (2010) POP
levels in breast milk and maternal serum and thyroid hormone levels in motherchild pairs from Uppsala, Sweden. Environ Int 36: 180–187.
6. Du G, Shen O, Sun H, Fei J, Lu C, et al. (2010) Assessing hormone receptor
activities of pyrethroid insecticides and their metabolites in reporter gene assays.
Toxicol Sci 116: 58–66.
7. Li N, Wang D, Zhou Y, Ma M, Li J, et al. (2010) Dibutyl phthalate contributes
to the thyroid receptor antagonistic activity in drinking water processes. Environ
Sci Technol 44: 6863–6868.
8. Suzuki G, Takigami H, Watanabe M, Takahashi S, Nose K, et al. (2008)
Identification of brominated and chlorinated phenols as potential thyroiddisrupting compounds in indoor dusts. Environ Sci Technol 42: 1794–1800.
9. Wu B, Zhang X, Zhang X, Yasun A, Zhang Y, et al. (2009) Semi-volatile
organic compounds and trace elements in the Yangtze River source of drinking
water. Ecotoxicology 18: 707–714.
10. Qu CS, Chen W, Bi J, Huang L, Li FY (2011) Ecological risk assessment of
pesticide residues in Taihu Lake wetland, China. Ecol Model 222: 287–292.
11. Luo J, Lei B, Ma M, Zha J, Wang Z (2011) Identification of estrogen receptor
agonists in sediments from Wenyu River, Beijing, China. Water Res 45: 3908–
3914.
12. Villeneuve D, Kannan K, Khim J, Falandysz J, Nikiforov V, et al. (2000)
Relative potencies of individual polychlorinated naphthalenes to induce dioxinlike responses in fish and mammalian in vitro bioassays. Arch Environ Contam
Toxicol 39: 273–281.
13. Blankenship AL, Kannan K, Villalobos SA, Villeneuve DL, Falandysz J, et al.
(2000) Relative potencies of individual polychlorinated naphthalenes and
Halowax mixtures to induce Ah receptor-mediated responses. Environ Sci
Technol 34: 3153–3158.
14. Putzrath RM (1997) Estimating relative potency for receptor-mediated toxicity:
reevaluating the toxicity equivalence factor (TEF) model. Regul Toxicol
Pharmacol 25: 68–78.
15. Machala M, Ciganek M, Blaha L, Minksova K, Vondrack J (2001) Aryl
hydrocarbon receptor-mediated and estrogenic activities of oxygenated
polycyclic aromatic hydrocarbons and azaarenes originally identified in extracts
of river sediments. Environ Toxicol Chem 20: 2736–2743.
16. Villeneuve DL, Blankenship AL, Giesy JP (2000) Derivation and application of
relative potency estimates based on in vitro bioassay results. Environ Toxicol
Chem 19: 2835–2843.
17. Hoefling M, Lima N, Haenni D, Seidel CA, Schuler B, et al. (2011) Structural
heterogeneity and quantitative FRET efficiency distributions of polyprolines
through a hybrid atomistic simulation and Monte Carlo approach. PLoS One 6:
e19791.
18. USEPA (1997) Guiding Principles for Monte Carlo Analysis. Washington, DC, ,
USA
19. National Research Council (1994) NRC Science and judgment in risk
assessment. Washington, DC, , USA
20. Jang CS, Liu CW, Lin KH, Huang FM, Wang SW (2006) Spatial analysis of
potential carcinogenic risks associated with ingesting arsenic in aquacultural
tilapia (Oreochromis mossambicus) in blackfoot disease hyperendemic areas.
Environ Sci Technol 40: 1707–1713.
21. Qu C, Sun K, Wang S, Huang L, Bi J (2012) Monte carlo simulation-based
health risk assessment of heavy metal soil pollution: A case study in the Qixia
mining area, China. Hum Ecol Risk Assess 18: 733–750.
22. Shen M, Yu Y, Zheng GJ, Yu H, Lam PKS, et al. (2006) Polychlorinated
biphenyls and polybrominated diphenyl ethers in surface sediments from the
Yangtze River Delta. Mar Pollut Bull 52: 1299–1304.
PLOS ONE | www.plosone.org
23. Sun C, Dong Y, Xu S, Yao S, Dai J, et al. (2002) Trace analysis of dissolved
polychlorinated organic compounds in the water of the Yangtse River (Nanjing,
China). Environ Pollut 117: 9–14.
24. Song L, Chen W, Peng L, Wan N, Gan N, et al. (2007) Distribution and
bioaccumulation of microcystins in water columns: A systematic investigation
into the environmental fate and the risks associated with microcystins in
Meiliang Bay, Lake Taihu. Water Res 41: 2853–2864.
25. Qiao M, Chen YY, Zhang QH, Huang SB, Ma M, et al. (2006) Identification of
Ah receptor agonists in sediment of Meiliang Bay, Taihu Lake, China. Environ
Sci Technol 40: 1415–1419.
26. Wang B, Yu G, Huang J, Yu Y, Hu H, et al. (2009) Tiered aquatic ecological
risk assessment of organochlorine pesticides and their mixture in Jiangsu reach of
Huaihe River, China. Environ Monit Assess 157: 29–42.
27. Ma F, Wan Y, Yuan G, Meng L, Dong Z, et al. (2012) Occurrence and source of
nitrosamines and secondary amines in groundwater and its adjacent Jialu River
basin, China. Environ Sci Technol 46: 3236–3243.
28. Shen O, Du G, Sun H, Wu W, Jiang Y, et al. (2009) Comparison of in vitro
hormone activities of selected phthalates using reporter gene assays. Toxicol Lett
191: 9–14.
29. Koh CH, Khim JS, Villeneuve DL, Kannan K, Johnson BG, et al. (2005)
Instrumental and bioanalytical measures of dioxin-like and estrogenic compounds and activities associated with sediment from the Korean coast.
Ecotoxicol Environ Saf 61: 366–379.
30. Hladik ML, Kuivila KM (2009) Assessing the occurrence and distribution of
pyrethroids in water and suspended sediments. J Agric Food Chem 57: 9079–
9085.
31. Davis PJ, Shih A, Lin HY, Martino LJ, Davis FB (2000) Thyroxine promotes
association of mitogen-activated protein kinase and nuclear thyroid hormone
receptor (TR) and causes serine phosphorylation of TR. J Biol Chem 275:
38032–38039.
32. Sun H, Shen OX, Wang XR, Zhou L, Zhen S, et al. (2009) Anti-thyroid
hormone activity of bisphenol A, tetrabromobisphenol A and tetrachlorobisphenol A in an improved reporter gene assay. Toxicol In Vitro 23: 950–954.
33. Vijayan M, Flett P, Leatherland J (1988) Effect of cortisol on the in vitro hepatic
conversion of thyroxine to triiodothyronine in brook charr (Salvelinus fontinalis
Mitchill). Gen Comp Endocrinol 70: 312–318.
34. Shi W, Hu X, Zhang F, Hu G, Hao Y, et al. (2012) Occurrence of thyroid
hormone activities in drinking water from eastern china: contributions of
phthalate esters. Environ Sci Technol 46: 1811–1818.
35. Zeng F, Cui K, Xie Z, Liu M, Li Y, et al. (2008) Occurrence of phthalate esters
in water and sediment of urban lakes in a subtropical city, Guangzhou, South
China. Environ Int 34: 372–380.
36. Guo Y, Kannan K (2011) Comparative assessment of human exposure to
phthalate esters from house dust in China and the United States. Environ Sci
Technol 45: 3788–3794.
37. Zeng F, Cui K, Xie Z, Wu L, Liu M, et al. (2008) Phthalate esters (PAEs):
Emerging organic contaminants in agricultural soils in peri-urban areas around
Guangzhou, China. Environ Pollut 156: 425–434.
38. Zeng F, Cui K, Xie Z, Wu L, Luo D, et al. (2009) Distribution of phthalate esters
in urban soils of subtropical city, Guangzhou, China. J Hazard Mater 164:
1171–1178.
39. Ministry of Health of the People’s Republic of China. http://www.moh.gov.cn/
publicfiles/business/cmsresources/zwgkzt/wsbz/new/20070628143525.pdf
(accessed July 1, 2007).
40. Xu Z, Zhang W, Lv L, Pan B, Lan P, et al. (2010) A new approach to catalytic
degradation of dimethyl phthlate by a macroporous OH-type strongly basic
anion exchange resin. Environ Sci Technol 44: 3130–3135.
41. Adhoum N, Monser L (2004) Removal of phthalate on modified activated
carbon: application to the treatment of industrial wastewater. Sep Purif Technol
38: 233–239.
42. Ghisari M, Bonefeld-Jorgensen EC (2005) Impact of environmental chemicals
on the thyroid hormone function in pituitary rat GH3 cells. Mol Cell Endocrinol
244: 31–41.
43. Finney DJ (1978) Developmental effects of endocrine-disrupting chemicals in
wildlife and humans. Statistical Method in Biological Assay Charles Griffin and
Company, London, UK.
9
October 2013 | Volume 8 | Issue 10 | e73883
Identification of thyroid receptor ant/agonists in water sources using mass
balance analysis and Monte Carlo simulation
Wei Shi1, Si Wei1, Xin-xin Hu1, Guan-jiu Hu2, Cu-lan Chen2, Xin-ru Wang3,
John P. Giesy1, 4, 5, 6, 7, Hong-xia Yu1*
1
State Key Laboratory of Pollution Control and Resource Reuse, School of the
Environment, Nanjing University, Nanjing, People’s Republic of China
2
State Environmental Protection Key Laboratory of Monitoring and Analysis for
Organic Pollutants in Surface Water, Jiangsu Provincial Environmental Monitoring
Center, Nanjing, People’s Republic of China
3
Key Laboratory of Reproductive Medicine & Institute of Toxicology, Nanjing
Medical University, Nanjing, People’s Republic of China
4
Department of Veterinary Biomedical Sciences and Toxicology Centre, University
of Saskatchewan, Saskatoon, Saskatchewan, Canada
5
Department of Zoology, and Center for Integrative Toxicology, Michigan State
University, East Lansing, MI, USA
6
Department of Biology & Chemistry and State Key Laboratory in Marine Pollution,
City University of Hong Kong, Kowloon, Hong Kong, SAR, China
7
School of Biological Sciences, University of Hong Kong, Hong Kong, SAR, China
Address correspondence to H. Yu.
Prof. Hongxia Yu, PhD: School of the Environment, Nanjing University, Nanjing,
210093, China. Tel.: +86 25 8968 0356, Fax: +86 25 8968 0356, E-mail:
yuhx@nju.edu.cn
Supporting Information, Table S1. The recovery, limit of quantification (LOQ) and
limit of detection (LOD) of the chemicals for instrumental analysis.
Recovery RSD
LOD
LOQ
Chemicals
Plasticizers
(%)
(%)
(ng/L)
(ng/L)
DMP
94
3.3
4.3×10-1
1.3×100
DEP
84
1.3
4.3×10-1
1.3×100
DIBP
89
6.7
1.0×10-1 3.0×10-1
DNBP
97
4.2
6.7×10-1
2.0×100
BBP
89
3.2
4.3×10-1
1.3×100
DEHA
110
5.4
3.3×10-1
1.0×100
DEHP
94
9.6
1.0×10-1 3.0×10-1
DNOP
89
3.7
2.3×10-1 7.0×10-1
Dichloran
88
8.8
5.0×10-2 1.8×10-1
Tefluthrin
90
3.6
6.0×10-2 1.9×10-1
Pendimethalin
91
1.3
6.0×10-2 1.9×10-1
Tetrachlorvinphos
95
2.0
2.5×10-1 8.2×10-1
L-Cyhalothrin
90
3.0
2.0×10-2 6.0×10-2
Permethrin1
82
3.6
2.0×10-2 6.0×10-2
Permethrin2
93
1.3
1.1×10-1 3.7×10-1
89
6.3
7.0×10-2 2.3×10-1
88
6.9
7.0×10-2 2.2×10-1
Fenvalerate1
93
2.7
4.0×10-2 1.3×10-1
Fenvalerate2
84
3.6
4.0×10-2 1.4×10-1
Pyrethroid
pesticides
Cyfluthrin
isomers
Cypermethrin
isomers
Deltamethrin
93
6.5
4.0×10-2 1.3×10-1
Cycloprothrin
87
2.4
2.0×10-2 6.0×10-2
Cyhalothrin
91
3.1
2.0×10-2 6.0×10-2
Etofenprox
86
2.2
2.0×10-2 6.0×10-2
LODs: Limits of detection (S/N =3); LOQs: Limits of quantitation (S/N =10);
Concentrations are expressed as mean ± SD (n=3)
Supporting Information, Table S2. The parameter for dose-response curves, the
most probable REP (REP-pro) (μmol tested chemical·L-1/μmol DNBP·L-1)and the
inhibition ranges of the phthalate esters.
Chemicals
a
REP-pro
inhibition
(probability)
ranges
0.033 (15.5%)
90.8%-91.6%
-5.61
0.12 (23.5%)
89.9%-91.6%
0.8811 -4.792
0.086 (7.4%)
88.2%-88.8%
b
c
DMP
1.013
DEP
0.9991 0.7972
DIBP
1.007
DNBP
0.9562 0.4653 -5.656
1
/
DNOP
0.9993 0.5228 -5.646
0.64 (21.2%)
74.9%-79.9%
1.006
0.8815 -4.797
0.005 (33.0%)
91.3%-92.6%
0.9987 0.7058 -5.112
0.077 (11.0%)
85.0%-87.4%
BBP
DEHP
0.8561 -5.437
Supporting Information, Figure S1. Concentration-dependent luciferase activities in
CV-1 cell line TR reporter gene assay treated with T3. Results are expressed as mean
Relative luciferase activity
(n-fold of control)
± SD (n = 3).
T3
100
50
0
-11
-10
-9
-8
-7
log concentration (M)
-6
-5
Supporting Information, Figure S2. The dose-response curves for relative potency
0.1
DEHP
-1
-1
REP(μmol•L /μmol•L )
(REP, μmol•L-1/μmol•L-1) and inhibition of the detected chemicals (μg DNBP/L).
0.08
0.06
0.04
0.02
0
0.6
0.65
0.7
0.75
0.8
0.85
0.9
0.95
1
Relative luciferase activity
(n-fold of 5 nmol T3)
-1
-1
REP(μmol•L /μmol•L )
DMP
0.04
0.03
0.02
0.01
0
0.84
0.86
0.88
0.9
0.92
0.94
0.96
0.98
-1
-1
REP(μmol•L /μmol•L )
Relative luciferase activity
(n-fold of 5 nmol T3)
0.7
DNOP
0.6
0.5
0.4
0.3
0.2
0.1
0
0.4
0.5
0.6
0.7
Relative luciferase activity
(n-fold of 5 nmol T3)
0.8
0.9
1
-1
-1
REP(μmol•L /μmol•L )
0.14
0.12
0.1
0.08
0.06
0.04
0.02
-1
-1
REP(μmol•L /μmol•L )
0
0.78
-1
-1
REP(μmol•L /μmol•L )
DEP
0.1
0.8
0.82
0.84
0.86
0.88
0.9
Relative luciferase activity
(n-fold of 5 nmol T3)
0.92
0.94
0.96
0.98
DIBP
0.08
0.06
0.04
0.02
0
0.87
0.006
0.88
0.89
0.9
0.93
0.91
0.92
Relative luciferase activity
(n-fold of 5 nmol T3)
0.94
0.95
0.96
BBP
0.005
0.004
0.003
0.002
0.001
0
0.87
0.88
0.89
0.9
0.91
0.92
0.93
Relative luciferase activity
(n-fold of 5 nmol T3)
0.94
0.95
0.96
Supporting Information, Figure S3.
Probability density distributions of observed
equivalent (ObTH-EQ) for the detected samples (μg DNBP/L).
Supporting Information, Figure S4. Observed equivalent (ObTH-EQ) ranges for the
source water samples.
MIN
ObTH-EQs–pro
MAX
MEAN
1.E-04
ObTH-EQ (μg DNBP/L)
1.E-05
1.E-06
1.E-07
1.E-08
1.E-09
1.E-10
1.E-11
1.E-12
1.E-13
1.E-14
1-NT
2-NT
3-TZ
4-SZ
5-SZ
6-WX
Locations
7-XZ
8-YC
9-YC
10-YZ
11-LYG
14-XZ
MATERIALS AND METHODS
Sampling Preparation. Because these water sources are considered to be the safest
water body in the contemporary conditions, studies of toxic chemicals in water
sources are essential for management and control of priority chemicals in this most
developed area in China [1]. No specific permissions were required for the chosen
locations/activities and the field study did not involve endangered or protected
species.
These waters are considered the most important sources and each provides more
than 400 thousand m3 drinking water per day.
A general population size for each
water source is about 500 thousand people.
Composite water samples were collected at each location and placed into brown
glass bottles, which were pre-cleaned with nitric acid and chromic acid solution, and
then rinsed with high-purity hexane (Merck), dichloromethane (TEDIA), acetone
(TEDIA) and methanol (TEDIA). Bottles were also washed 3 times with water
samples before sample collection. Samples were transported on ice and stored at 4 °C
and extracted within 24 h. Samples were transported and stored at 4 °C and extracted
within 24 h. Solid phase extraction (SPE, 500 mg Oasis HLB cartridges, Waters, USA)
was performed under vacuum at a flow rate of 6-8 mL/min without filtration.
Approximately 2 L of sample was passed through each cartridge to avoid over
filtration and was dried completely under a gentle stream of nitrogen gas (>99.9%
pure). SPE extracts were combined and dehydrated with anhydrous sodium sulfate
and reduced to dryness under a gentle nitrogen flow and reconstituted in 0.1 mL
dichloromethane for quantification. Samples used for bioassays were reconstituted in
0.2 mL of dimethyl sulfoxide (DMSO). Extracts were stored at −20 °C. The external
standard consisted of Mili-Q water spiked with each target analyte to determine the
recoveries of the detected compounds. The internal standards di-n-butyl phthalate-d4,
bis(2-ethylhexyl)Phthalate-3,4,5,6-d4 and
13
C-PCB 141 were added to the tested
extracts before instrumental analysis for quality control of phthalate esters, and
pesticides. A signal-to-noise ratio of 3 was used as the criteria for the analytical limit
of detection (LOD).
Compounds for bioassays were dissolved in dimethylsulfoxide (DMSO, BDH
Laboratory Supplies, UK) and then diluted with the appropriate culture medium
before use to give less than 0.5% (v/v) solvent.
MTT Cytotoxicity Test. The 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium
bromide (MTT) assay was performed in parallel with the luciferase induction assays,
according to the protocol described previously. Briefly, CV-1 cells were plated in
96-well plates using DMEM with 10% dextran-coated charcoal (DCC) serum with the
density of 1×104 cells/100 μL. After 24 h incubation, CV-1 cells were treated with
vehicle, extracts and standards alone or with 5.0×10−9 mol/L T3 for 24 h. Then
3-(4,5-dimethylthiazol-2-yl)-2,5- diphenyltetrazolium bromide was added to each
well. Absorbance was measured with a microplate reader (EL808, Bio-Tek, Winooski,
VT, USA) at 570 nm.
Reporter Gene Assay. Reporter gene assays were conducted according to previous
methods with some modification [2]. Cells were plated into 48-well culture plates at a
density of 5.0×104 cells per well in phenol red free DMEM medium containing 10%
bCDS-FBS. After 12 h, cells were transfected with 0.25 μg Gal4-responsive luciferase
reporter pUAS-tkluc, 0.1μg pGal4-L-TR which was an expression vector coding for
the ligand binding domain (LBD) of TRβ fused to the DNA binding domain of Gal4,
using 2.5 μg Sofast TM transfection reagent per well. After an additional 12 h of
incubation, the transfection medium was removed and the cells were exposed to
various concentrations of extracts for 24 h. To determine agonistic activity, CV-1 cells
were treated with various concentrations of chemicals. For determining antagonistic
activity, CV-1 cells were exposed to various concentrations of tested chemicals in the
presence of 5×10-9 mol/L T3. DMSO concentrations in wells never exceed 0.5% (v/v).
The transfection efficiency was 42%. For both agonists and antagonists, luciferase
activities of treatment groups were compared to that of the corresponding vehicle
control.
Data Analysis. The concentration of standard chemical which caused the same
response as the greatest concentration tested (200 times the original concentration)
was divided by the enrichment factor 200. In the bioassays, triplicate wells were
dosed for each treatment. And the variations between the parallel cells were very
small. All the inter-assay standard deviations for the luciferase activities (n-fold of 5
nmol T3) were less than 0.02. We repeated the experiments for at least 3 times to
make stable and believable results and the related data sets were used for the Monte
Carlo simulation.
RESULTS AND DISCUSSION
TR Agonist Activity. Phthalate esters exhibited week potencies as agonist.
REFERENCES:
1. Shi W, Zhang F-X, Hu G-J, Hao Y-Q, Zhang X-W, et al. (2012) Thyroid hormone
disrupting activities associated with phthalate esters in water sources from
Yangtze River Delta. Environ Int 42: 117-123.
2. Sun H, Shen O-X, Wang X-R, Zhou L, Zhen S-q, et al. (2009) Anti-thyroid
hormone
activity
of
bisphenol
A,
tetrabromobisphenol
A
and
tetrachlorobisphenol A in an improved reporter gene assay. Toxicol In Vitro 23:
950-954.