publications - shodhgangashodhganga.inflibnet.ac.in/bitstream/10603/33892/10/publication.pdf ·...

PUBLICATIONS

Please purchase PDF Split-Merge on www.verypdf.com to remove this watermark.

List of Publications

316 | P a g e

PAPERS PUBLISHED IN INTERNATIONAL JOURNALS

Satyanarayanan Senthil Kumaran, Chokkalingam Kavitha, Mathan Ramesh,

Tamara Grummt (2011). Toxicity studies of nonylphenol and octylphenol:

Hormonal, hematological and biochemical effects in Clarias gariepinus. Journal of

Applied Toxicology. 31: 752–761. Impact Factor: 2.322

Xiaowei Jin, Jinmiao Zha, Yiping Xu, Zijian Wang, Satyanarayanan Senthil

Kumaran (2011). Derivation of Aquatic predicted no effect concentration (PNEC)

for 2,4-dichlorophenol: Comparing native species data with non-native species data.

Chemosphere. 84(10): 1506-1511. Impact Factor: 3.155

Jiang Weiwei, Yan Ye, Ma Mei, Wang Donghong, Luo Qian, Wang Zijian,

Satyanarayanan Senthil Kumaran (2012). Assessment of source water

contamination by estrogenic disrupting compounds in China. Journal of

Environmental Sciences. 24(2) 1–10. Impact Factor: 1.513

Jiang Weiwei, Yan Ye, Li Na, Ma Mei, Wang Donghong, Rao Kaifeng, Wang

Zijian, Satyanarayanan Senthil Kumaran (2012). Retinoid X receptor activities of

source waters in China and their removal efficiencies of drinking water treatment

processes. Chinese Science Bulletin. 57(6): 595-600. Impact Factor: 1.087

Chokkalingam Kavitha, Satyanarayanan Senthil Kumaran, Audhi Lakshmi

Srinivasan, Mathan Ramesh (2011). Toxicity of Moringa oleifera seed extract on

some hematological and biochemical profiles in a freshwater fish, Cyprinus carpio.

Experimental and Toxicologic Pathology. Article in press (ETP-50598). Impact

Factor: 2.283

Li Na, Ma Mei, Wang Zijian, Satyanarayanan Senthil Kumaran (2011). In vitro

assay for human thyroid hormone receptor β agonist and antagonist effects of

individual polychlorinated naphthalenes and Halowax mixtures. Chinese Science

Bulletin, 56(1): 1-6. Impact Factor: 1.087

Na Li, Weiwei Jiang, Kaifeng Rao, Mei Ma, Zijian Wang, Satyanarayanan Senthil

Kumaran (2011). Estrogen-related receptor γ (ERRγ) disrupting activities in the

source water and drinking water treatment processes. Journal of Environmental

Science, 23(2): 301-306. Impact Factor: 1.513


List of Publications

317 | P a g e

Zhong WenJue , Wang DongHong, Xu XiaoWei, Wang BingYi,, Luo Qian, Senthil

Kumaran Satyanarayanan, Wang Zijian (2011). A gas chromatography/mass

spectrometry method for the simultaneous analysis of 50 phenols in wastewater

using deconvolution technology. Chinese science bulletin, 56 (3): 275–284. Impact

Factor: 1.087

Chokkalingam Kavitha, Annamalai Malarvizhi, Satyanarayanan Senthil

Kumaran, Mathan Ramesh (2010). Toxicological effects of arsenate exposure on

hematological, biochemical and liver transaminases activity in an Indian major carp,

Catla catla. Food and Chemical Toxicology, 48: 2848–2854. Impact Factor: 2.602

Mathan Ramesh, Sathyanarayanan Senthil Kumaran, Chokkalingam Kavitha,

Manoharan Saravanan and Ahmed Mustafa (2007). Primary stress responses of

common carp Cyprinus carpio exposed to copper toxicity. Acta Ichthyologica Et

Piscatoria. 37 (2): 81–85. Impact Factor: 0.490


Toxicity studies of nonylphenol andoctylphenol: hormonal, hematological andbiochemical effects in Clarias gariepinusSatyanarayanan Senthil Kumaran,a Chokkalingam Kavitha,a

Mathan Ramesha* and Tamara Grummtb

ABSTRACT: Among the numerous chemicals discharged into aquatic ecosystems, nonylphenol (NP) and octylphenol (OP)have been shown to have a potent effect on the endocrine system of fish; this issue has been clearly dealt with in severalstudies. The objective of this study was to assess and compare the general toxicity of these estrogenic chemicals individuallyon Clarias gariepinus. Fish were exposed to different concentrations of both NP and OP (250, 500, 750 and 1000 μg l−1) undersemi‐static conditions for a period of 7 days. The adverse effect was evaluated with use of blood cell counting, hemoglobin(Hb), hematocrit (HCT), hematimetric indices, bilirubin, protein, glucose, serum transaminases, serum phosphatases, lactatedehydrogenase and cortisol. The results showed a clear indication of anemia, increases in leukocyte count and bilirubincontent and a reduction in plasma protein levels with higher concentrations of both the toxicants compared with controls.Furthermore, with all the concentrations the inevitable increase in serum cortisol and plasma glucose showed primary andsecondary stress responses. Moreover, probable tissue damage gave rise to a series of fluctuations of enzyme levels at lowerconcentrations, but a decrease with higher concentrations showed the severity of the effect. Depending on the parametersexamined, OP had a relatively greater effect than NP. Overall, these two chemicals seemingly affected hematology and theactivity of some enzymes, leading to serious impairment of the metabolism and physiology of C. gariepinus. Copyright ©2011 John Wiley & Sons, Ltd.

Keywords: nonylphenol; octylphenol; Clarias gariepinus; hematology; biochemical profiles

INTRODUCTIONThere is growing concern worldwide, especially in developingcountries, about a group of xenobiotics, the surface activeagents, e.g. alkylphenols and alkylphenol polyethoxylates, theindiscriminate use and discharge of which result in environ-mental pollution. Alkylphenol ethoxylates (APEs) are non‐ionicsurfactants used as intermediates or as additives (emulsifiers,detergents and flotation and dispersing agents) for a wide rangeof industrial products and processes (Saito et al., 2004; Guentheret al., 2006). Their worldwide production is about 600 kt peryear, comprising 6.5% of the total surfactant (not includingsoaps) production in the world (data 2003) as reported by CESIO(http://www.cefic.be/cesio), with an estimated 60% of thisproduction ending up in water bodies around the world(Bennie, 1999; Barse et al., 2006). The pollution of the aquaticenvironment caused by the discharge of non‐ionic surfaceactive substances such as alkylphenols (APs) and theirbiodegradation products nonylphenol (NP) and octylphenol(OP) has attracted the attention of scientists due to theirestrogenic and toxic effects on living organisms. NP and OP arewidely found in surface waters at concentrations ranging fromnanograms to milligrams per liter (Bennie, 1999). NPs areemployed in lubricant oil, cosmetics, emulsifiers, plastics, latexpaints, household and industrial detergents, and paper andtextile industries (TemaNord, 1996). OPs are used as tackifiers intire rubber, in recovery of oil in offshore processes, and in

printing inks, pesticide formulations (as a dispersant), water‐based paints, textile auxiliaries, and emulsion polymerizationprocesses (Nimrod and Benson, 1996). NP is by far the mostcommercially prevalent member of the AP family, representingapproximately 85% of the total AP market with the remaining15% being octylphenol ethoxylates (Naylor, 1992).

The sources of both NP and OP are not natural; therefore,environmental concentrations result from anthropogenic activityonly. These are generally discharged in large quantities toaquatic environments either directly from untreated effluent orindirectly from sewage treatment plants (Maguire, 1999). Thesecompounds are known to be persistent toxic chemicals. The AP,4‐tert‐octylphenol is found in the environment at levels aboutone order of magnitude lower than the levels of 4‐ nonylphenol(Bennie, 1999). Pollution of water bodies not only impacts thewater adversely but also the organisms living in it. Among those

*Correspondence to: M. Ramesh, Unit of Toxicology, Department of Zoology,School of Life Sciences, Bharathiar University, Coimbatore‐641046, Tamil Nadu,India.E-mail: [email protected]

aUnit of Toxicology, Department of Zoology, School of Life Sciences, BharathiarUniversity, Coimbatore‐641046, Tamil Nadu, India

bGerman Federal Environmental Agency, Bad Elster Branch, Heinrich‐Heine‐Str.12, D‐08645, Bad Elster, Germany

J. Appl. Toxicol. 2011; 31: 752–761 Copyright © 2011 John Wiley & Sons, Ltd.

Research Article

Received: 4 August 2010, Revised: 8 October 2010, Accepted: 19 October 2010 Published online in Wiley Online Library: 15 March 2011

(wileyonlinelibrary.com) DOI 10.1002/jat.1629

752


organisms, fish play an important role in the monitoring ofaquatic pollution because they respond with great sensitivity tochanges in their environment (Van der Oost et al., 2003). Theharmful effects of NP and OP have been determined using bothfish and invertebrate models, and it has been reported that bothchemicals have toxic effects even at low concentrations, with theseverity of the effects depending on the sensitivity of the species(Schwaiger et al., 2000). It is well known that NP is a potentialEDC, but recently the Japanese government announced thatoctylphenol can also act as an endocrine disruptor, especially infish (http://www.env.go.jp/press). Recent studies on individual orcumulative effects of NP and OP have mostly demonstrated andfocused on their potential to exert estrogenic effects on aquaticanimals but not of their general toxicity.

It is well documented that many chemical contaminantstarget fish biology leading to an alteration in their physiologicalmechanisms. Toxicity biomarkers are recognized as measurablemodifications at the molecular, biochemical, cellular, physiolog-ical or behavioral levels, revealing the exposure of an organismto xenobiotics and risk assessment processes (Van der Oost et al.,2003). Blood parameters are considered to be pathophysiolo-gical indicators of the whole body and are therefore importantin diagnosing the structural and functional status of fish exposedto toxicants and medicaments (Adhikari et al., 2004). It is wellknown and accepted that excessive environmental stress causesa variety of detectable, recognizable changes in blood andtissues of the fish. This is the reason behind the increased use offish blood as a prominent parameter in toxicological research.Biochemical constituents such as serum total bilirubin, glucose,protein and certain enzymes have been explored as potentialbiomarkers as they are more sensitive, less variable, more highlyconserved between species and often easy to measure as stressindices (Agrahari et al., 2007; Kavitha et al., 2010) and to detectand document xenobiotics released into fish environments(Jeney et al., 1992).

The serum transaminases [aspartate aminotransferase (AST)and alanine aminotransferase (ALT)], phosphatases [alkalinephosphatase (ALP) and acid phosphatase (ACP)] as well aslactate dehydrogenase (LDH) are enzymes (entering the bloodafter the cell necrosis of certain organs) which are veryfrequently used in the diagnosis of damage in life forms causedby pollutants (De la Torre et al., 1999). Chronic or acute exposure toxenobiotics has been shown to adversely affect hypothalamus–pituitary–inter‐renal axis (HPI) and its related parameters, amongthem the role of cortisol (Hontela, 1997), is widely known(Wendelaar Bonga, 1997). Stress‐induced elevation of plasmacortisol concentration is commonly used as an indicator of theprimary stress response in fish (Wendelaar Bonga, 1997; Pottinger,1998). Otherwise, there are few reports focused on thesebiomarker profiles by these multifaceted compounds (NP andOP) in aquatic organisms, especially on fish.

To overcome the lacuna, the present study was undertaken tostudy the individual effects of the compounds (NP and OP) andcompare their toxic effects with the use of some prominentbiomarkers, including hematological data (hematocrit, hemo-globin content, blood cell count and erythrocytic indices),biochemical variables (bilirubin, protein and glucose), tissuedamage enzyme activities (AST, ALT, ALP, ACP and LDH) andstress response (cortisol) in the African catfish (Clarias gariepinus),species of the Clariidae family that has been well studiedowing to its importance in both fisheries and fish culture inAfrica and Asia.

MATERIALS AND METHODS

Chemicals

Technical‐grade NP (CAS no. 84852‐15‐3), OP (CAS no. 140‐66‐9)and most of the other chemicals used in this study werepurchased from Sigma–Aldrich (USA).

Animals and Acclimatization

C. gariepinus (50±2.5 g) of both sexes with an average length of24.5±1.6 cm were purchased from a local commercial fish farm,Coimbatore, Tamil Nadu, India. They were acclimatized tolaboratory conditions for a period of 15 days in a plastic fibertank (2000 l) supplied with dechlorinated water (ground source).The water quality parameters as an average during the studyperiod were: pH, 6.9±0.5; dissolved oxygen, 8.45±0.07 mg l−1;total hardness, 98±3.2 mg l−1 as CaCO3; total alkalinity, 145±2.4 mg l−1 as CaCO3; chlorides, 32.65±0.42 mg l−1; and salinity,0.30±0.01 ppt (APHA‐AWWA‐WPCF, 1998). A natural photoperiod(14:10 light:dark) with an ambient temperature of 26±1.5 °Cwere maintained throughout. Since C. gariepinus is an air‐breather, there was no necessity to aerate the setup. During the15‐day acclimatization period and the experimental period(7 days) the fish were fed once a day with boiled and mincedchicken liver. Nearly three‐quarters of the water, along with theexcreta, were replaced daily to maintain a healthy environment.

Experimental Procedures

Determination of 96‐h LC50 value

Prior to performing 96 h static renewal acute toxicity tests (LC50,96 h), preliminary range‐finding tests (data not shown) wereconducted for both chemicals (APHA/AWWA/WPCF, 1998).Based upon the data obtained, 10 randomly selected fish wereexposed to different concentrations of NP and OP in each glassaquaria containing 200 l water (three replicates), and also threecontrol and solvent control groups for each concentration wererun. Fish were not fed during this period. Mortality wasmonitored daily and dead fish were removed immediately.The LC50 and 95% confidence intervals for each test wascalculated using Probit Program Version 1.5 (USEPA, 1990).

Sub‐chronic exposure

Two experimental setups were maintained for this study, i.e. forNP and OP, with two controls (without solvent and with solvent)common for both the toxicants. For each toxicant, the studysetup was divided into four groups (T1–T4), with about 10 fish toeach group in fiberglass tanks of 100 l capacity. The experimentswere conducted under semi‐static conditions. The test concen-trations were prepared by dissolving NP and OP in appropriateamount of acetone. The volume of acetone was kept equal in alltreatment groups and the solvent control group. The treatmentgroups (T1–T4) received concentrations of 250, 500, 750 and1000 μg l−1 of NP and OP. The test solutions in each fiberglasstank were renewed every 24 h to maintain the chemical. Areplicate trial was performed for each NP and OP concentration.Behavioral changes were noted.

Blood sampling and analytical procedure

After the stipulated period of 7 days, five fish from each groupwere randomly selected and anesthetized to bring down the stress

Effect of nonylphenol and octylphenol on Clarias gariepinus

J. Appl. Toxicol. 2011; 31: 752–761 Copyright © 2011 John Wiley & Sons, Ltd. wileyonlinelibrary.com/journal/jat

753


due to handling using tricaine methanesulfonate (0.4 g l−1) withsodium bicarbonate as buffer (0.8 g l−1). Blood was collectedby cardiac puncture using sterilized syringes (2 ml). After thesampling a portion of blood was transferred to EDTA‐coatedtubes. The hematological parameters, namely hematocrit(HCT), hemoglobin concentration (Hb), erythrocyte count(RBC) and leukocyte count (WBC), and the derived parametersMCV (mean cell volume), MCH (mean cell hemoglobin) andMCHC (mean cell hemoglobin concentration) were deter-mined according to standard methods (Svobodova et al.,1991). For biochemical and hormonal studies the rest of theblood was collected in tubes and then allowed to clot for30 min at 25 °C. The serum was then removed by subjectingthe tubes to centrifugation at 3000 rpm for 5 min and thenstored at −80 °C until further analyses. Blood glucose wasestimated using the method of Cooper and McDaniel (1970).The protein content of the samples was determined accordingto the method of Lowry et al. (1951) using crystalline bovineserum albumin standard. Total bilirubin was determined usinga commercial kit supplied by Chemelex, SA, Barcelona. ASTand ALT were estimated following Reitman and Frankel (1957)and LDH activity was estimated by the 2,4‐dinitrophenylhydrazine method (Tietz, 1976). ALP and ACP were deter-mined using a commercial kit supplied by Span DiagnosticsPrivate Limited, Udana (Surat), India. Cortisol was analyzedwith a commercial immunoenzymatic kit (United Biotech Inc.,CA, USA).

Statistical Analysis

The statistical significances of the differences between thecontrol and experimental groups for hematological, biochemicaland hormonal variables were analyzed by Student’s t‐test. Thelevel of significance was evaluated with P‐values following themethod of Bailey (1995). All data are presented as means (X)±standard error (SE) of the means. Values of P≤0.05 wereconsidered significant.

RESULTSThe values obtained from the non‐solvent control and solventcontrol (acetone) did not show any marked difference.Therefore the data obtained from solvent control were notcompared with the experimental values.

Acute 96 h LC50 Value

LC50 values and 95% confidence intervals are presented inTable 1. The determined 96 h LC50 for C. gariepinus exposed toNP and OP were 3.48 mg l−1 and 3.93 mg l−1, respectively(Table 1).

Fish Behavior

The control and solvent control groups showed normal behaviorduring the test period. The fish when exposed to NP and OPshowed abnormal behavior. At the start of exposure with higherconcentrations (750 and 1000 μg l−1), the fish showed erraticmovement and hyper‐excitability and in the later stages tendedto be lethargic with loss of equilibrium, and an increase infrequency of air gulping and mucous secretion were observed.Body pigmentation on the dorsal surface decreased andhemorrhages on the ventral skin surface were seen. The groupreceiving the lowest concentrations (250 and 500 μg l−1)exhibited behavior similar to the control group in the earlierstages but at later stages (days 5–7) had similar behavior to thoseat the higher concentrations. No mortality and no significantdifference in weight were observed during the study period.

Hematology Indices

The changes in the hematological data, namelyHb, HCT, RBC,WBC,MCV, MCH and MCHC, when exposed to different concentrationsof NP and OP, are presented in Tables 2 and 3. The individualeffects of both compounds with different concentrations werecompared. The Hb and HCT levels significantly increased (P<0.05)when exposed to 250 and 500 μg l−1 concentration of NP and OPand there was a significant decrease with 750 and 1000 μg l−1

concentrations. The increase of Hb and HCT levels was maximum(54.27 and 51.97%) with 500 μg l−1 NP exposure; on the otherhand, the maximum decrease (51.93 and 47.84%) occurred with1000 μg l−1 OP, respectively. A significant increase (P<0.05) inRBC count was noted with NP‐treated fish (250 and 500 μg l−1) butwith OP exposure the increase was observed only with 250 μg l−1.With higher concentrations of NP andOP (750 and 1000 μg l−1), theRBC count considerably decreased, showing a higher decrease(55.09%) at 1000 μg l−1 NP exposure when compared with similarconcentrations of OP (45.96%).

With respect to the WBC count, it was noted that, irrespectiveof the toxicants and their concentration, there was a gradualsignificant increase throughout. The smallest increase (26.00 and36.12%) was observed with 250 μg l−1 and the highest (126.99and 132.5%) with 1000 μg l−1of NP and OP, respectively. Thisindicates that, with the increase in concentration of toxicant, therewas a clear increase in the count of WBC, even though, whencompared, OP had a greater effect than NP. Among the calculatedhematological indices, a significant increase (P<0.05) in MCV andMCH values was observed with 500, 750, 1000 μg l−1 NP exposure.Surprisingly in OP, MCV showed a different trend, exhibiting anabrupt significant decrease (6.80%) with 1000 μg l−1 concentra-tion towards their respective control value, showing significance(P<0.05), whereas the MCH values showed the highest change(increase) with 500 μg l−1 (39.19%) and highest decrease (29.99%)with 1000 μg l−1 OP concentrations. With increase in concentra-tion (OP), the other calculated index MCHC values registered agradual significant decrease (P<0.05). However, this trend wasdisturbed in NP exposure with 500 μg l−1 concentration, showinga decrease (4.91%) which was far smaller than the value (7.55%)found with 250 μg l−1 (Tables 2 and 3).

Biochemical Indices

Serum biochemical components like biochemical variables(bilirubin, protein and glucose), detoxifying enzyme activities

Table 1. LC50 value, confidence limits (95%) and relatedcoefficient of NP and OP for the fish C. gariepinus

Chemical LC50 value(mg l−1)

95% confidencelimit

R2

Nonylphenol 3.480 3.347–3.627 0.958Octylphenol 3.937 3.798–4.080 0.956

S. K. Satyanarayanan et al.

J. Appl. Toxicol. 2011; 31: 752–761Copyright © 2011 John Wiley & Sons, Ltd.wileyonlinelibrary.com/journal/jat

754


and cortisol levels of C. gariepinus exposed to different concentra-tions of NP and OP were analyzed and are presented in Figs 1–5. Adose‐dependent significant increase (P<0.05) in levels of totalserumbilirubinwas observedwith all the concentrations of NP andOP (Fig. 1a). Relative to control (0.42±0.01 mg dl−1), the maximumincrease (1.52±0.05 and 1.71±0.07 mg dl−1) was with NP and OPexposure (1000 μg l−1). The increase was maximum (307.14) withOP compared with NP exposure. The toxic effects of both NP andOP exerted a reduction in the levels of serum protein (Fig. 1b).Student’st‐test analysis indicated a significant (P<0.05) differencewith 750 and 1000 μg l−1 of NP, whereas in OP the difference waswith 500, 750 and 1000 μg l−1. The data clearly show that amaximum decrease (2.22±0.34 g dl−1), compared with the control(4.58±0.42 g dl−1), occurred with OP concentration (1000 μg l−1).On the other hand, serum glucose levels were significantlyincreased at all the concentrations, showing the smallest increase(71.64±1.84 and 80.44±2.02mg dl−1) at 250 μg l−1 and the highestincrease (157.08±1.46 and 165.08±2.15 mg dl−1) at 1000 μg l−1 ofNP and OP, respectively (Fig. 1c). These data show that OP had amore deleterious effect on glucose content than NP.

Tissue damage enzyme activities (AST, ALT, ALP, ACP and LDH)showed a mixed trend of both increase and decrease in theirlevels with NP and OP exposure (Figs 2–4). The serum AST levels(Fig. 2a) significantly increased (72.48±3.41 IU l−1) in 250 μg l−1

NP, then showed a decreasing trend with other higherconcentrations having a maximum significant decrease (36.94±2.12 IU l−1) with 1000 μg l−1 (P<0.05). On the other hand, in OPexposure the increase (80.22±2.64 and 93.78±3.08 IU l−1) wassignificant (P<0.05) with 250 and 500 μg l−1 concentrations,leading to a significant decrease (42.76±0.97 IU l−1) with

1000 μg l−1 concentration. The level of serum ALT (Fig. 2b)increased from 64.45±2.57 IU l−1 (control) to 79.65±2.48 IU l−1

and 72.16±3.60 IU l−1 with 250 and 500 μg l−1 NP concentrations.Furthermore, a significant decrease (57.25±1.85 and 41.80±2.02 IU l−1) was noted with 750 and 1000 μg l−1 NP concentra-tions. Although the ALT levels significantly increased with 250,500 and 750 μg l−1 OP concentrations, there was a decrease of51.55±1.68 IU l−1 only with 1000 μg l−1.A more pronounced increase in ALP level was seen in fish

exposed to 250 and 500 μg l−1 concentrations and a significantdecrease (P<0.05) in 750 and 1000 μg l−1 concentrations of bothNP and OP, but when compared OP exhibited the highestincreased level (38.10±1.26 IU l−1) with 500 μg l−1 concentrationand a significant decrease (12.68±0.62 IU l−1) with 1000 μg l−1

concentration (Fig. 3a). The serum ACP levels also showed asignificant increase (21.26±0.94 IU l−1) with 500 μg l−1 and thesmallest increase (15.06±0.51 IU l−1) with 750 μg l−1 NPexposure. Similarly to OP‐exposed fish, the ACP levels showeda maximum increase (27.66±0.04 IU l−1) when compared withthe respective control (14.36±0.76 IU l−1) with 500 μg l−1

concentration. The ACP levels decreased to a maximum of 8.54±0.45 and 11.72±0.09 IU l−1 with 1000 μg l−1 OP and NP exposure,respectively (Fig. 3b). LDH levels increased significantly (P<0.05)to a maximum (159.09±2.84 and 176.08±0.54 IU l−1) with500 μg l−1 concentration of NP and OP (Fig. 4). However, in1000 μg l−1 NP and OP exposure a significant (P<0.05) decrease(52.18±0.95 and 70.35±1.52 IU l−1) in LDH levels was observed.Serum cortisol levels were significantly elevated in all theconcentrations of both toxicants, although the maximumincrease in their levels (174.40±2.14 and 142.38±0.95 ng ml−1)

Table 2. Effects of different concentrations of NP on the hematological indices in Clarias gariepinus after 7 days of exposure (n=5)

Parameters (units) Nonylphenol concentration

Control Solvent control 250 μg l−1 500 μg l−1 750 μg l−1 1000 μg l−1

Hb (g dl−1) 7.26±0.54 7.05±0.14 8.58±0.25* 11.20±0.02* 6.30±0.05* 4.82±0.32*HCT (%) 21.78±0.64 21.34±0.38 26.12±0.40* 33.10±0.82* 19.12±0.15* 15.30±0.09*RBC (106/mm3) 2.85±0.20 2.67±0.14 3.62±0.06* 3.70±0.08* 1.95±0.34** 1.28±0.06*WBC (103/mm3) 31.42±0.86 34.56±0.58 39.59±1.20* 46.62±2.24* 63.86±1.78* 71.32±2.56*MCV (fl) 77.11±0.47 79.65±1.12 72.57±2.06* 105.04±2.42* 99.82±2.08* 118.24±3.05*MCH (pg) 25.92±1.01 26.32±0.98 23.14±0.81* 36.21±2.45* 31.76±0.75* 39.08±1.64*MCHC (g dl−1) 32.94±0.25 32.98±0.16 30.45±0.74* 31.32±0.46* 29.98±0.47* 28.64±0.71*

Data represent means±SE of three individuals values (n=5). *Significant, P<0.05; **non‐significant, P>0.05 (based on Students’t‐test).

Table 3. Effects of different concentrations of OP on the hematological indices in Clarias gariepinus after 7 days of exposure (n=5)

Parameters (units) Octylphenol concentration

Control Solvent control 250 μg l−1 500 μg l−1 750 μg l−1 1000 μg l−1

Hb (g dl−1) 7.26±0.54 7.05±0.14 9.24±0.12* 8.68±0.30* 5.12±0.11* 3.49±0.05*HCT (%) 21.78±0.64 21.34±0.38 28.64±0.18* 26.51±0.04* 15.57±0.26* 11.36±0.71*RBC (106/mm3) 2.85±0.20 2.67±0.14 3.40±0.05* 2.42±0.02* 1.86±0.08* 1.54±0.02*WBC (103/mm3) 31.42±0.86 34.56±0.58 42.77±0.42* 56.94±1.26* 69.48±1.08* 73.05±1.92*MCV (fl) 77.11±0.47 79.65±1.12 90.85±0.56* 111.54±0.72* 86.42±1.10* 71.86±0.84*MCH (pg) 25.92±1.01 26.32±0.98 31.45±0.84* 36.08±0.72* 22.42±0.96* 20.22±0.58*MCHC (g dl−1) 32.94±0.25 32.98±0.16 31.15±0.43* 30.98±0.16* 30.46±0.42* 28.75±0.85*

Data represent means ± SE of three individuals values (n=5). *Significant, P<0.05 (based on Students’t‐test).



755


was with 500 μg l−1 concentration of NP and OP, respectively(Fig. 5). Even if the levels of cortisol were significant (P<0.05)throughout, the smallest increase (23.16±0.46 and 34.81±1.75 ng ml−1) was with 1000 μg l−1 OP and NP, respectively.

DISCUSSIONThe aim of the present study was to assess and compare theindividual adverse effects of NP and OP (with differentconcentrations) on C. gariepinus using hematological andselected biochemical parameters. The African sharp tooth

catfish C. gariepinus is one of the most widespread andimportant aquacultural species in Africa and Asia (De Silvaet al., 2006), and therefore one of the most studied species inthe Clariidae family (Teugels, 1996). It is able to withstandadverse environmental conditions, and has a wide tolerance ofrelatively poor water quality conditions in which otherfreshwater fish would find it difficult to survive. Its ability tobreathe air (Buttle et al., 1995) and the hardiness of the fishmake it an ideal candidate for highly intensive culture, withoutthe need for pond aeration or high water exchange rates(Adeyemo et al., 1994).

Surveys of NP and OP have been performed in many countriesand they have been detected in samples of surface water, rivers,sewage sludge and effluents, sediments and estuaries, revealinga wide range of concentrations of NP reaching even higher than100 μg l−1, up to 644 μg l−1 (Naylor et al., 1992; Ahel et al., 1994;Blackburn and Waldock, 1995; Isobe et al., 2001; Fries andPüttmann, 2003; Vazquez‐Duhalt et al., 2005). With differentorganisms and using different test methods, NP was shown to betoxic (LC50) tofishatconcentrations ranging from17to3000μg l−1

(Servos, 1999). The reported LC50 values to Oryzias latipes varyfrom 1 10 000 to 1400 μg l−1 for a nonylphenol ethoxylatemixtureand NP, respectively (Yoshimura, 1986), whereas No‐observedeffect concentration (NOEC) concentrations ranged from

*

**

*

**

**

0

0.5

1

1.5

2

250 500 750 1000Concentration (µg/l)

Tot

al b

iliru

bin

(mg/

dL)

(a)

** ***

*

***

**

0

1

2

3

4

5

6


Tot

al P

rote

in (

g/dL

)

(b)

**

*

*

**

*

*

0

50

100

150

200


Glu

cose

(m

g/dL

)

Control S.control Nonylphenol Octylphenol

(c)



Figure 1. (a) Total bilirubin (mg dl−1), (b) total protein (g dl−1) and (c)glucose (mg dl−1) levels in serum of Clarias gariepinus exposed to differentconcentrations (250, 500, 750 and 1000 μg l−1) of nonylphenol andoctylphenol for 7 days. Bars represent means and vertical lines the SEs.*Significant, P<0.05; **non‐significant, P>0.05 (based on Students’t‐test).

*

** **

*

*

**

0

25

50

75

100

250 500 750 1000

Concentration (µg/l)

AS

T (

IU/L

)


(a)


(b)

**

*

*

*

*

*

*

0

15

30

45

60

75

90

250 500 750 1000

AL

T (

IU/L

)


Figure 2. Changes in serum transaminases [(a) AST and (b) ALT] activityof Clarias gariepinus exposed to different concentrations (250, 500, 750and 1000 μg l−1) of nonylphenol and octylphenol for 7 days. Barsrepresent means and vertical lines the SEs. *Significant, P<0.05; **non‐significant, P>0.05 (based on Students’t‐test).



756


3.9 to 143 μg l−1 for NP for various aquatic species (Staples et al.,1998). In previous studies 96 h LC50s of OP for rainbow troutwere found to range from 190 to 920 μg l−1 (Brooke, 1993;

Dwyer et al., 1995; Naylor, 1995) and for Pimephales promelasranged from 0.25 to 2.2 mg l−1 (OSPAR Commission, 2003). Pilotexperiments estimated the acute toxicity concentration (96 hLC50) of OP in adult guppies to be between 1400 and 3700 μg l−1

(Toft and Baatrup, 2001). OP is also said to cause larval death(Ambystoma barbouri) most rapidly at the highest concentrationof OP (500 mg l−1), indicating that short‐term exposure to thisconcentration would be more detrimental than for any otherchemical or concentration (Rohr et al., 2003). Gronen et al. (1999)clearly suggests that OP showed no toxicity to concentrationbelow 790 ppb in fish Oryzias latipes. Based on these previousdata and the 96 h acute toxicity tests, concentrations of 250,500, 750 and 1000 μg l−1 were selected for the study presentedhere. Even if selected NP and OP concentrations are higher andare very rare in the aquatic environment, they were carefullyselected to bring about desired effects to the organism(C. gariepinus) in the present study. Also, the selectedconcentrations were less than one‐thirtieth of the LC50 values(3.48 and 3.93 mg l−1) of NP and OP, respectively. This study isalso useful in predicting the safe concentration dose of thecontaminants in the environment. The present work alsocompares the individual effects of two related toxicants onselected hematological and biochemical parameters, which hasnot been attempted before (other than for compounds likeglucose and serum cortisol), although the results obtained canfollow a different pattern from other toxicants.Hematological and biochemical profiles of blood can provide

important information about the internal environment of theorganism. Thus, the evaluation of hematological and biochem-ical characteristics in fish has become an important means ofunderstanding normal and pathological processes and toxico-logical impacts (Kavitha et al., 2010). Typically, hematologicalparameters are non‐specific in their responses towards chemicalstressors. However, toxic substances can significantly damagethe hematological system of fish (Van der Oost et al., 2003).Probing RBCs is valuable in investigating anemia and hemopoi-esis, as they are responsible for vital transport inside the body.For the determination of size, content and hemoglobinconcentration of red cells, their indices such as MCHC, MCHand MCV are calculated from the red cell count, hemoglobinconcentration and hematocrit (Nelson and Morris, 1989).

0

10

20

30

40

250 500 750 1000


AL

P (

IU/L

)Control S.control Nonylphenol Octylphenol

(a)

0

5

10

15

20

25

30

250 500 750 1000


AC

P (

IU/L

)


(b)

**

**

*

*

*

*

* *

**

**

**

Figure 3. Activities of serum phosphatases [(a) ALP and (b) ACP] inClarias gariepinus exposed to different concentrations (250, 500, 750 and1000 μg l−1) of nonylphenol and octylphenol for 7 days. Bars representmeans and vertical lines the SEs. *Significant, P<0.05; **non‐significant,P>0.05 (based on Students’t‐test).

*

*

**

**

*

**

0

40

80

120

160

200

250 500 750 1000


LD

H (

IU/L

)


Figure 4. Specific activities of LDH in Clarias gariepinus exposed todifferent concentrations (250, 500, 750 and 1000 μg l−1) of nonylphenoland octylphenol for 7 days. Bars represent means and vertical lines the SEs.*Significant, P<0.05; **non‐significant, P>0.05 (based on Students’t‐test).

*

*

*

*

*

*

*

*

0

25

50

75

100

125

150

175

250 500 750 1000


Ser

um

cor

tiso

l(n

g/m

L)


Figure 5. Serum concentration levels of cortisol in Clarias gariepinusexposed to different concentrations (250, 500, 750 and 1000 μg l−1) ofnonylphenol and octylphenol for 7 days. Bars represent means andvertical lines the SEs. *Significant, P<0.05 (based on Students’t‐test).



757


In the present study, the erythrocyte counts accompanied byhemoglobin and hematocrit levels showed a significant increase(P<0.05) with lower concentrations of NP and OP (Tables 2 and 3),supported by similar results in catfish exposed to waterborneendosulfan (Gopal et al., 1981). As observed, the elevatedhemoglobin concentration and decreased MCHC with the lowerconcentrations of NP and OP may be due to stress responsewherein with time dependence activation of an erythrocytemembrane Na+/H+ exchange sets in due to rapid adrenergicallyinduced contraction of the spleen, resulting in cell swelling (Reidet al., 1998). This increase in hemoglobin and as well as hematocritin the present study might be due to decreased plasma volume,swelling of erythrocytes, and/or release of additional erythrocytesinto the blood. The increase in HCT levels brought about byerythrocyte swelling paves the way for observed reduced MCHClevel, suggesting the increase of immature RBC in the circulatorystream. Generally, the MCHC measure has been used to assess theamount of red cell swelling (decreased MCHC) or shrinkage(increased MCHC) present.

However, an altogether a different trend was observed duringexposure to higher concentrations of both the toxicants (750and 1000 μg l−1), showing a significant decrease in hematocrit,hemoglobin content and red cells counts that can be attributedto blood cell lyses, as well as exhaustion of the hemopoieticactivity of the kidney (Santhakumar et al., 1999) indicating bothfunctional and hemolytic anemia (Avilez et al., 2004). Further-more lyses of erythrocytes together with inhibition of erythro-cyte production and significant reduction in the hemoglobincontent at these higher concentrations caused a macrocytictype of anemia (Barnhart et al., 1983) in the individuals of C.gariepinus exposed to toxicants NP and OP. It has to be notedthat in the case of HCT, the decreased levels after exposure tohigher concentrations of the toxicants might be due to anemia.

The increases in MCV and MCH with all concentrations of NP(250, 500, 750 and 1000 μg l−1) and only with lowerconcentrations of OP (250 and 500 μg l−1) can be attributedto direct or feedback responses of structural damage to RBCmembranes, resulting in hemolysis and impairment in hemo-globin synthesis, and stress‐related release of RBCs from thespleen. The MCV gives an indication of the status and size of thered blood cells and reflects abnormal or normal cell divisionduring erythropoiesis. In spite of the increase in the RBC count, adecrease in MCV with NP (250 μg l−1) and OP (1000 μg l−1)intoxication may show the extent of the shrinking cell size.Therefore, we suggest that the increase in RBC value with thereduced erythrocyte size (microcytosis) indicates a highpercentage of immature red blood cells in circulation afterexposure to NP and OP. The lower values measured for MCHCcoupled with high MCV in most of the concentrations of bothtoxicants might be an indication of adrenalin‐mediated cellswelling (Nikinmaa, 1992). In addition, the MCHC concentrationsof blood of test fish were observed to be significantly lower thanthose of the controls. In accordance with the behavior of thecorpuscular constant and the detected findings in theerythrocytes, we can classify this anemia as normocytic anemia.The data on hematological alteration from this study clearlyreveal destruction of RBC by the toxicants (NP and OP), whichmay predispose to anemia with higher concentrations and wasevidently independent of the toxicant. Thus, it is clear thatexposure to the same chemical agent can induce differentalterations (increase or decrease) in hematological parameters,which can indicate adaptive responses to a stress agent or the

direct effects of these contaminants on erythrocytes or theirproduction.

With the prevailing hemolytic anemia observed, a significantincrease in the bilirubin content (one of the breakdownproducts of hemoglobin in the blood) was noted with all theconcentrations of both NP and OP (Fig. 1). Generally when fishare exposed to aquatic toxicants, reduction of RBC counts and/or an increase in the proportion of immature RBC is a commonresponse (Rao et al., 1990), which is associated with an increasein plasma bilirubin concentration. In some forms of anemia(hemolytic type), the level of bilirubin may rise due to theinability of the liver to pass the increased quantity of thepigment, suggesting liver damage. A similar rise in serumbilirubin level was observed in Tilapia mossambica treated withphosphamidon (Jayantha Rao et al., 1984), but only a slightincrease in C. gariepinus exposed to potassium permanganate(Ovie, 2008).

The significant increase in the leukocyte population notedthroughout the study (Tables 1 and 2) independent of toxicantinvolved could be related to the presence of tecidual damagessuch as necrosis (de Oliveira Ribeiro et al., 2002) and severedisturbance of the non‐specific immune system leading toincrease production of leukocytes (Das and Mukherjee, 2003). Insupport of this argument, a significant increase in WBC countwas observed in Onchorhynchus kistuch exposed to bleachedkraft pulpmill effluent and suggested leukocytosis probably dueto the tissue damage and subsequent removal of cell debris(McLeay, 1975) and also in Oreochromis niloticus exposed todeltamethrin, inducing immunological changes (El‐Sayed et al.,2007). In this study, both NP and OP, regardless of theconcentration, clearly induced leukocytosis in C. gariepinus.

Protein and carbohydrates play a major role as energyprecursors for fish under stress conditions. Changes in each ofthese blood components have been employed as useful generalindicators of stress in teleosts (Das et al., 2004). In the presentstudy, a significant decrease (P<0.05) in serum proteinconcentration compared with the control group with all theconcentrations and toxicant involved may be an indication ofprotein catabolism, the process converting blood and structuralprotein and carbohydrate reserves to energy, to meet the higherenergy demand during the prevailing stress caused by both NPand OP (Fig. 1). Some of the other possible reasons for theobserved protein reduction in response to a stressor NP and OPmight be due hemolysis and shrinkage of the erythrocytes,which must have caused dilution of the plasma volumecontributing to some extent in such a reduction (Das et al.,2004), or the blocking of protein synthesis or protein denatur-ation or interruption in the amino acid synthesis due to theincrease in cortisol, inhibiting protein synthesis and stimulationof protein catabolism (Van der Boon et al., 1991). Similarsignificant reduction in plasma protein level was reported inClarias batrachus exposed to cypermethrin (Begum, 2005), inOreochromis niloticus exposed to deltamethrin (El‐Sayed et al.,2007) in rainbow trout, and in Cyprinus carpio exposed todiazinon (Oruç and Usta, 2007).

The results of the present investigation indicated that theserum glucose content significantly increased as compared withthe control when exposed to different concentrations of boththe toxicants (Fig. 1). This suggests that hyperglycemia has set into help the animal by providing energy substrates to differenttissues to cope with the increased energy demand (Barton,2002). A similar observation was made in Dicentrarchus labrax



758


exposed to mixtures of β‐naphthoflavone, 17β‐estradiol and NPfor 24 h (Teles et al., 2004); and in Sparus aurata exposed to amixture of estradiol and 4‐nonylphenol (Teles et al., 2005). Thisincrease in the circulating glucose can be directly related to thesignificant increase in circulating catecholamines or corticoste-roids following stress (Vijayan et al., 1997) caused by NP and OPwith almost all the concentrations (Fig. 5). The cortisol andglucose plasmatic concentrations are commonly used, respec-tively, as indicators of primary and secondary acute stressresponses in fish (Santos and Pacheco, 1996; Hontela, 1997).Increases in plasma glucose levels and hematocrit are secondaryresponses to stress, and arise following cortisol and catechol-amine release, which was clearly observed in our present study.The hyperglycemic response by glycogenolysis and gluconeo-genesis during our study was mainly mediated by the increasein cortisol (Wendelaar Bonga, 1997). In the present study stresscaused by NP and OP individually might have resulted in anincrease in the synthesis of adrenocorticotropic hormone andglucagon and a decrease in the synthesis of insulin. Thereby,hepatic glycogen is rapidly converted into glucose and passesinto systemic circulation, ever‐increasing the blood glucose level(Datta and Kaviraj, 2003). Thereby we are able to clearlycorrelate the hyperglycemic response and catabolism of serumproteins with cortisol circulating levels. Meanwhile, the higherlevels of serum cortisol in the present study agree with studieson C. gariepinus (Martins et al., 2006; van de Nieuwegiessenet al., 2009). Moreover, simultaneous increases in plasma cortisoland glucose levels have been noticed in rainbow trout exposedto benzo(a)pyrene or β‐naphthoflavone (Tintos et al., 2008),which further supports the role of toxicants NP and OP in theinduction of a stress response in fish. However, at higherconcentrations of NP and OP (750 and 1000 μg l−1), in accordwith Teles et al. (2004), a peculiar pattern of decrease in cortisollevel (Fig. 5) and a dramatic increase in glucose (Fig. 1) wereobserved. The slight decrease in cortisol may be an indication ofendocrine impairment, when exposed to these organic con-taminants (Aluru et al., 2004). It is also been argued that in fishunder acute stress, the rapid release of catecholamines maycontribute to increase in glucose via glycogenolysis rather thaninterrenal cortisol release (Vijayan et al., 1997). Thus it can beconcluded that the mechanism and relation between glucoseand cortisol is difficult to establish and yet has to be clarified.

The analysis of studied marker enzymes such as aminotran-saminases, phosphatases and lactate dehydrogenase may serveas a specific indicator of toxicant‐induced changes in theenzyme activity of fish. The results of our present study clearlyshow increased activity of all enzymes (transaminases, phos-phatases and dehydrogenases) when C. gariepinus is exposed tolower concentrations of the toxicants NP and OP. Generallystress conditions induce elevation in the transaminationpathway (Awasthi et al., 1984), which offers excellent supportfor the elevation of AST and ALT with the lower concentrationsof both the toxicants, depicting a clear indication of shunting ofamino acids into the TCA cycle through oxidative deaminationand active transamination. As enzymes, ALP and ACP play asignificant role in metabolism, pathological necrosis, proteinsynthesis, synthesis of certain enzymes and secretion activity,and the changes in their activity as observed in the presentstudy were responsible for the changes in the levels of serumglucose and protein, possibly providing insult to the tissues.There are many reports supporting the increased levels of thesestudied serum enzymes noted in the present investigation,

proving severe cellular damage and necrosis of tissues(Sivakumari et al., 1997; Oluah, 1999; Zikic et al., 2001;Venkateswara Rao, 2006; Velíšek et al., 2007). The drasticreduction in serum enzymes with higher concentrations of thetoxicants indicates the adverse effects of both NP and OP,depending upon the increase in concentration (Figs 2–4). Theobserved decreased activities of ALT, AST, ACP and ALP indicatedisturbance in the structure and integrity of cell organelles, likethe endoplasmic reticulum, the membrane transport systemand impaired carbohydrate and protein metabolism, and lead toconsequent death of individuals (Karatas and Kalay, 2002; Rao,2006), whereas the inhibition of the activity of the dehydroge-nase (Fig. 4) may be due to the changes in the mitochondrialmembrane junction or it may be due to impaired glycolysis(Ramesh et al., 1993).

CONCLUSIONIn conclusion, this study proved that exposure to NP and OPindividually not only has adverse effects depending on theconcentration but also that their high toxic potential causesthem to be a pollution risk at any concentration, even to arelatively tolerant fish such as C. gariepinus. There was a rapidresponse after the fish had contact with either compound, asindicated by imbalance or disturbance in the studied biomarkers.The data from hematological, biochemical and hormonal targetsshow that the individual effects of OP seemed to be moredeleterious than those of NP, even if OP and NP share a commonparent compound, alkylphenol ethoxylates. Further, the presentresults yield valuable information on general toxicity and thetoxic efficiency of both these compounds. It is also clear thatthere is a need for further studies to determine accurately theireffects on several other biological organisms, and also todetermine whether the effects are similar when fish aresubjected to longer exposures to lower concentrations; acombined toxicity study will satisfy this need.

Acknowledgments

The authors are thankful to Professor Zijian Wang, ResearchCenter for Eco‐Environmental Sciences, CAS, China for thevaluable comments and suggestions to improve the manuscript.The authors are very grateful to Professor John C. Morse, USA forcritical reading of this manuscript and for providing languagehelp. The authors thank G. Mahendran and R.K. Poopal forassistance with the assay work.

REFERENCESAdeyemo AA, Oladosu GA, Ayinla AO. 1994. Growth and survival of fry of

African catfish species, Clarias gariepinus Burchell, Heterobranchusbidorsalis Geoffery and Heteroclarias reared on Moina dubia incomparison with other first feed sources. Aquaculture 119: 41–45.

Adhikari S, Sarkar B, Chatterjee A, Mahapatra CT, Ayyappan S. 2004.Effects of cypermethrin and carbofuran on certain hematologicalparameters and prediction of their recovery in a freshwater teleost,Labeo rohita (Hamilton). Ecotoxicol. Environ. Saf. 58: 220–226.

Agrahari S, Pandey KC, Gopal K. 2007. Biochemical alteration induced bymonocrotophos in the blood plasma of fish, Channa punctatus(Bloch). Pest. Biochem. Physiol. 88: 268–272.

Ahel M, Giger W, Schaffner C. 1994. Behaviour of alkylphenolpolyethoxylate surfactants in the aquatic environment – II. Occur-rence and transformation in rivers. Water Res. 28: 1143–1152.

Aluru N, Jorgensen EH, Maule A, Vijayan MM. 2004. PCB disruption of thehypothalamo–pituitary–interrenal axis involves brain glucocorticoid



759


receptor downregulation in anadromous Arctic charr. Am. J. Physiol.287: 787–793.

APHA‐AWWA‐WPCF. 1998. Standard Methods for the Examination ofWater and Wastewater, 20th edn. American Public Health Association:New York.

Avilez IM, Altran AE, Aguiar LH, Moraes G. 2004. Hematological responsesof the Neotropical teleost matrinxã (Brycon cephalus) to environ-mental nitrite. Comp. Biochem. Physiol. C 139: 135–139.

Awasthi M, Shah P, Dubale MS, Gadhia P. 1984. Metabolic changesinduced by organophosphates in the piscine organs. Environ. Res. 35:320–325.

Bailey NTJ. 1995. Statistical Methods in Biology, 3rd edn. CambridgeUniverstiy Press: Cambridge; 255.

Barnhart MI, Wallace MA, Lusher LM. 1983. Red blood cells. In BiomedicalResearch Applications of Scanning Electron Microscopy, Vol. 3. HodgesGM, Corr KE (eds), Academic Press: New York; 171–243.

Barse A, Chakrabarti T, Ghosh T, Pal A, Jadhao S. 2006. One‐tenth dose ofLC50 of 4‐tert‐butylphenol causes endocrine disruption andmetabolic changes in Cyprinus carpio. Pest. Biochem. Physiol. 86:172–179.

Barton B. 2002. Stress in fishes: a diversity of responses with particularreference to changes in circulating corticosteroids. Integr. Comp. Biol.42: 517.

Begum G. 2005. In vivo biochemical changes in liver and gill of Clariasbatrachus during cypermethrin exposure and following cessation ofexposure. Pest. Biochem. Physiol. 82: 185–196.

Bennie D. 1999. Review of the environmental occurrence of alkylphenolsand alkylphenol ethoxylates. Water Qual. Res. J. Can. 34: 79–122.

Blackburn M, Waldock M. 1995. Concentrations of alkylphenols in riversand estuaries in England and Wales. Water Res. 29: 1623–1629.

Brooke LT. 1993. Acute and chronic toxicity of nonylphenol to ten speciesof aquatic organisms. Report to the US Environmental ProtectionAgency, Duluth, MN (contract no. 68‐C1‐0034). Lake SuperiorResearch Institute, University of Wisconsin‐Superior, Superior, WI.

Buttle L, Uglow R, Cowx I. 1995. Effect of dietary protein on the nitrogenexcretion and growth of the African catfish, Clarias gariepinus. Aquat.Living Resour. 8: 407–414.

Cooper G, McDaniel V. 1970. Determination of glucose in blood.Standard Meth. Clin. Chem. 6: 159–170.

Das B, Mukherjee S. 2003. Toxicity of cypermethrin in Labeo rohitafingerlings: biochemical, enzymatic and haematological conse-quences. Comp. Biochem. Physiol. C 134: 109–121.

Das P, Ayyappan S, Jena J, Das B. 2004. Acute toxicity of ammonia and itssub‐lethal effects on selected haematological and enzymaticparameters of mrigal, Cirrhinus mrigala (Hamilton). Aquacult. Res.35: 134–143.

Datta M, Kaviraj A. 2003. Ascorbic acid supplementation of diet forreduction of deltamethrin induced stress in freshwater catfish Clariasgariepinus. Chemosphere 53: 883–888.

De la Torre F, Salibián A, Ferrari L, Conicet A. 1999. Enzyme activities asbiomarkers of freshwater pollution: responses of fish branchial (Na+

K+)‐ATPase and liver transaminases. Environ. Toxicol. Water Qual. 14:313–319.

de Oliveira Ribeiro C, Belger L, Pelletier E, Rouleau C. 2002.Histopathological evidence of inorganic mercury and methylmercury toxicity in the arctic charr (Salvelinus alpinus). Environ. Res.90: 217–225.

De Silva S, Nguyen T, Abery N, Amarasinghe U. 2006. An evaluation ofthe role and impacts of alien finfish in Asian inland aquaculture.Aquacul. Res. 37: 1–17.

Dwyer FJ, Sappington LC, Buckler DR, Jones SB. 1995. Use of surrogatespecies in assessing contaminant risk to endangered and threatenedfishes. Final report. US Environmental Protection Agency, GulfBreeze, FL (EPA/600/R96/029).

El‐Sayed Y, Saad T, El‐Bahr S. 2007. Acute intoxication of deltamethrin inmonosex Nile tilapia, Oreochromis niloticus with special reference tothe clinical, biochemical and haematological effects. Environ. Toxicol.Pharmacol. 24: 212–217.

Fries E, Püttmann W. 2003. Occurrence and behaviour of 4‐nonylphenolin river water of Germany. J. Environ. Monit. 5: 598–603.

Gopal K, Khanna R, Anand M, Gupta G. 1981. The acute toxicity ofendosulfan to fresh‐water organisms. Toxicol. Lett. 7: 453–456.

Gronen S, Denslow N, Manning S, Barnes S, Barnes D, Brouwer M. 1999.Serum vitellogenin levels and reproductive impairment of maleJapanese medaka (Oryzias latipes) exposed to 4‐tert‐octylphenol.Environ. Hlth Perspect. 107(5): 385–390.

Guenther K, Kleist E, Thiele B. 2006. Estrogen‐active nonylphenols froman isomer‐specific viewpoint: a systematic numbering system andfuture trends. Anal. Bioanal. Chem. 384: 542–546.

Hontela A. 1997. Endocrine and physiological responses of fish toxenobiotics: role of glucocorticosteroid hormones. Rev. Toxicol. 1: 1–46.

Isobe T, Nishiyama H, Nakashima A, Takada H. 2001. Distribution andbehavior of nonylphenol, octylphenol, and nonylphenol monoethox-ylate in Tokyo metropolitan area: their association with aquaticparticles and sedimentary distributions. Environ. Sci. Technol. 35:1041–1049.

Jayantha Rao K, Azhar Baig M, Ramamurthy K. 1984. Effect of a systemicpesticide phosphamidon on some aspects of fresh water fish, TilapiaMossambica. Int. J. Environ. Health 26: 60–64.

Jeney G, Nemcsók J, Jeney Z, Olah J. 1992. Acute effect of sublethalammonia concentrations on common carp (Cyprinus carpio L.). II:effect of ammonia on blood plasma transaminases (GOT, GPT), G 1DH enzyme activity, and ATP value. Aquaculture (Amsterdam) 104:149–156.

Karatas S, Kalay M. 2002. Accumulation of lead in the gill, liver, kidneyand brain tissues of Tilapia zilli. Turk. J. Vet. Anim. Sci. 26: 471–477.

Kavitha C, Malarvizhi A, Senthil Kumaran S, Ramesh M. 2010.Toxicological effects of arsenate exposure on hematological,biochemical and liver transaminases activity in an Indian majorcarp, Catla catla. Food Chem. Toxicol. 48: 2848–2854.

Lowry O, Rosebrough N, Farr A, Randall R. 1951. Protein measurementwith the folin phenol reagent. J. Boil. Chem. 193: 265–275.

Maguire R. 1999. Review of the persistence of nonylphenol andnonylphenol ethoxylates in aquatic environments. Water Qual. Res.J. Can. 34: 37–78.

Martins C, Schrama J, Verreth J. 2006. The effect of group compositionon the welfare of African catfish (Clarias gariepinus). App. Anim.Behav. Sci. 97: 323–334.

McLeay D. 1975. Sensitivity of blood cell counts in juvenile Coho salmon(Onchorhynchus kisutch) to stressors including sublethal concentra-tions of pulp mill effluent and zinc. J. Fish. Res. Bioconc. 32: 2357–2364.

Naylor C. 1992. Environmental fate of alkylphenol ethoxylates. SoapCosmet. Chem. Spec. 68: 27–31.

Naylor CG. 1995. Environmental fate and safety of nonylphenolethoxylates. Text. Chem. Color. 27: 29–33.

Naylor C, Mieure J, Adams W, Weeks J, Castaldi F, Ogle L, Romano R.1992. Alkylphenol ethoxylates in the environment. J. Am. Oil Chem.Soc. 69: 695–703.

Nelson DA, Morris MW. 1989. Basic methodology. Hematology andcoagulation, part IV. In Clinical Diagnosis and Management byLaboratory Methods, Nelson DA, Henry JB (eds). W.B. Saunders:Philadelphia, PA; 578–625.

Nikinmaa M. 1992. Membrane transport and control of hemoglobin–oxygen affinity in nucleated erythrocytes. Physiol. Rev. 72: 301–321.

Nimrod A, Benson W. 1996. Environmental estrogenic effects ofalkylphenol ethoxylates. CRC Crit. Rev. Toxicol. 26: 335–364.

Oluah N. 1999. Plasma aspartate aminotransferase activity in the catfishClarias albopunctatus exposed to sublethal zinc and mercury. Bull.Environ. Contam. Toxicol. 63: 343–349.

Oruç E, Usta D. 2007. Evaluation of oxidative stress responses andneurotoxicity potential of diazinon in different tissues of Cyprinuscarpio. Environ. Toxicol. Pharmacol. 23: 48–55.

OSPAR Commission. 2003. OSPAR background document on octylphenol;1–31.

Ovie K. 2008. Effects of sublethal concentrations of potassiumpermanganate on nitrogenous waste products of African catfish:Clarias gariepinus. Int. J. Integ. Biol. 4: 40.

Pottinger T. 1998. Changes in blood cortisol, glucose and lactate in carpretained in anglers’ keepnets. J. Fish Boil. 53: 728–742.

Ramesh M, Sivakumari K, Kanagaraj M, Manavalaramanujam R. 1993.Toxicity of dye effluent in lactate dehydrogenase activity in Labeorohita. Int. J. Environ. Protec. 13: 124–124.

Rao D, Bhaskar B, Rao K, Prasad Y, Rao N, Rao T. 1990. Haematologicaleffects in fishes from complex polluted waters of VisakhapatnamHarbour. Mar. Environ. Res. Lond. 30: 217–231.

Rao J. 2006. Biochemical alterations in euryhaline fish, Oreochromismossambicus exposed to sub‐lethal concentrations of an organophos-phorus insecticide, monocrotophos. Chemosphere 65: 1814–1820.

Reid S, Bernier N, Perry S. 1998. The adrenergic stress response in fish:control of catecholamine storage and release. Comp. Biochem.Physiol. C 120: 1–27.



760


Reitman S, Frankel A. 1957. A colorimetric method for the determinationof serum levels of glutamic oxaloacetic acid and pyruvic acidtransaminases. Am. J. Clin. Pathol. 29: 56–63.

Rohr JR, Elskus AA, Shepherd BS, Crowley PH, McCarthy TM, NiedzwieckiJH, Sager T, Sih A, Palmer BD. 2003. Lethal and sublethal effects ofatrazine, carbaryl, endosulfan, and octylphenol on the streamsidesalamander (Ambystoma barbouri). Environ. Toxicol. Chem. 22(10):2385–2392.

Saito I, Onuki A, Seto H. 2004. Indoor air pollution by alkylphenols inTokyo. Indoor Air 14: 325–332.

Santhakumar M, Balaji M, Ramudu K. 1999. Effect of sublethalconcentrations of monocrotophos on erythropoietic activity andcertain hematological parameters of fish Anabas testudineus (Bloch).Bull. Environ. Contam. Toxicol. 63: 379–384.

Santos M, Pacheco M. 1996. Anguilla Anguilla L. Stress biomarkersrecovery in clean water and secondary‐treated pulp mill effluent.Ecotoxicol. Environ. Saf. 35: 96–100.

Schwaiger J, Spieser O, Bauer C, Ferling H, Mallow U, Kalbfus W, NegeleR. 2000. Chronic toxicity of nonylphenol and ethinylestradiol:haematological and histopathological effects in juvenile commoncarp (Cyprinus carpio). Aquat. Toxicol. 51: 69–78.

Servos M. 1999. Review of the aquatic toxicity, estrogenic responses andbioaccumulation of alkylphenols and alkylphenol polyethoxylates.Water Qual. Res. J. Can. 34: 123–177.

Sivakumari K, Manavalaramanujam R, Ramesh M, Lakshmi R. 1997.Cypermethrin toxicity: Sublethal effects on enzyme activities in afreshwater fish, Cyprinus carpio var. communis. J. Environ. Biol. 18:121–125.

Staples CA, Weeks J, Hall J, Naylor C. 1998. Evaluation of aquatic toxicityand bioaccumulation of C8‐ and C9‐alkylphenol ethoxylates. Environ.Toxicol. Chem. 17: 2470–2480.

Svobodova Z, Prada D, Paláčková J. 1991. Unified Methods of Haemato-logical Examination of Fish. Research Institute on Fish Culture andHydrobiology: Vodany, Czechoslovakia; 31.

Teles M, Santos M, Pacheco M. 2004. Responses of European eel(Anguilla anguilla L.) in two polluted environments: in situ experi-ments. Ecotoxicol. Environ. Saf. 58: 373–378.

Teles M, Pacheco M, Santos M. 2005. Sparus aurata L. liver EROD and GSTactivities, plasma cortisol, lactate, glucose and erythrocytic nuclearanomalies following short‐term exposure either to 17‐estradiol (E2)or E2 combined with 4‐nonylphenol. Sci. Total Environ. 336: 57–69.

TemaNord. 1996. Chemicals with Estrogen‐like Effects. Nordic Council ofMinisters; 580.

Teugels G. 1996. Taxonomy, phylogeny and biogeography of catfishes(Ostariophysi, Siluroidei): an overview. Aquat. Living Resour. 9:9–34.

Tietz NW. 1976. Fundamentals of Clinical Chemistry. W.B. Saunders:Philadelphia, PA; 652.

Tintos A, Gesto M, Míguez J, Soengas J. 2008. β‐Naphthoflavone andbenzo(a)pyrene treatment affect liver intermediary metabolism andplasma cortisol levels in rainbow trout Oncorhynchus mykiss.Ecotoxicol. Environ. Saf. 69: 180–186.

Toft G, Baatrup E. 2001. Sexual characteristics are altered by 4‐tert‐octylphenol and 17β‐estradiol in the adult male guppy (Poeciliareticulata). Ecotoxicol. Environ. Saf. 48: 76–84.

USEPA. 1990. Probit Program Version 1.5. Ecological Monitoring ResearchDivision, Environmental Monitoring Systems Laboratory, USEPA:Cincinnati, OH.

van de Nieuwegiessen P, Olwo J, Khong S, Verreth J, Schrama J. 2009.Effects of age and stocking density on the welfare of African catfish,Clarias gariepinus Burchell. Aquaculture 288: 69–75.

Van der Boon J, Van Den Thillart G, Addink A. 1991. The effects of cortisoladministration on intermediary metabolism in teleost fish. Comp.Biochem. Physiol. A 100: 47–53.

Van der Oost R, Beyer J, Vermeulen N. 2003. Fish bioaccumulation andbiomarkers in environmental risk assessment: a review. Environ.Toxicol. Pharmacol. 13: 57–149.

Vazquez‐Duhalt R, Marquez‐Rocha F, Ponce E, Licea A, Viana M. 2005.Nonylphenol, an integrated vision of a pollutant. Appl. Ecol. Environ.Res. 4: 1–25.

Velíšek J, Juríková J, Dobšíková R, Svobodova Z, Piaková V, Machova J,Novotný L. 2007. Effects of deltamethrin on rainbow trout(Oncorhynchus mykiss). Environ. Toxicol. Pharmacol. 23: 297–301.

Venkateswara Rao J. 2006. Sublethal effects of an organophosphorusinsecticide (RPR‐II) on biochemical parameters of tilapia, Oreochromismossambicus. Comp. Biochem. Physiol. C 143: 492–498.

Vijayan M, Feist G, Otto D, Schreck C, Moon T. 1997. 3,3,4,4‐Tetrachlorobiphenyl affects cortisol dynamics and hepatic functionin rainbow trout. Aquat. Toxicol. 37: 87–98.

Wendelaar Bonga. 1997. The stress response in fish. Physiol. Rev. 77: 591.Yoshimura K. 1986. Biodegradation and fish toxicity of nonionic

surfactants. J. Am. Oil Chem. Soc. 63: 1590–1596.Zikic R, Stajn A, Pavlovic S, Ognjanovic B, Saicic Z. 2001. Activities of

superoxide dismutase and catalase in erythrocytes and plasmatransaminases of goldfish (Carassius auratus gibelio Bloch.) exposedto cadmium. Physiol. Res. 50: 105–111.



761


Derivation of aquatic predicted no-effect concentration (PNEC) for2,4-dichlorophenol: Comparing native species data with non-native species data

Xiaowei Jin a, Jinmiao Zha a, Yiping Xu a, Zijian Wang a,⇑, Satyanarayanan Senthil Kumaran b

a State Key Laboratory of Environmental Aquatic Chemistry, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, P.O. Box 2871, Beijing 100085, Chinab Unit of Toxicology, Bharathiar University, Coimbatore 641 046, India

a r t i c l e i n f o

Article history:Received 12 October 2010Received in revised form 24 March 2011Accepted 7 April 2011Available online xxxx

Keywords:2,4-DichlorophenolChronic toxicityNative speciesPredicted no-effect concentrationSpecies sensitivity distribution

a b s t r a c t

2,4-Dichlorophenol (2,4-DCP) is known as an important chemical intermediate and an environmentalendocrine disruptor. There is no paper dealing with the predicted no-effect concentration (PNEC) of2,4-DCP, mainly due to shortage of chronic and site-specific toxicity data. In the present study, toxicitydata was obtained from the tests using six Chinese native aquatic species. The HC5 (hazardous concen-tration for 5% of species) was derived based on the constructed species sensitivity distribution (SSD),which was compared with that derived from literature toxicity data of non-native species. For inverte-brates, the survival no-observed effect concentrations (NOECs) were 0.05 and 1.00 mg L1 for Macrob-rachium superbum and Corbicula fluminea, respectively. NOECs based on fishes’ growth were 0.10, 0.20and 0.40 mg L1 for Mylopharyngodon piceus, Plagiognathops microlepis and Erythroculter ilishaeformis,respectively. For aquatic plant Soirodela polyrhiza, NOEC based on concentration of chlorophyll was1.00 mg L1. A final PNEC calculated using the SSD approach with a 50% certainty based on different taxaranged between 0.008 and 0.045 mg L1. There is no significant difference between HC5 derived fromnative and that from non-native taxa.

2011 Elsevier Ltd. All rights reserved.

1. Introduction

Chlorophenols are widely used synthetic organic compoundseither used as synthesis intermediates in dyestuffs and pesticidesor as biocides themselves. Chlorophenols commonly occur inindustrial wastes and as direct pollutants in the water environ-ment, which have been frequently detected (Czaplicka, 2004; Gaoet al., 2008). Among them, 2,4-dichlorophenol (2,4-DCP) is themost abundant chlorophenol in aquatic environment (Houseet al., 1997). 2,4-DCP is usually used as a mothproofing agent, ger-micide, antiseptic and precursor in the production of herbicide 2,4-dichlorophenoxyacetate (Zhang et al., 2008). Although 2,4-DCPpresently has no direct commercial application, it is used as animportant chemical intermediate, it is also synthesized from dilute

aqueous solutions, and released into the environment as anintermediate compound from paper mills and chemical industries.2,4-DCP is recognized as a priority pollutant in the aquatic environ-ment in the USA as well as in China due to their high toxicity toaquatic life, resistance to degradation, and potential to be bioaccu-mulated (USEPA, 1979; Yin et al., 2003). It is also been reportedthat 2,4-DCP is an endocrine disruptor (Zhang et al., 2008). In addi-tion, permanent impairment of vision or blindness of the eyes andsevere injury of the upper respiratory tract were observed whilehuman and animals were exposed to 2,4-DCP (USEPA, 2000). Theconcentrations of 2,4-DCP in rivers were less than 1 lg L1 in Uni-ted Kingdom (House et al., 1997) and ranged from 1.1 to19 960 ng L1 in China (Gao et al., 2008). Therefore, the deleteriouseffects and ecological risk of 2,4-DCP on estuarine and coastal eco-systems have raised considerable concern.

An important step in ecological risk assessment of chemicals isthe determination of the maximum concentration at which theecosystem is protected, i.e., the predicted no-effect concentration(PNEC). PNECs are usually derived from laboratory-based toxicitytest (especially for chronic) using well-defined protocols on a lim-ited number of species. Despite the numerous toxicity data of 2,4-DCP available on fish, Daphnia and algae, few have been tested forits adverse effects on the environment on the basis of chronic testsowing to the high financial investment required, especially for lo-cal species in China (Yin et al., 2003). So no final decision was made

0045-6535/$ - see front matter 2011 Elsevier Ltd. All rights reserved.doi:10.1016/j.chemosphere.2011.04.033

Abbreviations: 2,4-DCP, 2,4-dichlorophenol; PNEC, predicted no-effect concen-tration; SSD, species sensitivity distribution; NOEC, no-observed effect concentra-tion; LOEC, lowest observed effect concentration; MATC, maximum allowabletoxicant concentration; CCC, criterion continuous concentration; ACRs, acute tochronic ratios; AF, application factor.⇑ Corresponding author. Address: State Key Laboratory of Environmental Aquatic

Chemistry, Research Center for Eco-Environmental Sciences, Shuangqing Rd. 18,Haidian District, Beijing 100085, China. Tel.: +86 10 6284 9140; fax: +86 10 62923543.

E-mail address: [email protected] (Z. Wang).

Chemosphere xxx (2011) xxx–xxx

Contents lists available at ScienceDirect

Chemosphere

journal homepage: www.elsevier .com/locate /chemosphere

Please cite this article in press as: Jin, X., et al. Derivation of aquatic predicted no-effect concentration (PNEC) for 2,4-dichlorophenol: Comparing nativespecies data with non-native species data. Chemosphere (2011), doi:10.1016/j.chemosphere.2011.04.033


http://dx.doi.org/10.1016/j.chemosphere.2011.04.033

mailto:[email protected]


http://www.sciencedirect.com/science/journal/00456535

http://www.elsevier.com/locate/chemosphere


regarding PNEC derivation for 2,4-DCP. Yin et al. (2003) have de-rived a criterion continuous concentration (CCC) of 0.212 mg L1

for protection of aquatic life in China using acute to chronic ratios(ACRs) (also called application factors, AFs). However, the use ofACRs has been criticized (Chapman et al., 1998; Crane and New-man, 2000; Roex et al., 2000; Isnard et al., 2001). In some cases,average ACRs may be inadequate to extrapolate accurately fromacute to chronic value (Brix et al., 2001; Besser et al., 2005).

The present paper focuses on the derivation of PNECs using thespecies sensitivity distribution (SSD) method (Garay et al., 2000;Hampel et al., 2007; Caldwell et al., 2008; Amorim et al., 2010).Usually a point estimate known as the HC5 (hazardous concentra-tion for 5% of species) is calculated. This is a concentration that willexceed no more than 5% of species effect levels. For this purpose,SSDs are generally constructed by fitting cumulative probabilitydistributions to a plot of species toxicity data against rank-assigned percentile (Van Straalen and Denneman, 1989; Aldenbergand Slob, 1993; Wheeler et al., 2002). The SSD method may resultin more robust PNECs, but only a substantial amount of chronicdata for several taxonomic groups is available, for most new andexisting substances, this type data is lacking (Sijm et al., 2001). Fur-thermore, in most countries, SSD curves and HC5 values are beingused to derive PNECs for toxicants based on local species data orsite-specific data (USEPA, 1985; ANZECC&ARMCANZ, 2000; Yinet al., 2003). The potential use of non-native toxicity data fordescription of local problems is controversial, and leaves one toquestion whether criteria based on species from one geographicalregion provide appropriate protection for species in a differentregion (Davies et al., 1994). However, this argument could not beresolved previously in large part due to the paucity of toxicity dataapplicable for local species.

In the current study, chronic toxicity tests were conducted forsix Chinese native species, including three fish species, two inver-tebrate species and one hygrophyte species. Then, the experimen-tal chronic toxicity data for 2,4-DCP combined with data reportedon native species in the literature were compared with non-nativetaxa using HC5 and values which was calculated by fitting SSDcurves. The aims to this study are (1) a supplement to 2,4-DCPchronic toxicity database, (2) derivation of PNEC for 2,4-DCP, and(3) comparison of the difference between native species and non-native species exposure to 2,4-DCP and discussion of the necessityof native species for the establishment of PNECs for site-specificecological risk assessment.

2. Materials and methods

2.1. Test species and conditions

Six Chinese local species of two benthic invertebrates (Corbiculafluminea and Macrobrachium superbum); three species of fish(Mylopharyngodon piceus, Plagiognathops microlepis and Erythrocul-ter ilishaeformis) and one hygrophyte (Soirodela polyrhiza) were se-lected primarily based on their wide distribution, economicsignificance and adaptability to laboratory conditions. These testspecies were provided by the Huazhong Agricultural University(Wuhan, China), and were acclimated to test conditions(24 ± 1 C, pH 7.24 ± 0.16) for more than 2 weeks prior to theexperiments.

In the experiment, the lowest average dissolved oxygen concen-tration for all the test species were approximately 80% of satura-tion. The pH ranged from 7.4 to 7.9. Conductivity (mmhos cm1)and hardness (as mg L1 CaCO3) averaged 512 and 100, respec-tively during the freshwater tests. Strip chart records of tempera-ture showed that an average temperature of 24 ± 1 C wasmaintained for all tests.

2.2. Test chemical

Analytical grade 2,4-DCP (CAS RN: 120-83-2) with 99.0% puritywas purchased from Sigma (Deisenhofen, Germany). Tap water,dechlorinated with activated carbon, was used for all tests. Thewater quality parameters were measured as follows: pH: 7.24± 0.16; dissolved oxygen concentration (DO): 8.43 ± 0.24 mg L1,total organic carbon (TOC) content: 0.017 mg L1, and total hard-ness: 100 mg L1.

2.3. Exposure of organisms

Chronic exposures of 2,4-DCP to six native species were con-ducted using daily replaced static-renewal diluters. Test solutionswere maintained by renewal of 90% every 24-h. There were fivetreatments (nominal concentration) of test chemical plus a controland three replicates of each treatment, each beaker containing 10test organisms. Test concentrations were chosen based upon theresults of preliminary acute toxicity tests (data not shown). Dis-solved oxygen, conductivity, temperature, pH, and salinity weremeasured every 2 d with a multiparameter water quality meter(YSI Model 85 m; Yellow Springs, OH).

2.3.1. InvertebratesThree week survival tests using M. superbum (39.63 ± 0.47 mm,

0.87 ± 0.08 g) and C. fluminea (20.80 ± 0.20 mm, 3.66 ± 0.40 g) wereconducted in glass container containing 4000 mL and 1000 mL testsolution, respectively. The nominal concentrations for C. flumineaand M. superbum used in the study were 0, 1.00, 2.00, 4.00, 6.00,8.00 mg L1 and 0, 0.05, 0.10, 0.20, 0.30, 0.40 mg L1 2,4-DCP,respectively. Test organisms were fed daily with a solution of mic-roalgae concentrate prepared from instant algae shellfish diet andnannochloropsis concentrate according to standard guidelines forconducting chronic tests with macro invertebrates (ASTM, 1993).During the exposure, beakers were kept in an incubator at24 ± 1 C with 16 L: 8 d photoperiod. Mortality and abnormalbehavior were monitored daily and dead organisms were removedimmediately. At the end of test, the 21 d no-observed effect con-centrations (NOEC) and the lowest observed effect concentrations(LOEC) were derived by analyzing survival rate and behavioral ef-fects of test organisms.

2.3.2. FishTwenty-eight days chronic growth inhibition toxicity test using

early life stages of M. piceus (17.65 ± 0.40 mm, 3.80 ± 0.22 102 g), P. microlepis (16.40 ± 0.37 mm, 2.67 ± 0.19 102 g) andE. ilishaeformis (23.59 ± 0.29 mm, 5.50 ± 0.20 102 g) were donein glass container containing 1000 mL test solution. The nominalconcentrations used in these studies were 0, 0.10, 0.20, 0.40, 0.60and 0.80 mg L1 2,4-DCP for both P. microlepis and E. ilishaeformis,and 0, 0.10, 0.20, 0.40, 0.80, 1.60 mg L1 2,4-DCP for M. piceus.During the exposure, beakers were kept in an incubator at24 ± 1 C with 16 L: 8 d photoperiod, and juvenile fishes were fedwith brine shrimp at a rate of 0.1% body weight twice daily. Atthe end of the test, length and weight of all tested fish weremeasured and survival rate was calculated at each concentration,from which NOEC and LOEC were derived. For fry growth, thespecific growth rate (SGR) was chosen because it is less dependenton the initial size of the fish and on the time between measure-ments than the other endpoint such as relative growth rate(RGR) (Mallett et al., 1997). The SGR was calculated as ((ln(finalmass) ln(initial mass)) 100)/d of exposure (Crossland, 1985).At the end of the chronic toxicity test, all animals survived in thecontrol.

2 X. Jin et al. / Chemosphere xxx (2011) xxx–xxx




2.3.3. Aquatic plantChronic toxicity of S. polyrhiza was conducted in 90 mm glass

crystallizing dish with 200 mL of test medium for 10 d. The nomi-nal concentrations of 2,4-DCP used in the definitive studies were 0,1.00, 5.00, 10.0, 25.0 and 50.0 mg L1. At the end of the test, chlo-rophyll was measured using 7550 ultraviolet and visible spectro-photometer (Zhang and Jin, 1997), from which NOEC and LOECwere derived.

2.4. Chemical analysis

During the acute and chronic toxicity exposure, 2,4-DCP treatedaquarium samples were randomly collected during the experi-ments from control, low, medium, and high dosage concentrations.Triplicate samples were taken from one tank of each concentrationlevel. Samples were spiked with surrogate standard (Biphenol A-d16), adjusted to pH < 2 with 6 lM hydrochloride buffer and en-riched with SPE using C18 cartridge. The cartridges were elutedwith 10 mL dichloromethane (DCM). All of the extracts were evap-orated under a gentle stream of nitrogen. Derivatization was per-formed to reduce the polarity of phenols. The dried residueswere derivatized by bis(trimethylsilyl)trifluoroacetamide (BSTFA)with 1% trimethylchlorosilane (TMCS), which were heated in aheating block at 60 C for 2 h. Samples were maintained at 4 Cin brown polypropylene bottles in the dark until analysis.

The samples were analyzed using an Agilent 6890 gas chro-matograph equipped with Agilent MSD 5975 mass spectrometer.The capillary column of 30 m 0.25 mm i.d. 0.25 lm HP-5 wasused. Gas chromatography (GC) oven temperature was pro-grammed from 40 C to 300 C via a ramp of 10 C min1 and main-tained at 40 C for 2 min and at 300 C for 15 min. Then constantpressure model was used in the whole analysis process. Sampleinjection (1 lL) was in splitless mode. Mass spectrum (MS) wasoperated in full-scan mode from m/z 50–700 for qualitative analy-sis, selected ion monitoring (SIM) mode for quantitative analysis.The inlet and MS transfer line temperatures were maintained at250 C, and the ion source temperature was 300 C. The data ofGC–MS were analyzed by the techniques of RTL and DRS (softwareprovided by Agilent).

2,4-DCP was not detected in control aquaria and in blanks. Mea-sured 2,4-DCP concentrations in the treated test species collectedduring experiments varied from 88.7% to 107.9% of nominal con-centrations (mean 95.1%, n = 72). Therefore, all subsequent chronictoxicity results were expressed on nominal concentrations of 2,4-DCP.

2.5. Statistical analysis

Data on chronic tests were analyzed using the SPSS Version 17software. The experimental data were checked for homogeneity ofvariance across treatments by using Levene’s test. The data weresubjected to one-way analysis of variance followed by Dunnett’smultiple comparison tests once the assumptions were met. Statis-tical significances were considered to be significant at p 6 0.05. TheNOEC was defined as the highest concentration that did not resultin a significant effect compared with the control. The LOEC was de-fined as the lowest concentration that did result in a significant ef-fect compared with the control, The maximum allowable toxicantconcentration (MATC) was equal to the geometric average of NOECand LOEC (USEPA, 1985).

2.6. Data collection and SSD generation

Additional chronic toxicity data for 2,4-DCP were collected fromexisting toxicity databases (e.g. ECOTOX database, http://cfpub.epa.gov/ecotox/), published literature, and government documents

following the principles of accuracy, relevance and reliability(Klimisch et al., 1997). NOECs were calculated from the availableliterature. When a NOEC was not available, MATC or LOEC or ECx

was used and noted. If more than one set of data for the same spe-cies was available, toxicity values for the most sensitive end pointwere chosen. In the case of multiple data on the same endpoint andspecies, the geometric mean was used. Toxicity data were consid-ered ‘‘Native’’ if test organisms occurred in natural ecosystems ofChina and if tests were conducted under local conditions. All localspecies data (including the six native species data in this study andother native data obtained from the literature) were combined andcompared with non-native taxa to 2,4-DCP by fitting SSD curves forchronic toxicity data. Sensitivity distributions were comparedusing the two-sample Kolmogorov–Smirnov test using the SPSSVersion 17 software.

We estimated lower (5% confidence), median (50% confidence),and upper (95% confidence) HC5 using ETX software (ETX 2.0,RIVM) based the method of Aldenberg and Jaworska (2000). Alog-normal distribution model was fitted to a minimum of ten datapoints, with model fit being evaluated using the Anderson–Darlinggoodness-of-fit test. The final PNECs were calculated as the derivedHC5 with a 50% certainty divided by a factor 1–5 (ECB, 2003). Thefactor 1–5, is a qualitatively chosen factor depending on theamount of supporting evidence e.g., multispecies data present,field data, etc.

3. Result

3.1. Chronic toxicity

Six test species showed different sensitivities to 2,4-DCP expo-sure (Table 1).

Results of the 21-d chronic toxicity test showed that M. super-bum was more sensitive than C. fluminea to the exposure of 2,4-DCP based on endpoint of survival. The NOEC of the two aquaticorganisms were 0.05 mg L1 and 1.00 mg L1; and their LOECswere 0.10 mg L1 and 2.00 mg L1, respectively. The calculatedMATC for both species were 0.07 mg L1 and 1.41 mg L1,respectively.

In 28-d chronic growth inhibition toxicity test on early lifestages of M. piceus, P. microlepis and E. ilishaeformis, all animals sur-vived at the end of tests, and the juvenile mean specific growthrates were 3.85%, 5.83% and 2.96% per day in the control, respec-tively. For M. piceus, the 0.20 mg L1 and above treatments weresignificantly reduced the juvenile specific growth rates (p < 0.05;ANOVA; Fig. 1A). For P. microlepis, juvenile specific growth ratesin the 0.40 mg L1 and above treatments were significantly lowerthan that in the control (Fig. 1B). For E. ilishaeformis, the critical va-lue was 0.60 mg L1 (Fig. 1C). Based on the statistical analysis,NOECs for growth inhibition were 0.10 mg L1, 0.20 mg L1 and0.40 mg L1, their LOECs were 0.20 mg L1, 0.40 mg L1 and0.60 mg L1, and the calculated MATC were 0.14 mg L1,0.28 mg L1 and 0.49 mg L1 for M. piceus, P. microlepis and E. ilis-haeformis, respectively.

The results of 10-d toxicity test with S. polyrhiza showed thatthe chlorophyll content decreased gradually with increasing 2,4-DCP exposure concentrations (Fig. 2). The chlorophyll content re-duced to 96.3% from the control at exposure concentrations of1.00 mg L1, and to 30.4% at 50.0 mg L1. The calculated NOEC,LOEC and MATC were 1.00 mg L1, 5.00 mg L1 and 2.50 mg L1,respectively.

3.2. Comparison of HC5 derived from native and non-native taxa

A total of 12 (six from this study and six gained from literature)chronic toxicity data based on the native species were collected,

X. Jin et al. / Chemosphere xxx (2011) xxx–xxx 3



http://cfpub.epa.gov/ecotox/



including six fishes, four invertebrates, one planktonic algae andone hygrophyte. Ten chronic NOEC (or LOEC) values were foundfrom database and literature that based on non-native taxa, amongthem three data points were from fish taxa, six from invertebrates,and one from hygrophyte, respectively (showed in Table 1). Log-normal distribution was fitted to both native and non-nativechronic datasets. The calculated results are given in Table 2. Themedian HC5 of chronic data for native and non-native taxa are verysimilar, and the differences of sensitivity distribution for nativeand non-native species were not statistically significant(Kolmogorov–Smirnov test: ks = 0.895, n1 = 12, n2 = 10, p = 0.399)(Fig. 3). Combined native species toxicity data for 2,4-DCP withthose of non-native, a median HC5 of 0.045 (0.021–0.077) mg L1

was calculated. This result was approximately equaled to medianHC5 derived from toxicity data of native or non-native taxa sepa-rately. The differences of sensitivity distribution for native taxa(ks = 0.486, n1 = 22, n2 = 12, p = 0.972) and non-native taxa(ks = 0.548, n1 = 22, n2 = 10, p = 0.925) were also not statisticallysignificant (Fig. 3).

Results of the calculations of PNECs can be seen in Table 2.

4. Discussion

Results of the present study indicate that 2,4-DCP is highly toxicto native freshwater aquatic organisms. Among different species,the fishes were more sensitive than aquatic macro invertebrates,the hygrophytes were the least sensitive. For individual species,C. fluminea is less sensitive than M. superbum that may be due tothe presence of protective shell. The three juvenile fish have simi-lar sensitivities during chronic exposure mainly because they be-long to the same family (Cyprinidae). Comparing the presentresults with previous studies, it reveals that NOEC value of 2,4-DCP for three tested fishes (0.10–0.40 mg L1) were close to theNOEC value (0.10–0.50 mg L1) to other members in Cyprinidae(Yin et al., 2003; Zhang et al., 2008). The chronic toxicity of theshrimp, bivalve and aquatic plant cannot be compared with previ-ous studies due to lack of chronic toxicity data for other local spe-

cies in China. Similar comparisons were conducted for results ofchronic tests based on native and non-native species. For fish,the results showed that the NOECs derived from the native species(Table 1) ranged from 0.10 mg L1 to 0.40 mg L1 that were consis-tent with those from non-native species including Oryzias latipes,Pimephales promelas and Oncorhynchus mykiss, whose NOECs are0.32 mg L1, 0.29 mg L1 and 0.18 mg L1, respectively (USEPA,2002). The native shrimp, M. superbum was more sensitive thannon-native shrimp with NOECs ranged from 0.10 mg L1 to1.00 mg L1 (Table 1). For aquatic plant, it is reported that 10-dNOEC for Lemna gibba was 1.50 mg L1 based on reduction in fronddensity, which is similar to that observed in present work(1.00 mg L1). In general, there is no significant difference for NOE-Cs derived from native species from that of non-native species ex-cept for the shrimp.

In general, European or North American species are being pri-marily used for environmental hazard assessment of freshwaterenvironments due to standardized testing protocol. Fewer toxicitydata is available for native species. The relevance of using one geo-graphical region to assess the hazard posed to species in a differentregion has been questioned (Davies et al., 1994), and differences inthe sensitivity of cold-water, temperate, and tropical fish specieshave been reported previously (Dyer et al., 1997). From the resultsof this study, there were no significant differences betweenChinese native freshwater organisms and non-native species forchronic 2,4-DCP exposure. From a global perspective, studies haveshown similar sensitivities between Australian and non-Australianorganisms exposed to endosulfan based on calculated HC5 (Hoseand Van den Brink, 2004). Dyer et al. (1997) and Maltby et al.(2002) showed similar sensitivities among North American andEuropean taxa with different geographic distributions. Maltbyet al. (2005) also noted that the habitat and geographical distribu-tion of the species used to construct the SSD do not have a signif-icant influence on the assessment of hazard, but the taxonomiccomposition of the species assemblage does.

The derivation of PNEC in EU risk assessment usually uses eitherthe application of an assessment factor of 10–1000 on the lowestNOEC or the HC5 (based in the SSD approach) divided by a factor

Table 1Summary of chronic toxicity data for exposure of native and non-native taxa to 2,4-dichlorophenol.

Family Species Time (d) Endpoint Measurement Con. (mg L1) Reference

Native taxaBufonidae Bufo bufo gargarizans 30 NOEC Growth 0.50 Yin et al. (2003)Corbiculidae Corbicula fluminea 21 NOEC Survival 1.00 In this studyDaphnidae Daphnia magna 14 NOEC Reproduction 0.40 Yin et al. (2003)Palaemonidae Macrobrachium superbum 21 NOEC Survival 0.05 In this studyCyprinidae Mylopharyngodon piceus 28 NOEC Growth 0.10 In this study

Plagiognathops microlepis 28 NOEC Growth 0.20 In this studyErythroculter ilishaeformis 28 NOEC Growth 0.40 In this studyCarassius auratus 30 NOEC Survival 0.25 Yin et al. (2003)Ctenopharyngodon idellus 60 NOEC Survival 0.50 Yin et al. (2003)Gobiocypris rarus 21 NOEC Reproduction 0.10 Zhang et al. (2008)

Lemnaceae Soirodela polyrhiza 10 NOEC Chlorophyll 1.00 In this studyScenedesmaceae Scendesmus obliquus 4 NOEC Growth 5.00 Yin et al. (2003)

Non-native taxaAstacoidea Cambarus robustus 10 NOEC Glucose 0.10 ECOTOXCambaridae Cambaridaea 10 NOEC Survival 1.00 ECOTOXCambaridae Orconectes propinquus 10 NOEC Glucose 0.10 ECOTOXCalanoida Calanoidaa 26 NOEC Development 0.30 ECOTOXDogielinotidae Allorchestes compressa 4 NOEC Survival 0.075 ECOTOXUnionidae Unio tumidus 3 LOEC Enzymes 0.10 ECOTOXAdrianichthyidae Oryzias latipes 40 NOEC Survival 0.32 ECOTOXCyprinidae Pimephales promelas 32 NOEC Survival 0.29 ECOTOXSalmonidae Oncorhynchus mykiss 85 NOEC Growth 0.18 ECOTOXLemnoideae Lemna gibba 10 NOEC Growth 1.50 ECOTOX

a Species names of these two organisms were not specified in ECOTOX database. Because of most of species in the family distribute in North America and the test conductedunder non-local conditions, toxicity data of these two species defined as non-native.





of 1–5, depending upon the additional data present such as multi-species test and field test (ECB, 2003). Assessment factors are rec-ognized as a conservative approach for dealing with uncertainty inassessing risks posed by chemicals (Chapman et al., 1998). It hasbeen also noted that current applications of safety factors arebased on policy rather than on empirical science and that they re-sult in values that are protective, but not predictive. Specificallyaddressing ACRs, Chapman et al. (1998) cited studies showing thatmeasured ACRs can vary from 1 to 20 000. In view of this, it isunreasonable to apply a generic factor (whether of 10 or someother magnitude) across species and across substances. In the pres-

ent study, a CCC of 0.212 mg L1 derived based on ACRs (Yin et al.,2003) could not provide enough protection to native M. superbum,M. piceus and P. microlepis, their NOEC being 0.05 mg L1,0.10 mg L1, 0.20 mg L1, respectively. In this study, the PNEC ran-ged from 0.008 to 0.045 mg L1 using the SSD approach with a 50%certainty based on different taxa. In spite of violations of someassumptions (OECD, 1995) and disadvantages (Posthuma et al.,2002), SSD methods still have many advantages over AF methodsin criteria derivation. Of particular importance to risk managersis the ability to select appropriate percentile levels and confidence

2,4-dichlorophenol Concentrations (mg L -1)

Spec

ific

Gro

wth

Rat

e (%

/day

)

0

1

2

3

4

5

Control 0.10 0.20 0.40 0.80 1.60

Control 0.10 0.20 0.40 0.60 0.80

Control 0.10 0.20 0.40 0.60 0.80

**

**

* *

0

1

2

3

4

5

6

7

* * *

0.0

.5

1.0

1.5

2.0

2.5

3.0

3.5

*

*

A

B

C

Fig. 1. Effect of 28-d exposure to 2,4-dichlorophenol on early life stages of M. piceus(A), P. microlepis (B) and E. ilishaeformis (C) specific growth rate. Data are presentedas means ± standard deviation (SD). ⁄ and ⁄⁄ significant differences from the valuesof the control at p < 0.05 and p < 0.01, respectively.

2,4-dichlorophenol Concentrations (mg L-1)

Chl

orop

hyll

Con

tent

(m

g g-1

)

0.0

.2

.4

.6

.8

1.0

Control 1.00 5.00 10.0 25.0 50.0

**

****

Fig. 2. Effect of 10-d exposure to 2,4-dichlorophenol on chlorophyll content inSoirodela polyrhiza. Data are presented as means ± standard deviation (SD). ⁄ and ⁄⁄significant differences from the values of the control at p < 0.05 and p < 0.01,respectively.

Table 2Parameters of species sensitivity distributions for 2,4-dichlorophenol based on nativeand non-native species toxicity data.

Toxicitydata

n Mean(mg L1)

Standarddeviation

Median HC5 PNEC(mg L1)

Native data 12 0.79 1.36 0.044 (0.012–0.097) 0.009–0.044Non-native

data10 0.40 0.47 0.042 (0.012–0.084) 0.008–0.042

All data 22 0.61 1.05 0.045 (0.021–0.077) 0.009–0.045

2,4-dichlorophenol Concentrations (mg L-1)101.1.01

Pot

enti

ally

Aff

ecte

d P

erce

ntag

e (%

)

0

10

20

30

40

50

60

70

80

90

100

Native taxaNon-native taxaAll taxa

Fig. 3. Species sensitivity distribution of chronic toxicity data for 2,4-dichlorophenol.

X. Jin et al. / Chemosphere xxx (2011) xxx–xxx 5




levels, which is not possible by the AF method. So far, PNECs de-rived from SSDs have proven to be protective for ecosystems. How-ever, a major limitation is the scarcity of suitable toxicity data,particular for site-specific chronic data. It is recommended thatat least 10–15 toxicity data (depending on the toxicant) are neces-sary to improve precision (Wheeler et al., 2002). From the result ofthis study, there were no significant difference between native andnon-native taxa for HC5 and sensitivity distributions of freshwaterorganisms to chronic 2,4-DCP exposure. Therefore, PNECs can bederived using SSD methods with combined data from native site-specific toxicity data and non-native toxicity data in hazard assess-ment of 2,4-DCP.

5. Conclusion

This study is a contribution in the assessment of the effect of2,4-dichlorophenol in the aquatic environment, where limitedsite-specific chronic data existed. 2,4-DCP caused different levelsof toxicity to various organisms, in which fishes and macro inver-tebrates were more sensitive than hygrophytes. Comparing thesensitivity distributions and HC5s, there were no significant differ-ence between native species and non-native species. It indicatesthat data for organisms from different geographic region can beused in estimating PNEC for ecological risk assessment of 2,4-DCP. Furthermore, the PNEC derived using SSD method is moreprecise and stable than AF method when the amount of chronictoxicity data increases.

Acknowledgements

This research was financially supported by Chinese Academy ofScience (KZCX2-YW-Q02-06), Ministry of Environmental Protec-tion of the People’s Republic of China (201009032) and Natural Sci-ence Foundation of China (20737003).

References

Aldenberg, T., Jaworska, J.S., 2000. Uncertainty of the hazardous concentration andfraction affected for normal species sensitivity distributions. Ecotoxicol.Environ. Saf. 46, 1–18.

Aldenberg, T., Slob, W., 1993. Confidence-limits for hazardous concentrations basedon logistically distributed NOEC toxicity data. Ecotoxicol. Environ. Saf. 25, 48–63.

Amorim, M.J.B., Oliveira, E., Soares, A.M.V.M., Scott-Fordsmand, J.J., 2010. Predictedno effect concentration (PNEC) for triclosan to terrestrial species (invertebratesand plants). Environ. Int. 36, 338–343.

ANZECC&ARMCANZ, 2000. Australian and New Zealand Guidelines for Fresh andMarine Water Quality. Australian and New Zealand Environment andConservation Council and Agriculture and Resource Management Council ofAustralia and New Zealand, Canberra, Australia.

ASTM, 1993. Standard Guide for Conducting Acute Toxicity Tests with Fishes,Macroinvertebrates and Amphibians. Annual Book of ASTM Standards.American Society of Testing and Materials, Philadelphia, PA, USA, pp. 88–729.

Besser, J.M., Wang, N., Dwyer, F.J., Mayer, F.L., Ingersoll, C.G., 2005. Assessingcontaminant sensitivity of endangered and threatened aquatic species: part II.Chronic toxicity of copper and pentachlorophenol to two endangered speciesand two surrogate species. Arch. Environ. Contam. Toxicol. 48, 155–165.

Brix, K.V., DeForest, D.K., Adams, W.J., 2001. Assessing acute and chronic copperrisks to freshwater aquatic life using species sensitivity distributions fordifferent taxonomic groups. Environ. Toxicol. Chem. 20, 1846–1856.

Caldwell, D.J., Mastrocco, F., Hutchinson, T.H., Lange, R., Heijerick, D., Janssen, C.,Anderson, P.D., Sumpter, J.P., 2008. Derivation of an aquatic predicted no-effectconcentration for the synthetic hormone, 17 alpha-ethinyl estradiol. Environ.Sci. Technol. 42, 7046–7054.

Chapman, P.M., Fairbrother, A., Brown, D., 1998. A critical evaluation of safety(uncertainty) factors for ecological risk assessment. Environ. Toxicol. Chem. 17,99–108.

Crane, M., Newman, M.C., 2000. What level of effect is a no observed effect?Environ. Toxicol. Chem. 19, 516–519.

Crossland, N.O., 1985. A method to evaluate effects of toxic chemicals on fishgrowth. Chemosphere 14, 1855–1870.

Czaplicka, M., 2004. Sources and transformations of chlorophenols in the naturalenvironment. Sci. Total Environ. 322, 21–39.

Davies, P.E., Cook, L.S.J., Goenarso, D., 1994. Sublethal responses to pesticides ofseveral species of Australian fresh-water fish and crustaceans and rainbow-trout. Environ. Toxicol. Chem. 13, 1341–1354.

Dyer, S.D., Belanger, S.E., Carr, G.J., 1997. An initial evaluation of the use of Euro/North American fish species for tropical effects assessments. Chemosphere 35,2767–2781.

ECB, 2003. Technical Guidance Document on Risk Assessment in Support ofCommission Directive 93/67/EEC on Risk Assessment for New NotifiedSubstances, Commission Regulation (EC) No. 1488/94 on Risk Assessment forExisting Substances, Directive 98/8/EC of the European Parliament and of theCouncil Concerning the Placing of Biocidal Products on the Market. Part II.Environmental Risk Assessment. European Chemicals Bureau, EuropeanCommission Joint Research Center, European Communities.

Gao, J.J., Liu, L.H., Liu, X.R., Zhou, H.D., Huang, S.B., Wang, Z.J., 2008. Levels andspatial distribution of chlorophenols 2,4-dichlorophenol, 2,4,6-trichlorophenol,and pentachlorophenol in surface water of China. Chemosphere 71, 1181–1187.

Garay, V., Roman, G., Isnard, P., 2000. Evaluation of PNEC values: extrapolation frommicrotox (R), algae, daphnid, and fish data to HC5. Chemosphere 40, 267–273.

Hampel, M., Gonzalez-Mazo, E., Vale, C., Blasco, J., 2007. Derivation of predicted noeffect concentrations (PNEC) for marine environmental risk assessment:application of different approaches to the model contaminant linearalkylbenzene sulphonates (LAS) in a site-specific environment. Environ. Int.33, 486–491.

Hose, G.C., Van den Brink, P.J., 2004. Confirming the species-sensitivity distributionconcept for endosulfan using laboratory, mesocosm, and field data. Arch.Environ. Contam. Toxicol. 47, 511–520.

House, W.A., Leach, D., Long, J.L.A., Cranwell, P., Smith, C., Bharwaj, L., Meharg, A.,Ryland, G., Orr, D.O., Wright, J., 1997. Micro-organic compounds in the Humberrivers. Sci. Total Environ. 194, 357–371.

Isnard, P., Flammarion, P., Roman, G., Babut, M., Bastien, P., Bintein, S., Essermeant,L., Ferard, J.F., Gallotti-Schmitt, S., Saouter, E., Saroli, M., Thiebaud, H.,Tomassone, R., Vindimian, E., 2001. Statistical analysis of regulatoryecotoxicity tests. Chemosphere 45, 659–669.

Klimisch, H.J., Andreae, M., Tillmann, U., 1997. A systematic approach for evaluatingthe quality of experimental toxicological and ecotoxicological data. Regul.Toxicol. Pharm. 25, 1–5.

Mallett, M.J., Grandy, N.J., Lacey, R.F., 1997. Interlaboratory comparison of a methodto evaluate the effects of chemicals on fish growth. Environ. Toxicol. Chem. 16,528–533.

Maltby, L., Blake, N., Brock, T.C.M., Van den Brink, P.J., 2002. Addressing InterspecificVariation in Sensitivity and the Potential to Reduce this Source of Uncertainty inEcotoxicological Assessments. DEFRA Project Code PN0932. UK Department forEnvironment, Food and Rural Affairs, London, UK.

Maltby, L., Blake, N., Brock, T.C.M., Van Den Brink, P.J., 2005. Insecticide speciessensitivity distributions: importance of test species selection and relevance toaquatic ecosystems. Environ. Toxicol. Chem. 24, 379–388.

OECD, 1995. Guidance document for aquatic effect assessment. In: Organization forEconomic Co-operation and Development (Ed.), Paris.

Posthuma, L., Suter, G.W., Traas, T.P., 2002. Species Sensitivity Distributions inEcotoxicology. Lewis Publishers, CRC Press, Boca Raton, FL.

Roex, E.W.M., Van Gestel, C.A., Van Wezel, A.P., Van Straalen, N.M., 2000. Ratiosbetween acute aquatic toxicity and effects on population growth rates inrelation to toxicant mode of action. Environ. Toxicol. Chem. 19, 685–693.

Sijm, D., De Bruijn, J., Crommentuijn, T., Van Leeuwen, K., 2001. Environmentalquality standards: endpoints or triggers for a tiered ecological effect assessmentapproach? Environ. Toxicol. Chem. 20, 2644–2648.

USEPA, 1979. Toxic Pollutant Effluent Standards. 40 CFR 401.15. US EnvironmentalProtection Agency, Washington, DC.

USEPA, 1985. Guidelines for Deriving Numerical National Water Quality Criteria forthe Protection of Aquatic Organisms and Their Uses. National TechnicalInformation Service Accession Number PB85-227049. US EnvironmentalProtection Agency, Washington, DC.

USEPA, 2000. Chemical Advisory and Notice of Potential Risk: Skin exposure tomolten 2,4-Dichlorophenol can Cause Rapid Death. pp. 1–13.

USEPA, 2002. US Environmental Protection Agency, ECOTOX Database. US EPA,Washington, DC. <http://cfpub.epa.gov/ecotox/>.

Van Straalen, N.M., Denneman, C.A.J., 1989. Ecotoxicological evaluation of soilquality criteria. Ecotoxicol. Environ. Saf. 18, 241–251.

Wheeler, J.R., Grist, E.P.M., Leung, K.M.Y., Morritt, D., Crane, M., 2002. Speciessensitivity distributions: data and model choice. Mar. Pollut. Bull. 45, 192–202.

Yin, D., Hu, S., Jin, H., Jin, Hongjun, 2003. Deriving freshwater quality criteria for2,4,6-trichlorophenol for protection of aquatic life in China. Chemosphere 52,67–73.

Zhang, T., Jin, H.J., 1997. Use of duckweed (Lemna minor L.) growth inhibition test toevaluate the toxicity of acrylonitrile, sulphocyanic sodium and acetonitrile inChina. Environ. Pollut. 98, 143–147.

Zhang, X.Y., Zha, J.M., Li, W., Yang, L.H., Wang, Z.J., 2008. Effects of 2,4-dichlorophenol on the expression of vitellogenin and estrogen receptor genesand physiology impairments in Chinese rare minnow (Gobiocypris rarus).Environ. Toxicol. 23, 694–701.






JOURNAL OFENVIRONMENTALSCIENCES

ISSN 1001-0742

CN 11-2629/X

www.jesc.ac.cn

Available online at www.sciencedirect.com

Journal of Environmental Sciences 2012, 24(2) 1–10

Assessment of source water contamination by estrogenic disruptingcompounds in China

Weiwei Jiang1, Ye Yan1, Mei Ma1,∗, Zijian Wang1, Senthil Kumaran Satyanarayanan2

1. Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China. E-mail: jiang [email protected]. Unit of Toxicology, Bharathiar University, Coimbatore 641046, India

Received 24 March 2011; revised 11 May 2011; accepted 13 May 2011

AbstractDetection of estrogenic disrupting compounds (EDCs) in drinking waters around China has led to rising concerns about health risksassociated with these compounds. There is, however, a paucity of studies on the occurrence and identification of the main compoundsresponsible for this pollution in the source waters. To fill this void, we screened estrogenic activities of 23 source water samples fromsix main river systems in China, using a recombinant two-hybrid yeast assay. All sample extracts induced significant estrogenic activity,with E2 equivalents (EEQ) of raw water ranging from 0.08 to 2.40 ng/L. Additionally, 16 samples were selected for chemical analysisby gas chromatography-mass spectrometry. The EDCs of most concern, including estrone (E1), 17β-estradiol (E2), 17α-ethinylestradiol(EE2), estriol (E3), diethylstilbestrol (DES), estradiol valerate (EV), 4-t-octylphenol (4-t-OP), 4-nonylphenols (4-NP) and bisphenolA (BPA), were determined at concentrations of up to 2.98, 1.07, 2.67, 4.37, 2.52, 1.96, 89.52, 280.19 and 710.65 ng/L, respectively.Causality analysis, involving comparison of EEQ values from yeast assay and chemical analysis identified E2, EE2 and 4-NP as themain responsible compounds, accounting for the whole estrogenic activities (39.74% to 96.68%). The proposed approach using bothchemical analysis and yeast assay could be used for the identification and evaluation of EDCs in source waters of China.

Key words: source water, estrogenic disrupting compounds, yeast assay, bioassay

DOI: 10.1016/S1001-0742(11)60746-8

Introduction

Due to the adverse biological effects of estrogenic disrupt-ing compounds (EDCs) in animals, there are increasingconcerns that low-level exposure to these compoundsmight cause similar effects in humans (Damstra et al.,2002). Changes in sex and reproductive ability in aquaticanimals are an indication that many environmental pollu-tants could act as EDCs (Sumpter, 1997). Pharmaceuticals,waste water plant effluents, agricultural fertilizers and fishfarming wastes are important man-made sources of theseenvironmental pollutants (Yamazaki, 1983; Desbrow etal., 1998; Tashiro et al., 2003). Moreover, they are notcompletely removed by many conventional water treat-ment processes, such as chlorination, coagulation, andsedimentation (Kuch and Ballschmiter, 2001; Magi et al.,2010). Estrogenic activity has been detected in effluentsof drinking water treatment plants (DWTP) in China,resulting in increased risks to human health (Rao et al.,2004; Wang et al., 2005; Luo et al., 2006). An additionalproblem is the absence of water quality threshold standardswith regard to estrogenic activity in drinking water inChina (MOH, 2006). It is therefore necessary to monitorEDCs levels in source water so as to evaluate the risks

* Corresponding author. E-mail: [email protected]

to humans, protect the ecosystem, and to provide usefulinformation for drinking water treatment.

To screen estrogenic activity in the environment, anumber of biological tools have been developed. In vitrobioassays that requires low equipments and has highsensitivities levels have been developed as rapid toolsfor screening the toxicity of chemical or environmentalsamples (Campbell et al., 2006). Knowledge of the com-position profiles of sample is not required for in vitrobioassays, which are useful for rapid and reliable iden-tification of estrogenic activity of environmental samplesor for sampling in the event of pollution emergencies.Among these bioassays, the yeast assay has been suc-cessfully applied for determining estrogenic activity ofchemicals or environmental samples (Vermeirssen et al.,2005). The composition profiles of the samples and thecompounds responsible for the estrogenic activity arenot, however, determined via bioassays. This informationis necessary to the removal of pollutants or for envi-ronmental remediation (Augulyte and Bergqvist, 2007).Combined in vitro bioassays and chemical analysis toolshave, therefore, now been recognized as effective methodsfor screening estrogenic chemicals and for environmentalrisk assessments (Reineke et al., 2002; Matthiessen et al.,2006). Chemical analytical methods, using gas (or liquid)


2 Journal of Environmental Sciences 2012, 24(2) ??–?? /Weiwei Jiang et al. Vol. 24

chromatography-mass spectrometry (GS-MS or LC-MS)combined with solid phase extraction (SPE) for deter-mining concentrations of EDCs in water, have proved tobe very useful complementary methods associated withbioassays (Kasprzyk-Hordern et al., 2008; Jonkers et al.,2010).

Several works pertaining to the investigation of estro-genic disrupting compounds in surface waters of Chinamake use of bioassays and chemical analysis. Nine com-pounds of natural and anthropogenic origin are consideredin the present study: estrone (E1), 17β-estradiol (E2),17α-ethinylestradiol (EE2), estriol (E3), diethylstilbestrol(DES), estradiol valerate (EV), 4-t-octylphenol (4-t-OP),4-nonylphenols (4-NP) and bisphenol A (BPA). Theserepresent the most frequently discovered EDCs in waterbodies in China (Zhao et al., 2009; Lu et al., 2010). Itshould be noted, however, that few studies on estrogenicactivity in source waters, and the compounds involvedin such activity, have been undertaken in China. The E2equivalent (EEQ) approach, which has been proved to beeffective in the identification of EDCs in water, was intro-duced in the present study (Ra et al., 2011). By assessingcausal links between activities observed by means of bioas-say and chemical levels by chemical analysis, the relevantestrogenic compounds can be identified. The aim of thepresent work was therefore to screen estrogenic activitylevels in 23 source waters in China, and to attempt toidentify specific compounds responsible for such activity,to provide useful information for source water protectionand drinking water treatment.

1 Materials and methods

1.1 Chemicals and materials

Target compounds E1, E2, EE2, E3, DES, EV, 4-t-OP,4-NP, and surrogate compounds E2-d3, BPA-d16 andsolvent dimethyl sulfoxide (DMSO), all of which hadpurity levels higher than 98%, were purchased fromSigma-Aldrich (USA). The derivatization reagent N,O-Bis(trimethylsilyl)trifluoroacetamide (BSTFA) with 1%trimethylchlorosilane (TMCS) was purchased from Supel-co (USA). All reagents of HPLC grade used (methanol,n-hexane, dichloromethane, methyl tertiary butyl ether)were obtained from J. T. Baker (USA). Water used in allexperiments was prepared by means of a Milli-Q waterpurification system (Millipore, USA). Stock solutions ofchemicals (2 mg/L) were prepared in n-hexane and storedat –20°C. Oasis hydrophilic lipophilic balance (HLB) car-tridges (N-vinylpyrrolidone-m-divinylbenzene copolymer,500 mg, 6 mL), obtained from Waters Corporation (USA)were used for solid phase extraction (SPE). Glass fiberfilters (APFF, pore size 0.45 µm) were purchased fromMillipore (USA) and pyrolyzed at 450°C for 4 hr prior touse.

1.2 Sample collection

Samples from 23 source waters, including reservoirs andrivers that supply water to local waterworks, were collected

Table 1 Site information

Site Type Coordinate

Songhua Rivera

S1 River 126.501E, 45.764NS2 Reservoir 127.697E, 44.399N

Liao RiverS3b Reservoir 124.101E, 41.886NS4b Reservoir 125.404E, 41.292N

Hai RiverS5 Reservoir 116.840E, 40.490N

Yangtze RiverS6b River 106.449E, 29.597NS7b River 106.554E, 29.570NS8b River 106.529E, 29.508NS9b River 118.694E, 31.994NS10b River 118.798E, 32.142NS11b River 118.717E, 32.049NS12b Lake 120.223E, 31.517NS13b Reservoir 121.357E, 31.492NS14b River 121.308E, 30.974NS15b Reservoir 121.710E, 31.420N

Huai RiverS16b River 117.173E, 34.401NS17b River 118.950E, 33.586NS18b River 119.000E, 33.625NS19b River 118.972E, 33.509N

Pearl RiverS20b Reservoir 114.603E, 23.794NS21b Reservoir 113.259E, 23.807NS22b Reservoir 114.149E, 22.571NS23b River 110.419E, 19.885N

a River system; b selected for chemical analysis.

between March 2010 and July 2010 (Table 1). The studyarea covered six out of the seven main river systems ofChina.

Samples (20 L for bioassay and 4 L for chemicalanalysis) were collected in pre-cleaned amber glass bottles.Prior to sample collection, the bottles were washed threetimes with water samples. To minimize contaminationof samples, throughout sample collection and processing,use of personal care items and pharmaceuticals werediscouraged. Immediately after sampling, an appropriateamount of methanol (2 mL/L in water sample) was addedto the 20 L samples to be used for bioassay, to suppresspossible biotic activities. Samples were stored at 4°C priorto treatment and were treated and prepared within 48 hr.

1.3 Sample preparation

Water samples were filtered through pre-baked glass fiberfilters to remove insoluble materials and extracted usingthe SPE method. Two litter source water sample (part 1)for chemical analysis for six estrogens (E1, E2, EE2,E3, DES and EV) was spiked with E2-d3, another 2 L(part 2) for chemical analysis for 4-t-OP, 4-NP and BPAwas spiked with BPA-d16. Samples were extracted usingHLB solid phase extraction cartridges, that had been pre-conditioned with 5 mL dichloromethane (5 mL methyltert-butyl ether for part 1), 5 mL methanol and 5 mLwater. During extraction, the cartridges were forced undervacuum at a flow rate of approximately 6 mL/min, and thenkept under vacuum aspiration for 5 min to dry the residualwater. In the end, the cartridges for chemicals analysis


No. 2 Assessment of source water contamination by estrogenic disrupting compounds in China 3

were eluted three times with 10 mL methyl tert-butylether for part 1 and 10 mL dichloromethane for part 2,respectively. Cartridge for bioassay was eluted three timeswith 5 mL dichloromethane. The elution was filtered byanhydrous sodiumsulfate to remove water and evaporatedto 2 mL in a rotary evaporator (R-200, Buchi, Switzerland)at 40°C. Then 2 mL extract was blown down to drynessunder a nitrogen stream and was reconstituted to 0.5 mLwith n-hexane (for chemical analysis) and 0.2 mL withDMSO (for bioassay) immediately. Procedural blank usingpurified water was also run alongside the samples as anassay control.

1.4 Yeast assay

The yeast assay was carried out as described previouslyby our research group with some modifications (Li etal., 2010). Shortly, the assay encompassed an exponentialgrowth at 30°C, 130 r/min overnight yeast strain as dilutedwith synthetic dextrose/-Leu/-Trp medium (SD medium)to an optical density of 0.75 at 600 nm (OD600). Allsamples were assayed with a minimum in triplicate. Eachassay group included a positive control (E2) and a negativecontrol (DMSO). Procedural blank samples, were alsorun alongside the samples to monitor any false positiveresults. The effects of estrogenic compounds and watersamples were standardized against E2. Each sample wasserially diluted in DMSO in a 1:2 series for a total offour concentrations. Five microlitter of serial dilutions ofsamples tested were combined with 995 µL of medium,which contained approximately 5 × 103 yeast cells/mL,resulting in a test culture in which the volume of DMSOdid not exceed 0.5% of the total volume. The test culturesample of 200 µL were transferred into each well of the96-well plate and incubated at 30°C with vigorous orbitalshaking (800 r/min) on a titer plate shaker for 2 hr, afterwhich the OD600 was measured. The volume of extractin each well represented 100 mL raw water. A volumeof 150 µL was then removed from test cultures, and 120µL test buffer and 20 µL chloroform were added to theremaining 50 µL of the cultures. The cultures were mixedcarefully (vortex 25 sec) and pre-incubated for 10 minat 30°C, 1300 r/min. The enzyme reaction was triggeredby adding 40 µL o-nitrophenyl-β-D-galactopyranoside, 4mg/mL test buffer, and incubated at 30°C, 800 r/min on atiter plate shaker. One hundred microlitter sodium carbon-ate of 106 g/L was then added to terminate the reactionswithin 60 min, after which 200 µL of the supernatantwas transferred to a new 96-well plate and the opticaldensity measured at 420 nm (OD420). To ensure that theactivities taking place in the bioassay were caused bytrue antagonistic responses and not cytotoxicity, the cellviability was also measured. After exposure, cell viabilitywas determined spectrophotometrically as a change inOD600 in the assay medium. The β-galactosidase activitywas calculated according to equations described previouslyby Gaido et al. (1997). Concentrations of a given chemicalthat caused significant cytotoxicity were excluded from thecalculation, to ensure that the potency classification wasnot biased by cytotoxicity.

1.5 Instrumental analysis

The residues of water samples were redissolved in 0.4mL of hexane that contained 50 µL of the derivatizationmixture BSTFA/TCMS (99/1, V/V) and 1 mmol/mL ofpyrene-d10. The derivatization was performed at 60°C for2 hr. The derivatives were cooled at room temperature andstored at 4°C.

Instrumental analysis was performed within two days.The targets in the samples were detected by using anAgilent 6890 gas chromatograph equipped with an AgilentMSD 5975 mass spectrometer (USA). System control anddata acquisition were achieved with ChemStation Software(USA). The capillary column of 30 m × 0.25 mm i.d. 0.25µm DB-5 was applied. Before analyzing samples, retentiontime was locked by changing column pressure, followed bythe use of a constant pressure model in the whole analysisprocess. For part 1, the GC oven temperature programswere as follows: the initial temperature of 80°C was heldfor 1 min, then increased to 200°C at a rate of 20°C/min,t to 300°C at a rate of 10°C/min, and then held for 10min, with a total run time of 27 min. For part 2, the GCoven temperature was programmed from 40 to 300°C viaa ramp of 10°C/min and maintained at 40°C for 1 min andthen at 300°C for 15 min. The MS was operated in selectedion monitoring (SIM) mode for quantitative analysis. Theinlet and MS transfer line temperatures were maintained at300°C (250°C for part 2), and the ion source temperaturewas 230°C (300°C for part 2). Sample injection (1 µL) wasin splitless mode. In order to ensure the accuracy of theanalysis, all of the assays were repeated three times.

1.6 Causality analysis

The β-galactosidase activities for sample extracts wereobtained and calibrated according to the dose-responsecurve of E2 standard solutions, derived simultaneously.The EEQbio (EEQ derived from bioassay) values werecalculated according to the dose-response curve of E2. TheEEQcal (EEQ derived from chemical analysis) values werecalculated from the concentrations of the analyzed targetcompounds using the following equation:

EEQcal =∑

EEQi =∑

(Ci × RPi) (1)

where, EEQi represents the EEQ value of selected com-pound i, Ci was the relative potency of selected compoundi, and RPi represented the relative potency of selectedcompoundi, obtained from the ratio between EC50 of E2and that of other target chemical. The RP values of E1,E2, EE2, E3, DES, EV, 4-t-OP, 4-NP and BPA were 0.053,1, 0.17, 0.0049, 0.021, 0.14, 0.0012, 0.0007 and 0.00003,respectively. The percentile contribution of the selectedcompounds (EEQi) in the EEQbio was then calculated.

1.7 Quality control

All data generated from the analysis were subject tostrict quality control procedures. To check for backgroundcontamination, peak identification and quantification, asolvent blank, a standard blank and a procedure blank were



processed in sequence along with each set of samples tobe analyzed. Surrogate standards were added to all thesamples to monitor matrix effects; recoveries of surro-gate standards E2-d3 and BPA-d16 were 94% and 83%respectively. Relative recoveries of the nine estrogeniccompounds ranged from 81% to 116% for the sourcewater samples at the spiked concentration of 5 ng/L. Thecalculations of the limit of detection (LOD) and limit ofquantitation (LOQ) of the target compounds were basedon the standard derivations (SD) of seven replicates ofspiked water at the concentration of 5 ng/L. LOD wasdefined as three times SD and LOQ is as nine times SD.The LOD and LOQ for source water were 0.10 to 0.65ng/L and 0.20 to 1.3 ng/L, respectively. For bioassay, theβ-galactosidase activities of the samples were examinedand compared with those of the controls. Significant dose-response relationships were obtained by testing samples atserial dilutions.

To avoid contamination during the sampling and samplepreparation processes, sampling bottles and all glasswareinvolved in the study were cleaned by soaking in 10%nitric acid overnight and chromic acid solution for 30min, washing three times with double-distilled water, andburning in a muffle furnace at 450°C for at least 4 hr. Alllaboratory materials were made of either glass or polyte-trafluoroethene (PTFE) to avoid sample contamination.

2 Results and discussion

2.1 Estrogenic activities in source waters

All extracts of source waters were found to induce sig-nificant estrogenic activities (Fig. 1). The EEQbio valuesranged from 0.16 to 2.4 ng/L, and six out of 23 sites werefound to have values of above 1.0 ng/L. Higher EEQbiovalues have been found at sampling sites 12, 14 and 15,whose EEQbio values were higher than 2.0 ng/L. Mostsource waters with high EEQ values were located in the

Table 2 Comparisons of estrogenic activities derived from bioassayscarried in different countries

Location EEQ (ng/L) Bioassay Reference

Netherlands < 0.17 ER-CALUX Vethaak et al., 2005France 0.30–4.52 MELN Cargouet et al., 2004Switzerland 0.3–7.0 Yeast Vermeirssen et al., 2005South Africa 0.63–2.48 Yeast Aneck-Hahn et al., 2009Japan 0.7–4.01 MVLN Hashimoto et al., 2005South Korea 0.38–6.27 E-Screen Ra et al., 2011China 2.2–8.3 HGELN Shen et al., 2001China 0.08–2.4 Yeast This study

Yangtze River Delta, which is the most developed region inChina, receiving sewage discharged from up-stream cities.

Table 2 summarizes the published results on EEQbioderived from various bioassay methods for different sam-pling sites around the world. The EEQbio value of TaihuLake, also located in Yangtze River Delta, was extraordi-narily higher than values from other sources. In contrast,EEQbiovalues were often relatively low in samples fromEuropean countries, which are well known for their suc-cessful environmental protection policies and advancedtechnologies. Nevertheless, conclusions from bioassayresults can only be drawn in a very general way. Con-centrations vary considerably in different types of watersand at different sites. Furthermore, differences in samplingmethods and analysis techniques, notably for bioassay, canoften obstruct detailed comparisons (Vethaak et al., 2005).

2.2 Concentrations of estrogenic compounds in sourcewaters

The presence of the selected compounds in source wa-ters varied spatially, except for DES and EV (Table 3).Among 16 samples, E1, 4-t-OP, 4-NP and BPA prevailedin all samples, with concentrations ranging 0.16–2.98;3.08–89.52; 30.09–280.19; and 7.61–710.65, respectively.E2, EE2 and E3 were partially detected but some werebelow LOQ, with concentrations ranging from nc (< LOQ,cannot be calculated) to 1.07 ng/L, nd (< LOD, cannot be

S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 S15 S16 S17 S18 S19 S20 S21 S22 S230.0

0.5

1.0

1.5

2.0

2.5

3.0

EE

Qb

io (

ng/L

)

Sample sites

Fig. 1 EEQbio values of source waters derived from yeast assay. Error bars represent the standard deviation of replicate samples (n = 3). EEQbio:bioassay derived E2 (estradiol) equivalent.



detected) to 2.67 ng/L, and nd to 4.37 ng/L, respectively.In contrast, DES and EV could only be quantified inthree samples, with concentrations ranging from 2.07 to2.52 ng/L and 1.34 to 1.96 ng/L, respectively. In general,concentrations of 4-t-OP, 4-NP and BPA were much higherthan other six compounds. These sites were all locatedin metropolitan areas, especially the Yangtze River Delta,showing similar distribution patterns of bioassay results.

In Table 4, the concentration ranges of nine selectedestrogenic compounds in source waters were comparedto those of previous studies in both source and surfacewaters. In the work of Lu et al. (2010), concentrationsof E1, E2, E3, 4-t-OP, 4-NP and BPA were found inthe Yangtze River (Nanjing section) of up to 3.80, 0.97,5.79, 95.77, 536.55 and 60.69 ng/L, respectively. Theseare similar to those determined in the present study. Theconcentrations of E1, E2, EE2, NP and BPA in sourcewaters in the USA were up to 0.90, 17, 1.4, 130 and 14ng/L, respectively (Benotti et al., 2009). Very few studieshave been carried out on DES and EV, so they were notincluded in the comparison. Similar to the previous studies,the presently observed concentrations of 4-t-OP, 4-NP andBPA in source waters were remarkably higher than othercompounds in the present study.

2.3 Risk assessment and causality analysis

The presence of estrogenic activity in source waters mightaffect aquatic organisms in such waters by disrupting theirnormal hormonal functions and jeopardizing the sourcewater quality. It was previously proposed that, for E2,a tentative long term predicted no-effect concentration(PNEC) for freshwater life was 1 ng/L (Young et al.,2002). According to this concept, the reproductive systemof organism live in the aquatic environment of which EEQvalues higher than 1 ng/L might be disrupted.

In the present study, the calculation of EEQcal valueswas based on the concept of concentration addition fromchemical analysis, representing the sum of estrogenic ac-tivities of nine selected compounds in the present study. Asignificant correlation between EEQcal and EEQbio was ob-served (Fig. 2). For all samples, the EEQcal values were notequal to, and were mostly lower than, the correspondingEEQbiovalues. Because quality control was strictly appliedin the present study and selected compounds acted on thesame target of ER, the disagreement between EEQbio andEEQcal could be due to the presence of unknown estrogenagonistic and antagonistic compounds in the water samples(Tanaka et al., 2001; Witters et al., 2001). This resultconfirmed the general robustness of both biological andchemical analysis tools. Moreover, these data indicatedthat the nine selected estrogen compounds represented themajor contributors to total estrogenic activity.

To investigate the individual contribution of the nineselected compounds to total estrogenic activity, their EEQvalues were compared with corresponding EEQbio values.The contribution rate of E1, E2, EE2, E3, DES, EV, 4-t-OP, 4-NP and BPA was in the range of 5.07–34.45%,0–72.45%, 0–61.28%, 0–1.97%, 0–2.97%, 0–12.35%,0.79–11.81%, 4.05–51.04% and 0.10 to 2.53%, respective-

1 2 30

0

1

2

3

EE

Qca

l (n

g/L

)

EEQbio

(ng/L)

R2 = 0.9270

p < 0.01

Fig. 2 Plots of the EEQbio values versus EEQcal values. EEQcal:Chemical analysis derived E2 (estradiol) equivalent.

ly. It could be speculated that E2, EE2 and 4-NP playeda major role in the estrogenic activity in source waters,especially E2 which was dominant in 12 out of 23 samples.The three compounds mentioned above together accountedfor 39.74% to 96.68% (mean value 69.36%) of EEQbio,while other compounds showed a minor contribution (Fig.3, Table S1). None of these three compounds are listedin the Chinese drinking water quality standards document(MOH, 2006). It is important that these three compoundsare included in future environmental regulations.

E2 belongs to a chemical family known as naturalestrogens, and EE2 is an orally bioactive estrogen used inalmost all modern oral contraceptive formulations. Chinais the country with the highest consumption of contra-ceptive pills, which explains the high concentrations ofE2 and EE2 in Chinese water bodies (Stanback, 1997).When these compounds enter the environment, they cancause male reproductive dysfunction in wildlife (Wanget al., 2008). Traditional water treatment processes, suchas chlorination, coagulation and sedimentation do notadequately remove EDCs. Water purification techniquessuch as ultraviolet, ozonation and activated charcoal havea great removal efficiency, but the high costs of thesetechniques represent a major constraint on the widespreaduse of these techniques (Johnson and Sumpter, 2001; Chenet al., 2007; Guedes Maniero et al., 2008).

4-NP is a mixture group of nonylphenol (NPs), whichis persistent in the environment and mainly arise fromthe degradation of the nonylphenol ethoxylates (NPEOs)in the environment. NPEOs are a subset of the alkylphe-nols ethoxylates (APEOs) that are used as surfactants indetergents, encompassing more than 80% of the worldmarket of APEOs, of which the total annual world-wideproduction was about 700,000 tons in 2005 (Jonkers etal., 2005). NPs and NPEOs have been classified in theEuropean Union as a hazard to human and environmen-tal safety (European Union, 2003). In the USA, thesecompounds have been removed from laundry detergents(McCoy, 2007). Nevertheless, these compounds have notbeen effectively restricted in China. The NPEOs are found



Table 3 Concentrations of selected compounds in source waters (ng/L)

Site E1 E2 EE2 E3 DES EV 4-t-OP 4-NP BPA

S3 1.15 ± 0.12 0.31 ± 0.08 1.01 ± 0.09 nc nd nd 4.01 ± 0.75 30.05 ± 3.97 17.86 ± 3.24S4 0.97 ± 0.11 0.28 ± 0.03 0.64 ± 0.07 nc nd nd 3.64 ± 0.55 54.27 ± 7.34 12.44 ± 1.56S5 0.45 ± 0.07 nc 1.55 ± 0.23 nd nd nd 5.21 ± 0.78 109.22 ± 12.37 7.61 ± 0.95S6 1.53 ± 0.09 0.26 ± 0.01 1.34 ± 0.17 nd nd nd 15.69 ± 2.34 168.25 ± 5.48 152.98 ± 10.57S7 0.96 ± 0.08 0.34 ± 0.05 0.28 ± 0.03 nc nd nd 12.42 ± 1.56 100.21 ± 7.97 135.14 ± 9.34S8 0.87 ± 0.09 0.31 ± 0.02 nc nc nd nd 13.78 ± 1.47 123.58 ± 10.29 124.73 ± 8.41S9 1.08 ± 0.08 0.55 ± 0.04 nc 4.37 ± 0.38 nd nd 37.62 ± 5.14 280.19 ± 17.67 80.32 ± 5.32S10 1.93 ± 0.23 0.71 ± 0.13 nd 3.94 ± 0.31 nd nd 96.44 ± 7.63 288.75 ± 21.48 65.04 ± 5.14S11 2.37 ± 0.17 0.58 ± 0.04 nd 4.22 ± 0.22 nd nd 69.29 ± 5.49 212.39 ± 14.63 90.65 ± 8.26S12 2.34 ± 0.14 1.07 ± 0.03 1.68 ± 0.16 2.14 ± 0.04 nc nc 53.68 ± 4.18 232.73 ± 14.65 147.69 ± 12.59S13 2.89 ± 0.18 1.78 ± 0.10 2.67 ± 0.09 2.73 ± 0.17 2.07 ± 0.16 1.96 ± 0.23 65.26 ± 3.89 230.84 ± 16.52 276.97 ± 20.48S14 2.98 ± 0.24 1.51 ± 0.07 2.59 ± 0.18 2.97 ± 0.21 2.52 ± 0.18 1.57 ± 0.07 89.52 ± 7.63 259.63 ± 14.21 710.65 ± 39.52S15 2.13 ± 0.12 0.65 ± 0.06 2.53 ± 0.31 2.68 ± 0.17 2.31 ± 0.30 1.34 ± 0.07 73.57 ± 5.23 224.13 ± 18.57 268.32 ± 22.36S20 0.52 ± 0.04 nc nc nc nd nd 4.52 ± 0.38 58.33 ± 4.23 32.02 ± 2.65S21 0.86 ± 0.11 nc nc nc nd nd 3.34 ± 0.25 85.16 ± 7.45 27.08 ± 1.29S22 0.97 ± 0.14 0.11 ± 0.01 nc nc nd nd 3.08 ± 0.26 72.65 ± 4.96 25.24 ± 1.72

E1: estrone, E2: 17β-estradiol, EE2: 17α-ethinylestradiol, E3: estriol, DES: diethylstilbestrol, EV: estradiol valerate, 4-t-OP: 4-t-octylphenol, 4-NP:4-nonylphenols, BPA: bisphenol A.Data are expressed as mean ± standard deviation (n= 3); nc: below limit of quantification, nd: below detection limit.

Table 4 Comparison of estrogenic compounds concentrations in water with other studies

Location E1 E2 EE2 E3 4-t-OP 4-NP BPA Reference

Germany 0.1–4.1 0.15–3.6 0.1–5.1 – 0.8–54 6.7–134 0.5–14 Kuch and Ballschmiter, 2001Greece nd nd nd nd 5.0–78 152–338 15–138 Arditsoglou and Voutsa, 2010Portugal nd nd nd – nd – nd–589.5 Ribeiro et al., 2009USA nd–0.9 nd–17 nd–1.4 – – nd–130 nd–14 Benotti et al., 2008Austria nd–4.6 nd–1.2 nd–0.33 nd–1.9 nd–41 nd–890 nd-600 Hohenblum et al., 2004S.Korea nd–5.0 nd nd nd – – – Kim et al., 2007China nd–3.80 nd–0.97 – nd–5.79 89.07–95.77 337.37–536.55 34.55–60.69 Lu et al., 2010China nd–75.0 nd–7.5 – – 1.0–2470 28.1–8890 2.2–1030 Zhao et al., 2009China 0.45–3.0 nd–1.8 nd–2.7 nd-4.4 3.1–96.4 30.1–288.8 7.6–710.7 This study

–: not available; nd: not detected.



S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 S15 S20 S21 S220.0

0.5

1.0

1.5

2.0

2.5

3.0E

EQ

(ng

/L)

Sample sites

BPA

4-NP

4-t-OP

EV

DES

E3

EE2

E2

E1

EEQbio

Fig. 3 Calculated EEQ values of selected compounds versus EEQbio values.

in various Chinese rivers at concentrations of up to 97.6µg/L (Shao et al., 2005; Shen et al., 2005; Yu et al., 2009).In contrast to E2 and EE2, the estrogenic activity of 4-NP isvery weak because 4-NP is a weak structural mimic of E2,but the levels of 4-NP can be extraordinary high to com-pensate (Soares et al., 2008). The NP removal efficiency indrinking water treatment systems, was found to be highlyvariable depending on the type of unit treatment processemployed, and facilities with high elimination rates adoptozonation in their treatment processes (Berryman, 2004).

Although it is well known that EDCs can affect theendocrine systems of aquatic organisms, even at lowconcentrations, it is hard to explain possible health risksto humans based on the results from laboratory experi-ments, particularly with regard to chronic effects, such asendocrine disrupting (Rogan and Ragan, 2003). Howev-er, humans are exposed to mixtures of EDCs and it isnecessary to consider the impact of synergistic effects ofthese compounds (Kortenkamp, 2007). The potential riskof mixtures of chemicals at low-effect levels has becomeknown as the “something from nothing ”phenomenon(Silva et al., 2002). Risk assessments that overlook thepossibility of synergistic effects of EDCs are likely tosignificantly undervalue risks (Kortenkamp et al., 2007).For example, Payne et al. (2001) found that the mixtureof four organchlorines, each of them present at a lowand individually-ineffective concentration, enhanced hu-man breast cancer cell proliferation. On the another hand,some EDCs are persistent in the environment and can beaccumulated in human body (Bianco et al., 2011). Hence,the impacts to humans of the EDCs in Chinese sourcewaters should not be ignored, even though current data onthe relationship between exposure to environmental EDCsand human health remains limited (Diamanti-Kandarakiset al., 2010). To take precaution, certain measures can betaken to decrease levels of EDCs in source waters, such asrestricting pollution discharge upstream of source waters,

and introducing proper treatment processes.

3 Conclusions

Estrogenic activity has been observed in all 23 sourcewaters of China. Samples from the Yangtze Delta indicatedhigher estrogenic potential than in other source watersamples. The nine selected compounds, found in varioussource waters, represent most of the whole estrogenicactivity. Furthermore, E2, EE2 and 4-NP were found to bethe main contributors to the estrogenic activities in mostsource waters out of nine selected compounds. Resultsof the present work could be useful to water treatmenttechnology and environmental risk assessment.

Acknowledgments

This work was supported by the Chinese Academy ofSciences (No. KZCX1-YW-06–02), the National BasicResearch Program of China (No. 2007CB407304), andthe Ministry of Environmental Protection of the People’sRepublic of China (No. 200909040).

Appendix A. Supplementary table

Supplementary table associated with this article can befound in the online version.

References

Aneck-Hahn N H, Bornman M S, de Jager C, 2009. Oestrogenicactivity in drinking waters from a rural area in the Water-berg District, Limpopo Province, South Africa. Water SouthAfrica, 35(3): 245–251.

Arditsoglou A, Voutsa D, 2010. Partitioning of endocrine disrupt-ing compounds in inland waters and wastewaters dischargedinto the coastal area of Thessaloniki, Northern Greece.Environmental Science and Pollution Research, 17(3): 529–



538.Benotti M J, Trenholm R A, Vanderford B J, Holady J C,

Stanford B D, Snyder S A, 2009. Pharmaceuticals andendocrine disrupting compounds in U.S. drinking water.Environmental Science and Technology, 43(3): 597–603.

Berryman D, Houde F, DeBlois C, O’Shea M, 2004. Nonylpheno-lic compounds in drinking and surface waters downstreamof treated textile and pulp and paper effluents: a survey andpreliminary assessment of their potential effects on publichealth and aquatic life. Chemosphere, 56(3): 247–255.

Bianco M, Mita L, Portaccio M, Diano N, Sica V, De Luca Bet al., 2011. Differential accumulation levels in the brain ofrats exposed to the endocrine disruptor 4-tert-octylphenol(OP). Environmental Toxicology and Pharmacology, 31(1):198–204.

Campbell C G, Borglin S E, Green F B, Grayson A, Wozei E,Stringfellow W T, 2006. Biologically directed environmen-tal monitoring, fate, and transport of estrogenic endocrinedisrupting compounds in water: A review. Chemosphere,65(8): 1265–1280.

Cargouet M, Perdiz D, Mouatassim-Souali A, Tamisier-KarolakS, Levi Y, 2004. Assessment of river contamination byestrogenic compounds in Paris area (France). Science of theTotal Environment, 324(1-3): 55–66.

Chen C Y, Wen T Y, Wang G S, Cheng H W, Lin Y H, Lien G W,2007. Determining estrogenic steroids in Taipei waters andremoval in drinking water treatment using high-flow solid-phase extraction and liquid chromatography/tandem massspectrometry. Science of the Total Environment, 378(3):352–365.

Damstra T, Barlow S, Bergman A, Kavlock R, Van Der Kraak G,2002. Global assessment of the state-of-the-science of en-docrine disruptors. International Programme on ChemicalSafety, World Health Organization. Geneva, Switzerland.

Desbrow C, Routledge E J, Brighty G C, Sumpter J P, WaldockM, 1998. Identification of estrogenic chemicals in STWeffluent. 1. Chemical fractionation and in vitro biologicalscreening. Environmental Science and Technology, 32(11):1549–1558.

Diamanti-Kandarakis E, Palioura E, Kandarakis S A, KoutsilierisM, 2010. The impact of endocrine disruptors on endocrinetargets. Hormone and Metaolic Research, 42(8): 543–552.

European Union, 2003. Directive 2003/53/EC of the EuropeanParliament and of the Council 18 June 2003. Luxembourg.

Gaido K W, Leonard L S, Lovell S, Gould J C, Babai D, PortierC J et al., 1997. Evaluation of chemicals with endocrinemodulating activity in a yeast-based steroid hormone re-ceptor gene transcription assay. Toxicology and AppliedPharmacology, 143(1): 205–212.

Guedes Maniero M, Maia Bila D, Dezotti M, 2008. Degradationand estrogenic activity removal of 17β-estradiol and 17α-ethinylestradiol by ozonation and O3/H2O2. Science of theTotal Environment, 407(1): 105–115.

Hashimoto S, Horiuchi A, Yoshimoto T, Nakao M, Omura H,Kato Y et al., 2005. Horizontal and vertical distribution ofestrogenic activities in sediments and waters from TokyoBay, Japan. Archives of Environmental Contamination andToxicology, 48(2): 209–216.

Hohenblum P, Gans O, Moche W, Scharf S, Lorbeer G, 2004.Monitoring of selected estrogenic hormones and industrialchemicals in groundwaters and surface waters in Austria.Science of the Total Environment, 333(1-3): 185–193.

Johnson A C, Sumpter J P, 2001. Removal of endocrine–disrupting chemicals in activated sludge treatment works.

Environmental Science and Technology, 35(24): 4697–4703.

Jonkers N, Laane R W P M, de Voogt P, 2005. Sources and fate ofnonylphenol ethoxylates and their metabolites in the Dutchcoastal zone of the North Sea. Marine Chemistry, 96(1-2):115–135.

Jonkers N, Sousa A, Galante-Oliveira S, Barroso C M, KohlerH P E, Giger W, 2010. Occurrence and sources of selectedphenolic endocrine disruptors in Ria de Aveiro, Portugal.Environmental Science and Pollution Research, 17(4): 834–843.

Kasprzyk-Hordern B, Dinsdale R M, Guwy A J, 2008. The occur-rence of pharmaceuticals, personal care products, endocrinedisruptors and illicit drugs in surface water in South Wales,UK. Water Research, 42(13): 3498–3518.

Kim S D, Cho J, Kim I S, Vanderford B J, Snyder S A, 2007.Occurrence and removal of pharmaceuticals and endocrinedisruptors in South Korean surface, drinking, and wastewaters. Water Research, 41(5): 1013–1021.

Kortenkamp A, Faust M, Scholze M, Backhaus T, 2007.Low-level exposure to multiple chemicals: Reason for hu-man health concerns? Environmental Health Perspectives,115(S-1): 106–114.

Kortenkamp A, 2007. Ten years of mixing cocktails: A reviewof combination effects of endocrine-disrupting chemicals.Environmental Health Perspectives, 115(S-1): 98–105.

Kuch H M, Ballschmiter K, 2001. Determination of endocrine-disrupting phenolic compounds and estrogens in surfaceand drinking water by HRGC-(NCI)-MS in the picogramper liter range. Environmental Science and Technology,35(15): 3201–3206.

Li J, Ma M, Wang Z J, 2010. In vitro profiling of endocrinedisrupting effects of phenols. Toxicology in Vitro, 24(1):201–207.

Augulyte L, Bergqvist P A, 2007. Estimation of water samplingrates and concentrations of PAHs in a municipal sewagetreatment plant using SPMDs with performance refer-ence compounds. Environmental Science and Technology,41(14): 5044–5049.

Lu G H, Song W T, Wang C, Yan Z H, 2010. Assessmentof in vivo estrogenic response and the identification ofenvironmental estrogens in the Yangtze River (Nanjingsection). Chemosphere, 80(9): 982–990.

Luo J P, Ma M, Wang Z J, Liu W L, Li T S, 2006. Assessmenton the ecological risks of drink water in a city in NorthChina by way of bioassay battery. Water and WastewaterEngineering, 32(8): 17–21.

Magi E, Scapolla C, Di Carro M, Liscio C, 2010. Determina-tion of endocrine-disrupting compounds in drinking watersby fast liquid chromatography-tandem mass spectrometry.Journal of Mass Spectrometry, 45(9): 1003–1011.

Matthiessen P, Arnold D, Johnson A C, Pepper T J, PottingerT G, Pulman K G T, 2006. Contamination of headwaterstreams in the United Kingdom by oestrogenic hormonesfrom livestock farms. Science of the Total Environment,367(2-3): 616–630.

McCoy M, 2007. Going green. Chemical and Engineering News,85(5): 13–23.

MOH (Ministry of Health of the People’s Republic of China),2006. Standards for Drinking Water Quality. Beijing, China.

Payne J, Scholze M, Kortenkamp A, 2001. Mixtures of fourorganochlorines enhance human breast cancer cell pro-liferation. Environmental Health and Perspective, 109(4):391–397.



Ra J S, Lee S H, Lee J, Kim H Y, Lim B J, Kim S H etal., 2011. Occurrence of estrogenic chemicals in SouthKorean surface waters and municipal wastewaters. Journalof Environmental Monitoring, 13(1): 101–109.

Rao K F, Ma M, Wang Z J, Liu L J, 2004. Variation of estrogeniceffects during Water treatment processes in a drinking waterwork in South China. Chinese Journal of EnvironmentalScience, 25(6): 123–126.

Reineke N, Bester K, Huhnerfuss H, Jastorff B, Weigel S,2002. Bioassay-directed chemical analysis of River Elbesurface water including large volume extractions and highperformance fractionation. Chemosphere, 47(7): 717–723.

Ribeiro C, Pardal M A, Martinho F, Margalho R, Tiritan M E,Rocha E et al., 2009. Distribution of endocrine disruptorsin the Mondego River estuary, Portugal. EnvironmentalMonitoring and Assessment, 149(1-4): 183–193.

Rogan W J, Ragan N B, 2003. Evidence of effects of envi-ronmental chemicals on the endocrine system in children.Pediatrics, 112(S1): 247–252.

Shao B, Hu J Y, Yang M, An W, Tao S, 2005. Nonylphenol andnonylphenol ethoxylates in river water, drinking water, andfish tissues in the area of Chongqing, China. Archives ofEnvironmental Contamination and Toxicology, 48(4): 467–473.

Shen G, Zhang Z, Yu G, Li X, Hu H, Li F, 2005. Dissolved neutralnonylphenol ethoxylates metabolites in the Haihe Riverand Bohai Bay, People’s Republic of China. Bulletin ofEnvironmental Contamination and Toxicology, 75(4): 827–834.

Shen J H, Gutendorf B, Vahl H H, Shen L, Westendorf J, 2001.Toxicological profile of pollutants in surface water from anarea in Taihu Lake, Yangtze Delta. Toxicology, 166(1-2):71–78.

Silva E, Rajapakse N, Kortenkamp A, 2002. Something from“nothing” – eight weak estrogenic chemicals combinedat concentrations below NOECs produce significant mix-ture effects. Environmental Science and Technology, 36(8):1751–1756.

Soares A, Guieysse B, Jefferson B, Cartmell E, Lester J N,2008. Nonylphenol in the environment: A critical reviewon occurrence, fate, toxicity and treatment in wastewaters.Environment International, 34(7): 1033–1049.

Stanback J, 1997. Perspectives on local manufacture of contra-ceptives in developing countries. Family Health Internation-al, Arlington, VA, USA.

Sumpter J P, 1997. Environmental control of fish reproduction:a different perspective. Fish Physiology and Biochemistry,17(1-6): 25–31.

Tanaka H, Yakou Y, Takahashi A, Higashitani T, Komori K,2001. Comparison between estrogenicities estimated fromDNA recombinant yeast assay and from chemical analysesof endocrine disruptors during sewage treatment. WaterScience and Technology, 43(2): 125–132.

Tashiro Y, Takemura A, Fujii H, Takahira K, Nakanishi Y, 2003.Livestock wastes as a source of estrogens and their effectson wildlife of Manko tidal flat, Okinawa. Marine PollutionBulletin, 47(1-6): 143–147.

Vermeirssen E L M, Burki R, Joris C, Peter A, Segner H, SuterM J E et al., 2005. Characterization of the estrogenicity ofswiss midland rivers using a recombinant yeast bioassayand plasma vitellogenin concentrations in feral male browntrout. Environmental Toxicology and Chemistry, 24(9):2226–2233.

Vethaak A D, Lahr J, Schrap S M, Belfroid A C, Rijs G

B J, Gerritsen A et al., 2005. An integrated assessmentof estrogenic contamination and biological effects in theaquatic environment of The Netherlands. Chemosphere,59(4): 511–524.

Wang F Y, Sun X, He S H, Jia L Z, Zhan W, Liang Z H, 2005.Determination of environmental estrogens in surface waterand tap water. Journal of Environment and Health, 22(4):284–286.

Wang S, Huang W, Fang G Z, Zhang Y, Qiao H, 2008. Analysisof steroidal estrogen residues in food and environmentalsamples. International Journal of Environmental AnalyticalChemistry, 88(1): 1–25.

Witters H E, Vangenechten C, Berckmans P, 2001. Detection ofestrogenic activity in flemish surface waters using an invitro recombinant assay with yeast cells. Water Science andTechnology, 43(2): 117–123.

Yamazaki F, 1983. Sex control and manipulation in fish. Aqua-culture, 33(1-4): 329–354.

Young W F, Whitehouse P, Johnson I, Sorokin N, 2002. Proposedpredicted-no-effect-concentrations (PNECs) for natural andsynthetic steroid oestrogens in surface waters. EnvironmentAgency R&D Technical Report P2-T04/1. England andWales Environment Agency Bristol; 172.

Yu Y, Zhai H Y, Hou S G, Sun H W, 2009. Nonylphenolethoxylates and their metabolites in sewage treatment plantsand rivers of Tianjin, China. Chemosphere, 77(1): 1–7.

Zhao J L, Ying G G, Wang L, Yang J F, Yang X B, Yang L H etal., 2009. Determination of phenolic endocrine disruptingchemicals and acidic pharmaceuticals in surface water ofthe Pearl Rivers in South China by gas chromatography–negative chemical ionization–mass spectrometry. Science ofthe Total Environment, 407(2): 962–974.



Appendix A. Supplementary table

Table S1 EEQ values of estrogenic compounds and EEQcal values (ng/L)

Site E1 E2 EE2 E3 DES EV 4-t-OP 4-NP BPA EEQcal

S3 0.06 0.31 0.17 b – – – 0.02 0.00 0.57S4 0.05 0.28 0.11 – – – – 0.04 0.00 0.48S5 0.02 – 0.26 – – – 0.01 0.08 0.00 0.37S6 0.05 0.16 0.06 – – – 0.02 0.12 0.00 0.41S7 0.01 – 0.05 – – – 0.01 0.07 0.00 0.15S8 0.05 0.11 – – – – 0.02 0.09 0.00 0.26S9 0.06 0.55 – 0.02 – – 0.05 0.20 0.00 0.87S10 0.1 0.71 – 0.02 – – 0.12 0.20 0.00 1.15S11 0.13 0.58 – 0.02 – – 0.08 0.15 0.00 0.96S12 0.12 1.07 0.29 0.01 – – 0.06 0.16 0.00 1.72S13 0.15 0.78 0.45 0.01 0.05 0.22 0.08 0.16 0.01 1.92S14 0.16 0.91 0.44 0.01 0.04 0.27 0.11 0.18 0.02 2.15S15 0.11 0.65 0.43 0.01 0.05 0.19 0.09 0.16 0.01 1.70S20 0.03 – – – – – 0.01 0.04 0.00 0.07S21 0.05 – – – – – – 0.06 0.00 0.11S22 0.05 0.11 – – – – – 0.05 0.00 0.22S3 0.06 0.31 0.17 – – – – 0.02 0.00 0.57

E1: estrone, E2: 17β-estradiol, EE2: 17α-ethinylestradiol, E3: estriol, DES: diethylstilbestrol, EV: estradiol valerate, 4-t-OP: 4-t-octylphenol, 4-NP:4-nonylphenols, BPA: bisphenol A, EEQcal: sum of EEQ of above nine compounds; b: not available.


© The Author(s) 2012. This article is published with open access at Springerlink.com csb.scichina.com www.springer.com/scp

*Corresponding author (email: [email protected])

Article

SPECIAL TOPICS:

Environmental Chemistry February 2012 Vol.57 No.6: 595600

doi: 10.1007/s11434-011-4906-0

Retinoid X receptor activities of source waters in China and their removal efficiencies during drinking water treatment processes

JIANG WeiWei1, YAN Ye1, LI Na1, MA Mei1*, WANG DongHong1, RAO KaiFeng1, WANG ZiJian1 & SATYANARAYANAN Senthil Kumaran2

1 State Key Laboratory of Environmental Aquatic Chemistry, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China;

2 Unit of Toxicology, Bharathiar University, Coimbatore 641046, India

Received March 24, 2011; accepted August 18, 2011; published online January 3, 2012

There is increasing evidence of estrogenic activities of source waters and drinking waters in China based on estrogen receptors (ERs) testing. However, relating such activities to retinoid X receptors (RXRs) in both drinking and source waters are lacking. To rectify this situation, we assessed 23 source water samples from six major river systems in China. We also collected samples at various stages of water processing from three drinking water treatment plants (DWTPs) using a two-hybrid RXR yeast assay with and without metabolism. No RXR agonistic activity was observed, but significant antagonistic activity was detected in all sample extracts. The RXR antagonistic activities of source water sample extracts ranged from 15.2% to 57.8% without metabolism and 11.5% to 68.3% with metabolism, respectively. In the drinking water treatment processes, RXR antagonistic activities without metabolism and with metabolism of up to 31.4% and 37.5% were removed, respectively. Nevertheless, the remaining RXR an-tagonists in treated drinking water from these source waters could still be harmful to human health. To the best of our knowledge, the occurrence of in vitro RXR disruption activities in source and drinking water has not been previously reported in China. Therefore, an attempt was made to conduct detailed studies investigating RXR disrupting activities and their possible risks in source and drinking water.

source water, drinking water, retinoid X receptor, yeast assay, bioassay

Citation: Jiang W W, Yan Y, Li N, et al. Retinoid X receptor activities of source waters in China and their removal efficiencies during drinking water treatment processes. Chin Sci Bull, 2012, 57: 595600, doi: 10.1007/s11434-011-4906-0

Over the past several decades, a number of different chemi-cals that are widely distributed in the environment have been found to disrupt delicate endocrine systems in wildlife and humans [1]. These endocrine disrupting chemicals (EDCs) disrupt various biological processes results in de-velopmental degeneration and reduced fecundity, as well as an increase in breast cancer in humans [2]. The principle anthropogenic sources of EDCs include pharmaceutical compounds, wastewater plant effluents, agricultural fertilizers, and fish farming wastes [3–5]. Because EDCs are water-soluble, most conventional water treatment processes that are applied in China (e.g. chlorination, coagulation and

sedimentation) do not completely remove these chemicals [6,7]. EDCs are biologically active at very low concentra-tions and have been detected in drinking water [8,9]. Ac-cordingly, there has been an increased effort to monitor the occurrence of these chemicals in source waters in China.

To date, most research has focused on estrogenic disrup-tion activity via estrogenic receptors (ERs) in water. It is also important to investigate retinoic acid hormone disrup-tion activity via the retinoid X receptor (RXR); however, very little research on this aspect has been conducted. Re- tinoic acid is necessary for vision and plays an essential role in apoptosis and differentiation of embryonic cells that con-trol the growth of epithelial cells in the skin, gastrointestinal tract, and bones [10]. Retinoic acid also affects the nervous


596 Jiang W W, et al. Chin Sci Bull February (2012) Vol.57 No.6

system and immune system, acts as anti-oxidative agent, and is involved in the biosynthesis of another antioxidant, coenzyme Q [11]. Suppressive effects of retinoic acid in cancer development have also been described [12]. Retinoic acid acts via RXR and EDCs that can also act on RXRs would disturb normal retinoic acid signaling [13]. Human exposure to these chemicals commonly occurs though air and food, but the primary route of exposure is through drinking water [14,15]. Thus, it is important to monitor the occurrence of RXR activity in drinking water. There is also a need to further investigate RXR activities in source waters in China and the removal efficiency of these compounds by drinking water treatment plants. The results of such investi-gations would be important for formulating management policies relating to source water protection and water treat-ment technology.

The development of efficient methods for evaluating biological activities in water samples will require further development of in vitro bioassays with high sensitivity. The development of rapid response methods using simple equipment has also become an attractive alternative to con-ventional chemical analytical techniques [16]. Among bio-assays that have been considered, the yeast assay was suc-cessfully applied to determine activities in chemical and/or environmental samples [17]. Although many EDCs can sur-vive drinking water treatment, little is known about the fate of RXR activity in drinking water [18]. Because there is no metabolic enzyme system in cell lines and metabolism could change the RXR activity of chemicals in water, the results from in vitro tests will not reflect the actual RXR activity of water intake by humans and animals. Therefore, to simulate the exposure conditions in vivo, an S9 mixture was introduced as a metabolic enzyme [19]. The goal of the present study is to screen for RXR activity in source and drinking water using a two-hybrid yeast assay, and to eval-uate the removal efficiency of drinking water treatment processes.



Dichloromethane, hexane and methanol (HPLC grade) were obtained from J. T. Baker (USA) and 9-cis-RA (9cRA, 98%) and dimethyl sulfoxides (DMSO, 99.5%) were obtained from Sigma Chemical (USA). For all chemicals, stock solu-tions were prepared in DMSO. Oasis hydrophilic lipophilic balance (HLB) cartridges (500 mg, 6 mL) from Waters Corporation (USA) were used for solid phase extraction (SPE). Glass fiber filters (APFF, pore size 0.45 μm) were purchased from Millipore (USA) and pyrolyzed at 450°C for 4 h prior to use. Purified water used in all experiments was prepared with a Milli-Q water purification system (Mil-lipore, USA).

1.2 Sample collection

Samples of 23 source waters, including reservoirs and rivers that supply water to local waterworks, were collected be-tween March 2010 and July 2010. The study area covered six out of seven major river systems of China. All six river systems are of concern because of the local pollution situa-tion. Site information is listed in Table 1.

Samples (of 20 L) were also collected from three drink-ing water treatment plants (DWTP) that processed source waters at sites S5 (North China), S14 (Middle China) and S16 (East China) (Table 2). Samples were collected in pre-cleaned amber glass bottles that had been soaked in 10% nitric acid overnight, chromic acid solution for 30 min, washed three times in double-distilled water and then dried in a furnace at 450°C for at least 4 h. Before sample collec-tion, the bottle was also washed three times with the sam-pled water. An appropriate amount of methanol (2 mL/L water sample) was added immediately after sampling to suppress possible biotic activities. Samples were stored at 4°C and were treated within 48 h.

1.3 Sample preparation

The water samples were filtered through pre-baked glass fiber filters to remove insoluble material, and then extracted

Table 1 Information from sampling sites

Site Type Site Type Site Type

Songhua River a) Yangtze River Huai River

S1 River S6 River S16 River

S2 Reservoir S7 River S17 River

S8 River S18 River

Liao River S9 River S19 River

S3 Reservoir S10 River

S4 Reservoir S11 River Pearl River

S12 Lake S20 Reservoir

Hai River S13 Reservoir S21 Reservoir

S5 Reservoir S14 River S22 Reservoir

S15 Reservoir S23 River

a) River system.

Table 2 Flow scheme of drinking water treatment plants

DWTP1 DWTP2 DWTP3

Source water S5 (A1a)) Source water S14 (A2) Source water S16 (A3)

Pre-chlorination (B1) Pre-chlorination (B2) Coagulation (B3)

Coagulation (C1) Coagulation Coal and sand filtration (C3)

Coal and sand filtration (D1)

Rapid filtration (C2) Secondary filtration (D3)

Active Carbon filtration (E1)

Secondary chlorina-tion (D2)

Secondary chlorination (F1)

a) Sample site.


Jiang W W, et al. Chin Sci Bull February (2012) Vol.57 No.6 597

according to methods used in our previous study [20]. The water samples were extracted using HLB cartridges that had been pre-conditioned with 5 mL dichloromethane, 5 mL methanol, and 5 mL water. During extraction, the cartridges were forced under vacuum at a flow rate of approximately 6 mL/min, and then kept under vacuum for 5 min to dry the water. The cartridges were then eluted three times with 15 mL dichloromethane. The elutions were combined and filtered through anhydrous sodiumsulfate (Na2SO4) to remove residual water, after which they were evaporated to 2 mL in a rotary evaporator (R-200, Buchi, Switzerland) at 40°C. The 2 mL extract was subsequently dried under a nitrogen stream, after which it was immediately reconsti-tuted to 0.2 mL with DMSO. A blank sample only consist-ing of purified water was also run alongside the samples as a control. Throughout the experiment, all laboratory materials were stored in glass or polytetrafluoroethene (PTFE) to prevent contamination.

1.4 Yeast assay

The yeast assay was conducted as described previously by our research group [21,22], with some modifications. The yeast strain used in the present study was Y187 (MATα, ura3-52, his3-200, ade2-101, trp1-901, leu2-3, 112, gal4∆, met-, gal80∆, URA3::GAL1UAS-GAL1TATA-lacZ) obtained from Clontech (Palo Alto, CA, USA). Yeast cells were co-transformed with pGBT9 hRXRβ and pGAD424 GRIP1/FL using the lithium acetate method and then selected by growth on synthetic dextrose (SD) agar (lacking leucine and tryptophan) according to Clontech yeast protocols handbook. Clones growing on the SD/-Leu/-Trp plate were selected for culture in liquid SD/-Leu/-Trp medium. In this assay, yeast is grown at an exponential rate overnight at 30°C, then cen-trifuged at 130 r/min and diluted to an optical density of 0.75 at 600 nm (OD600) with synthetic dextrose/-Leu/-Trp medium (SD medium). All samples were assayed at least in triplicate. Each assay group included a positive 9cRA con-trol and a negative DMSO control. A procedural blank that was subjected to SPE to monitor for any false positive re-sults was run alongside the samples. Each sample was di-luted in a 1:2 series to give a total of four concentrations diluted in DMSO. The 5 μL serial dilutions of the tested samples were combined with 995 μL of medium that con-tained approximately 5×103 yeast cells/mL, resulting in a test culture in which the volume of DMSO did not exceed 0.5% of the total volume. In the case of the metabolic test, the S9 mixture was added. S9 was prepared from the livers of male Sprague-Dawley rats that were pre-treated with 3-methyl- cholanthrene and 3-phenobarbital according to the method described by Ames et al. [19]. Water and cofac-tor (MgCl2·6H2O, KCl, G-6-P, nicotinamide adenine dinu-cleotide phosphate, nicotinamide adenine dinucleotide, Na2HPO4 and NaH2PO4) were added to the SD/-Leu/-Trp medium according to the method described Takatori et al.

[23]. Next, 200 μL of the test cultures were transferred into each well of a 96-well plate. The samples were then incu-bated at 30°C with vigorous orbital shaking (800 r/min) on a titer plate shaker for 2 h, after which the OD600 value was measured. The volume of extract in each well represented 100 mL of raw water.

Test cultures of 150 μL were collected and 120 μL of test buffer and 20 μL of chloroform were added to each culture. The cultures were mixed carefully (vortex 25 s) and pre-incubated for 10 min at 30°C and 1300 r/min. The enzyme reaction was then triggered by adding 40 μL O-nitrophenyl-β-D-galactopyranoside (ONPG) and 4 mg/mL test buffer and incubating the sample at 30°C and 800 r/min. Next, 100 μL of 1 mol/L sodium carbonate (Na2CO3) was added to terminate the reactions within 60 min, after which 200 μL of the supernatant was transferred into a new 96-well plate and the optical density (OD420) was measured at 420 nm. To ensure that the activity in the bio-assay was caused by true antagonistic responses and not by cytotoxicity, cell viability was also measured and deter-mined by spectrophotometric analysis after exposure as the change in cell density (OD600) in the assay medium.

1.5 Data analysis

β-galactosidase activity was calculated according to the following equation

U= (OD420sOD420b)/ (t×V×OD600), (1)

where U is the β-galactosidase activity of the sample; OD420s and OD420b are the optical density of the enzyme reaction supernatant of the sample and blank, respectively; OD600 is the optical density of the sample at 600 nm; t is the incubation duration of the enzyme reaction; V is the volume of the test culture.

The antagonistic activity of sample was calculated ac-cording to the following equation:

Antagonistic activity= (1Us/Up)×100%, (2)

where Up and Us represent the β-galactosidase activity of the positive control (1.5 mg/L 9cRA), and in the presence of 1.5 mg/L of 9cRA, respectively.


2.1 Response to source water extracts

No RXR agonistic activity was observed in any of the source water sample extracts (data not shown); however, RXR antagonistic activity was found in all extracts. The observed activity ranged from 15.2% to 57.8% and 11.5% to 68.3% without and with metabolism, respectively. The presence of RXR antagonistic activity of source waters varied spatially (Figure 1), and RXR antagonists were found to exist in many source waters in China.



Figure 1 RXR antagonistic activities of source sample extracts (100 mL raw water/well). Values are presented as the mean±S.D. (n = 3).

Various types of environmental contamination by chemical compounds such as anti-oxidants, organochlorines, or-ganophosphates, antimicrobials, estrogens and progestogens, and various types of industrial contamination such as pesti-cides, pharmaceuticals and personal care products (PPCPs) have been found in source and drinking waters [24–28]. Some of these contaminants have been identified as RXR agonists or antagonists [22] and include Bisphenol A (BPA), multiple phenols, phthalic acid esters (PAEs) and organic chlorine pesticides (OCPs) that have been found in various aquatic systems in China [29–32]. In the present study, most of the sample sites with relatively high RXR antagonistic activities were located in national grain production areas in China. The massive use of OCPs in these areas would con-tribute considerably to total activity levels [33]. However, the lack of sufficient data pertaining to toxic RXR antago-nists has prevented the identification of these chemicals in source waters.

The RXR activities in nine out of 23 extracts increased after metabolism, while the activities in the remaining 14 samples decreased. The results also indicate that the com-position profile of contamination in the samples is expected to be complicated. Some in vivo experiments have shown that metabolic enzymes can increase or decrease the estro-genic activity of chemicals such as BPA and 4-NP, but that these involve many biochemical processes such as hydrox-ylation, methylation, sulfonation, glucuronidation, and ary-lation [34–36]. The results from the present study have demonstrated that RXR antagonists can also be activated or deactivated after metabolism.

The results indicate that the source waters in China are generally affected by RXR antagonists. Therefore, an evaluation of the removal of these contaminants by DWTP is of considerable environmental importance.

2.2 Response to drinking water extracts

As was the case for source waters, no RXR agonistic activity was observed in any of the samples, but significant antagonistic activity was induced in all sample extracts (Figure 2). The removal efficiencies of RXR antagonistic activities of DWTP1, DWTP2 and DWTP3 were 15.2%, 31.4% and 29.2% without metabolism, and 10.0%, 37.5% and 30.2% with metabolism, respectively. The conventional drinking water treatments were ineffective with regard to the removal of RXR antagonists.

The removal efficiencies of RXR antagonists by the pro-cesses of the DWTPs were generally different in samples with or without metabolism. For example, at DWTP1 and DWTP2 chlorination slightly increased the RXR antagonis-tic activities without metabolism, while such activities de-creased with metabolism, indicating that the metabolites of RXR antagonists were less active in chlorinated samples. Nevertheless, the RXR antagonistic activity decreased after chlorination at DWTP3. Previous studies have indicated that chlorination does not effectively remove EDCs; indeed, in some cases the levels of EDCs increased with chlorination [37,38]. The same trends were found in association with other processes. When compared with other processes, coagulation seemed a more effective method for removing


Jiang W W, et al. Chin Sci Bull February (2012) Vol.57 No.6 599

Figure 2 RXR antagonistic activities of extracts of samples from various drinking water treatment plants (100 mL raw water/well). Values are pre-sented as the mean±S.D. (n = 3).

RXR antagonists, although its efficiency did not exceed 25%. According to another study, coagulation removed less than 25% of the EDCs or PPCPs [18]. Ormad et al. [39] demonstrated that adsorption onto coal, sand or activated carbon was a very efficient technique for removing about 60% of the OCPs from the water. However, since filtration is not a destructive process, the contamination passes from one medium to another, resulting in the sorbent becoming a new source of pollution. In summary, the removal effi-ciencies of RXR antagonistic activity were variable, even

differing between the same processes at different DWTPs. These findings indicate that the removal efficiency of RXR antagonists is expected to be largely dependent on the composition of solutes in water.

Although the concentrations of EDCs were very low in source and drinking waters, there is still increasing concern regarding the lack of understanding of the fate of RXR an-tagonists during drinking water treatment considering that even trace amounts of natural hormones can disturb the en-docrine system [24]. Since conventional drinking water treatment processes (chlorination, coagulation and sand filtration) are often inefficient for low-concentration con-taminants, finished waters can be expected to contain sig-nificant amounts of EDCs that could jeopardize drinking water quality and cause risks to human health [40]. In the present study, DWTPs were found to remove maximum levels of only 31.4% without metabolism and 37.5% with metabolism of RXR antagonistic activity. These results in-dicate that DWTP could not completely remove the RXR antagonist, as was also the case for other EDCs. Since RXR plays an important role in the mediation of hormones in human health and is a component of disrupting substances that is still harmful to wild animals and humans in source water, it is possible that the finished drinking water might be harmful to human health.

3 Conclusions

RXR antagonistic activities were found in all extracts of samples from 23 source waters in China and drinking water treatment processes of three DWTPs supplied by three out of the 23 source waters. None of the samples induced ago-nistic activity. The source waters were generally affected by RXR antagonists. Conventional drinking water treatment processes could not completely remove these RXR antago-nists, implying current risks to human health. The RXR two-hybrid yeast assay can be applied as an important and useful method for evaluation of drinking water safety, par-ticularly as it facilitates the efficient detection of RXR dis-ruptors. Further studies are needed to identify the com-pounds responsible for RXR antagonistic activity to provide useful information for environmental risk assessments and water treatment technology.

This work was supported by the Environmental Protection National Com-monweal Research Project (200909040) and International Scientific and Technological Cooperation Projects by the Ministry of Science and Tech-nology of China (2009DFA91920).

1 Colborn T, Saal F S V, Soto A M. Developmental effects of endo-crine-disrupting chemicals in wildlife and humans. Environ Health Perspect, 1993, 101: 378–384

2 Crews D, Willingham E, Skipper J K. Endocrine disruptors: Present issues, future directions. Q Rev Biol, 2000, 75: 243–260

3 Tashiro Y, Takemura A, Fujii H, et al. Livestock wastes as a source



of estrogens and their effects on wildlife of Manko tidal flat, Okina-wa. Mar Pollut Bull, 2003, 47: 143–147

4 Yamazaki F. Sex control and manipulation in fish. Aquaculture, 1983, 33: 329–354

5 Desbrow C, Routledge E J, Brighty G C, et al. Identification of es-trogenic chemicals in STW effluent. 1. Chemical fractionation and in vitro biological screening. Environ Sci Technol, 1998, 32: 1549– 1558

6 Li N, Wang D H, Zhou Y Q, et al. Dibutyl phthalate contributes to the thyroid receptor antagonistic activity in drinking water processes. Environ Sci Technol, 2010, 44: 6863–6868

7 Yuan S G, Wang D H, Ma M, et al. Assessment on removal effect of different advanced treatment techniques in waterworks. Chinese J Environ Eng, 2008, 2: 586–590

8 Magi E, Scapolla C, Di Carro M, et al. Determination of endocrine- disrupting compounds in drinking waters by fast liquid chromatog-raphy-tandemmass spectrometry. J Mass Spectrom, 2010, 45: 1003– 1011

9 Kuch H M, Ballschmiter K. Determination of endocrine-disrupting phenolic compounds and estrogens in surface and drinking water by HRGC-(NCI)-MS in the picogram per liter range. Environ Sci Tech-nol, 2001, 35: 3201–3206

10 Janosek J, Hilscherova K, Blaha L, et al. Environmental xenobiotics and nuclear receptors—Interactions, effects and in vitro assessment. Toxicol Vitro, 2006, 20: 18–37

11 Bentinger M, Turunen M, Zhang X X, et al. Involvement of retinoid X receptor alpha in coenzyme Q metabolism. J Mol Biol, 2003, 326: 795–803

12 Sun S Y, Lotan R. Retinoids and their receptors in cancer develop-ment and chemoprevention. Crit Rev Oncol Hemat, 2002, 41: 41–55

13 Van der Plas S A, Lutkeschipholt I, Spenkelink B, et al. Effects of subchronic exposure to complex mixtures of dioxin-like and non- dioxin-like polyhalogenated aromatic compounds on thyroid hor-mone and vitamin A levels in female Sprague-Dawley rats. Toxicol Sci, 2001, 59: 92–100

14 Fürst P. Dioxins, polychlorinated biphenyls and other organohalogen compounds in human milk. Levels, correlations, trends and exposure through breastfeeding. Mol Nutr Food Res, 2006, 50: 922–933

15 Weschler C. Changes in indoor pollutants since the 1950s. Atmos Environ, 2009, 43: 153–169

16 Campbell C, Borglin S, Green F, et al. Biologically directed envi-ronmental monitoring, fate, and transport of estrogenic endocrine disrupting compounds in water: A review. Chemosphere, 2006, 65: 1265–1280

17 Vermeirssen E L M, Burki R, Joris C, et al. Characterization of the estrogenicity of swiss midland rivers using a recombinant yeast bio-assay and plasma vitellogenin concentrations in feral male brown trout. Environ Toxicol Chem, 2005, 24: 2226–2233

18 Westerhoff P, Yoon Y, Snyder S, et al. Fate of endocrine-disruptor, pharmaceutical, and personal care product chemicals during simulat-ed drinking water treatment processes. Environ Sci Technol, 2005, 39: 6649–6663

19 Ames B N, Lee F D, Durston W E. Improved bacterial test system for detection and classification of mutagens and carcinogens. Proc Natl Acad Sci USA, 1973, 70: 782–786

20 Ma M, Rao K F, Wang Z J. Occurrence of estrogenic effects in sewage and industrial wastewaters in Beijing, China. Environ Pollut, 2007, 147: 331–336

21 Ma M, Li J, Wang Z J. Assessing the detoxication efficiencies of wastewater treatment processes using a battery of bioassays/biomarkers. Arch Environ Contam Toxicol, 2005, 49: 480–487

22 Li J, Ma M, Wang Z J. A two-hybrid yeast assay to quantify the ef-fects of xenobiotics on retinoid X receptor-mediated gene expression. Toxicol Lett, 2008, 176: 198–206

23 Takatori S, Kitagawa Y, Oda H, et al. Estrogenicity of metabolites of benzophenone derivatives examined by a yeast two-hybrid assay. J Health Sci, 2003, 49: 91–98

24 Benotti M J, Trenholm R A, Vanderford B J, et al. Pharmaceuticals and endocrine disrupting compounds in US drinking water. Environ Sci Technol, 2009, 43: 597–603

25 Casajuana N, Lacorte S. Presence and release of phthalic esters and other endocrine disrupting compounds in drinking water. Chroma-tographia, 2003, 57: 649–655

26 Kuster M, Lopezdealda M, Hernando M, et al. Analysis and occur-rence of pharmaceuticals, estrogens, progestogens and polar pesti-cides in sewage treatment plant effluents, river water and drinking water in the Llobregat river basin (Barcelona, Spain). J Hydrol, 2008, 358: 112–123

27 Lin Y, Shi Y, Jiang M, et al. Removal of phenolic estrogen pollutants from different sources of water using molecularly imprinted poly-meric microspheres. Environ Pollut, 2008, 153: 483–491

28 Murray K E, Thomas S M, Bodour A A. Prioritizing research for trace pollutants and emerging contaminants in the freshwater envi-ronment. Environ Pollut, 2010, 158: 3462–3471

29 Wu B, Zhang X X, Zhang X L, et al. Semi-volatile organic com-pounds and trace elements in the Yangtze River source of drinking water. Ecotoxicology, 2009, 18: 707–714

30 Zhang Z L, Hong H S, Zhou J L, et al. Fate and assessment of persis-tent organic pollutants in water and sediment from Minjiang River Estuary, Southeast China. Chemosphere, 2003, 52: 1423–1430

31 Zhong W J, Wang D H, Xu X W, et al. Screening level ecological risk assessment for phenols in surface water of the Taihu Lake. Chemosphere, 2010, 80: 998–1005

32 Lemaire G, Balaguer P, Michel S, et al. Activation of retinoic acid receptor-dependent transcription by organochlorine pesticides. Toxi-col Appl Pharmacol, 2005, 202: 38–49

33 Li X M, Gan Y P, Yang X P, et al. Human health risk of organochlo-rine pesticides (OCPs) and polychlorinated biphenyls (PCBs) in edi-ble fish from Huairou Reservoir and Gaobeidian Lake in Beijing, China. Food Chem, 2008, 109: 348–354

34 Legler J, Dennekamp M, Vethaak A D, et al. Detection of estrogenic activity in sediment-associated compounds using in vitro reporter gene assays. Sci Total Environ, 2002, 293: 69–83

35 Pottenger L H, Domoradzki J Y, Markham D A, et al. The relative bioavailability and metabolism of bisphenol A in rats is dependent upon the route of administration. Toxicol Sci, 2000, 54: 3–18

36 Moffat G J, Burns A, Van Miller J, et al. Glucuronidation of nonylphenol and octylphenol eliminates their ability to activate tran-scription via the estrogen receptor. Regul Toxicol Pharmacol, 2001, 34: 182–187

37 Itoh S, Ueda H, Naasaka T, et al. Evaluating variation of estrogenic effect by drinking water chlorination with the MVLN assay. Water Sci Technol, 2000, 42: 61–69

38 Chen C, Wen T, Wang G, et al. Determining estrogenic steroids in Taipei waters and removal in drinking water treatment using high- flow solid-phase extraction and liquid chromatography/tandem mass spectrometry. Sci Total Environ, 2007, 378: 352–365

39 Ormad M, Miguel N, Claver A, et al. Pesticides removal in the pro-cess of drinking water production. Chemosphere, 2008, 71: 97–106

40 Kim S D, Cho J, Kim I S, et al. Occurrence and removal of pharma-ceuticals and endocrine disruptors in South Korean surface, drinking, and waste waters. Water Res, 2007, 41: 1013–1021

Open Access This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction

in any medium, provided the original author(s) and source are credited.


Please cite this article in press as: C. Kavitha et al.. Toxicity of Moringa oleifera seed extract on some hematological and biochemicalprofiles in a freshwater fish, Cyprinus carpio. Exp Toxicol Pathol (2011), doi:10.1016/j.etp.2011.01.001

ARTICLE IN PRESSG ModelETP-50598; No. of Pages 7

Experimental and Toxicologic Pathology xxx (2011) xxx–xxx


Experimental and Toxicologic Pathology

journa l homepage: www.e lsev ier .de /e tp

Toxicity of Moringa oleifera seed extract on some hematological andbiochemical profiles in a freshwater fish, Cyprinus carpio

Chokkalingam Kavitha, Mathan Ramesh ∗, Satyanarayanan Senthil Kumaran,Srinivasan Audhi LakshmiUnit of Toxicology, Department of Zoology, School of Life Sciences, Bharathiar University, Coimbatore 641046, Tamil Nadu, India


Article history:Received 20 November 2009Accepted 2 January 2011

Keywords:Moringa oleiferaSeed extractCyprinus carpioHematologyBiochemical parameters

a b s t r a c t

The study was carried out to investigate the acute and sublethal toxicity of Moringa oleifera seed extract onhematological and biochemical variables of a freshwater fish Cyprinus carpio under laboratory conditions.The 96 h LC50 value of M. oleifera seed extract to the fish C. carpio was estimated by probit analysis methodand was found to be 124.0 mg/L (with 95% confidence limits). For sublethal studies a non lethal dose of1/10th of 96 h LC50 value (12.40 mg/L) was taken. During acute treatment (96 h), hematological variableslike red blood cell count (RBC), hemoglobin (Hb), hematocrit (Hct), and mean corpuscular hemoglobinconcentration (MCHC) were significantly (P < 0.05) decreased in fish exposed to seed extract. Howevera significant (P < 0.05) increase in white blood cell count (WBC), mean corpuscular volume (MCV) andmean corpuscular hemoglobin (MCH) value was observed in the exposed fish during above treatmentperiod when compared to that of the control groups. Biochemical parameters such as plasma proteinand glucose levels significantly declined in fish exposed to seed extract while a significant (P < 0.05)increase in aspartate aminotransferase (AST), alanine aminotransferase (ALT) and alkaline phosphatase(ALP) activity was observed. During sublethal treatment (12.40 mg/L), WBC count, MCV, MCH, plasmaglucose, AST, ALT and ALP activities were gradually elevated (P < 0.05) at the end of 7, 14, 21, 28 and 35thdays in seed extract exposed fish, whereas plasma protein level declined. However, a biphasic trend wasnoticed in Hb, Hct, RBC and MCHC levels. This study may provide baseline information about the toxicityof M. oleifera seed extract to C. carpio and to establish safer limit in water purification.

© 2011 Published by Elsevier GmbH.

1. Introduction

Aquaculture is one of the fastest growing aspects of the agri-culture industry worldwide to meet the food demand (FAO, 2004).The management of water quality, fish diseases and eradication ofaquatic weeds is very important in aquaculture farms. The use ofchemical pesticides and fertilizers for pond treatment has affectedthe health condition of the aquatic animals (Richard et al., 1991). Atpresent, the usage of several botanical products as effective alter-natives of synthetic pesticides and fertilizers has been increasedbecause of their easy availability, easy biodegradability and safe formankind and environment (Dahiya et al., 2000; Tiwari and Singh,2004). Such botanical products when used extensively may enteraquatic systems such as streams, river, and lakes, which may havean effect on non-target organisms in a due course of time (Singhand Agarwal, 1992; Singh and Singh, 2005; Dongmeza et al., 2006;Tiwari and Singh, 2006; Winkaler et al., 2007; Gabriel et al., 2009).

∗ Corresponding author. Tel.: +91 422 2428493; fax: +91 422 2422387.E-mail address: [email protected] (M. Ramesh).

M. oleifera Lam is a rapidly growing tree belonging to thefamily Moringaceae and popularly known as “arbol de rabano”,horseradish tree and drumstick tree (Ramachandran et al., 1980;Kwaambawa and Maikokera, 2007). It is an indigenous tree tonorthern India and Pakistan. The leaves and pods of moringa treeare rich in protein content, carotenoids, minerals and ascorbic acidand also used as food supplements for human and animals (Makkarand Becker, 1997; Afuang et al., 2003; Dongmeza et al., 2006).In addition to its use as a food supplements, most of its partsare widely used for many medical applications. Seeds extracts ofmoringa have established action against larval phase of the dengueand yellow fever’s mosquito transmitter (Ferreira, 2004) and anti-inflammatory, antispasmodic, diuretic (Carceres et al., 1992; Faiziet al., 1994) and antioxidant activities (Rao et al., 1999).

In many countries the seed powder of the M. oleifera is effec-tively used in water purification in aquaculture farms due toits coagulation properties (Jahn, 1988; Muyibi and Evison, 1995;Ndabigengesere and Nasarasiah, 1998; Ayotunde et al., 2004). How-ever, application of high quantity of moringa seed powder inaquaculture ponds leads to mortality of fish due to the presenceof toxic substances or antinutritional factors (Lim and Dominy,1989; Siddhuraju et al., 2000; Francis et al., 2001; Ayotunde et al.,

0940-2993/$ – see front matter © 2011 Published by Elsevier GmbH.doi:10.1016/j.etp.2011.01.001


dx.doi.org/10.1016/j.etp.2011.01.001

dx.doi.org/10.1016/j.etp.2011.01.001


http://www.elsevier.de/etp


dx.doi.org/10.1016/j.etp.2011.01.001



2 C. Kavitha et al. / Experimental and Toxicologic Pathology xxx (2011) xxx–xxx

Table 1LC50 value of Moringa oleifera seed extract for the fish C. carpio.

Exposure period (h) Regression equation Co-efficient correlation P value LC50 (mg/L)

96 Y = 79.1080 + 40.1761x 0.8798 0.8937 124.0

2004). The toxic effect of M. oleifera seed powder was observedin guppies (Poecillia reticulata), protozoa (Tetrahymens pyriformis)bacteria (Escherichia coli) and Oreochromis niloticus (Grabow et al.,1985; Ayotunde et al., 2004).

Biological monitoring techniques like hematological andbiochemical variables have become attractive and useful for mon-itoring environmental quality, water pollution and the healthcondition of aquatic organisms (Celik, 2004; Kohler et al., 2007;Kori-Siakpere and Ubogu, 2008; Olufayo, 2009). The entry of tox-icants in to aquatic media may affect the water quality parameterwhich in turn leads to changes in the hematological variables offish, due to its close association with the external environment(van Vuren, 1986; Nemcsok and Benedeczky, 1990; Carvalho andFernandes, 2006; Kavitha et al., 2010). Biochemical biomarkers likeglucose, protein and enzymes are frequently used as an indicatorof the general state of health and early warning of stress in fishunder stressful conditions (de la Torre et al., 2000; Barnhorn andvan Vuren, 2004; Abou El-Naga et al., 2005; Osman et al., 2010).

Many laboratory studies have shown the toxicity of plant extractto fish and changes in hematological and biochemical profiles lead-ing to death of fish (Omoniyi et al., 2002; Tiwari and Singh, 2004;Ayotunde and Ofem, 2008). However data on toxicity of M. oleiferaseed extract on freshwater fish are still scarce. The common carpCyprinus carpio is the most extensively cultivated fish throughoutthe world. In India it is cultivated either alone or along with othercarps. It is one of the most suitable fish model for toxicologicalstudies due to its easy availability and adaptable to the laboratorycondition.

In view of the scarcity of data on the toxic effects of M. oleiferaseed extract in aquaculture farms, the present study aims to test theacute and sublethal toxicity of M. oleifera seed extract on hemato-logical and biochemical parameters of fingerlings of C. carpio.


2.1. Plant material

The seeds of M. oleifera were collected from the Bharathiar Uni-versity campus, Bharathiar University, Coimbatore, India and seedpowder was prepared according to the method described by Price(2000). Seed powder (25 g) was soaked in 250 ml of distilled waterfor 15 h. Then, the suspension was shaken thoroughly and filteredthrough Whatman filter paper No. 1 to collect crude extract (stocksolution).

2.2. Animals

Healthy specimens of C. carpio (7.5 ± 0.54 cm, total length:15 ± 0.98 g) were obtained from Tamil Nadu Fisheries DevelopmentCorporation Limited, Aliyar, Tamilnadu, India and were stockedand acclimated to laboratory conditions for about 20 days. Dur-ing the period of acclimatization the fishes were fed ad libitumwith rice bran and groundnut oil cake and were fed once a day.The feeding was withheld for 48 h before the commencement ofthe experiment to keep the experimental animals more or lessin the same metabolic state. Aeration was provided throughoutthe study. Physico-chemical parameters of water such as tem-perature (25.0 ± 1.0 C), pH (7.0 ± 1), salinity (0.28 ± 0.1 ppt), totalhardness (16.0 ± 0.5 mg/L), calcium (4.00 ± 0.51 mg/L), and mag-nesium (2.00 ± 0.2 mg/L) were measured by the method of APHA

(1998) and were maintained throughout the study period. Beforethe start of the experiment suitable numbers of fish were trans-ferred into two glass aquaria which were continuously aerated.

2.3. Determination of median lethal concentration of M. oleiferaseed extract (96 h)

For the determination of median lethal concentration of seedextract for 96 h, different concentrations of seed extract (80, 100,120, 140, 160 mg/L) were prepared from the stock and added infive circular plastic tubs, filled with 50 L of water. Ten fish wereintroduced into each tub. Three replicates were maintained for eachconcentration. The test water was renewed at the end of 24 h andfreshly prepared seed extract was added to maintain the concentra-tion at constant level. The mortality/survival of fish was recordedafter 96 h. Dead fish was removed immediately to avoid contamina-tion. The concentration at which 50% mortality of fish occurred after96 h was taken as the median lethal concentration (LC50), whichwas found to be 124.0 mg/L (Table 1) (Finney, 1978).

2.4. Acute toxicity studies

For acute toxicity test, five circular plastic tubs were taken andfilled with 50 L of water. To each tub the concentration of M. oleiferaseed extract (124.0 mg/L) was added after removal of same quantityof water. Then 10 fish were introduced into each tub. Simultane-ously a control setup without the addition of extract was also main-tained. After 96 h, the live fish from treatment and control groupswere sacrificed for the hematological and biochemical assay.

2.5. Sublethal toxicity studies

For sublethal toxicity test a total of 200 fingerlings from thestock were introduced into fiber glass tank of 1000 L capacity withdechlorinated water. The sublethal concentration (1/10th of LC50which was 12.40 mg/L; Sprague, 1971) of M. oleifera seed extractwas added to the tank after removal of same quantity of water.A control was maintained in separate fiber glass tank. Sublethalstudy was carried out for a period of 35 days and sampled at every7th day interval. Fish were randomly selected from control andexperimental tanks and blood was collected by cardiac punctureusing heparinised syringes. The whole blood was used for hema-tological assay and the remaining blood was stored at −20 C. Forbiochemical assay the stored blood was then centrifuged for 20 minat 10,000 rpm to separate plasma which was used for the estimationof glucose, protein, AST, ALT and ALP activities.

2.6. Hematological and biochemical analysis

The hematological profiles like hemoglobin was estimated bythe method of Drabkin (1946), hematocrit value was estimated bythe method of Nelson and Morris (1989) and total erythrocytesand leucocytes were counted by the method of Rusia and Sood(1992). Biochemical parameter like plasma glucose was estimatedby the method of Cooper and Mc Daniel (1970), plasma proteinby the method of Lowry et al. (1951), aspartate aminotransferase(AST) and alanine aminotransferase (ALT) were estimated followingthe method of Reitman and Franckel (1957) and alkaline phos-phatase (ALP) was determined following the method of Kind andKing (1954).


dx.doi.org/10.1016/j.etp.2011.01.001



C. Kavitha et al. / Experimental and Toxicologic Pathology xxx (2011) xxx–xxx 3

Table 2Alterations of hematological and biochemical parameters in a freshwater fish Cypri-nus carpio during acute treatment of Moringa oleifera seed extract.

Parameters Control Experiment

Hematological parametersHb (g/dl) 7.54 ± 0.11 5.42 ± 0.131* (−28.12)Hct (%) 22.74 ± 0.15 16.86 ± 0.707* (−25.85)RBC (million/cu. mm) 1.82 ± 0.05 1.18 ± 0.034* (−35.05)WBC (1000/cu. mm) 27.61 ± 0.11 33.31 ± 0.26* (+20.64)MCV (fl) 12.49 ± 0.82 14.28 ± 0.84* (+14.33)MCH (pg) 41.42 ± 0.20 45.85 ± 0.32* (+10.69)MCHC (g/dl) 33.15 ± 0.70 32.14 ± 0.50* (−3.05)

Biochemical parametersPlasma glucose (mg/100 ml) 110.30 ± 0.35 84.21 ± 0.45* (−23.65)Plasma protein (g/ml) 2.45 ± 0.26 1.87 ± 0.14* (−23.67)Plasma AST (IU/L) 26.47 ± 0.69 41.61 ± 0.65* (+57.19)Plasma ALT (IU/L) 21.32 ± 0.58 36.76 ± 0.35* (+72.42)Plasma ALP (IU/L) 15.64 ± 0.24 24.81 ± 0.89* (+58.63)

Values are meant ±S.E. of five individual observation, (+) denotes percent increaseover control, and (−) denotes per cent decrease over control.

* Values are significant at P < 0.05.


The results of the studies were expressed as mean ± SE. The sig-nificance of sample mean between control and seed extract of M.oleifera treated fish was tested using Student’s ‘t’ test (Campbell,1981). Differences were considered significant at P levels < 0.05.

3. Results

3.1. Acute studies

3.1.1. Hematology and biochemical observationThe acute toxicity of M. oleifera seed extract on hematolog-

ical and biochemical parameters of C. carpio was presented inTable 2. Hematological examination showed a significant (P < 0.05)decrease in Hb, Hct, RBC, and MCHC values in fish treated withM. oleifera seed extract giving a percentage decrease of 28.12,25.85, 35.05 and 3.05 respectively. In contrast there was an ele-vation in WBC, MCV and MCH value giving a percentage increaseof 20.64, 14.33 and 10.69 when compared with their respectivecontrol groups (P < 0.05). The plasma glucose and protein levels ofexperimental fish were significantly (P < 0.05) decreased showinga percentage decrease of 23.65 and 23.67 when compared to con-trol. However plasma AST, ALT and ALP activities were significantly(P < 0.05) increased showing a percentage increase of 57.19, 72.42and 58.63 respectively.

3.2. Sublethal studies

3.2.1. Hematology observationFig. 1a–g represents hematological parameters of C. carpio

exposed to sublethal toxicity of M. oleifera seed extract. A bipha-sic response in hematological profiles like Hb, Hct and RBC countwas observed (Fig. 1a–c). A gradual increase in levels of WBC, MCVand MCH were noted throughout the study period. A maximumpercent increase of WBC (22.68) and MCH (22.09) was noted at theend of 35th day (Fig. 1d and e), whereas in MCV, the maximum per-cent increase (21.36) was noted at the end of 28th day (Fig. 1f). Amixed trend was noted in MCHC value (Fig. 1g).

3.2.2. Biochemical observationThe sublethal toxicity of M. oleifera seed extract on biochemi-

cal parameters of C. carpio was presented in Fig. 2a–e. The plasmaglucose, AST, ALT and ALP levels were gradually increased in seedextract treated fish throughout the experimental period showinga maximum percent increase of 53.92, 20.217, 20.963 and 32.309

at the end of 35th day respectively (Fig. 2a, c, d and e) while therewas a depletion in plasma protein level throughout the exposureperiod showing a minimum percentage decrease (6.25) and maxi-mum percentage decrease (32.45) at the end of 7th and 35th day,respectively (Fig. 2b).

4. Discussion

In the present investigation, the 96 h LC50 value of M. oleiferaseed extract for the freshwater fish C. carpio was found to be124.0 mg/L which indicates that M. oleifera seed extract is toxic toC. carpio at higher concentration. Kumar et al. (2010) reported thatthe 24, 48, 72 and 96 h LC50 values of aqueous extract of Euphor-bia tirucalli latex to the fish Heteropneustes fossilis was found tobe 3.450 l/L, 2.516 l/L, 1.623 l/L and 1.315 l/L respectively.Tiwari and Singh (2003) observed the toxicity of Nerium indicumleaf extract to the fish Channa punctatus and indicate that thetoxicity depends on the solvent used for extraction; the LC50value of diethyl ether, acetone, chloroform and methanol extractof N. indicum leaf extract were found to be 17.34 mg/L, 40.01 mg/L,40.61 mg/L and 106.37 mg/L, respectively. The 24 h LC50 value ofneem leaf extract for Prochilodus lineatus was found to be 4.8 g L−1

(Winkaler et al., 2007). The differences in the LC50 value of variousparts of plant species to fish depend on the chemicals present in theplants and also the sensitivity of the fish used for the experiment.Behavior responses of fish were used to examine the toxic natureof pollutants in the aquatic environment. In the present investiga-tion, copious mucous secretion, loss of equilibrium, restlessness,jerky movements, rapid opercula beat were noted during acutetreatment.

Hematological investigations have proven valuable for fisheriesbiologists for quick detection of changes in fish health and thesechanges may precede changes in fish behavior and visible lesions.In general the decrease level of RBC count, Hb and Hct may be dueto the destruction of RBCs and erythroblastosis leading to anaemia(Wintrobe, 1978). In the present study the decreased level of RBCcount, Hb and Hct content in fish treated with seed extract mighthave resulted from hemolysis caused by this extracts. Similar obser-vations were also noted in Clarias gariepinus exposed to leaf extractsof tobacco, Nicotiana tobaccum and cassava effluents (Omoniyi et al.,2002; Adeyemo, 2005). In contrast Ayotunde et al. (2004) noted anincrease in RBC count, Hb and Hct content in O. niloticus exposedto aqueous extracts of Moringa oleifera seeds.

The decrease in Hb content during stress condition may indicatea decrease in the rate of Hb synthesis which leads to impaired oxy-gen supply to various tissues resulting decrease in the number ofRBC through haemolysis (Larsson et al., 1985; Ahmad et al., 1995;Atamanalp and Yanik, 2003). Moreover the lysing of erythrocytesleads to a reduction in hamatocrit value (Martinez and Souza, 2002).However the increase in these parameters during sublethal treat-ment indicates adaptation of the fish to the seed extract toxicity.The observed increase in WBC during acute and sublethal treatmentmay be due to stimulated lymphopoiesis and/or enhanced releaseof lymphocytes from lymphomyeloid tissue as a defense mecha-nism of the fish to tolerate the seed extract toxicity. The increasein leucocyte count indicates the stimulatory effect of the toxicanton immune system and also depends on the toxicant stress (Ateset al., 2008).

The MCHC is an indicator of red blood cell swelling and thelowered MCHC during acute treatment might have resulted fromrelease of young erythrocytes containing less hemoglobin into cir-culation. Whereas the significant increase of MCHC value duringsublethal treatment may be due to congenital sphaerocytosis assuggested by Sobecka (2001). The significant increase of MCV andMCH during acute and sublethal treatment indicates the swellingof red blood cells. Further stress related increase in the erythrocyte


dx.doi.org/10.1016/j.etp.2011.01.001




*

0123456789

10

a

b

c

d

e

f

g

352821147

Hb

(g/d

l)

Exposure period (in days)

Control Experiment

*

0

4

8

12

16

20

24

352821147

Hct

(%

)


Control Experiment

* **

0

0.5

1

1.5

2

2.5

352821147

RB

C

(mill

ion/

cu.m

m)


Control Experiment

* * *

0

10

20

30

40

352821147

WB

C (

1000

/cu.

mm

)


Control Experiment

**

0

2

4

6

8

10

12

14

16

18

352821147

MC

V (

fl)


Control Experiment

* * *

0

10

20

30

40

50

60

352821147

MC

H (

pg)


Control Experiment

**

30

31

32

33

34

352821147

MC

HC

(g/

dl)


Control Experiment

Fig. 1. Hematological values ((a) Hb; (b) Hct; (c) RBC; (d) WBC; (e) MCV; (f) MCH; (g) MCHC) of C. carpio exposed to sublethal concentration of Moringa oleifera seed extractfor 35 days. Bars represent SE. *Significant at P < 0.05 (based on t test).

volume may be another reason as suggested by Jastrzebska andProtasowickiz (2005).

Measurement of plasma biochemical parameters is mostly usedin clinical diagnosis of fish physiology to determine the generalstatus of health (Ferreira et al., 2007; Osman et al., 2010). Carbo-hydrates are the main source of energy in many organisms and

their reserve used to meet energy demand in stress condition. Theobserved increase of plasma glucose level during sublethal treat-ment indicates a stress response triggered by the presence of seedextract in water or might be due to hypoxic condition caused by theseed extract in water. However the decrease in blood glucose dur-ing acute exposure can be attributed to high utilization of glucose


dx.doi.org/10.1016/j.etp.2011.01.001




**

**

*

0

40

80

120

160

200

a c

b d

e

352821147

Pla

sma

Glu

cose

(m

g/10

0ml)


Control Experiment

* *

0

0.5

1

1.5

2

2.5

3

3.5

352821147

Pla

sma

Pro

tein

(µ

g/m

l)


Control Experiment

* * * *

0

5

10

15

20

25

30

35

352821147

AST

(IU

/L)


Control Experiment

* * * *

0

5

10

15

20

25

30

35

352821147A

LT

(IU

/L)


Control Experiment

* * * *

0

5

10

15

20

25

352821147

AL

P (I

U/L

)


Control Experiment

Fig. 2. Biochemical changes ((a) plasma glucose; (b) plasma protein; (c) AST; (d) ALT; (e) ALP) of C. carpio exposed to sublethal concentration of Moringa oleifera seed extractfor 35 days. Bars represent SE. *Significant at P < 0.05 (based on t test).

for oxidation or hypoxic conditions leading to an excess utilizationof stored carbohydrates. The decreased level of protein in this studymay be due to their degradation and also to their possible utiliza-tion for metabolic purposes. Similar observation was also made inC. punctatus exposed to latices of Euphorbia royleana and Jatrophagossypifolia (Singh and Singh, 2002).

The alterations of enzyme activity under stress condition offerone of the most important biochemical parameter and their levelprovide information of diagnostic values (Adamu, 2009). Transam-inase enzymes play an important role in carbohydrate–proteinmetabolism in fish and determination of transaminase (AST andALT) can also be used for aquatic biomonitoring (Nemcsok andBenedeczky, 1990; Vutukuru et al., 2007). The enzymes ALT andAST in blood plasma indicate organ dysfunction in aquatic organ-isms during stress condition (Gabriel and George, 2005). Gabrielet al. (2009) noted elevation of both AST and ALT in different organsof catfish hybrid exposed to aqueous extracts from Lepidagathisalopecuroides leaves and suggested that the elevation may be due todisturbances in the Kreb’s cycle; the elevation in ALT indicates hep-atic damage caused by this plant extracts. The elevation in serumaspartate aminotransferase in Heteroclarias exposed to tobacco leaf

dust may be due to the process of either deamination or transam-ination caused by the plant dust (Adamu, 2009). In the presentinvestigation the significant increase in plasma AST and ALT activ-ity during acute and sublethal treatment might have resulted fromdisturbances in the Kreb’s cycle caused by the seed extract. Furtherstructural damages in liver and kidney of the fish due to seed extracttoxicity may result leakage of these enzymes into the bloodstreamand cause increased activity in plasma.

Alkaline phosphatase is an important enzyme of animalmetabolism, and plays important role in the transport of metabo-lites across the membranes (Vorbrodt, 1959). Changes in alkalinephosphatase activity can affect the metabolism of the fish.Increased levels of ALP was noted by Tiwari and Singh (2003) inC. punctatus to N. indicum leaf extracts and Tiwari and Singh (2006)in C. punctatus to aqueous extracts of E. tirucalli plant. Gabriel et al.(2009) reported an increase in ALP activity in catfish exposed toaqueous extracts from L. alopecuroides leaves and suggested thatthe elevation may be due to damage in the liver and kidney of fishwith increased cell membrane permeability. In the present studythe elevation of ALP activity may be the cellular damage caused byseed extract or a response to overcome toxicity of seed extract.


dx.doi.org/10.1016/j.etp.2011.01.001




4.1. Conclusion

Even though seed extract of M. oleifera has wide applicationsin aquaculture operations, the health hazard of these plant extractto aquatic organisms has not been studied in detail. The findingsof the present study indicate that seed extract of M. oleifera hassignificant effect on hematological and biochemical parameters ofthe fish. This study helps to establish the safe limits and effects ofaqueous extracts of M. oleifera on water quality and also the doseof the extract can safely be extrapolated in aquaculture operations.

References

Abou El-Naga EH, El-Moselhy KM, Hamed MA. Toxicity of cadmium and copper andtheir effect on some biochemical parameters of marine fish Mugil seheli. EgyptianJ Aquat Res 2005;31(2):60–71.

Adamu KM. Sublethal effects of tobacco (Nicotiana tobaccum) leaf dust on enzy-matic activities of Heteroclarias (a hybrid of Heterobranchus bidorsalis and Clariasgariepinus). Jordan J Biol Sci 2009;2(4):151–8.

Adeyemo OK. Haematological and histopathological effects of cassava mill effluentin Clarias gariepinus. Afr J Biomed Res 2005;8:179–83.

Afuang W, Siddhuraju P, Becker K. Comparative nutritional evaluation of raw,methanol extracted residues and methanol extracts of moringa (Moringa oleiferaLam.) leaves on growth performance and feed utilisation in Nile tilapia (Ore-ochromis niloticus L.). Aquacult Res 2003;34:1147–59.

Ahmad F, Ali SS, Shakoori AR. Sublethal effects of danitor (fenpropathrin), a syntheticpyrethroid on fresh water Chinese grass carp, Ctenopharyngodon idella. Folia Biol(Krakow) 1995;43:151–9.

APHA. Standard methods for the examination of water and wastewater. 20th ed.Washington, DC: American Public Health Association; 1998.

Atamanalp M, Yanik T. Alterations in hematological parameters of rainbowtrout (Oncorhynchus mykiss) exposed to mancozeb. Turk J Vet Anim Sci2003;27:1213–7.

Ates B, Orun I, Talas ZS, Durmaz G, Yilmaz I. Effects of sodium selenite on some bio-chemical and hematological parameters of rainbow trout (Oncorhynchus mykissWalbaum, 1792) exposed to Pb2+ and Cu2+. Fish Physiol Biochem 2008;34:53–9.

Ayotunde E, Ofem BO. Acute and chronic toxicity of pawpaw (Carica papaya) seedpowder to adult Nile tilapia (Oreochromis niloticus Linna 1757). Afr J Biotech2008;7(3):22675–32274.

Ayotunde EO, Fagbenro OA, Adebayo OT, Amoo AI. Toxicity of aqueous extracts ofdrumstick Moringa oleifera seeds to Nile tilapia Oreochromis niloticus, fingerlingsand adults. In: Proceedings of 6th international symposium on tilapia; 2004.

Barnhorn IEJ, van Vuren JHJ. The use of different enzymes in feral freshwater fish asa tool for the assessment of water pollution in South Africa. Ecotoxicol EnvironSafe 2004;59:180–5.

Campbell RC. Statistics for biologists. 2nd ed. Cambridge, London: Cambridge Uni-versity Press; 1981. p. 66.

Carceres A, Saraiva A, Rizzio S, Zabala L, De Leon E, Navy F. Pharmacological proper-ties of Moringa oleifera. 2 Screening for antispasmodic, anti-inflammatory anddiuretic activity. J Ethanopharmacol 1992;36:233–7.

Carvalho CS, Fernandes MN. Effect of temperature on copper toxicity and hemato-logical responses in the Neotropical fish Prochilodus scrofa at low and high pH.Aquaculture 2006;25:109–17.

Celik ES. Blood chemistry (electrolytes, lipoproteins and enzymes) values ofblack scorpion fish (Scorpaena porcus) in the Dardanelles. Turkey J Biol Sci2004;4(6):716–9.

Cooper GR, Mc Daniel V. The determination of glucose by the O-toluidine method.Stand Meth Clin Chem 1970;6:159–70.

Dahiya S, Kaur A, Jain N. Studies on difluoridation of water with Eichornia plant. JEnviron Biol 2000;21(4):337–40.

de la Torre FR, Salibian A, Ferrari L. Biomarkers assessment in juvenile Cyprinus carpioexposed to waterborne cadmium. Environ Pollut 2000;109:277–82.

Dongmeza E, Siddhuraju P, Francis G, Becker K. Effects of dehydrated methanolextracts of moringa (Moringa oleifera Lam.) leaves and three of its fractions ongrowth performance and feed nutrient assimilation in Nile tilapia (Oreochromisniloticus L.). Aquaculture 2006;261:407–22.

Drabkin DL. Spectrometric studies. XIV. The crystallographic and optimal propertiesof the hemoglobin of man in comparison with those of other species. J Biol Chem1946;164:703–23.

Faizi S, Siddiqui BS, Saleem R, Siddiqui S, Aftab K, Gilani AH. Isolation and structureelucidation of new nitrile and mustard oil glycosides from Moringa oleifera andtheir effect on blood pressure. J Nat Prod 1994;57:1256–61.

FAO. FAO Fisheries circular 886. Rev 2004; 2004. p. 25–9.Ferreira JG, Hawkins AJS, Bricker SB. Management of productivity, environmen-

tal effects and profitability of shellfish aquaculture—the Farm AquacultureResource Management (FARM) model. Aquaculture 2007;264:160–74.

Ferreira PMP. Atividade Larvicida do Extrato Aquoso de Moringa oleifera Lamarckcontra Aedes aegypti Linnaeus: Identificacao Parcial e Caracterizacao Toxico-logica do Principio Ativo. Monografia de Graduacao em Ciencias Biologicas,Fortaleza. Universidade Federal do Ceara; 2004. p. 70.

Finney DJ. Statistical methods in biological assay. 3rd ed. London, UK: Griffin Press;1978. p. 508.

Francis G, Makkar HPS, Becker K. Antinutritional factors present in plant-derived alternate fish feed ingredients and their effects in fish. Aquaculture2001;199:197–227.

Gabriel UU, George ADI. Plasma enzymes in Clarias gariepinus exposed to chroniclevels of round up (glyphosate). Environ Ecol 2005;23(2):271–6.

Gabriel UU, Obomanu FG, Edori OS. Haematology, plasma enzymes and organ indicesof Clarias gariepinus after intramuscular injection with aqueous leaves extractsof Lepidagathis alopecuroides. Afr J Biochem Res 2009;3(9):312–6.

Grabow WOK, Slabbert JL, Morgan WSG, Jahn SAA. Toxicity and mutagenicityevaluation of water coagulated with Moringa oleifera seed preparation usingfish protozoan, bacterial coliphage, enzyme and salmonella assay. CAB Abstr1985:1984–6.

Jahn SAA. Using moringa seeds as coagulants in developing countries. J Am WaterWorks Assoc 1988;80:43–50.

Jastrzebska EB, Protasowickiz M. Effects of cadmium and nickel exposure on hema-tological parameters of common carp, Cyprinus carpio L. Acta Ichthyol Piscat2005;35(1):29–38.

Kavitha C, Malarvizhi A, Senthil Kumaran S, Ramesh M. Toxicological effects of arse-nate exposure on hematological, biochemical and liver transaminases activityin an Indian major carp, Catla catla. Food Chem Toxicol 2010;48:2848–54.

Kind PRN, King EJ. Estimation of plasma phosphatase by determination of hydrolysedphenol with amino-antipyrine. J Clin Path 1954;7:322–6.

Kohler HR, Sandu C, Scheil V, Nagy-Petrica EM, Segner H, Telcean I, et al. Monitoringpollution in River Mures, Romania. Part III: Biochemical effect markers in fishand integrative reflection. Environ Monit Assess 2007;127:47–54.

Kori-Siakpere O, Ubogu EO. Sublethal haematological effects of zinc on thefreshwater fish, Heteroclarias sp. (Osteichthyes: Clariidae). Afr J Biotechnol2008;7:2068–73.

Kumar A, Prasad MR, Mishra D, Srivastav SK, Srivastav AK. Toxicity of aqueous extractof Euphorbia tirucalli latex on catfish, Heteropneustes fossilis. Ecotoxicol EnvironSafe 2010;73(7):1671–3.

Kwaambawa HM, Maikokera R. A fluorescence spectroscopic study of a coagulatingprotein extracted from Moringa oleifera seeds. Colloids Surf B 2007;60:213–20.

Larsson A, Haux C, Johansson-Sjobeck ML. Fish physiology and metal pollution:results and experiences from laboratory and field studies. Ecotoxicol EnvironSafe 1985;9:250–81.

Lim C, Dominy W. Utilization of plant proteins by warm water Fish. Hawaii: Amer-ican Soybean Association, USDA-ARS, Tropical Aquaculture Research Unit, TheOceanic Institute; 1989.

Lowry OH, Rosebrough NJ, Farr AL, Randall RI. Protein measurement with Folinphenol reagent. J Biol Chem 1951;193:265–75.

Makkar HPS, Becker K. Nutrient and antiquality factors in different morphologicalparts of Moringa oleifera tree. J Agric Sci (Cambridge) 1997;128:311–22.

Martinez CBR, Souza MM. Acute effects of nitrite on ion regulation in two Neotropicalfish species. Comp Biochem Physiol A 2002;133:151–60.

Muyibi SA, Evison LM. Moringa oleifera seeds for softening hard water. Water Res1995;29:1099–104.

Ndabigengesere A, Nasarasiah KS. Quality of water treated by coagulation usingMoringa oleifera seeds. Water Res 1998;32:781–91.

Nelson DA, Morris MW. Basic methodology. Hematology and coagulation, part IV. In:Nelson DA, Henry JB, editors. Clinical diagnosis and management by laboratorymethods. 17th ed. Philadelphia, USA: W.B. Saunder Company; 1989. p. 578–625[Chapter 27].

Nemcsok J, Benedeczky I. Effect of sublethal concentrations of phenol on someenzyme activities and blood sugar level of carp, Cyprinus carpio (L.). EnvironMonit Assess 1990;14:377–83.

Olufayo MO. Hematological characteristics of Clarias gariepinus (Burchell 1822)juveniles exposed to Derris elliptica root powder. Afr J Food Agric Nutr Sci2009;9(3):920–33.

Omoniyi I, Agbon AO, Sodunke SA. Effect of lethal and sublethal concentrationsof tobacco (Nicotiana tobaccum) leaf dust extract on weight and hemato-logical changes in Clarias gariepinus (Burch.). J Appl Sci Environ Manage2002;6(2):37–41.

Osman AGM, Koutb M, Sayed AEDH. Use of hematological parameters to assess theefficiency of quince (Cydonia oblonga Miller) leaf extract in alleviation of theeffect of ultraviolet—a radiation on African catfish Clarias gariepinus (Burchell,1822). J Photochem Photobiol B Biol 2010;99:1–8.

Price ML. The moringa tree. USA: ECHO Development Note; 2000.Ramachandran C, Peter KV, Gopalakrishnan PK. Drumstick (Moringa oleifera): a mul-

tipurpose Indian vegetable. Econ Bot 1980;34:276–83.Rao KNV, Gopalakrishnan V, Loganathan V. Anti-inflammatory activity of Moringa

oleifera Lam. Ancient Sci Life 1999;18:195–8.Reitman S, Franckel S. A colorimetric method for the determination of serum

glutamic oxalo acetic and glutamic pyruvic transaminase. Am J Clin Pathol1957;28:56–63.

Richard RH, Inglis V, Frerichs GN, Milloar SD. In: Working paper from the conference:problems of chemotherapy; from the theory of reality, vol. 12; 1991.

Rusia V, Sood SK. Routine haematological tests. In: Kanai L, Mukerjee, editors. Med-ical laboratory technology. I. Fifth reprint 1992. New Delhi: Tata McGraw HillPublishing Company Limited; 1992. p. 252–8.

Siddhuraju P, Becker K, Makkar HPS. Studies on the nutritional compositionand anti-nutritional factors of three different germplasm seed material of anunder-utilized tropical legume. Mucuna pruriens Var. Utilis. J Agric Food Chem2000;48:6048–60.

Singh A, Agarwal RA. Toxicity of the latex of euphorbiales. Effect on acid and alkalinephosphatase of the snail Lymnaea acuminata. Biol Agric Hortic 1992;8:211–9.


dx.doi.org/10.1016/j.etp.2011.01.001




Singh D, Singh A. Biochemical alteration in freshwater fish Channa punctatus due tolatices of Euphorbia royleana and Jatropha gossypifolia. Environ Toxicol Pharma-col 2002;12:129–36.

Singh D, Singh A. The toxicity of four native Indian plants: effect on AChEand acid/alkaline phosphatase level in fish Channa marulius. Chemosphere2005;60:135–40.

Sobecka E. Changes in the iron leveling the organs and tissues of wells catfish, Silurusglanis L. caused by nickel. Acta Ichthyol Piscat 2001;31(2):127–43.

Sprague JB. Measurement of pollution toxicity to fish. III. Sub-lethal effects and ‘safe’concentration. Water Res 1971;5:245–66.

Tiwari S, Singh A. Biochemical stress response in freshwater fish Channa punc-tatus induced by aqueous extracts of Euphorbia tirucalli plant. Chemosphere2006;64:36–42.

Tiwari S, Singh A. Control of common freshwater predatory fish, Channa punctatus,through Nerium indicum leaf extracts. Chemosphere 2003;53:865–75.

Tiwari S, Singh A. Piscicidal and anti-acetyl cholinesterase activity of Euphorbiaroyleana stem bark extracts against freshwater common predatory fish Channapunctatus. Environ Toxicol Pharmocol 2004;18:47–53.

van Vuren JH. The effect of toxicants on the hematology of Labeo umbratus (Teleostei:Cyprinidae). Comp Biochem Physiol C Pharmacol Toxicol 1986;83:155–9.

Vorbrodt A. The role of phosphatase in intracellular metabolism. Postepy Hig MedDosw 1959;13:200–6.

Vutukuru SS, Pauleena JS, Rao JV, Anjaneyulu Y. Architectural changes in the gillmorphology of the freshwater fish, Esomus danricus as potential biomarkers ofcopper toxicity using automated video tracking system. Environ Bioindicator2007;2:3–14.

Winkaler EU, Santos TRM, Machado-Neto JG, Martinez CBR. Acute lethal and sub-lethal effects of neem leaf extract on the Neotropical freshwater fish Prochiloduslineatus. Comp Biochem Physiol C 2007;145:236–44.

Wintrobe MM. Clinical haematology. London, UK: Henry Kimpton; 1978. p. 488.


dx.doi.org/10.1016/j.etp.2011.01.001


Article

SPECIAL TOPICS:

Environmental Chemistry February 2011 Vol.56 No.6: 508–513

doi: 10.1007/s11434-010-4315-9

In vitro assay for human thyroid hormone receptor β agonist and antagonist effects of individual polychlorinated naphthalenes and Halowax mixtures

LI Na1, MA Mei1, WANG ZiJian1* & SENTHIL KUMARAN Satyanarayanan2

1 State Key Laboratory of Environmental Aquatic Chemistry, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences , Beijing 100085, China;


Received April 15, 2010; accepted August 3, 2010

Polychlorinated naphthalenes (PCNs) are dioxin-like environmental contaminants. There is growing concern over the endo-crine-disrupting effects of PCNs, but very few studies have investigated the effect of PCNs on the thyroid system. This study used a yeast two-hybrid assay, which included the recombinant human thyroid receptor(TR)-β and reporter genes, to characterize the TRβ-disrupting effects of five individual PCN congeners, five PCN Halowax mixtures, and naphthalene. Their agonist and an-tagonist effects were studied in the absence and presence of 5×10–7 mol/L 3,3′,5-triiodo-L-thyronine, which induced submaximal β-galactosidase activity. Naphthalene, 1,2,3,4,5,6,7,8-octachloronaphthalene and all of the Halowax mixtures (Halowax 1000, 1001, 1013, 1014 and 1099) showed no agonist or antagonist activity on TRβ at the concentrations tested (up to 10–2 g/L). The lighter PCN congeners, namely 1-chloronaphthalene, 2-chloronaphthalene, 1,4-dichloronaphthalene and 1,2,3,4-tetrachloronaphthalene showed no agonist activity but showed significant antagonist activity on TRβ. The 20% relative inhibitory concentrations of these PCNs were less than 9.13 × 10–3 g/L. Thus, bioaccumulation of these lighter PCN congeners may disrupt the thyroid hormone system and inhibit TR-mediated cellular responses. Studies in the future should investigate the possible associations between the presence PCNs and adverse health outcomes.

in vitro bioassay, thyroid hormone receptors, polychlorinated naphthalenes, yeast two-hybrid assay

Citation: Li N, Ma M, Wang Z J, et al. In vitro assay for human thyroid hormone receptor β agonist and antagonist effects of individual polychlorinated naphtha-lenes and Halowax mixtures. Chinese Sci Bull, 2011, 56: 508−513, doi: 10.1007/s11434-010-4315-9

Concern over the effects of environmental chemicals on wildlife and humans via changes in endocrine systems has greatly increased over the last few decades [1]. Environ-mental estrogens have been the focus of the majority of studies in for over 20 years [2,3]. However, in recent years, the effects of synthetic chemicals on the thyroid system have received increasing attention because abundant evi-dence from in vivo and in vitro studies has demonstrated that the thyroid system is particularly vulnerable to endo-crine-disrupting effects [4].

Normal levels of thyroid hormones are essential for ap- *Corresponding author (email: [email protected])

propriate growth and development in fetal life and child-hood. Changes in thyroid hormone levels can adversely affect fertility and postnatal development in humans and animals [5]. Many environmental chemicals have been found to influence thyroid function, including polychlorinated bi-phenyls (PCBs), dioxins, polybrominated diphenylethers (PBDEs), polybrominated biphenyls (PBBs), phenols and phthalates [4]. In particular, the polyhalogenated aromatic hydrocarbons (PHAHs), such as PCBs, PBDEs and PBBs, have attracted much attention because of their ability to disrupt thyroid function due to their environmental persis-tence and lipophilicity. For example, PCBs can decrease the levels of circulating thyroid hormones [6] and BDE209 was


Li N, et al. Chinese Sci Bull February (2011) Vol.56 No.6 509

found to disrupt thyroid receptors (TRs) in vitro using the T-Screen method [7]. Meanwhile, in rodent studies, PBDEs reduced the circulating levels of thyroid hormones and showed an even closer structural relationship to 3,3′,5,5′- tetraiodo-L-thyronine (T4) than PCBs [8].

Polychlorinated naphthalenes (PCNs) are a group of in-dustrial chemicals belonging to the PHAH family, and con-sist of naphthalene substituted with 1–8 chlorine atoms [9]. PCNs are structurally similar to PCBs and they exhibit similar physical and chemical properties to PCBs [9]. PCNs are used as wood preservatives, for cable insulation, elec-troplating masking compounds, and in dye production [10]. The production and use of PCNs were banned in Europe and in the United States in the 1980s because of their toxicity and environmental persistence [11]. However, the global production of PCNs is estimated at about 150000 metric tons [12]. PCNs are still being released to the envi-ronment as contaminants of other industrial mixtures and as byproducts of solid waste combustion [13], while illegal importation of PCN-containing products into Japan has been reported after 2000 [14]. It is clear that PCNs are widespread pollutants and, with recent developments in analytical methods and increased availability of standards, they have been detected in air, water, sediment and biota [15]. PCNs are highly hydrophobic, semi-volatile, thermally stable, and low flammability, and they are detected in par-ticularly high levels in aquatic organisms, posing a severe threat to the environment [15]. Recently, PCNs were de-fined as persistent organic pollutants in the Convention on Long-Range Transboundary Air Pollution by the United Nations Economic Commission for Europe [16]. However, the toxic responses associated with PCNs were mostly studied in terms of aryl hydrocarbon receptor-dependent mechanisms of action [17,18], but their toxicity may also be mediated via other independent mechanisms. To date, very few studies have evaluated the disruptive activity of PCNs on thyroid function, which is known to be vulnerable to PHAHs. Therefore, there is an urgent need to evaluate these effects of PCNs.

The direct effects of chemicals on thyroid hormone re-ceptors appear to be more important and sensitive endpoints than simply analyzing circulating hormone levels, thyroid size or histopathology, because most of the bioactivity of steroid hormones is mediated through their receptors to regulate the transcription of target genes in ligand-depend ent manners [19,20]. In our previous study [21], we developed a yeast two-hybrid system to screen chemicals with agonist or antagonist activity on TRβ and found that many chemicals, including PCBs, PBDEs, PBBs, flame retar-dants, phthalates, pesticides and phenols target the TRβ. The yeast cells were co-transformed with human TRβ and a coactivator of human TRβ (GRIP1); therefore, this system overcomes the differences in transcriptional activation of yeast and vertebrates [22]. The aim of the present study was to determine whether PCNs have the capacity to disrupt TRβ. For in vitro screening, we tested five Halowax mix-tures (Koppers Company, Pittsburgh, PA, USA), which are typical PCN formulations, and five other PCNs using this yeast two-hybrid assay.


1.1 Chemicals

Dimethyl sulfoxide (DMSO, 99.5%), 3,3′,5-triiodo-L-thy-ronine (T3, 95%) and 3,3′,5,5′-tetraiodo-L-thyronine (T4, 95%) were purchased from Sigma Chemicals (St. Louis, MO, USA). All of the PCNs (Table 1) were obtained from AccuStandard (New Haven, CT, USA). Amiodarone hy-drochloride (AH, >95%) was purchased from Shanghai Pharmaceuticals Co. (Shanghai, China). Stock solutions of all compounds were prepared in DMSO.

1.2 β-Galactosidase assay

All bioassays, including the agonist and antagonist activity tests, were conducted using the yeast strain hTRβ-GRIP1,

Table 1 Chemicals tested in this study

Chemicals Abbreviation Supplier CAS no. Purity

Naphthalene Naphthalene Accustandard 91-20-3 99.80%

1-Chloronaphthalene 1-CN Accustandard 90-13-1 100%

2-Chloronaphthalene 2-CN Accustandard 91-58-7 98.50%

1,4-Dichloronaphthalene 1,4-DiCN Accustandard 1825-31-6 99.40%

1,2,3,4-Tetrachloronaphthalene 1, 2, 3, 4-TeCN Accustandard 20020-02-4 100%

1,2,3,4,5,6,7,8-Octachloronaphthalene OCN Accustandard 2234-13-1 98.30%

Halowax 1000 mono-diCN (26% Cl) Halowax 1000 Accustandard 58718-66-4 Tech Mix

Halowax 1001 di-penta (50% Cl) Halowax 1001 Accustandard 58718-67-5 Tech Mix

Halowax 1013 tri-pentaCN (56% Cl) Halowax 1013 Accustandard 1321-64-8 Tech Mix

Halowax 1014 tetra-hexaCN (62% Cl) Halowax 1014 Accustandard 1335-87-1 Tech Mix

Halowax 1099 di-pentaCN (52% Cl) Halowax 1099 Accustandard 39450-05-0 Tech Mix


510 Li N, et al. Chinese Sci Bull February (2011) Vol.56 No.6

as described previously [21]. All assays were conducted in at least triplicate. Exponentially growing overnight cultures were diluted with synthetic dropout nutrient medium lack-ing tryptophan and leucine (SD/-Trp-Leu) to an optical den-sity (A) at 600 nm of 0.75. Each test chemical was serially diluted in DMSO to generate 6–8 concentrations. Five mi-croliters of each dilution was combined with 995 μL of me-dium containing 5×103 yeast cells/mL, resulting in a test culture in which the volume of DMSO did not exceed 1.0% of the total volume (1.0% DMSO has no toxicity on this system). Each assay group included a positive control (T3) and a negative control (DMSO). To determine agonist ac-tivity, the PCNs were tested in the absence of T3. Antago-nist activity was determined in the presence of 5×10–7 mol/L of T3, a concentration that produces a submaximal stimulatory response [23].

Test cultures (200 μL) were transferred to each well of a 96-well plate and incubated at 30°C with vigorous orbital shaking (300×g) on a titer plate shaker (Heidolph TITRAMAX 1000, Germany) for 2 h. The cell density of the culture was then measured at a wavelength of 600 nm (TECAN GENios A-5002, Austria). Next, 50 μL of the test culture was transferred to a new 96-well plate and followed by the addition of 120 μL of of Z-buffer (16.1 g/L Na2HPO4·7H2O; 5.5 g/L NaH2PO4·H2O; 0.75 g/L KCl; 0.246 g/L MgSO4·7H2O) and 20 μL of chloroform. The samples were carefully mixed (vortex 25 s) and preincu-bated for 5 min at 30°C. The enzyme reaction was started by adding 40 μL of o-nitrophenyl-β-D-galactopyranoside (13.3 mmol/L, dissolved in Z-buffer) and incubated at 30°C on the titer plate shaker for 60 min. The reactions were ter-minated by adding 100 μL of Na2CO3 (1 mol/L). After cen-trifugation at 12000×g for 15 min (Sigma Laborzentrifugen 2K15, Germany), 200 μL of the supernatant was transferred into a new 96-well plate and the A420 nm was determined (TECAN GENios A-5002, Austria).

The β-galactosidase activity was calculated using the equations u=Cs/t·V·D·ODS and Cs=10–6(AS–AB)/ε·d, where u=β-galactosidase activity, t=enzyme reaction incubation time, V=volume of the test culture, D=dilution factor, ODS=A600 of the test culture, AS=A420 of the enzyme reaction supernatant of the sample, AB=A420 of the enzyme reaction supernatant of the blank, ε=ε for o-nitrophenol in the enzyme assay reaction mix, and d=diameter of the cuvette [23].

To exclude false results caused by cytotoxicity of the yeast, the viability of the cells was determined spectropho-tometrically as a change of cell density (A600 nm) of the assay medium, as previously described (Table 2) [21].

1.3 Data analysis

The 20% relative effective concentration (REC20) of each compound (inducing 20% of the maximum effect) and/or

Table 2 Two-hybrid TR bioassay used to determine the possible endo-crine disrupting potencya)

Reference material Endpoint REC50 or RIC50 (mol L–1)

T3 Agonistic activity of TR 1.1 × 10–7

T4 Agonistic activity of TR 2.7 × 10–7

AH Antagonistic activity of TR

in the presence of T3 2.4 × 10–7

a) According to [21]. TR = thyroid receptor; T3 = 3,3′,5-triiodo-L-thy-ronine; T4 = 3,3′,5,5′-tetraiodo-L-thyronine; AH = amiodarone hydrochlo-ride; REC50 = concentration inducing 50% of the maximum effect; RIC50 = concentration causing a 50% inhibition of the maximum effect.

the 20% relative inhibitory concentration (RIC20) of each compound (reducing 20% of the maximum effect) were calculated from a dose-response curve generated using a four-parameter logistic model based on the Marquardt- Levenberg algorithm (Sigmaplot 4.0, SPSS, Chicago, IL, USA) [24]. For data analysis, REC20 and RIC20 values were used to identify whether the tested chemicals had ago-nist or antagonist activities. If the magnitudes of the agonist or antagonist effects of the tested chemicals were less than 10%, they were considered to have no effect on the TR at these concentrations.

2 Results

To determine the agonist activity of PCNs, the yeast strains were treated with varying concentrations of PCNs, and β-galactosidase activities were measured. We found that β-galactosidase activity was not induced by PCNs, even at the highest concentration of 1.0 × 10–2 g/L. Therefore, none of the chemicals tested acted as TR agonists at the concen-trations used here. The dose-response relationships are pre-sented in Figure 1.

To determine the antagonist activity of PCNs, they were co-administered with 5×10–7 mol/L of T3, a concentration that induced submaximal β-galactosidase expression. This test revealed that some PCNs inhibited β-galactosidase ac-tivities in dose-dependent manners and that some of the PCNs were TR antagonists. In brief, Halowax 1000, Halowax 1001, Halowax 1013, Halowax 1014, Halowax 1099, naph-thalene and OCN did not exhibit TR antagonist effects. By contrast, 1-chloronaphthalene (1-CN), 2-chloronaphthalene (2-CN), 1,4-dichloronaphthalene (1,4-DiCN) and 1,2,3,4- tetrachloronaphthalene (1,2,3,4-TeCN) were TR antago-nists, acting in a dose-dependent manner (Figure 2). The RIC20s of 1-CN, 2-CN, 1,4-DiCN and 1,2,3,4-TeCN were 5.82×10–3, 9.13×10–3, 3.04×10–3 and 2.47×10–3 g/L, respec-tively (Table 3).

3 Discussion

In recent years, PCNs have been a focus of research using a



Figure 1 Dose-response activities of polychlorinated naphthalenes using the yeast strain hTR-GRIP1 system to determine their activity as agonists of the thyroid receptor (TR). The agonistic activity of each chemical is represented as the percent induction activity relative to the maximum induced by 3,3′,5-triiodo-L-thyronine (T3). Values are means ± standard error (n = 3). OCN = 1,2,3,4,5,6,7,8-octachloronaphthalene; 1-CN = 1-chloronaphthalene; 2-CN = 2-chloronaphthalene; 1,4-DiCN = 1,4-dichloronaphthalene; 1,2,3,4-TeCN = 1,2,3,4-tetrachloronaphthalene.

Table 3 Thyroid receptor (TR) agonistic and antagonistic potency of polychlorinated naphthalenes (PCNs) in the yeast strain hTR-GRIP1 assay a)

Compounds TR agonistic activity

REC20 (g L−1) TR antagonistic activity

RIC20 (g L–1)

Naphthalene – –

1-CN – 5.82 × 10–3

2-CN – 9.13 × 10–3

1,4-DiCN – 3.04 × 10–3

1,2,3,4-TeCN – 2.47 × 10–3

OCN – –

Halowax 1000 – –




Halowax 1099

a) Values are means ± standard error (n = 3). REC20 = concentration in-ducing 20% of the maximum effect; RIC20 = concentration reducing the maximum effect by 20%; OCN = 1,2,3,4,5,6,7,8-octachloronaphthalene; 1-CN=1-chloronaphthalene; 2-CN=2-chloronaphthalene; 1,4-DiCN=1,4- dichloronaphthalene; 1,2,3,4-TeCN = 1,2,3,4-tetrachloronaphthalene; –, no response.

variety of analytical methods, to determine their levels in the food chain and human or animal exposure, and the presence in the Laurentian Great Lakes ecosystem [15,25–27]. How-ever, to our knowledge, very few studies have examined the effects of PCNs on the thyroid hormone system.

In this study, we examined the thyroid-disrupting poten-cies of PCNs, and all of the PCNs tested here were ineffec-tive as TRβ agonists. However, some of the PCNs acted as TR antagonists at low concentrations (RIC20 < 9.13 × 10–3

g/L), and acted in dose-dependent manners. These results confirm those of our previous study using other PHAHs that PCBs, PBBs and PBDEs are not agonists for the TRβ, but instead acted as antagonists at very low concentration (RIC20s <5×10–7 g/L) [21]. Similar results were reported by Schriks et al. [7] for other PHAHs, where it was found that BDE206 was an antagonist and did not respond in the T-screen when tested in the absence of T3. PCNs were weaker TR antagonists than PCBs, PBBs and PBDEs, but had a simi-lar antagonist activity as phenols, phthalate, pesticides and bisphenol A derivatives [21]. The finding that the PCNs tested in this study have considerable thyroid antagonist effects is


512 Li N, et al. Chinese Sci Bull February (2011) Vol.56 No.6

Figure 2 Dose-response activities of polychlorinated naphthalenes using the yeast strain hTR-GRIP1 system to determine their activity as antagonists for the thyroid receptor (TR). The antagonistic activity of each chemical is represented as the percent inhibition activity relative to the maximum induced by 3,3′,5-triiodo-L-thyronine (T3). Values are means ± standard error (n = 3). OCN = 1,2,3,4,5,6,7,8-octachloronaphthalene; 1-CN = 1-chloronaphthalene; 2-CN = 2-chloronaphthalene; 1,4-DiCN = 1,4-dichloronaphthalene; 1,2,3,4-TeCN = 1,2,3,4-tetrachloronaphthalene.

particularly interesting. The thyroid-disrupting potencies of individual PCN con-

geners differ compared with their relative dioxin-like activi-ties.The dioxin-like activities of individual PCN congeners were found to be related to their chemical structures in terms of the number of chlorine molecules and the positions of these chlorine molecules. Monochlorinated, dichlorinated, trichlorinated and tetrachlorinated congeners were relatively inactive while pentachlorinated, hexachlorinated, and hepta-chlorinated congeners were the most potent [18]. In the pre-sent study, 1-CN, 2-CN, 1,4-DiCN and 1,2,3,4-TeCN exhib-ited similar potencies as TRβ antagonists, while OCN was not an antagonist for TRβ at the concentrations tested. This indicates that the lighter congeners show greater potential to disrupt the thyroid system, which is different from their di-oxin-like activities. Of note, most of the PCNs present in air are the lighter congeners; trichlorinated and tetrachlorinated naphthalenes account for approximately 80% and 90–95% of the total PCN mass in ambient and arctic air, respectively, based on air sampling of PCNs in the United Kingdom, and it

was concluded that air masses from the United Kingdom and Europe may be influencing PCN burdens more than PCBs [28,29]. Thus, the thyroid-disrupting effects of the lighter congeners may cause severe adverse effects in human acting via airborne exposure.

PCN mixtures are produced in several countries under the tradenames Halowax, Nibren, Clonaicre and Seekay waxes and Cerifal Materials, and are used worldwide, and persist in the environment causing long-term adverse effects [12]. In the present study, none of the Halowax compounds tested acted as agonists or antagonists of TRβ. Some reports have demonstrated the toxicity of Halowax mixtures. For example, Halowax 1014 was reported to induce hepatic ethoxyresorufin-O-deethylase (EROD) activity in rainbow trout [30], while Halowaxes 1014 and 1013 were reported to be toxic to medaka (Oryzias latipes) during early life [18]. From the results in the present study, we may speculate that only a few PCNs contained in Halowax mixtures can dis-rupt TRβ or that the concentrations of PCNs that act as ago-nists or antagonists for TRβ are very low in Halowax mix-



tures. In the present study, the RIC20s of these PCNs ranged

from 2.47×10–3 g/L to 9.13×10–3 g/L. Because these mole-cules readily bioaccumulate within the food chain [26] and T3 and T4 are always present in vivo (T3: 13.9–26.4 nmol; T4: 80–103 nmol) [31], PCNs may act as antagonists in hu-man and animals if their accumulation within the body reaches a threshold level. Thus, PCNs must receive greater attention and more comprehensive studies, including in vivo tests, are needed to collect more information for adequate risk assessment. If PCNs combine with other thyroid-disrupting chemicals such as phenols, phthalate, parabens and pesticides, their adverse effects in humans may escalate. Therefore, future studies should evaluate the possible link between the presence of additional PCNs and biological health.

This study was supported by the National Basic Research Program of China (2009CB421605) and the National Natural Science Foundation of China (20877089 and 20737003).

1 Sonnenschein C, Soto A M. An updated review of environmental es-trogen and androgen mimics and antagonists. J Steroid Biochem Mol Biol, 1998, 65: 143–150

2 Miller D, Wheals B B, Beresford N, et al. Estrogenic activity of phe-nolic additives determined by an in vitro yeast bioassay. Environ Health Perspect, 2001, 109: 133–138

3 Takeyoshi M, Yamasaki K, Sawaki M, et al. The efficacy of endo-crine disruptor screening tests in detecting anti-estrogenic effects downstream of receptor-ligand interactions. Toxicol Lett, 2002, 126: 91–98

4 Boas M, Feldt-Rasmussen U, Skakkebaek N E, et al. Environmental chemicals and thyroid function. Eur J Endocrinol, 2006, 154: 599–611

5 de Escobar G M, Obregón M J, del Rey F E. Maternal thyroid hor-mones early in pregnancy and fetal brain development. Best Pract Res Clin Endoc Metab, 2004, 18: 225–248

6 van der Plas S A, Lutkeschipholt I, Spenkelink B, et al. Effects of subchronic exposure to complex mixtures of dioxin-like and non-dioxin-like polyhalogenated aromatic compounds on thyroid hormone and vitamin A levels in female Sprague-Dawley rats. Toxi-col Sci, 2001, 59: 92–100

7 Schriks M, Vrabie C M, Gutleb A C, et al. T-screen to quantify func-tional potentiating, antagonistic and thyroid hormone-like activities of poly halogenated aromatic hydrocarbons (PHAHs). Toxicol Vitro, 2006, 20: 490–498

8 Fowles J R, Fairbrother A, Baecher-Steppan L, et al. Immunologic and endocrine effects of the flame-retardant pentabromodiphenyl ether (DE-71) in C57BL/6J mice. Toxicology, 1994, 86: 49–61

9 World Health Organization. Chlorinated Naphthalenes. Concise In-ternational Chemical Assessment Document 34. Geneva, 2001

10 Kannan K, Imagawa T, Blankenship A L, et al. Isomer-specific analysis and toxic evaluation of polychlorinated naphthalenes in soil, sediment, and biota collected near the site of a former chlor-alkali plant. Environ Sci Technol, 1998, 32: 2507–2514

11 Hayward D. Identification of bioaccumulating polychlorinated naph-thalenes and their toxicological significance. Environ Res, 1998, 76: 1–18

12 Falandysz J. Polychlorinated naphthalenes: An environmental update.

Environ Pollut, 1998, 101: 77–90 13 Benfenati E, Mariani G, Fanelli R, et al. “De novo” synthesis of

PCDD, PCDF, PCB, PCN and PAH in a pilot incinerator. Chemos-phere, 1991, 22: 1045–1052

14 Yamashita N, Taniyasu S, Hanari N, et al. Polychlorinated naphtha-lene contamination of some recently manufactured industrial products and commercial goods in Japan. J Environ Sci Health Part A-Toxic/ Hazard Subst Environ Eng, 2003, 38: 1745–1759

15 Falandysz J. Chloronaphthalenes as food-chain contaminants: A re-view. Food Addit Contam, 2003, 20: 995–1014

16 United Nations Economic Commission for Europe. Technical Input for Reviewing Substances Under the 1998 Protocol on Persistent Or-ganic Pollutants. Working Group on Strategies and Review, Thirty- eighth Session, Item 4 of the Provisional Agenda, 19–22 September 2006, Geneva

17 Blankenship A L, Kannan K, Villalobos S A, et al. Relative potencies of individual polychlorinated naphthalenes and Halowax mixtures to induce Ah receptor-mediated responses. Environ Sci Technol, 2000, 34: 3153–3158

18 Villeneuve D L, Kannan K, Khim J S, et al. Relative potencies of in-dividual polychlorinated naphthalenes to induce dioxin-like responses in fish and mammalian in vitro bioassays. Arch Environ Contam Toxicol, 2000, 39: 273–281

19 Brucker-Davis F. Effects of environmental synthetic chemicals on thyroid function. Thyroid, 1998, 8: 827–856

20 Kitagawa H, Fujiki R, Yoshimura K, et al. The chromatin-remodeling complex WINAC targets a nuclear receptor to promoters and is im-paired in Williams syndrome. Cell, 2003, 113: 905–917

21 Li J, Ma M, Wang Z J. A two-hybrid yeast assay to quantify the ef-fects of xenobiotics on thyroid hormone-mediated gene expression. Environ Toxicol Chem, 2008, 27: 159–167

22 Nishikawa J-I, Saito K, GOTO J, et al. New screening methods for chemicals with hormonal activities using interaction of nuclear hor-mone receptor with coactivator. Toxicol Appl Pharmacol, 1999, 154: 76–83

23 Gaido K W, Leonard L S, Lovell S, et al. Evaluation of chemicals with endocrine modulating activity in a yeast-based steroid hormone receptor gene transcription assay. Toxicol Appl Pharmacol, 1997, 143: 205–212

24 Rehmann R K, Schramm K W, Kettrup A A. Applicability of a yeast oestrogen screen for the detection of oestrogen-like activities in en-vironmental samples. Chemophere, 1999, 38: 3303–3312

25 Kucklick J, Helm P. Advances in the environmental analysis of polychlorinated naphthalenes and toxaphene. Anal Bioanal Chem, 2006, 386: 819–836

26 Domingo J L. Polychlorinated naphthalenes in animal aquatic species and human exposure through the diet: A review. J Chromatogr A, 2004, 1054: 327–334

27 Helm P A, Jantunen L M, Ridal J, et al. Spatial distribution of poly-chlorinated naphthalenes in air over the Great Lakes and air-water gas exchange in Lake Ontario. Environ Toxicol Chem, 2003, 22: 1937–1944

28 Harner T, Kylin H, Bidleman T F, et al. Polychlorinated naphthalenes and coplanar polychlorinated biphenyls in arctic air. Environ Sci Technol, 1998, 32: 3257–3265

29 Harner T, Lee R G M, Jones K C. Polychlorinated naphthalenes in the atmosphere of the United Kingdom. Environ Sci Technol, 2000, 34: 3137–3142

30 Norrgren L, Andersson T, Björk M. Liver morphology and cyto-chrome P450 activity in fry of rainbow trout after microinjection of lipid-soluble xenobiotics in the yolk-sac embryos. Aquat Toxicol, 1993, 26: 307–316

31 Henneman G, ed. Thyroid Hormone Metabolism. New York: Marcel Dekker, 1986




Journal of Environmental Sciences 2011, 23(2) 301–306

Estrogen-related receptor γ disruption of source water and drinking watertreatment processes extracts

Na Li1, Weiwei Jiang1, Kaifeng Rao1, Mei Ma1, Zijian Wang1,∗,Satyanarayanan Senthik Kumaran2

1. Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China. E-mail: [email protected]. Unit of Toxicology, Bharathiar University, Coimbatore 641046, India

Received 31 March 2010; revised 19 November 2010; accepted 24 November 2010

AbstractEnvironmental chemicals in drinking water can impact human health through nuclear receptors. Additionally, estrogen-related

receptors (ERRs) are vulnerable to endocrine-disrupting effects. To date, however, ERR disruption of drinking water potency hasnot been reported. We used ERRγ two-hybrid yeast assay to screen ERRγ disrupting activities in a drinking water treatment plant(DWTP) located in north China and in source water from a reservoir, focusing on agonistic, antagonistic, and inverse agonistic activityto 4-hydroxytamoxifen (4-OHT). Water treatment processes in the DWTP consisted of pre-chlorination, coagulation, coal and sandfiltration, activated carbon filtration, and secondary chlorination processes. Samples were extracted by solid phase extraction. Resultsshowed that ERRγ antagonistic activities were found in all sample extracts, but agonistic and inverse agonistic activity to 4-OHTwas not found. When calibrated with the toxic equivalent of 4-OHT, antagonistic effluent effects ranged from 3.4 to 33.1 µg/L. In thetreatment processes, secondary chlorination was effective in removing ERRγ antagonists, but the coagulation process led to significantlyincreased ERRγ antagonistic activity. The drinking water treatment processes removed 73.5% of ERRγ antagonists. To our knowledge,the occurrence of ERRγ disruption activities on source and drinking water in vitro had not been reported previously. It is vital, therefore,to increase our understanding of ERRγ disrupting activities in drinking water.

Key words: drinking water; estrogen receptor; estrogen-related receptor; two-hybrid yeast; solid phase extraction

DOI: 10.1016/S1001-0742(10)60406-8

Citation: Li N, Jiang W W, Rao K F, Ma M, Wang Z J, Kumaran S S, 2011. Estrogen-related receptor γ disruption of source water anddrinking water treatment processes extracts. Journal of Environmental Sciences, 23(2): 301–306

Introduction

Over the last several decades, an increasing number ofenvironmental contaminants have been found to disruptendocrine systems in wildlife and humans (Sonnenscheinand Soto, 1998). These endocrine disrupting chemicals(EDCs) can interact with human nuclear receptors (NRs),interfering with the endocrine system, causing develop-mental degeneration, reducing fecundity, and leading toan increase in human breast cancer (Colborn et al., 1993;Crews et al., 2000). Recently, EDCs have emerged as amajor water quality concern as they can interfere withendocrine systems when found at certain concentrationsin drinking water (Scruggs et al., 2005). Many EDCs arebiologically active at very low concentrations and havebeen detected in surface water (Heberer et al., 2002) anddrinking water (Stackelberg et al., 2004). This is of concernas many conventional treatment processes are ineffectivein completely removing EDCs from water (Johnson et al.,2007).

* Corresponding author. E-mail: [email protected]

While research has focused on the disruption activityof estrogen receptors (ERs) in water in recent years, farless attention has been paid to identifying compoundswith estrogen-related receptors (ERRs) disrupting activity.Increasing evidence from in vivo and in vitro stud-ies demonstrates, however, that ERRs are vulnerable toendocrine-disrupting effects (Horard and Vanacker, 2003)and are possibly disrupted by environmental chemicals(Takayanagi et al., 2006). Recent research has also doc-umented a correlation between ERs and ERRs in breastcancer patients (Ariazi et al., 2002), indicating that ERRdisrupting chemicals may play an important role in breasttumors. Therefore, the rate of elimination of ERRs disrupt-ing substances during the treatment process of drinkingwater and assessing the disrupting potency of surface waterresources are of considerable environmental importance.

Since their identification in the 1990s, ERRs have beenclassified as an orphan nuclear receptor subfamily asno endogenous ligands have been identified. Both ERRsand ERs have a high degree of amino acid sequencesimilarity and identity in their DNA-binding (DBD) and


302 Journal of Environmental Sciences 2011, 23(2) ??–?? / Na Li et al. Vol. 23

ligand-binding (LBD) domains (Horard and Vanacker,2003). ERRs can bind to functional estrogen responseelements (EREs) in ERs target genes, suggesting possiblesimilarities between ERRs and ERs action (Takayanagiet al., 2006). ERRγ and ERs functional crosstalk systemsmight explain low-dose effects of environmental estrogenbisphenol A (Takayanagi et al., 2006). Of the three ERRtypes, ERRα, ERRß and ERRγ (Giguere et al., 1988;Hong et al., 1999), ERRγ is essential for the develop-ment of the hypothalamic-hypophyseal-adrenocortical axis(Wilson et al., 1993; Luo et al., 1994), and is expressedin a number of human adult and fetal tissues includingthe brain, skeletal muscle, heart, kidney, and retina. Somesynthetic chemicals including bisphenol A, diethylstilbe-strol, 4-nonylphenol and some phytoestrogens can bind tohuman ERRγ (Tremblay et al., 2001; Coward et al., 2001;Greschik et al., 2004; Takayanagi et al., 2006), which havebeen detected in many environment samples and drinkingwater. Assessing the environmental pollutants interferingwith ERRγ is, therefore, of great importance.

We previously developed novel screening methods forchemicals with ERRγ disrupting properties using a yeasttwo-hybrid system, and found that some pesticides hadERRγ disrupting activity (Li et al., 2008a). Althoughmany endocrine disrupting chemicals can survive drinkingwater treatment (Westerhoff et al., 2005), little is knownabout the fate of ERRγ disrupting chemicals in drinkingwater and their possible effects on human health. In thepresent study we assessed, therefore, the ERRγ mediatedeffects in source and drinking waters using the yeast two-hybrid system. As ERRγ shows very high constitutiveactivity without ligand addition, the disrupting activitiesof drinking water extracts were tested with and with-out the standard antagonist4-hydroxytamoxifen (4-OHT)(Takayanagi et al., 2006) using ERRγ-GRIP1 yeast bymeasuring the change of β-galactosidase activity.


1.1 Chemicals

High performance liquid chromatography (HPLC)grade dichloromethane, hexane, methanol, and tert-butylmethyl ether were obtained from Fisher Scientific (FairLawn, USA). The 4-hydroxytamoxifen (4-OHT, 98%) anddimethyl sulfoxide (DMSO, 99.5%) were obtained fromSigma Chemical (USA). For all chemicals, stock solutionswere prepared in DMSO.

1.2 Sample collection and processing

Sampling was conducted in May 2007 at a drinkingwater treatment plant (DWTP) in north China. The DWTPhad four treatment lines with a total capacity of 1,500,000m3 per day. Samples were collected from line two, whichprocessed the source water from a reservoir. The DWTPconsisted of pre-chlorination, coagulation, coal and sandfiltration, activated carbon filtration, and secondary chlori-nation (Fig. 1).

Each water sample (20 L) was collected in a pre-cleaned

Source water

Pre-chlorination

Coagulation

Coal and sand filtration

Activated carbon

Secondary chlorination

A

B

C

D

E

F

Fig. 1 Flow scheme of the treatment processes and sampling locations(A–F).

amber glass bottle. The bottle was washed three times withdeionized water before sample collection. Approximately2 mL/L (V/V) of methanol was added to each sampleimmediately after sampling to suppress possible bioticactivity. All samples were stored at 4°C and treated within8 hr after sampling.

Water samples and procedural blank (Mini-Q water,18.2 Ω) were filtered with glass fiber filters (0.45 µm,Whatman, England) to remove insoluble materials. Solidphase extraction (SPE) was then performed using 500 mgOasis HLB cartridges (Waters, USA) conditioned accord-ing to the manufacturer’s directions. The cartridges wereforced under vacuum at a flow rate of approximately 6mL/min. The cartridges were kept under vacuum aspirationfor 5 min to dry off any residual water, and then washedtwice with 5 mL of hexane/dichloromethane (7/3, V/V),twice with 5 mL of tert-butyl methyl ether, twice with 5 mLof dichloromethane/methanol (9/1, V/V), and once with 5mL of methanol at a flow rate of 1 mL/min. The extractswere then combined and filtered by anhydrous sodiumsulphate to remove water and evaporated to dryness ina rotary evaporator (R-200, Buchi, France) at 40°C to 2mL. The dehydrated extract was then dried under gentlenitrogen flow and reconstituted in 0.1 mL of DMSO andused for bioassay immediately.

1.3 Bioassay

The bioassay was conducted using yeast strain hERRγ-GRIP1 (Li et al., 2008a). All assays were conducted in atleast triplicates. Each assay group included the sample, thepositive control (4-OHT for ERR antagonistic activity), thenegative control (DMSO), and the procedural blank. Testsamples (5 µL) of serial dilutions were combined with 995µL of medium containing 5×103 yeast cells/mL, resultingin a test culture in which the volume of DMSO did not


No. 2 Estrogen-related receptor γ disruption of source water and drinking water treatment processes extracts 303

exceed 1.0% of the total volume. Control assays wereperformed for all field blank and laboratory blank samplesand found to be lower than the detection limit.

Test cultures (200 µL) were transferred into each well ofa 96-well plate and incubated at 30°C with vigorous orbitalshaking (800 r/min) on a titer plate shaker (HeidolphTITRAMAX 1000, Hamburg, Germany) for 2 hr. Thecell density of the culture was then measured at 600-nmwavelength (TECAN GENios A-5002, Salzburg, Austria).After that, 50 µL of test culture was transferred to a new96-well plate and after addition of 120 µL of Z-buffer ((ing/L) Na2HPO4·7H2O 16.1; NaH2PO4·H2O 5.5; KCl 0.75;MgSO4·7H2O 0.246) and 20 µL of chloroform, the assayswere carefully mixed (vortex 25 sec) and preincubatedfor 5 min at 30°C. The enzyme reaction was startedby adding 40 µL of o-nitrophenyl-β-D-galactopyranoside(13.3 mmol/L, dissolved in Z-buffer), then incubated at30°C on a titer plate shaker for 60 min. The reactionswere terminated by the addition of 100 µL of Na2CO3(1 mol/L). After centrifugation at 12,000 ×g for 15 min(Sigma Laborzentrifugen 2K15, Osterode, Germany), 200µL of the supernatant was transferred into a new 96-wellplate and the OD420 nm was determined.

The β-galactosidase activity (u) was calculated accord-ing to the following Eqs. (1) and (2):

u = CS/t×V×D × ODS (1)

CS = 10−6(AS−AB) / ε × d (2)

where, CS: the concentration of o-nitrophenol in the en-zyme assay reaction mix, t (min): incubation duration ofthe enzyme reaction, V (µL): volume of the test culture,D: dilution factor, ODS: OD600 of test culture, AS: OD420of the enzyme supernatant of the sample, AB: OD420 ofthe enzyme reaction supernatant of the blank, ε: ε foro-nitrophenol in the enzyme assay reaction mix, and d:diameter of the cuvette (Routledge and Sumpter, 1996;Gaido et al., 1997; Li et al., 2008b).

To exclude false results caused by cytotoxicity, cell via-bility was determined spectrophotometrically as a changein cell density (OD600) in the assay medium. The procedu-ral blank was tested at the same concentration to monitorfor a false-positive result. Detailed steps are describedelsewhere (Li et al., 2008c).

1.4 Data analysis

Results were performed on the toxic equivalent (TEQ)approach (Qiao et al., 2006). The dose-response curve onthe inhibition of β-galactosidase expression by 4-OHT isdescribed in our previous work (Li et al., 2008a). Theextract responses were calibrated according to the dose-response curve of 4-OHT to obtain the bioassay derivedequivalent concentrations (TEQ). If necessary, the extractwas diluted to fit the linear part of the dose-response curvefor 4-OHT.

1E-9 1E-8 1E-7 1E-6 1E-5 1E-40

10

20

30

40

50

60

70

80

Inh

ibit

ion a

ctiv

ity (

%)

4-OHT concentration (mol/L)

Fig. 2 Inhibition of high constitutive β–galactosidase activity by4-hydroxytamoxifen (4-OHT) in yeast strain ERRγ-GRIP1. Chemicalantagonist activity is represented as inhibition activity percentage relativeto high constitutive activity in yeast strain ERRγ-GRIP1. Values areaverage ± standard error (n = 3).


2.1 Response to known ERRγ antagonist 4-OHT

The antagonistic activity of varying 4-OHT concen-trations was measured (Fig. 2). The 4-OHT antagonisticactivity in a concentration-dependent manner was similarto that previously reported (Li et al., 2008a). The halfmaximal effective concentration (EC50) value of 4-OHTwas 8.0 × 10−6 mol/L.

2.2 Response to drinking water extracts

Drinking water extracts did not increase β-galactosidaseactivity in the yeast assay compared with the negativecontrol. However, all extracts had ERRγ antagonistic ac-tivities that inhibited β-galactosidase expression. Removalrates of ERRγ antagonistic activities of B, C, D, E, andF treatment processes were –28.9%, –155.0%, –60.3%,–44.7% and 73.5% at fifty-fold raw water concentrationcompared with the reservoir water (step A) (Fig. 3). Whencalibrated regarding the toxic equivalent (TEQ) of 4-OHT(Fig. 2), values ranged from 3.4 to 33.1 µg/L 4-OHT (Fig.4).

After tested samples were incubated with 4-OHT (1.0 ×

0

5

10

15

20

25

Inh

ibit

ion

act

ivit

y (

%)

Sampling sites

A B C D E F Negative Positive Empty

Fig. 3 ERRγ antagonistic activity of the sample in yeast strain ERRγ-GRIP1 (fifty times concentrated of raw water). Values are average ±standard error (n = 3). Negative: dimethyl sulfoxide (DMSO); Positive:4-OHT; Empty: procedural blank.



A B C D E F

0

10

20

30

40

4-O

HT

eq

uiv

alen

ce (

μg/L

)

Sampling sites

Fig. 4 Bioassay-derived 4-OHT equivalence in yeast strain ERRγ-GRIP1 for sample ERRγ antagonistic activity. Values are average ±standard error (n = 3).

0

5

10

15

20

25

Inhib

itio

n a

ctiv

ity

(%

)

Sampling sites

A B C D E F Negative Positive Empty

Fig. 5 Effect of test samples on inverse agonist activity of 4-OHT inyeast strain ERRγ-GRIP1 for ERRγ antagonistic activity at fifty-foldconcentration. Sample inverse agonist activity is represented as inhibitionactivity percentage relative to the high constitutive activity in yeast strainERRγ-GRIP1. Values are average ± standard error (n = 3). Negative:dimethyl sulfoxide (DMSO), Positive: 4-OHT.

10−5 mol/L), which inhibited about 20% ERRγ constitutiveactivity in the recombined yeast, 4-OHT’s inverse activitywas not suppressed (Fig. 5).

2.3 Discussion

Multiple contaminants such as pharmaceuticals, steroidhormones, unregulated pesticides, flame retardants, rocketfuel chemicals, plasticizers, detergents, and stain repel-lants have been found in source and drinking waters(Kolpin et al., 2002; Barnes et al., 2008; Focazio et al.,2008).Although they are at low levels in water, consideringonly trace amounts of natural hormones can affect thebody, there is growing interest in understanding the fateof EDCs during drinking water treatment (Benotti et al.,2009). As contaminant removal by applied water treatmentis often incomplete, natural waters contain many dissolvedchemicals that affect ecosystems and impact drinkingwater supplies (Boyd et al., 2003).

In the present work, ERRγ antagonistic activities werefound in the reservoir and DWTP. When calibrated to theTEQ of 4-OHT, values ranged from 3.4 to 33.1 µg/L.The ERRγ antagonistic activities found in reservoir sourcewater with 4-OHT equivalent was 13.0 µg/L, suggesting

that source water contained many compounds that bind toERRγ. Among the processes, secondary chlorination waseffective in removing ERRγ disrupting substances, but co-agulation led to a significant increase in ERRγ disruptingactivity. Many previous studies have found that coagu-lation, flocculation, and precipitation were ineffective atremoving dissolved organic contaminants, especially forlow molecular weight compounds (Ternes et al., 2002).Additionally, pre-chlorination was responsible for higherconcentrations of disinfection byproducts including manyorganic chemicals (Simpson and Hayes, 1998), and coag-ulation caused small organic molecules to increase (Luo etal., 1998). In the present study, activated carbon showedno obvious removal effect. Although activated carbon hasbeen effective at removing organic contaminants, removalcapacity was limited by contact time, competition fromnatural organic matter, contaminant solubility, and carbontype (Kolpin et al., 2002; Boyd et al., 2003). Other studieshave also stated that several compounds were detectablein carbon effluent, and removal efficiency of activatedcarbon was largely dependent on water quality (Snyderet al., 2007). Compared with source water, DWTP canremove 73.4% of ERRγ disrupting substances, indicatingthat ERRγ antagonist elimination in the DWTP was in-complete. Considering some ERRγ disrupting substancesremained in the final effluent, it is possible that the outletmight be harmful to human health.

An increasing number of organic compounds have beendetected in surface waters, raising concerns about thecontamination of water resources as it is sometimes nec-essary to produce drinking water from polluted surfacewaters (Heberer et al., 2002). However, complete removalof EDCs is not possible through conventional wastewatertreatment and a significant fraction of EDCs may bereleased into the aquatic environment (Halling-Sorensen,1998; Daughton and Ternes, 1999; Joss et al., 2004). Thedischarge of ERRγ disrupting chemicals in water must,therefore, be understood.

Considering the important role ERRs play in humanhealth (Ariazi et al., 2002), assessing the rate of elimi-nation of ERR disrupting substances during DWTPs is ofconsiderable importance. To date, however, no report onERR disrupting activity in DWTPs has been presented.Results from this study suggested that ERRγ antagonisticactivity in drinking water may biologically impact humans,and ERRγ antagonists in drinking water acting via morethan one mechanism might contribute to biological effectson organisms and contribute to a wide range of hormon-al and/or anti-hormonal effects in vivo through differentpathways (Molina-Molina et al., 2006). Although ERRsplay an important role in breast cancer (Ariazi et al.,2002), for example, current information is insufficient fordetermining whether ERRγ antagonistic activity levels indrinking water can affect the human endocrine system.Further research is needed, especially in vivo studies, toassess the risk of drinking water on endocrine disruptionin humans. Based on current knowledge, it is clear thatensuring a safe and sustainable water supply will be anincreasingly great challenge. In addition, drinking water


No. 2 Estrogen-related receptor γ disruption of source water and drinking water treatment processes extracts 305

companies must effectively reduce the concentration ofall contaminants to guarantee clean drinking water forconsumers (Knepper et al., 1999).

3 Conclusions

This study described ERRγ disrupting activities in reser-voir and drinking water treatment processes. Secondarychlorination was effective in removing ERRγ antagonists,while coagulation led to a significant increase in ERRγantagonistic activity. The waterworks processes were ableto remove 73.5% of ERRγ antagonists compared to sourcewater, indicating that there are concerns about ERRγdisrupting contaminants in drinking and source waters.The ERRγ two-hybrid yeast assay can be employed asan important and useful method for drinking water safetyevaluation, allowing ERRγ disrupting pollutants to bedetected efficiently and accurately.

Acknowledgements

This work was supported by the National High Technol-ogy Research and Development Program (863) of China(No. 2007AA06Z414) and the National Natural ScienceFoundation of China (No. 50778170).

References

Ariazi E A, Clark G M, Mertz J E, 2002. Estrogen-related re-ceptor alpha and estrogen-related receptor gamma associatewith unfavorable and favorable biomarkers, respectively, inhuman breast cancer. Cancer Research, 62(22): 6510–6518.

Barnes K K, Kolpin D W, Furlong E T, Zaugg S D, Meyer MT, Barber L B, 2008. A national reconnaissance of phar-maceuticals and other organic wastewater contaminants inthe United States-1: Groundwater. The Science of the TotalEnvironment, 402(2-3): 192–200.

Benotti M J, Stanford B D, Wert E C, Snyder S A, 2009. Evalu-ation of a photocatalytic reactor membrane pilot system forthe removal of pharmaceuticals and endocrine disruptingcompounds from water. Water Research, 43 (6): 1513–1522.

Boyd G R, Reemtsma H, Grimm D A, Mitra S, 2003. Pharma-ceuticals and personal care products (PPCPs) in surface andtreated waters of Louisiana, USA and Ontario, Canada. TheScience of the Total Environment, 311(1-3): 135–149.

Colborn T, Saal F S V, Soto A M, 1993. Developmental effectsof endocrine-disrupting chemicals in wildlife and humans.Environmental Health Perspectives, 101(5): 378–384.

Coward P, Lee D, Hull M V, Lehmann J, 2001.4-Hydroxytamoxifen binds to and deactivates theestrogen-related receptor γ. Proceedings of the NationalAcademy of Sciences, 98(15): 8880–8884

Crews D, Willingham E, Skipper J K, 2000. Endocrine disruptors:Present issues, future directions. The Quarterly Review ofBiology, 75(3): 243–260.

Daughton C G, Ternes T A, 1999. Pharmaceuticals and personalcare products in the environment: Agents of subtle change?Environmental Health Perspectives, 107(S6): 907–938.

Focazio M J, Kolpin D W, Bames K K, Furlong E T, Meyer M T,Zaugg S D et al., 2008. A national reconnaissance for phar-maceuticals and other organic wastewater contaminants inthe United States–II: Untreated drinking water sources. The

Science of the Total Environment, 402(2-3): 201–216.Gaido K W, Leonard L S, Lovell S, Gould J C, Babai D, Portier

C J et al., 1997. Evaluation of chemicals with endocrinemodulating activity in a yeast-based steroid hormone re-ceptor gene transcription assay. Toxicology and AppliedPharmacology, 143(1): 205–212.

Giguere V, Yang N, Segui P, Evans R M, 1988. Identification of anew class of steroid hormone receptors. Nature, 331(6151):91–94.

Greschik H, Flaig R, Renaud J P, Moras D, 2004. Structural basisfor the deactivation of the estrogen-related receptor γ by di-ethylstilbestrol or 4-hydroxytamoxifen and determinants ofselectivity. Journal of Chemical Biology, 279(32): 33639–33646

Halling-Sorensen B, Nielsen S N, Lanzky P F, Ingerslev F, HoltenLu tzhoft H C, Jorgensen S E, 1998. Occurrence, fate andeffects of pharmaceutical substances in the environment: Areview. Chemosphere, 36(2): 357–393.

Heberer T, Feldmann D, Reddersen K, Altmann H J, Zimmer-mann T, 2002. Production of drinking water from highlycontaminated surface waters: Removal of organic, inorganicand microbial contaminants applying mobile membranefiltration units. Acta Hydrochim Hydrobiol, 30(1): 24–33

Hong H, Yang L, Stallcup M R, 1999. Hormone-independenttranscriptional activation and coactivator binding by novelorphan nuclear receptor ERR3. Journal of Chemical Biolo-gy, 274(32): 22618–22626.

Horard B, Vanacker J M, 2003. Estrogen receptor-related recep-tors: Orphan receptors desperately seeking a ligand. Journalof Molecular Endocrinology, 31(3): 349–357.

Johnson A C, Williams R J, Simpson P, Kanda R, 2007. Whatdifference might sewage treatment performance make to en-docrine disruption in rivers? Environment Pollution, 147(1):194–202.

Joss A, Andersen H, Ternes T, Richle P R, Siegrist H, 2004.Removal of estrogens in municipal wastewater treatmentunder aerobic and anaerobic conditions: consequences forplant optimization. Environmental Science and Technology,38(11): 3047–3055.

Knepper T P, Sacher F, Lange F T, Brauch H J, KarrenbrockF, Roerden O et al., 1999. Detection of polar organicsubstances relevant for drinking water. Waste Management,19(2): 77–99.

Kolpin D W, Furlong E T, Meyer M T, Thurman E M, ZauggS D, Barber L B et al., 2002. Pharmaceuticals, hormones,and other organic wastewater contaminants in U.S. streams,1999–2000: A national reconnaissance. Environmental Sci-ence and Technology, 36(6): 1202–121l.

Li J, Li N, Ma M, Giesy J P, Wang Z J, 2008a. In vitro profil-ing of the endocrine disrupting potency of organochlorinepesticides. Toxicology Letters, 183(1-3): 65–71.

Li J, Ma M, Rao K F, Wang Z J, 2008b. Construction therecombinant human estrogen receptor (hER) Gene yeastusing two-hybrid yeast technique. Asian Journal of Ecotox-icology, 3(1): 21–26.

Li J, Ma M, Wang Z J, 2008c. A two-hybrid yeast assay toquantify the effects of xenobiotics on thyroid hormone-mediated gene expression. Environmental Toxicology andChemistry, 27(1): 159–167.

Luo X H, Cao L L, Wang Z S, 1998. Study on the removal ofdifferent molecular weight organics by water purificationprocess. China Environmental Science, 18(4): 341–344

Luo X R, Ikeda Y Y, Parker K L, 1994. A cell specific nuclearreceptor is essential for adrenal and gonadal development



and sexual differentiation. Cell, 77(4): 481–490.Molina-Molina J M, Hillenweck A, Jouanin I, Zalko D, Cravedi

J P, Fernandez M F et al., 2006. Steroid receptor profilingof vinclozolin and its primary metabolites. Toxicology andApplied Pharmacology, 216(1): 44-54.

Qiao M, Chen Y Y, Zhang Q H, Huang S B, Ma M, Wang C X etal., 2006. Identification of Ah receptor agonists in sedimentof Meiliang Bay, Taihu Lake, China. Environmental Scienceand Technology, 40(5): 1415–1419.

Routledge E J, Sumpter J P, 1996. Estrogenic activity of surfac-tants and some of their degradation products assessed usinga recombinant yeast screen. Environmental Toxicology andChemistry, 15(3): 241–248.

Scruggs C, Hunter G, Snyder E, Long B, Snyder S, 2005. EDCs inwastewater: What’s the new step? Water Environment andTechnology, 17(3): 24–31.

Simpson K, Hayes K P, 1998. Drinking water disinfectionby-products: An Australian perspective. Water Research,32(5): 1522–1528

Snyder S A, Adham S, Redding A M, Cannon F S, DeCarolisJ, Oppenheimer J et al., 2007. Role of membranes andactivated carbon in the removal of endocrine disruptors andpharmaceuticals. Desalination, 202(1-3): 156–181.

Sonnenschein C, Soto A M, 1998. An updated review of environ-mental estrogen and androgen mimics and antagonists. TheJournal of Steroid Biochemistry and Molecular Biology,65(1): 143–150

Stackelberg P E, Furlong E T, Meyer M T, Zaugg S D, Henderson

A K, Reissman D B, 2004. Persistence of pharmaceuticalcompounds and other organic wastewater contaminants in aconventional drinking-water-treatment plant. Science of theTotal Environment, 329(1-3): 99–113.

Takayanagi S, Tokunaga T, Liu X H, Okada H, Matsushima A,Shimohigashi Y, 2006. Endocrine disruptor bisphenol Astrongly binds to human estrogen-related receptor gamma(ERR gamma) with high constitutive activity. ToxicologyLetters, 167(2): 95–105.

Ternes T A, Meisenheimer M, McDowell D, Brauch H J, BrigitteH G, Preuss G et al., 2002. Removal of pharmaceuticalsduring drinking water treatment. Environmental Scienceand Technology, 36(17): 3855–3863.

Tremblay G B, Bergeron D, Giguere V, 2001.4-Hydroxytamoxifen is an isoform-specific inhibitorof orphan estrogen-receptor-related (ERR) nuclearreceptors β and γ. Endocrinology, 142(10): 4572–4575

Westerhoff P, Yoon Y, Snyder S, Wert E, 2005. Fate ofendocrine-disruptor, pharmaceutical, and personal careproduct chemicals during simulated drinking water treat-ment processes. Environmental Science and Technology,39(17): 6649–6663.

Wilson T E, Mouw A R, Weaver C A, Milbrandt J, Parker KL, 1993. The orphan nuclear receptor NGFI-B regulatesexpression of the gene encoding steroid 21-hydroxylase.Molecular and Cellular Biology, 13(2): 861–868.



Article

SPECIAL TOPICS:

Environmental Chemistry January 2011 Vol.56 No.3: 275–284

doi: 10.1007/s11434-010-4266-1

A gas chromatography/mass spectrometry method for the simultaneous analysis of 50 phenols in wastewater using deconvolution technology

ZHONG WenJue1, WANG DongHong1, XU XiaoWei1, WANG BingYi1, LUO Qian1, SENTHIL KUMARAN Satyanarayanan2 & WANG ZiJian1*

1 State Key Laboratory of Environmental Aquatic Chemistry, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China;


Received April 6, 2010; accepted July 13, 2010

Phenolic compounds exist widely in the influents and effluents of sewage treatment plants (STPs) and most are un-regulated. In this study, a gas chromatography-mass spectrometry (GC-MS) method for the simultaneous analysis of 50 phenolic compounds in wastewater was developed. Deconvolution technology was used to identify contaminants that are covered by co-extracted materials. A mass spectral library containing all 50 silylated phenolic compounds was first established and used for deconvolution. Twelve typical phenolic compounds were selected to optimize the sample preparation procedures. Solid-phase extraction using a C18 cartridge coupled with an HLB cartridge was used for pre-concentration and dichloromethane was used for elution. The sol-utes were derivatized and analyzed by GC-MS. The blank and matrix spike recoveries ranged from 57.46% to 136.4% and 47.87% to 114.8%, respectively. Method detection limits ranged from 3.64 to 97.64 ng L–1. The relative standard deviations of all the recovery experiments were lower than 13.6%. The instrument limits of quantification ranged from 0.7 to 87.7 pg. The method has been applied to analyze the influents and effluents of 5 Chinese STPs. Except for regulated phenolic compounds (phenol and 2,4,6-trichlorophenol), three un-regulated phenolic compounds, including 2-chlorophenol, 2,5-dichlorophenol and 2,4-dichloro- 3-ethyl-6-nitrophenol were identified in the effluent wastewater. The detected concentrations of un-regulated phenolic compounds could possibly cause environmental effects, indicating that immediate attention is required to prevent complications.

identify, quantify, phenolic compounds, deconvolution, wastewater

Citation: Zhong W J, Wang D H, Xu X W, et al. A gas chromatography/mass spectrometry method for the simultaneous analysis of 50 phenols in wastewater using deconvolution technology. Chinese Sci Bull, 2011, 56: 275−284, doi: 10.1007/s11434-010-4266-1

In recent years, increasing attention has been paid to mi-cropollutants in wastewater due to increasing concerns about their potential negative impacts on the environment [1]. Phenolic compounds are known for their high solubility in water, strong reactivity and poor biodegradability [2]. Some phenolic compounds are capable of mimicking or disrupting estrogenic activity because their structures are similar to natural estrogen [3,4]. Some chlorophenols have been classified as possible carcinogens by the World Health *Corresponding author (email: [email protected])

Organization (WHO) and the International Agency for Research on Cancers (IARC) [5, 6]. Furthermore, chloro-phenols can produce a nasty smell and taste even at a very low concentration [7]. Once introduced into the environ-ment through wastewater, phenolic compounds can pose a threat to animal and vegetable organisms and perhaps also to humans through their toxicity, persistence and bioaccumula-tive potential [7]. Currently, sewage treatment plants (STPs) focus only on removing regulated phenolic compounds such as phenol, 2,4-dichlorophenol and pentachlorophenol. The occurrence of un-regulated phenolic compounds in waste-


276 Zhong W J, et al. Chinese Sci Bull January (2011) Vol.56 No.3

water does not attract the concern it deserves. However, the occurrence of phenolic compounds in effluents has been well documented, including many un-regulated phenolic compounds such as nonylphenol and octylphenol [8–10]. It is therefore necessary to pay more attention to the occur-rence and removal of phenolic compounds in effluents of STPs. In this study, we conducted a broad-spectrum analy-sis of municipal wastewaters to gain a comprehensive un-derstanding of the concentration range of 50 phenols in in-fluent and effluent wastewaters in Tianjin, China.

Many analytical methods for the detection and quantifi-cation of phenolic compounds are based on gas chromatography-mass spectrometry (GC-MS) [11,12]. However, most are focused on only few target compounds. An effec-tive method for identification and quantification of a large number of trace phenolic compounds in wastewater is gen-erally lacking. Retention time locking (RTL) and deconvo-lution report software (DRS) are new techniques developed to cater to multi-residue analysis. They help identify a large number of target compounds simultaneously, even when they are obscured by co-eluting matrix compounds [13]. Therefore, establishing a method for screening target phe-nolic compounds from a large number of candidates using DRS and RTL is advisable. Even though DRS can qualify and quantify the compounds listed in libraries, there is cur-rently no specialized library dedicated to phenolic com-pounds. Moreover, phenolic compounds exist at trace or low concentration levels in water samples, making their detection difficult, so little attention has been paid to them. There is therefore a need to find a suitable sample prepara-tion technique, which allows the separation of phenolic compounds from complicated matrices.

The objective of this study was to develop a method for identification and quantification of phenolic compounds by two aspects. The first was to establish a specialized library completely devoted to derivatized phenolic compounds for screening. The second was to optimize the method for sam-ple preparation. The method was then applied to analyze the influents and effluents of five STPs to demonstrate its feasi-bility.



All phenolic compound standards were purchased from Sigma-Aldrich (St. Louis, MO, USA). Stock solutions for each individual phenolic standard (1 mg L–1) were prepared in n-hexane. All solvents [methanol, acetone, n-hexane, methyl-tert-butyl ether (MTBE) and dichloromethane (DCM)] were of pesticide residue grade and were purchased from Mallinckrodt Baker, Inc., (USA). Ultrapure water was generated by the Milli-Q system (Millipore, Bedford, MA, USA). Derivatization reagent N,O-Bis(trimethylsilyl) triflu-

oroacetamide (BSTFA) with 1% trimethylchlorosilane (TMCS) was purchased from Supelco (USA). Two types of solid-phase extraction (SPE) cartridges were used, a C18 cartridge (500 mg) was from Supelco (USA) and an Oasis HLB cartridge (500 mg) from Waters (USA).

1.2 Methodology

(1) Identification and quantification of phenolic compounds. There are 3 steps to identify phenolic compounds in water: 1) sample preparation; 2) determination by GC-MS; and 3) analysis, based on the library of silylated phenolic com-pounds, using RTL, GC-MS ChemStation and DRS.

After preparing the samples by the optimized method, the samples were analyzed using GC-MS in scan and selected ion monitoring (SIM) mode using the RTL method. The scan data were analyzed using DRS to identify the com-pounds in the sample matrices. Combined spectra of sam-ples were analyzed by GC-MS with the library of silylated phenolic compounds, and a contaminant list including all the phenolic compounds was identified using spectral de-convolution technology. The phenolic compounds identified by GC-MS were quantified using the SIM results.

(2) Criteria for selecting target phenolic compounds. The selection of 50 target phenolic compounds was based on following criteria: 1) wide use (the production or re-quirement or import and export amount of one phenolic compound exceeded 1000 t y–1); 2) availability of relevant toxicity data; and 3) availability of a standard.

(3) Procedures for building library. After derivatized by BSTFA with 1% TMCS, each standard compound was ana-lyzed by GC-MS to obtain their mass spectrogram. A li-brary of silylated phenolic compounds was created as a .tab file using Microsoft Excel in which compound name, reten-tion time, target ion, quota ion and abundance ratio of ion of each target compound were recorded. A series of conver-sions were then carried out to build the library. Details for establishing a library can be found in the Agilent Technical Overview [14].

(4) Optimizing the preparation method. To prepare ar-tificial samples in the laboratory, Milli-Q water samples of 2 L were spiked by adding a mixture of phenolic com-pounds (including 12 phenolic compounds) dissolved in methanol to obtain a concentration of 250 ng L–1 for each analyte. All artificial samples were adjusted to pH < 2 with 6 μmol L–1 hydrochloride buffer, filtered through Millipore glass microfiber filters, preserved in brown glass containers, and processed by solid-phase extraction within 2 d. Samples were enriched by SPE using the C18 cartridge, the HLB car-tridge and the C18 cartridge coupled with the HLB car-tridge.

For the recovery test, a total of 12 different solvents were tested. Matrix spiked experiments were used to validate the selected optimized elution solvents.


Zhong W J, et al. Chinese Sci Bull January (2011) Vol.56 No.3 277

Derivatization was performed to reduce the polarity of phenolic compounds. All extracts were evaporated under a gentle stream of nitrogen. The dry residues were derivatized by 100 μL BSTFA with 1% TMCS and heated in a heating block at 60°C for 2 h [15]. TMCS can enhance the chemical reactivity of silylating agents. The derivatives were cooled to room temperature and then dissolved with 400 μL n-hexane to yield the sample solution. The constant volume of solutions was 500 μL.

1.3 Water sampling

Influent and effluent samples used in this study were col-lected from five STPs located in the Tianjin, China. STP1A, STP2A, STP3A, STP4A, STP5A were influents and STP1B, STP2B, STP3B, STP4B, STP5B were effluents of the five STPs. The treatment process of STP1 is anaero-bic/anoxic/oxic (A2/O) + continuous microfiltration (CMF) + O3 + Cl2. The treatment process of STP2 is anoxic/oxic (A/O). STP3 applied a conventional active sludge to treat wastewater. The treatment processes of STP4 and STP5 were hydrolysis acidification-biological filter and hydroly-sis acidification + membrane bioreactor (MBR) + Cl2, re-spectively. Cartridges and elution solvents optimized by recovery experiments were applied to prepare samples. Other procedures were the same as mentioned above.

1.4 Analytical procedure

The samples were detected using an Agilent 6890 gas chromatograph equipped with an Agilent MSD 5975 mass spectrometer. A capillary column of 30 m × 0.25 mm i.d. 0.25 μm HP-5 was used. Before analyzing samples, the re-tention time was locked by changing column pressure using standard samples. A constant pressure model was then used for the entire analysis process. The gas chromatography (GC) oven temperature was programmed from 40 to 300°C via a ramp of 10°C min–1 and maintained at 40°C for 2 min and at 300°C for 15 min. The mass spectrum (MS) was op-erated in full-scan mode from m/z, 50–700 for qualitative analysis or selected ion monitoring (SIM) mode for quanti-tative analysis. The inlet and MS transfer line temperatures were maintained at 250°C and the ion source temperature was 300°C. Sample injection (1 μL) was done in splitless mode. The data of GC-MS were analyzed by RTL and DRS (software provided by Agilent). The full-scan spectra data file was transferred to the Automatic Mass Spectral Decon-volution and Identification System (AMDIS), which de-convolutes the spectra and searches for compounds using the deconvoluted full spectra. A normal qualitative and quantitative analysis for target compounds was performed, using the characteristic fragment ions of each compound at the correct retention time.


2.1 Parameters of the library of silylated phenolic compounds

In this study, a library of 50 silylated phenolic compounds was established. To our knowledge, this is the first time such a library has been established for identifying and quan-tifying phenolic compounds. The retention time of each target compound, target ions, quota ions and abundance ratios of ions are listed in Table 1. For a compound, the spectrum is inherent in the quadrupole mass spectra. The deconvolution process finds ions whose individual abun-dances rise and fall together within the spectrum. The result first corrects for the spectral skew that is inherent in quad-rupole mass spectra and determines a more accurate apex retention time of each chromatographic peak. Therefore, to build the library, phenolic compounds names, retention times, target ions, quota ions and abundance ratios of ion were necessary. The full-scan was carried out to obtain mass spectra of the silylated phenolic compounds. The above parameters were received from the mass spectra (Ta-ble 1). For example, for 2,4,6-TCP, the molecular ion was found at m/z, 268 (abundance 100%) corresponding to [(CH3)3Si-O-C6H3-Cl3]

+ and ions at m/z, 253 and m/z, 217 were found due to the loss of the –CH3 group and –Cl from the molecular ion.

A standard mix containing 16 phenolic compounds (2,4-DNP; phenol; 2-cresol; 3-cresol; 2-CP; 2,4-xylenol; 4-C-3-MP; 2,6-DCP; 2,4-DCP; 2,5-DCP; 2,4,6-TCP; 2,4,5-TCP; 2,3,5,6-TeCP; 2,3,4,6-TeCP; 2,3,4,5-TeCP; PCP) was used to validate the library. All 16 phenolic compounds were identified accurately and the match ratios were more than 90%, except for 2,4,5-TCP (73%), showing that identifying phenolic compounds by the library was reliable.

2.2 Methods for qualification and quantification

Even though GC-MS is the most commonly used technique to separate and identify organic chemicals, it is difficult to obtain separation for some phenolic compounds, such as 2,5-DCP and 2,6-DCP, 2,4,6-TCP and 2,3,5-TCP; 4-NP and 2,3,5-TCP [11,16]. Banerjee et al. [17] optimized the oven temperature, ion source temperature, modulation period, duration of hot pulses, modulation-offset temperature, and acquisition rate, etc. to achieve the best possible separation of test compounds. The performance, however, was not satisfactory for a large number of target compounds. Heberer and Stan [11] obtained a good separation through changing chromatographic columns. However, they could not separate all phenolic compounds on the same chroma-tographic column and their approach consumes both time and money. Moreover, it is not a good choice for obtaining a high resolution. Simultaneously, full scan chromatograms



Table 1 Compound name, retention time, target ion, quota ion and abundance ratio of ion of each target phenolic compound

Name R.T.a) T.I.b) q1c) q1ratiod) q2e) q2ratiof) q3g) q3ratioh)

2,4-Dinitrophenol (2,4-DNP) 5.958 256 241 127.6 191 500 77 346.8 Phenol 7.809 166 166 100 151 390.9 77 49.5

2-Cresol 9.100 180 165 183.5 149 25.6 91 141

3-Cresol 9.277 180 165 272.9 149 14.8 91 53.1

4-Cresol 9.434 180 165 273.6 149 15 91 43.3

2-Chlororphenol (2-CP） 10.307 200 185 258.4 149 256.5 93 247.2

2,4-Xylenol 10.630 194 179 106.2 149 35.6 105 78.5

4-Chlorophenol (4-CP) 10.733 200 185 266.1 149 10.2 93 30.3

2,6-Xylenol 10.760 194 179 100.7 149 42.8 105 99

2-Isopropylphenol 10.825 208 193 297.6 151 41.4 77 46.8

2-Sec-butylphenol 11.904 222 193 499.3 149 31.6 77 74.5

Pyrocatechol 12.009 254 239 19.9 166 36.7 151 38.7

4-Chloro-3-methylphenol(4-C-3-MP) 12.096 214 199 188.7 149 11.3 77 24.6

2,5-Dichlorophenol (2,5-DCP) 12.401 234 219 333.6 183 17.1 93 287.4


2,3,6-Trimethylphenol (2,3,6-TMP) 12.467 208 193 113.3 119 88.2 77 30.1


Resorcinol 12.927 254 239 151.6 166 4.2 91 8.8

2,6-Diisopropylphenol 13.159 250 235 261.6 177 6.1 91 16.4

2-Nitrophenol (2-NP) 13.213 196 196 100 151 26.7 79 31.9

Hydroquinone 13.274 254 254 100 239 215.2 79 148

3,5-Dimethyl-4-chlorophenol (PCMX) 13.314 228 213 164.5 93 25.5 77 29

3,5,6-Trichloro-2-pyridinol 13.798 271 256 713.2 234 42.5 93 511.7

2,4,6-Trichlorophenol (2,4,6-TCP) 14.335 268 253 534.8 217 175.3 93 214.2

6-Chlorothymol 14.452 256 45 214.3 183 10.5 77 24.1

4-Nitrophenol (4-NP) 14.558 211 211 100 196 392.2 150 63.1

2,3,5-Trichlorophenol(2,3,5-TCP) 14.567 270 270 100 253 393.3 93 507.2

2,4,5-Trichlorophenol (2,4,5-TCP) 14.688 270 255 333 196 145.2 93 352.4


4-Chlororesorcinol 14.851 288 288 100 273 85 93 37.4

4-Chloro-2-nitrophenol (4-C-2-NP) 14.917 230 230 100 77 20.8 0 0

2-Chlorohydroquinone 14.955 288 288 100 257 55.1 93 35.3


2-Naphthol 15.324 216 201 129.5 185 12.4 127 21.8

2-Biphenylol 15.768 242 227 145.5 211 196.2 77 12.7

2-Chloro-4-nitrophenol (2-C-4-NP) 15.994 230 230 100 147 26.1 93 54.5

2,3,5,6-Tetrachlorophenol(2,3,5,6-TeCP) 16.62 304 304 100 289 549 93 337.3

2,3,4,6-Tetrachlorophenol(2,3,4,6-TeCP) 16.746 304 304 100 289 443.6 93 208.2

2,3,4,5-Tetrachlorophenol(2,3,4,5-TeCP) 17.058 304 304 100 289 418 93 455.4

2,4-Dichloro-3-ethyl-6-nitrophenol 18.181 292 292 100 247 25.5 93 12.8

Pentachlorophenol (PCP) 18.883 338 338 100 323 504.4 93 328

Ortho-benzyl-para-chlorophenol 19.337 290 290 100 275 94.2 181 14.9

2-Chloro-4-phenylphenol 19.539 276 261 60 225 146.9 93 89

Tetrachlorohydroquinone 19.985 392 392 100 375 110 93 138.5

4,4'-Biphenyldiol 21.725 330 330 100 315 13.2 150 7.4

Biphenol A (BPA) 22.250 357 357 100 372 11.2 0 0

Dichlorophene 23.207 412 412 100 377 82.9 0 0

Hexanoestrol 23.542 399 399 100 179 485.9 151 138.1

Bithionol 25.636 500 500 100 395 56.7 93 37.3

Hexachlorophene 27.47 550 550 100 515 226.3 208 532.2 a ) Retention time. b) Target ion. c) First qualitative ion. d) Abundance of q1/abundance of target ion × 100. e) Second qualitative ion. f) Abundance of

q2/abundance of target ion × 100. g) Third qualitative ion. h) Abundance of q3/abundance of target ion × 100.

obtained in our study (such as Figure 1(a)) are overloaded with matrix component peaks, making data evaluation difficult and time consuming. Matrix effect, a serious

interference, could not be effectively eliminated or reduced by changing GC-MS conditions or chromatographic col-umns.



Figure 1 (a) Total ion chromatogram of a wastewater sample; (b) DRS report from the analysis of the wastewater sample. From (a), we can find that 2,6-DCP and 2,5-DCP could not be separated absolutely. From (b), we can find that 2,6-DCP and 2,5-DCP could be identified simultaneously using the DRS report. The results of (a) and (b) describe the same wastewater sample.

In this study, RTL, spectral deconvolution and DRS were developed to identify target compounds in GC-MS analysis. Based on the retention times, quota ions and abundance ratio of ions, deconvolution technology could separate and identify chemicals accurately and quickly, even when chemicals were covered by complex matrix elements. For example, 2,5-DCP and 2,6-DCP could be identified simul-taneously in the wastewater sample (Figure 1(b)) using DRS and RTL. Therefore, the method developed using RTL and DRS is a good choice for identifying a large number of phenolic compounds in wastewater.

2.3 Methods for sample preparation

Phenolic compounds were at trace or low concentration levels in the water samples, so one of the most important requirements is to find a suitable sample preparation tech-nique that allows the separation of phenolic compounds from the sample matrix [18]. Development of SPE proce-

dures, which are able to enrich water with quantitative re-coveries for priority phenolic compounds, remains an elu-sive goal. Therefore, procedures for sample preparation to screen phenolic compounds in water were also optimized in this study. The extraction and elution efficiencies of target compounds from water samples were assessed using different types of SPE cartridges and elution solvents. 12 phenolic compounds including phenol, 2-cresol, 3-cresol, 4-cre-sol, 2-CP, 2,6-DCP, 2,4-DCP, 2-NP, 2,4,6-TCP, 2,4,5-TCP, 2,3,4,6-TeCP and PCP were selected as target compounds to optimize the pretreatment procedures. Polarity is an important factor for extraction efficiency [19]. The logKow

values of 12 phenolic compounds ranged from 1.5 to 5.07, which covered the polar range of the 50 phenolic com-pounds [20]. In addition, the mass spectral fragment path-ways were also considered. –CH3, –NO2 and –Cl are the three kinds of substituent groups that are easy to fragment from silylated phenolic compounds, so methylphenol, ni-trophenol and chlorophenol were included in the 12 typical



phenolic compounds. Furthermore, substituent positions and substituent number also were considered in the selection of target phenolic compounds which were then used to opti-mize the procedures for sample preparation. Therefore, these 12 typical phenolic compounds were representative of the 50 phenolic compounds for polarity, substituent groups, substituent positions and substituent number.

(1) Extraction recovery with various cartridges. Among the many kinds of SPE cartridges available, C18 cartridge and HLB cartridges are the top two most commonly used to pre-concentrate environmental samples. Furthermore, the C18 and HLB cartridges are less selective and retain more compounds, relatively, and they are most commonly used to analyze broad-spectrum compounds. Based on the above considerations, C18 and HLB cartridges with dichloro-methane as elution solvent were used in the present investi-gation (Figure 2). Each method was performed in triplicate. All of the relative standard deviation (RSD%) values were lower than 7.2%. SPE is very often used in the sample preparation step of the chromatographic analysis of pheno-lic compounds [21] due to its advantages in trace element determination, namely conservation of species and good pre-concentration factors, enabling the achievement of very low limit of detection [22]. The SPE cartridge is of primary importance in the extraction of target compounds from wa-ter samples [23]. The results have shown that C18 cartridges can strongly retain nonpolar phenolic compounds, com-pared with HLB cartridges (Figure 2). The recoveries of phenol, cresols, 2-CP and 2-NP (logKow < 2) from the C18 cartridge were lower than the recoveries of tri-, tetra- and pentachlorophenol, because phenol, cresols, 2-CP and 2-NP are hydrophilic compounds with lower affinity for nonpolar sorbents and low breakthrough volumes in comparison with tri-, tetra- and pentachlorophenol [19]. On the other hand, for HLB cartridges, the recoveries of nonpolar compounds were low. The objective of this study was to screen all the phenolic compounds in the library; therefore, using only one kind of SPE cartridge to enrich samples was unreason-able. The C18 and HLB cartridges could offset the defects of one another so the C18 cartridge coupled with the HLB cartridge was chosen for further experiments.

(2) Elution by different solvents. The recovery of or-ganic compounds by SPE is highly dependent on the polarity of the elution solvent [12]. Twelve different solvents (Table

Figure 2 Recoveries of different SPE cartridges. Numbers 1 to 12 repre-sent phenol, 2-cresol, 3-cresol, 4-cresol, 2-CP, 2,6-DCP, 2,4-DCP, 2-NP, 2,4,6-TCP, 2,4,5-TCP, 2,3,4,6-TeCP and PCP, respectively.

2) were tested for the elution recovery of 12 phenolic com-pounds. The cartridges were eluted with 10 mL of different solvents. For example, for method 1, the cartridges were first eluted with 10 mL of mixed solvent of hexane and DCM (1:9, V:V) and then eluted with 10 mL of mixed solvent of DCM and methanol (9:1, V:V). Each method was performed in triplicate. All RSD% values were lower than 13.6%. It can be seen from the results (Figure 3) that DCM produced the best recovery for most of the phenolic compounds (95.78% ± 26.44%). Methods 1 and 2 provided poor recovery for all target compounds. A possible reason is that the lower polarity of the elution solvent led to a lower elution ability of polar target compounds [23]. Phenolic compounds have different behavior in terms of acidity and polarity [19]. The purpose of this study was to screen phe-nolic compounds in water and the polarity range of target compounds was wide. By comprehensive consideration of various factors, dichloromethane was selected as the elution solvent.

2.4 Quality assurance/quality control (QA/QC)

Instrumental calibration curves were established from stan-dard solutions with seven concentrations ranging between 50 and 1000 μg L–1. The instrument limit of quantification (LOQ) was determined as the analyte mass corresponding to a signal/noise ratio of 10. The LOQs ranged 0.7 to 87.7 pg

Table 2 Proportion schemes of elution solvents

Method Solvent Method Solvent Method Solvent

1 Hexane:DCM=1:9 DCM:methanol=9:1





10 MTBE:methanol=9:1



11 Acetone



12 Dichloromethane



Figure 3 Recoveries using different elution solvents (box plot). Numbers 1 to 12 represent methods 1 to 12.

(injected) for individual phenolic compounds (Table 3). The calibration curve was linear in the entire range (R2 =0.995–1.000) (Table 4). Matrix-matched calibration curves are listed in Table 4. To further validate the precision and accuracy of the method, blank, matrix spiked and parallel experiments were carried out. Verification experiments were carried out using the 12 typical phenolic compounds selected to optimize the procedures for sample preparation. Seven replicate samples (2 ng L–1), concentrated 4000 times were analyzed using the entire analytical method to calcu-late method detection limits (MDLs). The MDLs of 12 phenolic compounds ranged from 3.56 to 97.64 ng L–1 (Table 4). No phenolic compound was detected in the blank sam-ples. The matrix spike recoveries for 12 phenolic compounds ranged from 47.87% to 114.8% (Table 4). The RSD% values

Table 3 Instrument LOQs of 50 phenolic compounds (pg)

Compound LOQ Compound LOQ Compound LOQ

2,4-DNP 10.0 Resorcinol 4.6 2-Biphenylol 13.3

Phenol 1.5 Pyrocatechol 3.2 2,6-Diisopropylphenol 10.0

2-Cresol 1.1 Hydroquinone 3.3 3,5,6-Trichloro-2-pyridinol 87.7

3-Cresol 2.4 6-Chlorothymol 1.4 2-Chlorohydroquinone 4.3

4-Cresol 2.5 PCMX 5.8 2-Isopropylphenol 5.1

2-CP 0.8 2,4,6-TCP 8.9 2,4-Dichloro-3-ethyl-6-nitrophenol 2.4

2,4- Xylenol 3.1 2,3,5-TCP 32.9 2-Sec-butylphenol 4.9

4-CP 6.2 2,4,5-TCP 9.0 Ortho-benzyl-para-chlorophenol 0.9

2,6-Xylenol 4.9 2,3,6-TCP 9.0 2-Chloro-4-phenylphenol 2.0

2-NP 2.6 2,3,5,6-TeCP 1.4 Tetrachlorohydroquinone 10.0

4-NP 0.9 2,3,4,6-TeCP 2.1 4,4'-Biphenyldiol 9.2

PCP 1.4 2,3,4,5-TeCP 1.9 BPA 0.9

4-C-3-MP 0.3 4-Chlororesorcinol 2.2 Dichlorophene 27.6

2,5-DCP 10.9 4-C-2-NP 10.0 Hexanoestrol 71.4

2,6-DCP 6.2 2-C-4-NP 6.1 Bithionol 55.6

2,3,6-TMP 7.3 3,4,5-TCP 1.4 Hexachlorophene 10.0

2,4-DCP 4.6 2-Naphthol 0.7

Table 4 MDLs and Matrix spike recoveries of 12 phenolic compounds

Compound MDLs (ng L–1) Matrix spike recoveries (%) Calibration curves R2

Phenol 3.56 58.06 Y=1.641x+0.0053 1.000

2-Cresol 29.73 78.12 Y=0.52x+0.0173 0.996

3-Cresol 22.84 74.64 Y=1.559x–0.1403 0.999

4-Cresol 18.42 47.87 Y=1.625x–0.1566 0.999

2-CP 26.98 114.80 Y=0.5757x+0.0036 0.999

2,6-DCP 36.10 68.34 Y=0.4959x–0.06 0.999

2,4-DCP 18.55 78.34 Y=0.4595x–0.0669 1.000

2-NP 97.64 56.80 Y=0.2173x–0.0193 0.997

2,4,6-TCP 44.54 55.97 Y=0.4066x–0.0948 0.997

2,4,5-TCP 36.86 84.88 Y=0.4478x–0.0872 0.995

2,3,4,6-TeCP 33.43 81.73 Y=0.4014x–0.1090 0.997

PCP 3.64 75.72 Y=0.4074x–0.1492 0.997



for all recovery experiments were lower than 13.6%, show-ing that the precision of this method is excellent.

2.5 Application of the method to real samples

Tianjin is located in northern China near Beijing, adjacent to the Bohai Sea, and it is the third largest industrial center in China. On average, the industries in those areas discharge about 180 million tons of wastewater annually. Confronted with water shortages in agriculture, wastewater irrigation has been commonly practiced in this area for more than 40 years [24]. Rivers in the Tianjin area are severely polluted with high loads of persistent organic pollutants [25] and these bring risks to the water environment. It is important and urgent, therefore, to evaluate the removal efficiency of pollutants in STPs in Tianjin, China.

(1) Identification of phenolic compounds in wastewater. The identification and quantification method was applied to analyze samples from five STPs located in Tianjin, China. All samples were analyzed by DRS: the match values were more than 80% and retention time difference between the database and observed values were less than 5 seconds. Identification of phenolic compounds in samples taken at different STPs indicates that phenolic compounds were widely present in wastewater. Different phenolic com-pounds were identified in different STPs (Table 5) and most were identified as un-regulated phenolic compounds. Al-though many kinds of phenolic compounds existed in in-fluents (2-cresol, 3-cresol, 4-cresol, 4-CP, 2,4-DCP, 2,6-DCP, 2,3,6-TMP, 2-sec-butylphenol, PCMX, 2-napthol, 6-chlorothymol and 2-phenylphenol), only few existed in effluents, indicating that treatment processes in STPs could have removed the 12 phenolic compounds effectively. Among the phenolic compounds identified in effluent,

phenol and 2,4,6-TCP belong to the regulated phenolic compounds; 2-CP, 2,5-DCP and 2,4-dichloro-3-ethyl-6- nitro-phenol belong to the un-regulated phenolic com-pounds. 2-CP and 2,4,6-TCP are classified as priority pol-lutants by the United States Environmental Protection Agency (US EPA) [26]. 2,5-DCP has been used as a bio-marker of exposure to 1,4-dichlorobenzene (1,4-DCB) [27]. Furthermore, it is been assumed that 2,5-DCP may have a key function in 1,4-DCB induced genotoxicity [28]. There is insufficient data available about the harm caused by 2,4-dichloro-3-ethyl-6-nitrophenol. Therefore, the occur-rence of the phenolic compounds in wastewater should be given more attention.

(2) Quantitative analysis of wastewater. The quantita-tive results are shown in Table 5. The surrogate recoveries of all samples ranged from 67.4% to 108.7%. For the total phenolic compounds, the removal efficiencies were 99.97% for STP1, 99.95% for STP2, 88.95% for STP3, 98.04% for STP4 and 99.51% for STP5.

Phenolic compounds were identified in all the effluents of the STPs. The highest concentration occurred in STP4 (0.98 μg L–1). The concentrations of 2,4,6-TCP in the ef-fluents from STP2, STP3, STP4 and STP5 were 0.07, 0.16, 0.25 and 0.10 μg L–1, respectively. Phenol and 2,4,6-TCP belong to regulated phenolic compounds, and their concen-trations met the discharge standard of pollutants for mu-nicipal wastewater treatment plants, China [29].

2-CP was identified in the influent of all the STPs and in the effluents of STP1 and STP4. The concentrations of 2-CP in effluents were 0.14 and 0.12 μg L–1 for STP1 and STP4, respectively. There is no relevant standard for 2-CP in China but it has been classed as a priority pollutant by the US EPA [26]. As reported by the US EPA [30], the threshold

Table 5 Qualitative and quantitative results of wastewater samples (μg L–1)

STP1 STP2 STP3 STP4 STP5 Compound

STP1A STP1B STP2A STP2B STP3A STP3B STP4A STP4B STP5A STP5B

Phenol 34.6 0.05 – 0.27 – 0.52 0.58 0.98 16.9 0.12 2-Cresol 16.5 – 23.1 – 16.2 – 25.8 – 4.4 –

3-Cresol 19.0 – 31 – 15.8 – 19.1 – 4.07 –

4-Cresol 18.2 – 29.7 – 15.1 – 18.3 – 3.9 –

2-CP 32.8 0.14 101 – 17.3 – 24.5 0.12 10.6 –

4-CP – – – – 0.7 – 13.2 – – –

2,6-DCP – – – – 28.4 – – – 0.98 –

2,4-DCP – – – – 30.7 – – – – –

2,5-DCP 30.2 – 1.66 – 41.8 – 0.31 1.89 1.42 –

2,4,6-TCP – – 0.36 0.07 – 0.16 – 0.25 0.57 0.1

2,3,6-TMP – – – – 2.3 – – – 0.36 –

2-Sec-butylphenol 210 – 348 – 12.4 – 55.8 – – –

PCMX 404 – 16.2 – 3.68 – 7.29 – – –

2-Naphthol 0.34 – 103 – 4.14 – 0.73 – 0.61 –

6-Chlorothymol – – 0.19 – 0.13 – – – 1.11 –

2,4-Dichloro-3-ethyl-6-nitrophenol – – – – 22.2 22.6 – – – –

2-Phenylphenol 7.66 – – – 0.18 – – – 0.1 –



level of 2-chlorophenol in water that causes tainting in eel flesh and oysters is 0.125 μg L–1

and the odor threshold concentration is 0.1 μg L–1. The occurrence of 2-CP should be given more attention.

2,5-DCP was identified only in the effluent of STP4 and is noteworthy as the content in the effluent (1.89 μg L–1) was much higher than in the influent water (0.31 μg L–1). This result indicates that 2,5-DCP must have been intro-duced during the hydrolysis acidification-biological filter process. The concentration of 2,5-DCP in the effluent of STP4 exceeds the odor threshold concentration (0.5 μg L–1) proposed by the US EPA [30]. 2,5-DCP has also been clas-sified as a strongly toxic material by a PBT profiler, devel-oped by the Environmental Science Center of the US EPA [31]. The occurrence of 2,5-DCP could cause serious issues.

2,4-dichloro-3-ethyl-6-nitrophenol was only identified in STP3. Furthermore, the conventional active sludge process applied by STP3 could not remove 2,4-dichloro-3-ethyl- 6-nitrophenol absolutely. 2,4-dichloro-3-ethyl-6-nitrophenol is one of the products of a chemical plant near STP3 so its presence might have been caused by effluent discharge from the chemical plant. 2,4-dichloro-3-ethyl-6-nitrophenol is a benzene series intermediate and has been classified to have strong toxic potential and to be a persistent material by the PBT profiler [31].

In brief, the concentrations of regulated phenolic com-pounds in the effluents of five STPs met the standard re-quirements but the occurrence of un-regulated phenolic compounds could cause serious environmental damage and indicates that more attention should be paid to them.

3 Conclusion

RTL and DRS were introduced for the first time to identify and quantify phenolic compounds in wastewater. This method allows accurate identification and quantification of phenolic compounds with high sensitivity and could be readily extended to include additional analytes. Further-more, the method demonstrated, including an optimized preparation procedure, is very simple, fast, and is a viable alternative for routine monitoring of phenolic compounds in water. The results indicate that enriching phenolic com-pounds by a C18 cartridge coupled with a HLB cartridge and eluting with DCM is the optimal preparation method (LOQs range 0.7–87.7 pg). Applying the entire analytical method, phenolic compounds can be detected at the ng L–1

level in environmental samples, independent of the origin of the sample and its matrix load.

The method was successfully applied to analyze waste-water of five STPs. Only a few types of phenolic compound were identified in effluents. The un-regulated phenolic compounds in effluents may cause environmental effects and should be given more attention, although the concentra-tions of regulated phenolic compounds met the discharge

standards of pollutants for municipal wastewater treatment plants in China.

This work was supported by the National Science & Technology Pillar Program (2007BAC27B02-1b), the National Natural Science Foundation of China (20977102), Important National Science & Technology Specific Projects (2008ZX07314-003), and a Special Fund from the State Key Laboratory of Environmental Aquatic Chemistry (09Y11ESPCR).

1 Kong X J, Li D, Cao L Q, et al. Evaluation of municipal sewage treatment systems for pollutant removal efficiency by measuring lev-els of micropollutants. Chemosphere, 2008, 72: 59–66

2 Bielicka-Daszkiewicz K, Dębicka M, Voelkel A. Comparison of three derivatization ways in the separation of 423 phenol and hydro-quinone from water samples. J Chromatogr A, 2004, 1052: 233–236

3 Korach K S. Surprising places of estrogenic activity. Endocrinology, 1993, 132: 2277–2278

4 Terasaka S, Inoue A, Tanji M, et al. Expression profiling of estro-gen-responsive genes in breast cancer cells treated with alkylphenols, chlorinated phenols, parabens, or bis- and benzoylphenols for evalua-tion of estrogenic activity. Toxicol Lett, 2006, 163: 130–141

5 WHO (World Health Organization), Environmental health criteria 93. Chlorophenols other than pentachlorophenol, Geneva, 1989

6 Kalliokoski P, Kauppinen T. Complex chlorinated hydrocarbons: oc-cupational exposure in the sawmill industry. IARC Sci Publ, 1990, 104: 390–396

7 Davì M L, Gnudi F. Phenolic compounds in surface water. Water Res, 1999, 33: 3213–3219

8 Kasprzyk-Hordern B, Dinsdale R M, Guwy A J. The removal of pharmaceuticals, personal care products, endocrine disruptors and il-licit drugs during wastewater treatment and its impact on the quality of receiving waters. Water Res, 2009, 43: 363–380

9 Nakada N, Shinohara H, Murata A, et al. Removal of selected pharma-ceuticals and personal care products (PPCPs) and endocrine-disrupting chemicals (EDCs) during sand filtration and ozonation at a municipal sewage treatment plant. Water Res, 2007, 41: 4373–4382

10 Wang Y Q, Hu W, Cao Z H, et al. Occurrence of endocrine-disrupting compounds in reclaimed water from Tianjin, China. Anal Bio-anal Chem, 2005, 383: 857–863

11 Heberer T, Stan H J. Detection of more than 50 substituted phenols as their t-butyldimethylsilyl derivatives using gas chromatography-mass spectrometry. Anal Chim Acta, 1997, 341: 21–34

12 Liu R, Zhou J L, Wilding A, Simultaneous determination of endo-crine disrupting phenolic compounds and steroids in water by solid-phase extraction-gas chromatography-mass spectrometry. J Chromatogr A, 2004, 1022: 179–189

13 Wylie P L, Szelewski M J, Meng C K. Comprehensive pesticide screening by GC/MSD using deconvolution reporting software. Agilent Technologies. Application Note (23) 5989–1157E, 2004, Available from: http://www.agilent.com/chem (last accessed Febru-ary, 2010)

14 Weiner K R, Prest H F. Retention time locking: creating custom re-tention time locked screener libraries. Agilent Technologies. Appli-cation Note (23) 5968–8657E, 1999, Available from: http://www. agilent.com/chem (last accessed February, 2010)

15 Zhou Y Q, Ma M, Wang Z J. Determination of nonylphenols in water by pre-column derivatization and gas chromatography coupled with mass spectrometry. Chinese J Analyt Chem, 2005, 33: 1109–1112

16 Kovάcs Á, Kende A, Mörtl M, et al. Determination of phenols and chlorophenols as trimethylsilyl derivatives using gas chromatogra-phy-mass spectrometry. J Chromatogr A, 2008, 1194: 139–142

17 Banerjee K, Patil S H, Dasgupta S, et al. Optimization of separation and detection conditions for the multiresidue analysis of pesticides in grapes by comprehensive two-dimensional gas chromatography-time- of-flight mass spectrometry. J Chromatogr A, 2008, 1190: 350–357



18 Montero L, Conradi S, Weiss H, et al. Determination of phenols in lake and ground water samples by stir bar sorptive extraction-thermal desorption-gas chromatography-mass spectrometry. J Chromatogr A, 2005, 1071: 163–169

19 Rodríguez I, Llompart M P, Cela R. Solid-phase extraction of phe-nols. J Chromatogr A, 2000, 885: 291–304

20 LOGKOW©. A databank of evaluated octanol-water partition coeffi-cients (LogP), February 2010. Available from: http://logkow.cisti.nrc. ca/logkow/ (last accessed February, 2010)

21 Ge F, Zhu L Z, Wang J. Distribution of chlorination products of phenols under various pHs in water disinfection. Desalination, 2008, 225: 156–166.

22 Mester Z, Sturgeon R. Sample preparation for trace element analysis. 2003. 393–451

23 Wu J M, Hu R K, Yue J Q, et al. Determination of fecal sterols by gas chromatography-mass spectrometry with solid-phase extraction and injection-port derivatization. J Chromatogr A, 2009, 1216: 1053–1058

24 Shi Z, Tao S, Pan B, et al. Contamination of rivers in Tianjin, China by polycyclic aromatic hydrocarbons. Environ Pollut, 2004, 134: 97– 111

25 Tao S, Cao H Y, Liu W X, et al. Fate modeling of phenanthrene with regional variation in Tianjin, China. Environ Sci Technol, 2003, 37: 2453–2459

26 U.S. EPA (U. S. Environmental Protection Agency). National Rec-ommended Water Quality Criteria, 2005, Available from: http:// www.epa.gov/waterscience/criteria/wqctable/#priority (last accessed February, 2010)

27 Hill R H, Head S L, Baker S, et al. Pesticide residues in urine of adults living in the United States: Reference Range concentrations. Environ Res, 1995, 71: 99–108

28 Tegethoff K, Herbold B A, Bomhard E M. Investigations on the mutagenicity of 1,4-dichlorobenzene and its main metabolite 2,5-dichlorophenol in vivo and in vitro. Mutat Res, 2000, 470: 161–167

29 Ministry of Environmental Protection of the People’s Republic of China. Discharge Standard of Pollutants for Municipal Wastewater Treatment Plant (GB18918-2002), 2002

30 US EPA (United States Environmental Protection Agency). Ambient water quality criteria for chlorinated phenols (EPA 440/5-80-032), 1980

31 US EPA (United States Environmental Protection Agency). Envi-ronmental Science Center. PBT profiler, 2006. Available from: http:// www.pbtprofiler.net/Results.asp (last accessed February, 2010)




Toxicological effects of arsenate exposure on hematological, biochemicaland liver transaminases activity in an Indian major carp, Catla catla

Chokkalingam Kavitha, Annamalai Malarvizhi, Satyanarayanan Senthil Kumaran, Mathan Ramesh *

Unit of Toxicology, Department of Zoology, School of Life Sciences, Bharathiar University, Coimbatore 641 046, Tamil Nadu, India


Article history:Received 26 February 2010Accepted 12 July 2010

Keywords:Catla catlaSodium arsenateHematologyGlucoseProteinTransaminases

a b s t r a c t

The impact of acute and sublethal toxicity of arsenate on hematological, biochemical and enzymologicalparameters of an Indian major carp Catla catla were estimated. The median lethal concentration ofsodium arsenate to the fish Catla catla for 96 h was found to be 43.78 mg/L. During acute treatment(43.78 mg/L), hemoglobin (Hb), hematocrit (Ht), red blood cell count (RBC), white blood cell count(WBC), plasma glucose, plasma protein, liver aspartate and alanine aminotransferase (AST and ALT) levelsdecreased, whereas corpuscular indices like mean cell volume (MCV), mean cell hemoglobin (MCH) andmean cell hemoglobin concentration (MCHC) increased in arsenate treated fish. In sublethal treatment(4.378 mg/L), Hb, Ht, RBC, plasma protein levels decreased while MCHC and plasma glucose levelsincreased throughout the exposure period. A biphasic trend was noticed in WBC, MCV, MCH, liver ASTand ALT levels. The alterations of these parameters can be effectively used as a rapid method to assesshealth of fish exposed to arsenate in the aquatic environment.

2010 Elsevier Ltd. All rights reserved.

1. Introduction

A number of hazardous chemicals are directly introduced in theaquatic environment and arsenic has been reported as one of themost alarming chemicals (ATSDR, 2002). Arsenic, an importantenvironmental contaminant, is present in the aquatic environmentas a result of geogenic and anthropogenic processes (Gonzalezet al., 2006; Singh and Banerjee, 2008). In the environment, arsenicis present in different forms and the toxicity depends upon itschemical form and oxidation states (Agusa et al., 2008). In theaquatic environment, arsenic (metalloid element) found either asarsenite (As3+) or arsenate (As5+) form which are inter-convertedthrough redox and methylation reactions (Bears et al., 2006). Thearsenic species can accumulate in many aquatic organisms whichmay catalyse the oxidation of arsenite to arsenate and also pro-mote the formation of methylarsines through biomethylation reac-tion (Ridley et al., 1977). The biotransformation of inorganicarsenic species (As3+ and As5+) into less toxic organic species canoccur through monomethylarsonic acid (MMAV) reductase andmethyltransferase enzymes involvement during reduction and

methylation reactions (Vahter, 2002; Akter et al., 2005). In generalinorganic arsenic species like As3+ and As5+ are more toxic than or-ganic species, in spite of the differences that exist between the ef-fects of arsenite (As3+) and arsenate (As5+) (Tseng, 2004; Akteret al., 2005; Tuzen et al., 2009). Among the inorganic arsenic spe-cies arsenate is less toxic when compared to arsenite both underin vivo and in vitro conditions (Cervantes et al., 1994; Smedleyet al., 1996). The toxicity of arsenite (As3+) is related to its highaffinity to sulphydryl (–SH) groups of proteins like glutathione(GSH) and lipoic acid and the cysteinyl residues of many enzymeswhile arsenate interferes with phosphorylation reactions (Gebel,2000; Aposhian and Aposhian, 2006; Ghosh et al., 2007).

Microorganisms present in the aquatic environment are able toeither reduce or oxidize arsenic; thereby converting it biologicallyavailable to aquatic organisms including fish (Duker et al., 2005).More over in the aquatic environment, a number of organisms likeyeast, fungi, algae, plants, phytoplanktons, zooplanktons and fishare able to either reduce or oxidize arsenic; thereby converting itbiologically available to aquatic organisms including fish (Maedaet al., 1990; Kaise et al., 1998; Hanaoka et al., 1992; Duker et al.,2005). A higher concentration of arsenic in the aquatic environmentis lethal to many organisms (Pedlar et al., 2002; Bhattacharya andBhattacharya, 2007). Among the aquatic organisms, fish can serveas a model to study arsenic toxicity, as they are continuously ex-posed to arsenic through gills and get accumulated in various tis-sues. The accumulation of different arsenic forms mostly dependson the analyzed species and tissue (Fattorini et al., 2004). The

0278-6915/$ - see front matter 2010 Elsevier Ltd. All rights reserved.doi:10.1016/j.fct.2010.07.017

Abbreviations: RBC, red blood cell; WBC, white blood cell; Hb, hemoglobin; Ht,hematocrit; MCV, mean cell volume; MCH, mean cell hemoglobin; MCHC, mean cellhemoglobin concentration; AST, aspartate aminotransferase; ALT, alanine amino-transferase; DNPH, dinitrophenyl hydrazine; NaOH, sodium hydroxide; IU, inter-national unit.

* Corresponding author. Tel.: +91 422 2428493; fax: +91 422 2422387.E-mail address: [email protected] (M. Ramesh).

Food and Chemical Toxicology 48 (2010) 2848–2854


Food and Chemical Toxicology

journal homepage: www.elsevier .com/locate/ foodchemtox


http://dx.doi.org/10.1016/j.fct.2010.07.017


http://dx.doi.org/10.1016/j.fct.2010.07.017


http://www.elsevier.com/locate/foodchemtox

accumulation of arsenobetaine (AsB), arseocholine (AsC) and arsen-osugarrs (AsS) has been reported in majority of aquatic species,whereas in polychaetes and other organisms the accumulation oftrimethylarsine oxide (TMAO), dimethylarsenic acid (DMA) andinorganic molecules has been reported (Maher et al., 1999; Fattoriniet al., 2004; Ventura-Lima et al., 2007). Suhendrayatna et al. (2002)suggested that higher trophic level organisms accumulate more Asthan lower level of organisms when exposed to As3+. Many authorshave reported that the accumulation of arsenic was higher in mar-ine fish when compared to freshwater fish due to lower concentra-tion of arsenic in freshwater environment (Ferguson and Gavis,1972; Oladimeji et al., 1984; Norin et al., 1985; Santa Maria et al.,1986). In fish, arsenic usually exists in two oxidation states, meth-ylated species, arseno-sugars and arsenolipids, which vary in theirtoxicity and the combination of these two states in tissues of fishleads to pathophysiological effects (Wrobel et al., 2002). Fish ex-posed to As for a longer period in the laboratory or in natural Ascontaminated habitats, induces histopathological lesions in liver,gallbladder and kidney which in turn affect the hepatic and renalfunctions (Pedlar et al., 2002; Roy and Bhattacharya, 2006). Pedlaret al. (2002) observed architectural and structural alterations,inflammation, and focal necrotic lesions in liver of lake whitefish(Coregonus clupeaformis) fed with As. Similarly histopathologicalalterations like including sloughing of the epithelium, edema andfibrosis of the sub mucosal tissues, were observed in gallbladdersof lake white fish (Coregonus clupeaformi) and in rainbow trout(Salvelinus namaycush) fed with dietary arsenate (Cockell et al.,1991; Pedlar et al., 2002). To assess the effects of a toxic compoundon aquatic organisms, responses to sublethal levels of the pollutantare very important rather than performing acute toxicity studies(De Boeck et al., 1995). The study of mechanism of sublethal arsenictoxicity to fishes is limited (Bears et al., 2006).

Knowledge on the physiological action of the toxicant helps topredict important sublethal effects and analyses of biochemistry,hematology, and histopathology may be used to determine themode of action of the toxicant. Various blood characteristics of fishhave been utilized to measure the responses of sublethal effects.The analyses of blood parameters (hematological and biochemical)of fish exposed to a toxicant are important in diagnosing the struc-tural and functional status of the animal (Adhikari et al., 2004). Thehematological variables such as RBC count, WBC count, Hb andhematological indices like MCV, MCH and MCHC, and biochemicalparameters like plasma glucose and protein are widely used to as-sess the toxic stress. Similarly changes in the enzyme activities arewidely used to detect tissue damage and biomarkers of animals ex-posed to chronic concentrations of a toxicant (Ozmen et al., 2006).Transaminases like aspartate aminotransferase (AST) and alanineaminotransferase (ALT) can be used to detect tissue damage causedby the toxicants and also used for aquatic monitoring (Nemcsok andBenedecky, 1990). AST acts by catalyzing the transfer of aminogroup of the aspartic acid to a – ketoglutaric acid, to form oxaloace-tic acid and glutamic acid, where as ALT acts by catalyzing thetransfer of the amino group from alanine to a – ketoglutaric acidto form pyruvic acid and glutamic acid. These enzymes are the stra-tegic link between carbohydrate and protein metabolism (Harperet al., 1978) and plays an important role in the utilization of aminoacids for the oxidation and/or for gluconeogenesis (Rodwell, 1988).

Reports are available on the toxicity of arsenic in mammaliansystem and also the arsenite toxicity in fishes. Information on im-pact of arsenate toxicity in Indian major carps is very limited. Thearsenates (e.g. Na2HAsO47H2O), being thermodynamically morestable, overwhelm the arsenites in the surface water and well-oxy-genated freshwater systems (Liu et al., 2008). Further arsenate isthe predominant form of arsenic in toxic littoral zones of freshwa-ter habitats (Cullen and Reimer, 1989). Hence the present investi-gation is aimed to assess the toxicity of arsenate on certain

hematological, biochemical and enzymological parameters in anIndian major carp Catla catla in order to understand the mode ofaction, stress response and organ dysfunction.


2.1. Test chemicals

The analytical grade sodium arsenate (Na2HAsO47H2O) (CAS No.: 7778-43-0(Anhydrous) with 98% purity was obtained from Hi Media, Mumbai, India and usedwithout further purification for the experiment.

2.2. Animal maintenance

The freshwater fingerlings, Catla catla (length 8.2 ± 0.4 cm and weight10.5 ± 1 g) were procured from Tamil Nadu Fisheries Development CorporationLimited, Aliyar Fish Farm, Aliyar, Tamil Nadu, India. The collected fish were safelybrought to the laboratory and acclimatized for one month in a large cement tank(1000 L capacity). During the acclimatization period, the fish were fed ad libitumwith rice bran and groundnut oil cake which had no detectable amount of arsenic.Food was provided once in a day. The water (three forth of the water) was reneweddaily to avoid accumulation and contamination of excretory materials and feedingwas withheld 24 h before the commencement of the experiment. Fish showing anyabnormal behavior was removed as soon as possible. In the present study tap waterfree from chlorine was used which had the following physicochemical characteris-tics (APHA, 2005); temperature 26 ± 1 C, pH 7.2 ± 1, salinity 0.30 ± 0.1 ppt, dis-solved oxygen 7.0 ± 0.02 mg/L, total hardness 17 ± 0.5 mg/L, alkalinity34.0 ± 5 mg/L, calcium 4 ± 0.51 mg/L and magnesium 2 ± 0.2 mg/L. Before the startof the experiment suitable numbers of fish were transferred into two glass aquariawhich were continuously aerated.

2.3. Preparation of stock solution and determination of 96 h LC50 value of sodiumarsenate

Stock solution of sodium arsenate was prepared by dissolving 1 g of sodiumarsenate in an appropriate amount of dilute acidic water (sodium arsenate is notsoluble in water and upon adding to aquarium water the pH of the water dosenot change). For the determination of median tolerance limits or LC 50, differentconcentrations of sodium arsenate (10, 20, 30, 40, 50 and 60 mg/L) were preparedfrom the stock and added in separate glass aquaria containing 50 L of water. Threereplicates were maintained for each concentration and 10 fishes of equal size andweight were introduced. The test water was renewed at the end of 24 h and freshlyprepared sodium arsenate was added to maintain the concentration of arsenic at aconstant level. A concurrent control of 30 fish in three different glass aquaria wasmaintained under identical conditions. The mortality/survival of fish was recordedafter 96 h. The dead fish were removed from the tank immediately. The concentra-tion at which 50% mortality of fish occurred after 96 h was taken as the medianlethal concentration (LC50), which was 43.78 mg/L (Finney, 1978). 1/10th valueof the LC50 value for 96 h (4.378 mg/L) was taken as the sublethal concentration(Sprague, 1971).

2.4. Lethal study

For the determination of acute toxicity test, five plastic tubs each of 55 L capacitywere taken and filled with 50 L of water and LC50 96 h concentration of sodium arse-nate (43.78 mg/L) was added after removal of same quantity of water. The experi-ment was initiated by introducing 10 fish in each tub. A common control was alsomaintained in five different tubs simultaneously. At the end of 96 h fish were ran-domly collected and blood samples were collected from each group for hematolog-ical, biochemical assays and the liver was dissected out for enzyme assay.

2.5. Sublethal studies

For sublethal toxicity tests 600 fingerlings were selected and divided into sixgroups (one control and five experimental) with 100 fish in each aquarium filledwith water. The desired concentration (1/10 of LC 50 which was 4.378 mg/L) ofthe toxicant was added directly into each glass aquarium after removal of the samevolume of water and renewed daily in order to maintain constant concentration ofthe toxicant. The experiment was conducted for 35 days and sampled at 5 daysinterval and no mortality was observed during the above treatment period. At theend of the stipulated periods (5th, 10th, 15th, 20th, 25th, 30th and 35th day) ofexposure, fish were randomly selected and sacrificed for further analysis.

2.6. Blood sample

Blood samples were collected by heart puncture using plastic disposable syrin-ges fitted with 26 gauge needle. The syringe and needle were prechilled and coatedwith heparin (Beparine R heparin sodium, IP 1000 IU/mL derived from beef

C. Kavitha et al. / Food and Chemical Toxicology 48 (2010) 2848–2854 2849


intestinal mucosa containing 0.15% w/v chlorocresol IP preservative), an anticoagu-lant manufactured by Biological E Limited, Hyderabad, India. It was transferred intosmall vials, which is previously rinsed with heparin. Whole blood was used for theestimation of hemoglobin, and RBC, WBC counts. The remainder of the bloodsample was centrifuged at 10,000 rpm for 20 min to separate the plasma, whichwas used for plasma glucose and protein estimation.

2.7. Hematological analysis

RBC and WBC were counted by the method of Rusia and Sood (1992) expressedas million/cu mm and 1000/cu mm, respectively. Hemoglobin content of the bloodwas estimated by the method of Drabkin (1946) and expressed as g/dl. Hematocritwas estimated according to Nelson and Morris (1989) and expressed as %. Erythro-cyte related indices like MCV, MCH and MCHC were calculated and expressed as fl,pg and g/dl, respectively.

2.8. Biochemical analysis

2.8.1. Estimation of plasma glucosePlasma glucose was estimated by the method of Cooper and Mc Daniel (1970).

To 5 mL of O-toluidine colour reagent, 0.1 mL of plasma was added. The content wasmixed well and heated in boiling water for 10 min. Then, cooled under running tapwater for 5 min and the optical density (OD) of the test sample was measured at630 nm within 30 min in a UV spectrophotometer and expressed as mg/100 mL.

2.8.2. Estimation of plasma proteinPlasma protein estimation was done by the method of Lowry et al. (1951). To

0.90 mL of distilled water, 0.10 mL of plasma was added and treated with 5.0 mLof solution C [50 mL of solution A (2.00 gm of sodium carbonate was dissolved in100.00 mL of 0.1 N NaOH), was dissolved with 1 mL of solution B (500.00 mg of cop-per sulphate was dissolved in 100.00 mL of 1% sodium potassium tartarate solu-tion)] and allowed to stand for room temperature for 10 min, and then 0.5 mL offolin-phenol reagent was added. After 15 min the colour intensity was read at720 nm in a UV Spectrophotometer and expressed as and lg/mL.

2.9. Enzymological analysis

2.9.1. Preparation of samples for enzyme assayAfter drawing the blood, fish were washed with double distilled water and blot-

ted dry with absorbent paper. The liver were isolated from the control and experi-mental fish and 100 mg of each tissue was weighed and homogenized with 2.5 mLof 0.25 M sucrose solution in ice cold condition (Hogeboom et al., 1948). Thehomogenates were centrifuged for 20 min at 6000 rpm and the clear supernatantfluid was taken for enzyme assay.

2.9.2. Determination of AST activityLiver AST activity was estimated following the method of Reitman and Franckel

(1957). To 50 mL supernatant, 0.25 mL of buffered aspartate was added and incubatedat 37 C for 60 min. To this 0.25 mL of 2, 4-DNPH was added and allowed to stand for20 min at room temperature. Then 2.5 mL of 0.4 (N) NaOH was added, mixed well andallowed to stand for 10 min. The OD was measured at 505 nm in a UV Spectrophotom-eter. A standard curve was also run simultaneously. The values were interpreted inthe standard curve and the enzyme activity was expressed as IU/L.

2.9.3. Determination of ALT activityLiver ALT activity was estimated by the method of Reitman and Franckel (1957).

To 50 mL supernatant, 0.25 mL of buffered Lalanine was added and incubated at37 C for 30 min. To this 0.25 mL of 2, 4-DNPH was added and allowed to standfor 20 min at room temperature. Then 2.5 mL of 0.4 (N) NaOH was added, mixedwell and allowed to stand for 10 min. The OD was measured at 505 nm in a UVSpectrophotometer. A standard curve was also run simultaneously. The values wereinterpreted in the standard curve and the enzyme activity was expressed as IU/L.


The data were analyzed statistically at P < 0.05. To test their significance the tvalues were calculated between control and experiment value by Student’s t-test.

3. Results

3.1. LC50 value – 96 h

In the present study the 96-h LC50 value of arsenate to Catlacatla was estimated and found to be 43.78 mg/L.

3.2. Acute toxicity – hematology, biochemical and enzymologicalprofiles

The hematological (Hb, Ht, RBC and WBC), biochemical (plasmaglucose and protein) and enzymological (AST and ALT) parameterswere significantly (P < 0.05) decreased (P < 0.05) in arsenate trea-ted fish from that of the control group (Table 1). However the otherhematological indices like MCV, MCH and MCHC were increasedsignificantly (P < 0.05) in arsenate treated fish (Table 1).

3.3. Sublethal toxicity

3.3.1. HematologyThe hematological profiles such as Hb, Ht, and RBC levels were

decreased (P < 0.05) in arsenate treated fish throughout the expo-sure period and a maximum percent decrease was noted at theend of 35th day (Fig. 1a–c). WBC content was increased up to20th day in arsenate treated fish and then declined from that ofthe control group (Fig. 1d). Similarly, MCV and MCH contents weresignificantly (P < 0.05) increased up to 25th day (Fig. 1e and f) andthen declined in the rest of the study period. Moreover a slight de-crease in MCHC content was noted in arsenate treated fishthroughout the study period when compared with the controlgroup (Fig. 1g).

3.3.2. Biochemical analysisPlasma glucose level was significantly (P < 0.05) elevated in

arsenate treated fish when compared with their respective controls(Fig. 2a). Plasma protein level was decreased in arsenate treatedfish throughout the experimental period significantly (P < 0.05)which showed a direct relationship with the exposure period(Fig. 2b).

3.3.3. Enzyme assayLiver AST was increased up to 10th day in arsenate treated fish.

However from 15th day onwards the enzyme activity was de-creased significantly (P < 0.05) in relation to the control groups(Fig. 3a). ALT activity was slightly increased on 5th day, and thensignificantly (P < 0.05) declined in the rest of the study period(Fig. 3b).

Table 1Alterations of hematological, biochemical and enzymological parameters in afreshwater fish Catla catla during acute treatment of sodium arsenate.

Parameters Control Experiment

Hematological parametersHb (g/dl) 3.20 ± 0.059 2.980 ± 0.079* (6.76)Ht (%) 9.50 ± 0.145 8.80 ± 0.089* (7.36)RBC (million/cu mm) 0.37 ± 0.006 0.340 ± 0.006* (8.11)WBC (1000/cu mm) 15.46 ± 0.209 10.01 ± 1.586* (35.25)MCV (fl) 25.67 ± 0.114 25.88 ± 0.316* (+0.82)MCH (picograms) 8.64 ± 0.035 8.76 ± 0.122* (+1.38)MCHC (g/dl) 33.64 ± 0.063 33.86 ± 0.032* (+0.65)

Biochemical parametersPlasma glucose (mg/100 mL) 124.2 ± 0.083 93.61 ± 0.797* (24.63)Plasma protein (lg/mL) 3.23 ± 0.001 1.44 ± 0.007* (55.38)

Enzymological parametersLiver AST (IU/L) 65.03 ± 0.152 42.87 ± 0.770* (35.73)Liver ALT (IU/L) 75.56 ± 0.338 59.16 ± 0.870* (21.71)

Values are mean ± SE of five individual observation, (+) denotes per cent increaseover control, () denotes per cent decrease over control.* Values are significant at P < 0.05.

2850 C. Kavitha et al. / Food and Chemical Toxicology 48 (2010) 2848–2854


4. Discussion

The arsenic concentration in natural water bodies mainly de-pends on geological composition and the degree of pollution (Jainand Ali, 2000). The concentration of arsenicals like As3+ and As5+ inthe aquatic environment mostly depends on the valance state, re-dox conditions and geological environment (Suhendrayatna et al.,2002). Further the toxicity of arsenic also depends on physicalstate, rate of absorption into cells, rate of elimination etc., (Mandaland Suzuki, 2002). The impact of arsenic toxicity is mostly con-trolled by physico chemical properties of water rather than by theirtotal concentration (Suhendrayatna et al., 2002). In the presentstudy, the median lethal concentration of sodium arsenate wasfound to be 43.78 mg/L indicating that arsenate compounds areless toxic when compared to arsenite compounds. The LC 50 valuesof arsenate to the fish Carassius carrassius auratus and Oryzias lati-pes were found to be 10.00 and 30.3 mg/L, respectively (Maedaet al., 1990; Suhendrayatna et al., 2002). Where as the LC 50 values

Fig. 1. Hematological values (a. Hb; b. Hct; c. RBC; d. WBC; e. MCV; f. MCH; g.MCHC) of C. catla exposed to sodium arsenate for 35 days. Bar represents SE of themean. Comparisons of means (control and treated fish) were done by Student’s t-test. * Significant at 5% level (P < 0.05).

Fig. 2. Biochemical changes (a. plasma glucose; b. plasma protein) of C. catlaexposed to sodium arsenate for 35 days. Bar represents SE of the mean. Compar-isons of means (control and treated fish) were done by Student’s t-test. * Significantat 5% level (P < 0.05).

Fig. 3. Enzymological alterations (a. AST; b. ALT) of C. catla exposed to sodiumarsenate for 35 days. Bar represents SE of the mean. Comparisons of means (controland treated fish) were done by Student’s t-test. * Significant at 5% level (P < 0.05).



of arsenite was found to be 14.9 mg/l in Apelts quadricus and 16.0mg/l in Menidia menidia (EPA, 1980), 15 mg/l in Oryzias latipes(Suhendrayatna et al., 2002), 21.0 mg/l in Oncorhynchus mykiss(Wang et al., 2004), 8.4 mg/l in C. batrachus (Ghosh et al., 2006)and 18.211 ppm in Anabas testudineus (Akter et al., 2008). Ourresults indicate that the observed LC 50 value may be due to thesensitivity of the fish and purity of the compounds.

In general the toxicity of arsenic depends on its chemical formor speciation; the inorganic forms are more toxic than organicforms (Sharma and Sohn, 2009). Arsenate (As5+) is usually thedominant form in natural waters and is less toxic to humans andanimals when compared to Arsenite (As3+) (Suhendrayatna et al.,2002). The high toxicity of arsenite (As3+) results from its greateraffinity with the sulfhydryl groups of biomolecules, whereas arse-nate (As5+) do not directly bind to sulfhydryl group to exert itstoxic effects (Suzuki et al., 2008). Inside a cell, arsenite bind with–SH groups present in proteins and arsenate interfering with phos-phorylation reactions (Andrew et al., 2003).

The elevated level of arsenic concentration in aquatic ecosystemaffects various physiological systems like growth, reproduction, ionregulation, smoltification, gene expression, immune function, en-zyme activities and histopathology of fish (Pedlar et al., 2002; Dat-ta et al., 2009). Arsenic may cause oxidative stress in the liver offish and brings about alterations in hematological parameters(Bhattacharya and Bhattacharya, 2007). Hematological profiles offishes are widely used to monitor the environmental pollution inaquatic ecosystem (Carvalho and Fernandes, 2006). These parame-ters are also used to detect the physiological status of animals andindicators of stress (Adhikari et al., 2004). The hematologicalparameters include RBC, WBC, Ht, Hb and other hematologicalindices like MCV, MCH and MCHC are frequently used to assessthe health status of fish (Nussey et al., 1995). The presence of tox-icant in the aquatic media may affect the water quality which inturn affects the values of hematological parameters of fish, dueto its close association with the external environment (van Vuren,1986).

Anaemic condition of fish exposed to arsenic has been reportedby Cockell et al. (1991) and Pedlar et al. (2002). The present studyalso an anaemic condition of the fish was observed during acuteand sublethal treatment, which may result in low level of Hb inarsenate treated fish. Inhibition of erythropoiesis due to arsenictoxicity by its action on membrane may form another possible rea-son. The decreased number of RBC in fish due to toxicant exposurehas been reported by Allin and Wilson (2000) and Chowdhury et al.(2004). The observed decrease in RBC in the present investigationin both the treatments resulted from inhibition of RBC productionor Hb synthesis by the toxicant or the accumulation of arsenic inthe gill region might have damaged the structure of gill leads tohemolysis. Tripathi et al. (2003) reported that the decrease levelof hemoglobin and packed cell volume in Clarias batrachus exposedto waterborne arsenic. Low levels of arsenic exposure may causedecreased production of red and white blood cells (Abernathyet al., 2003). The observed decrease in hematocrit value in the pres-ent study indicates the anemic condition of fish due to arsenic tox-icity. Swelling of RBC’s due to hypoxic condition in the toxicanttreated organisms may lead to a significant increase in MCV valueas suggested by Wepener et al. (1992). The increase in MCV mayalso result from an increase of immature RBC (Carvalho and Fer-nandes, 2006). In the present investigation the significant increaseof MCV and MCH during acute and sublethal treatment might bedue to the above said reasons. In the later stages the high percent-age of immature red blood cells in the circulation might be the rea-son for MCV and MCH decrease. The significant increase of MCHCvalue during acute treatment might be resulted from sphaerocyto-sis as suggested by Sobecka (2001). However the observed lowconcentration of MCHC during sublethal treatment might have re-

sulted from decrease in Hb synthesis due to toxic action (Nusseyet al., 1995).

It is well known that the changes in leucocyte counts afterexposure to pollutants may be associated to a decrease in nonspe-cific immunity of the fish. Leucocytes are involved in the regulationof immunological function in many organisms and the increase inWBC in stressed animals indicates a protective response to stress(Witeska, 2004). In the present investigation the significant in-crease in WBC during sublethal treatment (up to 20th day) mighthave resulted from stimulation of immune system by arsenateand to protect the fish against toxicity. Kotsanis et al. (2000) re-ported significant decrease in WBC count in Oncorhynchus mykissexposed to arsenic due to decrease in number of lymphocytes.The decrease in WBC count during acute and sublethal treatment(after 20th day) may be due to extended toxic effect of arsenic inkidney tissue, which is the primary site of haematopoiesis, provok-ing immunosuppression. Another possible reason may be due toinhibition of white blood cell maturation and the release from tis-sue reservoirs by the action of arsenic. Datta et al. (2009) statedthat chronic exposure of arsenic affected the structure of head kid-ney characterized by loss in leucocyte number.

In general the presence of toxicants in aquatic media exerts itseffect at cellular or molecular level which results in significantchanges in biochemical parameters. Due to metal complex forma-tion, normal functioning of cell is disturbed and that in turn mayresult in variation on physiological and biochemical mechanismsof animals (Gagnon et al., 2006). The influence of stressors on car-bohydrate metabolism of fish includes alterations in glucose, gly-cogen, and lactic acid content. Among these the blood glucoselevel has been used as an indicator of environmental stress and re-flected the changes in carbohydrate metabolism under hypoxiaand stress conditions. Tseng (2004) reported that chronic exposureof arsenic or its methylated metabolites induced diabetes mellitusin rats and this condition may be responsible for hyperglycemia.Thus an elevation of blood glucose level in the present study dur-ing sublethal treatment might be due to gluconeogenesis to pro-vide energy for the increased metabolic demands imposed bysodium arsenate stress. The significant reduction in plasma glucoselevels during acute treatment might be due to hypoxic conditionscaused by arsenic leading to an excess utilization of stored carbo-hydrates. In the present investigation the decrease in plasma pro-tein during acute and sublethal treatment is supported by thereports of Nandi et al. (2005), Yousef et al. (2008), and Palaniappanand Vijayasundaram (2009) suggesting that the decrease in plasmaprotein may be due to liver cirrhosis or nephrosis or might be dueto alteration in enzymatic activity involved in protein biosynthesis.

Enzyme activities are considered as sensitive biochemical indi-cators and widely used to assess the health of the organism inaquatic toxicology (Gul et al., 2004). Several soluble enzymes ofblood serum have been considered as indicators of the hepatic dys-function and damage. Among the array of enzymes used the aspar-tate aminotransferase (AST) and alanine aminotransferase (ALT)are widely used to detect the tissue damage caused by the toxi-cants (Jung et al., 2003). In fish, liver is the major organ for arsenictoxicity and plays a major role in uptake, accumulation, biotrans-formation and excretion of arsenic (Pedlar and Klaverkamp,2002). Datta et al. (2007) observed elevated level of AST and ALTin C. batrachus exposed to arsenic at sublethal concentration. Ar-senic can inhibit the activities of many enzymes especially thoseinvolved in the cellular glucose uptake, gluconeogenesis, fatty acidoxidation and production of glutathione due to its sulfhydryl groupbinding capability (Pal and Chatterjee, 2004). Humtsoe et al. (2007)reported significant decrease in liver AST and ALT in Labeo rohitaexposed to arsenic which reflects significant decrease in structureand function of cell organelles like endoplasmic reticulum andmembrane transport system. They also suggested that arsenate



which resembles phosphate is used by cells for energy and signal-ling. By displacing phosphate in enzymes or signalling proteins, ar-senic can block energy production and normal cell signalling(Dartmouth Toxic Metals Research, 2005).

In the present study a biphasic response of AST and ALT activitywas noticed during sublethal treatment. Long-term exposure en-hanced the activities of enzymes (AST and ALT) suggesting thatwith increase in exposure period, the organism tries to mitigatethe toxic and induced stress by increased rate of metabolism. Thesignificant decrease of AST and ALT activity during acute and sub-lethal treatment may be due to damaged hepatocytes are no longercapable of synthesizing AST protein. Further the significant de-crease in ALT activity might have been resulted from the renalfailure.

5. Conclusions

The results of the present investigation indicate that arsenicexposure during acute and sublethal treatment induces significantchanges in the hematological, biochemical and enzymological pro-files of an Indian major carp Catla catla. The presence of such levelof arsenic in the natural environment will definitely affect the sur-vival of fish. The results also imply a better understanding on thetoxicological endpoint of this specific toxicant and also guide toascertain safe levels in the aquatic environment and protection ofaquatic habitants. Further it is necessary to control the dischargeof arsenic compounds into nearby aquatic bodies, because fish isa chief and major source of protein worldwide.

Conflict of interest

The authors declare that there are no conflicts of interest.

Acknowledgments

The authors are thankful to Dr. Shelley Bhattacharya, Professor,Environmental Toxicology Laboratory, Centre for Advanced Studiesin Zoology, Department of Zoology, School of Life Science, VisvaBharati University, Santiniketan, West Bengal, India for the valu-able comments and suggestions to improve the manuscript.

References

Abernathy, C.O., Thomas, D.J., Calderon, R.L., 2003. Health and risk assessment ofarsenic. J. Nutr. 133, 1536–1538.

Adhikari, S., Sarkar, B., Chatterjee, A., Mahapatra, C.T., Ayyappan, S., 2004. Effects ofcypermethrin and carbofuran haematological parameters and prediction oftheir recovery in a freshwater teleost, Labeo rohita (Hamilton). Ecotoxicol.Environ. Saf. 58, 220–226.

Agusa, T., Takagi, K., Kubota, R., Anan, Y., Iwata, H., Tanabe, S., 2008. Specificaccumulation of arsenic compounds in greenturtles (Cheloniamydas) andhawksbill turtles (Eretmochelys imbricata) from Ishigaki Island, Japan. Environ.Pollut. 153, 127–136.

Akter, M.S., Ahmed, K., Akhand, A.A., Islam, M., 2008. Acute toxicity of arsenic andmercury to fresh water climbing perch, Anabas testudineus (Bloch). World J.Zool. 3 (1), 13–18.

Akter, K.F., Owens, G., Davey, D.E., Naidu, R., 2005. Arsenic speciation and toxicity inbiological systems. Rev. Environ. Contam. Toxicol. 184, 97–149.

Allin, C.J., Wilson, R.W., 2000. Effects of pre-acclimation to aluminium on thephysiology and swimming behaviour of juvenile rainbow trout (Oncorhynchusmykiss) during a pulsed exposure. Aquat. Toxicol. 51 (2), 213–224.

Andrew, A.S., Warren, A.J., Brachowsky, A., Temple, K.A., Klei, L., Soucy, N.V., Oara,K.A., Hamilton, J.W., 2003. Genomic and proteomic profiling of responses totoxic metals in human lung cells. Environ. Health Perspect. 111, 825–835.

APHA, American public health association (APHA), 2005. In: Eaton, Andrew E.,Clesceri, Lenore S., Rice, Eugene W., Greenberg, Arnold, E. (Eds.), StandardMethods for the Examination of Water and Wastewater, 21st ed., CentennialEdition. APHA, AWWA, WEF, Washington, DC.

Aposhian, H.V., Aposhian, M.M., 2006. Arsenic toxicology: five questions. Chem. Res.Toxicol. 19, 1–15.

ATSDR, 2002. Toxicological Profile for Arsenic. Agency for Toxic Substances andDisease Registry. SUDHHS, PHS, Washington, DC.

Bears, H., Richards, J.G., Schulte, P.M., 2006. Arsenic exposure alters hepatic arsenicspecies composition and stress mediated-gene expression in the commonkillifish (Fundulus heteroclitus). Aquat. Toxicol. 77, 257–266.

Bhattacharya, A., Bhattacharya, S., 2007. Induction of oxidative stress by arsenic inClarias batrachus: involvement of peroxisomes. Ecotoxicol. Environ. Saf. 66,178–187.

Carvalho, C.S., Fernandes, M.N., 2006. Effect of temperature on copper toxicity andhematological responses in the neotrophical fish, Prochilodus scrofa at low andhigh pH. Aquaculture 251, 109–117.

Cervantes, C., Ji, G., Ramirez, J.L., Silver, S., 1994. Resistance to arsenic compounds inmicroorganisms. FEMS Microbiol. Rev. 15, 355–367.

Chowdhury, M.J., Pane, E.F., Wood, C.M., 2004. Physiological effects of dietarycadmium acclimation and waterborne cadmium challenge in rainbow trout:respiratory, ionoregulatory, and stressparameters. Comp. Biochem. Physiol. CToxicol. Pharmacol. 139, 163–173.

Cockell, K.A., Hilton, J.W., Bettger, W.J., 1991. Chronic toxicity of dietary disodiumarsenate heptahydrate to juvenile rainbow trout (Oncorhynchus mykiss). Arch.Environ. Contam. Toxicol. 21, 518–527.

Cooper, G.R., Mc Daniel, V., 1970. The determination of glucose by the O-toluidinemethod. Stand. Meth. Clin. Chem., 159.

Cullen, W.R., Reimer, K.J., 1989. Arsenic speciation in the environment. Chem. Rev.89, 713–764.

Dartmouth Toxic Metals Research Programme, 2005. The Facts on Arsenic.University of Dartmouth, New Hampshire, USA.

Datta, S., Ghosh, D., Saha, D.R., Bhattacharaya, S., Mazumder, S., 2009. Chronicexposure to low concentration of arsenic is immunotoxic to fish: role of headkidney macrophages as biomarkers of arsenic toxicity to Clarias batrachus.Aquat. Toxicol. 92, 86–94.

Datta, S., Saha, D.R., Ghosh, D., Majumdar, T., Bhattacharya, S., Mazumder, S., 2007.Sub-lethal concentration of arsenic interferes with the proliferation ofhepatocytes and induces in vivo apoptosis in Clarias batrachus L.. Comp.Biochem. Physiol. C Comp. Pharmacol. Toxicol. 145, 339–349.

De Boeck, G., De Smet, H., Blust, R., 1995. The effect of sublethal levels of copper onoxygen consumption and ammonia excretion in the common carp Cyprinuscarpio. Aquat. Toxicol. 32, 127–141.

Drabkin, D.L., 1946. Spectrometric studies, XIV – the crystallographic and optimalproperties of the hemoglobin of man in comparison with those of other species.J. Biol. Chem. 164, 703–723.

Duker, A.A., Carranza, E.J.M., Hale, M., 2005. Arsenic geochemistry and health.Environ. Int. 31 (5), 631–641.

EPA, 1980. Ambient water quality criteria for lead. EPA Report 440/5/80-057.Fattorini, D., Bochetti, R., Bompadre, S., Regoli, F., 2004. Total content and chemical

speciation of arsenic in the polychaete Sabella spallanzanii. Mar. Environ. Res.58, 839–843.

Ferguson, J.F., Gavis, J., 1972. A review of the arsenic cycle in natural waters. WaterRes. 6 (11), 1259–1274.

Finney, D.J., 1978. Statistical Method in Biological Assay, third ed. CambridgeUniversity Press, London. p. 508.

Gagnon, A., Jumarie, C., Hontela, A., 2006. Effects of Cu on plasma cortisol andcortisol secretion by adrenocortical cells of rainbow trout, Oncorhynchus mykiss.Aquat. Toxicol. 78, 59–65.

Gebel, T., 2000. Confounding variables in the environmental toxicology of arsenic.Toxicology 144, 155–162.

Ghosh, D., Bhattacharya, S., Mazumder, S., 2006. Perturbations in the catfishimmune responses by arsenic: organ and cell specific effects. Comp. Biochem.Physiol. C Comp. Pharmacol. Toxicol. 143, 455–463.

Ghosh, D., Datta, S., Bhattacharya, S., Mazumder, S., 2007. Long-term exposure toarsenic affects head kidney and impairs humoral immune responses of Clariasbatrachus. Aquat. Toxicol. 81, 79–89.

Gonzalez, H.O., Roling, J.A., Baldwin, W.S., Bain, L.J., 2006. Physiological changes anddifferential gene expression in mummichogs (Fundulus heteroclitus) exposed toarsenic. Aquat. Toxicol. 77, 43–52.

Gul, S., Belge-Kuruta, E., Yildiz, E., Sahan, A., Doran, F., 2004. Pollution correlatedmodifications of liver antioxidant systems and histopathology of fish(Cyprinidae) living in Seyhan Dam Lake, Turkey. Environ. Int. 30, 605–609.

Hanaoka, K., Koga, H., Tagawa, S., Kaise, T., 1992. Degradation of arsenobetaine toinorganic arsenic by the microorganisms occurring in the suspendedsubstances. Comp. Biochem. Physiol. B Comp. Biochem. 101 (4), 595–599.

Harper, H.A., Rodwell, V.W., Mayer, P.A., 1978. Review of physiological chemistry,seventeen ed. Lange Medical Publication, California. pp. 19-80.

Hogeboom, G.H., Schneider, W.C., Palade, G.E., 1948. Cytochemical studies ofmammalian tissues: I. Isolation of intact mitochondria from rat liver; somebiochemical properties of mitochondria and submicroscopic particulatematerial. J. Biol. Chem. 172, 619–635.

Humtsoe, N., Davoodi, R., Kulkarni, B.G., Chavan, B., 2007. Effect of arsenic on theenzymes of the rohu carp, Labeo rohita (Hamilton 1822). Raffles Bull. Zool. 14,17–19.

Jain, C.K., Ali, I., 2000. Arsenic: occurence, toxicity and speciation techniques. Water.Res. 34, 4304–4312.

Jung, S.H., Sim, D.S., Park, M.S., Jo, Q.T., Kim, Y., 2003. Effects of formalin onhematological and blood chemistry in olive flounder, Paralichthys olivaceus(Temminck at Schlegel). Aquat. Res. 34, 1269–1275.

Kaise, T., Sakurai, T., Saitoh, T., Matsubara, C., Takada-Oikawa, N., Hanaoka, K., 1998.Biotransformation of arsenobetaine to trimethylarsine oxide by marinemicroorganisms in a gill of clam Meretrix Lusoria. Chemosphere 37 (3), 443–449.



Kotsanis, N., Iliopoulou-Georgudaki, J., Kapata-Zoumbos, K., 2000. Changes inselected hematological parameters at early stages of the rainbow trout,Oncorhynchus mykiss, subjected to metal toxicants: arsenic, cadmium andmercury. J. Appl. Ichthyol. 16, 276–278.

Liu, F., Gentles, A., Theodorakis, C.W., 2008. Arsenate and perchlorate toxicity,growth effects, and thyroid histopathology in hypothyroid zebrafish Danio rerio.Chemosphere 71, 1369–1376.

Lowry, O.H., Rosebrough, N.J., Farr, A.L., Randall, R.J., 1951. Protein measurementwith the folin phenol reagent. J. Biol. Chem. 193, 265–275.

Maeda, S., Inoue, R., Kozono, T., Tokuda, T., Ohki, A., Takeshita, T., 1990. Arsenicmetabolism in a freshwater food chain. Chemosphere 20, 101.

Maher, A., Goessler, W., Kirby, J., Raber, G., 1999. As concentration and speciation inthe tissues and blood of sea mullet (Mugil cephalus) from lake Macquarie NSW,Australia. Mar. Chem. 68, 169–182.

Mandal, B.K., Suzuki, K.T., 2002. Arsenic round the world: a review. Talanta 58, 201–235.

Nandi, D., Patra, R.C., Swarup, D., 2005. Effect of cysteine, methionine, ascorbic acidand thiamine on arsenic-induced oxidative stress and biochemical alterationsin rats. Toxicology 211, 26–35.

Nelson, D.A., Morris, M.W., 1989. Basic methodology. Hematology and coagulation,part IV. In: Nelson, D.A., Henry, J.B. (Eds.), Clinical Diagnosis and Managementby Laboratory Methods, 17th ed. W.B. Saunder Company, Philadelphia, USA, pp.578–625 (Chapter 27).

Nemcsok, J., Benedeczky, I., 1990. Effect of sublethal concentrations of phenol onsome enzyme activities and blood sugar level of carp, Cyprinus carpio (L.).Environ. Monit. Assess. 14, 377–383.

Norin, H., Vahter, M., Christakopoulos, A., Sandstrom, M., 1985. Concentration ofinorganic and total arsenic in fish from industrially polluted water.Chemosphere 14, 325–334.

Nussey, G., van Vuren, J.H., Du Preez, H.H., 1995. Effect of copper on bloodcoagulation of Oreochromis mossambicus (Cichlidae). Comp. Biochem. Physiol. CPharmacol. Toxicol. 111, 359–367.

Oladimeji, A.A., Qadri, S.U., DeFreitas, A.S.W., 1984. Long term effects of arsenicaccumulation in rainbow trout (Salmo gairdneri). Bull. Environ. Contam. Toxicol.32, 732–741.

Ozmen, M., Gungordu, A., Kucukbay, F.Z., Guler, R.E., 2006. Monitoring the effects ofwater pollution on Cyprinus carpio in Karakaya Dam Lake, Turkey. Ecotoxicology15, 157–169.

Pal, S., Chatterjee, A.K., 2004. Protective effect of N-acetylcysteine against arsenicinduced depletion in vivo of carbohydrate. Drug Chem. Toxicol. 27, 179–189.

Palaniappan, P.L.R.M., Vijayasundaram, V., 2009. The effect of arsenic exposure andthe efficacy of DMSA on the proteins and lipids of the gill tissues of Labeo rohita.Food Chem. Toxicol. 47, 1752–1759.

Pedlar, R.M., Klaverkamp, J.F., 2002. Accumulation and distribution of dietaryarsenic in Lake Whitefish (Coregonus clupeaformis). Aquat. Toxicol. 57, 153–166.

Pedlar, R.M., Ptashynski, M.D., Evans, R., Klaverkamp, J.F., 2002. Toxicological effectsof dietary arsenic exposure in Lake Whitefish (Coregonus clupeaformis). Aquat.Toxicol. 57 (3), 167–189.

Reitman, S., Franckel, S., 1957. A colorimetric method for the determination ofserum glutamic oxalo acetic and glutamic pyruvic transaminase. Am. J. Clin.Pathol. 28, 56–63.

Ridley, W.P., Dizikes, L.J., Wood, J.M., 1977. Biomethylation of toxic elements in theenvironment. Science 197, 329–332.

Rodwell, V.W., 1988. Metabolism of proteins and aminoacids. In: Mayes, P.A.,Rodwell, V.W. (Eds.), Review of Biochemistry. Lange Medical Publications,California, pp. 265–319.

Roy, S., Bhattacharya, S., 2006. Arsenic-induced histopathology and synthesis ofstress proteins in liver and kidney of Channa punctatus. Ecotoxicol. Environ. Saf.65, 218–229.

Rusia, V., Sood, S.K., 1992. Routine hematological tests. In: Mukerjee, Kanai L. (Ed.),Medical Laboratory Technology, vol. I. Tata McGraw Hill Publishing CompanyLimited, New Delhi, pp. 252–258 (Fifth reprint).

Santa Maria, I., Gonzalez, M., Lara, W., Ober, A., 1986. Arsenic levels in Chileanmarine species. Bull. Environ. Contam. Toxicol. 37, 593–598.

Sharma, V.K., Sohn, M., 2009. Aquatic arsenic: toxicity, speciation, transformations,and remediation. Environ. Int. 35, 743–759.

Singh, A.K., Banerjee, T.K., 2008. Toxic effects of sodium arsenate (Na2HAsO47H2O)on the skin epidermis of air-breathing catfish Clarias batrachus (L.). VeterinarskiArhiv. 78 (1), 73–88.

Smedley, P.L., Edmunds, W.M., Pelig-Ba, K.B., 1996. Mobility of arsenic ingroundwater in the Obuasi area of Ghana. In: Appleton, J.D., Fuge, R., McCall,G.J.H. (Eds.), Environmental Geochemistry and Health. Geological SocietySpecial Publication No133, Geological Society, London, pp. 163-181.

Sobecka, E., 2001. Changes in the iron leveling the organs and tissues of wellscatfish, Silurus glanis L. caused by nickel. Acta. Ichthyol. Piscat. 31 (2), 127–143.

Sprague, J.B., 1971. Measurement of pollution toxicity to fish. III. Sub-lethal effectsand ‘safe’ concentration. Water Res. 5, 245–266.

Suhendrayatna, O.A., Nakajima, T., Maeda, S., 2002. Studies on the accumulation andtransformation of arsenic in freshwater organisms. I. Accumulation,transformation and toxicity of arsenic compounds on the Japanese medaka,Oryzias latipes. Chemosphere 46, 319–324.

Suzuki, N., Naranmandura, H., Hirano, S., Suzuki, L.T., 2008. Theoretical calculationsand reaction analysis on the interaction of pentavelent thioarsenicals withbiorelevant thiol compounds. Chem. Res. Toxicol. 21, 550–553.

Tripathi, S., Sahu, D.B., Kumar, R., Kumar, A., 2003. Effect of acute exposure ofsodium arsenite (Na3AsO3) on some hematological parameters of Clariasbatrachus (common Indian catfish) in vivo. Indian J. Environ. Health 45, 183–188.

Tseng, C., 2004. The potential biological mechanisms of arsenic-induced diabetesmellitus. Toxicol. Appl. Pharmacol. 197, 67–83.

Tuzen, M., Çıtak, D., Mendil, D., Soylak, M., 2009. Arsenic speciation in natural watersamples by coprecipitation-hydride generation atomic absorption spectrometrycombination. Talanta 78 (1), 52–56.

Vahter, M., 2002. Mechanisms of arsenic biotransformation. Toxicology 181–182,211–217.

van Vuren, J.H., 1986. The effect of toxicants on the hematology of Labeo umbratus(Teleostei: Cyprinidae). Comp. Biochem. Physiol. C Pharmacol. Toxicol. 83, 155–159.

Ventura-Lima, J., Sandrini, J.Z., Ferreira-Cravo, M., Piedras, F.R., Moraes, T.B.,Fattorini, D., Notti, A., Regoli, F., Geracitano, L.A., Marins, L.F., Monserrat, J.M.,2007. Toxicological responses in Laeonereis acuta (Annelida, Polychaeta) afterarsenic exposure. Environ. Int. 33, 559–564.

Wang, Y.C., Chaung, R.H., Tung, L.C., 2004. Comparison of the cytotoxicity inducedby different exposure to sodium arsenite in two fish cell lines. Aquat. Toxicol.69, 67–79.

Wepener, V., van Vuren, J.H.J., Du Preez, H.H., 1992. The effect of hexavalentchromium at different pH values on the haematology of Tilapia sparrmanii(Cichlidae). Comp. Biochem. Physiol. C 10l (2), 375–381.

Witeska, M., 2004. The effect of toxic chemicals of blood cell morphology in fish.Fresenius Environ. Bull. 13 (12a), 1379–1384.

Wrobel, K., Wrobel, K., Parker, B., Kannamkumarath, S.S., Caruso, J.A., 2002.Determination of As(III), As(IV), monomethylarsonic acid, dimethyl arsenicacid and arsenobetaine by HPLC–ICP-MS: analysis of reference material, fishtissue and urine. Talanta 58, 899–907.

Yousef, M.I., El-Demerdash, F.M., Radwan, F.M.E., 2008. Sodium arsenite inducedbiochemical perturbations in rats: ameliorating effect of curcumin. Food Chem.Toxicol. 46, 3506–3511.



INTRODUCTIONA wide range of chemicals has been shown to cause

endocrine disturbances in living organisms. Under an envi-ronmental stress, organisms are known to exhibit primaryresponse by way of changes in hormone levels, which inturn are known to stimulate the secondary responses includ-ing physiological and biochemical changes. The homeosta-sis of an animal is disturbed as a result of the actions ofintrinsic and/or extrinsic stimuli or stressors (WendelaarBonga 1997). Among stressors, heavy metals are of greaterimportance because of their long biological half-lives, which

pose a real threat to aquatic organisms, especially fish.In sub-acute concentrations, heavy metals gradually accu-mulate in various organisms, as they reach higher trophiclevels of the food chain but at high concentrations heavymetal are lethal to aquatic organisms.Among the heavy met-als, copper has been regarded as strongly toxic to fish andother aquatic animals (Sloman 2003). Copper, at high con-centrations, causes disturbances in sodium- and chloridehomeostasis and alters nitrogenous metabolites in aquaticanimals (Bury et al. 2003, Sloman 2004). However, little isknown about the effects of copper on stress modulation.

ACTA ICHTHYOLOGICA ET PISCATORIA (2007) 37 (2): 81–85 DOI: 10.3750/AIP2007.37.2.02

* Correspondence: Dr Mathan Ramesh, Unit of Toxicology, Department of Zoology, Bharathiar University, Coimbatore – 641046, India, fax: +91-422-2422387,e-mail: [email protected]

PRIMARY STRESS RESPONSES OF COMMON CARP, CYPRINUS CARPIO,EXPOSED TO COPPER TOXICITY

Mathan RAMESH 1*, Sathyanarayanan SENTHIL KUMARAN 1, Chokkalingam KAVITH 1,Manoharan SARAVANAN 1, and Ahmed MUSTAFA 2

1Unit of Toxicology, Department of Zoology, Bharathiar University, Coimbatore, India2Department of Biology, Indiana University Purdue University Fort Wayne, IN 46805, USA

Ramesh M., Senthil Kumaran S., Kavith C., Saravanan M., Mustafa A. 2007. Primary stress responsesof common carp, Cyprinus carpio, exposed to copper toxicity. Acta Ichthyol. Piscat. 37 (2): 81–85.

Background. Copper is a heavy metal, and an aquatic pollutant, known for its bio-accumulative and non-biodegrad-able properties. In the aquatic ecosystems, acute and sublethal concentrations of copper may be linked to a vari-ety of effects. Recently, hormones, particularly those regulating vital functions, such as osmoregulation, energymetabolism, and reproduction, may be used as potential biomarkers for sublethal toxicity studies. In the presentstudy, the potential effect of a heavy metal—copper on hormonal changes (cortisol and prolactin) in an economi-cally important fresh-water fish—common carp, Cyprinus carpio, was examined.Materials and Methods. The experimental fish were subjected to two experimental regimes (backed by controls).In the first treatment they were exposed to the acute concentration of copper sulphate, amounting to 0.7 ppm.The second treatment featured copper sulphate concentration of 0.07 ppm, constituting 10% of LC50 (24 h).The acute-toxicity trials were carried out in two, 20-L, circular plastic tubs. Twenty fish from the tank were select-ed randomly and introduced to each tub. Control was maintained in 2 similar plastic tubs with 20 fish per tub. After24 h, fish from control- and copper-exposure tubs were taken for analyses. To observe the sublethal toxicity four,125-L, glass aquaria, filled with clean water were used. 200 fish were randomly selected from the stock and 100of them were added to two aquaria, 50 fish in each, as experimental fish and 100 in two other aquaria, 50 in each,for as control fish. By the end of the stipulated period, 20 fish from control and 20 fish from experimental groupwere used for the hormone assay.Results. In both acute- and sublethal treatments, both cortisol- and prolactin levels increased. In sublethal treat-ment, however, plasma prolactin level decreased after 28-day exposure, showing a minimum percentage pointdecrease of 3.84 by the end of 35-day trial.Conclusion. The increase of the plasma cortisol was probably caused by release of cortisol from the interrenal tis-sue, as a mechanism of coping with stress. Significantly lower content of prolactin levels in sublethal treatmentcould be an indicative of a possible restored hydromineral balance or atrophy of the pituitary prolactin cells lead-ing to inhibited prolactin secretion of the fish. These alterations of the above hormonal changes may be used asstress biomarkers in fish.

Keywords: copper, acute, sublethal, cortisol, prolactin, fish, carp, Cyprinus carpio


Animal responses to stressors have been focused on theactivation of the neuro-endocrine systems via, the hypo-thalamic-pituitary-inerrenal axis (HPI) (Donaldson 1981,Barton and Iwama 1991). Along this axis corticotropinrelease factors (CRF) are given off from the hypothalamusduring stress stimulating the secretion of the pituitary hor-mones as prolactin (PRL) and adrenocorticotropin (ACTH)(Fu et al. 1990, Barton and Iwama 1991, Iwama et al. 2003).In turn, ACTH stimulates the synthesis and release of cor-tisol, the major corticosteroid from the interrenal cells infish (Yang and Albright 1995). The role of cortisol as anintermediary in metabolism is vital, since it is the majorgulcocorticosteroid secreted by the teleosts’ interrenal tis-sue in response to adrenocorticotropic hormone stimula-tion (Yang andAlbright 1995, Pottinger et al. 2000). Indeed,increased PRL release has been implicated in the success-ful adaptation of fish to acidic water (Wendelaar Bonga etal. 1984, 1987) and heavy metals (Fu et al. 1990). Thus,endocrine responses through their integrative- and earlywarning capacity may offer as potential indicators that maybe useful in the detection and assessment of sublethal toxicstress in fish exposed to polluted environments. Hormoneshave been included in this study as they are easily measur-able from the blood and have been validated for endocrineresponse. The objective of the presently reported study wasto find out the primary responses (plasma cortisol and pro-lactin) in a freshwater teleost fish, Cyprinus carpio, exposedto acute- and sublethal copper toxicity.

MATERIALSAND METHODSFingerlings of scale carp, Cyprinus carpio carpio L.,

(5–7 cm) were procured from Tamil Nadu Fisheries Devel-opment Corporation Ltd., (Fish Farm,Alizhiar, Tamil Nadu,India) and were acclimated to laboratory conditions (24 ±2.0ºC) for 20 days. Fish were fed ad libitum with rice branand ground nut oil cake (3 : 1 ratio) in the form of smalldough, twice a day. Amajor portion of water was changeddaily in order to avoid any accumulation of excretory prod-ucts and unused feed, which might cause further stress tothe fish. Since, physico-chemical features of water havesignificant influence on the biodegradability and toxicityof pollutants, hydrobiological parameters such as temper-ature (26.0 ± 2.0ºC), pH (7.1 ± 0.1), salinity (0.6 ± 0.02ppt), total hardness (18.0 ± 0.4 mg · L–1), calcium (4.10 ±0.5 mg · L–1), and magnesium (2.2 ± 0.6 mg · L–1) weremeasured by following the guidelines ofAnonymous (1998)and were maintained throughout the study period.Five hundred fish were stocked in a large cement tank

(122 × 183 × 91 cm) after it was cleaned and disinfectedwith potassium permanganate. Fish with an average weightof 6.22 g and an average (total) length of 7.5 cm were select-ed for the experiment. The LC50 value of the copper sul-phate for the fish (=0.7 ppm) was calculated following themethod of Finney (1978). The acute toxicity experimentwas carried out in two circular plastic tubs, filled with 25L of water. A normal pH (7.1) and copper sulphate concen-tration of 0.7 ppm (LC50 24 h) were maintained through-out the experiment. Twenty fish, which were already with-

held from feeding for 48 h, were introduced into each tub.Control was maintained in 2 circular plastic tubs with 20fish per tub. After 24 h, 40 randomly sampled fish, 20 eachfrom the control- and treatment groups were used for thehormone assay.Chronic effects of sublethal concentration of the toxi-

cant were studied in four, 125-L glass aquaria, filled withclean water. The aquaria labelled A1 and A2 representedcontrol and experimental, respectively. Aquarium A1 wasfilled with sublethal aqueous solution of copper sulphateof 0.07 ppm (LC50 = 0.7 ppm, as suggested by Sprague1971) and AquariumA2 was filled with clean water. Then200 fish were randomly selected from the stock and addedto these aquaria, 100 in each group, 50 in each replicate.Care was taken to minimize disturbances to the animals.After the stipulated time period (24 h for the acute studyand 7 days for sublethal study) fish from control- and exper-imental aquaria were sacrificed and blood was collected bycardiac puncture using heparinised syringes and kept at lowtemperature (4˚C). Aminimum of 10 fish, randomly select-ed from each replicate, 20 from each group, were used forfurther assays. All analyses were performed on pooled bloodsamples from fish of identical exposure times. Then thepooled blood samples were centrifuged for 15 min at 10000 rpm, the plasma was withdrawn, and transferred intoclean vials for hormone analyses.Plasma cortisol was estimated quantitatively by direct

solid phase enzyme immunoassay according to the methodof Tietz (1986) using EIA gen cortisol kit manufactured andsupplied by IFCI Clone Systems, Casalecchio Di Reno,Italy by an automated microplate reader (Bio-Tek Instru-ments, USA) and plasma prolactin was estimated quanti-tatively by enzyme immunoassay by following the methodof Engvall (1980) using Medix Biotech prolactin enzymeimmunoassay test kit manufactured by Medix Biotech, Fos-ter City, California and marketed by Span Diagnostics, Indiaby an automated microplate reader. The method followedfor the plasma prolactin is a heterologous assay and crossreactivity of the antiserum to native carp growth hormoneand somatolactin is not known. This can be referred to as‘immunoreactive prolactin’ (ir-PRL). Statistical correlationbetween control and experimental values were made byStudent’s t-test.

RESULTSIn the acute-toxicity study, plasma cortisol and prolactin

levels of the experimental fish were elevated to 19.500 ±0.537 ng · mL–1 and 5.00 ± 0.126 ng · mL–1 respectivelycompared to those of control fish (6.110 ± 0.105 ng · mL–1;4.125 ± 0.156 ng · mL–1) showing a percentage-pointincrease of 219.14 and 21.21, respectively (Table 1). Sta-tistical analyses of data, by Student’s t-test, indicated thatvalues were significant (P < 0.05). In the sublethal-toxici-ty treatment, plasma cortisol levels steadily increased upto day 14, giving 96.24% increase (9.800 ± 0.505 to 11.500± 0.411 ng · mL–1) (Table 2). By the end of days 21, 28,and 35, plasma cortisol level showed a recovery by a per-centage-point increase of 38.27, 38.03, and 36.21, assum-

Ramesh et al.82


ing values: 8.200 ± 0.252, 8.020 ± 0.363 ng · mL–1, and8.350 ± 0.349 ng · mL–1. By the end of day 7, the plasmaprolactin level was 4.500 ± 0.221 and increased to 10.500± 0.221 by the end of day 14. This shows a sudden percent-age-point increase from 12.50 to 90.07. But after day 14(days 21 and 28, respectively) its level rapidly recoveredreaching 6.500 ± 0.221 and 5.800 ± 0.316, showing a per-centage-point increase of 27.45 and 20.23. However, at theend of day 35 of treatment, the prolactin level decreased to5.000 ± 0.126, showing a minimum decrease by 3.84 per-centage points.

DISCUSSIONFish are known to respond to environmental pollutants

by way of showing alterations in the serum hormonal lev-els (Thomas and Khan 1997). Plasma cortisol levels are themost commonly used stress indicator in fish because of the

rapid elevation that occurs in response to various stressorssuch as handling, confinement, poor water quality, anda wide variety of toxicants (Wendelaar Bonga 1997, Mustafaet al. 2000). Tomasso et al. (1981) reported that the releaseof corticosteroids into the circulation is brought about bytwo methods; firstly as in the case of handling, the animalperceives an external threat or disturbance and respondsphysiologically to meet the threat; secondly, the fish appar-ently is not threatened or stressed as long as the chemicalremains in the environment. However, when the chemicalis allowed to enter the animal, corticosteroids are releasedinto the circulation and corticosteroid release in this caseis probably a response to a physiological dysfunctionbrought about by the toxin.Lorz et al. (1978) reported a significant increase in plas-

ma cortisol level in Coho salmon Oncorhynchus kisutchexposed to cadmium, copper, and several metals, which

Stress response of carp to copper toxicity 83

Parameter Control Experiment Percentage-point change

Cortisol [ng·mL–1] 6.110 ± 0.105 19.500 ± 0.537* +219.14

Prolactin [ng·mL–1] 4.125 ± 0.156 5.00 ± 0.126* +21.21

E

Table 1Cortisol and prolactin levels in the plasma of Cyprinus carpio var. communis exposed to acute copper toxicity

(values are means ± standard error of five individual observations)

* Significant difference (P < 0.05).+ increase over control.

Exposuretime[days]

Plasma cortisol level [ng·mL–1] Plasma prolactin level [ng · mL–1]

control experiment control experiment

7 6.00 ± 0.254 9.800 ± 0.505*(+63.33)

4.00 ± 0.228 4.500 ± 0.221(+12.50)

14 5.860 ± 0.152 11.500 ± 0.411*(+96.24)

5.524 ± 0.255 10.500 ± 0.221*(+90.07)

21 5.930 ± 0.259 8.200 ± 0.252*(+38.27)

5.100 ± 0.334 6.500 ± 0.221*(+27.45)

28 5.810 ± 0.271 8.020 ± 0.363*(+38.03)

4.824 ± 0.302 5.800 ± 0.316(+20.23)

35 6.130 ± 0.154 8.350 ± 0.349*(+36.21)

5.200 ± 0.258 5.000 ± 0.126(–3.84)

Table 2Changes in the plasma cortisol and prolactin levels of Cyprinus carpio carpio exposed to varying periodsof sublethal copper sulphate toxicity (Values are means ± standard error of five individual observations)

* Significant difference (P < 0.05).Values in parentheses indicate percentage-point change over control.


may be due to the presence of metals in the ambient water.Fu et al. (1990) reported that the initial rise of cortisol con-centrations following 1 h of Cd treatment (representing analarm phase) appeared as a direct response of the fish(O. mossambicus) to a potentially harmful substance. Thesubsequent fall in the plasma cortisol level was consideredeither due to exhaustion or successful compensation. Brownand Waring (1996) in brown trout observed stimulation ofproteolysis and lipolysis for gluconeogenesis leading to theelevation of plasma glucose and also appear to be relatedto increased cortisol levels under stressful condition. In thepresent study, significant increase of plasma cortisol levelin Cyprinus carpio exposed to acute and sublethal coppertreatment might have resulted from the recognition of thepresence of a noxious substance.It appears in the present study that the fish exposed to

sublethal Cu treatment, went through all the three stages ofGeneral Adaptation Syndrome. The initial rise of cortisol(alarm phase) appears to be a direct response of the fish asa result of repartial of a potentiality harmful substance inwater (Iwama and Nakanishi 1996). The maintenance ofan elevated level during the following days apparently rep-resents a resistance phase during which period the animaltry to counteract the observed physiological changes, thesubsequent fall in its (plasma cortisol) levels thereaftermeans the exhaustion phase supporting the biphasic char-acter of cortisol release in fish.Prolactin is a member of the family of adenohypophysial

hormones and it has been termed a ‘‘jack of-all-trades’’withmore than 80 different hormonal activities ascribed to it(Nicoll and Bern 1971). Prolactin is one of the mainosmoregulatory hormones in fish maintaining the plasmaelectrolyte levels mainly by controlling permeability of thegill epithelium. Wood (1989) reported that pollutants areknown to interfere with osmotic and ionic regulations oforganisms thereby indirectly altering the various physio-logical processes and jeopardizing the very survival of thespecies in such polluted environments. In the present studythe observed increase in the prolactin level up to day 28could be taken to suggest that the fish adaptively tries toovercome the changes in the hydromineral metabolism inits body under copper stress by way of the action of pro-lactin on gills and kidney. Further the decrease in plasmaprolactin level after day 28 could be probably due toinhibitory effect of the pollutants on the adenohypophysialsecretory functions.In the present study it can be concluded that the alter-

ations of plasma cortisol and prolactin levels can be takenas a characteristic response to stressors and these primarystress hormones can be used as a stress biomarker in fish.

REFERENCESAnonymous 1998. Standard methods for the examination of water

and wastewater, 20th edn. American Public Health Associa-tion, Washington, DC.

Barton B.A., IwamaG.K. 1991. Physiological changes in fish fromstress in aquaculture with emphasis on the response and effectsof corticosteroids. Annual Review of Fish Diseases 1: 3–26.

Brown J.A.,Waring C.P. 1996. The physiological status of browntrout exposed to aluminium in acidic soft waters. Pp. 115–143.In: Taylor E.W. (ed.) Toxicology of Aquatic Pollution. Phys-iological, Cellular and Molecular Approaches. Society forExperimental Biology Seminar Series Vol. 57. CambridgeUniversity Press, Cambridge, UK.

Bury N.R., Walker P.A., Glover C.N. 2003. Nutritive metaluptake in teleost fish. Journal of Experimental Biology 206:11–23.

Donaldson E.M. 1981 The pituitary–interrenal axis as an indica-tor of stress in fish. Pp. 11–47. In: PickeringA.D. (ed.) Stressin fish. Academic Press, London.

Engvall E. 1980. Enzyme immunoassay—ELISA and EMJT. Pp.419–439. In: van Vunakis H., Langono J.J. (eds.) Methodsin Enzymology. Vol. 70. Academic Press, New York.

Finney D.J. 1978. Statistical methods in biological assay.3rd edn., Griffin Press, London.

Fu H., Steinebach O.M., van den Hamer C.J.A., Balm P.H.M.,Lock R.A.C. 1990. Involvement of cortisol and metal-lathionein-like proteins in the physiological responses of tilapia(Oreochromis mossambicus) to sublethal cadmium stress.Aquatic Toxicology 16: 257–369.

Iwama G.K., Afonso, L.O.B., Todgham A., Ackerman P.,Nakano K. 2003. Are hsps suitable for indicating stressedstates in fish? Journal of Experimental Biology 207: 15–19.

Iwama G., Nakanishi T. 1996. The fish immune system. Organ-ism, Pathogen, and Environment. Academic Press, San Diego.

Lorz H.W., Williams R.H., Fustish C.A. 1978. Effects of sev-eral metals on smolting of coho salmon,Oncorhynchus kisutch.(U.S. Environmental Protection Agency, Grant ReportR-804283). Oregon Department of Fish andWildlife, Corval-lis, Oregon.

MustafaA., MacWilliams C., Fernandez N., Matchett K., Con-boy G.A., Burka J.F. 2000. Effects of sea lice (Lepeoph-theirus salmonis Kröyer, 1837) infestation on macrophagefunctions in Atlantic salmon (Salmo salar L.). Fish and Shell-fish Immunology 10: 47–59.

Nicoll C.S., Bern H.A. 1971. On the actions of prolactin amongthe vertebrates: is there a common denominator? Pp. 299–324.In: Wolstenholme G.E.W., Knight, J. (eds.) Lactogenic Hor-mones. Churchill Livingstone, London.

Pottinger T.G., Carrick T.R., ApplebyA., YeomansW.E. 2000.High blood cortisol levels and low cortisol receptor affinity:Is the chub, Leuciscus cephalus, a cortisol-resistant teleost?General and Comparative Endocrinology 120: 108–117.

Sloman K.A. 2003. Copper, cortisol and the common carp. Jour-nal of Experimental Biology 206 (19): 3309.

Sloman K.A. 2004. Tough toadfish: surviving copper exposure.Journal of Experimental Biology 207 (19): vii.

Sprague J.B. 1971. Measurement of pollutant toxicity of fish III.Sublethal effects and safe concentrations. Water Research 5:245–266.

Thomas P., Khan I.A. 1997. Mechanisms of chemical interferencewith reproductive endocrine function in sciaenid fishes. Pp.29–51. In: Rolland R.M., Gilbertson M., Peterson R.E. (eds.)Chemically induced alterations in functional development andreproduction of fishes. Society of Environmental Toxicologyand Chemistry Technical Publications Series, Pensacola.

Ramesh et al.84


Tietz N.W. (ed.) 1986. Text Book of Clinical Chemistry.W.B. Saunders, Philadelphia.

Tomasso J.R., Davis K.B., Simco B.A. 1981. Plasma corticos-teroid dynamics in channel cat fish (Ictalurus punctatus)exposed to ammonia and nitrite. Canadian Journal of Fish-eries and Aquatic Sciences 38: 1106–1112.

Wendelaar Bonga S.E. 1997. The stress response in fish. Phys-iological Reviews 77: 591–625.

Wendelaar Bonga S.E., Flik G., Balm P.H.M. 1987. Physiolog-ical adaptation to acid stress in fish. Annales de la Sociétéroyale Zoologique de Belgique 117: 243–254.

Wendelaar Bonga S.E., Flik G., Fenwick, J.C. 1984. Prolactinand calcium metabolism in fish: Effects on plasma calcium andhigh-affinity Ca2+–ATPase in gills. Pp.188–190. In: Cohn D.V.,Potts jr. J.T., Fujita J. (eds.) Endocrine control of bone andcalcium metabolism. Elsevier Press, New York.

Wood C.M. 1989. The physiological problems of fish in acidwaters. Pp. 125–152. In: Morris R., Taylor E.W., BrownD.J.A., Brown J.A. (eds.) Acid toxicity and aquatic animals.Cambridge University Press, Cambridge, UK.

Yang C.Z., Albright L.J. 1995. Elevation of plasma cortisol andhypertrophic response of inter-renal and chromaffin tissuesof rainbow trout, Oncorhynchus mykiss (Walbaum), to theharmful diatom, Chaetoceros concavicornis. Journal of FishDiseases 18: 165–174.

Received: 11 May 2007Accepted: 11 October 2007

Published electronically: 30 November 2007

Stress response of carp to copper toxicity 85


publications - shodhgangashodhganga.inflibnet.ac.in/bitstream/10603/33892/10/publication.pdf ·...

Documents