PAPER www.rsc.org/jem | Journal of Environmental Monitoring

Publ

ishe

d on

07

Aug

ust 2

009.

Dow

nloa

ded

by L

omon

osov

Mos

cow

Sta

te U

nive

rsity

on

04/1

2/20

13 2

2:48

:23.

View Article Online / Journal Homepage / Table of Contents for this issue

A multibiomarker approach in Mytilus galloprovincialis to assessenvironmental quality

Alexandra Cravo, Belisandra Lopes, Angela Serafim, Rui Company, Luısa Barreira, Tania Gomesand Maria Joao Bebianno*

Received 19th May 2009, Accepted 24th July 2009

First published as an Advance Article on the web 7th August 2009

DOI: 10.1039/b909846a

A multibiomarker approach was carried out for the first time in the South Portuguese Coast using

Mytilus galloprovincialis, to assess environmental quality, establish if there are adverse biological

responses associated to different sources of anthropogenic contamination and to determine spatial and

seasonal trends. For this purpose the battery of biomarkers selected was: superoxide dismutase (SOD),

catalase (CAT), glutathione peroxidases (GPx total and Se dependent), Cytochrome P450 component

system, Glutathione-S-transferase (GST) and acetylcholinesterase (AChE), metallothionein (MT) and

lead-d-aminolevulinic acid dehydratase (ALAD), lipid peroxidation (LPO) and Condition Index (CI)

along with the determination of PAHs and metals (Cd, Cu, Ni, Pb and Zn). Results show that despite

the levels of both organic and metallic contaminants in these eight spots in the South Coast of Portugal

not being particularly high compared with other contaminated/polluted sites worldwide, the selected

battery of biomarkers responded efficiently to the environmental changes and allowed an

environmental assessment between seasons and sites. Different spatial and seasonal responses were

evident along the South Coast of Portugal, meaning that the contamination is not homogeneous. This

does not only reflect different competition, origin and intensity of contamination, but also different

environmental conditions (e.g. temperature, salinity). Along the South Portuguese Coast site 8 was the

most contaminated, while site 2 was considered the least contaminated. Despite environmental factors

possibly causing difficulties in the general interpretation of biomarker data, those that better responded

to environmental contamination were CYP450, SOD-mit and T-GPx for theP

PAHs, MT (digestive

gland) for metals (especially Cu), ALAD for Pb and LPO for both organic and metallic contamination.

These biomarkers were also positively correlated with temperature in summer, revealing this as a more

stressful/critical season. In future environmental contamination assessments there is no need to analyse

the components b5, P418, NADH and NADPH of phase I MFO system, and MT in the gills, since their

responses are not evident.

Introduction

Coastal areas including estuaries are usually highly productive.

However, over the years these ecosystems became increasingly

affected by anthropogenic activities, mainly due to urban

development, industrialization and tourism. In those areas,

complex mixtures of contaminants including metallic, organo-

CIMA - Faculty of Marine and Environmental Sciences, University ofAlgarve, Campus de Gambelas, 8005-130 Faro, Portugal. E-mail:mbebian@ualg.pt

Environmental impact

The present paper describes a multibiomarker approach used for the

galloprovincialis to assess the impact of contaminants in this Europe

commonly in ecotoxicology studies, this work integrates a battery

organic) and environmental physico-chemical parameters. This rep

ronment subjected to the impact of mixtures of contaminants and p

that allows pollution effects to be distinguished from those induced

This journal is ª The Royal Society of Chemistry 2009

metallic and persistent organic pollutants (POP; e.g. polycyclic

aromatic hydrocarbons (PAHs), polychlorinated byphenyls

(PCBs), fertilizers and pesticides) from different origins exist.

Due to the ecological relevance of such areas new tools to eval-

uate the environmental quality became necessary.1 Analysing all

the contaminants/pollutants present in the water is virtually

impossible and does not directly reflect the effects upon the biota.

Therefore, measuring the biological effects of pollutants as early

warning signals became increasingly important to assess the

‘‘health status’’ of the environment.2 Bivalve mussels in particular

Mytilus spp. have been widely used in environmental quality

first time in the south coast of Portugal with the mussel Mytilus

an coastal area. Contrary to the single biomarker approach used

of biomarkers to assess the effect of pollutants (metallic and

resents a new tool to evaluate the quality of the coastal envi-

rovides valuable information for environmental risk assessment

by natural factors using the mussels as biological indicators.

J. Environ. Monit., 2009, 11, 1673–1686 | 1673

Fig. 1 Sampling sites along the South coast of Portugal.

Publ

ishe

d on

07

Aug

ust 2

009.

Dow

nloa

ded

by L

omon

osov

Mos

cow

Sta

te U

nive

rsity

on

04/1

2/20

13 2

2:48

:23.

View Article Online

assessment.3,4 These studies enable the evaluation of integrated

biological effects in the environment and usually include the

determination of one or several biomarkers in target species. The

advantages of using biomarkers in the assessment of environ-

mental contamination are also highlighted by van der Oost et al.5

The use of a battery of different biomarkers (a multibiomarker

approach) is essential, particularly in environments where

complex mixtures of contaminants are present, for the assess-

ment of responses that reflect the environmental quality and for

the identification of the sources of contaminants in the envi-

ronment.6,7 Nevertheless, the use of biomarkers does not

completely replace the more common approach of chemical

analysis, but their integration provides a qualitative and/or semi-

quantitative approach to determine the effects and the possible

nature of contaminants. In addition it provides a unique

contribution to determine the synergistic effect of a mixture of

pollutants, even in low amounts.8

Biological responses are also influenced by natural environ-

mental factors. Studies using biomarkers pointed to the need to

incorporate the effects of abiotic (temperature, salinity, diet, etc.)

and biotic factors (reproduction cycle, growth, age, sex, etc.)9–11

to a correct interpretation of biomarker responses.

In the South Coast of Portugal, a highly touristic region, the

population increases markedly during the summer as well as the

volume of sewage discharges and maritime activities. Conse-

quently at some places which are already identified as hotspots of

contamination, complex mixtures exist and are magnified during

this season. In this region, the contaminants known to be present

include metals,12–14 PAHs, PCBs15,16 and organotin compounds

(mainly TBT).17–19 Nevertheless in this coastal area the biological

effects of pollutants in mussels are scarce and only include MT

and GST changes in M. galloprovincialis.12,20 Therefore, in order

to assess if and how mussels M. galloprovincialis are affected by

these contaminants, a multibiomarker approach was carried out

to establish if there are adverse biological responses associated

with different sources of anthropogenic contamination and to

determine spatial and seasonal trends. Moreover, it was also

aimed to discriminate between useful biomarkers and those less

helpful for environmental assessement.

The battery of biomarkers selected was: (i) oxidative stress

biomarkers (antioxidant enzymes – superoxide dismutase (SOD),

catalase (CAT), glutathione peroxidases (GPx total and Se

dependent), (ii) biomarkers of exposure to organic compounds,

including pesticides – Cytochrome P450 component system

including the ‘418-peak’, Cytochrome b5, NAD(P)H cytochrome

c reductase), Glutathione-S-transferase (GST) and acetylcho-

linesterase (AChE); (iii) biomarkers of metal exposure – metal-

lothionein (MT) and lead – d-aminolevulinic acid dehydratase

(ALAD) and (iv) biomarkers of effect – lipid peroxidation

(LPO).

Material and methods

Sampling sites and collection

Eight sites were selected at the South Coast of Portugal (Fig. 1),

and mussels Mytilus galloprovincialis collected at low tide, during

summer (2005) and winter (2006) namely at: 1. (37� 00,5880 N; 8�

55,7770 W), 2. (37� 06,4610 N; 8� 40,2810 W), 3. (37� 08,0870 N;

1674 | J. Environ. Monit., 2009, 11, 1673–1686

008� 32,0890 W), 4. (37� 04,4060 N; 008� 07,2950 W), 5. (37�

00,1660 N; 7� 54,9940 W), 6. (37� 01,3670 N; 7� 50,2120 W), 7. (37�

06,9950 N; 7� 37,7320 W) and 8. (37�10,6780 N0; 007� 24,5080 W).

Sites 1 and 6 are near fishing harbours, and sites 2 and 4 near

recreational marinas, while sites 3, 7 and 8 are close to the mouth

of the major rivers, whereas site 5 is close to a commercial

harbour.

From each sampling site about 100 mussels (5.2 � 0.8 cm shell

length) were collected for both biochemical (biomarker

measurements) and chemical (PAHs and metal) analyses.

Mussels were transported alive (at �4� C) to the laboratory. To

assess the physiological condition of native mussels, 10 animals

per site were randomly collected for condition index determina-

tion. Following dissection, gills (for acetylcholinesterase and

MT) and digestive gland of 40 mussels were immediately frozen

in liquid nitrogen and kept at –80 �C until analyses. The

remaining mussels were maintained at �20 �C for chemical

analyses. Environmental parameters (temperature and salinity)

were also measured at each site.

Condition index (CI)

The condition index (CI) was determined as a percentage of the

ratio between dry weight of the soft tissues and the dry weight of

the shell.

Biochemical analysis

Antioxidant enzymes. Antioxidant enzymatic activities were

determined in the digestive gland, the major site of organic

xenobiotic metabolism. Three pools (5 digestive glands each) of

M. galloprovincialis were used after homogenisation in 20 mM

Tris buffer, pH 7.6, containing 1 mM of EDTA, 0.5 M of sac-

charose, 0.15 M of KCl and 1 mM of DTT. The homogenates

were centrifuged at 500 g for 15 min at 4 �C to precipitate large

particles and recentrifuged at 12 000 g for 45 min at 4 �C to

precipitate the mitochondrial fraction. Gel filtration was used to

eliminate low molecular weight impurities. Hence, all cytosolic

fractions were chromatographed on a Sephadex G-25 column

(PD10, Pharmacia) to remove small weight proteins.

SOD activity (EC 1.15.1.1) was determined in the cytosolic

(SOD-cyt) and mitochondrial (SOD-mit) fractions by measuring

the reduction of cytochrome c by the xanthine oxidase/hypo-

xanthine system at 550 nm.21 One unit of SOD is defined as the

This journal is ª The Royal Society of Chemistry 2009

Publ

ishe

d on

07

Aug

ust 2

009.

Dow

nloa

ded

by L

omon

osov

Mos

cow

Sta

te U

nive

rsity

on

04/1

2/20

13 2

2:48

:23.

View Article Online

amount of enzyme that inhibits the reduction of cytochrome c by

50%. SOD activity was expressed in U mg�1 total protein

concentrations. CAT activity (EC 1.11.1.6) was determined

according to Greenwald22 by the decrease in absorbance at

240 nm due to H2O2 consumption. CAT activity was expressed

as mmol min�1 mg�1 of total protein concentrations. GPx activ-

ities were measured following NADPH oxidation at 340 nm in

the presence of excess glutathione reductase, reduced glutathione

and corresponding peroxide.23 The Se-GPx (EC 1.11.1.9) and

Total GPx activities were measured by using H2O2 and cumene

hydroperoxide as substrates, respectively. GPx activities are

expressed as mmol min�1 mg�1 of total protein concentrations.

CYP450 and GST enzymes

Like for the antioxidant enzymes, for the analysis of CYP450,

‘‘418 peak’’, b5, NADPH, NADH and GST, 3 pools (5 digestive

glands each) of mussels were used. Cytosolic and microsomal

fractions were prepared at 4 �C by differential centrifugation as

described by Livingstone.24 Samples were homogenized in 1 : 3.5

(tissue weight : buffer volume) ratio, at 4 �C with 10 mM Tris–

HCl pH 7.6, containing 1 mM dithiothreitol, 0.15 M KCl and 0.5

M sucrose using an ultra-Turrax homogenizer. Following

centrifugations of 500 g for 15 min, 10 000 g for 30 min and

100 000 g for 90 min, the resulting microsomal pellet was

resuspended in 10 mM Tris–HCl, pH 7.6, containing 20% (w/v)

glycerol to give a protein concentration of approximately

10 mg mL�1. Biochemical measurements were carried out on

microsomal samples either immediately (reductase activities), or

after overnight storage at �80 �C (CYP450, putative denatured

CYP450, cytochrome b5). The cytosolic fraction (GST) was also

stored at �80 �C until analyses.

CYP450 and reductase activities were assayed as described in

Livingstone and Farrar.25 Cytochrome P450 concentration and

‘‘418 peak’’ was measured by the carbon monoxide difference

spectrum of sodium dithionite reduced samples using an extinc-

tion coefficient of 91 mM�1 cm�1 (450–490 nm)26 as follows: 1 mL

100 mM Tris–HCl pH 7.6, 900 mL water and 100 mL of the

mussels digestive gland microsomes were mixed and divided into

two semi-micro cells. CO was bubbled (with a flow of 70 bubbles

per minute) in the cell containing the sample and the baseline

recorded. A few grains of sodium dithionite were added to both

cells and the cytochrome P450 content was measured. CYP450

concentration was expressed in pmol mg�1 proteins. Total ‘‘418

peak’’ was calculated in arbitrary units as described in Living-

stone,24 i.e. peak height (lmax – 490 nm) � 1000 mg�1. Total

cytochrome b5 was similarly analysed by difference spectroscopy

using 50 mL of microsomal sample, 30 mM NADH and an

extinction coefficient of 185 mM �1 cm �1 (426–409 nm). For the

difference spectra, each sample was scanned from 3 to 4 times,

and mean values were calculated from replicate spectra.

NADPH-dependent cytochrome c and NADH-dependent cyto-

chrome b5 reductase activities were measured, by the increase in

absorbance at 550 nm (3 ¼ 19.6 mM�1 cm�1). Final assay

conditions in a final volume of 1 mL were: 50 mM Tris–HCl pH

7.6, 1 mM KCN, 0.30 mM NADPH (or NADH), and 0.60 mM

cytochrome c. Sample volumes were: 50 mL of microsomes for

NADPH and 10 mL for NADH dependent reductases.

This journal is ª The Royal Society of Chemistry 2009

Microsomal protein concentration was determined by the

Lowry method using bovine serum albumin as standard.27

Protein yield of the microsomal fraction was measured and

expressed as protein content per gram of weight of fresh digestive

gland tissue.

Glutathione-S-transferase activity was measured spectropho-

tometrically in the cytosolic fraction of the 100 000 g centrifuge,

using 1-chloro 2,4 dinitrobenzene (CDNB) and reduced gluta-

thione (GSH) as co-substrate, according to the method of Habig

et al.28 Specific activity was expressed as nmol min�1 mg�1

protein, using a molar extinction coefficient of 49.6 mM�1 cm�1.

Acetylcolinesterase (AChE)

The activity of AChE was assayed in the gills of the mussels.

Measurements of AChE activity were performed using the col-

orometric method of Ellman.29 The absorbance at 405 nm was

recorded for samples and blanks. AChE activity was expressed in

nmol min�1 mg�1 protein using a molar extinction coefficient of

13.6 mM�1 cm�1.

Metallothionein and ALAD

Metallothionein concentrations were determined in the gills and

digestive gland of M. galloprovincialis. Three replicates of tissues

were weighed and homogenized in 3 volumes of 20 mM Tris-HCl

(pH 8.6) in an ice bath (4 �C). Subsamples of the total homog-

enate were used for wet/dry weight ratio determination and metal

analysis. A further aliquot of the homogenate (3 mL) was

centrifuged (30 000g for 1 h at 4 �C) to separate the soluble and

insoluble compounds. Two aliquots of the supernatant were

further collected to be used in LPO and protein determinations.

The supernatant was then heat treated at 80 �C and centrifuged

(30 000g for 1 h at 4 �C) to precipitate the denatured proteins.

Aliquots (50–250 mL) of the heat treated cytosol were used to

quantify MT concentrations by differential pulse polarography,

according to the method described by Bebianno and Langston.30

The standard addition method used for calibration of MT

concentrations was rabbit liver MT (MT-I from Sigma) (working

standard 10 mg L�1 in distilled water). MT concentrations in the

tissues of mussels were expressed as mg g�1 protein.

d-Aminolevulinic acid dehydratase activity (ALAD -

E.C.4.2.1.24) was determined according to the European stan-

dardized method for determination of d-ALAD activity in the

blood.31 The whole soft tissues of mussels were homogenized

with 0.1 M phosphate buffer (pH 6.6). The homogenates were

centrifuged at 10 000 g for 15 minutes at 4 �C. The resulting

supernatants were then separated in 5 aliquots of 50 ml each and

200 mL of phosphate buffer was added to 2 aliquots and 200 mL

of ALA-reagent (d-aminolevulinic acid) was added to the others.

The mixture was incubated for 2 hours at room temperature and

afterwards 750 mL of the precipitation reagent (containing tri-

chloroacetic acid) was added, mixed for 30 minutes and then

centrifuged at 2500 g for 5 minutes. 500 mL of the resulting

supernatant was transferred to a plastic cell (1 mL) mixed with

500 mL of the Ehrlich chromogenic reagent (dimethylamino-

benzaldehyde) and incubated for 15 minutes at 25 �C. The UV

absorbance of the amount of porphobilinogen (PBG) was

determined in the bivalve samples and blanks at 550 nm. The

J. Environ. Monit., 2009, 11, 1673–1686 | 1675

Table 1 Certified metal concentrations and analysed concentrationsexpressed by mean � 95% confidence limits and mean � standard devi-

�1

Publ

ishe

d on

07

Aug

ust 2

009.

Dow

nloa

ded

by L

omon

osov

Mos

cow

Sta

te U

nive

rsity

on

04/1

2/20

13 2

2:48

:23.

View Article Online

activity of ALAD was expressed in ng PBG min�1 mg�1 total

protein.

ation, respectively in TORT-2 reference materials (RM) (mg g dw)

Metal Certified Analysed

Cadmium 26.7 � 0.6 25.3 � 1.1Copper 106 � 10 106.5 � 1.8Chromium 0.77 � 0.15 0.80 � 0.21Lead 0.35 � 0.13 0.30 � 0.02Nickel 2.50 � 0.19 2.32 � 0.12Zinc 180 � 6 186 � 3.1

Lipid peroxidation

Lipid peroxidation was determined in the same homogenate as

MT in the digestive gland. The method, described by Erdelmeier

et al.,32 measures the amount of malondialdehyde (MDA) and 4-

hydroxyalkenals (4-HNE) produced in the peroxidation of

membrane lipids. LPO was expressed as nmol MDA + 4-HNE

g�1 protein.

Total protein concentrations

Total protein concentrations were determined by the method of

Lowry.27 The quantification was performed using bovine serum

albumin as standard. Protein concentrations are expressed as mg

mL�1.

PAHs analysis

PAHs were determined in the whole soft tissues of M. gallopro-

vincialis. Pools of mussels (n ¼ 5) were homogenised with

Na2SO4 and Soxhlet extracted with n-hexane/dichloromethane

(4 : 1) for 24 h, which was further separated by liquid chroma-

tography (silica–alumina). The PAH containing fraction was

eluted with n-hexane : dichloromethane, as described else-

where.33 Individual PAHs (ng g�1 dw) were identified and

quantified by HPLC-UV, by comparison of retention times and

library spectra of reference compounds. A standard mixture

containing 16 individual PAHs, (EPA 610 PAH Mix, Sigma)

namely naphthalene, acenaphthylene, acenaphthene, fluorene,

phenanthrene, anthracene, fluoranthene, pyrene, benzo(a)an-

thracene, chrysene, benzo(b)fluoranthene, benzo(k)fluoranthene,

benzo(a)pyrene, dibenzo(a,h)anthracene, benzo(g,h,i)perylene

and indeno-(1,2,3-cd) pyrene was used. Detection limit ranged

from 0.01 to 0.24 ng g�1 dw, for individual PAHs. PAH

measurements were validated using a standard reference material

of mussel tissue (SRM 2977; NIST, USA), that was extracted and

analyzed as the samples. PAH recoveries from the analyses of

certified material ranged between 73% and 112%. Blanks were

performed extracting an amount of sodium sulfate equivalent to

that used with the samples. Hydrocarbons were not detected in

the blanks.

Table 2 Temperature (�C) and salinity (PSU) from the sites in the SouthCoast of Portugal

Sites

Temperature (�C) Salinity (PSU)

Summer Winter Summer Winter

1 18.8 14.4 36.0 35.32 19.0 14.3 36.9 33.73 19.5 13.7 36.0 26.34 19.3 15.3 34.0 335 19.6 14.4 36.5 35.36 21.5 15.5 36.3 35.77 20.0 14.8 36.0 30.68 20.0 13.7 32.9 30.1

Metals

Metals (Cd, Cu, Ni, Pb and Zn) were analysed in the whole soft

tissues of M. galloprovincialis on dried subsamples by atomic

absorption spectrophotometry (SpectrA-A10/20; Varian,

Oxford, UK) after wet digestion with nitric acid. The accuracy of

the analytical procedure was checked using certified reference

material (TORT-2) from the National Research Council (Can-

ada). The results were in good agreement with the certified values

(Table 1). Metal levels were expressed as mg g�1 dry weight of soft

tissue.

1676 | J. Environ. Monit., 2009, 11, 1673–1686

Statistical analysis

Results are expressed as means � standard deviation (SD). The

data were tested for normality and homogeneity and analyzed by

analysis of variance (ANOVA). Duncan test was used to deter-

mine significant differences between variables. Pearson’s corre-

lation analysis was also applied between all the biomarkers and

between biomarkers and contaminants. Principal component

analysis (PCA – ordination method) was used to discriminate the

main variables responsible for the variance of biomarkers and

environmental factors. Canonical Correspondence Analysis

(CCA) was used to assess the influence of biomarkers associated

with the contaminants on the different sites. Statistical analysis

was carried out with Statistica 5.1 and CANOCO 4.5 package. A

minimum significance level of 0.05 was used for all statistical

analysis, i.e. a probability of p # 0.05 was considered significant.

Results

Environmental factors

Temperature and salinity data from each site are shown in Table 2.

Temperature in summer increased eastward, i.e., 18.8 �C (site 1) to

21.5 �C (site 6). In winter, the range was smaller, from 13.7 �C

(sites 3 and 8) to 15.5 �C (site 6) and lower than in summer (p <

0.05). Salinity ranged from 32.9 (site 8) to 36.9 (site 2) in summer

and was significantly higher than in winter (ranged from 26.3 (site

3) to 35.7 (site 6); p < 0.05). The lowest salinity was measured at the

sites close to the mouth of the rivers (sites 3, 7 and 8).

Condition index

No significant differences between the two seasons were observed

in the condition index of the mussels (8.8%� 2.5 and 9.0%� 2.1,

This journal is ª The Royal Society of Chemistry 2009

Publ

ishe

d on

07

Aug

ust 2

009.

Dow

nloa

ded

by L

omon

osov

Mos

cow

Sta

te U

nive

rsity

on

04/1

2/20

13 2

2:48

:23.

View Article Online

respectively; p > 0.05), with the exception of sites 2, 7 and 8. The

lowest values, that indicate poor physiological condition were at

sites 8 (4.8%) and 1 (6.5%) in summer and 2 (7.2% in winter). The

highest CI was at sites 2 (14.6% in the summer) and 7 (12.1% in

winter).

Biomarker levels

The biomarkers analysed in the digestive gland of M. gallopro-

vincialis are shown in Figs. 2–7. The antioxidant enzymes activity

(SOD, CAT, GPx) are shown in Fig. 2. Each of the antioxidant

Fig. 2 Cytosolic (A) and mitochondrial SOD (B), CAT (C), total (D) and Se-

M. galloprovincialis collected in South coast of Portugal. Different letters me

CAT in mmol/min/mg prot, Total and Se- dependent GPx in nmol/min/mg p

This journal is ª The Royal Society of Chemistry 2009

enzymes responded distinctively. The variation pattern of SOD-

cyt was more similar to that of CAT and Se-GPx than to the

SOD-mit.

SOD activity in the cytosolic fraction (SOD-cyt; Fig. 2A) was

higher than in the mitochondrial fraction (SOD-mit; Fig. 2B);

(pv< 0.05). The variation of SOD-cyt activity (Fig. 2A) was

similar between surveys except at sites 1 and 2. SOD-cyt activities

were significantly higher and similar at sites 1 and 6 (summer)

and 3 (winter) while a minimum was observed at site 4 for both

seasons. SOD-mit activity (Fig. 2B), showed a different pattern

with almost 2-fold higher activity in the summer (p < 0.05), than

dependent GPx (E) activities (mean� sd) in the digestive gland of mussels

an significant differences. Activities of SOD are expressed in U/mg prot,

rot.

J. Environ. Monit., 2009, 11, 1673–1686 | 1677

Fig. 3 CYP450 concentration (A), ‘‘peak 418’’ (B), b5 (C), NADPH (D) and NADH (E) activities (mean � sd) in the digestive gland of mussels M.

galloprovincialis collected in South coast of Portugal. Different letters mean significant differences. CYP450 is expressed in pmol/mg prot, ‘‘peak 418’’ in

arbitrary units, b5 in pmol/mg prot and NADP(H) in nmol/min/mg prot.

Publ

ishe

d on

07

Aug

ust 2

009.

Dow

nloa

ded

by L

omon

osov

Mos

cow

Sta

te U

nive

rsity

on

04/1

2/20

13 2

2:48

:23.

View Article Online

in winter (<3.5 U mg�1 prot). The maximum SOD-mit activity

was at site 6 (summer) and minimum at sites 4 and 8 in winter.

The highest CAT activity (Fig. 2C) was at sites 1 and 3 (62 and

58 mmol min�1 mg�1 prot in summer and winter, respectively).

Like for SOD-cyt, CAT activity was similar between surveys at

sites 2, 4, 6 and 7, (p > 0.05).

With respect to T-GPx and Se-dependent GPx activities

(Fig. 2D and E), both were of the same order of magnitude

despite slightly higher for T-GPx but showed a distinct pattern.

The maximum activity of T-GPx was at site 3 (9 nmol min�1 mg�1

prot in winter) but lower and similar at the other sites in both

seasons (# 5.5 nmol min�1 mg�1 prot) (Fig. 3D). Se-GPx the

1678 | J. Environ. Monit., 2009, 11, 1673–1686

highest activities (5–6 nmol min�1 mg�1 prot) were measured at

sites 1, 7 (summer) and 3 (winter), and minimum at site 4 (p <

0.05).

The activity of the phase I enzymes (CYP450 and the related

components ‘‘418 peak’’, cytochrome b5, NADPH cytochrome c

reductase and NADH-cyt b5) and of phase II GST in the

digestive gland of mussels M. galloprovincialis are shown in Fig. 3

and 4, respectively. In general, all biomarkers associated with

phase I (Fig. 3) showed a similar trend, higher in summer than in

winter. Levels generally increased from sites 1 to 6, decreasing

progressively at sites 7 and 8. The CYP450 activity (Fig. 3A) was

highest at site 6 (62 pmol mg�1 prot in summer), followed by 3, 4

This journal is ª The Royal Society of Chemistry 2009

Fig. 4 GST activity (mean � sd) in the digestive gland of mussels M.

galloprovincialis collected in South coast of Portugal. Different letters

mean significant differences. GST is expressed in nmol/min/mg prot.

Fig. 5 AChE activity (mean � sd) in the gills of mussels M. gallopro-

vincialis collected in South coast of Portugal. Different letters mean

significant differences. AChE is expressed in nmol/min/mg prot.

Publ

ishe

d on

07

Aug

ust 2

009.

Dow

nloa

ded

by L

omon

osov

Mos

cow

Sta

te U

nive

rsity

on

04/1

2/20

13 2

2:48

:23.

View Article Online

and 2 (p < 0.05). The ‘418- peak’ (Fig. 3B) as representative of

putative denatured cytochrome P450, followed a similar trend

(Fig. 3A), with the highest value at site 6 (9.5 a.u; p < 0.05).

Cytochrome b5 activity (Fig. 3C), as CYP450 (Fig. 3A) was also

highest at site 6, although in summer the values were similar at all

sites (p > 0.05). In winter cytochrome b5 activity decreased

drastically, with the maximum at sites 3 and 8 (�14 pmol mg�1

prot; p < 0.05). NADPH cytochrome c reductase activity

(Fig. 3D) like CYP450, ‘‘418 peak’’ and cytochrome b5 (Fig. 3A,

B, C) was also significantly higher at site 6 (14 nmol min�1 mg�1

prot, p < 0.05) in summer. Only at site 8 could no significant

difference between sites be detected. NADH-cyt b5 reductase

activity (Fig. 3E), was also significantly higher at site 6 (85 nmol

min�1 mg�1 prot in summer; p < 0.05), 4- to 6- fold higher than

NADPH-cyt c reductase (Fig. 3D) and like for NADPH cyt c

reductase activity levels were similar at site 8 between surveys.

GST (Fig. 4), however, showed a different spatial and seasonal

pattern of phase I enzymes, but followed that of SOD-cyt

(Fig. 2A), with a maximum at sites 2 (13.5 nmol min�1 mg�1 prot

in summer) and 3 (10.8 nmol min�1 mg�1 prot in winter). In

winter, the GST activity decreased reaching a minimum at site 4

(6.5 nmol min�1 mg�1 prot, p < 0.05).

The AChE activity in the gills of the M. galloprovincialis is

shown in Fig. 5. For this biomarker, although levels were in

general lower in summer than in winter, no seasonal variation

This journal is ª The Royal Society of Chemistry 2009

was observed between sites (except for site 3 and 7). Interestingly,

at site 5, AChE activity was lower than anywhere else and similar

to that of site 7 in the winter (5.5–6.0 nmol min�1 mg�1 prot),

suggesting an inhibition of this biomarker at these two sites.

MT concentrations in the gills and digestive gland of M. gal-

loprovincialis are shown in Fig. 6A, B, respectively. As expected,

MT levels were higher in the digestive gland than in the gills and

both tissues showed a distinct spatial and seasonal variation. MT

concentrations in the gills (Fig. 6A) were significantly higher in

summer than in winter, at sites 3, 4 and 8 (p < 0.05), while the

opposite occurs at sites 5 and 7. The highest concentration was in

winter at site 7 (�12 mg g�1 prot). Like for the gills, MT levels in

the digestive gland were 2-fold higher (10–18 mg g�1 prot; p <

0.05) in summer than in winter (Fig. 6B), particularly at site 4.

Only at sites 7 and 8 no significant differences of MT exist

between seasons (p > 0.05), with the minimum at site 8 (5 mg g�1

prot in winter). In winter the highest concentration was at site 7

(11 mg g�1 prot).

The ALAD activity in the whole soft tissues of M. gallopro-

vincialis is present in Fig. 6C. For this biomarker a marked

seasonal pattern exists. ALAD activity was significantly lower in

summer than in winter (p < 0.05) at all sites and varied in summer

within a narrow range (�0.1–0.3 ng PBG min�1mg�1 prot; p >

0.05). The minimum was at sites 3 and 4, which reveals that this

biomarker is particularly inhibited at these sites. In winter, ALAD

significantly increased particularly at sites 1 and 2 (�1.6 ng PBG

min�1mg�1 prot; p < 0.05). In general, ALAD activity showed an

opposite variation of that of MT in the digestive gland (Fig. 6A).

LPO concentrations in the digestive gland of M. gallopro-

vincialis are shown in Fig. 7. This biomarker also showed

a significant seasonal variation with levels significantly higher in

summer than in winter for all sites, with a maximum at site 8

(�13.5 mmol g�1 prot; p < 0.05). In winter, LPO levels were

similar at all the sites (�1 mmol g�1 prot; p > 0.05).

Influence of biotic and abiotic factors on biomarkers

The condition index varies with the reproductive cycle and the

food availability, but also with environmental factors. Despite

being similar between sites and seasons, a significant negative

relationship exists between CI and LPO (r ¼ �0.566; p < 0.05).

In order to minimize the influence of physiological conditions

upon biomarker levels, when the data matrix is normalised by the

condition index, GST was positively correlated with phase I

biomarkers (except the ‘‘418 peak’’), SOD (cyt and mit), CAT

and LPO (r > 0.580; p < 0.05).

The influence of abiotic parameters temperature and salinity

on biomarkers was also studied. Phase I (CYP450 and related

components) and Phase II (GST) enzymes, SOD-mit, MT in the

digestive gland and LPO increased when temperature increases (r

> 0.680; p < 0.05) while ALAD activity decreases (r ¼ �0.720; p

< 0.05). SOD-mit activity was also positively related to salinity

while T-GPx activity was inversely related (r¼�0.640; p < 0.05).

A PCA was applied to all biomarker data along with the

environmental variables (temperature and salinity) and CI of

mussels (Fig. 8). Biomarkers show a clear seasonal behaviour in

most of the sites (except sites 3 and 5) reflecting the seasonal

environmental changes associated with the bioavailability of

contaminants and abiotic factors.

J. Environ. Monit., 2009, 11, 1673–1686 | 1679

Fig. 6 MT concentrations (mean � sd) in the gills (A and digestive gland (B) and ALAD activity in the whole soft tissues (C) of M. galloprovincialis

collected in South coast of Portugal. Different letters mean significant differences. MT is expressed in mg/g prot and ALAD in ng/PBG/min/mg prot.

Fig. 7 LPO activity (mean � sd) in the digestive gland of mussels M.

galloprovincialis collected in South coast of Portugal. Different letters

mean significant differences. LPO is expressed in MDA + 4-HNE mmol/g

prot.

Publ

ishe

d on

07

Aug

ust 2

009.

Dow

nloa

ded

by L

omon

osov

Mos

cow

Sta

te U

nive

rsity

on

04/1

2/20

13 2

2:48

:23.

View Article Online

In Fig. 8, PC1 (explaining 55% of the variance) shows that the

most evident biomarker response was in summer, for CYP450,

SOD-mit, MT in the digestive gland and LPO associated with

1680 | J. Environ. Monit., 2009, 11, 1673–1686

highest temperature and salinity values (and condition index)

against ALAD. During winter, ALAD activity shows greater

response than in the summer, indicating that this biomarker

during summer was more inhibited. Moreover, sites in PCA are

closer in the winter period than in summer. PC2 (that explains

26% of the variance), shows an increase of antioxidant enzymes

activities SOD-cyt, CAT, T- and Se-GPx together with GST,

AChE and MT in the gills against MT in the digestive gland.

Contaminant levels

Since in summer there was an evident seasonal influence on the

biomarker levels with a general increase of SOD-mit, CYP450,

MT in the digestive gland and LPO along with an evident

decrease of ALAD, analyses of contaminants were carried out on

the same samples to help to interpret the biomarker results.

PAHs and metals (Cu, Cd, Cr, Ni, Pb and Zn) were analysed in

the whole soft tissues of M. galloprovincialis (Tables 3 and 4,

respectively).

Total PAHs concentrations (Table 3), showed an increasing

gradient from site 1 (<60 ng g�1) to 6 (�900 ng g�1; p > 0.05), as

occurred for the MFO system and SOD-mit. For the 16

This journal is ª The Royal Society of Chemistry 2009

Fig. 8 PCA of the biomarkers battery in mussels Mytilus gallopro-

vincialis for both summer and winter surveys showing the data scores

labeled as sites, temperature, salinity and condition index.

Publ

ishe

d on

07

Aug

ust 2

009.

Dow

nloa

ded

by L

omon

osov

Mos

cow

Sta

te U

nive

rsity

on

04/1

2/20

13 2

2:48

:23.

View Article Online

individual PAH concentrations, 2 + 3 rings were predominant

(>79%) at sites 4, 5, 6 and 8, while 4 ring PAHs (64–80%) were at

the other sites. Five ring PAHs, which are usually more toxic,

were only detected at site 8 (2%). The Phenanthrene/Anthracene

Table 3 PAHs concentrations (ng g�1 dw) in the soft tissues of mussels Myt

PAH compound

Sites

1 2 3 4

Naphthalene nd nd nd 323Acenaphthylene nd nd nd ndAcenaphthene nd nd nd 106Fluorene 11.3 � 2.0 6.1 � 1.5 6.3 � 1.9 6.8Phenanthrene 10.1 � 0.8 14.4 � 3.9 6.7 � 0.6 20.3Anthracene 0.63 � 0.05 0.94 � 0.36 2.6 � 0.03 0.65Fluoranthene 7.2 � 1.4 1.4 � 0.27 28.7 � 4.0 9.0Pyrene 2.5 � 0.03 7.7 � 0.17 15.1 � 2.9 10.1Benzo(a)anthracene 37.6 � 7.1 26.5 � 6.7 15.8 � 3.3 29.3Chrysene 5.3 � 1.2 2.9 � 0.01 3.6 � 0.08 5.5Benzo(b)fluoranthene nd nd nd ndBenzo(k)fluoranthene nd nd nd ndBenzo(a)pyrene nd nd nd ndDibenzo(a,h)anthracene nd nd nd ndBenzo(g,h,i)perylene nd nd nd ndIndeno-(1,2,3-cd)pyrene nd nd nd ndSPAH 74.7 � 1.8 (b) 59.9 � 2.1 (b) 78.8 � 2.1 (b) 511P/A 15.9 15.4 2.6 31.3F/P 2.9 0.2 1.9 0.9BaA/Chrys 7.1 9.2 4.3 5.32 + 3 rings (%) 29.5 35.8 19.8 89.44 rings (%) 70.5 64.2 80.2 10.65 + 6 rings (%)

a nd – not detected; () – Different letters mean significant differences.

This journal is ª The Royal Society of Chemistry 2009

(Phen/Ant) and Fluoranthene/Pyrene (F/P) ratios, used to iden-

tify the origin of PAHs, showed that PAH sources are different

along the South Coast of Portugal (Table 3). PAHs have a pet-

rogenic origin (fuel), (Phen/Ant ratio > 10 and F/P ratio # 1) at

sites 2, 4 and 8. At site 3, the origin is pyrogenic (pyrolysis) (Phen/

Ant and F/P ratios < 10 e > 1, respectively) while at sites 1, 6 and

7 the origin is both petrogenic and pyrolitic.

Concerning metal levels accumulated in the mussel tissues

(Table 4), different gradients were found. Cd, Ni and Pb levels

increased from site 4 to 8, as for the antioxidant enzymes SOD-

cyt, CAT and Se-GPx (Figs. 2A, C and E, respectively). Copper

showed a different pattern, increasing from site 1 to 3, where the

maximum occurred, and then decreased progressively from site 4

to 8. Cr and Zn were similar between sites (p > 0.05). Zn

concentrations were, like for Cd, maximum at site 8 (�380 mg

g�1) and similar between sites 7, 5, 3 and 1 (p > 0.05). Further-

more, a direct significant relationship exists between Cd and Zn

(r¼ 0.88, p < 0.01), Ni and Pb (r¼ 0.80, p < 0.05) and Zn and Ni

(r ¼ 0.74, p < 0.05) while Pb was only positively related with $ 5

ring PAHs (p < 0.01).

Considering the effect of abiotic parameters (temperature,

salinity) and CI with contaminants, it is observed that total PAH

concentrations were directly related with temperature, Cd was

inversely related with CI while LPO was negatively associated

with salinity. Total PAH concentrations were maximum at the

sites where temperature was highest (i.e. at site 6) and Cd was

maximum where CI was minimum (i.e. at site 8).

Relation between biomarkers and contaminant levels

CCA was applied to biomarkers, contaminants, condition index

and environmental factors, to provide insight into the factors

that explain the variance of biomarkers in the summer (Fig. 9). In

ilus galloprovincialis at the eight sites in summer 2005a

5 6 7 8

� 92 nd nd nd ndnd nd nd nd

� 8 128 � 44 735 � 129 nd 157 � 11� 1.3 6.6 � 0.7 31.5 � 3.8 3.4 � 0.2 12.8 � 0.2� 5.4 8.6 � 1.8 19.4 � 2.4 11.0 � 1.0 18.1 � 5.2� 0.17 0.38 � 0.07 0.33 � 0.07 0.90 � 0.16 1.5 � 0.33� 1.5 nd 58.5 � 5.1 3.5 � 0.5 2.6 � 0.03� 0.02 7.3 � 0.32 22.1 � 5.6 1.5 � 0.26 2.6 � 0.21� 7.8 8.6 � 3.0 25.8 � 7.0 21.9 � 2.2 24.6 � 0.13� 0.73 2.8 � 0.59 18.5 � 3.0 7.2 � 0.29 16.8 � 3.6

nd nd nd ndnd nd nd 4.8 � 0.50nd nd nd ndnd nd nd ndnd nd nd ndnd nd nd nd

� 13.9 (a) 162 � 7.2 (b) 911 � 19.5 (a) 49.3 � 0.66 (b) 241 � 2.4 (b)22.6 65.3 12.2 12.50 2.7 2.4 1.03.1 1.4 3.0 1.588.5 86.3 30.9 78.711.5 13.7 69.1 19.4

2.0

J. Environ. Monit., 2009, 11, 1673–1686 | 1681

Table 4 Metal concentrations of Cd, Cu, Cr, Ni, Pb and Zn (mg g�1 dw) in the soft tissues of mussels Mytilus galloprovincialis at the eight sites insummer 2005a

Metal

Sites

1 2 3 4 5 6 7 8

Cd 1.56 � 0.77 (b) 0.37 � 0.15 (c) 0.58 � 0.14 (c) 0.49 � 0.10 (c) 1.22 � 0.54 (bc) 0.46 � 0.05 (c) 1.19 � 0.51 (bc) 2.35 � 0.57 (a)Cu 10.2 � 1.3 (b) 16.8 � 3.9 (ab) 24.9 � 13.0 (a) 16.3 � 4.2 (ab) 12.5 � 7.3 (b) 10.0 � 2.8 (b) 10.9 � 1.7 (b) 11.4 � 0.4 (b)Cr 0.86 � 0.41 (a) 0.80 � 0.58 (a) 0.67 � 0.13 (a) 0.64 � 0.21 (a) 0.50 � 0.12 (a) 0.43 � 0.06 (a) 0.66 � 0.30 (a) 0.85 � 0.26 (a)Ni 0.03 � 0.02 (c) 0.05 � 0.02 (c) 0.26 � 0.07 (a) 0.05 � 0.02 (c) 0.21 � 0.12 (ab) 0.08 � 0.01 (bc) 0.16 � 0.04 (abc) 0.29 � 0.11 (a)Pb 0.66 � 0.17 (bc) 0.40 � 0.27 (c) 6.91 � 4.61 (b) 2.69 � 1.33 (bc) 3.51 � 2.05 (bc) 5.62 � 3.23 (bc) 4.14 � 2.55 (bc) 14.45 � 4.75 (a)Zn 238 � 73 (ab) 143 � 60 (b) 243 � 141 (ab) 181 � 47 (b) 268 � 99 (ab) 111 � 16 (b) 287 � 91 (ab) 380 � 171 (a)

a () – Different letters mean significant differences.

Fig. 9 CCA of the biomarkers battery in the mussels Mytilus galloprovincialis for the summer survey showing the data scores labeled as: (A)

contaminants, temperature (T), salinity (S) and condition Index (CI) and (B) sites.

Publ

ishe

d on

07

Aug

ust 2

009.

Dow

nloa

ded

by L

omon

osov

Mos

cow

Sta

te U

nive

rsity

on

04/1

2/20

13 2

2:48

:23.

View Article Online

Fig. 9A is represented the association of biomarkers responding to

contaminants while at Fig. 9B, the projection of the sites is asso-

ciated with the same contaminant data. The two main axes explain

68% of the total variance, where only PC1 represents 50%.

Axis 1 confirmed that the highest damage expressed by the

increase of LPO was at site 8, associated with the presence of 5–6

PAHs rings (2%), high levels ofP

PAHs (�240 ng g�1 dw) and

the maximum metal concentrations (Table 3 and 4). These metal

concentrations also induce an increase of MT in the gills. At site

6, the increase of CYP450, SOD-mit and T-GPx may be asso-

ciated withP

PAHs whose concentration was the maximum

(�900 ng g�1 dw; Table 3) of the whole South Portuguese Coast

while MT in the digestive gland with Cu.

In axis 2, the increase of SOD-cit, CAT and Se-GPx at sites 1, 2

and 3 responded to the moderate levels of PAHs (50–80 ng g�1

dw) mainly of 4 rings (65–80%) (Table 3). In opposition, the

general inhibition of antioxidant enzymes at site 4 and 5 is mainly

associated to 2 + 3 ring PAHs (�90%) within the range�160–500

ng g�1 dw (Table 3).

Discussion

Mussels are suitable organisms for environmental quality

assessment since they are able to provide cellular and

1682 | J. Environ. Monit., 2009, 11, 1673–1686

physiological responses to contamination.34 M. galloprovincialis

is a very common species along the South Coast of Portugal,

where it is subjected to different contamination loads. In envi-

ronmental risk assessment, the use of a battery of biomarkers is

strongly recommended7,8 because a multibiomarker approach

gives a more comprehensive and integrated view of the biological

responses, even where the levels of contaminants are not

particularly high, like in the South Coast of Portugal.

PAH levels are of the same order of magnitude of those found

previously in the South Coast of Portugal,15,35 in the NW

Portuguese coast,36 but lower than in mussels from areas affected

by oil spills or tanker accidents, such as the Prestige37 and the

Aegean Sea, at La Coru~na38 and the Erika, along the Bay of

Biscay.39 Nevertheless, the highest PAH concentrations are

similar to those in some polluted areas of the NW Mediterra-

nean.40–43 Metal concentrations are similar to those early repor-

ted, for the South Coast of Portugal12,44 and in reference sites in

the Adriatic Sea and Greece coast45,46 but lower when compared

to contaminated coastal areas in the Atlantic and the Mediter-

ranean (such as the Spanish,47 Italian,48 Moroccan49,50 and in the

NW Mediterranean coasts).43

The overall biomarker data along with contaminants and

environmental variables revealed that in the South Coast of

Portugal, biomarkers in M. galloprovincialis varied spatially and

This journal is ª The Royal Society of Chemistry 2009

Ta

ble

5S

pec

ific

act

ivit

ies

of

an

tio

xid

an

ten

zym

es,

LP

Oin

the

dig

esti

ve

gla

nd

an

dA

Ch

Ein

the

gil

lsin

My

tilu

sg

all

op

rovi

nci

ali

s

Sit

esS

OD

(Um

g�

1p

rot)

CA

T(m

mo

lm

in�

1m

g�

1p

rot)

GP

x(n

mo

lm

in�

1m

g�

1

pro

t)

LP

O(m

mo

lg�

1p

rot)

AC

hE

(Gil

ls)

nm

ol/

min

/mg

pro

tR

efer

ence

sT

ota

lG

Px

Se-

GP

x

So

uth

Po

rtu

gu

ese

Co

ast

8.8

–2

4.4

33–6

24

.0–8

.81

.7–5

.91

.1–1

3.4

6–1

2.6

Th

isst

ud

yN

WP

ort

ug

ues

eC

oa

st�

30

–7

0�

15

–50

�7

–3

5�

7–

17

36

Med

itte

ran

ean

–S

pa

in6

–1

32

.5–

42

.7–

3.8

40

5–

17

1.7

–8

6–

94

2E

bro

del

ta–

Sp

ain

12

.63

.43

.35

1B

ale

ari

cIs

lan

ds-

Sp

ain

8.6

–12

.88

0F

ran

ce�

37

�2

04

8V

enic

ela

go

on

,It

aly

39

.8–8

1.3

81

Med

iter

ran

ean

,It

aly

�7

–1

8�

40

–70

�1

0–

20

�3

–1

55

2A

dri

ati

cS

ea�

2.5

–7

�7

–3

2�

5–

18

�2

.5–

10

1–

3(w

ho

lest

)4

62

4.5

–4

0.8

10

–20

54

Fra

nce

,It

aly

,S

pa

in–

Med

iter

ran

ean

28

.6–1

76

0.1

3–2

.14

10

.7–

88

.57

6

BIO

MA

Rcr

uis

es–

Med

iter

ran

ean

10–102

0.6

–4.9

6.5

–28

77

Publ

ishe

d on

07

Aug

ust 2

009.

Dow

nloa

ded

by L

omon

osov

Mos

cow

Sta

te U

nive

rsity

on

04/1

2/20

13 2

2:48

:23.

View Article Online

seasonally depending upon both the origin and the magnitude of

the contaminants present. Considering both summer and winter

periods, PCA analyses demonstrated that the biomarkers

response differs markedly between seasons and was more

important in the summer (Fig. 8). In the winter, the major

biomarker changes were in mussels from site 3, with an increase

of all antioxidant enzymes (except SOD-mit), GST and AChE

(Figs. 2, 4 and 5), which suggests that contamination at this site

was more important in winter. Considering only the summer

data, the response of the biomarkers (Fig. 9A) reflects a rise in

the contamination levels during this period, leading to a clear

separation of sites (Fig. 9B). There was an increase of most of the

biomarkers responses, except for ALAD, which had an opposite

trend. Moreover, the selected battery of biomarkers reflects

different sources of contamination. The CCA analysis (Fig. 9)

discriminate that the principal factor responsible for the primary

biomarkers response, considered as the ‘‘contamination

component’’, depends on the nature and intensity of contami-

nation. At site 6, CYP450, SOD-mit and T-GPx, are responding

to maximumP

PAH concentrations, mainly of 2 + 3 rings and

MT in the digestive gland responds particularly to Cu. At site 8,

LPO responded primarily to high levels of PAH, including those

of high molecular weight, and the highest metal concentrations.

The secondary factor explaining the variability of the biomarkers

data, elected as the ‘‘oxidative stress component’’, was mainly

associated with the antioxidant enzymes Se-GPx and CAT, along

with SOD-cyt, responding to 4-ring PAHs, that caused oxidative

stress at sites 1 to 5. A very important feature related to the use of

a multibiomarker approach in risk assessment is the need for

having a detailed knowledge of basal levels of the biomarkers,

and of its seasonal variation, in order to distinguish pollution

induced effects from those induced by the natural biological cycle

of mussels. From these results, most of the biomarkers at site 2

can be used as baseline levels.

Despite the fact that the activity of antioxidant enzymes in the

mussels from the South Coast of Portugal (Fig. 2) is similar to

those of the same species of mussels from the Mediterranean sea,

farmed in the Ebro Delta,51 Italian,52 French coast53 and in the

Adriatic Sea46,54 (Table 5), spatially, their behaviour was inter-

esting, varying in an inconsistent way. Mussels from site 1

revealed an increase of SOD-mit, SOD-cyt, CAT and Se-GPx,

(Fig. 2 A, C, E) indicating a cascade of antioxidant enzymes

working to counteract the presence of ROS. The levels of anti-

oxidant enzymes at this site are associated with moderate levels

of PAHs (mainly of 4-rings) (Table 3) or other organic

compounds such as lindane, identified in the sediments as one of

the highest concentrations in the South Coast of Portugal.55 At

this site, the presence of PAHs and possibly other organochlorine

compounds were also reflected by the increase of GST activity

(Fig. 4). The levels of Cd (and Zn) are also important (Table 4)

and can be responsible for stimulating the lipid peroxidation56

(Fig. 7). Similarly, the increase of MT levels in the gills (Fig. 6A)

indicates the presence of bioavailable metals at this site, partic-

ularly Cd. This protein can, due to its high cysteine content, also

participate in defence against oxidative stress, not only acting as

oxyradical scavenger but also through metal binding/release

dynamics.57 The increase in the activity of antioxidant enzymes in

sites without significant differences in lipid peroxidation reflect

an adaptation to a chronic exposure to contaminants at this

This journal is ª The Royal Society of Chemistry 2009 J. Environ. Monit., 2009, 11, 1673–1686 | 1683

Publ

ishe

d on

07

Aug

ust 2

009.

Dow

nloa

ded

by L

omon

osov

Mos

cow

Sta

te U

nive

rsity

on

04/1

2/20

13 2

2:48

:23.

View Article Online

site.36,58 Opposed to what occurred at site 1, the inhibition of

most antioxidant enzyme systems (SOD-cyt, CAT and Se-GPx)

at site 4 (Fig. 9) points out the difficulty that mussels have at this

site in defending themselves against oxidative stress. Moreover,

CYP450 and MT were induced in the digestive gland suggesting

the presence of organic compounds and metals that can compete

to inhibit the antioxidant defence systems.

CYP450 followed the trend of variation of the concentration

of SPAH, expressed by a direct relationship between CYP450

and SPAHs, as previously reported and attained values similar

to those previously found in the South Coast of Portugal,15,35 in

the Spanish coast40,59 and in Venice lagoon.60 The highest

CYP450 values were found, like for SOD-myt and SOD-cyt

activities, in mussels from site 6. This suggests an increase of

oxidative stress and subsequent activation of the biotransfor-

mation enzyme GST (Fig. 4) indicating the formation of super-

oxide anion due to the presence of organic compounds. At this

site,P

PAHs were highest (Table 3), pesticides such as feni-

trothion and parathion-methyl were also identified,55 as well as

Cu, Ni and Pb (Table 4) that also induced MT in the digestive

gland. Moreover, at sites 3 (and 7) Se-GPx increases along with

CYP450, which indicates the presence of organic peroxides,

possibly due to the presence of low PAHs levels (Table 3). At site

2, CYP450 was induced along with of GST indicating the pres-

ence of organic pollutants (PAHs and possibly other organic

contaminants). However, the highest SPAHs concentrations

(sites 4 to 6 and 8) were not followed by the highest GST activity

(at sites 2, 3 and 1). The apparent lack of response of GST

activity in M. galloprovincialis to PAHs concentrations was also

found either from natural field conditions61,62 or under experi-

mental exposure.63 The activity of this biomarker in M. gallo-

provincialis was slightly lower than found previously for the same

area15 and other Portuguese regions36 or at the Mediterranean

and Adriatic Sea.46,52,54 Earlier results in the same area also

showed that when PAH concentrations are highest (sites 4 and

5), GST activity was inhibited, particularly at site 4.15 At site 5,

GST activity may be related to the high concentrations of total

PCBs and PAHs in mussels from this site.20

MT responses in mussels were metal specific (see the review of

Amiard et al.64). MT concentrations in the digestive gland of

mussels are �1 order of magnitude lower than those in mussels

from a heavily metal contaminated site in the NW Mediterra-

nean.43 MTs (gills and digestive gland) (Fig. 6A, B) followed the

trend of metals (Table 4). MTs in the gills were particularly related

with Cr concentrations (Fig. 9A), in agreement with Porte et al.65

At site 3, MT levels increased in both tissues (gills and digestive

gland) indicating the presence of metals, particularly Cu and Ni

that were maximum at this site (Table 4). Bivalve gills are the

primary site of metal uptake from the aqueous phase, suggesting

that bioavailable metals are accumulated in the gills via water. In

the digestive gland, MTs were mainly associated with Cu, which

reflects the transport of this metal by the circulatory system from

gills to the internal organs66 associated with food/diet (particulate

phase). MT concentrations in the digestive gland, in summer, were

relatively similar between sites, despite maximum at site 4, where

none of the analysed metals reached the maximum concentration.

One interesting feature is that, except at site 8 where metal levels

were highest, MT was not induced and the general response of this

biomarker reflects the low metal levels.

1684 | J. Environ. Monit., 2009, 11, 1673–1686

ALAD activity, which is a specific biomarker for Pb expo-

sure,67,68 showed a marked seasonal signature. During summer,

ALAD was inhibited at all sites suggesting an increase of Pb

concentration during this season, particularly at sites 3 and 8

(Table 4) probably associated to boat traffic increase, since lea-

ded petrol could still be used in some boat engines. In bivalves,

ALAD data is scarce. Levels were only reported for the clam

Chamelea gallina from the Southern Spanish coast69 and the

freshwater clam Corbicula fluminea along the Guadiana estuary,

within the range found in this study.70 Other ALAD levels in

mussel M. galloprovincialis from site 8 71 are of the same order of

magnitude as the present work and also negatively related to Pb,

which confirms the enzymatic inhibition of ALAD by this metal.

AChE has a fundamental role in the nervous system of both

vertebrates and invertebrates, and is a suitable biomarker to

detect environmental contamination caused by neurotoxic

compounds either organic (organophosphates, carbamates),

metals (Cd, Cu, and Pb)72 or surfactants.73,74 Compounds in

complex mixtures may also inhibit the AChE activity of bivalve

molluscs.75 The activity of this biomarker was similar to that

reported in mussels collected from the French, Italian and

Spanish coasts in the Mediterranean area (Table 5).53,76,77

Nevertheless, it is much higher than those found in species of

mussels at the Adriatic Sea (Table 5).46 AChE levels do not

change noticeably in the South Coast of Portugal between sites,

however lowest levels were found at sites 5 and 7 (Fig. 5), due to

the presence of neurotoxic organic compounds or even metals

(Table 4). Pesticides such as lindane were identified in the sedi-

ments from the Ria Formosa lagoon.55 At site 5 the impact of the

discharges from a small stream in the vicinity of a fruit crop area

can possibly transport neurotoxic compounds including pesti-

cides. Cu, Cd and Pb (Table 4) may in part contribute to the

inhibition of AChE activity. Site 7 is located in the vicinity of

intense agricultural activity where pesticides are used.

Metals are known to produce peroxidation of membrane

lipids.78,79 Lipid peroxidation in mussels from the South Portu-

guese Coast were similar to those found for the same species from

the NW Portuguese coast36 and Balearic Islands80 and relatively

higher than in some Mediterranean areas such as in the French,

Italian and Spanish coasts.76 However, levels were lower than at

the Venice lagoon, considered a highly polluted system81 (Table

5). LPO damage was maximum at site 8, the major estuarine area

in the South Coast of Portugal, where Cd, Ni, Pb and Zn

concentrations were the highest (Table 4). LPO may also be

associated to the exposure of high molecular weight PAHs.82,83

and site 8 was also the only site where 5 + 6 rings PAHs were

detected.

Nevertheless it is important to identify where synergistic,

addition or antagonistic effects exist (including environmental

factors) that might complicate the general interpretation. Abiotic

factors (temperature and salinity) may affect the response of

several biomarkers. Antioxidant enzymes,84 MT85 ALAD, LPO86

and AChE87 are directly affected by temperature variability. The

water temperature in summer (> 18.5 �C) contributes to increase

the environmental stress in M. galloprovincialis, reflected not

only by the variation of biomarker levels but also by a slight

decrease in CI in mussels at the eastern sites (4 to 8). In summer,

the variation of AChE in particular is directly related to

temperature (higher at site 6, while minimum at site 5). In fact,

This journal is ª The Royal Society of Chemistry 2009

Publ

ishe

d on

07

Aug

ust 2

009.

Dow

nloa

ded

by L

omon

osov

Mos

cow

Sta

te U

nive

rsity

on

04/1

2/20

13 2

2:48

:23.

View Article Online

temperature is claimed to be the most important natural factor

affecting AChE activity in mussels.75,88 Moreover, temperature

also increases the toxicity of some metals, namely Cd, leading to

elevated oxidative stress.66,89 This may represent a synergistic

effect between temperature and contaminants, particularly in the

summer at site 8 (one of highest temperature (Table 2) and

maximal metal concentrations (Table 4, including Cd). More-

over, changes in salinity are directly related to the bioavailability

of contaminants, either metals or POPs,90 due to modification of

speciation. This may lead to an increase of bioaccumulation with

decreasing salinity,91 changing the response of some biomarkers.

At site 8 (and 3 to a certain extent), the relatively lower salinity

together with a wider range of salinity variation between surveys

(Table 2), increases the environmental stress of mussels and

subsequently LPO levels (Fig. 7), that are negatively related to

salinity. Some other organic or other emerging contaminants not

analysed here may also affect the biomarker responses.

Conclusions

This is the first multibiomarker approach in the South Coast of

Portugal using M. galloprovincialis, while previous studies based

on few biomarkers provided limited information. Despite the

levels of contaminants in these eight hotspots of contamination

in the South coast of Portugal were not particularly high, the

selected battery of biomarkers responded efficiently to the envi-

ronmental changes and allowed an environmental assessment

between seasons and sites. Different responses in space and time

were evident along the South Coast of Portugal, meaning that the

contamination is not homogeneous, reflecting not only different

competition, origin and intensity of contamination, but also

different environmental conditions. Summer represents the most

stressful/critical situation, due to higher environmental contam-

ination and temperature. Despite environmental factors that

may complicate the general interpretation of biomarkers

response, the most suitable battery of biomarkers are: CYP450,

SOD-mit and T-GPx forP

PAHs concentrations (mainly of low

molecular weight), MT in the digestive gland particularly for Cu,

ALAD for Pb and LPO as a damage biomarker for both metals

and high molecular weight PAHs. Based on the interpretation of

PCA and CCA analysis, for further environmental contamina-

tion assessment studies it is possible to reduce the analytical

effort of some biomarkers, by eliminating the components of

phase I MFO system (b5, P418, NADH and NADPH), and MT

in the gills, since their responses are not so evident.

Acknowledgements

This study was financially supported by the FCT project ref:

POCTI/CTA/48027/2002.

References

1 P. M. Chapman and F. Wang, Environ. Toxicol. Chem., 2001, 20, 3–22.

2 M. P. Cajaraville, M. J. Bebianno, J. Blasco, C. Porte, C. Sarasqueteand A. Viarengo, Sci. Total Environ., 2000, 247, 295–311.

3 C. Nasci, L. Da Ros, N. Nesto, L. Sperni, F. Passarini and B. Pavoni,Mar. Environ. Res., 2000, 50, 425–430.

This journal is ª The Royal Society of Chemistry 2009

4 N. Bodin, T. Burgeot, J. Y. Stanisi�ere, G. Bocquen�e, D. Menard,C. Minier, I. Boutet, A. Amat, Y. Cherel and H. Budzinski, Comp.Biochem. Physiol., Part C: Toxicol. Pharmacol., 2004, 138, 411–427.

5 R. Van der Oost, J. Beyer and N. P. E. Vermeulen, Environ. Toxicol.Pharmacol., 2003, 13, 57–149.

6 A. Viarengo, B. Burlando, A. Giordana, C. Bolognesi andG. P. Gabrielides, Mar. Environ. Res., 2000, 49, 483–486.

7 J. M. Monserrat, P. E. Martınez, L. A. Geracitano, L. L. Amado,C. M. G. Martins, G. Lopes, L. Pinho, I. S. Chaves, M. Ferreira-Cravo, J. Ventura-Lima and A. Bianchini, Comp. Biochem. Physiol.,Part C: Toxicol. Pharmacol., 2007, 146, 221–234.

8 F. Donnini, E. Dinelli, F. Sangiorgi and E. Fabbri, Environ. Int.,2007, 33, 919–928.

9 R. Smolders, L. Bervoets, G. De Boeck and R. Burst, Environ.Toxicol. Chem., 2002, 21, 87–93.

10 D. Schiedek, K. Broeg, J. Bar�sien_e, K. K. Lehtonen, J. Gercken,S. Pfeifer, H. Vuontisj€arvi, P. J. Vuorinen, V. Dedonyte,A. Koehler, L. Balk and R. Schneider, Mar. Pollut. Bull., 2006, 53,387–405.

11 G. Damiens, E. His, M. Gnassia-Barelli, F. Quiniou and M. Rom�eo,Comp. Biochem. Physiol., Part C: Toxicol. Pharmacol., 2004, 138,121–128.

12 M. J. Bebianno and L. M. Machado, Mar. Pollut. Bull., 1997, 34, 666–671.

13 M. J. Bebianno and A. Serafim, Sci. Total Environ., 1998, 214, 123–131.14 M. A. Serafim and M. J. Bebianno, Environ. Toxicol. Chem., 2001, 20,

544–552.15 M. J. Bebianno, B. Lopes, L. Guerra, P. Hoarau and A. M. Ferreira,

Environ. Int., 2007, 33, 550–558.16 L. A. Barreira, S. M. Mudge and M. J. Bebianno, J. Environ. Monit.,

2007, 9, 187–198.17 C. M. Barroso, S. Mendo and M. H. Moreira, Mar. Pollut. Bull.,

2004, 48, 1145–1167.18 M. R. Coelho, M. J. Bebianno and W. J. Langston, Appl. Organomet.

Chem., 2002, 16, 384–8.19 S. Diez, S. Lacorte, P. Viana, D. Barcelo and J. M. Bayona, Environ.

Pollut., 2005, 136, 525–36.20 P. Hoarau, G. Damiens, M. Rom�eo, M. Gnassia-Barelli and

M. J. Bebianno, Comp. Biochem. Physiol., Part C: Toxicol.Pharmacol., 2006, 143, 196–203.

21 J. M. McCord and I. Fridovich, J. Biol. Chem., 1969, 244, 6049–6055.22 R. A. Greenwald, CRC Press, Boca Raton, Florida, 1985, pp. 447.23 R. A. Lawrence and R. F. Burk, Biochem. Biophys. Res. Commun.,

1976, 71, 952–958.24 D. R. Livingstone, Mar. Ecol.: Prog. Ser., 1988, 46, 37–43.25 D. R. Livingstone and S. V. Farrar, Sci. Total Environ., 1984, 39, 209–

235.26 R. W. Estabrook and J. Werringloer, Methods Enzymol., 1978, 52,

212–220.27 O. H. Lowry, N. J. Rosebrough, A. L. Farr and R. J. Randall, J. Biol.

Chem., 1951, 193, 265–275.28 W. H. Habig, M. J. Pabst and W. B. Jakoby, J. Biol. Chem., 1974, 25,

7130–7139.29 G. L. Ellman, K. O. Courtney, V. Anders and R. M. Featherstone,

Biochem. Pharmacol., 1961, 7, 88–95.30 M. J. Bebianno and W. J. Langston, Port. Electrochim Acta, 1989, 7,

511–524.31 A. Berlin and K. N. Schaller, Z. Klin. Chem. Klin. Biochem., 1974, 12,

389–390.32 I. Erdelmeier, D. Gerard-Monnier, J. C. Yadan and J. Acudiere,

Chem. Res. Toxicol., 1998, 11, 1184–1194.33 J. Albaig�es, A. Fadn, M. Soler, A. Gallifa and P. Martin, Mar.

Environ. Res., 1987, 22, 1–18.34 P. S. Lau and H. L. Wong, Mar. Pollut. Bull., 2003, 46, 1563–1572.35 A. Serafim, B. Lopes, R. Company, A. M. Ferreira and

M. J. Bebianno, Mar. Pollut. Bull., 2008, 57, 529–537.36 I. Lima, S. M. Moreira, J. Rend�on-Von Osten, A. M. V. M. Soares

and L. Guilhermino, Chemosphere, 2007, 66, 1230–1242.37 J. A. Soriano, L. Vi~nas, M. A. Franco, J. J. Gonz�alez, L. Ortiz,

J. M. Bayona and J. Albaig�es, Sci. Total Environ., 2006, 370, 80–90.38 C. Porte, X. Biosca, D. Pastor, M. Sol�e and J. Albaig�es, Environ. Sci.

Technol., 2000, 34, 5067–5075.39 J. Tronczynski, C. Miunschy, K. H�eas-Moisan, N. Guiot, I. Truquet,

N. Olivier, S. Men and A. Furaut, Aquat. Living Resour., 2004, 17,243–259.

J. Environ. Monit., 2009, 11, 1673–1686 | 1685

Publ

ishe

d on

07

Aug

ust 2

009.

Dow

nloa

ded

by L

omon

osov

Mos

cow

Sta

te U

nive

rsity

on

04/1

2/20

13 2

2:48

:23.

View Article Online

40 M. Sol�e, C. Porte and J. Albaiges, Sci. Total Environ., 1995, 159, 147–153.

41 C. Porte and J. Albaig�es, Arch. Environ. Contam. Toxicol., 1993, 26,273–281.

42 M. Sol�e, C. Porte and J. Albaig�es, Environ. Toxicol. Chem., 1995, 14,157–164.

43 I. Zorita, I. Apraiz, M. Ortiz-Zarragoitia, A. Orbea, I. Cancio,M. Soto, I. Marig�omez and M. P. Cajaraville, Environ. Pollut.,2007, 148, 236–250.

44 M. E. Morgado and M. J. Bebianno, Cienc. Mar., 2005, 31, 231–241.45 C. Tsangaris, E. Papathanasiou and E. Cotou, Ecotoxicol. Environ.

Saf., 2007, 66, 232–243.46 S. Gorbi, C. V. Lamberti, A. Notti, M. Benedetti, D. Fattorini,

G. Moltedo and F. Regoli, Mar. Environ. Res., 2008, 65, 34–49.47 V. Besada, J. Fumega and A. Vaamonde, Sci. Total Environ., 2002,

288, 239–253.48 C. Locatelli, J. Phys. IV, 2003, 107, 785–788.49 A. Chafik, M. Cheggour, D. Cossa, S. Benbrahim and M. Sifeddine,

Aquat. Living Resour., 2001, 14, 239–249.50 M. Maanan, Environ. Pollut., 2008, 153, 176–183.51 M. Sol�e, C. Porte and J. Albaig�es, Aquat. Toxicol., 1994, 30, 271–

283.52 F. Regoli, Arch. Environ. Contam. Toxicol., 1998, 34, 48–63.53 F. Akcha, C. Izuel, P. Venier, H. Budzinski, T. Burgeot and

J. F. Narbonne, Aquat. Toxicol., 2000, 49, 269–287.54 R. Bocchetti, C. V. Lamberti, B. Pisanelli, E. M. Razzetti, C. Maggi,

B. Catalano, G. Sesta, G. Martuccio, M. Gabellini and F. Regoli,Mar. Environ. Res., 2008, 66, 24–26.

55 J. Villaverde, A. Hildebrandt, E. Martınez, S. Lacorte, E. Morillo,C. Maqueda, P. Viana and D. Barcel�o, Sci. Total Environ., 2008,390, 507–513.

56 F. G�eret, A. Jouan, V. Turpin, M. J. Bebianno and R. P. Cosson,Aquat. Living Resour., 2002, 15, 61–66.

57 W. J. Langston, M. J. Bebianno and G. R. Burt, in Metal Metabolismin Aquatic Environments, ed. W. J. Langston and M. J. Bebianno,Chapman & Hall, London, 1998 ch 8, pp. 219–284.

58 C. C. C. Cheung, G. J. Zheng, A. M. Y. Li, B. J. Richardson andP. K. S. Lam, Aquat. Toxicol., 2001, 52, 189–203.

59 C. Porte, M. Biosca, M. Sole and J. Albaig�es, Environ. Pollut., 2001,112, 261–268.

60 M. Sol�e, C. Nasci and D. R. Livingstone, Biomarkers, 2000, 5, 129–140.

61 D. R. Livingstone, P. Lemaire, A. Matthews, L. D. Peters, C. Porte,P. J. Fitzpatrick, L. Forlin, C. Nasci, V. Fossato, N. Wootton andP. Goldfarb, Mar. Environ. Res., 1995, 39, 235–240.

62 M. Sol�e, C. Porte, X. Biosca, C. L. Mitchelmore, J. K. Chipman,D. R. Livingstone and J Albaig�es, Comp. Biochem. Physiol., 1996,113, 157–265.

63 X. R. Michel, PhD Thesis, University of Bordeaux I, 1993.64 J. C. Amiard, C. Amiard-Triquet, S. Barka, J. Pellerin and

P. S. Rainbow, Aquat. Toxicol., 2006, 76, 160–202.

1686 | J. Environ. Monit., 2009, 11, 1673–1686

65 C. Porte, M. Solea, V. Borghi, M. Martinez, J. Chamorro,A. Torreblanca, M. Ortiz, A. Orbea, M. Soto andM. P. Cajaraville, Biomarkers, 2001, 6, 335–350.

66 A. A. Cherkasov, R. A. Overton, E. P. Sokolov Jr andI. M. Sokolova, J. Exp. Mar. Biol., 2007, 210, 46–55.

67 S. N. Kelada, E. Shelton, R. B. Kaufmann and M. J. Khoury, Am. J.Epidemiol., 2001, 154, 1–13.

68 J. Aisemberg, D. E. Nahabedian, E. A. Wider and N. R. V. Guerrero,Toxicology, 2005, 210, 45–53.

69 J. Kalman, I. Riba, J. Blasco and T. A. DelValls, Mar. Environ. Res.,2008, 66, 38–40.

70 R. Company, A. Serafim, B. Lopes, A. Cravo, T. J. Shepherd,G. Pearson and M. J. Bebianno, Sci. Total Environ., 2008, 405,109–119.

71 R. Company, unpublished work.72 M. G. Lionetto, R. Caricato, M. E. Giordano, M. F. Pascariello,

L. Marinosci and T. Schettino, Mar. Pollut. Bull., 2003, 46, 324–330.73 F. Regoli and G. Principato, Aquat. Toxicol., 1995, 31, 143–164.74 L. Guilhermino, P. Barros, M. C. Silva and A. M. V. M. Soares,

Biomarkers, 1998, 3, 157–63.75 M. Dellali, M. G. Barelli, M. Rom�eo and P. Aissa, Comp. Biochem.

Physiol., Part B: Biochem. Mol. Biol., 2001, 130, 227–235.76 J. F. Narbonne, N. Aarab, C. Cl�erandeau, M. Daub�eze, J. Narbonne,

O. Champeau and P. Garrigues, Biomarkers, 2005, 10, 58–71.77 M. Rom�eo, P. Hoarau, G. Garello, M. Gnassia-Barelli and

J. P. Girard, Environ. Pollut., 2003, 122, 369–378.78 A. Viarengo, Rev. Acq. Sci., 1989, 1, 295–317.79 J. A. Knight and R. P. Voorhees, Ann. Clin. Lab. Sci., 1990, 20, 347–352.80 A. Box, A. Sureda, F. Galgani, A. Pons and S. Deudero, Comp.

Biochem. Physiol, 2007, 146, 531–539.81 D. M. Pampanin, I. Marangon, E. Volpato, G. Campesan and

C. Nasci, Environ. Pollut., 2005, 136, 103–107.82 D. R. Livingstone, P. Lemaire, A. Matthews, L. Peters, D. Bucke and

R. J. Law, Mar. Pollut. Bull., 1993, 26, 602–606.83 C. Cossu, A. Doyotte, M. C. Jacquin, M. Babut, A. Exinger and

P. Vasseur, Ecotoxicol. Environ. Saf., 1997, 38, 122–131.84 M. L. Vidal, A. Bass�eres and J. F. Narbonne, Comp. Biochem.

Physiol., Part A: Mol. Integr. Physiol., 2002, 132, S93–104.85 M. A. Serafim, R. M. Company, M. J. Bebianno and W. J. Langston,

Mar. Environ. Res., 2002, 54, 361–365.86 A. Viarengo, L. Canesi, L. Pertica and D. R Livingstone, Comp.

Biochem. Physiol., 1991, 100, 187–190.87 S. Pfeifer, D. Schiedek and J. Dippner, J. Exp. Mar. Biol. Ecol., 2005,

320, 93–103.88 M. F. Frasco, D. Fournier, F. Carvalho and L. Guilhermino,

Biomarkers, 2005, 10, 360–375.89 F. G�eret, A. Serafim, L. Barreira and M. J. Bebianno, Biomarkers,

2002, 7, 242–256.90 J. J. Johnston and M. D. Corbett, Comp. Biochem. Physiol., Part C:

Comp. Pharmacol., 1985, 80, 145–149.91 P. Bjerregaard and M. H. Depledge, Mar. Biol., 1994, 119, 385–395.

This journal is ª The Royal Society of Chemistry 2009