2705

Environmental Toxicology and Chemistry, Vol. 21, No. 12, pp. 2705–2712, 2002q 2002 SETAC

Printed in the USA0730-7268/02 $9.00 1 .00

GENETIC AND PHYSIOLOGICAL RESPONSES OF FLOUNDER(PLATICHTHYS FLESUS) POPULATIONS TO CHEMICAL

CONTAMINATION IN ESTUARIES

JEAN LAROCHE,*† LOUIS QUINIOU,† GUILLAUME JUHEL,† MICHEL AUFFRET,‡ and DARIO MORAGA‡†Laboratoire Ressources Halieutiques–Poissons Marins, Institut Universitaire Europeen de la Mer, Place Nicolas Copernic,

29280, Plouzane, France‡Unite Mixte de Recherche, Centre National de la Recherche Scientifique, 6539, Institut Universitaire Europeen de la Mer,

Place Nicolas Copernic, 29280, Plouzane, France

(Received 7 December 2001; Accepted 28 May 2002)

Abstract—We sampled and analyzed European flounder (Platichthys flesus) from two highly contaminated estuaries (Seine andLoire, France) and one moderately contaminated estuary (reference site: Ster, France). Significant and convergent modifications ofthe allelic frequencies for the loci phosphoglucomutase (PGM), glucose phosphate isomerase 2 (GPI-2), mannose phosphateisomerase (MPI), and aspartate aminotransferase (AAT-2) were evident for fish in the contaminated sites versus fish from thereference site. Back-calculation from otoliths showed that the average growth rate of fish between the first and the second winterwas greater at the reference site (ø150 mm/year) than at the contaminated sites (ø100 mm/year). Flounder from the reference sitealso had a higher condition factor (somatic wt/(fish length)3) compared to fish from the two contaminated sites. However, theobserved pattern of growth rate and condition factor might be biased by particular environmental conditions other than contaminantsand must be confirmed by more extensive study. Flow cytometry analysis of fish blood revealed a significant difference in thefrequency of abnormal profiles for fish from the Seine (20%) versus from the Ster (3%). We interpret this result as a markedgenotoxic effect of contaminants on fish in the Seine system. Some genotypes, such as PGM 85/85, appeared to be linked to themeasured components of fitness, particularly to DNA integrity. Thus, these genotypes might be considered to be more tolerant topollutants. The frequency of the PGM 85 allele was clearly elevated in flounder from the more contaminated sites, compared toflounder from the reference site.

Keywords—Flounder DNA damage Genetic diversity Contamination

INTRODUCTION

The genetic material of populations can change in responseto exposure to pollutants, either because of direct effects (e.g.,pollutant-induced DNA damage) or indirect effects (e.g., bot-tleneck, genetic drift, selection of tolerant genotypes, and soon) [1,2]. The particular focus of the emerging science ofgenetic ecotoxicology is on impacts of the contaminants at thepopulation level, rather than at the level of the individual.Significant modification of a population’s genetic compositioncan reduce mean fitness, erode evolutionary potential, and con-tribute to the likelihood of local or even global extinction.

Pollutants clearly can exert selective pressures on popu-lations in the field [3–5], with the net result being reductionsin the frequency of sensitive genotypes and relative increasesin the frequency of tolerant genotypes. The tolerant or sensitivecharacteristic observed in field-exposed populations may beevidenced by changes in one or more particular loci, as hasbeen confirmed by laboratory experiments [3–5].

Allelic frequencies for the protein loci that vary in responseto exposure to pollutants can be monitored, and the changesin these frequencies might be used to help characterize changesin water quality. This possibility seems plausible because thefrequency of resistant alleles or genotypes in at least somewide-spread species of freshwater fish has been shown to in-crease in parallel with the degree of contamination, for dif-ferent rivers within the same basin [6,7]. The return of allelic

* To whom correspondence may be addressed(jean.laroche@univ-brest.fr).

frequencies to prestress status also has been shown for a fishpopulation 10 years after interruption of a thermal stressor ina North American river [8].

Genotypic markers other than allozymes also can be usedto detect potentially deleterious changes in a population ex-posed to pollutants. Such markers can include stretches ofDNA that consist of tandem repeats of a simple sequence ofnucleotides (referred to as microsatellites). The identificationof potentially useful genotypic markers also can involve theanalysis of mitochondrial DNA, or use techniques such asDNA analysis by random amplified polymorphic DNA typing[9–12].

In short, the evaluation of damage to DNA, such as single-strand breaks, double-strand breaks, or DNA dimerization, cannow be accomplished by a variety of techniques, such as sin-gle-cell gel electrophoresis assay, agarose gel electrophoresis,and flow cytometry, among others. These methods allow ear-lier and more sensitive analysis of genetic indicators of pol-lution. To the extent that DNA damage can be specificallyassociated with components of fitness, and particularly withproperties such as fecundity, longevity, and growth in inver-tebrates and vertebrates, biomarkers may provide informationon contaminant effect, rather than simply exposure [13–15].

In this work, we examined the genetic material of popu-lations of European flounder (Platichthys flesus) collectedfrom two highly contaminated estuaries in France (Seine andLoire) and from one moderately contaminated estuary (Ster),which was used as a reference site. The purpose of the studywas to understand how pollutant effects might be expressed

2706 Environ. Toxicol. Chem. 21, 2002 J. Laroche et al.

Fig. 1. Sampling locations in two highly contaminated estuaries (Seineand Loire) in France and one reference estuary (Ster).

as disruption at the genomic level. In particular, we sought todetect possible modifications of allelic frequencies in the con-taminated estuaries versus in the reference estuary; to exploreDNA damage (determinated by flow cytometry) and other pos-sible alterations of physiological processes (growth, energystorage, and asymmetry) in flounder from the contaminatedsites; and to investigate the relationship between genotype andthe amount of DNA damage (or other physiological alteration),in an attempt to determine if differences in genetic diversitycould be explained by pollutant-induced selection [16].

MATERIALS AND METHODS

Study sites

Samples were collected in France from two polluted es-tuaries (Seine and Loire) and one estuary used as a reference(Ster) (Fig. 1). The Seine estuary (basin area, 78,000 km2) hasbeen extensively contaminated with polycyclic aromatic hy-drocarbons (PAHs), polychlorinated biphenyls (PCBs), andheavy metals from domestic and industrial effluents. Thesources of the pollutants to the Seine estuary are primarilylarge cities, including Paris, Rouen, and Le Havre, France. Thelevel of contamination of the Seine estuary is similar to thatreported for large estuaries in North America [17]. The levelof heavy metals in the Loire estuary (117,000 km2) is similarto the levels reported for the Seine estuary, but PAH and PCBlevels are lower than those in the Seine estuary, by a factorof two to three [18]. The Ster estuary (basin area, 100 km2)is moderately contaminated; it was selected as the referencesite for this study because it has been subject only to lowlevels of pollution from domestic and agricultural effluents[19].

Sample collection and processing

Flounder in the Seine estuary were collected by a beamtrawl; 32 and 27 fish were collected, respectively, on February17, 2001 (S1), and on April 19, 2001 (S2). We collected 25flounder from Seine Bay on April 12, 2001. Thirty fish werecollected in the Loire estuary by handlines (April 1, 2001) and37 fish were collected from the Ster estuary by gillnets (Jan-uary 19, 2001).

After anesthesizing the fish with methanesulfonate salt(MS-222) (Sigma Chemical, St. Louis, MO, USA), blood wascollected from the caudal peduncle with a syringe containing

the freezing medium [20]; the quantity of medium was equalin volume to the anticipated volume of whole blood to becollected. The blood collected in the syringe was expelledslowly into a cryovial on ice; the cryovial then was placed ondry ice, then frozen in liquid nitrogen. For each fish, we mea-sured total length, total weight, and the weights of variousorgans (e.g., the digestive tract, the liver, and the gonads).Samples of muscle and liver tissues were flash-frozen in liquidnitrogen for genetic analysis, and the otoliths (sagitta) werecollected. All the samples were transported to the laboratoryand stored in an ultracold freezer at 2808C until use.

A condition index was used to monitor potential changesin the energy reserves under chemical stress. The conditionfactor (K) was expressed with the formula

3K 5 S /LW (1)

where SW was somatic weight (total weight of the fish, lessgonad and stomach-content weight, in grams) and L was fishlength (mm). Hepatosomatic index (HSI) was calculated as

HSI 5 (L /S )·100W W (2)

where LW and SW represent, respectively, liver weight andsomatic weight (in grams).

Flow cytometry

Sixty samples of fish blood were analyzed by flow cytom-etry over 1 d. Thirty of these were from fish collected fromthe Ster estuary in January 2001, and 30 were from the Seineestuary (15 fish collected in February 2001 and 15 fish col-lected in July 2001). Before analysis by flow cytometry, theblood samples were thawed rapidly to 48C, then stained withpropidium iodide for 30 to 60 min [20]. To control variationin flow cytometry conditions, we added rainbow trout (On-corhynchus mykiss) blood from a single individual to eachsample as an internal standard before staining. The DNA pro-files from stained erythrocyte nuclei (at least 2 3 104 nucleiper sample) were generated on an Becton Dickinson FAC-SCalibur flow cytometer (Franklin Lakes, NJ, USA). Half-peakcoefficient of variation (CV) was determined for each histo-gram with WinMDI Ver 2.8 software (The Scripps ResearchInstitute, La Jolla, CA, USA). The data were first evaluatedvisually, and samples producing histograms with multiplepeaks or other asymmetries were identified. The final com-parisons were made with CV data only from individuals havingnormal, symmetrical DNA profiles [21]. Our assumption wasthat clastogenic effects of contaminant exposure would resultin higher individual CVs for normal DNA profiles, as has beenreported for turtles [22].

An additional sample of 27 fish was collected on June 15,2001, in the Ster estuary, and analyzed by cytometry. Thepossible day-to-day variation of analysis conditions of the in-strument for this set of samples also was accounted for byusing the rainbow trout blood internal standard.

Otolith measurements

Otoliths were measured in various ways by image pro-cessing (Image Tool Ver 2, University of Texas, Health ScienceCenter, San Antonio, TX, USA). The otoliths of Europeanflounder are relatively easy to analyze. With transmitted light,it is possible to detect a succession of opaque (high growthrate, associated with a higher rate of mineralization duringperiods favorable for growth) and hyaline zones (slowergrowth rate, associated with lower rates of mineralization dur-

Responses of flounder populations to chemical contamination Environ. Toxicol. Chem. 21, 2002 2707

Fig. 2. Heterozygosity (Ho 5 observed, He 5 expected), growth rate(GR), condition factor (K), hepatosomatic index (HSI), and fluctuatingasymmetry (FA) of European flounder from sampling sites (referencesite, Ster; highly contaminated sites are Seine 1, Seine 2, Seine Bay,and Loire estuary) in France. Antilogarithm of the arithmetic meansof the logged data 6 antilogarithm of 95% confidence interval.

ing periods less favorable for growth). For each fish and otolith,three successive radii were measured. These were the maxi-mum radius, or the maximum distance from the nucleus to theotolith periphery (Rm), the distance from the nucleus to thebeginning of the first hyaline zone (R1), and the distance fromthe nucleus to the beginning of the second hyaline zone (R2).The increase of the otolith radius between the first and thesecond winter, a period when growth rate of European flounderis high, is given by R2 2 R1.

We used linear regression to estimate the relationship be-tween total fish length (Lm, in mm) and otolith radius (Rm,in mm), for 152 individuals (this data set) and 130 individuals(supplementary fish available in our laboratory, collected fromthe west coast of France in 1980, having a similar growthpattern). The estimated total fish length at the beginning ofthe first and of the second winter (L1 and L2, respectively)was computed by back-calculation [23]

Li 5 [(c 1 dRi)/(c 1 d Rm)]·Lm (3)

where c and d were constants obtained by the previous re-gression. The individual growth rate between the first and thesecond winter (GR, in mm/year) was then estimated as L2 2L1, for L2 and L1 values that were obtained by using the back-calculation equation.

Fluctuating asymmetry (FA) sometimes allows the detec-tion of sublethal stress in environment that could be associatedwith a decrease in fitness components; FA is estimated as thesigned difference between the right and the left side, for acharacter of interest [24]. Flounder do not intrinsically showsymmetry because of their asymmetric metamorphosis pattern,but the otoliths of European flounder are presumed to be rel-atively free from developmental asymmetry. The FA is char-acterized by a normal distribution with a mean that does notdiffer significantly from zero [25].

Genetic analyses

Muscle and liver extracts were prepared, and zymogramswere obtained by migration on starch gels according to Borsaet al. [26]. The study by Borsa et al. [26] enabled us to testpolymorphic loci. Six loci extracted from muscle (m) or liver(l) generated reliable results. Following the nomenclature ofShaklee et al. [27], these loci were for alanine aminotransferase1 (AAT-1) (m), aspartate aminotransferase 2 (AAT-2) (m), iso-citrate dehydrogenase (IDH) (m), mannose phosphate isom-erase (MPI) (l), phosphoglucomutase (PGM) (m), and glucosephosphate isomerase 2 (GPI-2) (m).

Observed heterozygosity (Ho) and heterozygosity based onHardy–Weinberg expected values (He) were computed for eachpopulation. Within each population, deviation from Hardy–Weinberg equilibrium was determined by computing the in-breeding coefficient (Fis)

Fis 5 (He 2 Ho)/He (4)

The significance of Fis was assessed by Fisher’s exact test,with the program GENEPOP 3.2a [28]. Allele and genotypefrequencies were analyzed by chi-square contingency tests todetect possible heterogeneity among populations. The degreeof genetic differentiation between populations (Fst) was com-puted by GENETIX 3.0 [29; http://www.univ-montp2.fr/ge-nome-pop/genetix.htm]; the tests of significance of Fst werecarried out by using permuted data sets (1,000 permutations).

Statistical analyses (physiological data and relationshipsbetween genotypes and phenotypes)

Data for physiological parameters (K, HSI, GR, and FA)were log transformed to normalize the distributions (Shapiro–Wilk test; p . 0.05) and stabilize the variances (Brown–For-sythe test; p . 0.05). Analysis of variance (ANOVA) andStudent–Newman–Keuls procedures with transformed valuesof the parameters noted above were used to compare the phys-ical and physiological status of flounder in the different es-tuaries.

We used the principal component analysis (PCA) methoddescribed by Hill and Smith [30], which allows one to relatequalitative data (genotypes) to quantitative data (physiologicalparameters and individual heterozygosity). The PCA was ap-plied successively to data from the contaminated and referencesystems. First, the correlation circle related to the ordinationof the different quantitative variables on the main factorialplan (axis 1 and axis 2) was drawn. Second, the syntheticanalysis was conducted, which allowed display and ordinationof the genetic and physiological variables on the main factorialplan. All the multivariate analyses were performed with theADE-4 software package [31; http://biomserv.univ-lyon1.fr/ade-4.html].

RESULTS

Genetic variability within and between populations

The estimation of multilocus genetic diversity within pop-ulations did not reveal a significant difference between theSter population and the Seine populations: Ho was approxi-mately 0.20 (Fig. 2), and the mean allele number per locus (a)for the two populations was identical (a 5 2.67). Genetic di-versity was lower (Ho 5 0.14) for flounder from the Loire

2708 Environ. Toxicol. Chem. 21, 2002 J. Laroche et al.

Table 1. Polymorphic loci, alleles, and allelic frequencies in the reference site (Ster) and in thecontaminated sites (Seine, Loire) in Francea

Locus Allele Ster Seine 1 Seine Bay Seine 2 Loire

PGM

GPI-2

85100110

90100

0.1220.8510.0270.0270.973

0.3060.69400.1450.855

0.080.9200.440.54

0.1670.8140.0190.1480.852

0.20.800.10.9

MPI100

9095

100

00.2430.1760.541

00.1290.0970.758

0.020.060.040.88

00.0560.0370.907

000.050.95

IDH

AAT-1

10590

100110

95

0.0400.0540.9050.0410

0.0160.0320.96800.032

0.020.020.960.020.04

00.0190.9620.0190.037

00.0670.9170.0170.033

AAT-2

No. observa-tions

100110

90100110

0.9730.02700.9860.014

37

0.9360.0320.0810.9030.016

31

0.9600.060.940

25

0.96300.0740.9070.019

27

0.9670010

30

a PGM 5 phosphoglucomutase; GPI 5 glucose phosphate isomerase; MPI 5 mannose phosphate isom-erase; IDH 5 isocitrate dehydrogenase; AAT 5 aspartate aminotransferase.

Table 2. Genetic differentiation between populations (estimation ofthe degree of genetic differentiation between populations [Fst] by pair;the test of significance used 1,000 permutations); study locations are

found in Francea

Location

No.obser-vations Seine 1 Seine 2 Seine Bay Loire

SterSeine 1Seine 2Seine BayLoire

3731272530

0.0482**————

0.0815**0.0089NS

———

0.1721**0.0926**0.0671**

——

0.1017**0.0276*

20.0014NS

0.1157**—

a * p , 0.05; ** p , 0.01; NS 5 not significant.

estuary (Fig. 2); this result was confirmed by a lower meanallele number (a 5 2). A significant heterozygote deficit wasdetected only for flounder from the Seine 1 site (Fis 5 0.174;p , 0.05).

Allelic frequencies of the five samples (Table 1) were com-pared by chi-square test. The counts for the rare alleles (thosehaving a frequency of #4%) were pooled with those of thenearest common allele for this analysis. For the six loci ana-lyzed, differences in the allelic distribution were significant(i.e., p , 0.05) for PGM (x2 5 13, df 5 4), GPI-2 (x2 541.69, df 5 4), MPI (x2 5 40.03, df 5 8), and AAT-2 (x2 510.22, df 5 4). The distribution of allelic frequencies at thePGM loci highlighted the increasing frequency of the 85 allelein contaminated stations—the frequency ranged from 17 to31% in the Seine estuary and Loire estuary populations, butwas only 12% in the Ster estuary. The frequency of this allelein Seine Bay was particular low (8%). We observed a con-vergent increase in frequency of the 90 allele at GPI-2 in thecontaminated stations (from 10 to 44 %, in the Seine estuaryand bay, and in Loire estuary) compared to the reference sta-tion (3% in Ster estuary). In contrast, allelic frequencies atMPI loci for fish from contaminated sites showed a reducedgenetic variability for the 90, 95, and 105 alleles, comparedto frequencies for fish from the reference estuary. No cleartrend in allelic distribution at AAT-2 was found, for referenceversus contaminated sites.

A significant genetic differentiation was detected amongthe five samples (Fst 5 0.0749; p , 0.05). We also tested fordifferentiation among pairs of samples (Table 2). In most cases,the Fst values for pairwise comparisons were significantly dif-ferent (Table 2). For two of the pairwise comparisons (Seine1 vs Seine 2, and Seine 2 vs Loire estuary), genetic differ-entiation was not significantly different. The level of differ-entiation between Seine 1 (or Seine 2) and Seine Bay wassimilar to that observed between Seine 1 (or Seine 2) and thereference sample (Ster estuary).

Physiological responses of the populations

The linear regression between total fish length (Lm, in mm)and the otolith radius (Rm, in mm) yielded the following re-lationship for the European flounder: Lm 5 104.63Rm 1 13.99(R2 5 0.73). The good fit in this case allowed us to reliablyestimate individual growth rate between the first and the sec-ond winter (GR, in mm/year) by back-calculation. Both AN-OVA and Student–Newman–Keuls tests with log-transformedgrowth data (Fig. 2) revealed a significant difference betweenthe mean growth rates of flounder in the estuaries, as follows:GR Seine 1 ø GR Seine 2 ø GR Seine Bay , GR Loire ,GR Ster (p , 0.01). Flounder collected from the contaminatedsystems had a lower growth rate (77 , mean GR , 106 mm/year) compared to flounder in Ster estuary (mean GR 5 158mm/year).

The sequence of values for mean K and mean HSI forflounder from the various sites (Fig. 2) showed convergenceto the pattern noted for growth rate. For K, the sequence wasK Seine 1 ø K Seine 2 ø K Seine Bay ø K Loire , K Ster(p , 0.001 by ANOVA and Student–Newman–Keuls tests),and for HSI the sequence was HSI Seine 1 ø HSI Seine 2 øHSI Seine Bay ø HSI Loire , HSI Ster (p , 0.001 by ANOVA

Responses of flounder populations to chemical contamination Environ. Toxicol. Chem. 21, 2002 2709

Fig. 3. The DNA profiles from stained erythrocyte nuclei generatedby flow cytometry (number of counts correspond to channel number).The symmetrical profile (left) is for a normal flounder; the asym-metrical profile (right) is abnormal.

Fig. 4. Principal component analysis results for European flounderfrom the Seine estuary, France. (a) Synthetic analysis linking quan-titative variables (vectors) and genotypes (PGM85100: locus 5 phos-phoglucomutase [PGM], heterozygote with two alleles, 85 and 100),on the main factorial plan (ovoid box shows the limits of the plan).(b) Correlation circle for the ordination of the quantitative variableson the main factorial plan (CV 5 coefficient of variation of fish blood,analyzed by cytometry; HSI 5 hepatosomatic index; FA 5 fluctuatingasymmetry; TL 5 total fish length; GR 5 growth rate; H 5 individualheterozygosity; and K 5 condition factor).

and Student–Newman–Keuls tests). Fish from the Ster estuaryhad a greater mean K value and a greater mean HSI comparedto flounder from the other sites.

Of the various metrics for flounder otoliths (mass, area,total length, and perimeter), only mass yielded mean valuesfor FA that were not significantly different from zero (Student’st test; p . 0.05). For this reason, mass was the only otolithmetric used to compare flounder status among estuaries. TheANOVA and Student–Newman–Keuls tests with log-trans-formed absolute values of otolith mass FA revealed a slightbut statistically significant difference among estuaries. Theseqeuence of mean FA values for the sites was FA Seine 1 øFA Seine 2 ø FA Seine Bay ø FA Loire , FA Ster (p ,0.05). Individual variation in the FA for otolith mass for floun-der from Ster also was greater than for fish from the other sites(Fig. 2).

The flow cytometry analyses of fish blood revealed a sig-nificant difference in the frequency of abnormal profiles be-tween Seine (20%) and Ster (3%) (Fig. 3). Among normalprofiles, the mean (6 95% CI) of the CVs for blood from fishin the Ster estuary and the Seine estuary were 4.08 6 0.12and 3.42 6 0.20, respectively. These means differed signifi-cantly (t test, p,0.01).

Relationship between genotype and physiological markers

For the Seine estuary, the first part of the PCA was thecorrelation circle (Fig. 4b). The correlation circle shows therelationships between quantitative data for the 24 fish that hadsymmetrical DNA profiles, as determined by flow cytometry.Note that the individual heterozygosity (H) and CV vectorswere aligned but had opposing directions. This situation high-lights a negative correlation between H and CV, suggestingthat the most heterozygous fish also had less DNA damage.The orthogonality between the K vector and the H and CVvectors (Fig. 4) illustrates the lack of a relationship betweenK and H or CV. The relative positions of the other vectors(i.e., GR, FA, and HSI) are characterized by their proximityto total fish length (TL) and nonsignificant relation to vectorsCV and H.

The second part of the PCA involved linking qualitativeand quantitative data for flounder from the Seine estuary (i.e.,the synthetic analysis; Fig. 4b) and expressed the possiblerelationships between genotypes and physiological parameters.Axes 1 and 2 (main factorial plan) together explained 35% ofthe total variance. On axis 1, the opposite directions betweenCV and H vectors were confirmed and a clear trend in thegenotype distribution was observed, particularly for the PGM

locus (Fig. 4b). From the left to the right of this factorial plan,the following genotypes were observed: PGM 100/100, PGM85/100, and PGM 85/85. Thus, the homozygotes for the 85allele had a lower CV, indicating less DNA damage, and prob-ably a reduced growth rate, given that its direction was op-posite to the GR vector (Fig. 4b). On axis 2, the genotypesshowing the 110 allele (PGM 100/110) had a larger conditionfactor (K). No particular relationship was detected betweenthe GPI-2 genotype and CV, but on axis 2, the GPI-2 90/100genotype had a lower K, compared to the GPI-2 100/100genotype. Other particular genotypes were clearly localized onthe right of the plan and could be characterized as having alow CV for IDH 90/100, AAT-1 95/100, and MPI 95/100.

The six fish from the Seine estuary that had abnormal pro-files (as measured by flow cytometry) were not considered inthe previous PCA analysis, but had a similar genotype for PGMlocus: PGM 100/100. The genetic variability of these fish forthe other loci was large.

For the reference estuary, a new distribution of quantitativedata was expressed on the correlation circle (Fig. 5b). Weobserved a positive correlation between CV, GR, and H, andthis group of parameters was negatively correlated with K.Parameters HSI, FA, and TL were again near each other, andthe orthogonality of this group of parameters with the previousgroup (i.e., CV, GR, and H) emphasized the lack of relationshipbetween the two groups.

The main factorial plan of the synthetic analysis for theSter estuary (Fig. 5) explained 31% of the total variance. Theparticular genotypes PGM 85/100 and PGM 100/110 plottedon the left of the factorial plan had a high CV and a low valuefor K; the opposite trend was noted for these parameters forthe PGM 100/100 genotype, which was located on the right

2710 Environ. Toxicol. Chem. 21, 2002 J. Laroche et al.

Fig. 5. Principal component analysis for European flounder from theSter estuary, France. (a) Synthetic analysis linking quantitative var-iables (vectors) and genotypes (PGM85100: locus 5 phosphogluco-mutase [PGM], heterozygote with two alleles, 85 and 100), on themain factorial plan (ovoid box shows the limits of the plan). (b)Correlation circle for the ordination of the quantitative variables onthe main factorial plan (CV 5 coefficient of variation of fish blood,analyzed by cytometry; HSI 5 hepatosomatic index; FA 5 fluctuatingasymmetry; TL 5 total fish length; GR 5 growth rate; H 5 individualheterozygosity; and K 5 condition factor).

of the plan. No particular physiological responses were as-sociated with the GPI-2 genotypes. These genotypes were dis-tributed along axis 2. Some MPI genotypes were clearly dis-tributed on the right of the factorial plan (e.g., MPI 90/90 andMPI 95/105) and had a low CV and a high K; these genotypeswere characterized by the lack of the common MPI 100 allele.

DISCUSSION

Population genetic variability

The overall genetic variability (multilocus heterozygosityand mean number of alleles per locus) did not appear to beassociated to chemical stressors in the estuaries. Nevertheless,flounder from the contaminated Loire estuary had a lowerobserved heterozygosity and fewer alleles per locus comparedto flounder from the other estuaries. This trend could reflectthe impact of contaminants, but it also could be due to differingphylogeographic histories for the estuaries, or to environmen-tal differences unrelated to contaminants [32]. Investigationson the genetic and physiological status of fish in other estuariesalong the East Atlantic coast should allow us to more defin-itively determine the possible impact of contaminants on theoverall genetic diversity. A significant heterozygote deficit wasdetected for the contaminated Seine estuary in February 2001.However, this deficit was not confirmed at the site two monthslater. Thus, the deficit was probably due to sampling bias orto a Wahlund effect (microdifferentiation within the studiedpopulation), rather than to inbreeding.

Convergent distributions of the allelic frequencies were de-tected for flounder in the contaminated estuaries, comparedwith those for flounder from the reference estuary, particularlyfor PGM, GPI-2, and MPI. The frequencies of particular al-

leles for PGM and GPI-2 increased in the more contaminatedsystems (Seine and Loire estuaries), whereas the reverse trendwas evident for MPI, which was less variable in the sameestuaries. Such modifications of the allelic frequencies forthese particular loci apparently are common in freshwater andmarine populations subjected to pollutants, in the field, in me-socosms, and in laboratory tests [3,5,6,33–35].

No significant genetic differentiation was detected betweenflounder populations among contaminated estuaries (e.g., be-tween the two samples from the Seine estuary, or between theSeine-2 sample and the sample from Loire). On the other hand,a clear difference was detected between populations in con-taminated estuaries (Seine and Loire) versus the reference es-tuary (Ster). These results should be verified by analysis of amore extensive data set in the future.

In the Seine system, the level of genetic differentiationbetwen the estuary samples and the bay sample (microgeo-graphic scale) was similar to the differentiation observed be-tween those estuary samples and the reference site (regionalscale). Thus, the differentiation between the two componentsof the Seine system could be driven by a selective pressure.The possibility of a greater selective pressure in the estuaryalso could explain the particular increase of the allele PGM85 (associated with decreasing levels of DNA damage) in theSeine system, from the bay to the estuary.

Physiological responses at the population level

The estuary-to-estuary differences in GR, HSI, K, and FAfor the flounder that we analyzed seemed especially notewor-thy. The average growth rate of flounder between the beginningof the first winter and the beginning of the second winter(estimated by back-calculation with data from otoliths) wassignificantly greater in reference estuary, compared to the con-taminated estuaries. However, this result must be consideredcautiously for two reasons. First, the more contaminated es-tuaries have larger drainage basins, compared to the referenceestuary, and second, we did not establish controls for envi-ronmental parameters such as temperature [36]. In this study,we note that the Loire estuary was located farther south, rel-ative to the other estuaries. This, plus the fact that growth ratesof flounder from the Loire estuary were similar to growth ratesof flounder from the Seine estuary (which is contaminated),could indicate that flounder growth rate is linked to contam-ination. Diminished growth was also noted as a sign of chem-ical stress for a population of estuarine fish in North America[37].

The PCA for flounder from contaminated and referenceestuaries revealed a positive correlation between HSI, FA, andTL, probably linked to a fish-length effect. The higher valuesof HSI and FA for flounder from the reference estuary, com-pared to flounder from the contaminated estuaries, were likelydue to a greater mean length of fish for the Ster sample (meanTL 5 387.86 mm), compared to flounder from the Seine andLoire estuaries (221.82 mm , mean TL , 287.16 mm). Thus,HSI and FA are not simple parameters that can be used toassess directly the physiological responses of flounder to con-taminants. On the other hand, K and fish length were notcorrelated. Condition factor seemed to be a simple, usefulindex for monitoring the status of flounder potentially sub-jected to stress. The lower K values for flounder from thecontaminated estuaries, compared to those for flounder fromthe reference estuary, could indicate that a response of fish tochemical stress includes a lower energy-storage capacity. More

Responses of flounder populations to chemical contamination Environ. Toxicol. Chem. 21, 2002 2711

generally, K has been shown to relate to feeding intensity,growth, maturation, fecundity, and survival [38].

The assessment of DNA damage by flow cytometry wasfirst evaluated qualitatively. In the qualitative portion of theassessment, abnormal profiles (i.e., histograms with asym-metries) reflecting aneuploid mosaicism or chromosomal frag-mentation were considered to be a possible indication of con-taminant exposure [21,22]. For flounder, abnormal profileswere more frequent in fish from Seine estuary. This resultcould indicate a genotoxic effect of pollutants in the Seinesystem. Nevertheless, one fish from the Ster also had an ab-normal profile, hinting at the possibility of an episode of con-tamination in this reference site. As futher evidence for thispossibility, we note that on the day that fish were being sam-pled from the Ster, we observed an unusual irridescence onthe water’s surface. However, we were unable to determine ifthe sheen was due to a pollutant.

In the second stage of the flow cytometry analysis, histo-grams with asymmetries were removed from the data set, al-lowing comparisons of CVs to be made for individuals withnormal symmetrical profiles. In this stage of the analysis, weobserved a greater mean CV for fish from Ster compared tofish from the Seine (the CVs were 4.08 6 0.12 and 3.42 60.20, respectively). Five months later, on June 15, 2001, 27fish were caught in the Ster and the DNA profiles for thesefish were normal (CV 5 3.47 6 0.23). The latter result couldbe taken as evidence for intermittent contamination in the Ster(as noted previously), followed by recovery. Larger-scale (tem-poral and spatial) genotoxicological studies are needed to bet-ter understand the relationships between exposure to contam-inants and damage to flounder DNA [39].

Relationship between genotype and phenotype underchemical stress

For flounder from the Seine estuary, the correlation circle(Fig. 4) showed that the individual heterozygosity correlatednegatively with CV. This result may be related to the supe-riority of the heterozygotes to maintain the integrity of theirDNA in this contaminated system. The superiority of the het-erozygotes also has been observed for sunfish exposed to ra-dionuclides [40]. As an environment becomes more stressful,individuals that are more homozygous would suffer negativeenergy balance, compared to more heterozygous individuals,which have lower metabolic costs during nonstressful times[41]. In the reference estuary (Ster), we noted an inverse trendbetween heterozygosity and CV, with the more homozygousindividuals having the lowest CVs. This latter result suggeststhat the possible advantages of heterozygosity to fish mightbe revealed only in acute-exposure situations [42], or at siteswhere concentrations of various pollutants are relatively highfor extended periods of time. Such conditions can occur inestuaries (this study) or in rivers downstream from major cities[7].

Growth rate is an essential aspect of fitness, but more rapidgrowth may reduce resistance to stress. For example, rapidlygrowing juveniles are often more vulnerable than slowly grow-ing stages to damage from stress [43]. A possible trade-offbetween stress resistance and growth measured under favorableconditions was noted for the episodically and moderately con-taminated Ster estuary. Here, we observed a positive corre-lation between the higher juvenile growth rate and the higherCV (i.e., greater DNA damage). Similar observations weremade in experiments, wherein contaminants selected against

fast-growing minnows, presumably on the basis of metabolicrate [44].

As noted previously, the distribution of the allelic frequen-cies for flounder in the contaminated estuaries tended to con-verge, particularly for loci PGM, GPI, and MPI. These threeloci are linked to glycolysis and their efficiency at convertingresources into fitness-related output may be a major evolu-tionary pressure-point [5,45,46].

In the Seine system, the PGM 85/85 genotype had a greaterintegrity of DNA and a lower growth rate, compared to thePGM 85/100 and PGM 100/100 genotypes. We pose the hy-pothesis that the PGM 85/85 genotype could be considered asmore tolerant of pollution than the PGM 100/100 genotype.This hypothesis should be tested by experimentation. The re-duced capacity for the PGM 100/100 genotype to maintain itsDNA integrity was confirmed in part, because Seine flounderwith abnormal profiles (as determined by flow cytometry) allhad this unique genotype. Therefore, the increased frequencyof the PGM 85 allele in the Seine flounders could be the resultof a selective pressure that selectively retains in the systemindividuals that are better able to cope with the site-specificstressors and maintain DNA integrity. In the Ster system,where episodic exposure to pollutants was likely, the geno-types for PGM were different. The more common genotype,PGM 100/100, had a lower CV (i.e., a higher level of DNAintegrity) and a larger K. The genotoxic responses of the PGMgenotypes of flounder for the two estuaries are difficult toanalyze for two reasons. First, the chemical nature of the in-termittent contamination in Ster estuary could be very differentfrom the complex of contaminants in the Seine estuary, asnoted previously. And second, particular genotypes may bemore sensitive to acute or chronic stressors, as has been dem-onstrated for Gambusia in mesocosm-scale experiments [4].

The possible links between genotypic variability for theGPI-2 locus and physiological status were less evident thanfor the PGM locus. However, the GPI-2 90 allele was morecommon in flounder from the more highly contaminated es-tuaries, and the GPI-2 90/100 genotype in the Seine estuaryappeared to be linked to low values of K. Another trend wasfor lower CVs for flounders with the MPI 95/100 genotype inthe Seine estuary, but lower CVs associated with greater Kvalues for flounder having the MPI 90/90 and MPI 95/105genotypes in the Ster estuary.

In conclusion, we found substantial differences in the allelicfrequencies for flounder living in highly contaminated estu-aries versus a reference estuary, and we related these differ-ences by PCA to a suite of meaningful physiological prop-erties. However, such trends must be confirmed by more ex-tensive analyses at a larger spatiotemporal scale before theycan be used more broadly to monitor impacts of chemicalstressors on fish populations. The relationships between ge-notypes and physiological status suggest that suspected pol-lution-tolerant genotypes are characterized by their high levelof DNA integrity and a reduced growth rate and conditionfactor.

Acknowledgement—This study was supported by the Program SeineAval 2: L’analyse et la gestion environnementales, recherche appli-quee. Thanks to Christophe Minier, Jose Gouyen, Olivier Maire, andall the staff of the Cellule de Suivi du Littoral Haut Normand (GwenolaDe Roton, Sylvain Duhamel, and Serge Simon) for field assistance.We also are indebted to Patrick Berrebi and Philippe Borsa for theiradvice regarding the genetic markers. Many thanks are due to anon-ymous referees and to the editor for useful comments on the draft.

2712 Environ. Toxicol. Chem. 21, 2002 J. Laroche et al.

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