genotoxic substances in the st. lawrence system ii: extracts of fish and macroinvertebrates from the...

304

Environmental Toxicology and Chemistry, Vol. 17, No. 2, pp. 304–316, 1998q 1998 SETAC

Printed in the USA0730-7268/98 $6.00 1 .00

GENOTOXIC SUBSTANCES IN THE ST. LAWRENCE SYSTEM II: EXTRACTS OFFISH AND MACROINVERTEBRATES FROM THE ST. LAWRENCE AND

SAGUENAY RIVERS, CANADA

PAUL A. WHITE,*† JOSEPH B. RASMUSSEN,† and CHRISTIAN BLAISE‡†Department of Biology, McGill University, 1205 Dr. Penfield Avenue, Montreal, Quebec H3A 1B1, Canada

‡Ecotoxicology and Environmental Chemistry, The St. Lawrence Center, Environment Canada, 105 McGill Street,Montreal, Quebec H2Y 2E7, Canada

(Received 14 November 1996; Accepted 2 June 1997)

Abstract—Aquatic biota frequently accumulate organic contaminants and maintain steady state tissue concentrations that are asmuch as 105 times higher than those in the surrounding water. Although many researchers have studied the accumulation of genotoxicpolycyclic aromatic hydrocarbons (PAHs) by aquatic biota, few researchers have used bioassays to investigate the accumulationof genotoxins. In several previous studies we used the SOS Chromotest to investigate the genotoxicity of industrial effluent extracts,sediment extracts, and bivalve tissue extracts. In this study we use the SOS Chromotest to investigate the accumulation of organicgenotoxins by macroinvertebrates and fish in the St. Lawrence and Saguenay rivers (Quebec, Canada). Tissue concentrations ofgenotoxins (expressed as mg benzo[a]pyrene genotoxic equivalents) reveal bioconcentration factors in the 102 to 103 range. Con-centrations are partially determined by lipid content (r2 5 0.22). Lipid-normalized values indicate that genotoxin concentrations ininvertebrate tissues are significantly higher than those in fish. Fish values indicate that tissue concentrations are biodiminished,with fish at higher trophic levels having lower tissue burdens of genotoxins. The biodiminution pattern observed correspondsexceptionally well with trophic position assignments made by other authors. More contaminated sites yielded less contaminatedspecimens. This may be due to the induction of phase I and phase II detoxification enzymes that is likely to occur at high levelsof exposure. Although the results do not support PAHs as the putative genotoxins, the results do indicate that the accumulatedgenotoxins have similar properties. Tissue to sediment ratios of genotoxins are similar to those observed for genotoxic PAHs, andfar lower than those of more persistent organochlorines. Although we did not investigate genotoxic effects, we might expect themost dramatic effects in fish that consume contaminated macroinvertebrates.

Keywords—Genotoxicity Fish Macroinvertebrates SOS Chromotest Bioaccumulation

INTRODUCTION

Chronic exposure and accumulation of organic contami-nants by aquatic biota can result in tissue burdens that haveadverse effects on the exposed organisms (e.g., tissue necrosisand hyperplasia, reproductive failure, neoplasia) and/or theconsumers of these organisms [1]. Accumulation occurs whenthe rate of uptake from the environment exceeds the rate ofelimination (depuration), with long-term exposure and con-taminant retention resulting in steady state concentrations thatare as much as 105 times higher than those of the surroundingwater [2]. The tendency for organic contaminants to accu-mulate is primarily controlled by contaminant solubility, oftenexpressed in terms of the octanol/water partition coefficient(Kow or Poct) [3,4]. Contaminants with low solubility and a highKow have a strong tendency to accumulate in the lipid poolsof exposed organisms [5].

Contaminants enter aquatic biota via direct diffusion acrossthe gill–water interface or by uptake and assimilation follow-ing the consumption of contaminated food [6]. Thus, in ad-dition to lipid solubility and persistence, accumulation is de-termined by contaminant (bio)availability and the trophic level

* To whom correspondence may be addressed. The current addressof P.A. White is Atlantic Ecology Division, U.S. Environmental Pro-tection Agency, 27 Tarzwell Drive, Narragansett, RI 02883([email protected]).

Joint contribution of the Department of Biology, McGill Univer-sity, and The St. Lawrence Center, Environment Canada.

of the organism under consideration. The precise role of con-taminated food in determining steady state contamination lev-els of feral biota is a controversial topic [7–11]. Early studiesof dichlorodiphenyl trichloroethane (DDT) residues in aquaticfood chains concluded that biomagnification does occur [7].However, some researchers argue that convincing evidence islacking, and claim that tissue residues of persistent contami-nants can be explained solely by direct partitioning across thegill–water interface [8,9]. Mechanistic models indicate thatefficient transfer of contaminants from prey to predator willoccur in long-lived, slow-growing organisms that can assim-ilate contaminants from prey items more rapidly than the con-taminants are metabolized and excreted [6]. However, dem-onstration of food chain effects in feral populations has provedchallenging. Rasmussen et al. [11] recently confirmed the im-portance of food chain structure in determining tissue residuesof persistent contaminants in pelagic, freshwater fish.

Most of the available information concerning the bioac-cumulation and biomagnification of aquatic contaminants hasbeen obtained through investigations of specific substances, orgroups of substances. However, monitoring for specific con-taminants requires a priori knowledge of contaminant identity.An alternative approach to the study of toxicant bioaccumu-lation involves the use of bioassays to detect toxic substancesin complex tissue extracts. Tissue burdens of toxicants can becompared to ambient water and/or sediments levels to assessbioaccumulation. In addition, tissue burdens of biota from var-

Genotoxic substances in aquatic biota Environ. Toxicol. Chem. 17, 1998 305

ious trophic levels can be used to assess biomagnification. Theultimate hazard of the toxicants investigated will be dependenton potency as well as ecological behavior. Those substancesthat are both lipophilic and resistant to degradation will beaccumulated, and may be efficiently transferred from prey topredator.

Although a large number of studies have used bioassays todetect genotoxic or mutagenic substances in industrial wastes(see [12] for review), sediments (e.g., see [13–15]), and surfacewaters (see [16] for review), relatively few studies have in-vestigated the accumulation of genotoxins in aquatic biota (see[17] for brief review). In addition, published investigations ofaquatic biota are primarily restricted to invertebrates (e.g.,[18,19]), which are renowned for their ability to accumulategenotoxic polycyclic aromatic hydrocarbons (PAHs) such asbenzo[a]pyrene (BaP) [20,21]. To our knowledge, no pub-lished studies have examined biota from several trophic levelsin an effort to investigate both bioaccumulation and biom-agnification. Genotoxic substances that bioaccumulate andbiomagnify could constitute a serious health hazard for bothindigenous biota and human consumers.

In several previous works we demonstrated the use of theSOS Chromotest [22,23] for the detection of genotoxicity inindustrial effluents [24], river sediments [15], and bivalve mol-luscs [17]. Although our sediment analyses provided someinformation about the persistence of genotoxic substances, wedid not investigate other ecotoxicologic phenomena. In thisstudy, we extend our analyses to include macroinvertebratesand fish collected from sites that receive genotoxic industrialand municipal discharges [24].

MATERIALS AND METHODS

Study site and sample collection

Biota samples were collected from 19 sites along the St.Lawrence and Saguenay rivers (Quebec, Canada). The sitesinvestigated are a subset of those investigated in our compan-ion study [15]. All receive industrial and municipal wastesfrom facilities that have been identified by the government ofQuebec and the government of Canada as priorities for concernand control [25]. Many of the facilities are known to releasegenotoxic, organic contaminants [24,26]. The location of allsampling sites is illustrated in Figure 1 of White et al. [15].Additional sampling site information can also be found inWhite et al. [15]. In addition to specimens collected from theSt. Lawrence River system, samples of fish and macroinver-tebrates were also collected from Lake Memphremagog (;100km southwest of Montreal, PQ, Canada) and Lake Onatchiway(;350 km northeast of Montreal), two lakes that receive noovert industrial input.

All samples were collected during the summers of 1991and 1992. As outlined in White et al. [15] sample collectionsites were located 1,000 to 1,500 m downstream from previ-ously investigated sites [24]. Fish were captured using a varietyof 40 to 80 m 3 2 m, two to four panel, experimental gillnets. Mesh size ranged from 1 inch (2.54 cm) to 4 inch (10.16cm) (Filmar Industries, Quebec, PQ, Canada). Captured fishwere euthanatized by cervical dislocation, measured (totallength), wrapped in precleaned aluminum foil, and frozen im-mediately on site (propane freezer, Domestic, LaGrange, IN,USA).

At each site an attempt was made to collect a minimum ofthree northern pike (Esox lucius) specimens and six yellowperch (Perca flavescens) specimens. Because perch greater

than 15 cm in length are primarily piscivorous [27], an attemptwas made to collect three large perch (more than 15 cm) andthree small perch (less than 15 cm). Where perch and/or pikewere not available, the following species were collected: wall-eye (Stizostedion vitreum) at Beauport, Donnacona, and St.Romuald; sauger (Stizostedion canadense) at Pointe-aux-Trembles; brook trout (Salvelinus fontinalis) at Jonquiere; andAtlantic herring (Clupea harengus), rainbow smelt (Osmerusmordax), and ocean perch (Sebastes sp.) at La Baie. At LakeMemphremagog, seven perch specimens and three chain pick-erel (Esox niger) specimens were collected. Three northernpike specimens were obtained from Lake Onatchiway.

Macroinvertebrates were sampled with an 18 3 8-inch (45.73 20.3-cm) rectangular dip/kick net with an 800 3 900-mmmesh (Wildco Wildlife, Saginaw, MI, USA). At one site (Beau-harnois), benthic invertebrates were also collected with a cus-tom-made benthic sled. Organisms collected include a widevariety of gastropods, insect nymphs and larvae, crustaceans,and oligochaetes. For this preliminary investigation of geno-toxins in aquatic biota, little attempt was made to separate thesamples into their respective taxonomic groups. Samples werecollected such that the total wet weight exceeded a minimumof 10 g. Where quantities permitted, samples were separatedinto gastropods, amphipods (Gammarus spp.), decapods (pri-marily Orconectes spp.), and miscellaneous riparian inverte-brates. Gastropod samples consisted primarily of Bithyniidae,Planorbidae, and Physidae. Mixed invertebrate samples con-tained mostly hemipterans (e.g., Corixidae and Notonectidae),odonates (both Zygoptera and Anisoptera), and oligochaetes.Samples were separated from debris, placed in solvent-washedglass jars, and frozen immediately on site. Samples collectedfrom Lake Memphremagog contained primarily insect nymphsbelonging to the orders Trichoptera and Odonata (primarilyAnisoptera).

Preparation of biota extracts

Specimens less than 50 g wet weight were extracted whole.Small fish were combined to provide composite samples. Forlarger individuals, extracts were prepared from 50-g samplesof epaxial muscle taken from the caudal region. Biota extractswere prepared as described in White et al. [15,17]. The weightof the extractable residue was used as an estimate of lipidcontent [28].

Gel permeation chromatography (GPC)

Lipid removal was accomplished using GPC on Bio-Beadsy SX-3 (Bio-Rad Laboratories, Mississauga, ON, Can-ada). The method employed is a variation on U.S. Environ-mental Protection Agency method 3640 [29], fully describedin White et al. [15]. The weight of the post-GPC residue wasmeasured and the remaining extract dissolved in high-puritydimethyl-sulfoxide (DMSO) (Sigma Chemical, St. Louis, MO,USA). An aliquot of the post-GPC residue equivalent to ap-proximately 1 g of wet tissue was retained for polycyclic ar-omatic hydrocarbon (PAH) analyses.

SOS Chromotest analyses

Genotoxicity of tissue extracts was measured using the SOSChromotest [22,30]. The test involves incubation of Esche-richia coli PQ37 (lacDU169 uvrA rfa sulA::Mud(Ap,lac) ctsPhoC) with the pure compound or complex mixture to beinvestigated. The sulA::Mud(Ap,lac) fusion places the pro-duction of functional b-galactosidase under the express control

306 Environ. Toxicol. Chem. 17, 1998 P.A. White et al.

Fig. 1. SOS Chromotest concentration–response plots for dichloromethane extracts of biota collected from three St. Lawrence River sites. MeanSOS induction factor values are based on concentrations tested in duplicate. Error bars are one standard error of the mean. Where error bars arenot shown they were smaller than the plotting symbol. All results shown were obtained in the absence of S9 metabolic activation. The upper95% confidence limit of the solvent control was calculated according to the method of Welsch et al. [60].


Table 1. Minimum, maximum, and mean tissue genotoxicity levels.All values are expressed in mg benzo[a]pyrene (BaP) equivalents perg wet tissue. Large perch are those greater than 15 cm long. Small

perch are less than or equal to 15 cm long

SampleMini-mum

Maxi-mum Mean

Stan-darderror N

All fishAll perchPerch .15 cm onlyPerch #15 cmPike onlyWalleye only

0.00140.00140.00140.0280.00300.0018

10.310.3

1.3110.30.5910.176

0.580.730.271.60.150.033

0.140.210.0520.550.0430.024

9458382020

7All macroinvertebratesCrayfish onlyGastropodsMixed littorala

0.00550.0120.00680.093

1.71.70.520.79

0.220.350.0860.43

0.0840.260.0550.21

22693

a Samples contained a mixture of oligochaetes, insect nymphs, andamphipods.

of the SOS response pathway, which is induced by DNA-damaging agents. Postexposure b-galactosidase activity re-flects the genotoxicity of a given sample. Alkaline phosphataseactivity provides an indirect measure of bacteriostatic and bac-teriocidal effects [22]. The semiautomated SOS Chromotestprotocol employed in this study is described in detail in ourcompanion work [15] and White et al. [23].

Initial genotoxicity analyses conducted in the presence ofa postmitochondrial supernatant (S9 fraction) obtained fromAroclor 1254-induced rat liver (Molecular Toxicology Prod-ucts, Annapolis, MD, USA) indicated that S9 enzymes reducedsample potency. In the present work, only the direct-acting(without S9) results will be discussed. 4-Nitroquinoline-1-ox-ide (CAS 56-57-5, Sigma Chemical) was used as a positivecontrol.

Genotoxicity results were qualitatively categorized as out-lined in White et al. [15]. Genotoxic potency values werecalculated for each sample that elicited positive or marginalresponses. The SOS response-inducing potency (SRIP), ex-pressed in SOS induction factor units per equivalent g of wettissue, is the initial slope of the concentration response curve.The minimum detectable genotoxic concentration (MDGC) isthe concentration of extract (equivalent g wet tissue per assayml), inferred from the fitted concentration–response curve, re-quired to produce an induction factor that equals the upper95% confidence limit of the control. The maximum level ofSOS induction (MaxIF) was also recorded.

When concentration–response curves were distinctly non-linear, exhibiting zero-order kinetics at high sample concen-tration, they were analyzed by iterative, nonlinear regressionemploying a least squares loss function [31]. In these cases,the SRIP was calculated according to Langevin et al. [13].When the range of concentrations tested did not result in afull hyperbola, the SRIP was determined by ordinary, leastsquares linear regression.

All data analyses were performed using the SAS systemversion 6.10 for OS/2y (SAS Institute, Cary, NC, USA). Anal-ysis of covariance (ANCOVA), analysis of variance (ANO-VA), and least squares linear regression were used to inves-tigate patterns in the results. Where necessary the data werelog transformed to equalize the variance across the range ofobservations and meet the assumptions of linear regression,ANOVA, and ANCOVA [32]. The residual errors associatedwith all regression, ANOVA, and ANCOVA models were as-sumed to be independent and normally distributed. Normalitywas assessed using the Shapiro–Wilk test and visual exami-nation of a normal probability plot [31,33].

PAH analyses

The PAH analyses were conducted for 88 biota extracts (68fish samples and 20 invertebrate samples). For each sampleanalyzed, an aliquot of the post-GPC material equivalent toapproximately 1 g of wet tissue was dissolved in 100 ml pes-ticide-grade benzene (Anachemia Science, Montreal, PQ, Can-ada). The PAH concentrations were determined using gas chro-matography–mass spectrometry (GC-MS) as described in ourcompanion work [15]. A list of the PAHs analyzed is providedin Table 1 of White et al. [15].

RESULTS

A total of 152 biota samples (120 fish samples, 32 inver-tebrate samples) were analyzed for genotoxicity. In the absenceof metabolic activation roughly 70% of the fish extracts yielded

a positive, marginal, or erratic response. Roughly 88% of theinvertebrate samples yielded a positive, marginal, or erraticresponse. Of the 13 samples (9 fish, 4 invertebrate) collectedfrom Lake Memphremagog, the reference site that receives noovert industrial contamination, 2 perch extracts yielded mar-ginal, positive responses. Both chain pickerel samples failedto elicit a positive response. In addition, none of the fourinvertebrate samples elicited a positive response. In the ab-sence of a positive response from the invertebrate extracts, thetwo weak perch responses are suspect. None of the three pikesamples from Lake Onatchiway elicited a positive response.Figure 1 illustrates concentration–response relationships forseveral positive samples from three St. Lawrence River sites:St. Romuald, Contrecoeur, and Donnacona.

Where concentration–response relationships are nonlinearand approach zero-order kinetics at high concentrations, themaximum SOS induction factor reached reflects the point atwhich the response pathway of the bioassay is saturated. Itwas immediately apparent that the majority of the samplesexamined failed to elicit maximum SOS induction factorsgreater than 2.0. Only two extracts elicited induction factorsabove 2.5. This is in contrast to the results obtained in ourprevious analyses of Mya arenaria from the Saguenay Fjord[17]. Mya arenaria extracts frequently elicited MaxIF valuesabove 3.0 and occasionally elicited values that approached 5.0.Analysis of variance (F ratio 5 10.1, p , 0.0001) and posthoccomparisons (Bonferonni method) of mean MaxIF values re-vealed that the mean fish value (1.47 6 0.04) and the meaninvertebrate value (1.66 6 0.03) are both significantly smaller(p , 0.005) than the mean Mya value (2.53 6 0.3) [33].

Because genotoxins in environmental extracts are chemi-cally diverse, it is useful to express the results as equivalentsof a standard reference compound. All genotoxicity valueswere thus converted to their BaP genotoxic equivalence andexpressed as mg BaP equivalents per g wet tissue. Despite thefact that the samples investigated in this study possess direct-acting genotoxicity, and BaP requires metabolic activation,BaP equivalents nonetheless provided a useful ‘‘currency’’ ofgenotoxicity. Tissue concentrations of BaP equivalents werecalculated as the ratio of the MDGC of BaP to the MDGC ofthe sample investigated (MDGC of BaP 5 0.0757 mg per assayml, mean of 40 separate measurements made in our labora-tory). Minimum, maximum, and mean concentrations of BaP


Table 2. Measured lipid concentrations for aquatic biota investigatedin this study

Sample

Mean lipidcontent

(% wet wt.) Standard error

All fishAll invertebrates

2.260.48

0.180.071

PerchPikeTroutWalleyeHerring

2.580.942.001.178.75

0.200.120.230.171.85

CrayfishGastropodsMixed littoral invertebrates

0.860.190.51

0.110.0350.090

Fig. 2. The relationship between lipid content (% wet weight) and tissue concentrations of genotoxins (as mg benzo[a]pyrene [BaP] equivalentsper g wet tissue). Value labels indicate the type of biota sampled. Pe 5 perch, Pi 5 pike, Herr 5 herring, Seb 5 Sebastes, Wall 5 walleye, Sau5 sauger, Tr 5 trout, Cray 5 crayfish, Gast 5 gastropods, Gam/Gast 5 Gammarus/gastropods, Litt 5 mixed riparian invertebrates, Profund 5mixed benthic sled sample, Muss 5 mussels.

equivalents in the tissues examined are summarized in Table1. The results indicate that small perch (#15 cm) are the mostcontaminated, followed by the invertebrates, larger perch, andfinally pike and walleye.

Comparisons of the tissue concentrations summarized inTable 1 may be misleading. Organic contaminants in waterhave a tendency to partition into the lipid pools of the exposedorganisms [6]. As a result, tissue concentrations are affectedby the lipid content of the exposed organism [11]. We have

no reason to assume that genotoxic organics would not behavein a similar manner. Lipid contents of the biota samples ex-amined in this study vary from a low of ,1% (wet weight)for macroinvertebrates to a high of over 8% for herring fromLa Baie. Mean lipid content values for the samples examinedare summarized in Table 2.

Although Table 1 indicates that perch are more contami-nated than invertebrates, Table 2 indicates that invertebrateshave a much lower lipid content. Figure 2 illustrates the re-lationship between tissue concentrations of BaP equivalentsand lipid content. The result confirms a significant relationshipbetween lipid content and genotoxic contamination. In addi-tion, for a given lipid content, the results indicate that mac-roinvertebrate samples are frequently more contaminated thanfish samples. The following model relates log tissue concen-tration of BaP equivalents (mg per g) to log lipid content (%wet weight) and biota type (fish or invertebrate) (r2 5 0.28,n 5 116, F ratio 5 21.5, p , 0.0001):

log BaP equivalents (mg/g wet tissue)

21.15 all fish A5 [ ]20.65 all invertebrates B

1 [1.12 6 0.18·log lipid (% wet weight)] (1)

Both biota type and lipid content are significant at p , 0.02.


Fig. 3. Comparison of mean lipid-normalized tissue concentrationsof genotoxic substances. Values are arithmetic means. Error bars areone standard error of the mean. Letters adjacent to bars indicate theresults of post hoc contrasts. Separate analyses of variance were per-formed for each group of bars. Bars accompanied by different lettersare significantly different at a 5 0.05.

The value associated with the slope term is the standard error.Post hoc contrasts of regression coefficients [31] revealed asignificant difference between invertebrate contamination andfish contamination, with the coefficients in Equation 1 accom-panied by different letters being significantly different at a 50.05. The coefficients of biota type indicate that predictedinvertebrate levels will be approximately three fold higher thanfish levels.

Further analyses of the fish data revealed that for a givenlipid content, the more piscivorous species generally have low-er tissue levels of genotoxins. An ANCOVA revealed the fol-lowing model for fish data only (r2 5 0.35, n 5 85, F ratio5 10.7, p , 0.0001):

log BaP equivalents (mg/g wet tissue)

20.58 small perch A

21.12 large perch B5

21.12 pike B 21.91 walleye C

1 [0.61 6 0.27·log lipid (% wet weight)] (2)

Both fish type and lipid content are significant at p , 0.03.Again, coefficients accompanied by different letters are sig-nificantly different at a 5 0.05. Thus, for a given lipid contentsmall perch have significantly higher tissue levels of BaPequivalents than pike or large perch, which in turn are higherthan walleye.

Both models defined by Equations 1 and 2 indicate that thecoefficient of lipid content is not significantly different fromunity. In such cases, convention requires the expression ofchemical concentrations on a per unit lipid basis [5]. Lipid-corrected genotoxicity values are shown in Figure 3. In contrastto the untransformed data in Table 1, when the mean lipid-normalized concentrations of genotoxins were investigated, itis evident that macroinvertebrate samples are more contami-

nated than fish samples. An ANOVA comparing the mean fishvalue to the mean invertebrate value revealed a significantdifference (F ratio 5 6.1, p , 0.02). A separate ANOVArevealed a significant effect of fish type on mean genotoxiccontamination (F ratio 5 4.7, p , 0.005).

Although previous effluent analyses [24] had shown thatgenotoxic loadings vary from less than 1 g BaP equivalentper day at La Prairie to more than 30 kg per day at Pointe-aux-Trembles, regression analyses failed to demonstrate anysignificant relationship between biota contamination and re-gional genotoxic loading (Fig. 4). Despite the lack of a sig-nificant trend, the results suggest a negative relationship be-tween genotoxic loading and the genotoxic contamination ofdownstream aquatic biota.

Sites with contaminated invertebrates tend to have contam-inated fish and vice versa. Figure 5 illustrates the relationshipbetween fish contamination and invertebrate contaminationacross the 12 sites for which data are available. Linear re-gression analyses revealed the following model (r2 5 0.34, Fratio 5 5.1, p ,0.05):

log fish contamination (mg BaP equivalents/g lipid)

5 0.18 1 [0.57 ·log invertebrate contamination

(mg BaP equivalents/g lipid)] (3)

Similar to the results shown in Figure 2 and equation 1, themean concentration of BaP equivalents in fish from a givensite is usually, although not always, lower than that observedfor invertebrates. In most cases, the mean fish contaminationis about one half an order of magnitude lower than that ofinvertebrate samples. It is interesting to note that several ofthe sites with the lowest genotoxic loading contained the mostcontaminated biota samples.

Figure 6 illustrates the relationship between mean pike/walleye contamination and perch contamination. The linearregression result obtained is (r2 5 0.64, F ratio 5 14.2, p ,0.006)

log pike walleye contamination (mg BaP equivalents/g lipid)

5 0.24 1 [0.65 ·log perch contamination

(mg BaP equivalents/g lipid)](4)

Although the results reveal that lipid-corrected mean perchvalues frequently exceed pike/walleye values, they do not de-note large differences. Lack of data prohibited the division ofthe perch data used to generate Figure 6 into the same cate-gories as that used in Figure 3.

The results in Table 3 compare PAH concentrations in fishand invertebrates. Although genotoxic PAHs were detected infish tissues, concentrations are very low and frequently belowdetection. Mean tissue concentrations of genotoxic PAHs ininvertebrates are substantially higher (3- to 175-fold) thanthose observed in fish.

The difficulty of predicting the biological significance ofcontamination with complex mixtures of aromatic hydrocar-bons has led several researchers to convert contaminant con-centration values to biologically meaningful equivalents [34].We used a similar approach to convert PAH residues into theircorresponding BaP equivalence values, where PAH-derivedequivalence is defined as the sum of the individual PAH con-centrations multiplied by their respective genotoxic equiva-lency factors (see Table 3 of [15]).

Linear regression analysis revealed a weak, but significant


Fig. 4. The relationship between the total regional genotoxic loading from industrial and municipal sources and the observed genotoxic contam-ination of aquatic biota from the St. Lawrence and Saguenay rivers. Loading values are from White et al. [24]. Where several observations wereavailable, biota contamination values are arithmetic means. Number of observations ranged from 1 to 9.

(r2 5 0.14, F ratio 5 9.3, p , 0.004, N 5 61) relationshipbetween the PAH-derived concentration of BaP equivalentsand the bioassay-derived concentration of BaP equivalents de-scribed earlier (Fig. 7). However, the effect is not significantwhen each type of biota is considered separately. Concentra-tions of both bioassay-derived and PAH-derived BaP equiv-alents are higher in invertebrates than in fish. Therefore, itappears that the observed relationship is due to the same dif-ferences in biota contamination already described. The resultspresented also indicate that the levels of bioassay-derived BaPequivalents are on average two to three orders of magnitudegreater than the corresponding PAH-derived value.

DISCUSSION

Most published research efforts that employed bioassays toinvestigate genotoxins and mutagens in aquatic biota have beenrestricted to bivalve molluscs. For example, Rodrıguez-Arizaet al. [18] detected oxidative mutagens in the tissues of threespecies of marine molluscs collected from Spanish coastalregions contaminated with a variety of toxic metals. Marvinet al. [19] detected both frameshift and base-pair substitutionmutagens in zebra mussels (Dreissina polymorpha) fromHamilton Harbor (Lake Ontario, Ontario, Canada), an arearenowned for PAH contamination (PAH sediment concentra-tion . 500 ppm dry weight [35]). To our knowledge onlyKinae et al. [36] investigated the accumulation of mutagensin fish. Using the Ames/Salmonella mutagenicity assay and aBacillus subtilus DNA damage assay they detected both gen-otoxins and frameshift mutagens in the livers of spotted sea

trout (Nibea mitsukurii) collected from areas that receive pulpand paper mill wastes.

Aquatic biota in the St. Lawrence River system do accu-mulate direct-acting genotoxic substances detectable with theSOS Chromotest. Although we did not thoroughly investigatethe presence of genotoxins that require S9 activation, samplestested in the presence of S9 yielded a weaker, often negativeresponse. Our analyses of soft-shell clams from the SaguenayFjord revealed a similar reduction in potency upon additionof S9 [17]. Similar decreases in activity were observed byRodrıguez-Ariza et al. [18] and Frezza et al. [37]. However,Marvin et al. [19], Sparks et al. [38], and Kira et al. [39]observed increased mutagenicity in the presence of an S9 met-abolic activation mixture. Both Marvin et al. [19] and Kira etal. [39] indicated that the sites examined are heavily contam-inated with progenotoxic PAHs such as BaP.

The results presented indicate that both fish and invertebrateextracts contain SOS genotoxins. It seems likely that the dif-ference in their relative ability to invoke the SOS responsepathway is determined by differences in the physicochemicalproperties of the accumulated genotoxins, and differences inthe pharmacokinetics of genotoxins in aquatic biota. For ex-ample, metabolism of PAHs such as BaP in teleost fish ismediated by cytochrome P-450 monooxygenase. In contrast,cytochrome P-450 monooxygenase is thought to play only aminor role in molluscan PAH metabolism [21]. The resultsobtained here and elsewhere indicate that invertebrates, par-ticularly molluscs such as Mya arenaria [17], accumulate gen-otoxins that can elicit higher SOS induction factors than those


Fig. 5. The relationship between the genotoxic contamination of fish and the genotoxic contamination of macroinvertebrates for 12 sites alongthe St. Lawrence River. Where several observations were available, values are arithmetic means. Number of observations ranged from 2 to 9.Linear regression analysis revealed a significant relationship (see text). The dashed line is the 1:1 line.

accumulated by other biota. Pure compounds also reveal largedifferences in the magnitude of SOS induction. Benzo[a] py-rene elicits induction factors between 3 and 8 before ap-proaching zero-order kinetics. In contrast, compounds such as4-nitroquinoline-1-oxide can produce SOS induction factorsthat easily exceed 25, with zero-order kinetics manifested atvalues above 60 (P.A. White, unpublished results; P. Quillardet,unpublished results).

Organisms with a high lipid content tended to be morecontaminated with genotoxic organics (Fig. 2), with the lipidtrend being strong enough to justify lipid correction of results.However, lipid content alone was only able to account for 22%of the variation in tissue concentrations of BaP equivalents.At 1% lipid for example, there is a three orders of magnitudevariation in genotoxic contamination. Analysis of covarianceconfirmed that part of the variability is due to the type of biotaand demonstrated that organisms at lower trophic levels havesignificantly higher levels of contamination. This pattern wasmaintained when only the fish data were considered, and fishoccupying lower trophic levels were found to have highertissue concentrations of genotoxins. The results presented inFigure 3 indicate that walleye have the lowest tissue levels ofgenotoxins, followed by pike and large perch, small perch, andfinally macroinvertebrates. These results are supported by pub-lished diet and nitrogen-stable isotope studies, which indicatethat walleye usually occupy a trophic position that is higherthan other piscivores such as pike. Large perch and pike gen-erally occupy a similar trophic position that is below walleye.

Small perch generally occupy a position that is below pikeand large perch, and slightly above crayfish [40].

The observed relationship between trophic position and thetissue concentrations of genotoxins is quite different from thatobserved for persistent organic contaminants such as poly-cholorinated biphenyls (PCBs). Efficient transfer of PCBs fromprey to predator results in a positive effect of trophic positionon lipid-normalized concentrations [11]. For genotoxic organ-ics, on the other hand, we found a negative relationship be-tween trophic position and lipid-normalized concentration.This biodiminution likely results from the ability of fish tometabolize and excrete genotoxins contained in the tissues oftheir prey. Higher tissue burdens of genotoxins in invertebratesare likely the result of a lower trophic position and a decreasedcapacity for genotoxin metabolism and excretion. This de-creased capacity for genotoxin metabolism is in turn likelyrelated to difference in mixed function oxidase (MFO) activ-ities. Fish MFO levels are usually much higher (;200 pmol/min/mg 7-ethoxyresorufin-O-deethylase activity) than those ofinvertebrates (;10–50 pmol/min/mg) [20,21]. Although it isnot clear how increased MFO levels would effect SOS gen-otoxins, we would expect an increased ability for metabolismand excretion of organics to work against the biomagnificationof genotoxins.

Although the observed effect of trophic position on gen-otoxin concentration is different from that observed for per-sistent substances, it is similar to that observed for more readilymetabolized substances such as PAHs. For example, fish to


Fig. 6. The relationship between the genotoxic contamination of pike/walleye and the genotoxic contamination of perch for 12 sites along theSt. Lawrence River. Where several observations were available, values are arithmetic means. Number of observations ranged from 2 to 9. Linearregression analysis revealed a significant relationship (see text). The dashed line is the 1:1 line.

sediment ratios for persistent, chlorinated hydrocarbons suchas DDT and PCBs are in the 102 to 103 range [41]. In contrast,PAHs have little tendency to biomagnify and generally exhibitbiota to sediment ratios of 0.01 to 1.0, with wide variationsin the biota to sediment ratios for PAHs that are generallyattributed to a variable capacity for PAH metabolism and ex-cretion [42,43]. Eadie et al. [44] found that oligochaetes fromLake Erie have PAH levels that are approximately 0.2 to 0.5times sediment levels. Kauss and Hamdy [45] found that tissueto sediment ratios for genotoxic PAHs in bivalve molluscs aregenerally less than 1. Varanasi et al. [46] found that tissue tosediment ratios for PAHs in marine invertebrates ranged from0.05 to 0.5, with higher values being associated with largerPAHs. Black et al. [47] found that PAH levels in brown troutand white sucker from the Hershey River (Michigan, USA)ranged from not detectable to about 1% of the sediment levels.Comparisons of the tissue genotoxicity levels obtained here,with previously published suspended particulate matter andbottom sediment results [15], are consistent with PAH-likedegradability. Mean concentrations of SOS genotoxins in biotaare about one tenth (0.07–0.17) the mean suspended particulatematter values. Ratios to bottom sediment are slightly higher(0.25–1.25), but generally less than 1. Units for biota to sed-iment ratios are mg BaP per g dry tissue and mg BaP per gdry sediment. Wet weight to dry weight conversions for tissuevalues assumed 85% water content.

The surface water (SOS Chromotest) results of Langevinet al. [13] indicated that the St. Lawrence River contains ap-proximately 0.35 ppb BaP equivalents. The results presentedin Table 1 indicate that bioconcentration factors (BCFs) ofgenotoxins in the St. Lawrence River system are in the 102 to

103 range. Because Langevin et al. made an effort to samplein open waters not directly affected by local industrial andmunicipal discharges, this value should be considered a max-imum. Several published regression models relate BCF valuesin fish and invertebrates to physical-chemical properties suchas Kow [1–4]. However, the ability of aquatic biota to metab-olize and excrete genotoxic organics such as PAHs generallyresults in BCFs that are at least an order of magnitude lowerthan those of persistent organochlorines with similar Kows[48,49]. We used a Kow–BCF relationship for genotoxic PAHsto estimate the Kow of genotoxins accumulated by St. LawrenceRiver biota (linear regression function of log Kow vs log BCFcalculated using data of Mackay [4] and de Voogt et al. [50];log BCF 5 (0.71·log Kow) 1 0.11; n 5 8, r2 5 0.70, F ratio5 14.2, p , 0.009). The results indicate that the accumulatedsubstances have Kows in the 104 range.

The Kow value calculated above will determine particle ad-sorption and bioavailability of genotoxins in aquatic systems.At Kow 5 104 we might expect a high proportion of surfacewater genotoxins to be present in the dissolved, rather thanparticle-bound state (e.g., at 5 mg/L suspended solids, ;95%dissolved), with this low tendency for particle sorption re-sulting in increased bioavailability [51]. It is interesting to notethat the calculated Kow is similar to that inferred from thesorption partition coefficient of genotoxins in domestic waste-waters (Kd ; 8,000, Kow ; 2 3 104 [52]). Moreover, the massbalance calculations of White and Rasmussen (unpublished)indicate that the majority of direct-acting SOS genotoxins inthe surface waters of the St. Lawrence River system are likelydomestic in origin. Although this correspondence is interest-ing, it is not possible to state whether the substances accu-


Table 3. Maximum and mean concentrations of genotoxic PAHsdetected in the tissue samples examined. All values are in ppb (wetwt.). Naphthalene, acenaphthylene, acenaphthene, and fluorene arenot included because no evidence exists that they are genotoxic. 3-Methylcholanthrene was never detected. Benzo[c]phenanthrene,benzo[g,h,i]perylene, dibenz[a,h]pyrene, dibenz[a,l]pyrene, anddibenz[a,i]pyrene were not detected in fish tissues. 7,12-Dimethylbenz[a]anthracene was not detected in any invertebratesamples. Maximum values are rounded to the nearest ppb. Meanvalues are rounded to the nearest 0.01 ppb. The last columnsummarizes the percentage of samples in which the substance wasdetected. When the compound was not detected, 0 ppb was used for

the calculation of mean concentration

CompoundMaximum

concn.Meanconcn.

%Detected

Fish tissuesPhenanthreneAnthraceneFluoranthenePyreneBenz[a]anthraceneChryseneBenzo[b,j,k]fluoranthenea

7,12-Dimethylbenz[a]anthraceneBenzo[a]pyrene

10.93.02.02.08.8

117.93.92.05.9

1.000.150.070.040.262.710.090.050.08

46.07.85.32.6

10.531.6

2.63.91.3

Indeno[1,2,3-cd]pyreneDibenz[a,h]anthracene

2.01.9

0.030.03

1.31.3

Invertebrate tissuesPhenanthreneAnthraceneFluoranthenePyreneBenzo[c]phenanthreneBenz[a]anthraceneChryseneBenzo[b,j,k]fluoranthenea

Benzo[a]pyreneIndeno[1,2,3-cd]pyreneDibenz[a,h]anthraceneBenzo[g,h,i]peryleneDibenz[a,h]pyreneDibenz[a,l]pyreneDibenz[a,i]pyrene

15.64.8

60.439.615.826.7

107.038.616.4

7.71.99.60.93.01.9

4.920.618.946.950.757.01

15.276.001.900.600.090.830.050.280.92

95.219.090.576.2

4.881.090.557.138.114.3

4.819.1

4.89.54.8

a Sum of benzo[b]fluoranthene, benzo[k]fluoranthene, and ben-zo[j]fluoranthene.

mulated by biota examined here are industrial or domestic inorigin.

The results presented in Figures 3 and 4 and Equations 1and 2 do not address the fact that the biota collected inhabitregions with varying levels of contamination. Some of theunexplained variation in tissue contamination must be attrib-utable to these differences in site contamination. Althoughlittle evidence exists of genotoxicity at clean sites, sites thatreceive industrial and municipal wastes show a negative effectof loading on biota contamination (Fig. 4). Lower mutagenicityof tissue extracts at more contaminated sites was also observedby Rodrıguez-Ariza et al. [18]. They attributed the result toincreased levels of detoxifying enzymes such as glutathione-S-transferase and glutathione peroxidase in organisms inhab-iting more contaminated areas. Additional research by Rod-rıguez-Ariza et al. [53] and others (e.g., [54]) revealed thatfish inhabiting contaminated areas also have an enhanced abil-ity to metabolize and activate promutagenic substances. Thisenhanced ability has been attributed to increased MFO activityin fish and other organisms at polluted sites [21]. For example,Britvic et al. [55] observed that carp (Cyprinus carpio) in-habiting polluted environments had increased bile fluorescence

and increased liver BaP monooxygenase activity, and providedliver S9 preparations that had an enhanced ability to activateBaP in vitro. A similar enhancement of the ability to metab-olize genotoxic substances may be occurring at the sites in-vestigated here. Biota inhabiting sites that receive high gen-otoxic loadings (e.g., Trois Rivieres and Contrecoeur) mayhave increased phase I and/or phase II enzyme activities, anda concomitant increased ability to metabolize and excrete gen-otoxic substances. However, because metabolism also resultsin genotoxin activation, we might expect genotoxic effects(DNA adducts, mutations, strand breaks, etc.) to be higher inorganisms from sites where genotoxic loadings are very high.

Although the results failed to demonstrate a significant re-lationship between regional genotoxic loading and biota con-tamination, the results are consistent (Figs. 6 and 7 and Eqs.3 and 4). In Figure 5 and Equation 3 we confirmed that meanfish contamination is generally about one half an order ofmagnitude lower than corresponding invertebrate levels. Theresults presented in Figure 6 and Equation 4 revealed littledifference between the mean perch and mean pike/walleyecontamination. The discrepancy between this result and thatpresented in Figure 2 and Equation 2 is likely due to the factthat most (;70%) of the perch results used to calculate meancontamination levels at each site correspond to specimensgreater than 15 cm in length.

The PAH analyses summarized in Table 3 indicate thatinvertebrate tissues are far more contaminated than are fishtissues. Ratios of invertebrate PAH concentration to fish PAHconcentration (.10) are similar to those obtained by Black etal. [47]. Many researchers have identified similar patterns thatare generally attributed to the aforementioned differential abil-ities for PAH metabolism and excretion. The PAH results re-veal a similar pattern of biodiminution to that seen for gen-otoxins. Although the results presented in Figure 7 revealeda weak effect of PAH-derived BaP equivalents on bioassay-derived BaP equivalents, the relationship is dominated by thedifferences between invertebrates and fish that were summa-rized in Figure 3. However, because bioassay-derived concen-tration values were calculated from direct-acting genotoxicitymeasurements, and the PAHs investigated all require S9 ac-tivation, the results obtained cannot imply that PAHs are re-sponsible for the observed differences between fish and in-vertebrates. The fact that PAH values follow a biodiminutiontrend that is similar to that observed for genotoxins suggeststhat some putative genotoxins have physicochemical propertiesthat are similar to PAHs.

Moutschen [56] predicted the ‘‘amplified effects’’ thatwould result from genotoxin bioaccumulation and biomagni-fication. The goal of this study was to evaluate this hypothesisby investigating tissue burdens of genotoxins for biota fromthe St. Lawrence River system. The results obtained confirmedthat genotoxic organic substances do accumulate in the tissuesof aquatic biota. Tissue levels are 100 to 1,000 times higherthan ambient water concentrations. The results also show thatgenotoxins are much more readily degraded than persistentchlorinated organics such as PCBs and DDT. Comparisons ofdifferent types of biota indicate that genotoxins are biodimin-ished rather than biomagnified, with highest levels in inver-tebrates that occupy a low trophic position and have a reducedcapacity for metabolism and excretion of organics. This in-vertebrate contamination may constitute a serious health haz-ard to human consumers. Several researchers (e.g., [20]) havevoiced concern about the carcinogenic hazard of consuming


Fig. 7. The relationship between the tissue concentration of bioassay-derived benzo[a]pyrene (BaP) equivalents the concentration of polycyclicaromatic hydrocarbon (PAH)-derived BaP equivalents. Linear regression revealed a weak, but significant effect of PAH-derived concentrationon bioassay-derived concentration (see text). The dashed line is the 1:1 line. Value labels used are identical to those in Figure 3.

invertebrates that have a tendency to accumulate genotoxicorganics.

Moutschen [56] also expressed particular concern for anycontaminant that can exert genotoxic effects, because theseeffects can occur at far lower doses than those required forother, more readily observable toxic endpoints. Although wedid not investigate genotoxic effects, previous research effortshave demonstrated that these effects can be severe. Many re-searchers have documented the high frequency of neoplasia infish and invertebrates that inhabit areas contaminated with gen-otoxic and carcinogenic PAHs [57,58]. Adverse effects arecertainly not limited to neoplastic transformation. Kurelec [59]proposed a wide range of other genotoxic effects includinggrowth inhibition, premature aging, tissue degeneration, andimmunosuppression. Our results suggest that genotoxic effectswill likely be most pronounced in small perch, because of theposition they occupy in the trophic structure. Examination ofgenotoxic effects (e.g., neoplasia, DNA damage, chromosomalaberrations) and biomarkers of genotoxin metabolism (e.g.,bile metabolites, DNA adducts) in small perch and inverte-brates from the St. Lawrence River system seems a promisingarea for further research.

Acknowledgement—Pierre Fournier of the Quebec Ministry of En-vironment and Wildlife (MEF) furnished the permits required to col-lect fish for scientific research. Regional MEF representatives pro-vided additional assistance and advice. Jay Leopkey, Brigid Payne,

Cornelia den Heyer, and Brian Walker provided excellent technicalassistance in the field and the laboratory. Two anonymous reviewersprovided helpful comments and criticisms. Chain pickerel from LakeMemphremagog were graciously donated by Jake Vander Zanden.Northern pike from Lake Onatchiway were donated by Christian Bla-ise. The study was supported by a St. Lawrence Center–Natural Sci-ence and Engineering Research Council of Canada research partner-ship grant to J.B. Rosmussen and Natural Sciences and EngineeringResearch Council of Canada doctoral research fellowship to P.AWhite.

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