Histopathological, histomorphometrical, and immunohistochemical biomarkers in flounder (Platichthys flesus) from the southern Baltic Sea

Ecotoxicology and Environmental Safety 78 (2012) 14–21

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Histopathological, histomorphometrical, and immunohistochemical biomarkers in flounder (Platichthys flesus) from the southern Baltic Sea Henryka Dabrowska a,n, Teresa Ostaszewska b, Maciej Kamaszewski b, Agnieszka Antoniak a, Łukasz Napora-Rutkowski b, Orest Kopko a, Thomas Lang c, Nicolai F. Fricke c, Kari K. Lehtonen d a

National Marine Fisheries Research Institute, Department of Food and Environmental Chemistry, Ko!!a˛taja 1, 81-332 Gdynia, Poland Warsaw University of Life Sciences, Department of Ichthyobiology and Fisheries, Ciszewskiego 8, 02-786 Warsaw, Poland c Johann Heinrich von Th¨ unen-Institute/Institute of Fisheries Ecology, Deichstr. 12, D-27472 Cuxhaven, Germany d Marine Research Centre, Finnish Environment Institute, P.O. Box 140, FI-00251 Helsinki, Finland b

a r t i c l e i n f o

a b s t r a c t

Article history: Received 18 August 2011 Received in revised form 19 October 2011 Accepted 25 October 2011 Available online 25 November 2011

Flounder (Platichthys flesus), collected in late fall of 2009 from four coastal sites in the southern Baltic Sea including the Gulf of Gdan´sk (GoG), were investigated for a suite of biomarkers of contaminant effects. The biomarkers included liver histopathologies, which were diagnosed and assessed using commonly applied lesion categories, the size and density of melano-macrophage aggregates (MMAs), expression of proliferating cell nuclear antigen (PCNA) and of cytochrome P450 1A (CYP1A) in liver as well as the size and density of MMAs and density of Perls’-positive cells in the spleen. The prevalence of liver lesions differed among the sites. Most frequently occurring were non-specific and early toxicopathic non-neoplastic lesions. Mean MMA size was in the range of 264–519 mm2 and 717–2137 mm2 in liver and spleen, respectively, and density was in the range of 6–13 and 15–26 MMA mm  2, respectively. Mean density of PCNA-positive hepatocytes was in the range of 300–1281 cells mm  2. These histomorphometrical biomarkers correlated positively with the muscle Hg, S7PCB, and SDDT residues and negatively with the indices of general liver condition. They showed significant differences between the sites, which were in line with the spatial prevalence of liver lesions and CYP1A induction. Overall, the biomarker responses were more pronounced in the GoG sites in comparison to those outside the Gulf, which confirms some earlier results and broadens the knowledge of contaminant effects in the Polish coastal zone of the Baltic Sea. & 2011 Elsevier Inc. All rights reserved.

Keywords: Baltic Sea Flounder Biomarkers Histopathology Histomorphometry Melano-macrophage aggregates Proliferating cell nuclear antigen CYP1A induction

1. Introduction Histopathological alterations have been examined for decades in various fish tissues and organs in order to assess effects of chemical contaminants both in field and laboratory settings (Hinton and Lauren, 1990; Koehler, 1990; Manera et al., 2000; Wester and Canton, 1986). These types of alterations are increasingly used as biomarkers in marine pollution monitoring (Au, 2004). According to Hinton et al. (1992), histopathological biomarkers are higher level responses that reflect prior alterations in physiological and/or biochemical function and represent an ecologically relevant biological endpoint of exposure to environmental stressors including contaminants. In fact, liver histopathology along with macroscopic liver neoplasms and externally visible fish diseases has been included as biomarkers in several national and international integrated monitoring programmes

n

Corresponding author. Fax: þ48 58 7356 110. E-mail address: [email protected] (H. Dabrowska).

0147-6513/$ - see front matter & 2011 Elsevier Inc. All rights reserved. doi:10.1016/j.ecoenv.2011.10.025

(Lang, 2002; ICES, 2010). The liver has been the focus of histopathological biomarkers because of its key functions such as metabolism of xenobiotics and sex hormones, synthesis of vitellogenin, food digestion, and storage, and because many persistent organic contaminants accumulate in the liver to a greater extent than in other tissues (Couillard et al., 1999; Dabrowska et al., 2009; Stentiford et al., 2003). The present study was conducted within the frame of the BEAST (Biological Effects of Anthropogenic Chemical Stress: Tools for the assessment of Ecosystem Health) project, which was part of the Baltic Sea BONUS Program. The aim of the project was the development of integrated measures of chemical pollution and tools contributing to the assessment of ecosystem health of the Baltic Sea. The study focused on flounder (Platichthys flesus), a common marine bioindicator species, which, like other flatfish species, has been used in biomonitoring of coastal ecosystems in the U.S.A. and Europe (Myers et al., 1998; Vethaak and Wester, 1996; Lang et al., 2006; Kopecka et al., 2006). Histopathological alterations in livers of flounder from the Baltic Sea have been examined previously (Lang et al., 2006). In the present study,

H. Dabrowska et al. / Ecotoxicology and Environmental Safety 78 (2012) 14–21

2. Materials and methods 2.1. Fish sampling Flounder were collected aboard the research vessel Baltica in the period of 24 November–3 December 2009 during the Baltic International Trawl Survey (BITS4Q) coordinated by the International Council for the Exploration of the Sea (ICES) from each of the four locations shown in Fig. 1. The locations were selected because they represent a range of contaminant exposure conditions. The Gulf of Gdan´sk is one of the most contaminated areas of the Baltic Sea within the Polish coastal zone (HELCOM, 2010; Kopecka et al., 2006). This is due to the input of substantial amounts of pollutants from various and extensive human activities located on the southern shore of the Gulf, and also as a result of contaminant inflow from the Vistula River, which has the second largest drainage area of rivers entering the Baltic Sea. Of the two study sites within the Gulf (G1: E 191160 – 191230 , N 541250 –541300 ; G2: E 181540 –191100 , N 541250 –541300 ), G2 was located in proximity to and G1 further away from the Vistula River mouth. The other two sites (G3: E 181400 –181510 ; N 541440 –541510 ; G4: E 171200 –171300 ; N 541500 – 551050 ), i.e., the W"adys"awowskie and Ustecko-"ebskie fishing grounds located outside of the Gulf, were further from possible pollution sources. Based on previous research (Dabrowska et al., 2009; Kopecka et al., 2006), sites G2 and G4 were considered to represent the most and the least contaminated sites, respectively. The salinities were 7.9, 7.5, 7.4, and 7.5 at the bottom at the G1, G2, G3, and G4 sites, respectively. According to guidelines applied in the BEAST project, flounder of the same gender and size, i.e., females of 25–30 cm total length were used for the study to minimize potential effects of gender and size/age on biomarker responses. The fishing was done with a standard rigging ground trawl type TV-3 (mesh size 10 mm in the cod end) with towing time 30 min and towing speed of 3 nautical miles per hour. Only live fish in good condition without mechanical lesions attributable to trawling were selected. They were transported

58° Baltic Sea

57°

56° Baltic Sea

N

in addition to histopathological alterations, other cellular and biochemical biomarkers and chemical contaminants were investigated in flounder from several Polish coastal areas. These biomarkers included the size and density of melano-macrophage aggregates (MMA) in the liver and spleen, expression of proliferating cell nuclear antigen (PCNA) in hepatocytes and of cytochrome P450 1A (CYP1A) in the liver along with histopathological and histomorphometrical alterations. MMAs are focal aggregations of macrophages. It has been suggested that MMAs function as scavengers taking up and decomposing foreign molecules and particles and endogenous cell debris. They also have the ability to recycle iron compounds from aged or damaged red blood cells (Wolke, 1992). MMA proliferation in liver and spleen has been associated with several factors, including aging, infectious diseases, and chemical contaminants (Couillard et al., 1999; Leknes, 2007; Rabitto et al., 2005). PCNA is a nuclear protein required for DNA synthesis and repair. Its expression signals a cell proliferation process. Inhibition or stimulation of cell proliferation could be indicative of a disruption in homeostasis in the cell renewal system (Bravo et al., 1987; Celis and Celis, 1985; Fairman, 1990). The expression of PCNA has been reported to be affected by nutrition (Ostaszewska et al., 2010) and exposure to xenobiotics (Berntssen et al., 1999; Sanden and Olsvik, 2009). CYP1A is the major P450 subfamily, responsive to planar halogenated hydrocarbons [PCDD/Fs, dioxin-like PCBs (dl-PCBs), and polycyclic aromatic hydrocarbons (PAHs)]. The induction of CYP1A, i.e., increased synthesis of protein and related enzymatic activity following exposure to toxicants, forms the basis for the use of CYP1A in environmental monitoring (ICES, 2010). The biomarkers presented in this paper, i.e., the size and density of MMAs in liver and spleen and the density of PCNAresponsive hepatocytes along with liver histopathology lesion scores, were assessed for their relationships with (1) the most common organochlorine (PCBs and DDTs) and metal (Cu, Zn, Cd, Pb, and Hg) contaminants measured in individual specimens, and (2) indices of general liver and body condition, i.e., hepatocyte size, size of hepatocyte lipid droplet area, body condition factor (CF), and hepatosomatic (HSI) and gonadosomatic (GSI) indices, in order to provide information on the role of contaminant effects.

15

55°

G3

G4 GDAŃSK

G2

G1

54° 0 25 50

13°

15°

17°

19°

100 km

21°

E Fig. 1. Collection sites for flounder (Platichthys flesus) in the southern Baltic Sea, including two sites within the Gulf of Gdan´sk, (G1 and G2) and two sites outside the Gulf (G3 and G4). in 120 L tanks filled with aerated water taken from the collection sites and delivered within 10–12 h after trawling to the laboratory. During transportation the water temperature was maintained the same as in the Sea (7–8 1C); the density of fish was 16–18 g dcm3 of water. The fish were sacrificed by a blow on the head; weight and total length were recorded. Then they were dissected, the weight of the liver and gonads were recorded (Table 2), and samples of liver, spleen, muscles, and bile were taken. The biometric data were used to determine the following: (a) the condition factor, CF ¼ [[body mass (g)/(total length)3]  100], (b) the hepato-somatic index, HSI¼ [HW/(BW  HW)  100], and (3) the gonadosomatic index, GSI¼ [GW/(BW GW)  100], where HW—liver mass (g), GW—gonad mass (g), and BW—body weight (g). Each specimen was visually examined for the presence of external and internal diseases and parasites. The liver and spleen samples were processed for histopathological examination according to standard procedures described by Feist et al. (2004). Bile samples were frozen at  80 1C for measurements of PAH metabolites at a later time. Muscle samples were homogenized in a blender and freeze-dried for analyses of the most common organochlorine substances, PCBs and DDT, as well as heavy metals (Cu, Zn, Cd, Pb, and Hg). Reported S7PCBs represent the sum of concentrations of congeners PCB 28, 52, 101, 118, 138, 153, and 180, whereas SDDT is the sum of concentrations of p,p-DDT, o,p-DDE, p,p-DDE, o,p-DDD, and p,p-DDD. The analytical methods used to measure the contaminant levels have been described elsewhere (Dabrowska et al., 2009; Polak-Juszczak, 2009). The limits of quantification (LOQ) of individual PCBs and DDTs were in the range of 0.3–7 ng g  1 lipid. Recoveries from a certified reference material, SRM 1945, were in the range of 91–110% for PCBs and 68–115% for DDTs. LOQs for Cu, Zn, Cd, Pb, and Hg were 0.1, 1, 1, 10, and 1 mg kg  1dry weight, respectively. The metal recoveries from certified reference material (cod muscles) ranged from 97% to 111%. PAH metabolites in bile samples were analyzed using high performance liquid chromatography with fluorescent detection (HPLC-F) according to the method described by Ruczyn´ska et al. (2011. doi: 10.1039/c1em10423c). LOQ for 1-OH pyrene was 0.004 mg ml  1 bile.

2.2. Histology and histomorphometry Samples of liver and spleen were fixed in Bouin’s fixative, dehydrated in a graded series of ethanol, embedded in Paraplast, and cut into 5 mm thick sections using a Leica RM 2265 microtome (Leica Microsystems, Nussloch, Germany). The sections were stained with hematoxylin and eosin for histopathological and histomorphometric examinations. Periodic acid-Schiff was used to stain the glycogen in the liver and diastase was used as a control (Gona, 1979). Spleen and liver sections were also stained with Perls’ Prussian blue stain to examine the tissues for the presence of ferric iron (McManus and Mowry, 1965). Histopathological alterations in liver were qualitatively assessed as shown in Table 1 and categorized as non-specific, nonneoplastic toxicopathic, and pre-neoplastic according to Feist et al. (2004). Depending on the size of the affected tissue area and the degree of cellular change observed, the alterations were evaluated as mild, medium, and severe, and were assigned scoring values as shown in Table 1 (Lang et al., 2006). When more than one lesion category was observed in an individual specimen, the highest value was used in the scoring.

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Histopathological and histomorphometrical examinations were conducted by one examiner blind to a sampling site and involved 15–20 fish per site as shown in Table 2. Histomorphometry included the measurements of (a) the size (i.e., the surface area) of single hepatocytes and of lipid droplet in the hepatocytes, which were measured in 30 areas of 1 mm2 in each fish liver and (b) the size and density of MMAs in the liver and spleen, which were measured in 10 areas of 1 mm2 in each tissue type of each fish. The measurements were made based on images taken by a digital camera (Nikon DS5-U1) connected to a Nikon ECLIPSE 90i microscope and the computer image analysis system NIS-Elements AR (Nikon Corporation, Tokyo, Japan).

2.3. Immunohistochemistry Immunohistochemical examination was conducted in the same individual fish, which were subjected to histology and histomorphometry. Proliferating hepatic cells were identified using antibodies directed against PCNA based on a procedure previously described by Ostaszewska et al. (2008). In short, tissue sections were de-waxed with xylene and rehydrated. Endogenous peroxidase was blocked with a 3% H2O2 solution. The sections were incubated in Tris-buffered saline pH 8 (T-6664; Sigma) for 10 min, followed by incubation with a 1:300 diluted PCNA (clone PC10, Monoclonal Mouse Anti-Proliferating Cell Nuclear Antigen—DAKO M0879) for 1 h at room temperature. This antibody proved its efficacy and specificity for fish tissues in earlier studies (Ostaszewska et al., 2008, 2010). The sections were subsequently incubated in a DAKO Envision System (DAKO EnvisionTM þ/HRP K4006) until a change of color occurred. For negative control sections, the primary antibody was substituted by tris–BSA. PCNA-positive responses were scored for 10 fields of 0.035 mm2 per liver sections and recalculated to yield the number of PCNA-positive hepatocytes per 1 mm2. The scoring included hepatocytes only; it did not include endothelial, bile duct, or pancreatic cells. CYP1A expression was examined using mouse anti-fish (CYP1A) monoclonal antibody (C10-7, Biosence Laboratories AS). Tissue sections were incubated for 16 h at 4 1C in a moist chamber with a 1:100 dilution of antibody. Negative control incubations were performed with the omission of antibody. Immunohistochemistry was performed using Cytomation’s EnVision Systems Peroxidase (DAB), (DAKO, Glostrup, Denmark) according to the procedures described by the manufacturer. The occurrence and intensity of staining was examined by light microscopy. The expression of CYP1A was evaluated in hepatocytes on a scale of four as negative, weak, moderate, or strong.

Table 1 Observed histopathological liver lesions in flounder and scoring system used for their quantification (adapted from Lang et al., 2006). Lesion category

Type of alterations

Stage

Score

No anomaly detected Category 1, non-specific lesions

– Inflammatory change Degenerative change Proliferative change Increased number/area of MMAs

–

0

Mild 1 Medium 2 Severe 3

Category 2, early toxicopathic Nuclear pleomorphism non-neoplastic lesions Hydropic vacuolation Peliosis and spongiosis hepatic

Mild 4 Medium 5 Severe 6

Category 3, Pre-neoplastic lesions

Mild 7 Medium 8 Severe 9

Foci of cellular alteration: Vacuolated Basophilic

2.4. Statistical analysis Analysis started by testing each variable for equality of variance using Leven’s test and, for normality, using the Shapiro–Wilk test. Data for each biomarker,

Table 2 Liver and spleen biomarkers, liver histopthology scores, fish biological characteristics, and chemical contaminants in flounder collected from Polish coastal sites (G1–G4) in the southern Baltic Sea (mean values and SD). Collection site/parameter

G1

G2

G3

G4

Liver biomarkers Hepatocyte area (mm2) Hepatocyte lipid droplet area (mm2) MMA size (mm2) MMA density1 PCNA density ICES (2010) CYP1A expression3 Histopathology score

45.6 7 7.3c 11.00 73.4d 434 7 23b 12.4 7 2.0b 1281 7 217a 3 2.5 72.1a

43.6 78.3d 17.8 74.9c 524 728a 13.6 72.5a 858 7156b 3 1.97 1.2a

60.07 14.4b 22.7 7 6.5b 392 7 28c 11.6 7 2.4c 427 7 90c 1 1.6 72.5ab

71.2 7 13.6a 44.1 7 12.5a 264 7 17d 5.8 7 1.2d 300 748d 1 0.1 70.3b

Spleen biomarkers MMA size (mm2) MMA density1 Perls’ positive cells in MMA4

12727 68c 26.4 7 4.1a 3

2137 7153a 26.3 74.9a 4

1404 7 61b 26.1 7 4.6a 2

718 7 37d 15.2 7 2.8b 1

Biological data N Fish total length (cm) Fish weight (g) Muscle lipids (%) HSI5 GSI5 CF5

20 28.0 7 1.5a 257.7 7 54.1a 2.0 70.8a 2.4 70.4a 8.0 71.9a 1.17 7 0.11a

20 28.3 71.3a 269.5 749.6a 2.87 1.1b 2.27 0.5a 11.07 2.8b 1.17 70.08a

15 28.7 7 1.2a 297.0 7 42.4a 2.6 70.9ab 2.2 70.3a 12.3 7 3.4b 1.25 7 0.09a

17 27.3 7 2.3a 266.6 7 56.6a 2.1 7 0.7ab 2. 7 0.4a 8.8 7 6.0ab 1.25 7 0.14a

Contaminants S7PCB (ng g  1 lipid)6 SDDT (ng g  1 lipid) Cu (mg kg  1)7 Zn (mg kg  1)7 Cd (mg kg  1)7 Pb (mg kg  1)7 Hg (mg kg  1)7 1-OH pyrene in bile8

275 7 68a 368 7 79ab 1.5 70.5a 21.7 7 2.9a 5.8 71.5a 49 717a 338 7 149a 0.06 70.02a

268 758a 486 799a 1.27 0.5a 18.4 72.2b 4.37 2.0ab 487 27a 267 757ab 0.077 0.04a

162 7 71b 206 795bc 1.1 70.3a 18.8 7 2.6b 3.07 0.8b 38 716a 214 7 53b 0.057 0.04ab

74 7 45c 107 7 44c 0.9 70.2b 17.0 7 1.8b 3.6 7 1.8b 36 7 12a 146 7 55c 0.04 70.01b

1 2 3 4 5 6 7 8

Number of MMAs mm2 of tissue. Number of PCNA-positive cells mm2 of tissue. Expression was assessed according to the scale: 0—none/minimal, 1—mild, 2—medium, and 3—strong. Number of Perls’ positive cells in MMAs was assessed according to the scale: 1 ( r5 cells), 2 (5r 10 cells), 3 (10r 20 cells); mg kg  1 dry matter. Formulas for HSI, GSI, and CF calculations are given in Section 2. S7PCB is a sum of concentrations of congeners PCB 28, 52, 101, 118, 138, 153, and 180. Metal concentrations are expressed on a dry mass basis. Pyrene concentrations are expressed as mg ml  1 bile. Values in the same row with the same letter superscript are not significantly different (p o 0.05).

H. Dabrowska et al. / Ecotoxicology and Environmental Safety 78 (2012) 14–21

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chemical contaminant, and biological parameter were then analyzed for differences among the fish groups using one-way ANOVA where variances were homogeneous or by Kruskal–Wallis test for heterogeneous variances. For the assessment of statistical relationships between biomarker responses, chemical contaminant levels, and biological parameters, multivariate statistical analysis was conducted using Principal Component Analysis (PCA). PCA included the biomarker responses and chemical measures for which an initial univariate statistical analysis showed significant relationships. A significance level of 0.05 was applied. The data were auto-scaled in columns, with standard deviation set to 1 and the mean value to 0, and transformed into principal components using Kaiser criteria and varimax rotation. Individual histopathology scores with values of zero were assigned a value of 0.01 to fulfill the PCA requirements. The prevalence of liver lesions and the related 95% confidence intervals were calculated based on bi-nominal distribution. All statistical analyses were performed using Statistica 9.0 (StatSoft Inc, Tulsa, OK, USA).

3. Results 3.1. Biological characteristics of fish The results showed that the average values of biological parameters did not differ significantly among the fish groups, except for GSI and muscle lipids (Table 2) (ANOVA). Thus, the potential effect of size on biomarker responses was negligible. Based on an established age/length relationship for Baltic flounder it can be assumed that the mean age of females examined was four years (Drevs et al., 1999). The CF values were slightly higher in the fish groups from areas G3 and G4 than from G1 and G2; however, the difference was not significant. Visual inspection of fish showed no presence of external or internal parasites in any of the fish. 3.2. Liver

Fig. 2. Liver: (A) MMAs, G1 site, H&E staining, magnification 400  ; (B) vacuolated foci of cellular alteration, G3 site, H&E staining, magnification 200  ; (C) PCNA response, G1 site, magnification 400  ; (D) PCNA response, reference G4 site, magnification 400  ; (E) strong positive CYP1A response, G1 site, magnification 400  ; (F) weak positive CYP1A response, G4 site, magnification 400  .

100

Prevalence (% +/- 95% C.I.)

A normal, homogenous structure of the liver was observed in all specimens from the presumed least contaminated site (G4), except for two specimens showing the presence of non-specific alterations, i.e., lymphocyte infiltrations. Normal liver structure was characterized by the presence of round sinusoids with a thin endothelium surrounded by hepatocytes. The cytoplasm of hepatocytes contained both glycogen and lipids. The exocrine pancreas was present along the portal blood vessel. The pancreatic cells contained acidophilic zymogen granules. Bile ductules and ducts were lined with cuboidal ephitelial cells and supported by a thin layer of connective tissue. Histopatological alterations recorded in fish from all four study sites included the category of non-specific lesions, such as lymphocyte infiltrations of various intensity. An increased number of MMAs (Fig. 2A) were observed in the livers of flounder collected from the presumed contaminated sites G1, G2, and G3, in comparison to those from the G4 site. The G1–G3 livers displayed a range of histopathologies categorized as early toxicopathic non-neoplastic lesions such as hepatocellular/nuclear pleomorphism, peliosis, and hydropic vacuolation of biliary ducts. Relatively few clear cases of lesions categorized as pre-neoplastic lesions were observed in the G1 and G3 livers. These consisted of foci of cellular alterations (FCAs), which were seen in the G3 livers as aggregations of vacuolated hepatocytes (Fig. 2B), and basophilic FCAs, which were more common in the G1 livers. The fish from the G1–G3 sites exhibited marked PCNA and CYP1A expressions in comparison to fish from the G4 site. The density of PCNA-positive hepatocytes and the CYP1A response differed among the sites (Table 2). A significantly higher PCNApositive cell density was found in the G1 fish than in any other group. The CYP1A response was strong in both groups, G1 and G2, collected from inside of the Gulf of Gdan´sk, and mild in the G3 and G4 fish (Table 2). An example of an increased number of PCNA-positive cells in the G1 livers as compared to the G4 livers is depicted in Fig. 2C and D, respectively. CYP1A induction in the

G1 G2

80

G3 G4

60 40 20 0

NA D

1 2 Lesion Category

3

Fig. 3. Prevalence of histopathological liver lesions (the percentage of individuals affected and the 95% confidence intervals). G1–G4 indicate fish collection sites. NAD—no anomaly detected. Lesion categories: 1—non-specific, 2—early toxicopathic non-neoplastic, and 3—pre-neoplastic.

G1 livers and corresponding responses in the G4 livers are shown in Fig. 2E and F, respectively. The prevalence of the observed liver histopathologies, classified into three categories, is shown in Fig. 3. No benign or malignant neoplasms were found in any of the specimens examined. The non-specific liver lesions were the most common

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H. Dabrowska et al. / Ecotoxicology and Environmental Safety 78 (2012) 14–21

category of pathologies observed in all fish groups. It was the only liver histopathology observed in the G4 fish (11.8% prevalence). In fish from the other three sites, apart from a high prevalence of non-specific liver lesions in fish from sites G1 and G2 (both 90% prevalence), the proportion of individuals affected by non-neoplastic toxicopathic lesions did not exceed 20%. Pre-neoplastic lesions were observed only in the G1 and G3 fish, with prevalences of 10% and 13%, respectively. The mean lesion score, which reflects the overall assessment of the affected tissue area and the degree of cellular change, did not differ significantly among the G1–G3 groups. However, the G1 and G2 groups had a significantly higher score than the G3 and G4 fish groups (Table 2). The percentage of individuals with no anomalies detected (NAD) ranged from 0% in the G1 and G2 fish to 88% in the G4 fish (Fig. 3). Significant differences among the sites were found also in histomorphometrical parameters. The average hepatocyte size and hepatocyte lipid droplet size were smallest in the livers from inside the Gulf of Gdan´sk, G1 and G2 fish, and largest in the livers from the G4 site. Both these parameters formed an order of decreasing values as G4 4G3 4G24G1, except that the G2 livers had the smallest hepatocyte size. The average MMA size and density were largest in the G2 livers. These two parameters generally showed an opposite trend to that of hepatocyte and hepatocyte lipid droplet size, i.e., an order of decreasing values as follows: G2 4G14G3 4G4 (Table 2).

3.3. Spleen In spleen, the average size and density of MMA were 2–3 times higher than in livers of the same individuals (Table 2). The values of splenic MMA size reflected the trends of those observed in the liver, being highest in the G2 fish and significantly higher in fish from the G1–G3 sites compared to the G4 site. The MMA density did not differ among the G1–G3 fish groups but it was significantly higher than in the G4 fish. Examples of cross-sections of the spleen of individuals collected from the examined sites are shown in Fig. 4A and B. Perls’ staining indicated that the splenic MMAs of the G1–G3 fish contained high amounts of ferric iron

whereas only minute amounts of this iron form were found in the MMAs of the G4 fish (Fig. 4C and D). 3.4. Associations among biomarker responses and contamination PCA resulted in five PCs with eigenvalues higher than 1.0 (Table 3), which accounted for 73.3% of the variance in the original data set. Variables with a loading coefficientZ0.5 were considered as significant constituents of a PC and those with coefficients in the range of 0.5–0.4 were assumed to be of marginal significance (Comrey, 1973). PC1 accounted for 39.7% of the total variance and represented the relationships between biomarker responses and contaminant levels. The size and density of MMAs in both liver and spleen, the density of PCNA-responsive hepatocytes, and Hg, S7PCB, and SDDT levels, all of them having high negative loadings, were positively associated with each other and negatively related to the indices of general liver condition, i.e., the heptocyte size and the size of lipid droplet area in the hepatocyte (Table 3). PC2, which accounted for 15.7% of the total variance, represented the relationships among fish biological parameters, i.e., weight and total length, lipid content in muscles, and GSI. The grouping of these biological variables into a separate PC indicated that these biological parameters were not influential factors for the biomarker responses. PC3, PC4, and PC5 contributed 6.6%, 6.0%, and 5.3% of the total variance, respectively. Each of these PCs correspondingly contained a significant loading of only one variable, i.e., spleen MMA size, HSI, and CF. HSI and CF, constituting separate PCs, showed no association with the biomarker responses. Histopathology score, having a low significant loading on PC1, showed fair associations with liver and spleen biomarkers and contaminants that loaded on PC1. However, the histopathology score showed also some association with CF on PC5, which is difficult to explain. Metal elements, except for Hg, did not show significant associations with any of the PCs. Their loadings of low significance were distributed among PC1–PC4. The level of 1-OH pyrene in fish bile had no significant loadings on any of the PCs, it was, thus, not considered to be an important factor for any of the biomarkers examined. An initial univariate Table 3 Statistical parameters generated by PCA, describing relationships between liver and spleen biomarkers, histopathology scores, and contaminant concentrations.

Fig. 4. Spleen: (A) reference G4 site, very few and small-size MMAs, H&E staining, scale bar 100 mm; (B) contaminated G2 site, large number and large-size MMAs, H&E staining, scale bar 100 mm; (C) reference G4 site, iron deposition in the MMA, Perls’ staining, scale bar 10 mm; (D) contaminated G2 site, iron deposition in MMA, Perls’ staining, scale bar 10 mm.

Principal component Variance (%) Eigenvalues

1 39.7 9.1

2 15.7 3.6

Fish length Fish weight Muscle lipid content CF HSI GSI Hepatocyte area Hepatocyte lipid droplet area Liver MMA area Liver MMA density PCNA-positive hepatocyte density Spleen MMA area Spleen MMA density Histopathology score 1-OH pyrene in bile Cu Zn Cd Pb Hg SDDT S7PCB

 0.267 0.733 0.331  0.015 0.855 0.294  0.144 0.764  0.171 0.377 0.171  0.078  0.130 0.259 0.236  0.067 0.787 0.038 0.876 0.037 0.194 0.933  0.029  0.093  0.894 0.141  0.329  0.928 0.110  0.159  0.847  0.283 0.226

0.136  0.436  0.024 0.044  0.261 0.022  0.224 0.768  0.668 0.031  0.156  0.087  0.047  0.040  0.092 0.011 0.083 0.062 0.141 0.052  0.108 0.057

 0.738  0.864  0.452  0.307  0.374  0.495  0.322  0.270  0.661  0.851  0.836

0.079 0.147 0.320 0.356 0.015 0.086  0.361  0.464  0.225 10.218  0.132

0.274 0.104 0.016 0.306  0.391  0.485  0.415  0.324  0.025 0.090  0.012

3 6.6 1.5

 0.532  0.074 0.298 0.028 0.137 0.282 0.231  0.468 0.416  0.176 0.103

4 6.0 1.3

5 5.3 1.2

0.027 0.039 0.449  0.192  0.148  0.027  0.193  0.291 0.076 0.066 0.084

H. Dabrowska et al. / Ecotoxicology and Environmental Safety 78 (2012) 14–21

6 3 0 -3 -6 G1

G2

G3

G4

4 2 0 -2 -4

Fig. 5. PCA results: PC1 and PC2 scores for individual specimens (A) and (B), respectively, and a two-dimensional representation of the two PCs differentiating the fish groups (C).

statistical analysis showed no significant relationship between 1-OH-pyrene and CYP1A staining intensity indicating that 1-OH pyrene was not the main factor contributing to the CYP1A response observed in the G1 and G2 fish groups. A graphical presentation of the PC1 and PC2 values corresponding to individual specimens is shown in Fig. 5A and B to visualize the description of the PCs that reflected most of the total variance. The results revealed fairly separated aggregations of specimens, which corresponded to the study sites (Fig. 5C). The G1 and G2 fish groups, while partially overlapping, could be clearly distinguished from the G3 and G4 groups, which were separated from each other. This confirms the differences among the fish groups in respect to biomarker responses and contaminant levels presented in Table 2 and also shows that there was no clear difference between the G1 and G2 groups.

4. Discussion The results from the present study provided evidence that flounder from the study sites differed in their biomarker responses. Based on the spatial pattern of the biomarkers, the sites investigated can be ranked from the most to the least affected as follows: G2ZG1 4G3 4G4. Flounder from the two

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sites located within the Gulf of Gdan´sk (G1, G2) were apparently under greater stress than those collected from the other two areas, the W"adys"awowskie and the Ustecko-"ebskie fishing grounds (G3, G4), i.e., alterations in histopathology and histomorphometry as well as immunohistochemical responses were more pronounced in the former than in the latter two fish groups. Furthermore, the alterations were negligible in flounder from the Ustecko-"ebskie fishing ground (G4), rendering this site as the least affected. There was no clear evidence as to which of the two groups within the Gulf of Gdan´sk was more affected. The prevalence of non-specific and early toxicopathic non-neoplastic liver lesions was at the same level in the fish groups from G1 and G2, whereas pre-neoplastic liver alterations were only observed in the G1 group. In general, the prevalence of histopathological lesions in flounder from the Gulf of Gdan´sk sites was higher than that reported in an earlier study of flounder from the same area (Lang et al., 2006). This increase in prevalence of liver lesions can be associated with seasonal effects, related either to the biological status of the fish or to changes in environmental conditions. According to Koehler (2004) compounded effects of downregulation of NADPH production needed for contaminant detoxification reactions and upregulation of 17-b-estradiol, which is a potent promoter of preneplastic lesions and tumors, during sexual maturation may increase the susceptibility to chemical toxicity in the autumn–winter period. Additionally, the mobilization and depletion of liver lipids during gonadal development can potentially lead to bioamplification of contaminants and enhanced liver toxicity (Debruyn et al., 2004). A seasonal effect was in fact observed in an earlier study, which assessed histopathology in flounder collected in spring and autumn (Lang et al., 2006). When compared with studies of flounder from UK estuaries (Stentiford et al., 2003) and the German Wadden Sea (Koehler, 2004), the histopathological liver lesions observed in our study were less severe in terms of their prevalence and the categories assigned. None of the examined livers showed benign or malignant neoplasms, which were reported by Koehler (2004) to affect 49% of female and 19% of male flounder from German coastal waters of the North Sea. The prevalence of FCAs recorded, a transitional stage, which can lead to neoplasms, ranging from 0% to 13% in the G1–G4 fish, was in the lower range of that reported by Stentiford et al. (2003) and markedly lower than that reported by Koehler (2004). The presence of pre-neoplastic lesions in livers of the G1flounder might suggest that this fish were exposed to higher levels of carcinogenic contaminants than the G2 group, however other biological responses either did not differ, such as the density of MMAs in the spleen, or showed inconsistent trends between the G1 and G2 groups. The inter-site differences in biomarker responses seem to result from differences in the contamination of the respective sites. Some studies reported an influence of fish size and age on biomarker responses (Couillard et al., 1999; Greenfield et al., 2008; Lang et al., 2006). In the present study, fish were selected as relatively uniform size and only females and thus effect of these parameters on studied ones should have been minimized. The conducted multivariate statistical analysis confirmed that the biomarker responses were not related to the fish biological characteristics. Our results showed that the size and density of MMAs were effective indicators of contamination, since they were highly associated with the Hg, S7PCB, and SDDT levels. Extensive evidence from field and laboratory studies indicates a direct association of MMA proliferation with exposure to contaminants (Anderson et al., 2003; Couillard and Hodson, 1996; Couillard et al., 1999; Fournie et al., 2001; Giari et al., 2007; Hanson et al., 2010; Hansson et al., 2006; Rabitto et al., 2005; Schlacher et al., 2007). For example, an increased density of MMAs was observed

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in the European sea bass (Dicentrarchus labrax L.) experimentally exposed to Cd (Giari et al., 2007) and in a field study of several fish species, belonging to the family of Ariidae, Ictaluridae, Sparidae, and Sciaenidae, from contaminated coastal areas in the Gulf of Mexico (Fournie et al., 2001). In the latter study, the size and density of MMAs correlated with concentrations of sediment contaminants, and densities greater than 40 MMAs mm2 of spleen tissue were characteristic for fish from heavily degraded environments. In our study, the splenic MMA density did not differ among the G1–G3 fish groups but was higher than in the G4 fish. Nevertheless, the MMA density in spleen was much lower than that reported by Fournie et al. (2001) in fish from heavily contaminated sites. However, interspecies differences must be taken into account. While the G1–G3 fish groups showed no differences in splenic MMA density, there were differences among all four groups in the MMA density in liver and the MMA size in both tissues, liver and spleen. It was the G1 and G2 fish that showed the highest values for these biomarker responses. The MMA response in these fish was accompanied by comparatively strong hepatic CYP1A expression, higher density of PCNA-responsive hepatocytes, and larger numbers of Perls’ positive cells in splenic MMAs as compared to the G3–G4 fish groups. This finding is consistent with the observation of increased density of MMAs and deposition of hemosiderin in splenic MMAs that was reported in carp (Cyprinus carpio) experimentally exposed to a low dose of 2,3,7,8-TCDD (Van der Weiden et al., 1994). The highest density of PCNA-responsive hepatocytes occurred in the G1 fish, which showed also the presence of preneoplastic liver lesions. However, this type of lesions occurred also in the G3 fish, which showed a significantly lower density of PCNA-responsive hepatocytes. It is interesting to note that an increased proliferation of PCNA was found to be associated with FCAs and other hepatic carcinogenic lesions in flounder from the highly contaminated Elbe River estuary as compared to fish from ¨ areas of low contamination (Kohler and Van Noorden, 1998). Hepatic PCNA proliferation is known to be stimulated by PAHs. In livers of an estuarine fish, the common mummichog (Fundulus heteroclitus), experimentally exposed to benzo(a)pyrene via the diet, an increased cellular proliferation rate was observed, which was accompanied by an intestinal induction of CYP1A activity (Couillard et al., 2009). It can be assumed that aryl hydrocarbon receptor (AhR)-reactive contaminants such as PCDD/Fs, dioxinlike PCBs, and PAHs did play a role in the biological alterations observed in the present study. In addition to the correlations of biomarkers with the Hg, S7PCB, and SDDT levels, the indices of general liver condition, i.e., the hepatocyte size and the size of hepatocyte lipid droplet, showed significant associations with these contaminants. These relationships are consistent with the general hypothesis of adverse biological effects elicited by contaminants. However we found a negative relationship between the contaminant burden and the indices of general liver condition, no effect on the fish CF was apparent. Negative effects of contaminant burden on general condition of fish (including CF) have been reported in a number of studies for various fish species (e.g. Hanson et al., 2010; Kleinkauf et al., 2004; Kopecka et al., 2006). In a study of the Sacramento splittail (Pogonichthys macrolepidotus), negative relations between general health indicators and histopathology such as MMAs in gonads were observed. However, the correlations between histopathology and tissue contaminant concentrations were found to be weak and negative, this being attributed to variability in lipid content (Greenfield et al., 2008). In conclusion, for the evaluation of the relationships between biomarker responses and contaminant load, an effort to account for some of the biological factors (i.e., gender, size, and age) was undertaken in order to obtain meaningful and standardized data

that can be used for the environmental assessment of the study sites. These relationships strongly suggest that the biomarker responses were indicative of biological effects of contaminants. The study shows that biomarkers provide useful tools to demonstrate the effects of pollution on marine organisms, and they offer an adequate approach to take part in integrated monitoring and assessment programs including challenges introduced by the Marine Strategy Framework Directive.

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