Investigating the potential impact of polycyclic aromatic hydrocarbons (PAHs) and polychlorinated biphenyls (PCBs) on gene biomarker expression and global DNA methylation in loggerhead sea turtles (Caretta caretta) from the Adriatic Sea

Investigating the potential impact of polycyclic aromatic hydrocarbons (PAHs) and polychlorinated biphenyls (PCBs) on gene biomarker expression and global DNA methylation in loggerhead sea turtles (Caretta caretta) from the Adriatic Sea

Science of the Total Environment 619–620 (2018) 49–57 Contents lists available at ScienceDirect Science of the Total Environment journal homepage: w...

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Science of the Total Environment 619–620 (2018) 49–57

Contents lists available at ScienceDirect

Science of the Total Environment journal homepage: www.elsevier.com/locate/scitotenv

Investigating the potential impact of polycyclic aromatic hydrocarbons (PAHs) and polychlorinated biphenyls (PCBs) on gene biomarker expression and global DNA methylation in loggerhead sea turtles (Caretta caretta) from the Adriatic Sea Paolo Cocci a, Gilberto Mosconi a, Luca Bracchetti a, John Mark Nalocca a, Emanuela Frapiccini b, Mauro Marini b, Giovanni Caprioli c, Gianni Sagratini c, Francesco Alessandro Palermo a,⁎ a b c

School of Biosciences and Veterinary Medicine, University of Camerino, Via Gentile III Da Varano, I-62032 Camerino, MC, Italy Institute of Marine Sciences (CBR-ISMAR), National Research Council, Largo Fiera della Pesca 2, 60125 Ancona, AN, Italy School of Pharmacy, University of Camerino, Via Sant'Agostino 1, I-62032 Camerino, MC, Italy

H I G H L I G H T S

G R A P H I C A L

A B S T R A C T

• Plasma levels of PCBs and PAHs were detected in Adriatic loggerheads. • Associations between 3 gene biomarkers assessed and plasma levels of some PAH congeners were found. • Global DNA methylation was positively correlated with selected PAH congeners and total PAHs. • Whole blood cell expression of gene biomarkers as strategy for assessing POPs impact on sea turtles.

a r t i c l e

i n f o

Article history: Received 21 July 2017 Received in revised form 7 November 2017 Accepted 9 November 2017 Available online xxxx Editor: Kevin V. Thomas Keywords: Caretta caretta Adriatic Sea PAH PCB

a b s t r a c t Polycyclic aromatic hydrocarbons (PAHs) and polychlorinated biphenyls (PCBs) are priority contaminants that bioaccumulate through the food webs and affect the biology of a variety of resident and migratory species, including sea turtles. Few studies have evaluated toxicological biomarkers of exposure to PAHs and PCBs in these animals. The present paper reports the results of an initial field study to quantify the association between plasma concentrations of PAHs/PCBs and whole blood cell expression of gene biomarkers in juvenile loggerhead sea turtles (Caretta caretta) rescued along the Italian coasts of the northern and central areas of the Adriatic Sea. While detectable levels of PAHs were found in all plasma samples examined, only three PCB congeners (PCB52, PCB95, and PCB149) were noted, with detection percentages ranging between 48% and 57%. A significant correlation was found between 3 of the 6 gene biomarkers assessed (HSP60, CYP1A and ERα) and plasma levels of some PAH congeners. In contrast, no significant association between PCB burden and gene expression was observed. The global DNA methylation levels were significantly and positively correlated with the concentrations of most of the PAHs and only one of the PCB congeners (PCB52).

⁎ Corresponding author at: School of Biosciences and Biotechnologies, University of Camerino, Via Gentile III Da Varano, I-62032 Camerino, MC, Italy. E-mail address: [email protected] (F.A. Palermo).

https://doi.org/10.1016/j.scitotenv.2017.11.118 0048-9697/© 2017 Elsevier B.V. All rights reserved.

50 Biomarkers Gene transcription

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The relation between PAH concentration and gene expression in whole blood cells suggests that these genes may respond to environmental contaminant exposure and are promising candidates for the development of biomarkers for monitoring sea turtle exposure to persistent organic pollutants (POPs). © 2017 Elsevier B.V. All rights reserved.

1. Introduction Polycyclic aromatic hydrocarbons (PAHs) and polychlorinated biphenyls (PCBs), two of the most ubiquitous and predominant classes of persistent organic pollutants (POPs), reflect human activities in marine and coastal environments (Field and Sierra-Alvarez, 2008; Perugini et al., 2007). PAHs are released by natural events such as volcano activity and forest fires, as well as by such anthropogenic sources as waste, sewage, and industrial and agricultural outfalls (Zychowski and Godard-Codding, 2017). On the contrary, no known natural sources of PCBs exist and, once released in the environment, they can last for decades because of their persistence and slow degradation (Grossman, 2013). The North Adriatic basin is particularly vulnerable to the bioaccumulation of both PCBs and PAHs due to the physical-chemical properties and ecological processes that mark this area (Annibaldi et al., 2015; Korlevic et al., 2015; Marini et al., 2008; Pavoni et al., 2003). Previous studies have shown the widespread presence of these contaminants along the eastern coasts of Italy (Manodori et al., 2006; Pavoni et al., 2003). In this regard, we recently monitored the seawater PCB and PAH concentrations in a coastal area of the central Adriatic Sea, finding moderate to high contamination levels of PAHs (Cocci et al., 2017a; Taffi et al., 2014). PAHs and PCBs are considered priority contaminants that can bioaccumulate and biomagnify across marine ecosystems (Frapiccini et al., 2017; Perugini et al., 2013; Taffi et al., 2014), affecting the biology of a variety of marine organisms (Rodriguez-Hernandez et al., 2017), including loggerhead sea turtles (Caretta caretta, Linnaeus 1758) (D'Ilio et al., 2011). PAHs and PCBs move through the food chain in different ways: PAHs biodilute, perhaps because of their potential rapid metabolism and elimination (Amiard-Triquet and Rainbow, 2011; Takeuchi et al., 2009), while PCBs bioaccumulate. The well-known toxic effects of PAHs and PCBs on wildlife range from carcinogenicity to immunosuppression, liver damage, and endocrine disruption (Collier et al., 2014; Olenycz et al., 2015; Zychowski and Godard-Codding, 2017). Their mechanisms of toxicity involve a variety of molecular initiating events and pathways, including modulation in target gene expression (e.g. steroid hormone, antioxidant and detoxification genes) and DNA methylation (Cocci et al., 2017c; Dupuy et al., 2014; Mortensen and Arukwe, 2007; Ruiz-Hernandez et al., 2015; Spromberg and Meador, 2005). Changes in gene expression of Estrogen Receptors (ERs), Cytochrome P4501A (CYP1A) and heat-shock proteins (HSPs) have been found to be sensitive biomarkers of environmental exposure to PCBs and PAHs in different fish species (Cocci et al., 2017a; Huang et al., 2016; Mahmood et al., 2014). Moreover, exposure to selected PAHs was found to affect both gene-specific and global DNA methylation in zebrafish (Fang et al., 2013). Ecotoxicological studies on marine wildlife have shown the usefulness of biomarkers, which can serve as indicators of PAH/PCB exposure and elucidate potential underlying mechanisms (Cocci et al., 2017a,c; Sarkar et al., 2006; Viarengo et al., 2007). Concerning sea turtles, alarming levels of POPs, including PAHs, PCBs and organochlorine pesticides (OCPs), have recently been found in live loggerheads, suggesting that these pollutants are a real threat to sea turtle conservation (Bucchia et al., 2015; Camacho et al., 2012, 2013, 2014; Hamann et al., 2010; Keller et al., 2004a; Novillo et al., 2017). However, there is evidence that PAHs and PCBs are consistently the predominant POPs (in concentration) in sea turtles from distinct geographic areas. In this regard, it has been demonstrated that regional geographic

differences in pollution correlate to differing PAH/PCB concentrations detected in sea turtles, with higher levels of exposure found in individuals rescued in the northern Adriatic Sea, which is a semi-closed and highly anthropized basin (Bucchia et al., 2015; Lazar and Gracan, 2011; Lazar et al., 2011). Interestingly, the northern and middle Adriatic Sea, with its shallow water and rich benthic communities, is a major feeding habitat for turtles in the demersal stage (Lucchetti et al., 2016). These turtles, especially juvenile specimens, show strong fidelity to these specific foraging areas (Casale et al., 2012). In fact, tag returns (Casale et al., 2007) and satellite tracking data (Casale et al., 2012) have demonstrated the long-term permanence of juveniles in the neritic area. Overall, the North Adriatic Sea can be considered an important developmental area for juvenile loggerheads which then move southward along the Italian coast by taking advantage of favorable currents (Casale and Margaritoulis, 2010). Although the number of studies monitoring the effects of pollution in sea turtles continues to increase, contributing to the definition of the baseline levels of these contaminants, only limited information is available on the potential mechanisms by which PAHs and PCBs affect these species. It has been shown that bioaccumulation of PAHs results in hematological changes in both juvenile and nesting population of loggerhead sea turtles (Camacho et al., 2013; Casal and Oros, 2009; Lutcavage et al., 1997). Similarly, high PCB concentrations were found to correlate with certain biochemical parameters of blood (Camacho et al., 2013), and possibly to contribute to causing anemia in sea turtles (Keller et al., 2004b). However, few studies have evaluated the toxicological biomarkers of exposure to PAHs and PCBs in sea turtles. Thus, the present study aimed to determine PAH and PCB concentrations in the blood (collected in a non-lethal manner) of loggerhead turtles rescued along the Italian coasts of the northern and middle Adriatic Sea, and to investigate the relationship between pollutant burden levels and whole blood mRNA abundance profiles of gene biomarkers involved in physiological mechanisms such as chemical detoxification (CYP1A), the immune and endocrine systems (Interleukin 1β (IL-1β) and ER α), respiratory pathways (cytochrome c oxidase subunit 1 (COI)) and stress response (HSP60, 90). Gene expression data provide quantitative information at the molecular level that can be used for early detection of biological disturbance and serious health risk associated with environmental contamination. There may be many benefits to using blood as a target tissue for evaluating molecular biomarkers that indicate potential pathological changes in other organs of the body due to systemic exposure (Morey et al., 2016), especially in endangered species. Significant positive correlations between gene biomarker expression in blood cells and contaminant exposure have recently been found in different turtle species, in both in vivo and in vitro studies (Cocci et al., 2017b; Drake et al., 2017). We also investigated whether loggerhead exposure to PAHs/PCBs is associated with altered levels of global DNA methylation, in order to examine the potential correlation of a single epigenetic endpoint with marine pollutants in this reptilian species. 2. Material and methods 2.1. Sampling In the present study, we selected 20 live immature loggerhead sea turtles found entangled in fishing nets or cold-stunned along the Italian coasts of the northern and middle Adriatic Sea (Fig. 1) between 2014

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Fig. 1. Loggerhead turtle rescue locations arranged according to the carapace length of each specimen.

and 2015. All the stranded animals were rescued and brought to the regional center for the Care and Rehabilitation of Sea Turtles (Fondazione Cetacea onlus, Riccione, RN, Italy) for a complete clinical evaluation. Sea turtles with traumatic injuries (for example, from boat strikes) or eye/ skin diseases were not enrolled in the study. Whole blood samples (5 mL) were drawn from the cervical sinus (Owens and Ruiz, 1980) using 6 mL syringes with a 20-gauge 3.8 cm needle (Cocci et al., 2017b; Flower et al., 2015) and placed into a lithium heparin vacutainer blood collection tube. Virtually, all of the blood samples were taken within 10 min of contacting each animal. Subsequently, samples were centrifuged at 1000 × g for 15 min at 4 °C to separate out the plasma for PAH and PCB analyses. All nucleated blood cells (white blood cells (WBCs) and red blood cells (RBCs)) were used for the measurement of mRNA abundance profiles and stored at − 80 °C until isolation of total RNA. The procedures carried out on the turtles caused them no distress, and were performed in accordance with routine veterinary practice and guidelines for conservation and rehabilitation of marine turtles (ISPRA, 2013). 2.2. Determination of PAHs and PCBs Plasma samples (2 mL) were mixed with 10 mL of hexane. The mixture was vortexed for 20 s, centrifuged at 3000 rpm for 5 min and frozen at −80 °C. The pellet was discarded and the supernatant was evaporated to dryness using a vacuum centrifuge (Thermo SpeedVac, Genevac). Samples were maintained at −80 °C prior to analysis by GC–MS or HPLC system. This sample preparation procedure allowed the extraction of lipophilic compounds including PAHs and PCBs that could be present in the plasma (Pleil et al., 2010; Schoeters et al., 2004; Valdehita et al., 2012). Plasma extracts were analyzed for concentrations of 18 PCB congeners identified by their IUPAC number (PCB28, 52, 95, 99, 101, 105, 110, 118, 138, 146, 149, 151, 153, 170, 177, 180, 183, 187) and 15 of the most environmentally relevant PAHs (Naphthalene, Acenaphthene, Fluorene, Chrysene, Phenanthrene, Fluoranthene, Anthracene, Pyrene, Benzo[a]anthracene, Benzo[b]fluoranthene, Benzo[k]fluoranthene, Benzo[a]pyrene, Dibenz[a,h]anthracene, Benzo[g,h,i]perylene and

Indeno[1,2,3-c,d]pyrene). The detailed methodology for separation and quantification of target analytes was published previously (see “Supplementary data” of Cocci et al., 2017a). For the analysis of PCBs, linearity was tested by injecting five different dilutions of standard mixtures of the 18 PCBs studied. Calibration curves based on the peak area of the standard concentration were obtained and correlation coefficients ranged from 0.9960 to 0.9999. SIM ions, time conditions for each PCB congener and limit of detection (LOD)/limit of quantification (LOQ) were reported in Table S1 and S2, respectively. For the analysis of PAHs, a calibration solution was prepared for the standard PAH solution (EPA 610 Mix) by serial dilutions (1:50, 1:100, 1:200 and 1:400 v/ v). The efficiency and the accuracy of the analytical procedures were tested using different reference materials (IAEA-406 and IAEA-432) and the recovery fell within the confidence interval (95%). The LODs and the LOQs were calculated according to ICH Q2B (ICH, 2005) and reported in Table S3. 2.3. Quantitative real time PCR (q-PCR) Total RNA was extracted using the Trizol™ LS reagent (Invitrogen; Life Technologies) according to the manufacturer's instructions. DNase digestion (2 U, 30 min, 37 °C; Ambion®; Life Technologies) was performed to eliminate genomic DNA contamination. RNA concentration and purity were assessed spectrophotometrically at absorbances of 260/280 nm, and the integrity was confirmed by electrophoresis through 1% agarose gels stained with ethidium bromide. The complementary DNA (cDNA) was synthesized from 2 μg of total RNA in 20 μL of total volume reaction using random hexamers (50 ng μL−1) and 200 U of SuperScript™ III RT according to manufacturer's instruction (Invitrogen; Life Technologies). Absolute quantitative SYBR green-based real time PCR with genespecific primer pairs (Table 1) was used for evaluating transcription profiles of individual ERα, CYP1A, HSP60, HSP90, IL-1 and COI target genes using a Mx3000P™ Real Time PCR System (Stratagene) as previously described (Arukwe, 2006; Cocci et al., 2017b). All the CYP1A, IL-1 and COI primer sequences were designed using Primer3 software (http://bioinfo.ut.ee/primer3-0.4.0/) according to the Caretta caretta

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Table 1 List of primers used in this study. Gene

Primer sequence (5′-3′)

Genebank

Efficiency (%)

ERα CYP1A

ACAGCTCTCACCCTTCATCC TCATCCCAAAGCTGCTCTGA CGGTATGTGGTGGTCTCTGT ACATCCCCAAATTCCTCCGT TACTGATGCACTGAACGCT TGGCGTTAAAGCATCTAGTG GGATACTGGCATAGGGATG CAACACCAAACTGACCAATC GGTGCATTTGGAGAAGTGGG CAGCTCAAAATGATCCCCGG CGTTATCGTCACAGCCCATG TCCGAAGCCACCGATTATGA

EF577057 HQ293214

98.3 ± 2.9 96.4 ± 3.3

KJ683735

100.7 ± 2.9

KJ683737

101.4 ± 3.2

EU407254

96.8 ± 3.8

GQ152888

102.8 ± 3.2

HSP60 HSP90 IL-1 COI

gene specific sequences (Table 1). Primer sequences for HSP60, HSP90 and ERα were provided from Tedeschi et al. (2015) and Cocci et al. (2017b). The reaction included: 12.5 μL 2 × qSTAR SYBR Master Mix Kit (OriGene Technologies), 1 μL each of forward and reverse primers (both 10 μmol L−1), 1 μL cDNA template, and sterile distilled water to a final volume of 20 μL. Thermo-cycling for ERα, HSP60, HSP90 reactions was for 10 min at 95 °C, followed by 40 cycles of 15 s at 95 °C and 45 s at 57 °C. Thermo-cycling for CYP1A, IL-1 and COI reactions was for 10 min at 95 °C, followed by 40 cycles of 15 s at 95 °C and 30 s at 58 °C. Fluorescence was monitored at the end of every cycle. Melting curve analysis, conducted monitoring the fluorescent signal during temperature increase from 57 °C to 95 °C, demonstrated that a single amplicon encompassing the region of interest was generated during each amplification reaction. The efficiency of reactions was determined by performing real time PCR on serial dilutions of cDNA (Table 1). The cycle threshold (Ct) values thus obtained were converted into mRNA copy number using standard plots of Ct-value versus log copy number through the appropriate Strategene software provided with the Mx3000P™ Real Time PCR System. The standard plots were generated for each target sequence using serial dilution of known amounts of the amplicon of interest, as described by Arukwe (2006). Data obtained from triplicate runs for individual target cDNA amplification were averaged and expressed as initial copy number. This absolute quantification method is a well-documented procedure for testing modulation of gene expression following exposure to endocrine disruptors (Adeogun et al., 2016; Cocci et al., 2017a,b; Mortensen and Arukwe, 2007; Olufsen et al., 2014; Regoli et al., 2011). In addition, absolute quantification of gene expression avoids difficulties associated with the selection of optimal housekeeping genes. In fact, evaluation of suitability of common reference genes requires additional experiments that are difficult to conduct in field studies with endangered species. 2.4. Global DNA methylation Genomic DNA was isolated from whole blood cells of each loggerhead examined using Trizol™ LS reagent (Invitrogen; Life Technologies) according to the manufacturer's instructions. DNA samples were treated with RNase A (Qiagen) at 37 °C for 1 h to remove RNA contamination. The DNA concentration and the quality of samples were assessed by spectrophotometry and agarose gel electrophoresis. Quantification of global DNA methylation was examined using the colorimetric MethylFlash™ Methylated DNA Quantification Kit (Epigentek Group Inc.) following the manufacturer's instructions. The analysis was performed in duplicates with 100 ng of genomic DNA per sample. Briefly, DNA was bound to strip wells that were specifically treated to have a high DNA affinity. The methylated fraction of DNA was detected using capture and detection antibodies and then quantified colorimetrically by reading the absorbance (450 nm) in a microplate spectrophotometer and using a standard curve. The percentage of methylated cytosines (5mC) was calculated using the following formula described by the

manufacturer:

5−mCð%Þ ¼

Sample OD‐ME3 OD ðSlope  2Þ  S

*OD is optical density. ME3 is the negative control. 2 is a factor to normalize 5-mC in the positive control to 100%. S is the amount of input sample DNA in ng.

2.5. Statistical analyses Because the blood analytes (PAHs, PCBs, gene biomarker expression and global DNA methylation levels) were not normally distributed, we measured the strength and direction of association between our variables using Spearman and Kendall correlation tests. Statistical significance was based on p-values ≤ 0.05 (two-tailed). All statistical analyses were performed with the R software (http://www.R-project. org/) using the functions from the package corrplot (Wei, 2012).

3. Results 3.1. Morphometric data of loggerhead turtles The mean and standard deviation of the curved carapace length (CCL) of the sea turtles were 46.44 ± 14.71 cm. According to the size distribution of Mediterranean loggerheads, all sea turtles examined in the current study were identified as juveniles, since on average, Mediterranean loggerhead turtles mature at a size N 70 cm CCL (Casale et al., 2011, 2005; Cocci et al., 2014; Margaritoulis et al., 2003). Interestingly, there was no correlation between sea turtle size and plasma levels of PAHs or PCBs.

3.2. Plasma contaminant concentrations Detectable levels of PAHs were found in all plasma samples examined (Table 2). Benzo[b]fluoranthene was detected in 100% of the turtles analyzed, followed closely by Naphthalene and Anthracene (99% of the plasma samples). Although eighteen PCB congeners were analyzed, only three of them (PCB 52, PCB 95, and PCB 149) were detected in the samples analyzed, with percentages of detection ranging from 48% to 57% (Fig. 2). The PCB congener detected at the highest level (0.55 ng mL−1) was PCB 95, a chiral PCB. Overall, sea turtles were most consistently contaminated by PAHs; concentrations of the total PAHs (ΣPAHs) ranged from 1 to 91 ng mL−1 (median ΣPAHs: 16.97 ng mL− 1). On the contrary, we found lower levels of plasma PCBs (median ΣPCBs: 0.18 ng mL−1) in the sea turtle population examined.

P. Cocci et al. / Science of the Total Environment 619–620 (2018) 49–57 Table 2 PAH levels (ng mL−1) in plasma samples from loggerhead turtles from Italian coasts of the northern and middle Adriatic Sea. PAHs

Mean ± SD

Median (range)

Naphthalene Acenaphthene Fluorene Phenanthrene Fluoranthene Anthracene Pyrene Benzo[a]anthracene Benzo[b]fluoranthene Benzo[k]fluoranthene Benzo[a]pyrene Chrysene Dienzo[a,h]anthracene Indeno[1,2,3-c,d]pyrene Benzo[g,h,i]perylene ΣPAHs ΣLMW-PAHs ΣHMW-PAHs

3.82 ± 5.44 24.03 ± 28.25 4.83 ± 3.59 1.17 ± 0.77 1.04 ± 1.46 0.48 ± 0.33 0.56 ± 0.67 1.79 ± 1.59 0.40 ± 0.16 0.79 ± 0.51 0.24 ± 0.21 0.06 ± 0.09 1.73 ± 2.12 0.07 ± 0.10 0.51 ± 0.41 41.45 ± 36.58 34.32 ± 34.12 7.13 ± 4.58

1.21 (bLOD-17.61) 0.00 (bLOD-73.99) 3.81 (bLOD-10.23) 1.02 (bLOD-2.84) 0.00 (bLOD-5.13) 0.44 (bLOD-1.50) 0.00 (bLOD-1.64) 1.16 (bLOD-5.12) 0.38 (0.22–0.94) 0.96 (bLOD-1.43) 0.19 (bLOD-0.56) 0.00 (bLOD-0.27) 1.78 (bLOD-8.42) 0.00 (bLOD-0.29) 0.50 (bLOD-1.16) 16.97 (0.98–90.87) 8.82 (0.25–84.55) 6.18 (0.73–16.85)

3.3. Biomarker expression by qPCR and DNA methylation The relationship between biomarkers and plasma levels of PAHs/ PCBs showed varying results, including both positive and negative correlations (Fig. 3). According to both Spearman and Kendall analyses, 3 of the 6 gene biomarkers assessed (HSP60, CYP1A and ERα) and 5-mC had the higher correlations with PAH/PCB concentrations. In particular, we noted several positive correlations between HSP60 transcript levels and specific PAH congeners (Naphthalene, Fluoranthene, Benzo[a]Anthracene, Benzo[k]Fluoranthene and Indeno[1,2,3c,d]pyrene). On the contrary, both CYP1A and ERα were positively associated with only a single PAH congener: Naphthalene and Benzo[g,h,i]perylene, respectively. In contrast, no significant associations between PCB burdens and gene expression were observed. The global DNA methylation levels were significantly and positively correlated with most of the PAH congeners and ΣPAH concentrations (Fig. 3). In addition, a positive correlation between global DNA methylation and PCB52 was noted. Among all biomarkers tested in our study, 5-mC showed the most significant association with total PAHs (Spearman's r = 0.74, p = 2 × 10−4; Kendall's r = 0.59, p = 3 × 10−4).

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4. Discussion 4.1. PAH and PCB contamination levels In this work, average ∑PAH and PCB concentrations for loggerhead sea turtles from the northern and middle Adriatic Sea fell substantially within the range observed across different locations around the world, including the Mediterranean basin (Camacho et al., 2013, 2014; Lazar et al., 2011; Storelli et al., 2007; Storelli and Zizzo, 2014). Also, except for PCBs, our PAH results are consistent with those recently reported for Adriatic Sea turtles (Bucchia et al., 2015). In fact, high concentrations of PAHs were detectable in all samples examined, with a high prevalence of low molecular weight (LMW)-PAHs. This finding is in line with recent studies that report very similar PAH distribution patterns in sea turtles, suggesting potential correlation with PAH levels in the external environment (Bucchia et al., 2015; Camacho et al., 2013). In this regard, we previously reported high levels of sea water LMW-PAHs (Naphthalene) in a coastal area of the central Adriatic Sea (Cocci et al., 2017a). Indeed, the northern and middle Adriatic Sea, particularly the Italian Adriatic coast, along which most of the sea turtles examined in the present study were rescued, is characterized by the presence of several rivers from the Po Valley, by transitional areas such as the Venice Lagoon, by intensive maritime traffic and commercial vessels which, combined with atmospheric depositions, concur to increase the level of pollution, including PAH contamination (Manodori et al., 2006; Marini and Frapiccini, 2014; Secco et al., 2005). All this probably is the major cause of PAH contamination in Adriatic Sea turtles which, according to Lucchetti et al. (2016) and to satellite tracking data, reside and spend the whole year in the Adriatic. In addition, since marine organisms at higher trophic levels have been suggested to be capable of efficiently metabolizing PAHs (Wan et al., 2007), we cannot exclude that the concentrations found in the present study were caused by recent exposure to these toxicants. It is likely that sea turtles are able to extensively metabolize xenobiotics, including PAHs, as do other vertebrates (Ylitalo et al., 2017). Nevertheless, several studies have demonstrated that LMW-PAHs are less efficiently metabolized than high molecular weight (HMW)-PAHs (Jonsson et al., 2004; Troisi et al., 2006; Varanasi et al., 1993; Varanasi and Gmur, 1981). Regarding PCBs, plasma levels observed in our study population were much lower than those reported by Bucchia et al. (2015) in Adriatic Sea turtles. In fact, the median ∑ PCB value obtained in the present study was very similar to that found in loggerheads from the Canary Islands (Camacho et al., 2013). In addition, we found a totally different PCB profile, with a higher concentration of PCB 95 compared to that of marker PCBs. A previous study found both PCB 95 and 149 in liver samples of cetacean species found stranded along the Italian coasts (Jimenez et al., 2000). This finding is particularly interesting because it demonstrates the presence of chiral PCBs in sea turtles, suggesting the need to investigate the biological activity of these compounds, whose uptake and metabolism by aquatic organisms may be enantiomerselective (Faller et al., 1991; Reich et al., 1999). 4.2. Relation between gene biomarkers in whole blood cells and PAH/PCB plasma levels

Fig. 2. PCB (ng mL−1) plasma concentrations in loggerhead turtles from Italian coasts of the northern and middle Adriatic Sea.

Although several toxicological studies on the potential detrimental effects of oil exposure have been carried out in sea turtles (Hall et al., 1983; Milton et al., 2003; Witham, 1978), the present paper reports an initial field study to quantify the association between plasma concentrations of PAHs/PCBs and expression of biomarker genes in whole blood of juvenile loggerhead sea turtles. Several correlations were observed between individual PAH congeners and CYP1A, HSP60, and ERα. CYP1A expression increased with higher concentrations of Naphthalene. Although the association between CYP1A1 expression and dioxin-like compounds has been previously described in humans and experimental animals, little is known about CYP1A gene induction in

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Fig. 3. Spearman's (A) and Kendall's Tau-b (B) rank color-coded correlation matrices of relationships between PAH/PCB levels (ng mL−1) and gene biomarkers (copy number) or global DNA methylation (% 5-mC) in analyzed loggerhead samples. The colors of the scale bar denote the nature of the correlation with 1 indicating perfect positive correlation (dark blue) and −1 indicating perfect negative correlation (dark red) between two parameters. Size corresponds to strength of correlation. Correlations marked with circles were significant at p b 0.05(black) or at p b 0.01 (red). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

whole blood cells. Furthermore, induction of CYP1A has been mostly studied using liver ethoxyresorufin-O-deethylase (EROD) activity, rather than gene expression, as a marker of exposure to PAHs. CYP1A upregulation was commonly observed in different species of fish sampled or caged in polluted sites (Malmstrom et al., 2004; Valdehita et al., 2012). In addition, a significant induction of CYP1A gene expression was also reported in fish hepatocytes exposed to benzo[α]pyrene (B[a]P) (Choi et al., 2012). PAHs, in particular high levels of Naphthalene, have been suggested to play an important role in the CYP1A induction observed in cultured rainbow trout (Valdehita et al., 2012). Interestingly, CYP1A1 was induced by β-naphthoflavone in cetacean fibroblast cell cultures (Godard et al., 2004). Similarly, the CYP1A5 isoform was found to be up-regulated in loggerhead skin fibroblasts following exposure to B[a]P (Webb et al., 2014). Overall, these findings indicate that the CYP1A gene plays a key role in xenobiotic metabolism in sea turtles, supporting our suggestion that CYP1A expression might be upregulated in loggerheads with higher Naphthalene concentrations. Correlation between PAH congeners and HSP60, a gene typically located in the mitochondrial compartment, was also found. Genes involved in oxidative stress have been widely investigated as potential sublethal biomarkers of toxicant effects in aquatic organisms. In this regard, we have recently reported that exposure to environmental contaminants

increases HSP60 gene expression in primary loggerhead erythrocytes (Cocci et al., 2017b). Previous studies have correlated induction of HSP60 with toxic stress in nematodes, mussels and fish (Kammenga et al., 1998; Sanders and Martin, 1993; Sanders et al., 1994). To our knowledge, the potential relationship between HSP60 expression and some PAH congeners has never been reported in any animal models, much less specifically in loggerheads. The dearth of studies investigating potential relationships between PAH levels and oxidative stress transcriptional biomarkers in reptiles makes it difficult to compare our findings with others and to suggest potential mechanisms of toxicity. However, it may be possible that the elevated expression of HSP60 gene serves as a mechanism to compensate for the mitochondrial functional alterations due to the PAH-induced mitochondrial oxidative stress response. Previous studies have shown the mitochondriaspecific functions of HSP60 (Sarangi et al., 2013), further supporting the key role of chaperones in mitochondrial protein homeostasis (Bie et al., 2011; Voos and Rottgers, 2002). The cross-talk between mitochondrial activity and oxidative stress biomarkers in response to pollutants is an intriguing mechanism in sea turtles and deserves further investigation. Regarding the influence of PAHs on endocrine pathways, we found a positive association between ERα gene expression and

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Benzo[g,h,i]perylene plasma levels. Interestingly, we have recently shown that loggerhead erythrocytes constitutively express a functional signaling ERα that can respond to estrogen-like environmental contaminants (Cocci et al., 2017b). Several studies have suggested that PAHs or their metabolites can act on ER-mediated activity, showing both antiestrogenic and estrogenic properties (Abdelrahim et al., 2006; Arcaro et al., 1999; Fertuck et al., 2001; Gozgit et al., 2004; van Lipzig et al., 2005). In addition, recent reports have observed PAH-related estrogenic activity in both in vivo and in vitro models (Abdelrahim et al., 2006; Kummer et al., 2008; Tsai et al., 2004), clearly indicating that the impact of environmental PAHs on ER signaling still remains to be clarified. 4.3. Relation between global DNA methylation level in whole blood and PAH/PCB plasma concentrations

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Acknowledgments The authors would like to thank the staff of Sentina Natural Regional Reserve (Italy), and people from regional center for Care and Rehabilitation for Sea Turtles (Fondazione Cetacea onlus, Riccione, RN, Italy), especially Valeria Angelini and Sauro Pari, for their help during sampling of turtles. This study was conducted within the “D.G.R. 563/08/D.G.R. 664/08—Adesione protocollo intesa piano azione nazionale conservazione tartarughe marine PATMA (agreement for a national Action Plan for marine turtle conservation) - Approvazione accordo per istituzione rete regionale per la conservazione delle tartarughe marine (Regional marine turtle conservation arrangement-Marche Region, Italy)”. We would also like to thank Sheila Beatty for editing the English usage in the manuscript. Appendix A. Supplementary data

In the present study, we found that PAH levels were widely associated with global DNA hypermethylation. Moreover, there was also a significant correlation between global hypermethylation and exposure to PCB52. Thus, our findings, which reveal relationships between PAH/ PCB plasma concentrations and epigenetic mechanisms in sea turtle whole blood cells, indicate the need for further study. In contrast to our work, current evidence shows that most POPs are associated with a decreasing trend in global DNA methylation level (Itoh et al., 2014; Kim et al., 2010; Rusiecki et al., 2008). Similarly, a negative relationship between global DNA methylation and trace element concentrations (i.e. THg) was found in alligators living in highly polluted areas (Nilsen et al., 2016). On the other hand, two studies evaluating DNA methylation in specific genes by quantitative pyrosequencing or methylation-specific quantitative PCR showed a positive association with increasing PAH exposure levels (Pavanello et al., 2009; Yang et al., 2012). Perhaps these discrepancies in the literature about the correlation between global DNA methylation and environmental contaminant body burden can be attributed to the fact that such potential confounding factors as sex and age were not addressed. Interestingly, a recent report has shown that juvenile alligators have higher levels of global methylation than do adult alligators (Parrott et al., 2014). In the present study, we specifically focused on juvenile animals without addressing the potential confounding effect of sex because the only effective method for sex determination in the juvenile stage of sea turtles is laparoscopy, an invasive approach not recommended for endangered species. In the future it would be interesting to focus on DNA methylation levels of selected biomarkers, specifically, oxidative stress genes, and the relationships with their expression. 5. Conclusions Although the amount of data available on chemical contamination of sea turtles and the effects on their health has increased considerably in the last few years, studies on exposure biomarkers for evaluation of the toxicological impact are still scarce. In this study, we have identified whole blood expression profiles of biomarker genes that correlate with plasma levels of specific PAH congeners in loggerheads rescued along the northern and middle Adriatic coast in Italy. In addition, our study is the first to show that global DNA methylation can be positively associated with the levels of selected PAH congeners and total PAHs, particularly LMW-PAHs. Our study suggests a promising strategy for monitoring sea turtle POP exposure, in that identification of gene biomarkers in whole blood cells requires less invasive sampling methods than other approaches. Taken together, the results of the present work confirmed that Adriatic Sea turtles are considerably exposed to mixtures of organic contaminants, among which PAHs and PCBs are reasonably likely to cause potential adverse effects. These correlative findings clearly suggest the need for future large-scale controlled studies examining the underlying mechanisms by which exposure to pollutant mixtures adversely affects the health of sea turtles.

Supplementary data to this article can be found online at https://doi. org/10.1016/j.scitotenv.2017.11.118.

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