Environmental Pollution 205 (2015) 60e69

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A multibiomarker approach to explore interactive effects of propranolol and fluoxetine in marine mussels Silvia Franzellitti a, b, *, Sara Buratti b, Bowen Du c, Samuel P. Haddad c, C. Kevin Chambliss d, Bryan W. Brooks c, Elena Fabbri a, b a

University of Bologna, Department of Biological, Geological, and Environmental Sciences, via Selmi 3, 40100 Bologna, Italy University of Bologna, Interdepartment Centre for Environmental Science Research, via S. Alberto 163, 48123 Ravenna, Italy Department of Environmental Science, Baylor University, Waco, TX 76798, USA d Department of Chemistry and Biochemistry, Baylor University, Waco, TX 76798, USA b c

a r t i c l e i n f o

a b s t r a c t

Article history: Received 12 January 2015 Received in revised form 30 March 2015 Accepted 8 May 2015 Available online

A multi-biomarker approach, including several lysosomal parameters, activity and mRNA expression of antioxidant enzymes, and DNA damage, was employed to investigate the nominal effects of 0.3 ng/L fluoxetine (FX) and 0.3 ng/L propranolol (PROP) alone or in combination (0.3 ng/L FX þ 0.3 ng/L PROP) on Mediterranean mussels after a 7 day treatment. FX co-exposure appears to facilitate PROP bioaccumulation because PROP only accumulated in digestive gland of FX þ PROP treated mussels. Lysosomal parameters were significantly impaired by FX þ PROP treatment, while no clear antioxidant responses at the catalytic and transcriptional levels were observed. Biomarker responses led to a “medium stress level” diagnosis in FX þ PROP treated mussels, according to the Expert System, whereas 0.3 ng/L PROP or FX alone did not induce consistent stress conditions. These findings suggest vulnerability of coastal marine mussels to FX and PROP contamination at environmentally relevant levels. © 2015 Elsevier Ltd. All rights reserved.

Keywords: Marine mussel Fluoxetine Propranolol Bioaccumulation Biomarkers Lysosomal responses Drugedrug interaction Adverse outcome pathway

1. Introduction Developing an understanding of the biological consequences of pharmaceutical residues in aquatic ecosystems has become a research priority over the last decade, given the increased knowledge on the occurrence and widespread distribution of these contaminants worldwide. Indeed, many ingested pharmaceuticals are minimally metabolized by target organisms and not completely degraded during conventional wastewater treatments; thus, residues are released from final effluent discharges to receiving systems (Daughton and Ternes, 1999; Kolpin et al., 2002). Population growth, urbanization, aging populations, more effective delivery of health services, and climatic changes further contribute to concentrated releases of these substances in urban inland and coastal water bodies (Brooks, 2014). Because pharmaceuticals are

* Corresponding author. Department of Biological, Geological, and Environmental Sciences (BIGEA), University of Bologna, Via Sant'Alberto 163, 48123 Ravenna, Italy. E-mail address: [email protected] (S. Franzellitti). http://dx.doi.org/10.1016/j.envpol.2015.05.020 0269-7491/© 2015 Elsevier Ltd. All rights reserved.

inherently designed to have biological activity, and many therapeutic and adverse drug reaction targets are evolutionarily conserved across aquatic organisms (Gunnarsson et al., 2008), identifying inherent chemical properties (Brooks, 2014; McRobb et al., 2014) associated with cellular/molecular interactions resulting in adverse outcomes at environmental concentrations is necessary for protecting aquatic organisms (Franzellitti and Fabbri, 2014; Schmitt et al., 2010). Compared with freshwaters, studies on pharmaceuticals' fate and effects in marine environments are under-represented in literature (Gaw et al., 2014) presumably assuming that dilution and dispersion processes significantly decrease the risks to marine wildlife. Nevertheless, recent studies reported notable amounts of emerging contaminants being transported to coastal areas via riverine inputs, or due to their use in mariculture, and locally effluents from coastline WTPs are discharged directly in seawater to protect surface waters (Fenet et al., 2014; Jiang et al., 2014). Spot data on pharmaceuticals occurrence in seawaters are reported worldwide (Gaw et al., 2014), with exposure risks being strongly related to their hydrodynamic behaviors in marine ecosystems

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(Bayen et al., 2013; Fenet et al., 2014). In particular, many pharmaceuticals display high affinity for suspended solids and bottom sediments (Bayen et al., 2013), suggesting exposure in sedimentdwelling and filter-feeding marine benthos may be more relevant than for pelagic species. The present study used the Mediterranean mussel (Mytilus galloprovincialis) as a model species to explore potential pharmaceutical responses in marine benthonic invertebrates. Mussels live at the sediment/water interface and filter large volumes of water, suspended materials and colloids (Viarengo et al., 2007). As such, they can accumulate micro-pollutants through the gills (dissolved substances) and the digestive tract (substances adsorbed on parti
mez et al., 2012; Martinez-Bueno et al., 2013, 2014). Our cles) (Go objective was to investigate possible adverse outcomes triggered by a combination of fluoxetine (FX), a selective serotonin reuptake inhibitor used in the treatment of depression and other mood disorders, and propranolol (PROP), a b-adrenergic receptor antagonist used to counteract cardiovascular pathologies (Weir, 2009). These compounds have been detected in coastal environments at concentrations in the range of 3e596 ng/L (FX; Vasskog et al., 2008; Benotti and Brownawell, 2007) and 0.3e6329 ng/L (PROP; Wille et al., 2011, 2010; Yang et al., 2011) and also may be effectively bioaccumulated by mussels (Du et al., 2014a; Ericson et al., 2010; Franzellitti et al., 2014). Interactive studies of PROP and FX in aquatic organisms are lacking (Brausch et al., 2012), but may be of concern for aquatic wildlife. In humans, PROP and FX are contraindicated medications because FX is a potent inhibitor of CYP450-mediated metabolism (Hardman and Limbird, 2001). Whether co-exposure to FX influences toxicokinetics and bioaccumulation of PROP also in aquatic organisms is not understood. However, environmental consequences from pharmaceutical mixtures are identified as the #1 priority research need to understand risks of long term exposure to pharmaceuticals (Boxall et al., 2012; Rudd et al., 2014). Such information may provide support to the ongoing discussion of expanding biological approaches supporting pharmaceutical risk assessment in aquatic ecosystems (Caldwell et al., 2014). In the present study a multi-biomarker approach reflecting the general health status of mussels and the counteracting responses was employed to further investigate FX and PROP effects on marine mussels. This built on our recent studies, where pharmaceutical adverse modes of action were assessed under single-chemical exposure conditions (Franzellitti et al., 2011, 2014), because interactive effects in the present study were examined under the same exposure scenario used previously (Franzellitti et al., 2013). Though there is undeniable power in the use of biomarkers to elucidate pathways and mechanisms of adverse effects of contaminants, simply examining the simultaneous variation of different biomarkers it is generally difficult to obtain an inter-comparable assessment of the organism health status, so that their practical use for assessing the degree of environmental risk is still not always clear (Viarengo et al., 2000). We attempt to alleviate this through the application of the Mussel Expert System (Dagnino et al., 2007) able to integrate information derived from different biomarkers within a synthetic health status index, thus allowing common criteria in the evaluation of the biological effects of pollutants. 2. Materials and methods 2.1. Experimental animals and holding conditions Specimens of M. galloprovincialis (5e7 cm in length) were collected from the northwestern Adriatic Sea coast by fisherman of the “Cooperativa Copr.al.mo” (Cesenatico, Italy), and transferred to the laboratory in seawater tanks with continuous aeration. Animals

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(30 per aquarium) were acclimated for 3 days in aquaria containing 60 L of aerated artificial 35 psu seawater at 16  C, under a natural photoperiod. Mussels were fed once a day with an algal slurry (Koral filtrator, Xaqua, Italy). Fifteen mussels were sampled at zero time to assess parameters at the onset of each experiment. 2.2. Test substances Mussels were treated with propranolol ((±)-1-isopropylamino3-(1-naphthyloxy)-2-propanol) hydrochloride (PROP) and with fluoxetine ((±)-N-methyl-g-[4-(trifluoromethyl)phenoxy] benzenepropanamine) hydrochloride (FX) (Sigma Aldrich, Milan, Italy; purity  98%). According to the manufacture's datasheets, PROP and FX are water soluble up to 50 mg/mL and to 4 mg/mL, respectively. Therefore, stock solutions were prepared in distilled milliQ-grade water at a 0.1 mg/mL concentration, aliquoted and stored at 20  C. To achieve treatment levels, 1 aliquot of stock solution was employed and diluted to achieve the suitable volume to be spilled in each vessel. As the vessels used in this study are made up of a plastic material for use with foodstuff, vessels walls should neither absorb nor release chemicals. Although we cannot exclude that some interaction of FX and PROP with plastic could have occurred, our observations in previous studies (Brooks et al., 2003; Stanley et al., 2007) suggest it is minimal, also considering the concentrations used for the treatments. Half-life for the pharmaceuticals in water solutions was about 102 days (FX) and 30 days (PROP) (Kwon and Armbrust, 2006; Yamamoto et al., 2009), whereas in this study pharmaceutical administration was on a daily base along with mussel feeding and after water changes. 2.3. Experimental design Mussel treatments with FX, PROP, or their combination were carried out as reported by Franzellitti et al. (2013) and Franzellitti and Fabbri (2013). A total of 480 mussels were randomly selected and divided in groups of 20 animals each, and transferred to vessels containing 20 L of water. One liter of seawater per mussel is the suitable volume to avoid overloading and prevent the onset of unfavorable health conditions. For each experimental condition, 6 vessels containing a total of 120 mussels represented the 6 replicates. Mussels were treated for 7 days with nominal 0.3 ng/L PROP, 0.3 ng/L FX, or with the combination FX þ PROP (0.3 ng/ L þ 0.3 ng/L). These nominal concentrations fall within the lower range of environmental levels for the compounds and were selected for this study because of the previously induced interactive effects on MOA relevant parameters (Franzellitti et al., 2013). A group of unexposed (control) mussels were maintained in parallel to the treatment groups. Seawater was renewed each day and the chemicals added from stock solutions as described above along with mussel feeding. At the end of the experiment, haemolymph was taken from the abductor muscle of individual mussels. The gills, digestive gland and mantle/gonad complex were dissected from individuals and used immediately or snap-frozen in liquid nitrogen and stored at 80  C. There was no mortality during the exposure period. Mussels at zero time were immediately analyzed for biomarkers to assess their initial health status, and results were not significantly different from mussels maintained for 7 days under control conditions (data not shown). We established independent replicates within each treatment group by considering the 6 vessels as the operative replication level (N ¼ 6). FX and PROP bioaccumulation was assessed on duplicate pooled tissues, each pool consisting of digestive glands, gills or mantle/gonads from 12 animals. Lysosomal membrane stability was measured in haemolymph sampled from 4 individual mussels

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per vessel, which provided a mean neutral red retention time (NRRT) value per vessel for each experimental treatment used for data calculations and statistics (N ¼ 6). For the evaluation of lipofuscins, neutral lipids and lysosome/ cytoplasm ratio, 1 chuck per vessel each containing 4 digestive glands from 4 randomly selected mussels was used (N ¼ 6). Further technical replicates were also employed, as for these biomarkers multiple cryostat sections from each chuck were assessed. For catalase and glutathione-s-transferase activity and mRNA expression assays, and DNA damage each replicate consisted of pooled tissues from 3 randomly selected mussels (1 pool/vessel; N ¼ 6). 2.4. Bioaccumulation Instrumentation and extraction procedures for analyses of fluoxetine and propranolol in mussel tissues were as reported previously (Du et al., 2012; Ramirez et al., 2007). Pharmaceuticals were analyzed by liquid chromatography tandem mass spectrometry (LC-MS/MS) on a Varian model 410 autosampler, ProStar model 212 binary pumping system, and model 1200 L triple quadrupole mass analyzer. Gradient elution was used to monitor the target pharmaceuticals in a single sample. Accordingly, a gradient mobile phase condition that resulted in elution of propranolol at 5 min and fluoxetine at 8 min was identified. Salts and other highly polar constituents were diverted from the mass spectrometer during the first 2 min of each run. Chromatography was performed using a 15 cm  2.1 mm Extend-C18 column (5 mm, 80 Å; Agilent Technologies, Palo Alto, CA, USA) connected to a 12.5 mm  2.1 mm Extend-C18 guard cartridge (5 mm, 80 Å; Agilent Technologies). The ionization mode and monitored transitions for fluoxetine and propranolol as well as the internal standards fluoxetine-d6 and propranolol-d7 were: ESI þ fluoxetine 310 > 148, fluoxetine-d6 316 > 154, propranolol 260 > 183, and propranolol-d7 267 > 123. Method detection limits (MDLs) were determined extracting and analyzing reference samples (reference mussel tissue) fortified with FX and PROP at a concentration 10 times the reported MDLs for fish tissue (Du et al., 2012; Ramirez et al., 2009). MDLs of fluoxetine and propranolol for whole mussel tissue were determined to be 6.0 ng/g and 4.8 ng/g respectively, which represented the lowest detectable concentrations in mussel tissues for current study. Six standards, ranging from below MDLs to 500 ng/mL, were used to construct linear calibration curve (r2  0.998). Instrument calibration was monitored over time via analysis of continuing calibration verification (CCV) samples with an acceptability criterion of ±20%. Both calibration standards and calibration verification samples were prepared in 0.1% formic acid (v/v) (Du et al., 2014b). 2.5. Lysosomal membrane stability (LMS) LMS was evaluated in mussel haemocytes using the neutral red retention assay (NRRA) as reported in detail by Martinez-Gomez et al. (2008). LMS was assessed as destabilization time representing the time at which more than 50% of the lysosomes release the dye into the cytosol. For each treatment, data are expressed as the percentage of variation (mean ± SEM) with respect to control sample. 2.6. Lysosomal parameters measured in digestive gland Immediately after dissection, digestive glands were placed on aluminum cryostat chucks, frozen in N-hexane pre-cooled at 70  C with liquid nitrogen, and stored at 80  C. The following procedures were carried out according to the UNEP/ RAMOGE Manual (1999). Briefly, 10 mm-thick digestive gland sections were obtained using a cryostat (MICROM HM 505 N) at

a 30  C cabinet temperature and transferred onto microscope slides. For lysosome/cytoplasm volume ratio (LYS/CYT), tissue sections were stained for N-acetyl-b-hexosaminidase activity and processed according to Franzellitti et al. (2014). For neutral lipids (NL) determination, cryostat sections were fixed in calcium formol for 15 min at 4  C, rinsed and transferred into 60% triethylphosphate for 3 min. Sections were stained in 1% oil red O in 60% triethylphosphate for 15 min in the dark, then rinsed in 60% triethylphosphate for 30 s, washed in distilled water and mounted with glycerolegelatin. For lipofuscins (LIF) determination, triplicate slides were fixed in calcium formol for 15 min at 4  C, rinsed and immersed in the reaction medium containing an aqueous solution of 1% ferric chloride and 1% potassium ferricyanide in a 3:1 ratio. Sections were stained for 5 min, rinsed in 1% acetic acid and washed in distilled water before mounting with glycerol-gelatin. Tissue sections were quantitatively assessed under a light microscope (Axioskop 40, Carl Zeiss, Milan, Italy) equipped with a 40X objective and a digital camera (AxioCam MRc, Carl Zeiss, Milan, Italy). Four images were analyzed per each of the 4 sections on the same microscope slides, and 3 slides were analyzed for each chuck for each treatment using the Scion Image ver. 4.0.2 image analysis software (Scion Corporation Frederick, MD, USA). 2.7. Activity of antioxidant enzymes About 200 mg of pooled digestive glands were homogenized with 5 volumes of 50 mM potassium-phosphate buffer (KPB), pH 7.0, containing 0.5 mM Na2EDTA (Mimeault et al., 2006). Total protein content was estimated according to Lowry et al. (1951). Glutathione-s-transferase (GST) activity was determined by measuring the increase of absorbance at 340 nm due to the conjugation of 1-chloro-2,4-dinitrobenzene (CDNB) with reduced glutathione (GSH). The final activity was expressed as nmol/min/ mg protein. Catalase (CAT) activity was determined by measuring the decrease of absorbance at 240 nm due to hydrogen peroxide consumption (55 mM H2O2 in 50 mM KPB pH 7.0). The final activity was expressed as mmol/min/mg protein. 2.8. Mussel CAT and GST mRNA expression analyses Total RNA was extracted from digestive gland by tissue homogenization (about 200 mg) in the TRI reagent (Sigma Aldrich, Milan, Italy) according to the manufacturer's protocol. RNA concentration and quality were verified by UV spectroscopy and electrophoresis using a 1.2% agarose gel under denaturing conditions. First strand cDNA for each sample was synthesized from 1 mg total RNA using the iScript supermix (Biorad Laboratories, Milan, Italy) following the manufacture's protocol. CAT and GST mRNA expressions were assessed by real-time PCR according to Koutsogiannaki et al. (2014). A normalization factor, calculated using the geNorm software (Vandesompele et al., 2002),

Table 1 FX and PROP bioaccumulation (mg/kg w.w.) in digestive glands of Mediterranean mussels treated with FX, PROP, or to the combination FX þ PROP. Experimental treatment

[FX]

[PROP]

Control FX PROP FX þ PROP

ND ND ND ND

ND ND ND 25.74

ND: not detected; MDL: method detection limit for whole mussel tissue (FX ¼ 6.0 ng/g w.w.; PROP ¼ 4.8 ng/g w.w.). Levels of FX and PROP were not detectable or below MDL in gills and mantle/gonads of mussels from the different treatments as well as from controls.

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which assessed the best performing reference transcripts in the analyzed samples, was used for accurate normalization of real-time PCR data. The most stable reference gene products under the different experimental conditions were 18S rRNA and 28S rRNA. Relative expression of target mRNAs in comparison with the reference gene products was calculated by a comparative Ct method (Schmittgen and Livak, 2008) using the StepOne software tool (Life Technologies, Milan, Italy). Data were reported as normalized relative expression (fold change) with respect to control samples. 2.9. DNA damage DNA damage levels were determined by the modified alkaline
et al., 2009). Evaluations were DNA precipitation assay (Gagne performed on pooled digestive gland homogenates according to
mez et al. (2011) using the bisBenzimide H (Hoechst) Ramos-Go 33,258 dye (1 mg/mL). Strand broken DNA levels were assessed by fluorescence measurements (l excitation ¼ 350 nm, l emission ¼ 450 nm) against a standard curve of salmon sperm DNA. Data were expressed as mg DNA per mg total protein. 2.10. Health status index: the Mussel Expert System (MES) Analyzed biomarkers were integrated into a Health Status Index (HSI) using the Mussel Expert System (MES) developed by Dagnino et al. (2007). Biomarker responses were processed considering the level of biological organization and the profile of response to stress of each parameter. Data from pharmaceutical-treated mussels are compared to control values and statistically significant alterations (p < 0.05) are converted into alteration levels (ALs) by comparison with specific thresholds. In this study, default thresholds of the MES software were employed. HSI levels (ranked as: A-healthy; B-low stress; C-medium stress; D-high stress; E-pathological stress) are calculated integrating ALs with a classification algorithm applying a set of rules in the “if…then” form. Briefly, HSI accounts for the response of the most sensitive guide parameter (here the LYS/CYT ratio), the level of biological organization affected by the stressors, and the reached ALs. 2.11. Statistical analysis Statistical analysis of biomarker data was performed using the

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SigmaStat software. Significant differences between treatment groups were determined using one-way ANOVA followed by the multiple comparison Bonferroni's post-hoc test. Normality (ShapiroeWilk's test) and equal variance (F-test) ANOVA assumptions were verified using the SigmaStat software. Real time PCR data were first analyzed using the REST software (Pfaffl et al., 2002) that uses a randomization test with a pairwise reallocation to assess the statistical significance of the differences in expression between each treatment group and the controls. Further comparisons between pair of treatments were performed using the Bonferroni's test. Pairwise correlations between the different biological endpoints, FX or PROP nominal treatment levels and tissue concentrations were assessed using the Spearman's test. Statistical differences were accepted when p < 0.05. A Principal Component Analysis (PCA) extraction procedure was performed using the STATISTICA software package (StatSoft) in order to determine whether significantly different effects of the contaminant mixture with respect to single contaminant exposures occurred. 3. Results 3.1. Bioaccumulation of FX and PROP in tissues of Mediterranean mussels FX was not detected in digestive gland of mussels treated with 0.3 ng/L of FX, 0.3 ng/L PROP or in FX þ PROP-treated mussels, or in controls (Table 1). PROP was observed to appreciably accumulate in digestive glands of FX þ PROP treated mussels, while not detectable in FX- and PROP- treated mussels or in controls (Table 1). Levels of FX and PROP were not detectable or below MDL in gills and mantle/ gonads of mussels from the different treatment groups or controls (data not shown). 3.2. Effects of FX, PROP and their combination on lysosomal biomarkers Reduction of lysosomal membrane stability (LMS) compared to controls was observed in mussel haemocytes after nominal treatment with FX, PROP or with FX þ PROP (Fig. 1). Such a reduction was correlated with FX treatment (Table 2). Increase of LYS/CYT ratio compared to controls was detected in digestive gland of mussels from all treatment groups, reaching significance in the FX þ PROP group (mean 170% of controls; Fig 2A). LYS/CYT levels were positively correlated with nominal FX treatment and with PROP measured tissue levels (Table 2). A negative correlation was also found between LYS/CYT ratio and haemocyte LMS (Table 2). A significant increase (p < 0.05) of neutral lipid (NL) accumulation in lysosomes was observed in FX- and PROP- treated mussels (Fig. 2B). NL levels in the FX þ PROP group were not significantly different (p > 0.05) from both controls and single-chemical treatments, although values were higher than control values (Fig. 2B). Lipofuscin (LIF) accumulation in lysosomes was significantly increased (p < 0.05) in FX- and FX þ PROP- treated mussels, whereas no significant changes were observed in PROP-treated mussels (Fig. 2C). 3.3. Effects of FX, PROP and their combination on antioxidant enzyme activities and mRNA expressions

Fig. 1. Lysosomal membrane stability (neutral retention assay, NRRA) assessed in mussel haemocytes after a 7-days treatment with FX, PROP, or the combination FX þ PROP. Results are expressed as the mean ± SEM (N ¼ 6) of the destabilization time, i.e. the time at which more than 50% of the lysosomes appeared discolored. Different letters indicate statistical differences (p < 0.05).

CAT activity was not significantly modified compared to controls in digestive gland of mussels treated with FX or PROP, whereas a significant increase (p < 0.05) was observed in the FX þ PROP treatment group (Fig. 3A). Compared to controls, GST activity was

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Table 2 Correlation coefficients amongst biomarkers measured in digestive gland of mussels after a 7-days treatment with FX, PROP, or the combination FX þ PROP. Nominal concentrations of the pharmaceuticals, FX or PROP levels measured in digestive gland, and LMS measured in haemocytes were included in the analysis.

[FX] [PROP] FX tissue PROP tissue LMS LYS/CYT NL LIF CAT GST DNA dam CAT mRNA GST mRNA

[PROP]

[FX]T

[PROP]T

LMS

0

e e

0.58* 0.58* e

0.87** 0.19 e 0.47

LYS/CYT 0.68* 0.48 e 0.58* 0.69*

NL 0.19 0.39 e 0.028 0.32 0.17

LIF 0.43 0.24 e 0.36 0.27 0.62* 0.06

CAT

GST

DNA dam

CAT mRNA

GST mRNA

0.43 0.29 e 0.64* 0.59* 0.27 0.07 0.17

0.05 0.05 e 0.53 0.17 0.06 0.20 0.02 0.41

0.24 0.24 e 0.03 0.20 0.18 0.15 0.37 0.29 0.30

0.48 0.89** e 0.77** 0.56 0.73** 0.43 0.41 0.45 0.065 0.11

0.894 0.447 e 0.77 0.86 0.82** 0.34 0.49 0.52 0.065 0.11 0.8**

[FX], nominal fluoxetine treatment dose; [PROP], nominal propranolol treatment dose; [FX]T, concentrations of fluoxetine measured in digestive gland; [PROP]T, concentrations of propranolol measured in digestive gland; LMS, lysosomal membrane stability measured in haemocytes; LYS/CYT, lysosome/cytoplasm volume ratio; NL, neutral lipid; LIF, lipofuscin; CAT, catalase activity; GST, glutathione S-transferase activity; DNA dam, levels of DNA damages; CAT mRNA, M. galloprovincialis cat gene product; GST mRNA, M. galloprovincialis gst gene product. **p < 0.01 according to the Spearman's test. *p < 0.05 according to the Spearman's test.

slightly though significantly increased (p < 0.05) in FX- or PROPtreated mussels, while unmodified in the FX þ PROP group (Fig. 3B). Both antioxidant enzyme activities showed significant positive (CAT) or negative (GST) correlations with PROP accumulation levels in digestive gland (Table 2). CAT mRNA levels were significantly reduced (p < 0.05) in digestive gland of mussels treated with FX, PROP, or FX þ PROP (Fig. 4). GST mRNA expression was unaffected by mussel treatment with FX or PROP, while significantly down-regulated (p < 0.05) in digestive gland of FX þ PROP treated mussels (Fig. 4). 3.4. Effects of FX, PROP and their mixture on DNA damage levels Levels of strand-broken DNA were not significantly altered (p > 0.05) in digestive gland of mussels from the different treatment groups compared to controls (Fig. 5). 3.5. Expert System output and principal component analysis Biomarker responses observed in the present study (LMS, LYS/ CYT, NL, LIF, CAT activity, GST activity, DNA damage, mortality) were integrated and interpreted using the Mussel Expert System (MES; Dagnino et al., 2007) (Table 3). The LYS/CYT ratio was used as the guide parameter because present data and a previous investigation suggested that this is a suitable sensitive biomarker to pharmaceutical exposure in digestive gland (Franzellitti et al., 2014). Compared to control mussels, FX- and PROP- treated groups resulted in good health status (A, in the MES scale), whereas a moderate stress level (C) was assigned to FX þ PROP treated mussels (Table 3). PCA analysis applied to the biological parameters and pharmaceutical levels measured in digestive gland of mussels subjected to the different treatments (Fig. 6) showed two principal components explaining 88.5% of the total variance (61.95% and 26.55%, respectively). Single-chemical treatments (FX, PROP) showed evident separation from the FX þ PROP group. All the treatments were separated from controls (Fig 6). Single-chemical treatments are associated with slightly increased GST activity (unmodified by FX þ PROP treatment), and with NL alterations (Fig 6), whereas main lysosomal responses and CAT activity were associated with PROP accumulation in digestive gland of FX þ PROP treated mussels (Fig. 6).

4. Discussion Previous studies on Mediterranean mussels revealed interactive potential of FX and PROP on the cAMP/PKA pathway, assessed as part of the therapeutic modes of action of the compounds in human (Franzellitti et al., 2013; Franzellitti and Fabbri, 2013). In this study, a battery of 7 biomarkers were analyzed in mussels treated under the same experimental conditions of Franzellitti et al. (2013) to explore potential interactive effects of the pharmaceuticals on physiological parameters related to the animal health status. Both FX and PROP modulated stress responses in mussels over a wide range of environmentally realistic concentrations (Franzellitti et al., 2011, 2014). The mussel digestive gland is a tissue of choice for detecting early signs of exposure to various toxicants, as contaminant bioaccumulation and rate-limited metabolism of hydrophobic compounds peak in this organ (Venier et al., 2006). The digestive cells of bivalves also possess a complex endo-lysosomal system primarily involved in the uptake and digestion of food materials, and in processes of contaminant accumulation and detoxification
mez, 2009). Digestive gland appears to be (Izagirre and Marigo suitable for analyzing pharmaceutical effects, as suggested by previous results on therapeutic- and toxicity-related endpoints (Franzellitti et al., 2011; Martin-Diaz et al., 2009), and on bio
mez et al., 2012; Martinezaccumulation potential of the organ (Go Bueno et al., 2013, 2014). FX preferentially accumulated in digestive gland of mussels exposed to nominal concentrations of 30 and 300 ng/L, where the pharmaceutical significantly affected some lysosomal parameters (Franzellitti et al., 2014). PROP was also reported to bioaccumulate in mussels (Ericson et al., 2010), although no tissue partitioning has been reported. The present study only observed measurable bioaccumulation of PROP in digestive gland of mussels after combined treatment with FX, whereas no levels of both pharmaceuticals were detected in any other tissue or experimental treatment. Because drugedrug interactions resulting from FX inhibition of CYP activity and thus of PROP clearance occur in humans, FX and PROP are contraindicated medicines. FX is specifically known to inhibit CYP450 2D6 (Marathe et al., 1994), for which PROP is a major substrate (Lee et al., 2006). PROP is also a substrate for several other CYP450 isoenzymes in humans, including CYP1A2 (Lee et al., 2006). Though mammalian pharmacodynamic information can be useful

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Fig. 3. Catalase (CAT) activity (A) and glutathione-s-transferase (GST) activity (B) in digestive gland of mussels after a 7-days treatment with FX, PROP, or the combination FX þ PROP. Data are expressed as the mean ± SEM values (N ¼ 6). Different letters indicate statistical differences (p < 0.05).

Fig. 2. Lysosomal parameters assessed in digestive gland of mussels after a 7-days treatment with FX, PROP, or the combination FX þ PROP. (A) Lysosome/cytoplasm (LYS/CYT) ratio; (B) accumulation of neutral lipids (NL) and (C) of lipofuscins (LIF) in lysosomes. Results are expressed as the mean ± SEM (N ¼ 6) of the percentage of variation with respect to control samples. Different letters indicate statistical differences (p < 0.05).

when appropriate uncertainties are recognized to study pharmaceutical hazards in aquatic organisms, it is presently not possible to directly extrapolate pharmacokinetic and metabolism data to aquatic life due to significant differences in CYP families (Gunnarsson et al., 2012). For example, Connors et al. (2013a) identified enantiomer-specific differences in biotransformation of PROP by rainbow trout in vitro, but observed no significant biotransformation of FX or other drug substrates of other common CYPs involved in metabolism of most human medicines (Connors et al., 2013b). Neither of these observations would have been predicted from human biotransformation data for FX or PROP. In the

Fig. 4. Levels of CAT and GST mRNA expressions in digestive gland of mussels after a 7days treatment with FX, PROP, or the combination FX þ PROP. Values (mean ± SEM) are expressed as the relative variations (fold change) between each treatment and control samples (N ¼ 6). Different letters indicate statistical differences (p < 0.05).

present study, whether FX inhibited CYP activity, decreased clearance thus facilitating PROP accumulation in marine mussels is not known, but such an observation clearly points to a need for future studies to understand potential influences of FX and other medicines on bioaccumulation dynamics in the environment. Pharmaceutical co-treatment may also alter other endogenous

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Fig. 5. Levels of DNA strand breaks evaluated in digestive gland of mussels after a 7days treatment with FX, PROP, or the combination FX þ PROP. Data are expressed as the mean ± SEM values (N ¼ 6). Different letters indicate statistical differences (p < 0.05).

compounds that subsequently promoted the PROP accumulation observed in the present study. Lysosome-rich tissues as those with metabolic functions can preferentially accumulate lipophilic amines due to the pH partitioning of the compounds within the organelles through a process of lysosomal trapping (Kazmi et al., 2013). This process may alter lysosomal functionality and affect
jcikowski, drugedrug interaction (Daniel, 2003; Daniel and Wo 1997; Kazmi et al., 2013). As FX and PROP are known lysosomo
jcikowski, 1997; trophic drugs in mammalian cells (Daniel and Wo Kazmi et al., 2013), lysosomal trapping may provide another explanation for the PROP accumulation observed in mussel digestive gland in the presence of FX. This finding is also consistent with our previous study (Franzellitti et al., 2013), showing a prevalent effect of PROP on cAMP/PKA parameters of the digestive gland in FX þ PROP treated mussels. Lysosomal parameters measured in the same tissue provided important hints for interactions of FX and PROP, as suggested by the PCA analysis and the MES data

integration, and confirmed previous results showing significant effects of the single pharmaceuticals in a wider concentration range (Franzellitti et al., 2011, 2014). The LYS/CYT ratio, in particular, indicated a significantly increased lysosome volume after FX þ PROP treatment compared to single chemical administrations, which is consistent with a putative lysosomal partitioning mechanism. The increase of LYS/CYT ratio in FX-treated mussels was reported as dose-dependent and significantly enhanced in organisms displaying FX bioaccumulation within digestive gland (Franzellitti et al., 2014). NL and LIF lysosome accumulations were also differently affected by the single chemicals vs FX þ PROP treatment. From a physiological point of view, neutral lipids constitute an important nutrient storage related to growth and reproduction. Nevertheless, their anomalous accumulation may be related to enhanced lipid peroxidation by chemical exposure (Viarengo et al., 2007). Lipofuscins originate from autophagocytosed oxidized cellular components, and also from inhibition of lysosomal enzymes or general damaging effects accelerating lipid peroxidation (Terman and Brunk, 2004). Therefore, besides specific relationship with pharmakodynamic routes of the pharmaceuticals, lysosomal responses are robust early-warning biomarkers of animal health status (Viarengo et al., 2007). The MES biomarker data integration assigned a moderate stress level (HSI ¼ C) to FX þ PROP treated mussels, while single-chemical treated organisms and controls resulted unstressed (HSI ¼ A), suggesting an increased stress level following pharmaceutical coadministration. Changes in antioxidant defenses are rapidly activated in mussels to counteract pro-oxidant challenges (Regoli and Giuliani, 2014), and in general pharmaceuticals may cause these effects. Previous studies reported conflicting evidence about the induction of oxidative stress in mussels by FX or PROP. Gonzalez-Rey and Bebianno (2013) found a transient induction of catalase activity at 3 and 15 days of exposure in mussels exposed to 75 ng/L FX. No clear antioxidant responses to FX or PROP were detected in a range of environmental concentrations (Franzellitti et al., 2011, 2014). In this study, CAT activity was significantly increased in digestive

Table 3 The mussel expert system output. Alteration factors (AFs) for significant biomarker responses have been calculated by the MES and compared with default thresholds to give the reported alterations levels (ALs) also considering the biomarker response profile (Dagnino et al., 2007). For each treatment, ALs have been finally integrated into an Health Status Index (HSI). Control

FX

PROP

FX þ PROP

AF AL AF AL AF AL AF AL AF AL AF AL

1.00

0.46* e 1.47* þ 1.65* þ 1.07 NV 1.05 NV 1.17* NV

0.76* 1.29 NV 1.98* þ 0.94 NV 1.00 NV 1.16* NV

0.51* 1.59* þ 1.49 NV 0.95 NV 1.27* þ 0.99 NV

Increasing

AF AL

1.00

1.37 NV

1.29 NV

1.72* þ

Decreasing

AF AL

1.00

1.00 NV

1.00 NV

0.99 NV

A (healthy)

A (healthy)

A (healthy)

C (medium stress)

Biomarker profile Cell level LMS

Decreasing

LIF

Increasing

NL

Bell-shaped

DNA dam

Increasing

CAT

Bell-shaped

GST

Bell-shaped

Tissue level LYS/CYT (guide parameter) Organism level Survival rate HSI

1.00 1.00 1.00 1.00 1.00

LYS/CYT, lysosome/cytoplasm volume ratio; LMS, lysosomal membrane stability measured in haemocytes; NL, neutral lipid; LIF, lipofuscin; CAT, catalase activity; GST, glutathione S-transferase activity; DNA dam, levels of DNA damages. *p < 0.05 vs control, 1-way ANOVA followed by the Bonferroni post-hoc test. HSI: health status index. AF thresholds for increasing/bell-shaped biomarkers: NV (no variation) ¼ AF < 1.2; þ ¼ AF > 1.2; AF thresholds for decreasing biomarkers: NV ¼ AF > 0.8; - ¼ AF < 0.8;e ¼ AF < 0.5.

S. Franzellitti et al. / Environmental Pollution 205 (2015) 60e69

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Fig. 6. Principal component analysis (PCA) bi-plot of biomarker parameters and pharmaceutical bioaccumulations in digestive gland of mussels under the different experimental treatments.

gland of FX þ PROP treated mussels compared to either control or single-chemical treatments, where enzyme activity was unmodified. Differently, GST activity was affected by single-chemical treatments while not by FX þ PROP treatment. The bioaccumulation of PROP in digestive gland of FX þ PROP treated mussels may play a role in altering the antioxidant responses, given the significant correlations of enzyme activities with PROP tissue levels, as suggested by the PCA analysis. Induction of CAT activity may also explain the relative reduction of NL accumulation in FX þ PROP treated mussels. Patterns of CAT and GST mRNA expression did not follow variations of enzyme activities, being overall significantly downregulated or unmodified. Such discrepancies between transcriptional and enzymatic responses of antioxidant mediators are not surprising, since these defenses do not vary in a synchronous way (reviewed in Regoli and Giuliani, 2014). Transcriptional responses represent functions at lower biological hierarchies; thus, they are more sensitive and respond faster to stressors than biomarkers at higher biological hierarchies (Franzellitti et al., 2010), given the delayed timing of post-transcriptional processes and protein synthesis (Regoli and Giuliani, 2014). It is also worth noting that mRNA expression analyses were directed towards specific CAT and GST isoforms (i.e. peroxisomal CAT, GenBank Ac. Numb. AY743716; GSTpi, GeneBank Ac. Numb. AF527010), whereas enzymatic assays measured the total activity. As reported for other families of stressrelated proteins (Franzellitti et al., 2010; Franzellitti and Fabbri, 2005), different protein isoforms can be alternatively regulated to maintain a prompt response or minimize the adverse effects of the stress stimulus on the protein function itself. Observing significant biomarker responses in absence of clear bioaccumulation of the pharmaceuticals it is not surprising. Indeed, pollutant bioaccumulation takes place when the rate of intake exceeds the excretion abilities of the animal, while alterations of biomarkers and transcription rates represent early warning signals of animalechemical interaction, and detectable responses can be achieved faster than measurable tissue levels of pollutants. Comparing present results with those reported by Franzellitti

et al. (2013), where therapeutic MOAs of the pharmaceuticals were analyzed under the same experimental setup, we found that CAT mRNA expression profile is consistent with that of a mussel ABCB transcript encoding the membrane transporter P-glycoprotein (Pgp). As a part of the bivalve Multixenobiotic resistance (MXR) system, Pgp is involved in xenobiotic detoxification (Bard, 2000). Moreover, recent evidence reported Pgp being under transcriptional regulation by a cAMP/PKA pathway in human and in mussel cells (Franzellitti and Fabbri, 2013). Koutsogiannaki et al. (2014) showed that both ROS levels and mRNA expressions of antioxidant gene products were differently altered by haemocyte treatment with Cd or 17b-estradiol in presence/absence of various signaling molecules, suggesting that cell signaling can modify induction/repression of antioxidant mechanisms in response to oxidative stress-inducing chemicals. Since FX and PROP altered the cAMP signaling in mussels as part of their respective MOAs (Franzellitti et al., 2013), these findings may suggest a common regulatory network between some MXR-related proteins and the antioxidant machinery, and demonstrate that cell signaling modulation may have diverse physiological effects in mussels, including potentiating/inhibiting stress-activated response mechanisms.

5. Conclusions Co-treatment of mussels with FX and PROP at nominal environmentally relevant concentrations increased stress levels of the organisms and altered the responses to the single compounds, highlighting a potential susceptibility of marine organisms and coastal communities to pharmaceuticals. Further studies in a wide range of concentrations are warranted to understand the FX influences on PROP bioaccumulation dynamics in bivalves. Nevertheless, results reported in this study showed that FX treatment is likely to increase PROP accumulation in digestive gland of mussels. The alterations of the lysosomal and the antioxidant systems in the same tissue showed interactive actions of FX and PROP in modifying metabolic and detoxification processes of mussels. Together with previous investigations reporting significant effects of FX and

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PROP on higher-level relevant physiological functions in invertebrate species (reproduction, Bringolf et al., 2010; Gust et al., 2009; Lazzara et al., 2012; immune functions, Munari et al., 2014; feeding  et al., 2010), present data suggested that they may behavior, Sole affect bivalve capabilities of coping with other stressors, and jeopardize the fitness of individuals within natural populations. Therefore, the evaluation of biomarkers in environmental relevant species, as marine mussels, and their interpretation through decision support systems, as the MES, represent a promising approach to define and address risks of pharmaceuticals in coastal environments, including the identification of unpredictable adverse outcomes in non target species and their potential for homeostasis disruption. Acknowledgments The research has been funded by MEECE EU-FP7 Project, and Italian Ministry of University and Research (RFO2013) to E.F. References Bard, S.M., 2000. Multixenobiotic resistance as a cellular defence mechanism in aquatic organisms. Aquat. Toxicol. 48, 357e389. http://dx.doi.org/10.1016/ S0166-445X(00)00088-6. Bayen, S., Zhang, H., Desai, M.M., Ooi, S.K., Kelly, B.C., 2013. Occurrence and distribution of pharmaceutically active and endocrine disrupting compounds in Singapore's marine environment: influence of hydrodynamics and physicalchemical properties. Environ. Pollut. 182, 1e8. http://dx.doi.org/10.1016/ j.envpol.2013.06.028. Benotti, M.J., Brownawell, B.J., 2007. Distributions of pharmaceuticals in an urban estuary during both dry- and wet-weather conditions. Environ. Sci. Technol. 41, 5795e5802. http://dx.doi.org/10.1021/es0629965. Boxall, A.B.A., Rudd, M., Brooks, B.W., Caldwell, D., Choi, K., Hickmann, S., Innes, E., Ostapyk, K., Staveley, J., Verslycke, T., Ankley, G.T., Beazley, K., Belanger, S., Berninger, J.P., Carriquiriborde, P., Coors, A., DeLeo, P., Dyer, S., Ericson, J., Gagne, F., Giesy, J.P., Gouin, T., Hallstrom, L., Karlsson, M., Larsson, D.G.J., Lazorchak, J., Mastrocco, F., McLaughlin, A., McMaster, M., Meyerhoff, R., Moore, R., Parrott, J., Snape, J., Murray-Smith, R., Servos, M., Sibley, P.K., Straub, J.O., Szabo, N., Tetrault, G., Topp, E., Trudeau, V.L., van Der Kraak, G., 2012. Pharmaceuticals and personal care products in the environment: what are the big questions? Environ. Health Perspect. 120, 1221e1229. http:// dx.doi.org/10.1289/ehp.1104477. Brausch, J.M., Connors, K.A., Brooks, B.W., Rand, G.M., 2012. Human pharmaceuticals in the aquatic environment: a critical review of recent toxicological studies and considerations for toxicity testing. Rev. Environ. Contam. Toxicol. 218, 1e99. http://dx.doi.org/10.1007/978-1-4614-3137-4_1. Bringolf, R.B., Heltsley, R.M., Newton, T.J., Eads, C.B., Fraley, S.J., Shea, D., Cope, W.G., 2010. Environmental occurrence and reproductive effects of the pharmaceutical fluoxetine in native freshwater mussels. Environ. Toxicol. Chem. 6, 1311e1318. http://dx.doi.org/10.1002/etc.157. Brooks, B.W., 2014. Fish on Prozac (and Zoloft): ten years later. Aquat. Toxicol. 151, 61e67. http://dx.doi.org/10.1016/j.aquatox.2014.01.007. Brooks, B.W., Turner, P.K., Stanley, J.K., Weston, J., Glidewell, E., Foran, C.M., Slattery, M., La Point, T.W., Huggett, D.B., 2003. Waterborne and sediment toxicity of fluoxetine to selected organisms. Chemosphere 52, 135e142. http:// dx.doi.org/10.1016/S0045-6535(03)00103-6. Caldwell, D.J., Mastrocco, F., Margiotta-Casaluci, L., Brooks, B.W., 2014. An integrated approach for prioritizing pharmaceuticals found in the environment for risk assessment, monitoring and advanced research. Chemosphere 115, 4e12. http://dx.doi.org/10.1016/j.chemosphere.2014.01.021. Connors, K.A., Du, B., Fitzsimmons, P.N., Hoffman, A.D., Chambliss, C.K., Nichols, J.W., Brooks, B.W., 2013a. Enantiomer-specific biotransformation of select pharmaceuticals in rainbow trout (Oncorhynchus mykiss). Chirality 25, 763e767. http:// dx.doi.org/10.1002/chir.22211. Connors, K.A., Du, B., Fitzsimmons, P.N., Hoffman, A.D., Chambliss, C.K., Nichols, J.W., Brooks, B.W., 2013b. Comparative pharmaceutical metabolism by rainbow trout (Oncorhynchus mykiss) liver S9 fractions. Environ. Toxicol. Chem. 32, 1810e1818. http://dx.doi.org/10.1002/etc.2240. Dagnino, A., Allen, J.I., Moore, M.N., Broeg, K., Canesi, L., Viarengo, A., 2007. Development of an expert system for the integration of biomarker responses in mussels into an animal health index. Biomarkers 12, 155e172. http://dx.doi.org/ 10.1080/13547500601037171. Daniel, W.A., 2003. Mechanisms of cellular distribution of psychotropic drugs. Significance for drug action and interactions. Prog. Neuro-Psychopharmacol. Biol. Psychiatry 27, 65e73. http://dx.doi.org/10.1016/S0278-5846(02)00317-2.
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