Biochemical and physiological responses of halophilic nanophytoplankton (Dunaliella salina)

from exposure to xeno-estrogen 17α-ethinylestradiol

Dalel Belhaj1,2,*,  Khaled Athmouni1,3, Doniez Frikha1, Monem Kallel2, Abdelfattah El Feki3, Sami Maalej1, John L Zhou4, Habib Ayadi1

1,*University of Sfax-Tunisia, FSS, Department of Life Sciences, Laboratory of Biodiversity and Aquatic Ecosystems, Ecology and Planktonology, Street

of SoukraKm 3.5, BP 1171 CP 3000 Sfax, Tunisia

2University of Sfax-Tunisia, ENIS.Laboratory of Water-Energy-Environment,Street Soukra Km 3.5, BP 1173 CP 3038 Sfax, Tunisia

3University of Sfax-Tunisia, FSS, Department of Life Sciences, Laboratory of Animal Ecophysiology, Street of Soukra Km 3.5, BP 1171 CP 3000 Sfax,

Tunisia4University of Technology Sydney, School of Civil and Environmental

Engineering, Center of Technology in Water and Wastewater, Broadway, NSW 2007, Australia

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Corresponding author: dalel_belhaj@yahoo.fr Phone number: + 216 54 574 088Dalel Belhaj1,2,* and Khaled Athmouni1,3 contributed equally to this work. Abstract

Among different pollutants, endocrine disrupting compounds (EDCs) present a serious hazard, even though the environmental significance of these compounds remains uncertain. The aim of this study was to assess the effects of 11-day exposure to 17α-ethinylestradiol (EE2) on the growth, metabolic content, antioxidant response, oxidative stress and genetic damage of Dunaliella salina, isolated from Tunisian biotopes. The results showed that at 10 ngL-1, EE2 stimulated the growth of D. salina and increased its cellular content of photosynthetic pigments and metabolites; although it did not significantly increase the activities of superoxide dismutase (SOD), catalase (CAT) and glutathione peroxidase (GPx) or the level of malondialdehyde (MDA) and hydrogen peroxide. In contrast, exposure to high levels of EE2 concentrations (> 100 ng L-1) significantly inhibited the growth of D. salina (P < 0.05), decreased the cellular content of photosynthetic pigments, increased the cellular content of all of the metabolites and the SOD activity, and inhibited CAT and GPx activities. Hence the balance between oxidant and antioxidant enzymes was disrupted because H2O2 content along with MDA content were simultaneously increased. Interestingly, DNA damage (strand breaks) was decreased after algal exposure to EE2. The findings suggest that EE2 toxicity could potentially result in adverse impacts with consequences on the whole aquatic community.

Keywords: 17α-ethinylestradiol; Antioxidant states; Biomarkers; D. salina; Nanophytoplankton

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Introduction

Endocrine disrupting compounds (EDCs) such us estrone (E1), 17β-estradiol (E2), estriol (E3) and 17α-ethinylestradiol (EE2) are widely detected in water and wastewater, and are released into the environment through sewage discharge (Belhaj et al. 2015). With the growing release of EDCs into the aquatic ecosystems in recent years, concerns have been raised about their potential toxicity and impact to aquatic organisms. (Caldwell et al. 2012) reported that for long-term exposures to steroid estrogens in surface water, the predicted no effect concentrations (PNECs) were 6, 2, 60 and 0.1 ng L-1 for E1, E2, E3 and EE2, respectively, indicating that EE2, a derivative of the natural hormone estradiol, which is commonly used in approximately all current formulations of combined oral contraceptive pills (Aris et al. 2014), was more potent to aquatic organisms than E1, E2 and E3.

In order to protect ecological ecosystems, the study of potential toxic impact imposed by particular chemicals such EDCs has become a major concern in current environmental research. EDCs may cause the overproduction of reactive oxygen species (ROS) leading to disturbance in the antioxidant balance of aquatic organisms (Sharifi et al. 2012) and, eventually, shifting cells redox status. To counterbalance the hazard posed by ROS, photosynthetic organisms such as plants and algae have developed different antioxidant defence mechanisms. For instance, superoxide dismutase (SOD) plays a significant task in catalyzing the conversion of superoxide (O2-) to hydrogen peroxide (H2O2) and oxygen (Liu and Chen 2014), and the produced H2O2 is subsequently decomposed by catalase (CAT) and glutathione peroxidase (GPx) (Brandão et al. 2015).The measurements of various enzymes in microalgae, including SOD and CAT, are becoming increasingly trendy as they suggest swift and sensitive endpoints and are excellent indicators of environmental stresses (Gao et al. 2010). If these (among others) control mechanisms are ineffectual in preventing the establishment of an oxidative stress condition, oxidative damage including lipid peroxidation (LPO) of biological membranes, resulting in malondialdehyde (MDA) produced by degradation

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of initial products from lipid membranes by free radical attack (Wang et al. 2013) may occur at different cellular macromolecules, namely DNA, cellular proteins and lipids (Brandão et al. 2015) and, ultimately, cell death (Van Wychen and Laurens 2013a). The analysis of DNA alterations in aquatic organisms is currently the best accepted paradigms to assess the toxicity of diverse environmental contaminants, given that recent findings have shown that many types of chemicals exhibit oxidative and/or genotoxic potential on living organisms such as unicellular algae (Prado et al. 2015).

In coastal ecosystems, microalgae are a key component of food chains due to their fundamental contribution to energy conversion and ecosystem food web maintenance. Hence, it is crucial to have early assessment tools for cytotoxic and genotoxic effects at the cellular level, which could lead to disturbance in structure and productivity of the algae community which, in turn, could induce direct structural changes in the rest of the ecosystem (Martinez et al. 2015). Furthermore, phytoplankton represents an excellent aquatic model for the study of the effects of pollutant exposure at population level (Chen and Walker 2012), due to a short generation time and high sensitivities. Microalgae have also the potential to absorb lipophilic pollutants, such as EDCs from the aquatic environment (Liu et al. 2010).

The action of EDCs upon microalgae is frequently evaluated by parameters that integrate and reflect sublethal effects at population level such as growth rate, biomass, chlorophyll fluorescence and primary production (Pocock and Falk 2014). However, to shed further light on the toxic action of such micropollutants, it is useful to combine the examination of the cellular response such as cell viability and ROS production with genotoxicity (Suman et al. 2015). Herein, we studied the genotoxic and cytotoxic effects of EE2 toward Dunaliella salina, green microalgae isolated from the saline waters of Sfax, Tunisia, which serves as a potential source of natural antioxidant (Belghith et al. 2016). Besides the optimization culture condition and the traditional growth endpoint, several physiological and biochemical parameters were also investigated.

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Materials and methods

Microalgae culture conditions

Dunaliella salina, isolated from solar saltern of Sfax (Tunisia), was grown in 250 mL Erlenmeyer flasks containing 100 mL of a modified Johnson medium (Belghith et al. 2016) and cultured in homeothermic incubator with a 14/12h light/dark cycle.

Experimental and exposure procedures

17α-ethinylestradiol (EE2) (purity > 98%) was purchased from Santa Cruz Biotechnology, Inc., USA. For the exposure experiments, stock solution of EE2 (33 µg mL-1) was prepared in 0.001% (v/v) dimethylsulfoxide (DMSO; Merck, Germany) as EE2 in its original form is not soluble in water (Bell 2001).

Microalgae cells in early exponential growth phase (2*106 cells mL-1) were exposed to 3 different concentrations (10, 100 and 1000 ng L-1) of the target compound under culture conditions. Pollutant concentrations were selected to observe their potential cytotoxic effects on cultured microalgae cells, not depending of their environmental relevance. To achieve these nominal concentrations, the volume of stock solution added to the microalga cultures never exceeded 1% of final volume. Another set of flasks containing sterile Johnson medium spiked with 0.001% (v/v) DMSO (no observed effect concentration reported by (Quinn et al. 2008) and without EE2, was prepared as the control solvent. After inoculation, the flasks were closed with sterile cotton stoppers and cultured under the same condition as the pre-cultivation for 11 day. All cultures were performed at least three times in triplicate. The flasks were shaken well twice a day and before each sampling.

Algal culture (16 µL) was aseptically sampled from each flask every day. The cell number was counted using Malassez Cells in an Olympus BH-2 microscopeat with 400 times magnification. Only healthy, pigmented, unbroken cells were counted. The cell number was expressed in terms of 106 cells mL-1.

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The growth inhibition rate was calculated from the formula:

IR=(1−NN 0 )× 100 %

(1)

where N is the cell count of treated group, N0 is the cell count of the control group, and IR is the inhibition ratio.

At the end of the experiment, biomass was harvested by centrifugation at 10000 rpm for 10 min. The supernatant was discarded and the pellet was washed with deionized water. The algal pellet was freeze-dried at -20 °C until subsequent analysis.

Photosynthetic pigment determination

Pigment contents were carried out spectrophotometrically according to (Lichtenthaler and Buschmann 2001) method. Aliquots of the extracts were prepared at concentration of 1 mg mL-1 in ethanol. The absorbance of samples was measured at 470, 648 and 664 nm by a spectrophotometer (Anthelie advanced; SECOMAM). Ethanol was used as a blank. The pigment content (chlorophyll a, chlorophyll b and total carotenoids) was calculated using Lichtenthaler equations previously reported: (Chl a: chlorophyll a; Chl b: chlorophyll b; Caro: carotenoids).

Chla=13.36( A ¿¿664)−5.19( A648)¿ (2)Chlb=27.43 ( A648 )−8.12( A664) (3)Caro=1000 ( A470 )−1.63 (Chl a )−104.96(Chlb)/221 (4)

The above pigment contents were expressed as pg cell-1.

Estimation of primary metabolites: carbohydrate and protein

Soluble protein was extracted with 1 N NaOH at 90 °C for 15 min and quantified according to (Lowry et al. 1951). Absorbance was determined at 590 °C using albumin as standard. The total amount of simple sugars in the acid hydrolysates was determined by the phenol-sulfuric acid method (Van Wychen and Laurens 2013b) using glucose as a standard.

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Estimation of secondary metabolites: total phenolic content (TPC) and flavonoid

Freeze-dried cells (3.5 g) were extracted with 2 mL of 90% ethanol by sonication for 1 h at room temperature. The aqueous and organic phases were separated by centrifugation at 2000 rpm for 15 min. The supernatant (organic phase) was collected and evaporated to dryness by nitrogen gas under reduced pressure to yield the dry extracts (yield w/w: 12%). The freshly prepared crude extract of D. salina was subjected to total phenolic content and flavonoid analysis.

Total phenolic content of D. salina extract was determined using Folin-Ciocalteu method with minor modifications, using Gallic acid as a standard (Kabir et al. 2015). An aliquot of 0.5 mL of the algae extract (100 µg mL -1) was reacted with 2 mL of 10% (v/v) Folin-Ciocalteu reagent and 2 mL of 7.5% (v/v) sodium bicarbonate solution in triplicates. After 1 h of incubation at 40 °C, the absorbance of each reaction mixture was measured at 765 nm spectrophotometrically. The total phenolic content was expressed as milligram Gallic acid equivalent per gram biomass dry weight (mg GAE g-1 DW).

Flavonoid content was determined by following colorimetric method (Chang et al. 2002) with some modification. Briefly, 20 µL of extract were mixed with 20 µL of 10% aluminium chloride, 20 µL of 1M potassium acetate and 180 µL of distilled water, and left at room temperature for 30 min. The absorbance of the reaction was recorded at 415 nm. The calibration curve was prepared by using Catechin methanolic solution at concentrations of 0.05 to 0.5 µg mL-1. Flavonoid content was expressed as mg Catechin equivalent per gram of dried weight (mg CA g-1 DW).

In vitro antioxidant activity assay

The antioxidant activity of the extracts was determined by the method of scavenging ability on ABTS radical action and compared with the activity of synthetic antioxidants used in food and cosmetic industries: the BHT and vitamin C.

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ABTS-scavenging activity was determined according to the modified methodology previously reported by (Özgen et al. 2006). ABTS was generated by reacting ABTS stock solution (7 mM in 20 mM sodium acetate buffer, pH 4.5) with an oxidant (2.45 mM potassium persulfate) and left for 24 h in the dark (4 °C). The next day, ABTS working solution was obtained by dilution to an absorbance of 0.70 ± 0.01 at 734 nm. Subsequently, The reaction mixtures containing 20 μL of sample and 3 mL of reagent were incubated in a water bath at 30 °C for 30 min. As unpaired electrons were sequestered by antioxidants in the sample the test solution turned colorless and the absorbance at 734 nm was reduced. The final result was expressed as mM of Trolox equivalents (TE) per g dry weight (DW). 

Oxidative stress biomarkers: hydrogen peroxide, lipid peroxidation (TBARS) and DNA damage

Hydrogen peroxide level was determinate according to (Velikova et al. 2000). Freeze-dried biomass (0.5 mg) was homogenized in 0.1% (v/v) Trichloroacetic acid (TCA) solution and subsequently centrifuged at 10000 rpm for 10 min. 0.5 mL supernatant was mixed with 0.5 mL of 10 mM phosphate buffer (pH 7.0) and 1 mL of 1 M KI. Absorbance was recorded at 390 nm and the H2O2 level was calculated using a standard curve. H2O2

content was expressed as µmol H2O2 g-1 fresh weight (FW).The levels of lipid peroxidation in microalgae were estimated by the

content of the thiobarbituric acid reactive substances (TBARS) expressed as nM of malondialdehyde (MDA) equivalents per milligram of protein, which is a product of lipoperoxidation. TBARS content was determined by the thiobarbituric acid (TBA) reaction as described by (Buege and Aust 1978). This methodology is based on the reaction of compounds such as MDA formed by the degradation of initial products of free radical attack, with 2-TBA.

DNA damage was measured by a "DNA precipitation" assay, based on the K-SDS precipitation of DNA-protein cross link; which uses fluorescence to quantify the DNA strands

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(Gagné et al. 1995). Fluorescence reading was taken at 260 nm (excitation) and 280 nm (emission). Results were expressed as ng DNA mg-1 total protein.

Antioxidant enzyme activities

Enzyme extraction

Antioxidant enzyme activities of microalgae were determined spectrophotometrically. The algal pellets obtained as described above were resuspended in phosphate buffer solution (PBS; pH 7.4) containing 0.1 mM Ethylene diamine tetra-acetic acid (EDTA), 1 mM phenyl methyl sulfonyl fluoride and 3.75% polyvinyl pyrolidone (PVP). Cells were physically disrupted though three cycles of freezing (-80 °C) and thawing at room temperature. Broken cells were centrifuged at 10000 rpm for 20 min at 0 °C. Subsequently, the pellet was discarded and the supernatant was used for the quantification of superoxide dismutase (SOD), catalase (CAT) and glutathione peroxidase (GPx) activities. All enzymatic activities were determined in triplicate.

Superoxide dismutase (SOD)

Superoxide dismutase activity was measured by the nitro blue tetrazolium reduction method of (Beauchamp and Fridovich 1971). In this assay, one unit of SOD is defined as the amount required inhibiting the photoreduction of NBT by 50%. Riboflavin (0.26 mM) was added to start the reaction and the absorbance was recorded at 560 nm for 20 min. The activity was expressed as units per milligram of proteins (U mg-1 protein).

Catalase (CAT)

CAT activity was assessed by the procedure described by (Aebi 1984). CAT activity was quantified based on the degradation rate of H2O2, monitored at 240 nm for 5 min. The results were expressed by considering that one unit of activity equals the number of moles of H2O2 degraded per minute, per milligram of protein (U mg-1 protein).

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Glutathione peroxidase (GPx)

Glutathione peroxidase (GPx) activity was determined by the method of (Flohé and Günzler 1984). Quantification of enzymatic activity was performed by the measurement of the consumption of GSH at a wavelength of 412 nm every 2 min for 10 min, using DTNB as a substrate for the reaction. Enzymatic activity was expressed as nanomoles of reduced GSH per minute per milligram of protein (nmol reduced GSH min -1

mg-1 protein).

Fatty acid methyl esters (FAMEs)

Fatty acids profile in D. salina was determined by gas chromatography-mass spectrometry (GC-MS) after direct trans-esterification. Briefly, the microalgae was suspended in 2 mL 0.5 M H2SO4 methanol solution, 1 mL 5 % BHT-methanol solution (a synthetic antioxidant which protect fatty acids), and 20 μg of C17:0 as internal standard (Sigma-Aldrich, USA), the mixture was then heated 80 °C for 60 min. After cooling, the fatty acid methyl esters (FAMEs) were extracted with 2 mL n-hexane, vortexed, then centrifuged at 4000 rpm for 5 min. The n-hexane layer was transferred to a vial. The prepared sample was analyzed by GC (Hewlett-Packard 6890 Series, Agilent Technology) equipped with a mass spectrometer (Hewlett-Packard 5973 Mass Selective Detector, Agilent Technology) with fused silica capillary column HP-Innowax (Thickness 0.25 µm, i.d. 0.25 µm, length 60 m, Agilent Technology). The injection volume was 1 µL at a split ratio of 10/1. The initial oven temperature was 100 °C held for 2 min and then increased by 10 °C min-1 to 260 °C and held for 2 min. The temperatures of the injector port and the FID-detector were set at 260 and 290 °C, respectively. Helium was used as carrier gas at a flow rate of 1.07 mL min-1. The identification of components was assigned by matching their mass spectra with Wiley mass spectral library data.

Statistical analysis

The experiments were done in triplicate. Data were expressed as mean±SD. One-way analysis of variance (ANOVA) was used to determine

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the differences among various groups. Values were considered statistically significant when P < 0.05.

Results and discussions

Effect of EE2 on the growth and photosynthetic pigments of D. salina

To investigate the potential effects of EE2 hormone on the marine nanophytoplankton, an algae growth inhibition test was conducted by using D. salina as a model organism. This is the first systematic study focusing on the interaction of EE2 and D. salina. During the 11-day exposure, the growth of D. salina (measured as cell density) was significantly inhibited at 100 and 1000 ng L-1, exhibiting a typical concentration-response curve, while exposure to 0.001% DMSO showed no effect compared to the control (Fig. 1a). Compared to the control, EE2 concentrations of 100 and 1000 ng L-1 resulted in growth inhibition of 35.26% and 51.03%, respectively, after 11 days of exposure. Such relatively high EE2 concentrations inhibited the growth, possibly because the concentration of EE2 exceeded the tolerance limit of microalgae cells, causing the cell structure to crack and disintegrate; in this situation, the cells would be in a state of negative growth (Nie et al. 2008). However, the lowest concentration of EE2 (10 ng L-1) in this study had no inhibition effect on D. salina during the entire exposure period (Fig. 1b). In addition, no significant difference (P > 0.05) in kinetic growth was found between the control and low concentration of EE2. The lowest EE2 concentration may promote the growth of D. salina, possibly due to the promotion of certain enzymes involved in physiological and biochemical reactions. Furthermore, it is possible that the microalgae may partially degrade and absorb EE2 as a nutrient instead of toxic xenobiotic, which allowed plant cells to maintain accurate homeostatic regulation of intracellular xenobiotic levels. Thus, EE2 had a dual effect (promotion and inhibition) on the growth of D. salina, possibly causing hormesis in these microalgae. (Fong and Ford 2014) also found that hormesis is a no monotonic dose-response relationship characterised by low dose stimulation and high dose

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inhibition. Moreover, several studies have indicated that a variety of environmental contaminants including heavy metals, hydrocarbon, auxin and herbicides can cause hormesis in animals, higher plants and bacteria, which can lead to adaptation (Liu et al. 2012). Yet, the physiological mechanism by which hormesis occurs is still unknown.

Nevertheless, the evidence for a real physiological and developmental role of EE2 in algae is restricted and indecisive. Chlorophylls play a key role in all aspects of primary photosynthesis including harvesting, energy transfer, and light energy conversion. Photosynthetic pigments constitute potential biomarkers of anthropogenic stress (Zezulka et al. 2013). To further understand the effects of EE2 on photosynthesis, photosynthetic pigments were quantified at the end of the assay (11 days), with similar trends being observed (Table 1). Chlorophyll a and chlorophyll b were significantly reduced by EE2 treatments of 100 and 1000 ngL-1 over the entire exposure period (P < 0.05). This reduction of chlorophyll contents is a stress response of this green microalga. Our study indicated that this xenobiotic inhibited chlorophyll biosynthesis of D. salina and that the thylakoid may be a target site of EE2 of D. salina (Hu et al. 2004). The results of our investigation are consistent with the observation by (Pocock and Falk 2014), who reported that the photosynthetic activity of Chlamydomonas reinhardtii was significantly inhibited after EE2 exposure. This implied that EE2 reduced the maximum photochemical efficiency for electron transport in photosystem II, which indicates the involvement of carbonic anhydrase, specifically located in the thylakoid lumen involved in proton pumping across the thylakoid membranes. In contrast, at 10 ng L-1

of EE2, chlorophyll contents were increased significantly (P < 0.05) compared to the control.

Carotenoids can perform an essential role in photoprotection by quenching the triplet chlorophyll and scavenging singlet oxygen and other reactive oxygen species (Singh et al. 2010). In this study, the total carotenoids content was increased by EE2 treatments of 10 and 100 ng L-1, then decreased at the highest EE2 concentration (1000 ng L-1). This observation suggested that cells increased carotenoid contents to

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overcome oxidative stress induced by singlet oxygen, similar to SOD activity increase discussed above (Fig. 4).

Primary metabolites composition

The levels of primary metabolites in D. salina were determined in all treatments exposed to different EE2 concentrations (Fig. 2). Exposure to control and DMSO (0.001 % v/v) had no significant differences (P > 0.05). Upon low EE2 concentration (10 ng L-1), the production of protein was not affected, suggesting that the target xenobiotic at environmental relevant concentration was not suspected to influence the nutritional value of the diatom, which was one of important food sources for crustaceans and fish. For the higher EE2 concentrations (100 and 1000 ng L-1), the amount of total protein increased significantly (P < 0.05) to reach 23.8 ± 0.9 and 21.41 ± 0.58, respectively. Likewise, the carbohydrate increased with the increase of EE2 concentration. The increase in this primary metabolite at higher EE2 concentrations may be the result of the organisms’ responses to unfavorable conditions by degrading protein to provide amino acids for the synthesis of a small number of so-called stress proteins, designated heat stock proteins (HSPs), to complement more suitable for growth (Rasool et al. 2013). In this regard, under salinity stress, down regulation of genes involved in primary metabolism and protein synthesis as well as activation of genes related to autophagy and protein degradation has been observed in higher plant and microalgae.

Similar to proteins, EE2 stress significantly (P < 0.05) reduced the cellular carbohydrate levels in this green microalga. The increase in carbohydrate levels in D. salina could be the result of an exclusion process exhibited as defence mechanisms. In fact, algae divert the synthesis of carbohydrates to produce secondary metabolites that protect against oxidative stress generated by the presence of pollutants.

Secondary metabolites and antioxidative capacity of D. salina

Faced with these environmental challenges, microalgae species can generate a variety of

protective secondary metabolites, especially those that protect against the oxidative stress

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generated by the presence of xenobiotics. Polyphenols represent a group of chemical

compounds arising from a common intermediate, phenylalanine, or a close precursor,

shikimic acid (Rodrigo et al. 2014). Flavonoids are a class of phenolic metabolites that have significant antioxidant (Rodrigo et al. 2014). Table 2 shows the effects of EE2 exposure on secondary metabolites and antioxidant activity of D. salina. Results of secondary metabolites and antioxidative capacity measured at the end of the assay (11 days), indicated that D. salina exposed to control and those to DMSO (0.001 % v/v) had no significant differences (P > 0.05). The phenolic content of D. salina increased with the EE2 concentration and reached a maximum of 37.50 ± 6.04 mg GAE g-1 mg dry weight (DW). The flavonoid content varied similarly to the phenolic content, varying from 15.97 ± 3.08 mg quercetin equivalent (QEq) g-1 DW for the control to 18.54 ± 6.04 mg QEq g -1 DW at 1000 ng EE2 L-1. The results showed that the phenolic and flavonoid contents in this microalga decreased with increasing EE2 concentrations, explained by the fact these molecules contributed to protect the cells against the environmental pollution caused by the presence of EE2 in the medium. Most of these biomolecules make a significant contribution to the antioxidant activity of aquatic plants (Ferrat et al. 2003).

The antioxidant activity of D. salina was estimated through the ABTS•+

scavenging test which varied in the same way as the other secondary metabolites (Table 2). The ABTS scavenging capacity significantly increased at higher EE2 concentrations (P < 0.05) and reached a maximum of 0.218 ± 0.011 mM TEq g-1 DW and subsequently significantly decreased at 1000 ng L-1 (0.139 ± 0.015 mM TEq g-1 DW). This response was in accordance with previous work, indicating a positive correlation between non enzymatic antioxidant, including phenolic compounds and flavonoids, and antioxidant activity (Belghith et al. 2016)

Peroxidative damage and antioxidant responses

Under stress conditions microalgae produce various reactive oxygen species (ROS) such as H2O2, O2•‾ and OH•. These reactive oxygen species are highly toxic and damage protein, lipid, DNA and other cellular

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macromolecules thereby inhibiting the cell growth and ultimately leading to cell death. The results of peroxidative damage expressed as hydrogen peroxide, lipid peroxidation (TBARS) and DNA damage indicated that D. salina exposed to control and DMSO (0.001 % v/v) showed no significant differences (P > 0.05) (Fig. 3). EE2 induced oxidative stress, which was indicated by the significant increase of H2O2 and MDA measured at 100 and 1000 ng L-1 concentrations (P < 0.05). This stimulant xenobiotic produced toxic effects in D. salina (Fig. 3a, b). In addition, H2O2 was strongly enhanced, and the antioxidant enzyme activities were not adequate to scavenge ROS and prevent the photooxidation caused by high EE2 concentrations; thus, the intracellular over-accumulation of H2O2

affected membrane permeability, generated oxidative damage to biomolecules such as chloroplast pigments, nucleic acids and membrane lipids (Yang et al. 2013), and produced lipid peroxide; leading to cell dysfunction and death (Van Wychen and Laurens 2013a). Nevertheless, slight changes in the activities of antioxidant enzymes and H2O2 levels in treatment with low EE2 concentration (10 ng L-1) were observed. The response of D. salina was in agreement with hormesis, a dose response phenomenon characterized by a low dose stimulation and high dose inhibition (Fong and Ford 2014).

Significant oxidative stress was observed at high concentrations which could lead to DNA damage, which was not observed (Fig. 3c). Even though, oxidative stress can lead to permanent damage related to DNA strand breaks (Prado et al. 2015), the results from this study indicated that EE2 did not produce genotoxicity; this could be due to the fact that during 11 days of exposure, EE2 was not able to produce an irreversible damage, or due to the high efficiency of non enzymatic antioxidant responses to prevent severe damage. A significant decrease of DNA damage was observed for the lowest EE2 concentration (10 ng L-1), indicating a dose response relationship. In contrast, previous studies observed that EE2 caused oxidative DNA damage in fish (Zhu et al. 2011), amphipods (Maranho et al. 2015) and larvae (Schwaiger et al. 2000). A bioaccumulation study on the microalgae indicated a significant

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contribution from diatom to the uptake of EE2 (Liu et al. 2010). Their results suggested that EE2 would accumulate within the algae cell and pose threats to organisms at higher tropic levels.

Highly accumulated ROS in the cells are neutralized by various antioxidative enzymes such as superoxide dismutase (SOD), catalase (CAT) and glutathione peroxidase (GPx). The toxic effects of organic pollutants on microalgae are heterogeneous, and antioxidant systems are extremely important for understanding the antioxidant defence mechanisms caused by oxidative stress via the formation of ROS. Many studies have confirmed that most antioxidant enzymes activities increased under stress conditions. (Liu et al. 2012) pointed out the activities of SOD, CAT and POD increased visibly in M. aeruginosa exposed to amoxicillin. Figure 4 shows the effects of EE2 on the antioxidant enzyme activities in D. salina. SOD, CAT and GPx activities of DMSO treated group and low EE2 level (10 ng L-1) changed slightly compared to control, which showed no significant difference during the 11 days of exposure. Though, the highest concentration of EE2 significantly (P < 0.05) increased the SOD activity by 37.68% (Fig. 5a). The increased SOD activity may be attributed to the over production of superoxide, which is considered to be the central component of signal transduction, resulting in the activation of existing enzyme pools or the increased expression of genes that encode SOD (Xie et al. 2011). Different from the above enzyme, CAT and GPx activities showed a decrease of 25% and 0.42%, respectively, compared to the control at the highest concentration of EE2 (Figs 4b, 4c). Consecutively, the CAT activity was significantly suppressed by high EE2 concentrations. The decline of CAT activity could be attributed to the high amount of hydrogen peroxide generated through the SOD catalytic reaction (Fig. 4a), and the residual hydrogen peroxide might cause oxidative damage to the algal cells leading to growth inhibition (Fig. 1b). The decrease of GPx activity reflected that D. salina were under oxidative stress as a result of exposure to prooxidant chemicals. GPx enzymatic activity is efficient at protecting against damage caused by lipid peroxidation (LPO) (Brandão et al. 2015).

Fatty acid composition16

Fatty acid compositions of D. salina under different EE2 concentrations were determined by GC-MS analysis and are summarized in Table 3. The most commonly synthesized fatty acids were C16 and C18 which are appropriate for biodiesel production. Palmitic acid (C16:0), linoleic acid (C18:2) and linolenic acid (C18:3) were the most abundant fatty acids found in of D. salina, comprising 32.91%, 28.59% and 12.37% of total fatty acids in the control (Table 3). DMSO (0.001 % v/v) and low EE2 concentration (10 ng L-1) had no effects on fatty acids profile. However, distinct changes were clearly found under high EE2 concentrations that the sum of saturated fatty (SFA) and monounsaturated fatty acids (MUFA) increased from 36.18% to 50.46% and from 11.04% to 31.44%, respectively, accompanying with the decrease of polyunsaturated fatty acids (PUFA). Thus, LPO is an important consequence of oxidative stress (Wang et al. 2013). Consequently D. salina exposed to high EE2 concentrations (100 and 1000 ng L-1) exhibited a significant rise in LPO levels measured as MDA content (Fig. 3b), induced saturation of fatty acids by increasing SFA and MUFA levels and decreasing PUFA levels (Fig. 2, supplemental section). According to previous reports, high levels of SFA and MUFA combined with low level of PUFA are essential for biodiesel (Ben Moussa-Dahmen et al. 2016). The appearance of new components C19:0, C21:0 and C23:0 (Table 3) indicates that EE2 can affect the composition of the cell membrane.

Conclusions

In summary, xeno-estrogen EE2 inhibited the growth of D. salina at high concentrations, but stimulated its growth at relatively low concentration. High EE2 concentrations decreased the cellular content of photosynthetic pigments, stimulated the mechanism related to metabolic content production as well as antioxidant mechanisms by increasing the SOD activity. In contrast, CAT and GPx activities were not induced by EE2 exposure. The antioxidant enzymes was not sufficiently enough to degrade the over production of H2O2, leading to lipid peroxidation occurrence. Moreover, EE2 did not cause genotoxicity. Further research is

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required to explore the biomolecular mechanism of EE2 effect on nanophytoplankton in terms of effects indicators and receptors, and target biomarkers.

Acknowledgments

This research was supported by the research unit of Biodiversity and Aquatic Ecosystems, Ecology and Planktonology, and the Ministry of Higher Education, Scientific Research and Technology of Tunisia.

Conflict of interest declaration

The authors declare that this research was conducted in the absence of any commercial or financial relationships that could be regarded as potential conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

References

Aebi H (1984) Catalase in vitro. MethodEnzymol 105:121-126 Aris AZ, Shamsuddin AS, Praveena SM (2014) Occurrence of 17α-

ethynylestradiol (EE2) in the environment and effect on exposed biota: a review. Environ Int 69:104-119

Beauchamp C, Fridovich I (1971) Superoxide dismutase: improved assays and an assay applicable to acrylamide gels. Anal Biochem 44(1):276-287

Belghith T, Athmouni K, Bellassoued K, El Feki A, Ayadi H (2016) Physiological and biochemical response of Dunaliella salina to cadmium pollution. J Appl Phycol 28(2):991-999

Belhaj D, Baccar R, Jaabiri I, Bouzid J, Kallel M, Ayadi H, Zhou JL (2015) Fate of selected estrogenic hormones in an urban sewage treatment plant in Tunisia (North Africa). Sci Total Environ 505:154-160

18

Bell AM (2001) Effects of an endocrine disrupter on courtship and aggressive behaviour of male three-spined stickleback, Gasterosteus aculeatus. Anim Behav 62(4):775-780

BenMoussa-Dahmen I, Chtourou H, Rezgui F, Sayadi S, Dhouib A (2016) Salinity stress increases lipid, secondary metabolites and enzyme activity in Amphora subtropica and Dunaliella sp. for biodiesel production. Bioresource Technol218:816-825

Brandão F, Cappello T, Raimundo J, Santos MA, Maisano M, Mauceri A, Pacheco M, Pereira P (2015) Unravelling the mechanisms of mercury hepatotoxicity in wild fish (Liza aurata) through a triad approach: bioaccumulation, metabolomic profiles and oxidative stress. Metallomics 7(9):1352-1363

Buege JA, Aust SD (1978) [30] Microsomal lipid peroxidation. MethodEnzymol 52:302-310

Caldwell DJ, Mastrocco F, Anderson PD, Länge R, Sumpter JP (2012) Predicted‐no‐effect concentrations for the steroid estrogens estrone, 17β‐estradiol,

estriol, and 17α‐ethinylestradiol. Environ Toxicol Chem 31(6):1396-1406 Chang C-C, Yang M-H, Wen H-M, Chern J-C (2002) Estimation of total

flavonoid content in propolis by two complementary colorimetric methods. J food Drug Anal 10(3):178-182

Chen Y-H, Walker TH (2012) Fed-batch fermentation and supercritical fluid extraction of heterotrophic microalgal Chlorella protothecoides lipids. Bioresource Technol 114:512-517

Ferrat L, Pergent-Martini C, Roméo M (2003) Assessment of the use of biomarkers in aquatic plants for the evaluation of environmental quality: application to seagrasses. Aquat Toxicol 65(2):187-204

Flohé L, Günzler WA (1984) [12] Assays of glutathione peroxidase. MethodEnzymol 105:114-120

Fong PP, Ford AT (2014) The biological effects of antidepressants on the molluscs and crustaceans: a review. Aquat Toxicol 151:4-13

Gagné F, Trottier S, Blaise C, Sproull J, Ernst B (1995) Genotoxicity of sediment extracts obtained in the vicinity of a creosote-treated wharf to rainbow trout hepatocytes. ToxicolLett 78(3):175-182

19

Gao C, Zhai Y, Ding Y, Wu Q (2010) Application of sweet sorghum for biodiesel production by heterotrophic microalga Chlorella protothecoides. Appl Energ 87(3):756-761

Hu Zq, Liu Yd, Li Dh (2004) Physiological and biochemical analyses of microcystin‐RR toxicity to the cyanobacterium Synechococcus elongatus.

EnvironToxicol 19(6):571-577

Kabir F, Tow WW, Hamauzu Y, Katayama S, Tanaka S, Nakamura S (2015) Antioxidant and cytoprotective activities of extracts prepared from fruit and vegetable wastes and by-products. Food Chem 167:358-362

Lichtenthaler HK, Buschmann C (2001) Chlorophylls and carotenoids: Measurement and characterization by UV‐VIS spectroscopy. Curr

protocolFood Anal ChemF4.3.1-F4.3.8Liu J, Chen F (2014) Biology and industrial applications of Chlorella:

Advances and prospects Microalgae Biotechnology. Springer, pp 1-35

Liu Y, Guan Y, Gao Q, Tam NFY, Zhu W (2010) Cellular responses, biodegradation and bioaccumulation of endocrine disrupting chemicals in marine diatom Navicula incerta. Chemosphere 80(5):592-599

Liu Y, Tam NFY, Guan Y, Gao B (2012) Influence of a Marine Diatom on the Embryonic Toxicity of 17α-Ethynylestradiol to the Abalone Haliotis diversicolor supertexta. Water Air Soil Poll 223(7):4383-4395

Lowry OH, Rosebrough NJ, Farr AL, Randall RJ (1951) Protein measurement with the Folin phenol reagent. J biol Chem 193(1):265-275

Maranho LA, Moreira LB, Baena-Nogueras RM, Lara-Martín PA, DelValls T, Martín-Díaz ML (2015) A candidate short-term toxicity test using Ampelisca brevicornis to assess sublethal responses to pharmaceuticals bound to marine sediments. ArchEnviron Contam Toxicol 68(2):237-258

Martinez RS, Di Marzio WD, Sáenz ME (2015) Genotoxic effects of commercial formulations of Chlorpyrifos and Tebuconazole on green algae. Ecotoxicology 24(1):45-54

20

Nie X, Wang X, Chen J, Zitko V, An T (2008) Response of the freshwater alga Chlorella vulgaris to trichloroisocyanuric acid and ciprofloxacin. Environ Toxicol Chem 27(1):168-173

Özgen U, Mavi A, Terzi Z, Yιldιrιm A, Coşkun M, Houghton P (2006) Antioxidant properties of some medicinal Lamiaceae (Labiatae) species. Pharmbiol 44(2):107-112

Pocock T, Falk S (2014) Negative Impact on Growth and Photosynthesis in the Green Alga Chlamydomonas reinhardtii in the Presence of the Estrogen 17α-Ethynylestradiol. PloS one 9(10):e109289

Prado R, García R, Rioboo C, Herrero C, Cid Á (2015) Suitability of cytotoxicity endpoints and test microalgal species to disclose the toxic effect of common aquatic pollutants. EcotoxEnviron Safe 114:117-125

Quinn B, Gagne F, Blaise C (2008) An investigation into the acute and chronic toxicity of eleven pharmaceuticals (and their solvents) found in wastewater effluent on the cnidarian, Hydra attenuata. Sci Total Environ389(2-3):306-14

Rasool S, Hameed A, Azooz M, Siddiqi T, Ahmad P (2013) Salt stress: causes, types and responses of plants Ecophysiology and Responses of Plants under Salt Stress. Springer, pp 1-24

Rodrigo R, Libuy M, Feliu F, Hasson D (2014) Polyphenols in disease: from diet to supplements. CurrPharm Biot 15(4):304-317

Schwaiger J, Spieser O, Bauer C, Ferling H, Mallow U, Kalbfus W, Negele R (2000) Chronic toxicity of nonylphenol and ethinylestradiol: haematological and histopathological effects in juvenile Common carp (Cyprinus carpio). Aqua toxicol 51(1):69-78

Sharifi Y, Hasani A, Ghotaslou R, Varshochi M, Hasani A, Aghazadeh M, Milani M (2012) Survey of virulence determinants among vancomycin resistant Enterococcus faecalis and Enterococcus faecium isolated from clinical specimens of hospitalized patients of North west of Iran.Open microbiol J 6(1):34-39

Singh AK, Elvitigala T, Cameron JC, Ghosh BK, Bhattacharyya-Pakrasi M, Pakrasi HB (2010) Integrative analysis of large scale expression

21

profiles reveals core transcriptional response and coordination between multiple cellular processes in a cyanobacterium. BMC System Biol 4(1):105

Suman T, Rajasree SR, Kirubagaran R (2015) Evaluation of zinc oxide nanoparticles toxicity on marine algae Chlorella vulgaris through flow cytometric, cytotoxicity and oxidative stress analysis. EcotoxicolEnviron Safe 113:23-30

Van Wychen S, Laurens L (2013a) Determination of total lipids as fatty acid methyl esters (FAME) by in situ transesterification. Contract 303:375-300

Van Wychen S, Laurens LM (2013b) Determination of total carbohydrates in algal biomass. Contract 303:275-3000

Velikova V, Yordanov I, Edreva A (2000) Oxidative stress and some antioxidant systems in acid rain-treated bean plants: protective role of exogenous polyamines. Plant Sci 151(1):59-66

Wang S, Chen F, Mu S, Zhang D, Pan X, Lee D-J (2013) Simultaneous analysis of photosystem responses of Microcystis aeruginoga under chromium stress. Ecotoxicol Environ Safe 88:163-168

Xie X, Zhou Q, Lin D, Guo J, Bao Y (2011) Toxic effect of tetracycline exposure on growth, antioxidative and genetic indices of wheat (Triticum aestivum L.). Environ Sci Poll Res 18(4):566-575

Yang D-J, Lin J-T, Chen Y-C, Liu S-C, Lu F-J, Chang T-J, Wang M, Lin H-W, Chang Y-Y (2013) Suppressive effect of carotenoid extract of Dunaliella salina alga on production of LPS-stimulated pro-inflammatory mediators in RAW264. 7 cells via NF-κB and JNK inactivation. J Funct Food 5(2):607-615

Zezulka Š, Kummerová M, Babula P, Váňová L (2013) Lemna minor exposed to fluoranthene: growth, biochemical, physiological and histochemical changes. Aqua Toxicol 140:37-47

Zhu X, Zhang Y, Bjornsdottir G, Liu Z, Quan A, Costanzo M, López MD, Westholm JO, Ronne H, Boone C (2011) Histone modifications influence mediator interactions with chromatin. Nucleic Acids Res 39(19):8342-8354

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Figure captions

Figure 1. Daily growth (a) and inhibition rate (b) of D. salina during 11 days of exposure to EE2. Figure 2. Primary metabolites (mean ± SD; n=3) measured in D. salina during 11 days of EE2 exposure. Figure 3. Hydrogen peroxide, lipid peroxidation (TBARS) and DNA damage biomarkers stress (mean ± SD; n=3) in D. salina, after 11 days of EE2 exposure compared with the control, and microalgae spiked with DMSO and EE2.Figure 4. Superoxide dismutase (SOD), catalase (CAT) and glutathione peroxidase (GPx) enzymatic activities (mean ± SD; n=3) in D. salina, after 11 days of EE2 exposure compared with the control, and microalgae spiked with DMSO and EE2.Figure 5. Saturated, mono and poly unsaturated fatty acid composition (%) of D. salina under EE2 contamination.

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