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Use of Tridacna maxima, a bivalve in the biomonitoring of the Saudi Arabian Red Sea coast
Marine Pollution Bulletin 150 (2020) 110766
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Use of Tridacna maxima, a bivalve in the biomonitoring of the Saudi Arabian Red Sea coast
T
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Norah Salem Al-Howitia,1, Zouhour Ouanes Ben Othmena,b,1, , Abdelwaheb Ben Othmanea, Amel Hamza Chaffaib a b
Department of Biology, College of Sciences, Taibah University, Al Madinah Al Munawarah, Saudi Arabia Environmental and Marine Unit Research, UR 09-03, IPEIS Sfax University, Tunisia
A R T I C LE I N FO
A B S T R A C T
Keywords: Tridacna maxima Biomonitoring Red Sea coasts Oxidative stress Genotoxicity Neurotoxicity
The present study is an attempt to assess the effects of contamination of several sites in the Red Sea coasts of Saudi Arabia using bivalves as a biomonitoring tool. Oxidative stress biomarkers (including reduced glutathione level (GSH), glutathione-S-transferase activity (GST), Malondialdehyde level (MDA) and Catalase activity (CAT)), neurotoxicity acetylcholinesterase activity (ACHE), and genotoxicity micronucleus rate (MN) were measured in three distinct tissues - digestive glands, gills and mantle - of specimens of the giant clam Tridacna maxima, collected from five sites in Saudi Arabian Red Sea coast (Al-Khuraybah, Al-Wajh, Yanbu, Rabigh and Thuwal). Our results demonstrated that T. maxima showed differential biomarker responses according to the nature of pollutants and human activity that affect the coast. This study can be considered as the first one using biomarkers to assess the state of the Red Sea coast in Saudi Arabia which must be followed by periodic studies for surveillance of aquatic pollution.
1. Introduction For the last 30 years, human activities on the coastal space of the Kingdom of Saudi Arabia (KSA) have increased in a significant manner and resulted in the continuous invasion of various kinds of pollutants such as significant amounts of heavy metals and chemicals from oil refineries that are located along the Red Sea coasts. Whereas treatment units of all refineries in KSA are equipped with wastewater treatment units, their effluents are considered pollutants to the marine environment (Tortell, 2004; Badr et al., 2009; Al-Sofyani et al., 2014; Alzahrani et al., 2018; Baalkhuyur et al., 2018). The marine environment can be contaminated by many types of pollutants that can be either mineral or organic. Although chemicals can be analysed qualitatively and quantitatively by chemical procedures, adverse effects of the complex mixtures of those pollutants cannot be assessed (Hamza-Chaffai, 2014). In fact, the impact of those chemicals on the aquatic organisms cannot be revealed due to their potential synergistic/antagonistic effects. This is the reason why investigations of appropriate biomarkers of toxicity in living organisms are considered an alternative assessment technique of pollutant impact (Martinez-Haro et al., 2015). These parameters are investigated to
assess the adverse effect on physiological functions in the studied organisms and therefore the impact of environmental changes on population and community can be explained or expected (Hamza-Chaffai, 2014; Van der Oost et al., 2003). Among those, Antioxidant parameters like catalase (CAT), reduced Glutathione (GSH) and Glutathione-Stransferase (GST) are considered as helpful biomarkers which reflect the impact of some pollutants that exhibit their toxicities by generating oxidative stress (Livingstone, 2001). Moreover, high concentrations of malondialdehyde (MDA), an ultimate product of membrane lipid peroxidation, is related to the presence of oxidative pollutants in the environment or from free radicals generated by their metabolism (Sunderman and William, 1987; Wahsha et al., 2012). Otherwise, neurotoxic biomarkers such as acetylcholinesterase activity (AChE) have been used as biomarkers of exposure to many toxin chemicals, especially pesticides in aquatic environments (Oliveira et al., 2007). Because large scale biomonitoring programs have shown the association between genotoxicity and chronic health effects at the population level (Bolognesi and Cirillo, 2014), a high number of genotoxicity assays have been used to assess the genotoxic potential of polluted areas. The micronucleus (MN) assay is considered as one the most important techniques used for this purpose due to its reliability, simplicity and its
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Corresponding author at: Department of Biology, College of Sciences, Taibah University, Al Madinah Al Munawarah, Saudi Arabia. E-mail address: [email protected] (Z. Ouanes Ben Othmen). 1 Both authors contribute equally. https://doi.org/10.1016/j.marpolbul.2019.110766 Received 13 May 2019; Received in revised form 18 November 2019; Accepted 20 November 2019 Available online 06 December 2019 0025-326X/ © 2019 Elsevier Ltd. All rights reserved.
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applicability to many types of cells (Hose, 1994; Hughes and Hebert, 1991). Otherwise, contamination of aquatic organisms such as bivalves with different contaminants has been proven to be a risk to human health through their incorporation in the food chain (Bikham et al., 2000). In this survey, we chose to use the giant clam Tridacna maxima (Röding, 1798), an ecologically and economically important species of the Red Sea. It is the most widely distributed and an important species of giant clam. It has a large geographic distribution from the Red Sea and Western Indian Ocean across the Indo-Malay Archipelago to the Tuamotu Archipelago in the central Pacific and lives in coastal reef areas, attached to its substrate with a byssus (Bin Othman et al., 2010; Ayala et al., 1973). Like most bivalve mollusks, it belonged to filter feeder organisms (Klumpp and Lucas, 1994) and therefore it is a pollutant-accumulator such as described by Madkour (2005) for heavy metals in different sites in the Egyptian Red Sea coast (Madkour, 2005). In the present study, we used three different tissues: digestive glands (GSH, GST, and MDA), mantle (AChE) and gills (GSH, GST, MDA, CAT, and MN). Gills, by their main function of respiration, are considered as the first organs to be exposed to pollutants and constitute the major absorption site for dissolved pollutants (Banni et al., 2017) and have been shown to be very sensitive to a wide range of toxicants in several types of aquatic animals such as fish species (Hayashi et al., 1998). Digestive glands are the organs where all xenobiotics must pass to be metabolized in order to be excreted and consequently they become more reactive and they may accumulate there (Almeida et al., 2003; Kim et al., 2017). For these reasons, digestive glands were shown to exhibit high levels of oxidative stress (Lau and Wong, 2003; Power and Sheehan, 1996; Soldatov et al., 2007). The Mantle is chosen for neurotoxic activity because it is considered as the most innervated organ; in fact, the mantle is the organ responsible for sensory and regulation functions (Saleuddin, 1979) and is considered as the main neural and sensory network (Bauchau, 2001). This survey can be considered as an attempt to assess the contamination in marine environment of several sites along the Red Sea coasts of Saudi Arabia using T. maxima as a biomonitoring species and oxidative stress, neurotoxic and genotoxic parameters as a multi-biomarkers approach.
Fig. 1. Map of the Red Sea coast of Saudi Arabia, showing the location of the five sampling sites: T (Thuwal), R (Rabigh), Y (Yanbu), A (Al-Wajh) and K (Alkhuraybah).
−80 °C until biochemical analysis. All techniques were adapted to micro-titration; so the variation in absorbance was quantified using a micro-plate reader. Total proteins were determined according to Bradford (1976); bovine serum albumin was used as the standard.
2. Material and methods 2.1. Study area Five sampling stations were chosen (Fig. 1) on the eastern coasts of the Red Sea in Saudi Arabia. These Five sampling sites are: Thuwal (N22°17.445′ E38°58.018′) (T), Rabigh (N22°50′05.92 E38°44′29.98) (R), Yanbu (N24°8.84076′ E37°56.07444′) (Y), Al-Wajh (N25°58.126′ E36°38.598′) (A) and Al-Khuraybah (N28°2′18.7692E35°4′38.6976) (K).
2.3.1. Oxidative stress biomarkers Some relevant oxidative stress parameters were performed in this study such as Reduced glutathione (GSH) rate, which was assessed using the method described by Moron et al. (1979) with adjustment of volumes to be adapted to microtitration. In fact, supernatants were precipitated with TCA 5% (trichloroacetic acid) and the precipitate was removed after centrifugation (5000g for 10 min, at 4 °C). The absorbance of the substance formed when 5,5′-dithio-2-nitrobenzoic acid (DTNB) is reduced by glutathione was read at 405 nm. Pure reduced Glutathione was the standard to assess the rate of GSH in tissues expressed as nmoles GSH/mg of proteins. The Glutathione S-Transferase (GST) activity assay was also performed. This assay is based on the utilization of 1-chloro-2, 4-dinitrobenzene (CDNB), which was the substrate for GST. Conjugation of CDNB with GSH (by chloro-substitution) results in a change in absorbance of the compound at 340 nm; in our case we adapted the test to micro-titration according to Mannervik and Guthenberg (1981) by adding in each well 10 μl of the supernatant, 20 μl of the substrate (GSH), 20 μl of CDNB and 200 μl of the phosphate buffer. GST activity was expressed as μmol/min/mg of proteins. Malondialdehyde (MDA) assay is based on the reaction between a Chromogenic reagent, 2-Thiobarbituric Acid (TBA), and MDA at 25 °C. The Chromophore (pink colour) complex can absorb light at 492 nm. MDA levels were determined according to the method of
2.2. Sample collection For each station, 10 specimens of Tridacna maxima (Röding, 1798) at the same gonad development stage with shell length 12 ± 3 cm were sampled in February and March 2014. Once in the laboratory, the collected specimens of T. maxima were immediately dissected. Digestive glands, gills and mantle were removed, then weighed and stored at −80 °C until analyses. 2.3. Biomarker analysis Digestive glands, gills and mantle were homogenized with an ULTRA TURRAX (IKA© T18 basic & TISSUE – REAROR Model 985370 – BioSpecProducts, Inc) in a Phosphate Buffer (pH 7.6) (4 ml for 1 g of tissue). The homogenates were then centrifuged at 5000g for 30 min. All procedures were carried out at 4 °C. The supernatant was frozen at 2
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Ohkawa et al. (1979). MDA was used as the standard and expressed as mmol/mg of protein. For catalase activity assay, the Cohen et al. (1996) method was used to evaluate Catalase activity (CAT) and adapted for microtitration by reducing all reaction volumes to 1/5. Absorbance was read on 492 nm, after every 30 s 10 times. The CAT activity was expressed as μmol/mg of protein/min. 2.3.2. Neurotoxicity biomarker: acetylcholinesterase (AChE) activity assay Acetylcholinesterase activity (AChE) was estimated, as described by Ellman et al. (1961) and adapted to microtitration by Galgani and Bocquene (1991) by a colorimetric method. The absorption was measured at 450 nm. AChE is expressed as nmol/min/mg of protein.
Fig. 3. Glutathione s-transferase (GST) activity, expressed as (μmol/min/mg of protein), in digestive gland and gill of T. maxima collected from various sites of Saudi Arabia coasts: (K (Al-Khuraybah), A (Al-Wajh), Y (Yanbu), R (Rabigh), and T (Thuwal)). Values: mean ± standard deviation. Differences between sites attributed with small letters were a: statistically different from all other sites based on digestive glands results; b: non-statistically different sites based on gills results (p < 0.05).
2.3.3. Genotoxicity biomarker: micronucleus assay (MN) The micronuclei assay was done according to Baršienė et al. (2004). Briefly, gills tissue was spread on a slide and dried in the open air. Slides were then fixed in methanol/actique acid (3/1) for 2 min then stained in Giemsa 4% for 15 min. The slides were analysed under a light microscope at a final magnification of 1000× with a drop of oil immersion. Scoring involved 2000 of gill cells of five specimen for each slide.
(185.26 ± 56.10 nmol/mg of protein) is the highest in comparison to sites (A) (49.21 ± 13.12 nmol/mg of protein) (p < 0.05) and (R) (68.83 ± 27.13 nmol/mg of protein) (p < 0.05) (Fig. 2).
2.4. Statistical analysis
3.1.2. Glutathione-S-transferase (GST) There was a significant difference in GST activity values found in digestive glands collected from Al-Wajh(A) site (1.61 ± 0.49 μmol/ min/mg of protein) compared to all other sites (p < 0.05). Whereas, there were no significant differences found among the remaining sites (p < 0.05). As well as in gills, where no significant differences registered in GST activity among sampling sites (Fig. 3) was registered (p < 0.05).
Results of biochemical and genotoxic biomarkers are presented as means ± standard deviation (SD). Comparison of these parameters between the different studied sites was performed by Tukey honest significant difference assay after an ANOVA test was performed and showed significant F values. Differences were significant when p < 0.05. The software Statistica 10.0 (Stat- Soft, Tulsa, USA) was used. 3. Results
3.1.3. Malonedialdehyde (MDA) Our results showed that the level of MDA was highest in the digestive glands compared to the gills of T. maxima collected for all sites (Fig. 4). Significantly high MDA levels were noted in the digestive glands of T. maxima collected from site (A) (138.48 ± 16.98 nmol MDA/mg of protein) (p < 0.05) compared other sites, while a significant decrease in MDA level was registered in the digestive glands from site (T) (37.51 ± 5.36 nmol/mg of protein) (p < 0.05) compared to both sites (A) (138.48 ± 16.98 nmol MDA/mg of protein) and (K) (61.36 ± 5.30 nmol MDA/mg of protein). In the gills, significantly high MDA levels were recorded in both sites (K) and (T) with respective values of 22.99 ± 3.86 nmol MDA/mg of protein and 20.68 ± 5.58 nmol MDA/mg of protein compared to the remaining
3.1. Oxidative stress biomarkers results 3.1.1. Reduced glutathione (GSH) GSH variation in gills and digestive glands show a variation among the different study sites. In fact, the level of GSH registered from site (A) showed a significant increase (648.20 ± 196.89 nmol/mg of protein) in digestive glands compared to site (Y) (404.17 ± 135.94 nmol/mg of protein) (p < 0.05) and a non-significative increase compared to all other sites, whereas in gills, the level decreased significantly (p < 0.05) in site (A) (49.21 ± 13.12 nmol/mg of protein) and site (R) (68.83 ± 27.13 nmol/mg of protein) compared to the other sites (Fig. 2). Likewise, the level of GSH registered in gills from site (K)
Fig. 4. Malonedialdehyde (MDA), expressed as (nmol/mg of protein) in digestive gland and gills of T. maxima collected from various sites of Saudi Arabia coasts: (K (Al-Khuraybah), A (Al-Wajh), Y (Yanbu), R (Rabigh), and T (Thuwal)). Values: mean ± standard deviation. Differences between sites attributed with small letters were a: statistically different from (A) based on digestive glands. b: statistically different from (T) based on digestive glands results; c: statistically different from (K) based on gills results; d: statistically different from (T) based on gills results (p < 0.05).
Fig. 2. Reduced Glutathione (GSH), expressed as (nmol/mg of protein), indigestive glands and gills of T. maxima collected from various sites of Saudi Arabia coasts: (K (Al-Khuraybah), A (Al-Wajh), Y (Yanbu), R (Rabigh), and T (Thuwal)). Values: mean ± standard deviation. Differences between sites attributed with small letters were a: statistically different from (A) based on digestive glands results; b: statistically different from (A) based on gills results; c: statistically different from (R) based on gills results (p < 0.05). 3
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Fig. 5. Catalase activity, expressed as (μmol/min/mg of protein) in gill of T. maxima collected from various sites of Saudi Arabia coasts: (K (Al-Khuraybah), A (Al-Wajh), Y (Yanbu), R (Rabigh), and T (Thuwal)). Values: mean ± standard deviation. Differences between sites attributed with different letters were a: statistically different from (R) based on gills results; b: statistically different from (A) based on gills results (p < 0.05).
Fig. 7. Micronucleus rate (MN) expressed as (MN/1000 cells) in gills of T. maxima collected from various sites of Saudi Arabia coasts (K (Al-Khuraybah), A (Al-Wajh), Y (Yanbu), R (Rabigh), T (Thuwal)) Values mean ± standard deviation. Differences between sites attributed with small letters were a: statistically different from (K); b: statistically different from (R) based on gills results (p < 0.05).
sampling sites which have values of 7.27 ± 1.16 nmol MDA/mg of protein, 5.20 ± 1.59 nmol MDA/mg of protein and 4.64 ± 1.59 nmol/mg of protein for the sites (A), (Y) and (R) respectively at p < 0.05 (Fig. 4).
3.3. Genotoxicity biomarker results: micronucleus test MN frequency test performed in gills tissues found high counts of micronucleated cells in samples from sites (R) (6.34 ± 0.63 MN cells/ 1000 cells) (p < 0.05), (A) (5.46 ± 1.27 MN cells/1000 cells) and (Y) (3.60 ± 1.43 MN cells/1000 cells) (p < 0.005) compared to site (K) which represented the lowest count of (MN) (1.59 ± 1.08 MN cells/ 1000 cells). However, low counts of MN frequency were recorded in site (T) (3.60 ± 1.43 MN cells/1000 cells) compared to counts of MN cells registered in site (R) (6.34 ± 0.63 MN cells/1000 cells) (p < 0.05) (Fig. 7).
3.1.4. Catalase activity (CAT) Catalase activity was significantly higher in the gills from site (T) (294.41 ± 47.35 μmol/min/mg of protein) (p < 0.05) compared to sites (K) (228.43 ± 77.60 μmol/min/mg of protein), (Y) (214.58 ± 77.32 μmol/min/mg of protein) and (A) (138.05 ± 20.13 μmol/min/mg of protein) (Fig. 5). The lowest of this enzymatic activity was significantly observed in the measured results from site (R) (110.55 ± 21.92 μmol/min/mg of protein) (p < 0.05) (Fig. 5).
4. Discussion The Red Sea is considered one of the most important repositories of marine biodiversity in the world (PERSGA, 2006). Human activities in the coastal area of Saudi Arabia have increased in a significant manner with an increasing introduction of different of pollutants such as heavy metals and industrial sewage (Badr et al., 2009; Al-Mur et al., 2017; AlSofyani et al., 2014; Alzahrani et al., 2018). Biomarkers are considered as valuable tools for marine pollution monitoring and have been largely used to assess the coastal environment quality during recent years (Hamza-Chaffai, 2014; Damiens et al., 2007). In fact, many studies have demonstrated that there is an important and significant variation of antioxidant parameters in aquatic organisms coming from polluted and unpolluted sites (Livingstone, 2001; Balbi et al., 2017; Van Veld et al., 2018). Thus, the presence of chemical contaminants induces variations in antioxidant parameters, which can be used as biomarkers because they are able to differentiate between polluted areas and areas with lower human impact (Santovito et al., 2005; Box et al., 2007). In this study, a multi-biomarker approach was used to assess the level of pollution of different areas: CAT, GSH, GST, MDA, AChE and MN. These biomarkers were largely used and chosen because they have been proven suitable for monitoring the effects of pollutants on sentinel organisms (Dailianis, 2011). Benthic organisms are usually used as sentinel species for biomonitoring of coastal environments, and specially bivalves (De LucaAbbott et al., 2005; Gorman et al., 2017; Burgeot et al., 2017). We have chosen as a study species the giant clam Tridacna maxima for several reasons: it is abundant in the Red Sea (Andrew and Lance, 1993; Richter et al., 2008; Nuryanto and Kochzius, 2009; Neo et al., 2017), it can accumulate high levels of pollutants without dying, it occupies an important position in the food cycle and it is considered as a secondary consumer (Jones et al., 1986; Neo et al., 2015). Moreover, it serves as a filter-feeding organism and can absorb even the smallest particles like all bivalves (Livingstone, 1993). For these reasons, we chose to use T. maxima as a model organism for monitoring several sites along Red Sea coast in Saudi Arabia.
3.2. Neurotoxicity biomarker results: acetylcholinesterase activity (AChE) Samples from sites (R) and (K) exhibited lower AChE activity in the mantle (p < 0.05) with minimum values (5.69 ± 2.16 nmol/min/mg of protein), (9.17 ± 3.90 nmol/min/mg of protein) respectively. Whereas, in samples from site (A), a significantly higher AChE activity value was found in the mantle (37.29 ± 11.87 nmol/min/mg of protein) (p < 0.05) compared to the remaining sampling sites (Fig. 6). Sites (A) (37.29 ± 11.87 nmol/min/mg of protein), (Y) (28.19 ± 8.12 nmol/min/mg of protein) and (T) (24.06 ± 9.01 nmol/min/mg of protein) denote higher AChE activity in the mantle in comparison with sites (K) and (R).
Fig. 6. AChE activity, expressed as (nmol/min/mg of protein) in mantle of T. maxima collected from various sites of Saudi Arabia coasts: (K (Al-Khuraybah), A (AlWajh), Y (Yanbu), R (Rabigh), and T (Thuwal)). Values mean ± standard deviation. Differences between sites attributed with small letters were a: statistically different from (K); b: statistically different from (A); c: statistically different from (T) (p < 0.05). 4
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Commission for Jubail and Yanbu» that implement many environmental protection procedures and evaluate the impact of industrial activities on the air, water, soil and the health of humans (RCJY, 2015). Our results are in accordance with the survey conducted by Badr et al. (2009) where Rabigh is found to be more polluted than Yanbu based on the Pollution Load Index for metal pollution recorded in core sediments where Yanbu is found to be the least contaminated area compared to Rabigh and Jeddah except for Nickel (Ni). Concerning the Al-Wajh site, we observed a significant increase of all oxidative stress biomarkers (GSH, GST, MDA) in digestive glands compared to all other studied sites. Contrarily, in the gills, normal values were recorded for all oxidative stress parameters. This can be an indication of long-term exposure and/or a relatively acute old contamination (Almeida et al., 2003; Mezzelani et al., 2018). Likewise, MN frequency recorded in samples from site Al-Wajh was the most significant compared to all other sites. The same result was reported in gills in previous studies from sites polluted with urban wastes (Izquierdo et al., 2003) and from polluted sites with PCBs and DDTs (Schiedek et al., 2006) using Mytilus edulis in both studies. This result was expected as oxidative stress biomarkers are elevated in this site and the majority of substances which induce oxidative stress were found to be genotoxic too (Gagné et al., 2008). Generally, Al-Wajh is considered on the lowest level of direct threat from human impacts due to the absence of industrial and agricultural activities, except for water desalination plant activity (SWCC, 2015; Tuthill, 1987). Desalting processes are normally associated with the rejection of high concentrations of chemicals on open sea waste from the plant itself or from the pre-treatment units as well as during the cleaning period to improve plant performances. Moreover, heavy metals coming from corrosion and chemical from brines were also discharged to the sea (Al-Mutaz, 1991; Höpner and Lattemann, 2003). Adding to this, constant discharges of high salinity and high temperature streams were noted by these plants and was found to be fatal for marine life, and cause many changes in the entire population at the discharge site. In addition, benthic communities, such as bivalves, may thus be affected as a consequence of high salinity and chemical residuum (Lattemann and Höpner, 2008). Those factors may be able to explain the obtained results in this survey. Moreover, the large drainage basin, which has an area of 104,977 km2 and feeds the Saudi Arabian Red Sea at Al-Wajh, may be loaded with waste matter from different parts of the surrounding areas (Rowlands et al., 2014) and seems to be the principle cause of increase of MN frequency and oxidative stress biomarkers in this site. Our results demonstrated the altered metabolic response of T. maxima, probably due to the presence of pollutants that can alter other living organisms and ecosystems such as described by DeVantier et al. (2000) and Hariri (2012) that mentioned the presence of heavily damage reefs and an increase in dead corals in Al-Wajh. In contrast, AChE activity measured in mantle tissues is not inhibited proving the absence of neurotoxic substances in this region. This survey is the first study, which provides us a global idea about levels of pollution in some sites of the Red Sea coasts in the Kingdom of Saudi Arabia, which seem to vary qualitatively and quantitatively from one site to another due to the difference of humans' activities and therefore difference in pollutants. This survey must be followed by extensive studies in which bivalves can be used as a model in periodic biomonitoring of aquatic pollution in Saudi Arabia coasts and where such a multi-biomarkers approach can be adopted.
Our results showed that two sites (Al-Khuraybah) and (Thuwal) show a low rate of pollution regarding most of biomarkers used in this study compared to the other three sites. This was expected since these two sites have the least amount of urbanization and industrial activities among all studied sites. In fact, GST activity and the MDA level in digestive glands and gills from sites K and T seem to be in the same range with those found in the digestive glands in T. maxima from the bay of Cook located along the north coast of Moorea (Métais et al., 2012) and those found in the gills in Mytilus galloprovincialis of Ría de Vigo located in an unpolluted site (Vidal-Liñán et al., 2010). CAT activity in gills from sites (K) and (T) also seems to be in the same range with those obtained in other bivalves Donaxtrunculus from Sidi Jehmi in the Gulf of Tunis, which is considered as a reference site (Tlili et al., 2010). In accordance with previous results, the lowest MN frequencies in the gills of T. maxima were recorded in the two sites (K) and (T) compared to the other sites. These frequencies are similar to those reported in gills in Sacca di Goro lagoon (Sacchi et al., 2013), in Gijon (Spain) using Mytilus edulis (Izquierdo et al., 2003) and in the Gulf of Oristano (Sardinia, Italy) using Mytilus galloprovincialis (Magni et al., 2006) which are considered as non-polluted sites. Therefore, the average of 2 ± 2 MN seems to be the background of the induced MN in absence of any pollution. Contrarily, we observed an inhibition in AChE activity especially in site (K) (p < 0.05) compared to site (A). This may be due to the presence of neurotoxic substances in this site. Based on the lack of agricultural and industrial activities in site (K), abiotic parameters such as high temperature and/or presence of unknown substances can be the only explanations of this inhibition (Roméo et al., 2003; Dailianis et al., 2003; Serafim et al., 2011; Joyce and Vogeler, 2018). According to our results, especially on genotoxic and neurotoxic biomarkers, Yanbu and Rabigh are considered to be exposed to relatively high levels of pollution. This was expected since Yanbu and Rabigh are considered the most important industrial cities on the Red Sea coast of Saudi Arabia, which are characterized by its abundant industrial activities, oil refineries and marine navigation, particularly the presence of the largest industrial port in Yanbu city (Hashem, 1998; Al-Ghamdi, 2014). These results were not very relevant for oxidative stress biomarkers which almost all showed average levels both for enzymatic (CAT and GST) and non-enzymatic (MDA and GSH) oxidative stress biomarkers. Conversely, these sites present a relatively high count of MN compared to the sites in this study considered non-polluted (T and K). those values were comparable to the rate of MN in polluted sites in previous studies in the gills of Mytilus spp. from the Gulf of Gdansk in the Baltic Sea - which is supposed to be contaminated with Polychlorinated biphenyls (PCBs) and polynuclear aromatic hydrocarbons (PAHs) (Barsiene et al., 2006) - and in the gills of Mytilus galloprovincialis from the Gulf of Oristano near the S'Ena Arrubia (Magni et al., 2006) which has industrial and agriculture activities. In fact, previous studies mentioned the presence of damaged reefs and an increase in dead corals especially in Yanbu (Hariri, 2012) because of the presence of industrial activities. Sewage discharge from oil refineries and industrial facilities present in (R) (Al-Sofyani et al., 2014) certainly have detrimental effects on T.maxima in (R) as evidenced by the increased count of MN cells. Our results pertaining to AChE activities recorded in two sites (Y) and (R) were dissimilar. Whereas a drastic inhibition of AChE activity was found in site (R), site (Y) showed a comparable activity to sites (A) and (T). In fact, AChE activities in bivalves can be affected by urban and industrial pollutants as demonstrated by previous surveys (Tsangaris et al., 2010). Particularly, a decrease in AChE activity may be an indication of metal pollution. In Rabigh for example, and according to Bouhallaoui et al. (2017), many industrial activities and oil refineries exist along its coast and thus present a metal contamination (Al-Sofyani et al., 2014). Although Yanbu is an important industrial city, we noted that genotoxic and neurotoxic parameters are attenuated in this site compared to Rabigh; this may be explained by the presence of «The Royal
Author contribution statement Norah Salem Al-Howiti Investigation, Writing- Original draft preparation, Visualization. Zouhour Ouanes Ben Othmen Conceptualization, Methodology, Writing- Reviewing and Editing. Abdelwaheb Ben Othmane Software, Validation. 5
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Amel Hamza Chaffai Supervision.
reader and for the analysis of brain cell cultures. Journal of Neurology Methods 67, 53–56. Dailianis, S., 2011. Environmental impact of anthropogenic activities: the use of mussels as a reliable tool for monitoring marine pollution mussels: anatomy habitat and environmental impact. Nova Science Publishers Inc. New York pp. 43–61. Dailianis, S., Domouhtsidou, G.P., Raftopoulou, E., Kaloyianni, M., Dimitriadis, V.K., 2003. Evaluation of neutral red retention assay micronucleus test acetylcholinesterase activity and a signal transduction molecule (cAMP) in tissues of Mytilus galloprovincialis (L) in pollution monitoring. Mar. Environ. Res. 56 (4), 443–470. Damiens, G., Gnassia-Barelli, M., Loqués, F., Roméo, M., Salbert, V., 2007. Integrated biomarker response index as a useful tool for environmental assessment evaluated using transplanted mussels. Chemosphere 66, 574–583. De Luca-Abbott, S.B., Richardson, B.J., McClellan, K.E., Zheng, G.J., Martin, M., Lam, P.K.S., 2005. Field validation of antioxidant enzyme biomarkers in mussels (Pernaviridis) and clams (Ruditapesphili: inarum) transplanted in Hong Kong coastal waters. Mar Pollut Bull. 51, 694–707. DeVantier, L., Turak, E., Al-Shaikh, K., De'ath, G., 2000. Coral communities of the centralnorthern Saudi Arabian Red Sea. Fauna of Arabia 18, 23–66. Ellman, G.L., Courtney, K.O., Anders, V., Featherstone, R.M., 1961. A new and rapid colorimetric determination of acetylcholinesterase activity. Biochem. Pharmacol. 7, 88–95. Gagné, F., Auclair, J., Turcotte, P., Fournier, M., Gagnon, C., Sauve, S., et al., 2008. Ecotoxicity of Cd, Te quantum dots to freshwater mussels: impacts on immune system oxidative stress and genotoxicity. Aquat. Toxicol. 86 (3), 333–340. Galgani, F., Bocquene, G., 1991. Semi-automated colorimetric and enzymatic assays for aquatic organisms using plate readers. Water Res. 25, 147–150. Gorman, D., Turra, A., Connolly, R.M., Olds, A.D., Schlacher, T.A., 2017. Monitoring nitrogen pollution in seasonally-pulsed coastal waters requires judicious choice of indicator species. Mar. Pollut. Bull. 122 (1–2), 149–155. Hamza-Chaffai, A., 2014. Usefulness of bioindicators and biomarkers in pollution biomonitoring. Int J Biotechnol Wellness Ind 3, 19–26. Hariri, M.S.B., 2012. The present status of the red sea coral reefs between Haql and Yanbu Saudi Arabia. Life Science Journal 9 (4). Hashem, A.R., 1998. Metal pollution of sewage sludge from the Industrial City Yanbu Saudi Arabia. Journal of King Saud University 1 (10), 1–6. Hayashi, M., van der Kamp, G., Rudolph, D.L., 1998. Water and solute transfer between a prairie wetland and adjacent uplands 2 Chloride cycle. J Hydrol. 207 (l–2), 56–67. Höpner, T., Lattemann, S., 2003. Chemical impacts from seawater desalination plants—a case study of the northern Red Sea. Desalination 152 (1), 133–140. Hose, J.E., 1994. Large scale genotoxicity assessment in the marine environment. Environ. Health Perspect. 102, 29–32. Hughes, J.B., Hebert, A.T., 1991. Erythrocyte micronuclei in winter flounder (Pseudopleuronectes americanus): results of fields’ surveys during 1980–1988 from Virginia to Nova Scotia and in long Island sound Arch. Environ Contam Toxicol 20, 474–479. Izquierdo, J.I., Machado, G., Ayllon, F., d’Amico, V.L., Bala, L.O., Vallarino, E., et al., 2003. Assessing pollution in coastal ecosystems: a preliminary survey using the micronucleus test in the mussel Mytilus edulis. Ecotoxicol. Environ. Saf. 55, 24–29. Jones, D.S., Williams, D.F., Romanek, C.S., 1986. Life history of symbiont-bearing giant clams from stable isotope profiles. Science 231, 46–48. Joyce, A., Vogeler, S., 2018. Molluscan bivalve settlement and metamorphosis: neuroendocrine inducers and morphogenetic responses. Aquaculture 487, 64–82. Kim, Y.D., Kim, W.J., Shin, Y.K., Lee, D.H., Kim, Y.J., Kim, J.K., Rhee, J.S., 2017. Microcystin-LR bioconcentration induces antioxidant responses in the digestive gland of two marine bivalves Crassostreagigas and Mytilus edulis. Aquat. Toxicol. 188, 119–129. Klumpp, D.W., Lucas, J.S., 1994. Nutritional ecology of the giant clams Tridacna tevoroa and T. derasa from Tonga: influence of light on filter-feeding and photosynthesis. Marine Ecology Progress Series 147–156. Lattemann, S., Höpner, T., 2008. Environmental impact and impact assessment of seawater desalination. Desalination 220 (1), 1–15. Lau, P.S., Wong, H.L., 2003. Effect of size tissue parts and location on six biochemical markers in the green-lined mussel Pernaviridis. Mar. Pollut. Bull. 46, 1563–1572. Livingstone, D.R., 1993. Biotechnology and pollution monitoring: use of molecular biomarkers in the aquatic environment. J. Chem. Technol. Biotechnol. 57, 195–211. Livingstone, D.R., 2001. Contaminant-stimulated reactive oxygen species production and oxidative damage in aquatic organisms. Mar. Pollut. Bull. 42, 656–666. Madkour, H.A., 2005. Distribution and relationships of heavy metals in the giant clam (Tridacna maxima) and associated sediments from different sites in the Egyptian Red Sea coast. Egypt. J. Aquat. Res. 31, 45–59. Magni, P., De Falco, G., Falugi, C., Franzoni, M., Monteverde, M., Perrone, E., et al., 2006. Genotoxicity biomarkers and acetylcholinesterase activity in natural populations of Mytilus galloprovincialis along a pollution gradient in the Gulf of Oristano (Sardinia, western Mediterranean). Environ. Pollut. 142 (1), 65–72. Mannervik, B., Guthenberg, C., 1981. Glutathione transferase (human placenta). Methods Enzymol. 77, 231–235. Martinez-Haro, M., Beiras, R., Bellas, J., et al., 2015. A review on the ecological quality status assessment in aquatic systems using community based indicators and ecotoxicological tools: what might be the added value of their combination? Ecol. Indic. 48, 8–16. Métais, I., Ekouma, E.M., Ngpan, R., Planes, S., Mouneyrac, C., 2012. Oxidative stress responses and biological indices in the giant clam Tridacna maxima and the reef fish Epine phelusmerra from the French Polynesian Moorea Island. Mar. Pollut. Bull. 64 (10), 2233–2237. Mezzelani, M., Gorbi, S., Fattorini, D., d’Errico, G., Consolandi, G., Milan, M., Regoli, F.,
Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgements The authors want to thank Taibah University, Kingdom of Saudi Arabia for its financial support. References Al-Ghamdi, A.H., 2014. Natural radioactivity measurements for assessment radiation hazards from surface soil of industrial Yanbu City, Saudi Arabia. Life Science Journal 11, 10. Almeida, E.A., Marques, S., Klitzke, C.F., Bainy, A.C.D., Medeiros, M.H.G., Di Mascio, P., et al., 2003. DNA damage in digestive gland and mantle tissue of the mussel Perna perna. Comp Biochem Physiol Part C 135, 295–303. Al-Mur, B.A., Quicksall, A.N., Al-Ansari, A.M.A., 2017. Spatial and temporal distribution of heavy metals in coastal core sediments from the Red Sea Saudi Arabia. Oceanologia 59, 262–270. Al-Mutaz, I.S., 1991. Environmental impact of seawater desalination plants. Environ. Monit. Assess. 16 (1), 75–84. Al-Sofyani, A.A., Marimuthu, N., Wilson, J.J., 2014. A rapid assessment of scleractinian and non-scleractinian coral growth forms along the Saudi Arabian coast Red Sea. J. Ocean Univ. China 13 (2), 243–248. Alzahrani, D.A., Selim, E.M.M., El-Sherbiny, M.M., 2018. Ecological assessment of heavy metals in the grey mangrove (Avicennia marina) and associated sediments along the Red Sea coast of Saudi Arabia. Oceanologia 60 (4), 513–526. Andrew, W., Lance, H., 1993. Nearshore Marine Resources of the South Pacific. (Suva Honiara IPS and FFA). Ayala, F.J., Hedgecock, D., Zumwalt, G.S., Valentine, J.W., 1973. Genetic variation in Tridacna maxima, an ecological analog of some unsuccessful evolutionary lineages. Evolution 27, 177–191. Baalkhuyur, F.M., Dohaish, E.J.A.B., Elhalwagy, M.E., Alikunhi, N.M., AlSuwailem, A.M., Røstad, A., Duarte, C.M., 2018. Microplastic in the gastrointestinal tract of fishes along the Saudi Arabian Red Sea coast. Mar. Pollut. Bull. 131, 407–415. Badr, N.B., El-Fiky, A.A., Mostafa, A.R., Al-Mur, B.A., 2009. Metal pollution records in core sediments of some Red Sea coastal areas Kingdom of Saudi Arabia. Environ. Monit. Assess. 155 (1–4), 509–526. Balbi, T., Fabbri, R., Montagna, M., Camisassi, G., Canesi, L., 2017. Seasonal variability of different biomarkers in mussels (Mytilusgalloprovincialis) farmed at different sites of the Gulf of La Spezia Liguriansea Italy. Mar. Pollut. Bull. 116 (1–2), 348–356. Banni, M., Sforzini, S., Arlt, V.M., Barranger, A., Dallas, L.J., Oliveri, C., Readman, J.W., 2017. Assessing the impact of benzo [a] pyrene on marine mussels: application of a novel targeted low-density microarray complementing classical biomarker responses. PLoS One 12 (6). Baršienė, J., Lazutka, J., Šyvokienė, J., Dedonytė, V., Rybakovas, A., Bagdonas, E., Andersen, O.K., 2004. Analysis of micronuclei in blue mussels and fish from the Baltic and North Seas. Environ. Toxicol. 19 (4), 365–371. Barsiene, J., Schiedek, D., Rybakovas, A., Syvokiene, J., Kopecka, J., Forlin, L., 2006. Cytogenetic and cytotoxic effects in gill cells of the blue mussel Mytilus spp from different zones of the Baltic Sea. Mar. Pollut. Bull. 53, 469–478. Bauchau, V., 2001. Developmental stability as the primary function of the pigmentation patterns in bivalve shells. Belg J Zool 131 (l 2), 23–28. Bikham, J.W., Sandhu, S., Hebert, P.D.N., Chikhi, L., Athwal, R., 2000. Effects of chemical contaminants on genetic diversity in natural populations: implications for biomonitoring and ecotoxicology. Mutat. Res. 463, 33–51. Bin Othman, A.S., Goh, G.H., Todd, P.A., 2010. The distribution and status of giant clams (family Tridacnidae)-a short review. Raffles Bull. Zool. 58, 103–111. Bolognesi, C., Cirillo, S., 2014. Genotoxicity biomarkers in aquatic bioindicators. Current Zoology 60 (2), 273–284. Bouhallaoui, M., Zbiry, M., Elkhiati, N., Talba, S., Sforzini, S., Viarengo, A., Benhra, A., 2017. Use of biomarkers to evaluate the effects of environmental stressors on Mytilus galloprovincialis sampled along the Moroccan coasts: integrating biological and chemical data. Mar. Environ. Res. 130, 60–68. Box, A., Sureda, A., Galgani, F., Pons, A., Deudero, S., 2007. Assessment of environmental pollution at Balearic Islands applying oxidative stress biomarkers in the mussel Mytilus galloprovincialis. Comparative Biochemistry and Physiology Part C: Toxicology & Pharmacology 146 (4), 531–539. Bradford, M.M., 1976. A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Anal. Biochem. 72 (1), 248–254. Burgeot, T., Akcha, F., Ménard, D., Robinson, C., Loizeau, V., Brach-Papa, C., Cachot, J., 2017. Integrated monitoring of chemicals and their effects on four sentinel species Limandalimanda Platichthysflesus Nucella lapillus and Mytilus sp in Seine Bay: a key step towards a:lying biological effects to monitoring. Mar. Environ. Res. 124, 92–105. Cohen, M.B., Mimi, K., Vivian, O., 1996. A modified catalase assay suitable for a plate
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responses of the Mediterranean mussel Mytilus galloprovincialis to environmental variability of dissolved oxygen. Comp Biochem Physiol Part C Toxicol Pharmacol 140, 321–329. Schiedek, D., Broeg, K., Barsiene, J., et al., 2006. Biomarker responses as indication of contaminant effects in blue mussel (Mytilus edulis) and female eelpout (Zoarces viviparus) from the southwestern Baltic Sea. Mar. Pollut. Bull. 53, 387–405. Serafim, A., Lopes, B., Company, R., Cravo, A., Gomes, T., Sousa, V., et al., 2011. A multibiomarker approach in cross-transplanted mussels Mytilus galloprovincialis. Ecotoxicology 20, 959–1974. Soldatov, A.A., Gostyukhina, O.L., Golovina, I.V., 2007. Antioxidant enzyme complex of tissues of the bivalve Mytilus galloprovincialis L an under normal and oxidative-stress conditions: a review. A: lied Biochemistry and Microbiology 43, 556–562. Sunderman, J.R., William, F., 1987. Biochemical indices of lipid peroxidation in occupational and environmental medicine. In: Foa, V., Emmett, E.A., Maroni, M., Colomi, A. (Eds.), Occupational and Environmental Chemical Hazards: Cellular and Biochemical Indices for Monitoring Toxicity. Wiley Interscience, New York, pp. 151–158. SWCC, 2015. Saline Water Conversion Corporation (SWCC). Available from. http:// www.swcc.gov.sa/. Tlili, S., Métais, I., Boussetta, H., Mouneyrac, C., 2010. Linking changes at subindividual and population levels in Donaxtrunculus: assessment of marine stress. Chemosphere 81, 692–700. Tortell, P., 2004. Thoughts on Integrated Coastal Zone Management (ICZM) in Saudi Arabia. The Regional Organization for the Conservation of the Environment of the Red Sea and Gulf of Aden-PERSGA, Wellington. Tsangaris, C., Kormas, K., Strogyloudi, E., et al., 2010. Multiple biomarkers of pollution effects in caged mussels on the Greek coastline. Comparative Biochemistry and Physiology C 3 (151), 369–378. Tuthill, A.H., 1987. Guidelines for the use of copper alloys in seawater. Material Performance 12–22. Van der Oost, R., Beyer, J., Vermeulen, N.P.E., 2003. Fish bioaccumulation and biomarkers in environmental risk assessment: a review. Environ Toxicol Pharm 13, 57–149. Van Veld, P.A., Sanders, B.Μ., Fowler, B.A., Lars, F., Di Giulio, R.T., Marius, B., Stegeman, J.J., 2018. Molecular responses to environmental contamination: enzyme and protein systems as indicators of chemical exposure and effect. In: Biomarkers. CRC Press, pp. 235–336. Vidal-Liñán, L., Bellas, J., Campillo, J.A., Beiras, R., 2010. Integrated use of antioxidant enzymes in mussels, Mytilus galloprovincialis, for monitoring pollution in highly productive coastal areas of Galicia (NW Spain). Chemosphere 78 (3), 265–272. Wahsha, M., Bini, C., Fontana, S., Wahsha, A., Zilioli, D., 2012. Toxicity assessment of contaminated soils from a mining area in Northeast Italy by using lipid peroxidation assay. J. Geochem. Explor. 113, 112–117.
2018. Long-term exposure of Mytilus galloprovincialis to diclofenac Ibuprofen and Ketoprofen: insights into bioavailability biomarkers and transcriptomic changes. Chemosphere 198, 238–248. Moron, M.A., Depierre, J.W., Mannervick, B., 1979. Levels of glutathione reductase and glutathione S-transferase activities in rat lung and liver. Biochem Biophys Acta 582, 67–78. Neo, M.L., Eckman, W., Vicentuan, K., Teo, S.L.M., Todd, P.A., 2015. The ecological significance of giant clams in coral reef ecosystems. Biol. Conserv. 181, 111–123. Neo, M.L., Wabnitz, C.C., Braley, R.D., Heslinga, G.A., Fauvelot, C., Van Wynsberge, S., Tan, A., 2017. Giant clams (Bivalvia: Cardiidae: Tridacninae): a comprehensive update of species and their distribution current threats and conservation status. Oceanogr. Mar. Biol. 55, 87–387. Nuryanto, A., Kochzius, M., 2009. Highly restricted gene flow and deep evolutionary lineages in the giant clam Tridacna maxima. Coral Reefs 28, 607–619. Ohkawa, H., Ohishi, N., Yagi, K., 1979. Assay for lipid peroxides in animal tissues by thiobarbituric acid reaction. Anal. Biochem. 95, 351–358. Oliveira, M.M., Silva-Filho, M.V., Cunha-Bastos, V.L., Fernandes, F.C., Cunha-Bastos, J., 2007. Brain acetylcholinesterase as a marine pesticide biomarker using Brazilian fishes. Mar. Environ. Res. 63, 303–312. PERSGA, 2006. State of the Marine Environment, Report for the Red Sea and Gulf of Aden. PERSGA, Jeddah. Power, A., Sheehan, D., 1996. Seasonal variation in the antioxidant defence systems of gill and digestive gland of the blue mussel Mytilus edulis. Comp. Biochem. Physiol. 114, 99–103. RCJY, 2015. Royal Commission for Jubail and Yanbu (RCJY). Available from. http:// www.rcjy.gov.sa/en-US/Pages/default.aspx. Richter, C., Roa-Quiaoit, H., Jantzen, C., Al-Zibdah, M., Kochzius, M., 2008. Collapse of a new living species of giant clam in the Red Sea. Curr. Biol. 18, 1349–1354. Röding, P.F., 1798. Museum Boltenianumsive Catalogus cimeliorum etribusregnis naturae quae olimcollegerat Joa Fried Bolten MD pd Pars secunda continens Conchyliasive Testaceaunivalvia bivalvia et multivalvia. Roméo, M., Hoarau, P., Garello, G., Gnassia-Barelli, M., Girard, J.P., 2003. Mussel transplantation and biomarkers as useful tools for assessing water quality in the NW Mediterranean. Environ. Pollut. 122, 369–378. Rowlands, G., Purkis, S., Bruckner, A., 2014. Diversity in the geomorphology of shallowwater carbonate depositional systems in the Saudi Arabian Red Sea. Geomorphology 222, 3–13. Sacchi, A., Mouneyrac, C., Bolognesi, C., Sciutto, A., Roggieri, P., Fusi, M., et al., 2013. Biomonitoring study of an estuarine coastal ecosystem the Sacca di Goro lagoon using Ruditapesphili: inarum (Mollusca: Bivalvia). Environ. Pollut. 177, 82–89. Saleuddin, A.S.M., 1979. Shell formation in molluscs with special reference to periostracum formation and shell regeneration in: S van der Spoel, AC Van Bruggen & J Lever (Eds.) Pathways in Malacology. Junk The Hague pp. 47-81. Santovito, G., Piccinni, E., Cassini, A., Irato, P., Albergoni, V., 2005. Antioxidant
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Use of Tridacna maxima, a bivalve in the biomonitoring of the Saudi Arabian Red Sea coast
T
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Norah Salem Al-Howitia,1, Zouhour Ouanes Ben Othmena,b,1, , Abdelwaheb Ben Othmanea, Amel Hamza Chaffaib a b
Department of Biology, College of Sciences, Taibah University, Al Madinah Al Munawarah, Saudi Arabia Environmental and Marine Unit Research, UR 09-03, IPEIS Sfax University, Tunisia
A R T I C LE I N FO
A B S T R A C T
Keywords: Tridacna maxima Biomonitoring Red Sea coasts Oxidative stress Genotoxicity Neurotoxicity
The present study is an attempt to assess the effects of contamination of several sites in the Red Sea coasts of Saudi Arabia using bivalves as a biomonitoring tool. Oxidative stress biomarkers (including reduced glutathione level (GSH), glutathione-S-transferase activity (GST), Malondialdehyde level (MDA) and Catalase activity (CAT)), neurotoxicity acetylcholinesterase activity (ACHE), and genotoxicity micronucleus rate (MN) were measured in three distinct tissues - digestive glands, gills and mantle - of specimens of the giant clam Tridacna maxima, collected from five sites in Saudi Arabian Red Sea coast (Al-Khuraybah, Al-Wajh, Yanbu, Rabigh and Thuwal). Our results demonstrated that T. maxima showed differential biomarker responses according to the nature of pollutants and human activity that affect the coast. This study can be considered as the first one using biomarkers to assess the state of the Red Sea coast in Saudi Arabia which must be followed by periodic studies for surveillance of aquatic pollution.
1. Introduction For the last 30 years, human activities on the coastal space of the Kingdom of Saudi Arabia (KSA) have increased in a significant manner and resulted in the continuous invasion of various kinds of pollutants such as significant amounts of heavy metals and chemicals from oil refineries that are located along the Red Sea coasts. Whereas treatment units of all refineries in KSA are equipped with wastewater treatment units, their effluents are considered pollutants to the marine environment (Tortell, 2004; Badr et al., 2009; Al-Sofyani et al., 2014; Alzahrani et al., 2018; Baalkhuyur et al., 2018). The marine environment can be contaminated by many types of pollutants that can be either mineral or organic. Although chemicals can be analysed qualitatively and quantitatively by chemical procedures, adverse effects of the complex mixtures of those pollutants cannot be assessed (Hamza-Chaffai, 2014). In fact, the impact of those chemicals on the aquatic organisms cannot be revealed due to their potential synergistic/antagonistic effects. This is the reason why investigations of appropriate biomarkers of toxicity in living organisms are considered an alternative assessment technique of pollutant impact (Martinez-Haro et al., 2015). These parameters are investigated to
assess the adverse effect on physiological functions in the studied organisms and therefore the impact of environmental changes on population and community can be explained or expected (Hamza-Chaffai, 2014; Van der Oost et al., 2003). Among those, Antioxidant parameters like catalase (CAT), reduced Glutathione (GSH) and Glutathione-Stransferase (GST) are considered as helpful biomarkers which reflect the impact of some pollutants that exhibit their toxicities by generating oxidative stress (Livingstone, 2001). Moreover, high concentrations of malondialdehyde (MDA), an ultimate product of membrane lipid peroxidation, is related to the presence of oxidative pollutants in the environment or from free radicals generated by their metabolism (Sunderman and William, 1987; Wahsha et al., 2012). Otherwise, neurotoxic biomarkers such as acetylcholinesterase activity (AChE) have been used as biomarkers of exposure to many toxin chemicals, especially pesticides in aquatic environments (Oliveira et al., 2007). Because large scale biomonitoring programs have shown the association between genotoxicity and chronic health effects at the population level (Bolognesi and Cirillo, 2014), a high number of genotoxicity assays have been used to assess the genotoxic potential of polluted areas. The micronucleus (MN) assay is considered as one the most important techniques used for this purpose due to its reliability, simplicity and its
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Corresponding author at: Department of Biology, College of Sciences, Taibah University, Al Madinah Al Munawarah, Saudi Arabia. E-mail address: [email protected] (Z. Ouanes Ben Othmen). 1 Both authors contribute equally. https://doi.org/10.1016/j.marpolbul.2019.110766 Received 13 May 2019; Received in revised form 18 November 2019; Accepted 20 November 2019 Available online 06 December 2019 0025-326X/ © 2019 Elsevier Ltd. All rights reserved.
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applicability to many types of cells (Hose, 1994; Hughes and Hebert, 1991). Otherwise, contamination of aquatic organisms such as bivalves with different contaminants has been proven to be a risk to human health through their incorporation in the food chain (Bikham et al., 2000). In this survey, we chose to use the giant clam Tridacna maxima (Röding, 1798), an ecologically and economically important species of the Red Sea. It is the most widely distributed and an important species of giant clam. It has a large geographic distribution from the Red Sea and Western Indian Ocean across the Indo-Malay Archipelago to the Tuamotu Archipelago in the central Pacific and lives in coastal reef areas, attached to its substrate with a byssus (Bin Othman et al., 2010; Ayala et al., 1973). Like most bivalve mollusks, it belonged to filter feeder organisms (Klumpp and Lucas, 1994) and therefore it is a pollutant-accumulator such as described by Madkour (2005) for heavy metals in different sites in the Egyptian Red Sea coast (Madkour, 2005). In the present study, we used three different tissues: digestive glands (GSH, GST, and MDA), mantle (AChE) and gills (GSH, GST, MDA, CAT, and MN). Gills, by their main function of respiration, are considered as the first organs to be exposed to pollutants and constitute the major absorption site for dissolved pollutants (Banni et al., 2017) and have been shown to be very sensitive to a wide range of toxicants in several types of aquatic animals such as fish species (Hayashi et al., 1998). Digestive glands are the organs where all xenobiotics must pass to be metabolized in order to be excreted and consequently they become more reactive and they may accumulate there (Almeida et al., 2003; Kim et al., 2017). For these reasons, digestive glands were shown to exhibit high levels of oxidative stress (Lau and Wong, 2003; Power and Sheehan, 1996; Soldatov et al., 2007). The Mantle is chosen for neurotoxic activity because it is considered as the most innervated organ; in fact, the mantle is the organ responsible for sensory and regulation functions (Saleuddin, 1979) and is considered as the main neural and sensory network (Bauchau, 2001). This survey can be considered as an attempt to assess the contamination in marine environment of several sites along the Red Sea coasts of Saudi Arabia using T. maxima as a biomonitoring species and oxidative stress, neurotoxic and genotoxic parameters as a multi-biomarkers approach.
Fig. 1. Map of the Red Sea coast of Saudi Arabia, showing the location of the five sampling sites: T (Thuwal), R (Rabigh), Y (Yanbu), A (Al-Wajh) and K (Alkhuraybah).
−80 °C until biochemical analysis. All techniques were adapted to micro-titration; so the variation in absorbance was quantified using a micro-plate reader. Total proteins were determined according to Bradford (1976); bovine serum albumin was used as the standard.
2. Material and methods 2.1. Study area Five sampling stations were chosen (Fig. 1) on the eastern coasts of the Red Sea in Saudi Arabia. These Five sampling sites are: Thuwal (N22°17.445′ E38°58.018′) (T), Rabigh (N22°50′05.92 E38°44′29.98) (R), Yanbu (N24°8.84076′ E37°56.07444′) (Y), Al-Wajh (N25°58.126′ E36°38.598′) (A) and Al-Khuraybah (N28°2′18.7692E35°4′38.6976) (K).
2.3.1. Oxidative stress biomarkers Some relevant oxidative stress parameters were performed in this study such as Reduced glutathione (GSH) rate, which was assessed using the method described by Moron et al. (1979) with adjustment of volumes to be adapted to microtitration. In fact, supernatants were precipitated with TCA 5% (trichloroacetic acid) and the precipitate was removed after centrifugation (5000g for 10 min, at 4 °C). The absorbance of the substance formed when 5,5′-dithio-2-nitrobenzoic acid (DTNB) is reduced by glutathione was read at 405 nm. Pure reduced Glutathione was the standard to assess the rate of GSH in tissues expressed as nmoles GSH/mg of proteins. The Glutathione S-Transferase (GST) activity assay was also performed. This assay is based on the utilization of 1-chloro-2, 4-dinitrobenzene (CDNB), which was the substrate for GST. Conjugation of CDNB with GSH (by chloro-substitution) results in a change in absorbance of the compound at 340 nm; in our case we adapted the test to micro-titration according to Mannervik and Guthenberg (1981) by adding in each well 10 μl of the supernatant, 20 μl of the substrate (GSH), 20 μl of CDNB and 200 μl of the phosphate buffer. GST activity was expressed as μmol/min/mg of proteins. Malondialdehyde (MDA) assay is based on the reaction between a Chromogenic reagent, 2-Thiobarbituric Acid (TBA), and MDA at 25 °C. The Chromophore (pink colour) complex can absorb light at 492 nm. MDA levels were determined according to the method of
2.2. Sample collection For each station, 10 specimens of Tridacna maxima (Röding, 1798) at the same gonad development stage with shell length 12 ± 3 cm were sampled in February and March 2014. Once in the laboratory, the collected specimens of T. maxima were immediately dissected. Digestive glands, gills and mantle were removed, then weighed and stored at −80 °C until analyses. 2.3. Biomarker analysis Digestive glands, gills and mantle were homogenized with an ULTRA TURRAX (IKA© T18 basic & TISSUE – REAROR Model 985370 – BioSpecProducts, Inc) in a Phosphate Buffer (pH 7.6) (4 ml for 1 g of tissue). The homogenates were then centrifuged at 5000g for 30 min. All procedures were carried out at 4 °C. The supernatant was frozen at 2
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Ohkawa et al. (1979). MDA was used as the standard and expressed as mmol/mg of protein. For catalase activity assay, the Cohen et al. (1996) method was used to evaluate Catalase activity (CAT) and adapted for microtitration by reducing all reaction volumes to 1/5. Absorbance was read on 492 nm, after every 30 s 10 times. The CAT activity was expressed as μmol/mg of protein/min. 2.3.2. Neurotoxicity biomarker: acetylcholinesterase (AChE) activity assay Acetylcholinesterase activity (AChE) was estimated, as described by Ellman et al. (1961) and adapted to microtitration by Galgani and Bocquene (1991) by a colorimetric method. The absorption was measured at 450 nm. AChE is expressed as nmol/min/mg of protein.
Fig. 3. Glutathione s-transferase (GST) activity, expressed as (μmol/min/mg of protein), in digestive gland and gill of T. maxima collected from various sites of Saudi Arabia coasts: (K (Al-Khuraybah), A (Al-Wajh), Y (Yanbu), R (Rabigh), and T (Thuwal)). Values: mean ± standard deviation. Differences between sites attributed with small letters were a: statistically different from all other sites based on digestive glands results; b: non-statistically different sites based on gills results (p < 0.05).
2.3.3. Genotoxicity biomarker: micronucleus assay (MN) The micronuclei assay was done according to Baršienė et al. (2004). Briefly, gills tissue was spread on a slide and dried in the open air. Slides were then fixed in methanol/actique acid (3/1) for 2 min then stained in Giemsa 4% for 15 min. The slides were analysed under a light microscope at a final magnification of 1000× with a drop of oil immersion. Scoring involved 2000 of gill cells of five specimen for each slide.
(185.26 ± 56.10 nmol/mg of protein) is the highest in comparison to sites (A) (49.21 ± 13.12 nmol/mg of protein) (p < 0.05) and (R) (68.83 ± 27.13 nmol/mg of protein) (p < 0.05) (Fig. 2).
2.4. Statistical analysis
3.1.2. Glutathione-S-transferase (GST) There was a significant difference in GST activity values found in digestive glands collected from Al-Wajh(A) site (1.61 ± 0.49 μmol/ min/mg of protein) compared to all other sites (p < 0.05). Whereas, there were no significant differences found among the remaining sites (p < 0.05). As well as in gills, where no significant differences registered in GST activity among sampling sites (Fig. 3) was registered (p < 0.05).
Results of biochemical and genotoxic biomarkers are presented as means ± standard deviation (SD). Comparison of these parameters between the different studied sites was performed by Tukey honest significant difference assay after an ANOVA test was performed and showed significant F values. Differences were significant when p < 0.05. The software Statistica 10.0 (Stat- Soft, Tulsa, USA) was used. 3. Results
3.1.3. Malonedialdehyde (MDA) Our results showed that the level of MDA was highest in the digestive glands compared to the gills of T. maxima collected for all sites (Fig. 4). Significantly high MDA levels were noted in the digestive glands of T. maxima collected from site (A) (138.48 ± 16.98 nmol MDA/mg of protein) (p < 0.05) compared other sites, while a significant decrease in MDA level was registered in the digestive glands from site (T) (37.51 ± 5.36 nmol/mg of protein) (p < 0.05) compared to both sites (A) (138.48 ± 16.98 nmol MDA/mg of protein) and (K) (61.36 ± 5.30 nmol MDA/mg of protein). In the gills, significantly high MDA levels were recorded in both sites (K) and (T) with respective values of 22.99 ± 3.86 nmol MDA/mg of protein and 20.68 ± 5.58 nmol MDA/mg of protein compared to the remaining
3.1. Oxidative stress biomarkers results 3.1.1. Reduced glutathione (GSH) GSH variation in gills and digestive glands show a variation among the different study sites. In fact, the level of GSH registered from site (A) showed a significant increase (648.20 ± 196.89 nmol/mg of protein) in digestive glands compared to site (Y) (404.17 ± 135.94 nmol/mg of protein) (p < 0.05) and a non-significative increase compared to all other sites, whereas in gills, the level decreased significantly (p < 0.05) in site (A) (49.21 ± 13.12 nmol/mg of protein) and site (R) (68.83 ± 27.13 nmol/mg of protein) compared to the other sites (Fig. 2). Likewise, the level of GSH registered in gills from site (K)
Fig. 4. Malonedialdehyde (MDA), expressed as (nmol/mg of protein) in digestive gland and gills of T. maxima collected from various sites of Saudi Arabia coasts: (K (Al-Khuraybah), A (Al-Wajh), Y (Yanbu), R (Rabigh), and T (Thuwal)). Values: mean ± standard deviation. Differences between sites attributed with small letters were a: statistically different from (A) based on digestive glands. b: statistically different from (T) based on digestive glands results; c: statistically different from (K) based on gills results; d: statistically different from (T) based on gills results (p < 0.05).
Fig. 2. Reduced Glutathione (GSH), expressed as (nmol/mg of protein), indigestive glands and gills of T. maxima collected from various sites of Saudi Arabia coasts: (K (Al-Khuraybah), A (Al-Wajh), Y (Yanbu), R (Rabigh), and T (Thuwal)). Values: mean ± standard deviation. Differences between sites attributed with small letters were a: statistically different from (A) based on digestive glands results; b: statistically different from (A) based on gills results; c: statistically different from (R) based on gills results (p < 0.05). 3
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Fig. 5. Catalase activity, expressed as (μmol/min/mg of protein) in gill of T. maxima collected from various sites of Saudi Arabia coasts: (K (Al-Khuraybah), A (Al-Wajh), Y (Yanbu), R (Rabigh), and T (Thuwal)). Values: mean ± standard deviation. Differences between sites attributed with different letters were a: statistically different from (R) based on gills results; b: statistically different from (A) based on gills results (p < 0.05).
Fig. 7. Micronucleus rate (MN) expressed as (MN/1000 cells) in gills of T. maxima collected from various sites of Saudi Arabia coasts (K (Al-Khuraybah), A (Al-Wajh), Y (Yanbu), R (Rabigh), T (Thuwal)) Values mean ± standard deviation. Differences between sites attributed with small letters were a: statistically different from (K); b: statistically different from (R) based on gills results (p < 0.05).
sampling sites which have values of 7.27 ± 1.16 nmol MDA/mg of protein, 5.20 ± 1.59 nmol MDA/mg of protein and 4.64 ± 1.59 nmol/mg of protein for the sites (A), (Y) and (R) respectively at p < 0.05 (Fig. 4).
3.3. Genotoxicity biomarker results: micronucleus test MN frequency test performed in gills tissues found high counts of micronucleated cells in samples from sites (R) (6.34 ± 0.63 MN cells/ 1000 cells) (p < 0.05), (A) (5.46 ± 1.27 MN cells/1000 cells) and (Y) (3.60 ± 1.43 MN cells/1000 cells) (p < 0.005) compared to site (K) which represented the lowest count of (MN) (1.59 ± 1.08 MN cells/ 1000 cells). However, low counts of MN frequency were recorded in site (T) (3.60 ± 1.43 MN cells/1000 cells) compared to counts of MN cells registered in site (R) (6.34 ± 0.63 MN cells/1000 cells) (p < 0.05) (Fig. 7).
3.1.4. Catalase activity (CAT) Catalase activity was significantly higher in the gills from site (T) (294.41 ± 47.35 μmol/min/mg of protein) (p < 0.05) compared to sites (K) (228.43 ± 77.60 μmol/min/mg of protein), (Y) (214.58 ± 77.32 μmol/min/mg of protein) and (A) (138.05 ± 20.13 μmol/min/mg of protein) (Fig. 5). The lowest of this enzymatic activity was significantly observed in the measured results from site (R) (110.55 ± 21.92 μmol/min/mg of protein) (p < 0.05) (Fig. 5).
4. Discussion The Red Sea is considered one of the most important repositories of marine biodiversity in the world (PERSGA, 2006). Human activities in the coastal area of Saudi Arabia have increased in a significant manner with an increasing introduction of different of pollutants such as heavy metals and industrial sewage (Badr et al., 2009; Al-Mur et al., 2017; AlSofyani et al., 2014; Alzahrani et al., 2018). Biomarkers are considered as valuable tools for marine pollution monitoring and have been largely used to assess the coastal environment quality during recent years (Hamza-Chaffai, 2014; Damiens et al., 2007). In fact, many studies have demonstrated that there is an important and significant variation of antioxidant parameters in aquatic organisms coming from polluted and unpolluted sites (Livingstone, 2001; Balbi et al., 2017; Van Veld et al., 2018). Thus, the presence of chemical contaminants induces variations in antioxidant parameters, which can be used as biomarkers because they are able to differentiate between polluted areas and areas with lower human impact (Santovito et al., 2005; Box et al., 2007). In this study, a multi-biomarker approach was used to assess the level of pollution of different areas: CAT, GSH, GST, MDA, AChE and MN. These biomarkers were largely used and chosen because they have been proven suitable for monitoring the effects of pollutants on sentinel organisms (Dailianis, 2011). Benthic organisms are usually used as sentinel species for biomonitoring of coastal environments, and specially bivalves (De LucaAbbott et al., 2005; Gorman et al., 2017; Burgeot et al., 2017). We have chosen as a study species the giant clam Tridacna maxima for several reasons: it is abundant in the Red Sea (Andrew and Lance, 1993; Richter et al., 2008; Nuryanto and Kochzius, 2009; Neo et al., 2017), it can accumulate high levels of pollutants without dying, it occupies an important position in the food cycle and it is considered as a secondary consumer (Jones et al., 1986; Neo et al., 2015). Moreover, it serves as a filter-feeding organism and can absorb even the smallest particles like all bivalves (Livingstone, 1993). For these reasons, we chose to use T. maxima as a model organism for monitoring several sites along Red Sea coast in Saudi Arabia.
3.2. Neurotoxicity biomarker results: acetylcholinesterase activity (AChE) Samples from sites (R) and (K) exhibited lower AChE activity in the mantle (p < 0.05) with minimum values (5.69 ± 2.16 nmol/min/mg of protein), (9.17 ± 3.90 nmol/min/mg of protein) respectively. Whereas, in samples from site (A), a significantly higher AChE activity value was found in the mantle (37.29 ± 11.87 nmol/min/mg of protein) (p < 0.05) compared to the remaining sampling sites (Fig. 6). Sites (A) (37.29 ± 11.87 nmol/min/mg of protein), (Y) (28.19 ± 8.12 nmol/min/mg of protein) and (T) (24.06 ± 9.01 nmol/min/mg of protein) denote higher AChE activity in the mantle in comparison with sites (K) and (R).
Fig. 6. AChE activity, expressed as (nmol/min/mg of protein) in mantle of T. maxima collected from various sites of Saudi Arabia coasts: (K (Al-Khuraybah), A (AlWajh), Y (Yanbu), R (Rabigh), and T (Thuwal)). Values mean ± standard deviation. Differences between sites attributed with small letters were a: statistically different from (K); b: statistically different from (A); c: statistically different from (T) (p < 0.05). 4
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Commission for Jubail and Yanbu» that implement many environmental protection procedures and evaluate the impact of industrial activities on the air, water, soil and the health of humans (RCJY, 2015). Our results are in accordance with the survey conducted by Badr et al. (2009) where Rabigh is found to be more polluted than Yanbu based on the Pollution Load Index for metal pollution recorded in core sediments where Yanbu is found to be the least contaminated area compared to Rabigh and Jeddah except for Nickel (Ni). Concerning the Al-Wajh site, we observed a significant increase of all oxidative stress biomarkers (GSH, GST, MDA) in digestive glands compared to all other studied sites. Contrarily, in the gills, normal values were recorded for all oxidative stress parameters. This can be an indication of long-term exposure and/or a relatively acute old contamination (Almeida et al., 2003; Mezzelani et al., 2018). Likewise, MN frequency recorded in samples from site Al-Wajh was the most significant compared to all other sites. The same result was reported in gills in previous studies from sites polluted with urban wastes (Izquierdo et al., 2003) and from polluted sites with PCBs and DDTs (Schiedek et al., 2006) using Mytilus edulis in both studies. This result was expected as oxidative stress biomarkers are elevated in this site and the majority of substances which induce oxidative stress were found to be genotoxic too (Gagné et al., 2008). Generally, Al-Wajh is considered on the lowest level of direct threat from human impacts due to the absence of industrial and agricultural activities, except for water desalination plant activity (SWCC, 2015; Tuthill, 1987). Desalting processes are normally associated with the rejection of high concentrations of chemicals on open sea waste from the plant itself or from the pre-treatment units as well as during the cleaning period to improve plant performances. Moreover, heavy metals coming from corrosion and chemical from brines were also discharged to the sea (Al-Mutaz, 1991; Höpner and Lattemann, 2003). Adding to this, constant discharges of high salinity and high temperature streams were noted by these plants and was found to be fatal for marine life, and cause many changes in the entire population at the discharge site. In addition, benthic communities, such as bivalves, may thus be affected as a consequence of high salinity and chemical residuum (Lattemann and Höpner, 2008). Those factors may be able to explain the obtained results in this survey. Moreover, the large drainage basin, which has an area of 104,977 km2 and feeds the Saudi Arabian Red Sea at Al-Wajh, may be loaded with waste matter from different parts of the surrounding areas (Rowlands et al., 2014) and seems to be the principle cause of increase of MN frequency and oxidative stress biomarkers in this site. Our results demonstrated the altered metabolic response of T. maxima, probably due to the presence of pollutants that can alter other living organisms and ecosystems such as described by DeVantier et al. (2000) and Hariri (2012) that mentioned the presence of heavily damage reefs and an increase in dead corals in Al-Wajh. In contrast, AChE activity measured in mantle tissues is not inhibited proving the absence of neurotoxic substances in this region. This survey is the first study, which provides us a global idea about levels of pollution in some sites of the Red Sea coasts in the Kingdom of Saudi Arabia, which seem to vary qualitatively and quantitatively from one site to another due to the difference of humans' activities and therefore difference in pollutants. This survey must be followed by extensive studies in which bivalves can be used as a model in periodic biomonitoring of aquatic pollution in Saudi Arabia coasts and where such a multi-biomarkers approach can be adopted.
Our results showed that two sites (Al-Khuraybah) and (Thuwal) show a low rate of pollution regarding most of biomarkers used in this study compared to the other three sites. This was expected since these two sites have the least amount of urbanization and industrial activities among all studied sites. In fact, GST activity and the MDA level in digestive glands and gills from sites K and T seem to be in the same range with those found in the digestive glands in T. maxima from the bay of Cook located along the north coast of Moorea (Métais et al., 2012) and those found in the gills in Mytilus galloprovincialis of Ría de Vigo located in an unpolluted site (Vidal-Liñán et al., 2010). CAT activity in gills from sites (K) and (T) also seems to be in the same range with those obtained in other bivalves Donaxtrunculus from Sidi Jehmi in the Gulf of Tunis, which is considered as a reference site (Tlili et al., 2010). In accordance with previous results, the lowest MN frequencies in the gills of T. maxima were recorded in the two sites (K) and (T) compared to the other sites. These frequencies are similar to those reported in gills in Sacca di Goro lagoon (Sacchi et al., 2013), in Gijon (Spain) using Mytilus edulis (Izquierdo et al., 2003) and in the Gulf of Oristano (Sardinia, Italy) using Mytilus galloprovincialis (Magni et al., 2006) which are considered as non-polluted sites. Therefore, the average of 2 ± 2 MN seems to be the background of the induced MN in absence of any pollution. Contrarily, we observed an inhibition in AChE activity especially in site (K) (p < 0.05) compared to site (A). This may be due to the presence of neurotoxic substances in this site. Based on the lack of agricultural and industrial activities in site (K), abiotic parameters such as high temperature and/or presence of unknown substances can be the only explanations of this inhibition (Roméo et al., 2003; Dailianis et al., 2003; Serafim et al., 2011; Joyce and Vogeler, 2018). According to our results, especially on genotoxic and neurotoxic biomarkers, Yanbu and Rabigh are considered to be exposed to relatively high levels of pollution. This was expected since Yanbu and Rabigh are considered the most important industrial cities on the Red Sea coast of Saudi Arabia, which are characterized by its abundant industrial activities, oil refineries and marine navigation, particularly the presence of the largest industrial port in Yanbu city (Hashem, 1998; Al-Ghamdi, 2014). These results were not very relevant for oxidative stress biomarkers which almost all showed average levels both for enzymatic (CAT and GST) and non-enzymatic (MDA and GSH) oxidative stress biomarkers. Conversely, these sites present a relatively high count of MN compared to the sites in this study considered non-polluted (T and K). those values were comparable to the rate of MN in polluted sites in previous studies in the gills of Mytilus spp. from the Gulf of Gdansk in the Baltic Sea - which is supposed to be contaminated with Polychlorinated biphenyls (PCBs) and polynuclear aromatic hydrocarbons (PAHs) (Barsiene et al., 2006) - and in the gills of Mytilus galloprovincialis from the Gulf of Oristano near the S'Ena Arrubia (Magni et al., 2006) which has industrial and agriculture activities. In fact, previous studies mentioned the presence of damaged reefs and an increase in dead corals especially in Yanbu (Hariri, 2012) because of the presence of industrial activities. Sewage discharge from oil refineries and industrial facilities present in (R) (Al-Sofyani et al., 2014) certainly have detrimental effects on T.maxima in (R) as evidenced by the increased count of MN cells. Our results pertaining to AChE activities recorded in two sites (Y) and (R) were dissimilar. Whereas a drastic inhibition of AChE activity was found in site (R), site (Y) showed a comparable activity to sites (A) and (T). In fact, AChE activities in bivalves can be affected by urban and industrial pollutants as demonstrated by previous surveys (Tsangaris et al., 2010). Particularly, a decrease in AChE activity may be an indication of metal pollution. In Rabigh for example, and according to Bouhallaoui et al. (2017), many industrial activities and oil refineries exist along its coast and thus present a metal contamination (Al-Sofyani et al., 2014). Although Yanbu is an important industrial city, we noted that genotoxic and neurotoxic parameters are attenuated in this site compared to Rabigh; this may be explained by the presence of «The Royal
Author contribution statement Norah Salem Al-Howiti Investigation, Writing- Original draft preparation, Visualization. Zouhour Ouanes Ben Othmen Conceptualization, Methodology, Writing- Reviewing and Editing. Abdelwaheb Ben Othmane Software, Validation. 5
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Amel Hamza Chaffai Supervision.
reader and for the analysis of brain cell cultures. Journal of Neurology Methods 67, 53–56. Dailianis, S., 2011. Environmental impact of anthropogenic activities: the use of mussels as a reliable tool for monitoring marine pollution mussels: anatomy habitat and environmental impact. Nova Science Publishers Inc. New York pp. 43–61. Dailianis, S., Domouhtsidou, G.P., Raftopoulou, E., Kaloyianni, M., Dimitriadis, V.K., 2003. Evaluation of neutral red retention assay micronucleus test acetylcholinesterase activity and a signal transduction molecule (cAMP) in tissues of Mytilus galloprovincialis (L) in pollution monitoring. Mar. Environ. Res. 56 (4), 443–470. Damiens, G., Gnassia-Barelli, M., Loqués, F., Roméo, M., Salbert, V., 2007. Integrated biomarker response index as a useful tool for environmental assessment evaluated using transplanted mussels. Chemosphere 66, 574–583. De Luca-Abbott, S.B., Richardson, B.J., McClellan, K.E., Zheng, G.J., Martin, M., Lam, P.K.S., 2005. Field validation of antioxidant enzyme biomarkers in mussels (Pernaviridis) and clams (Ruditapesphili: inarum) transplanted in Hong Kong coastal waters. Mar Pollut Bull. 51, 694–707. DeVantier, L., Turak, E., Al-Shaikh, K., De'ath, G., 2000. Coral communities of the centralnorthern Saudi Arabian Red Sea. Fauna of Arabia 18, 23–66. Ellman, G.L., Courtney, K.O., Anders, V., Featherstone, R.M., 1961. A new and rapid colorimetric determination of acetylcholinesterase activity. Biochem. Pharmacol. 7, 88–95. Gagné, F., Auclair, J., Turcotte, P., Fournier, M., Gagnon, C., Sauve, S., et al., 2008. Ecotoxicity of Cd, Te quantum dots to freshwater mussels: impacts on immune system oxidative stress and genotoxicity. Aquat. Toxicol. 86 (3), 333–340. Galgani, F., Bocquene, G., 1991. Semi-automated colorimetric and enzymatic assays for aquatic organisms using plate readers. Water Res. 25, 147–150. Gorman, D., Turra, A., Connolly, R.M., Olds, A.D., Schlacher, T.A., 2017. Monitoring nitrogen pollution in seasonally-pulsed coastal waters requires judicious choice of indicator species. Mar. Pollut. Bull. 122 (1–2), 149–155. Hamza-Chaffai, A., 2014. Usefulness of bioindicators and biomarkers in pollution biomonitoring. Int J Biotechnol Wellness Ind 3, 19–26. Hariri, M.S.B., 2012. The present status of the red sea coral reefs between Haql and Yanbu Saudi Arabia. Life Science Journal 9 (4). Hashem, A.R., 1998. Metal pollution of sewage sludge from the Industrial City Yanbu Saudi Arabia. Journal of King Saud University 1 (10), 1–6. Hayashi, M., van der Kamp, G., Rudolph, D.L., 1998. Water and solute transfer between a prairie wetland and adjacent uplands 2 Chloride cycle. J Hydrol. 207 (l–2), 56–67. Höpner, T., Lattemann, S., 2003. Chemical impacts from seawater desalination plants—a case study of the northern Red Sea. Desalination 152 (1), 133–140. Hose, J.E., 1994. Large scale genotoxicity assessment in the marine environment. Environ. Health Perspect. 102, 29–32. Hughes, J.B., Hebert, A.T., 1991. Erythrocyte micronuclei in winter flounder (Pseudopleuronectes americanus): results of fields’ surveys during 1980–1988 from Virginia to Nova Scotia and in long Island sound Arch. Environ Contam Toxicol 20, 474–479. Izquierdo, J.I., Machado, G., Ayllon, F., d’Amico, V.L., Bala, L.O., Vallarino, E., et al., 2003. Assessing pollution in coastal ecosystems: a preliminary survey using the micronucleus test in the mussel Mytilus edulis. Ecotoxicol. Environ. Saf. 55, 24–29. Jones, D.S., Williams, D.F., Romanek, C.S., 1986. Life history of symbiont-bearing giant clams from stable isotope profiles. Science 231, 46–48. Joyce, A., Vogeler, S., 2018. Molluscan bivalve settlement and metamorphosis: neuroendocrine inducers and morphogenetic responses. Aquaculture 487, 64–82. Kim, Y.D., Kim, W.J., Shin, Y.K., Lee, D.H., Kim, Y.J., Kim, J.K., Rhee, J.S., 2017. Microcystin-LR bioconcentration induces antioxidant responses in the digestive gland of two marine bivalves Crassostreagigas and Mytilus edulis. Aquat. Toxicol. 188, 119–129. Klumpp, D.W., Lucas, J.S., 1994. Nutritional ecology of the giant clams Tridacna tevoroa and T. derasa from Tonga: influence of light on filter-feeding and photosynthesis. Marine Ecology Progress Series 147–156. Lattemann, S., Höpner, T., 2008. Environmental impact and impact assessment of seawater desalination. Desalination 220 (1), 1–15. Lau, P.S., Wong, H.L., 2003. Effect of size tissue parts and location on six biochemical markers in the green-lined mussel Pernaviridis. Mar. Pollut. Bull. 46, 1563–1572. Livingstone, D.R., 1993. Biotechnology and pollution monitoring: use of molecular biomarkers in the aquatic environment. J. Chem. Technol. Biotechnol. 57, 195–211. Livingstone, D.R., 2001. Contaminant-stimulated reactive oxygen species production and oxidative damage in aquatic organisms. Mar. Pollut. Bull. 42, 656–666. Madkour, H.A., 2005. Distribution and relationships of heavy metals in the giant clam (Tridacna maxima) and associated sediments from different sites in the Egyptian Red Sea coast. Egypt. J. Aquat. Res. 31, 45–59. Magni, P., De Falco, G., Falugi, C., Franzoni, M., Monteverde, M., Perrone, E., et al., 2006. Genotoxicity biomarkers and acetylcholinesterase activity in natural populations of Mytilus galloprovincialis along a pollution gradient in the Gulf of Oristano (Sardinia, western Mediterranean). Environ. Pollut. 142 (1), 65–72. Mannervik, B., Guthenberg, C., 1981. Glutathione transferase (human placenta). Methods Enzymol. 77, 231–235. Martinez-Haro, M., Beiras, R., Bellas, J., et al., 2015. A review on the ecological quality status assessment in aquatic systems using community based indicators and ecotoxicological tools: what might be the added value of their combination? Ecol. Indic. 48, 8–16. Métais, I., Ekouma, E.M., Ngpan, R., Planes, S., Mouneyrac, C., 2012. Oxidative stress responses and biological indices in the giant clam Tridacna maxima and the reef fish Epine phelusmerra from the French Polynesian Moorea Island. Mar. Pollut. Bull. 64 (10), 2233–2237. Mezzelani, M., Gorbi, S., Fattorini, D., d’Errico, G., Consolandi, G., Milan, M., Regoli, F.,
Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgements The authors want to thank Taibah University, Kingdom of Saudi Arabia for its financial support. References Al-Ghamdi, A.H., 2014. Natural radioactivity measurements for assessment radiation hazards from surface soil of industrial Yanbu City, Saudi Arabia. Life Science Journal 11, 10. Almeida, E.A., Marques, S., Klitzke, C.F., Bainy, A.C.D., Medeiros, M.H.G., Di Mascio, P., et al., 2003. DNA damage in digestive gland and mantle tissue of the mussel Perna perna. Comp Biochem Physiol Part C 135, 295–303. Al-Mur, B.A., Quicksall, A.N., Al-Ansari, A.M.A., 2017. Spatial and temporal distribution of heavy metals in coastal core sediments from the Red Sea Saudi Arabia. Oceanologia 59, 262–270. Al-Mutaz, I.S., 1991. Environmental impact of seawater desalination plants. Environ. Monit. Assess. 16 (1), 75–84. Al-Sofyani, A.A., Marimuthu, N., Wilson, J.J., 2014. A rapid assessment of scleractinian and non-scleractinian coral growth forms along the Saudi Arabian coast Red Sea. J. Ocean Univ. China 13 (2), 243–248. Alzahrani, D.A., Selim, E.M.M., El-Sherbiny, M.M., 2018. Ecological assessment of heavy metals in the grey mangrove (Avicennia marina) and associated sediments along the Red Sea coast of Saudi Arabia. Oceanologia 60 (4), 513–526. Andrew, W., Lance, H., 1993. Nearshore Marine Resources of the South Pacific. (Suva Honiara IPS and FFA). Ayala, F.J., Hedgecock, D., Zumwalt, G.S., Valentine, J.W., 1973. Genetic variation in Tridacna maxima, an ecological analog of some unsuccessful evolutionary lineages. Evolution 27, 177–191. Baalkhuyur, F.M., Dohaish, E.J.A.B., Elhalwagy, M.E., Alikunhi, N.M., AlSuwailem, A.M., Røstad, A., Duarte, C.M., 2018. Microplastic in the gastrointestinal tract of fishes along the Saudi Arabian Red Sea coast. Mar. Pollut. Bull. 131, 407–415. Badr, N.B., El-Fiky, A.A., Mostafa, A.R., Al-Mur, B.A., 2009. Metal pollution records in core sediments of some Red Sea coastal areas Kingdom of Saudi Arabia. Environ. Monit. Assess. 155 (1–4), 509–526. Balbi, T., Fabbri, R., Montagna, M., Camisassi, G., Canesi, L., 2017. Seasonal variability of different biomarkers in mussels (Mytilusgalloprovincialis) farmed at different sites of the Gulf of La Spezia Liguriansea Italy. Mar. Pollut. Bull. 116 (1–2), 348–356. Banni, M., Sforzini, S., Arlt, V.M., Barranger, A., Dallas, L.J., Oliveri, C., Readman, J.W., 2017. Assessing the impact of benzo [a] pyrene on marine mussels: application of a novel targeted low-density microarray complementing classical biomarker responses. PLoS One 12 (6). Baršienė, J., Lazutka, J., Šyvokienė, J., Dedonytė, V., Rybakovas, A., Bagdonas, E., Andersen, O.K., 2004. Analysis of micronuclei in blue mussels and fish from the Baltic and North Seas. Environ. Toxicol. 19 (4), 365–371. Barsiene, J., Schiedek, D., Rybakovas, A., Syvokiene, J., Kopecka, J., Forlin, L., 2006. Cytogenetic and cytotoxic effects in gill cells of the blue mussel Mytilus spp from different zones of the Baltic Sea. Mar. Pollut. Bull. 53, 469–478. Bauchau, V., 2001. Developmental stability as the primary function of the pigmentation patterns in bivalve shells. Belg J Zool 131 (l 2), 23–28. Bikham, J.W., Sandhu, S., Hebert, P.D.N., Chikhi, L., Athwal, R., 2000. Effects of chemical contaminants on genetic diversity in natural populations: implications for biomonitoring and ecotoxicology. Mutat. Res. 463, 33–51. Bin Othman, A.S., Goh, G.H., Todd, P.A., 2010. The distribution and status of giant clams (family Tridacnidae)-a short review. Raffles Bull. Zool. 58, 103–111. Bolognesi, C., Cirillo, S., 2014. Genotoxicity biomarkers in aquatic bioindicators. Current Zoology 60 (2), 273–284. Bouhallaoui, M., Zbiry, M., Elkhiati, N., Talba, S., Sforzini, S., Viarengo, A., Benhra, A., 2017. Use of biomarkers to evaluate the effects of environmental stressors on Mytilus galloprovincialis sampled along the Moroccan coasts: integrating biological and chemical data. Mar. Environ. Res. 130, 60–68. Box, A., Sureda, A., Galgani, F., Pons, A., Deudero, S., 2007. Assessment of environmental pollution at Balearic Islands applying oxidative stress biomarkers in the mussel Mytilus galloprovincialis. Comparative Biochemistry and Physiology Part C: Toxicology & Pharmacology 146 (4), 531–539. Bradford, M.M., 1976. A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Anal. Biochem. 72 (1), 248–254. Burgeot, T., Akcha, F., Ménard, D., Robinson, C., Loizeau, V., Brach-Papa, C., Cachot, J., 2017. Integrated monitoring of chemicals and their effects on four sentinel species Limandalimanda Platichthysflesus Nucella lapillus and Mytilus sp in Seine Bay: a key step towards a:lying biological effects to monitoring. Mar. Environ. Res. 124, 92–105. Cohen, M.B., Mimi, K., Vivian, O., 1996. A modified catalase assay suitable for a plate
6
Marine Pollution Bulletin 150 (2020) 110766
N. Salem Al-Howiti, et al.
responses of the Mediterranean mussel Mytilus galloprovincialis to environmental variability of dissolved oxygen. Comp Biochem Physiol Part C Toxicol Pharmacol 140, 321–329. Schiedek, D., Broeg, K., Barsiene, J., et al., 2006. Biomarker responses as indication of contaminant effects in blue mussel (Mytilus edulis) and female eelpout (Zoarces viviparus) from the southwestern Baltic Sea. Mar. Pollut. Bull. 53, 387–405. Serafim, A., Lopes, B., Company, R., Cravo, A., Gomes, T., Sousa, V., et al., 2011. A multibiomarker approach in cross-transplanted mussels Mytilus galloprovincialis. Ecotoxicology 20, 959–1974. Soldatov, A.A., Gostyukhina, O.L., Golovina, I.V., 2007. Antioxidant enzyme complex of tissues of the bivalve Mytilus galloprovincialis L an under normal and oxidative-stress conditions: a review. A: lied Biochemistry and Microbiology 43, 556–562. Sunderman, J.R., William, F., 1987. Biochemical indices of lipid peroxidation in occupational and environmental medicine. In: Foa, V., Emmett, E.A., Maroni, M., Colomi, A. (Eds.), Occupational and Environmental Chemical Hazards: Cellular and Biochemical Indices for Monitoring Toxicity. Wiley Interscience, New York, pp. 151–158. SWCC, 2015. Saline Water Conversion Corporation (SWCC). Available from. http:// www.swcc.gov.sa/. Tlili, S., Métais, I., Boussetta, H., Mouneyrac, C., 2010. Linking changes at subindividual and population levels in Donaxtrunculus: assessment of marine stress. Chemosphere 81, 692–700. Tortell, P., 2004. Thoughts on Integrated Coastal Zone Management (ICZM) in Saudi Arabia. The Regional Organization for the Conservation of the Environment of the Red Sea and Gulf of Aden-PERSGA, Wellington. Tsangaris, C., Kormas, K., Strogyloudi, E., et al., 2010. Multiple biomarkers of pollution effects in caged mussels on the Greek coastline. Comparative Biochemistry and Physiology C 3 (151), 369–378. Tuthill, A.H., 1987. Guidelines for the use of copper alloys in seawater. Material Performance 12–22. Van der Oost, R., Beyer, J., Vermeulen, N.P.E., 2003. Fish bioaccumulation and biomarkers in environmental risk assessment: a review. Environ Toxicol Pharm 13, 57–149. Van Veld, P.A., Sanders, B.Μ., Fowler, B.A., Lars, F., Di Giulio, R.T., Marius, B., Stegeman, J.J., 2018. Molecular responses to environmental contamination: enzyme and protein systems as indicators of chemical exposure and effect. In: Biomarkers. CRC Press, pp. 235–336. Vidal-Liñán, L., Bellas, J., Campillo, J.A., Beiras, R., 2010. Integrated use of antioxidant enzymes in mussels, Mytilus galloprovincialis, for monitoring pollution in highly productive coastal areas of Galicia (NW Spain). Chemosphere 78 (3), 265–272. Wahsha, M., Bini, C., Fontana, S., Wahsha, A., Zilioli, D., 2012. Toxicity assessment of contaminated soils from a mining area in Northeast Italy by using lipid peroxidation assay. J. Geochem. Explor. 113, 112–117.
2018. Long-term exposure of Mytilus galloprovincialis to diclofenac Ibuprofen and Ketoprofen: insights into bioavailability biomarkers and transcriptomic changes. Chemosphere 198, 238–248. Moron, M.A., Depierre, J.W., Mannervick, B., 1979. Levels of glutathione reductase and glutathione S-transferase activities in rat lung and liver. Biochem Biophys Acta 582, 67–78. Neo, M.L., Eckman, W., Vicentuan, K., Teo, S.L.M., Todd, P.A., 2015. The ecological significance of giant clams in coral reef ecosystems. Biol. Conserv. 181, 111–123. Neo, M.L., Wabnitz, C.C., Braley, R.D., Heslinga, G.A., Fauvelot, C., Van Wynsberge, S., Tan, A., 2017. Giant clams (Bivalvia: Cardiidae: Tridacninae): a comprehensive update of species and their distribution current threats and conservation status. Oceanogr. Mar. Biol. 55, 87–387. Nuryanto, A., Kochzius, M., 2009. Highly restricted gene flow and deep evolutionary lineages in the giant clam Tridacna maxima. Coral Reefs 28, 607–619. Ohkawa, H., Ohishi, N., Yagi, K., 1979. Assay for lipid peroxides in animal tissues by thiobarbituric acid reaction. Anal. Biochem. 95, 351–358. Oliveira, M.M., Silva-Filho, M.V., Cunha-Bastos, V.L., Fernandes, F.C., Cunha-Bastos, J., 2007. Brain acetylcholinesterase as a marine pesticide biomarker using Brazilian fishes. Mar. Environ. Res. 63, 303–312. PERSGA, 2006. State of the Marine Environment, Report for the Red Sea and Gulf of Aden. PERSGA, Jeddah. Power, A., Sheehan, D., 1996. Seasonal variation in the antioxidant defence systems of gill and digestive gland of the blue mussel Mytilus edulis. Comp. Biochem. Physiol. 114, 99–103. RCJY, 2015. Royal Commission for Jubail and Yanbu (RCJY). Available from. http:// www.rcjy.gov.sa/en-US/Pages/default.aspx. Richter, C., Roa-Quiaoit, H., Jantzen, C., Al-Zibdah, M., Kochzius, M., 2008. Collapse of a new living species of giant clam in the Red Sea. Curr. Biol. 18, 1349–1354. Röding, P.F., 1798. Museum Boltenianumsive Catalogus cimeliorum etribusregnis naturae quae olimcollegerat Joa Fried Bolten MD pd Pars secunda continens Conchyliasive Testaceaunivalvia bivalvia et multivalvia. Roméo, M., Hoarau, P., Garello, G., Gnassia-Barelli, M., Girard, J.P., 2003. Mussel transplantation and biomarkers as useful tools for assessing water quality in the NW Mediterranean. Environ. Pollut. 122, 369–378. Rowlands, G., Purkis, S., Bruckner, A., 2014. Diversity in the geomorphology of shallowwater carbonate depositional systems in the Saudi Arabian Red Sea. Geomorphology 222, 3–13. Sacchi, A., Mouneyrac, C., Bolognesi, C., Sciutto, A., Roggieri, P., Fusi, M., et al., 2013. Biomonitoring study of an estuarine coastal ecosystem the Sacca di Goro lagoon using Ruditapesphili: inarum (Mollusca: Bivalvia). Environ. Pollut. 177, 82–89. Saleuddin, A.S.M., 1979. Shell formation in molluscs with special reference to periostracum formation and shell regeneration in: S van der Spoel, AC Van Bruggen & J Lever (Eds.) Pathways in Malacology. Junk The Hague pp. 47-81. Santovito, G., Piccinni, E., Cassini, A., Irato, P., Albergoni, V., 2005. Antioxidant
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