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Integrated use of biomarkers to assess the impact of heavy metal pollution on Solea aegyptiaca fish in Lake Qarun

Environmental Sciences Europe volume 34, Article number: 74 (2022) Cite this article

Abstract

Background

Biomarkers have become a valuable tool in environmental assessment, since they contribute to predicting contaminants in monitoring programmes. This study aimed to investigate the toxicity of heavy metal pollution in Lake Qarun using a multibiomarker approach (morphological, oxidative stress, genotoxicity, stress proteins) in Solea aegyptiaca fish. During the winter and summer seasons, water and fish samples were collected from different locations along Lake Qarun; western and northern sectors were away from any source of pollution, while southern and eastern sectors were exposed to effluents discharged from El-Wadi and El-Bats drains, respectively. The environmental quality, as well as the accumulation of metals (Fe, Cu, Zn, Cd, Pb, Ni) in fish gills, liver, and muscles were assessed. Data were integrated using the integrated biomarker response index (IBRv2) for biomarker response interpretation.

Results

Water quality and bioaccumulation of heavy metals revealed a highly significant difference between samples collected from polluted sectors and those collected far from drainage water, and, seasonal differences were detected. Growth indices revealed a significant difference between sites and seasons. Fish from the western sector had the highest total antioxidant capacity in their gills, liver, and muscles, with no seasonal differences detected. However, the maximum value of malondialdehyde, protein carbonyl, 8-hydroxy-2′deoxyguanosine, metallothionein, heat shock protein 70, and DNA strand breaks in gills, liver, and muscles was detected in the polluting sectors. It revealed a significant difference between seasons, with the highest value during the winter season. According to IBRv2 results, the most effective biomarkers in this study were malondialdehyde and 8-hydroxy-2′deoxyguanosine in gills, protein carbonyl and metallothionein in the liver, heat shock protein 70 in gills and liver, and DNA strand break in gills, liver, and muscles.

Conclusions

This multibiomarker approach contributes to distinguishing between locations with varying levels of anthropogenic pollution, identifying the drainage water-exposed sectors as the most stressed and the winter season as the most critical time for Solea aegyptiaca owing to spawning. The biomarkers chosen are effective indicators in Solea aegyptiaca under stress, indicating the potential for environmental monitoring.

Graphical Abstract

Background

Lake Qarun is a closed saline lake and one of Egypt’s most important inland aquatic habitats. It collects agricultural and municipal pollution discharged from the depression of El-Fayoum throughout its two main drains, El-Bats and El-Wadi [1]. The water quality of Lake Qarun had previously been investigated [2, 3]. The increased pollution of water resources in Lake Qarun and the consequent effects on the aquatic environment and human health is an issue of great concern [4]. Fish, generally at the top of the aquatic food chain can bioaccumulate high levels of heavy metals. These metals accumulate in fish organs in diverse ways, posing a significant health risk to humans [5]. Consequently, the issue of hazardous metal contamination in fish has received more attention [6].

Biomarkers are valuable tools for determining how biological systems interact with potential pollutants (chemical, physical or biological) [7] and, therefore, contribute to evaluating the responses of heavy metals in organisms [8]. Metals can lead to oxidative stress in fish by stimulating the generation of reactive oxygen species (ROS), which damages biological components like lipids, proteins and DNA [9, 10]. These oxidative damages can be determined by measuring lipid peroxidation (LPO) [11, 12], protein carbonylation (PC) [12, 13], and DNA base oxidation [14]. ROS can be detoxified by cellular antioxidant defence systems, both enzymatic and non-enzymatic [15] while measuring the total antioxidant capacity (TAC), evaluating the overall efficacy of cellular antioxidants against oxyradicals, and providing a comprehensive assessment of responsiveness to oxidative stress [16]. DNA damage biomarkers can be used to assess the genotoxicity of environmental pollutants and a comet assay is a valuable tool for assessing genotoxicity in fish in the environment [17]. The induction of stress proteins is the only molecular mechanism used by fish to cope with stress [18]. Overexpression of heat shock proteins (HSPs) and metallothioneins (MTs) can be identified in response to a variety of adverse environmental conditions, including heavy metal exposure [19]. With respect to pollution in general and heavy metals in particular, fish condition factor (K) and hepatosomatic index (HSI) are utilized as biomarkers of health and growth [20].

In environmental monitoring, the indicator organism used is crucial. The sole, genus Solea, is one of the most important and valuable commercial flatfish in Egypt and is well-regarded for human consumption [21]. Thus, the presence of substantial quantities of hazardous metals in these species might severely impact their physiological function and consumers’ health [22]. Solea fish are sedentary demersal fish buried in the substrate on muddy bottoms [23, 24]. Eventually, they will be vulnerable to excessive metal concentrations in the sediments. Since they eat predominantly mollusks, invertebrates, small crustaceans, and small fish, which concentrate metals in their tissues, their feeding behaviour may enhance their chances of exposure to increased amounts of these components [24].

The proper application of biological reactions as biomarkers necessitates understanding seasonal fluctuations in biotic and abiotic variables, which have all been proven to impact the basal levels of several biomarkers and their responsiveness to pollution [25]. The combined effects of various natural stressors and pollutants can often be synergistic [26]. Recent studies have revealed that increased summer temperatures have a stronger impact on Solea fish due to increased physiological activity and metal uptake than lower winter temperatures [27, 28]. Biomarker responses demonstrate similar patterns in several fish species, as evidenced by the elevated oxidative stress [29,30,31], genotoxicity [32,33,34], and stress proteins [35,36,37]. There is a paucity of information with respect to Solea aegyptiaca inhabiting Lake Qarun, as well as the effect of seasonal variations on these biomarkers. Therefore, this study aimed to determine the toxic impact of heavy metal pollution in Lake Qarun using a suite of biomarkers; morphological, oxidative stress, genotoxicity, and stress proteins in Solea aegyptiaca fish to investigate the viability of using the Solea aegyptiaca fish as a water pollution indicator at Lake Qarun, El-Fayoum Governate, Egypt. Moreover, to compare the influence of the abiotic environmental factors (temperature, salinity, and dissolved oxygen) during the summer and physiological processes (reproduction) during the winter season on Solea aegyptiaca biomarkers. Furthermore, without an integrated strategy to handle issues in linking information and categorizing locations according to contaminant-induced variations in the health condition of organisms, the practical implementation of the biomarker approach in environmental evaluation is restricted [38]. Studies using an integrated biomarker response (IBRv2) index to simplify biomarker response interpretation have never been tested in Egyptian fishes under field or laboratory conditions. Therefore, the biomarker responses of Solea aegyptiaca fish were combined into a biomarker response index to assess the extent of contamination along Lake Qarun and to determine the biomarkers that indicate the strongest responses to environmental disturbances.

Materials and methods

Study area

Lake Qarun is Egypt’s only enclosed saline lake. It is located in the western desert region of the Fayoum depression, 83 kms southwest of Cairo. The lake is 43 m (140 feet) below sea level and encompasses 243 square kilometres (78 sq mi). It is located between 30o34" and 30o49" east longitudes and 29°25" and 29°34" north latitudes. The lake is 1–8 m deep and holds approximately 1,100,000,000 gallons of water [1]. The lake receives a large amount of untreated agricultural, industrial, sewage, and residential effluents (about 450 million m3 per year) from El-Fayoum province via two major drains (El-Bats and El-Wadi drains) in addition to several smaller drains that lead to the lake [39]. Figure 1 depicts the chosen locations. Site 1 (30º 31′ 09.6´´E 29º 25′ 42.4´´N): located in the western sector of the lake, it is a relatively unpolluted area with no drainage water. Site 2 (30º 37′ 42''E 29º 28′ 53''N): represents the northern sector of the lake; it lies north of El-Qarn Island, far from drainage water. Site 3 (30º 37′ 43.4´´E 29º 26′ 49.4´´N): it is located at the midpoint of the southern sector near the mouth of the El-Wadi drainage channel. Site 4 (30º 48′ 47.2´´E 29º 31′ 04.1´´N): is at the eastern sector near the mouth of the El-Bats drain.

Fig. 1
figure 1

Lake Qarun map with the studied sites

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Water sampling

In polyethylene bottles, water samples were obtained from the study sites throughout the winter (January–March) and summer (July–September) seasons of 2019, around 50 cm below the water’s surface. Samples were filtered in the field, acidified with 10% nitric acid (HNO3) for preservation, put in an ice bath, and brought to the laboratory.

Fish and tissue sampling

At the same time, a total of 120 fish of Solea agyptiaca (30 fish/site) were collected by fishers’ nets from the same sites, where the water samples were taken, with an average body weight of 55.38 ±15.65 and 36.80 ± 11.04 g and an average total length of 19.10 ± 2.50 and 16.30 ± 1.58 cm for winter and summer seasons, respectively, and then transported to the laboratory, National Institute of Oceanography and Fisheries, Shakshouk Station, El-Fayoum, in aerated, chilled containers containing seawater from the sampling locations.

Prior to decapitation and tissue sampling, fish (20 individuals per site) were assessed (total length, cm) and weighed (total and liver weights, g) to assess growth parameters. Gills, livers, and muscles were sampled, rinsed in a phosphate-buffered saline (PBS) solution (pH 7.4) to eliminate extra blood, and then pooled. Three pooled samples of 9 individuals per site were dried in an oven at 105 °C for 48 h and grounded to a fine powder for metals concentrations. Six pooled samples of 18 individuals per location were immediately frozen in liquid nitrogen and maintained at −80 ºC until homogenate preparation for biomarkers analysis. In addition, specimens of gills, liver, and muscles of each group were immediately excised and fixed in normal saline and stored at −80 °C for comet assay analysis.

All applicable international, national, or institutional guidelines for the care and use of animals were followed by the authors.

Water analysis

Field measurements

Water temperature, pH and salinity were monitored in the field using a Hydrolab (model Orion Research Ion Analyzer 399A).

Dissolved oxygen

According to APHA [40], dissolved oxygen (DO) was determined by Wrinkler’s iodometric method. A glass stoppered biochemical oxygen demand (BOD) bottle of 300 ml capacities was entirely filled with lake water. The DO in the sample was then fixed by adding a series of reagents (manganous sulphate, alkaline potassium iodide, and conc. H2SO4) that formed an acid compound that was then titrated against sodium thiosulphate until the solution became colorless; DO was expressed in mg/l.

Determination of residual heavy metals in Solea aegyptiaca tissues

The dried samples (gills, liver and muscles) were digested in accordance with the procedure outlined by Ghazally [41], in which 1.0 g (dry powder) was digested in (5 ml nitric acid + 5 ml perchloric acid) solution and heated on a hot plate at 80–90 °C until the sample became clear. The solution was cooled, filtered and transferred to a 25 ml volumetric flask, which was then filled with de-ionized water to the desired level. The digests were stored in plastic bottles, and Fe, Zn, Cu, Cd, Pb and Ni concentrations in the gills, liver and muscles were assessed using an Inductively Coupled Plasma Emission Spectrometer (ICP) (ICAP-6300 Duo) according to APHA [42]. The results were expressed in mg/kg dry weight. The limit of detection ranges from 7 µg/l to 100 mg/l for Fe, 2 µg/l to 100 mg/l for Zn, 6 µg/l to 50 mg/l for Cu, 4 µg/l to 50 mg/l for Cd, 40 µg/l to 100 mg/l for Pb, and 15 µg/l to 50 mg/l for Ni.

The metal pollution index calculation

Metal pollution index (MPI) was utilized to compare the overall metal content of the analyzed fish’s gills, liver, and muscles in different year seasons. According to Usero et al. [43], MPI was estimated with the following formula: MPI = (Fe × Zn × Cu × Cd × Pb × Ni)1/6.

Determination of growth parameters

The condition factor (K) and Hepato-somatic index (HSI) were determined using the method of Schreck and Moyle [44] as:

$${\text{K}}\, = \,{\text{Weight }}\left( {\text{g}} \right)/{\text{Length}}^{{3}} \left( {{\text{cm}}} \right)\, \times \,{1}00$$
$${\text{HSI}}\, = \,{\text{Weight of the liver }}\left( {\text{g}} \right)/{\text{Total fish weight }}\left( {\text{g}} \right)\, \times \,{1}00$$

Biomarker responses

Oxidative stress parameters

The total antioxidant capacity (TAC) level was estimated spectrophotometrically at 532 nm according to the methodology of Tween 80 oxidation [45]. After the homogenization of the frozen tissues (gills, liver, and muscles) in ice-cold buffer (100 mM Tris-HCl, pH 7.2) in 1:6 ratio (w/v) using Omni International Tissue Master 125 Homogenizer (USA) submerged in an ice water bath, the homogenates were centrifuged at 3000 × g for 15 min at 4 °C. Subsequently, 2 ml of 1% Tween 80 reagent, 0.2 ml of 1 mM FeSO4, and 0.2 ml of 10 mM ascorbic acid were added to 0.1 ml of homogenate supernatant. The sample was replaced by 0.1 ml of dis. water in the blank assay. The solution was boiled in a water bath for 48 h at 37 ºC. The mixture was then allowed to cool before adding1 ml of 20% trichloroacetic acid (TCA). 2 ml of 0.25% 2-thiobarbituric acid was mixed with 2 ml of supernatant after centrifugation at 3000 × g for 10 min. Using Spectrophotometer UV–visible double beam-labomed Inc., USA, the absorbance was measured at 532 nm after 15 min of heating in a water bath at 95 °C. The blank was defined as having a 100% absorption. The level of TAC in the sample (%) was quantified regarding the blank absorbance.

Malondialdehyde (MDA) was measured by detecting 2-thiobarbituric acid reactive substrates concentration according to Ohkawa et al. [46], using the Biodiagnostic (Egypt) Kit. The frozen gills, liver, and muscle tissues were homogenized in cold buffer (50 mM potassium phosphate, pH 7.4) in a 1:6 ratio (w/v) with Omni International Tissue Master 125 Homogenizer (USA). After that, the homogenates were centrifuged at 4000 rpm for 15 min. In the assay, 0.2 ml of homogenate supernatant was added to 1.0 ml of chromogen (thiobarbituric acid + detergent + stabilizer) and sealed with a glass bead. In a boiling water bath for 30 min, the solution was heated. The absorbance was measured at 534 nm by UV Visible double beam-labomed Inc. Spectrophotometer (USA). MDA level in the sample was expressed in nmol/g.

Protein carbonyl content (PC) was assessed colorimetrically by dinitrophenylhydrazone (DNPH) assay according to Reznick and Packer [47]. The frozen tissues (gill, liver, and muscles) were homogenized in PBS (pH 7.4) (1:10 w/v) with Omni International Tissue Master 125 Homogenizer (USA). The homogenates were then centrifuged for 15 min at 5000 rpm, and 200 μl of homogenate supernatant was added to 800 μl of 10 mM DNPH in 2.5 M HCl. A sample control was also made by mixing 200 μl of homogenate supernatant with 800 μl of 2.5 M HCl. After incubation at room temperature for 1 h with a 15 min vortexing interval, 1 ml of 20% TCA was added. The solution was then centrifuged at 10,000 × g for 10 min at 4 °C after being incubated on ice for 5 min. After collecting the supernatants, 1 ml of 10% TCA was added before being centrifuged at 10,000 × g for 10 min at 4 °C. The protein pellet was washed three times with 1 ml of 1:1 (v/v) ethanol: ethyl acetate and centrifuged at 10,000 × g for 10 min at 4 °C. The protein pellet was then resuspended in 500 μl of 6 M guanidine hydrochloride and centrifuged at 10,000 × g for 5 min at 4 °C. The supernatant was sampled, and the absorbance was measured at 370 nm with control as a blank by UV Visible double beam-labomed Inc. Spectrophotometer (USA). The protein carbonyl concentration was expressed in nmol/g.

8-hydroxy-2′deoxyguanosine (8-OHdG) concentration was analyzed using an ELISA kit provided by Bioassay Technology Laboratory (China). After the homogenization of the frozen samples (gill, liver, and muscles) in PBS (pH 7.4) (1:10 w/v) with Omni International Tissue Master 125 Homogenizer (USA), the homogenates were centrifuged at 5000 rpm for 15 min. In the assay, samples were added to sample wells with 40 μl of sample, 10 μl of antibody, and 50 μl streptavidin–HRP (enzyme conjugate). After 60 min at 37 °C and five washes with wash buffer, 50 μl substrate solution A and 50 μl substrate solution B were added to the wells and incubated for 10 min at 37 °C. To stop the reaction, 50 μl of stop solution was added to each well, and the blue color was turned yellow. The absorbance was detected at 450 nm using Thermo Scientific Multiskan FC Microplate Photometer (USA). The concentration of 8-OHdG was expressed in ng/g.

Genotoxicity estimated by comet assay

The degree of DNA damage was determined by the comet assay (alkaline single-cell gel electrophoresis) as detailed by Singh et al. [48]; 1 ml ice-cold PBS was used to dissolve 0.5 g of crushed samples. After stirring for 5 min, the suspension was filtered. Subsequently, 100 μl of cell suspension was mixed with 600 μl of low melting agarose (0.8% in PBS). 100 μl of this mixture was then placed on pre-coated slides. For 15 min, the coated slides were submerged in lysis buffer [0.045 M Tris-borate-EDTA, pH 8.4, containing 2.5% sodium dodecyl sulphate (SDS)]. The slides were placed in an electrophoresis chamber using the same Tris-borate-EDTA buffer as before but without SDS. The electrophoresis conditions were 2 V/cm for 2 min and 100 mA, and then stained with ethidium bromide 20 μg/ml at 4 °C. The DNA fragment migration patterns of 100 cells for each treatment level were examined using a fluorescence microscope (With excitation filter 420–490 nm [issue 510 nm]). The lengths of the comet's tails were measured from the nucleus to the tail’s end, with a 40 × increase to count and measure the comet's size. To visualise DNA damage, ethidium bromide-stained DNA using a 40 × objective on a fluorescent microscope. The Comet 5 image analysis software developed by Kinetic Imaging, Ltd. (Liverpool, UK) linked to a charged-coupled device camera was used to evaluate the quantitative and qualitative extent of DNA damage in the cells by measuring the length of DNA migration and the percentage of migrated DNA. Finally, the program calculates the tail moment. Finally, 50–100 cells were randomly selected and evaluated per sample.

Stress proteins

Metallothionein (MT) was assessed spectrophotometrically using the Ellman's SH according to Viarengo et al. [49] method and a modification of Cataldo et al. [50]. Gills, liver, and muscle tissues were homogenized in three volumes of the homogenization buffer (0.5 M sucrose, 20 mM Tris-HCl buffer, pH 8.6, containing 0.01% β-mercaptoethanol). The homogenates were divided into aliquots (3 ml) and centrifuged at 10.000 × g for 30 min. Afterward, 1 ml of supernatant was mixed with 1 ml of cold (−20 °C) absolute ethanol and 80 μl of chloroform. After centrifugation at 6000 × g for 10 min, three volumes of cold ethanol were added to the resulting supernatant, which was kept at −20 °C for 1 h. The supernatant was centrifuged for 10 min at 6000 × g, and the resulting pellets were washed with ethanol: chloroform: homogenization buffer (87:1:12) before being centrifuged for another 10 min at 6000 × g. The pellets were air-dried before resuspension in 100 μl of 5 mM Tris-HCl, 1 mM EDTA at pH 7, and then added to 420 μl of 0.43 mM 5,5-dithiobis-2-nitrobenzoic acid in a 0.2 M phosphate buffer, pH 8. After 30 min at room temperature, the absorbance was measured at 412 nm with a UV–visible double beam-labomed Inc. spectrophotometer, USA. The glutathione standard curve was used to quantify the amount of MT in the samples, considering that 1 mol of MT comprised 20 mol of cysteine and expressed in μg/g tissue.

Heat shock protein 70 (HSP 70) was quantified using an ELISA kit provided by Bioassay Technology Laboratory (China) and followed the same procedure described for 8-OHdG. The concentration of HSP70 was expressed in ng/g.

The integrated biomarker response index

The results of the biomarkers were incorporated into the integrated biomarker response version 2' (IBRv2) index, described by Beliaeff and Burgeot [51] and updated by Sanchez et al. [52]. In each studied site, the data from each biomarker (Xi) were compared to the reference data (X0), and variance was reduced using a log transformation.: Yi = log Xi/X0. The general mean (μ) and standard deviation (s) of Yi for all sites were computed for each biomarker, and Yi was normalized as Zi = (Yi—μ)/s. The mean of standardized biomarker response (Zi) and mean of reference biomarker data (Z0) were used to establish a biomarker deviation index (A), Ai = Zi−Z0 for each biomarker in each site, to draw a basal line centred on 0 and to describe biomarker variation according to this line. The absolute value of A parameters calculated for each biomarker in each site was summed as IBRv2 = Σ│Α│ to obtain the IBRv2. For a single site, ʽʽAˮ parameters are presented in a star plot to reflect the deviation of each studied biomarker from reference. The area above 0 indicates biomarker activation, while the area below 0 represents biomarker suppression.

Statistical analysis

Two-way analysis of variance (ANOVA) was used to determine the significant difference in season and site, followed by Duncan’s multiple range test when the differences were significant. The level of significance in all tests was P ≤ 0.05. The data were expressed as means ± standard deviation (SD).

Results

Water physicochemical parameters

As detailed in Table 1, water temperature demonstrated the lowest value in the southern sector during winter and the highest value in the northern sector during summer. The highest pH value was found in the eastern sector during summer, while the lowest value was found in the northern sector during winter. Salinity showed the highest value in the northern sector during summer and the lowest value during winter in the southern sector. The highest DO was in the western sector during winter and the lowest in the eastern sector during summer.

Table 1 Water physicochemical parameters for Lake Qarun during winter and summer seasons, 2019
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Heavy metals bioaccumulation and metal pollution index

The concentrations of Fe, Cu, Zn, Cd, Pb, and Ni in gills, liver, and muscle samples taken from the studied locations during the winter and summer seasons and MPI values are detailed in Tables 2, 3 and 4 for gills, liver, and muscles, respectively. The highest bioaccumulation was recorded in fishes collected from the eastern and southern sectors. The MPI sequence in the investigated Solea aegyptiaca tissues was: gills  > muscles  > liver. Moreover, MPI in gills, liver, and muscles showed the highest value for fishes collected from the eastern sector during summer, while the least MPI was for fishes collected from the western sector during summer for gills and winter for liver and muscles.

Table 2 Heavy metal concentrations and MPI in gills during winter and summer seasons, 2019
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Table 3 Heavy metal concentrations and MPI in liver during winter and summer seasons, 2019
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Table 4 Heavy metal concentrations and MPI in muscles during winter and summer seasons, 2019
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Growth parameters

According to the data obtained, the summer season demonstrated the highest K value. In addition, the southern sector had the highest K, while the western sector had the lowest K value. Moreover, results of HSI declared that the highest value was detected in the summer season. With regard to the sampling sites, the highest value of HSI was recorded in the western sector and the lowest value in the eastern sector (Table 5).

Table 5 Growth parameters of Solea aegyptiaca during winter and summer seasons, 2019
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Biomarker responses

Oxidative stress parameters

The mean values ± SD of gills, liver and muscle TAC, MDA, PC, and 8-OHdG, are depicted in Table 6. TAC showed an insignificant difference between seasons in terms of gills, liver, and muscles. While the highest TAC was detected in the western sector for gills, liver, and muscles, and the lowest TAC was detected in the eastern sector for gills and southern sector for liver and muscles. MDA demonstrated the highest mean value in gills, liver, and muscles during the winter season. In addition, the obtained data revealed that the eastern sector recorded the highest level in gills, liver, and muscles, and the western sector showed the lowest level in gills, liver, and muscles. Winter season demonstrated the highest PC concentration in gills, liver, and muscles of Solea aegyptiaca. Moreover, the southern sector recorded the highest concentration of PC in gills, liver, and muscles, while the western sector detected the lowest concentration in gills, liver, and muscles. The current study revealed an increased concentration of 8-OHdG in gills and muscles during the winter season. Furthermore, the eastern sector recorded the highest 8-OHdG concentration in Solea aegyptiaca organs. Meanwhile, the western sector detected the lowest 8-OHdG concentration.

Table 6 Oxidative stress biomarkers of Solea aegyptiaca organs during winter and summer seasons, 2019
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Comet assay

DNA damages of Solea aegyptiaca fish collected from the studied sites during the winter and summer seasons are displayed in Table 7. Concerning DNA damage in gills of Solea aegyptiaca presented as tail DNA (%), tail length (µm), and tail moment, the present study demonstrated that the highest value was recorded during the winter season. The eastern sector also showed the maximum gills DNA damage. Regarding liver DNA damage, the highest value of tail DNA (%), tail length (µm), and the tail moment was observed during winter, whereas the maximum damage in Solea aegyptiaca liver was recorded in the eastern sector. In addition, muscular DNA recorded the highest value during winter, and the eastern sector showed maximum DNA damage. (Fig. 2).

Table 7 DNA damage of Solea aegyptiaca organs during winter and summer seasons, 2019
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Fig. 2
figure 2

Representative results of comet assay in gills, liver, and muscles of Solea aegyptiaca fish collected from different sites along Lake Qarun during winter a and summer b seasons, 2019. [The more the damage, the larger the DNA tail area ((%)) or the longer the DNA tail length]

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Stress proteins

The results (mean values ± S.D) of MT and HSP70 in the gill, liver, and muscles of Solea aegyptiaca are presented in Table 8. MT revealed the highest concentration in gills, liver, and muscles during winter. Furthermore, the results showed the maximum MT concentration in the eastern sector for gills and muscles and the southern sector for the liver. On the contrary, the minimum concentration in gills, liver, and muscles was detected in the western sector. HSP70 is declared the highest HSP70 level in gills, liver, and muscles during winter. Regarding the studied sites, the highest HSP70 level was in the eastern sector for gills, liver, and muscles, while the lowest level was in the western sector.

Table 8 Stress proteins biomarkers of Solea aegyptiaca organs during winter and summer seasons, 2019
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The integrated biomarker response index

The winter season showed higher IBRv2 scores, where Solea aegyptiaca were more stressed than the summer season. Furthermore, the findings revealed a potential distinction between the sites in terms of pollution levels along the lake. The eastern sector had the highest IBRv2value, followed by the southern sector, which had the most polluted sites in direct contact with sewage and agricultural contaminants from El-Bats and El-Wadi drainage channels. In contrast, the western sector presented the lowest IBRv2. With regard to each site individually, the results showed that increased gills MDA, liver PC, gills and liver HSP70, liver MT, gills 8-OHdG and gills, liver and muscles DNA strand breaks were the most discriminant factors for the eastern sector, while variations in MDA level in gills and PC and MT concentrations in liver, were the most crucial responses that explain the IBRv2 score in the southern sector. The western and northern sectors, on the contrary, demonstrated minimal changes and inhibition in the biomarkers analyzed. Moreover, considering IBRv2 for each organ (gills, liver, and muscles) of Solea aegyptiaca inhabiting Lake Qarun, regardless of sites and seasons, it revealed different results, with the liver having the highest value, followed by the gills and muscles IBRv2 showing suppression (Fig. 3).

Fig. 3
figure 3

Integrated biomarker response index (IBRv2) depending on the following biomarkers: TAC, MDA, PC, HSP70, MT, 8-OHdG, and DNA damage (DNA dam) in different organs (g = gills, l = liver, m = muscles) of Solea aegyptiaca collected from Lake Qarun during winter and summer seasons, 2019

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Discussion

Lake Qarun water quality

Water temperatures are a critical control parameter in the aquatic system, influencing the aquatic environment's physical, chemical, and biological transformation [53]. The water temperature of Lake Qarun showed the expected seasonal pattern. The increase in temperature during the summer season corresponds to what Al-Afify et al. [4] had recorded and results from low water levels and solar heating, with summer days being longer than winter days [54]. The pH of natural water impacts biological and chemical reactions, as well as metal ion solubility and natural aquatic life [53]. During the summer, the relatively higher pH values in the lake's eastern and southern sectors may be due to an increase in photosynthetic activity, lowering CO2 levels in the water. Low concentrations of DO may also play a role [55]. These findings are consistent with those obtained Al-Afify et al. [4]. Water salinity is an essential parameter for fast evaluation of water quality, Vicente-Martorell et al. [56] stated that salinity decreases fish intake and accumulation of metals and contaminants and has an inverse relationship with the water level. In the current study, salinity demonstrated a significant decrease in the eastern and southern sectors due to the diluting impact caused by drainage water from the El-Bats and El-Wadi drains, as recorded by Abd Ellah [57]. DO is critical for aquatic organisms’ survival and wellness. Fish and other aquatic species rely on the DO concentration of a water body for breathing. The distribution of DO is influenced by the solubility of various inorganic nutrients [58]. In the present study, DO demonstrated low levels in the eastern and southern sectors, which may be due to dissolved oxygen depletion for oxidation of large amounts of organic materials from sewage and agricultural wastes discharged to the lake directly from El-Bats and El-Wadi drains at these areas, this observation agrees with that obtained by Tayel et al. [59]. Furthermore, the increased rate of oxygen uptake through a breakdown of organic matter by microorganisms, augmented by the rise in water temperature, is the leading cause of DO deficit in the summer [54, 60]. Long-term exposure to low DO levels (< 5 mg/l) increases an organism’s susceptibility to other environmental stresses [61] and has dire implications for fish and other aquatic animals' survival, as reduced DO activates physiological regulatory mechanisms responsible for maintaining the oxygen gradient between water and tissues, which is necessary for the aerobic metabolic pathways to function [62].

Heavy metal bioaccumulation and metal pollution index in Solea aegyptiaca

Metal contamination in aquatic systems has received special attention due to its toxicity, persistence/bioaccumulation in the environment, and ecological risks [63]. The increased concentrations of all the studied heavy metals in the gills, liver, and muscles of Solea aegyptiaca gathered from the eastern and southern sectors of the lake were inconsistent with our recent results of chemical analysis of Lake Qarun water [64]. This finding indicates that the eastern and southern parts are the most polluted sides of the lake due to the large amount of agricultural and industrial effluents discharged directly to the lake at these sites from El-Bats and El-Wadi drains. Furthermore, these findings are compatible with those of Hussein et al. [65]. The MPI of the total combination of metals revealed that metal concentrations in gills, liver, and muscles varied seasonally, with a greater MPI for fish taken in the summer. These results are supported by Ibrahim and Omar [66] and Mohamed et al. [67].

Status and condition of Solea aegyptiaca

K and HSI are morphological markers that can provide information on a fish's overall health status [68]. Although physiological activity (growth, reproduction, and secretion) may influence these values under certain environmental circumstances, they may act as a first screening biomarker to detect effects [69]. The significant increase in the K values in fish collected from the eastern and southern sectors could be explained by the fact that untreated sewage and agricultural wastewater discharged directly from El-Bats and El-Wadi drainage canals in these lake areas is high in nutrients contributing to a high K value, which aligns with Fonseca et al. [70]. While lowest values of K were found in the winter season at which spawning of Solea aegyptiaca occurs, as indicated by Ahmed et al. [71] and Kalifa et al. [72]. Similar patterns of K value decline have been observed in various fish species and have become an indicator of spawning processes [73, 74]. The significant decrease in HSI, which is another parameter of fish growth, in fish collected from the eastern and southern sectors of the lake is consistent with that of Zaghloul et al. [75], who attributed it to depletion of hepatic glycogen accompanied by hyperglycemia, indicating the fish’s requirement for energy to withstand the heavy metal contamination stress. Bakhoum et al. [76] reported that the lowest values of hepatosomatic indices were recorded only during the peak spawning period. This finding is in agreement with our finding, where the lowest values of HSI were found in the winter season at which spawning of Solea aegyptiaca occurs.

Oxidative stress responses

Oxidative stress is an inherent element of aerobic life, resulting from the imbalance between ROS formation and antioxidant defences in biological systems [77]. The production of radicals such as ROS, which can induce oxidative stress, is one of the most well-studied pathways by which HM can cause pathophysiological processes. These active species can further induce oxidative damages to biomolecules (such as DNA, proteins, and lipids), impairing their functional properties, resulting in changes in the normal activities of cells, tissues, organs, and eventually organisms, as manifested by disease symptoms and other pathological conditions [10, 78]. However, the antioxidant defence mechanism is triggered as a radical scavenging system to counteract the threat of reactive species [79]. An antioxidant is defined as any substance that, when present in low concentrations, inhibits or prevents oxidative damage to essential molecules [80].

Individual antioxidant responses were combined with the measurement of TAC [81]. The considerable decline in TAC in gills, liver, and muscles of fish caught from Lake Qarun’s eastern and southern regions, exposed to heavy metal pollution from El-Bats, and El-Wadi drainage channels at these sites, is similar to those of Benedetti et al. [82] showed a negative response of TAC in the liver of Anguilla Anguilla under field conditions. In addition, Mehrpak et al. [83] and Banaee et al. [84] reported antioxidant depletion following cadmium exposure in common carp (Cyprinus carpio) liver and muscles, respectively. Moreover, Drąg-Kozak et al. [85] found that the total antioxidant capacity level in the hepatopancreas was significantly decreased in Cd-treated Prussian carp (Carassius gibelio) fish. The present study demonstrated no seasonal variations in gills, liver, and muscles of Lake Qarun, s Solea aegyptiaca fish which could be because, according to the study of Gorbi et al. [16] in the European Eel Anguilla Anguilla liver, the seasonal rise in natural oxidative pressure is balanced by fluctuations in individual antioxidants, without changing the organisms’ total redox status.

Peroxidation of lipids is a sign of oxidative damage in cells and tissues resulting from a disturbance in the balance between prooxidant and antioxidant agents [11, 86]. The most common method for monitoring LPO is measuring the end-product, MDA [87]. The significant increase in MDA levels in gills, liver, and muscles of Solea aegyptiaca fish gathered from the eastern and southern sectors of Lake Qarun, exposed to heavy metals from drainage channels at these sites, is a clear oxidative stress indication. These observations are similar to that provided by da Silva Montes et al. [86], Nunes et al. [88], and Sifi and Soltani [89], who attributed the observed rise in MDA to heavy metals accumulating in several tissues of polluted fish. Heavy metal metabolism frequently leads to ROS production, which is known to extract hydrogen atoms from unsaturated bonds, changing lipid structure and function. The extraction of hydrogen atoms from a methylene group is easier in polyunsaturated fatty acids due to the near closeness of the unsaturated bonds, which allows for the easier abstraction of hydrogen atoms. The fluidity of the membrane, and thus the organelle's function and cell health, may be impaired as a result [90]. Therefore, the observed increased MDA level indicated lipid molecule vulnerability to ROS and the magnitude of oxidative damages imposed on these molecules.

In addition, previous evidence has indicated that acidic or alkaline pH can trigger a prooxidant in different fish organs [91, 92]. The higher LPO and lower TAC in the gills, liver, and muscles of Solea aegyptiaca exposed to alkaline pH at the eastern and southern sectors in this study were expected and demonstrated that the function of these organs was affected, and fish were not able to neutralise ROS. Similarly, in tambaqui (Colossoma macropomum), Nile tilapia (Oreochromis niloticus), Amazon catfish (Pseudoplatystoma reticulatum), and pacu (Piaractus mesopotamicus), alkaline pH present more deleterious effects than acidic pH [93,94,95]. However, the deterioration of water quality in extreme drought conditions during the dry season (summer season) causes oxidative stress and enhanced peroxidation of lipids as fish are subjected to hypoxia under these conditions [96]. The present results showed the highest gills, liver, and muscle MDA levels during the winter season. Elevated MDA levels during the spawning period were also shown by Soldatov et al. [97] in bivalve Mytilus galloprovincialis (L.) and Morozov et al. [98] in common bream Abramis brama (L.). Therefore, spawning could be a physiological state in which aquatic organisms are naturally exposed to oxidative stress [97]. Moreover, cold aquatic habitats had higher DO levels (in harmony with our previous results) and higher intracellular lipid contents [99]. Increased lipid concentrations and improved oxygen solubility facilitate oxygen transport in fish tissues, as does higher lipid unsaturation, which stimulates LPO chain reactions [100].

Another critical parameter by which to evaluate oxidative stress damage is PC formation. PCs are an irreversible post-translational alteration that occurs early in the oxidative stress process [101]. Proteins are targets for free radicals, and protein oxidation is described as a covalent modification of proteins caused by ROS or reaction with by-products of oxidative stress, resulting in the change of specific amino acid residues and the formation of PC derivatives [102]. It is a valuable biomarker for the exposure of aquatic organisms to environmental pollutants [103], and metal-catalyzed protein oxidation is an important process by which carbonyls are incorporated into proteins [104]. The significant increase in PC level in gills, liver, and muscles of Solea aegyptiaca from the eastern and southern sectors indicates that heavy metal pollution at these locations had induced oxidative stress in fish. Previous studies have shown similar observations that exposure to metals induces PC in the gill, liver, brain, kidney, and muscle of red sea bream [105], gill, liver, kidney, and brain of Channa striatus and Heteropneustes fossilis [106] and gill, liver, and muscle of Notopterus notopterus [107]. In the metal-catalyzed oxidation reactions, an electron donor system is needed to catalyze the reduction of O2 to H2O2 and Fe(III) to Fe(II). Superoxide anions can react directly with Fe(III) to produce the reduced form of the metal. The Fe(II) ion then binds to the metal-binding site on the protein, followed by a reaction with H2O2. This reaction generates •OH, OH-•, and Fe(III). The active oxygen species react locally with the amino acid side chains at the metal-binding site leading to metal oxidation and protein carbonylation [108]. The significant increase in protein damage (oxidation) during winter season, spawning period of Solea aegyptiaca, as indicated by elevated PC content in gills, liver, and muscle tissues was stated by Husmann et al. [109] found an induction in PC levels in some Mollusk species, such as Laternula elliptica contaminated with Copper and Iron during the reproductive period. This finding could be due to the release of sexual products during spawning, which causes tissue damage and oxidation [110]. In addition, the reduced environmental temperature may raise DO levels in seawater and, consequently, in ectothermic animals' internal fluids, thus increasing the danger of ROS generation [111]. Moreover, during cold acclimation, all tissues are expected to increase oxygen concentration and mitochondrial ROS generation and decrease protein turnover [112].

Deoxyribonucleic acid (DNA) nucleotides are common targets for oxidative damage because of their significant mutagenic and oxidative capacity [113]. Guanine is the most prone to oxidation of all nucleic base pairs [114]. When a free hydroxyl group oxidizes guanine, it becomes 8-OHdG, a common form of DNA distortion caused by free radicals [114, 115]. The levels of 8-OHdG in aquatic species have been studied and are thought to be a biomarker of oxidative stress caused by pollution [116]. The significant induction in 8-OHdG level in gills, liver, and muscles of Solea aegyptiaca collected from eastern and southern sectors of Lake Qarun revealed that exposure to heavy metals from the non-treated sewage and agricultural wastewater resulted in significant oxidative damage to DNA in Solea aegyptiaca fish, indicating that the lake water was genotoxic. This finding is confirmed by the study of Sun et al. [14] in zebrafish liver and Jebali et al. [117] in gills of clams, which found an increase in 8-OHdG levels in fish inhabiting ecosystems subjected to anthropogenic disturbances from wastewater effluents. In addition, according to our findings, Alak et al. [118] and Topal et al. [119] reported that the activity of 8-OHdG may be increased in the liver and brain tissues of rainbow trout as a result of toxic chemicals under laboratory conditions. The significantly increased levels of DNA oxidation in Solea aegyptiaca gills, liver, and muscles during winter (spawning period) are in line with the study of Nagasaka et al. [120] observed increased expression of 8-OHdG in ayu brain DNA during the spawning period, implying that DNA damages caused by oxidative stress and ROS had induced during reproduction.

Genotoxicity

Genotoxic agents can impair the DNA integrity, and the extent of DNA strand breaks can be utilized as a sensitive genotoxicity indicator and thus, as a biomarker of exposure. Single-cell gel electrophoresis, or comet assay, is a simple, adaptable, quick, sensitive, and widely used way of assessing DNA damages at the cellular level [121]. In this study, the increased DNA damage in Solea aegyptiaca collected from the eastern sector exposed to the El-Bats drainage channel may be related to the high detected levels of metals and the excessive metal bioaccumulation in fish tissues at this site. Heavy metals have been found to create adducts with DNA via intercalating or covalently interacting with the molecule. These metals generate ROS, inducing oxidative stress and single and double-strand breakage [122]. These results are confirmed by previous studies on Lake Qarun that reported increased DNA damage on Solea Vulgaris and Tilapia Zilli liver [123] and Tilapia Zilli and Mugil cephalus liver, gills, and muscle [124], which was related to the level of heavy metal pollution in the studied sites. The increased DNA damage during Solea aegyptiaca spawning (winter season) could be attributed to an increase in ROS generation during the reproductive cycle [125]. These free radicals can indirectly harm DNA through LPO [126] as MDA, an LPO product, forms adducts with DNA, causing DNA damage [127]. This finding is inconsistent with our results of increasing LPO during the spawning season of Solea aegyptiaca.

Stress proteins

In fish, sub-lethal exposure to heavy metals triggers a number of cellular defence mechanisms. The principal defence against heavy metals is the heavy metal-binding proteins gene expression in impacted cells. Heavy metal stress stimulates the production of several stress proteins, which reduce the harmful effects of heavy metals [128]. These stress proteins, such as HSPs and MTs, function as molecular chaperones [129] and have been proposed as a biomarker, because they are specific and provide a quick inductive signal of heavy metal contamination before the deleterious effects of heavy metals [130].

MT is a cysteine-rich low-molecular-weight cytosolic protein that binds heavy metals [129] and plays a crucial role in regulating metal homeostasis within cells, preventing metal toxicity, and guarding against oxidative damage within cell sequesters these metals, thus acting as a detoxification protein [131]. The detoxication occurs via metal-mediated activation of the gene transcription that expresses MTs, consequently increasing its synthesis and removing metals that bind to them. Considering the absorption of metals by aquatic organisms and the induction of MTs due to the increase in these elements, MTs are significant biomarkers in aquatic environments [132]. This importance is supported by our results of the significant increase in gills, liver, and muscles MT expression in the heavy metal contaminated sectors, which is in agreement with the study of Khodadoust, and Ahmad [133], who suggested that there was a connection between some heavy metal contamination and induction of MT in gill, liver, and muscle of Java medaka fish (Oryzias javanicus). In addition, Carvalho et al. [134] reported that MT levels were substantially induced in the liver and gill of the tilapia from Monjolinho River exposed to metal pollution from industrial and urban waste effluents as compared to their references. Therefore, it can be speculated that the induction of MTs is the most common way of metal detoxification in fish [135] and can be susceptible to a combination of metals (Fe, Cu, Zn, Cd, Pb, Ni), each in low concentration. Although MTs are commonly related to exposure to metals, their values can be affected by both endogenous and exogenous variables such as pH, salinity [136], reproduction, the existence of glucocorticoids, specific stress situations, or cold temperatures [137, 138]. The significant increase in MT levels in gills, liver, and muscles of Solea aegyptiaca fish during the spawning period (winter season) suggests that the seasonality of the reproductive cycle influences MT levels in Solea aegyptiaca. Similarly, Gorbi et al. [16] observed that the levels of hepatic MT revealed a double rise in October when the spawning of Mugil cephalus. Changes in MTs due to reproduction have also been identified as crucial in monitoring programmes for European flounders [139].

In addition to MT, HSP70 has been found to play a protective role in cells exposed to stress [140, 141]. It prevents non-native proteins from aggregating and promotes their refolding and transportation to cellular organelles [142]. The significant increase in HSP70 levels in gills, liver, and muscles of Solea aegyptiaca fish obtained from the heavy metal polluted sites was observed by many investigators who reported increased expression of HSP70 due to metal exposure in different fish organs/species such as Chanos chanos gills, liver and muscle [143], Tanichthys albonubes liver [144], Oreochromis niloticus muscle [145] and Cirrhinus cirrhosis liver [146]. In response to metal pollution stress, heat shock factors (HSFs) that are typically bind HSPs in the cytosol are dissociated from HSPs. Once liberated, HSFs are phosphorylated and form trimers. The trimerized HSF then enters the nucleus and binds to heat shock elements (HSEs) in the promoter region of the HSP70 gene, initiating the expression of HSP70 [147]. As a result, the significant induction of HSP70 in the organs of the Solea aegyptiaca fish verifies stress resistance and appears to be closely linked to metal pollution management through a cytoprotective role.

Contrary to the hypotheses, the present study showed that gills, liver, and muscles HSP70 levels increased significantly in Solea aegyptiaca during winter (spawning period). This finding may be related to the enhanced ROS production during the reproductive cycle [125], which can trigger the HSP induction [148]. In addition, during spawning, feeding activity may diminish or completely cease [149], as confirmed by our previous results of the decrease in growth indices of Solea aegyptiaca during winter, which in turn induced HSP70 expression as reported by Antonopoulou et al. [150] who observed increased HSP70 levels in the 3-week hunger. Furthermore, hormonal processes linked to reproduction may also elicit physiological changes before water temperatures rise to summer levels, leading to HSP70 activation [151]. Similarly, Bildik et al. [140] and Feidantsis et al. [152] illustrated that cold acclimatisation had enhanced HSP70 expression in a variety of fish tissues. Moreover, a direct impact of low temperature on protein stability is likely related to the heat shock response, because cold stress, like heat stress, could destabilize hydrophobic interactions, leading to damaged or misfolded proteins, and seems to stimulate chaperone or regulatory protein mechanisms [153]. Overall, although the stimulation of MT and HSP70 expression did not result in death, it compromised the ability of Solea aegyptiaca gills, liver, and muscles to handle xenobiotics and spawning-related stress through the expression of stress proteins.

The integrated biomarker response index

Several authors have recently proposed adopting approaches that combine numerous biomarker responses into a single value, thereby explaining the data and simplifying large-scale biomarker arrangement in environmental monitoring [154, 155]. Beliaeff–Burgeot’s IBR is a valuable tool for describing the health state of organisms exposed to stressful situations in a simple and comprehensive manner by presenting a graphical overview and an integrated numerical value of the various biomarkers [156]. The present work used a suite of biomarkers including TAC, MDA, PC, 8-OHdG, DNA dam, MT, and HSP-70 in gills, liver, and muscles to calculate IBRv2. Here, IBRv2 revealed that the winter season was more stressful for Solea aegyptiaca (high IBRv2 value), possibly due to stress during spawning. Similar results were recorded by Bodin et al. [157] and Leinio¨ and Lehtonen [158].

In addition, the IBRv2 star plots are consistent with the variations in the pollution levels at each site and the extent of anthropogenic impact in these ecosystems, since the highest value of IBRv2 was detected in eastern and southern sectors of Lake Qarun, exposed to heavy metals from El-Bats and El-Wadi drainage channels at these sites. Indeed, the different forms of the star plots of the examined locations revealed a distinct contamination pattern, supporting the chemical analysis of those sites. This finding demonstrates biomarker integration's effectiveness for environmental assessment as previously reported [155, 159]. Several biomarkers in the current study showed a response triggered or inhibited depending on the investigated location. The spatial arrangement of these biomarkers in the star plot provided a more precise visualisation of which biomarkers were the most sensitive in this kind of evaluation.

Consequently, MDA in gills, PC in the liver, HSP70 in gills and liver, MT in the liver, 8-OHdG in gills, and the comet assay, which measures DNA damage in gills, liver, and muscles were the biomarkers that turned out to be the most effective in this study. Moreover, IBRv2 could distinguish organs of Solea aegyptiaca depending on the responses of biomarkers. The liver was the most affected organ (higher IBRv2 value), followed by the gills, while muscles IBRv2 showed inhibition. This finding may be related to the level of heavy metal accumulation confirmed by the metal pollution index of these organs.

Conclusions

The use of an integrated approach based on fish biomarkers is a precise and efficient technique for assessing Lake Qarun's environmental state. Heavy metals had an impact on the contaminated sites (eastern and southern sectors) in concentrations enough to influence the health of Solea aegyptiaca fish. Moreover, the obtained results suggest that the examined responses are related to seasonality, and the most common finding in the current study was that Solea aegyptiaca showed the most significant fluctuations in the winter when spawning occurs. Therefore, Solea aegyptiaca fish has proven to be an appropriate sentinel species for assessing environmental pollutants using a set of biomarkers. Overall, IBRv2 analysis was able to compare seasons, sites, and organs based on integrating biomarkers responses, demonstrating the efficacy of this biomonitoring method.

Availability of data and materials

The data used and analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

IBRv2:

Integrated biomarker response index version 2

ROS:

Reactive oxygen species

LPO:

Lipid peroxidation

PC:

Protein carbonylation

TAC:

Total antioxidant capacity

HSPs:

Heat shock proteins

MTs:

Metallothioneins

K:

Condition factor

HIS:

Hepatosomatic index

DO:

Dissolved oxygen

BOD:

Biochemical oxygen demand

PBS:

Phosphate buffered saline

ICP:

Inductively coupled plasma emission spectrometer

MPI:

Metal pollution index

TCA:

Trichloroacetic acid

MDA:

Malondialdehyde

DNPH:

Dinitrophenylhydrazone

8-OHdG:

8-Hydroxy-2′deoxyguanosine

SDS:

Sodium dodecyl sulphate

HSP 70:

Heat shock protein 70

HSFs:

Heat shock factors

HSEs:

Heat shock elements

ANOVA:

Analysis of variance

SD:

Standard deviation

P.L.:

Permissible level

NS:

Non-significant

DNA dam:

DNA damage

G:

Gills

L:

Liver

M:

Muscles

DNA:

Deoxyribonucleic acid

References

  1. Ibrahim EA, Zaher SS, Ibrahim WM, Mosad YA (2021) Phytoplankton dynamics in relation to red tide appearance in Qarun Lake. Egypt Egypt J Aquat Res 47(3):293–300. https://doi.org/10.1016/j.ejar.2021.07.005

    Article  Google Scholar 

  2. El-Sayed WM, Mosad YA (2017) Studying of physico-chemical and biological characters of Qarun Lake El-Fayoum-Egypt. Egypt Acad J Biol Sci 9(2):11–20. https://doi.org/10.21608/EAJBSG.2017.16331

    Article  Google Scholar 

  3. Soliman NF, El Zokm GM, Okbah MA (2018) Risk assessment and chemical fractionation of selected elements in surface sediments from Lake Qarun, Egypt using modified BCR technique. Chemosphere 191:262–271. https://doi.org/10.1016/j.chemosphere.2017.10.049

    Article  CAS  Google Scholar 

  4. Al-Afify ADG, Tahoun UM, Abdo MH (2019) Water quality index and microbial assessment of Lake Qarun, El-Batts and El-Wadi Drains, Fayoum province Egypt. Egypt J Aquat Biol Fish 23(1):341–357. https://doi.org/10.21608/EJABF.2019.28270

    Article  Google Scholar 

  5. Mansour SA, Sidky MM (2002) Ecotoxicological studies. 3. Heavy metals contaminating water and fish from Fayoum Governorate Egypt. Food Chem 78(1):15–22. https://doi.org/10.1016/S0308-8146(01)00197-2

    Article  CAS  Google Scholar 

  6. Aytekin T, Kargın D, Çogun HY, Temiz O, Varkal HS, Kargın F (2019) Accumulation and health risk assessment of heavy metals in tissues of the shrimp and fish species from the Yumurtalik coast of Iskenderun Gulf. Turkey Heliyon 5(8):e02131. https://doi.org/10.1016/j.heliyon.2019.e02131

    Article  Google Scholar 

  7. US NRC (1989) Biologic markers in reproductive toxicology. The National Academies Press, DC. https://doi.org/10.17226/774

    Book  Google Scholar 

  8. Hemmadi V (2017) A critical review on integrating multiple fish biomarkers as indicator of heavy metals contamination in aquatic ecosystem. Int J Bioassays 6(9):5494–5506. https://doi.org/10.21746/ijbio.2017.9.5

    Article  CAS  Google Scholar 

  9. Burgos-Aceves MA, Cohen A, Smith Y, Faggio C (2018) MicroRNAs and their role on fish oxidative stress during xenobiotic environmental exposures. Ecotoxicol Environ Saf 148:995–1000. https://doi.org/10.1016/j.ecoenv.2017.12.001

    Article  CAS  Google Scholar 

  10. Gobi N, Vaseeharan B, Rekha R, Sekar Vijayakumar S, Faggio C (2018) Bioaccumulation, cytotoxicity and oxidative stress of the acute exposure selenium in Oreochromis mossambicus. Ecotoxicol Environ Saf 162:147–159. https://doi.org/10.1016/j.ecoenv.2018.06.070

    Article  CAS  Google Scholar 

  11. Saleh YS, Marie MAS (2016) Use of Arius thalassinus fish in a pollution biomonitoring study, applying combined oxidative stress, hematology, biochemical and histopathological biomarkers: a baseline field study. Mar Pollut Bull 106(1–2):308–322. https://doi.org/10.1016/j.marpolbul.2016.03.030

    Article  CAS  Google Scholar 

  12. Copat C, Rizzo M, Zuccaro A, Grasso A, Zuccarello P, Fiore M, Mancini G, Ferrante M (2020) Metals/metalloids and oxidative status markers in saltwater fish from the ionic coast of Sicily. Mediterranean Sea Int J Environ Res 14(240):1–13. https://doi.org/10.1007/s41742-019-00237-1

    Article  CAS  Google Scholar 

  13. Soltani N, Merad I (2016) Risk assessment of cadmium in an edible Mollusk Donax trunculus. In: effect of acute exposure on protein carbonyls. 2nd ICIEM 2016, international conference on integrated environmental management for sustainable development, 27–30, 2016

  14. Sun J, Zhang R, Qin L, Zhu H, Huang Y, Xue Y, An S, Xie X, Li A (2017) Genotoxicity and cytotoxicity reduction of the polluted urban river after ecological restoration: a field-scale study of Jialu River in northern China. Environ Sci Pollut Res 24(7):6715–6723. https://doi.org/10.1007/s11356-016-8352-z

    Article  CAS  Google Scholar 

  15. Santovito G, Trentin E, Gobbi I, Bisaccia P, Tallandini L, Irato P (2020) Non-enzymatic antioxidant responses of Mytilus galloprovincialis under cadmium-induced oxidative stress risk. Preprints. https://doi.org/10.20944/preprints202007.0235.v1

    Article  Google Scholar 

  16. Gorbi S, Baldini C, Regoli F (2005) Seasonal variability of metallothioneins, cytochrome p450, bile metabolites and oxyradical metabolism in the European Eel Anguilla anguilla L. (anguillidae) and striped mullet Mugil cephalus L. (mugilidae). Arch Environ Contam Toxicol 49(1):62–70. https://doi.org/10.1007/s00244-004-0150-9

    Article  CAS  Google Scholar 

  17. Ali D, Almarzoug MHA, Al Ali H, Samdani MS, Hussain SA, Manohrdas S (2020) Fish as bio indicators to determine the effects of pollution in river by using the micronucleus and alkaline single cell gel electrophoresis assay. J King Saud Univ Sci 32(6):2880–2885. https://doi.org/10.1016/j.jksus.2020.07.012

    Article  Google Scholar 

  18. Kayhan FE, Atasayar Z (2010) A biological importance of heat shock proteins (Hsp) in aquatic organisms and thermotolerance stress. J fish Sci 4(3):246–253. https://doi.org/10.3153/jfscom.2010026

    Article  CAS  Google Scholar 

  19. Osman AGM, Wuertz S, Geba KM (2019) Lead induced heat shock protein (HSP70) and metallothionein (MT) gene expression in the embryos of African catfish Clarias gariepinus (Burchell, 1822). Sci Afr 3:1–10. https://doi.org/10.1016/j.sciaf.2019.e00056

    Article  Google Scholar 

  20. Javed M, Nazura U (2019) An overview of the adverse effects of heavy metal contamination on fish health. Proc Natl Acad Sci India Sect B Biol Sci 89(2):389–403. https://doi.org/10.1007/s40011-017-0875-7

    Article  CAS  Google Scholar 

  21. Gabr HR, Ahmed AI, Haraz M (2003) Aquaculture potential of the flatfish Solea vulgaris in Egypt. J Egypt Acad Soc Environ Dev Aquac B 4(2):157–168

    Google Scholar 

  22. Castro-González MI, Méndez-Armenta M (2008) Heavy metals: implications associated to fish consumption. Environ Toxicol Pharmacol 26(3):263–271. https://doi.org/10.1016/j.etap.2008.06.001

    Article  CAS  Google Scholar 

  23. Jardas I (1996) Adriatic Ichthyofauna. School Books, Zagreb, p 536

    Google Scholar 

  24. Fischer W, Schneider M, Bauchot ML (1987) Fiches FAO d’identification des espèces pour les besoins de la pêche. (rev. 1). Méditerranée et Mer Noire. Zone de pêche 37. Volume I. Végétaux et Invertébrés. FAO, Rome, pp 1–760

  25. Silva S, Cravo A, Rodrigues J, Correia C, Almeida CMM (2021) Potential impact of UWWT effluent discharges on Ruditapes decussatus: an approach using biomarkers. Adv Environ Eng Res 2(2):1–19. https://doi.org/10.21926/aeer.2102015

    Article  Google Scholar 

  26. Holmstrup M, Bindesbøl AM, Oostingh GJ, Duschl A, Scheil V, Köhler HR, Loureiro S, Soares AM, Ferreira AL, Kienle C, Gerhardt A (2010) Interactions between efects of environmental chemicals and natural stressors: a review. Sci Total Environ 408:3746–3762. https://doi.org/10.1016/j.scitotenv.2009.10.067

    Article  CAS  Google Scholar 

  27. Aytekin T, Kargın D, Çoğun HY, Temiz Ö, Varkal HS, Kargın F (2019) Accumulation and health risk assessment of heavy metals in tissues of the shrimp and fish species from the Yumurtalik coast of Iskenderun Gulf Turkey. Heliyon 5(8):e02131. https://doi.org/10.1016/j.heliyon.2019.e02131

    Article  Google Scholar 

  28. Elwasify AYH, Ghanem MH, El-Bamby MMM, Ali FAF (2021) Impact of bioaccumulation and biosedimentation of some heavy metals on some biochemical responses in the sole fish, Solea solea inhabiting Lake Qarun Egypt. Egypt J Aquat Biol Fish 25:75–89. https://doi.org/10.21608/EJABF.2021.137091

    Article  Google Scholar 

  29. Fathy SA, Abdel Hamid FF, Shreadah MA, Mohamed LA, El-Gazar MG (2013) Effect of some environmental pollutants on enzymatic and total antioxidant activities in tilapia niloticus. Blue Biotechnol J 1:433–443

    Google Scholar 

  30. Hsu CY, Chiu YC (2009) Ambient temperature influences aging in an annual fish (Nothobranchius rachovii). Aging Cell 8:726–737. https://doi.org/10.1111/j.1474-9726.2009.00525.x

    Article  CAS  Google Scholar 

  31. Li X, Wang C, Li N, Gao Y, Ju Z, Liao G, Xiong D (2021) Combined effects of elevated temperature and crude oil pollution on oxidative stress and apoptosis in sea cucumber (Apostichopus japonicus, Selenka). Int J Environ Res Public Health 18:801. https://doi.org/10.3390/ijerph18020801

    Article  CAS  Google Scholar 

  32. De Andraden VM, Da Silva J, Da Silva FR, Heuser VD, Dias JF, Yoneama ML, De Freitas TR (2004) Fish as bioindicators to assess the effects of pollution in two southern Brazilian rivers using the comet assay and micronucleus test. Environ Mol Mutagen 44:459–468. https://doi.org/10.1002/em.20070

    Article  CAS  Google Scholar 

  33. Kostić J, Kolarević S, Kračun-Kolarević M, Aborgiba M, Gačić Z, Lenhardt M, Vuković Gačić B (2016) Genotoxicity assessment of the Danube River using tissues of fresh water bream (Abramis brama). Environ Sci Pollut Res 23:20783–20795. https://doi.org/10.1007/s11356-016-7213-0

    Article  CAS  Google Scholar 

  34. Kostić J, Kolarević S, Kračun-Kolarević M, Aborgiba M, Gačić Z, Paunović M, Višnjić-Jeftić Ž, Rašković B, Poleksić V, Lenhardt M, Vuković-Gačić B (2017) The impact of multiple stressors on the biomarkers response in gills and liver of freshwater breams during different seasons. Sci Total Environ 601–602:1670–1681. https://doi.org/10.1016/j.scitotenv.2017.05.273

    Article  CAS  Google Scholar 

  35. Carvalho CS, Bernusso VA, de Araújo HSS, Espíndola ELG, Fernandes MN (2012) Biomarker responses as indication of contaminant effects in Oreochromis niloticus. Chemosphere 89:60–69. https://doi.org/10.1016/j.chemosphere.2012.04.013

    Article  CAS  Google Scholar 

  36. Karl I, Sørensen JG, Loeschcke V, Fischer K (2009) HSP70 expression in the Copper butterfly Lycaena tityrus across altitudes and temperatures. J Evol Biol 22:172–178. https://doi.org/10.1111/j.1420-9101.2008.01630.x

    Article  CAS  Google Scholar 

  37. Waagner D, Heckmann L, Malmendal A, Nielsen NC, Holmstrup M, Bayley M (2010) Hsp70 expression and metabolite composition in response to short-term thermal changes in Folsomia candida (Collembola). Comp Biochem Physiol A Mol Integr Physiol 157:177–183. https://doi.org/10.1016/j.cbpa.2010.06.171

    Article  CAS  Google Scholar 

  38. Cravo A, Pereira C, Gomes T, Cardoso C, Serafim A, Almeida C, Rocha T, Lopes B, Company R, Medeiros A, Norberto R, Pereira R, Araújo O, Bebianno MJ (2012) A multibiomarker approach in the clam Ruditapes decussatus to assess the impact of pollution in the Ria Formosa lagoon, South Coast of Portugal. Mar Environ Res 75:23–34. https://doi.org/10.1016/j.marenvres.2011.09.012

    Article  CAS  Google Scholar 

  39. Gohar MEM (2002) Chemical studies on the precipitation and dissolution of some chemical elements in Qaroun Lake. Ph.D. Thesis. Faculty of Science, AL-Azhar University, Cairo, Egypt. p 359. 2002

  40. APHA (1998) Standard methods for the examination of water and wastewater, 20th edn. American Public Health Association, New York

    Google Scholar 

  41. Ghazally KS (1988) The bioaccumulation of Egyptian edible marine animals. Part I Crustaceaus. Bull Natl Inst Ocean Fish 14(2):71–77

    Google Scholar 

  42. APHA (2012) American water works association and water environment federation, standard methods for the examination of water and wastewater, 22nd edn. American public health association, NW

    Google Scholar 

  43. Usero J, Regalado EG, Gracia I (1997) Trace metals in bivalve molluscs Ruditapes decussatus and Ruditapes philippinarum from the Atlantic coast of southern Spain. Environ Int 23:291–298. https://doi.org/10.1016/S0160-4120(97)00030-5

    Article  CAS  Google Scholar 

  44. Schreck CB, Moyle PB (1990) Methods of fish biology. American Fisheries Society, Bethesda

    Book  Google Scholar 

  45. Galaktionova LP, Molchanov AV, El chaninova SA, Varshavskii BI (1998) Lipid peroxidation in patients with gastric and duodenal peptic ulcers. Klin Lab Diagn 6:10–14

    Google Scholar 

  46. Ohkawa H, Ohishi N, Yagi K (1979) Assay for lipid peroxides in animal tissues by thiobarbituric acid reaction. Anal Biochem 95(2):351–358. https://doi.org/10.1016/0003-2697(79)90738-3

    Article  CAS  Google Scholar 

  47. Reznick AZ, Packer L (1994) Oxidative damage to proteins: spectrophotometric method for carbonyl assay. Meth Enzymol 233:357–363. https://doi.org/10.1016/s0076-6879(94)33041-7

    Article  CAS  Google Scholar 

  48. Singh NP, McCoy MT, Tice RR, Schneider EL (1988) A simple technique for quantitation of low levels of DNA damage in individual cells. Exp Cell Res 175(1):184–191. https://doi.org/10.1016/0014-4827(88)90265-0

    Article  CAS  Google Scholar 

  49. Viarengo A, Ponzano E, Dondero F, Fabbri R (1997) A simple spectrophotometric method for metallothionein evaluation in marine organism: an application to Mediterranean and Antarctic molluscs. Mar Environ Res 44(1):69–84. https://doi.org/10.1016/S0141-1136(96)00103-1

    Article  CAS  Google Scholar 

  50. Cataldo J, Hidalgo ME, Neaman A, Gaete OH (2011) Use of molecular biomarkers in Eiseniafoetida to assess copper toxicity in agricultural soils affected by mining activities. J Soil Sci Plant Nutr 11(3):57–70. https://doi.org/10.4067/S0718-95162011000300005

    Article  Google Scholar 

  51. Beliaeff B, Burgeot T (2002) Integrated biomarker response: a useful tool for ecological risk assessment. Environ Toxicol Chem 21(6):1316–1322

    Article  CAS  Google Scholar 

  52. Sanchez W, Burgeot T, Porcher J (2013) A novel “integrated biomarker response” calculation based on reference deviation concept. Environ Sci Pollut Res 20(5):2721–2725. https://doi.org/10.1007/s11356-012-1359-1

    Article  CAS  Google Scholar 

  53. Mahmoud SA, Tayel SI, Yacoub AM (2008) Histopathological changes in kidneys of the fish Tilapia zillii and Clarias gariepinus under the effect of several pollutants along the River Nile. J Egyptian German Soc Zool 56:219–246

    Google Scholar 

  54. Shaaban MT, Ibrahim HAH, Hanafi AAM (2016) Distribution of bacteria in Lake Qarun, AL Fayoum, Egypt (2014–2015) in relation to its physical and hydrochemical characterization. J Biosci Appl Res 9(2):601–615

    Article  Google Scholar 

  55. Abdel-Moniem AM (1991) Changes in phytoplankton composition of Lake Qarun in relation to variation in salinity. M.Sc. Thesis, College of girls, Ain Shams University, Egypt

  56. Vicente-Martorell JJ, Galindo-Riaño MD, García-Vargas M, Granado-Castro MD (2009) Bioavailability of heavy metals monitoring water, sediments and fish species from a polluted estuary. J Hazard Mater 162(2–3):823–836. https://doi.org/10.1016/j.jhazmat.2008.05.106

    Article  CAS  Google Scholar 

  57. Abd Ellah RG (2009) Outlook on past, present and future status of water salinity in Lake Qarun. Egypt J fish mar sci 1(1):51–55

    CAS  Google Scholar 

  58. Mahmoud SA (2002) Evaluation of toxicity effect of some pollutants on histological feature and biochemical composition of Oreochromis niloticus L. living in river Nile (Damietta branch). Ph.D. Thesis, Faculty of Science, Zagazig University, Egypt

  59. Tayel SI, Ibrahim SA, Mahmoud SA (2013) Histopathological and muscle composition studies on Tilapia zillii in relation to water quality of Lake Qarun Egypt. j basic appl sci 9(6):3857–3872

    Google Scholar 

  60. Al-Afify ADG, Othman AA, Ramadan MA (2018) Characterization of chemical and microbiological quality of Nile river surface water at Cairo (Egypt). Rend Fis Acc Lincei 29:725–736. https://doi.org/10.1007/s12210-018-0721-8

    Article  Google Scholar 

  61. Osman AGM, Al-Awadhi RM, Harabawy ASA, Mahmoud UM (2010) Evaluation of the use of protein electrophoresis of the African Catfish (Clarias gariepinus Burchell, 1822) for biomonitoring aquatic pollution. Environ Res 4(3):235–243. https://doi.org/10.3923/erj.2010.235.243

    Article  Google Scholar 

  62. Adeogun AO (2012) Impact of industrial effluent on water quality and gill pathology of Clarias gariepinus from Alaro stream, Ibadan, Southwest. Nigeria Eur J Sci Res 76(1):83–94

    Google Scholar 

  63. Zahran MA, El-Amier YA, Elnaggar AA, Abd El-Azim H, El-Alfy MA (2015) Assessment and distribution of heavy metals pollutants in Manzala Lake Egypt. J Geosci Environ Prot 3(6):107–122. https://doi.org/10.4236/gep.2015.36017

    Article  Google Scholar 

  64. El-Agri AM, Emam MA, Gaber HS, Hassan EA, Hamdy SM (2021) Heavy metal bioaccumulation and related histopathological changes in gills, liver and muscle of Solea aegyptiaca fish inhabiting Lake Qarun Egypt. Egypt J Aquat Biol Fish 25(4):159–183. https://doi.org/10.21608/EJABF.2021.187056

    Article  Google Scholar 

  65. Hussein H, Amer R, Gaballah A, Refaat Y, AbdelWahab A (2008) Pollution monitoring for Lake Qarun. Adv Environ Biol 2(2):70–80

    CAS  Google Scholar 

  66. Ibrahim AA, Omar HM (2013) Seasonal variation of heavy metals accumulation in muscles of the African Catfish Clarias gariepinus and in river Nile water and sediments at Assiut Governorate. Egypt J Biol Earth Sci 3(2):B236–B248

    CAS  Google Scholar 

  67. Mohamed AS, El- Desoky MA, Gad NS (2019) Seasonal variation of Fe, Mn and Cu in the tissues of two fish species from Lake Qarun Egypt. J Heavy Met Toxic Dis 4(1):1–6. https://doi.org/10.21767/2473-6457.10026

    Article  Google Scholar 

  68. Darweesh MM, Gamal El-Dein HM, Abou-Shleel SM, El-Shirbeny MA (2019) Seasonal variation of heavy metals in water and organs of Oreochromis niloticus at Rosetta Branch, River Nile Egypt. Egypt J Aquat Biol Fish 23(3):513–526

    Article  Google Scholar 

  69. Van der Oost R, Beyer J, Vermeulen NPE (2003) Fish bioaccumulation and biomarkers in environmental risk assessment: a review. Environ Toxicol Pharmacol 13(2):57–149. https://doi.org/10.1016/s1382-6689(02)00126-6

    Article  Google Scholar 

  70. Fonseca VF, Vasconcelos RP, Tanner SE, Franca S, Serafim A, Lopes B, Company R, Bebianno MJ, Costa MJ, Cabral HN (2015) Habitat quality of estuarine nursery grounds: Integrating non-biological indicators and multilevel biological responses in Solea senegalensis. Ecol Indic 58:335–345. https://doi.org/10.1016/j.ecolind.2015.05.064

    Article  Google Scholar 

  71. Ahmed AI, Sharaf MM, Laban HA (2010) Reproduction of the Egyptian sole, Solea aegyptiaca (Actinopterygii: Pleuronectiformes: Soleidae), from Port Said, Egypt Mediterranean Sea. Acta Ichthyol Piscat 40(2):161–166. https://doi.org/10.3750/AIP2010.40.2.09

    Article  Google Scholar 

  72. Khalifa F, Hadj Taieb A, Hajji F, Ayadi H, Jarboui O (2019) Reproductive biology of the Egyptian sole, Solea aegyptiaca (Actinopterygii: Pleuronectiformes: Soleidae), in southern Tunisian waters (Central Mediterranean). J Mar Biolog 99(4):975–981. https://doi.org/10.1017/S002531541800098X

    Article  CAS  Google Scholar 

  73. Šantić M, Pallaoro A, Jardas I (2006) Co-variation of gonadosomatic index and parameters of length–weight relationships of Mediterranean horse mackerel, Trachurus mediterraneus (Steindachner, 1868), in the eastern Adriatic Sea. J Appl Ichthyol 22(3):214–217. https://doi.org/10.1111/j.1439-0426.2006.00735.x

    Article  Google Scholar 

  74. Tuapetel F, Nessa N, Ali SA, Sudirman S, Hutubessy G, Mosse JW (2017) Morphometric relationship, growth, and condition factor of flyingfish, Hirundicththys oxycephalus during spawning season. IOP Conf Ser Earth Environ Sci 89(1):012001. https://doi.org/10.1088/1755-1315/89/1/012001

    Article  Google Scholar 

  75. Zaghloul KH, Omar WA, Abdel-Khalek AA, AboHegab S (2011) Ecological monitoring of Mediterranean Solea aegyptiaca transplanted into Lake Qaroun Egypt. Aust J Basic & Appl Sci 5(7):851–862

    CAS  Google Scholar 

  76. Bakhoum SA, El-Bermawi NM, Srour TM, Goda AM, Hebalah MM (2015) Some biological aspects of European seabass Dicentrarchus labrax in Egyptian Mediterranean water and aquaculture Egypt. Mediterr Aquac J 7(1):22–35. https://doi.org/10.21608/MAJ.2015.4630

    Article  Google Scholar 

  77. Engwa GA, Ferdinand PU, Nwalo FN, Unachukwu MN (2019) Mechanism and health effects of heavy metal toxicity in humans, p 1-23. Poisoning in the modern world—new tricks for an old dog? IntechOpen. https://doi.org/10.5772/intechopen.73906

    Article  Google Scholar 

  78. Lee CC, Lin YH, Hou WC, Li MH, Chang JW (2020) Exposure to ZnO/TiO2 nanoparticles affects health outcomes in cosmetics salesclerks. Int J Environ Res Public Health 17(17):6088. https://doi.org/10.3390/ijerph17176088

    Article  CAS  Google Scholar 

  79. Hippeli S, Elstner F (1999) Transition metal ioncatalyzed oxygen activation during pathogenic processes. FEBS Lett 443(1):1–7. https://doi.org/10.1016/S0014-5793(98)01665-2

    Article  CAS  Google Scholar 

  80. Yadav A, Kumari R, Yadav A, Mishra JP, Srivastava S, Prabha S (2016) Antioxidants and its functions in human body—a review. Res Environ Life Sci 9(11):1328–1331

    Google Scholar 

  81. Regoli F, Winston GW (1999) Quantification of total oxidant scavenging capacity TOSC of antioxidants for peroxynitrite, peroxyl radicals and hydroxyl radicals. Toxicol Appl Pharmacol 156(2):96–105. https://doi.org/10.1006/taap.1999.8637

    Article  CAS  Google Scholar 

  82. Benedetti M, Ciaprini F, Piva F, Onorati F, Fattorini D, Notti A, Ausili A, Regoli F (2012) A multidisciplinary weight of evidence approach for classifying polluted sediments: integrating sediment chemistry, bioavailability, biomarkers responses and bioassays. Environ Int 38(1):17–28. https://doi.org/10.1016/j.envint.2011.08.003

    Article  CAS  Google Scholar 

  83. Mehrpak M, Banaee M, Haghi BN, Noori A (2015) Protective effects of vitamin C and chitosan against cadmium-induced oxidative stress in the liver of common carp (Cyprinus carpio). Iran j toxicol 9(30):1360–1367

    CAS  Google Scholar 

  84. Banaee M, Mehrpak M, Haghi BN, Noori A (2015) Amelioration of cadmium-induced changes in biochemical parameters of the muscle of common carp (Cyprinus carpio) by vitamin C and chitosan. Int J Aquat Biol 3(6):362–371

    Google Scholar 

  85. Drąg-Kozak E, Pawlica-Gosiewska D, Gawlik K, Socha M, Gosiewski G, Łuszczek-Trojnar E, Solnica B, Popek W (2019) Cadmium-induced oxidative stress in Prussian carp (Carassius gibelio Bloch) hepatopancreas: ameliorating effect of melatonin. Environ Sci Pollut Res 26(12):12264–12279. https://doi.org/10.1007/s11356-019-04595-3

    Article  CAS  Google Scholar 

  86. da Silva MC, Ferreira MAP, Giarrizzo T, Amado LL, Rocha RM (2020) Evaluation of metal contamination effects in piranhas through biomonitoring and multi biomarkers approach. Heliyon 6(8):e04666. https://doi.org/10.1016/j.heliyon.2020.e04666

    Article  Google Scholar 

  87. Lushchak VI (2011) Environmentally induced oxidative stress in aquatic animals. Aquat Toxicol 101(1):13–30. https://doi.org/10.1016/j.aquatox.2010.10.006

    Article  CAS  Google Scholar 

  88. Nunes B, Caldeira C, Pereira JL, Gonçalves F, Correia AT (2015) Perturbations in ROS-related processes of the fish Gambusia holbrooki after acute and chronic exposures to the metals copper and cadmium. Environ Sci Pollut Res 22(5):3756–3765. https://doi.org/10.1007/s11356-014-3580-6

    Article  CAS  Google Scholar 

  89. Sifi K, Soltani N (2018) Seasonal changes of two biomarkers of oxidative stress (LDH, MDA) in the edible mollusc Donaxtrunculus (Mollusca: Bivalvia) from the Gulf of Annaba (Algeria): correlation with carbohydrate and lipid contents. Molluscan Res 39(1):44–52. https://doi.org/10.1080/13235818.2018.1499389

    Article  Google Scholar 

  90. Grune T, Jung T, Merker K, Davies KJA (2004) Decreased proteolysis caused by protein aggregates, inclusion bodies, plaques, lipofuscin, ceroid, and “aggresomes” during oxidative stress, aging, and disease. Int J Biochem Cell Biol 36(12):2519–2530. https://doi.org/10.1016/j.biocel.2004.04.020

    Article  CAS  Google Scholar 

  91. Mai WJ, Yan JL, Wang L, Zheng Y, Xin Y, Wang WN (2010) Acute acidic exposure induces p53-mediated oxidative stress and DNA damage in tilapia (Oreochromis niloticus) blood cells. Aquat Toxicol 100:271–281. https://doi.org/10.1016/j.aquatox.2010.07.025

    Article  CAS  Google Scholar 

  92. Maqsood S, Benjakul S (2011) Comparative studies on molecular changes and pro-oxidative activity of haemoglobin from different fish species as inuenced by pH. Food Chem 124:875–883. https://doi.org/10.1016/j.foodchem.2010.07.011

    Article  CAS  Google Scholar 

  93. Aride PHR, Roubach R, Val AL (2007) Tolerance response of tambaqui Colossoma macropomum (Cuvier) to water pH. Aquac Res 38:588–594. https://doi.org/10.1111/j.1365-2109.2007.01693.x

    Article  CAS  Google Scholar 

  94. Lemos CHP, Ribeiro CVM, De Oliveira CPB, Couto RD, Copatti CE (2018) Effects of interaction between pH and stocking density on the growth, haematological and biochemical responses of Nile tilapia juveniles. Aquaculture 495:62–67. https://doi.org/10.1016/j.aquaculture.2018.05.037

    Article  CAS  Google Scholar 

  95. Copatti CE, Baldisserotto B, Souza C, Monserrat JM, Garcia L (2019) Water pH and hardness alter ATPases and oxidative stress in the gills and kidney of pacu (Piaractus mesopotamicus). Neotrop Ichthyol 17(4):e190032

    Article  Google Scholar 

  96. Ondei LS, Teresa FB, Garcia DP, Felício AA, da Silva DGH, de Almeida EA (2020) Fish biomarker responses to perturbation by drought in streams. Neotrop Ichthyol 18(2):1–15. https://doi.org/10.1590/1982-0224-2019-0130

    Article  Google Scholar 

  97. Soldatov AA, Gostyukhina OL, Golovina IV (2007) Antioxidant enzyme complex of tissues of the bivalve Mytilus galloprovincialis Lam. under normal and oxidative-stress conditions: a review. Appl Biochem Microbiol 43(5):556–562

    Article  CAS  Google Scholar 

  98. Morozov AA, Chuiko GM, Yurchenko VV (2017) Annual variations in hepatic antioxidant defenses and lipid peroxidation in a temperate fish, common bream Abramis brama (L.). Int Aquat Res 9(3):249–257. https://doi.org/10.1007/S40071-017-0176-Z

    Article  Google Scholar 

  99. Egginton S, Sidell BD (1989) Thermal acclimation induces adaptive changes in subcellular structure of fish skeletal muscle. Am J Physiol Cell Physiol 256(1):R1-9. https://doi.org/10.1152/ajpregu.1989.256.1

    Article  CAS  Google Scholar 

  100. Abele D, Puntarulo S (2004) Formation of reactive species and induction of antioxidant defence systems in polar and temperate marine invertebrates and fish. Comp Biochem Physiol A Mol Integr Physiol 138(4):405–415. https://doi.org/10.1016/j.cbpb.2004.05.013

    Article  CAS  Google Scholar 

  101. Muñoz S, Méndez L, Dasilva G, Torres JL, RamosRomero S, Romeu M, Nogués MR, Medina I (2018) Targeting hepatic protein carbonylation and oxidative stress occurring on diet-induced metabolic diseases through the supplementation with fsh oils. Mar Drugs 16(10):353. https://doi.org/10.3390/md16100353

    Article  CAS  Google Scholar 

  102. Dalle-Donne I, Rossi R, Giustarini D, Milzani A, Colombo R (2003) Protein carbonyl groups as biomarkers of oxidative stress. Clinica Chimica Act 329(1–2):23–38. https://doi.org/10.1016/s0009-8981(03)00003-2

    Article  CAS  Google Scholar 

  103. Wei K, Yang J (2015) Oxidative damage induced by copper and beta-cypermethrin in gill of the freshwater crayfish Procambarus clarkia. Ecotoxicol Environ Saf 113:446–453. https://doi.org/10.1016/j.ecoenv.2014.12.032

    Article  CAS  Google Scholar 

  104. Stadtman ER, Oliver CN (1991) Metal-catalyzed oxidation of proteins. Physiological consequences. J Biol Chem 266(4):2005–2008

    Article  CAS  Google Scholar 

  105. Gopalakrishnan S, Nai Z, Thilagam H, Bei C, Ding J, Wang X, Wang W, Ke C, Giesy J, Zhang X, Ke-Jian Wang K (2011) Biochemical responses and DNA damage in red sea bream from coastal Fujian Province China. Ecotoxicol Environ Saf 74(6):1526–1535. https://doi.org/10.1016/j.ecoenv.2011.05.007

    Article  CAS  Google Scholar 

  106. Fatima M, Usmani N, Firdaus F, Zafeer MF, Ahmad S, Akhtar K, Dawar Husain SM, Ahmad MH, Anis E, Hossain MM (2015) In vivo induction of antioxidant response and oxidative stress associated with genotoxicity and histopathological alteration in two commercial fish species due to heavy metals exposure in northern India (Kali) river. Comp Biochem Physiol C Toxicol Pharmacol 176–177:17–30. https://doi.org/10.1016/j.cbpc.2015.07.004

    Article  CAS  Google Scholar 

  107. Mohanty D, Samanta L (2016) Multivariate analysis of potential biomarkers of oxidative stress in Notopterus notopterus tissues from Mahanadi River as a function of concentration of heavy metals. Chemosphere 155:28–38. https://doi.org/10.1016/j.chemosphere.2016.04.035

    Article  CAS  Google Scholar 

  108. Carney Almroth, B (2008) Oxidative damage in fish used as biomarkers in field and laboratory studies. Ph.D. Thesis, Gothenburg University, Sweden

  109. Husmann G, Abele D, Monien D, Monien P, Kriews M, Philipp EER (2012) The influence of sedimentation on metal accumulation and cellular oxidative stress markers in the Antarctic bivalve Laternula elliptica. Estuar Coast Shelf Sci 111:48–59. https://doi.org/10.1016/j.ecss.2012.06.003

    Article  CAS  Google Scholar 

  110. Shulman GE, Love RM (1999) The biochemical ecology of marine fishes. Academic Press Ltd, Cambridge. eBook ISBN: 978-0-080-57959-7

    Google Scholar 

  111. Di Salvatore P, Calcagno JA, Ortíz N, de Molina MCR, Sabatini SE (2013) Effect of seasonality on oxidative stress responses and metal accumulation in soft tissues of Aulacomya atra, a mussel from the South Atlantic Patagonian coast. Mar Environ Res 92:244–252. https://doi.org/10.1016/j.marenvres.2013.10.004

    Article  CAS  Google Scholar 

  112. Kammer AR, Orczewska JI, O’Brien KM (2011) Oxidative stress is transient and tissue specific during cold acclimation of three spine stickleback. J Exp Biol 214(Pt 8):1248–1256. https://doi.org/10.1242/jeb.053207

    Article  CAS  Google Scholar 

  113. Wilson SM, Gravel MA, Mackie TA, Willmore WG, Cooke SJ (2012) Oxidative stress associated with paternal care in smallmouth bass (Micropterus dolomieu). Comp Biochem Physiol Part A Mol Integr Physiol 162(3):212–218. https://doi.org/10.1016/j.cbpa.2012.02.023

    Article  CAS  Google Scholar 

  114. Wu LL, Chiou CC, Chang PY, Wu JT (2004) Urinary 8-OHdG: a marker of oxidative stress to DNA and a risk factor for cancer, atherosclerosis and diabetics. Clin Chim Acta 339(1–2):1–9. https://doi.org/10.1016/j.cccn.2003.09.010

    Article  CAS  Google Scholar 

  115. Valavanidis A, Vlachogianni T, Fiotakis C (2009) 8- hydroxy-2′ -deoxyguanosine (8-OHdG): a critical biomarker of oxidative stress and carcinogenesis. J Environ Sci Health C Environ Carcinog Ecotoxicol Rev 27:120–139

    Article  CAS  Google Scholar 

  116. Machella N, Regoli F, Cambria A, Santella RM (2004) Application of an immunoperoxidase staining method for detection of 7,8-dihydro-8- oxodeoxyguanosine as a biomarker of chemical-induced oxidative stress in marine organisms. Aquat Toxicol 67(1):23–32. https://doi.org/10.1016/j.aquatox.2003.11.008

    Article  CAS  Google Scholar 

  117. Jebali J, Banni M, de Almeida EA, Boussetta H (2007) Oxidative DNA damage levels and catalase activity in the clam Ruditapes decussatus as pollution biomarkers of Tunisian marine environment. Environ Monit Assess 124(1–3):195–200. https://doi.org/10.1007/s10661-006-9217-6

    Article  CAS  Google Scholar 

  118. Alak G, Yeltekin AÇ, Tas IH, Ucar A, Parlak V, Topal A, Kocaman EM, Atamanalp M (2017) Investigation of 8-OHdG, CYP1A, HSP70 and transcriptional analyses of antioxidant defence system in liver tissues of rainbow trout exposed to eprinomectin. Fish Shellfish Immunol 65:136–144. https://doi.org/10.1016/j.fsi.2017.04.004

    Article  CAS  Google Scholar 

  119. Topal A, Alak G, Ozkaraca M, Yeltekin AÇ, Comaklı S, Acıl G, Kokturk M, Muhammed Atamanalp M (2017) Neurotoxic responses in brain tissues of rainbow trout exposed to imidacloprid pesticide: assessment of 8-hydroxy-2- deoxyguanosine activity, oxidative stress and acetylcholinesterase activity. Chemosphere 175:186–191. https://doi.org/10.1016/j.chemosphere.2017.02.047

    Article  CAS  Google Scholar 

  120. Nagasaka R, Okamoto N, Ushio H (2006) Elevated levels of oxidative DNA damage activate p53 and caspases in brain of ayu with aging. J Appl Ichthyol 22:357–362

    Article  CAS  Google Scholar 

  121. Frenzilli G, Nigroa M, Lyons BP (2009) The comet assay for the evaluation of genotoxic impact in aquatic environments. Mutat Res 681(1):80–92. https://doi.org/10.1016/j.mrrev.2008.03.001

    Article  CAS  Google Scholar 

  122. Ahmad I, Ahmad A, Ahmad M (2016) Binding properties of pendimethalin herbicide to DNA: multispectroscopic and molecular docking approaches. Phys Chem Chem Phys 18:6476–6485. https://doi.org/10.1039/C5CP07351K

    Article  CAS  Google Scholar 

  123. Elgendy MY, Abumourad IK, Ali SEM, Soliman WSE, Ibrahim TBE, Abbas WT (2017) Health status and genotoxic effects of metal pollution in Tilapia zillii and Solea vulgaris from polluted aquatic habitats. Int J Zool Res 13(2):54–63. https://doi.org/10.3923/ijzr.2017.54.63

    Article  CAS  Google Scholar 

  124. Abdel-Khalek AA, Zayed SH, Elsayad SM, Zaghloul HH (2020) Assessment of metal pollution impacts on Tilapia zillii and Mugil cephalus inhabiting Qaroun and Wadi El-Rayan lakes, Egypt, using integrated biomarkers. Environ Sci Pollut Res Int 27(21):26773–26785. https://doi.org/10.1007/s11356-020-09095-3

    Article  CAS  Google Scholar 

  125. Nahrgang J, Camus L, Broms F, Christiansen JS, Hop H (2010) Seasonal baseline levels of physiological and biochemical parameters in polar cod (Boreogadus saida): implications for environmental monitoring. Mar Pollut Bull 60(8):1336–1345. https://doi.org/10.1016/j.marpolbul.2010.03.004

    Article  CAS  Google Scholar 

  126. Nwani CD, Nagpure NS, Kumar R, Kushwahab B, Kumar P, Lakra WS (2011) Mutagenic and genotoxic assessment of atrazine based herbicide to freshwater fish Channa punctatus (Bloch) using micronucleus test and single cell gel electrophoresis. Environ Toxicol Pharmacol 31(2):314–322. https://doi.org/10.1016/j.etap.2010.12.001

    Article  CAS  Google Scholar 

  127. Łuczaj W, Skrzydlewska E (2003) DNA damage caused by lipid peroxidation products. Cell Mol Biol Lett 8(2):391–413

    Google Scholar 

  128. Bauman JW, Liu J, Klaassen CD (1993) Production of metallothioneins and heat shock proteins in response to metals. Toxicol Sci 21(1):15–22. https://doi.org/10.1093/toxsci/21.1.15

    Article  CAS  Google Scholar 

  129. Viarengo A, Lowe D, Bolognesi C, Fabbri E, Koehler A (2007) The use of biomarkers in biomonitoring: a 2-tier approach assessing the level of pollutant-induced stress syndrome in sentinel organisms. Comp Biochem Physiol C Toxicol Pharmacol 146(3):281–300. https://doi.org/10.1016/j.cbpc.2007.04.011

    Article  CAS  Google Scholar 

  130. Currie S, Moyes CD, Tufts BL (2000) The effects of heat shock and acclimation temperature on Hsp70 and Hsp30 mRNA expression in rainbow trout: In vivo and in vitro comparisons. J Fish Biol 56(2):398–408. https://doi.org/10.1006/jfbi.1999.1166

    Article  CAS  Google Scholar 

  131. Mason AZ, Jenkins K (1995) Metal detoxication in aquatic organisms. In: Tessier A, Turner DR (eds) Metal speciation and bioavailability in aquatic systems, 3rd edn. Wiley, Chichester, pp 479–608

    Google Scholar 

  132. Livingstone DR (1993) Biotechnology and pollution monitoring: use of molecular biomarkers in the aquatic environment. J Chem Technol Biotechnol 57:195–211. https://doi.org/10.1002/jctb.280570302

    Article  CAS  Google Scholar 

  133. Khodadoust D, Ahmad I (2014) Metallothionein-like protein levels in java medaka fish (Oryzias javanicus) exposed to different concentrations of cadmium. Walailak J Sci Tech 11(10):883–893

    Google Scholar 

  134. Carvalho CS, Bernusso VA, de Araújo HSS, Espíndola ELG, Fernandes MN (2012) Biomarker responses as indication of contaminant effects in Oreochromis niloticus. Chemosphere 89(1):60–69. https://doi.org/10.1016/j.chemosphere.2012.04.013

    Article  CAS  Google Scholar 

  135. Hamilton SJ, Mehrle PM (1986) Metallothionein in fish: review of its importance in assessing stress from metal contaminants. Trans Am Fish Soc 115:596–609

    Article  CAS  Google Scholar 

  136. Ben-Khedher S, Jebali J, Kamel N, Banni M, Rameh M, Jrad A, Boussetta H (2013) Biochemical effects in crabs (Carcinus maenas) and contamination levels in the Bizerta Lagoon: an integrated approach in biomonitoring of marine complex pollution. Environ Sci Pollut Res 20:2616–2631. https://doi.org/10.1007/s11356-012-1156-x

    Article  CAS  Google Scholar 

  137. Hylland K, Nissen-Lie T, Christensen PG, Sandvik M (1998) Natural modulation of hepatic metallothionein and cytochrome P4501A in flounder Platichthys flesus L. Mar Environ Res 46(1–5):51–55. https://doi.org/10.1016/S0141-1136(97)00059-7

    Article  CAS  Google Scholar 

  138. Langston WJ, Chasman BS, Burt GR, Pope ND, McEvoy J (2002) Metallothionein in liver of eels Anguilla anguilla from the Thames estuary: an indicator of environmental quality? Mar Environ Res 53(3):263–293. https://doi.org/10.1016/S0141-1136(01)00113-1

    Article  CAS  Google Scholar 

  139. Rotchell JM, Clarke KR, Newton LC, Bird DJ (2001) Hepatic metallothionein as biomarker for metal contamination: age effects and seasonal variation in European flounders (Pleuronectes flesus) from the Severn Estuary and Bristol Channel. Mar Environ Res 52(2):151–171

    Article  CAS  Google Scholar 

  140. Bildik A, Asıcı Ekren GS, Akdeniz G, Kıral F (2017) Effect of enviromental temperature on heat shock proteins (HSP30, HSP70, HSP90) and IGF-I mRNA expression in Sparus aurata. Iran J Fish Sci 18(4):1014–1024

    Google Scholar 

  141. Mohanty BP, Mahanty A, Mitra T, Parija SC, Mohanty S (2018) Heat shock proteins in stress in teleosts. In: Asea A, Kaur P (eds) Regulation of heat shock protein responses. Springer, Cham

    Google Scholar 

  142. Peng J, Jones GL, Watson K (2000) Stress proteins as biomarkers of oxidative stress: effects of antioxidant supplements. Free Radic Biol Med 28(11):1598–1606. https://doi.org/10.1016/s0891-5849(00)00276-8

    Article  CAS  Google Scholar 

  143. Rajeshkumar S, Munuswamy N (2011) Impact of metals on histopathology and expression of HSP 70 in different tissues of Milk fish (Chanos chanos) of Kaattuppalli Island, South East Coast India. Chemosphere 83(4):415–421. https://doi.org/10.1016/j.chemosphere.2010.12.086

    Article  CAS  Google Scholar 

  144. Jing J, Liu H, Chen H, Hu S, Xiao K, Ma X (2013) Acute effect of copper and cadmium exposure on the expression of heat shock protein 70 in the Cyprinidae fish Tanichthys albonubes. Chemosphere 91(8):1113–1122. https://doi.org/10.1016/j.chemosphere.2013.01.014

    Article  CAS  Google Scholar 

  145. Muposhi VK, Utete B, Sithole-Niang I, Stanley Mukangenyama S (2015) Active biomonitoring of a subtropical river using glutathione-S-transferase (GST) and heat shock proteins (HSP 70) in Oreochromis niloticus as surrogate biomarkers of metal contamination. Water SA 41(3):425–431. https://doi.org/10.4314/wsa.v41i3.15

    Article  CAS  Google Scholar 

  146. Moniruzzaman M, Midday P, Dhara A, Das D, Ghosal I, Mukherjee D, Chakraborty SB (2017) Change in redox state and heat shock protein expression in an Indian major carp Cirrhinus cirrhosus exposed to zinc and lead. Toxicol Sci 42(6):731–740. https://doi.org/10.2131/jts.42.731

    Article  CAS  Google Scholar 

  147. Zheng Z, Lee JE, Yenari MA (2003) Stroke: molecular mechanisms and potential targets for treatment. Curr Mol Med 3:361–372. https://doi.org/10.2174/1566524033479717

    Article  CAS  Google Scholar 

  148. Gornati R, Papis E, Rimoldi S, Terova G, Saroglia M, Bernardini G (2004) Rearing density influences the expression of stress-related genes in sea bass (Dicentrarchus labrax L.). Gene 341:111–118. https://doi.org/10.1016/j.gene.2004.06.020

    Article  CAS  Google Scholar 

  149. Kadri S, Thorpe JE, Metcalfe NB (1997) Anorexia in one-sea-winter Atlantic salmon (Salmo salar) during summer, associated with sexual maturation. Aquaculture 151(1–4):405–409. https://doi.org/10.1016/S0044-8486(96)01495-0

    Article  Google Scholar 

  150. Antonopoulou E, Kentepozidou E, Feidantsis K, Roufidou C, Despoti S, Chatzifotis S (2013) Starvation and re-feeding affect Hsp expression, MAPK activation and antioxidant enzymes activity of European sea bass (Dicentrarchus labrax). Comp Biochem Physiol A Mol Integr Physiol 165(1):79–88. https://doi.org/10.1016/j.cbpa.2013.02.019

    Article  CAS  Google Scholar 

  151. Fader SC, Yu Z, Spotila JR (1994) Seasonal (hsp70) variation in heat shock proteins in stream fish under natural conditions. J Therm Biol 19(5):335–341. https://doi.org/10.1016/0306-4565(94)90070-1

    Article  CAS  Google Scholar 

  152. Feidantsis K, Antonopoulou E, Lazou A, Portner HO, Michaelidis B (2013) Seasonal variations of cellular stress response of the gilthead sea bream (Sparus aurata). J Comp Physiol B 183(5):625–639. https://doi.org/10.1007/s00360-012-0735-y

    Article  CAS  Google Scholar 

  153. Po¨rtner HO, Peck MA, (2010) Climate change effects on fishes and fisheries: towards a cause-and-effect understanding. J Fish Biol 77(8):1745–1779. https://doi.org/10.1111/j.1095-8649.2010.02783.x

    Article  Google Scholar 

  154. Vieira CED, Costa PG, Lunardelli B, Oliveira LF, Cabrera LC, Risso WE, Primel EG, Meletti PC, Fillmann G, Martinez CBR (2016) Multiple biomarker responses in Prochilodus lineatus subjected to short-term in situ exposure to streams from agricultural areas in Southern Brazil. Sci Total Environ 542:44–56. https://doi.org/10.1016/j.scitotenv.2015.10.071

    Article  CAS  Google Scholar 

  155. Vieira CED, Costa PG, Cabrera LC, Primel EG, Fillmann G, Bianchini A, Martinez CBDR (2017) A comparative approach using biomarkers in feral and caged Neotropical fish: implications for biomonitoring freshwater ecosystems in agricultural areas. Sci Total Environ 586:598–609. https://doi.org/10.1016/j.scitotenv.2017.02.026

    Article  CAS  Google Scholar 

  156. Baudou FG, Ossana NA, Castañé PM, Mastrángelo MM, González Núñez AA, Palacio MJ, Ferrari L (2019) Use of integrated biomarker indexes for assessing the impact of receiving waters on a native Neotropical teleost fish. Sci Total Environ 650(Pt 2):1779–1786. https://doi.org/10.1016/j.scitotenv.2018.09.342

    Article  CAS  Google Scholar 

  157. Bodin N, Burgeot T, Stanisiere JY, Boquene G, Menard D, Minier C, Boutet I, Amat A, Cherel Y, Budzinski H (2004) Seasonal variations of a battery of biomarkers and physiological indices for the mussel Mytilus galloprovincialis transplanted into the northwest Mediterranean Sea. Comp Biochem Physiol C Toxicol Pharmacol 138(4):411–427. https://doi.org/10.1016/j.cca.2004.04.009

    Article  CAS  Google Scholar 

  158. Leinio S, Lehtonen KK (2005) Seasonal variability in biomarkers in the bivalves Mytilus edulis and Macoma balthica from the northern Baltic Sea. Comp Biochem Physiol C Toxicol Pharmacol 140(3–4):408–421. https://doi.org/10.1016/j.cca.2005.04.005

    Article  CAS  Google Scholar 

  159. Rementeria A, Mikolaczyk M, Lanceleur L, Blanc G, Soto M, Schäfer J, Zaldibar B (2016) Assessment of the effects of Cu and Ag in oysters Crassostrea gigas (Thunberg, 1793) using a battery of cell and tissue level biomarkers. Mar Environ Res 122:11–22. https://doi.org/10.1016/j.marenvres.2016.09.002

    Article  CAS  Google Scholar 

  160. WHO (World Health Organization) (1993) Guidelines for drinking water quality. Recommendations, 2nd edn. World Health Organization, Geneva

    Google Scholar 

  161. WHO (World Health Organization) (1993b) Evaluation of certain food additives and contaminates (Forty-first report of joint FAO/WHO export committee on food additives). WHO Technical Report Series No. 837, WHO, Geneva, 1993b

  162. WHO (World Health Organization) (1985) Guidelines for drinking water quality (ii): health criteria and supporting information. WHO, Geneva, p 130

    Google Scholar 

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Funding

Open access funding provided by The Science, Technology & Innovation Funding Authority (STDF) in cooperation with The Egyptian Knowledge Bank (EKB). This research received no external funding.

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Authors and Affiliations

  1. Pollution Department, National Institute of Oceanography and Fisheries, Cairo, Egypt

    Asmaa M. El-Agri & Hanan S. Gaber

  2. Biochemistry Department, Faculty of Science, Ain Shams University, Cairo, Egypt

    Manal A. Emam & Ekrami A. Hassan

  3. Chemistry Department, Faculty of Science, Fayoum University, Cairo, Egypt

    Soha M. Hamdy

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AE contributed to the study design, the sampling and processing of samples, analysis, evaluation and interpretation the data and wrote the manuscript. ME, HG, EH and SH supervised the study, contributed to the study design, the interpretation of the results and support writing the manuscript. All authors read and approved the final manuscript.

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El-Agri, A.M., Emam, M.A., Gaber, H.S. et al. Integrated use of biomarkers to assess the impact of heavy metal pollution on Solea aegyptiaca fish in Lake Qarun. Environ Sci Eur 34, 74 (2022). https://doi.org/10.1186/s12302-022-00656-6

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