Biomarkers of oxidative stress and metal accumulation in marsh frog ...

Environ Sci Pollut Res DOI 10.1007/s11356-016-6194-3

RESEARCH ARTICLE

Biomarkers of oxidative stress and metal accumulation in marsh frog (Pelophylax ridibundus) Slavica S. Borković-Mitić 1 & Marko D. Prokić 1 & Imre I. Krizmanić 2 & Jelena Mutić 3 & Jelena Trifković 3 & Jelena Gavrić 1 & Svetlana G. Despotović 1 & Branka R. Gavrilović 1 & Tijana B. Radovanović 1 & Slađan Z. Pavlović 1 & Zorica S. Saičić 1

Received: 10 November 2015 / Accepted: 27 January 2016 # Springer-Verlag Berlin Heidelberg 2016

Abstract To understand the effect of metals on the marsh frog Pelophylax ridibundus and the possible environmentinduced changes in oxidative stress enzymes, we determined the concentrations of 18 metals: Al, As, Ba, Ca, Cd, Co, Cr, Cu, Fe, Ga, Hg, In, Li, Mn, Ni, Pb, Sr, and Zn, in the tissues (liver, skin, and muscle) and water samples collected from different locations in Serbia. The activities of superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GSH-Px), glutathione reductase (GR), glutathione S-transferase (GST), acetylcholinesterase (AChE), and changes in concentrations of reduced glutathione (GSH) and sulfhydryl groups (SH) were analyzed in the tissues of the sampled frogs. The concentrations of Al, Cd, Co, Cr, Cu, Fe, Ga, Hg, and Ni were highest in the liver, whereas those of Ba, Ca, Li, Mn, Pb, Sr, and Zn were highest in the skin. Hg correlated positively with liver SOD (in frogs from Danube-Tisza-Danube Canal (DTD)), muscle CAT (DTD), and muscle GST Ponjavica River (PO); Pb

Responsible editor: Thomas Hutchinson Electronic supplementary material The online version of this article (doi:10.1007/s11356-016-6194-3) contains supplementary material, which is available to authorized users. * Slavica S. Borković-Mitić [email protected]

1

Department of Physiology, Institute for Biological Research BSiniša Stanković^, University of Belgrade, Bulevar despota Stefana 142, 11060 Belgrade, Serbia

2

Faculty of Biology, Institute of Zoology, University of Belgrade, Studentski trg 16, 11000 Belgrade, Serbia

3

Faculty of Chemistry, University of Belgrade, PO Box 51, 11158 Belgrade, Serbia

demonstrated a strong positive correlation with liver GR in frogs from Mt. Fruška Gora (FG); Cd only exhibited a positive correlation with AChE in the skin of frogs from DTD. In the skin, Zn correlated positively with AChE (DTD), SH groups (PO), and CAT (FG), and negatively with CAT, GST, and SH in the liver of frogs from DTD. Examination of these oxidative stress biomarkers, together with analysis of metal accumulation in the liver and skin of marsh frogs, provides a powerful tool for the assessment of metal pollution.

Keywords Antioxidative system . Biomonitoring . Marsh frogs . Liver . Skin . Muscle . Metals

Abbreviations SOD Superoxide dismutase CAT Catalase GSH-Px Glutathione peroxidase GR Glutathione reductase GST Glutathione S-transferase GSH Glutathione SH Sulfhydryl groups AChE Acetylcholinesterase DTD Danube-Tisza-Danube Canal PO River Ponjavica FG Fruška Gora Mountain NADPH Nicotinamide adenine dinucleotide phosphate GSSG Oxidized glutathione CDNB 1-Chloro-2,4-dinitrobenzene DTNB 5,5′-Dithiobis-(2-nitrobenzoic acid) ICP-OES Inductively coupled plasma atomic emission spectrometry

Environ Sci Pollut Res

Introduction Different anthropogenic influences are responsible for the increased presence of contaminants in aquatic habitats, and continual monitoring for the presence of different pollutants and their impact on living organisms is essential. As a result of the increase in anthropogenic activities, heavy metal pollution of the soil, water, and atmosphere is a growing ecological problem affecting the quality of food and human health. The main polluters of the waterways in Serbia are different industries, including refineries, petrochemical, chemical, and power plants, mines, metallurgical complexes, wood industry, agriculture (pesticides and fertilizers), traffic, urban settlements with unresolved sanitation issues, cities with sewage that flows into rivers, pollutants in the atmosphere, and pollutants present in international waterways. The main concern with heavy metal pollution is their acute toxicity and ability to accumulate in biological systems (Torre et al. 2013; Taiwo et al. 2014), with a number of detrimental effects, including oxidative stress (Farombi et al. 2007). Chemical analysis of water can provide vital data with regard to metal concentrations in the environment but is insufficient for assessing the toxicity of pollutants in target organisms and their effects on the ecosystem (Pereira et al. 2009; Bartoskova et al. 2013; Fazio et al. 2014; Prokić et al. 2015). Metals usually occur in aquatic environments in complex mixtures of pollutants. They can exert complex effects on living organisms that are difficult to anticipate by chemical analysis alone (Orbea et al. 2002; Aliko et al. 2015). The presence of certain metals in the environment is generally caused by human activities, and their accumulation in organisms implies that biological organisms are constantly exposed to them. Metal concentration in tissues provides a good indicator of recent exposure. Only a few studies have examined the effects of heavy metals on the biomarkers of oxidative stress in free-living frogs exposed to metals (Taiwo et al. 2014). It is necessary to understand the mechanisms of metal toxicity in frogs and determine the concentrations of metals that affect the biomarkers of oxidative stress. One of the main defensive mechanisms against toxic compounds involves the antioxidant system, which participates in the detoxification and elimination of toxic substances from the body. Under stress conditions, the activity of the antioxidant defense systems can either be induced or inhibited. Induction of the antioxidant defenses is usually interpreted as the adaptation of an organism to environmental disturbances, whereas inhibition is a reflection of the toxic effect of pollutants that points to cell damage (Cossu et al. 2000). Measuring the activities of antioxidant enzymes serves as an indicator of an organism’s antioxidant status and has been used as a biomarker of oxidative stress. Biomarkers are defined as a change in a biological response, ranging from molecular to cellular and from physiological responses to

behavioral changes, which can be related to the change of the aquatic habitat (Fazio et al. 2013). In general, assessment of antioxidant defense system components in different animal tissues provides non-specific biomarkers of the adverse effects of xenobiotics (Valavanidis et al. 2006; Borković-Mitić et al. 2013; Messina et al. 2014). Amphibian species are more sensitive bioindicators of aquatic contamination than any other aquatic vertebrate because of their permeable skin that easily absorbs substances from the environment. The natural habitat of frogs accumulates a considerable load of toxic heavy metals which are drained from the surrounding environment. Frogs assimilate metals by ingestion of particulate material suspended in water and from food, by ion exchange of dissolved metals across the skin, and by adsorption by tissues and membrane surfaces. Excretion of metals occurs via the feces, urine, and respiratory membranes. The distribution of metals between different tissues depends on the mode of exposure (dietary and/or aqueous exposure) and can serve as an indicator of pollution. Several processes, including uptake, storage, and elimination, are involved during bioaccumulation (Birungi et al. 2007). The object of our study was the marsh frog Pelophylax ridibundus, formerly Rana ridibunda, which is the largest frog native to Europe, belonging to the family of true frogs. The marsh frog is a water-dwelling, usually green-colored frog species. The present study was designed to measure the concentration of metals and to assess the levels of activation of different biomarkers of oxidative stress in the liver, skin, and muscle of marsh frogs collected from different sites in Serbia: the Danube-Tisza-Danube Canal (DTD), the Ponjavica River (PO), and Mt. Fruška Gora (FG). The aim of this study was to determine whether the frog P. ridibundus accumulates metals and how this affects the antioxidant defense system. Our main objectives were to evaluate the degree of metal contamination in this area and to determine whether this species of frog can serve as a bioindicator species of metal fluctuations in water bodies in Serbia.

Materials and methods Sampling site specifications Three sampling stations, the Danube-Tisza-Danube Canal (45°36′11.95″ North and 20°3′7.42″ East), the Ponjavica river (44°44′56.03″ North and 20°44′22.44″East), and lake Popovica (45°11′1.95″ North and 19°49′11.07″ East) on Mt. Fruška Gora, were chosen as sampling locations for this study based on the different levels of anthropogenic activities (Fig. 1). Samples of P. ridibundus frogs and water were collected in spring 2013 along the banks of the water habitats. DTD is a unique hydro-engineering system for flood control and amelioration forestry, and it serves as a water supply.


Fig. 1 Map of the sampling sites: DTD Danube-Tisza-Danube Canal, PO Ponjavica, FG Fruška Gora

The canal courses through the northern part of Serbia, in Vojvodina. Pollution of the Grand Bačka Canal, which drains into the Tisza and the Danube rivers, is considered to be one of the biggest environmental problems in Serbia. Food industries, which have for decades released untreated waste waters into the canal, are concentrated in this area. According to a study of the Norwegian Institute for Water Research NIVA (2006), the Grand Bačka Canal is one of the most polluted watercourses in Europe. PO is a small slow-running flatland river situated in southern Banat. The midstream section, where the frogs were collected, between the villages Omoljica and Banatski Brestovac, is a natural, very slightly perturbed section of the river in which the features of the original ecosystem of a slow-running flatland river have been preserved. To improve water quality, this part of the river was proclaimed a BNature Park^. Ponjavica was selected for sampling because it represents a locality of standing water undergoing eutrophication. The FG range is 80 km long, lying between the Danube and Sava Rivers in the southern part of Srem in Vojvodina. The oldest forests of the FG are under the highest level of protection. Lake Popovica, near the holiday settlement at the Popovica site, is the result of drainage from FG, created to irrigate agricultural land and provide defense from flash flooding. This location was chosen because it is isolated and there are no large polluters in the broader region of the lake.

Physicochemical analysis of water samples The physicochemical parameters of water (temperature, pH, and dissolved oxygen) were measured in situ using mobile analytical equipment (WTW Multi 340i). Water analysis was carried out in triplicate. Animals Animal capture was approved by the Serbian Ministry for Energy, Development and Environmental Protection (Permissions No. 353-01-446/2013-08). All animal procedures complied with the European Directive (2010/63/EU) on the protection of animals used for experimental and other scientific purposes. A total of 30 mature frogs (divided into 10 animals per group) were collected. The average values of the snout-vent length and body mass of the frogs from individual sites were as follows: DTD, 81.15 ± 9.4 mm and 54.50 ± 14.52 g; PO, 72.1 ± 13.76 mm and 37.55 ± 17.68 g; and FG, 71.80 ± 9.81 mm and 43.25 ± 14.28 g. The frogs were caught using sweep nets, transferred to properly aerated cages with ambient water, and transported to the laboratory for dissection. Dissection was performed to obtain the liver, skin, and muscles for analysis. The liver, ventral skin, and hind leg muscles were immediately frozen in liquid nitrogen and stored at −80 °C. Before analysis, the tissues were minced and homogenized in 5 volumes of 25 mmol/L sucrose containing 10 mmol/LTris-HCl, pH 7.5 at 4 °C (Lionetto et al. 2003) with


an IKA-Werk Ultra-Turrax homogenizer (Janke and Kunkel, Staufen, Germany) (Rossi et al. 1983). The homogenates were sonicated for 30 s at 10 kHz on ice to release enzymes (Takada et al. 1982), followed by centrifugation in a Beckman ultracentrifuge at 85,000×g for 90 min at 4 °C. The resulting supernatants were used for further biochemical analyses. Antioxidant enzyme assays The activity of SOD was assayed by the epinephrine method (Misra and Fridovich 1972). One unit of SOD activity was defined as the amount of protein causing 50 % inhibition of the autoxidation of adrenaline at 26 °C, and was expressed as specific activity (U/mg protein). CAT activity was evaluated by the rate of hydrogen peroxide (H2O2) decomposition (Claiborne 1984) and expressed as micromole H2O2/min/mg protein. The activity of GSH-Px was determined by following the oxidation of nicotinamide adenine dinucleotide phosphate (NADPH) which served as a substrate, with t-butyl hydroperoxide (Tamura et al. 1982), and expressed in nanomole NADPH/min/mg protein. The activity of GR was measured using the method of Glatzle et al. (1974). This method is based on the capability of GR to catalyze the reduction of oxidized glutathione (GSSG) to reduced glutathione (GSH), using NADPH as a substrate in a phosphate buffer (pH 7.4). GR activity was expressed as nanomole NADPH/min/mg protein. The activity of GST toward 1-chloro-2,4-dinitrobenzene (CDNB) was determined by the method of Habig et al. (1974) and expressed as nanomole GSH/min/mg protein The method is based on the reaction of CDNB with the SH group of GSH, which is catalyzed by GST contained in the samples. Protein concentrations in the supernatants were determined according to the method of Lowry et al. (1951) using bovine serum albumin as a standard, and expressed in milligram per gram wet mass. The activities of the antioxidant enzymes were measured simultaneously in triplicate for each sample using a Shimadzu UV-160 spectrophotometer with a temperaturecontrolled cuvette holder. All chemicals were obtained from Sigma-Aldrich (St Louis, MO, USA). Non-enzymatic antioxidants profile The concentration of total GSH was determined by the method of Griffith (1980) and expressed in nanomole per gram tissue. The concentrations of SH groups were determined using DTNB according to the Ellman (1959) method and expressed in micromole per gram wet mass. AChE activity was determined according to Ellman et al. (1961). The assay consisted of measuring the reaction of the thiol with of 5,5′dithiobis-(2-nitrobenzoic acid) DTNB. The yellow anion of 5thio-2-nitrobenzoic acid formed in the reaction was detected spectrophotometrically at 412 nm.

Tissue metal analysis Instrumentation The total concentrations of eighteen elements, Al, As, Ba, Ca, Cd, Co, Cr, Cu, Fe, Ga, Hg, In, Li, Mn, Ni, Pb, Sr, and Zn, were quantified in water and in the liver, muscle, and skin of frogs using inductively coupled plasma atomic emission spectrometry (ICP-OES) (Thermo Scientific, UK), model 6500 Duo. The entire system was controlled with iTEVA software. The microwave oven used for the digestion was equipped with rotor holding 10 PTFE cuvettes (Ethos 1, Advanced Microwave Digestion System, Milestone, Italy). All chemicals were of analytical grade and were supplied by Merck (Darmstadt, Germany). A multi-element stock solution (ICP multi-element standard solution IV, Merck) containing 1.000 g/L was used to prepare intermediate multielement standard solutions for ICP-OES measurements. To check the accuracy and precision of the instruments, certified reference material TORT-2 (lobster hepatopancreas reference material for trace metals), NRC Canada, was applied. Sample preparation The samples (muscles, liver and skin) were oven-dried at 105 °C to a constant weight. The samples were transferred to PTFE cuvettes, and 7 mL of 65 % HNO3 and 1 mL of 30 % H2O2 were added. Digestion was performed under the following program: warm-up to 200 °C for 10 min, heating for 15 min. After a cooling down period, the samples were quantitatively transferred to a volumetric flask (25 mL) and diluted with distilled water. Statistical analysis All data were expressed as means ± standard error (SE). The data were normally distributed (Lilliefors test and Kolmogorov-Smirnov test) and the parametric one-way ANOVA test was performed with p < 0.05 as the criterion of significance. Differences between the activities of antioxidant enzymes and concentrations of non-enzymatic components from three different localities were determined using ANOVA. The null hypothesis was rejected if p < 0.05. Statistical analysis was carried out to correlate metal concentrations with the biochemical responses of the frogs. The Pearson correlation was performed between the activities of antioxidant enzymes and the concentrations of non-enzymatic components, GSH and SH groups, and AChE activity, with the total metal concentrations in the tissues. To observe a likely mechanism of metal accumulation in frog body, three principal component analysis (PCA) models were constructed


for three different locations. Statistical analyses were performed with STATISTICA 10.0.

Results and discussion The results of this study reveal widespread pollution and its dependence on the human activity that predominates in the area of testing. Amphibians are physiologically sensitive, ideal as bioindicators, because they are readily available in high numbers; they are easy to work with and are excellent representatives of freshwater environments. Physicochemical parameters and metals in water The physicochemical parameters (water temperature, pH, and dissolved O2), measured at the time of sampling, are shown in Table 1. Water temperature was almost the same at all sites, varying from 18.06 ± 0.09 °C in PO to 20.26 ± 0.03 °C in FG. The concentration of dissolved O 2 ranged from 6.00 ± 0.04 mg/L in PO to 8.41 ± 0.04 mg/L in DTD. Oxygen depletion can result from a number of natural factors, but is most often a concern when it is the consequence of pollution and eutrophication in which plant nutrients enter a river and phytoplankton blooms appear. The low concentration of O2 Table 1 Concentrations of essential physicochemical parameters and metals (mg/L) in water at the sampling localities DTD, PO, and FG. Each water sample was taken at three points in order to determine the mean and standard error (SE). Part of the analysis was performed in situ (water temperature, pH, dissolved oxygen), using mobile analytical equipment

observed in water from PO is the result of several factors, most likely the process of eutrophication detected at this location. Metals cannot be degraded by biological or chemical processes and thus have a tendency to accumulate in the soil and water of the residue. As a result, they can enter the food chain, posing a risk to human and animal health (Castiglione et al. 2009). The concentrations of Co, Hg, In, Ni, and Pb were below the limit of detection in samples from all sites; Cd was below the limit of detection in samples from DTD and FG; Ga was below the limits only in the water samples from PO. The concentrations of As, Cd, Cu, Fe, and Li were highest at PO where Cd was also detected. The concentration of As was considerably increased in PO where it exceeded the allowed concentration in water (5 μg/L) according to TNMN standards (ICPDR 2006). The observed potentially toxic levels of As are mainly the result of the agricultural methods practiced in this area. Pollution from agricultural land has led to accelerated eutrophication of the river Ponjavica and the formation of predominantly algal blossoms that are harmful to aquatic life. Eutrophication is a natural phenomenon that cannot be prevented. However, natural eutrophication not stimulated by human activity is a very slow process and can take several thousands of years before its effects become manifest. This suggests that eutrophication can be slowed down considerably with adequate treatment of wastewater and by controlled use of mineral fertilizers.

Mean ± SE

DTD

PO

FG

Water temperature (°C) pH O2 (mg/L and %) Al As

20.00 ± 0.12 8.82 ± 0.02 8.41 ± 0.04 234.27 ± 1.65 2.21 ± 0.82

18.06 ± 0.09 9.05 ± 0.02 6.00 ± 0.04 228.62 ± 0.06 24.66 ± 0.26

20.26 ± 0.03 8.42 ± 0.01 7.83 ± 0.02 271.75 ± 0.07 3.22 ± 0.60

Ba Ca Cd Co Cr Cu Fe Ga Hg In Li Mn

57.31 ± 0.09 27866.00 ± 103.90 nd nd nd 10.92 ± 0.27 125.79 ± 4.30 0.225 ± 0.01 nd nd 5.91 ± 0.04 60.29 ± 0.30

51.50 ± 0.43 26570.00 ± 101.60 0.01 ± 0.001 nd nd 12.16 ± 0.33 256.02 ± 1.33 nd nd nd 19.95 ± 0.07 95.98 ± 0.31

37.38 ± 0.30 32681.00 ± 100.2 nd nd nd 9.39 ± 0.20 227.52 ± 1.60 1.52 ± 0.02 nd nd 1.90 ± 0.01 120.50 ± 0.40

Ni Pb Sr Zn

nd nd 371.02 ± 1.50 19.57 ± 0.06

nd nd 330.65 ± 1.30 16.03 ± 0.05

nd nd 228.04 ± 0.90 16.07 ± 0.03

nd not detected (below limit detection: Cd (