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Article

Oxidative Stress Biomarkers in Carassius gibelio from Lakes of Varying Ecological Quality

by
Dimitra Petrocheilou
1,2,
Olga Petriki
1,
Martha Kaloyianni
2 and
Dimitra C. Bobori
1,*
1
Laboratory of Ichthyology, Department of Zoology, School of Biology, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
2
Laboratory of Animal Physiology, Department of Zoology, School of Biology, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
*
Author to whom correspondence should be addressed.
Hydrobiology 2026, 5(1), 4; https://doi.org/10.3390/hydrobiology5010004
Submission received: 17 December 2025 / Revised: 5 January 2026 / Accepted: 12 January 2026 / Published: 14 January 2026
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Abstract

The Water Framework Directive 2000/60/EC requires the assessment of the ecological quality in all surface waters using biological indices, yet the effective application of these indices often demands extensive and long-term monitoring data. Oxidative stress biomarkers offer a promising complementary approach, as they can detect early biochemical responses of organisms to environmental degradation. In this study, we evaluated the suitability of two oxidative stress biomarkers—malondialdehyde (MDA) levels and DNA damage—in the gonads of a freshwater fish species, the Prussian carp Carassius gibelio (Bloch, 1782) as indicators of ecological condition in lakes of differing environmental quality. Fish were sampled from four lakes (Doirani, Vegoritida, Volvi, Petron; Northern Greece) representing a gradient of physicochemical and ecological quality. Both MDA concentrations and DNA damage showed significant (p < 0.05) differences among lakes. However, only DNA damage in the gonads was significantly (p < 0.05) associated with lake ecological quality as determined by the Greek Lake Fish Index (GLFI), with higher biomarker responses observed in lakes of poorer status. These findings demonstrate that oxidative stress biomarkers in C. gibelio reflect variations in lake ecological quality and may serve as sensitive, early-warning tools for biomonitoring and pollution assessment in freshwater ecosystems.

1. Introduction

The world’s aquatic ecosystems are increasingly threatened by human activities [1,2], which alter their physical and chemical conditions [3] and exacerbate pollution processes. Aquatic organisms inhabiting these ecosystems are consequently exposed to environmental changes that may adversely affect their physiology [4] and survival. Among these organisms, fish are particularly responsive to environmental conditions and are widely regarded as reliable indicators of aquatic ecosystem degradation [5]. Accordingly, fish play a crucial role in ecotoxicological studies and biomonitoring surveys [4,6,7] and are commonly used as sentinel organisms across multiple levels of biological organization, ranging from community-level to cellular-level approaches [6].
At the cellular level, pollutants can disrupt homeostasis in fish [4,8,9]. A primary mechanism underlying this disruption is the induction of oxidative stress in fish tissues, resulting from the excessive production of reactive oxygen species (ROS) [9,10]. Elevated ROS levels can trigger lipid peroxidation and lead to significant DNA damage [10]. In this context, the assessment of oxidative stress-related biomarker responses in bioindicator species has been widely recommended. Biomarkers are measurable indicators of biological responses to environmental changes and provide valuable insights into the effects of pollutants on living organisms [11,12].
Although biomarkers can serve as crucial tools in environmental assessment, the established approach adopted within the European Union is the implementation of the European Water Framework Directive 2000/60/EC (WFD) [13]. WFD has promoted the biomonitoring of surface waters (inland, transitional, coastal) across Europe and requires all EU Member States to achieve at least good ecological status or potential for their surface water bodies by the year 2027. The assessment of ecological status is based on the condition of biological quality elements (BQEs), such as phytoplankton, aquatic macrophytes, phytobenthos, benthic macroinvertebrates and fish. Specifically, in accordance with WFD requirements, the ecological status of surface water bodies should be evaluated using biological indices that rely on well-defined pressure–response relationships. Moreover, these indices assess ecological quality as a deviation from reference conditions, defined as the absence of significant human disturbance, and express results on a five-class color-coded scale ranging from 0 (bad quality) to 1 (high quality).
Following this concept, the use of biomarkers could support the implementation of the WFD, as they may function as early warning systems for environmental degradation [14]. The Prussian carp Carassius gibelio (Bloch, 1782), a widely distributed freshwater fish [15], has been successfully used in ecotoxicological studies and has been proposed as a reliable bioindicator organism [4,16,17,18]. Consequently, the assessment of biomarker responses in such a widespread species could provide valuable insights into ecosystem health, particularly when focusing on specific tissues that play crucial role in species population persistence. Gonads, the reproductive organs of fish, are lipid-rich tissues that are highly responsive to pollution [19]; however, they remain relatively underutilized as target tissues in ecotoxicological research. To date, only a limited number of studies have investigated oxidative stress biomarkers in fish gonads [20,21,22,23].
The present study aimed to investigate the responses of sensitive biochemical and genotoxic biomarkers related to oxidative stress—Malondialdehyde (MDA) levels and DNA damage—in the gonads of C. gibelio, a successful invasive species in Greek lakes [24]. In detail, we focused on assessing and comparing the ecotoxicological responses of fish gonads in relation to the physicochemical characteristics and ecological quality of four studied lakes, testing the hypothesis that differences in lake ecological quality would be reflected in variations in biomarker responses. To our knowledge, this is the first study to examine oxidative stress biomarkers in the gonads of C. gibelio in Greek lakes, and also the first attempt to correlate biochemical and genotoxic biomarkers with environmental variables and further to lakes ecological quality. Establishing such a relationship between water quality and the two biomarkers—MDA and DNA damage—is essential to determine whether these biochemical indicators reliably reflect ecological conditions.

2. Materials and Methods

2.1. Study Area

The study included four natural lakes located in Northern Greece, namely Doirani, Vegoritida, Volvi, Petron (Figure 1). Among them, Lake Doirani is transboundary and shared with the Republic of North Macedonia. The studied lakes vary in their limnological and physicochemical characteristics (Table 1), as well as their ecological quality classification based on different national ecological quality indices (Table 2).

2.2. Fish Species Selection and Sample Procedure

A total of 32 adult female C. gibelio individuals (n = 8 from each lake) were provided by local professional fishermen in January 2023. The species was selected based on its abundance and frequent occurrence in commercial catches of the selected lakes, as well as its previous use in ecotoxicological studies [4]. C. gibelio is common in shallow eutrophic lakes and is sold in local markets for human consumption, with some quantities exported to EU countries [33]. Specimens were immediately placed on dry-ice and transferred to the laboratory within the shortest possible timeframe (less than 3 h) where they were measured for total length (to the nearest 1 mm) and weighed (to the nearest 0.1 g). Then dissected for gonad tissue collection. Samples were stored at −80 °C until further analyses. Fish treatment was conducted in accordance with local guidelines for the care of animals [34].

2.3. Biochemical and Genotoxic Indicators

2.3.1. Lipid Peroxidation Quantification, MDA Levels Measurement

Gonad samples were analyzed following the method described by [35]. This experimental procedure is based on the formation of lipid peroxyl radicals and hydroperoxides as the result of the reaction of free radicals or non-radical species with polyunsaturated fatty acids (PUFAs). To maintain biochemical accuracy, results are expressed as Thiobarbituric Acid Reactive Substances (TBARSs) in nmol MDA equivalents per mg protein. This is since one of the terminal products of lipid peroxidation is MDA, a reactive aldehyde, which forms an adduct with two thiobarbituric acid molecules producing a pink-colored compound (TBARS). While a TBARS assay is a widely accepted proxy for lipid peroxidation in environmental studies, it is noted that the assay may also react with other aldehydes and secondary oxidation products. However, as 99% of TBARSs are MDA [36], TBARS levels are calculated as the molar extinction coefficient of ΜDA. The TBARS concentration was detected spectrophotometrically at 535 nm as the absorbance is proportional to MDA concentration (ε 1.5 × 105 L/mol cm) [37]. The quantification of the total protein concentration was conducted using bovine serum albumin as a standard solution according to the Bradford method [38]. The procedure followed was described in detail in [39].

2.3.2. Alkaline Single-Cell Gel Electrophoresis (Comet Assay)

Gonad samples were analyzed using the alkaline comet assay following the protocol of [40], with modifications. Detailed descriptions of the procedure are provided in [39,40]. In brief, gonad cells were treated with 0.01% collagenase (type CLS IV, 175 U/mg) in calcium-magnesium-free saline buffer, embedded in 1% low-melting point agarose in PS (physiological saline) solution, underwent cell lysis (pH = 10, 1 h, 4 °C, in dark), unwinding (20 min, 4 °C, in dark) and electrophoresis (15 min, 25 V, 300 mA, 4 °C, in dark) under alkaline conditions (pH > 12), and also neutralization (pH = 7.5, 5 min, 4 °C in dark). Finally, after ethidium bromide staining (20 μg/mL), the presence of comets was examined under an inverted fluorescence microscope (Olympus CKX41). Four slides per sample were measured as technical replicates. One hundred cells were randomly selected and scored from each slide using the software Tritek CometScoreTM 2.0 (Tritek Corporation, Wilmington, DE, USA). The findings are expressed as a percentage of DNA in the tail (%DNA in tail) (Figure 2). %DNA in tail and Olive moment in positive control data (1 μM H2O2) were 28.3 ± 5.2 and 40 ± 6.3, respectively.

2.4. Data Acquire and Statistical Analysis

Morphometric data for the studied lakes were obtained from [25,26]. The lakes’ physicochemical characteristics were derived from [27] and correspond to the years 2020–2022, a period reflecting the presence of the sampled fish individuals in the lakes.
All data were first explored for normality using the Shapiro–Wilk test and for homogeneity of variances using Levene’s test. As most of the biomarker, total length, and weight data deviated from normality, non-parametric statistical tests were applied throughout the study. Thus, the independent Kruskal–Wallis tests were performed to test whether fish total length, weight and biomarker values differed significantly across lakes (p < 0.05). When significant differences were detected, pairwise comparisons were contacted using Mann–Whitney U tests with Bonferroni correction to identify specific differences between lakes for each biomarker (p < 0.05). Relationships of biomarker responses with environmental variables were assessed using the non-parametric Spearman’s rank correlation. Moreover, to examine the association between biomarker responses and lake ecological quality, fish biomarker values were regressed against the corresponding lake EQR values, as estimated using various ecological indices. All statistical analyses were conducted using IBM SPSS ver. 29 (SPSS, Inc. Chicago, IL, USA) with significance level set at p < 0.05. Graphs were generated using RStudio (Rstudio, ver. 2025.05.0+496, PBC, Boston, MA, USA).

3. Results

3.1. Fish Morphometrics

Fish mean total length (TL ± standard error) was 341 ± 5.7 mm for specimens from Lake Doirani, 281 ± 22.6 mm for specimens from Lake Petron, 340 ± 6.8 mm for specimens from Lake Vegoritida, 307 ± 17 mm for specimens from lake Volvi. Accordingly, fish weight averaged 765 ± 66.9 g for specimens from Lake Doirani, 399 ± 132.8 g for Lake Petron, 858 ± 41.3 g for Lake Vegoritida and 562 ± 118.9 g for Lake Volvi. The distribution of fish total lengths and weights (Figure 2) did not differ significantly among lakes (Kruskal–Wallis, p > 0.05). These measurements indicate that the sampled individuals were predominantly 2–3 years old [41]. This age class corresponds to the period 2020–2022, reflecting the time during which the sampled fish were present in the lakes and, therefore, their period of exposure to environmental stressors.

3.2. Oxidative Stress Biomarkers

MDA values differed significantly across lakes (Kruskal–Wallis test, p < 0.01; Table 3, Figure 3). Mean MDA values were higher in the gonads of fish collected from Lake Petron compared to those from the other studied lakes (Table 3). More specifically, mean MDA values were significantly higher (approximately sixfold) in fish from Lake Petron than in specimens from Lake Doirani (Mann–Whitney, p < 0.01) where the lowest mean MDA value was observed, as well as those from Lake Vegoritida (Mann–Whitney test, p < 0.01).
Mean DNA damage values also differed significantly among lakes (Kruskal–Wallis test, p < 0.01), following the same pattern observed for MDA. Gonads of fish collected from Lake Petron exhibited a higher degree of DNA fragmentation compared to those from the other studied lakes (Table 3, Figure 3). Specifically, mean DNA damage values were 1.3-fold higher in fish from Lake Petron than in those from Lake Doirani (Mann–Whitney test, p < 0.01). In addition, mean DNA damage values in samples from Lake Volvi were significantly higher than those from Lake Doirani (Mann–Whitney test, p < 0.05), while specimens from Lake Vegoritida and Lake Volvi exhibited mean DNA damage values that were 1.1- and 1.2-fold higher, respectively, compared to samples from Lake Doirani.
Overall, both biomarkers followed a consistent trend, with gonadal samples from Lake Petron exhibiting the highest biomarker values, whereas those from Lake Doirani showed the lowest.

3.3. Biomarker–Environmental Parameter Relationships

MDA and DNA damage values showed no significant correlation (p > 0.05) with the examined morphological and environmental lake parameters (Table 4). However, a significant interrelationship (p < 0.01) was observed between MDA levels and DNA damage (Table 4).

3.4. Biomarker–Ecological Quality Relationships

Biomarker values were regressed against lake water ecological quality, as assessed by various biological indices (Table 2). MDA values did not show significant relationships with any of the tested ecological quality indices. In contrast, mean %DNA in tail exhibited a significant negative association only with the fish-based ecological quality index (GLFI; R2 = 0.915, p < 0.05). Specifically, DNA damage increased as GLFI values decreased (Figure 4). Overall, genotoxic biomarkers appeared to be more sensitive to variations in lake ecological quality than lipid peroxidation. This negative correlation is more obvious in Figure 5 where the mean values of the DNA damage are presented in relation to GLFI values of the lakes.

4. Discussion

There is a growing body of research employing biochemical and molecular biomarkers in fish as effective tools for environmental biomonitoring of aquatic ecosystems [4,17,42,43]. Among these, MDA and DNA damage, have been selected in this study due to their sensitivity, ecological relevance, and wide use in ecotoxicological assessments. MDA is a well-established indicator of lipid peroxidation, reflecting oxidative damage to cell membranes, whereas DNA damage provides a measure of genotoxic stress that can directly impact reproductive health and population fitness. While both biomarkers respond to environmental stressors, DNA damage appears to be more sensitive to long-term ecological conditions. This is because genotoxic indicators integrate cumulative cellular damage over time, reflecting chronic exposure to pollutants, whereas lipid peroxidation represents more transient oxidative responses that can fluctuate with short-term environmental changes, such as temperature, food availability, or acute pollution events. These biomarkers respond rapidly to a variety of environmental stressors, allowing early detection of ecosystem degradation. Compared to other biochemical or enzymatic markers, MDA and DNA damage integrate both oxidative and genotoxic effects, making them particularly suitable for assessing ecological quality across aquatic systems with varying anthropogenic pressures [4,44,45].
Most ecotoxicological studies investigating oxidative stress and genotoxicity in fish have focused on tissues such as gills, liver, spleen, heart, and muscle [46,47,48], whereas fish gonads have been used comparatively rarely [49]. In this study, gonads were selected due to their high content of polyunsaturated fatty acids (PUFAs), which renders them particularly susceptible to oxidative damage and pollutant-induced stress [21,22,50,51,52], making thus gonads sensitive indicators of environmental stress. Additionally, gonadal oxidative stress directly reflects potential impacts on reproductive health, which is ecologically relevant for population-level assessments. It is important to note that C. gibelio populations are often dominated by females due to gynogenetic reproduction, and males are rare [15,24]. The individuals sampled in this study were females, minimizing sex-related variability in biomarker responses.
Elevated lipid peroxidation and DNA damage in fish gonads have been consistently reported in contaminated environments [53,54,55]. MDA, in particular, has been proposed as a reliable biomarker against heavy metal contamination in the gonads of Oreochromis niloticus [22]. Kaptaner [20] reported an increase in lipid peroxidation and histological lesions in the gonads of Alburnus tarichi from impacted lakes, followed by reduction in gonadosomatic index. Moreover, [51] linked histological abnormalities to increased oxidative stress responses, suggesting that water pollution in lake waters may affect the reproductive health of fish. In addition, [21], observed oxidative stress-related increases in TBARSs in testes of Clarias gariepinus from contaminated areas of a riverine system. Also, [23] reported a significant decline in antioxidant enzyme activity in the ovaries of Clarias gariepinus from polluted areas. To better understand the biological mechanisms underlying our field observations, it is useful to consider laboratory-based in vitro studies. These experiments allow controlled exposure of fish tissues to specific pollutants, demonstrating direct causal links between contaminants and biomarker responses, which are often difficult to establish in complex natural environments [56,57,58,59,60]. By comparing our field results with findings from in vitro studies, we can more confidently interpret the elevated MDA and DNA damage observed in fish from impacted lakes as responses to environmental stressors rather than natural variability or confounding factors. Thus, in vitro studies provide mechanistic support that complements and strengthens the ecological relevance of field-based biomonitoring.
With respect to genotoxicity, both field and laboratory studies have demonstrated that environmental contaminants can induce DNA damage in fish gonads [54,61,62,63]. Santos et al. [50] demonstrated a link between sperm DNA integrity and reproductive impairment in Gasterosteus aculeatus. In general, genotoxicity is suggested to disrupt reproductive processes through mechanisms such as gamete loss via cell death, increased embryonic mortality, and harmful heritable mutations, all of which can affect recruitment rates and population dynamics [50,64]. In parallel, high oxidative stress in gonads may be indicative of impaired reproductive capacity [65]. According to [66], DNA damage in the sperm cells of Salmo trutta and Salvelinus alpinus is associated with decreased reproductive rates. Additionally, environmental contaminants have been shown to reduce the motility and fertilization ability of fish spermatozoa that result in a high level of infertility [52,67]. In line with this notion, it is plausible to speculate that the lower biomarker values observed in fish gonads from Lake Doirani may indicate reduced oxidative stress and, consequently, a higher potential for reproductive health compared to fish from the other studied lakes. In contrast, the elevated MDA and DNA damage values observed in the gonads of fish from lake Petron—a shallower and more eutrophic lake—may suggest impaired reproductive performance, as pollutant-induced alterations and lesions in gonadal tissue can lead to reduced fertility [52]. However, since we did not directly assess egg quality, fecundity, or hatching success, any inference regarding potential effects on reproductive health remains speculative. Future studies should directly evaluate the condition of eggs, fertilization rates, and offspring survival to confirm whether oxidative and genotoxic stress in gonads translates into measurable impacts on reproductive performance and population-level outcomes.
Our results revealed clear differences in biomarker values among the studied lakes. Specifically, fish from Lake Doirani exhibited the lowest mean levels of both MDA and DNA damage, suggesting comparatively lower oxidative and genotoxic stress in this system. In contrast, fish collected from Lake Petron showed markedly elevated levels of both biomarkers, indicating increased oxidative stress in gonadal tissue, as reflected by enhanced lipid peroxidation and DNA fragmentation. These findings are consistent with the trophic status of the lakes: Lake Petron is characterized by higher concentrations of total phosphorus and total suspended solids, as well as lower Secchi disc depth, indicative of greater eutrophication pressure. Furthermore, Lake Petron is classified as having moderate ecological quality based on the Greek Lake Fish Index (GLFI), exhibiting the lowest ecological quality ratio (EQR) among the studied lakes. The GLFI is an ecological quality index designed to reflect the response of lake fish communities to eutrophication, particularly total phosphorus levels, by incorporating metrics such as the relative contribution of omnivorous fish species to total catch [28]. Although no direct relationships were detected between the studied biomarkers and specific environmental parameters, higher GLFI values were generally associated with lower MDA levels and reduced DNA damage. This pattern supports a negative relationship between oxidative/genotoxic stress in fish gonads and ecological quality. Conversely, the low biomarker values observed in Lake Doirani are in agreement with its classification as having high ecological quality according to GLFI, suggesting that the biomarkers’ responses measured here reflect differences in lake ecological condition.
In general, environmental and anthropogenic pressures appear to play an important role in shaping oxidative stress responses in fish tissues. Previous studies have shown that eutrophication can elevate oxidative stress while suppressing antioxidant defenses [68]. Furthermore, the presence of high chlorophyll levels in lake systems correlates with increased lipid peroxidation values, as observed in the gills of Liza aurata [69]. Specifically, MDA values were also increased in the liver of Cyprinus carpio and Hypophthalmichthys nobilis from eutrophic lakes affected by cyanobacterial blooms [70,71]. In addition to eutrophication, elevated levels of BOD5 and TSS have been associated with increased oxidative stress levels in fish tissues [72,73]. Moreover, low dissolved oxygen levels and highwater turbidity contribute to elevated lipid peroxidation and DNA damage in fish from rivers under anthropogenic pressures [74,75]. According to [76], increased lipid peroxidation and DNA damage in the sperm cells of Colossoma macropomum, due to elevated water temperature, high pH, and hypoxia, may adversely affect reproduction and reduce sperm quality. These observations support the interpretation that the biomarker patterns observed in the present study may be related to differences in water quality and trophic status among the lakes.
Overall, our research enhances the comprehension of the correlation between biomarkers associated with oxidative stress and lake water ecological quality, as assessed by a fish-based index. While community-level biological metrics remain central to ecological status assessment under the WFD, the present findings suggest that MDA levels and DNA damage in fish gonads may provide complementary, early-warning signals of ecosystem disturbance. Following this concept, community metrics and ecotoxicological approaches seem to be complementary [77,78], reinforcing the need to use combined approaches of different disciplines to achieve the best and early evaluation of the ecosystem health and ecological water quality. We acknowledge that the sample size in this study was limited due to the need to select individuals of similar size and age. However, sampling had minimal impact on fish populations, as only a small number of individuals were collected from each lake. It should also be noted that the present study was conducted only in one period, in January 2023, during the winter season, when baseline oxidative stress levels are generally lower compared to periods of higher physiological or environmental stress, such as the spawning season or summer heat, limiting thus the assessment of interannual variability in biomarker responses. Despite these constraints, significant differences in biomarker responses among lakes indicate the robustness of our findings. Future studies with larger sample sizes, both sexes where possible, multi-year sampling and larger spatial coverage will help to confirm the consistency and robustness of these oxidative stress biomarkers across broader spatial and temporal scales and support their potential incorporation into harmonized ecological assessment and classification schemes for lake water quality assessment.

5. Conclusions

The current study suggests that measuring MDA and DNA damage values in fish gonads may reveal variations in environmental conditions and differences in ecological quality across different lakes. Notably, significant correlations were observed between DNA damage and the lake ecological quality assessed by the Greek Lake Fish Index (GLFI). Higher levels of oxidative stress biomarkers were associated with lower ecological quality, indicating that these biomarkers could be useful as early indicators of water quality. Importantly, this study suggests a reliable and fast way to check lake health, even when traditional water quality parameters such as pH or dissolved oxygen, do not show clear problems. However, additional research is needed to confirm these results and to assess the broader applicability of biomarkers in evaluating ecological quality and biomonitoring in freshwater ecosystems.

Author Contributions

Conceptualization, D.C.B. and M.K.; methodology, D.P.; investigation, D.P.; data curation, D.P. and O.P.; writing—original draft preparation, D.P. and O.P.; writing—review and editing, D.C.B. and M.K.; visualization, D.P. and O.P.; supervision, D.C.B. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Fish treatment was conducted in accordance with local guidelines for the care of animals, complying with the Official Journal of the Greek Government No. 106/30 April 2013 on the protection of animals used for scientific purposes.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in this study are included in the article material. Further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

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Hydrobiology 05 00004 g001
Figure 1. Map of the studied lakes.
Figure 1. Map of the studied lakes.
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Figure 2. Box plots of (a) total length (TL, mm) and (b) weights (W, g) of Carassius gibelio from lakes Doirani, Petron, Vegoritida and Volvi. The lower and upper boundaries of the boxes represent the 25th and 75th percentiles, respectively. The lines (whiskers) indicate the maximum and minimum values of the measurements. The interior line of the box represents the median, while the cross (×) indicates the mean and the circles the outlier values. In all cases n = 8.
Figure 2. Box plots of (a) total length (TL, mm) and (b) weights (W, g) of Carassius gibelio from lakes Doirani, Petron, Vegoritida and Volvi. The lower and upper boundaries of the boxes represent the 25th and 75th percentiles, respectively. The lines (whiskers) indicate the maximum and minimum values of the measurements. The interior line of the box represents the median, while the cross (×) indicates the mean and the circles the outlier values. In all cases n = 8.
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Figure 3. Boxplots of (a) MDA levels and (b) %DNA in tail estimated in the gonads of Carassius gibelio in lakes Doirani (DOI), Petron (PETR), Vegoritida (VEG) and Volvi (VOL). The lower and upper boundaries of the boxes represent the 25th and 75th percentiles, respectively. The lines (whiskers) indicate the maximum and minimum values of the measurements. The interior line of the box represents the median, while the cross (×) indicates the mean and the circles the outlier values. * and # indicate statistically significant differences between lakes (Mann–Whitney pairwise comparisons, p-value < 0.05) between biomarker values across lakes. In all cases n = 8.
Figure 3. Boxplots of (a) MDA levels and (b) %DNA in tail estimated in the gonads of Carassius gibelio in lakes Doirani (DOI), Petron (PETR), Vegoritida (VEG) and Volvi (VOL). The lower and upper boundaries of the boxes represent the 25th and 75th percentiles, respectively. The lines (whiskers) indicate the maximum and minimum values of the measurements. The interior line of the box represents the median, while the cross (×) indicates the mean and the circles the outlier values. * and # indicate statistically significant differences between lakes (Mann–Whitney pairwise comparisons, p-value < 0.05) between biomarker values across lakes. In all cases n = 8.
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Figure 4. Linear regression of mean %DNA in tail values against the ecological quality ratio (EQR) of each of the studied lake as defined by the Greek Lake Fish Index (GLFI). Each dot represents one lake.
Figure 4. Linear regression of mean %DNA in tail values against the ecological quality ratio (EQR) of each of the studied lake as defined by the Greek Lake Fish Index (GLFI). Each dot represents one lake.
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Figure 5. Mean %DNA in tail values (columns) and EQR values (diamonds) as assessed by the Greek Lake Fish Index (GLFI). DOI, VEG, VOL, PETR for Lakes Doirani, Vegoritida, Volvi and Petron, respectively.
Figure 5. Mean %DNA in tail values (columns) and EQR values (diamonds) as assessed by the Greek Lake Fish Index (GLFI). DOI, VEG, VOL, PETR for Lakes Doirani, Vegoritida, Volvi and Petron, respectively.
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Table 1. Morphometric and physicochemical characteristics (mean ± standard error, minimum–maximum values) of the studied lakes. Data acquired from: a [25], b [26] and c [27]. DO: Dissolved Oxygen; EC: Electrical Conductivity; TP: Total Phosphorus; NO3: Nitrates; TSS: Total Suspended Solids; BOD5: Biochemical Oxygen Demand.
Table 1. Morphometric and physicochemical characteristics (mean ± standard error, minimum–maximum values) of the studied lakes. Data acquired from: a [25], b [26] and c [27]. DO: Dissolved Oxygen; EC: Electrical Conductivity; TP: Total Phosphorus; NO3: Nitrates; TSS: Total Suspended Solids; BOD5: Biochemical Oxygen Demand.
LakeArea a (km2)Mean Depth b
(m)		Secchi Depth c (m)pH cDO c
(mg/L)		EC c (μS/cm)TP c (mg/L)NO3 c
(mg/L)		TSS c (mg/L)BOD5 c
(mg/L)
Mean (± Standard Error)
(Minimum–Maximum Values)
Doirani38.8741.48 (±0.14)
(0.8–4.0)		8.90 (±0.04)
(8.53–9.26)		10.16 (±0.28) (7.33–13.01)686.45 (±14.98)
(583–965.9)		0.044 (±0.004)
(0.019–0.085)		0.47 (±0.08) (0.27–2.1)7.93 (±0.66)
(1.76–14.89)		4.52 (±0.49)
(0.8–8.5)
Petron12.3630.34 (±0.04)
(0.20–0.70)		8.91 (±0.09)
(8.2–9.55)		10.51 (±0.69)
(7.65–18.39)		979.82 (±32.88)
(737.7–1162)		0.066 (±0.006)
(0.022–0.127)		1.41 (±0.59) (0.27–7.1)29.51 (±5.26)
(10.4–96.7)		5.4 (±0.86)
(7.65–18.39)
Vegoritida53.96253.14 (±0.28)
(1.10–5.20)		8.84 (±0.06)
(8.11–9.16)		9.66 (±0.29)
(7.66–13.26)		629.27 (±14.54)
(510.2–727.3)		0.042 (±0.005)
(0.016–0.091)		0.75 (±0.21) (0.27–3.6)2.26 (±0.32)
(0.35–5.67)		2.92 (±0.5)
(0.3–7.3)
Volvi72.07131.62 (±0.08)
(1.1–2.5)		8.94 (±0.05)
(8.5–9.35)		9.64 (±0.46)
(6.3–13.5)		923.87 (±23.15) (773.3–1069)0.060 (±0.007)
(0.023–0.132)		1.48 (±0.57) (0.27–7.0)3.94 (±0.34)
(0.69–6.75)		4.7 (±0.7)
(6.3–13.5)
Table 2. Ecological quality classification of the studied lakes assessed by different Greek indices covering the last decade. EQR: Ecological Quality Ratio; a GLFI: Greek Lake Fish Index [28]; b GLBiI: Greek Lake Benthic macroinvertebrate Index [29]; c HeLPhy: Hellenic Lake Phytoplankton [30]; d HeLM: Hellenic Lake Macrophytes [31]; e HelLBI: Hellenic Lake Littoral Benthic macroinvertebrate Index [32].
Table 2. Ecological quality classification of the studied lakes assessed by different Greek indices covering the last decade. EQR: Ecological Quality Ratio; a GLFI: Greek Lake Fish Index [28]; b GLBiI: Greek Lake Benthic macroinvertebrate Index [29]; c HeLPhy: Hellenic Lake Phytoplankton [30]; d HeLM: Hellenic Lake Macrophytes [31]; e HelLBI: Hellenic Lake Littoral Benthic macroinvertebrate Index [32].
LakeQuality Class (EQR) per Index
GLFI aGLBiI bHelPhy cHeLM dHelLBI e
DoiraniHigh
(0.81)		Good
(0.69)		Moderate
(0.57)		Good
(0.77)		Moderate
(0.47)
PetronModerate
(0.52)		Moderate
(0.54)		Good
(0.63)		-Moderate
(0.55)
VegoritidaGood (0.66)Moderate
(0.54)		Good
(0.64)		Good
(0.62)		Good
(0.69)
VolviModerate
(0.58)		Moderate
(0.41)		Moderate
(0.46)		Good
(0.73)		Moderate
(0.44)
Table 3. Mean MDA (nmol/mg protein) and %DNA in tail values. Standard error, minimum and maximum values are also provided.
Table 3. Mean MDA (nmol/mg protein) and %DNA in tail values. Standard error, minimum and maximum values are also provided.
Lake
ParameterDoiraniPetronVegoritidaVolvi
Mean (± Standard Error)
Minimum–Maximum Values
MDA (nmol/mg protein)2.31 (±0.28)
1.67–2.97		14.70 (±0.81)
10.39–17.81		4.97 (±0.64)
2.97–7.35		5.42 (±1)
3.91–9.19
%DNA in tail15.1 (±0.54)
13.14–18.35		19.68 (±1.15)
16.08–24.81		16.19 (±0.53)
13.41–18.73		18.44 (±0.34)
16.69–19.82
Table 4. Spearman correlation analysis of environmental parameters and the estimated mean MDA (nmol/mg protein) and %DNA in tail values. ** statistically significant correlations (p < 0.01).
Table 4. Spearman correlation analysis of environmental parameters and the estimated mean MDA (nmol/mg protein) and %DNA in tail values. ** statistically significant correlations (p < 0.01).
AreaMean DepthSecchi DepthpHDOECTPNO3BODTSSChlaMean MDAMean %DNA in Tail
Area10.800.800.20−1 **−0.40−0.400.40−0.40−0.80−0.80−0.20−0.20
Mean Depth 11 **−0.40−0.80−0.80−0.800.01−0.80−1 **−1 **−0.40−0.40
Secchi Depth 1−0.40−0.80−0.80−0.800.01−0.80−1**−1 **−0.40−0.40
pH 1−0.200.800.800.800.800.400.400.600.60
DO 10.400.40−0.400.400.800.800.200.20
EC 11 **0.601 **0.800.800.800.80
TP 10.601 **0.800.800.800.80
NO3 10.600.010.010.800.80
BOD 10.800.800.800.80
TSS 11 **0.400.40
Chla 10.400.40
Mean MDA 11 **
Mean %DNA in tail 1
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Petrocheilou, D.; Petriki, O.; Kaloyianni, M.; Bobori, D.C. Oxidative Stress Biomarkers in Carassius gibelio from Lakes of Varying Ecological Quality. Hydrobiology 2026, 5, 4. https://doi.org/10.3390/hydrobiology5010004

AMA Style

Petrocheilou D, Petriki O, Kaloyianni M, Bobori DC. Oxidative Stress Biomarkers in Carassius gibelio from Lakes of Varying Ecological Quality. Hydrobiology. 2026; 5(1):4. https://doi.org/10.3390/hydrobiology5010004

Chicago/Turabian Style

Petrocheilou, Dimitra, Olga Petriki, Martha Kaloyianni, and Dimitra C. Bobori. 2026. "Oxidative Stress Biomarkers in Carassius gibelio from Lakes of Varying Ecological Quality" Hydrobiology 5, no. 1: 4. https://doi.org/10.3390/hydrobiology5010004

APA Style

Petrocheilou, D., Petriki, O., Kaloyianni, M., & Bobori, D. C. (2026). Oxidative Stress Biomarkers in Carassius gibelio from Lakes of Varying Ecological Quality. Hydrobiology, 5(1), 4. https://doi.org/10.3390/hydrobiology5010004

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