Banded tetra (Astyanax aeneus) as bioindicator of trace metals in aquatic ecosystems of the Yucatan Peninsula, Mexico: Experimental biomarkers validation and wild populations biomonitoring

Organic contamination and multi-biomarker assessment in watersheds of the southern Brazil: an integrated approach using fish from the Astyanax genus

We aimed to examine the responses of pollution biomarkers in feral fish from Astyanax genus collected at three hydrographic regions in southern Brazil and the capacity of these tools to differentiate between various levels of contamination. To achieve this, levels of organochlorine pesticides (liver), as well as the biomarkers AChE (muscle and brain), TBARS (liver), and EROD (liver) were assessed. Collections were conducted in four municipalities (Alegrete, Caraá, Lavras, and Santa Vitória) during 1 year, encompassing winter and summer. Fish from Alegrete were the most contaminated overall, but animals sampled in Caraá, and Lavras also displayed elevated levels of current-use pesticides. Elevated levels of endosulfans, DDTs, HCHs, and current-use pesticides were accompanied by elevated levels of TBARS in the liver. Conversely, fish from Santa Vitória exhibited the highest levels of PAHs, accompanied by elevated levels of EROD in the liver and reduced levels of AChE in muscle and brain. TBARS proved to be a reliable biomarker for assessing impacts arising from pesticide accumulation, while EROD and AChE served as valuable indicators of impacts resulting from PAHs accumulation. Ultimately, the results obtained in this study demonstrate the reliable use of the proposed biomarkers for tracking biological impacts stemming from aquatic pollution using feral Astyanax as biomonitoring species.

Seasonal assessment of selected trace elements in grass carp (Ctenopharyngodon idella) blood and their effects on the biochemistry and oxidative stress markers

Environmental pollution by anthropogenic activity is still a highly relevant global problem. Aquatic animals are a specifically endangered group of organisms due to their continuous direct contact with the contaminated environment. Concentrations of selected trace elements in the grass carp (Ctenopharyngodon idella) (n = 36) blood serum/clot were monitored. Possible effects of the elements on selected biochemical and oxidative markers were evaluated. The concentrations of trace elements (Al, Ba, Be, Bi, Cd, Co, Cr, Cu, Fe, Ga, Mn, Mo, Ni, Pb, Sr, Tl, and Zn) were analysed in the fish blood serum and blood clot by inductively coupled plasma optical emission spectrometry (ICP OES). A general scheme of decreasing concentrations of trace elements in the blood serum samples was: Zn ˃ Fe ˃ Sr ˃ Ba ˃ Ni ˃ Al ˃ Cu ˃ Be ˃ Co; < LOQ (below limit of quantification): Bi, Cd, Cr, Ga, Mn, Mo, Pb, Tl; and in the case of the blood clot, the scheme was as follows: Fe ˃ Zn ˃ Sr ˃ Al ˃ Ni ˃ Ba ˃ Cu ˃ Be ˃ Co ˃ Mn; < LOQ (below limit of quantification): Bi, Cd, Cr, Ga, Mo, Pb, Tl. Significant differences among the seasons were detected. The Spearman R correlation coefficients and linear or non-linear regression were used to evaluate direct relationships between trace elements and selected blood biomarkers. The correlation analysis between biochemical parameters (Na, K, P, Mg, AST, ALT, ALP, GGT, TAG, TP, urea, glucose) and trace elements (Al, Ba, Be, Cu, Fe, Ni, Sr, and Zn) concentrations confirmed statistically significant interactions in both seasons (summer and autumn). The regression analysis between oxidative stress markers (ROS, GPx, creatinine, uric acid, and bilirubin) and elements (Al, Ba, Co, Cu, Fe, Ni, and Sr) content confirmed statistically significant interactions. The results point to numerous connections between the observed elements and the physiological parameters of freshwater fish.

Assessment of single and combined effects of bisphenol-A and its analogue bisphenol-S on biochemical and histopathological responses of sea cucumber Holothuria poli

Bisphenols (BPs) are among emerging pollutants that have been frequently detected in different compartments of marine ecosystems and elicited great concern due to their potential toxicity to marine organisms. This work aimed to investigate the toxicity of bisphenol A (BPA) and bisphenol S (BPS) on oxidative stress markers, neurotoxicity and histopathological alterations in sea cucumbers (Holothuria poli). The results showed that exposure to 200 μg/L of BPA and BPS produced oxidative stress, neurotoxicity in the digestive tract and respiratory tree, and several types of histopathological lesions in tissues of the respiratory tree of the sea cucumber, posing a health hazard to this aquatic organism. In addition, BPA has greater effects than BPS on the generation of oxidative stress marked by the inductions of catalase (CAT), glutathione S-transferase (GST) and malondialdehyde (MDA) levels and neurotoxicity shown by the decrease in acetylcholinesterase activity (AChE). The respiratory tree of sea cucumbers might be an appropriate tissue for assessing CAT, MDA and AChE activity levels, which are reliable biomarkers that may be useful in marine biomonitoring studies. Evaluation of histopathological lesions of the respiratory tree suggests that BPA and BPS and their mixture cause various tissue alterations that may be associated with oxidative stress damage and neurotoxicity. In conclusion, this study showed that oxidative stress (CAT and MDA) and neurotoxicity (AChE) markers, as well as respiratory tree lesions, are sensitive biomarkers for the assessment of BPA and BPS toxicity in sea cucumbers.

Modulation of endogenous antioxidants by zinc and copper in signal crayfish (Pacifastacus leniusculus)

Metal pollution is a long-standing concern and bioindicators are commonly used in ecotoxicological studies to monitor impacted wildlife populations for evidence of sublethal effects. Significant variation in the response of common biomarkers to metals is reported across taxa, thus necessitating careful characterization in model organisms. In this study, we describe the regulation of glutathione S-transferase (GST), glutathione (GSH), and metallothionein (MT) by zinc chloride (0.6, 0.9, 1.2, 2.4, 4.8, 9.6 μg g^-1) and copper chloride (0.6, 0.9, 1.2 μg g^-1) in signal crayfish (Pacifastacus leniusculus). Zinc chloride did not alter GST activity relative to controls in the hepatopancreas. Crayfish exposed to copper chloride exhibited decreased GST activity at the lowest dose tested (0.6 μg g^-1) with no change observed at the higher doses. GSH did not change in response to either metal when sexes were grouped together. MT concentrations increased in response to zinc (2.4, 4.6, and 9.6 μg g^-1 doses) and copper (0.6, 0.9, and 1.2 μg g^-1 doses) in gill tissue. In tail tissue, MT increased at the 2.4 and 4.8 μg g^-1 zinc chloride doses and all the concentrations of copper tested. Sex-specific differences in endogenous antioxidant expression were also analyzed with no clear patterns emerging. We concluded that these endpoints are sensitive to zinc and copper in signal crayfish, although careful interpretation is needed when applying them in field studies given the variation in responses, non-monotonic dose responses, and differences in biotic and abiotic factors that inevitably exist in different aquatic ecosystems.

Ecotoxicological evaluation of water from the Sorocaba River using an integrated analysis of biochemical and morphological biomarkers in bullfrog tadpoles, Lithobates catesbeianus ()

Lithobates catesbeianus tadpoles were exposed for 96 h to water from two sites of the Sorocaba River (summer and winter), Ibiúna (PI) and Itupararanga reservoir (PIR) that contained metals. In the liver, in PI, the glutathione peroxidase (GPx) decreased, and the glutathione S-transferase (GST) and carbonyl proteins (PCO) increased. In PIR, the glutathione reduced (GSH) increased, while there was a decrease in catalase (CAT), GPx, GST, PCO, and superoxide dismutase (SOD). In winter, GPx and GST increased in both points. Regarding the kidneys, lipoperoxidation (LPO) levels and GST decreased, while GSH increased in the summer. In the winter, LPO increased in PI. In the muscle, in the summer, there was an increase in GSH and GST and change in PCO. In the winter, the levels of PCO increased and CAT decreased in PIR. The area and volume of the hepatocyte and nucleus area increased in the summer and decreased in the winter. Hepatic melanin decreased in the summer after exposure to PIR water. There were the systemic effects of Sorocaba River water exposure at different times of the year with alterations in biomarkers at different levels, in which kidney shows highest Integrated Response of Biomarkers (IBR) value followed by liver and muscle. Biochemical biomarkers were more sensitive than morphological ones. The more sensitive biochemical markers were MT, PCO, GST and LPO. These effects confirm the hypothesis of metabolic alteration in bullfrog tadpoles by the Sorocaba River water.

A Machine Learning Approach in Analyzing Bioaccumulation of Heavy Metals in Turbot Tissues

Metals are considered to be one of the most hazardous substances due to their potential for accumulation, magnification, persistence, and wide distribution in water, sediments, and aquatic organisms. Demersal fish species, such as turbot (Psetta maxima maeotica), are accepted by the scientific communities as suitable bioindicators of heavy metal pollution in the aquatic environment. The present study uses a machine learning approach, which is based on multiple linear and non-linear models, in order to effectively estimate the concentrations of heavy metals in both turbot muscle and liver tissues. For multiple linear regression (MLR) models, the stepwise method was used, while non-linear models were developed by applying random forest (RF) algorithm. The models were based on data that were provided from scientific literature, attributed to 11 heavy metals (As, Ca, Cd, Cu, Fe, K, Mg, Mn, Na, Ni, Zn) from both muscle and liver tissues of turbot exemplars. Significant MLR models were recorded for Ca, Fe, Mg, and Na in muscle tissue and K, Cu, Zn, and Na in turbot liver tissue. The non-linear tree-based RF prediction models (over 70% prediction accuracy) were identified for As, Cd, Cu, K, Mg, and Zn in muscle tissue and As, Ca, Cd, Mg, and Fe in turbot liver tissue. Both machine learning MLR and non-linear tree-based RF prediction models were identified to be suitable for predicting the heavy metal concentration from both turbot muscle and liver tissues. The models can be used for improving the knowledge and economic efficiency of linked heavy metals food safety and environment pollution studies.