The Capibaribe River Basin is located in the northeastern portion of Pernambuco and has an area corresponding to approximately 7.58% of the territory of Pernambuco (SRH-PE, 2010). Therefore, Capibaribe drains through several urban centers, which serve as drains for industrial and domestic effluents.
According to the National Water Agency, the lowest availability of water per capita in Brazil is in the Capibaribe Basin in Pernambuco (ANA, 2005). In addition, is polluted by solid and liquid release, organic and inorganic, industrial and agricultural waste generated by the surrounding population, the clothing hub in Alto Capibaribe, and the sugar and alcohol production chain. (SRH-PE, 2010). These data corroborate the results of this study. According to CONAMA resolution 357/2005, which classifies water bodies and the environmental guidelines for making this classification, there are five classes of freshwater bodies (rivers, lakes, and ponds, etc.). The points investigated in this study are located on the Capibaribe River, which is classified as freshwater class 2, according to this resolution.
Water samples collected from SAC and TOR showed physicochemical parameters associated with high pollution levels. Dissolved Oxygen (DO) was below the recommended levels (DO should not be less than 05 mg/L, and pH should be in the range of 6.0 to 9.0), whereas turbidity exceeded the maximum allowed limit of 100 NTU. The reduction in DO of water bodies is a consequence of the dumping of organic residues (organic matter), which are decomposed by microorganisms that use oxygen for respiration (Araújo et al., 2018). These residues may also be responsible for the pH reduction and turbidity in the water (owing to the presence of solid materials in suspension) and are directly related to the disposal of domestic effluents.
Furthermore, SAC and TOR exhibited the highest levels of metals in all collections, which are associated with the presence of textile industries on riverbanks in both cities (Bezerra et al., 2015). Textile wastewater carries a large amount and variety of pollutants used in the treatment of fabrics, especially dyes (Santos et al., 2007). These effluents are characterized by the presence of heavy metals, micronutrients, dissolved solids, and high biological and chemical oxygen demand (Araújo et al., 2022; Khan and Malik, 2014).
The physicochemical parameters and the concentrations of metals found in the samples collected in SUR characterized better quality water in the river course. At this point, the river passes through a rural area of a small town with approximately 58,000 in habitants and is more prone to contamination from agricultural activities, especially sugarcane production (Bezerra et al., 2015). It is likely that some pollution from agriculture, primarily pesticides, reaches this environment; however, there are no references in the literature regarding the type and pollution levels in this part of the river. Moreover, this point is 45 km downstream of TOR, demonstrating that water quality can be substantially improved, even at a relatively small distance from leading industrial pollution sources, at least when heavy metals are concerned.
The dynamics of chemical changes in water are very complex; however, degradation, evaporation, incorporation into the sediment, and the action of microorganisms can explain the decrease in pollution and the improvement in water quality (Tak, 2020; Wilkes and Aristilde, 2017) in SUR when compared with those collected in TOR and SAC.
At the next four points (LIM, SAL, CAV, and REC) the river passes through the urban areas. At these points, the water quality parameters were worse than those of SUR and better than those of SAC and TOR. The metal levels varied across points and stations. At these three points, the water quality deteriorated in the dry season. Sewage is probably the highest source of pollution, and the best regional sewage treatment rate is that of Recife, with approximately 68% of treated sewage (IBGE, 2018). It is likely that some specific events, which we could not identify, must have caused the two peaks in the Mn and Cd concentrations at CAV in the collections made during the dry seasons.
Aquatic species are normally exposed to a complex mixture of chemical substances that induce genetic damage, which can be expressed at different levels of ecological organization (individual, population or ecosystem) (Castro et al., 2021). A wide variety of environmental contaminants can directly or indirectly cause changes in the DNA. Thus, they have significant toxicological relevance because they are involved in various pathological processes, including reproductive and carcinogenic effects. Among these contaminants, metals stand out as in addition to affecting the individual, they become active in subsequent generations owing to their bioaccumulation ability (Castro et al., 2021; Lewis and Galloway, 2008).
The SEM results suggest that metals were the primary factors responsible for the genetic damage (comet test) and mutations (micronucleus test) observed in fish collected from the Capibaribe River. The sites with the highest heavy metal pollution were also those having tilapia specimens with the highest frequency of Mns and ID, specifically SAC and TOR. SUR had the lowest concentrations of metals and fish with lower Mn frequencies and IDs. The genotoxic effects of metals on fish have been reported in various ecotoxicological studies carried out in the field (Turan et al., 2020; Omar et al., 2012) and in controlled experiments (Shah et al., 2020; Hamed et al., 2019).
Specimens of tilapia (O. mossambicus) exposed to different concentrations of sodium arsenite (NaAsO2) were used to demonstrate the genotoxic potential of this compound using the comet assay and micronucleus test (Ahmed et al., 2013), and results indicate that these methodologies have different sensitivities in detecting genomic damage, providing an explanation of the effects of NaAsO2.
Adam et al. (2010) studied specimens of the viviparous Poecilia species in an urban lake in Curitiba, Southern Brazil, and observed that the heavy metal concentrations in this region can cause adverse effects on the genome through the formation of micronuclei in the evaluated erythrocytes. Recent studies have indicated that these contaminants have genotoxic potential in various taxonomic groups, including aquatic animals (Musrri et al., 2021; Rocha et al., 2014), fish (Lima et al., 2019; Barsiene et al., 2013; Ragugnetti et al., 2011; Sponchiado et al., 2011), and gastropods (Maltseva et al., 2022; Sarkar et al., 2015).
Pinheiro et al. (2013) observed that high heavy metal concentrations, such as Cu, Cd, Cr, Pb, and mercury (Hg), quantified in water and sediment samples collected in a heavily impacted mangrove region are directly related to the induction mechanism of genomic damage in Ucides cordatus crabs, revealing the mutagenic potential of these compounds in crustaceans.
The heavy metal ions studied here can cause genetic damage directly by binding to DNA molecules and forming adducts, or indirectly by inducing the generation of free radicals in cells, which cause single and double breaks. Cu (Tkeshelashvili et al., 1991) and Cr (Salnikow and Zhitkovich, 2008) ions can form adducts with DNA molecules, generating labile sites that are prone to breaking the molecule.
Moreover, Cr ions can generate free radicals (Nickens et al., 2010) as well as those of Fe (McCord, 2004), Mn (Farina et al., 2013), Cd (Wang et al., 2004), and Pb (Lee et al., 2019), primarily due to reactions with hydrogen peroxide or interference with cellular respiration processes in the mitochondria. Markers of oxidative stress in fish exposed to heavy metals, such as superoxide dismutase, catalase, glutathione S-transferase, glutathione, and malondialdehyde, have been used to characterize the generation of free oxygen radicals (Farombi et al., 2007; Pandey et al., 2003).
Thus, biomonitoring of aquatic environments is necessary because these environments are the final destination for most urban, industrial, and agricultural waste (Sanou et al., 2021; Maciel et al., 2015; Ginebreda et al., 2014; Adam et al., 2010). Many of these pollutants are present at minimal levels in the environment; however, they can accumulate in the tissues of aquatic organisms and induce DNA damage in these species (Adam et al., 2010; Santos et al., 2010).
In addition, these contaminants can lead to diverse pathophysiological changes, including loss of gametes due to cell death, sterility, embryonic mortality, growth inhibition, developmental abnormalities, enzymatic dysfunction, metabolic dysregulation, premature aging, and neoplasms depending on the exposure time and concentration levels (Paixao et al., 2011; Pinheiro and Toledo, 2010; Belfiore and Anderson, 2001; Depledge, 1996). Species that are bioindicators of environmental quality are more sensitive to the effects of these compounds, and Nile tilapia have proven to be a promising species for this purpose (Lima et al., 2019; Amoozadeh et al., 2014).
The results observed at the SAC and TOR points revealed that the industrial centers present in the vicinity of Capibaribe had a strong influence on the high levels of environmental degradation detected in these areas. This is similar to the genotoxic results observed by Galindo and Moreira (2009) in fish species exposed to domestic and industrial waste.
The SEM not only verifies the effect of metals as a latent variable, explaining biological effects but also makes inferences about other types of pollution that can affect biological responses. Thus, 15% of micronucleus frequency and 31% of ID were not explained by the latent variable (metals). It is likely that a relevant part of the genotoxic effects observed in the fish collected from SAC and TOR is owing to substances dumped by the textile industry, especially dyes (Araújo et al., 2022).
The water collected in SUR was virtually metal-free; however, the levels of genetic damage were much higher than those observed in the control group. Since this point is downstream of SAC and TOR, chemical contaminants can reach and cause genetic damage in organisms. Furthermore, this point is in a rural area that is characterized by sugarcane plantation, which makes heavy use of pesticides, thus explaining the genetic damage seen in the organisms at this point in the river.
The following points (LIM, SAL, CAV, and REC) represent urban regions with variable concentrations of metals, where pollution is probably more complex and a mixture of varying levels of domestic and industrial exhaustion. Such factors cause difficulty in making inferences about genotoxicity that cannot be explained by heavy metals. Thus, the pollution at these points requires better characterization to understand the genotoxic effects on the collected animals.