Correlation between Heavy Metal-Induced Histopathological Changes and Trophic Interactions between Different Fish Species

This study assessed the distribution of heavy metals in the gills, kidney, and liver, correlated with the severity of histopathological changes, of three fish species with different feeding habitats (Barbus barbus, Squalius cephalus, and Chondrostoma nasus) from the Crisul Negru river, Romania. The levels of copper (Cu), chromium (Cr), cadmium (Cd), lead (Pb), and zinc (Zn) in fish tissues were measured by atomic absorption spectrophotometry. Histopathology and the expressions of TNF-alpha and proliferation cell nuclear antigen (PCNA) were investigated by immunohistochemistry and Western blot. Our data suggest a significant correlation between the bioconcentration level of metals and structural changes. The carnivorous species was the most affected compared to the omnivorous and herbivorous ones, and the most affected organ was the kidney. Moreover, the correlation of tissue damage with the PCNA and TNF-alpha expression levels revealed that the herbivorous species presented less extended lesions, likely due to higher activated repair mechanisms and lower levels of inflammation. In conclusion, our data and the subsequent statistical analysis suggest that feeding behavior could be correlated with the histopathological alterations and might be used for a more profound evaluation of aquatic environment safety and analysis of aquatic ecosystems.

Automated summary

The study found a significant correlation between the bioconcentration of heavy metals and structural changes in different feeding habit fish species, with carnivorous species being most affected and kidney being the most affected organ. Herbivorous species showed less extensive lesions, likely due to higher activated repair mechanisms and lower levels of inflammation as indicated by PCNA and TNF-alpha expression levels. Feeding behavior could be used for a more in-depth evaluation of aquatic environment safety and analysis of aquatic ecosystems based on data and statistical analysis.