Seasonal modulation of oxidative stress biomarkers in mangrove oyster (Crassostrea gasar) from an Amazon estuary

Abstract

Estuaries are the final destination of many pollutants derived from anthropogenic activity. Therefore, it is difficult to find this kind of ecosystem in a pristine condition. In this context, biomonitoring studies that characterize the organism's conditions against the environment’ s natural variation are essential for future impact analysis due to anthropic activity. The present study aims to characterize the natural modulation of biochemical biomarkers in oysters Crassostrea gasar. The research was conducted in Japerica Bay, an estuary region located in the Eastern Amazon (Pará, Brazil), which has remained in pristine condition for many years. The samplings were carried out throughout one year during the rainy-dry transition period (June/2013), dry period (September/2013), dry-rainy transition period (November / 2013), and rainy period (February / 2014) in the lower and upper estuary. The activity of glutathione-S-transferase (GST) and total antioxidant capacity (ACAP) were evaluated as biomarkers of exposure and lipid peroxidation (LPO) as an effect biomarker. In gills, GST decreased during the rainy season in both sites and increased during the salinity peak (dry-rainy transition period) for the upper estuary's organisms. In this organ, the lowest levels of LPO occurred during the dry season for both points. There was an induction of ACAP in muscle during the rainy-dry transition period compared to the dry and dry-rainy transition periods for the lower estuary's organisms, and there were no differences for GST suggesting low tissue sensitivity. There was an increase in LPO during the rainy season compared to the rainy-dry transition period for the lower estuaries animals. Biomarkers in gills suggest a metabolic challenge to the rainy season and stability during the dry season. The species shows high viability of use in biomonitoring programs. However, these seasonality-induced alterations in biomarkers responses must be taken into account to interpret the results.