Multi-marker study of Dreissena polymorpha populations from hydropower plant reservoir and natural lake in Latvia

Published: 29-10-2018| Version 1 | DOI: 10.17632/2d34ynnx68.1
Lesya Gnatyshyna


Hydropower plants (HPPs) are equipped with reservoirs that can accumulate the toxic effluents and, at least, disturb the water flow of the rivers. However, the information about the combined effects of these causes in aquatic ecosystems is scarce. Invasive mollusk zebra mussel (Dreissena polymorpha) successfully adapted to new environments. Therefore, the aim of this study was to evaluate the suitability of the utilizing zebra mussel as a sentinel organism basing on the comparison of the responses of stress and toxicity in the populations inhabiting the reservoir of Riga HPP and natural lake in Latvia. According to the Mn-SOD and LPO levels in the soft tissues, the antioxidant preference was indicated in the mussels from HPP. However, they demonstrated the depletion of GSH/GSSG and pyruvate and, consequently higher by 1.4 times lactate/pyruvate ratio compare to the specimens from the lake. In the mussels from HPP reservoir, higher levels of protein carbonilation can be explained by lower apoptotic activities (caspase-3 and lysosomal cantepsin D efflux (by 1.4 and 1.6 times correspondingly). Alkali-labile phosphate (vitellogenin-like proteins) and cholinesterase (unexpectedly) levels were higher in the mussels from reservoir. The catalase and GST activities and metallothionein concentration were similar in both groups. The redox state indices demonstrated the higher number of the correlations (5-7). The data concerning the suitability of zebra mussel as indicative organism needs to be evaluated in the terms of adaptive ability of this invasive species.


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The data are presented as means ± standard deviation (SD) unless indicated otherwise. Data were tested for normality and homogeneity of variance by using Kolmogorov-Smirnoff and Levene’s tests, respectively. Whenever possible, data were normalized by Box-Cox common transforming method. For the data that were not normally distributed even after the transformation, non-parametric tests (Kruskall–Wallis ANOVA and Mann–Whitney U-test) were performed. Pearson’s correlation test for the pairs of variables was performed at a 0.05 level of significance. All statistical calculations were performed with Statistica v. 10.0 and Excel for Windows-2010. Differences were considered significant if the probability of Type I error was less than 0.05.