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Aquat Toxicol. 2013 Nov 15;144-145:172-85. doi: 10.1016/j.aquatox.2013.10.002. Epub 2013 Oct 12.

Mercury contamination in deep-water fish: transcriptional responses in tusk (Brosme brosme) from a fjord gradient.

Author information

1
National Institute of Nutrition and Seafood Research, Nordnesboder 1-2, N-5005 Bergen, Norway. Electronic address: pal.olsvik@nifes.no.

Abstract

Recent findings have shown that deep-water fish from coastal areas may contain elevated levels of mercury (Hg). Tusk (Brosme brosme) was collected from six locations in Hardangerfjord, a fjord system where the inner parts are contaminated by metals due to historic industrial activity. ICPMS was used to determine the accumulated levels of metals (Hg, MeHg, Cd, Pb, As, and Se) in the fish, whereas oxidative status of the liver was assessed by measuring TBARS, vitamin C, vitamin E and catalase activity. To find out whether accumulated Hg triggers toxicologically relevant transcriptional responses and in order to gain genomic knowledge from a non-model species, the liver transcriptome of the gadoid fish was sequenced and assembled, and RNA-seq and RT-qPCR were used to screen for effects of Hg. The results showed high levels of accumulated Hg in tusk liver, probably reflecting an adaptation to deep-water life history, and only a weak declining outward fjord gradient of Hg concentration in tusk liver. MeHg only accounted for about 17% of total Hg in liver, suggesting hepatotoxicity of both inorganic and organic Hg. Pathway analysis suggested an effect of Hg exposure on lipid metabolism and beta-oxidation in liver. Oxidative stress markers glutathione peroxidase 1 and ferritin mRNA, as well as vitamin C and vitamin E (alpha and gamma tocopherol) showed a significant correlation with accumulated levels of Hg. Many transcripts of genes encoding established markers for Hg exposure were co-regulated in the fish. In conclusion, tusk from Hardangerfjord contains high levels of Hg, with possible hepatic effects on lipid metabolism and oxidative stress.

KEYWORDS:

Bioinformatics; Next-generation sequencing; Non-model fish; Toxicogenomics

PMID:
24184472
DOI:
10.1016/j.aquatox.2013.10.002
[Indexed for MEDLINE]
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