4.6 Article

Contaminants of emerging concern in the Maumee River and their effects on freshwater mussel physiology

Journal

PLOS ONE
Volume 18, Issue 2, Pages -

Publisher

PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0280382

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Contaminants of emerging concern, particularly in aquatic systems, pose a serious threat to the health of freshwater mussels. This study aimed to identify the sub-category of contaminants that are most likely to impact Pyganodon grandis and to investigate the alterations in metabolites and gene expression at different sites. The findings identified specific contaminants that significantly covaried with changes in metabolites and revealed their potential negative impact on mussel health and ongoing declines in population. The integration of omics technologies provided a comprehensive assessment of the short-term effects of contaminants on organismal physiology.
Contaminants of emerging concern pose a serious hazard to aquatic wildlife, especially freshwater mussels. The growing number of contaminants in aquatic systems requires scientists and managers to prioritize contaminants that are most likely to elicit a biological response for further monitoring and toxicological testing. The objectives of this study were to identify a sub-category of contaminants most likely to affect Pyganodon grandis and to describe alterations in metabolites and gene expression between various sites. Mussels were deployed in cages for two weeks at four sites along the Maumee River Basin, Ohio, USA. Water samples were analyzed for the presence of 220 contaminants. Hemolymph samples were collected for metabolomics and analyzed using mass spectrometry. Contaminants that significantly covaried with metabolites were identified using partial least-squares (PLS) regression. Tissue samples were collected for transcriptomics, RNA was sequenced using an Illumina HiSeq 2500, and differential expression analysis was performed on assembled transcripts. Of the 220 targeted contaminants, 69 were detected in at least one water sample. Of the 186 metabolites detected in mussel hemolymph, 43 showed significant differences between the four sites. The PLS model identified 44 contaminants that significantly covaried with changes in metabolites. A total of 296 transcripts were differentially expressed between two or more sites, 107 received BLAST hits, and 52 were annotated and assigned to one or more Gene Ontology domains. Our analyses reveal the contaminants that significantly covaried with changes in metabolites and are most likely to negatively impact freshwater mussel health and contribute to ongoing population declines in this group of highly endangered animals. Our integration of omics technologies provides a broad and in-depth assessment of the short-term effects of contaminants on organismal physiology. Our findings highlight which contaminants are most likely to be causing these changes and should be prioritized for more extensive toxicological testing.

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