Department of Evolution, Ecology, and Organismal Biology, The Ohio State University, Columbus, Ohio, United States of America.
Faculty of Biology, University of Latvia, Riga, Latvia.
PLoS One. 2023 Feb 1;18(2):e0280382. doi: 10.1371/journal.pone.0280382. eCollection 2023.
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.
新兴关注污染物对水生野生动物,尤其是淡水贻贝构成严重危害。水生系统中污染物数量的增加要求科学家和管理者优先考虑最有可能引起生物反应的污染物,以便进一步进行监测和毒理学测试。本研究的目的是确定最有可能影响 Pyganodon grandis 的污染物亚类,并描述不同地点之间代谢物和基因表达的变化。贻贝被放置在笼子中,在美国俄亥俄州莫米河盆地的四个地点进行了为期两周的部署。对水样进行了 220 种污染物的存在分析。采集血淋巴样本进行代谢组学分析,并使用质谱进行分析。使用偏最小二乘法(PLS)回归鉴定与代谢物显著相关的污染物。采集组织样本进行转录组学分析,使用 Illumina HiSeq 2500 对 RNA 进行测序,并对组装的转录本进行差异表达分析。在所靶向的 220 种污染物中,有 69 种在至少一个水样中被检测到。在所检测到的贻贝血淋巴中的 186 种代谢物中,有 43 种在四个地点之间存在显著差异。PLS 模型确定了 44 种与代谢物变化显著相关的污染物。共有 296 个转录本在两个或多个地点之间差异表达,其中 107 个获得 BLAST 命中,52 个被注释并分配到一个或多个基因本体论域。我们的分析揭示了与代谢物变化显著相关且最有可能对淡水贻贝健康产生负面影响并导致该高度濒危动物种群持续下降的污染物。我们整合了“组学”技术,对污染物对生物体生理的短期影响进行了广泛而深入的评估。我们的研究结果突出了最有可能导致这些变化的污染物,并应优先进行更广泛的毒理学测试。