Aquatic toxicology (Amsterdam, Netherlands) · 2026
A multi-omics approach reveals molecular alterations in the digestive gland of Mytilus galloprovincialis following fluoxetine exposure.
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Lemaire Etienne, Gomez Elena, Boccard Julien, Armengaud Jean, Bilbao Eider, Escande Aurélie, Kielbasa Mélodie, Dumas Thibaut, Arrigoni Zoé, Aguirre Mikel, Arribas Gorka, Cajaraville Miren P, Courant Frédérique
Аннотация
Antidepressant consumption has increased markedly in recent years, a trend further amplified by the COVID-19 pandemic. Among these compounds, fluoxetine (FLX), a selective serotonin reuptake inhibitor (SSRI), is one of the most widely prescribed worldwide. Although the effects of FLX on aquatic organisms are well documented, the molecular mechanisms underlying these effects remain insufficiently understood and are essential for a comprehensive assessment of its environmental impact. The present study investigated the molecular effects of FLX in the marine mussel Mytilus galloprovincialis. Mussels were exposed to a nominal concentration of FLX (3.1 µg/L) for 28 days with sampling on days 2, 7, 14, and 28. Molecular responses were characterized using a multi-omics approach. Transcriptomics, proteomics, and metabolomics were acquired from paired digestive gland samples (from the same individual) and subsequently integrated through data fusion modeling and pathway-enrichment analyses. Although molecular responses to FLX were relatively subtle, multi-omics integration revealed consistent modulation of pathways involved in cellular signaling, oxidative stress, energy metabolism, and MAPK pathways. These molecular responses were consistent with previously reported organism-level effects of FLX in mussels. Based on these findings, a putative Adverse Outcome Pathway (AOP) was proposed to link the molecular events identified in this study to individual effects previously reported in the literature. Overall, these findings highlight the value of multi-omics approaches for elucidating pharmaceutical effects in marine organisms and underscore the importance of integrating molecular data with organism-level observations to support AOP development.