Ibuprofen/graphene oxide co-exposure in Chlorella vulgaris: Distinct targets and a dose- and time-dependent shift from synergy to antagonism
Xin Hu, Qichen Yuan, Liang Tang, Jing Fu
Journal:JOURNAL OF HAZARDOUS MATERIALS
IF:10.6
DOI:10.1016/j.jhazmat.2026.142264
PMID:
Published:2026-05-02
research field:分子生物学组学科学水生生态学纳米毒理学药物污染环境毒理学
Abstract
As the use of pharmaceuticals and nanomaterials continues to rise, their concurrent presence in aquatic ecosystems has become increasingly likely, challenging primary producers with complex exposure conditions. Yet, the molecular mechanisms governing their joint impacts are still unclear. This study presents a multi-scale investigation of the time- and concentration-dependent interactions between ibuprofen (IBU) and graphene oxide (GO) in the green alga Chlorella vulgaris . Environmentally relevant concentrations (ERCs) and sublethal concentrations were used, with physiological screening integrated with transcriptomic and metabolomic analyses to assess the effects of IBU, GO, and their mixture (MIX) on algal growth, energy metabolism, and cellular vitality under both acute and chronic conditions. Multi-omics and physiological data revealed concentration-dependent disruptions of MIX in cellular energy metabolism, redox homeostasis, photosynthesis, and cofactor biosynthesis. IBU chiefly disturbed cellular energy pathways and redox homeostasis, consistent with mitochondrial dysfunction, while GO primarily impaired photosynthesis and caused pronounced oxidative stress. Under ERCs and acute conditions, exposure produced largely additive effects with instances of IBU-driven synergism. But the net interaction between IBU and GO shifted toward antagonism, with GO inducing more pronounced oxidative stress and exacerbated mitochondrial damage under sublethal and chronic conditions. By elucidating the time- and concentration- dependent mechanistic interplay between pharmaceuticals and nanomaterials, this work advances understanding of complex co-exposure effects in algae and highlights the importance of chronic, multi-endpoint omics approaches in ecological risk assessment.
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