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Evidence that microplastics at environmentally relevant concentration and size interfere with energy metabolism of microalgal community
Summary
In a community of three algae species, environmentally realistic concentrations of micron-sized microplastics reduced sugar production and increased energy consumption in the cells. The microplastics interfered with algal movement, nutrient absorption, and caused lasting oxidative stress and DNA damage. Since algae are the foundation of aquatic food chains, this disruption at realistic pollution levels could ripple through ecosystems that ultimately affect human food sources.
To address two current issues in evaluating the toxicity of microplastics (MPs) namely, conflicting results due to species specificity and the ecological irrelevance of laboratory data, this study conducted a 10-day exposure experiment using a microalgal community comprising three symbiotic species. The experiment involved virgin and Benzo[a]pyrene-spiked micron-scale fibers and fragments made of polyethylene terephthalate (PET) and polypropylene (PP). The results showed that, from a physiological perspective, environmentally relevant concentrations of micron-scale MPs decreased saccharide accumulation in microalgal cells, as confirmed by ultrastructural observations. MPs may increase cellular energy consumption by obstructing cellular motility, interfering with nutrient uptake, and causing sustained oxidative stress. Additionally, MPs and adsorbed B[a]P induced DNA damage in microalgae, potentially further disrupting cellular energy metabolism. Ecologically, MPs altered the species abundance in microalgal communities, suggesting they could weaken the ecological functions of these communities as producers and affect ecosystem diversity and stability. This study marks a significant advancement from traditional single-species toxicity experiments to community-level assessments, providing essential insights for ecological risk assessment of microplastics and guiding future mechanistic studies utilizing multi-omics analysis.
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