Exposure pathway dependent effects of titanium dioxide and silver nanoparticles on the benthic amphipod Gammarus...

The increasing production of engineered inorganic nanoparticles (EINPs) elevates their release into aquatic ecosystems raising concerns about associated environmental risks. Numerous investigations indicate sediments as the final sink, facilitating the exposure of benthic species to EINPs. Although reports of sub-lethal EINP effects on benthic species are increasing, the importance of exposure pathways (either waterborne or dietary) is poorly understood. This study investigates the influence of two EINPs, namely titanium dioxide (nTiO₂) and silver (nAg), on the benthic model organism Gammarus fossarum specifically addressing the relative relevance of these pathways. For each type of EINP an individual 30-day long bioassay was conducted, applying a two-factorial test design. The factors include the presence or absence of the EINPs (nTiO₂: ∼80 nm, 4 mg/L or nAg: ∼30 nm, 0.125 mg/L; n = 30) in the water phase (waterborne), combined with a preceding 6-day long aging of their diet (black alder leaves) also in presence or absence of the EINPs (dietary). Response variables were mortality, food consumption, feces production and energy assimilation. Additionally, the physiological fitness was examined using lipid content and dry weight of the organisms as measures. Results revealed a significantly reduced energy assimilation (up to ∼30%) in G. fossarum induced by waterborne exposure towards nTiO₂. In contrast, the dietary exposure towards nAg significantly increased the organisms' energy assimilation (up to ∼50%). Hence, exposure pathway dependent effects of EINPs cannot be generalized and remain particle specific resting upon their intrinsic properties affecting their potential to interact with the surrounding environment. As a result of the different properties of the EINPs used in this study, we clearly demonstrated variations in type and direction of observed effects in G. fossarum. The results of the present study are thus supporting current approaches for nano-specific grouping that might enable an enhanced accuracy in predicting EINP effects facilitating their environmental risk assessment.