DUGi

Hidden drivers of low-dose pharmaceutical pollutant mixtures revealed by the novel GSA-QHTS screening method

http://dugi.udg.edu/item/http:@@@@hdl.handle.net@@2072@@284527

The ecological impacts of emerging pollutants such as pharmaceuticals are not well understood. The lack of experimentalapproaches for the identification of pollutant effects in realistic settings (that is, low doses, complex mixtures,and variable environmental conditions) supports the widespread perception that these effects are often unpredictable.To address this, we developed a novel screening method (GSA-QHTS) that couples the computationalpower of global sensitivity analysis (GSA) with the experimental efficiency of quantitative high-throughput screening(QHTS). We present a case study where GSA-QHTS allowed for the identification of the main pharmaceutical pollutants(and their interactions), driving biological effects of low-dose complex mixtures at the microbial population level. TheQHTS experiments involved the integrated analysis of nearly 2700 observations from an array of 180 unique low-dosemixtures, representing the most complex and data-rich experimental mixture effect assessment of main pharmaceuticalpollutants to date. An ecological scaling-up experiment confirmed that this subset of pollutants also affects typicalfreshwater microbial community assemblages. Contrary to our expectations and challenging established scientificopinion, the bioactivity of the mixtures was not predicted by the null mixture models, and the main drivers that wereidentified by GSA-QHTS were overlooked by the current effect assessment scheme. Our results suggest that currentchemical effect assessment methods overlook a substantial number of ecologically dangerous chemical pollutantsand introduce a new operational framework for their systematic identification

American Association for the Advancement of Science