作者：Xiong, G., Liu, M., Zhu, X., et al.

Emerging contaminants (ECs) in coastal hydrological systems pose an increasingly severe threat to the nitrogen cycle. However, current research remains severely insufficient, and conventional understanding suggests that strongly-correlated ECs exert greater impacts on nitrogen cycling than weakly-correlated ones, thereby overlooking the potential synergistic effects of weakly-correlated ECs. This study investigates the coastal hydrological system of Laizhou Bay, integrating hydrochemical analysis, non-targeted screening (identifying 552 ECs), high-throughput sequencing, and molecular ecological network analysis to systematically explore the mechanisms by which weakly-correlated ECs mixtures influence nitrogen cycling. Findings reveal that lowering the correlation threshold (from |r| >= 0.8 to |r| >= 0.6) significantly increases both the number and diversity of ECs associated with nitrogen transformation functional genes. These weakly-correlated ECs form a much denser network of functional modules (i.e., "clustering effect") through nonlinear relationships. Variance decomposition analysis further confirmed that weakly-correlated ECs collectively explained nitrogen cycle gene distribution better than strongly-correlated ECs. Additionally, environmental factors such as salinity, organic carbon, and redox conditions jointly modulated the strength and direction of ECs' effects. This study provides the first multi-omics evidence that in coastal hydrological systems, the synergistic effects of numerous weakly-correlated ECs exert a stronger influence on the intensity and scope of nitrogen cycling than a few strongly-correlated ECs. This finding challenges existing ecological risk assessment paradigms, emphasizing the need to shift from a single-pollutant focus to evaluating the holistic effects of complex mixtures and to address the impacts of weakly-correlated ECs. It holds significant implications for coastal environmental management and pollution control strategies.

（来源：Water Research 2025  DOI: 10.1016/j.watres.2025.125130）