Enhanced Reality in Assessing Antibiotic Risks in Water: Bacterial Resistance Insight from the Microflora–Microcosm–Modeling Framework
Qingbin Yuan, Yuying Chen, Yating Zhang, Na Wang, Guang‐Guo Ying, Hongqiang Ren, Yi Luo
Abstract
In addition to direct ecological effects, antibiotic residuals in the environment contribute to the development of antibiotic resistance, which is not addressed by traditional ecological risk assessment frameworks such as the persistence, bioaccumulation, and toxicity (P-B-T) criteria. Here, we propose a novel 3M (microflora-microcosm-modeling) framework to assess the risk of antibiotics in promoting bacterial resistance within bacterial flora. Results reveal that aquatic microflora in water environments harbor unexpectedly high antibiotic resistance levels, comparable to clinical settings, despite ambient antibiotic concentrations being orders of magnitude lower, which underscores the rationale for using bacterial resistance as a key indicator in antibiotic risk assessments. Then, building on previous microflora-based studies in lab media, we developed microflora-based microcosm integrated with advanced ecological and pharmacodynamic modeling, establishing the innovative 3M framework. This framework establishes more realistic risk thresholds than the traditional ecological risk assessment criterion. When applied to the Yangtze River, Asia's largest river, the 3M framework identified moderate or high antibiotic risks at 21.7, 30.6, and 47.3% sites in the upper, middle, and lower reach sections, respectively. This study establishes an adaptable, evidence-based complement to traditional ecological risk assessment criteria, in line with increasing regulatory requirements.