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Updated: Nov 27, 2025

Isolation and Identification of Waterborne Antibiotic-Resistant Bacteria and Molecular Characterization of their Antibiotic Resistance Genes
Published on: March 3, 2023
The microbial network property as a bio-indicator of antibiotic transmission in the environment
Qun Gao1, Shuhong Gao2, Colin Bates3
1State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China.
Abstract:
Interspecies interaction is an essential mechanism for bacterial communities to develop antibiotic resistance via horizontal gene transfer. Nonetheless, how bacterial interactions vary along the environmental transmission of antibiotics and the underpinnings remain unclear. To address it, we explore potential microbial associations by analyzing bacterial networks generated from 16S rRNA gene sequences and functional networks containing a large number of antibiotic-resistance genes (ARGs). Antibiotic concentration decreased by more than 4000-fold along the environmental transmission chain from manure samples of swine farms to aerobic compost, compost-amended agricultural soils, and neighboring agricultural soils. Both bacterial and functional networks became larger in nodes and links with decreasing antibiotic concentrations, likely resulting from lower antibiotics stress. Nonetheless, bacterial networks became less clustered with decreasing antibiotic concentrations, while functional networks became more clustered. Modularity, a key topological property that enhances system resilience to antibiotic stress, remained high for functional networks, but the modularity values of bacterial networks were the lowest when antibiotic concentrations were intermediate. To explain it, we identified a clear shift from deterministic processes, particularly variable selection, to stochastic processes at intermediate antibiotic concentrations as the dominant mechanism in shaping bacterial communities. Collectively, our results revealed microbial network dynamics and suggest that the modularity value of association networks could serve as an important indicator of antibiotic concentrations in the environment.
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