Chen Wang , Xiao Luan , Junya Zhang , Hong Zhang , Yu Zhang , Min Yang , Zhe Tian
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引用次数: 0
Abstract
Bacteriophages are pivotal in shaping microbial communities, but their structural and functional responses to antibiotic stress in aerobic biofilms remain underexplored. This study aims to fill this void by providing a comprehensive understanding of how viral communities in aerobic biofilms adapt to increasing antibiotic pressures through interactions with their bacterial hosts. Three lab-scale aerobic biofilm systems were established and operated for 577 days, two of those were exposed to increasing influent concentrations of oxytetracycline (OTC) and streptomycin (STM), respectively. The dynamics of the biofilm virome under antibiotic stress was revealed by metagenomic sequencing. Results showed that the virome in aerobic biofilms displayed a high percentage (98.7 %) of unknown bacteriophages, indicating considerable viral diversity. As for the hosts of phages, a total of 1741 bacteriophage contigs were associated with 660 distinct bacterial hosts. In antibiotic-treated systems, broad-host-range generalist bacteriophages accounted for over 17.95 % (STM) and 17.90 % (OTC), compared to 14.32 % in the control. Furthermore, viral community did not carry diverse antibiotic resistance genes, which only accounted for 0.34 % of the resistome. Additionally, it did not regulate the number of resistant bacteria by activating the lytic and lysogenic cycles in this study. This indicated that the contribution of transduction to the horizontal spread of resistant determinants is very limited in the aerobic biofilm. Under antibiotic stress, viral auxiliary metabolic genes compensated for incomplete metabolic pathways in host cells, particularly those related to carbohydrate, amino acid, and cofactor metabolism. These genes likely offer dual benefits to bacterial hosts by repairing antibiotic-induced cellular damage and supporting energy generation, thereby providing adaptive advantages for bacterial survival and proliferation under antibiotic selection pressure. This study uncovers the complex interactions between bacteriophages, their hosts, and environmental pressures. It suggests that viral communities in these environments compensate for functional metabolism rather than promote resistance development under antibiotic stress, providing new insights into the potential roles of bacteriophages in the regulation of microbial-driven processes.
期刊介绍:
Water Research, along with its open access companion journal Water Research X, serves as a platform for publishing original research papers covering various aspects of the science and technology related to the anthropogenic water cycle, water quality, and its management worldwide. The audience targeted by the journal comprises biologists, chemical engineers, chemists, civil engineers, environmental engineers, limnologists, and microbiologists. The scope of the journal include:
•Treatment processes for water and wastewaters (municipal, agricultural, industrial, and on-site treatment), including resource recovery and residuals management;
•Urban hydrology including sewer systems, stormwater management, and green infrastructure;
•Drinking water treatment and distribution;
•Potable and non-potable water reuse;
•Sanitation, public health, and risk assessment;
•Anaerobic digestion, solid and hazardous waste management, including source characterization and the effects and control of leachates and gaseous emissions;
•Contaminants (chemical, microbial, anthropogenic particles such as nanoparticles or microplastics) and related water quality sensing, monitoring, fate, and assessment;
•Anthropogenic impacts on inland, tidal, coastal and urban waters, focusing on surface and ground waters, and point and non-point sources of pollution;
•Environmental restoration, linked to surface water, groundwater and groundwater remediation;
•Analysis of the interfaces between sediments and water, and between water and atmosphere, focusing specifically on anthropogenic impacts;
•Mathematical modelling, systems analysis, machine learning, and beneficial use of big data related to the anthropogenic water cycle;
•Socio-economic, policy, and regulations studies.