Junjie Meng
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Junjie Meng has a total of 6 co-authors. Here are the top co-authors by number of shared publications:
- Qingjia Meng
Chinese Research Academy of Environmental Sciences, Beijing 100012, China
1 shared publication - Rongpeng Dou
Linqu Sub-Bureau of Weifang Municipal Ecology and Environment Bureau, Weifang 261000, China
1 shared publication - Shengwang Gao
State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
1 shared publication - Shuhan Yu
Chinese Research Academy of Environmental Sciences, Beijing 100012, China
1 shared publication - Yun Liu
College of Bioscience and Resources Environment, https://ror.org/03t9adt98Beijing University of Agriculture, Beijing 102206, China
1 shared publication - Yuxuan Zhang
State Environmental Protection Key Laboratory of Estuarine and Coastal Environment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
1 shared publication
Latest Publications
- Open Access
A 16S rRNA-Based Screening Framework Reveals Distinct Microbial and Antimicrobial Resistance-Related Fingerprints in Aquaculture and Municipal Wastewater Effluents
Bacterial taxa of potential public-health relevance and predicted antimicrobial-resistance functions are important in effluent management. This study compared bacterial communities, environmental associations, and predicted functions in aquaculture effluents (Group A) and wastewater treatment plant effluents (Group W) from the Mi River Basin, China, using a 16S rRNA-based framework, with the WHO 2024 Bacterial Priority Pathogens List used for contextual interpretation. relatively consistent profiles, with Acinetobacter, Limnohabitans, and Pseudomonas among abundant genera. Group W showed site-specific patterns, including high relative abundances of Legionella, Flavobacterium, and Mycobacterium in W3 and Pseudarcobacter and Arcobacter in W4 and W5. Among 400 genus–factor correlations, only the negative Sphingorhabdus–COD association remained significant after BH correction. The aggregate predicted abundance of six ARG-related KOs was 2.22-fold higher in Group A. The tetA-type KO was higher in Group A, whereas erm-type was higher in Group W. Seven samples had abundance-weighted NSTI values below 0.10, and directional patterns remained after excluding W5. Although 16S-based analyses cannot directly confirm pathogens or ARGs, the framework distinguished effluent-specific microbial and predicted resistance-related patterns, supporting large-scale routine monitoring and tiered risk management for water reuse and receiving waters.
Open AccessA 16S rRNA-Based Screening Framework Reveals Distinct Microbial and Antimicrobial Resistance-Related Fingerprints in Aquaculture and Municipal Wastewater Effluents
Bacterial taxa of potential public-health relevance and predicted antimicrobial-resistance functions are important in effluent management. This study compared bacterial communities, environmental associations, and predicted functions in aquaculture effluents (Group A) and wastewater treatment plant effluents (Group W) from the Mi River Basin, China, using a 16S rRNA-based framework, with the WHO 2024 Bacterial Priority Pathogens List used for contextual interpretation. relatively consistent profiles, with Acinetobacter, Limnohabitans, and Pseudomonas among abundant genera. Group W showed site-specific patterns, including high relative abundances of Legionella, Flavobacterium, and Mycobacterium in W3 and Pseudarcobacter and Arcobacter in W4 and W5. Among 400 genus–factor correlations, only the negative Sphingorhabdus–COD association remained significant after BH correction. The aggregate predicted abundance of six ARG-related KOs was 2.22-fold higher in Group A. The tetA-type KO was higher in Group A, whereas erm-type was higher in Group W. Seven samples had abundance-weighted NSTI values below 0.10, and directional patterns remained after excluding W5. Although 16S-based analyses cannot directly confirm pathogens or ARGs, the framework distinguished effluent-specific microbial and predicted resistance-related patterns, supporting large-scale routine monitoring and tiered risk management for water reuse and receiving waters.