Wastewater treatment systems are hotspots for mobile genetic elements proliferation and exchange, where dense biofilms create ideal conditions for horizontal gene transfer. In these settings, phages can kill or reprogram bacteria, while plasmids can spread adaptive traits such as antibiotic resistance and virulence functions. Yet one major challenge has persisted: in complex natural biofilms, scientists have struggled to identify which mobile genetic elements belong to which hosts. Traditional culture-based methods are not only time-consuming but also reliant on the culturability of the microorganisms, while computational prediction alone often lacks accuracy or broad coverage. Even newer tools such as single-cell sequencing remain difficult to apply in dense, matrix-rich biofilms. Based on these challenges, deeper research is needed to resolve phage– and plasmid–host relationships directly in situ.
Researchers led by teams at The University of Hong Kong, together with collaborators from the University of Vienna and the Massachusetts Institute of Technology, reported the findings (DOI: 10.1016/j.ese.2026.100683) in Environmental Science and Ecotechnology after the paper was accepted on March 5, 2026. Focusing on wastewater biofilms from the Ma Wan Sewage Treatment Plant in Hong Kong, the team used an integrated framework combining metagenomics, metatranscriptomics, metaviromics, and Hi-C proximity ligation sequencing to decode how phages and plasmids assemble, spread, and connect with microbial hosts inside a biofilm wastewater treatment system.
The study’s central advance lies in turning a complex biofilm into a readable interaction map. Using samples collected along two rotating biological contactor trains, the team reconstructed a vast catalog of largely novel phages and plasmids, then linked them to recovered microbial genomes using Hi-C plus complementary in silico approaches. Hi-C proved especially powerful, nearly doubling phage–host detection beyond other methods combined and delivering the majority of plasmid–host linkages. The results revealed that up to 52% of phages could be linked to 56% of prokaryotes, while up to 70% of plasmids could be linked to 91% of prokaryotes. The networks were not random. Phage communities separated clearly between reactor stages, and plasmid profiles also shifted along the flow path, suggesting that microbial composition and biofilm structure shape where these elements persist. The biological consequences were equally striking. Phages carried and expressed auxiliary metabolic genes tied to carbohydrate metabolism and amino acid biosynthesis, implying that they may help augment host metabolism during infection. Plasmids, meanwhile, carried antibiotic resistance genes and virulence factors, some alongside conjugation genes, pointing to active routes for horizontal transfer. Together, the findings portray biofilms not as static microbial layers, but as dynamic gene-sharing ecosystems wired together by mobile DNA.
“This work helps make the invisible architecture of microbial ecosystems visible”, the study suggests. By physically linking mobile genetic elements to hosts rather than inferring relationships from sequence alone, the researchers provide a more direct view of how gene flow operates in engineered environments. The findings also highlight that phages and plasmids are not just passengers in wastewater biofilms—they may actively shape microbial turnover, metabolic function, and the circulation of adaptive traits. In that sense, the study offers both a technical advance and a new ecological lens for understanding biofilm stability.
The implications reach beyond wastewater treatment. A scalable framework for mapping phage– and plasmid–host networks could help scientists better track the spread of antibiotic resistance, identify microbial weak points in engineered systems, and design strategies to stabilize or optimize beneficial biofilms. It may also support broader environmental microbiome research in soils, marine systems, and other complex habitats where mobile genetic elements shape community function.
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References
DOI
10.1016/j.ese.2026.100683
Original Source URL
https://doi.org/10.1016/j.ese.2026.100683
Funding Information
Dr. Dou Wang and Dr. Xiaoqing Xu would like to thank The University of Hong Kong for the postdoctoral fellowship. Technical assistance from Ms. Vicky Fung is greatly appreciated. This work was financially supported by the General Research Fund (17212124) of Hong Kong.
About Environmental Science and Ecotechnology
Environmental Science and Ecotechnology (ISSN 2666-4984) is an international, peer-reviewed, and open-access journal published by Elsevier. The journal publishes significant views and research across the full spectrum of ecology and environmental sciences, such as climate change, sustainability, biodiversity conservation, environment & health, green catalysis/processing for pollution control, and AI-driven environmental engineering. The latest impact factor of ESE is 14.3, according to the Journal Citation ReportsTM 2024.