Mobile genetic elements (MGEs) such as bacteriophages and plasmids profoundly shape microbial community structure and drive horizontal gene transfer across ecosystems. Wastewater treatment systems, with their high cell densities, steep physicochemical gradients and close cell-to-cell contact, act as hotspots for MGE proliferation and exchange, yet the in situ assembly dynamics and host interaction networks of these elements have remained largely unresolved because conventional methods fail to establish direct MGE–host linkages in complex matrices. Here we show that an integrated framework combining metagenomics, metatranscriptomics, metaviromics, and Hi-C proximity ligation sequencing enables the efficient elucidation of DNA phage and plasmid assembly dynamics alongside their host interaction networks in biofilms. We reconstructed 17,672 viral operational taxonomic units and 11,454 high-confidence non-redundant plasmids, and established 529 phage–host and 5739 plasmid–host associations that link up to 52% of phages to 56% of prokaryotes and 70% of plasmids to 91% of prokaryotes, respectively. Hi-C substantially expanded and refined these networks, revealing taxon-specific and multi-host patterns. Host community composition and biofilm architecture emerge as primary drivers of MGE occurrence and abundance along the reactor flow path. Expression of auxiliary metabolic genes, antibiotic resistance genes and virulence factors carried by these MGEs demonstrates their active roles in modulating biogeochemical cycles and maintaining ecosystem stability. These findings establish a scalable, cultivation-independent framework for deciphering MGE–host networks in complex microbial ecosystems, and underscore the power of Hi-C sequencing to transform our mechanistic understanding of gene flow, resistome dissemination, and ecological resilience in engineered and natural microbiomes.

Wastewater treatment plants (WWTPs) represent one of biotechnology's largest and most critical applications, playing a pivotal role in environmental protection and public health. In WWTPs, activated sludge (AS) plays a major role in removing contaminants and pathogens from wastewater. While metagenomics has advanced our understanding of microbial communities, it still faces challenges in revealing the genomic heterogeneity of cells, uncovering the microbial dark matter, and establishing precise links between genetic elements and their host cells as a bulk method. These issues could be largely resolved by single-cell sequencing, which can offer unprecedented resolution to show the unique genetic information. Here we show the high-throughput single-cell sequencing to the AS microbiome. The single-amplified genomes (SAGs) of 15,110 individual cells were clustered into 2,454 SAG bins. We find that 27.5% of the genomes in the AS microbial community represent potential novel species, highlighting the presence of microbial dark matter. Furthermore, we identified 1,137 antibiotic resistance genes (ARGs), 10,450 plasmid fragments, and 1,343 phage contigs, with shared plasmid and phage groups broadly distributed among hosts, indicating a high frequency of horizontal gene transfer (HGT) within the AS microbiome. Complementary analysis using 1,529 metagenome-assembled genomes from the AS samples allowed for the taxonomic classification of 98 SAG bins, which were previously unclassified. Our study establishes the feasibility of single-cell sequencing in characterizing the AS microbiome, providing novel insights into its ecological dynamics, and deepening our understanding of HGT processes, particularly those involving ARGs. Additionally, this valuable tool could monitor the distribution, spread, and pathogenic hosts of ARGs both within AS environments and between AS and other environments, which will ultimately contribute to developing a health risk evaluation system for diverse environments within a One Health framework.

Antibiotic resistance has been recognized as a major challenge worldwide for humans. “One Health” has been recognized as a key concept for containment of antibiotic resistance. Under the framework, the role of the environment in the development of antibiotic resistance genes (ARGs) has become increasingly obvious. Despite numerous efforts, response to antibiotic resistance is considered to be inadequate, which is probably due to the lack of a clear roadmap. Here, we propose a “One Health” roadmap to combat antibiotic resistance in the environment through (1) understanding environmental resistome. The environmental gene pool has long been recognized as the single largest reservoir of both known and novel ARGs. (2) Standardizing ARG quantification. Systematic joint efforts based on standardized quantification are urgently needed to understand the true tempospatial profiles of the environmental resistome. (3) Identifying mechanisms of resistome development. Horizontal gene transfer and co-selection have been recognized as the two main mechanisms contributing to the environmental resistome. (4) Establishing a risk-assessment framework. The first critical step for large-scale cost-effective targeted ARG management in the environment is the risk assessment to identify the priority ARGs for control. (5) Formulating regulatory standards. By correlating the environmental ARG profile with public health, we may identify the indicator ARGs that can be integrated into current environmental quality standards. (6) Developing control strategies. Systematic analysis of available control technologies is required to identify the most feasible ones to curtail the spread of ARGs in the environment. The proposed roadmap under the “One Health” framework provides a guide to tackle antibiotic resistance in the environment.