Viruses in wastewater: Silent drivers of pollution removal and antibiotic resistance

These findings suggest that current monitoring strategies, which rely heavily on bacterial indicators alone, may miss critical viral-driven risks and opportunities for safer wastewater reuse.

Viruses are among the most abundant biological entities in engineered water systems, including wastewater treatment plants (WWTPs). They interact intimately with microbial hosts, altering microbial metabolism, community structure, and ecological functions. In recent years, wastewater-based surveillance has gained attention for tracking pathogens and public health threats. However, most monitoring frameworks focus on a narrow set of bacterial indicators, such as Escherichia coli, while largely ignoring viruses and their complex interactions with pathogens. This gap limits our understanding of how viral communities respond to treatment processes and how they may influence health risks in reclaimed water systems. Based on these challenges, deeper investigation into virus–host dynamics across entire treatment processes is urgently needed.

A study (DOI:10.48130/biocontam-0025-0015) published in Biocontaminant on 04 December 2025 by Shu-Hong Gao’s team, Harbin Institute of Technology, reveals that persistent viral communities in wastewater treatment plants play a critical dual role in pollutant removal and antibiotic resistance dissemination, highlighting the urgent need to incorporate virus-based indicators and viral functional monitoring into wastewater treatment optimization and public health risk assessment.

Using a full-scale, process-wide metagenomic workflow, researchers analyzed 28 samples spanning influent-to-effluent units across three wastewater treatment configurations (AAO, AAO-MBR, and MBR), recovering 29,708, 14,138, and 13,961 high-quality viral contigs (≥5 kb) from the respective systems. These contigs were subjected to family-level taxonomic profiling, diversity and abundance analyses across treatment units and matrices (wastewater versus sludge), functional annotation of virus-encoded auxiliary metabolic genes (AMGs), and machine-learning–based virus–host prediction complemented by metagenome-assembled genomes (MAGs) and pathogen–virus co-occurrence networks. This integrated analysis identified 99 viral families across the full treatment continuum, with several taxa—most notably Peduoviridae and Casjensviridae—showing persistent, high prevalence from influent to effluent, demonstrating that viral populations are not confined to activated sludge but persist throughout treatment. Viral abundance and diversity were highest in AAO systems and in wastewater phases relative to sludge, while comparable Shannon diversity across plants and slightly elevated effluent diversity suggested convergent community assembly under shared treatment objectives. Community composition differed significantly among processes, with Gracegardnervirinae, Straboviridae, and Peduoviridae dominating AAO, AAO-MBR, and MBR, respectively, consistent with selective pressures imposed by treatment configurations. Importantly, viral dynamics did not mirror those of traditional indicators such as Escherichia coli, but instead closely tracked opportunistic pathogens Pseudomonas aeruginosa and Aeromonas caviae, supporting their potential as alternative indicators of virus-associated risk. Functional analyses revealed 117 AMGs across 12 metabolic pathways, enriched in wastewater and particularly active during biological treatment stages, implicating a “double-edged” role in enhancing carbohydrate, amino acid, and xenobiotic metabolism for pollutant removal while potentially facilitating the dissemination of antibiotic resistance genes via phage-mediated processes. Host prediction further identified Pseudomonadota as the predominant viral host phylum, enriched for multidrug-resistant pathogens, underscoring wastewater systems as hotspots of microbial evolution and highlighting the need for routine viral metagenomic monitoring and targeted process optimization to mitigate viral and antimicrobial-resistance risks in reclaimed water.

These findings have immediate implications for wastewater management and public health. They demonstrate that viruses should be integrated into routine biological monitoring frameworks, alongside bacteria, to better assess treatment performance and health risks. Identifying persistent viral–pathogen pairs offers new bioindicators for evaluating system efficiency and early warning signals for emerging threats. Moreover, understanding viral metabolic functions opens opportunities to harness beneficial viruses to enhance pollutant removal, while carefully managing the risks of resistance spread.

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References

DOI

10.48130/biocontam-0025-0015

Original Source URL

https://doi.org/10.48130/biocontam-0025-0015

Funding information

The study was financially supported by the National Natural Science Foundation of China (grants No. 52293443, 52321005, 52091545, and 52230004), the Natural Science Foundation of Guangdong Basic and Applied Basic Research Foundation (Grant No. 2024A1515010085), Shenzhen Science and Technology Program (Grant Nos GXWD20231127195344001 and JCYJ20241202123735045), and Shenzhen Overseas High-level Talents Research Startup Program (Grant No. 20200518750C).

About Biocontaminant

Biocontaminant is a multidisciplinary platform dedicated to advancing fundamental and applied research on biological contaminants across diverse environments and systems. The journal serves as an innovative, efficient, and professional forum for global researchers to disseminate findings in this rapidly evolving field.

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