PREreview of Untargeted longitudinal ultra deep metagenomic sequencing of wastewater provides a comprehensive readout of expected and unexpected viral pathogens

Summary

This study investigates whether untargeted ultra-deep metagenomic sequencing can provide comprehensive wastewater viral surveillance without targeted enrichment. Across 78 weekly samples collected from January 2024 through June 2025 with about 1.1 billion reads each, the authors detected expected enteric viruses and seasonal respiratory viruses, with SARS-CoV-2 metagenomic counts moderately correlating with digital PCR (R² = 0.416–0.471). They also identified unexpected signals, including H5N1 B3.13 (March–May 2024), influenza C dominance in winter 2023–24, and a brief hepatitis A surge, while plant viruses such as tomato brown rugose fruit virus dominated overall reads.

Major Revision

At approximately one billion reads per sample, the sequencing cost is likely very high, which may limit routine adoption of this approach by public health laboratories.

Recommendation: It would be helpful if the authors could report the projected sequencing cost per sample and briefly discuss cost considerations, including potential strategies to improve feasibility for public health laboratories

The methods are complex and span many sequential filtering and assembly steps, which makes the workflow difficult to follow.

Recommendation: Add a simple workflow diagram illustrating the key steps to improve clarity and reader understanding.

Minor Revision

Although the study is described as untargeted, the viral detection pipeline includes an initial reference-based filtering step using STAT against a predefined set of human virus families before assembly and classification.

Recommendation: It would be helpful to clarify in the manuscript that the approach is broad but reference-guided rather than fully untargeted, to prevent readers from interpreting the method as fully open-ended.

Some heatmaps and bar plots have small labels or unclear color scales, making them difficult to interpret.

Recommendation: Increase label sizes and clarify the color scales to make the figures easier to read

Overall Impression

This study addresses an important question: whether deep metagenomic sequencing can serve as a comprehensive alternative to targeted wastewater surveillance. The authors present a valuable dataset and demonstrate that this approach can detect both expected and unexpected pathogens. However, the manuscript would benefit from clearer discussion of methodological limitations and stronger validation of key findings. Overall, the results indicate that ultra-deep metagenomics can capture a broad range of viral pathogens, including low-abundance and clinically overlooked ones.

Competing interests

The author declares that they have no competing interests.

Use of Artificial Intelligence (AI)

The author declares that they used generative AI to come up with new ideas for their review.