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Summary: 

This preprint describes a longitudinal study of ultra deep metagenomic sequencing of wastewater in Missouri that evaluates untargeted ultra deep metagenomic sequencing as a tool for comprehensive wastewater surveillance of viral pathogens. Following Missouri Wastewater Surveillance Program’s protocols, the study collected wastewater samples for 24 hrs each week from January 2024 to June of 2025 allowing for comparison between their samples and current surveillance methods. The study investigated different techniques for viral concentration and rRNA isolation using the first set of data from January 2024 - March 2024 comparing Ct values and found that no treatment reduced rRNA abundance in the samples.

After collecting data for 18 months, they used surveillance results from Missouri's wastewater surveillance program to evaluate whether the metagenomic method is comparable with current methods. They were able to detect the expected respiratory and Samples from this study allowed for detection of Influenza A subtype H5N1 which was not reported in standard surveillance. Using SARS-CoV-2, the authors found that with metagenomics the abundances and epidemiological trends were comparable to current methods. In the study they found that eukaryotic viruses were more abundant and less diverse than prokaryotic viruses, largely due to the greater than expected abundance of plant viruses. The high plant virus abundance was unexpected, but is consistent with previous work on wastewater surveillance.

Recommendation:

This preprint is one of the few longitudinal studies that evaluate the use of metagenomics for wastewater surveillance. The findings from this preprint are encouraging for the utilization of ultra deep metagenomics, however there are a few unclear points and limitations in the preprint that should be addressed and reviewed before publication. 

Major Concerns:

• The implications of low species assignment using GOTTCHA2 and selection for the low false positive method is unclear. The preprint states that on average only 3.9% (1.78%) of sequences were able to be quantified which is due to its low false positive rate. There is a clear explanation why GOTTCHA2 was chosen over other assembly methods. However, it's unclear why a low false positive rate was favored over the ability to classify reads, especially when applied to public health surveillance. 

  • To address this, the authors could include additional information in the discussion after paragraph 4 on their thought process of favoring assembly methods with low false positives over other methods that could assemble reads. 

  • If a secondary analysis is performed on this study’s data, performing a reference free secondary analysis on the unclassified reads by alternative methods (for example Kraken2 as mentioned in the preprint) might provide insightful information on the other 96% of reads that the methods used in this preprint did not utilize. 

Minor Concerns:

• It could be useful to know how many samples were used in the Qubit RNA High Sensitivity Assay. In the Library preparation and deep sequencing section of the methods, the preprint states "some samples were below the detection limit for this assay.”

  • To provide more clarity, the authors could consider adding the percentage or a specific count of how many samples were below the detection limit to provide additional clarity for readers. 

Suggestions:

• Expansion on the validation of metagenomics’ ability to detect epidemiological trends. It could be useful to include comparative data on how much the variability of groupings were associated with seasonality when calculated from methods typically used for wastewater surveillance (RT-PCR, RT-qPCR, or dPCR). This would provide additional clarity to readers of how well metagenomics can describe epidemiological trends in wastewater in comparison to current methods.

Competing interests

The author declares that they have no competing interests.

Use of Artificial Intelligence (AI)

The author declares that they did not use generative AI to come up with new ideas for their review.