Genomic surveillance of SARS-CoV-2: a resource-efficient wastewater-based workflow

Area of Science:

• Environmental microbiology
• Genomics
• Epidemiology

Background:

• Large-scale clinical sequencing for SARS-CoV-2 variant detection is declining due to cost, threatening surveillance.
• Wastewater analysis offers an alternative for identifying viral mutations but is underexploited for diversity studies.
• Current wastewater virus concentration and purification methods require optimization.

Purpose of the Study:

• To develop and validate a workflow for comprehensive genomic monitoring of SARS-CoV-2 using wastewater.
• To assess the utility of wastewater sequencing for identifying viral diversity, mutations, and biogeographical trends.
• To provide an accessible complement to clinical surveillance for viral variant tracking.

Main Methods:

• Integration of a high-purity laboratory procedure with an information theory-based R package for genomic data analysis.
• Validation using wastewater samples from an urban node during different pandemic stages (early endemism and Omicron cosmopolitanism).
• Profiling of amino acid-level diversity and identification of single-nucleotide variants.

Main Results:

• Successful recovery of known SARS-CoV-2 diversity features and identification of clinically elusive mutations.
• Detection of spatial distribution signatures and location-specific mutation frequency differences, revealing biogeographical trends.
• Identification of hotspots for amino acid diversity in key functional regions like the receptor binding domain.

Conclusions:

• Wastewater analysis is a viable method for effective genomic monitoring of SARS-CoV-2.
• The proposed workflow offers an accessible tool for complementing clinical surveillance, particularly where patient-level sequencing is restricted.
• This approach enhances the ability to detect viral variants and understand their evolution and spread.