Assessing different next-generation sequencing technologies for wastewater-based epidemiology

Area of Science:

• Environmental microbiology
• Public health surveillance
• Genomic epidemiology

Background:

• Wastewater-based epidemiology (WBE) is a valuable tool for population-level disease monitoring, particularly for COVID-19.
• Next-generation sequencing (NGS) is crucial for identifying and quantifying SARS-CoV-2 strains in wastewater.
• The choice of sequencing technology impacts data quality, timeliness, and utility in WBE.

Purpose of the Study:

• To systematically benchmark different NGS technologies for SARS-CoV-2 surveillance in wastewater.
• To evaluate the trade-offs between sequencing platforms regarding cost, speed, and accuracy of variant detection.

Main Methods:

• Comparative analysis of sequencing data from Illumina NovaSeq 6000, Element Aviti, and Oxford Nanopore Technologies (ONT) R9.4.1 MinION and Flongle flow cells.
• Utilized a time series of wastewater samples from Swiss treatment plants and spike-in experiments.
• Assessed accuracy of viral variant abundance estimates and impact of sequencing runtime.

Main Results:

• All tested sequencing technologies enabled SARS-CoV-2 variant tracking.
• ONT Nanopore sequencing exhibited higher error rates, affecting variant abundance accuracy but showing overall trend concordance.
• ONT Nanopore sequencing runtime could be reduced to five hours without significant impact on variant estimate quality.

Conclusions:

• SARS-CoV-2 variant tracking in wastewater is feasible across multiple NGS platforms.
• ONT Nanopore sequencing offers a rapid option, though with potential accuracy trade-offs compared to Illumina.
• Technology selection for WBE should consider specific project needs regarding cost, timeliness, and required accuracy.