Population-level genomic surveillance of human norovirus using wastewater-based whole-genome sequencing

Abstract

ABSTRACT Wastewater-based surveillance has garnered increasing attention as a valuable approach for capturing community-level infection dynamics that are often difficult to detect through clinical reporting systems alone. In this study, we analyzed human norovirus genotype distributions and whole-genome-level variations in wastewater samples collected in Gwangju, Korea. These results were interpreted in conjunction with a documented foodborne outbreak to evaluate the epidemiological relevance of wastewater-based monitoring. Human norovirus concentrations were quantified using TaqMan Array Card–based RT-qPCR, and whole-genome next-generation sequencing (NGS) was performed to obtain viral read counts and reads per kilobase per million filtered reads values. Overall, strong correlations were observed between RT-qPCR-based concentrations and NGS-derived metrics. Genotype dynamics varied among wastewater treatment plants, reflecting differences in catchment size and local population characteristics. In particular, the relative abundance of GII.17[P17] increased during epidemiological week 50, temporally coinciding with a documented local foodborne outbreak. Variant analysis revealed that wastewater samples exhibited mixed nucleotide patterns, with multiple alleles coexisting at varying relative frequencies rather than fixed substitutions. Notably, some nonsynonymous variants detected in clinical samples were also observed in wastewater samples collected surrounding the outbreak period. Together, these findings demonstrate that wastewater-based whole-genome surveillance can capture both genotype-level shifts and nucleotide-level dynamics at the population scale, highlighting its potential as a complementary tool for monitoring community-level norovirus circulation and outbreak-associated genotype dynamics. IMPORTANCE Wastewater-based surveillance is increasingly recognized as a promising approach for capturing community-level infection dynamics that are often missed by clinical surveillance. In this study, we applied whole-genome sequencing to wastewater samples collected in Gwangju, South Korea, to comprehensively characterize human norovirus genotype distributions and genetic variation. Distinct genotype patterns were observed across wastewater treatment plants, reflecting differences in catchment population size and local characteristics. Notably, an increase in the GII.17[P17] genotype detected in wastewater coincided with a foodborne outbreak investigated in Gwangju, demonstrating the potential of wastewater surveillance to reflect ongoing community transmission and emerging outbreak-associated genotypes. In addition, wastewater samples contained diverse and coexisting genetic variants, capturing population-level viral diversity and evolutionary dynamics that are not readily detected through clinical surveillance alone. These findings highlight the value of wastewater-based whole-genome surveillance for monitoring community-level viral circulation and support its integration as a complementary strategy to existing clinical surveillance systems. Wastewater-based surveillance is increasingly recognized as a promising approach for capturing community-level infection dynamics that are often missed by clinical surveillance. In this study, we applied whole-genome sequencing to wastewater samples collected in Gwangju, South Korea, to comprehensively characterize human norovirus genotype distributions and genetic variation. Distinct genotype patterns were observed across wastewater treatment plants, reflecting differences in catchment population size and local characteristics. Notably, an increase in the GII.17[P17] genotype detected in wastewater coincided with a foodborne outbreak investigated in Gwangju, demonstrating the potential of wastewater surveillance to reflect ongoing community transmission and emerging outbreak-associated genotypes. In addition, wastewater samples contained diverse and coexisting genetic variants, capturing population-level viral diversity and evolutionary dynamics that are not readily detected through clinical surveillance alone. These findings highlight the value of wastewater-based whole-genome surveillance for monitoring community-level viral circulation and support its integration as a complementary strategy to existing clinical surveillance systems.