Detection of norovirus epidemic genotypes in raw sewage using next generation sequencing

Abstract

Noroviruses are a leading cause of epidemic and pandemic acute gastroenteritis (AGE) worldwide, and contaminated food and water are important routes for its transmission. Raw sewage has been used for viral surveillance to monitor the emergence of new norovirus strains with the potential to cause epidemics. In this study, we investigated norovirus occurrence and norovirus RNA levels in 156 samples collected from May 2013 to May 2014, across three different stages (52 samples each) of a wastewater treatment plant (WWTP) in Rio de Janeiro, Brazil. We also explored norovirus GII diversity in raw sewage samples by next-sequencing generation (NGS). In addition, we examined norovirus prevalence and molecular epidemiology from acute gastroenteritis cases. Using RT-qPCR, norovirus GI and GII was detected in 38.5% and 96.1% of raw sewage samples, 40.4% and 96.1% of primary effluent samples and 1.9% and 5.8% of final effluent samples, respectively. Norovirus RNA levels varied from 4 to 6.2 log10 genome copies per litre (gc L−1) for GI and from 4.4 to 7.3 log10 gc L−1 for GII. Using MiSeq NGS, we identified 13 norovirus genotypes over the one-year period, with six dominant capsid genotypes, including GII.4, GII.17, GII.5, GII.2, GII.3 and GII.1. GII.4 noroviruses were the most prevalent in wastewater samples (68.5%), and a similar trend was observed in AGE cases (71%). The emergent GII.17 was the second most prevalent genotype (14.3%) identified in the raw sewage samples, however, it was not detected in clinical cases. Due to the high burden of norovirus outbreaks and the lack of vaccine and antiviral drugs, it is essential to understand the genotypic diversity of norovirus at the population level. Complementary data obtained from both clinical and environmental (sewage) samples proved to be an effective strategy to monitor the circulation and emergence of norovirus epidemic genotypes. Keywords: Noroviruses, Wastewater, Environmental surveillance, Next-generation sequencing, Phylogenetic analysis