Deep Sequencing of Norovirus Genomes Defines Evolutionary Patterns in an Urban Tropical Setting

UNLABELLED Norovirus is a highly transmissible infectious agent that causes epidemic gastroenteritis in susceptible children and adults. Norovirus infections can be severe and can be initiated from an exceptionally small number of viral particles. Detailed genome sequence data are useful for tracking norovirus transmission and evolution. To address this need, we have developed a whole-genome deep-sequencing method that generates entire genome sequences from small amounts of clinical specimens. This novel approach employs an algorithm for reverse transcription and PCR amplification primer design using all of the publically available norovirus sequence data. Deep sequencing and de novo assembly were used to generate norovirus genomes from a large set of diarrheal patients attending three hospitals in Ho Chi Minh City, Vietnam, over a 2.5-year period. Positive-selection analysis and direct examination of protein changes in the virus over time identified codons in the regions encoding proteins VP1, p48 (NS1-2), and p22 (NS4) under positive selection and expands the known targets of norovirus evolutionary pressure. IMPORTANCE The high transmissibility and rapid evolutionary rate of norovirus, combined with a short-lived host immune responses, are thought to be the reasons why the virus causes the majority of pediatric viral diarrhea cases. The evolutionary patterns of this RNA virus have been described in detail for only a portion of the virus genome and never for a virus from a detailed urban tropical setting. We provide a detailed sequence description of the noroviruses circulating in three Ho Chi Minh City hospitals over a 2.5-year period. This study identified patterns of virus change in known sites of host immune response and identified three additional regions of the virus genome under selection that were not previously recognized. In addition, the method described here provides a robust full-genome sequencing platform for community-based virus surveillance.