Amplicon-Based High-Throughput Sequencing Method for Genotypic Characterization of Norovirus in Oysters.

Norovirus is a highly diverse RNA virus often implicated in foodborne outbreaks, particularly those associated with shellfish. Shellfish are filter feeders, and when harvested in bays exposed to wastewater overflow or storm overflows, they can harbor various pathogens, including human-pathogenic viruses. The application of Sanger or amplicon-based high-throughput sequencing (HTS) technologies to identify human pathogens in shellfish faces two main challenges: (i) distinguishing multiple genotypes/variants in a single sample and (ii) low concentrations of norovirus RNA. Here, we assessed the performance of a novel norovirus capsid amplicon HTS method. We generated a panel of spiked oysters containing various norovirus concentrations with different genotypic compositions. Several DNA polymerases and reverse transcriptases (RTs) were compared, and performance was evaluated based on (i) the number of reads passing quality filters per sample, (ii) the number of correct genotypes identified, and (iii) the sequence identity of outputs compared to Sanger-derived sequences. A combination of the reverse transcriptase LunaScript and the DNA polymerase AmpliTaq Gold provided the best results. The method was then employed, and compared with Sanger sequencing, to characterize norovirus populations in naturally contaminated oysters. IMPORTANCE While foodborne outbreaks account for approximately 14% of norovirus cases (L. Verhoef, J. Hewitt, L. Barclay, S. Ahmed, R. Lake, A. J. Hall, B. Lopman, A. Kroneman, H. Vennema, J. Vinjé, and M. Koopmans, Emerg Infect Dis 21:592-599, 2015), we do not have standardized high-throughput sequencing methods for genotypic characterization in foodstuffs. Here, we present an optimized amplicon high-throughput sequencing method for the genotypic characterization of norovirus in oysters. This method can accurately detect and characterize norovirus at concentrations found in oysters grown in production areas impacted by human wastewater discharges. It will permit the investigation of norovirus genetic diversity in complex matrices and contribute to ongoing surveillance of norovirus in the environment.

Benchmarking Bioinformatic Tools for Amplicon-Based Sequencing of Norovirus.

In order to survey noroviruses in our environment, it is essential that both wet-lab and computational methods are fit for purpose. Using a simulated sequencing data set, denoising-based (DADA2, Deblur and USEARCH-UNOISE3) and clustering-based pipelines (VSEARCH and FROGS) were compared with respect to their ability to represent composition and sequence information. Open source classifiers (Ribosomal Database Project [RDP], BLASTn, IDTAXA, QIIME2 naive Bayes, and SINTAX) were trained using three different databases: a custom database, the NoroNet database, and the Human calicivirus database. Each classifier and database combination was compared from the perspective of their classification accuracy. VSEARCH provides a robust option for analyzing viral amplicons based on composition analysis; however, all pipelines could return OTUs with high similarity to the expected sequences. Importantly, pipeline choice could lead to more false positives (DADA2) or underclassification (FROGS), a key aspect when considering pipeline application for source attribution. Classification was more strongly impacted by the classifier than the database, although disagreement increased with norovirus GII.4 capsid variant designation. We recommend the use of the RDP classifier in conjunction with VSEARCH; however, maintenance of the underlying database is essential for optimal use. IMPORTANCE In benchmarking bioinformatic pipelines for analyzing high-throughput sequencing (HTS) data sets, we provide method standardization for bioinformatics broadly and specifically for norovirus in situations for which no officially endorsed methods exist at present. This study provides recommendations for the appropriate analysis and classification of norovirus amplicon HTS data and will be widely applicable during outbreak investigations.

High Throughput Sequencing for the Detection and Characterization of RNA Viruses.

This review aims to assess and recommend approaches for targeted and agnostic High Throughput Sequencing of RNA viruses in a variety of sample matrices. HTS also referred to as deep sequencing, next generation sequencing and third generation sequencing; has much to offer to the field of environmental virology as its increased sequencing depth circumvents issues with cloning environmental isolates for Sanger sequencing. That said however, it is important to consider the challenges and biases that method choice can impart to sequencing results. Here, methodology choices from RNA extraction, reverse transcription to library preparation are compared based on their impact on the detection or characterization of RNA viruses.