Next-Generation Sequencing Analysis of the Diversity of Human Noroviruses in Japanese Oysters

Abstract

To obtain detailed information on the diversity of infectious norovirus in oysters (Crossostrea gigas), oysters obtained from fish producers at six different sites (sites A, B, C, D, E, and F) in Japan were analyzed once a month during the period spanning October 2015–February 2016. To avoid false-positive polymerase chain reaction (PCR) results derived from noninfectious virus particles, samples were pretreated with RNase before reverse transcription-PCR (RT-PCR). RT-PCR products were subjected to next-generation sequencing to identify norovirus genotypes in oysters. As a result, all GI genotypes were detected in the investigational period. The detection rate and proportion of norovirus GI genotypes differed depending on the sampling site and month. GII.3, GII.4, GII.13, GII.16, and GII.17 were detected in this study. Both the detection rate and proportion of norovirus GII genotypes differed depending on the sampling site and month. In total, the detection rate and proportion of GII.3 were highest from October to December among all detected genotypes. In January, the detection rates of GII.4 and GII.17 reached the same level as that of GII.3. The proportion of GII.17 was relatively lower from October to December, whereas it was the highest in January. To our knowledge, this is the first investigation on noroviruses in oysters in Japan, based on a method that can distinguish their infectivity.

Introduction

Noroviruses are members of the Caliciviridae family and are the major cause of viral gastroenteritis in humans worldwide (EFSA, 2011). Human sewage disposal contributes greatly to contamination of the environment with noroviruses (Maalouf et al., 2010). Noroviruses are transported to rivers and seas through heavy rains or melting snow (Gentry et al., 2009; Wyn-Jones et al., 2011), which may result in the contamination of aquatic environments. As filter feeders, shellfish are able to readily accumulate contaminants such as bacteria and viruses from the surrounding water (Oliveira et al., 2011). Shellfish are known as vectors for noroviruses and are considered a high-risk food for norovirus outbreaks (Lees, 2000).

Reverse transcription-polymerase chain reaction (RT-PCR) is the most commonly applied method for the detection of noroviruses, since there is no commonly available in vitro cell-culture system or small-animal model. Although this method is rapid and highly sensitive, it simply detects the presence of norovirus RNA and is thus unable to distinguish infectious from noninfectious viral particles (Baert et al., 2008; Lowther et al., 2010). When applying conventional RT-PCR for the detection and quantification of noroviruses in oysters, the health risk presented by the oysters may be overestimated owing to the detection of noninfectious viral particles (Uema, 2016). Nuanualsuwan and Cliver (2002) first proposed the elimination of false positives by simultaneous use of protease K (PK) and RNase before the RT reaction to digest viral particles and RNAs derived from noninfectious viruses. This enzymatic pretreatment has been further considered by other researchers (Baert et al., 2008; Lamhoujeb et al., 2008) and was applied in an inactivation study of norovirus against various interventions (Baert et al., 2008; Topping et al., 2009; Ye et al., 2014). Ye et al. (2014) pretreated samples with RNase and evaluated the inactivation of human norovirus in contaminated oysters and clams by high hydrostatic pressure.

Meanwhile, several studies have applied next-generation sequencing (NGS) in an attempt to describe the full range of microbes present in foods, as well as to understand temporal microflora changes during various steps of procedures (O'Sullivan, 2000; Lusk et al., 2012). We were the first to report the application of NGS to investigate norovirus diversity in shellfish collected from coastal sites in Japan from 2013 to 2014, and we revealed the diversity of norovirus genotypes present in shellfish (Imamura et al., 2016a). In this previous study, however, we found insufficient information regarding infectious noroviruses associated with oysters. Thus, this study aimed to obtain more detailed information on the diversity of infectious norovirus in oysters. For this reason, we combined enzymatic pretreatment of samples with RNase and NGS to investigate infectious norovirus diversity in oysters.

Materials and Methods

Oysters

Oysters (Crossostrea gigas) were purchased from fish producers at six different main production sites in Japan (designated sites A, B, C, D, E, and F) once a month during the time spanning October 2015–February 2016. The fish producers at sites A, B, D, E, and F supplied 30 aquacultured oysters, and the fish producer at site C supplied 60 aquacultured oysters in total.

Sample preparation of viral suspensions and enzymatic pretreatment

The oysters were refrigerated (4°C) and sent to the laboratory within 24 h after sampling. For the preparation of viral suspensions, oysters were shucked and the digestive diverticula were collected by dissection on the day of their arrival at the laboratory. Three dissected digestive diverticula were combined into one sample so that the combined mass was greater than 2.0 ± 0.2 g, as described previously (ISO/TS 15216-1, 2013). The combined sample was homogenized in 18 mL of phosphate-buffered saline (PBS) solution (without magnesium and calcium) (Le Guyader et al., 1996). The homogenates were incubated with α-amylase (Wako, Tokyo, Japan) at a final concentration of 2.5 mg/mL for 1 h at 37°C with shaking by vortex every 15 min. For concentration of viral particles derived from the digestive diverticula, the method provided by the Japanese Committee for Standardization of Virus Detection in Food (2010) was used. In brief, after 20 min centrifugation at 8000 × g, the supernatant was recovered. To concentrate the virus, polyethylene glycol 6000 (Sigma-Aldrich) and sodium chloride (Wako, Tokyo, Japan) were added to a final concentration of 12% and 5.8%, respectively. After 18 h of incubation at 4°C, the supernatant was centrifuged at 8000 × g for 20 min. After removing the supernatant, the pellet was resuspended in 400 μL of PBS (containing 0.5% Zwittergent 3–14 detergent) (Merck, Frankfurt, Germany). Fourteen units of RNase ONE™ ribonuclease (Promega, Wisconsin) and × 10 reaction mixture were added to 70 μL of the resulting viral suspension, and the resulting 100 μL mixture was incubated at 37°C for 1 h (Topping et al., 2009). The resulting enzyme-treated virus suspension was added to 100 μL of PBS(−) and was subsequently used for RNA extraction.

RNA extraction and reverse transcription

Viral RNA was extracted from 200 μL of viral suspension, using a High-Pure RNA Kit (Roche diagnostics, Tokyo, Japan) with recombinant DNase I (Roche diagnostics, Tokyo, Japan) according to the manufacturer's instructions, with the following modification: instead of poly (A) carrier RNA in the kit component, 8 μL of MS2 RNA (Roche diagnostics) was added to 400 μL of the binding buffer, since poly (A) carrier RNA will be able to compete with Oligo dT primers. First-strand cDNA synthesis was performed using the High-Capacity cDNA Reverse Transcription Kit (Life technologies, Tokyo, Japan). To avoid detection of reverse transcripts present owing to fragmented genomic DNA (thus noninfective), Oligo dT primers were used for the reverse transcription.

NGS analysis of the capsid N-terminal Shell (N/S) region of VP1 gene by Illumina MiSeq

To amplify the partial capsid N/S region of noroviruses by RT-PCR, primers were prepared in accordance with previous reports (Imamura et al., 2016a, 2016b). The PCR protocol was carried out in an Applied Biosystems Veriti 96 Well Thermal Cycler (Applied Biosystem, CA) as follows: an initial incubation for 3 min at 94°C, followed by 40 cycles of 94°C for 60 s, 50°C for 60 s, and 72°C for 2 min, with an additional 15 min elongation step at 72°C after the last cycle. This PCR procedure was repeated using internal primers with an adaptor sequence for MiSeq sequencing by nested PCR. Following the purification and amplification of the PCR products using AMPure XP beads (Beckman Coulter, CA), the concentration of the nested-PCR products was determined using an Agilent 2200 TapeStation System (Agilent Technologies Japan Ltd., Tokyo, Japan). Amplicons were diluted and pooled to generate a mixture containing an equimolar representation of each sample. Pooled amplicons were purified using a QIAquick PCR Purification Kit (Qiagen, CA) and sequenced using the Illumina MiSeq (Illumina K.K.), with 300-base paired-end reads to ensure that the average number of reads per sample ranged from 200,000 to 400,000 (96 samples/RUN). All kits were used according to the manufacturer's instructions. Consequently, the average length of reads obtained/sample was 88 Mbp (minimum; 57 Mbp: maximum; 135 Mbp). The average number of reads obtained/sample was 291,917 (minimum; 190,716: maximum; 449,514).

Read mapping for genotyping of noroviruses

The paired-end reads from MiSeq were adaptor- and quality-trimmed, and read pairs were assembled into consensus sequences, using FastqJoin version 1.1.2-806 (http://code.google.com/p/ea-utils/wiki/FastqJoin). Resultant reads were mapped against reference sequences using Burrows–Wheeler Aligner version 0.7.10 (http://bio-bwa.sourceforge.net), and output alignment data were sorted using SAMtools version 1.2 (www.htslib.org/man/samtools). The number of reads mapped against each reference sequence was counted with a custom script. The GenBank accession numbers of genes for read mappings used in this article are in accordance with those of previous reports (Imamura et al., 2016a, b).

To calculate the proportion of each genotype, the number of reads mapped against each reference was divided by the total reads obtained.

Quantification of norovirus GI and GII by real-time PCR

The samples that were positive for the partial capsid N/S region of noroviruses by RT-PCR were subjected to real-time PCR to quantify norovirus capsid genes, using Eagle Taq Master Mix with ROX. Primers for GI were as follows: 5′-CGY TGG ATG CGN TTY CAT GA-3′ (COG1F; sense) (Kageyama et al., 2003) and 5′-CTT AGA CGC CAT CAT CAT TYA C-3′ (COG1R; antisense) (Kageyama et al., 2003). Primers for GII were 5′-CAR GAR BCN ATG TTY AGR TGG ATG AG-3′ (COG2F; sense) (Kageyama et al., 2003), 5′-TTT GAG TCC ATG TAC AAG TGG ATG CG −3′ (ALPF; Sense) (JMHLW, 2007), and 5′-TCG ACG CCA TCT TCA TTC ACA −3′ (COG2R; antisense) (Kageyama et al., 2003). The Taq Man probes for GI were 5′-FAM-AGA TYG CGA TCY CCT GTC CA-TMRA-3′ (RING1-TP(a)) (Kageyama et al., 2003) and 5′-FAM-AGA TCG CGG TCT CCT GTC CA-TMRA-3′ (RING1-TP(b) (Kageyama et al., 2003). The Taq Man probe for GII was 5′-FAM-TGG GAG GGS GAT CGC GAT CGC RATCT-TMRA −3′ (RING2AL-TP) (JMHLW, 2007). The real-time PCR protocol included incubation for 2 min at 50°C and then 10 min at 95°C and 45 cycles of 95°C for 15 s and 56°C for 60 s. In each operation, GI- or GII-specific standard curve was generated by a 10-fold serial dilution (10⁷ to 10¹ copies) of GI or GII cDNA plasmids. Plasmid standards containing PCR products of the ORF1-ORF2 junction were prepared with strains SzUG1 and U201 with primer sets G1FF-G1SKR and G2FB-G2SKR, respectively. When the R² value was over 0.990, the real-time PCR procedure was regarded as successful. Genome copy number was calculated as genome copy number per one gram of digestive diverticula. Average genome copy number shown in Tables 1 and 2 are expressed as average genome copy numbers of positive samples.

Table 1.

Detection Rate and Proportion of Norovirus GI Genotypes in Japanese Oysters

			No. positive for GI (%) ^a /average genome copy no ^b
		Genogroups	No. positive samples (%) ^d /Proportion ^e
Sites	n/month	Genotypes ^c	October	November	December	January	February	Total
A	10	GI	0 (0.0)	0 (0.0)	2 (20.0)/108.5	1 (10.0)/448.8	0 (0.0)	3 (6.0)/221.9
		GI.1			2 (20.0)/20.16	1 (10.0)/13.36		3 (6.0)
		GI.2			2 (20.0)/54.16	1 (10.0)/68.44		3 (6.0)
		GI.3			2 (20.0)/0.36			2 (4.0)
		GI.4			2 (20.0)/0.05	1 (10.0)/≤0.01		3 (6.0)
		GI.5			1 (10.0)/≤0.01			1 (2.0)
		GI.6			2 (20.0)/20.32	1 (10.0)/13.35		3 (6.0)
		GI.8						0 (0.0)
		GI.9			1 (10.0)/≤0.01			1 (2.0)
B	10	GI	1 (10.0)/40.0	0 (0.0)	0 (0.0)	0 (0.0)	0 (0.0)	1 (2.0)/40.0
		GI.1	1 (10.0)/≤0.01					1 (2.0)
		GI.2	1 (10.0)/≤0.01					1 (2.0)
		GI.3	1 (10.0)/99.99					1 (2.0)
		GI.4	1 (10.0)/≤0.01					1 (2.0)
		GI.5						0 (0.0)
		GI.6	1 (10.0)/≤0.01					1 (2.0)
		GI.8	1 (10.0)/≤0.01					1 (2.0)
		GI.9						0 (0.0)
C	20	GI	0 (0.0)	0 (0.0)	0 (0.0)	0 (0.0)	0 (0.0)	0 (0.0)
		GI.1						0 (0.0)
		GI.2						0 (0.0)
		GI.3						0 (0.0)
		GI.4						0 (0.0)
		GI.5						0 (0.0)
		GI.6						0 (0.0)
		GI.8						0 (0.0)
		GI.9						0 (0.0)
D	10	GI	0 (0.0)	0 (0.0)	0 (0.0)	0 (0.0)	0 (0.0)	0 (0.0)
		GI.1						0 (0.0)
		GI.2						0 (0.0)
		GI.3						0 (0.0)
		GI.4						0 (0.0)
		GI.5						0 (0.0)
		GI.6						0 (0.0)
		GI.8						0 (0.0)
		GI.9						0 (0.0)
E	10	GI	2 (20.0)/256.7	0 (0.0)	0 (0.0)	0 (0.0)	0 (0.0)	2 (4.0)/256.7
		GI.1	2 (20.0)/≤0.01					2 (4.0)
		GI.2	1 (10.0)/≤0.01					1 (2.0)
		GI.3	2 (20.0)/99.99					2 (4.0)
		GI.4						0 (0.0)
		GI.5						0 (0.0)
		GI.6	1 (10.0)/≤0.01					1 (2.0)
		GI.8						0 (0.0)
		GI.9						0 (0.0)
F	10	GI	1 (10.0)/878.6	0 (0.0)	2 (20.0)/110.1	0 (0.0)	0 (0.0)	3 (6.0)/366.2
		GI.1			2 (20.0)/99.99			2 (4.0)
		GI.2	1 (10.0)/≤0.01		2 (20.0)/≤0.01			3 (6.0)
		GI.3	1 (10.0)/99.99					1 (2.0)
		GI.4						0 (0.0)
		GI.5						0 (0.0)
		GI.6	1 (10.0)/≤0.01					1 (2.0)
		GI.8						0 (0.0)
		GI.9						0 (0.0)

Number of GI-positive samples were demonstrated. Positive rate was in bracket.

Average genome copy number of GI-positive samples were demonstrated.

GI.7 was abbreviated from the Table, since there were no positive samples for these genotypes.

Number of positive samples for each genotype were demonstrated. Positive rate was in bracket.

To calculate the proportion of each genotype, the number of reads mapped against each reference was divided by the total reads obtained. Proportion less than 0.01 is represented as “≤0.01”.

Table 2.

Detection Rate and Proportion of Norovirus GII Genotypes in Japanese Oysters

			No. positive for GII (%) ^a /average genome copy no ^b
		Genogroups	No. positive samples (%) ^d /proportion ^e
Sites	n/month	Genotypes ^c	October	November	December	January	February	Total
A	10	GII	7 (70.0)/439.9	6 (60.0)/97.7	0 (0.0)^* ^f	0 (0.0)	0 (0.0)	13 (26.0)/282.0
		GII.3	7 (70.0)/99.99	6 (60.0)/99.99				13 (26.0)
		GII.4	2 (50.0)/≤0.01	3 (30.0)/≤0.01				5 (10.0)
		GII.13	0 (0.0)	0 (0.0)				0 (0.0)
		GII.16	0 (0.0)	0 (0.0)				0 (0.0)
		GII.17	6 (60.0)/≤0.01	4 (40.0)/≤0.01				10 (20.0)
B	10	GII	3 (30.0)/833.0	1 (10.0)/451.1	8 (80.0)^*/108.7	4 (40.0)/158.7	0 (0.0)	16 (32.0)/291.5
		GII.3	3 (30.0)/99.99	1 (10.0)/99.99	8 (80.0)^*/99.99	4 (40.0)/0.16^*		16 (32.0)
		GII.4	2 (20.0)/≤0.01		3 (30.0)/≤0.01	4 (40.0)/20.78		9 (18.0)
		GII.13						0 (0.0)
		GII.16			1 (10.0)/≤0.01	4 (40.0)/≤0.01^*		5 (10.0)
		GII.17	2 (20.0)/≤0.01	1 (10.0)/0.02	7 (70.0)^*/0.17	4 (40.0)/79.05^*		14 (28.0)
C	20	GII	0 (0.0)	0 (0.0)	11 (55.0)^*/77.0	2 (10.0)^*/44.7	0 (0.0)	13 (13.0)/72.0
		GII.3			11 (55.0)^*/99.67	2 (10.0)^/≤0.01^		13 (13.0)
		GII.4			4 (20.0)/≤0.01	2 (10.0)/≤0.01		6 (6.0)
		GII.13				1 (5.0)/≤0.01		1 (1.0)
		GII.16				2 (10.0)/≤0.01^*		2 (2.0)
		GII.17			8 (40.0)/≤0.01	2 (10.0)/99.80^*		10 (10.0)
D	10	GII	3 (30.0)/312.2	5 (50.0)/177.7	0 (0.0)^*	1 (10.0)/775.8	0 (0.0)	9 (18.0)/289.0
		GII.3	3 (30.0)/99.99	5 (50.0)/99.99		1 (10.0)/99.99		9 (18.0)
		GII.4	1 (10.0)/≤0.01	1 (10.0)/≤0.01		1 (10.0)/≤0.01		3 (6.0)
		GII.13						0 (0.0)
		GII.16						0 (0.0)
		GII.17	3 (30.0)/≤0.01	5 (50.0)/≤0.01		1 (10.0)/≤0.01		9 (18.0)
E	10	GII	2 (20.0)/71.4	6 (60.0)/275.4	0 (0.0)^*	0 (0.0)	0 (0.0)	8 (16.0)/224.4
		GII.3	2 (20.0)/99.99	6 (60.0)/99.99				8 (16.0)
		GII.4		1 (10.0)/≤0.01				1 (2.0)
		GII.13						0 (0.0)
		GII.16		1 (10.0)/≤0.01				1 (2.0)
		GII.17	2 (20.0)/≤0.01	6 (60.0)/≤0.01				8 (16.0)
F	10	GII	6 (60.0)/1533.7	6 (60.0)/106.4	0 (0.0)^*	1 (10.0)/0.0	0 (0.0)	13 (26.0)/756.9
		GII.3	6 (60.0)/99.99	6 (60.0)/99.99		1 (10.0)/0.17		13 (26.0)
		GII.4	3 (30.0)/≤0.01	3 (30.0)/≤0.01		1 (10.0)/99.80		7 (14.0)
		GII.13						0 (0.0)
		GII.16				1 (10.0)/≤0.01		1 (2.0)
		GII.17	5 (50.0)/≤0.01	5 (50.0)/≤0.01		1 (10.0)/≤0.01		11 (22.0)

Number of GII-positive samples were demonstrated. Positive rate was in bracket.

Average genome copy number of GI-positive samples were demonstrated.

GII genotypes except for GII.3, GII.4, GII.13, GII.16, and GII.17 were abbreviated from the Table, since there were no positive samples for these genotypes.

Number of positive samples for each genotype were demonstrated. Positive rate was in bracket.

To calculate the proportion of each genotype, the number of reads mapped against each reference was divided by the total reads obtained. Proportion less than 0.01 is represented as “≤0.01”.

Asterisk demonstrates significant difference between detection rates compared with that of previous month.

Statistical analysis

Significant differences for detection rate and proportion of genotypes were determined by the Fisher's exact test and the Mann–Whitney U test, respectively. Differences were considered significant where p < 0.01.

Results

Profiles of norovirus GI in Japanese oysters

The profiles of norovirus GI detected in Japanese oysters are presented in Table 1. Norovirus GI was detected in 9 out of 200 samples collected from sites A, B, E, and F, and its genome copy number differed depending on the sampling sites and month. GI was not detected in all 150 samples collected from sites C and D.

The detection rate and proportion of norovirus GI genotypes differed depending on the sample site and month. For example, GI.3 had the highest proportion at site F in October, whereas GI.1 had the highest proportion at the same site in December. GI.7 was never detected in any sample regardless of the sampling site and month.

Profiles of norovirus GII in Japanese oysters

Profiles of norovirus GII in Japanese oysters are presented in Table 2. Norovirus GII were detected in 72 out of 350 samples. The detection rates of GII at sites A, B, C, D, E, and F were 26, 32, 13, 18, 16, and 26%, respectively. There were significant differences in detection rates between site B and C (p < 0.01). GII was not detected in any sample collected in February. In Table 2, we have A = 60%, D = 50%, E = 60%, and F = 60% for November and 0% in all cases for December. In Table 2, we have B = 10% and C = 0 for November and B = 80% and C = 55% for December. The genome copy number of GII differed depending on the sampling site and month.

GII.3, GII.4, GII.13, GII.16, and GII.17 were detected in this study. The detection rates and proportion of norovirus GII genotypes differed depending on the sampling site and month. In total, the detection rate and proportion of GII.3 were highest among all genotypes detected from October to December. In January, the detection rates of GII.4 and GII.17 reached the same level as that of GII.3. The proportion of GII.17 was relatively low from October to December, whereas it was highest in January.

Discussion

Understanding the manner of pathogen contamination in oysters may illuminate the epidemiology of noroviruses. However, conventional RT-PCR does not provide any information about infectious risk (Richards, 1999; Gassilloud et al., 2003; Simonet and Gantzer, 2006). In this study, we adopted a molecular method for detection of noroviruses, which are thought to be related to human health risks, and revealed the diversity of infectious noroviruses in Japanese oysters by NGS.

For the detection of infectious noroviruses, Nuanualsuwan and Cliver (2002) reported that inactivated viruses gave a negative PCR result following simultaneous treatment with PK and RNase before conventional RT-PCR. Topping et al. (2009) discussed the use of high concentrations of PK to remove residual protection offered by the capsid RNA and may also digest viral capsids from intact virus particles. A recent study regarding the necessity of PK treatment conducted by Noda (2014) demonstrated that no significant difference was observed between samples treated simultaneously with PK and RNase, and RNase alone. Basis on enzymatic pretreatment will thought to be digestion of complete/partial exposed RNAs derived from noninfectious virus in the sample. Thus, we used RNase alone for pretreatment of samples. Additional research will be needed to determine whether the positive PCR results observed were only obtained from infectious viruses, since we did not compare the results obtained by RT-PCR without enzymatic pretreatment. Our present results appear to indicate that there is less norovirus genotype diversity in oysters collected at the same site compared with what was reported in a previous study, in which we investigated the diversity of norovirus genotypes in oysters by conventional RT-PCR. For example, all GII genotypes except for GII.10 were detected in oysters collected at site D in the investigation conducted from October 2013 to February 2014 (Imamura et al., 2016a). Although statistical analysis between the present and previous study seems not appropriate to be compared, this may be because RNase pretreatment digests exposed viral RNAs from incomplete viral particles, resulting in less diversity of genotypes. However, Baert et al. (2008) demonstrated no correlation between the number of infectious particles and viral genomes after heat treatment, regardless of the presence or nature of the enzyme pretreatment. Further consideration is needed to validate a method to distinguish infectious viruses from noninfectious ones.

Although information on the epidemiological characteristics of noroviruses presenting human health risks in oysters has been limited so far, this study demonstrated the diversity of infectious noroviruses in oysters by a molecular method to distinguish their infectivity. As we demonstrated previously (Imamura et al., 2016a, b), oysters appear to harbor several norovirus genotypes, and the detection rate and proportion in oysters differed between genotypes. This phenomenon may be explained by strain-dependent norovirus bioaccumulation in oysters, as reported by Maalouf et al. (2011). Bioaccumulation of GI.1 specifically occurred in digestive tissues in a dose-dependent manner and efficiency paralleled ligand expression in the oyster, which was highest during cold months (Maalouf et al., 2011). In comparison, GII.4 displayed poor bioaccumulation and was recovered in almost all tissues without seasonal influence (Maalouf et al., 2011). Thus, based on the assumption that norovirus levels in the surrounding environment of the investigated oysters remain unchanged, the relationship between the ligand expressed in the oysters and the corresponding receptor on the norovirus particle may affect the detection rate and proportion of each norovirus genotype in the oyster.

The various norovirus genotypes detected from each site differed depending on the month of the year. Water contamination occurred principally because of sewage pollution in the shellfish's habitat, and the level of pollution often increases after heavy rainfall (Ma et al., 2013). It is difficult to discern candidate factors behind the detection of noroviruses in oysters from the current results. Data relating to the geographic background of each site are needed to properly determine the factors associated with norovirus prevalence in oysters. Out of the various genotypes observed in the present study, GII.3 was proportionately predominant from October to December, whereas GII.17 was predominant during January. Frequent detection of certain genotypes may reflect the true virus circulation, resulting from cases of infectious gastroenteritis. A previous study reported that rGII-3a (recombinant Harrow/Mexico) was detected and characterized as the predominant genotype identified in several symptomatic cases from an outbreak (Gallimore et al., 2005). Thus, frequent detection of GII.3 in oysters may be a result of outbreaks in humans. Also, genetic analysis of GII.17 in diarrheal disease outbreaks from December 2014 to March 2015 in Japan demonstrated that a novel norovirus variant, GII.P17-GII.17, was prevalent in Japan from December 2014 onward, and GII.17 has been the predominant variant besides GII.4 (Matsushima et al., 2015). This trend seems to be reflected by the norovirus profile observed in oysters. Regarding the human health risk of GII.17, Japan Ministry of Health, Labor, and Welfare (JMHLW) has advised that the GII.17 variant, which was first identified from a clinical specimen in 2014 in Japan, is expected to be a candidate genotype for the next major outbreak in Japan (JMHLW, 2015). However, evidence for human outbreaks caused by GII.17 are limited thus far. Further epidemiological investigations are needed to clarify the risk of human infection originating in oysters.

Conclusions

To our knowledge, this is the first report to investigate diversity of infectious noroviruses in oysters in Japan, using a combination of enzymatic pretreatment for sample preparation and NGS analysis. A better understanding of the relationship between noroviruses and oysters, in terms of contamination, pathogen persistence, and pathogen selection, may contribute to understanding the epidemiology of noroviruses.

Footnotes

Acknowledgments

This study was performed as part of the surveillance/monitoring program of microbiological hazards in the Ministry of Agriculture, Forestry, and Fisheries, Tokyo, Japan.

Disclosure statement

No competing financial interests exist.

References

Baert

, Wobus

, Van Coillie

, Thackray

, Debevere

, Uyttendaele

. Detection of murine norovirus 1 by using plaque assay, transfection assay, and real-time reverse transcription-PCR before and after heat exposure. Appl Environ Microbiol, 2008; 74:543–546.

[EFSA] European Food Safety Authority. Panel on Biological Hazard (BIOHAZ). Scientific opinion on an update on the present knowledge on the occurrence and control of foodborne viruses. EFSA J, 2011; 9:2190.

Gallimore

, Cheesbrough

, Lamden

, Bingham

, Gray

. Multiple norovirus genotypes characterised from an oyster-associated outbreak of gastroenteritis. Int J Food Microbiol, 2005; 103:323–330.

Gassilloud

, Schwartzbrod

, Gantzer

. Presence of viral genomes in mineral water: A sufficient condition to assume infectious risk?. Appl Environ Microbiol, 2003; 69:3965–3969.

Gentry

, Vinjé

, Guadagnoli

, Lipp

. Norovirus distribution within an estuarine environment. Appl Environ Microbiol, 2009; 75:474–5480.

[ISO/TS 15216-1]. Microbiology of food and animal feed -Horizontal method for determination of hepatitis A virus and norovirus in food using real-time RT-PCR. 2013; pp. 10.

Imamura

, Haruna

, Goshima

, Kanezashi

, Okada

, Akimoto

. Application of next-generation sequencing to investigation of norovirus diversity in shellfish collected from two coastal sites in Japan from 2013 to 2014. Jpn J Vet Res, 2016a;64:113–122.

Imamura

, Haruna

, Goshima

, Kanezashi

, Okada

, Akimoto

. Application of next-generation sequencing to evaluate the profile of noroviruses in pre- and post-depurated oysters. Foodborne Pathog Dis, 2016b;13:559–565.

[Japanese Committee for Standardization Virus of Detection in Food]. 2010. Available at: http://www.nihs.go.jp/fhm/csvdf/kentest/csvdf001_wg_100820.pdf, accessed January 6, 2017 .

10.

[JMHLW]. 2007. Available at: http://www.mhlw.go.jp/topics/syokuchu/kanren/kanshi/dl/031105-1a.pdf, accessed January 6, 2017 .

11.

[JMHLW]. 2015. Available at: http://www.mhlw.go.jp/seisakunitsuite/bunya/kenkou_iryou/shokuhin/syokuchu/dl/151023-01.pdf, accessed January 6, 2017 .

12.

Kageyama

, Kojima

, Shinohara

, Uchida

, Fukushi

, Hoshino

, Takeda

, Katayama

. Broadly reactive and highly sensitive assay for Norwalk-like viruses based on real-time quantitative reverse transcription-PCR. J Clin Microbiol, 2003; 41:1548–1557.

13.

Lamhoujeb

, Fliss

, Ngazoa

, Jean

. Evaluation of the persistence of infectious human noroviruses on food surfaces by using real-time nucleic acid sequence-based amplification. Appl Environ Microbiol, 2008; 74:3349–3355.

14.

Le Guyader

, Neill

, Estes

, Monroe

, Ando

, Atmer

. Detection and analysis of a small round-structured virus strain in oysters implicated in an outbreak of acute gastroenteritis. Appl Environ Microbiol, 1996; 62:4268–4272.

15.

Lees

. Viruses and bivalve shellfish. Int J Food Microbiol, 2000; 59:81–116.

16.

Lowther

, Avant

, Gizynski

, Rangdale

, Lees

. Comparison between quantitative real-time reverse transcription PCR results for norovirus in oysters and self-reported gastroenteric illness in restaurant customers. J Food Prot, 2010; 73:305–311.

17.

Lusk

, Ottesen

, White

, Allard

, Brown

, Kase

. Characterization of microflora in Latin-style cheeses by next-generation sequencing technology. BMC Microbiol, 2012; 12:254.

18.

Maalouf

, Schaeffer

, Parnaudeau

, Le Pendu

, Atmar

, Crawford

, Le Guyader

. Strain-dependent norovirus bioaccumulation in oysters. Appl Environ Microbiol, 2011; 77:3189–3196.

19.

Maalouf

, Zakhour

, Le Pendu

, Le Saux

, Atmar

, Le Guyader

. Distribution in tissue and seasonal variation of Norovirus genogroup I and II ligands in oysters. Appl Environ Microbiol, 2010; 76:5621–5630.

20.

Matsushima

, Ishikawa

, Shimizu

, Komane

, Kasuo

, Shinohara

, Nagasawa

, Kimura

, Ryo

, Okabe

, Haga

, Doan

, Katayama

, Shimizu

. Genetic analyses of GII.17 norovirus strains in diarrheal disease outbreaks from December 2014 to March 2015 in Japan reveal a novel polymerase sequence and amino acid substitutions in the capsid region. Euro Surveill, 2015; 20:21173.

21.

, Zhao

, Yao

, Li

, Zhou

, Zhang

. The presence of genogroup II norovirus in retail shellfish from seven coastal cities in China. Food Environ Virol, 2013; 5:81–86.

22.

Noda

. Development and application of genetic methods to detect infectious viruses for risk analysis of foodborne viruses in foods. In Research and Survey Program, Food Safety Comission of Japan. 2014. Available at: https://www.fsc.go.jp/english/survey_programs/h25_research_no1203.pdf, accessed January 6, 2017 .

23.

Nuanualsuwan

, Cliver

. Pretreatment to avoid positive RT-PCR results with inactivated viruses. J Virol Methods, 2002; 104:217–225.

24.

Oliveira

, Cunha

, Castilho

, Romalde

, Pereira

. Microbial contamination and purification of bivalve shellfish: Crucial aspects in monitoring and future perspectives–A mini-review. Food Cont, 2011; 22:805–816.

25.

O'Sullivan

. Methods for analysis of the intestinal microflora. Curr Issues Intest Microbiol, 2000; 1:39–50.

26.

Richards

. Limitations of molecular biological techniques for assessing the virological safety of foods. J Food Prot, 1999; 62:691–697.

27.

Simonet

, Gantzer

. Degradation of the Poliovirus 1 genome by chlorine dioxide. J Appl Microbiol, 2006; 100:862–870.

28.

Topping

, Schnerr

, Haines

, Scott

, Carter

, Willcocks

, Bellamy

, Brown

, Gray

, Gallimore

, Knight

. Temperature inactivation of Feline calicivirus vaccine strain FCV F-9 in comparison with human noroviruses using an RNA exposure assay and reverse transcribed quantitative real-time polymerase chain reaction-A novel method for predicting virus infectivity. J Virol Methods, 2009; 156:89–895.

29.

Uema

. Current status and issues of detection of virus from food. Jpn J Microbiol, 2016; 33:121–126.

30.

Wyn-Jones

, Carducci

, Cook

, D'Agostino

, Divizia

, Fleischer

, Gantzer

, Gawler

, Girones

, Höller

, de Roda Husman

, Kay

, Kozyra

, López-Pila

, Muscillo

, Nascimento

, Papageorgiou

, Rutjes

, Sellwood

, Szewzyk

, Wyer

. Surveillance of adenoviruses and noroviruses in European recreational waters. Water Res, 2011; 45:1025–1038.

31.

, Li

, Kingsley

, Jiang

, Chen

. Inactivation of human norovirus in contaminated oysters and clams by high hydrostatic pressure. Appl Environ Microbiol, 2014; 80:2248–2253.