Skip to main page content

• HOME
• Current Issue
• Archive
• Alerts
• About ASM
• Contact us
• Tech Support
• Journals.ASM.org

This Article Abstract Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Reprints and Permissions Copyright Information Books from ASM Press MicrobeWorld Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Tajiri-Utagawa, E. Articles by Wakita, T. Search for Related Content PubMed PubMed Citation Articles by Tajiri-Utagawa, E. Articles by Wakita, T.

 Previous Article  |  Next Article 

Journal of Clinical Microbiology, February 2009, p. 435-440, Vol. 47, No. 2
0095-1137/09/$08.00+0     doi:10.1128/JCM.01247-08
Copyright © 2009, American Society for Microbiology. All Rights Reserved.

Development of a Rapid High-Throughput Method for High-Resolution Melting Analysis for Routine Detection and Genotyping of Noroviruses

Etsuko Tajiri-Utagawa,^1* Masayuki Hara,^1,2 Kuniaki Takahashi,³ Mayumi Watanabe,² and Takaji Wakita¹

Second Department of Virology, National Institute of Infectious Diseases, 4-7-1 Gakuen, Musashimurayama-shi, Tokyo 208-0012,¹ Department of Virology, Kitasato Research Center for Environmental Science, 1-15-1 Kitasato, Sagamihara-shi, Kanagawa 228-8555,² Roche Diagnostics K.K., 2-6-1 Shiba, Tokyo 105-0014, Japan³

Received 2 July 2008/ Returned for modification 8 August 2008/ Accepted 2 December 2008

Top ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION REFERENCES

 
We developed a simple, rapid, high-throughput detection and genotyping method for noroviruses using real-time reverse transcription-PCR (RT-PCR) and high-resolution melting (HRM) analysis to create a difference plot. The capsid gene was amplified by real-time RT-PCR in the presence of ResoLight HRM dye, a saturating DNA dye. Following optimization of the HRM assay conditions, the major norovirus genotypes were selected. Because we had only small quantities of the patient stool samples used in this study, we constructed plasmids for each genotype and used these to optimize the HRM assay. We selected six stool samples, each positive for one of the six dominant subtypes of noroviruses that have been circulating in Japan, namely, genotypes 4, 8, and 9 from genogroup 1 and genotypes 3, 4, and 10 from genogroup 2. The specific high-resolution derivate plot of the HRM assay for each plasmid was constructed by subtracting the melting-curve shape of the plasmid from the reference or base curve. The RNAs extracted from 14 clinical samples positive for small round structured viruses were then directly analyzed using the HRM assay. The HRM data from the clinical RNA samples corresponded with the genotype results obtained by RT-PCR and sequencing of the clinical samples. In addition, the HRM data from the clinical RNA samples corresponded with the HRM data from the six reference plasmid DNAs, indicating that this assay is useful for the direct detection and genotyping of noroviruses in clinical samples. This assay requires no multiplexing or hybridization probes and provides a new approach to the genetic screening of noroviruses in clinical virology laboratories.

Top ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION REFERENCES

 
The positive-sense polyadenylated single-stranded RNA virus family Caliciviridae contains four genera: Norovirus, Sapovirus, Lagovirus, and Vesivirus (1). Noroviruses are the leading causative agents of outbreaks of gastroenteritis worldwide in various settings, including hospitals, cruise ships, schools, and restaurants (2, 4, 5, 8, 13, 14, 17). Numerous molecular epidemiological studies have revealed a global distribution of these viruses (15, 16, 19). The most widely used method of detecting noroviruses is reverse transcription-PCR (RT-PCR), which has high sensitivity, and the products can be used for further genetic analysis. Real-time RT-PCR assays have also been developed, and these are sensitive, broadly reactive, rapid assays for the detection of human noroviruses in clinical stool specimens and environmental samples (6, 7, 12). As detection methods become more sensitive, the numbers of genogroups and genotypes are expected to increase (3).

Recently, the noroviruses were divided into five genetically distinct genogroups, but the majority of human noroviruses can be divided into two genetically distinct genogroups, genogroup I and genogroup II (GI and GII), which can be further subdivided into at least 14 GI and 17 GII genotypes (7). Norovirus genotype identities are generally maintained across the open reading frames (ORFs). However, a number of norovirus strains have failed to maintain their sequence identities for RNA-dependent RNA polymerase and VP1, and they have been shown to be recombinant (9, 10, 11, 18). Evidence suggests that the recombination site is at the conserved polymerase and capsid junction between ORF1 and ORF2.

The purpose of this study was to develop a more rapid, technically simpler detection and typing method for noroviruses in clinical samples. Data on the sensitivity and specificity of the method are reported, and the applicability of this technology to the clinical diagnosis of noroviruses is discussed.

Top ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION REFERENCES

 
Stool specimens and RNA extraction. Stool specimens were collected from children under the age of 5 years with sporadic cases of gastroenteritis in Japan between June 1998 and December 1999. The 14 fecal samples used were all SRSV (small round structured virus) positive by transmission electron microscopy (TEM). For the reference strains of the high-resolution melting (HRM) assay, we selected stool samples that were determined by RT-PCR and sequencing to be positive for six noroviruses belonging to the dominant subtypes that have been circulating in Japan: genotypes 4, 8, and 9 from GI and genotypes 3, 4, and 10 from GII. Stool specimens were stored at –80°C until RNA extraction. A 20% stool suspension was prepared in phosphate-buffered saline and homogenized. This suspension was treated with an equal volume of 1,1,2-trichloro-1,2,2-trifluoroethane (Wako Chemical Co., Tokyo, Japan) and then centrifuged at 2,000 x g for 30 min at 4°C, and the aqueous layer was collected. The QIAamp viral RNA minikit (Qiagen, Hilden, Germany) was used to extract RNA from 140 µl of the aqueous layer according to the manufacturer's instructions.

Cloning. Because we had only small quantities of the patient stool samples used in this study, we constructed plasmids for each genotype and used these to optimize the HRM assay. We selected six patient stool samples to use as the reference strains and constructed plasmids.

DNAs containing the target sequences amplified with primer set COG1F-G1-SKR (381 bp) for GI typing and primer set COG2F-G2-SKR (387 bp) for GII typing were cloned into the pCR 2.1 TOPO vector (Invitrogen, Tokyo, Japan) according to the manufacturer's instructions.

Conventional RT-PCR. A conventional RT-PCR was performed so that the findings could be compared with those of the HRM assay. A 25-µl aliquot of purified RNA was added to 3 µl of a reaction mixture containing 1x DNase I buffer and 2 U of DNase (Promega, Tokyo, Japan). This reaction mixture was incubated for 30 min at 37°C, followed by 5 min at 75°C to inactivate the DNase. The DNase-treated RNA (30 µl) was added to a reaction mixture containing 1x SuperScript II RT buffer (Invitrogen, Carlsbad, CA), 2.5 mM dithiothreitol (Invitrogen), 0.4 mM each deoxynucleoside triphosphate (Roche Diagnostics GmbH, Mannheim, Germany), 1 U RNase inhibitor (Toyobo, Tokyo, Japan), and 10 U SuperScript RT II (Invitrogen) in a final reaction volume of 50 µl. Reverse transcription was performed at 42°C for 1 h, followed by inactivation at 72°C for 15 min.

PCR was carried out according to the method described by Kojima et al. (10). For GI, we used sense primer COG1F and antisense primer G1SKR and produced a 381-bp amplicon. For GII, we used sense primer COG2F and antisense primer G2SKR to produce a 387-bp amplicon. PCR was performed with 5 µl of cDNA in a 50-µl reaction mixture containing 33 pmol of each sense and antisense primer, 1x Taq polymerase buffer (Toyobo), 0.2 mM each deoxynucleoside triphosphate, and 2.5 U of Taq polymerase (Toyobo). After initial denaturation at 94°C for 3 min, 40 cycles of amplification were performed using the GeneAmp PCR system 9600 (Perkin-Elmer Applied Biosystems, Foster City, CA). Each cycle consisted of denaturation at 94°C for 1 min, primer annealing at 55°C for 1 min, and extension at 72°C for 2 min, followed by a final extension at 72°C for 15 min. Products were visualized under UV light in a 2% agarose gel stained with ethidium bromide.

Sequence analysis. PCR-generated amplicons were extracted from the gel and purified using the QIAquick gel extraction kit (Qiagen). The nucleotide sequences of the amplified fragments were directly determined with the Terminator cycle sequencing kit (version 1.1) and the ABI 3100-Avant sequencer (Perkin-Elmer ABI, Boston, MA). Sequence analysis was performed using GENETYX (for MAC, version 10.1.4; Genetyx Co., Tokyo, Japan). The sequences were compared, by use of Cluster-X, with those of the reference strains of noroviruses obtained from GenBank, and distances from each of the tested genotypes were calculated using Kimura's two-parameter method (9). Positive-control plasmids were developed by using cDNA, as described above.

HRM curve acquisition and analysis. HRM curve acquisition and analysis were performed on the LightCycler 480 instrument (Roche). Plasmids (1 x 10⁷ copies/well) or cDNA (2 µl/well) was added to 20 µl of a reaction mixture containing 500 nM each primer (G1-SKF-G1-SKR [330 bp] and G2-SKF-G2-SKR [344 bp]), 3.5 mM MgCl₂, and 1x LightCycler 480 HRM master mix, which includes ResoLight HRM dye (Roche). Both the GI genotype 8 (GI/8) plasmid and the GII/10 plasmid were used as reference genotypes for the HRM analysis. All samples were tested in duplicate in a 96-well plate at every examination.

PCR cycling for HRM curve acquisition was run under the following conditions: 1 cycle of 95°C for 10 min; 45 cycles of 95°C for 10 s, 62°C to 58°C in 0.5°C/cycle increments for 10 s, and 72°C for 15 s; and 1 cycle of 95°C for 60 s and 40°C for 60 s. Then the fragment was melted by raising the temperature from 60°C to 97°C, with an increment of 0.11°C/s, in order to obtain information on melting profiles.

Melting-curve analysis was performed using the LightCycler 480 gene-scanning software module as reported by Wittwer et al. (20). This software analyzes the HRM curve data to identify changes in the shape of the curve that indicate sequence polymorphisms. Software programs employ a three-step analysis (Fig. 1) as follows. (i) The first step is to normalize the raw melting-curve data by setting the premelt (initial fluorescence) and postmelt (final fluorescence) signals of all samples to uniform values. Premelt signals are uniformly set to a relative value of 100%, while postmelt signals are set to a relative value of 0%, as shown in Fig. 1A. (ii) The second step is to shift the temperature along the x axis of the normalized melting curves at the point where the entire double-stranded DNA is completely denatured (Fig. 1B). (iii) The final step is to further analyze the differences in melting-curve shape by subtracting the curves from a reference curve (also called the "base curve"), thus generating a difference plot curve, which helps to cluster samples into groups that have similar melting curves (i.e., those with the same genotype), as shown in Fig. 1C.

View larger version (33K): [in this window] [in a new window]

FIG. 1. Principle of high-resolution amplicon melting-curve analysis to produce fluorescence difference plot curves. Melting-curve acquisitions and analyses were performed on the LightCycler 480 instrument (Roche). PCR products were denatured at 95°C for 60 s, renatured at 40°C for 60 s, and then melted at 60°C to 97°C with 25 signal acquisitions per degree. Melting-curve analysis was then performed using the LightCycler 480 gene-scanning software module. This software analyzes the HRM curve data to identify changes in the shape of the curve (difference plot curve) that indicate sequence polymorphisms. The amplicon melting curve is automatically calculated by the software in a three-step process, shown in the three panels. (A) Normalization. The raw data (left) are normalized to both 100% (at the beginning of the melting) and 0% (at the end of the melting). (Left) Raw data; (right) the same curve after normalization. (B) Temperature shift. (Left) The point (ellipse) at which the entire double-stranded DNA was completely denatured; (right) the same curve after the temperature has been shifted along the x axis. The temperature shifting with the curve allows comparisons between samples. (C) Fluorescence difference plot. (Left) Three points that show the difference between the base curve and the samples; (right) fluorescence difference plot curve obtained by subtracting each curve from the base curve. Because of the shift in the temperature of the curve, the temperature axis no longer reflects absolute temperature but rather reflects temperature differences relative to the superimposed segment of the curves. Data for three samples (a, b, and c) are shown.

LightCycler real-time RT-PCR. LightCycler real-time RT-PCR was carried out according to the method described by Kageyama et al. (6). To measure the numbers of genomes in the HRM-positive samples, real-time RT-PCR was performed with a LightCycler 480 instrument (Roche) by using primers COG1F and COG1R and fluorogenic probe RING1-TP for GI and primers COG2F and COG2R and fluorogenic probe RINGG2-TP for GII. The original cDNA used in conventional RT-PCR was also used in LightCycler real-time PCR. PCR was performed with 2 µl of cDNA in a 20-µl reaction mixture containing 500 nM each sense and antisense primer, 200 nM TaqMan probes, and LightCycler 480 Probe Master (Roche). PCR cycles were run as follows: 1 cycle of 95°C for 10 min; 45 cycles of 95°C for 10 s and 56°C for 25 s.

Sensitivity of HRM analysis. To monitor the sensitivity of the HRM assay, serial 10-fold dilutions (1 x 10⁷ copies/well to 1 copy/well) of the positive-control plasmids were prepared. The HRM reaction was performed in duplicate for each dilution.

Top ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION REFERENCES

 
A broad-range LightCycler real-time RT-PCR for HRM analysis was established to amplify the ORF1-ORF2 junction region of noroviruses. Because we had only small quantities of the patient stool samples used in this study, we constructed plasmids for each genotype and used these to optimize the HRM assay. We selected six stool samples positive for noroviruses belonging to the dominant subtypes that have been circulating in Japan: genotypes 4, 8, and 9 from GI and genotypes 3, 4, and 10 from GII. To identify the optimal conditions for this analysis, we compared two commonly used primer sets: COG1F-COG1R (85 bp) and G1-SKF-G1-SKR (330-bp) for GI typing and COG2F-COG2R (98 bp) and G2-SKF-G2-SKR (344 bp) for GII typing. Furthermore, we investigated the optimal concentration of Mg²⁺ in the reaction mixture. The HRM analysis showed a positive reactive pattern with the SKF-SKR primer pair but not with the COGF-COGR primers. Concentrations of Mg²⁺ ions ranging from 2.5 mM to 3.5 mM in the reaction mixture were also examined. We found that 3.5 mM was suitable for this study. Thus, we used the SKF-SKR primer pair and 3.5 mM Mg²⁺ ions for the detection of the GI and GII genotypes in further studies (data not shown).

The difference plot curves of GI/8 for genogroup I and GII/10 for genogroup II were tentatively used as base curves in this study (Fig. 2 and 3). We identified other GI genotypes by comparing their unique subtracted difference plot curves from the HRM analysis with that of GI/8. The subtracted difference plot curves of GI/4 and GI/9 were distinguishable from that of GI/8, as shown in Fig. 2A. For GII genotyping, we selected GII/10 as the base curve and examined two additional samples. We distinguished GII/3 and GII/4 from GII/10 (base curve) (Fig. 2B).

View larger version (31K): [in this window] [in a new window]

FIG. 2. Genotyping of noroviruses within a 380-bp fragment using high-resolution amplicon melting-curve analysis. (A) Difference plots from HRM analysis of the norovirus GI genotypes. GI/8 was the reference genotype (base curve) for the HRM analysis. Samples contained 107 copies/reaction. Each sample was measured in duplicate in a 96-well plate at every examination. (B) Difference plots from HRM analysis of norovirus GII genotypes. GII/10 was the reference genotype (base curve) for the HRM analysis. Samples contained 107 copies/reaction.

View larger version (42K): [in this window] [in a new window]

FIG. 3. Alignment of the nucleotide sequences and difference plots of four different clones of the GII/4 plasmid samples. Each clone of the four GII/4 plasmid samples was measured. GII/10 was the baseline sample for the HRM analysis. (Bottom) Alignment of the nucleotide sequences of four GII/4 plasmids. The positions of primers are shown. (Top) Difference plots from HRM analysis of four GII/4 plasmids compared with GII/10.

The effect of base variability in each plasmid tested was further investigated. When we cloned patient sample RNA into plasmids, we constructed and selected four clones for each plasmid sample. The variation and alignment of the sequence data for the four GII/4 plasmids are summarized in Fig. 3. Although a few point mutations in the GII/4 bases among the four plasmid samples were detected, there was no significant effect on the shape of the subtracted difference plot in HRM analysis, as shown in Fig. 3. In our examination, only one subtracted difference plot was constructed for each genotype.

In order to investigate the detection limits of the HRM assay, the six sample plasmids were examined four to nine times, as shown in Table 1. We found that 10 copies of sample RNA per reaction mixture was the detection limit for all genotypes tested. Based on these observations, we generated an HRM database and analysis schema for rapid identification of the norovirus genotypes used.

View this table: [in this window] [in a new window]

TABLE 1. End points of detection levels of the HRM assaya

We further assessed the ability of our novel approach to differentiate norovirus genotypes directly in 14 clinical stool samples. All of the stool samples tested were positive for SRSVs by TEM (Table 2). Of these 14 samples, 9 were norovirus positive and the remaining 5 were norovirus negative by both RT-PCR and real-time RT-PCR, as shown in Table 2. The RNA extracted from the stool specimen of patient 5 was also examined directly using the HRM assay and compared with the data from the reference GII/4 plasmid. The RNA from patient 5 showed a difference plot curve similar to that of the GII/4 reference plasmid (Fig. 4). Among the nine positive samples, viruses were identified as follows: patient 1, GI/8; patient 4, GI/9; patients 5, 12, 13, and 14, GII/4; patient 9, GII/3; patient 10, GII/10; and patient 11, GI/4. (Table 2 shows a summary of all results.) Conventional real-time PCR showed a high concentration of viral genes in norovirus-positive stool samples. The HRM analysis data were consistent with the results of conventional RT-PCR, sequencing, and real-time RT-PCR.

View this table: [in this window] [in a new window]

TABLE 2. Comparative study of HRM with RT-PCR, sequencing, and real-time PCRa

View larger version (29K): [in this window] [in a new window]

FIG. 4. Results of HRM analysis of the sample from patient 5. Patient 5's sample was identified as GII/4 by RT-PCR and sequencing, as shown in Table 2. To monitor the sensitivity of the HRM assay, serial 10-fold dilutions (1 x 107 copies/well to 1 copy/well) of the GII/4 positive-control plasmids were prepared. The HRM reaction was performed in duplicate for each dilution. In this study, the RNA from patient 5 was identified as GII/4 by the HRM analysis. The examination gave the same pattern as the reference GII/4 plasmid.

Top ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION REFERENCES

 
In this study, we describe a "broad-range" real-time RT-PCR technique for the simultaneous detection, quantification, and presumptive differentiation of norovirus genotypes. Since Wittwer et al. reported that the HRM analysis method can identify both heterozygous and homozygous sequence variants (20), we explored its use in norovirus genotyping. ResoLight HRM dye is a new fluorescent, saturating DNA dye designed to detect heteroduplexes during homogeneous melting-curve analysis. Unlike SYBR green I, ResoLight HRM dye saturates the products of PCR without inhibiting amplification and does not redistribute as the amplicon melts. This allows closed-tube, homogeneous genotyping without fluorescently labeled probes. Heterozygotes are identified by a change in the shape of the difference plot curve.

Most of the methods currently available for norovirus genotyping use genotype-specific primers to amplify genes, allowing for the detection of one specific pathogen at a time. For sample screening and genotype identification in an outbreak, multiplexing or multiple reactions followed by post-PCR electrophoresis to separate amplicons of different sizes are usually required. Although real-time RT-PCR has been used successfully for the detection of noroviruses, TaqMan or hybridization probes are usually required, increasing the expense on a cost-per-sample basis. This type of assay is based on a phylogenetic analysis that reveals the preferential association between norovirus genes and coevolution of these genes.

Because the quantity of patient stool sample that we stored was small, we tried to construct plasmids and examined them to clarify the conditions of the HRM assay. We selected six strains from patient stools for reference and constructed plasmids. The HRM assay could directly detect the genotypes of noroviruses with difference plot curve patterns in patient stool samples.

The detection limit of this method is equivalent to 1 to 10 copies of viral RNA in the reaction mixture, and it has a dynamic linear range for quantification across at least 7 log units of RNA concentration.

We demonstrated that noroviruses can be differentiated simply through the use of one PCR primer pair for real-time RT-PCR, followed by HRM of the ORF1-ORF2 junction. PCR products likely contain information for at least partial phylogenetic characterization and genotyping of clinically important noroviruses. Compared to other genotyping methods, HRM-based genotyping gives superior resolving power. When combined with rapid-cycle PCR, HRM analysis requires minimal time, and the cost of materials is typically less than that for standard methods. The time required for the differentiation of norovirus genotypes is considerably shorter when PCR and sequencing are performed directly on clinical samples.

The HRM assay demonstrated good sensitivity, detecting 10⁷ to around 1 copy per reaction mixture of RNA collected directly from patient stool samples for both GI and GII noroviruses. A comparative study with patient feces revealed good correlation with the reference plasmids between the sequencing and HRM results. When we obtained normalized HRM data for a reference plasmid, it was simple to classify the genotype in less than 60 min. Our approach is also a very convenient method to classify noroviruses.

The circulating norovirus genotypes in Japan from 2000 have been reported by the Infectious Agents Surveillance Report to be GI/4 (48%), GI/8 (20%), and GI/9 (12%) for GI and GII/4 (90%), GII/3 (4%), and GII/6 (2%) for GII. In this study, we confirmed that those typed norovirus strains can be identified by HRM analysis. However, untyped noroviruses could not be identified, because the primer pairs commonly used were not suitable.

The conventional RT-PCR and real-time RT-PCR methods are commonly used for the detection of typed noroviruses in outbreaks and sporadic cases in Japan. The primer pairs commonly used for GI and/or GII can be used only for the detection of well-known and typed strains of noroviruses. TEM is still detecting untyped, circulating SRSVs (Table 2). In the present study, we also found five samples that were negative by conventional RT-PCR, real-time PCR, and the HRM assay; nevertheless, they contained SRSVs detected by TEM.

RT-PCR, real-time PCR, and the HRM assay with the commonly used primer pairs are currently unable to detect untyped SRSVs. Further study will need to focus on selecting and identifying untyped caliciviruses. In addition, the broad reactivity of this assay will be validated using a panel of stool samples containing typed GI and/or GII genotypes in the near future.

 
This work was partially supported by a grant-in-aid for Scientific Research from the Japan Society for the Promotion of Science and from the Ministry of Health, Labor, and Welfare of Japan and by a Research on Health Sciences Focusing on Drug Innovation grant from the Japan Health Sciences Foundation.

 
* Corresponding author. Mailing address: Laboratory of Diarrhea, Second Department of Virology, National Institute of Infectious Diseases, 4-7-1 Gakuen, Mushashimurayama-shi, Tokyo 208-0012, Japan. Phone: 81-42-561-0771. Fax: 81-42-561-4729. E-mail: etu{at}nih.go.jp

Published ahead of print on 10 December 2008.

Top ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION REFERENCES

 

1
1. Atmar, R. L., and M. K. Estes. 2001. Diagnosis of noncultivatable gastroenteritis viruses, the human caliciviruses. Clin. Microbiol. Rev. 14:15-37.[Abstract/Free Full Text]
2
2. Beuret, C., A. Baumgartner, and J. Schluep. 2003. Virus-contaminated oysters: a three-month monitoring of oysters imported to Switzerland. Appl. Environ. Microbiol. 69:2292-2297.[Abstract/Free Full Text]
3
3. Infectious Disease Surveillance Center. 2008. Isolation number of viruses. Infect. Agents Surveill. Rep. 29(10):29-31. (In Japanese.)
4
4. Inouye, S., K. Yamashita, S. Yamadera, M. Yoshikawa, N. Kato, and N. Okabe. 2000. Surveillance of viral gastroenteritis in Japan: pediatric cases and outbreak incidents. J. Infect. Dis. 181(Suppl. 2):S270-S274.[CrossRef][Medline]
5
5. Johansson, P. J., M. Torven, A. C. Hammarlund, U. Bjorne, K. O. Hedlund, and L. Svensson. 2002. Food-borne outbreak of gastroenteritis associated with genogroup I calicivirus. J. Clin. Microbiol. 40:794-798.[Abstract/Free Full Text]
6
6. Kageyama, T., S. Kojima, M. Shinohara, K. Uchida, S. Fukushi, F. B. Hoshino, N. Takeda, and K. Katayama. 2003. Broadly reactive and highly sensitive assay for Norwalk-like viruses based on real-time quantitative reverse transcription-PCR. J. Clin. Microbiol. 41:1548-1557.[Abstract/Free Full Text]
7
7. Kageyama, T., M. Shinohara, K. Uchida, S. Fukushi, F. B. Hoshino, S. Kojima, R. Takai, T. Oka, N. Takeda, and K. Katayama. 2004. Coexistence of multiple genotypes, including newly identified genotypes, in outbreaks of gastroenteritis due to norovirus in Japan. J. Clin. Microbiol. 42:2988-2995.[Abstract/Free Full Text]
8
8. Kapikian, A. Z., R. G. Wyatt, R. Dolin, T. S. Thornhill, A. R. Kalica, and R. M. Chanock. 1972. Visualization by immune electron microscopy of a 27-nm particle associated with acute infectious nonbacterial gastroenteritis. J. Virol. 10:1075-1081.[Abstract/Free Full Text]
9
9. Katayama, K., H. Shirato-Horikoshi, S. Kojima, T. Kageyama, T. Oka, F. Hoshino, S. Fukushi, M. Shinohara, K. Uchida, Y. Suzuki, T. Gojobori, and N. Takeda. 2002. Phylogenetic analysis of the complete genome of 18 Norwalk-like viruses. Virology 299:225-239.[CrossRef][Medline]
10
10. Kojima, S., T. Kageyama, S. Fukushi, F. B. Hoshino, M. Shinohara, K. Uchida, K. Natori, N. Takeda, and K. Katayama. 2002. Genogroup-specific PCR primers for detection of Norwalk-like viruses. J. Virol. Methods 100:107-114.[CrossRef][Medline]
11
11. Lochridge, V. P., and M. E. Hardy. 2003. Snow Mountain virus genome sequence and virus-like particle assembly. Virus Genes 26:71-82.[CrossRef][Medline]
12
12. Loisy, F., R. L. Atmar, P. Guillon, P. Le Cann, M. Pommepuy, and F. S. Le Guyader. 2005. Real-time RT-PCR for norovirus screening in shellfish. J. Virol. Methods 123:1-7.[CrossRef][Medline]
13
13. McEvoy, M., W. Blake, D. Brown, J. Green, and R. Cartwright. 1996. An outbreak of viral gastroenteritis on a cruise ship. Commun. Dis. Rep. CDR Rev. 6:R188-R192.[Medline]
14
14. McIntyre, L., L. Vallaster, C. Kurzac, J. Fung, A. McNabb, M. K. Lee, P. Daly, M. Petric, and J. Isaac-Renton. 2002. Gastrointestinal outbreaks associated with Norwalk virus in restaurants in Vancouver, British Columbia. Can. Commun. Dis. Rep. 28:197-203.[Medline]
15
15. Nakata, S., S. Honma, K. Numata, K. Kogawa, S. Ukae, N. Adachi, X. Jiang, M. K. Estes, Z. Gatheru, P. M. Tukei, and S. Chiba. 1998. Prevalence of human calicivirus infections in Kenya as determined by enzyme immunoassays for three genogroups of the virus. J. Clin. Microbiol. 36:3160-3163.[Abstract/Free Full Text]
16
16. Noel, J. S., R. L. Fankhauser, T. Ando, S. S. Monroe, and R. I. Glass. 1999. Identification of a distinct common strain of "Norwalk-like viruses" having a global distribution. J. Infect. Dis. 179:1334-1344.[CrossRef][Medline]
17
17. Russo, P. L., D. W. Spelman, G. A. Harrington, A. W. Jenney, I. C. Gunesekere, P. J. Wright, J. C. Doultree, and J. A. Marshall. 1997. Hospital outbreak of Norwalk-like virus. Infect. Control Hosp. Epidemiol. 18:576-579.[Medline]
18
18. Vinjé, J., J. Green, D. C. Lewis, C. I. Gallimore, D. W. Brown, and M. P. Koopmans. 2000. Genetic polymorphism across regions of the three open reading frames of "Norwalk-like viruses." Arch. Virol. 145:223-241.[CrossRef][Medline]
19
19. White, P. A., G. S. Hansman, A. Li, J. Dable, M. Isaacs, M. Ferson, C. J. McIver, and W. D. Rawlinson. 2002. Norwalk-like virus 95/96-US strain is a major cause of gastroenteritis outbreaks in Australia. J. Med. Virol. 68:113-118.[CrossRef][Medline]
20
20. Wittwer, C. T., G. H. Reed, C. N. Gundry, J. G. Vandersteen, and R. J. Pryor. 2003. High-resolution genotyping by amplicon melting analysis using LCGreen. Clin. Chem. 49:853-860.[Abstract/Free Full Text]

---

Journal of Clinical Microbiology, February 2009, p. 435-440, Vol. 47, No. 2
0095-1137/09/$08.00+0     doi:10.1128/JCM.01247-08
Copyright © 2009, American Society for Microbiology. All Rights Reserved.

This article has been cited by other articles:

• Henke-Gendo, C., Harste, G., Juergens-Saathoff, B., Mattner, F., Deppe, H., Heim, A. (2009). New Real-Time PCR Detects Prolonged Norovirus Excretion in Highly Immunosuppressed Patients and Children. J. Clin. Microbiol. 47: 2855-2862 [Abstract] [Full Text]  

This Article Abstract Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Reprints and Permissions Copyright Information Books from ASM Press MicrobeWorld Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Tajiri-Utagawa, E. Articles by Wakita, T. Search for Related Content PubMed PubMed Citation Articles by Tajiri-Utagawa, E. Articles by Wakita, T.