Rapid detection and differentiation of human noroviruses using RT-PCR coupled to electrospray ionization mass spectrometry

Accepted Manuscript Rapid Detection and Differentiation of Human Noroviruses using RT-PCR coupled to Electrospray Ionization Mass Spectrometry Rosalee S. Hellberg , Feng Li , Rangarajan Sampath , Irene J. Yasuda , Heather E. Carolan , Julia M. Wolfe , Michael K. Brown , Richard C. Alexander , Donna M. Williams-Hill , William B. Martin PII:

S0740-0020(14)00123-3

DOI:

10.1016/j.fm.2014.05.017

Reference:

YFMIC 2176

To appear in:

Food Microbiology

Received Date: 26 September 2013 Revised Date:

25 April 2014

Accepted Date: 25 May 2014

Please cite this article as: Hellberg, R.S., Li, F., Sampath, R., Yasuda, I.J., Carolan, H.E., Wolfe, J.M., Brown, M.K., Alexander, R.C., Williams-Hill, D.M., Martin, W.B., Rapid Detection and Differentiation of Human Noroviruses using RT-PCR coupled to Electrospray Ionization Mass Spectrometry, Food Microbiology (2014), doi: 10.1016/j.fm.2014.05.017. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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Rapid Detection and Differentiation of Human Noroviruses using RT-PCR coupled to

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Electrospray Ionization Mass Spectrometry

3 Rosalee S. Hellberga*, Feng Lib, Rangarajan Sampathb, Irene J. Yasudab, Heather E. Carolanb,

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Julia M. Wolfec, Michael K. Brownc, Richard C. Alexanderc, Donna M. Williams-Hilld,

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William B. Martind

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a

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Nutrition, One University Drive, Orange, CA 92866

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Chapman University, Schmid College of Science and Technology, Food Science and

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b

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c

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d

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Laboratory Southwest, 19701 Fairchild, Irvine, CA 92612

Ibis Biosciences, Abbott, 2251 Faraday Ave., Suite 150, Carlsbad, CA 92008

Orange County Public Health Laboratory, 1729 West 17th Street, Santa Ana, CA 92706

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U.S. Food and Drug Administration, Office of Regulatory Affairs, Pacific Regional

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*Corresponding author: e-mail: [email protected], Ph: 1-714-628-2811

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Disclaimer: The views in this publication represent those of the authors. The inclusion of

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specific trade names or technologies does not imply endorsement by the U.S. Food and Drug

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Administration nor is criticism implied of similar commercial technologies not mentioned

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within.

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Conflict of Interest

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F.L., R.S., I.Y., and H.C. are employees of Ibis Biosciences, Abbott, the commercial

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manufacturer of the technology described here.

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Abstract

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The goal of this study was to develop an assay for the detection and differentiation of

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noroviruses using RT-PCR followed by electrospray ionization mass spectrometry (ESI-MS).

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Detection of hepatitis A virus was also considered. Thirteen primer pairs were designed for

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use in this assay and a reference database was created using GenBank sequences and

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reference norovirus samples. The assay was tested for inclusivity and exclusivity using 160

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clinical norovirus samples, 3 samples of hepatitis A virus and 3 other closely related viral

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strains. Results showed that the assay was able to detect norovirus with a sensitivity of 92%

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and a specificity of 100%. Norovirus identification at the genogroup level was correct for

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98% of samples detected by the assay and for 75% of a subset of samples (n = 32) compared

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at the genotype level. Identification of norovirus genotypes is expected to improve as more

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reference samples are added to the database. The assay was also capable of detecting and

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genotyping hepatitis A virus in all 3 samples tested. Overall, the assay developed here allows

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for detection and differentiation of noroviruses within one working day and may be used as a

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tool in surveillance efforts or outbreak investigations.

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Keywords

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Norovirus; hepatitis A virus; RT-PCR; electrospray ionization mass spectrometry; genotyping

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1. Introduction Noroviruses are the leading cause of foodborne disease among all known pathogens, with an estimated 5.5 million foodborne illnesses annually in the United States (Scallan et al.,

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2011). These viruses are genetically diverse members of the Caliciviridae family (genus

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Norovirus) and consist of at least 32 genetic clusters organized into 5 genogroups (GI-GV)

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(Zheng et al., 2006; Zheng et al., 2010). Genogroups I, II, and IV have been associated with

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human infection, with the majority of outbreaks due to GII strains, particularly GII.4 variants.

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The ability to identify noroviruses at the genotype and strain levels is important for tracing the

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source and spread of outbreaks as well as for routine surveillance. Norovirus surveillance

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programs have revealed that some norovirus strains are only found within geographically

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limited regions, while others experience widespread distribution over specific time periods

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(Siebenga et al., 2009; Vega et al., 2011). Evidence has also been found for the presence of

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multiple strains associated with a single infection or outbreak, with reports of 3-12% of

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outbreaks being associated with strains from both GI and GII (Blanton et al., 2006; Green et

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al., 2001; Hall et al., 2012; Matthews et al., 2012). Food and waterborne outbreaks have been

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found to be more likely associated with strains from multiple genogroups than person-to-

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person outbreaks (Matthews et al., 2012).

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Because noroviruses have not been successfully cultivated in vitro, nucleic acid-based

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methods are widely used for their detection and differentiation (Hall et al., 2011).

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Noroviruses have a small, single-stranded RNA genome of ~7.5 kb with three open reading

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frames: ORF1, ORF2, and ORF3 (Green et al., 2001). ORF1 contains several genes coding

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for nonstructural proteins, including RNA-dependent RNA polymerase (RdRp); ORF2

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contains the gene coding for the major capsid protein (VP1); and ORF3 contains the gene

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coding for the minor capsid protein (VP2). Reverse-transcriptase polymerase chain reaction

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(RT-PCR) analysis of regions of the VP1 or RdRp genes is generally used to presumptively

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detect noroviruses at the organismal and genogroup level, while DNA sequencing can be used

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for confirmation and for differentiation of genotypes and strains (Zheng et al., 2006).

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Although standardized methods for differentiation of noroviruses have been proposed based

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on the complete sequence of the VP1 gene (Zheng et al., 2006), many studies sequence

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smaller regions of either the RdRp or VP1 genes and use a variety of primer sets, sequence

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analysis methods, and nomenclature, leading to inconsistencies in data reporting and

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strain/genotype identification (Kroneman et al., 2013; Kroneman et al., 2011; Mattison et al.,

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2009). Furthermore, frequent recombination events at the ORF1-ORF2 region have resulted

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in different genotype assignments depending on which gene region is targeted for sequencing

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(Bull et al., 2007) and rapid evolution of GII.4 noroviruses has led to the emergence of highly

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virulent strains that have not previously been characterized (Siebenga et al., 2007; Siebenga et

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al., 2009; Zheng et al., 2010). Infections consisting of multiple strains are also difficult to

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analyze using traditional sequencing because this method is not able to discern multiple

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sequences in a mixed sample.

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The use of RT-PCR followed by electrospray ionization mass spectrometry (ESI-MS)

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provides a potential means for rapid detection and differentiation of norovirus genotypes and

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strains (Ecker et al., 2008; Sampath et al., 2007b). With this method, fragments of the

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genome are first amplified by RT-PCR and then analyzed by ESI-MS to determine the precise

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mass and corresponding base composition (numbers of A, G, C, and T) of each PCR product.

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These base compositions are then compared to a reference database to allow for the

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identification and differentiation of organisms. While this method does not provide the

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ordered sequence of the nucleotides, knowledge of the base composition alone has proven to

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be sufficient in many cases to allow for organism identification, as PCR/ESI-MS assays

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utilize primers that bind to conserved regions flanking highly variable sequences among the

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organism(s) of interest (Ecker et al. 2008; Sampath et al. 2007b). In addition to the potential

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to detect noroviruses and characterize them at the genotype and strain levels, PCR/ESI-MS

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allows for the identification of organisms in mixed samples, and analysis can be completed

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within one working day. Furthermore, this method allows for multiplexing of primers so that

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several regions of the genome can be targeted simultaneously, resulting in greater potential

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for the identification of new strains and recombinants. PCR/ESI-MS assays have been

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published for the detection and characterization of a number of organisms, including

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respiratory pathogens (Ecker et al., 2005; Sampath et al., 2005; Sampath et al., 2007a;

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Sampath et al., 2007b), vector-borne pathogens (Crowder et al., 2012; Crowder et al., 2010;

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Eshoo et al., 2010; Eshoo et al., 2007; Grant-Klein et al., 2010), biothreat agents (Jacob et al.,

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2012; Sampath et al., 2012; Van Ert et al., 2004) and common bacterial food pathogens (e.g.,

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Salmonella, E. coli, and Campylobacter) (Hannis et al., 2008; Pierce et al., 2012; Shen et al.,

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2013), but not for noroviruses. PCR/ESI-MS could potentially be used alongside current

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sequence-based techniques to rapidly identify norovirus genotypes and variants in

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surveillance and outbreak situations.

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The goal of this study was to develop a novel RT-PCR/ESI-MS assay for the rapid

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detection and genetic differentiation of noroviruses. Because of the ability of the assay to test

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for multiple pathogens simultaneously, detection of hepatitis A virus was also considered for

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incorporation into this assay. Like norovirus, hepatitis A virus is a single-stranded RNA virus

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spread through the fecal-oral route (Nainan et al., 2006). There are three known genogroups

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of hepatitis A virus (I-III) that infect humans, with genotype IA being most commonly

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associated with disease (Sanchez et al. 2007). Although hepatitis A virus has a relatively low

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incidence among foodborne viruses in the U.S., it has the highest rates of hospitalization

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(31.5%) and death (2.4%) (Scallan et al. 2011). As current detection techniques for hepatitis

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A virus generally rely on RT-PCR assays specific for the virus (Sanchez et al. 2007), an assay

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that allows for simultaneous identification of both noroviruses and hepatitis A viruses would

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likely prove advantageous when performing screening for these viruses.

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2. Materials and Methods

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2.1 Assay Design

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Over 5000 norovirus sequences and 150 hepatitis A virus sequences were downloaded from GenBank for use in assay design. In cases where genotype information was not

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available for a particular norovirus sequence, the Norovirus Automated Genotyping Tool was

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used (Kroneman et al., 2011). Sequences were aligned with Clustal W (Thompson et al.,

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1994) in BioEdit Sequence Alignment Editor, v. 7.1.3.0 (Hall, 1999) and examined for

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regions of high variability flanked by regions of conserved primer-binding sites. Based on

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these alignments, a set of primers was designed for this study to collectively amplify all

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human noroviruses (Table 1). Norovirus primers were designed for maximal differentiation

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amongst the various human norovirus genotypes, as well as differentiation among GII.4

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strains. Primers targeting human hepatitis A viruses (Table 1) were also used in this study for

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the purpose of universal amplification and detection at the virus level. The hepatitis A virus

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primers had been designed previously by Ibis Biosciences, but had not been published. A set

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of primer pairs was also designed for amplification of the internal control. Primers were

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analyzed in silico for parameters such as primer-dimer formation, %GC, and annealing

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temperature. The primers were separated into 8 wells, with 5 of the wells containing multiple

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primer pairs, and then arranged in a 96-well plate format, allowing for analysis of 12 samples

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per plate (Fig. 1).

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2.2 Specimen collection and preparation

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A total of 206 stool samples from the Orange County Public Health Laboratory (Santa

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Ana, CA) were obtained for use in this project. Use of biological specimens was approved by

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the U.S. Food and Drug Administration (FDA) Research Involving Human Subjects

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Committee (RIHSC #12-009A). The specimens were derived from various outbreaks and

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single cases of norovirus illness reported to the public health laboratory during 2006-2011.

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This collection consisted of 196 stool samples that previously tested positive for norovirus

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and 10 stool samples that previously tested negative for norovirus. Norovirus detection and

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genogroup information were based on the results of real-time RT-PCR testing at the time of

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illness using a previously described method (Kageyama et al., 2003). A subset of these

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samples (n = 36) had previously undergone sequencing-based genotyping (Vinje et al., 2004)

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as part of CaliciNet, a national outbreak surveillance network developed by the Centers for

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Disease Control and Prevention (CDC) (Vega et al., 2011). The genotyped samples were

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used to build the RT-PCR/ESI-MS database (Table 2). The remaining norovirus samples

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were used to test the RT-PCR/ESI-MS assay for inclusivity. All stool samples underwent

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clarification prior to RNA extraction as follows: approximately 0.1 g of stool was added to a

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glass vial containing 1 ml of Vertrel XF (DuPont, Wilmington, DE) and 1 ml of sterile water.

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Samples were then mixed by vortex for 1 min and centrifuged at 1700 x g for 10 min. The

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aqueous phase containing the virus was then removed by pipetting and stored at -70ºC until

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RNA extraction. RNA was extracted from clarified samples using the QIAamp Viral RNA

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Mini Kit (Qiagen, Valencia, CA), Spin Column Protocol, according to the manufacturer’s

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instructions. Reagent blanks were included in the RNA extractions as negative controls.

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Hepatitis A virus, feline calicivirus, murine norovirus, and poliovirus from the American Type Culture Collection (ATCC) were also used for inclusivity and exclusivity

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testing of the RT-PCR/ESI-MS assay. Three samples of hepatitis A virus were tested from

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strains HAS-15 (ATCC #VR-2281), HM-175/18f (ATCC #VR-1402) and PA21 (ATCC

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#VR-1357), representing human genotypes IA, IB and IIIA, respectively. One sample of each

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of the following was used for exclusivity testing: feline calicivirus strain F9 (ATCC #VR-

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782), murine norovirus-1 (ATCC #PTA-5935), and poliovirus type 3, strain LSC (ATCC

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#VR-1001AS/HO).

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2.3 RT-PCR/ESI-MS

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All samples underwent RT-PCR/ESI-MS using the assay designed in this study. One-step

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RT-PCR was performed with each reaction well having the following components: 5 µl RNA

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or non-template control, 2 U Superscript III Reverse Transcriptase (Life Technologies,

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Carlsbad, CA), 2 ng/µl sonicated poly A RNA (Sigma-Aldrich, St. Louis, MO), 1 ng/µl

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random hexamers (Life Technologies), 10 mM dithiothreitol (DTT, Life Technologies), 0.01

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U/µl SUPERase In RNase Inhibitor (Life Technologies), 5 U AmpliTaq Gold DNA

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Polymerase (Roche Molecular Systems, Pleasanton, CA), 200 µM each dATP, dCTP, and

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dTTP (Bioline, Taunton, MA), 200 µM 13C-enriched dGTP (Cambridge Isotope Laboratories,

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Andover, MA), 1.4 mM MgCl2 (Life Technologies), 250 nM each primer (Table 1; Integrated

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DNA Technologies, Coralville, IA), 20 mM Tris (pH 8.3), 75 mM KCl, 0.4 M betaine, and 20

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mM sorbitol (Sigma-Aldrich) in a total volume of 40 µl. RT-PCR was carried out with a

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Mastercycler proS thermocycler (Eppendorf, Hauppauge, NY) using the following cycling

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conditions: 60ºC for 5 min; 4ºC for 10 min; 55ºC for 45 min; 95ºC for 10 min; 8 cycles of

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95ºC for 30 s, 48ºC for 30 s (increase 0.9°C for each cycle), and 72ºC for 30 s; 37 cycles of

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95ºC for 15 s, 56ºC for 20 s, and 72ºC for 20 s; and a final extension of 72ºC for 2 min

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followed by a 4ºC hold. Each reaction also contained an internal positive control (“calibrant”)

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made from synthetic DNA (Blue Heron Biotechnology, Bothell, WA). The calibrant was

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present in each reaction at a level of 200 copies and allowed for a semi-quantitative estimate

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of the starting number of genome copies in each PCR well.

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Following RT-PCR, the assay plate was loaded onto the PCR/ESI-MS platform (Abbott Molecular, Des Plaines, IL) for amplicon desalting and ESI-MS analysis, as described

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previously (Ecker et al., 2008; Hofstadler et al., 2005; Jiang and Hofstadler, 2003). The

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analysis software determined the base compositions of each amplicon based on analysis of

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both the forward and reverse strands. The resulting base compositions were queried against

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an ESI-MS database populated with the expected base compositions for the norovirus and

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hepatitis A virus sequences downloaded from GenBank (described in section 2.1) and the

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base compositions acquired in this study for the 36 previously genotyped norovirus samples

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(Table 2). The top database matches, approximate levels of genome copies per well, and

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associated Q-scores were recorded for each sample. The Q-score, a rating between 0 (low)

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and 1 (high), represents a relative measure of the strength of the data supporting identification

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(Sampath et al., 2012; Simner et al., 2013). For this assay, a Q-score ≥ 0.85 was considered to

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be a reportable result. To reduce the possibility of false positives, a threshold of ≥ 25 genome

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copies per well was also required for a reportable result. In cases where the ESI-MS result

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did not match previous identifications, the genotypes of sequences derived from GenBank

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were checked with the Norovirus Automated Genotyping Tool to ensure proper nomenclature

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was used (Kroneman et al. 2011).

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2.4 Comparison to recognized method The ability of the RT-PCR/ESI-MS assay plate designed in this study to detect and

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differentiate norovirus samples was compared to a DNA sequencing method for genotyping

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(Vinje et al., 2004). A subset of 41 of the norovirus samples listed above was chosen for

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method comparison. Samples were selected to include both GI and GII noroviruses detected

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over the course of several years (2007-2011). These samples had previously been identified

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as norovirus GI or GII by real-time RT-PCR, but had not been genotyped. All samples

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underwent both sequencing-based genotyping and RT-PCR/ESI-MS genotyping using the

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newly developed plate and the identifications from each method were compared. The DNA

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sequences obtained through sequencing-based genotyping were submitted to GenBank

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(Accession No. KF569765-KF569799).

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2.5 Statistical analysis

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Concordance among RT-PCR/ESI-MS-determined genotypes and strains for norovirus samples involved in outbreaks was assessed statistically by assigning a numerical value to

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each outbreak. Concordant outbreaks were assigned a score of 2, semi-concordant outbreaks

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were assigned a score of 1, and discordant outbreaks were assigned a score of 0. An outbreak

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was considered to be concordant when all samples from that outbreak showed the exact same

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top match or matches to the ESI-MS database, resulting in the exact same identification. An

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outbreak was considered to be semi-concordant when all samples from that outbreak shared a

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top match to the ESI-MS database, but one or more samples also showed a top match to

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another entry in the database. Discordant outbreaks were those in which none of the top

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matches to the ESI-MS database were shared by all samples from a given outbreak. After

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each outbreak was assigned a concordance value, the samples were randomly sorted into new

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outbreak groups and the same scoring system was carried out. Analyses were performed

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separately based on concordance among top genotype matches and concordance among top

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strain matches. For the purposes of this paper, strains were defined as distinct signatures in

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the ESI-MS database. The scores of the randomized samples were compared to the original

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samples using a Pearson’s chi-square test in IBM SPSS Statistics 21 (Armonk, NY), with a

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pre-determined significance value of p < 0.05, two-tailed.

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3. Results and Discussion

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3.1 Assay and database design

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A total of 13 primer pairs were designed to amplify ~50-150 bp fragments of norovirus RNA, hepatitis A virus RNA, and an internal control in a 96-well plate format

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(Table 1; Fig. 1). The ESI-MS database was successfully populated with the expected base

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compositions of over 5000 sequences downloaded from GenBank. In many instances, these

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sequences did not include information for all gene fragments targeted in this assay, in which

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case the expected signature could only be generated for a portion of the fragments. In a few

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cases, incomplete sequences that shared base counts with many other database entries and

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were only amplified by one set of primers were removed from the database to improve data

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interpretation. RT-PCR/ESI-MS base composition signatures were successfully obtained for

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the 36 previously genotyped norovirus samples analyzed in this study (Table 2). These

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samples had a total of 21 unique RT-PCR/ESI-MS signatures that were added to the database

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prior to inclusivity and exclusivity testing.

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Due to limitations in sample collection, the reference samples used in the database only included information for 5 genotypes: GI.3, GII.1, GII.4, GII.6, and GII.12, with 78% of

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samples identified as GII.4 Minerva or GII.4 New Orleans. However, these samples represent

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some of the most predominant genotypes associated with outbreaks. For example, GII.12

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accounted for 20% of noroviruses submitted to CDC from October 2009 to June 2010 (Vega

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and Vinje, 2011) and GII.4 strains were found to be responsible for 44% of U.S. outbreaks

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over the course of 1994-2006 (Zheng et al., 2010) and 62% of global outbreaks over 2001-

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2007 (Siebenga et al., 2009). The GII.4 strains Minerva (also known as GII.4 2006b) and

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New Orleans have been predominant outbreak strains in the U.S., with Minerva surfacing in

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late 2005/early 2006 and New Orleans surfacing in 2009 (Vega et al., 2011). Interestingly,

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the RT-PCR/ESI-MS signatures determined for these two GII.4 strains showed a number of

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subtypes due to differences in base compositions of the amplified regions; the GII.4 Minerva

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samples revealed 6 unique signatures and the GII.4 New Orleans samples revealed 10 unique

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signatures (Table 2). These differences are likely due to the fact that the RT-PCR/ESI-MS

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assay targets multiple regions of the norovirus genome and therefore is able to determine

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sequence variation at multiple locations.

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3.2 Inclusivity and exclusivity testing

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Norovirus samples used for inclusivity testing included representatives of GI (n = 16),

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GI/GII (n = 1), and GII (n = 126), as well as 17 samples with no genogroup information

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(Table 3). Among these samples, 92% were identified as norovirus and 8% could not be

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detected by RT-PCR/ESI-MS. Previous PCR/ESI-MS studies have found similar to slightly

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higher levels of sensitivity, ranging from 92 to 100% (Blyn et al., 2008; Eshoo et al., 2010;

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Sampath et al., 2012; Sampath et al., 2007a). The estimated number of genomic copies per

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norovirus-positive well ranged from 26 to >2000 copies. It should be noted that these levels

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are only approximate and are based on relative amplification in comparison to the calibrant.

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Furthermore, above 2000 genome copies per well, the levels of target organism far exceed

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those of the calibrant, resulting in an inaccurate estimate of the target concentration (Jacob et

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al., 2012; Sampath et al., 2012). In these cases, it can only be determined that the amplicon is

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present in the well at high levels (i.e., >2000 copies). Q-scores ranged from 0.85 to 0.99, with

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an average of 0.96, indicating high-quality matches to the database entries. Among the

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samples detected by RT-PCR/ESI-MS for which genogroup information was originally

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available, the RT-PCR/ESI-MS genogroup designation showed high concordance (98%) with

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the original real-time RT-PCR-based identification (Table 3). All 125 samples of GII

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detected by RT-PCR/ESI-MS were correctly identified as belonging to this genogroup and the

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1 sample previously identified as GI/GII also matched both GI and GII signatures in the RT-

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PCR/ESI-MS database, indicating a case of illness involving multiple norovirus genogroups.

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As mentioned previously, GI and GII noroviruses have been reported to occur together in a

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small percentage (3-12%) of outbreaks (Hall et al., 2012; Matthews et al., 2012). Among the

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10 GI samples detected by RT-PCR/ESI-MS, 8 were identified as GI and 2 showed top

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matches to both GI and GII signatures within the RT-PCR/ESI-MS database. Considering

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that the assay was designed with a focus on GII noroviruses, particularly GII.4 strains, it is not

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surprising that a greater identification success rate was observed with this genogroup as

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compared to the GI noroviruses. The 13 norovirus samples that could not be detected by RT-

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PCR/ESI-MS were relatively old samples within the dataset, having originally been collected

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during 2007-2008, and included 6 samples with no genogroup information, 6 originally

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identified as GI and 1 originally identified as GII. These samples likely failed due to poor

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quality, as the nucleic acid may have degraded over time. Alternatively, it is possible that

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polymorphisms in the primer-binding areas prevented amplification of the target regions.

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The 147 samples that tested positive for norovirus with RT-PCR/ESI-MS (Table 3) were also assigned a genotype based on the top match(es) to entries in the ESI-MS database.

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Within GI, the following genotypes were detected: GI.2, GI.3, GI.4, GI.P3/GI.11, and GI.14.

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Within GII, the genotypes that were detected included: GII.1, GII.4, GII.5, GII.6, GII.12,

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GII.13, GII.16, GII.17, and several recombinants: GII.Pa-GII.3, GII.P12-GII.10, GII.P16-

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GII.2, and GII.P19-GII.5. Nomenclature for recombinant noroviruses is as described in

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Kroneman et al. (2013), where the RdRp-based genotype is listed first (with a capital P for

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‘polymerase’), followed by the VP1-based genotype. The majority of samples (n = 119)

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matched only one genotype in the database, with GII.4 having the greatest number of matches

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(n = 90). The remaining samples showed top matches to 2-3 genotypes and/or recombinant

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genotypes in the database.

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All three of the hepatitis A virus samples were correctly identified by RT-PCR/ESIMS (Table 3). Hepatitis A virus has been classified into three human (I-III) and three simian

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(IV-VI) genotypes, with genotypes I and III most commonly isolated from humans (Nainan et

314

al., 2006). The human genotypes have been further divided into subtypes A and B, based on

315

genetic relatedness. Although this assay was only designed with the goal of detecting

316

hepatitis A virus, each of the three samples tested (IA, IB, and IIIA) was also correctly

317

identified at the subgenotype level by RT-PCR/ESI-MS. While these results are promising,

318

additional testing will be necessary to determine whether or not the assay is a reliable

319

indicator of hepatitis A virus genotypes and/or subgenotypes.

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As shown in Table 3, no cross reactivity was observed during exclusivity testing with murine norovirus, feline calicivirus, and poliovirus, with all samples testing negative for

322

norovirus and hepatitis A virus. Furthermore, the norovirus primers did not show any cross-

323

reactivity when tested against hepatitis A virus and the hepatitis A virus primers did not cross-

324

react with norovirus samples. The 10 stool samples previously identified as being negative

325

for norovirus with real-time RT-PCR all tested negative for norovirus and hepatitis A virus, as

326

well as the 11 reagent blanks from RNA extraction and 23 non-template controls (Table 3).

327

These results demonstrate the high specificity (100%) of the assay developed here, with no

328

false positives observed. Previous PCR/ESI-MS studies have also reported high levels of

329

specificity, with values of 94-100% (Blyn et al., 2008; Crowder et al., 2012; Eshoo et al.,

330

2010; Sampath et al., 2012; Sampath et al., 2007a).

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3.3 Comparison to recognized method

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were also genotyped using a currently recognized sequencing-based method (Vinje et al.,

334

2004) for comparison (Table 4). Out of the 41 samples tested, initially 31 were identified by

335

both methods and 22 of these showed concordant identifications, meaning that the sample

336

matched the exact same genotype when tested with RT-PCR/ESI-MS as it did when tested

337

with sequenced-based genotyping. When the results of repeat RNA extraction and

338

sequencing analyses were included for two samples identified as possible mix-ups, a total of

339

32 samples were detected by both methods and 24 showed concordant identifications.

340

Subsequent discussion of results incorporates these two updated identifications. Five samples

341

showed semi-concordant identifications, meaning that the genotype identified by sequencing

342

was also among the top matches to the ESI-MS database, but additional genotypes were also

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among the top database matches. Three of the samples were discordant, meaning that the

344

genotype identified by sequencing was not among the top matches identified by ESI-MS.

345

Among the samples that could not be identified by one or both methods, 5 could not be

346

identified by PCR/ESI-MS, 3 could not be identified by sequencing and 1 could not be

347

identified by either method.

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Within the GI noroviruses (n = 16), 10 samples were genotyped by both methods: 7 samples showed complete concordance, 2 were semi-concordant, and 1 was discordant (Table

350

4). The concordant samples included 2 GI.2 noroviruses and 5 GI.3 noroviruses detected with

351

Q-scores of 0.93-0.99 and at levels of 48-1586 genomes/well. One of the semi-concordant

352

samples was identified as GI.3 by sequencing, but had multiple database matches (GI.3 and

353

GII.12) when tested with RT-PCR/ESI-MS. The primary match was to GI.3, with a Q-score

354

of 0.98 and a level of 1564 genomes/well compared to the secondary match to GII.12 with a

355

Q-score of 0.91 and a level of 172 genomes/well. The other semi-concordant sample was also

356

identified as GI.3 by sequencing, but had database matches to both GI.3 and GII.4 when

357

tested with RT-PCR/ESI-MS. As with the other sample, the GI.3 identification showed a

358

higher Q-score and level compared to the GII.4 identification. In both cases with semi-

359

concordant results, the secondary match was to a database entry originating from GenBank

360

with limited sequence information, whereas the top match was to a database entry obtained

361

from one of the GI.3 reference norovirus samples used to initially build the database (Table 2).

362

The one discordant sample was identified as GI.3 by sequencing, but RT-PCR/ESI-MS

363

identified it as GI.4 (Q-score = 0.88; level = 488 genomes/well). The low Q-score indicates a

364

poor quality match that may be improved with the incorporation of GI.4 reference samples

365

into the RT-PCR/ESI-MS database. RT-PCR/ESI-MS was unable to detect five of the

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samples identified by sequencing as GI.3 and both methods were unable to detect one sample

367

originally identified by real-time RT-PCR as a GI norovirus. The inability of RT-PCR/ESI-

368

MS to amplify some of the GI.3 samples may reflect a lack of primer specificity for this

369

genotype. Additionally, all six samples that failed to amplify were collected during the years

370

2007-2008 and the viral nucleic acid may have degraded over time.

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As expected, GII noroviruses showed greater success with the RT-PCR/ESI-MS assay, with detections obtained for all 24 GII samples (Table 4). Three of these samples could not

373

be identified with the sequencing-based method even though they previously tested positive

374

for norovirus GII with real-time RT-PCR. In all 3 cases, RT-PCR/ESI-MS was able to

375

identify these noroviruses at the genotype level (Q-scores 0.96-0.99, 564-1662 copies/well).

376

Among the remaining 21 samples, 17 showed complete concordance between the RT-

377

PCR/ESI-MS genotype and the sequencing-based genotype, with the majority of samples (n =

378

10) identified as GII.4. Samples of GII.1 and GII.12 also showed concordant genotype

379

identifications between the two methods. As shown in Table 4, 2 of the GII samples showed

380

semi-concordant genotype identifications and 2 showed discordant genotype identifications.

381

In both instances of semi-concordant genotype identifications, the ESI-MS identification with

382

the highest Q-score was concordant with the sequencing result, while secondary ESI-MS

383

identifications with lower Q-scores did not agree with the sequencing result. This trend was

384

also observed with the GI noroviruses (discussed above), indicating the importance of

385

considering Q-score in the interpretation of results.

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Among the discordant results for GII noroviruses, one sample was identified by

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sequencing as GII.4 and by RT-PCR/ESI-MS as GII.16 and the recombinant GII.P12/GII.10

388

(Q-score = 0.89, >2000 copies/well). The low Q-score for this sample indicates a relatively

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poor quality match to entries in the ESI-MS database, a result which may be improved upon

390

as more reference samples are added to the database. Indeed, a previous study using

391

PCR/ESI-MS for the detection of fungi reported that an upgrade to the fungal database

392

reduced the number of misidentifications observed with the assay (Simner et al., 2013). The

393

third discordant sample was identified as GII.4 by RT-PCR/ESI-MS (Q-score = 0.99, >2000

394

copies/well) and as Bacteroides spp. by sequencing, even though it was previously identified

395

as a GII norovirus by real-time RT-PCR. The most likely explanation for this discordance is

396

that the original stool sample contained both norovirus GII and Bacteroides spp., which are

397

significant inhabitants of the gastrointestinal tract and are found in human feces (Wexler,

398

2007). This particular strain of Bacteroides appears to have been preferentially amplified by

399

the norovirus sequencing primers but not by the RT-PCR/ESI-MS assay.

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Much of the discordance between the sequencing-based method and the RT-PCR/ESIMS method is likely due to the use of incomplete sequences derived from GenBank to

402

populate the ESI-MS database. In many cases, these sequences did not provide full coverage

403

of the regions targeted by the assay and therefore only provided partial matches to the ESI-

404

MS signatures. As more reference samples with complete information for the target regions

405

are added to the database, the occurrence of semi-concordant or discordant results is likely to

406

be reduced. An additional source of discordance may be due to differences in genome

407

coverage between the two methods. While the sequencing-based method assigns genotype

408

based on only a portion of the norovirus genome (< 260 bp) within the VP1 gene (Vinje et al.,

409

2004), RT-PCR/ESI-MS targets multiple regions of the genome within short stretches (50-150

410

bp) of both the RdRp and VP1 genes. Recombination of norovirus genomes at the ORF1-

411

ORF2 junction is common and can result in a different genotype for the RdRp region as

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compared to the VP1 region (Bull et al., 2007). Therefore, it is possible that a sample

413

identified as one genotype by sequencing may show multiple matches by RT-PCR/ESI-MS

414

due to recombination. While this results in the potential for RT-PCR/ESI-MS to show

415

conflicting results when compared to sequencing, it also allows for greater potential for

416

discovery of variants and recombinants that may not have been detected with sequencing

417

alone. Furthermore, RT-PCR/ESI-MS is able to detect multiple strains within one sample,

418

which may contribute to some discordance when comparing identifications with sequencing-

419

based results, especially if one strain is present in lower concentrations.

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Taken together, the results presented above show that the RT-PCR/ESI-MS assay has

421

a number of advantages and disadvantages when compared to the sequencing-based method.

422

One advantage, which has been illustrated in previous RT-PCR/ESI-MS studies (Crowder et

423

al., 2010; Sampath et al., 2005), is the ability to identify mixtures of multiple genotypes in one

424

sample. Additionally, by covering multiple regions of the norovirus genome, the RT-

425

PCR/ESI-MS assay has potential for a higher level of differentiation among strains than that

426

achieved with sequencing. Considering the high level of diversity and rapid evolution of

427

norovirus strains, especially GII.4 strains (Siebenga et al., 2007; Siebenga et al., 2009; Zheng

428

et al., 2010), coverage of multiple regions also improves the possibility of detecting norovirus

429

using a single assay. Similarly, previous studies found RT-PCR/ESI-MS to be advantageous

430

for the simultaneous detection and differentiation of arboviruses, which are also genetically

431

diverse RNA viruses that often require multiple assays for their detection (Eshoo et al., 2007;

432

Grant-Klein et al., 2010). A further advantage of ESI-MS is its ease of use, as it involves

433

fewer steps than sequencing-based methods and relies primarily on automation. However, a

434

disadvantage of the RT-PCR/ESI-MS assay is that the results are not always concordant with

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the sequencing-based assay, especially in the case of GI or recombinant noroviruses. This is

436

likely to improve as the database is populated with more reference samples, but it may never

437

reach full concordance due to the multiple regions targeted by the RT-PCR/ESI-MS assay and

438

the ability of this assay to detect multiple strains in one sample. With the above in mind, it is

439

recommended that the RT-PCR/ESI-MS assay be used to assist with the rapid detection and

440

differentiation of noroviruses, but that traditional sequencing should also be performed for

441

confirmation purposes. As more reference sample sequences are added to the database, it is

442

expected that the RT-PCR/ESI-MS assay will become an increasingly powerful tool for

443

norovirus testing.

444

3.4 Outbreak concordance

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As a further step in evaluating the usefulness of the RT-PCR/ESI-MS assay for

446

norovirus typing in outbreak and surveillance situations, the top ESI-MS database matches for

447

norovirus samples in this study associated with outbreaks were compared for genotype and

448

strain concordance within each outbreak (Figs. 2a and 2b). These samples (n = 131) were

449

associated with 50 different outbreaks in Orange County, CA, including 26 outbreaks with 2

450

samples per outbreak and 24 outbreaks with 3 or more samples per outbreak. Complete

451

concordance among genotype identifications was observed for 24 of the 26 outbreaks

452

represented by 2 cases, meaning that both samples from the same outbreak showed the exact

453

same top match or matches to the ESI-MS database. The majority (n = 21) of the outbreaks

454

with concordant genotype results were associated with GII.4, while a few were associated

455

with other genotypes, including GI.3, GII.1, GII.12, and GII.17. One of the outbreaks

456

represented by 2 cases showed semi-concordant genotype results, in which one sample

457

showed top matches to GII.4 and GII.17 and the other sample showed top matches to GII.4,

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GII.17, and GII.P16/GII.2. The one outbreak represented by 2 cases that showed discordant

459

genotype results was associated with one sample that had a top match to GII.4 and another

460

sample with a top match to GII.1. When the 26 outbreaks represented by 2 cases each were

461

compared based on identification of samples at the strain level, there were 17 outbreaks with

462

concordant results, 4 outbreaks with semi-concordant results, and 5 outbreaks with discordant

463

results. The majority (82%) of concordant outbreaks were associated with GII.4 strains, while

464

the remaining concordant outbreaks were associated with GI.3, GII.1, or GII.12 strains. The

465

outbreaks with semi-concordant strain identifications included the 1 outbreak described above

466

with semi-concordant genotype results, as well as 3 involving strains from GII.4 and GII.17.

467

With the exception of the outbreak described above involving 2 different genotypes,

468

outbreaks with discordant strain identifications were all associated with GII.4, but were linked

469

to different GII.4 strains in the database.

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Outbreaks represented by 3 or more cases are shown graphically (Figs. 2a and 2b). As

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shown in Fig. 2a, samples from the same outbreak had a high level of genotype concordance,

472

with 18 of 24 outbreaks showing 100% concordance among all samples analyzed. These

473

outbreaks were each represented by 3-5 samples and were primarily outbreaks of GII.4 (n =

474

14), but also included one outbreak of each of the following: GII.1, GII.6, GII.12, and a set of

475

recombinants (GII.P16/GII.2 and GII.Pa/GII.3). An additional 5 outbreaks showed

476

concordance among genotype results for the majority of samples, but had one sample with

477

semi-concordant genotype results. For example, 2 of the samples associated with outbreak no.

478

2 showed top matches to GII.4 and a third sample showed a top match to database entries

479

corresponding to GII.4 and GII.17. Only 1 of the 24 outbreaks had samples that showed

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480

discordant genotype results (outbreak no. 7). This outbreak had 2 samples with top matches

481

to both GII.16 and GII.P12/GII.10, while a third sample had a top match to GII.4.

482

As shown in Fig. 2b, when the results were compared on the basis of the top strain(s) in the database matching each sample, the number of concordant outbreaks decreased. Out of

484

the 18 outbreaks that showed concordance on the basis of genotype, only 9 continued to show

485

complete concordance with strain identifications. For most (80%) of the outbreaks showing

486

semi-concordance or discordance, the majority of samples showed complete concordance for

487

the top strain match, with just one sample showing a semi-concordant or discordant result.

488

For example, all 5 samples from outbreak no. 17 showed a top match to one of the ESI-MS

489

signatures for GII.4 New Orleans, but 1 of the samples also matched another ESI-MS

490

signature linked to a different sample of GII.4 New Orleans found in the database. Since

491

strains are defined here as ESI-MS database entries with distinct signatures, this sample was

492

determined to be semi-concordant.

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The results of statistical analysis on all outbreak samples revealed that both genotype and strain concordance values were significantly greater (p < 0.05, two-tailed) for the original

495

ESI-MS identifications as compared to the randomized dataset. Based on a scale of 0

496

(discordant) to 2 (fully concordant), the average genotype concordance score for the original

497

dataset was 1.8 ± 0.6 compared to 1.0 ± 1.0 in the randomized dataset, while the average

498

strain concordance score for the original dataset was 1.3 ± 0.8 compared to 0.1 ± 0.4 in the

499

randomized dataset. These results show that RT-PCR/ESI-MS allows for a high level of

500

agreement among outbreak samples based on genotype, with an average score close to that for

501

full concordance. The lower level of agreement found with strains is likely due to the fact

502

that single nucleotide polymorphisms among samples associated with the same outbreak can

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result in different matches to the database, especially when the database is largely comprised

504

of fragmented sequences from GenBank. As the database becomes updated with additional

505

reference samples, it is likely that the concordance score will improve. Overall, the results of

506

the outbreak concordance analysis indicate the potential usefulness of this assay for norovirus

507

detection and differentiation in surveillance and outbreak applications, especially with regard

508

to genotype identifications.

509

4. Conclusions

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An RT-PCR/ESI-MS assay was developed in this study for the detection and

511

differentiation of human noroviruses as well as the detection of hepatitis A virus. The assay

512

was successful at identifying human norovirus in 92% of clinical samples and showed a

513

specificity of 100% when tested against closely related viruses. In addition to detection of

514

norovirus, the assay was able to correctly identify norovirus at the genogroup level in 98% of

515

amplified samples and at the genotype level in 71-75% of samples. As more reference

516

samples are added to the database, the genotyping ability of the assay is expected to improve.

517

This assay shows potential to reduce the time and labor needed to detect and differentiate

518

noroviruses and may enhance the ability of public health scientists to identify the source and

519

the spread of norovirus illnesses related to outbreak situations. In addition to identification of

520

strains currently in circulation, this assay allows for the classification of recombinants and

521

new norovirus strains due to its range of target amplicons. Importantly, this assay would not

522

be expected to replace the current sequencing-based genotyping method, but rather it would

523

provide an additional tool for rapid characterization of noroviruses in outbreak or surveillance

524

situations.

525

Acknowledgments

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Funding for this study was provided by the FDA Center for Food Safety and Applied

527

Nutrition (CFSAN). We would like to thank the FDA Commissioner's Fellowship

528

Program; Steven Musser, John Callahan, Rebecca Bell, Marc Allard, and Erik Burrows at

529

FDA/CFSAN for their support; Lee-Ann Jaykus at North Carolina State University for

530

assistance with this project; and Natasha Fazel for help with sample processing.

531

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genogroup II-genotype 4 noroviruses in the United States between 1994 and 2006.

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Figure 1. Layout of the RT-PCR/ESI-MS assay plate developed in this study. This assay

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plate is able to process 12 samples per run and can simultaneously test for the presence of

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norovirus and hepatitis A virus. PP, PCR primer pair(s).

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Figure 2a. Concordance among the genotype identified by RT-PCR/ESI-MS for samples (n =

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79) from the same outbreak.

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Figure 2b. Concordance among strains identified by RT-PCR/ESI-MS for samples (n = 79)

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from the same outbreak.

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Tables

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Table 1. Primers designed for use in the RT-PCR/ESI-MS assay described in this study. PCR primer pair (PP) groupings indicate singleplex or multiplex arrangements. RdRp, RNA-dependent RNA polymerase; VP1, major capsid protein. PCR primer pair (PP) grouping

Target organism

Target gene

Product length

Primer sequences, 5’-3’ (F, forward; R, reverse)

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PP1

Norovirus GII and GIV

RdRp

57 bp

F: TGGGAGGGCGATCGCAATCT R: TCATTCGACGCCATCTTCATTCAC

5742

PP2

Norovirus GI and GII

RdRp

101 bp

F: TAGGCCATGTTCCGCTGGAT R: TGTCCTTCGACGCCATCATCATT

5698

PP3

Norovirus GII, including all GII.4

VP1

141 bp

F: TCAGAGGTCAACAATGAGGTTATGGC R: TACTGTAAACTCTCCACCAGGGGC

5699

PP4

Norovirus GII.4

VP1

3035

PP4

Hepatitis A virus

62 bp

5656

PP5

Norovirus GI

Protease gene/RNA polymerase gene VP1

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PP5

Hepatitis A virus

79 bp

5701

PP6

Norovirus GII

RNA polymerase gene VP1

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126 bp

67 bp

120 bp

F: TCAGGAATGGGTGCAGCACTT R: TAGCCTGATTTATGAAGCTTGCACTC F: TGAAAGTCAGAGAATGATGAAAGTGGA R: TGCGTTTTGGAGACTACATTCATTGAACA

F: TTGGAGTCTTTGTCTTTGTTTCTTGGGT R: TCAGGCAGTTCCCACAGGCTT F: TCCAGGGATGTGTGGTGGGGC R: TCCAGCAACATGAATGCCCAAAATGGCATTCTG F: TTGGCTGGGAATGCGTTCAC R: TACATCAATAATCACATGAGGGCACAT

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VP1

73 bp

5702

PP7

Norovirus GI

VP1

101 bp

5744

PP7

Norovirus GII.4

VP1

135 bp

5651

PP8

Norovirus GIV

RdRp

120 bp

4437

PP8

Internal Positive Control

N/A

77 bp

F: TGGTTACTTCAGGTTTGATTCTTGGGT R: TCGCCCAGTTCCAGTTCCCA F: TACACCCGGTGATGTTTTGTTTGA R: TCATATTGCCAACCCAGCCATTATACAT F: TCAGGCTATGTCACAGTGGCTCA R: TCGTCTACGCCCCGTTCCA F: TCCTTCTATGGTGATGATGAGATTGTGTC R: TGGGCCCTCTGTCTTGTCTGG F: TGACGAGTTCATGAGGGCAGGC R: TCTGGCCTTTCAGCAAGTTTCCAAC

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Table 2. Norovirus samples (n = 36) used to build the RT-PCR/ESI-MS database. All samples were derived from human stool specimens associated with norovirus illness and were previously genotyped through CaliciNet based on sequencing (Vinje et al., 2004). Strain

Samples (n)

GI.3 GII.1

N/A N/A

2 3

GII.4

Minerva

9

GII.4

New Orleans

19

GII.6

N/A

2

GII.12

N/A

Institution Hotel, long-term care facility Institution, school, long-term care facility Institution, hospital, school, long-term care facility Long-term care facility School

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Outbreak setting(s)

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Collection year(s)

2007 2011

No. of unique RTPCR/ESI-MS signatures 1 2

2008-2011

6

2010-2011

10

2010

1

2011

1

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Table 3. Results of inclusivity, exclusivity and negative control testing with the RT-PCR/ESI-MS assay designed in this study. Test Sample type N RT-PCR/ESI-MS ID (n) Inclusivity Norovirus GI 16 Norovirus GI (n = 8) Norovirus GI/GII (n = 2) Not detected (n = 6) Inclusivity Norovirus GI/GII 1 Norovirus GI/GII Inclusivity Norovirus GII 126 Norovirus GII (n = 125) Not detected (n = 1) Inclusivity Norovirus, genogroup 17 Norovirus GI (n = 3) unknown Norovirus GII (n = 8) Not detected (n = 6) Inclusivity Hepatitis A virus 3 Hepatitis A virus Exclusivity Murine norovirus-1 1 No detections Exclusivity Feline calicivirus 1 No detections Exclusivity Poliovirus type 3 1 No detections Negative Control Norovirus-negative stool 10 No detections sample Negative Control RNA extraction reagent 11 No detections blank Negative Control Non-template control 23 No detections

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Table 4. Identification of norovirus samples (n = 41) by real-time RT-PCR, RT-PCR/ESI-MS and a sequencing-based method for norovirus genotyping (Vinje et al., 2004). RT-PCR/ESI-MS genotype

Genotyping concordance

GI.2 GI.3 GI.3 GI.3 GI.3 GI.3 Unable to genotype GI.3 GII.1b GII.4 GII.4

GI.2 GI.3 GI.4 GI.3 and GII.12 GI.3 and GII.4 Not detected Not detected GI.14, GI.P3/GI.11a and GII.4 GII.1 GII.4 GII.4, GII.12, and GII.17

Concordant Concordant Discordant Semi-concordant Semi-concordant N/A N/A Semi-concordant Concordant Concordant Semi-concordant

1 4 1 1 1 1 1

GII GII GII GII GII GII GII

GII.4 GII.12c GII.12 Bacteroides spp. Negative Negative Negative

a

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Sequencing-based genotype

2 5 1 1 1 5 1 1 3 10 1

Original identification with real-time RT-PCR GI GI GI GI GI GI GI GI/GII GII GII GII

GII.16 and GII.P12/GII.10 GII.12 GII.4 and GII.12 GII.4 GII.6 GII.4 GII.P19/GII.5

Discordant Concordant Semi-concordant Discordant N/A N/A N/A

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Recombinant nomenclature according to Kroneman et al. (2013). One of these samples was originally found to have a mixed sequence, but repeat RNA extraction and sequencing resulted in a GII.1 identification, concordant with the RT-PCR/ESI-MS genotype. c One of these samples was originally identified as GII.1 by sequencing, but repeat RNA extraction and sequencing resulted in a GII.12 identification, concordant with the RT-PCR/ESI-MS genotype. b

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4

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Outbreak No.

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7

8

9

10

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Outbreak No.

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Highlights

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This paper describes a novel method for the identification of human noroviruses. RT-PCR was combined with mass spectrometry to develop a foodborne viral assay. This assay showed a sensitivity of 92% for detection of norovirus in 160 samples. Genogroup and genotype were correctly identified in the majority of viral samples. The assay showed 100% specificity and was also able to detect hepatitis A virus.

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