Genetic and Epidemiologic Trends ofNorovirus Outbreaks in the UnitedStates from 2013 to 2016 DemonstratedEmergence of Novel GII.4 RecombinantViruses

Jennifer L. Cannon,a Leslie Barclay,b Nikail R. Collins,c Mary E. Wikswo,b

Christina J. Castro,d Laura Cristal Magaña,d Nicole Gregoricus,b Rachel L. Marine,b

Preeti Chhabra,e Jan Vinjéb

CDC Foundation, Atlanta, Georgia, USAa; Division of Viral Diseases, Centers for Disease Control and Prevention,Atlanta, Georgia, USAb; Atlanta Research and Education Foundation, Decatur, Georgia, USAc; Oak RidgeInstitute for Science and Education, Oak Ridge, Tennessee, USAd; Synergy America, Inc., Atlanta, Georgia, USAe

ABSTRACT Noroviruses are the most frequent cause of epidemic acute gastroen-teritis in the United States. Between September 2013 and August 2016, 2,715 geno-typed norovirus outbreaks were submitted to CaliciNet. GII.4 Sydney viruses caused58% of the outbreaks during these years. A GII.4 Sydney virus with a novel GII.P16 poly-merase emerged in November 2015, causing 60% of all GII.4 outbreaks in the 2015-2016season. Several genotypes detected were associated with more than one polymerasetype, including GI.3, GII.2, GII.3, GII.4 Sydney, GII.13, and GII.17, four of which harboredGII.P16 polymerases. GII.P16 polymerase sequences associated with GII.2 and GII.4Sydney viruses were nearly identical, suggesting common ancestry. Other commongenotypes, each causing 5 to 17% of outbreaks in a season, included GI.3, GI.5, GII.2,GII.3, GII.6, GII.13, and GII.17 Kawasaki 308. Acquisition of alternative RNA poly-merases by recombination is an important mechanism for norovirus evolution and aphenomenon that was shown to occur more frequently than previously recognizedin the United States. Continued molecular surveillance of noroviruses, including typ-ing of both polymerase and capsid genes, is important for monitoring emergingstrains in our continued efforts to reduce the overall burden of norovirus disease.

KEYWORDS genetic recombination, genotypic identification, noroviruses

Noroviruses are the leading cause of acute gastroenteritis in all age groups, causing18% of all cases globally (1). In the United States, noroviruses are also the most

common cause of outbreaks of acute gastroenteritis (2). Symptoms of vomiting and/ordiarrhea are normally self-limiting, but severe outcomes and deaths have been re-ported, particularly among young children and elderly adults (3). In several countrieswhere rotavirus vaccine programs have been successfully implemented, norovirus isnow recognized as the leading cause of pediatric gastroenteritis (4, 5). Over half of allnorovirus outbreaks in the United States and other industrialized countries occur inhealth care settings, including hospitals and long-term-care facilities (6). Other commonoutbreak settings include restaurants and catered events, cruise ships, schools, childcare facilities, and other institutional settings, the global economic impact of which isestimated to be over $64 billion a year (7, 8).

The norovirus single-stranded RNA genome, approximately 7.5 kb in length, isdivided into three open reading frames (ORFs). ORF1 encodes the nonstructural viralproteins including the RNA-dependent RNA polymerase. ORF2 and ORF3 encode therespective major (VP1) and minor (VP2) structural proteins. VP1 can be further divided

Received 20 March 2017 Returned formodification 19 April 2017 Accepted 25 April2017

Accepted manuscript posted online 10 May2017

Citation Cannon JL, Barclay L, Collins NR,Wikswo ME, Castro CJ, Magaña LC, GregoricusN, Marine RL, Chhabra P, Vinjé J. 2017. Geneticand epidemiologic trends of norovirusoutbreaks in the United States from 2013 to2016 demonstrated emergence of novel GII.4recombinant viruses. J Clin Microbiol 55:2208 –2221. https://doi.org/10.1128/JCM.00455-17.

Editor Yi-Wei Tang, Memorial Sloan KetteringCancer Center

Copyright © 2017 American Society forMicrobiology. All Rights Reserved.

Address correspondence to Jan Vinjé,jvinje@cdc.gov.

J.L.C. and L.B. contributed equally to this article.

VIROLOGY

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into a highly conserved N-terminal shell (S) domain and a protruding (P) domainconsisting of the central P1 region and an inserted, highly variable P2 region, which isthe most surface-exposed region of the norovirus capsid and therefore the target forboth neutralizing antibodies and receptor binding.

Based on phylogenetic clustering of the complete VP1 amino acid sequence,norovirus can be classified into at least seven recognized norovirus genogroups (GI toGVII), among which viruses from the GI, GII, and GIV groups infect humans (9, 10).Genogroups can be further divided into 9 GI, 22 GII, and 2 GIV genotypes (10). Becausecomplete sequencing of VP1 is not routinely performed by most laboratories, smallerregions of ORF2 (e.g., regions C and D) are often used to genotype norovirus strains (8,9). In addition, norovirus strains can be genotyped using partial regions of the ORF1RNA polymerase (P)-encoding region (regions A and B), which has been performed forover a decade (11–13). At least 14 GI polymerase (GI.P) types and 27 GII.P types havebeen described in the polymerase region (10). A dual-nomenclature system has beenproposed for GI and GII noroviruses (9); however, until recently few laboratoriesperformed typing using both ORF1 and ORF2 sequences. Recombination amongnorovirus strains occurs primarily at the ORF1-ORF2 junction and happens more oftenthan previously recognized (14–18).

Since the mid-1990s, genogroup II genotype 4 (GII.4) noroviruses have caused themajority of outbreaks and sporadic cases worldwide (19). Since 2002, new GII.4 variantshave emerged every 2 to 3 years, resulting in epidemics and sometimes globalpandemics (20). GII.4 norovirus evolution is driven by antigenic drift and recombination(21). Mutations of key epitopes in the P2 domain of ORF2 allow emergent variants toescape recognition by neutralizing antibodies generated by previously circulating GII.4variants (22). Such mutations can also alter the repertoire of histo-blood group antigen([HBGA] attachment factors associated with genetic susceptibility to certain norovirusstrains [23]) that GII.4 variants recognize, potentially allowing previously naive popu-lations to become genetically susceptible (24). Intragenotypic (possibly also intergeno-typic) recombination occurring primarily at the ORF1-ORF2 junction, but also withinORF2 and at the ORF2-ORF3 junction, is another mechanism for the emergence ofpandemic GII.4 variants (25). Epidemic GII.4 variants reported in 1995 to 1996, 2002,2004, and 2006 evolved primarily through antigenic drift, and GII.4 variants reported in2009 and 2012 evolved through recombination (21). Some of these variants wereresponsible for increased outbreak activity among vulnerable populations and in healthcare settings (19, 25); however, this was not the case for GII.4 Sydney, which emergedin 2012 (26). Non-GII.4 strains can also contribute significantly to the norovirus diseaseburden. GII.12, GII.1, and GI.6 viruses have been reported to cocirculate with GII.4 strainsand to contribute to as much as 15% of all norovirus outbreaks during a season (8).

In this report, we describe the molecular epidemiology of norovirus outbreaks in theUnited States from 1 September 2013 to 31 August 2016 as a continuation of ourprevious publications (8, 27). In the winter of 2015 to 2016, a novel GII.4 virus emergedwhich had similarities to the pandemic GII.4 Sydney virus in the capsid region but hada unique polymerase sequence (GII.P16). By combining two previously published typingprotocols (12, 28), we implemented a dual-typing (polymerase and capsid [P-C]) assay,allowing robust detection of multiple cocirculating GI and GII norovirus genotypes.

RESULTSGenotype and seasonal distribution of norovirus outbreaks submitted to

CaliciNet, 2013 to 2016. A total of 2,715 genotyped norovirus outbreaks weresubmitted to CaliciNet from 1 September 2013 through 31 August 2016; 1,083 out-breaks were submitted in 2013 to 2014, 910 outbreaks were submitted in 2014 to 2015,and 722 outbreaks were submitted in 2015 to 2016 (Fig. 1). GII.4 Sydney viruses caused595 (54.9%), 641 (70.4%), and 338 (46.8%) outbreaks, respectively, during the 3-yearstudy (Table 1). Other genotypes that caused 5% or more outbreaks for one or moreyears included GI.3, GI.5, GII.2, GII.3, GII.6, GII.13, and GII.17 (Fig. 1; Table 1). Genotypesrepresenting less than 5% of all outbreaks included the following genotypes: GI.1, GI.2,

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GI.4, GI.6, GI.7, GI.9, GII.1, GII.7, GII.8, GII.10, GII.12, GII.14, GII.15, GII.25 (a tentative newgenotype), and GIV and mixed outbreaks containing more than one genotype (Table 1).

There was a clear winter seasonality for norovirus outbreaks that was drivenprimarily by GII.4 noroviruses (Fig. 1). The proportion of outbreaks caused by allnorovirus genotypes occurring from 1 January through 31 March (3-year total of 1,385outbreaks [51.0%], with 52.8%, 52.8%, and 46.1% of all outbreaks each consecutiveyear) was higher than the proportion of outbreaks occurring in other quarters of theyear (P � 0.01). Among GII.4 noroviruses, 57.2%, 61.5%, and 49.1% of all GII.4 outbreaksoccurred during these months for the consecutive years, more than any other quarter(P � 0.01). However, outbreaks caused by other genotypes also peaked during the

FIG 1 Distribution, by month, of norovirus genotypes from outbreaks submitted to CaliciNet from 1 September 2013 through31 August 2016. “Other” includes the following capsid genotypes: GI.1, GI.2, GI.4, GI.6, GI.7, GI.9, GII.1, GII.5, GII.7, GII.8, GII.4 NewOrleans, GII.4 Den Haag, GII.10, GII.12, GII.14, GII.15, a tentative novel genotype, GIV, and mixed outbreaks containing morethan one GI or GII genotype.

TABLE 1 Number and percentage of outbreaks by genotype and by year

Genotype (year)

No. (%) of outbreaksTotal no. (%) ofoutbreaks2013–2014 2014–2015 2015–2016

GI.1 2 (0.2) 4 (0.4) 1 (0.1) 7 (0.3)GI.2 13 (1.2) 43 (4.7) 8 (1.1) 64 (2.4)GI.3 181 (16.7) 36 (4.0) 24 (3.3) 241 (8.9)GI.4 3 (0.3) 1 (0.1) 2 (0.3) 6 (0.2)GI.5 4 (0.4) 17 (1.9) 51 (7.1) 72 (2.7)GI.6 20 (1.9) 5 (0.6) 3 (0.4) 28 (1.0)GI.7 4 (0.4) 1 (0.1) 0 (0.0) 5 (0.2)GI.9 2 (0.2) 0 (0.0) 2 (0.3) 4 (0.2)GII.1 5 (0.5) 5 (0.6) 29 (4.0) 39 (1.4)GII.2 21 (1.9) 12 (1.3) 90 (12.5) 123 (4.5)GII.3 42 (3.9) 6 (0.7) 50 (6.9) 98 (3.6)GII.4 Den Haag (2006) 1 (0.1) 1 (0.1) 0 (0.0) 2 (0.1)GII.4 New Orleans (2009) 2 (0.2) 0 (0.0) 0 (0.0) 2 (0.1)GII.4 Sydney (2012) 595 (54.9) 641 (70.4) 338 (46.8) 1,574 (58.0)GII.5 15 (1.4) 0 (0.0) 0 (0.0) 15 (0.6)GII.6 42 (3.9) 94 (10.3) 11 (1.5) 147 (5.4)GII.7 44 (4.1) 10 (1.1) 4 (0.6) 58 (2.1)GII.8 1 (0.1) 3 (0.3) 0 (0.0) 4 (0.2)GII.10 0 (0.0) 1 (0.1) 3 (0.4) 4 (0.2)GII.12 1 (0.1) 0 (0.0) 0 (0.0) 1 (0.0)GII.13 58 (5.4) 0 (0.0) 13 (1.8) 71 (2.6)GII.14 10 (0.9) 1 (0.1) 3 (0.4) 14 (0.5)GII.15 1 (0.1) 0 (0.0) 0 (0.0) 1 (0.0)GII.17 3 (0.3) 19 (2.1) 75 (10.4) 97 (3.6)GII.25 1 (0.1) 0 (0.0) 0 (0.0) 1 (0.0)GIV 0 (0.0) 0 (0.0) 1 (0.1) 1 (0.0)Mixed 12 (1.1) 10 (1.1) 14 (1.9) 36 (1.3)

Total 1,083 (100.0) 910 (100.0) 722 (100.0) 2,715 (100.0)

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winter months: GI.3 and GII.13 in the winter of 2013 to 2014, GII.6 in the winter of 2014to 2015, and GI.5, GII.2, GII.3, and GII.17 Kawasaki 308 in the winter of 2015 to 2016(Fig. 1). GII.17 Kawasaki 308 noroviruses caused 10.4% of all outbreaks in 2015 to 2016(Table 1).

Emergence of a novel GII.4 Sydney recombinant. In November 2015, GII.4 viruseswere detected that had �2% (3.7% to 4.9%) nucleotide difference in region C com-pared to the GII.4 Sydney viruses that had been circulating since 2012. Completegenome sequencing by next-generation sequencing (NGS) showed that this was arecombinant virus with a GII.4 Sydney capsid and a GII.P16 polymerase (GII.P16-GII.4Sydney), closely related to a virus detected in Japan in 2016 (29). In 2015 to 2016, 208(61.5%) of the 338 GII.4 outbreaks and 28% of the total number of outbreaks werecaused by this novel GII.P16 recombinant. In addition, GII.4 Sydney viruses sharing�98% nucleotide identity with the GII.4 Sydney reference strain of the capsid genecaused 130 (38.5%) of all GII.4 outbreaks and 18% of all outbreaks in 2015 to 2016.

Additional recombinant noroviruses with GII.P16 polymerases were foundamong GII.2, GII.3, and GII.13 genotypes. Dual typing was performed for viruses from410 outbreaks (Table 2). Several genotypes were detected that were associated withmore than one polymerase type, including GI.3, GII.2, GII.3, GII.4 Sydney, GII.13, andGII.17. The GII.P16 polymerase was found associated with GII.2, GII.3, GII.4 Sydney, andGII.13 genotypes. In addition, noroviruses having the GII.Pe polymerase were primarilyassociated with GII.4 Sydney but also with three GII.17 outbreaks occurring in 2015.These GII.Pe-GII.17 viruses shared �98% nucleotide identity with a GII.Pe-GII.17 virusfrom Hong Kong in 2015. All other GII.17 viruses had the GII.P17 polymerase typical ofGII.17 Kawasaki 308 viruses. Viruses with GII.P12 and GII.P21 polymerases were associ-ated with GII.3. Of note, in samples from 30 outbreaks, GII.4 Sydney viruses with a GII.P4

TABLE 2 Dual typing of norovirus outbreaks reported in CaliciNet, 1 September 2013through 31 August 2016

Genogroup and capsidgenotype

Percentage ofoutbreaks availablefor dual typing Polymerase type

No. of outbreakswith dual typing

GIGI.1 28.6 GI.P1 2GI.2 1.6 GI.P2 1GI.3 4.6 GI.P3 3

GI.Pa 1GI.Pd 7

GI.5 12.5 GI.P5 9

GIIGII.2 65.9 GII.P2 77

GII.P16 1GII.Pe 3

GII.3 25.5 GII.P12 14GII.P21 6GII.P16 5

GII.4 Den Haag 50 GII.P4 Den Haag 1GII.4 Sydney 14.5 GII.Pea 138

GII.P4 New Orleansa 30GII.P16a 71

GII.6 3.4 GII.P7 5GII.10 25.0 GII.Pg 1GII.13 7.0 GII.P16a 3

GII.Pe 1GII.14 14.3 GII.P7a 2GII.17 36.1 GII.P17a 32

GII.Pea 3

GIVGIV 100 GIV 1

aIncludes mixed-genotype outbreaks.

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New Orleans polymerase were detected (Table 2). This virus was detected in 2014 to2016 although GII.Pe-GII.4 Sydney predominated in 2014 to 2015, and GII.P16-GII.4Sydney predominated the following year (Fig. 2).

Genetic similarities among GII.P16 polymerase types associated with differentnorovirus genotypes. Partial polymerase sequences from viruses from 80 outbreakswere typed as GII.P16 (Table 2; Fig. 3). All GII.P16-GII.4 Sydney sequences clustered withthe GII.P16-GII.4 Sydney virus detected in Japan in 2016 (29). Interestingly, GII.P16sequences of GII.2 viruses clustered closely (�98% nucleotide sequence identity) withthe GII.P16 sequences of the GII.4 Sydney viruses, whereas GII.P16 sequences of GII.3and GII.13 viruses formed distinctly separate clades (Fig. 3). Specific nucleotide changeswere observed among the partial polymerase sequences of GII.P16 clades, but only oneamino acid change (K to R at position 1646 of the complete ORF1 amino acid sequence)was detected among 17 (8.2%) GII.P16-GII.4 Sydney outbreaks. The amino acid changedid not occur in any of the other GII.P16 polymerases, including those among GII.2genotypes (data not shown). The GII.P16 polymerase sequences of GII.16 and GII.17viruses formed a clade separate from the GII.P16 sequences identified in our study(Fig. 3).

NGS and three-dimensional modeling showed key amino acid substitutions inthe novel GII.P16 polymerase protein. We obtained nearly full-length sequences of30 specimens from 20 outbreaks (one GII.Pe-GII.4 Sydney, five GII.4 New Orleans-GII.4Sydney, six GII.P16-GII.4 Sydney, five GII.P16-GII.2, one GII.P2-GII.2, and four GII.P16-GII.13 outbreaks, two of which were mixed-genotype outbreaks). Of these, seven nearlyfull-length complete coding sequences were submitted to GenBank. Multiple aminoacid substitutions were observed when the GII.Pe and GII.P16 polymerases of GII.4Sydney viruses were compared with reference sequences for GII.Pe-GII.4 Sydney,GII.P16-GII.3, and GII.P16-GII.13 (GenBank accession numbers JX459908, KF895841, andKM036380, respectively) (Fig. 4). Fitting these amino acid changes to the three-dimensional crystal structure of a human norovirus polymerase showed key amino acidchanges within motifs F (G163A) and C (L337M) and at the RNA binding site (S502N),among other changes within the fingers, palm, and thumb subdomains (Fig. 4). All ofthe changes to the GII.P16-GII.4 Sydney polymerase were also present in the GII.P16-GII.2 polymerase. When the novel GII.P16 polymerase was compared to ancestralGII.P16 polymerases of GII.3 and GII.13 viruses, 6 amino acid (aa) substitutions were

FIG 2 Number of GII.4 Sydney outbreaks from 1 September 2014 through 31 August 2016 submitted to CaliciNet withdual-typing information available. The percentage of all GII.4 outbreaks with polymerase typing information (percentcoverage) is presented above the bars for each month. GII.P4 New Orleans; GII.Pe-GII.4 Sydney is a mixed outbreak with somespecimens typing as GII.P4 New Orleans-GII.4 Sydney and others typing as GII.Pe-GII.4 Sydney.

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FIG 3 Maximum likelihood phylogenetic analysis of GII.P16 polymerase sequences (172 nucleotides)from GII.2, GII.3, GII.4 Sydney, and GII.13 outbreaks in CaliciNet for the period 2013 to 2016.Bootstrap support is indicated (percentage from 500 replicates) with values below 50% hidden.Evolutionary distances were computed using the Kimura two-parameter method with rate variationamong sites modeled with a gamma distribution (shape parameter, 0.55). This substitution modelwas determined to be the best fit, producing the lowest BIC (Bayesian information criterion) andAkaike information criterion (corrected) scores, as determined by the maximum likelihood modeltesting tool (MEGA, version 7.0.18). Reference strains are represented by their GenBank accessionnumbers and indicated with filled circles. Sequences obtained in this study are indicated as follows:Œ, GII.4 Sydney; o, GII.2; ▫, GII.3; �, GII.13.

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observed (at positions 173 and 175 of the fingers subdomain and at positions 293, 332,357, and 360 of the palm subdomain) (data not shown).

Characterization of antigenic regions of VP1 of recombinant GII.4 Sydneyviruses. Consensus sequences of key amino acid residues within VP1 were createdusing specimens from 23 outbreaks with complete GII.4 Sydney VP1 sequences (5GII.Pe, 8 GII.P4 New Orleans, and 12 GII.P16 outbreaks) and 36 outbreaks (19 GII.Pe, 4GII.P4 New Orleans, and 13 GII.P16 outbreaks) for which P2 sequences were available(Fig. 5). For amino acids under positive selection, only the amino acid at position 373changed among the different GII.4 Sydney viruses (R373H). Amino acids T294 and E368of epitope A remained unchanged, but R297H fluctuated among GII.Pe and GII.P4 NewOrleans viruses. At position 393 of epitope D (corresponding with HBGA binding site 2),amino acids fluctuated among the GII.4 viruses, while position 395 remained un-changed. Few changes were observed for amino acids of epitope E. The NERK motif (aa310, 316, 484, and 493) that regulates access to epitope F (30) was conserved for all GII.4viruses of this study although an N310S substitution was observed for about half ofthose with a GII.P4 New Orleans polymerase.

DISCUSSION

From 1 September 2013 to 31 August 2016, 2,715 norovirus outbreaks werereported to CaliciNet. A novel GII.P16-GII.4 Sydney recombinant virus first detected inNovember 2015 became the predominant norovirus genotype in the winter of 2015 to2016, causing over 29% of all norovirus outbreaks. This novel GII.P16 polymerasewas �98% identical to the polymerase of GII.2 viruses detected in the United States in2016 but �5% different from the GII.P16 polymerases detected among GII.3 and GII.13strains.

The percentage of GII.4 outbreaks in 2013 to 2016 was lower than in previous years.GII.4 Sydney viruses caused over 58% of outbreaks in this period in contrast to 72% in2009 to 2012 (8). Non-GII.4 genotypes that caused 5.4% to 16.8% of outbreaks in asingle year included GI.3, GI.5, GII.2, GII.3, GII.6, GII.13, and GII.17 Kawasaki 308. Thesegenotypes are different from the GI.6, GII.1, and GII.12 genotypes that caused a higherthan usual number of outbreaks in the United States in 2009 to 2013 (8). Despite the

FIG 4 Ribbon structure (PDB accession number 1SH0) indicating amino acid changes to the polymeraseof GII.Pe-GII.4 Sydney resulting in the GII.P16 polymerase of GII.4 Sydney and GII.2 genotypes detectedin the United States as early as 2015. Colors indicate the subdomains and motifs where the amino acidchanges reside in the three-dimensional structure and correspond to those outlined in the text box.

FIG 5 Specific amino acid changes, compared to reference strains, within VP1 corresponding to sites under positive selection, antibody recognition epitopes,or HBGA binding sites for three GII.4 Sydney viruses in circulation from 2013 to 2016 in the United States. Consensus sequences were derived by an alignmentof all GII.4 Sydney specimens for which complete VP1 sequences or P2 region sequences were available. Epitope binding regions A, B, C, D, and E and the NERKmotif that blocks access to epitope F are indicated. �, amino acid sites under positive selection; #, sites within HBGA binding site 2. Colors indicate amino acidcategory, as follows: yellow, hydrophobic; green, uncharged; blue, positively charged; red, negatively charged; purple, special. NO, New Orleans.

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emergence and predominance of GII.17 Kawasaki 308 noroviruses throughout Asiabeginning in the winter of 2014 to 2015 (31–33), this genotype caused only 10.4% ofthe U.S. outbreaks in 2015 to 2016. One outbreak each was reported for the very rareGIV and the tentative novel GII genotype previously detected exclusively in sporadiccases or sewage samples (34, 35).

Dual typing of norovirus strains showed norovirus genotypes with multiplepolymerase types. GII.4 Sydney was associated primarily with GII.Pe until 2015 whenthe GII.P16-GII.4 Sydney viruses emerged and caused 61.5% of the outbreaks in2015 to 2016. A GII.P4 New Orleans-GII.4 Sydney virus which has been reported byothers (36–39) also caused 1.1% of all outbreaks. The majority of the GII.3 viruseshad either a GII.P12 or GII.P21 (formerly GII.Pb) polymerase, as has been describedpreviously (15, 40–42), but GII.P16-GII.3 viruses were also found. GII.2 viruses wereprimarily associated with a GII.P2 polymerase, but GII.Pe-GII.2 and GII.P16-GII.2 werealso detected. All GII.17 Kawasaki 308 viruses carried GII.P17 polymerases, which isconsistent with strains reported widely in Asia (32, 43). A GII.Pe-GII.17 virus sharingcommon ancestry with GII.17 viruses dating back to 1966 was also found (32).

Interestingly, the GII.P16 sequences shared by GII.2 and GII.4 Sydney genotypeswere nearly identical to the GII.P16-GII.4 Sydney sequences reported in Japan inJanuary of 2016 (29) and in coastal waters impacted by sewage in China (44). GII.2,GII.3, GII.10, GII.12, GII.13, and GII.17 viruses are known to harbor GII.P16 poly-merases. GII.P16-GII.2 viruses reported previously in China, Japan, and Australia/New Zealand (16, 40, 45, 46) are genetically distinct from the recently emergingGII.P16-GII.2 viruses that caused a sharp increase in the number of norovirusinfections in Germany and China in late 2016 (47, 48). This novel GII.P16-GII.2recombinant virus caused at least seven outbreaks in the United States in 2016 asearly as August. While GII.P16 polymerases associated with different GII capsidshave circulated for decades (17, 18, 42, 49–54) and caused occasional outbreaks (16,55, 56), the GII.P16 polymerase associated with GII.4 Sydney and GII.2 genotypesappears to have made these viruses evolve toward greater transmissibility.

High error rates among low-fidelity RNA polymerases drive intrahost diversity, afeature important for viral fitness, evolution, and pathogenesis (57). There is evidencethat epidemic GII.4 variants have historically evolved through both antigenic drift andrecombination at the ORF1-ORF2 junction, resulting in acquisition of a new polymerase(21, 25). Recombination resulting in polymerase switching is also an important mech-anism for the evolution of GII.3 genotypes (15). It has long been hypothesized that theincreased transmissibility of pandemic GII.4 viruses is due at least partially to theirpolymerases having lower fidelity than those of nonpandemic variants (58). Indeed, theemergent GII.17 Kawasaki 308 viruses that recently temporarily replaced GII.4 Sydney2012 viruses in Asia had a polymerase with a higher error rate than the polymerases ofGII.4 viruses circulating since the 1970s (31). In further support for this hypothesis, avariant of murine norovirus encoding a high-fidelity polymerase was transmitted lessefficiently than the wild-type murine norovirus among mice, demonstrating that thepolymerase fidelity of noroviruses can impact their transmission (59). However, it is stilltoo early to conclude if the recently emerging viruses harboring similar GII.P16 poly-merases (GII.P16-GII.4 Sydney and GII.P16-GII.2) are due to changes in the polymeraseor other nonstructural proteins encoded by ORF1. Future studies are also needed todetermine what structural differences contemporary GII.P16 polymerases have gainedand what is the functional role of these changes.

In the current study, antigenic sites of VP1 were not drastically changed due topolymerase switching. The GII.Pe-GII.4 Sydney viruses had a high amino acid sequencesimilarity with those containing GII.P4 New Orleans and GII.P16 polymerases. EpitopesA and D are particularly important vaccine targets as antibodies directed to theseepitopes provide a physical barrier for HBGA blockade (30, 60), which is correlated witha reduced frequency of moderate to severe vomiting or diarrhea following GII.4norovirus infection (61). Epitope A amino acid sequences from the three GII.4 Sydneyviruses found in this study fluctuated only at positions 297 and 372; R297H and D372N

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were noted for some of the GII.4 viruses harboring GII.Pe and GII.P4 New Orleanspolymerases. Within epitope D, which includes amino acids directly involved in HBGAbinding, variability occurred only at position 393. Amino acid fluctuation among thesesites reflects those of the GII.4 New Orleans viruses (62). Not surprisingly, there wasmore sequence variability among GII.4 viruses harboring the GII.Pe and GII.P4 NewOrleans polymerases in this study which have been circulating much longer thanviruses with the GII.P16 polymerase. Taken together, the three GII.4 Sydney virusesidentified in our study appear to be antigenically similar, in contrast with findingsreported elsewhere (39). If these in silico findings are bona fide and if polymeraseswitching occurs without significant antigenic variation, vaccine development effortsmay become more complicated. It would indicate that factors other than populationherd immunity must be considered for a successful norovirus vaccine. Alternatively, therecombinant viruses we describe may be intermediary viruses affecting naive pocketsin the population, and acquisition of a new (lower-fidelity) polymerase is needed forcapsid evolution and emergence of the next antigenic GII.4 variant.

A limitation of this study is that dual-typing data were not available for alloutbreak specimens since polymerase typing is not yet routinely performed by allCaliciNet laboratories. We therefore requested specimens from 20% of outbreakscaused by genotypes (GII.2, GII.3, GII.4 Sydney, GII.13, and GII.17) known to harborGII.P16 polymerases. We were successful in obtaining dual-typing information for atleast 10% of these outbreaks occurring primarily in the last 2 years of the study, asfew laboratories retained specimens from the 2013-2014 season. The current studyhighlights the importance of dual typing for a more complete understanding of themolecular epidemiology of noroviruses, and hence P-C testing is currently beingimplemented as a standard protocol for all CaliciNet laboratories.

In this first description and analysis of CaliciNet data using the dual-typing assay,recombination among noroviruses was frequently detected. Acquisition of the GII.P16polymerase and/or associated nonstructural proteins appears to be the impetus for thepredominance of GII.P16-GII.4 Sydney viruses in 2015 to 2016. GII.2 and GII.4 Sydneyviruses with the GII.P16 polymerase also predominated in the 2016-2017 season in theUnited States (https://www.cdc.gov/norovirus/reporting/calicinet/data.html), indicatinga fitness advantage occurring with polymerase switching. Greater access to next-generation sequencing technologies and the recent development of cell culture prop-agation methods for human noroviruses (63, 64) will greatly enhance our abilities todetermine the importance of nonstructural protein changes on norovirus fitness.Continued molecular surveillance, including typing of both polymerase and capsidgenes, is important for monitoring emerging norovirus strains in our continued effortsto reduce the overall burden of norovirus disease.

MATERIALS AND METHODSCaliciNet. Epidemiologic and genotype information for confirmed norovirus outbreaks was submit-

ted to CaliciNet by participating state and local public health laboratories in the United States, asdescribed previously (8, 27). In CaliciNet, norovirus surveillance years are defined as starting on 1September and ending on 31 August. The median number of genotype-confirmed specimens from eachoutbreak was 2 (range, 1 to 18 specimens; interquartile range, 2 to 3 specimens).

Selection of specimens. We requested specimens and/or further laboratory testing to be performedat CaliciNet laboratories for outbreaks meeting certain inclusion criteria in order to capture the preva-lence of GII.P16 polymerases among noroviruses in the United States. Specifically, to gather dual-typing(polymerase and capsid) information for norovirus genotypes in the United States, we validated and useda new polymerase-capsid (P-C) assay which combines previously published assays targeting regions Band C (see below). Inclusion criteria for additional specimen testing were outbreaks caused by thefollowing: (i) GII.4 genotypes that differed by greater than 2% nucleotide difference in region C fromknown GII.4 strains, (ii) non-GII.4 genotypes known to be associated with GII.P16 polymerases, and (iii)mixed-genotype outbreaks. Among this selection, 20% of outbreaks occurring within each U.S. censusregion (West, Midwest, South, and Northeast), as well as within each season, early, middle, and late,corresponding with January to April, May to August, and September to December, respectively, weresought for P-C testing. The intent for requesting 20% of outbreaks was that at least 10% of outbreakswould have specimens available for analysis. For some outbreaks (primarily those caused by GII.2 andGII.4 Sydney viruses), full-length genome sequencing and complete sequencing of the VP1 or P2 regionsequencing were performed. Sequences from five additional GII.P16-GII.2 outbreaks from 1 September to

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31 December 2016 were also included in our phylogenetic and structural analysis of the GII.P16polymerase since only one GII.P16-GII.2 outbreak had been submitted to CaliciNet prior to 1 September2016. Complete VP1 and full-length norovirus genome sequencing was performed using Sanger andnext-generation sequencing (NGS) approaches, respectively.

Norovirus RT-PCR assays. Real-time reverse transcription-PCR (RT-PCR) targeting the ORF1/ORF2overlap region was performed initially on all outbreak specimens by CaliciNet laboratories. The currentstandard CaliciNet detection protocol is a multiplex real-time assay (65, 66) (see Table S1 in thesupplemental material) using an Ag-Path kit (Applied Biosystems, Carlsbad, CA, USA) without detectionenhancer, 400 nM each oligonucleotide primer (Cog1F and Cog1R for GI viruses; Cog2F and Cog2R forGII viruses) (27), and 200 nM each probe (Ring 1E, FAM-TGG ACA GGR GAY CGC-MGBNFQ, where FAMis 6-carboxyfluorescein and MGBNFQ is minor groove binder and nonfluorescent quencher [64, 65]; Ring2 [27]) as well as 100 nM each primer and probe (MS2.F/R and MS2.P) for an MS2 bacteriophage internalamplification and extraction control (MS2; ATCC 15597-B1) (67). Cycling conditions were performed asfollows: reverse transcription for 10 min at 45°C, followed by denaturation for 10 min at 95°C, and then40 cycles of 95°C for 15 s and 60°C for 1 min each. Cycle threshold (CT) cutoff values of 35 and 37 wereused as the limits of detection for GI and GII real-time results, respectively. Positive samples wereprimarily genotyped using a modified region C protocol which included (1 �M each) G1SKF/R oligonu-cleotide primers for GI and oligonucleotide primers Ring 2 (TGG GAG GGC GAT CGC AAT CT) and G2SKRfor GII using cycling parameters as described previously (27), with the exceptions that the denaturation(95°C) and primer annealing (50°C) phases were 1 min each and the final extension at 72°C was for 10min. Region C-negative samples were genotyped using a region D protocol as described previously (27).A novel RT-PCR (P-C typing assay) was performed by using a combination of previously publishedoligonucleotide primers: primers MON432 (TGG ACI CGY GGI CCY AAY CA) and G1SKR (CCA ACC CAR CCATTR TAC A) for GI viruses; primers MON431 (TGG ACI AGR GGI CCY AAY CA) and G2SKR (CCR CCN GCATRH CCR TTR TAC AT) for GII viruses (12, 28). For GI viruses, the expected PCR product size is �543 bp,and for GII viruses it is �557 bp. Viral nucleic acid was extracted from 10% clarified fecal suspensionsprepared in phosphate-buffered saline using a MagMax-96 Viral RNA Isolation kit (Ambion, Foster City,CA, USA), according to the manufacturer’s instructions, on an automated KingFisher extractor (ThermoFisher Scientific, Pittsburgh, PA, USA). Qiagen One-Step RT-PCR (Qiagen) master mix was used with 20 Uof RNase inhibitor (Applied Biosystems) with the following cycling conditions: 30 min at 42°C, 15 min at95°C, and 40 cycles of 95°C, 50°C, and 72°C for 1 min each, followed by 10 min at 72°C. GII.4 specimenswere also tested in the P2 region using primers EVP2F and EVP2R (674-bp product size) as describedpreviously (8). Complete VP1 genes of GII.4 viruses were amplified by overlapping RT-PCR assays usinga Qiagen One-Step RT-PCR kit and oligonucleotide primer set Ring2 (TGG GAG GGC GAT CGC AAT CT)and RingP2R-1 (GGG AAY CTT GAR TTG GTC AT) and primer set EVF9-1 (AAT GAA CCY CAA CAA TG) andPanGIIR1 (GTC CAG GAG TCC AAA A). Cycling conditions included reverse transcription for 30 min at42°C, denaturation for 15 min at 95°C, and 40 cycles of 94°C (30 s), 50°C (30 s), and 68°C (2 min), followedby a final extension for 10 min at 68°C.

PCR products were visualized on a 2% agarose gel (Seakem-ME, Lonza, Allendale, NJ, USA) containingGel Red (Biotium, Fremont, CA, USA) and gel purified by an ExoSAP-IT (Affymetrix, USB, Cleveland, OH,USA) or QIAquick PCR purification kit (Qiagen) and Sanger sequencing (Eurofins MWG Operon, Louisville,KY, USA).

Next-generation sequencing to obtain full-length norovirus genomes. Viral RNA extraction wasperformed using a QIAmp Viral RNA minikit extraction kit (Qiagen) with nuclease and DNase treatmentas described previously (68). After random PCR amplification, cDNA libraries were generated using anIllumina Nextera XT DNA Library Prep kit, and sequencing was performed on an Illumina MiSeq platform(69, 70). Raw reads were preprocessed by adaptor and primer removal, host sequence subtraction,sequence deduplication, and quality filtering with a Phred score cutoff of 30 before de novo assemblywas performed using SPAdes, version 3.7 (71), with multiple k-mer lengths. A recruitment mappingapproach utilizing the internal algorithm in the Geneious, version 9.1.6, software package (Biomatters Inc.Newark, NJ) resolved the final consensus sequence for each specimen.

Data analysis. CaliciNet genotyping and epidemiological data (outbreak date and location [state orcruise ship]) were downloaded and imported into MS Excel (2016) for basic data manipulation andgraphing, and graphing was performed with Origin 2017 software. Statistical analysis was performed inJMP, version 13.0.0 (SAS). Pearson’s chi-square test was also used to determine monthly quarters (Januaryto March, April to June, July to September, October to December) for which the proportion of outbreaksthat occurred each year differed from the hypothetical proportion of 25%. Genotypes were assigned byphylogenetic analysis using the unweighted-pair group method using average linkages (UPGMA) withreference sequences used by CaliciNet (27) for capsid typing and reference strains used by the NorovirusTyping Tool, version 2.0, for polymerase typing (10, 72). Multiple alignments using MUSCLE andphylogenetic analysis by the neighbor-joining method were performed using MEGA, version 7(73–75). The MEGA maximum likelihood model selection tool was used to determine the best modelfor branch support using the Bayesian information criterion for analysis, which was determined tobe the Kimura two-parameter method with rate variation among sites modeled with a gammadistribution (K2�G) (76). Amino acid substitutions occurring within the complete polymerase regionwere visualized by overlay on the three-dimensional crystal structure of Norwalk virus polymerase(Protein Data Bank accession number 1SH0) (77) using DeepView/Swiss-PdbViewer, version 4.1.0 (SwissInstitute of Bioinformatics).

Accession number(s). Sequences derived in this study were deposited in the GenBank underaccession numbers KY865306, KY865307, and KY947546 to KY947550.

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SUPPLEMENTAL MATERIAL

Supplemental material for this article may be found at https://doi.org/10.1128/JCM.00455-17.

SUPPLEMENTAL FILE 1, XLSX file, 0.1 MB.

ACKNOWLEDGMENTSWe thank Annie Phillips and Hannah Browne for excellent assistance with dual-

typing of norovirus specimens. We gratefully acknowledge the CaliciNet members whocontributed to the data presented in the manuscript: Courtney Chesnutt and NicholasSwitzer (Alabama Department of Public Health, Bureau of Clinical Laboratories); ChengYang (Arkansas Department of Health, Public Health Laboratory); Chao-Yang Pan, TashaPadilla, and Thalia Huynh (California Department of Public Health); Julia Wolfe, KathrynSiemers, and Rina Tjiptahadi (Orange County Public Health Laboratory, CA); TaylorMundt, Eduardo Ramos, and Peijia Chen (Los Angeles County, Public Health Laboratory,CA); Justin Nucci and Mary-Kate Cichon (Colorado Department of Public Health andEnvironment); Horng-Yuan Kan (Washington, DC, Public Health Laboratory); GregoryHovan (Delaware Public Health Laboratories); Jacquelina Woods (U.S. FDA); Lea A.Heberlein-Larson and Marshall Cone (Florida Department of Health, Bureau of PublicHealth Laboratories, Tampa, FL); Precilia Calimlim, Cheryl-Lynn Daquip, and KrisRimando (Hawaii Department of Health); Kari Getz, Lindsey Catlin, and Amanda Bruesch(Idaho Bureau of Laboratories); Cassandra Campion and Melissa Hindenlang (IndianaState Department of Health Laboratories); Beth Anna Leigh Young (Kentucky StateHealth Laboratory); Erika Buzby, Pinal Patel, and Brandon Sabina (Massachusetts De-partment of Public Health); Jonathan Johnston, Julie Haendiges, and Eric Keller (Mary-land Department of Health and Mental Hygiene, Laboratories Administration); LauraMosher, Victoria Vavricka, and Kevin Rodeman (Michigan Department of CommunityHealth, Bureau of Laboratories); Elizabeth Cebelinski, Ginette Dobbins, and Mary Eliz-abeth Horn (Minnesota Department of Health, Infectious Disease Laboratory); ShadiaRath, Katja Manninen, and Robbie Li Ann Hall (North Carolina State Laboratory Of PublicHealth); Xinglu Zhang, Fengxiang Gao, and Xinglu Zhang (New Hampshire PublicHealth Laboratories, Department of Health and Human Services); Kendra Pesko andCharles Yaple (New Mexico Department of Health, Scientific Laboratory Division);Patrick Bryant and Daryl M. Lamson (New York State Department of Health, WadsworthCenter); Rebekah Carman, Rosemary Hage, Lai Ming Woo, Eric Brandt, and Jade Mowery(Ohio Department of Health Laboratory); James M. Terry, Laura Flint, Vanda Makris, andLaura J. Tsaknaridis (Oregon State Public Health Laboratory); Andrea Maloney andAndrea Licata (South Carolina Department of Health and Environmental Control); LindaS. Thomas, Christina Moore, and Amy M. Woron (Tennessee Department of Health,Laboratory Services); Chun Wang and Jenny Zhang (Texas Department of State HealthServices); Leigh-Emma Lion, Patricia Croscutt, and Mary Kathryne Dickinson (VirginiaDivision of Consolidated Laboratory Services); Valarie Devlin and Jessica Chenette(Vermont Department of Health Laboratory); Tim Davis, T. J. Whyte, Richard Griesser,and Tonya Danz (Wisconsin State Laboratory of Hygiene); Jose Navidad (City of Mil-waukee Health Department, WI); and Rob Christensen (Wyoming Public Health Labo-ratory).

This study was partially supported by a grant from the National Institute of Food andAgriculture, U.S. Department of Agriculture (2011-68003-30395), by the intramural foodsafety program and the Advanced Molecular Detection program at the Centers forDisease Control and Prevention (CDC). This research was also supported in part byfellowships from the Oak Ridge Institute for Science and Education through an inter-agency agreement between the U.S. Department of Energy and the CDC.

The findings and conclusions in this article are those of the authors and do notnecessarily represent the official position of the Centers for Disease Control andPrevention.

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Emergence of Norovirus GII.4 Recombinant Viruses Journal of Clinical Microbiology

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Correction for Cannon et al., “Genetic and EpidemiologicTrends of Norovirus Outbreaks in the United States from 2013to 2016 Demonstrated Emergence of Novel GII.4 RecombinantViruses”

Jennifer L. Cannon,a Leslie Barclay,b Nikail R. Collins,c Mary E. Wikswo,b Christina J. Castro,d Laura Cristal Magaña,d

Nicole Gregoricus,b Rachel L. Marine,b Preeti Chhabra,e Jan Vinjéb

CDC Foundation, Atlanta, Georgia, USAa; Division of Viral Diseases, Centers for Disease Control and Prevention,Atlanta, Georgia, USAb; Atlanta Research and Education Foundation, Decatur, Georgia, USAc; Oak RidgeInstitute for Science and Education, Oak Ridge, Tennessee, USAd; Synergy America, Inc., Atlanta, Georgia, USAe

Volume 55, no. 7, p. 2208 –2221, 2017, https://doi.org/10.1128/JCM.00455-17. Page2217, lines 25–26: “For GI viruses, the expected PCR product size is �543 bp, and for GIIviruses it is �557 bp” should read “For GI viruses, the expected PCR product size is 579bp, and for GII viruses it is 570 bp.”

Citation Cannon JL, Barclay L, Collins NR,Wikswo ME, Castro CJ, Magaña LC, GregoricusN, Marine RL, Chhabra P, Vinjé J. 2019.Correction for Cannon et al., “Genetic andepidemiologic trends of norovirus outbreaks inthe United States from 2013 to 2016demonstrated emergence of novel GII.4recombinant viruses.” J Clin Microbiol57:e00695-19. https://doi.org/10.1128/JCM.00695-19.

Copyright © 2019 American Society forMicrobiology. All Rights Reserved.

Address correspondence to Jan Vinjé,jvinje@cdc.gov.

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