Epidemiology and evolution of Norovirus in China

ABSTRACT

Norovirus (NoV) has been recognized as a leading cause of gastroenteritis worldwide. This review estimates the prevalence and genotype distribution of NoV in China to provide a sound reference for vaccine development. Studies were searched up to October 2020 from CNKI database and inclusion criteria were study duration of at least one calendar year and population size of >100. The mean overall NoV prevalence in individuals with sporadic diarrhea/gastroenteritis was 16.68% (20796/124649, 95% CI 16.63–16.72), and the detection rate of NoV was the highest among children. Non-GII.4 strains have replaced GII.4 as the predominant caused multiple outbreaks since 2014. Especially the recombinant GII.P16-GII.2 increased sharply, and virologic data show that the polymerase GII.P16 rather than VP1 triggers pandemic. Due to genetic diversity and rapid evolution, predominant genotypes might change unexpectedly, which has become major obstacle for the development of effective NoV vaccines.

KEYWORDS:

• Norovirus
• epidemiology
• China
• genotype diversity
• evolution
• vaccine

Introduction

The burden of NoV worldwide

With the gradual promotion of rotavirus vaccines, NoV has now become the key pathogen associated with gastroenteritis/diarrhea.^1,2 It was estimated that more than 600 million people worldwide suffer from acute gastroenteritis (AGE) due to NoV infection, resulting in approximately 210,000 deaths annually.³ Analysis of the burden of diarrhea across 195 countries by the 2016 Global Burden of Diseases, Injuries, and Risk Factors Study (GBD)⁴ attributed an estimated 19496 deaths to NoV (95% CI: 8747–38421). Among these cases, a significant number were younger than 5 years (10,629; 5274–19582) or older than 70 years (3693; 810–8647). Bartsch in 2016 concluded that NoV caused direct health system costs 4.2 billion U.S. dollars and the socioeconomic burden amounted to more than 60 billion U.S. dollars per year globally, 39.8 billion U.S. dollars of which could be attributed to the disease in children under 5 years old.⁵

NoV etiology

NoV is a non-enveloped icosahedral symmetrical structure with a diameter of 25–40 nm. NoV genome is 7.5–7.7 kb single-stranded, positive-stranded RNA, with 3 open reading regions (ORF-1, ORF-2 and ORF-3). ORF1 encodes the nonstructural proteins, including NTPase, 3 C-like protease, and RNA-dependent RNA polymerase (RdRp). ORF2 encodes the capsid protein VP1 and ORF3 encodes the minor structural protein VP2. VP2 is located inside the viral particle and is thought to participate in capsid aggregation. According to the position of the protein in the capsid, VP1 is divided into a shell domain (S region) and a protruding domain (P region). The P domain contains the main antigenic site and is further divided into the P1 and P2 domains. The P2 region forms a binding pocket composed of an RGD-like motif located at the bottom and around certain specific Amino acid (AA); this then becomes the binding site between the virus particles and human histo-blood group antigens (HBGAs).⁶ Importantly, this is considered to be a key aspect of immune recognition and receptor binding. In addition, the eukaryotic cell can express VP1 and self-assemble to form virus-like particles (VLPs), whose morphology and antigenicity are similar to those of natural viral particles. Thus, VLPs can be used as candidate vaccines against NoV. Due to the frequent recombination of ORF1 and ORF2 sequences, NoV strains usually use the double genotype encoding RdRp and VP1 sequence.⁷ According to the nucleotide sequence of VP1, NoV can be divided into 7 genogroups (GI-GVII) and more than 30 genotypes. GI, GII, and GIV.1 NoV are closely related to human disease, and GII genogroup includes 22 genotypes and GI genogroup includes 9 genotypes.⁸

The diversity of NoV genotypes and the global pandemics caused by its novel strains have shown an evolutionary pattern similar to that of influenza viruses. The Centers for Disease Control and Prevention (CDC) in United States launched CaliciNet as early as 2009 to analyze the epidemiologic of NoV and concluded that NoV has become the leading pathogen of foodborne disease. The NoV Outbreak Network in China (CaliciNet China) was not established until 2016 and involving only 6 provinces up to 2018. The selection of antigen components based on epidemiological investigation is expected to crucially provide the direction for NoV vaccine research. However, the absence of NoV epidemic data, coupled with the characteristic genetic diversity and rapid evolution of NoV has currently restricted vaccine development. This review analyzed the molecular epidemiology of NoV in China over the past 20 years in order to provide a sound reference for vaccine development.

Methods

Methods for Epidemiology of NoV in China

Search Strategy: The China National Knowledge Infrastructure (CNKI) database was searched up to 31 October 2020 with the following search terms “norovirus,” “calicivirus” or “norwalk virus” in combination with gastroenteritis or diarrhea.

Inclusion Criteria: Chinese mainland-based investigations into sporadic gastroenteritis/diarrheal diseases, which included spatial distribution and age information. Inclusion criteria for the review were study duration of at least one calendar year, population size of >100 and diagnosis by RT-PCR or ELISA. Publications in both English and Chinese were considered.

Data Extraction: The following information was extracted from each included study: study district; study duration; age group; number of cases screened; number of cases positive for the NoV; Peak NoV detection; genotype information; number of NoV GI, GII, and GIV detections.

Statistical Analysis: The web based open source statistical calculator OpenEpi version 3 (https://www.openepi.com) was used to calculate the 95% confidence intervals for proportions.⁹

1. NoV GII.2 VP1 sequence and phylogenetic tree construction.

To define why recombinant GII.P16-GII.2 caused pandemic outbreaks, the sequences from GenBank were downloaded and MEGA5.05 software employed to analyze the evolution of the VP1 region.

Results

Epidemiology of NoV in China

NoV prevalence and age distribution

NoV infection is very common, both in gastroenteritis patients and healthy individuals.^10,11 The prevalence of NoV infection in symptomatic and asymptomatic individuals of 20% and 7% globally.² The NoV prevalence in asymptomatic patients was 9.7% in Africa.¹² Surprisingly, NoV was up to 29.8% detected in Mexican Children, with 49.2% having at least one positive stool from June to August 1998.¹³ Asymptomatic individuals might be act as reservoirs, facilitating the transmission of the NoV. Considering whether NoV was shed from a recent symptomatic NoV gastroenteritis or whether the subjects were experiencing primary asymptomatic infections is difficult to determine, it’s plausible that the results of studies on asymptomatic infections are controversial. Given that relatively few past studies focused on NoV infections without symptomatic disease in China, asymptomatic infections were excluded in our research.

The mean overall NoV prevalence in individuals with sporadic diarrhea/gastroenteritis from 52 studies originating from 28 provinces (Table 1) was 16.68% (20796/124649, 95% CI 16.63–16.72).^14–65 Data were stratified by age into three categories: children, hospitalized young children ≤5 years and mixed (studies that did not report age stratified). Prevalence was significant difference in patients with diarrhea/gastroenteritis children 24.00% (5889/24537, 95% CI 23.92–24.08), hospitalized young children ≤5 years 17.39% (3801/21852, 95% CI 17.32–17.47) and mixed 13.26% (8776/66177, 95% CI 13.21–13.31). Of note, A 6-year study showed that NoV detection among adult patients with infectious diarrhea reached 19.28% (2330/12083, 95% CI 19.23–19.33), this data far exceeds the mixed population.⁶⁵ Considering the samples were only taken from Shanghai might introduce bias assessment, the spatial distribution of NoV infection were summarized (Figure 1). In general, the spatial distribution of infection favors southern coastal regions, such as Yellow Sea (Jiangsu), East China Sea (Shanghai and Fujian), North China Sea (Guangxi), which were severely hit by NoV infection. Interestingly, inland areas concentrated in Southwest China, notably Chongqing and Sichuan, were extremely eye-catching. Studies in Guizhou excluded from our research revealed NoV infection also especially serious.^66,67 Taiwan^68,69 and Hong Kong^7,70,71 were reported to experience severe NoV burdens, but data related to detection rates in sporadic diarrhea was absent. In July 2017, the CDC in Jiangxi announced that NoV was found in food-borne diarrhea cases in Ji’an, which is the second discovery of NoV in Ji’an and the first reported in food-borne sporadic diarrhea cases. Possibly due to poor surveillance, no NoV infection cases have been reported in areas such as Macau and Tibet. Several limitations of our study need to be addressed. NoV infection emerges obvious geographical distribution, causing the data 19.28% drawn from Shanghai adult patients could thus for be higher than the national infection rates. Judging from the number of studies, coastal cities were included more than inland, which might introduce prevalence bias across all age groups. The prevalence was higher in children and young children ≤5 years were more likely to be hospitalized, which correlates with studies from Taiwan and Hong Kong.^68,70 Moreover, NoV seasonality is obvious in China, where great majority NoV disease peaks from October to March of the following year.

Table 1. The detection of NoV in sporadic AGE/diarrhea cases. The detection of NoV in sporadic gastroenteritis/diarrhea cases

District	Year	Duration of the studies	Number of Cases Tested	Number of Norovirus+	Peak NoV detection	Norovirus detection
NoV Infections: Children
Guangdong-Zhuhai^Citation14	2011–2013	3 years	1150	381	Oct-Feb	33.13%
Beijing^Citation15	2019.01–2019.12	1 year	2135	651	Oct – Dec	30.49%
Tianjin^Citation16	2017.01–2017.12	1 year	758	241	Winter	31.80%
Chongqing^Citation17	2008.08–2009.07	1 year	806	251	Oct	31.14%
Jiangsu-Suzhou^Citation18	2010.01–2013.12	3 years	1682	454	-	27.00%
Jiangsu^Citation19	2011.01–2012.12	2 years	850	225	-	26.47%
Shanghai^Citation20	2009.01–2011.12	3 years	2288	531	-	23.20%
Fujian-Xiamen^Citation21	2010.05–2011.04	1 year	366	81	July and Nov	22.13%
Ningxia-Yinchuan^Citation22	2012.04–2013.04	1 year	286	62	-	21.68%
Guangdong-Guangzhou^Citation23	2007–2008	2 years	954	179	-	18.80%
Tianjin^Citation24	2007.12–2009.12	2 years	289	52	-	17.99%
Guangdong-Jiangmen^Citation25	2006	1 year	362	52	Sep-Nov	14.36%
Shanghai^Citation26	2012.01–2017.12	6 years	1433	221	Autumn- winter	15.40%
Zhejiang-Hangzhou^Citation27	2010.06–2011.09	15 months	325	45	-	13.85%
Hunan^Citation28	2012.01–2014.12	3 years	936	100	-	10. 68%
Qinghai-Xining^Citation29	2015–2016	2 years	400	38	July-Sep	9. 50%
5 cities nationwide^Citation30	2008.07–2009.09	15 months	5091	1512	Oct-Feb	29.70%
13 districts nationwide^Citation31	1999–2005	6 years	4426	813	Oct-Jan	18.37%
Norovirus Detection (95% CI): 24.00% (5889/24537,CI 23.92–24.08)
NoV Infection: Hospitalized young children ≤ 5 years
Shaanxi-Xian^Citation32	2009.03–2011.03	2 years	124	34	-	27.40%
Gansu-Lanzhou^Citation33	2015.01–2018.12	4 years	785	112	Jan/May/Oct	14.27%
Jilin^Citation34	2012.01–2013.12	2 years	770	139	Mar and Apr	18.10%
Jilin^Citation35	2011.01–2011.12	1 year	375	51	Jan-mar	13.60%
19 districts nationwide^Citation36	2011.01–2014.12	4 years	19798	3465	Sep and Feb-Mar	17.50%
Norovirus Detection (95% CI): 17.39% (3801/21852,CI 17.32–17.47)
NoV Infections: no age stratification
Guangxi-Nanning^Citation37	2007.01–2008.12	2 years	696	183	Oct- Mar	26.30%
Zhejiang-Huzhou^Citation38	2015.01–2017.12	3 years	1757	416	Mar and Nov- Dec	23.70%
Shanghai^Citation39	2014–2016	3 years	5927	1363	Autumn and spring	23%
Hubei^Citation40	2015.01–2015.12	1 year	687	149	Sep	21.69%
Qinghai^Citation41	2016–2017	2 years	238	47	Oct	19.74%
Guangxi-Nanning^Citation42	2015.05–2019.03	4 years	1199	238	Mar and Nov	19.85%
Guangdong-Guangzhou^Citation43	2011.01–2011.12	1 year	218	38	Oct-Nov	17.43%
Xinjiang- Urumqi^Citation44	2012–2014	3 years	895	150	-	16.80%
Shaanxi-Hanzhong^Citation45	2016–2019	4 years	822	139	Nov-Jan	16.91%
Ningxia^Citation46	2016–2018	3 years	3458	528	Nov- Mar	15.27%
Anhui -Ma’anshan^Citation47	2015.01–2018.06	3.5 years	911	134	Nov- Apr	14.70%
Guangdong-Shenzhen^Citation48	2015–2017	3 years	362	53	-	14.64%
Zhejiang-Haiyan^Citation49	2013.01–2013.12	1 year	170	24	Jan-Mar	14.12%
Hainan^Citation50	2015.01–2017.12	3 years	857	121	Oct-Nov	14.12%
Zhejiang-Huzhou^Citation51	2017.04–2018.06	> 1 year	1259	171	-	13.58%
Liaoning-Shenyang^Citation52	2015–2017	3 years	1505	161	-	10.70%
Hainan-Haikou^Citation53	2014–2015	2 years	592	63	Oct-Nov	10.64%
Zhejiang^Citation54	2016.01–2016.12	1 year	1308	138	Dec	10.55%
Tianjin^Citation24	2007.12–2009.12	2 years	951	95	-	9.94%
Beijing^Citation55	2009.04–2011.11	32 Months	685	66	-	9.60%
Liaoning-Dalian^Citation56	2013.01–2013.12	1 year	300	27	Winter	9.00%
Shanxi-Taiyuan^Citation57	2015–2017	3 years	1 031	91	Feb-June	8.83％
Zhejiang-Zhoushan^Citation58	2013.01–2018.08	>5.5 years	1849	134	Dec- Apr	7.25%
Heilongjiang^Citation59	2017.01–2019.12	3 years	560	40	Feb	7.14%
Tianjin^Citation60	2019.01–2019.12	1 year	1615	97	-	6.01%
Jiangsu-Zhenjiang^Citation61	2015.01–2016.12	2 years	1605	85	Nov- Mar	5.30%
Hebei^Citation62	2015.09–2016.12	21 Months	1240	58	-	4.68%
Heilongjiang^Citation63	2012.01–2015.12	4 years	480	17	-	3.55%
nationwide^Citation64	2009–2013	> 3 years	34 031	3950	Winter	11.60%
Norovirus Detection% (95% CI): 13.26% (8776/66177, CI 13.21–13.31)
NoV Infections: Adults
Shanghai^Citation65	2013–2018	6 years	12083	2330	Oct – Apr	19.28%
Norovirus Detection% (95% CI): 19.28%(2330/12083, CI 19.23–19.33)^Citation65

Figure 1. Heat map of unique datasets from each province. The study references are as follow:Chongqing,¹⁷ Shaanxi,^32,45 Sichuan,³⁶ Fujian,^21,36 Shanghai-,^{20,26,36,39,65} Jiangsu,^18,19,36,61 Guangxi,^36,37,42 Qinghai,^29,41 InnerMongolia,³⁶ Beijing,^15,36,55 Guangdong,^{14,23,25,36,43,48} Hubei,⁴⁰ Shandong,³⁶ Gansu,^33,36 Tianjin,^16,24,60 Anhui,^36,47 Jilin,^34–36 Ningxia,^22,46 Xinjiang,^36,44 Zhejiang,^{27,38,49,51,54,58} Shanxi,^36,57 Hebei,^36,62 Yunnan,³⁶ Heilongjiang,^36,59,63 Hainan,^50,53 Hunan,^28,36 Liaoning,^52,56 Henan.³⁶

NoV genotype diversity

A total of 13 studies reporting the predominant infection-causing NoV genotypes in different time periods and locations^{20,31,36,40,60,72–79} were analyzed to derive an epidemiologic summary of NoV strains in China (Figure 2). Before 2014, more than half of NoV infections were caused by GII.4, and it was still the dominant strains in some regions until 2015, while decreased significantly after 2016. In fact, since the fall of 2014, non-GII.4 strains replaced GII.4 as the predominant cause in outbreaks of NoV gastroenteritis. In the winter of 2014–2015, GII.17 was involved in multiple epidemics.^80–83 Following this, NoV GII.2 became the circulation strain in many regions of China since 2016. Comprehensive epidemiological data confirms that GII.6 has shown sustained and widespread transmission in the last 20 years, although it did not yet cause large-scale outbreaks like GII.4, GII.17 and GII.2.

Figure 2. The predominant genotype of NoV in 1999–2019.^{20,31,36,40,60,72–79}

In order to accurately summarize the diversity of NoV genotypes, capsid-based genotypes detected from 28 studies were analyzed to determine the prevalent and widely distributed NoV genotypes in two time periods (Figure 3).^{14,17,19–21,23,25,31,32,34,35,40,46,55,58,59,61,62,77,79,84–91} It was verified that GII.4 was the most frequently detected, accounting for nearly 70%, subsequently preceded by NoV GII.3, GII.6 and GII.12 prior to 2014. However, GII.2 replaced GII.4 as the most predominant (accounting for more than 50%), and GII.17 was the next most widely distributed genotypes (accounting for 15.38%) from 2014 to 2019. Moreover, GI genogroup has shown an obvious upward trend after 2014, accounting for nearly 5%, of which GI.2, GI.3, especially GI.6 have demonstrated an absolute advantage. It is worth noting that GI.1 was not detected in the studies included between 2014 and 2019. Ongoing surveillance should be needed to determine the evolution of the epidemic strains across regions and time in China.

Figure 3. (a) The Proportion of NoV Genotypes from 1999 to 2014 (1250 cases from 15 studies);^{14,17,19–21,23,25,31,32,34,35,55,84–86} (b)The Proportion of NoV Genotypes from 2014 to 2019 (1697 cases from 13 studies).^{40,46,58,59,61,62,77,79,87–91}

The National Public Health Emergency Management Information System (PHEMIS) reported 56 NoV outbreaks nationwide from 2006 to 2013.⁹² However, 915 NoV outbreaks involved in 26 provinces from 2014 to 2018 were reported by PHEMIS, and CaliciNet China reported 556 NoV outbreaks from October 2016 to September 2018 in 6 provinces.^77,93 NoV outbreaks increase when new strains circulate in the community, and the surge of NoV outbreaks after 2016 was mainly attributed to the recombinant strain GII.P16-GII.2. A logical follow-up question concerns why GII.P16-GII.2 caused such large-scale outbreaks?

Molecular evolution of reemerging NoV GII.P16-GII.2

Using NCBI database, we downloaded 304 GII.2 VP1 capsid sequences worldwide from 1971 to 2019. Overall, The VP1 sequences were 96.57% AA identical to each other and most of the sequences were from Japan and China. The key AAs Asn352/Arg353/Asp382 of NoV GII.2 HBGA binding sites in the P2 subdomain are highly conserved (Figure 4), this result correlates with the statement reported by National institute for viral disease control and prevention, China CDC.⁹⁴ Of note, GII.2 experienced limited evolutions after 2016 and mutations only appeared in a few sequences.

Figure 4. Summary of mutations in the P2 subdomain of GII.2 strains from 1970–2019 (Strains without mutations were not involved). Red letters denote concentrated mutations that have appeared in multiple sequences. GenBank accession numbers: ASO96884, AGI17590, AFN06726, AFX71659, AGT62523.

BBB86933(30/27/24/23/81/72/15/18/54/87/84/48/51/45/12/69/42/36/90/96), BAL60747(49/51/53/55/57/59/63/65/67/69/71/75/77/79/81/83/85/87/89/91/93/95/), BBB87002, BAL608(11/13/15/17/19), BBB87041(14/26/29/53), BAL60797(99), BAL608(01/03/05/07/21/23/25/27/29/31/33/35/37/43/45/47/49/51), , BAV19392(86), BAV19407(19/31/34/37/40/43/46/52), ATI15400(01/02/03), AQT19693(94), AQT19704, ATL75628, ARQ84912(14), ARQ84856(78), BBC20612, BBC28106(20/30/40), BBC20967, AYV96328(29), AXF50011, QBC36483.

Further, we screened out 62 sequences from 304 to construct evolutionary tree by minimum evolution method to analyze the full-length sequence evolution of GII.2 VP1 region (Figure 5). The VP1 gene phylogenetic tree could be grouped into two major clusters: the GII.2 strains from 1970s (Group I) and 2004–2019 (Group II). Sequence analysis revealed significant time and geographical characteristics, e.g. sequences from 2008 to 2014 in the GroupII.1 formed a phylogenetic cluster concentrated in Japan, while the sequences (GroupII.2) from 2016 to 2019 were concentrated in China. Collectively this reveals that mutations in GII.2 VP1 sequence stably accumulate in human populations. Of note, one strain isolated from 2008 (Accession Number: BBB87008) recognized as GII.P2-GII.2 was closely related to the lineage of the GII.P16–GII.2 strain after 2016 in GroupII.2. Further research by Ao.et al revealed that the GII.P2–GII.2 strain emerged in 2016 harbors a capsid sequence identical to the GII.P16–GII.2 reemerged in 2016–2017 in Fengtai.⁹⁵ Phylogenetic and sequence analyses indicated that GII.P16-GII.2 had no remarkable change on capsid protein compared with GII.P2–GII.2, implying that factors other than capsid proteins contribute to the GII.P16–GII.2 virus epidemic.⁹⁶

Figure 5. Phylogenetic analysis of GII.2 full length VP1 sequences. Minimum evolution method phylogenetic inference of VP1 aa sequences was performed. Statistical evaluation was performed by 1,000 bootstrap replications and percentages of clustering (>50%) are shown at nodes. Scale bars indicate the number of substitutions per site. Country/region abbreviations: CN, China (circles); JP, Japan (squares); US, United States (triangles); MY, Malaysia (diamonds); BJ, Beijing; TW, Taiwan; HK, Hong Kong; TZ, Taizhou; ZS, Zhoushan.

It was reported that GII.P2-GII.2 was only sporadically detected in Japan before 2009. However, NoV GII.2 associated outbreaks were observed in Japan during 2009–2010 and the frequency of GII.2 in individual cases and outbreaks was close to that of GII.4. Genetic analyses revealed the GII.2 epidemic resulted from GII.P2-GII.2 and GII.P16-GII.2. It is worth noting that this likely represents the first epidemic of GII.P16-GII.2 worldwide.⁹⁷ GII.P16-GII.4 increased in Australia and New Zealand in 2017, and it has been verified the polymerase of GII.P16-GII.4 was derived from the GII.P16-GII.2 virus which was dominant at the end of 2016.⁹⁸ The polymerase of GII.P16 is more adaptable than others, and it has been hypothesized that outbreaks caused by GII.P16-GII.2 and GII.P16-GII.4 are mainly due to the polymerase GII.P16 and slight change of capsid genotypes may also have contributed to immune escape and conferred higher virological fitness.

Typically, various genotypes of NoV circulated in human populations during the same period, providing opportunities for recombination between different strains. We assumed that multiple viruses are transcribed simultaneously in a single cell of an infected host and template switching occurs during the transcription process, and after optimized selection, the recombinant strain is finally formed. Most scholars endorse the sub-genomic RNA NoV gene recombination theory: the promoter site located in the overlapping region of RdRp/Capsid, and the sequence between the 5ʹ end of the NoV genome and the ORF1/ORF2 overlapping region is highly consistent.^99–102 According to the above theory, underlying theoretical recombination mechanism of GII.P16-GII.2 is demonstrated in Figure 6.^103,104

Figure 6. The hypothesis of recombination GII.P16-GII.2: GII.P16-GII.X positive-sense RNA as a template to synthesize negative-sense RNA. This negative-sense RNA and its internal subgenomic RNA are used as templates to synthesize positive-sense genomic RNA and subgenomic RNA respectively. These two positive-sense RNAs serve as template to synthetic negative-sense genomic RNA and subgenomic RNA. Recombination occurs during the process of synthesizing GII.P16-GII.X positive-sense RNA and subgenomic RNA. The RdRp region of the positive-sense RNA initiates synthesis at the promoter (blue triangle) located at the 3′end of negative-sense RNA. However, the process stalls at the ORF1/ORF2 overlap region subgenomic promoter (red triangle) and then switches template to GII.PX-GII.2 negative-sense subgenomic RNA to continue transcription and finally the recombinant strain GII.P16-GII.2 formed.

Progress toward NoV vaccines

Simulation studies have shown that 100–6125 NoV AGE cases could been prevented per 10 thousand individuals vaccinated.¹⁰⁵ Unfortunately, NoV vaccination has not yet been given permission globally. Live attenuated and inactivated NoV particle vaccines cannot been created due to the prior lack of an in vitro culture system for human NoV. Candidate vaccines in the research pipeline predominately target P particle (PP) and virus-like particle (VLP).

The PP protein occurs as several oligomers, including 2-mer, 12-mer and 24-mer. The subunit vaccines based on PP have been presented the characteristics of high immunogenicity, easily expressed and low cost. The surface of PP protein has three ring structures which are suitable for inserting and displaying foreign epitopes on the surface of the particle. Using this approach, NoV PP have been used to develop vaccines with enhanced antigen immunogenicity using epitopes from rotavirus, HIV, influenza, and EV71. For example, Tan et al.¹⁰⁶ chimerized PP with rotavirus VP8 antigen, which not only blocked the binding of NoV VLPs to HBGAs receptors but also produced higher levels of neutralizing antibodies against Rv infection compared with free VP8 antigen. Furthermore, the trivalent subunit vaccine (AstV P-HEV P-NoV P) induced higher levels of antibody response after intranasal immunization of mice compared to the three mixed vaccines.¹⁰⁷ PP can be easily produced in Escherichia coli and preclinical data based on GII.4 PP have been sprung up in recent years^108–114 (Table 2). Although PP vaccine ease of particle production at scale offers a potential cost advantage, it has not yet progressed to trials in humans until now.

Table 2. Human NoV vaccine candidates in preclinical trials

Reference	Genotypes included in vaccine		Technology platform	Route of administration
P particle–based vaccines
Tan et al^Citation106		GII.4/GI.1+ rVP8	Protein Expression in Bacteria	Intranasal
Xia et al^Citation107		GII.4+ HEV+ AstV	Protein Expression in E.coli	Intranasal
Tan et al^Citation108		GII.4/GI.1	Protein Expression in E.coli	Intranasal
Verma et al^Citation109		GII.4	Protein Expression in Bacteria	Intranasal/ Subcutaneous
Xia et al^Citation110		GII.4+ influenza A M2e	Protein Expression in E.coli(pQE-30)	Intranasal
Wang et al^Citation111		GST+GII.4+ HEV and GII.4+ HEV	Protein Expression in E.coli(BL21, DE3)	Intranasal
Jiang et al^Citation112		GII.4+ EV71	Protein Expression in E.coli(pET28a)	Intraperitoneal
Yu et al^Citation113		GII.4+ HIV-1(4E10/10E8)	Protein Expression in E.coli(BL21)	subcutaneous
Dai et al^Citation114		GII.4/GII.17	P proteins were expressed in E. coli.	/
Multivalent VLP-based vaccines
Malm et al^Citation115		GI.1/GI.3/GII.4/GII.12	Baculovirus expression system and purified from insect cells	Intramuscular
Malm et al^Citation116		GII.17+ GII.4+ GII.12+ GI.1+ GI.3	Sf9 insect cells using Bacto-Bac baculovirus expression system	Intramuscular
Czakó et al^Citation117		GI.1/GI.4/GI.7/ GII.4	Baculovirus expression system	/
Han et al^Citation118		GI.1/GII.2/GII.3/GII.4/GII.17	Hansenula polymorpha expression system	Intraperitoneal
Son et al^Citation119		GI.4/GII.3/GII.4	baculovirus expression system	//
Tamminen et al^Citation120		GI.3/GII.4+ rVP6	Baculovirus expression vector system(BEVS)	Intramuscular
Blazevic et al^Citation121		GI.3/GII.12/GII.4+ rVP6	Insect Baculovirus Expression Vector System(IBEVS)	Intramuscular/Intradermal
Malm et al^Citation122		GI.4 /GII.4+ rVP6	Nicotiana benthamiana expressing norovirus VLP	Intradermal

Notwithstanding these results, the extensive antigenic diversity between different NoV genotypes affords only weak cross-protection, leading many researchers to focus on the development of multivalent VLP vaccines containing major epidemic genotypes. The antigenicity and receptor binding characteristics of VLPs are similar to those of PPs. However, VLPs using VP1 as antigen are more advantageous than PPs in inducing the production of high-level, high-affinity NoV-specific IgG antibodies, balancing Th1 and Th2 immune responses, and cross-immune protection of different NoV genotypes.¹²³ The technical platforms for preparing NoV VLP vaccines vary widely and include expression systems involving adenovirus, E. coli (bacteria), baculovirus (insect), Pichia/Hansenula (yeast) as well as expression in transgenic plants, and some of which have entered the clinical research phase (Table 3). The bivalent GI.1/GII.4 VLP vaccine designed by Takeda Pharmaceutical Company Limited has now entered phase II clinical stage, and Clinical studies have shown that this vaccine have good safety and immunogenicity, and it may induce the production of broadly neutralizing antibodies against new genotypes and heterologous strains. The recombinant NoV bivalent (GI.1/GII.4) vaccine (Hansenula) developed by the domestic Lanzhou Institute of Biological Products Co., Ltd. and the tetravalent (GI.1+ GII.3+ GII.4+ GII.17) recombinant NoV vaccine (Pichia pastoris) jointly developed by Shanghai Pasteur and Zhifei Biopharmaceutical Co., Ltd. have been approved by the National Medical Products Administration (NMPA) Clinical Trial License. Notably, the tetravalent recombinant NoV vaccine has applicability to the most NoV genotypes and has obtained clinical approval worldwide. With the emergence of non-GII.4 epidemic strains, more multivalent VLP vaccines are being assessed in preclinical studies^115–119(Table 2). In addition, the incorporation of rotavirus VP6 nanotubes as a delivery vehicle for NoV VLPs represents a unique feature, and this multivalent vaccine can induce protective immune responses to the vast majority of circulating NoV and RV genotypes^120–122 (Table 2).

Table 3. Human NoV vaccine candidates in clinical trials

Investigators	NoV genotypes included in vaccine	Technology platform	Route of administration	Present status/ ClinicalTrials.gov identifier:
Takeda Pharmaceuticals	GI.1/GII.4	Baculovirus expression vector system	Intramuscular (previously formulated as intranasal)	Phase II NCT02475278 NCT02669121 NCT02661490 NCT02153112 NCT02038907 NCT03039790 NCT02142504
Anhui Zhifeilong Kema Bio-Pharmaceutical Co. Ltd	GI.1/GII.3/GII.4/GII.17	Pichia pastoris expression system	Intramuscular	Phase I/II NCT04563533
Vaxart	GI.1/GII.4	Recombinant serotype 5 adenovirus expressing NoV VP1	Oral	Phase I NCT03897309
Lanzhou Institute of Biological Products Co., Ltd.|Bejing Vigoo Biological Co., Ltd.|National Vaccine & Serum Institute Co., Ltd.	GI.1/GII.4	Hansenula polymorpha expression system	Intramuscular	Phase I NCT04188691

Discussion

Economic development has accelerated population movement and provided opportunities for NoV infections to spread nationwide, e.g., the widespread distribution of contaminated frozen seafood. Fruit or vegetables irrigated with contaminated water can also act as a source of NoV infections. People of all ages can be infected with NoV, children are especially at risk and those under 5 year of age experience high hospitalization rates. In addition to coastal areas, NoV infections have been quite serious in Southwest China, which may be due to dietary habits and a lack of awareness of NoV prevention and control. In view of the increasingly serious NoV infection in China, epidemic surveillance needs to be strengthened urgently. In 2016, CaliciNet China started with 9 laboratories in 3 provinces and by 2018 their efforts increased to 17 laboratories in 6 provinces to monitor the epidemiology of NoV.⁷⁷ While the monitoring area of CaliciNet China continues to expand, we will have a comprehensive understanding of China’s NoV outbreaks in the future to better respond to infectious diarrhea outbreaks and targeting control and prevention efforts for risk reduction.

The structure of NoV RNA is unstable, this instability lead to the formation of new strains through the recombination between different NoV strains and antigenic drifts, triggering outbreaks, and escaping immunity. High viral load and faster reproduction speed promoted the outbreak of GII.P16-GII.2 and molecular evolution analysis has demonstrated that RdRp rather than VP1 sequence triggers pandemic.⁷¹ The widespread prevalence of GII.4 generates new variant strains through point mutations in the P2 region of the VP1 and accumulation of homologous recombination between different genotypes, showing genetic diversification and triggering pandemic! Since 1995, there have been at least 6 epidemic strains of GII.4, namely US 1995/96, Farmington Hills 2002, Hunter 2004, Den Haag 2006b/Yerseke_2006a, New Orleans 2009 and Sydney 2012. The study found GII.4 Sydney_2012 strain tends to undergo stable mutations during the asymptomatic shedding phase and may generate new variants in chronic patients via rapid evolution with stable mutations, so the evolution of GII.4 strain is more inclined to accumulated over time and co-evolution at the genome level.^124,125 Evolution analysis shows that GII.17 evolves faster than GII.4 viral protein (VP1) and is more likely to result in immune evasion. The rate of nucleotide substitution in the P2 region of the VP1 capsid protein of the GII.17 strain has averaged 1.2 × 10⁻² since 1978, but its evolution rate has accelerated to 3 × 10⁻² after 2014.¹²⁶ Why has the evolution rate of GII.17 accelerated after 2014? It may be that recombination has resulted in obvious nucleotide substitution in the VP1 region of GII.17 and accelerated evolution, which in turn led to changes in its receptor recognition site and epitope, giving GII.17 rapid spread and strong infectivity. Whether GII.2 and GII.17 will be sustained pandemic like GII.4, still needs monitoring and further confirmation.

Either from China or global perspective, GII.6 deserves attention. According to the Centers for Disease Control and Prevention (CDC) in United States, 7% outbreaks were caused by GII.P7-GII.6 from September 1, 2019 to August 31, 2020. It was reported the proportion of GII.6 strains in non-GII.4 strains was second only to GII.3 in developing countries from 1997 to 2018.⁹ In China, GII.6 followed by GII.3, was the second prevalent strain among non-GII.4 genotypes, accounting for 6% before 2014. Although data showed the proportion of GII.6 had declined in recent years, it still played a prominent role in gastroenteritis outbreak, e.g., CaliciNet China epidemiological surveillance showed 13 of the 16 outbreaks were caused by GII.6 in the winter between 2017 and 2018.^77,127 GI genotypes should be strengthened in routine surveillance. Although the main epidemic strains causing NoV infection were mainly GII genotypes, GI genotypes detected have increased significantly in recent years, e.g., GI strains accounted for 12.5% and more than 16.67% of patients with AGE in Heilongjiang Province and Fushun City Liaoning Province from 2017 to 2019.^59,128

Immunoassay research based on VLP and PP vaccine candidates helps to understand the immune response of NoV to the host. The findings from in clinical and preclinical studies have suggested that VLP and PP are promising vaccines and multivalent vaccination might be an effective strategy for inducing broadly neutralizing antibodies protective against challenge with novel and heterologous NoV strains. The uncertainty of NoV evolution brings great risks to long-term vaccine development. Due to the lack of simple and standardized animal models and effective tissue culture systems in vitro that can be applied to vaccine evaluation, HBGA in vitro blocking test is usually evaluated for the protective effect of NoV vaccine by laboratories. The HBGA receptor binding domain of VP1 was relatively conservative, and the antibodies produced by infected persons with the same genotype can cross-protect different mutant strains. Dai et al.¹²⁹ in 2013 conducted genetic analysis on GII.4 strains from 1974 to 2012, and found that the HBGA receptor blocking experiment produced antibodies from GII.4 in infected volunteers which can cross-protect 14 different GII.4 strains. Swanstrom et al. in 2014 analyzed the GII.2 sequence from 1976 to 2010 and found that serum infected with GII.2.1976 can block GII.2.2002, GII.2.2008 and GII.2.2010.¹³⁰ Most researchers agree that cross-immunity exists only possible within the same genogroup.^115–118 However, evidence confirms that cross-immunity can exist between genogroups (GI and GII). Czakó et al. in 2015 demonstrated that following GI.1 infection, cross-blocking antibodies against GII.4 were also produced.¹¹⁷ Although results were not consistent, molecular evolution mechanism have shown that the key residues bind to HBGAs between GI and GII genogroups are highly conserved,¹³¹ which provides a theoretical basis for the development of a vaccine that induces broad-spectrum cross-protective antibody immunity against multiple NoV genotypes. Whether multivalent vaccines under development can meet the needs of preventing strains not included in the vaccine and whether the breadth and stability of the vaccine response are sufficient to cope with the diversity and cyclical changes of NoV genotypes remains to be verified. Currently, NoV vaccine development aims to expand the protective efficacy by increasing exposure to genotypes. Candidate vaccines under research prioritize GII.4 and GI.1 strains. Although GII.4 has been supplanted by the GII.2 and GII.17 genotypes for some time in China, it remained prevalent strain globally. In contrast, GI.1 rarely caused an epidemic and GII.6 has a continuous and extensive epidemic capacity on a global scale based on comprehensive global epidemiologic data. Of note, prior work has showed that recombinant strain carrying GII.P16 RdRp genotype like GII.2 and GII.4 have caused pandemics, whether GII.P16 combination with other capsid genotypes would cause pandemic remains to be monitored continual. Molecular epidemiologic surveillance for identifying promptly the emergence of NoV variants is highly significant to the development of multivalent NoV vaccines with broad protective efficacy. During the process of vaccine development, it is necessary to make adjustments according to the change of the predominant strains.

Conclusions

In China, there is very little data on NoV infections in asymptomatic individuals. The frequency and severity of NoV infections was surprisingly serious in gastroenteritis patients, notably children. Because of the rapid evolution, non-GII.4 strains have become the predominant strains and caused multiple outbreaks since 2014. Immunization is one of the most effective strategies to prevent infectious disease, but genetic variability remains the major obstacle for the development of effective vaccines against NoV. Successfully developing a vaccine that can broadly induce neutralizing antibodies protective against novel and heterologous strains has being an international problem and also the key problem to be addressed in future work. Presently, however, the selection of antigen components remains an important factor in evaluating vaccine efficacy. Nonetheless, much uncertainty exists when predicting future NoV predominant strains, and ongoing vaccine development efforts must be ready to face this obstacle. Thankfully, NoV epidemic surveillance can be a tool to guide vaccine development. Disease outbreaks can be effectively prevented and controlled by cutting off the route of transmission at the earliest possible stage, and the best way is to strengthen the public’s awareness of self-protection before vaccination available.

Author contributions

Formal analysis, Na Wei; Investigation, Na Wei; Original draft preparation, Na Wei; Manuscript critical revisions, Jun Ge, Changyao Tan, Yunlong Song, Mengru Bao and Jianqiang Li. All authors have read and agreed to the published version of the manuscript.

Disclosure of potential conflicts of interest

The authors declare no conflict of interest for this paper.

Additional information

Funding

This review received no external funding.