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Detection of human noroviruses in sewage by next generation sequencing in Shandong Province, 2019–2021

Virology Journal volume 22, Article number: 18 (2025) Cite this article

Abstract

Background

Human noroviruses are the major cause of acute gastroenteritis and exhibit considerable genetic diversity. Next generation sequencing (NGS) analysis based on environmental surveillance has been proved to be an effective method in norovirus surveillance.

Methods

Between January 2019 and December 2021, 36 sewage samples were collected and analyzed using real-time quantitative PCR to detect noroviruses. Partial VP1 region was amplified and subjected to NGS analysis to assess the abundance and genetic characterization of various norovirus genotypes across different samples.

Results

A total of 23 norovirus genotypes were identified, including 9 genotypes of GI, 13 genotypes of GII and 1 genotype of GIX. The most frequently detected genotypes were GI.5 (86.11%), GII.2 (86.11%), GII.4 (63.89%), GII.17 (58.33%), and GII.13 (55.56%). Additionally, some rare genotypes, such as GI.7, GII.5, GII.9, and GII.16, which had not been previously reported in Shandong, were identified. No significant differences were observed in genotypic diversity or viral copy numbers in sewage samples when comparing pre- and post-COVID-19 periods. A total of 379 partial VP1 sequences were obtained, with the means sequence identity within a genotype of Shandong sequences ranging from 92.69 to 98.37% and a coefficient of variation ranging from 1.46 to 6.73%. Phylogenetic analysis indicated that local noroviruses within each genotype comprised multiple co-circulating lineages.

Conclusions

Our data demonstrate that sewage contains noroviruses with considerable high diversities. NGS based environmental surveillance greatly improves the understanding of norovirus circulation and should be encouraged.

Background

Noroviruses (NoVs) constitute a genus within the family Caliciviridae and are capable of infecting a diverse array of mammalian host species. Human NoVs exhibit significant genetic diversity and represent the primary etiological agent of acute gastroenteritis across all age groups globally, with an estimated 685 million cases annually [1, 2]. Presently, there are no approved therapeutics or vaccines available for the prevention or treatment of NoV infections [3, 4].

NoV is a single-stranded, positive-sense RNA virus. The genome of human NoV is organized into three ORFs (ORF1, ORF2, and ORF3), which encode eight viral proteins. ORF1 encodes six nonstructural proteins (NS1/2 to NS7). ORF2 and ORF3 encode structural proteins VP1 and VP2, respectively [5, 6]. Based on the diversity of VP1 sequence, NoVs can be classified into 10 genogroups (GI–GX) and 2 tentative new genogroups (GNA1 and GNA2). GI, GII, GIV, GVIII, and GIX NoVs can infect humans among which GII is the most prevalent [7].

Molecular epidemiological studies have demonstrated a marked genetic diversity among circulating NoVs [8]. While GII.4 variants have historically been responsible for widespread epidemics, the predominant genotype shifted from GII.4 to GII.17 in certain regions, such as China, during the period of 2014–2016 [9, 10]. Additionally, recombinant strains such as GII.2 (P16) have been implicated in gastroenteritis outbreaks [11]. Therefore, investigating the genetic diversity of NoVs is crucial for early warning systems and vaccine development. However, detecting emerging variants prior to widespread transmission poses a significant challenge when relying solely on conventional clinical surveillance systems [11]. Consequently, the current clinical surveillance framework may fail to provide a timely response to emerging epidemics. In this context, sewage surveillance has emerged as a critical complement to traditional clinical monitoring. The RNA of NoVs present in wastewater samples can be quantitatively assessed via reverse transcription-quantitative polymerase chain reaction (RT-qPCR), thereby providing a numerical estimation of the potential infection levels [12, 13].

Shandong is a coastal province with a land area of 158,100 square kilometers and a population of 101.23 million as of 2023. Previous research has indicated that 21.76% of hospitalized patients with acute gastroenteritis in Shandong between 2016 and 2018 tested positive for NoV [14]. Additionally, a significant waterborne norovirus gastroenteritis outbreak was documented in a school, resulting in 1614 cases [15]. These findings highlight the critical role of NoV as a major pathogen responsible for viral gastroenteritis in Shandong. In this study, we employed next generation sequencing (NGS)-based environmental surveillance to investigate the genetic diversity and temporal dynamics of NoVs from January 2019 to December 2021, covering 12 months prior to and 24 months following the onset of the COVID-19 pandemic.

Materials and methods

Sewage collection and concentration

Sewage samples were monthly collected from a sewage treatment plant in Jinan, the capital city of Shandong Province, China, from January 2019 to December 2021. In addition to NoV, these sewage samples were analyzed for the presence of poliovirus, in support of the polio eradication initiative, as well as for the detection and study of other enteroviruses. The plant serves an area with approximately 400,000 inhabitants, and the average daily inflow of raw sewage ranges from 6 × 104 to 10 × 104 m3, originating from both domestic sewage and industrial wastewater. Approximately 1.6 L of influent sewage was collected using the grab sampling method between 2:00 and 3:00 p.m in the middle of each month. During sample transport to the laboratory, storage (less than 24 h), and processing, a cold temperature (approximately 4 °C) was maintained. The concentration of the samples was achieved using the electro-negative charged membrane adsorption elution method [16, 17]. Briefly, 1 l of sewage was centrifuged at 3000 × g for 30 min. 2.5 M MgCl2 was added to the supernatant for a final concentration of 0.05 M, and 0.5 M HCl was added to adjust to pH 3.5. The solution was then filtered through a cellulose acetate membrane (pore size 10 μm, diameter 124 mm, Advantec, Japan) and a mixed cellulose ester (MCE) membrane (pore size 0.45 μm, diameter 142 mm, Advantec, Japan). The MCE membrane was cut into tiny pieces, then soaked with 10 ml of 3.0% beef extract solution (pH 8.5). After ultrasonication for 3 min, centrifugation at 3600 × g for 30 min, and filtration (pore size 0.22 μm, Millipore, USA), the filtrated solution was ready for detection.

RNA extraction and real-time quantitative PCR (qPCR)

Viral nucleic acid was extracted from the filtrated solution using MagMAX Pathogen RNA/DNA Kit (Thermo Fisher, Lithuania). TaqMan-based qPCR for norovirus GI and GII was performed separately using primers and probes described previously (Cog 1F, Cog 1R, Ring 1A, and Ring 1B for GI and Cog 2F, Cog 2R, and Ring 2 for GII) [18] with AgPath-ID One-Step RT-PCR reagents (Applied Biosystems, Foster City, USA) in ABI 7500 instrument. Two microliters of sample RNA were added as the template, and the final volume was adjusted to 25 μl. Each sample was tested in triplicate. The amplification conditions were 45 °C for 10 min and 95 °C for 10 min, followed by 40 cycles of 95 °C for 15 s and 60 °C for 45 s. In each reaction, a positive control using positive NoV RNA and a negative water control were used. To determine the copy numbers of GI and GII norovirus genome, standard curves were conducted by tenfold dilutions (101 ~ 109) of plasmid DNA containing target genes. Quantification of pepper mild mottle virus (PMMoV) RNAs in concentrated wastewater samples was used as quality control [17, 19].

Partial VP1 amplification, NGS library preparation and sequencing

Viral nucleic acid was extracted from the sewage concentrate as described above. Purified RNA was reverse transcribed with Superscript III (Thermo Fisher, USA) by using random primers. The cDNA was then used for the first round of PCR amplification with primer pairs COG1F/G1SKR for GI and COG2F/G2SKR for GII. After 35 cycles of amplification, 0.5 μl of the first PCR products were used as a template in the second-round PCR with the primer pairs G1SKF/G1SKR for GI and G2SKF/G2SKR for GII [20]. The length of amplicons is 330-nt for GI (positions 5342–5671 on strain GI/Hu/US/1968/GI.1/Norwalk, M87661) and 342-nt for GII (positions 5048–5389 on strain GII/Hu/US/1971/GII.1/Hawaii, U07611), respectively.

After 35 cycles of amplification, the positive products were subjected to BGI (Shenzhen, Guangdong Province, China) for library preparation and sequencing using the DNBSEQ platform. NGS assay was performed separately for each amplicon. Briefly, A-Tailing Mix and RNA Index Adapters were added by incubation to carry out end repair. PCR amplification was conducted on the obtained fragments, and PCR products were subjected to heat denaturation, followed by circularization using the splint oligo sequence. The final library was amplified with phi29 to make DNA nanoballs (DNBs) which were compacted on high density patterned nanoarray and sequenced by combinatorial Probe Anchor Synthesis.

After sequencing, clean reads were obtained by removing reads containing adapters, reads < 150 bp in length, reads containing poly-N, and low-quality reads (> 30% bases with Q-values < 20). The output read quality value system is set to Phred + 33.

De Novo assembly of the clean data was conducted in CLC Genomics Workbench 12.0 (CLC Bio, Qiagen, Hilden, Germany) using the default options. Contigs > 200 bp in length and with > 10 × coverage was queried for sequence similarity using BLAST (https://blast.ncbi.nlm.nih.gov/Blast.cgi). An additional resequencing assembly of the clean reads was carried out to obtain consensuses of all norovirus genotypes observed in the above de novo assembly.

Homologous comparison and phylogenetic analysis

The 5′-end of VP1 (region C) was used for further sequence analysis, corresponding to genomic positions 5358–5671 on strain GI/Hu/US/1968/GI.1/Norwalk (M87661) for GI-NoV and positions 5085–5389 on strain GII/Hu/US/1971/GII.1/Hawaii (U07611) for GII-NoV, respectively. Multiple sequence alignment was performed using ClustalW and sequence similarities were calculated by the BioEdit software (version 7.0.5.3). Genotypes were assigned using the Norovirus Genotyping Tool (http://www.rivm.nl/mpf/norovirus/typing tool). Phylogenetic analysis was performed by Mega 11.0 software using the neighbor-joining method with a Kimura-2 parameter model and 1000 bootstrap replications.

The evolutionary rate and molecular clock phylogeny were inferred using the Bayesian Markov chain Monte Carlo (MCMC) method in BEAST version 1.6.1. The best nucleotide substitution Model was selected using Mega 11.0. The clock model and demographic model were compared by calculating Akaike’s information criterion through MCMC (AICM), for each model using Tracer v1.6.1. In this study, we tested 4 clock models including a strict clock, an uncorrelated lognormal relaxed clock, an uncorrelated exponential relaxed clock, and a random local clock. Two demographic models, constant size model and exponential growth model, were also compared using AICM calculation. We employed the model with the lowest AICM value. The MCMC chains were run for 30,000,000 steps and sampled every 10,000 steps. Convergence was assessed from the effective sample size (ESS) after a 10% burn-in using Tracer v1.6.1. ESS values above 200 were accepted. Uncertainty in the estimates was indicated by 95% highest posterior density (95% HPD) intervals.

Statistical analysis

To compare the means of two independent groups, the Independent Samples t-test was utilized. For categorical data, the chi-square test was employed to assess the association between variables or to compare proportions across groups. All statistical analyses were conducted using SPSS version 19.0, with a significance threshold set at P < 0.05 for all tests.

Nucleotide sequence accession numbers

The partial VP1 region sequences of environmental norovirus described in this report were deposited in the GenBank database under the accession numbers OR994323-OR994497, OR994513-OR994520, OR999378-OR999385, PP000305-PP000492.

Results

Quantification of norovirus genomes in wastewater

All 36 sewage samples collected from January 2019 to December 2021 tested positive for both GI and GII NoV RNA via qPCR assay. The concentrations (genomic copies l−1) of norovirus GI and GII ranged from 7.37 × 102 in January 2019 to 1.29 × 107 in August 2019, and from 2.38 × 105 in June 2021 to 1.83 × 107 in May 2021, respectively (Fig. 1A). The average viral concentrations of NoV GI and GII were calculated and compared using a t-test, revealing a significant difference (F = 7.366, P < 0.01). The logarithm of the geometric means of GI concentrations was significantly lower than that of GII (Fig. 1B). The peak concentrations of NoV GI and GII were both observed in August, with values of 1.06 × 106 and 3.69 × 106, respectively. The minimum concentrations were recorded in February, with values of 8.60 × 103 and 3.05 × 105 respectively. However, the concentrations of genogroups GI and GII did not exhibit statistically significant differences before and during the COVID-19 pandemic (GI: F = 4.12, P = 0.05; GII: F = 2.19, P = 0.148; t-test).

Fig. 1
figure 1

Genome Concentrations of norovirus GI and GII in sewage. Panel A displays log values of genome concentrations of norovirus GI and GII in sewage in each month from 2019 to 2021. Panel B displays the log values of genome concentrations of GI and GII by month

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As internal quality control, PMMoV was tested positive in all samples with the genomic copies l−1 ranging from 1.1 × 107 to 1.0 × 109 copies per liter. These relatively stable and high values suggest that sewage was concentrated at high efficiencies.

Partial VP1 gene amplification and NGS data

VP1 nested RT-PCR assay revealed a 100.0% (36/36) positivity rate for GII and a 94.4% (34/36) positivity rate for GI amplification. The negative results were associated with sewage samples collected in February and November 2020. The NGS clean data from 70 amplicons was independently analyzed using the CLC Genomics Workbench. The number of NGS reads and NoV reads produced from each amplicon is detailed in Supplementary Table 1. In total, 722,234,524 NGS reads were generated from 34 GI amplicons, with 721,931,942 (99.96%) identified as NoV. Similarly, 733,146,126 NGS reads were generated from 36 GII amplicons, with 722,743,097 (98.58%) classified as NoV. The total filtered reads per amplicon ranged from 5,884,219 to 31,363,014, with 78.30% to 100.00% of these reads mapped to NoV.

A total of three genogroups (GI, GII and GIX) were detected from all 36 sewage samples. For the 34 amplicons generated using the GI primer set, 721,931,942 reads were mapped to NoV, of which 99.99% (721,919,682/721,931,942) were identified as GI while less than 0.01% (12,260/721,931,942) were identified as GII. For the 36 amplicons generated using the GII primer set, 722,743,097 reads were mapped to NoV, of which 89.03% (643,486,469/722,743,097) were identified as GII while 0.51% (3,694,068/722,743,097) and 10.46% (75,562,560/722,743,097) were identified as GI and GIX, respectively.

Genotype diversity

A total of 23 genotypes were identified in this study. When summing up the NGS reads of all samples, the read counts ranged from 14,578 (GII.10) to 328,172,418 (GI.5). The five most abundant genotypes were GI.5, GII.2, GI.3, GII.4, and GII.17. Additionally, the detection frequency of individual genotypes was calculated, revealing that the five most frequently detected genotypes were GI.5 (86.11%), GII.2 (86.11%), GII.4 (63.89%), GII.17 (58.33%), and GII.13 (55.56%) (Table 1 and Fig. 2).

Table 1 Numbers of NGS reads, frequencies, and ranks for individual norovirus genotypes detected in sewage
Full size table
Fig. 2
figure 2

Norovirus genotypes detected from sewage samples in every month during 2019–2021. The color illustrates the logarithm value of the number of NGS reads belonging to different genotypes

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The genotype proportion, termed G-proportion, was determined by dividing the read counts of a specific genotype by the total read counts of all genotypes within the same month. Subsequently, the G-proportion was categorized into six groups: 0– < 5%, 5– < 10%, 10– < 15%, 15– < 20%, 20– < 30%, and ≥ 30%. Based on this classification, the number of genotypes detected each month was enumerated (Table 2), with monthly detections ranging from 3 to 13 genotypes. The lowest number of genotypes were observed in June 2021, while the highest was recorded in September 2020. When considering genotypes with a G-proportion exceeding 5%, the monthly detections varied between 2 and 8 genotypes. The minimum number of such genotypes was detected in November 2020, whereas the maximum was observed in both August 2020 and April 2021. There were 23 months during which at least 5 genotypes with a G-proportion greater than 5% were detected. Among these, 7 months exhibited at least 7 genotypes with a G-proportion exceeding 5%, specifically in July 2019, September 2019, January 2020, April 2020, August 2020, September 2020, and April 2021. Annually, 20, 18, and 19 genotypes were detected in 2019, 2020, and 2021, respectively.

Table 2 The numbers of genotypes in different G-proportion groups, by year and by month*
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To further investigate the predominant genotypes during the study period, we identified genotypes with a G-proportion exceeding 15% and recorded the number of months in which these genotypes were detected (Supplementary Table 2). The findings indicated that five genotypes—GI.3, GI.5, GII.2, GII.4, and GII.17—exhibited a G-proportion greater than 15% and were detected in more than five months. Notably, GI.3, GI.5, and GII.2 were detected in over ten months.

We analyzed the G-proportion of these five main genotypes across different months (Fig. 3). A long-term competitive relationship was observed between GI.5 and GII.2, with these two genotypes displaying opposite trends in more than 20 out of the 36 months, as their G-proportions alternated in dominance. During the period of 2019–2020, GII.17 emerged as one of the predominant genotypes. However, from June to August 2020, its detection rate experienced a marked decline, and since September 2020, GII.17 has been classified as a minor genotype. In contrast, the detection pattern of GI.3 exhibited a pulse-like trend from September 2019 to June 2021, indicating the occurrence of intermittent small-scale outbreaks during this timeframe. Although the G-proportions of GII.4 were lower than those of GII.2, GII.4 remained consistently present from 2019 to 2021.

Fig. 3
figure 3

The G-proportion of 5 predominant genotypes in each month from 2019 to 2021. Panel A displays GI.3 and GI.5. Panel B displays GII.2, GII.4, and GII.17

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Monthly distribution of common genotypes

We independently computed the read counts for each season during the years 2019, 2020, and 2021. Subsequently, we determined the monthly proportion (denoted as M-proportion) of a specific genotype by dividing its read count for a given month by the total annual read count of that genotype within the same year. We then categorized the M-proportion into six groups: 0– < 5%, 5– < 10%, 10– < 15%, 15– < 20%, 20– < 30%, and ≥ 30%. Based on this classification, we quantified the number of genotypes detected each month. We focused on genotypes that were detectable in the majority of months and, for these genotypes, we counted the number of months in which the M-proportion exceeded 15%. Our findings indicated that 14 genotypes, specifically GI.5, GII.2, GI.3, GII.4, GII.17, GII.3, GIX.1, GII.13, GI.2, GI.1, GI.8, GI.4, GI.9, and GI.6, were consistently detected in most months with an M-proportion greater than 15%. Further analysis on a monthly basis revealed several instances of notably higher M-proportions: November 2019 for genotype GI.3, July 2020 for genotype GII.4, May 2021 for genotype GI.3, June 2021 for genotype GII.2, and October 2021 for genotype GII.17. Then we conducted a statistical comparison of the M-proportions by seasons for each genotype, but no significant differences were observed.

Homologous comparison and phylogenetic analysis

Homologous comparison was conducted on the partial VP1 sequences generated from resequencing analysis (n = 379). Nucleotide similarities and the coefficient of variation (CV) of these similarities were calculated. The incorporation of the mean and CV of similarity provides a more precise reflection of the average similarity and dispersion among indigenous viruses compared to traditional indices. The analysis revealed that, for GI and GII, GI.3 exhibited the highest CV (6.73%), with similarities ranging from 80.5 to 100.0%, while GII.3 demonstrated the lowest CV (1.46%), with similarities ranging from 93.7 to 100%. Specifically for GI, GI.5 had the lowest CV (2.54%), with similarities ranging from 86.3 to 100.0%. For GII, GII.2 had the highest CV (5.00%), with the similarities ranging from 79.9 to 100.0%. The mean nucleotide similarities of each genotype were also explored and they ranged from 92.69% (GII.17) to 98.37% (GII.3).

To investigate the genetic relationships of NoV, phylogenetic analysis were performed based on the partial VP1 region, utilizing sequences from Shandong and 51 reference sequences from GenBank (Fig. 4). The phylogenetic trees did not reveal distinct temporal demarcations among the isolates, as sequences from different years of isolation were found within the same cluster. Multiple transmission chains were identified in the phylogenetic trees for genotypes GI.1, GI.2, GI.3, GI.5, GII.2, GII.4, and GII.17.

Fig. 4
figure 4

Phylogenetic trees based on partial VP1 nucleotide sequences of GI (A) and GII (B) noroviruses. The sequences are identified by a code that consists of primer set (GI/GII), followed by collection year (YY), collection month, and genotypes

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Evolutionary rate of norovirus GI and GII

The molecular evolution rate analysis was carried out on genotypes with more than 10 sequences and effective sample size (ESS) values exceeding 200. The results indicated that GI.3 exhibited the highest evolutionary rate at 9.81 × 10–3 substitutions/site/year (95% HPD: 1.71 × 10–3–3.38 × 10–3), while GII.3 displayed the lowest evolutionary rate at 3.07 × 10−4 (95% HPD: 1.34 × 10−5–1.75 × 10−3) (Supplementary Table 3).

Discussion

In this study, we identified multiple NoV genotypes and observed dynamic variations in the predominant genotypes present in sewage samples collected between 2019 and 2021. NoVs are genetically diverse RNA viruses that continue to evolve in human populations through mechanisms such as point mutations and genome recombination [21]. Various factors, including immune selection pressure, geographic influences, and seasonal variations, may contribute to the diversity of norovirus genotypes [22]. Although the GII.4 genotype has predominated for over two decades, other genotypes can temporarily become predominant in specific geographic regions, as evidenced by the recent emergence and increased incidence of GII.17 and GII.2 in various countries [9, 23]. Consequently, regional surveillance is increasingly critical for detecting the emergence of new variants, providing early warnings of potential outbreaks, and informing vaccine development strategies.

Currently, NoV surveillance networks primarily focus on outbreaks or sporadic infections reported by clinical settings. However, it is important to consider potential biases in the reporting of sporadic infections by sentinel hospitals, as genotypes associated with relatively severe symptoms are more likely to be detected. Outbreak surveillance predominantly identifies genotypes that are already efficiently transmitted within the population. However, detecting variants that have not yet established transmission in the local population presents a challenge [20]. Consequently, environmental surveillance serves as a crucial supplement.

Sewage contains a diverse array of organisms, including bacteria, archaea, insects, and their associated viruses, although the proportion of human viruses is relatively small in metagenomic NGS analysis [24, 25]. In previous studies, we investigated NoVs in sewage from Shandong Province during 2013–2014 using partial VP1 RT-PCR, cloning, and Sanger sequencing methodologies, identifying 16 norovirus genotypes [26, 27]. However, this approach is labor-intensive, and genotypes with low genomic copy numbers are challenging to detect. NGS analysis based on PCR amplicons has demonstrated efficacy in investigating specific viral pathogens, such as adenovirus, sapovirus, and enterovirus, in sewage [28,29,30,31,32]. Moreover, compared to traditional Sanger sequencing and cloning methods, NGS analysis has significantly enhanced the understanding of NoV diversity [29, 33]. Therefore, in this study, we employed NGS-based environmental surveillance to explore the diversity and temporal dynamics of NoVs. We identified a greater number of genotypes (23 compared to 16) via NGS method, including several rare variants such as GI.7, GII.5, GII.9, and GII.16, which had not been previously detected in Shandong. Additionally, we noted a decreased prevalence of genotypes that were common in 2013–2014, specifically GI.2, GI.6, GII.3, and GII.13, which ranked 8th, 14th, 6th, and 5th, respectively, in frequency during the period from 2019 to 2022. This observation underscores the dynamic shifts in dominant genotypes over time.

The study encompasses both pre- and post-COVID-19 periods, with a notably larger sample size in 2020–2021 (n = 24) compared to 2019 (n = 12). Consequently, we conducted an annual analysis and found that 14, 15, and 18 genotypes were detected in 2019, 2020, and 2021, respectively. These findings suggest that noroviruses maintained high genotypic diversity, with no reduction observed during the COVID-19 pandemic. The concentrations of genogroups GI and GII did not exhibit significant differences before and during the pandemic; however, GII noroviruses were present at significantly higher concentrations than GI, aligning with previous studies [30].

In this study, GI.3, GI.5, GII.2, GII.4 and GII.17 were the predominant genotypes. Previously, GI.5 was identified as one of the most prevalent GI genotypes in sewage samples collected in Shandong in 2013 [26]. A notable outbreak of acute gastroenteritis in a primary school in Shanghai, China, in 2017 was linked to the GI.5 norovirus, marking the first reported outbreak of this genotype in the country [34]. Despite this, outbreaks caused by GI.5 remain relatively rare compared to those caused by other genotypes. In the present study, GI.5 emerged as the most frequently detected genotype, with the highest number of NGS reads, indicating significant activity in Shandong Province during the study period. Notably, research conducted by Hoque et al. [35] on NoVs in Japanese sewage between 2019 and 2022 identified GI.3 and GI.6 as the predominant GI genotypes, with no detection of GI.5. This suggests that the heightened activity of GI.5 may have been confined to a specific region and was not observed concurrently in other countries.

GII.2 strains have recently emerged, with a notable increase in prevalence during the 2016–2017 winter season, leading to significant outbreaks in several countries, including Japan, China, France, Italy, Germany, and Thailand [36, 37]. An analysis of data from laboratory-based surveillance of norovirus outbreaks in China (CaliciNet China) from October 2016 to December 2020 identified GII.2 [P16] as the predominant strain, accounting for 69.0% of GII outbreaks [38]. This study found GII.2 to be the most prevalent GII genotype, with multiple transmission lineages observed in the phylogenetic tree, indicating its high prevalence and circulation history among local gastroenteritis patients. However, previous reports suggest that the prevalence of GII.2 has not consistently remained high and may not be as dominant as other genotypes, such as GII.4, in many regions [39]. Therefore, continuous monitoring should be enhanced to track the incidence of gastroenteritis cases caused by the GII.2 genotype.

GII.17 has been a significant NoV genotype associated with widespread regional epidemics, having been detected globally for over three decades. Notably, during the winter of 2014–2015, there was an observed increase in the prevalence of GII.17 in NoV outbreaks in East Asia, surpassing the incidence of GII.4 NoV infections [40]. However, the current study indicates a marked decline in the detection of GII.17 since September 2020. Similarly, six European countries and the United States reported low detection levels of GII.17 in gastroenteritis surveillance during 2020–2021 [41]. This decline may be attributed, in part, to the non-pharmaceutical interventions implemented following the COVID-19 outbreak.

The evolutionary rates were also calculated according to the partial VP1 (region C). Compared to others reports in which the evolutionary rate were calculated according to the whole VP1 region isolated from acute NoV-associated gastroenteritis patients, the evolutionary rates of GII.4 and GII.17 were similar with previous reports, all about 5.22 × 10–3 and 1.87 × 10–3 substitutions/site/year. However, the accuracy of using partial VP1 to calculate the evolutionary rate needs further study. Because amino acid mutations in the structural proteins of some genotypes such as GII.4 and GII.17 can bring out sudden transitions in their antigenicity or infectivity [42,43,44], it is important to closely monitor the genetic changes by using efficient monitoring and detection methods, thereby enhancing public health responses and reducing the spread of related diseases.

The present study is subject to several limitations. Firstly, our analysis relies on the amplification of a partial VP1 coding region. Although this approach is sensitive and suitable for NoV typing, the resulting amplicon is approximately 300 nucleotides in length, providing less information than the full-length VP1 sequence. This limitation may affect the accuracy of evolutionary rate calculations. Future research should focus on developing methods to amplify the full-length VP1 coding region, which would enhance the impact of sewage surveillance and evolutionary genetics studies. Secondly, there was an imbalance in sample sizes between the years 2019 and 2020–2021. To address this discrepancy, our comparative analysis of the pre- and post-COVID-19 periods emphasized annual average levels rather than overall figures. Lastly, the complexity of sewage and environmental factors can influence NoV detection. To minimize bias, future studies should increase sampling frequency and employ a 24-h mixed sampling method.

Conclusions

In this study, NGS-based environmental surveillance was utilized to investigate the diversity and temporal dynamics of NoVs. Our findings reveal that sewage harbors noroviruses with considerable genetic diversity. Genotypes that are consistently detected in significant proportions warrant particular attention. NGS-based environmental surveillance significantly enhances our understanding of NoV circulation. Given the continuous reduction in costs, amplicon NGS represents a promising approach that merits further encouragement.

Availability of data and materials

The sequences have been deposited in the GenBank database under the accession numbers OR994323-OR994497, OR994513-OR994520, OR999378-OR999385, and PP000305-PP000492.

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Funding

This study was supported by three grants from Medical and Health Science and Technology Development Plan Program of Shandong (202012051301, 202312050983, 202412051234) and a grant from Taishan Scholar Program of Young Experts (tsqn.202103187).

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Author notes

  1. Suting Wang and Mingyi Xu have contributed equally to this work.

Authors and Affiliations

  1. Shandong Center for Disease Control and Prevention, Jinan, 250014, China

    Suting Wang, Xiaojuan Lin, Ping Xiong, Yao Liu, Aiqiang Xu, Meng Chen & Zexin Tao

  2. Shandong Academy of Occupational Health and Occupational Medicine, Jinan, 250062, China

    Mingyi Xu

  3. Linyi Center for Disease Control and Prevention, Linyi, 276007, China

    Shengxiang Ji

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  1. Suting Wang
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Contributions

S.W., X.L. and M.C. performed the analyses. X.L., P.X., Y.L. and analyzed the data. S.W. and M.X. drafted the manuscript. S.J. and Z.T. conceived and designed the experiments. A.X. supervised the project, and revised the manuscript. S.W. and Z.T. acquired funding. All the authors have reviewed the manuscript.

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Correspondence to Shengxiang Ji or Zexin Tao.

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Wang, S., Xu, M., Lin, X. et al. Detection of human noroviruses in sewage by next generation sequencing in Shandong Province, 2019–2021. Virol J 22, 18 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12985-025-02638-5

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