The saga to monitor and control norovirus: the rise of GII.17

Abstract

Norovirus is a major cause of acute gastroenteritis in all age groups, with recent surges of cases in Europe and the USA reinforcing the influence of this virus on human health. Despite its societal impact, no vaccine or antiviral drug is available. The development of these countermeasures has been impaired at least in part by the extreme genetic and antigenic diversity of noroviruses. Here, we reviewed historical norovirus outbreaks, including the pandemics of GII.4 norovirus that were first documented in the mid-1990s, sporadic increases of non-GII.4 norovirus (e.g. GII.17 and GII.2) during the 2010s and, most recently, the ongoing large outbreaks caused by a new cluster of GII.17 noroviruses. This five-decade-long journey of tracking noroviruses in the human population illustrates the importance and challenges of battling this evolving virus.

Keywords: antigenic diversity; diarrhea; histo-blood group antigen (HBGA); norovirus; virus evolution.

Fig. 1.. Temporal distribution of major norovirus genotypes and polymerase types. The human norovirus sequences (≥100 nt in length, n=39,345) deposited in GenBank were collected (15 January 2025) and annotated by time, location and genotypes using Norovirus Typing Tool when available [110]. (a) Distribution of capsid genotypes. The solid-coloured lines denote the temporal trend of the top five major genotypes, GII.4, GII.3, GII.2, GII.17 and GII.6 per year. (b) Distribution of polymerase types. The solid-coloured lines denote the temporal trend of the top five major polymerase types per year. The pie charts indicate the prevalence of different genotypes and polymerase types detected before (left) and after (right) 1995. The dotted grey lines represent the total number of human norovirus sequences reported for each gene between the years 1995 and 2024.

Fig. 2.. Evolution and characteristics of GII.4 norovirus variants that emerged since 1995. (a) Phylogenetic relationship of GII.4 variants inferred using VP1 amino acid sequences through a maximum likelihood method using mega v11 [111]. Each colour on the branch denotes a different GII.4 variants that emerged at different time points. Representative viruses from each variant were used to construct the tree [GenBank accessions: ancestral (JX023286), Camberwell (AY032605), Grimsby (AJ004864), Farmington Hills (DQ658413), Hunter (EU078414), Sakai (AB220922), Yerseke (EF126963), Den Haag (EF126965), Osaka (AB434770), Apeldoorn (AB541274), New Orleans (KX353958), Sydney (KY424328), Hong Kong (MN400355) and San Francisco (MW506849)]. (b) The top line graph indicates the number of GII.4 norovirus sequences reported between the years 1995–2024 (n=16,826). The bottom area plot indicates the temporal trend of GII.4 variants as represented by the ratio (%) per year. The colour of the area follows the colour palette of each variant in panel a. Classification of the GII.4 variants was determined by the Norovirus Typing Tool [110]. (c) Two-dimensional antigenic cartography of GII.4 variants confirmed the antigenic diversity among chronologically emerged GII.4 variants. Each unit of the grid represents a twofold difference of HBGA-blockade EC₅₀ titers. The antigenic map was created using previously published blockade EC₅₀ titers of sera collected from VLP-immunized mice [4277] and the Racmacs package in R v4.2 [112]. (d) The heatmaps show the temporal prevalence of polymerase types from different GII.4 variants. Variants presenting the same polymerase types are grouped within the same heatmaps.

Fig. 3.. Evolution and characteristics of GII.17 norovirus variants detected in humans. (a) Phylogenetic relationship of GII.17 noroviruses inferred using VP1 amino acid sequences through a maximum-likelihood method using mega v11 [111]. Each colour on the branch denotes different clusters of GII.17 noroviruses; cluster A represented by CS-E1/2002 (blue), cluster B represented by Katrina/2005 (green), cluster C represented by Kawasaki323/2014 (orange), cluster D represented by Kawasaki308/2015 (purple) and a recently emerged new cluster represented by Romania/2021 (red). (b) The top solid line graph indicates the number of GII.17 norovirus sequences reported between the years 2010–2024 (n=2,381). As GII.17 clusters were not able to be appropriately classified using short partial genomes (e.g. ~300 nt of conserved shell domain), VP1 sequences with ≥1,000 nt were retrieved (n=974) and subjected to phylogenetic analysis to classify the viruses into the clusters. Thus, the dotted line in the graph summarizes the number of sequences with ≥1,000 nt, which reflects the overall temporal trend of GII.17 sequence reports as shown by the solid line. The bottom area plot indicates the temporal trend of GII.17 clusters as determined using ≥1,000 nt-length VP1 sequences. The colour of the area follows the colour palette of each cluster in panel A. (c) Multidimensional scaling analysis of VP1 amino acid sequences used in the tree (panel a) suggests different antigenic profiles of GII.17 clusters, while the newly emerged cluster was closely located to cluster C viruses with 10–15 amino acid mutations. (d) GII.17 clusters presented different HBGA-binding patterns as measured by ELISA. The binding data of VLPs and HBGA molecules in saliva from individuals with different blood types (O, A, B, AB, NS; non-secretor) were extracted from a previous study [72]. (e) The heatmaps show the temporal prevalence of polymerase types from different GII.17 clusters.

Fig. 4.. Norovirus outbreaks are likely driven by a combination of host and viral factors. Following initial infections, the population develops immunity (indicated by the black solid line), leading to a decline in subsequent infections over time and contributing to herd immunity. However, the number of viral infections in the population (indicated by the grey dotted line) could be influenced by factors such as the birth of new individuals (or the replenishment of a naïve population) or the waning of antibody responses from primary infections. To accelerate reinfection rates, norovirus may (i) undergo antigenic diversification, allowing it to escape pre-existing immunity; (ii) alter its binding profile to HBGA attachment factors, increasing susceptibility across a broader population; and (iii) enhance viral load through mechanisms such as increased RNA replication, improved entry or innate immune antagonism. These factors – whether individually or in combination – can drive the emergence of new strains and accelerate reinfection, even in the presence of prior immunity.