Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2025 Feb 4;231(1):e154-e164.
doi: 10.1093/infdis/jiae347.

Genomic Epidemiology and Evolution of Rhinovirus in Western Washington State, 2021-2022

Stephanie Goya  1 , Seffir T Wendm  1 , Hong Xie  1 , Tien V Nguyen  1 , Sarina Barnes  1 , Rohit R Shankar  1 , Jaydee Sereewit  1 , Kurtis Cruz  1 , Ailyn C Pérez-Osorio  1 , Margaret G Mills  1 , Alexander L Greninger  1   2
Affiliations

Genomic Epidemiology and Evolution of Rhinovirus in Western Washington State, 2021-2022

Stephanie Goya et al. J Infect Dis. .

Abstract

Background: Human rhinoviruses (RVs) primarily cause the common cold, but infection outcomes vary from subclinical to severe cases, including asthma exacerbations and fatal pneumonia in individuals who are immunocompromised. To date, therapeutic strategies have been hindered by the high diversity of serotypes. Global surveillance efforts have traditionally focused on sequencing VP1 or VP2/VP4 genetic regions, leaving gaps in our understanding of RV genomic diversity.

Methods: We sequenced 1078 RV genomes from nasal swabs of symptomatic and asymptomatic individuals to explore viral evolution during 2 epidemiologically distinct periods in Washington State: when the COVID-19 pandemic affected the circulation of other seasonal respiratory viruses except for RV (February-July 2021) and when the seasonal viruses reemerged with the severe outbreak of respiratory syncytial virus and influenza (November-December 2022). We constructed maximum likelihood and BEAST phylodynamic trees to characterize intragenotype evolution.

Results: We detected 99 of 168 known genotypes and observed intergenotypic recombination and genotype cluster swapping from 2021 to 2022. We found a significant association between the presence of symptoms and viral load but not with RV species or genotype. Phylodynamic trees, polyprotein selection pressure, and Shannon entropy revealed cocirculation of divergent clades within genotypes with high amino acid constraints throughout the polyprotein.

Conclusions: Our study underscores the dynamic nature of RV genomic epidemiology within a localized geographic region, as >20% of existing genotypes within each RV species cocirculated each studied month. Our findings also emphasize the importance of investigating correlations between RV genotypes and serotypes to understand long-term immunity and cross-protection.

Keywords: VP1; Washington; genomic epidemiology; rhinovirus; viral evolution.

PubMed Disclaimer

Conflict of interest statement

Potential conflict of interest. A. L. G. reports contract testing from Abbott, Cepheid, Novavax, Pfizer, Janssen, and Hologic and research support from Gilead outside the described work. All other authors report no potential conflict of interest. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed.

Figures

Figure 1.
Figure 1.
Rhinovirus infections and relationship with age group and symptom presence. The association of age, presence of respiratory symptoms, and Ct value was evaluated. Violin plots illustrate the distribution of cases for (A) Ct value and stratified age group, (B) Ct value and symptom presence, and (C) nonstratified age and symptom presence. Black dots represent individuals. Within the violin plot, a box plot shows the median, IQR, and 95% CI. A Kruskal-Wallis test was used to assess the association between variables and a Wilcoxon test for the age group pairwise analysis. ***P < .0001. **P < .001. D, Binomial logistic regression of symptom presence considering the effect of the Ct value and age group. The plot shows the probability model of an individual being asymptomatic for each age group. Shadows around the main line indicate 95% CI. Ct, cycle threshold.
Figure 2.
Figure 2.
Abundance of rhinovirus (RV) species and genotypes within the sequenced genomes. The stacked bar plot shows the proportion of (A) RV species, (B) genotypes within RV-A, (C) genotypes within RV-B, and (D) genotypes within RV-C by studied month. For genotype bar plots, the total number of genomes per month is detailed above each column.
Figure 3.
Figure 3.
Geographic spread of rhinovirus (RV) species in Puget Sound region. For each studied month, the proportion of RV species (RV-A, pink; RV-B, green; RV-C, blue) is mapped according to the UW Medicine COVID-19 community testing sites where the individuals attended. The total number detected is shown below each pie plot. February 2021 is not shown due to the low number of cases available. A map at the bottom right highlights the geographic location of Puget Sound. UW, University of Washington.
Figure 4.
Figure 4.
Genotyping of rhinovirus (RV) detected in Washington State in 2021 and 2022. A, Seasonality of RV genotypes detected within RV-A, RV-B, and RV-C. The bubble chart details the number of cases (by size of circle) for each genotype per month of the studied period. Circle color denotes the RV species. B, Maximum likelihood tree with the VP1 nucleotide sequence of the cases studied in this work and reference sequences. Tree tips of sequences from this study are denoted with a red or light blue circle if collected in period 1 or 2, respectively. The total number of sequences in the tree is informed below the rhinovirus species. High-frequency genotypes, defined as >1% of the cases within the RV species and >10 sequences available, are highlighted orange, including the name of the genotype in italics. Scale bar indicates substitution per site.
Figure 5.
Figure 5.
Recombination between RV-A105 and RV-A21 genotypes. A, Phylogenetic clades from the maximum likelihood trees with VP-1 and 3D nucleotide sequences. Branches highlight the inferred major (dark green) and minor (violet) parents for the recombinant clade (gray). Bootstrap values of relevant nodes are indicated in the nodes. Scale bar indicates substitution per site. B, pairwise sequence identity plot among the sequences MZ542285 (A105, major parent), JN837693 (A21, minor parent), and MZ268661 (recombinant). The gray background denotes the 95% recombination breakpoint confidence interval, and the pink background highlights the region with recombinant origin. The bottom of the plot represents the parent combination and the RV genome organization following the same scale of nucleotide positions. RV, rhinovirus.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

References

    1. Hansen C, Perofsky AC, Burstein R, et al. Trends in risk factors and symptoms associated with SARS-CoV-2 and rhinovirus test positivity in king county, Washington, June 2020 to July 2022. JAMA Netw Open 2022; 5:e2245861. - PMC - PubMed
    1. Chow EJ, Casto AM, Roychoudhury P, et al. The clinical and genomic epidemiology of rhinovirus in homeless shelters—King County, Washington. J Infect Dis 2022; 226(suppl 3):S304–14. - PMC - PubMed
    1. Zlateva KT, van Rijn AL, Simmonds P, et al. Molecular epidemiology and clinical impact of rhinovirus infections in adults during three epidemic seasons in 11 European countries (2007–2010). Thorax 2020; 75:882–90. - PMC - PubMed
    1. Halabi KC, Stockwell MS, Alba L, et al. Clinical and socioeconomic burden of rhinoviruses/enteroviruses in the community. Influenza Other Respir Viruses 2022; 16:891–6. - PMC - PubMed
    1. Makhsous N, Goya S, Avendaño CC, et al. Within-host rhinovirus evolution in upper and lower respiratory tract highlights capsid variability and mutation-independent compartmentalization. J Infect Dis 2024; 229:403–12. - PMC - PubMed