1887

Abstract

Novel variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continue to emerge as the coronavirus disease 2019 (COVID-19) pandemic extends into its fourth year. Understanding SARS-CoV-2 circulation in university populations is vital for effective interventions in higher education settings and will inform public health policy during pandemics. In this study, we performed whole-genome sequencing of 537 of 1717 SARS-CoV-2-positive nasopharyngeal/nasal swab samples collected over a nearly 20-month period from two university populations in Wisconsin, USA. We observed that the viral sequences were distributed into 57 lineages/sub-lineages belonging to 15 clades, of which the majority were from 21K (omicron, 36.13 %) and 21J (delta, 30.91 %). Nearly 40 % (213) of the sequences were omicron, of which BA.1 and its eight descendent lineages accounted for 91 %, while the remaining belonged to BA.2 and its six descendent lineages. Independent analysis of the sequences from these two universities revealed significant differences in the circulating SARS-CoV-2 variants. Phylogenetic analysis of university sequences with a global sub-dataset demonstrated that the sequences of the same lineages from the university populations were more closely related. Genome-based analysis of closely related strains, along with phylogenetic clusters and mutational differences, identified that potential virus transmission occurred within and between universities, as well as between the university and the local community. Although this study improves our understanding of the distinct transmission patterns of circulating variants in local universities, expanding genomic surveillance capacity will aid local jurisdictions not only in identifying emerging SARS-CoV-2 variants, but also in improving data-driven public health mitigation and policy efforts.

  • This is an open-access article distributed under the terms of the Creative Commons Attribution NonCommercial License.
Loading

Article metrics loading...

/content/journal/mgen/10.1099/mgen.0.000970
2023-03-31
2024-04-26
Loading full text...

Full text loading...

/deliver/fulltext/mgen/9/3/mgen000970.html?itemId=/content/journal/mgen/10.1099/mgen.0.000970&mimeType=html&fmt=ahah

References

  1. Huang C, Wang Y, Li X, Ren L, Zhao J et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet 2020; 395:497–506 [View Article]
    [Google Scholar]
  2. Ramaiah A, Arumugaswami V. Insights into cross-species evolution of novel human coronavirus SARS-cov-2 and defining immune determinants for vaccine development. bioRxiv 2020 [View Article]
    [Google Scholar]
  3. Aggarwal D, Page AJ, Schaefer U, Savva GM, Myers R et al. Genomic assessment of quarantine measures to prevent SARS-CoV-2 importation and transmission. Nat Commun 2022; 13(1):1012 [View Article]
    [Google Scholar]
  4. Pray IW, Kocharian A, Mason J, Westergaard R, Meiman J. Trends in outbreak-associated cases of COVID-19 - Wisconsin, March-November 2020. MMWR Morb Mortal Wkly Rep 2021; 70:114–117 [View Article]
    [Google Scholar]
  5. Fox MD, Bailey DC, Seamon MD, Miranda ML. Response to a COVID-19 outbreak on a university campus - Indiana, August 2020. MMWR Morb Mortal Wkly Rep 2021; 70:118–122 [View Article]
    [Google Scholar]
  6. Vang KE, Krow-Lucal ER, James AE, Cima MJ, Kothari A et al. Participation in fraternity and sorority activities and the spread of COVID-19 among residential university communities - Arkansas, August 21-September 5, 2020. MMWR Morb Mortal Wkly Rep 2021; 70:20–23 [View Article]
    [Google Scholar]
  7. Wilson E, Donovan CV, Campbell M, Chai T, Pittman K et al. Multiple COVID-19 clusters on a university campus - North Carolina, August 2020. MMWR Morb Mortal Wkly Rep 2020; 69:1416–1418 [View Article]
    [Google Scholar]
  8. Nickbakhsh S, Hughes J, Christofidis N, Griffiths E, Shaaban S et al. Genomic epidemiology of SARS-CoV-2 in a university outbreak setting and implications for public health planning. Sci Rep 2022; 12:11735 [View Article] [PubMed]
    [Google Scholar]
  9. Hamer DH, White LF, Jenkins HE, Gill CJ, Landsberg HE et al. Assessment of a COVID-19 control plan on an urban university campus during a second wave of the pandemic. JAMA Netw Open 2021; 4:e2116425 [View Article]
    [Google Scholar]
  10. Avendano C, Lilienfeld A, Rulli L, Stephens M, Barrios WA et al. SARS-CoV-2 variant tracking and mitigation during in-person learning at a midwestern university in the 2020-2021 school year. JAMA Netw Open 2022; 5:e2146805 [View Article]
    [Google Scholar]
  11. Ciubotariu II, Dorman J, Perry NM, Gorenstein L, Kattoor JJ et al. Genomic surveillance of SARS-CoV-2 in a university community: insights into tracking variants, transmission, and spread of Gamma (P.1) variant. Open Forum Infect Dis 2022; 9:ofac268 [View Article]
    [Google Scholar]
  12. Petros BA, Turcinovic J, Welch NL, White LF, Kolaczyk ED et al. Early introduction and rise of the Omicron SARS-CoV-2 variant in highly vaccinated university populations. Clin Infect Dis 2022ciac413 [View Article]
    [Google Scholar]
  13. Valesano AL, Fitzsimmons WJ, Blair CN, Woods RJ, Gilbert J et al. SARS-CoV-2 genomic surveillance reveals little spread from a large university campus to the surrounding community. Open Forum Infect Dis 2021; 8:ofab518 [View Article]
    [Google Scholar]
  14. Education Principles for managing SARS-CoV-2 transmission associated with higher education - 3 September 2020; 2020 https://www.gov.uk/government/publications/principles-for-managing-sars-cov-2-transmission-associated-with-higher-education-3-september-2020
  15. Aggarwal D, Warne B, Jahun AS, Hamilton WL, Fieldman T et al. Genomic epidemiology of SARS-CoV-2 in a UK university identifies dynamics of transmission. Nat Commun 2022; 13:751 [View Article] [PubMed]
    [Google Scholar]
  16. Centers for Disease Control and Prevention Interim guidelines for collecting and handling of clinical specimens for COVID-19 testing. Summary of recent changes. Key points. Collecting and handling specimens safely; 2021 https://www.cdc.gov/coronavirus/2019-nCoV/lab/guidelines-clinical-specimens.html
  17. Centers for Disease Control and Prevention CDC 2019-novel corona-virus (2019-NCoV) real-time RT-PCR diagnostic panel. For emergency use only. Instructions for use; 2020 https://www.fda.gov/media/134922/download accessed 14 March 2021
  18. Centers for Disease Control and Prevention CDC influenza SARS-CoV-2 (flu SC2) multiplex assay. For emergency use only. Instructions for use; 2020 https://www.fda.gov/media/139743/download
  19. Khare S, Gurry C, Freitas L, Schultz MB, Bach G et al. GISAID’s role in pandemic response. China CDC Wkly 2021; 3:1049–1051 [View Article]
    [Google Scholar]
  20. Quick J. ARCTIC Network amplicon sequencing protocol for MinION for SARS-CoV-2 v3. https://www.protocols.io/view/ncov-2019-sequencing-protocol-v3-locost-bh42j8ye
  21. SARS-CoV-2 Sequencing on Illumina MiSeq Using ARTIC Protocol: Part 2 – Illumina DNA Flex Protocol V.1 – Joel Sevinsky, StaPH-B Consortium, Coronavirus Method Development Community. https://www.protocols.io/private/EF7D7A9B84D611EAAB080242AC110005?step=4
  22. Moreno GK, Braun KM, Riemersma KK, Martin MA, Halfmann PJ et al. Revealing fine-scale spatiotemporal differences in SARS-CoV-2 introduction and spread. Nat Commun 2020; 11:5558 [View Article] [PubMed]
    [Google Scholar]
  23. Li H. New strategies to improve minimap2 alignment accuracy. Bioinformatics 2021; 37:4572–4574 [View Article] [PubMed]
    [Google Scholar]
  24. SARS-CoV-2 Sequencing on Illumina MiSeq Using ARTIC Protocol: Part 2 - Illumina DNA Prep Protocol V.1; 2021 https://www.protocols.io/view/sars-cov-2-sequencing-on-illumina-miseq-using-arti-n92ld9w1xg5b/v1
  25. Aksamentov I, Roemer C, Hodcroft E, Neher R. Nextclade: clade assignment, mutation calling and quality control for viral genomes. J Open Source Softw 2021; 6:3773 [View Article]
    [Google Scholar]
  26. Katoh K, Rozewicki J, Yamada KD. MAFFT online service: multiple sequence alignment, interactive sequence choice and visualization. Brief Bioinform 2019; 20:1160–1166 [View Article]
    [Google Scholar]
  27. Kalyaanamoorthy S, Minh BQ, Wong TKF, von Haeseler A, Jermiin LS. ModelFinder: fast model selection for accurate phylogenetic estimates. Nat Methods 2017; 14:587–589 [View Article] [PubMed]
    [Google Scholar]
  28. Minh BQ, Schmidt HA, Chernomor O, Schrempf D, Woodhams MD et al. IQ-TREE 2: new models and efficient methods for phylogenetic inference in the genomic era. Mol Biol Evol 2020; 37:1530–1534 [View Article]
    [Google Scholar]
  29. Letunic I, Bork P. Interactive Tree Of Life (iTOL) v5: an online tool for phylogenetic tree display and annotation. Nucleic Acids Res 2021; 49:W293–W296 [View Article]
    [Google Scholar]
  30. Currie DW, Moreno GK, Delahoy MJ, Pray IW, Jovaag A et al. Interventions to disrupt coronavirus disease transmission at a university, wisconsin, USA, august-october 2020. Emerg Infect Dis 2021; 27:2776–2785 [View Article]
    [Google Scholar]
  31. Dighe H, Sarkale P, Patil DY, Mohandas S, Shete AM et al. Differential cell line susceptibility to the SARS-CoV-2 omicron BA.1.1 variant of concern. Vaccines 2022; 10:11 [View Article]
    [Google Scholar]
  32. Ai J, Wang X, He X, Zhao X, Zhang Y et al. Antibody evasion of SARS-CoV-2 Omicron BA.1, BA.1.1, BA.2, and BA.3 sub-lineages. Cell Host Microbe 2022; 30:1077–1083 [View Article] [PubMed]
    [Google Scholar]
  33. Wang Q, Guo Y, Iketani S, Nair MS, Li Z et al. Antibody evasion by SARS-CoV-2 Omicron subvariants BA.2.12.1, BA.4 and BA.5. Nature 2022; 608:603–608 [View Article] [PubMed]
    [Google Scholar]
  34. Cao Y, Yisimayi A, Jian F, Song W, Xiao T et al. BA.2.12.1, BA.4 and BA.5 escape antibodies elicited by Omicron infection. Nature 2022; 608:593–602 [View Article] [PubMed]
    [Google Scholar]
  35. Yamasoba D, Kosugi Y, Kimura I, Fujita S, Uriu K et al. Neutralisation sensitivity of SARS-CoV-2 omicron subvariants to therapeutic monoclonal antibodies. Lancet Infect Dis 2022; 22:942–943 [View Article] [PubMed]
    [Google Scholar]
  36. Chauhan D, Chakravarty N, Jeyachandran AV, Jayakarunakaran A, Sinha S et al. In silico genome analysis reveals the evolution and potential impact of SARS-CoV-2 Omicron structural changes on host immune evasion and antiviral therapeutics. Viruses 2022; 14:2461 [View Article]
    [Google Scholar]
http://instance.metastore.ingenta.com/content/journal/mgen/10.1099/mgen.0.000970
Loading
/content/journal/mgen/10.1099/mgen.0.000970
Loading

Data & Media loading...

Supplements

Supplementary material 1

PDF

Supplementary material 2

EXCEL

Supplementary material 3

EXCEL

Supplementary material 4

EXCEL
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error