1887

Abstract

To date, little is known about the effect of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for the coronavirus disease 2019 (COVID-19) pandemic, on the upper respiratory tract (URT) microbiota over time. To fill this knowledge gap, we used 16S ribosomal RNA gene sequencing to characterize the URT microbiota in 48 adults, including (1) 24 participants with mild-to-moderate COVID-19 who had serial mid-turbinate swabs collected up to 21 days after enrolment and (2) 24 asymptomatic, uninfected controls who had mid-turbinate swabs collected at enrolment only. To compare the URT microbiota between groups in a comprehensive manner, different types of statistical analyses that are frequently employed in microbial ecology were used, including ⍺-diversity, β-diversity and differential abundance analyses. Final statistical models included age, sex and the presence of at least one comorbidity as covariates. The median age of all participants was 34.00 (interquartile range=28.75–46.50) years. In comparison to samples from controls, those from participants with COVID-19 had a lower observed species index at day 21 (linear regression coefficient=−13.30; 95 % CI=−21.72 to −4.88; =0.02). In addition, the Jaccard index was significantly different between samples from participants with COVID-19 and those from controls at all study time points (PERMANOVA <0.05 for all comparisons). The abundance of three amplicon sequence variants (ASVs) (one ASV, , and one ASV) were decreased in samples from participants with COVID-19 at all seven study time points, whereas the abundance of one ASV (from the family ) was increased in samples from participants with COVID-19 at five (71.43 %) of the seven study time points. Our results suggest that mild-to-moderate COVID-19 can lead to alterations of the URT microbiota that persist for several weeks after the initial infection.

Funding
This study was supported by the:
  • National Heart, Lung, and Blood Institute (Award K23HL148638)
    • Principle Award Recipient: ChristianRosas-Salazar
  • Division of Microbiology and Infectious Diseases, National Institute of Allergy and Infectious Diseases (Award R21AI149262)
    • Principle Award Recipient: SumanRanjan Das
  • Division of Microbiology and Infectious Diseases, National Institute of Allergy and Infectious Diseases (Award R21AI154016)
    • Principle Award Recipient: SumanRanjan Das
  • Centers for Disease Control and Prevention (Award 75D3012110094)
    • Principle Award Recipient: SumanRanjan Das
  • Division of Microbiology and Infectious Diseases, National Institute of Allergy and Infectious Diseases (Award R21AI142321)
    • Principle Award Recipient: DasSuman RanjanRosas-SalazarChristian
  • 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.0.000957
2023-02-23
2024-04-23
Loading full text...

Full text loading...

/deliver/fulltext/mgen/9/2/mgen000957.html?itemId=/content/journal/mgen/10.1099/mgen.0.000957&mimeType=html&fmt=ahah

References

  1. Man WH, de Steenhuijsen Piters WAA, Bogaert D. The microbiota of the respiratory tract: gatekeeper to respiratory health. Nat Rev Microbiol 2017; 15:259–270 [View Article] [PubMed]
    [Google Scholar]
  2. Bosch A, de Steenhuijsen Piters WAA, van Houten MA, Chu M, Biesbroek G et al. Maturation of the infant respiratory microbiota, environmental drivers, and health consequences. A prospective cohort study. Am J Respir Crit Care Med 2017; 196:1582–1590 [View Article]
    [Google Scholar]
  3. Petersen C, Round JL. Defining dysbiosis and its influence on host immunity and disease. Cell Microbiol 2014; 16:1024–1033 [View Article] [PubMed]
    [Google Scholar]
  4. Rosas-Salazar C, Shilts MH, Tovchigrechko A, Chappell JD, Larkin EK et al. Nasopharyngeal microbiome in respiratory syncytial virus resembles profile associated with increased childhood Asthma risk. Am J Respir Crit Care Med 2016; 193:1180–1183 [View Article]
    [Google Scholar]
  5. Rosas-Salazar C, Shilts MH, Tovchigrechko A, Schobel S, Chappell JD et al. Differences in the nasopharyngeal microbiome during acute respiratory tract infection with human rhinovirus and respiratory syncytial virus in infancy. J Infect Dis 2016; 214:1924–1928 [View Article]
    [Google Scholar]
  6. Allen EK, Koeppel AF, Hendley JO, Turner SD, Winther B et al. Characterization of the nasopharyngeal microbiota in health and during rhinovirus challenge. Microbiome 2014; 2:22 [View Article] [PubMed]
    [Google Scholar]
  7. Kaul D, Rathnasinghe R, Ferres M, Tan GS, Barrera A et al. Microbiome disturbance and resilience dynamics of the upper respiratory tract during influenza A virus infection. Nat Commun 2020; 11:2537 [View Article]
    [Google Scholar]
  8. Ederveen THA, Ferwerda G, Ahout IM, Vissers M, de Groot R et al. Haemophilus is overrepresented in the nasopharynx of infants hospitalized with RSV infection and associated with increased viral load and enhanced mucosal CXCL8 responses. Microbiome 2018; 6:10 [View Article]
    [Google Scholar]
  9. de Steenhuijsen Piters WAA, Heinonen S, Hasrat R, Bunsow E, Smith B et al. Nasopharyngeal microbiota, host transcriptome, and disease severity in children with respiratory syncytial virus infection. Am J Respir Crit Care Med 2016; 194:1104–1115 [View Article]
    [Google Scholar]
  10. Rosas-Salazar C, Tang Z-Z, Shilts MH, Turi KN, Hong Q et al. Upper respiratory tract bacterial-immune interactions during respiratory syncytial virus infection in infancy. J Allergy Clin Immunol 2022; 149:966–976 [View Article]
    [Google Scholar]
  11. Rosas-Salazar C, Shilts MH, Tovchigrechko A, Schobel S, Chappell JD et al. Nasopharyngeal Lactobacillus is associated with a reduced risk of childhood wheezing illnesses following acute respiratory syncytial virus infection in infancy. J Allergy Clin Immunol 2018; 142:1447–1456 [View Article]
    [Google Scholar]
  12. Dumas O, Hasegawa K, Mansbach JM, Sullivan AF, Piedra PA et al. Severe bronchiolitis profiles and risk of recurrent wheeze by age 3 years. J Allergy Clin Immunol 2019; 143:1371–1379 [View Article]
    [Google Scholar]
  13. Raita Y, Pérez-Losada M, Freishtat RJ, Harmon B, Mansbach JM et al. Integrated omics endotyping of infants with respiratory syncytial virus bronchiolitis and risk of childhood asthma. Nat Commun 2021; 12:3601 [View Article]
    [Google Scholar]
  14. Kimura KS, Freeman MH, Wessinger BC, Gupta V, Sheng Q et al. Interim analysis of an open-label randomized controlled trial evaluating nasal irrigations in non-hospitalized patients with coronavirus disease 2019. Int Forum Allergy Rhinol 2020; 10:1325–1328 [View Article]
    [Google Scholar]
  15. Esther CR, Kimura KS, Mikami Y, Edwards CE, Das SR et al. Pharmacokinetic-based failure of a detergent virucidal for severe acute respiratory syndrome-coronavirus-2 (SARS-COV-2) nasal infections: a preclinical study and randomized controlled trial. Int Forum Allergy Rhinol 2022; 12:1137–1147 [View Article]
    [Google Scholar]
  16. Rosas-Salazar C, Kimura KS, Shilts MH, Strickland BA, Freeman MH et al. SARS-CoV-2 infection and viral load are associated with the upper respiratory tract microbiome. J Allergy Clin Immunol 2021; 147:1226–1233 [View Article]
    [Google Scholar]
  17. World Health Organization Operational considerations for case management of COVID-19 in health facility and community. Interim guidance. Pediatr Med Rodz 2020; 16:27–32 [View Article]
    [Google Scholar]
  18. Singh K, Gobert AP, Coburn LA, Barry DP, Allaman M et al. Dietary arginine regulates severity of experimental colitis and affects the colonic microbiome. Front Cell Infect Microbiol 2019; 9:66 [View Article]
    [Google Scholar]
  19. Hiremath G, Shilts MH, Boone HH, Correa H, Acra S et al. The salivary microbiome is altered in children with Eosinophilic Esophagitis and correlates with disease activity. Clin Transl Gastroenterol 2019; 10:e00039 [View Article]
    [Google Scholar]
  20. Kozich JJ, Westcott SL, Baxter NT, Highlander SK, Schloss PD. Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform. Appl Environ Microbiol 2013; 79:5112–5120 [View Article]
    [Google Scholar]
  21. Shilts MH, Rosas-Salazar C, Strickland BA, Kimura KS, Asad M et al. Severe COVID-19 is associated with an altered upper respiratory tract microbiome. Front Cell Infect Microbiol 2021; 11:781968 [View Article]
    [Google Scholar]
  22. Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA et al. DADA2: High-resolution sample inference from Illumina amplicon data. Nat Methods 2016; 13:581–583 [View Article] [PubMed]
    [Google Scholar]
  23. Pruesse E, Quast C, Knittel K, Fuchs BM, Ludwig W et al. SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB. Nucleic Acids Res 2007; 35:7188–7196 [View Article] [PubMed]
    [Google Scholar]
  24. Davis NM, Proctor DM, Holmes SP, Relman DA, Callahan BJ. Simple statistical identification and removal of contaminant sequences in marker-gene and metagenomics data. Microbiome 2018; 6:226 [View Article]
    [Google Scholar]
  25. McMurdie PJ, Holmes S. phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS One 2013; 8:e61217 [View Article]
    [Google Scholar]
  26. Weiss S, Xu ZZ, Peddada S, Amir A, Bittinger K et al. Normalization and microbial differential abundance strategies depend upon data characteristics. Microbiome 2017; 5:27 [View Article]
    [Google Scholar]
  27. R Development Core Team R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2006 http://www.R-project.org/
  28. Anderson MJ. A new method for non-parametric multivariate analysis of variance. Austral Ecol 2001; 26:32–46 [View Article]
    [Google Scholar]
  29. Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 2014; 15:550 [View Article] [PubMed]
    [Google Scholar]
  30. Shields-Cutler RR, Al-Ghalith GA, Yassour M, Knights D. SplinectomeR enables group comparisons in longitudinal microbiome studies. Front Microbiol 2018; 9:785 [View Article]
    [Google Scholar]
  31. Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc: Series B 1995; 57:289–300 [View Article]
    [Google Scholar]
  32. McGinnis S, Madden TL. BLAST: at the core of a powerful and diverse set of sequence analysis tools. Nucleic Acids Res 2004; 32:W20–5 [View Article] [PubMed]
    [Google Scholar]
  33. Zaneveld JR, McMinds R, Vega Thurber R. Stress and stability: applying the Anna Karenina principle to animal microbiomes. Nat Microbiol 2017; 2:17121 [View Article] [PubMed]
    [Google Scholar]
  34. Qi L, Yang Y, Jiang D, Tu C, Wan L et al. Factors associated with the duration of viral shedding in adults with COVID-19 outside of Wuhan, China: a retrospective cohort study. Int J Infect Dis 2020; 96:531–537 [View Article] [PubMed]
    [Google Scholar]
  35. World Health Organization Criteria for releasing COVID-19 patients from isolation: scientific brief World Health Organization; 2020
    [Google Scholar]
  36. Wagner Mackenzie B, Chang K, Zoing M, Jain R, Hoggard M et al. Longitudinal study of the bacterial and fungal microbiota in the human sinuses reveals seasonal and annual changes in diversity. Sci Rep 2019; 9:17416 [View Article]
    [Google Scholar]
  37. Frank DN, Feazel LM, Bessesen MT, Price CS, Janoff EN et al. The human nasal microbiota and Staphylococcus aureus carriage. PLoS One 2010; 5:e10598 [View Article]
    [Google Scholar]
  38. Costello EK, Lauber CL, Hamady M, Fierer N, Gordon JI et al. Bacterial community variation in human body habitats across space and time. Science 2009; 326:1694–1697 [View Article] [PubMed]
    [Google Scholar]
  39. Camarinha-Silva A, Jáuregui R, Pieper DH, Wos-Oxley ML. The temporal dynamics of bacterial communities across human anterior nares. Environ Microbiol Rep 2012; 4:126–132 [View Article] [PubMed]
    [Google Scholar]
  40. McCullers JA. Insights into the interaction between influenza virus and pneumococcus. Clin Microbiol Rev 2006; 19:571–582 [View Article] [PubMed]
    [Google Scholar]
  41. Hanada S, Pirzadeh M, Carver KY, Deng JC. Respiratory viral infection-induced microbiome alterations and secondary bacterial Pneumonia. Front Immunol 2018; 9:2640 [View Article]
    [Google Scholar]
  42. Merenstein C, Liang G, Whiteside SA, Cobián-Güemes AG, Merlino MS et al. Signatures of COVID-19 severity and immune response in the respiratory tract microbiome. mBio 2021; 12:e0177721 [View Article]
    [Google Scholar]
  43. Ren L, Wang Y, Zhong J, Li X, Xiao Y et al. Dynamics of the upper respiratory tract microbiota and its association with mortality in COVID-19. Am J Respir Crit Care Med 2021; 204:1379–1390 [View Article]
    [Google Scholar]
  44. Xu R, Lu R, Zhang T, Wu Q, Cai W et al. Temporal association between human upper respiratory and gut bacterial microbiomes during the course of COVID-19 in adults. Commun Biol 2021; 4:240 [View Article]
    [Google Scholar]
  45. Lloréns-Rico V, Gregory AC, Van Weyenbergh J, Jansen S, Van Buyten T et al. Clinical practices underlie COVID-19 patient respiratory microbiome composition and its interactions with the host. Nat Commun 2021; 12:6243 [View Article]
    [Google Scholar]
  46. Sulaiman I, Chung M, Angel L, Tsay J-CJ, Wu BG et al. Microbial signatures in the lower airways of mechanically ventilated COVID-19 patients associated with poor clinical outcome. Nat Microbiol 2021; 6:1245–1258 [View Article] [PubMed]
    [Google Scholar]
http://instance.metastore.ingenta.com/content/journal/mgen/10.1099/mgen.0.000957
Loading
/content/journal/mgen/10.1099/mgen.0.000957
Loading

Data & Media loading...

Supplements

Supplementary material 1

PDF
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