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
. 2022 Jan:149:155757.
doi: 10.1016/j.cyto.2021.155757. Epub 2021 Nov 6.

In-vitro cytokine production and nasopharyngeal microbiota composition in the early stage of COVID-19 infection

Affiliations

In-vitro cytokine production and nasopharyngeal microbiota composition in the early stage of COVID-19 infection

Mehmet Hursitoglu et al. Cytokine. 2022 Jan.

Abstract

Background: To determine and compare nasopharyngeal microbiota (NM) composition, in vitro basal (Nil tube), provoked (Mitogen tube) production of cytokines at the early stage of COVID-19.

Methods: This cross-sectional study included 4 age and sex-matched study groups; group 1 (recovered COVID-19) (n = 26), group 2 (mild COVID-19) (n = 24), group 3 (severe COVID-19) (n = 25), and group 4 (healthy controls) (n = 25). The study parameters obtained from the COVID-19 (group 2, and 3) at the early phase of hospital admission.

Results: The results from the reaserch deoicted that the Mean ± SD age was 53.09 ± 14.51 years. Some of the in vitro cytokines production was significantly different between the study groups. Some of the findinggs on cytokines depicted a significant differences between study groups were interleukin (IL)-1β Nil, IL-1β Mitogen, and their subtraction (i.e Mitogen-Nil). Regarding IL-10, and IL-17a levels, Mitogen, and Mitogen-Nil tube production levels were significantly different between the groups. Surprisingly, most of these measures were lowest in the severe COVID-19 patients' group. Using discriminant analysis effect size (LEfSe), Taxa of NM with significant abundance was determined. About 20 taxa with an LDA score > 4 were identified as candidate biomarkers. Some of these taxa showed a significant correlation with IL-1β and IL-10 Mitogen and Mitogen- Nil levels (R > 0.3 or < -0.3, p < 0.05).

Conclusions: The findings of this perticular study regarting the early stage of COVID-19 showed that in vitro cytokines production, studies might be more useful than the ordinary cytokines' blood level measurement. Besides, the study identified some NM species that could be candidate biomarkers in managing this infection. However, further detailed studies are needed in these fields.

Keywords: COVID-19; Cytokine; Dysbiosis; In-vitro; Microbiota; Quantiferon test; Virus.

PubMed Disclaimer

Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
Gen copies (A), and observed species (B) plots.
Fig. 2
Fig. 2
Alpha diversity indices; Chao1 (A), Phylogenetic Diversity (PD) Whole Tree(WT) (B), and simpson (C).
Fig. 3
Fig. 3
Beta diversity analysis. Principal coordinate analysis (PCoA) based on Bray-Curtis dissimilarity, weighted (quantitative), and unweighted (qualitative) Unifrac distance metric (A,B, and C, respectively).
Fig. 4
Fig. 4
Compositional differences (at phylum level) in nasal microbiota between 4 study groups.
Fig. 5
Fig. 5
Comparison of microbiota species by Linear discriminant analysis effect size (LEfSe) tool with a p-value < 0.05 and the effect size (LDA score) > 2.
Fig. 6
Fig. 6
Correlation of microbiota taxa with in vitro cytokine production; (A) IL-1β Mitogen Nil (B) IL-1β Mitogen (C)IL-10 Mitogen (D) IL-10 Mitogen-Nil. Only significant correlations (R > 0.3 or < -0.3) are seen.The blue and shaded regions represent 95% confidence intervals (Cıs).

References

    1. Mehta D., Petes C., Gee K., Basta S. The role of virus infection in deregulating the cytokine response to secondary bacterial infection. J. Interf. Cytokine Res. 2015;35:925–934. doi: 10.1089/jir.2015.0072. - DOI - PubMed
    1. Imanishi J. Expression of cytokines in bacterial and viral infections and their biochemical aspects. J. Biochem. 2000;127:525–530. doi: 10.1093/oxfordjournals.jbchem.a022636. - DOI - PubMed
    1. Lu Q., Zhu Z., Tan C., Zhou H., Hu Y., Shen G., Zhu P., Yang G., Xie X. Changes of serum IL-10, IL-1β, IL-6, MCP-1, TNF-α, IP-10 and IL-4 in COVID-19 patients. Int. J. Clin. Pract. 2021:e14462. doi: 10.1111/ijcp.14462. - DOI - PMC - PubMed
    1. Han H., Ma Q., Li C., Liu R., Zhao L., Wang W., Zhang P., Liu X., Gao G., Liu F., Jiang Y., Cheng X., Zhu C., Xia Y. Profiling serum cytokines in COVID-19 patients reveals IL-6 and IL-10 are disease severity predictors. Emerg. Microbes Infect. 2020;9:1123–1130. doi: 10.1080/22221751.2020.1770129. - DOI - PMC - PubMed
    1. Xu X., Han M., Li T., Sun W., Wang D., Fu B., Zhou Y., Zheng X., Yang Y., Li X., Zhang X., Pan A., Wei H. Effective treatment of severe COVID-19 patients with tocilizumab. Proc. Natl. Acad. Sci. U. S. A. 2020;117:10970–10975. doi: 10.1073/pnas.2005615117. - DOI - PMC - PubMed

Publication types