Epigenetic rewiring of pathways related to odour perception in immune cells exposed to SARS-CoV-2 in vivo and in vitro

ABSTRACT

A majority of SARS-CoV-2 recoverees develop only mild-to-moderate symptoms, while some remain completely asymptomatic. Although viruses, including SARS-CoV-2, may evade host immune responses by epigenetic mechanisms including DNA methylation, little is known about whether these modifications are important in defence against and healthy recovery from COVID-19 in the host. To this end, epigenome-wide DNA methylation patterns from COVID-19 convalescents were compared to uninfected controls from before and after the pandemic. Peripheral blood mononuclear cell (PBMC) DNA was extracted from uninfected controls, COVID-19 convalescents, and symptom-free individuals with SARS-CoV-2-specific T cell-responses, as well as from PBMCs stimulated in vitro with SARS-CoV-2. Subsequently, the Illumina MethylationEPIC 850K array was performed, and statistical/bioinformatic analyses comprised differential DNA methylation, pathway over-representation, and module identification analyses. Differential DNA methylation patterns distinguished COVID-19 convalescents from uninfected controls, with similar results in an experimental SARS-CoV-2 infection model. A SARS-CoV-2-induced module was identified in vivo, comprising 66 genes of which six (TP53, INS, HSPA4, SP1, ESR1, and FAS) were present in corresponding in vitro analyses. Over-representation analyses revealed involvement in Wnt, muscarinic acetylcholine receptor signalling, and gonadotropin-releasing hormone receptor pathways. Furthermore, numerous differentially methylated and network genes from both settings interacted with the SARS-CoV-2 interactome. Altered DNA methylation patterns of COVID-19 convalescents suggest recovery from mild-to-moderate SARS-CoV-2 infection leaves longstanding epigenetic traces. Both in vitro and in vivo exposure caused epigenetic modulation of pathways thataffect odour perception. Future studies should determine whether this reflects host-induced protective antiviral defense or targeted viral hijacking to evade host defence.

KEYWORDS:

• SARS-CoV-2
• mild-to-moderate
• PBMC
• DNA methylation
• in vitro stimulation
• module identification
• network analysis
• interactome

Acknowledgments

We would like to thank the Bioinformatics and Expression analysis Core facility at Karolinska Institutet for their fruitful collaboration and the performance of the Illumina Infinium MethylationEPIC 850K arrays described in this paper. Additionally, we acknowledge the Swedish National Infrastructure for Computing (SNIC) at the National Supercomputing Centre (NSC), Linköping University for the computing systems enabling the data handling, partially funded by the Swedish Research Council (Grant No. 2018-05973).

Author contributions

Conceptualization: M.L. – equal, A.R. - equal, Data curation: S.Sa. – lead, J.D. – support, J.H. – support, Formal analysis: S.Sa. – lead, J.D. – support, L.K. – support, L.P. – support, J.H. – support, Funding acquisition: M.L. – equal, A.R. – equal, Investigation: E.A. – equal, M.R. – equal (ELISpot/SMIA), M.L. – equal, L.K. – equal, S.Sh. – support (in vitro SARS-CoV-2 stimulation of PBMCs), L.K. – lead (DNA extraction of PBMC samples), Methodology: M.L. – equal, L.K. – equal, A.R. – equal, E.A. – equal, M.R. – equal, Project administration: M.L. - equal, A.R. – equal, J.H. – equal, S. Sa. – equal, Resources: A.R. – equal, M.L. - equal, Software: S.Sa. - lead, J.D. – support, L.K. – support, L.P. – support, Supervision: M.L. - equal, A.R. – equal, J.H. – equal, S.Sa. – equal, Validation: Not applicable, Visualization: S.Sa. – equal, J.H. - equal, L.K. – support, J.D. – support, L.P. – support, Writing – original draft: J.H. – lead, all other authors - support, Writing – review and editing: J.H. – lead, all other authors – support.

Data availability statement

The datasets used and/or analysed in the presented work will be available upon publication on GeneExpression Omnibus, due to a pending patent application. The datasets comprise filtered and preprocessed DNA methylation data from deidentified individual samples in the study. The dataset will until publication be available using a secure token, provided by the authors upon request. Please, refer to GEO-ID: GSE178962 for further information on the data set.

Utilized scripts for performing the described statistical analyses within the paper, as well as for creating graphs, will be available on the following GitHub account upon publication (https://github.com/Lerm-Lab/Covid19).

Disclosure statement

M.L., S.Sa., and J.D. have prepared and filed a patent based on the findings from the present study. None of the remaining authors declare any competing interests.

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/15592294.2022.2089471

Additional information

Funding

This work was supported by the Swedish Heart and Lung Foundation under grants 20200319, 20200067, and 20210067 (M.L.); the Swedish Research Council under grant Covid-19/biobank 210202#1 (A.R.) and the Open Medicine foundation under grant OMF190626 (A.R.); Hjärt-Lungfonden; Open Medicine Foundation; Vetenskapsrådet.