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. 2023 Apr 13;18(4):e0283589.
doi: 10.1371/journal.pone.0283589. eCollection 2023.

Mapping CircRNA-miRNA-mRNA regulatory axis identifies hsa_circ_0080942 and hsa_circ_0080135 as a potential theranostic agents for SARS-CoV-2 infection

Hassan Ayaz  1 , Nouman Aslam  1 , Faryal Mehwish Awan  1 , Rabea Basri  1 , Bisma Rauff  2 , Badr Alzahrani  3 , Muhammad Arif  1 , Aqsa Ikram  4 , Ayesha Obaid  1 , Anam Naz  4 , Sadiq Noor Khan  1 , Burton B Yang  5   6   7 , Azhar Nazir  1
Affiliations

Mapping CircRNA-miRNA-mRNA regulatory axis identifies hsa_circ_0080942 and hsa_circ_0080135 as a potential theranostic agents for SARS-CoV-2 infection

Hassan Ayaz et al. PLoS One. .

Abstract

Non-coding RNAs (ncRNAs) can control the flux of genetic information; affect RNA stability and play crucial roles in mediating epigenetic modifications. A number of studies have highlighted the potential roles of both virus-encoded and host-encoded ncRNAs in viral infections, transmission and therapeutics. However, the role of an emerging type of non-coding transcript, circular RNA (circRNA) in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has not been fully elucidated so far. Moreover, the potential pathogenic role of circRNA-miRNA-mRNA regulatory axis has not been fully explored as yet. The current study aimed to holistically map the regulatory networks driven by SARS-CoV-2 related circRNAs, miRNAs and mRNAs to uncover plausible interactions and interplay amongst them in order to explore possible therapeutic options in SARS-CoV-2 infection. Patient datasets were analyzed systematically in a unified approach to explore circRNA, miRNA, and mRNA expression profiles. CircRNA-miRNA-mRNA network was constructed based on cytokine storm related circRNAs forming a total of 165 circRNA-miRNA-mRNA pairs. This study implies the potential regulatory role of the obtained circRNA-miRNA-mRNA network and proposes that two differentially expressed circRNAs hsa_circ_0080942 and hsa_circ_0080135 might serve as a potential theranostic agents for SARS-CoV-2 infection. Collectively, the results shed light on the functional role of circRNAs as ceRNAs to sponge miRNA and regulate mRNA expression during SARS-CoV-2 infection.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Using circRNA based therapeutics to mitigate cytokine storm syndrome induced by SARS-CoV-2.
Fig 2
Fig 2. Flow chart of the approach utilized in the present study for the construction of SARS-CoV-2 related circRNA-miRNA-mRNA regulator network.
Fig 3
Fig 3. Venn diagram of overlapped differentially expressed circRNAs among circRNAs of circRNA datasets, miRNA datasets and mRNA datasets.
a) Overlapped differentially expressed circRNAs among circRNAs of circRNA datasets, miRNA datasets and mRNA datasets (whole genes). b) Overlapped differentially expressed circRNAs among circRNAs of circRNA datasets, miRNA datasets and mRNA datasets (cytokine storm related mRNAs).
Fig 4
Fig 4. The SARS-CoV-2 induced cytokine storm related circRNA-miRNA-mRNA network visualized using Cytoscape software.
The circRNA-miRNA-mRNA network contains 81 nodes and 205 edges.
Fig 5
Fig 5. Gene ontology analysis of differentially expressed genes.
Top GO terms with lowest P-values in cellular component, molecular function, and biological process were shown, respectively.
Fig 6
Fig 6. The cytoHubba plug-in in Cytoscape was used to search the list of top 10 genes from the PPI network with node degrees indicating hub differentially expressed genes, including STAT1, RSAD2, IFIT1, IFIT3, IFIT2, DDX58, OAS2, MX2, IFI44 and IFI44L.
Fig 7
Fig 7. Pathway analysis of COVID-19 pathogenesis (KEGG pathway ID: map05171).
Highlighted genes are targets of miRNAs and indirect targets of two prioritized circRNAs.
See this image and copyright information in PMC

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