Exploring common pathogenic association between Epstein Barr virus infection and long-COVID by integrating RNA-Seq and molecular dynamics simulations

The term "Long-COVID" (LC) is characterized by the aftereffects of COVID-19 infection. Various studies have suggested that Epstein-Barr virus (EBV) reactivation is among the significant reported causes of LC. However, there is a lack of in-depth research that could largely explore the pathogenic mechanism and pinpoint the key genes in the EBV and LC context. This study mainly aimed to predict the potential disease-associated common genes between EBV reactivation and LC condition using next-generation sequencing (NGS) data and reported naturally occurring biomolecules as inhibitors. We applied the bulk RNA-Seq from LC and EBV-infected peripheral blood mononuclear cells (PBMCs), identified the differentially expressed genes (DEGs) and the Protein-Protein interaction (PPI) network using the STRING database, identified hub genes using the cytoscape plugins CytoHubba and MCODE, and performed enrichment analysis using ClueGO. The interaction analysis of a hub gene was performed against naturally occurring bioflavonoid molecules using molecular docking and the molecular dynamics (MD) simulation method. Out of 357 common genes, 22 genes (CCL2, CCL20, CDCA2, CEP55, CHI3L1, CKAP2L, DEPDC1, DIAPH3, DLGAP5, E2F8, FGF1, NEK2, PBK, TOP2A, CCL3, CXCL8, DEPDC1, IL6, RETN, MMP2, LCN2, and OLR1) were classified as hub genes, and the remaining ones were classified as neighboring genes. Enrichment analysis showed the role of hub genes in various pathways such as immune-signaling pathways, including JAK-STAT signaling, interleukin signaling, protein kinase signaling, and toll-like receptor pathways associated with the symptoms reported in the LC condition. ZNF and MYBL TF-family were predicted as abundant TFs controlling hub genes' transcriptional machinery. Furthermore, OLR1 (PDB: 7XMP) showed stable interactions with the five shortlisted refined naturally occurring bioflavonoids, i.e., apigenin, amentoflavone, ilexgenin A, myricetin, and orientin compounds. The total binding energy pattern was observed, with amentoflavone being the top docked molecule (with a binding affinity of -8.3 kcal/mol) with the lowest total binding energy of -18.48 kcal/mol. In conclusion, our research has predicted the hub genes, their molecular pathways, and the potential inhibitors between EBV and LC potential pathogenic association. The <i>in vivo</i> or <i>in vitro</i> experimental methods could be utilized to functionally validate our findings, which would be helpful to cure LC or to prevent EBV reactivation.

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Publication Details

Journal
Frontiers in Immunology
Published
2024-09-26
DOI
https://doi.org/10.3389/fimmu.2024.1435170
Citations
5
Primary Topic
Inflammasome and immune disorders
Type
article
Field-Weighted Citation Impact
1.17

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article

Exploring common pathogenic association between Epstein Barr virus infection and long-COVID by integrating RNA-Seq and molecular dynamics simulations

Ayesha Kanwal, Zhiyong Zhang
5 citations
Frontiers in Immunology
Inflammasome and immune disorders
1.17
article

Exploring common pathogenic association between Epstein Barr virus infection and long-COVID by integrating RNA-Seq and molecular dynamics simulations

Ayesha Kanwal, Zhiyong Zhang
article en
5 citations

Abstract

The term "Long-COVID" (LC) is characterized by the aftereffects of COVID-19 infection. Various studies have suggested that Epstein-Barr virus (EBV) reactivation is among the significant reported causes of LC. However, there is a lack of in-depth research that could largely explore the pathogenic mechanism and pinpoint the key genes in the EBV and LC context. This study mainly aimed to predict the potential disease-associated common genes between EBV reactivation and LC condition using next-generation sequencing (NGS) data and reported naturally occurring biomolecules as inhibitors. We applied the bulk RNA-Seq from LC and EBV-infected peripheral blood mononuclear cells (PBMCs), identified the differentially expressed genes (DEGs) and the Protein-Protein interaction (PPI) network using the STRING database, identified hub genes using the cytoscape plugins CytoHubba and MCODE, and performed enrichment analysis using ClueGO. The interaction analysis of a hub gene was performed against naturally occurring bioflavonoid molecules using molecular docking and the molecular dynamics (MD) simulation method. Out of 357 common genes, 22 genes (CCL2, CCL20, CDCA2, CEP55, CHI3L1, CKAP2L, DEPDC1, DIAPH3, DLGAP5, E2F8, FGF1, NEK2, PBK, TOP2A, CCL3, CXCL8, DEPDC1, IL6, RETN, MMP2, LCN2, and OLR1) were classified as hub genes, and the remaining ones were classified as neighboring genes. Enrichment analysis showed the role of hub genes in various pathways such as immune-signaling pathways, including JAK-STAT signaling, interleukin signaling, protein kinase signaling, and toll-like receptor pathways associated with the symptoms reported in the LC condition. ZNF and MYBL TF-family were predicted as abundant TFs controlling hub genes' transcriptional machinery. Furthermore, OLR1 (PDB: 7XMP) showed stable interactions with the five shortlisted refined naturally occurring bioflavonoids, i.e., apigenin, amentoflavone, ilexgenin A, myricetin, and orientin compounds. The total binding energy pattern was observed, with amentoflavone being the top docked molecule (with a binding affinity of -8.3 kcal/mol) with the lowest total binding energy of -18.48 kcal/mol. In conclusion, our research has predicted the hub genes, their molecular pathways, and the potential inhibitors between EBV and LC potential pathogenic association. The <i>in vivo</i> or <i>in vitro</i> experimental methods could be utilized to functionally validate our findings, which would be helpful to cure LC or to prevent EBV reactivation.

Frontiers in ImmunologyVol. 15
University of Science and Technology of China (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
Good health and well-being
Openalex Percentile: Top 22%
Inflammasome and immune disorders
1.17
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