m6A Regulator-Mediated Methylation Modification Patterns and Characteristics in COVID-19 Patients

Emerging role of N6-methyladenosine RNA modification in regulation of SARS-CoV-2 infection and virus-host interactions

Since December 2019, the infection caused by Severe Acute Respiratory Syndrome Coronavirus Type 2 (SARS-CoV-2) has posed an enormous threat to human health security worldwide. Constant mutation of viral genome and varying therapeutic responses of patients infected with this virus prompted efforts to uncover more novel regulators in the pathogenesis. The involvement of N6-methyladenosine, a modified form of RNA, plays a crucial role in viral replication, viral pathogenicity, and intricate signaling pathways connected with immune responses. This review discusses research advances revealing the regulation of the life cycle of SARS-CoV-2 and antiviral responses of host cells by RNA m6A modification, highlights the biological functions of N6-methyladenosine components in SARS-CoV-2 infection and virus-host interactions, and outlines current challenges and future directions for exploring the potential clinical value of m6A modification in COVID-19.

Targeting G9a translational mechanism of SARS-CoV-2 pathogenesis for multifaceted therapeutics of COVID-19 and its sequalae

By largely unknown mechanism(s), SARS-CoV-2 hijacks the host translation apparatus to promote COVID-19 pathogenesis. We report that the histone methyltransferase G9a noncanonically regulates viral hijacking of the translation machinery to bring about COVID-19 symptoms of hyperinflammation, lymphopenia, and blood coagulation. Chemoproteomic analysis of COVID-19 patient peripheral mononuclear blood cells (PBMC) identified enhanced interactions between SARS-CoV-2-upregulated G9a and distinct translation regulators, particularly the N 6 -methyladenosine (m 6 A) RNA methylase METTL3. These interactions with translation regulators implicated G9a in translational regulation of COVID-19. Inhibition of G9a activity suppressed SARS-CoV-2 replication in human alveolar epithelial cells. Accordingly, multi-omics analysis of the same alveolar cells identified SARS-CoV-2-induced changes at the transcriptional, m 6 A-epitranscriptional, translational, and post-translational (phosphorylation or secretion) levels that were reversed by inhibitor treatment. As suggested by the aforesaid chemoproteomic analysis, these multi-omics-correlated changes revealed a G9a-regulated translational mechanism of COVID-19 pathogenesis in which G9a directs translation of viral and host proteins associated with SARS-CoV-2 replication and with dysregulation of host response. Comparison of proteomic analyses of G9a inhibitor-treated, SARS-CoV-2 infected cells, or ex vivo culture of patient PBMCs, with COVID-19 patient data revealed that G9a inhibition reversed the patient proteomic landscape that correlated with COVID-19 pathology/symptoms. These data also indicated that the G9a-regulated, inhibitor-reversed, translational mechanism outperformed G9a-transcriptional suppression to ultimately determine COVID-19 pathogenesis and to define the inhibitor action, from which biomarkers of serve symptom vulnerability were mechanistically derived. This cell line-to-patient conservation of G9a-translated, COVID-19 proteome suggests that G9a inhibitors can be used to treat patients with COVID-19, particularly patients with long-lasting COVID-19 sequelae.

m6A methylation: a potential key player in understanding and treating COVID-2019 infection

Since its discovery in 2019, coronavirus disease 2019 (COVID-2019) spans a wide clinical spectrum from the asymptomatic stage, mild infection, to severe pneumonia. In patients with COVID-2019, factors such as advanced age, diabetes, or hypertension are associated with a significantly increased risk of severe diseases and death. Of note, the mechanisms underlying differences in the risk and symptoms of COVID-2019 among different populations are still poorly characterized. Accordingly, it is imperative to elucidate potential pathophysiological mechanisms and develop targeted therapeutic approaches for COVID-2019 infection. N6-methyladenosine (m6A) is one of the most common modifications in mammalian RNA transcripts and is widely found in messenger RNAs and some non-coding RNAs. It has been reported that m6A methylation modifications are present in viral RNA transcripts, which are of great significance for the regulation of the viral life cycle. Furthermore, m6A methylation has recently been found to be strongly associated with COVID-2019 infection. Therefore, this article reviews recent advances in studies related to the role of m6A methylation in COVID-2019 infection.

A Novel 3-Gene Signature for Identifying COVID-19 Patients Based on Bioinformatics and Machine Learning

Although many biomarkers associated with coronavirus disease 2019 (COVID-19) were found, a novel signature relevant to immune cells has not been developed. In this work, the “CIBERSORT” algorithm was used to assess the fraction of immune infiltrating cells in GSE152641 and GSE171110. Key modules associated with important immune cells were selected by the “WGCNA” package. The “GO” enrichment analysis was used to reveal the biological function associated with COVID-19. The “Boruta” algorithm was used to screen candidate genes, and the “LASSO” algorithm was used for collinearity reduction. A novel gene signature was developed based on multivariate logistic regression analysis. Subsequently, M0 macrophages (PRAUC = 0.948 in GSE152641 and PRAUC = 0.981 in GSE171110) and neutrophils (PRAUC = 0.892 in GSE152641 and PRAUC = 0.960 in GSE171110) were considered as important immune cells. Forty-three intersected genes from two modules were selected, which mainly participated in some immune-related activities. Finally, a three-gene signature comprising CLEC4D, DUSP13, and UNC5A that can accurately distinguish COVID-19 patients and healthy controls in three datasets was constructed. The ROCAUC was 0.974 in the training set, 0.946 in the internal test set, and 0.709 in the external test set. In conclusion, we constructed a three-gene signature to identify COVID-19, and CLEC4D, DUSP13, and UNC5A may be potential biomarkers for COVID-19 patients.