Computational Methods to Study Human Transcript Variants in COVID-19 Infected Lung Cancer Cells

All differential on the splicing front: Host alternative splicing alters the landscape of virus-host conflict

Alternative RNA splicing is a co-transcriptional process that richly increases proteome diversity, and is dynamically regulated based on cell species, lineage, and activation state. Virus infection in vertebrate hosts results in rapid host transcriptome-wide changes, and regulation of alternative splicing can direct a combinatorial effect on the host transcriptome. There has been a recent increase in genome-wide studies evaluating host alternative splicing during viral infection, which integrates well with prior knowledge on viral interactions with host splicing proteins. A critical challenge remains in linking how these individual events direct global changes, and whether alternative splicing is an overall favorable pathway for fending off or supporting viral infection. Here, we introduce the process of alternative splicing, discuss how to analyze splice regulation, and detail studies on genome-wide and splice factor changes during viral infection. We seek to highlight where the field can focus on moving forward, and how incorporation of a virus-host co-evolutionary perspective can benefit this burgeoning subject.

An L-theanine derivative targets against SARS-CoV-2 and its Delta and Omicron variants

Recent research efforts have shown that tea has activities against SARS-CoV-2. However, the active compounds and the action mechanisms are largely unknown. Here we study the inhibitory potential of L-theanine from tea and its semi-synthesized derivative, a small-molecule fluorescent compound, ethyl 6-bromocoumarin-3-carboxylyl L-theanine (TBrC) against infection and replication of SARS-CoV-2 and the underlying mechanisms of action. We reveal that TBrC has potential activities against SARS-CoV-2 in addition to its activity against lung cancer. TBrC showed extracellular inhibition of SARS-CoV-2 M^pro/3CL and the host cell receptor ACE2 while interacting with the viral spike glycoproteins (wild-type, Delta, and Omicron mutants). Moreover, TBrC and L-theanine significantly suppressed growth and TNFα-induced nuclear transcriptional activation of NF-κB in human lung cancer cells without affecting the viability of normal lung cells, suggesting a potential protection of TBrC and L-theanine from pulmonary damages in SARS-CoV-2 infected patients, especially for lung cancer patients with SARS-CoV-2 infection.

Differential Co-Expression Network Analysis Reveals Key Hub-High Traffic Genes as Potential Therapeutic Targets for COVID-19 Pandemic

Background

The recent emergence of COVID-19, rapid worldwide spread, and incomplete knowledge of molecular mechanisms underlying SARS-CoV-2 infection have limited development of therapeutic strategies. Our objective was to systematically investigate molecular regulatory mechanisms of COVID-19, using a combination of high throughput RNA-sequencing-based transcriptomics and systems biology approaches.

Methods

RNA-Seq data from peripheral blood mononuclear cells (PBMCs) of healthy persons, mild and severe 17 COVID-19 patients were analyzed to generate a gene expression matrix. Weighted gene co-expression network analysis (WGCNA) was used to identify co-expression modules in healthy samples as a reference set. For differential co-expression network analysis, module preservation and module-trait relationships approaches were used to identify key modules. Then, protein-protein interaction (PPI) networks, based on co-expressed hub genes, were constructed to identify hub genes/TFs with the highest information transfer (hub-high traffic genes) within candidate modules.

Results

Based on differential co-expression network analysis, connectivity patterns and network density, 72% (15 of 21) of modules identified in healthy samples were altered by SARS-CoV-2 infection. Therefore, SARS-CoV-2 caused systemic perturbations in host biological gene networks. In functional enrichment analysis, among 15 non-preserved modules and two significant highly-correlated modules (identified by MTRs), 9 modules were directly related to the host immune response and COVID-19 immunopathogenesis. Intriguingly, systemic investigation of SARS-CoV-2 infection identified signaling pathways and key genes/proteins associated with COVID-19's main hallmarks, e.g., cytokine storm, respiratory distress syndrome (ARDS), acute lung injury (ALI), lymphopenia, coagulation disorders, thrombosis, and pregnancy complications, as well as comorbidities associated with COVID-19, e.g., asthma, diabetic complications, cardiovascular diseases (CVDs), liver disorders and acute kidney injury (AKI). Topological analysis with betweenness centrality (BC) identified 290 hub-high traffic genes, central in both co-expression and PPI networks. We also identified several transcriptional regulatory factors, including NFKB1, HIF1A, AHR, and TP53, with important immunoregulatory roles in SARS-CoV-2 infection. Moreover, several hub-high traffic genes, including IL6, IL1B, IL10, TNF, SOCS1, SOCS3, ICAM1, PTEN, RHOA, GDI2, SUMO1, CASP1, IRAK3, HSPA5, ADRB2, PRF1, GZMB, OASL, CCL5, HSP90AA1, HSPD1, IFNG, MAPK1, RAB5A, and TNFRSF1A had the highest rates of information transfer in 9 candidate modules and central roles in COVID-19 immunopathogenesis.

Conclusion

This study provides comprehensive information on molecular mechanisms of SARS-CoV-2-host interactions and identifies several hub-high traffic genes as promising therapeutic targets for the COVID-19 pandemic.