Signaling Pathway Reporter Screen with SARS-CoV-2 Proteins Identifies nsp5 as a Repressor of p53 Activity

The diversification of methods for studying cell-cell interactions and communication

No cell lives in a vacuum, and the molecular interactions between cells define most phenotypes. Transcriptomics provides rich information to infer cell-cell interactions and communication, thus accelerating the discovery of the roles of cells within their communities. Such research relies heavily on algorithms that infer which cells are interacting and the ligands and receptors involved. Specific pressures on different research niches are driving the evolution of next-generation computational tools, enabling new conceptual opportunities and technological advances. More sophisticated algorithms now account for the heterogeneity and spatial organization of cells, multiple ligand types and intracellular signalling events, and enable the use of larger and more complex datasets, including single-cell and spatial transcriptomics. Similarly, new high-throughput experimental methods are increasing the number and resolution of interactions that can be analysed simultaneously. Here, we explore recent progress in cell-cell interaction research and highlight the diversification of the next generation of tools, which have yielded a rich ecosystem of tools for different applications and are enabling invaluable discoveries.

The nucleocapsid protein facilitates p53 ubiquitination-dependent proteasomal degradation via recruiting host ubiquitin ligase COP1 in PEDV infection

Porcine epidemic diarrhea virus (PEDV) is a highly contagious enteric pathogen of the coronavirus family and caused severe economic losses to the global swine industry. Previous studies have established that p53 is a host restriction factor for PEDV infection, and p53 degradation occurs in PEDV-infected cells. However, the underlying molecular mechanisms through which PEDV viral proteins regulate p53 degradation remain unclear. In this study, we found that PEDV infection or expression of the nucleocapsid protein downregulates p53 through a post-translational mechanism: increasing the ubiquitination of p53 and preventing its nuclear translocation. We also show that the PEDV N protein functions by recruiting the E3 ubiquitin ligase COP1 and suppressing COP1 self-ubiquitination and protein degradation, thereby augmenting COP1-mediated degradation of p53. Additionally, COP1 knockdown compromises N-mediated p53 degradation. Functional mapping using truncation analysis showed that the N-terminal domains of N protein were responsible for interacting with COP1 and critical for COP1 stability and p53 degradation. The results presented here suggest the COP1-dependent mechanism for PEDV N protein to abolish p53 activity. This study significantly increases our understanding of PEDV in antagonizing the host antiviral factor p53 and will help initiate novel antiviral strategies against PEDV.

Bioinformatics Approach to Identify the Influences of COVID-19 on Ischemic Stroke

As severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) is becoming more infectious and less virulent, symptoms beyond the lungs of the Coronavirus Disease 2019 (COVID-19) patients are a growing concern. Studies have found that the severity of COVID-19 patients is associated with an increased risk of ischemic stroke (IS); however, the underlying pathogenic mechanisms remain unknown. In this study, bioinformatics approaches were utilized to explore potential pathogenic mechanisms and predict potential drugs that may be useful in the treatment of COVID-19 and IS. The GSE152418 and GSE122709 datasets were downloaded from the GEO website to obtain the common differentially expressed genes (DEGs) of the two datasets for further functional enrichment, pathway analysis, and drug candidate prediction. A total of 80 common DEGs were identified in COVID-19 and IS datasets for GO and KEGG analysis. Next, the protein-protein interaction (PPI) network was constructed and hub genes were identified. Further, transcription factor-gene interactions and DEGs-miRNAs coregulatory network were investigated to explore their regulatory roles in disease. Finally, protein-drug interactions with common DEGs were analyzed to predict potential drugs. We successfully identified the top 10 hub genes that could serve as novel targeted therapies for COVID-19 and screened out some potential drugs for the treatment of COVID-19 and IS.

Identification of Key Genes Related to Immune Cells in Patients with COVID-19 Via Integrated Bioinformatics-Based Analysis

COVID-19 has spread all over the world which poses a serious threat to social economic development and public health. Despite enormous progress has been made in the prevention and treatment of COVID-19, the specific mechanism and biomarker related to disease severity or prognosis have not been clarified yet. Our study intended to further explore the diagnostic markers of COVID-19 and their relationship with serum immunology by bioinformatics analysis. The datasets about COVID-19 were downloaded from the Gene Expression Omnibus (GEO) dataset. The differentially expressed genes (DEGs) were selected via the limma package. Then, weighted gene co-expression network analysis (WGCNA) was conducted to identify the critical module associated with the clinic status. The intersection DEGs were processed for further enrichment analysis. The final diagnostic genes for COVID-19 were selected and verified through special bioinformatics algorithms. There were significant DEGs between the normal and COVID-19 patients. These genes were mainly enriched in cell cycle, complement and coagulation cascade, extracellular matrix (ECM) receptor interaction, and the P53 signaling pathway. As much as 357 common intersected DEGs were selected in the end. These DEGs were enriched in organelle fission, mitotic cell cycle phase transition, DNA helicase activity, cell cycle, cellular senescence, and P53 signaling pathway. Our study also identified CDC25A, PDCD6, and YWAHE were potential diagnostic markers of COVID-19 with the AUC (area under curve), 0.958 (95% CI 0.920-0.988), 0.941(95% CI 0.892-0.980), and 0.929 (95% CI 0.880-0.971). Moreover, CDC25A, PDCD6, and YWAHE were correlated with plasma cells, macrophages M0, T cells CD4 memory resting, T cells CD8, dendritic cells, and NK cells. Our study discovered that CDC25A, PDCD6, and YWAHE can be used as diagnostic markers for COVID-19. Moreover, these biomarkers were also closely associated with immune cell infiltration, which plays a pivotal role in the diagnosis and progression of COVID-19.

SARS-CoV-2 and the DNA damage response

The recent coronavirus disease 2019 (COVID-19) pandemic was caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). COVID-19 is characterized by respiratory distress, multiorgan dysfunction and, in some cases, death. The virus is also responsible for post-COVID-19 condition (commonly referred to as 'long COVID'). SARS-CoV-2 is a single-stranded, positive-sense RNA virus with a genome of approximately 30 kb, which encodes 26 proteins. It has been reported to affect multiple pathways in infected cells, resulting, in many cases, in the induction of a 'cytokine storm' and cellular senescence. Perhaps because it is an RNA virus, replicating largely in the cytoplasm, the effect of SARS-Cov-2 on genome stability and DNA damage responses (DDRs) has received relatively little attention. However, it is now becoming clear that the virus causes damage to cellular DNA, as shown by the presence of micronuclei, DNA repair foci and increased comet tails in infected cells. This review considers recent evidence indicating how SARS-CoV-2 causes genome instability, deregulates the cell cycle and targets specific components of DDR pathways. The significance of the virus's ability to cause cellular senescence is also considered, as are the implications of genome instability for patients suffering from long COVID.

The Wheel of p53 Helps to Drive the Immune System

The p53 tumor suppressor protein is best known as an inhibitor of the cell cycle and an inducer of apoptosis. Unexpectedly, these functions of p53 are not required for its tumor suppressive activity in animal models. High-throughput transcriptomic investigations as well as individual studies have demonstrated that p53 stimulates expression of many genes involved in immunity. Probably to interfere with its immunostimulatory role, many viruses code for proteins that inactivate p53. Judging by the activities of immunity-related p53-regulated genes it can be concluded that p53 is involved in detection of danger signals, inflammasome formation and activation, antigen presentation, activation of natural killer cells and other effectors of immunity, stimulation of interferon production, direct inhibition of virus replication, secretion of extracellular signaling molecules, production of antibacterial proteins, negative feedback loops in immunity-related signaling pathways, and immunologic tolerance. Many of these p53 functions have barely been studied and require further, more detailed investigations. Some of them appear to be cell-type specific. The results of transcriptomic studies have generated many new hypotheses on the mechanisms utilized by p53 to impact on the immune system. In the future, these mechanisms may be harnessed to fight cancer and infectious diseases.

Deep learning-based network pharmacology for exploring the mechanism of licorice for the treatment of COVID-19

Licorice, a traditional Chinese medicine, has been widely used for the treatment of COVID-19, but all active compounds and corresponding targets are still not clear. Therefore, this study proposed a deep learning-based network pharmacology approach to identify more potential active compounds and targets of licorice. 4 compounds (quercetin, naringenin, liquiritigenin, and licoisoflavanone), 2 targets (SYK and JAK2) and the relevant pathways (P53, cAMP, and NF-kB) were predicted, which were confirmed by previous studies to be associated with SARS-CoV-2-infection. In addition, 2 new active compounds (glabrone and vestitol) and 2 new targets (PTEN and MAP3K8) were further validated by molecular docking and molecular dynamics simulations (simultaneous molecular dynamics), as well as the results showed that these active compounds bound well to COVID-19 related targets, including the main protease (Mpro), the spike protein (S-protein) and the angiotensin-converting enzyme 2 (ACE2). Overall, in this study, glabrone and vestitol from licorice were found to inhibit viral replication by inhibiting the activation of Mpro, S-protein and ACE2; related compounds in licorice may reduce the inflammatory response and inhibit apoptosis by acting on PTEN and MAP3K8. Therefore, licorice has been proposed as an effective candidate for the treatment of COVID-19 through PTEN, MAP3K8, Mpro, S-protein and ACE2.

Roles of p53-Mediated Host–Virus Interaction in Coronavirus Infection

The emergence of the SARS-CoV-2 coronavirus has garnered global attention due to its highly pathogenic nature and the resulting health crisis and economic burden. Although drugs such as Remdesivir have been considered a potential cure by targeting the virus on its RNA polymerase, the high mutation rate and unique 3’ to 5’ exonuclease with proofreading function make it challenging to develop effective anti-coronavirus drugs. As a result, there is an increasing focus on host–virus interactions because coronaviruses trigger stress responses, cell cycle changes, apoptosis, autophagy, and the dysregulation of immune function and inflammation in host cells. The p53 tumor suppressor molecule is a critical regulator of cell signaling pathways, cellular stress responses, DNA repair, and apoptosis. However, viruses can activate or inhibit p53 during viral infections to enhance viral replication and spread. Given its pivotal role in cell physiology, p53 represents a potential target for anti-coronavirus drugs. This review aims to summarize the relationship between p53 and coronaviruses from various perspectives, to shed light on potential targets for antiviral drug development and vaccine design.

Cell cycle block by p53 activation reduces SARS-CoV-2 release in infected alveolar basal epithelial A549-hACE2 cells

SARS-CoV viruses have been shown to downregulate cellular events that control antiviral defenses. They adopt several strategies to silence p53, key molecule for cell homeostasis and immune control, indicating that p53 has a central role in controlling their proliferation in the host. Specific actions are the stabilization of its inhibitor, MDM2, and the interference with its transcriptional activity. The aim of our work was to evaluate a new approach against SARS-CoV-2 by using MDM2 inhibitors to raise p53 levels and activate p53-dependent pathways, therefore leading to cell cycle inhibition. Experimental setting was performed in the alveolar basal epithelial cell line A549-hACE2, expressing high level of ACE2 receptor, to allow virus entry, as well as p53 wild-type. Cells were treated with several concentrations of Nutlin-3 or RG-7112, two known MDM2 inhibitors, for the instauration of a cell cycle block steady-state condition before and during SARS-CoV-2 infection, and for the evaluation of p53 activation and impact on virus release and related innate immune events. The results indicated an efficient cell cycle block with inhibition of the virion release and a significant inhibition of IL-6, NF-kB and IFN-λ expression. These data suggest that p53 is an efficient target for new therapies against the virus and that MDM2 inhibitors deserve to be further investigated in this field.

A novel gene signature based on the hub genes of COVID-19 predicts the prognosis of idiopathic pulmonary fibrosis

Background: Increasing evidence has demonstrated that there was a strong correlation between COVID-19 and idiopathic pulmonary fibrosis (IPF). However, the studies are limited, and the real biological mechanisms behind the IPF progression were still uncleared.

Methods: GSE70866 and GSE 157103 datasets were downloaded. The weight gene co-expression network analysis (WGCNA) algorithms were conducted to identify the most correlated gene module with COVID-19. Then the genes were extracted to construct a risk signature in IPF patients by performing Univariate and Lasso Cox Regression analysis. Univariate and Multivariate Cox Regression analyses were used to identify the independent value for predicting the prognosis of IPF patients. What’s more, the Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and gene set enrichment analysis (GSEA) were conducted to unveil the potential biological pathways. CIBERSORT algorithms were performed to calculate the correlation between the risk score and immune cells infiltrating levels.

Results: Two hundred thirty three differentially expressed genes were calculated as the hub genes in COVID-19. Fourteen of these genes were identified as the prognostic differentially expressed genes in IPF. Three (MET, UCHL1, and IGF1) of the fourteen genes were chosen to construct the risk signature. The risk signature can greatly predict the prognosis of high-risk and low-risk groups based on the calculated risk score. The functional pathway enrichment analysis and immune infiltrating analysis showed that the risk signature may regulate the immune-related pathways and immune cells.

Conclusion: We identified prognostic differentially expressed hub genes related to COVID-19 in IPF. A risk signature was constructed based on those genes and showed great value for predicting the prognosis in IPF patients. What’s more, three genes in the risk signature may be clinically valuable as potential targets for treating IPF patients and IPF patients with COVID-19.

Therapeutic potential of the MDM2 inhibitor Nutlin-3 in counteracting SARS-CoV-2 infection of the eye through p53 activation

Starting from the beginning of the severe acute respiratory syndrome Coronavirus-2 (SARS-CoV-2) global pandemic, most of the published data has concentrated on the respiratory signs and symptoms of Covid-19 infection, underestimating the presence and importance of ocular manifestations, such as conjunctivitis, usually reported in SARS-CoV-2 infected patients. With the present review we intend to resume the ocular involvement in SARS-CoV-2 infection and the recent discoveries about the different cell types and tissues of the eye that can be directly infected by SARS-CoV-2 and propagate the infection. Moreover, reviewing literature data about p53 expression in normal and diseased eye tissues, we hypothesize that the pleiotropic protein p53 present at high levels in cornea, conjunctiva and tear film might play a protective role against SARS-CoV-2 infection. Since p53 can be easily up-regulated by using small molecule non-genotoxic inhibitors of MDM2, we propose that topical use of Nutlin-3, the prototype member of MDM2 inhibitors, might protect the anterior surface of the eye from SARS-CoV-2 infection, reducing the spreading of the virus.