A SARS-CoV-2 host infection model network based on genomic human Transcription Factors (TFs) depletion

The Potential Roles of Host Cell miRNAs in Fine-Tuning Bovine Coronavirus (BCoV) Molecular Pathogenesis, Tissue Tropism, and Immune Regulation

Bovine coronavirus (BCoV) infection causes significant economic loss to the dairy and beef industries worldwide. BCoV exhibits dual tropism, infecting the respiratory and enteric tracts of cattle. The enteric BCoV isolates could also induce respiratory manifestations under certain circumstances. However, the mechanism of this dual tropism of BCoV infection has not yet been studied well. MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression and play a dual role in virus infection, mediating virus or modulating host immune regulatory genes through complex virus-host cell interactions. However, their role in BCoV infection remains unclear. This study aims to identify bovine miRNAs crucial for regulating virus-host interaction, influencing tissue tropism, and explore their potential as biomarkers and therapeutic agents against BCoV. We downloaded 18 full-length BCoV genomes (10 enteric and eight respiratory) from GenBank. We applied several bioinformatic tools to study the host miRNAs targeting various regions in the viral genome. We used the criteria of differential targeting between the enteric/respiratory isolates to identify some critical miRNAs as biological markers for BCoV infection. Using various online bioinformatic tools, we also searched for host miRNA target genes involved in BCoV infection, immune evasion, and regulation. Our results show that four bovine miRNAs (miR-2375, miR-193a-3p, miR-12059, and miR-494) potentially target the BCoV spike protein at multiple sites. These miRNAs also regulate the host immune suppressor pathways, which negatively impacts BCoV replication. Furthermore, we found that bta-(miR-2338, miR-6535, miR-2392, and miR-12054) also target the BCoV genome at certain regions but are involved in regulating host immune signal transduction pathways, i.e., type I interferon (IFN) and retinoic acid-inducible gene I (RIG-I) pathways. Moreover, both miR-2338 and miR-2392 also target host transcriptional factors RORA, YY1, and HLF, which are potential diagnostic markers for BCoV infection. Therefore, miR-2338, miR-6535, miR-2392, and miR-12054 have the potential to fine-tune BCoV tropism and immune evasion and enhance viral pathogenesis. Our results indicate that host miRNAs play essential roles in the BCoV tissue tropism, pathogenesis, and immune regulation. Four bovine miRNAs (miR-2375, bta-miR-193a-3p, bta-miR-12059, and bta-miR-494) target BCoV-S glycoprotein and are potentially involved in several immune suppression pathways during the viral infection. These miRNA candidates could serve as good genetic markers for BCoV infection. However, further studies are urgently needed to validate these identified miRNAs and their target genes in the context of BCoV infection and dual tropism and as genetic markers.

Identification of host genomic biomarkers from multiple transcriptomics datasets for diagnosis and therapies of SARS-CoV-2 infections

The pandemic of COVID-19 is a severe threat to human life and the global economy. Despite the success of vaccination efforts in reducing the spread of the virus, the situation remains largely uncontrolled due to the random mutation in the RNA sequence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which demands different variants of effective drugs. Disease-causing gene-mediated proteins are usually used as receptors to explore effective drug molecules. In this study, we analyzed two different RNA-Seq and one microarray gene expression profile datasets by integrating EdgeR, LIMMA, weighted gene co-expression network and robust rank aggregation approaches, which revealed SARS-CoV-2 infection causing eight hub-genes (HubGs) including HubGs; REL, AURKA, AURKB, FBXL3, OAS1, STAT4, MMP2 and IL6 as the host genomic biomarkers. Gene Ontology and pathway enrichment analyses of HubGs significantly enriched some crucial biological processes, molecular functions, cellular components and signaling pathways that are associated with the mechanisms of SARS-CoV-2 infections. Regulatory network analysis identified top-ranked 5 TFs (SRF, PBX1, MEIS1, ESR1 and MYC) and 5 miRNAs (hsa-miR-106b-5p, hsa-miR-20b-5p, hsa-miR-93-5p, hsa-miR-106a-5p and hsa-miR-20a-5p) as the key transcriptional and post-transcriptional regulators of HubGs. Then, we conducted a molecular docking analysis to determine potential drug candidates that could interact with HubGs-mediated receptors. This analysis resulted in the identification of top-ranked ten drug agents, including Nilotinib, Tegobuvir, Digoxin, Proscillaridin, Olysio, Simeprevir, Hesperidin, Oleanolic Acid, Naltrindole and Danoprevir. Finally, we investigated the binding stability of the top-ranked three drug molecules Nilotinib, Tegobuvir and Proscillaridin with the three top-ranked proposed receptors (AURKA, AURKB, OAS1) by using 100 ns MD-based MM-PBSA simulations and observed their stable performance. Therefore, the findings of this study might be useful resources for diagnosis and therapies of SARS-CoV-2 infections.

Insight into designing of 2-pyridone derivatives for COVID-19 drug discovery - A computational study

Presently, the prime global focus is on SARS-CoV-2, as no fully established, licensed medicine has been found thus far, in spite of the existence of various reports and administration of partially proven certain class of natural products. However, in case of natural products, the extraction and purification limit their application. This situation drives researchers to explore synthetically viable drugs. In the present investigation, twenty-three 2-pyridone synthetic derivatives (P1-P23) have been theoretically tested for their suitability as potential inhibitors for COVID-19 main protease through DFT, molecular docking, and molecular dynamics simulations. DFT calculations offer insights into structure-property relationships, while ADMET studies indicate the pharmacological characteristics of these molecules. Molecular docking studies ascertain the nature and mode of interactions of these entities with COVID-19 main protease. Furthermore, covalent docking has been carried out to verify the feasibility of the formation of a covalent bond with the active site. The top protein-inhibitor complexes, such as P18, P11, and P12, were identified based on their glide score. These molecules, along with the covalent docked complexes, namely P18 and P16, were selected and subjected to molecular dynamics simulations. The 100 ns simulation process exhibited that the covalent docked ones, due to their stable form could serve as lead compounds against SARS-CoV-2. Hence, this study affirms the potential candidature of 2-pyridone-based inhibitors.

An in silico pipeline approach uncovers a potentially intricate network involving spike SARS-CoV-2 RNA, RNA vaccines, host RNA-binding proteins (RBPs), and host miRNAs at the cellular level

BACKGROUND

In the last 2 years, we have been fighting against SARS-CoV-2 viral infection, which continues to claim victims all over the world. The entire scientific community has been mobilized in an attempt to stop and eradicate the infection. A well-known feature of RNA viruses is their high mutational rate, particularly in specific gene regions. The SARS-CoV-2 S protein is also affected by these changes, allowing viruses to adapt and spread more easily. The vaccines developed using mRNA coding protein S undoubtedly contributed to the "fight" against the COVID-19 pandemic even though the presence of new variants in the spike protein could result in protein conformational changes, which could affect vaccine immunogenicity and thus vaccine effectiveness.

RESULTS

The study presents the findings of an in silico analysis using various bioinformatics tools finding conserved sequences inside SARS-CoV-2 S protein (encoding mRNA) same as in the vaccine RNA sequences that could be targeted by specific host RNA-binding proteins (RBPs). According to the results an interesting scenario emerges involving host RBPs competition and subtraction. The presence of viral RNA in cytoplasm could be a new tool in the virus's armory, allowing it to improve its chances of survival by altering cell gene expression and thus interfering with host cell processes. In silico analysis was used also to evaluate the presence of similar human miRNA sequences within RBPs motifs that can modulate human RNA expression. Increased cytoplasmic availability of exogenous RNA fragments derived from RNA physiological degradation could potentially mimic the effect of host human miRNAs within the cell, causing modulation of the host cell network.

CONCLUSIONS

Our in silico analysis could aid in shedding light on the potential effects of exogenous RNA (i.e. viruses and vaccines), thereby improving our understanding of the cellular interactions between virus and host biomolecules. Finally, using the computational approach, it is possible to obtain a safety assessment of RNA-based vaccines as well as indications for use in specific clinical conditions.

Systems biology models to identify the influence of SARS-CoV-2 infections to the progression of human autoimmune diseases

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been circulating since 2019, and its global dominance is rising. Evidences suggest the respiratory illness SARS-CoV-2 has a sensitive affect on causing organ damage and other complications to the patients with autoimmune diseases (AD), posing a significant risk factor. The genetic interrelationships and molecular appearances between SARS-CoV-2 and AD are yet unknown. We carried out the transcriptomic analytical framework to delve into the SARS-CoV-2 impacts on AD progression. We analyzed both gene expression microarray and RNA-Seq datasets from SARS-CoV-2 and AD affected tissues. With neighborhood-based benchmarks and multilevel network topology, we obtained dysfunctional signaling and ontological pathways, gene disease (diseasesome) association network and protein-protein interaction network (PPIN), uncovered essential shared infection recurrence connectivities with biological insights underlying between SARS-CoV-2 and AD. We found a total of 77, 21, 9, 54 common DEGs for SARS-CoV-2 and inflammatory bowel disorder (IBD), SARS-CoV-2 and rheumatoid arthritis (RA), SARS-CoV-2 and systemic lupus erythematosus (SLE) and SARS-CoV-2 and type 1 diabetes (T1D). The enclosure of these common DEGs with bimolecular networks revealed 10 hub proteins (FYN, VEGFA, CTNNB1, KDR, STAT1, B2M, CD3G, ITGAV, TGFB3). Drugs such as amlodipine besylate, vorinostat, methylprednisolone, and disulfiram have been identified as a common ground between SARS-CoV-2 and AD from drug repurposing investigation which will stimulate the optimal selection of medications in the battle against this ongoing pandemic triggered by COVID-19.

A Path-Based Analysis of Infected Cell Line and COVID-19 Patient Transcriptome Reveals Novel Potential Targets and Drugs Against SARS-CoV-2

Most transcriptomic studies of SARS-CoV-2 infection have focused on differentially expressed genes, which do not necessarily reveal the genes mediating the transcriptomic changes. In contrast, exploiting curated biological network, our PathExt tool identifies central genes from the differentially active paths mediating global transcriptomic response. Here we apply PathExt to multiple cell line infection models of SARS-CoV-2 and other viruses, as well as to COVID-19 patient-derived PBMCs. The central genes mediating SARS-CoV-2 response in cell lines were uniquely enriched for ATP metabolic process, G1/S transition, leukocyte activation and migration. In contrast, PBMC response reveals dysregulated cell-cycle processes. In PBMC, the most frequently central genes are associated with COVID-19 severity. Importantly, relative to differential genes, PathExt-identified genes show greater concordance with several benchmark anti-COVID-19 target gene sets. We propose six novel anti-SARS-CoV-2 targets ADCY2, ADSL, OCRL, TIAM1, PBK, and BUB1, and potential drugs targeting these genes, such as Bemcentinib, Phthalocyanine, and Conivaptan.

Identification of host transcriptome-guided repurposable drugs for SARS-CoV-1 infections and their validation with SARS-CoV-2 infections by using the integrated bioinformatics approaches

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is one of the most severe global pandemic due to its high pathogenicity and death rate starting from the end of 2019. Though there are some vaccines available against SAER-CoV-2 infections, we are worried about their effectiveness, due to its unstable sequence patterns. Therefore, beside vaccines, globally effective supporting drugs are also required for the treatment against SARS-CoV-2 infection. To explore commonly effective repurposable drugs for the treatment against different variants of coronavirus infections, in this article, an attempt was made to explore host genomic biomarkers guided repurposable drugs for SARS-CoV-1 infections and their validation with SARS-CoV-2 infections by using the integrated bioinformatics approaches. At first, we identified 138 differentially expressed genes (DEGs) between SARS-CoV-1 infected and control samples by analyzing high throughput gene-expression profiles to select drug target key receptors. Then we identified top-ranked 11 key DEGs (SMAD4, GSK3B, SIRT1, ATM, RIPK1, PRKACB, MED17, CCT2, BIRC3, ETS1 and TXN) as hub genes (HubGs) by protein-protein interaction (PPI) network analysis of DEGs highlighting their functions, pathways, regulators and linkage with other disease risks that may influence SARS-CoV-1 infections. The DEGs-set enrichment analysis significantly detected some crucial biological processes (immune response, regulation of angiogenesis, apoptotic process, cytokine production and programmed cell death, response to hypoxia and oxidative stress), molecular functions (transcription factor binding and oxidoreductase activity) and pathways (transcriptional mis-regulation in cancer, pathways in cancer, chemokine signaling pathway) that are associated with SARS-CoV-1 infections as well as SARS-CoV-2 infections by involving HubGs. The gene regulatory network (GRN) analysis detected some transcription factors (FOXC1, GATA2, YY1, FOXL1, TP53 and SRF) and micro-RNAs (hsa-mir-92a-3p, hsa-mir-155-5p, hsa-mir-106b-5p, hsa-mir-34a-5p and hsa-mir-19b-3p) as the key transcriptional and post- transcriptional regulators of HubGs, respectively. We also detected some chemicals (Valproic Acid, Cyclosporine, Copper Sulfate and arsenic trioxide) that may regulates HubGs. The disease-HubGs interaction analysis showed that our predicted HubGs are also associated with several other diseases including different types of lung diseases. Then we considered 11 HubGs mediated proteins and their regulatory 6 key TFs proteins as the drug target proteins (receptors) and performed their docking analysis with the SARS-CoV-2 3CL protease-guided top listed 90 anti-viral drugs out of 3410. We found Rapamycin, Tacrolimus, Torin-2, Radotinib, Danoprevir, Ivermectin and Daclatasvir as the top-ranked 7 candidate-drugs with respect to our proposed target proteins for the treatment against SARS-CoV-1 infections. Then, we validated these 7 candidate-drugs against the already published top-ranked 11 target proteins associated with SARS-CoV-2 infections by molecular docking simulation and found their significant binding affinity scores with our proposed candidate-drugs. Finally, we validated all of our findings by the literature review. Therefore, the proposed candidate-drugs might play a vital role for the treatment against different variants of SARS-CoV-2 infections with comorbidities, since the proposed HubGs are also associated with several comorbidities.

On Deep Landscape Exploration of COVID-19 Patients Cells and Severity Markers

COVID-19 is a disease with a spectrum of clinical responses ranging from moderate to critical. To study and control its effects, a large number of researchers are focused on two substantial aims. On the one hand, the discovery of diverse biomarkers to classify and potentially anticipate the disease severity of patients. These biomarkers could serve as a medical criterion to prioritize attention to those patients with higher prone to severe responses. On the other hand, understanding how the immune system orchestrates its responses in this spectrum of disease severities is a fundamental issue required to design new and optimized therapeutic strategies. In this work, using single-cell RNAseq of bronchoalveolar lavage fluid of nine patients with COVID-19 and three healthy controls, we contribute to both aspects. First, we presented computational supervised machine-learning models with high accuracy in classifying the disease severity (moderate and severe) in patients with COVID-19 starting from single-cell data from bronchoalveolar lavage fluid. Second, we identified regulatory mechanisms from the heterogeneous cell populations in the lungs microenvironment that correlated with different clinical responses. Given the results, patients with moderate COVID-19 symptoms showed an activation/inactivation profile for their analyzed cells leading to a sequential and innocuous immune response. In comparison, severe patients might be promoting cytotoxic and pro-inflammatory responses in a systemic fashion involving epithelial and immune cells without the possibility to develop viral clearance and immune memory. Consequently, we present an in-depth landscape analysis of how transcriptional factors and pathways from these heterogeneous populations can regulate their expression to promote or restrain an effective immune response directly linked to the patients prognosis.

Chronic lung diseases are associated with gene expression programs favoring SARS-CoV-2 entry and severity

Patients with chronic lung disease (CLD) have an increased risk for severe coronavirus disease-19 (COVID-19) and poor outcomes. Here, we analyze the transcriptomes of 611,398 single cells isolated from healthy and CLD lungs to identify molecular characteristics of lung cells that may account for worse COVID-19 outcomes in patients with chronic lung diseases. We observe a similar cellular distribution and relative expression of SARS-CoV-2 entry factors in control and CLD lungs. CLD AT2 cells express higher levels of genes linked directly to the efficiency of viral replication and the innate immune response. Additionally, we identify basal differences in inflammatory gene expression programs that highlight how CLD alters the inflammatory microenvironment encountered upon viral exposure to the peripheral lung. Our study indicates that CLD is accompanied by changes in cell-type-specific gene expression programs that prime the lung epithelium for and influence the innate and adaptive immune responses to SARS-CoV-2 infection.

In Silico Analysis of Possible Interaction between Host Genomic Transcription Factors (TFs) and Zika Virus (ZikaSPH2015) Strain with Combinatorial Gene Regulation; Virus Versus Host-The Game Reloaded

In silico analysis is a promising approach for understanding biological events in complex diseases. Herein we report on the innovative computational workflow allowed to highlight new direct interactions between human transcription factors (TFs) and an entire genome of virus ZikaSPH2015 strain in order to identify the occurrence of specific motifs on a genomic Zika Virus sequence that is able to bind and, therefore, sequester host’s TFs. The analysis pipeline was performed using different bioinformatics tools available online (free of charge). According to obtained results of this in silico analysis, it is possible to hypothesize that these TFs binding motifs might be able to explain the complex and heterogeneous phenotype presentation in Zika-virus-affected fetuses/newborns, as well as the less severe condition in adults. Moreover, the proposed in silico protocol identified thirty-three different TFs identical to the distribution of TFBSs (Transcription Factor Binding Sites) on ZikaSPH2015 strain, potentially able to influence genes and pathways with biological functions confirming that this approach could find potential answers on disease pathogenesis.