Comparative Transcriptomic and Molecular Pathway Analyses of HL-CZ Human Pro-Monocytic Cells Expressing SARS-CoV-2 Spike S1, S2, NP, NSP15 and NSP16 Genes

Generic model to unravel the deeper insights of viral infections: an empirical application of evolutionary graph coloring in computational network biology

PURPOSE

Graph coloring approach has emerged as a valuable problem-solving tool for both theoretical and practical aspects across various scientific disciplines, including biology. In this study, we demonstrate the graph coloring's effectiveness in computational network biology, more precisely in analyzing protein-protein interaction (PPI) networks to gain insights about the viral infections and its consequences on human health. Accordingly, we propose a generic model that can highlight important hub proteins of virus-associated disease manifestations, changes in disease-associated biological pathways, potential drug targets and respective drugs. We test our model on SARS-CoV-2 infection, a highly transmissible virus responsible for the COVID-19 pandemic. The pandemic took significant human lives, causing severe respiratory illnesses and exhibiting various symptoms ranging from fever and cough to gastrointestinal, cardiac, renal, neurological, and other manifestations.

METHODS

To investigate the underlying mechanisms of SARS-CoV-2 infection-induced dysregulation of human pathobiology, we construct a two-level PPI network and employed a differential evolution-based graph coloring (DEGCP) algorithm to identify critical hub proteins that might serve as potential targets for resolving the associated issues. Initially, we concentrate on the direct human interactors of SARS-CoV-2 proteins to construct the first-level PPI network and subsequently applied the DEGCP algorithm to identify essential hub proteins within this network. We then build a second-level PPI network by incorporating the next-level human interactors of the first-level hub proteins and use the DEGCP algorithm to predict the second level of hub proteins.

RESULTS

We first identify the potential crucial hub proteins associated with SARS-CoV-2 infection at different levels. Through comprehensive analysis, we then investigate the cellular localization, interactions with other viral families, involvement in biological pathways and processes, functional attributes, gene regulation capabilities as transcription factors, and their associations with disease-associated symptoms of these identified hub proteins. Our findings highlight the significance of these hub proteins and their intricate connections with disease pathophysiology. Furthermore, we predict potential drug targets among the hub proteins and identify specific drugs that hold promise in preventing or treating SARS-CoV-2 infection and its consequences.

CONCLUSION

Our generic model demonstrates the effectiveness of DEGCP algorithm in analyzing biological PPI networks, provides valuable insights into disease biology, and offers a basis for developing novel therapeutic strategies for other viral infections that may cause future pandemic.

HCV Infection Increases the Expression of ACE2 Receptor, Leading to Enhanced Entry of Both HCV and SARS-CoV-2 into Hepatocytes and a Coinfection State

Recent studies suggest the enhancement of liver injury in COVID-19 patients infected with Hepatitis C virus (HCV). Hepatocytes express low levels of angiotensin-converting enzyme 2 (ACE2), the SARS-CoV-2 entry receptor, raising the possibility of HCV-SARS-CoV-2 coinfection in the liver. This work aimed to explore whether HCV and SARS-CoV-2 coinfect hepatocytes and the interplay between these viruses. We demonstrate that SARS-CoV-2 coinfects HCV-infected Huh7.5 (Huh7.5HCV) cells. Both viruses replicated efficiently in the coinfected cells, with HCV replication enhanced in coinfected compared to HCV-mono-infected cells. Strikingly, Huh7.5HCV cells were eight fold more susceptible to SARS-CoV-2 pseudoviruses than naive Huh7.5 cells, suggesting enhanced SARS-CoV-2 entry into HCV-preinfected hepatocytes. In addition, we observed increased binding of spike receptor-binding domain (RBD) protein to Huh7.5HCV cells, as well as enhanced cell-to-cell fusion of Huh7.5HCV cells with spike-expressing Huh7.5 cells. We explored the mechanism of enhanced SARS-CoV-2 entry and identified an increased ACE2 mRNA and protein levels in Huh7.5HCV cells, primary hepatocytes, and in data from infected liver biopsies obtained from database. Importantly, higher expression of ACE2 increased HCV infection by enhancing its binding to the host cell, underscoring its role in the HCV life cycle as well. Transcriptome analysis revealed that shared host signaling pathways were induced in HCV-SARS-CoV-2 coinfection. This study revealed complex interactions between HCV and SARS-CoV-2 infections in hepatocytes, which may lead to the increased liver damage recently reported in HCV-positive COVID-19 patients. IMPORTANCE Here, we provide the first experimental evidence for the coexistence of SARS-CoV-2 infection with HCV, and the interplay between them. The study revealed a complex relationship of enhancement between the two viruses, where HCV infection increased the expression of the SARS-CoV-2 entry receptor ACE2, thus facilitating SARS-CoV-2 entry, and potentially, also HCV entry. Thereafter, SARS-CoV-2 infection enhanced HCV replication in hepatocytes. This study may explain the aggravation of liver damage that was recently reported in COVID-19 patients with HCV coinfection and suggests preinfection with HCV as a risk factor for severe COVID-19. Moreover, it highlights the possible importance of HCV treatment for coinfected patients. In a broader view, these findings emphasize the importance of identifying coinfecting pathogens that increase the risk of SARS-CoV-2 infection and that may accelerate COVID-19-related co-morbidities.

Potential Coronaviral Inhibitors of the Nucleocapsid Protein Identified In Silico and In Vitro from a Large Natural Product Library

The nucleocapsid protein (NP) is one of the main proteins out of four structural proteins of coronaviruses including the severe acute respiratory syndrome coronavirus 2, SARS-CoV-2, discovered in 2019. NP packages the viral RNA during virus assembly and is, therefore, indispensable for virus reproduction. NP consists of two domains, i.e., the N- and C-terminal domains. RNA-binding is mainly performed by a binding pocket within the N-terminal domain (NTD). NP represents an important target for drug discovery to treat COVID-19. In this project, we used the Vina LC virtual drug screening software and a ZINC-based database with 210,541 natural and naturally derived compounds that specifically target the binding pocket of NTD of NP. Our aim was to identify coronaviral inhibitors that target NP not only of SARS-CoV-2 but also of other diverse human pathogenic coronaviruses. Virtual drug screening and molecular docking procedures resulted in 73 candidate compounds with a binding affinity below −9 kcal/mol with NP NTD of SARS-CoV-1, SARS-CoV-2, MERS-CoV, HCoV-OC43, HCoV-NL63, HoC-229E, and HCoV-HKU1. The top five compounds that met the applied drug-likeness criteria were then tested for their binding in vitro to the NTD of the full-length recombinant NP proteins using microscale thermophoresis. Compounds (1), (2), and (4), which belong to the same scaffold family of 4-oxo-substituted-6-[2-(4a-hydroxy-decahydroisoquinolin-2-yl)2H-chromen-2-ones and which are derivates of coumarin, were bound with good affinity to NP. Compounds (1) and (4) were bound to the full-length NP of SARS-CoV-2 (aa 1–419) with Kd values of 0.798 (±0.02) µM and 8.07 (±0.36) µM, respectively. Then, these coumarin derivatives were tested with the SARS-CoV-2 NP NTD (aa 48–174). Compounds (1) and (4) revealed Kd-values of 0.95 (±0.32) µM and 7.77 (±6.39) µM, respectively. Compounds (1) and (4) caused low toxicity in human A549 and MRC-5 cell lines. These compounds may represent possible drug candidates, which need further optimization to be used against COVID-19 and other coronaviral infections.

Altered Lipid Profile in COVID-19 Patients and Metabolic Reprogramming

Background

Coronavirus disease 2019 (COVID-19) is a global pandemic. Previous studies have reported dyslipidemia in patients with COVID-19. Herein, we conducted a retrospective study and a bioinformatics analysis to evaluate the essential data of the lipid profile as well as the possible mechanism in patients with COVID-19.

Methods

First of all, the retrospective study included three cohorts: patients with COVID-19, a healthy population, and patients with chronic obstructive pulmonary disease (COPD). For each subject, serum lipid profiles in the biochemical data were compared, including triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C). Furthermore, bioinformatics analyses were performed for exploring the biological or immunological mechanisms.

Results

In line with the biochemical data of the three cohorts, the statistical result displayed that patients with COVID-19 were more likely to have lower levels of TC and HDL-C as compared with healthy individuals. The differential proteins associated with COVID-19 are involved in the lipid pathway and can target and regulate cytokines and immune cells. Additionally, a heatmap revealed that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections were possibly involved in lipid metabolic reprogramming. The viral proteins, such as spike (S) and non-structural protein 2 (Nsp2) of SARS-CoV-2, may be involved in metabolic reprogramming.

Conclusion

The metabolic reprogramming after SARS-CoV-2 infections is probably associated with the immune and clinical phenotype of patients. Hence, metabolic reprogramming may be targeted for developing antivirals against COVID-19.

SARS-CoV-2 Spike Protein and Mouse Coronavirus Inhibit Biofilm Formation by Streptococcus pneumoniae and Staphylococcus aureus

The presence of co-infections or superinfections with bacterial pathogens in COVID-19 patients is associated with poor outcomes, including increased morbidity and mortality. We hypothesized that SARS-CoV-2 and its components interact with the biofilms generated by commensal bacteria, which may contribute to co-infections. This study employed crystal violet staining and particle-tracking microrheology to characterize the formation of biofilms by Streptococcus pneumoniae and Staphylococcus aureus that commonly cause secondary bacterial pneumonia. Microrheology analyses suggested that these biofilms were inhomogeneous soft solids, consistent with their dynamic characteristics. Biofilm formation by both bacteria was significantly inhibited by co-incubation with recombinant SARS-CoV-2 spike S1 subunit and both S1 + S2 subunits, but not with S2 extracellular domain nor nucleocapsid protein. Addition of spike S1 and S2 antibodies to spike protein could partially restore bacterial biofilm production. Furthermore, biofilm formation in vitro was also compromised by live murine hepatitis virus, a related beta-coronavirus. Supporting data from LC-MS-based proteomics of spike-biofilm interactions revealed differential expression of proteins involved in quorum sensing and biofilm maturation, such as the AI-2E family transporter and LuxS, a key enzyme for AI-2 biosynthesis. Our findings suggest that these opportunistic pathogens may egress from biofilms to resume a more virulent planktonic lifestyle during coronavirus infections. The dispersion of pathogens from biofilms may culminate in potentially severe secondary infections with poor prognosis. Further detailed investigations are warranted to establish bacterial biofilms as risk factors for secondary pneumonia in COVID-19 patients.

Combination Treatment With Remdesivir and Ivermectin Exerts Highly Synergistic and Potent Antiviral Activity Against Murine Coronavirus Infection

The recent COVID-19 pandemic has highlighted the urgency to develop effective antiviral therapies against the disease. Murine hepatitis virus (MHV) is a coronavirus that infects mice and shares some sequence identity to SARS-CoV-2. Both viruses belong to the Betacoronavirus genus, and MHV thus serves as a useful and safe surrogate model for SARS-CoV-2 infections. Clinical trials have indicated that remdesivir is a potentially promising antiviral drug against COVID-19. Using an in vitro model of MHV infection of RAW264.7 macrophages, the safety and efficacy of monotherapy of remdesivir, chloroquine, ivermectin, and doxycycline were investigated. Of the four drugs tested, remdesivir monotherapy exerted the strongest inhibition of live virus and viral RNA replication of about 2-log10 and 1-log10, respectively (at 6 µM). Ivermectin treatment showed the highest selectivity index. Combination drug therapy was also evaluated using remdesivir (6 µM) together with chloroquine (15 µM), ivermectin (2 µM) or doxycycline (15 µM) - above their IC50 values and at high macrophage cell viability of over 95%. The combination of remdesivir and ivermectin exhibited highly potent synergism by achieving significant reductions of about 7-log10 of live virus and 2.5-log10 of viral RNA in infected macrophages. This combination also resulted in the lowest cytokine levels of IL-6, TNF-α, and leukemia inhibitory factor. The next best synergistic combination was remdesivir with doxycycline, which decreased levels of live virus by ~3-log10 and viral RNA by ~1.5-log10. These results warrant further studies to explore the mechanisms of action of the combination therapy, as well as future in vivo experiments and clinical trials for the treatment of SARS-CoV-2 infection.