Comparative transcriptome analysis of SARS-CoV, MERS-CoV, and SARS-CoV-2 to identify potential pathways for drug repurposing

Establishment of a human organoid-based evaluation system for assessing interspecies infection risk of animal-borne coronaviruses

The COVID-19 pandemic presents a major threat to global public health. Several lines of evidence have shown that the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), along with two other highly pathogenic coronaviruses, SARS-CoV and Middle East Respiratory Syndrome (MERS-CoV) originated from bats. To prevent and control future coronavirus outbreaks, it is necessary to investigate the interspecies infection and pathogenicity risks of animal-related coronaviruses. Currently used infection models, including in vitro cell lines and in vivo animal models, fail to fully mimic the primary infection in human tissues. Here, we employed organoid technology as a promising new model for studying emerging pathogens and their pathogenic mechanisms. We investigated the key host-virus interaction patterns of five human coronaviruses (SARS-CoV-2 original strain, Omicron BA.1, MERS-CoV, HCoV-229E, and HCoV-OC43) in different human respiratory organoids. Five indicators, including cell tropism, invasion preference, replication activity, host response and virus-induced cell death, were developed to establish a comprehensive evaluation system to predict coronavirus interspecies infection and pathogenicity risks. Using this system, we further examined the pathogenicity and interspecies infection risks of three SARS-related coronaviruses (SARSr-CoV), including WIV1 and rRsSHC014S from bats, and MpCoV-GX from pangolins. Moreover, we found that cannabidiol, a non-psychoactive plant extract, exhibits significant inhibitory effects on various coronaviruses in human lung organoid. Cannabidiol significantly enhanced interferon-stimulated gene expression but reduced levels of inflammatory cytokines. In summary, our study established a reliable comprehensive evaluation system to analyse infection and pathogenicity patterns of zoonotic coronaviruses, which could aid in prevention and control of potentially emerging coronavirus diseases.

Comparative transcriptome reveals EphA2 and c-Fos as key factors driving enhanced replication in high-passage porcine deltacoronavirus strain

Porcine deltacoronavirus (PDCoV), a cross-species transmissible enterovirus, frequently induces severe diarrhea and vomiting symptoms in piglets, which not only pose a significant menace to the global pig industry but also a potential public safety risk. In a previous study, we isolated a vaccine candidate, PDCoV CZ2020-P100, by passaging a parental PDCoV strain in vitro, exhibiting attenuated virulence and enhanced replication. However, the factors underlying these differences between primary and passaged strains remain unknown. In this study, we present the transcriptional landscapes of porcine kidney epithelial cells (LLC-PK1) cells infected with PDCoV CZ2020-P1 strain and P100 strain using the RNA-sequencing. We identified 105 differentially expressed genes (DEGs) in P1-infected cells and 295 DEGs in P100-infected cells. Enrichment analyses indicated that many DEGs showed enrichment in immune and inflammatory responses, with a more and higher upregulation of DEGs enriched in the P100-infected group. Notably, the DEGs were concentrated in the MAPK pathway within the P100-infected group, with significant upregulation in EphA2 and c-Fos. Knockdown of EphA2 and c-Fos reduced PDCoV infection and significantly impaired P100 replication compared to P1, suggesting a novel mechanism in which EphA2 and c-Fos are highly involved in passaged virus replication. Our findings illuminate the resemblances and distinctions in the gene expression patterns of host cells infected with P1 and P100, confirming that EphA2 and c-Fos play key roles in high-passage PDCoV replication. These results enhance our understanding of the changes in virulence and replication capacity during the process of passaging.

A deep learning drug screening framework for integrating local-global characteristics: A novel attempt for limited data

At the beginning of the "Disease X" outbreak, drug discovery and development are often challenged by insufficient and unbalanced data. To address this problem and maximize the information value of limited data, we propose a drug screening model, LGCNN, based on convolutional neural network (CNN), which enables rapid drug screening by integrating features of drug molecular structures and drug-target interactions at both local and global (LG) levels. Experimental results show that LGCNN exhibits better performance compared to other state-of-the-art classification methods under limited data. In addition, LGCNN was applied to anti-SARS-CoV-2 drug screening to realize therapeutic drug mining against COVID-19. LGCNN transcends the limitations of traditional models for predicting interactions between single drug targets and shows new advantages in predicting multi-target drug-target interactions. Notably, the cross-coronavirus generalizability of the model is also implied by the analysis of targets, drugs, and mechanisms in the prediction results. In conclusion, LGCNN provides new ideas and methods for rapid drug screening in emergency situations where data are scarce.

CompCorona: A web application for comparative transcriptome analyses of coronaviruses reveals SARS-CoV-2-specific host response

Background/aim

Understanding the mechanism of host transcriptomic response to infection by the SARS-CoV-2 virus is crucial, especially for patients suffering from long-term effects of COVID-19, such as long COVID or pericarditis inflammation, potentially linked to side effects of the SARS-CoV-2 spike proteins. We conducted comprehensive transcriptome and enrichment analyses on lung and peripheral blood mononuclear cells (PBMCs) infected with SARS-CoV-2, as well as on SARS-CoV and MERS-CoV, to uncover shared pathways and elucidate their common disease progression and viral replication mechanisms.

Materials and methods

We developed CompCorona, the first interactive online tool for visualizing gene response variance among the family Coronaviridae through 2D and 3D principal component analysis (PCA) and exploring systems biology variance using pathway plots. We also made preprocessed datasets of lungs and PBMCs infected by SARS-CoV-2, SARS-CoV, and MERS-CoV publicly available through CompCorona.

Results

One remarkable finding from the lung and PBMC datasets for infections by SARS-CoV-2, but not infections by other coronaviruses (CoVs), was the significant downregulation of the angiogenin (ANG) and vascular endothelial growth factor A (VEGFA) genes, both directly involved in epithelial and vascular endothelial cell dysfunction. Suppression of the TNF signaling pathway was also observed in cells infected by SARS-CoV-2, along with simultaneous activation of complement and coagulation cascades and pertussis pathways. The ribosome pathway was found to be universally suppressed across all three viruses. The CompCorona online tool enabled the comparative analysis of 9 preprocessed host transcriptome datasets of cells infected by CoVs, revealing the specific host response differences in cases of SARS-CoV-2 infection. This included identifying markers of epithelial dysfunction via interactive 2D and 3D PCA, Venn diagrams, and pathway plots.

Conclusion

Our findings suggest that infection by SARS-CoV-2 might induce pulmonary epithelial dysfunction, a phenomenon not observed in cells infected by other CoVs. The publicly available CompCorona tool, along with the preprocessed datasets of cells infected by various CoVs, constitutes a valuable resource for further research into CoV-associated syndromes.

Comparative transcriptome analysis of SARS-CoV-2, SARS-CoV, MERS-CoV, and HCoV-229E identifying potential IFN/ISGs targets for inhibiting virus replication

Introduction

Since its outbreak in December 2019, SARS-CoV-2 has spread rapidly across the world, posing significant threats and challenges to global public health. SARS-CoV-2, together with SARS-CoV and MERS-CoV, is a highly pathogenic coronavirus that contributes to fatal pneumonia. Understanding the similarities and differences at the transcriptome level between SARS-CoV-2, SARS-CoV, as well as MERS-CoV is critical for developing effective strategies against these viruses.

Methods

In this article, we comparatively analyzed publicly available transcriptome data of human cell lines infected with highly pathogenic SARS-CoV-2, SARS-CoV, MERS-CoV, and lowly pathogenic HCoV-229E. The host gene expression profiles during human coronavirus (HCoV) infections were generated, and the pathways and biological functions involved in immune responses, antiviral efficacy, and organ damage were intensively elucidated.

Results

Our results indicated that SARS-CoV-2 induced a stronger immune response versus the other two highly pathogenic HCoVs. Specifically, SARS-CoV-2 induced robust type I and type III IFN responses, marked by higher upregulation of type I and type III IFNs, as well as numerous interferon-stimulated genes (ISGs). Further Ingenuity Pathway Analysis (IPA) revealed the important role of ISGs for impeding SARS-CoV-2 infection, and the interferon/ISGs could be potential targets for therapeutic interventions. Moreover, our results uncovered that SARS-CoV-2 infection was linked to an enhanced risk of multi-organ toxicity in contrast to the other two highly pathogenic HCoVs.

Discussion

These findings provided valuable insights into the pathogenic mechanism of SARS-CoV-2, which showed a similar pathological feature but a lower fatality rate compared to SARS-CoV and MERS-CoV.

Virus-specific and shared gene expression signatures in immune cells after vaccination in response to influenza and vaccinia stimulation

Background

In the vaccine era, individuals receive multiple vaccines in their lifetime. Host gene expression in response to antigenic stimulation is usually virus-specific; however, identifying shared pathways of host response across a wide spectrum of vaccine pathogens can shed light on the molecular mechanisms/components which can be targeted for the development of broad/universal therapeutics and vaccines.

Method

We isolated PBMCs, monocytes, B cells, and CD8+ T cells from the peripheral blood of healthy donors, who received both seasonal influenza vaccine (within <1 year) and smallpox vaccine (within 1 - 4 years). Each of the purified cell populations was stimulated with either influenza virus or vaccinia virus. Differentially expressed genes (DEGs) relative to unstimulated controls were identified for each in vitro viral infection, as well as for both viral infections (shared DEGs). Pathway enrichment analysis was performed to associate identified DEGs with KEGG/biological pathways.

Results

We identified 2,906, 3,888, 681, and 446 DEGs in PBMCs, monocytes, B cells, and CD8+ T cells, respectively, in response to influenza stimulation. Meanwhile, 97, 120, 20, and 10 DEGs were identified as gene signatures in PBMCs, monocytes, B cells, and CD8+ T cells, respectively, upon vaccinia stimulation. The majority of DEGs identified in PBMCs were also found in monocytes after either viral stimulation. Of the virus-specific DEGs, 55, 63, and 9 DEGs occurred in common in PBMCs, monocytes, and B cells, respectively, while no DEGs were shared in infected CD8+ T cells after influenza and vaccinia. Gene set enrichment analysis demonstrated that these shared DEGs were over-represented in innate signaling pathways, including cytokine-cytokine receptor interaction, viral protein interaction with cytokine and cytokine receptor, Toll-like receptor signaling, RIG-I-like receptor signaling pathways, cytosolic DNA-sensing pathways, and natural killer cell mediated cytotoxicity.

Conclusion

Our results provide insights into virus-host interactions in different immune cells, as well as host defense mechanisms against viral stimulation. Our data also highlights the role of monocytes as a major cell population driving gene expression in ex vivo PBMCs in response to viral stimulation. The immune response signaling pathways identified in this study may provide specific targets for the development of novel virus-specific therapeutics and improved vaccines for vaccinia and influenza. Although influenza and vaccinia viruses have been selected in this study as pathogen models, this approach could be applicable to other pathogens.

Machine learning-driven blood transcriptome-based discovery of SARS-CoV-2 specific severity biomarkers

The Coronavirus disease 2019 (COVID-19) pandemic, caused by rapidly evolving variants of severe acute respiratory syndrome coronavirus (SARS-CoV-2), continues to be a global health threat. SARS-CoV-2 infection symptoms often intersect with other nonsevere respiratory infections, making early diagnosis challenging. There is an urgent need for early diagnostic and prognostic biomarkers to predict severity and reduce mortality when a sudden outbreak occurs. This study implemented a novel approach of integrating bioinformatics and machine learning algorithms over publicly available clinical COVID-19 transcriptome data sets. The robust 7-gene biomarker identified through this analysis can not only discriminate SARS-CoV-2 associated acute respiratory illness (ARI) from other types of ARIs but also can discriminate severe COVID-19 patients from nonsevere COVID-19 patients. Validation of the 7-gene biomarker in an independent blood transcriptome data set of longitudinal analysis of COVID-19 patients across various stages of the disease showed that the dysregulation of the identified biomarkers during severe disease is restored during recovery, showing their prognostic potential. The blood biomarkers identified in this study can serve as potential diagnostic candidates and help reduce COVID-19-associated mortality.

Protein Arginylation Is Regulated during SARS-CoV-2 Infection

BACKGROUND

In 2019, the world witnessed the onset of an unprecedented pandemic. By February 2022, the infection by SARS-CoV-2 has already been responsible for the death of more than 5 million people worldwide. Recently, we and other groups discovered that SARS-CoV-2 infection induces ER stress and activation of the unfolded protein response (UPR) pathway. Degradation of misfolded/unfolded proteins is an essential element of proteostasis and occurs mainly in lysosomes or proteasomes. The N-terminal arginylation of proteins is characterized as an inducer of ubiquitination and proteasomal degradation by the N-degron pathway.

RESULTS

The role of protein arginylation during SARS-CoV-2 infection was elucidated. Protein arginylation was studied in Vero CCL-81, macrophage-like THP1, and Calu-3 cells infected at different times. A reanalysis of in vivo and in vitro public omics data combined with immunoblotting was performed to measure levels of arginyl-tRNA-protein transferase (ATE1) and its substrates. Dysregulation of the N-degron pathway was specifically identified during coronavirus infections compared to other respiratory viruses. We demonstrated that during SARS-CoV-2 infection, there is an increase in ATE1 expression in Calu-3 and Vero CCL-81 cells. On the other hand, infected macrophages showed no enzyme regulation. ATE1 and protein arginylation was variant-dependent, as shown using P1 and P2 viral variants and HEK 293T cells transfection with the spike protein and receptor-binding domains (RBD). In addition, we report that ATE1 inhibitors, tannic acid and merbromine (MER) reduce viral load. This finding was confirmed in ATE1-silenced cells.

CONCLUSIONS

We demonstrate that ATE1 is increased during SARS-CoV-2 infection and its inhibition has potential therapeutic value.

Plant Molecular Pharming and Plant-Derived Compounds towards Generation of Vaccines and Therapeutics against Coronaviruses

The current century has witnessed infections of pandemic proportions caused by Coronaviruses (CoV) including severe acute respiratory syndrome-related CoV (SARS-CoV), Middle East respiratory syndrome-related CoV (MERS-CoV) and the recently identified SARS-CoV2. Significantly, the SARS-CoV2 outbreak, declared a pandemic in early 2020, has wreaked devastation and imposed intense pressure on medical establishments world-wide in a short time period by spreading at a rapid pace, resulting in high morbidity and mortality. Therefore, there is a compelling need to combat and contain the CoV infections. The current review addresses the unique features of the molecular virology of major Coronaviruses that may be tractable towards antiviral targeting and design of novel preventative and therapeutic intervention strategies. Plant-derived vaccines, in particular oral vaccines, afford safer, effectual and low-cost avenues to develop antivirals and fast response vaccines, requiring minimal infrastructure and trained personnel for vaccine administration in developing countries. This review article discusses recent developments in the generation of plant-based vaccines, therapeutic/drug molecules, monoclonal antibodies and phytochemicals to preclude and combat infections caused by SARS-CoV, MERS-CoV and SARS-CoV-2 viruses. Efficacious plant-derived antivirals could contribute significantly to combating emerging and re-emerging pathogenic CoV infections and help stem the tide of any future pandemics.

Transcriptomics and RNA-Based Therapeutics as Potential Approaches to Manage SARS-CoV-2 Infection

SARS-CoV-2 is a coronavirus family member that appeared in China in December 2019 and caused the disease called COVID-19, which was declared a pandemic in 2020 by the World Health Organization. In recent months, great efforts have been made in the field of basic and clinical research to understand the biology and infection processes of SARS-CoV-2. In particular, transcriptome analysis has contributed to generating new knowledge of the viral sequences and intracellular signaling pathways that regulate the infection and pathogenesis of SARS-CoV-2, generating new information about its biology. Furthermore, transcriptomics approaches including spatial transcriptomics, single-cell transcriptomics and direct RNA sequencing have been used for clinical applications in monitoring, detection, diagnosis, and treatment to generate new clinical predictive models for SARS-CoV-2. Consequently, RNA-based therapeutics and their relationship with SARS-CoV-2 have emerged as promising strategies to battle the SARS-CoV-2 pandemic with the assistance of novel approaches such as CRISPR-CAS, ASOs, and siRNA systems. Lastly, we discuss the importance of precision public health in the management of patients infected with SARS-CoV-2 and establish that the fusion of transcriptomics, RNA-based therapeutics, and precision public health will allow a linkage for developing health systems that facilitate the acquisition of relevant clinical strategies for rapid decision making to assist in the management and treatment of the SARS-CoV-2-infected population to combat this global public health problem.

SARS-CoV-2 potential drugs, drug targets, and biomarkers: a viral-host interaction network-based analysis

COVID-19 is a global pandemic impacting the daily living of millions. As variants of the virus evolve, a complete comprehension of the disease and drug targets becomes a decisive duty. The Omicron variant, for example, has a notably high transmission rate verified in 155 countries. We performed integrative transcriptomic and network analyses to identify drug targets and diagnostic biomarkers and repurpose FDA-approved drugs for SARS-CoV-2. Upon the enrichment of 464 differentially expressed genes, pathways regulating the host cell cycle were significant. Regulatory and interaction networks featured hsa-mir-93-5p and hsa-mir-17-5p as blood biomarkers while hsa-mir-15b-5p as an antiviral agent. MYB, RRM2, ERG, CENPF, CIT, and TOP2A are potential drug targets for treatment. HMOX1 is suggested as a prognostic biomarker. Enhancing HMOX1 expression by neem plant extract might be a therapeutic alternative. We constructed a drug-gene network for FDA-approved drugs to be repurposed against the infection. The key drugs retrieved were members of anthracyclines, mitotic inhibitors, anti-tumor antibiotics, and CDK1 inhibitors. Additionally, hydroxyquinone and digitoxin are potent TOP2A inhibitors. Hydroxyurea, cytarabine, gemcitabine, sotalol, and amiodarone can also be redirected against COVID-19. The analysis enforced the repositioning of fluorouracil and doxorubicin, especially that they have multiple drug targets, hence less probability of resistance.

HYGIEIA: HYpothesizing the Genesis of Infectious Diseases and Epidemics through an Integrated Systems Biology Approach

More than two years on, the COVID-19 pandemic continues to wreak havoc around the world and has battle-tested the pandemic-situation responses of all major global governments. Two key areas of investigation that are still unclear are: the molecular mechanisms that lead to heterogenic patient outcomes, and the causes of Post COVID condition (AKA Long-COVID). In this paper, we introduce the HYGIEIA project, designed to respond to the enormous challenges of the COVID-19 pandemic through a multi-omic approach supported by network medicine. It is hoped that in addition to investigating COVID-19, the logistics deployed within this project will be applicable to other infectious agents, pandemic-type situations, and also other complex, non-infectious diseases. Here, we first look at previous research into COVID-19 in the context of the proteome, metabolome, transcriptome, microbiome, host genome, and viral genome. We then discuss a proposed methodology for a large-scale multi-omic longitudinal study to investigate the aforementioned biological strata through high-throughput sequencing (HTS) and mass-spectrometry (MS) technologies. Lastly, we discuss how a network medicine approach can be used to analyze the data and make meaningful discoveries, with the final aim being the translation of these discoveries into the clinics to improve patient care.

Differing coronavirus genres alter shared host signaling pathways upon viral infection

Coronaviruses are important viral pathogens across a range of animal species including humans. They have a high potential for cross-species transmission as evidenced by the emergence of COVID-19 and may be the origin of future pandemics. There is therefore an urgent need to study coronaviruses in depth and to identify new therapeutic targets. This study shows that distant coronaviruses such as Alpha-, Beta-, and Deltacoronaviruses can share common host immune associated pathways and genes. Differentially expressed genes (DEGs) in the transcription profile of epithelial cell lines infected with swine acute diarrhea syndrome, severe acute respiratory syndrome coronavirus 2, or porcine deltacoronavirus, showed that DEGs within 10 common immune associated pathways were upregulated upon infection. Twenty Three pathways and 21 DEGs across 10 immune response associated pathways were shared by these viruses. These 21 DEGs can serve as focused targets for therapeutics against newly emerging coronaviruses. We were able to show that even though there is a positive correlation between PDCoV and SARS-CoV-2 infections, these viruses could be using different strategies for efficient replication in their cells from their natural hosts. To the best of our knowledge, this is the first report of comparative host transcriptome analysis across distant coronavirus genres.

Chikungunya virus time course infection of human macrophages reveals intracellular signaling pathways relevant to repurposed therapeutics

Background

Chikungunya virus (CHIKV) is a mosquito-borne pathogen, within the Alphavirus genus of the Togaviridae family, that causes ~1.1 million human infections annually. CHIKV uses Aedes albopictus and Aedes aegypti mosquitoes as insect vectors. Human infections can develop arthralgia and myalgia, which results in debilitating pain for weeks, months, and even years after acute infection. No therapeutic treatments or vaccines currently exist for many alphaviruses, including CHIKV. Targeting the phagocytosis of CHIKV by macrophages after mosquito transmission plays an important role in early productive viral infection in humans, and could reduce viral replication and/or symptoms.

Methods

To better characterize the transcriptional response of macrophages during early infection, we generated RNA-sequencing data from a CHIKV-infected human macrophage cell line at eight or 24 hours post-infection (hpi), together with mock-infected controls. We then calculated differential gene expression, enriched functional annotations, modulated intracellular signaling pathways, and predicted therapeutic drugs from these sequencing data.

Results

We observed 234 pathways were significantly affected 24 hpi, resulting in six potential pharmaceutical treatments to modulate the affected pathways. A subset of significant pathways at 24 hpi includes AGE-RAGE, Fc epsilon RI, Chronic myeloid leukemia, Fc gamma R-mediated phagocytosis, and Ras signaling. We found that the MAPK1 and MAPK3 proteins are shared among this subset of pathways and that Telmisartan and Dasatinib are strong candidates for repurposed small molecule therapeutics that target human processes. The results of our analysis can be further characterized in the wet lab to contribute to the development of host-based prophylactics and therapeutics.

Evolutionary history of the SARS-CoV-2 Gamma variant of concern (P.1): a perfect storm

Our goal was to describe in more detail the evolutionary history of Gamma and two derived lineages (P.1.1 and P.1.2), which are part of the arms race that SARS-CoV-2 wages with its host. A total of 4,977 sequences of the Gamma strain of SARS-CoV-2 from Brazil were analyzed. We detected 194 sites under positive selection in 12 genes/ORFs: Spike, N, M, E, ORF1a, ORF1b, ORF3, ORF6, ORF7a, ORF7b, ORF8, and ORF10. Some diagnostic sites for Gamma lacked a signature of positive selection in our study, but these were not fixed, apparently escaping the action of purifying selection. Our network analyses revealed branches leading to expanding haplotypes with sites under selection only detected when P.1.1 and P.1.2 were considered. The P.1.2 exclusive haplotype H_5 originated from a non-synonymous mutational step (H3509Y) in H_1 of ORF1a. The selected allele, 3509Y, represents an adaptive novelty involving ORF1a of P.1. Finally, we discuss how phenomena such as epistasis and antagonistic pleiotropy could limit the emergence of new alleles (and combinations thereof) in SARS-COV-2 lineages, maintaining infectivity in humans, while providing rapid response capabilities to face the arms race triggered by host immuneresponses.

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.

Possible Role of Accessory Proteins in the Viral Replication for the 20I/501Y.V1 (B.1.1.7) SARS CoV-2 Variant

The emergence of new severe acute respiratory syndrome coronavirus-2 (SARS CoV-2) has been a global concern. The B.1.1.7 variant of SARS CoV-2 is reported to cause higher transmission. The study investigates the replication cycle and transcriptional pattern of the B.1.1.7 to hypothesis the possible role of different genes in viral replication. It was observed that the B.1.1.7 variant required a longer maturation time. The transcriptional response demonstrated higher expression of ORF6 and ORF8 compared to nucleocapsid transcript till the eclipse period which might influence higher viral replication. The number of infectious viruses titer is higher in the B.1.1.7, despite a lesser copy number than B.1, indicating higher transmissibility. The experimental evidence published linked ORF6 and ORF8 to play important role in replication and we also observed their higher expression. This leads us to hypothesis the possible role of ORF6 and ORF8 in B.1.1.7 higher replication which causes higher transmission.

Interactome of human and SARS-CoV-2 proteins to identify human hub proteins associated with comorbidities

SARS-CoV-2 has a higher chance of progression in adults of any age with certain underlying health conditions or comorbidities like cancer, neurological diseases and in certain cases may even lead to death. Like other viruses, SARS-CoV-2 also interacts with host proteins to pave its entry into host cells. Therefore, to understand the behaviour of SARS-CoV-2 and design of effective antiviral drugs, host-virus protein-protein interactions (PPIs) can be very useful. In this regard, we have initially created a human-SARS-CoV-2 PPI database from existing works in the literature which has resulted in 7085 unique PPIs. Subsequently, we have identified at most 10 proteins with highest degrees viz. hub proteins from interacting human proteins for individual virus protein. The identification of these hub proteins is important as they are connected to most of the other human proteins. Consequently, when they get affected, the potential diseases are triggered in the corresponding pathways, thereby leading to comorbidities. Furthermore, the biological significance of the identified hub proteins is shown using KEGG pathway and GO enrichment analysis. KEGG pathway analysis is also essential for identifying the pathways leading to comorbidities. Among others, SARS-CoV-2 proteins viz. NSP2, NSP5, Envelope and ORF10 interacting with human hub proteins like COX4I1, COX5A, COX5B, NDUFS1, CANX, HSP90AA1 and TP53 lead to comorbidities. Such comorbidities are Alzheimer, Parkinson, Huntington, HTLV-1 infection, prostate cancer and viral carcinogenesis. Subsequently, using Enrichr tool possible repurposable drugs which target the human hub proteins are reported in this paper as well. Therefore, this work provides a consolidated study for human-SARS-CoV-2 protein interactions to understand the relationship between comorbidity and hub proteins so that it may pave the way for the development of anti-viral drugs.

SARS-Coronavirus 2, A Metabolic Reprogrammer: A Review in the Context of the Possible Therapeutic Strategies

Novel coronavirus, SARS-CoV-2 is advancing at a staggering pace to devastate the health care system and foster the concerns over public health. In contrast to the past outbreaks, coronaviruses aren't clinging themselves as a strict respiratory virus. Rather, becoming a multifaceted virus, it affects multiple organs by interrupting a number of metabolic pathways leading to significant rates of morbidity and mortality. Following infection they rigorously reprogram multiple metabolic pathways of glucose, lipid, protein, nucleic acid and their metabolites to extract adequate energy and carbon skeletons required for their existence and further molecular constructions inside a host cell. Although the mechanism of these alterations are yet to be known, the impact of these reprogramming is reflected in the hyper inflammatory responses, so called cytokine storm and the hindrance of host immune defence system. The metabolic reprogramming during SARS-CoV-2 infection needs to be considered while devising therapeutic strategies to combat the disease and its further complication. The inhibitors of cholesterol and phospholipids synthesis and cell membrane lipid raft of the host cell can, to a great extent, control the viral load and further infection. Depletion of energy source by inhibiting the activation of glycolytic and hexoseamine biosynthetic pathway can also augment the antiviral therapy. The cross talk between these pathways also necessitates the inhibition of amino acid catabolism and tryptophan metabolism. A combinatorial strategy which can address the cross talks between the metabolic pathways might be more effective than a single approach and the infection stage and timing of therapy will also influence the effectiveness of the antiviral approach. We herein focus on the different metabolic alterations during the course of virus infection that help to exploit the cellular machinery and devise a therapeutic strategy which promotes resistance to viral infection and can augment body's antivirulence mechanisms. This review may cast the light into the possibilities of targeting altered metabolic pathways to defend virus infection in a new perspective.

Evolutionary selectivity of amino acid is inspired from the enhanced structural stability and flexibility of the folded protein

AIM

The present study attempts to decipher the site-specific amino acid alterations at certain positions experiencing preferential selectivity and their effect on proteins' stability and flexibility. The study examines the selection preferences by considering pair-wise non-bonded interaction energies of adjacent and interacting amino acids present at the interacting site, along with their evolutionary history.

MATERIALS AND METHODS

For the study, variations in the interacting residues of spike protein (S-Protein) receptor-binding domain (RBD) of different coronaviruses were examined. The MD simulation trajectory analysis revealed that, though all the variants studied were structurally stable at their native and bound confirmations, the RBD of 2019-nCoV/SARS-CoV-2 was found to be more flexible and more dynamic. Furthermore, a noticeable change observed in the non-bonded interaction energies of the amino acids interacting with the receptor corroborated their selection at respective positions.

KEY FINDINGS

The conformational changes exerted by the altered amino acids could be the reason for a broader range of interacting receptors among the selected proteins.

SIGNIFICANCE

The results envisage a strong indication that the residue selection at certain positions is governed by a well-orchestrated feedback mechanism, which follows increased stability and flexibility in the folded structure compared to its evolutionary predecessor.

Hyperactivated RAGE in Comorbidities as a Risk Factor for Severe COVID-19-The Role of RAGE-RAS Crosstalk

The receptor for advanced glycation-end products (RAGE) is a multiligand receptor with a role in inflammatory and pulmonary pathologies. Hyperactivation of RAGE by its ligands has been reported to sustain inflammation and oxidative stress in common comorbidities of severe COVID-19. RAGE is essential to the deleterious effects of the renin-angiotensin system (RAS), which participates in infection and multiorgan injury in COVID-19 patients. Thus, RAGE might be a major player in severe COVID-19, and appears to be a useful therapeutic molecular target in infections by SARS-CoV-2. The role of RAGE gene polymorphisms in predisposing patients to severe COVID-19 is discussed.&nbsp.

The differences in SARS-CoV and SARS-CoV-2 specific co-expression network mediated biological process in human gut enterocytes

Novel coronavirus SARS-CoV-2 was recently outbreak worldwide causes severe acute respiratory syndrome along with gastrointestinal symptoms for some infected patients. Information on detail pathogenesis, host immune responses and responsible biological pathways are limited. Therefore, infection specific host gut responses and dietary supplements to neutralize immune inflammation demand extensive research. This study aimed to find differences in global co-expression protein-protein interaction sub-network and enriched biological processes in SARS-CoV and SARS-CoV-2 infected gut enterocytes cell line. Attempts have also been made to predict some dietary supplements to boost human health. The SARS-CoV and SARS-CoV-2 infected differential express proteins were integrated with the human protein interaction network and co-expression subnetworks were constructed. Common hubs of these sub-networks reshape central cellular pathways of metabolic processes, lipid localization, hypoxia response to decrease oxygen level and transport of bio-molecules. The major biological process enriched in the unique hub of SARS-CoV-2 significantly differ from SARS-CoV, related to interferon signaling, regulation of viral process and influenza-A enzymatic pathway. Predicted dietary supplements can improve SARS-CoV-2 infected person’'s health by boosting the host immunity/reducing inflammation. To the best of our knowledge this is the first report on co-expression network mediated biological process in human gut enterocytes to predict dietary supplements/compounds.

Identification of 37 Heterogeneous Drug Candidates for Treatment of COVID-19 via a Rational Transcriptomics-Based Drug Repurposing Approach

A year after the initial outbreak, the COVID-19 pandemic caused by SARS-CoV-2 virus remains a serious threat to global health, while current treatment options are insufficient to bring major improvements. The aim of this study is to identify repurposable drug candidates with a potential to reverse transcriptomic alterations in the host cells infected by SARS-CoV-2. We have developed a rational computational pipeline to filter publicly available transcriptomic datasets of SARS-CoV-2-infected biosamples based on their responsiveness to the virus, to generate a list of relevant differentially expressed genes, and to identify drug candidates for repurposing using LINCS connectivity map. Pathway enrichment analysis was performed to place the results into biological context. We identified 37 structurally heterogeneous drug candidates and revealed several biological processes as druggable pathways. These pathways include metabolic and biosynthetic processes, cellular developmental processes, immune response and signaling pathways, with steroid metabolic process being targeted by half of the drug candidates. The pipeline developed in this study integrates biological knowledge with rational study design and can be adapted for future more comprehensive studies. Our findings support further investigations of some drugs currently in clinical trials, such as itraconazole and imatinib, and suggest 31 previously unexplored drugs as treatment options for COVID-19.