Unveiling COVID-19-associated organ-specific cell types and cell-specific pathway cascade

SARS-CoV-2 mechanisms of cell tropism in various organs considering host factors

A critical step in the drug design for SARS-CoV-2 is to discover its molecular targets. This study comprehensively reviewed the molecular mechanisms of SARS-CoV-2, exploring host cell tropism and interaction targets crucial for cell entry. The findings revealed that beyond ACE2 as the primary entry receptor, alternative receptors, co-receptors, and several proteases such as TMPRSS2, Furin, Cathepsin L, and ADAM play critical roles in virus entry and subsequent pathogenesis. Additionally, SARS-CoV-2 displays tropism in various human organs due to its diverse receptors. This review delves into the intricate details of receptors, host proteases, and the involvement of each organ. Polymorphisms in the ACE2 receptor and mutations in the spike or its RBD region contribute to the emergence of variants like Alpha, Beta, Gamma, Delta, and Omicron, impacting the pathogenicity of SARS-CoV-2. The challenge posed by mutations raises questions about the effectiveness of existing vaccines and drugs, necessitating consideration for updates in their formulations. In the urgency of these critical situations, repurposed drugs such as Camostat Mesylate and Nafamostat Mesylate emerge as viable pharmaceutical options. Numerous drugs are involved in inhibiting receptors and host factors crucial for SARS-CoV-2 entry, with most discussed in this review. In conclusion, this study may provide valuable insights to inform decisions in therapeutic approaches.

Liver in infections: a single-cell and spatial transcriptomics perspective

The liver is an immune organ that plays a vital role in the detection, capture, and clearance of pathogens and foreign antigens that invade the human body. During acute and chronic infections, the liver transforms from a tolerant to an active immune state. The defence mechanism of the liver mainly depends on a complicated network of intrahepatic and translocated immune cells and non-immune cells. Therefore, a comprehensive liver cell atlas in both healthy and diseased states is needed for new therapeutic target development and disease intervention improvement. With the development of high-throughput single-cell technology, we can now decipher heterogeneity, differentiation, and intercellular communication at the single-cell level in sophisticated organs and complicated diseases. In this concise review, we aimed to summarise the advancement of emerging high-throughput single-cell technologies and re-define our understanding of liver function towards infections, including hepatitis B virus, hepatitis C virus, Plasmodium, schistosomiasis, endotoxemia, and corona virus disease 2019 (COVID-19). We also unravel previously unknown pathogenic pathways and disease mechanisms for the development of new therapeutic targets. As high-throughput single-cell technologies mature, their integration into spatial transcriptomics, multiomics, and clinical data analysis will aid in patient stratification and in developing effective treatment plans for patients with or without liver injury due to infectious diseases.

Haplotypic variants of COVID-19 related genes are associated with blood pressure and metabolites levels

The genetic association of coronavirus disease 2019 (COVID-19) with its complications has not been fully understood. This study aimed to identify variants and haplotypes of candidate genes implicated in COVID-19 related traits by combining the literature review and pathway analysis. To explore such genes, the protein-protein interactions and relevant pathways of COVID-19-associated genes were assessed. A number of variants on candidate genes were identified from Genome-wide association studies (GWASs) which were associated with COVID-19 related traits (p ˂ 10^-6 ). Haplotypic blocks were assessed using haplotypic structures among the 1000 Genomes Project (r²  ≥ 0.8, D' ≥ 0.8). Further functional analyses were performed on the selected variants. The results demonstrated that a group of variants in ACE and AGT genes were significantly correlated with COVID-19 related traits. Three haplotypes were identified to be involved in the blood metabolites levels and the development of blood pressure. Functional analyses revealed that most GWAS index variants were expression quantitative trait loci and had transcription factor binding sites, exonic splicing enhancers or silencer activities. Furthermore, the proxy haplotype variants, rs4316, rs4353, rs4359, and three variants, namely rs2493133, rs2478543, and rs5051, were associated with blood metabolite and systolic blood pressure, respectively. These variants exerted more regulatory effects compared with other GWAS variants. The present study indicates that the genetic variants and candidate haplotypes of COVID-19 related genes are associated with blood pressure and blood metabolites. However, further observational studies are warranted to confirm these results.

Antiviral Potential of Small Molecules Cordycepin, Thymoquinone, and N6, N6-Dimethyladenosine Targeting SARS-CoV-2 Entry Protein ADAM17

COVID-19 is an acute respiratory disease caused by SARS-CoV-2 that has spawned a worldwide pandemic. ADAM17 is a sheddase associated with the modulation of the receptor ACE2 of SARS-CoV-2. Studies have revealed that malignant phenotypes of several cancer types are closely relevant to highly expressed ADAM17. However, ADAM17 regulation in SARS-CoV-2 invasion and its role on small molecules are unclear. Here, we evaluated the ADAM17 inhibitory effects of cordycepin (CD), thymoquinone (TQ), and N6, N6-dimethyladenosine (m⁶₂A), on cancer cells and predicted the anti-COVID-19 potential of the three compounds and their underlying signaling pathways by network pharmacology. It was found that CD, TQ, and m⁶₂A repressed the ADAM17 expression upon different cancer cells remarkably. Moreover, CD inhibited GFP-positive syncytia formation significantly, suggesting its potential against SARS-CoV-2. Pharmacological analysis by constructing CD-, TQ-, and m⁶₂A-based drug-target COVID-19 networks further indicated that ADAM17 is a potential target for anti-COVID-19 therapy with these compounds, and the mechanism might be relevant to viral infection and transmembrane receptors-mediated signal transduction. These findings imply that ADAM17 is of potentially medical significance for cancer patients infected with SARS-CoV-2, which provides potential new targets and insights for developing innovative drugs against COVID-19.

In silico strategies to identify protein-protein interaction modulator in cell-to-cell transmission of SARS CoV2

RNA sequence data from SARS CoV2 patients helps to construct a gene network related to this disease. A detailed analysis of the human host response to SARS CoV2 with expression profiling by high-throughput sequencing has been accomplished with primary human lung epithelial cell lines. Using this data, the clustered gene annotation and gene network construction are performed with the help of the String database. Among the four clusters identified, only 1 with 44 genes could be annotated. Interestingly, this corresponded to basal cells with p = 1.37e - 05, which is relevant for respiratory tract infection. Functional enrichment analysis of genes present in the gene network has been completed using the String database and the Network Analyst tool. Among three types of cell-cell communication, only the anchoring junction between the basal cell membrane and the basal lamina in the host cell is involved in the virus transmission. In this junction point, a hemidesmosome structure plays a vital role in virus spread from one cell to basal lamina in the respiratory tract. In this protein complex structure, different integrin protein molecules of the host cell are used to promote the spread of virus infection into the extracellular matrix. So, small molecular blockers of different anchoring junction proteins, such as integrin alpha 3, integrin beta 1, can provide efficient protection against this deadly viral disease. ORF8 from SARS CoV2 virus can interact with both integrin proteins of human host. By using molecular docking technique, a ternary complex of these three proteins is modelled. Several oligopeptides are predicted as modulators for this ternary complex. In silico analysis of these modulators is very important to develop novel therapeutics for the treatment of SARS CoV2.

Mesenchymal stem cells and their derived small extracellular vesicles for COVID-19 treatment

Since December 2019, the coronavirus (COVID-19) pandemic has imposed huge burdens to the whole world, seriously affecting global economic growth, and threatening people’s lives and health. At present, some therapeutic regimens are available for treatment of COVID-19 pneumonia, including antiviral therapy, immunity therapy, anticoagulant therapy, and others. Among them, injection of mesenchymal stem cells (MSCs) is currently a promising therapy. The preclinical studies and clinical trials using MSCs and small extracellular vesicles derived from MSCs (MSC-sEVs) in treating COVID-19 were summarized. Then, the molecular mechanism, feasibility, and safety of treating COVID-19 with MSCs and MSC-sEVs were also discussed.

Glycyrrhetinic acid: A potential drug for the treatment of COVID-19 cytokine storm

BACKGROUND

The cytokine storm (CS) triggered by coronavirus disease 2019 (COVID-19) has caused serious harm to health of humanity and huge economic burden to the world, and there is a lack of effective methods to treat this complication.

PURPOSE

In this research, we used network pharmacology and molecular docking to reveal the interaction mechanism in the glycyrrhetinic acid (GA) for the treatment of CS, and validated the effect of GA intervention CS by experiments.

STUDY DESIGN

First, we screened corresponding target of GA and CS from online databases, and obtained the action target genes through the Venn diagram. Then, protein-protein interaction (PPI) network, Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment of the action target genes were acquired by R language to predict its mechanism. Next, molecular docking was performed on core targets. Finally, experiments in which GA intervened in lipopolysaccharide (LPS)-induced CS were implemented.

RESULTS

84 action target genes were obtained from online database. The PPI network of target genes showed that TNF, IL6, MAPK3, PTGS2, ESR1 and PPARG were considered as the core genes. The results of GO and KEGG showed that action target genes were closely related to inflammatory and immune related signaling pathways, such as TNF signaling pathway, IL-17 signaling pathway, Human cytomegalovirus infection, PPAR signaling pathway and so on. Molecule docking results prompted that GA had fine affinity with IL6 and TNF proteins. Finally, in vivo and in vitro experimental results showed that GA could significantly inhibit LPS-induced CS.

CONCLUSION

GA has a potential inhibitory effect on CS, which is worthy of further exploration.

Network-based integrative analysis of single-cell transcriptomic and epigenomic data for cell types

Advances in single-cell biotechnologies simultaneously generate the transcriptomic and epigenomic profiles at cell levels, providing an opportunity for investigating cell fates. Although great efforts have been devoted to either of them, the integrative analysis of single-cell multi-omics data is really limited because of the heterogeneity, noises and sparsity of single-cell profiles. In this study, a network-based integrative clustering algorithm (aka NIC) is present for the identification of cell types by fusing the parallel single-cell transcriptomic (scRNA-seq) and epigenomic profiles (scATAC-seq or DNA methylation). To avoid heterogeneity of multi-omics data, NIC automatically learns the cell–cell similarity graphs, which transforms the fusion of multi-omics data into the analysis of multiple networks. Then, NIC employs joint non-negative matrix factorization to learn the shared features of cells by exploiting the structure of learned cell–cell similarity networks, providing a better way to characterize the features of cells. The graph learning and integrative analysis procedures are jointly formulated as an optimization problem, and then the update rules are derived. Thirteen single-cell multi-omics datasets from various tissues and organisms are adopted to validate the performance of NIC, and the experimental results demonstrate that the proposed algorithm significantly outperforms the state-of-the-art methods in terms of various measurements. The proposed algorithm provides an effective strategy for the integrative analysis of single-cell multi-omics data (The software is coded using Matlab, and is freely available for academic https://github.com/xkmaxidian/NIC ).

Single-cell RNA analysis reveals the potential risk of organ-specific cell types vulnerable to SARS-CoV-2 infections

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global pandemic of coronavirus disease 2019 (COVID-19) since December 2019 that has led to more than 160 million confirmed cases, including 3.3 million deaths. To understand the mechanism by which SARS-CoV-2 invades human cells and reveal organ-specific susceptible cell types for COVID-19, we conducted comprehensive bioinformatic analysis using public single-cell RNA sequencing datasets. Utilizing the expression information of six confirmed COVID-19 receptors (ACE2, TMPRSS2, NRP1, AXL, FURIN and CTSL), we demonstrated that macrophages are the most likely cells that may be associated with SARS-CoV-2 pathogenesis in lung. Besides the widely reported 'chemokine storm', we identified ribosome related pathways that may also be potential therapeutic target for COVID-19 lung infection patients. Moreover, cell-cell communication analysis and trajectory analysis revealed that M1-like macrophages showed the highest relation to severe COVID-19 patients. And we also demonstrated that up-regulation of chemokine pathways generally lead to severe symptoms, while down-regulation of ribosome and RNA activity related pathways are more likely to be mild. Other organ-specific susceptible cell type analyses could also provide potential targets for COVID-19 therapy. This work can provide clues for understanding the pathogenesis of COVID-19 and contribute to understanding the mechanism by which SARS-CoV-2 invades human cells.

Coronavirus Infection-Associated Cell Death Signaling and Potential Therapeutic Targets

COVID-19 is the name of the disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection that occurred in 2019. The virus-host-specific interactions, molecular targets on host cell deaths, and the involved signaling are crucial issues, which become potential targets for treatment. Spike protein, angiotensin-converting enzyme 2 (ACE2), cathepsin L-cysteine peptidase, transmembrane protease serine 2 (TMPRSS2), nonstructural protein 1 (Nsp1), open reading frame 7a (ORF7a), viral main protease (3C-like protease (3CLpro) or Mpro), RNA dependent RNA polymerase (RdRp) (Nsp12), non-structural protein 13 (Nsp13) helicase, and papain-like proteinase (PLpro) are molecules associated with SARS-CoV infection and propagation. SARS-CoV-2 can induce host cell death via five kinds of regulated cell death, i.e., apoptosis, necroptosis, pyroptosis, autophagy, and PANoptosis. The mechanisms of these cell deaths are well established and can be disrupted by synthetic small molecules or natural products. There are a variety of compounds proven to play roles in the cell death inhibition, such as pan-caspase inhibitor (z-VAD-fmk) for apoptosis, necrostatin-1 for necroptosis, MCC950, a potent and specific inhibitor of the NLRP3 inflammasome in pyroptosis, and chloroquine/hydroxychloroquine, which can mitigate the corresponding cell death pathways. However, NF-κB signaling is another critical anti-apoptotic or survival route mediated by SARS-CoV-2. Such signaling promotes viral survival, proliferation, and inflammation by inducing the expression of apoptosis inhibitors such as Bcl-2 and XIAP, as well as cytokines, e.g., TNF. As a result, tiny natural compounds functioning as proteasome inhibitors such as celastrol and curcumin can be used to modify NF-κB signaling, providing a responsible method for treating SARS-CoV-2-infected patients. The natural constituents that aid in inhibiting viral infection, progression, and amplification of coronaviruses are also emphasized, which are in the groups of alkaloids, flavonoids, terpenoids, diarylheptanoids, and anthraquinones. Natural constituents derived from medicinal herbs have anti-inflammatory and antiviral properties, as well as inhibitory effects, on the viral life cycle, including viral entry, replication, assembly, and release of COVID-19 virions. The phytochemicals contain a high potential for COVID-19 treatment. As a result, SARS-CoV-2-infected cell death processes and signaling might be of high efficacy for therapeutic targeting effects and yielding encouraging outcomes.

Attenuation of clinical and immunological outcomes during SARS-CoV-2 infection by ivermectin

The devastating pandemic due to SARS-CoV-2 and the emergence of antigenic variants that jeopardize the efficacy of current vaccines create an urgent need for a comprehensive understanding of the pathophysiology of COVID-19, including the contribution of inflammation to disease. It also warrants for the search of immunomodulatory drugs that could improve disease outcome. Here, we show that standard doses of ivermectin (IVM), an anti-parasitic drug with potential immunomodulatory activities through the cholinergic anti-inflammatory pathway, prevent clinical deterioration, reduce olfactory deficit, and limit the inflammation of the upper and lower respiratory tracts in SARS-CoV-2-infected hamsters. Whereas it has no effect on viral load in the airways of infected animals, transcriptomic analyses of infected lungs reveal that IVM dampens type I interferon responses and modulates several other inflammatory pathways. In particular, IVM dramatically reduces the Il-6/Il-10 ratio in lung tissue and promotes macrophage M2 polarization, which might account for the more favorable clinical presentation of IVM-treated animals. Altogether, this study supports the use of immunomodulatory drugs such as IVM, to improve the clinical condition of SARS-CoV-2-infected patients.

Liver injury in the era of COVID-19

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has undoubtedly revolutionized the whole globe and given a new point of view on respiratory tract infections. Nevertheless, coronavirus disease 2019 (COVID-19) cannot be perceived as a disease limited only to pneumonia with diverse severity. More and more reports have demonstrated a wide range of possible systemic symptoms, including hepatic complications. Liver injury has been observed in a significant proportion of patients, especially in those with a severe or critical illness. COVID-19 might provoke a deterioration of liver function in patients with already diagnosed chronic liver diseases and without pre-existing liver disorders. The deterioration of liver function worsens the prognosis, increases the risk of a severe course of SARS-CoV-2 infection and prolongs the hospital stay. In general, patients who develop liver dysfunction in COVID-19 are mainly males, elderly people, and those with higher body mass index. The underlying mechanisms for hepatic failure in patients infected with SARS-CoV-2 are still unclear, nevertheless liver damage appears to be directly connected with virus-induced cytopathic effects. A liver injury observed during hospitalization might be simultaneously caused by the use of potentially hepatotoxic drugs, mainly antiviral agents. This minireview focuses on a possible relationship between COVID-19 and the liver, potential molecular mechanisms of liver damage, the characteristics of liver injury and suggested factors predisposing to hepatic manifestations in COVID-19 patients.

Topological Analysis for Sequence Variability: Case Study on more than 2K SARS-CoV-2 sequences of COVID-19 infected 54 countries in comparison with SARS-CoV-1 and MERS-CoV

The pandemic due to novel coronavirus, SARS-CoV-2 is a serious global concern now. More than thousand new COVID-19 infections are getting reported daily for this virus across the globe. Thus, the medical research communities are trying to find the remedy to restrict the spreading of this virus, while the vaccine development work is still under research in parallel. In such critical situation, not only the medical research community, but also the scientists in different fields like microbiology, pharmacy, bioinformatics and data science are also sharing effort to accelerate the process of vaccine development, virus prediction, forecasting the transmissible probability and reproduction cases of virus for social awareness. With the similar context, in this article, we have studied sequence variability of the virus primarily focusing on three aspects: (a) sequence variability among SARS-CoV-1, MERS-CoV and SARS-CoV-2 in human host, which are in the same coronavirus family, (b) sequence variability of SARS-CoV-2 in human host for 54 different countries and (c) sequence variability between coronavirus family and country specific SARS-CoV-2 sequences in human host. For this purpose, as a case study, we have performed topological analysis of 2391 global genomic sequences of SARS-CoV-2 in association with SARS-CoV-1 and MERS-CoV using an integrated semi-alignment based computational technique. The results of the semi-alignment based technique are experimentally and statistically found similar to alignment based technique and computationally faster. Moreover, the outcome of this analysis can help to identify the nations with homogeneous SARS-CoV-2 sequences, so that same vaccine can be applied to their heterogeneous human population.