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1.
Cell Mol Biol Lett ; 27(1): 6, 2022 Jan 11.
Article in English | MEDLINE | ID: covidwho-1622208

ABSTRACT

Coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), is associated with a high mortality rate. The majority of deaths in this disease are caused by ARDS (acute respiratory distress syndrome) followed by cytokine storm and coagulation complications. Although alterations in the level of the number of coagulation factors have been detected in samples from COVID-19 patients, the direct molecular mechanism which has been involved in this pathologic process has not been explored yet. The PI3K/AKT signaling pathway is an intracellular pathway which plays a central role in cell survival. Also, in recent years the association between this pathway and coagulopathies has been well clarified. Therefore, based on the evidence on over-activity of the PI3K/AKT signaling pathway in SARS-CoV-2 infection, in the current review, the probable role of this cellular pathway as a therapeutic target for the prevention of coagulation complications in patients with COVID-19 is discussed.


Subject(s)
Blood Coagulation Disorders/etiology , Blood Coagulation , COVID-19/complications , Phosphatidylinositol 3-Kinases/metabolism , Proto-Oncogene Proteins c-akt/metabolism , Signal Transduction , Animals , Blood Coagulation Disorders/blood , Blood Coagulation Disorders/metabolism , COVID-19/blood , COVID-19/metabolism , Humans , Inflammation/blood , Inflammation/etiology , Inflammation/metabolism , Molecular Targeted Therapy , SARS-CoV-2/physiology
3.
Nucleic Acids Res ; 50(D1): D1-D10, 2022 01 07.
Article in English | MEDLINE | ID: covidwho-1607482

ABSTRACT

The 2022 Nucleic Acids Research Database Issue contains 185 papers, including 87 papers reporting on new databases and 85 updates from resources previously published in the Issue. Thirteen additional manuscripts provide updates on databases most recently published elsewhere. Seven new databases focus specifically on COVID-19 and SARS-CoV-2, including SCoV2-MD, the first of the Issue's Breakthrough Articles. Major nucleic acid databases reporting updates include MODOMICS, JASPAR and miRTarBase. The AlphaFold Protein Structure Database, described in the second Breakthrough Article, is the stand-out in the protein section, where the Human Proteoform Atlas and GproteinDb are other notable new arrivals. Updates from DisProt, FuzDB and ELM comprehensively cover disordered proteins. Under the metabolism and signalling section Reactome, ConsensusPathDB, HMDB and CAZy are major returning resources. In microbial and viral genomes taxonomy and systematics are well covered by LPSN, TYGS and GTDB. Genomics resources include Ensembl, Ensembl Genomes and UCSC Genome Browser. Major returning pharmacology resource names include the IUPHAR/BPS guide and the Therapeutic Target Database. New plant databases include PlantGSAD for gene lists and qPTMplants for post-translational modifications. The entire Database Issue is freely available online on the Nucleic Acids Research website (https://academic.oup.com/nar). Our latest update to the NAR online Molecular Biology Database Collection brings the total number of entries to 1645. Following last year's major cleanup, we have updated 317 entries, listing 89 new resources and trimming 80 discontinued URLs. The current release is available at http://www.oxfordjournals.org/nar/database/c/.


Subject(s)
Databases, Factual , Molecular Biology , Animals , COVID-19 , Databases, Nucleic Acid , Databases, Protein , Genome, Microbial , Genome, Viral , Humans , Mice , Plants/genetics , Protein Processing, Post-Translational , Proteome , SARS-CoV-2/genetics , Signal Transduction
4.
Signal Transduct Target Ther ; 7(1): 7, 2022 01 04.
Article in English | MEDLINE | ID: covidwho-1606287

ABSTRACT

Activation-induced cytidine deaminase (AID) initiates class-switch recombination and somatic hypermutation (SHM) in antibody genes. Protein expression and activity are tightly controlled by various mechanisms. However, it remains unknown whether a signal from the extracellular environment directly affects the AID activity in the nucleus where it works. Here, we demonstrated that a deubiquitinase USP10, which specifically stabilizes nuclear AID protein, can translocate into the nucleus after AKT-mediated phosphorylation at its T674 within the NLS domain. Interestingly, the signals from BCR and TLR1/2 synergistically promoted this phosphorylation. The deficiency of USP10 in B cells significantly decreased AID protein levels, subsequently reducing neutralizing antibody production after immunization with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or human immunodeficiency virus type 1 (HIV-1) nanoparticle vaccines. Collectively, we demonstrated that USP10 functions as an integrator for both BCR and TLR signals and directly regulates nuclear AID activity. Its manipulation could be used for the development of vaccines and adjuvants.


Subject(s)
AIDS Vaccines/immunology , B-Cell Activating Factor/immunology , COVID-19 Vaccines/immunology , Cytidine Deaminase/immunology , HIV-1/immunology , Nanoparticles , SARS-CoV-2/immunology , Signal Transduction/immunology , Ubiquitin Thiolesterase/immunology , Ubiquitination/immunology , AIDS Vaccines/genetics , Animals , B-Cell Activating Factor/genetics , COVID-19 Vaccines/genetics , Cytidine Deaminase/genetics , HEK293 Cells , HIV-1/genetics , Humans , Mice , Mice, Knockout , SARS-CoV-2/genetics , Signal Transduction/genetics , Ubiquitin Thiolesterase/genetics
5.
Front Immunol ; 12: 784989, 2021.
Article in English | MEDLINE | ID: covidwho-1603282

ABSTRACT

Effective treatment strategies for severe coronavirus disease (COVID-19) remain scarce. Hydrolysis of membrane-embedded, inert sphingomyelin by stress responsive sphingomyelinases is a hallmark of adaptive responses and cellular repair. As demonstrated in experimental and observational clinical studies, the transient and stress-triggered release of a sphingomyelinase, SMPD1, into circulation and subsequent ceramide generation provides a promising target for FDA-approved drugs. Here, we report the activation of sphingomyelinase-ceramide pathway in 23 intensive care patients with severe COVID-19. We observed an increase of circulating activity of sphingomyelinase with subsequent derangement of sphingolipids in serum lipoproteins and from red blood cells (RBC). Consistent with increased ceramide levels derived from the inert membrane constituent sphingomyelin, increased activity of acid sphingomyelinase (ASM) accurately distinguished the patient cohort undergoing intensive care from healthy controls. Positive correlational analyses with biomarkers of severe clinical phenotype support the concept of an essential pathophysiological role of ASM in the course of SARS-CoV-2 infection as well as of a promising role for functional inhibition with anti-inflammatory agents in SARS-CoV-2 infection as also proposed in independent observational studies. We conclude that large-sized multicenter, interventional trials are now needed to evaluate the potential benefit of functional inhibition of this sphingomyelinase in critically ill patients with COVID-19.


Subject(s)
COVID-19/metabolism , Ceramides/metabolism , Signal Transduction , Sphingomyelin Phosphodiesterase/metabolism , Anti-Inflammatory Agents/therapeutic use , COVID-19/drug therapy , COVID-19/virology , Ceramides/blood , Enzyme Activation , Erythrocyte Membrane/metabolism , Erythrocytes/metabolism , Fatty Acids/metabolism , Humans , Intensive Care Units , Patient Acuity , SARS-CoV-2/drug effects , SARS-CoV-2/physiology , Sphingomyelin Phosphodiesterase/blood , Sphingomyelins/metabolism
6.
Am J Chin Med ; 49(8): 1965-1999, 2021.
Article in English | MEDLINE | ID: covidwho-1599109

ABSTRACT

Pulmonary fibrosis (PF) is a chronic and irreversible interstitial lung disease that even threatens the lives of some patients infected with COVID-19. PF is a multicellular pathological process, including the initial injuries of epithelial cells, recruitment of inflammatory cells, epithelial-mesenchymal transition, activation and differentiation of fibroblasts, etc. TGF-[Formula: see text]1 acts as a key effect factor that participates in these cellular processes of PF. Recently, much attention was paid to inhibiting TGF-[Formula: see text]1 mediated cell processes in the treatment of PF with Chinese herbal medicines (CHM), an important part of traditional Chinese medicine. Here, this review first summarized the effects of TGF-[Formula: see text]1 in different cellular processes of PF. Then, this review summarized the recent research on CHM (compounds, multi-components, single medicines and prescriptions) to directly and/or indirectly inhibit TGF-[Formula: see text]1 signaling (TLRs, PPARs, micrRNA, etc.) in PF. Most of the research focused on CHM natural compounds, including but not limited to alkaloids, flavonoids, phenols and terpenes. After review, the research perspectives of CHM on TGF-[Formula: see text]1 inhibition in PF were further discussed. This review hopes that revealing the inhibiting effects of CHM on TGF-[Formula: see text]1-mediated cellular processes of PF can promote CHM to be better understood and utilized, thus transforming the therapeutic activities of CHM into practice.


Subject(s)
Cell Physiological Phenomena/drug effects , Drugs, Chinese Herbal/therapeutic use , Pulmonary Fibrosis/drug therapy , Signal Transduction/drug effects , Transforming Growth Factor beta1/antagonists & inhibitors , COVID-19/complications , COVID-19/metabolism , COVID-19/virology , Humans , Medicine, Chinese Traditional/methods , Phytotherapy/methods , Pulmonary Fibrosis/complications , Pulmonary Fibrosis/metabolism , SARS-CoV-2/physiology , Transforming Growth Factor beta1/metabolism
7.
Front Immunol ; 12: 789317, 2021.
Article in English | MEDLINE | ID: covidwho-1593957

ABSTRACT

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.


Subject(s)
COVID-19/genetics , Gene Expression Profiling/methods , Signal Transduction/genetics , Transcription Factors/genetics , Transcriptome/genetics , COVID-19/epidemiology , COVID-19/virology , Cluster Analysis , Gene Ontology , Gene Regulatory Networks , Humans , Immunity/genetics , Models, Genetic , Pandemics , Protein Interaction Maps/genetics , SARS-CoV-2/physiology
8.
Genet Res (Camb) ; 2021: 2728757, 2021.
Article in English | MEDLINE | ID: covidwho-1593203

ABSTRACT

Coronavirus disease 2019 (COVID-19) is acutely infectious pneumonia. Currently, the specific causes and treatment targets of COVID-19 are still unclear. Herein, comprehensive bioinformatics methods were employed to analyze the hub genes in COVID-19 and tried to reveal its potential mechanisms. First of all, 34 groups of COVID-19 lung tissues and 17 other diseases' lung tissues were selected from the GSE151764 gene expression profile for research. According to the analysis of the DEGs (differentially expressed genes) in the samples using the limma software package, 84 upregulated DEGs and 46 downregulated DEGs were obtained. Later, by the Database for Annotation, Visualization, and Integrated Discovery (DAVID), they were enriched in the Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. It was found that the upregulated DEGs were enriched in the type I interferon signaling pathway, AGE-RAGE signaling pathway in diabetic complications, coronavirus disease, etc. Downregulated DEGs were in cellular response to cytokine stimulus, IL-17 signaling pathway, FoxO signaling pathway, etc. Then, based on GSEA, the enrichment of the gene set in the sample was analyzed in the GO terms, and the gene set was enriched in the positive regulation of myeloid leukocyte cytokine production involved in immune response, programmed necrotic cell death, translesion synthesis, necroptotic process, and condensed nuclear chromosome. Finally, with the help of STRING tools, the PPI (protein-protein interaction) network diagrams of DEGs were constructed. With degree ≥13 as the cutoff degree, 3 upregulated hub genes (ISG15, FN1, and HLA-G) and 4 downregulated hub genes (FOXP3, CXCR4, MMP9, and CD69) were screened out for high degree. All these findings will help us to understand the potential molecular mechanisms of COVID-19, which is also of great significance for its diagnosis and prevention.


Subject(s)
COVID-19 , Computational Biology , Gene Expression Profiling , Humans , SARS-CoV-2 , Signal Transduction , Transcriptome
9.
Front Immunol ; 12: 724936, 2021.
Article in English | MEDLINE | ID: covidwho-1592205

ABSTRACT

The COVID-19 pandemic has created an urgent situation throughout the globe. Therefore, it is necessary to identify the differentially expressed genes (DEGs) in COVID-19 patients to understand disease pathogenesis and the genetic factor(s) responsible for inter-individual variability. The DEGs will help understand the disease's potential underlying molecular mechanisms and genetic characteristics, including the regulatory genes associated with immune response elements and protective immunity. This study aimed to determine the DEGs in mild and severe COVID-19 patients versus healthy controls. The Agilent-085982 Arraystar human lncRNA V5 microarray GEO dataset (GSE164805 dataset) was used for this study. We used statistical tools to identify the DEGs. Our 15 human samples dataset was divided into three groups: mild, severe COVID-19 patients and healthy control volunteers. We compared our result with three other published gene expression studies of COVID-19 patients. Along with significant DEGs, we developed an interactome map, a protein-protein interaction (PPI) pattern, a cluster analysis of the PPI network, and pathway enrichment analysis. We also performed the same analyses with the top-ranked genes from the three other COVID-19 gene expression studies. We also identified differentially expressed lncRNA genes and constructed protein-coding DEG-lncRNA co-expression networks. We attempted to identify the regulatory genes related to immune response elements and protective immunity. We prioritized the most significant 29 protein-coding DEGs. Our analyses showed that several DEGs were involved in forming interactome maps, PPI networks, and cluster formation, similar to the results obtained using data from the protein-coding genes from other investigations. Interestingly we found six lncRNAs (TALAM1, DLEU2, and UICLM CASC18, SNHG20, and GNAS) involved in the protein-coding DEG-lncRNA network; which might be served as potential biomarkers for COVID-19 patients. We also identified three regulatory genes from our study and 44 regulatory genes from the other investigations related to immune response elements and protective immunity. We were able to map the regulatory genes associated with immune elements and identify the virogenomic responses involved in protective immunity against SARS-CoV-2 infection during COVID-19 development.


Subject(s)
COVID-19/genetics , Gene Expression Profiling/methods , Gene Expression Regulation , Immunity/genetics , Aged , COVID-19/epidemiology , COVID-19/immunology , Female , Gene Ontology , Gene Regulatory Networks , Humans , Male , Middle Aged , Pandemics/prevention & control , Protein Interaction Maps/genetics , SARS-CoV-2/immunology , SARS-CoV-2/physiology , Signal Transduction/genetics , Signal Transduction/immunology
10.
Signal Transduct Target Ther ; 6(1): 167, 2021 04 24.
Article in English | MEDLINE | ID: covidwho-1585891

ABSTRACT

The ongoing 2019 novel coronavirus disease (COVID-19) caused by SARS-CoV-2 has posed a worldwide pandemic and a major global public health threat. The severity and mortality of COVID-19 are associated with virus-induced dysfunctional inflammatory responses and cytokine storms. However, the interplay between host inflammatory responses and SARS-CoV-2 infection remains largely unknown. Here, we demonstrate that SARS-CoV-2 nucleocapsid (N) protein, the major structural protein of the virion, promotes the virus-triggered activation of NF-κB signaling. After binding to viral RNA, N protein robustly undergoes liquid-liquid phase separation (LLPS), which recruits TAK1 and IKK complex, the key kinases of NF-κB signaling, to enhance NF-κB activation. Moreover, 1,6-hexanediol, the inhibitor of LLPS, can attenuate the phase separation of N protein and restrict its regulatory functions in NF-κB activation. These results suggest that LLPS of N protein provides a platform to induce NF-κB hyper-activation, which could be a potential therapeutic target against COVID-19 severe pneumonia.


Subject(s)
COVID-19/metabolism , Coronavirus Nucleocapsid Proteins/metabolism , NF-kappa B/metabolism , RNA, Viral/metabolism , SARS-CoV-2/metabolism , Signal Transduction , A549 Cells , Acrylates/pharmacology , Animals , COVID-19/drug therapy , COVID-19/pathology , Chlorocebus aethiops , HEK293 Cells , HeLa Cells , Humans , Inflammation/drug therapy , Inflammation/metabolism , Inflammation/pathology , Phosphoproteins/metabolism , Vero Cells
11.
Cell Death Dis ; 12(12): 1156, 2021 12 14.
Article in English | MEDLINE | ID: covidwho-1585874

ABSTRACT

Lots of cell death initiator and effector molecules, signalling pathways and subcellular sites have been identified as key mediators in both cell death processes in cancer. The XDeathDB visualization platform provides a comprehensive cell death and their crosstalk resource for deciphering the signaling network organization of interactions among different cell death modes associated with 1461 cancer types and COVID-19, with an aim to understand the molecular mechanisms of physiological cell death in disease and facilitate systems-oriented novel drug discovery in inducing cell deaths properly. Apoptosis, autosis, efferocytosis, ferroptosis, immunogenic cell death, intrinsic apoptosis, lysosomal cell death, mitotic cell death, mitochondrial permeability transition, necroptosis, parthanatos, and pyroptosis related to 12 cell deaths and their crosstalk can be observed systematically by the platform. Big data for cell death gene-disease associations, gene-cell death pathway associations, pathway-cell death mode associations, and cell death-cell death associations is collected by literature review articles and public database from iRefIndex, STRING, BioGRID, Reactom, Pathway's commons, DisGeNET, DrugBank, and Therapeutic Target Database (TTD). An interactive webtool, XDeathDB, is built by web applications with R-Shiny, JavaScript (JS) and Shiny Server Iso. With this platform, users can search specific interactions from vast interdependent networks that occur in the realm of cell death. A multilayer spectral graph clustering method that performs convex layer aggregation to identify crosstalk function among cell death modes for a specific cancer. 147 hallmark genes of cell death could be observed in detail in these networks. These potential druggable targets are displayed systematically and tailoring networks to visualize specified relations is available to fulfil user-specific needs. Users can access XDeathDB for free at https://pcm2019.shinyapps.io/XDeathDB/ .


Subject(s)
Cell Death/physiology , Regulated Cell Death/physiology , Signal Transduction/physiology , Animals , COVID-19/metabolism , COVID-19/physiopathology , Cluster Analysis , Databases, Factual , Humans , Necroptosis , Neoplasms/metabolism , Neoplasms/physiopathology , Phagocytosis , SARS-CoV-2/metabolism , SARS-CoV-2/physiology , Signal Transduction/drug effects , Software
13.
Bioengineered ; 12(2): 12461-12469, 2021 12.
Article in English | MEDLINE | ID: covidwho-1585255

ABSTRACT

Severe mortality due to the COVID-19 pandemic resulted from the lack of effective treatment. Although COVID-19 vaccines are available, their side effects have become a challenge for clinical use in patients with chronic diseases, especially cancer patients. In the current report, we applied network pharmacology and systematic bioinformatics to explore the use of biochanin A in patients with colorectal cancer (CRC) and COVID-19 infection. Using the network pharmacology approach, we identified two clusters of genes involved in immune response (IL1A, IL2, and IL6R) and cell proliferation (CCND1, PPARG, and EGFR) mediated by biochanin A in CRC/COVID-19 condition. The functional analysis of these two gene clusters further illustrated the effects of biochanin A on interleukin-6 production and cytokine-cytokine receptor interaction in CRC/COVID-19 pathology. In addition, pathway analysis demonstrated the control of PI3K-Akt and JAK-STAT signaling pathways by biochanin A in the treatment of CRC/COVID-19. The findings of this study provide a therapeutic option for combination therapy against COVID-19 infection in CRC patients.


Subject(s)
Anticarcinogenic Agents/therapeutic use , Antiviral Agents/therapeutic use , COVID-19/drug therapy , Colorectal Neoplasms/drug therapy , Gene Expression Regulation, Neoplastic/drug effects , Genistein/therapeutic use , Phytoestrogens/therapeutic use , Atlases as Topic , COVID-19/immunology , COVID-19/pathology , COVID-19/virology , Colorectal Neoplasms/immunology , Colorectal Neoplasms/pathology , Colorectal Neoplasms/virology , Cyclin D1/genetics , Cyclin D1/immunology , ErbB Receptors/genetics , ErbB Receptors/immunology , Humans , Interleukin-1alpha/genetics , Interleukin-1alpha/immunology , Interleukin-2/genetics , Interleukin-2/immunology , Janus Kinases/genetics , Janus Kinases/immunology , Metabolic Networks and Pathways/drug effects , Metabolic Networks and Pathways/genetics , Molecular Targeted Therapy/methods , Multigene Family , PPAR gamma/genetics , PPAR gamma/immunology , Pharmacogenetics/methods , Phosphatidylinositol 3-Kinases/genetics , Phosphatidylinositol 3-Kinases/immunology , Proto-Oncogene Proteins c-akt/genetics , Proto-Oncogene Proteins c-akt/immunology , Receptors, Interleukin-6/genetics , Receptors, Interleukin-6/immunology , SARS-CoV-2/drug effects , SARS-CoV-2/growth & development , SARS-CoV-2/pathogenicity , STAT Transcription Factors/genetics , STAT Transcription Factors/immunology , Signal Transduction
14.
Front Cell Infect Microbiol ; 11: 766922, 2021.
Article in English | MEDLINE | ID: covidwho-1581381

ABSTRACT

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread worldwide and has infected more than 250 million people. A typical feature of COVID-19 is the lack of type I interferon (IFN-I)-mediated antiviral immunity in patients. However, the detailed molecular mechanisms by which SARS-CoV-2 evades the IFN-I-mediated antiviral response remain elusive. Here, we performed a comprehensive screening and identified a set of SARS-CoV-2 proteins that antagonize the IFN-I response. Subsequently, we characterized the mechanisms of two viral proteins antagonize IFN-I production and downstream signaling. SARS-CoV-2 membrane protein binds to importin karyopherin subunit alpha-6 (KPNA6) to inhibit interferon regulatory factor 3(IRF3) nuclear translocation. Further, the spike protein interacts with signal transducer and activator of transcription 1 (STAT1) to block its association with Janus kinase 1 (JAK1). This study increases our understanding of SARS-CoV-2 pathogenesis and suggests novel therapeutic targets for the treatment of COVID-19.


Subject(s)
COVID-19 , Interferon Type I , Spike Glycoprotein, Coronavirus , Viral Matrix Proteins , Humans , SARS-CoV-2 , Signal Transduction , Viral Proteins
15.
Front Immunol ; 12: 784028, 2021.
Article in English | MEDLINE | ID: covidwho-1581324

ABSTRACT

Background: Extracellular vesicles (EVs) are mediators of cell-to-cell communication in inflammatory lung diseases. They function as carriers for miRNAs which regulate mRNA transcripts and signaling pathways after uptake into recipient cells. We investigated whether miRNAs associated with circulating EVs regulate immunologic processes in COVID-19. Methods: We prospectively studied 20 symptomatic patients with COVID-19 pneumonia, 20 mechanically ventilated patients with severe COVID-19 (severe acute respiratory corona virus-2 syndrome, ARDS) and 20 healthy controls. EVs were isolated by precipitation, total RNA was extracted, profiled by small RNA sequencing and evaluated by differential gene expression analysis (DGE). Differentially regulated miRNAs between groups were bioinformatically analyzed, mRNA target transcripts identified and signaling networks constructed, thereby comparing COVID-19 pneumonia to the healthy state and pneumonia to severe COVID-19 ARDS. Results: DGE revealed 43 significantly and differentially expressed miRNAs (25 downregulated) in COVID-19 pneumonia when compared to controls, and 20 miRNAs (15 downregulated) in COVID-19 ARDS patients in comparison to those with COVID-19 pneumonia. Network analysis for comparison of COVID-19 pneumonia to healthy controls showed upregulated miR-3168 (log2FC=2.28, padjusted<0.001), among others, targeting interleukin-6 (IL6) (25.1, 15.2 - 88.2 pg/ml in COVID-19 pneumonia) and OR52N2, an olfactory smell receptor in the nasal epithelium. In contrast, miR-3168 was significantly downregulated in COVID-19 ARDS (log2FC=-2.13, padjusted=0.003) and targeted interleukin-8 (CXCL8) in a completely activated network. Toll-like receptor 4 (TLR4) was inhibited in COVID-19 pneumonia by miR-146a-5p and upregulated in ARDS by let-7e-5p. Conclusion: EV-derived miRNAs might have important regulative functions in the pathophysiology of COVID-19: CXCL8 regulates neutrophil recruitment into the lung causing epithelial damage whereas activated TLR4, to which SARS-CoV-2 spike protein binds strongly, increases cell surface ACE2 expression and destroys type II alveolar cells that secrete pulmonary surfactants; both resulting in pulmonary-capillary leakage and ARDS. These miRNAs may serve as biomarkers or as possible therapeutic targets.


Subject(s)
Biomarkers/blood , COVID-19/immunology , Extracellular Vesicles/immunology , MicroRNAs/immunology , Aged , Aged, 80 and over , COVID-19/pathology , Disease Progression , Female , Humans , Male , Middle Aged , Pneumonia/immunology , Pneumonia/pathology , SARS-CoV-2 , Signal Transduction/immunology
16.
Int J Mol Sci ; 23(1)2021 Dec 24.
Article in English | MEDLINE | ID: covidwho-1580700

ABSTRACT

Acute respiratory distress syndrome (ARDS) followed by repair with lung remodeling is observed in COVID-19. These findings can lead to pulmonary terminal fibrosis, a form of irreversible sequelae. There is evidence that TGF-ß is intimately involved in the fibrogenic process. When activated, TGF-ß promotes the differentiation of fibroblasts into myofibroblasts and regulates the remodeling of the extracellular matrix (ECM). In this sense, the present study evaluated the histopathological features and immunohistochemical biomarkers (ACE-2, AKT-1, Caveolin-1, CD44v6, IL-4, MMP-9, α-SMA, Sphingosine-1, and TGF-ß1 tissue expression) involved in the TGF-ß1 signaling pathways and pulmonary fibrosis. The study consisted of 24 paraffin lung samples from patients who died of COVID-19 (COVID-19 group), compared to 10 lung samples from patients who died of H1N1pdm09 (H1N1 group) and 11 lung samples from patients who died of different causes, with no lung injury (CONTROL group). In addition to the presence of alveolar septal fibrosis, diffuse alveolar damage (DAD) was found to be significantly increased in the COVID-19 group, associated with a higher density of Collagen I (mature) and III (immature). There was also a significant increase observed in the immunoexpression of tissue biomarkers ACE-2, AKT-1, CD44v6, IL-4, MMP-9, α-SMA, Sphingosine-1, and TGF-ß1 in the COVID-19 group. A significantly lower expression of Caveolin-1 was also found in this group. The results suggest the participation of TGF-ß pathways in the development process of pulmonary fibrosis. Thus, it would be plausible to consider therapy with TGF-ß inhibitors in those patients recovered from COVID-19 to mitigate a possible development of pulmonary fibrosis and its consequences for post-COVID-19 life quality.


Subject(s)
COVID-19/metabolism , Pulmonary Fibrosis/metabolism , Signal Transduction , Transforming Growth Factor beta/metabolism , Actins/metabolism , Adrenal Cortex Hormones/therapeutic use , Adult , Aged , Aged, 80 and over , Angiotensin-Converting Enzyme 2/metabolism , COVID-19/complications , COVID-19/drug therapy , COVID-19/pathology , Caveolin 1/metabolism , Collagen Type I/metabolism , Collagen Type III/metabolism , Female , Humans , Hyaluronan Receptors/metabolism , Immunohistochemistry , Influenza A Virus, H1N1 Subtype/metabolism , Influenza, Human/metabolism , Influenza, Human/pathology , Interleukin-4/metabolism , Male , Matrix Metalloproteinase 9/metabolism , Middle Aged , Proto-Oncogene Proteins c-akt/metabolism , Pulmonary Fibrosis/complications , Pulmonary Fibrosis/drug therapy , Pulmonary Fibrosis/pathology , Retrospective Studies , Transforming Growth Factor beta1/metabolism
17.
Gastroenterology ; 160(3): 925-928.e4, 2021 02.
Article in English | MEDLINE | ID: covidwho-1575253
18.
Viruses ; 13(12)2021 11 27.
Article in English | MEDLINE | ID: covidwho-1574265

ABSTRACT

Modulation of the antiviral innate immune response has been proposed as a putative cellular target for the development of novel pan-viral therapeutic strategies. The Janus kinase-signal transducer and activator of transcription (JAK-STAT) pathway is especially relevant due to its essential role in the regulation of local and systemic inflammation in response to viral infections, being, therefore, a putative therapeutic target. Here, we review the extraordinary diversity of strategies that viruses have evolved to interfere with JAK-STAT signaling, stressing the relevance of this pathway as a putative antiviral target. Moreover, due to the recent remarkable progress on the development of novel JAK inhibitors (JAKi), the current knowledge on its efficacy against distinct viral infections is also discussed. JAKi have a proven efficacy against a broad spectrum of disorders and exhibit safety profiles comparable to biologics, therefore representing good candidates for drug repurposing strategies, including viral infections.


Subject(s)
Janus Kinases/metabolism , STAT Transcription Factors/metabolism , Signal Transduction/drug effects , Virus Diseases/metabolism , Viruses/metabolism , Antiviral Agents/pharmacology , Antiviral Agents/therapeutic use , Humans , Immunity, Innate , Inflammation , Janus Kinase Inhibitors/pharmacology , Janus Kinase Inhibitors/therapeutic use , Janus Kinases/antagonists & inhibitors , Virus Diseases/drug therapy , Virus Diseases/immunology , Viruses/classification , Viruses/drug effects
19.
Viruses ; 13(12)2021 12 11.
Article in English | MEDLINE | ID: covidwho-1572663

ABSTRACT

BACKGROUND: There is an urgent need for new antivirals with powerful therapeutic potential and tolerable side effects. METHODS: Here, we tested the antiviral properties of interferons (IFNs), alone and with other drugs in vitro. RESULTS: While IFNs alone were insufficient to completely abolish replication of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), IFNα, in combination with remdesivir, EIDD-2801, camostat, cycloheximide, or convalescent serum, proved to be more effective. Transcriptome and metabolomic analyses revealed that the IFNα-remdesivir combination suppressed SARS-CoV-2-mediated changes in Calu-3 cells and lung organoids, although it altered the homeostasis of uninfected cells and organoids. We also demonstrated that IFNα combinations with sofosbuvir, telaprevir, NITD008, ribavirin, pimodivir, or lamivudine were effective against HCV, HEV, FLuAV, or HIV at lower concentrations, compared to monotherapies. CONCLUSIONS: Altogether, our results indicated that IFNα can be combined with drugs that affect viral RNA transcription, protein synthesis, and processing to make synergistic combinations that can be attractive targets for further pre-clinical and clinical development against emerging and re-emerging viral infections.


Subject(s)
Antiviral Agents/pharmacology , Interferon-alpha/pharmacology , SARS-CoV-2/drug effects , Cell Line , Drug Synergism , Humans , Lung/drug effects , Lung/metabolism , Lung/virology , Metabolome/drug effects , Organoids , RNA, Viral/biosynthesis , RNA, Viral/drug effects , Signal Transduction/drug effects , Transcriptome/drug effects , Virus Replication/drug effects , Viruses/classification , Viruses/drug effects
20.
Viruses ; 13(12)2021 12 09.
Article in English | MEDLINE | ID: covidwho-1572656

ABSTRACT

In the past year and a half, SARS-CoV-2 has caused 240 million confirmed cases and 5 million deaths worldwide. Autophagy is a conserved process that either promotes or inhibits viral infections. Although coronaviruses are known to utilize the transport of autophagy-dependent vesicles for the viral life cycle, the underlying autophagy-inducing mechanisms remain largely unexplored. Using several autophagy-deficient cell lines and autophagy inhibitors, we demonstrated that SARS-CoV-2 ORF3a was able to induce incomplete autophagy in a FIP200/Beclin-1-dependent manner. Moreover, ORF3a was involved in the induction of the UPR (unfolded protein response), while the IRE1 and ATF6 pathways, but not the PERK pathway, were responsible for mediating the ORF3a-induced autophagy. These results identify the role of the UPR pathway in the ORF3a-induced classical autophagy process, which may provide us with a better understanding of SARS-CoV-2 and suggest new therapeutic modalities in the treatment of COVID-19.


Subject(s)
Autophagy , SARS-CoV-2/metabolism , Unfolded Protein Response , Viroporin Proteins/metabolism , Animals , Autophagy/genetics , Autophagy-Related Proteins/genetics , Beclin-1/genetics , Cell Line , Humans , Signal Transduction
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