Effects of Bacille Calmette Guerin (BCG) vaccination during COVID-19 infection

IFNγ-secreting T cells that highly express IL-2 potently inhibit the growth of intracellular M. tuberculosis in macrophages

Cytokine of interferon-gamma (IFNγ) plays a vital role in the immune response against Mycobacteria tuberculosis (Mtb) infection, yet the specific function of T cells producing IFNγ in this process remains unclear. In this study, we first isolated IFNγ+CD3+ T cells induced by Mtb antigens using surface staining assays. which showed a strong ability to inhibit the growth of intracellular mycobacteria in macrophages. Peripheral blood mononuclear cells (PBMCs) from healthy individuals were then challenged with Bacillus Calmette-Guérin (BCG) or Mtb, respectively, to sort IFNγ-secreting T cells for mRNA sequencing to analyze the gene expression patterns. The results of the integrated data analysis revealed distinct patterns of gene expression between IFNγ+CD3+ T cells induced by the BCG vaccine and those induced by Mtb pathogens. Further, unlike Mtb-induced cells, BCG-induced IFNγ+CD3+ T cells expressed high levels of interleukin-2 (IL-2), which increased the frequencies of these cells and the production of effector cytokines IFNγ and IL-2. Our findings suggested that IFNγ+CD3+ T cells with high IL-2 expression presented potent effector functions to inhibit intracellular Mtb growth, while Mtb infection impaired IL-2 expression in IFNγ+CD3+ T cells.

Identification of toll-like receptor 5 and acyl-CoA synthetase long chain family member 1 as hub genes are correlated with the severe forms of COVID-19 by Weighted gene co-expression network analysis

Since a 25% mortality rate occurred in critical Coronavirus disease 2019 (COVID-19) patients, investigating the potential drivers remains to be important. Here, the authors applied Weighted Gene Co-expression Network Analysis to identify the potential drivers in the blood samples of multiple COVID-19 expression profiles. The authors found that the darkslateblue module was significantly correlated with critical COVID-19, and Gene Ontology analysis indicated terms associated with the inflammation pathway and apoptotic process. The authors intersected differentially expressed genes, Maximal Clique Centrality calculated hub genes, and COVID-19 related genes in the Genecards dataset, and two genes, toll-like receptor 5 (TLR5) and acyl-CoA synthetase long chain family member 1 (ACSL1), were screened out. The Gene Set Enrichment Analysis further supports their core role in the inflammatory pathway. Furthermore, the cell-type identification by estimating relative subsets of RNA transcript demonstrated that TLR5 and ACSL1 were associated with neutrophil enrichment in critical COVID-19 patients. Collectively, the aurthors identified two hub genes that were strongly correlated with critical COVID-19. These may help clarify the pathogenesis and assist the immunotherapy development.

Analysis of mechanisms of Shenhuang Granule in treating severe COVID-19 based on network pharmacology and molecular docking

OBJECTIVE

Severe cases of coronavirus disease 2019 (COVID-19) are expected to have a worse prognosis than mild cases. Shenhuang Granule (SHG) has been shown to be a safe and effective treatment for severe COVID-19 in a previous randomized clinical trial, but the active chemical constituents and underlying mechanisms of action remain unknown. The goal of this study is to explore the chemical basis and mechanisms of SHG in the treatment of severe COVID-19, using network pharmacology.

METHODS

Ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry was employed to screen chemical constituents of SHG. Putative therapeutic targets were predicted by searching traditional Chinese medicine system pharmacology database and analysis platform, SwissTargetPrediction, and Gene Expression Omnibus (GEO) databases. The target protein-protein interaction network and enrichment analysis were performed to investigate the hub genes and presumptive mechanisms. Molecular docking and molecular dynamics simulations were used to verify the stability and interaction between the key chemical constituents of SHG and COVID-19 protein targets.

RESULTS

Forty-five chemical constituents of SHG were identified along with 131 corresponding therapeutic targets, including hub genes such as HSP90AA1, MMP9, CXCL8, PTGS2, IFNG, DNMT1, TYMS, MDM2, HDAC3 and ABCB1. Functional enrichment analysis indicated that SHG mainly acted on the neuroactive ligand-receptor interaction, calcium signaling pathway and cAMP signaling pathway. Molecular docking showed that the key constituents had a good affinity with the severe acute respiratory syndrome coronavirus 2 protein targets. Molecular dynamics simulations indicated that ginsenoside Rg4 formed a stable protein-ligand complex with helicase.

CONCLUSION

Multiple components of SHG regulated multiple targets to inhibit virus invasion and cytokine storm through several signaling pathways; this provides a scientific basis for clinical applications and further experiments.

Severity of COVID-19 patients with coexistence of asthma and vitamin D deficiency

Coronavirus disease 2019 (COVID-19)-driven global pandemic triggered innumerable health complications, imposing great challenges in managing other respiratory diseases like asthma. Furthermore, increases in the underlying inflammation involved in the fatality of COVID-19 have been linked with lack of vitamin D. In this research work, we intend to investigate the possible genetic linkage of asthma and vitamin D deficiency with the severity and fatality of COVID-19 using a network-based approach. We identified and analysed 41 and 14 differentially expressed genes (DEGs) of COVID-19 being common with asthma and vitamin D deficiency, respectively, through the comparative differential gene expression analysis and their footprints on signalling pathways. Gene set enrichment analysis for GO terms and signalling pathways reveals key biological activities, including inflammatory response-related pathways (e.g., cytokine- and chemokine-mediated signalling pathways, IL-17, and TNF signalling pathways). Besides, the Protein–Protein Interaction network analysis of those DEGs reveals hub proteins, some of which are reported as inflammatory antiviral interferon-stimulated biomarkers that potentially drive the cytokine storm leading to COVID-19 severity and fatality, and contributes in the early stage of viral replication, respectively. Moreover, the regulatory network analysis found these DEGs associated with antiviral and tumour inhibitory transcription factors and micro-RNAs. Finally, drug–target enrichment analysis yields tetradioxin, estradiol, arsenenous acid, and zinc, which have been reported to be effective in suppressing the pro-inflammatory cytokines production, and other respiratory tract infections. Our results yield shared biomarker-driven key hypotheses followed by network-based analytics, demystifying the mechanistic details of COVID-19 comorbidity of asthma and vitamin D deficiency with their potential therapeutic implications.