miRNA difference analysis, target gene prediction and heat map construction in critically ill patients with COVID-19
Screening miRNA sequencing data of severe COVID-19 patients in the gene expression profiling database (GSE176498), where’s the blood for the miRNA detection, 10 healthy volunteers and 11 severe COVID-19 patients are selected. Difference analysis revealed 38 up-regulated miRNAs including miR-15a-5p, miR-126-5p, miR-29a-3p, miR-29c-3p, and miR-425-5p, and 65 down-regulated miRNAs including miR-92a-3p, miR-26a-5p, miR-150-5p, and miR-181a-5p. Differential miRNAs with LogFC ≥ 3 were selected, and target gene prediction was performed using two databases and the intersection was taken as a potential target gene, and 3158 up-regulated miRNA target genes and 1912 down-regulated miRNA target genes were obtained. The heat map clustering analysis showed that the miRNA with large differential multiple in severe COVID-19 patients were mainly low-expressed (Fig. 1a).Enrichment analysis of differential miRNA revealed that PI3K-Akt, MAPK, autophagy, cell cycle, chemokines and T cell receptor signaling pathways participated in the development of severe COVID-19 (Fig. 1b).
Transcriptomics analysis, volcanic and thermal mapping of critical patients
The transcriptome sequencing data of patients with severe pneumonia were obtained after screening. With mild COVID-19 as the control, we found that such differential genes are responsible for the disease development. The results were illustrated as volcanic diagram and it became apparent that the overall distribution of the differential genes was dominated by high mRNA expression. The grouping and clustering analysis of the samples showed that such differential genes as CYP19A1, MMP8, CCNA1, FAP, SLPI, and PPARG were mainly highly expressed in patients with severe COVID-19 (Fig. 2). Transcription factor predictions revealed that 116 transcription molecules including NFKB1, RELA, STAT1, and CEBPB participated in the phenotypic changes of genes in critically ill patients.
Gene Set Enrichment Analysis of DGE and Construction of miRNA and mRNA Network
To clarify the pathophysiological mechanism of the COVID-19 development in patients, the gene set enrichment analysis of different numbers of up-regulated and down-regulated genes was performed using a “ClusterProfiler” library in R software. The up-regulated genes has a role in the activation of interferon α/γ, TNF-α, complement and inflammatory response signals, and the differential genes jointly inhibited the unfolded protein response and oxidative phosphorylation signals. These results indicated that severe COVID-19 was closely related to endoplasmic reticulum stress, and mitochondrial dysfunction and immune dysfunction (Fig. 3a). Complement system, hypoxia, inflammatory response, IFN-α, TNF-α signals were plotted against the ordered dataset, ranked according to enrichment fraction (Fig. 3b). Mapping of the miRNA and mRNA regulatory network revealed that nine down-regulated miRNAs, including miR-26b-5p and miR-181a-5p, mediated the up-regulation of 31 mRNAs, including PFKFB2, DRAM1 and GRB10. Seven up-regulated miRNA, including miR-126-5p and miR-27a-3p, participated in the down-regulation of 28 mRNA, including RORA, NCALD and CNTNAP2 (Fig. 3c).
Collection of component and targets and disease target of YXTMG
Ninety-three active compounds of YXTMG, with 2,812 targets, were screened and obtained from the databases of TCMSP and BATMAN. Some compounds are shown in table 1. After being interpreted by the UniProt database and de-duplicated, 83 active components and 757 targets were obtained. Using Genecards, NCBI, and TTD databases, and using "COVID-19" as the keyword search target, we obtained 3767 COVID-19 targets.
Venn diagram and protein interaction network draw
757 targets of YXTMG and 3767 targets of COVID-19 were entered and Venn diagram was drawn on the bioinformatics platform, respectively, and 375 intersecting targets were obtained. Including NFKBIA, RELA, TNF, TLR4, IL6, IL10, EGFR, CXCL10, STAT3, SCARB1, ACE, etc. (Fig.4a). The STRING database was used to analyze the protein-protein interaction relationships of the intersecting targets, and 375 nodes and 1765 interaction relationships were obtained. After setting the parameters, the targets such as SRC, TP53, STAT3, MAPK3, and HSP90AA1 were found to be important target sites for the drug to show the therapeutic effect, after being visualized with Cytoscape software (Fig. 4b).
Drug-target-disease network diagram and pharmacodynamic basic analysis
The information of active constituents, targets, and intersecting targets was imported into Cytoscape to draw the relationship network of YXTMG, Compounds, Targets and COVID-19(Fig. 5a). Overall, 78 constituents of the eight Chinese medicinal materials act on 375 targets of the COVID-19. As shown in supplement table 1, among the common constituents of YXTMG, the more important in a context of pharmacological effect are quercetin, kaempferol and β-sitosterol. Constituents classification analysis showed that the those constituents with higher component proportion were successively flavonoids, terpenes, steroids, Alkaloids, and lignans(Fig. 5b), among which, flavonoids were mainly found in Hedysarum Multijugum Maxim, terpenoids were mainly enriched in Curcumae Radix, Figwort Root, and Panax Ginseng C., and the steroidal compounds of the eight Chinese medicines accounted for the same proportion. Alkaloids were mainly found in Panax Ginseng C. A. Mey, (supplement Fig. 1).
Results of GO enrichment analysis and KEGG pathway analysis
GO and KEGG enrichment analysis was performed using R software, and gene ontology analysis resulted in 3,209 biological processes, 144 cellular pathways and 246 molecular functions. Biological processes were enriched to include responses to lipopolysaccharide, reactive oxygen metabolism, and oxidative stress response, regulation of reactive oxygen metabolism, leukocyte migration, and cell response to drugs, (Fig. 6a). Kyoto gene and genome analysis revealed 191 pathways of information, including PI3K-Akt, MAPK, cAMP, TNF, HIF-1 and other environmental information processing as well as tissue systems such as chemokines, Toll-like receptor, C-type lectin receptor and T cell receptor and their involvement in the incidence of COVID-19 disease, as shown in Fig. 6b.
Effect of YXTMG on pathological mechanisms of mRNA and miRNA involvement in severe patients
Through intersection analysis of differential mRNA between drug targets and patient's transcriptome, it was found that the drug might affect MAPK signaling pathway, Toll-like receptor signaling pathway, C-type lectin receptor signaling pathway, HIF-1 signaling pathway, cell cycle and other biological processes by regulating such pathways like cytokine production regulation, inflammation response regulation, epithelial cell proliferation regulation, and DNA binding regulation. The results are shown in supplement fig. 2.In the analysis data set, miR-181a-5p expression was down-regulated. While its target genes PLAU and SERPINE1 were up-regulated(fig.7a).The above phenomena were validated on an expanded dataset based on ARDS symptoms in critically ill patients with COVID-19, and the results were as expected(fig.7b). The intersection of miRNA-induced mRNA expression difference and drug action reveals that stigmasterol and quercetin of Panax ginseng C. A. Mey, Glehniae radix, Hedysarum multijugum maxim act on the down-regulated miR-181a-5p-mediated mRNA up-regulation of PLAU and SERPINE1, and the mRNA expression levels of the two groups, the severe patients are significantly higher than those in mild patients (p<0.01)(fig.7c). Molecular docking indicated that stigmasterol and quercetin both had good binding with two target molecules (supplement table 2, supplement Fig. 4).
Heat map for combined analysis of pathological mechanism and drug action mechanism in severe COVID-19 patients
The combined analysis of differential miRNA, mRNA and drug action targets revealed that drugs may affect the regulation of acute inflammatory response, T cell-mediated immunity, humoral immune response and other biological processes in severe COVID-19 patients through such pathways as complement system and coagulation cascade, TNF signaling pathway, NF-κB signaling pathway, T cell receptor signaling pathway, and natural killer cell-mediated cytotoxicity. It is possible that PI3K-Akt signaling pathway can interfere with miRNA-mediated α-β T cell differentiation, epithelial cell differentiation regulation (fig.8b), response to oxygen levels, and its role in the hypoxic conditions of biological processes (fig.8a), therefore its efficacy against the severe Covid-19 conditions is inevitable.
Network topology result and qualitative and quantitative analysis of quercetin
The network topology analysis showed that the constituents such as Quercetin, Kaempferol and Beta-sitosterol had high central freedom(Table 2), and they could be used as the important material basis of the compound. First, the standard curve(fig.9a) of quercetin was drawn, and the linearity(fig.9c) achieved of quercetin was good within the range of 50-350μg/mL. Qualitative and quantitative analysis of quercetin in YXTMG showed that the compound constituted this component at a high concentration(Table 3) of about 1.12 mg/g.
Establishment of cell inflammation model and effect of drugs on oxidative damage cells
Using a model of inflammatory injury induced by hydrogen peroxide at different concentrations, it was found that the cell inhibition rate was concentration-dependent for hydrogen peroxide, and the inhibition rate of 50μM on AECⅡ was about 75%, as shown in Fig. 10a.When 50μM H2O2 was selected for modeling, the survival rate of the model group was significantly decreased as compared with that of the control group (p<0.01). The cell activity of the prednisone group was increased as compared with that of the model group (p<0.05), and the cell activities of quercetin and YXTMG group were significantly increased as compared with that of the model group (p<0.01) (Fig. 10b).
Evaluation of oxygen free radical scavenge ability and determination of quercetin IC50
The oxygen free radical scavenging abilities of vitamin C, YXTMG and quercetin were evaluated, and it was found that both the traditional Chinese medicine compound and the active monomer compound had good antioxidant capacity (Fig. 11a). At the concentration of 5 mg mL-1, the antioxidant capacity was ranked as YXTMG, vitamin C, and quercetin in descending order of strength. The IC50 curve was illustrated and it was found that the ½ of the actual concentration (responsible for activity) of quercetin improved the cells damaged by oxidative stress, which was 7.07 μ M (fig.11b).
Molecular docking verification results
The 3D structures of protein and drug molecules were downloaded in the database, and the docking was performed using ADT4.2 tool. The docking results were displayed in the form of heat map. The binding energies of multiple components of YXTMG to multiple targets of TLR4 pathway of COVID-19 pathway were low. Compared with the positive drug (prednisone), the panaxadiol in the compound showed better binding ability with zelactone A (fig 12a), indicating that YXTMG had good anti-inflammatory effect. The Pymol software was used for analysis and mapping of panaxadiol and IKBA, IKKB, and TLR4, and for analysis and mapping of zelactone A and NFκB, and IRAK4. It was found that the compound was stably combined in the cavity of the target molecule, as shown in Fig. 12b.
Effect of YXTMG on Expression of Target Molecular Proteins
Western blot was used to detect the relative expression levels of TLR4 and NFκB in the COVID-19 pathway of the control group, the model group, the prednisone group, the quercetin group and the YXTMG group. It was found that the expression levels of TLR4 and NFκB in the model group were significantly higher than those in the control group (p<0.05). Compared with the model group, the protein expression level of the prednisone group was decreased (p<0.05). The expression of TLR4 was significantly reduced by 50μM quercetin (p<0.01). The expressions of TLR4 and NFκB in the YXTMG group were decreased to different degrees, and the decreases were noted mostly in the three dosing groups (fig.13)
Effect of YXTMG on Levels of Cytokines of AECⅡ Induced by Oxidative Injury
To determine whether the drugs improved the activity of cells damaged by oxidation through immune pathway, TNF-α, IL-6 and IL-10 of cells in each group were tested. The results showed that while compared with the control group, the levels of TNF-α and IL-6 in the model group were increased, while the level of IL-10 was decreased (p<0.05). The levels of TNF-α and IL-6 in each administration group were decreased to different degrees, and the level of IL-10 was increased to different degrees in comparison with the model group (fig.14).