3.1 YQJPF preserved liver failure in vivo
Establish ACLF model on SD rat as previously described[[i]]. The pathological changes in liver tissues were evaluated with H&E staining. The livers were rosy and smooth with intact lobule structure in the Control group. However, the livers in the ACLF Model group became small and hard accompanied by necrosis, with small nodules on their surface (Fig. 1A). As shown in Fig. 1B, the liver tissue of rats in the Control group was well-organized and the liver cells were intact. In the ACLF Model group, the liver tissue structure was disordered, and the fibrous tissue was obviously proliferated, accompanied by a large number of inflammatory cell infiltration, pseudolobule formation, large and sub-large hepatocyte necrosis, vacuolation, dilation and congestion of hepatic sinusoids. The liver tissue fibrosis in the YQJPF group and Methylprednisolone group was improved, the number of inflammatory cell infiltration and pseudolobule formation were reduced compared with the Model group, so was the hepatocyte necrosis and vacuolation.
As shown in Masson staining (Fig. 1C), in the Control group, only a small amount of collagen staining was seen on the blood vessel wall. The collagen deposition in the ACLF Model group was significantly increased. Collagen fibers were found to form filaments or even thick cords around the sinuses. The structure of liver lobules was disordered and fibrous tissue proliferation was also seen. After YQJPF and methylprednisolone treatment, collagen deposition and collagen volume fraction were significantly improved compared with the ACLF Model group .
Sirius staining results showed that the liver tissues in the Model group were severely fibrotic (Fig. 1D), and there was a large amount of red collagen-like fibrous material deposited around the liver tissue portal area. Compared with the Model group, the red fiber-like material around the liver tissue portal area, and the bold duct of the treatment group were significantly reduced after YQJPF and methylprednisolone treatment.
Levels of AST and ALT were detected to assess the damage of hepatocytes. Liver tissue levels of ALT and AST were increased significantly in the Model group. The levels of these enzymes were decreased in YQJPF treatment group and methylprednisolone group. Thus, YQJPF exerted a protective effect on liver damage in ACLF.
3.2 YQJPF impress Hepatocyte proliferation and apoptosis in Liver Injury
In order to further explain the mechanism of YQJPF, we selected L02 human hepatocyte cell line for further analysis, LPS (4 μg/ml) induced to establish a liver injury model, and then YQJPF (10μg/ml, 20μg/ml, 40μg/ml) intervent for 24 hours to verify the effect. Cell Counting Kit-8 analysis showed that YQJPF could dose-dependently attenuates cell viability (Fig. 2A). Apoptosis morphology was detected with fluorescence microscopy, it implied that LPS induce apoptosis in hepatocytes and YQJPF could inhibit apoptosis (Fig. 2B). In the LPS-induced Model group, the expression of Bax was increased, while the production of Bcl-2 was dramatically reduced compared to that in the Control group. YQJPF activates Bcl2, reduces BAX, and shifts the BAX/Bcl2 ratio in a anti-apoptotic direction (Fig. 2D). CCK-8 analysis indicated that YQJPF 20μg/ml have the analogous effect as apoptosis inhibitor Z-VAD-FMK to restore cell viability (Fig. 2C). Overall YQJPF could promote hepatocyte proliferation, and influence the apoptosis.
3.3 Network Pharmacology
3.3.1 Screening of Active Components in YQJPF
The fingerprint of the water extract of YQJPF was performed by high performance liquid chromatography (HPLC) (Fig.1A). The four main peak compounds in the HPLC were identified as Calycosin-7-O-β-D-glucoside, Ferulic acid, Hesperidin, Glycyrrhizic acid.
By a comprehensive search of the TCMSP, a list of components in YQJPF was obtained, after ADME screening (OB ≥30%, OB(Glycyrrhiza uralensis) ≥50%; DL ≥0.18), 117 active components in YQJPF matched the combined filtering criteria which integrated by OB and DL. 15 components, like Resveratrol, Astragalus polysaccharide, Licopyranocoumarin, etc, confirmed as the bioactive components of the herb medicines according to previous researches, simultaneous determination of four bioactive compounds in YQJPF extracts by high performance liquid chromatography. Other components were obtained from TCMID database (Supplementary Table S1).
For further analysis, there were totally 135 active components in 9 herbs, among them 24 active components in Astragalus membranaceus (Huang Qi), 18 active components in Radix pseudostellariae (Tai Zishen), 15 active components in Angelica sinensis (Dang Gui), 12 active components in Fructus Ligustri Lucidi (Nv Zhenzi), 11 active components in Poria Wolfiporia extensa (Fu Lin) and 9 in Atractylodes macrocephala (Bai Zhu), 6 in Pericarpium citri reticulatae (Chen Pi), 31 in Scutellaria baicalensis (Huang Qin), 25 active components in Glycyrrhiza uralensis (Gan Cao). In addition, 14 active components were common ingredients in more than two herbs (Table S2).
3.3.2 The Potential Targets of Active Compounds in YQJPF
The active compound targets were searched via the TCMSP and Swiss Target Prediction databases for each chemical component. The targets were transformed using the UniProt knowledge database, data were merged to obtain gene symbols. After eliminating the redundant targets, a total of 573 known therapeutic targets were collected from 135 compounds (Tables S3-S11). For further analysis, a Compound-Target network was visualized using Cytoscape. The network contains 715 nodes and 2979 edges. Among them 135 nodes represented the active components, and 573 nodes represent the corresponding targets of the ingredients (Fig. 3B). The Compound-Target network showed that a herb could interact with multiple components, and a compound could also interact with several targets, which coincided with the synergistic effect theory of multi-components and multi-targets of traditional Chinese medicine formula. The degree (connection strength) was reflected by the node’s sizes, according to the degree value, Fig. 3C and Table S12-13 showed the top 10 active components and targets.
3.3.3 Acquisition of Therapeutic Gene Targets for Liver Failure
To investigate the therapeutic gene targets in liver failure, we analyzed the expression profiles data from GEO database. We applied the GEO2R online analysis tool with default parameters to screen the differentially expressed genes (DEGs) in two GEO series (GSE14668, GSE38941 ), using adjusted P value < 0.05 and logFC ≤ −1 or logFC ≥ 1 as the cut-off criteria. Two GEO series contains 18 normal and 25 liver failure samples. Fig. 4A-4B showed the up-regulated genes and down-regulated genes. Venn diagram identified 2961 common DEGs in two GEO series. 21 DEGs with inconsistent trends had been excluded. Overall, 2940 DEGs were obtained, including 1760 up-regulated and 1180 down-regulated genes (Fig. 4C,Table S14-16).
3.3.4 Potential Targets of YQJPF Decoction on Liver Failure
Venn diagram showed that 2940 gene symbols for disease and 573 gene symbols for drugs had 163 overlap. That was, 163 gene symbols would mostly likely to be the therapeutic targets for liver failure treatment by YQJPF Decoction (Fig. 5A, Table S17).
3.3.5 Construction of PPI and Compound-Target-Disease network for potential therapeutic targets
The 163 potential therapeutic targets were uploaded to the STRING database, which provided the information on predicted interaction. Furthermore, we imported the above data into Cytoscape 3.7.1 to calculate the characteristics of the network and construct the protein-protein interaction network (PPI network) (Fig. 5B). In the PPI network, targets with higher degree played an important role in the protein-protein correlation. In Fig. 5C, ranked by degree value, 18 targets were collected to be the hub targets, namely VEGFA, EGFR, STAT3, CXCL8, ESR1, CCND1, PTPRC, MMP2, PECAM1, AR, SPP1, EDN1, CRP, F2, TIMP1, IRS1, HGF, CAV1, more details shown in Table S18. Then we built a Compound-Target-Disease network of complex information based on interactions between the drug (YQJPF), active compounds, and disease (ACLF) using Cytoscape to undertake visual analysis (Fig. 5D). In this network quercetin, resveratrol, syringaresinol diglucoside, luteolin, etc had higher degree value than other active compounds, connected to more than seven genes, so they would be the main active compounds to treat liver failure, more details shown in Table 1.
3.3.6 Analyses of Enrichment of the KEGG/GO Pathways
Gene ontology (GO), KEGG pathway enrichment analysis were performed in Metascape (http://metascape.org), with P Value <0.01; Enrichment > 1.5. GO enrichment analysis of the 163 potential therapeutic targets was performed for identifying the relevant biological functions of YQJPF against liver failure. The top 10 significantly enriched terms with a greater number of involved targets in biological process (BP) , molecular unction (MF) and cellular component (CC) categories were shown in Fig. 5E, which indicated that YQJPF may regulate oxidoreductase, nuclear receptor, get involved in wound healing, regeneration, metabolic process and so on. To explore the potential pathways of YQJPF on liver failure, the pathway enrichment of the 163 potential therapeutic targets was performed. The top 20 significantly enriched pathways were shown in Fig. 5F. Excluded pathways not related to liver disease or cancer-related pathways. PI3K/AKT, p53, FoxO, HIF-1, AMPK signaling pathways were the prominently enriched signaling pathways according to the gene count and P value (Table S20), which associated with inflammation, hypoxia, metabolism and proliferation. VEGF-A showed the highest degree value in hub targets. According to KEGG pathway enrichment analysis (Table 2, Table S20), apoptosis related genes BAX, Bcl-2 were closely related to the above pathways.
3.4 Effects of YQJPF on the hypoxic and apoptosis pathways
According to the network pharmacology analysis results, PI3K-AKT, HIF-ɑ were the primary pathways, VEGF-A was identified as the primary drug candidate targets for the treatment of YQJPF on liver failure, and it was a downstream target marker of HIF-1ɑ, hypoxia-related cell injury plays an important role in acute and chronic liver failure[[ii]]. HIF-1 and VEGF-A increase under hypoxic conditions, act as a mediator for cell adaptation to a harmful environment. So we further investigated the mechanism of YQJPF on relieving liver injury by examining the protein levels in CCl4 and LPS/D-gal induced ACLF model rats. YQJPF upregulated the expression of PI3K, AKT, HIF-1ɑ, VEGF-A. Besides, YQJPF increased HIF-1ɑ and VEGF-A expression by immunohistochemistry analysis, which indicated that hypoxic pathway significantly enhanced after YQJPF treatment. Moreover The expression of BCL-2, and BAX followed the same trend as the in vitro study results. Taken together, these findings may indicate that the mechanism of YQJPF on ACLF may through PI3K/AKT signaling pathway, modulate the the expression of HIF-1ɑ, VEGF-A, and apoptosis associated BCL-2, BAX. YQJPF could ameliorates liver injury through influencing hypoxia damage and apotosis (Fig. 6A).