The effect of Hua-Feng-Dan and Yaomu on serum enzyme activities and liver pathology
Seven days after administration, the body weight of mice in each group increased slightly (The initial weights were 22.52 ± 0.51, 22.12 ± 1.16, 23.06 ± 1.28, 23.28 ± 0.68 g for Control, Yaomu-0.1, Yaomu-0.3, and Hua-Feng-Dan groups, respectively; the final weights were 23.64 ± 1.08, 23.3 ±1.06, 23.9 ± 1.15, 24.74 ± 0.66 g for Control, Yaomu-0.1, Yaomu-0.3, and Hua-Feng-Dan groups, respectively). All mice were in good health, the hair is shiny, there is no hair loss, the intake of diet and water is normal, and there were no other abnormal phenomena. Compared with the Control group (ALT, 14.5 ± 0.73IU/L; AST, 19.0 ± 2.21 IU/L), there was no significant difference in serum ALT and AST of mice in Yaomu-0.1 group (ALT, 13.9 ± 2.66 IU/L; AST, 23.2 ± 1.09 IU/L), Yaomu-0.3 group (ALT, 13.8 ± 3.06 IU/L; AST, 16.7 ± 3.62 IU/L) and Hua-Feng-Dan group (ALT, 22.3 ± 8.70IU/L; AST, 20.0 ± 6.59 IU/L). This result showed that Hua-Feng-Dan and Yaomu at the clinical dose did not cause hepatic toxicity.
The liver lobules of the mice in the Control group and treatment groups were clear and complete, without degeneration and necrosis of hepatocytes, and the liver cords were arranged radially around the central vein. No obvious pathological damage was observed in the liver after administration of different doses of Yaomu (YM) and Hua-Feng-Dan (HFD) to mice (Fig. 1).
Gene Expression Pattern overview
The results (~22500/sample) obtained from RNA-Seq FPKM were transformed to gene raw counts, and then subjected to cluster analysis. The clustering heatmaps of gene expressions from 12 individual samples (Fig. 2A) and 4 groups (Fig. 2B) are shown. Red represents the up-regulation; blue represents the down-regulation. The color brightness is associated with differences. Fig. 2A shows the heatmap of 12 individual samples. Some of the three samples in each group showed similar patterns (L-1, L-2 and L-3, Control group; L-7, L-8 and L9, YM-H group), while in YM-L group, L-5 was somewhat different from L-4, and quite different from L6. In Hua-Feng-Dan (HFD) group, L-11 was separated from L-10 and L-12. Fig. 2B shows the heatmap of 4 groups, YM-L was separated from others, and YM-H was slightly different from Control; and Hua-Feng-Dan (HFD) had clear pattern different from Control.
GO and KEGG pathway enrichment analysis
The GO database standardizes the description of differentially expressed genes in terms of function, participating biological pathways, and cell location. The KEGG is a database of the metabolic pathways of gene products in cells and the functions of these gene products. Here we focus on the comparison between Hua-Feng-Dan and Control group. Figure 3 summarizes the top 20 enriched by GO and the top 7 enriched by KEGG pathway. GO Enrichment Analysis shows that the biological process of differentially expressed genes was mainly involved in lipid metabolism, sterol homeostasis, cholesterol homeostasis, intestinal absorption, protein folding and cell adhesion (Figure 3A). KEGG Enrichment Analysis shows that pathways of differentially expressed genes were mainly involved in cholesterol metabolism, bile secretion, PPAR signaling pathway, drug metabolism, fat digestion and absorption, retinol metabolism and the like (Figure 3B).
Differentially Expressed Gene Analysis
Differentially expressed genes (DEGs) were analyzed via the DESeq2 method compared to Controls. DEGs were set at p < 0.05. Using complete clustering, the DEGs were clustered and input into Treeview to visualize the differences between groups (red indicates up-regulation and blue indicates down-regulation). From Figure 4, compared to Hua-Feng-Dan group (806 DEGs), YM-L group had 235 DEGs and YM-H group had 92 DEGs. Four clusters were selected for annotation (two upregulated: line 42-150, 109 genes increased in HFD and YM-L group only, involved in cellular function and signal regulation; line 151-179, 28 genes involved in cellular function, circadian, and signal transduction were increased in all three groups. Two downregulated cluster: line 494-556, 63 genes decreased in HFD and YM-L group only, while line 557-567, 11 genes decreased in all three groups. These genes are involved in Phase-I, II, and III metabolism and immunomodulation. The clustered DEGs with the annotation for gene names are shown in Supplementary Table 1.
qPCR analysis of selected DEGs
Selected 10 DEGs were further analyzed via real time qPCR (Figure 5). The expression of Cyp2a4 was increased 2.2-fold by Hua-Feng-Dan (HFD), but was unaffected by YM-0.1 and YM-0.3; the expression of Cyp4a14 was increased 2.3-fold by HFD, YM-0.1 and 0.3 did not affect its expression. The expression of Fgf21 was increased by HFD (3.7-fold), although not reaching significance; the expression of Gm3776 was increased 6.5-fold by HFD; The expression of Mt2 (10-fold) and Gsta1 (4.7-fold) was increased by HFD. The expression of Il1rn (24-fold) and Egr1 (8.9-fold) was increased by HFD. The expression of Trib3 (1.7-fold) and Bcl2a1d (1.7-fold) was tended to increase, but not significant. The two doses of YM had little effects on the expression of these genes.
Ingenuity Pathways Analysis of DEGs
The IPA upstream regulator analysis (Figure 6) was used to identify the upstream regulators that may be responsible for gene expression changes observed in the study. IPA predicts which upstream regulators are activated or inhibited to explain the up-regulated and down-regulated genes observed. The top 25 upstream regulators were selected, including 18 increased by Hua-Feng-Dan with molecules (Tgf beta; NRG1; Vegf; NFκB (complex); JUN; STAT3; CREB1; P38 MAPK; CHUK; EGR1; ERK1/2; and EP300) or with chemicals (Tretinoin; carbon tetrachloride; decitabine; ursodeoxycholic acid; AGN194204 and 4-hydroxytamoxifen). The 7 downregulated regulators were molecules (Let-7a-5p, ACOX1, and DICER1) and chemicals (MEK1/2 inhibitor U0126; p38 MAPK inhibitor SB203580; JNK inhibitor SP600125; and PIK3 inhibitor LY294002). All of these upstream regulators point towards activation of MAPK signaling pathways and adaptive responses with the downregulation of inhibitors for MAPK and PIK3 signaling pathways. YM-0.1 produced similar upstream regulator alternations in the similar direction, except for ursodeoxycholic acid; while the high dose of YM (0.3g/kg) produced weak alterations in these regulators, with 3 in opposite directions (different color).
Illumina BaseSpace Correlation Engine analysis of DEGs
All the biosets were imported into BSCE for curated studies, filtered by mice, RNA expression and treatment vs control, and the curated files were exported and the -log (p-values) were calculated and the VLOOKUP function was used for correlation comparison with the GEO database. There were very high correlations between HFD-induced DEGs and 25 GSE databases with -log(p-values) from 12 to 26.9 (Figure 7). The deeper the red color, the higher -log (p-values), and the values >4 is considered significant . YM-0.1 moderately correlated with 18 GSE databases in the same direction but to the lesser extent, while YM-0.3 only weakly correlated with 9 databases, and negatively correlated with 3 databases (blue color). Thus, Hua-Feng-Dan at the clinical dose mimics chemical-induced adaptive responses, while YM-0.1 could mimic some effects of HFD, but YM-0.3 has little effect, suggesting that the use of Yaomu at appropriate doses is important to induce adaptive responses.