Intestinal flora disorder PPI network
Introduce 80 disease targets related to intestinal flora disorder obtained from the database into String 11.0 database, and set high confidence >0.7. In addition, "the 1st shell" and "the 2nd shell" were set to "no more than 20 interactors" in this study. The protein interaction data was then visualized by Cytoscape 3.7.2 software to obtain the PPI network of intestinal flora disorder (as shown in Figure 2). The network had 86 nodes, which interacted with 930 edges. The size of nodes is positively correlated with the degree value of nodes. Module analysis was conducted through the MCODE plugin. Select the genes for module 1 (41 genes) and module 2 (12 genes) and intersect the first 10 hub genes obtained from cytoHubba plugin to obtain the key disease targets related to intestinal flora disorder. According to the above method, a total of 10 key targets related to intestinal flora disorder were produced (as shown in Supplementary Table 1).
DEGs screening of NAFLD
The gene chips obtained from GEO database were analyzed by R 4.0.2 (as shown in Figure 3). In the volcano plots, the red nodes represent upregulated genes and green nodes represent downregulated genes. In the heat maps, red areas represent upregulated genes and blue or green represents downregulated genes. According to the adjusted criteria of P≤0.05 and |log2 (FC) |≥1.5, 93 DEGs were selected from GSE89632 chip (67 down-regulated genes, 26 up-regulated genes). 50 integrated DEGs were screened from GSE17470, GSE24807, GSE33814, GSE89632 and GSE48452 (24 down-regulated genes, 26 up-regulated genes). And 53 DEGs were screened out in GSE58979 (51 down-regulated genes, 2 up-regulated genes). Information on differentially expressed genes is shown in supplementary table 2.
NAFLD PPI network
718 SS disease targets, 379 NASH related targets and 171 NASH cirrhosis relates targets were input into the String 11.0 database, respectively, with a high confidence greater than 0.7. And the obtained protein interaction data were imported into Cytoscape 3.7.2 software to build SS PPI network (Figure 4-a), NASH PPI network (Figure 4-b) and NASH cirrhosis PPI network (Figure 4-c). The module analysis of the MCODE plugin and the hub genes of cytoHubba plugin were used to screen the key disease targets of these three PPI networks. The key targets of the disease are obtained by intersecting the genes of the first two modules and the top 10% of the hub genes.
The PPI network of SS has 591 nodes and 5295 edges. Module analysis was conducted through the MCODE plugin. Select the genes for module 1 (25 genes) and module 2 (45 genes) and intersect the first 72 hub genes obtained from cytoHubba plugin to obtain the key disease targets related to SS. According to the above method, a total of 57 key targets related to SS were produced (as shown in Supplementary Table 1). The PPI network of NASH has 300 nodes and 1746 edges. Module analysis was conducted through the MCODE plugin. Select the genes for module 1 (18 genes) and module 2 (21 genes) and intersect the first 38 hub genes obtained from cytoHubba plugin to obtain the key disease targets related to NASH. According to the above method, a total of 36 key targets related to NASH were produced (as shown in Supplementary Table 1). The PPI network of NASH cirrhosis has 128 nodes and 630 edges. Module analysis was conducted through the MCODE plugin. Select the genes for module 1 (17 genes) and module 2 (9 genes) and intersect the first 18 hub genes obtained from cytoHubba plugin to obtain the key disease targets related to NASH. According to the above method, a total of 17 key targets related to NASH were produced (as shown in Supplementary Table 1).
Merge of intestinal flora disorder PPI network and NAFLD PPI network
The PPI network of intestinal flora disorder and the PPI network of SS, NASH and NASH cirrhosis were merged through the merge function of Cytoscape 3.7.2 software, respectively. And the possible targets of intestinal flora in the treatment of NAFLD were found. We have obtained 20 possible targets for treating SS, 7 for treating NASH, and 7 for treating NASH cirrhosis. These are potential targets for intestinal flora to intervene in different stages of NAFLD. The information of merge genes is shown in Table 1.
Merge network of NAFLD progress
The SS PPI network, NASH PPI network, and NASH cirrhosis PPI network are merged by the merge function of Cytoscape software respectively, in order to find key targets for NAFLD development. The module analysis of the MCODE plugin and the hub genes of cytoHubba plugin were used to screen the key progress targets of NAFLD. The key progress targets of NAFLD are obtained by intersecting the first two modules and the top 10% of the hub genes, in the merge network.
The merge network of SS PPI network and NASH PPI network has 171 nodes and 1044 edges (as shown in Figure 5-a). Module analysis was conducted through the MCODE plugin. Select the genes for module 1 (27 genes) and module 2 (9 genes) and intersect the first 18 hub genes obtained from cytoHubba plugin to obtain the key disease targets related to the progression from SS to NASH. Based on the above approach, a total of 17 key targets related to the progression from SS to NASH were obtained. The merge network of NASH PPI network and NASH cirrhosis PPI network has 50 nodes and 207 edges. (as shown in Figure 5-b) Module analysis was conducted through the MCODE plugin. Select the genes for module 1 (14 genes) and module 2 (5 genes) and intersect the first 11 hub genes obtained from cytoHubba plugin to obtain the key disease targets related to the progression from NASH to NASH cirrhosis. Based on the above approach, a total of 11 key targets related to the progression from NASH to NASH cirrhosis were obtained. The merge network of SS PPI network and NASH cirrhosis PPI network has 108 nodes and 530 edges. (as shown in Figure 5-c) Module analysis was conducted through the MCODE plugin. Select the genes for module 1 (15 genes) and module 2 (6 genes) and intersect the first 5 hub genes obtained from cytoHubba plugin to obtain the key disease targets related to the progression from SS to NASH cirrhosis. Based on the above approach, a total of 5 key targets related to the progression from SS to NASH cirrhosis were obtained. The information of merge genes is shown in Table 1.
The intestinal flora disorder PPI network was merged with the merge network of NAFLD progress through the Merge function of Cytoscape 3.7.2 software, and the potential targets for intestinal flora interfering NAFLD progress were found. We obtained five potential targets (AKT1, F2, ICAM1, PTGS2, CRP) for intestinal flora to intervene the progression of NAFLD from SS to NASH, three potential targets (CRP, ICAM1, F2) for intestinal flora to intervene the progression of NAFLD from NASH to NASH cirrhosis. And seven potential targets (NOS3, IL2RA, F2, CD8A, NOS2, ICAM1, CRP) for intestinal flora to intervene the progression of NAFLD from SS to NASH cirrhosis were obtained. These are considered as potential targets for intestinal flora to intervene in the NAFLD process.
Subsequently, we compared all merge genes with DEGs of NAFLD, and found seven overlapping targets (CCL2, PTGS2, IL6, IL1B, FOS, SPINK1 and C5AR1). In this study, these 7 targets were the core potential targets for intestinal flora to intervene in NAFLD.
GO function enrichment and KEGG pathway enrichment analysis
We used R 4.0.2 (https://cran.r-project.org/doc/FAQ/R-FAQ.html#Citing-R) software to perform GO and KEGG enrichment analysis on the protein targets of the merge networks. In the bubble chart, the X-axis represents the number of target genes (Gene Ratio), and the Y-axis represents the KEGG pathway or GO term where the target gene is significantly enriched. The size of the dots intuitively reflects the size of the Gene Ratio, and the color depth of the dots reflects different p-value ranges.
The merge genes enrichment analysis of intestinal flora disorder and NAFLD PPI network is as shown in Figure 6. (1) Analysis of merge of intestinal flora disorder and SS PPI networks: (1) KEGG pathway enrichment analysis (Figure 6-a) found 148 pathways, of which 20 pathways had p-value and q-value less than 0.05. In the GO enrichment analysis (Figure 6-b), a total of 541 terms were found, of which 512 terms were related to biological processes (BP), 11 terms were related to cell composition (CC) and 18 terms were related to molecular function (MF). (2) Analysis of merge of intestinal flora disorder and NASH PPI networks: KEGG pathway enrichment analysis (Figure 6-c) found 121 pathways, of which 22 pathways had p-value and q-value less than 0.05. In the GO enrichment analysis (Figure 6-d), a total of 616 terms were found, of which 590 terms were related to biological processes (BP), 7 terms were related to cell composition (CC) and 19 terms were related to molecular function (MF). (3) Analysis of merge of intestinal flora disorder and NASH cirrhosis PPI networks: KEGG pathway enrichment analysis (Figure 6-e) found 57 pathways, of which 12 pathways had p-value and q-value less than 0.05. In the GO enrichment analysis (Figure 6-f), a total of 347 terms were found, of which 305 terms were related to biological processes (BP), 10 terms were related to cell composition (CC) and 32 terms were related to molecular function (MF).
The merge genes enrichment analysis of merge network of NAFLD progress is as shown in Figure 7. (1) Analysis of merge of intestinal flora disorder, SS, and NASH PPI networks: (1) KEGG pathway enrichment analysis (Figure 7-a) found 115 pathways, of which 15 pathways had p-value and q-value less than 0.05. In the GO enrichment analysis (Figure 7-b), a total of 670 terms were found, of which 636 terms were related to biological processes (BP), 12 terms were related to cell composition (CC) and 22 terms were related to molecular function (MF). (2) Analysis of merge of intestinal flora disorder, NASH and NASH cirrhosis PPI networks: KEGG pathway enrichment analysis (Figure 7-c) found 22 pathways, of which 21 pathways had p-value and q-value less than 0.06. In the GO enrichment analysis (Figure 7-d), a total of 323 terms were found, of which 299 terms were related to biological processes (BP), 5 terms were related to cell composition (CC) and 19 terms were related to molecular function (MF). (3) Analysis of merge of intestinal flora disorder, SS and NASH cirrhosis PPI networks: KEGG pathway enrichment analysis (Figure 7-e) found 57 pathways, of which 12 pathways had p-value and q-value less than 0.05. In the GO enrichment analysis (Figure 7-f), a total of 347 terms were found, of which 305 terms were related to biological processes (BP), 10 terms were related to cell composition (CC) and 32 terms were related to molecular function (MF).
Sort-target-term-pathway network
Figure 8 was obtained by visualizing the merge genes, GO terms and KEGG pathways through Cytoscape 3.7.2 software. The network has 153 nodes (6 nodes for merge sort, 20 nodes for merge genes, 3 nodes for GO sort, 69 nodes for GO terms, 13 nodes for KEGG BRITE, 42 nodes for KEGG pathways) and 480 edges. The targets with degree value greater than 10 were AKT1, ICAM1, NOS3, PTGS2, NOS2, F2, CRP, EDN1, CSF2, CD8A and CDH1. The top 10 GO terms of degree value are mainly BP terms (response to molecule of bacterial origin, response to lipopolysaccharide, reactive oxygen species metabolic process, neurotransmitter metabolic process, nitric oxide biosynthetic process, neurotransmitter biosynthetic process, nitric oxide metabolic process, reactive oxygen species biosynthetic process, positive regulation of reactive oxygen species metabolic process, and reactive nitrogen species metabolic process). The KEGG pathway with higher degree value is mainly related to signal transduction (TNF signaling pathway, HIF-1 signaling pathway, Apelin signaling pathway, JAK-STAT signaling pathway), human disease (AGE-RAGE signaling pathway in diabetic complications, Human T-cell leukemia virus 1 infection, Kaposi sarcoma-associated herpesvirus infection, Fluid shear stress and atherosclerosis) and endocrine system (Estrogen signaling pathway, Relaxin signaling pathway)
Interference of intestinal flora with the pathological process of NAFLD is closely associated with inflammation and insulin resistance. TNF signaling pathway, AGE - RAGE signaling pathway in the diabetic activity and NF-kappa B signaling pathway will promote the up-regulation of CCL2, IL6, IL1B, FOS, SPINK1, C5AR1 and PTGS2 after activation, which will lead to liver inflammation and promote the occurrence and development of NAFLD. Intestinal flora can act on SPINK1, C5AR1, and PTGS2 to improve NAFLD. CCL2, IL6, IL1B, FOS and NF-κB may play an important role in the occurrence and development of NAFLD. KEGG Database (https://www.kegg.jp/kegg/kegg1.html) and software of Pathway Builder Tool 2.0 were used to generate the figure. As seen in Figure 9, the major predictive signaling pathways for intestinal flora interfering with NAFLD were constructed.