Integrated multi-omic analysis identifies fatty acid binding protein 4 as a biomarker and therapeutic target of ischemia-reperfusion injury in steatotic liver transplantation

Abstract

Background and aims: Due to a lack of donor grafts, steatotic livers are used more often for liver transplantation (LT). However, steatotic donor livers are more sensitive to ischemia-reperfusion (IR) injury and have a worse prognosis after LT. Efforts to optimize steatotic liver grafts by identifying injury targets and interventions have become a hot issue.

Methods: Mouse LT models were established, and 4D label-free proteome sequencing was performed for four groups: normal control (NC) SHAM, high-fat (HF) SHAM, NC LT, and HF LT to screen molecular targets for aggravating liver injury in steatotic LT. Expression detection of molecular targets was performed based on liver specimens from 110 donors to verify its impact on the overall survival of recipients. Pharmacological intervention using small-molecule inhibitors on an injury-related target was used to evaluate the therapeutic effect. Transcriptomics and metabolomics were performed to explore the regulatory network and further integrated bioinformatics analysis and multiplex immunofluorescence were adopted to assess the regulation of pathways and organelles.

Results: HF LT group represented worse liver function compared with NC LT group, including more apoptotic hepatocytes (P < 0.01) and higher serum transaminase (P < 0.05). Proteomic results revealed that the mitochondrial membrane, endocytosis, and oxidative phosphorylation pathways were upregulated in HF LT group. Fatty acid binding protein 4 (FABP4) was identified as a hypoxia-inducible protein (fold change > 2 and P < 0.05) that sensitized mice to IR injury in steatotic LT. The overall survival of recipients using liver grafts with high expression of FABP4 was significantly worse than low expression of FABP4 (68.5 vs. 87.3%, P < 0.05). Adoption of FABP4 inhibitor could protect the steatotic liver from IR injury during transplantation, including reducing hepatocyte apoptosis, reducing serum transaminase (P < 0.05), and alleviating oxidative stress damage (P < 0.01). According to integrated transcriptomics and metabolomics analysis, cAMP signaling pathway was enriched following FABP4 inhibitor use. The activation of cAMP signaling pathway was validated. Microscopy and immunofluorescence staining results suggested that FABP4 inhibitors could regulate mitochondrial membrane homeostasis in steatotic LT.

Conclusions: FABP4 was identified as a hypoxia-inducible protein that sensitized steatotic liver grafts to IR injury. The FABP4 inhibitor, BMS-309403, could activate of cAMP signaling pathway thereby modulating mitochondrial membrane homeostasis, reducing oxidative stress injury in steatotic donors.

Keywords: Fatty acid binding protein 4; Liver steatosis; Liver transplantation; Metabolomics; Mitochondrion; Proteomics; Transcriptomics.

Fig. 1

Establishment and validation of mouse liver transplantation model. A Oil Red O staining of mouse liver transplantation model. B H&E staining. C, D TUNEL staining. E–H Liver function detection of ALT, AST, LDH, and TB. I–L Relative expression of Bax, cleaved Caspase-3, and cleaved PARP. ns, not significant; *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.001

Fig. 2

Proteomic profile revealing the change during liver transplantation. A Heatmap of the differentially expressed proteins. Red rectangles mean that proteins are upregulated, and green ones mean that they are downregulated. B Principal component analysis of the duplicate samples, in which the degree of aggregation among samples represents statistical consistency. C Volcano plot of the differentially expressed proteins between NC SHAM and HF SHAM groups. Gray dots represent genes that are not differentially expressed; red dots and blue dots represent genes that are upregulated and downregulated significantly. D Volcano plot of the differentially expressed proteins between NC LT and HF LT groups. E Venn diagram demonstrating shared and discrete proteins in each of these four groups. F Expression patterns of these differentially expressed proteins based on membership and expression. G Protein–protein interaction network of differentially expressed proteins with FABP4

Fig. 3

Relationship with FABP4 expression and liver transplantation recipients’ overall survival. A FABP4 is a high expression of donors’ liver tissue microarray IHC staining. B FABP4 low expression of IHC staining. C Comparison of overall survival rate between FABP4 high- and low-expression groups. D Comparison of the incidence of early allograft dysfunction. E Comparison of the risk of liver steatosis

Fig. 4

Influence of FABP4 inhibitor on mouse high fatty liver transplantation model. A H&E staining of mouse liver transplantation model after using FABP4 inhibitor. B TUNEL staining. C–F Liver function detection of ALT, AST, LDH, and TB. G–I Oxidative stress injury assay of GSH, MDA, and SOD. J–N Relative expression of FABP4, Bax, cleaved Caspase-3, and cleaved PARP. ns, not significant; *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.001

Fig. 5

Transcriptomic profiles revealing the influence of FABP4 inhibitor. A Violin diagram of expression patterns of all genes. B Principal component analysis of the duplicate samples. C Heatmap of the differentially expressed genes. D Volcano plot of the differentially expressed genes between HF LT and HF BMS groups. E Gene ontology pathway enrichment for differentially expressed proteins. The circle sizes represent the number of genes enriched in pathways, and the circle’s color means significance. F KEGG pathway enrichment for differentially expressed proteins

Fig. 6

Metabolomic profiles revealing the influence of FABP4 inhibitor. A Total ion chromatogram of spectral overlap comparison, with response intensity and retention time overlapping. B Principal component analysis of the duplicate samples. C Volcano plot of the differentially expressed metabolites between HF LT and HF BMS groups. D Heatmap of the differentially expressed metabolites. E Correlation analysis between metabolites and visualized in the form of correlation heatmaps. F Revealing the co-regulatory relationships between various metabolites by chord diagrams

Fig. 7

Integrated transcriptomic and metabolomic analysis. A KEGG pathways that transcriptomic and metabolomic respectively enriched. B KEGG pathways that transcriptomic and metabolomic simultaneously enriched. C Spearman’s correlation hierarchical clustering analysis of differences in the expression patterns. D Correlation network analysis of significant differences in key node locations

Fig. 8

Influence of FABP4 inhibitor on cAMP signaling pathway. A–E Relative expression of HHIP, ADRB2, RAC2, and PKA. F, G The content of Prostaglandin i2 and N-oleoylethanolamine validated by ELISA. H–K The mRNA expression of Hhip, Adrb2, Rac2, and Adcy7 of HF LT and HF BMS groups. ns, not significant; *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.001

Fig. 9

Influence of FABP4 inhibitor on high fatty liver mitochondrion. A–C Transmission electron microscopy image of mouse liver in each group. A The mitochondrial structure was clear, and no autophagosomes were presented in the HF SHAM group. B Autophagosomes and autolysosomes were found in the HF LT group with mitochondrial swelling. C The mitochondrial structure of the HF BMS group was clear, and damaged parts of mitochondria were lytic. D–F Multiplex immunofluorescence staining of rhodamine reagent for detecting mitochondrial membrane potential. Green fluorescence represents mitochondrial membranous potential, red fluorescence represents apoptotic hepatocytes, and blue fluorescence represents nuclear staining. G–I Relative expression of DRP1 and MFN-1. ns, not significant; *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.001. AP, autophagosomes; ASS, autolysosome; LD, lipid droplets; M, mitochondria; RER, rough endoplasmic reticulum

Fig. 10

Influence of FABP4 siRNA on in vitro hypoxia / reoxygenation model. A–D Flow cytometry was performed to detect the hypoxic injury-induced apoptosis of AML12 cells. E–H Liver function detection of ALT, AST, LDH, and TB using the supernatant of each group. I–P Relative expression of FABP4, PKA, RAC2, HHIP, ADRB, DRP1, and MFN-1. ns, not significant; *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.001