Tandem Mass Tag-based quantitative proteomics analysis of metabolic associated fatty liver disease induced by high fat diet in mice

Abstract

Abstract Background Although metabolic associated fatty liver disease (MAFLD) is the most common chronic liver disease worldwide, the exact molecular mechanism of MAFLD progression remains unknown. In the present study, Tandem Mass Tag-labeled quantitative proteomic technology was used to elucidate the protein expression patterns of liver tissues in the progression of MAFLD, providing new potential therapeutic targets of it. Methods Five 6-week-old male C57BL/6 mice were fed with high fat diet (HFD) for 22 weeks to establish the MAFLD mouse models. Five C57BL/6 mice of the same age were fed with normal diet (ND) and taken as controls. Mice serum were sampled for biochemical tests, and livers were isolated for histopathological examinations. Six mouse liver samples (three from each group) were performed for proteomic analysis. Differentially expressed proteins were defined using fold change of > 1.5 or < 0.67 and p value < 0.05 as thresholds. Bioinformatic analysis was used to identify the hub proteins. Real-Time Quantitative Polymerase Chain Reaction (RT-qPCR), Gene Expression Omnibus dataset, western blotting and immunohistochemistry were used to validate the expression of identified hub proteins. Results After 22 weeks on HFD diet, all mice developed MAFLD demonstrated by histopathological examination. Mouse body weights, liver weights, serum alanine transaminase and aspartate transaminase levels were significantly higher in the HFD group than ND group. Proteomics technology identified 4915 proteins in the mouse livers, among which 71 proteins were differentially expressed. Kyoto Encyclopedia of Genes and Genomes pathway analysis showed that majority of the differentially expressed proteins were involved in the peroxisome and peroxisome proliferator-activated receptor signaling pathway, as well as biosynthesis of unsaturated fatty acids. Protein–protein interaction analysis showed that these differentially expressed proteins interacted with each other and formed a complex network. Ten hub proteins were identified and validated using RT-qPCR. Five of these proteins were validated in the Gene Expression Omnibus dataset. Finally, Enoyl-CoA hydratase and 3-hydroxyacyl CoA dehydrogenase protein was validated in mouse liver tissue samples using western blotting and immunohistochemistry. Conclusion Our data showed that lipid metabolism-related pathways are closely associated with the development of MAFLD. The identified hub proteins might be novel targets for treating MAFLD.

Keywords

• Metabolic associated fatty liver disease
• Proteomics
• Tandem Mass Tag