Quantitative proteomics of HFD-induced fatty liver uncovers novel transcription factors of lipid metabolism

Nonalcoholic fatty liver disease (NAFLD) has become the most common chronic liver disease, which progression is tightly regulated by transcription factors (TFs), nuclear receptors, and cellular enzymes. In this study, a label-free quantitative proteomic approach was used to determine the effect of the high-fat diet on the proteomics profile of liver tissue and to identify novel NAFLD related TFs. Mice were fed with HFD for 16 weeks to establish a NAFLD mouse model. Mice fed with normal chow diet were taken as controls. Liver samples were collected from each group for proteomics analysis. A total of 2298 proteins were quantified, among which 106 proteins were downregulated, while 256 proteins were upregulated in HFD-fed mice compared with the controls with fold change more than 1.5 and p value less than 0.05. Bioinformatic analysis revealed that metabolic-related functions and pathways were most significantly enriched. A subgroup of 11 TFs were observed to share interactions with metabolic-related enzymes and kinases by protein-protein interaction analysis. Among them, 7 TFs were selected for verification, and 3 TFs were finally validated, including Rbbp4, Tcea1, and ILF2. Downregulating each of the 3 TFs could significantly promote lipid accumulation in AML12 hepatocytes, by regulating the expression of fatty acid synthesis- or beta-oxidation-related genes. In contrast, overexpression of Tcea1, Rbbp4, and ILF2, respectively, could ameliorate hepatocyte steatosis. These findings propose novel lipid metabolism related TFs, which might have potential roles in preventing NAFLD.

Automated summary

This study used a label-free quantitative proteomic approach to explore the impact of a high-fat diet on liver tissue proteomic profile and identify novel transcription factors (TFs) related to nonalcoholic fatty liver disease (NAFLD). Results showed that metabolic-related proteins were significantly enriched and a subgroup of 11 TFs were found to interact with metabolic-related enzymes and kinases. Further analysis identified Rbbp4, Tcea1, and ILF2 as TFs that play important roles in lipid metabolism and NAFLD prevention.