Poster Presentation HUPO 2019 - 18th Human Proteome Organization World Congress

Proteomics of triacylglycerol accumulation and DGAT inhibition in HepG2 cells   (#778)

Lifeng Peng 1 , Bhumika Bhatt-Wessel 1 , Bill Jordan 1 , John Miller 1
  1. Victoria University of Wellington, Kelburn, WELLINGTON, New Zealand

Excess accumulation of triacylglycerol (TAG) in liver occurs in a variety of diseases including non-alcoholic fatty liver disease (NAFLD) in which TAG-rich lipid droplets accumulate in the cytoplasm of hepatocytes leading to liver injury, including inflammation, and in some cases fibrosis and cirrhosis. This represents a huge public health problem worldwide. The final and committed step of TAG synthesis in the ER is catalysed by diacylglycerol O-acyltransferase (DGAT) enzymes DGAT1 and DGAT2 (Bhatt-Wessel et al., 2018). DGAT inhibition to eliminate TAG accumulation as a therapy for NAFLD has attracted interest. Changes in proteins, and the pathways they are a part of, represent the molecular mechanisms that lead to NAFLD and the way in which the cell copes with the reduced lipid accumulation caused by DGAT inhibition. Protein biomarkers and the underlying molecular mechanisms provide potential diagnostic and treatment measures of NAFLD; however, they have not been well-studied. Here we used HepG2 human liver carcinoma cells as a model for lipid accumulation, DGAT inhibition, and proteomics. We treated HepG2 cells with 1 mM of a mixture of fatty acids (FAs) for 18 hours and induced TAG accumulation by about 2-fold with a minor effect on cytotoxicity (82% cell viability). When DGAT was partially inhibited, the triacylglycerol accumulation was reduced by 50%. We compared the proteomics profiles of these cells. Among the 1,202 proteins identified, 111 proteins significantly changed in abundance in FA-treated cells compared to untreated control cells; 184 proteins significantly changed in inhibitor and FA-treated cells compared to the FA-treated cells, and 185 significantly changed in inhibitor and FA-treated cells compared to control cells. Bioinformatics analysis revealed that these changed proteins were organised into pathways responsible for lipid metabolism and dyslipidaemia disease. This study provides a resource for the proteomes of fatty liver cells.