Obesity predisposes individuals to the development of numerous metabolic complications including hepatosteatosis, also referred to as metabolic dysfunction-associated steatotic liver disease (MASLD). MASLD is characterised by lipid accumulation partly due to excessive dietary consumption of fatty acids (FAs) and monosaccharides. The associated pathological perturbations in metabolism and immune function present ongoing challenges to the development of effective therapeutics for MASLD, underscoring a significant unmet clinical need. Our research aims to improve the understanding of the disease through four in vitro models. Specifically, our models serve as a comprehensive investigation into effects of metabolic substrates and agents which enable us to characterise key molecular pathologies associated with MASLD.
Briefly, the human liver cell line, Hep3B, and the mouse liver cell line, Hepa1-6, were used to assess how pathogenicity of different metabolic substrates can induce MASLD. Cells were treated for 24 hours with palmitic or oleic acids, high and low glucose or fructose concentrations, or agents that stimulate glucose and lipid pathways; glucosamine, TNFa and insulin. Gene and protein expression of lipid metabolism, inflammatory pathways and lipid droplet development, were used as experimental readouts across the four models. Additionally, Oil Red O staining and lipidomic analyses were performed on two models to complement expression readouts.
Our findings support using exogenous fatty acids, various concentrations of monosaccharides and agents across human and mouse cell lines to trigger key metabolic pathways associated with disease onset and progression. Furthermore, through mass-spectrometry lipidomic analysis we gained unprecedented access into the respective lipidomes, which provided novel insight into cell-line specific regulation of cholesterol and acylglycerol metabolism
Taken together, our models provide for an expanded understanding of the metabolic landscape seen in MASLD. Additionally, these models could facilitate a high throughput format to test potential novel therapeutics for the treatment of fatty liver disease.