Abstract

Progression of Metabolic-associated Fatty Liver Disease (MAFLD) involves excessive accumulation of intrahepatic lipid droplets (LDs). However, cost-effective, high-throughput imaging for detailed, multi-parametric LDs quantification at the single-cell level remains difficult. MATERIALS AND METHODS Here, we established a high-content screening (HCS) platform that utilizes the fluorescence of Oil Red O (ORO) to quantify LD phenotypes. This method enables the simultaneous extraction of multi-parametric morphological features, including LD number, size, intensity, and spatial dispersion, in free fatty acid (FFA)-induced AML12 hepatocytes. As a proof-of-concept, we systematically screened and validated a library of 36 lipid-lowering compounds derived from the literature. RESULTS The ORO fluorescence-based HCS platform demonstrated adequate sensitivity, low background interference, and spatial resolution for single-cell quantification compared to bright-field analysis. Data clustering classified monomeric compounds into distinct lipid-regulatory patterns. For instance, pentacyclic triterpenoids decreased the number and size of LDs, while diterpene quinones reduced LD density. CONCLUSION This study establishes a credible, visualizable, and economical HCS approach for assessing LD dynamics. By correlating multidimensional imaging metrics with specific cellular phenotypes, this platform provides a practical method for evaluating lipotoxicity and for high-throughput discovery of anti-steatotic drug candidates from natural product libraries.