Adipogenic differentiation is the process by which preadipocytes become mature adipocytes, cells that store energy and regulate metabolic homeostasis. During differentiation, neutral lipids that accumulate in adipocytes can be detected using stains and used as an index of cell differentiation. However, imaging tools for evaluating intracellular lipid droplets remain at their infancy. Nutrition, stress, or chemical exposure can dysregulate adipogenic differentiation and lipid metabolism. Therefore, the aims of this study were to develop an accurate, standardized approach to quantify lipid droplet size of mature adipocytes and a clustering approach to analyze the total lipid content per adipocyte. For the lipid droplet analysis, we used two approaches, the free online computer software of reference, ImageJ, and another free online computer software, CellProfiler. For ImageJ, we used an already developed macro designed to identify particles and quantify their area, and for CellProfiler, we developed a new analysis pipeline. Our results show that CellProfiler is able to accurately identify a greater number of lipid droplets compared to ImageJ. A clustering analysis is also possible using CellProfiler which allows for the quantification of total lipid content per individual adipocyte to provide insight into single-cell responsiveness to adipogenic stimuli. CellProfiler streamlines the lipid droplet phenotypic analysis of adipocytes compared to more traditional analysis methods. In conclusion, this novel image analysis tool can provide a more precise evaluation of lipid droplet and adipogenesis dysregulation, a critical need in the understanding of metabolic disorders.
Keywords: Adipocyte; image segmentation; lipid droplet; quantitative analyses.