Automated lipid droplet quantification system for phenotypic analysis of adipocytes using CellProfiler

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.

成脂分化（Adipogenic differentiation）是指前脂肪细胞（preadipocytes）转化为成熟脂肪细胞（mature adipocytes）的过程，这类细胞负责储存能量并调控代谢稳态（metabolic homeostasis）。在分化进程中，脂肪细胞内积累的中性脂质（neutral lipids）可通过染色试剂标记，并作为细胞分化程度的评价指标。然而，当前用于评估细胞内脂滴（intracellular lipid droplets）的成像工具仍处于起步阶段。营养状况异常、应激状态或化学暴露均可干扰成脂分化与脂质代谢过程。因此，本研究旨在开发一种精准且标准化的方法，以定量成熟脂肪细胞的脂滴大小，并构建一套聚类分析方法，用于解析单个脂肪细胞的总脂质含量。
在脂滴分析环节，本研究采用了两款免费在线计算机软件：作为行业参考标准的ImageJ，以及CellProfiler。针对ImageJ，我们使用了已开发完成的粒子识别与面积定量宏脚本；针对CellProfiler，则自主搭建了全新的分析流程。
研究结果显示，相较ImageJ，CellProfiler可精准识别更多数量的脂滴。此外，借助CellProfiler还可开展聚类分析，实现对单个脂肪细胞总脂质含量的定量，从而深入揭示细胞对成脂刺激的单细胞应答特征。相较于传统分析方法，CellProfiler可简化脂肪细胞脂滴的表型分析流程。
综上，这款全新的图像分析工具可实现对脂滴与成脂失调的更精准评估，这对于代谢紊乱相关研究具有至关重要的意义。