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

ABSTRACT: 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.

SUBMITTER: Adomshick V

PROVIDER: S-EPMC7533149 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundHistological assessment of skeletal muscle sections is important for the research of muscle physiology and diseases. Quantifiable measures of skeletal muscle often include mean fiber diameter, fiber size distribution, and centrally nucleated muscle fibers. These parameters offer insights into the dynamic adaptation of skeletal muscle cells during repeated cycles of degeneration and regeneration associated with many muscle diseases and injuries. Computational programs designed to obtain these parameters would greatly facilitate such efforts and offer significant advantage over manual image analysis, which is very labor-intensive and often subjective. Here, we describe a customized pipeline termed MuscleAnalyzer for muscle histology analysis based upon CellProfiler, a free, open-source software for measuring and analyzing cell images.ResultsThe MuscleAnalyzer pipeline consists of loading, adjusting, and running a series of image-processing modules provided by CellProfiler. This pipeline was evaluated using wild-type and mdx muscle sections co-stained with laminin (to demarcate the muscle fiber boundaries) and 4',6-diamidino-2-phenylindole (DAPI, to label the nuclei). The immunofluorescence images analyzed using the MuscleAnalyzer pipeline or manually yielded similar results in the number of muscle fibers per image (p = 0.42) and central nucleated fiber (CNF) percentage (p = 0.29) in mdx mice. However, for a total of 67 images, CellProfiler completed the analysis in ~ 10 min on a regular PC while it took an investigator ~ 3 h using the manual approach in order to quantify the number of muscle fibers and CNF. Moreover, the MuscleAnalyzer pipeline also provided the measurement of the cross-sectional area (CSA) and minimal Feret's diameter (MFD) of muscle fibers, and thus fiber size distribution can be plotted.ConclusionsOur data indicate that the MuscleAnalyzer pipeline can efficiently and accurately analyze laminin and DAPI co-stained muscle images in a batch format and provide quantitative measurements for muscle histological properties such as muscle fiber diameters, fiber size distribution, and CNF percentage.

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

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