Abstract
Phenotypic heterogeneity in a clonal cell population is a well-observed but poorly understood phenomenon. Here, a single-cell approach is employed to investigate non-mutative causes of phenotypic heterogeneity during the differentiation of 3T3-L1 cells into fat cells. Using coherent anti-Stokes Raman scattering microscopy and flow cytometry, adipogenic gene expression, insulin signaling, and glucose import are visualized simultaneously with lipid droplet accumulation in single cells. Expression of adipogenic genes PPARγ, C/EBPα, aP2, LP2 suggests a commitment to fat cell differentiation in all cells. However, the lack of lipid droplet in many differentiating cells suggests adipogenic gene expression is insufficient for lipid droplet formation. Instead, cell-to-cell variability in lipid droplet formation is dependent on the cascade responses of an insulin signaling pathway which includes insulin sensitivity, kinase activity, glucose import, expression of an insulin degradation enzyme, and insulin degradation rate. Increased and prolonged insulin stimulation promotes lipid droplet accumulation in all differentiating cells. Single-cell profiling reveals the kinetics of an insulin signaling cascade as the origin of phenotypic variability in drug-inducible adipogenesis.
Highlights
Targeting adipose tissues to reduce adipose mass has been proposed as a viable approach to obesity treatment [1,2,3]
Adipogenesis in 3T3-L1 cells can be measured using a number of techniques including coherent anti-Stokes Raman scattering (CARS) microscopy [1,19], adipogenic gene expression profiling [3], and flow cytometry [4]
We find that phenotypic variability among differentiating 3T3-L1 cells is dependent on the kinetics of an insulin signaling cascade
Summary
Targeting adipose tissues to reduce adipose mass has been proposed as a viable approach to obesity treatment [1,2,3]. To improve the efficacy of drug treatment, the source of cell-to-cell variability should be identified and targeted [7]. Unlike genetic mutation which can be identified with sequencing, non-genetic cause of cell-to-cell variability cannot be readily investigated. Standard population measurement techniques describe average behavior and are insufficient to investigate variability among cells [8]. To describe the molecular cause of phenotypic variability, cellular events and phenotypic expression must be measured simultaneously at the level of single cells [9,10]. Such requirement demands multiple signals to be analyzed at the same time within a single cell
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