Adipogenesis and lipid production in adipocytes subjected to sustained tensile deformations and elevated glucose concentration: a living cell-scale model system of diabesity

Abstract

Adipocyte fate commitment is characterized by morphological changes of fibroblastic pre-adipocyte cells, and specifically by accumulation of lipid droplets (LDs) as part of the adipogenesis metabolism. Formation of LDs indicates the production of triglycerides from glucose through an insulin-regulated glucose internalization process. In obesity, adipocytes typically become insulin resistant, and glucose transport into the cells is impaired, resulting in type 2 diabetes. In the present study, we monitored the adipogenesis in 3T3-L1 cultured cells exposed to high (450 mg/dL hyperglycemia) and low (100 mg/dL physiological) glucose concentrations, in a novel cell culture model system of diabesity. In addition to glucose conditions, cells were concurrently exposed to different substrate tensile strains (12% and control) based on our prior work which revealed that adipogenesis is accelerated in cultures subjected to static, chronic substrate tensile deformations. Phase-contrast images were taken throughout the adipogenesis process (3 weeks) and were analyzed by an image processing algorithm which quantitatively monitors cell differentiation and lipid accumulation (number of LDs per cell and their radius as well as cell size and shape). The results indicated that high glucose concentrations and substrate tensile strains delivered to adipocytes accelerated lipid production by 1.7- and 1.4-fold, respectively. In addition, significant changes in average cell projected area and in other morphological attributes were observed during the differentiation process. The importance of this study is in characterizing the adipogenesis parameters as potential read-outs that can predict the occurrence of insulin resistance in the development of diabesity.

Appendix

The following equations and explanations describe the parameters used in the image processing algorithm to quantitate the lipid contents in the cells and the cell morphology at different time points during differentiation:

1.1 Lipid droplet (LD) parameters

• i. Lipid area per field of view (FOV)

  $$\begin{aligned} \% \,{\hbox {Lipid}}\,{\hbox {Area}}\,{\hbox {Per}}\,{\mathrm{FOV}}=\frac{N_{{\mathrm{white}}} }{N_{{\mathrm{total}}} } \end{aligned}$$

  (1)

  where $N_{\mathrm{white}}$ is the number of white pixels in a marked region, representing a cell, and $N_{\mathrm{total}}$ is the total number of pixels in a FOV (the total number of pixels in the micrograph).

• ii. Mean LD radius per cell

  $$\begin{aligned} R=\sqrt{\frac{S}{\pi }} \end{aligned}$$

  (2)

  where S is the mean LD area per cell (for calculating S, the area of all LDs is extracted, per cell, followed by calculation of mean LD area).

• iii. Number of LDs per cell—the count of LDs for each cell is performed automatically by the image processing code.

1.2 Cell morphological parameters

• i. Cell projected area—the area contained in a marked region representing the cell, automatically calculated in pixels and converted to $\upmu \hbox {m}^{2}$.

• ii. Cell circularity—measure of how closely the shape of the marked region approaches that of a circle. Circularity can be valued between 0 and 1 inclusive, where 1 is the circularity value of an ideal circle.

  $$\begin{aligned} {\hbox {Circularity}}=\,\frac{4\pi A}{P^{2}} \end{aligned}$$

  (3)

  where A is the area and P is the perimeter of the cell.

• iii. Cell eccentricity—measure of how closely the shape of the marked region approaches that of a line or a circle. Eccentricity varies between 0 and 1 inclusive, where 0 is the eccentricity value of an ideal circle shape and 1 is the eccentricity value of a line segment.

  $$\begin{aligned} {\hbox {Eccentricity}}\,=\,\frac{c}{a}\, \end{aligned}$$

  (4)

  where c is the distance between the foci of the ellipse and a is the major axis length.