Correlation between Nuclear Morphology and Adipogenic Differentiation: Application of a Combined Experimental and Computational Modeling Approach

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Abstract

Stem cells undergo drastic morphological alterations during differentiation. While extensive studies have been performed to examine the cytoskeletal remodeling, there is a growing interest to determine the morphological, structural and functional changes of the nucleus. The current study is therefore aimed at quantifying the extent of remodeling of the nuclear morphology of human mesenchymal stem cells during biochemically-induced adipogenic differentiation. Results show the size of nuclei decreased exponentially over time as the lipid accumulation is up-regulated. Increases in the lipid accumulation appear to lag the nuclear reorganization, suggesting the nuclear deformation is a prerequisite to adipocyte maturation. Furthermore, the lamin A/C expression was increased and redistributed to the nuclear periphery along with a subsequent increase in the nuclear aspect ratio. To further assess the role of the nucleus, a nuclear morphology with a high aspect ratio was achieved using microcontact-printed substrate. The cells with an elongated nuclear shape did not efficiently undergo adipogenesis, suggesting the cellular and nuclear processes associated with stem cell differentiation at the early stage of adipogenesis cause a change in the nuclear morphology and cannot be abrogated by the morphological cues. In addition, a novel computational biomechanical model was generated to simulate the nuclear shape change during differentiation and predict the forces acting upon the nucleus. This effort led to the development of computational scaling approach to simulate the experimentally observed adipogenic differentiation processes over 15 days in less than 1.5 hours.

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McColloch, A., Rabiei, M., Rabbani, P., Bowling, A., & Cho, M. (2019). Correlation between Nuclear Morphology and Adipogenic Differentiation: Application of a Combined Experimental and Computational Modeling Approach. Scientific Reports, 9(1). https://doi.org/10.1038/s41598-019-52926-8

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