Long-term and label-free monitoring for osteogenic differentiation of mesenchymal stem cells using force sensor and impedance measurement. Issue 43 (9th October 2020) - Zhang, Zhizhong; Zheng, Tianyang; Zhu, Rong
Abstract : Label-free and continuous multimodal measurements of cell traction force and cell impedance for studying osteogenic differentiation of stem cells. Abstract : Stem cells have attracted increasing research interest in the field of regenerative medicine due to their unique abilities to differentiate into multiple cell lineages. Label-free, real-time, and long-term monitoring for stem cell differentiation is requisite in studying directional differentiation and development mechanisms for tissue engineering applications, but a great challenge because of the rigorous demands for sensitivity, stability and biocompatibility of devices. In this article, a label-free and real-time monitoring approach using a zinc oxide (ZnO) nanorod field effect transistor (FET) is proposed to detect cell traction forces (CTFs) exerted by cells on underlying substrates. The ZnO nanorod FET with the approach of difference-frequency lock-in detection achieves high sensitivity, good stability, and excellent biocompatibility, by which real-time and long-term (over 20 days) monitoring of cellular mechanical changes in osteogenic differentiation of mesenchymal stem cells (MSCs) is successfully achieved. We also employ electrical impedance monitoring using microelectrode array chips and microscopic observation to investigate cell migration and nodular aggregation behaviors of MSCs in osteogenic differentiation. Various biochemical assays including alkaline phosphatase (ALP), osteopontin expression and alizarin red staining are utilized to verify osteogenic differentiation of MSCs. We propose a combination of cell traction force measurement, impedance measurement and microscopic observation to provide multimodal profiling of cell morphology, and cellular biomechanical and electrophysiological phenotypes, which can track cellular dynamics in stem cell development and help to deeply understand the mechanism of osteogenic differentiation.