A mathematical model of mechanotransduction reveals how mechanical memory regulates mesenchymal stem cell fate decisions

• DOI: 10.1186/s12918-017-0429-x
• Publication Date: 2017-05-16T13:43:23Z
• Authors: Tao Peng; Linan Liu; Adam L MacLean; Chi Wut Wong; Weian Zhao; Qing Nie
• Keywords: 0301 basic medicine; 570; Mechanotransduction; Bioinformatics; 1.1 Normal biological development and functioning; Physiological; 610; Bioengineering; Regenerative Medicine; Mechanotransduction, Cellular; Models, Biological; Feedback; Computer Software; 03 medical and health sciences; Stem Cell Research - Nonembryonic - Human; Models; Memory; Cell Adhesion; YAP/TAZ; Medical biochemistry and metabolomics; Cell Lineage; Gene Regulatory Networks; Cell fate decision; Mesenchymal stem cell; Mechanical Phenomena; Feedback, Physiological; Transplantation; ECM; Other Medical and Health Sciences; 5.2 Cellular and gene therapies; Stiffness sensing; Cell Differentiation; Mesenchymal Stem Cells; Biological Sciences; Stem Cell Research; Biological; Bioinformatics and computational biology; Biomechanical Phenomena; Nonlinear dynamics; Stem Cell Research - Nonembryonic - Non-Human; Mathematical modeling; Biochemistry and Cell Biology; Cellular; Bistability; Research Article

Mechanical and biophysical properties of the cellular microenvironment regulate cell fate decisions. Mesenchymal stem cell (MSC) fate is influenced by past mechanical dosing (memory), but the mechanisms underlying this process have not yet been well defined. We have yet to understand how memory affects specific cell fate decisions, such as the differentiation of MSCs into neurons, adipocytes, myocytes, and osteoblasts.We study a minimal gene regulatory network permissive of multi-lineage MSC differentiation into four cell fates. We present a continuous model that is able to describe the cell fate transitions that occur during differentiation, and analyze its dynamics with tools from multistability, bifurcation, and cell fate landscape analysis, and via stochastic simulation. Whereas experimentally, memory has only been observed during osteogenic differentiation, this model predicts that memory regions can exist for each of the four MSC-derived cell lineages. We can predict the substrate stiffness ranges over which memory drives differentiation; these are directly testable in an experimental setting. Furthermore, we quantitatively predict how substrate stiffness and culture duration co-regulate the fate of a stem cell, and we find that the feedbacks from the differentiating MSC onto its substrate are critical to preserve mechanical memory. Strikingly, we show that re-seeding MSCs onto a sufficiently soft substrate increases the number of cell fates accessible.Control of MSC differentiation is crucial for the success of much-lauded regenerative therapies based on MSCs. We have predicted new memory regions that will directly impact this control, and have quantified the size of the memory region for osteoblasts, as well as the co-regulatory effects on cell fates of substrate stiffness and culture duration. Taken together, these results can be used to develop novel strategies to better control the fates of MSCs in vitro and following transplantation.