Engineering synthetic mechanotransduction through nucleocytoplasmic transport

Our understanding of cell biology has reached the point in which cells can be exogenously engineered to carry out specific tasks.

This is typically applied to generate gene circuits that respond to biochemical interactions between specific molecules. However, cells sense not only biochemical but also mechanical signals, in the process of mechanotransduction.

Here, we propose to re-engineer cell mechanotransduction from scratch, in a manner that is not based on any endogenous cell signalling pathway.

We will achieve this by harnessing our novel findings that force application to the cell nucleus regulates transport through nuclear pore complexes (NPCs), in such a way that proteins can be made to translocate to the cell nucleus with force by appropriately tuning their active and passive transport properties.

First, we will implement a mechanosensing element, involving a precise understanding of the mechanical parameters regulating nucleocytoplasmic transport, and subsequent design of molecules with optimal mechanosensitivity (that is, force-dependent nuclear localization).

Second, we will implement a control element, enabling a system to control to what extent, and for how long, force reaches the nucleus and triggers subsequent mechanosensing.

Finally, we will implement a functional element, by which mechanosensitive molecules will be engineered to trigger the transcription of specific genes in the nucleus.

As a proof-of-concept, we will apply this system to re-engineer three main properties of fibroblasts and mesenchymal cells (matrix remodelling, migration, and epithelial/mesenchymal plasticity), all involved in pathological responses to altered tissue mechanics.

This project will deliver synthetic mechanotransduction, a novel tool that will be orthogonal and compatible with existing cell engineering approaches.

Further, it will provide an answer to the fundamental question of how a functional, biological mechanotransduction system can be generated de novo.