EPSRC logo

Details of Grant 

EPSRC Reference: EP/X026663/1
Title: CMMI-EPSRC: A novel multifunctional platform to study cell and nuclear mechanosensing
Principal Investigator: Smutny, Dr M
Other Investigators:
Ott, Professor S Bretschneider, Professor T
Researcher Co-Investigators:
Project Partners:
3i - Intelligent Imaging Innovation Duquesne University
Department: Warwick Medical School
Organisation: University of Warwick
Scheme: Standard Research
Starts: 01 July 2023 Ends: 30 June 2026 Value (£): 876,547
EPSRC Research Topic Classifications:
Artificial Intelligence Biophysics
Image & Vision Computing
EPSRC Industrial Sector Classifications:
Healthcare Information Technologies
Related Grants:
Panel History:
Panel DatePanel NameOutcome
24 Jan 2023 EPSRC ICT Prioritisation Panel January 2023 Announced
Summary on Grant Application Form
Cells are able to sense and translate external mechanical cues into biochemical signals, which have major effects on cellular processes during tissue homeostasis, development and diseases. However, our understanding of the specific mechanisms of force sensing and transduction is currently limited and molecular mechanisms underpinning many important mechanochemical processes in a physiological context remain largely elusive.

In this project we will build on recent advances in microfluidics and fast 3D imaging as well as new machine learning methods for analysing complex 3D timeseries to develop precise, high-throughput methods to probe and quantify cellular force sensing and response.

Our versatile high-throughput mechanobiology platform will allow us to study cellular and molecular responses of cells to specific mechanical signals transmitted through physical cell-cell interactions, providing insights into the role of mechanical stimuli in fundamental cellular and developmental processes. The generation of such a platform relies on an interdisciplinary approach with innovations in engineering and microfabrication, biophysics, computer vision and modelling, advanced microscopy for bioimaging and bioinformatics. The novel design of our platform will enable sequential loading of cells to form cell doublets for parallel cell manipulation and imaging. It will allow for the application of three physiologically relevant force types (shear, compression, tension) to cells with precise regulation of their magnitude, duration and frequency, which is vastly challenging with conventional microfluidic devices. We will also develop a new flow management system allowing programmable and targeted retrieval of cells for off-chip analyses such as omics approaches.

We will further adapt light-sheet microscopy to image whole cell volumes and subcellular molecular dynamics. We will develop new microfluidic chamber designs and imaging protocols for simultaneous dual-color image acquisition. Moreover, industry partner Intelligent imaging innovations (3i), who are a leading developer of lightsheet microscopy, will provide practicable solutions that will be valuable to a wide range of users.

We will use advanced methods for automated cell segmentation and tracking of subcellular regions to map fluorescence distributions in 4D. We will build on recent developments in generative modelling using neural networks to aggregate data from dual colour channel experiments. Mathematical models will help to interpret the complex relationships in the data and to guide new experiments.

To demonstrate broad applicability and versatility of our platform, we will utilize two independent cellular systems. Cardiomyocyte cells that make the heart/cardiac muscle are responsible for generating contractile forces and are permanently exposed to mechanical stimulation. External forces transmitted to the nuclear envelope were shown to be critical in cardiomyocyte function and defects in this pathway can lead to diseases (cardiac laminopathies). Embryonic stem (ES) cells play pivotal roles in development by giving rise to all cell lineages in the body and are also crucial in regenerative medicine. ES cells require mechanical signals from neighboring cells for proper function during development including establishing specific cell identities . We will further advance recent bioinformatic analysis tools to identify changes in chromatin accessibility and gene expression due to specific force inputs.

Importantly, our platform is easily adaptable to other cell types and non-suspended cells on adhesive substrates, and can be combined with targeted delivery of compounds. We anticipate that our platform will also enable investigating the role of mechanotransduction in a broader context, including cancer, immunology and regeneration, and can further be adapted for drug discovery and screening.

Key Findings
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
Potential use in non-academic contexts
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
Description This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
Date Materialised
Sectors submitted by the Researcher
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
Project URL:  
Further Information:  
Organisation Website: http://www.warwick.ac.uk