CMMI-EPSRC: A novel multifunctional platform to study cell and nuclear mechanosensing
Lead Research Organisation:
University of Warwick
Abstract
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.
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.
Publications
| Description | This project has developed a prototype of a new mechanobiology platform that allows trapping of cell doublets in a microfluidic device. Further, this setup allows for live imaging of cellular and intracellular protein dynamics and mechanical manipulation (deformation) of cells by applying different forces. Further, this work has generated new computational data analysis tools that can be used to segment cell membranes in 3D and study the dynamics of proteins at the cell surface and within the cell. |
| Exploitation Route | Once fully developed, the mechanobiology platform can be used across labs from different disciplines interested in testing the mechanical behaviour of any cells. |
| Sectors | Digital/Communication/Information Technologies (including Software) Healthcare Manufacturing including Industrial Biotechology |
| Description | University of Warwick and Intelligent Imaging Innovations Ltd KTP 25_26 R1 |
| Amount | £295,400 (GBP) |
| Funding ID | 10159795 |
| Organisation | Innovate UK |
| Sector | Public |
| Country | United Kingdom |
| Start | 08/2025 |
| End | 02/2028 |
| Description | Melikhan Tanyeri |
| Organisation | Duquesne University |
| Country | United States |
| Sector | Academic/University |
| PI Contribution | We perform biophysical experiments and live imaging of isolated stem cells in microfluidic devices. |
| Collaborator Contribution | The engineering lab at Duquesne fabricates specialised custom-made microfluidic devices and develops comsol simulations necessary for biophysical characterisation of cells. |
| Impact | Interdisciplinary at the interface of cell biology and engineering and microfabrication. |
| Start Year | 2023 |
| Description | Till Bretschneider |
| Organisation | University of Warwick |
| Department | Department of Computer Science |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Our team provided live imaging data of biological samples for computational image analysis. |
| Collaborator Contribution | The Bretschneider lab developed computational tools and AI neural networks for image analysis and modelling. |
| Impact | Interdisciplinary at the interface of cell and developmental biology and computer science and mathematical modelling. |
| Start Year | 2023 |
| Description | Resonate Festival of Science and Technology 2025 |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Schools |
| Results and Impact | We presented our research at the Resonate Festival of Science and Technology 2025, held at Warwick University on 9th March 2025. The activity was aimed at primary school children and consisted of a 3D virtual reality demonstration, showing complex surface deformations while cells drink which illustrating a number of computational tools to extract data from 3D biological time series . Approximately 50 children were able to navigate the virtual space using a headset, while around 250 more (children and parents) were able to watch and discuss the science behind the activity illustrated with 3D printed cell models. |
| Year(s) Of Engagement Activity | 2025 |
| URL | https://www.resonatefestival.co.uk/events/festival-science-tech-day-out-ecr72 |
