Project description
Real-time imaging of stem cell differentiation
Light microscopy is routinely used in research and the diagnostic field around the world, enabling the visualisation of objects down to 250 nm in size. Super-resolution (SR) microscopy is gaining ground over optical microscopy as it bypasses the diffraction limit and significantly improves the resolution capacity. Funded by the European Innovation Council, the RT-SuperES project aims to develop an automated SR technology that offers the possibility of real-time imaging that can switch from conventional to SR fluorescence microscopy. Researchers plan to use this SR system to study the differentiation of embryonic stem cells.
Objective
The development of super-resolution (SR) microscopy in recent years has revolutionized cell biology, breaking the diffraction limit of light microscopy by order of magnitude. However, SR is currently incompatible with high-content imaging. RT-SuperES will provide a groundbreaking and affordable technology with automated SR capabilities beyond the state-of-the-art. To this end, we will generate a library of endogenously-labelled SNAP-tag fusion proteins in mouse embryonic stem cells (ESCs), and deploy a real-time decision-making module, which will continuously monitor our SNAP-tagged cells using fast fluorescence imaging, and, once a change is detected, will fix the desired cells, and switch to SR mode. By bringing together seven world-leading experts from four different countries, combining basic and applied research and industry, we propose several firsts: a) The first endogenously-labelled clone library of SNAP-tag fusion proteins; b) Utilize machine learning (ML) for real-time automated decision making, autonomously switching from fast conventional to SR imaging; c) Combine high content with SR imaging; d) Integrate novel, cutting-edge technologies, namely SR Radial Fluctuations (SRRF), NanoJ-Fluidics, Single Molecule Localization Microscopy (SMLM) and Structured Illumination Microscopy (SIM); e) Collect large scale imaging datasets of cell states in ESCs, and f) Provide cell-cycle stage-dependent nanoscale localization of selected nuclear and chromatin proteins (e.g. H3.3) during early ESC differentiation. RT-SuperES will provide the scientific community with the first-of-its-kind commercial real-time SR-highcontent imaging system, and the first library of endogenously SNAP-tagged ESC clones, which are ideal, among many other things, for SR imaging.
Fields of science
- natural sciencesphysical sciencesopticsmicroscopysuper resolution microscopy
- natural sciencesbiological sciencesbiochemistrybiomoleculesproteins
- natural sciencesbiological sciencescell biology
- medical and health sciencesmedical biotechnologycells technologiesstem cells
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
Keywords
Programme(s)
- HORIZON.3.1 - The European Innovation Council (EIC) Main Programme
Funding Scheme
EIC - EICCoordinator
91904 Jerusalem
Israel