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Real-Time high-content Super-Resolution Imaging of ES Cell States

CORDIS · observation · Publication date unknown

s 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. Super-Resolution; high-content;Stem Cells; Machine Learning; Microscopy; R

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recordType

award

status

SIGNED

region

EU

value

3488483

unit

EUR