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Biology subjects

Betjes, M.

Publications and source records attributed to Betjes, M..

2 recordsLinked to original sources

Following cell type transitions in space and time by combining live-cell tracking and endpoint cell identity in intestinal organoids

Elucidating the dynamics of cellular differentiation in space and time is key to advancing organoid biology and technology. Direct visualization of differentiation patterns is challenging, however, in part because of the difficulty of simultaneously detecting all relevant cell types by fluorescence imaging. Here we present TypeTracker, which determines the differentiation trajectories of all cells within a region of interest, including their type transitions, growth, divisions, and changes in spatial organization. We show how the lineage tree topology, as determined by automated cell tracking, allows for the retrospective identification of cell types across multiple generations. The data revealed various surprising aspects of intestinal organoid differentiation, including symmetric fate adoption by sister cells, cell type abundance regulated by division, and type commitment of cells occurring prior to their spatial reorganization. Our method can be applied broadly to study other organoid systems and to screen for compounds that affect differentiation programs.

biophysics↗

Functional single cell selection and annotated profiling of dynamically changing cancer cells

A method connecting single cell genomic or transcriptomic profiles to functional cellular characteristics, in particular time-varying phenotypic changes, would be transformative for single cell and cancer biology. Here, we present fSCS: functional single cell selection. This technology combines a custom-built ultrawide field-of-view optical screening microscope, fast automated image analysis and a new photolabeling method, phototagging, using a newly synthesized visible-light-photoactivatable dye. Using fSCS, we screen, selectively photolabel and isolate cells of interest from large heterogeneous populations based on functional dynamics like fast migration, morphological variation, small molecule uptake or cell division. We combined fSCS with single cell RNA sequencing for functionally annotated transcriptomic profiling of fast migrating and spindle-shaped MCF10A cells with or without TGF{beta} induction. We identified critical genes and pathways driving aggressive migration as well as mesenchymal-like morphology that could not be detected with state-of-the-art single cell transcriptomic analysis. fSCS provides a crucial upstream selection paradigm for single cell sequencing independent of biomarkers, allows enrichment of rare cells and can facilitate the identification and understanding of molecular mechanisms underlying functional phenotypes.

bioengineering↗