Signalling-dependent refinement of cell fate choice during tissue remodelling
Herszterg, S.; de Gennes, M.; Cicolini, S.; Huang, A.; Alexandre, C.; Smith, M. B.; Araujo, H.; Vincent, J.-P.; Salbreux, G.
Show abstract
How biological form emerges from cell fate decisions and tissue remodelling is a fundamental question in development biology. However, an understanding of how these processes operate side-by-side to set precise and robust patterns is largely missing. Here, we investigate this interplay during the process of vein refinement in the Drosophila pupal wing. By following reporters of signalling activity dynamically, together with tissue flows, we show that longitudinal vein refinement arises from a combination of local tissue deformation and cell fate adjustments controlled by a signalling network involving Notch, Dpp, and EGFR. Perturbing large-scale convergence and extension tissue flows does not affect vein refinement, showing that pre-patterned vein domains are able to intrinsically refine to the correct width. A minimal biophysical description taking into account key signalling interactions recapitulates the intrinsic tissue ability to establish a thin, regular vein independently of large-scale tissue flows. Supporting this prediction, artificial proveins optogenetically generated orthogonal to the axis of wing elongation refine against large-scale flows. Overall, we find that signalling-mediated updating of cell fate is a key contributor to reproducible patterning.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Robustness of epithelial sealing is an emerging property of local ERK feedbacks driven by cell elimination 95%
- Existing actin filaments orient new filament growth to provide structural memory of filament alignment during cytokinesis 95%
- Structural redundancy in supracellular actomyosin networks enables robust tissue folding 95%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.