Dynamic morphoskeletons in development.
Mattia SerraSebastian StreichanManli ChuaiCornelis J WeijerLakshminarayanan MahadevanPublished in: Proceedings of the National Academy of Sciences of the United States of America (2020)
Morphogenetic flows in developmental biology are characterized by the coordinated motion of thousands of cells that organize into tissues, naturally raising the question of how this collective organization arises. Using only the kinematics of tissue deformation, which naturally integrates local and global mechanisms along cell paths, we identify the dynamic morphoskeletons behind morphogenesis, i.e., the evolving centerpieces of multicellular trajectory patterns. These features are model- and parameter-free, frame-invariant, and robust to measurement errors and can be computed from unfiltered cell-velocity data. We reveal the spatial attractors and repellers of the embryo by quantifying its Lagrangian deformation, information that is inaccessible to simple trajectory inspection or Eulerian methods that are local and typically frame-dependent. Computing these dynamic morphoskeletons in wild-type and mutant chick and fly embryos, we find that they capture the early footprint of known morphogenetic features, reveal new ones, and quantitatively distinguish between different phenotypes.
Keyphrases
- single cell
- wild type
- cell therapy
- induced apoptosis
- genome wide
- gene expression
- cell cycle arrest
- healthcare
- stem cells
- patient safety
- dna methylation
- cell death
- pregnant women
- machine learning
- computed tomography
- bone marrow
- big data
- cell proliferation
- health information
- signaling pathway
- high speed
- blood flow
- high resolution
- deep learning
- diffusion weighted imaging