Axial segmentation by iterative mechanical signaling.
Susan WopatPriyom AdhyapokBijoy DagaJanice M CrawfordBrianna PeskinJames NormanJennifer BagwellStephanie M FogersonStefano Di TaliaDaniel P KiehartPatrick CharbonneauMichel BagnatPublished in: bioRxiv : the preprint server for biology (2023)
In bony fishes, formation of the vertebral column, or spine, is guided by a metameric blueprint established in the epithelial sheath of the notochord. Generation of the notochord template begins days after somitogenesis and even occurs in the absence of somite segmentation. However, patterning defects in the somites lead to imprecise notochord segmentation, suggesting these processes are linked. Here, we reveal that spatial coordination between the notochord and the axial musculature is necessary to ensure segmentation of the zebrafish spine both in time and space. We find that the connective tissues that anchor the axial skeletal musculature, known as the myosepta in zebrafish, transmit spatial patterning cues necessary to initiate notochord segment formation, a critical pre-patterning step in spine morphogenesis. When an irregular pattern of muscle segments and myosepta interact with the notochord sheath, segments form non-sequentially, initiate at atypical locations, and eventually display altered morphology later in development. We determine that locations of myoseptum-notochord connections are hubs for mechanical signal transmission, which are characterized by localized sites of deformation of the extracellular matrix (ECM) layer encasing the notochord. The notochord sheath responds to the external mechanical changes by locally augmenting focal adhesion machinery to define the initiation site for segmentation. Using a coarse-grained mathematical model that captures the spatial patterns of myoseptum-notochord interactions, we find that a fixed-length scale of external cues is critical for driving sequential segment patterning in the notochord. Together, this work identifies a robust segmentation mechanism that hinges upon mechanical coupling of adjacent tissues to control patterning dynamics.
Keyphrases
- deep learning
- convolutional neural network
- extracellular matrix
- gene expression
- magnetic resonance imaging
- molecular dynamics
- escherichia coli
- magnetic resonance
- computed tomography
- simultaneous determination
- cystic fibrosis
- candida albicans
- molecularly imprinted
- pseudomonas aeruginosa
- molecular dynamics simulations
- cell adhesion