AI Article Synopsis

  • The study focuses on how cell and tissue polarization is crucial for biological development and tissue regeneration, using planarian flatworms as a model.
  • It introduces a new alignment model that describes how global signals, local cell interactions, and cell turnover work together to shape cell polarity patterns.
  • The findings suggest that a consistent global signal influences the final polarity alignment, while local cell interactions slow down changes in polarity, and replacing cells speeds up the reorganization process.

Article Abstract

The polarization of cells and tissues is fundamental for tissue morphogenesis during biological development and regeneration. A deeper understanding of biological polarity pattern formation can be gained from the consideration of pattern reorganization in response to an opposing instructive cue, which we here consider using the example of experimentally inducible body axis inversions in planarian flatworms. We define a dynamically diluted alignment model linking three processes: entrainment of cell polarity by a global signal, local cell-cell coupling aligning polarity among neighbours, and cell turnover replacing polarized cells by initially unpolarized cells. We show that a persistent global orienting signal determines the final mean polarity orientation in this stochastic model. Combining numerical and analytical approaches, we find that neighbour coupling retards polarity pattern reorganization, whereas cell turnover accelerates it. We derive a formula for an effective neighbour coupling strength integrating both effects and find that the time of polarity reorganization depends linearly on this effective parameter and no abrupt transitions are observed. This allows us to determine neighbour coupling strengths from experimental observations. Our model is related to a dynamic 8-Potts model with annealed site-dilution and makes testable predictions regarding the polarization of dynamic systems, such as the planarian epithelium.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5665830PMC
http://dx.doi.org/10.1098/rsif.2017.0466DOI Listing

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