AI Article Synopsis

  • Morphogenesis is the process by which a group of cells establishes and repairs complex anatomical structures, and it plays a crucial role in development and medical applications.
  • The ability of embryos to recover from disturbances, like splitting into twins, suggests a goal-oriented feedback mechanism, but understanding the detailed processes involved is still lacking.
  • This study illustrates how cells can communicate in a wave-like manner to analyze body shape features, enabling a reliable feedback system to create varied reaction-diffusion patterns, which are essential for controlling morphological traits.

Article Abstract

Morphogenesis, the establishment and repair of emergent complex anatomy by groups of cells, is a fascinating and biomedically-relevant problem. One of its most fascinating aspects is that a developing embryo can reliably recover from disturbances, such as splitting into twins. While this reliability implies some type of goal-seeking error minimization over a morphogenic field, there are many gaps with respect to detailed, constructive models of such a process. A common way to achieve reliability is negative feedback, which requires characterizing the existing body shape to create an error signal-but measuring properties of a shape may not be simple. We show how cells communicating in a wave-like pattern could analyze properties of the current body shape. We then describe a closed-loop negative-feedback system for creating reaction-diffusion (RD) patterns with high reliability. Specifically, we use a wave to count the number of peaks in a RD pattern, letting us use a negative-feedback controller to create a pattern with repetitions, where can be altered over a wide range. Furthermore, the individual repetitions of the RD pattern can be easily stretched or shrunk under genetic control to create, e.g., some morphological features larger than others. This work contributes to the exciting effort of understanding design principles of morphological computation, which can be used to understand evolved developmental mechanisms, manipulate them in regenerative-medicine settings, or engineer novel synthetic morphology constructs with desired robust behavior.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10461482PMC
http://dx.doi.org/10.3389/fcell.2023.1087650DOI Listing

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