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闭合形态发生的循环:基于闭环反应扩散的形态发生数学模型

Closing the loop on morphogenesis: a mathematical model of morphogenesis by closed-loop reaction-diffusion.

作者信息

Grodstein Joel, McMillen Patrick, Levin Michael

机构信息

Department of Electrical and Computer Engineering, Tufts University, Medford, MA, United States.

Allen Discovery Center at Tufts University, Medford, MA, United States.

出版信息

Front Cell Dev Biol. 2023 Aug 14;11:1087650. doi: 10.3389/fcell.2023.1087650. eCollection 2023.

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.

摘要

形态发生,即由细胞群建立和修复复杂的新兴解剖结构,是一个引人入胜且与生物医学相关的问题。其最引人入胜的方面之一是,发育中的胚胎能够可靠地从干扰中恢复,比如分裂成双胞胎。虽然这种可靠性意味着在形态发生场中存在某种类型的寻求目标的误差最小化,但在这种过程的详细、建设性模型方面仍存在许多空白。实现可靠性的一种常见方法是负反馈,这需要表征现有的身体形状以创建误差信号——但测量形状的属性可能并不简单。我们展示了以波状模式进行通信的细胞如何分析当前身体形状的属性。然后,我们描述了一个用于创建具有高可靠性的反应 - 扩散(RD)模式的闭环负反馈系统。具体而言,我们使用一个波来计算RD模式中的峰值数量,从而能够使用负反馈控制器创建具有重复次数的模式,其中重复次数可以在很宽的范围内改变。此外,RD模式的各个重复部分可以在基因控制下轻松拉伸或收缩,以创建例如一些比其他形态特征更大的形态特征。这项工作有助于推动理解形态计算设计原则这一令人兴奋的努力,该原则可用于理解进化的发育机制、在再生医学环境中对其进行操控,或设计具有所需稳健行为的新型合成形态结构。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3b3/10461482/2c1f2c753e80/fcell-11-1087650-g001.jpg

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