Self-organization of primitive metabolic cycles due to non-reciprocal interactions

Vincent Ouazan-Reboul, Jaime Agudo-Canalejo, Ramin Golestanian
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Abstract

We study analytically and numerically a model metabolic cycle composed of an arbitrary number of species of catalytically active particles. Each species converts a substrate into a product, the latter being used as the substrate by the next species in the cycle. Through a combination of catalytic activity and chemotactic mobility, the active particles develop effective non-reciprocal interactions with particles belonging to neighbouring species in the cycle. We find that such model metabolic cycles are able to self-organize through a macroscopic instability, with a strong dependence on the number of species they incorporate. The parity of that number has a key influence: cycles containing an even number of species are able to minimize repulsion between their component particles by aggregating all even-numbered species in one cluster, and all odd-numbered species in another. Such a grouping is not possible if the cycle contains an odd number of species, which can lead to oscillatory steady states in the case of chasing interactions.
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由于非相互作用的原始代谢循环的自组织
我们用解析和数值方法研究了一个由任意数量的催化活性粒子组成的代谢循环模型。每个物种将一种底物转化为产物,后者被循环中的下一个物种用作底物。通过催化活性和趋化迁移率的结合,活性颗粒与循环中邻近物种的颗粒形成有效的非相互作用。我们发现这种模型代谢周期能够通过非宏观不稳定性自组织,并强烈依赖于它们所包含的物种数量。这个数字的宇称有一个关键的影响:包含偶数个物种的循环能够通过将所有偶数个物种聚集在一个簇中,将所有奇数个物种聚集在另一个簇中,从而使它们的组成粒子之间的排斥最小化。如果循环包含奇数个物种,这样的分组是不可能的,在追逐相互作用的情况下,这可能导致振荡稳态。
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