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与细胞表型转换相关的适应代价驱动种群多样化动态和可控性。

Fitness cost associated with cell phenotypic switching drives population diversification dynamics and controllability.

机构信息

Terra Research and Teaching Centre, Microbial Processes and Interactions (MiPI), Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium.

Microsystems in Bioprocess Engineering, Institute of Process Engineering in Life Sciences, Karlsruhe Institute of Technology, Karlsruhe, Germany.

出版信息

Nat Commun. 2023 Oct 2;14(1):6128. doi: 10.1038/s41467-023-41917-z.

Abstract

Isogenic cell populations can cope with stress conditions by switching to alternative phenotypes. Even if it can lead to increased fitness in a natural context, this feature is typically unwanted for a range of applications (e.g., bioproduction, synthetic biology, and biomedicine) where it tends to make cellular response unpredictable. However, little is known about the diversification profiles that can be adopted by a cell population. Here, we characterize the diversification dynamics for various systems (bacteria and yeast) and for different phenotypes (utilization of alternative carbon sources, general stress response and more complex development patterns). Our results suggest that the diversification dynamics and the fitness cost associated with cell switching are coupled. To quantify the contribution of the switching cost on population dynamics, we design a stochastic model that let us reproduce the dynamics observed experimentally and identify three diversification regimes, i.e., constrained (at low switching cost), dispersed (at medium and high switching cost), and bursty (for very high switching cost). Furthermore, we use a cell-machine interface called Segregostat to demonstrate that different levels of control can be applied to these diversification regimes, enabling applications involving more precise cellular responses.

摘要

同基因细胞群体可以通过切换到替代表型来应对应激条件。尽管这种表型在自然环境中可能会增加适应性,但对于一系列应用(如生物生产、合成生物学和生物医学)来说,这种特征通常是不希望出现的,因为它会使细胞反应变得不可预测。然而,对于细胞群体可以采用的多样化特征,我们知之甚少。在这里,我们对不同的系统(细菌和酵母)和不同的表型(利用替代碳源、一般应激反应和更复杂的发育模式)进行了多样化动力学的特征描述。我们的结果表明,多样化动力学和与细胞切换相关的适应代价是耦合的。为了量化切换代价对群体动力学的贡献,我们设计了一个随机模型,该模型可以重现实验中观察到的动力学,并确定了三种多样化状态,即受约束状态(切换代价低)、分散状态(切换代价中高)和突发状态(切换代价非常高)。此外,我们使用了一种称为 Segregostat 的细胞-机器接口来证明可以对这些多样化状态施加不同水平的控制,从而实现涉及更精确细胞反应的应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/73eb/10545768/c7732239486b/41467_2023_41917_Fig1_HTML.jpg

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