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异质细胞群体的稳健性和可进化性。

Robustness and evolvability of heterogeneous cell populations.

机构信息

Center for Cell Dynamics, Department of Cell Biology, Johns Hopkins University School of Medicine, Baltimore, MD 21205.

Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD 21218.

出版信息

Mol Biol Cell. 2018 Jun 1;29(11):1400-1409. doi: 10.1091/mbc.E18-01-0070. Epub 2018 Apr 5.

Abstract

Biological systems are endowed with two fundamental but seemingly contradictory properties: robustness, the ability to withstand environmental fluctuations and genetic variability; and evolvability, the ability to acquire selectable and heritable phenotypic changes. Cell populations with heterogeneous genetic makeup, such as those of infectious microbial organisms or cancer, rely on their inherent robustness to maintain viability and fitness, but when encountering environmental insults, such as drug treatment, these populations are also poised for rapid adaptation through evolutionary selection. In this study, we develop a general mathematical model that allows us to explain and quantify this fundamental relationship between robustness and evolvability of heterogeneous cell populations. Our model predicts that robustness is, in fact, essential for evolvability, especially for more adverse environments, a trend we observe in aneuploid budding yeast and breast cancer cells. Robustness also compensates for the negative impact of the systems' complexity on their evolvability. Our model also provides a mathematical means to estimate the number of independent processes underlying a system's performance and identify the most generally adapted subpopulation, which may resemble the multi-drug-resistant "persister" cells observed in cancer.

摘要

生物系统具有两个基本但看似矛盾的特性

稳健性,即能够承受环境波动和遗传变异的能力;可进化性,即能够获得可选择和可遗传的表型变化的能力。具有异质遗传组成的细胞群体,如感染性微生物或癌症,依靠其内在的稳健性来维持生存能力和适应性,但当遇到环境压力,如药物治疗时,这些群体也能够通过进化选择快速适应。在这项研究中,我们开发了一个通用的数学模型,使我们能够解释和量化异质细胞群体的稳健性和可进化性之间的基本关系。我们的模型预测,稳健性实际上是可进化性的基础,特别是在更不利的环境下,我们在非整倍体芽殖酵母和乳腺癌细胞中观察到了这种趋势。稳健性也补偿了系统复杂性对其可进化性的负面影响。我们的模型还提供了一种数学方法来估计系统性能的独立过程数量,并确定最普遍适应的亚群,这可能类似于癌症中观察到的多药耐药“持久”细胞。

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