Emergent Simplicities in the Living Histories of Individual Cells

Charles S. Wright, Kunaal Joshi, Rudro R. Biswas, Srividya Iyer-Biswas
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Abstract

Organisms maintain the status quo, holding key physiological variables constant to within an acceptable tolerance, and yet adapt with precision and plasticity to dynamic changes in externalities. What organizational principles ensure such exquisite yet robust control of systems-level "state variables" in complex systems with an extraordinary number of moving parts and fluctuating variables? Here we focus on these issues in the specific context of intra- and intergenerational life histories of individual bacterial cells, whose biographies are precisely charted via high-precision dynamic experiments using the SChemostat technology. We highlight intra- and intergenerational scaling laws and other "emergent simplicities" revealed by these high-precision data. In turn, these facilitate a principled route to dimensional reduction of the problem, and serve as essential building blocks for phenomenological and mechanistic theory. Parameter-free data-theory matches for multiple organisms validate theory frameworks, and explicate the systems physics of stochastic homeostasis and adaptation.
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单个细胞生命历程中的新兴简单性
生物体维持现状,将关键的生理变量保持在可接受的容差范围内,同时又能精确地、可塑性地适应外部环境的动态变化。在具有大量运动部件和波动变量的复杂系统中,什么样的组织原则才能确保对系统级 "状态变量 "进行如此精细而稳健的控制?在这里,我们以单个细菌细胞的代内和代际生命史为特定背景,重点讨论了这些问题。我们利用 SChemostat 技术,通过高精度动态实验精确绘制了这些细胞的生命史。我们强调了这些高精度数据所揭示的代内和代际缩放规律及其他 "突现的简单性"。反过来,这些数据又促进了问题降维的原则性途径,并成为现象学和机理理论的重要基石。多个生物体的无参数数据理论匹配验证了理论框架,并解释了随机稳态和适应的系统物理学。
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