A bacterial size law revealed by a coarse-grained model of cell physiology.
A bacterial size law revealed by a coarse-grained model of cell physiology.
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由细胞生理学的粗粒度模型揭示的细菌大小规律。
DOI：
10.1371/journal.pcbi.1008245
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发表时间：
2020-09
影响因子：
4.3
通讯作者：
Shahrezaei V
中科院分区：
文献类型：
--
作者：
Bertaux F;von Kügelgen J;Marguerat S;Shahrezaei V
生物学中的普遍观察有时被描述为“定律”。在大肠杆菌中，过去60年进行的实验研究揭示了将核糖体质量分数和细胞大小与生长速度联系起来的主要生长规律。由于它们形式化了生物学中复杂的新兴原理，生长定律在塑造我们对细菌生理学的理解方面发挥了重要作用。在这里，我们发现了一个新的大小定律，它将细胞大小与代谢蛋白质组质量分数和核糖体活性组分的倒数联系起来。我们使用了一个简单的全细胞粗粒度细胞生理学模型，该模型结合了蛋白质组分配理论和细胞分裂的结构模型。这个集成的模型捕获了所有可用的实验数据，这些数据连接了细胞蛋白质组组成、核糖体活性、分裂大小和生长速度，以响应营养质量、抗生素处理和增加的蛋白质负担。最后，模型的随机扩展解释了在单细胞实验中观察到的非平凡关联，包括加法器原理。这项工作为研究单细胞生物体中细胞大小确定的基本原理提供了一个简单而稳健的理论框架。细菌通过调整其分子组成、细胞大小和生长速度来应对环境变化。这种可塑性被认为是多年进化的结果，至少在一定程度上对细菌生理学是最佳的。在过去的几十年里，对细菌生长的定量研究揭示了简单的现象学关系，称为“生长定律”，它将细胞大小和细胞组成与生长速度联系起来。简化的细胞生理学数学模型是定量了解生长规律背后的分子机制的有用工具。例如，这些模型帮助解释了细胞资源对生理过程和途径的最佳分配如何管理细胞分子组成以响应特定的环境条件。在这项研究中，我们扩展和整合了现有的数学模型，并使用最近几项研究的实验数据来了解细胞组成、细胞大小和细胞生长速度的共同调节。模型预测揭示了一种新的“大小定律”，它将细胞大小与细胞中存在的代谢蛋白质水平和活性核糖体的比例联系起来。这项工作为从机制上理解细菌生理学作为外界条件的函数提供了有用的理论工具和定量基础。
Universal observations in Biology are sometimes described as “laws”. In E. coli, experimental studies performed over the past six decades have revealed major growth laws relating ribosomal mass fraction and cell size to the growth rate. Because they formalize complex emerging principles in biology, growth laws have been instrumental in shaping our understanding of bacterial physiology. Here, we discovered a novel size law that connects cell size to the inverse of the metabolic proteome mass fraction and the active fraction of ribosomes. We used a simple whole-cell coarse-grained model of cell physiology that combines the proteome allocation theory and the structural model of cell division. This integrated model captures all available experimental data connecting the cell proteome composition, ribosome activity, division size and growth rate in response to nutrient quality, antibiotic treatment and increased protein burden. Finally, a stochastic extension of the model explains non-trivial correlations observed in single cell experiments including the adder principle. This work provides a simple and robust theoretical framework for studying the fundamental principles of cell size determination in unicellular organisms. Bacteria respond to environmental changes by adjusting their molecular composition, cell size and growth rate. This plasticity is thought to result from years of evolution and to be at least in part optimal for bacterial physiology. Over the past decades, quantitative studies of bacterial growth have revealed simple phenomenological relationships, called “growth laws”, which link cell size and cell composition to the growth rate. Simplified mathematical models of cell physiology are useful tools to gain quantitative understanding of the molecular mechanisms that underlie growth laws. For instance, these models helped explaining how optimal allocation of cellular resource to physiological processes and pathways governs the cell molecular composition in response to specific environmental conditions. In this study, we have extended and integrated existing mathematical models and used experimental data from several recent studies to understand the co-regulation of cell composition, cell size and the cellular growth rate. The model predictions uncovered a novel “size law” that links cell size to the levels of metabolic proteins and the fraction of active ribosomes present in the cell. This work provides a useful theoretical tool and a quantitative basis for understanding mechanistically bacterial physiology as a function of external conditions.
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DOI：
10.1088/1361-6633/aaa628
发表时间：
2018-05
期刊：
Reports on progress in physics. Physical Society (Great Britain)
影响因子：
--
作者：
Jun S;Si F;Pugatch R;Scott M
通讯作者：
Scott M
影响因子：
28.3
作者：
Eun, Ye-Jin;Ho, Po-Yi;Amir, Ariel
通讯作者：
Amir, Ariel
影响因子：
3.4
作者：
Deforet, Maxime;van Ditmarsch, Dave;Xavier, Joao B.
通讯作者：
Xavier, Joao B.
影响因子：
30.8
作者：
Dunlop, Mary J.;Cox, Robert Sidney, III;Levine, Joseph H.;Murray, Richard M.;Elowitz, Michael B.
通讯作者：
Elowitz, Michael B.
影响因子：
16.6
作者：
Cadart C;Monnier S;Grilli J;Sáez PJ;Srivastava N;Attia R;Terriac E;Baum B;Cosentino-Lagomarsino M;Piel M
通讯作者：
Piel M