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How are granular details of stochastic growth and division of individual cells reflected in smooth deterministic growth of population numbers? We provide an integrated, multiscale perspective of microbial growth dynamics by formulating a…

Single-cell experiments revealed substantial variability in generation times, growth rates but also in birth and division sizes between genetically identical cells. Understanding how these fluctuations determine the fitness of the…

种群与进化 · 定量生物学 2025-03-24 Arthur Genthon

We study the effect of correlations in generation times on the dynamics of population growth of microorganisms. We show that any non-zero correlation that is due to cell-size regulation, no matter how small, induces long-term oscillations…

种群与进化 · 定量生物学 2019-03-27 Farshid Jafarpour

In this paper, experimental data is presented and a simple model is developed for the time evolution of a F-amp \textit{E. Coli} culture population. In general, the bacteria life cycle as revealed by monitoring a culture's population…

种群与进化 · 定量生物学 2019-12-19 Atanu Chatterjee , Nicholas Mears , Abigail Charest , Saad Algarni , Germano Iannnacchione

In exponential population growth, variability in the timing of individual division events and environmental factors (including stochastic inoculation) compound to produce variable growth trajectories. In several stochastic models of…

种群与进化 · 定量生物学 2023-12-25 Eric W. Jones , Joshua Derrick , Roger M. Nisbet , Will Ludington , David A. Sivak

Collective oscillation of cells in a population has been reported under diverse biological contexts and with vastly different molecular constructs. Could there be common principles similar to those that govern spontaneous oscillation in…

细胞行为 · 定量生物学 2019-07-08 Shou-Wen Wang , Lei-Han Tang

Establishing a quantitative connection between the population growth rate and the generation times of single cells is a prerequisite for understanding evolutionary dynamics of microbes. However, existing theories fail to account for the…

种群与进化 · 定量生物学 2017-09-19 Jie Lin , Ariel Amir

Microbial populations in the natural environment are likely to experience growth conditions very different from those of a typical laboratory xperiment. In particular, removal rates of biomass and substrate are unlikely to be balanced under…

种群与进化 · 定量生物学 2015-05-18 Bhavin S. Khatri , Andrew Free , Rosalind J. Allen

The rate at which individual bacterial cells grow depends on the concentrations of cellular components such as ribosomes and proteins. These concentrations continuously fluctuate over time and are inherited from mother to daughter cells,…

种群与进化 · 定量生物学 2024-08-21 Yaïr Hein , Farshid Jafarpour

We propose a modelling framework to analyse the stochastic behaviour of heterogeneous, multi-scale cellular populations. We illustrate our methodology with a particular example in which we study a population with an oxygen-regulated…

生物物理 · 物理学 2017-09-01 Roberto de la Cruz , Pilar Guerrero , Fabian Spill , Tomás Alarcón

Biofilm communities of Bacillus subtilis bacteria have recently been shown to exhibit collective growth-rate oscillations mediated by electrochemical signaling to cope with nutrient starvation. These oscillations emerge once the colony…

细胞行为 · 定量生物学 2018-03-06 Rosa Martinez-Corral , Jintao Liu , Gurol Suel , Jordi Garcia-Ojalvo

Laboratory experiments with bacterial colonies, under well-controlled conditions often lead to evolutionary diversification, where at least two ecotypes emerge from an initially monomorphic population. Empirical evidence suggests that such…

种群与进化 · 定量生物学 2024-11-06 Roberto Corral López , Samir Suweis , Sandro Azaele , Miguel A. Muñoz

Two powerful and complementary experimental approaches are commonly used to study the cell cycle and cell biology: One class of experiments characterizes the statistics (or demographics) of an unsynchronized exponentially-growing…

生物物理 · 物理学 2022-02-02 Dean Huang , Teresa Lo , Houra Merrikh , Paul A. Wiggins

We study the interplay of population growth and evolutionary dynamics using a stochastic model based on birth and death events. In contrast to the common assumption of an independent population size, evolution can be strongly affected by…

种群与进化 · 定量生物学 2012-06-05 Jonas Cremer , Anna Melbinger , Erwin Frey

A mathematical model of Min oscillation in Escherichia coli is numerically studied. The oscillatory state and hysteretic transition are explained with simpler coupled differential equations. Next, we propose a simple model of cell growth…

适应与自组织系统 · 物理学 2019-10-23 Hidetsugu Sakaguchi , Yuka Kawasaki

Microbial growth and division are fundamental processes relevant to many areas of life science. Of particular interest are homeostasis mechanisms, which buffer growth and division from accumulating fluctuations over multiple cycles. These…

细胞行为 · 定量生物学 2022-10-12 Lee Susman , Maryam Kohram , Harsh Vashistha , Jeffrey T. Nechleba , Hanna Salman , Naama Brenner

Chemical reactions in cell are subject to intense stochastic fluctuations. An important question is how the fundamental physiological behavior of cell is kept stable against those noisy perturbations. In this paper a stochastic model of…

分子网络 · 定量生物学 2009-11-13 Yurie Okabe , Masaki Sasai

Single-cell experiments have revealed cell-to-cell variability in generation times and growth rates for genetically identical cells. Theoretical models relating the fluctuating generation times of single cells to the population growth rate…

种群与进化 · 定量生物学 2020-01-15 Jie Lin , Ariel Amir

Isogenic Escherichia coli growing exponentially in a constant environment display large variation in growth-rates, division-sizes and generation-times. It is unclear how these seemingly random cell cycles can be reconciled with the precise…

定量方法 · 定量生物学 2015-10-14 Mats Wallden , David Fange , Özden Baltekin , Johan Elf

Quantitative single cell measurements have shown that cell cycle duration (the time between cell divisions) for diverse cell types is a noisy variable. The underlying distribution is mean scalable with a universal shape for many cell types…

细胞行为 · 定量生物学 2016-03-07 Nash Rochman , Fangwei Si , Sean X. Sun
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