A Population-Based Approach to Study the Effects of Growth and Division Rates on the Dynamics of Cell Size Statistics

Totis, Niccoló; Nieto, César; Küper, Armin; Vargas-García, César Augusto; Singh, Abhyudai; Waldherr, Steffen

doi:10.1109/lcsys.2020.3005069

Cited by 24 publications

(36 citation statements)

References 17 publications

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“…In different division strategies (λ = 1), ∆ is now function of s b . Now, the typical size as explained in past studies [14,17], s b , is the size at birth that is perfectly doubled by the division strategy:…”

Section: Different Division Strategiesmentioning

confidence: 99%

“…This distribution is related to the histograms of bacterial populations. Some attempts have described the dynamics of this distributions including effects due to the increasing of population number and the mother-daughter correlations [17][18][19]. In our framework, we consider a cell population with an asymptotically large number.…”

Section: Theoretical Details the Population Balance Equationmentioning

confidence: 99%

“…where g(s, t) is the size change per unit time. Some studies have considered the constant growth [17,20,21] we will focus con exponential growth rate (g(s) = µs) with µ being the growth rate and s 0 is the initial cell size. Since (2) defines a deterministic process, the change in the size distribution p(s, t|s 0 ) conditioned on initial size s 0 can be obtained by solving…”

Section: Theoretical Details the Population Balance Equationmentioning

confidence: 99%

“…Some studies have explored the particular case where h(s) = ks with k being a constant and discarding the dependence upon s [17,22]. This, resulting on:…”

Section: Theoretical Details the Population Balance Equationmentioning

confidence: 99%

“…Which is also known as the Population Balance Equation for a fixed population number [17]. Some theoretical methods like moment closure were used in past studies to solve (7) but stable solutions were not found already [17].…”

Section: Theoretical Details the Population Balance Equationmentioning

confidence: 99%

See 4 more Smart Citations

Continuous Rate Modelling of bacterial stochastic size dynamics

Nieto

Vargas-García

Pedraza

2020

Preprint

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Bacterial division is an inherently stochastic process. However, theoretical tools to simulate and study the stochastic transient dynamics of cell-size are scarce. Here, we present a general theoretical approach based on the Chapman-Kolmogorov formalism to describe these stochastic dynamics including continuous growth and division events as jump processes. Using this approach, we analyze the effect of different sources of noise on the dynamics of the size distribution. Oscillations in the distribution central moments were found as consequence of the discrete translation invariance of the system with period of one doubling time, these oscillations are found in both the central moments of the size distribution and the auto-correlation function and do not disappear including stochasticity on division times or size heterogeneity on the population but only after include noise in either growth rate or septum position.

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Section: Different Division Strategiesmentioning

confidence: 99%

Section: Theoretical Details the Population Balance Equationmentioning

confidence: 99%

Section: Theoretical Details the Population Balance Equationmentioning

confidence: 99%

“…Some studies have explored the particular case where h(s) = ks with k being a constant and discarding the dependence upon s [17,22]. This, resulting on:…”

Section: Theoretical Details the Population Balance Equationmentioning

confidence: 99%

Section: Theoretical Details the Population Balance Equationmentioning

confidence: 99%

See 3 more Smart Citations

Continuous Rate Modelling of bacterial stochastic size dynamics

Nieto

Vargas-García

Pedraza

2020

Preprint

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Cell size distribution of lineage data: Analytic results and parameter inference

2021

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Population Mass Balance Model for Precipitation with Turbidity Measurements

Papp,

Tóth,

Horváth

2024

ACS Omega

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The discretized population balance theory has been proven to be a useful method to simulate systems in which solid particles are present. In this work, we introduce a new approach to model precipitation reactions based on the temporal evolution of product concentration, from which particle size distribution, its dynamics, and the specific interfacial energies can be obtained. For a reference study, the previously investigated calcium oxalate precipitation was selected, where the reaction was followed via turbidity measurement. From the obtained particle size distribution, we can show that at low supersaturation, growth is the dominant process, while at higher supersaturation, nucleation is the dominant process. Moreover, the temporal change of the distribution curve has allowed us to split the precipitation into a nucleation, a growth-driven intermediate, and a saturation regime. Furthermore, the comparison between the experimental and calculated results has proved that the method is suitable for predicting particle size distributions and specific interfacial energies.

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A Population-Based Approach to Study the Effects of Growth and Division Rates on the Dynamics of Cell Size Statistics

Cited by 24 publications

References 17 publications

Continuous Rate Modelling of bacterial stochastic size dynamics

Continuous Rate Modelling of bacterial stochastic size dynamics

Cell size distribution of lineage data: Analytic results and parameter inference

Population Mass Balance Model for Precipitation with Turbidity Measurements

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