2017
DOI: 10.1038/s41598-017-15895-4
|View full text |Cite
|
Sign up to set email alerts
|

Statistics and simulation of growth of single bacterial cells: illustrations with B. subtilis and E. coli

Abstract: The inherent stochasticity of molecular reactions prevents us from predicting the exact state of single-cells in a population. However, when a population grows at steady-state, the probability to observe a cell with particular combinations of properties is fixed. Here we validate and exploit existing theory on the statistics of single-cell growth in order to predict the probability of phenotypic characteristics such as cell-cycle times, volumes, accuracy of division and cell-age distributions, using real-time … Show more

Help me understand this report
View preprint versions

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
2
1

Citation Types

0
33
1

Year Published

2019
2019
2023
2023

Publication Types

Select...
6
1
1
1

Relationship

1
8

Authors

Journals

citations
Cited by 48 publications
(34 citation statements)
references
References 49 publications
0
33
1
Order By: Relevance
“…The specific growth rate ( k ) for each substrate was calculated from the following equation: Kh1=2.303log10X2log10X1/t2t1where, X1 and X2 were cell counts at times t 1 and t 2 , respectively (Cogan, 1978). The reciprocal of specific growth rate was recorded as generation time (van Heerden et al., 2017).…”
Section: Methodsmentioning
confidence: 99%
“…The specific growth rate ( k ) for each substrate was calculated from the following equation: Kh1=2.303log10X2log10X1/t2t1where, X1 and X2 were cell counts at times t 1 and t 2 , respectively (Cogan, 1978). The reciprocal of specific growth rate was recorded as generation time (van Heerden et al., 2017).…”
Section: Methodsmentioning
confidence: 99%
“…Results from single-cell experiments are generally close to theoretical expectations (van Heerden et al . 2017 ).…”
Section: Foundational Principlesmentioning
confidence: 99%
“…GFP fluorescence images (1 second exposure at 25% power) were acquired every 10 min. Time-lapse data were processed with custom MATLAB functions developed within our group 4 . Briefly, an automated pipeline segmented every image, identifying individual cells and calculating their spatial features.…”
Section: Methodsmentioning
confidence: 99%
“…Under constant conditions, isogenic populations of bacteria maintain time-invariant distributions of cell size, generation time and macromolecular composition. This growth mode is called balanced growth 1,2,3,4 . Yet, individual cells display molecular fluctuations that are the source for non-genetic heterogeneity within an isogenic population 5,6,7,8,9 and influence single cell growth behaviour 10 .…”
Section: Introductionmentioning
confidence: 99%