Literature DB >> 16524598

Individual-based modelling of bacterial cultures to study the microscopic causes of the lag phase.

Clara Prats1, Daniel López, Antoni Giró, Jordi Ferrer, Joaquim Valls.   

Abstract

The lag phase has been widely studied for years in an effort to contribute to the improvement of food safety. Many analytical models have been built and tested by several authors. The use of Individual-based Modelling (IbM) allows us to probe deeper into the behaviour of individual cells; it is a bridge between theories and experiments when needed. INDividual DIScrete SIMulation (INDISIM) has been developed and coded by our group as an IbM simulator and used to study bacterial growth, including the microscopic causes of the lag phase. First of all, the evolution of cellular masses, specifically the mean mass and biomass distribution, is shown to be a determining factor in the beginning of the exponential phase. Secondly, whenever there is a need for an enzyme synthesis, its rate has a direct effect on the lag duration. The variability of the lag phase with different factors is also studied. The known decrease of the lag phase with an increase in the temperature is also observed in the simulations. An initial study of the relationship between individual and collective lag phases is presented, as a complement to the studies already published. One important result is the variability of the individual lag times and generation times. It has also been found that the mean of the individual lags is greater than the population lag. This is the first in a series of studies of the lag phase that we are carrying out. Therefore, the present work addresses a generic system by making a simple set of assumptions.

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Year:  2006        PMID: 16524598     DOI: 10.1016/j.jtbi.2006.01.029

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  6 in total

1.  Individual-based modelling: an essential tool for microbiology.

Authors:  Jordi Ferrer; Clara Prats; Daniel López
Journal:  J Biol Phys       Date:  2008-07-19       Impact factor: 1.365

2.  Analysis of the effect of inoculum characteristics on the first stages of a growing yeast population in beer fermentations by means of an individual-based model.

Authors:  M Ginovart; C Prats; X Portell; M Silbert
Journal:  J Ind Microbiol Biotechnol       Date:  2010-09-03       Impact factor: 3.346

3.  Skew-laplace and cell-size distribution in microbial axenic cultures: statistical assessment and biological interpretation.

Authors:  Olga Julià; Jaume Vidal-Mas; Nicolai S Panikov; Josep Vives-Rego
Journal:  Int J Microbiol       Date:  2010-06-01

4.  Simulation of Escherichia coli Dynamics in Biofilms and Submerged Colonies with an Individual-Based Model Including Metabolic Network Information.

Authors:  Ignace L M M Tack; Philippe Nimmegeers; Simen Akkermans; Ihab Hashem; Jan F M Van Impe
Journal:  Front Microbiol       Date:  2017-12-13       Impact factor: 5.640

5.  A low-complexity metabolic network model for the respiratory and fermentative metabolism of Escherichia coli.

Authors:  Ignace L M M Tack; Philippe Nimmegeers; Simen Akkermans; Filip Logist; Jan F M Van Impe
Journal:  PLoS One       Date:  2018-08-29       Impact factor: 3.240

6.  Biomimicry of quorum sensing using bacterial lifecycle model.

Authors:  Ben Niu; Hong Wang; Qiqi Duan; Li Li
Journal:  BMC Bioinformatics       Date:  2013-05-09       Impact factor: 3.169

  6 in total

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