Literature DB >> 15530497

Connection between stochastic and deterministic modelling of microbial growth.

Zoltán Kutalik1, Moe Razaz, József Baranyi.   

Abstract

We present in this paper various links between individual and population cell growth. Deterministic models of the lag and subsequent growth of a bacterial population and their connection with stochastic models for the lag and subsequent generation times of individual cells are analysed. We derived the individual lag time distribution inherent in population growth models, which shows that the Baranyi model allows a wide range of shapes for individual lag time distribution. We demonstrate that individual cell lag time distributions cannot be retrieved from population growth data. We also present the results of our investigation on the effect of the mean and variance of the individual lag time and the initial cell number on the mean and variance of the population lag time. These relationships are analysed theoretically, and their consequence for predictive microbiology research is discussed.

Mesh:

Year:  2005        PMID: 15530497     DOI: 10.1016/j.jtbi.2004.08.013

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


  12 in total

1.  Use of optical density detection times to assess the effect of acetic acid on single-cell kinetics.

Authors:  A Métris; S M George; J Baranyi
Journal:  Appl Environ Microbiol       Date:  2006-09-01       Impact factor: 4.792

2.  Kinetics of single cells: observation and modeling of a stochastic process.

Authors:  Carmen Pin; József Baranyi
Journal:  Appl Environ Microbiol       Date:  2006-03       Impact factor: 4.792

3.  Single-cell and population lag times as a function of cell age.

Authors:  Carmen Pin; József Baranyi
Journal:  Appl Environ Microbiol       Date:  2008-02-22       Impact factor: 4.792

4.  Age-dependent stochastic models for understanding population fluctuations in continuously cultured cells.

Authors:  Evgeny B Stukalin; Ivie Aifuwa; Jin Seob Kim; Denis Wirtz; Sean X Sun
Journal:  J R Soc Interface       Date:  2013-06-12       Impact factor: 4.118

5.  Historical and contemporary NaCl concentrations affect the duration and distribution of lag times from individual spores of nonproteolytic clostridium botulinum.

Authors:  Martin D Webb; Carmen Pin; Michael W Peck; Sandra C Stringer
Journal:  Appl Environ Microbiol       Date:  2007-02-02       Impact factor: 4.792

6.  Wide lag time distributions break a trade-off between reproduction and survival in bacteria.

Authors:  Stefany Moreno-Gámez; Daniel J Kiviet; Clément Vulin; Susan Schlegel; Kim Schlegel; G Sander van Doorn; Martin Ackermann
Journal:  Proc Natl Acad Sci U S A       Date:  2020-07-15       Impact factor: 11.205

7.  Modeling and estimating bacterial lag phase.

Authors:  Peter Olofsson; Xin Ma
Journal:  Math Biosci       Date:  2011-10-01       Impact factor: 2.144

8.  Modeling bacterial population growth from stochastic single-cell dynamics.

Authors:  Antonio A Alonso; Ignacio Molina; Constantinos Theodoropoulos
Journal:  Appl Environ Microbiol       Date:  2014-06-13       Impact factor: 4.792

9.  Temperature- and Nutrients-Induced Phenotypic Changes of Antarctic Green Snow Bacteria Probed by High-Throughput FTIR Spectroscopy.

Authors:  Margarita Smirnova; Valeria Tafintseva; Achim Kohler; Uladzislau Miamin; Volha Shapaval
Journal:  Biology (Basel)       Date:  2022-06-09

10.  Evidence for a bimodal distribution of Escherichia coli doubling times below a threshold initial cell concentration.

Authors:  Peter L Irwin; Ly-Huong T Nguyen; George C Paoli; Chin-Yi Chen
Journal:  BMC Microbiol       Date:  2010-08-02       Impact factor: 3.605

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