Literature DB >> 9849786

The effect of the growth environment on the lag phase of Listeria monocytogenes.

T P Robinson1, M J Ocio, A Kaloti, B M Mackey.   

Abstract

The duration of lag in Listeria monocytogenes was examined in relation to the physico-chemical properties of the growth environment. It was supposed that lag would be determined by two hypothetical quantities, the amount of work that a cell has to perform to adapt to new conditions and the rate at which it can perform that work. If the rate at which the cell can perform the necessary work is a function of the maximum specific growth rate in the new environment, the hypothesis predicts that lag time should be related in some way to growth rate, provided cells are initially in approximately the same physiological state. Literature data suggest this is true for many organisms when temperature is the sole growth limiting factor. However, lag times of L. monocytogenes displayed an unusual response to temperature in which lag times of cells precultured at 37 degrees C were shorter at 15 degrees C than at 20 degrees C or 25 degrees C. Analysis of data from the Food Micromodel in which growth of L. monocytogenes was controlled by combinations of pH, NaCl concentration and temperature, showed that there was a linear relationship between lag time and mean generation time although there was much scatter in the data. When the effects of pH, solute type and concentration were investigated individually in this work the correlation between lag time and mean generation time was often poor. It would thus appear that the relationship between growth environment and lag time is more complex than the corresponding relationship between growth environment and maximum specific growth rate.

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Year:  1998        PMID: 9849786     DOI: 10.1016/s0168-1605(98)00120-2

Source DB:  PubMed          Journal:  Int J Food Microbiol        ISSN: 0168-1605            Impact factor:   5.277


  22 in total

1.  Predictive modeling of the shelf life of fish under nonisothermal conditions.

Authors:  K Koutsoumanis
Journal:  Appl Environ Microbiol       Date:  2001-04       Impact factor: 4.792

2.  Lag phase of Salmonella enterica under osmotic stress conditions.

Authors:  K Zhou; S M George; A Métris; P L Li; J Baranyi
Journal:  Appl Environ Microbiol       Date:  2010-12-30       Impact factor: 4.792

3.  Development of a microbial model for the combined effect of temperature and pH on spoilage of ground meat, and validation of the model under dynamic temperature conditions.

Authors:  K Koutsoumanis; A Stamatiou; P Skandamis; G-J E Nychas
Journal:  Appl Environ Microbiol       Date:  2006-01       Impact factor: 4.792

4.  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

5.  Influence of environmental stress on distributions of times to first division in Escherichia coli populations, as determined by digital-image analysis of individual cells.

Authors:  Gordon W Niven; Jennifer S Morton; Tamara Fuks; Bernard M Mackey
Journal:  Appl Environ Microbiol       Date:  2008-04-18       Impact factor: 4.792

6.  Modeling the lag period and exponential growth of Listeria monocytogenes under conditions of fluctuating temperature and water activity values.

Authors:  Marina Muñoz-Cuevas; Pablo S Fernández; Susan George; Carmen Pin
Journal:  Appl Environ Microbiol       Date:  2010-03-05       Impact factor: 4.792

7.  Modeling the effect of abrupt acid and osmotic shifts within the growth region and across growth boundaries on adaptation and growth of Listeria monocytogenes.

Authors:  Y Le Marc; P N Skandamis; C I A Belessi; S I Merkouri; S M George; A S Gounadaki; S Schvartzman; K Jordan; E H Drosinos; J Baranyi
Journal:  Appl Environ Microbiol       Date:  2010-07-30       Impact factor: 4.792

8.  Influence of stress on individual lag time distributions of Listeria monocytogenes.

Authors:  L Guillier; P Pardon; J-C Augustin
Journal:  Appl Environ Microbiol       Date:  2005-06       Impact factor: 4.792

9.  Comparison of two optical-density-based methods and a plate count method for estimation of growth parameters of Bacillus cereus.

Authors:  Elisabeth G Biesta-Peters; Martine W Reij; Han Joosten; Leon G M Gorris; Marcel H Zwietering
Journal:  Appl Environ Microbiol       Date:  2010-01-15       Impact factor: 4.792

10.  A random effect multiplicative heteroscedastic model for bacterial growth.

Authors:  Ricardo Cao; Mario Francisco-Fernández; Emiliano J Quinto
Journal:  BMC Bioinformatics       Date:  2010-02-08       Impact factor: 3.169

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