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

doi:10.1016/S0168-1605(98)00120-2

International Journal of Food Microbiology

Volume 44, Issues 1–2, 20 October 1998, Pages 83-92

https://doi.org/10.1016/S0168-1605(98)00120-2 Get rights and content

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°C were shorter at 15°C than at 20°C or 25°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.

Introduction

The lag phase of microbial growth was defined by Penfold (1914)as the interval between the inoculation of a bacterial culture and the time of commencement of its maximum rate of growth. It has been conventionally measured as the point at which the slope of the exponential phase of growth (on a semi-logarithmic plot) intercepts a horizontal line drawn from the initial cell concentration (Lodge and Hinshelwood, 1943). Several other definitions of lag have been employed depending on the mathematical model or curve fitting procedure applied to the growth data (Buchanan and Cygnarowicz, 1990Zwietering et al., 1991Zwietering et al., 1992). In physiological terms, lag represents a transition period during which cells adjust to their new environment. Pirt (1975)recognized the following causes of lag: (i) change in nutrition, (ii) change in physical environment, (iii) presence of an inhibitor, (iv) spore germination and (v) state of the inoculum. The early literature was reviewed by Penfold (1914), Winslow and Wilson (1939)and Hinshelwood (1946). The effect of inoculum age, inoculum size, nutrient content of media, carbon dioxide concentration was established in these studies at least on a broad qualitative basis. More recent work has also examined the effect of cellular injury (Mackey and Derrick, 1982, Mackey and Derrick, 1984, Tsuchido et al., 1989).

Lag times and growth rates of the major foodborne pathogens and some spoilage organisms have been measured under a wide range of growth conditions to develop methods for predicting microbial behaviour in foods. The data have been incorporated into mathematical models that allow growth rates of many foodborne bacteria to be predicted with a fair degree of accuracy from a knowledge of temperature, pH, solute content or water activity, gas atmosphere and preservative content (reviewed by McMeekin et al., 1993).

Lag is inherently more difficult to predict than growth rate because it depends on the physiological state of the inoculum as well as growth conditions. Pre-adaptation to inimical growth conditions can shorten lag times dramatically (Hudson, 1993, Kroll and Patchett, 1992, Buchanan and Klawitter, 1991, Dufrenne et al., 1997) and the magnitude of this effect is difficult to predict. Even when inoculum effects have been minimised, it has still proved difficult to obtain a clear picture of the way lag varies as a function of the external environment. However, several studies have demonstrated a relationship between lag time and growth rate (Smith, 1985, Mackey and Kerridge, 1988, Adair et al., 1989, Baranyi and Roberts, 1994) but the general validity of this relationship has not been fully explored.

A better understanding of the determinants of lag and the relative importance of physiological state and environmental conditions would help define the accuracy limits of predictive models, and might also suggest ways of extending lag and so delaying or preventing growth of undesirable microbes. On the other hand, reducing lag times would have benefits in improving use of starter cultures and in recovering bacteria from food and environmental samples.

The aim of this work was to investigate systematically the effects of solute concentration, pH and temperature on lag times of the foodborne pathogen Listeria monocytogenes, in an attempt to find a quantitative relationship between the physicochemical properties of the growth environment and the duration of lag. The variation in lag time between individual cells in a population is an important aspect of the problem (Baranyi, 1998, Stephens et al., 1997) but is not considered here.

Section snippets

Preparation of inocula

Stationary phase cultures of Listeria monocytogenes NCTC 11994 were prepared by inoculating 10 ml tryptone soya broth, (TSB; Oxoid, Basingstoke, UK) from a slope and then incubating overnight, shaken at 37°C. One hundred μl of this culture were then used to inoculate 10 ml TSB and this was incubated until an OD₆₈₀ of 0.15 was reached. The culture was then incubated for a further 17 h. Stationary phase cultures prepared in this way gave more reproducible results than log phase cultures (results

Experimental approach

We may suppose a priori that the duration of lag will depend on (a) the amount of work that a cell needs to do to adapt to its environment and prepare for division and (b) the rate at which it is able to do that work. By work we mean the various biosynthetic and homeostatic processes needed to prepare for growth in a new environment.

Since there is no convenient direct way of measuring the hypothetical quantities “work needed” (W) and “work rate” (R) independently, we sought to determine whether

Discussion

The work/rate model of bacterial lag described here may be compared with the relative rate concept of Olley and Ratkowsky (1973)where the rate of spoilage of flesh foods (a product of lag and growth rate) at any temperature, was divided by the rate at 0°C to produce the relative rate. This gave an approximately straight line relationship, when compared to temperature (the determinant of rate). Similar ideas are inherent in the gamma model of Zwietering et al. (1994)in which a temperature shift

Acknowledgements

This work was funded by The Ministry of Agriculture Fisheries and Food. M.J.O. was supported by the Spanish Ministry for Science and Education.

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