Temperature-dependent growth kinetics of Escherichia coli ML 30 in glucose-limited continuous culture

Abstract

Knowledge concerning the influence of environmental factors such as temperature, pH, salinity, etc., on microbial growth is of crucial practical importance in the control of bioprocesses, for the safe handling of food (1, 2, 12, 50, 51), in wastewater treatment (7), and in bioremediation (2). In addition, in taxonomy, cardinal temperatures for growth are key characteristics of microbial strains (37).In recent years, several models for predicting the growth rate of microorganisms as a function of either temperature alone (11,13,22,31,32,52,53) or of temperature in combination with other factors have been proposed (1, 5, 20-22, 36, 50). Surprisingly, few attempts at a better basic understanding have been made to relate the rate of growth and actual substrate concentration. This relationship is traditionally termed growth kinetics (23,30). (However, note that the same expression has also been used for the description of the time courses of population densities [5].) The current lack of systematic data on the influence of temperature on the kinetics of growth makes the prediction of this effect difficult. Temperature modulation of growth kinetics is to be expected, because both metabolism and cellular composition are affected by cultivation temperature, as was demonstrated by the cellular fatty acid composition (16, 26, 41), the synthesis or degradation of certain proteins (14,15,17,20,25), changes in protein activity (15, 35), changes in maintenance requirements of cells (19,27,39,42,47), changes in end products of metabolism (17), and increases in pigment formation (27).Bacterial metabolism represents a network of reactions. Although these individual biochemical reactions are temperature dependent, the fundamental question of whether the parameters used in growth kinetic models are temperature dependent must be asked. To determine this, a detailed comparison of growth kinetics at temperatures below and above the optimal temperature was carried out for Escherichia coli ML 30 cultivated in continuous culture with glucose and/or galactose. Such investigations are possible only by using an extremely sensitive method for measuring low concentrations of sugars (in micrograms per liter) in culture media (40). The objective of the present study was to compare the experimentally established relationships between growth rate and steady-state substrate concentrations at different constant temperatures and to find out whether the whole set of relationships can be described by a simple mathematical model (Table 1 summarizes the nomenclature used throughout). Additionally, the effect of temperature on steady-state substrate concentrations at constant growth rates (dilution rates in continuous culture) was studied.Compendium of the models proposed in the literature. (i) Conventional growth kinetics and models containing an s min term. Various mathematical models have been proposed to quantitatively describe microbial growth kinetics. The Monod model (equation 1) is considered the basic equation (23), which has since been improve...

In glucose-limited continuous culture the minimum substrate concentration for growth, smin, is crucial in the competition between the enterobacterium Escherichia coli and Chelatobacter heintzii, an environmentally abundant bacterium

“…In earlier work on the growth of E. coli in glucoselimited chemostat culture at 37 1C (Senn et al, 1994), we found that s ¼ f(D) three kinetic models fitted the data with similar quality (Monod, Shehata and Marr, Westerhoff). Extending this work to suboptimal and superoptimal temperatures (17, 28 and 40 1C), we experimentally observed a clear indication for the existence of a finite glucose concentration at zero growth rate, and when extending the classical Monod model with an s min , the obtained kinetic data could be fitted well and statistically better than with any other model of similar complexity (Kovárová et al, 1996). Hence, the original (1) and the extended Monod model (2) were the obvious model of choice to be applied to our competition experiments.…”

“…The most important one is the very low residual substrate concentrations under which this competition takes place; they are usually in the range of a few mg per litre, that is, below detection limit. Therefore, in contrast to earlier studies at higher growth rates (Senn et al, 1994;Kovárová et al, 1996;Lendenmann et al, 2000), K s can usually not be determined by measuring the residual concentration of the growth controlling substrate. Another aspect is that slow-growing cells (for example, from a low D in continuous culture) are usually not able to immediately increase the rate of growth when transferred to substrate excess conditions.…”

“…Recently, van Bodegom (2007) introduced an additional conceptual model that differentiates between growth and non-growth components of maintenance. In several studies, existence of an s min has been observed in continuous culture systems (Kovárová et al, 1996;Tros et al, 1996a;Fü chslin et al, 2003). In glucose-limited chemostat culture, Kovárová et al (1996) experimentally examined the growth kinetics of E. coli ML30 (the strain also used in this study) and proposed to expand the Monod model by the additional term of s min .…”

“…In several studies, existence of an s min has been observed in continuous culture systems (Kovárová et al, 1996;Tros et al, 1996a;Fü chslin et al, 2003). In glucose-limited chemostat culture, Kovárová et al (1996) experimentally examined the growth kinetics of E. coli ML30 (the strain also used in this study) and proposed to expand the Monod model by the additional term of s min . It was suggested that the phenomenon of s min is caused by the maintenance energy demand (Pirt, 1965), limiting diffusion kinetics (Schmidt et al, 1985;Bosma et al, 1996) or by the minimum concentration required for enzyme induction (Lechner and Straube, 1984).…”

Speciation and concentrations of dissolved nitrogen as determinants of brown tide Aureococcus anophagefferens bloom initiation

“…Growth rates in most experiments were saturating functions of dissolved nitrogen concentration, S (μ = μ max [S/K s + S]), permitting calculation of the Monod kinetic parameters K s (half-saturation constant) and μ max (maximum growth rate). In 2 instances, an extended form of the Monod model (μ = μ max [(S -S min )/(K s + S -S min ]) was employed because negative growth was observed below a finite nutrient concentration (S min ; Kovarova et al 1996). Monod constants were estimated by 2 methods; indirectly by Eadee-Hofstee linear transformation and directly by iterative non-linear curve fitting (Marquardt-Levenberg method: SPSS SigmaPlot version 8.0).…”