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Modelling the work to be done by Escherichia coli to adapt to sudden temperature upshifts
Author(s) -
Swinnen I.A.M.,
Bernaerts K.,
Van Impe J.F.
Publication year - 2006
Publication title -
letters in applied microbiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.698
H-Index - 110
eISSN - 1472-765X
pISSN - 0266-8254
DOI - 10.1111/j.1472-765x.2006.01896.x
Subject(s) - amplitude , growth rate , lag , exponential growth , work (physics) , escherichia coli , biological system , function (biology) , phase (matter) , biology , bacterial growth , thermodynamics , materials science , chemistry , mathematics , physics , genetics , computer science , optics , mathematical analysis , bacteria , computer network , geometry , gene , organic chemistry
Aims: This paper studies and models the effect of the amplitude of a sudden temperature upshift Δ T on the adaptation period of Escherichia coli , in terms of the work to be done by the cells during the subsequent lag phase (i.e., the product of growth rate μ max and lag phase duration λ ). Methods and Results: Experimental data are obtained from bioreactor experiments with E. coli K12 MG1655. At a predetermined time instant during the exponential growth phase, a sudden temperature upshift is applied (no other environmental changes take place). The length of the (possibly) induced lag phase and the specific growth rate after the shift are quantified with the growth model of Baranyi and Roberts (Int J Food Microbiol 23, 1994, 277). Different models to describe the evolution of the product λ × μ max as a function of the amplitude of the temperature shift are statistically compared. Conclusions: The evolution of λ × μ max is influenced by the amplitude of the temperature shift Δ T and by the normal physiological temperature range. As some cut‐off is observed, the linear model with translation is preferred to describe this evolution. Significance and Impact of the Study: This work contributes to the characterization of microbial lag phenomena, in this case for E. coli K12 MG1655, in view of accurate predictive model building.