Abstract

Individual Escherichia coli (E. coli) strains can be characterized by measuring growth rate. Strains better adapted to the environment are expected to grow faster. Classic bacterial growth curves display an increase in optical density over time. In this paper, we use the logistic function to model growth in optical density of E. coli over time. We examine 16 curves for 8 E. coli strains originally isolated from cattle and found many curves have a paradoxical dip at the beginning that is indicative of hormesis (an initial contrarian response showing, stimulation or suppression of growth). We examine several switching functions that allow for the effect of hormesis and compare the ability of nonlinear fixed and mixed models to detect the presence of hormesis.

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Apr 27th, 11:30 AM

USING NONLINEAR FIXED AND MIXED MODELS WITH SWITCHING FUNCTIONS TO ALLOW FOR HORMESIS IN GROWTH OF ESCHERICHIA COLI

Individual Escherichia coli (E. coli) strains can be characterized by measuring growth rate. Strains better adapted to the environment are expected to grow faster. Classic bacterial growth curves display an increase in optical density over time. In this paper, we use the logistic function to model growth in optical density of E. coli over time. We examine 16 curves for 8 E. coli strains originally isolated from cattle and found many curves have a paradoxical dip at the beginning that is indicative of hormesis (an initial contrarian response showing, stimulation or suppression of growth). We examine several switching functions that allow for the effect of hormesis and compare the ability of nonlinear fixed and mixed models to detect the presence of hormesis.