To grow is not enough: impact of noise on cell environmental response and fitness

Abstract

Quantitative single cell measurements have shown that cell cycle duration (the time between cell divisions) for diverse cell types is a noisy variable. The underlying distribution is mean scalable with a universal shape for many cell types in a variety of environments. Here we explore through both experiment and theory the response of these distributions to large environmental perturbations. In particular, we discuss how the stochasticity of the ensemble may be related to the response. Our findings show that slow growing, noisy populations are more adaptive than those which are fast growing. We suggest that even non-cooperative cells in exponential growth phase may not optimize fitness through growth rate alone, but also optimize adaptability to changing conditions. In this work, we wish to emphasize that in a manner similar to genetic evolution, noise in biochemical processes may be important to allow for cells to adapt to rapid to environmental changes.

Theoretical investigation of stochastic clearance of bacteria: first-passage analysis

“…Our method is also applied to investigate the effect of fluctuations in the growth rates on the stochastic clearance of bacterial populations. These fluctuations can be attributed to various environmental factors such as the availability of nutrients, changes in osmolarity and other factors [25]. Our results suggest that these fluctuations influence the extinction probabilities and extinction times differently.…”

Theoretical investigation of stochastic clearance of bacteria: First-passage analysis

“…Our 61 method is also applied to investigate the effect of fluctuations in the growth rates on the 62 stochastic clearance of bacterial populations. These fluctuations can be attributed to 63 various environmental factors such as availability of nutrients, changes in osmolarity and 64 2/18 other factors [30]. Our results suggest that these fluctuations influence the extinction 65 probabilities and extinction times differently.…”

“…This 119 result suggests that even for concentrations above MIC the extinction probability is 120 never equal to one, which is again due to the stochastic fluctuations in the system. Our 121 analytical calculations were verified with Monte Carlo computer simulations, in which 122 we utilized typical growth rates associated with bacteria E. coli, in range from 1/300 123 min −1 to 1/20 min −1 [30]. 124 The stochastic effects of the bacterial clearance can be understood better if we 125 consider the extinction probability of a specific inoculum size (n = N/2), equally distant 126 from the state n = 0 (eradication) and n = N (death), which is plotted in figure 2(b).…”

“…For this reason, the model is characterized by only 75 two parameters: the rate of cell growth λ and the rate of cell death φ: see figure 1. The 76 bacterial growth rate is generally controlled by the environmental factors such as the 77 availability of nutrients, temperature, osmotic pressure and other factors [30]. When 78 exposed to antibiotics, the cell growth rate can also depend on the antibiotic 79 concentration [16].…”

“…For 198 example, single cell experiments have shown that the cell cycle duration is subject to 199 random fluctuations. [30,31]. We can investigate the effect of growth rate fluctuations 200 on the bacterial clearance dynamics using our theoretical first-passage probabilities 201 method.…”