Code for "Proteome adaptation in the last phase of growth contributes to lower the death rate of Escherichia coli during starvation"
Description
Code used for the simulations employed in the manuscript "Proteome adaptation in the last phase of growth contributes to lower the death rate of Escherichia coli during starvation" In this folder you can find the code that simulates the allocation strategy and proteome dynamics during the shift to starvation, as described in the manuscript. The model is based upon the FCR model, published by Erikson, Schink et al in 2017. In this program, you can simulate the dynamics of the shift experiment by fitting the time course of the growth rate with a sigmoid (as in the manuscript) and inserting the values of the parameters of the fit in the program. You can simulate the three different dynamics that we propose: the global regulation one, the targeted towards the survival sector, and the targeted towards the harmful. Abstract: One form of non-genetic memory in microorganisms is in the composition of the cellular proteome, which changes only slowly, as without significant protein degradation the dilution of the old proteome by cell growth and division sets the lifetime for this proteome memory. Cells can benefit from their non-genetic memory when previously encountered environmental conditions recur, but the proteome memory has also been shown to limit the speed of adaptation processes. This limitation could be particularly severe when the environment shifts to carbon starvation, depriving cells of both energy and material needed for growth. Here, we study the adaptation that occurs during gradual transitions from exponential growth to carbon starvation. We probe such transitions in cultures with different initial growth conditions and measure the resulting rates of cell death after the transition. We consistently observe lower death rates for cells that could adapt their proteome before entering carbon starvation compared to cells that could not. The quantitative data is consistent with a theoretical model built on the assumption that before starvation, cells up-regulate a specific sector of the proteome, the effect of which is to decrease the death rate in energy-limiting conditions. Our results emphasize that a comprehensive understanding of bacterial fitness requires quantitative characterization of bacterial physiology in all phases of their life cycle, including growth, stationary phase, and death, as well as the transitions between them.
Files
Steps to reproduce
Please refer to the README.txt file contained in the folder