Availability of the Molecular Switch XylR Controls Phenotypic Heterogeneity and Lag Duration during Escherichia coli Adaptation from Glucose to Xylose

ABSTRACT

The glucose-xylose metabolic transition is of growing interest as a model to explore cellular adaption since these molecules are the main substrates resulting from the deconstruction of lignocellulosic biomass. Here, we investigated the role of the XylR transcription factor in the length of the lag phases when the bacterium Escherichia coli needs to adapt from glucose- to xylose-based growth. First, a variety of lag times were observed when different strains of E. coli were switched from glucose to xylose. These lag times were shown to be controlled by XylR availability in the cells with no further effect on the growth rate on xylose. XylR titration provoked long lag times demonstrated to result from phenotypic heterogeneity during the switch from glucose to xylose, with a subpopulation unable to resume exponential growth, whereas the other subpopulation grew exponentially on xylose. A stochastic model was then constructed based on the assumption that XylR availability influences the probability of individual cells to switch to xylose growth. The model was used to understand how XylR behaves as a molecular switch determining the bistability set-up. This work shows that the length of lag phases in E. coli is controllable and reinforces the role of stochastic mechanism in cellular adaptation, paving the way for new strategies for the better use of sustainable carbon sources in bioeconomy.

IMPORTANCE For decades, it was thought that the lags observed when microorganisms switch from one substrate to another are inherent to the time required to adapt the molecular machinery to the new substrate. Here, the lag duration was found to be the time necessary for a subpopulation of adapted cells to emerge and become the main population. By identifying the molecular mechanism controlling the subpopulation emergence, we were able to extend or reduce the duration of the lags. This work is of special importance since it demonstrates the unexpected complexity of monoclonal populations during growth on mixed substrates and provides novel mechanistic insights with regard to bacterial cellular adaptation.