Applied Microbial and Cell Physiology

Applied Microbiology and Biotechnology

, Volume 89, Issue 3, pp 791-798

First online:

Non-linear population dynamics in chemostats associated with live–dead cell cycling in Escherichia coli strain K12-MG1655

  • Ernest Chi FruAffiliated withSchool of Civil Engineering and Geosciences, Newcastle University
  • , Irina Dana OfiţeruAffiliated withSchool of Civil Engineering and Geosciences, Newcastle UniversityChemical Engineering Department, University Politehnica of Bucharest
  • , Vasile LavricAffiliated withChemical Engineering Department, University Politehnica of Bucharest
  • , David W. GrahamAffiliated withSchool of Civil Engineering and Geosciences, Newcastle University Email author 

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Bacterial populations conditionally display non-linear dynamic behaviour in bioreactors with steady inputs, which is often attributed to varying habitat conditions or shifting intracellular metabolic activity. However, mathematical modelling has predicted that such dynamics also might simply result from staggered birth, growth, and death events of groups of cells within the population, causing density oscillations and the cycling of live and dead cells within the system. To assess this prediction, laboratory experiments were performed on Escherichia coli strain K12-MG1655 grown in chemostats to first define fine-scale population dynamics over time (minutes) and then determine whether the dynamics correlate with live–dead cell cycles in the system. E. coli populations displayed consistent oscillatory behaviour in all experiments. However, close synchronisation between OD600 and live–dead cell oscillations (within ~33–38 min cycles) only became statistically significant (p < 0.01) when pseudo-steady state operations approaching carrying capacity existed in the bioreactor. Specifically, live cells were highest at local OD600 maxima and lowest at local OD600 minima, showing that oscillations followed live–dead cell cycles as predicted by the model and also consistent with recent observations that death is non-stochastic in such populations. These data show that oscillatory dynamic behaviour is intrinsic in bioreactor populations, which has implications to process operations in biotechnology.


Bacteria Chemostats Population dynamics Cell death Carrying capacity