Objective method to estimate the duration of the DNAreplication cycle without perturbation in Escherichia coli.

Abstract

All cells, including unicellular organisms such as Escherichia coli, depend on the robustness of their cell cycle for proliferation. The cell cycle is central to the organisms highly resilient proliferation program and is thus a key focus in many areas of cell biology. However, studying the DNA replication cycle in bacteria remains challenging due to technical limitations. The durations of the replicative and post-replicative phases (known as the C and D periods, respectively) are inferred from the analysis of cellular DNA content distributions, obtained through microscopy or flow cytometry. This analysis typically requires pharmacological treatments to conduct replication run-off experiments, which help distinguish between cells that have or have not yet initiated DNA replication. Four decades ago, Skarstad, Steen and Boye showed that flow cytometry profiles measuring DNA amount per cell from exponentially growing cells could provide sufficient information to infer the durations of cell cycle periods at low growth rates. In this study, we propose an objective and automated approach that implements this idea to estimate cell cycle parameters for any growth conditions. Specifically, we validate a Nested Sampling method to estimate cell cycle parameters directly from flow cytometry data, eliminating the dependence on bacterial strain sensitivity to drugs. This tool, available as a Python package, allows for the accurate and minimally biased estimation of the C+D period under any biologically relevant conditions. Given its independence from pharmacological treatments, we anticipate broad adoption of this tool, especially as we show that most natural isolates of E. coli are not amenable to the state of the art replication run-off experiments.