# Inferring bacterial cell size dynamics across media conditions

## TL;DR

The paper studies how bacterial cell size changes under different growth conditions and develops a model to predict these changes.

## Contribution

A mathematical model is introduced to predict time-varying division rates affecting cell size dynamics across media conditions.

## Key findings

- Escherichia coli and Salmonella enterica show similar cell volume distributions in stationary phase regardless of growth media.
- Resuspending cells in rich media causes a transient increase in cell volume before returning to stationary phase size.
- A mathematical model successfully predicts mean cell size dynamics based on division rate changes.

## Abstract

Under stable growth conditions, bacteria maintain cell size homeostasis through coordinated elongation and division. Changes in nutrient availability perturb these mechanisms, resulting in dynamic regulation of the target cell size. Using microscopy imaging and mathematical modeling, we studied how bacterial cell volume changes over the population growth curve and found that Escherichia coli and Salmonella enterica, in stationary phase, exhibit similar cell volume distributions irrespective of growth media. Resuspending cells in rich media resulted in a transient increase in cell volume to a media-dependent maximum cell volume after \documentclass[12pt]{minimal}
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\begin{document}$$\approx$$\end{document} 2h before decreasing to the stationary phase cell size. Interestingly, stabilizing the growth phase through continuous fresh media supply sustained the size distribution. In poor media conditions, cell volume changed minimally over the growth curve, but cell width was markedly decreased. This cell volume dynamics along the growth curve can be related to a similar increase and decrease dynamics of the ratio between cell density (\documentclass[12pt]{minimal}
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\begin{document}$$\mathrm{OD}_{600}$$\end{document}) and cell numbers (CFU). We developed a simple mathematical modeling framework that predicted a time-varying division rate needed to capture the dynamics of the mean cell size across media conditions. The proposed analysis can be used for comparison of cell size regulation mechanisms across dynamic environments when single-cell tracking is not possible.