Division in Escherichia coli is triggered by a size-sensing rather than a timing mechanism
- Equal contributors
1 INRA, Micalis CNRS-UMR 1319, 78350 Jouy-en-Josas, France
2 AgroParisTech, Micalis CNRS-UMR 1319, 78350 Jouy-en-Josas, France
3 Paris Dauphine University, CNRS-UMR 7534, Place du maréchal De Lattre de Tassigny, 75775 Paris, France
4 University of Rennes 1, CNRS-UMR 6625, Campus de Beaulieu, 35042 Rennes, France
5 CNRS/UPMC University of Paris 6, FRE 3231, Laboratoire Jean Perrin LJP, 75005 Paris, France
6 INRIA Paris-Rocquencourt, Domaine de Voluceau, BP 105, 781153 Le Chesnay, France
7 UPMC University of Paris 6, JL Lions Lab., 4 place Jussieu, 75005 Paris, France
BMC Biology 2014, 12:17 doi:10.1186/1741-7007-12-17Published: 28 February 2014
Many organisms coordinate cell growth and division through size control mechanisms: cells must reach a critical size to trigger a cell cycle event. Bacterial division is often assumed to be controlled in this way, but experimental evidence to support this assumption is still lacking. Theoretical arguments show that size control is required to maintain size homeostasis in the case of exponential growth of individual cells. Nevertheless, if the growth law deviates slightly from exponential for very small cells, homeostasis can be maintained with a simple ‘timer’ triggering division. Therefore, deciding whether division control in bacteria relies on a ‘timer’ or ‘sizer’ mechanism requires quantitative comparisons between models and data.
The timer and sizer hypotheses find a natural expression in models based on partial differential equations. Here we test these models with recent data on single-cell growth of Escherichia coli. We demonstrate that a size-independent timer mechanism for division control, though theoretically possible, is quantitatively incompatible with the data and extremely sensitive to slight variations in the growth law. In contrast, a sizer model is robust and fits the data well. In addition, we tested the effect of variability in individual growth rates and noise in septum positioning and found that size control is robust to this phenotypic noise.
Confrontations between cell cycle models and data usually suffer from a lack of high-quality data and suitable statistical estimation techniques. Here we overcome these limitations by using high precision measurements of tens of thousands of single bacterial cells combined with recent statistical inference methods to estimate the division rate within the models. We therefore provide the first precise quantitative assessment of different cell cycle models.