Two different cell-cycle processes determine the timing of cell division in Escherichia coli

  1. Alexandra Colin
  2. Gabriele Micali
  3. Louis Faure
  4. Marco Cosentino Lagomarsino  Is a corresponding author
  5. Sven van Teeffelen  Is a corresponding author
  1. Institut Pasteur, France
  2. ETH Zürich, Switzerland
  3. Medical University of Vienna, Austria
  4. IFOM Foundation and University of Milan, Italy
  5. Université de Montréal, Canada

Abstract

Cells must control the cell cycle to ensure that key processes are brought to completion. In Escherichia coli, it is controversial whether cell division is tied to chromosome replication or to a replication-independent inter-division process. A recent model suggests instead that both processes may limit cell division with comparable odds in single cells. Here, we tested this possibility experimentally by monitoring single-cell division and replication over multiple generations at slow growth. We then perturbed cell width, causing an increase of the time between replication termination and division. As a consequence, replication became decreasingly limiting for cell division, while correlations between birth and division and between subsequent replication-initiation events were maintained. Our experiments support the hypothesis that both chromosome replication and a replication-independent inter-division process can limit cell division: the two processes have balanced contributions in non-perturbed cells, while our width perturbations increase the odds of the replication-independent process being limiting.

Data availability

All data generated or analysed during this study are included in supplemental datasets provided for each figure. Average quantities and sample sizes for each biological replicate can be found in Supplementary file 1. Supplementary file 2 contains all single-cell data used in this study.

Article and author information

Author details

  1. Alexandra Colin

    Microbial Morphogenesis and Growth Laboratory, Institut Pasteur, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9144-3282
  2. Gabriele Micali

    Department of Environmental Systems Science, ETH Zürich, Zürich, Switzerland
    Competing interests
    The authors declare that no competing interests exist.
  3. Louis Faure

    Department of Neuro-Immunology, Medical University of Vienna, Wien, Austria
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4621-586X
  4. Marco Cosentino Lagomarsino

    Quantitative Biology and Physics, IFOM Foundation and University of Milan, Milan, Italy
    For correspondence
    marco.cosentino-lagomarsino@ifom.eu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0235-0445
  5. Sven van Teeffelen

    Département de Microbiologie, Infectiologie et Immunologie, Université de Montréal, Montréal, Canada
    For correspondence
    sven.vanteeffelen@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0877-1294

Funding

H2020 European Research Council (679980)

  • Sven van Teeffelen

Agence Nationale de la Recherche (ANR-10-LABX-62-IBEID)

  • Sven van Teeffelen

Mairie de Paris Emergence program

  • Sven van Teeffelen

Volkswagen Foundation Life program

  • Sven van Teeffelen

Italian Association for Cancer Research AIRC-IG (23258)

  • Marco Cosentino Lagomarsino

National Science Foundationce Foundation (310030_188642)

  • Gabriele Micali

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2021, Colin et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 3,348
    views
  • 414
    downloads
  • 29
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Alexandra Colin
  2. Gabriele Micali
  3. Louis Faure
  4. Marco Cosentino Lagomarsino
  5. Sven van Teeffelen
(2021)
Two different cell-cycle processes determine the timing of cell division in Escherichia coli
eLife 10:e67495.
https://doi.org/10.7554/eLife.67495

Share this article

https://doi.org/10.7554/eLife.67495

Further reading

    1. Computational and Systems Biology
    2. Evolutionary Biology
    Pierre Barrat-Charlaix, Richard A Neher
    Research Article

    As pathogens spread in a population of hosts, immunity is built up, and the pool of susceptible individuals are depleted. This generates selective pressure, to which many human RNA viruses, such as influenza virus or SARS-CoV-2, respond with rapid antigenic evolution and frequent emergence of immune evasive variants. However, the host’s immune systems adapt, and older immune responses wane, such that escape variants only enjoy a growth advantage for a limited time. If variant growth dynamics and reshaping of host-immunity operate on comparable time scales, viral adaptation is determined by eco-evolutionary interactions that are not captured by models of rapid evolution in a fixed environment. Here, we use a Susceptible/Infected model to describe the interaction between an evolving viral population in a dynamic but immunologically diverse host population. We show that depending on strain cross-immunity, heterogeneity of the host population, and durability of immune responses, escape variants initially grow exponentially, but lose their growth advantage before reaching high frequencies. Their subsequent dynamics follows an anomalous random walk determined by future escape variants and results in variant trajectories that are unpredictable. This model can explain the apparent contradiction between the clearly adaptive nature of antigenic evolution and the quasi-neutral dynamics of high-frequency variants observed for influenza viruses.

    1. Computational and Systems Biology
    2. Medicine
    Xin Zhou, Zhinuo Jenny Wang ... Blanca Rodriguez
    Research Article

    Sudden death after myocardial infarction (MI) is associated with electrophysiological heterogeneities and ionic current remodelling. Low ejection fraction (EF) is used in risk stratification, but its mechanistic links with pro-arrhythmic heterogeneities are unknown. We aim to provide mechanistic explanations of clinical phenotypes in acute and chronic MI, from ionic current remodelling to ECG and EF, using human electromechanical modelling and simulation to augment experimental and clinical investigations. A human ventricular electromechanical modelling and simulation framework is constructed and validated with rich experimental and clinical datasets, incorporating varying degrees of ionic current remodelling as reported in literature. In acute MI, T-wave inversion and Brugada phenocopy were explained by conduction abnormality and local action potential prolongation in the border zone. In chronic MI, upright tall T-waves highlight large repolarisation dispersion between the border and remote zones, which promoted ectopic propagation at fast pacing. Post-MI EF at resting heart rate was not sensitive to the extent of repolarisation heterogeneity and the risk of repolarisation abnormalities at fast pacing. T-wave and QT abnormalities are better indicators of repolarisation heterogeneities than EF in post-MI.