Patterns of interdivision time correlations reveal hidden cell cycle factors

  1. Fern A Hughes
  2. Alexis Barr  Is a corresponding author
  3. Philipp Thomas  Is a corresponding author
  1. Imperial College London, United Kingdom
  2. MRC London Institute of Medical Sciences, United Kingdom

Abstract

The time taken for cells to complete a round of cell division is a stochastic process controlled, in part, by intracellular factors. These factors can be inherited across cellular generations which gives rise to, often non-intuitive, correlation patterns in cell cycle timing between cells of different family relationships on lineage trees. Here, we formulate a framework of hidden inherited factors affecting the cell cycle that unifies known cell cycle control models and reveals three distinct interdivision time correlation patterns: aperiodic, alternator and oscillator. We use Bayesian inference with single-cell datasets of cell division in bacteria, mammalian and cancer cells, to identify the inheritance motifs that underlie these datasets. From our inference, we find that interdivision time correlation patterns do not identify a single cell cycle model but generally admit a broad posterior distribution of possible mechanisms. Despite this unidentifiability, we observe that the inferred patterns reveal interpretable inheritance dynamics and hidden rhythmicity of cell cycle factors. This reveals that cell cycle factors are commonly driven by circadian rhythms, but their period may differ in cancer. Our quantitative analysis thus reveals that correlation patterns are an emergent phenomenon that impact cell proliferation and these patterns may be altered in disease.

Data availability

The current manuscript is a computational study, so no data have been generated for this manuscript. Modelling code is uploaded to gitHub https://github.com/fernhughes/Lineage-tree-correlation-pattern-inference.

The following previously published data sets were used

Article and author information

Author details

  1. Fern A Hughes

    Department of Mathematics, Imperial College London, London, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  2. Alexis Barr

    MRC London Institute of Medical Sciences, London, United Kingdom
    For correspondence
    a.barr@lms.mrc.ac.uk
    Competing interests
    The authors declare that no competing interests exist.
  3. Philipp Thomas

    Department of Mathematics, Imperial College London, London, United Kingdom
    For correspondence
    p.thomas@imperial.ac.uk
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4919-8452

Funding

EPSRC Centre for Mathematics of Precision Healthcare (EP/N014529/1)

  • Fern A Hughes

MRC London Institute of Medical Sciences (MC-A658-5TY60)

  • Alexis Barr

UKRI Future Leaders Fellowship (MR/T018429/1)

  • Philipp Thomas

CRUK Career Development Fellowship (C63833/A25729)

  • Alexis Barr

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

Reviewing Editor

  1. Arvind Murugan, University of Chicago, United States

Version history

  1. Received: June 9, 2022
  2. Preprint posted: June 28, 2022 (view preprint)
  3. Accepted: November 14, 2022
  4. Accepted Manuscript published: November 15, 2022 (version 1)
  5. Version of Record published: January 6, 2023 (version 2)

Copyright

© 2022, Hughes 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.

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  1. Fern A Hughes
  2. Alexis Barr
  3. Philipp Thomas
(2022)
Patterns of interdivision time correlations reveal hidden cell cycle factors
eLife 11:e80927.
https://doi.org/10.7554/eLife.80927

Share this article

https://doi.org/10.7554/eLife.80927

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