Patterns of interdivision time correlations reveal hidden cell cycle factors
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 differe...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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eLife Sciences Publications Ltd
2022-11-01
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| Series: | eLife |
| Subjects: | |
| Online Access: | https://elifesciences.org/articles/80927 |
| _version_ | 1797959794993135616 |
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| author | Fern A Hughes Alexis R Barr Philipp Thomas |
| author_facet | Fern A Hughes Alexis R Barr Philipp Thomas |
| author_sort | Fern A Hughes |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-11T00:37:47Z |
| format | Article |
| id | doaj.art-281be6ad616c44e196df61e250e3120e |
| institution | Directory Open Access Journal |
| issn | 2050-084X |
| language | English |
| last_indexed | 2024-04-11T00:37:47Z |
| publishDate | 2022-11-01 |
| publisher | eLife Sciences Publications Ltd |
| record_format | Article |
| series | eLife |
| spelling | doaj.art-281be6ad616c44e196df61e250e3120e2023-01-06T15:08:21ZengeLife Sciences Publications LtdeLife2050-084X2022-11-011110.7554/eLife.80927Patterns of interdivision time correlations reveal hidden cell cycle factorsFern A Hughes0https://orcid.org/0000-0002-4599-5027Alexis R Barr1https://orcid.org/0000-0002-6684-8114Philipp Thomas2https://orcid.org/0000-0003-4919-8452Department of Mathematics, Imperial College London, London, United Kingdom; MRC London Institute of Medical Sciences, London, United KingdomMRC London Institute of Medical Sciences, London, United Kingdom; Institute of Clinical Sciences, Imperial College London, London, United KingdomDepartment of Mathematics, Imperial College London, London, United KingdomThe 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.https://elifesciences.org/articles/80927cell cyclecircadian rhythmpatternslineage correlationcellular noisestochastic modelling |
| spellingShingle | Fern A Hughes Alexis R Barr Philipp Thomas Patterns of interdivision time correlations reveal hidden cell cycle factors eLife cell cycle circadian rhythm patterns lineage correlation cellular noise stochastic modelling |
| title | Patterns of interdivision time correlations reveal hidden cell cycle factors |
| title_full | Patterns of interdivision time correlations reveal hidden cell cycle factors |
| title_fullStr | Patterns of interdivision time correlations reveal hidden cell cycle factors |
| title_full_unstemmed | Patterns of interdivision time correlations reveal hidden cell cycle factors |
| title_short | Patterns of interdivision time correlations reveal hidden cell cycle factors |
| title_sort | patterns of interdivision time correlations reveal hidden cell cycle factors |
| topic | cell cycle circadian rhythm patterns lineage correlation cellular noise stochastic modelling |
| url | https://elifesciences.org/articles/80927 |
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