ArticlePLoS computational biology2022
Concentration fluctuations in growing and dividing cells: Insights into the emergence of concentration homeostasis.
Article in PLoS computational biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Multiscale modeling guided potency assessment of mRNA-lipid nanoparticles.Molecular therapy. Nucleic acids · 2026Article
- Isolation, validation, and long-term culture of mouse ear fibroblasts.Biology open · 2026Article
- Cell Growth and Division Shape mRNA-Protein Correlations.bioRxiv : the preprint server for biology · 2026Article
- Impact of variability in cell generation times on cell-to-cell variability of protein concentrations.bioRxiv : the preprint server for biology · 2026Article
- Cyclo-stationary distributions of mRNA and Protein counts for random cell division times.bioRxiv : the preprint server for biology · 2025Article
- Stochastic gene expression in proliferating cells: Differing noise intensity in single-cell and population perspectives.PLoS computational biology · 2025Article
- Cell-cycle dependence of bursty gene expression: insights from fitting mechanistic models to single-cell RNA-seq data.Nucleic acids research · 2025Article
- Optimisation of gene expression noise for cellular persistence against lethal events.Journal of theoretical biology · 2025Article
- Homeostasis of mRNA concentrations through coupling transcription, export, and degradation.iScience · 2024Article
- Stochastic Gene Expression in Proliferating Cells: Differing Noise Intensity in Single-Cell and Population Perspectives.bioRxiv : the preprint server for biology · 2024Article
- Solving stochastic gene-expression models using queueing theory: A tutorial review.Biophysical journal · 2024Review
- What can we learn when fitting a simple telegraph model to a complex gene expression model?PLoS computational biology · 2024Article
- Quantifying and correcting bias in transcriptional parameter inference from single-cell data.Biophysical journal · 2024Article
- Inferring delays in partially observed gene regulation processes.Bioinformatics (Oxford, England) · 2023Article
- Poisson representation: a bridge between discrete and continuous models of stochastic gene regulatory networks.Journal of the Royal Society, Interface · 2023Article
- PyEcoLib: a python library for simulating stochastic cell size dynamics.Physical biology · 2023Article
- Mitochondrial network structure controls cell-to-cell mtDNA variability generated by cell divisions.PLoS computational biology · 2023Article
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3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Intracellular reaction rates depend on concentrations and hence their levels are often regulated. However classical models of stochastic gene expression lack a cell size description and cannot be used to predict noise in concentrations. Here, we construct a model of gene product dynamics that includes a description of cell growth, cell division, size-dependent gene expression, gene dosage compensation, and size control mechanisms that can vary with the cell cycle phase. We obtain expressions for the approximate distributions and power spectra of concentration fluctuations which lead to insight into the emergence of concentration homeostasis. We find that (i) the conditions necessary to suppress cell division-induced concentration oscillations are difficult to achieve; (ii) mRNA concentration and number distributions can have different number of modes; (iii) two-layer size control strategies such as sizer-timer or adder-timer are ideal because they maintain constant mean concentrations whilst minimising concentration noise; (iv) accurate concentration homeostasis requires a fine tuning of dosage compensation, replication timing, and size-dependent gene expression; (v) deviations from perfect concentration homeostasis show up as deviations of the concentration distribution from a gamma distribution. Some of these predictions are confirmed using data for E. coli, fission yeast, and budding yeast.
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