Frequency domain analysis of fluctuations of mRNA and protein copy numbers within a cell lineage: theory and experimental validation

Chen, Jia; Grima, Ramon

doi:10.1101/2020.09.23.309724

Cited by 4 publications

(4 citation statements)

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“…(2020) . Here, we follow the methodology that we devised in Jia and Grima (2020) and extend previous models by considering asymmetric partitioning at cell division: the mother cell divides into two daughters with different sizes.…”

Section: Resultsmentioning

confidence: 99%

“…Escherichia coli may also undergo asymmetric division with old daughters receiving fewer gene products than new daughters Shi et al (2020). Here, we follow the methodology that we devised in Jia and Grima (2020) and extend previous models by considering asymmetric partitioning at cell division: the mother cell divides into two daughters with different sizes.…”

Section: Model Specificationmentioning

confidence: 99%

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Cell size distribution of lineage data: Analytic results and parameter inference

2021

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Section: Resultsmentioning

confidence: 99%

Section: Model Specificationmentioning

confidence: 99%

Cell size distribution of lineage data: Analytic results and parameter inference

2021

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“…Experimentally, fission yeast in general do not divide perfectly in half. Here we follow the methodology 6/24 that we devised in [13,26] and extend previous models by considering asymmetric partitioning at division: the mother cell divides into two daughters with different sizes.…”

Section: Model Specificationmentioning

confidence: 99%

Characterizing non-exponential growth and bimodal cell size distributions in Schizosaccharomyces pombe: an analytical approach

Chen

Singh

Grima

2021

Preprint

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Unlike many single-celled organisms, the growth of fission yeast cells within a cell cycle is not exponential. It is rather characterized by three distinct phases (elongation, septation and fission), each with a different growth rate. Experiments also show that the distribution of cell size in a lineage is often bimodal, unlike the unimodal distributions measured for the bacterium Escherichia coli. Here we construct a detailed stochastic model of cell size dynamics in fission yeast. The theory leads to analytic expressions for the cell size and the birth size distributions, and explains the origin of bimodality seen in experiments. In particular our theory shows that the left peak in the bimodal distribution is associated with cells in the elongation phase while the right peak is due to cells in the septation and fission phases. We show that the size control strategy, the variability in the added size during a cell cycle and the fraction of time spent in each of the three cell growth phases have a strong bearing on the shape of the cell size distribution. Furthermore we infer all the parameters of our model by matching the theoretical cell size and birth size distributions to those from experimental single cell time-course data for seven different growth conditions. Our method provides a much more accurate means of determining the cell size control strategy (timer, adder or sizer) than the standard method based on the slope of the best linear fit between the birth and division sizes. We also show that the variability in added size and the strength of cell size control of fission yeast depend weakly on the temperature but strongly on the culture medium.

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“…Escherichia coli may also undergo asymmetric division with old daughters receiving fewer gene products than new daughters [26]. Here we follow the methodology that we devised in [27] and extend previous models by considering asymmetric partitioning at cell division: the mother cell divides into two daughters with different sizes.…”

Section: Model Specificationmentioning

confidence: 99%

Cell size distribution of lineage data: analytic results and parameter inference

Chen

Singh

Grima

2020

Preprint

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Recent advances in single-cell technologies have enabled time-resolved measurements of the cell size over several cell cycles. This data encodes information on how cells correct size aberrations so that they do not grow abnormally large or small. Here we formulate a piecewise deterministic Markov model describing the evolution of the cell size over many generations, for all three cell size homeostasis strategies (timer, sizer, and adder). The model is solved to obtain an analytical expression for the non-Gaussian cell size distribution in a cell lineage; the theory is used to understand how the shape of the distribution is influenced by the parameters controlling the dynamics of the cell cycle and by the choice of cell tracking protocol. The theoretical cell size distribution is found to provide an excellent match to the experimental cell size distribution of E. coli lineage data collected under various growth conditions.

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Frequency domain analysis of fluctuations of mRNA and protein copy numbers within a cell lineage: theory and experimental validation

Cited by 4 publications

References 50 publications

Cell size distribution of lineage data: Analytic results and parameter inference

Cell size distribution of lineage data: Analytic results and parameter inference

Characterizing non-exponential growth and bimodal cell size distributions in Schizosaccharomyces pombe: an analytical approach

Cell size distribution of lineage data: analytic results and parameter inference

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