Reply to 'The interface of nanoparticles with proliferating mammalian cells'

Åberg, Christoffer; Kim, Jong Ah; Salvati, Anna; Dawson, Kenneth A.

doi:10.1038/nnano.2017.139

Cited by 14 publications

(24 citation statements)

References 6 publications

(11 reference statements)

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“…See also our previous work for further details, arguments and agreements between the results of the simulations and experiments [23][24][25][26]. The initial (mean) number of nanoparticles is indicated by the linestyle (solid, dashed, dotted; also indicated in the legend).…”

Section: Plos Onementioning

confidence: 74%

“…In order to simulate an exponentially growing cell population, we used an exponentially decaying initial age distribution where the number of cells at the very beginning of the cell cycle was twice as many as the number of cells at the very end. This also ensures that the age distribution does not change in time [23,24,26,40].…”

Section: Methodsmentioning

confidence: 99%

“…Thus, we performed simple simulations of a continuously evolving cell population [23][24][25][26], where cells age as time goes on and, when reaching the end of one full cell cycle, cells divide into two new daughter cells that start the cell cycle anew. While the total duration of the cell cycle in reality is not the same for all cells, the variation is nevertheless moderate for cell lines, with a coefficient of variation of around 20% [30,31].…”

Section: Plos Onementioning

confidence: 99%

“…When cells divide, the nanoparticles they contain were shared between the daughter cells in accordance with the inheritance distribution [Eq (1)]. More details may be found in the Methods section and our previously published work [23][24][25][26].…”

Section: Plos Onementioning

confidence: 99%

“…Here we complement these approaches by showing that the coefficient of variation over the cell population (i.e., the standard deviation over the mean) is a useful observable to quickly assess the degree of asymmetry upon cell division. We have previously developed a model of nanoparticle uptake in dividing cell populations and demonstrated that it describes experimental observations well [23][24][25][26]. With this firm basis, we perform simulations of the evolution of the cell population and, specifically assess how the coefficient of variation evolves in time both after a nanoparticle exposure as well as during continuous exposure.…”

Section: Introductionmentioning

confidence: 98%

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Asymmetry of nanoparticle inheritance upon cell division: Effect on the coefficient of variation

Lijster

Åberg

2020

PLoS ONE

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Several previous studies have shown that when a cell that has taken up nanoparticles divides, the nanoparticles are inherited by the two daughter cells in an asymmetrical fashion, with one daughter cell receiving more nanoparticles than the other. This interesting observation is typically demonstrated either indirectly using mathematical modelling of high-throughput experimental data or more directly by imaging individual cells as they divide. Here we suggest that measurements of the coefficient of variation (standard deviation over mean) of the number of nanoparticles per cell over the cell population is another means of assessing the degree of asymmetry. Using simulations of an evolving cell population, we show that the coefficient of variation is sensitive to the degree of asymmetry and note its characteristic evolution in time. As the coefficient of variation is readily measurable using high-throughput techniques, this should allow a more rapid experimental assessment of the degree of asymmetry.

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Section: Plos Onementioning

confidence: 74%

Section: Methodsmentioning

confidence: 99%