Dataset Information

Biological noise and positional effects influence cell stemness.

ABSTRACT: Biological (or cellular) noise is the random quantitative variability of proteins and other molecules in individual, genetically identical cells. As the result of biological noise in the levels of some transcription factors that determine a cell's differentiation status, differentiated cells may dedifferentiate to a stem cell state given a sufficiently long time period. Here, to provide direct evidence supporting this hypothesis, we used a live-cell monitoring system based on enhanced green fluorescent protein (eGFP) expression to continuously assess the "stemness" of individual human and murine malignant mesothelioma cells over a period of up to 3 months. Re-expression of the transcription factors, the top hierarchical stemness markers Sox2 (SRY-box 2) and Oct4 (octamer-binding transcription factor), monitored as cell eGFP expression was observed in a subpopulation of differentiated eGFP(-) malignant mesothelioma cells. However, we found that this transition was extremely rare. Of note, when it did occur, neighboring cells that were not direct descendants of a newly emerged eGFP(+) stem cell were more likely than non-neighboring cells to also become an eGFP(+) stem cell. This observation suggested a positional effect and led to a clustered "mosaic" reappearance of eGFP(+) stem cells. Moreover, stem cells reappeared even in cell cultures derived from one single differentiated eGFP(-) cell. On the basis of our experimental in vitro and in vivo findings, we developed a tumor growth model to predict the clustered localization of cancer stem cells within a tumor mass.

SUBMITTER: Blum W

PROVIDER: S-EPMC5892591 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

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Biological noise and positional effects influence cell stemness.

Blum Walter W Henzi Thomas T Schwaller Beat B Pecze László L

The Journal of biological chemistry 20180212 14

Biological (or cellular) noise is the random quantitative variability of proteins and other molecules in individual, genetically identical cells. As the result of biological noise in the levels of some transcription factors that determine a cell's differentiation status, differentiated cells may dedifferentiate to a stem cell state given a sufficiently long time period. Here, to provide direct evidence supporting this hypothesis, we used a live-cell monitoring system based on enhanced green fluo ...[more]

PMID: 29440274

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Project description:Oscillatory dynamics are common in biological pathways, emerging from the coupling of positive and negative feedback loops. Due to the small numbers of molecules typically contained in cellular volumes, stochastic effects may play an important role in system behavior. Thus, for moderate noise strengths, stochasticity has been shown to enhance signal-to-noise ratios or even induce oscillations in a class of phenomena referred to as "stochastic resonance" and "coherence resonance," respectively. Furthermore, the biological oscillators are subject to influences from the division cycle of the cell. In this paper we consider a biologically relevant oscillator and investigate the effect of intrinsic noise as well as division cycle which encompasses the processes of growth, DNA duplication, and cell division. We first construct a minimal reaction network which can oscillate in the presence of large or negligible timescale separation. We then derive corresponding deterministic and stochastic models and compare their dynamical behaviors with respect to (i) the extent of the parameter space where each model can exhibit oscillatory behavior and (ii) the oscillation characteristics, namely, the amplitude and the period. We further incorporate division cycle effects on both models and investigate the effect of growth rate on system behavior. Our results show that in the presence but not in the absence of large timescale separation, coherence resonance effects result in extending the oscillatory region and lowering the period for the stochastic model. When the division cycle is taken into account, the oscillatory region of the deterministic model is shown to extend or shrink for moderate or high growth rates, respectively. Further, under the influence of the division cycle, the stochastic model can oscillate for parameter sets for which the deterministic model does not. The division cycle is also found to be able to resonate with the oscillator, thereby enhancing oscillation robustness. The results of this study can give valuable insight into the complex interplay between oscillatory intracellular dynamics and various noise sources, stemming from gene expression, cell growth, and division.

Dataset Information

Biological noise and positional effects influence cell stemness.

Publications

Biological noise and positional effects influence cell stemness.

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