Drugs modulating stochastic gene expression affect the erythroid differentiation process

PLoS One. 2019 Nov 21;14(11):e0225166. doi: 10.1371/journal.pone.0225166. eCollection 2019.

Abstract

To better understand the mechanisms behind cells decision-making to differentiate, we assessed the influence of stochastic gene expression (SGE) modulation on the erythroid differentiation process. It has been suggested that stochastic gene expression has a role in cell fate decision-making which is revealed by single-cell analyses but studies dedicated to demonstrate the consistency of this link are still lacking. Recent observations showed that SGE significantly increased during differentiation and a few showed that an increase of the level of SGE is accompanied by an increase in the differentiation process. However, a consistent relation in both increasing and decreasing directions has never been shown in the same cellular system. Such demonstration would require to be able to experimentally manipulate simultaneously the level of SGE and cell differentiation in order to observe if cell behavior matches with the current theory. We identified three drugs that modulate SGE in primary erythroid progenitor cells. Both Artemisinin and Indomethacin decreased SGE and reduced the amount of differentiated cells. On the contrary, a third component called MB-3 simultaneously increased the level of SGE and the amount of differentiated cells. We then used a dynamical modelling approach which confirmed that differentiation rates were indeed affected by the drug treatment. Using single-cell analysis and modeling tools, we provide experimental evidence that, in a physiologically relevant cellular system, SGE is linked to differentiation.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Cell Differentiation / drug effects*
  • Cell Survival / drug effects
  • Computational Biology / methods
  • Erythropoiesis / drug effects*
  • Erythropoiesis / genetics*
  • Gene Expression Profiling
  • Gene Expression Regulation, Developmental / drug effects*
  • High-Throughput Nucleotide Sequencing
  • Models, Biological
  • Transcriptome

Grants and funding

This work was supported by funding from the French agency ANR (SinCity; ANR-17-CE12-0031) and La Ligue Contre le Cancer (Comite de Haute Savoie; LS 136994). There was no additional external funding received for this study. All these funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.