A system-level model reveals that transcriptional stochasticity is required for hematopoietic stem cell differentiation

NPJ Syst Biol Appl. 2024 Dec 5;10(1):145. doi: 10.1038/s41540-024-00469-8.

Abstract

HSCs differentiation has been difficult to study experimentally due to the high number of components and interactions involved, as well as the impact of diverse physiological conditions. From a 200-node network, that was grounded on experimental data, we derived a 21-node regulatory network by collapsing linear pathways and retaining the functional feedback loops. This regulatory network core integrates key nodes and interactions underlying HSCs differentiation, including transcription factors, metabolic, and redox signaling pathways. We used Boolean, continuous, and stochastic dynamic models to simulate the hypoxic conditions of the HSCs niche, as well as the patterns and temporal sequences of HSCs transitions and differentiation. Our findings indicate that HSCs differentiation is a plastic process in which cell fates can transdifferentiate among themselves. Additionally, we found that cell heterogeneity is fundamental for HSCs differentiation. Lastly, we found that oxygen activates ROS production, inhibiting quiescence and promoting growth and differentiation pathways of HSCs.

MeSH terms

  • Animals
  • Cell Differentiation* / genetics
  • Cell Differentiation* / physiology
  • Gene Regulatory Networks* / genetics
  • Hematopoietic Stem Cells* / cytology
  • Hematopoietic Stem Cells* / metabolism
  • Humans
  • Models, Biological
  • Reactive Oxygen Species / metabolism
  • Signal Transduction / genetics
  • Signal Transduction / physiology
  • Stochastic Processes
  • Systems Biology / methods
  • Transcription Factors / genetics
  • Transcription Factors / metabolism

Substances

  • Reactive Oxygen Species
  • Transcription Factors