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Keywords:

  • Embryonic stem cells;
  • gp130;
  • Ligand-receptor signaling complexes;
  • Thresholds;
  • Self-renewal;
  • LIF

Abstract

We previously demonstrated that embryonic stem (ES) cell self-renewal required sustained signaling by leukemia inhibitory factor (LIF) in a concentration-dependent manner, allowing us to hypothesize that thresholds in ligand-receptor signaling modulate stem cell differentiation control. To test this hypothesis, we have experimentally and computationally compared the abilities of two gp130-signaling cytokines (LIF and Hyper-interleukin-6 [HIL-6]) to sustain ES cell self-renewal. Quantitative measurements of ES cell phenotypic markers (stage-specific embryonic antigen-1 and E-cadherin), functional assays (alkaline phosphatase activity and embryoid body formation efficiency), and transcription factor (Oct-4) expression over a range of LIF and HIL-6 concentrations demonstrated a superior ability of LIF to maintain ES cell pluripotentiality at higher concentrations (≥500 pM). Additionally, we observed distinct qualitative differences in the ES cell self-renewal dose response profiles between the two cytokines. A computational model permitted calculation of the number of signaling complexes as a function of receptor expression, ligand concentration, and ligand/receptor-binding properties, generating predictions for the degree of self-renewal as a function of cytokine concentration by comparison of these calculated complex numbers to experimentally determined threshold cytokine concentrations. Model predictions, consistent with experimental data, indicated that differences in the potencies of these two cytokines were based primarily on differences in receptor-binding stoichiometries and properties. These results support a ligand/receptor signaling threshold model of ES cell fate modulation through appropriate types and levels of cytokine stimulation. Insights from these results may be more generally applicable to tissue-specific stem cells and could aid in the development of stem cell-based technologies.