A common molecular logic determines embryonic stem cell self-renewal and reprogramming.

Area of Science:

• Systems Biology
• Developmental Biology
• Computational Biology

Background:

• Cell identity is established by dynamic gene regulatory networks (GRNs).
• Understanding GRN logic is crucial for controlling cell differentiation and reprogramming.

Purpose of the Study:

• To uncover the logical rules governing gene network activation during the induction of naïve pluripotency.
• To determine if a single GRN model can explain both naïve pluripotency maintenance and reprogramming.

Main Methods:

• Combined automated formal reasoning with experimental validation.
• Developed a Boolean network model for naïve pluripotency.
• Utilized single-cell resolution RT-qPCR for experimental substantiation.
• Tested 124 computational predictions derived from the dynamic network.

Main Results:

• A Boolean network architecture for naïve pluripotency maintenance also explains reprogramming dynamics.
• Experimentally validated computationally identified gene activation trajectories at single-cell resolution.
• Demonstrated that factor availability contingency explains Klf2's role in resetting.
• Achieved a 77.4% predictive accuracy for 124 tested network predictions.

Conclusions:

• A common, deterministic gene regulatory program underlies both the maintenance and induction of naïve pluripotency.
• The developed dynamic network model successfully explains and predicts somatic cell reprogramming.
• The employed computational and experimental tools can be broadly applied to study cell fate transitions.