Multi-scale Dynamical Modeling of T Cell Development from an Early Thymic Progenitor State to Lineage Commitment

Area of Science:

• * Developmental immunology
• * Molecular systems biology
• * Computational biology

Background:

• * T-cell development involves complex transitions from hematopoietic stem cells to committed T-cell progenitors.
• * Understanding the molecular mechanisms governing T-cell commitment is crucial for immunology and regenerative medicine.
• * Previous studies highlighted cis-acting chromatin effects and kinetics but lacked a unified mechanistic model.

Purpose of the Study:

• * To develop a multi-scale dynamic model of T-cell commitment.
• * To integrate gene regulatory networks, chromatin state dynamics, and cell proliferation.
• * To mechanistically explain the programmed gene expression changes and commitment kinetics observed during T-cell development.

Main Methods:

• * Developed a three-level dynamic model incorporating gene regulatory network (GRN) architecture, a stochastic chromatin-state gate, and a single-cell proliferation model.
• * Utilized transcription factor (TF) perturbation data to define the core GRN.
• * Employed RNA fluorescence in situ hybridization (FISH) and bulk population dynamics for model validation against clonal growth and commitment kinetics.

Main Results:

• * The model successfully predicts state-switching kinetics during T-cell commitment.
• * Validated model predictions using experimental data on clonal proliferation and commitment times.
• * Demonstrated the interplay between gene regulation, chromatin accessibility, and proliferation in driving cell fate decisions.

Conclusions:

• * The developed multi-scale model provides a mechanistic framework for dissecting T-cell commitment dynamics.
• * This approach offers insights into how environmental signals and internal circuitry establish cell identity.
• * The model serves as a foundation for further investigation into T-cell differentiation and potential therapeutic targets.