Excitability as a design principle in the immune system

Area of Science:

• Immunology
• Dynamical Systems Theory
• Computational Biology

Background:

• Current immunology lacks unifying concepts for immune circuit functions like pathogen response and self-tolerance.
• Molecular circuits in immunology are complex, making it challenging to understand their emergent properties.

Purpose of the Study:

• To propose excitability as a unifying concept for understanding immune circuit behavior.
• To identify specific molecular circuits within the immune system that exhibit excitable properties.

Main Methods:

• Mathematical screening of thousands of cytokine and cell circuits.
• Analysis using dynamical systems theory to identify excitable circuits.
• Evaluation of Pareto optimality for speed and strength in identified circuits.

Main Results:

• A single, robust excitable circuit was identified as Pareto optimal for speed and strength.
• This optimal circuit, characterized by self-induction and inhibitor induction, appears frequently in the human immune network.
• Suboptimal circuits were found to be less prevalent.

Conclusions:

• Excitability provides a unifying framework for understanding diverse immune circuit functions.
• The identified optimal excitable circuit is a key component of the human immune network.
• This framework explains phenomena in infectious disease (e.g., SARS-CoV-2), autoimmunity, and tumor immunity, suggesting new therapeutic targets.