Affinity maturation for an optimal balance between long-term immune coverage and short-term resource constraints

Area of Science:

• Immunology
• Computational Biology
• Evolutionary Medicine

Background:

• The adaptive immune system reorganizes its lymphocyte repertoire to target pathogens.
• B cell affinity maturation generates a memory pool with unpredictable diversity and size.
• Predicting memory pool characteristics is crucial for understanding long-term immunity.

Purpose of the Study:

• To model the immune system's strategy for balancing long-term immune coverage and metabolic costs during affinity maturation.
• To explain the observed low specificity and high diversity of memory B cells.
• To understand the factors influencing memory pool size and diversity.

Main Methods:

• Developed an optimal decision process model on a finite dimensional phenotypic space.
• Simulated sequential challenges of a preexisting cell population with a neutrally evolving strain.
• Analyzed the emergence of distinct regimes for memory pool size and diversity.

Main Results:

• Low specificity and high diversity of memory B cells are explained as a strategy against rapidly evolving pathogens.
• Model predicts distinct regimes for memory pool size and diversity based on cell density and pathogen mutation rate.
• Predicted power-law distributions of clonotype sizes align with experimental data.

Conclusions:

• The immune system employs a strategy to maximize long-term coverage while minimizing metabolic costs.
• Repertoire plasticity is key to adapting to evolving pathogens and maintaining broad immune protection.
• Antigenic imprinting is rationalized as a cost-minimizing strategy for future immune defense.