Hierarchical Preemption: A Novel Information-Theoretic Control Mechanism in Lambda Phage Decision-Making

TL;DR

This paper introduces hierarchical preemption as a new information-theoretic control mechanism in Lambda phage decision-making, showing how higher layers collapse decision space to influence outcomes.

Contribution

It reveals that hierarchical control operates through preemption, collapsing decision space rather than blocking signals, and provides a quantitative framework for this process.

Findings

RecA achieves 2.01x information advantage over environmental signals.

Hierarchical preemption leads to 85-98% outcome certainty.

Signals remove decision space, enabling precise cellular decisions.

Abstract

Biological systems organize into hierarchies to manage complexity, yet the mechanisms governing hierarchical control remain incompletely understood. Using information theory and the Lambda phage lysis-lysogeny decision as a model system, we discover that hierarchical control operates through hierarchical preemption - higher layers collapse decision space rather than blocking lower-layer signals. Through mutual information (MI) analysis of 200 stochastic simulations, we demonstrate that the UV damage sensor (RecA) achieves 2.01x information advantage over environmental signals by preempting bistable outcomes into monostable attractors (98% lysogenic or 85% lytic). Conditional MI analysis reveals that the integrator signal (CII) carries lower information when RecA is absent (saturated, 0.06 bits) than when RecA is active (subsaturated, 0.38 bits). This saturation effect demonstrates that signals orchestrate compartment behaviors by removing decision space - achieving 85-98% outcome certainty while preserving 2-15% escape routes. These findings establish a quantitative framework for hierarchical information processing in cellular decision-making.