Signaling receptor localization maximizes cellular information acquisition in spatially-structured, natural environments

TL;DR

This paper introduces an information theoretic framework to optimize cell surface receptor localization for enhanced sensing and navigation in complex, spatially-structured environments like tissue and soil, demonstrating significant improvements in simulated scenarios.

Contribution

It develops a novel framework for optimizing receptor spatial organization based on environmental structure, revealing how receptor localization enhances cellular information acquisition and navigation.

Findings

Receptor localization maximizes information acquisition in natural environments.

Dynamic receptor redistribution improves navigation efficiency by 30-fold.

The framework can be applied to other signaling components for better cellular processing.

Abstract

Cells in natural environments like tissue or soil sense and respond to extracellular ligands with intricately structured and non-monotonic spatial distributions that are sculpted by processes such as fluid flow and substrate adhesion. Nevertheless, traditional approaches to studying cell sensing assume signals are either uniform or monotonic, neglecting spatial structures of natural environments. In this work, we show that spatial sensing and navigation can be optimized by adapting the spatial organization of signaling pathways to the spatial structure of the environment. By viewing cell surface receptors as a sensor network, we develop an information theoretic framework for computing the optimal spatial organization of a sensing system for a given spatial signaling environment. Applying the framework to simulated environments, we find that spatial receptor localization maximizes information acquisition in many natural contexts, including tissue and soil. Receptor localization extends naturally to produce a dynamic protocol for redistributing signaling receptors during cell navigation and can be implemented in a cell using a feedback scheme. In a simulated tissue environment, dynamic receptor localization boosts navigation efficiency by 30-fold. Broadly, our framework readily adapts to studying how the spatial organization of signaling components other than receptors can be modulated to improve cellular information processing.