# Cooperative metabolic resource allocation in spatially-structured systems

## TL;DR

This paper develops a cooperative extension of the maximum entropy framework for dynamic metabolic resource allocation in spatially-structured systems, explaining how local regulation can achieve community-wide objectives through limited global information.

## Contribution

It introduces a cooperative maximum entropy model for metabolism in spatial systems, incorporating social interactions and limited global knowledge.

## Key findings

- Local regulation can optimize community-wide metabolic objectives.
- Cooperative strategies are facilitated by quorum sensing or signaling molecules.
- The model explains social cooperation in microbial and multicellular systems.

## Abstract

Natural selection has shaped the evolution of cells and multi-cellular organisms such that social cooperation can often be preferred over an individualistic approach to metabolic regulation. This paper extends a framework for dynamic metabolic resource allocation based on the maximum entropy principle to spatiotemporal models of metabolism with cooperation. Much like the maximum entropy principle encapsulates `bet-hedging' behaviour displayed by organisms dealing with future uncertainty in a fluctuating environment, its cooperative extension describes how individuals adapt their metabolic resource allocation strategy to further accommodate limited knowledge about the welfare of others within a community. The resulting theory explains why local regulation of metabolic cross-feeding can fulfil a community-wide metabolic objective if individuals take into consideration an ensemble measure of total population performance as the only form of global information. The latter is likely supplied by quorum sensing in microbial systems or signalling molecules such as hormones in multi-cellular eukaryotic organisms.